Confident difference criterion: a new Bayesian differentially expressed gene selection algorithm with applications.

PubMed

Yu, Fang; Chen, Ming-Hui; Kuo, Lynn; Talbott, Heather; Davis, John S

2015-08-07

Recently, the Bayesian method becomes more popular for analyzing high dimensional gene expression data as it allows us to borrow information across different genes and provides powerful estimators for evaluating gene expression levels. It is crucial to develop a simple but efficient gene selection algorithm for detecting differentially expressed (DE) genes based on the Bayesian estimators. In this paper, by extending the two-criterion idea of Chen et al. (Chen M-H, Ibrahim JG, Chi Y-Y. A new class of mixture models for differential gene expression in DNA microarray data. J Stat Plan Inference. 2008;138:387-404), we propose two new gene selection algorithms for general Bayesian models and name these new methods as the confident difference criterion methods. One is based on the standardized differences between two mean expression values among genes; the other adds the differences between two variances to it. The proposed confident difference criterion methods first evaluate the posterior probability of a gene having different gene expressions between competitive samples and then declare a gene to be DE if the posterior probability is large. The theoretical connection between the proposed first method based on the means and the Bayes factor approach proposed by Yu et al. (Yu F, Chen M-H, Kuo L. Detecting differentially expressed genes using alibrated Bayes factors. Statistica Sinica. 2008;18:783-802) is established under the normal-normal-model with equal variances between two samples. The empirical performance of the proposed methods is examined and compared to those of several existing methods via several simulations. The results from these simulation studies show that the proposed confident difference criterion methods outperform the existing methods when comparing gene expressions across different conditions for both microarray studies and sequence-based high-throughput studies. A real dataset is used to further demonstrate the proposed methodology. In the real data application, the confident difference criterion methods successfully identified more clinically important DE genes than the other methods. The confident difference criterion method proposed in this paper provides a new efficient approach for both microarray studies and sequence-based high-throughput studies to identify differentially expressed genes.

Time-dependent solutions for a stochastic model of gene expression with molecule production in the form of a compound Poisson process.

PubMed

Jędrak, Jakub; Ochab-Marcinek, Anna

2016-09-01

We study a stochastic model of gene expression, in which protein production has a form of random bursts whose size distribution is arbitrary, whereas protein decay is a first-order reaction. We find exact analytical expressions for the time evolution of the cumulant-generating function for the most general case when both the burst size probability distribution and the model parameters depend on time in an arbitrary (e.g., oscillatory) manner, and for arbitrary initial conditions. We show that in the case of periodic external activation and constant protein degradation rate, the response of the gene is analogous to the resistor-capacitor low-pass filter, where slow oscillations of the external driving have a greater effect on gene expression than the fast ones. We also demonstrate that the nth cumulant of the protein number distribution depends on the nth moment of the burst size distribution. We use these results to show that different measures of noise (coefficient of variation, Fano factor, fractional change of variance) may vary in time in a different manner. Therefore, any biological hypothesis of evolutionary optimization based on the nonmonotonic dependence of a chosen measure of noise on time must justify why it assumes that biological evolution quantifies noise in that particular way. Finally, we show that not only for exponentially distributed burst sizes but also for a wider class of burst size distributions (e.g., Dirac delta and gamma) the control of gene expression level by burst frequency modulation gives rise to proportional scaling of variance of the protein number distribution to its mean, whereas the control by amplitude modulation implies proportionality of protein number variance to the mean squared.

A new variance stabilizing transformation for gene expression data analysis.

PubMed

Kelmansky, Diana M; Martínez, Elena J; Leiva, Víctor

2013-12-01

In this paper, we introduce a new family of power transformations, which has the generalized logarithm as one of its members, in the same manner as the usual logarithm belongs to the family of Box-Cox power transformations. Although the new family has been developed for analyzing gene expression data, it allows a wider scope of mean-variance related data to be reached. We study the analytical properties of the new family of transformations, as well as the mean-variance relationships that are stabilized by using its members. We propose a methodology based on this new family, which includes a simple strategy for selecting the family member adequate for a data set. We evaluate the finite sample behavior of different classical and robust estimators based on this strategy by Monte Carlo simulations. We analyze real genomic data by using the proposed transformation to empirically show how the new methodology allows the variance of these data to be stabilized.

Comparison of gene expression microarray data with count-based RNA measurements informs microarray interpretation.

PubMed

Richard, Arianne C; Lyons, Paul A; Peters, James E; Biasci, Daniele; Flint, Shaun M; Lee, James C; McKinney, Eoin F; Siegel, Richard M; Smith, Kenneth G C

2014-08-04

Although numerous investigations have compared gene expression microarray platforms, preprocessing methods and batch correction algorithms using constructed spike-in or dilution datasets, there remains a paucity of studies examining the properties of microarray data using diverse biological samples. Most microarray experiments seek to identify subtle differences between samples with variable background noise, a scenario poorly represented by constructed datasets. Thus, microarray users lack important information regarding the complexities introduced in real-world experimental settings. The recent development of a multiplexed, digital technology for nucleic acid measurement enables counting of individual RNA molecules without amplification and, for the first time, permits such a study. Using a set of human leukocyte subset RNA samples, we compared previously acquired microarray expression values with RNA molecule counts determined by the nCounter Analysis System (NanoString Technologies) in selected genes. We found that gene measurements across samples correlated well between the two platforms, particularly for high-variance genes, while genes deemed unexpressed by the nCounter generally had both low expression and low variance on the microarray. Confirming previous findings from spike-in and dilution datasets, this "gold-standard" comparison demonstrated signal compression that varied dramatically by expression level and, to a lesser extent, by dataset. Most importantly, examination of three different cell types revealed that noise levels differed across tissues. Microarray measurements generally correlate with relative RNA molecule counts within optimal ranges but suffer from expression-dependent accuracy bias and precision that varies across datasets. We urge microarray users to consider expression-level effects in signal interpretation and to evaluate noise properties in each dataset independently.

Scoring clustering solutions by their biological relevance.

PubMed

Gat-Viks, I; Sharan, R; Shamir, R

2003-12-12

A central step in the analysis of gene expression data is the identification of groups of genes that exhibit similar expression patterns. Clustering gene expression data into homogeneous groups was shown to be instrumental in functional annotation, tissue classification, regulatory motif identification, and other applications. Although there is a rich literature on clustering algorithms for gene expression analysis, very few works addressed the systematic comparison and evaluation of clustering results. Typically, different clustering algorithms yield different clustering solutions on the same data, and there is no agreed upon guideline for choosing among them. We developed a novel statistically based method for assessing a clustering solution according to prior biological knowledge. Our method can be used to compare different clustering solutions or to optimize the parameters of a clustering algorithm. The method is based on projecting vectors of biological attributes of the clustered elements onto the real line, such that the ratio of between-groups and within-group variance estimators is maximized. The projected data are then scored using a non-parametric analysis of variance test, and the score's confidence is evaluated. We validate our approach using simulated data and show that our scoring method outperforms several extant methods, including the separation to homogeneity ratio and the silhouette measure. We apply our method to evaluate results of several clustering methods on yeast cell-cycle gene expression data. The software is available from the authors upon request.

Technical and biological variance structure in mRNA-Seq data: life in the real world

PubMed Central

2012-01-01

Background mRNA expression data from next generation sequencing platforms is obtained in the form of counts per gene or exon. Counts have classically been assumed to follow a Poisson distribution in which the variance is equal to the mean. The Negative Binomial distribution which allows for over-dispersion, i.e., for the variance to be greater than the mean, is commonly used to model count data as well. Results In mRNA-Seq data from 25 subjects, we found technical variation to generally follow a Poisson distribution as has been reported previously and biological variability was over-dispersed relative to the Poisson model. The mean-variance relationship across all genes was quadratic, in keeping with a Negative Binomial (NB) distribution. Over-dispersed Poisson and NB distributional assumptions demonstrated marked improvements in goodness-of-fit (GOF) over the standard Poisson model assumptions, but with evidence of over-fitting in some genes. Modeling of experimental effects improved GOF for high variance genes but increased the over-fitting problem. Conclusions These conclusions will guide development of analytical strategies for accurate modeling of variance structure in these data and sample size determination which in turn will aid in the identification of true biological signals that inform our understanding of biological systems. PMID:22769017

Stochastic models for inferring genetic regulation from microarray gene expression data.

PubMed

Tian, Tianhai

2010-03-01

Microarray expression profiles are inherently noisy and many different sources of variation exist in microarray experiments. It is still a significant challenge to develop stochastic models to realize noise in microarray expression profiles, which has profound influence on the reverse engineering of genetic regulation. Using the target genes of the tumour suppressor gene p53 as the test problem, we developed stochastic differential equation models and established the relationship between the noise strength of stochastic models and parameters of an error model for describing the distribution of the microarray measurements. Numerical results indicate that the simulated variance from stochastic models with a stochastic degradation process can be represented by a monomial in terms of the hybridization intensity and the order of the monomial depends on the type of stochastic process. The developed stochastic models with multiple stochastic processes generated simulations whose variance is consistent with the prediction of the error model. This work also established a general method to develop stochastic models from experimental information. 2009 Elsevier Ireland Ltd. All rights reserved.

The Inheritance of Metabolic Flux: Expressions for the within-Sibship Mean and Variance Given the Parental Genotypes

PubMed Central

Ward, P. J.

1990-01-01

Recent developments have related quantitative trait expression to metabolic flux. The present paper investigates some implications of this for statistical aspects of polygenic inheritance. Expressions are derived for the within-sibship genetic mean and genetic variance of metabolic flux given a pair of parental, diploid, n-locus genotypes. These are exact and hold for arbitrary numbers of gene loci, arbitrary allelic values at each locus, and for arbitrary recombination fractions between adjacent gene loci. The within-sibship, genetic variance is seen to be simply a measure of parental heterozygosity plus a measure of the degree of linkage coupling within the parental genotypes. Approximations are given for the within-sibship phenotypic mean and variance of metabolic flux. These results are applied to the problem of attaining adequate statistical power in a test of association between allozymic variation and inter-individual variation in metabolic flux. Simulations indicate that statistical power can be greatly increased by augmenting the data with predictions and observations on progeny statistics in relation to parental allozyme genotypes. Adequate power may thus be attainable at small sample sizes, and when allozymic variation is scored at a only small fraction of the total set of loci whose catalytic products determine the flux. PMID:2379825

Divergent and nonuniform gene expression patterns in mouse brain

PubMed Central

Morris, John A.; Royall, Joshua J.; Bertagnolli, Darren; Boe, Andrew F.; Burnell, Josh J.; Byrnes, Emi J.; Copeland, Cathy; Desta, Tsega; Fischer, Shanna R.; Goldy, Jeff; Glattfelder, Katie J.; Kidney, Jolene M.; Lemon, Tracy; Orta, Geralyn J.; Parry, Sheana E.; Pathak, Sayan D.; Pearson, Owen C.; Reding, Melissa; Shapouri, Sheila; Smith, Kimberly A.; Soden, Chad; Solan, Beth M.; Weller, John; Takahashi, Joseph S.; Overly, Caroline C.; Lein, Ed S.; Hawrylycz, Michael J.; Hohmann, John G.; Jones, Allan R.

2010-01-01

Considerable progress has been made in understanding variations in gene sequence and expression level associated with phenotype, yet how genetic diversity translates into complex phenotypic differences remains poorly understood. Here, we examine the relationship between genetic background and spatial patterns of gene expression across seven strains of mice, providing the most extensive cellular-resolution comparative analysis of gene expression in the mammalian brain to date. Using comprehensive brainwide anatomic coverage (more than 200 brain regions), we applied in situ hybridization to analyze the spatial expression patterns of 49 genes encoding well-known pharmaceutical drug targets. Remarkably, over 50% of the genes examined showed interstrain expression variation. In addition, the variability was nonuniformly distributed across strain and neuroanatomic region, suggesting certain organizing principles. First, the degree of expression variance among strains mirrors genealogic relationships. Second, expression pattern differences were concentrated in higher-order brain regions such as the cortex and hippocampus. Divergence in gene expression patterns across the brain could contribute significantly to variations in behavior and responses to neuroactive drugs in laboratory mouse strains and may help to explain individual differences in human responsiveness to neuroactive drugs. PMID:20956311

Evaluation of Bias-Variance Trade-Off for Commonly Used Post-Summarizing Normalization Procedures in Large-Scale Gene Expression Studies

PubMed Central

Qiu, Xing; Hu, Rui; Wu, Zhixin

2014-01-01

Normalization procedures are widely used in high-throughput genomic data analyses to remove various technological noise and variations. They are known to have profound impact to the subsequent gene differential expression analysis. Although there has been some research in evaluating different normalization procedures, few attempts have been made to systematically evaluate the gene detection performances of normalization procedures from the bias-variance trade-off point of view, especially with strong gene differentiation effects and large sample size. In this paper, we conduct a thorough study to evaluate the effects of normalization procedures combined with several commonly used statistical tests and MTPs under different configurations of effect size and sample size. We conduct theoretical evaluation based on a random effect model, as well as simulation and biological data analyses to verify the results. Based on our findings, we provide some practical guidance for selecting a suitable normalization procedure under different scenarios. PMID:24941114

Modeling gene expression measurement error: a quasi-likelihood approach

PubMed Central

Strimmer, Korbinian

2003-01-01

Background Using suitable error models for gene expression measurements is essential in the statistical analysis of microarray data. However, the true probabilistic model underlying gene expression intensity readings is generally not known. Instead, in currently used approaches some simple parametric model is assumed (usually a transformed normal distribution) or the empirical distribution is estimated. However, both these strategies may not be optimal for gene expression data, as the non-parametric approach ignores known structural information whereas the fully parametric models run the risk of misspecification. A further related problem is the choice of a suitable scale for the model (e.g. observed vs. log-scale). Results Here a simple semi-parametric model for gene expression measurement error is presented. In this approach inference is based an approximate likelihood function (the extended quasi-likelihood). Only partial knowledge about the unknown true distribution is required to construct this function. In case of gene expression this information is available in the form of the postulated (e.g. quadratic) variance structure of the data. As the quasi-likelihood behaves (almost) like a proper likelihood, it allows for the estimation of calibration and variance parameters, and it is also straightforward to obtain corresponding approximate confidence intervals. Unlike most other frameworks, it also allows analysis on any preferred scale, i.e. both on the original linear scale as well as on a transformed scale. It can also be employed in regression approaches to model systematic (e.g. array or dye) effects. Conclusions The quasi-likelihood framework provides a simple and versatile approach to analyze gene expression data that does not make any strong distributional assumptions about the underlying error model. For several simulated as well as real data sets it provides a better fit to the data than competing models. In an example it also improved the power of tests to identify differential expression. PMID:12659637

A comparative study of ripening among berries of the grape cluster reveals an altered transcriptional programme and enhanced ripening rate in delayed berries

PubMed Central

Gouthu, Satyanarayana; O’Neil, Shawn T.; Di, Yanming; Ansarolia, Mitra; Megraw, Molly; Deluc, Laurent G.

2014-01-01

Transcriptional studies in relation to fruit ripening generally aim to identify the transcriptional states associated with physiological ripening stages and the transcriptional changes between stages within the ripening programme. In non-climacteric fruits such as grape, all ripening-related genes involved in this programme have not been identified, mainly due to the lack of mutants for comparative transcriptomic studies. A feature in grape cluster ripening (Vitis vinifera cv. Pinot noir), where all berries do not initiate the ripening at the same time, was exploited to study their shifted ripening programmes in parallel. Berries that showed marked ripening state differences in a véraison-stage cluster (ripening onset) ultimately reached similar ripeness states toward maturity, indicating the flexibility of the ripening programme. The expression variance between these véraison-stage berry classes, where 11% of the genes were found to be differentially expressed, was reduced significantly toward maturity, resulting in the synchronization of their transcriptional states. Defined quantitative expression changes (transcriptional distances) not only existed between the véraison transitional stages, but also between the véraison to maturity stages, regardless of the berry class. It was observed that lagging berries complete their transcriptional programme in a shorter time through altered gene expressions and ripening-related hormone dynamics, and enhance the rate of physiological ripening progression. Finally, the reduction in expression variance of genes can identify new genes directly associated with ripening and also assess the relevance of gene activity to the phase of the ripening programme. PMID:25135520

Correction of gene expression data: Performance-dependency on inter-replicate and inter-treatment biases.

PubMed

Darbani, Behrooz; Stewart, C Neal; Noeparvar, Shahin; Borg, Søren

2014-10-20

This report investigates for the first time the potential inter-treatment bias source of cell number for gene expression studies. Cell-number bias can affect gene expression analysis when comparing samples with unequal total cellular RNA content or with different RNA extraction efficiencies. For maximal reliability of analysis, therefore, comparisons should be performed at the cellular level. This could be accomplished using an appropriate correction method that can detect and remove the inter-treatment bias for cell-number. Based on inter-treatment variations of reference genes, we introduce an analytical approach to examine the suitability of correction methods by considering the inter-treatment bias as well as the inter-replicate variance, which allows use of the best correction method with minimum residual bias. Analyses of RNA sequencing and microarray data showed that the efficiencies of correction methods are influenced by the inter-treatment bias as well as the inter-replicate variance. Therefore, we recommend inspecting both of the bias sources in order to apply the most efficient correction method. As an alternative correction strategy, sequential application of different correction approaches is also advised. Copyright © 2014 Elsevier B.V. All rights reserved.

Identification of Human HK Genes and Gene Expression Regulation Study in Cancer from Transcriptomics Data Analysis

PubMed Central

Zhang, Zhang; Liu, Jingxing; Wu, Jiayan; Yu, Jun

2013-01-01

The regulation of gene expression is essential for eukaryotes, as it drives the processes of cellular differentiation and morphogenesis, leading to the creation of different cell types in multicellular organisms. RNA-Sequencing (RNA-Seq) provides researchers with a powerful toolbox for characterization and quantification of transcriptome. Many different human tissue/cell transcriptome datasets coming from RNA-Seq technology are available on public data resource. The fundamental issue here is how to develop an effective analysis method to estimate expression pattern similarities between different tumor tissues and their corresponding normal tissues. We define the gene expression pattern from three directions: 1) expression breadth, which reflects gene expression on/off status, and mainly concerns ubiquitously expressed genes; 2) low/high or constant/variable expression genes, based on gene expression level and variation; and 3) the regulation of gene expression at the gene structure level. The cluster analysis indicates that gene expression pattern is higher related to physiological condition rather than tissue spatial distance. Two sets of human housekeeping (HK) genes are defined according to cell/tissue types, respectively. To characterize the gene expression pattern in gene expression level and variation, we firstly apply improved K-means algorithm and a gene expression variance model. We find that cancer-associated HK genes (a HK gene is specific in cancer group, while not in normal group) are expressed higher and more variable in cancer condition than in normal condition. Cancer-associated HK genes prefer to AT-rich genes, and they are enriched in cell cycle regulation related functions and constitute some cancer signatures. The expression of large genes is also avoided in cancer group. These studies will help us understand which cell type-specific patterns of gene expression differ among different cell types, and particularly for cancer. PMID:23382867

Partial Least Squares Based Gene Expression Analysis in EBV- Positive and EBV-Negative Posttransplant Lymphoproliferative Disorders.

PubMed

Wu, Sa; Zhang, Xin; Li, Zhi-Ming; Shi, Yan-Xia; Huang, Jia-Jia; Xia, Yi; Yang, Hang; Jiang, Wen-Qi

2013-01-01

Post-transplant lymphoproliferative disorder (PTLD) is a common complication of therapeutic immunosuppression after organ transplantation. Gene expression profile facilitates the identification of biological difference between Epstein-Barr virus (EBV) positive and negative PTLDs. Previous studies mainly implemented variance/regression analysis without considering unaccounted array specific factors. The aim of this study is to investigate the gene expression difference between EBV positive and negative PTLDs through partial least squares (PLS) based analysis. With a microarray data set from the Gene Expression Omnibus database, we performed PLS based analysis. We acquired 1188 differentially expressed genes. Pathway and Gene Ontology enrichment analysis identified significantly over-representation of dysregulated genes in immune response and cancer related biological processes. Network analysis identified three hub genes with degrees higher than 15, including CREBBP, ATXN1, and PML. Proteins encoded by CREBBP and PML have been reported to be interact with EBV before. Our findings shed light on expression distinction of EBV positive and negative PTLDs with the hope to offer theoretical support for future therapeutic study.

Validating internal controls for quantitative plant gene expression studies.

PubMed

Brunner, Amy M; Yakovlev, Igor A; Strauss, Steven H

2004-08-18

Real-time reverse transcription PCR (RT-PCR) has greatly improved the ease and sensitivity of quantitative gene expression studies. However, accurate measurement of gene expression with this method relies on the choice of a valid reference for data normalization. Studies rarely verify that gene expression levels for reference genes are adequately consistent among the samples used, nor compare alternative genes to assess which are most reliable for the experimental conditions analyzed. Using real-time RT-PCR to study the expression of 10 poplar (genus Populus) housekeeping genes, we demonstrate a simple method for determining the degree of stability of gene expression over a set of experimental conditions. Based on a traditional method for analyzing the stability of varieties in plant breeding, it defines measures of gene expression stability from analysis of variance (ANOVA) and linear regression. We found that the potential internal control genes differed widely in their expression stability over the different tissues, developmental stages and environmental conditions studied. Our results support that quantitative comparisons of candidate reference genes are an important part of real-time RT-PCR studies that seek to precisely evaluate variation in gene expression. The method we demonstrated facilitates statistical and graphical evaluation of gene expression stability. Selection of the best reference gene for a given set of experimental conditions should enable detection of biologically significant changes in gene expression that are too small to be revealed by less precise methods, or when highly variable reference genes are unknowingly used in real-time RT-PCR experiments.

Partial least squares based gene expression analysis in estrogen receptor positive and negative breast tumors.

PubMed

Ma, W; Zhang, T-F; Lu, P; Lu, S H

2014-01-01

Breast cancer is categorized into two broad groups: estrogen receptor positive (ER+) and ER negative (ER-) groups. Previous study proposed that under trastuzumab-based neoadjuvant chemotherapy, tumor initiating cell (TIC) featured ER- tumors response better than ER+ tumors. Exploration of the molecular difference of these two groups may help developing new therapeutic strategies, especially for ER- patients. With gene expression profile from the Gene Expression Omnibus (GEO) database, we performed partial least squares (PLS) based analysis, which is more sensitive than common variance/regression analysis. We acquired 512 differentially expressed genes. Four pathways were found to be enriched with differentially expressed genes, involving immune system, metabolism and genetic information processing process. Network analysis identified five hub genes with degrees higher than 10, including APP, ESR1, SMAD3, HDAC2, and PRKAA1. Our findings provide new understanding for the molecular difference between TIC featured ER- and ER+ breast tumors with the hope offer supports for therapeutic studies.

Validating internal controls for quantitative plant gene expression studies

PubMed Central

Brunner, Amy M; Yakovlev, Igor A; Strauss, Steven H

2004-01-01

Background Real-time reverse transcription PCR (RT-PCR) has greatly improved the ease and sensitivity of quantitative gene expression studies. However, accurate measurement of gene expression with this method relies on the choice of a valid reference for data normalization. Studies rarely verify that gene expression levels for reference genes are adequately consistent among the samples used, nor compare alternative genes to assess which are most reliable for the experimental conditions analyzed. Results Using real-time RT-PCR to study the expression of 10 poplar (genus Populus) housekeeping genes, we demonstrate a simple method for determining the degree of stability of gene expression over a set of experimental conditions. Based on a traditional method for analyzing the stability of varieties in plant breeding, it defines measures of gene expression stability from analysis of variance (ANOVA) and linear regression. We found that the potential internal control genes differed widely in their expression stability over the different tissues, developmental stages and environmental conditions studied. Conclusion Our results support that quantitative comparisons of candidate reference genes are an important part of real-time RT-PCR studies that seek to precisely evaluate variation in gene expression. The method we demonstrated facilitates statistical and graphical evaluation of gene expression stability. Selection of the best reference gene for a given set of experimental conditions should enable detection of biologically significant changes in gene expression that are too small to be revealed by less precise methods, or when highly variable reference genes are unknowingly used in real-time RT-PCR experiments. PMID:15317655

The functional importance of sequence versus expression variability of MHC alleles in parasite resistance.

PubMed

Axtner, Jan; Sommer, Simone

2012-12-01

Understanding selection processes driving the pronounced allelic polymorphism of the major histocompatibility complex (MHC) genes and its functional associations to parasite load have been the focus of many recent wildlife studies. Two main selection scenarios are currently debated which explain the susceptibility or resistance to parasite infections either by the effects of (1) specific MHC alleles which are selected frequency-dependent in space and time or (2) a heterozygote or divergent allele advantage. So far, most studies have focused only on structural variance in co-evolutionary processes although this might not be the only trait subject to natural selection. In the present study, we analysed structural variance stretching from exon1 through exon3 of MHC class II DRB genes as well as genotypic expression variance in relation to the gastrointestinal helminth prevalence and infection intensity in wild yellow-necked mice (Apodemus flavicollis). We found support for the functional importance of specific alleles both on the sequence and expression level. By resampling a previously investigated study population we identified specific MHC alleles affected by temporal shifts in parasite pressure and recorded associated changes in allele frequencies. The allele Apfl-DRB*23 was associated with resistance to infections by the oxyurid nematode Syphacia stroma and at the same time with susceptibility to cestode infection intensity. In line with our expectation, MHC mRNA transcript levels tended to be higher in cestode-infected animals carrying the allele Apfl-DRB*23. However, no support for a heterozygote or divergent allele advantage on the sequence or expression level was detected. The individual amino acid distance of genotypes did not explain individual differences in parasite loads and the genetic distance had no effect on MHC genotype expression. For ongoing studies on the functional importance of expression variance in parasite resistance, allele-specific expression data would be preferable.

A microarray analysis of potential genes underlying the neurosensitivity of mice to propofol.

PubMed

Lowes, Damon A; Galley, Helen F; Lowe, Peter R; Rikke, Brad A; Johnson, Thomas E; Webster, Nigel R

2005-09-01

Establishing the mechanism of action of general anesthetics at the molecular level is difficult because of the multiple targets with which these drugs are associated. Inbred short sleep (ISS) and long sleep (ILS) mice are differentially sensitive in response to ethanol and other sedative hypnotics and contain a single quantitative trait locus (Lorp1) that accounts for the genetic variance of loss-of-righting reflex in response to propofol (LORP). In this study, we used high-density oligonucleotide microarrays to identify global gene expression and candidate genes differentially expressed within the Lorp1 region that may give insight into the molecular mechanism underlying LORP. Microarray analysis was performed using Affymetrix MG-U74Av2 Genechips and a selection of differentially expressed genes was confirmed by semiquantitative reverse transcription-polymerase chain reaction. Global expression in the brains of ILS and ISS mice revealed 3423 genes that were significantly expressed, of which 139 (4%) were differentially expressed. Analysis of genes located within the Lorp1 region showed that 26 genes were significantly expressed and that just 2 genes (7%) were differentially expressed. These genes encoded for the proteins AWP1 (associated with protein kinase 1) and "BTB (POZ) domain containing 1," whose functions are largely uncharacterized. Genes differentially expressed outside Lorp1 included seven genes with previously characterized neuronal functions and thus stand out as additional candidate genes that may be involved in mediating the neurosensitivity differences between ISS and ILS.

Using RNA-seq data to select reference genes for normalizing gene expression in apple roots.

PubMed

Zhou, Zhe; Cong, Peihua; Tian, Yi; Zhu, Yanmin

2017-01-01

Gene expression in apple roots in response to various stress conditions is a less-explored research subject. Reliable reference genes for normalizing quantitative gene expression data have not been carefully investigated. In this study, the suitability of a set of 15 apple genes were evaluated for their potential use as reliable reference genes. These genes were selected based on their low variance of gene expression in apple root tissues from a recent RNA-seq data set, and a few previously reported apple reference genes for other tissue types. Four methods, Delta Ct, geNorm, NormFinder and BestKeeper, were used to evaluate their stability in apple root tissues of various genotypes and under different experimental conditions. A small panel of stably expressed genes, MDP0000095375, MDP0000147424, MDP0000233640, MDP0000326399 and MDP0000173025 were recommended for normalizing quantitative gene expression data in apple roots under various abiotic or biotic stresses. When the most stable and least stable reference genes were used for data normalization, significant differences were observed on the expression patterns of two target genes, MdLecRLK5 (MDP0000228426, a gene encoding a lectin receptor like kinase) and MdMAPK3 (MDP0000187103, a gene encoding a mitogen-activated protein kinase). Our data also indicated that for those carefully validated reference genes, a single reference gene is sufficient for reliable normalization of the quantitative gene expression. Depending on the experimental conditions, the most suitable reference genes can be specific to the sample of interest for more reliable RT-qPCR data normalization.

Using RNA-seq data to select reference genes for normalizing gene expression in apple roots

PubMed Central

Zhou, Zhe; Cong, Peihua; Tian, Yi

2017-01-01

Gene expression in apple roots in response to various stress conditions is a less-explored research subject. Reliable reference genes for normalizing quantitative gene expression data have not been carefully investigated. In this study, the suitability of a set of 15 apple genes were evaluated for their potential use as reliable reference genes. These genes were selected based on their low variance of gene expression in apple root tissues from a recent RNA-seq data set, and a few previously reported apple reference genes for other tissue types. Four methods, Delta Ct, geNorm, NormFinder and BestKeeper, were used to evaluate their stability in apple root tissues of various genotypes and under different experimental conditions. A small panel of stably expressed genes, MDP0000095375, MDP0000147424, MDP0000233640, MDP0000326399 and MDP0000173025 were recommended for normalizing quantitative gene expression data in apple roots under various abiotic or biotic stresses. When the most stable and least stable reference genes were used for data normalization, significant differences were observed on the expression patterns of two target genes, MdLecRLK5 (MDP0000228426, a gene encoding a lectin receptor like kinase) and MdMAPK3 (MDP0000187103, a gene encoding a mitogen-activated protein kinase). Our data also indicated that for those carefully validated reference genes, a single reference gene is sufficient for reliable normalization of the quantitative gene expression. Depending on the experimental conditions, the most suitable reference genes can be specific to the sample of interest for more reliable RT-qPCR data normalization. PMID:28934340

Altered Expression of Diabetes-Related Genes in Alzheimer's Disease Brains: The Hisayama Study

PubMed Central

Hokama, Masaaki; Oka, Sugako; Leon, Julio; Ninomiya, Toshiharu; Honda, Hiroyuki; Sasaki, Kensuke; Iwaki, Toru; Ohara, Tomoyuki; Sasaki, Tomio; LaFerla, Frank M.; Kiyohara, Yutaka; Nakabeppu, Yusaku

2014-01-01

Diabetes mellitus (DM) is considered to be a risk factor for dementia including Alzheimer's disease (AD). However, the molecular mechanism underlying this risk is not well understood. We examined gene expression profiles in postmortem human brains donated for the Hisayama study. Three-way analysis of variance of microarray data from frontal cortex, temporal cortex, and hippocampus was performed with the presence/absence of AD and vascular dementia, and sex, as factors. Comparative analyses of expression changes in the brains of AD patients and a mouse model of AD were also performed. Relevant changes in gene expression identified by microarray analysis were validated by quantitative real-time reverse-transcription polymerase chain reaction and western blotting. The hippocampi of AD brains showed the most significant alteration in gene expression profile. Genes involved in noninsulin-dependent DM and obesity were significantly altered in both AD brains and the AD mouse model, as were genes related to psychiatric disorders and AD. The alterations in the expression profiles of DM-related genes in AD brains were independent of peripheral DM-related abnormalities. These results indicate that altered expression of genes related to DM in AD brains is a result of AD pathology, which may thereby be exacerbated by peripheral insulin resistance or DM. PMID:23595620

Constrained clusters of gene expression profiles with pathological features.

PubMed

Sese, Jun; Kurokawa, Yukinori; Monden, Morito; Kato, Kikuya; Morishita, Shinichi

2004-11-22

Gene expression profiles should be useful in distinguishing variations in disease, since they reflect accurately the status of cells. The primary clustering of gene expression reveals the genotypes that are responsible for the proximity of members within each cluster, while further clustering elucidates the pathological features of the individual members of each cluster. However, since the first clustering process and the second classification step, in which the features are associated with clusters, are performed independently, the initial set of clusters may omit genes that are associated with pathologically meaningful features. Therefore, it is important to devise a way of identifying gene expression clusters that are associated with pathological features. We present the novel technique of 'itemset constrained clustering' (IC-Clustering), which computes the optimal cluster that maximizes the interclass variance of gene expression between groups, which are divided according to the restriction that only divisions that can be expressed using common features are allowed. This constraint automatically labels each cluster with a set of pathological features which characterize that cluster. When applied to liver cancer datasets, IC-Clustering revealed informative gene expression clusters, which could be annotated with various pathological features, such as 'tumor' and 'man', or 'except tumor' and 'normal liver function'. In contrast, the k-means method overlooked these clusters.

Complex Genotype by Environment interactions and changing genetic architectures across thermal environments in the Australian field cricket, Teleogryllus oceanicus

PubMed Central

2011-01-01

Background Biologists studying adaptation under sexual selection have spent considerable effort assessing the relative importance of two groups of models, which hinge on the idea that females gain indirect benefits via mate discrimination. These are the good genes and genetic compatibility models. Quantitative genetic studies have advanced our understanding of these models by enabling assessment of whether the genetic architectures underlying focal phenotypes are congruent with either model. In this context, good genes models require underlying additive genetic variance, while compatibility models require non-additive variance. Currently, we know very little about how the expression of genotypes comprised of distinct parental haplotypes, or how levels and types of genetic variance underlying key phenotypes, change across environments. Such knowledge is important, however, because genotype-environment interactions can have major implications on the potential for evolutionary responses to selection. Results We used a full diallel breeding design to screen for complex genotype-environment interactions, and genetic architectures underlying key morphological traits, across two thermal environments (the lab standard 27°C, and the cooler 23°C) in the Australian field cricket, Teleogryllus oceanicus. In males, complex three-way interactions between sire and dam parental haplotypes and the rearing environment accounted for up to 23 per cent of the scaled phenotypic variance in the traits we measured (body mass, pronotum width and testes mass), and each trait harboured significant additive genetic variance in the standard temperature (27°C) only. In females, these three-way interactions were less important, with interactions between the paternal haplotype and rearing environment accounting for about ten per cent of the phenotypic variance (in body mass, pronotum width and ovary mass). Of the female traits measured, only ovary mass for crickets reared at the cooler temperature (23°C), exhibited significant levels of additive genetic variance. Conclusions Our results show that the genetics underlying phenotypic expression can be complex, context-dependent and different in each of the sexes. We discuss the implications of these results, particularly in terms of the evolutionary processes that hinge on good and compatible genes models. PMID:21791118

Precision matters for position decoding in the early fly embryo

NASA Astrophysics Data System (ADS)

Petkova, Mariela D.; Tkacik, Gasper; Wieschaus, Eric F.; Bialek, William; Gregor, Thomas

Genetic networks can determine cell fates in multicellular organisms with precision that often reaches the physical limits of the system. However, it is unclear how the organism uses this precision and whether it has biological content. Here we address this question in the developing fly embryo, in which a genetic network of patterning genes reaches 1% precision in positioning cells along the embryo axis. The network consists of three interconnected layers: an input layer of maternal gradients, a processing layer of gap genes, and an output layer of pair-rule genes with seven-striped patterns. From measurements of gap gene protein expression in hundreds of wild-type embryos we construct a ``decoder'', which is a look-up table that determines cellular positions from the concentration means, variances and co-variances. When we apply the decoder to measurements in mutant embryos lacking various combinations of the maternal inputs, we predict quantitative changes in the output layer such as missing, altered or displaced stripes. We confirm these predictions by measuring pair-rule expression in the mutant embryos. Our results thereby show that the precision of the patterning network is biologically meaningful and a necessary feature for decoding cell positions in the early fly embryo.

A multiplex branched DNA assay for parallel quantitative gene expression profiling.

PubMed

Flagella, Michael; Bui, Son; Zheng, Zhi; Nguyen, Cung Tuong; Zhang, Aiguo; Pastor, Larry; Ma, Yunqing; Yang, Wen; Crawford, Kimberly L; McMaster, Gary K; Witney, Frank; Luo, Yuling

2006-05-01

We describe a novel method to quantitatively measure messenger RNA (mRNA) expression of multiple genes directly from crude cell lysates and tissue homogenates without the need for RNA purification or target amplification. The multiplex branched DNA (bDNA) assay adapts the bDNA technology to the Luminex fluorescent bead-based platform through the use of cooperative hybridization, which ensures an exceptionally high degree of assay specificity. Using in vitro transcribed RNA as reference standards, we demonstrated that the assay is highly specific, with cross-reactivity less than 0.2%. We also determined that the assay detection sensitivity is 25,000 RNA transcripts with intra- and interplate coefficients of variance of less than 10% and less than 15%, respectively. Using three 10-gene panels designed to measure proinflammatory and apoptosis responses, we demonstrated sensitive and specific multiplex gene expression profiling directly from cell lysates. The gene expression change data demonstrate a high correlation coefficient (R(2)=0.94) compared with measurements obtained using the single-plex bDNA assay. Thus, the multiplex bDNA assay provides a powerful means to quantify the gene expression profile of a defined set of target genes in large sample populations.

Gene set analysis using variance component tests.

PubMed

Huang, Yen-Tsung; Lin, Xihong

2013-06-28

Gene set analyses have become increasingly important in genomic research, as many complex diseases are contributed jointly by alterations of numerous genes. Genes often coordinate together as a functional repertoire, e.g., a biological pathway/network and are highly correlated. However, most of the existing gene set analysis methods do not fully account for the correlation among the genes. Here we propose to tackle this important feature of a gene set to improve statistical power in gene set analyses. We propose to model the effects of an independent variable, e.g., exposure/biological status (yes/no), on multiple gene expression values in a gene set using a multivariate linear regression model, where the correlation among the genes is explicitly modeled using a working covariance matrix. We develop TEGS (Test for the Effect of a Gene Set), a variance component test for the gene set effects by assuming a common distribution for regression coefficients in multivariate linear regression models, and calculate the p-values using permutation and a scaled chi-square approximation. We show using simulations that type I error is protected under different choices of working covariance matrices and power is improved as the working covariance approaches the true covariance. The global test is a special case of TEGS when correlation among genes in a gene set is ignored. Using both simulation data and a published diabetes dataset, we show that our test outperforms the commonly used approaches, the global test and gene set enrichment analysis (GSEA). We develop a gene set analyses method (TEGS) under the multivariate regression framework, which directly models the interdependence of the expression values in a gene set using a working covariance. TEGS outperforms two widely used methods, GSEA and global test in both simulation and a diabetes microarray data.

Evolution under canalization and the dual roles of microRNAs—A hypothesis

PubMed Central

Wu, Chung-I; Shen, Yang; Tang, Tian

2009-01-01

Canalization refers to the process by which phenotypes are stabilized within species. Evolution by natural selection can proceed efficiently only when phenotypes are canalized. The existence and identity of canalizing genes have thus been an important, but controversial topic. Recent evidence has increasingly hinted that microRNAs may be involved in canalizing gene expression. Their paradoxical properties (e.g., strongly conserved but functionally dispensable) suggest unconventional regulatory roles. We synthesized published and unpublished results and hypothesize that miRNAs may have dual functions—in gene expression tuning and in expression buffering. In tuning, miRNAs modify the mean expression level of their targets, but in buffering they merely reduce the variance around a preset mean. In light of the constant emergence of new miRNAs, we further discuss the relative importance of these two functions in evolution. PMID:19411598

Analysis on evolutionary relationship of amylases from archaea, bacteria and eukaryota.

PubMed

Yan, Shaomin; Wu, Guang

2016-02-01

Amylase is one of the earliest characterized enzymes and has many applications in clinical and industrial settings. In biotechnological industries, the amylase activity is enhanced through modifying amylase structure and through cloning and expressing targeted amylases in different species. It is important to understand how engineered amylases can survive from generation to generation. This study used phylogenetic and statistical approaches to explore general patterns of amylases evolution, including 3118 α-amylases and 280 β-amylases from archaea, eukaryota and bacteria with fully documented taxonomic lineage. First, the phylogenetic tree was created to analyze the evolution of amylases with focus on individual amylases used in biofuel industry. Second, the average pairwise p-distance was computed for each kingdom, phylum, class, order, family and genus, and its diversity implies multi-time and multi-clan evolution. Finally, the variance was further partitioned into inter-clan variance and intra-clan variance for each taxonomic group, and they represent horizontal and vertical gene transfer. Theoretically, the results show a full picture on the evolution of amylases in manners of vertical and horizontal gene transfer, and multi-time and multi-clan evolution as well. Practically, this study provides the information on the surviving chance of desired amylase in a given taxonomic group, which may potentially enhance the successful rate of cloning and expression of amylase gene in different species.

Alternative-splicing-mediated gene expression

NASA Astrophysics Data System (ADS)

Wang, Qianliang; Zhou, Tianshou

2014-01-01

Alternative splicing (AS) is a fundamental process during gene expression and has been found to be ubiquitous in eukaryotes. However, how AS impacts gene expression levels both quantitatively and qualitatively remains to be fully explored. Here, we analyze two common models of gene expression, each incorporating a simple splice mechanism that a pre-mRNA is spliced into two mature mRNA isoforms in a probabilistic manner. In the constitutive expression case, we show that the steady-state molecular numbers of two mature mRNA isoforms follow mutually independent Poisson distributions. In the bursting expression case, we demonstrate that the tail decay of the steady-state distribution for both mature mRNA isoforms that in general are not mutually independent can be characterized by the product of mean burst size and splicing probability. In both cases, we find that AS can efficiently modulate both the variability (measured by variance) and the noise level of the total mature mRNA, and in particular, the latter is always lower than the noise level of the pre-mRNA, implying that AS always reduces the noise. These results altogether reveal that AS is a mechanism of efficiently controlling the gene expression noise.

Expression of venom gene homologs in diverse python tissues suggests a new model for the evolution of snake venom.

PubMed

Reyes-Velasco, Jacobo; Card, Daren C; Andrew, Audra L; Shaney, Kyle J; Adams, Richard H; Schield, Drew R; Casewell, Nicholas R; Mackessy, Stephen P; Castoe, Todd A

2015-01-01

Snake venom gene evolution has been studied intensively over the past several decades, yet most previous studies have lacked the context of complete snake genomes and the full context of gene expression across diverse snake tissues. We took a novel approach to studying snake venom evolution by leveraging the complete genome of the Burmese python, including information from tissue-specific patterns of gene expression. We identified the orthologs of snake venom genes in the python genome, and conducted detailed analysis of gene expression of these venom homologs to identify patterns that differ between snake venom gene families and all other genes. We found that venom gene homologs in the python are expressed in many different tissues outside of oral glands, which illustrates the pitfalls of using transcriptomic data alone to define "venom toxins." We hypothesize that the python may represent an ancestral state prior to major venom development, which is supported by our finding that the expansion of venom gene families is largely restricted to highly venomous caenophidian snakes. Therefore, the python provides insight into biases in which genes were recruited for snake venom systems. Python venom homologs are generally expressed at lower levels, have higher variance among tissues, and are expressed in fewer organs compared with all other python genes. We propose a model for the evolution of snake venoms in which venom genes are recruited preferentially from genes with particular expression profile characteristics, which facilitate a nearly neutral transition toward specialized venom system expression. © The Author 2014. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Super-delta: a new differential gene expression analysis procedure with robust data normalization.

PubMed

Liu, Yuhang; Zhang, Jinfeng; Qiu, Xing

2017-12-21

Normalization is an important data preparation step in gene expression analyses, designed to remove various systematic noise. Sample variance is greatly reduced after normalization, hence the power of subsequent statistical analyses is likely to increase. On the other hand, variance reduction is made possible by borrowing information across all genes, including differentially expressed genes (DEGs) and outliers, which will inevitably introduce some bias. This bias typically inflates type I error; and can reduce statistical power in certain situations. In this study we propose a new differential expression analysis pipeline, dubbed as super-delta, that consists of a multivariate extension of the global normalization and a modified t-test. A robust procedure is designed to minimize the bias introduced by DEGs in the normalization step. The modified t-test is derived based on asymptotic theory for hypothesis testing that suitably pairs with the proposed robust normalization. We first compared super-delta with four commonly used normalization methods: global, median-IQR, quantile, and cyclic loess normalization in simulation studies. Super-delta was shown to have better statistical power with tighter control of type I error rate than its competitors. In many cases, the performance of super-delta is close to that of an oracle test in which datasets without technical noise were used. We then applied all methods to a collection of gene expression datasets on breast cancer patients who received neoadjuvant chemotherapy. While there is a substantial overlap of the DEGs identified by all of them, super-delta were able to identify comparatively more DEGs than its competitors. Downstream gene set enrichment analysis confirmed that all these methods selected largely consistent pathways. Detailed investigations on the relatively small differences showed that pathways identified by super-delta have better connections to breast cancer than other methods. As a new pipeline, super-delta provides new insights to the area of differential gene expression analysis. Solid theoretical foundation supports its asymptotic unbiasedness and technical noise-free properties. Implementation on real and simulated datasets demonstrates its decent performance compared with state-of-art procedures. It also has the potential of expansion to be incorporated with other data type and/or more general between-group comparison problems.

Identification of appropriate reference genes for normalizing transcript expression by quantitative real-time PCR in Litsea cubeba.

PubMed

Lin, Liyuan; Han, Xiaojiao; Chen, Yicun; Wu, Qingke; Wang, Yangdong

2013-12-01

Quantitative real-time PCR has emerged as a highly sensitive and widely used method for detection of gene expression profiles, via which accurate detection depends on reliable normalization. Since no single control is appropriate for all experimental treatments, it is generally advocated to select suitable internal controls prior to use for normalization. This study reported the evaluation of the expression stability of twelve potential reference genes in different tissue/organs and six fruit developmental stages of Litsea cubeba in order to screen the superior internal reference genes for data normalization. Two softwares-geNorm, and NormFinder-were used to identify stability of these candidate genes. The cycle threshold difference and coefficient of variance were also calculated to evaluate the expression stability of candidate genes. F-BOX, EF1α, UBC, and TUA were selected as the most stable reference genes across 11 sample pools. F-BOX, EF1α, and EIF4α exhibited the highest expression stability in different tissue/organs and different fruit developmental stages. Besides, a combination of two stable reference genes would be sufficient for gene expression normalization in different fruit developmental stages. In addition, the relative expression profiles of DXS and DXR were evaluated by EF1α, UBC, and SAMDC. The results further validated the reliability of stable reference genes and also highlighted the importance of selecting suitable internal controls for L. cubeba. These reference genes will be of great importance for transcript normalization in future gene expression studies on L. cubeba.

Spotting and validation of a genome wide oligonucleotide chip with duplicate measurement of each gene

DOE Office of Scientific and Technical Information (OSTI.GOV)

Thomassen, Mads; Skov, Vibe; Eiriksdottir, Freyja

2006-06-16

The quality of DNA microarray based gene expression data relies on the reproducibility of several steps in a microarray experiment. We have developed a spotted genome wide microarray chip with oligonucleotides printed in duplicate in order to minimise undesirable biases, thereby optimising detection of true differential expression. The validation study design consisted of an assessment of the microarray chip performance using the MessageAmp and FairPlay labelling kits. Intraclass correlation coefficient (ICC) was used to demonstrate that MessageAmp was significantly more reproducible than FairPlay. Further examinations with MessageAmp revealed the applicability of the system. The linear range of the chips wasmore » three orders of magnitude, the precision was high, as 95% of measurements deviated less than 1.24-fold from the expected value, and the coefficient of variation for relative expression was 13.6%. Relative quantitation was more reproducible than absolute quantitation and substantial reduction of variance was attained with duplicate spotting. An analysis of variance (ANOVA) demonstrated no significant day-to-day variation.« less

Sources of Variance in Baseline Gene Expression in the Rodent Liver

PubMed Central

Corton, J. Christopher; Bushel, Pierre R.; Fostel, Jennifer; O'Lone, Raegan B.

2012-01-01

The use of gene expression profiling in both clinical and laboratory settings would be enhanced by better characterization of variation due to individual, environmental, and technical factors. Analysis of microarray data from untreated or vehicle-treated animals within the control arm of toxicogenomics studies has yielded useful information on baseline fluctuations in liver gene expression in the rodent. Here, studies which highlight contributions of different factors to gene expression variability in the rodent liver are discussed including a large meta-analysis of rat liver, which identified genes that vary in control animals in the absence of chemical treatment. Genes and their pathways that are the most and least variable were identified in a number of these studies. Life stage, fasting, sex, diet, circadian rhythm and liver lobe source can profoundly influence gene expression in the liver. Recognition of biological and technical factors that contribute to variability of background gene expression can help the investigator in the design of an experiment that maximizes sensitivity and reduces the influence of confounders that may lead to misinterpretation of genomic changes. The factors that contribute to variability in liver gene expression in rodents are likely analogous to those contributing to human interindividual variability in drug response and chemical toxicity. Identification of batteries of genes that are altered in a variety of background conditions could be used to predict responses to drugs and chemicals in appropriate models of the human liver. PMID:22230429

Aflatoxin formation and gene expression in response to carbon source media shift in Aspergillus parasiticus.

PubMed

Wilkinson, J R; Yu, J; Abbas, H K; Scheffler, B E; Kim, H S; Nierman, W C; Bhatnagar, D; Cleveland, T E

2007-10-01

Aflatoxins are toxic and carcinogenic polyketide metabolites produced by fungal species, including Aspergillus flavus and A. parasiticus. The biosynthesis of aflatoxins is modulated by many environmental factors, including the availability of a carbon source. The gene expression profile of A. parasiticus was evaluated during a shift from a medium with low concentration of simple sugars, yeast extract (YE), to a similar medium with sucrose, yeast extract sucrose (YES). Gene expression and aflatoxins (B1, B2, G1, and G2) were quantified from fungal mycelia harvested pre- and post-shifting. When compared with YE media, YES caused temporary reduction of the aflatoxin levels detected at 3-h post-shifting and they remained low well past 12 h post-shift. Aflatoxin levels did not exceed the levels in YE until 24 h post-shift, at which time point a tenfold increase was observed over YE. Microarray analysis comparing the RNA samples from the 48-h YE culture to the YES samples identified a total of 2120 genes that were expressed across all experiments, including most of the aflatoxin biosynthesis genes. One-way analysis of variance (ANOVA) identified 56 genes that were expressed with significant variation across all time points. Three genes responsible for converting norsolorinic acid to averantin were identified among these significantly expressed genes. The potential involvement of these genes in the regulation of aflatoxin biosynthesis is discussed.

The age dependency of gene expression for plasma lipids, lipoproteins, and apolipoproteins

DOE Office of Scientific and Technical Information (OSTI.GOV)

Snieder, H.; Doornen, L.J.P. van; Boomsma, D.I.

The aim of this study was to investigate and disentangle the genetic and nongenetic causes of stability and change in lipids and (apo)lipoproteins that occur during the lifespan. Total cholesterol, low-density lipoprotein (LDL), high-density lipoprotein (HDL), triglycerides, apolipoprotein A1 (ApoA1), apolipoprotein B (ApoB), and lipoprotein(a) (Lp[a]) were measured in a group of 160 middle-aged parents and their twin offspring (first project) and in a group of 203 middle-aged twin pairs (second project). Combining the data of both projects enabled the estimation of the extent to which measured lipid parameters are influenced by different genes in adolescence and adulthood. To thatmore » end, an extended quantitative genetic model was specified, which allowed the estimation of heritabilities for each sex and generation separately. Heritabilities were similar for both sexes and both generations. Larger variances in the parental generation could be ascribed to proportional increases in both unique environmental and additive genetic variance from childhood to adulthood, which led to similar heritability estimates in adolescent and middle-aged twins. Although the magnitudes of heritabilities were similar across generations, results showed that, for total cholesterol, triglycerides, HDL, and LDL, partly different genes are expressed in adolescence compared to adulthood. For triglycerides, only 46% of the genetic variance was common to both age groups; for total cholesterol this was 80%. Intermediate values were found for HDL (66%) and LDL (76%). For ApoA1, ApoB, and Lp(a), the same genes seem to act in both generations. 56 refs., 2 figs., 5 tabs.« less

Validation of reference genes for quantitative gene expression analysis in experimental epilepsy.

PubMed

Sadangi, Chinmaya; Rosenow, Felix; Norwood, Braxton A

2017-12-01

To grasp the molecular mechanisms and pathophysiology underlying epilepsy development (epileptogenesis) and epilepsy itself, it is important to understand the gene expression changes that occur during these phases. Quantitative real-time polymerase chain reaction (qPCR) is a technique that rapidly and accurately determines gene expression changes. It is crucial, however, that stable reference genes are selected for each experimental condition to ensure that accurate values are obtained for genes of interest. If reference genes are unstably expressed, this can lead to inaccurate data and erroneous conclusions. To date, epilepsy studies have used mostly single, nonvalidated reference genes. This is the first study to systematically evaluate reference genes in male Sprague-Dawley rat models of epilepsy. We assessed 15 potential reference genes in hippocampal tissue obtained from 2 different models during epileptogenesis, 1 model during chronic epilepsy, and a model of noninjurious seizures. Reference gene ranking varied between models and also differed between epileptogenesis and chronic epilepsy time points. There was also some variance between the four mathematical models used to rank reference genes. Notably, we found novel reference genes to be more stably expressed than those most often used in experimental epilepsy studies. The consequence of these findings is that reference genes suitable for one epilepsy model may not be appropriate for others and that reference genes can change over time. It is, therefore, critically important to validate potential reference genes before using them as normalizing factors in expression analysis in order to ensure accurate, valid results. © 2017 Wiley Periodicals, Inc.

An extended data mining method for identifying differentially expressed assay-specific signatures in functional genomic studies.

PubMed

Rollins, Derrick K; Teh, Ailing

2010-12-17

Microarray data sets provide relative expression levels for thousands of genes for a small number, in comparison, of different experimental conditions called assays. Data mining techniques are used to extract specific information of genes as they relate to the assays. The multivariate statistical technique of principal component analysis (PCA) has proven useful in providing effective data mining methods. This article extends the PCA approach of Rollins et al. to the development of ranking genes of microarray data sets that express most differently between two biologically different grouping of assays. This method is evaluated on real and simulated data and compared to a current approach on the basis of false discovery rate (FDR) and statistical power (SP) which is the ability to correctly identify important genes. This work developed and evaluated two new test statistics based on PCA and compared them to a popular method that is not PCA based. Both test statistics were found to be effective as evaluated in three case studies: (i) exposing E. coli cells to two different ethanol levels; (ii) application of myostatin to two groups of mice; and (iii) a simulated data study derived from the properties of (ii). The proposed method (PM) effectively identified critical genes in these studies based on comparison with the current method (CM). The simulation study supports higher identification accuracy for PM over CM for both proposed test statistics when the gene variance is constant and for one of the test statistics when the gene variance is non-constant. PM compares quite favorably to CM in terms of lower FDR and much higher SP. Thus, PM can be quite effective in producing accurate signatures from large microarray data sets for differential expression between assays groups identified in a preliminary step of the PCA procedure and is, therefore, recommended for use in these applications.

Transforming RNA-Seq data to improve the performance of prognostic gene signatures.

PubMed

Zwiener, Isabella; Frisch, Barbara; Binder, Harald

2014-01-01

Gene expression measurements have successfully been used for building prognostic signatures, i.e for identifying a short list of important genes that can predict patient outcome. Mostly microarray measurements have been considered, and there is little advice available for building multivariable risk prediction models from RNA-Seq data. We specifically consider penalized regression techniques, such as the lasso and componentwise boosting, which can simultaneously consider all measurements and provide both, multivariable regression models for prediction and automated variable selection. However, they might be affected by the typical skewness, mean-variance-dependency or extreme values of RNA-Seq covariates and therefore could benefit from transformations of the latter. In an analytical part, we highlight preferential selection of covariates with large variances, which is problematic due to the mean-variance dependency of RNA-Seq data. In a simulation study, we compare different transformations of RNA-Seq data for potentially improving detection of important genes. Specifically, we consider standardization, the log transformation, a variance-stabilizing transformation, the Box-Cox transformation, and rank-based transformations. In addition, the prediction performance for real data from patients with kidney cancer and acute myeloid leukemia is considered. We show that signature size, identification performance, and prediction performance critically depend on the choice of a suitable transformation. Rank-based transformations perform well in all scenarios and can even outperform complex variance-stabilizing approaches. Generally, the results illustrate that the distribution and potential transformations of RNA-Seq data need to be considered as a critical step when building risk prediction models by penalized regression techniques.

Transforming RNA-Seq Data to Improve the Performance of Prognostic Gene Signatures

PubMed Central

Zwiener, Isabella; Frisch, Barbara; Binder, Harald

2014-01-01

Gene expression measurements have successfully been used for building prognostic signatures, i.e for identifying a short list of important genes that can predict patient outcome. Mostly microarray measurements have been considered, and there is little advice available for building multivariable risk prediction models from RNA-Seq data. We specifically consider penalized regression techniques, such as the lasso and componentwise boosting, which can simultaneously consider all measurements and provide both, multivariable regression models for prediction and automated variable selection. However, they might be affected by the typical skewness, mean-variance-dependency or extreme values of RNA-Seq covariates and therefore could benefit from transformations of the latter. In an analytical part, we highlight preferential selection of covariates with large variances, which is problematic due to the mean-variance dependency of RNA-Seq data. In a simulation study, we compare different transformations of RNA-Seq data for potentially improving detection of important genes. Specifically, we consider standardization, the log transformation, a variance-stabilizing transformation, the Box-Cox transformation, and rank-based transformations. In addition, the prediction performance for real data from patients with kidney cancer and acute myeloid leukemia is considered. We show that signature size, identification performance, and prediction performance critically depend on the choice of a suitable transformation. Rank-based transformations perform well in all scenarios and can even outperform complex variance-stabilizing approaches. Generally, the results illustrate that the distribution and potential transformations of RNA-Seq data need to be considered as a critical step when building risk prediction models by penalized regression techniques. PMID:24416353

Patterns of gene expression in a scleractinian coral undergoing natural bleaching.

PubMed

Seneca, Francois O; Forêt, Sylvain; Ball, Eldon E; Smith-Keune, Carolyn; Miller, David J; van Oppen, Madeleine J H

2010-10-01

Coral bleaching is a major threat to coral reefs worldwide and is predicted to intensify with increasing global temperature. This study represents the first investigation of gene expression in an Indo-Pacific coral species undergoing natural bleaching which involved the loss of algal symbionts. Quantitative real-time polymerase chain reaction experiments were conducted to select and evaluate coral internal control genes (ICGs), and to investigate selected coral genes of interest (GOIs) for changes in gene expression in nine colonies of the scleractinian coral Acropora millepora undergoing bleaching at Magnetic Island, Great Barrier Reef, Australia. Among the six ICGs tested, glyceraldehyde 3-phosphate dehydrogenase and the ribosomal protein genes S7 and L9 exhibited the most constant expression levels between samples from healthy-looking colonies and samples from the same colonies when severely bleached a year later. These ICGs were therefore utilised for normalisation of expression data for seven selected GOIs. Of the seven GOIs, homologues of catalase, C-type lectin and chromoprotein genes were significantly up-regulated as a result of bleaching by factors of 1.81, 1.46 and 1.61 (linear mixed models analysis of variance, P < 0.05), respectively. We present these genes as potential coral bleaching response genes. In contrast, three genes, including one putative ICG, showed highly variable levels of expression between coral colonies. Potential variation in microhabitat, gene function unrelated to the stress response and individualised stress responses may influence such differences between colonies and need to be better understood when designing and interpreting future studies of gene expression in natural coral populations.

Aging Shapes the Population-Mean and -Dispersion of Gene Expression in Human Brains

PubMed Central

Brinkmeyer-Langford, Candice L.; Guan, Jinting; Ji, Guoli; Cai, James J.

2016-01-01

Human aging is associated with cognitive decline and an increased risk of neurodegenerative disease. Our objective for this study was to evaluate potential relationships between age and variation in gene expression across different regions of the brain. We analyzed the Genotype-Tissue Expression (GTEx) data from 54 to 101 tissue samples across 13 brain regions in post-mortem donors of European descent aged between 20 and 70 years at death. After accounting for the effects of covariates and hidden confounding factors, we identified 1446 protein-coding genes whose expression in one or more brain regions is correlated with chronological age at a false discovery rate of 5%. These genes are involved in various biological processes including apoptosis, mRNA splicing, amino acid biosynthesis, and neurotransmitter transport. The distribution of these genes among brain regions is uneven, suggesting variable regional responses to aging. We also found that the aging response of many genes, e.g., TP37 and C1QA, depends on individuals' genotypic backgrounds. Finally, using dispersion-specific analysis, we identified genes such as IL7R, MS4A4E, and TERF1/TERF2 whose expressions are differentially dispersed by aging, i.e., variances differ between age groups. Our results demonstrate that age-related gene expression is brain region-specific, genotype-dependent, and associated with both mean and dispersion changes. Our findings provide a foundation for more sophisticated gene expression modeling in the studies of age-related neurodegenerative diseases. PMID:27536236

Gene network polymorphism is the raw material of natural selection: the selfish gene network hypothesis.

PubMed

Boldogköi, Zsolt

2004-09-01

Population genetics, the mathematical theory of modern evolutionary biology, defines evolution as the alteration of the frequency of distinct gene variants (alleles) differing in fitness over the time. The major problem with this view is that in gene and protein sequences we can find little evidence concerning the molecular basis of phenotypic variance, especially those that would confer adaptive benefit to the bearers. Some novel data, however, suggest that a large amount of genetic variation exists in the regulatory region of genes within populations. In addition, comparison of homologous DNA sequences of various species shows that evolution appears to depend more strongly on gene expression than on the genes themselves. Furthermore, it has been demonstrated in several systems that genes form functional networks, whose products exhibit interrelated expression profiles. Finally, it has been found that regulatory circuits of development behave as evolutionary units. These data demonstrate that our view of evolution calls for a new synthesis. In this article I propose a novel concept, termed the selfish gene network hypothesis, which is based on an overall consideration of the above findings. The major statements of this hypothesis are as follows. (1) Instead of individual genes, gene networks (GNs) are responsible for the determination of traits and behaviors. (2) The primary source of microevolution is the intraspecific polymorphism in GNs and not the allelic variation in either the coding or the regulatory sequences of individual genes. (3) GN polymorphism is generated by the variation in the regulatory regions of the component genes and not by the variance in their coding sequences. (4) Evolution proceeds through continuous restructuring of the composition of GNs rather than fixing of specific alleles or GN variants.

Sexually antagonistic selection on genetic variation underlying both male and female same-sex sexual behavior.

PubMed

Berger, David; You, Tao; Minano, Maravillas R; Grieshop, Karl; Lind, Martin I; Arnqvist, Göran; Maklakov, Alexei A

2016-05-13

Intralocus sexual conflict, arising from selection for different alleles at the same locus in males and females, imposes a constraint on sex-specific adaptation. Intralocus sexual conflict can be alleviated by the evolution of sex-limited genetic architectures and phenotypic expression, but pleiotropic constraints may hinder this process. Here, we explored putative intralocus sexual conflict and genetic (co)variance in a poorly understood behavior with near male-limited expression. Same-sex sexual behaviors (SSBs) generally do not conform to classic evolutionary models of adaptation but are common in male animals and have been hypothesized to result from perception errors and selection for high male mating rates. However, perspectives incorporating sex-specific selection on genes shared by males and females to explain the expression and evolution of SSBs have largely been neglected. We performed two parallel sex-limited artificial selection experiments on SSB in male and female seed beetles, followed by sex-specific assays of locomotor activity and male sex recognition (two traits hypothesized to be functionally related to SSB) and adult reproductive success (allowing us to assess fitness consequences of genetic variance in SSB and its correlated components). Our experiments reveal both shared and sex-limited genetic variance for SSB. Strikingly, genetically correlated responses in locomotor activity and male sex-recognition were associated with sexually antagonistic fitness effects, but these effects differed qualitatively between male and female selection lines, implicating intralocus sexual conflict at both male- and female-specific genetic components underlying SSB. Our study provides experimental support for the hypothesis that widespread pleiotropy generates pervasive intralocus sexual conflict governing the expression of SSBs, suggesting that SSB in one sex can occur due to the expression of genes that carry benefits in the other sex.

Quantitative trait loci and metabolic pathways: genetic control of the concentration of maysin, a corn earworm resistance factor, in maize silks.

PubMed Central

Byrne, P F; McMullen, M D; Snook, M E; Musket, T A; Theuri, J M; Widstrom, N W; Wiseman, B R; Coe, E H

1996-01-01

Interpretation of quantitative trait locus (QTL) studies of agronomic traits is limited by lack of knowledge of biochemical pathways leading to trait expression. To more fully elucidate the biological significance of detected QTL, we chose a trait that is the product of a well-characterized pathway, namely the concentration of maysin, a C-glycosyl flavone, in silks of maize, Zea mays L. Maysin is a host-plant resistance factor against the corn earworm, Helicoverpa zea (Boddie). We determined silk maysin concentrations and restriction fragment length polymorphism genotypes at flavonoid pathway loci or linked markers for 285 F2 plants derived from the cross of lines GT114 and GT119. Single-factor analysis of variance indicated that the p1 region on chromosome 1 accounted for 58.0% of the phenotypic variance and showed additive gene action. The p1 locus is a transcription activator for portions of the flavonoid pathway. A second QTL, represented by marker umc 105a near the brown pericarp1 locus on chromosome 9, accounted for 10.8% of the variance. Gene action of this region was dominant for low maysin, but was only expressed in the presence of a functional p1 allele. The model explaining the greatest proportion of phenotypic variance (75.9%) included p1, umc105a, umc166b (chromosome 1), r1 (chromosome 10), and two epistatic interaction terms, p1 x umc105a and p1 x r1. Our results provide evidence that regulatory loci have a central role and that there is a complex interplay among different branches of the flavonoid pathway in the expression of this trait. PMID:11607699

Validation of endogenous internal real-time PCR controls in renal tissues.

PubMed

Cui, Xiangqin; Zhou, Juling; Qiu, Jing; Johnson, Martin R; Mrug, Michal

2009-01-01

Endogenous internal controls ('reference' or 'housekeeping' genes) are widely used in real-time PCR (RT-PCR) analyses. Their use relies on the premise of consistently stable expression across studied experimental conditions. Unfortunately, none of these controls fulfills this premise across a wide range of experimental conditions; consequently, none of them can be recommended for universal use. To determine which endogenous RT-PCR controls are suitable for analyses of renal tissues altered by kidney disease, we studied the expression of 16 commonly used 'reference genes' in 7 mildly and 7 severely affected whole kidney tissues from a well-characterized cystic kidney disease model. Expression levels of these 16 genes, determined by TaqMan RT-PCR analyses and Affymetrix GeneChip arrays, were normalized and tested for overall variance and equivalence of the means. Both statistical approaches and both TaqMan- and GeneChip-based methods converged on 3 out of the 4 top-ranked genes (Ppia, Gapdh and Pgk1) that had the most constant expression levels across the studied phenotypes. A combination of the top-ranked genes will provide a suitable endogenous internal control for similar studies of kidney tissues across a wide range of disease severity. Copyright 2009 S. Karger AG, Basel.

BASiCS: Bayesian Analysis of Single-Cell Sequencing Data

PubMed Central

Vallejos, Catalina A.; Marioni, John C.; Richardson, Sylvia

2015-01-01

Single-cell mRNA sequencing can uncover novel cell-to-cell heterogeneity in gene expression levels in seemingly homogeneous populations of cells. However, these experiments are prone to high levels of unexplained technical noise, creating new challenges for identifying genes that show genuine heterogeneous expression within the population of cells under study. BASiCS (Bayesian Analysis of Single-Cell Sequencing data) is an integrated Bayesian hierarchical model where: (i) cell-specific normalisation constants are estimated as part of the model parameters, (ii) technical variability is quantified based on spike-in genes that are artificially introduced to each analysed cell’s lysate and (iii) the total variability of the expression counts is decomposed into technical and biological components. BASiCS also provides an intuitive detection criterion for highly (or lowly) variable genes within the population of cells under study. This is formalised by means of tail posterior probabilities associated to high (or low) biological cell-to-cell variance contributions, quantities that can be easily interpreted by users. We demonstrate our method using gene expression measurements from mouse Embryonic Stem Cells. Cross-validation and meaningful enrichment of gene ontology categories within genes classified as highly (or lowly) variable supports the efficacy of our approach. PMID:26107944

BASiCS: Bayesian Analysis of Single-Cell Sequencing Data.

PubMed

Vallejos, Catalina A; Marioni, John C; Richardson, Sylvia

2015-06-01

Single-cell mRNA sequencing can uncover novel cell-to-cell heterogeneity in gene expression levels in seemingly homogeneous populations of cells. However, these experiments are prone to high levels of unexplained technical noise, creating new challenges for identifying genes that show genuine heterogeneous expression within the population of cells under study. BASiCS (Bayesian Analysis of Single-Cell Sequencing data) is an integrated Bayesian hierarchical model where: (i) cell-specific normalisation constants are estimated as part of the model parameters, (ii) technical variability is quantified based on spike-in genes that are artificially introduced to each analysed cell's lysate and (iii) the total variability of the expression counts is decomposed into technical and biological components. BASiCS also provides an intuitive detection criterion for highly (or lowly) variable genes within the population of cells under study. This is formalised by means of tail posterior probabilities associated to high (or low) biological cell-to-cell variance contributions, quantities that can be easily interpreted by users. We demonstrate our method using gene expression measurements from mouse Embryonic Stem Cells. Cross-validation and meaningful enrichment of gene ontology categories within genes classified as highly (or lowly) variable supports the efficacy of our approach.

Transcriptional differences between smokers and non-smokers and variance by obesity as a risk factor for human sensitivity to environmental exposures.

PubMed

Nikodemova, Maria; Yee, Jeremiah; Carney, Patrick R; Bradfield, Christopher A; Malecki, Kristen Mc

2018-04-01

Obesity has been shown to alter response to air pollution and smoking but underlying biological mechanisms are largely unknown and few studies have explored mechanisms by which obesity increases human sensitivity to environmental exposures. Overall study goals were to investigate whole blood gene expression in smokers and non-smokers to examine associations between cigarette smoke and changes in gene expression by obesity status and test for effect modification. Relative fold-change in mRNA expression levels of 84 genes were analyzed using a Toxicity and Stress PCR array among 50 21-54 year old adults. Data on smoking status was confirmed using urinary cotinine levels. Adjusted models included age, gender, white blood cell count and body-mass index. Models comparing gene expression of smokers vs. non-smokers identified six differentially expressed genes associated with smoking after adjustments for covariates. Obesity was associated with 29 genes differentially expressed compared to non-obese. We also identified 9 genes with significant smoking/obesity interactions influencing mRNA levels in adjusted models comparing expression between smokers vs non-smokers for four DNA damage related genes (GADD45A, DDB2, RAD51 and P53), two oxidative stress genes (FTH1, TXN), two hypoxia response genes (BN1P3lL, ARNT), and one gene associated with unfolded protein response (ATF6B). Findings suggest that obesity alters human sensitivity to smoke exposures through several biological pathways by modifying gene expression. Additional studies are needed to fully understand the clinical impact of these effects, but risk assessments should consider underlying phenotypes, such as obesity, that may modulate sensitivity of vulnerable populations to environmental exposures. Copyright © 2018 Elsevier Ltd. All rights reserved.

Origin and Consequences of the Relationship between Protein Mean and Variance

PubMed Central

Vallania, Francesco Luigi Massimo; Sherman, Marc; Goodwin, Zane; Mogno, Ilaria; Cohen, Barak Alon; Mitra, Robi David

2014-01-01

Cell-to-cell variance in protein levels (noise) is a ubiquitous phenomenon that can increase fitness by generating phenotypic differences within clonal populations of cells. An important challenge is to identify the specific molecular events that control noise. This task is complicated by the strong dependence of a protein's cell-to-cell variance on its mean expression level through a power-law like relationship (σ2∝μ1.69). Here, we dissect the nature of this relationship using a stochastic model parameterized with experimentally measured values. This framework naturally recapitulates the power-law like relationship (σ2∝μ1.6) and accurately predicts protein variance across the yeast proteome (r2 = 0.935). Using this model we identified two distinct mechanisms by which protein variance can be increased. Variables that affect promoter activation, such as nucleosome positioning, increase protein variance by changing the exponent of the power-law relationship. In contrast, variables that affect processes downstream of promoter activation, such as mRNA and protein synthesis, increase protein variance in a mean-dependent manner following the power-law. We verified our findings experimentally using an inducible gene expression system in yeast. We conclude that the power-law-like relationship between noise and protein mean is due to the kinetics of promoter activation. Our results provide a framework for understanding how molecular processes shape stochastic variation across the genome. PMID:25062021

Intensive cardiovascular risk reduction induces sustainable changes in expression of genes and pathways important to vascular function.

PubMed

Ellsworth, Darrell L; Croft, Daniel T; Weyandt, Jamie; Sturtz, Lori A; Blackburn, Heather L; Burke, Amy; Haberkorn, Mary Jane; McDyer, Fionnuala A; Jellema, Gera L; van Laar, Ryan; Mamula, Kimberly A; Chen, Yaqin; Vernalis, Marina N

2014-04-01

Healthy lifestyle changes are thought to mediate cardiovascular disease risk through pathways affecting endothelial function and progression of atherosclerosis; however, the extent, persistence, and clinical significance of molecular change during lifestyle modification are not well known. We examined the effect of a rigorous cardiovascular disease risk reduction program on peripheral blood gene expression profiles in 63 participants and 63 matched controls to characterize molecular responses and identify regulatory pathways important to cardiovascular health. Dramatic changes in dietary fat intake (-61%; P<0.001 versus controls) and physical fitness (+34%; P<0.001) led to significant improvements in cardiovascular disease risk factors. Analysis of variance with false discovery rate correction for multiple testing (P<0.05) identified 26 genes after 12 weeks and 143 genes after 52 weeks that were differentially expressed from baseline in participants. Controls showed little change in cardiovascular disease risk factors or gene expression. Quantitative reverse transcription polymerase chain reaction validated differential expression for selected transcripts. Lifestyle modification effectively reduced expression of proinflammatory genes associated with neutrophil activation and molecular pathways important to vascular function, including cytokine production, carbohydrate metabolism, and steroid hormones. Prescription medications did not significantly affect changes in gene expression. Successful and sustained modulation of gene expression through lifestyle changes may have beneficial effects on the vascular system not apparent from traditional risk factors. Healthy lifestyles may restore homeostasis to the leukocyte transcriptome by downregulating lactoferrin and other genes important in the pathogenesis of atherosclerosis. Clinical Trial Registration- URL: www.clinicaltrials.gov. Unique identifier: NCT01805492.

Evaluation of reference genes for reverse transcription quantitative real-time PCR (RT-qPCR) studies in Silene vulgaris considering the method of cDNA preparation

PubMed Central

Koloušková, Pavla; Stone, James D.

2017-01-01

Accurate gene expression measurements are essential in studies of both crop and wild plants. Reverse transcription quantitative real-time PCR (RT-qPCR) has become a preferred tool for gene expression estimation. A selection of suitable reference genes for the normalization of transcript levels is an essential prerequisite of accurate RT-qPCR results. We evaluated the expression stability of eight candidate reference genes across roots, leaves, flower buds and pollen of Silene vulgaris (bladder campion), a model plant for the study of gynodioecy. As random priming of cDNA is recommended for the study of organellar transcripts and poly(A) selection is indicated for nuclear transcripts, we estimated gene expression with both random-primed and oligo(dT)-primed cDNA. Accordingly, we determined reference genes that perform well with oligo(dT)- and random-primed cDNA, making it possible to estimate levels of nucleus-derived transcripts in the same cDNA samples as used for organellar transcripts, a key benefit in studies of cyto-nuclear interactions. Gene expression variance was estimated by RefFinder, which integrates four different analytical tools. The SvACT and SvGAPDH genes were the most stable candidates across various organs of S. vulgaris, regardless of whether pollen was included or not. PMID:28817728

Copy number variation of human AMY1 is a minor contributor to variation in salivary amylase expression and activity.

PubMed

Carpenter, Danielle; Mitchell, Laura M; Armour, John A L

2017-02-20

Salivary amylase in humans is encoded by the copy variable gene AMY1 in the amylase gene cluster on chromosome 1. Although the role of salivary amylase is well established, the consequences of the copy number variation (CNV) at AMY1 on salivary amylase protein production are less well understood. The amylase gene cluster is highly structured with a fundamental difference between odd and even AMY1 copy number haplotypes. In this study, we aimed to explore, in samples from 119 unrelated individuals, not only the effects of AMY1 CNV on salivary amylase protein expression and amylase enzyme activity but also whether there is any evidence for underlying difference between the common haplotypes containing odd numbers of AMY1 and even copy number haplotypes. AMY1 copy number was significantly correlated with the variation observed in salivary amylase production (11.7% of variance, P < 0.0005) and enzyme activity (13.6% of variance, P < 0.0005) but did not explain the majority of observed variation between individuals. AMY1-odd and AMY1-even haplotypes showed a different relationship between copy number and expression levels, but the difference was not statistically significant (P = 0.052). Production of salivary amylase is correlated with AMY1 CNV, but the majority of interindividual variation comes from other sources. Long-range haplotype structure may affect expression, but this was not significant in our data.

High-Dimensional Heteroscedastic Regression with an Application to eQTL Data Analysis

PubMed Central

Daye, Z. John; Chen, Jinbo; Li, Hongzhe

2011-01-01

Summary We consider the problem of high-dimensional regression under non-constant error variances. Despite being a common phenomenon in biological applications, heteroscedasticity has, so far, been largely ignored in high-dimensional analysis of genomic data sets. We propose a new methodology that allows non-constant error variances for high-dimensional estimation and model selection. Our method incorporates heteroscedasticity by simultaneously modeling both the mean and variance components via a novel doubly regularized approach. Extensive Monte Carlo simulations indicate that our proposed procedure can result in better estimation and variable selection than existing methods when heteroscedasticity arises from the presence of predictors explaining error variances and outliers. Further, we demonstrate the presence of heteroscedasticity in and apply our method to an expression quantitative trait loci (eQTLs) study of 112 yeast segregants. The new procedure can automatically account for heteroscedasticity in identifying the eQTLs that are associated with gene expression variations and lead to smaller prediction errors. These results demonstrate the importance of considering heteroscedasticity in eQTL data analysis. PMID:22547833

Evidence of sex-bias in gene expression in the brain transcriptome of two populations of rainbow trout (Oncorhynchus mykiss) with divergent life histories.

PubMed

Hale, Matthew C; McKinney, Garrett J; Thrower, Frank P; Nichols, Krista M

2018-01-01

Sex-bias in gene expression is a mechanism that can generate phenotypic variance between the sexes, however, relatively little is known about how patterns of sex-bias vary during development, and how variable sex-bias is between different populations. To that end, we measured sex-bias in gene expression in the brain transcriptome of rainbow trout (Oncorhynchus mykiss) during the first two years of development. Our sampling included from the fry stage through to when O. mykiss either migrate to the ocean or remain resident and undergo sexual maturation. Samples came from two F1 lines: One from migratory steelhead trout and one from resident rainbow trout. All samples were reared in a common garden environment and RNA sequencing (RNA-seq) was used to estimate patterns of gene expression. A total of 1,716 (4.6% of total) genes showed evidence of sex-bias in gene expression in at least one time point. The majority (96.7%) of sex-biased genes were differentially expressed during the second year of development, indicating that patterns of sex-bias in expression are tied to key developmental events, such as migration and sexual maturation. Mapping of differentially expressed genes to the O. mykiss genome revealed that the X chromosome is enriched for female upregulated genes, and this may indicate a lack of dosage compensation in rainbow trout. There were many more sex-biased genes in the migratory line than the resident line suggesting differences in patterns of gene expression in the brain between populations subjected to different forces of selection. Overall, our results suggest that there is considerable variation in the extent and identity of genes exhibiting sex-bias during the first two years of life. These differentially expressed genes may be connected to developmental differences between the sexes, and/or between adopting a resident or migratory life history.

A structured sparse regression method for estimating isoform expression level from multi-sample RNA-seq data.

PubMed

Zhang, L; Liu, X J

2016-06-03

With the rapid development of next-generation high-throughput sequencing technology, RNA-seq has become a standard and important technique for transcriptome analysis. For multi-sample RNA-seq data, the existing expression estimation methods usually deal with each single-RNA-seq sample, and ignore that the read distributions are consistent across multiple samples. In the current study, we propose a structured sparse regression method, SSRSeq, to estimate isoform expression using multi-sample RNA-seq data. SSRSeq uses a non-parameter model to capture the general tendency of non-uniformity read distribution for all genes across multiple samples. Additionally, our method adds a structured sparse regularization, which not only incorporates the sparse specificity between a gene and its corresponding isoform expression levels, but also reduces the effects of noisy reads, especially for lowly expressed genes and isoforms. Four real datasets were used to evaluate our method on isoform expression estimation. Compared with other popular methods, SSRSeq reduced the variance between multiple samples, and produced more accurate isoform expression estimations, and thus more meaningful biological interpretations.

Impact of angiogenesis-related gene expression on the tracer kinetics of 18F-FDG in colorectal tumors.

PubMed

Strauss, Ludwig G; Koczan, Dirk; Klippel, Sven; Pan, Leyun; Cheng, Caixia; Willis, Stefan; Haberkorn, Uwe; Dimitrakopoulou-Strauss, Antonia

2008-08-01

18F-FDG kinetics are primarily dependent on the expression of genes associated with glucose transporters and hexokinases but may be modulated by other genes. The dependency of 18F-FDG kinetics on angiogenesis-related gene expression was evaluated in this study. Patients with primary colorectal tumors (n = 25) were examined with PET and 18F-FDG within 2 days before surgery. Tissue specimens were obtained from the tumor and the normal colon during surgery, and gene expression was assessed using gene arrays. Overall, 23 angiogenesis-related genes were identified with a tumor-to-normal ratio exceeding 1.50. Analysis revealed a significant correlation between k1 and vascular endothelial growth factor (VEGF-A, r = 0.51) and between fractal dimension and angiopoietin-2 (r = 0.48). k3 was negatively correlated with VEGF-B (r = -0.46), and a positive correlation was noted for angiopoietin-like 4 gene (r = 0.42). A multiple linear regression analysis was used for the PET parameters to predict the gene expression, and a correlation coefficient of r = 0.75 was obtained for VEGF-A and of r = 0.76 for the angiopoietin-2 expression. Thus, on the basis of these multiple correlation coefficients, angiogenesis-related gene expression contributes to about 50% of the variance of the 18F-FDG kinetic data. The global 18F-FDG uptake, as measured by the standardized uptake value and influx, was not significantly correlated with angiogenesis-associated genes. 18F-FDG kinetics are modulated by angiogenesis-related genes. The transport rate for 18F-FDG (k1) is higher in tumors with a higher expression of VEGF-A and angiopoietin-2. The regression functions for the PET parameters provide the possibility to predict the gene expression of VEGF-A and angiopoietin-2.

Neuron-Enriched Gene Expression Patterns are Regionally Anti-Correlated with Oligodendrocyte-Enriched Patterns in the Adult Mouse and Human Brain

PubMed Central

Tan, Powell Patrick Cheng; French, Leon; Pavlidis, Paul

2013-01-01

An important goal in neuroscience is to understand gene expression patterns in the brain. The recent availability of comprehensive and detailed expression atlases for mouse and human creates opportunities to discover global patterns and perform cross-species comparisons. Recently we reported that the major source of variation in gene transcript expression in the adult normal mouse brain can be parsimoniously explained as reflecting regional variation in glia to neuron ratios, and is correlated with degree of connectivity and location in the brain along the anterior-posterior axis. Here we extend this investigation to two gene expression assays of adult normal human brains that consisted of over 300 brain region samples, and perform comparative analyses of brain-wide expression patterns to the mouse. We performed principal components analysis (PCA) on the regional gene expression of the adult human brain to identify the expression pattern that has the largest variance. As in the mouse, we observed that the first principal component is composed of two anti-correlated patterns enriched in oligodendrocyte and neuron markers respectively. However, we also observed interesting discordant patterns between the two species. For example, a few mouse neuron markers show expression patterns that are more correlated with the human oligodendrocyte-enriched pattern and vice-versa. In conclusion, our work provides insights into human brain function and evolution by probing global relationships between regional cell type marker expression patterns in the human and mouse brain. PMID:23440889

Neuron-Enriched Gene Expression Patterns are Regionally Anti-Correlated with Oligodendrocyte-Enriched Patterns in the Adult Mouse and Human Brain.

PubMed

Tan, Powell Patrick Cheng; French, Leon; Pavlidis, Paul

2013-01-01

An important goal in neuroscience is to understand gene expression patterns in the brain. The recent availability of comprehensive and detailed expression atlases for mouse and human creates opportunities to discover global patterns and perform cross-species comparisons. Recently we reported that the major source of variation in gene transcript expression in the adult normal mouse brain can be parsimoniously explained as reflecting regional variation in glia to neuron ratios, and is correlated with degree of connectivity and location in the brain along the anterior-posterior axis. Here we extend this investigation to two gene expression assays of adult normal human brains that consisted of over 300 brain region samples, and perform comparative analyses of brain-wide expression patterns to the mouse. We performed principal components analysis (PCA) on the regional gene expression of the adult human brain to identify the expression pattern that has the largest variance. As in the mouse, we observed that the first principal component is composed of two anti-correlated patterns enriched in oligodendrocyte and neuron markers respectively. However, we also observed interesting discordant patterns between the two species. For example, a few mouse neuron markers show expression patterns that are more correlated with the human oligodendrocyte-enriched pattern and vice-versa. In conclusion, our work provides insights into human brain function and evolution by probing global relationships between regional cell type marker expression patterns in the human and mouse brain.

Partial least squares based identification of Duchenne muscular dystrophy specific genes.

PubMed

An, Hui-bo; Zheng, Hua-cheng; Zhang, Li; Ma, Lin; Liu, Zheng-yan

2013-11-01

Large-scale parallel gene expression analysis has provided a greater ease for investigating the underlying mechanisms of Duchenne muscular dystrophy (DMD). Previous studies typically implemented variance/regression analysis, which would be fundamentally flawed when unaccounted sources of variability in the arrays existed. Here we aim to identify genes that contribute to the pathology of DMD using partial least squares (PLS) based analysis. We carried out PLS-based analysis with two datasets downloaded from the Gene Expression Omnibus (GEO) database to identify genes contributing to the pathology of DMD. Except for the genes related to inflammation, muscle regeneration and extracellular matrix (ECM) modeling, we found some genes with high fold change, which have not been identified by previous studies, such as SRPX, GPNMB, SAT1, and LYZ. In addition, downregulation of the fatty acid metabolism pathway was found, which may be related to the progressive muscle wasting process. Our results provide a better understanding for the downstream mechanisms of DMD.

Overcoming confounded controls in the analysis of gene expression data from microarray experiments.

PubMed

Bhattacharya, Soumyaroop; Long, Dang; Lyons-Weiler, James

2003-01-01

A potential limitation of data from microarray experiments exists when improper control samples are used. In cancer research, comparisons of tumour expression profiles to those from normal samples is challenging due to tissue heterogeneity (mixed cell populations). A specific example exists in a published colon cancer dataset, in which tissue heterogeneity was reported among the normal samples. In this paper, we show how to overcome or avoid the problem of using normal samples that do not derive from the same tissue of origin as the tumour. We advocate an exploratory unsupervised bootstrap analysis that can reveal unexpected and undesired, but strongly supported, clusters of samples that reflect tissue differences instead of tumour versus normal differences. All of the algorithms used in the analysis, including the maximum difference subset algorithm, unsupervised bootstrap analysis, pooled variance t-test for finding differentially expressed genes and the jackknife to reduce false positives, are incorporated into our online Gene Expression Data Analyzer ( http:// bioinformatics.upmc.edu/GE2/GEDA.html ).

The allostatic impact of chronic ethanol on gene expression: A genetic analysis of chronic intermittent ethanol treatment in the BXD cohort

PubMed Central

van der Vaart, Andrew D.; Wolstenholme, Jennifer T.; Smith, Maren L.; Harris, Guy M.; Lopez, Marcelo F.; Wolen, Aaron R.; Becker, Howard C.; Williams, Robert W.; Miles, Michael F.

2016-01-01

The transition from acute to chronic ethanol exposure leads to lasting behavioral and physiological changes such as increased consumption, dependence, and withdrawal. Changes in brain gene expression are hypothesized to underlie these adaptive responses to ethanol. Previous studies on acute ethanol identified genetic variation in brain gene expression networks and behavioral responses to ethanol across the BXD panel of recombinant inbred mice. In this work, we have performed the first joint genetic and genomic analysis of transcriptome shifts in response to chronic intermittent ethanol (CIE) by vapor chamber exposure in a BXD cohort. CIE treatment is known to produce significant and sustained changes in ethanol consumption with repeated cycles of ethanol vapor. Using Affymetrix microarray analysis of prefrontal cortex (PFC) and nucleus accumbens (NAC) RNA, we compared CIE expression responses to those seen following acute ethanol treatment, and to voluntary ethanol consumption. Gene expression changes in PFC and NAC after CIE overlapped significantly across brain regions and with previously published expression following acute ethanol. Genes highly modulated by CIE were enriched for specific biological processes including synaptic transmission, neuron ensheathment, intracellular signaling, and neuronal projection development. Expression quantitative trait locus (eQTL) analyses identified genomic loci associated with ethanol-induced transcriptional changes with largely distinct loci identified between brain regions. Correlating CIE-regulated genes to ethanol consumption data identified specific genes highly associated with variation in the increase in drinking seen with repeated cycles of CIE. In particular, multiple myelin-related genes were identified. Furthermore, genetic variance in or near dynamin3 (Dnm3) on Chr1 at ~164 Mb may have a major regulatory role in CIE-responsive gene expression. Dnm3 expression correlates significantly with ethanol consumption, is contained in a highly ranked functional group of CIE-regulated genes in the NAC, and has a cis-eQTL within a genomic region linked with multiple CIE-responsive genes. PMID:27838001

Clustering of time-course gene expression profiles using normal mixture models with autoregressive random effects

PubMed Central

2012-01-01

Background Time-course gene expression data such as yeast cell cycle data may be periodically expressed. To cluster such data, currently used Fourier series approximations of periodic gene expressions have been found not to be sufficiently adequate to model the complexity of the time-course data, partly due to their ignoring the dependence between the expression measurements over time and the correlation among gene expression profiles. We further investigate the advantages and limitations of available models in the literature and propose a new mixture model with autoregressive random effects of the first order for the clustering of time-course gene-expression profiles. Some simulations and real examples are given to demonstrate the usefulness of the proposed models. Results We illustrate the applicability of our new model using synthetic and real time-course datasets. We show that our model outperforms existing models to provide more reliable and robust clustering of time-course data. Our model provides superior results when genetic profiles are correlated. It also gives comparable results when the correlation between the gene profiles is weak. In the applications to real time-course data, relevant clusters of coregulated genes are obtained, which are supported by gene-function annotation databases. Conclusions Our new model under our extension of the EMMIX-WIRE procedure is more reliable and robust for clustering time-course data because it adopts a random effects model that allows for the correlation among observations at different time points. It postulates gene-specific random effects with an autocorrelation variance structure that models coregulation within the clusters. The developed R package is flexible in its specification of the random effects through user-input parameters that enables improved modelling and consequent clustering of time-course data. PMID:23151154

Correlating Gene-specific DNA Methylation Changes with Expression and Transcriptional Activity of Astrocytic KCNJ10 (Kir4.1)

PubMed Central

Nwaobi, Sinifunanya E.; Olsen, Michelle L.

2015-01-01

DNA methylation serves to regulate gene expression through the covalent attachment of a methyl group onto the C5 position of a cytosine in a cytosine-guanine dinucleotide. While DNA methylation provides long-lasting and stable changes in gene expression, patterns and levels of DNA methylation are also subject to change based on a variety of signals and stimuli. As such, DNA methylation functions as a powerful and dynamic regulator of gene expression. The study of neuroepigenetics has revealed a variety of physiological and pathological states that are associated with both global and gene-specific changes in DNA methylation. Specifically, striking correlations between changes in gene expression and DNA methylation exist in neuropsychiatric and neurodegenerative disorders, during synaptic plasticity, and following CNS injury. However, as the field of neuroepigenetics continues to expand its understanding of the role of DNA methylation in CNS physiology, delineating causal relationships in regards to changes in gene expression and DNA methylation are essential. Moreover, in regards to the larger field of neuroscience, the presence of vast region and cell-specific differences requires techniques that address these variances when studying the transcriptome, proteome, and epigenome. Here we describe FACS sorting of cortical astrocytes that allows for subsequent examination of a both RNA transcription and DNA methylation. Furthermore, we detail a technique to examine DNA methylation, methylation sensitive high resolution melt analysis (MS-HRMA) as well as a luciferase promoter assay. Through the use of these combined techniques one is able to not only explore correlative changes between DNA methylation and gene expression, but also directly assess if changes in the DNA methylation status of a given gene region are sufficient to affect transcriptional activity. PMID:26436772

Analysis of baseline gene expression levels from ...

EPA Pesticide Factsheets

The use of gene expression profiling to predict chemical mode of action would be enhanced by better characterization of variance due to individual, environmental, and technical factors. Meta-analysis of microarray data from untreated or vehicle-treated animals within the control arm of toxicogenomics studies has yielded useful information on baseline fluctuations in gene expression. A dataset of control animal microarray expression data was assembled by a working group of the Health and Environmental Sciences Institute's Technical Committee on the Application of Genomics in Mechanism Based Risk Assessment in order to provide a public resource for assessments of variability in baseline gene expression. Data from over 500 Affymetrix microarrays from control rat liver and kidney were collected from 16 different institutions. Thirty-five biological and technical factors were obtained for each animal, describing a wide range of study characteristics, and a subset were evaluated in detail for their contribution to total variability using multivariate statistical and graphical techniques. The study factors that emerged as key sources of variability included gender, organ section, strain, and fasting state. These and other study factors were identified as key descriptors that should be included in the minimal information about a toxicogenomics study needed for interpretation of results by an independent source. Genes that are the most and least variable, gender-selectiv

CDK5RAP2 gene and tau pathophysiology in late-onset sporadic Alzheimer's disease.

PubMed

Miron, Justin; Picard, Cynthia; Nilsson, Nathalie; Frappier, Josée; Dea, Doris; Théroux, Louise; Poirier, Judes

2018-06-01

Because currently known Alzheimer's disease (AD) single-nucleotide polymorphisms only account for a small fraction of the genetic variance in this disease, there is a need to identify new variants associated with AD. Our team performed a genome-wide association study in the Quebec Founder Population isolate to identify novel protective or risk genetic factors for late-onset sporadic AD and examined the impact of these variants on gene expression and AD pathology. The rs10984186 variant is associated with an increased risk of developing AD and with a higher CDK5RAP2 mRNA prevalence in the hippocampus. On the other hand, the rs4837766 variant, which is among the best cis-expression quantitative trait loci in the CDK5RAP2 gene, is associated with lower mild cognitive impairment/AD risk and conversion rate. The rs10984186 risk and rs4837766 protective polymorphic variants of the CDK5RAP2 gene might act as potent genetic modifiers for AD risk and/or conversion by modulating the expression of this gene. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

Linkage disequilibrium and association mapping.

PubMed

Weir, B S

2008-01-01

Linkage disequilibrium refers to the association between alleles at different loci. The standard definition applies to two alleles in the same gamete, and it can be regarded as the covariance of indicator variables for the states of those two alleles. The corresponding correlation coefficient rho is the parameter that arises naturally in discussions of tests of association between markers and genetic diseases. A general treatment of association tests makes use of the additive and nonadditive components of variance for the disease gene. In almost all expressions that describe the behavior of association tests, additive variance components are modified by the squared correlation coefficient rho2 and the nonadditive variance components by rho4, suggesting that nonadditive components have less influence than additive components on association tests.

Silencing of Essential Genes within a Highly Coordinated Operon in Escherichia coli.

PubMed

Goh, Shan; Hohmeier, Angela; Stone, Timothy C; Offord, Victoria; Sarabia, Francisco; Garcia-Ruiz, Cristina; Good, Liam

2015-08-15

Essential bacterial genes located within operons are particularly challenging to study independently because of coordinated gene expression and the nonviability of knockout mutants. Essentiality scores for many operon genes remain uncertain. Antisense RNA (asRNA) silencing or in-frame gene disruption of genes may help establish essentiality but can lead to polar effects on genes downstream or upstream of the target gene. Here, the Escherichia coli ribF-ileS-lspA-fkpB-ispH operon was used to evaluate the possibility of independently studying an essential gene using expressed asRNA and target gene overexpression to deregulate coupled expression. The gene requirement for growth in conditional silencing strains was determined by the relationship of target mRNA reduction with growth inhibition as the minimum transcript level required for 50% growth (MTL50). Mupirocin and globomycin, the protein inhibitors of IleS and LspA, respectively, were used in sensitization assays of strains containing both asRNA-expressing and open reading frame-expressing plasmids to examine deregulation of the overlapping ileS-lspA genes. We found upstream and downstream polar silencing effects when either ileS or lspA was silenced, indicating coupled expression. Weighted MTL50 values (means and standard deviations) of ribF, ileS, and lspA were 0.65 ± 0.18, 0.64 ± 0.06, and 0.76 ± 0.10, respectively. However, they were not significantly different (P = 0.71 by weighted one-way analysis of variance). The gene requirement for ispH could not be determined due to insufficient growth reduction. Mupirocin and globomycin sensitization experiments indicated that ileS-lspA expression could not be decoupled. The results highlight the inherent challenges associated with genetic analyses of operons; however, coupling of essential genes may provide opportunities to improve RNA-silencing antimicrobials. Copyright © 2015, American Society for Microbiology. All Rights Reserved.

Silencing of Essential Genes within a Highly Coordinated Operon in Escherichia coli

PubMed Central

Hohmeier, Angela; Stone, Timothy C.; Offord, Victoria; Sarabia, Francisco; Garcia-Ruiz, Cristina; Good, Liam

2015-01-01

Essential bacterial genes located within operons are particularly challenging to study independently because of coordinated gene expression and the nonviability of knockout mutants. Essentiality scores for many operon genes remain uncertain. Antisense RNA (asRNA) silencing or in-frame gene disruption of genes may help establish essentiality but can lead to polar effects on genes downstream or upstream of the target gene. Here, the Escherichia coli ribF-ileS-lspA-fkpB-ispH operon was used to evaluate the possibility of independently studying an essential gene using expressed asRNA and target gene overexpression to deregulate coupled expression. The gene requirement for growth in conditional silencing strains was determined by the relationship of target mRNA reduction with growth inhibition as the minimum transcript level required for 50% growth (MTL50). Mupirocin and globomycin, the protein inhibitors of IleS and LspA, respectively, were used in sensitization assays of strains containing both asRNA-expressing and open reading frame-expressing plasmids to examine deregulation of the overlapping ileS-lspA genes. We found upstream and downstream polar silencing effects when either ileS or lspA was silenced, indicating coupled expression. Weighted MTL50 values (means and standard deviations) of ribF, ileS, and lspA were 0.65 ± 0.18, 0.64 ± 0.06, and 0.76 ± 0.10, respectively. However, they were not significantly different (P = 0.71 by weighted one-way analysis of variance). The gene requirement for ispH could not be determined due to insufficient growth reduction. Mupirocin and globomycin sensitization experiments indicated that ileS-lspA expression could not be decoupled. The results highlight the inherent challenges associated with genetic analyses of operons; however, coupling of essential genes may provide opportunities to improve RNA-silencing antimicrobials. PMID:26070674

Validation of Endogenous Internal Real-Time PCR Controls in Renal Tissues

PubMed Central

Cui, Xiangqin; Zhou, Juling; Qiu, Jing; Johnson, Martin R.; Mrug, Michal

2009-01-01

Background Endogenous internal controls (‘reference’ or ‘housekeeping’ genes) are widely used in real-time PCR (RT-PCR) analyses. Their use relies on the premise of consistently stable expression across studied experimental conditions. Unfortunately, none of these controls fulfills this premise across a wide range of experimental conditions; consequently, none of them can be recommended for universal use. Methods To determine which endogenous RT-PCR controls are suitable for analyses of renal tissues altered by kidney disease, we studied the expression of 16 commonly used ‘reference genes’ in 7 mildly and 7 severely affected whole kidney tissues from a well-characterized cystic kidney disease model. Expression levels of these 16 genes, determined by TaqMan® RT-PCR analyses and Affymetrix GeneChip® arrays, were normalized and tested for overall variance and equivalence of the means. Results Both statistical approaches and both TaqMan- and GeneChip-based methods converged on 3 out of the 4 top-ranked genes (Ppia, Gapdh and Pgk1) that had the most constant expression levels across the studied phenotypes. Conclusion A combination of the top-ranked genes will provide a suitable endogenous internal control for similar studies of kidney tissues across a wide range of disease severity. PMID:19729889

In Silico Analysis of Expression Data for Identification of Genes Involved in Spatial Accumulation of Calcium in Developing Seeds of Rice

PubMed Central

Goel, Anshita; Gaur, Vikram S.; Arora, Sandeep; Gupta, Sanjay

2012-01-01

Abstract The calcium (Ca2+) transporters, like Ca2+ channels, Ca2+ ATPases, and Ca2+ exchangers, are instrumental for signaling and transport. However, the mechanism by which they orchestrate the accumulation of Ca2+ in grain filling has not yet been investigated. Hence the present study was designed to identify the potential calcium transporter genes that may be responsible for the spatial accumulation of calcium during grain filling. In silico expression analyses were performed to identify Ca2+ transporters that predominantly express during the different developmental stages of Oryza sativa. A total of 13 unique calcium transporters (7 from massively parallel signature sequencing [MPSS] data analysis, and 9 from microarray analysis) were identified. Analysis of variance (ANOVA) revealed differential expression of the transporters across tissues, and principal component analysis (PCA) exhibited their seed-specific distinctive expression profile. Interestingly, Ca2+ exchanger genes are highly expressed in the initial stages, whereas some Ca2+ ATPase genes are highly expressed throughout seed development. Furthermore, analysis of the cis-elements located in the promoter region of the subset of 13 genes suggested that Dof proteins play essential roles in regulating the expression of Ca2+ transporter genes during rice seed development. Based on these results, we developed a hypothetical model explaining the transport and tissue specific distribution of calcium in developing cereal seeds. The model may be extrapolated to understand the mechanism behind the exceptionally high level of calcium accumulation seen in grains like finger millet. PMID:22734689

Uncovering Hidden Layers of Cell Cycle Regulation through Integrative Multi-omic Analysis

PubMed Central

Aviner, Ranen; Shenoy, Anjana; Elroy-Stein, Orna; Geiger, Tamar

2015-01-01

Studying the complex relationship between transcription, translation and protein degradation is essential to our understanding of biological processes in health and disease. The limited correlations observed between mRNA and protein abundance suggest pervasive regulation of post-transcriptional steps and support the importance of profiling mRNA levels in parallel to protein synthesis and degradation rates. In this work, we applied an integrative multi-omic approach to study gene expression along the mammalian cell cycle through side-by-side analysis of mRNA, translation and protein levels. Our analysis sheds new light on the significant contribution of both protein synthesis and degradation to the variance in protein expression. Furthermore, we find that translation regulation plays an important role at S-phase, while progression through mitosis is predominantly controlled by changes in either mRNA levels or protein stability. Specific molecular functions are found to be co-regulated and share similar patterns of mRNA, translation and protein expression along the cell cycle. Notably, these include genes and entire pathways not previously implicated in cell cycle progression, demonstrating the potential of this approach to identify novel regulatory mechanisms beyond those revealed by traditional expression profiling. Through this three-level analysis, we characterize different mechanisms of gene expression, discover new cycling gene products and highlight the importance and utility of combining datasets generated using different techniques that monitor distinct steps of gene expression. PMID:26439921

Biological annotation of genetic loci associated with intelligence in a meta-analysis of 87,740 individuals.

PubMed

Coleman, Jonathan R I; Bryois, Julien; Gaspar, Héléna A; Jansen, Philip R; Savage, Jeanne E; Skene, Nathan; Plomin, Robert; Muñoz-Manchado, Ana B; Linnarsson, Sten; Crawford, Greg; Hjerling-Leffler, Jens; Sullivan, Patrick F; Posthuma, Danielle; Breen, Gerome

2018-03-08

Variance in IQ is associated with a wide range of health outcomes, and 1% of the population are affected by intellectual disability. Despite a century of research, the fundamental neural underpinnings of intelligence remain unclear. We integrate results from genome-wide association studies (GWAS) of intelligence with brain tissue and single cell gene expression data to identify tissues and cell types associated with intelligence. GWAS data for IQ (N = 78,308) were meta-analyzed with a study comparing 1247 individuals with mean IQ ~170 to 8185 controls. Genes associated with intelligence implicate pyramidal neurons of the somatosensory cortex and CA1 region of the hippocampus, and midbrain embryonic GABAergic neurons. Tissue-specific analyses find the most significant enrichment for frontal cortex brain expressed genes. These results suggest specific neuronal cell types and genes may be involved in intelligence and provide new hypotheses for neuroscience experiments using model systems.

CXCR4 expression is associated with time-course permanent and temporary myocardial infarction in rats.

PubMed

Kiani, Ali Asghar; Babaei, Fereshteh; Sedighi, Mehrnoosh; Soleimani, Azam; Ahmadi, Kolsum; Shahrokhi, Somayeh; Anbari, Khatereh; Nazari, Afshin

2017-06-01

Experimental myocardial infarction triggers secretion of Stromal cell-derived factor1 and lead to increase in the expression of its receptor "CXCR4" on the surface of various cells. The aim of this study was to evaluate the expression pattern of CXCR4 in peripheral blood cells following time-course permanent and temporary ischemia in rats. Fourteen male Wistar rats were divided into two groups of seven and were placed under permanent and transient ischemia. Peripheral blood mononuclear cells were isolated at different time points, RNAs extracted and applied to qRT-PCR analysis of the CXCR4 gene. Based on repeated measures analysis of variance, the differences in the expression levels of the gene in each of the groups were statistically significant over time (the effect of time) ( P <0.001). Additionally, the difference in gene expression between the two groups was statistically significant (the effect of group), such that at all times, the expression levels of the gene were significantly higher in the permanent ischemia than in the transient ischemia group ( P <0.001). Moreover, the interactive effect of time-group on gene expression was statistically significant ( P <0.001). CXCR4 is modulated in an induced ischemia context implying a possible association with myocardial infarction. Checking of CXCR4 expression in the ischemic changes shows that damage to the heart tissue trigger the secretion of inflammatory chemokine SDF, Followed by it CXCR4 expression in blood cells. These observations suggest that changes in the expression of CXCR4 may be considered a valuable marker for monitoring myocardial infarction.

No control genes required: Bayesian analysis of qRT-PCR data.

PubMed

Matz, Mikhail V; Wright, Rachel M; Scott, James G

2013-01-01

Model-based analysis of data from quantitative reverse-transcription PCR (qRT-PCR) is potentially more powerful and versatile than traditional methods. Yet existing model-based approaches cannot properly deal with the higher sampling variances associated with low-abundant targets, nor do they provide a natural way to incorporate assumptions about the stability of control genes directly into the model-fitting process. In our method, raw qPCR data are represented as molecule counts, and described using generalized linear mixed models under Poisson-lognormal error. A Markov Chain Monte Carlo (MCMC) algorithm is used to sample from the joint posterior distribution over all model parameters, thereby estimating the effects of all experimental factors on the expression of every gene. The Poisson-based model allows for the correct specification of the mean-variance relationship of the PCR amplification process, and can also glean information from instances of no amplification (zero counts). Our method is very flexible with respect to control genes: any prior knowledge about the expected degree of their stability can be directly incorporated into the model. Yet the method provides sensible answers without such assumptions, or even in the complete absence of control genes. We also present a natural Bayesian analogue of the "classic" analysis, which uses standard data pre-processing steps (logarithmic transformation and multi-gene normalization) but estimates all gene expression changes jointly within a single model. The new methods are considerably more flexible and powerful than the standard delta-delta Ct analysis based on pairwise t-tests. Our methodology expands the applicability of the relative-quantification analysis protocol all the way to the lowest-abundance targets, and provides a novel opportunity to analyze qRT-PCR data without making any assumptions concerning target stability. These procedures have been implemented as the MCMC.qpcr package in R.

Exposure to air pollution interacts with obesogenic nutrition to induce tissue-specific response patterns.

PubMed

Pardo, Michal; Kuperman, Yael; Levin, Liron; Rudich, Assaf; Haim, Yulia; Schauer, James J; Chen, Alon; Rudich, Yinon

2018-04-20

Obesity and exposure to particular matter (PM) have become two leading global threats to public health. However, the exact mechanisms and tissue-specificity of their health effects are largely unknown. Here we investigate whether a metabolic challenge (early nutritional obesity) synergistically interacts with an environmental challenge (PM exposure) to alter genes representing key response pathways, in a tissue-specific manner. Mice subjected to 7 weeks obesogenic nutrition were exposed every other day during the final week and a half to aqueous extracts of PM collected in the city of London (UK). The expression of 61 selected genes representing key response pathways were investigated in lung, liver, white and brown adipose tissues. Principal component analysis (PCA) revealed distinct patterns of expression changes between the 4 tissues, particularly in the lungs and the liver. Surprisingly, the lung responded to the nutrition challenge. The response of these organs to the PM challenge displayed opposite patterns for some key genes, in particular, those related to the Nrf2 pathway. While the contribution to the variance in gene expression changes in mice exposed to the combined challenge were largely similar among the tissues in PCA1, PCA2 exhibited predominant contribution of inflammatory and oxidative stress responses to the variance in the lungs, and a greater contribution of autophagy genes and MAP kinases in adipose tissues. Possible involvement of alterations in DNA methylation was demonstrated by cell-type-specific responses to a methylation inhibitor. Correspondingly, the DNA methyltransferase Dnmt3a2 increased in the lungs but decreased in the liver, demonstrating potential tissue-differential synergism between nutritional and PM exposure. The results suggest that urban PM, containing dissolved metals, interacts with obesogenic nutrition to regulate diverse response pathways including inflammation and oxidative stress, in a tissue-specific manner. Tissue-differential effects on DNA methylation may underlie tissue-specific responses to key stress-response genes such as catalase and Nrf2. Copyright © 2018 Elsevier Ltd. All rights reserved.

Combining mouse mammary gland gene expression and comparative mapping for the identification of candidate genes for QTL of milk production traits in cattle

PubMed Central

Ron, Micha; Israeli, Galit; Seroussi, Eyal; Weller, Joel I; Gregg, Jeffrey P; Shani, Moshe; Medrano, Juan F

2007-01-01

Background Many studies have found segregating quantitative trait loci (QTL) for milk production traits in different dairy cattle populations. However, even for relatively large effects with a saturated marker map the confidence interval for QTL location by linkage analysis spans tens of map units, or hundreds of genes. Combining mapping and arraying has been suggested as an approach to identify candidate genes. Thus, gene expression analysis in the mammary gland of genes positioned in the confidence interval of the QTL can bridge the gap between fine mapping and quantitative trait nucleotide (QTN) determination. Results We hybridized Affymetrix microarray (MG-U74v2), containing 12,488 murine probes, with RNA derived from mammary gland of virgin, pregnant, lactating and involuting C57BL/6J mice in a total of nine biological replicates. We combined microarray data from two additional studies that used the same design in mice with a total of 75 biological replicates. The same filtering and normalization was applied to each microarray data using GeneSpring software. Analysis of variance identified 249 differentially expressed probe sets common to the three experiments along the four developmental stages of puberty, pregnancy, lactation and involution. 212 genes were assigned to their bovine map positions through comparative mapping, and thus form a list of candidate genes for previously identified QTLs for milk production traits. A total of 82 of the genes showed mammary gland-specific expression with at least 3-fold expression over the median representing all tissues tested in GeneAtlas. Conclusion This work presents a web tool for candidate genes for QTL (cgQTL) that allows navigation between the map of bovine milk production QTL, potential candidate genes and their level of expression in mammary gland arrays and in GeneAtlas. Three out of four confirmed genes that affect QTL in livestock (ABCG2, DGAT1, GDF8, IGF2) were over expressed in the target organ. Thus, cgQTL can be used to determine priority of candidate genes for QTN analysis based on differential expression in the target organ. PMID:17584498

Heritability and molecular-genetic basis of the P3 event-related brain potential: A genome-wide association study

PubMed Central

MALONE, STEPHEN M.; VAIDYANATHAN, UMA; BASU, SAONLI; MILLER, MICHAEL B.; MCGUE, MATT; IACONO, WILLIAM G.

2014-01-01

P3 amplitude is a candidate endophenotype for disinhibitory psychopathology, psychosis, and other disorders. The present study is a comprehensive analysis of the behavioral- and molecular-genetic basis of P3 amplitude and a P3 genetic factor score in a large community sample (N = 4,211) of adolescent twins and their parents, genotyped for 527,829 single nucleotide polymorphisms (SNPs). Biometric models indicated that as much as 65% of the variance in each measure was due to additive genes. All SNPs in aggregate accounted for approximately 40% to 50% of the heritable variance. However, analyses of individual SNPs did not yield any significant associations. Analyses of individual genes did not confirm previous associations between P3 amplitude and candidate genes but did yield a novel association with myelin expression factor 2 (MYEF2). Main effects of individual variants may be too small to be detected by GWAS without larger samples. PMID:25387705

Exploring valid internal-control genes in Porphyra yezoensis (Bangiaceae) during stress response conditions

NASA Astrophysics Data System (ADS)

Wang, Wenlei; Wu, Xiaojie; Wang, Chao; Jia, Zhaojun; He, Linwen; Wei, Yifan; Niu, Jianfeng; Wang, Guangce

2014-07-01

To screen the stable expression genes related to the stress (strong light, dehydration and temperature shock) we applied Absolute real-time PCR technology to determine the transcription numbers of the selected test genes in P orphyra yezoensis, which has been regarded as a potential model species responding the stress conditions in the intertidal. Absolute real-time PCR technology was applied to determine the transcription numbers of the selected test genes in P orphyra yezoensis, which has been regarded as a potential model species in stress responding. According to the results of photosynthesis parameters, we observed that Y(II) and F v/ F m were significantly affected when stress was imposed on the thalli of P orphyra yezoensis, but underwent almost completely recovered under normal conditions, which were collected for the following experiments. Then three samples, which were treated with different grade stresses combined with salinity, irradiation and temperature, were collected. The transcription numbers of seven constitutive expression genes in above samples were determined after RNA extraction and cDNA synthesis. Finally, a general insight into the selection of internal control genes during stress response was obtained. We found that there were no obvious effects in terms of salinity stress (at salinity 90) on transcription of most genes used in the study. The 18S ribosomal RNA gene had the highest expression level, varying remarkably among different tested groups. RPS8 expression showed a high irregular variance between samples. GAPDH presented comparatively stable expression and could thus be selected as the internal control. EF-1α showed stable expression during the series of multiple-stress tests. Our research provided available references for the selection of internal control genes for transcripts determination of P. yezoensis.

Optimal consistency in microRNA expression analysis using reference-gene-based normalization.

PubMed

Wang, Xi; Gardiner, Erin J; Cairns, Murray J

2015-05-01

Normalization of high-throughput molecular expression profiles secures differential expression analysis between samples of different phenotypes or biological conditions, and facilitates comparison between experimental batches. While the same general principles apply to microRNA (miRNA) normalization, there is mounting evidence that global shifts in their expression patterns occur in specific circumstances, which pose a challenge for normalizing miRNA expression data. As an alternative to global normalization, which has the propensity to flatten large trends, normalization against constitutively expressed reference genes presents an advantage through their relative independence. Here we investigated the performance of reference-gene-based (RGB) normalization for differential miRNA expression analysis of microarray expression data, and compared the results with other normalization methods, including: quantile, variance stabilization, robust spline, simple scaling, rank invariant, and Loess regression. The comparative analyses were executed using miRNA expression in tissue samples derived from subjects with schizophrenia and non-psychiatric controls. We proposed a consistency criterion for evaluating methods by examining the overlapping of differentially expressed miRNAs detected using different partitions of the whole data. Based on this criterion, we found that RGB normalization generally outperformed global normalization methods. Thus we recommend the application of RGB normalization for miRNA expression data sets, and believe that this will yield a more consistent and useful readout of differentially expressed miRNAs, particularly in biological conditions characterized by large shifts in miRNA expression.

The Role of Genome Accessibility in Transcription Factor Binding in Bacteria.

PubMed

Gomes, Antonio L C; Wang, Harris H

2016-04-01

ChIP-seq enables genome-scale identification of regulatory regions that govern gene expression. However, the biological insights generated from ChIP-seq analysis have been limited to predictions of binding sites and cooperative interactions. Furthermore, ChIP-seq data often poorly correlate with in vitro measurements or predicted motifs, highlighting that binding affinity alone is insufficient to explain transcription factor (TF)-binding in vivo. One possibility is that binding sites are not equally accessible across the genome. A more comprehensive biophysical representation of TF-binding is required to improve our ability to understand, predict, and alter gene expression. Here, we show that genome accessibility is a key parameter that impacts TF-binding in bacteria. We developed a thermodynamic model that parameterizes ChIP-seq coverage in terms of genome accessibility and binding affinity. The role of genome accessibility is validated using a large-scale ChIP-seq dataset of the M. tuberculosis regulatory network. We find that accounting for genome accessibility led to a model that explains 63% of the ChIP-seq profile variance, while a model based in motif score alone explains only 35% of the variance. Moreover, our framework enables de novo ChIP-seq peak prediction and is useful for inferring TF-binding peaks in new experimental conditions by reducing the need for additional experiments. We observe that the genome is more accessible in intergenic regions, and that increased accessibility is positively correlated with gene expression and anti-correlated with distance to the origin of replication. Our biophysically motivated model provides a more comprehensive description of TF-binding in vivo from first principles towards a better representation of gene regulation in silico, with promising applications in systems biology.

Orthogonal control of expression mean and variance by epigenetic features at different genomic loci

DOE PAGES

Dey, Siddharth S.; Foley, Jonathan E.; Limsirichai, Prajit; ...

2015-05-05

While gene expression noise has been shown to drive dramatic phenotypic variations, the molecular basis for this variability in mammalian systems is not well understood. Gene expression has been shown to be regulated by promoter architecture and the associated chromatin environment. However, the exact contribution of these two factors in regulating expression noise has not been explored. Using a dual-reporter lentiviral model system, we deconvolved the influence of the promoter sequence to systematically study the contribution of the chromatin environment at different genomic locations in regulating expression noise. By integrating a large-scale analysis to quantify mRNA levels by smFISH andmore » protein levels by flow cytometry in single cells, we found that mean expression and noise are uncorrelated across genomic locations. Furthermore, we showed that this independence could be explained by the orthogonal control of mean expression by the transcript burst size and noise by the burst frequency. Finally, we showed that genomic locations displaying higher expression noise are associated with more repressed chromatin, thereby indicating the contribution of the chromatin environment in regulating expression noise.« less

Identification of Putative Genes Involved in Limonoids Biosynthesis in Citrus by Comparative Transcriptomic Analysis

PubMed Central

Wang, Fusheng; Wang, Mei; Liu, Xiaona; Xu, Yuanyuan; Zhu, Shiping; Shen, Wanxia; Zhao, Xiaochun

2017-01-01

Limonoids produced by citrus are a group of highly bioactive secondary metabolites which provide health benefits for humans. Currently there is a lack of information derived from research on the genetic mechanisms controlling the biosynthesis of limonoids, which has limited the improvement of citrus for high production of limonoids. In this study, the transcriptome sequences of leaves, phloems and seeds of pummelo (Citrus grandis (L.) Osbeck) at different development stages with variances in limonoids contents were used for digital gene expression profiling analysis in order to identify the genes corresponding to the biosynthesis of limonoids. Pair-wise comparison of transcriptional profiles between different tissues identified 924 differentially expressed genes commonly shared between them. Expression pattern analysis suggested that 382 genes from three conjunctive groups of K-means clustering could be possibly related to the biosynthesis of limonoids. Correlation analysis with the samples from different genotypes, and different developing tissues of the citrus revealed that the expression of 15 candidate genes were highly correlated with the contents of limonoids. Among them, the cytochrome P450s (CYP450s) and transcriptional factor MYB demonstrated significantly high correlation coefficients, which indicated the importance of those genes on the biosynthesis of limonoids. CiOSC gene encoding the critical enzyme oxidosqualene cyclase (OSC) for biosynthesis of the precursor of triterpene scaffolds was found positively corresponding to the accumulation of limonoids during the development of seeds. Suppressing the expression of CiOSC with VIGS (Virus-induced gene silencing) demonstrated that the level of gene silencing was significantly correlated to the reduction of limonoids contents. The results indicated that the CiOSC gene plays a pivotal role in biosynthesis of limonoids. PMID:28553308

Expression profiling of cassava storage roots reveals an active process of glycolysis/gluconeogenesis.

PubMed

Yang, Jun; An, Dong; Zhang, Peng

2011-03-01

Mechanisms related to the development of cassava storage roots and starch accumulation remain largely unknown. To evaluate genome-wide expression patterns during tuberization, a 60 mer oligonucleotide microarray representing 20 840 cassava genes was designed to identify differentially expressed transcripts in fibrous roots, developing storage roots and mature storage roots. Using a random variance model and the traditional twofold change method for statistical analysis, 912 and 3 386 upregulated and downregulated genes related to the three developmental phases were identified. Among 25 significantly changed pathways identified, glycolysis/gluconeogenesis was the most evident one. Rate-limiting enzymes were identified from each individual pathway, for example, enolase, L-lactate dehydrogenase and aldehyde dehydrogenase for glycolysis/gluconeogenesis, and ADP-glucose pyrophosphorylase, starch branching enzyme and glucan phosphorylase for sucrose and starch metabolism. This study revealed that dynamic changes in at least 16% of the total transcripts, including transcription factors, oxidoreductases/transferases/hydrolases, hormone-related genes, and effectors of homeostasis. The reliability of these differentially expressed genes was verified by quantitative real-time reverse transcription-polymerase chain reaction. These studies should facilitate our understanding of the storage root formation and cassava improvement. © 2011 Institute of Botany, Chinese Academy of Sciences.

voomDDA: discovery of diagnostic biomarkers and classification of RNA-seq data.

PubMed

Zararsiz, Gokmen; Goksuluk, Dincer; Klaus, Bernd; Korkmaz, Selcuk; Eldem, Vahap; Karabulut, Erdem; Ozturk, Ahmet

2017-01-01

RNA-Seq is a recent and efficient technique that uses the capabilities of next-generation sequencing technology for characterizing and quantifying transcriptomes. One important task using gene-expression data is to identify a small subset of genes that can be used to build diagnostic classifiers particularly for cancer diseases. Microarray based classifiers are not directly applicable to RNA-Seq data due to its discrete nature. Overdispersion is another problem that requires careful modeling of mean and variance relationship of the RNA-Seq data. In this study, we present voomDDA classifiers: variance modeling at the observational level (voom) extensions of the nearest shrunken centroids (NSC) and the diagonal discriminant classifiers. VoomNSC is one of these classifiers and brings voom and NSC approaches together for the purpose of gene-expression based classification. For this purpose, we propose weighted statistics and put these weighted statistics into the NSC algorithm. The VoomNSC is a sparse classifier that models the mean-variance relationship using the voom method and incorporates voom's precision weights into the NSC classifier via weighted statistics. A comprehensive simulation study was designed and four real datasets are used for performance assessment. The overall results indicate that voomNSC performs as the sparsest classifier. It also provides the most accurate results together with power-transformed Poisson linear discriminant analysis, rlog transformed support vector machines and random forests algorithms. In addition to prediction purposes, the voomNSC classifier can be used to identify the potential diagnostic biomarkers for a condition of interest. Through this work, statistical learning methods proposed for microarrays can be reused for RNA-Seq data. An interactive web application is freely available at http://www.biosoft.hacettepe.edu.tr/voomDDA/.

Comparative transcriptomics of 5 high-altitude vertebrates and their low-altitude relatives.

PubMed

Tang, Qianzi; Gu, Yiren; Zhou, Xuming; Jin, Long; Guan, Jiuqiang; Liu, Rui; Li, Jing; Long, Kereng; Tian, Shilin; Che, Tiandong; Hu, Silu; Liang, Yan; Yang, Xuemei; Tao, Xuan; Zhong, Zhijun; Wang, Guosong; Chen, Xiaohui; Li, Diyan; Ma, Jideng; Wang, Xun; Mai, Miaomiao; Jiang, An'an; Luo, Xiaolin; Lv, Xuebin; Gladyshev, Vadim N; Li, Xuewei; Li, Mingzhou

2017-12-01

Species living at high altitude are subject to strong selective pressures due to inhospitable environments (e.g., hypoxia, low temperature, high solar radiation, and lack of biological production), making these species valuable models for comparative analyses of local adaptation. Studies that have examined high-altitude adaptation have identified a vast array of rapidly evolving genes that characterize the dramatic phenotypic changes in high-altitude animals. However, how high-altitude environment shapes gene expression programs remains largely unknown. We generated a total of 910 Gb of high-quality RNA-seq data for 180 samples derived from 6 tissues of 5 agriculturally important high-altitude vertebrates (Tibetan chicken, Tibetan pig, Tibetan sheep, Tibetan goat, and yak) and their cross-fertile relatives living in geographically neighboring low-altitude regions. Of these, ∼75% reads could be aligned to their respective reference genomes, and on average ∼60% of annotated protein coding genes in each organism showed FPKM expression values greater than 0.5. We observed a general concordance in topological relationships between the nucleotide alignments and gene expression-based trees. Tissue and species accounted for markedly more variance than altitude based on either the expression or the alternative splicing patterns. Cross-species clustering analyses showed a tissue-dominated pattern of gene expression and a species-dominated pattern for alternative splicing. We also identified numerous differentially expressed genes that could potentially be involved in phenotypic divergence shaped by high-altitude adaptation. These data serve as a valuable resource for examining the convergence and divergence of gene expression changes between species as they adapt or acclimatize to high-altitude environments. © The Authors 2017. Published by Oxford University Press.

Global gene expression profiling of oral cavity cancers suggests molecular heterogeneity within anatomic subsites

PubMed Central

Severino, Patricia; Alvares, Adriana M; Michaluart, Pedro; Okamoto, Oswaldo K; Nunes, Fabio D; Moreira-Filho, Carlos A; Tajara, Eloiza H

2008-01-01

Background Oral squamous cell carcinoma (OSCC) is a frequent neoplasm, which is usually aggressive and has unpredictable biological behavior and unfavorable prognosis. The comprehension of the molecular basis of this variability should lead to the development of targeted therapies as well as to improvements in specificity and sensitivity of diagnosis. Results Samples of primary OSCCs and their corresponding surgical margins were obtained from male patients during surgery and their gene expression profiles were screened using whole-genome microarray technology. Hierarchical clustering and Principal Components Analysis were used for data visualization and One-way Analysis of Variance was used to identify differentially expressed genes. Samples clustered mostly according to disease subsite, suggesting molecular heterogeneity within tumor stages. In order to corroborate our results, two publicly available datasets of microarray experiments were assessed. We found significant molecular differences between OSCC anatomic subsites concerning groups of genes presently or potentially important for drug development, including mRNA processing, cytoskeleton organization and biogenesis, metabolic process, cell cycle and apoptosis. Conclusion Our results corroborate literature data on molecular heterogeneity of OSCCs. Differences between disease subsites and among samples belonging to the same TNM class highlight the importance of gene expression-based classification and challenge the development of targeted therapies. PMID:19014556

Characterization of distinct classes of differential gene expression in osteoblast cultures from non-syndromic craniosynostosis bone.

PubMed

Rojas-Peña, Monica L; Olivares-Navarrete, Rene; Hyzy, Sharon; Arafat, Dalia; Schwartz, Zvi; Boyan, Barbara D; Williams, Joseph; Gibson, Greg

2014-01-01

Craniosynostosis, the premature fusion of one or more skull sutures, occurs in approximately 1 in 2500 infants, with the majority of cases non-syndromic and of unknown etiology. Two common reasons proposed for premature suture fusion are abnormal compression forces on the skull and rare genetic abnormalities. Our goal was to evaluate whether different sub-classes of disease can be identified based on total gene expression profiles. RNA-Seq data were obtained from 31 human osteoblast cultures derived from bone biopsy samples collected between 2009 and 2011, representing 23 craniosynostosis fusions and 8 normal cranial bones or long bones. No differentiation between regions of the skull was detected, but variance component analysis of gene expression patterns nevertheless supports transcriptome-based classification of craniosynostosis. Cluster analysis showed 4 distinct groups of samples; 1 predominantly normal and 3 craniosynostosis subtypes. Similar constellations of sub-types were also observed upon re-analysis of a similar dataset of 199 calvarial osteoblast cultures. Annotation of gene function of differentially expressed transcripts strongly implicates physiological differences with respect to cell cycle and cell death, stromal cell differentiation, extracellular matrix (ECM) components, and ribosomal activity. Based on these results, we propose non-syndromic craniosynostosis cases can be classified by differences in their gene expression patterns and that these may provide targets for future clinical intervention.

Characterization of Distinct Classes of Differential Gene Expression in Osteoblast Cultures from Non-Syndromic Craniosynostosis Bone

PubMed Central

Rojas-Peña, Monica L.; Olivares-Navarrete, Rene; Hyzy, Sharon; Arafat, Dalia; Schwartz, Zvi; Boyan, Barbara D.; Williams, Joseph; Gibson, Greg

2014-01-01

Craniosynostosis, the premature fusion of one or more skull sutures, occurs in approximately 1 in 2500 infants, with the majority of cases non-syndromic and of unknown etiology. Two common reasons proposed for premature suture fusion are abnormal compression forces on the skull and rare genetic abnormalities. Our goal was to evaluate whether different sub-classes of disease can be identified based on total gene expression profiles. RNA-Seq data were obtained from 31 human osteoblast cultures derived from bone biopsy samples collected between 2009 and 2011, representing 23 craniosynostosis fusions and 8 normal cranial bones or long bones. No differentiation between regions of the skull was detected, but variance component analysis of gene expression patterns nevertheless supports transcriptome-based classification of craniosynostosis. Cluster analysis showed 4 distinct groups of samples; 1 predominantly normal and 3 craniosynostosis subtypes. Similar constellations of sub-types were also observed upon re-analysis of a similar dataset of 199 calvarial osteoblast cultures. Annotation of gene function of differentially expressed transcripts strongly implicates physiological differences with respect to cell cycle and cell death, stromal cell differentiation, extracellular matrix (ECM) components, and ribosomal activity. Based on these results, we propose non-syndromic craniosynostosis cases can be classified by differences in their gene expression patterns and that these may provide targets for future clinical intervention. PMID:25184005

A pilot study of gene expression analysis in workers with hand-arm vibration syndrome.

PubMed

Maeda, Setsuo; Yu, Xiaozhong; Wang, Rui-Sheng; Sakakibara, Hisataka

2008-04-01

The purpose of this pilot study was to examine differences in gene expressions by cDNA microarray analysis of hand-arm vibration syndrome (HAVS) patients. Vein blood samples were collected and total RNA was extracted. All blood samples were obtained in the morning in one visit after a standard light breakfast. We performed microarray analysis with the labeled cDNA prepared by reverse transcription from RNA samples, using the Human CHIP version 1 (DNA Chip Research Inc, Yokohama, Japan). There are 2,976 genes on the chip, and these genes were selected from a cDNA library prepared with human peripheral white blood cells (WBC). Different gene levels between the HAVS patients and controls, and between groups of HAVS with different levels of symptoms, were indicated by the randomized variance model. The most up-regulated genes were analyzed for their possible functions and association with the occurrence of HAVS. From the results of this pilot study, although the results were obtained a limited number of subjects, it would appear that cDNA microarray analysis of HAVS patients has potential as a new objective method of HAVS diagnosis. Further research is needed to examine the gene expression with increased numbers of patients at different stages of HAVS.

Transcriptome sequencing of purple petal spot region in tree peony reveals differentially expressed anthocyanin structural genes.

PubMed

Zhang, Yanzhao; Cheng, Yanwei; Ya, Huiyuan; Xu, Shuzhen; Han, Jianming

2015-01-01

The pigmented cells in defined region of a petal constitute the petal spots. Petal spots attract pollinators and are found in many angiosperm families. Several cultivars of tree peony contain a single red or purple spot at the base of petal that makes the flower more attractive for the ornamental market. So far, the understanding of the molecular mechanism of spot formation is inadequate. In this study, we sequenced the transcriptome of the purple spot and the white non-spot of tree peony flower. We assembled and annotated 67,892 unigenes. Comparative analyses of the two transcriptomes showed 1,573 differentially expressed genes, among which 933 were up-regulated, and 640 were down-regulated in the purple spot. Subsequently, we examined four anthocyanin structural genes, including PsCHS, PsF3'H, PsDFR, and PsANS, which expressed at a significantly higher level in the purple spot than in the white non-spot. We further validated the digital expression data using quantitative real-time PCR. Our result uncovered transcriptome variance between the spot and non-spot of tree peony flower, and revealed that the co-expression of four anthocyanin structural genes was responsible for spot pigment in tree peony. The data will further help to unravel the genetic mechanism of peony flower spot formation.

De novo metatranscriptome assembly and coral gene expression profile of Montipora capitata with growth anomaly.

PubMed

Frazier, Monika; Helmkampf, Martin; Bellinger, M Renee; Geib, Scott M; Takabayashi, Misaki

2017-09-11

Scleractinian corals are a vital component of coral reef ecosystems, and of significant cultural and economic value worldwide. As anthropogenic and natural stressors are contributing to a global decline of coral reefs, understanding coral health is critical to help preserve these ecosystems. Growth anomaly (GA) is a coral disease that has significant negative impacts on coral biology, yet our understanding of its etiology and pathology is lacking. In this study we used RNA-seq along with de novo metatranscriptome assembly and homology assignment to identify coral genes that are expressed in three distinct coral tissue types: tissue from healthy corals ("healthy"), GA lesion tissue from diseased corals ("GA-affected") and apparently healthy tissue from diseased corals ("GA-unaffected"). We conducted pairwise comparisons of gene expression among these three tissue types to identify genes and pathways that help us to unravel the molecular pathology of this coral disease. The quality-filtered de novo-assembled metatranscriptome contained 76,063 genes, of which 13,643 were identified as putative coral genes. Overall gene expression profiles of coral genes revealed high similarity between healthy tissue samples, in contrast to high variance among diseased samples. This indicates GA has a variety of genetic effects at the colony level, including on seemingly healthy (GA-unaffected) tissue. A total of 105 unique coral genes were found differentially expressed among tissue types. Pairwise comparisons revealed the greatest number of differentially expressed genes between healthy and GA-affected tissue (93 genes), followed by healthy and GA-unaffected tissue (33 genes), and GA-affected and -unaffected tissue (7 genes). The putative function of these genes suggests GA is associated with changes in the activity of genes involved in developmental processes and activation of the immune system. This is one of the first transcriptome-level studies to investigate coral GA, and the first metatranscriptome assembly for the M. capitata holobiont. The gene expression data, metatranscriptome assembly and methodology developed through this study represent a significant addition to the molecular information available to further our understanding of this coral disease.

A Protocol for Using Gene Set Enrichment Analysis to Identify the Appropriate Animal Model for Translational Research.

PubMed

Weidner, Christopher; Steinfath, Matthias; Wistorf, Elisa; Oelgeschläger, Michael; Schneider, Marlon R; Schönfelder, Gilbert

2017-08-16

Recent studies that compared transcriptomic datasets of human diseases with datasets from mouse models using traditional gene-to-gene comparison techniques resulted in contradictory conclusions regarding the relevance of animal models for translational research. A major reason for the discrepancies between different gene expression analyses is the arbitrary filtering of differentially expressed genes. Furthermore, the comparison of single genes between different species and platforms often is limited by technical variance, leading to misinterpretation of the con/discordance between data from human and animal models. Thus, standardized approaches for systematic data analysis are needed. To overcome subjective gene filtering and ineffective gene-to-gene comparisons, we recently demonstrated that gene set enrichment analysis (GSEA) has the potential to avoid these problems. Therefore, we developed a standardized protocol for the use of GSEA to distinguish between appropriate and inappropriate animal models for translational research. This protocol is not suitable to predict how to design new model systems a-priori, as it requires existing experimental omics data. However, the protocol describes how to interpret existing data in a standardized manner in order to select the most suitable animal model, thus avoiding unnecessary animal experiments and misleading translational studies.

Early signatures of regime shifts in gene expression dynamics

NASA Astrophysics Data System (ADS)

Pal, Mainak; Pal, Amit Kumar; Ghosh, Sayantari; Bose, Indrani

2013-06-01

Recently, a large number of studies have been carried out on the early signatures of sudden regime shifts in systems as diverse as ecosystems, financial markets, population biology and complex diseases. The signatures of regime shifts in gene expression dynamics are less systematically investigated. In this paper, we consider sudden regime shifts in the gene expression dynamics described by a fold-bifurcation model involving bistability and hysteresis. We consider two alternative models, models 1 and 2, of competence development in the bacterial population B. subtilis and determine some early signatures of the regime shifts between competence and noncompetence. We use both deterministic and stochastic formalisms for the purpose of our study. The early signatures studied include the critical slowing down as a transition point is approached, rising variance and the lag-1 autocorrelation function, skewness and a ratio of two mean first passage times. Some of the signatures could provide the experimental basis for distinguishing between bistability and excitability as the correct mechanism for the development of competence.

Changing expression of vertebrate immunity genes in an anthropogenic environment: a controlled experiment.

PubMed

Hablützel, Pascal I; Brown, Martha; Friberg, Ida M; Jackson, Joseph A

2016-09-01

The effect of anthropogenic environments on the function of the vertebrate immune system is a problem of general importance. For example, it relates to the increasing rates of immunologically-based disease in modern human populations and to the desirability of identifying optimal immune function in domesticated animals. Despite this importance, our present understanding is compromised by a deficit of experimental studies that make adequately matched comparisons between wild and captive vertebrates. We transferred post-larval fishes (three-spined sticklebacks), collected in the wild, to an anthropogenic (captive) environment. We then monitored, over 11 months, how the systemic expression of immunity genes changed in comparison to cohort-matched wild individuals in the originator population (total n = 299). We found that a range of innate (lyz, defbl2, il1r-like, tbk1) and adaptive (cd8a, igmh) immunity genes were up-regulated in captivity, accompanied by an increase in expression of the antioxidant enzyme, gpx4a. For some genes previously known to show seasonality in the wild, this appeared to be reduced in captive fishes. Captive fishes tended to express immunity genes, including igzh, foxp3b, lyz, defbl2, and il1r-like, more variably. Furthermore, although gene co-expression patterns (analyzed through gene-by-gene correlations and mutual information theory based networks) shared common structure in wild and captive fishes, there was also significant divergence. For one gene in particular, defbl2, high expression was associated with adverse health outcomes in captive fishes. Taken together, these results demonstrate widespread regulatory changes in the immune system in captive populations, and that the expression of immunity genes is more constrained in the wild. An increase in constitutive systemic immune activity, such as we observed here, may alter the risk of immunopathology and contribute to variance in health in vertebrate populations exposed to anthropogenic environments.

Genetic and Genomic Response to Selection for Food Consumption in Drosophila melanogaster.

PubMed

Garlapow, Megan E; Everett, Logan J; Zhou, Shanshan; Gearhart, Alexander W; Fay, Kairsten A; Huang, Wen; Morozova, Tatiana V; Arya, Gunjan H; Turlapati, Lavanya; St Armour, Genevieve; Hussain, Yasmeen N; McAdams, Sarah E; Fochler, Sophia; Mackay, Trudy F C

2017-03-01

Food consumption is an essential component of animal fitness; however, excessive food intake in humans increases risk for many diseases. The roles of neuroendocrine feedback loops, food sensing modalities, and physiological state in regulating food intake are well understood, but not the genetic basis underlying variation in food consumption. Here, we applied ten generations of artificial selection for high and low food consumption in replicate populations of Drosophila melanogaster. The phenotypic response to selection was highly asymmetric, with significant responses only for increased food consumption and minimal correlated responses in body mass and composition. We assessed the molecular correlates of selection responses by DNA and RNA sequencing of the selection lines. The high and low selection lines had variants with significantly divergent allele frequencies within or near 2081 genes and 3526 differentially expressed genes in one or both sexes. A total of 519 genes were both genetically divergent and differentially expressed between the divergent selection lines. We performed functional analyses of the effects of RNAi suppression of gene expression and induced mutations for 27 of these candidate genes that have human orthologs and the strongest statistical support, and confirmed that 25 (93 %) affected the mean and/or variance of food consumption.

Dynamic association rules for gene expression data analysis.

PubMed

Chen, Shu-Chuan; Tsai, Tsung-Hsien; Chung, Cheng-Han; Li, Wen-Hsiung

2015-10-14

The purpose of gene expression analysis is to look for the association between regulation of gene expression levels and phenotypic variations. This association based on gene expression profile has been used to determine whether the induction/repression of genes correspond to phenotypic variations including cell regulations, clinical diagnoses and drug development. Statistical analyses on microarray data have been developed to resolve gene selection issue. However, these methods do not inform us of causality between genes and phenotypes. In this paper, we propose the dynamic association rule algorithm (DAR algorithm) which helps ones to efficiently select a subset of significant genes for subsequent analysis. The DAR algorithm is based on association rules from market basket analysis in marketing. We first propose a statistical way, based on constructing a one-sided confidence interval and hypothesis testing, to determine if an association rule is meaningful. Based on the proposed statistical method, we then developed the DAR algorithm for gene expression data analysis. The method was applied to analyze four microarray datasets and one Next Generation Sequencing (NGS) dataset: the Mice Apo A1 dataset, the whole genome expression dataset of mouse embryonic stem cells, expression profiling of the bone marrow of Leukemia patients, Microarray Quality Control (MAQC) data set and the RNA-seq dataset of a mouse genomic imprinting study. A comparison of the proposed method with the t-test on the expression profiling of the bone marrow of Leukemia patients was conducted. We developed a statistical way, based on the concept of confidence interval, to determine the minimum support and minimum confidence for mining association relationships among items. With the minimum support and minimum confidence, one can find significant rules in one single step. The DAR algorithm was then developed for gene expression data analysis. Four gene expression datasets showed that the proposed DAR algorithm not only was able to identify a set of differentially expressed genes that largely agreed with that of other methods, but also provided an efficient and accurate way to find influential genes of a disease. In the paper, the well-established association rule mining technique from marketing has been successfully modified to determine the minimum support and minimum confidence based on the concept of confidence interval and hypothesis testing. It can be applied to gene expression data to mine significant association rules between gene regulation and phenotype. The proposed DAR algorithm provides an efficient way to find influential genes that underlie the phenotypic variance.

Comprehensive QTL mapping survey dissects the complex fruit texture physiology in apple (Malus x domestica Borkh.).

PubMed

Longhi, Sara; Moretto, Marco; Viola, Roberto; Velasco, Riccardo; Costa, Fabrizio

2012-02-01

Fruit ripening is a complex physiological process in plants whereby cell wall programmed changes occur mainly to promote seed dispersal. Cell wall modification also directly regulates the textural properties, a fundamental aspect of fruit quality. In this study, two full-sib populations of apple, with 'Fuji' as the common maternal parent, crossed with 'Delearly' and 'Pink Lady', were used to understand the control of fruit texture by QTL mapping and in silico gene mining. Texture was dissected with a novel high resolution phenomics strategy, simultaneously profiling both mechanical and acoustic fruit texture components. In 'Fuji × Delearly' nine linkage groups were associated with QTLs accounting from 15.6% to 49% of the total variance, and a highly significant QTL cluster for both textural components was mapped on chromosome 10 and co-located with Md-PG1, a polygalacturonase gene that, in apple, is known to be involved in cell wall metabolism processes. In addition, other candidate genes related to Md-NOR and Md-RIN transcription factors, Md-Pel (pectate lyase), and Md-ACS1 were mapped within statistical intervals. In 'Fuji × Pink Lady', a smaller set of linkage groups associated with the QTLs identified for fruit texture (15.9-34.6% variance) was observed. The analysis of the phenotypic variance over a two-dimensional PCA plot highlighted a transgressive segregation for this progeny, revealing two QTL sets distinctively related to both mechanical and acoustic texture components. The mining of the apple genome allowed the discovery of the gene inventory underlying each QTL, and functional profile assessment unravelled specific gene expression patterns of these candidate genes.

Comparison of multipoint linkage analyses for quantitative traits in the CEPH data: parametric LOD scores, variance components LOD scores, and Bayes factors.

PubMed

Sung, Yun Ju; Di, Yanming; Fu, Audrey Q; Rothstein, Joseph H; Sieh, Weiva; Tong, Liping; Thompson, Elizabeth A; Wijsman, Ellen M

2007-01-01

We performed multipoint linkage analyses with multiple programs and models for several gene expression traits in the Centre d'Etude du Polymorphisme Humain families. All analyses provided consistent results for both peak location and shape. Variance-components (VC) analysis gave wider peaks and Bayes factors gave fewer peaks. Among programs from the MORGAN package, lm_multiple performed better than lm_markers, resulting in less Markov-chain Monte Carlo (MCMC) variability between runs, and the program lm_twoqtl provided higher LOD scores by also including either a polygenic component or an additional quantitative trait locus.

Comparison of multipoint linkage analyses for quantitative traits in the CEPH data: parametric LOD scores, variance components LOD scores, and Bayes factors

PubMed Central

Sung, Yun Ju; Di, Yanming; Fu, Audrey Q; Rothstein, Joseph H; Sieh, Weiva; Tong, Liping; Thompson, Elizabeth A; Wijsman, Ellen M

2007-01-01

We performed multipoint linkage analyses with multiple programs and models for several gene expression traits in the Centre d'Etude du Polymorphisme Humain families. All analyses provided consistent results for both peak location and shape. Variance-components (VC) analysis gave wider peaks and Bayes factors gave fewer peaks. Among programs from the MORGAN package, lm_multiple performed better than lm_markers, resulting in less Markov-chain Monte Carlo (MCMC) variability between runs, and the program lm_twoqtl provided higher LOD scores by also including either a polygenic component or an additional quantitative trait locus. PMID:18466597

Gene expression factor analysis to differentiate pathways linked to fibromyalgia, chronic fatigue syndrome, and depression in a diverse patient sample

PubMed Central

Iacob, Eli; Light, Alan R.; Donaldson, Gary W.; Okifuji, Akiko; Hughen, Ronald W.; White, Andrea T.; Light, Kathleen C.

2015-01-01

Objective To determine if independent candidate genes can be grouped into meaningful biological factors and if these factors are associated with the diagnosis of chronic fatigue syndrome (CFS) and fibromyalgia (FMS) while controlling for co-morbid depression, sex, and age. Methods We included leukocyte mRNA gene expression from a total of 261 individuals including healthy controls (n=61), patients with FMS only (n=15), CFS only (n=33), co-morbid CFS and FMS (n=79), and medication-resistant (n=42) or medication-responsive (n=31) depression. We used Exploratory Factor Analysis (EFA) on 34 candidate genes to determine factor scores and regression analysis to examine if these factors were associated with specific diagnoses. Results EFA resulted in four independent factors with minimal overlap of genes between factors explaining 51% of the variance. We labeled these factors by function as: 1) Purinergic and cellular modulators; 2) Neuronal growth and immune function; 3) Nociception and stress mediators; 4) Energy and mitochondrial function. Regression analysis predicting these biological factors using FMS, CFS, depression severity, age, and sex revealed that greater expression in Factors 1 and 3 was positively associated with CFS and negatively associated with depression severity (QIDS score), but not associated with FMS. Conclusion Expression of candidate genes can be grouped into meaningful clusters, and CFS and depression are associated with the same 2 clusters but in opposite directions when controlling for co-morbid FMS. Given high co-morbid disease and interrelationships between biomarkers, EFA may help determine patient subgroups in this population based on gene expression. PMID:26097208

Effect of GDNF on depressive-like behavior, spatial learning and key genes of the brain dopamine system in genetically predisposed to behavioral disorders mouse strains.

PubMed

Naumenko, Vladimir S; Kondaurova, Elena M; Bazovkina, Daria V; Tsybko, Anton S; Ilchibaeva, Tatyana V; Khotskin, Nikita V; Semenova, Alina A; Popova, Nina K

2014-11-01

The effect of glial cell line-derived neurotrophic factor (GDNF) on behavior and brain dopamine system in predisposed to depressive-like behavior ASC (Antidepressant Sensitive Cataleptics) mice in comparison with the parental "nondepressive" CBA mice was studied. In 7days after administration (800ng, i.c.v.) GDNF decreased escape latency time and the path traveled to reach hidden platform in Morris water maze in ASC mice. GDNF enhanced depressive-like behavioral traits in both "nondepressive" CBA and "depressive" ASC mice. In CBA mice, GDNF decreased functional response to agonists of D1 (chloro-APB hydrobromide) and D2 (sumanirole maleate) receptors in tail suspension test, reduced D2 receptor gene expression in the substantia nigra and increased monoamine oxydase A (MAO A) gene expression in the striatum. GDNF increased D1 and D2 receptor genes expression in the nucleus accumbens of ASC mice but failed to alter expression of catechol-O-methyltransferase, dopamine transporter, MAO B and tyrosine hydroxylase genes in both investigated mouse strains. Thus, GDNF produced long-term genotype-dependent effect on behavior and the brain dopamine system. GDNF pretreatment (1) reduced D1 and D2 receptors functional responses and D2 receptor gene expression in s. nigra of CBA mice; (2) increased D1 and D2 receptor genes expression in n. accumbens of ASC mice and (3) improved spatial learning in ASC mice. GDNF enhanced depressive-like behavior both in CBA and ASC mice. The data suggest that genetically defined variance in the cross-talk between GDNF and brain dopamine system contributes to the variability of GDNF-induced responses and might be responsible for controversial GDNF effects. Copyright © 2014 Elsevier B.V. All rights reserved.

Comparative transcriptomics of 5 high-altitude vertebrates and their low-altitude relatives

PubMed Central

Tang, Qianzi; Zhou, Xuming; Jin, Long; Guan, Jiuqiang; Liu, Rui; Li, Jing; Long, Kereng; Tian, Shilin; Che, Tiandong; Hu, Silu; Liang, Yan; Yang, Xuemei; Tao, Xuan; Zhong, Zhijun; Wang, Guosong; Chen, Xiaohui; Li, Diyan; Ma, Jideng; Wang, Xun; Mai, Miaomiao; Jiang, An’an; Luo, Xiaolin; Lv, Xuebin; Gladyshev, Vadim N; Li, Xuewei

2017-01-01

Abstract Background Species living at high altitude are subject to strong selective pressures due to inhospitable environments (e.g., hypoxia, low temperature, high solar radiation, and lack of biological production), making these species valuable models for comparative analyses of local adaptation. Studies that have examined high-altitude adaptation have identified a vast array of rapidly evolving genes that characterize the dramatic phenotypic changes in high-altitude animals. However, how high-altitude environment shapes gene expression programs remains largely unknown. Findings We generated a total of 910 Gb of high-quality RNA-seq data for 180 samples derived from 6 tissues of 5 agriculturally important high-altitude vertebrates (Tibetan chicken, Tibetan pig, Tibetan sheep, Tibetan goat, and yak) and their cross-fertile relatives living in geographically neighboring low-altitude regions. Of these, ∼75% reads could be aligned to their respective reference genomes, and on average ∼60% of annotated protein coding genes in each organism showed FPKM expression values greater than 0.5. We observed a general concordance in topological relationships between the nucleotide alignments and gene expression–based trees. Tissue and species accounted for markedly more variance than altitude based on either the expression or the alternative splicing patterns. Cross-species clustering analyses showed a tissue-dominated pattern of gene expression and a species-dominated pattern for alternative splicing. We also identified numerous differentially expressed genes that could potentially be involved in phenotypic divergence shaped by high-altitude adaptation. Conclusions These data serve as a valuable resource for examining the convergence and divergence of gene expression changes between species as they adapt or acclimatize to high-altitude environments. PMID:29149296

A novel variant associated with HDL-C levels by modifying DAGLB expression levels: An annotation-based genome-wide association study.

PubMed

Zhou, Dan; Zhang, Dandan; Sun, Xiaohui; Li, Zhiqiang; Ni, Yaqin; Shan, Zhongyan; Li, Hong; Liu, Chengguo; Zhang, Shuai; Liu, Yi; Zheng, Ruizhi; Pan, Feixia; Zhu, Yimin; Shi, Yongyong; Lai, Maode

2018-06-01

Although numbers of genome-wide association studies (GWAS) have been performed for serum lipid levels, limited heritability has been explained. Studies showed that combining data from GWAS and expression quantitative trait loci (eQTLs) signals can both enhance the discovery of trait-associated SNPs and gain a better understanding of the mechanism. We performed an annotation-based, multistage genome-wide screening for serum-lipid-level-associated loci in totally 6863 Han Chinese. A serum high-density lipoprotein cholesterol (HDL-C) associated variant rs1880118 (hg19 chr7:g. 6435220G>C) was replicated (P combined  = 1.4E-10). rs1880118 was associated with DAGLB (diacylglycerol lipase, beta) expression levels in subcutaneous adipose tissue (P = 5.9E-42) and explained 47.7% of the expression variance. After the replication, an active segment covering variants tagged by rs1880118 near 5' of DAGLB was annotated using histone modification and transcription factor binding signals. The luciferase report assay revealed that the segment containing the minor alleles showed increased transcriptional activity compared with segment contains the major alleles, which was consistent with the eQTL analyses. The expression-trait association tests indicated the association between the DAGLB and serum HDL-C levels using gene-based approaches called "TWAS" (P = 3.0E-8), "SMR" (P = 1.1E-4), and "Sherlock" (P = 1.6E-6). To summarize, we identified a novel HDL-C-associated variant which explained nearly half of the expression variance of DAGLB. Integrated analyses established a genotype-gene-phenotype three-way association and expanded our knowledge of DAGLB in lipid metabolism.

Pasture-feeding of Charolais steers influences skeletal muscle metabolism and gene expression.

PubMed

Cassar-Malek, I; Jurie, C; Bernard, C; Barnola, I; Micol, D; Hocquette, J-F

2009-10-01

Extensive beef production systems on pasture are promoted to improve animal welfare and beef quality. This study aimed to compare the influence on muscle characteristics of two management approaches representative of intensive and extensive production systems. One group of 6 Charolais steers was fed maize-silage indoors and another group of 6 Charolais steers grazed on pasture. Activities of enzymes representative of glycolytic and oxidative (Isocitrate dehydrogenase [ICDH], citrate synthase [CS], hydroxyacyl-CoA dehydrogenase [HAD]) muscle metabolism were assessed in Rectus abdominis (RA) and Semitendinosus (ST) muscles. Activities of oxidative enzymes ICDH, CS and HAD were higher in muscles from grazing animals demonstrating a plasticity of muscle metabolism according to the production and feeding system. Gene expression profiling in RA and ST muscles was performed on both production groups using a multi-tissue bovine cDNA repertoire. Variance analysis showed an effect of the muscle type and of the production system on gene expression (P<0.001). A list of the 212 most variable genes according to the production system was established, of which 149 genes corresponded to identified genes. They were classified according to their gene function annotation mainly in the "protein metabolism and modification", "signal transduction", "cell cycle", "developmental processes" and "muscle contraction" biological processes. Selenoprotein W was found to be underexpressed in pasture-fed animals and could be proposed as a putative gene marker of the grass-based system. In conclusion, enzyme-specific adaptations and gene expression modifications were observed in response to the production system and some of them could be candidates for grazing or grass-feeding traceability.

Evolution of dosage compensation under sexual selection differs between X and Z chromosomes

PubMed Central

Mullon, Charles; Wright, Alison E.; Reuter, Max; Pomiankowski, Andrew; Mank, Judith E.

2015-01-01

Complete sex chromosome dosage compensation has more often been observed in XY than ZW species. In this study, using a population genetic model and the chicken transcriptome, we assess whether sexual conflict can account for this difference. Sexual conflict over expression is inevitable when mutation effects are correlated across the sexes, as compensatory mutations in the heterogametic sex lead to hyperexpression in the homogametic sex. Coupled with stronger selection and greater reproductive variance in males, this results in slower and less complete evolution of Z compared with X dosage compensation. Using expression variance as a measure of selection strength, we find that, as predicted by the model, dosage compensation in the chicken is most pronounced in genes that are under strong selection biased towards females. Our study explains the pattern of weak dosage compensation in ZW systems, and suggests that sexual selection plays a major role in shaping sex chromosome dosage compensation. PMID:26212613

Distributional fold change test – a statistical approach for detecting differential expression in microarray experiments

PubMed Central

2012-01-01

Background Because of the large volume of data and the intrinsic variation of data intensity observed in microarray experiments, different statistical methods have been used to systematically extract biological information and to quantify the associated uncertainty. The simplest method to identify differentially expressed genes is to evaluate the ratio of average intensities in two different conditions and consider all genes that differ by more than an arbitrary cut-off value to be differentially expressed. This filtering approach is not a statistical test and there is no associated value that can indicate the level of confidence in the designation of genes as differentially expressed or not differentially expressed. At the same time the fold change by itself provide valuable information and it is important to find unambiguous ways of using this information in expression data treatment. Results A new method of finding differentially expressed genes, called distributional fold change (DFC) test is introduced. The method is based on an analysis of the intensity distribution of all microarray probe sets mapped to a three dimensional feature space composed of average expression level, average difference of gene expression and total variance. The proposed method allows one to rank each feature based on the signal-to-noise ratio and to ascertain for each feature the confidence level and power for being differentially expressed. The performance of the new method was evaluated using the total and partial area under receiver operating curves and tested on 11 data sets from Gene Omnibus Database with independently verified differentially expressed genes and compared with the t-test and shrinkage t-test. Overall the DFC test performed the best – on average it had higher sensitivity and partial AUC and its elevation was most prominent in the low range of differentially expressed features, typical for formalin-fixed paraffin-embedded sample sets. Conclusions The distributional fold change test is an effective method for finding and ranking differentially expressed probesets on microarrays. The application of this test is advantageous to data sets using formalin-fixed paraffin-embedded samples or other systems where degradation effects diminish the applicability of correlation adjusted methods to the whole feature set. PMID:23122055

A small system--high-resolution study of metabolic adaptation in the central metabolic pathway to temperate climates in Drosophila melanogaster.

PubMed

Lavington, Erik; Cogni, Rodrigo; Kuczynski, Caitlin; Koury, Spencer; Behrman, Emily L; O'Brien, Katherine R; Schmidt, Paul S; Eanes, Walter F

2014-08-01

In this article, we couple the geographic variation in 127 single-nucleotide polymorphism (SNP) frequencies in genes of 46 enzymes of central metabolism with their associated cis-expression variation to predict latitudinal or climatic-driven gene expression changes in the metabolic architecture of Drosophila melanogaster. Forty-two percent of the SNPs in 65% of the genes show statistically significant clines in frequency with latitude across the 20 local population samples collected from southern Florida to Ontario. A number of SNPs in the screened genes are also associated with significant expression variation within the Raleigh population from North Carolina. A principal component analysis of the full variance-covariance matrix of latitudinal changes in SNP-associated standardized gene expression allows us to identify those major genes in the pathway and its associated branches that are likely targets of natural selection. When embedded in a central metabolic context, we show that these apparent targets are concentrated in the genes of the upper glycolytic pathway and pentose shunt, those controlling glycerol shuttle activity, and finally those enzymes associated with the utilization of glutamate and pyruvate. These metabolites possess high connectivity and thus may be the points where flux balance can be best shifted. We also propose that these points are conserved points associated with coupling energy homeostasis and energy sensing in mammals. We speculate that the modulation of gene expression at specific points in central metabolism that are associated with shifting flux balance or possibly energy-state sensing plays a role in adaptation to climatic variation. © The Author 2014. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

GmDREB1 overexpression affects the expression of microRNAs in GM wheat seeds

PubMed Central

Niu, Fengjuan; Hu, Zheng; Chen, Rui; Zhang, Hui

2017-01-01

MicroRNAs (miRNAs) are small regulators of gene expression that act on many different molecular and biochemical processes in eukaryotes. To date, miRNAs have not been considered in the current evaluation system for GM crops. In this study, small RNAs from the dry seeds of a GM wheat line overexpressing GmDREB1 and non-GM wheat cultivars were investigated using deep sequencing technology and bioinformatic approaches. As a result, 23 differentially expressed miRNAs in dry seeds were identified and confirmed between GM wheat and a non-GM acceptor. Notably, more differentially expressed tae-miRNAs between non-GM wheat varieties were found, indicating that the degree of variance between non-GM cultivars was considerably higher than that induced by the transgenic event. Most of the target genes of these differentially expressed miRNAs between GM wheat and a non-GM acceptor were associated with abiotic stress, in accordance with the product concept of GM wheat in improving drought and salt tolerance. Our data provided useful information and insights into the evaluation of miRNA expression in edible GM crops. PMID:28459812

GmDREB1 overexpression affects the expression of microRNAs in GM wheat seeds.

PubMed

Jiang, Qiyan; Sun, Xianjun; Niu, Fengjuan; Hu, Zheng; Chen, Rui; Zhang, Hui

2017-01-01

MicroRNAs (miRNAs) are small regulators of gene expression that act on many different molecular and biochemical processes in eukaryotes. To date, miRNAs have not been considered in the current evaluation system for GM crops. In this study, small RNAs from the dry seeds of a GM wheat line overexpressing GmDREB1 and non-GM wheat cultivars were investigated using deep sequencing technology and bioinformatic approaches. As a result, 23 differentially expressed miRNAs in dry seeds were identified and confirmed between GM wheat and a non-GM acceptor. Notably, more differentially expressed tae-miRNAs between non-GM wheat varieties were found, indicating that the degree of variance between non-GM cultivars was considerably higher than that induced by the transgenic event. Most of the target genes of these differentially expressed miRNAs between GM wheat and a non-GM acceptor were associated with abiotic stress, in accordance with the product concept of GM wheat in improving drought and salt tolerance. Our data provided useful information and insights into the evaluation of miRNA expression in edible GM crops.

Integrated lipidomics and transcriptomic analysis of peripheral blood reveals significantly enriched pathways in type 2 diabetes mellitus.

PubMed

Zhao, Chen; Mao, Jinghe; Ai, Junmei; Shenwu, Ming; Shi, Tieliu; Zhang, Daqing; Wang, Xiaonan; Wang, Yunliang; Deng, Youping

2013-01-01

Insulin resistance is a key element in the pathogenesis of type 2 diabetes mellitus. Plasma free fatty acids were assumed to mediate the insulin resistance, while the relationship between lipid and glucose disposal remains to be demonstrated across liver, skeletal muscle and blood. We profiled both lipidomics and gene expression of 144 total peripheral blood samples, 84 from patients with T2D and 60 from healthy controls. Then, factor and partial least squares models were used to perform a combined analysis of lipidomics and gene expression profiles to uncover the bioprocesses that are associated with lipidomic profiles in type 2 diabetes. According to factor analysis of the lipidomic profile, several species of lipids were found to be correlated with different phenotypes, including diabetes-related C23:2CE, C23:3CE, C23:4CE, ePE36:4, ePE36:5, ePE36:6; race-related (African-American) PI36:1; and sex-related PE34:1 and LPC18:2. The major variance of gene expression profile was not caused by known factors and no significant difference can be directly derived from differential gene expression profile. However, the combination of lipidomic and gene expression analyses allows us to reveal the correlation between the altered lipid profile with significantly enriched pathways, such as one carbon pool by folate, arachidonic acid metabolism, insulin signaling pathway, amino sugar and nucleotide sugar metabolism, propanoate metabolism, and starch and sucrose metabolism. The genes in these pathways showed a good capability to classify diabetes samples. Combined analysis of gene expression and lipidomic profiling reveals type 2 diabetes-associated lipid species and enriched biological pathways in peripheral blood, while gene expression profile does not show direct correlation. Our findings provide a new clue to better understand the mechanism of disordered lipid metabolism in association with type 2 diabetes.

Fyn-Dependent Gene Networks in Acute Ethanol Sensitivity

PubMed Central

Farris, Sean P.; Miles, Michael F.

2013-01-01

Studies in humans and animal models document that acute behavioral responses to ethanol are predisposing factor for the risk of long-term drinking behavior. Prior microarray data from our laboratory document strain- and brain region-specific variation in gene expression profile responses to acute ethanol that may be underlying regulators of ethanol behavioral phenotypes. The non-receptor tyrosine kinase Fyn has previously been mechanistically implicated in the sedative-hypnotic response to acute ethanol. To further understand how Fyn may modulate ethanol behaviors, we used whole-genome expression profiling. We characterized basal and acute ethanol-evoked (3 g/kg) gene expression patterns in nucleus accumbens (NAC), prefrontal cortex (PFC), and ventral midbrain (VMB) of control and Fyn knockout mice. Bioinformatics analysis identified a set of Fyn-related gene networks differently regulated by acute ethanol across the three brain regions. In particular, our analysis suggested a coordinate basal decrease in myelin-associated gene expression within NAC and PFC as an underlying factor in sensitivity of Fyn null animals to ethanol sedation. An in silico analysis across the BXD recombinant inbred (RI) strains of mice identified a significant correlation between Fyn expression and a previously published ethanol loss-of-righting-reflex (LORR) phenotype. By combining PFC gene expression correlates to Fyn and LORR across multiple genomic datasets, we identified robust Fyn-centric gene networks related to LORR. Our results thus suggest that multiple system-wide changes exist within specific brain regions of Fyn knockout mice, and that distinct Fyn-dependent expression networks within PFC may be important determinates of the LORR due to acute ethanol. These results add to the interpretation of acute ethanol behavioral sensitivity in Fyn kinase null animals, and identify Fyn-centric gene networks influencing variance in ethanol LORR. Such networks may also inform future design of pharmacotherapies for the treatment and prevention of alcohol use disorders. PMID:24312422

Genome-Wide Association Study for Carcass Traits in an Experimental Nelore Cattle Population

PubMed Central

Medeiros de Oliveira Silva, Rafael; Bonvino Stafuzza, Nedenia; de Oliveira Fragomeni, Breno; Miguel Ferreira de Camargo, Gregório; Matos Ceacero, Thaís; Noely dos Santos Gonçalves Cyrillo, Joslaine; Baldi, Fernando; Augusti Boligon, Arione; Zerlotti Mercadante, Maria Eugênia; Lino Lourenco, Daniela; Misztal, Ignacy; Galvão de Albuquerque, Lucia

2017-01-01

The purpose of this study was to identify genomic regions associated with carcass traits in an experimental Nelore cattle population. The studied data set contained 2,306 ultrasound records for longissimus muscle area (LMA), 1,832 for backfat thickness (BF), and 1,830 for rump fat thickness (RF). A high-density SNP panel (BovineHD BeadChip assay 700k, Illumina Inc., San Diego, CA) was used for genotyping. After genomic data quality control, 437,197 SNPs from 761 animals were available, of which 721 had phenotypes for LMA, 669 for BF, and 718 for RF. The SNP solutions were estimated using a single-step genomic BLUP approach (ssGWAS), which calculated the variance for windows of 50 consecutive SNPs and the regions that accounted for more than 0.5% of the additive genetic variance were used to search for candidate genes. The results indicated that 12, 18, and 15 different windows were associated to LMA, BF, and RF, respectively. Confirming the polygenic nature of the studied traits, 43, 65, and 53 genes were found in those associated windows, respectively for LMA, BF, and RF. Among the candidate genes, some of them, which already had their functions associated with the expression of energy metabolism, were found associated with fat deposition in this study. In addition, ALKBH3 and HSD17B12 genes, which are related in fibroblast death and metabolism of steroids, were found associated with LMA. The results presented here should help to better understand the genetic and physiologic mechanism regulating the muscle tissue deposition and subcutaneous fat cover expression of Zebu animals. The identification of candidate genes should contribute for Zebu breeding programs in order to consider carcass traits as selection criteria in their genetic evaluation. PMID:28118362

Identification and analysis of pig chimeric mRNAs using RNA sequencing data

PubMed Central

2012-01-01

Background Gene fusion is ubiquitous over the course of evolution. It is expected to increase the diversity and complexity of transcriptomes and proteomes through chimeric sequence segments or altered regulation. However, chimeric mRNAs in pigs remain unclear. Here we identified some chimeric mRNAs in pigs and analyzed the expression of them across individuals and breeds using RNA-sequencing data. Results The present study identified 669 putative chimeric mRNAs in pigs, of which 251 chimeric candidates were detected in a set of RNA-sequencing data. The 618 candidates had clear trans-splicing sites, 537 of which obeyed the canonical GU-AG splice rule. Only two putative pig chimera variants whose fusion junction was overlapped with that of a known human chimeric mRNA were found. A set of unique chimeric events were considered middle variances in the expression across individuals and breeds, and revealed non-significant variance between sexes. Furthermore, the genomic region of the 5′ partner gene shares a similar DNA sequence with that of the 3′ partner gene for 458 putative chimeric mRNAs. The 81 of those shared DNA sequences significantly matched the known DNA-binding motifs in the JASPAR CORE database. Four DNA motifs shared in parental genomic regions had significant similarity with known human CTCF binding sites. Conclusions The present study provided detailed information on some pig chimeric mRNAs. We proposed a model that trans-acting factors, such as CTCF, induced the spatial organisation of parental genes to the same transcriptional factory so that parental genes were coordinatively transcribed to give birth to chimeric mRNAs. PMID:22925561

A microarray analysis of the effects of moderate hypothermia and rewarming on gene expression by human hepatocytes (HepG2).

PubMed

Sonna, Larry A; Kuhlmeier, Matthew M; Khatri, Purvesh; Chen, Dechang; Lilly, Craig M

2010-09-01

The gene expression changes produced by moderate hypothermia are not fully known, but appear to differ in important ways from those produced by heat shock. We examined the gene expression changes produced by moderate hypothermia and tested the hypothesis that rewarming after hypothermia approximates a heat-shock response. Six sets of human HepG2 hepatocytes were subjected to moderate hypothermia (31 degrees C for 16 h), a conventional in vitro heat shock (43 degrees C for 30 min) or control conditions (37 degrees C), then harvested immediately or allowed to recover for 3 h at 37 degrees C. Expression analysis was performed with Affymetrix U133A gene chips, using analysis of variance-based techniques. Moderate hypothermia led to distinct time-dependent expression changes, as did heat shock. Hypothermia initially caused statistically significant, greater than or equal to twofold changes in expression (relative to controls) of 409 sequences (143 increased and 266 decreased), whereas heat shock affected 71 (35 increased and 36 decreased). After 3 h of recovery, 192 sequences (83 increased, 109 decreased) were affected by hypothermia and 231 (146 increased, 85 decreased) by heat shock. Expression of many heat shock proteins was decreased by hypothermia but significantly increased after rewarming. A comparison of sequences affected by thermal stress without regard to the magnitude of change revealed that the overlap between heat and cold stress was greater after 3 h of recovery than immediately following thermal stress. Thus, while some overlap occurs (particularly after rewarming), moderate hypothermia produces extensive, time-dependent gene expression changes in HepG2 cells that differ in important ways from those induced by heat shock.

Age Dependent Variability in Gene Expression in Fischer 344 ...

EPA Pesticide Factsheets

Recent evidence suggests older adults may be a sensitive population with regard to environmental exposure to toxic compounds. One source of this sensitivity could be an enhanced variability in response. Studies on phenotypic differences have suggested that variation in response does increase with age. However, few reports address the question of variation in gene expression as an underlying cause for increased variability of phenotypic response in the aged. In this study, we utilized global analysis to compare variation in constitutive gene expression in the retinae of young (4 mos), middle-aged (11 mos) and aged (23 mos) Fischer 344 rats. Three hundred and forty transcripts were identified in which variance in expression increased from 4 to 23 mos of age, while only twelve transcripts were found for which it decreased. Functional roles for identified genes were clustered in basic biological categories including cell communication, function, metabolism and response to stimuli. Our data suggest that population stochastically-induced variability should be considered in assessing sensitivity due to old age. Recent evidence suggests older adults may be a sensitive population with regard to environmental exposure to toxic compounds. One source of this sensitivity could be an enhanced variability in response. Studies on phenotypic differences have suggested that variation in response does increase with age. However, few reports address the question of variation in

Gene Expression Profiling of Benign and Malignant Pheochromocytoma

PubMed Central

BROUWERS, FREDERIEKE M.; ELKAHLOUN, ABDEL G.; MUNSON, PETER J.; EISENHOFER, GRAEME; BARB, JENNIFER; LINEHAN, W. MARSTON; LENDERS, JACQUES W.M.; DE KRIJGER, RONALD; MANNELLI, MASSIMO; UDELSMAN, ROBERT; OCAL, IDRIS T.; SHULKIN, BARRY L.; BORNSTEIN, STEFAN R.; BREZA, JAN; KSINANTOVA, LUCIA; PACAK, KAREL

2016-01-01

There are currently no reliable diagnostic and prognostic markers or effective treatments for malignant pheochromocytoma. This study used oligonucleotide microarrays to examine gene expression profiles in pheochromocytomas from 90 patients, including 20 with malignant tumors, the latter including metastases and primary tumors from which metastases developed. Other subgroups of tumors included those defined by tissue norepinephrine compared to epinephrine contents (i.e., noradrenergic versus adrenergic phenotypes), adrenal versus extra-adrenal locations, and presence of germline mutations of genes pre-disposing to the tumor. Correcting for the confounding influence of nora-drenergic versus adrenergic catecholamine phenotype by the analysis of variance revealed a larger and more accurate number of genes that discriminated benign from malignant pheochromocytomas than when the confounding influence of catecholamine phenotype was not considered. Seventy percent of these genes were underexpressed in malignant compared to benign tumors. Similarly, 89% of genes were underexpressed in malignant primary tumors compared to benign tumors, suggesting that malignant potential is largely characterized by a less-differentiated pattern of gene expression. The present database of differentially expressed genes provides a unique resource for mapping the pathways leading to malignancy and for establishing new targets for treatment and diagnostic and prognostic markers of malignant disease. The database may also be useful for examining mechanisms of tumorigenesis and genotype–phenotype relationships. Further progress on the basis of this database can be made from follow-up confirmatory studies, application of bioinformatics approaches for data mining and pathway analyses, testing in pheochromocytoma cell culture and animal model systems, and retrospective and prospective studies of diagnostic markers. PMID:17102123

Drosophila selenophosphate synthetase 1 regulates vitamin B6 metabolism: prediction and confirmation

PubMed Central

2011-01-01

Background There are two selenophosphate synthetases (SPSs) in higher eukaryotes, SPS1 and SPS2. Of these two isotypes, only SPS2 catalyzes selenophosphate synthesis. Although SPS1 does not contain selenophosphate synthesis activity, it was found to be essential for cell growth and embryogenesis in Drosophila. The function of SPS1, however, has not been elucidated. Results Differentially expressed genes in Drosophila SL2 cells were identified using two-way analysis of variance methods and clustered according to their temporal expression pattern. Gene ontology analysis was performed against differentially expressed genes and gene ontology terms related to vitamin B6 biosynthesis were found to be significantly affected at the early stage at which megamitochondria were not formed (day 3) after SPS1 knockdown. Interestingly, genes related to defense and amino acid metabolism were affected at a later stage (day 5) following knockdown. Levels of pyridoxal phosphate, an active form of vitamin B6, were decreased by SPS1 knockdown. Treatment of SL2 cells with an inhibitor of pyridoxal phosphate synthesis resulted in both a similar pattern of expression as that found by SPS1 knockdown and the formation of megamitochondria, the major phenotypic change observed by SPS1 knockdown. Conclusions These results indicate that SPS1 regulates vitamin B6 synthesis, which in turn impacts various cellular systems such as amino acid metabolism, defense and other important metabolic activities. PMID:21864351

Effect of inter- and intragenic epistasis on the heritability of oil content in rapeseed (Brassica napus L.).

PubMed

Würschum, Tobias; Maurer, Hans Peter; Dreyer, Felix; Reif, Jochen C

2013-02-01

The loci detected by association mapping which are involved in the expression of important agronomic traits in crops often explain only a small proportion of the total genotypic variance. Here, 17 SNPs derived from 9 candidate genes from the triacylglycerol biosynthetic pathway were studied in an association analysis in a population of 685 diverse elite rapeseed inbred lines. The 685 lines were evaluated for oil content, as well as for glucosinolates, yield, and thousand-kernel weight in field trials at 4 locations. We detected main effects for most of the studied genes illustrating that genetic diversity for oil content can be exploited by the selection of favorable alleles. In addition to main effects, both intergenic and intragenic epistasis was detected that contributes to a considerable amount to the genotypic variance observed for oil content. The proportion of explained genotypic variance was doubled when in addition to main effects epistasis was considered. Therefore, a knowledge-based improvement of oil content in rapeseed should also take such favorable epistatic interactions into account. Our results suggest, that the observed high contribution of epistasis may to some extent explain the missing heritability in genome-wide association studies.

Transcriptome sequencing of purple petal spot region in tree peony reveals differentially expressed anthocyanin structural genes

PubMed Central

Zhang, Yanzhao; Cheng, Yanwei; Ya, Huiyuan; Xu, Shuzhen; Han, Jianming

2015-01-01

The pigmented cells in defined region of a petal constitute the petal spots. Petal spots attract pollinators and are found in many angiosperm families. Several cultivars of tree peony contain a single red or purple spot at the base of petal that makes the flower more attractive for the ornamental market. So far, the understanding of the molecular mechanism of spot formation is inadequate. In this study, we sequenced the transcriptome of the purple spot and the white non-spot of tree peony flower. We assembled and annotated 67,892 unigenes. Comparative analyses of the two transcriptomes showed 1,573 differentially expressed genes, among which 933 were up-regulated, and 640 were down-regulated in the purple spot. Subsequently, we examined four anthocyanin structural genes, including PsCHS, PsF3′H, PsDFR, and PsANS, which expressed at a significantly higher level in the purple spot than in the white non-spot. We further validated the digital expression data using quantitative real-time PCR. Our result uncovered transcriptome variance between the spot and non-spot of tree peony flower, and revealed that the co-expression of four anthocyanin structural genes was responsible for spot pigment in tree peony. The data will further help to unravel the genetic mechanism of peony flower spot formation. PMID:26583029

The use of laser microdissection in the identification of suitable reference genes for normalization of quantitative real-time PCR in human FFPE epithelial ovarian tissue samples.

PubMed

Cai, Jing; Li, Tao; Huang, Bangxing; Cheng, Henghui; Ding, Hui; Dong, Weihong; Xiao, Man; Liu, Ling; Wang, Zehua

2014-01-01

Quantitative real-time PCR (qPCR) is a powerful and reproducible method of gene expression analysis in which expression levels are quantified by normalization against reference genes. Therefore, to investigate the potential biomarkers and therapeutic targets for epithelial ovarian cancer by qPCR, it is critical to identify stable reference genes. In this study, twelve housekeeping genes (ACTB, GAPDH, 18S rRNA, GUSB, PPIA, PBGD, PUM1, TBP, HRPT1, RPLP0, RPL13A, and B2M) were analyzed in 50 ovarian samples from normal, benign, borderline, and malignant tissues. For reliable results, laser microdissection (LMD), an effective technique used to prepare homogeneous starting material, was utilized to precisely excise target tissues or cells. One-way analysis of variance (ANOVA) and nonparametric (Kruskal-Wallis) tests were used to compare the expression differences. NormFinder and geNorm software were employed to further validate the suitability and stability of the candidate genes. Results showed that epithelial cells occupied a small percentage of the normal ovary indeed. The expression of ACTB, PPIA, RPL13A, RPLP0, and TBP were stable independent of the disease progression. In addition, NormFinder and geNorm identified the most stable combination (ACTB, PPIA, RPLP0, and TBP) and the relatively unstable reference gene GAPDH from the twelve commonly used housekeeping genes. Our results highlight the use of homogeneous ovarian tissues and multiple-reference normalization strategy, e.g. the combination of ACTB, PPIA, RPLP0, and TBP, for qPCR in epithelial ovarian tissues, whereas GAPDH, the most commonly used reference gene, is not recommended, especially as a single reference gene.

No Control Genes Required: Bayesian Analysis of qRT-PCR Data

PubMed Central

Matz, Mikhail V.; Wright, Rachel M.; Scott, James G.

2013-01-01

Background Model-based analysis of data from quantitative reverse-transcription PCR (qRT-PCR) is potentially more powerful and versatile than traditional methods. Yet existing model-based approaches cannot properly deal with the higher sampling variances associated with low-abundant targets, nor do they provide a natural way to incorporate assumptions about the stability of control genes directly into the model-fitting process. Results In our method, raw qPCR data are represented as molecule counts, and described using generalized linear mixed models under Poisson-lognormal error. A Markov Chain Monte Carlo (MCMC) algorithm is used to sample from the joint posterior distribution over all model parameters, thereby estimating the effects of all experimental factors on the expression of every gene. The Poisson-based model allows for the correct specification of the mean-variance relationship of the PCR amplification process, and can also glean information from instances of no amplification (zero counts). Our method is very flexible with respect to control genes: any prior knowledge about the expected degree of their stability can be directly incorporated into the model. Yet the method provides sensible answers without such assumptions, or even in the complete absence of control genes. We also present a natural Bayesian analogue of the “classic” analysis, which uses standard data pre-processing steps (logarithmic transformation and multi-gene normalization) but estimates all gene expression changes jointly within a single model. The new methods are considerably more flexible and powerful than the standard delta-delta Ct analysis based on pairwise t-tests. Conclusions Our methodology expands the applicability of the relative-quantification analysis protocol all the way to the lowest-abundance targets, and provides a novel opportunity to analyze qRT-PCR data without making any assumptions concerning target stability. These procedures have been implemented as the MCMC.qpcr package in R. PMID:23977043

Coordinated transcriptional regulation patterns associated with infertility phenotypes in men

PubMed Central

Ellis, Peter J I; Furlong, Robert A; Conner, Sarah J; Kirkman‐Brown, Jackson; Afnan, Masoud; Barratt, Christopher; Griffin, Darren K; Affara, Nabeel A

2007-01-01

Introduction Microarray gene‐expression profiling is a powerful tool for global analysis of the transcriptional consequences of disease phenotypes. Understanding the genetic correlates of particular pathological states is important for more accurate diagnosis and screening of patients, and thus for suggesting appropriate avenues of treatment. As yet, there has been little research describing gene‐expression profiling of infertile and subfertile men, and thus the underlying transcriptional events involved in loss of spermatogenesis remain unclear. Here we present the results of an initial screen of 33 patients with differing spermatogenic phenotypes. Methods Oligonucleotide array expression profiling was performed on testis biopsies for 33 patients presenting for testicular sperm extraction. Significantly regulated genes were selected using a mixed model analysis of variance. Principle components analysis and hierarchical clustering were used to interpret the resulting dataset with reference to the patient history, clinical findings and histological composition of the biopsies. Results Striking patterns of coordinated gene expression were found. The most significant contains multiple germ cell‐specific genes and corresponds to the degree of successful spermatogenesis in each patient, whereas a second pattern corresponds to inflammatory activity within the testis. Smaller‐scale patterns were also observed, relating to unique features of the individual biopsies. PMID:17496197

Genetic and Genomic Response to Selection for Food Consumption in Drosophila melanogaster

PubMed Central

Garlapow, Megan E.; Everett, Logan J.; Zhou, Shanshan; Gearhart, Alexander W.; Fay, Kairsten A.; Huang, Wen; Morozova, Tatiana V.; Arya, Gunjan H.; Turlapati, Lavanya; Armour, Genevieve St.; Hussain, Yasmeen N.; McAdams, Sarah E.; Fochler, Sophia; Mackay, Trudy F. C.

2016-01-01

Food consumption is an essential component of animal fitness; however, excessive food intake in humans increases risk for many diseases. The roles of neuroendocrine feedback loops, food sensing modalities, and physiological state in regulating food intake are well understood, but not the genetic basis underlying variation in food consumption. Here, we applied ten generations of artificial selection for high and low food consumption in replicate populations of Drosophila melanogaster. The phenotypic response to selection was highly asymmetric, with significant responses only for increased food consumption and minimal correlated responses in body mass and composition. We assessed the molecular correlates of selection responses by DNA and RNA sequencing of the selection lines. The high and low selection lines had variants with significantly divergent allele frequencies within or near 2,081 genes and 3,526 differentially expressed genes in one or both sexes. A total of 519 genes were both genetically divergent and differentially expressed between the divergent selection lines. We performed functional analyses of the effects of RNAi suppression of gene expression and induced mutations for 27 of these candidate genes that have human orthologs and the strongest statistical support, and confirmed that 25 (93%) affected the mean and/or variance of food consumption. PMID:27704301

Spectral gene set enrichment (SGSE).

PubMed

Frost, H Robert; Li, Zhigang; Moore, Jason H

2015-03-03

Gene set testing is typically performed in a supervised context to quantify the association between groups of genes and a clinical phenotype. In many cases, however, a gene set-based interpretation of genomic data is desired in the absence of a phenotype variable. Although methods exist for unsupervised gene set testing, they predominantly compute enrichment relative to clusters of the genomic variables with performance strongly dependent on the clustering algorithm and number of clusters. We propose a novel method, spectral gene set enrichment (SGSE), for unsupervised competitive testing of the association between gene sets and empirical data sources. SGSE first computes the statistical association between gene sets and principal components (PCs) using our principal component gene set enrichment (PCGSE) method. The overall statistical association between each gene set and the spectral structure of the data is then computed by combining the PC-level p-values using the weighted Z-method with weights set to the PC variance scaled by Tracy-Widom test p-values. Using simulated data, we show that the SGSE algorithm can accurately recover spectral features from noisy data. To illustrate the utility of our method on real data, we demonstrate the superior performance of the SGSE method relative to standard cluster-based techniques for testing the association between MSigDB gene sets and the variance structure of microarray gene expression data. Unsupervised gene set testing can provide important information about the biological signal held in high-dimensional genomic data sets. Because it uses the association between gene sets and samples PCs to generate a measure of unsupervised enrichment, the SGSE method is independent of cluster or network creation algorithms and, most importantly, is able to utilize the statistical significance of PC eigenvalues to ignore elements of the data most likely to represent noise.

Global Gene Expression Differences in Joints of Mice with Divergent Post Traumatic Osteoarthritis Phenotypes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kibui, J.

Osteoarthritis (OA) is a debilitating joint disease characterized by cartilage degradation which prompts pain, stiffness and swelling. Contributing factors include age, genetics, obesity, injury and overuse of joints. OA is defined by an acute phase and a chronic phase whereby inflammation and degeneration of articular cartilage and other tissues is followed by joint pain and limited mobility. Patients remain asymptomatic until substantial joint damage has occurred and therefore rely on long term surgical joint replacement and pain management as their sole treatment options. For this reason, there is an increasing need to identify early stage osteoarthritis biomarkers. Our study aimedmore » to identify and characterize gene expression variances in 3 different mouse strains (STR/ort, C57BL/6 and MRL/MpJ) with different susceptibility to post traumatic osteoarthritis (PTOA). Through RNA sequence analysis of whole knee joint RNA, we identified differentially expressed genes associated with the initial stages of PTOA in relation to mice with divergent phenotypes. These results will help elucidate potential mechanisms responsible for PTOA outcomes.« less

Meta-Analysis of Placental Transcriptome Data Identifies a Novel Molecular Pathway Related to Preeclampsia.

PubMed

van Uitert, Miranda; Moerland, Perry D; Enquobahrie, Daniel A; Laivuori, Hannele; van der Post, Joris A M; Ris-Stalpers, Carrie; Afink, Gijs B

2015-01-01

Studies using the placental transcriptome to identify key molecules relevant for preeclampsia are hampered by a relatively small sample size. In addition, they use a variety of bioinformatics and statistical methods, making comparison of findings challenging. To generate a more robust preeclampsia gene expression signature, we performed a meta-analysis on the original data of 11 placenta RNA microarray experiments, representing 139 normotensive and 116 preeclamptic pregnancies. Microarray data were pre-processed and analyzed using standardized bioinformatics and statistical procedures and the effect sizes were combined using an inverse-variance random-effects model. Interactions between genes in the resulting gene expression signature were identified by pathway analysis (Ingenuity Pathway Analysis, Gene Set Enrichment Analysis, Graphite) and protein-protein associations (STRING). This approach has resulted in a comprehensive list of differentially expressed genes that led to a 388-gene meta-signature of preeclamptic placenta. Pathway analysis highlights the involvement of the previously identified hypoxia/HIF1A pathway in the establishment of the preeclamptic gene expression profile, while analysis of protein interaction networks indicates CREBBP/EP300 as a novel element central to the preeclamptic placental transcriptome. In addition, there is an apparent high incidence of preeclampsia in women carrying a child with a mutation in CREBBP/EP300 (Rubinstein-Taybi Syndrome). The 388-gene preeclampsia meta-signature offers a vital starting point for further studies into the relevance of these genes (in particular CREBBP/EP300) and their concomitant pathways as biomarkers or functional molecules in preeclampsia. This will result in a better understanding of the molecular basis of this disease and opens up the opportunity to develop rational therapies targeting the placental dysfunction causal to preeclampsia.

Cuticular lipid composition, surface structure, and gene expression in Arabidopsis stem epidermis.

PubMed

Suh, Mi Chung; Samuels, A Lacey; Jetter, Reinhard; Kunst, Ljerka; Pollard, Mike; Ohlrogge, John; Beisson, Fred

2005-12-01

All vascular plants are protected from the environment by a cuticle, a lipophilic layer synthesized by epidermal cells and composed of a cutin polymer matrix and waxes. The mechanism by which epidermal cells accumulate and assemble cuticle components in rapidly expanding organs is largely unknown. We have begun to address this question by analyzing the lipid compositional variance, the surface micromorphology, and the transcriptome of epidermal cells in elongating Arabidopsis (Arabidopsis thaliana) stems. The rate of cell elongation is maximal near the apical meristem and decreases steeply toward the middle of the stem, where it is 10 times slower. During and after this elongation, the cuticular wax load and composition remain remarkably constant (32 microg/cm2), indicating that the biosynthetic flux into waxes is closely matched to surface area expansion. By contrast, the load of polyester monomers per unit surface area decreases more than 2-fold from the upper (8 microg/cm2) to the lower (3 microg/cm2) portion of the stem, although the compositional variance is minor. To aid identification of proteins involved in the biosynthesis of waxes and cutin, we have isolated epidermal peels from Arabidopsis stems and determined transcript profiles in both rapidly expanding and nonexpanding cells. This transcriptome analysis was validated by the correct classification of known epidermis-specific genes. The 15% transcripts preferentially expressed in the epidermis were enriched in genes encoding proteins predicted to be membrane associated and involved in lipid metabolism. An analysis of the lipid-related subset is presented.

Triiodothyronine (T3) induces HIF1A and TGFA expression in MCF7 cells by activating PI3K.

PubMed

Moretto, Fernanda Cristina Fontes; De Sibio, Maria Teresa; Luvizon, Aline Carbonera; Olimpio, Regiane Marques Castro; de Oliveira, Miriane; Alves, Carlos Augusto Barnabe; Conde, Sandro José; Nogueira, Célia Regina

2016-06-01

High expression levels of hypoxia inducing factor 1 alpha are related to mammary carcinogenesis. In previous studies, we demonstrated that expression of transforming growth factor alpha increases upon treatment with triiodothyronine, but this expression does not occur in cellular models that do not express the estrogen receptor, or when cells are co-treated with the anti-estrogen, tamoxifen. The aim of this study was to determine the effect of the hormone triiodothyronine on the expression of the genes HIF1A and TGFA in the breast cancer cell line MCF7. The cell line was subjected to treatment with triiodothyronine at the supraphysiological dose of 10(-8)M for 10min, 30min, 1h, and 4h in the presence or absence of actinomycin D, the gene expression inhibitor, cycloheximide, the protein synthesis inhibitor, and LY294002, the phosphoinositide 3 kinase inhibitor. HIF1A and TGFA mRNA expression was analyzed by reverse transcription polymerase chain reaction. For data analysis, we used analysis of variance complemented by Tukey test and an adopted minimum of 5% significance. We found that HIF1A and TGFA expression increased in the presence of triiodothyronine at all times studied. HIF1A expression decreased in triiodothyronine-treated cells when gene transcription was also inhibited; however, TGFA expression decreased after 10 and 30min of treatment even when transcription was not inhibited. We found that activation of PI3K was necessary for triiodothyronine to modulate HIF1A and TGFA expression. Copyright © 2016 Elsevier Inc. All rights reserved.

A powerful and flexible approach to the analysis of RNA sequence count data.

PubMed

Zhou, Yi-Hui; Xia, Kai; Wright, Fred A

2011-10-01

A number of penalization and shrinkage approaches have been proposed for the analysis of microarray gene expression data. Similar techniques are now routinely applied to RNA sequence transcriptional count data, although the value of such shrinkage has not been conclusively established. If penalization is desired, the explicit modeling of mean-variance relationships provides a flexible testing regimen that 'borrows' information across genes, while easily incorporating design effects and additional covariates. We describe BBSeq, which incorporates two approaches: (i) a simple beta-binomial generalized linear model, which has not been extensively tested for RNA-Seq data and (ii) an extension of an expression mean-variance modeling approach to RNA-Seq data, involving modeling of the overdispersion as a function of the mean. Our approaches are flexible, allowing for general handling of discrete experimental factors and continuous covariates. We report comparisons with other alternate methods to handle RNA-Seq data. Although penalized methods have advantages for very small sample sizes, the beta-binomial generalized linear model, combined with simple outlier detection and testing approaches, appears to have favorable characteristics in power and flexibility. An R package containing examples and sample datasets is available at http://www.bios.unc.edu/research/genomic_software/BBSeq yzhou@bios.unc.edu; fwright@bios.unc.edu Supplementary data are available at Bioinformatics online.

Changes in Dorsal Root Ganglion Gene Expression in Response to Spinal Cord Stimulation.

PubMed

Tilley, Dana M; Cedeño, David L; Kelley, Courtney A; DeMaegd, Margaret; Benyamin, Ramsin; Vallejo, Ricardo

Spinal cord stimulation (SCS) has been shown to influence pain-related genes in the spinal cord directly under the stimulating electrodes. There is limited information regarding changes occurring at the dorsal root ganglion (DRG). This study evaluates gene expression in the DRG in response to SCS therapy. Rats were randomized into experimental or control groups (n = 6 per group). Experimental animals underwent spared-nerve injury, implantation of lead, and continuous SCS (72 hours). Behavioral assessment for mechanical hyperalgesia was conducted to compare responses after injury and treatment. Ipsilateral DRG tissue was collected, and gene expression quantified for interleukin 1b (IL-1b), interleukin 6 (IL-6), tumor necrosis factor α (TNF-α), GABA B receptor 1 (GABAbr1), substance P (subP), Integrin alpha M (ITGAM), sodium/potassium ATP-ase (Na/K ATPase), fos proto-oncogene (cFOS), serotonin receptor 3A (5HT3r), galanin (Gal), vasoactive intestinal peptide (VIP), neuropeptide Y (NpY), glial fibrillary acidic protein (GFAP), and brain derived neurotropic factor (BDNF) via quantitative polymerase chain reaction. Statistical significance was established using analysis of variance (ANOVA), independent t tests, and Pearson correlation tests. Expression of IL-1b and IL-6 was reversed following SCS therapy relative to the increase caused by the injury model. Both GABAbr1 and Na/K ATPase were significantly up-regulated upon implantation of the lead, and SCS therapy reversed their expression to within control levels. Pearson correlation analyses reveal that GABAbr1 and Na/K ATPase expression was dependent on the stimulating current intensity. Spinal cord stimulation modulates expression of key pain-related genes in the DRG. Specifically, SCS led to reversal of IL-1b and IL-6 expression induced by injury. Interleukin 6 expression was still significantly larger than in sham animals, which may correlate to residual sensitivity following continuous SCS treatment. In addition, expression of GABAbr1 and Na/K ATPase was down-regulated to within control levels following SCS and correlates with applied current.

Model-based variance-stabilizing transformation for Illumina microarray data.

PubMed

Lin, Simon M; Du, Pan; Huber, Wolfgang; Kibbe, Warren A

2008-02-01

Variance stabilization is a step in the preprocessing of microarray data that can greatly benefit the performance of subsequent statistical modeling and inference. Due to the often limited number of technical replicates for Affymetrix and cDNA arrays, achieving variance stabilization can be difficult. Although the Illumina microarray platform provides a larger number of technical replicates on each array (usually over 30 randomly distributed beads per probe), these replicates have not been leveraged in the current log2 data transformation process. We devised a variance-stabilizing transformation (VST) method that takes advantage of the technical replicates available on an Illumina microarray. We have compared VST with log2 and Variance-stabilizing normalization (VSN) by using the Kruglyak bead-level data (2006) and Barnes titration data (2005). The results of the Kruglyak data suggest that VST stabilizes variances of bead-replicates within an array. The results of the Barnes data show that VST can improve the detection of differentially expressed genes and reduce false-positive identifications. We conclude that although both VST and VSN are built upon the same model of measurement noise, VST stabilizes the variance better and more efficiently for the Illumina platform by leveraging the availability of a larger number of within-array replicates. The algorithms and Supplementary Data are included in the lumi package of Bioconductor, available at: www.bioconductor.org.

Nonlinear Dynamics in Gene Regulation Promote Robustness and Evolvability of Gene Expression Levels.

PubMed

Steinacher, Arno; Bates, Declan G; Akman, Ozgur E; Soyer, Orkun S

2016-01-01

Cellular phenotypes underpinned by regulatory networks need to respond to evolutionary pressures to allow adaptation, but at the same time be robust to perturbations. This creates a conflict in which mutations affecting regulatory networks must both generate variance but also be tolerated at the phenotype level. Here, we perform mathematical analyses and simulations of regulatory networks to better understand the potential trade-off between robustness and evolvability. Examining the phenotypic effects of mutations, we find an inverse correlation between robustness and evolvability that breaks only with nonlinearity in the network dynamics, through the creation of regions presenting sudden changes in phenotype with small changes in genotype. For genotypes embedding low levels of nonlinearity, robustness and evolvability correlate negatively and almost perfectly. By contrast, genotypes embedding nonlinear dynamics allow expression levels to be robust to small perturbations, while generating high diversity (evolvability) under larger perturbations. Thus, nonlinearity breaks the robustness-evolvability trade-off in gene expression levels by allowing disparate responses to different mutations. Using analytical derivations of robustness and system sensitivity, we show that these findings extend to a large class of gene regulatory network architectures and also hold for experimentally observed parameter regimes. Further, the effect of nonlinearity on the robustness-evolvability trade-off is ensured as long as key parameters of the system display specific relations irrespective of their absolute values. We find that within this parameter regime genotypes display low and noisy expression levels. Examining the phenotypic effects of mutations, we find an inverse correlation between robustness and evolvability that breaks only with nonlinearity in the network dynamics. Our results provide a possible solution to the robustness-evolvability trade-off, suggest an explanation for the ubiquity of nonlinear dynamics in gene expression networks, and generate useful guidelines for the design of synthetic gene circuits.

Bayesian inference of the number of factors in gene-expression analysis: application to human virus challenge studies.

PubMed

Chen, Bo; Chen, Minhua; Paisley, John; Zaas, Aimee; Woods, Christopher; Ginsburg, Geoffrey S; Hero, Alfred; Lucas, Joseph; Dunson, David; Carin, Lawrence

2010-11-09

Nonparametric Bayesian techniques have been developed recently to extend the sophistication of factor models, allowing one to infer the number of appropriate factors from the observed data. We consider such techniques for sparse factor analysis, with application to gene-expression data from three virus challenge studies. Particular attention is placed on employing the Beta Process (BP), the Indian Buffet Process (IBP), and related sparseness-promoting techniques to infer a proper number of factors. The posterior density function on the model parameters is computed using Gibbs sampling and variational Bayesian (VB) analysis. Time-evolving gene-expression data are considered for respiratory syncytial virus (RSV), Rhino virus, and influenza, using blood samples from healthy human subjects. These data were acquired in three challenge studies, each executed after receiving institutional review board (IRB) approval from Duke University. Comparisons are made between several alternative means of per-forming nonparametric factor analysis on these data, with comparisons as well to sparse-PCA and Penalized Matrix Decomposition (PMD), closely related non-Bayesian approaches. Applying the Beta Process to the factor scores, or to the singular values of a pseudo-SVD construction, the proposed algorithms infer the number of factors in gene-expression data. For real data the "true" number of factors is unknown; in our simulations we consider a range of noise variances, and the proposed Bayesian models inferred the number of factors accurately relative to other methods in the literature, such as sparse-PCA and PMD. We have also identified a "pan-viral" factor of importance for each of the three viruses considered in this study. We have identified a set of genes associated with this pan-viral factor, of interest for early detection of such viruses based upon the host response, as quantified via gene-expression data.

Reliable Gene Expression Measurements from Fine Needle Aspirates of Pancreatic Tumors

PubMed Central

Anderson, Michelle A.; Brenner, Dean E.; Scheiman, James M.; Simeone, Diane M.; Singh, Nalina; Sikora, Matthew J.; Zhao, Lili; Mertens, Amy N.; Rae, James M.

2010-01-01

Background and aims: Biomarker use for pancreatic cancer diagnosis has been impaired by a lack of samples suitable for reliable quantitative RT-PCR (qRT-PCR). Fine needle aspirates (FNAs) from pancreatic masses were studied to define potential causes of RNA degradation and develop methods for accurately measuring gene expression. Methods: Samples from 32 patients were studied. RNA degradation was assessed by using a multiplex PCR assay for varying lengths of glyceraldehyde-3-phosphate dehydrogenase, and effects on qRT-PCR were determined by using a 150-bp and a 80-bp amplicon for RPS6. Potential causes of and methods to circumvent RNA degradation were studied by using FNAs from a pancreatic cancer xenograft. Results: RNA extracted from pancreatic mass FNAs was extensively degraded. Fragmentation was related to needle bore diameter and could not be overcome by alterations in aspiration technique. Multiplex PCR for glyceraldehyde-3-phosphate dehydrogenase could distinguish samples that were suitable for qRT-PCR. The use of short PCR amplicons (<100 bp) provided reliable gene expression analysis from FNAs. When appropriate samples were used, the assay was highly reproducible for gene copy number with minimal (0.0003 or about 0.7% of total) variance. Conclusions: The degraded properties of endoscopic FNAs markedly affect the accuracy of gene expression measurements. Our novel approach to designate specimens “informative” for qRT-PCR allowed accurate molecular assessment for the diagnosis of pancreatic diseases. PMID:20709792

A Practical Platform for Blood Biomarker Study by Using Global Gene Expression Profiling of Peripheral Whole Blood

PubMed Central

Schmid, Patrick; Yao, Hui; Galdzicki, Michal; Berger, Bonnie; Wu, Erxi; Kohane, Isaac S.

2009-01-01

Background Although microarray technology has become the most common method for studying global gene expression, a plethora of technical factors across the experiment contribute to the variable of genome gene expression profiling using peripheral whole blood. A practical platform needs to be established in order to obtain reliable and reproducible data to meet clinical requirements for biomarker study. Methods and Findings We applied peripheral whole blood samples with globin reduction and performed genome-wide transcriptome analysis using Illumina BeadChips. Real-time PCR was subsequently used to evaluate the quality of array data and elucidate the mode in which hemoglobin interferes in gene expression profiling. We demonstrated that, when applied in the context of standard microarray processing procedures, globin reduction results in a consistent and significant increase in the quality of beadarray data. When compared to their pre-globin reduction counterparts, post-globin reduction samples show improved detection statistics, lowered variance and increased sensitivity. More importantly, gender gene separation is remarkably clearer in post-globin reduction samples than in pre-globin reduction samples. Our study suggests that the poor data obtained from pre-globin reduction samples is the result of the high concentration of hemoglobin derived from red blood cells either interfering with target mRNA binding or giving the pseudo binding background signal. Conclusion We therefore recommend the combination of performing globin mRNA reduction in peripheral whole blood samples and hybridizing on Illumina BeadChips as the practical approach for biomarker study. PMID:19381341

ArraySolver: an algorithm for colour-coded graphical display and Wilcoxon signed-rank statistics for comparing microarray gene expression data.

PubMed

Khan, Haseeb Ahmad

2004-01-01

The massive surge in the production of microarray data poses a great challenge for proper analysis and interpretation. In recent years numerous computational tools have been developed to extract meaningful interpretation of microarray gene expression data. However, a convenient tool for two-groups comparison of microarray data is still lacking and users have to rely on commercial statistical packages that might be costly and require special skills, in addition to extra time and effort for transferring data from one platform to other. Various statistical methods, including the t-test, analysis of variance, Pearson test and Mann-Whitney U test, have been reported for comparing microarray data, whereas the utilization of the Wilcoxon signed-rank test, which is an appropriate test for two-groups comparison of gene expression data, has largely been neglected in microarray studies. The aim of this investigation was to build an integrated tool, ArraySolver, for colour-coded graphical display and comparison of gene expression data using the Wilcoxon signed-rank test. The results of software validation showed similar outputs with ArraySolver and SPSS for large datasets. Whereas the former program appeared to be more accurate for 25 or fewer pairs (n < or = 25), suggesting its potential application in analysing molecular signatures that usually contain small numbers of genes. The main advantages of ArraySolver are easy data selection, convenient report format, accurate statistics and the familiar Excel platform.

ArraySolver: An Algorithm for Colour-Coded Graphical Display and Wilcoxon Signed-Rank Statistics for Comparing Microarray Gene Expression Data

PubMed Central

2004-01-01

The massive surge in the production of microarray data poses a great challenge for proper analysis and interpretation. In recent years numerous computational tools have been developed to extract meaningful interpretation of microarray gene expression data. However, a convenient tool for two-groups comparison of microarray data is still lacking and users have to rely on commercial statistical packages that might be costly and require special skills, in addition to extra time and effort for transferring data from one platform to other. Various statistical methods, including the t-test, analysis of variance, Pearson test and Mann–Whitney U test, have been reported for comparing microarray data, whereas the utilization of the Wilcoxon signed-rank test, which is an appropriate test for two-groups comparison of gene expression data, has largely been neglected in microarray studies. The aim of this investigation was to build an integrated tool, ArraySolver, for colour-coded graphical display and comparison of gene expression data using the Wilcoxon signed-rank test. The results of software validation showed similar outputs with ArraySolver and SPSS for large datasets. Whereas the former program appeared to be more accurate for 25 or fewer pairs (n ≤ 25), suggesting its potential application in analysing molecular signatures that usually contain small numbers of genes. The main advantages of ArraySolver are easy data selection, convenient report format, accurate statistics and the familiar Excel platform. PMID:18629036

A Hybrid One-Way ANOVA Approach for the Robust and Efficient Estimation of Differential Gene Expression with Multiple Patterns

PubMed Central

Mollah, Mohammad Manir Hossain; Jamal, Rahman; Mokhtar, Norfilza Mohd; Harun, Roslan; Mollah, Md. Nurul Haque

2015-01-01

Background Identifying genes that are differentially expressed (DE) between two or more conditions with multiple patterns of expression is one of the primary objectives of gene expression data analysis. Several statistical approaches, including one-way analysis of variance (ANOVA), are used to identify DE genes. However, most of these methods provide misleading results for two or more conditions with multiple patterns of expression in the presence of outlying genes. In this paper, an attempt is made to develop a hybrid one-way ANOVA approach that unifies the robustness and efficiency of estimation using the minimum β-divergence method to overcome some problems that arise in the existing robust methods for both small- and large-sample cases with multiple patterns of expression. Results The proposed method relies on a β-weight function, which produces values between 0 and 1. The β-weight function with β = 0.2 is used as a measure of outlier detection. It assigns smaller weights (≥ 0) to outlying expressions and larger weights (≤ 1) to typical expressions. The distribution of the β-weights is used to calculate the cut-off point, which is compared to the observed β-weight of an expression to determine whether that gene expression is an outlier. This weight function plays a key role in unifying the robustness and efficiency of estimation in one-way ANOVA. Conclusion Analyses of simulated gene expression profiles revealed that all eight methods (ANOVA, SAM, LIMMA, EBarrays, eLNN, KW, robust BetaEB and proposed) perform almost identically for m = 2 conditions in the absence of outliers. However, the robust BetaEB method and the proposed method exhibited considerably better performance than the other six methods in the presence of outliers. In this case, the BetaEB method exhibited slightly better performance than the proposed method for the small-sample cases, but the the proposed method exhibited much better performance than the BetaEB method for both the small- and large-sample cases in the presence of more than 50% outlying genes. The proposed method also exhibited better performance than the other methods for m > 2 conditions with multiple patterns of expression, where the BetaEB was not extended for this condition. Therefore, the proposed approach would be more suitable and reliable on average for the identification of DE genes between two or more conditions with multiple patterns of expression. PMID:26413858

Elasmobranch qPCR reference genes: a case study of hypoxia preconditioned epaulette sharks

PubMed Central

2010-01-01

Background Elasmobranch fishes are an ancient group of vertebrates which have high potential as model species for research into evolutionary physiology and genomics. However, no comparative studies have established suitable reference genes for quantitative PCR (qPCR) in elasmobranchs for any physiological conditions. Oxygen availability has been a major force shaping the physiological evolution of vertebrates, especially fishes. Here we examined the suitability of 9 reference candidates from various functional categories after a single hypoxic insult or after hypoxia preconditioning in epaulette shark (Hemiscyllium ocellatum). Results Epaulette sharks were caught and exposed to hypoxia. Tissues were collected from 10 controls, 10 individuals with single hypoxic insult and 10 individuals with hypoxia preconditioning (8 hypoxic insults, 12 hours apart). We produced sequence information for reference gene candidates and monitored mRNA expression levels in four tissues: cerebellum, heart, gill and eye. The stability of the genes was examined with analysis of variance, geNorm and NormFinder. The best ranking genes in our study were eukaryotic translation elongation factor 1 beta (eef1b), ubiquitin (ubq) and polymerase (RNA) II (DNA directed) polypeptide F (polr2f). The performance of the ribosomal protein L6 (rpl6) was tissue-dependent. Notably, in one tissue the analysis of variance indicated statistically significant differences between treatments for genes that were ranked as the most stable candidates by reference gene software. Conclusions Our results indicate that eef1b and ubq are generally the most suitable reference genes for the conditions and tissues in the present epaulette shark studies. These genes could also be potential reference gene candidates for other physiological studies examining stress in elasmobranchs. The results emphasise the importance of inter-group variation in reference gene evaluation. PMID:20416043

Dissection of Insertion–Deletion Variants within Differentially Expressed Genes Involved in Wood Formation in Populus

PubMed Central

Gong, Chenrui; Du, Qingzhang; Xie, Jianbo; Quan, Mingyang; Chen, Beibei; Zhang, Deqiang

2018-01-01

Short insertions and deletions (InDels) are one of the major genetic variants and are distributed widely across the genome; however, few investigations of InDels have been conducted in long-lived perennial plants. Here, we employed a combination of RNA-seq and population resequencing to identify InDels within differentially expressed (DE) genes underlying wood formation in a natural population of Populus tomentosa (435 individuals) and utilized InDel-based association mapping to detect the causal variants under additive, dominance, and epistasis underlying growth and wood properties. In the present paper, 5,482 InDels detected from 629 DE genes showed uneven distributions throughout all 19 chromosomes, and 95.9% of these loci were diallelic InDels. Seventy-four InDels (positive false discovery rate q ≤ 0.10) from 68 genes exhibited significant additive/dominant effects on 10 growth and wood-properties, with an average of 14.7% phenotypic variance explained. Potential pleiotropy was observed in one-third of the InDels (representing 24 genes). Seven genes exhibited significantly differential expression among the genotypic classes of associated InDels, indicating possible important roles for these InDels. Epistasis analysis showed that overlapping interacting genes formed unique interconnected networks for each trait, supporting the putative biochemical links that control quantitative traits. Therefore, the identification and utilization of InDels in trees will be recognized as an effective marker system for molecular marker-assisted breeding applications, and further facilitate our understanding of quantitative genomics. PMID:29403506

Genetic mechanisms underlying the methylation level of anthocyanins in grape (Vitis vinifera L.)

PubMed Central

2011-01-01

Background Plant color variation is due not only to the global pigment concentration but also to the proportion of different types of pigment. Variation in the color spectrum may arise from secondary modifications, such as hydroxylation and methylation, affecting the chromatic properties of pigments. In grapes (Vitis vinifera L.), the level of methylation modifies the stability and reactivity of anthocyanin, which directly influence the color of the berry. Anthocyanin methylation, as a complex trait, is controlled by multiple molecular factors likely to involve multiple regulatory steps. Results In a Syrah × Grenache progeny, two QTLs were detected for variation in level of anthocyanin methylation. The first one, explaining up to 27% of variance, colocalized with a cluster of Myb-type transcription factor genes. The second one, explaining up to 20% of variance, colocalized with a cluster of O-methyltransferase coding genes (AOMT). In a collection of 32 unrelated cultivars, MybA and AOMT expression profiles correlated with the level of methylated anthocyanin. In addition, the newly characterized AOMT2 gene presented two SNPs associated with methylation level. These mutations, probably leading to a structural change of the AOMT2 protein significantly affected the enzyme specific catalytic efficiency for the 3'-O-methylation of delphinidin 3-glucoside. Conclusion We demonstrated that variation in methylated anthocyanin accumulation is susceptible to involve both transcriptional regulation and structural variation. We report here the identification of novel AOMT variants likely to cause methylated anthocyanin variation. The integration of QTL mapping and molecular approaches enabled a better understanding of how variation in gene expression and catalytic efficiency of the resulting enzyme may influence the grape anthocyanin profile. PMID:22171701

Identification and characterization of nuclear genes involved in photosynthesis in Populus

PubMed Central

2014-01-01

Background The gap between the real and potential photosynthetic rate under field conditions suggests that photosynthesis could potentially be improved. Nuclear genes provide possible targets for improving photosynthetic efficiency. Hence, genome-wide identification and characterization of the nuclear genes affecting photosynthetic traits in woody plants would provide key insights on genetic regulation of photosynthesis and identify candidate processes for improvement of photosynthesis. Results Using microarray and bulked segregant analysis strategies, we identified differentially expressed nuclear genes for photosynthesis traits in a segregating population of poplar. We identified 515 differentially expressed genes in this population (FC ≥ 2 or FC ≤ 0.5, P < 0.05), 163 up-regulated and 352 down-regulated. Real-time PCR expression analysis confirmed the microarray data. Singular Enrichment Analysis identified 48 significantly enriched GO terms for molecular functions (28), biological processes (18) and cell components (2). Furthermore, we selected six candidate genes for functional examination by a single-marker association approach, which demonstrated that 20 SNPs in five candidate genes significantly associated with photosynthetic traits, and the phenotypic variance explained by each SNP ranged from 2.3% to 12.6%. This revealed that regulation of photosynthesis by the nuclear genome mainly involves transport, metabolism and response to stimulus functions. Conclusions This study provides new genome-scale strategies for the discovery of potential candidate genes affecting photosynthesis in Populus, and for identification of the functions of genes involved in regulation of photosynthesis. This work also suggests that improving photosynthetic efficiency under field conditions will require the consideration of multiple factors, such as stress responses. PMID:24673936

Gene expression profiles in rainbow trout, Onchorynchus mykiss, exposed to a simple chemical mixture.

PubMed

Hook, Sharon E; Skillman, Ann D; Gopalan, Banu; Small, Jack A; Schultz, Irvin R

2008-03-01

Among proposed uses for microarrays in environmental toxiciology is the identification of key contributors to toxicity within a mixture. However, it remains uncertain whether the transcriptomic profiles resulting from exposure to a mixture have patterns of altered gene expression that contain identifiable contributions from each toxicant component. We exposed isogenic rainbow trout Onchorynchus mykiss, to sublethal levels of ethynylestradiol, 2,2,4,4-tetrabromodiphenyl ether, and chromium VI or to a mixture of all three toxicants Fluorescently labeled complementary DNA (cDNA) were generated and hybridized against a commercially available Salmonid array spotted with 16,000 cDNAs. Data were analyzed using analysis of variance (p<0.05) with a Benjamani-Hochberg multiple test correction (Genespring [Agilent] software package) to identify up and downregulated genes. Gene clustering patterns that can be used as "expression signatures" were determined using hierarchical cluster analysis. The gene ontology terms associated with significantly altered genes were also used to identify functional groups that were associated with toxicant exposure. Cross-ontological analytics approach was used to assign functional annotations to genes with "unknown" function. Our analysis indicates that transcriptomic profiles resulting from the mixture exposure resemble those of the individual contaminant exposures, but are not a simple additive list. However, patterns of altered genes representative of each component of the mixture are clearly discernible, and the functional classes of genes altered represent the individual components of the mixture. These findings indicate that the use of microarrays to identify transcriptomic profiles may aid in the identification of key stressors within a chemical mixture, ultimately improving environmental assessment.

Population effect model identifies gene expression predictors of survival outcomes in lung adenocarcinoma for both Caucasian and Asian patients

PubMed Central

Cai, Guoshuai; Xiao, Feifei; Cheng, Chao; Li, Yafang; Amos, Christopher I.; Whitfield, Michael L.

2017-01-01

Background We analyzed and integrated transcriptome data from two large studies of lung adenocarcinomas on distinct populations. Our goal was to investigate the variable gene expression alterations between paired tumor-normal tissues and prospectively identify those alterations that can reliably predict lung disease related outcomes across populations. Methods We developed a mixed model that combined the paired tumor-normal RNA-seq from two populations. Alterations in gene expression common to both populations were detected and validated in two independent DNA microarray datasets. A 10-gene prognosis signature was developed through a l1 penalized regression approach and its prognostic value was evaluated in a third independent microarray cohort. Results Deregulation of apoptosis pathways and increased expression of cell cycle pathways were identified in tumors of both Caucasian and Asian lung adenocarcinoma patients. We demonstrate that a 10-gene biomarker panel can predict prognosis of lung adenocarcinoma in both Caucasians and Asians. Compared to low risk groups, high risk groups showed significantly shorter overall survival time (Caucasian patients data: HR = 3.63, p-value = 0.007; Asian patients data: HR = 3.25, p-value = 0.001). Conclusions This study uses a statistical framework to detect DEGs between paired tumor and normal tissues that considers variances among patients and ethnicities, which will aid in understanding the common genes and signalling pathways with the largest effect sizes in ethnically diverse cohorts. We propose multifunctional markers for distinguishing tumor from normal tissue and prognosis for both populations studied. PMID:28426704

Statistical models for RNA-seq data derived from a two-condition 48-replicate experiment.

PubMed

Gierliński, Marek; Cole, Christian; Schofield, Pietà; Schurch, Nicholas J; Sherstnev, Alexander; Singh, Vijender; Wrobel, Nicola; Gharbi, Karim; Simpson, Gordon; Owen-Hughes, Tom; Blaxter, Mark; Barton, Geoffrey J

2015-11-15

High-throughput RNA sequencing (RNA-seq) is now the standard method to determine differential gene expression. Identifying differentially expressed genes crucially depends on estimates of read-count variability. These estimates are typically based on statistical models such as the negative binomial distribution, which is employed by the tools edgeR, DESeq and cuffdiff. Until now, the validity of these models has usually been tested on either low-replicate RNA-seq data or simulations. A 48-replicate RNA-seq experiment in yeast was performed and data tested against theoretical models. The observed gene read counts were consistent with both log-normal and negative binomial distributions, while the mean-variance relation followed the line of constant dispersion parameter of ∼0.01. The high-replicate data also allowed for strict quality control and screening of 'bad' replicates, which can drastically affect the gene read-count distribution. RNA-seq data have been submitted to ENA archive with project ID PRJEB5348. g.j.barton@dundee.ac.uk. © The Author 2015. Published by Oxford University Press.

Statistical models for RNA-seq data derived from a two-condition 48-replicate experiment

PubMed Central

Cole, Christian; Schofield, Pietà; Schurch, Nicholas J.; Sherstnev, Alexander; Singh, Vijender; Wrobel, Nicola; Gharbi, Karim; Simpson, Gordon; Owen-Hughes, Tom; Blaxter, Mark; Barton, Geoffrey J.

2015-01-01

Motivation: High-throughput RNA sequencing (RNA-seq) is now the standard method to determine differential gene expression. Identifying differentially expressed genes crucially depends on estimates of read-count variability. These estimates are typically based on statistical models such as the negative binomial distribution, which is employed by the tools edgeR, DESeq and cuffdiff. Until now, the validity of these models has usually been tested on either low-replicate RNA-seq data or simulations. Results: A 48-replicate RNA-seq experiment in yeast was performed and data tested against theoretical models. The observed gene read counts were consistent with both log-normal and negative binomial distributions, while the mean-variance relation followed the line of constant dispersion parameter of ∼0.01. The high-replicate data also allowed for strict quality control and screening of ‘bad’ replicates, which can drastically affect the gene read-count distribution. Availability and implementation: RNA-seq data have been submitted to ENA archive with project ID PRJEB5348. Contact: g.j.barton@dundee.ac.uk PMID:26206307

Diel pattern of circadian clock and storage protein gene expression in leaves and during seed filling in cowpea (Vigna unguiculata).

PubMed

Weiss, Julia; Terry, Marta I; Martos-Fuentes, Marina; Letourneux, Lisa; Ruiz-Hernández, Victoria; Fernández, Juan A; Egea-Cortines, Marcos

2018-02-14

Cowpea (Vigna unguiculata) is an important source of protein supply for animal and human nutrition. The major storage globulins VICILIN and LEGUMIN (LEG) are synthesized from several genes including LEGA, LEGB, LEGJ and CVC (CONVICILIN). The current hypothesis is that the plant circadian core clock genes are conserved in a wide array of species and that primary metabolism is to a large extent controlled by the plant circadian clock. Our aim was to investigate a possible link between gene expression of storage proteins and the circadian clock. We identified cowpea orthologues of the core clock genes VunLHY, VunTOC1, VunGI and VunELF3, the protein storage genes VunLEG, VunLEGJ, and VunCVC as well as nine candidate reference genes used in RT-PCR. ELONGATION FACTOR 1-A (ELF1A) resulted the most suitable reference gene. The clock genes VunELF3, VunGI, VunTOC1 and VunLHY showed a rhythmic expression profile in leaves with a typical evening/night and morning/midday phased expression. The diel patterns were not completely robust and only VungGI and VungELF3 retained a rhythmic pattern under free running conditions of darkness. Under field conditions, rhythmicity and phasing apparently faded during early pod and seed development and was regained in ripening pods for VunTOC1 and VunLHY. Mature seeds showed a rhythmic expression of VunGI resembling leaf tissue under controlled growth chamber conditions. Comparing time windows during developmental stages we found that VunCVC and VunLEG were significantly down regulated during the night in mature pods as compared to intermediate ripe pods, while changes in seeds were non-significant due to high variance. The rhythmic expression under field conditions was lost under growth chamber conditions. The core clock gene network is conserved in cowpea leaves showing a robust diel expression pattern except VunELF3 under growth chamber conditions. There appears to be a clock transcriptional reprogramming in pods and seeds compared to leaves. Storage protein deposition may be circadian regulated under field conditions but the strong environmental signals are not met under artificial growth conditions. Diel expression pattern in field conditions may result in better usage of energy for protein storage.

Genetic variation and co-variation for fitness between intra-population and inter-population backgrounds in the red flour beetle, Tribolium castaneum

PubMed Central

Drury, Douglas W.; Wade, Michael J.

2010-01-01

Hybrids from crosses between populations of the flour beetle, Tribolium castaneum, express varying degrees of inviability and morphological abnormalities. The proportion of allopatric population hybrids exhibiting these negative hybrid phenotypes varies widely, from 3% to 100%, depending upon the pair of populations crossed. We crossed three populations and measured two fitness components, fertility and adult offspring numbers from successful crosses, to determine how genes segregating within populations interact in inter-population hybrids to cause the negative phenotypes. With data from crosses of 40 sires from each of three populations to groups of 5 dams from their own and two divergent populations, we estimated the genetic variance and covariance for breeding value of fitness between the intra- and inter-population backgrounds and the sire × dam-population interaction variance. The latter component of the variance in breeding values estimates the change in genic effects between backgrounds owing to epistasis. Interacting genes with a positive effect, prior to fixation, in the sympatric background but a negative effect in the hybrid background cause reproductive incompatibility in the Dobzhansky-Muller speciation model. Thus, the sire × dam-population interaction provides a way to measure the progress toward speciation of genetically differentiating populations on a trait by trait basis using inter-population hybrids. PMID:21044199

Ovary transcriptome profiling via artificial intelligence reveals a transcriptomic fingerprint predicting egg quality in striped bass, Morone saxatilis.

PubMed

Chapman, Robert W; Reading, Benjamin J; Sullivan, Craig V

2014-01-01

Inherited gene transcripts deposited in oocytes direct early embryonic development in all vertebrates, but transcript profiles indicative of embryo developmental competence have not previously been identified. We employed artificial intelligence to model profiles of maternal ovary gene expression and their relationship to egg quality, evaluated as production of viable mid-blastula stage embryos, in the striped bass (Morone saxatilis), a farmed species with serious egg quality problems. In models developed using artificial neural networks (ANNs) and supervised machine learning, collective changes in the expression of a limited suite of genes (233) representing <2% of the queried ovary transcriptome explained >90% of the eventual variance in embryo survival. Egg quality related to minor changes in gene expression (<0.2-fold), with most individual transcripts making a small contribution (<1%) to the overall prediction of egg quality. These findings indicate that the predictive power of the transcriptome as regards egg quality resides not in levels of individual genes, but rather in the collective, coordinated expression of a suite of transcripts constituting a transcriptomic "fingerprint". Correlation analyses of the corresponding candidate genes indicated that dysfunction of the ubiquitin-26S proteasome, COP9 signalosome, and subsequent control of the cell cycle engenders embryonic developmental incompetence. The affected gene networks are centrally involved in regulation of early development in all vertebrates, including humans. By assessing collective levels of the relevant ovarian transcripts via ANNs we were able, for the first time in any vertebrate, to accurately predict the subsequent embryo developmental potential of eggs from individual females. Our results show that the transcriptomic fingerprint evidencing developmental dysfunction is highly predictive of, and therefore likely to regulate, egg quality, a biologically complex trait crucial to reproductive fitness.

Molecular insight into the association between cartilage regeneration and ear wound healing in genetic mouse models: targeting new genes in regeneration.

PubMed

Rai, Muhammad Farooq; Schmidt, Eric J; McAlinden, Audrey; Cheverud, James M; Sandell, Linda J

2013-11-06

Tissue regeneration is a complex trait with few genetic models available. Mouse strains LG/J and MRL are exceptional healers. Using recombinant inbred strains from a large (LG/J, healer) and small (SM/J, nonhealer) intercross, we have previously shown a positive genetic correlation between ear wound healing, knee cartilage regeneration, and protection from osteoarthritis. We hypothesize that a common set of genes operates in tissue healing and articular cartilage regeneration. Taking advantage of archived histological sections from recombinant inbred strains, we analyzed expression of candidate genes through branched-chain DNA technology directly from tissue lysates. We determined broad-sense heritability of candidates, Pearson correlation of candidates with healing phenotypes, and Ward minimum variance cluster analysis for strains. A bioinformatic assessment of allelic polymorphisms within and near candidate genes was also performed. The expression of several candidates was significantly heritable among strains. Although several genes correlated with both ear wound healing and cartilage healing at a marginal level, the expression of four genes representing DNA repair (Xrcc2, Pcna) and Wnt signaling (Axin2, Wnt16) pathways was significantly positively correlated with both phenotypes. Cluster analysis accurately classified healers and nonhealers for seven out of eight strains based on gene expression. Specific sequence differences between LG/J and SM/J were identified as potential causal polymorphisms. Our study suggests a common genetic basis between tissue healing and osteoarthritis susceptibility. Mapping genetic variations causing differences in diverse healing responses in multiple tissues may reveal generic healing processes in pursuit of new therapeutic targets designed to induce or enhance regeneration and, potentially, protection from osteoarthritis.

Ovary Transcriptome Profiling via Artificial Intelligence Reveals a Transcriptomic Fingerprint Predicting Egg Quality in Striped Bass, Morone saxatilis

PubMed Central

2014-01-01

Inherited gene transcripts deposited in oocytes direct early embryonic development in all vertebrates, but transcript profiles indicative of embryo developmental competence have not previously been identified. We employed artificial intelligence to model profiles of maternal ovary gene expression and their relationship to egg quality, evaluated as production of viable mid-blastula stage embryos, in the striped bass (Morone saxatilis), a farmed species with serious egg quality problems. In models developed using artificial neural networks (ANNs) and supervised machine learning, collective changes in the expression of a limited suite of genes (233) representing <2% of the queried ovary transcriptome explained >90% of the eventual variance in embryo survival. Egg quality related to minor changes in gene expression (<0.2-fold), with most individual transcripts making a small contribution (<1%) to the overall prediction of egg quality. These findings indicate that the predictive power of the transcriptome as regards egg quality resides not in levels of individual genes, but rather in the collective, coordinated expression of a suite of transcripts constituting a transcriptomic “fingerprint”. Correlation analyses of the corresponding candidate genes indicated that dysfunction of the ubiquitin-26S proteasome, COP9 signalosome, and subsequent control of the cell cycle engenders embryonic developmental incompetence. The affected gene networks are centrally involved in regulation of early development in all vertebrates, including humans. By assessing collective levels of the relevant ovarian transcripts via ANNs we were able, for the first time in any vertebrate, to accurately predict the subsequent embryo developmental potential of eggs from individual females. Our results show that the transcriptomic fingerprint evidencing developmental dysfunction is highly predictive of, and therefore likely to regulate, egg quality, a biologically complex trait crucial to reproductive fitness. PMID:24820964

Gene expression profiling of anti-GBM glomerulonephritis model: the role of NF-kappaB in immune complex kidney disease.

PubMed

Kim, Ju Han; Ha, Il Soo; Hwang, Chang-Il; Lee, Young-Ju; Kim, Jihoon; Yang, Seung-Hee; Kim, Yon Su; Cao, Yun Anna; Choi, Sangdun; Park, Woong-Yang

2004-11-01

Immune complexes may cause an irreversible onset of chronic renal disease. Most patients with chronic renal disease undergo a final common pathway, marked by glomerulosclerosis and interstitial fibrosis. We attempted to draw a molecular map of anti-glomerular basement membrane (GBM) glomerulonephritis in mice using oligonucleotide microarray technology. Kidneys were harvested at days 1, 3, 7, 11, and 16 after inducing glomerulonephritis by using anti-GBM antibody. In parallel with examining the biochemical and histologic changes, gene expression profiles were acquired against five pooled control kidneys. Gene expression levels were cross-validated by either reverse transcription-polymerase chain reaction (RT-PCR), real-time PCR, or immunohistochemistry. Pathologic changes in anti-GBM glomerulonephritis were confirmed in both BALB/c and C57BL/6 strains. Among the 13,680 spotted 65mer oligonucleotides, 1112 genes showing significant temporal patterns by permutation analysis of variance (ANOVA) with multiple testing correction [false discovery ratio (FDR) < 0.05] were chosen for cluster analysis. From the expression profile, acute inflammatory reactions characterized by the elevation of various cytokines, including interleukin (IL)-1 and IL-6, were identified within 3 days of disease onset. After 7 days, tissue remodeling response was prominent with highly induced extracellular-matrix (ECM) genes. Although cytokines related to lymphocyte activation were not detected, monocyte or mesangial cell proliferation-related genes were increased. Tumor necrosis factor-alpha (TNF-alpha) and nuclear factor-kappaB (NF-kappaB) pathway were consistently activated along the entire disease progression, inducing various target genes like complement 3, IL-1b, IL-6, Traf1, and Saa1. We made a large-scale gene expression time table for mouse anti-GBM glomerulonephritis model, providing a comprehensive overview on the mechanism governing the initiation and the progression of inflammatory renal disease.

Collective Dynamics of Specific Gene Ensembles Crucial for Neutrophil Differentiation: The Existence of Genome Vehicles Revealed

PubMed Central

Giuliani, Alessandro; Tomita, Masaru

2010-01-01

Cell fate decision remarkably generates specific cell differentiation path among the multiple possibilities that can arise through the complex interplay of high-dimensional genome activities. The coordinated action of thousands of genes to switch cell fate decision has indicated the existence of stable attractors guiding the process. However, origins of the intracellular mechanisms that create “cellular attractor” still remain unknown. Here, we examined the collective behavior of genome-wide expressions for neutrophil differentiation through two different stimuli, dimethyl sulfoxide (DMSO) and all-trans-retinoic acid (atRA). To overcome the difficulties of dealing with single gene expression noises, we grouped genes into ensembles and analyzed their expression dynamics in correlation space defined by Pearson correlation and mutual information. The standard deviation of correlation distributions of gene ensembles reduces when the ensemble size is increased following the inverse square root law, for both ensembles chosen randomly from whole genome and ranked according to expression variances across time. Choosing the ensemble size of 200 genes, we show the two probability distributions of correlations of randomly selected genes for atRA and DMSO responses overlapped after 48 hours, defining the neutrophil attractor. Next, tracking the ranked ensembles' trajectories, we noticed that only certain, not all, fall into the attractor in a fractal-like manner. The removal of these genome elements from the whole genomes, for both atRA and DMSO responses, destroys the attractor providing evidence for the existence of specific genome elements (named “genome vehicle”) responsible for the neutrophil attractor. Notably, within the genome vehicles, genes with low or moderate expression changes, which are often considered noisy and insignificant, are essential components for the creation of the neutrophil attractor. Further investigations along with our findings might provide a comprehensive mechanistic view of cell fate decision. PMID:20725638

Differential expression patterns of housekeeping genes increase diagnostic and prognostic value in lung cancer

PubMed Central

Chang, Yu-Chun; Ding, Yan; Dong, Lingsheng; Zhu, Lang-Jing; Jensen, Roderick V.

2018-01-01

Background Using DNA microarrays, we previously identified 451 genes expressed in 19 different human tissues. Although ubiquitously expressed, the variable expression patterns of these “housekeeping genes” (HKGs) could separate one normal human tissue type from another. Current focus on identifying “specific disease markers” is problematic as single gene expression in a given sample represents the specific cellular states of the sample at the time of collection. In this study, we examine the diagnostic and prognostic potential of the variable expressions of HKGs in lung cancers. Methods Microarray and RNA-seq data for normal lungs, lung adenocarcinomas (AD), squamous cell carcinomas of the lung (SQCLC), and small cell carcinomas of the lung (SCLC) were collected from online databases. Using 374 of 451 HKGs, differentially expressed genes between pairs of sample types were determined via two-sided, homoscedastic t-test. Principal component analysis and hierarchical clustering classified normal lung and lung cancers subtypes according to relative gene expression variations. We used uni- and multi-variate cox-regressions to identify significant predictors of overall survival in AD patients. Classifying genes were selected using a set of training samples and then validated using an independent test set. Gene Ontology was examined by PANTHER. Results This study showed that the differential expression patterns of 242, 245, and 99 HKGs were able to distinguish normal lung from AD, SCLC, and SQCLC, respectively. From these, 70 HKGs were common across the three lung cancer subtypes. These HKGs have low expression variation compared to current lung cancer markers (e.g., EGFR, KRAS) and were involved in the most common biological processes (e.g., metabolism, stress response). In addition, the expression pattern of 106 HKGs alone was a significant classifier of AD versus SQCLC. We further highlighted that a panel of 13 HKGs was an independent predictor of overall survival and cumulative risk in AD patients. Discussion Here we report HKG expression patterns may be an effective tool for evaluation of lung cancer states. For example, the differential expression pattern of 70 HKGs alone can separate normal lung tissue from various lung cancers while a panel of 106 HKGs was a capable class predictor of subtypes of non-small cell carcinomas. We also reported that HKGs have significantly lower variance compared to traditional cancer markers across samples, highlighting the robustness of a panel of genes over any one specific biomarker. Using RNA-seq data, we showed that the expression pattern of 13 HKGs is a significant, independent predictor of overall survival for AD patients. This reinforces the predictive power of a HKG panel across different gene expression measurement platforms. Thus, we propose the expression patterns of HKGs alone may be sufficient for the diagnosis and prognosis of individuals with lung cancer. PMID:29761043

Analytical results for a stochastic model of gene expression with arbitrary partitioning of proteins

NASA Astrophysics Data System (ADS)

Tschirhart, Hugo; Platini, Thierry

2018-05-01

In biophysics, the search for analytical solutions of stochastic models of cellular processes is often a challenging task. In recent work on models of gene expression, it was shown that a mapping based on partitioning of Poisson arrivals (PPA-mapping) can lead to exact solutions for previously unsolved problems. While the approach can be used in general when the model involves Poisson processes corresponding to creation or degradation, current applications of the method and new results derived using it have been limited to date. In this paper, we present the exact solution of a variation of the two-stage model of gene expression (with time dependent transition rates) describing the arbitrary partitioning of proteins. The methodology proposed makes full use of the PPA-mapping by transforming the original problem into a new process describing the evolution of three biological switches. Based on a succession of transformations, the method leads to a hierarchy of reduced models. We give an integral expression of the time dependent generating function as well as explicit results for the mean, variance, and correlation function. Finally, we discuss how results for time dependent parameters can be extended to the three-stage model and used to make inferences about models with parameter fluctuations induced by hidden stochastic variables.

A Versatile Omnibus Test for Detecting Mean and Variance Heterogeneity

PubMed Central

Bailey, Matthew; Kauwe, John S. K.; Maxwell, Taylor J.

2014-01-01

Recent research has revealed loci that display variance heterogeneity through various means such as biological disruption, linkage disequilibrium (LD), gene-by-gene (GxG), or gene-by-environment (GxE) interaction. We propose a versatile likelihood ratio test that allows joint testing for mean and variance heterogeneity (LRTMV) or either effect alone (LRTM or LRTV) in the presence of covariates. Using extensive simulations for our method and others we found that all parametric tests were sensitive to non-normality regardless of any trait transformations. Coupling our test with the parametric bootstrap solves this issue. Using simulations and empirical data from a known mean-only functional variant we demonstrate how linkage disequilibrium (LD) can produce variance-heterogeneity loci (vQTL) in a predictable fashion based on differential allele frequencies, high D’ and relatively low r2 values. We propose that a joint test for mean and variance heterogeneity is more powerful than a variance only test for detecting vQTL. This takes advantage of loci that also have mean effects without sacrificing much power to detect variance only effects. We discuss using vQTL as an approach to detect gene-by-gene interactions and also how vQTL are related to relationship loci (rQTL) and how both can create prior hypothesis for each other and reveal the relationships between traits and possibly between components of a composite trait. PMID:24482837

Why weight? Modelling sample and observational level variability improves power in RNA-seq analyses

PubMed Central

Liu, Ruijie; Holik, Aliaksei Z.; Su, Shian; Jansz, Natasha; Chen, Kelan; Leong, Huei San; Blewitt, Marnie E.; Asselin-Labat, Marie-Liesse; Smyth, Gordon K.; Ritchie, Matthew E.

2015-01-01

Variations in sample quality are frequently encountered in small RNA-sequencing experiments, and pose a major challenge in a differential expression analysis. Removal of high variation samples reduces noise, but at a cost of reducing power, thus limiting our ability to detect biologically meaningful changes. Similarly, retaining these samples in the analysis may not reveal any statistically significant changes due to the higher noise level. A compromise is to use all available data, but to down-weight the observations from more variable samples. We describe a statistical approach that facilitates this by modelling heterogeneity at both the sample and observational levels as part of the differential expression analysis. At the sample level this is achieved by fitting a log-linear variance model that includes common sample-specific or group-specific parameters that are shared between genes. The estimated sample variance factors are then converted to weights and combined with observational level weights obtained from the mean–variance relationship of the log-counts-per-million using ‘voom’. A comprehensive analysis involving both simulations and experimental RNA-sequencing data demonstrates that this strategy leads to a universally more powerful analysis and fewer false discoveries when compared to conventional approaches. This methodology has wide application and is implemented in the open-source ‘limma’ package. PMID:25925576

Sociogenomics of self vs. non-self cooperation during development of Dictyostelium discoideum.

PubMed

Li, Si I; Buttery, Neil J; Thompson, Christopher R L; Purugganan, Michael D

2014-07-21

Dictyostelium discoideum, a microbial model for social evolution, is known to distinguish self from non-self and show genotype-dependent behavior during chimeric development. Aside from a small number of cell-cell recognition genes, however, little is known about the genetic basis of self/non-self recognition in this species. Based on the key hypothesis that there should be differential expression of genes if D. discoideum cells were interacting with non-clone mates, we performed transcriptomic profiling study in this species during clonal vs. chimeric development. The transcriptomic profiles of D. discoideum cells in clones vs. different chimeras were compared at five different developmental stages using a customized microarray. Effects of chimerism on global transcriptional patterns associated with social interactions were observed. We find 1,759 genes significantly different between chimera and clone, 1,144 genes associated significant strain differences, and 6,586 genes developmentally regulated over time. Principal component analysis showed a small amount of the transcriptional variance to chimerism-related factors (Chimerism: 0.18%, Chimerism × Timepoint: 0.03%). There are 162 genes specifically regulated under chimeric development, with continuous small differences between chimera vs. clone over development. Almost 60% of chimera-associated differential genes were differentially expressed at the 4 h aggregate stage, which corresponds to the initial transition of D. discoideum from solitary life to a multicellular phase. A relatively small proportion of over-all variation in gene expression is explained by differences between chimeric and clonal development. The relatively small modifications in gene expression associated with chimerism is compatible with the high level of cooperation observed among different strains of D. discoideum; cells of distinct genetic backgrounds will co-aggregate indiscriminately and co-develop into fruiting bodies. Chimeric development may involve re-programming of the transcriptome through small modifications of the developmental genetic network, which may also indicate that response to social interaction involves many genes with individually small transcriptional effect.

Differential gene expression in dentate granule cells in mesial temporal lobe epilepsy with and without hippocampal sclerosis.

PubMed

Griffin, Nicole G; Wang, Yu; Hulette, Christine M; Halvorsen, Matt; Cronin, Kenneth D; Walley, Nicole M; Haglund, Michael M; Radtke, Rodney A; Skene, J H Pate; Sinha, Saurabh R; Heinzen, Erin L

2016-03-01

Hippocampal sclerosis is the most common neuropathologic finding in cases of medically intractable mesial temporal lobe epilepsy. In this study, we analyzed the gene expression profiles of dentate granule cells of patients with mesial temporal lobe epilepsy with and without hippocampal sclerosis to show that next-generation sequencing methods can produce interpretable genomic data from RNA collected from small homogenous cell populations, and to shed light on the transcriptional changes associated with hippocampal sclerosis. RNA was extracted, and complementary DNA (cDNA) was prepared and amplified from dentate granule cells that had been harvested by laser capture microdissection from surgically resected hippocampi from patients with mesial temporal lobe epilepsy with and without hippocampal sclerosis. Sequencing libraries were sequenced, and the resulting sequencing reads were aligned to the reference genome. Differential expression analysis was used to ascertain expression differences between patients with and without hippocampal sclerosis. Greater than 90% of the RNA-Seq reads aligned to the reference. There was high concordance between transcriptional profiles obtained for duplicate samples. Principal component analysis revealed that the presence or absence of hippocampal sclerosis was the main determinant of the variance within the data. Among the genes up-regulated in the hippocampal sclerosis samples, there was significant enrichment for genes involved in oxidative phosphorylation. By analyzing the gene expression profiles of dentate granule cells from surgically resected hippocampal specimens from patients with mesial temporal lobe epilepsy with and without hippocampal sclerosis, we have demonstrated the utility of next-generation sequencing methods for producing biologically relevant results from small populations of homogeneous cells, and have provided insight on the transcriptional changes associated with this pathology. Wiley Periodicals, Inc. © 2016 International League Against Epilepsy.

Bayesian estimation of the discrete coefficient of determination.

PubMed

Chen, Ting; Braga-Neto, Ulisses M

2016-12-01

The discrete coefficient of determination (CoD) measures the nonlinear interaction between discrete predictor and target variables and has had far-reaching applications in Genomic Signal Processing. Previous work has addressed the inference of the discrete CoD using classical parametric and nonparametric approaches. In this paper, we introduce a Bayesian framework for the inference of the discrete CoD. We derive analytically the optimal minimum mean-square error (MMSE) CoD estimator, as well as a CoD estimator based on the Optimal Bayesian Predictor (OBP). For the latter estimator, exact expressions for its bias, variance, and root-mean-square (RMS) are given. The accuracy of both Bayesian CoD estimators with non-informative and informative priors, under fixed or random parameters, is studied via analytical and numerical approaches. We also demonstrate the application of the proposed Bayesian approach in the inference of gene regulatory networks, using gene-expression data from a previously published study on metastatic melanoma.

A powerful and flexible approach to the analysis of RNA sequence count data

PubMed Central

Zhou, Yi-Hui; Xia, Kai; Wright, Fred A.

2011-01-01

Motivation: A number of penalization and shrinkage approaches have been proposed for the analysis of microarray gene expression data. Similar techniques are now routinely applied to RNA sequence transcriptional count data, although the value of such shrinkage has not been conclusively established. If penalization is desired, the explicit modeling of mean–variance relationships provides a flexible testing regimen that ‘borrows’ information across genes, while easily incorporating design effects and additional covariates. Results: We describe BBSeq, which incorporates two approaches: (i) a simple beta-binomial generalized linear model, which has not been extensively tested for RNA-Seq data and (ii) an extension of an expression mean–variance modeling approach to RNA-Seq data, involving modeling of the overdispersion as a function of the mean. Our approaches are flexible, allowing for general handling of discrete experimental factors and continuous covariates. We report comparisons with other alternate methods to handle RNA-Seq data. Although penalized methods have advantages for very small sample sizes, the beta-binomial generalized linear model, combined with simple outlier detection and testing approaches, appears to have favorable characteristics in power and flexibility. Availability: An R package containing examples and sample datasets is available at http://www.bios.unc.edu/research/genomic_software/BBSeq Contact: yzhou@bios.unc.edu; fwright@bios.unc.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:21810900

Gene signature of the post-Chernobyl papillary thyroid cancer.

PubMed

Handkiewicz-Junak, Daria; Swierniak, Michal; Rusinek, Dagmara; Oczko-Wojciechowska, Małgorzata; Dom, Genevieve; Maenhaut, Carine; Unger, Kristian; Detours, Vincent; Bogdanova, Tetiana; Thomas, Geraldine; Likhtarov, Ilya; Jaksik, Roman; Kowalska, Malgorzata; Chmielik, Ewa; Jarzab, Michal; Swierniak, Andrzej; Jarzab, Barbara

2016-07-01

Following the nuclear accidents in Chernobyl and later in Fukushima, the nuclear community has been faced with important issues concerning how to search for and diagnose biological consequences of low-dose internal radiation contamination. Although after the Chernobyl accident an increase in childhood papillary thyroid cancer (PTC) was observed, it is still not clear whether the molecular biology of PTCs associated with low-dose radiation exposure differs from that of sporadic PTC. We investigated tissue samples from 65 children/young adults with PTC using DNA microarray (Affymetrix, Human Genome U133 2.0 Plus) with the aim of identifying molecular differences between radiation-induced (exposed to Chernobyl radiation, ECR) and sporadic PTC. All participants were resident in the same region so that confounding factors related to genetics or environment were minimized. There were small but significant differences in the gene expression profiles between ECR and non-ECR PTC (global test, p < 0.01), with 300 differently expressed probe sets (p < 0.001) corresponding to 239 genes. Multifactorial analysis of variance showed that besides radiation exposure history, the BRAF mutation exhibited independent effects on the PTC expression profile; the histological subset and patient age at diagnosis had negligible effects. Ten genes (PPME1, HDAC11, SOCS7, CIC, THRA, ERBB2, PPP1R9A, HDGF, RAD51AP1, and CDK1) from the 19 investigated with quantitative RT-PCR were confirmed as being associated with radiation exposure in an independent, validation set of samples. Significant, but subtle, differences in gene expression in the post-Chernobyl PTC are associated with previous low-dose radiation exposure.

Shrinkage estimation of effect sizes as an alternative to hypothesis testing followed by estimation in high-dimensional biology: applications to differential gene expression.

PubMed

Montazeri, Zahra; Yanofsky, Corey M; Bickel, David R

2010-01-01

Research on analyzing microarray data has focused on the problem of identifying differentially expressed genes to the neglect of the problem of how to integrate evidence that a gene is differentially expressed with information on the extent of its differential expression. Consequently, researchers currently prioritize genes for further study either on the basis of volcano plots or, more commonly, according to simple estimates of the fold change after filtering the genes with an arbitrary statistical significance threshold. While the subjective and informal nature of the former practice precludes quantification of its reliability, the latter practice is equivalent to using a hard-threshold estimator of the expression ratio that is not known to perform well in terms of mean-squared error, the sum of estimator variance and squared estimator bias. On the basis of two distinct simulation studies and data from different microarray studies, we systematically compared the performance of several estimators representing both current practice and shrinkage. We find that the threshold-based estimators usually perform worse than the maximum-likelihood estimator (MLE) and they often perform far worse as quantified by estimated mean-squared risk. By contrast, the shrinkage estimators tend to perform as well as or better than the MLE and never much worse than the MLE, as expected from what is known about shrinkage. However, a Bayesian measure of performance based on the prior information that few genes are differentially expressed indicates that hard-threshold estimators perform about as well as the local false discovery rate (FDR), the best of the shrinkage estimators studied. Based on the ability of the latter to leverage information across genes, we conclude that the use of the local-FDR estimator of the fold change instead of informal or threshold-based combinations of statistical tests and non-shrinkage estimators can be expected to substantially improve the reliability of gene prioritization at very little risk of doing so less reliably. Since the proposed replacement of post-selection estimates with shrunken estimates applies as well to other types of high-dimensional data, it could also improve the analysis of SNP data from genome-wide association studies.

Association of breast cancer risk with genetic variants showing differential allelic expression: Identification of a novel breast cancer susceptibility locus at 4q21

PubMed Central

Adoue, Véronique; Michailidou, Kyriaki; Canisius, Sander; Lemaçon, Audrey; Droit, Arnaud; Andrulis, Irene L; Anton-Culver, Hoda; Arndt, Volker; Baynes, Caroline; Blomqvist, Carl; Bogdanova, Natalia V.; Bojesen, Stig E.; Bolla, Manjeet K.; Bonanni, Bernardo; Borresen-Dale, Anne-Lise; Brand, Judith S.; Brauch, Hiltrud; Brenner, Hermann; Broeks, Annegien; Burwinkel, Barbara; Chang-Claude, Jenny; Couch, Fergus J.; Cox, Angela; Cross, Simon S.; Czene, Kamila; Darabi, Hatef; Dennis, Joe; Devilee, Peter; Dörk, Thilo; Dos-Santos-Silva, Isabel; Eriksson, Mikael; Fasching, Peter A.; Figueroa, Jonine; Flyger, Henrik; García-Closas, Montserrat; Giles, Graham G.; Goldberg, Mark S.; González-Neira, Anna; Grenaker-Alnæs, Grethe; Guénel, Pascal; Haeberle, Lothar; Haiman, Christopher A.; Hamann, Ute; Hallberg, Emily; Hooning, Maartje J.; Hopper, John L.; Jakubowska, Anna; Jones, Michael; Kabisch, Maria; Kataja, Vesa; Lambrechts, Diether; Marchand, Loic Le; Lindblom, Annika; Lubinski, Jan; Mannermaa, Arto; Maranian, Mel; Margolin, Sara; Marme, Frederik; Milne, Roger L.; Neuhausen, Susan L.; Nevanlinna, Heli; Neven, Patrick; Olswold, Curtis; Peto, Julian; Plaseska-Karanfilska, Dijana; Pylkäs, Katri; Radice, Paolo; Rudolph, Anja; Sawyer, Elinor J.; Schmidt, Marjanka K.; Shu, Xiao-Ou; Southey, Melissa C.; Swerdlow, Anthony; Tollenaar, Rob A.E.M.; Tomlinson, Ian; Torres, Diana; Truong, Thérèse; Vachon, Celine; Van Den Ouweland, Ans M. W.; Wang, Qin; Winqvist, Robert; Investigators, kConFab/AOCS; Zheng, Wei; Benitez, Javier; Chenevix-Trench, Georgia; Dunning, Alison M.; Pharoah, Paul D. P.; Kristensen, Vessela; Hall, Per; Easton, Douglas F.; Pastinen, Tomi; Nord, Silje; Simard, Jacques

2016-01-01

There are significant inter-individual differences in the levels of gene expression. Through modulation of gene expression, cis-acting variants represent an important source of phenotypic variation. Consequently, cis-regulatory SNPs associated with differential allelic expression are functional candidates for further investigation as disease-causing variants. To investigate whether common variants associated with differential allelic expression were involved in breast cancer susceptibility, a list of genes was established on the basis of their involvement in cancer related pathways and/or mechanisms. Thereafter, using data from a genome-wide map of allelic expression associated SNPs, 313 genetic variants were selected and their association with breast cancer risk was then evaluated in 46,451 breast cancer cases and 42,599 controls of European ancestry ascertained from 41 studies participating in the Breast Cancer Association Consortium. The associations were evaluated with overall breast cancer risk and with estrogen receptor negative and positive disease. One novel breast cancer susceptibility locus on 4q21 (rs11099601) was identified (OR = 1.05, P = 5.6x10-6). rs11099601 lies in a 135 kb linkage disequilibrium block containing several genes, including, HELQ, encoding the protein HEL308 a DNA dependant ATPase and DNA Helicase involved in DNA repair, MRPS18C encoding the Mitochondrial Ribosomal Protein S18C and FAM175A (ABRAXAS), encoding a BRCA1 BRCT domain-interacting protein involved in DNA damage response and double-strand break (DSB) repair. Expression QTL analysis in breast cancer tissue showed rs11099601 to be associated with HELQ (P = 8.28x10-14), MRPS18C (P = 1.94x10-27) and FAM175A (P = 3.83x10-3), explaining about 20%, 14% and 1%, respectively of the variance inexpression of these genes in breast carcinomas. PMID:27792995

Association of breast cancer risk with genetic variants showing differential allelic expression: Identification of a novel breast cancer susceptibility locus at 4q21.

PubMed

Hamdi, Yosr; Soucy, Penny; Adoue, Véronique; Michailidou, Kyriaki; Canisius, Sander; Lemaçon, Audrey; Droit, Arnaud; Andrulis, Irene L; Anton-Culver, Hoda; Arndt, Volker; Baynes, Caroline; Blomqvist, Carl; Bogdanova, Natalia V; Bojesen, Stig E; Bolla, Manjeet K; Bonanni, Bernardo; Borresen-Dale, Anne-Lise; Brand, Judith S; Brauch, Hiltrud; Brenner, Hermann; Broeks, Annegien; Burwinkel, Barbara; Chang-Claude, Jenny; Couch, Fergus J; Cox, Angela; Cross, Simon S; Czene, Kamila; Darabi, Hatef; Dennis, Joe; Devilee, Peter; Dörk, Thilo; Dos-Santos-Silva, Isabel; Eriksson, Mikael; Fasching, Peter A; Figueroa, Jonine; Flyger, Henrik; García-Closas, Montserrat; Giles, Graham G; Goldberg, Mark S; González-Neira, Anna; Grenaker-Alnæs, Grethe; Guénel, Pascal; Haeberle, Lothar; Haiman, Christopher A; Hamann, Ute; Hallberg, Emily; Hooning, Maartje J; Hopper, John L; Jakubowska, Anna; Jones, Michael; Kabisch, Maria; Kataja, Vesa; Lambrechts, Diether; Le Marchand, Loic; Lindblom, Annika; Lubinski, Jan; Mannermaa, Arto; Maranian, Mel; Margolin, Sara; Marme, Frederik; Milne, Roger L; Neuhausen, Susan L; Nevanlinna, Heli; Neven, Patrick; Olswold, Curtis; Peto, Julian; Plaseska-Karanfilska, Dijana; Pylkäs, Katri; Radice, Paolo; Rudolph, Anja; Sawyer, Elinor J; Schmidt, Marjanka K; Shu, Xiao-Ou; Southey, Melissa C; Swerdlow, Anthony; Tollenaar, Rob A E M; Tomlinson, Ian; Torres, Diana; Truong, Thérèse; Vachon, Celine; Van Den Ouweland, Ans M W; Wang, Qin; Winqvist, Robert; Zheng, Wei; Benitez, Javier; Chenevix-Trench, Georgia; Dunning, Alison M; Pharoah, Paul D P; Kristensen, Vessela; Hall, Per; Easton, Douglas F; Pastinen, Tomi; Nord, Silje; Simard, Jacques

2016-12-06

There are significant inter-individual differences in the levels of gene expression. Through modulation of gene expression, cis-acting variants represent an important source of phenotypic variation. Consequently, cis-regulatory SNPs associated with differential allelic expression are functional candidates for further investigation as disease-causing variants. To investigate whether common variants associated with differential allelic expression were involved in breast cancer susceptibility, a list of genes was established on the basis of their involvement in cancer related pathways and/or mechanisms. Thereafter, using data from a genome-wide map of allelic expression associated SNPs, 313 genetic variants were selected and their association with breast cancer risk was then evaluated in 46,451 breast cancer cases and 42,599 controls of European ancestry ascertained from 41 studies participating in the Breast Cancer Association Consortium. The associations were evaluated with overall breast cancer risk and with estrogen receptor negative and positive disease. One novel breast cancer susceptibility locus on 4q21 (rs11099601) was identified (OR = 1.05, P = 5.6x10-6). rs11099601 lies in a 135 kb linkage disequilibrium block containing several genes, including, HELQ, encoding the protein HEL308 a DNA dependant ATPase and DNA Helicase involved in DNA repair, MRPS18C encoding the Mitochondrial Ribosomal Protein S18C and FAM175A (ABRAXAS), encoding a BRCA1 BRCT domain-interacting protein involved in DNA damage response and double-strand break (DSB) repair. Expression QTL analysis in breast cancer tissue showed rs11099601 to be associated with HELQ (P = 8.28x10-14), MRPS18C (P = 1.94x10-27) and FAM175A (P = 3.83x10-3), explaining about 20%, 14% and 1%, respectively of the variance inexpression of these genes in breast carcinomas.

MAVTgsa: An R Package for Gene Set (Enrichment) Analysis

DOE PAGES

Chien, Chih-Yi; Chang, Ching-Wei; Tsai, Chen-An; ...

2014-01-01

Gene semore » t analysis methods aim to determine whether an a priori defined set of genes shows statistically significant difference in expression on either categorical or continuous outcomes. Although many methods for gene set analysis have been proposed, a systematic analysis tool for identification of different types of gene set significance modules has not been developed previously. This work presents an R package, called MAVTgsa, which includes three different methods for integrated gene set enrichment analysis. (1) The one-sided OLS (ordinary least squares) test detects coordinated changes of genes in gene set in one direction, either up- or downregulation. (2) The two-sided MANOVA (multivariate analysis variance) detects changes both up- and downregulation for studying two or more experimental conditions. (3) A random forests-based procedure is to identify gene sets that can accurately predict samples from different experimental conditions or are associated with the continuous phenotypes. MAVTgsa computes the P values and FDR (false discovery rate) q -value for all gene sets in the study. Furthermore, MAVTgsa provides several visualization outputs to support and interpret the enrichment results. This package is available online.« less

Cross-disorder genome-wide analyses suggest a complex genetic relationship between Tourette's syndrome and OCD.

PubMed

Yu, Dongmei; Mathews, Carol A; Scharf, Jeremiah M; Neale, Benjamin M; Davis, Lea K; Gamazon, Eric R; Derks, Eske M; Evans, Patrick; Edlund, Christopher K; Crane, Jacquelyn; Fagerness, Jesen A; Osiecki, Lisa; Gallagher, Patience; Gerber, Gloria; Haddad, Stephen; Illmann, Cornelia; McGrath, Lauren M; Mayerfeld, Catherine; Arepalli, Sampath; Barlassina, Cristina; Barr, Cathy L; Bellodi, Laura; Benarroch, Fortu; Berrió, Gabriel Bedoya; Bienvenu, O Joseph; Black, Donald W; Bloch, Michael H; Brentani, Helena; Bruun, Ruth D; Budman, Cathy L; Camarena, Beatriz; Campbell, Desmond D; Cappi, Carolina; Silgado, Julio C Cardona; Cavallini, Maria C; Chavira, Denise A; Chouinard, Sylvain; Cook, Edwin H; Cookson, M R; Coric, Vladimir; Cullen, Bernadette; Cusi, Daniele; Delorme, Richard; Denys, Damiaan; Dion, Yves; Eapen, Valsama; Egberts, Karin; Falkai, Peter; Fernandez, Thomas; Fournier, Eduardo; Garrido, Helena; Geller, Daniel; Gilbert, Donald L; Girard, Simon L; Grabe, Hans J; Grados, Marco A; Greenberg, Benjamin D; Gross-Tsur, Varda; Grünblatt, Edna; Hardy, John; Heiman, Gary A; Hemmings, Sian M J; Herrera, Luis D; Hezel, Dianne M; Hoekstra, Pieter J; Jankovic, Joseph; Kennedy, James L; King, Robert A; Konkashbaev, Anuar I; Kremeyer, Barbara; Kurlan, Roger; Lanzagorta, Nuria; Leboyer, Marion; Leckman, James F; Lennertz, Leonhard; Liu, Chunyu; Lochner, Christine; Lowe, Thomas L; Lupoli, Sara; Macciardi, Fabio; Maier, Wolfgang; Manunta, Paolo; Marconi, Maurizio; McCracken, James T; Mesa Restrepo, Sandra C; Moessner, Rainald; Moorjani, Priya; Morgan, Jubel; Muller, Heike; Murphy, Dennis L; Naarden, Allan L; Nurmi, Erika; Ochoa, William Cornejo; Ophoff, Roel A; Pakstis, Andrew J; Pato, Michele T; Pato, Carlos N; Piacentini, John; Pittenger, Christopher; Pollak, Yehuda; Rauch, Scott L; Renner, Tobias; Reus, Victor I; Richter, Margaret A; Riddle, Mark A; Robertson, Mary M; Romero, Roxana; Rosário, Maria C; Rosenberg, David; Ruhrmann, Stephan; Sabatti, Chiara; Salvi, Erika; Sampaio, Aline S; Samuels, Jack; Sandor, Paul; Service, Susan K; Sheppard, Brooke; Singer, Harvey S; Smit, Jan H; Stein, Dan J; Strengman, Eric; Tischfield, Jay A; Turiel, Maurizio; Valencia Duarte, Ana V; Vallada, Homero; Veenstra-VanderWeele, Jeremy; Walitza, Susanne; Wang, Ying; Weale, Mike; Weiss, Robert; Wendland, Jens R; Westenberg, Herman G M; Shugart, Yin Yao; Hounie, Ana G; Miguel, Euripedes C; Nicolini, Humberto; Wagner, Michael; Ruiz-Linares, Andres; Cath, Danielle C; McMahon, William; Posthuma, Danielle; Oostra, Ben A; Nestadt, Gerald; Rouleau, Guy A; Purcell, Shaun; Jenike, Michael A; Heutink, Peter; Hanna, Gregory L; Conti, David V; Arnold, Paul D; Freimer, Nelson B; Stewart, S Evelyn; Knowles, James A; Cox, Nancy J; Pauls, David L

2015-01-01

Obsessive-compulsive disorder (OCD) and Tourette's syndrome are highly heritable neurodevelopmental disorders that are thought to share genetic risk factors. However, the identification of definitive susceptibility genes for these etiologically complex disorders remains elusive. The authors report a combined genome-wide association study (GWAS) of Tourette's syndrome and OCD. The authors conducted a GWAS in 2,723 cases (1,310 with OCD, 834 with Tourette's syndrome, 579 with OCD plus Tourette's syndrome/chronic tics), 5,667 ancestry-matched controls, and 290 OCD parent-child trios. GWAS summary statistics were examined for enrichment of functional variants associated with gene expression levels in brain regions. Polygenic score analyses were conducted to investigate the genetic architecture within and across the two disorders. Although no individual single-nucleotide polymorphisms (SNPs) achieved genome-wide significance, the GWAS signals were enriched for SNPs strongly associated with variations in brain gene expression levels (expression quantitative loci, or eQTLs), suggesting the presence of true functional variants that contribute to risk of these disorders. Polygenic score analyses identified a significant polygenic component for OCD (p=2×10(-4)), predicting 3.2% of the phenotypic variance in an independent data set. In contrast, Tourette's syndrome had a smaller, nonsignificant polygenic component, predicting only 0.6% of the phenotypic variance (p=0.06). No significant polygenic signal was detected across the two disorders, although the sample is likely underpowered to detect a modest shared signal. Furthermore, the OCD polygenic signal was significantly attenuated when cases with both OCD and co-occurring Tourette's syndrome/chronic tics were included in the analysis (p=0.01). Previous work has shown that Tourette's syndrome and OCD have some degree of shared genetic variation. However, the data from this study suggest that there are also distinct components to the genetic architectures of these two disorders. Furthermore, OCD with co-occurring Tourette's syndrome/chronic tics may have different underlying genetic susceptibility compared with OCD alone.

Epigenetic hereditary transcription profiles III, evidence for an epigenetic network resulting in gender, tissue and age-specific variation in overall transcription

PubMed Central

Simons, Johannes WIM

2009-01-01

Background We have previously shown that deviations from the average transcription profile of a group of functionally related genes are not only heritable, but also demonstrate specific patterns associated with age, gender and differentiation, thereby implicating genome-wide nuclear programming as the cause. To determine whether these results could be reproduced, a different micro-array database (obtained from two types of muscle tissue, derived from 81 human donors aged between 16 to 89 years) was studied. Results This new database also revealed the existence of age, gender and tissue-specific features in a small group of functionally related genes. In order to further analyze this phenomenon, a method was developed for quantifying the contribution of different factors to the variability in gene expression, and for generating a database limited to residual values reflecting constitutional differences between individuals. These constitutional differences, presumably epigenetic in origin, contribute to about 50% of the observed residual variance which is connected with a network of interrelated changes in gene expression with some genes displaying a decrease or increase in residual variation with age. Conclusion Epigenetic variation in gene expression without a clear concomitant relation to gene function appears to be a widespread phenomenon. This variation is connected with interactions between genes, is gender and tissue specific and is related to cellular aging. This finding, together with the method developed for analysis, might contribute to the elucidation of the role of nuclear programming in differentiation, aging and carcinogenesis Reviewers This article was reviewed by Thiago M. Venancio (nominated by Aravind Iyer), Hua Li (nominated by Arcady Mushegian) and Arcady Mushegian and J.P.de Magelhaes (nominated by G. Church). PMID:19796384

Quantitative and qualitative stem rust resistance factors in barley are associated with transcriptional suppression of defense regulons.

PubMed

Moscou, Matthew J; Lauter, Nick; Steffenson, Brian; Wise, Roger P

2011-07-01

Stem rust (Puccinia graminis f. sp. tritici; Pgt) is a devastating fungal disease of wheat and barley. Pgt race TTKSK (isolate Ug99) is a serious threat to these Triticeae grain crops because resistance is rare. In barley, the complex Rpg-TTKSK locus on chromosome 5H is presently the only known source of qualitative resistance to this aggressive Pgt race. Segregation for resistance observed on seedlings of the Q21861 × SM89010 (QSM) doubled-haploid (DH) population was found to be predominantly qualitative, with little of the remaining variance explained by loci other than Rpg-TTKSK. In contrast, analysis of adult QSM DH plants infected by field inoculum of Pgt race TTKSK in Njoro, Kenya, revealed several additional quantitative trait loci that contribute to resistance. To molecularly characterize these loci, Barley1 GeneChips were used to measure the expression of 22,792 genes in the QSM population after inoculation with Pgt race TTKSK or mock-inoculation. Comparison of expression Quantitative Trait Loci (eQTL) between treatments revealed an inoculation-dependent expression polymorphism implicating Actin depolymerizing factor3 (within the Rpg-TTKSK locus) as a candidate susceptibility gene. In parallel, we identified a chromosome 2H trans-eQTL hotspot that co-segregates with an enhancer of Rpg-TTKSK-mediated, adult plant resistance discovered through the Njoro field trials. Our genome-wide eQTL studies demonstrate that transcript accumulation of 25% of barley genes is altered following challenge by Pgt race TTKSK, but that few of these genes are regulated by the qualitative Rpg-TTKSK on chromosome 5H. It is instead the chromosome 2H trans-eQTL hotspot that orchestrates the largest inoculation-specific responses, where enhanced resistance is associated with transcriptional suppression of hundreds of genes scattered throughout the genome. Hence, the present study associates the early suppression of genes expressed in this host-pathogen interaction with enhancement of R-gene mediated resistance.

Quantitative and Qualitative Stem Rust Resistance Factors in Barley Are Associated with Transcriptional Suppression of Defense Regulons

PubMed Central

Moscou, Matthew J.; Lauter, Nick; Steffenson, Brian; Wise, Roger P.

2011-01-01

Stem rust (Puccinia graminis f. sp. tritici; Pgt) is a devastating fungal disease of wheat and barley. Pgt race TTKSK (isolate Ug99) is a serious threat to these Triticeae grain crops because resistance is rare. In barley, the complex Rpg-TTKSK locus on chromosome 5H is presently the only known source of qualitative resistance to this aggressive Pgt race. Segregation for resistance observed on seedlings of the Q21861 × SM89010 (QSM) doubled-haploid (DH) population was found to be predominantly qualitative, with little of the remaining variance explained by loci other than Rpg-TTKSK. In contrast, analysis of adult QSM DH plants infected by field inoculum of Pgt race TTKSK in Njoro, Kenya, revealed several additional quantitative trait loci that contribute to resistance. To molecularly characterize these loci, Barley1 GeneChips were used to measure the expression of 22,792 genes in the QSM population after inoculation with Pgt race TTKSK or mock-inoculation. Comparison of expression Quantitative Trait Loci (eQTL) between treatments revealed an inoculation-dependent expression polymorphism implicating Actin depolymerizing factor3 (within the Rpg-TTKSK locus) as a candidate susceptibility gene. In parallel, we identified a chromosome 2H trans-eQTL hotspot that co-segregates with an enhancer of Rpg-TTKSK-mediated, adult plant resistance discovered through the Njoro field trials. Our genome-wide eQTL studies demonstrate that transcript accumulation of 25% of barley genes is altered following challenge by Pgt race TTKSK, but that few of these genes are regulated by the qualitative Rpg-TTKSK on chromosome 5H. It is instead the chromosome 2H trans-eQTL hotspot that orchestrates the largest inoculation-specific responses, where enhanced resistance is associated with transcriptional suppression of hundreds of genes scattered throughout the genome. Hence, the present study associates the early suppression of genes expressed in this host–pathogen interaction with enhancement of R-gene mediated resistance. PMID:21829384

Conjunctival transcriptome profiling of Solomon Islanders with active trachoma in the absence of Chlamydia trachomatis infection.

PubMed

Vasileva, Hristina; Butcher, Robert; Pickering, Harry; Sokana, Oliver; Jack, Kelvin; Solomon, Anthony W; Holland, Martin J; Roberts, Chrissy H

2018-02-21

Clinical signs of active (inflammatory) trachoma are found in many children in the Solomon Islands, but the majority of these individuals have no serological evidence of previous infection with Chlamydia trachomatis. In Temotu and Rennell and Bellona provinces, ocular infections with C. trachomatis were seldom detected among children with active trachoma; a similar lack of association was seen between active trachoma and other common bacterial and viral causes of follicular conjunctivitis. Here, we set out to characterise patterns of gene expression at the conjunctivae of children in these provinces with and without clinical signs of trachomatous inflammation-follicular (TF) and C. trachomatis infection. Purified RNA from children with and without active trachoma was run on Affymetrix GeneChip Human Transcriptome Array 2.0 microarrays. Profiles were compared between individuals with ocular C. trachomatis infection and TF (group DI; n = 6), individuals with TF but no C. trachomatis infection (group D; n = 7), and individuals without TF or C. trachomatis infection (group N; n = 7). Differential gene expression and gene set enrichment for pathway membership were assessed. Conjunctival gene expression profiles were more similar within-group than between-group. Principal components analysis indicated that the first and second principal components combined explained almost 50% of the variance in the dataset. When comparing the DI group to the N group, genes involved in T-cell proliferation, B-cell signalling and CD8+ T cell signalling pathways were differentially regulated. When comparing the DI group to the D group, CD8+ T-cell regulation, interferon-gamma and IL17 production pathways were enriched. Genes involved in RNA transcription and translation pathways were upregulated when comparing the D group to the N group. Gene expression profiles in children in the Solomon Islands indicate immune responses consistent with bacterial infection when TF and C. trachomatis infection are concurrent. The transcriptomes of children with TF but without identified infection were not consistent with allergic or viral conjunctivitis.

Transcription Analysis of the Myometrium of Labouring and Non-Labouring Women

PubMed Central

Hutchinson, James L.; Hibbert, Nanette; Freeman, Tom C.; Saunders, Philippa T. K.; Norman, Jane E.

2016-01-01

An incomplete understanding of the molecular mechanisms that initiate normal human labour at term seriously hampers the development of effective ways to predict, prevent and treat disorders such as preterm labour. Appropriate analysis of large microarray experiments that compare gene expression in non-labouring and labouring gestational tissues is necessary to help bridge these gaps in our knowledge. In this work, gene expression in 48 (22 labouring, 26 non-labouring) lower-segment myometrial samples collected at Caesarean section were analysed using Illumina HT-12 v4.0 BeadChips. Normalised data were compared between labouring and non-labouring groups using traditional statistical methods and a novel network graph approach. We sought technical validation with quantitative real-time PCR, and biological replication through inverse variance-weighted meta-analysis with published microarray data. We have extended the list of genes suggested to be associated with labour: Compared to non-labouring samples, labouring samples showed apparent higher expression at 960 probes (949 genes) and apparent lower expression at 801 probes (789 genes) (absolute fold change ≥1.2, rank product percentage of false positive value (RP-PFP) <0.05). Although half of the women in the labouring group had received pharmaceutical treatment to induce or augment labour, sensitivity analysis suggested that this did not confound our results. In agreement with previous studies, functional analysis suggested that labour was characterised by an increase in the expression of inflammatory genes and network analysis suggested a strong neutrophil signature. Our analysis also suggested that labour is characterised by a decrease in the expression of muscle-specific processes, which has not been explicitly discussed previously. We validated these findings through the first formal meta-analysis of raw data from previous experiments and we hypothesise that this represents a change in the composition of myometrial tissue at labour. Further work will be necessary to reveal whether these results are solely due to leukocyte infiltration into the myometrium as a mechanism initiating labour, or in addition whether they also represent gene changes in the myocytes themselves. We have made all our data available at www.ebi.ac.uk/arrayexpress/ (accession number E-MTAB-3136) to facilitate progression of this work. PMID:27176052

Identification and characterization of the autophagy-related genes Atg12 and Atg5 in hydra.

PubMed

Dixit, Nishikant S; Shravage, Bhupendra V; Ghaskadbi, Surendra

2017-01-01

Autophagy is an evolutionarily conserved process in eukaryotic cells that is involved in the degradation of cytoplasmic contents including organelles via the lysosome. Hydra is an early metazoan which exhibits simple tissue grade organization, a primitive nervous system, and is one of the classical non-bilaterian models extensively used in evo-devo research. Here, we describe the characterization of two core autophagy genes, Atg12 and Atg5, from hydra. In silico analyses including sequence similarity, domain analysis, and phylogenetic analysis demonstrate the conservation of these genes across eukaryotes. The predicted 3D structure of hydra Atg12 showed very little variance when compared to human Atg12 and yeast Atg12, whereas the hydra Atg5 predicted 3D structure was found to be variable, when compared with its human and yeast homologs. Strikingly, whole mount in situ hybridization showed high expression of Atg12 transcripts specifically in nematoblasts, whereas Atg5 transcripts were found to be expressed strongly in budding region and growing buds. This study may provide a framework to understand the evolution of autophagy networks in higher eukaryotes.

Application of the laser capture microdissection technique for molecular definition of skeletal cell differentiation in vivo.

PubMed

Benayahu, Dafna; Socher, Rina; Shur, Irena

2008-01-01

Laser capture microdissection (LCM) method allows selection of individual or clustered cells from intact tissues. This technology enables one to pick cells from tissues that are difficult to study individually, sort the anatomical complexity of these tissues, and make the cells available for molecular analyses. Following the cells' extraction, the nucleic acids and proteins can be isolated and used for multiple applications that provide an opportunity to uncover the molecular control of cellular fate in the natural microenvironment. Utilization of LCM for the molecular analysis of cells from skeletal tissues will enable one to study differential patterns of gene expression in the native intact skeletal tissue with reliable interpretation of function for known genes as well as to discover novel genes. Variability between samples may be caused either by differences in the tissue samples (different areas isolated from the same section) or some variances in sample handling. LCM is a multi-task technology that combines histology, microscopy work, and dedicated molecular biology. The LCM application will provide results that will pave the way toward high throughput profiling of tissue-specific gene expression using Gene Chip arrays. Detailed description of in vivo molecular pathways will make it possible to elaborate on control systems to apply for the repair of genetic or metabolic diseases of skeletal tissues.

Bayesian inference of the number of factors in gene-expression analysis: application to human virus challenge studies

PubMed Central

2010-01-01

Background Nonparametric Bayesian techniques have been developed recently to extend the sophistication of factor models, allowing one to infer the number of appropriate factors from the observed data. We consider such techniques for sparse factor analysis, with application to gene-expression data from three virus challenge studies. Particular attention is placed on employing the Beta Process (BP), the Indian Buffet Process (IBP), and related sparseness-promoting techniques to infer a proper number of factors. The posterior density function on the model parameters is computed using Gibbs sampling and variational Bayesian (VB) analysis. Results Time-evolving gene-expression data are considered for respiratory syncytial virus (RSV), Rhino virus, and influenza, using blood samples from healthy human subjects. These data were acquired in three challenge studies, each executed after receiving institutional review board (IRB) approval from Duke University. Comparisons are made between several alternative means of per-forming nonparametric factor analysis on these data, with comparisons as well to sparse-PCA and Penalized Matrix Decomposition (PMD), closely related non-Bayesian approaches. Conclusions Applying the Beta Process to the factor scores, or to the singular values of a pseudo-SVD construction, the proposed algorithms infer the number of factors in gene-expression data. For real data the "true" number of factors is unknown; in our simulations we consider a range of noise variances, and the proposed Bayesian models inferred the number of factors accurately relative to other methods in the literature, such as sparse-PCA and PMD. We have also identified a "pan-viral" factor of importance for each of the three viruses considered in this study. We have identified a set of genes associated with this pan-viral factor, of interest for early detection of such viruses based upon the host response, as quantified via gene-expression data. PMID:21062443

Exploring homogeneity of correlation structures of gene expression datasets within and between etiological disease categories.

PubMed

Jong, Victor L; Novianti, Putri W; Roes, Kit C B; Eijkemans, Marinus J C

2014-12-01

The literature shows that classifiers perform differently across datasets and that correlations within datasets affect the performance of classifiers. The question that arises is whether the correlation structure within datasets differ significantly across diseases. In this study, we evaluated the homogeneity of correlation structures within and between datasets of six etiological disease categories; inflammatory, immune, infectious, degenerative, hereditary and acute myeloid leukemia (AML). We also assessed the effect of filtering; detection call and variance filtering on correlation structures. We downloaded microarray datasets from ArrayExpress for experiments meeting predefined criteria and ended up with 12 datasets for non-cancerous diseases and six for AML. The datasets were preprocessed by a common procedure incorporating platform-specific recommendations and the two filtering methods mentioned above. Homogeneity of correlation matrices between and within datasets of etiological diseases was assessed using the Box's M statistic on permuted samples. We found that correlation structures significantly differ between datasets of the same and/or different etiological disease categories and that variance filtering eliminates more uncorrelated probesets than detection call filtering and thus renders the data highly correlated.

Reparameterization of PAM50 Expression Identifies Novel Breast Tumor Dimensions and Leads to Discovery of a Genome-Wide Significant Breast Cancer Locus at 12q15.

PubMed

Madsen, Michael J; Knight, Stacey; Sweeney, Carol; Factor, Rachel; Salama, Mohamed; Stijleman, Inge J; Rajamanickam, Venkatesh; Welm, Bryan E; Arunachalam, Sasi; Jones, Brandt; Rachamadugu, Rakesh; Rowe, Kerry; Cessna, Melissa H; Thomas, Alun; Kushi, Lawrence H; Caan, Bette J; Bernard, Philip S; Camp, Nicola J

2018-06-01

Background: Breast tumor subtyping has failed to provide impact in susceptibility genetics. The PAM50 assay categorizes breast tumors into: Luminal A, Luminal B, HER2-enriched and Basal-like. However, tumors are often more complex than simple categorization can describe. The identification of heritable tumor characteristics has potential to decrease heterogeneity and increase power for gene finding. Methods: We used 911 sporadic breast tumors with PAM50 expression data to derive tumor dimensions using principal components (PC). Dimensions in 238 tumors from high-risk pedigrees were compared with the sporadic tumors. Proof-of-concept gene mapping, informed by tumor dimension, was performed using Shared Genomic Segment (SGS) analysis. Results: Five dimensions (PC1-5) explained the majority of the PAM50 expression variance: three captured intrinsic subtype, two were novel (PC3, PC5). All five replicated in 745 TCGA tumors. Both novel dimensions were significantly enriched in the high-risk pedigrees (intrinsic subtypes were not). SGS gene-mapping in a pedigree identified a 0.5 Mb genome-wide significant region at 12q15 This region segregated through 32 meioses to 8 breast cancer cases with extreme PC3 tumors ( P = 2.6 × 10 -8 ). Conclusions: PC analysis of PAM50 gene expression revealed multiple independent, quantitative measures of tumor diversity. These tumor dimensions show evidence for heritability and potential as powerful traits for gene mapping. Impact: Our study suggests a new approach to describe tumor expression diversity, provides new avenues for germline studies, and proposes a new breast cancer locus. Similar reparameterization of expression patterns may inform other studies attempting to model the effects of tumor heterogeneity. Cancer Epidemiol Biomarkers Prev; 27(6); 644-52. ©2018 AACR . ©2018 American Association for Cancer Research.

Why weight? Modelling sample and observational level variability improves power in RNA-seq analyses.

PubMed

Liu, Ruijie; Holik, Aliaksei Z; Su, Shian; Jansz, Natasha; Chen, Kelan; Leong, Huei San; Blewitt, Marnie E; Asselin-Labat, Marie-Liesse; Smyth, Gordon K; Ritchie, Matthew E

2015-09-03

Variations in sample quality are frequently encountered in small RNA-sequencing experiments, and pose a major challenge in a differential expression analysis. Removal of high variation samples reduces noise, but at a cost of reducing power, thus limiting our ability to detect biologically meaningful changes. Similarly, retaining these samples in the analysis may not reveal any statistically significant changes due to the higher noise level. A compromise is to use all available data, but to down-weight the observations from more variable samples. We describe a statistical approach that facilitates this by modelling heterogeneity at both the sample and observational levels as part of the differential expression analysis. At the sample level this is achieved by fitting a log-linear variance model that includes common sample-specific or group-specific parameters that are shared between genes. The estimated sample variance factors are then converted to weights and combined with observational level weights obtained from the mean-variance relationship of the log-counts-per-million using 'voom'. A comprehensive analysis involving both simulations and experimental RNA-sequencing data demonstrates that this strategy leads to a universally more powerful analysis and fewer false discoveries when compared to conventional approaches. This methodology has wide application and is implemented in the open-source 'limma' package. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

The distribution of genetic variance across phenotypic space and the response to selection.

PubMed

Blows, Mark W; McGuigan, Katrina

2015-05-01

The role of adaptation in biological invasions will depend on the availability of genetic variation for traits under selection in the new environment. Although genetic variation is present for most traits in most populations, selection is expected to act on combinations of traits, not individual traits in isolation. The distribution of genetic variance across trait combinations can be characterized by the empirical spectral distribution of the genetic variance-covariance (G) matrix. Empirical spectral distributions of G from a range of trait types and taxa all exhibit a characteristic shape; some trait combinations have large levels of genetic variance, while others have very little genetic variance. In this study, we review what is known about the empirical spectral distribution of G and show how it predicts the response to selection across phenotypic space. In particular, trait combinations that form a nearly null genetic subspace with little genetic variance respond only inconsistently to selection. We go on to set out a framework for understanding how the empirical spectral distribution of G may differ from the random expectations that have been developed under random matrix theory (RMT). Using a data set containing a large number of gene expression traits, we illustrate how hypotheses concerning the distribution of multivariate genetic variance can be tested using RMT methods. We suggest that the relative alignment between novel selection pressures during invasion and the nearly null genetic subspace is likely to be an important component of the success or failure of invasion, and for the likelihood of rapid adaptation in small populations in general. © 2014 John Wiley & Sons Ltd.

Evolution and inheritance of early embryonic patterning in D. simulans and D. sechellia

PubMed Central

Lott, Susan E.; Ludwig, Michael Z.; Kreitman, Martin

2010-01-01

Pattern formation in Drosophila is a widely studied example of a robust developmental system. Such robust systems pose a challenge to adaptive evolution, as they mask variation which selection may otherwise act upon. Yet we find variation in the localization of expression domains (henceforth ‘stripe allometry’) in the pattern formation pathway. Specifically, we characterize differences in the gap genes giant and Kruppel, and the pair-rule gene even-skipped, which differ between the sibling species D. simulans and D. sechellia. In a double-backcross experiment, stripe allometry is consistent with maternal inheritance of stripe positioning and multiple genetic factors, with a distinct genetic basis from embryo length. Embryos produced by F1 and F2 backcross mothers exhibit novel spatial patterns of gene expression relative to the parental species, with no measurable increase in positional variance among individuals. Buffering of novel spatial patterns in the backcross genotypes suggests that robustness need not be disrupted in order for the trait to evolve, and perhaps the system is incapable of evolving to prevent the expression of all genetic variation. This limitation, and the ability of natural selection to act on minute genetic differences that are within the “margin of error” for the buffering mechanism, indicates that developmentally buffered traits can evolve without disruption of robustness PMID:21121913

Tumour-associated and non-tumour-associated microbiota in colorectal cancer

PubMed Central

Flemer, Burkhardt; Lynch, Denise B; Brown, Jillian M R; Jeffery, Ian B; Ryan, Feargal J; Claesson, Marcus J; O'Riordain, Micheal; Shanahan, Fergus; O'Toole, Paul W

2017-01-01

Objective A signature that unifies the colorectal cancer (CRC) microbiota across multiple studies has not been identified. In addition to methodological variance, heterogeneity may be caused by both microbial and host response differences, which was addressed in this study. Design We prospectively studied the colonic microbiota and the expression of specific host response genes using faecal and mucosal samples (‘ON’ and ‘OFF’ the tumour, proximal and distal) from 59 patients undergoing surgery for CRC, 21 individuals with polyps and 56 healthy controls. Microbiota composition was determined by 16S rRNA amplicon sequencing; expression of host genes involved in CRC progression and immune response was quantified by real-time quantitative PCR. Results The microbiota of patients with CRC differed from that of controls, but alterations were not restricted to the cancerous tissue. Differences between distal and proximal cancers were detected and faecal microbiota only partially reflected mucosal microbiota in CRC. Patients with CRC can be stratified based on higher level structures of mucosal-associated bacterial co-abundance groups (CAGs) that resemble the previously formulated concept of enterotypes. Of these, Bacteroidetes Cluster 1 and Firmicutes Cluster 1 were in decreased abundance in CRC mucosa, whereas Bacteroidetes Cluster 2, Firmicutes Cluster 2, Pathogen Cluster and Prevotella Cluster showed increased abundance in CRC mucosa. CRC-associated CAGs were differentially correlated with the expression of host immunoinflammatory response genes. Conclusions CRC-associated microbiota profiles differ from those in healthy subjects and are linked with distinct mucosal gene-expression profiles. Compositional alterations in the microbiota are not restricted to cancerous tissue and differ between distal and proximal cancers. PMID:26992426

Continuous variation caused by genes with graduated effects.

PubMed Central

Matthysse, S; Lange, K; Wagener, D K

1979-01-01

The classical polygenic theory of inheritance postulates a large number of genes with small, and essentially similar, effects. We propose instead a model with genes of gradually decreasing effects. The resulting phenotypic distribution is not normal; if the gene effects are geometrically decreasing, it can be triangular. The joint distribution of parent and offspring genic value is calculated. The most readily testable difference between the two models is that, in the decreasing-effect model, the variance of the offspring distribution from given parents depends on the parents' genic values. The more the parents deviate from the mean, the smaller the variance of the offspring should be. In the equal-effect model the offspring variance is independent of the parents' genic values. PMID:288073

Inference from clustering with application to gene-expression microarrays.

PubMed

Dougherty, Edward R; Barrera, Junior; Brun, Marcel; Kim, Seungchan; Cesar, Roberto M; Chen, Yidong; Bittner, Michael; Trent, Jeffrey M

2002-01-01

There are many algorithms to cluster sample data points based on nearness or a similarity measure. Often the implication is that points in different clusters come from different underlying classes, whereas those in the same cluster come from the same class. Stochastically, the underlying classes represent different random processes. The inference is that clusters represent a partition of the sample points according to which process they belong. This paper discusses a model-based clustering toolbox that evaluates cluster accuracy. Each random process is modeled as its mean plus independent noise, sample points are generated, the points are clustered, and the clustering error is the number of points clustered incorrectly according to the generating random processes. Various clustering algorithms are evaluated based on process variance and the key issue of the rate at which algorithmic performance improves with increasing numbers of experimental replications. The model means can be selected by hand to test the separability of expected types of biological expression patterns. Alternatively, the model can be seeded by real data to test the expected precision of that output or the extent of improvement in precision that replication could provide. In the latter case, a clustering algorithm is used to form clusters, and the model is seeded with the means and variances of these clusters. Other algorithms are then tested relative to the seeding algorithm. Results are averaged over various seeds. Output includes error tables and graphs, confusion matrices, principal-component plots, and validation measures. Five algorithms are studied in detail: K-means, fuzzy C-means, self-organizing maps, hierarchical Euclidean-distance-based and correlation-based clustering. The toolbox is applied to gene-expression clustering based on cDNA microarrays using real data. Expression profile graphics are generated and error analysis is displayed within the context of these profile graphics. A large amount of generated output is available over the web.

Spatial analysis and high resolution mapping of the human whole-brain transcriptome for integrative analysis in neuroimaging.

PubMed

Gryglewski, Gregor; Seiger, René; James, Gregory Miles; Godbersen, Godber Mathis; Komorowski, Arkadiusz; Unterholzner, Jakob; Michenthaler, Paul; Hahn, Andreas; Wadsak, Wolfgang; Mitterhauser, Markus; Kasper, Siegfried; Lanzenberger, Rupert

2018-08-01

The quantification of big pools of diverse molecules provides important insights on brain function, but is often restricted to a limited number of observations, which impairs integration with other modalities. To resolve this issue, a method allowing for the prediction of mRNA expression in the entire brain based on microarray data provided in the Allen Human Brain Atlas was developed. Microarray data of 3702 samples from 6 brain donors was registered to MNI and cortical surface space using FreeSurfer. For each of 18,686 genes, spatial dependence of transcription was assessed using variogram modelling. Variogram models were employed in Gaussian process regression to calculate best linear unbiased predictions for gene expression at all locations represented in well-established imaging atlases for cortex, subcortical structures and cerebellum. For validation, predicted whole-brain transcription of the HTR1A gene was correlated with [carbonyl- 11 C]WAY-100635 positron emission tomography data collected from 30 healthy subjects. Prediction results showed minimal bias ranging within ±0.016 (cortical surface), ±0.12 (subcortical regions) and ±0.14 (cerebellum) in units of log2 expression intensity for all genes. Across genes, the correlation of predicted and observed mRNA expression in leave-one-out cross-validation correlated with the strength of spatial dependence (cortical surface: r = 0.91, subcortical regions: r = 0.85, cerebellum: r = 0.84). 816 out of 18,686 genes exhibited a high spatial dependence accounting for more than 50% of variance in the difference of gene expression on the cortical surface. In subcortical regions and cerebellum, different sets of genes were implicated by high spatially structured variability. For the serotonin 1A receptor, correlation between PET binding potentials and predicted comprehensive mRNA expression was markedly higher (Spearman ρ = 0.72 for cortical surface, ρ = 0.84 for subcortical regions) than correlation of PET and discrete samples only (ρ = 0.55 and ρ = 0.63, respectively). Prediction of mRNA expression in the entire human brain allows for intuitive visualization of gene transcription and seamless integration in multimodal analysis without bias arising from non-uniform distribution of available samples. Extension of this methodology promises to facilitate translation of omics research and enable investigation of human brain function at a systems level. Copyright © 2018 Elsevier Inc. All rights reserved.

Evaluation of the branched-chain DNA assay for measurement of RNA in formalin-fixed tissues.

PubMed

Knudsen, Beatrice S; Allen, April N; McLerran, Dale F; Vessella, Robert L; Karademos, Jonathan; Davies, Joan E; Maqsodi, Botoul; McMaster, Gary K; Kristal, Alan R

2008-03-01

We evaluated the branched-chain DNA (bDNA) assay QuantiGene Reagent System to measure RNA in formalin-fixed, paraffin-embedded (FFPE) tissues. The QuantiGene Reagent System does not require RNA isolation, avoids enzymatic preamplification, and has a simple workflow. Five selected genes were measured by bDNA assay; quantitative polymerase chain reaction (qPCR) was used as a reference method. Mixed-effect statistical models were used to partition the overall variance into components attributable to xenograft, sample, and assay. For FFPE tissues, the coefficients of reliability were significantly higher for the bDNA assay (93-100%) than for qPCR (82.4-95%). Correlations between qPCR(FROZEN), the gold standard, and bDNA(FFPE) ranged from 0.60 to 0.94, similar to those from qPCR(FROZEN) and qPCR(FFPE). Additionally, the sensitivity of the bDNA assay in tissue homogenates was 10-fold higher than in purified RNA. In 9- to 13-year-old blocks with poor RNA quality, the bDNA assay allowed the correct identification of the overexpression of known cancer genes. In conclusion, the QuantiGene Reagent System is considerably more reliable, reproducible, and sensitive than qPCR, providing an alternative method for the measurement of gene expression in FFPE tissues. It also appears to be well suited for the clinical analysis of FFPE tissues with diagnostic or prognostic gene expression biomarker panels for use in patient treatment and management.

Evaluation of the Branched-Chain DNA Assay for Measurement of RNA in Formalin-Fixed Tissues

PubMed Central

Knudsen, Beatrice S.; Allen, April N.; McLerran, Dale F.; Vessella, Robert L.; Karademos, Jonathan; Davies, Joan E.; Maqsodi, Botoul; McMaster, Gary K.; Kristal, Alan R.

2008-01-01

We evaluated the branched-chain DNA (bDNA) assay QuantiGene Reagent System to measure RNA in formalin-fixed, paraffin-embedded (FFPE) tissues. The QuantiGene Reagent System does not require RNA isolation, avoids enzymatic preamplification, and has a simple workflow. Five selected genes were measured by bDNA assay; quantitative polymerase chain reaction (qPCR) was used as a reference method. Mixed-effect statistical models were used to partition the overall variance into components attributable to xenograft, sample, and assay. For FFPE tissues, the coefficients of reliability were significantly higher for the bDNA assay (93–100%) than for qPCR (82.4–95%). Correlations between qPCRFROZEN, the gold standard, and bDNAFFPE ranged from 0.60 to 0.94, similar to those from qPCRFROZEN and qPCRFFPE. Additionally, the sensitivity of the bDNA assay in tissue homogenates was 10-fold higher than in purified RNA. In 9- to 13-year-old blocks with poor RNA quality, the bDNA assay allowed the correct identification of the overexpression of known cancer genes. In conclusion, the QuantiGene Reagent System is considerably more reliable, reproducible, and sensitive than qPCR, providing an alternative method for the measurement of gene expression in FFPE tissues. It also appears to be well suited for the clinical analysis of FFPE tissues with diagnostic or prognostic gene expression biomarker panels for use in patient treatment and management. PMID:18276773

Beyond mean allelic effects: A locus at the major color gene MC1R associates also with differing levels of phenotypic and genetic (co)variance for coloration in barn owls.

PubMed

San-Jose, Luis M; Ducret, Valérie; Ducrest, Anne-Lyse; Simon, Céline; Roulin, Alexandre

2017-10-01

The mean phenotypic effects of a discovered variant help to predict major aspects of the evolution and inheritance of a phenotype. However, differences in the phenotypic variance associated to distinct genotypes are often overlooked despite being suggestive of processes that largely influence phenotypic evolution, such as interactions between the genotypes with the environment or the genetic background. We present empirical evidence for a mutation at the melanocortin-1-receptor gene, a major vertebrate coloration gene, affecting phenotypic variance in the barn owl, Tyto alba. The white MC1R allele, which associates with whiter plumage coloration, also associates with a pronounced phenotypic and additive genetic variance for distinct color traits. Contrarily, the rufous allele, associated with a rufous coloration, relates to a lower phenotypic and additive genetic variance, suggesting that this allele may be epistatic over other color loci. Variance differences between genotypes entailed differences in the strength of phenotypic and genetic associations between color traits, suggesting that differences in variance also alter the level of integration between traits. This study highlights that addressing variance differences of genotypes in wild populations provides interesting new insights into the evolutionary mechanisms and the genetic architecture underlying the phenotype. © 2017 The Author(s). Evolution © 2017 The Society for the Study of Evolution.

Split-plot microarray experiments: issues of design, power and sample size.

PubMed

Tsai, Pi-Wen; Lee, Mei-Ling Ting

2005-01-01

This article focuses on microarray experiments with two or more factors in which treatment combinations of the factors corresponding to the samples paired together onto arrays are not completely random. A main effect of one (or more) factor(s) is confounded with arrays (the experimental blocks). This is called a split-plot microarray experiment. We utilise an analysis of variance (ANOVA) model to assess differentially expressed genes for between-array and within-array comparisons that are generic under a split-plot microarray experiment. Instead of standard t- or F-test statistics that rely on mean square errors of the ANOVA model, we use a robust method, referred to as 'a pooled percentile estimator', to identify genes that are differentially expressed across different treatment conditions. We illustrate the design and analysis of split-plot microarray experiments based on a case application described by Jin et al. A brief discussion of power and sample size for split-plot microarray experiments is also presented.

Hypothalamic transcriptomes of 99 mouse strains reveal trans eQTL hotspots, splicing QTLs and novel non-coding genes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hasin-Brumshtein, Yehudit; Khan, Arshad H.; Hormozdiari, Farhad

2016-09-13

Previous studies had shown that the integration of genome wide expression profiles, in metabolic tissues, with genetic and phenotypic variance, provided valuable insight into the underlying molecular mechanisms. We used RNA-Seq to characterize hypothalamic transcriptome in 99 inbred strains of mice from the Hybrid Mouse Diversity Panel (HMDP), a reference resource population for cardiovascular and metabolic traits. We report numerous novel transcripts supported by proteomic analyses, as well as novel non coding RNAs. High resolution genetic mapping of transcript levels in HMDP, reveals bothlocalandtransexpression Quantitative Trait Loci (eQTLs) demonstrating 2transeQTL 'hotspots' associated with expression of hundreds of genes. We alsomore » report thousands of alternative splicing events regulated by genetic variants. Finally, comparison with about 150 metabolic and cardiovascular traits revealed many highly significant associations. Our data provide a rich resource for understanding the many physiologic functions mediated by the hypothalamus and their genetic regulation.« less

Differential Expression of Inflammatory Cytokines and Stress Genes in Male and Female Mice in Response to a Lipopolysaccharide Challenge

PubMed Central

Everhardt Queen, Ashleigh; Moerdyk-Schauwecker, Megan; McKee, Leslie M.; Leamy, Larry J.

2016-01-01

Background Sex plays a key role in an individual’s immune response against pathogenic challenges such that females fare better when infected with certain pathogens. It is thought that sex hormones impact gene expression in immune cells and lead to sexually dimorphic responses to pathogens. We predicted that, in the presence of E. coli gram-negative lipopolysaccharide (LPS), there would be a sexually dimorphic response in proinflammatory cytokine production and acute phase stress gene expression and that these responses might vary among different mouse strains and times in a pattern opposite to that of body temperature associated with LPS-induced shock. Materials and Methods Interleukin-6 (IL-6), macrophage inflammatory protein-Iβ (MIP-1β), tumor necrosis factor alpha (TNF-α) and interleukin-1β (IL-1β) as well as beta-fibrinogen (Fgb) and metallothionein-1 (Mt-1) mRNA expression were measured at four time points (0, 2, 4 and 7 hours) after injection of E. coli LPS in mice from three inbred strains. Results Statistical analysis using analyses of variance (ANOVAs) showed that the levels of the all six traits changed over time, generally peaking at 2 hours after LPS injection. Mt-1, Fgb, and IL-6 showed differences among strains, although these were time-specific. Sexual dimorphism was seen for Fgb and IL6, and was most pronounced at the latest time period (7 hours) where male levels exceeded those for females. Trends for all six cytokine/gene expression traits were negatively correlated with those for body temperatures. Discussion The higher levels of expression of Fgb and IL6 in males compared with females are consistent with the greater vulnerability of males to infection and subsequent inflammation. Temperature appears to be a useful proxy for mortality in endotoxic shock, but sexual dimorphism in cytokine and stress gene expression levels may persist after an LPS challenge even if temperatures in the two sexes are similar and have begun to stabilize. PMID:27120355

Gene expression-based dosimetry by dose and time in mice following acute radiation exposure.

PubMed

Tucker, James D; Divine, George W; Grever, William E; Thomas, Robert A; Joiner, Michael C; Smolinski, Joseph M; Auner, Gregory W

2013-01-01

Rapid and reliable methods for performing biological dosimetry are of paramount importance in the event of a large-scale nuclear event. Traditional dosimetry approaches lack the requisite rapid assessment capability, ease of use, portability and low cost, which are factors needed for triaging a large number of victims. Here we describe the results of experiments in which mice were acutely exposed to (60)Co gamma rays at doses of 0 (control) to 10 Gy. Blood was obtained from irradiated mice 0.5, 1, 2, 3, 5, and 7 days after exposure. mRNA expression levels of 106 selected genes were obtained by reverse-transcription real time PCR. Stepwise regression of dose received against individual gene transcript expression levels provided optimal dosimetry at each time point. The results indicate that only 4-7 different gene transcripts are needed to explain ≥ 0.69 of the variance (R(2)), and that receiver-operator characteristics, a measure of sensitivity and specificity, of ≥ 0.93 for these statistical models were achieved at each time point. These models provide an excellent description of the relationship between the actual and predicted doses up to 6 Gy. At doses of 8 and 10 Gy there appears to be saturation of the radiation-response signals with a corresponding diminution of accuracy. These results suggest that similar analyses in humans may be advantageous for use in a field-portable device designed to assess exposures in mass casualty situations.

Selenium and Vitamin E: Cell Type– and Intervention-Specific Tissue Effects in Prostate Cancer

PubMed Central

Tsavachidou, Dimitra; McDonnell, Timothy J.; Wen, Sijin; Wang, Xuemei; Vakar-Lopez, Funda; Pisters, Louis L.; Pettaway, Curtis A.; Wood, Christopher G.; Do, Kim-Anh; Thall, Peter F.; Stephens, Clifton; Efstathiou, Eleni; Taylor, Robert; Menter, David G.; Troncoso, Patricia; Lippman, Scott M.; Logothetis, Christopher J.

2009-01-01

Background Secondary analyses of two randomized, controlled phase III trials demonstrated that selenium and vitamin E could reduce prostate cancer incidence. To characterize pharmacodynamic and gene expression effects associated with use of selenium and vitamin E, we undertook a randomized, placebo-controlled phase IIA study of prostate cancer patients before prostatectomy and created a preoperative model for prostatectomy tissue interrogation. Methods Thirty-nine men with prostate cancer were randomly assigned to treatment with 200 μg of selenium, 400 IU of vitamin E, both, or placebo. Laser capture microdissection of prostatectomy biopsy specimens was used to isolate normal, stromal, and tumor cells. Gene expression in each cell type was studied with microarray analysis and validated with a real-time polymerase chain reaction (PCR) and immunohistochemistry. An analysis of variance model was fit to identify genes differentially expressed between treatments and cell types. A beta-uniform mixture model was used to analyze differential expression of genes and to assess the false discovery rate. All statistical tests were two-sided. Results The highest numbers of differentially expressed genes by treatment were 1329 (63%) of 2109 genes in normal epithelial cells after selenium treatment, 1354 (66%) of 2051 genes in stromal cells after vitamin E treatment, and 329 (56%) of 587 genes in tumor cells after combination treatment (false discovery rate = 2%). Validation of 21 representative genes across all treatments and all cell types yielded Spearman correlation coefficients between the microarray analysis and the PCR validation ranging from 0.64 (95% confidence interval [CI] = 0.31 to 0.79) for the vitamin E group to 0.87 (95% CI = 0.53 to 0.99) for the selenium group. The increase in the mean percentage of p53-positive tumor cells in the selenium-treated group (26.3%), compared with that in the placebo-treated group (5%), showed borderline statistical significance (difference = 21.3%; 95% CI = 0.7 to 41.8; P = .051). Conclusions We have demonstrated the feasibility and efficiency of the preoperative model and its power as a hypothesis-generating engine. We have also identified cell type– and zone-specific tissue effects of interventions with selenium and vitamin E that may have clinical implications. PMID:19244175

Examining Radiation-Induced In Vivo and In Vitro Gene Expression Changes of the Peripheral Blood in Different Laboratories for Biodosimetry Purposes: First RENEB Gene Expression Study.

PubMed

Abend, M; Badie, C; Quintens, R; Kriehuber, R; Manning, G; Macaeva, E; Njima, M; Oskamp, D; Strunz, S; Moertl, S; Doucha-Senf, S; Dahlke, S; Menzel, J; Port, M

2016-02-01

The risk of a large-scale event leading to acute radiation exposure necessitates the development of high-throughput methods for providing rapid individual dose estimates. Our work addresses three goals, which align with the directive of the European Union's Realizing the European Network of Biodosimetry project (EU-RENB): 1. To examine the suitability of different gene expression platforms for biodosimetry purposes; 2. To perform this examination using blood samples collected from prostate cancer patients (in vivo) and from healthy donors (in vitro); and 3. To compare radiation-induced gene expression changes of the in vivo with in vitro blood samples. For the in vitro part of this study, EDTA-treated whole blood was irradiated immediately after venipuncture using single X-ray doses (1 Gy/min(-1) dose rate, 100 keV). Blood samples used to generate calibration curves as well as 10 coded (blinded) samples (0-4 Gy dose range) were incubated for 24 h in vitro, lysed and shipped on wet ice. For the in vivo part of the study PAXgene tubes were used and peripheral blood (2.5 ml) was collected from prostate cancer patients before and 24 h after the first fractionated 2 Gy dose of localized radiotherapy to the pelvis [linear accelerator (LINAC), 580 MU/min, exposure 1-1.5 min]. Assays were run in each laboratory according to locally established protocols using either microarray platforms (2 laboratories) or qRT-PCR (2 laboratories). Report times on dose estimates were documented. The mean absolute difference of estimated doses relative to the true doses (Gy) were calculated. Doses were also merged into binary categories reflecting aspects of clinical/diagnostic relevance. For the in vitro part of the study, the earliest report time on dose estimates was 7 h for qRT-PCR and 35 h for microarrays. Methodological variance of gene expression measurements (CV ≤10% for technical replicates) and interindividual variance (≤twofold for all genes) were low. Dose estimates based on one gene, ferredoxin reductase (FDXR), using qRT-PCR were as precise as dose estimates based on multiple genes using microarrays, but the precision decreased at doses ≥2 Gy. Binary dose categories comprising, for example, unexposed compared with exposed samples, could be completely discriminated with most of our methods. Exposed prostate cancer blood samples (n = 4) could be completely discriminated from unexposed blood samples (n = 4, P < 0.03, two-sided Fisher's exact test) without individual controls. This could be performed by introducing an in vitro-to-in vivo correction factor of FDXR, which varied among the laboratories. After that the in vitro-constructed calibration curves could be used for dose estimation of the in vivo exposed prostate cancer blood samples within an accuracy window of ±0.5 Gy in both contributing qRT-PCR laboratories. In conclusion, early and precise dose estimates can be performed, in particular at doses ≤2 Gy in vitro. Blood samples of prostate cancer patients exposed to 0.09-0.017 Gy could be completely discriminated from pre-exposure blood samples with the doses successfully estimated using adjusted in vitro-constructed calibration curves.

Volcano plots in analyzing differential expressions with mRNA microarrays.

PubMed

Li, Wentian

2012-12-01

A volcano plot displays unstandardized signal (e.g. log-fold-change) against noise-adjusted/standardized signal (e.g. t-statistic or -log(10)(p-value) from the t-test). We review the basic and interactive use of the volcano plot and its crucial role in understanding the regularized t-statistic. The joint filtering gene selection criterion based on regularized statistics has a curved discriminant line in the volcano plot, as compared to the two perpendicular lines for the "double filtering" criterion. This review attempts to provide a unifying framework for discussions on alternative measures of differential expression, improved methods for estimating variance, and visual display of a microarray analysis result. We also discuss the possibility of applying volcano plots to other fields beyond microarray.

Defining genes using "blueprint" versus "instruction" metaphors: effects for genetic determinism, response efficacy, and perceived control.

PubMed

Parrott, Roxanne; Smith, Rachel A

2014-01-01

Evidence supports mixed attributions aligned with personal and/or clinical control and gene expression for health in this era of genomic science and health care. We consider variance in these attributions and possible relationships to individual mind sets associated with essentialist beliefs that genes determine health versus threat beliefs that genes increase susceptibility for disease and severity linked to gene-environment interactions. Further, we contribute to theory and empirical research to evaluate the use of metaphors to define genes. Participants (N = 324) read a message that varied the introduction by providing a definition of genes that used either an "instruction" metaphor or a "blueprint" metaphor. The "instruction" metaphor compared to the "blueprint" metaphor promoted stronger threat perceptions, which aligned with both belief in the response efficacy of genetic research for health and perceived behavioral control linked to genes and health. The "blueprint" metaphor compared to the "instruction" metaphor promoted stronger essentialist beliefs, which aligned with more intense positive regard for the efficacy of genetic research and human health. Implications for health communicators include societal effects aligned with stigma and discrimination that such findings portend.

A genetic modifier suggests that endurance exercise exacerbates Huntington's disease

PubMed Central

Corrochano, Silvia; Blanco, Gonzalo; Williams, Debbie; Wettstein, Jessica; Simon, Michelle; Kumar, Saumya; Moir, Lee; Agnew, Thomas; Stewart, Michelle; Landman, Allison; Kotiadis, Vassilios N; Duchen, Michael R; Wackerhage, Henning; Rubinsztein, David C; Brown, Steve D M

2018-01-01

Abstract Polyglutamine expansions in the huntingtin gene cause Huntington’s disease (HD). Huntingtin is ubiquitously expressed, leading to pathological alterations also in peripheral organs. Variations in the length of the polyglutamine tract explain up to 70% of the age-at-onset variance, with the rest of the variance attributed to genetic and environmental modifiers. To identify novel disease modifiers, we performed an unbiased mutagenesis screen on an HD mouse model, identifying a mutation in the skeletal muscle voltage-gated sodium channel (Scn4a, termed ‘draggen’ mutation) as a novel disease enhancer. Double mutant mice (HD; Scn4aDgn/+) had decreased survival, weight loss and muscle atrophy. Expression patterns show that the main tissue affected is skeletal muscle. Intriguingly, muscles from HD; Scn4aDgn/+ mice showed adaptive changes similar to those found in endurance exercise, including AMPK activation, fibre type switching and upregulation of mitochondrial biogenesis. Therefore, we evaluated the effects of endurance training on HD mice. Crucially, this training regime also led to detrimental effects on HD mice. Overall, these results reveal a novel role for skeletal muscle in modulating systemic HD pathogenesis, suggesting that some forms of physical exercise could be deleterious in neurodegeneration. PMID:29509900

Expression of the filaggrin gene in umbilical cord blood predicts eczema risk in infancy: A birth cohort study.

PubMed

Ziyab, A H; Ewart, S; Lockett, G A; Zhang, H; Arshad, H; Holloway, J W; Karmaus, W

2017-09-01

Filaggrin gene (FLG) expression, particularly in the skin, has been linked to the development of the skin barrier and is associated with eczema risk. However, knowledge as to whether FLG expression in umbilical cord blood (UCB) is associated with eczema development and prediction is lacking. This study sought to assess whether FLG expression in UCB associates with and predicts the development of eczema in infancy. Infants enrolled in a birth cohort study (n=94) were assessed for eczema at ages 3, 6, and 12 months. Five probes measuring FLG transcripts expression in UCB were available from genomewide gene expression profiling. FLG genetic variants R501X, 2282del4, and S3247X were genotyped. Associations were assessed using Poisson regression with robust variance estimation. Area under the curve (AUC), describing the discriminatory/predictive performance of fitted models, was estimated from logistic regression. Increased level of FLG expression measured by probe A_24_P51322 was associated with reduced risk of eczema during the first year of life (RR=0.60, 95% CI: 0.38-0.95). In contrast, increased level of FLG antisense transcripts measured by probe A_21_P0014075 was associated with increased risk of eczema (RR=2.02, 95% CI: 1.10-3.72). In prediction models including FLG expression, FLG genetic variants, and sex, discrimination between children who will and will not develop eczema at 3 months of age was high (AUC: 0.91, 95% CI: 0.84-0.98). This study demonstrated, for the first time, that FLG expression in UCB is associated with eczema development in infancy. Moreover, our analysis provided prediction models that were capable of discriminating, to a great extent, between those who will and will not develop eczema in infancy. Therefore, early identification of infants at increased risk of developing eczema is possible and such high-risk newborns may benefit from early stratification and intervention. © 2017 John Wiley & Sons Ltd.

Hierarchical Bayesian modelling of gene expression time series across irregularly sampled replicates and clusters.

PubMed

Hensman, James; Lawrence, Neil D; Rattray, Magnus

2013-08-20

Time course data from microarrays and high-throughput sequencing experiments require simple, computationally efficient and powerful statistical models to extract meaningful biological signal, and for tasks such as data fusion and clustering. Existing methodologies fail to capture either the temporal or replicated nature of the experiments, and often impose constraints on the data collection process, such as regularly spaced samples, or similar sampling schema across replications. We propose hierarchical Gaussian processes as a general model of gene expression time-series, with application to a variety of problems. In particular, we illustrate the method's capacity for missing data imputation, data fusion and clustering.The method can impute data which is missing both systematically and at random: in a hold-out test on real data, performance is significantly better than commonly used imputation methods. The method's ability to model inter- and intra-cluster variance leads to more biologically meaningful clusters. The approach removes the necessity for evenly spaced samples, an advantage illustrated on a developmental Drosophila dataset with irregular replications. The hierarchical Gaussian process model provides an excellent statistical basis for several gene-expression time-series tasks. It has only a few additional parameters over a regular GP, has negligible additional complexity, is easily implemented and can be integrated into several existing algorithms. Our experiments were implemented in python, and are available from the authors' website: http://staffwww.dcs.shef.ac.uk/people/J.Hensman/.

Evolution and inheritance of early embryonic patterning in Drosophila simulans and D. sechellia.

PubMed

Lott, Susan E; Ludwig, Michael Z; Kreitman, Martin

2011-05-01

Pattern formation in Drosophila is a widely studied example of a robust developmental system. Such robust systems pose a challenge to adaptive evolution, as they mask variation that selection may otherwise act upon. Yet we find variation in the localization of expression domains (henceforth "stripe allometry") in the pattern formation pathway. Specifically, we characterize differences in the gap genes giant and Kruppel, and the pair-rule gene even-skipped, which differ between the sibling species Drosophila simulans and D. sechellia. In a double-backcross experiment, stripe allometry is consistent with maternal inheritance of stripe positioning and multiple genetic factors, with a distinct genetic basis from embryo length. Embryos produced by F1 and F2 backcross mothers exhibit novel spatial patterns of gene expression relative to the parental species, with no measurable increase in positional variance among individuals. Buffering of novel spatial patterns in the backcross genotypes suggests that robustness need not be disrupted in order for the trait to evolve, and perhaps the system is incapable of evolving to prevent the expression of all genetic variation. This limitation, and the ability of natural selection to act on minute genetic differences that are within the "margin of error" for the buffering mechanism, indicates that developmentally buffered traits can evolve without disruption of robustness. © 2010 The Author(s). Evolution© 2010 The Society for the Study of Evolution.

DNA methylation Landscape of body size variation in sheep.

PubMed

Cao, Jiaxue; Wei, Caihong; Liu, Dongming; Wang, Huihua; Wu, Mingming; Xie, Zhiyuan; Capellini, Terence D; Zhang, Li; Zhao, Fuping; Li, Li; Zhong, Tao; Wang, Linjie; Lu, Jian; Liu, Ruizao; Zhang, Shifang; Du, Yongfei; Zhang, Hongping; Du, Lixin

2015-10-16

Sub-populations of Chinese Mongolian sheep exhibit significant variance in body mass. In the present study, we sequenced the whole genome DNA methylation in these breeds to detect whether DNA methylation plays a role in determining the body mass of sheep by Methylated DNA immunoprecipitation - sequencing method. A high quality methylation map of Chinese Mongolian sheep was obtained in this study. We identified 399 different methylated regions located in 93 human orthologs, which were previously reported as body size related genes in human genome-wide association studies. We tested three regions in LTBP1, and DNA methylation of two CpG sites showed significant correlation with its RNA expression. Additionally, a particular set of differentially methylated windows enriched in the "development process" (GO: 0032502) was identified as potential candidates for association with body mass variation. Next, we validated small part of these windows in 5 genes; DNA methylation of SMAD1, TSC1 and AKT1 showed significant difference across breeds, and six CpG were significantly correlated with RNA expression. Interestingly, two CpG sites showed significant correlation with TSC1 protein expression. This study provides a thorough understanding of body size variation in sheep from an epigenetic perspective.

Good genes, genetic compatibility and the evolution of polyandry: use of the diallel cross to address competing hypotheses.

PubMed

Ivy, T M

2007-03-01

Genetic benefits can enhance the fitness of polyandrous females through the high intrinsic genetic quality of females' mates or through the interaction between female and male genes. I used a full diallel cross, a quantitative genetics design that involves all possible crosses among a set of genetically homogeneous lines, to determine the mechanism through which polyandrous female decorated crickets (Gryllodes sigillatus) obtain genetic benefits. I measured several traits related to fitness and partitioned the phenotypic variance into components representing the contribution of additive genetic variance ('good genes'), nonadditive genetic variance (genetic compatibility), as well as maternal and paternal effects. The results reveal a significant variance attributable to both nonadditive and additive sources in the measured traits, and their influence depended on which trait was considered. The lack of congruence in sources of phenotypic variance among these fitness-related traits suggests that the evolution and maintenance of polyandry are unlikely to have resulted from one selective influence, but rather are the result of the collective effects of a number of factors.

Accounting for technical noise in differential expression analysis of single-cell RNA sequencing data.

PubMed

Jia, Cheng; Hu, Yu; Kelly, Derek; Kim, Junhyong; Li, Mingyao; Zhang, Nancy R

2017-11-02

Recent technological breakthroughs have made it possible to measure RNA expression at the single-cell level, thus paving the way for exploring expression heterogeneity among individual cells. Current single-cell RNA sequencing (scRNA-seq) protocols are complex and introduce technical biases that vary across cells, which can bias downstream analysis without proper adjustment. To account for cell-to-cell technical differences, we propose a statistical framework, TASC (Toolkit for Analysis of Single Cell RNA-seq), an empirical Bayes approach to reliably model the cell-specific dropout rates and amplification bias by use of external RNA spike-ins. TASC incorporates the technical parameters, which reflect cell-to-cell batch effects, into a hierarchical mixture model to estimate the biological variance of a gene and detect differentially expressed genes. More importantly, TASC is able to adjust for covariates to further eliminate confounding that may originate from cell size and cell cycle differences. In simulation and real scRNA-seq data, TASC achieves accurate Type I error control and displays competitive sensitivity and improved robustness to batch effects in differential expression analysis, compared to existing methods. TASC is programmed to be computationally efficient, taking advantage of multi-threaded parallelization. We believe that TASC will provide a robust platform for researchers to leverage the power of scRNA-seq. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Accounting for technical noise in differential expression analysis of single-cell RNA sequencing data

PubMed Central

Jia, Cheng; Hu, Yu; Kelly, Derek; Kim, Junhyong

2017-01-01

Abstract Recent technological breakthroughs have made it possible to measure RNA expression at the single-cell level, thus paving the way for exploring expression heterogeneity among individual cells. Current single-cell RNA sequencing (scRNA-seq) protocols are complex and introduce technical biases that vary across cells, which can bias downstream analysis without proper adjustment. To account for cell-to-cell technical differences, we propose a statistical framework, TASC (Toolkit for Analysis of Single Cell RNA-seq), an empirical Bayes approach to reliably model the cell-specific dropout rates and amplification bias by use of external RNA spike-ins. TASC incorporates the technical parameters, which reflect cell-to-cell batch effects, into a hierarchical mixture model to estimate the biological variance of a gene and detect differentially expressed genes. More importantly, TASC is able to adjust for covariates to further eliminate confounding that may originate from cell size and cell cycle differences. In simulation and real scRNA-seq data, TASC achieves accurate Type I error control and displays competitive sensitivity and improved robustness to batch effects in differential expression analysis, compared to existing methods. TASC is programmed to be computationally efficient, taking advantage of multi-threaded parallelization. We believe that TASC will provide a robust platform for researchers to leverage the power of scRNA-seq. PMID:29036714

Elementary screening of lymph node metastatic-related genes in gastric cancer based on the co-expression network of messenger RNA, microRNA and long non-coding RNA.

PubMed

Song, Zhonghua; Zhao, Wenhua; Cao, Danfeng; Zhang, Jinqing; Chen, Shouhua

2018-01-01

Gastric cancer (GC) is the fifth most common cancer and the third leading cause of cancer-related deaths worldwide. The high mortality might be attributed to delay in detection and is closely related to lymph node metastasis. Therefore, it is of great importance to explore the mechanism of lymph node metastasis and find strategies to block GC metastasis. Messenger RNA (mRNA), microRNA (miRNA) and long non-coding RNA (lncRNA) expression data and clinical data were downloaded from The Cancer Genome Atlas (TCGA) database. A total of 908 differentially expressed factors with variance >0.5 including 542 genes, 42 miRNA, and 324 lncRNA were screened using significant analysis microarray algorithm, and interaction networks were constructed using these differentially expressed factors. Furthermore, we conducted functional modules analysis in the network, and found that yellow and turquoise modules could separate samples efficiently. The groups classified in the yellow and turquoise modules had a significant difference in survival time, which was verified in another independent GC mRNA dataset (GSE62254). The results suggested that differentially expressed factors in the yellow and turquoise modules may participate in lymph node metastasis of GC and could be applied as potential biomarkers or therapeutic targets for GC.

Elementary screening of lymph node metastatic-related genes in gastric cancer based on the co-expression network of messenger RNA, microRNA and long non-coding RNA

PubMed Central

Song, Zhonghua; Zhao, Wenhua; Cao, Danfeng; Zhang, Jinqing; Chen, Shouhua

2018-01-01

Gastric cancer (GC) is the fifth most common cancer and the third leading cause of cancer-related deaths worldwide. The high mortality might be attributed to delay in detection and is closely related to lymph node metastasis. Therefore, it is of great importance to explore the mechanism of lymph node metastasis and find strategies to block GC metastasis. Messenger RNA (mRNA), microRNA (miRNA) and long non-coding RNA (lncRNA) expression data and clinical data were downloaded from The Cancer Genome Atlas (TCGA) database. A total of 908 differentially expressed factors with variance >0.5 including 542 genes, 42 miRNA, and 324 lncRNA were screened using significant analysis microarray algorithm, and interaction networks were constructed using these differentially expressed factors. Furthermore, we conducted functional modules analysis in the network, and found that yellow and turquoise modules could separate samples efficiently. The groups classified in the yellow and turquoise modules had a significant difference in survival time, which was verified in another independent GC mRNA dataset (GSE62254). The results suggested that differentially expressed factors in the yellow and turquoise modules may participate in lymph node metastasis of GC and could be applied as potential biomarkers or therapeutic targets for GC. PMID:29489999

Predictive Genes in Adjacent Normal Tissue Are Preferentially Altered by sCNV during Tumorigenesis in Liver Cancer and May Rate Limiting

PubMed Central

Lamb, John R.; Zhang, Chunsheng; Xie, Tao; Wang, Kai; Zhang, Bin; Hao, Ke; Chudin, Eugene; Fraser, Hunter B.; Millstein, Joshua; Ferguson, Mark; Suver, Christine; Ivanovska, Irena; Scott, Martin; Philippar, Ulrike; Bansal, Dimple; Zhang, Zhan; Burchard, Julja; Smith, Ryan; Greenawalt, Danielle; Cleary, Michele; Derry, Jonathan; Loboda, Andrey; Watters, James; Poon, Ronnie T. P.; Fan, Sheung T.; Yeung, Chun; Lee, Nikki P. Y.; Guinney, Justin; Molony, Cliona; Emilsson, Valur; Buser-Doepner, Carolyn; Zhu, Jun; Friend, Stephen; Mao, Mao; Shaw, Peter M.; Dai, Hongyue; Luk, John M.; Schadt, Eric E.

2011-01-01

Background In hepatocellular carcinoma (HCC) genes predictive of survival have been found in both adjacent normal (AN) and tumor (TU) tissues. The relationships between these two sets of predictive genes and the general process of tumorigenesis and disease progression remains unclear. Methodology/Principal Findings Here we have investigated HCC tumorigenesis by comparing gene expression, DNA copy number variation and survival using ∼250 AN and TU samples representing, respectively, the pre-cancer state, and the result of tumorigenesis. Genes that participate in tumorigenesis were defined using a gene-gene correlation meta-analysis procedure that compared AN versus TU tissues. Genes predictive of survival in AN (AN-survival genes) were found to be enriched in the differential gene-gene correlation gene set indicating that they directly participate in the process of tumorigenesis. Additionally the AN-survival genes were mostly not predictive after tumorigenesis in TU tissue and this transition was associated with and could largely be explained by the effect of somatic DNA copy number variation (sCNV) in cis and in trans. The data was consistent with the variance of AN-survival genes being rate-limiting steps in tumorigenesis and this was confirmed using a treatment that promotes HCC tumorigenesis that selectively altered AN-survival genes and genes differentially correlated between AN and TU. Conclusions/Significance This suggests that the process of tumor evolution involves rate-limiting steps related to the background from which the tumor evolved where these were frequently predictive of clinical outcome. Additionally treatments that alter the likelihood of tumorigenesis occurring may act by altering AN-survival genes, suggesting that the process can be manipulated. Further sCNV explains a substantial fraction of tumor specific expression and may therefore be a causal driver of tumor evolution in HCC and perhaps many solid tumor types. PMID:21750698

Global Genetic Variations Predict Brain Response to Faces

PubMed Central

Dickie, Erin W.; Tahmasebi, Amir; French, Leon; Kovacevic, Natasa; Banaschewski, Tobias; Barker, Gareth J.; Bokde, Arun; Büchel, Christian; Conrod, Patricia; Flor, Herta; Garavan, Hugh; Gallinat, Juergen; Gowland, Penny; Heinz, Andreas; Ittermann, Bernd; Lawrence, Claire; Mann, Karl; Martinot, Jean-Luc; Nees, Frauke; Nichols, Thomas; Lathrop, Mark; Loth, Eva; Pausova, Zdenka; Rietschel, Marcela; Smolka, Michal N.; Ströhle, Andreas; Toro, Roberto; Schumann, Gunter; Paus, Tomáš

2014-01-01

Face expressions are a rich source of social signals. Here we estimated the proportion of phenotypic variance in the brain response to facial expressions explained by common genetic variance captured by ∼500,000 single nucleotide polymorphisms. Using genomic-relationship-matrix restricted maximum likelihood (GREML), we related this global genetic variance to that in the brain response to facial expressions, as assessed with functional magnetic resonance imaging (fMRI) in a community-based sample of adolescents (n = 1,620). Brain response to facial expressions was measured in 25 regions constituting a face network, as defined previously. In 9 out of these 25 regions, common genetic variance explained a significant proportion of phenotypic variance (40–50%) in their response to ambiguous facial expressions; this was not the case for angry facial expressions. Across the network, the strength of the genotype-phenotype relationship varied as a function of the inter-individual variability in the number of functional connections possessed by a given region (R2 = 0.38, p<0.001). Furthermore, this variability showed an inverted U relationship with both the number of observed connections (R2 = 0.48, p<0.001) and the magnitude of brain response (R2 = 0.32, p<0.001). Thus, a significant proportion of the brain response to facial expressions is predicted by common genetic variance in a subset of regions constituting the face network. These regions show the highest inter-individual variability in the number of connections with other network nodes, suggesting that the genetic model captures variations across the adolescent brains in co-opting these regions into the face network. PMID:25122193

Variation patterns in individual fish responses to chemical stress among estuaries, seasons and genders: the case of the European flounder (Platichthys flesus) in the Bay of Biscay.

PubMed

Laroche, Jean; Gauthier, Olivier; Quiniou, Louis; Devaux, Alain; Bony, Sylvie; Evrard, Estérine; Cachot, Jérôme; Chérel, Yan; Larcher, Thibaut; Riso, Ricardo; Pichereau, Vianney; Devier, Marie Hélène; Budzinski, Hélène

2013-02-01

The objective was to describe and model variation patterns in individual fish responses to contaminants among estuaries, season and gender. Two hundred twenty-seven adult European flounders were collected in two seasons (winter and summer) in four estuaries along the Bay of Biscay (South West France), focusing on a pristine system (the Ster), vs. three estuaries displaying contrasted levels of contaminants (the Vilaine, Loire and Gironde). Twenty-three variables were measured by fish, considering the load of contaminants (liver metals, liver and muscle persistent organic pollutants, muscle polycyclic aromatic hydrocarbons); the gene expression (Cyt C oxydase, ATPase, BHMT, Cyt P450 1A1, ferritin); the blood genotoxicity (Comet test); and liver histology (foci of cellular alteration-tumour, steatosis, inflammation, abnormal glycogen storage). Canonical redundancy analysis (RDA) was used to model these variables using gender, season and estuary of origin as explanatory variables. The results underlined the homogeneity of fish responses within the pristine site (Ster) and more important seasonal variability within the three contaminated systems. The complete model RDA was significant and explained 35 % of total variance. Estuary and season respectively explained 30 and 5 % of the total independent variation components, whilst gender was not a significant factor. The first axis of the RDA explains nearly 27 % of the total variance and mostly represents a gradient of contamination. The links between the load of contaminants, the expression of several genes and the biomarkers were analysed considering different levels of chemical stress and a possible multi-stress, particularly in the Vilaine estuary.

Probiotic lactobacillus and estrogen effects on vaginal epithelial gene expression responses to Candida albicans.

PubMed

Wagner, R Doug; Johnson, Shemedia J

2012-06-20

Vaginal epithelial cells have receptors, signal transduction mechanisms, and cytokine secretion capabilities to recruit host defenses against Candida albicans infections. This research evaluates how probiotic lactobacilli affect the defensive epithelial response. This study used quantitative reverse transcription-polymerase chain reaction assay (qRT-PCR), flow cytometry, and a multiplex immunoassay to observe changes in the regulation of gene expression related to cytokine responses in the VK2 (E6/E7) vaginal epithelial cell line treated with 17β-estradiol, exposed to probiotic Lactobacillus rhamnosus GR-1® and Lactobacillus reuteri RC-14® and challenged with C. albicans. Data were statistically evaluated by repeated measures analysis of variance and paired t-tests where appropriate. C. albicans induced mRNA expression of genes related to inflammatory cytokine responses associated with nuclear factor-kappa B (NF-κB) and mitogen-activated protein kinase (MAPK) signal transduction pathways. 17β-estradiol suppressed expression of interleukin-1α (IL-1α), IL-6, IL-8, and tumor necrosis factor alpha (TNFα) mRNA. Probiotic lactobacilli suppressed C. albicans-induced nuclear factor-kappa B inhibitor kinase kinase alpha (Iκκα), Toll-like receptor-2 (TLR2), TLR6, IL-8, and TNFα, also suggesting inhibition of NF-κB signaling. The lactobacilli induced expression of IL-1α, and IL-1β mRNA, which was not inhibited by curcumin, suggesting that they induce an alternate inflammatory signal transduction pathway to NF-κB, such as the mitogen activated protein kinase and activator protein-1 (MAPK/AP-1) signal transduction pathway. Curcumin inhibited IL-13 secretion, suggesting that expression of this cytokine is mainly regulated by NF-κB signaling in VK2 cells. The results suggest that C. albicans infection induces pro-inflammatory responses in vaginal epithelial cells, and estrogen and lactobacilli suppress expression of NF-κB-related inflammatory genes. Probiotic lactobacilli may induce IL-1α and IL-1β expression by an alternate signal transduction pathway, such as MAPK/AP-1. Activation of alternate signaling mechanisms by lactobacilli to modify epithelial cell cytokine production may be a mechanism for probiotic modulation of morbidity in vulvovaginal candidiasis.

Three-dimensional Tissue Culture Based on Magnetic Cell Levitation

PubMed Central

Souza, Glauco R.; Molina, Jennifer R.; Raphael, Robert M.; Ozawa, Michael G.; Stark, Daniel J.; Levin, Carly S.; Bronk, Lawrence F.; Ananta, Jeyarama S.; Mandelin, Jami; Georgescu, Maria-Magdalena; Bankson, James A.; Gelovani, Juri G.

2015-01-01

Cell culture is an essential tool for drug discovery, tissue engineering, and stem cell research. Conventional tissue culture produces two-dimensional (2D) cell growth with gene expression, signaling, and morphology that can differ from those in vivo and thus compromise clinical relevancy1–5. Here we report a three-dimensional (3D) culture of cells based on magnetic levitation in the presence of hydrogels containing gold and magnetic iron oxide (MIO) nanoparticles plus filamentous bacteriophage. This methodology allows for control of cell mass geometry and guided, multicellular clustering of different cell types in co-culture through spatial variance of the magnetic field. Moreover, magnetic levitation of human glioblastoma cells demonstrates similar protein expression profiles to those observed in human tumor xenografts. Taken together, these results suggest levitated 3D culture with magnetized phage-based hydrogels more closely recapitulates in vivo protein expression and allows for long-term multi-cellular studies. PMID:20228788

Variation in the Oxytocin Receptor Gene Predicts Brain Region Specific Expression and Social Attachment

PubMed Central

King, Lanikea B.; Walum, Hasse; Inoue, Kiyoshi; Eyrich, Nicholas W.; Young, Larry J.

2015-01-01

Background Oxytocin (OXT) modulates several aspects of social behavior. Intranasal OXT is a leading candidate for treating social deficits in autism spectrum disorder (ASD) and common genetic variants in the human oxytocin receptor (OXTR) are associated with emotion recognition, relationship quality and ASD. Animal models have revealed that individual differences in Oxtr expression in the brain drive social behavior variation. Our understanding of how genetic variation contributes to brain OXTR expression is very limited. Methods We investigated Oxtr expression in monogamous prairie voles, which have a well characterized OXT system. We quantified brain region-specific levels of Oxtr mRNA and OXTR protein with established neuroanatomical methods. We used pyrosequencing to investigate allelic imbalance of Oxtr mRNA, a molecular signature of polymorphic genetic regulatory elements. We performed next-generation sequencing to discover variants in and near the Oxtr gene. We investigated social attachment using the partner preference test. Results Our allelic imbalance data demonstrates that genetic variants contribute to individual differences in Oxtr expression, but only in particular brain regions, including the nucleus accumbens (NAcc), where OXTR signaling facilitates social attachment. Next-generation sequencing identified one polymorphism in the Oxtr intron, near a putative cis-regulatory element, explaining 74% of the variance in striatal Oxtr expression specifically. Males homozygous for the high expressing allele display enhanced social attachment. Discussion Taken together, these findings provide convincing evidence for robust genetic influence on Oxtr expression and provide novel insights into how non-coding polymorphisms in the OXTR might influence individual differences in human social cognition and behavior PMID:26893121

Determination of absolute expression profiles using multiplexed miRNA analysis

PubMed Central

Song, Jee Hoon; Cheng, Yulan; Saeui, Christopher T.; Cheung, Douglas G.; Croce, Carlo M.; Yarema, Kevin J.; Meltzer, Stephen J.; Liu, Kelvin J.; Wang, Tza-Huei

2017-01-01

Accurate measurement of miRNA expression is critical to understanding their role in gene expression as well as their application as disease biomarkers. Correct identification of changes in miRNA expression rests on reliable normalization to account for biological and technological variance between samples. Ligo-miR is a multiplex assay designed to rapidly measure absolute miRNA copy numbers, thus reducing dependence on biological controls. It uses a simple 2-step ligation process to generate length coded products that can be quantified using a variety of DNA sizing methods. We demonstrate Ligo-miR’s ability to quantify miRNA expression down to 20 copies per cell sensitivity, accurately discriminate between closely related miRNA, and reliably measure differential changes as small as 1.2-fold. Then, benchmarking studies were performed to show the high correlation between Ligo-miR, microarray, and TaqMan qRT-PCR. Finally, Ligo-miR was used to determine copy number profiles in a number of breast, esophageal, and pancreatic cell lines and to demonstrate the utility of copy number analysis for providing layered insight into expression profile changes. PMID:28704432

Statistical aspects of quantitative real-time PCR experiment design.

PubMed

Kitchen, Robert R; Kubista, Mikael; Tichopad, Ales

2010-04-01

Experiments using quantitative real-time PCR to test hypotheses are limited by technical and biological variability; we seek to minimise sources of confounding variability through optimum use of biological and technical replicates. The quality of an experiment design is commonly assessed by calculating its prospective power. Such calculations rely on knowledge of the expected variances of the measurements of each group of samples and the magnitude of the treatment effect; the estimation of which is often uninformed and unreliable. Here we introduce a method that exploits a small pilot study to estimate the biological and technical variances in order to improve the design of a subsequent large experiment. We measure the variance contributions at several 'levels' of the experiment design and provide a means of using this information to predict both the total variance and the prospective power of the assay. A validation of the method is provided through a variance analysis of representative genes in several bovine tissue-types. We also discuss the effect of normalisation to a reference gene in terms of the measured variance components of the gene of interest. Finally, we describe a software implementation of these methods, powerNest, that gives the user the opportunity to input data from a pilot study and interactively modify the design of the assay. The software automatically calculates expected variances, statistical power, and optimal design of the larger experiment. powerNest enables the researcher to minimise the total confounding variance and maximise prospective power for a specified maximum cost for the large study. Copyright 2010 Elsevier Inc. All rights reserved.

On the design of classifiers for crop inventories

NASA Technical Reports Server (NTRS)

Heydorn, R. P.; Takacs, H. C.

1986-01-01

Crop proportion estimators that use classifications of satellite data to correct, in an additive way, a given estimate acquired from ground observations are discussed. A linear version of these estimators is optimal, in terms of minimum variance, when the regression of the ground observations onto the satellite observations in linear. When this regression is not linear, but the reverse regression (satellite observations onto ground observations) is linear, the estimator is suboptimal but still has certain appealing variance properties. In this paper expressions are derived for those regressions which relate the intercepts and slopes to conditional classification probabilities. These expressions are then used to discuss the question of classifier designs that can lead to low-variance crop proportion estimates. Variance expressions for these estimates in terms of classifier omission and commission errors are also derived.

Susceptibility to Inhaled Flame-Generated Ultrafine Soot in Neonatal and Adult Rat Lungs

PubMed Central

Chan, Jackie K. W.; Fanucchi, Michelle V.; Anderson, Donald S.; Abid, Aamir D.; Wallis, Christopher D.; Dickinson, Dale A.; Kumfer, Benjamin M.; Kennedy, Ian M.; Wexler, Anthony S.; Van Winkle, Laura S.

2011-01-01

Over a quarter of the U.S. population is exposed to harmful levels of airborne particulate matter (PM) pollution, which has been linked to development and exacerbation of respiratory diseases leading to morbidity and mortality, especially in susceptible populations. Young children are especially susceptible to PM and can experience altered anatomic, physiologic, and biological responses. Current studies of ambient PM are confounded by the complex mixture of soot, metals, allergens, and organics present in the complex mixture as well as seasonal and temporal variance. We have developed a laboratory-based PM devoid of metals and allergens that can be replicated to study health effects of specific PM components in animal models. We exposed 7-day-old postnatal and adult rats to a single 6-h exposure of fuel-rich ultrafine premixed flame particles (PFPs) or filtered air. These particles are high in polycyclic aromatic hydrocarbons content. Pulmonary cytotoxicity, gene, and protein expression were evaluated at 2 and 24 h postexposure. Neonates were more susceptible to PFP, exhibiting increased lactate dehydrogenase activity in bronchoalveolar lavage fluid and ethidium homodimer-1 cellular staining in the lung in situ as an index of cytotoxicity. Basal gene expression between neonates and adults differed for a significant number of antioxidant, oxidative stress, and proliferation genes and was further altered by PFP exposure. PFP diminishes proliferation marker PCNA gene and protein expression in neonates but not adults. We conclude that neonates have an impaired ability to respond to environmental exposures that increases lung cytotoxicity and results in enhanced susceptibility to PFP, which may lead to abnormal airway growth. PMID:21914721

Susceptibility to inhaled flame-generated ultrafine soot in neonatal and adult rat lungs.

PubMed

Chan, Jackie K W; Fanucchi, Michelle V; Anderson, Donald S; Abid, Aamir D; Wallis, Christopher D; Dickinson, Dale A; Kumfer, Benjamin M; Kennedy, Ian M; Wexler, Anthony S; Van Winkle, Laura S

2011-12-01

Over a quarter of the U.S. population is exposed to harmful levels of airborne particulate matter (PM) pollution, which has been linked to development and exacerbation of respiratory diseases leading to morbidity and mortality, especially in susceptible populations. Young children are especially susceptible to PM and can experience altered anatomic, physiologic, and biological responses. Current studies of ambient PM are confounded by the complex mixture of soot, metals, allergens, and organics present in the complex mixture as well as seasonal and temporal variance. We have developed a laboratory-based PM devoid of metals and allergens that can be replicated to study health effects of specific PM components in animal models. We exposed 7-day-old postnatal and adult rats to a single 6-h exposure of fuel-rich ultrafine premixed flame particles (PFPs) or filtered air. These particles are high in polycyclic aromatic hydrocarbons content. Pulmonary cytotoxicity, gene, and protein expression were evaluated at 2 and 24 h postexposure. Neonates were more susceptible to PFP, exhibiting increased lactate dehydrogenase activity in bronchoalveolar lavage fluid and ethidium homodimer-1 cellular staining in the lung in situ as an index of cytotoxicity. Basal gene expression between neonates and adults differed for a significant number of antioxidant, oxidative stress, and proliferation genes and was further altered by PFP exposure. PFP diminishes proliferation marker PCNA gene and protein expression in neonates but not adults. We conclude that neonates have an impaired ability to respond to environmental exposures that increases lung cytotoxicity and results in enhanced susceptibility to PFP, which may lead to abnormal airway growth.

Robust Inference of Cell-to-Cell Expression Variations from Single- and K-Cell Profiling

PubMed Central

Narayanan, Manikandan; Martins, Andrew J.; Tsang, John S.

2016-01-01

Quantifying heterogeneity in gene expression among single cells can reveal information inaccessible to cell-population averaged measurements. However, the expression level of many genes in single cells fall below the detection limit of even the most sensitive technologies currently available. One proposed approach to overcome this challenge is to measure random pools of k cells (e.g., 10) to increase sensitivity, followed by computational “deconvolution” of cellular heterogeneity parameters (CHPs), such as the biological variance of single-cell expression levels. Existing approaches infer CHPs using either single-cell or k-cell data alone, and typically within a single population of cells. However, integrating both single- and k-cell data may reap additional benefits, and quantifying differences in CHPs across cell populations or conditions could reveal novel biological information. Here we present a Bayesian approach that can utilize single-cell, k-cell, or both simultaneously to infer CHPs within a single condition or their differences across two conditions. Using simulated as well as experimentally generated single- and k-cell data, we found situations where each data type would offer advantages, but using both together can improve precision and better reconcile CHP information contained in single- and k-cell data. We illustrate the utility of our approach by applying it to jointly generated single- and k-cell data to reveal CHP differences in several key inflammatory genes between resting and inflammatory cytokine-activated human macrophages, delineating differences in the distribution of ‘ON’ versus ‘OFF’ cells and in continuous variation of expression level among cells. Our approach thus offers a practical and robust framework to assess and compare cellular heterogeneity within and across biological conditions using modern multiplexed technologies. PMID:27438699

Discovery of gene-gene interactions across multiple independent data sets of late onset Alzheimer disease from the Alzheimer Disease Genetics Consortium.

PubMed

Hohman, Timothy J; Bush, William S; Jiang, Lan; Brown-Gentry, Kristin D; Torstenson, Eric S; Dudek, Scott M; Mukherjee, Shubhabrata; Naj, Adam; Kunkle, Brian W; Ritchie, Marylyn D; Martin, Eden R; Schellenberg, Gerard D; Mayeux, Richard; Farrer, Lindsay A; Pericak-Vance, Margaret A; Haines, Jonathan L; Thornton-Wells, Tricia A

2016-02-01

Late-onset Alzheimer disease (AD) has a complex genetic etiology, involving locus heterogeneity, polygenic inheritance, and gene-gene interactions; however, the investigation of interactions in recent genome-wide association studies has been limited. We used a biological knowledge-driven approach to evaluate gene-gene interactions for consistency across 13 data sets from the Alzheimer Disease Genetics Consortium. Fifteen single nucleotide polymorphism (SNP)-SNP pairs within 3 gene-gene combinations were identified: SIRT1 × ABCB1, PSAP × PEBP4, and GRIN2B × ADRA1A. In addition, we extend a previously identified interaction from an endophenotype analysis between RYR3 × CACNA1C. Finally, post hoc gene expression analyses of the implicated SNPs further implicate SIRT1 and ABCB1, and implicate CDH23 which was most recently identified as an AD risk locus in an epigenetic analysis of AD. The observed interactions in this article highlight ways in which genotypic variation related to disease may depend on the genetic context in which it occurs. Further, our results highlight the utility of evaluating genetic interactions to explain additional variance in AD risk and identify novel molecular mechanisms of AD pathogenesis. Copyright © 2016 Elsevier Inc. All rights reserved.

The Cohesive Population Genetics of Molecular Drive

PubMed Central

Ohta, Tomoko; Dover, Gabriel A.

1984-01-01

The long-term population genetics of multigene families is influenced by several biased and unbiased mechanisms of nonreciprocal exchanges (gene conversion, unequal exchanges, transposition) between member genes, often distributed on several chromosomes. These mechanisms cause fluctuations in the copy number of variant genes in an individual and lead to a gradual replacement of an original family of n genes (A) in N number of individuals by a variant gene (a). The process for spreading a variant gene through a family and through a population is called molecular drive. Consideration of the known slow rates of nonreciprocal exchanges predicts that the population variance in the copy number of gene a per individual is small at any given generation during molecular drive. Genotypes at a given generation are expected only to range over a small section of all possible genotypes from one extreme (n number of A) to the other (n number of a). A theory is developed for estimating the size of the population variance by using the concept of identity coefficients. In particular, the variance in the course of spreading of a single mutant gene of a multigene family was investigated in detail, and the theory of identity coefficients at the state of steady decay of genetic variability proved to be useful. Monte Carlo simulations and numerical analysis based on realistic rates of exchange in families of known size reveal the correctness of the theoretical prediction and also assess the effect of bias in turnover. The population dynamics of molecular drive in gradually increasing the mean copy number of a variant gene without the generation of a large variance (population cohesion) is of significance regarding potential interactions between natural selection and molecular drive. PMID:6500260

The cohesive population genetics of molecular drive.

PubMed

Ohta, T; Dover, G A

1984-10-01

The long-term population genetics of multigene families is influenced by several biased and unbiased mechanisms of nonreciprocal exchanges (gene conversion, unequal exchanges, transposition) between member genes, often distributed on several chromosomes. These mechanisms cause fluctuations in the copy number of variant genes in an individual and lead to a gradual replacement of an original family of n genes (A) in N number of individuals by a variant gene (a). The process for spreading a variant gene through a family and through a population is called molecular drive. Consideration of the known slow rates of nonreciprocal exchanges predicts that the population variance in the copy number of gene a per individual is small at any given generation during molecular drive. Genotypes at a given generation are expected only to range over a small section of all possible genotypes from one extreme (n number of A) to the other (n number of a). A theory is developed for estimating the size of the population variance by using the concept of identity coefficients. In particular, the variance in the course of spreading of a single mutant gene of a multigene family was investigated in detail, and the theory of identity coefficients at the state of steady decay of genetic variability proved to be useful. Monte Carlo simulations and numerical analysis based on realistic rates of exchange in families of known size reveal the correctness of the theoretical prediction and also assess the effect of bias in turnover. The population dynamics of molecular drive in gradually increasing the mean copy number of a variant gene without the generation of a large variance (population cohesion) is of significance regarding potential interactions between natural selection and molecular drive.

What is the danger of the anomaly zone for empirical phylogenetics?

PubMed

Huang, Huateng; Knowles, L Lacey

2009-10-01

The increasing number of observations of gene trees with discordant topologies in phylogenetic studies has raised awareness about the problems of incongruence between species trees and gene trees. Moreover, theoretical treatments focusing on the impact of coalescent variance on phylogenetic study have also identified situations where the most probable gene trees are ones that do not match the underlying species tree (i.e., anomalous gene trees [AGTs]). However, although the theoretical proof of the existence of AGTs is alarming, the actual risk that AGTs pose to empirical phylogenetic study is far from clear. Establishing the conditions (i.e., the branch lengths in a species tree) for which AGTs are possible does not address the critical issue of how prevalent they might be. Furthermore, theoretical characterization of the species trees for which AGTs may pose a problem (i.e., the anomaly zone or the species histories for which AGTs are theoretically possible) is based on consideration of just one source of variance that contributes to species tree and gene tree discord-gene lineage coalescence. Yet, empirical data contain another important stochastic component-mutational variance. Estimated gene trees will differ from the underlying gene trees (i.e., the actual genealogy) because of the random process of mutation. Here, we take a simulation approach to investigate the prevalence of AGTs, among estimated gene trees, thereby characterizing the boundaries of the anomaly zone taking into account both coalescent and mutational variances. We also determine the frequency of realized AGTs, which is critical to putting the theoretical work on AGTs into a realistic biological context. Two salient results emerge from this investigation. First, our results show that mutational variance can indeed expand the parameter space (i.e., the relative branch lengths in a species tree) where AGTs might be observed in empirical data. By exploring the underlying cause for the expanded anomaly zone, we identify aspects of empirical data relevant to avoiding the problems that AGTs pose for species tree inference from multilocus data. Second, for the empirical species histories where AGTs are possible, unresolved trees-not AGTs-predominate the pool of estimated gene trees. This result suggests that the risk of AGTs, while they exist in theory, may rarely be realized in practice. By considering the biological realities of both mutational and coalescent variances, the study has refined, and redefined, what the actual challenges are for empirical phylogenetic study of recently diverged taxa that have speciated rapidly-AGTs themselves are unlikely to pose a significant danger to empirical phylogenetic study.

Increased gender variance in autism spectrum disorders and attention deficit hyperactivity disorder.

PubMed

Strang, John F; Kenworthy, Lauren; Dominska, Aleksandra; Sokoloff, Jennifer; Kenealy, Laura E; Berl, Madison; Walsh, Karin; Menvielle, Edgardo; Slesaransky-Poe, Graciela; Kim, Kyung-Eun; Luong-Tran, Caroline; Meagher, Haley; Wallace, Gregory L

2014-11-01

Evidence suggests over-representation of autism spectrum disorders (ASDs) and behavioral difficulties among people referred for gender issues, but rates of the wish to be the other gender (gender variance) among different neurodevelopmental disorders are unknown. This chart review study explored rates of gender variance as reported by parents on the Child Behavior Checklist (CBCL) in children with different neurodevelopmental disorders: ASD (N = 147, 24 females and 123 males), attention deficit hyperactivity disorder (ADHD; N = 126, 38 females and 88 males), or a medical neurodevelopmental disorder (N = 116, 57 females and 59 males), were compared with two non-referred groups [control sample (N = 165, 61 females and 104 males) and non-referred participants in the CBCL standardization sample (N = 1,605, 754 females and 851 males)]. Significantly greater proportions of participants with ASD (5.4%) or ADHD (4.8%) had parent reported gender variance than in the combined medical group (1.7%) or non-referred comparison groups (0-0.7%). As compared to non-referred comparisons, participants with ASD were 7.59 times more likely to express gender variance; participants with ADHD were 6.64 times more likely to express gender variance. The medical neurodevelopmental disorder group did not differ from non-referred samples in likelihood to express gender variance. Gender variance was related to elevated emotional symptoms in ADHD, but not in ASD. After accounting for sex ratio differences between the neurodevelopmental disorder and non-referred comparison groups, gender variance occurred equally in females and males.

Effects of coarse-graining on fluctuations in gene expression

NASA Astrophysics Data System (ADS)

Pedraza, Juan; Paulsson, Johan

2008-03-01

Many cellular components are present in such low numbers per cell that random births and deaths of individual molecules can cause significant `noise' in concentrations. But biochemical events do not necessarily occur in steps of individual molecules. Some processes are greatly randomized when synthesis or degradation occurs in large bursts of many molecules in a short time interval. Conversely, each birth or death of a macromolecule could involve several small steps, creating a memory between individual events. Here we present generalized theory for stochastic gene expression, formulating the variance in protein abundance in terms of the randomness of the individual events, and discuss the effective coarse-graining of the molecular hardware. We show that common molecular mechanisms produce gestation and senescence periods that can reduce noise without changing average abundances, lifetimes, or any concentration-dependent control loops. We also show that single-cell experimental methods that are now commonplace in cell biology do not discriminate between qualitatively different stochastic principles, but that this in turn makes them better suited for identifying which components introduce fluctuations.

Inheritance of Resistance to Sorghum Shoot Fly, Atherigona soccata in Sorghum, Sorghum bicolor (L.) Moench

PubMed Central

Mohammed, Riyazaddin; Are, Ashok Kumar; Munghate, Rajendra Sudhakar; Bhavanasi, Ramaiah; Polavarapu, Kavi Kishor B.; Sharma, Hari Chand

2016-01-01

Sorghum production is affected by a wide array of biotic constraints, of which sorghum shoot fly, Atherigona soccata is the most important pest, which severely damages the sorghum crop during the seedling stage. Host plant resistance is one of the major components to control sorghum shoot fly, A. soccata. To understand the nature of gene action for inheritance of shoot fly resistance, we evaluated 10 parents, 45 F1's and their reciprocals in replicated trials during the rainy and postrainy seasons. The genotypes ICSV 700, Phule Anuradha, ICSV 25019, PS 35805, IS 2123, IS 2146, and IS 18551 exhibited resistance to shoot fly damage across seasons. Crosses between susceptible parents were preferred for egg laying by the shoot fly females, resulting in a susceptible reaction. ICSV 700, ICSV 25019, PS 35805, IS 2123, IS 2146, and IS 18551 exhibited significant and negative general combining ability (gca) effects for oviposition, deadheart incidence, and overall resistance score. The plant morphological traits associated with expression of resistance/susceptibility to shoot fly damage such as leaf glossiness, plant vigor, and leafsheath pigmentation also showed significant gca effects by these genotypes, suggesting the potential for use as a selection criterion to breed for resistance to shoot fly, A. soccata. ICSV 700, Phule Anuradha, IS 2146 and IS 18551 with significant positive gca effects for trichome density can also be utilized in improving sorghums for shoot fly resistance. The parents involved in hybrids with negative specific combining ability (sca) effects for shoot fly resistance traits can be used in developing sorghum hybrids with adaptation to postrainy season. The significant reciprocal effects of combining abilities for oviposition, leaf glossy score and trichome density suggested the influence of cytoplasmic factors in inheritance of shoot fly resistance. Higher values of variance due to specific combining ability (σ2s), dominance variance (σ2d), and lower predictability ratios than the variance due to general combining ability (σ2g) and additive variance (σ2a) for shoot fly resistance traits indicated the predominance of dominance type of gene action, whereas trichome density, leaf glossy score, and plant vigor score with high σ2g, additive variance, predictability ratio, and the ratio of general combining ability to the specific combining ability showed predominance of additive type of gene action indicating importance of heterosis breeding followed by simple selection in breeding shoot fly-resistant sorghums. Most of the traits exhibited high broadsense heritability, indicating high inheritance of shoot fly resistance traits. PMID:27200020

Identification of α-Chimaerin as a Candidate Gene for Critical Period Neuronal Plasticity in Cat and Mouse Visual Cortex

PubMed Central

2011-01-01

Background In cat visual cortex, critical period neuronal plasticity is minimal until approximately 3 postnatal weeks, peaks at 5 weeks, gradually declines to low levels at 20 weeks, and disappears by 1 year of age. Dark rearing slows the entire time course of this critical period, such that at 5 weeks of age, normal cats are more plastic than dark reared cats, whereas at 20 weeks, dark reared cats are more plastic. Thus, a stringent criterion for identifying genes that are important for plasticity in visual cortex is that they show differences in expression between normal and dark reared that are of opposite direction in young versus older animals. Results The present study reports the identification by differential display PCR of a novel gene, α-chimaerin, as a candidate visual cortex critical period plasticity gene that showed bidirectional regulation of expression due to age and dark rearing. Northern blotting confirmed the bidirectional expression and 5'RACE sequencing identified the gene. There are two alternatively-spliced α-chimaerin isoforms: α1 and α2. Western blotting extended the evidence for bidirectional regulation of visual cortex α-chimaerin isoform expression to protein in cats and mice. α1- and α2-Chimaerin were elevated in dark reared compared to normal visual cortex at the peak of the normal critical period and in normal compared to dark reared visual cortex at the nadir of the normal critical period. Analysis of variance showed a significant interaction in both cats and mice for both α-chimaerin isoforms, indicating that the effect of dark rearing depended on age. This differential expression was not found in frontal cortex. Conclusions Chimaerins are RhoGTPase-activating proteins that are EphA4 effectors and have been implicated in a number of processes including growth cone collapse, axon guidance, dendritic spine development and the formation of corticospinal motor circuits. The present results identify α-chimaerin as a candidate molecule for a role in the postnatal critical period of visual cortical plasticity. PMID:21767388

pH regulates genes for flagellar motility, catabolism, and oxidative stress in Escherichia coli K-12.

PubMed

Maurer, Lisa M; Yohannes, Elizabeth; Bondurant, Sandra S; Radmacher, Michael; Slonczewski, Joan L

2005-01-01

Gene expression profiles of Escherichia coli K-12 W3110 were compared as a function of steady-state external pH. Cultures were grown to an optical density at 600 nm of 0.3 in potassium-modified Luria-Bertani medium buffered at pH 5.0, 7.0, and 8.7. For each of the three pH conditions, cDNA from RNA of five independent cultures was hybridized to Affymetrix E. coli arrays. Analysis of variance with an alpha level of 0.001 resulted in 98% power to detect genes showing a twofold difference in expression. Normalized expression indices were calculated for each gene and intergenic region (IG). Differential expression among the three pH classes was observed for 763 genes and 353 IGs. Hierarchical clustering yielded six well-defined clusters of pH profiles, designated Acid High (highest expression at pH 5.0), Acid Low (lowest expression at pH 5.0), Base High (highest at pH 8.7), Base Low (lowest at pH 8.7), Neutral High (highest at pH 7.0, lower in acid or base), and Neutral Low (lowest at pH 7.0, higher at both pH extremes). Flagellar and chemotaxis genes were repressed at pH 8.7 (Base Low cluster), where the cell's transmembrane proton potential is diminished by the maintenance of an inverted pH gradient. High pH also repressed the proton pumps cytochrome o (cyo) and NADH dehydrogenases I and II. By contrast, the proton-importing ATP synthase F1Fo and the microaerophilic cytochrome d (cyd), which minimizes proton export, were induced at pH 8.7. These observations are consistent with a model in which high pH represses synthesis of flagella, which expend proton motive force, while stepping up electron transport and ATPase components that keep protons inside the cell. Acid-induced genes, on the other hand, were coinduced by conditions associated with increased metabolic rate, such as oxidative stress. All six pH-dependent clusters included envelope and periplasmic proteins, which directly experience external pH. Overall, this study showed that (i) low pH accelerates acid consumption and proton export, while coinducing oxidative stress and heat shock regulons; (ii) high pH accelerates proton import, while repressing the energy-expensive flagellar and chemotaxis regulons; and (iii) pH differentially regulates a large number of periplasmic and envelope proteins.

Aging and Intermittent Fasting Impact on Transcriptional Regulation and Physiological Responses of Adult Drosophila Neuronal and Muscle Tissues

PubMed Central

Zhang, Sharon; Ratliff, Eric P.; Molina, Brandon; El-Mecharrafie, Nadja; Mastroianni, Jessica; Kotzebue, Roxanne W.; Achal, Madhulika; Mauntz, Ruth E.; Gonzalez, Arysa; Barekat, Ayeh; Bray, William A.; Macias, Andrew M.; Daugherty, Daniel; Harris, Greg L.; Edwards, Robert A.; Finley, Kim D.

2018-01-01

The progressive decline of the nervous system, including protein aggregate formation, reflects the subtle dysregulation of multiple functional pathways. Our previous work has shown intermittent fasting (IF) enhances longevity, maintains adult behaviors and reduces aggregates, in part, by promoting autophagic function in the aging Drosophila brain. To clarify the impact that IF-treatment has upon aging, we used high throughput RNA-sequencing technology to examine the changing transcriptome in adult Drosophila tissues. Principle component analysis (PCA) and other analyses showed ~1200 age-related transcriptional differences in head and muscle tissues, with few genes having matching expression patterns. Pathway components showing age-dependent expression differences were involved with stress response, metabolic, neural and chromatin remodeling functions. Middle-aged tissues also showed a significant increase in transcriptional drift-variance (TD), which in the CNS included multiple proteolytic pathway components. Overall, IF-treatment had a demonstrably positive impact on aged transcriptomes, partly ameliorating both fold and variance changes. Consistent with these findings, aged IF-treated flies displayed more youthful metabolic, behavioral and basal proteolytic profiles that closely correlated with transcriptional alterations to key components. These results indicate that even modest dietary changes can have therapeutic consequences, slowing the progressive decline of multiple cellular systems, including proteostasis in the aging nervous system. PMID:29642630

Aging and Intermittent Fasting Impact on Transcriptional Regulation and Physiological Responses of Adult Drosophila Neuronal and Muscle Tissues.

PubMed

Zhang, Sharon; Ratliff, Eric P; Molina, Brandon; El-Mecharrafie, Nadja; Mastroianni, Jessica; Kotzebue, Roxanne W; Achal, Madhulika; Mauntz, Ruth E; Gonzalez, Arysa; Barekat, Ayeh; Bray, William A; Macias, Andrew M; Daugherty, Daniel; Harris, Greg L; Edwards, Robert A; Finley, Kim D

2018-04-10

The progressive decline of the nervous system, including protein aggregate formation, reflects the subtle dysregulation of multiple functional pathways. Our previous work has shown intermittent fasting (IF) enhances longevity, maintains adult behaviors and reduces aggregates, in part, by promoting autophagic function in the aging Drosophila brain. To clarify the impact that IF-treatment has upon aging, we used high throughput RNA-sequencing technology to examine the changing transcriptome in adult Drosophila tissues. Principle component analysis (PCA) and other analyses showed ~1200 age-related transcriptional differences in head and muscle tissues, with few genes having matching expression patterns. Pathway components showing age-dependent expression differences were involved with stress response, metabolic, neural and chromatin remodeling functions. Middle-aged tissues also showed a significant increase in transcriptional drift-variance (TD), which in the CNS included multiple proteolytic pathway components. Overall, IF-treatment had a demonstrably positive impact on aged transcriptomes, partly ameliorating both fold and variance changes. Consistent with these findings, aged IF-treated flies displayed more youthful metabolic, behavioral and basal proteolytic profiles that closely correlated with transcriptional alterations to key components. These results indicate that even modest dietary changes can have therapeutic consequences, slowing the progressive decline of multiple cellular systems, including proteostasis in the aging nervous system.

TU-CD-BRB-12: Radiogenomics of MRI-Guided Prostate Cancer Biopsy Habitats

DOE Office of Scientific and Technical Information (OSTI.GOV)

Stoyanova, R; Lynne, C; Abraham, S

2015-06-15

Purpose: Diagnostic prostate biopsies are subject to sampling bias. We hypothesize that quantitative imaging with multiparametric (MP)-MRI can more accurately direct targeted biopsies to index lesions associated with highest risk clinical and genomic features. Methods: Regionally distinct prostate habitats were delineated on MP-MRI (T2-weighted, perfusion and diffusion imaging). Directed biopsies were performed on 17 habitats from 6 patients using MRI-ultrasound fusion. Biopsy location was characterized with 52 radiographic features. Transcriptome-wide analysis of 1.4 million RNA probes was performed on RNA from each habitat. Genomics features with insignificant expression values (<0.25) and interquartile range <0.5 were filtered, leaving total of 212more » genes. Correlation between imaging features, genes and a 22 feature genomic classifier (GC), developed as a prognostic assay for metastasis after radical prostatectomy was investigated. Results: High quality genomic data was derived from 17 (100%) biopsies. Using the 212 ‘unbiased’ genes, the samples clustered by patient origin in unsupervised analysis. When only prostate cancer related genomic features were used, hierarchical clustering revealed samples clustered by needle-biopsy Gleason score (GS). Similarly, principal component analysis of the imaging features, found the primary source of variance segregated the samples into high (≥7) and low (6) GS. Pearson’s correlation analysis of genes with significant expression showed two main patterns of gene expression clustering prostate peripheral and transitional zone MRI features. Two-way hierarchical clustering of GC with radiomics features resulted in the expected groupings of high and low expressed genes in this metastasis signature. Conclusions: MP-MRI-targeted diagnostic biopsies can potentially improve risk stratification by directing pathological and genomic analysis to clinically significant index lesions. As determinant lesions are more reliably identified, targeting with radiotherapy should improve outcome. This is the first demonstration of a link between quantitative imaging features (radiomics) with genomic features in MRI-directed prostate biopsies. The research was supported by NIH- NCI R01 CA 189295 and R01 CA 189295; E Davicioni is partial owner of GenomeDx Biosciences, Inc. M Takhar, N Erho, L Lam, C Buerki and E Davicioni are current employees at GenomeDx Biosciences, Inc.« less

Cross-Disorder Genome-Wide Analyses Suggest a Complex Genetic Relationship Between Tourette Syndrome and Obsessive-Compulsive Disorder

PubMed Central

Yu, Dongmei; Mathews, Carol A.; Scharf, Jeremiah M.; Neale, Benjamin M.; Davis, Lea K.; Gamazon, Eric R.; Derks, Eske M.; Evans, Patrick; Edlund, Christopher K.; Crane, Jacquelyn; Fagerness, Jesen A.; Osiecki, Lisa; Gallagher, Patience; Gerber, Gloria; Haddad, Stephen; Illmann, Cornelia; McGrath, Lauren M.; Mayerfeld, Catherine; Arepalli, Sampath; Barlassina, Cristina; Barr, Cathy L.; Bellodi, Laura; Benarroch, Fortu; Berrió, Gabriel Bedoya; Bienvenu, O. Joseph; Black, Donald; Bloch, Michael H.; Brentani, Helena; Bruun, Ruth D.; Budman, Cathy L.; Camarena, Beatriz; Campbell, Desmond D.; Cappi, Carolina; Cardona Silgado, Julio C.; Cavallini, Maria C.; Chavira, Denise A.; Chouinard, Sylvain; Cook, Edwin H.; Cookson, M. R.; Coric, Vladimir; Cullen, Bernadette; Cusi, Daniele; Delorme, Richard; Denys, Damiaan; Dion, Yves; Eapen, Valsama; Egberts, Karin; Falkai, Peter; Fernandez, Thomas; Fournier, Eduardo; Garrido, Helena; Geller, Daniel; Gilbert, Donald; Girard, Simon L.; Grabe, Hans J.; Grados, Marco A.; Greenberg, Benjamin D.; Gross-Tsur, Varda; Grünblatt, Edna; Hardy, John; Heiman, Gary A.; Hemmings, Sian M.J.; Herrera, Luis D.; Hezel, Dianne M.; Hoekstra, Pieter J.; Jankovic, Joseph; Kennedy, James L.; King, Robert A.; Konkashbaev, Anuar I.; Kremeyer, Barbara; Kurlan, Roger; Lanzagorta, Nuria; Leboyer, Marion; Leckman, James F.; Lennertz, Leonhard; Liu, Chunyu; Lochner, Christine; Lowe, Thomas L.; Lupoli, Sara; Macciardi, Fabio; Maier, Wolfgang; Manunta, Paolo; Marconi, Maurizio; McCracken, James T.; Mesa Restrepo, Sandra C.; Moessner, Rainald; Moorjani, Priya; Morgan, Jubel; Muller, Heike; Murphy, Dennis L.; Naarden, Allan L.; Ochoa, William Cornejo; Ophoff, Roel A.; Pakstis, Andrew J.; Pato, Michele T.; Pato, Carlos N.; Piacentini, John; Pittenger, Christopher; Pollak, Yehuda; Rauch, Scott L.; Renner, Tobias; Reus, Victor I.; Richter, Margaret A.; Riddle, Mark A.; Robertson, Mary M.; Romero, Roxana; Rosário, Maria C.; Rosenberg, David; Ruhrmann, Stephan; Sabatti, Chiara; Salvi, Erika; Sampaio, Aline S.; Samuels, Jack; Sandor, Paul; Service, Susan K.; Sheppard, Brooke; Singer, Harvey S.; Smit, Jan H.; Stein, Dan J.; Strengman, Eric; Tischfield, Jay A.; Turiel, Maurizio; Valencia Duarte, Ana V.; Vallada, Homero; Veenstra-VanderWeele, Jeremy; Walitza, Susanne; Walkup, John; Wang, Ying; Weale, Mike; Weiss, Robert; Wendland, Jens R.; Westenberg, Herman G.M.; Yao, Yin; Hounie, Ana G.; Miguel, Euripedes C.; Nicolini, Humberto; Wagner, Michael; Ruiz-Linares, Andres; Cath, Danielle C.; McMahon, William; Posthuma, Danielle; Oostra, Ben A.; Nestadt, Gerald; Rouleau, Guy A.; Purcell, Shaun; Jenike, Michael A.; Heutink, Peter; Hanna, Gregory L.; Conti, David V.; Arnold, Paul D.; Freimer, Nelson; Stewart, S. Evelyn; Knowles, James A.; Cox, Nancy J.; Pauls, David L.

2014-01-01

Obsessive-compulsive disorder (OCD) and Tourette Syndrome (TS) are highly heritable neurodevelopmental disorders that are thought to share genetic risk factors. However, the identification of definitive susceptibility genes for these etiologically complex disorders remains elusive. Here, we report a combined genome-wide association study (GWAS) of TS and OCD in 2723 cases (1310 with OCD, 834 with TS, 579 with OCD plus TS/chronic tics (CT)), 5667 ancestry-matched controls, and 290 OCD parent-child trios. Although no individual single nucleotide polymorphisms (SNPs) achieved genome-wide significance, the GWAS signals were enriched for SNPs strongly associated with variations in brain gene expression levels, i.e. expression quantitative loci (eQTLs), suggesting the presence of true functional variants that contribute to risk of these disorders. Polygenic score analyses identified a significant polygenic component for OCD (p=2×10−4), predicting 3.2% of the phenotypic variance in an independent data set. In contrast, TS had a smaller, non-significant polygenic component, predicting only 0.6% of the phenotypic variance (p=0.06). No significant polygenic signal was detected across the two disorders, although the sample is likely underpowered to detect a modest shared signal. Furthermore, the OCD polygenic signal was significantly attenuated when cases with both OCD and TS/CT were included in the analysis (p=0.01). Previous work has shown that TS and OCD have some degree of shared genetic variation. However, the data from this study suggest that there are also distinct components to the genetic architectures of TS and OCD. Furthermore, OCD with co-occurring TS/CT may have different underlying genetic susceptibility compared to OCD alone. PMID:25158072

Adaptable gene-specific dye bias correction for two-channel DNA microarrays.

PubMed

Margaritis, Thanasis; Lijnzaad, Philip; van Leenen, Dik; Bouwmeester, Diane; Kemmeren, Patrick; van Hooff, Sander R; Holstege, Frank C P

2009-01-01

DNA microarray technology is a powerful tool for monitoring gene expression or for finding the location of DNA-bound proteins. DNA microarrays can suffer from gene-specific dye bias (GSDB), causing some probes to be affected more by the dye than by the sample. This results in large measurement errors, which vary considerably for different probes and also across different hybridizations. GSDB is not corrected by conventional normalization and has been difficult to address systematically because of its variance. We show that GSDB is influenced by label incorporation efficiency, explaining the variation of GSDB across different hybridizations. A correction method (Gene- And Slide-Specific Correction, GASSCO) is presented, whereby sequence-specific corrections are modulated by the overall bias of individual hybridizations. GASSCO outperforms earlier methods and works well on a variety of publically available datasets covering a range of platforms, organisms and applications, including ChIP on chip. A sequence-based model is also presented, which predicts which probes will suffer most from GSDB, useful for microarray probe design and correction of individual hybridizations. Software implementing the method is publicly available.

Adaptable gene-specific dye bias correction for two-channel DNA microarrays

PubMed Central

Margaritis, Thanasis; Lijnzaad, Philip; van Leenen, Dik; Bouwmeester, Diane; Kemmeren, Patrick; van Hooff, Sander R; Holstege, Frank CP

2009-01-01

DNA microarray technology is a powerful tool for monitoring gene expression or for finding the location of DNA-bound proteins. DNA microarrays can suffer from gene-specific dye bias (GSDB), causing some probes to be affected more by the dye than by the sample. This results in large measurement errors, which vary considerably for different probes and also across different hybridizations. GSDB is not corrected by conventional normalization and has been difficult to address systematically because of its variance. We show that GSDB is influenced by label incorporation efficiency, explaining the variation of GSDB across different hybridizations. A correction method (Gene- And Slide-Specific Correction, GASSCO) is presented, whereby sequence-specific corrections are modulated by the overall bias of individual hybridizations. GASSCO outperforms earlier methods and works well on a variety of publically available datasets covering a range of platforms, organisms and applications, including ChIP on chip. A sequence-based model is also presented, which predicts which probes will suffer most from GSDB, useful for microarray probe design and correction of individual hybridizations. Software implementing the method is publicly available. PMID:19401678

Recent developments in the genetics of ADHD.

PubMed

Grimm, Oliver; Kittel-Schneider, Sarah; Reif, Andreas

2018-05-02

Attention deficit hyperactivity disorder (ADHD) is a developmental psychiatric disorder which affects children and adults. ADHD is one of the psychiatric disorders with the strongest genetic basis according to familial, twin and SNP-based epidemiological studies. In this review, we provide an update of recent insights in the genetic basis of ADHD. We discuss recent progress from genome-wide association studies (GWAS) looking at common variants as well as rare copy number variations (CNVs). New analysis of gene groups, so-called functional ontologies, provide some insight into the gene networks afflicted, pointing to the role of neurodevelopmentally expressed gene-networks. Bioinformatic methods such as functional enrichment analysis and protein-protein network analysis are used to highlight biological processes of likely relevance to the aetiology of ADHD. Additionally, CNVs seem to map on important pathways implicated in synaptic signalling and neurodevelopment. While some candidate gene associations of e.g. neurotransmitter receptors and signalling have been replicated, they do not seem to explain significant variance in recent GWAS. We discuss insights from recent case-control SNP-GWAS which gave whole-genome significant SNPs in ADHD. This article is protected by copyright. All rights reserved.

Real-time quantitative polymerase chain reaction analysis of patients with refractory chronic periodontitis.

PubMed

Marconcini, Simone; Covani, Ugo; Barone, Antonio; Vittorio, Orazio; Curcio, Michele; Barbuti, Serena; Scatena, Fabrizio; Felli, Lamberto; Nicolini, Claudio

2011-07-01

Periodontitis is a complex multifactorial disease and is typically polygenic in origin. Genes play a fundamental part in each biologic process forming complex networks of interactions. However, only some genes have a high number of interactions with other genes in the network and may, therefore, be considered to play an important role. In a preliminary bioinformatic analysis, five genes that showed a higher number of interactions were identified and termed leader genes. In the present study, we use real-time quantitative polymerase chain reaction (PCR) technology to evaluate the expression levels of leader genes in the leukocytes of 10 patients with refractory chronic periodontitis and compare the expression levels with those of the same genes in 24 healthy patients. Blood was collected from 24 healthy human subjects and 10 patients with refractory chronic periodontitis and placed into heparinized blood collection tubes by personnel trained in phlebotomy using a sterile technique. Blood leukocyte cells were immediately lysed by using a kit for total RNA purification from human whole blood. Complementary DNA (cDNA) synthesis was obtained from total RNA and then real-time quantitative PCR was performed. PCR efficiencies were calculated with a relative standard curve derived from a five cDNA dilution series in triplicate that gave regression coefficients >0.98 and efficiencies >96%. The standard curves were obtained using glyceraldehyde-3-phosphate dehydrogenase (GAPDH) and growth factor receptor binding protein 2 (GRB2), casitas B-lineage lymphoma (CBL), nuclear factor-KB1 (NFKB1), and REL-A (gene for transcription factor p65) gene primers and amplified with 1.6, 8, 40, 200, and 1,000 ng/μL total cDNA. Curves obtained for each sample showed a linear relationship between RNA concentrations and the cycle threshold value of real-time quantitative PCR for all genes. Data were expressed as mean ± SE (SEM). The groups were compared to the analysis of variance. A probability value <0.01 was considered statistically significant. The present study agrees with the preliminary bioinformatics analysis. In our experiments, the association of pathology with the genes was statistically significant for GRB2 and CBL (P <0.01), and it was not statistically significant for REL-A and NFKB1. This article lends support to our preliminary hypothesis that assigned an important role in refractory aggressive periodontitis to leader genes.

Specification, testing, and interpretation of gene-by-measured-environment interaction models in the presence of gene-environment correlation

PubMed Central

Rathouz, Paul J.; Van Hulle, Carol A.; Lee Rodgers, Joseph; Waldman, Irwin D.; Lahey, Benjamin B.

2009-01-01

Purcell (2002) proposed a bivariate biometric model for testing and quantifying the interaction between latent genetic influences and measured environments in the presence of gene-environment correlation. Purcell’s model extends the Cholesky model to include gene-environment interaction. We examine a number of closely-related alternative models that do not involve gene-environment interaction but which may fit the data as well Purcell’s model. Because failure to consider these alternatives could lead to spurious detection of gene-environment interaction, we propose alternative models for testing gene-environment interaction in the presence of gene-environment correlation, including one based on the correlated factors model. In addition, we note mathematical errors in the calculation of effect size via variance components in Purcell’s model. We propose a statistical method for deriving and interpreting variance decompositions that are true to the fitted model. PMID:18293078

The contribution of the mitochondrial genome to sex-specific fitness variance.

PubMed

Smith, Shane R T; Connallon, Tim

2017-05-01

Maternal inheritance of mitochondrial DNA (mtDNA) facilitates the evolutionary accumulation of mutations with sex-biased fitness effects. Whereas maternal inheritance closely aligns mtDNA evolution with natural selection in females, it makes it indifferent to evolutionary changes that exclusively benefit males. The constrained response of mtDNA to selection in males can lead to asymmetries in the relative contributions of mitochondrial genes to female versus male fitness variation. Here, we examine the impact of genetic drift and the distribution of fitness effects (DFE) among mutations-including the correlation of mutant fitness effects between the sexes-on mitochondrial genetic variation for fitness. We show how drift, genetic correlations, and skewness of the DFE determine the relative contributions of mitochondrial genes to male versus female fitness variance. When mutant fitness effects are weakly correlated between the sexes, and the effective population size is large, mitochondrial genes should contribute much more to male than to female fitness variance. In contrast, high fitness correlations and small population sizes tend to equalize the contributions of mitochondrial genes to female versus male variance. We discuss implications of these results for the evolution of mitochondrial genome diversity and the genetic architecture of female and male fitness. © 2017 The Author(s). Evolution © 2017 The Society for the Study of Evolution.

Multi-ethnic analysis reveals soluble L-selectin may be post-transcriptionally regulated by 3′UTR polymorphism: the Multi-Ethnic Study of Atherosclerosis (MESA)

PubMed Central

Berardi, Cecilia; Larson, Nicholas B.; Decker, Paul A.; Wassel, Christina L.; Kirsch, Phillip S.; Pankow, James S.; Sale, Michele M.; de Andrade, Mariza; Sicotte, Hugues; Tang, Weihong; Hanson, Naomi Q.; Tsai, Michael Y.; da Chen, Yii-Der I; Bielinski, Suzette J.

2015-01-01

L-selectin is constitutively expressed on leukocytes and mediates their interaction with endothelial cells during inflammation. Previous studies on the association of soluble L-selectin (sL-selectin) with cardiovascular disease (CVD) are inconsistent. Genetic variants associated with sL-selectin levels may be a better surrogate of levels over a lifetime. We explored the association of genetic variants and sL-selectin levels in a race/ethnicity stratified random sample of 2,403 participants in the Multi-Ethnic Study of Atherosclerosis (MESA). Through a genome-wide analysis with additive linear regression models, we found that rs12938 on the SELL gene accounted for a significant portion of the protein level variance across all four races/ethnicities. To evaluate potential additional associations, elastic net models were used for variants located in the SELL/SELP/SELE genetic region and an additional two SNPs, rs3917768 and rs4987361, were associated with sL-selectin levels in African Americans. These variants accounted for a portion of protein variance that ranged from 4% in Hispanic to 14% in African Americans. To investigate the relationship of these variants with CVD, 6,317 subjects were used. No significant association was found between any of the identified SNPs and carotid intima-media thickness or presence of carotid plaque using linear and logistic regression, respectively. Similarly no significant results were found for coronary artery calcium or coronary heart disease events. In conclusion, we found that variants within the SELL gene are associated with sL-selectin levels. Despite accounting for a significant portion of the protein level variance, none of the variants was associated with clinical or subclinical CVD. PMID:25576479

[CONDITIONS OF SYNOVIAL MESENCHYMAL STEM CELLS DIFFERENTIATING INTO FIBROCARTILAGE CELLS].

PubMed

Fu, Peiliang; Cong, Ruijun; Chen, Song; Zhang, Lei; Ding, Zheru; Zhou, Qi; Li, Lintao; Xu, Zhenyu; Wu, Yuli; Wu, Haishan

2015-01-01

To explore the conditions of synovial derived mesenchymal stem cells (SMSCs) differentiating into the fibrocartilage cells by using the orthogonal experiment. The synovium was harvested from 5 adult New Zealand white rabbits, and SMSCs were separated by adherence method. The flow cytometry and multi-directional differentiation method were used to identify the SMSCs. The conditions were found from the preliminary experiment and literature review. The missing test was carried out to screen the conditions and then 12 conditions were used for the orthogonal experiment, including transforming growth factor β1 (TGF-β1), bone morphogenic protein 2 (BMP-2), dexamethasone (DEX), proline, ascorbic acid (ASA), pyruvic acid, insulin + transferrin + selenious acid pre-mixed solution (ITS), bovin serum albumin (BSA), basic fibroblast growth factor (bFGF), intermittent hydraulic pressure (IHP), bone morphogenic protein 7 (BMP-7), and insulin-like growth factor (IGF). The L60 (212) orthogonal experiment was designed using the SPSS 18.0 with 2 level conditions and the cells were induced to differentiate on the small intestinal submucosa (SIS)-3D scaffold. The CD151+/CD44+ cells were detected with the flow cytometry and then the differentiation rate was recorded. The immumohistochemical staining, cellular morphology, toluidine blue staining, and semi-quantitative RT-PCR examination for the gene expressions of sex determining region Y (SRY)-box 9 gene (Sox9), aggrecan gene (AGN), collagen type I gene (Col I), collagen type II gene (Col II), collagen type IX gene (Col IX) were used for result confirmation. The differentiation rate was calculated as the product of CD151/CD44+ cells and cells with Col I high expression. The grow curve was detected with the DNA abundance using the PicoGreen Assay. The visual observation and the variances analysis among the variable were used to evaluate the result of the orthogonal experiment, 1 level interaction was considered. The q-test and the least significant difference (LDS) were used for the variance analysis with a type III calibration model. The test criteria (a) was 0.05. The cells were certified as SMSCs, the double-time of the cells was 28 hours. During the differentiation into the fibrocartilage, the volume of the SIS-3D scaffold enlarged double every 5 days. The scaffolds were positively stained by toluidine blue at 14 days. The visual observation showed that high levels of TGF-β1 and BMP-7 were optimum for the differentiation, and BMP-7 showed the interaction with BMP-2. The conditions of DEX, ASA, ITS, transferrin, bFGF showed decreasing promotional function by degrees, and the model showed the perfect relevance. P value was 0.000 according to the variance analysis. The intercept analysis showed different independent variables brought about variant contribution; the TGF-β1, ASA, bFGF, IGF, and BMP-7 were more remarkable, which were similar to the visual observation. In the process of the SMSCs differentiation into the fibrocartilage, the concentrations of TGF-β1, ASA, bFGF, and IGF reasonably can improve the conversion rate of the fibrocartilage cells. The accurate conditions of the reaulatory factor should be explored further.

Genetic Variance in the F2 Generation of Divergently Selected Parents

Treesearch

M.P. Koshy; G. Namkoong; J.H. Roberds

1998-01-01

Either by selective breeding for population divergence or by using natural population differences, F2 and advanced generation hybrids can be developed with high variances. We relate the size of the genetic variance to the population divergence based on a forward and backward mutation model at a locus with two alleles with additive gene action....

Prediction of flow duration curves for ungauged basins

NASA Astrophysics Data System (ADS)

Atieh, Maya; Taylor, Graham; M. A. Sattar, Ahmed; Gharabaghi, Bahram

2017-02-01

This study presents novel models for prediction of flow Duration Curves (FDCs) at ungauged basins using artificial neural networks (ANN) and Gene Expression Programming (GEP) trained and tested using historical flow records from 171 unregulated and 89 regulated basins across North America. For the 89 regulated basins, FDCs were generated for both before and after flow regulation. Topographic, climatic, and land use characteristics are used to develop relationships between these basin characteristics and FDC statistical distribution parameters: mean (m) and variance (ν). The two main hypotheses that flow regulation has negligible effect on the mean (m) while it the variance (ν) were confirmed. The novel GEP model that predicts the mean (GEP-m) performed very well with high R2 (0.9) and D (0.95) values and low RAE value of 0.25. The simple regression model that predicts the variance (REG-v) was developed as a function of the mean (m) and a flow regulation index (R). The measured performance and uncertainty analysis indicated that the ANN-m was the best performing model with R2 (0.97), RAE (0.21), D (0.93) and the lowest 95% confidence prediction error interval (+0.22 to +3.49). Both GEP and ANN models were most sensitive to drainage area followed by mean annual precipitation, apportionment entropy disorder index, and shape factor.

Osteogenic gene expression of murine osteoblastic (MC3T3-E1) cells under cyclic tension

NASA Astrophysics Data System (ADS)

Kao, C. T.; Chen, C. C.; Cheong, U.-I.; Liu, S. L.; Huang, T. H.

2014-08-01

Low-level laser therapy (LLLT) can promote cell proliferation. The remodeling ability of the tension side of orthodontic teeth affects post-orthodontic stability. The purpose of the present study was to investigate the osteogenic effects of LLLT on osteoblast-like cells treated with a simulated tension system that provides a mechanical tension regimen. Murine osteoblastic (MC3T3-E1) cells were cultured in a Flexcell strain unit with programmed loads of 12% elongation at a frequency of 0.5 Hz for 24 and 48 h. The cultured cells were treated with a low-level diode laser using powers of 5 J and 10 J. The proliferation of MC3T3-E1 cells was determined using the Alamar Blue assay. The expression of osteogenic genes (type I collagen (Col-1), osteopontin (OPN), osteocalcin (OC), osteoprotegerin (OPG), receptor activator of nuclear factor kappa B ligand (RANKL), bone morphologic protein (BMP-2), and bone morphologic protein (BMP-4)) in MC3T3-E1 cells was analyzed using reverse transcription polymerase chain reaction (RT-PCR). The data were analyzed using one-way analysis of variance. The proliferation rate of tension-cultured MC3T3-E1 cells under 5 J and 10 J LLLT increased compared with that of the control group (p < 0.05). Prominent mineralization of the MC3T3-E1 cells was visible using a von Kossa stain in the 5 J LLLT group. Osteogenic genes (Col-1, OC, OPG and BMP-2) were significantly expressed in the MC3T3-E1 cells treated with 5 J and 10 J LLLT (p < 0.05). LLLT in tension-cultured MC3T3-E1 cells showed synergistic osteogenic effects, including increases in cell proliferation and Col-1, OPN, OC, OPG and BMP-2 gene expression. LLLT might be beneficial for bone remodeling on the tension side of orthodontics.

MyoD expression restores defective myogenic differentiation of human mesoangioblasts from inclusion-body myositis muscle.

PubMed

Morosetti, Roberta; Mirabella, Massimiliano; Gliubizzi, Carla; Broccolini, Aldobrando; De Angelis, Luciana; Tagliafico, Enrico; Sampaolesi, Maurilio; Gidaro, Teresa; Papacci, Manuela; Roncaglia, Enrica; Rutella, Sergio; Ferrari, Stefano; Tonali, Pietro Attilio; Ricci, Enzo; Cossu, Giulio

2006-11-07

Inflammatory myopathies (IM) are acquired diseases of skeletal muscle comprising dermatomyositis (DM), polymyositis (PM), and inclusion-body myositis (IBM). Immunosuppressive therapies, usually beneficial for DM and PM, are poorly effective in IBM. We report the isolation and characterization of mesoangioblasts, vessel-associated stem cells, from diagnostic muscle biopsies of IM. The number of cells isolated, proliferation rate and lifespan, markers expression, and ability to differentiate into smooth muscle do not differ among normal and IM mesoangioblasts. At variance with normal, DM and PM mesoangioblasts, cells isolated from IBM, fail to differentiate into skeletal myotubes. These data correlate with lack in connective tissue of IBM muscle of alkaline phosphatase (ALP)-positive cells, conversely dramatically increased in PM and DM. A myogenic inhibitory basic helix-loop-helix factor B3 is highly expressed in IBM mesoangioblasts. Indeed, silencing this gene or overexpressing MyoD rescues the myogenic defect of IBM mesoangioblasts, opening novel cell-based therapeutic strategies for this crippling disorder.

MyoD expression restores defective myogenic differentiation of human mesoangioblasts from inclusion-body myositis muscle

PubMed Central

Morosetti, Roberta; Mirabella, Massimiliano; Gliubizzi, Carla; Broccolini, Aldobrando; De Angelis, Luciana; Tagliafico, Enrico; Sampaolesi, Maurilio; Gidaro, Teresa; Papacci, Manuela; Roncaglia, Enrica; Rutella, Sergio; Ferrari, Stefano; Tonali, Pietro Attilio; Ricci, Enzo; Cossu, Giulio

2006-01-01

Inflammatory myopathies (IM) are acquired diseases of skeletal muscle comprising dermatomyositis (DM), polymyositis (PM), and inclusion-body myositis (IBM). Immunosuppressive therapies, usually beneficial for DM and PM, are poorly effective in IBM. We report the isolation and characterization of mesoangioblasts, vessel-associated stem cells, from diagnostic muscle biopsies of IM. The number of cells isolated, proliferation rate and lifespan, markers expression, and ability to differentiate into smooth muscle do not differ among normal and IM mesoangioblasts. At variance with normal, DM and PM mesoangioblasts, cells isolated from IBM, fail to differentiate into skeletal myotubes. These data correlate with lack in connective tissue of IBM muscle of alkaline phosphatase (ALP)-positive cells, conversely dramatically increased in PM and DM. A myogenic inhibitory basic helix–loop–helix factor B3 is highly expressed in IBM mesoangioblasts. Indeed, silencing this gene or overexpressing MyoD rescues the myogenic defect of IBM mesoangioblasts, opening novel cell-based therapeutic strategies for this crippling disorder. PMID:17077152

Effects of selection for ethanol preference on gene expression in the nucleus accumbens of HS-CC mice

PubMed Central

Colville, A. M.; Iancu, O. D.; Oberbeck, D. L.; Darakjian, P.; Zheng, C. L.; Walter, N. A. R.; Harrington, C. A.; Searles, R. P.; McWeeney, S.; Hitzemann, R. J.

2017-01-01

Previous studies on changes in murine brain gene expression associated with the selection for ethanol preference have used F2 intercross or heterogeneous stock (HS) founders, derived from standard laboratory strains. However, these populations represent only a small proportion of the genetic variance available in Mus musculus. To investigate a wider range of genetic diversity, we selected mice for ethanol preference using an HS derived from the eight strains of the collaborative cross. These HS mice were selectively bred (four generations) for high and low ethanol preference. The nucleus accumbens shell of naive S4 mice was interrogated using RNA sequencing (RNA-Seq). Gene networks were constructed using the weighted gene coexpression network analysis assessing both coexpression and cosplicing. Selection targeted one of the network coexpression modules (greenyellow) that was significantly enriched in genes associated with receptor signaling activity including Chrna7, Grin2a, Htr2a and Oprd1. Connectivity in the module as measured by changes in the hub nodes was significantly reduced in the low preference line. Of particular interest was the observation that selection had marked effects on a large number of cell adhesion molecules, including cadherins and protocadherins. In addition, the coexpression data showed that selection had marked effects on long non-coding RNA hub nodes. Analysis of the cosplicing network data showed a significant effect of selection on a large cluster of Ras GTPase-binding genes including Cdkl5, Cyfip1, Ndrg1, Sod1 and Stxbp5. These data in part support the earlier observation that preference is linked to Ras/Mapk pathways. PMID:28058793

Evolutionary perspectives on the links between mitochondrial genotype and disease phenotype.

PubMed

Dowling, Damian K

2014-04-01

Disorders of the mitochondrial respiratory chain are heterogeneous in their symptoms and underlying genetics. Simple links between candidate mutations and expression of disease phenotype typically do not exist. It thus remains unclear how the genetic variation in the mitochondrial genome contributes to the phenotypic expression of complex traits and disease phenotypes. I summarize the basic genetic processes known to underpin mitochondrial disease. I highlight other plausible processes, drawn from the evolutionary biological literature, whose contribution to mitochondrial disease expression remains largely empirically unexplored. I highlight recent advances to the field, and discuss common-ground and -goals shared by researchers across medical and evolutionary domains. Mitochondrial genetic variance is linked to phenotypic variance across a variety of traits (e.g. reproductive function, life expectancy) fundamental to the upkeep of good health. Evolutionary theory predicts that mitochondrial genomes are destined to accumulate male-harming (but female-friendly) mutations, and this prediction has received proof-of-principle support. Furthermore, mitochondrial effects on the phenotype are typically manifested via interactions between mitochondrial and nuclear genes. Thus, whether a mitochondrial mutation is pathogenic in effect can depend on the nuclear genotype in which is it expressed. Many disease phenotypes associated with OXPHOS malfunction might be determined by the outcomes of mitochondrial-nuclear interactions, and by the evolutionary forces that historically shaped mitochondrial DNA (mtDNA) sequences. Concepts and results drawn from the evolutionary sciences can have broad, but currently under-utilized, applicability to the medical sciences and provide new insights into understanding the complex genetics of mitochondrial disease. This article is part of a Special Issue entitled Frontiers of Mitochondrial Research. Copyright © 2013. Published by Elsevier B.V.

A mathematical model of in vivo bovine blastocyst developmental to gestational Day 15.

PubMed

Shorten, P R; Donnison, M; McDonald, R M; Meier, S; Ledgard, A M; Berg, D

2018-06-20

Bovine embryo growth involves a complex interaction between the developing embryo and the growth-promoting potential of the uterine environment. We have previously established links between embryonic factors (embryo stage, embryo gene expression), maternal factors (progesterone, body condition score), and embryonic growth to 8 d after bulk transfer of Day 7 in vitro-produced blastocysts. In this study we recovered blastocysts on Days 7 and 15 after artificial insemination to test the hypothesis that in vivo and in vitro embryos follow a similar growth program. We conducted our study using 4 commercial farms and repeated our study over 2 yr (2014, 2015), with data available from 2 of the 4 farms in the second year. Morphological and gene expression measurements (196 candidate genes) of the Day 7 embryos were measured and the progesterone concentration of the cows were measured throughout the reproductive cycle as a reflection of the state of the uterine environment. These data were also used to assess the interaction between the uterine environment and the developing embryo and to examine how well Day 7 embryo stage can be predicted from the Day 7 gene expression profile. Progesterone was not a strong predictor of in vivo embryo growth to Day 15. This contrasts with a range of Day 7 embryo transfer studies which demonstrated that progesterone is a very good predictor of embryo growth to Day 15. Our analysis demonstrates that in vivo embryos are 3 times less sensitive to progesterone than in vitro-transferred embryos (up to Day 15). This highlights that caution must be applied when extrapolating the results of in vitro embryo transfer studies to the in vivo situation. The similar variance in measured and predicted (based on Day 15 length) Day 7 embryo stage indicate low stochastic perturbations for in vivo embryo growth (large stochastic growth effects would generate a significantly larger standard deviation in measured embryo length on Day 15). We also identified that Day 7 embryo stage could be predicted based on the Day 7 gene expression profile (58% overall success rate for classification of 5 embryo stages). Our analysis also associated genes with each developmental stage and demonstrates the high level of temporal regulation of genes that occurs during early embryonic development. Copyright © 2018 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Asporin stably expressed in the surface layer of mandibular condylar cartilage and augmented in the deeper layer with age.

PubMed

Miyamoto, Yutaka; Kanzaki, Hiroyuki; Wada, Satoshi; Tsuruoka, Sari; Itohiya, Kanako; Kumagai, Kenichi; Hamada, Yoshiki; Nakamura, Yoshiki

2017-12-01

Mandibular condylar cartilage (MCC) exhibits dual roles both articular cartilage and growth center. Of many growth factors, TGF-β has been implicated in the growth of articular cartilage including MCC. Recently, Asporin, decoy to TGF-β, was discovered and it blocks TGF-β signaling. Asporin is expressed in a variety of tissues including osteoarthritic articular cartilage, though there was no report of Asporin expression in MCC. In the present study, we investigated the temporal and spatial expression of Asporin in MCC. Gene expression profile of MCC and epiphyseal cartilage in tibia of 5 weeks old ICR mice were firstly compared with microarray analysis using the laser capture microdissected samples. Variance of gene expression was further confirmed by real-time RT-PCR and immunohistochemical staining at 1,3,10, and 20 weeks old. TGF-β and its signaling molecule, phosphorylated Smad-2/3 (p-Smad2/3), were also examined by immunohistochemical staining. Microarray analysis revealed that Asporin was highly expressed in MCC. Real-time RT-PCR analysis confirmed that the fibrous layer of MCC exhibited stable higher Asporin expression at any time points as compared to epiphyseal cartilage. This was also observed in immunohistochemical staining. Deeper layer in MCC augmented Asporin expression with age. Whereas, TGF-β was stably highly observed in the layer. The fibrous layer of MCC exhibited weak staining of p-Smad2/3, though the proliferating layer of MCC was strongly stained as compared to epiphyseal cartilage of tibia at early time point. Consistent with the increase of Asporin expression in the deeper layer of MCC, the intensity of p-Smad-2/3 staining was decreased with age. In conclusion, we discovered that Asporin was stably expressed at the fibrous layer of MCC, which makes it possible to manage both articular cartilage and growth center at the same time.

Fetal DNA methylation of autism spectrum disorders candidate genes: association with spontaneous preterm birth.

PubMed

Behnia, Fara; Parets, Sasha E; Kechichian, Talar; Yin, Huaizhi; Dutta, Eryn H; Saade, George R; Smith, Alicia K; Menon, Ramkumar

2015-04-01

Autism spectrum disorder (ASD) is associated with preterm birth (PTB), although the reason underlying this relationship is still unclear. Our objective was to examine DNA methylation patterns of 4 ASD candidate genes in human fetal membranes from spontaneous PTB and uncomplicated term birth. A literature search for genes that have been implicated in ASD yielded 14 candidate genes (OXTR, SHANK3, BCL2, RORA, EN2, RELN, MECP2, AUTS2, NLGN3, NRXN1, SLC6A4, UBE3A, GABA, AFF2) that were epigenetically modified in relation to ASD. DNA methylation in fetal leukocyte DNA in 4 of these genes (OXTR, SHANK3, BCL2, and RORA) was associated with PTB in a previous study. This study evaluated DNA methylation, transcription (reverse transcription polymerase chain reaction), and translation patterns (immunostaining and Western blot) in fetal membrane from term labor (n = 14), term not in labor (TNIL; n = 29), and spontaneous preterm birth (PTB; n = 27). Statistical analysis was performed with analysis of variance; a probability value of < .05 was significant. Higher methylation of the OXTR promoter was seen in fetal membranes from PTB, compared with term labor or TNIL. No other gene showed any methylation differences among groups. Expression of OXTR was not different among groups, but the 70 kDa OXTR protein was seen only in PTB, and immunostaining was more intense in PTB amniocytes than term labor or TNIL. Among the 4 genes that were studied, fetal membranes from PTB demonstrate differences in OXTR methylation and regulation and expression, which suggest that epigenetic alteration of this gene in fetal membrane may likely be indicating an in utero programing of this gene and serve as a surrogate in a subset of PTB. The usefulness of OXTR hypermethylation as a surrogate for a link to ASD should be further evaluated in longitudinal and in vitro studies. Copyright © 2015 Elsevier Inc. All rights reserved.

Asymptotic Effect of Misspecification in the Random Part of the Multilevel Model

ERIC Educational Resources Information Center

Berkhof, Johannes; Kampen, Jarl Kennard

2004-01-01

The authors examine the asymptotic effect of omitting a random coefficient in the multilevel model and derive expressions for the change in (a) the variance components estimator and (b) the estimated variance of the fixed effects estimator. They apply the method of moments, which yields a closed form expression for the omission effect. In…

MeSH key terms for validation and annotation of gene expression clusters

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rechtsteiner, A.; Rocha, L. M.

2004-01-01

Integration of different sources of information is a great challenge for the analysis of gene expression data, and for the field of Functional Genomics in general. As the availability of numerical data from high-throughput methods increases, so does the need for technologies that assist in the validation and evaluation of the biological significance of results extracted from these data. In mRNA assaying with microarrays, for example, numerical analysis often attempts to identify clusters of co-expressed genes. The important task to find the biological significance of the results and validate them has so far mostly fallen to the biological expert whomore » had to perform this task manually. One of the most promising avenues to develop automated and integrative technology for such tasks lies in the application of modern Information Retrieval (IR) and Knowledge Management (KM) algorithms to databases with biomedical publications and data. Examples of databases available for the field are bibliographic databases c ntaining scientific publications (e.g. MEDLINE/PUBMED), databases containing sequence data (e.g. GenBank) and databases of semantic annotations (e.g. the Gene Ontology Consortium and Medical Subject Headings (MeSH)). We present here an approach that uses the MeSH terms and their concept hierarchies to validate and obtain functional information for gene expression clusters. The controlled and hierarchical MeSH vocabulary is used by the National Library of Medicine (NLM) to index all the articles cited in MEDLINE. Such indexing with a controlled vocabulary eliminates some of the ambiguity due to polysemy (terms that have multiple meanings) and synonymy (multiple terms have similar meaning) that would be encountered if terms would be extracted directly from the articles due to differing article contexts or author preferences and background. Further, the hierarchical organization of the MeSH terms can illustrate the conceptuallfunctional relationships of genes associated with MeSH terms. MeSH terms can be associated with genes through co-occurrence of these in MEDLINE citations, i.e. the genes occur in titles or abstracts and the MeSH terms are assigned by experts. To identify MeSH terms associated with a group of genes we used the tool MESHGENE developed at the Information Dynamics Lab at HP Labs (http://www-idl.hpl.hp.com/meshgene/). When presented with a list of human genes, MESHGENE uses some sophisticated techniques to search for these gene symbols in the titles and abstracts of all MEDLINE citations. MeSH terms and the number of co-occurrences can be retrieved. Gene symbols that are aliases of each other are pooled from several databases. This addresses the problem of synonymy, the fact that several symbols can refer to the same gene. MESHGENE employs some sophisticated algorithms that disregards symbols that are likely to be acronyms for other concepts than a gene. This addresses the problem of polysemy, i.e. possible multiple meanings of a gene symbol. We applied our approach to gene expression data from herpes virus infected human fibroblast cells. The data contains 12 time-points, between 1/2 hrs and 48 hrs after infection. Singular Value Decomposition was used to identify the dominant modes of expression. 75% of the variance in the expression data was captured by the first two modes, the first exhibiting a monotonly increasing expression pattern and the second a more transient pattern. Projection of the gene expression vectors onto this first two modes identified 3 statistically significant clusters of co-expressed genes. 500 genes from cluster 1 and 300 genes from clusters 2 and 3 each were uploaded to MESHGENE and the MeSH terms and co-occurrence values were retrieved. MeSH terms were also obtained for 5 groups of randomly selected genes with similar numbers of genes. The log was taken of the co-occurrence values and for each MeSH term these log co-occurrence values were summed for each group over the genes in that group. A matrix with 8 columns for the 8 groups of genes and with 14,000 rows with the MeSH terms was obtained. To analyze this association matrix we used a Latent Semantic Analysis (LSA) approach. We applied SVD to this gene-group vs. MeSH term association matrix. The first 2 modes that capture most of the variation (and therefore most times also information) in the association matrix were highly associated with MeSH terms that occurred uniquely or disproportionally in the 3 gene clusters. MeSH terms highly associated with the 5 groups of randomly selected genes were associated with the lower modes. These modes seem to just capture 'noise' in the association matrix. This result by itself is of great interest for gene expression analysis. We were able to show that the 3 clusters of genes not only separated in 'expression space' but also in the MeSH term space with which they are associated through the literature.« less

Exploring Expressive Vocabulary Variability in Two-Year-Olds: The Role of Working Memory.

PubMed

Newbury, Jayne; Klee, Thomas; Stokes, Stephanie F; Moran, Catherine

2015-12-01

This study explored whether measures of working memory ability contribute to the wide variation in 2-year-olds' expressive vocabulary skills. Seventy-nine children (aged 24-30 months) were assessed by using standardized tests of vocabulary and visual cognition, a processing speed measure, and behavioral measures of verbal working memory and phonological short-term memory. Strong correlations were observed between phonological short-term memory, verbal working memory, and expressive vocabulary. Speed of spoken word recognition showed a moderate significant correlation with expressive vocabulary. In a multivariate regression model for expressive vocabulary, the most powerful predictor was a measure of phonological short-term memory (accounting for 66% unique variance), followed by verbal working memory (6%), sex (2%), and age (1%). Processing speed did not add significant unique variance. These findings confirm previous research positing a strong role for phonological short-term memory in early expressive vocabulary acquisition. They also extend previous research in two ways. First, a unique association between verbal working memory and expressive vocabulary in 2-year-olds was observed. Second, processing speed was not a unique predictor of variance in expressive vocabulary when included alongside measures of working memory.

Design of microarray experiments for genetical genomics studies.

PubMed

Bueno Filho, Júlio S S; Gilmour, Steven G; Rosa, Guilherme J M

2006-10-01

Microarray experiments have been used recently in genetical genomics studies, as an additional tool to understand the genetic mechanisms governing variation in complex traits, such as for estimating heritabilities of mRNA transcript abundances, for mapping expression quantitative trait loci, and for inferring regulatory networks controlling gene expression. Several articles on the design of microarray experiments discuss situations in which treatment effects are assumed fixed and without any structure. In the case of two-color microarray platforms, several authors have studied reference and circular designs. Here, we discuss the optimal design of microarray experiments whose goals refer to specific genetic questions. Some examples are used to illustrate the choice of a design for comparing fixed, structured treatments, such as genotypic groups. Experiments targeting single genes or chromosomic regions (such as with transgene research) or multiple epistatic loci (such as within a selective phenotyping context) are discussed. In addition, microarray experiments in which treatments refer to families or to subjects (within family structures or complex pedigrees) are presented. In these cases treatments are more appropriately considered to be random effects, with specific covariance structures, in which the genetic goals relate to the estimation of genetic variances and the heritability of transcriptional abundances.

Use of gene expression data to determine effects on gonad phenotype in Japanese medaka after exposure to trenbolone or estradiol.

PubMed

Flynn, Kevin; Swintek, Joe; Johnson, Rodney

2013-06-01

Various aquatic bioassays using one of several fish species have been developed or are in the process of being developed by organizations like the US Environmental Protection Agency and the Office of Economic Cooperation and Development for testing potential endocrine-disrupting chemicals (EDCs). Often, these involve assessment of the gonad phenotype of individuals as a key endpoint that is inputted into a risk or hazard assessment. Typically, gonad phenotype is determined histologically, which involves specialized and time-consuming techniques. The methods detailed here utilize an entirely different methodology, reverse-transcription quantitative polymerase chain reaction, to determine the relative expression levels of 4 genes after exposure to either 17β-estradiol or 17β-trenbolone and, by extension, the effects of EDCs on the phenotypic status of the gonad. The 4 genes quantified, Sox9b, protamine, Fig1α, and ZPC1, are all involved in gonad development and maintenance in Japanese medaka (Oryzias latipes); these data were then inputted into a permutational multivariate analysis of variance to determine whether significant differences exist between treatment groups. This information in conjunction with the sexual genotype, which can be determined in medaka, can be used to determine adverse effects of exposure to EDCs in a similar fashion to the histologically determined gonad phenotype. Copyright © 2013 SETAC.

Heritability of Lumbar Trabecular Bone Mechanical Properties in Baboons

PubMed Central

Havill, L.M.; Allen, M.R.; Bredbenner, T.L.; Burr, D.B.; Nicolella, D.P.; Turner, C.H.; Warren, D.M.; Mahaney, M.C.

2010-01-01

Genetic effects on mechanical properties have been demonstrated in rodents, but not confirmed in primates. Our aim was to quantify the proportion of variation in vertebral trabecular bone mechanical properties that is due to the effects of genes. L3 vertebrae were collected from 110 females and 46 male baboons (6–32 years old) from a single extended pedigree. Cranio-caudally oriented trabecular bone cores were scanned with microCT then tested in monotonic compression to determine apparent ultimate stress, modulus, and toughness. Age and sex effects and heritability (h2) were assessed using maximum likelihood-based variance components methods. Additive effects of genes on residual trait variance were significant for ultimate stress (h2=0.58), toughness (h2=0.64), and BV/TV (h2=0.55). When BV/TV was accounted for, the residual variance in ultimate stress accounted for by the additive effects of genes was no longer significant. Toughness, however, showed evidence of a non-BV/TV-related genetic effect. Overall, maximum stress and modulus show strong genetic effects that are nearly entirely due to bone volume. Toughness shows strong genetic effects related to bone volume and shows additional genetic effects (accounting for 10% of the total trait variance) that are independent of bone volume. These results support continued use of bone volume as a focal trait to identify genes related to skeletal fragility, but also show that other focal traits related to toughness and variation in the organic component of bone matrix will enhance our ability to find additional genes that are particularly relevant to fatigue-related fractures. PMID:19900599

Early warm-rewarding parenting moderates the genetic contributions to callous-unemotional traits in childhood.

PubMed

Henry, Jeffrey; Dionne, Ginette; Viding, Essi; Vitaro, Frank; Brendgen, Mara; Tremblay, Richard E; Boivin, Michel

2018-04-23

Previous gene-environment interaction studies of CU traits have relied on the candidate gene approach, which does not account for the entire genetic load of complex phenotypes. Moreover, these studies have not examined the role of positive environmental factors such as warm/rewarding parenting. The aim of the present study was to determine whether early warm/rewarding parenting moderates the genetic contributions (i.e., heritability) to callous-unemotional (CU) traits at school age. Data were collected in a population sample of 662 twin pairs (Quebec Newborn Twin Study - QNTS). Mothers reported on their warm/rewarding parenting. Teachers assessed children's CU traits. These reports were subjected to twin modeling. Callous-unemotional traits were highly heritable, with the remaining variance accounted for by nonshared environmental factors. Warm/rewarding parenting significantly moderated the role of genes in CU traits; heritability was lower when children received high warm/rewarding parenting than when they were exposed to low warm/rewarding parenting. High warm/rewarding parenting may partly impede the genetic expression of CU traits. Developmental models of CU traits need to account for such gene-environment processes. © 2018 Association for Child and Adolescent Mental Health.

ACC oxidase and miRNA 159a, and their involvement in fresh fruit bunch yield (FFB) via sex ratio determination in oil palm.

PubMed

Somyong, Suthasinee; Poopear, Supannee; Sunner, Supreet Kaur; Wanlayaporn, Kitti; Jomchai, Nukoon; Yoocha, Thippawan; Ukoskit, Kittipat; Tangphatsornruang, Sithichoke; Tragoonrung, Somvong

2016-06-01

Oil palm (Elaeis guineesis Jacq.) is the most productive oil-bearing crop, yielding more oil per area than any other oil-bearing crops. However, there are still efforts to improve oil palm yield, in order to serve consumer and manufacturer demand. Oil palm produces female and male inflorescences in an alternating cycle. So, high sex ratio (SR), the ratio of female inflorescences to the total inflorescences, is a favorable trait in term of increasing yields in oil palm. This study aims to understand the genetic control for SR related traits, such as fresh fruit bunch yield (FFB), by characterizing genes at FFB quantitative trait loci (QTLs) on linkage 10 (chromosome 6) and linkage 15 (chromosome 10). Published oil palm sequences at the FFB QTLs were used to develop gene-based and simple sequence repeat (SSR) markers. We used the multiple QTL analysis model (MQM) to characterize the relationship of new markers with the SR traits in the oil palm population. The RNA expression of the most linked QTL genes was also evaluated in various tissues of oil palm. We identified EgACCO1 (encoding aminocyclopropane carboxylate (ACC) oxidase) at chromosome 10 and EgmiR159a (microRNA 159a) at chromosome 6 to be the most linked QTL genes or determinants for FFB yield and/or female inflorescence number with a phenotype variance explained (PVE) from 10.4 to 15 % and suggest that these play the important roles in sex determination and differentiation in oil palm. The strongest expression of EgACCO1 and the predicted precursor of EgmiR159a was found in ovaries and, to a lesser extent, fruit development. In addition, highly normalized expression of EgmiR159a was found in female flowers. In summary, the QTL analysis and the RNA expression reveal that EgACCO1 and EgmiR159a are the potential genetic factors involved in female flower determination and hence would affect yield in oil palm. However, to clarify how these genetic factors regulate female flower determination, more investigation of their down regulation or target may be essential. Additionally, if more sex determination genes controlled by plant hormones are identified, it may possible to reveal a crosstalk of sex determination genes with hormones and environment factors.

Genomic and transcriptomic predictors of triglyceride response to regular exercise

PubMed Central

Sarzynski, Mark A; Davidsen, Peter K; Sung, Yun Ju; Hesselink, Matthijs K C; Schrauwen, Patrick; Rice, Treva K; Rao, D C; Falciani, Francesco; Bouchard, Claude

2015-01-01

Aim We performed genome-wide and transcriptome-wide profiling to identify genes and single nucleotide polymorphisms (SNPs) associated with the response of triglycerides (TG) to exercise training. Methods Plasma TG levels were measured before and after a 20-week endurance training programme in 478 white participants from the HERITAGE Family Study. Illumina HumanCNV370-Quad v3.0 BeadChips were genotyped using the Illumina BeadStation 500GX platform. Affymetrix HG-U133+2 arrays were used to quantitate gene expression levels from baseline muscle biopsies of a subset of participants (N=52). Genome-wide association study (GWAS) analysis was performed using MERLIN, while transcriptomic predictor models were developed using the R-package GALGO. Results The GWAS results showed that eight SNPs were associated with TG training-response (ΔTG) at p<9.9×10−6, while another 31 SNPs showed p values <1×10−4. In multivariate regression models, the top 10 SNPs explained 32.0% of the variance in ΔTG, while conditional heritability analysis showed that four SNPs statistically accounted for all of the heritability of ΔTG. A molecular signature based on the baseline expression of 11 genes predicted 27% of ΔTG in HERITAGE, which was validated in an independent study. A composite SNP score based on the top four SNPs, each from the genomic and transcriptomic analyses, was the strongest predictor of ΔTG (R2=0.14, p=3.0×10−68). Conclusions Our results indicate that skeletal muscle transcript abundance at 11 genes and SNPs at a number of loci contribute to TG response to exercise training. Combining data from genomics and transcriptomics analyses identified a SNP-based gene signature that should be further tested in independent samples. PMID:26491034

Influence of mom and dad: quantitative genetic models for maternal effects and genomic imprinting.

PubMed

Santure, Anna W; Spencer, Hamish G

2006-08-01

The expression of an imprinted gene is dependent on the sex of the parent it was inherited from, and as a result reciprocal heterozygotes may display different phenotypes. In contrast, maternal genetic terms arise when the phenotype of an offspring is influenced by the phenotype of its mother beyond the direct inheritance of alleles. Both maternal effects and imprinting may contribute to resemblance between offspring of the same mother. We demonstrate that two standard quantitative genetic models for deriving breeding values, population variances and covariances between relatives, are not equivalent when maternal genetic effects and imprinting are acting. Maternal and imprinting effects introduce both sex-dependent and generation-dependent effects that result in differences in the way additive and dominance effects are defined for the two approaches. We use a simple example to demonstrate that both imprinting and maternal genetic effects add extra terms to covariances between relatives and that model misspecification may over- or underestimate true covariances or lead to extremely variable parameter estimation. Thus, an understanding of various forms of parental effects is essential in correctly estimating quantitative genetic variance components.

Genetic research: who is at risk for alcoholism.

PubMed

Foroud, Tatiana; Edenberg, Howard J; Crabbe, John C

2010-01-01

The National Institute on Alcohol Abuse and Alcoholism (NIAAA) was founded 40 years ago to help elucidate the biological underpinnings of alcohol dependence, including the potential contribution of genetic factors. Twin, adoption, and family studies conclusively demonstrated that genetic factors account for 50 to 60 percent of the variance in risk for developing alcoholism. Case-control studies and linkage analyses have helped identify DNA variants that contribute to increased risk, and the NIAAA-sponsored Collaborative Studies on Genetics of Alcoholism (COGA) has the expressed goal of identifying contributing genes using state-of-the-art genetic technologies. These efforts have ascertained several genes that may contribute to an increased risk of alcoholism, including certain variants encoding alcohol-metabolizing enzymes and neurotransmitter receptors. Genome-wide association studies allowing the analysis of millions of genetic markers located throughout the genome will enable discovery of further candidate genes. In addition to these human studies, genetic animal models of alcohol's effects and alcohol use have greatly advanced our understanding of the genetic basis of alcoholism, resulting in the identification of quantitative trait loci and allowing for targeted manipulation of candidate genes. Novel research approaches-for example, into epigenetic mechanisms of gene regulation-also are under way and undoubtedly will further clarify the genetic basis of alcoholism.

Putative bovine topological association domains and CTCF binding motifs can reduce the search space for causative regulatory variants of complex traits.

PubMed

Wang, Min; Hancock, Timothy P; Chamberlain, Amanda J; Vander Jagt, Christy J; Pryce, Jennie E; Cocks, Benjamin G; Goddard, Mike E; Hayes, Benjamin J

2018-05-24

Topological association domains (TADs) are chromosomal domains characterised by frequent internal DNA-DNA interactions. The transcription factor CTCF binds to conserved DNA sequence patterns called CTCF binding motifs to either prohibit or facilitate chromosomal interactions. TADs and CTCF binding motifs control gene expression, but they are not yet well defined in the bovine genome. In this paper, we sought to improve the annotation of bovine TADs and CTCF binding motifs, and assess whether the new annotation can reduce the search space for cis-regulatory variants. We used genomic synteny to map TADs and CTCF binding motifs from humans, mice, dogs and macaques to the bovine genome. We found that our mapped TADs exhibited the same hallmark properties of those sourced from experimental data, such as housekeeping genes, transfer RNA genes, CTCF binding motifs, short interspersed elements, H3K4me3 and H3K27ac. We showed that runs of genes with the same pattern of allele-specific expression (ASE) (either favouring paternal or maternal allele) were often located in the same TAD or between the same conserved CTCF binding motifs. Analyses of variance showed that when averaged across all bovine tissues tested, TADs explained 14% of ASE variation (standard deviation, SD: 0.056), while CTCF explained 27% (SD: 0.078). Furthermore, we showed that the quantitative trait loci (QTLs) associated with gene expression variation (eQTLs) or ASE variation (aseQTLs), which were identified from mRNA transcripts from 141 lactating cows' white blood and milk cells, were highly enriched at putative bovine CTCF binding motifs. The linearly-furthermost, and most-significant aseQTL and eQTL for each genic target were located within the same TAD as the gene more often than expected (Chi-Squared test P-value < 0.001). Our results suggest that genomic synteny can be used to functionally annotate conserved transcriptional components, and provides a tool to reduce the search space for causative regulatory variants in the bovine genome.

An approach to the analysis of performance of quasi-optimum digital phase-locked loops.

NASA Technical Reports Server (NTRS)

Polk, D. R.; Gupta, S. C.

1973-01-01

An approach to the analysis of performance of quasi-optimum digital phase-locked loops (DPLL's) is presented. An expression for the characteristic function of the prior error in the state estimate is derived, and from this expression an infinite dimensional equation for the prior error variance is obtained. The prior error-variance equation is a function of the communication system model and the DPLL gain and is independent of the method used to derive the DPLL gain. Two approximations are discussed for reducing the prior error-variance equation to finite dimension. The effectiveness of one approximation in analyzing DPLL performance is studied.

Nascent RNA kinetics: Transient and steady state behavior of models of transcription

NASA Astrophysics Data System (ADS)

Choubey, Sandeep

2018-02-01

Regulation of transcription is a vital process in cells, but mechanistic details of this regulation still remain elusive. The dominant approach to unravel the dynamics of transcriptional regulation is to first develop mathematical models of transcription and then experimentally test the predictions these models make for the distribution of mRNA and protein molecules at the individual cell level. However, these measurements are affected by a multitude of downstream processes which make it difficult to interpret the measurements. Recent experimental advancements allow for counting the nascent mRNA number of a gene as a function of time at the single-inglr cell level. These measurements closely reflect the dynamics of transcription. In this paper, we consider a general mechanism of transcription with stochastic initiation and deterministic elongation and probe its impact on the temporal behavior of nascent RNA levels. Using techniques from queueing theory, we derive exact analytical expressions for the mean and variance of the nascent RNA distribution as functions of time. We apply these analytical results to obtain the mean and variance of nascent RNA distribution for specific models of transcription. These models of initiation exhibit qualitatively distinct transient behaviors for both the mean and variance which further allows us to discriminate between them. Stochastic simulations confirm these results. Overall the analytical results presented here provide the necessary tools to connect mechanisms of transcription initiation to single-cell measurements of nascent RNA.

Variance-reduced simulation of lattice discrete-time Markov chains with applications in reaction networks

NASA Astrophysics Data System (ADS)

Maginnis, P. A.; West, M.; Dullerud, G. E.

2016-10-01

We propose an algorithm to accelerate Monte Carlo simulation for a broad class of stochastic processes. Specifically, the class of countable-state, discrete-time Markov chains driven by additive Poisson noise, or lattice discrete-time Markov chains. In particular, this class includes simulation of reaction networks via the tau-leaping algorithm. To produce the speedup, we simulate pairs of fair-draw trajectories that are negatively correlated. Thus, when averaged, these paths produce an unbiased Monte Carlo estimator that has reduced variance and, therefore, reduced error. Numerical results for three example systems included in this work demonstrate two to four orders of magnitude reduction of mean-square error. The numerical examples were chosen to illustrate different application areas and levels of system complexity. The areas are: gene expression (affine state-dependent rates), aerosol particle coagulation with emission and human immunodeficiency virus infection (both with nonlinear state-dependent rates). Our algorithm views the system dynamics as a ;black-box;, i.e., we only require control of pseudorandom number generator inputs. As a result, typical codes can be retrofitted with our algorithm using only minor changes. We prove several analytical results. Among these, we characterize the relationship of covariances between paths in the general nonlinear state-dependent intensity rates case, and we prove variance reduction of mean estimators in the special case of affine intensity rates.

At what scale should microarray data be analyzed?

PubMed

Huang, Shuguang; Yeo, Adeline A; Gelbert, Lawrence; Lin, Xi; Nisenbaum, Laura; Bemis, Kerry G

2004-01-01

The hybridization intensities derived from microarray experiments, for example Affymetrix's MAS5 signals, are very often transformed in one way or another before statistical models are fitted. The motivation for performing transformation is usually to satisfy the model assumptions such as normality and homogeneity in variance. Generally speaking, two types of strategies are often applied to microarray data depending on the analysis need: correlation analysis where all the gene intensities on the array are considered simultaneously, and gene-by-gene ANOVA where each gene is analyzed individually. We investigate the distributional properties of the Affymetrix GeneChip signal data under the two scenarios, focusing on the impact of analyzing the data at an inappropriate scale. The Box-Cox type of transformation is first investigated for the strategy of pooling genes. The commonly used log-transformation is particularly applied for comparison purposes. For the scenario where analysis is on a gene-by-gene basis, the model assumptions such as normality are explored. The impact of using a wrong scale is illustrated by log-transformation and quartic-root transformation. When all the genes on the array are considered together, the dependent relationship between the expression and its variation level can be satisfactorily removed by Box-Cox transformation. When genes are analyzed individually, the distributional properties of the intensities are shown to be gene dependent. Derivation and simulation show that some loss of power is incurred when a wrong scale is used, but due to the robustness of the t-test, the loss is acceptable when the fold-change is not very large.

TLR and NLRP3 inflammasome expression deregulation in macrophages of adult rats subjected to neonatal malnutrition and infected with methicillin-resistant Staphylococcus aureus.

PubMed

Gomes de Morais, Natália; Barreto da Costa, Thacianna; Bezerra de Lira, Joana Maria; da Cunha Gonçalves de Albuquerque, Suênia; Alves Pereira, Valéria Rêgo; de Paiva Cavalcanti, Milena; Machado Barbosa de Castro, Célia Maria

2017-01-01

Nutritional aggression in critical periods may lead to epigenetic changes that affect gene expression. The aim of this study was to assess the effect of neonatal malnutrition on the expression of toll-like receptor (TLR)-2, TLR-4, and NLRP3 receptors, caspase-1 enzyme, and interleukin (IL)-1 β production in macrophages infected with methicillin-resistant (MRSA) and methicillin-sensitive (MSSA) Staphylococcus aureus. Wistar rats (N = 24) were divided in two distinct groups: nourished (17% casein) and malnourished (8% casein). Four systems were established after the isolation of mononuclear cells: negative control, positive control, MRSA, and MSSA. The plates were incubated at 37°C for 24 h in humidified atmosphere and 5% carbon dioxide. Tests were performed after this period to analyze the expression of standard recognition receptors, caspase-1 enzyme, and the production of IL-1 β. Student's t test and analysis of variance were used in the statistical analysis; P < 0.05 was statistically significant. Malnutrition reduced animal growth and the expression of TLR-2, TLR-4, and NLRP3 receptors, the caspase-1 enzyme, and the IL-1 β levels in macrophages infected with lipopolysaccharides in the present study. However, the interaction between the S. aureus and the macrophages promoted greater gene expression of receptors and enzymes. The neonatal malnutrition model compromised the expression of standard recognition receptors, of the caspase-1 enzyme as well as the production of IL-1 β. However, the S. aureus and neonatal malnutrition combination led to intense transcription of such innate immunity components. Therefore, the deregulation in the expression of TLR and NLRP3 receptors and of the caspase-1 enzyme may induce extensive tissue injury and favor the permanence and spread of these bacteria, especially those that are methicillin resistant. Copyright © 2016 Elsevier Inc. All rights reserved.

Deterministic theory of Monte Carlo variance

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ueki, T.; Larsen, E.W.

1996-12-31

The theoretical estimation of variance in Monte Carlo transport simulations, particularly those using variance reduction techniques, is a substantially unsolved problem. In this paper, the authors describe a theory that predicts the variance in a variance reduction method proposed by Dwivedi. Dwivedi`s method combines the exponential transform with angular biasing. The key element of this theory is a new modified transport problem, containing the Monte Carlo weight w as an extra independent variable, which simulates Dwivedi`s Monte Carlo scheme. The (deterministic) solution of this modified transport problem yields an expression for the variance. The authors give computational results that validatemore » this theory.« less

flowVS: channel-specific variance stabilization in flow cytometry

DOE Office of Scientific and Technical Information (OSTI.GOV)

Azad, Ariful; Rajwa, Bartek; Pothen, Alex

Comparing phenotypes of heterogeneous cell populations from multiple biological conditions is at the heart of scientific discovery based on flow cytometry (FC). When the biological signal is measured by the average expression of a biomarker, standard statistical methods require that variance be approximately stabilized in populations to be compared. Since the mean and variance of a cell population are often correlated in fluorescence-based FC measurements, a preprocessing step is needed to stabilize the within-population variances.

flowVS: channel-specific variance stabilization in flow cytometry

DOE PAGES

Azad, Ariful; Rajwa, Bartek; Pothen, Alex

2016-07-28

Comparing phenotypes of heterogeneous cell populations from multiple biological conditions is at the heart of scientific discovery based on flow cytometry (FC). When the biological signal is measured by the average expression of a biomarker, standard statistical methods require that variance be approximately stabilized in populations to be compared. Since the mean and variance of a cell population are often correlated in fluorescence-based FC measurements, a preprocessing step is needed to stabilize the within-population variances.

An integrated multi-layered analysis of the metabolic networks of different tissues uncovers key genetic components of primary metabolism in maize.

PubMed

Wen, Weiwei; Jin, Min; Li, Kun; Liu, Haijun; Xiao, Yingjie; Zhao, Mingchao; Alseekh, Saleh; Li, Wenqiang; de Abreu E Lima, Francisco; Brotman, Yariv; Willmitzer, Lothar; Fernie, Alisdair R; Yan, Jianbing

2018-03-01

Primary metabolism plays a pivotal role in normal plant growth, development and reproduction. As maize is a major crop worldwide, the primary metabolites produced by maize plants are of immense importance from both calorific and nutritional perspectives. Here a genome-wide association study (GWAS) of 61 primary metabolites using a maize association panel containing 513 inbred lines identified 153 significant loci associated with the level of these metabolites in four independent tissues. The genome-wide expression level of 760 genes was also linked with metabolite levels within the same tissue. On average, the genetic variants at each locus or transcriptional variance of each gene identified here were estimated to have a minor effect (4.4-7.8%) on primary metabolic variation. Thirty-six loci or genes were prioritized as being worthy of future investigation, either with regard to functional characterization or for their utility for genetic improvement. This target list includes the well-known opaque 2 (O2) and lkr/sdh genes as well as many less well-characterized genes. During our investigation of these 36 loci, we analyzed the genetic components and variations underlying the trehalose, aspartate and aromatic amino acid pathways, thereby functionally characterizing four genes involved in primary metabolism in maize. © 2018 The Authors The Plant Journal © 2018 John Wiley & Sons Ltd.

Triiodothyronine modulates the expression of leptin and adiponectin in 3T3-L1 adipocytes

PubMed Central

de Oliveira, Miriane; Síbio, Maria Teresa De; Olimpio, Regiane Marques Castro; Moretto, Fernanda Cristina Fontes; Luvizotto, Renata de Azevedo Melo; Nogueira, Celia Regina

2015-01-01

Objective To study the effect of different doses of triiodothyronine on gene expression of the adipokines leptin and adiponectin, at different times, and to evaluate the difference in expression between the two adipokines in each group. Methods 3T3-L1 adipocytes were incubated with triiodothyronine at physiological dose (10nM) and supraphysiological doses (100nM or 1,000nM), or without triiodothyronine (control, C) for 0.5, 6, or 24 hours. Leptin and adiponectin mRNA was detected using real-time polymerase chain reaction (RT-PCR). One-way analyses of variance, Tukey’s test or Student’s t test, were used to analyze data, and significance level was set at 5%. Results Leptin levels decreased in the 1,000nM-dose group after 0.5 hour. Adiponectin levels dropped in the 10nM-dose group, but increased at the 100nM dose. After 6 hours, both genes were suppressed in all hormone concentrations. After 24 hours, leptin levels increased at 10, 100 and 1,000nM groups as compared to the control group; and adiponectin levels increased only in the 100nM group as compared to the control group. Conclusion These results demonstrated fast actions of triiodothyronine on the leptin and adiponectin expression, starting at 0.5 hour, at a dose of 1,000nM for leptin and 100nM for adiponectin. Triiodothyronine stimulated or inhibited the expression of adipokines in adipocytes at different times and doses which may be useful to assist in the treatment of obesity, assuming that leptin is increased and adiponectin is decreased, in obesity cases. PMID:25993072

Triiodothyronine modulates the expression of leptin and adiponectin in 3T3-L1 adipocytes.

PubMed

Oliveira, Miriane de; de Síbio, Maria Teresa; Olimpio, Regiane Marques Castro; Moretto, Fernanda Cristina Fontes; Luvizotto, Renata de Azevedo Melo; Nogueira, Celia Regina

2015-01-01

To study the effect of different doses of triiodothyronine on gene expression of the adipokines leptin and adiponectin, at different times, and to evaluate the difference in expression between the two adipokines in each group. 3T3-L1 adipocytes were incubated with triiodothyronine at physiological dose (10nM) and supraphysiological doses (100nM or 1,000nM), or without triiodothyronine (control, C) for 0.5, 6, or 24 hours. Leptin and adiponectin mRNA was detected using real-time polymerase chain reaction (RT-PCR). One-way analyses of variance, Tukey's test or Student's t test, were used to analyze data, and significance level was set at 5%. Leptin levels decreased in the 1,000nM-dose group after 0.5 hour. Adiponectin levels dropped in the 10nM-dose group, but increased at the 100nM dose. After 6 hours, both genes were suppressed in all hormone concentrations. After 24 hours, leptin levels increased at 10, 100 and 1,000nM groups as compared to the control group; and adiponectin levels increased only in the 100nM group as compared to the control group. These results demonstrated fast actions of triiodothyronine on the leptin and adiponectin expression, starting at 0.5 hour, at a dose of 1,000nM for leptin and 100nM for adiponectin. Triiodothyronine stimulated or inhibited the expression of adipokines in adipocytes at different times and doses which may be useful to assist in the treatment of obesity, assuming that leptin is increased and adiponectin is decreased, in obesity cases.

Metabolic surgery and intestinal gene expression: Digestive tract and diabetes evolution considerations

PubMed Central

Rodrigues, Marcos Ricardo da Silva; Santo, Marco Aurelio; Favero, Giovani Marino; Vieira, Elaine Cristina; Artoni, Roberto Ferreira; Nogaroto, Viviane; de Moura, Egberto Gaspar; Lisboa, Patricia; Milleo, Fabio Quirillo

2015-01-01

AIM: To investigate the effects of bariatric surgery on metabolic parameters, incretin hormone secretion, and duodenal and ileal mucosal gene expression. METHODS: Nine patients with type 2 diabetes mellitus (T2DM), chronic serum hyperglycemia for more than 2 years, and a body mass index (BMI) of 30-35 kg/m2 underwent metabolic surgery sleeve gastrectomy with transit bipartition between May 2011 and December 2011. Blood samples were collected pre and 3, 6 and 12 mo postsurgery. Duodenal and ileal mucosa samples were collected pre- and 3 mo postsurgery. Pre- and postoperative blood samples were collected in the fasting state before ingestion of a standard meal (520 kcal) and again 30, 60, 90, and 120 min after the meal to determine hemoglobin A1c (HbA1c) levels and the lipid profile, which consisted of triglyceride and total cholesterol levels. Intestinal gene expression of p53 and transforming growth factor (TGF)-β was analyzed using quantitative reverse-transcription PCR. Gastric inhibitory polypeptide (GIP) and glucagon-like peptide-1 (GLP-1) were quantified using the enzyme-linked immunoassay method and analyzed pre- and postoperatively. Student’s t test or repeated measurements analysis of variance with Bonferroni corrections were performed as appropriate. RESULTS: BMI values decreased by 15.7% within the initial 3 mo after surgery (31.29 ± 0.73 vs 26.398 ± 0.68, P < 0.05) and then stabilized at 22% at 6 mo postoperative, resulting in similar values 12 mo postoperatively (20-25 kg/m2). All of the patients experienced improved T2DM, with 7 patients (78%) achieving complete remission (HbA1c < 6.5%), and 2 patients (22%) achieving improved diabetes (HbA1c < 7.0% with or without the use of oral hypoglycemic agents). At 3 mo postoperatively, fasting plasma glucose had also decreased (59%) (269.55 ± 18.24 mg/dL vs 100.77 ± 3.13 mg/dL, P < 0.05) with no further significant changes at 6 or 12 mo postoperatively. In the first month postoperatively, there was a complete withdrawal of hypoglycemic medications in all patients, who were taking at least 2 hypoglycemic drugs preoperatively. GLP-1 levels significantly increased after surgery (149.96 ± 31.25 vs 220.23 ± 27.55) (P < 0.05), while GIP levels decreased but not significantly. p53 gene expression significantly increased in the duodenal mucosa (P < 0.05, 2.06 fold) whereas the tumor growth factor-β gene expression significantly increased (P < 0.05, 2.52 fold) in the ileal mucosa after surgery. CONCLUSION: Metabolic surgery ameliorated diabetes in all of the patients, accompanied by increased anti-proliferative intestinal gene expression in non-excluded segments of the intestine. PMID:26078577

QNB: differential RNA methylation analysis for count-based small-sample sequencing data with a quad-negative binomial model.

PubMed

Liu, Lian; Zhang, Shao-Wu; Huang, Yufei; Meng, Jia

2017-08-31

As a newly emerged research area, RNA epigenetics has drawn increasing attention recently for the participation of RNA methylation and other modifications in a number of crucial biological processes. Thanks to high throughput sequencing techniques, such as, MeRIP-Seq, transcriptome-wide RNA methylation profile is now available in the form of count-based data, with which it is often of interests to study the dynamics at epitranscriptomic layer. However, the sample size of RNA methylation experiment is usually very small due to its costs; and additionally, there usually exist a large number of genes whose methylation level cannot be accurately estimated due to their low expression level, making differential RNA methylation analysis a difficult task. We present QNB, a statistical approach for differential RNA methylation analysis with count-based small-sample sequencing data. Compared with previous approaches such as DRME model based on a statistical test covering the IP samples only with 2 negative binomial distributions, QNB is based on 4 independent negative binomial distributions with their variances and means linked by local regressions, and in the way, the input control samples are also properly taken care of. In addition, different from DRME approach, which relies only the input control sample only for estimating the background, QNB uses a more robust estimator for gene expression by combining information from both input and IP samples, which could largely improve the testing performance for very lowly expressed genes. QNB showed improved performance on both simulated and real MeRIP-Seq datasets when compared with competing algorithms. And the QNB model is also applicable to other datasets related RNA modifications, including but not limited to RNA bisulfite sequencing, m 1 A-Seq, Par-CLIP, RIP-Seq, etc.

In Search of 'Birth Month Genes': Using Existing Data Repositories to Locate Genes Underlying Birth Month-Disease Relationships.

PubMed

Boland, Mary Regina; Tatonetti, Nicholas P

2016-01-01

Prenatal and perinatal exposures vary seasonally (e.g., sunlight, allergens) and many diseases are linked with variance in exposure. Epidemiologists often measure these changes using birth month as a proxy for seasonal variance. Likewise, Genome-Wide Association Studies have associated or implicated these same diseases with many genes. Both disparate data types (epidemiological and genetic) can provide key insights into the underlying disease biology. We developed an algorithm that links 1) epidemiological data from birth month studies with 2) genetic data from published gene-disease association studies. Our framework uses existing data repositories - PubMed, DisGeNET and Gene Ontology - to produce a bipartite network that connects enriched seasonally varying biofactorss with birth month dependent diseases (BMDDs) through their overlapping developmental gene sets. As a proof-of-concept, we investigate 7 known BMDDs and highlight three important biological networks revealed by our algorithm and explore some interesting genetic mechanisms potentially responsible for the seasonal contribution to BMDDs.

Stress, and pathogen response gene expression in modeled microgravity

NASA Technical Reports Server (NTRS)

Sundaresan, Alamelu; Pellis, Neal R.

2006-01-01

Purpose: Immune suppression in microgravity has been well documented. With the advent of human exploration and long-term space travel, the immune system of the astronaut must be optimally maintained. It is important to investigate the expression patterns of cytokine genes, because they are directly related to immune response. Heat shock proteins (HSPs), also called stress proteins, are a group of proteins that are present in the cells of every life form. These proteins are induced when a cell responds to stressors such as heat, cold and oxygen deprivation. Microgravity is another stressor that may regulate HSPs. Heat shock proteins trigger immune response through activities that occur both inside the cell (intracellular) and outside the cell (extracellular). Knowledge about these two gene groups could lead to establishment of a blueprint of the immune response and adaptation-related genes in the microgravity environment. Methods: Human peripheral blood cells were cultured in 1g (T flask) and modeled microgravity (MMG, rotating-wall vessel) for 24 and 72 hours. Cell samples were collected and subjected to gene array analysis using the Affymetrix HG_U95 array. Data was collected and subjected to a two-way analysis of variance. The genes related to immune and stress responses were analyzed. Results and Conclusions: HSP70 was up-regulated by more than two fold in microgravity culture, while HSP90 was significantly down-regulated. HSP70 is not typically expressed in all kinds of cells, but it is expressed at high levels in stress conditions. HSP70 participates in translation, protein translocation, proteolysis and protein folding, suppressing aggregation and reactivating denatured proteins. Increased serum HSP70 levels correlate with a better outcome for heat-stroke or severe trauma patients. At the same time, elevated serum levels of HSP70 have been detected in patients with peripheral or renal vascular disease. HSP90 has been identified in the cytosol, nucleus and endoplasmic reticulum, and exists in many tissue types. HSP90 associates with actin filaments in certain conditions and aids cell motility. The down-regulation of HSP90 could lead to deleterious effects in the lymphocytes, thereby contributing to suppressed immune function in microgravity. Interleukins such as IL 1 alpha, IL11 receptor chain alpha, IL7R, and IL4R were significantly down regulated in modeled microgravity. Further analysis of the genes involved in immune response at the protein level may provide a basis for prophylactic and countermeasure strategies to augment the human immune system for space exploration.

Heart ABCA1 and PPAR- α Genes Expression Responses in Male rats: Effects of High Intensity Treadmill Running Training and Aqueous Extraction of Black Crataegus-Pentaegyna.

PubMed

Ghanbari-Niaki, Abbass; Ghanbari-Abarghooi, Safieyh; Rahbarizadeh, Fatemeh; Zare-Kookandeh, Navabeh; Gholizadeh, Monireh; Roudbari, Fatemeh; Zare-Kookandeh, Asghar

2013-11-01

Heart as a high metabolic and aerobic tissue is consuming lipid as a fuel for its energy provision at rest during light and moderate exercise, except when lactate level is higher in blood circulation. It has been shown that any type of regular exercise and crataegus species would improve cardiovascular function and minimizes several risk factors via stimulating lipid metabolism by acting on enzymes and genes expression such as ABCA1 and PPAR α which are involving in this process. Twenty Wistar male rats (4-6 weeks old, 140-173 g weight) were used. Animals were randomly classified into training (n = 10) and control (n = 10) groups and then divided into saline-control (SC), saline-training (ST), Crataegus-Pentaegyna -control (CPC), and Crataegus-Pentaegyna -training (CPT) groups. Training groups have performed a high-intensity running program (at 34 m/min (0% grade), 60 min/day, 5 days/week) on a motor-driven treadmill for eight weeks. Animals were orally fed with Crataegus-Pentaegyna extraction (500mg/kg) and saline solution for six weeks. Seventy- two hours after the last training session, rats were sacrificed, hearts were excised, cleaned and immediately frozen in liquid nitrogen and stored at -80 °C until RNA extraction. Plasma also was collected for plasma variable measurements. Statistical analysis was performed using a two way analysis of variance, and significance was accepted at P < 0.05. A non-significant (P < 0.4, P < 0.79, respectively) increase in ABCA1 and PPAR α genes expression was accompanied by a significant (P < 0.01, P < 0.04, P < 0.04, respectively) reduction in TC, TG, and VLDL-C levels in Crataegus-Pentaegyna groups. Our findings show that a high intensity treadmill running was able to express ABCA1 and PPAR α in rat heart. Data also possibly indicate that the Crataeguse-Pentaegyna supplementation solely could mimic training effect on the mentioned genes and lipid profiles via different mechanism(s).

Heart ABCA1 and PPAR- α Genes Expression Responses in Male rats: Effects of High Intensity Treadmill Running Training and Aqueous Extraction of Black Crataegus-Pentaegyna

PubMed Central

Ghanbari-Niaki, Abbass; Ghanbari-Abarghooi, Safieyh; Rahbarizadeh, Fatemeh; Zare-Kookandeh, Navabeh; Gholizadeh, Monireh; Roudbari, Fatemeh; Zare-Kookandeh, Asghar

2013-01-01

Introduction: Heart as a high metabolic and aerobic tissue is consuming lipid as a fuel for its energy provision at rest during light and moderate exercise, except when lactate level is higher in blood circulation. It has been shown that any type of regular exercise and crataegus species would improve cardiovascular function and minimizes several risk factors via stimulating lipid metabolism by acting on enzymes and genes expression such as ABCA1 and PPAR α which are involving in this process. Materials and Methods: Twenty Wistar male rats (4-6 weeks old, 140-173 g weight) were used. Animals were randomly classified into training (n = 10) and control (n = 10) groups and then divided into saline-control (SC), saline-training (ST), Crataegus-Pentaegyna -control (CPC), and Crataegus-Pentaegyna -training (CPT) groups. Training groups have performed a high-intensity running program (at 34 m/min (0% grade), 60 min/day, 5 days/week) on a motor-driven treadmill for eight weeks. Animals were orally fed with Crataegus-Pentaegyna extraction (500mg/kg) and saline solution for six weeks. Seventy- two hours after the last training session, rats were sacrificed, hearts were excised, cleaned and immediately frozen in liquid nitrogen and stored at -80 °C until RNA extraction. Plasma also was collected for plasma variable measurements. Statistical analysis was performed using a two way analysis of variance, and significance was accepted at P < 0.05. Results: A non-significant (P < 0.4, P < 0.79, respectively) increase in ABCA1 and PPAR α genes expression was accompanied by a significant (P < 0.01, P < 0.04, P < 0.04, respectively) reduction in TC, TG, and VLDL-C levels in Crataegus-Pentaegyna groups. Conclusions: Our findings show that a high intensity treadmill running was able to express ABCA1 and PPAR α in rat heart. Data also possibly indicate that the Crataeguse-Pentaegyna supplementation solely could mimic training effect on the mentioned genes and lipid profiles via different mechanism(s). PMID:25478513

Genetic analyses using GGE model and a mixed linear model approach, and stability analyses using AMMI bi-plot for late-maturity alpha-amylase activity in bread wheat genotypes.

PubMed

Rasul, Golam; Glover, Karl D; Krishnan, Padmanaban G; Wu, Jixiang; Berzonsky, William A; Fofana, Bourlaye

2017-06-01

Low falling number and discounting grain when it is downgraded in class are the consequences of excessive late-maturity α-amylase activity (LMAA) in bread wheat (Triticum aestivum L.). Grain expressing high LMAA produces poorer quality bread products. To effectively breed for low LMAA, it is necessary to understand what genes control it and how they are expressed, particularly when genotypes are grown in different environments. In this study, an International Collection (IC) of 18 spring wheat genotypes and another set of 15 spring wheat cultivars adapted to South Dakota (SD), USA were assessed to characterize the genetic component of LMAA over 5 and 13 environments, respectively. The data were analysed using a GGE model with a mixed linear model approach and stability analysis was presented using an AMMI bi-plot on R software. All estimated variance components and their proportions to the total phenotypic variance were highly significant for both sets of genotypes, which were validated by the AMMI model analysis. Broad-sense heritability for LMAA was higher in SD adapted cultivars (53%) compared to that in IC (49%). Significant genetic effects and stability analyses showed some genotypes, e.g. 'Lancer', 'Chester' and 'LoSprout' from IC, and 'Alsen', 'Traverse' and 'Forefront' from SD cultivars could be used as parents to develop new cultivars expressing low levels of LMAA. Stability analysis using an AMMI bi-plot revealed that 'Chester', 'Lancer' and 'Advance' were the most stable across environments, while in contrast, 'Kinsman', 'Lerma52' and 'Traverse' exhibited the lowest stability for LMAA across environments.

Computing molecular fluctuations in biochemical reaction systems based on a mechanistic, statistical theory of irreversible processes.

PubMed

Kulasiri, Don

2011-01-01

We discuss the quantification of molecular fluctuations in the biochemical reaction systems within the context of intracellular processes associated with gene expression. We take the molecular reactions pertaining to circadian rhythms to develop models of molecular fluctuations in this chapter. There are a significant number of studies on stochastic fluctuations in intracellular genetic regulatory networks based on single cell-level experiments. In order to understand the fluctuations associated with the gene expression in circadian rhythm networks, it is important to model the interactions of transcriptional factors with the E-boxes in the promoter regions of some of the genes. The pertinent aspects of a near-equilibrium theory that would integrate the thermodynamical and particle dynamic characteristics of intracellular molecular fluctuations would be discussed, and the theory is extended by using the theory of stochastic differential equations. We then model the fluctuations associated with the promoter regions using general mathematical settings. We implemented ubiquitous Gillespie's algorithms, which are used to simulate stochasticity in biochemical networks, for each of the motifs. Both the theory and the Gillespie's algorithms gave the same results in terms of the time evolution of means and variances of molecular numbers. As biochemical reactions occur far away from equilibrium-hence the use of the Gillespie algorithm-these results suggest that the near-equilibrium theory should be a good approximation for some of the biochemical reactions. © 2011 Elsevier Inc. All rights reserved.

Influence of A-21T and C-262T genetic polymorphisms at the promoter region of the catalase (CAT) on gene expression.

PubMed

Saify, Khyber; Saadat, Iraj; Saadat, Mostafa

2016-09-01

Catalase (CAT, OMIM: 115500) is one of the major antioxidant enzymes, which plays an important role in the clearance of reactive oxygen species. Three genetic polymorphisms of A-21T (rs7943316), C-262T (rs1001179), and C-844T (rs769214) in the promoter region of the CAT have been reported. It has been suggested that these polymorphisms may alter the recognition sites of transcriptional factors, therefore it might be concluded that these polymorphisms may alter the expression levels of the gene. The aim of the present study is to evaluate the associations between these genetic variations and the CAT mRNA levels in human peripheral blood cells. The present study consisted of 47 healthy students of Shiraz University (south-west Iran). Genotypes of the CAT polymorphisms were determined by PCR based method. The quantitative CAT mRNA expression levels were investigated using quantitative real-time PCR. Analysis of variance revealed significant differences between the study genotypes (For A-21T polymorphism: F = 7.45; df = 2, 44; P = 0.002; For C-262T polymorphism: F = 15.17; df = 2, 44; P < 0.001). The studied polymorphisms showed linkage disequilibrium (D' = 1.0, r 2  = 0.1813, χ 2  = 17.03, P < 0.0001). The mRNA levels of CAT in the AC/TT, TC/TC, TC/TT, and TC/TC diplotypes significantly were higher than the mRNA levels in AC/AC diplotype. There was a significant difference between the study genotypes (F = 9.24; df = 5, 41; P < 0.001). The TC/TC and TT/TT diplotypes showed about 2 and 4 folds CAT mRNA levels compared with the AC/AC diplotype. The present findings indicated that these polymorphisms were significantly associated with the gene expression.

Genome-scale cluster analysis of replicated microarrays using shrinkage correlation coefficient.

PubMed

Yao, Jianchao; Chang, Chunqi; Salmi, Mari L; Hung, Yeung Sam; Loraine, Ann; Roux, Stanley J

2008-06-18

Currently, clustering with some form of correlation coefficient as the gene similarity metric has become a popular method for profiling genomic data. The Pearson correlation coefficient and the standard deviation (SD)-weighted correlation coefficient are the two most widely-used correlations as the similarity metrics in clustering microarray data. However, these two correlations are not optimal for analyzing replicated microarray data generated by most laboratories. An effective correlation coefficient is needed to provide statistically sufficient analysis of replicated microarray data. In this study, we describe a novel correlation coefficient, shrinkage correlation coefficient (SCC), that fully exploits the similarity between the replicated microarray experimental samples. The methodology considers both the number of replicates and the variance within each experimental group in clustering expression data, and provides a robust statistical estimation of the error of replicated microarray data. The value of SCC is revealed by its comparison with two other correlation coefficients that are currently the most widely-used (Pearson correlation coefficient and SD-weighted correlation coefficient) using statistical measures on both synthetic expression data as well as real gene expression data from Saccharomyces cerevisiae. Two leading clustering methods, hierarchical and k-means clustering were applied for the comparison. The comparison indicated that using SCC achieves better clustering performance. Applying SCC-based hierarchical clustering to the replicated microarray data obtained from germinating spores of the fern Ceratopteris richardii, we discovered two clusters of genes with shared expression patterns during spore germination. Functional analysis suggested that some of the genetic mechanisms that control germination in such diverse plant lineages as mosses and angiosperms are also conserved among ferns. This study shows that SCC is an alternative to the Pearson correlation coefficient and the SD-weighted correlation coefficient, and is particularly useful for clustering replicated microarray data. This computational approach should be generally useful for proteomic data or other high-throughput analysis methodology.

A GWAS meta-analysis from 5 population-based cohorts implicates ion channel genes in the pathogenesis of irritable bowel syndrome.

PubMed

Bonfiglio, F; Henström, M; Nag, A; Hadizadeh, F; Zheng, T; Cenit, M C; Tigchelaar, E; Williams, F; Reznichenko, A; Ek, W E; Rivera, N V; Homuth, G; Aghdassi, A A; Kacprowski, T; Männikkö, M; Karhunen, V; Bujanda, L; Rafter, J; Wijmenga, C; Ronkainen, J; Hysi, P; Zhernakova, A; D'Amato, M

2018-04-19

Irritable bowel syndrome (IBS) shows genetic predisposition, however, large-scale, powered gene mapping studies are lacking. We sought to exploit existing genetic (genotype) and epidemiological (questionnaire) data from a series of population-based cohorts for IBS genome-wide association studies (GWAS) and their meta-analysis. Based on questionnaire data compatible with Rome III Criteria, we identified a total of 1335 IBS cases and 9768 asymptomatic individuals from 5 independent European genotyped cohorts. Individual GWAS were carried out with sex-adjusted logistic regression under an additive model, followed by meta-analysis using the inverse variance method. Functional annotation of significant results was obtained via a computational pipeline exploiting ontology and interaction networks, and tissue-specific and gene set enrichment analyses. Suggestive GWAS signals (P ≤ 5.0 × 10 -6 ) were detected for 7 genomic regions, harboring 64 gene candidates to affect IBS risk via functional or expression changes. Functional annotation of this gene set convincingly (best FDR-corrected P = 3.1 × 10 -10 ) highlighted regulation of ion channel activity as the most plausible pathway affecting IBS risk. Our results confirm the feasibility of population-based studies for gene-discovery efforts in IBS, identify risk genes and loci to be prioritized in independent follow-ups, and pinpoint ion channels as important players and potential therapeutic targets warranting further investigation. © 2018 John Wiley & Sons Ltd.

Distinct promoter activation mechanisms modulate noise-driven HIV gene expression

NASA Astrophysics Data System (ADS)

Chavali, Arvind K.; Wong, Victor C.; Miller-Jensen, Kathryn

2015-12-01

Latent human immunodeficiency virus (HIV) infections occur when the virus occupies a transcriptionally silent but reversible state, presenting a major obstacle to cure. There is experimental evidence that random fluctuations in gene expression, when coupled to the strong positive feedback encoded by the HIV genetic circuit, act as a ‘molecular switch’ controlling cell fate, i.e., viral replication versus latency. Here, we implemented a stochastic computational modeling approach to explore how different promoter activation mechanisms in the presence of positive feedback would affect noise-driven activation from latency. We modeled the HIV promoter as existing in one, two, or three states that are representative of increasingly complex mechanisms of promoter repression underlying latency. We demonstrate that two-state and three-state models are associated with greater variability in noisy activation behaviors, and we find that Fano factor (defined as variance over mean) proves to be a useful noise metric to compare variability across model structures and parameter values. Finally, we show how three-state promoter models can be used to qualitatively describe complex reactivation phenotypes in response to therapeutic perturbations that we observe experimentally. Ultimately, our analysis suggests that multi-state models more accurately reflect observed heterogeneous reactivation and may be better suited to evaluate how noise affects viral clearance.

Synthetic data sets for the identification of key ingredients for RNA-seq differential analysis.

PubMed

Rigaill, Guillem; Balzergue, Sandrine; Brunaud, Véronique; Blondet, Eddy; Rau, Andrea; Rogier, Odile; Caius, José; Maugis-Rabusseau, Cathy; Soubigou-Taconnat, Ludivine; Aubourg, Sébastien; Lurin, Claire; Martin-Magniette, Marie-Laure; Delannoy, Etienne

2018-01-01

Numerous statistical pipelines are now available for the differential analysis of gene expression measured with RNA-sequencing technology. Most of them are based on similar statistical frameworks after normalization, differing primarily in the choice of data distribution, mean and variance estimation strategy and data filtering. We propose an evaluation of the impact of these choices when few biological replicates are available through the use of synthetic data sets. This framework is based on real data sets and allows the exploration of various scenarios differing in the proportion of non-differentially expressed genes. Hence, it provides an evaluation of the key ingredients of the differential analysis, free of the biases associated with the simulation of data using parametric models. Our results show the relevance of a proper modeling of the mean by using linear or generalized linear modeling. Once the mean is properly modeled, the impact of the other parameters on the performance of the test is much less important. Finally, we propose to use the simple visualization of the raw P-value histogram as a practical evaluation criterion of the performance of differential analysis methods on real data sets. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Study of 300,486 individuals identifies 148 independent genetic loci influencing general cognitive function.

PubMed

Davies, Gail; Lam, Max; Harris, Sarah E; Trampush, Joey W; Luciano, Michelle; Hill, W David; Hagenaars, Saskia P; Ritchie, Stuart J; Marioni, Riccardo E; Fawns-Ritchie, Chloe; Liewald, David C M; Okely, Judith A; Ahola-Olli, Ari V; Barnes, Catriona L K; Bertram, Lars; Bis, Joshua C; Burdick, Katherine E; Christoforou, Andrea; DeRosse, Pamela; Djurovic, Srdjan; Espeseth, Thomas; Giakoumaki, Stella; Giddaluru, Sudheer; Gustavson, Daniel E; Hayward, Caroline; Hofer, Edith; Ikram, M Arfan; Karlsson, Robert; Knowles, Emma; Lahti, Jari; Leber, Markus; Li, Shuo; Mather, Karen A; Melle, Ingrid; Morris, Derek; Oldmeadow, Christopher; Palviainen, Teemu; Payton, Antony; Pazoki, Raha; Petrovic, Katja; Reynolds, Chandra A; Sargurupremraj, Muralidharan; Scholz, Markus; Smith, Jennifer A; Smith, Albert V; Terzikhan, Natalie; Thalamuthu, Anbupalam; Trompet, Stella; van der Lee, Sven J; Ware, Erin B; Windham, B Gwen; Wright, Margaret J; Yang, Jingyun; Yu, Jin; Ames, David; Amin, Najaf; Amouyel, Philippe; Andreassen, Ole A; Armstrong, Nicola J; Assareh, Amelia A; Attia, John R; Attix, Deborah; Avramopoulos, Dimitrios; Bennett, David A; Böhmer, Anne C; Boyle, Patricia A; Brodaty, Henry; Campbell, Harry; Cannon, Tyrone D; Cirulli, Elizabeth T; Congdon, Eliza; Conley, Emily Drabant; Corley, Janie; Cox, Simon R; Dale, Anders M; Dehghan, Abbas; Dick, Danielle; Dickinson, Dwight; Eriksson, Johan G; Evangelou, Evangelos; Faul, Jessica D; Ford, Ian; Freimer, Nelson A; Gao, He; Giegling, Ina; Gillespie, Nathan A; Gordon, Scott D; Gottesman, Rebecca F; Griswold, Michael E; Gudnason, Vilmundur; Harris, Tamara B; Hartmann, Annette M; Hatzimanolis, Alex; Heiss, Gerardo; Holliday, Elizabeth G; Joshi, Peter K; Kähönen, Mika; Kardia, Sharon L R; Karlsson, Ida; Kleineidam, Luca; Knopman, David S; Kochan, Nicole A; Konte, Bettina; Kwok, John B; Le Hellard, Stephanie; Lee, Teresa; Lehtimäki, Terho; Li, Shu-Chen; Liu, Tian; Koini, Marisa; London, Edythe; Longstreth, Will T; Lopez, Oscar L; Loukola, Anu; Luck, Tobias; Lundervold, Astri J; Lundquist, Anders; Lyytikäinen, Leo-Pekka; Martin, Nicholas G; Montgomery, Grant W; Murray, Alison D; Need, Anna C; Noordam, Raymond; Nyberg, Lars; Ollier, William; Papenberg, Goran; Pattie, Alison; Polasek, Ozren; Poldrack, Russell A; Psaty, Bruce M; Reppermund, Simone; Riedel-Heller, Steffi G; Rose, Richard J; Rotter, Jerome I; Roussos, Panos; Rovio, Suvi P; Saba, Yasaman; Sabb, Fred W; Sachdev, Perminder S; Satizabal, Claudia L; Schmid, Matthias; Scott, Rodney J; Scult, Matthew A; Simino, Jeannette; Slagboom, P Eline; Smyrnis, Nikolaos; Soumaré, Aïcha; Stefanis, Nikos C; Stott, David J; Straub, Richard E; Sundet, Kjetil; Taylor, Adele M; Taylor, Kent D; Tzoulaki, Ioanna; Tzourio, Christophe; Uitterlinden, André; Vitart, Veronique; Voineskos, Aristotle N; Kaprio, Jaakko; Wagner, Michael; Wagner, Holger; Weinhold, Leonie; Wen, K Hoyan; Widen, Elisabeth; Yang, Qiong; Zhao, Wei; Adams, Hieab H H; Arking, Dan E; Bilder, Robert M; Bitsios, Panos; Boerwinkle, Eric; Chiba-Falek, Ornit; Corvin, Aiden; De Jager, Philip L; Debette, Stéphanie; Donohoe, Gary; Elliott, Paul; Fitzpatrick, Annette L; Gill, Michael; Glahn, David C; Hägg, Sara; Hansell, Narelle K; Hariri, Ahmad R; Ikram, M Kamran; Jukema, J Wouter; Vuoksimaa, Eero; Keller, Matthew C; Kremen, William S; Launer, Lenore; Lindenberger, Ulman; Palotie, Aarno; Pedersen, Nancy L; Pendleton, Neil; Porteous, David J; Räikkönen, Katri; Raitakari, Olli T; Ramirez, Alfredo; Reinvang, Ivar; Rudan, Igor; Dan Rujescu; Schmidt, Reinhold; Schmidt, Helena; Schofield, Peter W; Schofield, Peter R; Starr, John M; Steen, Vidar M; Trollor, Julian N; Turner, Steven T; Van Duijn, Cornelia M; Villringer, Arno; Weinberger, Daniel R; Weir, David R; Wilson, James F; Malhotra, Anil; McIntosh, Andrew M; Gale, Catharine R; Seshadri, Sudha; Mosley, Thomas H; Bressler, Jan; Lencz, Todd; Deary, Ian J

2018-05-29

General cognitive function is a prominent and relatively stable human trait that is associated with many important life outcomes. We combine cognitive and genetic data from the CHARGE and COGENT consortia, and UK Biobank (total N = 300,486; age 16-102) and find 148 genome-wide significant independent loci (P < 5 × 10 -8 ) associated with general cognitive function. Within the novel genetic loci are variants associated with neurodegenerative and neurodevelopmental disorders, physical and psychiatric illnesses, and brain structure. Gene-based analyses find 709 genes associated with general cognitive function. Expression levels across the cortex are associated with general cognitive function. Using polygenic scores, up to 4.3% of variance in general cognitive function is predicted in independent samples. We detect significant genetic overlap between general cognitive function, reaction time, and many health variables including eyesight, hypertension, and longevity. In conclusion we identify novel genetic loci and pathways contributing to the heritability of general cognitive function.

Ranking and characterization of established BMI and lipid associated loci as candidates for gene-environment interactions

PubMed Central

Luan, Jian'an; Mihailov, Evelin; Metspalu, Andres; Forouhi, Nita G.; Magnusson, Patrik K. E.; Pedersen, Nancy L.; Hallmans, Göran; Chu, Audrey Y.; Justice, Anne E.; Graff, Mariaelisa; Rose, Lynda M.; Langenberg, Claudia; Cupples, L. Adrienne; Ridker, Paul M.; Ong, Ken K.; Loos, Ruth J. F.; Chasman, Daniel I.; Ingelsson, Erik; Kilpeläinen, Tuomas O.; Scott, Robert A.; Mägi, Reedik

2017-01-01

Phenotypic variance heterogeneity across genotypes at a single nucleotide polymorphism (SNP) may reflect underlying gene-environment (G×E) or gene-gene interactions. We modeled variance heterogeneity for blood lipids and BMI in up to 44,211 participants and investigated relationships between variance effects (Pv), G×E interaction effects (with smoking and physical activity), and marginal genetic effects (Pm). Correlations between Pv and Pm were stronger for SNPs with established marginal effects (Spearman’s ρ = 0.401 for triglycerides, and ρ = 0.236 for BMI) compared to all SNPs. When Pv and Pm were compared for all pruned SNPs, only BMI was statistically significant (Spearman’s ρ = 0.010). Overall, SNPs with established marginal effects were overrepresented in the nominally significant part of the Pv distribution (Pbinomial <0.05). SNPs from the top 1% of the Pm distribution for BMI had more significant Pv values (PMann–Whitney = 1.46×10−5), and the odds ratio of SNPs with nominally significant (<0.05) Pm and Pv was 1.33 (95% CI: 1.12, 1.57) for BMI. Moreover, BMI SNPs with nominally significant G×E interaction P-values (Pint<0.05) were enriched with nominally significant Pv values (Pbinomial = 8.63×10−9 and 8.52×10−7 for SNP × smoking and SNP × physical activity, respectively). We conclude that some loci with strong marginal effects may be good candidates for G×E, and variance-based prioritization can be used to identify them. PMID:28614350

A revised design for microarray experiments to account for experimental noise and uncertainty of probe response.

PubMed

Pozhitkov, Alex E; Noble, Peter A; Bryk, Jarosław; Tautz, Diethard

2014-01-01

Although microarrays are analysis tools in biomedical research, they are known to yield noisy output that usually requires experimental confirmation. To tackle this problem, many studies have developed rules for optimizing probe design and devised complex statistical tools to analyze the output. However, less emphasis has been placed on systematically identifying the noise component as part of the experimental procedure. One source of noise is the variance in probe binding, which can be assessed by replicating array probes. The second source is poor probe performance, which can be assessed by calibrating the array based on a dilution series of target molecules. Using model experiments for copy number variation and gene expression measurements, we investigate here a revised design for microarray experiments that addresses both of these sources of variance. Two custom arrays were used to evaluate the revised design: one based on 25 mer probes from an Affymetrix design and the other based on 60 mer probes from an Agilent design. To assess experimental variance in probe binding, all probes were replicated ten times. To assess probe performance, the probes were calibrated using a dilution series of target molecules and the signal response was fitted to an adsorption model. We found that significant variance of the signal could be controlled by averaging across probes and removing probes that are nonresponsive or poorly responsive in the calibration experiment. Taking this into account, one can obtain a more reliable signal with the added option of obtaining absolute rather than relative measurements. The assessment of technical variance within the experiments, combined with the calibration of probes allows to remove poorly responding probes and yields more reliable signals for the remaining ones. Once an array is properly calibrated, absolute quantification of signals becomes straight forward, alleviating the need for normalization and reference hybridizations.

A polynomial based model for cell fate prediction in human diseases.

PubMed

Ma, Lichun; Zheng, Jie

2017-12-21

Cell fate regulation directly affects tissue homeostasis and human health. Research on cell fate decision sheds light on key regulators, facilitates understanding the mechanisms, and suggests novel strategies to treat human diseases that are related to abnormal cell development. In this study, we proposed a polynomial based model to predict cell fate. This model was derived from Taylor series. As a case study, gene expression data of pancreatic cells were adopted to test and verify the model. As numerous features (genes) are available, we employed two kinds of feature selection methods, i.e. correlation based and apoptosis pathway based. Then polynomials of different degrees were used to refine the cell fate prediction function. 10-fold cross-validation was carried out to evaluate the performance of our model. In addition, we analyzed the stability of the resultant cell fate prediction model by evaluating the ranges of the parameters, as well as assessing the variances of the predicted values at randomly selected points. Results show that, within both the two considered gene selection methods, the prediction accuracies of polynomials of different degrees show little differences. Interestingly, the linear polynomial (degree 1 polynomial) is more stable than others. When comparing the linear polynomials based on the two gene selection methods, it shows that although the accuracy of the linear polynomial that uses correlation analysis outcomes is a little higher (achieves 86.62%), the one within genes of the apoptosis pathway is much more stable. Considering both the prediction accuracy and the stability of polynomial models of different degrees, the linear model is a preferred choice for cell fate prediction with gene expression data of pancreatic cells. The presented cell fate prediction model can be extended to other cells, which may be important for basic research as well as clinical study of cell development related diseases.

Statistical design of quantitative mass spectrometry-based proteomic experiments.

PubMed

Oberg, Ann L; Vitek, Olga

2009-05-01

We review the fundamental principles of statistical experimental design, and their application to quantitative mass spectrometry-based proteomics. We focus on class comparison using Analysis of Variance (ANOVA), and discuss how randomization, replication and blocking help avoid systematic biases due to the experimental procedure, and help optimize our ability to detect true quantitative changes between groups. We also discuss the issues of pooling multiple biological specimens for a single mass analysis, and calculation of the number of replicates in a future study. When applicable, we emphasize the parallels between designing quantitative proteomic experiments and experiments with gene expression microarrays, and give examples from that area of research. We illustrate the discussion using theoretical considerations, and using real-data examples of profiling of disease.

Evidence that molecular changes in cells occur before morphological alterations during the progression of breast ductal carcinoma

PubMed Central

Castro, Nadia P; Osório, Cynthia ABT; Torres, César; Bastos, Elen P; Mourão-Neto, Mário; Soares, Fernando A; Brentani, Helena P; Carraro, Dirce M

2008-01-01

Introduction Ductal carcinoma in situ (DCIS) of the breast includes a heterogeneous group of preinvasive tumors with uncertain evolution. Definition of the molecular factors necessary for progression to invasive disease is crucial to determining which lesions are likely to become invasive. To obtain insight into the molecular basis of DCIS, we compared the gene expression pattern of cells from the following samples: non-neoplastic, pure DCIS, in situ component of lesions with co-existing invasive ductal carcinoma, and invasive ductal carcinoma. Methods Forty-one samples were evaluated: four non-neoplastic, five pure DCIS, 22 in situ component of lesions with co-existing invasive ductal carcinoma, and 10 invasive ductal carcinoma. Pure cell populations were isolated using laser microdissection. Total RNA was purified, DNase treated, and amplified using the T7-based method. Microarray analysis was conducted using a customized cDNA platform. The concept of molecular divergence was applied to classify the sample groups using analysis of variance followed by Tukey's test. Results Among the tumor sample groups, cells from pure DCIS exhibited the most divergent molecular profile, consequently identifying cells from in situ component of lesions with co-existing invasive ductal carcinoma as very similar to cells from invasive lesions. Additionally, we identified 147 genes that were differentially expressed between pure DCIS and in situ component of lesions with co-existing invasive ductal carcinoma, which can discriminate samples representative of in situ component of lesions with co-existing invasive ductal carcinoma from 60% of pure DCIS samples. A gene subset was evaluated using quantitative RT-PCR, which confirmed differential expression for 62.5% and 60.0% of them using initial and partial independent sample groups, respectively. Among these genes, LOX and SULF-1 exhibited features that identify them as potential participants in the malignant process of DCIS. Conclusions We identified new genes that are potentially involved in the malignant transformation of DCIS, and our findings strongly suggest that cells from the in situ component of lesions with co-existing invasive ductal carcinoma exhibit molecular alterations that enable them to invade the surrounding tissue before morphological changes in the lesion become apparent. PMID:18928525

Evidence that molecular changes in cells occur before morphological alterations during the progression of breast ductal carcinoma.

PubMed

Castro, Nadia P; Osório, Cynthia A B T; Torres, César; Bastos, Elen P; Mourão-Neto, Mário; Soares, Fernando A; Brentani, Helena P; Carraro, Dirce M

2008-01-01

Ductal carcinoma in situ (DCIS) of the breast includes a heterogeneous group of preinvasive tumors with uncertain evolution. Definition of the molecular factors necessary for progression to invasive disease is crucial to determining which lesions are likely to become invasive. To obtain insight into the molecular basis of DCIS, we compared the gene expression pattern of cells from the following samples: non-neoplastic, pure DCIS, in situ component of lesions with co-existing invasive ductal carcinoma, and invasive ductal carcinoma. Forty-one samples were evaluated: four non-neoplastic, five pure DCIS, 22 in situ component of lesions with co-existing invasive ductal carcinoma, and 10 invasive ductal carcinoma. Pure cell populations were isolated using laser microdissection. Total RNA was purified, DNase treated, and amplified using the T7-based method. Microarray analysis was conducted using a customized cDNA platform. The concept of molecular divergence was applied to classify the sample groups using analysis of variance followed by Tukey's test. Among the tumor sample groups, cells from pure DCIS exhibited the most divergent molecular profile, consequently identifying cells from in situ component of lesions with co-existing invasive ductal carcinoma as very similar to cells from invasive lesions. Additionally, we identified 147 genes that were differentially expressed between pure DCIS and in situ component of lesions with co-existing invasive ductal carcinoma, which can discriminate samples representative of in situ component of lesions with co-existing invasive ductal carcinoma from 60% of pure DCIS samples. A gene subset was evaluated using quantitative RT-PCR, which confirmed differential expression for 62.5% and 60.0% of them using initial and partial independent sample groups, respectively. Among these genes, LOX and SULF-1 exhibited features that identify them as potential participants in the malignant process of DCIS. We identified new genes that are potentially involved in the malignant transformation of DCIS, and our findings strongly suggest that cells from the in situ component of lesions with co-existing invasive ductal carcinoma exhibit molecular alterations that enable them to invade the surrounding tissue before morphological changes in the lesion become apparent.

Transcriptome profiling of anthocyanin-related genes reveals effects of light intensity on anthocyanin biosynthesis in red leaf lettuce.

PubMed

Zhang, Yanzhao; Xu, Shuzhen; Cheng, Yanwei; Peng, Zhengfeng; Han, Jianming

2018-01-01

Red leaf lettuce ( Lactuca sativa L.) is popular due to its high anthocyanin content, but poor leaf coloring often occurs under low light intensity. In order to reveal the mechanisms of anthocyanins affected by light intensity, we compared the transcriptome of L. sativa L. var. capitata under light intensities of 40 and 100 μmol m -2 s -1 . A total of 62,111 unigenes were de novo assembled with an N50 of 1,681 bp, and 48,435 unigenes were functionally annotated in public databases. A total of 3,899 differentially expressed genes (DEGs) were detected, of which 1,377 unigenes were up-regulated and 2,552 unigenes were down-regulated in the high light samples. By Kyoto Encyclopedia of Genes and Genomes enrichment analysis, the DEGs were significantly enriched in 14 pathways. Using gene annotation and phylogenetic analysis, we identified seven anthocyanin structural genes, including CHS , CHI , F3H , F3'H , DFR , ANS , and 3GT , and two anthocyanin transport genes, GST and MATE . In terms of anthocyanin regulatory genes, five MYBs and one bHLH gene were identified. An HY5 gene was discovered, which may respond to light-signaling and regulate anthocyanin structural genes. These genes showed a log2FC of 2.7-9.0 under high irradiance, and were validated using quantitative real-time-PCR. In conclusion, our results indicated transcriptome variance in red leaf lettuce under low and high light intensity, and observed a anthocyanin biosynthesis and regulation pattern. The data should further help to unravel the molecular mechanisms of anthocyanins influenced by light intensity.

Genome-wide interaction of genotype by erythrocyte n-3 PUFAs contributes to phenotypic variance of diabetes-related traits

USDA-ARS?s Scientific Manuscript database

While genome-wide association studies (GWAS) and candidate gene approach have identified many genetic variants that contribute to disease risk as main effects, the impact of genotype by environment (GxE) interactions remains rather under-surveyed. The present study aimed to examine variance contribu...

flowVS: channel-specific variance stabilization in flow cytometry.

PubMed

Azad, Ariful; Rajwa, Bartek; Pothen, Alex

2016-07-28

Comparing phenotypes of heterogeneous cell populations from multiple biological conditions is at the heart of scientific discovery based on flow cytometry (FC). When the biological signal is measured by the average expression of a biomarker, standard statistical methods require that variance be approximately stabilized in populations to be compared. Since the mean and variance of a cell population are often correlated in fluorescence-based FC measurements, a preprocessing step is needed to stabilize the within-population variances. We present a variance-stabilization algorithm, called flowVS, that removes the mean-variance correlations from cell populations identified in each fluorescence channel. flowVS transforms each channel from all samples of a data set by the inverse hyperbolic sine (asinh) transformation. For each channel, the parameters of the transformation are optimally selected by Bartlett's likelihood-ratio test so that the populations attain homogeneous variances. The optimum parameters are then used to transform the corresponding channels in every sample. flowVS is therefore an explicit variance-stabilization method that stabilizes within-population variances in each channel by evaluating the homoskedasticity of clusters with a likelihood-ratio test. With two publicly available datasets, we show that flowVS removes the mean-variance dependence from raw FC data and makes the within-population variance relatively homogeneous. We demonstrate that alternative transformation techniques such as flowTrans, flowScape, logicle, and FCSTrans might not stabilize variance. Besides flow cytometry, flowVS can also be applied to stabilize variance in microarray data. With a publicly available data set we demonstrate that flowVS performs as well as the VSN software, a state-of-the-art approach developed for microarrays. The homogeneity of variance in cell populations across FC samples is desirable when extracting features uniformly and comparing cell populations with different levels of marker expressions. The newly developed flowVS algorithm solves the variance-stabilization problem in FC and microarrays by optimally transforming data with the help of Bartlett's likelihood-ratio test. On two publicly available FC datasets, flowVS stabilizes within-population variances more evenly than the available transformation and normalization techniques. flowVS-based variance stabilization can help in performing comparison and alignment of phenotypically identical cell populations across different samples. flowVS and the datasets used in this paper are publicly available in Bioconductor.

An Unbiased Systems Genetics Approach to Mapping Genetic Loci Modulating Susceptibility to Severe Streptococcal Sepsis

PubMed Central

Abdeltawab, Nourtan F.; Aziz, Ramy K.; Kansal, Rita; Rowe, Sarah L.; Su, Yin; Gardner, Lidia; Brannen, Charity; Nooh, Mohammed M.; Attia, Ramy R.; Abdelsamed, Hossam A.; Taylor, William L.; Lu, Lu; Williams, Robert W.; Kotb, Malak

2008-01-01

Striking individual differences in severity of group A streptococcal (GAS) sepsis have been noted, even among patients infected with the same bacterial strain. We had provided evidence that HLA class II allelic variation contributes significantly to differences in systemic disease severity by modulating host responses to streptococcal superantigens. Inasmuch as the bacteria produce additional virulence factors that participate in the pathogenesis of this complex disease, we sought to identify additional gene networks modulating GAS sepsis. Accordingly, we applied a systems genetics approach using a panel of advanced recombinant inbred mice. By analyzing disease phenotypes in the context of mice genotypes we identified a highly significant quantitative trait locus (QTL) on Chromosome 2 between 22 and 34 Mb that strongly predicts disease severity, accounting for 25%–30% of variance. This QTL harbors several polymorphic genes known to regulate immune responses to bacterial infections. We evaluated candidate genes within this QTL using multiple parameters that included linkage, gene ontology, variation in gene expression, cocitation networks, and biological relevance, and identified interleukin1 alpha and prostaglandin E synthases pathways as key networks involved in modulating GAS sepsis severity. The association of GAS sepsis with multiple pathways underscores the complexity of traits modulating GAS sepsis and provides a powerful approach for analyzing interactive traits affecting outcomes of other infectious diseases. PMID:18421376

Deconstructing sub-clinical psychosis into latent-state and trait variables over a 30-year time span.

PubMed

Rössler, Wulf; Hengartner, Michael P; Ajdacic-Gross, Vladeta; Haker, Helene; Angst, Jules

2013-10-01

Our aim was to deconstruct the variance underlying the expression of sub-clinical psychosis symptoms into portions associated with latent time-dependent states and time-invariant traits. We analyzed data of 335 subjects from the general population of Zurich, Switzerland, who had been repeatedly measured between 1979 (age 20/21) and 2008 (age 49/50). We applied two measures of sub-clinical psychosis derived from the SCL-90-R, namely schizotypal signs (STS) and schizophrenia nuclear symptoms (SNS). Variance was decomposed with latent state-trait analysis and associations with covariates were examined with generalized linear models. At ages 19/20 and 49/50, the latent states underlying STS accounted for 48% and 51% of variance, whereas for SNS those estimates were 62% and 50%. Between those age classes, however, expression of sub-clinical psychosis was strongly associated with stable traits (75% and 89% of total variance in STS and SNS, respectively, at age 27/28). Latent states underlying variance in STS and SNS were particularly related to partnership problems over almost the entire observation period. STS was additionally related to employment problems, whereas drug-use was a strong predictor of states underlying both syndromes at age 19/20. The latent trait underlying expression of STS and SNS was particularly related to low sense of mastery and self-esteem and to high depressiveness. Although most psychosis symptoms are transient and episodic in nature, the variability in their expression is predominantly caused by stable traits. Those time-invariant and rather consistent effects are particularly influential around age 30, whereas the occasion-specific states appear to be particularly influential at ages 20 and 50. © 2013.

Using the Positive and Negative Syndrome Scale (PANSS) to Define Different Domains of Negative Symptoms

PubMed Central

Khan, Anzalee; Keefe, Richard S. E.

2017-01-01

Background: Reduced emotional experience and expression are two domains of negative symptoms. The authors assessed these two domains of negative symptoms using previously developed Positive and Negative Syndrome Scale (PANSS) factors. Using an existing dataset, the authors predicted three different elements of everyday functioning (social, vocational, and everyday activities) with these two factors, as well as with performance on measures of functional capacity. Methods: A large (n=630) sample of people with schizophrenia was used as the data source of this study. Using regression analyses, the authors predicted the three different aspects of everyday functioning, first with just the two Positive and Negative Syndrome Scale factors and then with a global negative symptom factor. Finally, we added neurocognitive performance and functional capacity as predictors. Results: The Positive and Negative Syndrome Scale reduced emotional experience factor accounted for 21 percent of the variance in everyday social functioning, while reduced emotional expression accounted for no variance. The total Positive and Negative Syndrome Scale negative symptom factor accounted for less variance (19%) than the reduced experience factor alone. The Positive and Negative Syndrome Scale expression factor accounted for, at most, one percent of the variance in any of the functional outcomes, with or without the addition of other predictors. Implications: Reduced emotional experience measured with the Positive and Negative Syndrome Scale, often referred to as “avolition and anhedonia,” specifically predicted impairments in social outcomes. Further, reduced experience predicted social impairments better than emotional expression or the total Positive and Negative Syndrome Scale negative symptom factor. In this cross-sectional study, reduced emotional experience was specifically related with social outcomes, accounting for essentially no variance in work or everyday activities, and being the sole meaningful predictor of impairment in social outcomes. PMID:29410933

Natural and synthetic STAT3 inhibitors reduce hepcidin expression in differentiated mouse hepatocytes expressing the active phosphorylated STAT3 form.

PubMed

Fatih, Nadia; Camberlein, Emilie; Island, Marie Laure; Corlu, Anne; Abgueguen, Emmanuelle; Détivaud, Lénaïck; Leroyer, Patricia; Brissot, Pierre; Loréal, Olivier

2010-05-01

During the inflammatory process, hepcidin overexpression favours the development of anaemia of chronic diseases which represents the second most common form of anaemia worldwide. The identification of therapeutic agents decreasing hepcidin expression is therefore an important goal. The aim of this study was to target the STAT3 signalling involved in the development of increased hepcidin expression related to chronic inflammation. In a co-culture model associating mouse hepatocytes and rat liver epithelial cells, the mRNA levels of hepcidin1, albumin, aldolase B, Cyp3a4, Stat3, Smad4 and iron regulatory genes were measured by real-time PCR. STAT3 and phosphorylated SMAD1/5/8 proteins were analysed by Western blot. At variance of hepatocyte pure culture, co-culture provided high levels of hepcidin1 mRNA, reaching 400% of the freshly isolated hepatocyte values after 6 days of culture. Hepcidin expression was associated with the maintenance of hepatocyte phenotype, STAT3 phosphorylation and functional BMP/SMAD pathway. Stat3 siRNAs inhibited the hepcidin1 mRNA expression. STAT3 inhibitors, including curcumin, AG490 and a peptide (PpYLKTK), reduced hepcidin1 mRNA expression even when cells were additionally exposed to IL-6. Hepcidin1 mRNA was expressed at high levels by hepatocytes in the co-culture model, and STAT3 pathway activation was controlled through STAT3 inhibitors. Such inhibitors could be useful to prevent anaemia related to hepcidin overexpression during chronic inflammation.

Using the Positive and Negative Syndrome Scale (PANSS) to Define Different Domains of Negative Symptoms: Prediction of Everyday Functioning by Impairments in Emotional Expression and Emotional Experience.

PubMed

Harvey, Philip D; Khan, Anzalee; Keefe, Richard S E

2017-12-01

Background: Reduced emotional experience and expression are two domains of negative symptoms. The authors assessed these two domains of negative symptoms using previously developed Positive and Negative Syndrome Scale (PANSS) factors. Using an existing dataset, the authors predicted three different elements of everyday functioning (social, vocational, and everyday activities) with these two factors, as well as with performance on measures of functional capacity. Methods: A large (n=630) sample of people with schizophrenia was used as the data source of this study. Using regression analyses, the authors predicted the three different aspects of everyday functioning, first with just the two Positive and Negative Syndrome Scale factors and then with a global negative symptom factor. Finally, we added neurocognitive performance and functional capacity as predictors. Results: The Positive and Negative Syndrome Scale reduced emotional experience factor accounted for 21 percent of the variance in everyday social functioning, while reduced emotional expression accounted for no variance. The total Positive and Negative Syndrome Scale negative symptom factor accounted for less variance (19%) than the reduced experience factor alone. The Positive and Negative Syndrome Scale expression factor accounted for, at most, one percent of the variance in any of the functional outcomes, with or without the addition of other predictors. Implications: Reduced emotional experience measured with the Positive and Negative Syndrome Scale, often referred to as "avolition and anhedonia," specifically predicted impairments in social outcomes. Further, reduced experience predicted social impairments better than emotional expression or the total Positive and Negative Syndrome Scale negative symptom factor. In this cross-sectional study, reduced emotional experience was specifically related with social outcomes, accounting for essentially no variance in work or everyday activities, and being the sole meaningful predictor of impairment in social outcomes.

Reward dependence is related to norepinephrine transporter T-182C gene polymorphism in a Korean population.

PubMed

Ham, Byung-Joo; Choi, Myoung-Jin; Lee, Heon-Jeong; Kang, Rhee-Hun; Lee, Min-Soo

2005-06-01

It is well established that approximately 50% of the variance in personality traits is genetic. The goal of this study was to investigate a relationship between personality traits and the T-182C polymorphism in the norepinephrine transporter gene. The participants included 115 healthy adults with no history of psychiatric disorders and other physical illness during the past 6 months. All participants were tested with the Temperament and Character Inventory and genotyped norepinephrine transporter gene polymorphism. Differences on the Temperament and Character Inventory dimensions among three groups were examined with one-way analysis of variance. Our study suggests that the norepinephrine transporter T-182C gene polymorphism is associated with reward dependence in Koreans, but the small number of study participants and their sex and age heterogeneity limits generalization of our results. Further studies are necessary with a larger number of homogeneous participants to confirm whether the norepinephrine transporter gene is related to personality traits.

Sampling hazelnuts for aflatoxin: uncertainty associated with sampling, sample preparation, and analysis.

PubMed

Ozay, Guner; Seyhan, Ferda; Yilmaz, Aysun; Whitaker, Thomas B; Slate, Andrew B; Giesbrecht, Francis

2006-01-01

The variability associated with the aflatoxin test procedure used to estimate aflatoxin levels in bulk shipments of hazelnuts was investigated. Sixteen 10 kg samples of shelled hazelnuts were taken from each of 20 lots that were suspected of aflatoxin contamination. The total variance associated with testing shelled hazelnuts was estimated and partitioned into sampling, sample preparation, and analytical variance components. Each variance component increased as aflatoxin concentration (either B1 or total) increased. With the use of regression analysis, mathematical expressions were developed to model the relationship between aflatoxin concentration and the total, sampling, sample preparation, and analytical variances. The expressions for these relationships were used to estimate the variance for any sample size, subsample size, and number of analyses for a specific aflatoxin concentration. The sampling, sample preparation, and analytical variances associated with estimating aflatoxin in a hazelnut lot at a total aflatoxin level of 10 ng/g and using a 10 kg sample, a 50 g subsample, dry comminution with a Robot Coupe mill, and a high-performance liquid chromatographic analytical method are 174.40, 0.74, and 0.27, respectively. The sampling, sample preparation, and analytical steps of the aflatoxin test procedure accounted for 99.4, 0.4, and 0.2% of the total variability, respectively.

Modified signal-to-noise: a new simple and practical gene filtering approach based on the concept of projective adaptive resonance theory (PART) filtering method.

PubMed

Takahashi, Hiro; Honda, Hiroyuki

2006-07-01

Considering the recent advances in and the benefits of DNA microarray technologies, many gene filtering approaches have been employed for the diagnosis and prognosis of diseases. In our previous study, we developed a new filtering method, namely, the projective adaptive resonance theory (PART) filtering method. This method was effective in subclass discrimination. In the PART algorithm, the genes with a low variance in gene expression in either class, not both classes, were selected as important genes for modeling. Based on this concept, we developed novel simple filtering methods such as modified signal-to-noise (S2N') in the present study. The discrimination model constructed using these methods showed higher accuracy with higher reproducibility as compared with many conventional filtering methods, including the t-test, S2N, NSC and SAM. The reproducibility of prediction was evaluated based on the correlation between the sets of U-test p-values on randomly divided datasets. With respect to leukemia, lymphoma and breast cancer, the correlation was high; a difference of >0.13 was obtained by the constructed model by using <50 genes selected by S2N'. Improvement was higher in the smaller genes and such higher correlation was observed when t-test, NSC and SAM were used. These results suggest that these modified methods, such as S2N', have high potential to function as new methods for marker gene selection in cancer diagnosis using DNA microarray data. Software is available upon request.

A Genome-Wide Association Analysis Reveals Epistatic Cancellation of Additive Genetic Variance for Root Length in Arabidopsis thaliana.

PubMed

Lachowiec, Jennifer; Shen, Xia; Queitsch, Christine; Carlborg, Örjan

2015-01-01

Efforts to identify loci underlying complex traits generally assume that most genetic variance is additive. Here, we examined the genetics of Arabidopsis thaliana root length and found that the genomic narrow-sense heritability for this trait in the examined population was statistically zero. The low amount of additive genetic variance that could be captured by the genome-wide genotypes likely explains why no associations to root length could be found using standard additive-model-based genome-wide association (GWA) approaches. However, as the broad-sense heritability for root length was significantly larger, and primarily due to epistasis, we also performed an epistatic GWA analysis to map loci contributing to the epistatic genetic variance. Four interacting pairs of loci were revealed, involving seven chromosomal loci that passed a standard multiple-testing corrected significance threshold. The genotype-phenotype maps for these pairs revealed epistasis that cancelled out the additive genetic variance, explaining why these loci were not detected in the additive GWA analysis. Small population sizes, such as in our experiment, increase the risk of identifying false epistatic interactions due to testing for associations with very large numbers of multi-marker genotypes in few phenotyped individuals. Therefore, we estimated the false-positive risk using a new statistical approach that suggested half of the associated pairs to be true positive associations. Our experimental evaluation of candidate genes within the seven associated loci suggests that this estimate is conservative; we identified functional candidate genes that affected root development in four loci that were part of three of the pairs. The statistical epistatic analyses were thus indispensable for confirming known, and identifying new, candidate genes for root length in this population of wild-collected A. thaliana accessions. We also illustrate how epistatic cancellation of the additive genetic variance explains the insignificant narrow-sense and significant broad-sense heritability by using a combination of careful statistical epistatic analyses and functional genetic experiments.

MicroRNA-138 is a potential regulator of memory performance in humans

PubMed Central

Schröder, Julia; Ansaloni, Sara; Schilling, Marcel; Liu, Tian; Radke, Josefine; Jaedicke, Marian; Schjeide, Brit-Maren M.; Mashychev, Andriy; Tegeler, Christina; Radbruch, Helena; Papenberg, Goran; Düzel, Sandra; Demuth, Ilja; Bucholtz, Nina; Lindenberger, Ulman; Li, Shu-Chen; Steinhagen-Thiessen, Elisabeth; Lill, Christina M.; Bertram, Lars

2014-01-01

Genetic factors underlie a substantial proportion of individual differences in cognitive functions in humans, including processes related to episodic and working memory. While genetic association studies have proposed several candidate “memory genes,” these currently explain only a minor fraction of the phenotypic variance. Here, we performed genome-wide screening on 13 episodic and working memory phenotypes in 1318 participants of the Berlin Aging Study II aged 60 years or older. The analyses highlight a number of novel single nucleotide polymorphisms (SNPs) associated with memory performance, including one located in a putative regulatory region of microRNA (miRNA) hsa-mir-138-5p (rs9882688, P-value = 7.8 × 10−9). Expression quantitative trait locus analyses on next-generation RNA-sequencing data revealed that rs9882688 genotypes show a significant correlation with the expression levels of this miRNA in 309 human lymphoblastoid cell lines (P-value = 5 × 10−4). In silico modeling of other top-ranking GWAS signals identified an additional memory-associated SNP in the 3′ untranslated region (3′ UTR) of DCP1B, a gene encoding a core component of the mRNA decapping complex in humans, predicted to interfere with hsa-mir-138-5p binding. This prediction was confirmed in vitro by luciferase assays showing differential binding of hsa-mir-138-5p to 3′ UTR reporter constructs in two human cell lines (HEK293: P-value = 0.0470; SH-SY5Y: P-value = 0.0866). Finally, expression profiling of hsa-mir-138-5p and DCP1B mRNA in human post-mortem brain tissue revealed that both molecules are expressed simultaneously in frontal cortex and hippocampus, suggesting that the proposed interaction between hsa-mir-138-5p and DCP1B may also take place in vivo. In summary, by combining unbiased genome-wide screening with extensive in silico modeling, in vitro functional assays, and gene expression profiling, our study identified miRNA-138 as a potential molecular regulator of human memory function. PMID:25071529

Cyber-T web server: differential analysis of high-throughput data.

PubMed

Kayala, Matthew A; Baldi, Pierre

2012-07-01

The Bayesian regularization method for high-throughput differential analysis, described in Baldi and Long (A Bayesian framework for the analysis of microarray expression data: regularized t-test and statistical inferences of gene changes. Bioinformatics 2001: 17: 509-519) and implemented in the Cyber-T web server, is one of the most widely validated. Cyber-T implements a t-test using a Bayesian framework to compute a regularized variance of the measurements associated with each probe under each condition. This regularized estimate is derived by flexibly combining the empirical measurements with a prior, or background, derived from pooling measurements associated with probes in the same neighborhood. This approach flexibly addresses problems associated with low replication levels and technology biases, not only for DNA microarrays, but also for other technologies, such as protein arrays, quantitative mass spectrometry and next-generation sequencing (RNA-seq). Here we present an update to the Cyber-T web server, incorporating several useful new additions and improvements. Several preprocessing data normalization options including logarithmic and (Variance Stabilizing Normalization) VSN transforms are included. To augment two-sample t-tests, a one-way analysis of variance is implemented. Several methods for multiple tests correction, including standard frequentist methods and a probabilistic mixture model treatment, are available. Diagnostic plots allow visual assessment of the results. The web server provides comprehensive documentation and example data sets. The Cyber-T web server, with R source code and data sets, is publicly available at http://cybert.ics.uci.edu/.

Novel approach identifies SNPs in SLC2A10 and KCNK9 with evidence for parent-of-origin effect on body mass index.

PubMed

Hoggart, Clive J; Venturini, Giulia; Mangino, Massimo; Gomez, Felicia; Ascari, Giulia; Zhao, Jing Hua; Teumer, Alexander; Winkler, Thomas W; Tšernikova, Natalia; Luan, Jian'an; Mihailov, Evelin; Ehret, Georg B; Zhang, Weihua; Lamparter, David; Esko, Tõnu; Macé, Aurelien; Rüeger, Sina; Bochud, Pierre-Yves; Barcella, Matteo; Dauvilliers, Yves; Benyamin, Beben; Evans, David M; Hayward, Caroline; Lopez, Mary F; Franke, Lude; Russo, Alessia; Heid, Iris M; Salvi, Erika; Vendantam, Sailaja; Arking, Dan E; Boerwinkle, Eric; Chambers, John C; Fiorito, Giovanni; Grallert, Harald; Guarrera, Simonetta; Homuth, Georg; Huffman, Jennifer E; Porteous, David; Moradpour, Darius; Iranzo, Alex; Hebebrand, Johannes; Kemp, John P; Lammers, Gert J; Aubert, Vincent; Heim, Markus H; Martin, Nicholas G; Montgomery, Grant W; Peraita-Adrados, Rosa; Santamaria, Joan; Negro, Francesco; Schmidt, Carsten O; Scott, Robert A; Spector, Tim D; Strauch, Konstantin; Völzke, Henry; Wareham, Nicholas J; Yuan, Wei; Bell, Jordana T; Chakravarti, Aravinda; Kooner, Jaspal S; Peters, Annette; Matullo, Giuseppe; Wallaschofski, Henri; Whitfield, John B; Paccaud, Fred; Vollenweider, Peter; Bergmann, Sven; Beckmann, Jacques S; Tafti, Mehdi; Hastie, Nicholas D; Cusi, Daniele; Bochud, Murielle; Frayling, Timothy M; Metspalu, Andres; Jarvelin, Marjo-Riitta; Scherag, André; Smith, George Davey; Borecki, Ingrid B; Rousson, Valentin; Hirschhorn, Joel N; Rivolta, Carlo; Loos, Ruth J F; Kutalik, Zoltán

2014-07-01

The phenotypic effect of some single nucleotide polymorphisms (SNPs) depends on their parental origin. We present a novel approach to detect parent-of-origin effects (POEs) in genome-wide genotype data of unrelated individuals. The method exploits increased phenotypic variance in the heterozygous genotype group relative to the homozygous groups. We applied the method to >56,000 unrelated individuals to search for POEs influencing body mass index (BMI). Six lead SNPs were carried forward for replication in five family-based studies (of ∼4,000 trios). Two SNPs replicated: the paternal rs2471083-C allele (located near the imprinted KCNK9 gene) and the paternal rs3091869-T allele (located near the SLC2A10 gene) increased BMI equally (beta = 0.11 (SD), P<0.0027) compared to the respective maternal alleles. Real-time PCR experiments of lymphoblastoid cell lines from the CEPH families showed that expression of both genes was dependent on parental origin of the SNPs alleles (P<0.01). Our scheme opens new opportunities to exploit GWAS data of unrelated individuals to identify POEs and demonstrates that they play an important role in adult obesity.

Novel Approach Identifies SNPs in SLC2A10 and KCNK9 with Evidence for Parent-of-Origin Effect on Body Mass Index

PubMed Central

Hoggart, Clive J.; Venturini, Giulia; Mangino, Massimo; Gomez, Felicia; Ascari, Giulia; Zhao, Jing Hua; Teumer, Alexander; Winkler, Thomas W.; Tšernikova, Natalia; Luan, Jian'an; Mihailov, Evelin; Ehret, Georg B.; Zhang, Weihua; Lamparter, David; Esko, Tõnu; Macé, Aurelien; Rüeger, Sina; Bochud, Pierre-Yves; Barcella, Matteo; Dauvilliers, Yves; Benyamin, Beben; Evans, David M.; Hayward, Caroline; Lopez, Mary F.; Franke, Lude; Russo, Alessia; Heid, Iris M.; Salvi, Erika; Vendantam, Sailaja; Arking, Dan E.; Boerwinkle, Eric; Chambers, John C.; Fiorito, Giovanni; Grallert, Harald; Guarrera, Simonetta; Homuth, Georg; Huffman, Jennifer E.; Porteous, David; Moradpour, Darius; Iranzo, Alex; Hebebrand, Johannes; Kemp, John P.; Lammers, Gert J.; Aubert, Vincent; Heim, Markus H.; Martin, Nicholas G.; Montgomery, Grant W.; Peraita-Adrados, Rosa; Santamaria, Joan; Negro, Francesco; Schmidt, Carsten O.; Scott, Robert A.; Spector, Tim D.; Strauch, Konstantin; Völzke, Henry; Wareham, Nicholas J.; Yuan, Wei; Bell, Jordana T.; Chakravarti, Aravinda; Kooner, Jaspal S.; Peters, Annette; Matullo, Giuseppe; Wallaschofski, Henri; Whitfield, John B.; Paccaud, Fred; Vollenweider, Peter; Bergmann, Sven; Beckmann, Jacques S.; Tafti, Mehdi; Hastie, Nicholas D.; Cusi, Daniele; Bochud, Murielle; Frayling, Timothy M.; Metspalu, Andres; Jarvelin, Marjo-Riitta; Scherag, André; Smith, George Davey; Borecki, Ingrid B.; Rousson, Valentin; Hirschhorn, Joel N.; Rivolta, Carlo; Loos, Ruth J. F.; Kutalik, Zoltán

2014-01-01

The phenotypic effect of some single nucleotide polymorphisms (SNPs) depends on their parental origin. We present a novel approach to detect parent-of-origin effects (POEs) in genome-wide genotype data of unrelated individuals. The method exploits increased phenotypic variance in the heterozygous genotype group relative to the homozygous groups. We applied the method to >56,000 unrelated individuals to search for POEs influencing body mass index (BMI). Six lead SNPs were carried forward for replication in five family-based studies (of ∼4,000 trios). Two SNPs replicated: the paternal rs2471083-C allele (located near the imprinted KCNK9 gene) and the paternal rs3091869-T allele (located near the SLC2A10 gene) increased BMI equally (beta = 0.11 (SD), P<0.0027) compared to the respective maternal alleles. Real-time PCR experiments of lymphoblastoid cell lines from the CEPH families showed that expression of both genes was dependent on parental origin of the SNPs alleles (P<0.01). Our scheme opens new opportunities to exploit GWAS data of unrelated individuals to identify POEs and demonstrates that they play an important role in adult obesity. PMID:25078964

The genetic architecture of photosynthesis and plant growth-related traits in tomato.

PubMed

de Oliveira Silva, Franklin Magnum; Lichtenstein, Gabriel; Alseekh, Saleh; Rosado-Souza, Laise; Conte, Mariana; Suguiyama, Vanessa Fuentes; Lira, Bruno Silvestre; Fanourakis, Dimitrios; Usadel, Björn; Bhering, Leonardo Lopes; DaMatta, Fábio M; Sulpice, Ronan; Araújo, Wagner L; Rossi, Magdalena; de Setta, Nathalia; Fernie, Alisdair R; Carrari, Fernando; Nunes-Nesi, Adriano

2018-02-01

To identify genomic regions involved in the regulation of fundamental physiological processes such as photosynthesis and respiration, a population of Solanum pennellii introgression lines was analyzed. We determined phenotypes for physiological, metabolic, and growth related traits, including gas exchange and chlorophyll fluorescence parameters. Data analysis allowed the identification of 208 physiological and metabolic quantitative trait loci with 33 of these being associated to smaller intervals of the genomic regions, termed BINs. Eight BINs were identified that were associated with higher assimilation rates than the recurrent parent M82. Two and 10 genomic regions were related to shoot and root dry matter accumulation, respectively. Nine genomic regions were associated with starch levels, whereas 12 BINs were associated with the levels of other metabolites. Additionally, a comprehensive and detailed annotation of the genomic regions spanning these quantitative trait loci allowed us to identify 87 candidate genes that putatively control the investigated traits. We confirmed 8 of these at the level of variance in gene expression. Taken together, our results allowed the identification of candidate genes that most likely regulate photosynthesis, primary metabolism, and plant growth and as such provide new avenues for crop improvement. © 2017 John Wiley & Sons Ltd.

Posed versus spontaneous facial expressions are modulated by opposite cerebral hemispheres.

PubMed

Ross, Elliott D; Pulusu, Vinay K

2013-05-01

Clinical research has indicated that the left face is more expressive than the right face, suggesting that modulation of facial expressions is lateralized to the right hemisphere. The findings, however, are controversial because the results explain, on average, approximately 4% of the data variance. Using high-speed videography, we sought to determine if movement-onset asymmetry was a more powerful research paradigm than terminal movement asymmetry. The results were very robust, explaining up to 70% of the data variance. Posed expressions began overwhelmingly on the right face whereas spontaneous expressions began overwhelmingly on the left face. This dichotomy was most robust for upper facial expressions. In addition, movement-onset asymmetries did not predict terminal movement asymmetries, which were not significantly lateralized. The results support recent neuroanatomic observations that upper versus lower facial movements have different forebrain motor representations and recent behavioral constructs that posed versus spontaneous facial expressions are modulated preferentially by opposite cerebral hemispheres and that spontaneous facial expressions are graded rather than non-graded movements. Published by Elsevier Ltd.

Identification of gene-specific polymorphisms and association with capsaicin pathway metabolites in Capsicum annuum L. collections.

PubMed

Reddy, Umesh K; Almeida, Aldo; Abburi, Venkata L; Alaparthi, Suresh Babu; Unselt, Desiree; Hankins, Gerald; Park, Minkyu; Choi, Doil; Nimmakayala, Padma

2014-01-01

Pepper (Capsicum annuum L.) is an economically important crop with added nutritional value. Production of capsaicin is an important quantitative trait with high environmental variance, so the development of markers regulating capsaicinoid accumulation is important for pepper breeding programs. In this study, we performed association mapping at the gene level to identify single nucleotide polymorphisms (SNPs) associated with capsaicin pathway metabolites in a diverse Capsicum annuum collection during two seasons. The genes Pun1, CCR, KAS and HCT were sequenced and matched with the whole-genome sequence draft of pepper to identify SNP locations and for further characterization. The identified SNPs for each gene underwent candidate gene association mapping. Association mapping results revealed Pun1 as a key regulator of major metabolites in the capsaicin pathway mainly affecting capsaicinoids and precursors for acyl moieties of capsaicinoids. Six different SNPs in the promoter sequence of Pun1 were found associated with capsaicin in plants from both seasons. Our results support that CCR is an important control point for the flux of p-coumaric acid to specific biosynthesis pathways. KAS was found to regulate the major precursors for acyl moieties of capsaicinoids and may play a key role in capsaicinoid production. Candidate gene association mapping of Pun1 suggested that the accumulation of capsaicinoids depends on the expression of Pun1, as revealed by the most important associated SNPs found in the promoter region of Pun1.

Identification of Gene-Specific Polymorphisms and Association with Capsaicin Pathway Metabolites in Capsicum annuum L. Collections

PubMed Central

Abburi, Venkata L.; Alaparthi, Suresh Babu; Unselt, Desiree; Hankins, Gerald; Park, Minkyu; Choi, Doil

2014-01-01

Pepper (Capsicum annuum L.) is an economically important crop with added nutritional value. Production of capsaicin is an important quantitative trait with high environmental variance, so the development of markers regulating capsaicinoid accumulation is important for pepper breeding programs. In this study, we performed association mapping at the gene level to identify single nucleotide polymorphisms (SNPs) associated with capsaicin pathway metabolites in a diverse Capsicum annuum collection during two seasons. The genes Pun1, CCR, KAS and HCT were sequenced and matched with the whole-genome sequence draft of pepper to identify SNP locations and for further characterization. The identified SNPs for each gene underwent candidate gene association mapping. Association mapping results revealed Pun1 as a key regulator of major metabolites in the capsaicin pathway mainly affecting capsaicinoids and precursors for acyl moieties of capsaicinoids. Six different SNPs in the promoter sequence of Pun1 were found associated with capsaicin in plants from both seasons. Our results support that CCR is an important control point for the flux of p-coumaric acid to specific biosynthesis pathways. KAS was found to regulate the major precursors for acyl moieties of capsaicinoids and may play a key role in capsaicinoid production. Candidate gene association mapping of Pun1 suggested that the accumulation of capsaicinoids depends on the expression of Pun1, as revealed by the most important associated SNPs found in the promoter region of Pun1. PMID:24475113

Fenretinide

PubMed Central

Pavone, Mary Ellen; Malpani, Saurabh S.; Dyson, Matthew; Kim, J. Julie; Bulun, Serdar E.

2016-01-01

Objective: Fenretinide is a synthetic retinoid analogue that promotes apoptosis but has decreased toxicity when compared to other retinoids. We have previously shown that retinoic acid (RA) production in endometriotic tissue is decreased, resulting in reduced estrogen metabolism and apoptotic resistance. We hypothesize fenretinide may induce apoptosis in endometriotic cells and tissues, thereby reducing disease burden. Materials and Methods: Primary endometriotic stromal cells were collected, isolated, cultured, and treated with fenretinide in doses from 0 to 20 µmol/L. Cell count, viability, and immunoblots were performed to examine apoptosis. Quantitative reverse transcription-polymerase chain reaction from endometriotic cells treated with fenretinide was used to examine expression of genes involved in RA signaling including stimulated by RA 6 (STRA6), cellular RA binding protein 2 (CRABP2), and fatty acid binding protein 5 (FABP5). Endometriotic tissue was xenografted subcutaneously into the flanks of mice which were treated with fenretinide for 2 weeks, after which the mice were killed and lesion volumes calculated. Statistical analysis was performed using t test and analysis of variance. Results: Treatment with fenretinide significantly decreased total cell count (doses 5-20 µL) and viability (doses 10-20 µmol/L). Fenretinide increased protein levels of the apoptotic marker poly (ADP ribose) polymerase (starting at 10 µmol/L) and decreased proliferation marker proliferating cell nuclear antigen (10 µmol/L, starting at 8-day treatment). Examination of genes involved in retinoid uptake and action showed that treatment induced STRA6 expression while expression of CRABP2 and FABP5 remained unchanged. Fenretinide also significantly decreased the endometriotic lesion xenograft volume. Conclusions: Fenretinide increases STRA6 expression thereby potentially reversing the pathological loss of retinoid availability. Treatment with this compound induces apoptosis. In vivo treatments decrease lesion volume. Targeting the RA signaling pathway may be a promising novel treatment for women with endometriosis. PMID:26919975

Segregation analysis of abdominal visceral fat: the HERITAGE Family Study.

PubMed

Rice, T; Després, J P; Pérusse, L; Gagnon, J; Leon, A S; Skinner, J S; Wilmore, J H; Rao, D C; Bouchard, C

1997-09-01

A major gene hypothesis for abdominal visceral fat (AVF) level, both before and after adjustment for total body fat mass, was investigated in 86 white families who participated in the HERITAGE Family Study. In this study, sedentary families were tested for a battery of measures (baseline), endurance exercise trained for 20 weeks, and then remeasured again. The baseline measures reported here are unique in that the variance due to a potentially important environmental factor (activity level) was limited. AVF area was assessed at L4 to L5 by the use of computerized tomography scan, and total body fat mass was assessed with underwater weighing. For fat mass, a putative locus accounted for 64% of the variance, but there was no evidence of a multifactorial component (i.e., no polygenic and/or common familial environmental effects). For AVF area, both a major gene effect accounting for 54% of the variance and a multifactorial component accounting for 17% of the variance were significant. However, after AVF area was adjusted for the effects of total level of body fat, the support for a major gene was reduced. In particular, there was a major effect for fat mass-adjusted AVF area, but it was not transmitted from parents to offspring (i.e., the three transmission probabilities were equal). The importance of this study is twofold. First, these results confirm a previous study that suggested that there is a putative major locus for AVF and for total body fat mass. Second, the findings from the HERITAGE Family Study suggest that the factors underlying AVF area in sedentary families may be similar to those in the population at large, which includes both sedentary and active families. Whether the gene(s) responsible for the high levels of AVF area is the same as that which influences total body fat content remains to be further investigated.

Examining Genetic and Environmental Effects on Reactive versus Proactive Aggression

ERIC Educational Resources Information Center

Brendgen, Mara; Vitaro, Frank; Boivin, Michel; Dionne, Ginette; Perusse, Daniel

2006-01-01

This study compared the contribution of genes and environment to teacher-rated reactive and proactive aggression in 6-year-old twin pairs (172 pairs: 55 monozygotic girls, 48 monozygotic boys, 33 dizygotic girls, 36 dizygotic boys). Genetic effects accounted for 39% of the variance of reactive aggression and for 41% of the variance of proactive…

A long-term predictive validity study: can the CDI Short Form be used to predict language and early literacy skills four years later?

PubMed

Can, Dilara Deniz; Ginsburg-Block, Marika; Golinkoff, Roberta Michnick; Hirsh-Pasek, Kathryn

2013-09-01

This longitudinal study examined the predictive validity of the MacArthur Communicative Developmental Inventories-Short Form (CDI-SF), a parent report questionnaire about children's language development (Fenson, Pethick, Renda, Cox, Dale & Reznick, 2000). Data were first gathered from parents on the CDI-SF vocabulary scores for seventy-six children (mean age=1 ; 10). Four years later (mean age=6 ; 1), children were assessed on language outcomes (expressive vocabulary, syntax, semantics and pragmatics) and code-related skills, including phonemic awareness, word recognition and decoding skills. Hierarchical regression analyses revealed that early expressive vocabulary accounted for 17% of the variance in picture vocabulary, 11% of the variance in syntax, and 7% of the variance in semantics, while not accounting for any variance in pragmatics in kindergarten. CDI-SF scores did not predict code-related skills in kindergarten. The importance of early vocabulary skills for later language development and CDI-SF as a valuable research tool are discussed.

Jackknife variance of the partial area under the empirical receiver operating characteristic curve.

PubMed

Bandos, Andriy I; Guo, Ben; Gur, David

2017-04-01

Receiver operating characteristic analysis provides an important methodology for assessing traditional (e.g., imaging technologies and clinical practices) and new (e.g., genomic studies, biomarker development) diagnostic problems. The area under the clinically/practically relevant part of the receiver operating characteristic curve (partial area or partial area under the receiver operating characteristic curve) is an important performance index summarizing diagnostic accuracy at multiple operating points (decision thresholds) that are relevant to actual clinical practice. A robust estimate of the partial area under the receiver operating characteristic curve is provided by the area under the corresponding part of the empirical receiver operating characteristic curve. We derive a closed-form expression for the jackknife variance of the partial area under the empirical receiver operating characteristic curve. Using the derived analytical expression, we investigate the differences between the jackknife variance and a conventional variance estimator. The relative properties in finite samples are demonstrated in a simulation study. The developed formula enables an easy way to estimate the variance of the empirical partial area under the receiver operating characteristic curve, thereby substantially reducing the computation burden, and provides important insight into the structure of the variability. We demonstrate that when compared with the conventional approach, the jackknife variance has substantially smaller bias, and leads to a more appropriate type I error rate of the Wald-type test. The use of the jackknife variance is illustrated in the analysis of a data set from a diagnostic imaging study.

Detecting epistasis with the marginal epistasis test in genetic mapping studies of quantitative traits

PubMed Central

Zeng, Ping; Mukherjee, Sayan; Zhou, Xiang

2017-01-01

Epistasis, commonly defined as the interaction between multiple genes, is an important genetic component underlying phenotypic variation. Many statistical methods have been developed to model and identify epistatic interactions between genetic variants. However, because of the large combinatorial search space of interactions, most epistasis mapping methods face enormous computational challenges and often suffer from low statistical power due to multiple test correction. Here, we present a novel, alternative strategy for mapping epistasis: instead of directly identifying individual pairwise or higher-order interactions, we focus on mapping variants that have non-zero marginal epistatic effects—the combined pairwise interaction effects between a given variant and all other variants. By testing marginal epistatic effects, we can identify candidate variants that are involved in epistasis without the need to identify the exact partners with which the variants interact, thus potentially alleviating much of the statistical and computational burden associated with standard epistatic mapping procedures. Our method is based on a variance component model, and relies on a recently developed variance component estimation method for efficient parameter inference and p-value computation. We refer to our method as the “MArginal ePIstasis Test”, or MAPIT. With simulations, we show how MAPIT can be used to estimate and test marginal epistatic effects, produce calibrated test statistics under the null, and facilitate the detection of pairwise epistatic interactions. We further illustrate the benefits of MAPIT in a QTL mapping study by analyzing the gene expression data of over 400 individuals from the GEUVADIS consortium. PMID:28746338

Multi-location wheat stripe rust QTL analysis: genetic background and epistatic interactions.

PubMed

Vazquez, M Dolores; Zemetra, Robert; Peterson, C James; Chen, Xianming M; Heesacker, Adam; Mundt, Christopher C

2015-07-01

Epistasis and genetic background were important influences on expression of stripe rust resistance in two wheat RIL populations, one with resistance conditioned by two major genes and the other conditioned by several minor QTL. Stripe rust is a foliar disease of wheat (Triticum aestivum L.) caused by the air-borne fungus Puccinia striiformis f. sp. tritici and is present in most regions around the world where commercial wheat is grown. Breeding for durable resistance to stripe rust continues to be a priority, but also is a challenge due to the complexity of interactions among resistance genes and to the wide diversity and continuous evolution of the pathogen races. The goal of this study was to detect chromosomal regions for resistance to stripe rust in two winter wheat populations, 'Tubbs'/'NSA-98-0995' (T/N) and 'Einstein'/'Tubbs' (E/T), evaluated across seven environments and mapped with diversity array technology and simple sequence repeat markers covering polymorphic regions of ≈1480 and 1117 cM, respectively. Analysis of variance for phenotypic data revealed significant (P < 0.01) genotypic differentiation for stripe rust among the recombinant inbred lines. Results for quantitative trait loci/locus (QTL) analysis in the E/T population indicated that two major QTL located in chromosomes 2AS and 6AL, with epistatic interaction between them, were responsible for the main phenotypic response. For the T/N population, eight QTL were identified, with those in chromosomes 2AL and 2BL accounting for the largest percentage of the phenotypic variance.

Linear score tests for variance components in linear mixed models and applications to genetic association studies.

PubMed

Qu, Long; Guennel, Tobias; Marshall, Scott L

2013-12-01

Following the rapid development of genome-scale genotyping technologies, genetic association mapping has become a popular tool to detect genomic regions responsible for certain (disease) phenotypes, especially in early-phase pharmacogenomic studies with limited sample size. In response to such applications, a good association test needs to be (1) applicable to a wide range of possible genetic models, including, but not limited to, the presence of gene-by-environment or gene-by-gene interactions and non-linearity of a group of marker effects, (2) accurate in small samples, fast to compute on the genomic scale, and amenable to large scale multiple testing corrections, and (3) reasonably powerful to locate causal genomic regions. The kernel machine method represented in linear mixed models provides a viable solution by transforming the problem into testing the nullity of variance components. In this study, we consider score-based tests by choosing a statistic linear in the score function. When the model under the null hypothesis has only one error variance parameter, our test is exact in finite samples. When the null model has more than one variance parameter, we develop a new moment-based approximation that performs well in simulations. Through simulations and analysis of real data, we demonstrate that the new test possesses most of the aforementioned characteristics, especially when compared to existing quadratic score tests or restricted likelihood ratio tests. © 2013, The International Biometric Society.

B4GALNT2 (GALGT2) Gene Therapy Reduces Skeletal Muscle Pathology in the FKRP P448L Mouse Model of Limb Girdle Muscular Dystrophy 2I.

PubMed

Thomas, Paul J; Xu, Rui; Martin, Paul T

2016-09-01

Overexpression of B4GALNT2 (previously GALGT2) inhibits the development of muscle pathology in mouse models of Duchenne muscular dystrophy, congenital muscular dystrophy 1A, and limb girdle muscular dystrophy 2D. In these models, muscle GALGT2 overexpression induces the glycosylation of α dystroglycan with the cytotoxic T cell glycan and increases the overexpression of dystrophin and laminin α2 surrogates known to inhibit disease. Here, we show that GALGT2 gene therapy significantly reduces muscle pathology in FKRP P448Lneo(-) mice, a model for limb girdle muscular dystrophy 2I. rAAVrh74.MCK.GALGT2-treated FKRP P448Lneo(-) muscles showed reduced levels of centrally nucleated myofibers, reduced variance, increased size of myofiber diameters, reduced myofiber immunoglobulin G uptake, and reduced muscle wasting at 3 and 6 months after treatment. GALGT2 overexpression in FKRP P448Lneo(-) muscles did not cause substantial glycosylation of α dystroglycan with the cytotoxic T cell glycan or increased expression of dystrophin and laminin α2 surrogates in mature skeletal myofibers, but it increased the number of embryonic myosin-positive regenerating myofibers. These data demonstrate that GALGT2 overexpression can reduce the extent of muscle pathology in FKRP mutant muscles, but that it may do so via a mechanism that differs from its ability to induce surrogate gene expression. Copyright © 2016 American Society for Investigative Pathology. Published by Elsevier Inc. All rights reserved.

GEM-TREND: a web tool for gene expression data mining toward relevant network discovery

PubMed Central

Feng, Chunlai; Araki, Michihiro; Kunimoto, Ryo; Tamon, Akiko; Makiguchi, Hiroki; Niijima, Satoshi; Tsujimoto, Gozoh; Okuno, Yasushi

2009-01-01

Background DNA microarray technology provides us with a first step toward the goal of uncovering gene functions on a genomic scale. In recent years, vast amounts of gene expression data have been collected, much of which are available in public databases, such as the Gene Expression Omnibus (GEO). To date, most researchers have been manually retrieving data from databases through web browsers using accession numbers (IDs) or keywords, but gene-expression patterns are not considered when retrieving such data. The Connectivity Map was recently introduced to compare gene expression data by introducing gene-expression signatures (represented by a set of genes with up- or down-regulated labels according to their biological states) and is available as a web tool for detecting similar gene-expression signatures from a limited data set (approximately 7,000 expression profiles representing 1,309 compounds). In order to support researchers to utilize the public gene expression data more effectively, we developed a web tool for finding similar gene expression data and generating its co-expression networks from a publicly available database. Results GEM-TREND, a web tool for searching gene expression data, allows users to search data from GEO using gene-expression signatures or gene expression ratio data as a query and retrieve gene expression data by comparing gene-expression pattern between the query and GEO gene expression data. The comparison methods are based on the nonparametric, rank-based pattern matching approach of Lamb et al. (Science 2006) with the additional calculation of statistical significance. The web tool was tested using gene expression ratio data randomly extracted from the GEO and with in-house microarray data, respectively. The results validated the ability of GEM-TREND to retrieve gene expression entries biologically related to a query from GEO. For further analysis, a network visualization interface is also provided, whereby genes and gene annotations are dynamically linked to external data repositories. Conclusion GEM-TREND was developed to retrieve gene expression data by comparing query gene-expression pattern with those of GEO gene expression data. It could be a very useful resource for finding similar gene expression profiles and constructing its gene co-expression networks from a publicly available database. GEM-TREND was designed to be user-friendly and is expected to support knowledge discovery. GEM-TREND is freely available at . PMID:19728865

GEM-TREND: a web tool for gene expression data mining toward relevant network discovery.

PubMed

Feng, Chunlai; Araki, Michihiro; Kunimoto, Ryo; Tamon, Akiko; Makiguchi, Hiroki; Niijima, Satoshi; Tsujimoto, Gozoh; Okuno, Yasushi

2009-09-03

DNA microarray technology provides us with a first step toward the goal of uncovering gene functions on a genomic scale. In recent years, vast amounts of gene expression data have been collected, much of which are available in public databases, such as the Gene Expression Omnibus (GEO). To date, most researchers have been manually retrieving data from databases through web browsers using accession numbers (IDs) or keywords, but gene-expression patterns are not considered when retrieving such data. The Connectivity Map was recently introduced to compare gene expression data by introducing gene-expression signatures (represented by a set of genes with up- or down-regulated labels according to their biological states) and is available as a web tool for detecting similar gene-expression signatures from a limited data set (approximately 7,000 expression profiles representing 1,309 compounds). In order to support researchers to utilize the public gene expression data more effectively, we developed a web tool for finding similar gene expression data and generating its co-expression networks from a publicly available database. GEM-TREND, a web tool for searching gene expression data, allows users to search data from GEO using gene-expression signatures or gene expression ratio data as a query and retrieve gene expression data by comparing gene-expression pattern between the query and GEO gene expression data. The comparison methods are based on the nonparametric, rank-based pattern matching approach of Lamb et al. (Science 2006) with the additional calculation of statistical significance. The web tool was tested using gene expression ratio data randomly extracted from the GEO and with in-house microarray data, respectively. The results validated the ability of GEM-TREND to retrieve gene expression entries biologically related to a query from GEO. For further analysis, a network visualization interface is also provided, whereby genes and gene annotations are dynamically linked to external data repositories. GEM-TREND was developed to retrieve gene expression data by comparing query gene-expression pattern with those of GEO gene expression data. It could be a very useful resource for finding similar gene expression profiles and constructing its gene co-expression networks from a publicly available database. GEM-TREND was designed to be user-friendly and is expected to support knowledge discovery. GEM-TREND is freely available at http://cgs.pharm.kyoto-u.ac.jp/services/network.

Inheritance of downy mildew (Plasmopara viticola) and anthracnose (Sphaceloma ampelinum) resistance in grapevines.

PubMed

Poolsawat, O; Mahanil, S; Laosuwan, P; Wongkaew, S; Tharapreuksapong, A; Reisch, B I; Tantasawat, P A

2013-12-13

Downy mildew (Plasmopara viticola) and anthracnose (Sphaceloma ampelinum) are two of the major diseases of most grapevine (Vitis vinifera L.) cultivars grown in Thailand. Therefore, breeding grapevines for improved downy mildew and anthracnose resistance is crucial. Factorial crosses were made between three downy mildew and/or anthracnose resistant lines ('NY88.0517.01', 'NY65.0550.04', and 'NY65.0551.05'; male parents) and two or three susceptible cultivars of V. vinifera ('Black Queen', 'Carolina Black Rose', and/or 'Italia'; female parents). F1 hybrid seedlings were evaluated for downy mildew and anthracnose resistance using a detached/excised leaf assay. For both diseases, the general combining ability (GCA) variance among male parents was significant, while the variance of GCA among females and the specific combining ability (SCA) variance were not significant, indicating the prevalence of additive over non-additive gene actions. The estimated narrow sense heritabilities of downy mildew and anthracnose resistance were 55.6 and 79.2%, respectively, suggesting that downy mildew/anthracnose resistance gene(s) were highly heritable. The 'Carolina Black Rose x NY65.0550.04' cross combination is recommended for future use.

Adaptive linear rank tests for eQTL studies

PubMed Central

Szymczak, Silke; Scheinhardt, Markus O.; Zeller, Tanja; Wild, Philipp S.; Blankenberg, Stefan; Ziegler, Andreas

2013-01-01

Expression quantitative trait loci (eQTL) studies are performed to identify single-nucleotide polymorphisms that modify average expression values of genes, proteins, or metabolites, depending on the genotype. As expression values are often not normally distributed, statistical methods for eQTL studies should be valid and powerful in these situations. Adaptive tests are promising alternatives to standard approaches, such as the analysis of variance or the Kruskal–Wallis test. In a two-stage procedure, skewness and tail length of the distributions are estimated and used to select one of several linear rank tests. In this study, we compare two adaptive tests that were proposed in the literature using extensive Monte Carlo simulations of a wide range of different symmetric and skewed distributions. We derive a new adaptive test that combines the advantages of both literature-based approaches. The new test does not require the user to specify a distribution. It is slightly less powerful than the locally most powerful rank test for the correct distribution and at least as powerful as the maximin efficiency robust rank test. We illustrate the application of all tests using two examples from different eQTL studies. PMID:22933317

Adaptive linear rank tests for eQTL studies.

PubMed

Szymczak, Silke; Scheinhardt, Markus O; Zeller, Tanja; Wild, Philipp S; Blankenberg, Stefan; Ziegler, Andreas

2013-02-10

Expression quantitative trait loci (eQTL) studies are performed to identify single-nucleotide polymorphisms that modify average expression values of genes, proteins, or metabolites, depending on the genotype. As expression values are often not normally distributed, statistical methods for eQTL studies should be valid and powerful in these situations. Adaptive tests are promising alternatives to standard approaches, such as the analysis of variance or the Kruskal-Wallis test. In a two-stage procedure, skewness and tail length of the distributions are estimated and used to select one of several linear rank tests. In this study, we compare two adaptive tests that were proposed in the literature using extensive Monte Carlo simulations of a wide range of different symmetric and skewed distributions. We derive a new adaptive test that combines the advantages of both literature-based approaches. The new test does not require the user to specify a distribution. It is slightly less powerful than the locally most powerful rank test for the correct distribution and at least as powerful as the maximin efficiency robust rank test. We illustrate the application of all tests using two examples from different eQTL studies. Copyright © 2012 John Wiley & Sons, Ltd.

An empirical likelihood ratio test robust to individual heterogeneity for differential expression analysis of RNA-seq.

PubMed

Xu, Maoqi; Chen, Liang

2018-01-01

The individual sample heterogeneity is one of the biggest obstacles in biomarker identification for complex diseases such as cancers. Current statistical models to identify differentially expressed genes between disease and control groups often overlook the substantial human sample heterogeneity. Meanwhile, traditional nonparametric tests lose detailed data information and sacrifice the analysis power, although they are distribution free and robust to heterogeneity. Here, we propose an empirical likelihood ratio test with a mean-variance relationship constraint (ELTSeq) for the differential expression analysis of RNA sequencing (RNA-seq). As a distribution-free nonparametric model, ELTSeq handles individual heterogeneity by estimating an empirical probability for each observation without making any assumption about read-count distribution. It also incorporates a constraint for the read-count overdispersion, which is widely observed in RNA-seq data. ELTSeq demonstrates a significant improvement over existing methods such as edgeR, DESeq, t-tests, Wilcoxon tests and the classic empirical likelihood-ratio test when handling heterogeneous groups. It will significantly advance the transcriptomics studies of cancers and other complex disease. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Reasoning over genetic variance information in cause-and-effect models of neurodegenerative diseases

PubMed Central

Naz, Mufassra; Kodamullil, Alpha Tom

2016-01-01

The work we present here is based on the recent extension of the syntax of the Biological Expression Language (BEL), which now allows for the representation of genetic variation information in cause-and-effect models. In our article, we describe, how genetic variation information can be used to identify candidate disease mechanisms in diseases with complex aetiology such as Alzheimer’s disease and Parkinson’s disease. In those diseases, we have to assume that many genetic variants contribute moderately to the overall dysregulation that in the case of neurodegenerative diseases has such a long incubation time until the first clinical symptoms are detectable. Owing to the multilevel nature of dysregulation events, systems biomedicine modelling approaches need to combine mechanistic information from various levels, including gene expression, microRNA (miRNA) expression, protein–protein interaction, genetic variation and pathway. OpenBEL, the open source version of BEL, has recently been extended to match this requirement, and we demonstrate in our article, how candidate mechanisms for early dysregulation events in Alzheimer’s disease can be identified based on an integrative mining approach that identifies ‘chains of causation’ that include single nucleotide polymorphism information in BEL models. PMID:26249223

Neighboring Genes Show Correlated Evolution in Gene Expression

PubMed Central

Ghanbarian, Avazeh T.; Hurst, Laurence D.

2015-01-01

When considering the evolution of a gene’s expression profile, we commonly assume that this is unaffected by its genomic neighborhood. This is, however, in contrast to what we know about the lack of autonomy between neighboring genes in gene expression profiles in extant taxa. Indeed, in all eukaryotic genomes genes of similar expression-profile tend to cluster, reflecting chromatin level dynamics. Does it follow that if a gene increases expression in a particular lineage then the genomic neighbors will also increase in their expression or is gene expression evolution autonomous? To address this here we consider evolution of human gene expression since the human-chimp common ancestor, allowing for both variation in estimation of current expression level and error in Bayesian estimation of the ancestral state. We find that in all tissues and both sexes, the change in gene expression of a focal gene on average predicts the change in gene expression of neighbors. The effect is highly pronounced in the immediate vicinity (<100 kb) but extends much further. Sex-specific expression change is also genomically clustered. As genes increasing their expression in humans tend to avoid nuclear lamina domains and be enriched for the gene activator 5-hydroxymethylcytosine, we conclude that, most probably owing to chromatin level control of gene expression, a change in gene expression of one gene likely affects the expression evolution of neighbors, what we term expression piggybacking, an analog of hitchhiking. PMID:25743543

Conjugated linoleic acid influences the metabolism of tocopherol in lactating rats but has little effect on tissue tocopherol concentrations in pups.

PubMed

Zeitz, Johanna O; Most, Erika; Eder, Klaus

2016-05-31

Conjugated linoleic acid (CLA) is known to affect the lipid metabolism in growing and lactating animals. However, potential effects on the metabolism of fat-soluble vitamins in lactating animals and co-occurring effects on their offspring are unknown. We aimed to investigate the effects of dietary CLA on concentrations of tocopherol in various tissues of lactating rats and their offspring and expression of genes involved in tocopherol metabolism. Twenty-eight Wistar Han rats were allocated to 2 groups and fed either a control diet (control group) or a diet containing 0.9 % of cis-9, trans-11 and trans-10, cis-12 (1:1) CLA (CLA group) during pregnancy and lactation. Feed intake of dams and body weight of dams and their pups were recorded weekly. Tocopherol concentrations in various body tissues were determined at day 14 of lactation in dams and 1, 7 and 14 days after birth in pups. Expression of selected genes involved in metabolism of tocopherol was determined in dams and pups. The data were statistically analysed by analysis of variance. Feed intake and body weight development of nursing rats and their pups was similar in both groups. In livers of CLA-fed dams, tocopherol concentrations decreased by 24 % but expression of TTPA and CYP3A1, involved in tocopherol transport and metabolism, were not influenced. In the dams' adipose tissue, gene expression of receptors involved in tissue tocopherol uptake, LDLR and SCARB1, but not of LPL, increased by 30 to 50 % and tocopherol concentrations increased by 47 % in CLA-fed compared to control dams. Expression of LPL, LDLR and SCARB1 in mammary gland was not influenced by CLA-feeding. Tocopherol concentrations in the pup's livers and lungs were similar in both groups, but at 14 days of age, adipose tissue tocopherol concentrations, and LDLR and SCARB1 expression, were higher in the CLA-exposed pups. We show that dietary CLA affects tissue concentrations of tocopherol in lactating rats and tocopherol metabolism in rats and pups, but hardly influences tissue tocopherol concentrations in their offspring. This indicates that supplementation of CLA in pregnant and lactating animals is uncritical considering the tocopherol status of new-borns.

Neighboring Genes Show Correlated Evolution in Gene Expression.

PubMed

Ghanbarian, Avazeh T; Hurst, Laurence D

2015-07-01

When considering the evolution of a gene's expression profile, we commonly assume that this is unaffected by its genomic neighborhood. This is, however, in contrast to what we know about the lack of autonomy between neighboring genes in gene expression profiles in extant taxa. Indeed, in all eukaryotic genomes genes of similar expression-profile tend to cluster, reflecting chromatin level dynamics. Does it follow that if a gene increases expression in a particular lineage then the genomic neighbors will also increase in their expression or is gene expression evolution autonomous? To address this here we consider evolution of human gene expression since the human-chimp common ancestor, allowing for both variation in estimation of current expression level and error in Bayesian estimation of the ancestral state. We find that in all tissues and both sexes, the change in gene expression of a focal gene on average predicts the change in gene expression of neighbors. The effect is highly pronounced in the immediate vicinity (<100 kb) but extends much further. Sex-specific expression change is also genomically clustered. As genes increasing their expression in humans tend to avoid nuclear lamina domains and be enriched for the gene activator 5-hydroxymethylcytosine, we conclude that, most probably owing to chromatin level control of gene expression, a change in gene expression of one gene likely affects the expression evolution of neighbors, what we term expression piggybacking, an analog of hitchhiking. © The Author 2015. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Gene variants associated with antisocial behaviour: A latent variable approach

PubMed Central

Bentley, Mary Jane; Lin, Haiqun; Fernandez, Thomas V.; Lee, Maria; Yrigollen, Carolyn M.; Pakstis, Andrew J.; Katsovich, Liliya; Olds, David L.; Grigorenko, Elena L.; Leckman, James F.

2013-01-01

Objective The aim of this study was to determine if a latent variable approach might be useful in identifying shared variance across genetic risk alleles that is associated with antisocial behaviour at age 15 years. Methods Using a conventional latent variable approach, we derived an antisocial phenotype in 328 adolescents utilizing data from a 15-year follow-up of a randomized trial of a prenatal and infancy nurse-home visitation program in Elmira, New York. We then investigated, via a novel latent variable approach, 450 informative genetic polymorphisms in 71 genes previously associated with antisocial behaviour, drug use, affiliative behaviours, and stress response in 241 consenting individuals for whom DNA was available. Haplotype and Pathway analyses were also performed. Results Eight single-nucleotide polymorphisms (SNPs) from 8 genes contributed to the latent genetic variable that in turn accounted for 16.0% of the variance within the latent antisocial phenotype. The number of risk alleles was linearly related to the latent antisocial variable scores. Haplotypes that included the putative risk alleles for all 8 genes were also associated with higher latent antisocial variable scores. In addition, 33 SNPs from 63 of the remaining genes were also significant when added to the final model. Many of these genes interact on a molecular level, forming molecular networks. The results support a role for genes related to dopamine, norepinephrine, serotonin, glutamate, opioid, and cholinergic signaling as well as stress response pathways in mediating susceptibility to antisocial behaviour. Conclusions This preliminary study supports use of relevant behavioural indicators and latent variable approaches to study the potential “co-action” of gene variants associated with antisocial behaviour. It also underscores the cumulative relevance of common genetic variants for understanding the etiology of complex behaviour. If replicated in future studies, this approach may allow the identification of a ‘shared’ variance across genetic risk alleles associated with complex neuropsychiatric dimensional phenotypes using relatively small numbers of well-characterized research participants. PMID:23822756

Decomposing genomic variance using information from GWA, GWE and eQTL analysis.

PubMed

Ehsani, A; Janss, L; Pomp, D; Sørensen, P

2016-04-01

A commonly used procedure in genome-wide association (GWA), genome-wide expression (GWE) and expression quantitative trait locus (eQTL) analyses is based on a bottom-up experimental approach that attempts to individually associate molecular variants with complex traits. Top-down modeling of the entire set of genomic data and partitioning of the overall variance into subcomponents may provide further insight into the genetic basis of complex traits. To test this approach, we performed a whole-genome variance components analysis and partitioned the genomic variance using information from GWA, GWE and eQTL analyses of growth-related traits in a mouse F2 population. We characterized the mouse trait genetic architecture by ordering single nucleotide polymorphisms (SNPs) based on their P-values and studying the areas under the curve (AUCs). The observed traits were found to have a genomic variance profile that differed significantly from that expected of a trait under an infinitesimal model. This situation was particularly true for both body weight and body fat, for which the AUCs were much higher compared with that of glucose. In addition, SNPs with a high degree of trait-specific regulatory potential (SNPs associated with subset of transcripts that significantly associated with a specific trait) explained a larger proportion of the genomic variance than did SNPs with high overall regulatory potential (SNPs associated with transcripts using traditional eQTL analysis). We introduced AUC measures of genomic variance profiles that can be used to quantify relative importance of SNPs as well as degree of deviation of a trait's inheritance from an infinitesimal model. The shape of the curve aids global understanding of traits: The steeper the left-hand side of the curve, the fewer the number of SNPs controlling most of the phenotypic variance. © 2015 Stichting International Foundation for Animal Genetics.

Monoamine Oxidase-A Genetic Variants and Childhood Abuse Predict Impulsiveness in Borderline Personality Disorder.

PubMed

Kolla, Nathan J; Meyer, Jeffrey; Sanches, Marcos; Charbonneau, James

2017-11-30

Impulsivity is a core feature of borderline personality disorder (BPD) and antisocial personality disorder (ASPD) that likely arises from combined genetic and environmental influences. The interaction of the low activity variant of the monoamine oxidase-A (MAOA-L) gene and early childhood adversity has been shown to predict aggression in clinical and non-clinical populations. Although impulsivity is a risk factor for aggression in BPD and ASPD, little research has investigated potential gene-environment (G×E) influences impacting its expression in these conditions. Moreover, G×E interactions may differ by diagnosis. Full factorial analysis of variance was employed to investigate the influence of monoamine oxidase-A (MAO-A) genotype, childhood abuse, and diagnosis on Barratt Impulsiveness Scale-11 (BIS-11) scores in 61 individuals: 20 subjects with BPD, 18 subjects with ASPD, and 23 healthy controls. A group×genotype×abuse interaction was present (F(2,49)=4.4, p =0.018), such that the interaction of MAOA-L and childhood abuse predicted greater BIS-11 motor impulsiveness in BPD. Additionally, BPD subjects reported higher BIS-11 attentional impulsiveness versus ASPD participants (t(1,36)=2.3, p =0.025). These preliminary results suggest that MAOA-L may modulate the impact of childhood abuse on impulsivity in BPD. Results additionally indicate that impulsiveness may be expressed differently in BPD and ASPD.

Application of community phylogenetic approaches to understand gene expression: differential exploration of venom gene space in predatory marine gastropods.

PubMed

Chang, Dan; Duda, Thomas F

2014-06-05

Predatory marine gastropods of the genus Conus exhibit substantial variation in venom composition both within and among species. Apart from mechanisms associated with extensive turnover of gene families and rapid evolution of genes that encode venom components ('conotoxins'), the evolution of distinct conotoxin expression patterns is an additional source of variation that may drive interspecific differences in the utilization of species' 'venom gene space'. To determine the evolution of expression patterns of venom genes of Conus species, we evaluated the expression of A-superfamily conotoxin genes of a set of closely related Conus species by comparing recovered transcripts of A-superfamily genes that were previously identified from the genomes of these species. We modified community phylogenetics approaches to incorporate phylogenetic history and disparity of genes and their expression profiles to determine patterns of venom gene space utilization. Less than half of the A-superfamily gene repertoire of these species is expressed, and only a few orthologous genes are coexpressed among species. Species exhibit substantially distinct expression strategies, with some expressing sets of closely related loci ('under-dispersed' expression of available genes) while others express sets of more disparate genes ('over-dispersed' expression). In addition, expressed genes show higher dN/dS values than either unexpressed or ancestral genes; this implies that expression exposes genes to selection and facilitates rapid evolution of these genes. Few recent lineage-specific gene duplicates are expressed simultaneously, suggesting that expression divergence among redundant gene copies may be established shortly after gene duplication. Our study demonstrates that venom gene space is explored differentially by Conus species, a process that effectively permits the independent and rapid evolution of venoms in these species.

Modulation of gene expression as a new skin anti-aging strategy.

PubMed

Talbourdet, Sylvie; Sadick, Neil S; Lazou, Kristell; Bonnet-Duquennoy, Mathilde; Kurfurst, Robin; Neveu, Michele; Heusèle, Catherine; André, Patrice; Schnebert, Sylvianne; Draelos, Zoe D; Perrier, Eric

2007-06-01

[corrected] The signs of aging may originate from natural processes or from exposure to the sun, wind, or other environmental factors. To evaluate the anti-aging effects of potential agents researchers must first identify and be able to quantify epidermal markers that change with aging. This paper summarizes the results of studies conducted to evaluate the transcriptional effects of an Aframomum angustifolium seed extract and Malva Sylvestris extract, and the antiaging efficacy of a skin care product containing the Aframomum angustifolium seed extract. The transcriptional effect of an Aframomum angustifolium seed extract on normal human keratinocytes (NHKs) and normal human fibroblasts (NHF) was evaluated in vitro with the use of a low-density DNA array technology. The Malva Sylvestris extract was studied with a commercial DNA macroarray and by a real-time quantitative reverse transcriptase-polymerase chain reaction. The in vitro anti-aging activities of the Malva sylvestris extract were compared with those of all-trans retinoic acid (RA), a well-established topical therapy for photodamage and wrinkles. The genes studied were known to be modified by RA. The anti-aging efficacy of a facial skin care product containing Aframomum angustifolium seed extract was evaluated in a single-center study using image processing analysis and in a 2-center study by evaluation of the photographs by the investigator, independent evaluators, and subjects. In general, the Aframomum angustifolium seed extract strongly modified the gene expression profiles of NHKs and weakly modified the gene expression profiles of NHFs. After incubation with Aframomum angustifolium seed extract, the expressions of 3 antioxidant genes (metallothionein 1, metallothionein 2, and thioredoxin) were increased in NHKs, while expressions of 1 antioxidant gene (glutathione peroxidase) was increased in NHFs. Concerning the Malva sylvestris extract, a cDNA macro-array technology experiment with the reconstructed human epidermis model showed that some genes modulated by treatment with the Malva sylvestris extract are also regulated by RA treatment indicating a similar activity at the mRNA level. In the single-center study, a facial skin care product containing the Aframomum angustifolium seed extract significantly improved the homogeneity of the skin. The areas of the detected objects (skin imperfections) decreased significantly on each studied area of the face and the variance decreased significantly over the entire face. In the 2-center study, 28% percent of the subjects reported a greater than 50% overall global improvement in their skin by the end of the study compared to 11% of the subjects after 4 weeks of treatment. Seventy-six percent of subjects said they would purchase the cream. The authors developed a low-density DNA chip method that permitted the study of the transcriptional effect of Malva Sylvestris extract and of Aframomum angustrifolium seed extract. The gene expression profiles obtained demonstrate the anti-aging properties of these compounds. An in vivo single-center study, performed and analyzed with an assay based on image processing analysis, demonstrated the antiwrinkle activity of a formulation containing the Aframomum angustifolium seed extract. The data obtained in the 2-center study suggests that the cosmeceutical containing Aframomum angustifolium seed extract produces a global rejuvenation effect in terms of redness, pigmentation, and fine lines similar to that noted utilizing an intense pulse light source.

Association Genetics of Wood Physical Traits in the Conifer White Spruce and Relationships With Gene Expression

PubMed Central

Beaulieu, Jean; Doerksen, Trevor; Boyle, Brian; Clément, Sébastien; Deslauriers, Marie; Beauseigle, Stéphanie; Blais, Sylvie; Poulin, Pier-Luc; Lenz, Patrick; Caron, Sébastien; Rigault, Philippe; Bicho, Paul; Bousquet, Jean; MacKay, John

2011-01-01

Marker-assisted selection holds promise for highly influencing tree breeding, especially for wood traits, by considerably reducing breeding cycles and increasing selection accuracy. In this study, we used a candidate gene approach to test for associations between 944 single-nucleotide polymorphism markers from 549 candidate genes and 25 wood quality traits in white spruce. A mixed-linear model approach, including a weak but nonsignificant population structure, was implemented for each marker–trait combination. Relatedness among individuals was controlled using a kinship matrix estimated either from the known half-sib structure or from the markers. Both additive and dominance effect models were tested. Between 8 and 21 single-nucleotide polymorphisms (SNPs) were found to be significantly associated (P ≤ 0.01) with each of earlywood, latewood, or total wood traits. After controlling for multiple testing (Q ≤ 0.10), 13 SNPs were still significant across as many genes belonging to different families, each accounting for between 3 and 5% of the phenotypic variance in 10 wood characters. Transcript accumulation was determined for genes containing SNPs associated with these traits. Significantly different transcript levels (P ≤ 0.05) were found among the SNP genotypes of a 1-aminocyclopropane-1-carboxylate oxidase, a β-tonoplast intrinsic protein, and a long-chain acyl-CoA synthetase 9. These results should contribute toward the development of efficient marker-assisted selection in an economically important tree species. PMID:21385726

TMPRSS2:ERG Gene Fusions in Prostate Cancer of West African Men and a Meta-Analysis of Racial Differences

PubMed Central

Zhou, Cindy Ke; Young, Denise; Yeboah, Edward D; Coburn, Sally B; Tettey, Yao; Biritwum, Richard B; Adjei, Andrew A; Tay, Evelyn; Niwa, Shelley; Truelove, Ann; Welsh, Judith; Mensah, James E; Hoover, Robert N; Sesterhenn, Isabell A; Hsing, Ann W; Srivastava, Shiv; Cook, Michael B

2017-01-01

Abstract The prevalence of fusions of the transmembrane protease, serine 2, gene (TMPRSS2) with the erythroblast transformation-specific–related gene (ERG), or TMPRSS2:ERG, in prostate cancer varies by race. However, such somatic aberration and its association with prognostic factors have neither been studied in a West African population nor been systematically reviewed in the context of racial differences. We used immunohistochemistry to assess oncoprotein encoded by the ERG gene as the established surrogate of ERG fusion genes among 262 prostate cancer biopsies from the Ghana Prostate Study (2004–2006). Poisson regression with robust variance estimation provided prevalence ratios and 95% confidence intervals of ERG expression in relation to patient characteristics. We found that 47 of 262 (18%) prostate cancers were ERG-positive, and being negative for ERG staining was associated with higher Gleason score. We further conducted a systematic review and meta-analysis of TMPRSS2:ERG fusions in relation to race, Gleason score, and tumor stage, combining results from Ghana with 40 additional studies. Meta-analysis showed the prevalence of TMPRSS2:ERG fusions in prostate cancer to be highest in men of European descent (49%), followed by men of Asian (27%) and then African (25%) descent. The lower prevalence of TMPRSS2:ERG fusions in men of African descent implies that alternative genomic mechanisms might explain the disproportionately high prostate cancer burden in such populations. PMID:28633309

Genome-wide meta-analysis identifies novel determinants of circulating serum progranulin.

PubMed

Tönjes, Anke; Scholz, Markus; Krüger, Jacqueline; Krause, Kerstin; Schleinitz, Dorit; Kirsten, Holger; Gebhardt, Claudia; Marzi, Carola; Grallert, Harald; Ladenvall, Claes; Heyne, Henrike; Laurila, Esa; Kriebel, Jennifer; Meisinger, Christa; Rathmann, Wolfgang; Gieger, Christian; Groop, Leif; Prokopenko, Inga; Isomaa, Bo; Beutner, Frank; Kratzsch, Jürgen; Fischer-Rosinsky, Antje; Pfeiffer, Andreas; Krohn, Knut; Spranger, Joachim; Thiery, Joachim; Blüher, Matthias; Stumvoll, Michael; Kovacs, Peter

2018-02-01

Progranulin is a secreted protein with important functions in processes including immune and inflammatory response, metabolism and embryonic development. The present study aimed at identification of genetic factors determining progranulin concentrations. We conducted a genome-wide association meta-analysis for serum progranulin in three independent cohorts from Europe: Sorbs (N = 848) and KORA (N = 1628) from Germany and PPP-Botnia (N = 335) from Finland (total N = 2811). Single nucleotide polymorphisms (SNPs) associated with progranulin levels were replicated in two additional German cohorts: LIFE-Heart Study (Leipzig; N = 967) and Metabolic Syndrome Berlin Potsdam (Berlin cohort; N = 833). We measured mRNA expression of genes in peripheral blood mononuclear cells (PBMC) by micro-arrays and performed mRNA expression quantitative trait and expression-progranulin association studies to functionally substantiate identified loci. Finally, we conducted siRNA silencing experiments in vitro to validate potential candidate genes within the associated loci. Heritability of circulating progranulin levels was estimated at 31.8% and 26.1% in the Sorbs and LIFE-Heart cohort, respectively. SNPs at three loci reached study-wide significance (rs660240 in CELSR2-PSRC1-MYBPHL-SORT1, rs4747197 in CDH23-PSAP and rs5848 in GRN) explaining 19.4%/15.0% of the variance and 61%/57% of total heritability in the Sorbs/LIFE-Heart Study. The strongest evidence for association was at rs660240 (P = 5.75 × 10-50), which was also associated with mRNA expression of PSRC1 in PBMC (P = 1.51 × 10-21). Psrc1 knockdown in murine preadipocytes led to a consecutive 30% reduction in progranulin secretion. In conclusion, the present meta-GWAS combined with mRNA expression identified three loci associated with progranulin and supports the role of PSRC1 in the regulation of progranulin secretion. © The Author(s) 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

FARO server: Meta-analysis of gene expression by matching gene expression signatures to a compendium of public gene expression data.

PubMed

Manijak, Mieszko P; Nielsen, Henrik B

2011-06-11

Although, systematic analysis of gene annotation is a powerful tool for interpreting gene expression data, it sometimes is blurred by incomplete gene annotation, missing expression response of key genes and secondary gene expression responses. These shortcomings may be partially circumvented by instead matching gene expression signatures to signatures of other experiments. To facilitate this we present the Functional Association Response by Overlap (FARO) server, that match input signatures to a compendium of 242 gene expression signatures, extracted from more than 1700 Arabidopsis microarray experiments. Hereby we present a publicly available tool for robust characterization of Arabidopsis gene expression experiments which can point to similar experimental factors in other experiments. The server is available at http://www.cbs.dtu.dk/services/faro/.

Genomic analyses identify hundreds of variants associated with age at menarche and support a role for puberty timing in cancer risk.

PubMed

Day, Felix R; Thompson, Deborah J; Helgason, Hannes; Chasman, Daniel I; Finucane, Hilary; Sulem, Patrick; Ruth, Katherine S; Whalen, Sean; Sarkar, Abhishek K; Albrecht, Eva; Altmaier, Elisabeth; Amini, Marzyeh; Barbieri, Caterina M; Boutin, Thibaud; Campbell, Archie; Demerath, Ellen; Giri, Ayush; He, Chunyan; Hottenga, Jouke J; Karlsson, Robert; Kolcic, Ivana; Loh, Po-Ru; Lunetta, Kathryn L; Mangino, Massimo; Marco, Brumat; McMahon, George; Medland, Sarah E; Nolte, Ilja M; Noordam, Raymond; Nutile, Teresa; Paternoster, Lavinia; Perjakova, Natalia; Porcu, Eleonora; Rose, Lynda M; Schraut, Katharina E; Segrè, Ayellet V; Smith, Albert V; Stolk, Lisette; Teumer, Alexander; Andrulis, Irene L; Bandinelli, Stefania; Beckmann, Matthias W; Benitez, Javier; Bergmann, Sven; Bochud, Murielle; Boerwinkle, Eric; Bojesen, Stig E; Bolla, Manjeet K; Brand, Judith S; Brauch, Hiltrud; Brenner, Hermann; Broer, Linda; Brüning, Thomas; Buring, Julie E; Campbell, Harry; Catamo, Eulalia; Chanock, Stephen; Chenevix-Trench, Georgia; Corre, Tanguy; Couch, Fergus J; Cousminer, Diana L; Cox, Angela; Crisponi, Laura; Czene, Kamila; Davey Smith, George; de Geus, Eco J C N; de Mutsert, Renée; De Vivo, Immaculata; Dennis, Joe; Devilee, Peter; Dos-Santos-Silva, Isabel; Dunning, Alison M; Eriksson, Johan G; Fasching, Peter A; Fernández-Rhodes, Lindsay; Ferrucci, Luigi; Flesch-Janys, Dieter; Franke, Lude; Gabrielson, Marike; Gandin, Ilaria; Giles, Graham G; Grallert, Harald; Gudbjartsson, Daniel F; Guénel, Pascal; Hall, Per; Hallberg, Emily; Hamann, Ute; Harris, Tamara B; Hartman, Catharina A; Heiss, Gerardo; Hooning, Maartje J; Hopper, John L; Hu, Frank; Hunter, David J; Ikram, M Arfan; Im, Hae Kyung; Järvelin, Marjo-Riitta; Joshi, Peter K; Karasik, David; Kellis, Manolis; Kutalik, Zoltan; LaChance, Genevieve; Lambrechts, Diether; Langenberg, Claudia; Launer, Lenore J; Laven, Joop S E; Lenarduzzi, Stefania; Li, Jingmei; Lind, Penelope A; Lindstrom, Sara; Liu, YongMei; Luan, Jian'an; Mägi, Reedik; Mannermaa, Arto; Mbarek, Hamdi; McCarthy, Mark I; Meisinger, Christa; Meitinger, Thomas; Menni, Cristina; Metspalu, Andres; Michailidou, Kyriaki; Milani, Lili; Milne, Roger L; Montgomery, Grant W; Mulligan, Anna M; Nalls, Mike A; Navarro, Pau; Nevanlinna, Heli; Nyholt, Dale R; Oldehinkel, Albertine J; O'Mara, Tracy A; Padmanabhan, Sandosh; Palotie, Aarno; Pedersen, Nancy; Peters, Annette; Peto, Julian; Pharoah, Paul D P; Pouta, Anneli; Radice, Paolo; Rahman, Iffat; Ring, Susan M; Robino, Antonietta; Rosendaal, Frits R; Rudan, Igor; Rueedi, Rico; Ruggiero, Daniela; Sala, Cinzia F; Schmidt, Marjanka K; Scott, Robert A; Shah, Mitul; Sorice, Rossella; Southey, Melissa C; Sovio, Ulla; Stampfer, Meir; Steri, Maristella; Strauch, Konstantin; Tanaka, Toshiko; Tikkanen, Emmi; Timpson, Nicholas J; Traglia, Michela; Truong, Thérèse; Tyrer, Jonathan P; Uitterlinden, André G; Edwards, Digna R Velez; Vitart, Veronique; Völker, Uwe; Vollenweider, Peter; Wang, Qin; Widen, Elisabeth; van Dijk, Ko Willems; Willemsen, Gonneke; Winqvist, Robert; Wolffenbuttel, Bruce H R; Zhao, Jing Hua; Zoledziewska, Magdalena; Zygmunt, Marek; Alizadeh, Behrooz Z; Boomsma, Dorret I; Ciullo, Marina; Cucca, Francesco; Esko, Tõnu; Franceschini, Nora; Gieger, Christian; Gudnason, Vilmundur; Hayward, Caroline; Kraft, Peter; Lawlor, Debbie A; Magnusson, Patrik K E; Martin, Nicholas G; Mook-Kanamori, Dennis O; Nohr, Ellen A; Polasek, Ozren; Porteous, David; Price, Alkes L; Ridker, Paul M; Snieder, Harold; Spector, Tim D; Stöckl, Doris; Toniolo, Daniela; Ulivi, Sheila; Visser, Jenny A; Völzke, Henry; Wareham, Nicholas J; Wilson, James F; Spurdle, Amanda B; Thorsteindottir, Unnur; Pollard, Katherine S; Easton, Douglas F; Tung, Joyce Y; Chang-Claude, Jenny; Hinds, David; Murray, Anna; Murabito, Joanne M; Stefansson, Kari; Ong, Ken K; Perry, John R B

2017-06-01

The timing of puberty is a highly polygenic childhood trait that is epidemiologically associated with various adult diseases. Using 1000 Genomes Project-imputed genotype data in up to ∼370,000 women, we identify 389 independent signals (P < 5 × 10 -8 ) for age at menarche, a milestone in female pubertal development. In Icelandic data, these signals explain ∼7.4% of the population variance in age at menarche, corresponding to ∼25% of the estimated heritability. We implicate ∼250 genes via coding variation or associated expression, demonstrating significant enrichment in neural tissues. Rare variants near the imprinted genes MKRN3 and DLK1 were identified, exhibiting large effects when paternally inherited. Mendelian randomization analyses suggest causal inverse associations, independent of body mass index (BMI), between puberty timing and risks for breast and endometrial cancers in women and prostate cancer in men. In aggregate, our findings highlight the complexity of the genetic regulation of puberty timing and support causal links with cancer susceptibility.

Genomic analyses identify hundreds of variants associated with age at menarche and support a role for puberty timing in cancer risk

PubMed Central

Day, Felix R; Thompson, Deborah J; Helgason, Hannes; Chasman, Daniel I; Finucane, Hilary; Sulem, Patrick; Ruth, Katherine S; Whalen, Sean; Sarkar, Abhishek K; Albrecht, Eva; Altmaier, Elisabeth; Amini, Marzyeh; Barbieri, Caterina M; Boutin, Thibaud; Campbell, Archie; Demerath, Ellen; Giri, Ayush; He, Chunyan; Hottenga, Jouke J; Karlsson, Robert; Kolcic, Ivana; Loh, Po-Ru; Lunetta, Kathryn L; Mangino, Massimo; Marco, Brumat; McMahon, George; Medland, Sarah E; Nolte, Ilja M; Noordam, Raymond; Nutile, Teresa; Paternoster, Lavinia; Perjakova, Natalia; Porcu, Eleonora; Rose, Lynda M; Schraut, Katharina E; Segrè, Ayellet V; Smith, Albert V; Stolk, Lisette; Teumer, Alexander; Andrulis, Irene L; Bandinelli, Stefania; Beckmann, Matthias W; Benitez, Javier; Bergmann, Sven; Bochud, Murielle; Boerwinkle, Eric; Bojesen, Stig E; Bolla, Manjeet K; Brand, Judith S; Brauch, Hiltrud; Brenner, Hermann; Broer, Linda; Brüning, Thomas; Buring, Julie E; Campbell, Harry; Catamo, Eulalia; Chanock, Stephen; Chenevix-Trench, Georgia; Corre, Tanguy; Couch, Fergus J; Cousminer, Diana L; Cox, Angela; Crisponi, Laura; Czene, Kamila; Smith, George Davey; de Geus, Eco JCN; de Mutsert, Renée; De Vivo, Immaculata; Dennis, Joe; Devilee, Peter; dos-Santos-Silva, Isabel; Dunning, Alison M; Eriksson, Johan G; Fasching, Peter A; Fernández-Rhodes, Lindsay; Ferrucci, Luigi; Flesch-Janys, Dieter; Franke, Lude; Gabrielson, Marike; Gandin, Ilaria; Giles, Graham G; Grallert, Harald; Gudbjartsson, Daniel F; Guénel, Pascal; Hall, Per; Hallberg, Emily; Hamann, Ute; Harris, Tamara B; Hartman, Catharina A; Heiss, Gerardo; Hooning, Maartje J; Hopper, John L; Hu, Frank; Hunter, David J; Ikram, M Arfan; Im, Hae Kyung; Järvelin, Marjo-Riitta; Joshi, Peter K; Karasik, David; Kellis, Manolis; Kutalik, Zoltan; LaChance, Genevieve; Lambrechts, Diether; Langenberg, Claudia; Launer, Lenore J; Laven, Joop S E; Lenarduzzi, Stefania; Li, Jingmei; Lind, Penelope A; Lindstrom, Sara; Liu, YongMei; Luan, Jian’an; Mägi, Reedik; Mannermaa, Arto; Mbarek, Hamdi; McCarthy, Mark I; Meisinger, Christa; Meitinger, Thomas; Menni, Cristina; Metspalu, Andres; Michailidou, Kyriaki; Milani, Lili; Milne, Roger L; Montgomery, Grant W; Mulligan, Anna M; Nalls, Mike A; Navarro, Pau; Nevanlinna, Heli; Nyholt, Dale R; Oldehinkel, Albertine J; O’Mara, Tracy A; Padmanabhan, Sandosh; Palotie, Aarno; Pedersen, Nancy; Peters, Annette; Peto, Julian; Pharoah, Paul D P; Pouta, Anneli; Radice, Paolo; Rahman, Iffat; Ring, Susan M; Robino, Antonietta; Rosendaal, Frits R; Rudan, Igor; Rueedi, Rico; Ruggiero, Daniela; Sala, Cinzia F; Schmidt, Marjanka K; Scott, Robert A; Shah, Mitul; Sorice, Rossella; Southey, Melissa C; Sovio, Ulla; Stampfer, Meir; Steri, Maristella; Strauch, Konstantin; Tanaka, Toshiko; Tikkanen, Emmi; Timpson, Nicholas J; Traglia, Michela; Truong, Thérèse; Tyrer, Jonathan P; Uitterlinden, André G; Velez Edwards, Digna R; Vitart, Veronique; Völker, Uwe; Vollenweider, Peter; Wang, Qin; Widen, Elisabeth; van Dijk, Ko Willems; Willemsen, Gonneke; Winqvist, Robert; Wolffenbuttel, Bruce H R; Zhao, Jing Hua; Zoledziewska, Magdalena; Zygmunt, Marek; Alizadeh, Behrooz Z; Boomsma, Dorret I; Ciullo, Marina; Cucca, Francesco; Esko, Tõnu; Franceschini, Nora; Gieger, Christian; Gudnason, Vilmundur; Hayward, Caroline; Kraft, Peter; Lawlor, Debbie A; Magnusson, Patrik K E; Martin, Nicholas G; Mook-Kanamori, Dennis O; Nohr, Ellen A; Polasek, Ozren; Porteous, David; Price, Alkes L; Ridker, Paul M; Snieder, Harold; Spector, Tim D; Stöckl, Doris; Toniolo, Daniela; Ulivi, Sheila; Visser, Jenny A; Völzke, Henry; Wareham, Nicholas J; Wilson, James F; Spurdle, Amanda B; Thorsteindottir, Unnur; Pollard, Katherine S; Easton, Douglas F; Tung, Joyce Y; Chang-Claude, Jenny; Hinds, David; Murray, Anna; Murabito, Joanne M; Stefansson, Kari; Ong, Ken K; Perry, John R B

2018-01-01

The timing of puberty is a highly polygenic childhood trait that is epidemiologically associated with various adult diseases. Using 1000 Genomes Project–imputed genotype data in up to ~370,000 women, we identify 389 independent signals (P < 5 × 10−8) for age at menarche, a milestone in female pubertal development. In Icelandic data, these signals explain ~7.4% of the population variance in age at menarche, corresponding to ~25% of the estimated heritability. We implicate ~250 genes via coding variation or associated expression, demonstrating significant enrichment in neural tissues. Rare variants near the imprinted genes MKRN3 and DLK1 were identified, exhibiting large effects when paternally inherited. Mendelian randomization analyses suggest causal inverse associations, independent of body mass index (BMI), between puberty timing and risks for breast and endometrial cancers in women and prostate cancer in men. In aggregate, our findings highlight the complexity of the genetic regulation of puberty timing and support causal links with cancer susceptibility. PMID:28436984

Epi-fingerprinting and epi-interventions for improved crop production and food quality

PubMed Central

Rodríguez López, Carlos M.; Wilkinson, Mike J.

2015-01-01

Increasing crop production at a time of rapid climate change represents the greatest challenge facing contemporary agricultural research. Our understanding of the genetic control of yield derives from controlled field experiments designed to minimize environmental variance. In spite of these efforts there is substantial residual variability among plants attributable to Genotype × Environment interactions. Recent advances in the field of epigenetics have revealed a plethora of gene control mechanisms that could account for much of this unassigned variation. These systems act as a regulatory interface between the perception of the environment and associated alterations in gene expression. Direct intervention of epigenetic control systems hold the enticing promise of creating new sources of variability that could enhance crop performance. Equally, understanding the relationship between various epigenetic states and responses of the crop to specific aspects of the growing environment (epigenetic fingerprinting) could allow for a more tailored approach to plant agronomy. In this review, we explore the many ways in which epigenetic interventions and epigenetic fingerprinting can be deployed for the improvement of crop production and quality. PMID:26097484

Digital gene expression analysis of the zebra finch genome

PubMed Central

2010-01-01

Background In order to understand patterns of adaptation and molecular evolution it is important to quantify both variation in gene expression and nucleotide sequence divergence. Gene expression profiling in non-model organisms has recently been facilitated by the advent of massively parallel sequencing technology. Here we investigate tissue specific gene expression patterns in the zebra finch (Taeniopygia guttata) with special emphasis on the genes of the major histocompatibility complex (MHC). Results Almost 2 million 454-sequencing reads from cDNA of six different tissues were assembled and analysed. A total of 11,793 zebra finch transcripts were represented in this EST data, indicating a transcriptome coverage of about 65%. There was a positive correlation between the tissue specificity of gene expression and non-synonymous to synonymous nucleotide substitution ratio of genes, suggesting that genes with a specialised function are evolving at a higher rate (or with less constraint) than genes with a more general function. In line with this, there was also a negative correlation between overall expression levels and expression specificity of contigs. We found evidence for expression of 10 different genes related to the MHC. MHC genes showed relatively tissue specific expression levels and were in general primarily expressed in spleen. Several MHC genes, including MHC class I also showed expression in brain. Furthermore, for all genes with highest levels of expression in spleen there was an overrepresentation of several gene ontology terms related to immune function. Conclusions Our study highlights the usefulness of next-generation sequence data for quantifying gene expression in the genome as a whole as well as in specific candidate genes. Overall, the data show predicted patterns of gene expression profiles and molecular evolution in the zebra finch genome. Expression of MHC genes in particular, corresponds well with expression patterns in other vertebrates. PMID:20359325

Location tests for biomarker studies: a comparison using simulations for the two-sample case.

PubMed

Scheinhardt, M O; Ziegler, A

2013-01-01

Gene, protein, or metabolite expression levels are often non-normally distributed, heavy tailed and contain outliers. Standard statistical approaches may fail as location tests in this situation. In three Monte-Carlo simulation studies, we aimed at comparing the type I error levels and empirical power of standard location tests and three adaptive tests [O'Gorman, Can J Stat 1997; 25: 269 -279; Keselman et al., Brit J Math Stat Psychol 2007; 60: 267- 293; Szymczak et al., Stat Med 2013; 32: 524 - 537] for a wide range of distributions. We simulated two-sample scenarios using the g-and-k-distribution family to systematically vary tail length and skewness with identical and varying variability between groups. All tests kept the type I error level when groups did not vary in their variability. The standard non-parametric U-test performed well in all simulated scenarios. It was outperformed by the two non-parametric adaptive methods in case of heavy tails or large skewness. Most tests did not keep the type I error level for skewed data in the case of heterogeneous variances. The standard U-test was a powerful and robust location test for most of the simulated scenarios except for very heavy tailed or heavy skewed data, and it is thus to be recommended except for these cases. The non-parametric adaptive tests were powerful for both normal and non-normal distributions under sample variance homogeneity. But when sample variances differed, they did not keep the type I error level. The parametric adaptive test lacks power for skewed and heavy tailed distributions.

Environmental influences on the longitudinal covariance of expressive vocabulary: measuring the home literacy environment in a genetically sensitive design

PubMed Central

Hart, Sara A.; Petrill, Stephen A.; DeThorne, Laura S.; Deater-Deckard, Kirby; Thompson, Lee A.; Schatschneider, Chris; Cutting, Laurie E.

2010-01-01

Background Despite the well-replicated relationship between the home literacy environment and expressive vocabulary, few studies have examined the extent to which the home literacy environment is associated with the development of early vocabulary ability in the context of genetic influences. This study examined the influence of the home literacy environment on the longitudinal covariance of expressive vocabulary within a genetically sensitive design. Methods Participants were drawn from the Western Reserve Reading Project, a longitudinal twin project of 314 twin pairs based in Ohio. Twins were assessed via three annual home visits during early elementary school; expressive vocabulary was measured via the Boston Naming Test (BNT), and the Home Literacy Environment (HLE) was assessed using mothers’ report. Results The heritability of the BNT was moderate and significant at each measurement occasion, h2 = .29–.49, as were the estimates of the shared environment, c2 = .27–.39. HLE accounted for between 6–10% of the total variance in each year of vocabulary assessment. Furthermore, 7–9% of the total variance of the stability over time in BNT was accounted for by covariance in the home literacy environment. Conclusions These results indicate that aspects of the home literacy environment, as reported by mothers, account for some of the shared environmental variance associated with expressive vocabulary in school aged children. PMID:19298476

Identification of additive, dominant, and epistatic variation conferred by key genes in cellulose biosynthesis pathway in Populus tomentosa†

PubMed Central

Du, Qingzhang; Tian, Jiaxing; Yang, Xiaohui; Pan, Wei; Xu, Baohua; Li, Bailian; Ingvarsson, Pär K.; Zhang, Deqiang

2015-01-01

Economically important traits in many species generally show polygenic, quantitative inheritance. The components of genetic variation (additive, dominant and epistatic effects) of these traits conferred by multiple genes in shared biological pathways remain to be defined. Here, we investigated 11 full-length genes in cellulose biosynthesis, on 10 growth and wood-property traits, within a population of 460 unrelated Populus tomentosa individuals, via multi-gene association. To validate positive associations, we conducted single-marker analysis in a linkage population of 1,200 individuals. We identified 118, 121, and 43 associations (P< 0.01) corresponding to additive, dominant, and epistatic effects, respectively, with low to moderate proportions of phenotypic variance (R2). Epistatic interaction models uncovered a combination of three non-synonymous sites from three unique genes, representing a significant epistasis for diameter at breast height and stem volume. Single-marker analysis validated 61 associations (false discovery rate, Q ≤ 0.10), representing 38 SNPs from nine genes, and its average effect (R2 = 3.8%) nearly 2-fold higher than that identified with multi-gene association, suggesting that multi-gene association can capture smaller individual variants. Moreover, a structural gene–gene network based on tissue-specific transcript abundances provides a better understanding of the multi-gene pathway affecting tree growth and lignocellulose biosynthesis. Our study highlights the importance of pathway-based multiple gene associations to uncover the nature of genetic variance for quantitative traits and may drive novel progress in molecular breeding. PMID:25428896

A novel approach for human whole transcriptome analysis based on absolute gene expression of microarray data.

PubMed

Bikel, Shirley; Jacobo-Albavera, Leonor; Sánchez-Muñoz, Fausto; Cornejo-Granados, Fernanda; Canizales-Quinteros, Samuel; Soberón, Xavier; Sotelo-Mundo, Rogerio R; Del Río-Navarro, Blanca E; Mendoza-Vargas, Alfredo; Sánchez, Filiberto; Ochoa-Leyva, Adrian

2017-01-01

In spite of the emergence of RNA sequencing (RNA-seq), microarrays remain in widespread use for gene expression analysis in the clinic. There are over 767,000 RNA microarrays from human samples in public repositories, which are an invaluable resource for biomedical research and personalized medicine. The absolute gene expression analysis allows the transcriptome profiling of all expressed genes under a specific biological condition without the need of a reference sample. However, the background fluorescence represents a challenge to determine the absolute gene expression in microarrays. Given that the Y chromosome is absent in female subjects, we used it as a new approach for absolute gene expression analysis in which the fluorescence of the Y chromosome genes of female subjects was used as the background fluorescence for all the probes in the microarray. This fluorescence was used to establish an absolute gene expression threshold, allowing the differentiation between expressed and non-expressed genes in microarrays. We extracted the RNA from 16 children leukocyte samples (nine males and seven females, ages 6-10 years). An Affymetrix Gene Chip Human Gene 1.0 ST Array was carried out for each sample and the fluorescence of 124 genes of the Y chromosome was used to calculate the absolute gene expression threshold. After that, several expressed and non-expressed genes according to our absolute gene expression threshold were compared against the expression obtained using real-time quantitative polymerase chain reaction (RT-qPCR). From the 124 genes of the Y chromosome, three genes (DDX3Y, TXLNG2P and EIF1AY) that displayed significant differences between sexes were used to calculate the absolute gene expression threshold. Using this threshold, we selected 13 expressed and non-expressed genes and confirmed their expression level by RT-qPCR. Then, we selected the top 5% most expressed genes and found that several KEGG pathways were significantly enriched. Interestingly, these pathways were related to the typical functions of leukocytes cells, such as antigen processing and presentation and natural killer cell mediated cytotoxicity. We also applied this method to obtain the absolute gene expression threshold in already published microarray data of liver cells, where the top 5% expressed genes showed an enrichment of typical KEGG pathways for liver cells. Our results suggest that the three selected genes of the Y chromosome can be used to calculate an absolute gene expression threshold, allowing a transcriptome profiling of microarray data without the need of an additional reference experiment. Our approach based on the establishment of a threshold for absolute gene expression analysis will allow a new way to analyze thousands of microarrays from public databases. This allows the study of different human diseases without the need of having additional samples for relative expression experiments.

Longevity candidate genes and their association with personality traits in the elderly

PubMed Central

Luciano, Michelle; Lopez, Lorna M.; de Moor, Marleen H.M.; Harris, Sarah E.; Davies, Gail; Nutile, Teresa; Krueger, Robert F.; Esko, Tõnu; Schlessinger, David; Toshiko, Tanaka; Derringer, Jaime L.; Realo, Anu; Hansell, Narelle K.; Pergadia, Michele L.; Pesonen, Anu-Katriina; Sanna, Serena; Terracciano, Antonio; Madden, Pamela A.F.; Penninx, Brenda; Spinhoven, Philip; Hartman, Catherine; Oostra, Ben A.; Janssens, A. Cecile J.W.; Eriksson, Johan G; Starr, John M.; Cannas, Alessandra; Ferrucci, Luigi; Metspalu, Andres; Wright, Margeret J.; Heath, Andrew C.; van Duijn, Cornelia M.; Bierut, Laura J.; Raikkonen, Katri; Martin, Nicholas G.; Ciullo, Marina; Rujescu, Dan; Boomsma, Dorret I.; Deary, Ian J.

2013-01-01

Human longevity and personality traits are both heritable and are consistently linked at the phenotypic level. We test the hypothesis that candidate genes influencing longevity in lower organisms are associated with variance in the five major dimensions of human personality (measured by the NEO-FFI and IPIP inventories) plus related mood states of anxiety and depression. Seventy single nucleotide polymorphisms (SNPs) in six brain expressed, longevity candidate genes (AFG3L2, FRAP1, MAT1A, MAT2A, SYNJ1 and SYNJ2) were typed in over one thousand 70-year old participants from the Lothian Birth Cohort of 1936 (LBC1936). No SNPs were associated with the personality and psychological distress traits at a Bonferroni corrected level of significance (p < 0.0002), but there was an over-representation of nominally significant (p < 0.05) SNPs in the synaptojanin-2 (SYNJ2) gene associated with agreeableness and symptoms of depression. Eight SNPs which showed nominally significant association across personality measurement instruments were tested in an extremely large replication sample of 17 106 participants. SNP rs350292, in SYNJ2, was significant: the minor allele was associated with an average decrease in NEO agreeableness scale scores of 0.25 points, and 0.67 points in the restricted analysis of elderly cohorts (most aged > 60 years). Because we selected a specific set of longevity genes based on functional genomics findings, further research on other longevity gene candidates is warranted to discover whether they are relevant candidates for personality and psychological distress traits. PMID:22213687

Sex-dependent expression of behavioural genetic architectures and the evolution of sexual dimorphism.

PubMed

Han, Chang S; Dingemanse, Niels J

2017-10-11

Empirical studies imply that sex-specific genetic architectures can resolve evolutionary conflicts between males and females, and thereby facilitate the evolution of sexual dimorphism. Sex-specificity of behavioural genetic architectures has, however, rarely been considered. Moreover, as the expression of genetic (co)variances is often environment-dependent, general inferences on sex-specific genetic architectures require estimates of quantitative genetics parameters under multiple conditions. We measured exploration and aggression in pedigreed populations of southern field crickets ( Gryllus bimaculatus ) raised on either naturally balanced (free-choice) or imbalanced (protein-deprived) diets. For each dietary condition, we measured for each behavioural trait (i) level of sexual dimorphism, (ii) level of sex-specificity of survival selection gradients, (iii) level of sex-specificity of additive genetic variance, and (iv) strength of the cross-sex genetic correlation. We report here evidence for sexual dimorphism in behaviour as well as sex-specificity in the expression of genetic (co)variances as predicted by theory. The additive genetic variances of exploration and aggression were significantly greater in males compared with females. Cross-sex genetic correlations were highly positive for exploration but deviating (significantly) from one for aggression; findings were consistent across dietary treatments. This suggests that genetic architectures characterize the sexually dimorphic focal behaviours across various key environmental conditions in the wild. Our finding also highlights that sexual conflict can be resolved by evolving sexually independent genetic architectures. © 2017 The Author(s).

Differential gene expression analysis in glioblastoma cells and normal human brain cells based on GEO database.

PubMed

Wang, Anping; Zhang, Guibin

2017-11-01

The differentially expressed genes between glioblastoma (GBM) cells and normal human brain cells were investigated to performed pathway analysis and protein interaction network analysis for the differentially expressed genes. GSE12657 and GSE42656 gene chips, which contain gene expression profile of GBM were obtained from Gene Expression Omniub (GEO) database of National Center for Biotechnology Information (NCBI). The 'limma' data packet in 'R' software was used to analyze the differentially expressed genes in the two gene chips, and gene integration was performed using 'RobustRankAggreg' package. Finally, pheatmap software was used for heatmap analysis and Cytoscape, DAVID, STRING and KOBAS were used for protein-protein interaction, Gene Ontology (GO) and KEGG analyses. As results: i) 702 differentially expressed genes were identified in GSE12657, among those genes, 548 were significantly upregulated and 154 were significantly downregulated (p<0.01, fold-change >1), and 1,854 differentially expressed genes were identified in GSE42656, among the genes, 1,068 were significantly upregulated and 786 were significantly downregulated (p<0.01, fold-change >1). A total of 167 differentially expressed genes including 100 upregulated genes and 67 downregulated genes were identified after gene integration, and the genes showed significantly different expression levels in GBM compared with normal human brain cells (p<0.05). ii) Interactions between the protein products of 101 differentially expressed genes were identified using STRING and expression network was established. A key gene, called CALM3, was identified by Cytoscape software. iii) GO enrichment analysis showed that differentially expressed genes were mainly enriched in 'neurotransmitter:sodium symporter activity' and 'neurotransmitter transporter activity', which can affect the activity of neurotransmitter transportation. KEGG pathway analysis showed that the differentially expressed genes were mainly enriched in 'protein processing in endoplasmic reticulum', which can affect protein processing in endoplasmic reticulum. The results showed that: i) 167 differentially expressed genes were identified from two gene chips after integration; and ii) protein interaction network was established, and GO and KEGG pathway analyses were successfully performed to identify and annotate the key gene, which provide new insights for the studies on GBN at gene level.

Diallel analysis for sex-linked and maternal effects.

PubMed

Zhu, J; Weir, B S

1996-01-01

Genetic models including sex-linked and maternal effects as well as autosomal gene effects are described. Monte Carlo simulations were conducted to compare efficiencies of estimation by minimum norm quadratic unbiased estimation (MINQUE) and restricted maximum likelihood (REML) methods. MINQUE(1), which has 1 for all prior values, has a similar efficiency to MINQUE(θ), which requires prior estimates of parameter values. MINQUE(1) has the advantage over REML of unbiased estimation and convenient computation. An adjusted unbiased prediction (AUP) method is developed for predicting random genetic effects. AUP is desirable for its easy computation and unbiasedness of both mean and variance of predictors. The jackknife procedure is appropriate for estimating the sampling variances of estimated variances (or covariances) and of predicted genetic effects. A t-test based on jackknife variances is applicable for detecting significance of variation. Worked examples from mice and silkworm data are given in order to demonstrate variance and covariance estimation and genetic effect prediction.

Discovery and validation of a glioblastoma co-expressed gene module

PubMed Central

Dunwoodie, Leland J.; Poehlman, William L.; Ficklin, Stephen P.; Feltus, Frank Alexander

2018-01-01

Tumors exhibit complex patterns of aberrant gene expression. Using a knowledge-independent, noise-reducing gene co-expression network construction software called KINC, we created multiple RNAseq-based gene co-expression networks relevant to brain and glioblastoma biology. In this report, we describe the discovery and validation of a glioblastoma-specific gene module that contains 22 co-expressed genes. The genes are upregulated in glioblastoma relative to normal brain and lower grade glioma samples; they are also hypo-methylated in glioblastoma relative to lower grade glioma tumors. Among the proneural, neural, mesenchymal, and classical glioblastoma subtypes, these genes are most-highly expressed in the mesenchymal subtype. Furthermore, high expression of these genes is associated with decreased survival across each glioblastoma subtype. These genes are of interest to glioblastoma biology and our gene interaction discovery and validation workflow can be used to discover and validate co-expressed gene modules derived from any co-expression network. PMID:29541392

Discovery and validation of a glioblastoma co-expressed gene module.

PubMed

Dunwoodie, Leland J; Poehlman, William L; Ficklin, Stephen P; Feltus, Frank Alexander

2018-02-16

Tumors exhibit complex patterns of aberrant gene expression. Using a knowledge-independent, noise-reducing gene co-expression network construction software called KINC, we created multiple RNAseq-based gene co-expression networks relevant to brain and glioblastoma biology. In this report, we describe the discovery and validation of a glioblastoma-specific gene module that contains 22 co-expressed genes. The genes are upregulated in glioblastoma relative to normal brain and lower grade glioma samples; they are also hypo-methylated in glioblastoma relative to lower grade glioma tumors. Among the proneural, neural, mesenchymal, and classical glioblastoma subtypes, these genes are most-highly expressed in the mesenchymal subtype. Furthermore, high expression of these genes is associated with decreased survival across each glioblastoma subtype. These genes are of interest to glioblastoma biology and our gene interaction discovery and validation workflow can be used to discover and validate co-expressed gene modules derived from any co-expression network.

The latitude dependence of the variance of zonally averaged quantities. [in polar meteorology with attention to geometrical effects of earth

NASA Technical Reports Server (NTRS)

North, G. R.; Bell, T. L.; Cahalan, R. F.; Moeng, F. J.

1982-01-01

Geometric characteristics of the spherical earth are shown to be responsible for the increase of variance with latitude of zonally averaged meteorological statistics. An analytic model is constructed to display the effect of a spherical geometry on zonal averages, employing a sphere labeled with radial unit vectors in a real, stochastic field expanded in complex spherical harmonics. The variance of a zonally averaged field is found to be expressible in terms of the spectrum of the vector field of the spherical harmonics. A maximum variance is then located at the poles, and the ratio of the variance to the zonally averaged grid-point variance, weighted by the cosine of the latitude, yields the zonal correlation typical of the latitude. An example is provided for the 500 mb level in the Northern Hemisphere compared to 15 years of data. Variance is determined to increase north of 60 deg latitude.

Mapping QTLs for resistance against Globodera pallida (Stone) Pa2/3 in a diploid potato progeny originating from Solanum spegazzinii.

PubMed

Caromel, B; Mugniéry, D; Lefebvre, V; Andrzejewski, S; Ellissèche, D; Kerlan, M C; Rousselle, P; Rousselle-Bourgeois, F

2003-05-01

A "F1" diploid population between Solanum tuberosum 2 x and the wild Solanum spegazzinii was studied. It segregated for resistance against the potato cyst nematode Globodera pallida derived from the wild species. The inheritance had a quantitative nature. Linkage maps of AFLP and RFLP markers were constructed for both parents. Three QTLs were identified on the map of the resistant parent on chromosomes V, VI and XII, respectively. The first one had a major effect and explained more than 50% of the total variance of resistance. It is located in a cluster of resistance genes and may be the same locus as Gpa which has been described formerly. The two others explained about 20% of the total variance each. The QTL on chromosome XII is also in a cluster of resistance genes, and in an orthologous position with resistance genes against nematodes in tomato and pepper.

Gender-Specific Gene Expression in Post-Mortem Human Brain: Localization to Sex Chromosomes

PubMed Central

Vawter, Marquis P; Evans, Simon; Choudary, Prabhakara; Tomita, Hiroaki; Meador-Woodruff, Jim; Molnar, Margherita; Li, Jun; Lopez, Juan F; Myers, Rick; Cox, David; Watson, Stanley J; Akil, Huda; Jones, Edward G; Bunney, William E

2011-01-01

Gender differences in brain development and in the prevalence of neuropsychiatric disorders such as depression have been reported. Gender differences in human brain might be related to patterns of gene expression. Microarray technology is one useful method for investigation of gene expression in brain. We investigated gene expression, cell types, and regional expression patterns of differentially expressed sex chromosome genes in brain. We profiled gene expression in male and female dorsolateral prefrontal cortex, anterior cingulate cortex, and cerebellum using the Affymetrix oligonucleotide microarray platform. Differentially expressed genes between males and females on the Y chromosome (DBY, SMCY, UTY, RPS4Y, and USP9Y) and X chromosome (XIST) were confirmed using real-time PCR measurements. In situ hybridization confirmed the differential expression of gender-specific genes and neuronal expression of XIST, RPS4Y, SMCY, and UTY in three brain regions examined. The XIST gene, which silences gene expression on regions of the X chromosome, is expressed in a subset of neurons. Since a subset of neurons express gender-specific genes, neural subpopulations may exhibit a subtle sexual dimorphism at the level of differences in gene regulation and function. The distinctive pattern of neuronal expression of XIST, RPS4Y, SMCY, and UTY and other sex chromosome genes in neuronal subpopulations may possibly contribute to gender differences in prevalence noted for some neuropsychiatric disorders. Studies of the protein expression of these sex- chromosome-linked genes in brain tissue are required to address the functional consequences of the observed gene expression differences. PMID:14583743

A Plasmodium yoelii HECT-like E3 ubiquitin ligase regulates parasite growth and virulence.

PubMed

Nair, Sethu C; Xu, Ruixue; Pattaradilokrat, Sittiporn; Wu, Jian; Qi, Yanwei; Zilversmit, Martine; Ganesan, Sundar; Nagarajan, Vijayaraj; Eastman, Richard T; Orandle, Marlene S; Tan, John C; Myers, Timothy G; Liu, Shengfa; Long, Carole A; Li, Jian; Su, Xin-Zhuan

2017-08-09

Infection of mice with strains of Plasmodium yoelii parasites can result in different pathology, but molecular mechanisms to explain this variation are unclear. Here we show that a P. yoelii gene encoding a HECT-like E3 ubiquitin ligase (Pyheul) influences parasitemia and host mortality. We genetically cross two lethal parasites with distinct disease phenotypes, and identify 43 genetically diverse progeny by typing with microsatellites and 9230 single-nucleotide polymorphisms. A genome-wide quantitative trait loci scan links parasite growth and host mortality to two major loci on chromosomes 1 and 7 with LOD (logarithm of the odds) scores = 6.1 and 8.1, respectively. Allelic exchange of partial sequences of Pyheul in the chromosome 7 locus and modification of the gene expression alter parasite growth and host mortality. This study identifies a gene that may have a function in parasite growth, virulence, and host-parasite interaction, and therefore could be a target for drug or vaccine development.Many strains of Plasmodium differ in virulence, but factors that control these distinctions are not known. Here the authors comparatively map virulence loci using the offspring from a P. yoelii YM and N67 genetic cross, and identify a putative HECT E3 ubiquitin ligase that may explain the variance.

An Unbiased Estimator of Gene Diversity with Improved Variance for Samples Containing Related and Inbred Individuals of any Ploidy

PubMed Central

Harris, Alexandre M.; DeGiorgio, Michael

2016-01-01

Gene diversity, or expected heterozygosity (H), is a common statistic for assessing genetic variation within populations. Estimation of this statistic decreases in accuracy and precision when individuals are related or inbred, due to increased dependence among allele copies in the sample. The original unbiased estimator of expected heterozygosity underestimates true population diversity in samples containing relatives, as it only accounts for sample size. More recently, a general unbiased estimator of expected heterozygosity was developed that explicitly accounts for related and inbred individuals in samples. Though unbiased, this estimator’s variance is greater than that of the original estimator. To address this issue, we introduce a general unbiased estimator of gene diversity for samples containing related or inbred individuals, which employs the best linear unbiased estimator of allele frequencies, rather than the commonly used sample proportion. We examine the properties of this estimator, H∼BLUE, relative to alternative estimators using simulations and theoretical predictions, and show that it predominantly has the smallest mean squared error relative to others. Further, we empirically assess the performance of H∼BLUE on a global human microsatellite dataset of 5795 individuals, from 267 populations, genotyped at 645 loci. Additionally, we show that the improved variance of H∼BLUE leads to improved estimates of the population differentiation statistic, FST, which employs measures of gene diversity within its calculation. Finally, we provide an R script, BestHet, to compute this estimator from genomic and pedigree data. PMID:28040781

Gene expression variability in human hepatic drug metabolizing enzymes and transporters.

PubMed

Yang, Lun; Price, Elvin T; Chang, Ching-Wei; Li, Yan; Huang, Ying; Guo, Li-Wu; Guo, Yongli; Kaput, Jim; Shi, Leming; Ning, Baitang

2013-01-01

Interindividual variability in the expression of drug-metabolizing enzymes and transporters (DMETs) in human liver may contribute to interindividual differences in drug efficacy and adverse reactions. Published studies that analyzed variability in the expression of DMET genes were limited by sample sizes and the number of genes profiled. We systematically analyzed the expression of 374 DMETs from a microarray data set consisting of gene expression profiles derived from 427 human liver samples. The standard deviation of interindividual expression for DMET genes was much higher than that for non-DMET genes. The 20 DMET genes with the largest variability in the expression provided examples of the interindividual variation. Gene expression data were also analyzed using network analysis methods, which delineates the similarities of biological functionalities and regulation mechanisms for these highly variable DMET genes. Expression variability of human hepatic DMET genes may affect drug-gene interactions and disease susceptibility, with concomitant clinical implications.

A novel approach for human whole transcriptome analysis based on absolute gene expression of microarray data

PubMed Central

Bikel, Shirley; Jacobo-Albavera, Leonor; Sánchez-Muñoz, Fausto; Cornejo-Granados, Fernanda; Canizales-Quinteros, Samuel; Soberón, Xavier; Sotelo-Mundo, Rogerio R.; del Río-Navarro, Blanca E.; Mendoza-Vargas, Alfredo; Sánchez, Filiberto

2017-01-01

Background In spite of the emergence of RNA sequencing (RNA-seq), microarrays remain in widespread use for gene expression analysis in the clinic. There are over 767,000 RNA microarrays from human samples in public repositories, which are an invaluable resource for biomedical research and personalized medicine. The absolute gene expression analysis allows the transcriptome profiling of all expressed genes under a specific biological condition without the need of a reference sample. However, the background fluorescence represents a challenge to determine the absolute gene expression in microarrays. Given that the Y chromosome is absent in female subjects, we used it as a new approach for absolute gene expression analysis in which the fluorescence of the Y chromosome genes of female subjects was used as the background fluorescence for all the probes in the microarray. This fluorescence was used to establish an absolute gene expression threshold, allowing the differentiation between expressed and non-expressed genes in microarrays. Methods We extracted the RNA from 16 children leukocyte samples (nine males and seven females, ages 6–10 years). An Affymetrix Gene Chip Human Gene 1.0 ST Array was carried out for each sample and the fluorescence of 124 genes of the Y chromosome was used to calculate the absolute gene expression threshold. After that, several expressed and non-expressed genes according to our absolute gene expression threshold were compared against the expression obtained using real-time quantitative polymerase chain reaction (RT-qPCR). Results From the 124 genes of the Y chromosome, three genes (DDX3Y, TXLNG2P and EIF1AY) that displayed significant differences between sexes were used to calculate the absolute gene expression threshold. Using this threshold, we selected 13 expressed and non-expressed genes and confirmed their expression level by RT-qPCR. Then, we selected the top 5% most expressed genes and found that several KEGG pathways were significantly enriched. Interestingly, these pathways were related to the typical functions of leukocytes cells, such as antigen processing and presentation and natural killer cell mediated cytotoxicity. We also applied this method to obtain the absolute gene expression threshold in already published microarray data of liver cells, where the top 5% expressed genes showed an enrichment of typical KEGG pathways for liver cells. Our results suggest that the three selected genes of the Y chromosome can be used to calculate an absolute gene expression threshold, allowing a transcriptome profiling of microarray data without the need of an additional reference experiment. Discussion Our approach based on the establishment of a threshold for absolute gene expression analysis will allow a new way to analyze thousands of microarrays from public databases. This allows the study of different human diseases without the need of having additional samples for relative expression experiments. PMID:29230367

Applying species-tree analyses to deep phylogenetic histories: challenges and potential suggested from a survey of empirical phylogenetic studies.

PubMed

Lanier, Hayley C; Knowles, L Lacey

2015-02-01

Coalescent-based methods for species-tree estimation are becoming a dominant approach for reconstructing species histories from multi-locus data, with most of the studies examining these methodologies focused on recently diverged species. However, deeper phylogenies, such as the datasets that comprise many Tree of Life (ToL) studies, also exhibit gene-tree discordance. This discord may also arise from the stochastic sorting of gene lineages during the speciation process (i.e., reflecting the random coalescence of gene lineages in ancestral populations). It remains unknown whether guidelines regarding methodologies and numbers of loci established by simulation studies at shallow tree depths translate into accurate species relationships for deeper phylogenetic histories. We address this knowledge gap and specifically identify the challenges and limitations of species-tree methods that account for coalescent variance for deeper phylogenies. Using simulated data with characteristics informed by empirical studies, we evaluate both the accuracy of estimated species trees and the characteristics associated with recalcitrant nodes, with a specific focus on whether coalescent variance is generally responsible for the lack of resolution. By determining the proportion of coalescent genealogies that support a particular node, we demonstrate that (1) species-tree methods account for coalescent variance at deep nodes and (2) mutational variance - not gene-tree discord arising from the coalescent - posed the primary challenge for accurate reconstruction across the tree. For example, many nodes were accurately resolved despite predicted discord from the random coalescence of gene lineages and nodes with poor support were distributed across a range of depths (i.e., they were not restricted to a particular recent divergences). Given their broad taxonomic scope and large sampling of taxa, deep level phylogenies pose several potential methodological complications including difficulties with MCMC convergence and estimation of requisite population genetic parameters for coalescent-based approaches. Despite these difficulties, the findings generally support the utility of species-tree analyses for the estimation of species relationships throughout the ToL. We discuss strategies for successful application of species-tree approaches to deep phylogenies. Copyright © 2014 Elsevier Inc. All rights reserved.

Genetic loci associated with heart rate variability and their effects on cardiac disease risk

PubMed Central

Nolte, Ilja M.; Munoz, M. Loretto; Tragante, Vinicius; Amare, Azmeraw T.; Jansen, Rick; Vaez, Ahmad; von der Heyde, Benedikt; Avery, Christy L.; Bis, Joshua C.; Dierckx, Bram; van Dongen, Jenny; Gogarten, Stephanie M.; Goyette, Philippe; Hernesniemi, Jussi; Huikari, Ville; Hwang, Shih-Jen; Jaju, Deepali; Kerr, Kathleen F.; Kluttig, Alexander; Krijthe, Bouwe P.; Kumar, Jitender; van der Laan, Sander W.; Lyytikäinen, Leo-Pekka; Maihofer, Adam X.; Minassian, Arpi; van der Most, Peter J.; Müller-Nurasyid, Martina; Nivard, Michel; Salvi, Erika; Stewart, James D.; Thayer, Julian F.; Verweij, Niek; Wong, Andrew; Zabaneh, Delilah; Zafarmand, Mohammad H.; Abdellaoui, Abdel; Albarwani, Sulayma; Albert, Christine; Alonso, Alvaro; Ashar, Foram; Auvinen, Juha; Axelsson, Tomas; Baker, Dewleen G.; de Bakker, Paul I. W.; Barcella, Matteo; Bayoumi, Riad; Bieringa, Rob J.; Boomsma, Dorret; Boucher, Gabrielle; Britton, Annie R.; Christophersen, Ingrid; Dietrich, Andrea; Ehret, George B.; Ellinor, Patrick T.; Eskola, Markku; Felix, Janine F.; Floras, John S.; Franco, Oscar H.; Friberg, Peter; Gademan, Maaike G. J.; Geyer, Mark A.; Giedraitis, Vilmantas; Hartman, Catharina A.; Hemerich, Daiane; Hofman, Albert; Hottenga, Jouke-Jan; Huikuri, Heikki; Hutri-Kähönen, Nina; Jouven, Xavier; Junttila, Juhani; Juonala, Markus; Kiviniemi, Antti M.; Kors, Jan A.; Kumari, Meena; Kuznetsova, Tatiana; Laurie, Cathy C.; Lefrandt, Joop D.; Li, Yong; Li, Yun; Liao, Duanping; Limacher, Marian C.; Lin, Henry J.; Lindgren, Cecilia M.; Lubitz, Steven A.; Mahajan, Anubha; McKnight, Barbara; zu Schwabedissen, Henriette Meyer; Milaneschi, Yuri; Mononen, Nina; Morris, Andrew P.; Nalls, Mike A.; Navis, Gerjan; Neijts, Melanie; Nikus, Kjell; North, Kari E.; O'Connor, Daniel T.; Ormel, Johan; Perz, Siegfried; Peters, Annette; Psaty, Bruce M.; Raitakari, Olli T.; Risbrough, Victoria B.; Sinner, Moritz F.; Siscovick, David; Smit, Johannes H.; Smith, Nicholas L.; Soliman, Elsayed Z.; Sotoodehnia, Nona; Staessen, Jan A.; Stein, Phyllis K.; Stilp, Adrienne M.; Stolarz-Skrzypek, Katarzyna; Strauch, Konstantin; Sundström, Johan; Swenne, Cees A.; Syvänen, Ann-Christine; Tardif, Jean-Claude; Taylor, Kent D.; Teumer, Alexander; Thornton, Timothy A.; Tinker, Lesley E.; Uitterlinden, André G.; van Setten, Jessica; Voss, Andreas; Waldenberger, Melanie; Wilhelmsen, Kirk C.; Willemsen, Gonneke; Wong, Quenna; Zhang, Zhu-Ming; Zonderman, Alan B.; Cusi, Daniele; Evans, Michele K.; Greiser, Halina K.; van der Harst, Pim; Hassan, Mohammad; Ingelsson, Erik; Järvelin, Marjo-Riitta; Kääb, Stefan; Kähönen, Mika; Kivimaki, Mika; Kooperberg, Charles; Kuh, Diana; Lehtimäki, Terho; Lind, Lars; Nievergelt, Caroline M.; O'Donnell, Chris J.; Oldehinkel, Albertine J.; Penninx, Brenda; Reiner, Alexander P.; Riese, Harriëtte; van Roon, Arie M.; Rioux, John D.; Rotter, Jerome I.; Sofer, Tamar; Stricker, Bruno H.; Tiemeier, Henning; Vrijkotte, Tanja G. M.; Asselbergs, Folkert W.; Brundel, Bianca J. J. M.; Heckbert, Susan R.; Whitsel, Eric A.; den Hoed, Marcel; Snieder, Harold; de Geus, Eco J. C.

2017-01-01

Reduced cardiac vagal control reflected in low heart rate variability (HRV) is associated with greater risks for cardiac morbidity and mortality. In two-stage meta-analyses of genome-wide association studies for three HRV traits in up to 53,174 individuals of European ancestry, we detect 17 genome-wide significant SNPs in eight loci. HRV SNPs tag non-synonymous SNPs (in NDUFA11 and KIAA1755), expression quantitative trait loci (eQTLs) (influencing GNG11, RGS6 and NEO1), or are located in genes preferentially expressed in the sinoatrial node (GNG11, RGS6 and HCN4). Genetic risk scores account for 0.9 to 2.6% of the HRV variance. Significant genetic correlation is found for HRV with heart rate (−0.74

Genomic BLUP including additive and dominant variation in purebreds and F1 crossbreds, with an application in pigs.

PubMed

Vitezica, Zulma G; Varona, Luis; Elsen, Jean-Michel; Misztal, Ignacy; Herring, William; Legarra, Andrès

2016-01-29

Most developments in quantitative genetics theory focus on the study of intra-breed/line concepts. With the availability of massive genomic information, it becomes necessary to revisit the theory for crossbred populations. We propose methods to construct genomic covariances with additive and non-additive (dominance) inheritance in the case of pure lines and crossbred populations. We describe substitution effects and dominant deviations across two pure parental populations and the crossbred population. Gene effects are assumed to be independent of the origin of alleles and allelic frequencies can differ between parental populations. Based on these assumptions, the theoretical variance components (additive and dominant) are obtained as a function of marker effects and allelic frequencies. The additive genetic variance in the crossbred population includes the biological additive and dominant effects of a gene and a covariance term. Dominance variance in the crossbred population is proportional to the product of the heterozygosity coefficients of both parental populations. A genomic BLUP (best linear unbiased prediction) equivalent model is presented. We illustrate this approach by using pig data (two pure lines and their cross, including 8265 phenotyped and genotyped sows). For the total number of piglets born, the dominance variance in the crossbred population represented about 13 % of the total genetic variance. Dominance variation is only marginally important for litter size in the crossbred population. We present a coherent marker-based model that includes purebred and crossbred data and additive and dominant actions. Using this model, it is possible to estimate breeding values, dominant deviations and variance components in a dataset that comprises data on purebred and crossbred individuals. These methods can be exploited to plan assortative mating in pig, maize or other species, in order to generate superior crossbred individuals in terms of performance.

Nucleotide variability of protamine genes influencing bull sperm motility variables.

PubMed

H M, Yathish; Kumar, Subodh; Chaudhary, Rajni; Mishra, Chinmoy; A, Sivakumar; Kumar, Amit; Chauhan, Anuj; Ghosh, S K; Mitra, Abhijit

2018-06-01

Protamines (PRMs), important proteins of chromatin condensation in spermiogenesis, are promising candidate genes to explore markers of sperm motility. The coding and in-silico predicted promoter regions of these genes were investigated in 102 crossbred and 32 purebred cattle. Also, mRNA quantification was done to explore its possibility as diagnostic tool of infertility. The PCR-SSCP analysis indicated there were two band patterns only in fragment I of the PRM1 and fragment II of the PRM2 gene. The sequence analysis revealed A152G and G179A transitions in the PRM1 gene. Similarly, G35A, A49G and A64G transitions were identified in the PRM2 gene which resulted in altered amino acid sequences from arginine (R) to glutamine (Q), from arginine (R) to glycine (G) and from arginine (R) to glycine (G), respectively. This caused the reduction in molecular weight of PRM2 from 2157.66 to 1931.33 Da due to reduction in the number of basic amino acids. These altered properties of the PRM2 protein led to the reduction in Mass Motility (MM: P < 0.01), Initial Progressive Motility (IPM; P < 0.05) and Post Thaw Motility (PTM; P < 0.05) in crossbred bulls. The least squares analysis of variance indicated there was an effect of PRM2 haplotypes on MM (P = 0.0069), IPM (P = 0.0306) and PTM (P = 0.0500) in crossbred cattle and on PTM (P = 0.0408) in the overall cattle population. Based on the RT-qPCR analysis, however, there was not any significant variation of PRM1 and PRM2 gene expression among sperm of Vrindavani bulls with relatively lesser and greater sperm motility. Copyright © 2018 Elsevier B.V. All rights reserved.

Sequencing of sporadic Attention-Deficit Hyperactivity Disorder (ADHD) identifies novel and potentially pathogenic de novo variants and excludes overlap with genes associated with autism spectrum disorder.

PubMed

Kim, Daniel Seung; Burt, Amber A; Ranchalis, Jane E; Wilmot, Beth; Smith, Joshua D; Patterson, Karynne E; Coe, Bradley P; Li, Yatong K; Bamshad, Michael J; Nikolas, Molly; Eichler, Evan E; Swanson, James M; Nigg, Joel T; Nickerson, Deborah A; Jarvik, Gail P

2017-06-01

Attention-Deficit Hyperactivity Disorder (ADHD) has high heritability; however, studies of common variation account for <5% of ADHD variance. Using data from affected participants without a family history of ADHD, we sought to identify de novo variants that could account for sporadic ADHD. Considering a total of 128 families, two analyses were conducted in parallel: first, in 11 unaffected parent/affected proband trios (or quads with the addition of an unaffected sibling) we completed exome sequencing. Six de novo missense variants at highly conserved bases were identified and validated from four of the 11 families: the brain-expressed genes TBC1D9, DAGLA, QARS, CSMD2, TRPM2, and WDR83. Separately, in 117 unrelated probands with sporadic ADHD, we sequenced a panel of 26 genes implicated in intellectual disability (ID) and autism spectrum disorder (ASD) to evaluate whether variation in ASD/ID-associated genes were also present in participants with ADHD. Only one putative deleterious variant (Gln600STOP) in CHD1L was identified; this was found in a single proband. Notably, no other nonsense, splice, frameshift, or highly conserved missense variants in the 26 gene panel were identified and validated. These data suggest that de novo variant analysis in families with independently adjudicated sporadic ADHD diagnosis can identify novel genes implicated in ADHD pathogenesis. Moreover, that only one of the 128 cases (0.8%, 11 exome, and 117 MIP sequenced participants) had putative deleterious variants within our data in 26 genes related to ID and ASD suggests significant independence in the genetic pathogenesis of ADHD as compared to ASD and ID phenotypes. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Accelerated Evolution of Developmentally Biased Genes in the Tetraphenic Ant Cardiocondyla obscurior.

PubMed

Schrader, Lukas; Helanterä, Heikki; Oettler, Jan

2017-03-01

Plastic gene expression underlies phenotypic plasticity and plastically expressed genes evolve under different selection regimes compared with ubiquitously expressed genes. Social insects are well-suited models to elucidate the evolutionary dynamics of plastic genes for their genetically and environmentally induced discrete polymorphisms. Here, we study the evolution of plastically expressed genes in the ant Cardiocondyla obscurior-a species that produces two discrete male morphs in addition to the typical female polymorphism of workers and queens. Based on individual-level gene expression data from 28 early third instar larvae, we test whether the same evolutionary dynamics that pertain to plastically expressed genes in adults also pertain to genes with plastic expression during development. In order to quantify plasticity of gene expression over multiple contrasts, we develop a novel geometric measure. For genes expressed during development, we show that plasticity of expression is positively correlated with evolutionary rates. We furthermore find a strong correlation between expression plasticity and expression variation within morphs, suggesting a close link between active and passive plasticity of gene expression. Our results support the notion of relaxed selection and neutral processes as important drivers in the evolution of adaptive plasticity. © The Author 2016. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Clock Genes Explain a Large Proportion of Phenotypic Variance in Systolic Blood Pressure and This Control Is Not Modified by Environmental Temperature.

PubMed

Dashti, Hassan S; Aslibekyan, Stella; Scheer, Frank A J L; Smith, Caren E; Lamon-Fava, Stefania; Jacques, Paul; Lai, Chao-Qiang; Tucker, Katherine L; Arnett, Donna K; Ordovás, José M

2016-01-01

Diurnal variation in blood pressure (BP) is regulated, in part, by an endogenous circadian clock; however, few human studies have identified associations between clock genes and BP. Accounting for environmental temperature may be necessary to correct for seasonal bias. We examined whether environmental temperature on the day of participants' assessment was associated with BP, using adjusted linear regression models in the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) (n = 819) and the Boston Puerto Rican Health Study (BPRHS) (n = 1,248) cohorts. We estimated phenotypic variance in BP by 18 clock genes and examined individual single-nucleotide polymorphism (SNP) associations with BP using an additive genetic model, with further consideration of environmental temperature. In GOLDN, each additional 1 °C increase in environmental temperature was associated with 0.18 mm Hg lower systolic BP [SBP; β ± SE = -0.18 ± 0.05 mm Hg; P = 0.0001] and 0.10mm Hg lower diastolic BP [DBP; -0.10 ± 0.03 mm Hg; P = 0.001]. Similar results were seen in the BPRHS for SBP only. Clock genes explained a statistically significant proportion of the variance in SBP [V G/V P ± SE = 0.071 ± 0.03; P = 0.001] in GOLDN, but not in the BPRHS, and we did not observe associations between individual SNPs and BP. Environmental temperature did not influence the identified genetic associations. We identified clock genes that explained a statistically significant proportion of the phenotypic variance in SBP, supporting the importance of the circadian pathway underlying cardiac physiology. Although temperature was associated with BP, it did not affect results with genetic markers in either study. Therefore, it does not appear that temperature measures are necessary for interpreting associations between clock genes and BP. Trials related to this study were registered at clinicaltrials.gov as NCT00083369 (Genetic and Environmental Determinants of Triglycerides) and NCT01231958 (Boston Puerto Rican Health Study). © Published by Oxford University Press on behalf of American Journal of Hypertension Ltd 2015. This work is written by (a) US Government employees(s) and is in the public domain in the US.

Biometrics Foundation Documents

DTIC Science & Technology

2009-01-01

a digital form. The quality of the sensor used has a significant impact on the recognition results. Example “sensors” could be digital cameras...Difficult to control sensor and channel variances that significantly impact capabilities Not sufficiently distinctive for identification over large...expressions, hairstyle, glasses, hats, makeup, etc. have on face recognition systems? Minor variances , such as those mentioned, will have a moderate

Economic Pressure and Marital Quality: An Illustration of the Method Variance Problem in the Causal Modeling of Family Processes.

ERIC Educational Resources Information Center

Lorenz, Frederick O.; And Others

1991-01-01

Examined effects of method variance on models linking family economic pressure, marital quality, and expressions of hostility and warmth among 76 couples. Observer reports yielded results linking economic pressure to marital quality indirectly through interactional processes such as hostility. Self-reports or spouses' reports made it difficult to…

SpoVT: From Fine-Tuning Regulator in Bacillus subtilis to Essential Sporulation Protein in Bacillus cereus

PubMed Central

Eijlander, Robyn T.; Holsappel, Siger; de Jong, Anne; Ghosh, Abhinaba; Christie, Graham; Kuipers, Oscar P.

2016-01-01

Sporulation is a highly sophisticated developmental process adopted by most Bacilli as a survival strategy to withstand extreme conditions that normally do not support microbial growth. A complicated regulatory cascade, divided into various stages and taking place in two different compartments of the cell, involves a number of primary and secondary regulator proteins that drive gene expression directed toward the formation and maturation of an endospore. Such regulator proteins are highly conserved among various spore formers. Despite this conservation, both regulatory and phenotypic differences are observed between different species of spore forming bacteria. In this study, we demonstrate that deletion of the regulatory sporulation protein SpoVT results in a severe sporulation defect in Bacillus cereus, whereas this is not observed in Bacillus subtilis. Although spores are initially formed, the process is stalled at a later stage in development, followed by lysis of the forespore and the mother cell. A transcriptomic investigation of B. cereus ΔspoVT shows upregulation of genes involved in germination, potentially leading to premature lysis of prespores formed. Additionally, extreme variation in the expression of species-specific genes of unknown function was observed. Introduction of the B. subtilis SpoVT protein could partly restore the sporulation defect in the B. cereus spoVT mutant strain. The difference in phenotype is thus more than likely explained by differences in promoter targets rather than differences in mode of action of the conserved SpoVT regulator protein. This study stresses that evolutionary variances in regulon members of sporulation regulators can have profound effects on the spore developmental process and that mere protein homology is not a foolproof predictor of similar phenotypes. PMID:27790204

SpoVT: From Fine-Tuning Regulator in Bacillus subtilis to Essential Sporulation Protein in Bacillus cereus.

PubMed

Eijlander, Robyn T; Holsappel, Siger; de Jong, Anne; Ghosh, Abhinaba; Christie, Graham; Kuipers, Oscar P

2016-01-01

Sporulation is a highly sophisticated developmental process adopted by most Bacilli as a survival strategy to withstand extreme conditions that normally do not support microbial growth. A complicated regulatory cascade, divided into various stages and taking place in two different compartments of the cell, involves a number of primary and secondary regulator proteins that drive gene expression directed toward the formation and maturation of an endospore. Such regulator proteins are highly conserved among various spore formers. Despite this conservation, both regulatory and phenotypic differences are observed between different species of spore forming bacteria. In this study, we demonstrate that deletion of the regulatory sporulation protein SpoVT results in a severe sporulation defect in Bacillus cereus , whereas this is not observed in Bacillus subtilis . Although spores are initially formed, the process is stalled at a later stage in development, followed by lysis of the forespore and the mother cell. A transcriptomic investigation of B. cereus Δ spoVT shows upregulation of genes involved in germination, potentially leading to premature lysis of prespores formed. Additionally, extreme variation in the expression of species-specific genes of unknown function was observed. Introduction of the B. subtilis SpoVT protein could partly restore the sporulation defect in the B. cereus spoVT mutant strain. The difference in phenotype is thus more than likely explained by differences in promoter targets rather than differences in mode of action of the conserved SpoVT regulator protein. This study stresses that evolutionary variances in regulon members of sporulation regulators can have profound effects on the spore developmental process and that mere protein homology is not a foolproof predictor of similar phenotypes.

Analysis of multiplex gene expression maps obtained by voxelation.

PubMed

An, Li; Xie, Hongbo; Chin, Mark H; Obradovic, Zoran; Smith, Desmond J; Megalooikonomou, Vasileios

2009-04-29

Gene expression signatures in the mammalian brain hold the key to understanding neural development and neurological disease. Researchers have previously used voxelation in combination with microarrays for acquisition of genome-wide atlases of expression patterns in the mouse brain. On the other hand, some work has been performed on studying gene functions, without taking into account the location information of a gene's expression in a mouse brain. In this paper, we present an approach for identifying the relation between gene expression maps obtained by voxelation and gene functions. To analyze the dataset, we chose typical genes as queries and aimed at discovering similar gene groups. Gene similarity was determined by using the wavelet features extracted from the left and right hemispheres averaged gene expression maps, and by the Euclidean distance between each pair of feature vectors. We also performed a multiple clustering approach on the gene expression maps, combined with hierarchical clustering. Among each group of similar genes and clusters, the gene function similarity was measured by calculating the average gene function distances in the gene ontology structure. By applying our methodology to find similar genes to certain target genes we were able to improve our understanding of gene expression patterns and gene functions. By applying the clustering analysis method, we obtained significant clusters, which have both very similar gene expression maps and very similar gene functions respectively to their corresponding gene ontologies. The cellular component ontology resulted in prominent clusters expressed in cortex and corpus callosum. The molecular function ontology gave prominent clusters in cortex, corpus callosum and hypothalamus. The biological process ontology resulted in clusters in cortex, hypothalamus and choroid plexus. Clusters from all three ontologies combined were most prominently expressed in cortex and corpus callosum. The experimental results confirm the hypothesis that genes with similar gene expression maps might have similar gene functions. The voxelation data takes into account the location information of gene expression level in mouse brain, which is novel in related research. The proposed approach can potentially be used to predict gene functions and provide helpful suggestions to biologists.

Quantifying Temporal Autocorrelations for the Expression of Geobacter species mRNA Gene Transcripts at Variable Ammonium Levels during in situ U(VI) Bioremediation

NASA Astrophysics Data System (ADS)

Mouser, P. J.

2010-12-01

In order to develop decision-making tools for the prediction and optimization of subsurface bioremediation strategies, we must be able to link the molecular-scale activity of microorganisms involved in remediation processes with biogeochemical processes observed at the field-scale. This requires the ability to quantify changes in the in situ metabolic condition of dominant microbes and associate these changes to fluctuations in nutrient levels throughout the bioremediation process. It also necessitates a need to understand the spatiotemporal variability of the molecular-scale information to develop meaningful parameters and constraint ranges in complex bio-physio-chemical models. The expression of three Geobacter species genes (ammonium transporter (amtB), nitrogen fixation (nifD), and a housekeeping gene (recA)) were tracked at two monitoring locations that differed significantly in ammonium (NH4+) concentrations during a field-scale experiment where acetate was injected into the subsurface to simulate Geobacteraceae in a uranium-contaminated aquifer. Analysis of amtB and nifD mRNA transcript levels indicated that NH4+ was the primary form of fixed nitrogen during bioremediation. Overall expression levels of amtB were on average 8-fold higher at NH4+ concentrations of 300 μM or more than at lower NH4+ levels (average 60 μM). The degree of temporal correlation in Geobacter species mRNA expression levels was calculated at both locations using autocorrelation methods that describe the relationship between sample semi-variance and time lag. At the monitoring location with lower NH4+, a temporal correlation lag of 8 days was observed for both amtB and nifD transcript patterns. At the location where higher NH4+ levels were observed, no discernable temporal correlation lag above the sampling frequency (approximately every 2 days) was observed for amtB or nifD transcript fluctuations. Autocorrelation trends in recA expression levels at both locations indicated that while a temporal correlation in the general metabolic activity of Geobacter species may exist, considerable variability in transcript levels masked these correlations at the sampled scale. These findings suggest that when Geobacter species are dependent upon a particular nutrient such as NH4+, the time length for which their activity level relating to this nutrient condition can be predicted is significantly enhanced.

Co-expression network analysis of duplicate genes in maize (Zea mays L.) reveals no subgenome bias.

PubMed

Li, Lin; Briskine, Roman; Schaefer, Robert; Schnable, Patrick S; Myers, Chad L; Flagel, Lex E; Springer, Nathan M; Muehlbauer, Gary J

2016-11-04

Gene duplication is prevalent in many species and can result in coding and regulatory divergence. Gene duplications can be classified as whole genome duplication (WGD), tandem and inserted (non-syntenic). In maize, WGD resulted in the subgenomes maize1 and maize2, of which maize1 is considered the dominant subgenome. However, the landscape of co-expression network divergence of duplicate genes in maize is still largely uncharacterized. To address the consequence of gene duplication on co-expression network divergence, we developed a gene co-expression network from RNA-seq data derived from 64 different tissues/stages of the maize reference inbred-B73. WGD, tandem and inserted gene duplications exhibited distinct regulatory divergence. Inserted duplicate genes were more likely to be singletons in the co-expression networks, while WGD duplicate genes were likely to be co-expressed with other genes. Tandem duplicate genes were enriched in the co-expression pattern where co-expressed genes were nearly identical for the duplicates in the network. Older gene duplications exhibit more extensive co-expression variation than younger duplications. Overall, non-syntenic genes primarily from inserted duplications show more co-expression divergence. Also, such enlarged co-expression divergence is significantly related to duplication age. Moreover, subgenome dominance was not observed in the co-expression networks - maize1 and maize2 exhibit similar levels of intra subgenome correlations. Intriguingly, the level of inter subgenome co-expression was similar to the level of intra subgenome correlations, and genes from specific subgenomes were not likely to be the enriched in co-expression network modules and the hub genes were not predominantly from any specific subgenomes in maize. Our work provides a comprehensive analysis of maize co-expression network divergence for three different types of gene duplications and identifies potential relationships between duplication types, duplication ages and co-expression consequences.

Anger Expression Types and Interpersonal Problems in Nurses.

PubMed

Han, Aekyung; Won, Jongsoon; Kim, Oksoo; Lee, Sang E

2015-06-01

The purpose of this study was to investigate the anger expression types in nurses and to analyze the differences between the anger expression types and interpersonal problems. The data were collected from 149 nurses working in general hospitals with 300 beds or more in Seoul or Gyeonggi province, Korea. For anger expression type, the anger expression scale from the Korean State-Trait Anger Expression Inventory was used. For interpersonal problems, the short form of the Korean Inventory of Interpersonal Problems Circumplex Scales was used. Data were analyzed using descriptive statistics, cluster analysis, multivariate analysis of variance, and Duncan's multiple comparisons test. Three anger expression types in nurses were found: low-anger expression, anger-in, and anger-in/control type. From the results of multivariate analysis of variance, there were significant differences between anger expression types and interpersonal problems (Wilks lambda F = 3.52, p < .001). Additionally, anger-in/control type was found to have the most difficulty with interpersonal problems by Duncan's post hoc test (p < .050). Based on this research, the development of an anger expression intervention program for nurses is recommended to establish the means of expressing the suppressed emotions, which would help the nurses experience less interpersonal problems. Copyright © 2015. Published by Elsevier B.V.

Tissue Non-Specific Genes and Pathways Associated with Diabetes: An Expression Meta-Analysis.

PubMed

Mei, Hao; Li, Lianna; Liu, Shijian; Jiang, Fan; Griswold, Michael; Mosley, Thomas

2017-01-21

We performed expression studies to identify tissue non-specific genes and pathways of diabetes by meta-analysis. We searched curated datasets of the Gene Expression Omnibus (GEO) database and identified 13 and five expression studies of diabetes and insulin responses at various tissues, respectively. We tested differential gene expression by empirical Bayes-based linear method and investigated gene set expression association by knowledge-based enrichment analysis. Meta-analysis by different methods was applied to identify tissue non-specific genes and gene sets. We also proposed pathway mapping analysis to infer functions of the identified gene sets, and correlation and independent analysis to evaluate expression association profile of genes and gene sets between studies and tissues. Our analysis showed that PGRMC1 and HADH genes were significant over diabetes studies, while IRS1 and MPST genes were significant over insulin response studies, and joint analysis showed that HADH and MPST genes were significant over all combined data sets. The pathway analysis identified six significant gene sets over all studies. The KEGG pathway mapping indicated that the significant gene sets are related to diabetes pathogenesis. The results also presented that 12.8% and 59.0% pairwise studies had significantly correlated expression association for genes and gene sets, respectively; moreover, 12.8% pairwise studies had independent expression association for genes, but no studies were observed significantly different for expression association of gene sets. Our analysis indicated that there are both tissue specific and non-specific genes and pathways associated with diabetes pathogenesis. Compared to the gene expression, pathway association tends to be tissue non-specific, and a common pathway influencing diabetes development is activated through different genes at different tissues.

Multi-allelic haplotype model based on genetic partition for genomic prediction and variance component estimation using SNP markers.

PubMed

Da, Yang

2015-12-18

The amount of functional genomic information has been growing rapidly but remains largely unused in genomic selection. Genomic prediction and estimation using haplotypes in genome regions with functional elements such as all genes of the genome can be an approach to integrate functional and structural genomic information for genomic selection. Towards this goal, this article develops a new haplotype approach for genomic prediction and estimation. A multi-allelic haplotype model treating each haplotype as an 'allele' was developed for genomic prediction and estimation based on the partition of a multi-allelic genotypic value into additive and dominance values. Each additive value is expressed as a function of h - 1 additive effects, where h = number of alleles or haplotypes, and each dominance value is expressed as a function of h(h - 1)/2 dominance effects. For a sample of q individuals, the limit number of effects is 2q - 1 for additive effects and is the number of heterozygous genotypes for dominance effects. Additive values are factorized as a product between the additive model matrix and the h - 1 additive effects, and dominance values are factorized as a product between the dominance model matrix and the h(h - 1)/2 dominance effects. Genomic additive relationship matrix is defined as a function of the haplotype model matrix for additive effects, and genomic dominance relationship matrix is defined as a function of the haplotype model matrix for dominance effects. Based on these results, a mixed model implementation for genomic prediction and variance component estimation that jointly use haplotypes and single markers is established, including two computing strategies for genomic prediction and variance component estimation with identical results. The multi-allelic genetic partition fills a theoretical gap in genetic partition by providing general formulations for partitioning multi-allelic genotypic values and provides a haplotype method based on the quantitative genetics model towards the utilization of functional and structural genomic information for genomic prediction and estimation.

QTL mapping in white spruce: gene maps and genomic regions underlying adaptive traits across pedigrees, years and environments.

PubMed

Pelgas, Betty; Bousquet, Jean; Meirmans, Patrick G; Ritland, Kermit; Isabel, Nathalie

2011-03-10

The genomic architecture of bud phenology and height growth remains poorly known in most forest trees. In non model species, QTL studies have shown limited application because most often QTL data could not be validated from one experiment to another. The aim of our study was to overcome this limitation by basing QTL detection on the construction of genetic maps highly-enriched in gene markers, and by assessing QTLs across pedigrees, years, and environments. Four saturated individual linkage maps representing two unrelated mapping populations of 260 and 500 clonally replicated progeny were assembled from 471 to 570 markers, including from 283 to 451 gene SNPs obtained using a multiplexed genotyping assay. Thence, a composite linkage map was assembled with 836 gene markers.For individual linkage maps, a total of 33 distinct quantitative trait loci (QTLs) were observed for bud flush, 52 for bud set, and 52 for height growth. For the composite map, the corresponding numbers of QTL clusters were 11, 13, and 10. About 20% of QTLs were replicated between the two mapping populations and nearly 50% revealed spatial and/or temporal stability. Three to four occurrences of overlapping QTLs between characters were noted, indicating regions with potential pleiotropic effects. Moreover, some of the genes involved in the QTLs were also underlined by recent genome scans or expression profile studies.Overall, the proportion of phenotypic variance explained by each QTL ranged from 3.0 to 16.4% for bud flush, from 2.7 to 22.2% for bud set, and from 2.5 to 10.5% for height growth. Up to 70% of the total character variance could be accounted for by QTLs for bud flush or bud set, and up to 59% for height growth. This study provides a basic understanding of the genomic architecture related to bud flush, bud set, and height growth in a conifer species, and a useful indicator to compare with Angiosperms. It will serve as a basic reference to functional and association genetic studies of adaptation and growth in Picea taxa. The putative QTNs identified will be tested for associations in natural populations, with potential applications in molecular breeding and gene conservation programs. QTLs mapping consistently across years and environments could also be the most important targets for breeding, because they represent genomic regions that may be least affected by G × E interactions.

QTL mapping in white spruce: gene maps and genomic regions underlying adaptive traits across pedigrees, years and environments

PubMed Central

2011-01-01

Background The genomic architecture of bud phenology and height growth remains poorly known in most forest trees. In non model species, QTL studies have shown limited application because most often QTL data could not be validated from one experiment to another. The aim of our study was to overcome this limitation by basing QTL detection on the construction of genetic maps highly-enriched in gene markers, and by assessing QTLs across pedigrees, years, and environments. Results Four saturated individual linkage maps representing two unrelated mapping populations of 260 and 500 clonally replicated progeny were assembled from 471 to 570 markers, including from 283 to 451 gene SNPs obtained using a multiplexed genotyping assay. Thence, a composite linkage map was assembled with 836 gene markers. For individual linkage maps, a total of 33 distinct quantitative trait loci (QTLs) were observed for bud flush, 52 for bud set, and 52 for height growth. For the composite map, the corresponding numbers of QTL clusters were 11, 13, and 10. About 20% of QTLs were replicated between the two mapping populations and nearly 50% revealed spatial and/or temporal stability. Three to four occurrences of overlapping QTLs between characters were noted, indicating regions with potential pleiotropic effects. Moreover, some of the genes involved in the QTLs were also underlined by recent genome scans or expression profile studies. Overall, the proportion of phenotypic variance explained by each QTL ranged from 3.0 to 16.4% for bud flush, from 2.7 to 22.2% for bud set, and from 2.5 to 10.5% for height growth. Up to 70% of the total character variance could be accounted for by QTLs for bud flush or bud set, and up to 59% for height growth. Conclusions This study provides a basic understanding of the genomic architecture related to bud flush, bud set, and height growth in a conifer species, and a useful indicator to compare with Angiosperms. It will serve as a basic reference to functional and association genetic studies of adaptation and growth in Picea taxa. The putative QTNs identified will be tested for associations in natural populations, with potential applications in molecular breeding and gene conservation programs. QTLs mapping consistently across years and environments could also be the most important targets for breeding, because they represent genomic regions that may be least affected by G × E interactions. PMID:21392393

GENETIC MODIFICATION OF GIBBERELLIC ACID SIGNALING TO PROMOTE CARBON SEQUESTRATION IN TREE ROOTS AND STEMS

DOE Office of Scientific and Technical Information (OSTI.GOV)

Busov, Victor

Semidwarfism has been used extensively in row crops and horticulture to promote yield, reduce lodging, and improve harvest index, and it might have similar benefits for trees for short-rotation forestry or energy plantations, reclamation, phytoremediation, or other applications. We studied the effects of the dominant semidwarfism transgenes GA Insensitive (GAI) and Repressor of GAI-Like, which affect gibberellin (GA) action, and the GA catabolic gene, GA 2-oxidase, in nursery beds and in 2-year-old high-density stands of hybrid poplar (Populus tremula - Populus alba). Twenty-nine traits were analyzed, including measures of growth, morphology, and physiology. Endogenous GA levels were modified in mostmore » transgenic events; GA(20) and GA(8), in particular, had strong inverse associations with tree height. Nearly all measured traits varied significantly among genotypes, and several traits interacted with planting density, including aboveground biomass, root-shoot ratio, root fraction, branch angle, and crown depth. Semidwarfism promoted biomass allocation to roots over shoots and substantially increased rooting efficiency with most genes tested. The increased root proportion and increased leaf chlorophyll levels were associated with changes in leaf carbon isotope discrimination, indicating altered water use efficiency. Semidwarf trees had dramatically reduced growth when in direct competition with wild-type trees, supporting the hypothesis that semidwarfism genes could be effective tools to mitigate the spread of exotic, hybrid, and transgenic plants in wild and feral populations. We modified gibberellin (GA) metabolism and signaling in transgenic poplars using dominant transgenes and studied their effects for 3 years under field conditions. The transgenes that we employed either reduced the bioactive GAs, or attenuated their signaling. The majority of transgenic trees had significant and in many cases dramatic changes in height, crown architecture, foliage morphology, flowering onset, floral structure, and vegetative phenology. Most transgenes elicited various levels of height reduction consistent with the roles of GA in elongation growth. Several other growth traits were proportionally reduced, including branch length, internode distance, and leaf length. In contrast to elongation growth, stem diameter growth was much less affected, suggesting that semi-dwarf trees in dense stands might provide high levels of biomass production and carbon sequestration. The severity of phenotypic effects was strongly correlated with transgene expression among independent transgenic events, but often in a non-linear manner, the form of which varied widely among constructs. The majority of semi-dwarfed, transgenic plants showed delayed bud flush and early bud set, and expression of a native GAI transgene accelerated first time flowering in the field. All of the phenotypic changes observed in multiple years were stable over the 3 years of field study. Our results suggest that transgenic modification of GA action may be useful for producing semi-dwarf trees with modified growth and morphology for horticulture and other uses. We studied the poplar C(19) gibberellin 2-oxidase (GA2ox) gene subfamily. We show that a set of paralogous gene pairs differentially regulate shoot and root development. ? PtGA2ox4 and its paralogous gene PtGA2ox5 are primarily expressed in aerial organs, and overexpression of PtGA2ox5 produced a strong dwarfing phenotype characteristic of GA deficiency. Suppression of PtGA2ox4 and PtGA2ox5 led to increased biomass growth, but had no effect on root development. By contrast, the PtGA2ox2 and PtGA2ox7 paralogous pair was predominantly expressed in roots, and when these two genes were RNAi-suppressed it led to a decrease of root biomass. ? The morphological changes in the transgenic plants were underpinned by tissue-specific increases in bioactive GAs that corresponded to the predominant native expression of the targeted paralogous gene pair. Although RNAi suppression of both paralogous pairs led to changes in wood development, they were much greater in the transgenics with suppressed PtGA2ox4 and PtGA2ox5. The degree of gene suppression in independent events was strongly associated with phenotypes, demonstrating dose-dependent control of growth by GA2ox RNA concentrations. ? The expression and transgenic modifications reported here show that shoot- and leaf-expressed PtGA2ox4 and PtGA2ox5 specifically restrain aerial shoot growth, while root-expressed PtGA2ox2 and PtGA2ox7 promote root development. Genes controlling plant growth and form are of considerable interest, because they affect survival and productivity traits, and are largely unknown or poorly characterized. The SHORT INTERNODES(SHI) gene is one of a 10-member SHI-RELATED SEQUENCE (SRS) gene family in Arabidopsis that includes important developmental regulators. ? Using comparative sequence analysis of the SRS gene families in poplar and Arabidopsis, we identified two poplar proteins that are most similar to SHI and its closely related gene STYLISH1 (STY1). The two poplar genes are very similar in sequence and expression and are therefore probably paralogs with redundant functions. ? RNAi suppression of the two Populus genes enhanced shoot and root growth, whereas the overexpression of Arabidopsis SHI in poplar reduced internode and petiole length. The suppression of the two genes increased fiber length and the proportion of xylem tissue, mainly through increased xylem cell proliferation. The transgenic modifications were also associated with significant changes in the concentrations of gibberellins and cytokinin. ? We conclude that Populus SHI-RELATED SEQUENCE (SRS) genes play an important role in the regulation of vegetative growth, including wood formation, and thus could be useful tools for the modification of biomass productivity, wood quality or plant form. We studied the effects on plant growth from insertion of five cisgenes that encode proteins involved in gibberellin metabolism or signalling. Intact genomic copies of PtGA20ox7, PtGA2ox2,Pt RGL1_1, PtRGL1_2 and PtGAI1 genes from the genome-sequenced Populus trichocarpa clone Nisqually-1 were transformed into Populus tremula - alba (clone INRA 717-1B4), and growth, morphology and xylem cell size characterized in the greenhouse. Each cisgene encompassed 1-2?kb of 5' and 1?kb of 3' flanking DNA, as well as all native exons and introns. Large numbers of independent insertion events per cisgene (19-38), including empty vector controls, were studied. Three of the cisgenic modifications had significant effects on plant growth rate, morphology or wood properties. The PtGA20ox7 cisgene increased rate of shoot regeneration in vitro, accelerated early growth, and variation in growth rate was correlated with PtGA20ox7 gene expression. PtRGL1_1 and PtGA2ox2 caused reduced growth, while PtRGL1_2 gave rise to plants that grew normally but had significantly longer xylem fibres. RT-PCR studies suggested that the lack of growth inhibition observed in PtRGL1_2 cisgenic plants was a result of co-suppression. PtGAI1 slowed regeneration rate and both PtGAI1 and PtGA20ox7 gave rise to increased variance among events for early diameter and volume index, respectively. Our work suggests that cisgenic insertion of additional copies of native genes involved in growth regulation may provide tools to help modify plant architecture, expand the genetic variance in plant architecture available to breeders and accelerate transfer of alleles between difficult-to-cross species. The role of gibberellins (GAs) in regulation of lateral root development is poorly understood. We show that GA-deficient (35S:PcGA2ox1) and GA-insensitive (35S:rgl1) transgenic Populus exhibited increased lateral root proliferation and elongation under in vitro and greenhouse conditions, and these effects were reversed by exogenous GA treatment. In addition, RNA interference suppression of two poplar GA 2-oxidases predominantly expressed in roots also decreased lateral root formation. GAs negatively affected lateral root formation by inhibiting lateral root primordium initiation. A whole-genome microarray analysis of root development in GA-modified transgenic plants revealed 2069 genes with significantly altered expression. The expression of 1178 genes, including genes that promote cell proliferation, growth, and cell wall loosening, corresponded to the phenotypic severity of the root traits when transgenic events with differential phenotypic expression were compared. The array data and direct hormone measurements suggested crosstalk of GA signaling with other hormone pathways, including auxin and abscisic acid. Transgenic modification of a differentially expressed gene encoding an auxin efflux carrier suggests that GA modulation of lateral root development is at least partly imparted by polar auxin transport modification. These results suggest a mechanism for GA-regulated modulation of lateral root proliferation associated with regulation of plant allometry during the stress response. Here we summarize progress in identification of three classes of genes useful for control of plant architecture: those affecting hormone metabolism and signaling; transcription and other regulatory factors; and the cell cycle. We focus on strong modifiers of stature and form that may be useful for directed modification of plant architecture, rather than the detailed mechanisms of gene action. Gibberellin (GA) metabolic and response genes are particularly attractive targets for manipulation because many act in a dose-dependent manner; similar phenotypic effects can be readily achieved in heterologous species; and induced pleiotropic effects--such as on nitrogen assimilation, photosynthesis, and lateral root production--are usually positive with respect to crop performance. Genes encoding transcription factors represent strong candidates for manipulation of plant architecture. For example, AINTEGUMENTA, ARGOS (auxin-regulated gene controlling organ size), and growth-regulating factors (GRFs) are strong modifiers of leaf and/or flower size. Plants overexpressing these genes had increased organ size and did not display negative pleiotropic effects in glasshouse environments. TCP-domain genes such as CINCINNATA, and the associated regulatory miRNAs such as miRJAW, may provide useful means to modulate leaf curvature and other foliage properties. There are considerable opportunities for comparative and translational genomics in nonmodel plant systems.« less

The Constrained Maximal Expression Level Owing to Haploidy Shapes Gene Content on the Mammalian X Chromosome.

PubMed

Hurst, Laurence D; Ghanbarian, Avazeh T; Forrest, Alistair R R; Huminiecki, Lukasz

2015-12-01

X chromosomes are unusual in many regards, not least of which is their nonrandom gene content. The causes of this bias are commonly discussed in the context of sexual antagonism and the avoidance of activity in the male germline. Here, we examine the notion that, at least in some taxa, functionally biased gene content may more profoundly be shaped by limits imposed on gene expression owing to haploid expression of the X chromosome. Notably, if the X, as in primates, is transcribed at rates comparable to the ancestral rate (per promoter) prior to the X chromosome formation, then the X is not a tolerable environment for genes with very high maximal net levels of expression, owing to transcriptional traffic jams. We test this hypothesis using The Encyclopedia of DNA Elements (ENCODE) and data from the Functional Annotation of the Mammalian Genome (FANTOM5) project. As predicted, the maximal expression of human X-linked genes is much lower than that of genes on autosomes: on average, maximal expression is three times lower on the X chromosome than on autosomes. Similarly, autosome-to-X retroposition events are associated with lower maximal expression of retrogenes on the X than seen for X-to-autosome retrogenes on autosomes. Also as expected, X-linked genes have a lesser degree of increase in gene expression than autosomal ones (compared to the human/Chimpanzee common ancestor) if highly expressed, but not if lowly expressed. The traffic jam model also explains the known lower breadth of expression for genes on the X (and the Z of birds), as genes with broad expression are, on average, those with high maximal expression. As then further predicted, highly expressed tissue-specific genes are also rare on the X and broadly expressed genes on the X tend to be lowly expressed, both indicating that the trend is shaped by the maximal expression level not the breadth of expression per se. Importantly, a limit to the maximal expression level explains biased tissue of expression profiles of X-linked genes. Tissues whose tissue-specific genes are very highly expressed (e.g., secretory tissues, tissues abundant in structural proteins) are also tissues in which gene expression is relatively rare on the X chromosome. These trends cannot be fully accounted for in terms of alternative models of biased expression. In conclusion, the notion that it is hard for genes on the Therian X to be highly expressed, owing to transcriptional traffic jams, provides a simple yet robustly supported rationale of many peculiar features of X's gene content, gene expression, and evolution.

The Constrained Maximal Expression Level Owing to Haploidy Shapes Gene Content on the Mammalian X Chromosome

PubMed Central

Hurst, Laurence D.; Ghanbarian, Avazeh T.; Forrest, Alistair R. R.; Huminiecki, Lukasz

2015-01-01

X chromosomes are unusual in many regards, not least of which is their nonrandom gene content. The causes of this bias are commonly discussed in the context of sexual antagonism and the avoidance of activity in the male germline. Here, we examine the notion that, at least in some taxa, functionally biased gene content may more profoundly be shaped by limits imposed on gene expression owing to haploid expression of the X chromosome. Notably, if the X, as in primates, is transcribed at rates comparable to the ancestral rate (per promoter) prior to the X chromosome formation, then the X is not a tolerable environment for genes with very high maximal net levels of expression, owing to transcriptional traffic jams. We test this hypothesis using The Encyclopedia of DNA Elements (ENCODE) and data from the Functional Annotation of the Mammalian Genome (FANTOM5) project. As predicted, the maximal expression of human X-linked genes is much lower than that of genes on autosomes: on average, maximal expression is three times lower on the X chromosome than on autosomes. Similarly, autosome-to-X retroposition events are associated with lower maximal expression of retrogenes on the X than seen for X-to-autosome retrogenes on autosomes. Also as expected, X-linked genes have a lesser degree of increase in gene expression than autosomal ones (compared to the human/Chimpanzee common ancestor) if highly expressed, but not if lowly expressed. The traffic jam model also explains the known lower breadth of expression for genes on the X (and the Z of birds), as genes with broad expression are, on average, those with high maximal expression. As then further predicted, highly expressed tissue-specific genes are also rare on the X and broadly expressed genes on the X tend to be lowly expressed, both indicating that the trend is shaped by the maximal expression level not the breadth of expression per se. Importantly, a limit to the maximal expression level explains biased tissue of expression profiles of X-linked genes. Tissues whose tissue-specific genes are very highly expressed (e.g., secretory tissues, tissues abundant in structural proteins) are also tissues in which gene expression is relatively rare on the X chromosome. These trends cannot be fully accounted for in terms of alternative models of biased expression. In conclusion, the notion that it is hard for genes on the Therian X to be highly expressed, owing to transcriptional traffic jams, provides a simple yet robustly supported rationale of many peculiar features of X’s gene content, gene expression, and evolution. PMID:26685068

Allelic frequencies and association with carcass traits of six genes in local subpopulations of Japanese Black cattle.

PubMed

Nishimaki, Takahiro; Ibi, Takayuki; Siqintuya; Kobayashi, Naohiko; Matsuhashi, Tamako; Akiyama, Takayuki; Yoshida, Emi; Imai, Kazumi; Matsui, Mayu; Uemura, Keiichi; Eto, Hisayoshi; Watanabe, Naoto; Fujita, Tatsuo; Saito, Yosuke; Komatsu, Tomohiko; Hoshiba, Hiroshi; Mannen, Hideyuki; Sasazaki, Shinji; Kunieda, Tetsuo

2016-04-01

Marker-assisted selection (MAS) is expected to accelerate the genetic improvement of Japanese Black cattle. However, verification of the effects of the genes for MAS in different subpopulations is required prior to the application of MAS. In this study, we investigated the allelic frequencies and genotypic effects for carcass traits of six genes, which can be used in MAS, in eight local subpopulations. These genes are SCD, FASN and SREBP1, which are associated with the fatty acid composition of meat, and NCAPG, MC1R and F11, which are associated with carcass weight, coat color and blood coagulation abnormality, respectively. The frequencies of desirable alleles of SCD and FASN were relatively high and that of NCAPG was relatively low, and NCAPG was significantly associated with several carcass traits, including carcass weight. The proportions of genotypic variance explained by NCAPG to phenotypic variance were 4.83 for carcass weight. We thus confirmed that NCAPG is a useful marker for selection of carcass traits in these subpopulations. In addition, we found that the desirable alleles of six genes showed no negative effects on carcass traits. Therefore, selection using these genes to improve target traits should not have negative impacts on carcass traits. © 2015 Japanese Society of Animal Science.

Development of a high efficiency integration system and promoter library for rapid modification of Pseudomonas putida KT2440

DOE Office of Scientific and Technical Information (OSTI.GOV)

Elmore, Joshua R.; Furches, Anna; Wolff, Gara N.

Pseudomonas putida strains are highly robust bacteria known for their ability to efficiently utilize a variety of carbon sources, including aliphatic and aromatic hydrocarbons. Recently, P. putida has been engineered to valorize the lignin stream of a lignocellulosic biomass pretreatment process. Nonetheless, when compared to platform organisms such as Escherichia coli, the toolkit for engineering P. putida is underdeveloped. Heterologous gene expression in particular is problematic. Plasmid instability and copy number variance provide challenges for replicative plasmids, while use of homologous recombination for insertion of DNA into the chromosome is slow and laborious. Furthermore, heterologous expression efforts to date typicallymore » rely on overexpression of exogenous pathways using a handful of poorly characterized promoters. In order to improve the P. putida toolkit, we developed a rapid genome integration system using the site-specific recombinase from bacteriophage Bxb1 to enable rapid, high efficiency integration of DNA into the P. putida chromosome. We also developed a library of synthetic promoters with various UP elements, -35 sequences, and -10 sequences, as well as different ribosomal binding sites. We tested these promoters using a fluorescent reporter gene, mNeonGreen, to characterize the strength of each promoter, and identified UP-element-promoter-ribosomal binding sites combinations capable of driving a ~150-fold range of protein expression levels. One additional integrating vector was developed that confers more robust kanamycin resistance when integrated at single copy into the chromosome. This genome integration and reporter systems are extensible for testing other genetic parts, such as examining terminator strength, and will allow rapid integration of heterologous pathways for metabolic engineering.« less

Limits to TYMS and TP53 genes as predictive determinants for fluoropyrimidine sensitivity and further evidence for an RNA-based toxicity as a major influence

PubMed Central

Brody, Jonathan R.; Hucl, Tomas; Costantino, Christina L.; Eshleman, James; Gallmeier, Eike; Zhu, Heng; Heijden, Michael S. van der; Winter, Jordan M; Wikiewicz, Agnieszka K.; Yeo, Charles J.; Kern, Scott E.

2010-01-01

The major determinants of 5-flurouracil response would appear, based on accumulated literature, to be thymidylate synthase (TYMS, TS) expression levels, TS gene modifications, and TP53 status. We tested 5-fluorouracil sensitivity in yeast and human cancer cell models in which TS or TP53 alleles and expression were varied. Polymorphic TS tandem repeat status, TS expression levels reported, TS intragenic mutations, and TP53 status in outbred and experimental cancer cell lines did not predict 5-FU sensitivity or resistance. Novel observations included a dose-resistant persistence of unbound TS protein in many cancers and, upon 5-FU treatment of the colon cancer cell line, HCT116, evidence of allelic switching favoring transcripts of the mutant TS allele. The reported alleles having an intragenic mutation could not be causally associated with major degrees of 5-FU sensitivity. In yeast, TS protein was altered upon treatment with fluoro-deoxyuridine monophosphate, but 5-FU toxicity appeared largely to be RNA-based, being rescued by uridine rather than by thymidine. Cancer cell lines were also rescued from 5-FU toxicity with uridine rather than thymidine. Additionally, a TS (CDC21) knockout yeast strain, obviating any potential role for TS protein as a target, was hypersensitive to 5-FU. When denatured proteins from cancer cells treated with radio-labeled 5-FU were, labeled species with alternative molecular weights other than TS were visualized, providing further evidence for alternative 5-FU protein targets. These data emphasize that TS and TP53 status do not consistently explain the variance in responses of fluoropyrimidine-treated cancer cells, in part due to RNA-based toxicity. PMID:19155291

P-glycoprotein expression in Ehrlich ascites tumour cells after in vitro and in vivo selection with daunorubicin.

PubMed Central

Nielsen, D.; Eriksen, J.; Maare, C.; Jakobsen, A. H.; Skovsgaard, T.

1998-01-01

Fluctuation analysis experiments were performed to assess whether selection or induction determines expression of P-glycoprotein and resistance in the murine Ehrlich ascites tumour cell line (EHR2) after exposure to daunorubicin. Thirteen expanded populations of EHR2 cells were exposed to daunorubicin 7.5 x 10(-9) M or 10(-8) M for 2 weeks. Surviving clones were scored and propagated. Only clones exposed to daunorubicin 7.5 x 10(-9) M could be expanded for investigation. Drug resistance was assessed by the tetrazolium dye (MTT) cytotoxicity assay. Western blot was used for determination of P-glycoprotein. Compared with EHR2, the variant cells were 2.5- to 5.2-fold resistant to daunorubicin (mean 3.6-fold). P-glycoprotein was significantly increased in 11 of 25 clones (44%). Analysis of variance supported the hypothesis that spontaneous mutations conferred drug resistance in EHR2 cells exposed to daunorubicin 7.5 x 10(-9) M. At this level (5 log cell killing) of drug exposure, the mutation rate was estimated at 4.1 x 10(-6) per cell generation. In contrast, induction seemed to determine resistance in EHR2 cells in vitro exposed to daunorubicin 10(-8) M. The revertant EHR2/0.8/R was treated in vivo with daunorubicin for 24 h. After treatment, P-glycoprotein increased in EHR2/0.8/R (sevenfold) and the cell line developed resistance to daunorubicin (12-fold), suggesting that in EHR2/0.8/R the mdr1 gene was activated by induction. In conclusion, our study demonstrates that P-glycoprotein expression and daunorubicin resistance are primarily acquired by selection of spontaneously arising mutants. However, under certain conditions the mdr1 gene may be activated by induction. PMID:9820176

Effect of Body Composition Methodology on Heritability Estimation of Body Fatness

PubMed Central

Elder, Sonya J.; Roberts, Susan B.; McCrory, Megan A.; Das, Sai Krupa; Fuss, Paul J.; Pittas, Anastassios G.; Greenberg, Andrew S.; Heymsfield, Steven B.; Dawson-Hughes, Bess; Bouchard, Thomas J.; Saltzman, Edward; Neale, Michael C.

2014-01-01

Heritability estimates of human body fatness vary widely and the contribution of body composition methodology to this variability is unknown. The effect of body composition methodology on estimations of genetic and environmental contributions to body fatness variation was examined in 78 adult male and female monozygotic twin pairs reared apart or together. Body composition was assessed by six methods – body mass index (BMI), dual energy x-ray absorptiometry (DXA), underwater weighing (UWW), total body water (TBW), bioelectric impedance (BIA), and skinfold thickness. Body fatness was expressed as percent body fat, fat mass, and fat mass/height2 to assess the effect of body fatness expression on heritability estimates. Model-fitting multivariate analyses were used to assess the genetic and environmental components of variance. Mean BMI was 24.5 kg/m2 (range of 17.8–43.4 kg/m2). There was a significant effect of body composition methodology (p<0.001) on heritability estimates, with UWW giving the highest estimate (69%) and BIA giving the lowest estimate (47%) for fat mass/height2. Expression of body fatness as percent body fat resulted in significantly higher heritability estimates (on average 10.3% higher) compared to expression as fat mass/height2 (p=0.015). DXA and TBW methods expressing body fatness as fat mass/height2 gave the least biased heritability assessments, based on the small contribution of specific genetic factors to their genetic variance. A model combining DXA and TBW methods resulted in a relatively low FM/ht2 heritability estimate of 60%, and significant contributions of common and unique environmental factors (22% and 18%, respectively). The body fatness heritability estimate of 60% indicates a smaller contribution of genetic variance to total variance than many previous studies using less powerful research designs have indicated. The results also highlight the importance of environmental factors and possibly genotype by environmental interactions in the etiology of weight gain and the obesity epidemic. PMID:25067962

APLP2 Regulates Refractive Error and Myopia Development in Mice and Humans

PubMed Central

Verhoeven, Virginie J. M.; Hysi, Pirro G.; Wojciechowski, Robert; Singh, Pawan Kumar; Kumar, Ashok; Thinakaran, Gopal; Williams, Cathy

2015-01-01

Myopia is the most common vision disorder and the leading cause of visual impairment worldwide. However, gene variants identified to date explain less than 10% of the variance in refractive error, leaving the majority of heritability unexplained (“missing heritability”). Previously, we reported that expression of APLP2 was strongly associated with myopia in a primate model. Here, we found that low-frequency variants near the 5’-end of APLP2 were associated with refractive error in a prospective UK birth cohort (n = 3,819 children; top SNP rs188663068, p = 5.0 × 10−4) and a CREAM consortium panel (n = 45,756 adults; top SNP rs7127037, p = 6.6 × 10−3). These variants showed evidence of differential effect on childhood longitudinal refractive error trajectories depending on time spent reading (gene x time spent reading x age interaction, p = 4.0 × 10−3). Furthermore, Aplp2 knockout mice developed high degrees of hyperopia (+11.5 ± 2.2 D, p < 1.0 × 10−4) compared to both heterozygous (-0.8 ± 2.0 D, p < 1.0 × 10−4) and wild-type (+0.3 ± 2.2 D, p < 1.0 × 10−4) littermates and exhibited a dose-dependent reduction in susceptibility to environmentally induced myopia (F(2, 33) = 191.0, p < 1.0 × 10−4). This phenotype was associated with reduced contrast sensitivity (F(12, 120) = 3.6, p = 1.5 × 10−4) and changes in the electrophysiological properties of retinal amacrine cells, which expressed Aplp2. This work identifies APLP2 as one of the “missing” myopia genes, demonstrating the importance of a low-frequency gene variant in the development of human myopia. It also demonstrates an important role for APLP2 in refractive development in mice and humans, suggesting a high level of evolutionary conservation of the signaling pathways underlying refractive eye development. PMID:26313004

General statistics of stochastic process of gene expression in eukaryotic cells.

PubMed Central

Kuznetsov, V A; Knott, G D; Bonner, R F

2002-01-01

Thousands of genes are expressed at such very low levels (< or =1 copy per cell) that global gene expression analysis of rarer transcripts remains problematic. Ambiguity in identification of rarer transcripts creates considerable uncertainty in fundamental questions such as the total number of genes expressed in an organism and the biological significance of rarer transcripts. Knowing the distribution of the true number of genes expressed at each level and the corresponding gene expression level probability function (GELPF) could help resolve these uncertainties. We found that all observed large-scale gene expression data sets in yeast, mouse, and human cells follow a Pareto-like distribution model skewed by many low-abundance transcripts. A novel stochastic model of the gene expression process predicts the universality of the GELPF both across different cell types within a multicellular organism and across different organisms. This model allows us to predict the frequency distribution of all gene expression levels within a single cell and to estimate the number of expressed genes in a single cell and in a population of cells. A random "basal" transcription mechanism for protein-coding genes in all or almost all eukaryotic cell types is predicted. This fundamental mechanism might enhance the expression of rarely expressed genes and, thus, provide a basic level of phenotypic diversity, adaptability, and random monoallelic expression in cell populations. PMID:12136033

Prevalence and Penetrance of Major Genes and Polygenes for Colorectal Cancer

PubMed Central

Win, Aung Ko; Jenkins, Mark A.; Dowty, James G.; Antoniou, Antonis C.; Lee, Andrew; Giles, Graham G.; Buchanan, Daniel D.; Clendenning, Mark; Rosty, Christophe; Ahnen, Dennis J.; Thibodeau, Stephen N.; Casey, Graham; Gallinger, Steven; Le Marchand, Loïc; Haile, Robert W.; Potter, John D.; Zheng, Yingye; Lindor, Noralane M.; Newcomb, Polly A.; Hopper, John L.; MacInnis, Robert J.

2016-01-01

Background While high-risk mutations in identified major susceptibility genes (DNA mismatch repair genes and MUTYH) account for some familial aggregation of colorectal cancer, their population prevalence and the causes of the remaining familial aggregation are not known. Methods We studied the families of 5,744 colorectal cancer cases (probands) recruited from population cancer registries in the USA, Canada and Australia and screened probands for mutations in mismatch repair genes and MUTYH. We conducted modified segregation analyses using the cancer history of first-degree relatives, conditional on the proband’s age at diagnosis. We estimated the prevalence of mutations in the identified genes, the prevalence of and hazard ratio for unidentified major gene mutations, and the variance of the residual polygenic component. Results We estimated that 1 in 279 of the population carry mutations in mismatch repair genes (MLH1= 1 in 1946, MSH2= 1 in 2841, MSH6= 1 in 758, PMS2= 1 in 714), 1 in 45 carry mutations in MUTYH, and 1 in 504 carry mutations associated with an average 31-fold increased risk of colorectal cancer in unidentified major genes. The estimated polygenic variance was reduced by 30–50% after allowing for unidentified major genes and decreased from 3.3 for age <40 years to 0.5 for age ≥70 years (equivalent to sibling relative risks of 5.1 to 1.3, respectively). Conclusion Unidentified major genes might explain one-third to one-half of the missing heritability of colorectal cancer. Impact Our findings could aid gene discovery and development of better colorectal cancer risk prediction models. PMID:27799157

The changes of gene expression profiling between segmental vitiligo, generalized vitiligo and healthy individual.

PubMed

Wang, Ping; Li, Yong; Nie, Huiqiong; Zhang, Xiaoyan; Shao, Qiongyan; Hou, Xiuli; Xu, Wen; Hong, Weisong; Xu, Aie

2016-10-01

Vitiligo is a common acquired depigmentation skin disease characterized by loss or dysfunction of melanocytes within the skin lesion, but its pathologenesis is far from lucid. The gene expression profiling of segmental vitiligo (SV) and generalized vitiligo (GV) need further investigation. To better understanding the common and distinct factors, especially in the view of gene expression profile, which were involved in the diseases development and maintenance of segmental vitiligo (SV) and generalized vitiligo (GV). Peripheral bloods were collected from SV, GV and healthy individual (HI), followed by leukocytes separation and total RNA extraction. The high-throughput whole genome expression microarrays were used to assay the gene expression profiles between HI, SV and GV. Bioinformatics tools were employed to annotated the biological function of differently expressed genes. Quantitative PCR assay was used to validate the gene expression of array. Compared to HI, 239 over-expressed genes and 175 down-expressed genes detected in SV, 688 over-expressed genes and 560 down-expressed genes were found in GV, following the criteria of log2 (fold change)≥0.585 and P value<0.05. In these differently expressed genes, 60 over-expressed genes and 60 down-expressed genes had similar tendency in SV and GV. Compared to SV, 223 genes were up regulated and 129 genes were down regulated in GV. In the SV with HI as control, the differently expressed genes were mainly involved in the adaptive immune response, cytokine-cytokine receptor interaction, chemokine signaling, focal adhesion and sphingolipid metabolism. The differently expressed genes between GV and HI were mainly involved in the innate immune, autophagy, apoptosis, melanocyte biology, ubiquitin mediated proteolysis and tyrosine metabolism, which was different from SV. While the differently expressed genes between SV and GV were mainly involved in the metabolism pathway of purine, pyrimidine, glycolysis and sphingolipid. Above results suggested that they not only shared part bio-process and signal pathway, but more important, they utilized different biological mechanism in their pathogenesis and maintenance. Our results provide a comprehensive view on the gene expression profiling change between SV and GV especially in the side of leukocytes, and may facilitate the future study on their molecular mechanism and theraputic targets. Copyright © 2016 Japanese Society for Investigative Dermatology. Published by Elsevier Ireland Ltd. All rights reserved.

Detection of gene-environment interaction in pedigree data using genome-wide genotypes.

PubMed

Nivard, Michel G; Middeldorp, Christel M; Lubke, Gitta; Hottenga, Jouke-Jan; Abdellaoui, Abdel; Boomsma, Dorret I; Dolan, Conor V

2016-12-01

Heritability may be estimated using phenotypic data collected in relatives or in distantly related individuals using genome-wide single nucleotide polymorphism (SNP) data. We combined these approaches by re-parameterizing the model proposed by Zaitlen et al and extended this model to include moderation of (total and SNP-based) genetic and environmental variance components by a measured moderator. By means of data simulation, we demonstrated that the type 1 error rates of the proposed test are correct and parameter estimates are accurate. As an application, we considered the moderation by age or year of birth of variance components associated with body mass index (BMI), height, attention problems (AP), and symptoms of anxiety and depression. The genetic variance of BMI was found to increase with age, but the environmental variance displayed a greater increase with age, resulting in a proportional decrease of the heritability of BMI. Environmental variance of height increased with year of birth. The environmental variance of AP increased with age. These results illustrate the assessment of moderation of environmental and genetic effects, when estimating heritability from combined SNP and family data. The assessment of moderation of genetic and environmental variance will enhance our understanding of the genetic architecture of complex traits.

Hilbert-Schmidt and Sobol sensitivity indices for static and time series Wnt signaling measurements in colorectal cancer - part A.

PubMed

Sinha, Shriprakash

2017-12-04

Ever since the accidental discovery of Wingless [Sharma R.P., Drosophila information service, 1973, 50, p 134], research in the field of Wnt signaling pathway has taken significant strides in wet lab experiments and various cancer clinical trials, augmented by recent developments in advanced computational modeling of the pathway. Information rich gene expression profiles reveal various aspects of the signaling pathway and help in studying different issues simultaneously. Hitherto, not many computational studies exist which incorporate the simultaneous study of these issues. This manuscript ∙ explores the strength of contributing factors in the signaling pathway, ∙ analyzes the existing causal relations among the inter/extracellular factors effecting the pathway based on prior biological knowledge and ∙ investigates the deviations in fold changes in the recently found prevalence of psychophysical laws working in the pathway. To achieve this goal, local and global sensitivity analysis is conducted on the (non)linear responses between the factors obtained from static and time series expression profiles using the density (Hilbert-Schmidt Information Criterion) and variance (Sobol) based sensitivity indices. The results show the advantage of using density based indices over variance based indices mainly due to the former's employment of distance measures & the kernel trick via Reproducing kernel Hilbert space (RKHS) that capture nonlinear relations among various intra/extracellular factors of the pathway in a higher dimensional space. In time series data, using these indices it is now possible to observe where in time, which factors get influenced & contribute to the pathway, as changes in concentration of the other factors are made. This synergy of prior biological knowledge, sensitivity analysis & representations in higher dimensional spaces can facilitate in time based administration of target therapeutic drugs & reveal hidden biological information within colorectal cancer samples.

Identification of reference genes in human myelomonocytic cells for gene expression studies in altered gravity.

PubMed

Thiel, Cora S; Hauschild, Swantje; Tauber, Svantje; Paulsen, Katrin; Raig, Christiane; Raem, Arnold; Biskup, Josefine; Gutewort, Annett; Hürlimann, Eva; Unverdorben, Felix; Buttron, Isabell; Lauber, Beatrice; Philpot, Claudia; Lier, Hartwin; Engelmann, Frank; Layer, Liliana E; Ullrich, Oliver

2015-01-01

Gene expression studies are indispensable for investigation and elucidation of molecular mechanisms. For the process of normalization, reference genes ("housekeeping genes") are essential to verify gene expression analysis. Thus, it is assumed that these reference genes demonstrate similar expression levels over all experimental conditions. However, common recommendations about reference genes were established during 1 g conditions and therefore their applicability in studies with altered gravity has not been demonstrated yet. The microarray technology is frequently used to generate expression profiles under defined conditions and to determine the relative difference in expression levels between two or more different states. In our study, we searched for potential reference genes with stable expression during different gravitational conditions (microgravity, normogravity, and hypergravity) which are additionally not altered in different hardware systems. We were able to identify eight genes (ALB, B4GALT6, GAPDH, HMBS, YWHAZ, ABCA5, ABCA9, and ABCC1) which demonstrated no altered gene expression levels in all tested conditions and therefore represent good candidates for the standardization of gene expression studies in altered gravity.

Romantic Jealousy and Relational Satisfaction: A Look at the Impact of Jealousy Experience and Expression.

ERIC Educational Resources Information Center

Andersen, Peter A.; And Others

1995-01-01

Finds that cognitive jealousy is a more potent predictor of relational satisfaction than emotional jealousy, individuals using integrative communication and/or expression of negative affect to communicate jealousy are most likely to be satisfied with their relationships, and jealousy expression accounts for significantly more variance in…

Adaptation of Musca domestica L. Field Population to Laboratory Breeding Causes Transcriptional Alterations

PubMed Central

Højland, Dorte H.; Jensen, Karl-Martin Vagn; Kristensen, Michael

2014-01-01

Background The housefly, Musca domestica, has developed resistance to most insecticides applied for its control. Expression of genes coding for detoxification enzymes play a role in the response of the housefly when encountered by a xenobiotic. The highest level of constitutive gene expression of nine P450 genes was previously found in a newly-collected susceptible field population in comparison to three insecticide-resistant laboratory strains and a laboratory reference strain. Results We compared gene expression of five P450s by qPCR as well as global gene expression by RNAseq in the newly-acquired field population (845b) in generation F1, F13 and F29 to test how gene expression changes following laboratory adaption. Four (CYP6A1, CYP6A36, CYP6D3, CYP6G4) of five investigated P450 genes adapted to breeding by decreasing expression. CYP6D1 showed higher female expression in F29 than in F1. For males, about half of the genes accessed in the global gene expression were up-regulated in F13 and F29 in comparison with the F1 population. In females, 60% of the genes were up-regulated in F13 in comparison with F1, while 33% were up-regulated in F29. Forty potential P450 genes were identified. In most cases, P450 gene expression was decreased in F13 flies in comparison with F1. Gene expression then increased from F13 to F29 in males and decreased further in females. Conclusion The global gene expression changes massively during adaptation to laboratory breeding. In general, global expression decreased as a result of laboratory adaption in males, while female expression was not unidirectional. Expression of P450 genes was in general down-regulated as a result of laboratory adaption. Expression of hexamerin, coding for a storage protein was increased, while gene expression of genes coding for amylases decreased. This suggests a major impact of the surrounding environment on gene response to xenobiotics and genetic composition of housefly strains. PMID:24489682

IDENTIFYING GENETIC ASSOCIATIONS WITH VARIABILITY IN METABOLIC HEALTH AND BLOOD COUNT LABORATORY VALUES: DIVING INTO THE QUANTITATIVE TRAITS BY LEVERAGING LONGITUDINAL DATA FROM AN EHR.

PubMed

Verma, Shefali S; Lucas, Anastasia M; Lavage, Daniel R; Leader, Joseph B; Metpally, Raghu; Krishnamurthy, Sarathbabu; Dewey, Frederick; Borecki, Ingrid; Lopez, Alexander; Overton, John; Penn, John; Reid, Jeffrey; Pendergrass, Sarah A; Breitwieser, Gerda; Ritchie, Marylyn D

2017-01-01

A wide range of patient health data is recorded in Electronic Health Records (EHR). This data includes diagnosis, surgical procedures, clinical laboratory measurements, and medication information. Together this information reflects the patient's medical history. Many studies have efficiently used this data from the EHR to find associations that are clinically relevant, either by utilizing International Classification of Diseases, version 9 (ICD-9) codes or laboratory measurements, or by designing phenotype algorithms to extract case and control status with accuracy from the EHR. Here we developed a strategy to utilize longitudinal quantitative trait data from the EHR at Geisinger Health System focusing on outpatient metabolic and complete blood panel data as a starting point. Comprehensive Metabolic Panel (CMP) as well as Complete Blood Counts (CBC) are parts of routine care and provide a comprehensive picture from high level screening of patients' overall health and disease. We randomly split our data into two datasets to allow for discovery and replication. We first conducted a genome-wide association study (GWAS) with median values of 25 different clinical laboratory measurements to identify variants from Human Omni Express Exome beadchip data that are associated with these measurements. We identified 687 variants that associated and replicated with the tested clinical measurements at p<5×10-08. Since longitudinal data from the EHR provides a record of a patient's medical history, we utilized this information to further investigate the ICD-9 codes that might be associated with differences in variability of the measurements in the longitudinal dataset. We identified low and high variance patients by looking at changes within their individual longitudinal EHR laboratory results for each of the 25 clinical lab values (thus creating 50 groups - a high variance and a low variance for each lab variable). We then performed a PheWAS analysis with ICD-9 diagnosis codes, separately in the high variance group and the low variance group for each lab variable. We found 717 PheWAS associations that replicated at a p-value less than 0.001. Next, we evaluated the results of this study by comparing the association results between the high and low variance groups. For example, we found 39 SNPs (in multiple genes) associated with ICD-9 250.01 (Type-I diabetes) in patients with high variance of plasma glucose levels, but not in patients with low variance in plasma glucose levels. Another example is the association of 4 SNPs in UMOD with chronic kidney disease in patients with high variance for aspartate aminotransferase (discovery p-value: 8.71×10-09 and replication p-value: 2.03×10-06). In general, we see a pattern of many more statistically significant associations from patients with high variance in the quantitative lab variables, in comparison with the low variance group across all of the 25 laboratory measurements. This study is one of the first of its kind to utilize quantitative trait variance from longitudinal laboratory data to find associations among genetic variants and clinical phenotypes obtained from an EHR, integrating laboratory values and diagnosis codes to understand the genetic complexities of common diseases.

The effect of trait type and strength of selection on heritability and evolvability in an island bird population.

PubMed

Wheelwright, Nathaniel T; Keller, Lukas F; Postma, Erik

2014-11-01

The heritability (h(2) ) of fitness traits is often low. Although this has been attributed to directional selection having eroded genetic variation in direct proportion to the strength of selection, heritability does not necessarily reflect a trait's additive genetic variance and evolutionary potential ("evolvability"). Recent studies suggest that the low h(2) of fitness traits in wild populations is caused not by a paucity of additive genetic variance (VA ) but by greater environmental or nonadditive genetic variance (VR ). We examined the relationship between h(2) and variance-standardized selection intensities (i or βσ ), and between evolvability (IA :VA divided by squared phenotypic trait mean) and mean-standardized selection gradients (βμ ). Using 24 years of data from an island population of Savannah sparrows, we show that, across diverse traits, h(2) declines with the strength of selection, whereas IA and IR (VR divided by squared trait mean) are independent of the strength of selection. Within trait types (morphological, reproductive, life-history), h(2) , IA , and IR are all independent of the strength of selection. This indicates that certain traits have low heritability because of increased residual variance due to the age at which they are expressed or the multiple factors influencing their expression, rather than their association with fitness. © 2014 The Author(s). Evolution © 2014 The Society for the Study of Evolution.

Cross-frequency and band-averaged response variance prediction in the hybrid deterministic-statistical energy analysis method

NASA Astrophysics Data System (ADS)

Reynders, Edwin P. B.; Langley, Robin S.

2018-08-01

The hybrid deterministic-statistical energy analysis method has proven to be a versatile framework for modeling built-up vibro-acoustic systems. The stiff system components are modeled deterministically, e.g., using the finite element method, while the wave fields in the flexible components are modeled as diffuse. In the present paper, the hybrid method is extended such that not only the ensemble mean and variance of the harmonic system response can be computed, but also of the band-averaged system response. This variance represents the uncertainty that is due to the assumption of a diffuse field in the flexible components of the hybrid system. The developments start with a cross-frequency generalization of the reciprocity relationship between the total energy in a diffuse field and the cross spectrum of the blocked reverberant loading at the boundaries of that field. By making extensive use of this generalization in a first-order perturbation analysis, explicit expressions are derived for the cross-frequency and band-averaged variance of the vibrational energies in the diffuse components and for the cross-frequency and band-averaged variance of the cross spectrum of the vibro-acoustic field response of the deterministic components. These expressions are extensively validated against detailed Monte Carlo analyses of coupled plate systems in which diffuse fields are simulated by randomly distributing small point masses across the flexible components, and good agreement is found.

An RNA-Seq based gene expression atlas of the common bean.

PubMed

O'Rourke, Jamie A; Iniguez, Luis P; Fu, Fengli; Bucciarelli, Bruna; Miller, Susan S; Jackson, Scott A; McClean, Philip E; Li, Jun; Dai, Xinbin; Zhao, Patrick X; Hernandez, Georgina; Vance, Carroll P

2014-10-06

Common bean (Phaseolus vulgaris) is grown throughout the world and comprises roughly 50% of the grain legumes consumed worldwide. Despite this, genetic resources for common beans have been lacking. Next generation sequencing, has facilitated our investigation of the gene expression profiles associated with biologically important traits in common bean. An increased understanding of gene expression in common bean will improve our understanding of gene expression patterns in other legume species. Combining recently developed genomic resources for Phaseolus vulgaris, including predicted gene calls, with RNA-Seq technology, we measured the gene expression patterns from 24 samples collected from seven tissues at developmentally important stages and from three nitrogen treatments. Gene expression patterns throughout the plant were analyzed to better understand changes due to nodulation, seed development, and nitrogen utilization. We have identified 11,010 genes differentially expressed with a fold change ≥ 2 and a P-value < 0.05 between different tissues at the same time point, 15,752 genes differentially expressed within a tissue due to changes in development, and 2,315 genes expressed only in a single tissue. These analyses identified 2,970 genes with expression patterns that appear to be directly dependent on the source of available nitrogen. Finally, we have assembled this data in a publicly available database, The Phaseolus vulgaris Gene Expression Atlas (Pv GEA), http://plantgrn.noble.org/PvGEA/ . Using the website, researchers can query gene expression profiles of their gene of interest, search for genes expressed in different tissues, or download the dataset in a tabular form. These data provide the basis for a gene expression atlas, which will facilitate functional genomic studies in common bean. Analysis of this dataset has identified genes important in regulating seed composition and has increased our understanding of nodulation and impact of the nitrogen source on assimilation and distribution throughout the plant.

On the Interplay between the Evolvability and Network Robustness in an Evolutionary Biological Network: A Systems Biology Approach

PubMed Central

Chen, Bor-Sen; Lin, Ying-Po

2011-01-01

In the evolutionary process, the random transmission and mutation of genes provide biological diversities for natural selection. In order to preserve functional phenotypes between generations, gene networks need to evolve robustly under the influence of random perturbations. Therefore, the robustness of the phenotype, in the evolutionary process, exerts a selection force on gene networks to keep network functions. However, gene networks need to adjust, by variations in genetic content, to generate phenotypes for new challenges in the network’s evolution, ie, the evolvability. Hence, there should be some interplay between the evolvability and network robustness in evolutionary gene networks. In this study, the interplay between the evolvability and network robustness of a gene network and a biochemical network is discussed from a nonlinear stochastic system point of view. It was found that if the genetic robustness plus environmental robustness is less than the network robustness, the phenotype of the biological network is robust in evolution. The tradeoff between the genetic robustness and environmental robustness in evolution is discussed from the stochastic stability robustness and sensitivity of the nonlinear stochastic biological network, which may be relevant to the statistical tradeoff between bias and variance, the so-called bias/variance dilemma. Further, the tradeoff could be considered as an antagonistic pleiotropic action of a gene network and discussed from the systems biology perspective. PMID:22084563

Going beyond the Mean: Using Variances to Enhance Understanding of the Impact of Educational Interventions for Multilevel Models

ERIC Educational Resources Information Center

Peralta, Yadira; Moreno, Mario; Harwell, Michael; Guzey, S. Selcen; Moore, Tamara J.

2018-01-01

Variance heterogeneity is a common feature of educational data when treatment differences expressed through means are present, and often reflects a treatment by subject interaction with respect to an outcome variable. Identifying variables that account for this interaction can enhance understanding of whom a treatment does and does not benefit in…

Analysis of bHLH coding genes using gene co-expression network approach.

PubMed

Srivastava, Swati; Sanchita; Singh, Garima; Singh, Noopur; Srivastava, Gaurava; Sharma, Ashok

2016-07-01

Network analysis provides a powerful framework for the interpretation of data. It uses novel reference network-based metrices for module evolution. These could be used to identify module of highly connected genes showing variation in co-expression network. In this study, a co-expression network-based approach was used for analyzing the genes from microarray data. Our approach consists of a simple but robust rank-based network construction. The publicly available gene expression data of Solanum tuberosum under cold and heat stresses were considered to create and analyze a gene co-expression network. The analysis provide highly co-expressed module of bHLH coding genes based on correlation values. Our approach was to analyze the variation of genes expression, according to the time period of stress through co-expression network approach. As the result, the seed genes were identified showing multiple connections with other genes in the same cluster. Seed genes were found to be vary in different time periods of stress. These analyzed seed genes may be utilized further as marker genes for developing the stress tolerant plant species.

A General Definition of the Heritable Variation That Determines the Potential of a Population to Respond to Selection

PubMed Central

Bijma, Piter

2011-01-01

Genetic selection is a major force shaping life on earth. In classical genetic theory, response to selection is the product of the strength of selection and the additive genetic variance in a trait. The additive genetic variance reflects a population’s intrinsic potential to respond to selection. The ordinary additive genetic variance, however, ignores the social organization of life. With social interactions among individuals, individual trait values may depend on genes in others, a phenomenon known as indirect genetic effects. Models accounting for indirect genetic effects, however, lack a general definition of heritable variation. Here I propose a general definition of the heritable variation that determines the potential of a population to respond to selection. This generalizes the concept of heritable variance to any inheritance model and level of organization. The result shows that heritable variance determining potential response to selection is the variance among individuals in the heritable quantity that determines the population mean trait value, rather than the usual additive genetic component of phenotypic variance. It follows, therefore, that heritable variance may exceed phenotypic variance among individuals, which is impossible in classical theory. This work also provides a measure of the utilization of heritable variation for response to selection and integrates two well-known models of maternal genetic effects. The result shows that relatedness between the focal individual and the individuals affecting its fitness is a key determinant of the utilization of heritable variance for response to selection. PMID:21926298

A general definition of the heritable variation that determines the potential of a population to respond to selection.

PubMed

Bijma, Piter

2011-12-01

Genetic selection is a major force shaping life on earth. In classical genetic theory, response to selection is the product of the strength of selection and the additive genetic variance in a trait. The additive genetic variance reflects a population's intrinsic potential to respond to selection. The ordinary additive genetic variance, however, ignores the social organization of life. With social interactions among individuals, individual trait values may depend on genes in others, a phenomenon known as indirect genetic effects. Models accounting for indirect genetic effects, however, lack a general definition of heritable variation. Here I propose a general definition of the heritable variation that determines the potential of a population to respond to selection. This generalizes the concept of heritable variance to any inheritance model and level of organization. The result shows that heritable variance determining potential response to selection is the variance among individuals in the heritable quantity that determines the population mean trait value, rather than the usual additive genetic component of phenotypic variance. It follows, therefore, that heritable variance may exceed phenotypic variance among individuals, which is impossible in classical theory. This work also provides a measure of the utilization of heritable variation for response to selection and integrates two well-known models of maternal genetic effects. The result shows that relatedness between the focal individual and the individuals affecting its fitness is a key determinant of the utilization of heritable variance for response to selection.

Transcriptional analysis of apple fruit proanthocyanidin biosynthesis

PubMed Central

Henry-Kirk, Rebecca A.

2012-01-01

Proanthocyanidins (PAs) are products of the flavonoid pathway, which also leads to the production of anthocyanins and flavonols. Many flavonoids have antioxidant properties and may have beneficial effects for human health. PAs are found in the seeds and fruits of many plants. In apple fruit (Malus × domestica Borkh.), the flavonoid biosynthetic pathway is most active in the skin, with the flavan-3-ols, catechin, and epicatechin acting as the initiating units for the synthesis of PA polymers. This study examined the genes involved in the production of PAs in three apple cultivars: two heritage apple cultivars, Hetlina and Devonshire Quarrenden, and a commercial cultivar, Royal Gala. HPLC analysis shows that tree-ripe fruit from Hetlina and Devonshire Quarrenden had a higher phenolic content than Royal Gala. Epicatechin and catechin biosynthesis is under the control of the biosynthetic enzymes anthocyanidin reductase (ANR) and leucoanthocyanidin reductase (LAR1), respectively. Counter-intuitively, real-time quantitative PCR analysis showed that the expression levels of Royal Gala LAR1 and ANR were significantly higher than those of both Devonshire Quarrenden and Hetlina. This suggests that a compensatory feedback mechanism may be active, whereby low concentrations of PAs may induce higher expression of gene transcripts. Further investigation is required into the regulation of these key enzymes in apple. Abbreviations:ANOVAanalysis of varianceANRanthocyanidin reductaseDADdiode array detectorDAFBdays after full bloomDFRdihydroflavonol reductaseLARleucoanthocyanidin reductaseLC-MSliquid chromatography/mass spectrometryPAproanthocyanidinqPCRreal-time quantitative PCR PMID:22859681

Tobacco Smoking Leads to Extensive Genome-Wide Changes in DNA Methylation

PubMed Central

Zeilinger, Sonja; Kühnel, Brigitte; Klopp, Norman; Baurecht, Hansjörg; Kleinschmidt, Anja; Gieger, Christian; Weidinger, Stephan; Lattka, Eva; Adamski, Jerzy; Peters, Annette; Strauch, Konstantin

2013-01-01

Environmental factors such as tobacco smoking may have long-lasting effects on DNA methylation patterns, which might lead to changes in gene expression and in a broader context to the development or progression of various diseases. We conducted an epigenome-wide association study (EWAs) comparing current, former and never smokers from 1793 participants of the population-based KORA F4 panel, with replication in 479 participants from the KORA F3 panel, carried out by the 450K BeadChip with genomic DNA obtained from whole blood. We observed wide-spread differences in the degree of site-specific methylation (with p-values ranging from 9.31E-08 to 2.54E-182) as a function of tobacco smoking in each of the 22 autosomes, with the percent of variance explained by smoking ranging from 1.31 to 41.02. Depending on cessation time and pack-years, methylation levels in former smokers were found to be close to the ones seen in never smokers. In addition, methylation-specific protein binding patterns were observed for cg05575921 within AHRR, which had the highest level of detectable changes in DNA methylation associated with tobacco smoking (–24.40% methylation; p = 2.54E-182), suggesting a regulatory role for gene expression. The results of our study confirm the broad effect of tobacco smoking on the human organism, but also show that quitting tobacco smoking presumably allows regaining the DNA methylation state of never smokers. PMID:23691101

Tobacco smoking leads to extensive genome-wide changes in DNA methylation.

PubMed

Zeilinger, Sonja; Kühnel, Brigitte; Klopp, Norman; Baurecht, Hansjörg; Kleinschmidt, Anja; Gieger, Christian; Weidinger, Stephan; Lattka, Eva; Adamski, Jerzy; Peters, Annette; Strauch, Konstantin; Waldenberger, Melanie; Illig, Thomas

2013-01-01

Environmental factors such as tobacco smoking may have long-lasting effects on DNA methylation patterns, which might lead to changes in gene expression and in a broader context to the development or progression of various diseases. We conducted an epigenome-wide association study (EWAs) comparing current, former and never smokers from 1793 participants of the population-based KORA F4 panel, with replication in 479 participants from the KORA F3 panel, carried out by the 450K BeadChip with genomic DNA obtained from whole blood. We observed wide-spread differences in the degree of site-specific methylation (with p-values ranging from 9.31E-08 to 2.54E-182) as a function of tobacco smoking in each of the 22 autosomes, with the percent of variance explained by smoking ranging from 1.31 to 41.02. Depending on cessation time and pack-years, methylation levels in former smokers were found to be close to the ones seen in never smokers. In addition, methylation-specific protein binding patterns were observed for cg05575921 within AHRR, which had the highest level of detectable changes in DNA methylation associated with tobacco smoking (-24.40% methylation; p = 2.54E-182), suggesting a regulatory role for gene expression. The results of our study confirm the broad effect of tobacco smoking on the human organism, but also show that quitting tobacco smoking presumably allows regaining the DNA methylation state of never smokers.

Characterization of basal gene expression trends over a diurnal cycle in Xiphophorus maculatus skin, brain and liver.

PubMed

Lu, Yuan; Reyes, Jose; Walter, Sean; Gonzalez, Trevor; Medrano, Geraldo; Boswell, Mikki; Boswell, William; Savage, Markita; Walter, Ronald

2018-06-01

Evolutionarily conserved diurnal circadian mechanisms maintain oscillating patterns of gene expression based on the day-night cycle. Xiphophorus fish have been used to evaluate transcriptional responses after exposure to various light sources and it was determined that each source incites distinct genetic responses in skin tissue. However, basal expression levels of genes that show oscillating expression patterns in day-night cycle, may affect the outcomes of such experiments, since basal gene expression levels at each point in the circadian path may influence the profile of identified light responsive genes. Lack of knowledge regarding diurnal fluctuations in basal gene expression patterns may confound the understanding of genetic responses to external stimuli (e.g., light) since the dynamic nature of gene expression implies animals subjected to stimuli at different times may be at very different stages within the continuum of genetic homeostasis. We assessed basal gene expression changes over a 24-hour period in 200 select Xiphophorus gene targets known to transcriptionally respond to various types of light exposure. We identified 22 genes in skin, 36 genes in brain and 28 genes in liver that exhibit basal oscillation of expression patterns. These genes, including known circadian regulators, produced the expected expression patterns over a 24-hour cycle when compared to circadian regulatory genes identified in other species, especially human and other vertebrate animal models. Our results suggest the regulatory network governing diurnal oscillating gene expression is similar between Xiphophorus and other vertebrates for the three Xiphophorus organs tested. In addition, we were able to categorize light responsive gene sets in Xiphophorus that do, and do not, exhibit circadian based oscillating expression patterns. Copyright © 2017 Elsevier Inc. All rights reserved.

Identification of Reference Genes in Human Myelomonocytic Cells for Gene Expression Studies in Altered Gravity

PubMed Central

Thiel, Cora S.; Hauschild, Swantje; Tauber, Svantje; Paulsen, Katrin; Raig, Christiane; Raem, Arnold; Biskup, Josefine; Gutewort, Annett; Hürlimann, Eva; Philpot, Claudia; Lier, Hartwin; Engelmann, Frank; Layer, Liliana E.

2015-01-01

Gene expression studies are indispensable for investigation and elucidation of molecular mechanisms. For the process of normalization, reference genes (“housekeeping genes”) are essential to verify gene expression analysis. Thus, it is assumed that these reference genes demonstrate similar expression levels over all experimental conditions. However, common recommendations about reference genes were established during 1 g conditions and therefore their applicability in studies with altered gravity has not been demonstrated yet. The microarray technology is frequently used to generate expression profiles under defined conditions and to determine the relative difference in expression levels between two or more different states. In our study, we searched for potential reference genes with stable expression during different gravitational conditions (microgravity, normogravity, and hypergravity) which are additionally not altered in different hardware systems. We were able to identify eight genes (ALB, B4GALT6, GAPDH, HMBS, YWHAZ, ABCA5, ABCA9, and ABCC1) which demonstrated no altered gene expression levels in all tested conditions and therefore represent good candidates for the standardization of gene expression studies in altered gravity. PMID:25654098

Life-cycle and growth-phase-dependent regulation of the ubiquitin genes of Trypanosoma cruzi.

PubMed

Manning-Cela, Rebeca; Jaishankar, Sobha; Swindle, John

2006-07-01

Trypanosoma cruzi, the causative agent of Chagas disease, exhibits a complex life cycle that is accompanied by the stage-specific gene expression. At the molecular level, very little is known about gene regulation in trypanosomes. Complex gene organizations coupled with polycistronic transcription units make the analysis of regulated gene expression difficult in trypanosomes. The ubiquitin genes of T. cruzi are a good example of this complexity. They are organized as a single cluster containing five ubiquitin fusion (FUS) and five polyubiquitin (PUB) genes that are polycistronically transcribed but expressed differently in response to developmental and environmental changes. Gene replacements were used to study FUS and PUB gene expression at different stages of growth and at different points in the life cycle of T. cruzi. Based on the levels of reporter gene expression, it was determined that FUS1 expression was downregulated as the parasites approached stationary phase, whereas PUB12.5 polyubiquitin gene expression increased. Conversely, FUS1 expression increases when epimastigotes and amastigotes differentiate into trypomastigotes, whereas the expression of PUB12.5 decreases when epimastigotes differentiate into amastigotes and trypomastigotes. Although the level of CAT activity in logarithmic growing epimastigotes is six- to seven-fold higher when the gene was expressed from the FUS1 locus than when expressed from the PUB12.5 locus, the rate of transcription from the two loci was the same implying that post-transcriptional mechanisms play a dominant role in the regulation of gene expression.

Comparison of the efficiency between two sampling plans for aflatoxins analysis in maize

PubMed Central

Mallmann, Adriano Olnei; Marchioro, Alexandro; Oliveira, Maurício Schneider; Rauber, Ricardo Hummes; Dilkin, Paulo; Mallmann, Carlos Augusto

2014-01-01

Variance and performance of two sampling plans for aflatoxins quantification in maize were evaluated. Eight lots of maize were sampled using two plans: manual, using sampling spear for kernels; and automatic, using a continuous flow to collect milled maize. Total variance and sampling, preparation, and analysis variance were determined and compared between plans through multifactor analysis of variance. Four theoretical distribution models were used to compare aflatoxins quantification distributions in eight maize lots. The acceptance and rejection probabilities for a lot under certain aflatoxin concentration were determined using variance and the information on the selected distribution model to build the operational characteristic curves (OC). Sampling and total variance were lower at the automatic plan. The OC curve from the automatic plan reduced both consumer and producer risks in comparison to the manual plan. The automatic plan is more efficient than the manual one because it expresses more accurately the real aflatoxin contamination in maize. PMID:24948911

Maintaining evolvability.

PubMed

Crow, James F

2008-12-01

Although molecular methods, such as QTL mapping, have revealed a number of loci with large effects, it is still likely that the bulk of quantitative variability is due to multiple factors, each with small effect. Typically, these have a large additive component. Conventional wisdom argues that selection, natural or artificial, uses up additive variance and thus depletes its supply. Over time, the variance should be reduced, and at equilibrium be near zero. This is especially expected for fitness and traits highly correlated with it. Yet, populations typically have a great deal of additive variance, and do not seem to run out of genetic variability even after many generations of directional selection. Long-term selection experiments show that populations continue to retain seemingly undiminished additive variance despite large changes in the mean value. I propose that there are several reasons for this. (i) The environment is continually changing so that what was formerly most fit no longer is. (ii) There is an input of genetic variance from mutation, and sometimes from migration. (iii) As intermediate-frequency alleles increase in frequency towards one, producing less variance (as p --> 1, p(1 - p) --> 0), others that were originally near zero become more common and increase the variance. Thus, a roughly constant variance is maintained. (iv) There is always selection for fitness and for characters closely related to it. To the extent that the trait is heritable, later generations inherit a disproportionate number of genes acting additively on the trait, thus increasing genetic variance. For these reasons a selected population retains its ability to evolve. Of course, genes with large effect are also important. Conspicuous examples are the small number of loci that changed teosinte to maize, and major phylogenetic changes in the animal kingdom. The relative importance of these along with duplications, chromosome rearrangements, horizontal transmission and polyploidy is yet to be determined. It is likely that only a case-by-case analysis will provide the answers. Despite the difficulties that complex interactions cause for evolution in Mendelian populations, such populations nevertheless evolve very well. Longlasting species must have evolved mechanisms for coping with such problems. Since such difficulties do not arise in asexual populations, a comparison of epistatic patterns in closely related sexual and asexual species might provide some important insights.

Gene expression changes with age in skin, adipose tissue, blood and brain.

PubMed

Glass, Daniel; Viñuela, Ana; Davies, Matthew N; Ramasamy, Adaikalavan; Parts, Leopold; Knowles, David; Brown, Andrew A; Hedman, Asa K; Small, Kerrin S; Buil, Alfonso; Grundberg, Elin; Nica, Alexandra C; Di Meglio, Paola; Nestle, Frank O; Ryten, Mina; Durbin, Richard; McCarthy, Mark I; Deloukas, Panagiotis; Dermitzakis, Emmanouil T; Weale, Michael E; Bataille, Veronique; Spector, Tim D

2013-07-26

Previous studies have demonstrated that gene expression levels change with age. These changes are hypothesized to influence the aging rate of an individual. We analyzed gene expression changes with age in abdominal skin, subcutaneous adipose tissue and lymphoblastoid cell lines in 856 female twins in the age range of 39-85 years. Additionally, we investigated genotypic variants involved in genotype-by-age interactions to understand how the genomic regulation of gene expression alters with age. Using a linear mixed model, differential expression with age was identified in 1,672 genes in skin and 188 genes in adipose tissue. Only two genes expressed in lymphoblastoid cell lines showed significant changes with age. Genes significantly regulated by age were compared with expression profiles in 10 brain regions from 100 postmortem brains aged 16 to 83 years. We identified only one age-related gene common to the three tissues. There were 12 genes that showed differential expression with age in both skin and brain tissue and three common to adipose and brain tissues. Skin showed the most age-related gene expression changes of all the tissues investigated, with many of the genes being previously implicated in fatty acid metabolism, mitochondrial activity, cancer and splicing. A significant proportion of age-related changes in gene expression appear to be tissue-specific with only a few genes sharing an age effect in expression across tissues. More research is needed to improve our understanding of the genetic influences on aging and the relationship with age-related diseases.

Differential expression profiles and pathways of genes in sugarcane leaf at elongation stage in response to drought stress

PubMed Central

Li, Changning; Nong, Qian; Solanki, Manoj Kumar; Liang, Qiang; Xie, Jinlan; Liu, Xiaoyan; Li, Yijie; Wang, Weizan; Yang, Litao; Li, Yangrui

2016-01-01

Water stress causes considerable yield losses in sugarcane. To investigate differentially expressed genes under water stress, a pot experiment was performed with the sugarcane variety GT21 at three water-deficit levels (mild, moderate, and severe) during the elongation stage and gene expression was analyzed using microarray technology. Physiological parameters of sugarcane showed significant alterations in response to drought stress. Based on the expression profile of 15,593 sugarcane genes, 1,501 (9.6%) genes were differentially expressed under different water-level treatments; 821 genes were upregulated and 680 genes were downregulated. A gene similarity analysis showed that approximately 62.6% of the differentially expressed genes shared homology with functional proteins. In a Gene Ontology (GO) analysis, 901 differentially expressed genes were assigned to 36 GO categories. Moreover, 325 differentially expressed genes were classified into 101 pathway categories involved in various processes, such as the biosynthesis of secondary metabolites, ribosomes, carbon metabolism, etc. In addition, some unannotated genes were detected; these may provide a basis for studies of water-deficit tolerance. The reliability of the observed expression patterns was confirmed by RT-PCR. The results of this study may help identify useful genes for improving drought tolerance in sugarcane. PMID:27170459

A multidisciplinary approach providing new insight into fruit flesh browning physiology in apple (Malus x domestica Borkh.).

PubMed

Di Guardo, Mario; Tadiello, Alice; Farneti, Brian; Lorenz, Giorgia; Masuero, Domenico; Vrhovsek, Urska; Costa, Guglielmo; Velasco, Riccardo; Costa, Fabrizio

2013-01-01

In terms of the quality of minimally processed fruit, flesh browning is fundamentally important in the development of an aesthetically unpleasant appearance, with consequent off-flavours. The development of browning depends on the enzymatic action of the polyphenol oxidase (PPO). In the 'Golden Delicious' apple genome ten PPO genes were initially identified and located on three main chromosomes (2, 5 and 10). Of these genes, one element in particular, here called Md-PPO, located on chromosome 10, was further investigated and genetically mapped in two apple progenies ('Fuji x Pink Lady' and 'Golden Delicious x Braeburn'). Both linkage maps, made up of 481 and 608 markers respectively, were then employed to find QTL regions associated with fruit flesh browning, allowing the detection of 25 QTLs related to several browning parameters. These were distributed over six linkage groups with LOD values spanning from 3.08 to 4.99 and showed a rate of phenotypic variance from 26.1 to 38.6%. Anchoring of these intervals to the apple genome led to the identification of several genes involved in polyphenol synthesis and cell wall metabolism. Finally, the expression profile of two specific candidate genes, up and downstream of the polyphenolic pathway, namely phenylalanine ammonia lyase (PAL) and polyphenol oxidase (PPO), provided insight into flesh browning physiology. Md-PPO was further analyzed and two haplotypes were characterised and associated with fruit flesh browning in apple.

A Multidisciplinary Approach Providing New Insight into Fruit Flesh Browning Physiology in Apple (Malus x domestica Borkh.)

PubMed Central

Farneti, Brian; Lorenz, Giorgia; Masuero, Domenico; Vrhovsek, Urska; Costa, Guglielmo; Velasco, Riccardo; Costa, Fabrizio

2013-01-01

In terms of the quality of minimally processed fruit, flesh browning is fundamentally important in the development of an aesthetically unpleasant appearance, with consequent off-flavours. The development of browning depends on the enzymatic action of the polyphenol oxidase (PPO). In the ‘Golden Delicious’ apple genome ten PPO genes were initially identified and located on three main chromosomes (2, 5 and 10). Of these genes, one element in particular, here called Md-PPO, located on chromosome 10, was further investigated and genetically mapped in two apple progenies (‘Fuji x Pink Lady’ and ‘Golden Delicious x Braeburn’). Both linkage maps, made up of 481 and 608 markers respectively, were then employed to find QTL regions associated with fruit flesh browning, allowing the detection of 25 QTLs related to several browning parameters. These were distributed over six linkage groups with LOD values spanning from 3.08 to 4.99 and showed a rate of phenotypic variance from 26.1 to 38.6%. Anchoring of these intervals to the apple genome led to the identification of several genes involved in polyphenol synthesis and cell wall metabolism. Finally, the expression profile of two specific candidate genes, up and downstream of the polyphenolic pathway, namely phenylalanine ammonia lyase (PAL) and polyphenol oxidase (PPO), provided insight into flesh browning physiology. Md-PPO was further analyzed and two haplotypes were characterised and associated with fruit flesh browning in apple. PMID:24205065

GSEH: A Novel Approach to Select Prostate Cancer-Associated Genes Using Gene Expression Heterogeneity.

PubMed

Kim, Hyunjin; Choi, Sang-Min; Park, Sanghyun

2018-01-01

When a gene shows varying levels of expression among normal people but similar levels in disease patients or shows similar levels of expression among normal people but different levels in disease patients, we can assume that the gene is associated with the disease. By utilizing this gene expression heterogeneity, we can obtain additional information that abets discovery of disease-associated genes. In this study, we used collaborative filtering to calculate the degree of gene expression heterogeneity between classes and then scored the genes on the basis of the degree of gene expression heterogeneity to find "differentially predicted" genes. Through the proposed method, we discovered more prostate cancer-associated genes than 10 comparable methods. The genes prioritized by the proposed method are potentially significant to biological processes of a disease and can provide insight into them.

Experimental assessment of diazotroph responses to elevated seawater pCO2 in the North Pacific Subtropical Gyre

NASA Astrophysics Data System (ADS)

Böttjer, Daniela; Karl, David M.; Letelier, Ricardo M.; Viviani, Donn A.; Church, Matthew J.

2014-06-01

We examined short-term (24-72 h) responses of naturally occurring marine N2 fixing microorganisms (termed diazotrophs) to abrupt increases in the partial pressure of carbon dioxide (pCO2) in seawater during nine incubation experiments conducted between May 2010 and September 2012 at Station ALOHA (A Long-term Oligotrophic Habitat Assessment) (22°45'N, 158°W) in the North Pacific Subtropical Gyre (NPSG). Rates of N2 fixation, nitrogenase (nifH) gene abundances and transcripts of six major groups of cyanobacterial diazotrophs (including both unicellular and filamentous phylotypes), and rates of primary productivity (as measured by 14C-bicarbonate assimilation into plankton biomass) were determined under contemporary (~390 ppm) and elevated pCO2 conditions (~1100 ppm). Quantitative polymerase chain reaction (QPCR) amplification of planktonic nifH genes revealed that unicellular cyanobacteria phylotypes dominated gene abundances during these experiments. In the majority of experiments (seven out of nine), elevated pCO2 did not significantly influence rates of dinitrogen (N2) fixation or primary productivity (two-way analysis of variance (ANOVA), P > 0.05). During two experiments, rates of N2 fixation and primary productivity were significantly lower (by 79 to 82% and 52 to 72%, respectively) in the elevated pCO2 treatments relative to the ambient controls (two-way ANOVA, P < 0.05). QPCR amplification of nifH genes and gene transcripts revealed that diazotroph abundances and nifH gene expression were largely unchanged by the perturbation of the seawater pCO2. Our results suggest that naturally occurring N2 fixing plankton assemblages in the NPSG are relatively resilient to large, short-term increases in pCO2.

Analysis of phylogeny and codon usage bias and relationship of GC content, amino acid composition with expression of the structural nif genes.

PubMed

Mondal, Sunil Kanti; Kundu, Sudip; Das, Rabindranath; Roy, Sujit

2016-08-01

Bacteria and archaea have evolved with the ability to fix atmospheric dinitrogen in the form of ammonia, catalyzed by the nitrogenase enzyme complex which comprises three structural genes nifK, nifD and nifH. The nifK and nifD encodes for the beta and alpha subunits, respectively, of component 1, while nifH encodes for component 2 of nitrogenase. Phylogeny based on nifDHK have indicated that Cyanobacteria is closer to Proteobacteria alpha and gamma but not supported by the tree based on 16SrRNA. The evolutionary ancestor for the different trees was also different. The GC1 and GC2% analysis showed more consistency than GC3% which appeared to below for Firmicutes, Cyanobacteria and Euarchaeota while highest in Proteobacteria beta and clearly showed the proportional effect on the codon usage with a few exceptions. Few genes from Firmicutes, Euryarchaeota, Proteobacteria alpha and delta were found under mutational pressure. These nif genes with low and high GC3% from different classes of organisms showed similar expected number of codons. Distribution of the genes and codons, based on codon usage demonstrated opposite pattern for different orientation of mirror plane when compared with each other. Overall our results provide a comprehensive analysis on the evolutionary relationship of the three structural nif genes, nifK, nifD and nifH, respectively, in the context of codon usage bias, GC content relationship and amino acid composition of the encoded proteins and exploration of crucial statistical method for the analysis of positive data with non-constant variance to identify the shape factors of codon adaptation index.

Circular RNA and gene expression profiles in gastric cancer based on microarray chip technology.

PubMed

Sui, Weiguo; Shi, Zhoufang; Xue, Wen; Ou, Minglin; Zhu, Ying; Chen, Jiejing; Lin, Hua; Liu, Fuhua; Dai, Yong

2017-03-01

The aim of the present study was to screen gastric cancer (GC) tissue and adjacent tissue for differences in mRNA and circular (circRNA) expression, to analyze the differences in circRNA and mRNA expression, and to investigate the circRNA expression in gastric carcinoma and its mechanism. circRNA and mRNA differential expression profiles generated using Agilent microarray technology were analyzed in the GC tissues and adjacent tissues. qRT-PCR was used to verify the differential expression of circRNAs and mRNAs according to the interactions between circRNAs and miRNAs as well as the possible existence of miRNA and mRNA interactions. We found that: i) the circRNA expression profile revealed 1,285 significant differences in circRNA expression, with circRNA expression downregulated in 594 samples and upregulated in 691 samples via interactions with miRNAs. The qRT-PCR validation experiments showed that hsa_circRNA_400071, hsa_circRNA_000543 and hsa_circRNA_001959 expression was consistent with the microarray analysis results. ii) 29,112 genes were found in the GC tissues and adjacent tissues, including 5,460 differentially expressed genes. Among them, 2,390 differentially expressed genes were upregulated and 3,070 genes were downregulated. Gene Ontology (GO) analysis of the differentially expressed genes revealed these genes involved in biological process classification, cellular component classification and molecular function classification. Pathway analysis of the differentially expressed genes identified 83 significantly enriched genes, including 28 upregulated genes and 55 downregulated genes. iii) 69 differentially expressed circRNAs were found that might adsorb specific miRNAs to regulate the expression of their target gene mRNAs. The conclusions are: i) differentially expressed circRNAs had corresponding miRNA binding sites. These circRNAs regulated the expression of target genes through interactions with miRNAs and might become new molecular biomarkers for GC in the future. ii) Differentially expressed genes may be involved in the occurrence of GC via a variety of mechanisms. iii) CD44, CXXC5, MYH9, MALAT1 and other genes may have important implications for the occurrence and development of GC through the regulation, interaction, and mutual influence of circRNA-miRNA-mRNA via different mechanisms.

A P-Norm Robust Feature Extraction Method for Identifying Differentially Expressed Genes

PubMed Central

Liu, Jian; Liu, Jin-Xing; Gao, Ying-Lian; Kong, Xiang-Zhen; Wang, Xue-Song; Wang, Dong

2015-01-01

In current molecular biology, it becomes more and more important to identify differentially expressed genes closely correlated with a key biological process from gene expression data. In this paper, based on the Schatten p-norm and Lp-norm, a novel p-norm robust feature extraction method is proposed to identify the differentially expressed genes. In our method, the Schatten p-norm is used as the regularization function to obtain a low-rank matrix and the Lp-norm is taken as the error function to improve the robustness to outliers in the gene expression data. The results on simulation data show that our method can obtain higher identification accuracies than the competitive methods. Numerous experiments on real gene expression data sets demonstrate that our method can identify more differentially expressed genes than the others. Moreover, we confirmed that the identified genes are closely correlated with the corresponding gene expression data. PMID:26201006

A P-Norm Robust Feature Extraction Method for Identifying Differentially Expressed Genes.

PubMed

Liu, Jian; Liu, Jin-Xing; Gao, Ying-Lian; Kong, Xiang-Zhen; Wang, Xue-Song; Wang, Dong

2015-01-01

In current molecular biology, it becomes more and more important to identify differentially expressed genes closely correlated with a key biological process from gene expression data. In this paper, based on the Schatten p-norm and Lp-norm, a novel p-norm robust feature extraction method is proposed to identify the differentially expressed genes. In our method, the Schatten p-norm is used as the regularization function to obtain a low-rank matrix and the Lp-norm is taken as the error function to improve the robustness to outliers in the gene expression data. The results on simulation data show that our method can obtain higher identification accuracies than the competitive methods. Numerous experiments on real gene expression data sets demonstrate that our method can identify more differentially expressed genes than the others. Moreover, we confirmed that the identified genes are closely correlated with the corresponding gene expression data.

Genetic and epigenetic architecture of sex-biased expression in the jewel wasps Nasonia vitripennis and giraulti

PubMed Central

Wang, Xu; Werren, John H.; Clark, Andrew G.

2015-01-01

There is extraordinary diversity in sexual dimorphism (SD) among animals, but little is known about its epigenetic basis. To study the epigenetic architecture of SD in a haplodiploid system, we performed RNA-seq and whole-genome bisulfite sequencing of adult females and males from two closely related parasitoid wasps, Nasonia vitripennis and Nasonia giraulti. More than 75% of expressed genes displayed significantly sex-biased expression. As a consequence, expression profiles are more similar between species within each sex than between sexes within each species. Furthermore, extremely male- and female-biased genes are enriched for totally different functional categories: male-biased genes for key enzymes in sex-pheromone synthesis and female-biased genes for genes involved in epigenetic regulation of gene expression. Remarkably, just 70 highly expressed, extremely male-biased genes account for 10% of all transcripts in adult males. Unlike expression profiles, DNA methylomes are highly similar between sexes within species, with no consistent sex differences in methylation found. Therefore, methylation changes cannot explain the extensive level of sex-biased gene expression observed. Female-biased genes have smaller sequence divergence between species, higher conservation to other hymenopterans, and a broader expression range across development. Overall, female-biased genes have been recruited from genes with more conserved and broadly expressing “house-keeping” functions, whereas male-biased genes are more recently evolved and are predominately testis specific. In summary, Nasonia accomplish a striking degree of sex-biased expression without sex chromosomes or epigenetic differences in methylation. We propose that methylation provides a general signal for constitutive gene expression, whereas other sex-specific signals cause sex-biased gene expression. PMID:26100871

Lck is a relevant target in chronic lymphocytic leukaemia cells whose expression variance is unrelated to disease outcome.

PubMed

Till, Kathleen J; Allen, John C; Talab, Fatima; Lin, Ke; Allsup, David; Cawkwell, Lynn; Bentley, Alison; Ringshausen, Ingo; Duckworth, Andrew D; Pettitt, Andrew R; Kalakonda, Nagesh; Slupsky, Joseph R

2017-12-01

Pathogenesis of chronic lymphocytic leukaemia (CLL) is contingent upon antigen receptor (BCR) expressed by malignant cells of this disease. Studies on somatic hypermutation of the antigen binding region, receptor expression levels and signal capacity have all linked BCR on CLL cells to disease prognosis. Our previous work showed that the src-family kinase Lck is a targetable mediator of BCR signalling in CLL cells, and that variance in Lck expression associated with ability of BCR to induce signal upon engagement. This latter finding makes Lck similar to ZAP70, another T-cell kinase whose aberrant expression in CLL cells also associates with BCR signalling capacity, but also different because ZAP70 is not easily pharmacologically targetable. Here we describe a robust method of measuring Lck expression in CLL cells using flow cytometry. However, unlike ZAP70 whose expression in CLL cells predicts prognosis, we find Lck expression and disease outcome in CLL are unrelated despite observations that its inhibition produces effects that biologically resemble the egress phenotype taken on by CLL cells treated with idelalisib. Taken together, our findings provide insight into the pathobiology of CLL to suggest a more complex relationship between expression of molecules within the BCR signalling pathway and disease outcome.

Extent and character of circadian gene expression in Drosophila melanogaster: identification of twenty oscillating mRNAs in the fly head.

PubMed

Van Gelder, R N; Bae, H; Palazzolo, M J; Krasnow, M A

1995-12-01

Although mRNAs expressed with a circadian rhythm have been isolated from many species, the extent and character of circadianly regulated gene expression is unknown for any animal. In Drosophila melanogaster, only the period (per) gene, an essential component of the circadian pacemaker, is known to show rhythmic mRNA expression. Recent work suggests that the encoded Per protein controls its own transcription by an autoregulatory feedback loop. Per might also control the rhythmic expression of other genes to generate circadian behavior and physiology. The goals of this work were to evaluate the extent and character of circadian control of gene expression in Drosophila, and to identify genes dependent on per for circadian expression. A large collection of anonymous, independent cDNA clones was used to screen for transcripts that are rhythmically expressed in the fly head. 20 of the 261 clones tested detected mRNAs with a greater than two-fold daily change in abundance. Three mRNAs were maximally expressed in the morning, whereas 17 mRNAs were most abundant in the evening--when per mRNA is also maximally expressed (but when the flies are inactive). Further analysis of the three 'morning' cDNAs showed that each has a unique dependence on the presence of a light-dark cycle, on timed feeding, and on the function of the per gene for its oscillation. These dependencies were different from those determined for per and for a novel 'evening' gene. Sequence analysis indicated that all but one of the 20 cDNAs identified previously uncloned genes. Diurnal control of gene expression is a significant but limited phenomenon in the fly head, which involves many uncharacterized genes. Diurnal control is mediated by multiple endogenous and exogenous mechanisms, even at the level of individual genes. A subset of circadianly expressed genes are predominantly or exclusively dependent on per for their rhythmic expression. The per gene can therefore influence the expression of genes other than itself, but for many rhythmically expressed genes, per functions in conjunction with external inputs to control their daily expression patterns.

A first linkage map and downy mildew resistance QTL discovery for sweet basil (Ocimum basilicum) facilitated by double digestion restriction site associated DNA sequencing (ddRADseq).

PubMed

Pyne, Robert; Honig, Josh; Vaiciunas, Jennifer; Koroch, Adolfina; Wyenandt, Christian; Bonos, Stacy; Simon, James

2017-01-01

Limited understanding of sweet basil (Ocimum basilicum L.) genetics and genome structure has reduced efficiency of breeding strategies. This is evidenced by the rapid, worldwide dissemination of basil downy mildew (Peronospora belbahrii) in the absence of resistant cultivars. In an effort to improve available genetic resources, expressed sequence tag simple sequence repeat (EST-SSR) and single nucleotide polymorphism (SNP) markers were developed and used to genotype the MRI x SB22 F2 mapping population, which segregates for response to downy mildew. SNP markers were generated from genomic sequences derived from double digestion restriction site associated DNA sequencing (ddRADseq). Disomic segregation was observed in both SNP and EST-SSR markers providing evidence of an O. basilicum allotetraploid genome structure and allowing for subsequent analysis of the mapping population as a diploid intercross. A dense linkage map was constructed using 42 EST-SSR and 1,847 SNP markers spanning 3,030.9 cM. Multiple quantitative trait loci (QTL) model (MQM) analysis identified three QTL that explained 37-55% of phenotypic variance associated with downy mildew response across three environments. A single major QTL, dm11.1 explained 21-28% of phenotypic variance and demonstrated dominant gene action. Two minor QTL dm9.1 and dm14.1 explained 5-16% and 4-18% of phenotypic variance, respectively. Evidence is provided for an additive effect between the two minor QTL and the major QTL dm11.1 increasing downy mildew susceptibility. Results indicate that ddRADseq-facilitated SNP and SSR marker genotyping is an effective approach for mapping the sweet basil genome.

A first linkage map and downy mildew resistance QTL discovery for sweet basil (Ocimum basilicum) facilitated by double digestion restriction site associated DNA sequencing (ddRADseq)

PubMed Central

Honig, Josh; Vaiciunas, Jennifer; Koroch, Adolfina; Wyenandt, Christian; Bonos, Stacy; Simon, James

2017-01-01

Limited understanding of sweet basil (Ocimum basilicum L.) genetics and genome structure has reduced efficiency of breeding strategies. This is evidenced by the rapid, worldwide dissemination of basil downy mildew (Peronospora belbahrii) in the absence of resistant cultivars. In an effort to improve available genetic resources, expressed sequence tag simple sequence repeat (EST-SSR) and single nucleotide polymorphism (SNP) markers were developed and used to genotype the MRI x SB22 F2 mapping population, which segregates for response to downy mildew. SNP markers were generated from genomic sequences derived from double digestion restriction site associated DNA sequencing (ddRADseq). Disomic segregation was observed in both SNP and EST-SSR markers providing evidence of an O. basilicum allotetraploid genome structure and allowing for subsequent analysis of the mapping population as a diploid intercross. A dense linkage map was constructed using 42 EST-SSR and 1,847 SNP markers spanning 3,030.9 cM. Multiple quantitative trait loci (QTL) model (MQM) analysis identified three QTL that explained 37–55% of phenotypic variance associated with downy mildew response across three environments. A single major QTL, dm11.1 explained 21–28% of phenotypic variance and demonstrated dominant gene action. Two minor QTL dm9.1 and dm14.1 explained 5–16% and 4–18% of phenotypic variance, respectively. Evidence is provided for an additive effect between the two minor QTL and the major QTL dm11.1 increasing downy mildew susceptibility. Results indicate that ddRADseq-facilitated SNP and SSR marker genotyping is an effective approach for mapping the sweet basil genome. PMID:28922359

Polycistronic gene expression in Aspergillus niger.

PubMed

Schuetze, Tabea; Meyer, Vera

2017-09-25

Genome mining approaches predict dozens of biosynthetic gene clusters in each of the filamentous fungal genomes sequenced so far. However, the majority of these gene clusters still remain cryptic because they are not expressed in their natural host. Simultaneous expression of all genes belonging to a biosynthetic pathway in a heterologous host is one approach to activate biosynthetic gene clusters and to screen the metabolites produced for bioactivities. Polycistronic expression of all pathway genes under control of a single and tunable promoter would be the method of choice, as this does not only simplify cloning procedures, but also offers control on timing and strength of expression. However, polycistronic gene expression is a feature not commonly found in eukaryotic host systems, such as Aspergillus niger. In this study, we tested the suitability of the viral P2A peptide for co-expression of three genes in A. niger. Two genes descend from Fusarium oxysporum and are essential to produce the secondary metabolite enniatin (esyn1, ekivR). The third gene (luc) encodes the reporter luciferase which was included to study position effects. Expression of the polycistronic gene cassette was put under control of the Tet-On system to ensure tunable gene expression in A. niger. In total, three polycistronic expression cassettes which differed in the position of luc were constructed and targeted to the pyrG locus in A. niger. This allowed direct comparison of the luciferase activity based on the position of the luciferase gene. Doxycycline-mediated induction of the Tet-On expression cassettes resulted in the production of one long polycistronic mRNA as proven by Northern analyses, and ensured comparable production of enniatin in all three strains. Notably, gene position within the polycistronic expression cassette matters, as, luciferase activity was lowest at position one and had a comparable activity at positions two and three. The P2A peptide can be used to express at least three genes polycistronically in A. niger. This approach can now be applied to heterologously express entire secondary metabolite gene clusters polycistronically or to co-express any genes of interest in equimolar amounts.

Intracellular high cholesterol content disorders the clock genes, apoptosis-related genes and fibrinolytic-related genes rhythmic expressions in human plaque-derived vascular smooth muscle cells.

PubMed

Lin, Changpo; Tang, Xiao; Xu, Lirong; Qian, Ruizhe; Shi, Zhenyu; Wang, Lixin; Cai, Tingting; Yan, Dong; Fu, Weiguo; Guo, Daqiao

2017-07-10

The clock genes are involved in regulating cardiovascular functions, and their expression disorders would lead to circadian rhythm disruptions of clock-controlled genes (CCGs), resulting in atherosclerotic plaque formation and rupture. Our previous study revealed the rhythmic expression of clock genes were attenuated in human plaque-derived vascular smooth muscle cells (PVSMCs), but failed to detect the downstream CCGs expressions and the underlying molecular mechanism. In this study, we examined the difference of CCGs rhythmic expression between human normal carotid VSMCs (NVSMCs) and PVSMCs. Furthermore, we compared the cholesterol and triglycerides levels between two groups and the link to clock genes and CCGs expressions. Seven health donors' normal carotids and 19 carotid plaques yielded viable cultured NVSMCs and PVSMCs. The expression levels of target genes were measured by quantitative real-time PCR and Western-blot. The intracellular cholesterol and triglycerides levels were measured by kits. The circadian expressions of apoptosis-related genes and fibrinolytic-related genes were disordered. Besides, the cholesterol levels were significant higher in PVSMCs. After treated with cholesterol or oxidized low density lipoprotein (ox-LDL), the expressions of clock genes were inhibited; and the rhythmic expressions of clock genes, apoptosis-related genes and fibrinolytic-related genes were disturbed in NVSMCs, which were similar to PVSMCs. The results suggested that intracellular high cholesterol content of PVSMCs would lead to the disorders of clock genes and CCGs rhythmic expressions. And further studies should be conducted to demonstrate the specific molecular mechanisms involved.

Double-filter identification of vascular-expressed genes using Arabidopsis plants with vascular hypertrophy and hypotrophy.

PubMed

Ckurshumova, Wenzislava; Scarpella, Enrico; Goldstein, Rochelle S; Berleth, Thomas

2011-08-01

Genes expressed in vascular tissues have been identified by several strategies, usually with a focus on mature vascular cells. In this study, we explored the possibility of using two opposite types of altered tissue compositions in combination with a double-filter selection to identify genes with a high probability of vascular expression in early organ primordia. Specifically, we generated full-transcriptome microarray profiles of plants with (a) genetically strongly reduced and (b) pharmacologically vastly increased vascular tissues and identified a reproducible cohort of 158 transcripts that fulfilled the dual requirement of being underrepresented in (a) and overrepresented in (b). In order to assess the predictive value of our identification scheme for vascular gene expression, we determined the expression patterns of genes in two unbiased subsamples. First, we assessed the expression patterns of all twenty annotated transcription factor genes from the cohort of 158 genes and found that seventeen of the twenty genes were preferentially expressed in leaf vascular cells. Remarkably, fifteen of these seventeen vascular genes were clearly expressed already very early in leaf vein development. Twelve genes with published leaf expression patterns served as a second subsample to monitor the representation of vascular genes in our cohort. Of those twelve genes, eleven were preferentially expressed in leaf vascular tissues. Based on these results we propose that our compendium of 158 genes represents a sample that is highly enriched for genes expressed in vascular tissues and that our approach is particularly suited to detect genes expressed in vascular cell lineages at early stages of their inception. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Increased gene expression noise in human cancers is correlated with low p53 and immune activities as well as late stage cancer.

PubMed

Han, Rongfei; Huang, Guanqun; Wang, Yejun; Xu, Yafei; Hu, Yueming; Jiang, Wenqi; Wang, Tianfu; Xiao, Tian; Zheng, Duo

2016-11-01

Gene expression in metazoans is delicately organized. As genetic information transmits from DNA to RNA and protein, expression noise is inevitably generated. Recent studies begin to unveil the mechanisms of gene expression noise control, but the changes of gene expression precision in pathologic conditions like cancers are unknown. Here we analyzed the transcriptomic data of human breast, liver, lung and colon cancers, and found that the expression noise of more than 74.9% genes was increased in cancer tissues as compared to adjacent normal tissues. This suggested that gene expression precision controlling collapsed during cancer development. A set of 269 genes with noise increased more than 2-fold were identified across different cancer types. These genes were involved in cell adhesion, catalytic and metabolic functions, implying the vulnerability of deregulation of these processes in cancers. We also observed a tendency of increased expression noise in patients with low p53 and immune activity in breast, liver and lung caners but not in colon cancers, which indicated the contributions of p53 signaling and host immune surveillance to gene expression noise in cancers. Moreover, more than 53.7% genes had increased noise in patients with late stage than early stage cancers, suggesting that gene expression precision was associated with cancer outcome. Together, these results provided genomic scale explorations of gene expression noise control in human cancers.

Insulin-like growth factor-I gene delivery to astrocytes reduces their inflammatory response to lipopolysaccharide

PubMed Central

2011-01-01

Background Insulin-like growth factor-I (IGF-I) exerts neuroprotective actions in the central nervous system that are mediated at least in part by control of activation of astrocytes. In this study we have assessed the efficacy of exogenous IGF-I and IGF-I gene therapy in reducing the inflammatory response of astrocytes from cerebral cortex. Methods An adenoviral vector harboring the rat IGF-I gene and a control adenoviral vector harboring a hybrid gene encoding the herpes simplex virus type 1 thymidine kinase fused to Aequorea victoria enhanced green fluorescent protein were used in this study. Primary astrocytes from mice cerebral cortex were incubated for 24 h or 72 h with vehicle, IGF-I, the IGF-I adenoviral vector, or control vector; and exposed to bacterial lipopolysaccharide to induce an inflammatory response. IGF-I levels were measured by radioimmunoassay. Levels of interleukin 6, tumor necrosis factor-α, interleukin-1β and toll-like receptor 4 mRNA were assessed by quantitative real-time polymerase chain reaction. Levels of IGF-I receptor and IGF binding proteins 2 and 3 were assessed by western blotting. The subcellular distribution of nuclear factor κB (p65) was assessed by immunocytochemistry. Statistical significance was assessed by one way analysis of variance followed by the Bonferroni pot hoc test. Results IGF-I gene therapy increased IGF-I levels without affecting IGF-I receptors or IGF binding proteins. Exogenous IGF-I, and IGF-I gene therapy, decreased expression of toll-like receptor 4 and counteracted the lipopolysaccharide-induced inflammatory response of astrocytes. In addition, IGF-I gene therapy decreased lipopolysaccharide-induced translocation of nuclear factor κB (p65) to the cell nucleus. Conclusion These findings demonstrate efficacy of exogenous IGF-I and of IGF-I gene therapy in reducing the inflammatory response of astrocytes. IGF-I gene therapy may represent a new approach to reduce inflammatory reactions in glial cells. PMID:21371294

Identification of stress responsive genes by studying specific relationships between mRNA and protein abundance.

PubMed

Morimoto, Shimpei; Yahara, Koji

2018-03-01

Protein expression is regulated by the production and degradation of mRNAs and proteins but the specifics of their relationship are controversial. Although technological advances have enabled genome-wide and time-series surveys of mRNA and protein abundance, recent studies have shown paradoxical results, with most statistical analyses being limited to linear correlation, or analysis of variance applied separately to mRNA and protein datasets. Here, using recently analyzed genome-wide time-series data, we have developed a statistical analysis framework for identifying which types of genes or biological gene groups have significant correlation between mRNA and protein abundance after accounting for potential time delays. Our framework stratifies all genes in terms of the extent of time delay, conducts gene clustering in each stratum, and performs a non-parametric statistical test of the correlation between mRNA and protein abundance in a gene cluster. Consequently, we revealed stronger correlations than previously reported between mRNA and protein abundance in two metabolic pathways. Moreover, we identified a pair of stress responsive genes ( ADC17 and KIN1 ) that showed a highly similar time series of mRNA and protein abundance. Furthermore, we confirmed robustness of the analysis framework by applying it to another genome-wide time-series data and identifying a cytoskeleton-related gene cluster (keratin 18, keratin 17, and mitotic spindle positioning) that shows similar correlation. The significant correlation and highly similar changes of mRNA and protein abundance suggests a concerted role of these genes in cellular stress response, which we consider provides an answer to the question of the specific relationships between mRNA and protein in a cell. In addition, our framework for studying the relationship between mRNAs and proteins in a cell will provide a basis for studying specific relationships between mRNA and protein abundance after accounting for potential time delays.

[Differential expression genes of bone tissues surrounding implants in diabetic rats by gene chip].

PubMed

Wang, Xin-xin; Ma, Yue; Li, Qing; Jiang, Bao-qi; Lan, Jing

2012-10-01

To compare mRNA expression profiles of bone tissues surrounding implants between normal rats and rats with diabetes using microarray technology. Six Wistar rats were randomly selected and divided into normal model group and diabetic group. Diabetic model condition was established by injecting Streptozotocin into peritoneal space. Titanium implants were implanted into the epiphyseal end of the rats' tibia. Bone tissues surrounding implant were harvested and sampled after 3 months to perform comprehensive RNA gene expression profiling, including 17983 for genome-wide association study.GO analysis was used to compare different gene expression and real-time PCR was used to confirm the results on core samples. The results indicated that there were 1084 differential gene expression. In the diabetic model, there were 352 enhanced expression genes, 732 suppressed expression genes. GO analysis involved 1154 different functional type. Osteoblast related gene expressions in bone tissue samples of diabetic rats were decreased, and lipid metabolism pathway related gene expression was increased.

Gene Architectures that Minimize Cost of Gene Expression.

PubMed

Frumkin, Idan; Schirman, Dvir; Rotman, Aviv; Li, Fangfei; Zahavi, Liron; Mordret, Ernest; Asraf, Omer; Wu, Song; Levy, Sasha F; Pilpel, Yitzhak

2017-01-05

Gene expression burdens cells by consuming resources and energy. While numerous studies have investigated regulation of expression level, little is known about gene design elements that govern expression costs. Here, we ask how cells minimize production costs while maintaining a given protein expression level and whether there are gene architectures that optimize this process. We measured fitness of ∼14,000 E. coli strains, each expressing a reporter gene with a unique 5' architecture. By comparing cost-effective and ineffective architectures, we found that cost per protein molecule could be minimized by lowering transcription levels, regulating translation speeds, and utilizing amino acids that are cheap to synthesize and that are less hydrophobic. We then examined natural E. coli genes and found that highly expressed genes have evolved more forcefully to minimize costs associated with their expression. Our study thus elucidates gene design elements that improve the economy of protein expression in natural and heterologous systems. Copyright © 2017 Elsevier Inc. All rights reserved.

Segregation analysis of apolipoproteins A-1 and B-100 measured before and after an exercise training program: the HERITAGE Family Study.

PubMed

An, P; Rice, T; Gagnon, J; Borecki, I B; Bergeron, J; Després, J P; Leon, A S; Skinner, J S; Wilmore, J H; Bouchard, C; Rao, D C

2000-03-01

Complex segregation analyses of apolipoproteins (apo) A-1 and B-100 were performed in a sample of 520 individuals from 99 white families who participated in the HERITAGE Family Study. In these sedentary families, plasma apo A-1 and B-100 concentrations were measured before and after a 20-week endurance exercise training program. Baseline apo A-1 and B-100 were adjusted for the effects of age (age-adjusted baseline apo A-1 and B-100) and for the effects of age and BMI (age-BMI-adjusted baseline apo A-1 and B-100). The change in response to training was computed as a simple Delta (posttraining minus baseline) and was adjusted for age and the baseline (age-baseline-adjusted apo A-1 and B-100 responses to training). In the present study, a major gene could not be inferred for baseline apo A-1. Rather, we found a major effect along with a multifactorial effect accounting for 8% to 9% and 51% to 56% of the variance, respectively. In addition, no clear evidence supported a major-gene effect for its response to training, whereas the transmission of a major effect from parents to offspring was ambiguous, ie, genetic in nature or familial environmental in origin. The major effect accounted for 15% of the variance, with an additional 21% and 58% of the variance being accounted for by a multifactorial effect in parents and offspring, respectively. It is interesting to have obtained evidence of a putative recessive major locus for baseline apo B-100, which accounted for 50% to 56% of the variance, with an additional 25% to 29% of the variance due to a multifactorial effect. In contrast, no major effect for its response to training was identified, although a multifactorial effect was found that accounted for 27% of the variance. The novel findings arising from the present study are summarized as follows. Baseline apo A-1 and its response to training were influenced by a major effect and a multifactorial effect. Baseline apo B-100 was influenced by a putative major recessive gene with a multifactorial component, but its response to training was influenced solely by a multifactorial component in these sedentary families.

Transcriptome sequencing of Eucalyptus camaldulensis seedlings subjected to water stress reveals functional single nucleotide polymorphisms and genes under selection

PubMed Central

2012-01-01

Background Water stress limits plant survival and production in many parts of the world. Identification of genes and alleles responding to water stress conditions is important in breeding plants better adapted to drought. Currently there are no studies examining the transcriptome wide gene and allelic expression patterns under water stress conditions. We used RNA sequencing (RNA-seq) to identify the candidate genes and alleles and to explore the evolutionary signatures of selection. Results We studied the effect of water stress on gene expression in Eucalyptus camaldulensis seedlings derived from three natural populations. We used reference-guided transcriptome mapping to study gene expression. Several genes showed differential expression between control and stress conditions. Gene ontology (GO) enrichment tests revealed up-regulation of 140 stress-related gene categories and down-regulation of 35 metabolic and cell wall organisation gene categories. More than 190,000 single nucleotide polymorphisms (SNPs) were detected and 2737 of these showed differential allelic expression. Allelic expression of 52% of these variants was correlated with differential gene expression. Signatures of selection patterns were studied by estimating the proportion of nonsynonymous to synonymous substitution rates (Ka/Ks). The average Ka/Ks ratio among the 13,719 genes was 0.39 indicating that most of the genes are under purifying selection. Among the positively selected genes (Ka/Ks > 1.5) apoptosis and cell death categories were enriched. Of the 287 positively selected genes, ninety genes showed differential expression and 27 SNPs from 17 positively selected genes showed differential allelic expression between treatments. Conclusions Correlation of allelic expression of several SNPs with total gene expression indicates that these variants may be the cis-acting variants or in linkage disequilibrium with such variants. Enrichment of apoptosis and cell death gene categories among the positively selected genes reveals the past selection pressures experienced by the populations used in this study. PMID:22853646

Functional clustering of time series gene expression data by Granger causality

PubMed Central

2012-01-01

Background A common approach for time series gene expression data analysis includes the clustering of genes with similar expression patterns throughout time. Clustered gene expression profiles point to the joint contribution of groups of genes to a particular cellular process. However, since genes belong to intricate networks, other features, besides comparable expression patterns, should provide additional information for the identification of functionally similar genes. Results In this study we perform gene clustering through the identification of Granger causality between and within sets of time series gene expression data. Granger causality is based on the idea that the cause of an event cannot come after its consequence. Conclusions This kind of analysis can be used as a complementary approach for functional clustering, wherein genes would be clustered not solely based on their expression similarity but on their topological proximity built according to the intensity of Granger causality among them. PMID:23107425

Intergenerational impact of paternal lifetime exposures to both folic acid deficiency and supplementation on reproductive outcomes and imprinted gene methylation.

PubMed

Ly, Lundi; Chan, Donovan; Aarabi, Mahmoud; Landry, Mylène; Behan, Nathalie A; MacFarlane, Amanda J; Trasler, Jacquetta

2017-07-01

Do paternal exposures to folic acid deficient (FD), and/or folic acid supplemented (FS) diets, throughout germ cell development adversely affect male germ cells and consequently offspring health outcomes? Male mice exposed over their lifetimes to both FD and FS diets showed decreased sperm counts and altered imprinted gene methylation with evidence of transmission of adverse effects to the offspring, including increased postnatal-preweaning mortality and variability in imprinted gene methylation. There is increasing evidence that disruptions in male germ cell epigenetic reprogramming are associated with offspring abnormalities and intergenerational disease. The fetal period is the critical time of DNA methylation pattern acquisition for developing male germ cells and an adequate supply of methyl donors is required. In addition, DNA methylation patterns continue to be remodeled during postnatal spermatogenesis. Previous studies have shown that lifetime (prenatal and postnatal) folic acid deficiency can alter the sperm epigenome and increase the incidence of fetal morphological abnormalities. Female BALB/c mice (F0) were placed on one of four amino-acid defined diets for 4 weeks before pregnancy and throughout pregnancy and lactation: folic acid control (Ctrl; 2 mg/kg), 7-fold folic acid deficient (7FD; 0.3 mg/kg), 10-fold high FS (10FS, 20 mg/kg) or 20-fold high FS (20FS, 40 mg/kg) diets. F1 males were weaned to their respective prenatal diets to allow for diet exposure during all windows of germline epigenetic reprogramming: the erasure, re-establishment and maintenance phases. F0 females were mated with chow-fed males to produce F1 litters whose germ cells were exposed to the diets throughout embryonic development. F1 males were subsequently mated with chow-fed female mice. Two F2 litters, unexposed to the experimental diets, were generated from each F1 male; one litter was collected at embryonic day (E)18.5 and one delivered and followed postnatally. DNA methylation at a global level and at the differentially methylated regions of imprinted genes (H19, Imprinted Maternally Expressed Transcript (Non-Protein Coding)-H19, Small Nuclear Ribonucleoprotein Polypeptide N-Snrpn, KCNQ1 Opposite Strand/Antisense Transcript 1 (Non-Protein Coding)-Kcnq1ot1, Paternally Expressed Gene 1-Peg1 and Paternally Expressed Gene 3-Peg3) was assessed by luminometric methylation analysis and bisulfite pyrosequencing, respectively, in F1 sperm, F2 E18.5 placenta and F2 E18.5 brain cortex. F1 males exhibited lower sperm counts following lifetime exposure to both folic acid deficiency and the highest dose of folic acid supplementation (20FS), (both P < 0.05). Post-implantation losses were increased amongst F2 E18.5 day litters from 20FS exposed F1 males (P < 0.05). F2 litters derived from both 7FD and 20FS exposed F1 males had significantly higher postnatal-preweaning pup death (both P < 0.05). Sperm from 10FS exposed males had increased variance in methylation across imprinted gene H19, P < 0.05; increased variance at a few sites within H19 was also found for the 7FD and 20FS groups (P < 0.05). While the 20FS diet resulted in inter-individual alterations in methylation across the imprinted genes Snrpn and Peg3 in F2 E18.5 placenta, ≥50% of individual sites tested in Peg1 and/or Peg3 were affected in the 7FD and 10FS groups. Inter-individual alterations in Peg1 methylation were found in F2 E18.5 day 10FS group brain cortex (P < 0.05). Not applicable. The cause of the increase in postnatal-preweaning mortality was not investigated post-mortem. Further studies are required to understand the mechanisms underlying the adverse effects of folic acid deficiency and supplementation on developing male germ cells. Genome-wide DNA and histone methylome studies as well as gene expression studies are required to better understand the links between folic acid exposures, an altered germ cell epigenome and offspring outcomes. The findings of this study provide further support for paternally transmitted environmental effects. The results indicate that both folic acid deficiency and high dose supplementation can be detrimental to germ cell development and reproductive fitness, in part by altering DNA methylation in sperm. This study was supported by a grant to J.M.T. from the Canadian Institutes of Health Research (CIHR #89944). The authors declare they have no conflicts of interest. © The Author 2017. Published by Oxford University Press on behalf of the European Society of Human Reproduction and Embryology. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Global gene expression analyses of hematopoietic stem cell-like cell lines with inducible Lhx2 expression

PubMed Central

Richter, Karin; Wirta, Valtteri; Dahl, Lina; Bruce, Sara; Lundeberg, Joakim; Carlsson, Leif; Williams, Cecilia

2006-01-01

Background Expression of the LIM-homeobox gene Lhx2 in murine hematopoietic cells allows for the generation of hematopoietic stem cell (HSC)-like cell lines. To address the molecular basis of Lhx2 function, we generated HSC-like cell lines where Lhx2 expression is regulated by a tet-on system and hence dependent on the presence of doxycyclin (dox). These cell lines efficiently down-regulate Lhx2 expression upon dox withdrawal leading to a rapid differentiation into various myeloid cell types. Results Global gene expression of these cell lines cultured in dox was compared to different time points after dox withdrawal using microarray technology. We identified 267 differentially expressed genes. The majority of the genes overlapping with HSC-specific databases were those down-regulated after turning off Lhx2 expression and a majority of the genes overlapping with those defined as late progenitor-specific genes were the up-regulated genes, suggesting that these cell lines represent a relevant model system for normal HSCs also at the level of global gene expression. Moreover, in situ hybridisations of several genes down-regulated after dox withdrawal showed overlapping expression patterns with Lhx2 in various tissues during embryonic development. Conclusion Global gene expression analysis of HSC-like cell lines with inducible Lhx2 expression has identified genes putatively linked to self-renewal / differentiation of HSCs, and function of Lhx2 in organ development and stem / progenitor cells of non-hematopoietic origin. PMID:16600034

Influence of simulated microgravity on clock genes expression rhythmicity and underlying blood circulating miRNAs-mRNA co-expression regulatory mechanism in C57BL/6J mice

NASA Astrophysics Data System (ADS)

Lv, Ke; Qu, Lina

Purpose: It is vital for astronauts to maintain the optimal alertness and neurobehavioral function. Among various factors that exist in the space flight and long-duration mission environment, gravity changes may probably an essential environmental factor to interfere with internal circadian rhythms homeostasis and sleep quality, but the underlying mechanism is unclear. Mammals' biological clock is controlled by the suprachiasmatic nucleus (SCN), and peripheral organs adjust their own rhythmicity with the central signals. Nevertheless the mechanism underlying this synchronizition process is still unknown. microRNAs (miRNAs) are about 19˜22nt long regulatory RNAs that serve as critical modulators of post-transcriptional gene regulation. Recently, circulating miRNAs were found to have the regulatory role between cells and peripheral tissues, besides its function inside the cells. This study aims to investigate the regulatory signal transduction role of miRNAs between SCN and peripheral biological clock effecter tissues and to further decipher the mechanism of circadian disturbance under microgravity. Method: Firstly, based on the assumption that severe alterations in the expression of genes known to be involved in circadian rhythms may affect the expression of other genes, the labeled cDNA from liver and suprachiasmatic nucleus (SCN) of clock-knockout mice and control mice in different time points were cohybridized to microarrays. The fold change exceeding 2 (FC>2) was used to identify genes with altered expression levels in the knockout mice compared with control mice. Secondly, male C57BL/6J mice at 8 weeks of age were individually caged and acclimatized to the laboratory conditions (12h light/dark cycle) before being used for continuous core body temperature and activity monitoring. The mice were individually caged and tail suspended using a strip of adhesive surgical tape attached to a chain hanging from a pulley. Peripheral blood and liver tissues collection were consecutively performed. Blood samples and liver tissues were collected from tail-suspended and control mice under LD 12:12h and DD conditions during the 12th, 13th and 14th testing days at 4h intervals. Melatonin and corticosterone in mice plasma at different time points were assayed. NIH-3T3 cells were plated in culture dish for 22h before the experiment. For ground-based simulation of weightlessness, the medium was exchanged with DMEM containing 50% horse serum to synchronization, after 2 h, this medium was replaced with DMEM and 10% FBS. Then, at various time point (0, 6, 12, 18, 24, 30, 36, 42, 48h), cells were cultured on the roating clinostat at 30r/min. Total RNA was extracted from liver and NIH-3T3 cells and subsequently reverse-transcribed. The SYBR green I real-time quantitative PCR system was conducted to examine the mRNA expression level of clock, bmal1, per1, per2, cry1 and cry2 in mice and NIH-3T3 cells, respectively. Paired comparisons of the circadian genes expression between period, peak values, amplitude and mesor (midline estimating statistic of rhythm) were examined for evidence of circadian variation using Chronos-Fit software in mice and Cosine analyses in NIH-3T3 cells. Statistical analysis: All numerical data were expressed as the mean ± standard deviation (SD). Statistical differences among groups were analyzed by one-way analysis of variance (ANOVA) to determine time points differences in the study parameters. Statistical differences between two groups were determined by the Student's t test. Results: (1) Circadian rhythm of clock and bmal1 mRNA expression was found in each testing day with similar peak phase in both tail suspension group and control group. Compared with control group, tail suspension group showed that the peak phase of clock gene mRNA level advanced approximately 4 hours and the amplitude of bmal1 gene mRNA level significantly reduced at ZT2 and ZT6. (2) The expression of circadian genes in NIH-3T3 cells demonstrated that the maximum and minimum value of mRNA relative expression levels of clock and bmal1 during clinorotation were both found approximately at the time points 6h and 18h, respectively. The period length of experimental group was about 16h longer than control group. The peak phase and peak time of clock and bmal1 with simulated weightlessness group were ahead of control group. (3) At the Zeitgeber time 2 (ZT2), we found that 23 miRNAs in the SCN and 60 miRNAs in liver were significantly altered on the basis of an adjusted FC>2 among 611 miRNAs. At the ZT14, 23 miRNAs in the SCN and 57 miRNAs in liver were altered compared with the control group (FC>2). (a) Effects of clock knock out altered expression of miRNA. We analyzed the miRNA profile in SCN and liver of clock knonck out and WT mouse at two different time points using miRNA microarray. Of these, miR-122,miR-144, miR-210 and miR-669b at ZT2, miR-200a, miR-200b, miR-429, miR-455, miR-669d and miR-96 at ZT14 were both changed in SCN and liver, respectively. Interestingly, the miR-122, a tissue specific miRNA of liver was also changed in SCN at ZT2. (b) Effects of light altered expression of miRNA: Light is an important environmental factors to regulate circadian genes expression. In clock mutant mice, all altered miRNAs except miR-144 were down-regulated in SCN while up-regulated in liver at ZT14 compared to ZT2. Interestingly, the miRNAs expression profiling in SCN and liver were opposite of WT mice at ZT14 compared to ZT2. (c) Effects of clock mutant on mRNA expression: To test whether the alteration in expression of miRNAs correlates with the gene expression pattern, cDNA microarray of SCN were assayed. The results revealed that the expression of nearly 1285 genes was altered substantially with at least 1 fold change absolute in the absence of clock. Among these altered genes, we chose the mRNAs with at least 4 fold changes to further study. Only 23 genes were altered in clock knockout compared with WT at ZT2, but 67 genes at ZT14. (d) Effects of light on mRNA expression. To evaluate the light effecting on genes expression in SCN, the cDNA microarrays in SCN at ZT2 and ZT14 were tested. 21 genes were over expression and 12 genes were down regulation ZT14 compared with ZT2 in WT. The number of altered genes in clock-/- mice was 67. (e) Direct interaction between altered miRNAs and mRNAs. To identify the interaction between regulatory miRNAs and altered mRNAs in the absence of clock, we predicted the target genes of miRNAs by TargetScan. The genes both the target genes of miRNAs and altered in cDNA microarray were unravelled. The exploration of functional interaction between miRNAs and clock genes mRNA is ongoing. Conclusion: Taken together, these results indicate that ground-based simulated weightlessness could alter the molecular biological rhythm patterns, which may preliminarily present the biological regulatory mechanism of circadian rhythm systems under spaceflight-related gravity. The potential underlying functional miRNAs could serve as targets to interfere with for interaction between central and peripheral circadian organs under simulated microgravity. This preliminary study may facilitate the exploration of circadian rhythm characteristics in space and the detailed process of signal transduction and circadian gene regulation. Key words: circadian rhythms, tail-suspension, simulated microgravity, clock genes, miRNAs Acknowledgments: This study was supported by the National Basic Research Program of China (Grant NO. 2011CB707704) and the Foundation of State Key Laboratory of Space Medicine Fundamentals and Application, China Astronaut Research and Training Center (Grant NO. SMFA13B02, SMFA09A06 and SMFA12B05).

Integrated analysis of gene expression and methylation profiles of 48 candidate genes in breast cancer patients.

PubMed

Li, Zibo; Heng, Jianfu; Yan, Jinhua; Guo, Xinwu; Tang, Lili; Chen, Ming; Peng, Limin; Wu, Yepeng; Wang, Shouman; Xiao, Zhi; Deng, Zhongping; Dai, Lizhong; Wang, Jun

2016-11-01

Gene-specific methylation and expression have shown biological and clinical importance for breast cancer diagnosis and prognosis. Integrated analysis of gene methylation and gene expression may identify genes associated with biology mechanism and clinical outcome of breast cancer and aid in clinical management. Using high-throughput microfluidic quantitative PCR, we analyzed the expression profiles of 48 candidate genes in 96 Chinese breast cancer patients and investigated their correlation with gene methylation and associations with breast cancer clinical parameters. Breast cancer-specific gene expression alternation was found in 25 genes with significant expression difference between paired tumor and normal tissues. A total of 9 genes (CCND2, EGFR, GSTP1, PGR, PTGS2, RECK, SOX17, TNFRSF10D, and WIF1) showed significant negative correlation between methylation and gene expression, which were validated in the TCGA database. Total 23 genes (ACADL, APC, BRCA2, CADM1, CAV1, CCND2, CST6, EGFR, ESR2, GSTP1, ICAM5, NPY, PGR, PTGS2, RECK, RUNX3, SFRP1, SOX17, SYK, TGFBR2, TNFRSF10D, WIF1, and WRN) annotated with potential TFBSs in the promoter regions showed negative correlation between methylation and expression. In logistics regression analysis, 31 of the 48 genes showed improved performance in disease prediction with combination of methylation and expression coefficient. Our results demonstrated the complex correlation and the possible regulatory mechanisms between DNA methylation and gene expression. Integration analysis of methylation and expression of candidate genes could improve performance in breast cancer prediction. These findings would contribute to molecular characterization and identification of biomarkers for potential clinical applications.

Genome-wide profiling identifies a subset of methamphetamine (METH)-induced genes associated with METH-induced increased H4K5Ac binding in the rat striatum

PubMed Central

2013-01-01

Background METH is an illicit drug of abuse that influences gene expression in the rat striatum. Histone modifications regulate gene transcription. Methods We therefore used microarray analysis and genome-scale approaches to examine potential relationships between the effects of METH on gene expression and on DNA binding of histone H4 acetylated at lysine 4 (H4K5Ac) in the rat dorsal striatum of METH-naïve and METH-pretreated rats. Results Acute and chronic METH administration caused differential changes in striatal gene expression. METH also increased H4K5Ac binding around the transcriptional start sites (TSSs) of genes in the rat striatum. In order to relate gene expression to histone acetylation, we binned genes of similar expression into groups of 100 genes and proceeded to relate gene expression to H4K5Ac binding. We found a positive correlation between gene expression and H4K5Ac binding in the striatum of control rats. Similar correlations were observed in METH-treated rats. Genes that showed acute METH-induced increased expression in saline-pretreated rats also showed METH-induced increased H4K5Ac binding. The acute METH injection caused similar increases in H4K5Ac binding in METH-pretreated rats, without affecting gene expression to the same degree. Finally, genes that showed METH-induced decreased expression exhibited either decreases or no changes in H4K5Ac binding. Conclusion Acute METH injections caused increased gene expression of genes that showed increased H4K5Ac binding near their transcription start sites. PMID:23937714

Genome-wide profiling identifies a subset of methamphetamine (METH)-induced genes associated with METH-induced increased H4K5Ac binding in the rat striatum.

PubMed

Cadet, Jean Lud; Jayanthi, Subramaniam; McCoy, Michael T; Ladenheim, Bruce; Saint-Preux, Fabienne; Lehrmann, Elin; De, Supriyo; Becker, Kevin G; Brannock, Christie

2013-08-12

METH is an illicit drug of abuse that influences gene expression in the rat striatum. Histone modifications regulate gene transcription. We therefore used microarray analysis and genome-scale approaches to examine potential relationships between the effects of METH on gene expression and on DNA binding of histone H4 acetylated at lysine 4 (H4K5Ac) in the rat dorsal striatum of METH-naïve and METH-pretreated rats. Acute and chronic METH administration caused differential changes in striatal gene expression. METH also increased H4K5Ac binding around the transcriptional start sites (TSSs) of genes in the rat striatum. In order to relate gene expression to histone acetylation, we binned genes of similar expression into groups of 100 genes and proceeded to relate gene expression to H4K5Ac binding. We found a positive correlation between gene expression and H4K5Ac binding in the striatum of control rats. Similar correlations were observed in METH-treated rats. Genes that showed acute METH-induced increased expression in saline-pretreated rats also showed METH-induced increased H4K5Ac binding. The acute METH injection caused similar increases in H4K5Ac binding in METH-pretreated rats, without affecting gene expression to the same degree. Finally, genes that showed METH-induced decreased expression exhibited either decreases or no changes in H4K5Ac binding. Acute METH injections caused increased gene expression of genes that showed increased H4K5Ac binding near their transcription start sites.

Multiple interval QTL mapping and searching for PSTOL1 homologs associated with root morphology, biomass accumulation and phosphorus content in maize seedlings under low-P.

PubMed

Azevedo, Gabriel C; Cheavegatti-Gianotto, Adriana; Negri, Bárbara F; Hufnagel, Bárbara; E Silva, Luciano da Costa; Magalhaes, Jurandir V; Garcia, Antonio Augusto F; Lana, Ubiraci G P; de Sousa, Sylvia M; Guimaraes, Claudia T

2015-07-07

Modifications in root morphology are important strategies to maximize soil exploitation under phosphorus starvation in plants. Here, we used two multiple interval models to map QTLs related to root traits, biomass accumulation and P content in a maize RIL population cultivated in nutrient solution. In addition, we searched for putative maize homologs to PSTOL1, a gene responsible to enhance early root growth, P uptake and grain yield in rice and sorghum. Based on path analysis, root surface area was the root morphology component that most strongly contributed to total dry weight and to P content in maize seedling under low-P availability. Multiple interval mapping models for single (MIM) and multiple traits (MT-MIM) were combined and revealed 13 genomic regions significantly associated with the target traits in a complementary way. The phenotypic variances explained by all QTLs and their epistatic interactions using MT-MIM (23.4 to 35.5 %) were higher than in previous studies, and presented superior statistical power. Some of these QTLs were coincident with QTLs for root morphology traits and grain yield previously mapped, whereas others harbored ZmPSTOL candidate genes, which shared more than 55 % of amino acid sequence identity and a conserved serine/threonine kinase domain with OsPSTOL1. Additionally, four ZmPSTOL candidate genes co-localized with QTLs for root morphology, biomass accumulation and/or P content were preferentially expressed in roots of the parental lines that contributed the alleles enhancing the respective phenotypes. QTL mapping strategies adopted in this study revealed complementary results for single and multiple traits with high accuracy. Some QTLs, mainly the ones that were also associated with yield performance in other studies, can be good targets for marker-assisted selection to improve P-use efficiency in maize. Based on the co-localization with QTLs, the protein domain conservation and the coincidence of gene expression, we selected novel maize genes as putative homologs to PSTOL1 that will require further validation studies.

Evaluating the consistency of gene sets used in the analysis of bacterial gene expression data.

PubMed

Tintle, Nathan L; Sitarik, Alexandra; Boerema, Benjamin; Young, Kylie; Best, Aaron A; Dejongh, Matthew

2012-08-08

Statistical analyses of whole genome expression data require functional information about genes in order to yield meaningful biological conclusions. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) are common sources of functionally grouped gene sets. For bacteria, the SEED and MicrobesOnline provide alternative, complementary sources of gene sets. To date, no comprehensive evaluation of the data obtained from these resources has been performed. We define a series of gene set consistency metrics directly related to the most common classes of statistical analyses for gene expression data, and then perform a comprehensive analysis of 3581 Affymetrix® gene expression arrays across 17 diverse bacteria. We find that gene sets obtained from GO and KEGG demonstrate lower consistency than those obtained from the SEED and MicrobesOnline, regardless of gene set size. Despite the widespread use of GO and KEGG gene sets in bacterial gene expression data analysis, the SEED and MicrobesOnline provide more consistent sets for a wide variety of statistical analyses. Increased use of the SEED and MicrobesOnline gene sets in the analysis of bacterial gene expression data may improve statistical power and utility of expression data.

Clock genes explain large proportion of phenotypic variance in systolic blood pressure and this control is not modified by environmental temperature

USDA-ARS?s Scientific Manuscript database

BACKGROUND: Diurnal variation in blood pressure (BP) is regulated, in part, by an endogenous circadian clock; however, few human studies have identified associations between clock genes and BP. Accounting for environmental temperature may be necessary to correct for seasonal bias. METHODS: We examin...

Validation of housekeeping genes as an internal control for gene expression studies in Giardia lamblia using quantitative real-time PCR.

PubMed

Marcial-Quino, Jaime; Fierro, Francisco; De la Mora-De la Mora, Ignacio; Enríquez-Flores, Sergio; Gómez-Manzo, Saúl; Vanoye-Carlo, America; Garcia-Torres, Itzhel; Sierra-Palacios, Edgar; Reyes-Vivas, Horacio

2016-04-25

The analysis of transcript levels of specific genes is important for understanding transcriptional regulation and for the characterization of gene function. Real-time quantitative reverse transcriptase PCR (RT-qPCR) has become a powerful tool to quantify gene expression. The objective of this study was to identify reliable housekeeping genes in Giardia lamblia. Twelve genes were selected for this purpose, and their expression was analyzed in the wild type WB strain and in two strains with resistance to nitazoxanide (NTZ) and metronidazole (MTZ), respectively. RefFinder software analysis showed that the expression of the genes is different in the three strains. The integrated data from the four analyses showed that the NADH oxidase (NADH) and aldolase (ALD) genes were the most steadily expressed genes, whereas the glyceraldehyde-3-phosphate dehydrogenase gene was the most unstable. Additionally, the relative expression of seven genes were quantified in the NTZ- and MTZ-resistant strains by RT-qPCR, using the aldolase gene as the internal control, and the results showed a consistent differential pattern of expression in both strains. The housekeeping genes found in this work will facilitate the analysis of mRNA expression levels of other genes of interest in G. lamblia. Copyright © 2016 Elsevier B.V. All rights reserved.

Targeting gene expression selectively in cancer cells by using the progression-elevated gene-3 promoter.

PubMed

Su, Zhao-Zhong; Sarkar, Devanand; Emdad, Luni; Duigou, Gregory J; Young, Charles S H; Ware, Joy; Randolph, Aaron; Valerie, Kristoffer; Fisher, Paul B

2005-01-25

One impediment to effective cancer-specific gene therapy is the rarity of regulatory sequences targeting gene expression selectively in tumor cells. Although many tissue-specific promoters are recognized, few cancer-selective gene promoters are available. Progression-elevated gene-3 (PEG-3) is a rodent gene identified by subtraction hybridization that displays elevated expression as a function of transformation by diversely acting oncogenes, DNA damage, and cancer cell progression. The promoter of PEG-3, PEG-Prom, displays robust expression in a broad spectrum of human cancer cell lines with marginal expression in normal cellular counterparts. Whereas GFP expression, when under the control of a CMV promoter, is detected in both normal and cancer cells, when GFP is expressed under the control of the PEG-Prom, cancer-selective expression is evident. Mutational analysis identifies the AP-1 and PEA-3 transcription factors as primary mediators of selective, cancer-specific expression of the PEG-Prom. Synthesis of apoptosis-inducing genes, under the control of the CMV promoter, inhibits the growth of both normal and cancer cells, whereas PEG-Prom-mediated expression of these genes kills only cancer cells and spares normal cells. The efficacy of the PEG-Prom as part of a cancer gene therapeutic regimen is further documented by in vivo experiments in which PEG-Prom-controlled expression of an apoptosis-inducing gene completely inhibited prostate cancer xenograft growth in nude mice. These compelling observations indicate that the PEG-Prom, with its cancer-specific expression, provides a means of selectively delivering genes to cancer cells, thereby providing a crucial component in developing effective cancer gene therapies.

Evaluation of Allelic Expression of Imprinted Genes in Adult Human Blood

PubMed Central

Frost, Jennifer M.; Monk, Dave; Stojilkovic-Mikic, Taita; Woodfine, Kathryn; Chitty, Lyn S.; Murrell, Adele; Stanier, Philip; Moore, Gudrun E.

2010-01-01

Background Imprinted genes are expressed from only one allele in a parent-of-origin dependent manner. Loss of imprinted (LOI) expression can result in a variety of human disorders and is frequently reported in cancer. Biallelic expression of imprinted genes in adult blood has been suggested as a useful biomarker and is currently being investigated in colorectal cancer. In general, the expression profiles of imprinted genes are well characterised during human and mouse fetal development, but not in human adults. Methodology/Principal Findings We investigated quantitative expression of 36 imprinted genes in adult human peripheral blood leukocytes obtained from healthy individuals. Allelic expression was also investigated in B and T lymphocytes and myeloid cells. We found that 21 genes were essentially undetectable in adult blood. Only six genes were demonstrably monoallelic, and most importantly, we found that nine genes were either biallelic or showed variable expression in different individuals. Separated leukocyte populations showed the same expression patterns as whole blood. Differential methylation at each of the imprinting control loci analysed was maintained, including regions that contained biallelically expressed genes. This suggests in some cases methylation has become uncoupled from its role in regulating gene expression. Conclusions/Significance We conclude that only a limited set of imprinted genes, including IGF2 and SNRPN, may be useful for LOI cancer biomarker studies. In addition, blood is not a good tissue to use for the discovery of new imprinted genes. Finally, lymphocyte DNA methylation status in the adult may not always be a reliable indicator of monoallelic gene expression. PMID:21042416

Evaluation and selection of reliable reference genes for gene expression under abiotic stress in cotton (Gossypium hirsutum L.).

PubMed

Wang, Min; Wang, Qinglian; Zhang, Baohong

2013-11-01

Reference genes are critical for normalization of the gene expression level of target genes. The widely used housekeeping genes may change their expression levels at different tissue under different treatment or stress conditions. Therefore, systematical evaluation on the housekeeping genes is required for gene expression analysis. Up to date, no work was performed to evaluate the housekeeping genes in cotton under stress treatment. In this study, we chose 10 housekeeping genes to systematically assess their expression levels at two different tissues (leaves and roots) under two different abiotic stresses (salt and drought) with three different concentrations. Our results show that there is no best reference gene for all tissues at all stress conditions. The reliable reference gene should be selected based on a specific condition. For example, under salt stress, UBQ7, GAPDH and EF1A8 are better reference genes in leaves; TUA10, UBQ7, CYP1, GAPDH and EF1A8 were better in roots. Under drought stress, UBQ7, EF1A8, TUA10, and GAPDH showed less variety of expression level in leaves and roots. Thus, it is better to identify reliable reference genes first before performing any gene expression analysis. However, using a combination of housekeeping genes as reference gene may provide a new strategy for normalization of gene expression. In this study, we found that combination of four housekeeping genes worked well as reference genes under all the stress conditions. © 2013.

Does Marriage Moderate Genetic Effects on Delinquency and Violence?

PubMed Central

Li, Yi; Liu, Hexuan; Guo, Guang

2015-01-01

Using data from the National Longitudinal Study of Adolescent to Adult Health (N = 1,254), the authors investigated whether marriage can foster desistance from delinquency and violence by moderating genetic effects. In contrast to existing gene–environment research that typically focuses on one or a few genetic polymorphisms, they extended a recently developed mixed linear model to consider the collective influence of 580 single nucleotide polymorphisms in 64 genes related to aggression and risky behavior. The mixed linear model estimates the proportion of variance in the phenotype that is explained by the single nucleotide polymorphisms. The authors found that the proportion of variance in delinquency/violence explained was smaller among married individuals than unmarried individuals. Because selection, confounding, and heterogeneity may bias the estimate of the Gene × Marriage interaction, they conducted a series of analyses to address these issues. The findings suggest that the Gene × Marriage interaction results were not seriously affected by these issues. PMID:26549892

Bayesian segregation analysis of production traits in two strains of laying chickens.

PubMed

Szydłowski, M; Szwaczkowski, T

2001-02-01

A bayesian marker-free segregation analysis was applied to search for evidence of segregating genes affecting production traits in two strains of laying hens under long-term selection. The study used data from 6 generations of Leghorn (H77) and New Hampshire (N88) breeding nuclei. Estimation of marginal posterior means of variance components and parameters of a single autosomal locus was performed by use of the Gibbs sampler. The results showed evidence for a mixed major gene: -polygenic inheritance of BW and age at sexual maturity (ASM) in both strains. Single genes affecting BW and ASM explained one-third of the genetic variance. For ASM large overdominance effect at single locus was estimated. Initial egg production (IEP) and average egg weight (EW) showed a polygenic model of inheritance. The polygenic heritability estimates for BW, ASM, IEP, and EW were 0.32, 0.25, 0.23, and 0.08 in Strain H77 and 0.25, 0.24, 0.11, and 0.38 in Strain N88, respectively.

The effects of parental education on exercise behavior in childhood and youth: a study in Dutch and Finnish twins.

PubMed

Huppertz, C; Bartels, M; de Geus, E J C; van Beijsterveldt, C E M; Rose, R J; Kaprio, J; Silventoinen, K

2017-10-01

Twin studies have estimated the relative contribution of genes and the environment to variance in exercise behavior and it is known that parental education positively affects exercise levels. This study investigates the role of parental education as a potential modifier of variance in exercise behavior from age 7 to 18 years. The study is based on large datasets from the Netherlands Twin Register (NTR: N = 24 874 twins; surveys around the ages of 7, 10, 12, 14, 16 and 18 years) and two Finnish twin cohorts (FinnTwin12: N = 4399; 12, 14 and 17 years; FinnTwin16: N = 4648; 16, 17 and 18 years). Regular participation in moderate-to-vigorous exercise activities during leisure time was assessed by survey. Parental education was dichotomized ("both parents with a low education" vs "at least one parent with a high education"). The mean in exercise behavior tended to be higher and the variance tended to be lower in children of high educated parents. Evidence for gene-by-environment interaction was weak. To develop successful interventions that specifically target children of low educated parents, the mechanisms causing the mean and variance differences between the two groups should be better understood. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

The gsdf gene locus harbors evolutionary conserved and clustered genes preferentially expressed in fish previtellogenic oocytes.

PubMed

Gautier, Aude; Le Gac, Florence; Lareyre, Jean-Jacques

2011-02-01

The gonadal soma-derived factor (GSDF) belongs to the transforming growth factor-β superfamily and is conserved in teleostean fish species. Gsdf is specifically expressed in the gonads, and gene expression is restricted to the granulosa and Sertoli cells in trout and medaka. The gsdf gene expression is correlated to early testis differentiation in medaka and was shown to stimulate primordial germ cell and spermatogonia proliferation in trout. In the present study, we show that the gsdf gene localizes to a syntenic chromosomal fragment conserved among vertebrates although no gsdf-related gene is detected on the corresponding genomic region in tetrapods. We demonstrate using quantitative RT-PCR that most of the genes localized in the synteny are specifically expressed in medaka gonads. Gsdf is the only gene of the synteny with a much higher expression in the testis compared to the ovary. In contrast, gene expression pattern analysis of the gsdf surrounding genes (nup54, aff1, klhl8, sdad1, and ptpn13) indicates that these genes are preferentially expressed in the female gonads. The tissue distribution of these genes is highly similar in medaka and zebrafish, two teleostean species that have diverged more than 110 million years ago. The cellular localization of these genes was determined in medaka gonads using the whole-mount in situ hybridization technique. We confirm that gsdf gene expression is restricted to Sertoli and granulosa cells in contact with the premeiotic and meiotic cells. The nup54 gene is expressed in spermatocytes and previtellogenic oocytes. Transcripts corresponding to the ovary-specific genes (aff1, klhl8, and sdad1) are detected only in previtellogenic oocytes. No expression was detected in the gonocytes in 10 dpf embryos. In conclusion, we show that the gsdf gene localizes to a syntenic chromosomal fragment harboring evolutionary conserved genes in vertebrates. These genes are preferentially expressed in previtelloogenic oocytes, and thus, they display a different cellular localization compared to that of the gsdf gene indicating that the later gene is not co-regulated. Interestingly, our study identifies new clustered genes that are specifically expressed in previtellogenic oocytes (nup54, aff1, klhl8, sdad1). Copyright © 2010 Elsevier B.V. All rights reserved.

Single cell transcriptome analysis of MCF-7 reveals consistently and inconsistently expressed gene groups each associated with distinct cellular localization and functions

PubMed Central

Chen, Tzu-Han; Shiau, Hsin-Chieh

2018-01-01

Single cell transcriptome (SCT) analysis provides superior resolution to illustrate tumor cell heterogeneity for clinical implications. We characterized four SCTs of MCF-7 using 143 housekeeping genes (HKGs) as control, of which lactate dehydrogenase B (LDHB) expression is silenced. These SCT libraries mapped to 11,423, 11,486, 10,380, and 11,306 RefSeq genes (UCSC), respectively. High consistency in HKG expression levels across all four SCTs, along with transcriptional silencing of LDHB, was observed, suggesting a high sensitivity and reproducibility of the SCT analysis. Cross-library comparison on expression levels by scatter plotting revealed a linear correlation and an 83–94% overlap in transcript isoforms and expressed genes were also observed. To gain insight of transcriptional diversity among the SCTs, expressed genes were split into consistently expressed (CE) (expressed in all SCTs) and inconsistently expressed (IE) (expressed in some but not all SCTs) genes for further characterization, along with the 142 expressed HKGs as a reference. Distinct transcriptional strengths were found among these groups, with averages of 1,612.0, 88.0 and 1.2 FPKM for HKGs, CE and IE, respectively. Comparison between CE and IE groups further indicated that expressions of CE genes vary more significantly than that of IE genes. Gene Ontology analysis indicated that proteins encoded by CE genes are mainly involved in fundamental intracellular activities, while proteins encoded by IE genes are mainly for extracellular activities, especially acting as receptors or ion channels. The diversified gene expressions, especially for those encoded by IE genes, may contribute to cancer drug resistance. PMID:29920548

Identification of reference genes for quantitative expression analysis using large-scale RNA-seq data of Arabidopsis thaliana and model crop plants.

PubMed

Kudo, Toru; Sasaki, Yohei; Terashima, Shin; Matsuda-Imai, Noriko; Takano, Tomoyuki; Saito, Misa; Kanno, Maasa; Ozaki, Soichi; Suwabe, Keita; Suzuki, Go; Watanabe, Masao; Matsuoka, Makoto; Takayama, Seiji; Yano, Kentaro

2016-10-13

In quantitative gene expression analysis, normalization using a reference gene as an internal control is frequently performed for appropriate interpretation of the results. Efforts have been devoted to exploring superior novel reference genes using microarray transcriptomic data and to evaluating commonly used reference genes by targeting analysis. However, because the number of specifically detectable genes is totally dependent on probe design in the microarray analysis, exploration using microarray data may miss some of the best choices for the reference genes. Recently emerging RNA sequencing (RNA-seq) provides an ideal resource for comprehensive exploration of reference genes since this method is capable of detecting all expressed genes, in principle including even unknown genes. We report the results of a comprehensive exploration of reference genes using public RNA-seq data from plants such as Arabidopsis thaliana (Arabidopsis), Glycine max (soybean), Solanum lycopersicum (tomato) and Oryza sativa (rice). To select reference genes suitable for the broadest experimental conditions possible, candidates were surveyed by the following four steps: (1) evaluation of the basal expression level of each gene in each experiment; (2) evaluation of the expression stability of each gene in each experiment; (3) evaluation of the expression stability of each gene across the experiments; and (4) selection of top-ranked genes, after ranking according to the number of experiments in which the gene was expressed stably. Employing this procedure, 13, 10, 12 and 21 top candidates for reference genes were proposed in Arabidopsis, soybean, tomato and rice, respectively. Microarray expression data confirmed that the expression of the proposed reference genes under broad experimental conditions was more stable than that of commonly used reference genes. These novel reference genes will be useful for analyzing gene expression profiles across experiments carried out under various experimental conditions.

Near-isogenic cotton germplasm lines that differ in fiber-bundle strength have temporal differences in fiber gene expression patterns as revealed by comparative high-throughput profiling.

PubMed

Hinchliffe, Doug J; Meredith, William R; Yeater, Kathleen M; Kim, Hee Jin; Woodward, Andrew W; Chen, Z Jeffrey; Triplett, Barbara A

2010-05-01

Gene expression profiles of developing cotton (Gossypium hirsutum L.) fibers from two near-isogenic lines (NILs) that differ in fiber-bundle strength, short-fiber content, and in fewer than two genetic loci were compared using an oligonucleotide microarray. Fiber gene expression was compared at five time points spanning fiber elongation and secondary cell wall (SCW) biosynthesis. Fiber samples were collected from field plots in a randomized, complete block design, with three spatially distinct biological replications for each NIL at each time point. Microarray hybridizations were performed in a loop experimental design that allowed comparisons of fiber gene expression profiles as a function of time between the two NILs. Overall, developmental expression patterns revealed by the microarray experiment agreed with previously reported cotton fiber gene expression patterns for specific genes. Additionally, genes expressed coordinately with the onset of SCW biosynthesis in cotton fiber correlated with gene expression patterns of other SCW-producing plant tissues. Functional classification and enrichment analysis of differentially expressed genes between the two NILs revealed that genes associated with SCW biosynthesis were significantly up-regulated in fibers of the high-fiber quality line at the transition stage of cotton fiber development. For independent corroboration of the microarray results, 15 genes were selected for quantitative reverse transcription PCR analysis of fiber gene expression. These analyses, conducted over multiple field years, confirmed the temporal difference in fiber gene expression between the two NILs. We hypothesize that the loci conferring temporal differences in fiber gene expression between the NILs are important regulatory sequences that offer the potential for more targeted manipulation of cotton fiber quality.

Evolutionary conservation of vertebrate notochord genes in the ascidian Ciona intestinalis.

PubMed

Kugler, Jamie E; Passamaneck, Yale J; Feldman, Taya G; Beh, Jeni; Regnier, Todd W; Di Gregorio, Anna

2008-11-01

To reconstruct a minimum complement of notochord genes evolutionarily conserved across chordates, we scanned the Ciona intestinalis genome using the sequences of 182 genes reported to be expressed in the notochord of different vertebrates and identified 139 candidate notochord genes. For 66 of these Ciona genes expression data were already available, hence we analyzed the expression of the remaining 73 genes and found notochord expression for 20. The predicted products of the newly identified notochord genes range from the transcription factors Ci-XBPa and Ci-miER1 to extracellular matrix proteins. We examined the expression of the newly identified notochord genes in embryos ectopically expressing Ciona Brachyury (Ci-Bra) and in embryos expressing a repressor form of this transcription factor in the notochord, and we found that while a subset of the genes examined are clearly responsive to Ci-Bra, other genes are not affected by alterations in its levels. We provide a first description of notochord genes that are not evidently influenced by the ectopic expression of Ci-Bra and we propose alternative regulatory mechanisms that might control their transcription. Copyright 2008 Wiley-Liss, Inc.

Mining microbial metatranscriptomes for expression of antibiotic resistance genes under natural conditions.

PubMed

Versluis, Dennis; D'Andrea, Marco Maria; Ramiro Garcia, Javier; Leimena, Milkha M; Hugenholtz, Floor; Zhang, Jing; Öztürk, Başak; Nylund, Lotta; Sipkema, Detmer; van Schaik, Willem; de Vos, Willem M; Kleerebezem, Michiel; Smidt, Hauke; van Passel, Mark W J

2015-07-08

Antibiotic resistance genes are found in a broad range of ecological niches associated with complex microbiota. Here we investigated if resistance genes are not only present, but also transcribed under natural conditions. Furthermore, we examined the potential for antibiotic production by assessing the expression of associated secondary metabolite biosynthesis gene clusters. Metatranscriptome datasets from intestinal microbiota of four human adults, one human infant, 15 mice and six pigs, of which only the latter have received antibiotics prior to the study, as well as from sea bacterioplankton, a marine sponge, forest soil and sub-seafloor sediment, were investigated. We found that resistance genes are expressed in all studied ecological niches, albeit with niche-specific differences in relative expression levels and diversity of transcripts. For example, in mice and human infant microbiota predominantly tetracycline resistance genes were expressed while in human adult microbiota the spectrum of expressed genes was more diverse, and also included β-lactam, aminoglycoside and macrolide resistance genes. Resistance gene expression could result from the presence of natural antibiotics in the environment, although we could not link it to expression of corresponding secondary metabolites biosynthesis clusters. Alternatively, resistance gene expression could be constitutive, or these genes serve alternative roles besides antibiotic resistance.

Clustering cancer gene expression data by projective clustering ensemble

PubMed Central

Yu, Xianxue; Yu, Guoxian

2017-01-01

Gene expression data analysis has paramount implications for gene treatments, cancer diagnosis and other domains. Clustering is an important and promising tool to analyze gene expression data. Gene expression data is often characterized by a large amount of genes but with limited samples, thus various projective clustering techniques and ensemble techniques have been suggested to combat with these challenges. However, it is rather challenging to synergy these two kinds of techniques together to avoid the curse of dimensionality problem and to boost the performance of gene expression data clustering. In this paper, we employ a projective clustering ensemble (PCE) to integrate the advantages of projective clustering and ensemble clustering, and to avoid the dilemma of combining multiple projective clusterings. Our experimental results on publicly available cancer gene expression data show PCE can improve the quality of clustering gene expression data by at least 4.5% (on average) than other related techniques, including dimensionality reduction based single clustering and ensemble approaches. The empirical study demonstrates that, to further boost the performance of clustering cancer gene expression data, it is necessary and promising to synergy projective clustering with ensemble clustering. PCE can serve as an effective alternative technique for clustering gene expression data. PMID:28234920

Mining microbial metatranscriptomes for expression of antibiotic resistance genes under natural conditions

NASA Astrophysics Data System (ADS)

Versluis, Dennis; D'Andrea, Marco Maria; Ramiro Garcia, Javier; Leimena, Milkha M.; Hugenholtz, Floor; Zhang, Jing; Öztürk, Başak; Nylund, Lotta; Sipkema, Detmer; Schaik, Willem Van; de Vos, Willem M.; Kleerebezem, Michiel; Smidt, Hauke; Passel, Mark W. J. Van

2015-07-01

Antibiotic resistance genes are found in a broad range of ecological niches associated with complex microbiota. Here we investigated if resistance genes are not only present, but also transcribed under natural conditions. Furthermore, we examined the potential for antibiotic production by assessing the expression of associated secondary metabolite biosynthesis gene clusters. Metatranscriptome datasets from intestinal microbiota of four human adults, one human infant, 15 mice and six pigs, of which only the latter have received antibiotics prior to the study, as well as from sea bacterioplankton, a marine sponge, forest soil and sub-seafloor sediment, were investigated. We found that resistance genes are expressed in all studied ecological niches, albeit with niche-specific differences in relative expression levels and diversity of transcripts. For example, in mice and human infant microbiota predominantly tetracycline resistance genes were expressed while in human adult microbiota the spectrum of expressed genes was more diverse, and also included β-lactam, aminoglycoside and macrolide resistance genes. Resistance gene expression could result from the presence of natural antibiotics in the environment, although we could not link it to expression of corresponding secondary metabolites biosynthesis clusters. Alternatively, resistance gene expression could be constitutive, or these genes serve alternative roles besides antibiotic resistance.

Involvement of Resveratrol and ω-3 Polyunsaturated Fatty Acids on Sirtuin 1 Gene Expression in THP1 Cells.

PubMed

Tsuchiya, Takafumi; Endo, Ayano; Tsujikado, Kyoko; Inukai, Toshihiko

2017-10-01

Resveratrol, a kind of polyphenol, has the potential to activate the longevity gene in several cells, in the same manner as calorie restriction. We investigated the effect of resveratrol and ω-3-line polyunsaturated fatty acid on surtuin 1 (SIRT1) gene expression in human monocytes (THP1) cells. We examined the gene expression of THP1 cells using real-time polymerase chain reaction and Western blotting analysis. Resveratol, eicosapentaenoic acid (EPA) and docosahexaeanoic acid (DHA) as n-3 polyunsaturated fatty acid were added on THP1 cells. We observed the changes in the SIRT1 gene expression in those cells, under various doses of agents and in time courses. Then, we examined the interaction of glucose and mannitol on those agents׳ effect of the gene expression. The concentration range of glucose and mannitol was from 5-20mM, respectively. The SIRT1 gene expression could be defined in 24 and 48 hours both in real-time polymerase chain reaction analysis and in Western blotting. Resveratrol showed SIRT1 gene expression in a dose-dependent manner in the range of 0-20μM in both analyses. Although EPA at 10μM showed marked increase in SIRT1 gene expression compared to control condition in Western blotting, this phenomenon was not in dose-dependent manner. DHA did not exhibit any augmentation of SIRT1 gene expression in a dose-dependent manner in the range of 0-20μM in both analyses. We refined the dose-dependent inhibition of the SIRT1 gene expression within 20mM glucose medium. Although 20mM did not exhibit any inhibition, 10μM resveratrol induced the gene expression compared to control medium. Both 5 and 15mM mannitol medium did not significantly alter basic gene expression and 10μM resveratrol-induced gene expression. The present results suggest that resveratrol and EPA, but not DHA, markedly activated the SIRT1 gene expression in THP1 cells, and that high glucose medium could inhibit the basic gene expression, but not powerful resveratrol-induced gene expression, in those cells. Copyright © 2017 Southern Society for Clinical Investigation. Published by Elsevier Inc. All rights reserved.

Influence of Genetic Variations in Selenoprotein Genes on the Pattern of Gene Expression after Supplementation with Brazil Nuts

PubMed Central

Rogero, Marcelo M.; Hesketh, John

2017-01-01

Selenium (Se) is an essential micronutrient for human health. Its beneficial effects are exerted by selenoproteins, which can be quantified in blood and used as molecular biomarkers of Se status. We hypothesize that the presence of genetic polymorphisms in selenoprotein genes may: (1) influence the gene expression of specific selenoproteins and (2) influence the pattern of global gene expression after Brazil nut supplementation. The study was conducted with 130 healthy volunteers in Sao Paulo, Brazil, who consumed one Brazil nut (300 μg/Se) a day for eight weeks. Gene expression of GPX1 and SELENOP and genotyping were measured by real-time PCR using TaqMan Assays. Global gene expression was assessed by microarray using Illumina HumanHT-12 v4 BeadChips. Brazil nut supplementation significantly increased GPX1 mRNA expression only in subjects with CC genotype at rs1050450 (p < 0.05). SELENOP mRNA expression was significantly higher in A-carriers at rs7579 either before or after supplementation (p < 0.05). Genotype for rs713041 in GPX4 affected the pattern of blood cell global gene expression. Genetic variations in selenoprotein genes modulated both GPX1 and SELENOP selenoprotein gene expression and global gene expression in response to Brazil nut supplementation. PMID:28696394

GEOGLE: context mining tool for the correlation between gene expression and the phenotypic distinction.

PubMed

Yu, Yao; Tu, Kang; Zheng, Siyuan; Li, Yun; Ding, Guohui; Ping, Jie; Hao, Pei; Li, Yixue

2009-08-25

In the post-genomic era, the development of high-throughput gene expression detection technology provides huge amounts of experimental data, which challenges the traditional pipelines for data processing and analyzing in scientific researches. In our work, we integrated gene expression information from Gene Expression Omnibus (GEO), biomedical ontology from Medical Subject Headings (MeSH) and signaling pathway knowledge from sigPathway entries to develop a context mining tool for gene expression analysis - GEOGLE. GEOGLE offers a rapid and convenient way for searching relevant experimental datasets, pathways and biological terms according to multiple types of queries: including biomedical vocabularies, GDS IDs, gene IDs, pathway names and signature list. Moreover, GEOGLE summarizes the signature genes from a subset of GDSes and estimates the correlation between gene expression and the phenotypic distinction with an integrated p value. This approach performing global searching of expression data may expand the traditional way of collecting heterogeneous gene expression experiment data. GEOGLE is a novel tool that provides researchers a quantitative way to understand the correlation between gene expression and phenotypic distinction through meta-analysis of gene expression datasets from different experiments, as well as the biological meaning behind. The web site and user guide of GEOGLE are available at: http://omics.biosino.org:14000/kweb/workflow.jsp?id=00020.

Validation of reference genes for quantitative RT-PCR studies of gene expression in perennial ryegrass (Lolium perenne L.)

PubMed Central

2010-01-01

Background Perennial ryegrass (Lolium perenne L.) is an important pasture and turf crop. Biotechniques such as gene expression studies are being employed to improve traits in this temperate grass. Quantitative reverse transcription-polymerase chain reaction (qRT-PCR) is among the best methods available for determining changes in gene expression. Before analysis of target gene expression, it is essential to select an appropriate normalisation strategy to control for non-specific variation between samples. Reference genes that have stable expression at different biological and physiological states can be effectively used for normalisation; however, their expression stability must be validated before use. Results Existing Serial Analysis of Gene Expression data were queried to identify six moderately expressed genes that had relatively stable gene expression throughout the year. These six candidate reference genes (eukaryotic elongation factor 1 alpha, eEF1A; TAT-binding protein homolog 1, TBP-1; eukaryotic translation initiation factor 4 alpha, eIF4A; YT521-B-like protein family protein, YT521-B; histone 3, H3; ubiquitin-conjugating enzyme, E2) were validated for qRT-PCR normalisation in 442 diverse perennial ryegrass (Lolium perenne L.) samples sourced from field- and laboratory-grown plants under a wide range of experimental conditions. Eukaryotic EF1A is encoded by members of a multigene family exhibiting differential expression and necessitated the expression analysis of different eEF1A encoding genes; a highly expressed eEF1A (h), a moderately, but stably expressed eEF1A (s), and combined expression of multigene eEF1A (m). NormFinder identified eEF1A (s) and YT521-B as the best combination of two genes for normalisation of gene expression data in perennial ryegrass following different defoliation management in the field. Conclusions This study is unique in the magnitude of samples tested with the inclusion of numerous field-grown samples, helping pave the way to conduct gene expression studies in perennial biomass crops under field-conditions. From our study several stably expressed reference genes have been validated. This provides useful candidates for reference gene selection in perennial ryegrass under conditions other than those tested here. PMID:20089196

DNMT3B modulates the expression of cancer-related genes and downregulates the expression of the gene VAV3 via methylation

PubMed Central

Peralta-Arrieta, Irlanda; Hernández-Sotelo, Daniel; Castro-Coronel, Yaneth; Leyva-Vázquez, Marco Antonio; Illades-Aguiar, Berenice

2017-01-01

Altered promoter DNA methylation is one of the most important epigenetic abnormalities in human cancer. DNMT3B, de novo methyltransferase, is clearly related to abnormal methylation of tumour suppressor genes, DNA repair genes and its overexpression contributes to oncogenic processes and tumorigenesis in vivo. The purpose of this study was to assess the effect of the overexpression of DNMT3B in HaCaT cells on global gene expression and on the methylation of selected genes to the identification of genes that can be target of DNMT3B. We found that the overexpression of DNMT3B in HaCaT cells, modulate the expression of genes related to cancer, downregulated the expression of 151 genes with CpG islands and downregulated the expression of the VAV3 gene via methylation of its promoter. These results highlight the importance of DNMT3B in gene expression and human cancer. PMID:28123849

DNMT3B modulates the expression of cancer-related genes and downregulates the expression of the gene VAV3 via methylation.

PubMed

Peralta-Arrieta, Irlanda; Hernández-Sotelo, Daniel; Castro-Coronel, Yaneth; Leyva-Vázquez, Marco Antonio; Illades-Aguiar, Berenice

2017-01-01

Altered promoter DNA methylation is one of the most important epigenetic abnormalities in human cancer. DNMT3B, de novo methyltransferase, is clearly related to abnormal methylation of tumour suppressor genes, DNA repair genes and its overexpression contributes to oncogenic processes and tumorigenesis in vivo . The purpose of this study was to assess the effect of the overexpression of DNMT3B in HaCaT cells on global gene expression and on the methylation of selected genes to the identification of genes that can be target of DNMT3B. We found that the overexpression of DNMT3B in HaCaT cells, modulate the expression of genes related to cancer, downregulated the expression of 151 genes with CpG islands and downregulated the expression of the VAV3 gene via methylation of its promoter. These results highlight the importance of DNMT3B in gene expression and human cancer.

Biophysical Constraints Arising from Compositional Context in Synthetic Gene Networks.

PubMed

Yeung, Enoch; Dy, Aaron J; Martin, Kyle B; Ng, Andrew H; Del Vecchio, Domitilla; Beck, James L; Collins, James J; Murray, Richard M

2017-07-26

Synthetic gene expression is highly sensitive to intragenic compositional context (promoter structure, spacing regions between promoter and coding sequences, and ribosome binding sites). However, much less is known about the effects of intergenic compositional context (spatial arrangement and orientation of entire genes on DNA) on expression levels in synthetic gene networks. We compare expression of induced genes arranged in convergent, divergent, or tandem orientations. Induction of convergent genes yielded up to 400% higher expression, greater ultrasensitivity, and dynamic range than divergent- or tandem-oriented genes. Orientation affects gene expression whether one or both genes are induced. We postulate that transcriptional interference in divergent and tandem genes, mediated by supercoiling, can explain differences in expression and validate this hypothesis through modeling and in vitro supercoiling relaxation experiments. Treatment with gyrase abrogated intergenic context effects, bringing expression levels within 30% of each other. We rebuilt the toggle switch with convergent genes, taking advantage of supercoiling effects to improve threshold detection and switch stability. Copyright © 2017 Elsevier Inc. All rights reserved.

Differential gene expression in queen–worker caste determination in bumble-bees

PubMed Central

Pereboom, Jeffrey J. M; Jordan, William C; Sumner, Seirian; Hammond, Robert L; Bourke, Andrew F. G

2005-01-01

Investigating how differential gene expression underlies caste determination in the social Hymenoptera is central to understanding how variation in gene expression underlies adaptive phenotypic diversity. We investigated for the first time the association between differential gene expression and queen–worker caste determination in the bumble-bee Bombus terrestris. Using suppression subtractive hybridization we isolated 12 genes that were differentially expressed in queen- and worker-destined larvae. We found that the sets of genes underlying caste differences in larvae and adults failed to overlap greatly. We also found that B. terrestris shares some of the genes whose differential expression is associated with caste determination in the honeybee, Apis mellifera, but their expression patterns were not identical. Instead, we found B. terrestris to exhibit a novel pattern, whereby most genes upregulated (i.e. showing relatively higher levels of expression) in queen-destined larvae early in development were upregulated in worker-destined larvae late in development. Overall, our results suggest that caste determination in B. terrestris involves a difference not so much in the identity of genes expressed by queen- and worker-destined larvae, but primarily in the relative timing of their expression. This conclusion is of potential importance in the further study of phenotypic diversification via differential gene expression. PMID:16024376

Genetic and environmental contributions to pro-social attitudes: a twin study of social responsibility.

PubMed

Rushton, J Philippe

2004-12-22

Although 51 twin and adoption studies have been performed on the genetic architecture of antisocial behaviour, only four previous studies have examined a genetic contribution to pro-social behaviour. Earlier work by the author with the University of London Institute of Psychiatry Adult Twin Register found that genes contributed approximately half of the variance to measures of self-report altruism, empathy, nurturance and aggression, including acts of violence. The present study extends those results by using a 22-item Social Responsibility Questionnaire with 174 pairs of monozygotic twins and 148 pairs of dizygotic twins. Forty-two per cent of the reliable variance was due to the twins' genes, 23% to the twins' common environment and the remainder to the twins' non-shared environment.

Genetic and environmental contributions to pro-social attitudes: a twin study of social responsibility.

PubMed Central

Rushton, J. Philippe

2004-01-01

Although 51 twin and adoption studies have been performed on the genetic architecture of antisocial behaviour, only four previous studies have examined a genetic contribution to pro-social behaviour. Earlier work by the author with the University of London Institute of Psychiatry Adult Twin Register found that genes contributed approximately half of the variance to measures of self-report altruism, empathy, nurturance and aggression, including acts of violence. The present study extends those results by using a 22-item Social Responsibility Questionnaire with 174 pairs of monozygotic twins and 148 pairs of dizygotic twins. Forty-two per cent of the reliable variance was due to the twins' genes, 23% to the twins' common environment and the remainder to the twins' non-shared environment. PMID:15615684

Regulatory systems for hypoxia-inducible gene expression in ischemic heart disease gene therapy.

PubMed

Kim, Hyun Ah; Rhim, Taiyoun; Lee, Minhyung

2011-07-18

Ischemic heart diseases are caused by narrowed coronary arteries that decrease the blood supply to the myocardium. In the ischemic myocardium, hypoxia-responsive genes are up-regulated by hypoxia-inducible factor-1 (HIF-1). Gene therapy for ischemic heart diseases uses genes encoding angiogenic growth factors and anti-apoptotic proteins as therapeutic genes. These genes increase blood supply into the myocardium by angiogenesis and protect cardiomyocytes from cell death. However, non-specific expression of these genes in normal tissues may be harmful, since growth factors and anti-apoptotic proteins may induce tumor growth. Therefore, tight gene regulation is required to limit gene expression to ischemic tissues, to avoid unwanted side effects. For this purpose, various gene expression strategies have been developed for ischemic-specific gene expression. Transcriptional, post-transcriptional, and post-translational regulatory strategies have been developed and evaluated in ischemic heart disease animal models. The regulatory systems can limit therapeutic gene expression to ischemic tissues and increase the efficiency of gene therapy. In this review, recent progresses in ischemic-specific gene expression systems are presented, and their applications to ischemic heart diseases are discussed. Copyright © 2011 Elsevier B.V. All rights reserved.

Expression patterns of WRKY genes in di-haploid Populus simonii × P. nigra in response to salinity stress revealed by quantitative real-time PCR and RNA sequencing.

PubMed

Wang, Shengji; Wang, Jiying; Yao, Wenjing; Zhou, Boru; Li, Renhua; Jiang, Tingbo

2014-10-01

Spatio-temporal expression patterns of 13 out of 119 poplar WRKY genes indicated dynamic and tissue-specific roles of WRKY family proteins in salinity stress tolerance. To understand the expression patterns of poplar WRKY genes under salinity stress, 51 of the 119 WRKY genes were selected from di-haploid Populus simonii × P. nigra by quantitative real-time PCR (qRT-PCR). We used qRT-PCR to profile the expression of the top 13 genes under salinity stress across seven time points, and employed RNA-Seq platforms to cross-validate it. Results demonstrated that all the 13 WRKY genes were expressed in root, stem, and leaf tissues, but their expression levels and overall patterns varied notably in these tissues. Regarding overall gene expression in roots, the 13 genes were significantly highly expressed at all six time points after the treatment, reaching the plateau of expression at hour 9. In leaves, the 13 genes were similarly up-regulated from 3 to 12 h in response to NaCl treatment. In stems, however, expression levels of the 13 genes did not show significant changes after the NaCl treatment. Regarding individual gene expression across the time points and the three tissues, the 13 genes can be classified into three clusters: the lowly expressed Cluster 1 containing PthWRKY28, 45 and 105; intermediately expressed Clusters 2 including PthWRKY56, 88 and 116; and highly expressed Cluster 3 consisting of PthWRKY41, 44, 51, 61, 62, 75 and 106. In general, genes in Cluster 2 and 3 displayed a dynamic pattern of "induced amplification-recovering", suggesting that these WRKY genes and corresponding pathways may play a critical role in mediating salt response and tolerance in a dynamic and tissue-specific manner.

Hox gene expression during postlarval development of the polychaete Alitta virens.

PubMed

Bakalenko, Nadezhda I; Novikova, Elena L; Nesterenko, Alexander Y; Kulakova, Milana A

2013-05-01

Hox genes are the family of transcription factors that play a key role in the patterning of the anterior-posterior axis of all bilaterian animals. These genes display clustered organization and colinear expression. Expression boundaries of individual Hox genes usually correspond with morphological boundaries of the body. Previously, we studied Hox gene expression during larval development of the polychaete Alitta virens (formerly Nereis virens) and discovered that Hox genes are expressed in nereid larva according to the spatial colinearity principle. Adult Alitta virens consist of multiple morphologically similar segments, which are formed sequentially in the growth zone. Since the worm grows for most of its life, postlarval segments constantly change their position along the anterior-posterior axis. We studied the expression dynamics of the Hox cluster during postlarval development of the nereid Alitta virens and found that 8 out of 11 Hox genes are transcribed as wide gene-specific gradients in the ventral nerve cord, ectoderm, and mesoderm. The expression domains constantly shift in accordance with the changing proportions of the growing worm, so expression domains of most Hox genes do not have stable anterior or/and posterior boundaries.In the course of our study, we revealed long antisense RNA (asRNA) for some Hox genes. Expression patterns of two of these genes were analyzed using whole-mount in-situ hybridization. This is the first discovery of antisense RNA for Hox genes in Lophotrochozoa. Hox gene expression in juvenile A. virens differs significantly from Hox gene expression patterns both in A. virens larva and in other Bilateria.We suppose that the postlarval function of the Hox genes in this polychaete is to establish and maintain positional coordinates in a constantly growing body, as opposed to creating morphological difference between segments.

Light and auxin responsive cytochrome P450s from Withania somnifera Dunal: cloning, expression and molecular modelling of two pairs of homologue genes with differential regulation.

PubMed

Srivastava, Sudhakar; Sangwan, Rajender Singh; Tripathi, Sandhya; Mishra, Bhawana; Narnoliya, L K; Misra, L N; Sangwan, Neelam S

2015-11-01

Cytochrome P450s (CYPs) catalyse a wide variety of oxygenation/hydroxylation reactions that facilitate diverse metabolic functions in plants. Specific CYP families are essential for the biosynthesis of species-specialized metabolites. Therefore, we investigated the role of different CYPs related to secondary metabolism in Withania somnifera, a medicinally important plant of the Indian subcontinent. In this study, complete complementary DNAs (cDNAs) of four different CYP genes were isolated and christened as WSCYP93Id, WSCYP93Sm, WSCYP734B and WSCYP734R. These cDNAs encoded polypeptides comprising of 498, 496, 522 and 550 amino acid residues with their deduced molecular mass of 56.7, 56.9, 59.4 and 62.2 kDa, respectively. Phylogenetic study and molecular modelling analysis of the four cloned WSCYPs revealed their categorization into two CYP families (CYP83B1 and CYP734A1) belonging to CYP71 and CYP72 clans, respectively. BLASTp searches showed similarity of 75 and 56 %, respectively, between the two CYP members of CYP83B1 and CYP734A1 with major variances exhibited in their N-terminal regions. The two pairs of homologues exhibited differential expression profiles in the leaf tissues of selected chemotypes of W. somnifera as well as in response to treatments such as methyl jasmonate, wounding, light and auxin. Light and auxin regulated two pairs of WSCYP homologues in a developing seedling in an interesting differential manner. Their lesser resemblance and homology with other CYP sequences suggested these genes to be more specialized and distinct ones. The results on chemotype-specific expression patterns of the four genes strongly suggested their key/specialized involvement of the CYPs in the biosynthesis of chemotype-specific metabolites, though their further biochemical characterization would reveal the specificity in more detail. It is revealed that WSCYP93Id and WSCYP93Sm may be broadly involved in the oxygenation reactions in the plant and, thereby, control various pathways involving such metabolic reactions in the plant. As a representative experimental validation of this notion, WSCYP93Id was heterologouly expressed in Escherichia coli and catalytic capabilities of the recombinant WSCYP93Id protein were evaluated using withanolides as substrates. Optimized assays with some major withanolides (withanone, withaferin A and withanolide A) involving spectrophotometric as well as high-pressure liquid chromatography (HPLC)-based evaluation (product detection) of the reactions showed conversion of withaferin A to a hydroxylated product. The genes belonging to other CYP group are possibly involved in some specialised synthesis such as that of brassinosteroids.