Gene circuit analysis of the terminal gap gene huckebein.

PubMed

Ashyraliyev, Maksat; Siggens, Ken; Janssens, Hilde; Blom, Joke; Akam, Michael; Jaeger, Johannes

2009-10-01

The early embryo of Drosophila melanogaster provides a powerful model system to study the role of genes in pattern formation. The gap gene network constitutes the first zygotic regulatory tier in the hierarchy of the segmentation genes involved in specifying the position of body segments. Here, we use an integrative, systems-level approach to investigate the regulatory effect of the terminal gap gene huckebein (hkb) on gap gene expression. We present quantitative expression data for the Hkb protein, which enable us to include hkb in gap gene circuit models. Gap gene circuits are mathematical models of gene networks used as computational tools to extract regulatory information from spatial expression data. This is achieved by fitting the model to gap gene expression patterns, in order to obtain estimates for regulatory parameters which predict a specific network topology. We show how considering variability in the data combined with analysis of parameter determinability significantly improves the biological relevance and consistency of the approach. Our models are in agreement with earlier results, which they extend in two important respects: First, we show that Hkb is involved in the regulation of the posterior hunchback (hb) domain, but does not have any other essential function. Specifically, Hkb is required for the anterior shift in the posterior border of this domain, which is now reproduced correctly in our models. Second, gap gene circuits presented here are able to reproduce mutants of terminal gap genes, while previously published models were unable to reproduce any null mutants correctly. As a consequence, our models now capture the expression dynamics of all posterior gap genes and some variational properties of the system correctly. This is an important step towards a better, quantitative understanding of the developmental and evolutionary dynamics of the gap gene network.

A chain reaction approach to modelling gene pathways.

PubMed

Cheng, Gary C; Chen, Dung-Tsa; Chen, James J; Soong, Seng-Jaw; Lamartiniere, Coral; Barnes, Stephen

2012-08-01

BACKGROUND: Of great interest in cancer prevention is how nutrient components affect gene pathways associated with the physiological events of puberty. Nutrient-gene interactions may cause changes in breast or prostate cells and, therefore, may result in cancer risk later in life. Analysis of gene pathways can lead to insights about nutrient-gene interactions and the development of more effective prevention approaches to reduce cancer risk. To date, researchers have relied heavily upon experimental assays (such as microarray analysis, etc.) to identify genes and their associated pathways that are affected by nutrient and diets. However, the vast number of genes and combinations of gene pathways, coupled with the expense of the experimental analyses, has delayed the progress of gene-pathway research. The development of an analytical approach based on available test data could greatly benefit the evaluation of gene pathways, and thus advance the study of nutrient-gene interactions in cancer prevention. In the present study, we have proposed a chain reaction model to simulate gene pathways, in which the gene expression changes through the pathway are represented by the species undergoing a set of chemical reactions. We have also developed a numerical tool to solve for the species changes due to the chain reactions over time. Through this approach we can examine the impact of nutrient-containing diets on the gene pathway; moreover, transformation of genes over time with a nutrient treatment can be observed numerically, which is very difficult to achieve experimentally. We apply this approach to microarray analysis data from an experiment which involved the effects of three polyphenols (nutrient treatments), epigallo-catechin-3-O-gallate (EGCG), genistein, and resveratrol, in a study of nutrient-gene interaction in the estrogen synthesis pathway during puberty. RESULTS: In this preliminary study, the estrogen synthesis pathway was simulated by a chain reaction model. By applying it to microarray data, the chain reaction model computed a set of reaction rates to examine the effects of three polyphenols (EGCG, genistein, and resveratrol) on gene expression in this pathway during puberty. We first performed statistical analysis to test the time factor on the estrogen synthesis pathway. Global tests were used to evaluate an overall gene expression change during puberty for each experimental group. Then, a chain reaction model was employed to simulate the estrogen synthesis pathway. Specifically, the model computed the reaction rates in a set of ordinary differential equations to describe interactions between genes in the pathway (A reaction rate K of A to B represents gene A will induce gene B per unit at a rate of K; we give details in the "method" section). Since disparate changes of gene expression may cause numerical error problems in solving these differential equations, we used an implicit scheme to address this issue. We first applied the chain reaction model to obtain the reaction rates for the control group. A sensitivity study was conducted to evaluate how well the model fits to the control group data at Day 50. Results showed a small bias and mean square error. These observations indicated the model is robust to low random noises and has a good fit for the control group. Then the chain reaction model derived from the control group data was used to predict gene expression at Day 50 for the three polyphenol groups. If these nutrients affect the estrogen synthesis pathways during puberty, we expect discrepancy between observed and expected expressions. Results indicated some genes had large differences in the EGCG (e.g., Hsd3b and Sts) and the resveratrol (e.g., Hsd3b and Hrmt12) groups. CONCLUSIONS: In the present study, we have presented (I) experimental studies of the effect of nutrient diets on the gene expression changes in a selected estrogen synthesis pathway. This experiment is valuable because it allows us to examine how the nutrient-containing diets regulate gene expression in the estrogen synthesis pathway during puberty; (II) global tests to assess an overall association of this particular pathway with time factor by utilizing generalized linear models to analyze microarray data; and (III) a chain reaction model to simulate the pathway. This is a novel application because we are able to translate the gene pathway into the chemical reactions in which each reaction channel describes gene-gene relationship in the pathway. In the chain reaction model, the implicit scheme is employed to efficiently solve the differential equations. Data analysis results show the proposed model is capable of predicting gene expression changes and demonstrating the effect of nutrient-containing diets on gene expression changes in the pathway. One of the objectives of this study is to explore and develop a numerical approach for simulating the gene expression change so that it can be applied and calibrated when the data of more time slices are available, and thus can be used to interpolate the expression change at a desired time point without conducting expensive experiments for a large amount of time points. Hence, we are not claiming this is either essential or the most efficient way for simulating this problem, rather a mathematical/numerical approach that can model the expression change of a large set of genes of a complex pathway. In addition, we understand the limitation of this experiment and realize that it is still far from being a complete model of predicting nutrient-gene interactions. The reason is that in the present model, the reaction rates were estimated based on available data at two time points; hence, the gene expression change is dependent upon the reaction rates and a linear function of the gene expressions. More data sets containing gene expression at various time slices are needed in order to improve the present model so that a non-linear variation of gene expression changes at different time can be predicted.

Modeling genome-wide dynamic regulatory network in mouse lungs with influenza infection using high-dimensional ordinary differential equations.

PubMed

Wu, Shuang; Liu, Zhi-Ping; Qiu, Xing; Wu, Hulin

2014-01-01

The immune response to viral infection is regulated by an intricate network of many genes and their products. The reverse engineering of gene regulatory networks (GRNs) using mathematical models from time course gene expression data collected after influenza infection is key to our understanding of the mechanisms involved in controlling influenza infection within a host. A five-step pipeline: detection of temporally differentially expressed genes, clustering genes into co-expressed modules, identification of network structure, parameter estimate refinement, and functional enrichment analysis, is developed for reconstructing high-dimensional dynamic GRNs from genome-wide time course gene expression data. Applying the pipeline to the time course gene expression data from influenza-infected mouse lungs, we have identified 20 distinct temporal expression patterns in the differentially expressed genes and constructed a module-based dynamic network using a linear ODE model. Both intra-module and inter-module annotations and regulatory relationships of our inferred network show some interesting findings and are highly consistent with existing knowledge about the immune response in mice after influenza infection. The proposed method is a computationally efficient, data-driven pipeline bridging experimental data, mathematical modeling, and statistical analysis. The application to the influenza infection data elucidates the potentials of our pipeline in providing valuable insights into systematic modeling of complicated biological processes.

Comparative methods for the analysis of gene-expression evolution: an example using yeast functional genomic data.

PubMed

Oakley, Todd H; Gu, Zhenglong; Abouheif, Ehab; Patel, Nipam H; Li, Wen-Hsiung

2005-01-01

Understanding the evolution of gene function is a primary challenge of modern evolutionary biology. Despite an expanding database from genomic and developmental studies, we are lacking quantitative methods for analyzing the evolution of some important measures of gene function, such as gene-expression patterns. Here, we introduce phylogenetic comparative methods to compare different models of gene-expression evolution in a maximum-likelihood framework. We find that expression of duplicated genes has evolved according to a nonphylogenetic model, where closely related genes are no more likely than more distantly related genes to share common expression patterns. These results are consistent with previous studies that found rapid evolution of gene expression during the history of yeast. The comparative methods presented here are general enough to test a wide range of evolutionary hypotheses using genomic-scale data from any organism.

Composite transcriptome assembly of RNA-seq data in a sheep model for delayed bone healing.

PubMed

Jäger, Marten; Ott, Claus-Eric; Grünhagen, Johannes; Hecht, Jochen; Schell, Hanna; Mundlos, Stefan; Duda, Georg N; Robinson, Peter N; Lienau, Jasmin

2011-03-24

The sheep is an important model organism for many types of medically relevant research, but molecular genetic experiments in the sheep have been limited by the lack of knowledge about ovine gene sequences. Prior to our study, mRNA sequences for only 1,556 partial or complete ovine genes were publicly available. Therefore, we developed a composite de novo transcriptome assembly method for next-generation sequence data to combine known ovine mRNA and EST sequences, mRNA sequences from mouse and cow, and sequences assembled de novo from short read RNA-Seq data into a composite reference transcriptome, and identified transcripts from over 12 thousand previously undescribed ovine genes. Gene expression analysis based on these data revealed substantially different expression profiles in standard versus delayed bone healing in an ovine tibial osteotomy model. Hundreds of transcripts were differentially expressed between standard and delayed healing and between the time points of the standard and delayed healing groups. We used the sheep sequences to design quantitative RT-PCR assays with which we validated the differential expression of 26 genes that had been identified by RNA-seq analysis. A number of clusters of characteristic expression profiles could be identified, some of which showed striking differences between the standard and delayed healing groups. Gene Ontology (GO) analysis showed that the differentially expressed genes were enriched in terms including extracellular matrix, cartilage development, contractile fiber, and chemokine activity. Our results provide a first atlas of gene expression profiles and differentially expressed genes in standard and delayed bone healing in a large-animal model and provide a number of clues as to the shifts in gene expression that underlie delayed bone healing. In the course of our study, we identified transcripts of 13,987 ovine genes, including 12,431 genes for which no sequence information was previously available. This information will provide a basis for future molecular research involving the sheep as a model organism.

Composite transcriptome assembly of RNA-seq data in a sheep model for delayed bone healing

PubMed Central

2011-01-01

Background The sheep is an important model organism for many types of medically relevant research, but molecular genetic experiments in the sheep have been limited by the lack of knowledge about ovine gene sequences. Results Prior to our study, mRNA sequences for only 1,556 partial or complete ovine genes were publicly available. Therefore, we developed a composite de novo transcriptome assembly method for next-generation sequence data to combine known ovine mRNA and EST sequences, mRNA sequences from mouse and cow, and sequences assembled de novo from short read RNA-Seq data into a composite reference transcriptome, and identified transcripts from over 12 thousand previously undescribed ovine genes. Gene expression analysis based on these data revealed substantially different expression profiles in standard versus delayed bone healing in an ovine tibial osteotomy model. Hundreds of transcripts were differentially expressed between standard and delayed healing and between the time points of the standard and delayed healing groups. We used the sheep sequences to design quantitative RT-PCR assays with which we validated the differential expression of 26 genes that had been identified by RNA-seq analysis. A number of clusters of characteristic expression profiles could be identified, some of which showed striking differences between the standard and delayed healing groups. Gene Ontology (GO) analysis showed that the differentially expressed genes were enriched in terms including extracellular matrix, cartilage development, contractile fiber, and chemokine activity. Conclusions Our results provide a first atlas of gene expression profiles and differentially expressed genes in standard and delayed bone healing in a large-animal model and provide a number of clues as to the shifts in gene expression that underlie delayed bone healing. In the course of our study, we identified transcripts of 13,987 ovine genes, including 12,431 genes for which no sequence information was previously available. This information will provide a basis for future molecular research involving the sheep as a model organism. PMID:21435219

Inference of sigma factor controlled networks by using numerical modeling applied to microarray time series data of the germinating prokaryote.

PubMed

Strakova, Eva; Zikova, Alice; Vohradsky, Jiri

2014-01-01

A computational model of gene expression was applied to a novel test set of microarray time series measurements to reveal regulatory interactions between transcriptional regulators represented by 45 sigma factors and the genes expressed during germination of a prokaryote Streptomyces coelicolor. Using microarrays, the first 5.5 h of the process was recorded in 13 time points, which provided a database of gene expression time series on genome-wide scale. The computational modeling of the kinetic relations between the sigma factors, individual genes and genes clustered according to the similarity of their expression kinetics identified kinetically plausible sigma factor-controlled networks. Using genome sequence annotations, functional groups of genes that were predominantly controlled by specific sigma factors were identified. Using external binding data complementing the modeling approach, specific genes involved in the control of the studied process were identified and their function suggested.

Robust variable selection method for nonparametric differential equation models with application to nonlinear dynamic gene regulatory network analysis.

PubMed

Lu, Tao

2016-01-01

The gene regulation network (GRN) evaluates the interactions between genes and look for models to describe the gene expression behavior. These models have many applications; for instance, by characterizing the gene expression mechanisms that cause certain disorders, it would be possible to target those genes to block the progress of the disease. Many biological processes are driven by nonlinear dynamic GRN. In this article, we propose a nonparametric differential equation (ODE) to model the nonlinear dynamic GRN. Specially, we address following questions simultaneously: (i) extract information from noisy time course gene expression data; (ii) model the nonlinear ODE through a nonparametric smoothing function; (iii) identify the important regulatory gene(s) through a group smoothly clipped absolute deviation (SCAD) approach; (iv) test the robustness of the model against possible shortening of experimental duration. We illustrate the usefulness of the model and associated statistical methods through a simulation and a real application examples.

Novel prediction of anticancer drug chemosensitivity in cancer cell lines: evidence of moderation by microRNA expressions.

PubMed

Yang, Daniel S

2014-01-01

The objectives of this study are (1) to develop a novel "moderation" model of drug chemosensitivity and (2) to investigate if miRNA expression moderates the relationship between gene expression and drug chemosensitivity, specifically for HSP90 inhibitors applied to human cancer cell lines. A moderation model integrating the interaction between miRNA and gene expressions was developed to examine if miRNA expression affects the strength of the relationship between gene expression and chemosensitivity. Comprehensive datasets on miRNA expressions, gene expressions, and drug chemosensitivities were obtained from National Cancer Institute's NCI-60 cell lines including nine different cancer types. A workflow including steps of selecting genes, miRNAs, and compounds, correlating gene expression with chemosensitivity, and performing multivariate analysis was utilized to test the proposed model. The proposed moderation model identified 12 significantly-moderating miRNAs: miR-15b*, miR-16-2*, miR-9, miR-126*, miR-129*, miR-138, miR-519e*, miR-624*, miR-26b, miR-30e*, miR-32, and miR-196a, as well as two genes ERCC2 and SF3B1 which affect chemosensitivities of Tanespimycin and Alvespimycin - both HSP90 inhibitors. A bootstrap resampling of 2,500 times validates the significance of all 12 identified miRNAs. The results confirm that certain miRNA and gene expressions interact to produce an effect on drug response. The lack of correlation between miRNA and gene expression themselves suggests that miRNA transmits its effect through translation inhibition/control rather than mRNA degradation. The results suggest that miRNAs could serve not only as prognostic biomarkers for cancer treatment outcome but also as interventional agents to modulate desired chemosensitivity.

Clustering change patterns using Fourier transformation with time-course gene expression data.

PubMed

Kim, Jaehee

2011-01-01

To understand the behavior of genes, it is important to explore how the patterns of gene expression change over a period of time because biologically related gene groups can share the same change patterns. In this study, the problem of finding similar change patterns is induced to clustering with the derivative Fourier coefficients. This work is aimed at discovering gene groups with similar change patterns which share similar biological properties. We developed a statistical model using derivative Fourier coefficients to identify similar change patterns of gene expression. We used a model-based method to cluster the Fourier series estimation of derivatives. We applied our model to cluster change patterns of yeast cell cycle microarray expression data with alpha-factor synchronization. It showed that, as the method clusters with the probability-neighboring data, the model-based clustering with our proposed model yielded biologically interpretable results. We expect that our proposed Fourier analysis with suitably chosen smoothing parameters could serve as a useful tool in classifying genes and interpreting possible biological change patterns.

Intra- and interspecies gene expression models for predicting drug response in canine osteosarcoma.

PubMed

Fowles, Jared S; Brown, Kristen C; Hess, Ann M; Duval, Dawn L; Gustafson, Daniel L

2016-02-19

Genomics-based predictors of drug response have the potential to improve outcomes associated with cancer therapy. Osteosarcoma (OS), the most common primary bone cancer in dogs, is commonly treated with adjuvant doxorubicin or carboplatin following amputation of the affected limb. We evaluated the use of gene-expression based models built in an intra- or interspecies manner to predict chemosensitivity and treatment outcome in canine OS. Models were built and evaluated using microarray gene expression and drug sensitivity data from human and canine cancer cell lines, and canine OS tumor datasets. The "COXEN" method was utilized to filter gene signatures between human and dog datasets based on strong co-expression patterns. Models were built using linear discriminant analysis via the misclassification penalized posterior algorithm. The best doxorubicin model involved genes identified in human lines that were co-expressed and trained on canine OS tumor data, which accurately predicted clinical outcome in 73 % of dogs (p = 0.0262, binomial). The best carboplatin model utilized canine lines for gene identification and model training, with canine OS tumor data for co-expression. Dogs whose treatment matched our predictions had significantly better clinical outcomes than those that didn't (p = 0.0006, Log Rank), and this predictor significantly associated with longer disease free intervals in a Cox multivariate analysis (hazard ratio = 0.3102, p = 0.0124). Our data show that intra- and interspecies gene expression models can successfully predict response in canine OS, which may improve outcome in dogs and serve as pre-clinical validation for similar methods in human cancer research.

Multiple abiotic stimuli are integrated in the regulation of rice gene expression under field conditions.

PubMed

Plessis, Anne; Hafemeister, Christoph; Wilkins, Olivia; Gonzaga, Zennia Jean; Meyer, Rachel Sarah; Pires, Inês; Müller, Christian; Septiningsih, Endang M; Bonneau, Richard; Purugganan, Michael

2015-11-26

Plants rely on transcriptional dynamics to respond to multiple climatic fluctuations and contexts in nature. We analyzed the genome-wide gene expression patterns of rice (Oryza sativa) growing in rainfed and irrigated fields during two distinct tropical seasons and determined simple linear models that relate transcriptomic variation to climatic fluctuations. These models combine multiple environmental parameters to account for patterns of expression in the field of co-expressed gene clusters. We examined the similarities of our environmental models between tropical and temperate field conditions, using previously published data. We found that field type and macroclimate had broad impacts on transcriptional responses to environmental fluctuations, especially for genes involved in photosynthesis and development. Nevertheless, variation in solar radiation and temperature at the timescale of hours had reproducible effects across environmental contexts. These results provide a basis for broad-based predictive modeling of plant gene expression in the field.

Noise in gene expression is coupled to growth rate.

PubMed

Keren, Leeat; van Dijk, David; Weingarten-Gabbay, Shira; Davidi, Dan; Jona, Ghil; Weinberger, Adina; Milo, Ron; Segal, Eran

2015-12-01

Genetically identical cells exposed to the same environment display variability in gene expression (noise), with important consequences for the fidelity of cellular regulation and biological function. Although population average gene expression is tightly coupled to growth rate, the effects of changes in environmental conditions on expression variability are not known. Here, we measure the single-cell expression distributions of approximately 900 Saccharomyces cerevisiae promoters across four environmental conditions using flow cytometry, and find that gene expression noise is tightly coupled to the environment and is generally higher at lower growth rates. Nutrient-poor conditions, which support lower growth rates, display elevated levels of noise for most promoters, regardless of their specific expression values. We present a simple model of noise in expression that results from having an asynchronous population, with cells at different cell-cycle stages, and with different partitioning of the cells between the stages at different growth rates. This model predicts non-monotonic global changes in noise at different growth rates as well as overall higher variability in expression for cell-cycle-regulated genes in all conditions. The consistency between this model and our data, as well as with noise measurements of cells growing in a chemostat at well-defined growth rates, suggests that cell-cycle heterogeneity is a major contributor to gene expression noise. Finally, we identify gene and promoter features that play a role in gene expression noise across conditions. Our results show the existence of growth-related global changes in gene expression noise and suggest their potential phenotypic implications. © 2015 Keren et al.; Published by Cold Spring Harbor Laboratory Press.

Noise in gene expression is coupled to growth rate

PubMed Central

Keren, Leeat; van Dijk, David; Weingarten-Gabbay, Shira; Davidi, Dan; Jona, Ghil; Weinberger, Adina; Milo, Ron; Segal, Eran

2015-01-01

Genetically identical cells exposed to the same environment display variability in gene expression (noise), with important consequences for the fidelity of cellular regulation and biological function. Although population average gene expression is tightly coupled to growth rate, the effects of changes in environmental conditions on expression variability are not known. Here, we measure the single-cell expression distributions of approximately 900 Saccharomyces cerevisiae promoters across four environmental conditions using flow cytometry, and find that gene expression noise is tightly coupled to the environment and is generally higher at lower growth rates. Nutrient-poor conditions, which support lower growth rates, display elevated levels of noise for most promoters, regardless of their specific expression values. We present a simple model of noise in expression that results from having an asynchronous population, with cells at different cell-cycle stages, and with different partitioning of the cells between the stages at different growth rates. This model predicts non-monotonic global changes in noise at different growth rates as well as overall higher variability in expression for cell-cycle–regulated genes in all conditions. The consistency between this model and our data, as well as with noise measurements of cells growing in a chemostat at well-defined growth rates, suggests that cell-cycle heterogeneity is a major contributor to gene expression noise. Finally, we identify gene and promoter features that play a role in gene expression noise across conditions. Our results show the existence of growth-related global changes in gene expression noise and suggest their potential phenotypic implications. PMID:26355006

Escherichia coli global gene expression in urine from women with urinary tract infection.

PubMed

Hagan, Erin C; Lloyd, Amanda L; Rasko, David A; Faerber, Gary J; Mobley, Harry L T

2010-11-11

Murine models of urinary tract infection (UTI) have provided substantial data identifying uropathogenic E. coli (UPEC) virulence factors and assessing their expression in vivo. However, it is unclear how gene expression in these animal models compares to UPEC gene expression during UTI in humans. To address this, we used a UPEC strain CFT073-specific microarray to measure global gene expression in eight E. coli isolates monitored directly from the urine of eight women presenting at a clinic with bacteriuria. The resulting gene expression profiles were compared to those of the same E. coli isolates cultured statically to exponential phase in pooled, sterilized human urine ex vivo. Known fitness factors, including iron acquisition and peptide transport systems, were highly expressed during human UTI and support a model in which UPEC replicates rapidly in vivo. While these findings were often consistent with previous data obtained from the murine UTI model, host-specific differences were observed. Most strikingly, expression of type 1 fimbrial genes, which are among the most highly expressed genes during murine experimental UTI and encode an essential virulence factor for this experimental model, was undetectable in six of the eight E. coli strains from women with UTI. Despite the lack of type 1 fimbrial expression in the urine samples, these E. coli isolates were generally capable of expressing type 1 fimbriae in vitro and highly upregulated fimA upon experimental murine infection. The findings presented here provide insight into the metabolic and pathogenic profile of UPEC in urine from women with UTI and represent the first transcriptome analysis for any pathogenic E. coli during a naturally occurring infection in humans.

Disruption of DNA methylation-dependent long gene repression in Rett syndrome

PubMed Central

Gabel, Harrison W.; Kinde, Benyam Z.; Stroud, Hume; Gilbert, Caitlin S.; Harmin, David A.; Kastan, Nathaniel R.; Hemberg, Martin; Ebert, Daniel H.; Greenberg, Michael E.

2015-01-01

Disruption of the MECP2 gene leads to Rett syndrome (RTT), a severe neurological disorder with features of autism1. MECP2 encodes a methyl-DNA-binding protein2 that has been proposed to function as a transcriptional repressor, but despite numerous studies examining neuronal gene expression in Mecp2 mutants, no clear model has emerged for how MeCP2 regulates transcription3–9. Here we identify a genome-wide length-dependent increase in gene expression in MeCP2 mutant mouse models and human RTT brains. We present evidence that MeCP2 represses gene expression by binding to methylated CA sites within long genes, and that in neurons lacking MeCP2, decreasing the expression of long genes attenuates RTT-associated cellular deficits. In addition, we find that long genes as a population are enriched for neuronal functions and selectively expressed in the brain. These findings suggest that mutations in MeCP2 may cause neurological dysfunction by specifically disrupting long gene expression in the brain. PMID:25762136

Digital gene expression for non-model organisms

PubMed Central

Hong, Lewis Z.; Li, Jun; Schmidt-Küntzel, Anne; Warren, Wesley C.; Barsh, Gregory S.

2011-01-01

Next-generation sequencing technologies offer new approaches for global measurements of gene expression but are mostly limited to organisms for which a high-quality assembled reference genome sequence is available. We present a method for gene expression profiling called EDGE, or EcoP15I-tagged Digital Gene Expression, based on ultra-high-throughput sequencing of 27-bp cDNA fragments that uniquely tag the corresponding gene, thereby allowing direct quantification of transcript abundance. We show that EDGE is capable of assaying for expression in >99% of genes in the genome and achieves saturation after 6–8 million reads. EDGE exhibits very little technical noise, reveals a large (106) dynamic range of gene expression, and is particularly suited for quantification of transcript abundance in non-model organisms where a high-quality annotated genome is not available. In a direct comparison with RNA-seq, both methods provide similar assessments of relative transcript abundance, but EDGE does better at detecting gene expression differences for poorly expressed genes and does not exhibit transcript length bias. Applying EDGE to laboratory mice, we show that a loss-of-function mutation in the melanocortin 1 receptor (Mc1r), recognized as a Mendelian determinant of yellow hair color in many different mammals, also causes reduced expression of genes involved in the interferon response. To illustrate the application of EDGE to a non-model organism, we examine skin biopsy samples from a cheetah (Acinonyx jubatus) and identify genes likely to control differences in the color of spotted versus non-spotted regions. PMID:21844123

From Coexpression to Coregulation: An Approach to Inferring Transcriptional Regulation Among Gene Classes from Large-Scale Expression Data

NASA Technical Reports Server (NTRS)

Mjolsness, Eric; Castano, Rebecca; Mann, Tobias; Wold, Barbara

2000-01-01

We provide preliminary evidence that existing algorithms for inferring small-scale gene regulation networks from gene expression data can be adapted to large-scale gene expression data coming from hybridization microarrays. The essential steps are (I) clustering many genes by their expression time-course data into a minimal set of clusters of co-expressed genes, (2) theoretically modeling the various conditions under which the time-courses are measured using a continuous-time analog recurrent neural network for the cluster mean time-courses, (3) fitting such a regulatory model to the cluster mean time courses by simulated annealing with weight decay, and (4) analysing several such fits for commonalities in the circuit parameter sets including the connection matrices. This procedure can be used to assess the adequacy of existing and future gene expression time-course data sets for determining transcriptional regulatory relationships such as coregulation.

Expression of Innate Immune Response Genes in Liver and Three Types of Adipose Tissue in Cloned Pigs

PubMed Central

Rødgaard, Tina; Skovgaard, Kerstin; Stagsted, Jan

2012-01-01

Abstract The pig has been proposed as a relevant model for human obesity-induced inflammation, and cloning may improve the applicability of this model. We tested the assumptions that cloning would reduce interindividual variation in gene expression of innate immune factors and that their expression would remain unaffected by the cloning process. We investigated the expression of 40 innate immune factors by high-throughput quantitative real-time PCR in samples from liver, abdominal subcutaneous adipose tissue (SAT), visceral adipose tissue (VAT), and neck SAT in cloned pigs compared to normal outbred pigs. The variation in gene expression was found to be similar for the two groups, and the expression of a small number of genes was significantly affected by cloning. In the VAT and abdominal SAT, six out of seven significantly differentially expressed genes were downregulated in the clones. In contrast, most differently expressed genes in both liver and neck SAT were upregulated (seven out of eight). Remarkably, acute phase proteins (APPs) dominated the upregulated genes in the liver, whereas APP expression was either unchanged or downregulated in abdominal SAT and VAT. The general conclusion from this work is that cloning leads to subtle changes in specific subsets of innate immune genes. Such changes, even if minor, may have phenotypic effects over time, e.g., in models of long-term inflammation related to obesity. PMID:22928970

Gene expression patterns in rainbow trout, Oncorhynchus mykiss, exposed to a suite of model toxicants

PubMed Central

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

2008-01-01

The increased availability and use of DNA microarrays has allowed the characterization of gene expression patterns associated with exposure to different toxicants. An important question is whether toxicant induced changes in gene expression in fish are sufficiently diverse to allow for identification of specific modes of action and/or specific contaminants. In theory, each class of toxicant may generate a gene expression profile unique to its mode of toxic action. In this study, isogenic (cloned) rainbow trout Oncorhynchus mykiss were exposed to sublethal levels of a series of model toxicants with varying modes of action, including ethynylestradiol (xeno-estrogen), 2,2,4,4′-tetrabromodiphenyl ether (BDE-47, thyroid active), diquat (oxidant stressor), chromium VI, and benzo[a]pyrene (BaP) for a period of 1–3 weeks. An additional experiment measured trenbolone (anabolic steroid; model androgen) induced gene expression changes in sexually mature female trout. Following exposure, fish were euthanized, livers removed and RNA extracted. Fluorescently labeled cDNA were generated and hybridized against a commercially available Atlantic Salmon/Trout array (GRASP project, University of Victoria) spotted with 16,000 cDNA’s. The slides were scanned to measure abundance of a given transcript in each sample relative to controls. Data were analyzed via Genespring (Silicon Genetics) to identify a list of up- and downregulated genes, as well as to determine gene clustering patterns that can be used as “expression signatures”. The results indicate each toxicant exposure caused between 64 and 222 genes to be significantly altered in expression. Most genes exhibiting altered expression responded to only one of the toxicants and relatively few were co-expressed in multiple treatments. For example, BaP and Diquat, both of which exert toxicity via oxidative stress, upregulated 28 of the same genes, of over 100 genes altered by either treatment. Other genes associated with steroidogenesis, p450 and estrogen responsive genes appear to be useful for selectively identifying toxicant mode of action in fish, suggesting a link between gene expression profile and mode of toxicity. Our array results showed good agreement with quantitative real time polymerase chain reaction (qRT PCR), which demonstrates that the arrays are an accurate measure of gene expression. The specificity of the gene expression profile in response to a model toxicant, the link between genes with altered expression and mode of toxic action, and the consistency between array and qRT PCR results all suggest that cDNA microarrays have the potential to screen environmental contaminants for biomarkers and mode of toxic action. PMID:16488489

Gene expression patterns in rainbow trout, Oncorhynchus mykiss, exposed to a suite of model toxicants.

PubMed

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

2006-05-25

The increased availability and use of DNA microarrays has allowed the characterization of gene expression patterns associated with exposure to different toxicants. An important question is whether toxicant induced changes in gene expression in fish are sufficiently diverse to allow for identification of specific modes of action and/or specific contaminants. In theory, each class of toxicant may generate a gene expression profile unique to its mode of toxic action. In this study, isogenic (cloned) rainbow trout Oncorhynchus mykiss were exposed to sublethal levels of a series of model toxicants with varying modes of action, including ethynylestradiol (xeno-estrogen), 2,2,4,4'-tetrabromodiphenyl ether (BDE-47, thyroid active), diquat (oxidant stressor), chromium VI, and benzo[a]pyrene (BaP) for a period of 1-3 weeks. An additional experiment measured trenbolone (anabolic steroid; model androgen) induced gene expression changes in sexually mature female trout. Following exposure, fish were euthanized, livers removed and RNA extracted. Fluorescently labeled cDNA were generated and hybridized against a commercially available Atlantic Salmon/Trout array (GRASP project, University of Victoria) spotted with 16,000 cDNA's. The slides were scanned to measure abundance of a given transcript in each sample relative to controls. Data were analyzed via Genespring (Silicon Genetics) to identify a list of up- and downregulated genes, as well as to determine gene clustering patterns that can be used as "expression signatures". The results indicate each toxicant exposure caused between 64 and 222 genes to be significantly altered in expression. Most genes exhibiting altered expression responded to only one of the toxicants and relatively few were co-expressed in multiple treatments. For example, BaP and Diquat, both of which exert toxicity via oxidative stress, upregulated 28 of the same genes, of over 100 genes altered by either treatment. Other genes associated with steroidogenesis, p450 and estrogen responsive genes appear to be useful for selectively identifying toxicant mode of action in fish, suggesting a link between gene expression profile and mode of toxicity. Our array results showed good agreement with quantitative real time polymerase chain reaction (qRT PCR), which demonstrates that the arrays are an accurate measure of gene expression. The specificity of the gene expression profile in response to a model toxicant, the link between genes with altered expression and mode of toxic action, and the consistency between array and qRT PCR results all suggest that cDNA microarrays have the potential to screen environmental contaminants for biomarkers and mode of toxic action.

An improved Pearson's correlation proximity-based hierarchical clustering for mining biological association between genes.

PubMed

Booma, P M; Prabhakaran, S; Dhanalakshmi, R

2014-01-01

Microarray gene expression datasets has concerned great awareness among molecular biologist, statisticians, and computer scientists. Data mining that extracts the hidden and usual information from datasets fails to identify the most significant biological associations between genes. A search made with heuristic for standard biological process measures only the gene expression level, threshold, and response time. Heuristic search identifies and mines the best biological solution, but the association process was not efficiently addressed. To monitor higher rate of expression levels between genes, a hierarchical clustering model was proposed, where the biological association between genes is measured simultaneously using proximity measure of improved Pearson's correlation (PCPHC). Additionally, the Seed Augment algorithm adopts average linkage methods on rows and columns in order to expand a seed PCPHC model into a maximal global PCPHC (GL-PCPHC) model and to identify association between the clusters. Moreover, a GL-PCPHC applies pattern growing method to mine the PCPHC patterns. Compared to existing gene expression analysis, the PCPHC model achieves better performance. Experimental evaluations are conducted for GL-PCPHC model with standard benchmark gene expression datasets extracted from UCI repository and GenBank database in terms of execution time, size of pattern, significance level, biological association efficiency, and pattern quality.

An Improved Pearson's Correlation Proximity-Based Hierarchical Clustering for Mining Biological Association between Genes

PubMed Central

Booma, P. M.; Prabhakaran, S.; Dhanalakshmi, R.

2014-01-01

Microarray gene expression datasets has concerned great awareness among molecular biologist, statisticians, and computer scientists. Data mining that extracts the hidden and usual information from datasets fails to identify the most significant biological associations between genes. A search made with heuristic for standard biological process measures only the gene expression level, threshold, and response time. Heuristic search identifies and mines the best biological solution, but the association process was not efficiently addressed. To monitor higher rate of expression levels between genes, a hierarchical clustering model was proposed, where the biological association between genes is measured simultaneously using proximity measure of improved Pearson's correlation (PCPHC). Additionally, the Seed Augment algorithm adopts average linkage methods on rows and columns in order to expand a seed PCPHC model into a maximal global PCPHC (GL-PCPHC) model and to identify association between the clusters. Moreover, a GL-PCPHC applies pattern growing method to mine the PCPHC patterns. Compared to existing gene expression analysis, the PCPHC model achieves better performance. Experimental evaluations are conducted for GL-PCPHC model with standard benchmark gene expression datasets extracted from UCI repository and GenBank database in terms of execution time, size of pattern, significance level, biological association efficiency, and pattern quality. PMID:25136661

Learning Gene Expression Through Modelling and Argumentation. A Case Study Exploring the Connections Between the Worlds of Knowledge

NASA Astrophysics Data System (ADS)

Puig, Blanca; Ageitos, Noa; Jiménez-Aleixandre, María Pilar

2017-12-01

There is emerging interest on the interactions between modelling and argumentation in specific contexts, such as genetics learning. It has been suggested that modelling might help students understand and argue on genetics. We propose modelling gene expression as a way to learn molecular genetics and diseases with a genetic component. The study is framed in Tiberghien's (2000) two worlds of knowledge, the world of "theories & models" and the world of "objects & events", adding a third component, the world of representations. We seek to examine how modelling and argumentation interact and connect the three worlds of knowledge while modelling gene expression. It is a case study of 10th graders learning about diseases with a genetic component. The research questions are as follows: (1) What argumentative and modelling operations do students enact in the process of modelling gene expression? Specifically, which operations allow connecting the three worlds of knowledge? (2) What are the interactions between modelling and argumentation in modelling gene expression? To what extent do these interactions help students connect the three worlds of knowledge and modelling gene expression? The argumentative operation of using evidence helps students to relate the three worlds of knowledge, enacted in all the connections. It seems to be a relationship among the number of interactions between modelling and argumentation, the connections between world of knowledge and students' capacity to develop a more sophisticated representation. Despite this is a case study, this approach of analysis reveals potentialities for a deeper understanding of learning genetics though scientific practices.

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

Diurnal Transcriptome and Gene Network Represented through Sparse Modeling in Brachypodium distachyon.

PubMed

Koda, Satoru; Onda, Yoshihiko; Matsui, Hidetoshi; Takahagi, Kotaro; Yamaguchi-Uehara, Yukiko; Shimizu, Minami; Inoue, Komaki; Yoshida, Takuhiro; Sakurai, Tetsuya; Honda, Hiroshi; Eguchi, Shinto; Nishii, Ryuei; Mochida, Keiichi

2017-01-01

We report the comprehensive identification of periodic genes and their network inference, based on a gene co-expression analysis and an Auto-Regressive eXogenous (ARX) model with a group smoothly clipped absolute deviation (SCAD) method using a time-series transcriptome dataset in a model grass, Brachypodium distachyon . To reveal the diurnal changes in the transcriptome in B. distachyon , we performed RNA-seq analysis of its leaves sampled through a diurnal cycle of over 48 h at 4 h intervals using three biological replications, and identified 3,621 periodic genes through our wavelet analysis. The expression data are feasible to infer network sparsity based on ARX models. We found that genes involved in biological processes such as transcriptional regulation, protein degradation, and post-transcriptional modification and photosynthesis are significantly enriched in the periodic genes, suggesting that these processes might be regulated by circadian rhythm in B. distachyon . On the basis of the time-series expression patterns of the periodic genes, we constructed a chronological gene co-expression network and identified putative transcription factors encoding genes that might be involved in the time-specific regulatory transcriptional network. Moreover, we inferred a transcriptional network composed of the periodic genes in B. distachyon , aiming to identify genes associated with other genes through variable selection by grouping time points for each gene. Based on the ARX model with the group SCAD regularization using our time-series expression datasets of the periodic genes, we constructed gene networks and found that the networks represent typical scale-free structure. Our findings demonstrate that the diurnal changes in the transcriptome in B. distachyon leaves have a sparse network structure, demonstrating the spatiotemporal gene regulatory network over the cyclic phase transitions in B. distachyon diurnal growth.

A framework for analyzing the relationship between gene expression and morphological, topological, and dynamical patterns in neuronal networks.

PubMed

de Arruda, Henrique Ferraz; Comin, Cesar Henrique; Miazaki, Mauro; Viana, Matheus Palhares; Costa, Luciano da Fontoura

2015-04-30

A key point in developmental biology is to understand how gene expression influences the morphological and dynamical patterns that are observed in living beings. In this work we propose a methodology capable of addressing this problem that is based on estimating the mutual information and Pearson correlation between the intensity of gene expression and measurements of several morphological properties of the cells. A similar approach is applied in order to identify effects of gene expression over the system dynamics. Neuronal networks were artificially grown over a lattice by considering a reference model used to generate artificial neurons. The input parameters of the artificial neurons were determined according to two distinct patterns of gene expression and the dynamical response was assessed by considering the integrate-and-fire model. As far as single gene dependence is concerned, we found that the interaction between the gene expression and the network topology, as well as between the former and the dynamics response, is strongly affected by the gene expression pattern. In addition, we observed a high correlation between the gene expression and some topological measurements of the neuronal network for particular patterns of gene expression. To our best understanding, there are no similar analyses to compare with. A proper understanding of gene expression influence requires jointly studying the morphology, topology, and dynamics of neurons. The proposed framework represents a first step towards predicting gene expression patterns from morphology and connectivity. Copyright © 2015. Published by Elsevier B.V.

Gene Expression Profiling Predicts the Development of Oral Cancer

PubMed Central

Saintigny, Pierre; Zhang, Li; Fan, You-Hong; El-Naggar, Adel K.; Papadimitrakopoulou, Vali; Feng, Lei; Lee, J. Jack; Kim, Edward S.; Hong, Waun Ki; Mao, Li

2011-01-01

Patients with oral preneoplastic lesion (OPL) have high risk of developing oral cancer. Although certain risk factors such as smoking status and histology are known, our ability to predict oral cancer risk remains poor. The study objective was to determine the value of gene expression profiling in predicting oral cancer development. Gene expression profile was measured in 86 of 162 OPL patients who were enrolled in a clinical chemoprevention trial that used the incidence of oral cancer development as a prespecified endpoint. The median follow-up time was 6.08 years and 35 of the 86 patients developed oral cancer over the course. Gene expression profiles were associated with oral cancer-free survival and used to develope multivariate predictive models for oral cancer prediction. We developed a 29-transcript predictive model which showed marked improvement in terms of prediction accuracy (with 8% predicting error rate) over the models using previously known clinico-pathological risk factors. Based on the gene expression profile data, we also identified 2182 transcripts significantly associated with oral cancer risk associated genes (P-value<0.01, single variate Cox proportional hazards model). Functional pathway analysis revealed proteasome machinery, MYC, and ribosomes components as the top gene sets associated with oral cancer risk. In multiple independent datasets, the expression profiles of the genes can differentiate head and neck cancer from normal mucosa. Our results show that gene expression profiles may improve the prediction of oral cancer risk in OPL patients and the significant genes identified may serve as potential targets for oral cancer chemoprevention. PMID:21292635

Hippocampal gene expression in a rat model of depression after electroacupuncture at the Baihui and Yintang acupoints

PubMed Central

Duan, Dongmei; Yang, Xiuyan; Ya, Tu; Chen, Liping

2014-01-01

Preliminary basic research and clinical findings have demonstrated that electroacupuncture therapy exhibits positive effects in ameliorating depression. However, most studies of the underlying mechanism are at the single gene level; there are few reports regarding the mechanism at the whole-genome level. Using a rat genomic gene-chip, we profiled hippocampal gene expression changes in rats after electroacupuncture therapy. Electroacupuncture therapy alleviated depression-related manifestations in the model rats. Using gene-chip analysis, we demonstrated that electroacupuncture at Baihui (DU20) and Yintang (EX-HN3) regulates the expression of 21 genes. Real-time PCR showed that the genes Vgf, Igf2, Tmp32, Loc500373, Hif1a, Folr1, Nmb, and Rtn were upregulated or downregulated in depression and that their expression tended to normalize after electroacupuncture therapy. These results indicate that electroacupuncture at Baihui and Yintang modulates depression by regulating the expression of particular genes. PMID:25206746

Dissecting Embryonic Stem Cell Self-Renewal and Differentiation Commitment from Quantitative Models.

PubMed

Hu, Rong; Dai, Xianhua; Dai, Zhiming; Xiang, Qian; Cai, Yanning

2016-10-01

To model quantitatively embryonic stem cell (ESC) self-renewal and differentiation by computational approaches, we developed a unified mathematical model for gene expression involved in cell fate choices. Our quantitative model comprised ESC master regulators and lineage-specific pivotal genes. It took the factors of multiple pathways as input and computed expression as a function of intrinsic transcription factors, extrinsic cues, epigenetic modifications, and antagonism between ESC master regulators and lineage-specific pivotal genes. In the model, the differential equations of expression of genes involved in cell fate choices from regulation relationship were established according to the transcription and degradation rates. We applied this model to the Murine ESC self-renewal and differentiation commitment and found that it modeled the expression patterns with good accuracy. Our model analysis revealed that Murine ESC was an attractor state in culture and differentiation was predominantly caused by antagonism between ESC master regulators and lineage-specific pivotal genes. Moreover, antagonism among lineages played a critical role in lineage reprogramming. Our results also uncovered that the ordered expression alteration of ESC master regulators over time had a central role in ESC differentiation fates. Our computational framework was generally applicable to most cell-type maintenance and lineage reprogramming.

Translating natural genetic variation to gene expression in a computational model of the Drosophila gap gene regulatory network

PubMed Central

Kozlov, Konstantin N.; Kulakovskiy, Ivan V.; Zubair, Asif; Marjoram, Paul; Lawrie, David S.; Nuzhdin, Sergey V.; Samsonova, Maria G.

2017-01-01

Annotating the genotype-phenotype relationship, and developing a proper quantitative description of the relationship, requires understanding the impact of natural genomic variation on gene expression. We apply a sequence-level model of gap gene expression in the early development of Drosophila to analyze single nucleotide polymorphisms (SNPs) in a panel of natural sequenced D. melanogaster lines. Using a thermodynamic modeling framework, we provide both analytical and computational descriptions of how single-nucleotide variants affect gene expression. The analysis reveals that the sequence variants increase (decrease) gene expression if located within binding sites of repressors (activators). We show that the sign of SNP influence (activation or repression) may change in time and space and elucidate the origin of this change in specific examples. The thermodynamic modeling approach predicts non-local and non-linear effects arising from SNPs, and combinations of SNPs, in individual fly genotypes. Simulation of individual fly genotypes using our model reveals that this non-linearity reduces to almost additive inputs from multiple SNPs. Further, we see signatures of the action of purifying selection in the gap gene regulatory regions. To infer the specific targets of purifying selection, we analyze the patterns of polymorphism in the data at two phenotypic levels: the strengths of binding and expression. We find that combinations of SNPs show evidence of being under selective pressure, while individual SNPs do not. The model predicts that SNPs appear to accumulate in the genotypes of the natural population in a way biased towards small increases in activating action on the expression pattern. Taken together, these results provide a systems-level view of how genetic variation translates to the level of gene regulatory networks via combinatorial SNP effects. PMID:28898266

Gene expression profiling via LongSAGE in a non-model plant species: a case study in seeds of Brassica napus

PubMed Central

Obermeier, Christian; Hosseini, Bashir; Friedt, Wolfgang; Snowdon, Rod

2009-01-01

Background Serial analysis of gene expression (LongSAGE) was applied for gene expression profiling in seeds of oilseed rape (Brassica napus ssp. napus). The usefulness of this technique for detailed expression profiling in a non-model organism was demonstrated for the highly complex, neither fully sequenced nor annotated genome of B. napus by applying a tag-to-gene matching strategy based on Brassica ESTs and the annotated proteome of the closely related model crucifer A. thaliana. Results Transcripts from 3,094 genes were detected at two time-points of seed development, 23 days and 35 days after pollination (DAP). Differential expression showed a shift from gene expression involved in diverse developmental processes including cell proliferation and seed coat formation at 23 DAP to more focussed metabolic processes including storage protein accumulation and lipid deposition at 35 DAP. The most abundant transcripts at 23 DAP were coding for diverse protease inhibitor proteins and proteases, including cysteine proteases involved in seed coat formation and a number of lipid transfer proteins involved in embryo pattern formation. At 35 DAP, transcripts encoding napin, cruciferin and oleosin storage proteins were most abundant. Over both time-points, 18.6% of the detected genes were matched by Brassica ESTs identified by LongSAGE tags in antisense orientation. This suggests a strong involvement of antisense transcript expression in regulatory processes during B. napus seed development. Conclusion This study underlines the potential of transcript tagging approaches for gene expression profiling in Brassica crop species via EST matching to annotated A. thaliana genes. Limits of tag detection for low-abundance transcripts can today be overcome by ultra-high throughput sequencing approaches, so that tag-based gene expression profiling may soon become the method of choice for global expression profiling in non-model species. PMID:19575793

Inferring evolution of gene duplicates using probabilistic models and nonparametric belief propagation.

PubMed

Zeng, Jia; Hannenhalli, Sridhar

2013-01-01

Gene duplication, followed by functional evolution of duplicate genes, is a primary engine of evolutionary innovation. In turn, gene expression evolution is a critical component of overall functional evolution of paralogs. Inferring evolutionary history of gene expression among paralogs is therefore a problem of considerable interest. It also represents significant challenges. The standard approaches of evolutionary reconstruction assume that at an internal node of the duplication tree, the two duplicates evolve independently. However, because of various selection pressures functional evolution of the two paralogs may be coupled. The coupling of paralog evolution corresponds to three major fates of gene duplicates: subfunctionalization (SF), conserved function (CF) or neofunctionalization (NF). Quantitative analysis of these fates is of great interest and clearly influences evolutionary inference of expression. These two interrelated problems of inferring gene expression and evolutionary fates of gene duplicates have not been studied together previously and motivate the present study. Here we propose a novel probabilistic framework and algorithm to simultaneously infer (i) ancestral gene expression and (ii) the likely fate (SF, NF, CF) at each duplication event during the evolution of gene family. Using tissue-specific gene expression data, we develop a nonparametric belief propagation (NBP) algorithm to predict the ancestral expression level as a proxy for function, and describe a novel probabilistic model that relates the predicted and known expression levels to the possible evolutionary fates. We validate our model using simulation and then apply it to a genome-wide set of gene duplicates in human. Our results suggest that SF tends to be more frequent at the earlier stage of gene family expansion, while NF occurs more frequently later on.

Sig2GRN: a software tool linking signaling pathway with gene regulatory network for dynamic simulation.

PubMed

Zhang, Fan; Liu, Runsheng; Zheng, Jie

2016-12-23

Linking computational models of signaling pathways to predicted cellular responses such as gene expression regulation is a major challenge in computational systems biology. In this work, we present Sig2GRN, a Cytoscape plugin that is able to simulate time-course gene expression data given the user-defined external stimuli to the signaling pathways. A generalized logical model is used in modeling the upstream signaling pathways. Then a Boolean model and a thermodynamics-based model are employed to predict the downstream changes in gene expression based on the simulated dynamics of transcription factors in signaling pathways. Our empirical case studies show that the simulation of Sig2GRN can predict changes in gene expression patterns induced by DNA damage signals and drug treatments. As a software tool for modeling cellular dynamics, Sig2GRN can facilitate studies in systems biology by hypotheses generation and wet-lab experimental design. http://histone.scse.ntu.edu.sg/Sig2GRN/.

A Pathway Based Classification Method for Analyzing Gene Expression for Alzheimer's Disease Diagnosis.

PubMed

Voyle, Nicola; Keohane, Aoife; Newhouse, Stephen; Lunnon, Katie; Johnston, Caroline; Soininen, Hilkka; Kloszewska, Iwona; Mecocci, Patrizia; Tsolaki, Magda; Vellas, Bruno; Lovestone, Simon; Hodges, Angela; Kiddle, Steven; Dobson, Richard Jb

2016-01-01

Recent studies indicate that gene expression levels in blood may be able to differentiate subjects with Alzheimer's disease (AD) from normal elderly controls and mild cognitively impaired (MCI) subjects. However, there is limited replicability at the single marker level. A pathway-based interpretation of gene expression may prove more robust. This study aimed to investigate whether a case/control classification model built on pathway level data was more robust than a gene level model and may consequently perform better in test data. The study used two batches of gene expression data from the AddNeuroMed (ANM) and Dementia Case Registry (DCR) cohorts. Our study used Illumina Human HT-12 Expression BeadChips to collect gene expression from blood samples. Random forest modeling with recursive feature elimination was used to predict case/control status. Age and APOE ɛ4 status were used as covariates for all analysis. Gene and pathway level models performed similarly to each other and to a model based on demographic information only. Any potential increase in concordance from the novel pathway level approach used here has not lead to a greater predictive ability in these datasets. However, we have only tested one method for creating pathway level scores. Further, we have been able to benchmark pathways against genes in datasets that had been extensively harmonized. Further work should focus on the use of alternative methods for creating pathway level scores, in particular those that incorporate pathway topology, and the use of an endophenotype based approach.

Gene expression profiling of the hippocampal dentate gyrus in an adult toxicity study captures a variety of neurodevelopmental dysfunctions in rat models of hypothyroidism.

PubMed

Shiraki, Ayako; Saito, Fumiyo; Akane, Hirotoshi; Akahori, Yumi; Imatanaka, Nobuya; Itahashi, Megu; Yoshida, Toshinori; Shibutani, Makoto

2016-01-01

We previously found that developmental hypothyroidism changed the expression of genes in the rat hippocampal dentate gyrus, a brain region where adult neurogenesis is known to occur. In the present study, we performed brain region-specific global gene expression profiling in an adult rat hypothyroidism model to see if it reflected the developmental neurotoxicity we saw in the developmental hypothyroidism model. Starting when male rats were 5 weeks old, we administered 6-propyl-2-thiouracil at a doses of 0, 0.1 and 10 mg kg(-1) body weight by gavage for 28 days. We selected four brain regions to represent both cerebral and cerebellar tissues: hippocampal dentate gyrus, cerebral cortex, corpus callosum and cerebellar vermis. We observed significant alterations in the expression of genes related to neural development (Eph family genes and Robo3) in the cerebral cortex and hippocampal dentate gyrus and in the expression of genes related to myelination (Plp1 and Mbp) in the hippocampal dentate gyrus. We observed only minor changes in the expression of these genes in the corpus callosum and cerebellar vermis. We used real-time reverse-transcription polymerase chain reaction to confirm Chrdl1, Hes5, Mbp, Plp1, Slit1, Robo3 and the Eph family transcript expression changes. The most significant changes in gene expression were found in the dentate gyrus. Considering that the gene expression profile of the adult dentate gyrus closely related to neurogenesis, 28-day toxicity studies looking at gene expression changes in adult hippocampal dentate gyrus may also detect possible developmental neurotoxic effects. Copyright © 2015 John Wiley & Sons, Ltd.

Multiple abiotic stimuli are integrated in the regulation of rice gene expression under field conditions

PubMed Central

Plessis, Anne; Hafemeister, Christoph; Wilkins, Olivia; Gonzaga, Zennia Jean; Meyer, Rachel Sarah; Pires, Inês; Müller, Christian; Septiningsih, Endang M; Bonneau, Richard; Purugganan, Michael

2015-01-01

Plants rely on transcriptional dynamics to respond to multiple climatic fluctuations and contexts in nature. We analyzed the genome-wide gene expression patterns of rice (Oryza sativa) growing in rainfed and irrigated fields during two distinct tropical seasons and determined simple linear models that relate transcriptomic variation to climatic fluctuations. These models combine multiple environmental parameters to account for patterns of expression in the field of co-expressed gene clusters. We examined the similarities of our environmental models between tropical and temperate field conditions, using previously published data. We found that field type and macroclimate had broad impacts on transcriptional responses to environmental fluctuations, especially for genes involved in photosynthesis and development. Nevertheless, variation in solar radiation and temperature at the timescale of hours had reproducible effects across environmental contexts. These results provide a basis for broad-based predictive modeling of plant gene expression in the field. DOI: http://dx.doi.org/10.7554/eLife.08411.001 PMID:26609814

Microarray-based cancer prediction using soft computing approach.

PubMed

Wang, Xiaosheng; Gotoh, Osamu

2009-05-26

One of the difficulties in using gene expression profiles to predict cancer is how to effectively select a few informative genes to construct accurate prediction models from thousands or ten thousands of genes. We screen highly discriminative genes and gene pairs to create simple prediction models involved in single genes or gene pairs on the basis of soft computing approach and rough set theory. Accurate cancerous prediction is obtained when we apply the simple prediction models for four cancerous gene expression datasets: CNS tumor, colon tumor, lung cancer and DLBCL. Some genes closely correlated with the pathogenesis of specific or general cancers are identified. In contrast with other models, our models are simple, effective and robust. Meanwhile, our models are interpretable for they are based on decision rules. Our results demonstrate that very simple models may perform well on cancerous molecular prediction and important gene markers of cancer can be detected if the gene selection approach is chosen reasonably.

Modelling gene expression profiles related to prostate tumor progression using binary states

PubMed Central

2013-01-01

Background Cancer is a complex disease commonly characterized by the disrupted activity of several cancer-related genes such as oncogenes and tumor-suppressor genes. Previous studies suggest that the process of tumor progression to malignancy is dynamic and can be traced by changes in gene expression. Despite the enormous efforts made for differential expression detection and biomarker discovery, few methods have been designed to model the gene expression level to tumor stage during malignancy progression. Such models could help us understand the dynamics and simplify or reveal the complexity of tumor progression. Methods We have modeled an on-off state of gene activation per sample then per stage to select gene expression profiles associated to tumor progression. The selection is guided by statistical significance of profiles based on random permutated datasets. Results We show that our method identifies expected profiles corresponding to oncogenes and tumor suppressor genes in a prostate tumor progression dataset. Comparisons with other methods support our findings and indicate that a considerable proportion of significant profiles is not found by other statistical tests commonly used to detect differential expression between tumor stages nor found by other tailored methods. Ontology and pathway analysis concurred with these findings. Conclusions Results suggest that our methodology may be a valuable tool to study tumor malignancy progression, which might reveal novel cancer therapies. PMID:23721350

Mimosa: Mixture Model of Co-expression to Detect Modulators of Regulatory Interaction

NASA Astrophysics Data System (ADS)

Hansen, Matthew; Everett, Logan; Singh, Larry; Hannenhalli, Sridhar

Functionally related genes tend to be correlated in their expression patterns across multiple conditions and/or tissue-types. Thus co-expression networks are often used to investigate functional groups of genes. In particular, when one of the genes is a transcription factor (TF), the co-expression-based interaction is interpreted, with caution, as a direct regulatory interaction. However, any particular TF, and more importantly, any particular regulatory interaction, is likely to be active only in a subset of experimental conditions. Moreover, the subset of expression samples where the regulatory interaction holds may be marked by presence or absence of a modifier gene, such as an enzyme that post-translationally modifies the TF. Such subtlety of regulatory interactions is overlooked when one computes an overall expression correlation. Here we present a novel mixture modeling approach where a TF-Gene pair is presumed to be significantly correlated (with unknown coefficient) in a (unknown) subset of expression samples. The parameters of the model are estimated using a Maximum Likelihood approach. The estimated mixture of expression samples is then mined to identify genes potentially modulating the TF-Gene interaction. We have validated our approach using synthetic data and on three biological cases in cow and in yeast. While limited in some ways, as discussed, the work represents a novel approach to mine expression data and detect potential modulators of regulatory interactions.

A Modified ABCDE Model of Flowering in Orchids Based on Gene Expression Profiling Studies of the Moth Orchid Phalaenopsis aphrodite

PubMed Central

Lee, Ann-Ying; Chen, Chun-Yi; Chang, Yao-Chien Alex; Chao, Ya-Ting; Shih, Ming-Che

2013-01-01

Previously we developed genomic resources for orchids, including transcriptomic analyses using next-generation sequencing techniques and construction of a web-based orchid genomic database. Here, we report a modified molecular model of flower development in the Orchidaceae based on functional analysis of gene expression profiles in Phalaenopsis aphrodite (a moth orchid) that revealed novel roles for the transcription factors involved in floral organ pattern formation. Phalaenopsis orchid floral organ-specific genes were identified by microarray analysis. Several critical transcription factors including AP3, PI, AP1 and AGL6, displayed distinct spatial distribution patterns. Phylogenetic analysis of orchid MADS box genes was conducted to infer the evolutionary relationship among floral organ-specific genes. The results suggest that gene duplication MADS box genes in orchid may have resulted in their gaining novel functions during evolution. Based on these analyses, a modified model of orchid flowering was proposed. Comparison of the expression profiles of flowers of a peloric mutant and wild-type Phalaenopsis orchid further identified genes associated with lip morphology and peloric effects. Large scale investigation of gene expression profiles revealed that homeotic genes from the ABCDE model of flower development classes A and B in the Phalaenopsis orchid have novel functions due to evolutionary diversification, and display differential expression patterns. PMID:24265826

The Zebrafish Model Organism Database: new support for human disease models, mutation details, gene expression phenotypes and searching

PubMed Central

Howe, Douglas G.; Bradford, Yvonne M.; Eagle, Anne; Fashena, David; Frazer, Ken; Kalita, Patrick; Mani, Prita; Martin, Ryan; Moxon, Sierra Taylor; Paddock, Holly; Pich, Christian; Ramachandran, Sridhar; Ruzicka, Leyla; Schaper, Kevin; Shao, Xiang; Singer, Amy; Toro, Sabrina; Van Slyke, Ceri; Westerfield, Monte

2017-01-01

The Zebrafish Model Organism Database (ZFIN; http://zfin.org) is the central resource for zebrafish (Danio rerio) genetic, genomic, phenotypic and developmental data. ZFIN curators provide expert manual curation and integration of comprehensive data involving zebrafish genes, mutants, transgenic constructs and lines, phenotypes, genotypes, gene expressions, morpholinos, TALENs, CRISPRs, antibodies, anatomical structures, models of human disease and publications. We integrate curated, directly submitted, and collaboratively generated data, making these available to zebrafish research community. Among the vertebrate model organisms, zebrafish are superbly suited for rapid generation of sequence-targeted mutant lines, characterization of phenotypes including gene expression patterns, and generation of human disease models. The recent rapid adoption of zebrafish as human disease models is making management of these data particularly important to both the research and clinical communities. Here, we describe recent enhancements to ZFIN including use of the zebrafish experimental conditions ontology, ‘Fish’ records in the ZFIN database, support for gene expression phenotypes, models of human disease, mutation details at the DNA, RNA and protein levels, and updates to the ZFIN single box search. PMID:27899582

Potential usefulness of D2R reporter gene imaging by IBF as gene therapy monitoring for cerebellar neurodegenerative diseases.

PubMed

Shiba, Kazuhiro; Torashima, Takashi; Hirai, Hirokazu; Ogawa, Kazuma; Akhter, Nasima; Nakajima, Kenichi; Kinuya, Seigo; Mori, Hirofumi

2009-02-01

We investigated a gene expression imaging method to examine the level of therapeutic gene expression in the cerebellum. Using a human immunodeficiency virus derived lentivial vector, we expressed the dopamine D(2) receptor (D(2)R) as a reporter protein to mouse cerebellar Purkinje cells. Biodistribution and ex vivo autoradiography studies were performed by giving [(125)I]5-iodo-7-N-[(1-ethyl-2-pyrrolidinyl)methyl]carboxamide-2,3-dihydrobenzofuran ([(125)I]IBF) (1.85 MBq), as a radioactive D(2)R ligand, to model mice expressing the D(2)R with an HA tag (HA-D(2)R) in the cerebellum. In this study, [(125)I]IBF was bound to the D(2)R expressed in the cerebellum of the model mice selectively. Immunostaining was performed to confirm the HA-D(2)R expression in the cerebellum of the model mice. A significant correlation (r=0.900, P<0.001) between areas that expressed HA-D(2)R by immunostaining and areas in which [(125)I]IBF accumulated by the ex vivo autoradiograms was found. These results indicated that radioiodinated IBF is useful as a reporter probe to detect D(2)R reporter gene expression, which can be used for monitoring therapeutic gene expression in the cerebellum.

Comparison of dorsal root ganglion gene expression in rat models of traumatic and HIV-associated neuropathic pain

PubMed Central

Maratou, Klio; Wallace, Victoria C.J.; Hasnie, Fauzia S.; Okuse, Kenji; Hosseini, Ramine; Jina, Nipurna; Blackbeard, Julie; Pheby, Timothy; Orengo, Christine; Dickenson, Anthony H.; McMahon, Stephen B.; Rice, Andrew S.C.

2009-01-01

To elucidate the mechanisms underlying peripheral neuropathic pain in the context of HIV infection and antiretroviral therapy, we measured gene expression in dorsal root ganglia (DRG) of rats subjected to systemic treatment with the anti-retroviral agent, ddC (Zalcitabine) and concomitant delivery of HIV-gp120 to the rat sciatic nerve. L4 and L5 DRGs were collected at day 14 (time of peak behavioural change) and changes in gene expression were measured using Affymetrix whole genome rat arrays. Conventional analysis of this data set and Gene Set Enrichment Analysis (GSEA) was performed to discover biological processes altered in this model. Transcripts associated with G protein coupled receptor signalling and cell adhesion were enriched in the treated animals, while ribosomal proteins and proteasome pathways were associated with gene down-regulation. To identify genes that are directly relevant to neuropathic mechanical hypersensitivity, as opposed to epiphenomena associated with other aspects of the response to a sciatic nerve lesion, we compared the gp120 + ddC-evoked gene expression with that observed in a model of traumatic neuropathic pain (L5 spinal nerve transection), where hypersensitivity to a static mechanical stimulus is also observed. We identified 39 genes/expressed sequence tags that are differentially expressed in the same direction in both models. Most of these have not previously been implicated in mechanical hypersensitivity and may represent novel targets for therapeutic intervention. As an external control, the RNA expression of three genes was examined by RT-PCR, while the protein levels of two were studied using western blot analysis. PMID:18606552

Implementation of plaid model biclustering method on microarray of carcinoma and adenoma tumor gene expression data

NASA Astrophysics Data System (ADS)

Ardaneswari, Gianinna; Bustamam, Alhadi; Sarwinda, Devvi

2017-10-01

A Tumor is an abnormal growth of cells that serves no purpose. Carcinoma is a tumor that grows from the top of the cell membrane and the organ adenoma is a benign tumor of the gland-like cells or epithelial tissue. In the field of molecular biology, the development of microarray technology is used in the data store of disease genetic expression. For each of microarray gene, an amount of information is stored for each trait or condition. In gene expression data clustering can be done with a bicluster algorithm, thats clustering method which not only the objects to be clustered, but also the properties or condition of the object. This research proposed Plaid Model Biclustering as one of biclustering method. In this study, we discuss the implementation of Plaid Model Biclustering Method on microarray of Carcinoma and Adenoma tumor gene expression data. From the experimental results, we found three biclusters are formed by Carcinoma gene expression data and four biclusters are formed by Adenoma gene expression data.

Gene expression profiles reveal key genes for early diagnosis and treatment of adamantinomatous craniopharyngioma.

PubMed

Yang, Jun; Hou, Ziming; Wang, Changjiang; Wang, Hao; Zhang, Hongbing

2018-04-23

Adamantinomatous craniopharyngioma (ACP) is an aggressive brain tumor that occurs predominantly in the pediatric population. Conventional diagnosis method and standard therapy cannot treat ACPs effectively. In this paper, we aimed to identify key genes for ACP early diagnosis and treatment. Datasets GSE94349 and GSE68015 were obtained from Gene Expression Omnibus database. Consensus clustering was applied to discover the gene clusters in the expression data of GSE94349 and functional enrichment analysis was performed on gene set in each cluster. The protein-protein interaction (PPI) network was built by the Search Tool for the Retrieval of Interacting Genes, and hubs were selected. Support vector machine (SVM) model was built based on the signature genes identified from enrichment analysis and PPI network. Dataset GSE94349 was used for training and testing, and GSE68015 was used for validation. Besides, RT-qPCR analysis was performed to analyze the expression of signature genes in ACP samples compared with normal controls. Seven gene clusters were discovered in the differentially expressed genes identified from GSE94349 dataset. Enrichment analysis of each cluster identified 25 pathways that highly associated with ACP. PPI network was built and 46 hubs were determined. Twenty-five pathway-related genes that overlapped with the hubs in PPI network were used as signatures to establish the SVM diagnosis model for ACP. The prediction accuracy of SVM model for training, testing, and validation data were 94, 85, and 74%, respectively. The expression of CDH1, CCL2, ITGA2, COL8A1, COL6A2, and COL6A3 were significantly upregulated in ACP tumor samples, while CAMK2A, RIMS1, NEFL, SYT1, and STX1A were significantly downregulated, which were consistent with the differentially expressed gene analysis. SVM model is a promising classification tool for screening and early diagnosis of ACP. The ACP-related pathways and signature genes will advance our knowledge of ACP pathogenesis and benefit the therapy improvement.

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.

Gene expression inference with deep learning.

PubMed

Chen, Yifei; Li, Yi; Narayan, Rajiv; Subramanian, Aravind; Xie, Xiaohui

2016-06-15

Large-scale gene expression profiling has been widely used to characterize cellular states in response to various disease conditions, genetic perturbations, etc. Although the cost of whole-genome expression profiles has been dropping steadily, generating a compendium of expression profiling over thousands of samples is still very expensive. Recognizing that gene expressions are often highly correlated, researchers from the NIH LINCS program have developed a cost-effective strategy of profiling only ∼1000 carefully selected landmark genes and relying on computational methods to infer the expression of remaining target genes. However, the computational approach adopted by the LINCS program is currently based on linear regression (LR), limiting its accuracy since it does not capture complex nonlinear relationship between expressions of genes. We present a deep learning method (abbreviated as D-GEX) to infer the expression of target genes from the expression of landmark genes. We used the microarray-based Gene Expression Omnibus dataset, consisting of 111K expression profiles, to train our model and compare its performance to those from other methods. In terms of mean absolute error averaged across all genes, deep learning significantly outperforms LR with 15.33% relative improvement. A gene-wise comparative analysis shows that deep learning achieves lower error than LR in 99.97% of the target genes. We also tested the performance of our learned model on an independent RNA-Seq-based GTEx dataset, which consists of 2921 expression profiles. Deep learning still outperforms LR with 6.57% relative improvement, and achieves lower error in 81.31% of the target genes. D-GEX is available at https://github.com/uci-cbcl/D-GEX CONTACT: xhx@ics.uci.edu Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Gene expression inference with deep learning

PubMed Central

Chen, Yifei; Li, Yi; Narayan, Rajiv; Subramanian, Aravind; Xie, Xiaohui

2016-01-01

Motivation: Large-scale gene expression profiling has been widely used to characterize cellular states in response to various disease conditions, genetic perturbations, etc. Although the cost of whole-genome expression profiles has been dropping steadily, generating a compendium of expression profiling over thousands of samples is still very expensive. Recognizing that gene expressions are often highly correlated, researchers from the NIH LINCS program have developed a cost-effective strategy of profiling only ∼1000 carefully selected landmark genes and relying on computational methods to infer the expression of remaining target genes. However, the computational approach adopted by the LINCS program is currently based on linear regression (LR), limiting its accuracy since it does not capture complex nonlinear relationship between expressions of genes. Results: We present a deep learning method (abbreviated as D-GEX) to infer the expression of target genes from the expression of landmark genes. We used the microarray-based Gene Expression Omnibus dataset, consisting of 111K expression profiles, to train our model and compare its performance to those from other methods. In terms of mean absolute error averaged across all genes, deep learning significantly outperforms LR with 15.33% relative improvement. A gene-wise comparative analysis shows that deep learning achieves lower error than LR in 99.97% of the target genes. We also tested the performance of our learned model on an independent RNA-Seq-based GTEx dataset, which consists of 2921 expression profiles. Deep learning still outperforms LR with 6.57% relative improvement, and achieves lower error in 81.31% of the target genes. Availability and implementation: D-GEX is available at https://github.com/uci-cbcl/D-GEX. Contact: xhx@ics.uci.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:26873929

Comprehensive Expression Map of Transcription Regulators in the Adult Zebrafish Telencephalon Reveals Distinct Neurogenic Niches

PubMed Central

Diotel, Nicolas; Rodriguez Viales, Rebecca; Armant, Olivier; März, Martin; Ferg, Marco; Rastegar, Sepand; Strähle, Uwe

2015-01-01

The zebrafish has become a model to study adult vertebrate neurogenesis. In particular, the adult telencephalon has been an intensely studied structure in the zebrafish brain. Differential expression of transcriptional regulators (TRs) is a key feature of development and tissue homeostasis. Here we report an expression map of 1,202 TR genes in the telencephalon of adult zebrafish. Our results are summarized in a database with search and clustering functions to identify genes expressed in particular regions of the telencephalon. We classified 562 genes into 13 distinct patterns, including genes expressed in the proliferative zone. The remaining 640 genes displayed unique and complex patterns of expression and could thus not be grouped into distinct classes. The neurogenic ventricular regions express overlapping but distinct sets of TR genes, suggesting regional differences in the neurogenic niches in the telencephalon. In summary, the small telencephalon of the zebrafish shows a remarkable complexity in TR gene expression. The adult zebrafish telencephalon has become a model to study neurogenesis. We established the expression pattern of more than 1200 transcription regulators (TR) in the adult telencephalon. The neurogenic regions express overlapping but distinct sets of TR genes suggesting regional differences in the neurogenic potential. J. Comp. Neurol. 523:1202–1221, 2015. © 2015 Wiley Periodicals, Inc. PMID:25556858

Comprehensive expression map of transcription regulators in the adult zebrafish telencephalon reveals distinct neurogenic niches.

PubMed

Diotel, Nicolas; Rodriguez Viales, Rebecca; Armant, Olivier; März, Martin; Ferg, Marco; Rastegar, Sepand; Strähle, Uwe

2015-06-01

The zebrafish has become a model to study adult vertebrate neurogenesis. In particular, the adult telencephalon has been an intensely studied structure in the zebrafish brain. Differential expression of transcriptional regulators (TRs) is a key feature of development and tissue homeostasis. Here we report an expression map of 1,202 TR genes in the telencephalon of adult zebrafish. Our results are summarized in a database with search and clustering functions to identify genes expressed in particular regions of the telencephalon. We classified 562 genes into 13 distinct patterns, including genes expressed in the proliferative zone. The remaining 640 genes displayed unique and complex patterns of expression and could thus not be grouped into distinct classes. The neurogenic ventricular regions express overlapping but distinct sets of TR genes, suggesting regional differences in the neurogenic niches in the telencephalon. In summary, the small telencephalon of the zebrafish shows a remarkable complexity in TR gene expression. The adult zebrafish telencephalon has become a model to study neurogenesis. We established the expression pattern of more than 1200 transcription regulators (TR) in the adult telencephalon. The neurogenic regions express overlapping but distinct sets of TR genes suggesting regional differences in the neurogenic potential. © 2015 Wiley Periodicals, Inc.

GESearch: An Interactive GUI Tool for Identifying Gene Expression Signature.

PubMed

Ye, Ning; Yin, Hengfu; Liu, Jingjing; Dai, Xiaogang; Yin, Tongming

2015-01-01

The huge amount of gene expression data generated by microarray and next-generation sequencing technologies present challenges to exploit their biological meanings. When searching for the coexpression genes, the data mining process is largely affected by selection of algorithms. Thus, it is highly desirable to provide multiple options of algorithms in the user-friendly analytical toolkit to explore the gene expression signatures. For this purpose, we developed GESearch, an interactive graphical user interface (GUI) toolkit, which is written in MATLAB and supports a variety of gene expression data files. This analytical toolkit provides four models, including the mean, the regression, the delegate, and the ensemble models, to identify the coexpression genes, and enables the users to filter data and to select gene expression patterns by browsing the display window or by importing knowledge-based genes. Subsequently, the utility of this analytical toolkit is demonstrated by analyzing two sets of real-life microarray datasets from cell-cycle experiments. Overall, we have developed an interactive GUI toolkit that allows for choosing multiple algorithms for analyzing the gene expression signatures.

Rat Models of Cardiovascular Disease Demonstrate Distinctive Pulmonary Gene Expressions for Vascular Response Genes: Impact of Ozone Exposure

EPA Science Inventory

Comparative gene expression profiling of multiple tissues from rat strains with genetic predisposition to diverse cardiovascular diseases (CVD) can help decode the transcriptional program that governs organ-specific functions. We examined expressions of CVD genes in the lungs of ...

Selection of low-variance expressed Malus x domestica (apple) genes for use as quantitative PCR reference genes (housekeepers)

USDA-ARS?s Scientific Manuscript database

To accurately measure gene expression using PCR-based approaches, there is the need for reference genes that have low variance in expression (housekeeping genes) to normalise the data for RNA quantity and quality. For non-model species such as Malus x domestica (apples), previously, the selection of...

An in vivo and in silico approach to study cis-antisense: a short cut to higher order response

NASA Astrophysics Data System (ADS)

Courtney, Colleen; Varanasi, Usha; Chatterjee, Anushree

2014-03-01

Antisense interactions are present in all domains of life. Typically sense, antisense RNA pairs originate from overlapping genes with convergent face to face promoters, and are speculated to be involved in gene regulation. Recent studies indicate the role of transcriptional interference (TI) in regulating expression of genes in convergent orientation. Modeling antisense, TI gene regulation mechanisms allows us to understand how organisms control gene expression. We present a modeling and experimental framework to understand convergent transcription that combines the effects of transcriptional interference and cis-antisense regulation. Our model shows that combining transcriptional interference and antisense RNA interaction adds multiple-levels of regulation which affords a highly tunable biological output, ranging from first order response to complex higher-order response. To study this system we created a library of experimental constructs with engineered TI and antisense interaction by using face-to-face inducible promoters separated by carefully tailored overlapping DNA sequences to control expression of a set of fluorescent reporter proteins. Studying this gene expression mechanism allows for an understanding of higher order behavior of gene expression networks.

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.

Origins of extrinsic variability in eukaryotic gene expression

NASA Astrophysics Data System (ADS)

Volfson, Dmitri; Marciniak, Jennifer; Blake, William J.; Ostroff, Natalie; Tsimring, Lev S.; Hasty, Jeff

2006-02-01

Variable gene expression within a clonal population of cells has been implicated in a number of important processes including mutation and evolution, determination of cell fates and the development of genetic disease. Recent studies have demonstrated that a significant component of expression variability arises from extrinsic factors thought to influence multiple genes simultaneously, yet the biological origins of this extrinsic variability have received little attention. Here we combine computational modelling with fluorescence data generated from multiple promoter-gene inserts in Saccharomyces cerevisiae to identify two major sources of extrinsic variability. One unavoidable source arising from the coupling of gene expression with population dynamics leads to a ubiquitous lower limit for expression variability. A second source, which is modelled as originating from a common upstream transcription factor, exemplifies how regulatory networks can convert noise in upstream regulator expression into extrinsic noise at the output of a target gene. Our results highlight the importance of the interplay of gene regulatory networks with population heterogeneity for understanding the origins of cellular diversity.

Origins of extrinsic variability in eukaryotic gene expression

NASA Astrophysics Data System (ADS)

Volfson, Dmitri; Marciniak, Jennifer; Blake, William J.; Ostroff, Natalie; Tsimring, Lev S.; Hasty, Jeff

2006-03-01

Variable gene expression within a clonal population of cells has been implicated in a number of important processes including mutation and evolution, determination of cell fates and the development of genetic disease. Recent studies have demonstrated that a significant component of expression variability arises from extrinsic factors thought to influence multiple genes in concert, yet the biological origins of this extrinsic variability have received little attention. Here we combine computational modeling with fluorescence data generated from multiple promoter-gene inserts in Saccharomyces cerevisiae to identify two major sources of extrinsic variability. One unavoidable source arising from the coupling of gene expression with population dynamics leads to a ubiquitous noise floor in expression variability. A second source which is modeled as originating from a common upstream transcription factor exemplifies how regulatory networks can convert noise in upstream regulator expression into extrinsic noise at the output of a target gene. Our results highlight the importance of the interplay of gene regulatory networks with population heterogeneity for understanding the origins of cellular diversity.

Pluripotency, Differentiation, and Reprogramming: A Gene Expression Dynamics Model with Epigenetic Feedback Regulation

PubMed Central

Miyamoto, Tadashi; Furusawa, Chikara; Kaneko, Kunihiko

2015-01-01

Embryonic stem cells exhibit pluripotency: they can differentiate into all types of somatic cells. Pluripotent genes such as Oct4 and Nanog are activated in the pluripotent state, and their expression decreases during cell differentiation. Inversely, expression of differentiation genes such as Gata6 and Gata4 is promoted during differentiation. The gene regulatory network controlling the expression of these genes has been described, and slower-scale epigenetic modifications have been uncovered. Although the differentiation of pluripotent stem cells is normally irreversible, reprogramming of cells can be experimentally manipulated to regain pluripotency via overexpression of certain genes. Despite these experimental advances, the dynamics and mechanisms of differentiation and reprogramming are not yet fully understood. Based on recent experimental findings, we constructed a simple gene regulatory network including pluripotent and differentiation genes, and we demonstrated the existence of pluripotent and differentiated states from the resultant dynamical-systems model. Two differentiation mechanisms, interaction-induced switching from an expression oscillatory state and noise-assisted transition between bistable stationary states, were tested in the model. The former was found to be relevant to the differentiation process. We also introduced variables representing epigenetic modifications, which controlled the threshold for gene expression. By assuming positive feedback between expression levels and the epigenetic variables, we observed differentiation in expression dynamics. Additionally, with numerical reprogramming experiments for differentiated cells, we showed that pluripotency was recovered in cells by imposing overexpression of two pluripotent genes and external factors to control expression of differentiation genes. Interestingly, these factors were consistent with the four Yamanaka factors, Oct4, Sox2, Klf4, and Myc, which were necessary for the establishment of induced pluripotent stem cells. These results, based on a gene regulatory network and expression dynamics, contribute to our wider understanding of pluripotency, differentiation, and reprogramming of cells, and they provide a fresh viewpoint on robustness and control during development. PMID:26308610

Genes and Proteins Differentially Expressed during In Vitro Malignant Transformation of Bovine Pancreatic Duct Cells1

PubMed Central

Jesnowski, R; Zubakov, Dmitri; Faissner, Ralf; Ringel, Jörg; Hoheisel, Jörg D; Lösel, Ralf; Schnölzer, Martina; Löhr, Matthias

2007-01-01

Abstract Pancreatic carcinoma has an extremely bad prognosis due to lack of early diagnostic markers and lack of effective therapeutic strategies. Recently, we have established an in vitro model recapitulating the first steps in the carcinogenesis of the pancreas. SV40 large T antigen-immortalized bovine pancreatic duct cells formed intrapancreatic adenocarcinoma tumors on k-rasmut transfection after orthotopic injection in the nude mouse pancreas. Here we identified genes and proteins differentially expressed in the course of malignant transformation using reciprocal suppression subtractive hybridization and 2D gel electrophoresis and mass spectrometry, respectively. We identified 34 differentially expressed genes, expressed sequence tags, and 15 unique proteins. Differential expression was verified for some of the genes or proteins in samples from pancreatic carcinoma. Among these genes and proteins, the majority had already been described either to be influenced by a mutated ras or to be differentially expressed in pancreatic adenocarcinoma, thus proving the feasibility of our model. Other genes and proteins (e.g., BBC1, GLTSCR2, and rhoGDIα), up to now, have not been implicated in pancreatic tumor development. Thus, we were able to establish an in vitro model of pancreatic carcinogenesis, which enabled us to identify genes and proteins differentially expressed during the early steps of malignant transformation. PMID:17356710

Stochastic model of transcription factor-regulated gene expression

NASA Astrophysics Data System (ADS)

Karmakar, Rajesh; Bose, Indrani

2006-09-01

We consider a stochastic model of transcription factor (TF)-regulated gene expression. The model describes two genes, gene A and gene B, which synthesize the TFs and the target gene proteins, respectively. We show through analytic calculations that the TF fluctuations have a significant effect on the distribution of the target gene protein levels when the mean TF level falls in the highest sensitive region of the dose-response curve. We further study the effect of reducing the copy number of gene A from two to one. The enhanced TF fluctuations yield results different from those in the deterministic case. The probability that the target gene protein level exceeds a threshold value is calculated with the knowledge of the probability density functions associated with the TF and target gene protein levels. Numerical simulation results for a more detailed stochastic model are shown to be in agreement with those obtained through analytic calculations. The relevance of these results in the context of the genetic disorder haploinsufficiency is pointed out. Some experimental observations on the haploinsufficiency of the tumour suppressor gene, Nkx 3.1, are explained with the help of the stochastic model of TF-regulated gene expression.

Creating and validating cis-regulatory maps of tissue-specific gene expression regulation

PubMed Central

O'Connor, Timothy R.; Bailey, Timothy L.

2014-01-01

Predicting which genomic regions control the transcription of a given gene is a challenge. We present a novel computational approach for creating and validating maps that associate genomic regions (cis-regulatory modules–CRMs) with genes. The method infers regulatory relationships that explain gene expression observed in a test tissue using widely available genomic data for ‘other’ tissues. To predict the regulatory targets of a CRM, we use cross-tissue correlation between histone modifications present at the CRM and expression at genes within 1 Mbp of it. To validate cis-regulatory maps, we show that they yield more accurate models of gene expression than carefully constructed control maps. These gene expression models predict observed gene expression from transcription factor binding in the CRMs linked to that gene. We show that our maps are able to identify long-range regulatory interactions and improve substantially over maps linking genes and CRMs based on either the control maps or a ‘nearest neighbor’ heuristic. Our results also show that it is essential to include CRMs predicted in multiple tissues during map-building, that H3K27ac is the most informative histone modification, and that CAGE is the most informative measure of gene expression for creating cis-regulatory maps. PMID:25200088

Clinical and multiple gene expression variables in survival analysis of breast cancer: Analysis with the hypertabastic survival model

PubMed Central

2012-01-01

Background We explore the benefits of applying a new proportional hazard model to analyze survival of breast cancer patients. As a parametric model, the hypertabastic survival model offers a closer fit to experimental data than Cox regression, and furthermore provides explicit survival and hazard functions which can be used as additional tools in the survival analysis. In addition, one of our main concerns is utilization of multiple gene expression variables. Our analysis treats the important issue of interaction of different gene signatures in the survival analysis. Methods The hypertabastic proportional hazards model was applied in survival analysis of breast cancer patients. This model was compared, using statistical measures of goodness of fit, with models based on the semi-parametric Cox proportional hazards model and the parametric log-logistic and Weibull models. The explicit functions for hazard and survival were then used to analyze the dynamic behavior of hazard and survival functions. Results The hypertabastic model provided the best fit among all the models considered. Use of multiple gene expression variables also provided a considerable improvement in the goodness of fit of the model, as compared to use of only one. By utilizing the explicit survival and hazard functions provided by the model, we were able to determine the magnitude of the maximum rate of increase in hazard, and the maximum rate of decrease in survival, as well as the times when these occurred. We explore the influence of each gene expression variable on these extrema. Furthermore, in the cases of continuous gene expression variables, represented by a measure of correlation, we were able to investigate the dynamics with respect to changes in gene expression. Conclusions We observed that use of three different gene signatures in the model provided a greater combined effect and allowed us to assess the relative importance of each in determination of outcome in this data set. These results point to the potential to combine gene signatures to a greater effect in cases where each gene signature represents some distinct aspect of the cancer biology. Furthermore we conclude that the hypertabastic survival models can be an effective survival analysis tool for breast cancer patients. PMID:23241496

On construction of stochastic genetic networks based on gene expression sequences.

PubMed

Ching, Wai-Ki; Ng, Michael M; Fung, Eric S; Akutsu, Tatsuya

2005-08-01

Reconstruction of genetic regulatory networks from time series data of gene expression patterns is an important research topic in bioinformatics. Probabilistic Boolean Networks (PBNs) have been proposed as an effective model for gene regulatory networks. PBNs are able to cope with uncertainty, corporate rule-based dependencies between genes and discover the sensitivity of genes in their interactions with other genes. However, PBNs are unlikely to use directly in practice because of huge amount of computational cost for obtaining predictors and their corresponding probabilities. In this paper, we propose a multivariate Markov model for approximating PBNs and describing the dynamics of a genetic network for gene expression sequences. The main contribution of the new model is to preserve the strength of PBNs and reduce the complexity of the networks. The number of parameters of our proposed model is O(n2) where n is the number of genes involved. We also develop efficient estimation methods for solving the model parameters. Numerical examples on synthetic data sets and practical yeast data sequences are given to demonstrate the effectiveness of the proposed model.

On the robustness of complex heterogeneous gene expression networks.

PubMed

Gómez-Gardeñes, Jesús; Moreno, Yamir; Floría, Luis M

2005-04-01

We analyze a continuous gene expression model on the underlying topology of a complex heterogeneous network. Numerical simulations aimed at studying the chaotic and periodic dynamics of the model are performed. The results clearly indicate that there is a region in which the dynamical and structural complexity of the system avoid chaotic attractors. However, contrary to what has been reported for Random Boolean Networks, the chaotic phase cannot be completely suppressed, which has important bearings on network robustness and gene expression modeling.

Large-scale gene expression profiling data for the model moss Physcomitrella patens aid understanding of developmental progression, culture and stress conditions.

PubMed

Hiss, Manuel; Laule, Oliver; Meskauskiene, Rasa M; Arif, Muhammad A; Decker, Eva L; Erxleben, Anika; Frank, Wolfgang; Hanke, Sebastian T; Lang, Daniel; Martin, Anja; Neu, Christina; Reski, Ralf; Richardt, Sandra; Schallenberg-Rüdinger, Mareike; Szövényi, Peter; Tiko, Theodhor; Wiedemann, Gertrud; Wolf, Luise; Zimmermann, Philip; Rensing, Stefan A

2014-08-01

The moss Physcomitrella patens is an important model organism for studying plant evolution, development, physiology and biotechnology. Here we have generated microarray gene expression data covering the principal developmental stages, culture forms and some environmental/stress conditions. Example analyses of developmental stages and growth conditions as well as abiotic stress treatments demonstrate that (i) growth stage is dominant over culture conditions, (ii) liquid culture is not stressful for the plant, (iii) low pH might aid protoplastation by reduced expression of cell wall structure genes, (iv) largely the same gene pool mediates response to dehydration and rehydration, and (v) AP2/EREBP transcription factors play important roles in stress response reactions. With regard to the AP2 gene family, phylogenetic analysis and comparison with Arabidopsis thaliana shows commonalities as well as uniquely expressed family members under drought, light perturbations and protoplastation. Gene expression profiles for P. patens are available for the scientific community via the easy-to-use tool at https://www.genevestigator.com. By providing large-scale expression profiles, the usability of this model organism is further enhanced, for example by enabling selection of control genes for quantitative real-time PCR. Now, gene expression levels across a broad range of conditions can be accessed online for P. patens. © 2014 The Authors The Plant Journal © 2014 John Wiley & Sons Ltd.

Comparison of the Gene Expression Profiles of Human Hematopoietic Stem Cells between Humans and a Humanized Xenograft Model.

PubMed

Matsuzawa, Hideyuki; Matsushita, Hiromichi; Yahata, Takashi; Tanaka, Masayuki; Ando, Kiyoshi

2017-04-20

The aim of this study is to evaluate the feasibility of NOD/Shi-scid-IL2Rγ null (NOG) mice transplanted with human CD34 + /CD38 - /Lin -/low hematopoietic cells from cord blood (CB) as an experimental model of the gene expression in human hematopoiesis. We compared the gene expressions of human CD34 + /CD38 - /Lin -/low cells from human bone marrow (BM) and in xenograft models. The microarray data revealed that 25 KEGG pathways were extracted from the comparison of human CD34 + /CD38 - /Lin -/low HSCs between CB and BM, and that 17 of them--which were mostly related to cellular survival, RNA metabolism and lymphoid development--were shared with the xenograft model. When the probes that were commonly altered in CD34 + /CD38 - /Lin -/low cells from both human and xenograft BM were analyzed, most of them, including the genes related hypoxia, hematopoietic differentiation, epigenetic modification, translation initiation, and RNA degradation, were downregulated. These alterations of gene expression suggest a reduced differentiation capacity and likely include key alterations of gene expression for settlement of CB CD34 + /CD38 - /Lin -/low cells in BM. Our findings demonstrate that the xenograft model of human CB CD34 + /CD38 - /Lin -/low cells using NOG mice was useful, at least in part, for the evaluation of the gene expression profile of human hematopoietic stem cells.

Triazole induced concentration-related gene signatures in rat whole embryo culture.

PubMed

Robinson, Joshua F; Tonk, Elisa C M; Verhoef, Aart; Piersma, Aldert H

2012-09-01

Commonly used as antifungal agents in agriculture and medicine, triazoles have been shown to cause teratogenicity in a diverse set of animal models. Here, we evaluated the dose-dependent impacts of flusilazole, cyproconazole and triadimefon, on global gene expression in relation to effects on embryonic development using the rat whole embryo culture (WEC) model. After 4 h exposure, we identified changes in gene expression due to triazole exposure which preceded morphological alterations observed at 48 h. In general, across the three triazoles, we observed similar directionality of regulation in gene expression and the magnitude of effects on gene expression correlated with the degree of induced developmental toxicity. Significantly regulated genes included key members of steroid/cholesterol and retinoic acid metabolism and hindbrain developmental pathways. Direct comparisons with previous studies suggest that triazole-gene signatures identified in the WEC overlap with zebrafish and mouse, and furthermore, triazoles impact gene expression in a similar manner as retinoic acid exposures in rat embryos. In summary, we further differentiate pathways underlying triazole-developmental toxicity using WEC and demonstrate the conservation of these response-pathways across model systems. Copyright © 2012 Elsevier Inc. All rights reserved.

Identification of Primary Transcriptional Regulation of Cell Cycle-Regulated Genes upon DNA Damage

PubMed Central

Zhou, Tong; Chou, Jeff; Mullen, Thomas E.; Elkon, Rani; Zhou, Yingchun; Simpson, Dennis A.; Bushel, Pierre R.; Paules, Richard S.; Lobenhofer, Edward K.; Hurban, Patrick; Kaufmann, William K.

2007-01-01

The changes in global gene expression in response to DNA damage may derive from either direct induction or repression by transcriptional regulation or indirectly by synchronization of cells to specific cell cycle phases, such as G1 or G2. We developed a model that successfully estimated the expression levels of >400 cell cycle-regulated genes in normal human fibroblasts based on the proportions of cells in each phase of the cell cycle. By isolating effects on the gene expression associated with the cell cycle phase redistribution after genotoxin treatment, the direct transcriptional target genes were distinguished from genes for which expression changed secondary to cell synchronization. Application of this model to ionizing radiation (IR)-treated normal human fibroblasts identified 150 of 406 cycle-regulated genes as putative direct transcriptional targets of IR-induced DNA damage. Changes in expression of these genes after IR treatment derived from both direct transcriptional regulation and cell cycle synchronization. PMID:17404513

Regional and temporal differences in gene expression of LH(BETA)T(AG) retinoblastoma tumors.

PubMed

Houston, Samuel K; Pina, Yolanda; Clarke, Jennifer; Koru-Sengul, Tulay; Scott, William K; Nathanson, Lubov; Schefler, Amy C; Murray, Timothy G

2011-07-23

The purpose of this study was to evaluate by microarray the hypothesis that LH(BETA)T(AG) retinoblastoma tumors exhibit regional and temporal variations in gene expression. LH(BETA)T(AG) mice aged 12, 16, and 20 weeks were euthanatized (n = 9). Specimens were taken from five tumor areas (apex, anterior lateral, center, base, and posterior lateral). Samples were hybridized to gene microarrays. The data were preprocessed and analyzed, and genes with a P < 0.01, according to the ANOVA models, and a log(2)-fold change >2.5 were considered to be differentially expressed. Differentially expressed genes were analyzed for overlap with known networks by using pathway analysis tools. There were significant temporal (P < 10(-8)) and regional differences in gene expression for LH(BETA)T(AG) retinoblastoma tumors. At P < 0.01 and log(2)-fold change >2.5, there were significant changes in gene expression of 190 genes apically, 84 genes anterolaterally, 126 genes posteriorly, 56 genes centrally, and 134 genes at the base. Differentially expressed genes overlapped with known networks, with significant involvement in regulation of cellular proliferation and growth, response to oxygen levels and hypoxia, regulation of cellular processes, cellular signaling cascades, and angiogenesis. There are significant temporal and regional variations in the LH(BETA)T(AG) retinoblastoma model. Differentially expressed genes overlap with key pathways that may play pivotal roles in murine retinoblastoma development. These findings suggest the mechanisms involved in tumor growth and progression in murine retinoblastoma tumors and identify pathways for analysis at a functional level, to determine significance in human retinoblastoma. Microarray analysis of LH(BETA)T(AG) retinal tumors showed significant regional and temporal variations in gene expression, including dysregulation of genes involved in hypoxic responses and angiogenesis.

Automated Protocol for Large-Scale Modeling of Gene Expression Data.

PubMed

Hall, Michelle Lynn; Calkins, David; Sherman, Woody

2016-11-28

With the continued rise of phenotypic- and genotypic-based screening projects, computational methods to analyze, process, and ultimately make predictions in this field take on growing importance. Here we show how automated machine learning workflows can produce models that are predictive of differential gene expression as a function of a compound structure using data from A673 cells as a proof of principle. In particular, we present predictive models with an average accuracy of greater than 70% across a highly diverse ∼1000 gene expression profile. In contrast to the usual in silico design paradigm, where one interrogates a particular target-based response, this work opens the opportunity for virtual screening and lead optimization for desired multitarget gene expression profiles.

Changes in expression of genes involved in apoptosis in activated human T-cells in response to modeled microgravity

NASA Astrophysics Data System (ADS)

Ward, Nancy E.; Pellis, Neal R.; Risin, Diana; Risin, Semyon A.; Liu, Wenbin

2006-09-01

Space flights result in remarkable effects on various physiological systems, including a decline in cellular immune functions. Previous studies have shown that exposure to microgravity, both true and modeled, can cause significant changes in numerous lymphocyte functions. The purpose of this study was to search for microgravity-sensitive genes, and specifically for apoptotic genes influenced by the microgravity environment and other genes related to immune response. The experiments were performed on anti-CD3 and IL-2 activated human T cells. To model microgravity conditions we have utilized the NASA rotating wall vessel bioreactor. Control lymphocytes were cultured in static 1g conditions. To assess gene expression we used DNA microarray chip technology. We had shown that multiple genes (approximately 3-8% of tested genes) respond to microgravity conditions by 1.5 and more fold change in expression. There is a significant variability in the response. However, a certain reproducible pattern in gene response could be identified. Among the genes showing reproducible changes in expression in modeled microgravity, several genes involved in apoptosis as well as in immune response were identified. These are IL-7 receptor, Granzyme B, Beta-3-endonexin, Apo2 ligand and STAT1. Possible functional consequences of these changes are discussed.

Alpha-fetoprotein-targeted reporter gene expression imaging in hepatocellular carcinoma.

PubMed

Kim, Kwang Il; Chung, Hye Kyung; Park, Ju Hui; Lee, Yong Jin; Kang, Joo Hyun

2016-07-21

Hepatocellular carcinoma (HCC) is one of the most common cancers in Eastern Asia, and its incidence is increasing globally. Numerous experimental models have been developed to better our understanding of the pathogenic mechanism of HCC and to evaluate novel therapeutic approaches. Molecular imaging is a convenient and up-to-date biomedical tool that enables the visualization, characterization and quantification of biologic processes in a living subject. Molecular imaging based on reporter gene expression, in particular, can elucidate tumor-specific events or processes by acquiring images of a reporter gene's expression driven by tumor-specific enhancers/promoters. In this review, we discuss the advantages and disadvantages of various experimental HCC mouse models and we present in vivo images of tumor-specific reporter gene expression driven by an alpha-fetoprotein (AFP) enhancer/promoter system in a mouse model of HCC. The current mouse models of HCC development are established by xenograft, carcinogen induction and genetic engineering, representing the spectrum of tumor-inducing factors and tumor locations. The imaging analysis approach of reporter genes driven by AFP enhancer/promoter is presented for these different HCC mouse models. Such molecular imaging can provide longitudinal information about carcinogenesis and tumor progression. We expect that clinical application of AFP-targeted reporter gene expression imaging systems will be useful for the detection of AFP-expressing HCC tumors and screening of increased/decreased AFP levels due to disease or drug treatment.

Predictive model for inflammation grades of chronic hepatitis B: Large-scale analysis of clinical parameters and gene expressions.

PubMed

Zhou, Weichen; Ma, Yanyun; Zhang, Jun; Hu, Jingyi; Zhang, Menghan; Wang, Yi; Li, Yi; Wu, Lijun; Pan, Yida; Zhang, Yitong; Zhang, Xiaonan; Zhang, Xinxin; Zhang, Zhanqing; Zhang, Jiming; Li, Hai; Lu, Lungen; Jin, Li; Wang, Jiucun; Yuan, Zhenghong; Liu, Jie

2017-11-01

Liver biopsy is the gold standard to assess pathological features (eg inflammation grades) for hepatitis B virus-infected patients although it is invasive and traumatic; meanwhile, several gene profiles of chronic hepatitis B (CHB) have been separately described in relatively small hepatitis B virus (HBV)-infected samples. We aimed to analyse correlations among inflammation grades, gene expressions and clinical parameters (serum alanine amino transaminase, aspartate amino transaminase and HBV-DNA) in large-scale CHB samples and to predict inflammation grades by using clinical parameters and/or gene expressions. We analysed gene expressions with three clinical parameters in 122 CHB samples by an improved regression model. Principal component analysis and machine-learning methods including Random Forest, K-nearest neighbour and support vector machine were used for analysis and further diagnosis models. Six normal samples were conducted to validate the predictive model. Significant genes related to clinical parameters were found enriching in the immune system, interferon-stimulated, regulation of cytokine production, anti-apoptosis, and etc. A panel of these genes with clinical parameters can effectively predict binary classifications of inflammation grade (area under the ROC curve [AUC]: 0.88, 95% confidence interval [CI]: 0.77-0.93), validated by normal samples. A panel with only clinical parameters was also valuable (AUC: 0.78, 95% CI: 0.65-0.86), indicating that liquid biopsy method for detecting the pathology of CHB is possible. This is the first study to systematically elucidate the relationships among gene expressions, clinical parameters and pathological inflammation grades in CHB, and to build models predicting inflammation grades by gene expressions and/or clinical parameters as well. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Gene network reconstruction from transcriptional dynamics under kinetic model uncertainty: a case for the second derivative

PubMed Central

Bickel, David R.; Montazeri, Zahra; Hsieh, Pei-Chun; Beatty, Mary; Lawit, Shai J.; Bate, Nicholas J.

2009-01-01

Motivation: Measurements of gene expression over time enable the reconstruction of transcriptional networks. However, Bayesian networks and many other current reconstruction methods rely on assumptions that conflict with the differential equations that describe transcriptional kinetics. Practical approximations of kinetic models would enable inferring causal relationships between genes from expression data of microarray, tag-based and conventional platforms, but conclusions are sensitive to the assumptions made. Results: The representation of a sufficiently large portion of genome enables computation of an upper bound on how much confidence one may place in influences between genes on the basis of expression data. Information about which genes encode transcription factors is not necessary but may be incorporated if available. The methodology is generalized to cover cases in which expression measurements are missing for many of the genes that might control the transcription of the genes of interest. The assumption that the gene expression level is roughly proportional to the rate of translation led to better empirical performance than did either the assumption that the gene expression level is roughly proportional to the protein level or the Bayesian model average of both assumptions. Availability: http://www.oisb.ca points to R code implementing the methods (R Development Core Team 2004). Contact: dbickel@uottawa.ca Supplementary information: http://www.davidbickel.com PMID:19218351

Modeling T-cell activation using gene expression profiling and state-space models.

PubMed

Rangel, Claudia; Angus, John; Ghahramani, Zoubin; Lioumi, Maria; Sotheran, Elizabeth; Gaiba, Alessia; Wild, David L; Falciani, Francesco

2004-06-12

We have used state-space models to reverse engineer transcriptional networks from highly replicated gene expression profiling time series data obtained from a well-established model of T-cell activation. State space models are a class of dynamic Bayesian networks that assume that the observed measurements depend on some hidden state variables that evolve according to Markovian dynamics. These hidden variables can capture effects that cannot be measured in a gene expression profiling experiment, e.g. genes that have not been included in the microarray, levels of regulatory proteins, the effects of messenger RNA and protein degradation, etc. Bootstrap confidence intervals are developed for parameters representing 'gene-gene' interactions over time. Our models represent the dynamics of T-cell activation and provide a methodology for the development of rational and experimentally testable hypotheses. Supplementary data and Matlab computer source code will be made available on the web at the URL given below. http://public.kgi.edu/~wild/LDS/index.htm

A statistical approach to identify, monitor, and manage incomplete curated data sets.

PubMed

Howe, Douglas G

2018-04-02

Many biological knowledge bases gather data through expert curation of published literature. High data volume, selective partial curation, delays in access, and publication of data prior to the ability to curate it can result in incomplete curation of published data. Knowing which data sets are incomplete and how incomplete they are remains a challenge. Awareness that a data set may be incomplete is important for proper interpretation, to avoiding flawed hypothesis generation, and can justify further exploration of published literature for additional relevant data. Computational methods to assess data set completeness are needed. One such method is presented here. In this work, a multivariate linear regression model was used to identify genes in the Zebrafish Information Network (ZFIN) Database having incomplete curated gene expression data sets. Starting with 36,655 gene records from ZFIN, data aggregation, cleansing, and filtering reduced the set to 9870 gene records suitable for training and testing the model to predict the number of expression experiments per gene. Feature engineering and selection identified the following predictive variables: the number of journal publications; the number of journal publications already attributed for gene expression annotation; the percent of journal publications already attributed for expression data; the gene symbol; and the number of transgenic constructs associated with each gene. Twenty-five percent of the gene records (2483 genes) were used to train the model. The remaining 7387 genes were used to test the model. One hundred and twenty-two and 165 of the 7387 tested genes were identified as missing expression annotations based on their residuals being outside the model lower or upper 95% confidence interval respectively. The model had precision of 0.97 and recall of 0.71 at the negative 95% confidence interval and precision of 0.76 and recall of 0.73 at the positive 95% confidence interval. This method can be used to identify data sets that are incompletely curated, as demonstrated using the gene expression data set from ZFIN. This information can help both database resources and data consumers gauge when it may be useful to look further for published data to augment the existing expertly curated information.

Commonly dysregulated genes in murine APL cells

PubMed Central

Yuan, Wenlin; Payton, Jacqueline E.; Holt, Matthew S.; Link, Daniel C.; Watson, Mark A.; DiPersio, John F.; Ley, Timothy J.

2007-01-01

To identify genes that are commonly dysregulated in a murine model of acute promyelocytic leukemia (APL), we first defined gene expression patterns during normal murine myeloid development; serial gene expression profiling studies were performed with primary murine hematopoietic progenitors that were induced to undergo myeloid maturation in vitro with G-CSF. Many genes were reproducibly expressed in restricted developmental “windows,” suggesting a structured hierarchy of expression that is relevant for the induction of developmental fates and/or differentiated cell functions. We compared the normal myeloid developmental transcriptome with that of APL cells derived from mice expressing PML-RARα under control of the murine cathepsin G locus. While many promyelocyte-specific genes were highly expressed in all APL samples, 116 genes were reproducibly dysregulated in many independent APL samples, including Fos, Jun, Egr1, Tnf, and Vcam1. However, this set of commonly dysregulated genes was expressed normally in preleukemic, early myeloid cells from the same mouse model, suggesting that dysregulation occurs as a “downstream” event during disease progression. These studies suggest that the genetic events that lead to APL progression may converge on common pathways that are important for leukemia pathogenesis. PMID:17008535

At-TAX: a whole genome tiling array resource for developmental expression analysis and transcript identification in Arabidopsis thaliana

PubMed Central

Laubinger, Sascha; Zeller, Georg; Henz, Stefan R; Sachsenberg, Timo; Widmer, Christian K; Naouar, Naïra; Vuylsteke, Marnik; Schölkopf, Bernhard; Rätsch, Gunnar; Weigel, Detlef

2008-01-01

Gene expression maps for model organisms, including Arabidopsis thaliana, have typically been created using gene-centric expression arrays. Here, we describe a comprehensive expression atlas, Arabidopsis thaliana Tiling Array Express (At-TAX), which is based on whole-genome tiling arrays. We demonstrate that tiling arrays are accurate tools for gene expression analysis and identified more than 1,000 unannotated transcribed regions. Visualizations of gene expression estimates, transcribed regions, and tiling probe measurements are accessible online at the At-TAX homepage. PMID:18613972

Development of a transgenic zebrafish model expressing GFP in the notochord, somite and liver directed by the hfe2 gene promoter.

PubMed

Bian, Yue-Hong; Xu, Cheng; Li, Junling; Xu, Jin; Zhang, Hongwei; Du, Shao Jun

2011-08-01

Hemojuvelin, also known as RGMc, is encoded by hfe2 gene that plays an important role in iron homeostasis. hfe2 is specifically expressed in the notochord, developing somite and skeletal muscles during development. The molecular regulation of hfe2 expression is, however, not clear. We reported here the characterization of hfe2 gene expression and the regulation of its tissue-specific expression in zebrafish embryos. We demonstrated that the 6 kb 5'-flanking sequence upstream of the ATG start codon in the zebrafish hfe2 gene could direct GFP specific expression in the notochord, somites, and skeletal muscle of zebrafish embryos, recapitulating the expression pattern of the endogenous gene. However, the Tg(hfe2:gfp) transgene is also expressed in the liver of fish embryos, which did not mimic the expression of the endogenous hfe2 at the early stage. Nevertheless, the Tg(hfe2:gfp) transgenic zebrafish provides a useful model to study liver development. Treating Tg(hfe2:gfp) transgenic zebrafish embryos with valproic acid, a liver development inhibitor, significantly inhibited GFP expression in zebrafish. Together, these data indicate that the tissue specific expression of hfe2 in the notochord, somites and muscles is regulated by regulatory elements within the 6 kb 5'-flanking sequence of the hfe2 gene. Moreover, the Tg(hfe2:gfp) transgenic zebrafish line provides a useful model system for analyzing liver development in zebrafish.

Characterization of human septic sera induced gene expression modulation in human myocytes

PubMed Central

Hussein, Shaimaa; Michael, Paul; Brabant, Danielle; Omri, Abdelwahab; Narain, Ravin; Passi, Kalpdrum; Ramana, Chilakamarti V.; Parrillo, Joseph E.; Kumar, Anand; Parissenti, Amadeo; Kumar, Aseem

2009-01-01

To gain a better understanding of the gene expression changes that occurs during sepsis, we have performed a cDNA microarray study utilizing a tissue culture model that mimics human sepsis. This study utilized an in vitro model of cultured human fetal cardiac myocytes treated with 10% sera from septic patients or 10% sera from healthy volunteers. A 1700 cDNA expression microarray was used to compare the transcription profile from human cardiac myocytes treated with septic sera vs normal sera. Septic sera treatment of myocytes resulted in the down-regulation of 178 genes and the up-regulation of 4 genes. Our data indicate that septic sera induced cell cycle, metabolic, transcription factor and apoptotic gene expression changes in human myocytes. Identification and characterization of gene expression changes that occur during sepsis may lead to the development of novel therapeutics and diagnostics. PMID:19684886

Gene expression profile of mouse prostate tumors reveals dysregulations in major biological processes and identifies potential murine targets for preclinical development of human prostate cancer therapy.

PubMed

Haram, Kerstyn M; Peltier, Heidi J; Lu, Bin; Bhasin, Manoj; Otu, Hasan H; Choy, Bob; Regan, Meredith; Libermann, Towia A; Latham, Gary J; Sanda, Martin G; Arredouani, Mohamed S

2008-10-01

Translation of preclinical studies into effective human cancer therapy is hampered by the lack of defined molecular expression patterns in mouse models that correspond to the human counterpart. We sought to generate an open source TRAMP mouse microarray dataset and to use this array to identify differentially expressed genes from human prostate cancer (PCa) that have concordant expression in TRAMP tumors, and thereby represent lead targets for preclinical therapy development. We performed microarrays on total RNA extracted and amplified from eight TRAMP tumors and nine normal prostates. A subset of differentially expressed genes was validated by QRT-PCR. Differentially expressed TRAMP genes were analyzed for concordant expression in publicly available human prostate array datasets and a subset of resulting genes was analyzed by QRT-PCR. Cross-referencing differentially expressed TRAMP genes to public human prostate array datasets revealed 66 genes with concordant expression in mouse and human PCa; 56 between metastases and normal and 10 between primary tumor and normal tissues. Of these 10 genes, two, Sox4 and Tubb2a, were validated by QRT-PCR. Our analysis also revealed various dysregulations in major biologic pathways in the TRAMP prostates. We report a TRAMP microarray dataset of which a gene subset was validated by QRT-PCR with expression patterns consistent with previous gene-specific TRAMP studies. Concordance analysis between TRAMP and human PCa associated genes supports the utility of the model and suggests several novel molecular targets for preclinical therapy.

Improving RNA-Seq expression estimation by modeling isoform- and exon-specific read sequencing rate.

PubMed

Liu, Xuejun; Shi, Xinxin; Chen, Chunlin; Zhang, Li

2015-10-16

The high-throughput sequencing technology, RNA-Seq, has been widely used to quantify gene and isoform expression in the study of transcriptome in recent years. Accurate expression measurement from the millions or billions of short generated reads is obstructed by difficulties. One is ambiguous mapping of reads to reference transcriptome caused by alternative splicing. This increases the uncertainty in estimating isoform expression. The other is non-uniformity of read distribution along the reference transcriptome due to positional, sequencing, mappability and other undiscovered sources of biases. This violates the uniform assumption of read distribution for many expression calculation approaches, such as the direct RPKM calculation and Poisson-based models. Many methods have been proposed to address these difficulties. Some approaches employ latent variable models to discover the underlying pattern of read sequencing. However, most of these methods make bias correction based on surrounding sequence contents and share the bias models by all genes. They therefore cannot estimate gene- and isoform-specific biases as revealed by recent studies. We propose a latent variable model, NLDMseq, to estimate gene and isoform expression. Our method adopts latent variables to model the unknown isoforms, from which reads originate, and the underlying percentage of multiple spliced variants. The isoform- and exon-specific read sequencing biases are modeled to account for the non-uniformity of read distribution, and are identified by utilizing the replicate information of multiple lanes of a single library run. We employ simulation and real data to verify the performance of our method in terms of accuracy in the calculation of gene and isoform expression. Results show that NLDMseq obtains competitive gene and isoform expression compared to popular alternatives. Finally, the proposed method is applied to the detection of differential expression (DE) to show its usefulness in the downstream analysis. The proposed NLDMseq method provides an approach to accurately estimate gene and isoform expression from RNA-Seq data by modeling the isoform- and exon-specific read sequencing biases. It makes use of a latent variable model to discover the hidden pattern of read sequencing. We have shown that it works well in both simulations and real datasets, and has competitive performance compared to popular methods. The method has been implemented as a freely available software which can be found at https://github.com/PUGEA/NLDMseq.

Evaluation of phenoxybenzamine in the CFA model of pain following gene expression studies and connectivity mapping.

PubMed

Chang, Meiping; Smith, Sarah; Thorpe, Andrew; Barratt, Michael J; Karim, Farzana

2010-09-16

We have previously used the rat 4 day Complete Freund's Adjuvant (CFA) model to screen compounds with potential to reduce osteoarthritic pain. The aim of this study was to identify genes altered in this model of osteoarthritic pain and use this information to infer analgesic potential of compounds based on their own gene expression profiles using the Connectivity Map approach. Using microarrays, we identified differentially expressed genes in L4 and L5 dorsal root ganglia (DRG) from rats that had received intraplantar CFA for 4 days compared to matched, untreated control animals. Analysis of these data indicated that the two groups were distinguishable by differences in genes important in immune responses, nerve growth and regeneration. This list of differentially expressed genes defined a "CFA signature". We used the Connectivity Map approach to identify pharmacologic agents in the Broad Institute Build02 database that had gene expression signatures that were inversely related ('negatively connected') with our CFA signature. To test the predictive nature of the Connectivity Map methodology, we tested phenoxybenzamine (an alpha adrenergic receptor antagonist) - one of the most negatively connected compounds identified in this database - for analgesic activity in the CFA model. Our results indicate that at 10 mg/kg, phenoxybenzamine demonstrated analgesia comparable to that of Naproxen in this model. Evaluation of phenoxybenzamine-induced analgesia in the current study lends support to the utility of the Connectivity Map approach for identifying compounds with analgesic properties in the CFA model.

Strong Correlation of Genome-Wide Expression after Traumatic Brain Injury In Vitro and In Vivo Implicates a Role for SORLA

PubMed Central

Lamprecht, Michael R.; Elkin, Benjamin S.; Kesavabhotla, Kartik; Crary, John F.; Hammers, Jennifer L.; Huh, Jimmy W.; Raghupathi, Ramesh

2017-01-01

Abstract The utility of in vitro models of traumatic brain injury (TBI) depends on their ability to recapitulate the in vivo TBI cascade. In this study, we used a genome-wide approach to compare changes in gene expression at several time points post-injury in both an in vitro model and an in vivo model of TBI. We found a total of 2073 differentially expressed genes in our in vitro model and 877 differentially expressed genes in our in vivo model when compared to noninjured controls. We found a strong correlation in gene expression changes between the two models (r = 0.69), providing confidence that the in vitro model represented at least part of the in vivo injury cascade. From these data, we searched for genes with significant changes in expression over time (analysis of covariance) and identified sorting protein-related receptor with A-type repeats (SORLA). SORLA directs amyloid precursor protein to the recycling pathway by direct binding and away from amyloid-beta producing enzymes. Mutations of SORLA have been linked to Alzheimer's disease (AD). We confirmed downregulation of SORLA expression in organotypic hippocampal slice cultures by immunohistochemistry and Western blotting and present preliminary data from human tissue that is consistent with these experimental results. Together, these data suggest that the in vitro model of TBI used in this study strongly recapitulates the in vivo TBI pathobiology and is well suited for future mechanistic or therapeutic studies. The data also suggest the possible involvement of SORLA in the post-traumatic cascade linking TBI to AD. PMID:26919808

A high resolution atlas of gene expression in the domestic sheep (Ovis aries)

PubMed Central

Farquhar, Iseabail L.; Young, Rachel; Lefevre, Lucas; Pridans, Clare; Tsang, Hiu G.; Afrasiabi, Cyrus; Watson, Mick; Whitelaw, C. Bruce; Freeman, Tom C.; Archibald, Alan L.; Hume, David A.

2017-01-01

Sheep are a key source of meat, milk and fibre for the global livestock sector, and an important biomedical model. Global analysis of gene expression across multiple tissues has aided genome annotation and supported functional annotation of mammalian genes. We present a large-scale RNA-Seq dataset representing all the major organ systems from adult sheep and from several juvenile, neonatal and prenatal developmental time points. The Ovis aries reference genome (Oar v3.1) includes 27,504 genes (20,921 protein coding), of which 25,350 (19,921 protein coding) had detectable expression in at least one tissue in the sheep gene expression atlas dataset. Network-based cluster analysis of this dataset grouped genes according to their expression pattern. The principle of ‘guilt by association’ was used to infer the function of uncharacterised genes from their co-expression with genes of known function. We describe the overall transcriptional signatures present in the sheep gene expression atlas and assign those signatures, where possible, to specific cell populations or pathways. The findings are related to innate immunity by focusing on clusters with an immune signature, and to the advantages of cross-breeding by examining the patterns of genes exhibiting the greatest expression differences between purebred and crossbred animals. This high-resolution gene expression atlas for sheep is, to our knowledge, the largest transcriptomic dataset from any livestock species to date. It provides a resource to improve the annotation of the current reference genome for sheep, presenting a model transcriptome for ruminants and insight into gene, cell and tissue function at multiple developmental stages. PMID:28915238

A high resolution atlas of gene expression in the domestic sheep (Ovis aries).

PubMed

Clark, Emily L; Bush, Stephen J; McCulloch, Mary E B; Farquhar, Iseabail L; Young, Rachel; Lefevre, Lucas; Pridans, Clare; Tsang, Hiu G; Wu, Chunlei; Afrasiabi, Cyrus; Watson, Mick; Whitelaw, C Bruce; Freeman, Tom C; Summers, Kim M; Archibald, Alan L; Hume, David A

2017-09-01

Sheep are a key source of meat, milk and fibre for the global livestock sector, and an important biomedical model. Global analysis of gene expression across multiple tissues has aided genome annotation and supported functional annotation of mammalian genes. We present a large-scale RNA-Seq dataset representing all the major organ systems from adult sheep and from several juvenile, neonatal and prenatal developmental time points. The Ovis aries reference genome (Oar v3.1) includes 27,504 genes (20,921 protein coding), of which 25,350 (19,921 protein coding) had detectable expression in at least one tissue in the sheep gene expression atlas dataset. Network-based cluster analysis of this dataset grouped genes according to their expression pattern. The principle of 'guilt by association' was used to infer the function of uncharacterised genes from their co-expression with genes of known function. We describe the overall transcriptional signatures present in the sheep gene expression atlas and assign those signatures, where possible, to specific cell populations or pathways. The findings are related to innate immunity by focusing on clusters with an immune signature, and to the advantages of cross-breeding by examining the patterns of genes exhibiting the greatest expression differences between purebred and crossbred animals. This high-resolution gene expression atlas for sheep is, to our knowledge, the largest transcriptomic dataset from any livestock species to date. It provides a resource to improve the annotation of the current reference genome for sheep, presenting a model transcriptome for ruminants and insight into gene, cell and tissue function at multiple developmental stages.

Using deep RNA sequencing for the structural annotation of the laccaria bicolor mycorrhizal transcriptome.

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

Larsen, P. E.; Trivedi, G.; Sreedasyam, A.

2010-07-06

Accurate structural annotation is important for prediction of function and required for in vitro approaches to characterize or validate the gene expression products. Despite significant efforts in the field, determination of the gene structure from genomic data alone is a challenging and inaccurate process. The ease of acquisition of transcriptomic sequence provides a direct route to identify expressed sequences and determine the correct gene structure. We developed methods to utilize RNA-seq data to correct errors in the structural annotation and extend the boundaries of current gene models using assembly approaches. The methods were validated with a transcriptomic data set derivedmore » from the fungus Laccaria bicolor, which develops a mycorrhizal symbiotic association with the roots of many tree species. Our analysis focused on the subset of 1501 gene models that are differentially expressed in the free living vs. mycorrhizal transcriptome and are expected to be important elements related to carbon metabolism, membrane permeability and transport, and intracellular signaling. Of the set of 1501 gene models, 1439 (96%) successfully generated modified gene models in which all error flags were successfully resolved and the sequences aligned to the genomic sequence. The remaining 4% (62 gene models) either had deviations from transcriptomic data that could not be spanned or generated sequence that did not align to genomic sequence. The outcome of this process is a set of high confidence gene models that can be reliably used for experimental characterization of protein function. 69% of expressed mycorrhizal JGI 'best' gene models deviated from the transcript sequence derived by this method. The transcriptomic sequence enabled correction of a majority of the structural inconsistencies and resulted in a set of validated models for 96% of the mycorrhizal genes. The method described here can be applied to improve gene structural annotation in other species, provided that there is a sequenced genome and a set of gene models.« less

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.

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

An integrative systems genetics approach reveals potential causal genes and pathways related to obesity.

PubMed

Kogelman, Lisette J A; Zhernakova, Daria V; Westra, Harm-Jan; Cirera, Susanna; Fredholm, Merete; Franke, Lude; Kadarmideen, Haja N

2015-10-20

Obesity is a multi-factorial health problem in which genetic factors play an important role. Limited results have been obtained in single-gene studies using either genomic or transcriptomic data. RNA sequencing technology has shown its potential in gaining accurate knowledge about the transcriptome, and may reveal novel genes affecting complex diseases. Integration of genomic and transcriptomic variation (expression quantitative trait loci [eQTL] mapping) has identified causal variants that affect complex diseases. We integrated transcriptomic data from adipose tissue and genomic data from a porcine model to investigate the mechanisms involved in obesity using a systems genetics approach. Using a selective gene expression profiling approach, we selected 36 animals based on a previously created genomic Obesity Index for RNA sequencing of subcutaneous adipose tissue. Differential expression analysis was performed using the Obesity Index as a continuous variable in a linear model. eQTL mapping was then performed to integrate 60 K porcine SNP chip data with the RNA sequencing data. Results were restricted based on genome-wide significant single nucleotide polymorphisms, detected differentially expressed genes, and previously detected co-expressed gene modules. Further data integration was performed by detecting co-expression patterns among eQTLs and integration with protein data. Differential expression analysis of RNA sequencing data revealed 458 differentially expressed genes. The eQTL mapping resulted in 987 cis-eQTLs and 73 trans-eQTLs (false discovery rate < 0.05), of which the cis-eQTLs were associated with metabolic pathways. We reduced the eQTL search space by focusing on differentially expressed and co-expressed genes and disease-associated single nucleotide polymorphisms to detect obesity-related genes and pathways. Building a co-expression network using eQTLs resulted in the detection of a module strongly associated with lipid pathways. Furthermore, we detected several obesity candidate genes, for example, ENPP1, CTSL, and ABHD12B. To our knowledge, this is the first study to perform an integrated genomics and transcriptomics (eQTL) study using, and modeling, genomic and subcutaneous adipose tissue RNA sequencing data on obesity in a porcine model. We detected several pathways and potential causal genes for obesity. Further validation and investigation may reveal their exact function and association with obesity.

Use of transcriptomic data for extending a model of the AppA/PpsR system in Rhodobacter sphaeroides.

PubMed

Pandey, Rakesh; Armitage, Judith P; Wadhams, George H

2017-12-28

Photosynthetic (PS) gene expression in Rhodobacter sphaeroides is regulated in response to changes in light and redox conditions mainly by PrrB/A, FnrL and AppA/PpsR systems. The PrrB/A and FnrL systems activate the expression of them under anaerobic conditions while the AppA/PpsR system represses them under aerobic conditions. Recently, two mathematical models have been developed for the AppA/PpsR system and demonstrated how the interaction between AppA and PpsR could lead to a phenotype in which PS genes are repressed under semi-aerobic conditions. These models have also predicted that the transition from aerobic to anaerobic growth mode could occur via a bistable regime. However, they lack experimentally quantifiable inputs and outputs. Here, we extend one of them to include such quantities and combine all relevant micro-array data publically available for a PS gene of this bacterium and use that to parameterise the model. In addition, we hypothesise that the AppA/PpsR system alone might account for the observed trend of PS gene expression under semi-aerobic conditions. Our extended model of the AppA/PpsR system includes the biological input of atmospheric oxygen concentration and an output of photosynthetic gene expression. Following our hypothesis that the AppA/PpsR system alone is sufficient to describe the overall trend of PS gene expression we parameterise the model and suggest that the rate of AppA reduction in vivo should be faster than its oxidation. Also, we show that despite both the reduced and oxidised forms of PpsR binding to the PS gene promoters in vitro, binding of the oxidised form as a repressor alone is sufficient to reproduce the observed PS gene expression pattern. Finally, the combination of model parameters which fit the biological data well are broadly consistent with those which were previously determined to be required for the system to show (i) the repression of PS genes under semi-aerobic conditions, and (ii) bistability. We found that despite at least three pathways being involved in the regulation of photosynthetic genes, the AppA/PpsR system alone is capable of accounting for the observed trends in photosynthetic gene expression seen at different oxygen levels.

Molecular Structure-Based Large-Scale Prediction of Chemical-Induced Gene Expression Changes.

PubMed

Liu, Ruifeng; AbdulHameed, Mohamed Diwan M; Wallqvist, Anders

2017-09-25

The quantitative structure-activity relationship (QSAR) approach has been used to model a wide range of chemical-induced biological responses. However, it had not been utilized to model chemical-induced genomewide gene expression changes until very recently, owing to the complexity of training and evaluating a very large number of models. To address this issue, we examined the performance of a variable nearest neighbor (v-NN) method that uses information on near neighbors conforming to the principle that similar structures have similar activities. Using a data set of gene expression signatures of 13 150 compounds derived from cell-based measurements in the NIH Library of Integrated Network-based Cellular Signatures program, we were able to make predictions for 62% of the compounds in a 10-fold cross validation test, with a correlation coefficient of 0.61 between the predicted and experimentally derived signatures-a reproducibility rivaling that of high-throughput gene expression measurements. To evaluate the utility of the predicted gene expression signatures, we compared the predicted and experimentally derived signatures in their ability to identify drugs known to cause specific liver, kidney, and heart injuries. Overall, the predicted and experimentally derived signatures had similar receiver operating characteristics, whose areas under the curve ranged from 0.71 to 0.77 and 0.70 to 0.73, respectively, across the three organ injury models. However, detailed analyses of enrichment curves indicate that signatures predicted from multiple near neighbors outperformed those derived from experiments, suggesting that averaging information from near neighbors may help improve the signal from gene expression measurements. Our results demonstrate that the v-NN method can serve as a practical approach for modeling large-scale, genomewide, chemical-induced, gene expression changes.

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

Public data mining plus domestic experimental study defined involvement of the old-yet-uncharacterized gene matrix-remodeling associated 7 (MXRA7) in physiopathology of the eye.

PubMed

Jia, Changkai; Zhang, Feng; Zhu, Ying; Qi, Xia; Wang, Yiqiang

2017-10-20

Matrix-remodeling associated 7 (MXRA7) gene was first reported in 2002 and named so for its co-expression with several genes known to relate with matrix-remodeling. However, not any studies had been intentionally performed to characterize this gene. We started defining the functions of MXRA7 by integrating bioinformatics analysis and experimental study. Data mining of MXRA7 expression in BioGPS, Gene Expression Omnibus and EurExpress platforms highlighted high level expression of Mxra7 in murine ocular tissues. Real-time PCR was employed to measure Mxra7 mRNA in tissues of adult C57BL/6 mice and demonstrated that Mxra7 was preferentially expressed at higher level in retina, corneas and lens than in other tissues. Then the inflammatory corneal neovascularization (CorNV) model and fungal corneal infections were induced in Balb/c mice, and mRNA levels of Mxra7 as well as several matrix-remodeling related genes (Mmp3, Mmp13, Ecm1, Timp1) were monitored with RT-PCR. The results demonstrated a time-dependent Mxra7 under-expression pattern (U-shape curve along timeline), while all other matrix-remodeling related genes manifested an opposite changes pattern (dome-shape curve). When limited data from BioGPS concerning human MXRA7 gene expression in human tissues were looked at, it was found that ocular tissue was also the one expressing highest level of MXRA7. To conclude, integrative assay of MXRA7 gene expression in public databank as well as domestic animal models revealed a selective high expression MXRA7 in murine and human ocular tissues, and its change patterns in two corneal disease models implied that MXRA7 might play a role in pathological processes or diseases involving injury, neovascularization and would healing. Copyright © 2017 Elsevier B.V. All rights reserved.

Identification of a new peptide deformylase gene from enterococcus faecium and establishment of a new screening model targeted on PDF for novel antibiotics.

PubMed

Tang, Xian-Bing; Si, Shu-Yi; Zhang, Yue-Qin

2004-09-01

To identify a new peptide deformylase (PDF) gene (Genebank Accession AY238515) from Enterococcus faecium and to establish a new screening model targeted on PDF. A new PDF gene was identified by BLAST analysis and PCR and was subsequently over-expressed in the prokaryotic expression host E. coli B121(DE3). Over-expressed protein was purified for enzymatic assay by metal affinity chromatography and a new screening model was established for novel antibiotics. A new PDF gene of Enterococcus faecium was identified successfully. Ten positive samples were picked up from 8000 compound library and the microbial fermentation broth samples. A new PDF of gene Enterococcus faecium was first identified and the model had a high efficacy. Positive samples screened may be antibacterial agents of broad spectrum.

Models of stochastic gene expression

NASA Astrophysics Data System (ADS)

Paulsson, Johan

2005-06-01

Gene expression is an inherently stochastic process: Genes are activated and inactivated by random association and dissociation events, transcription is typically rare, and many proteins are present in low numbers per cell. The last few years have seen an explosion in the stochastic modeling of these processes, predicting protein fluctuations in terms of the frequencies of the probabilistic events. Here I discuss commonalities between theoretical descriptions, focusing on a gene-mRNA-protein model that includes most published studies as special cases. I also show how expression bursts can be explained as simplistic time-averaging, and how generic approximations can allow for concrete interpretations without requiring concrete assumptions. Measures and nomenclature are discussed to some extent and the modeling literature is briefly reviewed.

Analysis of host response to bacterial infection using error model based gene expression microarray experiments

PubMed Central

Stekel, Dov J.; Sarti, Donatella; Trevino, Victor; Zhang, Lihong; Salmon, Mike; Buckley, Chris D.; Stevens, Mark; Pallen, Mark J.; Penn, Charles; Falciani, Francesco

2005-01-01

A key step in the analysis of microarray data is the selection of genes that are differentially expressed. Ideally, such experiments should be properly replicated in order to infer both technical and biological variability, and the data should be subjected to rigorous hypothesis tests to identify the differentially expressed genes. However, in microarray experiments involving the analysis of very large numbers of biological samples, replication is not always practical. Therefore, there is a need for a method to select differentially expressed genes in a rational way from insufficiently replicated data. In this paper, we describe a simple method that uses bootstrapping to generate an error model from a replicated pilot study that can be used to identify differentially expressed genes in subsequent large-scale studies on the same platform, but in which there may be no replicated arrays. The method builds a stratified error model that includes array-to-array variability, feature-to-feature variability and the dependence of error on signal intensity. We apply this model to the characterization of the host response in a model of bacterial infection of human intestinal epithelial cells. We demonstrate the effectiveness of error model based microarray experiments and propose this as a general strategy for a microarray-based screening of large collections of biological samples. PMID:15800204

Modulation of Immune Signaling and Metabolism Highlights Host and Fungal Transcriptional Responses in Mouse Models of Invasive Pulmonary Aspergillosis.

PubMed

Kale, Shiv D; Ayubi, Tariq; Chung, Dawoon; Tubau-Juni, Nuria; Leber, Andrew; Dang, Ha X; Karyala, Saikumar; Hontecillas, Raquel; Lawrence, Christopher B; Cramer, Robert A; Bassaganya-Riera, Josep

2017-12-06

Incidences of invasive pulmonary aspergillosis, an infection caused predominantly by Aspergillus fumigatus, have increased due to the growing number of immunocompromised individuals. While A. fumigatus is reliant upon deficiencies in the host to facilitate invasive disease, the distinct mechanisms that govern the host-pathogen interaction remain enigmatic, particularly in the context of distinct immune modulating therapies. To gain insights into these mechanisms, RNA-Seq technology was utilized to sequence RNA derived from lungs of 2 clinically relevant, but immunologically distinct murine models of IPA on days 2 and 3 post inoculation when infection is established and active disease present. Our findings identify notable differences in host gene expression between the chemotherapeutic and steroid models at the interface of immunity and metabolism. RT-qPCR verified model specific and nonspecific expression of 23 immune-associated genes. Deep sequencing facilitated identification of highly expressed fungal genes. We utilized sequence similarity and gene expression to categorize the A. fumigatus putative in vivo secretome. RT-qPCR suggests model specific gene expression for nine putative fungal secreted proteins. Our analysis identifies contrasting responses by the host and fungus from day 2 to 3 between the two models. These differences may help tailor the identification, development, and deployment of host- and/or fungal-targeted therapeutics.

Multiple fuzzy neural network system for outcome prediction and classification of 220 lymphoma patients on the basis of molecular profiling.

PubMed

Ando, Tatsuya; Suguro, Miyuki; Kobayashi, Takeshi; Seto, Masao; Honda, Hiroyuki

2003-10-01

A fuzzy neural network (FNN) using gene expression profile data can select combinations of genes from thousands of genes, and is applicable to predict outcome for cancer patients after chemotherapy. However, wide clinical heterogeneity reduces the accuracy of prediction. To overcome this problem, we have proposed an FNN system based on majoritarian decision using multiple noninferior models. We used transcriptional profiling data, which were obtained from "Lymphochip" DNA microarrays (http://llmpp.nih.gov/DLBCL), reported by Rosenwald (N Engl J Med 2002; 346: 1937-47). When the data were analyzed by our FNN system, accuracy (73.4%) of outcome prediction using only 1 FNN model with 4 genes was higher than that (68.5%) of the Cox model using 17 genes. Higher accuracy (91%) was obtained when an FNN system with 9 noninferior models, consisting of 35 independent genes, was used. The genes selected by the system included genes that are informative in the prognosis of Diffuse large B-cell lymphoma (DLBCL), such as genes showing an expression pattern similar to that of CD10 and BCL-6 or similar to that of IRF-4 and BCL-4. We classified 220 DLBCL patients into 5 groups using the prediction results of 9 FNN models. These groups may correspond to DLBCL subtypes. In group A containing half of the 220 patients, patients with poor outcome were found to satisfy 2 rules, i.e., high expression of MAX dimerization with high expression of unknown A (LC_26146), or high expression of MAX dimerization with low expression of unknown B (LC_33144). The present paper is the first to describe the multiple noninferior FNN modeling system. This system is a powerful tool for predicting outcome and classifying patients, and is applicable to other heterogeneous diseases.

Survey of the Heritability and Sparse Architecture of Gene Expression Traits across Human Tissues.

PubMed

Wheeler, Heather E; Shah, Kaanan P; Brenner, Jonathon; Garcia, Tzintzuni; Aquino-Michaels, Keston; Cox, Nancy J; Nicolae, Dan L; Im, Hae Kyung

2016-11-01

Understanding the genetic architecture of gene expression traits is key to elucidating the underlying mechanisms of complex traits. Here, for the first time, we perform a systematic survey of the heritability and the distribution of effect sizes across all representative tissues in the human body. We find that local h2 can be relatively well characterized with 59% of expressed genes showing significant h2 (FDR < 0.1) in the DGN whole blood cohort. However, current sample sizes (n ≤ 922) do not allow us to compute distal h2. Bayesian Sparse Linear Mixed Model (BSLMM) analysis provides strong evidence that the genetic contribution to local expression traits is dominated by a handful of genetic variants rather than by the collective contribution of a large number of variants each of modest size. In other words, the local architecture of gene expression traits is sparse rather than polygenic across all 40 tissues (from DGN and GTEx) examined. This result is confirmed by the sparsity of optimal performing gene expression predictors via elastic net modeling. To further explore the tissue context specificity, we decompose the expression traits into cross-tissue and tissue-specific components using a novel Orthogonal Tissue Decomposition (OTD) approach. Through a series of simulations we show that the cross-tissue and tissue-specific components are identifiable via OTD. Heritability and sparsity estimates of these derived expression phenotypes show similar characteristics to the original traits. Consistent properties relative to prior GTEx multi-tissue analysis results suggest that these traits reflect the expected biology. Finally, we apply this knowledge to develop prediction models of gene expression traits for all tissues. The prediction models, heritability, and prediction performance R2 for original and decomposed expression phenotypes are made publicly available (https://github.com/hakyimlab/PrediXcan).

RT-PCR detection of Candida albicans ALS gene expression in the reconstituted human epithelium (RHE) model of oral candidiasis and in model biofilms.

PubMed

Green, Clayton B; Cheng, Georgina; Chandra, Jyotsna; Mukherjee, Pranab; Ghannoum, Mahmoud A; Hoyer, Lois L

2004-02-01

An RT-PCR assay was developed to analyse expression patterns of genes in the Candida albicans ALS (agglutinin-like sequence) family. Inoculation of a reconstituted human buccal epithelium (RHE) model of mucocutaneous candidiasis with strain SC5314 showed destruction of the epithelial layer by C. albicans and also formation of an upper fungal layer that had characteristics similar to a biofilm. RT-PCR analysis of total RNA samples extracted from C. albicans-inoculated buccal RHE showed that ALS1, ALS2, ALS3, ALS4, ALS5 and ALS9 were consistently detected over time as destruction of the RHE progressed. Detection of transcripts from ALS7, and particularly from ALS6, was more sporadic, but not associated with a strictly temporal pattern. The expression pattern of ALS genes in C. albicans cultures used to inoculate the RHE was similar to that observed in the RHE model, suggesting that contact of C. albicans with buccal RHE does little to alter ALS gene expression. RT-PCR analysis of RNA samples extracted from model denture and catheter biofilms showed similar gene expression patterns to the buccal RHE specimens. Results from the RT-PCR analysis of biofilm RNA specimens were consistent between various C. albicans strains during biofilm development and were comparable to gene expression patterns in planktonic cells. The RT-PCR assay described here will be useful for analysis of human clinical specimens and samples from other disease models. The method will provide further insight into the role of ALS genes and their encoded proteins in the diverse interactions between C. albicans and its host.

Assessing differential gene expression with small sample sizes in oligonucleotide arrays using a mean-variance model.

PubMed

Hu, Jianhua; Wright, Fred A

2007-03-01

The identification of the genes that are differentially expressed in two-sample microarray experiments remains a difficult problem when the number of arrays is very small. We discuss the implications of using ordinary t-statistics and examine other commonly used variants. For oligonucleotide arrays with multiple probes per gene, we introduce a simple model relating the mean and variance of expression, possibly with gene-specific random effects. Parameter estimates from the model have natural shrinkage properties that guard against inappropriately small variance estimates, and the model is used to obtain a differential expression statistic. A limiting value to the positive false discovery rate (pFDR) for ordinary t-tests provides motivation for our use of the data structure to improve variance estimates. Our approach performs well compared to other proposed approaches in terms of the false discovery rate.

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.

Genome-wide transcriptomics of aging in the rotifer Brachionus manjavacas, an emerging model system.

PubMed

Gribble, Kristin E; Mark Welch, David B

2017-03-01

Understanding gene expression changes over lifespan in diverse animal species will lead to insights to conserved processes in the biology of aging and allow development of interventions to improve health. Rotifers are small aquatic invertebrates that have been used in aging studies for nearly 100 years and are now re-emerging as a modern model system. To provide a baseline to evaluate genetic responses to interventions that change health throughout lifespan and a framework for new hypotheses about the molecular genetic mechanisms of aging, we examined the transcriptome of an asexual female lineage of the rotifer Brachionus manjavacas at five life stages: eggs, neonates, and early-, late-, and post-reproductive adults. There are widespread shifts in gene expression over the lifespan of B. manjavacas; the largest change occurs between neonates and early reproductive adults and is characterized by down-regulation of developmental genes and up-regulation of genes involved in reproduction. The expression profile of post-reproductive adults was distinct from that of other life stages. While few genes were significantly differentially expressed in the late- to post-reproductive transition, gene set enrichment analysis revealed multiple down-regulated pathways in metabolism, maintenance and repair, and proteostasis, united by genes involved in mitochondrial function and oxidative phosphorylation. This study provides the first examination of changes in gene expression over lifespan in rotifers. We detected differential expression of many genes with human orthologs that are absent in Drosophila and C. elegans, highlighting the potential of the rotifer model in aging studies. Our findings suggest that small but coordinated changes in expression of many genes in pathways that integrate diverse functions drive the aging process. The observation of simultaneous declines in expression of genes in multiple pathways may have consequences for health and longevity not detected by single- or multi-gene knockdown in otherwise healthy animals. Investigation of subtle but genome-wide change in these pathways during aging is an important area for future study.

Identifying differentially expressed genes in cancer patients using a non-parameter Ising model.

PubMed

Li, Xumeng; Feltus, Frank A; Sun, Xiaoqian; Wang, James Z; Luo, Feng

2011-10-01

Identification of genes and pathways involved in diseases and physiological conditions is a major task in systems biology. In this study, we developed a novel non-parameter Ising model to integrate protein-protein interaction network and microarray data for identifying differentially expressed (DE) genes. We also proposed a simulated annealing algorithm to find the optimal configuration of the Ising model. The Ising model was applied to two breast cancer microarray data sets. The results showed that more cancer-related DE sub-networks and genes were identified by the Ising model than those by the Markov random field model. Furthermore, cross-validation experiments showed that DE genes identified by Ising model can improve classification performance compared with DE genes identified by Markov random field model. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

A quantitative validated model reveals two phases of transcriptional regulation for the gap gene giant in Drosophila.

PubMed

Hoermann, Astrid; Cicin-Sain, Damjan; Jaeger, Johannes

2016-03-15

Understanding eukaryotic transcriptional regulation and its role in development and pattern formation is one of the big challenges in biology today. Most attempts at tackling this problem either focus on the molecular details of transcription factor binding, or aim at genome-wide prediction of expression patterns from sequence through bioinformatics and mathematical modelling. Here we bridge the gap between these two complementary approaches by providing an integrative model of cis-regulatory elements governing the expression of the gap gene giant (gt) in the blastoderm embryo of Drosophila melanogaster. We use a reverse-engineering method, where mathematical models are fit to quantitative spatio-temporal reporter gene expression data to infer the regulatory mechanisms underlying gt expression in its anterior and posterior domains. These models are validated through prediction of gene expression in mutant backgrounds. A detailed analysis of our data and models reveals that gt is regulated by domain-specific CREs at early stages, while a late element drives expression in both the anterior and the posterior domains. Initial gt expression depends exclusively on inputs from maternal factors. Later, gap gene cross-repression and gt auto-activation become increasingly important. We show that auto-regulation creates a positive feedback, which mediates the transition from early to late stages of regulation. We confirm the existence and role of gt auto-activation through targeted mutagenesis of Gt transcription factor binding sites. In summary, our analysis provides a comprehensive picture of spatio-temporal gene regulation by different interacting enhancer elements for an important developmental regulator. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

A systems approach to model the relationship between aflatoxin gene cluster expression, environmental factors, growth and toxin production by Aspergillus flavus

PubMed Central

Abdel-Hadi, Ahmed; Schmidt-Heydt, Markus; Parra, Roberto; Geisen, Rolf; Magan, Naresh

2012-01-01

A microarray analysis was used to examine the effect of combinations of water activity (aw, 0.995–0.90) and temperature (20–42°C) on the activation of aflatoxin biosynthetic genes (30 genes) in Aspergillus flavus grown on a conducive YES (20 g yeast extract, 150 g sucrose, 1 g MgSO4·7H2O) medium. The relative expression of 10 key genes (aflF, aflD, aflE, aflM, aflO, aflP, aflQ, aflX, aflR and aflS) in the biosynthetic pathway was examined in relation to different environmental factors and phenotypic aflatoxin B1 (AFB1) production. These data, plus data on relative growth rates and AFB1 production under different aw × temperature conditions were used to develop a mixed-growth-associated product formation model. The gene expression data were normalized and then used as a linear combination of the data for all 10 genes and combined with the physical model. This was used to relate gene expression to aw and temperature conditions to predict AFB1 production. The relationship between the observed AFB1 production provided a good linear regression fit to the predicted production based in the model. The model was then validated by examining datasets outside the model fitting conditions used (37°C, 40°C and different aw levels). The relationship between structural genes (aflD, aflM) in the biosynthetic pathway and the regulatory genes (aflS, aflJ) was examined in relation to aw and temperature by developing ternary diagrams of relative expression. These findings are important in developing a more integrated systems approach by combining gene expression, ecophysiological influences and growth data to predict mycotoxin production. This could help in developing a more targeted approach to develop prevention strategies to control such carcinogenic natural metabolites that are prevalent in many staple food products. The model could also be used to predict the impact of climate change on toxin production. PMID:21880616

DREISS: Using State-Space Models to Infer the Dynamics of Gene Expression Driven by External and Internal Regulatory Networks.

PubMed

Wang, Daifeng; He, Fei; Maslov, Sergei; Gerstein, Mark

2016-10-01

Gene expression is controlled by the combinatorial effects of regulatory factors from different biological subsystems such as general transcription factors (TFs), cellular growth factors and microRNAs. A subsystem's gene expression may be controlled by its internal regulatory factors, exclusively, or by external subsystems, or by both. It is thus useful to distinguish the degree to which a subsystem is regulated internally or externally-e.g., how non-conserved, species-specific TFs affect the expression of conserved, cross-species genes during evolution. We developed a computational method (DREISS, dreiss.gerteinlab.org) for analyzing the Dynamics of gene expression driven by Regulatory networks, both External and Internal based on State Space models. Given a subsystem, the "state" and "control" in the model refer to its own (internal) and another subsystem's (external) gene expression levels. The state at a given time is determined by the state and control at a previous time. Because typical time-series data do not have enough samples to fully estimate the model's parameters, DREISS uses dimensionality reduction, and identifies canonical temporal expression trajectories (e.g., degradation, growth and oscillation) representing the regulatory effects emanating from various subsystems. To demonstrate capabilities of DREISS, we study the regulatory effects of evolutionarily conserved vs. divergent TFs across distant species. In particular, we applied DREISS to the time-series gene expression datasets of C. elegans and D. melanogaster during their embryonic development. We analyzed the expression dynamics of the conserved, orthologous genes (orthologs), seeing the degree to which these can be accounted for by orthologous (internal) versus species-specific (external) TFs. We found that between two species, the orthologs have matched, internally driven expression patterns but very different externally driven ones. This is particularly true for genes with evolutionarily ancient functions (e.g. the ribosomal proteins), in contrast to those with more recently evolved functions (e.g., cell-cell communication). This suggests that despite striking morphological differences, some fundamental embryonic-developmental processes are still controlled by ancient regulatory systems.

Probe-level linear model fitting and mixture modeling results in high accuracy detection of differential gene expression.

PubMed

Lemieux, Sébastien

2006-08-25

The identification of differentially expressed genes (DEGs) from Affymetrix GeneChips arrays is currently done by first computing expression levels from the low-level probe intensities, then deriving significance by comparing these expression levels between conditions. The proposed PL-LM (Probe-Level Linear Model) method implements a linear model applied on the probe-level data to directly estimate the treatment effect. A finite mixture of Gaussian components is then used to identify DEGs using the coefficients estimated by the linear model. This approach can readily be applied to experimental design with or without replication. On a wholly defined dataset, the PL-LM method was able to identify 75% of the differentially expressed genes within 10% of false positives. This accuracy was achieved both using the three replicates per conditions available in the dataset and using only one replicate per condition. The method achieves, on this dataset, a higher accuracy than the best set of tools identified by the authors of the dataset, and does so using only one replicate per condition.

Nursing frequency alters circadian patterns of mammary gene expression in lactating mice

USDA-ARS?s Scientific Manuscript database

Milking frequency impacts lactation in dairy cattle and in rodent models of lactation. The role of circadian gene expression in this process is unknown. The hypothesis tested was that changing nursing frequency alters the circadian patterns of mammary gene expression. Mid-lactation CD1 mice were stu...

On the presence and role of human gene-body DNA methylation

PubMed Central

Jjingo, Daudi; Conley, Andrew B.; Yi, Soojin V.; Lunyak, Victoria V.; Jordan, I. King

2012-01-01

DNA methylation of promoter sequences is a repressive epigenetic mark that down-regulates gene expression. However, DNA methylation is more prevalent within gene-bodies than seen for promoters, and gene-body methylation has been observed to be positively correlated with gene expression levels. This paradox remains unexplained, and accordingly the role of DNA methylation in gene-bodies is poorly understood. We addressed the presence and role of human gene-body DNA methylation using a meta-analysis of human genome-wide methylation, expression and chromatin data sets. Methylation is associated with transcribed regions as genic sequences have higher levels of methylation than intergenic or promoter sequences. We also find that the relationship between gene-body DNA methylation and expression levels is non-monotonic and bell-shaped. Mid-level expressed genes have the highest levels of gene-body methylation, whereas the most lowly and highly expressed sets of genes both have low levels of methylation. While gene-body methylation can be seen to efficiently repress the initiation of intragenic transcription, the vast majority of methylated sites within genes are not associated with intragenic promoters. In fact, highly expressed genes initiate the most intragenic transcription, which is inconsistent with the previously held notion that gene-body methylation serves to repress spurious intragenic transcription to allow for efficient transcriptional elongation. These observations lead us to propose a model to explain the presence of human gene-body methylation. This model holds that the repression of intragenic transcription by gene-body methylation is largely epiphenomenal, and suggests that gene-body methylation levels are predominantly shaped via the accessibility of the DNA to methylating enzyme complexes. PMID:22577155

Candidate innate immune system gene expression in the ecological model Daphnia

PubMed Central

Decaestecker, Ellen; Labbé, Pierrick; Ellegaard, Kirsten; Allen, Judith E.; Little, Tom J.

2011-01-01

The last ten years have witnessed increasing interest in host–pathogen interactions involving invertebrate hosts. The invertebrate innate immune system is now relatively well characterised, but in a limited range of genetic model organisms and under a limited number of conditions. Immune systems have been little studied under real-world scenarios of environmental variation and parasitism. Thus, we have investigated expression of candidate innate immune system genes in the water flea Daphnia, a model organism for ecological genetics, and whose capacity for clonal reproduction facilitates an exceptionally rigorous control of exposure dose or the study of responses at many time points. A unique characteristic of the particular Daphnia clones and pathogen strain combinations used presently is that they have been shown to be involved in specific host–pathogen coevolutionary interactions in the wild. We choose five genes, which are strong candidates to be involved in Daphnia–pathogen interactions, given that they have been shown to code for immune effectors in related organisms. Differential expression of these genes was quantified by qRT-PCR following exposure to the bacterial pathogen Pasteuria ramosa. Constitutive expression levels differed between host genotypes, and some genes appeared to show correlated expression. However, none of the genes appeared to show a major modification of expression level in response to Pasteuria exposure. By applying knowledge from related genetic model organisms (e.g. Drosophila) to models for the study of evolutionary ecology and coevolution (i.e. Daphnia), the candidate gene approach is temptingly efficient. However, our results show that detection of only weak patterns is likely if one chooses target genes for study based on previously identified genome sequences by comparison to homologues from other related organisms. Future work on the Daphnia–Pasteuria system will need to balance a candidate gene approach with more comprehensive approaches to de novo identify immune system genes specific to the Daphnia–Pasteuria interaction. PMID:21550363

Candidate innate immune system gene expression in the ecological model Daphnia.

PubMed

Decaestecker, Ellen; Labbé, Pierrick; Ellegaard, Kirsten; Allen, Judith E; Little, Tom J

2011-10-01

The last ten years have witnessed increasing interest in host-pathogen interactions involving invertebrate hosts. The invertebrate innate immune system is now relatively well characterised, but in a limited range of genetic model organisms and under a limited number of conditions. Immune systems have been little studied under real-world scenarios of environmental variation and parasitism. Thus, we have investigated expression of candidate innate immune system genes in the water flea Daphnia, a model organism for ecological genetics, and whose capacity for clonal reproduction facilitates an exceptionally rigorous control of exposure dose or the study of responses at many time points. A unique characteristic of the particular Daphnia clones and pathogen strain combinations used presently is that they have been shown to be involved in specific host-pathogen coevolutionary interactions in the wild. We choose five genes, which are strong candidates to be involved in Daphnia-pathogen interactions, given that they have been shown to code for immune effectors in related organisms. Differential expression of these genes was quantified by qRT-PCR following exposure to the bacterial pathogen Pasteuria ramosa. Constitutive expression levels differed between host genotypes, and some genes appeared to show correlated expression. However, none of the genes appeared to show a major modification of expression level in response to Pasteuria exposure. By applying knowledge from related genetic model organisms (e.g. Drosophila) to models for the study of evolutionary ecology and coevolution (i.e. Daphnia), the candidate gene approach is temptingly efficient. However, our results show that detection of only weak patterns is likely if one chooses target genes for study based on previously identified genome sequences by comparison to homologues from other related organisms. Future work on the Daphnia-Pasteuria system will need to balance a candidate gene approach with more comprehensive approaches to de novo identify immune system genes specific to the Daphnia-Pasteuria interaction. Copyright © 2011 Elsevier Ltd. All rights reserved.

Stage-specific differential gene expression profiling and functional network analysis during morphogenesis of diphyodont dentition in miniature pigs, Sus Scrofa

PubMed Central

2014-01-01

Background Our current knowledge of tooth development derives mainly from studies in mice, which have only one set of non-replaced teeth, compared with the diphyodont dentition in humans. The miniature pig is also diphyodont, making it a valuable alternative model for understanding human tooth development and replacement. However, little is known about gene expression and function during swine odontogenesis. The goal of this study is to undertake the survey of differential gene expression profiling and functional network analysis during morphogenesis of diphyodont dentition in miniature pigs. The identification of genes related to diphyodont development should lead to a better understanding of morphogenetic patterns and the mechanisms of diphyodont replacement in large animal models and humans. Results The temporal gene expression profiles during early diphyodont development in miniature pigs were detected with the Affymetrix Porcine GeneChip. The gene expression data were further evaluated by ANOVA as well as pathway and STC analyses. A total of 2,053 genes were detected with differential expression. Several signal pathways and 151 genes were then identified through the construction of pathway and signal networks. Conclusions The gene expression profiles indicated that spatio-temporal down-regulation patterns of gene expression were predominant; while, both dynamic activation and inhibition of pathways occurred during the morphogenesis of diphyodont dentition. Our study offers a mechanistic framework for understanding dynamic gene regulation of early diphyodont development and provides a molecular basis for studying teeth development, replacement, and regeneration in miniature pigs. PMID:24498892

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.

A Primary Xenograft Model of Small Cell Lung Cancer Reveals Irreversible Changes in Gene Expression Imposed by Culture In-Vitro

PubMed Central

Daniel, Vincent C.; Marchionni, Luigi; Hierman, Jared S.; Rhodes, Jonathan T.; Devereux, Wendy L.; Rudin, Charles M.; Yung, Rex; Parmigani, Giovanni; Dorsch, Marion; Peacock, Craig D.; Watkins, D. Neil

2009-01-01

Traditional approaches to the preclinical investigation of cancer therapies rely on the use of established cell lines maintained in serum-based growth media. This is particularly true of small cell lung cancer (SCLC), where surgically resected tissue is rarely available. Recent attention has focused on the need for better models that preserve the integrity of cancer stem cell populations, as well as three-dimensional tumor-stromal interactions. Here we describe a primary xenograft model of SCLC in which endobronchial tumor specimens obtained from chemo-naive patients are serially propagated in vivo in immunodeficient mice. In parallel, cell lines grown in conventional tissue culture conditions were derived from each xenograft line, passaged for 6 months, and then re-implanted to generate secondary xenografts. Using the Affymetrix platform, we analyzed gene expression in primary xenograft, xenograft-derived cell line, and secondary xenograft, and compared these data to similar analyses of unrelated primary SCLC samples and laboratory models. When compared to normal lung, primary tumors, xenografts and cell lines displayed a gene expression signature specific for SCLC. Comparison of gene expression within the xenograft model identified a group of tumor-specific genes expressed in primary SCLC and xenografts that was lost during the transition to tissue culture, and that was not regained when the tumors were re-established as secondary xenografts. Such changes in gene expression may be a common feature of many cancer cell culture systems, with functional implications for the use of such models for preclinical drug development. PMID:19351829

Genomic pathways modulated by Twist in breast cancer.

PubMed

Vesuna, Farhad; Bergman, Yehudit; Raman, Venu

2017-01-13

The basic helix-loop-helix transcription factor TWIST1 (Twist) is involved in embryonic cell lineage determination and mesodermal differentiation. There is evidence to indicate that Twist expression plays a role in breast tumor formation and metastasis, but the role of Twist in dysregulating pathways that drive the metastatic cascade is unclear. Moreover, many of the genes and pathways dysregulated by Twist in cell lines and mouse models have not been validated against data obtained from larger, independant datasets of breast cancer patients. We over-expressed the human Twist gene in non-metastatic MCF-7 breast cancer cells to generate the estrogen-independent metastatic breast cancer cell line MCF-7/Twist. These cells were inoculated in the mammary fat pad of female severe compromised immunodeficient mice, which subsequently formed xenograft tumors that metastasized to the lungs. Microarray data was collected from both in vitro (MCF-7 and MCF-7/Twist cell lines) and in vivo (primary tumors and lung metastases) models of Twist expression. Our data was compared to several gene datasets of various subtypes, classes, and grades of human breast cancers. Our data establishes a Twist over-expressing mouse model of breast cancer, which metastasizes to the lung and replicates some of the ontogeny of human breast cancer progression. Gene profiling data, following Twist expression, exhibited novel metastasis driver genes as well as cellular maintenance genes that were synonymous with the metastatic process. We demonstrated that the genes and pathways altered in the transgenic cell line and metastatic animal models parallel many of the dysregulated gene pathways observed in human breast cancers. Analogous gene expression patterns were observed in both in vitro and in vivo Twist preclinical models of breast cancer metastasis and breast cancer patient datasets supporting the functional role of Twist in promoting breast cancer metastasis. The data suggests that genetic dysregulation of Twist at the cellular level drives alterations in gene pathways in the Twist metastatic mouse model which are comparable to changes seen in human breast cancers. Lastly, we have identified novel genes and pathways that could be further investigated as targets for drugs to treat metastatic breast cancer.

Transcriptional Coupling of Neighboring Genes and Gene Expression Noise: Evidence that Gene Orientation and Noncoding Transcripts Are Modulators of Noise

PubMed Central

Wang, Guang-Zhong; Lercher, Martin J.; Hurst, Laurence D.

2011-01-01

Abstract How is noise in gene expression modulated? Do mechanisms of noise control impact genome organization? In yeast, the expression of one gene can affect that of a very close neighbor. As the effect is highly regionalized, we hypothesize that genes in different orientations will have differing degrees of coupled expression and, in turn, different noise levels. Divergently organized gene pairs, in particular those with bidirectional promoters, have close promoters, maximizing the likelihood that expression of one gene affects the neighbor. With more distant promoters, the same is less likely to hold for gene pairs in nondivergent orientation. Stochastic models suggest that coupled chromatin dynamics will typically result in low abundance-corrected noise (ACN). Transcription of noncoding RNA (ncRNA) from a bidirectional promoter, we thus hypothesize to be a noise-reduction, expression-priming, mechanism. The hypothesis correctly predicts that protein-coding genes with a bidirectional promoter, including those with a ncRNA partner, have lower ACN than other genes and divergent gene pairs uniquely have correlated ACN. Moreover, as predicted, ACN increases with the distance between promoters. The model also correctly predicts ncRNA transcripts to be often divergently transcribed from genes that a priori would be under selection for low noise (essential genes, protein complex genes) and that the latter genes should commonly reside in divergent orientation. Likewise, that genes with bidirectional promoters are rare subtelomerically, cluster together, and are enriched in essential gene clusters is expected and observed. We conclude that gene orientation and transcription of ncRNAs are candidate modulators of noise. PMID:21402863

Generation of a Tet-On Expression System to Study Transactivation Ability of Tax-2.

PubMed

Bignami, Fabio; Sozzi, Riccardo Alessio; Pilotti, Elisabetta

2017-01-01

HTLV Tax proteins (Tax-1 and Tax-2) are known to be able to transactivate several host cellular genes involved in complex molecular pathways. Here, we describe a stable and regulated high-level expression model based on Tet-On system, to study the capacity of Tax-2 to transactivate host genes. In particular, the Jurkat Tet-On cell line suitable for evaluating the ability of Tax-2 to stimulate transactivation of a specific host gene, CCL3L1 (C-C motif chemokine ligand 3 like 1 gene), was selected. Then, a plasmid expressing tax-2 gene under control of a tetracycline-response element was constructed. To avoid the production of a fusion protein between the report gene and the inserted gene, a bidirectional plasmid was designed. Maximum expression and fast response time were achieved by using nucleofection technology as transfection method. After developing an optimized protocol for efficiently transferring tax-2 gene in Jurkat Tet-On cellular model and exposing transfected cells to Dox (doxycycline, a tetracycline derivate), a kinetics of tax-2 expression through TaqMan Real-time PCR assay was determined.

A stochastic model for optimizing composite predictors based on gene expression profiles.

PubMed

Ramanathan, Murali

2003-07-01

This project was done to develop a mathematical model for optimizing composite predictors based on gene expression profiles from DNA arrays and proteomics. The problem was amenable to a formulation and solution analogous to the portfolio optimization problem in mathematical finance: it requires the optimization of a quadratic function subject to linear constraints. The performance of the approach was compared to that of neighborhood analysis using a data set containing cDNA array-derived gene expression profiles from 14 multiple sclerosis patients receiving intramuscular inteferon-beta1a. The Markowitz portfolio model predicts that the covariance between genes can be exploited to construct an efficient composite. The model predicts that a composite is not needed for maximizing the mean value of a treatment effect: only a single gene is needed, but the usefulness of the effect measure may be compromised by high variability. The model optimized the composite to yield the highest mean for a given level of variability or the least variability for a given mean level. The choices that meet this optimization criteria lie on a curve of composite mean vs. composite variability plot referred to as the "efficient frontier." When a composite is constructed using the model, it outperforms the composite constructed using the neighborhood analysis method. The Markowitz portfolio model may find potential applications in constructing composite biomarkers and in the pharmacogenomic modeling of treatment effects derived from gene expression endpoints.

ExprAlign - the identification of ESTs in non-model species by alignment of cDNA microarray expression profiles

PubMed Central

2009-01-01

Background Sequence identification of ESTs from non-model species offers distinct challenges particularly when these species have duplicated genomes and when they are phylogenetically distant from sequenced model organisms. For the common carp, an environmental model of aquacultural interest, large numbers of ESTs remained unidentified using BLAST sequence alignment. We have used the expression profiles from large-scale microarray experiments to suggest gene identities. Results Expression profiles from ~700 cDNA microarrays describing responses of 7 major tissues to multiple environmental stressors were used to define a co-expression landscape. This was based on the Pearsons correlation coefficient relating each gene with all other genes, from which a network description provided clusters of highly correlated genes as 'mountains'. We show that these contain genes with known identities and genes with unknown identities, and that the correlation constitutes evidence of identity in the latter. This procedure has suggested identities to 522 of 2701 unknown carp ESTs sequences. We also discriminate several common carp genes and gene isoforms that were not discriminated by BLAST sequence alignment alone. Precision in identification was substantially improved by use of data from multiple tissues and treatments. Conclusion The detailed analysis of co-expression landscapes is a sensitive technique for suggesting an identity for the large number of BLAST unidentified cDNAs generated in EST projects. It is capable of detecting even subtle changes in expression profiles, and thereby of distinguishing genes with a common BLAST identity into different identities. It benefits from the use of multiple treatments or contrasts, and from the large-scale microarray data. PMID:19939286

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

Quantitative developmental transcriptomes of the Mediterranean sea urchin Paracentrotus lividus.

PubMed

Gildor, Tsvia; Malik, Assaf; Sher, Noa; Avraham, Linor; Ben-Tabou de-Leon, Smadar

2016-02-01

Embryonic development progresses through the timely activation of thousands of differentially activated genes. Quantitative developmental transcriptomes provide the means to relate global patterns of differentially expressed genes to the emerging body plans they generate. The sea urchin is one of the classic model systems for embryogenesis and the models of its developmental gene regulatory networks are of the most comprehensive of their kind. Thus, the sea urchin embryo is an excellent system for studies of its global developmental transcriptional profiles. Here we produced quantitative developmental transcriptomes of the sea urchin Paracentrotus lividus (P. lividus) at seven developmental stages from the fertilized egg to prism stage. We generated de-novo reference transcriptome and identified 29,817 genes that are expressed at this time period. We annotated and quantified gene expression at the different developmental stages and confirmed the reliability of the expression profiles by QPCR measurement of a subset of genes. The progression of embryo development is reflected in the observed global expression patterns and in our principle component analysis. Our study illuminates the rich patterns of gene expression that participate in sea urchin embryogenesis and provide an essential resource for further studies of the dynamic expression of P. lividus genes. Copyright © 2015 Elsevier B.V. All rights reserved.

GENOMIC IMPRINTING, DISRUPTED PLACENTAL EXPRESSION, AND SPECIATION

PubMed Central

Brekke, Thomas D.; Henry, Lindy A.; Good, Jeffrey M.

2016-01-01

The importance of regulatory incompatibilities to the early stages of speciation remains unclear. Hybrid mammals often show extreme parent-of-origin growth effects that are thought to be a consequence of disrupted genetic imprinting (parent-specific epigenetic gene silencing) during early development. Here we test the long-standing hypothesis that abnormal hybrid growth reflects disrupted gene expression due to loss of imprinting (LOI) in hybrid placentas, resulting in dosage imbalances between paternal growth factors and maternal growth repressors. We analyzed placental gene expression in reciprocal dwarf hamster hybrids that show extreme parent-of-origin growth effects relative to their parental species. In massively enlarged hybrid placentas, we observed both extensive transgressive expression of growth-related genes and bi-allelic expression of many genes that were paternally silenced in normal sized hybrids. However, the apparent widespread disruption of paternal silencing was coupled with reduced gene expression levels overall. These patterns are contrary to the predictions of the LOI model and indicate that hybrid misexpression of dosage sensitive genes is caused by other regulatory mechanisms in this system. Collectively, our results support a central role for disrupted gene expression and imprinting in the evolution of mammalian hybrid inviability, but call into question the generality of the widely invoked LOI model. PMID:27714796

A 3-dimensional human embryonic stem cell (hESC)-derived model to detect developmental neurotoxicity of nanoparticles.

PubMed

Hoelting, Lisa; Scheinhardt, Benjamin; Bondarenko, Olesja; Schildknecht, Stefan; Kapitza, Marion; Tanavde, Vivek; Tan, Betty; Lee, Qian Yi; Mecking, Stefan; Leist, Marcel; Kadereit, Suzanne

2013-04-01

Nanoparticles (NPs) have been shown to accumulate in organs, cross the blood-brain barrier and placenta, and have the potential to elicit developmental neurotoxicity (DNT). Here, we developed a human embryonic stem cell (hESC)-derived 3-dimensional (3-D) in vitro model that allows for testing of potential developmental neurotoxicants. Early central nervous system PAX6(+) precursor cells were generated from hESCs and differentiated further within 3-D structures. The 3-D model was characterized for neural marker expression revealing robust differentiation toward neuronal precursor cells, and gene expression profiling suggested a predominantly forebrain-like development. Altered neural gene expression due to exposure to non-cytotoxic concentrations of the known developmental neurotoxicant, methylmercury, indicated that the 3-D model could detect DNT. To test for specific toxicity of NPs, chemically inert polyethylene NPs (PE-NPs) were chosen. They penetrated deep into the 3-D structures and impacted gene expression at non-cytotoxic concentrations. NOTCH pathway genes such as HES5 and NOTCH1 were reduced in expression, as well as downstream neuronal precursor genes such as NEUROD1 and ASCL1. FOXG1, a patterning marker, was also reduced. As loss of function of these genes results in severe nervous system impairments in mice, our data suggest that the 3-D hESC-derived model could be used to test for Nano-DNT.

Rhesus monkey model of liver disease reflecting clinical disease progression and hepatic gene expression analysis

PubMed Central

Wang, Hong; Tan, Tao; Wang, Junfeng; Niu, Yuyu; Yan, Yaping; Guo, Xiangyu; Kang, Yu; Duan, Yanchao; Chang, Shaohui; Liao, Jianpeng; Si, Chenyang; Ji, Weizhi; Si, Wei

2015-01-01

Alcoholic liver disease (ALD) is a significant public health issue with heavy medical and economic burdens. The aetiology of ALD is not yet completely understood. The development of drugs and therapies for ALD is hampered by a lack of suitable animal models that replicate both the histological and metabolic features of human ALD. Here, we characterize a rhesus monkey model of alcohol-induced liver steatosis and hepatic fibrosis that is compatible with the clinical progression of the biochemistry and pathology in humans with ALD. Microarray analysis of hepatic gene expression was conducted to identify potential molecular signatures of ALD progression. The up-regulation of expression of hepatic genes related to liver steatosis (CPT1A, FASN, LEPR, RXRA, IGFBP1, PPARGC1A and SLC2A4) was detected in our rhesus model, as was the down-regulation of such genes (CYP7A1, HMGCR, GCK and PNPLA3) and the up-regulation of expression of hepatic genes related to liver cancer (E2F1, OPCML, FZD7, IGFBP1 and LEF1). Our results demonstrate that this ALD model reflects the clinical disease progression and hepatic gene expression observed in humans. These findings will be useful for increasing the understanding of ALD pathogenesis and will benefit the development of new therapeutic procedures and pharmacological reagents for treating ALD. PMID:26442469

Retrotransposed genes such as Frat3 in the mouse Chromosome 7C Prader-Willi syndrome region acquire the imprinted status of their insertion site.

PubMed

Chai, J H; Locke, D P; Ohta, T; Greally, J M; Nicholls, R D

2001-11-01

Prader-Willi syndrome (PWS) results from loss of function of a 1.0- to 1.5-Mb domain of imprinted, paternally expressed genes in human Chromosome (Chr) 15q11-q13. The loss of imprinted gene expression in the homologous region in mouse Chr 7C leads to a similar neonatal PWS phenotype. Several protein-coding genes in the human PWS region are intronless, possibly arising by retrotransposition. Here we present evidence for continued acquisition of genes by the mouse PWS region during evolution. Bioinformatic analyses identified a BAC containing four genes, Mkrn3, Magel2, Ndn, Frat3, and the Atp5l-ps1 pseudogene, the latter two genes derived from recent L1-mediated retrotransposition. Analyses of eight overlapping BACs indicate that these genes are clustered within 120 kb in two inbred strains, in the order tel-Atp5l-ps1-Frat3-Mkrn3-Magel2-Ndn-cen. Imprinting analyses show that Frat3 is differentially methylated and expressed solely from the paternal allele in a transgenic mouse model of Angelman syndrome, with no expression from the maternal allele in a mouse model of PWS. Loss of Frat3 expression may, therefore, contribute to the phenotype of mouse models of PWS. The identification of five intronless genes in a small genomic interval suggests that this region is prone to retroposition in germ cells or their zygotic and embryonic cell precursors, and that it allows the subsequent functional expression of these foreign sequences. The recent evolutionary acquisition of genes that adopt the same imprint as older, flanking genes indicates that the newly acquired genes become 'innocent bystanders' of a primary epigenetic signal causing imprinting in the PWS domain.

Effect of external and internal factors on the expression of reporter genes driven by the N resistance gene promoter.

PubMed

Kathiria, Palak; Sidler, Corinne; Woycicki, Rafal; Yao, Youli; Kovalchuk, Igor

2013-07-01

The role of resistance (R) genes in plant pathogen interaction has been studied extensively due to its economical impact on agriculture. Interaction between tobacco mosaic virus (TMV) and the N protein from tobacco is one of the most widely used models to understand various aspects of pathogen resistance. The transcription activity governed by N gene promoter is one of the least understood elements of the model. In this study, the N gene promoter was cloned and fused with two different reporter genes, one encoding β-glucuronidase (N::GUS) and another, luciferase (N::LUC). Tobacco plants transformed with the N::GUS or N::LUC reporter constructs were screened for homozygosity and stable expression. Histochemical analysis of N::GUS tobacco plants revealed that the expression is organ specific and developmentally regulated. Whereas two week old plants expressed GUS in midveins only, 6-wk-old plants also expressed GUS in leaf lamella. Roots did not show GUS expression at any time during development. Experiments to address effects of external stress were performed using N::LUC tobacco plants. These experiments showed that N gene promoter expression was suppressed when plants were exposed to high but not low temperatures. Expression was also upregulated in response to TMV, but no changes were observed in plants treated with SA.

Left Ventricular Gene Expression Profile of Healthy and Cardiovascular Compromised Rat Models Used in Air Pollution Studies

EPA Science Inventory

The link between pollutant exposure and cardiovascular disease (CVD) has prompted mechanistic research with animal models of CVD. We hypothesized that the cardiac gene expression patterns of healthy and genetically compromised, CVD-prone rat models, with or without metabolic impa...

SYSTEMIC BIOMARKERS AND CARDIAC GENE EXPRESSION PROFILES OF RAT DISEASE MODELS EMPLOYED IN AIR POLLUTION STUDIES

EPA Science Inventory

Cardiovascular disease (CVD) models are used for identification of mechanisms of susceptibility to air pollution. We hypothesized that baseline systemic biomarkers and cardiac gene expression in CVD rat models will have influence on their ozone-induced lung inflammation. Male 12-...

Mapping gene expression patterns during myeloid differentiation using the EML hematopoietic progenitor cell line.

PubMed

Du, Yang; Campbell, Janee L; Nalbant, Demet; Youn, Hyewon; Bass, Ann C Hughes; Cobos, Everardo; Tsai, Schickwann; Keller, Jonathan R; Williams, Simon C

2002-07-01

The detailed examination of the molecular events that control the early stages of myeloid differentiation has been hampered by the relative scarcity of hematopoietic stem cells and the lack of suitable cell line models. In this study, we examined the expression of several myeloid and nonmyeloid genes in the murine EML hematopoietic stem cell line. Expression patterns for 19 different genes were examined by Northern blotting and RT-PCR in RNA samples from EML, a variety of other immortalized cell lines, and purified murine hematopoietic stem cells. Representational difference analysis (RDA) was performed to identify differentially expressed genes in EML. Expression patterns of genes encoding transcription factors (four members of the C/EBP family, GATA-1, GATA-2, PU.1, CBFbeta, SCL, and c-myb) in EML were examined and were consistent with the proposed functions of these proteins in hematopoietic differentiation. Expression levels of three markers of terminal myeloid differentiation (neutrophil elastase, proteinase 3, and Mac-1) were highest in EML cells at the later stages of differentiation. In a search for genes that were differentially expressed in EML cells during myeloid differentiation, six cDNAs were isolated. These included three known genes (lysozyme, histidine decarboxylase, and tryptophan hydroxylase) and three novel genes. Expression patterns of known genes in differentiating EML cells accurately reflected their expected expression patterns based on previous studies. The identification of three novel genes, two of which encode proteins that may act as regulators of hematopoietic differentiation, suggests that EML is a useful model system for the molecular analysis of hematopoietic differentiation.

RNA Expression Profiling Reveals Differentially Regulated Growth Factor and Receptor Expression in Redirected Cancer Cells.

PubMed

Schmucker, Hannah S; Park, Jang Pyo; Coissieux, Marie-May; Bentires-Alj, Mohamed; Feltus, F Alex; Booth, Brian W

2017-05-01

Tumorigenic cells can be redirected to adopt a normal phenotype when transplanted into cleared mammary fat pads of juvenile female mice in specific ratios with normal epithelial cells. The redirected tumorigenic cells enter stem cell niches and provide progeny that differentiate into all mammary epithelial subtypes. We have developed an in vitro model that mimics the in vivo phenomenon. The shift in phenotype to redirection should be accomplished through a return to a normal gene expression state. To measure this shift, we interrogated the transcriptome of various in vitro model states in search for casual genes. For this study, expression of growth factors, cytokines, and their associated receptors was examined. In all, we queried 251 growth factor and cytokine-related genes. We found numerous growth factor and cytokine genes whose expression levels switched from expression levels seen in cancer cells to expression levels observed in normal cells. The comparisons of gene expression between normal mammary epithelial cells, tumor-derived cells, and redirected cancer cells have revealed insight into active and inactive growth factors and cytokines in cancer cell redirection.

Alpha-fetoprotein-targeted reporter gene expression imaging in hepatocellular carcinoma

PubMed Central

Kim, Kwang Il; Chung, Hye Kyung; Park, Ju Hui; Lee, Yong Jin; Kang, Joo Hyun

2016-01-01

Hepatocellular carcinoma (HCC) is one of the most common cancers in Eastern Asia, and its incidence is increasing globally. Numerous experimental models have been developed to better our understanding of the pathogenic mechanism of HCC and to evaluate novel therapeutic approaches. Molecular imaging is a convenient and up-to-date biomedical tool that enables the visualization, characterization and quantification of biologic processes in a living subject. Molecular imaging based on reporter gene expression, in particular, can elucidate tumor-specific events or processes by acquiring images of a reporter gene’s expression driven by tumor-specific enhancers/promoters. In this review, we discuss the advantages and disadvantages of various experimental HCC mouse models and we present in vivo images of tumor-specific reporter gene expression driven by an alpha-fetoprotein (AFP) enhancer/promoter system in a mouse model of HCC. The current mouse models of HCC development are established by xenograft, carcinogen induction and genetic engineering, representing the spectrum of tumor-inducing factors and tumor locations. The imaging analysis approach of reporter genes driven by AFP enhancer/promoter is presented for these different HCC mouse models. Such molecular imaging can provide longitudinal information about carcinogenesis and tumor progression. We expect that clinical application of AFP-targeted reporter gene expression imaging systems will be useful for the detection of AFP-expressing HCC tumors and screening of increased/decreased AFP levels due to disease or drug treatment. PMID:27468205

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

A method to identify differential expression profiles of time-course gene data with Fourier transformation.

PubMed

Kim, Jaehee; Ogden, Robert Todd; Kim, Haseong

2013-10-18

Time course gene expression experiments are an increasingly popular method for exploring biological processes. Temporal gene expression profiles provide an important characterization of gene function, as biological systems are both developmental and dynamic. With such data it is possible to study gene expression changes over time and thereby to detect differential genes. Much of the early work on analyzing time series expression data relied on methods developed originally for static data and thus there is a need for improved methodology. Since time series expression is a temporal process, its unique features such as autocorrelation between successive points should be incorporated into the analysis. This work aims to identify genes that show different gene expression profiles across time. We propose a statistical procedure to discover gene groups with similar profiles using a nonparametric representation that accounts for the autocorrelation in the data. In particular, we first represent each profile in terms of a Fourier basis, and then we screen out genes that are not differentially expressed based on the Fourier coefficients. Finally, we cluster the remaining gene profiles using a model-based approach in the Fourier domain. We evaluate the screening results in terms of sensitivity, specificity, FDR and FNR, compare with the Gaussian process regression screening in a simulation study and illustrate the results by application to yeast cell-cycle microarray expression data with alpha-factor synchronization.The key elements of the proposed methodology: (i) representation of gene profiles in the Fourier domain; (ii) automatic screening of genes based on the Fourier coefficients and taking into account autocorrelation in the data, while controlling the false discovery rate (FDR); (iii) model-based clustering of the remaining gene profiles. Using this method, we identified a set of cell-cycle-regulated time-course yeast genes. The proposed method is general and can be potentially used to identify genes which have the same patterns or biological processes, and help facing the present and forthcoming challenges of data analysis in functional genomics.

Dietary restriction decreases coenzyme Q and ubiquinol potentially via changes in gene expression in the model organism C. elegans.

PubMed

Fischer, Alexandra; Klapper, Maja; Onur, Simone; Menke, Thomas; Niklowitz, Petra; Döring, Frank

2015-05-06

Dietary restriction (DR) is a robust intervention that extends both health span and life span in many organisms. Ubiquinol and ubiquinone represent the reduced and oxidized forms of coenzyme Q (CoQ). CoQ plays a central role in energy metabolism and functions in several cellular processes including gene expression. Here we used the model organism Caenorhabditis elegans to determine level and redox state of CoQ and expression of genes in response to DR. We found that DR down-regulates the steady-state expression levels of several evolutionary conserved genes (i.e. coq-1) that encode key enzymes of the mevalonate and CoQ-synthesizing pathways. In line with this, DR decreases the levels of total CoQ and ubiquinol. This CoQ-reducing effect of DR is obvious in adult worms but not in L4 larvae and is also evident in the eat-2 mutant, a genetic model of DR. In conclusion, we propose that DR reduces the level of CoQ and ubiquinol via gene expression in the model organism C. elegans. © 2015 International Union of Biochemistry and Molecular Biology.

Effect of various classes of pesticides on expression of stress genes in transgenic C. elegans model of Parkinson's disease.

PubMed

Jadiya, Pooja; Mir, Snober S; Nazir, Aamir

2012-12-01

Neurodegenerative diseases are known to be associated with genetic and environmental factors. The multifactorial Parkinson's disease (PD) is triggered and/or further worsened by exposure to certain pesticides. Existing literature suggests a link between pesticide exposure and increased incidence of PD. We carried out the present study to look into the stress gene expression pattern of transgenic Caenorhabditis elegans (C. elegans) model of PD after exposure to pesticides from different classes. Expression level of sod-1, sod-2, sod-3, hsp-70, hsp-60, and hsp-16.2 stress responsive genes was determined using qPCR. Our findings demonstrate that the expression of stress related genes does not follow a generalized pattern to different toxicants; rather each pesticide class has a specific expression signature.

Reverse engineering the gap gene network of Drosophila melanogaster.

PubMed

Perkins, Theodore J; Jaeger, Johannes; Reinitz, John; Glass, Leon

2006-05-01

A fundamental problem in functional genomics is to determine the structure and dynamics of genetic networks based on expression data. We describe a new strategy for solving this problem and apply it to recently published data on early Drosophila melanogaster development. Our method is orders of magnitude faster than current fitting methods and allows us to fit different types of rules for expressing regulatory relationships. Specifically, we use our approach to fit models using a smooth nonlinear formalism for modeling gene regulation (gene circuits) as well as models using logical rules based on activation and repression thresholds for transcription factors. Our technique also allows us to infer regulatory relationships de novo or to test network structures suggested by the literature. We fit a series of models to test several outstanding questions about gap gene regulation, including regulation of and by hunchback and the role of autoactivation. Based on our modeling results and validation against the experimental literature, we propose a revised network structure for the gap gene system. Interestingly, some relationships in standard textbook models of gap gene regulation appear to be unnecessary for or even inconsistent with the details of gap gene expression during wild-type development.

Gene selection and cancer type classification of diffuse large-B-cell lymphoma using a bivariate mixture model for two-species data.

PubMed

Su, Yuhua; Nielsen, Dahlia; Zhu, Lei; Richards, Kristy; Suter, Steven; Breen, Matthew; Motsinger-Reif, Alison; Osborne, Jason

2013-01-05

: A bivariate mixture model utilizing information across two species was proposed to solve the fundamental problem of identifying differentially expressed genes in microarray experiments. The model utility was illustrated using a dog and human lymphoma data set prepared by a group of scientists in the College of Veterinary Medicine at North Carolina State University. A small number of genes were identified as being differentially expressed in both species and the human genes in this cluster serve as a good predictor for classifying diffuse large-B-cell lymphoma (DLBCL) patients into two subgroups, the germinal center B-cell-like diffuse large B-cell lymphoma and the activated B-cell-like diffuse large B-cell lymphoma. The number of human genes that were observed to be significantly differentially expressed (21) from the two-species analysis was very small compared to the number of human genes (190) identified with only one-species analysis (human data). The genes may be clinically relevant/important, as this small set achieved low misclassification rates of DLBCL subtypes. Additionally, the two subgroups defined by this cluster of human genes had significantly different survival functions, indicating that the stratification based on gene-expression profiling using the proposed mixture model provided improved insight into the clinical differences between the two cancer subtypes.

Mathematical Modeling of RNA-Based Architectures for Closed Loop Control of Gene Expression.

PubMed

Agrawal, Deepak K; Tang, Xun; Westbrook, Alexandra; Marshall, Ryan; Maxwell, Colin S; Lucks, Julius; Noireaux, Vincent; Beisel, Chase L; Dunlop, Mary J; Franco, Elisa

2018-05-08

Feedback allows biological systems to control gene expression precisely and reliably, even in the presence of uncertainty, by sensing and processing environmental changes. Taking inspiration from natural architectures, synthetic biologists have engineered feedback loops to tune the dynamics and improve the robustness and predictability of gene expression. However, experimental implementations of biomolecular control systems are still far from satisfying performance specifications typically achieved by electrical or mechanical control systems. To address this gap, we present mathematical models of biomolecular controllers that enable reference tracking, disturbance rejection, and tuning of the temporal response of gene expression. These controllers employ RNA transcriptional regulators to achieve closed loop control where feedback is introduced via molecular sequestration. Sensitivity analysis of the models allows us to identify which parameters influence the transient and steady state response of a target gene expression process, as well as which biologically plausible parameter values enable perfect reference tracking. We quantify performance using typical control theory metrics to characterize response properties and provide clear selection guidelines for practical applications. Our results indicate that RNA regulators are well-suited for building robust and precise feedback controllers for gene expression. Additionally, our approach illustrates several quantitative methods useful for assessing the performance of biomolecular feedback control systems.

Cellular reprogramming dynamics follow a simple 1D reaction coordinate

NASA Astrophysics Data System (ADS)

Teja Pusuluri, Sai; Lang, Alex H.; Mehta, Pankaj; Castillo, Horacio E.

2018-01-01

Cellular reprogramming, the conversion of one cell type to another, induces global changes in gene expression involving thousands of genes, and understanding how cells globally alter their gene expression profile during reprogramming is an ongoing problem. Here we reanalyze time-course data on cellular reprogramming from differentiated cell types to induced pluripotent stem cells (iPSCs) and show that gene expression dynamics during reprogramming follow a simple 1D reaction coordinate. This reaction coordinate is independent of both the time it takes to reach the iPSC state as well as the details of the experimental protocol used. Using Monte-Carlo simulations, we show that such a reaction coordinate emerges from epigenetic landscape models where cellular reprogramming is viewed as a ‘barrier-crossing’ process between cell fates. Overall, our analysis and model suggest that gene expression dynamics during reprogramming follow a canonical trajectory consistent with the idea of an ‘optimal path’ in gene expression space for reprogramming.

Molecular pathology of acute kidney injury in a choline-deficient model and fish oil protective effect.

PubMed

Denninghoff, Valeria; Ossani, Georgina; Uceda, Ana; Rugnone, Matias; Fernández, Elmer; Fresno, Cristóbal; González, German; Díaz, Maria Luisa; Avagnina, Alejandra; Elsner, Boris; Monserrat, Alberto

2014-04-01

The aim of this work was to investigate the potential protective effects of fish oil on the basis of kidney transcriptomic data on a nutritional experimental model. Male weanling Wistar rats were divided into four groups and fed choline-deficient (CD) and choline-supplemented (CS) diets with vegetable oil (VO) and menhaden oil (MO): CSVO, CDVO, CSMO and CDMO. Animals were killed after receiving the diets for 6 days. Total RNA was purified from the right kidney and hybridized to Affymetrix GeneChip Rat Gene 1.0 ST Array. Differentially expressed genes were analyzed. All CSVO, CSMO and CDMO rats showed no renal alterations, while all CDVO rats showed renal cortical necrosis. A thorough analysis of the differential expression between groups CSMO and CDMO was carried out. There were no differential genes for p < 0.01. The analysis of the differential expression between groups CSVO and CSMO revealed 32 genes, 11 were over-expressed and 21 were under-expressed in CSMO rats. This work was part of a large set of experiments and was used in a hypothesis-generating manner. The comprehensive analysis of genetic expression allowed confirming that menhaden oil has a protective effect on this nutritional experimental model and identifying 32 genes that could be responsible for that protection, including Gstp1. These results reveal that gene changes could play a role in renal injury.

EPConDB: a web resource for gene expression related to pancreatic development, beta-cell function and diabetes.

PubMed

Mazzarelli, Joan M; Brestelli, John; Gorski, Regina K; Liu, Junmin; Manduchi, Elisabetta; Pinney, Deborah F; Schug, Jonathan; White, Peter; Kaestner, Klaus H; Stoeckert, Christian J

2007-01-01

EPConDB (http://www.cbil.upenn.edu/EPConDB) is a public web site that supports research in diabetes, pancreatic development and beta-cell function by providing information about genes expressed in cells of the pancreas. EPConDB displays expression profiles for individual genes and information about transcripts, promoter elements and transcription factor binding sites. Gene expression results are obtained from studies examining tissue expression, pancreatic development and growth, differentiation of insulin-producing cells, islet or beta-cell injury, and genetic models of impaired beta-cell function. The expression datasets are derived using different microarray platforms, including the BCBC PancChips and Affymetrix gene expression arrays. Other datasets include semi-quantitative RT-PCR and MPSS expression studies. For selected microarray studies, lists of differentially expressed genes, derived from PaGE analysis, are displayed on the site. EPConDB provides database queries and tools to examine the relationship between a gene, its transcriptional regulation, protein function and expression in pancreatic tissues.

Physiologically Shrinking the Solution Space of a Saccharomyces cerevisiae Genome-Scale Model Suggests the Role of the Metabolic Network in Shaping Gene Expression Noise.

PubMed

Chi, Baofang; Tao, Shiheng; Liu, Yanlin

2015-01-01

Sampling the solution space of genome-scale models is generally conducted to determine the feasible region for metabolic flux distribution. Because the region for actual metabolic states resides only in a small fraction of the entire space, it is necessary to shrink the solution space to improve the predictive power of a model. A common strategy is to constrain models by integrating extra datasets such as high-throughput datasets and C13-labeled flux datasets. However, studies refining these approaches by performing a meta-analysis of massive experimental metabolic flux measurements, which are closely linked to cellular phenotypes, are limited. In the present study, experimentally identified metabolic flux data from 96 published reports were systematically reviewed. Several strong associations among metabolic flux phenotypes were observed. These phenotype-phenotype associations at the flux level were quantified and integrated into a Saccharomyces cerevisiae genome-scale model as extra physiological constraints. By sampling the shrunken solution space of the model, the metabolic flux fluctuation level, which is an intrinsic trait of metabolic reactions determined by the network, was estimated and utilized to explore its relationship to gene expression noise. Although no correlation was observed in all enzyme-coding genes, a relationship between metabolic flux fluctuation and expression noise of genes associated with enzyme-dosage sensitive reactions was detected, suggesting that the metabolic network plays a role in shaping gene expression noise. Such correlation was mainly attributed to the genes corresponding to non-essential reactions, rather than essential ones. This was at least partially, due to regulations underlying the flux phenotype-phenotype associations. Altogether, this study proposes a new approach in shrinking the solution space of a genome-scale model, of which sampling provides new insights into gene expression noise.

Microarray-based gene expression profiling in patients with cryopyrin-associated periodic syndromes defines a disease-related signature and IL-1-responsive transcripts.

PubMed

Balow, James E; Ryan, John G; Chae, Jae Jin; Booty, Matthew G; Bulua, Ariel; Stone, Deborah; Sun, Hong-Wei; Greene, James; Barham, Beverly; Goldbach-Mansky, Raphaela; Kastner, Daniel L; Aksentijevich, Ivona

2013-06-01

To analyse gene expression patterns and to define a specific gene expression signature in patients with the severe end of the spectrum of cryopyrin-associated periodic syndromes (CAPS). The molecular consequences of interleukin 1 inhibition were examined by comparing gene expression patterns in 16 CAPS patients before and after treatment with anakinra. We collected peripheral blood mononuclear cells from 22 CAPS patients with active disease and from 14 healthy children. Transcripts that passed stringent filtering criteria (p values≤false discovery rate 1%) were considered as differentially expressed genes (DEG). A set of DEG was validated by quantitative reverse transcription PCR and functional studies with primary cells from CAPS patients and healthy controls. We used 17 CAPS and 66 non-CAPS patient samples to create a set of gene expression models that differentiates CAPS patients from controls and from patients with other autoinflammatory conditions. Many DEG include transcripts related to the regulation of innate and adaptive immune responses, oxidative stress, cell death, cell adhesion and motility. A set of gene expression-based models comprising the CAPS-specific gene expression signature correctly classified all 17 samples from an independent dataset. This classifier also correctly identified 15 of 16 post-anakinra CAPS samples despite the fact that these CAPS patients were in clinical remission. We identified a gene expression signature that clearly distinguished CAPS patients from controls. A number of DEG were in common with other systemic inflammatory diseases such as systemic onset juvenile idiopathic arthritis. The CAPS-specific gene expression classifiers also suggest incomplete suppression of inflammation at low doses of anakinra.

Microarray-based gene expression profiling in patients with cryopyrin-associated periodic syndromes defines a disease-related signature and IL-1-responsive transcripts

PubMed Central

Balow, James E; Ryan, John G; Chae, Jae Jin; Booty, Matthew G; Bulua, Ariel; Stone, Deborah; Sun, Hong-Wei; Greene, James; Barham, Beverly; Goldbach-Mansky, Raphaela; Kastner, Daniel L; Aksentijevich, Ivona

2014-01-01

Objective To analyse gene expression patterns and to define a specific gene expression signature in patients with the severe end of the spectrum of cryopyrin-associated periodic syndromes (CAPS). The molecular consequences of interleukin 1 inhibition were examined by comparing gene expression patterns in 16 CAPS patients before and after treatment with anakinra. Methods We collected peripheral blood mononuclear cells from 22 CAPS patients with active disease and from 14 healthy children. Transcripts that passed stringent filtering criteria (p values ≤ false discovery rate 1%) were considered as differentially expressed genes (DEG). A set of DEG was validated by quantitative reverse transcription PCR and functional studies with primary cells from CAPS patients and healthy controls. We used 17 CAPS and 66 non-CAPS patient samples to create a set of gene expression models that differentiates CAPS patients from controls and from patients with other autoinflammatory conditions. Results Many DEG include transcripts related to the regulation of innate and adaptive immune responses, oxidative stress, cell death, cell adhesion and motility. A set of gene expression-based models comprising the CAPS-specific gene expression signature correctly classified all 17 samples from an independent dataset. This classifier also correctly identified 15 of 16 postanakinra CAPS samples despite the fact that these CAPS patients were in clinical remission. Conclusions We identified a gene expression signature that clearly distinguished CAPS patients from controls. A number of DEG were in common with other systemic inflammatory diseases such as systemic onset juvenile idiopathic arthritis. The CAPS-specific gene expression classifiers also suggest incomplete suppression of inflammation at low doses of anakinra. PMID:23223423

Network regularised Cox regression and multiplex network models to predict disease comorbidities and survival of cancer.

PubMed

Xu, Haoming; Moni, Mohammad Ali; Liò, Pietro

2015-12-01

In cancer genomics, gene expression levels provide important molecular signatures for all types of cancer, and this could be very useful for predicting the survival of cancer patients. However, the main challenge of gene expression data analysis is high dimensionality, and microarray is characterised by few number of samples with large number of genes. To overcome this problem, a variety of penalised Cox proportional hazard models have been proposed. We introduce a novel network regularised Cox proportional hazard model and a novel multiplex network model to measure the disease comorbidities and to predict survival of the cancer patient. Our methods are applied to analyse seven microarray cancer gene expression datasets: breast cancer, ovarian cancer, lung cancer, liver cancer, renal cancer and osteosarcoma. Firstly, we applied a principal component analysis to reduce the dimensionality of original gene expression data. Secondly, we applied a network regularised Cox regression model on the reduced gene expression datasets. By using normalised mutual information method and multiplex network model, we predict the comorbidities for the liver cancer based on the integration of diverse set of omics and clinical data, and we find the diseasome associations (disease-gene association) among different cancers based on the identified common significant genes. Finally, we evaluated the precision of the approach with respect to the accuracy of survival prediction using ROC curves. We report that colon cancer, liver cancer and renal cancer share the CXCL5 gene, and breast cancer, ovarian cancer and renal cancer share the CCND2 gene. Our methods are useful to predict survival of the patient and disease comorbidities more accurately and helpful for improvement of the care of patients with comorbidity. Software in Matlab and R is available on our GitHub page: https://github.com/ssnhcom/NetworkRegularisedCox.git. Copyright © 2015. Published by Elsevier Ltd.

A big data pipeline: Identifying dynamic gene regulatory networks from time-course Gene Expression Omnibus data with applications to influenza infection.

PubMed

Carey, Michelle; Ramírez, Juan Camilo; Wu, Shuang; Wu, Hulin

2018-07-01

A biological host response to an external stimulus or intervention such as a disease or infection is a dynamic process, which is regulated by an intricate network of many genes and their products. Understanding the dynamics of this gene regulatory network allows us to infer the mechanisms involved in a host response to an external stimulus, and hence aids the discovery of biomarkers of phenotype and biological function. In this article, we propose a modeling/analysis pipeline for dynamic gene expression data, called Pipeline4DGEData, which consists of a series of statistical modeling techniques to construct dynamic gene regulatory networks from the large volumes of high-dimensional time-course gene expression data that are freely available in the Gene Expression Omnibus repository. This pipeline has a consistent and scalable structure that allows it to simultaneously analyze a large number of time-course gene expression data sets, and then integrate the results across different studies. We apply the proposed pipeline to influenza infection data from nine studies and demonstrate that interesting biological findings can be discovered with its implementation.

Identifying arsenic trioxide (ATO) functions in leukemia cells by using time series gene expression profiles.

PubMed

Yang, Hong; Lin, Shan; Cui, Jingru

2014-02-10

Arsenic trioxide (ATO) is presently the most active single agent in the treatment of acute promyelocytic leukemia (APL). In order to explore the molecular mechanism of ATO in leukemia cells with time series, we adopted bioinformatics strategy to analyze expression changing patterns and changes in transcription regulation modules of time series genes filtered from Gene Expression Omnibus database (GSE24946). We totally screened out 1847 time series genes for subsequent analysis. The KEGG (Kyoto encyclopedia of genes and genomes) pathways enrichment analysis of these genes showed that oxidative phosphorylation and ribosome were the top 2 significantly enriched pathways. STEM software was employed to compare changing patterns of gene expression with assigned 50 expression patterns. We screened out 7 significantly enriched patterns and 4 tendency charts of time series genes. The result of Gene Ontology showed that functions of times series genes mainly distributed in profiles 41, 40, 39 and 38. Seven genes with positive regulation of cell adhesion function were enriched in profile 40, and presented the same first increased model then decreased model as profile 40. The transcription module analysis showed that they mainly involved in oxidative phosphorylation pathway and ribosome pathway. Overall, our data summarized the gene expression changes in ATO treated K562-r cell lines with time and suggested that time series genes mainly regulated cell adhesive. Furthermore, our result may provide theoretical basis of molecular biology in treating acute promyelocytic leukemia. Copyright © 2013 Elsevier B.V. All rights reserved.

Mapping eQTL Networks with Mixed Graphical Markov Models

PubMed Central

Tur, Inma; Roverato, Alberto; Castelo, Robert

2014-01-01

Expression quantitative trait loci (eQTL) mapping constitutes a challenging problem due to, among other reasons, the high-dimensional multivariate nature of gene-expression traits. Next to the expression heterogeneity produced by confounding factors and other sources of unwanted variation, indirect effects spread throughout genes as a result of genetic, molecular, and environmental perturbations. From a multivariate perspective one would like to adjust for the effect of all of these factors to end up with a network of direct associations connecting the path from genotype to phenotype. In this article we approach this challenge with mixed graphical Markov models, higher-order conditional independences, and q-order correlation graphs. These models show that additive genetic effects propagate through the network as function of gene–gene correlations. Our estimation of the eQTL network underlying a well-studied yeast data set leads to a sparse structure with more direct genetic and regulatory associations that enable a straightforward comparison of the genetic control of gene expression across chromosomes. Interestingly, it also reveals that eQTLs explain most of the expression variability of network hub genes. PMID:25271303

Expression of interferon-induced antiviral genes is delayed in a STAT1 knockout mouse model of Crimean-Congo hemorrhagic fever.

PubMed

Bowick, Gavin C; Airo, Adriana M; Bente, Dennis A

2012-06-19

Crimean Congo hemorrhagic fever (CCHF) is a tick-borne hemorrhagic zoonosis associated with high mortality. Pathogenesis studies and the development of vaccines and antivirals against CCHF have been severely hampered by the lack of suitable animal model. We recently developed and characterized a mature mouse model for CCHF using mice carrying STAT1 knockout (KO). Given the importance of interferons in controlling viral infections, we investigated the expression of interferon pathway-associated genes in KO and wild-type (WT) mice challenged with CCHF virus. We expected that the absence of the STAT1 protein would result in minimal expression of IFN-related genes. Surprisingly, the KO mice showed high levels of IFN-stimulated gene expression, beginning on day 2 post-infection, while in WT mice challenged with virus the same genes were expressed at similar levels on day 1. We conclude that CCHF virus induces similar type I IFN responses in STAT1 KO and WT mice, but the delayed response in the KO mice permits rapid viral dissemination and fatal illness.

Statistical inference for time course RNA-Seq data using a negative binomial mixed-effect model.

PubMed

Sun, Xiaoxiao; Dalpiaz, David; Wu, Di; S Liu, Jun; Zhong, Wenxuan; Ma, Ping

2016-08-26

Accurate identification of differentially expressed (DE) genes in time course RNA-Seq data is crucial for understanding the dynamics of transcriptional regulatory network. However, most of the available methods treat gene expressions at different time points as replicates and test the significance of the mean expression difference between treatments or conditions irrespective of time. They thus fail to identify many DE genes with different profiles across time. In this article, we propose a negative binomial mixed-effect model (NBMM) to identify DE genes in time course RNA-Seq data. In the NBMM, mean gene expression is characterized by a fixed effect, and time dependency is described by random effects. The NBMM is very flexible and can be fitted to both unreplicated and replicated time course RNA-Seq data via a penalized likelihood method. By comparing gene expression profiles over time, we further classify the DE genes into two subtypes to enhance the understanding of expression dynamics. A significance test for detecting DE genes is derived using a Kullback-Leibler distance ratio. Additionally, a significance test for gene sets is developed using a gene set score. Simulation analysis shows that the NBMM outperforms currently available methods for detecting DE genes and gene sets. Moreover, our real data analysis of fruit fly developmental time course RNA-Seq data demonstrates the NBMM identifies biologically relevant genes which are well justified by gene ontology analysis. The proposed method is powerful and efficient to detect biologically relevant DE genes and gene sets in time course RNA-Seq data.

Gene expression profiling in the hippocampus of learned helpless and nonhelpless rats.

PubMed

Kohen, R; Kirov, S; Navaja, G P; Happe, H Kevin; Hamblin, M W; Snoddy, J R; Neumaier, J F; Petty, F

2005-01-01

In the learned helplessness (LH) animal model of depression, failure to attempt escape from avoidable environmental stress, LH, indicates behavioral despair, whereas nonhelpless (NH) behavior reflects behavioral resilience to the effects of environmental stress. Comparing hippocampal gene expression with large-scale oligonucleotide microarrays, we found that stress-resilient (NH) rats, although behaviorally indistinguishable from controls, showed a distinct gene expression profile compared to LH, sham stressed, and naïve control animals. Genes that were confirmed as differentially expressed in the NH group by quantitative PCR strongly correlated in their levels of expression across all four animal groups. Differential expression could not be confirmed at the protein level. We identified several shared degenerate sequence motifs in the 3' untranslated region (3'UTR) of differentially expressed genes that could be a factor in this tight correlation of expression levels among differentially expressed genes.

Gene expression patterns in four brain areas associate with quantitative measure of estrous behavior in dairy cows.

PubMed

Kommadath, Arun; Woelders, Henri; Beerda, Bonne; Mulder, Herman A; de Wit, Agnes A C; Veerkamp, Roel F; te Pas, Marinus F W; Smits, Mari A

2011-04-19

The decline noticed in several fertility traits of dairy cattle over the past few decades is of major concern. Understanding of the genomic factors underlying fertility, which could have potential applications to improve fertility, is very limited. Here, we aimed to identify and study those genes that associated with a key fertility trait namely estrous behavior, among genes expressed in four bovine brain areas (hippocampus, amygdala, dorsal hypothalamus and ventral hypothalamus), either at the start of estrous cycle, or at mid cycle, or regardless of the phase of cycle. An average heat score was calculated for each of 28 primiparous cows in which estrous behavior was recorded for at least two consecutive estrous cycles starting from 30 days post-partum. Gene expression was then measured in brain tissue samples collected from these cows, 14 of which were sacrificed at the start of estrus and 14 around mid cycle. For each brain area, gene expression was modeled as a function of the orthogonally transformed average heat score values using a Bayesian hierarchical mixed model. Genes whose expression patterns showed significant linear or quadratic relationships with heat scores were identified. These included genes expected to be related to estrous behavior as they influence states like socio-sexual behavior, anxiety, stress and feeding motivation (OXT, AVP, POMC, MCHR1), but also genes whose association with estrous behavior is novel and warrants further investigation. Several genes were identified whose expression levels in the bovine brain associated with the level of expression of estrous behavior. The genes OXT and AVP play major roles in regulating estrous behavior in dairy cows. Genes related to neurotransmission and neuronal plasticity are also involved in estrous regulation, with several genes and processes expressed in mid-cycle probably contributing to proper expression of estrous behavior in the next estrus. Studying these genes and the processes they control improves our understanding of the genomic regulation of estrous behavior expression.

Influence of TRAIL gene on biomechanical properties of the human leukemic cell line Jurkat.

PubMed

Yao, Weijuan; Chen, Kai; Wang, Xinjuan; Xie, Lide; Wen, Zongyao; Yan, Zongyi; Chien, Shu

2002-12-01

We cloned the cDNA fragment of human TNF-related apoptosis inducing ligand (TRAIL) into RevTet-On, a Tet-regulated and high-level gene expression system. Making use of the TRAIL gene expression system in Jurkat as a cell model, we studied the influence of TRAIL gene on the biomechanics properties of Jurkat through measuring changes of cellular biomechanics properties before and after the TRAIL gene expression, which was induced by adding tetracycline derivative doxycycline (Dox). The results indicated that the TRAIL gene expression led to significant changes in cellular biomechanics properties. The osmotic fragility increased and the cell stiffness increased after the expression of TRAIL gene. Thus, the apoptosis-inducing TRAIL gene caused significant changes in the biomechanics properties of Jurkat cells.

Selection of appropriate reference genes for RT-qPCR analysis in a streptozotocin-induced Alzheimer's disease model of cynomolgus monkeys (Macaca fascicularis).

PubMed

Park, Sang-Je; Kim, Young-Hyun; Lee, Youngjeon; Kim, Kyoung-Min; Kim, Heui-Soo; Lee, Sang-Rae; Kim, Sun-Uk; Kim, Sang-Hyun; Kim, Ji-Su; Jeong, Kang-Jin; Lee, Kyoung-Min; Huh, Jae-Won; Chang, Kyu-Tae

2013-01-01

Reverse transcription quantitative real-time polymerase chain reaction (RT-qPCR) has been widely used to quantify relative gene expression because of the specificity, sensitivity, and accuracy of this technique. In order to obtain reliable gene expression data from RT-qPCR experiments, it is important to utilize optimal reference genes for the normalization of target gene expression under varied experimental conditions. Previously, we developed and validated a novel icv-STZ cynomolgus monkey model for Alzheimer's disease (AD) research. However, in order to enhance the reliability of this disease model, appropriate reference genes must be selected to allow meaningful analysis of the gene expression levels in the icv-STZ cynomolgus monkey brain. In this study, we assessed the expression stability of 9 candidate reference genes in 2 matched-pair brain samples (5 regions) of control cynomolgus monkeys and those who had received intracerebroventricular injection of streptozotocin (icv-STZ). Three well-known analytical programs geNorm, NormFinder, and BestKeeper were used to choose the suitable reference genes from the total sample group, control group, and icv-STZ group. Combination analysis of the 3 different programs clearly indicated that the ideal reference genes are RPS19 and YWHAZ in the total sample group, GAPDH and RPS19 in the control group, and ACTB and GAPDH in the icv-STZ group. Additionally, we validated the normalization accuracy of the most appropriate reference genes (RPS19 and YWHAZ) by comparison with the least stable gene (TBP) using quantification of the APP and MAPT genes in the total sample group. To the best of our knowledge, this research is the first study to identify and validate the appropriate reference genes in cynomolgus monkey brains. These findings provide useful information for future studies involving the expression of target genes in the cynomolgus monkey.

Transcriptomic correlates of neuron electrophysiological diversity

PubMed Central

Li, Brenna; Crichlow, Cindy-Lee; Mancarci, B. Ogan; Pavlidis, Paul

2017-01-01

How neuronal diversity emerges from complex patterns of gene expression remains poorly understood. Here we present an approach to understand electrophysiological diversity through gene expression by integrating pooled- and single-cell transcriptomics with intracellular electrophysiology. Using neuroinformatics methods, we compiled a brain-wide dataset of 34 neuron types with paired gene expression and intrinsic electrophysiological features from publically accessible sources, the largest such collection to date. We identified 420 genes whose expression levels significantly correlated with variability in one or more of 11 physiological parameters. We next trained statistical models to infer cellular features from multivariate gene expression patterns. Such models were predictive of gene-electrophysiological relationships in an independent collection of 12 visual cortex cell types from the Allen Institute, suggesting that these correlations might reflect general principles relating expression patterns to phenotypic diversity across very different cell types. Many associations reported here have the potential to provide new insights into how neurons generate functional diversity, and correlations of ion channel genes like Gabrd and Scn1a (Nav1.1) with resting potential and spiking frequency are consistent with known causal mechanisms. Our work highlights the promise and inherent challenges in using cell type-specific transcriptomics to understand the mechanistic origins of neuronal diversity. PMID:29069078

Amyloid protein-mediated differential DNA methylation status regulates gene expression in Alzheimer's disease model cell line

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

Sung, Hye Youn; Choi, Eun Nam; Ahn Jo, Sangmee

2011-11-04

Highlights: Black-Right-Pointing-Pointer Genome-wide DNA methylation pattern in Alzheimer's disease model cell line. Black-Right-Pointing-Pointer Integrated analysis of CpG methylation and mRNA expression profiles. Black-Right-Pointing-Pointer Identify three Swedish mutant target genes; CTIF, NXT2 and DDR2 gene. Black-Right-Pointing-Pointer The effect of Swedish mutation on alteration of DNA methylation and gene expression. -- Abstract: The Swedish mutation of amyloid precursor protein (APP-sw) has been reported to dramatically increase beta amyloid production through aberrant cleavage at the beta secretase site, causing early-onset Alzheimer's disease (AD). DNA methylation has been reported to be associated with AD pathogenesis, but the underlying molecular mechanism of APP-sw-mediated epigenetic alterationsmore » in AD pathogenesis remains largely unknown. We analyzed genome-wide interplay between promoter CpG DNA methylation and gene expression in an APP-sw-expressing AD model cell line. To identify genes whose expression was regulated by DNA methylation status, we performed integrated analysis of CpG methylation and mRNA expression profiles, and identified three target genes of the APP-sw mutant; hypomethylated CTIF (CBP80/CBP20-dependent translation initiation factor) and NXT2 (nuclear exporting factor 2), and hypermethylated DDR2 (discoidin domain receptor 2). Treatment with the demethylating agent 5-aza-2 Prime -deoxycytidine restored mRNA expression of these three genes, implying methylation-dependent transcriptional regulation. The profound alteration in the methylation status was detected at the -435, -295, and -271 CpG sites of CTIF, and at the -505 to -341 region in the promoter of DDR2. In the promoter region of NXT2, only one CpG site located at -432 was differentially unmethylated in APP-sw cells. Thus, we demonstrated the effect of the APP-sw mutation on alteration of DNA methylation and subsequent gene expression. This epigenetic regulatory mechanism may contribute to the pathogenesis of AD.« less

Verification and Optimal Control of Context-Sensitive Probabilistic Boolean Networks Using Model Checking and Polynomial Optimization

PubMed Central

Hiraishi, Kunihiko

2014-01-01

One of the significant topics in systems biology is to develop control theory of gene regulatory networks (GRNs). In typical control of GRNs, expression of some genes is inhibited (activated) by manipulating external stimuli and expression of other genes. It is expected to apply control theory of GRNs to gene therapy technologies in the future. In this paper, a control method using a Boolean network (BN) is studied. A BN is widely used as a model of GRNs, and gene expression is expressed by a binary value (ON or OFF). In particular, a context-sensitive probabilistic Boolean network (CS-PBN), which is one of the extended models of BNs, is used. For CS-PBNs, the verification problem and the optimal control problem are considered. For the verification problem, a solution method using the probabilistic model checker PRISM is proposed. For the optimal control problem, a solution method using polynomial optimization is proposed. Finally, a numerical example on the WNT5A network, which is related to melanoma, is presented. The proposed methods provide us useful tools in control theory of GRNs. PMID:24587766

Toxoplasma Gondii Infection of Chicken Embryos Causes Retinal Changes and Modulates HSP90B1 Gene Expression: A Promising Ocular Toxoplasmosis Model.

PubMed

Nasaré, Alex M; Tedesco, Roberto C; Cristovam, Priscila C; Cenedese, Marcos A; Galisteo, Andrés J; Andrade, Heitor F; Gomes, José Álvaro P; Guimarães, Érik V; Barbosa, Helene S; Alonso, Luis G

2015-12-01

HSP90B1 is a gene that codifies heat shock protein 108 (HSP108) that belongs to a group of proteins induced under stress situation, and it has close relation with the nervous system, especially in the retina. Toxoplasma gondii causes ocular toxoplasmosis that has been associated with a late manifestation of the congenital toxoplasmosis although experimental models show that morphological alterations are already present during embryological development. Here, we used 18 eyes of Gallus domesticus embryos in 7th and 20th embryonic days to establish a model of congenital ocular toxoplasmosis, experimentally infected in its fifth day correlating with HSP90B1 gene expression. Embryos' eyes were histologically evaluated, and gene expression was performed by real-time polymerase chain reaction (PCR). Our data showed parasite present in the choroid, unusual migration of retinal pigment epithelium, and chorioretinal scars, and a tendency to a lower expression of the HSP90B1 gene upon experimental infection. This is a promising model to better understand T. gondii etiopathogeny.

Tissue-specific selection of stable reference genes for real-time PCR normalization in an obese rat model.

PubMed

Cabiati, Manuela; Raucci, Serena; Caselli, Chiara; Guzzardi, Maria Angela; D'Amico, Andrea; Prescimone, Tommaso; Giannessi, Daniela; Del Ry, Silvia

2012-06-01

Obesity is a complex pathology with interacting and confounding causes due to the environment, hormonal signaling patterns, and genetic predisposition. At present, the Zucker rat is an eligible genetic model for research on obesity and metabolic syndrome, allowing scrutiny of gene expression profiles. Real-time PCR is the benchmark method for measuring mRNA expressions, but the accuracy and reproducibility of its data greatly depend on appropriate normalization strategies. In the Zucker rat model, no specific reference genes have been identified in myocardium, kidney, and lung, the main organs involved in this syndrome. The aim of this study was to select among ten candidates (Actb, Gapdh, Polr2a, Ywhag, Rpl13a, Sdha, Ppia, Tbp, Hprt1 and Tfrc) a set of reference genes that can be used for the normalization of mRNA expression data obtained by real-time PCR in obese and lean Zucker rats both at fasting and during acute hyperglycemia. The most stable genes in the heart were Sdha, Tbp, and Hprt1; in kidney, Tbp, Actb, and Gapdh were chosen, while Actb, Ywhag, and Sdha were selected as the most stably expressed set for pulmonary tissue. The normalization strategy was used to analyze mRNA expression of tumor necrosis factor α, the main inflammatory mediator in obesity, whose variations were more significant when normalized with the appropriately selected reference genes. The findings obtained in this study underline the importance of having three stably expressed reference gene sets for use in the cardiac, renal, and pulmonary tissues of an experimental model of obese and hyperglycemic Zucker rats.

Transcriptional alterations in the left ventricle of three hypertensive rat models.

PubMed

Cerutti, Catherine; Kurdi, Mazen; Bricca, Giampiero; Hodroj, Wassim; Paultre, Christian; Randon, Jacques; Gustin, Marie-Paule

2006-11-27

Left ventricular hypertrophy (LVH) is commonly associated with hypertension and represents an independent cardiovascular risk factor. The aim of this study was to test the hypothesis that the cardiac overload related to hypertension is associated to a specific gene expression pattern independently of genetic background. Gene expression levels were obtained with microarrays for 15,866 transcripts from RNA of left ventricles from 12-wk-old rats of three hypertensive models [spontaneously hypertensive rat (SHR), Lyon hypertensive rat (LH), and heterozygous TGR(mRen2)27 rat] and their respective controls. More than 60% of the detected transcripts displayed significant changes between the three groups of normotensive rats, showing large interstrain variability. Expression data were analyzed with respect to hypertension, LVH, and chromosomal distribution. Only four genes had significantly modified expression in the three hypertensive models among which a single gene, coding for sialyltransferase 7A, was consistently overexpressed. Correlation analysis between expression data and left ventricular mass index (LVMI) over all rats identified a larger set of genes whose expression was continuously related with LVMI, including known genes associated with cardiac remodeling. Positioning the detected transcripts along the chromosomes pointed out high-density regions mostly located within blood pressure and cardiac mass quantitative trait loci. Although our study could not detect a unique reprogramming of cardiac cells involving specific genes at early stage of LVH, it allowed the identification of some genes associated with LVH regardless of genetic background. This study thus provides a set of potentially important genes contained within restricted chromosomal regions involved in cardiovascular diseases.

Fast and robust group-wise eQTL mapping using sparse graphical models.

PubMed

Cheng, Wei; Shi, Yu; Zhang, Xiang; Wang, Wei

2015-01-16

Genome-wide expression quantitative trait loci (eQTL) studies have emerged as a powerful tool to understand the genetic basis of gene expression and complex traits. The traditional eQTL methods focus on testing the associations between individual single-nucleotide polymorphisms (SNPs) and gene expression traits. A major drawback of this approach is that it cannot model the joint effect of a set of SNPs on a set of genes, which may correspond to hidden biological pathways. We introduce a new approach to identify novel group-wise associations between sets of SNPs and sets of genes. Such associations are captured by hidden variables connecting SNPs and genes. Our model is a linear-Gaussian model and uses two types of hidden variables. One captures the set associations between SNPs and genes, and the other captures confounders. We develop an efficient optimization procedure which makes this approach suitable for large scale studies. Extensive experimental evaluations on both simulated and real datasets demonstrate that the proposed methods can effectively capture both individual and group-wise signals that cannot be identified by the state-of-the-art eQTL mapping methods. Considering group-wise associations significantly improves the accuracy of eQTL mapping, and the successful multi-layer regression model opens a new approach to understand how multiple SNPs interact with each other to jointly affect the expression level of a group of genes.

The Inheritance of Apomixis in Poa pratensis Confirms a Five Locus Model with Differences in Gene Expressivity and PenetranceW⃞

PubMed Central

Matzk, Fritz; Prodanovic, Sanja; Bäumlein, Helmut; Schubert, Ingo

2005-01-01

The genetic control of apomixis was studied in numerous segregating progenies originated from intercrossing and selfing of obligate sexual and facultative apomictic parents in Poa pratensis by means of the flow cytometric seed screen. The data support a novel model with five major genes required to control asexual seed formation: the Apospory initiator (Ait) gene, the Apospory preventer (Apv) gene, a Megaspore development (Mdv) gene, the Parthenogenesis initiator (Pit) gene, and the Parthenogenesis preventer (Ppv) gene. Differences in expressivity and interactions of these genes are responsible for the wide variation of the mode of reproduction. Apospory and parthenogenesis as well as the initiator and preventer genes of these components segregate independently. The genotypes with the highest expressivity of apospory and parthenogenesis were assigned as Ait-/apvapv/Pit-/ppvppv, those with intermediate expressivity as Ait-/Apv-/Pit-/Ppv-, and those with low expressivity as aitait/apvapv/pitpit/ppvppv. Among the self progenies of obligate sexual individuals, plants with a low capacity for apospory and/or parthenogenesis occurred, indicating that the sexual parents were heterozygous for the preventer genes and homozygous for the recessive initiator alleles (aitait/Apv-/pitpit/Ppv-). The dominant allele Ait exhibits incomplete penetrance. The degree of expressivity of apospory and parthenogenesis was constant among several harvest years of F1 plants. PMID:15608334

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.

The Role of Multiple Transcription Factors In Archaeal Gene Expression

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

Charles J. Daniels

2008-09-23

Since the inception of this research program, the project has focused on two central questions: What is the relationship between the 'eukaryal-like' transcription machinery of archaeal cells and its counterparts in eukaryal cells? And, how does the archaeal cell control gene expression using its mosaic of eukaryal core transcription machinery and its bacterial-like transcription regulatory proteins? During the grant period we have addressed these questions using a variety of in vivo approaches and have sought to specifically define the roles of the multiple TATA binding protein (TBP) and TFIIB-like (TFB) proteins in controlling gene expression in Haloferax volcanii. H. volcaniimore » was initially chosen as a model for the Archaea based on the availability of suitable genetic tools; however, later studies showed that all haloarchaea possessed multiple tbp and tfb genes, which led to the proposal that multiple TBP and TFB proteins may function in a manner similar to alternative sigma factors in bacterial cells. In vivo transcription and promoter analysis established a clear relationship between the promoter requirements of haloarchaeal genes and those of the eukaryal RNA polymerase II promoter. Studies on heat shock gene promoters, and the demonstration that specific tfb genes were induced by heat shock, provided the first indication that TFB proteins may direct expression of specific gene families. The construction of strains lacking tbp or tfb genes, coupled with the finding that many of these genes are differentially expressed under varying growth conditions, provided further support for this model. Genetic tools were also developed that led to the construction of insertion and deletion mutants, and a novel gene expression scheme was designed that allowed the controlled expression of these genes in vivo. More recent studies have used a whole genome array to examine the expression of these genes and we have established a linkage between the expression of specific tfb genes and the regulation of nitrogen metabolism and other global cellular responses.« less

Predicting features of breast cancer with gene expression patterns.

PubMed

Lu, Xuesong; Lu, Xin; Wang, Zhigang C; Iglehart, J Dirk; Zhang, Xuegong; Richardson, Andrea L

2008-03-01

Data from gene expression arrays hold an enormous amount of biological information. We sought to determine if global gene expression in primary breast cancers contained information about biologic, histologic, and anatomic features of the disease in individual patients. Microarray data from the tumors of 129 patients were analyzed for the ability to predict biomarkers [estrogen receptor (ER) and HER2], histologic features [grade and lymphatic-vascular invasion (LVI)], and stage parameters (tumor size and lymph node metastasis). Multiple statistical predictors were used and the prediction accuracy was determined by cross-validation error rate; multidimensional scaling (MDS) allowed visualization of the predicted states under study. Models built from gene expression data accurately predict ER and HER2 status, and divide tumor grade into high-grade and low-grade clusters; intermediate-grade tumors are not a unique group. In contrast, gene expression data is inaccurate at predicting tumor size, lymph node status or LVI. The best model for prediction of nodal status included tumor size, LVI status and pathologically defined tumor subtype (based on combinations of ER, HER2, and grade); the addition of microarray-based prediction to this model failed to improve the prediction accuracy. Global gene expression supports a binary division of ER, HER2, and grade, clearly separating tumors into two categories; intermediate values for these bio-indicators do not define intermediate tumor subsets. Results are consistent with a model of regional metastasis that depends on inherent biologic differences in metastatic propensity between breast cancer subtypes, upon which time and chance then operate.

Renal Gene Expression Database (RGED): a relational database of gene expression profiles in kidney disease

PubMed Central

Zhang, Qingzhou; Yang, Bo; Chen, Xujiao; Xu, Jing; Mei, Changlin; Mao, Zhiguo

2014-01-01

We present a bioinformatics database named Renal Gene Expression Database (RGED), which contains comprehensive gene expression data sets from renal disease research. The web-based interface of RGED allows users to query the gene expression profiles in various kidney-related samples, including renal cell lines, human kidney tissues and murine model kidneys. Researchers can explore certain gene profiles, the relationships between genes of interests and identify biomarkers or even drug targets in kidney diseases. The aim of this work is to provide a user-friendly utility for the renal disease research community to query expression profiles of genes of their own interest without the requirement of advanced computational skills. Availability and implementation: Website is implemented in PHP, R, MySQL and Nginx and freely available from http://rged.wall-eva.net. Database URL: http://rged.wall-eva.net PMID:25252782

Renal Gene Expression Database (RGED): a relational database of gene expression profiles in kidney disease.

PubMed

Zhang, Qingzhou; Yang, Bo; Chen, Xujiao; Xu, Jing; Mei, Changlin; Mao, Zhiguo

2014-01-01

We present a bioinformatics database named Renal Gene Expression Database (RGED), which contains comprehensive gene expression data sets from renal disease research. The web-based interface of RGED allows users to query the gene expression profiles in various kidney-related samples, including renal cell lines, human kidney tissues and murine model kidneys. Researchers can explore certain gene profiles, the relationships between genes of interests and identify biomarkers or even drug targets in kidney diseases. The aim of this work is to provide a user-friendly utility for the renal disease research community to query expression profiles of genes of their own interest without the requirement of advanced computational skills. Website is implemented in PHP, R, MySQL and Nginx and freely available from http://rged.wall-eva.net. http://rged.wall-eva.net. © The Author(s) 2014. Published by Oxford University Press.

Length bias correction in gene ontology enrichment analysis using logistic regression.

PubMed

Mi, Gu; Di, Yanming; Emerson, Sarah; Cumbie, Jason S; Chang, Jeff H

2012-01-01

When assessing differential gene expression from RNA sequencing data, commonly used statistical tests tend to have greater power to detect differential expression of genes encoding longer transcripts. This phenomenon, called "length bias", will influence subsequent analyses such as Gene Ontology enrichment analysis. In the presence of length bias, Gene Ontology categories that include longer genes are more likely to be identified as enriched. These categories, however, are not necessarily biologically more relevant. We show that one can effectively adjust for length bias in Gene Ontology analysis by including transcript length as a covariate in a logistic regression model. The logistic regression model makes the statistical issue underlying length bias more transparent: transcript length becomes a confounding factor when it correlates with both the Gene Ontology membership and the significance of the differential expression test. The inclusion of the transcript length as a covariate allows one to investigate the direct correlation between the Gene Ontology membership and the significance of testing differential expression, conditional on the transcript length. We present both real and simulated data examples to show that the logistic regression approach is simple, effective, and flexible.

Learning Gene Expression through Modelling and Argumentation: A Case Study Exploring the Connections between the Worlds of Knowledge

ERIC Educational Resources Information Center

Puig, Blanca; Ageitos, Noa; Jiménez-Aleixandre, María Pilar

2017-01-01

There is emerging interest on the interactions between modelling and argumentation in specific contexts, such as genetics learning. It has been suggested that modelling might help students understand and argue on genetics. We propose modelling gene expression as a way to learn molecular genetics and diseases with a genetic component. The study is…

Metastatic canine mammary carcinomas can be identified by a gene expression profile that partly overlaps with human breast cancer profiles

PubMed Central

2010-01-01

Background Similar to human breast cancer mammary tumors of the female dog are commonly associated with a fatal outcome due to the development of distant metastases. However, the molecular defects leading to metastasis are largely unknown and the value of canine mammary carcinoma as a model for human breast cancer is unclear. In this study, we analyzed the gene expression signatures associated with mammary tumor metastasis and asked for parallels with the human equivalent. Methods Messenger RNA expression profiles of twenty-seven lymph node metastasis positive or negative canine mammary carcinomas were established by microarray analysis. Differentially expressed genes were functionally characterized and associated with molecular pathways. The findings were also correlated with published data on human breast cancer. Results Metastatic canine mammary carcinomas had 1,011 significantly differentially expressed genes when compared to non-metastatic carcinomas. Metastatic carcinomas had a significant up-regulation of genes associated with cell cycle regulation, matrix modulation, protein folding and proteasomal degradation whereas cell differentiation genes, growth factor pathway genes and regulators of actin organization were significantly down-regulated. Interestingly, 265 of the 1,011 differentially expressed canine genes are also related to human breast cancer and, vice versa, parts of a human prognostic gene signature were identified in the expression profiles of the metastatic canine tumors. Conclusions Metastatic canine mammary carcinomas can be discriminated from non-metastatic carcinomas by their gene expression profiles. More than one third of the differentially expressed genes are also described of relevance for human breast cancer. Many of the differentially expressed genes are linked to functions and pathways which appear to be relevant for the induction and maintenance of metastatic progression and may represent new therapeutic targets. Furthermore, dogs are in some aspects suitable as a translational model for human breast tumors in order to identify prognostic molecular signatures and potential therapeutic targets. PMID:21062462

Gene Expression-Based Survival Prediction in Lung Adenocarcinoma: A Multi-Site, Blinded Validation Study

PubMed Central

Shedden, Kerby; Taylor, Jeremy M.G.; Enkemann, Steve A.; Tsao, Ming S.; Yeatman, Timothy J.; Gerald, William L.; Eschrich, Steve; Jurisica, Igor; Venkatraman, Seshan E.; Meyerson, Matthew; Kuick, Rork; Dobbin, Kevin K.; Lively, Tracy; Jacobson, James W.; Beer, David G.; Giordano, Thomas J.; Misek, David E.; Chang, Andrew C.; Zhu, Chang Qi; Strumpf, Dan; Hanash, Samir; Shepherd, Francis A.; Ding, Kuyue; Seymour, Lesley; Naoki, Katsuhiko; Pennell, Nathan; Weir, Barbara; Verhaak, Roel; Ladd-Acosta, Christine; Golub, Todd; Gruidl, Mike; Szoke, Janos; Zakowski, Maureen; Rusch, Valerie; Kris, Mark; Viale, Agnes; Motoi, Noriko; Travis, William; Sharma, Anupama

2009-01-01

Although prognostic gene expression signatures for survival in early stage lung cancer have been proposed, for clinical application it is critical to establish their performance across different subject populations and in different laboratories. Here we report a large, training-testing, multi-site blinded validation study to characterize the performance of several prognostic models based on gene expression for 442 lung adenocarcinomas. The hypotheses proposed examined whether microarray measurements of gene expression either alone or combined with basic clinical covariates (stage, age, sex) can be used to predict overall survival in lung cancer subjects. Several models examined produced risk scores that substantially correlated with actual subject outcome. Most methods performed better with clinical data, supporting the combined use of clinical and molecular information when building prognostic models for early stage lung cancer. This study also provides the largest available set of microarray data with extensive pathological and clinical annotation for lung adenocarcinomas. PMID:18641660

Gene expression during blow fly development: improving the precision of age estimates in forensic entomology.

PubMed

Tarone, Aaron M; Foran, David R

2011-01-01

Forensic entomologists use size and developmental stage to estimate blow fly age, and from those, a postmortem interval. Since such estimates are generally accurate but often lack precision, particularly in the older developmental stages, alternative aging methods would be advantageous. Presented here is a means of incorporating developmentally regulated gene expression levels into traditional stage and size data, with a goal of more precisely estimating developmental age of immature Lucilia sericata. Generalized additive models of development showed improved statistical support compared to models that did not include gene expression data, resulting in an increase in estimate precision, especially for postfeeding third instars and pupae. The models were then used to make blind estimates of development for 86 immature L. sericata raised on rat carcasses. Overall, inclusion of gene expression data resulted in increased precision in aging blow flies. © 2010 American Academy of Forensic Sciences.

DigOut: viewing differential expression genes as outliers.

PubMed

Yu, Hui; Tu, Kang; Xie, Lu; Li, Yuan-Yuan

2010-12-01

With regards to well-replicated two-conditional microarray datasets, the selection of differentially expressed (DE) genes is a well-studied computational topic, but for multi-conditional microarray datasets with limited or no replication, the same task is not properly addressed by previous studies. This paper adopts multivariate outlier analysis to analyze replication-lacking multi-conditional microarray datasets, finding that it performs significantly better than the widely used limit fold change (LFC) model in a simulated comparative experiment. Compared with the LFC model, the multivariate outlier analysis also demonstrates improved stability against sample variations in a series of manipulated real expression datasets. The reanalysis of a real non-replicated multi-conditional expression dataset series leads to satisfactory results. In conclusion, a multivariate outlier analysis algorithm, like DigOut, is particularly useful for selecting DE genes from non-replicated multi-conditional gene expression dataset.

Heterotopic expression of class B floral homeotic genes supports a modified ABC model for tulip (Tulipa gesneriana).

PubMed

Kanno, Akira; Saeki, Hiroshi; Kameya, Toshiaki; Saedler, Heinz; Theissen, Günter

2003-07-01

In higher eudicotyledonous angiosperms the floral organs are typically arranged in four different whorls, containing sepals, petals, stamens and carpels. According to the ABC model, the identity of these organs is specified by floral homeotic genes of class A, A+B, B+C and C, respectively. In contrast to the sepal and petal whorls of eudicots, the perianths of many plants from the Liliaceae family have two outer whorls of almost identical petaloid organs, called tepals. To explain the Liliaceae flower morphology, van Tunen et al. (1993) proposed a modified ABC model, exemplified with tulip. According to this model, class B genes are not only expressed in whorls 2 and 3, but also in whorl 1. Thus the organs of both whorls 1 and 2 express class A plus class B genes and, therefore, get the same petaloid identity. To test this modified ABC model we have cloned and characterized putative class B genes from tulip. Two DEF- and one GLO-like gene were identified, named TGDEFA, TGDEFB and TGGLO. Northern hybridization analysis showed that all of these genes are expressed in whorls 1, 2 and 3 (outer and inner tepals and stamens), thus corroborating the modified ABC model. In addition, these experiments demonstrated that TGGLO is also weakly expressed in carpels, leaves, stems and bracts. Gel retardation assays revealed that TGGLO alone binds to DNA as a homodimer. In contrast, TGDEFA and TGDEFB cannot homodimerize, but make heterodimers with PI. Homodimerization of GLO-like protein has also been reported for lily, suggesting that this phenomenon is conserved within Liliaceae plants or even monocot species.

From genes to milk: genomic organization and epigenetic regulation of the mammary transcriptome.

PubMed

Lemay, Danielle G; Pollard, Katherine S; Martin, William F; Freeman Zadrowski, Courtneay; Hernandez, Joseph; Korf, Ian; German, J Bruce; Rijnkels, Monique

2013-01-01

Even in genomes lacking operons, a gene's position in the genome influences its potential for expression. The mechanisms by which adjacent genes are co-expressed are still not completely understood. Using lactation and the mammary gland as a model system, we explore the hypothesis that chromatin state contributes to the co-regulation of gene neighborhoods. The mammary gland represents a unique evolutionary model, due to its recent appearance, in the context of vertebrate genomes. An understanding of how the mammary gland is regulated to produce milk is also of biomedical and agricultural importance for human lactation and dairying. Here, we integrate epigenomic and transcriptomic data to develop a comprehensive regulatory model. Neighborhoods of mammary-expressed genes were determined using expression data derived from pregnant and lactating mice and a neighborhood scoring tool, G-NEST. Regions of open and closed chromatin were identified by ChIP-Seq of histone modifications H3K36me3, H3K4me2, and H3K27me3 in the mouse mammary gland and liver tissue during lactation. We found that neighborhoods of genes in regions of uniquely active chromatin in the lactating mammary gland, compared with liver tissue, were extremely rare. Rather, genes in most neighborhoods were suppressed during lactation as reflected in their expression levels and their location in regions of silenced chromatin. Chromatin silencing was largely shared between the liver and mammary gland during lactation, and what distinguished the mammary gland was mainly a small tissue-specific repertoire of isolated, expressed genes. These findings suggest that an advantage of the neighborhood organization is in the collective repression of groups of genes via a shared mechanism of chromatin repression. Genes essential to the mammary gland's uniqueness are isolated from neighbors, and likely have less tolerance for variation in expression, properties they share with genes responsible for an organism's survival.

From Genes to Milk: Genomic Organization and Epigenetic Regulation of the Mammary Transcriptome

PubMed Central

Lemay, Danielle G.; Pollard, Katherine S.; Martin, William F.; Freeman Zadrowski, Courtneay; Hernandez, Joseph; Korf, Ian; German, J. Bruce; Rijnkels, Monique

2013-01-01

Even in genomes lacking operons, a gene's position in the genome influences its potential for expression. The mechanisms by which adjacent genes are co-expressed are still not completely understood. Using lactation and the mammary gland as a model system, we explore the hypothesis that chromatin state contributes to the co-regulation of gene neighborhoods. The mammary gland represents a unique evolutionary model, due to its recent appearance, in the context of vertebrate genomes. An understanding of how the mammary gland is regulated to produce milk is also of biomedical and agricultural importance for human lactation and dairying. Here, we integrate epigenomic and transcriptomic data to develop a comprehensive regulatory model. Neighborhoods of mammary-expressed genes were determined using expression data derived from pregnant and lactating mice and a neighborhood scoring tool, G-NEST. Regions of open and closed chromatin were identified by ChIP-Seq of histone modifications H3K36me3, H3K4me2, and H3K27me3 in the mouse mammary gland and liver tissue during lactation. We found that neighborhoods of genes in regions of uniquely active chromatin in the lactating mammary gland, compared with liver tissue, were extremely rare. Rather, genes in most neighborhoods were suppressed during lactation as reflected in their expression levels and their location in regions of silenced chromatin. Chromatin silencing was largely shared between the liver and mammary gland during lactation, and what distinguished the mammary gland was mainly a small tissue-specific repertoire of isolated, expressed genes. These findings suggest that an advantage of the neighborhood organization is in the collective repression of groups of genes via a shared mechanism of chromatin repression. Genes essential to the mammary gland's uniqueness are isolated from neighbors, and likely have less tolerance for variation in expression, properties they share with genes responsible for an organism's survival. PMID:24086428

Gene expression distribution deconvolution in single-cell RNA sequencing.

PubMed

Wang, Jingshu; Huang, Mo; Torre, Eduardo; Dueck, Hannah; Shaffer, Sydney; Murray, John; Raj, Arjun; Li, Mingyao; Zhang, Nancy R

2018-06-26

Single-cell RNA sequencing (scRNA-seq) enables the quantification of each gene's expression distribution across cells, thus allowing the assessment of the dispersion, nonzero fraction, and other aspects of its distribution beyond the mean. These statistical characterizations of the gene expression distribution are critical for understanding expression variation and for selecting marker genes for population heterogeneity. However, scRNA-seq data are noisy, with each cell typically sequenced at low coverage, thus making it difficult to infer properties of the gene expression distribution from raw counts. Based on a reexamination of nine public datasets, we propose a simple technical noise model for scRNA-seq data with unique molecular identifiers (UMI). We develop deconvolution of single-cell expression distribution (DESCEND), a method that deconvolves the true cross-cell gene expression distribution from observed scRNA-seq counts, leading to improved estimates of properties of the distribution such as dispersion and nonzero fraction. DESCEND can adjust for cell-level covariates such as cell size, cell cycle, and batch effects. DESCEND's noise model and estimation accuracy are further evaluated through comparisons to RNA FISH data, through data splitting and simulations and through its effectiveness in removing known batch effects. We demonstrate how DESCEND can clarify and improve downstream analyses such as finding differentially expressed genes, identifying cell types, and selecting differentiation markers. Copyright © 2018 the Author(s). Published by PNAS.

Improved transcription and translation with L-leucine stimulation of mTORC1 in Roberts syndrome.

PubMed

Xu, Baoshan; Gogol, Madelaine; Gaudenz, Karin; Gerton, Jennifer L

2016-01-05

Roberts syndrome (RBS) is a human developmental disorder caused by mutations in the cohesin acetyltransferase ESCO2. We previously reported that mTORC1 signaling was depressed and overall translation was reduced in RBS cells and zebrafish models for RBS. Treatment of RBS cells and zebrafish RBS models with L-leucine partially rescued mTOR function and protein synthesis, correlating with increased cell division and improved development. In this study, we use RBS cells to model mTORC1 repression and analyze transcription and translation with ribosome profiling to determine gene-level effects of L-leucine. L-leucine treatment partially rescued translational efficiency of ribosomal subunits, translation initiation factors, snoRNA production, and mitochondrial function in RBS cells, consistent with these processes being mTORC1 controlled. In contrast, other genes are differentially expressed independent of L-leucine treatment, including imprinted genes such as H19 and GTL2, miRNAs regulated by GTL2, HOX genes, and genes in nucleolar associated domains. Our study distinguishes between gene expression changes in RBS cells that are TOR dependent and those that are independent. Some of the TOR independent gene expression changes likely reflect the architectural role of cohesin in chromatin looping and gene expression. This study reveals the dramatic rescue effects of L-leucine stimulation of mTORC1 in RBS cells and supports that normal gene expression and translation requires ESCO2 function.

VTCdb: a gene co-expression database for the crop species Vitis vinifera (grapevine).

PubMed

Wong, Darren C J; Sweetman, Crystal; Drew, Damian P; Ford, Christopher M

2013-12-16

Gene expression datasets in model plants such as Arabidopsis have contributed to our understanding of gene function and how a single underlying biological process can be governed by a diverse network of genes. The accumulation of publicly available microarray data encompassing a wide range of biological and environmental conditions has enabled the development of additional capabilities including gene co-expression analysis (GCA). GCA is based on the understanding that genes encoding proteins involved in similar and/or related biological processes may exhibit comparable expression patterns over a range of experimental conditions, developmental stages and tissues. We present an open access database for the investigation of gene co-expression networks within the cultivated grapevine, Vitis vinifera. The new gene co-expression database, VTCdb (http://vtcdb.adelaide.edu.au/Home.aspx), offers an online platform for transcriptional regulatory inference in the cultivated grapevine. Using condition-independent and condition-dependent approaches, grapevine co-expression networks were constructed using the latest publicly available microarray datasets from diverse experimental series, utilising the Affymetrix Vitis vinifera GeneChip (16 K) and the NimbleGen Grape Whole-genome microarray chip (29 K), thus making it possible to profile approximately 29,000 genes (95% of the predicted grapevine transcriptome). Applications available with the online platform include the use of gene names, probesets, modules or biological processes to query the co-expression networks, with the option to choose between Affymetrix or Nimblegen datasets and between multiple co-expression measures. Alternatively, the user can browse existing network modules using interactive network visualisation and analysis via CytoscapeWeb. To demonstrate the utility of the database, we present examples from three fundamental biological processes (berry development, photosynthesis and flavonoid biosynthesis) whereby the recovered sub-networks reconfirm established plant gene functions and also identify novel associations. Together, we present valuable insights into grapevine transcriptional regulation by developing network models applicable to researchers in their prioritisation of gene candidates, for on-going study of biological processes related to grapevine development, metabolism and stress responses.

Gene Profiling in Experimental Models of Eye Growth: Clues to Myopia Pathogenesis

PubMed Central

Stone, Richard A.; Khurana, Tejvir S.

2010-01-01

To understand the complex regulatory pathways that underlie the development of refractive errors, expression profiling has evaluated gene expression in ocular tissues of well-characterized experimental models that alter postnatal eye growth and induce refractive errors. Derived from a variety of platforms (e.g. differential display, spotted microarrays or Affymetrix GeneChips), gene expression patterns are now being identified in species that include chicken, mouse and primate. Reconciling available results is hindered by varied experimental designs and analytical/statistical features. Continued application of these methods offers promise to provide the much-needed mechanistic framework to develop therapies to normalize refractive development in children. PMID:20363242

Gene expression analysis of a Helicobacter pylori-infected and high-salt diet-treated mouse gastric tumor model: identification of CD177 as a novel prognostic factor in patients with gastric cancer

PubMed Central

2013-01-01

Background Helicobacter pylori (H. pylori) infection and excessive salt intake are known as important risk factors for stomach cancer in humans. However, interactions of these two factors with gene expression profiles during gastric carcinogenesis remain unclear. In the present study, we investigated the global gene expression associated with stomach carcinogenesis and prognosis of human gastric cancer using a mouse model. Methods To find candidate genes involved in stomach carcinogenesis, we firstly constructed a carcinogen-induced mouse gastric tumor model combined with H. pylori infection and high-salt diet. C57BL/6J mice were given N-methyl-N-nitrosourea in their drinking water and sacrificed after 40 weeks. Animals of a combination group were inoculated with H. pylori and fed a high-salt diet. Gene expression profiles in glandular stomach of the mice were investigated by oligonucleotide microarray. Second, we examined an availability of the candidate gene as prognostic factor for human patients. Immunohistochemical analysis of CD177, one of the up-regulated genes, was performed in human advanced gastric cancer specimens to evaluate the association with prognosis. Results The multiplicity of gastric tumor in carcinogen-treated mice was significantly increased by combination of H. pylori infection and high-salt diet. In the microarray analysis, 35 and 31 more than two-fold up-regulated and down-regulated genes, respectively, were detected in the H. pylori-infection and high-salt diet combined group compared with the other groups. Quantitative RT-PCR confirmed significant over-expression of two candidate genes including Cd177 and Reg3g. On immunohistochemical analysis of CD177 in human advanced gastric cancer specimens, over-expression was evident in 33 (60.0%) of 55 cases, significantly correlating with a favorable prognosis (P = 0.0294). Multivariate analysis including clinicopathological factors as covariates revealed high expression of CD177 to be an independent prognostic factor for overall survival. Conclusions These results suggest that our mouse model combined with H. pylori infection and high-salt diet is useful for gene expression profiling in gastric carcinogenesis, providing evidence that CD177 is a novel prognostic factor for stomach cancer. This is the first report showing a prognostic correlation between CD177 expression and solid tumor behavior. PMID:23899160

Pharmacokinetics and Pharmacodynamics of Curcumin in regulating anti-inflammatory and epigenetic gene expression.

PubMed

Boyanapalli, Sarandeep S S; Huang, Ying; Su, Zhengyuan; Cheng, David; Zhang, Chengyue; Guo, Yue; Rao, Rohit; Androulakis, Ioannis P; Kong, Ah-Ng

2018-06-05

Chronic inflammation is a key driver of cancer development. Nitrite levels, which are regulated by inducible nitric oxide synthase (iNOS), play a critical role in inflammation. While the anti-oxidant and anti-inflammatory effects of curcumin, a natural product present in the roots of Curcuma longa have been widely studied, the acute pharmacokinetics (PK) and pharmacodynamics (PD) of curcumin in suppressing pro-inflammatory markers and epigenetic modulators remain unclear. In this study, we evaluated the PK and PD of curcumin-induced suppression of lipopolysaccharide (LPS)-mediated inflammation in rat lymphocytes. LPS was administered intravenously either alone or with curcumin to female Sprague-Dawley rats. Plasma samples were analyzed for curcumin concentration and mRNA expression was quantified in lymphocytes. Relative gene expression of several inflammatory and epigenetic modulators was analyzed. To investigate the relationship between curcumin concentration and iNOS, TNF-α, and IL-6 gene expression, PK/PD modeling using Jusko's indirect response model (IDR) integrating transit compartments (TC) describing the delayed response was conducted. The concentration-time profile of curcumin exhibited a bi-exponential decline, which was well described by a two-compartmental pharmacokinetic model. Importantly our results demonstrate that LPS induced gene expression of pro-inflammatory markers in lymphocytes, with peak expression at approximately 3 h and curcumin suppressed the gene expression in animals administered with LPS. These effects were well captured using the IDR model and an IDR model with the transit compartments. In summary, the PK/PD modeling approach could potentially provide a robust quantitative framework for evaluating the acute anti-inflammatory and epigenetic effects of curcumin in future clinical trials. This article is protected by copyright. All rights reserved.

Long non-coding RNA expression patterns in lung tissues of chronic cigarette smoke induced COPD mouse model.

PubMed

Zhang, Haiyun; Sun, Dejun; Li, Defu; Zheng, Zeguang; Xu, Jingyi; Liang, Xue; Zhang, Chenting; Wang, Sheng; Wang, Jian; Lu, Wenju

2018-05-15

Long non-coding RNAs (lncRNAs) have critical regulatory roles in protein-coding gene expression. Aberrant expression profiles of lncRNAs have been observed in various human diseases. In this study, we investigated transcriptome profiles in lung tissues of chronic cigarette smoke (CS)-induced COPD mouse model. We found that 109 lncRNAs and 260 mRNAs were significantly differential expressed in lungs of chronic CS-induced COPD mouse model compared with control animals. GO and KEGG analyses indicated that differentially expressed lncRNAs associated protein-coding genes were mainly involved in protein processing of endoplasmic reticulum pathway, and taurine and hypotaurine metabolism pathway. The combination of high throughput data analysis and the results of qRT-PCR validation in lungs of chronic CS-induced COPD mouse model, 16HBE cells with CSE treatment and PBMC from patients with COPD revealed that NR_102714 and its associated protein-coding gene UCHL1 might be involved in the development of COPD both in mouse and human. In conclusion, our study demonstrated that aberrant expression profiles of lncRNAs and mRNAs existed in lungs of chronic CS-induced COPD mouse model. From animal models perspective, these results might provide further clues to investigate biological functions of lncRNAs and their potential target protein-coding genes in the pathogenesis of COPD.

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

Kolker, Eugene

Our project focused primarily on analysis of different types of data produced by global high-throughput technologies, data integration of gene annotation, and gene and protein expression information, as well as on getting a better functional annotation of Shewanella genes. Specifically, four of our numerous major activities and achievements include the development of: statistical models for identification and expression proteomics, superior to currently available approaches (including our own earlier ones); approaches to improve gene annotations on the whole-organism scale; standards for annotation, transcriptomics and proteomics approaches; and generalized approaches for data integration of gene annotation, gene and protein expression information.

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.

Graphical modeling of gene expression in monocytes suggests molecular mechanisms explaining increased atherosclerosis in smokers.

PubMed

Verdugo, Ricardo A; Zeller, Tanja; Rotival, Maxime; Wild, Philipp S; Münzel, Thomas; Lackner, Karl J; Weidmann, Henri; Ninio, Ewa; Trégouët, David-Alexandre; Cambien, François; Blankenberg, Stefan; Tiret, Laurence

2013-01-01

Smoking is a risk factor for atherosclerosis with reported widespread effects on gene expression in circulating blood cells. We hypothesized that a molecular signature mediating the relation between smoking and atherosclerosis may be found in the transcriptome of circulating monocytes. Genome-wide expression profiles and counts of atherosclerotic plaques in carotid arteries were collected in 248 smokers and 688 non-smokers from the general population. Patterns of co-expressed genes were identified by Independent Component Analysis (ICA) and network structure of the pattern-specific gene modules was inferred by the PC-algorithm. A likelihood-based causality test was implemented to select patterns that fit models containing a path "smoking→gene expression→plaques". Robustness of the causal inference was assessed by bootstrapping. At a FDR ≤0.10, 3,368 genes were associated to smoking or plaques, of which 93% were associated to smoking only. SASH1 showed the strongest association to smoking and PPARG the strongest association to plaques. Twenty-nine gene patterns were identified by ICA. Modules containing SASH1 and PPARG did not show evidence for the "smoking→gene expression→plaques" causality model. Conversely, three modules had good support for causal effects and exhibited a network topology consistent with gene expression mediating the relation between smoking and plaques. The network with the strongest support for causal effects was connected to plaques through SLC39A8, a gene with known association to HDL-cholesterol and cellular uptake of cadmium from tobacco, while smoking was directly connected to GAS6, a gene reported to have anti-inflammatory effects in atherosclerosis and to be up-regulated in the placenta of women smoking during pregnancy. Our analysis of the transcriptome of monocytes recovered genes relevant for association to smoking and atherosclerosis, and connected genes that before, were only studied in separate contexts. Inspection of correlation structure revealed candidates that would be missed by expression-phenotype association analysis alone.

Graphical Modeling of Gene Expression in Monocytes Suggests Molecular Mechanisms Explaining Increased Atherosclerosis in Smokers

PubMed Central

Verdugo, Ricardo A.; Zeller, Tanja; Rotival, Maxime; Wild, Philipp S.; Münzel, Thomas; Lackner, Karl J.; Weidmann, Henri; Ninio, Ewa; Trégouët, David-Alexandre; Cambien, François; Blankenberg, Stefan; Tiret, Laurence

2013-01-01

Smoking is a risk factor for atherosclerosis with reported widespread effects on gene expression in circulating blood cells. We hypothesized that a molecular signature mediating the relation between smoking and atherosclerosis may be found in the transcriptome of circulating monocytes. Genome-wide expression profiles and counts of atherosclerotic plaques in carotid arteries were collected in 248 smokers and 688 non-smokers from the general population. Patterns of co-expressed genes were identified by Independent Component Analysis (ICA) and network structure of the pattern-specific gene modules was inferred by the PC-algorithm. A likelihood-based causality test was implemented to select patterns that fit models containing a path “smoking→gene expression→plaques”. Robustness of the causal inference was assessed by bootstrapping. At a FDR ≤0.10, 3,368 genes were associated to smoking or plaques, of which 93% were associated to smoking only. SASH1 showed the strongest association to smoking and PPARG the strongest association to plaques. Twenty-nine gene patterns were identified by ICA. Modules containing SASH1 and PPARG did not show evidence for the “smoking→gene expression→plaques” causality model. Conversely, three modules had good support for causal effects and exhibited a network topology consistent with gene expression mediating the relation between smoking and plaques. The network with the strongest support for causal effects was connected to plaques through SLC39A8, a gene with known association to HDL-cholesterol and cellular uptake of cadmium from tobacco, while smoking was directly connected to GAS6, a gene reported to have anti-inflammatory effects in atherosclerosis and to be up-regulated in the placenta of women smoking during pregnancy. Our analysis of the transcriptome of monocytes recovered genes relevant for association to smoking and atherosclerosis, and connected genes that before, were only studied in separate contexts. Inspection of correlation structure revealed candidates that would be missed by expression-phenotype association analysis alone. PMID:23372645

Global gene expression analysis in a mouse model for Norrie disease: late involvement of photoreceptor cells.

PubMed

Lenzner, Steffen; Prietz, Sandra; Feil, Silke; Nuber, Ulrike A; Ropers, H-Hilger; Berger, Wolfgang

2002-09-01

Mutations in the NDP gene give rise to a variety of eye diseases, including classic Norrie disease (ND), X-linked exudative vitreoretinopathy (EVRX), retinal telangiectasis (Coats disease), and advanced retinopathy of prematurity (ROP). The gene product is a cystine-knot-containing extracellular signaling molecule of unknown function. In the current study, gene expression was determined in a mouse model of ND, to unravel disease-associated mechanisms at the molecular level. Gene transcription in the eyes of 2-year-old Ndp knockout mice was compared with that in the eyes of age-matched wild-type control animals, by means of cDNA subtraction and microarrays. Clones (n = 3072) from the cDNA subtraction libraries were spotted onto glass slides and hybridized with fluorescently labeled RNA-derived targets. More than 230 differentially expressed clones were sequenced, and their expression patterns were verified by virtual Northern blot analysis. Numerous gene transcripts that are absent or downregulated in the eye of Ndp knockout mice are photoreceptor cell specific. In younger Ndp knockout mice (up to 1 year old), however, all these transcripts were found to be expressed at normal levels. The identification of numerous photoreceptor cell-specific transcripts with a reduced expression in 2-year-old, but not in young, Ndp knockout mice indicates that normal gene expression in these light-sensitive cells of mutant mice is established and maintained over a long period and that rods and cones are affected relatively late in the mouse model of ND. Obviously, the absence of the Ndp gene product is not compatible with long-term survival of photoreceptor cells in the mouse.

Gene expression profile associated with superimposed non-alcoholic fatty liver disease and hepatic fibrosis in patients with chronic hepatitis C.

PubMed

Younossi, Zobair M; Afendy, Arian; Stepanova, Maria; Hossain, Noreen; Younossi, Issah; Ankrah, Kathy; Gramlich, Terry; Baranova, Ancha

2009-10-01

Hepatic steatosis occurs in 40-70% of patients chronically infected with hepatitis C virus [chronic hepatitis C (CH-C)]. Hepatic steatosis in CH-C is associated with progressive liver disease and a low response rate to antiviral therapy. Gene expression profiles were examined in CH-C patients with and without hepatic steatosis, non-alcoholic steatohepatitis (NASH) and fibrosis. This study included 65 CH-C patients who were not receiving antiviral treatment. Total RNA was extracted from peripheral blood mononuclear cells, quantified and used for one-step reverse transcriptase-polymerase chain reaction to profile 153 mRNAs that were normalized with six 'housekeeping' genes and a reference RNA. Multiple regression and stepwise selection assessed differences in gene expression and the models' performances were evaluated. Models predicting the grade of hepatic steatosis in patients with CH-C genotype 3 involved two genes: SOCS1 and IFITM1, which progressively changed their expression level with the increasing grade of steatosis. On the other hand, models predicting hepatic steatosis in non-genotype 3 patients highlighted MIP-1 cytokine encoding genes: CCL3 and CCL4 as well as IFNAR and PRKRIR. Expression levels of PRKRIR and SMAD3 differentiated patients with and without superimposed NASH only in the non-genotype 3 cohort (area under the receiver operating characteristic curve=0.822, P-value 0.006]. Gene expression signatures related to hepatic fibrosis were not genotype specific. Gene expression might predict moderate to severe hepatic steatosis, NASH and fibrosis in patients with CH-C, providing potential insights into the pathogenesis of hepatic steatosis and fibrosis in these patients.

Transcriptomic Analysis of Lung Tissue from Cigarette Smoke-Induced Emphysema Murine Models and Human Chronic Obstructive Pulmonary Disease Show Shared and Distinct Pathways.

PubMed

Yun, Jeong H; Morrow, Jarrett; Owen, Caroline A; Qiu, Weiliang; Glass, Kimberly; Lao, Taotao; Jiang, Zhiqiang; Perrella, Mark A; Silverman, Edwin K; Zhou, Xiaobo; Hersh, Craig P

2017-07-01

Although cigarette smoke (CS) is the primary risk factor for chronic obstructive pulmonary disease (COPD), the underlying molecular mechanisms for the significant variability in developing COPD in response to CS are incompletely understood. We performed lung gene expression profiling of two different wild-type murine strains (C57BL/6 and NZW/LacJ) and two genetic models with mutations in COPD genome-wide association study genes (HHIP and FAM13A) after 6 months of chronic CS exposure and compared the results to human COPD lung tissues. We identified gene expression patterns that correlate with severity of emphysema in murine and human lungs. Xenobiotic metabolism and nuclear erythroid 2-related factor 2-mediated oxidative stress response were commonly regulated molecular response patterns in C57BL/6, Hhip +/- , and Fam13a -/- murine strains exposed chronically to CS. The CS-resistant Fam13a -/- mouse and NZW/LacJ strain revealed gene expression response pattern differences. The Fam13a -/- strain diverged in gene expression compared with C57BL/6 control only after CS exposure. However, the NZW/LacJ strain had a unique baseline expression pattern, enriched for nuclear erythroid 2-related factor 2-mediated oxidative stress response and xenobiotic metabolism, and converged to a gene expression pattern similar to the more susceptible wild-type C57BL/6 after CS exposure. These results suggest that distinct molecular pathways may account for resistance to emphysema. Surprisingly, there were few genes commonly modulated in mice and humans. Our study suggests that gene expression responses to CS may be largely species and model dependent, yet shared pathways could provide biologically significant insights underlying individual susceptibility to CS.

Homo sapiens exhibit a distinct pattern of CNV genes regulation: an important role of miRNAs and SNPs in expression plasticity.

PubMed

Dweep, Harsh; Kubikova, Nada; Gretz, Norbert; Voskarides, Konstantinos; Felekkis, Kyriacos

2015-07-16

Gene expression regulation is a complex and highly organized process involving a variety of genomic factors. It is widely accepted that differences in gene expression can contribute to the phenotypic variability between species, and that their interpretation can aid in the understanding of the physiologic variability. CNVs and miRNAs are two major players in the regulation of expression plasticity and may be responsible for the unique phenotypic characteristics observed in different lineages. We have previously demonstrated that a close interaction between these two genomic elements may have contributed to the regulation of gene expression during evolution. This work presents the molecular interactions between CNV and non CNV genes with miRNAs and other genomic elements in eight different species. A comprehensive analysis of these interactions indicates a unique nature of human CNV genes regulation as compared to other species. By using genes with short 3' UTR that abolish the "canonical" miRNA-dependent regulation, as a model, we demonstrate a distinct and tight regulation of human genes that might explain some of the unique features of human physiology. In addition, comparison of gene expression regulation between species indicated that there is a significant difference between humans and mice possibly questioning the effectiveness of the latest as experimental models of human diseases.

Homo sapiens exhibit a distinct pattern of CNV genes regulation: an important role of miRNAs and SNPs in expression plasticity

PubMed Central

Dweep, Harsh; Kubikova, Nada; Gretz, Norbert; Voskarides, Konstantinos; Felekkis, Kyriacos

2015-01-01

Gene expression regulation is a complex and highly organized process involving a variety of genomic factors. It is widely accepted that differences in gene expression can contribute to the phenotypic variability between species, and that their interpretation can aid in the understanding of the physiologic variability. CNVs and miRNAs are two major players in the regulation of expression plasticity and may be responsible for the unique phenotypic characteristics observed in different lineages. We have previously demonstrated that a close interaction between these two genomic elements may have contributed to the regulation of gene expression during evolution. This work presents the molecular interactions between CNV and non CNV genes with miRNAs and other genomic elements in eight different species. A comprehensive analysis of these interactions indicates a unique nature of human CNV genes regulation as compared to other species. By using genes with short 3′ UTR that abolish the “canonical” miRNA-dependent regulation, as a model, we demonstrate a distinct and tight regulation of human genes that might explain some of the unique features of human physiology. In addition, comparison of gene expression regulation between species indicated that there is a significant difference between humans and mice possibly questioning the effectiveness of the latest as experimental models of human diseases. PMID:26178010

Differential Gene Expression (DEX) and Alternative Splicing Events (ASE) for Temporal Dynamic Processes Using HMMs and Hierarchical Bayesian Modeling Approaches.

PubMed

Oh, Sunghee; Song, Seongho

2017-01-01

In gene expression profile, data analysis pipeline is categorized into four levels, major downstream tasks, i.e., (1) identification of differential expression; (2) clustering co-expression patterns; (3) classification of subtypes of samples; and (4) detection of genetic regulatory networks, are performed posterior to preprocessing procedure such as normalization techniques. To be more specific, temporal dynamic gene expression data has its inherent feature, namely, two neighboring time points (previous and current state) are highly correlated with each other, compared to static expression data which samples are assumed as independent individuals. In this chapter, we demonstrate how HMMs and hierarchical Bayesian modeling methods capture the horizontal time dependency structures in time series expression profiles by focusing on the identification of differential expression. In addition, those differential expression genes and transcript variant isoforms over time detected in core prerequisite steps can be generally further applied in detection of genetic regulatory networks to comprehensively uncover dynamic repertoires in the aspects of system biology as the coupled framework.

Reciprocal transcriptional regulation of metabolic and signaling pathways correlates with disease severity in heart failure.

PubMed

Barth, Andreas S; Kumordzie, Ami; Frangakis, Constantine; Margulies, Kenneth B; Cappola, Thomas P; Tomaselli, Gordon F

2011-10-01

Systolic heart failure (HF) is a complex systemic syndrome that can result from a wide variety of clinical conditions and gene mutations. Despite phenotypic similarities, characterized by ventricular dilatation and reduced contractility, the extent of common and divergent gene expression between different forms of HF remains a matter of intense debate. Using a meta-analysis of 28 experimental (mouse, rat, dog) and human HF microarray studies, we demonstrate that gene expression changes are characterized by a coordinated and reciprocal regulation of major metabolic and signaling pathways. In response to a wide variety of stressors in animal models of HF, including ischemia, pressure overload, tachypacing, chronic isoproterenol infusion, Chagas disease, and transgenic mouse models, major metabolic pathways are invariably downregulated, whereas cell signaling pathways are upregulated. In contrast to this uniform transcriptional pattern that recapitulates a fetal gene expression program in experimental animal models of HF, human HF microarray studies displayed a greater heterogeneity, with some studies even showing upregulation of metabolic and downregulation of signaling pathways in end-stage human hearts. These discrepant results between animal and human studies are due to a number of factors, prominently cardiac disease and variable exposure to cold cardioplegic solution in nonfailing human samples, which can downregulate transcripts involved in oxidative phosphorylation (OXPHOS), thus mimicking gene expression patterns observed in failing samples. Additionally, β-blockers and ACE inhibitor use in end-stage human HF was associated with higher levels of myocardial OXPHOS transcripts, thus partially reversing the fetal gene expression pattern. In human failing samples, downregulation of metabolism was associated with hemodynamic markers of disease severity. Irrespective of the etiology, gene expression in failing myocardium is characterized by downregulation of metabolic transcripts and concomitant upregulation of cell signaling pathways. Gene expression changes along this metabolic-signaling axis in mammalian myocardium are a consistent feature in the heterogeneous transcriptional response observed in phenotypically similar models of HF.

Gene Expression Profile of NF-κB, Nrf2, Glycolytic, and p53 Pathways During the SH-SY5Y Neuronal Differentiation Mediated by Retinoic Acid.

PubMed

de Bittencourt Pasquali, Matheus Augusto; de Ramos, Vitor Miranda; Albanus, Ricardo D Oliveira; Kunzler, Alice; de Souza, Luis Henrinque Trentin; Dalmolin, Rodrigo Juliani Siqueira; Gelain, Daniel Pens; Ribeiro, Leila; Carro, Luigi; Moreira, José Cláudio Fonseca

2016-01-01

SH-SY5Y cells, a neuroblastoma cell line that is a well-established model system to study the initial phases of neuronal differentiation, have been used in studies to elucidate the mechanisms of neuronal differentiation. In the present study, we investigated alterations of gene expression in SH-SY5Y cells during neuronal differentiation mediated by retinoic acid (RA) treatment. We evaluated important pathways involving nuclear factor kappa B (NF-κB), nuclear E2-related factor 2 (Nrf2), glycolytic, and p53 during neuronal differentiation. We also investigated the involvement of reactive oxygen species (ROS) in modulating the gene expression profile of those pathways by antioxidant co-treatment with Trolox®, a hydrophilic analogue of α-tocopherol. We found that RA treatment increases levels of gene expression of NF-κB, glycolytic, and antioxidant pathway genes during neuronal differentiation of SH-SY5Y cells. We also found that ROS production induced by RA treatment in SH-SY5Y cells is involved in gene expression profile alterations, chiefly in NF-κB, and glycolytic pathways. Antioxidant co-treatment with Trolox® reversed the effects mediated by RA NF-κB, and glycolytic pathways gene expression. Interestingly, co-treatment with Trolox® did not reverse the effects in antioxidant gene expression mediated by RA in SH-SY5Y. To confirm neuronal differentiation, we quantified endogenous levels of tyrosine hydroxylase, a recognized marker of neuronal differentiation. Our data suggest that during neuronal differentiation mediated by RA, changes in profile gene expression of important pathways occur. These alterations are in part mediated by ROS production. Therefore, our results reinforce the importance in understanding the mechanism by which RA induces neuronal differentiation in SH-SY5Y cells, principally due this model being commonly used as a neuronal cell model in studies of neuronal pathologies.

Novel Dedifferentiated Liposarcoma Xenograft Models Reveal PTEN Down-Regulation as a Malignant Signature and Response to PI3K Pathway Inhibition

PubMed Central

Smith, Kathleen B.; Tran, Linh M.; Tam, Brenna M.; Shurell, Elizabeth M.; Li, Yunfeng; Braas, Daniel; Tap, William D.; Christofk, Heather R.; Dry, Sarah M.; Eilber, Fritz C.; Wu, Hong

2014-01-01

Liposarcoma is a type of soft tissue sarcoma that exhibits poor survival and a high recurrence rate. Treatment is generally limited to surgery and radiation, which emphasizes the need for better understanding of this disease. Because very few in vivo and in vitro models can reproducibly recapitulate the human disease, we generated several xenograft models from surgically resected human dedifferentiated liposarcoma. All xenografts recapitulated morphological and gene expression characteristics of the patient tumors after continuous in vivo passages. Importantly, xenograftability was directly correlated with disease-specific survival of liposarcoma patients. Thus, the ability for the tumor of a patient to engraft may help identify those patients who will benefit from more aggressive treatment regimens. Gene expression analyses highlighted the association between xenograftability and a unique gene expression signature, including down-regulated PTEN tumor-suppressor gene expression and a progenitor-like phenotype. When treated with the PI3K/AKT/mTOR pathway inhibitor rapamycin alone or in combination with the multikinase inhibitor sorafenib, all xenografts responded with increased lipid content and a more differentiated gene expression profile. These human xenograft models may facilitate liposarcoma research and accelerate the generation of readily translatable preclinical data that could ultimately influence patient care. PMID:23416162

[Joint effects of water temperature and salinity on the expression of gill Hsp70 gene in Pinctada martensii (Dunker)].

PubMed

Wang, Ya-Nan; Wang, Hui; Zhu, Xiao-Wen; Luo, Ming-Ming; Liu, Zhi-Gang; Du, Xiao-Dong

2012-12-01

By using central composite experimental design and response surface method, the joint effects of water temperature (16-40 degrees C) and salinity (10-50) on the expression of gill Hsp70 gene in Pinctada martensii (Dunker) were studied under laboratory conditions. The results showed that the linear and quadratic effects of temperature on the expression of gill Hsp70 gene were significant, the linear effect of salinity was not significant, while the quadratic effect of salinity was significant. The interactive effect of temperature and salinity was not significant, and the effect of temperature was greater than that of salinity. The model equation of the gill Hsp70 gene expression was established, with the R2, Adj. R2, and Pred. R2 as high as 98.7%, 97.4%, and 89.2%, respectively, suggesting that the overarching predictive capability of the model was very satisfactory, and could be practicably applied for prediction. Through the optimization of the model, the expression of the gill Hsp70 gene reached its minimum (0.5276) when the temperature was 26.78 degrees C and the salinity was 29.33, with the desirability value being 98%. These experimental results could offer theoretical reference for the high expression of gill Hsp70 gene in P. martensii, the maintenance of cell internal environment stability, and the enhancement of P. martensii stress resistance.

[Establishment of an iRFP and luciferase dual-color fluorescence-traced hepatocellular carcinoma transplantation model in nude mice].

PubMed

Li, Hongjun; Yang, Tianhua; Huang, Yanping; Liu, Mingzhu; Qin, Zhongqiang; Chu, Fei; Li, Zhenghong; Li, Yonghai

2017-11-01

Objective To establish a hepatocellular carcinoma xenograft model in nude mice which could stably express gene and be monitored dynamically. Methods We first constructed the lentiviral particles containing luciferase (Luc) and near-infrared fluorescent protein (iRFP) and puromycin resistance gene, and then transduced them into the HepG2 hepatoma cells. The cell line stably expressing Luc and iRFP genes were screened and inoculated into nude mice to establish xenograft tumor model. Tumor growth was monitored using in vivo imaging system. HE staining and immunohistochemistry were used to evaluate the pathological features and tumorigenic ability. Results HepG2 cells stably expressing iRFP and Luc were obtained; with the engineered cell line, xenograft model was successfully established with the features of proper tumor developing time and high rate of tumor formation as well as typical pathological features as showed by HE staining and immunohistochemistry. Conclusion Hepatocellular carcinoma model in nude mice with the features of stable gene expression and dynamical monitoring has been established successfully with the HepG2-iRFP-Luc cell line.

Angiogenesis-related gene expression analysis in celiac disease.

PubMed

Castellanos-Rubio, Ainara; Caja, Sergio; Irastorza, Iñaki; Fernandez-Jimenez, Nora; Plaza-Izurieta, Leticia; Vitoria, Juan Carlos; Maki, Markku; Lindfors, Katri; Bilbao, Jose Ramon

2012-05-01

Celiac disease (CD) involves disturbance of the small-bowel mucosal vascular network, and transglutaminase autoantibodies (TGA) have been related to angiogenesis disturbance, a complex phenomenon probably also influenced by common genetic variants in angiogenesis-related genes. A set of genes with "angiogenesis" GO term identified in a previous expression microarray experiment (SCG2, STAB1, TGFA, ANG, ERBB2, GNA13, PML, CASP8, ECGF1, JAG1, HIF1A, TNFSF13 and TGM2) was selected for genetic and functional studies. SNPs that showed a trend for association with CD in the first GWAS were genotyped in 555 patients and 541 controls. Gene expression of all genes was quantified in 15 pairs of intestinal biopsies (diagnosis vs. GFD) and in three-dimensional HUVEC and T84 cell cultures incubated with TGA-positive and negative serum. A regulatory SNP in TNFSF13 (rs11552708) is associated with CD (p = 0.01, OR = 0.7). Expression changes in biopsies pointed to TGM2 and PML as up-regulated antiangiogenic genes and to GNA13, TGFA, ERBB2 and SCG2 as down-regulated proangiogenic factors in CD. TGA seem to enhance TGM2 expression in both cell models, but PML expression was induced only in T84 enterocytes while GNA13 and ERBB2 were repressed in HUVEC endothelial cells, with several genes showing discordant effects in each model, highlighting the complexity of gene interactions in the pathogenesis of CD. Finally, cell culture models are useful tools to help dissect complex responses observed in human explants.

Global molecular changes in a tibial compression induced ACL rupture model of post-traumatic osteoarthritis.

PubMed

Chang, Jiun C; Sebastian, Aimy; Murugesh, Deepa K; Hatsell, Sarah; Economides, Aris N; Christiansen, Blaine A; Loots, Gabriela G

2017-03-01

Joint injury causes post-traumatic osteoarthritis (PTOA). About ∼50% of patients rupturing their anterior cruciate ligament (ACL) will develop PTOA within 1-2 decades of the injury, yet the mechanisms responsible for the development of PTOA after joint injury are not well understood. In this study, we examined whole joint gene expression by RNA sequencing (RNAseq) at 1 day, 1-, 6-, and 12 weeks post injury, in a non-invasive tibial compression (TC) overload mouse model of PTOA that mimics ACL rupture in humans. We identified 1446 genes differentially regulated between injured and contralateral joints. This includes known regulators of osteoarthritis such as MMP3, FN1, and COMP, and several new genes including Suco, Sorcs2, and Medag. We also identified 18 long noncoding RNAs that are differentially expressed in the injured joints. By comparing our data to gene expression data generated using the surgical destabilization of the medial meniscus (DMM) PTOA model, we identified several common genes and shared mechanisms. Our study highlights several differences between these two models and suggests that the TC model may be a more rapidly progressing model of PTOA. This study provides the first account of gene expression changes associated with PTOA development and progression in a TC model. © 2016 The Authors. Journal of Orthopaedic Research Published by Wiley Periodicals, Inc. J Orthop Res 35:474-485, 2017. © 2016 The Authors. Journal of Orthopaedic Research Published by Wiley Periodicals, Inc.

Global molecular changes in a tibial compression induced ACL rupture model of post‐traumatic osteoarthritis

PubMed Central

Chang, Jiun C.; Sebastian, Aimy; Murugesh, Deepa K.; Hatsell, Sarah; Economides, Aris N.; Christiansen, Blaine A.

2016-01-01

ABSTRACT Joint injury causes post‐traumatic osteoarthritis (PTOA). About ∼50% of patients rupturing their anterior cruciate ligament (ACL) will develop PTOA within 1–2 decades of the injury, yet the mechanisms responsible for the development of PTOA after joint injury are not well understood. In this study, we examined whole joint gene expression by RNA sequencing (RNAseq) at 1 day, 1‐, 6‐, and 12 weeks post injury, in a non‐invasive tibial compression (TC) overload mouse model of PTOA that mimics ACL rupture in humans. We identified 1446 genes differentially regulated between injured and contralateral joints. This includes known regulators of osteoarthritis such as MMP3, FN1, and COMP, and several new genes including Suco, Sorcs2, and Medag. We also identified 18 long noncoding RNAs that are differentially expressed in the injured joints. By comparing our data to gene expression data generated using the surgical destabilization of the medial meniscus (DMM) PTOA model, we identified several common genes and shared mechanisms. Our study highlights several differences between these two models and suggests that the TC model may be a more rapidly progressing model of PTOA. This study provides the first account of gene expression changes associated with PTOA development and progression in a TC model. © 2016 The Authors. Journal of Orthopaedic Research Published by Wiley Periodicals, Inc. J Orthop Res 35:474–485, 2017. PMID:27088242

An Unexpected Function of the Prader-Willi Syndrome Imprinting Center in Maternal Imprinting in Mice

PubMed Central

Wu, Mei-Yi; Jiang, Ming; Zhai, Xiaodong; Beaudet, Arthur L.; Wu, Ray-Chang

2012-01-01

Genomic imprinting is a phenomenon that some genes are expressed differentially according to the parent of origin. Prader-Willi syndrome (PWS) and Angelman syndrome (AS) are neurobehavioral disorders caused by deficiency of imprinted gene expression from paternal and maternal chromosome 15q11–q13, respectively. Imprinted genes at the PWS/AS domain are regulated through a bipartite imprinting center, the PWS-IC and AS-IC. The PWS-IC activates paternal-specific gene expression and is responsible for the paternal imprint, whereas the AS-IC functions in the maternal imprint by allele-specific repression of the PWS-IC to prevent the paternal imprinting program. Although mouse chromosome 7C has a conserved PWS/AS imprinted domain, the mouse equivalent of the human AS-IC element has not yet been identified. Here, we suggest another dimension that the PWS-IC also functions in maternal imprinting by negatively regulating the paternally expressed imprinted genes in mice, in contrast to its known function as a positive regulator for paternal-specific gene expression. Using a mouse model carrying a 4.8-kb deletion at the PWS-IC, we demonstrated that maternal transmission of the PWS-IC deletion resulted in a maternal imprinting defect with activation of the paternally expressed imprinted genes and decreased expression of the maternally expressed imprinted gene on the maternal chromosome, accompanied by alteration of the maternal epigenotype toward a paternal state spread over the PWS/AS domain. The functional significance of this acquired paternal pattern of gene expression was demonstrated by the ability to complement PWS phenotypes by maternal inheritance of the PWS-IC deletion, which is in stark contrast to paternal inheritance of the PWS-IC deletion that resulted in the PWS phenotypes. Importantly, low levels of expression of the paternally expressed imprinted genes are sufficient to rescue postnatal lethality and growth retardation in two PWS mouse models. These findings open the opportunity for a novel approach to the treatment of PWS. PMID:22496793

An unexpected function of the Prader-Willi syndrome imprinting center in maternal imprinting in mice.

PubMed

Wu, Mei-Yi; Jiang, Ming; Zhai, Xiaodong; Beaudet, Arthur L; Wu, Ray-Chang

2012-01-01

Genomic imprinting is a phenomenon that some genes are expressed differentially according to the parent of origin. Prader-Willi syndrome (PWS) and Angelman syndrome (AS) are neurobehavioral disorders caused by deficiency of imprinted gene expression from paternal and maternal chromosome 15q11-q13, respectively. Imprinted genes at the PWS/AS domain are regulated through a bipartite imprinting center, the PWS-IC and AS-IC. The PWS-IC activates paternal-specific gene expression and is responsible for the paternal imprint, whereas the AS-IC functions in the maternal imprint by allele-specific repression of the PWS-IC to prevent the paternal imprinting program. Although mouse chromosome 7C has a conserved PWS/AS imprinted domain, the mouse equivalent of the human AS-IC element has not yet been identified. Here, we suggest another dimension that the PWS-IC also functions in maternal imprinting by negatively regulating the paternally expressed imprinted genes in mice, in contrast to its known function as a positive regulator for paternal-specific gene expression. Using a mouse model carrying a 4.8-kb deletion at the PWS-IC, we demonstrated that maternal transmission of the PWS-IC deletion resulted in a maternal imprinting defect with activation of the paternally expressed imprinted genes and decreased expression of the maternally expressed imprinted gene on the maternal chromosome, accompanied by alteration of the maternal epigenotype toward a paternal state spread over the PWS/AS domain. The functional significance of this acquired paternal pattern of gene expression was demonstrated by the ability to complement PWS phenotypes by maternal inheritance of the PWS-IC deletion, which is in stark contrast to paternal inheritance of the PWS-IC deletion that resulted in the PWS phenotypes. Importantly, low levels of expression of the paternally expressed imprinted genes are sufficient to rescue postnatal lethality and growth retardation in two PWS mouse models. These findings open the opportunity for a novel approach to the treatment of PWS.

Developmental stage related patterns of codon usage and genomic GC content: searching for evolutionary fingerprints with models of stem cell differentiation

PubMed Central

2007-01-01

Background The usage of synonymous codons shows considerable variation among mammalian genes. How and why this usage is non-random are fundamental biological questions and remain controversial. It is also important to explore whether mammalian genes that are selectively expressed at different developmental stages bear different molecular features. Results In two models of mouse stem cell differentiation, we established correlations between codon usage and the patterns of gene expression. We found that the optimal codons exhibited variation (AT- or GC-ending codons) in different cell types within the developmental hierarchy. We also found that genes that were enriched (developmental-pivotal genes) or specifically expressed (developmental-specific genes) at different developmental stages had different patterns of codon usage and local genomic GC (GCg) content. Moreover, at the same developmental stage, developmental-specific genes generally used more GC-ending codons and had higher GCg content compared with developmental-pivotal genes. Further analyses suggest that the model of translational selection might be consistent with the developmental stage-related patterns of codon usage, especially for the AT-ending optimal codons. In addition, our data show that after human-mouse divergence, the influence of selective constraints is still detectable. Conclusion Our findings suggest that developmental stage-related patterns of gene expression are correlated with codon usage (GC3) and GCg content in stem cell hierarchies. Moreover, this paper provides evidence for the influence of natural selection at synonymous sites in the mouse genome and novel clues for linking the molecular features of genes to their patterns of expression during mammalian ontogenesis. PMID:17349061

Applications of Gene Targeting Technology to Mental Retardation and Developmental Disability Research

ERIC Educational Resources Information Center

Pimenta, Aurea F.; Levitt, Pat

2005-01-01

The human and mouse genome projects elucidated the sequence and position map of innumerous genes expressed in the central nervous system (CNS), advancing our ability to manipulate these sequences and create models to investigate regulation of gene expression and function. In this article, we reviewed gene targeting methodologies with emphasis on…

Transcriptome assembly and digital gene expression atlas of the rainbow trout

USDA-ARS?s Scientific Manuscript database

Background: Transcriptome analysis is a preferred method for gene discovery, marker development and gene expression profiling in non-model organisms. Previously, we sequenced a transcriptome reference using Sanger-based and 454-pyrosequencing, however, a transcriptome assembly is still incomplete an...

p53 Mediates Vast Gene Expression Changes That Contribute to Poor Chemotherapeutic Response in a Mouse Model of Breast Cancer.

PubMed

Tonnessen-Murray, Crystal; Ungerleider, Nathan A; Rao, Sonia G; Wasylishen, Amanda R; Frey, Wesley D; Jackson, James G

2018-05-28

p53 is a transcription factor that regulates expression of genes involved in cell cycle arrest, senescence, and apoptosis. TP53 harbors mutations that inactivate its transcriptional activity in roughly 30% of breast cancers, and these tumors are much more likely to undergo a pathological complete response to chemotherapy. Thus, the gene expression program activated by wild-type p53 contributes to a poor response. We used an in vivo genetic model system to comprehensively define the p53- and p21-dependent genes and pathways modulated in tumors following doxorubicin treatment. We identified genes differentially expressed in spontaneous mammary tumors harvested from treated MMTV-Wnt1 mice that respond poorly (Trp53+/+) or favorably (Trp53-null) and those that lack the critical senescence/arrest p53 target gene Cdkn1a. Trp53 wild-type tumors differentially expressed nearly 10-fold more genes than Trp53-null tumors after treatment. Pathway analyses showed that genes involved in cell cycle, senescence, and inflammation were enriched in treated Trp53 wild-type tumors; however, no genes/pathways were identified that adequately explain the superior cell death/tumor regression observed in Trp53-null tumors. Cdkn1a-null tumors that retained arrest capacity (responded poorly) and those that proliferated (responded well) after treatment had remarkably different gene regulation. For instance, Cdkn1a-null tumors that arrested upregulated Cdkn2a (p16), suggesting an alternative, p21-independent route to arrest. Live animal imaging of longitudinal gene expression of a senescence/inflammation gene reporter in Trp53+/+ tumors showed induction during and after chemotherapy treatment, while tumors were arrested, but expression rapidly diminished immediately upon relapse. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.

DREISS: Using State-Space Models to Infer the Dynamics of Gene Expression Driven by External and Internal Regulatory Networks

PubMed Central

Gerstein, Mark

2016-01-01

Gene expression is controlled by the combinatorial effects of regulatory factors from different biological subsystems such as general transcription factors (TFs), cellular growth factors and microRNAs. A subsystem’s gene expression may be controlled by its internal regulatory factors, exclusively, or by external subsystems, or by both. It is thus useful to distinguish the degree to which a subsystem is regulated internally or externally–e.g., how non-conserved, species-specific TFs affect the expression of conserved, cross-species genes during evolution. We developed a computational method (DREISS, dreiss.gerteinlab.org) for analyzing the Dynamics of gene expression driven by Regulatory networks, both External and Internal based on State Space models. Given a subsystem, the “state” and “control” in the model refer to its own (internal) and another subsystem’s (external) gene expression levels. The state at a given time is determined by the state and control at a previous time. Because typical time-series data do not have enough samples to fully estimate the model’s parameters, DREISS uses dimensionality reduction, and identifies canonical temporal expression trajectories (e.g., degradation, growth and oscillation) representing the regulatory effects emanating from various subsystems. To demonstrate capabilities of DREISS, we study the regulatory effects of evolutionarily conserved vs. divergent TFs across distant species. In particular, we applied DREISS to the time-series gene expression datasets of C. elegans and D. melanogaster during their embryonic development. We analyzed the expression dynamics of the conserved, orthologous genes (orthologs), seeing the degree to which these can be accounted for by orthologous (internal) versus species-specific (external) TFs. We found that between two species, the orthologs have matched, internally driven expression patterns but very different externally driven ones. This is particularly true for genes with evolutionarily ancient functions (e.g. the ribosomal proteins), in contrast to those with more recently evolved functions (e.g., cell-cell communication). This suggests that despite striking morphological differences, some fundamental embryonic-developmental processes are still controlled by ancient regulatory systems. PMID:27760135

Host-Specific Response to HCV Infection in the Chimeric SCID-beige/Alb-uPA Mouse Model: Role of the Innate Antiviral Immune Response

PubMed Central

Thompson, Jill C; Smith, Maria W; Yeh, Matthew M; Proll, Sean; Zhu, Lin-Fu; Gao, T. J; Kneteman, Norman M; Tyrrell, D. Lorne; Katze, Michael G

2006-01-01

The severe combined immunodeficiency disorder (SCID)-beige/albumin (Alb)-urokinase plasminogen activator (uPA) mouse containing a human-mouse chimeric liver is currently the only small animal model capable of supporting hepatitis C virus (HCV) infection. This model was utilized to characterize the host transcriptional response to HCV infection. The purpose of these studies was to investigate the genetic component of the host response to HCV infection and also to distinguish virus-induced gene expression changes from adaptive HCV-specific immune-mediated effects. Gene expression profiles from HCV-infected mice were also compared to those from HCV-infected patients. Analyses of the gene expression data demonstrate that host factors regulate the response to HCV infection, including the nature of the innate antiviral immune response. They also indicate that HCV mediates gene expression changes, including regulation of lipid metabolism genes, which have the potential to be directly cytopathic, indicating that liver pathology may not be exclusively mediated by HCV-specific adaptive immune responses. This effect appears to be inversely related to the activation of the innate antiviral immune response. In summary, the nature of the initial interferon response to HCV infection may determine the extent of viral-mediated effects on host gene expression. PMID:16789836

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

Genome-wide expression profiling of five mouse models identifies similarities and differences with human psoriasis.

PubMed

Swindell, William R; Johnston, Andrew; Carbajal, Steve; Han, Gangwen; Wohn, Christian; Lu, Jun; Xing, Xianying; Nair, Rajan P; Voorhees, John J; Elder, James T; Wang, Xiao-Jing; Sano, Shigetoshi; Prens, Errol P; DiGiovanni, John; Pittelkow, Mark R; Ward, Nicole L; Gudjonsson, Johann E

2011-04-04

Development of a suitable mouse model would facilitate the investigation of pathomechanisms underlying human psoriasis and would also assist in development of therapeutic treatments. However, while many psoriasis mouse models have been proposed, no single model recapitulates all features of the human disease, and standardized validation criteria for psoriasis mouse models have not been widely applied. In this study, whole-genome transcriptional profiling is used to compare gene expression patterns manifested by human psoriatic skin lesions with those that occur in five psoriasis mouse models (K5-Tie2, imiquimod, K14-AREG, K5-Stat3C and K5-TGFbeta1). While the cutaneous gene expression profiles associated with each mouse phenotype exhibited statistically significant similarity to the expression profile of psoriasis in humans, each model displayed distinctive sets of similarities and differences in comparison to human psoriasis. For all five models, correspondence to the human disease was strong with respect to genes involved in epidermal development and keratinization. Immune and inflammation-associated gene expression, in contrast, was more variable between models as compared to the human disease. These findings support the value of all five models as research tools, each with identifiable areas of convergence to and divergence from the human disease. Additionally, the approach used in this paper provides an objective and quantitative method for evaluation of proposed mouse models of psoriasis, which can be strategically applied in future studies to score strengths of mouse phenotypes relative to specific aspects of human psoriasis.

Transcriptional interference networks coordinate the expression of functionally related genes clustered in the same genomic loci

PubMed Central

Boldogköi, Zsolt

2012-01-01

The regulation of gene expression is essential for normal functioning of biological systems in every form of life. Gene expression is primarily controlled at the level of transcription, especially at the phase of initiation. Non-coding RNAs are one of the major players at every level of genetic regulation, including the control of chromatin organization, transcription, various post-transcriptional processes, and translation. In this study, the Transcriptional Interference Network (TIN) hypothesis was put forward in an attempt to explain the global expression of antisense RNAs and the overall occurrence of tandem gene clusters in the genomes of various biological systems ranging from viruses to mammalian cells. The TIN hypothesis suggests the existence of a novel layer of genetic regulation, based on the interactions between the transcriptional machineries of neighboring genes at their overlapping regions, which are assumed to play a fundamental role in coordinating gene expression within a cluster of functionally linked genes. It is claimed that the transcriptional overlaps between adjacent genes are much more widespread in genomes than is thought today. The Waterfall model of the TIN hypothesis postulates a unidirectional effect of upstream genes on the transcription of downstream genes within a cluster of tandemly arrayed genes, while the Seesaw model proposes a mutual interdependence of gene expression between the oppositely oriented genes. The TIN represents an auto-regulatory system with an exquisitely timed and highly synchronized cascade of gene expression in functionally linked genes located in close physical proximity to each other. In this study, we focused on herpesviruses. The reason for this lies in the compressed nature of viral genes, which allows a tight regulation and an easier investigation of the transcriptional interactions between genes. However, I believe that the same or similar principles can be applied to cellular organisms too. PMID:22783276

Transcriptional interference networks coordinate the expression of functionally related genes clustered in the same genomic loci.

PubMed

Boldogköi, Zsolt

2012-01-01

The regulation of gene expression is essential for normal functioning of biological systems in every form of life. Gene expression is primarily controlled at the level of transcription, especially at the phase of initiation. Non-coding RNAs are one of the major players at every level of genetic regulation, including the control of chromatin organization, transcription, various post-transcriptional processes, and translation. In this study, the Transcriptional Interference Network (TIN) hypothesis was put forward in an attempt to explain the global expression of antisense RNAs and the overall occurrence of tandem gene clusters in the genomes of various biological systems ranging from viruses to mammalian cells. The TIN hypothesis suggests the existence of a novel layer of genetic regulation, based on the interactions between the transcriptional machineries of neighboring genes at their overlapping regions, which are assumed to play a fundamental role in coordinating gene expression within a cluster of functionally linked genes. It is claimed that the transcriptional overlaps between adjacent genes are much more widespread in genomes than is thought today. The Waterfall model of the TIN hypothesis postulates a unidirectional effect of upstream genes on the transcription of downstream genes within a cluster of tandemly arrayed genes, while the Seesaw model proposes a mutual interdependence of gene expression between the oppositely oriented genes. The TIN represents an auto-regulatory system with an exquisitely timed and highly synchronized cascade of gene expression in functionally linked genes located in close physical proximity to each other. In this study, we focused on herpesviruses. The reason for this lies in the compressed nature of viral genes, which allows a tight regulation and an easier investigation of the transcriptional interactions between genes. However, I believe that the same or similar principles can be applied to cellular organisms too.

A microarray whole-genome gene expression dataset in a rat model of inflammatory corneal angiogenesis.

PubMed

Mukwaya, Anthony; Lindvall, Jessica M; Xeroudaki, Maria; Peebo, Beatrice; Ali, Zaheer; Lennikov, Anton; Jensen, Lasse Dahl Ejby; Lagali, Neil

2016-11-22

In angiogenesis with concurrent inflammation, many pathways are activated, some linked to VEGF and others largely VEGF-independent. Pathways involving inflammatory mediators, chemokines, and micro-RNAs may play important roles in maintaining a pro-angiogenic environment or mediating angiogenic regression. Here, we describe a gene expression dataset to facilitate exploration of pro-angiogenic, pro-inflammatory, and remodelling/normalization-associated genes during both an active capillary sprouting phase, and in the restoration of an avascular phenotype. The dataset was generated by microarray analysis of the whole transcriptome in a rat model of suture-induced inflammatory corneal neovascularisation. Regions of active capillary sprout growth or regression in the cornea were harvested and total RNA extracted from four biological replicates per group. High quality RNA was obtained for gene expression analysis using microarrays. Fold change of selected genes was validated by qPCR, and protein expression was evaluated by immunohistochemistry. We provide a gene expression dataset that may be re-used to investigate corneal neovascularisation, and may also have implications in other contexts of inflammation-mediated angiogenesis.

Meta-analysis of expression of l(3)mbt tumor-associated germline genes supports the model that a soma-to-germline transition is a hallmark of human cancers.

PubMed

Feichtinger, Julia; Larcombe, Lee; McFarlane, Ramsay J

2014-05-15

Evidence is starting to emerge indicating that tumorigenesis in metazoans involves a soma-to-germline transition, which may contribute to the acquisition of neoplastic characteristics. Here, we have meta-analyzed gene expression profiles of the human orthologs of Drosophila melanogaster germline genes that are ectopically expressed in l(3)mbt brain tumors using gene expression datasets derived from a large cohort of human tumors. We find these germline genes, some of which drive oncogenesis in D. melanogaster, are similarly ectopically activated in a wide range of human cancers. Some of these genes normally have expression restricted to the germline, making them of particular clinical interest. Importantly, these analyses provide additional support to the emerging model that proposes a soma-to-germline transition is a general hallmark of a wide range of human tumors. This has implications for our understanding of human oncogenesis and the development of new therapeutic and biomarker targets with clinical potential. © 2013 The Authors. Published by Wiley Periodicals, Inc. on behalf of UICC.

Embryonic Wnt gene expression in the nitrofen-induced hypoplastic lung using 3-dimensional imaging.

PubMed

Takayasu, Hajime; Murphy, Paula; Sato, Hideaki; Doi, Takashi; Puri, Prem

2010-11-01

Wnts have been reported to play a key role in the lung morphogenesis. We have previously reported that pulmonary gene expression of Wnt2 and Wnt7b is downregulated on day 15 of gestation in the nitrofen-induced congenital diaphragmatic hernia (CDH) model. However, the distribution pattern of gene expression of Wnts in the very early lung development remains unclear. Optical projection tomography (OPT) is a new technique for 3-dimensional imaging of small developing organs and gene distribution combined with whole-mount in situ hybridization. We designed this study to investigate the distribution pattern of Wnts gene expression in lung buds of nitrofen-induced CDH model using OPT. Embryos from normal and nitrofen-treated dams were harvested on embryonic day 10 (E10), and divided into controls and nitrofen group, respectively. Whole-mount in situ hybridization to detect transcripts of Wnt2 and Wnt7b was performed, analyzed, and reconstructed using OPT. The expression of Wnt2 transcripts was detected in the lung bud mesenchyme and markedly diminished in nitrofen group compared to controls, whereas Wnt7b transcripts were expressed in the mesoderm of bronchi and the lung bud with no detectable difference between 2 groups. We provide evidence for the first time that Wnt2 expression is downregulated at lung bud stage in the nitrofen model. Optical projection tomography is potentially a useful approach to visualize both gene expression and morphology during very early stages of lung development. Copyright © 2010 Elsevier Inc. All rights reserved.

A method to identify differential expression profiles of time-course gene data with Fourier transformation

PubMed Central

2013-01-01

Background Time course gene expression experiments are an increasingly popular method for exploring biological processes. Temporal gene expression profiles provide an important characterization of gene function, as biological systems are both developmental and dynamic. With such data it is possible to study gene expression changes over time and thereby to detect differential genes. Much of the early work on analyzing time series expression data relied on methods developed originally for static data and thus there is a need for improved methodology. Since time series expression is a temporal process, its unique features such as autocorrelation between successive points should be incorporated into the analysis. Results This work aims to identify genes that show different gene expression profiles across time. We propose a statistical procedure to discover gene groups with similar profiles using a nonparametric representation that accounts for the autocorrelation in the data. In particular, we first represent each profile in terms of a Fourier basis, and then we screen out genes that are not differentially expressed based on the Fourier coefficients. Finally, we cluster the remaining gene profiles using a model-based approach in the Fourier domain. We evaluate the screening results in terms of sensitivity, specificity, FDR and FNR, compare with the Gaussian process regression screening in a simulation study and illustrate the results by application to yeast cell-cycle microarray expression data with alpha-factor synchronization. The key elements of the proposed methodology: (i) representation of gene profiles in the Fourier domain; (ii) automatic screening of genes based on the Fourier coefficients and taking into account autocorrelation in the data, while controlling the false discovery rate (FDR); (iii) model-based clustering of the remaining gene profiles. Conclusions Using this method, we identified a set of cell-cycle-regulated time-course yeast genes. The proposed method is general and can be potentially used to identify genes which have the same patterns or biological processes, and help facing the present and forthcoming challenges of data analysis in functional genomics. PMID:24134721

A Pipeline for High-Throughput Concentration Response Modeling of Gene Expression for Toxicogenomics

PubMed Central

House, John S.; Grimm, Fabian A.; Jima, Dereje D.; Zhou, Yi-Hui; Rusyn, Ivan; Wright, Fred A.

2017-01-01

Cell-based assays are an attractive option to measure gene expression response to exposure, but the cost of whole-transcriptome RNA sequencing has been a barrier to the use of gene expression profiling for in vitro toxicity screening. In addition, standard RNA sequencing adds variability due to variable transcript length and amplification. Targeted probe-sequencing technologies such as TempO-Seq, with transcriptomic representation that can vary from hundreds of genes to the entire transcriptome, may reduce some components of variation. Analyses of high-throughput toxicogenomics data require renewed attention to read-calling algorithms and simplified dose–response modeling for datasets with relatively few samples. Using data from induced pluripotent stem cell-derived cardiomyocytes treated with chemicals at varying concentrations, we describe here and make available a pipeline for handling expression data generated by TempO-Seq to align reads, clean and normalize raw count data, identify differentially expressed genes, and calculate transcriptomic concentration–response points of departure. The methods are extensible to other forms of concentration–response gene-expression data, and we discuss the utility of the methods for assessing variation in susceptibility and the diseased cellular state. PMID:29163636

Discretization of Gene Expression Data Unmasks Molecular Subgroups Recurring in Different Human Cancer Types.

PubMed

Beleut, Manfred; Soeldner, Robert; Egorov, Mark; Guenther, Rolf; Dehler, Silvia; Morys-Wortmann, Corinna; Moch, Holger; Henco, Karsten; Schraml, Peter

2016-01-01

Despite the individually different molecular alterations in tumors, the malignancy associated biological traits are strikingly similar. Results of a previous study using renal cell carcinoma (RCC) as a model pointed towards cancer-related features, which could be visualized as three groups by microarray based gene expression analysis. In this study, we used a mathematic model to verify the presence of these groups in RCC as well as in other cancer types. We developed an algorithm for gene-expression deviation profiling for analyzing gene expression data of a total of 8397 patients with 13 different cancer types and normal tissues. We revealed three common Cancer Transcriptomic Profiles (CTPs) which recurred in all investigated tumors. Additionally, CTPs remained robust regardless of the functions or numbers of genes analyzed. CTPs may represent common genetic fingerprints, which potentially reflect the closely related biological traits of human cancers.

ImpulseDE: detection of differentially expressed genes in time series data using impulse models.

PubMed

Sander, Jil; Schultze, Joachim L; Yosef, Nir

2017-03-01

Perturbations in the environment lead to distinctive gene expression changes within a cell. Observed over time, those variations can be characterized by single impulse-like progression patterns. ImpulseDE is an R package suited to capture these patterns in high throughput time series datasets. By fitting a representative impulse model to each gene, it reports differentially expressed genes across time points from a single or between two time courses from two experiments. To optimize running time, the code uses clustering and multi-threading. By applying ImpulseDE , we demonstrate its power to represent underlying biology of gene expression in microarray and RNA-Seq data. ImpulseDE is available on Bioconductor ( https://bioconductor.org/packages/ImpulseDE/ ). niryosef@berkeley.edu. Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Bayesian median regression for temporal gene expression data

NASA Astrophysics Data System (ADS)

Yu, Keming; Vinciotti, Veronica; Liu, Xiaohui; 't Hoen, Peter A. C.

2007-09-01

Most of the existing methods for the identification of biologically interesting genes in a temporal expression profiling dataset do not fully exploit the temporal ordering in the dataset and are based on normality assumptions for the gene expression. In this paper, we introduce a Bayesian median regression model to detect genes whose temporal profile is significantly different across a number of biological conditions. The regression model is defined by a polynomial function where both time and condition effects as well as interactions between the two are included. MCMC-based inference returns the posterior distribution of the polynomial coefficients. From this a simple Bayes factor test is proposed to test for significance. The estimation of the median rather than the mean, and within a Bayesian framework, increases the robustness of the method compared to a Hotelling T2-test previously suggested. This is shown on simulated data and on muscular dystrophy gene expression data.

The impact of preserved Klotho gene expression on anti-oxidative stress activity in healthy kidney.

PubMed

Kimura, Takaaki; Shiizaki, Kazuhiro; Kurosu, Hiroshi; Akimoto, Tetsu; Shinzato, Takahiro; Shimizu, Toshihiro; Kurosawa, Akira; Kubo, Taro; Nanmoku, Koji; Kuro-O, Makoto; Yagisawa, Takashi

2018-04-25

Klotho, which was originally identified as an anti-aging gene, forms a complex with fibroblast growth factor 23 (FGF23) receptor in kidney, with subsequent signaling that regulates mineral metabolism. Other biological activities of Klotho including anti-aging effects such as protection from various cellular stress have been shown, however, the precise mechanism of these effects of Klotho gene in the healthy human kidney is not well understood. In this study, we examined the relationships of Klotho and anti-oxidative stress gene expression levels in zero-hour biopsy specimens from 44 donors in kidney transplantation and verified them in animal models whose Klotho gene expression levels were varied. The nitrotyrosine expression level in kidney was evaluated in these animal models. Expression levels of Klotho gene were positively correlated with p53 gene, and antioxidant enzyme genes such as Catalase, superoxide dismutase 1 (SOD1), SOD2, peroxiredoxin 3 (PRDX3), and glutathione peroxidase 1 (GPX1) but not clinical parameters such as age and renal function, and pathological features such as glomerulosclerosis and interstitial fibrosis tubular atrophy. The expression levels of all genes were significantly higher in mice with Klotho overexpression than in wild-type mice, and those except for PRDX3 and GPX1 were significantly lower in Klotho-deficient mice than in wild-type littermate mice. Nitrotyrosine-positive bands of various sizes were observed in kidney from Klotho-deficient mice only. The preservation of Klotho gene expression might induce the anti-oxidative stress mechanism for homeostasis of healthy human kidney independently of its general condition including age, renal function, and histological findings.

Selection of Valid Reference Genes for Reverse Transcription Quantitative PCR Analysis in Heliconius numata (Lepidoptera: Nymphalidae)

PubMed Central

Chouteau, Mathieu; Whibley, Annabel; Joron, Mathieu; Llaurens, Violaine

2016-01-01

Identifying the genetic basis of adaptive variation is challenging in non-model organisms and quantitative real time PCR. is a useful tool for validating predictions regarding the expression of candidate genes. However, comparing expression levels in different conditions requires rigorous experimental design and statistical analyses. Here, we focused on the neotropical passion-vine butterflies Heliconius, non-model species studied in evolutionary biology for their adaptive variation in wing color patterns involved in mimicry and in the signaling of their toxicity to predators. We aimed at selecting stable reference genes to be used for normalization of gene expression data in RT-qPCR analyses from developing wing discs according to the minimal guidelines described in Minimum Information for publication of Quantitative Real-Time PCR Experiments (MIQE). To design internal RT-qPCR controls, we studied the stability of expression of nine candidate reference genes (actin, annexin, eF1α, FK506BP, PolyABP, PolyUBQ, RpL3, RPS3A, and tubulin) at two developmental stages (prepupal and pupal) using three widely used programs (GeNorm, NormFinder and BestKeeper). Results showed that, despite differences in statistical methods, genes RpL3, eF1α, polyABP, and annexin were stably expressed in wing discs in late larval and pupal stages of Heliconius numata. This combination of genes may be used as a reference for a reliable study of differential expression in wings for instance for genes involved in important phenotypic variation, such as wing color pattern variation. Through this example, we provide general useful technical recommendations as well as relevant statistical strategies for evolutionary biologists aiming to identify candidate-genes involved adaptive variation in non-model organisms. PMID:27271971

Overexpression of heterogeneous nuclear ribonucleoprotein F stimulates renal Ace-2 gene expression and prevents TGF-β1-induced kidney injury in a mouse model of diabetes.

PubMed

Lo, Chao-Sheng; Shi, Yixuan; Chang, Shiao-Ying; Abdo, Shaaban; Chenier, Isabelle; Filep, Janos G; Ingelfinger, Julie R; Zhang, Shao-Ling; Chan, John S D

2015-10-01

We investigated whether heterogeneous nuclear ribonucleoprotein F (hnRNP F) stimulates renal ACE-2 expression and prevents TGF-β1 signalling, TGF-β1 inhibition of Ace-2 gene expression and induction of tubulo-fibrosis in an Akita mouse model of type 1 diabetes. Adult male Akita transgenic (Tg) mice overexpressing specifically hnRNP F in their renal proximal tubular cells (RPTCs) were studied. Non-Akita littermates and Akita mice served as controls. Immortalised rat RPTCs stably transfected with plasmid containing either rat Hnrnpf cDNA or rat Ace-2 gene promoter were also studied. Overexpression of hnRNP F attenuated systemic hypertension, glomerular filtration rate, albumin/creatinine ratio, urinary angiotensinogen (AGT) and angiotensin (Ang) II levels, renal fibrosis and profibrotic gene (Agt, Tgf-β1, TGF-β receptor II [Tgf-βrII]) expression, stimulated anti-profibrotic gene (Ace-2 and Ang 1-7 receptor [MasR]) expression, and normalised urinary Ang 1-7 level in Akita Hnrnpf-Tg mice as compared with Akita mice. In vitro, hnRNP F overexpression stimulated Ace-2 gene promoter activity, mRNA and protein expression, and attenuated Agt, Tgf-β1 and Tgf-βrII gene expression. Furthermore, hnRNP F overexpression prevented TGF-β1 signalling and TGF-β1 inhibition of Ace-2 gene expression. These data demonstrate that hnRNP F stimulates Ace-2 gene transcription, prevents TGF-β1 inhibition of Ace-2 gene transcription and induction of kidney injury in diabetes. HnRNP F may be a potential target for treating hypertension and renal fibrosis in diabetes.

A whole blood gene expression-based signature for smoking status

PubMed Central

2012-01-01

Background Smoking is the leading cause of preventable death worldwide and has been shown to increase the risk of multiple diseases including coronary artery disease (CAD). We sought to identify genes whose levels of expression in whole blood correlate with self-reported smoking status. Methods Microarrays were used to identify gene expression changes in whole blood which correlated with self-reported smoking status; a set of significant genes from the microarray analysis were validated by qRT-PCR in an independent set of subjects. Stepwise forward logistic regression was performed using the qRT-PCR data to create a predictive model whose performance was validated in an independent set of subjects and compared to cotinine, a nicotine metabolite. Results Microarray analysis of whole blood RNA from 209 PREDICT subjects (41 current smokers, 4 quit ≤ 2 months, 64 quit > 2 months, 100 never smoked; NCT00500617) identified 4214 genes significantly correlated with self-reported smoking status. qRT-PCR was performed on 1,071 PREDICT subjects across 256 microarray genes significantly correlated with smoking or CAD. A five gene (CLDND1, LRRN3, MUC1, GOPC, LEF1) predictive model, derived from the qRT-PCR data using stepwise forward logistic regression, had a cross-validated mean AUC of 0.93 (sensitivity=0.78; specificity=0.95), and was validated using 180 independent PREDICT subjects (AUC=0.82, CI 0.69-0.94; sensitivity=0.63; specificity=0.94). Plasma from the 180 validation subjects was used to assess levels of cotinine; a model using a threshold of 10 ng/ml cotinine resulted in an AUC of 0.89 (CI 0.81-0.97; sensitivity=0.81; specificity=0.97; kappa with expression model = 0.53). Conclusion We have constructed and validated a whole blood gene expression score for the evaluation of smoking status, demonstrating that clinical and environmental factors contributing to cardiovascular disease risk can be assessed by gene expression. PMID:23210427

Differential in vivo gene expression of major Leptospira proteins in resistant or susceptible animal models.

PubMed

Matsui, Mariko; Soupé, Marie-Estelle; Becam, Jérôme; Goarant, Cyrille

2012-09-01

Transcripts of Leptospira 16S rRNA, FlaB, LigB, LipL21, LipL32, LipL36, LipL41, and OmpL37 were quantified in the blood of susceptible (hamsters) and resistant (mice) animal models of leptospirosis. We first validated adequate reference genes and then evaluated expression patterns in vivo compared to in vitro cultures. LipL32 expression was downregulated in vivo and differentially regulated in resistant and susceptible animals. FlaB expression was also repressed in mice but not in hamsters. In contrast, LigB and OmpL37 were upregulated in vivo. Thus, we demonstrated that a virulent strain of Leptospira differentially adapts its gene expression in the blood of infected animals.

A Theoretical Lower Bound for Selection on the Expression Levels of Proteins

DOE PAGES

Price, Morgan N.; Arkin, Adam P.

2016-06-11

We use simple models of the costs and benefits of microbial gene expression to show that changing a protein's expression away from its optimum by 2-fold should reduce fitness by at least [Formula: see text], where P is the fraction the cell's protein that the gene accounts for. As microbial genes are usually expressed at above 5 parts per million, and effective population sizes are likely to be above 10(6), this implies that 2-fold changes to gene expression levels are under strong selection, as [Formula: see text], where Ne is the effective population size and s is the selection coefficient.more » Thus, most gene duplications should be selected against. On the other hand, we predict that for most genes, small changes in the expression will be effectively neutral.« less

A Theoretical Lower Bound for Selection on the Expression Levels of Proteins

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

Price, Morgan N.; Arkin, Adam P.

We use simple models of the costs and benefits of microbial gene expression to show that changing a protein's expression away from its optimum by 2-fold should reduce fitness by at least [Formula: see text], where P is the fraction the cell's protein that the gene accounts for. As microbial genes are usually expressed at above 5 parts per million, and effective population sizes are likely to be above 10(6), this implies that 2-fold changes to gene expression levels are under strong selection, as [Formula: see text], where Ne is the effective population size and s is the selection coefficient.more » Thus, most gene duplications should be selected against. On the other hand, we predict that for most genes, small changes in the expression will be effectively neutral.« less

Maternal residential air pollution and placental imprinted gene expression.

PubMed

Kingsley, Samantha L; Deyssenroth, Maya A; Kelsey, Karl T; Awad, Yara Abu; Kloog, Itai; Schwartz, Joel D; Lambertini, Luca; Chen, Jia; Marsit, Carmen J; Wellenius, Gregory A

2017-11-01

Maternal exposure to air pollution is associated with reduced fetal growth, but its relationship with expression of placental imprinted genes (important regulators of fetal growth) has not yet been studied. To examine relationships between maternal residential air pollution and expression of placental imprinted genes in the Rhode Island Child Health Study (RICHS). Women-infant pairs were enrolled following delivery between 2009 and 2013. We geocoded maternal residential addresses at delivery, estimated daily levels of fine particulate matter (PM 2.5 ; n=355) and black carbon (BC; n=336) using spatial-temporal models, and estimated residential distance to nearest major roadway (n=355). Using linear regression models we investigated the associations between each exposure metric and expression of nine candidate genes previously associated with infant birthweight in RICHS, with secondary analyses of a panel of 108 imprinted genes expressed in the placenta. We also explored effect measure modification by infant sex. PM 2.5 and BC were associated with altered expression for seven and one candidate genes, respectively, previously linked with birthweight in this cohort. Adjusting for multiple comparisons, we found that PM 2.5 and BC were associated with changes in expression of 41 and 12 of 108 placental imprinted genes, respectively. Infant sex modified the association between PM 2.5 and expression of CHD7 and between proximity to major roadways and expression of ZDBF2. We found that maternal exposure to residential PM 2.5 and BC was associated with changes in placental imprinted gene expression, which suggests a plausible line of investigation of how air pollution affects fetal growth and development. Copyright © 2017 Elsevier Ltd. All rights reserved.

EvoCor: a platform for predicting functionally related genes using phylogenetic and expression profiles.

PubMed

Dittmar, W James; McIver, Lauren; Michalak, Pawel; Garner, Harold R; Valdez, Gregorio

2014-07-01

The wealth of publicly available gene expression and genomic data provides unique opportunities for computational inference to discover groups of genes that function to control specific cellular processes. Such genes are likely to have co-evolved and be expressed in the same tissues and cells. Unfortunately, the expertise and computational resources required to compare tens of genomes and gene expression data sets make this type of analysis difficult for the average end-user. Here, we describe the implementation of a web server that predicts genes involved in affecting specific cellular processes together with a gene of interest. We termed the server 'EvoCor', to denote that it detects functional relationships among genes through evolutionary analysis and gene expression correlation. This web server integrates profiles of sequence divergence derived by a Hidden Markov Model (HMM) and tissue-wide gene expression patterns to determine putative functional linkages between pairs of genes. This server is easy to use and freely available at http://pilot-hmm.vbi.vt.edu/. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

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.

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.

Downregulation of p300 gene expression in airway mesenchyme of nitrofen-induced hypoplastic lungs.

PubMed

Takahashi, Hiromizu; Friedmacher, Florian; Fujiwara, Naho; Hofmann, Alejandro; Takahashi, Toshiaki; Puri, Prem

2014-04-01

Congenital diaphragmatic hernia (CDH) is a relatively common developmental abnormality causing life-threatening respiratory distress at birth. The nitrofen model has been widely used to investigate the pathogenesis of hypoplastic lungs associated with CDH. Embryos lacking p300 and CBP genes are significantly smaller in lung formation. We hypothesized that pulmonary gene expression of p300 and CBP is downregulated during late gestation in the nitrofen-induced CDH model. Time-pregnant rats were treated with either nitrofen or vehicle on gestational day 9 (D9). Fetal lungs were harvested on D18 and D21 (n = 8 at each time point). Pulmonary gene expression of p300 and CBP was analyzed by quantitative real-time PCR. Immunohistochemistry was performed to investigate expression and localization of pulmonary p300 and CBP proteins. Relative mRNA expression levels of p300 were significantly decreased in nitrofen-induced hypoplastic lungs on D18 compared to controls (3.00 ± 0.20 vs. 3.76 ± 0.14; p = 0.0039), while CBP levels were not altered. p300 immunoreactivity was markedly diminished in surrounding mesenchymal compartments and nuclei of proximal and distal airway cells, while CBP expression was not altered. Downregulation of p300 gene expression during the early canalicular stage may disrupt epithelial-mesenchymal signaling interactions, contributing to the development of hypoplastic lungs in the nitrofen-induced CDH model.

Relaxation rates of gene expression kinetics reveal the feedback signs of autoregulatory gene networks

NASA Astrophysics Data System (ADS)

Jia, Chen; Qian, Hong; Chen, Min; Zhang, Michael Q.

2018-03-01

The transient response to a stimulus and subsequent recovery to a steady state are the fundamental characteristics of a living organism. Here we study the relaxation kinetics of autoregulatory gene networks based on the chemical master equation model of single-cell stochastic gene expression with nonlinear feedback regulation. We report a novel relation between the rate of relaxation, characterized by the spectral gap of the Markov model, and the feedback sign of the underlying gene circuit. When a network has no feedback, the relaxation rate is exactly the decaying rate of the protein. We further show that positive feedback always slows down the relaxation kinetics while negative feedback always speeds it up. Numerical simulations demonstrate that this relation provides a possible method to infer the feedback topology of autoregulatory gene networks by using time-series data of gene expression.

GENE EXPRESSION PATTERNS ASSOCIATED WITH INFERTILITY IN HUMAN AND RODENT MODELS

EPA Science Inventory

Modern genomic technologies such as DNA arrays provide the means to investigate molecular interactions at an unprecedented level, and arrays have been used to carry out gene expression profiling as a means of identifying candidate genes involved in molecular mechanisms underlying...

Mixture models for detecting differentially expressed genes in microarrays.

PubMed

Jones, Liat Ben-Tovim; Bean, Richard; McLachlan, Geoffrey J; Zhu, Justin Xi

2006-10-01

An important and common problem in microarray experiments is the detection of genes that are differentially expressed in a given number of classes. As this problem concerns the selection of significant genes from a large pool of candidate genes, it needs to be carried out within the framework of multiple hypothesis testing. In this paper, we focus on the use of mixture models to handle the multiplicity issue. With this approach, a measure of the local FDR (false discovery rate) is provided for each gene. An attractive feature of the mixture model approach is that it provides a framework for the estimation of the prior probability that a gene is not differentially expressed, and this probability can subsequently be used in forming a decision rule. The rule can also be formed to take the false negative rate into account. We apply this approach to a well-known publicly available data set on breast cancer, and discuss our findings with reference to other approaches.

The transcriptional landscape of age in human peripheral blood

PubMed Central

Peters, Marjolein J.; Joehanes, Roby; Pilling, Luke C.; Schurmann, Claudia; Conneely, Karen N.; Powell, Joseph; Reinmaa, Eva; Sutphin, George L.; Zhernakova, Alexandra; Schramm, Katharina; Wilson, Yana A.; Kobes, Sayuko; Tukiainen, Taru; Nalls, Michael A.; Hernandez, Dena G.; Cookson, Mark R.; Gibbs, Raphael J.; Hardy, John; Ramasamy, Adaikalavan; Zonderman, Alan B.; Dillman, Allissa; Traynor, Bryan; Smith, Colin; Longo, Dan L.; Trabzuni, Daniah; Troncoso, Juan; van der Brug, Marcel; Weale, Michael E.; O'Brien, Richard; Johnson, Robert; Walker, Robert; Zielke, Ronald H.; Arepalli, Sampath; Ryten, Mina; Singleton, Andrew B.; Ramos, Yolande F.; Göring, Harald H. H.; Fornage, Myriam; Liu, Yongmei; Gharib, Sina A.; Stranger, Barbara E.; De Jager, Philip L.; Aviv, Abraham; Levy, Daniel; Murabito, Joanne M.; Munson, Peter J.; Huan, Tianxiao; Hofman, Albert; Uitterlinden, André G.; Rivadeneira, Fernando; van Rooij, Jeroen; Stolk, Lisette; Broer, Linda; Verbiest, Michael M. P. J.; Jhamai, Mila; Arp, Pascal; Metspalu, Andres; Tserel, Liina; Milani, Lili; Samani, Nilesh J.; Peterson, Pärt; Kasela, Silva; Codd, Veryan; Peters, Annette; Ward-Caviness, Cavin K.; Herder, Christian; Waldenberger, Melanie; Roden, Michael; Singmann, Paula; Zeilinger, Sonja; Illig, Thomas; Homuth, Georg; Grabe, Hans-Jörgen; Völzke, Henry; Steil, Leif; Kocher, Thomas; Murray, Anna; Melzer, David; Yaghootkar, Hanieh; Bandinelli, Stefania; Moses, Eric K.; Kent, Jack W.; Curran, Joanne E.; Johnson, Matthew P.; Williams-Blangero, Sarah; Westra, Harm-Jan; McRae, Allan F.; Smith, Jennifer A.; Kardia, Sharon L. R.; Hovatta, Iiris; Perola, Markus; Ripatti, Samuli; Salomaa, Veikko; Henders, Anjali K.; Martin, Nicholas G.; Smith, Alicia K.; Mehta, Divya; Binder, Elisabeth B.; Nylocks, K Maria; Kennedy, Elizabeth M.; Klengel, Torsten; Ding, Jingzhong; Suchy-Dicey, Astrid M.; Enquobahrie, Daniel A.; Brody, Jennifer; Rotter, Jerome I.; Chen, Yii-Der I.; Houwing-Duistermaat, Jeanine; Kloppenburg, Margreet; Slagboom, P. Eline; Helmer, Quinta; den Hollander, Wouter; Bean, Shannon; Raj, Towfique; Bakhshi, Noman; Wang, Qiao Ping; Oyston, Lisa J.; Psaty, Bruce M.; Tracy, Russell P.; Montgomery, Grant W.; Turner, Stephen T.; Blangero, John; Meulenbelt, Ingrid; Ressler, Kerry J.; Yang, Jian; Franke, Lude; Kettunen, Johannes; Visscher, Peter M.; Neely, G. Gregory; Korstanje, Ron; Hanson, Robert L.; Prokisch, Holger; Ferrucci, Luigi; Esko, Tonu; Teumer, Alexander; van Meurs, Joyce B. J.; Johnson, Andrew D.

2015-01-01

Disease incidences increase with age, but the molecular characteristics of ageing that lead to increased disease susceptibility remain inadequately understood. Here we perform a whole-blood gene expression meta-analysis in 14,983 individuals of European ancestry (including replication) and identify 1,497 genes that are differentially expressed with chronological age. The age-associated genes do not harbor more age-associated CpG-methylation sites than other genes, but are instead enriched for the presence of potentially functional CpG-methylation sites in enhancer and insulator regions that associate with both chronological age and gene expression levels. We further used the gene expression profiles to calculate the ‘transcriptomic age' of an individual, and show that differences between transcriptomic age and chronological age are associated with biological features linked to ageing, such as blood pressure, cholesterol levels, fasting glucose, and body mass index. The transcriptomic prediction model adds biological relevance and complements existing epigenetic prediction models, and can be used by others to calculate transcriptomic age in external cohorts. PMID:26490707

Delivery of Na/I symporter gene into skeletal muscle using nanobubbles and ultrasound: visualization of gene expression by PET.

PubMed

Watanabe, Yukiko; Horie, Sachiko; Funaki, Yoshihito; Kikuchi, Youhei; Yamazaki, Hiromichi; Ishii, Keizo; Mori, Shiro; Vassaux, Georges; Kodama, Tetsuya

2010-06-01

The development of nonviral gene delivery systems is essential in gene therapy, and the use of a minimally invasive imaging methodology can provide important clinical endpoints. In the current study, we present a new methodology for gene therapy-a delivery system using nanobubbles and ultrasound as a nonviral gene delivery method. We assessed whether the gene transfer allowed by this methodology was detectable by PET and bioluminescence imaging. Two kinds of reported vectors (luciferase and human Na/I symporter [hNIS]) were transfected or cotransfected into the skeletal muscles of normal mice (BALB/c) using the ultrasound-nanobubbles method. The kinetics of luciferase gene expression were analyzed in vivo using bioluminescence imaging. At the peak of gene transfer, PET of hNIS expression was performed using our recently developed PET scanner, after (124)I injection. The imaging data were confirmed using reverse-transcriptase polymerase chain reaction amplification, biodistribution, and a blocking study. The imaging potential of the 2 methodologies was evaluated in 2 mouse models of human pathology (McH/lpr-RA1 mice showing vascular disease and C57BL/10-mdx Jic mice showing muscular dystrophy). Peak luciferase gene activity was observed in the skeletal muscle 4 d after transfection. On day 2 after hNIS and luciferase cotransfection, the expression of these genes was confirmed by reverse-transcriptase polymerase chain reaction on a muscle biopsy. PET of the hNIS gene, biodistribution, the blocking study, and autoradiography were performed on day 4 after transfection, and it was indicated that hNIS expression was restricted to the site of plasmid administration (skeletal muscle). Similar localized PET and (124)I accumulation were successfully obtained in the disease-model mice. The hNIS gene was delivered into the skeletal muscle of healthy and disease-model mice by the ultrasound-nanobubbles method, and gene expression was successfully visualized with PET. The combination of ultrasound-nanobubble gene transfer and PET may be applied to gene therapy clinical protocols.

Genetic regulation of gene expression in the lung identifies CST3 and CD22 as potential causal genes for airflow obstruction.

PubMed

Lamontagne, Maxime; Timens, Wim; Hao, Ke; Bossé, Yohan; Laviolette, Michel; Steiling, Katrina; Campbell, Joshua D; Couture, Christian; Conti, Massimo; Sherwood, Karen; Hogg, James C; Brandsma, Corry-Anke; van den Berge, Maarten; Sandford, Andrew; Lam, Stephen; Lenburg, Marc E; Spira, Avrum; Paré, Peter D; Nickle, David; Sin, Don D; Postma, Dirkje S

2014-11-01

COPD is a complex chronic disease with poorly understood pathogenesis. Integrative genomic approaches have the potential to elucidate the biological networks underlying COPD and lung function. We recently combined genome-wide genotyping and gene expression in 1111 human lung specimens to map expression quantitative trait loci (eQTL). To determine causal associations between COPD and lung function-associated single nucleotide polymorphisms (SNPs) and lung tissue gene expression changes in our lung eQTL dataset. We evaluated causality between SNPs and gene expression for three COPD phenotypes: FEV(1)% predicted, FEV(1)/FVC and COPD as a categorical variable. Different models were assessed in the three cohorts independently and in a meta-analysis. SNPs associated with a COPD phenotype and gene expression were subjected to causal pathway modelling and manual curation. In silico analyses evaluated functional enrichment of biological pathways among newly identified causal genes. Biologically relevant causal genes were validated in two separate gene expression datasets of lung tissues and bronchial airway brushings. High reliability causal relations were found in SNP-mRNA-phenotype triplets for FEV(1)% predicted (n=169) and FEV(1)/FVC (n=80). Several genes of potential biological relevance for COPD were revealed. eQTL-SNPs upregulating cystatin C (CST3) and CD22 were associated with worse lung function. Signalling pathways enriched with causal genes included xenobiotic metabolism, apoptosis, protease-antiprotease and oxidant-antioxidant balance. By using integrative genomics and analysing the relationships of COPD phenotypes with SNPs and gene expression in lung tissue, we identified CST3 and CD22 as potential causal genes for airflow obstruction. This study also augmented the understanding of previously described COPD pathways. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Gene Expression Profiles of Human Dendritic Cells Interacting with Aspergillus fumigatus in a Bilayer Model of the Alveolar Epithelium/Endothelium Interface

PubMed Central

Morton, Charles Oliver; Fliesser, Mirjam; Dittrich, Marcus; Mueller, Tobias; Bauer, Ruth; Kneitz, Susanne; Hope, William; Rogers, Thomas Richard; Einsele, Hermann; Loeffler, Juergen

2014-01-01

The initial stages of the interaction between the host and Aspergillus fumigatus at the alveolar surface of the human lung are critical in the establishment of aspergillosis. Using an in vitro bilayer model of the alveolus, including both the epithelium (human lung adenocarcinoma epithelial cell line, A549) and endothelium (human pulmonary artery epithelial cells, HPAEC) on transwell membranes, it was possible to closely replicate the in vivo conditions. Two distinct sub-groups of dendritic cells (DC), monocyte-derived DC (moDC) and myeloid DC (mDC), were included in the model to examine immune responses to fungal infection at the alveolar surface. RNA in high quantity and quality was extracted from the cell layers on the transwell membrane to allow gene expression analysis using tailored custom-made microarrays, containing probes for 117 immune-relevant genes. This microarray data indicated minimal induction of immune gene expression in A549 alveolar epithelial cells in response to germ tubes of A. fumigatus. In contrast, the addition of DC to the system greatly increased the number of differentially expressed immune genes. moDC exhibited increased expression of genes including CLEC7A, CD209 and CCL18 in the absence of A. fumigatus compared to mDC. In the presence of A. fumigatus, both DC subgroups exhibited up-regulation of genes identified in previous studies as being associated with the exposure of DC to A. fumigatus and exhibiting chemotactic properties for neutrophils, including CXCL2, CXCL5, CCL20, and IL1B. This model closely approximated the human alveolus allowing for an analysis of the host pathogen interface that complements existing animal models of IA. PMID:24870357

The dynamics of gene expression changes in a mouse model of oral tumorigenesis may help refine prevention and treatment strategies in patients with oral cancer.

PubMed

Foy, Jean-Philippe; Tortereau, Antonin; Caulin, Carlos; Le Texier, Vincent; Lavergne, Emilie; Thomas, Emilie; Chabaud, Sylvie; Perol, David; Lachuer, Joël; Lang, Wenhua; Hong, Waun Ki; Goudot, Patrick; Lippman, Scott M; Bertolus, Chloé; Saintigny, Pierre

2016-06-14

A better understanding of the dynamics of molecular changes occurring during the early stages of oral tumorigenesis may help refine prevention and treatment strategies. We generated genome-wide expression profiles of microdissected normal mucosa, hyperplasia, dysplasia and tumors derived from the 4-NQO mouse model of oral tumorigenesis. Genes differentially expressed between tumor and normal mucosa defined the "tumor gene set" (TGS), including 4 non-overlapping gene subsets that characterize the dynamics of gene expression changes through different stages of disease progression. The majority of gene expression changes occurred early or progressively. The relevance of these mouse gene sets to human disease was tested in multiple datasets including the TCGA and the Genomics of Drug Sensitivity in Cancer project. The TGS was able to discriminate oral squamous cell carcinoma (OSCC) from normal oral mucosa in 3 independent datasets. The OSCC samples enriched in the mouse TGS displayed high frequency of CASP8 mutations, 11q13.3 amplifications and low frequency of PIK3CA mutations. Early changes observed in the 4-NQO model were associated with a trend toward a shorter oral cancer-free survival in patients with oral preneoplasia that was not seen in multivariate analysis. Progressive changes observed in the 4-NQO model were associated with an increased sensitivity to 4 different MEK inhibitors in a panel of 51 squamous cell carcinoma cell lines of the areodigestive tract. In conclusion, the dynamics of molecular changes in the 4-NQO model reveal that MEK inhibition may be relevant to prevention and treatment of a specific molecularly-defined subgroup of OSCC.

Selection and Validation of Reference Genes for qRT-PCR Expression Analysis of Candidate Genes Involved in Olfactory Communication in the Butterfly Bicyclus anynana

PubMed Central

Arun, Alok; Baumlé, Véronique; Amelot, Gaël; Nieberding, Caroline M.

2015-01-01

Real-time quantitative reverse transcription PCR (qRT-PCR) is a technique widely used to quantify the transcriptional expression level of candidate genes. qRT-PCR requires the selection of one or several suitable reference genes, whose expression profiles remain stable across conditions, to normalize the qRT-PCR expression profiles of candidate genes. Although several butterfly species (Lepidoptera) have become important models in molecular evolutionary ecology, so far no study aimed at identifying reference genes for accurate data normalization for any butterfly is available. The African bush brown butterfly Bicyclus anynana has drawn considerable attention owing to its suitability as a model for evolutionary ecology, and we here provide a maiden extensive study to identify suitable reference gene in this species. We monitored the expression profile of twelve reference genes: eEF-1α, FK506, UBQL40, RpS8, RpS18, HSP, GAPDH, VATPase, ACT3, TBP, eIF2 and G6PD. We tested the stability of their expression profiles in three different tissues (wings, brains, antennae), two developmental stages (pupal and adult) and two sexes (male and female), all of which were subjected to two food treatments (food stress and control feeding ad libitum). The expression stability and ranking of twelve reference genes was assessed using two algorithm-based methods, NormFinder and geNorm. Both methods identified RpS8 as the best suitable reference gene for expression data normalization. We also showed that the use of two reference genes is sufficient to effectively normalize the qRT-PCR data under varying tissues and experimental conditions that we used in B. anynana. Finally, we tested the effect of choosing reference genes with different stability on the normalization of the transcript abundance of a candidate gene involved in olfactory communication in B. anynana, the Fatty Acyl Reductase 2, and we confirmed that using an unstable reference gene can drastically alter the expression profile of the target candidate genes. PMID:25793735

Selection and validation of reference genes for qRT-PCR expression analysis of candidate genes involved in olfactory communication in the butterfly Bicyclus anynana.

PubMed

Arun, Alok; Baumlé, Véronique; Amelot, Gaël; Nieberding, Caroline M

2015-01-01

Real-time quantitative reverse transcription PCR (qRT-PCR) is a technique widely used to quantify the transcriptional expression level of candidate genes. qRT-PCR requires the selection of one or several suitable reference genes, whose expression profiles remain stable across conditions, to normalize the qRT-PCR expression profiles of candidate genes. Although several butterfly species (Lepidoptera) have become important models in molecular evolutionary ecology, so far no study aimed at identifying reference genes for accurate data normalization for any butterfly is available. The African bush brown butterfly Bicyclus anynana has drawn considerable attention owing to its suitability as a model for evolutionary ecology, and we here provide a maiden extensive study to identify suitable reference gene in this species. We monitored the expression profile of twelve reference genes: eEF-1α, FK506, UBQL40, RpS8, RpS18, HSP, GAPDH, VATPase, ACT3, TBP, eIF2 and G6PD. We tested the stability of their expression profiles in three different tissues (wings, brains, antennae), two developmental stages (pupal and adult) and two sexes (male and female), all of which were subjected to two food treatments (food stress and control feeding ad libitum). The expression stability and ranking of twelve reference genes was assessed using two algorithm-based methods, NormFinder and geNorm. Both methods identified RpS8 as the best suitable reference gene for expression data normalization. We also showed that the use of two reference genes is sufficient to effectively normalize the qRT-PCR data under varying tissues and experimental conditions that we used in B. anynana. Finally, we tested the effect of choosing reference genes with different stability on the normalization of the transcript abundance of a candidate gene involved in olfactory communication in B. anynana, the Fatty Acyl Reductase 2, and we confirmed that using an unstable reference gene can drastically alter the expression profile of the target candidate genes.

Chromosome position effects on gene expression in Escherichia coli K-12

PubMed Central

Bryant, Jack A.; Sellars, Laura E.; Busby, Stephen J. W.; Lee, David J.

2014-01-01

In eukaryotes, the location of a gene on the chromosome is known to affect its expression, but such position effects are poorly understood in bacteria. Here, using Escherichia coli K-12, we demonstrate that expression of a reporter gene cassette, comprised of the model E. coli lac promoter driving expression of gfp, varies by ∼300-fold depending on its precise position on the chromosome. At some positions, expression was more than 3-fold higher than at the natural lac promoter locus, whereas at several other locations, the reporter cassette was completely silenced: effectively overriding local lac promoter control. These effects were not due to differences in gene copy number, caused by partially replicated genomes. Rather, the differences in gene expression occur predominantly at the level of transcription and are mediated by several different features that are involved in chromosome organization. Taken together, our findings identify a tier of gene regulation above local promoter control and highlight the importance of chromosome position effects on gene expression profiles in bacteria. PMID:25209233

TRACING CO-REGULATORY NETWORK DYNAMICS IN NOISY, SINGLE-CELL TRANSCRIPTOME TRAJECTORIES.

PubMed

Cordero, Pablo; Stuart, Joshua M

2017-01-01

The availability of gene expression data at the single cell level makes it possible to probe the molecular underpinnings of complex biological processes such as differentiation and oncogenesis. Promising new methods have emerged for reconstructing a progression 'trajectory' from static single-cell transcriptome measurements. However, it remains unclear how to adequately model the appreciable level of noise in these data to elucidate gene regulatory network rewiring. Here, we present a framework called Single Cell Inference of MorphIng Trajectories and their Associated Regulation (SCIMITAR) that infers progressions from static single-cell transcriptomes by employing a continuous parametrization of Gaussian mixtures in high-dimensional curves. SCIMITAR yields rich models from the data that highlight genes with expression and co-expression patterns that are associated with the inferred progression. Further, SCIMITAR extracts regulatory states from the implicated trajectory-evolvingco-expression networks. We benchmark the method on simulated data to show that it yields accurate cell ordering and gene network inferences. Applied to the interpretation of a single-cell human fetal neuron dataset, SCIMITAR finds progression-associated genes in cornerstone neural differentiation pathways missed by standard differential expression tests. Finally, by leveraging the rewiring of gene-gene co-expression relations across the progression, the method reveals the rise and fall of co-regulatory states and trajectory-dependent gene modules. These analyses implicate new transcription factors in neural differentiation including putative co-factors for the multi-functional NFAT pathway.

Alterations of Clock Gene RNA Expression in Brain Regions of a Triple Transgenic Model of Alzheimer’s Disease

PubMed Central

Bellanti, Francesco; Iannelli, Giuseppina; Blonda, Maria; Tamborra, Rosanna; Villani, Rosanna; Romano, Adele; Calcagnini, Silvio; Mazzoccoli, Gianluigi; Vinciguerra, Manlio; Gaetani, Silvana; Giudetti, Anna Maria; Vendemiale, Gianluigi; Cassano, Tommaso; Serviddio, Gaetano

2017-01-01

A disruption to circadian rhythmicity and the sleep/wake cycle constitutes a major feature of Alzheimer’s disease (AD). The maintenance of circadian rhythmicity is regulated by endogenous clock genes and a number of external Zeitgebers, including light. This study investigated the light induced changes in the expression of clock genes in a triple transgenic model of AD (3×Tg-AD) and their wild type littermates (Non-Tg). Changes in gene expression were evaluated in four brain areas¾suprachiasmatic nucleus (SCN), hippocampus, frontal cortex and brainstem¾of 6- and 18-month-old Non-Tg and 3×Tg-AD mice after 12 h exposure to light or darkness. Light exposure exerted significant effects on clock gene expression in the SCN, the site of the major circadian pacemaker. These patterns of expression were disrupted in 3×Tg-AD and in 18-month-old compared with 6-month-old Non-Tg mice. In other brain areas, age rather than genotype affected gene expression; the effect of genotype was observed on hippocampal Sirt1 expression, while it modified the expression of genes regulating the negative feedback loop as well as Rorα, Csnk1ɛ and Sirt1 in the brainstem. In conclusion, during the early development of AD, there is a disruption to the normal expression of genes regulating circadian function after exposure to light, particularly in the SCN but also in extra-hypothalamic brain areas supporting circadian regulation, suggesting a severe impairment of functioning of the clock gene pathway. Even though this study did not demonstrate a direct association between these alterations in clock gene expression among brain areas with the cognitive impairments and chrono-disruption that characterize the early onset of AD, our novel results encourage further investigation aimed at testing this hypothesis. PMID:28671110

Histone acetylation is associated with differential gene expression in the rapid and robust memory CD8+ T-cell response

PubMed Central

Fann, Monchou; Godlove, Jason M.; Catalfamo, Marta; Wood, William H.; Chrest, Francis J.; Chun, Nicholas; Granger, Larry; Wersto, Robert; Madara, Karen; Becker, Kevin; Henkart, Pierre A.; Weng, Nan-ping

2006-01-01

To understand the molecular basis for the rapid and robust memory T-cell responses, we examined gene expression and chromatin modification by histone H3 lysine 9 (H3K9) acetylation in resting and activated human naive and memory CD8+ T cells. We found that, although overall gene expression patterns were similar, a number of genes are differentially expressed in either memory or naive cells in their resting and activated states. To further elucidate the basis for differential gene expression, we assessed the role of histone H3K9 acetylation in differential gene expression. Strikingly, higher H3K9 acetylation levels were detected in resting memory cells, prior to their activation, for those genes that were differentially expressed following activation, indicating that hyperacetylation of histone H3K9 may play a role in selective and rapid gene expression of memory CD8+ T cells. Consistent with this model, we showed that inducing high levels of H3K9 acetylation resulted in an increased expression in naive cells of those genes that are normally expressed differentially in memory cells. Together, these findings suggest that differential gene expression mediated at least in part by histone H3K9 hyperacetylation may be responsible for the rapid and robust memory CD8+ T-cell response. PMID:16868257

Molecular mechanisms underlying origin and diversification of the angiosperm flower.

PubMed

Theissen, Guenter; Melzer, Rainer

2007-09-01

Understanding the mode and mechanisms of the evolution of the angiosperm flower is a long-standing and central problem of evolutionary biology and botany. It has essentially remained unsolved, however. In contrast, considerable progress has recently been made in our understanding of the genetic basis of flower development in some extant model species. The knowledge that accumulated this way has been pulled together in two major hypotheses, termed the 'ABC model' and the 'floral quartet model'. These models explain how the identity of the different types of floral organs is specified during flower development by homeotic selector genes encoding transcription factors. We intend to explain how the 'ABC model' and the 'floral quartet model' are now guiding investigations that help to understand the origin and diversification of the angiosperm flower. Investigation of orthologues of class B and class C floral homeotic genes in gymnosperms suggest that bisexuality was one of the first innovations during the origin of the flower. The transition from dimer to tetramer formation of floral homeotic proteins after establishment of class E proteins may have increased cooperativity of DNA binding of the transcription factors controlling reproductive growth. That way, we hypothesize, better 'developmental switches' originated that facilitated the early evolution of the flower. Expression studies of ABC genes in basally diverging angiosperm lineages, monocots and basal eudicots suggest that the 'classical' ABC system known from core eudicots originated from a more fuzzy system with fading borders of gene expression and gradual transitions in organ identity, by sharpening of ABC gene expression domains and organ borders. Shifting boundaries of ABC gene expression may have contributed to the diversification of the angiosperm flower many times independently, as may have changes in interactions between ABC genes and their target genes.

Testing the predictive value of peripheral gene expression for nonremission following citalopram treatment for major depression.

PubMed

Guilloux, Jean-Philippe; Bassi, Sabrina; Ding, Ying; Walsh, Chris; Turecki, Gustavo; Tseng, George; Cyranowski, Jill M; Sibille, Etienne

2015-02-01

Major depressive disorder (MDD) in general, and anxious-depression in particular, are characterized by poor rates of remission with first-line treatments, contributing to the chronic illness burden suffered by many patients. Prospective research is needed to identify the biomarkers predicting nonremission prior to treatment initiation. We collected blood samples from a discovery cohort of 34 adult MDD patients with co-occurring anxiety and 33 matched, nondepressed controls at baseline and after 12 weeks (of citalopram plus psychotherapy treatment for the depressed cohort). Samples were processed on gene arrays and group differences in gene expression were investigated. Exploratory analyses suggest that at pretreatment baseline, nonremitting patients differ from controls with gene function and transcription factor analyses potentially related to elevated inflammation and immune activation. In a second phase, we applied an unbiased machine learning prediction model and corrected for model-selection bias. Results show that baseline gene expression predicted nonremission with 79.4% corrected accuracy with a 13-gene model. The same gene-only model predicted nonremission after 8 weeks of citalopram treatment with 76% corrected accuracy in an independent validation cohort of 63 MDD patients treated with citalopram at another institution. Together, these results demonstrate the potential, but also the limitations, of baseline peripheral blood-based gene expression to predict nonremission after citalopram treatment. These results not only support their use in future prediction tools but also suggest that increased accuracy may be obtained with the inclusion of additional predictors (eg, genetics and clinical scales).

Gene Expression Analyses of Subchondral Bone in Early Experimental Osteoarthritis by Microarray

PubMed Central

Chen, YuXian; Shen, Jun; Lu, HuaDing; Zeng, Chun; Ren, JianHua; Zeng, Hua; Li, ZhiFu; Chen, ShaoMing; Cai, DaoZhang; Zhao, Qing

2012-01-01

Osteoarthritis (OA) is a degenerative joint disease that affects both cartilage and bone. A better understanding of the early molecular changes in subchondral bone may help elucidate the pathogenesis of OA. We used microarray technology to investigate the time course of molecular changes in the subchondral bone in the early stages of experimental osteoarthritis in a rat model. We identified 2,234 differentially expressed (DE) genes at 1 week, 1,944 at 2 weeks and 1,517 at 4 weeks post-surgery. Further analyses of the dysregulated genes indicated that the events underlying subchondral bone remodeling occurred sequentially and in a time-dependent manner at the gene expression level. Some of the identified dysregulated genes that were identified have suspected roles in bone development or remodeling; these genes include Alp, Igf1, Tgf β1, Postn, Mmp3, Tnfsf11, Acp5, Bmp5, Aspn and Ihh. The differences in the expression of these genes were confirmed by real-time PCR, and the results indicated that our microarray data accurately reflected gene expression patterns characteristic of early OA. To validate the results of our microarray analysis at the protein level, immunohistochemistry staining was used to investigate the expression of Mmp3 and Aspn protein in tissue sections. These analyses indicate that Mmp3 protein expression completely matched the results of both the microarray and real-time PCR analyses; however, Aspn protein expression was not observed to differ at any time. In summary, our study demonstrated a simple method of separation of subchondral bone sample from the knee joint of rat, which can effectively avoid bone RNA degradation. These findings also revealed the gene expression profiles of subchondral bone in the rat OA model at multiple time points post-surgery and identified important DE genes with known or suspected roles in bone development or remodeling. These genes may be novel diagnostic markers or therapeutic targets for OA. PMID:22384228

Reverse-engineering the genetic circuitry of a cancer cell with predicted intervention in chronic lymphocytic leukemia.

PubMed

Vallat, Laurent; Kemper, Corey A; Jung, Nicolas; Maumy-Bertrand, Myriam; Bertrand, Frédéric; Meyer, Nicolas; Pocheville, Arnaud; Fisher, John W; Gribben, John G; Bahram, Seiamak

2013-01-08

Cellular behavior is sustained by genetic programs that are progressively disrupted in pathological conditions--notably, cancer. High-throughput gene expression profiling has been used to infer statistical models describing these cellular programs, and development is now needed to guide orientated modulation of these systems. Here we develop a regression-based model to reverse-engineer a temporal genetic program, based on relevant patterns of gene expression after cell stimulation. This method integrates the temporal dimension of biological rewiring of genetic programs and enables the prediction of the effect of targeted gene disruption at the system level. We tested the performance accuracy of this model on synthetic data before reverse-engineering the response of primary cancer cells to a proliferative (protumorigenic) stimulation in a multistate leukemia biological model (i.e., chronic lymphocytic leukemia). To validate the ability of our method to predict the effects of gene modulation on the global program, we performed an intervention experiment on a targeted gene. Comparison of the predicted and observed gene expression changes demonstrates the possibility of predicting the effects of a perturbation in a gene regulatory network, a first step toward an orientated intervention in a cancer cell genetic program.

Gluten affects epithelial differentiation-associated genes in small intestinal mucosa of coeliac patients

PubMed Central

Juuti-Uusitalo, K; Mäki, M; Kainulainen, H; Isola, J; Kaukinen, K

2007-01-01

In coeliac disease gluten induces an immunological reaction in genetically susceptible patients, and influences on epithelial cell proliferation and differentiation in the small-bowel mucosa. Our aim was to find novel genes which operate similarly in epithelial proliferation and differentiation in an epithelial cell differentiation model and in coeliac disease patient small-bowel mucosal biopsy samples. The combination of cDNA microarray data originating from a three-dimensional T84 epithelial cell differentiation model and small-bowel mucosal biopsy samples from untreated and treated coeliac disease patients and healthy controls resulted in 30 genes whose mRNA expression was similarly affected. Nine of 30 were located directly or indirectly in the receptor tyrosine kinase pathway starting from the epithelial growth factor receptor. Removal of gluten from the diet resulted in a reversion in the expression of 29 of the 30 genes in the small-bowel mucosal biopsy samples. Further characterization by blotting and labelling revealed increased epidermal growth factor receptor and beta-catenin protein expression in the small-bowel mucosal epithelium in untreated coeliac disease patients compared to healthy controls and treated coeliac patients. We found 30 genes whose mRNA expression was affected similarly in the epithelial cell differentiation model and in the coeliac disease patient small-bowel mucosal biopsy samples. In particular, those genes involved in the epithelial growth factor-mediated signalling pathways may be involved in epithelial cell differentiation and coeliac disease pathogenesis. The epithelial cell differentiation model is a useful tool for studying gene expression changes in the crypt–villus axis. PMID:17888028

Using expression genetics to study the neurobiology of ethanol and alcoholism.

PubMed

Farris, Sean P; Wolen, Aaron R; Miles, Michael F

2010-01-01

Recent simultaneous progress in human and animal model genetics and the advent of microarray whole genome expression profiling have produced prodigious data sets on genetic loci, potential candidate genes, and differential gene expression related to alcoholism and ethanol behaviors. Validated target genes or gene networks functioning in alcoholism are still of meager proportions. Genetical genomics, which combines genetic analysis of both traditional phenotypes and whole genome expression data, offers a potential methodology for characterizing brain gene networks functioning in alcoholism. This chapter will describe concepts, approaches, and recent findings in the field of genetical genomics as it applies to alcohol research. Copyright 2010 Elsevier Inc. All rights reserved.

Dynamic sporulation gene co-expression networks for Bacillus subtilis 168 and the food-borne isolate Bacillus amyloliquefaciens: a transcriptomic model

PubMed Central

Omony, Jimmy; de Jong, Anne; Krawczyk, Antonina O.; Eijlander, Robyn T.; Kuipers, Oscar P.

2018-01-01

Sporulation is a survival strategy, adapted by bacterial cells in response to harsh environmental adversities. The adaptation potential differs between strains and the variations may arise from differences in gene regulation. Gene networks are a valuable way of studying such regulation processes and establishing associations between genes. We reconstructed and compared sporulation gene co-expression networks (GCNs) of the model laboratory strain Bacillus subtilis 168 and the food-borne industrial isolate Bacillus amyloliquefaciens. Transcriptome data obtained from samples of six stages during the sporulation process were used for network inference. Subsequently, a gene set enrichment analysis was performed to compare the reconstructed GCNs of B. subtilis 168 and B. amyloliquefaciens with respect to biological functions, which showed the enriched modules with coherent functional groups associated with sporulation. On basis of the GCNs and time-evolution of differentially expressed genes, we could identify novel candidate genes strongly associated with sporulation in B. subtilis 168 and B. amyloliquefaciens. The GCNs offer a framework for exploring transcription factors, their targets, and co-expressed genes during sporulation. Furthermore, the methodology described here can conveniently be applied to other species or biological processes. PMID:29424683

Dynamic sporulation gene co-expression networks for Bacillus subtilis 168 and the food-borne isolate Bacillus amyloliquefaciens: a transcriptomic model.

PubMed

Omony, Jimmy; de Jong, Anne; Krawczyk, Antonina O; Eijlander, Robyn T; Kuipers, Oscar P

2018-02-09

Sporulation is a survival strategy, adapted by bacterial cells in response to harsh environmental adversities. The adaptation potential differs between strains and the variations may arise from differences in gene regulation. Gene networks are a valuable way of studying such regulation processes and establishing associations between genes. We reconstructed and compared sporulation gene co-expression networks (GCNs) of the model laboratory strain Bacillus subtilis 168 and the food-borne industrial isolate Bacillus amyloliquefaciens. Transcriptome data obtained from samples of six stages during the sporulation process were used for network inference. Subsequently, a gene set enrichment analysis was performed to compare the reconstructed GCNs of B. subtilis 168 and B. amyloliquefaciens with respect to biological functions, which showed the enriched modules with coherent functional groups associated with sporulation. On basis of the GCNs and time-evolution of differentially expressed genes, we could identify novel candidate genes strongly associated with sporulation in B. subtilis 168 and B. amyloliquefaciens. The GCNs offer a framework for exploring transcription factors, their targets, and co-expressed genes during sporulation. Furthermore, the methodology described here can conveniently be applied to other species or biological processes.

[Transcription of protein arginine N-methyltransferase genes in mouse dorsal root ganglia following peripheral nerve injury].

PubMed

Xu, Hua-Li; Xu, Shi-Yuan; Mo, Kai

2017-12-20

To investigate the changes in the transcription of protein arginine methylation enzyme family genes in the dorsal root ganglia (DRG) following peripheral nerve injury in mice. C57BL6 mouse models of neuropathic pain induced by peripheral nerve injury were established by bilateral L4 spinal nerve ligation (SNL). At 7 days after SNL or sham operation, the DRG tissue was collected for transcriptional analysis of 9 protein arginine methylation enzyme genes (Prmt1?3, Carm1, and Prmt5?9) using RNA?Seq to identify the differentially expressed genes in the injured DRGs. We also established mouse models of lateral L4 SNL and models of chronic constriction injury (CCI) of the sciatic nerve and tested the paw withdrawal frequency (PWF) in response to mechanical stimulation and paw withdrawal latency (PWL) in response to thermal stimulation on 0, 3, 7 and 14 days after SNL or CCI; the expressions of the differentially expressed genes in the injured DRGs were verified in the two models using RT?qPCR. Among the 9 protein arginine methylation enzyme family genes that were tissue?specifically expressed in the DRG, Prmt2 and Prmt3 showed the highest and Prmt6 showed the lowest basal expression. Compared with the sham?operated mice group, the mice receiving SNL exhibited upregulated Carm1 gene transcription (by 1.7 folds) but downregulated Prmt5, Prmt8 and Prmt9 transcription in the injured DRG (Prmt8 gene showed the most significant down?regulation by 16.3 folds). In mouse models of SNL and CCI, Carm1 gene expression increased progressively with time while Prmt8 transcription was obviously lowered on days 3, 7 and 14 after the injury; the transcription levels of Prmt1, Prmt5 and Prmt9 presented with no significant changes following the injuries. Both SNL and CCI induced mechanical allodynia and thermal hypersensitivities in the mice shown by increased PWF and decreased PWL on days 3, 7 and 14 after the injuries. Periphery nerve injury induces Carm1 upregulation and Prmt8 downregulation in the injured DRG in mice, which sheds light on new targets for treatment of neuropathic pain.

Dietary sodium propionate affects mucosal immune parameters, growth and appetite related genes expression: Insights from zebrafish model.

PubMed

Hoseinifar, Seyed Hossein; Safari, Roghieh; Dadar, Maryam

2017-03-01

Propionate is a short-chain fatty acid (SCFA) that improves physiological and pathophysiological properties. However, there is limited information available about the effects of SCFAs on mucosal immune parameters as well as growth and appetite related genes expression. The aim of the present study was to evaluate the effect of sodium propionate (SP) intake on the mucosal immune parameters, growth and appetite related genes expression using zebrafish (Danio rerio) as model organism. Zebrafish fed control or diet supplemented with different levels (0.5, 1 and 2%) of SP for 8weeks. At the end of feeding trial, the expression of the key genes related to growth and appetite (GH, IGF1, MYSTN and Ghrl) was evaluated. Also, mucosal immune parameters (Total Ig, lysozyme and protease activity) were studied in skin mucus of zebrafish. The results showed that dietary administration of SP significantly (P<0.05) up-regulated the expression of GH, IGF1 and down-regulated MYSTN gene. Also, feeding zebrafish with SP supplemented diet significantly increased appetite related gene expression (P<0.05) with a more pronounced effect in higher inclusion levels. Compared with control group, the expression of appetite related gene (Ghrl) was remarkably (P<0.05) higher in SP fed zebrafish. Also, elevated mucosal immune parameters was observed in zebrafish fed SP supplemented diet. The present results revealed beneficial effects of dietary SP on mucosal immune response and growth and appetite related genes expression. These results also highlighted the potential use of SP as additive in human diets. Copyright © 2016 Elsevier Inc. All rights reserved.

Gene expression complex networks: synthesis, identification, and analysis.

PubMed

Lopes, Fabrício M; Cesar, Roberto M; Costa, Luciano Da F

2011-10-01

Thanks to recent advances in molecular biology, allied to an ever increasing amount of experimental data, the functional state of thousands of genes can now be extracted simultaneously by using methods such as cDNA microarrays and RNA-Seq. Particularly important related investigations are the modeling and identification of gene regulatory networks from expression data sets. Such a knowledge is fundamental for many applications, such as disease treatment, therapeutic intervention strategies and drugs design, as well as for planning high-throughput new experiments. Methods have been developed for gene networks modeling and identification from expression profiles. However, an important open problem regards how to validate such approaches and its results. This work presents an objective approach for validation of gene network modeling and identification which comprises the following three main aspects: (1) Artificial Gene Networks (AGNs) model generation through theoretical models of complex networks, which is used to simulate temporal expression data; (2) a computational method for gene network identification from the simulated data, which is founded on a feature selection approach where a target gene is fixed and the expression profile is observed for all other genes in order to identify a relevant subset of predictors; and (3) validation of the identified AGN-based network through comparison with the original network. The proposed framework allows several types of AGNs to be generated and used in order to simulate temporal expression data. The results of the network identification method can then be compared to the original network in order to estimate its properties and accuracy. Some of the most important theoretical models of complex networks have been assessed: the uniformly-random Erdös-Rényi (ER), the small-world Watts-Strogatz (WS), the scale-free Barabási-Albert (BA), and geographical networks (GG). The experimental results indicate that the inference method was sensitive to average degree variation, decreasing its network recovery rate with the increase of . The signal size was important for the inference method to get better accuracy in the network identification rate, presenting very good results with small expression profiles. However, the adopted inference method was not sensible to recognize distinct structures of interaction among genes, presenting a similar behavior when applied to different network topologies. In summary, the proposed framework, though simple, was adequate for the validation of the inferred networks by identifying some properties of the evaluated method, which can be extended to other inference methods.

Dysregulation of gene expression in the striatum of BACHD rats expressing full-length mutant huntingtin and associated abnormalities on molecular and protein levels.

PubMed

Yu-Taeger, Libo; Bonin, Michael; Stricker-Shaver, Janice; Riess, Olaf; Nguyen, Hoa Huu Phuc

2017-05-01

Huntington disease (HD) is an autosomal dominantly inherited neurodegenerative disorder caused by a CAG repeat expansion in the gene coding for the huntingtin protein (HTT). Mutant HTT (mHTT) has been proposed to cause neuronal dysfunction and neuronal loss through multiple mechanisms. Transcriptional changes may be a core pathogenic feature of HD. Utilizing the Affymetrix platform we performed a genome-wide RNA expression analysis in two BACHD transgenic rat lines (TG5 and TG9) at 12 months of age, both of which carry full-length human mHTT but with different expression levels. By defining the threshold of significance at p < 0.01, we found 1608 genes and 871 genes differentially expressed in both TG5 and TG9 rats when compared to the wild type littermates, respectively. We only chose the highly up-/down-regulated genes for further analysis by setting an additional threshold of 1.5 fold change. Comparing gene expression profiles of human HD brains and BACHD rats revealed a high concordance in both functional and IPA (Ingenuity Pathway Analysis) canonical pathways relevant to HD. In addition, we investigated the causes leading to gene expression changes at molecular and protein levels in BACHD rats including the involvement of polyQ-containing transcription factors TATA box-binding protein (TBP), Sp1 and CBP as well as the chromatin structure. We demonstrate that the BACHD rat model recapitulates the gene expression changes of the human disease supporting its role as a preclinical research animal model. We also show for the first time that TFIID complex formation is reduced, while soluble TBP is increased in an HD model. This finding suggests that mHTT is a competitor instead of a recruiter of polyQ-containing transcription factors in the transcription process in HD. Copyright © 2017 Elsevier Ltd. All rights reserved.

Meta-analysis of gene expression patterns in animal models of prenatal alcohol exposure suggests role for protein synthesis inhibition and chromatin remodeling

PubMed Central

Rogic, Sanja; Wong, Albertina; Pavlidis, Paul

2017-01-01

Background Prenatal alcohol exposure (PAE) can result in an array of morphological, behavioural and neurobiological deficits that can range in their severity. Despite extensive research in the field and a significant progress made, especially in understanding the range of possible malformations and neurobehavioral abnormalities, the molecular mechanisms of alcohol responses in development are still not well understood. There have been multiple transcriptomic studies looking at the changes in gene expression after PAE in animal models, however there is a limited apparent consensus among the reported findings. In an effort to address this issue, we performed a comprehensive re-analysis and meta-analysis of all suitable, publically available expression data sets. Methods We assembled ten microarray data sets of gene expression after PAE in mouse and rat models consisting of samples from a total of 63 ethanol-exposed and 80 control animals. We re-analyzed each data set for differential expression and then used the results to perform meta-analyses considering all data sets together or grouping them by time or duration of exposure (pre- and post-natal, acute and chronic, respectively). We performed network and Gene Ontology enrichment analysis to further characterize the identified signatures. Results For each sub-analysis we identified signatures of differential expressed genes that show support from multiple studies. Overall, the changes in gene expression were more extensive after acute ethanol treatment during prenatal development than in other models. Considering the analysis of all the data together, we identified a robust core signature of 104 genes down-regulated after PAE, with no up-regulated genes. Functional analysis reveals over-representation of genes involved in protein synthesis, mRNA splicing and chromatin organization. Conclusions Our meta-analysis shows that existing studies, despite superficial dissimilarity in findings, share features that allow us to identify a common core signature set of transcriptome changes in PAE. This is an important step to identifying the biological processes that underlie the etiology of FASD. PMID:26996386

Integrating toxin gene expression, growth and fumonisin B1 and B2 production by a strain of Fusarium verticillioides under different environmental factors

PubMed Central

Medina, Angel; Schmidt-Heydt, Markus; Cárdenas-Chávez, Diana L.; Parra, Roberto; Geisen, Rolf; Magan, Naresh

2013-01-01

The objective of this study was to integrate data on the effect of water activity (aw; 0.995–0.93) and temperature (20–35°C) on activation of the biosynthetic FUM genes, growth and the mycotoxins fumonisin (FB1, FB2) by Fusarium verticillioides in vitro. The relative expression of nine biosynthetic cluster genes (FUM1, FUM7, FUM10, FUM11, FUM12, FUM13, FUM14, FUM16 and FUM19) in relation to the environmental factors was determined using a microarray analysis. The expression was related to growth and phenotypic FB1 and FB2 production. These data were used to develop a mixed-growth-associated product formation model and link this to a linear combination of the expression data for the nine genes. The model was then validated by examining datasets outside the model fitting conditions used (35°C). The relationship between the key gene (FUM1) and other genes in the cluster (FUM11, FUM13, FUM9, FUM14) were examined in relation to aw, temperature, FB1 and FB2 production by developing ternary diagrams of relative expression. This model is important in developing an integrated systems approach to develop prevention strategies to control fumonisin biosynthesis in staple food commodities and could also be used to predict the potential impact that climate change factors may have on toxin production. PMID:23697716

Expression profiles of urbilaterian genes uniquely shared between honey bee and vertebrates

PubMed Central

Matsui, Toshiaki; Yamamoto, Toshiyuki; Wyder, Stefan; Zdobnov, Evgeny M; Kadowaki, Tatsuhiko

2009-01-01

Background Large-scale comparison of metazoan genomes has revealed that a significant fraction of genes of the last common ancestor of Bilateria (Urbilateria) is lost in each animal lineage. This event could be one of the underlying mechanisms involved in generating metazoan diversity. However, the present functions of these ancient genes have not been addressed extensively. To understand the functions and evolutionary mechanisms of such ancient Urbilaterian genes, we carried out comprehensive expression profile analysis of genes shared between vertebrates and honey bees but not with the other sequenced ecdysozoan genomes (honey bee-vertebrate specific, HVS genes) as a model. Results We identified 30 honey bee and 55 mouse HVS genes. Many HVS genes exhibited tissue-selective expression patterns; intriguingly, the expression of 60% of honey bee HVS genes was found to be brain enriched, and 24% of mouse HVS genes were highly expressed in either or both the brain and testis. Moreover, a minimum of 38% of mouse HVS genes demonstrated neuron-enriched expression patterns, and 62% of them exhibited expression in selective brain areas, particularly the forebrain and cerebellum. Furthermore, gene ontology (GO) analysis of HVS genes predicted that 35% of genes are associated with DNA transcription and RNA processing. Conclusion These results suggest that HVS genes include genes that are biased towards expression in the brain and gonads. They also demonstrate that at least some of Urbilaterian genes retained in the specific animal lineage may be selectively maintained to support the species-specific phenotypes. PMID:19138430

Expression profiles of urbilaterian genes uniquely shared between honey bee and vertebrates.

PubMed

Matsui, Toshiaki; Yamamoto, Toshiyuki; Wyder, Stefan; Zdobnov, Evgeny M; Kadowaki, Tatsuhiko

2009-01-12

Large-scale comparison of metazoan genomes has revealed that a significant fraction of genes of the last common ancestor of Bilateria (Urbilateria) is lost in each animal lineage. This event could be one of the underlying mechanisms involved in generating metazoan diversity. However, the present functions of these ancient genes have not been addressed extensively. To understand the functions and evolutionary mechanisms of such ancient Urbilaterian genes, we carried out comprehensive expression profile analysis of genes shared between vertebrates and honey bees but not with the other sequenced ecdysozoan genomes (honey bee-vertebrate specific, HVS genes) as a model. We identified 30 honey bee and 55 mouse HVS genes. Many HVS genes exhibited tissue-selective expression patterns; intriguingly, the expression of 60% of honey bee HVS genes was found to be brain enriched, and 24% of mouse HVS genes were highly expressed in either or both the brain and testis. Moreover, a minimum of 38% of mouse HVS genes demonstrated neuron-enriched expression patterns, and 62% of them exhibited expression in selective brain areas, particularly the forebrain and cerebellum. Furthermore, gene ontology (GO) analysis of HVS genes predicted that 35% of genes are associated with DNA transcription and RNA processing. These results suggest that HVS genes include genes that are biased towards expression in the brain and gonads. They also demonstrate that at least some of Urbilaterian genes retained in the specific animal lineage may be selectively maintained to support the species-specific phenotypes.

Transcriptome analyses and differential gene expression in a non-model fish species with alternative mating tactics

PubMed Central

2014-01-01

Background Social dominance is important for the reproductive success of males in many species. In the black-faced blenny (Tripterygion delaisi) during the reproductive season, some males change color and invest in nest making and defending a territory, whereas others do not change color and ‘sneak’ reproductions when females lay their eggs. Using RNAseq, we profiled differential gene expression between the brains of territorial males, sneaker males, and females to study the molecular signatures of male dimorphism. Results We found that more genes were differentially expressed between the two male phenotypes than between males and females, suggesting that during the reproductive period phenotypic plasticity is a more important factor in differential gene expression than sexual dimorphism. The territorial male overexpresses genes related to synaptic plasticity and the sneaker male overexpresses genes involved in differentiation and development. Conclusions Previously suggested candidate genes for social dominance in the context of alternative mating strategies seem to be predominantly species-specific. We present a list of novel genes which are differentially expressed in Tripterygion delaisi. This is the first genome-wide study for a molecular non-model species in the context of alternative mating strategies and provides essential information for further studies investigating the molecular basis of social dominance. PMID:24581002

Cutaneous gene expression of plasmid DNA in excised human skin following delivery via microchannels created by radio frequency ablation.

PubMed

Birchall, James; Coulman, Sion; Anstey, Alexander; Gateley, Chris; Sweetland, Helen; Gershonowitz, Amikam; Neville, Lewis; Levin, Galit

2006-04-07

The skin is a valuable organ for the development and exploitation of gene medicines. Delivering genes to skin is restricted however by the physico-chemical properties of DNA and the stratum corneum (SC) barrier. In this study, we demonstrate the utility of an innovative technology that creates transient microconduits in human skin, allowing DNA delivery and resultant gene expression within the epidermis and dermis layers. The radio frequency (RF)-generated microchannels were of sufficient morphology and depth to permit the epidermal delivery of 100 nm diameter nanoparticles. Model fluorescent nanoparticles were used to confirm the capacity of the channels for augmenting diffusion of macromolecules through the SC. An ex vivo human organ culture model was used to establish the gene expression efficiency of a beta-galactosidase reporter plasmid DNA applied to ViaDerm treated skin. Skin treated with ViaDerm using 50 microm electrode arrays promoted intense levels of gene expression in the viable epidermis. The intensity and extent of gene expression was superior when ViaDerm was used following a prior surface application of the DNA formulation. In conclusion, the RF-microchannel generator (ViaDerm) creates microchannels amenable for delivery of nanoparticles and gene therapy vectors to the viable region of skin.

Transcriptome analyses and differential gene expression in a non-model fish species with alternative mating tactics.

PubMed

Schunter, Celia; Vollmer, Steven V; Macpherson, Enrique; Pascual, Marta

2014-02-28

Social dominance is important for the reproductive success of males in many species. In the black-faced blenny (Tripterygion delaisi) during the reproductive season, some males change color and invest in nest making and defending a territory, whereas others do not change color and 'sneak' reproductions when females lay their eggs. Using RNAseq, we profiled differential gene expression between the brains of territorial males, sneaker males, and females to study the molecular signatures of male dimorphism. We found that more genes were differentially expressed between the two male phenotypes than between males and females, suggesting that during the reproductive period phenotypic plasticity is a more important factor in differential gene expression than sexual dimorphism. The territorial male overexpresses genes related to synaptic plasticity and the sneaker male overexpresses genes involved in differentiation and development. Previously suggested candidate genes for social dominance in the context of alternative mating strategies seem to be predominantly species-specific. We present a list of novel genes which are differentially expressed in Tripterygion delaisi. This is the first genome-wide study for a molecular non-model species in the context of alternative mating strategies and provides essential information for further studies investigating the molecular basis of social dominance.

Reconstructing regulatory networks from the dynamic plasticity of gene expression by mutual information

PubMed Central

Wang, Jianxin; Chen, Bo; Wang, Yaqun; Wang, Ningtao; Garbey, Marc; Tran-Son-Tay, Roger; Berceli, Scott A.; Wu, Rongling

2013-01-01

The capacity of an organism to respond to its environment is facilitated by the environmentally induced alteration of gene and protein expression, i.e. expression plasticity. The reconstruction of gene regulatory networks based on expression plasticity can gain not only new insights into the causality of transcriptional and cellular processes but also the complex regulatory mechanisms that underlie biological function and adaptation. We describe an approach for network inference by integrating expression plasticity into Shannon’s mutual information. Beyond Pearson correlation, mutual information can capture non-linear dependencies and topology sparseness. The approach measures the network of dependencies of genes expressed in different environments, allowing the environment-induced plasticity of gene dependencies to be tested in unprecedented details. The approach is also able to characterize the extent to which the same genes trigger different amounts of expression in response to environmental changes. We demonstrated the usefulness of this approach through analysing gene expression data from a rabbit vein graft study that includes two distinct blood flow environments. The proposed approach provides a powerful tool for the modelling and analysis of dynamic regulatory networks using gene expression data from distinct environments. PMID:23470995

Genome-Wide Gene Expression in relation to Age in Large Laboratory Cohorts of Drosophila melanogaster

PubMed Central

Carlson, Kimberly A.; Gardner, Kylee; Pashaj, Anjeza; Carlson, Darby J.; Yu, Fang; Eudy, James D.; Zhang, Chi; Harshman, Lawrence G.

2015-01-01

Aging is a complex process characterized by a steady decline in an organism's ability to perform life-sustaining tasks. In the present study, two cages of approximately 12,000 mated Drosophila melanogaster females were used as a source of RNA from individuals sampled frequently as a function of age. A linear model for microarray data method was used for the microarray analysis to adjust for the box effect; it identified 1,581 candidate aging genes. Cluster analyses using a self-organizing map algorithm on the 1,581 significant genes identified gene expression patterns across different ages. Genes involved in immune system function and regulation, chorion assembly and function, and metabolism were all significantly differentially expressed as a function of age. The temporal pattern of data indicated that gene expression related to aging is affected relatively early in life span. In addition, the temporal variance in gene expression in immune function genes was compared to a random set of genes. There was an increase in the variance of gene expression within each cohort, which was not observed in the set of random genes. This observation is compatible with the hypothesis that D. melanogaster immune function genes lose control of gene expression as flies age. PMID:26090231

Genome-Wide Identification and Testing of Superior Reference Genes for Transcript Normalization in Arabidopsis1[w

PubMed Central

Czechowski, Tomasz; Stitt, Mark; Altmann, Thomas; Udvardi, Michael K.; Scheible, Wolf-Rüdiger

2005-01-01

Gene transcripts with invariant abundance during development and in the face of environmental stimuli are essential reference points for accurate gene expression analyses, such as RNA gel-blot analysis or quantitative reverse transcription-polymerase chain reaction (PCR). An exceptionally large set of data from Affymetrix ATH1 whole-genome GeneChip studies provided the means to identify a new generation of reference genes with very stable expression levels in the model plant species Arabidopsis (Arabidopsis thaliana). Hundreds of Arabidopsis genes were found that outperform traditional reference genes in terms of expression stability throughout development and under a range of environmental conditions. Most of these were expressed at much lower levels than traditional reference genes, making them very suitable for normalization of gene expression over a wide range of transcript levels. Specific and efficient primers were developed for 22 genes and tested on a diverse set of 20 cDNA samples. Quantitative reverse transcription-PCR confirmed superior expression stability and lower absolute expression levels for many of these genes, including genes encoding a protein phosphatase 2A subunit, a coatomer subunit, and an ubiquitin-conjugating enzyme. The developed PCR primers or hybridization probes for the novel reference genes will enable better normalization and quantification of transcript levels in Arabidopsis in the future. PMID:16166256

A Compendium of Canine Normal Tissue Gene Expression

PubMed Central

Chen, Qing-Rong; Wen, Xinyu; Khan, Javed; Khanna, Chand

2011-01-01

Background Our understanding of disease is increasingly informed by changes in gene expression between normal and abnormal tissues. The release of the canine genome sequence in 2005 provided an opportunity to better understand human health and disease using the dog as clinically relevant model. Accordingly, we now present the first genome-wide, canine normal tissue gene expression compendium with corresponding human cross-species analysis. Methodology/Principal Findings The Affymetrix platform was utilized to catalogue gene expression signatures of 10 normal canine tissues including: liver, kidney, heart, lung, cerebrum, lymph node, spleen, jejunum, pancreas and skeletal muscle. The quality of the database was assessed in several ways. Organ defining gene sets were identified for each tissue and functional enrichment analysis revealed themes consistent with known physio-anatomic functions for each organ. In addition, a comparison of orthologous gene expression between matched canine and human normal tissues uncovered remarkable similarity. To demonstrate the utility of this dataset, novel canine gene annotations were established based on comparative analysis of dog and human tissue selective gene expression and manual curation of canine probeset mapping. Public access, using infrastructure identical to that currently in use for human normal tissues, has been established and allows for additional comparisons across species. Conclusions/Significance These data advance our understanding of the canine genome through a comprehensive analysis of gene expression in a diverse set of tissues, contributing to improved functional annotation that has been lacking. Importantly, it will be used to inform future studies of disease in the dog as a model for human translational research and provides a novel resource to the community at large. PMID:21655323

Analysis of functional importance of binding sites in the Drosophila gap gene network model.

PubMed

Kozlov, Konstantin; Gursky, Vitaly V; Kulakovskiy, Ivan V; Dymova, Arina; Samsonova, Maria

2015-01-01

The statistical thermodynamics based approach provides a promising framework for construction of the genotype-phenotype map in many biological systems. Among important aspects of a good model connecting the DNA sequence information with that of a molecular phenotype (gene expression) is the selection of regulatory interactions and relevant transcription factor bindings sites. As the model may predict different levels of the functional importance of specific binding sites in different genomic and regulatory contexts, it is essential to formulate and study such models under different modeling assumptions. We elaborate a two-layer model for the Drosophila gap gene network and include in the model a combined set of transcription factor binding sites and concentration dependent regulatory interaction between gap genes hunchback and Kruppel. We show that the new variants of the model are more consistent in terms of gene expression predictions for various genetic constructs in comparison to previous work. We quantify the functional importance of binding sites by calculating their impact on gene expression in the model and calculate how these impacts correlate across all sites under different modeling assumptions. The assumption about the dual interaction between hb and Kr leads to the most consistent modeling results, but, on the other hand, may obscure existence of indirect interactions between binding sites in regulatory regions of distinct genes. The analysis confirms the previously formulated regulation concept of many weak binding sites working in concert. The model predicts a more or less uniform distribution of functionally important binding sites over the sets of experimentally characterized regulatory modules and other open chromatin domains.

Expression of glutathione S-transferases in poplar trees (Populus trichocarpa) exposed to 2,4,6-trinitrotoluene (TNT).

PubMed

Brentner, Laura B; Mukherji, Sachiyo T; Merchie, Kate M; Yoon, Jong Moon; Schnoor, Jerald L; Van Aken, Benoit

2008-10-01

Twelve Populus genes were identified from Arabidopsis thaliana sequences previously shown to be induced by exposure to 2,4,6-trinitrotoluene (TNT). Using the resources of the Poplar Genome Project and National Center for Biotechnology Information databases, Populus conserved domains were identified and used to design gene specific primers. RNA extracted from root tissues of TNT-exposed hydroponic poplar plants was used to quantify the expression of genes by reverse-transcriptase real-time polymerase chain reaction. Cyclophilin and 18S ribosomal DNA genes were used as internal standards. Exposure to TNT resulted in a significant increase of gene expression of two glutathione S-transferases (GST), peaking at levels of 25.0 +/- 13.1 and 10 +/- 0.7 fold the expression level of non-exposed plants after 24 h for each of the GST genes, respectively. This paper demonstrates the use of functional genomics information from the model plant species, Arabidopsis, to identify genes which may be important in detoxification of TNT in the model phytoremediation species, Populus trichocarpa.

Systems biology approach to late-onset Alzheimer's disease genome-wide association study identifies novel candidate genes validated using brain expression data and Caenorhabditis elegans experiments.

PubMed

Mukherjee, Shubhabrata; Russell, Joshua C; Carr, Daniel T; Burgess, Jeremy D; Allen, Mariet; Serie, Daniel J; Boehme, Kevin L; Kauwe, John S K; Naj, Adam C; Fardo, David W; Dickson, Dennis W; Montine, Thomas J; Ertekin-Taner, Nilufer; Kaeberlein, Matt R; Crane, Paul K

2017-10-01

We sought to determine whether a systems biology approach may identify novel late-onset Alzheimer's disease (LOAD) loci. We performed gene-wide association analyses and integrated results with human protein-protein interaction data using network analyses. We performed functional validation on novel genes using a transgenic Caenorhabditis elegans Aβ proteotoxicity model and evaluated novel genes using brain expression data from people with LOAD and other neurodegenerative conditions. We identified 13 novel candidate LOAD genes outside chromosome 19. Of those, RNA interference knockdowns of the C. elegans orthologs of UBC, NDUFS3, EGR1, and ATP5H were associated with Aβ toxicity, and NDUFS3, SLC25A11, ATP5H, and APP were differentially expressed in the temporal cortex. Network analyses identified novel LOAD candidate genes. We demonstrated a functional role for four of these in a C. elegans model and found enrichment of differentially expressed genes in the temporal cortex. Copyright © 2017 the Alzheimer's Association. Published by Elsevier Inc. All rights reserved.

Topical Gene Electrotransfer to the Epidermis of Hairless Guinea Pig by Non-Invasive Multielectrode Array

PubMed Central

Guo, Siqi; Israel, Annelise L.; Basu, Gaurav; Donate, Amy; Heller, Richard

2013-01-01

Topical gene delivery to the epidermis has the potential to be an effective therapy for skin disorders, cutaneous cancers, vaccinations and systemic metabolic diseases. Previously, we reported on a non-invasive multielectrode array (MEA) that efficiently delivered plasmid DNA and enhanced expression to the skin of several animal models by in vivo gene electrotransfer. Here, we characterized plasmid DNA delivery with the MEA in a hairless guinea pig model, which has a similar histology and structure to human skin. Significant elevation of gene expression up to 4 logs was achieved with intradermal DNA administration followed by topical non-invasive skin gene electrotransfer. This delivery produced gene expression in the skin of hairless guinea pig up to 12 to 15 days. Gene expression was observed exclusively in the epidermis. Skin gene electrotransfer with the MEA resulted in only minimal and mild skin changes. A low level of human Factor IX was detected in the plasma of hairless guinea pig after gene electrotransfer with the MEA, although a significant increase of Factor IX was obtained in the skin of animals. These results suggest gene electrotransfer with the MEA can be a safe, efficient, non-invasive skin delivery method for skin disorders, vaccinations and potential systemic diseases where low levels of gene products are sufficient. PMID:24015305

Prenatal administration of retinoic acid upregulates connective tissue growth factor in the nitrofen CDH model.

PubMed

Ruttenstock, Elke Maria; Doi, Takashi; Dingemann, Jens; Puri, Prem

2011-06-01

Recent studies have suggested that retinoids may be involved in the molecular mechanisms of pulmonary hypoplasia (PH) in congenital diaphragmatic hernia (CDH). Connective tissue growth factor (CTGF) plays a key role in foetal lung development and remodelling during later gestation. CTGF knockout mice exhibit PH with similar characteristics to the human and nitrofen-induced PH. Prenatal administration of retinoic acid (RA) has been shown to stimulate alveologenesis in nitrofen-induced PH. In vitro studies have revealed that RA can induce CTGF gene expression. We hypothesized that pulmonary gene expression of CTGF is downregulated during the later stages of lung development, and that prenatal administration of RA upregulates CTGF in the nitrofen CDH model. Pregnant rats were exposed to either olive oil or nitrofen on day 9 (D9) of gestation. RA was given intraperitoneally on D18, D19 and D20. Foetuses were harvested on D21 and divided into control, CDH, control + RA and CDH + RA group. Pulmonary CTGF gene and protein expression levels were determined using RT-PCR and immunohistochemistry. On D21, CTGF relative mRNA expression levels were significantly downregulated in CDH group compared to controls. After RA treatment, expression levels of CTGF were significantly upregulated in CDH + RA and control + RA compared to the CDH group. Immunohistochemical studies confirmed these results. Downregulation of pulmonary CTGF gene and protein expression during later stages of lung development may interfere with normal alveologenesis in the nitrofen CDH model. Upregulation of CTGF pulmonary gene expression after prenatal RA treatment may promote lung growth by promoting alveologenesis in the nitrofen-induced CDH model.

Analysis of changes in hepatic gene expression in a murine model of tolerance to acetaminophen hepatotoxicity (autoprotection)

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

O'Connor, Meeghan A., E-mail: meeghan.oconnor@boehringer-ingelheim.com; Boehringer Ingelheim Pharmaceuticals Inc., 900 Ridgebury Road, Ridgefield, CT 06877-0368; Koza-Taylor, Petra, E-mail: petra.h.koza-taylor@pfizer.com

Pretreatment of mice with a low hepatotoxic dose of acetaminophen (APAP) results in resistance to a subsequent, higher dose of APAP. This mouse model, termed APAP autoprotection was used here to identify differentially expressed genes and cellular pathways that could contribute to this development of resistance to hepatotoxicity. Male C57BL/6J mice were pretreated with APAP (400 mg/kg) and then challenged 48 h later with 600 mg APAP/kg. Livers were obtained 4 or 24 h later and total hepatic RNA was isolated and hybridized to Affymetrix Mouse Genome MU430{sub 2} GeneChip. Statistically significant genes were determined and gene expression changes weremore » also interrogated using the Causal Reasoning Engine (CRE). Extensive literature review narrowed our focus to methionine adenosyl transferase-1 alpha (MAT1A), nuclear factor (erythroid-derived 2)-like 2 (Nrf2), flavin-containing monooxygenase 3 (Fmo3) and galectin-3 (Lgals3). Down-regulation of MAT1A could lead to decreases in S-adenosylmethionine (SAMe), which is known to protect against APAP toxicity. Nrf2 activation is expected to play a role in protective adaptation. Up-regulation of Lgals3, one of the genes supporting the Nrf2 hypothesis, can lead to suppression of apoptosis and reduced mitochondrial dysfunction. Fmo3 induction suggests the involvement of an enzyme not known to metabolize APAP in the development of tolerance to APAP toxicity. Subsequent quantitative RT-PCR and immunochemical analysis confirmed the differential expression of some of these genes in the APAP autoprotection model. In conclusion, our genomics strategy identified cellular pathways that might further explain the molecular basis for APAP autoprotection. - Highlights: • Differential expression of genes in mice resistant to acetaminophen hepatotoxicity. • Increased gene expression of Flavin-containing monooxygenase 3 and Galectin-3. • Decrease in MAT1A expression and compensatory hepatocellular regeneration. • Two distinct gene expression patterns support contrasting Nrf2 responses. • Genomics identification of pathways relevant to resistance to APAP hepatotoxicity.« less

Transcript profiling reveals expression differences in wild-type and glabrous soybean lines

PubMed Central

2011-01-01

Background Trichome hairs affect diverse agronomic characters such as seed weight and yield, prevent insect damage and reduce loss of water but their molecular control has not been extensively studied in soybean. Several detailed models for trichome development have been proposed for Arabidopsis thaliana, but their applicability to important crops such as cotton and soybean is not fully known. Results Two high throughput transcript sequencing methods, Digital Gene Expression (DGE) Tag Profiling and RNA-Seq, were used to compare the transcriptional profiles in wild-type (cv. Clark standard, CS) and a mutant (cv. Clark glabrous, i.e., trichomeless or hairless, CG) soybean isoline that carries the dominant P1 allele. DGE data and RNA-Seq data were mapped to the cDNAs (Glyma models) predicted from the reference soybean genome, Williams 82. Extending the model length by 250 bp at both ends resulted in significantly more matches of authentic DGE tags indicating that many of the predicted gene models are prematurely truncated at the 5' and 3' UTRs. The genome-wide comparative study of the transcript profiles of the wild-type versus mutant line revealed a number of differentially expressed genes. One highly-expressed gene, Glyma04g35130, in wild-type soybean was of interest as it has high homology to the cotton gene GhRDL1 gene that has been identified as being involved in cotton fiber initiation and is a member of the BURP protein family. Sequence comparison of Glyma04g35130 among Williams 82 with our sequences derived from CS and CG isolines revealed various SNPs and indels including addition of one nucleotide C in the CG and insertion of ~60 bp in the third exon of CS that causes a frameshift mutation and premature truncation of peptides in both lines as compared to Williams 82. Conclusion Although not a candidate for the P1 locus, a BURP family member (Glyma04g35130) from soybean has been shown to be abundantly expressed in the CS line and very weakly expressed in the glabrous CG line. RNA-Seq and DGE data are compared and provide experimental data on the expression of predicted soybean gene models as well as an overview of the genes expressed in young shoot tips of two closely related isolines. PMID:22029708

A Risk Stratification Model for Lung Cancer Based on Gene Coexpression Network and Deep Learning

PubMed Central

2018-01-01

Risk stratification model for lung cancer with gene expression profile is of great interest. Instead of previous models based on individual prognostic genes, we aimed to develop a novel system-level risk stratification model for lung adenocarcinoma based on gene coexpression network. Using multiple microarray, gene coexpression network analysis was performed to identify survival-related networks. A deep learning based risk stratification model was constructed with representative genes of these networks. The model was validated in two test sets. Survival analysis was performed using the output of the model to evaluate whether it could predict patients' survival independent of clinicopathological variables. Five networks were significantly associated with patients' survival. Considering prognostic significance and representativeness, genes of the two survival-related networks were selected for input of the model. The output of the model was significantly associated with patients' survival in two test sets and training set (p < 0.00001, p < 0.0001 and p = 0.02 for training and test sets 1 and 2, resp.). In multivariate analyses, the model was associated with patients' prognosis independent of other clinicopathological features. Our study presents a new perspective on incorporating gene coexpression networks into the gene expression signature and clinical application of deep learning in genomic data science for prognosis prediction. PMID:29581968

Myostatin propeptide gene delivery by gene gun ameliorates muscle atrophy in a rat model of botulinum toxin-induced nerve denervation.

PubMed

Tsai, Sen-Wei; Tung, Yu-Tang; Chen, Hsiao-Ling; Yang, Shang-Hsun; Liu, Chia-Yi; Lu, Michelle; Pai, Hui-Jing; Lin, Chi-Chen; Chen, Chuan-Mu

2016-02-01

Muscle atrophy is a common symptom after nerve denervation. Myostatin propeptide, a precursor of myostatin, has been documented to improve muscle growth. However, the mechanism underlying the muscle atrophy attenuation effects of myostatin propeptide in muscles and the changes in gene expression are not well established. We investigated the possible underlying mechanisms associated with myostatin propeptide gene delivery by gene gun in a rat denervation muscle atrophy model, and evaluated gene expression patterns. In a rat botulinum toxin-induced nerve denervation muscle atrophy model, we evaluated the effects of wild-type (MSPP) and mutant-type (MSPPD75A) of myostatin propeptide gene delivery, and observed changes in gene activation associated with the neuromuscular junction, muscle and nerve. Muscle mass and muscle fiber size was moderately increased in myostatin propeptide treated muscles (p<0.05). And enhancement of the gene expression of the muscle regulatory factors, neurite outgrowth factors (IGF-1, GAP43) and acetylcholine receptors was observed. Our results demonstrate that myostatin propeptide gene delivery, especially the mutant-type of MSPPD75A, attenuates muscle atrophy through myogenic regulatory factors and acetylcholine receptor regulation. Our data concluded that myostatin propeptide gene therapy may be a promising treatment for nerve denervation induced muscle atrophy. Copyright © 2016 Elsevier Inc. All rights reserved.

Molecular Signatures Discriminating the Male and the Female Sexual Pathways in the Pearl Oyster Pinctada margaritifera

PubMed Central

Teaniniuraitemoana, Vaihiti; Huvet, Arnaud; Levy, Peva; Gaertner-Mazouni, Nabila; Gueguen, Yannick; Le Moullac, Gilles

2015-01-01

The genomics of economically important marine bivalves is studied to provide better understanding of the molecular mechanisms underlying their different reproductive strategies. The recently available gonad transcriptome of the black-lip pearl oyster Pinctada margaritifera is a novel and powerful resource to study these mechanisms in marine mollusks displaying hermaphroditic features. In this study, RNAseq quantification data of the P. margaritifera gonad transcriptome were analyzed to identify candidate genes in histologically-characterized gonad samples to provide molecular signatures of the female and male sexual pathway in this pearl oyster. Based on the RNAseq data set, stringent expression analysis identified 1,937 contigs that were differentially expressed between the gonad histological categories. From the hierarchical clustering analysis, a new reproduction model is proposed, based on a dual histo-molecular analytical approach. Nine candidate genes were identified as markers of the sexual pathway: 7 for the female pathway and 2 for the male one. Their mRNA levels were assayed by real-time PCR on a new set of gonadic samples. A clustering method revealed four principal expression patterns based on the relative gene expression ratio. A multivariate regression tree realized on these new samples and validated on the previously analyzed RNAseq samples showed that the sexual pathway of P. margaritifera can be predicted by a 3-gene-pair expression ratio model of 4 different genes: pmarg-43476, pmarg-foxl2, pmarg-54338 and pmarg-fem1-like. This 3-gene-pair expression ratio model strongly suggests only the implication of pmarg-foxl2 and pmarg-fem1-like in the sex inversion of P. margaritifera. This work provides the first histo-molecular model of P. margaritifera reproduction and a gene expression signature of its sexual pathway discriminating the male and female pathways. These represent useful tools for understanding and studying sex inversion, sex differentiation and sex determinism in this species and other related species for aquaculture purposes such as genetic selection programs. PMID:25815473

Validation of reference genes for normalization of qPCR mRNA expression levels in Staphylococcus aureus exposed to osmotic and lactic acid stress conditions encountered during food production and preservation.

PubMed

Sihto, Henna-Maria; Tasara, Taurai; Stephan, Roger; Johler, Sophia

2014-07-01

Staphylococcus aureus represents the most prevalent cause of food-borne intoxications worldwide. While being repressed by competing bacteria in most matrices, this pathogen exhibits crucial competitive advantages during growth at high salt concentrations or low pH, conditions frequently encountered in food production and preservation. We aimed to identify reference genes that could be used to normalize qPCR mRNA expression levels during growth of S. aureus in food-related osmotic (NaCl) and acidic (lactic acid) stress adaptation models. Expression stability of nine housekeeping genes was evaluated in full (LB) and nutrient-deficient (CYGP w/o glucose) medium under conditions of osmotic (4.5% NaCl) and acidic stress (lactic acid, pH 6.0) after 2-h exposure. Among the set of candidate reference genes investigated, rplD, rpoB,gyrB, and rho were most stably expressed in LB and thus represent the most suitable reference genes for normalization of qPCR data in osmotic or lactic acid stress models in a rich medium. Under nutrient-deficient conditions, expression of rho and rpoB was highly stable across all tested conditions. The presented comprehensive data on changes in expression of various S. aureus housekeeping genes under conditions of osmotic and lactic acid stress facilitate selection of reference genes for qPCR-based stress response models. © 2014 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved.

Reference gene selection for quantitative gene expression studies during biological invasions: A test on multiple genes and tissues in a model ascidian Ciona savignyi.

PubMed

Huang, Xuena; Gao, Yangchun; Jiang, Bei; Zhou, Zunchun; Zhan, Aibin

2016-01-15

As invasive species have successfully colonized a wide range of dramatically different local environments, they offer a good opportunity to study interactions between species and rapidly changing environments. Gene expression represents one of the primary and crucial mechanisms for rapid adaptation to local environments. Here, we aim to select reference genes for quantitative gene expression analysis based on quantitative Real-Time PCR (qRT-PCR) for a model invasive ascidian, Ciona savignyi. We analyzed the stability of ten candidate reference genes in three tissues (siphon, pharynx and intestine) under two key environmental stresses (temperature and salinity) in the marine realm based on three programs (geNorm, NormFinder and delta Ct method). Our results demonstrated only minor difference for stability rankings among the three methods. The use of different single reference gene might influence the data interpretation, while multiple reference genes could minimize possible errors. Therefore, reference gene combinations were recommended for different tissues - the optimal reference gene combination for siphon was RPS15 and RPL17 under temperature stress, and RPL17, UBQ and TubA under salinity treatment; for pharynx, TubB, TubA and RPL17 were the most stable genes under temperature stress, while TubB, TubA and UBQ were the best under salinity stress; for intestine, UBQ, RPS15 and RPL17 were the most reliable reference genes under both treatments. Our results suggest that the necessity of selection and test of reference genes for different tissues under varying environmental stresses. The results obtained here are expected to reveal mechanisms of gene expression-mediated invasion success using C. savignyi as a model species. Copyright © 2015 Elsevier B.V. All rights reserved.

Bayesian estimation of differential transcript usage from RNA-seq data.

PubMed

Papastamoulis, Panagiotis; Rattray, Magnus

2017-11-27

Next generation sequencing allows the identification of genes consisting of differentially expressed transcripts, a term which usually refers to changes in the overall expression level. A specific type of differential expression is differential transcript usage (DTU) and targets changes in the relative within gene expression of a transcript. The contribution of this paper is to: (a) extend the use of cjBitSeq to the DTU context, a previously introduced Bayesian model which is originally designed for identifying changes in overall expression levels and (b) propose a Bayesian version of DRIMSeq, a frequentist model for inferring DTU. cjBitSeq is a read based model and performs fully Bayesian inference by MCMC sampling on the space of latent state of each transcript per gene. BayesDRIMSeq is a count based model and estimates the Bayes Factor of a DTU model against a null model using Laplace's approximation. The proposed models are benchmarked against the existing ones using a recent independent simulation study as well as a real RNA-seq dataset. Our results suggest that the Bayesian methods exhibit similar performance with DRIMSeq in terms of precision/recall but offer better calibration of False Discovery Rate.

EMAP and EMAGE: a framework for understanding spatially organized data.

PubMed

Baldock, Richard A; Bard, Jonathan B L; Burger, Albert; Burton, Nicolas; Christiansen, Jeff; Feng, Guanjie; Hill, Bill; Houghton, Derek; Kaufman, Matthew; Rao, Jianguo; Sharpe, James; Ross, Allyson; Stevenson, Peter; Venkataraman, Shanmugasundaram; Waterhouse, Andrew; Yang, Yiya; Davidson, Duncan R

2003-01-01

The Edinburgh MouseAtlas Project (EMAP) is a time-series of mouse-embryo volumetric models. The models provide a context-free spatial framework onto which structural interpretations and experimental data can be mapped. This enables collation, comparison, and query of complex spatial patterns with respect to each other and with respect to known or hypothesized structure. The atlas also includes a time-dependent anatomical ontology and mapping between the ontology and the spatial models in the form of delineated anatomical regions or tissues. The models provide a natural, graphical context for browsing and visualizing complex data. The Edinburgh Mouse Atlas Gene-Expression Database (EMAGE) is one of the first applications of the EMAP framework and provides a spatially mapped gene-expression database with associated tools for data mapping, submission, and query. In this article, we describe the underlying principles of the Atlas and the gene-expression database, and provide a practical introduction to the use of the EMAP and EMAGE tools, including use of new techniques for whole body gene-expression data capture and mapping.

Sequential Logic Model Deciphers Dynamic Transcriptional Control of Gene Expressions

PubMed Central

Yeo, Zhen Xuan; Wong, Sum Thai; Arjunan, Satya Nanda Vel; Piras, Vincent; Tomita, Masaru; Selvarajoo, Kumar; Giuliani, Alessandro; Tsuchiya, Masa

2007-01-01

Background Cellular signaling involves a sequence of events from ligand binding to membrane receptors through transcription factors activation and the induction of mRNA expression. The transcriptional-regulatory system plays a pivotal role in the control of gene expression. A novel computational approach to the study of gene regulation circuits is presented here. Methodology Based on the concept of finite state machine, which provides a discrete view of gene regulation, a novel sequential logic model (SLM) is developed to decipher control mechanisms of dynamic transcriptional regulation of gene expressions. The SLM technique is also used to systematically analyze the dynamic function of transcriptional inputs, the dependency and cooperativity, such as synergy effect, among the binding sites with respect to when, how much and how fast the gene of interest is expressed. Principal Findings SLM is verified by a set of well studied expression data on endo16 of Strongylocentrotus purpuratus (sea urchin) during the embryonic midgut development. A dynamic regulatory mechanism for endo16 expression controlled by three binding sites, UI, R and Otx is identified and demonstrated to be consistent with experimental findings. Furthermore, we show that during transition from specification to differentiation in wild type endo16 expression profile, SLM reveals three binary activities are not sufficient to explain the transcriptional regulation of endo16 expression and additional activities of binding sites are required. Further analyses suggest detailed mechanism of R switch activity where indirect dependency occurs in between UI activity and R switch during specification to differentiation stage. Conclusions/Significance The sequential logic formalism allows for a simplification of regulation network dynamics going from a continuous to a discrete representation of gene activation in time. In effect our SLM is non-parametric and model-independent, yet providing rich biological insight. The demonstration of the efficacy of this approach in endo16 is a promising step for further application of the proposed method. PMID:17712424

Finding gene clusters for a replicated time course study

PubMed Central

2014-01-01

Background Finding genes that share similar expression patterns across samples is an important question that is frequently asked in high-throughput microarray studies. Traditional clustering algorithms such as K-means clustering and hierarchical clustering base gene clustering directly on the observed measurements and do not take into account the specific experimental design under which the microarray data were collected. A new model-based clustering method, the clustering of regression models method, takes into account the specific design of the microarray study and bases the clustering on how genes are related to sample covariates. It can find useful gene clusters for studies from complicated study designs such as replicated time course studies. Findings In this paper, we applied the clustering of regression models method to data from a time course study of yeast on two genotypes, wild type and YOX1 mutant, each with two technical replicates, and compared the clustering results with K-means clustering. We identified gene clusters that have similar expression patterns in wild type yeast, two of which were missed by K-means clustering. We further identified gene clusters whose expression patterns were changed in YOX1 mutant yeast compared to wild type yeast. Conclusions The clustering of regression models method can be a valuable tool for identifying genes that are coordinately transcribed by a common mechanism. PMID:24460656

Promoter architecture dictates cell-to-cell variability in gene expression.

PubMed

Jones, Daniel L; Brewster, Robert C; Phillips, Rob

2014-12-19

Variability in gene expression among genetically identical cells has emerged as a central preoccupation in the study of gene regulation; however, a divide exists between the predictions of molecular models of prokaryotic transcriptional regulation and genome-wide experimental studies suggesting that this variability is indifferent to the underlying regulatory architecture. We constructed a set of promoters in Escherichia coli in which promoter strength, transcription factor binding strength, and transcription factor copy numbers are systematically varied, and used messenger RNA (mRNA) fluorescence in situ hybridization to observe how these changes affected variability in gene expression. Our parameter-free models predicted the observed variability; hence, the molecular details of transcription dictate variability in mRNA expression, and transcriptional noise is specifically tunable and thus represents an evolutionarily accessible phenotypic parameter. Copyright © 2014, American Association for the Advancement of Science.

Pathway activity inference for multiclass disease classification through a mathematical programming optimisation framework.

PubMed

Yang, Lingjian; Ainali, Chrysanthi; Tsoka, Sophia; Papageorgiou, Lazaros G

2014-12-05

Applying machine learning methods on microarray gene expression profiles for disease classification problems is a popular method to derive biomarkers, i.e. sets of genes that can predict disease state or outcome. Traditional approaches where expression of genes were treated independently suffer from low prediction accuracy and difficulty of biological interpretation. Current research efforts focus on integrating information on protein interactions through biochemical pathway datasets with expression profiles to propose pathway-based classifiers that can enhance disease diagnosis and prognosis. As most of the pathway activity inference methods in literature are either unsupervised or applied on two-class datasets, there is good scope to address such limitations by proposing novel methodologies. A supervised multiclass pathway activity inference method using optimisation techniques is reported. For each pathway expression dataset, patterns of its constituent genes are summarised into one composite feature, termed pathway activity, and a novel mathematical programming model is proposed to infer this feature as a weighted linear summation of expression of its constituent genes. Gene weights are determined by the optimisation model, in a way that the resulting pathway activity has the optimal discriminative power with regards to disease phenotypes. Classification is then performed on the resulting low-dimensional pathway activity profile. The model was evaluated through a variety of published gene expression profiles that cover different types of disease. We show that not only does it improve classification accuracy, but it can also perform well in multiclass disease datasets, a limitation of other approaches from the literature. Desirable features of the model include the ability to control the maximum number of genes that may participate in determining pathway activity, which may be pre-specified by the user. Overall, this work highlights the potential of building pathway-based multi-phenotype classifiers for accurate disease diagnosis and prognosis problems.

Tightly Regulated Expression of Autographa californica Multicapsid Nucleopolyhedrovirus Immediate Early Genes Emerges from Their Interactions and Possible Collective Behaviors

PubMed Central

Taka, Hitomi; Asano, Shin-ichiro; Matsuura, Yoshiharu; Bando, Hisanori

2015-01-01

To infect their hosts, DNA viruses must successfully initiate the expression of viral genes that control subsequent viral gene expression and manipulate the host environment. Viral genes that are immediately expressed upon infection play critical roles in the early infection process. In this study, we investigated the expression and regulation of five canonical regulatory immediate-early (IE) genes of Autographa californica multicapsid nucleopolyhedrovirus: ie0, ie1, ie2, me53, and pe38. A systematic transient gene-expression analysis revealed that these IE genes are generally transactivators, suggesting the existence of a highly interactive regulatory network. A genetic analysis using gene knockout viruses demonstrated that the expression of these IE genes was tolerant to the single deletions of activator IE genes in the early stage of infection. A network graph analysis on the regulatory relationships observed in the transient expression analysis suggested that the robustness of IE gene expression is due to the organization of the IE gene regulatory network and how each IE gene is activated. However, some regulatory relationships detected by the genetic analysis were contradictory to those observed in the transient expression analysis, especially for IE0-mediated regulation. Statistical modeling, combined with genetic analysis using knockout alleles for ie0 and ie1, showed that the repressor function of ie0 was due to the interaction between ie0 and ie1, not ie0 itself. Taken together, these systematic approaches provided insight into the topology and nature of the IE gene regulatory network. PMID:25816136

Identification of Conflicting Selective Effects on Highly Expressed Genes

PubMed Central

Higgs, Paul G.; Hao, Weilong; Golding, G. Brian

2007-01-01

Many different selective effects on DNA and proteins influence the frequency of codons and amino acids in coding sequences. Selection is often stronger on highly expressed genes. Hence, by comparing high- and low-expression genes it is possible to distinguish the factors that are selected by evolution. It has been proposed that highly expressed genes should (i) preferentially use codons matching abundant tRNAs (translational efficiency), (ii) preferentially use amino acids with low cost of synthesis, (iii) be under stronger selection to maintain the required amino acid content, and (iv) be selected for translational robustness. These effects act simultaneously and can be contradictory. We develop a model that combines these factors, and use Akaike’s Information Criterion for model selection. We consider pairs of paralogues that arose by whole-genome duplication in Saccharmyces cerevisiae. A codon-based model is used that includes asymmetric effects due to selection on highly expressed genes. The largest effect is translational efficiency, which is found to strongly influence synonymous, but not non-synonymous rates. Minimization of the cost of amino acid synthesis is implicated. However, when a more general measure of selection for amino acid usage is used, the cost minimization effect becomes redundant. Small effects that we attribute to selection for translational robustness can be identified as an improvement in the model fit on top of the effects of translational efficiency and amino acid usage. PMID:19430600

Novel dedifferentiated liposarcoma xenograft models reveal PTEN down-regulation as a malignant signature and response to PI3K pathway inhibition.

PubMed

Smith, Kathleen B; Tran, Linh M; Tam, Brenna M; Shurell, Elizabeth M; Li, Yunfeng; Braas, Daniel; Tap, William D; Christofk, Heather R; Dry, Sarah M; Eilber, Fritz C; Wu, Hong

2013-04-01

Liposarcoma is a type of soft tissue sarcoma that exhibits poor survival and a high recurrence rate. Treatment is generally limited to surgery and radiation, which emphasizes the need for better understanding of this disease. Because very few in vivo and in vitro models can reproducibly recapitulate the human disease, we generated several xenograft models from surgically resected human dedifferentiated liposarcoma. All xenografts recapitulated morphological and gene expression characteristics of the patient tumors after continuous in vivo passages. Importantly, xenograftability was directly correlated with disease-specific survival of liposarcoma patients. Thus, the ability for the tumor of a patient to engraft may help identify those patients who will benefit from more aggressive treatment regimens. Gene expression analyses highlighted the association between xenograftability and a unique gene expression signature, including down-regulated PTEN tumor-suppressor gene expression and a progenitor-like phenotype. When treated with the PI3K/AKT/mTOR pathway inhibitor rapamycin alone or in combination with the multikinase inhibitor sorafenib, all xenografts responded with increased lipid content and a more differentiated gene expression profile. These human xenograft models may facilitate liposarcoma research and accelerate the generation of readily translatable preclinical data that could ultimately influence patient care. Copyright © 2013 American Society for Investigative Pathology. Published by Elsevier Inc. All rights reserved.

Gene Expression Differences in Peripheral Blood of Parkinson’s Disease Patients with Distinct Progression Profiles

PubMed Central

Soreq, Lilach; Lobo, Patrícia P.; Mestre, Tiago; Coelho, Miguel; Rosa, Mário M.; Gonçalves, Nilza; Wales, Pauline; Mendes, Tiago; Gerhardt, Ellen; Fahlbusch, Christiane; Bonifati, Vincenzo; Bonin, Michael; Miltenberger-Miltényi, Gabriel; Borovecki, Fran; Soreq, Hermona; Ferreira, Joaquim J.; F. Outeiro, Tiago

2016-01-01

The prognosis of neurodegenerative disorders is clinically challenging due to the inexistence of established biomarkers for predicting disease progression. Here, we performed an exploratory cross-sectional, case-control study aimed at determining whether gene expression differences in peripheral blood may be used as a signature of Parkinson’s disease (PD) progression, thereby shedding light into potential molecular mechanisms underlying disease development. We compared transcriptional profiles in the blood from 34 PD patients who developed postural instability within ten years with those of 33 patients who did not develop postural instability within this time frame. Our study identified >200 differentially expressed genes between the two groups. The expression of several of the genes identified was previously found deregulated in animal models of PD and in PD patients. Relevant genes were selected for validation by real-time PCR in a subset of patients. The genes validated were linked to nucleic acid metabolism, mitochondria, immune response and intracellular-transport. Interestingly, we also found deregulation of these genes in a dopaminergic cell model of PD, a simple paradigm that can now be used to further dissect the role of these molecular players on dopaminergic cell loss. Altogether, our study provides preliminary evidence that expression changes in specific groups of genes and pathways, detected in peripheral blood samples, may be correlated with differential PD progression. Our exploratory study suggests that peripheral gene expression profiling may prove valuable for assisting in prediction of PD prognosis, and identifies novel culprits possibly involved in dopaminergic cell death. Given the exploratory nature of our study, further investigations using independent, well-characterized cohorts will be essential in order to validate our candidates as predictors of PD prognosis and to definitively confirm the value of gene expression analysis in aiding patient stratification and therapeutic intervention. PMID:27322389

Within and between Whorls: Comparative Transcriptional Profiling of Aquilegia and Arabidopsis

PubMed Central

Voelckel, Claudia; Borevitz, Justin O.; Kramer, Elena M.; Hodges, Scott A.

2010-01-01

Background The genus Aquilegia is an emerging model system in plant evolutionary biology predominantly because of its wide variation in floral traits and associated floral ecology. The anatomy of the Aquilegia flower is also very distinct. There are two whorls of petaloid organs, the outer whorl of sepals and the second whorl of petals that form nectar spurs, as well as a recently evolved fifth whorl of staminodia inserted between stamens and carpels. Methodology/Principal Findings We designed an oligonucleotide microarray based on EST sequences from a mixed tissue, normalized cDNA library of an A. formosa x A. pubescens F2 population representing 17,246 unigenes. We then used this array to analyze floral gene expression in late pre-anthesis stage floral organs from a natural A. formosa population. In particular, we tested for gene expression patterns specific to each floral whorl and to combinations of whorls that correspond to traditional and modified ABC model groupings. Similar analyses were performed on gene expression data of Arabidopsis thaliana whorls previously obtained using the Ath1 gene chips (data available through The Arabidopsis Information Resource). Conclusions/Significance Our comparative gene expression analyses suggest that 1) petaloid sepals and petals of A. formosa share gene expression patterns more than either have organ-specific patterns, 2) petals of A. formosa and A. thaliana may be independently derived, 3) staminodia express B and C genes similar to stamens but the staminodium genetic program has also converged on aspects of the carpel program and 4) staminodia have unique up-regulation of regulatory genes and genes that have been implicated with defense against microbial infection and herbivory. Our study also highlights the value of comparative gene expression profiling and the Aquilegia microarray in particular for the study of floral evolution and ecology. PMID:20352114

Differential In Vivo Gene Expression of Major Leptospira Proteins in Resistant or Susceptible Animal Models

PubMed Central

Matsui, Mariko; Soupé, Marie-Estelle; Becam, Jérôme

2012-01-01

Transcripts of Leptospira 16S rRNA, FlaB, LigB, LipL21, LipL32, LipL36, LipL41, and OmpL37 were quantified in the blood of susceptible (hamsters) and resistant (mice) animal models of leptospirosis. We first validated adequate reference genes and then evaluated expression patterns in vivo compared to in vitro cultures. LipL32 expression was downregulated in vivo and differentially regulated in resistant and susceptible animals. FlaB expression was also repressed in mice but not in hamsters. In contrast, LigB and OmpL37 were upregulated in vivo. Thus, we demonstrated that a virulent strain of Leptospira differentially adapts its gene expression in the blood of infected animals. PMID:22729538

Comparison of RNA-seq and microarray-based models for clinical endpoint prediction.

PubMed

Zhang, Wenqian; Yu, Ying; Hertwig, Falk; Thierry-Mieg, Jean; Zhang, Wenwei; Thierry-Mieg, Danielle; Wang, Jian; Furlanello, Cesare; Devanarayan, Viswanath; Cheng, Jie; Deng, Youping; Hero, Barbara; Hong, Huixiao; Jia, Meiwen; Li, Li; Lin, Simon M; Nikolsky, Yuri; Oberthuer, André; Qing, Tao; Su, Zhenqiang; Volland, Ruth; Wang, Charles; Wang, May D; Ai, Junmei; Albanese, Davide; Asgharzadeh, Shahab; Avigad, Smadar; Bao, Wenjun; Bessarabova, Marina; Brilliant, Murray H; Brors, Benedikt; Chierici, Marco; Chu, Tzu-Ming; Zhang, Jibin; Grundy, Richard G; He, Min Max; Hebbring, Scott; Kaufman, Howard L; Lababidi, Samir; Lancashire, Lee J; Li, Yan; Lu, Xin X; Luo, Heng; Ma, Xiwen; Ning, Baitang; Noguera, Rosa; Peifer, Martin; Phan, John H; Roels, Frederik; Rosswog, Carolina; Shao, Susan; Shen, Jie; Theissen, Jessica; Tonini, Gian Paolo; Vandesompele, Jo; Wu, Po-Yen; Xiao, Wenzhong; Xu, Joshua; Xu, Weihong; Xuan, Jiekun; Yang, Yong; Ye, Zhan; Dong, Zirui; Zhang, Ke K; Yin, Ye; Zhao, Chen; Zheng, Yuanting; Wolfinger, Russell D; Shi, Tieliu; Malkas, Linda H; Berthold, Frank; Wang, Jun; Tong, Weida; Shi, Leming; Peng, Zhiyu; Fischer, Matthias

2015-06-25

Gene expression profiling is being widely applied in cancer research to identify biomarkers for clinical endpoint prediction. Since RNA-seq provides a powerful tool for transcriptome-based applications beyond the limitations of microarrays, we sought to systematically evaluate the performance of RNA-seq-based and microarray-based classifiers in this MAQC-III/SEQC study for clinical endpoint prediction using neuroblastoma as a model. We generate gene expression profiles from 498 primary neuroblastomas using both RNA-seq and 44 k microarrays. Characterization of the neuroblastoma transcriptome by RNA-seq reveals that more than 48,000 genes and 200,000 transcripts are being expressed in this malignancy. We also find that RNA-seq provides much more detailed information on specific transcript expression patterns in clinico-genetic neuroblastoma subgroups than microarrays. To systematically compare the power of RNA-seq and microarray-based models in predicting clinical endpoints, we divide the cohort randomly into training and validation sets and develop 360 predictive models on six clinical endpoints of varying predictability. Evaluation of factors potentially affecting model performances reveals that prediction accuracies are most strongly influenced by the nature of the clinical endpoint, whereas technological platforms (RNA-seq vs. microarrays), RNA-seq data analysis pipelines, and feature levels (gene vs. transcript vs. exon-junction level) do not significantly affect performances of the models. We demonstrate that RNA-seq outperforms microarrays in determining the transcriptomic characteristics of cancer, while RNA-seq and microarray-based models perform similarly in clinical endpoint prediction. Our findings may be valuable to guide future studies on the development of gene expression-based predictive models and their implementation in clinical practice.

Investigating the Effects of Imputation Methods for Modelling Gene Networks Using a Dynamic Bayesian Network from Gene Expression Data

PubMed Central

CHAI, Lian En; LAW, Chow Kuan; MOHAMAD, Mohd Saberi; CHONG, Chuii Khim; CHOON, Yee Wen; DERIS, Safaai; ILLIAS, Rosli Md

2014-01-01

Background: Gene expression data often contain missing expression values. Therefore, several imputation methods have been applied to solve the missing values, which include k-nearest neighbour (kNN), local least squares (LLS), and Bayesian principal component analysis (BPCA). However, the effects of these imputation methods on the modelling of gene regulatory networks from gene expression data have rarely been investigated and analysed using a dynamic Bayesian network (DBN). Methods: In the present study, we separately imputed datasets of the Escherichia coli S.O.S. DNA repair pathway and the Saccharomyces cerevisiae cell cycle pathway with kNN, LLS, and BPCA, and subsequently used these to generate gene regulatory networks (GRNs) using a discrete DBN. We made comparisons on the basis of previous studies in order to select the gene network with the least error. Results: We found that BPCA and LLS performed better on larger networks (based on the S. cerevisiae dataset), whereas kNN performed better on smaller networks (based on the E. coli dataset). Conclusion: The results suggest that the performance of each imputation method is dependent on the size of the dataset, and this subsequently affects the modelling of the resultant GRNs using a DBN. In addition, on the basis of these results, a DBN has the capacity to discover potential edges, as well as display interactions, between genes. PMID:24876803

A cross-species analysis method to analyze animal models' similarity to human's disease state

PubMed Central

2012-01-01

Background Animal models are indispensable tools in studying the cause of human diseases and searching for the treatments. The scientific value of an animal model depends on the accurate mimicry of human diseases. The primary goal of the current study was to develop a cross-species method by using the animal models' expression data to evaluate the similarity to human diseases' and assess drug molecules' efficiency in drug research. Therefore, we hoped to reveal that it is feasible and useful to compare gene expression profiles across species in the studies of pathology, toxicology, drug repositioning, and drug action mechanism. Results We developed a cross-species analysis method to analyze animal models' similarity to human diseases and effectiveness in drug research by utilizing the existing animal gene expression data in the public database, and mined some meaningful information to help drug research, such as potential drug candidates, possible drug repositioning, side effects and analysis in pharmacology. New animal models could be evaluated by our method before they are used in drug discovery. We applied the method to several cases of known animal model expression profiles and obtained some useful information to help drug research. We found that trichostatin A and some other HDACs could have very similar response across cell lines and species at gene expression level. Mouse hypoxia model could accurately mimic the human hypoxia, while mouse diabetes drug model might have some limitation. The transgenic mouse of Alzheimer was a useful model and we deeply analyzed the biological mechanisms of some drugs in this case. In addition, all the cases could provide some ideas for drug discovery and drug repositioning. Conclusions We developed a new cross-species gene expression module comparison method to use animal models' expression data to analyse the effectiveness of animal models in drug research. Moreover, through data integration, our method could be applied for drug research, such as potential drug candidates, possible drug repositioning, side effects and information about pharmacology. PMID:23282076

A cross-species analysis method to analyze animal models' similarity to human's disease state.

PubMed

Yu, Shuhao; Zheng, Lulu; Li, Yun; Li, Chunyan; Ma, Chenchen; Li, Yixue; Li, Xuan; Hao, Pei

2012-01-01

Animal models are indispensable tools in studying the cause of human diseases and searching for the treatments. The scientific value of an animal model depends on the accurate mimicry of human diseases. The primary goal of the current study was to develop a cross-species method by using the animal models' expression data to evaluate the similarity to human diseases' and assess drug molecules' efficiency in drug research. Therefore, we hoped to reveal that it is feasible and useful to compare gene expression profiles across species in the studies of pathology, toxicology, drug repositioning, and drug action mechanism. We developed a cross-species analysis method to analyze animal models' similarity to human diseases and effectiveness in drug research by utilizing the existing animal gene expression data in the public database, and mined some meaningful information to help drug research, such as potential drug candidates, possible drug repositioning, side effects and analysis in pharmacology. New animal models could be evaluated by our method before they are used in drug discovery. We applied the method to several cases of known animal model expression profiles and obtained some useful information to help drug research. We found that trichostatin A and some other HDACs could have very similar response across cell lines and species at gene expression level. Mouse hypoxia model could accurately mimic the human hypoxia, while mouse diabetes drug model might have some limitation. The transgenic mouse of Alzheimer was a useful model and we deeply analyzed the biological mechanisms of some drugs in this case. In addition, all the cases could provide some ideas for drug discovery and drug repositioning. We developed a new cross-species gene expression module comparison method to use animal models' expression data to analyse the effectiveness of animal models in drug research. Moreover, through data integration, our method could be applied for drug research, such as potential drug candidates, possible drug repositioning, side effects and information about pharmacology.

Genome-Wide Expression Profiling of Five Mouse Models Identifies Similarities and Differences with Human Psoriasis

PubMed Central

Swindell, William R.; Johnston, Andrew; Carbajal, Steve; Han, Gangwen; Wohn, Christian; Lu, Jun; Xing, Xianying; Nair, Rajan P.; Voorhees, John J.; Elder, James T.; Wang, Xiao-Jing; Sano, Shigetoshi; Prens, Errol P.; DiGiovanni, John; Pittelkow, Mark R.; Ward, Nicole L.; Gudjonsson, Johann E.

2011-01-01

Development of a suitable mouse model would facilitate the investigation of pathomechanisms underlying human psoriasis and would also assist in development of therapeutic treatments. However, while many psoriasis mouse models have been proposed, no single model recapitulates all features of the human disease, and standardized validation criteria for psoriasis mouse models have not been widely applied. In this study, whole-genome transcriptional profiling is used to compare gene expression patterns manifested by human psoriatic skin lesions with those that occur in five psoriasis mouse models (K5-Tie2, imiquimod, K14-AREG, K5-Stat3C and K5-TGFbeta1). While the cutaneous gene expression profiles associated with each mouse phenotype exhibited statistically significant similarity to the expression profile of psoriasis in humans, each model displayed distinctive sets of similarities and differences in comparison to human psoriasis. For all five models, correspondence to the human disease was strong with respect to genes involved in epidermal development and keratinization. Immune and inflammation-associated gene expression, in contrast, was more variable between models as compared to the human disease. These findings support the value of all five models as research tools, each with identifiable areas of convergence to and divergence from the human disease. Additionally, the approach used in this paper provides an objective and quantitative method for evaluation of proposed mouse models of psoriasis, which can be strategically applied in future studies to score strengths of mouse phenotypes relative to specific aspects of human psoriasis. PMID:21483750

HOX gene expression in phenotypic and genotypic subgroups and low HOXA gene expression as an adverse prognostic factor in pediatric ALL.

PubMed

Starkova, Julia; Zamostna, Blanka; Mejstrikova, Ester; Krejci, Roman; Drabkin, Harry A; Trka, Jan

2010-12-01

HOX genes play an important role in both normal lymphopoiesis and leukemogenesis. However, HOX expression patterns in leukemia cells compared to normal lymphoid progenitors have not been systematically studied in acute lymphoblastic leukemia (ALL) subtypes. The RNA expression levels of HOXA, HOXB, and CDX1/2 genes were analyzed by qRT-PCR in a cohort of 61 diagnostic pediatric ALL samples and FACS-sorted subpopulations of normal lymphoid progenitors. The RNA expression of HOXA7-10, HOXA13, and HOXB2-4 genes was exclusively detected in leukemic cells and immature progenitors. The RNA expression of HOXB6 and CDX2 genes was exclusively detected in leukemic cells but not in B-lineage cells at any of the studied developmental stages. HOXA3-4, HOXA7, and HOXB3-4 genes were differentially expressed between BCP-ALL and T-ALL subgroups, and among genotypically defined MLL/AF4, TEL/AML1, BCR/ABL, hyperdiploid and normal karyotype subgroups. However, this differential expression did not define specific clusters in hierarchical cluster analysis. HOXA7 gene was low expressed at the RNA level in patients with hyperdiploid leukemia, whereas HOXB7 and CDX2 genes were low expressed in TEL/AML1-positive and BCR/ABL-positive cases, respectively. In contrast to previous findings in acute myeloid leukemia, high HOXA RNA expression was associated with an excellent prognosis in Cox's regression model (P = 0.03). In MLL/AF4-positive ALL, lower HOXA RNA expression correlated with the methylation status of their promoters. HOX gene RNA expression cannot discriminate leukemia subgroups or relative maturity of leukemic cells. However, HOXA RNA expression correlates with prognosis, and particular HOX genes are expressed in specific genotypically characterized subgroups.

Keratinocyte Growth Factor Gene Electroporation into Skeletal Muscle as a Novel Gene Therapeutic Approach for Elastase-Induced Pulmonary Emphysema in Mice.

PubMed

Tobinaga, Shuichi; Matsumoto, Keitaro; Nagayasu, Takeshi; Furukawa, Katsuro; Abo, Takafumi; Yamasaki, Naoya; Tsuchiya, Tomoshi; Miyazaki, Takuro; Koji, Takehiko

2015-06-29

Pulmonary emphysema is a progressive disease with airspace destruction and an effective therapy is needed. Keratinocyte growth factor (KGF) promotes pulmonary epithelial proliferation and has the potential to induce lung regeneration. The aim of this study was to determine the possibility of using KGF gene therapy for treatment of a mouse emphysema model induced by porcine pancreatic elastase (PPE). Eight-week-old BALB/c male mice treated with intra-tracheal PPE administration were transfected with 80 μg of a recombinant human KGF (rhKGF)-expressing FLAG-CMV14 plasmid (pKGF-FLAG gene), or with the pFLAG gene expressing plasmid as a control, into the quadriceps muscle by electroporation. In the lung, the expression of proliferating cell nuclear antigen (PCNA) was augmented, and surfactant protein A (SP-A) and KGF receptor (KGFR) were co-expressed in PCNA-positive cells. Moreover, endogenous KGF and KGFR gene expression increased significantly by pKGF-FLAG gene transfection. Arterial blood gas analysis revealed that the PaO2 level was not significantly reduced on day 14 after PPE instillation with pKGF-FLAG gene transfection compared to that of normal mice. These results indicated that KGF gene therapy with electroporation stimulated lung epithelial proliferation and protected depression of pulmonary function in a mouse emphysema model, suggesting a possible method of treating pulmonary emphysema.

Keratinocyte Growth Factor Gene Electroporation into Skeletal Muscle as a Novel Gene Therapeutic Approach for Elastase-Induced Pulmonary Emphysema in Mice

PubMed Central

Tobinaga, Shuichi; Matsumoto, Keitaro; Nagayasu, Takeshi; Furukawa, Katsuro; Abo, Takafumi; Yamasaki, Naoya; Tsuchiya, Tomoshi; Miyazaki, Takuro; Koji, Takehiko

2015-01-01

Pulmonary emphysema is a progressive disease with airspace destruction and an effective therapy is needed. Keratinocyte growth factor (KGF) promotes pulmonary epithelial proliferation and has the potential to induce lung regeneration. The aim of this study was to determine the possibility of using KGF gene therapy for treatment of a mouse emphysema model induced by porcine pancreatic elastase (PPE). Eight-week-old BALB/c male mice treated with intra-tracheal PPE administration were transfected with 80 μg of a recombinant human KGF (rhKGF)-expressing FLAG-CMV14 plasmid (pKGF-FLAG gene), or with the pFLAG gene expressing plasmid as a control, into the quadriceps muscle by electroporation. In the lung, the expression of proliferating cell nuclear antigen (PCNA) was augmented, and surfactant protein A (SP-A) and KGF receptor (KGFR) were co-expressed in PCNA-positive cells. Moreover, endogenous KGF and KGFR gene expression increased significantly by pKGF-FLAG gene transfection. Arterial blood gas analysis revealed that the PaO2 level was not significantly reduced on day 14 after PPE instillation with pKGF-FLAG gene transfection compared to that of normal mice. These results indicated that KGF gene therapy with electroporation stimulated lung epithelial proliferation and protected depression of pulmonary function in a mouse emphysema model, suggesting a possible method of treating pulmonary emphysema. PMID:26160987

Gene expression analysis uncovers novel Hedgehog interacting protein (HHIP) effects in human bronchial epithelial cells

PubMed Central

Zhou, Xiaobo; Qiu, Weiliang; Sathirapongsasuti, J. Fah.; Cho, Michael H.; Mancini, John D.; Lao, Taotao; Thibault, Derek M.; Litonjua, Gus; Bakke, Per S.; Gulsvik, Amund; Lomas, David A.; Beaty, Terri H.; Hersh, Craig P.; Anderson, Christopher; Geigenmuller, Ute; Raby, Benjamin A.; Rennard, Stephen I.; Perrella, Mark A.; Choi, Augustine M.K.; Quackenbush, John; Silverman, Edwin K.

2013-01-01

Hedgehog Interacting Protein (HHIP) was implicated in chronic obstructive pulmonary disease (COPD) by genome-wide association studies (GWAS). However, it remains unclear how HHIP contributes to COPD pathogenesis. To identify genes regulated by HHIP, we performed gene expression microarray analysis in a human bronchial epithelial cell line (Beas-2B) stably infected with HHIP shRNAs. HHIP silencing led to differential expression of 296 genes; enrichment for variants nominally associated with COPD was found. Eighteen of the differentially expressed genes were validated by real-time PCR in Beas-2B cells. Seven of 11 validated genes tested in human COPD and control lung tissues demonstrated significant gene expression differences. Functional annotation indicated enrichment for extracellular matrix and cell growth genes. Network modeling demonstrated that the extracellular matrix and cell proliferation genes influenced by HHIP tended to be interconnected. Thus, we identified potential HHIP targets in human bronchial epithelial cells that may contribute to COPD pathogenesis. PMID:23459001

Identification of Genes Uniquely Expressed in the Germ-Line Tissues of the Jewel Wasp Nasonia vitripennis

PubMed Central

Ferree, Patrick M.; Fang, Christopher; Mastrodimos, Mariah; Hay, Bruce A.; Amrhein, Henry; Akbari, Omar S.

2015-01-01

The jewel wasp Nasonia vitripennis is a rising model organism for the study of haplo-diploid reproduction characteristic of hymenopteran insects, which include all wasps, bees, and ants. We performed transcriptional profiling of the ovary, the female soma, and the male soma of N. vitripennis to complement a previously existing transcriptome of the wasp testis. These data were deposited into an open-access genome browser for visualization of transcripts relative to their gene models. We used these data to identify the assemblies of genes uniquely expressed in the germ-line tissues. We found that 156 protein-coding genes are expressed exclusively in the wasp testis compared with only 22 in the ovary. Of the testis-specific genes, eight are candidates for male-specific DNA packaging proteins known as protamines. We found very similar expression patterns of centrosome associated genes in the testis and ovary, arguing that de novo centrosome formation, a key process for development of unfertilized eggs into males, likely does not rely on large-scale transcriptional differences between these tissues. In contrast, a number of meiosis-related genes show a bias toward testis-specific expression, despite the lack of true meiosis in N. vitripennis males. These patterns may reflect an unexpected complexity of male gamete production in the haploid males of this organism. Broadly, these data add to the growing number of genomic and genetic tools available in N. vitripennis for addressing important biological questions in this rising insect model organism. PMID:26464360

[Establishment of a human bladder cancer cell line stably co-expressing hSPRY2 and luciferase genes and its subcutaneous tumor xenograft model in nude mice].

PubMed

Yin, Xiaotao; Li, Fanglong; Jin, Yipeng; Yin, Zhaoyang; Qi, Siyong; Wu, Shuai; Wang, Zicheng; Wang, Lin; Yu, Jiyun; Gao, Jiangping

2017-03-01

Objective To establish a human bladder cancer cell line stably co-expressing human sprouty2 (hSPRY2) and luciferase (Luc) genes simultaneously, and develop its subcutaneous tumor xenograft model in nude mice. Methods The hSPRY2 and Luc gene segments were amplified by PCR, and were cloned into lentiviral vector pCDH and pLVX respectively to produce corresponding lentivirus particles. The J82 human bladder cancer cells were infected with these two kinds of lentivirus particles, and then further screened by puromycin and G418. The expressions of hSPRY2 and Luc genes were detected by bioluminescence, immunofluorescence and Western blot analysis. The screened J82-hSPRY2/Luc cells were injected subcutaneously into BALB/c nude mice, and the growth of tumor was monitored dynamically using in vivo fluorescence imaging system. Results J82-hSPRY2/Luc cell line stably expressing hSPRY2 and Luc genes was established successfully. Bioluminescence, immunofluorescence and Western blot analysis validated the expressions of hSPRY2 and Luc genes. The in vivo fluorescence imaging system showed obvious fluorescence in subcutaneous tumor xenograft in nude mice. Conclusion The J82-hSPRY2/Luc bladder cancer cell line and its subcutaneous tumor xenograft model in nude mice have been established successfully.

The effect of boron deficiency on gene expression and boron compartmentalization in sugarbeet

USDA-ARS?s Scientific Manuscript database

NIP5, BOR1, NIP6, and WRKY6 genes were investigated for their role in boron deficiency in sugar beet, each with a proposed role in boron use in model plant species. All genes showed evidence of polymorphism in fragment size and gene expression in the target genomic DNA and cDNA libraries, with no co...

Selection and Validation of Reference Genes for Quantitative Real-Time PCR in Buckwheat (Fagopyrum esculentum) Based on Transcriptome Sequence Data

PubMed Central

Demidenko, Natalia V.; Logacheva, Maria D.; Penin, Aleksey A.

2011-01-01

Quantitative reverse transcription PCR (qRT-PCR) is one of the most precise and widely used methods of gene expression analysis. A necessary prerequisite of exact and reliable data is the accurate choice of reference genes. We studied the expression stability of potential reference genes in common buckwheat (Fagopyrum esculentum) in order to find the optimal reference for gene expression analysis in this economically important crop. Recently sequenced buckwheat floral transcriptome was used as source of sequence information. Expression stability of eight candidate reference genes was assessed in different plant structures (leaves and inflorescences at two stages of development and fruits). These genes are the orthologs of Arabidopsis genes identified as stable in a genome-wide survey gene of expression stability and a traditionally used housekeeping gene GAPDH. Three software applications – geNorm, NormFinder and BestKeeper - were used to estimate expression stability and provided congruent results. The orthologs of AT4G33380 (expressed protein of unknown function, Expressed1), AT2G28390 (SAND family protein, SAND) and AT5G46630 (clathrin adapter complex subunit family protein, CACS) are revealed as the most stable. We recommend using the combination of Expressed1, SAND and CACS for the normalization of gene expression data in studies on buckwheat using qRT-PCR. These genes are listed among five the most stably expressed in Arabidopsis that emphasizes utility of the studies on model plants as a framework for other species. PMID:21589908

Evidence of Dynamically Dysregulated Gene Expression Pathways in Hyperresponsive B Cells from African American Lupus Patients

PubMed Central

Dozmorov, Igor; Dominguez, Nicolas; Sestak, Andrea L.; Robertson, Julie M.; Harley, John B.; James, Judith A.; Guthridge, Joel M.

2013-01-01

Recent application of gene expression profiling to the immune system has shown a great potential for characterization of complex regulatory processes. It is becoming increasingly important to characterize functional systems through multigene interactions to provide valuable insights into differences between healthy controls and autoimmune patients. Here we apply an original systematic approach to the analysis of changes in regulatory gene interconnections between in Epstein-Barr virus transformed hyperresponsive B cells from SLE patients and normal control B cells. Both traditional analysis of differential gene expression and analysis of the dynamics of gene expression variations were performed in combination to establish model networks of functional gene expression. This Pathway Dysregulation Analysis identified known transcription factors and transcriptional regulators activated uniquely in stimulated B cells from SLE patients. PMID:23977035

Pan- and core- network analysis of co-expression genes in a model plant

DOE PAGES

He, Fei; Maslov, Sergei

2016-12-16

Genome-wide gene expression experiments have been performed using the model plant Arabidopsis during the last decade. Some studies involved construction of coexpression networks, a popular technique used to identify groups of co-regulated genes, to infer unknown gene functions. One approach is to construct a single coexpression network by combining multiple expression datasets generated in different labs. We advocate a complementary approach in which we construct a large collection of 134 coexpression networks based on expression datasets reported in individual publications. To this end we reanalyzed public expression data. To describe this collection of networks we introduced concepts of ‘pan-network’ andmore » ‘core-network’ representing union and intersection between a sizeable fractions of individual networks, respectively. Here, we showed that these two types of networks are different both in terms of their topology and biological function of interacting genes. For example, the modules of the pan-network are enriched in regulatory and signaling functions, while the modules of the core-network tend to include components of large macromolecular complexes such as ribosomes and photosynthetic machinery. Our analysis is aimed to help the plant research community to better explore the information contained within the existing vast collection of gene expression data in Arabidopsis.« less

Pan- and core- network analysis of co-expression genes in a model plant

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

He, Fei; Maslov, Sergei

Genome-wide gene expression experiments have been performed using the model plant Arabidopsis during the last decade. Some studies involved construction of coexpression networks, a popular technique used to identify groups of co-regulated genes, to infer unknown gene functions. One approach is to construct a single coexpression network by combining multiple expression datasets generated in different labs. We advocate a complementary approach in which we construct a large collection of 134 coexpression networks based on expression datasets reported in individual publications. To this end we reanalyzed public expression data. To describe this collection of networks we introduced concepts of ‘pan-network’ andmore » ‘core-network’ representing union and intersection between a sizeable fractions of individual networks, respectively. Here, we showed that these two types of networks are different both in terms of their topology and biological function of interacting genes. For example, the modules of the pan-network are enriched in regulatory and signaling functions, while the modules of the core-network tend to include components of large macromolecular complexes such as ribosomes and photosynthetic machinery. Our analysis is aimed to help the plant research community to better explore the information contained within the existing vast collection of gene expression data in Arabidopsis.« less

Conserved Non-Coding Regulatory Signatures in Arabidopsis Co-Expressed Gene Modules

PubMed Central

Spangler, Jacob B.; Ficklin, Stephen P.; Luo, Feng; Freeling, Michael; Feltus, F. Alex

2012-01-01

Complex traits and other polygenic processes require coordinated gene expression. Co-expression networks model mRNA co-expression: the product of gene regulatory networks. To identify regulatory mechanisms underlying coordinated gene expression in a tissue-enriched context, ten Arabidopsis thaliana co-expression networks were constructed after manually sorting 4,566 RNA profiling datasets into aerial, flower, leaf, root, rosette, seedling, seed, shoot, whole plant, and global (all samples combined) groups. Collectively, the ten networks contained 30% of the measurable genes of Arabidopsis and were circumscribed into 5,491 modules. Modules were scrutinized for cis regulatory mechanisms putatively encoded in conserved non-coding sequences (CNSs) previously identified as remnants of a whole genome duplication event. We determined the non-random association of 1,361 unique CNSs to 1,904 co-expression network gene modules. Furthermore, the CNS elements were placed in the context of known gene regulatory networks (GRNs) by connecting 250 CNS motifs with known GRN cis elements. Our results provide support for a regulatory role of some CNS elements and suggest the functional consequences of CNS activation of co-expression in specific gene sets dispersed throughout the genome. PMID:23024789

Conserved non-coding regulatory signatures in Arabidopsis co-expressed gene modules.

PubMed

Spangler, Jacob B; Ficklin, Stephen P; Luo, Feng; Freeling, Michael; Feltus, F Alex

2012-01-01

Complex traits and other polygenic processes require coordinated gene expression. Co-expression networks model mRNA co-expression: the product of gene regulatory networks. To identify regulatory mechanisms underlying coordinated gene expression in a tissue-enriched context, ten Arabidopsis thaliana co-expression networks were constructed after manually sorting 4,566 RNA profiling datasets into aerial, flower, leaf, root, rosette, seedling, seed, shoot, whole plant, and global (all samples combined) groups. Collectively, the ten networks contained 30% of the measurable genes of Arabidopsis and were circumscribed into 5,491 modules. Modules were scrutinized for cis regulatory mechanisms putatively encoded in conserved non-coding sequences (CNSs) previously identified as remnants of a whole genome duplication event. We determined the non-random association of 1,361 unique CNSs to 1,904 co-expression network gene modules. Furthermore, the CNS elements were placed in the context of known gene regulatory networks (GRNs) by connecting 250 CNS motifs with known GRN cis elements. Our results provide support for a regulatory role of some CNS elements and suggest the functional consequences of CNS activation of co-expression in specific gene sets dispersed throughout the genome.

[Development of a mouse cell line containing stably integrated copies of pMCLacI/Neo plasmid: a model for studying mutations in vitro].

PubMed

Lu, Y; Li, H; Fu, J

2000-04-01

To establish a suitable model for studying the different mechanisms of mutation between expressed and non-expressed genes in mammalian cells. The NIH3T3 cells were transfected with the linearized pMCLacI/Neo DNAs by liposome-mediated transfection, and grew in the presence of G418. One drug resistant cell clone was selected to proliferate and to be analyzed with Southern blot and RT-PCR analyses on its genomic DNAs. (1) Multiple copies of pMCLacI/Neo plasmid DNA were intactly integrated in the genomic DNAs of the cell clone. (2) One of lac I target genes in the integrated plasmid could be transcribed in the NIH3T3 cells while the other could not. (3) The pMCLacI/Neo plasmid DNA could be efficiently rescued from the genomic DNAs of the cell clone with the average rescue efficiency of 410 cfu/microg DNA. The NIH3T3 cell line containing copies of a stably integrated pMCLacI/Neo has been established. The two lacI target genes in the cell line could imitate the functional states of expressed and non-expressed genes in mammalian cells respectively. The cell line will be a useful model for studying the different mechanisms of mutation between expressed and non-expressed genes in mammalian cells.

Selection and evaluation of reference genes for expression studies with quantitative PCR in the model fungus Neurospora crassa under different environmental conditions in continuous culture.

PubMed

Cusick, Kathleen D; Fitzgerald, Lisa A; Pirlo, Russell K; Cockrell, Allison L; Petersen, Emily R; Biffinger, Justin C

2014-01-01

Neurospora crassa has served as a model organism for studying circadian pathways and more recently has gained attention in the biofuel industry due to its enhanced capacity for cellulase production. However, in order to optimize N. crassa for biotechnological applications, metabolic pathways during growth under different environmental conditions must be addressed. Reverse-transcription quantitative PCR (RT-qPCR) is a technique that provides a high-throughput platform from which to measure the expression of a large set of genes over time. The selection of a suitable reference gene is critical for gene expression studies using relative quantification, as this strategy is based on normalization of target gene expression to a reference gene whose expression is stable under the experimental conditions. This study evaluated twelve candidate reference genes for use with N. crassa when grown in continuous culture bioreactors under different light and temperature conditions. Based on combined stability values from NormFinder and Best Keeper software packages, the following are the most appropriate reference genes under conditions of: (1) light/dark cycling: btl, asl, and vma1; (2) all-dark growth: btl, tbp, vma1, and vma2; (3) temperature flux: btl, vma1, act, and asl; (4) all conditions combined: vma1, vma2, tbp, and btl. Since N. crassa exists as different cell types (uni- or multi-nucleated), expression changes in a subset of the candidate genes was further assessed using absolute quantification. A strong negative correlation was found to exist between ratio and threshold cycle (CT) values, demonstrating that CT changes serve as a reliable reflection of transcript, and not gene copy number, fluctuations. The results of this study identified genes that are appropriate for use as reference genes in RT-qPCR studies with N. crassa and demonstrated that even with the presence of different cell types, relative quantification is an acceptable method for measuring gene expression changes during growth in bioreactors.

Interhemispheric gene expression differences in the cerebral cortex of humans and macaque monkeys.

PubMed

Muntané, Gerard; Santpere, Gabriel; Verendeev, Andrey; Seeley, William W; Jacobs, Bob; Hopkins, William D; Navarro, Arcadi; Sherwood, Chet C

2017-09-01

Handedness and language are two well-studied examples of asymmetrical brain function in humans. Approximately 90% of humans exhibit a right-hand preference, and the vast majority shows left-hemisphere dominance for language function. Although genetic models of human handedness and language have been proposed, the actual gene expression differences between cerebral hemispheres in humans remain to be fully defined. In the present study, gene expression profiles were examined in both hemispheres of three cortical regions involved in handedness and language in humans and their homologues in rhesus macaques: ventrolateral prefrontal cortex, posterior superior temporal cortex (STC), and primary motor cortex. Although the overall pattern of gene expression was very similar between hemispheres in both humans and macaques, weighted gene correlation network analysis revealed gene co-expression modules associated with hemisphere, which are different among the three cortical regions examined. Notably, a receptor-enriched gene module in STC was particularly associated with hemisphere and showed different expression levels between hemispheres only in humans.

Effect of Periodontal Pathogens on the Metatranscriptome of a Healthy Multispecies Biofilm Model

PubMed Central

Duran-Pinedo, Ana

2012-01-01

Oral bacterial biofilms are highly complex microbial communities with up to 700 different bacterial taxa. We report here the use of metatranscriptomic analysis to study patterns of community gene expression in a multispecies biofilm model composed of species found in healthy oral biofilms (Actinomyces naeslundii, Lactobacillus casei, Streptococcus mitis, Veillonella parvula, and Fusobacterium nucleatum) and the same biofilm plus the periodontopathogens Porphyromonas gingivalis and Aggregatibacter actinomycetemcomitans. The presence of the periodontopathogens altered patterns in gene expression, and data indicate that transcription of protein-encoding genes and small noncoding RNAs is stimulated. In the healthy biofilm hypothetical proteins, transporters and transcriptional regulators were upregulated while chaperones and cell division proteins were downregulated. However, when the pathogens were present, chaperones were highly upregulated, probably due to increased levels of stress. We also observed a significant upregulation of ABC transport systems and putative transposases. Changes in Clusters of Orthologous Groups functional categories as well as gene set enrichment analysis based on Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways showed that in the absence of pathogens, only sets of proteins related to transport and secondary metabolism were upregulated, while in the presence of pathogens, proteins related to growth and division as well as a large portion of transcription factors were upregulated. Finally, we identified several small noncoding RNAs whose predicted targets were genes differentially expressed in the open reading frame libraries. These results show the importance of pathogens controlling gene expression of a healthy oral community and the usefulness of metatranscriptomic techniques to study gene expression profiles in complex microbial community models. PMID:22328675

Dose–response analysis of phthalate effects on gene expression in rat whole embryo culture

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

Robinson, Joshua F.; Department of Toxicogenomics, Maastricht University, Maastricht; Verhoef, Aart

2012-10-01

The rat postimplantation whole embryo culture (WEC) model serves as a potential screening tool for developmental toxicity. In this model, cultured rat embryos are exposed during early embryogenesis and evaluated for morphological effects. The integration of molecular-based markers may lead to improved objectivity, sensitivity and predictability of WEC in assessing developmental toxic properties of compounds. In this study, we investigated the concentration-dependent effects of two phthalates differing in potency, mono(2-ethylhexyl) phthalate (MEHP) and monomethyl phthalate (MMP, less toxic), on the transcriptome in WEC to examine gene expression in relation with dysmorphogenesis. MEHP was more potent than MMP in inducing genemore » expression changes as well as changes on morphology. MEHP induced significant enrichment of cholesterol/lipid/steroid (CLS) metabolism and apoptosis pathways which was associated with developmental toxicity. Regulation of genes within CLS metabolism pathways represented the most sensitive markers of MEHP exposure, more sensitive than classical morphological endpoints. As shown in direct comparisons with toxicogenomic in vivo studies, alterations in the regulation of CLS metabolism pathways has been previously identified to be associated with developmental toxicity due to phthalate exposure in utero. Our results support the application of WEC as a model to examine relative phthalate potency through gene expression and morphological responses. Additionally, our results further define the applicability domain of the WEC model for developmental toxicological investigations. -- Highlights: ► We examine the effect of two phthalates on gene expression and morphology in WEC. ► MEHP is more potent than MMP in inducing gene expression changes and dysmorphogenesis. ► MEHP significantly disrupts cholesterol metabolism pathways in a dose-dependent manner. ► Specific phthalate-related mechanisms in WEC are relevant to mechanisms in vivo.« less

In silico evolution of the hunchback gene indicates redundancy in cis-regulatory organization and spatial gene expression

PubMed Central

Zagrijchuk, Elizaveta A.; Sabirov, Marat A.; Holloway, David M.; Spirov, Alexander V.

2014-01-01

Biological development depends on the coordinated expression of genes in time and space. Developmental genes have extensive cis-regulatory regions which control their expression. These regions are organized in a modular manner, with different modules controlling expression at different times and locations. Both how modularity evolved and what function it serves are open questions. We present a computational model for the cis-regulation of the hunchback (hb) gene in the fruit fly (Drosophila). We simulate evolution (using an evolutionary computation approach from computer science) to find the optimal cis-regulatory arrangements for fitting experimental hb expression patterns. We find that the cis-regulatory region tends to readily evolve modularity. These cis-regulatory modules (CRMs) do not tend to control single spatial domains, but show a multi-CRM/multi-domain correspondence. We find that the CRM-domain correspondence seen in Drosophila evolves with a high probability in our model, supporting the biological relevance of the approach. The partial redundancy resulting from multi-CRM control may confer some biological robustness against corruption of regulatory sequences. The technique developed on hb could readily be applied to other multi-CRM developmental genes. PMID:24712536

Combined effects of dietary polyunsaturated fatty acids and parasite exposure on eicosanoid-related gene expression in an invertebrate model.

PubMed

Schlotz, Nina; Roulin, Anne; Ebert, Dieter; Martin-Creuzburg, Dominik

2016-11-01

Eicosanoids derive from essential polyunsaturated fatty acids (PUFA) and play crucial roles in immunity, development, and reproduction. However, potential links between dietary PUFA supply and eicosanoid biosynthesis are poorly understood, especially in invertebrates. Using Daphnia magna and its bacterial parasite Pasteuria ramosa as model system, we studied the expression of genes coding for key enzymes in eicosanoid biosynthesis and of genes related to oogenesis in response to dietary arachidonic acid and eicosapentaenoic acid in parasite-exposed and non-exposed animals. Gene expression related to cyclooxygenase activity was especially responsive to the dietary PUFA supply and parasite challenge, indicating a role for prostanoid eicosanoids in immunity and reproduction. Vitellogenin gene expression was induced upon parasite exposure in all food treatments, suggesting infection-related interference with the host's reproductive system. Our findings highlight the potential of dietary PUFA to modulate the expression of key enzymes involved in eicosanoid biosynthesis and reproduction and thus underpin the idea that the dietary PUFA supply can influence invertebrate immune functions and host-parasite interactions. Copyright © 2016 Elsevier Inc. All rights reserved.

An integrated approach to reconstructing genome-scale transcriptional regulatory networks

DOE PAGES

Imam, Saheed; Noguera, Daniel R.; Donohue, Timothy J.; ...

2015-02-27

Transcriptional regulatory networks (TRNs) program cells to dynamically alter their gene expression in response to changing internal or environmental conditions. In this study, we develop a novel workflow for generating large-scale TRN models that integrates comparative genomics data, global gene expression analyses, and intrinsic properties of transcription factors (TFs). An assessment of this workflow using benchmark datasets for the well-studied γ-proteobacterium Escherichia coli showed that it outperforms expression-based inference approaches, having a significantly larger area under the precision-recall curve. Further analysis indicated that this integrated workflow captures different aspects of the E. coli TRN than expression-based approaches, potentially making themmore » highly complementary. We leveraged this new workflow and observations to build a large-scale TRN model for the α-Proteobacterium Rhodobacter sphaeroides that comprises 120 gene clusters, 1211 genes (including 93 TFs), 1858 predicted protein-DNA interactions and 76 DNA binding motifs. We found that ~67% of the predicted gene clusters in this TRN are enriched for functions ranging from photosynthesis or central carbon metabolism to environmental stress responses. We also found that members of many of the predicted gene clusters were consistent with prior knowledge in R. sphaeroides and/or other bacteria. Experimental validation of predictions from this R. sphaeroides TRN model showed that high precision and recall was also obtained for TFs involved in photosynthesis (PpsR), carbon metabolism (RSP_0489) and iron homeostasis (RSP_3341). In addition, this integrative approach enabled generation of TRNs with increased information content relative to R. sphaeroides TRN models built via other approaches. We also show how this approach can be used to simultaneously produce TRN models for each related organism used in the comparative genomics analysis. Our results highlight the advantages of integrating comparative genomics of closely related organisms with gene expression data to assemble large-scale TRN models with high-quality predictions.« less

Faster-X Evolution of Gene Expression in Drosophila

PubMed Central

Meisel, Richard P.; Malone, John H.; Clark, Andrew G.

2012-01-01

DNA sequences on X chromosomes often have a faster rate of evolution when compared to similar loci on the autosomes, and well articulated models provide reasons why the X-linked mode of inheritance may be responsible for the faster evolution of X-linked genes. We analyzed microarray and RNA–seq data collected from females and males of six Drosophila species and found that the expression levels of X-linked genes also diverge faster than autosomal gene expression, similar to the “faster-X” effect often observed in DNA sequence evolution. Faster-X evolution of gene expression was recently described in mammals, but it was limited to the evolutionary lineages shortly following the creation of the therian X chromosome. In contrast, we detect a faster-X effect along both deep lineages and those on the tips of the Drosophila phylogeny. In Drosophila males, the dosage compensation complex (DCC) binds the X chromosome, creating a unique chromatin environment that promotes the hyper-expression of X-linked genes. We find that DCC binding, chromatin environment, and breadth of expression are all predictive of the rate of gene expression evolution. In addition, estimates of the intraspecific genetic polymorphism underlying gene expression variation suggest that X-linked expression levels are not under relaxed selective constraints. We therefore hypothesize that the faster-X evolution of gene expression is the result of the adaptive fixation of beneficial mutations at X-linked loci that change expression level in cis. This adaptive faster-X evolution of gene expression is limited to genes that are narrowly expressed in a single tissue, suggesting that relaxed pleiotropic constraints permit a faster response to selection. Finally, we present a conceptional framework to explain faster-X expression evolution, and we use this framework to examine differences in the faster-X effect between Drosophila and mammals. PMID:23071459

A transgenic model of transactivation by the Tax protein of HTLV-I.

PubMed

Bieberich, C J; King, C M; Tinkle, B T; Jay, G

1993-09-01

The human T-lymphotropic virus type I (HTLV-I) Tax protein is a transcriptional regulatory protein that has been suggested to play a causal role in the development of several HTLV-I-associated diseases. Tax regulates expression of its own LTR and of certain cellular promoters perhaps by usurping the function of the host transcriptional machinery. We have established a transgenic mouse model system to define the spectrum of tissues in vivo that are capable of supporting Tax-mediated transcriptional transactivation. Transgenic mice carrying the HTLV-I LTR driving expression of the Escherichia coli beta-galactosidase (beta gal) gene were generated, and this LTR-beta gal gene was transcriptionally inactive in all tissues. When LTR-beta gal mice were mated to transgenic mice carrying the same LTR driving expression of the HTLV-I tax gene, mice that carried both transgenes showed restricted expression of the beta gal reporter gene in several tissues including muscle, bone, salivary glands, skin, and nerve. In addition, a dramatic increase in the number of beta gal-expressing cells was seen in response to wounding. These observations provide direct evidence for viral transactivation in vivo, delimit the tissues capable of supporting that transactivation, and provide a model system to study the mechanism of gene regulation by Tax.

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.

IDENTIFICATION OF DIFFERENTIALLY EXPRESSED GENES IN THE KIDNEYS OF GROWTH HORMONE TRANSGENIC MICE

PubMed Central

Coschigano, K.T.; Wetzel, A.N.; Obichere, N.; Sharma, A.; Lee, S.; Rasch, R.; Guigneaux, M.M.; Flyvbjerg, A.; Wood, T.G.; Kopchick, J.J.

2010-01-01

Objective Bovine growth hormone (bGH) transgenic mice develop severe kidney damage. This damage may be due, at least in part, to changes in gene expression. Identification of genes with altered expression in the bGH kidney may identify mechanisms leading to damage in this system that may also be relevant to other models of kidney damage. Design cDNA subtraction libraries, northern blot analyses, microarray analyses and real-time reverse transcription polymerase chain reaction (RT/PCR) assays were used to identify and verify specific genes exhibiting differential RNA expression between kidneys of bGH mice and their non-transgenic (NT) littermates. Results Immunoglobulins were the vast majority of genes identified by the cDNA subtractions and the microarray analyses as being up-regulated in bGH. Several glycoprotein genes and inflammation-related genes also showed increased RNA expression in the bGH kidney. In contrast, only a few genes were identified as being significantly down-regulated in the bGH kidney. The most notable decrease in RNA expression was for the gene encoding kidney androgen-regulated protein. Conclusions A number of genes were identified as being differentially expressed in the bGH kidney. Inclusion of two groups, immunoglobulins and inflammation-related genes, suggests a role of the immune system in bGH kidney damage. PMID:20655258

Complexity of Gene Expression Evolution after Duplication: Protein Dosage Rebalancing

PubMed Central

Rogozin, Igor B.

2014-01-01

Ongoing debates about functional importance of gene duplications have been recently intensified by a heated discussion of the “ortholog conjecture” (OC). Under the OC, which is central to functional annotation of genomes, orthologous genes are functionally more similar than paralogous genes at the same level of sequence divergence. However, a recent study challenged the OC by reporting a greater functional similarity, in terms of gene ontology (GO) annotations and expression profiles, among within-species paralogs compared to orthologs. These findings were taken to indicate that functional similarity of homologous genes is primarily determined by the cellular context of the genes, rather than evolutionary history. Subsequent studies suggested that the OC appears to be generally valid when applied to mammalian evolution but the complete picture of evolution of gene expression also has to incorporate lineage-specific aspects of paralogy. The observed complexity of gene expression evolution after duplication can be explained through selection for gene dosage effect combined with the duplication-degeneration-complementation model. This paper discusses expression divergence of recent duplications occurring before functional divergence of proteins encoded by duplicate genes. PMID:25197576

A wing expressed sequence tag resource for Bicyclus anynana butterflies, an evo-devo model

PubMed Central

Beldade, Patrícia; Rudd, Stephen; Gruber, Jonathan D; Long, Anthony D

2006-01-01

Background Butterfly wing color patterns are a key model for integrating evolutionary developmental biology and the study of adaptive morphological evolution. Yet, despite the biological, economical and educational value of butterflies they are still relatively under-represented in terms of available genomic resources. Here, we describe an Expression Sequence Tag (EST) project for Bicyclus anynana that has identified the largest available collection to date of expressed genes for any butterfly. Results By targeting cDNAs from developing wings at the stages when pattern is specified, we biased gene discovery towards genes potentially involved in pattern formation. Assembly of 9,903 ESTs from a subtracted library allowed us to identify 4,251 genes of which 2,461 were annotated based on BLAST analyses against relevant gene collections. Gene prediction software identified 2,202 peptides, of which 215 longer than 100 amino acids had no homology to any known proteins and, thus, potentially represent novel or highly diverged butterfly genes. We combined gene and Single Nucleotide Polymorphism (SNP) identification by constructing cDNA libraries from pools of outbred individuals, and by sequencing clones from the 3' end to maximize alignment depth. Alignments of multi-member contigs allowed us to identify over 14,000 putative SNPs, with 316 genes having at least one high confidence double-hit SNP. We furthermore identified 320 microsatellites in transcribed genes that can potentially be used as genetic markers. Conclusion Our project was designed to combine gene and sequence polymorphism discovery and has generated the largest gene collection available for any butterfly and many potential markers in expressed genes. These resources will be invaluable for exploring the potential of B. anynana in particular, and butterflies in general, as models in ecological, evolutionary, and developmental genetics. PMID:16737530

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.

Discovering Condition-Specific Gene Co-Expression Patterns Using Gaussian Mixture Models: A Cancer Case Study.

PubMed

Ficklin, Stephen P; Dunwoodie, Leland J; Poehlman, William L; Watson, Christopher; Roche, Kimberly E; Feltus, F Alex

2017-08-17

A gene co-expression network (GCN) describes associations between genes and points to genetic coordination of biochemical pathways. However, genetic correlations in a GCN are only detectable if they are present in the sampled conditions. With the increasing quantity of gene expression samples available in public repositories, there is greater potential for discovery of genetic correlations from a variety of biologically interesting conditions. However, even if gene correlations are present, their discovery can be masked by noise. Noise is introduced from natural variation (intrinsic and extrinsic), systematic variation (caused by sample measurement protocols and instruments), and algorithmic and statistical variation created by selection of data processing tools. A variety of published studies, approaches and methods attempt to address each of these contributions of variation to reduce noise. Here we describe an approach using Gaussian Mixture Models (GMMs) to address natural extrinsic (condition-specific) variation during network construction from mixed input conditions. To demonstrate utility, we build and analyze a condition-annotated GCN from a compendium of 2,016 mixed gene expression data sets from five tumor subtypes obtained from The Cancer Genome Atlas. Our results show that GMMs help discover tumor subtype specific gene co-expression patterns (modules) that are significantly enriched for clinical attributes.

Environment-dependent striatal gene expression in the BACHD rat model for Huntington disease.

PubMed

Novati, Arianna; Hentrich, Thomas; Wassouf, Zinah; Weber, Jonasz J; Yu-Taeger, Libo; Déglon, Nicole; Nguyen, Huu Phuc; Schulze-Hentrich, Julia M

2018-04-11

Huntington disease (HD) is an autosomal dominant neurodegenerative disorder caused by a mutation in the huntingtin (HTT) gene which results in progressive neurodegeneration in the striatum, cortex, and eventually most brain areas. Despite being a monogenic disorder, environmental factors influence HD characteristics. Both human and mouse studies suggest that mutant HTT (mHTT) leads to gene expression changes that harbor potential to be modulated by the environment. Yet, the underlying mechanisms integrating environmental cues into the gene regulatory program have remained largely unclear. To better understand gene-environment interactions in the context of mHTT, we employed RNA-seq to examine effects of maternal separation (MS) and environmental enrichment (EE) on striatal gene expression during development of BACHD rats. We integrated our results with striatal consensus modules defined on HTT-CAG length and age-dependent co-expression gene networks to relate the environmental factors with disease progression. While mHTT was the main determinant of expression changes, both MS and EE were capable of modulating these disturbances, resulting in distinctive and in several cases opposing effects of MS and EE on consensus modules. This bivalent response to maternal separation and environmental enrichment may aid in explaining their distinct effects observed on disease phenotypes in animal models of HD and related neurodegenerative disorders.

Maintenance and Loss of Duplicated Genes by Dosage Subfunctionalization.

PubMed

Gout, Jean-Francois; Lynch, Michael

2015-08-01

Whole-genome duplications (WGDs) have contributed to gene-repertoire enrichment in many eukaryotic lineages. However, most duplicated genes are eventually lost and it is still unclear why some duplicated genes are evolutionary successful whereas others quickly turn to pseudogenes. Here, we show that dosage constraints are major factors opposing post-WGD gene loss in several Paramecium species that share a common ancestral WGD. We propose a model where a majority of WGD-derived duplicates preserve their ancestral function and are retained to produce enough of the proteins performing this same ancestral function. Under this model, the expression level of individual duplicated genes can evolve neutrally as long as they maintain a roughly constant summed expression, and this allows random genetic drift toward uneven contributions of the two copies to total expression. Our analysis suggests that once a high level of imbalance is reached, which can require substantial lengths of time, the copy with the lowest expression level contributes a small enough fraction of the total expression that selection no longer opposes its loss. Extension of our analysis to yeast species sharing a common ancestral WGD yields similar results, suggesting that duplicated-gene retention for dosage constraints followed by divergence in expression level and eventual deterministic gene loss might be a universal feature of post-WGD evolution. © The Author 2015. 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.

Quantifying the contribution of chromatin dynamics to stochastic gene expression reveals long, locus-dependent periods between transcriptional bursts.

PubMed

Viñuelas, José; Kaneko, Gaël; Coulon, Antoine; Vallin, Elodie; Morin, Valérie; Mejia-Pous, Camila; Kupiec, Jean-Jacques; Beslon, Guillaume; Gandrillon, Olivier

2013-02-25

A number of studies have established that stochasticity in gene expression may play an important role in many biological phenomena. This therefore calls for further investigations to identify the molecular mechanisms at stake, in order to understand and manipulate cell-to-cell variability. In this work, we explored the role played by chromatin dynamics in the regulation of stochastic gene expression in higher eukaryotic cells. For this purpose, we generated isogenic chicken-cell populations expressing a fluorescent reporter integrated in one copy per clone. Although the clones differed only in the genetic locus at which the reporter was inserted, they showed markedly different fluorescence distributions, revealing different levels of stochastic gene expression. Use of chromatin-modifying agents showed that direct manipulation of chromatin dynamics had a marked effect on the extent of stochastic gene expression. To better understand the molecular mechanism involved in these phenomena, we fitted these data to a two-state model describing the opening/closing process of the chromatin. We found that the differences between clones seemed to be due mainly to the duration of the closed state, and that the agents we used mainly seem to act on the opening probability. In this study, we report biological experiments combined with computational modeling, highlighting the importance of chromatin dynamics in stochastic gene expression. This work sheds a new light on the mechanisms of gene expression in higher eukaryotic cells, and argues in favor of relatively slow dynamics with long (hours to days) periods of quiet state.

Expression of the G72/G30 gene in transgenic mice induces behavioral changes

PubMed Central

Cheng, Lijun; Hattori, Eiji; Nakajima, Akira; Woehrle, Nancy S.; Opal, Mark D.; Zhang, Chunling; Grennan, Kay; Dulawa, Stephanie C.; Tang, Ya-Ping; Gershon, Elliot S.; Liu, Chunyu

2012-01-01

The G72/G30 gene complex is a candidate gene for schizophrenia and bipolar disorder. However, G72 and G30 mRNAs are expressed at very low levels in human brain, with only rare splicing forms observed. We report here G72/G30 expression profiles and behavioral changes in a G72/G30 transgenic mouse model. A human BAC clone containing the G72/G30 genomic region was used to establish the transgenic mouse model, on which gene expression studies, Western blot and behavioral tests were performed. Relative to their minimal expression in humans, G72 and G30 mRNAs were highly expressed in the transgenic mice, and had a more complex splicing pattern. The highest G72 transcript levels were found in testis, followed by cerebral cortex, with very low or undetectable levels in other tissues. No LG72 (the long putative isoform of G72) protein was detected in the transgenic mice. Whole-genome expression profiling identified 361 genes differentially-expressed in transgenic mice compared to wild-type, including genes previously implicated in neurological and psychological disorders. Relative to wild-type mice, the transgenic mice exhibited fewer stereotypic movements in the open field test, higher baseline startle responses in the course of the prepulse inhibition test, and lower hedonic responses in the sucrose preference test. The transcriptome profile changes and multiple mouse behavioral effects suggest that the G72 gene may play a role in modulating behaviors relevant to psychiatric disorders. PMID:23337943

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

Farahani, Poupak; Chiu, Sally; Bowlus, Christopher L.

Obesity is a complex disease. To date, over 100 chromosomal loci for body weight, body fat, regional white adipose tissue weight, and other obesity-related traits have been identified in humans and in animal models. For most loci, the underlying genes are not yet identified; some of these chromosomal loci will be alleles of known obesity genes, whereas many will represent alleles of unknown genes. Microarray analysis allows simultaneous multiple gene and pathway discovery. cDNA and oligonucleotide arrays are commonly used to identify differentially expressed genes by surveys of large numbers of known and unnamed genes. Two papers previously identified genesmore » differentially expressed in adipose tissue of mouse models of obesity and diabetes by analysis of hybridization to Affymetrix oligonucleotide chips.« less

Comparative analysis of cis-regulation following stroke and seizures in subspaces of conserved eigensystems

PubMed Central

2010-01-01

Background It is often desirable to separate effects of different regulators on gene expression, or to identify effects of the same regulator across several systems. Here, we focus on the rat brain following stroke or seizures, and demonstrate how the two tasks can be approached simultaneously. Results We applied SVD to time-series gene expression datasets from the rat experimental models of stroke and seizures. We demonstrate conservation of two eigensystems, reflecting inflammation and/or apoptosis (eigensystem 2) and neuronal synaptic activity (eigensystem 3), between the stroke and seizures. We analyzed cis-regulation of gene expression in the subspaces of the conserved eigensystems. Bayesian networks analysis was performed separately for either experimental model, with cross-system validation of the highest-ranking features. In this way, we correctly re-discovered the role of AP1 in the regulation of apoptosis, and the involvement of Creb and Egr in the regulation of synaptic activity-related genes. We identified a novel antagonistic effect of the motif recognized by the nuclear matrix attachment region-binding protein Satb1 on AP1-driven transcriptional activation, suggesting a link between chromatin loop structure and gene activation by AP1. The effects of motifs binding Satb1 and Creb on gene expression in brain conform to the assumption of the linear response model of gene regulation. Our data also suggest that numerous enhancers of neuronal-specific genes are important for their responsiveness to the synaptic activity. Conclusion Eigensystems conserved between stroke and seizures separate effects of inflammation/apoptosis and neuronal synaptic activity, exerted by different transcription factors, on gene expression in rat brain. PMID:20565733

Gene therapies that restore dystrophin expression for the treatment of Duchenne muscular dystrophy

PubMed Central

Robinson-Hamm, Jacqueline N.; Gersbach, Charles A.

2016-01-01

Duchenne muscular dystrophy is one of the most common inherited genetic diseases and is caused by mutations to the DMD gene that encodes the dystrophin protein. Recent advances in genome editing and gene therapy offer hope for the development of potential therapeutics. Truncated versions of the DMD gene can be delivered to the affected tissues with viral vectors and show promising results in a variety of animal models. Genome editing with the CRISPR/Cas9 system has recently been used to restore dystrophin expression by deleting one or more exons of the DMD gene in patient cells and in a mouse model that led to functional improvement of muscle strength. Exon skipping with oligonucleotides has been successful in several animal models and evaluated in multiple clinical trials. Next-generation oligonucleotide formulations offer significant promise to build on these results. All these approaches to restoring dystrophin expression are encouraging, but many hurdles remain. This review summarizes the current state of these technologies and summarizes considerations for their future development. PMID:27542949

Forniceal deep brain stimulation induces gene expression and splicing changes that promote neurogenesis and plasticity

PubMed Central

Pohodich, Amy E; Yalamanchili, Hari; Raman, Ayush T; Wan, Ying-Wooi; Gundry, Michael; Hao, Shuang; Jin, Haijing; Tang, Jianrong; Liu, Zhandong

2018-01-01

Clinical trials are currently underway to assess the efficacy of forniceal deep brain stimulation (DBS) for improvement of memory in Alzheimer’s patients, and forniceal DBS has been shown to improve learning and memory in a mouse model of Rett syndrome (RTT), an intellectual disability disorder caused by loss-of-function mutations in MECP2. The mechanism of DBS benefits has been elusive, however, so we assessed changes in gene expression, splice isoforms, DNA methylation, and proteome following acute forniceal DBS in wild-type mice and mice lacking Mecp2. We found that DBS upregulates genes involved in synaptic function, cell survival, and neurogenesis and normalized expression of ~25% of the genes altered in Mecp2-null mice. Moreover, DBS induced expression of 17–24% of the genes downregulated in other intellectual disability mouse models and in post-mortem human brain tissue from patients with Major Depressive Disorder, suggesting forniceal DBS could benefit individuals with a variety of neuropsychiatric disorders. PMID:29570050

Computing and Applying Atomic Regulons to Understand Gene Expression and Regulation

PubMed Central

Faria, José P.; Davis, James J.; Edirisinghe, Janaka N.; Taylor, Ronald C.; Weisenhorn, Pamela; Olson, Robert D.; Stevens, Rick L.; Rocha, Miguel; Rocha, Isabel; Best, Aaron A.; DeJongh, Matthew; Tintle, Nathan L.; Parrello, Bruce; Overbeek, Ross; Henry, Christopher S.

2016-01-01

Understanding gene function and regulation is essential for the interpretation, prediction, and ultimate design of cell responses to changes in the environment. An important step toward meeting the challenge of understanding gene function and regulation is the identification of sets of genes that are always co-expressed. These gene sets, Atomic Regulons (ARs), represent fundamental units of function within a cell and could be used to associate genes of unknown function with cellular processes and to enable rational genetic engineering of cellular systems. Here, we describe an approach for inferring ARs that leverages large-scale expression data sets, gene context, and functional relationships among genes. We computed ARs for Escherichia coli based on 907 gene expression experiments and compared our results with gene clusters produced by two prevalent data-driven methods: Hierarchical clustering and k-means clustering. We compared ARs and purely data-driven gene clusters to the curated set of regulatory interactions for E. coli found in RegulonDB, showing that ARs are more consistent with gold standard regulons than are data-driven gene clusters. We further examined the consistency of ARs and data-driven gene clusters in the context of gene interactions predicted by Context Likelihood of Relatedness (CLR) analysis, finding that the ARs show better agreement with CLR predicted interactions. We determined the impact of increasing amounts of expression data on AR construction and find that while more data improve ARs, it is not necessary to use the full set of gene expression experiments available for E. coli to produce high quality ARs. In order to explore the conservation of co-regulated gene sets across different organisms, we computed ARs for Shewanella oneidensis, Pseudomonas aeruginosa, Thermus thermophilus, and Staphylococcus aureus, each of which represents increasing degrees of phylogenetic distance from E. coli. Comparison of the organism-specific ARs showed that the consistency of AR gene membership correlates with phylogenetic distance, but there is clear variability in the regulatory networks of closely related organisms. As large scale expression data sets become increasingly common for model and non-model organisms, comparative analyses of atomic regulons will provide valuable insights into fundamental regulatory modules used across the bacterial domain. PMID:27933038

Computational Model of the Modulation of Gene Expression Following DNA Damage

NASA Technical Reports Server (NTRS)

Cucinotta, F. A.; Dicello, J. F.; Nikjoo, H.; Cherubini, R.

2002-01-01

High linear energy transfer (LET) radiation, such as heavy ions or neutrons, has an increased biological effectiveness compared to X rays for gene mutation, genomic instability, and carcinogenesis. In the traditional paradigm, mutations or chromosomal aberrations are causative of late effects. However, in recent years experimental evidence has demonstrated the important role of the description of the modification of gene expression by radiation in understanding the mechanisms of radiation action. In this report, approaches are discussed to the mathematical description of mRNA and protein expression kinetics following DNA damage. Several hypotheses for models of radiation modulation of protein expression are discussed including possible non-linear processes that evolve from the linear dose responses that follow the initial DNA damage produced by radiation.

Significant obesity-associated gene expression changes occur in the stomach but not intestines in obese mice.

PubMed

Chen, Jing; Chen, Lihong; Sanseau, Philippe; Freudenberg, Johannes M; Rajpal, Deepak K

2016-05-01

The gastrointestinal (GI) tract can have significant impact on the regulation of the whole-body metabolism and may contribute to the development of obesity and diabetes. To systemically elucidate the role of the GI tract in obesity, we performed a transcriptomic analysis in different parts of the GI tract of two obese mouse models: ob/ob and high-fat diet (HFD) fed mice. Compared to their lean controls, significant changes in the gene expression were observed in both obese mouse groups in the stomach (ob/ob: 959; HFD: 542). In addition, these changes were quantitatively much higher than in the intestine. Despite the difference in genetic background, the two mouse models shared 296 similar gene expression changes in the stomach. Among those genes, some had known associations to obesity, diabetes, and insulin resistance. In addition, the gene expression profiles strongly suggested an increased gastric acid secretion in both obese mouse models, probably through an activation of the gastrin pathway. In conclusion, our data reveal a previously unknown dominant connection between the stomach and obesity in murine models extensively used in research. © 2016 The Authors. Physiological Reports published by Wiley Periodicals, Inc. on behalf of the American Physiological Society and The Physiological Society.

Stability of Reference Gene Expression After Porcine Sapelovirus Infection in Porcine Intestinal Epithelial Cells.

PubMed

Huang, Yong; Chen, Yabing; Sun, Huan; Lan, Daoliang

2016-01-01

Intestinal epithelial cells, which serve as the first physical barrier to protect intestinal tract from external antigens, have an important role in the local innate immunity. Screening of reference genes that have stable expression levels after viral infection in porcine intestinal epithelial cells is critical for ensuring the reliability of the expression analysis on anti-infection genes in porcine intestinal epithelial cells. In this study, nine common reference genes in pigs, including ACTB, B2M, GAPDH, HMBS, SDHA, HPRT1, TBP, YWHAZ, and RPL32, were chosen as the candidate reference genes. Porcine sapelovirus (PSV) was used as a model virus to infect porcine intestinal epithelial cell line (IPEC-J2). The expression stability of the nine genes was assessed by the geNorm, NormFinder, and BestKeeper software. Moreover, RefFinder program was used to evaluate the analytical results of above three softwares, and a relative expression experiment of selected target gene was used to verify the analysis results. The comprehensive results indicated that the gene combination of TBP and RPL32 has the most stable expression, which could be considered as an appropriate reference gene for research on gene expression after PSV infection in IPEC-J2cells. The results provided essential data for expression analysis of anti-infection genes in porcine intestinal epithelial cells.

Kinetic models of gene expression including non-coding RNAs

NASA Astrophysics Data System (ADS)

Zhdanov, Vladimir P.

2011-03-01

In cells, genes are transcribed into mRNAs, and the latter are translated into proteins. Due to the feedbacks between these processes, the kinetics of gene expression may be complex even in the simplest genetic networks. The corresponding models have already been reviewed in the literature. A new avenue in this field is related to the recognition that the conventional scenario of gene expression is fully applicable only to prokaryotes whose genomes consist of tightly packed protein-coding sequences. In eukaryotic cells, in contrast, such sequences are relatively rare, and the rest of the genome includes numerous transcript units representing non-coding RNAs (ncRNAs). During the past decade, it has become clear that such RNAs play a crucial role in gene expression and accordingly influence a multitude of cellular processes both in the normal state and during diseases. The numerous biological functions of ncRNAs are based primarily on their abilities to silence genes via pairing with a target mRNA and subsequently preventing its translation or facilitating degradation of the mRNA-ncRNA complex. Many other abilities of ncRNAs have been discovered as well. Our review is focused on the available kinetic models describing the mRNA, ncRNA and protein interplay. In particular, we systematically present the simplest models without kinetic feedbacks, models containing feedbacks and predicting bistability and oscillations in simple genetic networks, and models describing the effect of ncRNAs on complex genetic networks. Mathematically, the presentation is based primarily on temporal mean-field kinetic equations. The stochastic and spatio-temporal effects are also briefly discussed.

Co-regulation of the atrial natriuretic factor and cardiac myosin light chain-2 genes during alpha-adrenergic stimulation of neonatal rat ventricular cells. Identification of cis sequences within an embryonic and a constitutive contractile protein gene which mediate inducible expression.

PubMed

Knowlton, K U; Baracchini, E; Ross, R S; Harris, A N; Henderson, S A; Evans, S M; Glembotski, C C; Chien, K R

1991-04-25

To study the mechanisms which mediate the transcriptional activation of cardiac genes during alpha adrenergic stimulation, the present study examined the regulated expression of three cardiac genes, a ventricular embryonic gene (atrial natriuretic factor, ANF), a constitutively expressed contractile protein gene (cardiac MLC-2), and a cardiac sodium channel gene. alpha 1-Adrenergic stimulation activates the expression and release of ANF from neonatal ventricular cells. As assessed by RNase protection analyses, treatment with alpha-adrenergic agonists increases the steady-state levels of ANF mRNA by greater than 15-fold. However, a rat cardiac sodium channel gene mRNA is not induced, indicating that alpha-adrenergic stimulation does not lead to an increase in the expression of all cardiac genes. Studies employing a series of rat ANF luciferase and rat MLC-2 luciferase fusion genes identify 315- and 92-base pair cis regulatory sequences within an embryonic gene (ANF) and a constitutively expressed contractile protein gene (MLC-2), respectively, which mediate alpha-adrenergic-inducible gene expression. Transfection of various ANF luciferase reporters into neonatal rat ventricular cells demonstrated that upstream sequences which mediate tissue-specific expression (-3003 to -638) can be segregated from those responsible for inducibility. The lack of inducibility of a cardiac Na+ channel gene, and the segregation of ANF gene sequences which mediate cardiac specific from those which mediate inducible expression, provides further insight into the relationship between muscle-specific and inducible expression during cardiac myocyte hypertrophy. Based on these results, a testable model is proposed for the induction of embryonic cardiac genes and constitutively expressed contractile protein genes and the noninducibility of a subset of cardiac genes during alpha-adrenergic stimulation of neonatal rat ventricular cells.

With Reference to Reference Genes: A Systematic Review of Endogenous Controls in Gene Expression Studies.

PubMed

Chapman, Joanne R; Waldenström, Jonas

2015-01-01

The choice of reference genes that are stably expressed amongst treatment groups is a crucial step in real-time quantitative PCR gene expression studies. Recent guidelines have specified that a minimum of two validated reference genes should be used for normalisation. However, a quantitative review of the literature showed that the average number of reference genes used across all studies was 1.2. Thus, the vast majority of studies continue to use a single gene, with β-actin (ACTB) and/or glyceraldehyde 3-phosphate dehydrogenase (GAPDH) being commonly selected in studies of vertebrate gene expression. Few studies (15%) tested a panel of potential reference genes for stability of expression before using them to normalise data. Amongst studies specifically testing reference gene stability, few found ACTB or GAPDH to be optimal, whereby these genes were significantly less likely to be chosen when larger panels of potential reference genes were screened. Fewer reference genes were tested for stability in non-model organisms, presumably owing to a dearth of available primers in less well characterised species. Furthermore, the experimental conditions under which real-time quantitative PCR analyses were conducted had a large influence on the choice of reference genes, whereby different studies of rat brain tissue showed different reference genes to be the most stable. These results highlight the importance of validating the choice of normalising reference genes before conducting gene expression studies.

Prenatal Nutritional Deficiency Reprogrammed Postnatal Gene Expression in Mammal Brains: Implications for Schizophrenia

PubMed Central

Xu, Jiawei; He, Guang; Zhu, Jingde; Zhou, Xinyao; St Clair, David; Wang, Teng; Xiang, Yuqian; Zhao, Qingzhu; Xing, Qinghe; Liu, Yun; Wang, Lei; Li, Qiaoli

2015-01-01

Background: Epidemiological studies have identified prenatal exposure to famine as a risk factor for schizophrenia, and animal models of prenatal malnutrition display structural and functional brain abnormalities implicated in schizophrenia. Methods: The offspring of the RLP50 rat, a recently developed animal model of prenatal famine malnutrition exposure, was used to investigate the changes of gene expression and epigenetic modifications in the brain regions. Microarray gene expression analysis was carried out in the prefrontal cortex and the hippocampus from 8 RLP50 offspring rats and 8 controls. MBD-seq was used to test the changes in DNA methylation in hippocampus depending on prenatal malnutrition exposure. Results: In the prefrontal cortex, offspring of RLP50 exhibit differences in neurotransmitters and olfactory-associated gene expression. In the hippocampus, the differentially-expressed genes are related to synaptic function and transcription regulation. DNA methylome profiling of the hippocampus also shows widespread but systematic epigenetic changes; in most cases (87%) this involves hypermethylation. Remarkably, genes encoded for the plasma membrane are significantly enriched for changes in both gene expression and DNA methylome profiling screens (p = 2.37×10–9 and 5.36×10–9, respectively). Interestingly, Mecp2 and Slc2a1, two genes associated with cognitive impairment, show significant down-regulation, and Slc2a1 is hypermethylated in the hippocampus of the RLP50 offspring. Conclusions: Collectively, our results indicate that prenatal exposure to malnutrition leads to the reprogramming of postnatal brain gene expression and that the epigenetic modifications contribute to the reprogramming. The process may impair learning and memory ability and result in higher susceptibility to schizophrenia. PMID:25522397

Expression of the Wilm's tumor gene WT1 during diaphragmatic development in the nitrofen model for congenital diaphragmatic hernia.

PubMed

Dingemann, Jens; Doi, Takashi; Ruttenstock, Elke; Puri, Prem

2011-02-01

The nitrofen model of congenital diaphragmatic hernia (CDH) reproduces a typical diaphragmatic defect. However, the exact pathomechanism of CDH is still unknown. The Wilm's tumor 1 gene (WT1) is crucial for diaphragmatic development. Mutations in WT1 associated with CDH have been described in humans. Additionally, WT1(-/-) mice display CDH. Furthermore, WT1 is involved in the retinoid signaling pathway, a candidate pathway for CDH. We hypothesized that diaphragmatic WT1 gene expression is downregulated during diaphragmatic development in the nitrofen CDH model. Pregnant rats received vehicle or nitrofen on gestational day 9 (D9). Embryos were delivered on D13, D18 and D21. The pleuroperitoneal folds (PPFs) were dissected using laser capture microdissection (D13). Diaphragms of D18 and D21 were manually dissected. RNA was extracted and relative mRNA expression of WT1 was determined using real-time PCR. Immunofluorescence was performed to evaluate protein expression of WT1. Statistical significance was considered p < 0.05. Diaphragmatic mRNA expression of WT1 was significantly decreased in the nitrofen group on D13, D18 and D21. Intensity of immunofluorescencence of WT1 was markedly decreased in the CDH diaphragms on D13, D18 and D21. Downregulation of diaphragmatic WT1 gene expression may impair diaphragmatic development in the nitrofen CDH model.

Plasticity for axolotl lens regeneration is associated with age‐related changes in gene expression

PubMed Central

Sousounis, Konstantinos; Athippozhy, Antony T.; Voss, S. Randal

2014-01-01

Abstract Mexican axolotls lose potential for lens regeneration 2 weeks after hatching. We used microarrays to identify differently expressed genes before and after this critical time, using RNA isolated from iris. Over 3700 genes were identified as differentially expressed in response to lentectomy between young (7 days post‐hatching) and old (3 months post‐hatching) axolotl larvae. Strikingly, many of the genes were only expressed in the early or late iris. Genes that were highly expressed in young iris significantly enriched electron transport chain, transcription, metabolism, and cell cycle gene ontologies, all of which are associated with lens regeneration. In contrast, genes associated with cellular differentiation and tissue maturation were uniquely expressed in old iris. Many of these expression differences strongly suggest that young and old iris samples were collected before and after the spleen became developmentally competent to produce and secrete cells with humoral and innate immunity functions. Our study establishes the axolotl as a powerful model to investigate age‐related cellular differentiation and immune system ontogeny within the context of tissue regeneration. PMID:27499863

Cancer cell redirection biomarker discovery using a mutual information approach.

PubMed

Roche, Kimberly; Feltus, F Alex; Park, Jang Pyo; Coissieux, Marie-May; Chang, Chenyan; Chan, Vera B S; Bentires-Alj, Mohamed; Booth, Brian W

2017-01-01

Introducing tumor-derived cells into normal mammary stem cell niches at a sufficiently high ratio of normal to tumorous cells causes those tumor cells to undergo a change to normal mammary phenotype and yield normal mammary progeny. This phenomenon has been termed cancer cell redirection. We have developed an in vitro model that mimics in vivo redirection of cancer cells by the normal mammary microenvironment. Using the RNA profiling data from this cellular model, we examined high-level characteristics of the normal, redirected, and tumor transcriptomes and found the global expression profiles clearly distinguish the three expression states. To identify potential redirection biomarkers that cause the redirected state to shift toward the normal expression pattern, we used mutual information relationships between normal, redirected, and tumor cell groups. Mutual information relationship analysis reduced a dataset of over 35,000 gene expression measurements spread over 13,000 curated gene sets to a set of 20 significant molecular signatures totaling 906 unique loci. Several of these molecular signatures are hallmark drivers of the tumor state. Using differential expression as a guide, we further refined the gene set to 120 core redirection biomarker genes. The expression levels of these core biomarkers are sufficient to make the normal and redirected gene expression states indistinguishable from each other but radically different from the tumor state.

Cancer cell redirection biomarker discovery using a mutual information approach

PubMed Central

Roche, Kimberly; Feltus, F. Alex; Park, Jang Pyo; Coissieux, Marie-May; Chang, Chenyan; Chan, Vera B. S.; Bentires-Alj, Mohamed

2017-01-01

Introducing tumor-derived cells into normal mammary stem cell niches at a sufficiently high ratio of normal to tumorous cells causes those tumor cells to undergo a change to normal mammary phenotype and yield normal mammary progeny. This phenomenon has been termed cancer cell redirection. We have developed an in vitro model that mimics in vivo redirection of cancer cells by the normal mammary microenvironment. Using the RNA profiling data from this cellular model, we examined high-level characteristics of the normal, redirected, and tumor transcriptomes and found the global expression profiles clearly distinguish the three expression states. To identify potential redirection biomarkers that cause the redirected state to shift toward the normal expression pattern, we used mutual information relationships between normal, redirected, and tumor cell groups. Mutual information relationship analysis reduced a dataset of over 35,000 gene expression measurements spread over 13,000 curated gene sets to a set of 20 significant molecular signatures totaling 906 unique loci. Several of these molecular signatures are hallmark drivers of the tumor state. Using differential expression as a guide, we further refined the gene set to 120 core redirection biomarker genes. The expression levels of these core biomarkers are sufficient to make the normal and redirected gene expression states indistinguishable from each other but radically different from the tumor state. PMID:28594912

The gene expression profile of non-cultured, highly purified human adipose tissue pericytes: Transcriptomic evidence that pericytes are stem cells in human adipose tissue

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

Silva Meirelles, Lindolfo da, E-mail: lindolfomeirelles@gmail.com; Laboratory for Stem Cells and Tissue Engineering, PPGBioSaúde, Lutheran University of Brazil, Av. Farroupilha 8001, 92425-900 Canoas, RS; Deus Wagatsuma, Virgínia Mara de

Pericytes (PCs) are a subset of perivascular cells that can give rise to mesenchymal stromal cells (MSCs) when culture-expanded, and are postulated to give rise to MSC-like cells during tissue repair in vivo. PCs have been suggested to behave as stem cells (SCs) in situ in animal models, although evidence for this role in humans is lacking. Here, we analyzed the transcriptomes of highly purified, non-cultured adipose tissue (AT)-derived PCs (ATPCs) to detect gene expression changes that occur as they acquire MSC characteristics in vitro, and evaluated the hypothesis that human ATPCs exhibit a gene expression profile compatible with anmore » AT SC phenotype. The results showed ATPCs are non-proliferative and express genes characteristic not only of PCs, but also of AT stem/progenitor cells. Additional analyses defined a gene expression signature for ATPCs, and revealed putative novel ATPC markers. Almost all AT stem/progenitor cell genes differentially expressed by ATPCs were not expressed by ATMSCs or culture-expanded ATPCs. Genes expressed by ATMSCs but not by ATPCs were also identified. These findings strengthen the hypothesis that PCs are SCs in vascularized tissues, highlight gene expression changes they undergo as they assume an MSC phenotype, and provide new insights into PC biology. - Highlights: • Non-cultured adipose tissue-derived human pericytes (ncATPCs) exhibit a distinctive gene expression signature. • ncATPCs express key adipose tissue stem cell genes previously described in vivo in mice. • ncATPCs express message for anti-proliferative and antiangiogenic molecules. • Most ncATPC-specific transcripts are absent in culture-expanded pericytes or ATMSCs • Gene expression changes ncATPCs undergo as they acquire a cultured ATMSC phenotype are pointed out.« less

Expression profiling of the mouse early embryo: Reflections and Perspectives

PubMed Central

Ko, Minoru S. H.

2008-01-01

Laboratory mouse plays important role in our understanding of early mammalian development and provides invaluable model for human early embryos, which are difficult to study for ethical and technical reasons. Comprehensive collection of cDNA clones, their sequences, and complete genome sequence information, which have been accumulated over last two decades, have provided even more advantages to mouse models. Here the progress in global gene expression profiling in early mouse embryos and, to some extent, stem cells are reviewed and the future directions and challenges are discussed. The discussions include the restatement of global gene expression profiles as snapshot of cellular status, and subsequent distinction between the differentiation state and physiological state of the cells. The discussions then extend to the biological problems that can be addressed only through global expression profiling, which include: bird’s-eye view of global gene expression changes, molecular index for developmental potency, cell lineage trajectory, microarray-guided cell manipulation, and the possibility of delineating gene regulatory cascades and networks. PMID:16739220

A comparative analysis of biclustering algorithms for gene expression data

PubMed Central

Eren, Kemal; Deveci, Mehmet; Küçüktunç, Onur; Çatalyürek, Ümit V.

2013-01-01

The need to analyze high-dimension biological data is driving the development of new data mining methods. Biclustering algorithms have been successfully applied to gene expression data to discover local patterns, in which a subset of genes exhibit similar expression levels over a subset of conditions. However, it is not clear which algorithms are best suited for this task. Many algorithms have been published in the past decade, most of which have been compared only to a small number of algorithms. Surveys and comparisons exist in the literature, but because of the large number and variety of biclustering algorithms, they are quickly outdated. In this article we partially address this problem of evaluating the strengths and weaknesses of existing biclustering methods. We used the BiBench package to compare 12 algorithms, many of which were recently published or have not been extensively studied. The algorithms were tested on a suite of synthetic data sets to measure their performance on data with varying conditions, such as different bicluster models, varying noise, varying numbers of biclusters and overlapping biclusters. The algorithms were also tested on eight large gene expression data sets obtained from the Gene Expression Omnibus. Gene Ontology enrichment analysis was performed on the resulting biclusters, and the best enrichment terms are reported. Our analyses show that the biclustering method and its parameters should be selected based on the desired model, whether that model allows overlapping biclusters, and its robustness to noise. In addition, we observe that the biclustering algorithms capable of finding more than one model are more successful at capturing biologically relevant clusters. PMID:22772837

Genome-wide DNA methylation drives human embryonic stem cell erythropoiesis by remodeling gene expression dynamics.

PubMed

Liu, Zhijing; Feng, Qiang; Sun, Pengpeng; Lu, Yan; Yang, Minlan; Zhang, Xiaowei; Jin, Xiangshu; Li, Yulin; Lu, Shi-Jiang; Quan, Chengshi

2017-12-01

To investigate the role of DNA methylation during erythrocyte production by human embryonic stem cells (hESCs). We employed an erythroid differentiation model from hESCs, and then tracked the genome-wide DNA methylation maps and gene expression patterns through an Infinium HumanMethylation450K BeadChip and an Ilumina Human HT-12 v4 Expression Beadchip, respectively. A negative correlation between DNA methylation and gene expression was substantially enriched during the later differentiation stage and was present in both the promoter and the gene body. Moreover, erythropoietic genes with differentially methylated CpG sites that were primarily enriched in nonisland regions were upregulated, and demethylation of their gene bodies was associated with the presence of enhancers and DNase I hypersensitive sites. Finally, the components of JAK-STAT-NF-κB signaling were DNA hypomethylated and upregulated, which targets the key genes for erythropoiesis. Erythroid lineage commitment by hESCs requires genome-wide DNA methylation modifications to remodel gene expression dynamics.

Effect of Retinol Palmitate on Corneal and Conjunctival Mucin Gene Expression in a Rat Dry Eye Model After Injury.

PubMed

Tabuchi, Nobuhito; Toshida, Hiroshi; Koike, Daisuke; Odaka, Akito; Suto, Chikako; Ohta, Toshihiko; Murakami, Akira

We examined the wound-healing effect of retinol palmitate (VApal) on mucin gene and protein expressions in a rat dry eye model based on lacrimal gland (LG) resection after injury. The rat dry eye model was prepared by surgical resection of the main LG in male Long-Evans rats. After alkaline injury of the central part of the lower palpebral conjunctiva bilaterally, VApal eye drops at 1,500 IU/mL in one eye and a vehicle in the fellow eye were both administered 6 times a day for 7 days. The expression of mucin gene and protein was analyzed by real-time polymerase chain reaction or enzyme-linked immunosorbent assay in the cornea and conjunctiva of MUC1, MUC4, MUC16, and MUC5AC after 1, 3, (5), and 7 days of treatment with VApal. Significant decreases in fluorescein-stained areas and rose bengal scores were observed in VApal-treated dry eyes compared with vehicle-treated dry eyes at both 3 (P < 0.05) and 7 days (P < 0.01). Significant increases in corneal rMuc4 and conjunctival rMuc5AC after 1 day (P < 0.01) and conjunctival rMuc16 gene expression after 3 days were observed with VApal treatment (P < 0.05). Furthermore, conjunctival MUC16 expression significantly increased after 3 days of VApal treatment (P < 0.05). VApal promoted corneal rMuc4, conjunctival rMuc5AC, and conjunctival rMuc16 gene expression in a rat dry eye model after injury. VApal also promoted conjunctival MUC16 expression. These results indicate that VApal has efficacy in improving keratoconjunctival epithelial damage associated with decreased tear production.

Characterization of docosahexaenoic acid (DHA)-induced heme oxygenase-1 (HO-1) expression in human cancer cells: the importance of enhanced BTB and CNC homology 1 (Bach1) degradation.

PubMed

Wang, Shuai; Hannafon, Bethany N; Wolf, Roman F; Zhou, Jundong; Avery, Jori E; Wu, Jinchang; Lind, Stuart E; Ding, Wei-Qun

2014-05-01

The effect of docosahexaenoic acid (DHA) on heme oxygenase-1 (HO-1) expression in cancer cells has never been characterized. This study examines DHA-induced HO-1 expression in human cancer cell model systems. DHA enhanced HO-1 gene expression in a time- and concentration-dependent manner, with maximal induction at 21 h of treatment. This induction of HO-1 expression was confirmed in vivo using a xenograft nude mouse model fed a fish-oil-enriched diet. The increase in HO-1 gene transcription induced by DHA was significantly attenuated by the antioxidant N-acetyl cysteine, suggesting the involvement of oxidative stress. This was supported by direct measurement of lipid peroxide levels after DHA treatment. Using a human HO-1 gene promoter reporter construct, we identified two antioxidant response elements (AREs) that mediate the DHA-induced increase in HO-1 gene transcription. Knockdown of nuclear factor (erythroid-derived 2)-like 2 (Nrf2) expression compromised the DHA-induced increase in HO-1 gene transcription, indicating the importance of the Nrf2 pathway in this event. However, the nuclear protein levels of Nrf2 remained unchanged upon DHA treatment. Further studies demonstrated that DHA reduces nuclear Bach1 protein expression by promoting its degradation and attenuates Bach1 binding to the AREs in the HO-1 gene promoter. In contrast, DHA enhanced Nrf2 binding to the AREs without affecting nuclear Nrf2 expression levels, indicating a new cellular mechanism that mediates DHA's induction of HO-1 gene transcription. To our knowledge, this is the first characterization of DHA-induced HO-1 expression in human malignant cells. Copyright © 2014 Elsevier Inc. All rights reserved.

Stability-driven nonnegative matrix factorization to interpret spatial gene expression and build local gene networks

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

Wu, Siqi; Joseph, Antony; Hammonds, Ann S.

Spatial gene expression patterns enable the detection of local covariability and are extremely useful for identifying local gene interactions during normal development. The abundance of spatial expression data in recent years has led to the modeling and analysis of regulatory networks. The inherent complexity of such data makes it a challenge to extract biological information. We developed staNMF, a method that combines a scalable implementation of nonnegative matrix factorization (NMF) with a new stability-driven model selection criterion. When applied to a set of Drosophila early embryonic spatial gene expression images, one of the largest datasets of its kind, staNMF identifiedmore » 21 principal patterns (PP). Providing a compact yet biologically interpretable representation of Drosophila expression patterns, PP are comparable to a fate map generated experimentally by laser ablation and show exceptional promise as a data-driven alternative to manual annotations. Our analysis mapped genes to cell-fate programs and assigned putative biological roles to uncharacterized genes. Finally, we used the PP to generate local transcription factor regulatory networks. Spatially local correlation networks were constructed for six PP that span along the embryonic anterior-posterior axis. Using a two-tail 5% cutoff on correlation, we reproduced 10 of the 11 links in the well-studied gap gene network. In conclusion, the performance of PP with the Drosophila data suggests that staNMF provides informative decompositions and constitutes a useful computational lens through which to extract biological insight from complex and often noisy gene expression data.« less

Stability-driven nonnegative matrix factorization to interpret spatial gene expression and build local gene networks

DOE PAGES

Wu, Siqi; Joseph, Antony; Hammonds, Ann S.; ...

2016-04-06

Spatial gene expression patterns enable the detection of local covariability and are extremely useful for identifying local gene interactions during normal development. The abundance of spatial expression data in recent years has led to the modeling and analysis of regulatory networks. The inherent complexity of such data makes it a challenge to extract biological information. We developed staNMF, a method that combines a scalable implementation of nonnegative matrix factorization (NMF) with a new stability-driven model selection criterion. When applied to a set of Drosophila early embryonic spatial gene expression images, one of the largest datasets of its kind, staNMF identifiedmore » 21 principal patterns (PP). Providing a compact yet biologically interpretable representation of Drosophila expression patterns, PP are comparable to a fate map generated experimentally by laser ablation and show exceptional promise as a data-driven alternative to manual annotations. Our analysis mapped genes to cell-fate programs and assigned putative biological roles to uncharacterized genes. Finally, we used the PP to generate local transcription factor regulatory networks. Spatially local correlation networks were constructed for six PP that span along the embryonic anterior-posterior axis. Using a two-tail 5% cutoff on correlation, we reproduced 10 of the 11 links in the well-studied gap gene network. In conclusion, the performance of PP with the Drosophila data suggests that staNMF provides informative decompositions and constitutes a useful computational lens through which to extract biological insight from complex and often noisy gene expression data.« less

GEM2Net: from gene expression modeling to -omics networks, a new CATdb module to investigate Arabidopsis thaliana genes involved in stress response.

PubMed

Zaag, Rim; Tamby, Jean Philippe; Guichard, Cécile; Tariq, Zakia; Rigaill, Guillem; Delannoy, Etienne; Renou, Jean-Pierre; Balzergue, Sandrine; Mary-Huard, Tristan; Aubourg, Sébastien; Martin-Magniette, Marie-Laure; Brunaud, Véronique

2015-01-01

CATdb (http://urgv.evry.inra.fr/CATdb) is a database providing a public access to a large collection of transcriptomic data, mainly for Arabidopsis but also for other plants. This resource has the rare advantage to contain several thousands of microarray experiments obtained with the same technical protocol and analyzed by the same statistical pipelines. In this paper, we present GEM2Net, a new module of CATdb that takes advantage of this homogeneous dataset to mine co-expression units and decipher Arabidopsis gene functions. GEM2Net explores 387 stress conditions organized into 18 biotic and abiotic stress categories. For each one, a model-based clustering is applied on expression differences to identify clusters of co-expressed genes. To characterize functions associated with these clusters, various resources are analyzed and integrated: Gene Ontology, subcellular localization of proteins, Hormone Families, Transcription Factor Families and a refined stress-related gene list associated to publications. Exploiting protein-protein interactions and transcription factors-targets interactions enables to display gene networks. GEM2Net presents the analysis of the 18 stress categories, in which 17,264 genes are involved and organized within 681 co-expression clusters. The meta-data analyses were stored and organized to compose a dynamic Web resource. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

Mitochondrial Gene Expression Profiles and Metabolic Pathways in the Amygdala Associated with Exaggerated Fear in an Animal Model of PTSD.

PubMed

Li, He; Li, Xin; Smerin, Stanley E; Zhang, Lei; Jia, Min; Xing, Guoqiang; Su, Yan A; Wen, Jillian; Benedek, David; Ursano, Robert

2014-01-01

The metabolic mechanisms underlying the development of exaggerated fear in post-traumatic stress disorder (PTSD) are not well defined. In the present study, alteration in the expression of genes associated with mitochondrial function in the amygdala of an animal model of PTSD was determined. Amygdala tissue samples were excised from 10 non-stressed control rats and 10 stressed rats, 14 days post-stress treatment. Total RNA was isolated, cDNA was synthesized, and gene expression levels were determined using a cDNA microarray. During the development of the exaggerated fear associated with PTSD, 48 genes were found to be significantly upregulated and 37 were significantly downregulated in the amygdala complex based on stringent criteria (p < 0.01). Ingenuity pathway analysis revealed up- or downregulation in the amygdala complex of four signaling networks - one associated with inflammatory and apoptotic pathways, one with immune mediators and metabolism, one with transcriptional factors, and one with chromatin remodeling. Thus, informatics of a neuronal gene array allowed us to determine the expression profile of mitochondrial genes in the amygdala complex of an animal model of PTSD. The result is a further understanding of the metabolic and neuronal signaling mechanisms associated with delayed and exaggerated fear.

Function does not follow form in gene regulatory circuits.

PubMed

Payne, Joshua L; Wagner, Andreas

2015-08-20

Gene regulatory circuits are to the cell what arithmetic logic units are to the chip: fundamental components of information processing that map an input onto an output. Gene regulatory circuits come in many different forms, distinct structural configurations that determine who regulates whom. Studies that have focused on the gene expression patterns (functions) of circuits with a given structure (form) have examined just a few structures or gene expression patterns. Here, we use a computational model to exhaustively characterize the gene expression patterns of nearly 17 million three-gene circuits in order to systematically explore the relationship between circuit form and function. Three main conclusions emerge. First, function does not follow form. A circuit of any one structure can have between twelve and nearly thirty thousand distinct gene expression patterns. Second, and conversely, form does not follow function. Most gene expression patterns can be realized by more than one circuit structure. And third, multifunctionality severely constrains circuit form. The number of circuit structures able to drive multiple gene expression patterns decreases rapidly with the number of these patterns. These results indicate that it is generally not possible to infer circuit function from circuit form, or vice versa.

Analytical workflow profiling gene expression in murine macrophages

PubMed Central

Nixon, Scott E.; González-Peña, Dianelys; Lawson, Marcus A.; McCusker, Robert H.; Hernandez, Alvaro G.; O’Connor, Jason C.; Dantzer, Robert; Kelley, Keith W.

2015-01-01

Comprehensive and simultaneous analysis of all genes in a biological sample is a capability of RNA-Seq technology. Analysis of the entire transcriptome benefits from summarization of genes at the functional level. As a cellular response of interest not previously explored with RNA-Seq, peritoneal macrophages from mice under two conditions (control and immunologically challenged) were analyzed for gene expression differences. Quantification of individual transcripts modeled RNA-Seq read distribution and uncertainty (using a Beta Negative Binomial distribution), then tested for differential transcript expression (False Discovery Rate-adjusted p-value < 0.05). Enrichment of functional categories utilized the list of differentially expressed genes. A total of 2079 differentially expressed transcripts representing 1884 genes were detected. Enrichment of 92 categories from Gene Ontology Biological Processes and Molecular Functions, and KEGG pathways were grouped into 6 clusters. Clusters included defense and inflammatory response (Enrichment Score = 11.24) and ribosomal activity (Enrichment Score = 17.89). Our work provides a context to the fine detail of individual gene expression differences in murine peritoneal macrophages during immunological challenge with high throughput RNA-Seq. PMID:25708305

Probabilistic representation of gene regulatory networks.

PubMed

Mao, Linyong; Resat, Haluk

2004-09-22

Recent experiments have established unambiguously that biological systems can have significant cell-to-cell variations in gene expression levels even in isogenic populations. Computational approaches to studying gene expression in cellular systems should capture such biological variations for a more realistic representation. In this paper, we present a new fully probabilistic approach to the modeling of gene regulatory networks that allows for fluctuations in the gene expression levels. The new algorithm uses a very simple representation for the genes, and accounts for the repression or induction of the genes and for the biological variations among isogenic populations simultaneously. Because of its simplicity, introduced algorithm is a very promising approach to model large-scale gene regulatory networks. We have tested the new algorithm on the synthetic gene network library bioengineered recently. The good agreement between the computed and the experimental results for this library of networks, and additional tests, demonstrate that the new algorithm is robust and very successful in explaining the experimental data. The simulation software is available upon request. Supplementary material will be made available on the OUP server.

Molecular Mechanisms of Increased Heart Rate in Shenxianshengmai-treated Bradycardia Rabbits.

PubMed

Liu, Zhou-Ying; Huang, Jian; Liu, Na-Na; Zheng, Min; Zhao, Tao; Zhao, Bu-Chang; Wang, Yi-Min; Pu, Jie-Lin

2017-01-20

The molecular mechanisms of Shenxianshengmai (SXSM), a traditional Chinese medicine, on bradycardia have been incompletely understood. The study tried to investigate the gene expression profile and proteomics of bradycardia rabbits' hearts after SXSM treatment. Twenty-four adult rabbits were randomly assigned in four groups: sham, model, model plus SXSM treatment, and sham plus SXSM treatment groups. Heart rate was recorded in all rabbits. Then, total RNA of atria and proteins of ventricle were isolated and quantified, respectively. Gene expression profiling was conducted by gene expression chip, and quantitative real-time reverse transcription-polymerase chain reaction (RT-PCR) was performed to confirm the results of gene expression chip. We used isobaric tags for elative and absolute quantitation and Western blotting to identify altered proteins after SXSM treatment. There was a constant decrease in the mean heart rate (32%, from 238 ± 6 beats/min to 149 ± 12 beats/min) after six weeks in model compared with that in sham group. This effect was partially reversed by 4-week SXSM treatment. Complementary DNA microarray demonstrated that the increased acetylcholinesterase and reduced nicotinic receptor were take responsibility for the increased heart rate. In addition, proteins involved in calcium handling and signaling were affected by SXSM treatment. Real-time RT-PCR verified the results from gene chip. Results from proteomics demonstrated that SXSM enhanced oxidative phosphorylation and tricarboxylic acid (TCA) cycle in ventricular myocardium to improve ATP generation. Long-term SXSM stimulates sympathetic transmission by increasing the expression of acetylcholinesterase and reduces the expression of nicotinic receptor to increase heart rate. SXSM also restored the calcium handling genes and altered genes involved in signaling. In addition, SXSM improves the ATP supply of ventricular myocardium by increasing proteins involved in TCA cycle and oxidation-respiratory chain.

Molecular Mechanisms of Increased Heart Rate in Shenxianshengmai-treated Bradycardia Rabbits

PubMed Central

Liu, Zhou-Ying; Huang, Jian; Liu, Na-Na; Zheng, Min; Zhao, Tao; Zhao, Bu-Chang; Wang, Yi-Min; Pu, Jie-Lin

2017-01-01

Background: The molecular mechanisms of Shenxianshengmai (SXSM), a traditional Chinese medicine, on bradycardia have been incompletely understood. The study tried to investigate the gene expression profile and proteomics of bradycardia rabbits’ hearts after SXSM treatment. Methods: Twenty-four adult rabbits were randomly assigned in four groups: sham, model, model plus SXSM treatment, and sham plus SXSM treatment groups. Heart rate was recorded in all rabbits. Then, total RNA of atria and proteins of ventricle were isolated and quantified, respectively. Gene expression profiling was conducted by gene expression chip, and quantitative real-time reverse transcription-polymerase chain reaction (RT-PCR) was performed to confirm the results of gene expression chip. We used isobaric tags for elative and absolute quantitation and Western blotting to identify altered proteins after SXSM treatment. Results: There was a constant decrease in the mean heart rate (32%, from 238 ± 6 beats/min to 149 ± 12 beats/min) after six weeks in model compared with that in sham group. This effect was partially reversed by 4-week SXSM treatment. Complementary DNA microarray demonstrated that the increased acetylcholinesterase and reduced nicotinic receptor were take responsibility for the increased heart rate. In addition, proteins involved in calcium handling and signaling were affected by SXSM treatment. Real-time RT-PCR verified the results from gene chip. Results from proteomics demonstrated that SXSM enhanced oxidative phosphorylation and tricarboxylic acid (TCA) cycle in ventricular myocardium to improve ATP generation. Conclusions: Long-term SXSM stimulates sympathetic transmission by increasing the expression of acetylcholinesterase and reduces the expression of nicotinic receptor to increase heart rate. SXSM also restored the calcium handling genes and altered genes involved in signaling. In addition, SXSM improves the ATP supply of ventricular myocardium by increasing proteins involved in TCA cycle and oxidation-respiratory chain. PMID:28091410

Gene Expression Ratios Lead to Accurate and Translatable Predictors of DR5 Agonism across Multiple Tumor Lineages.

PubMed

Reddy, Anupama; Growney, Joseph D; Wilson, Nick S; Emery, Caroline M; Johnson, Jennifer A; Ward, Rebecca; Monaco, Kelli A; Korn, Joshua; Monahan, John E; Stump, Mark D; Mapa, Felipa A; Wilson, Christopher J; Steiger, Janine; Ledell, Jebediah; Rickles, Richard J; Myer, Vic E; Ettenberg, Seth A; Schlegel, Robert; Sellers, William R; Huet, Heather A; Lehár, Joseph

2015-01-01

Death Receptor 5 (DR5) agonists demonstrate anti-tumor activity in preclinical models but have yet to demonstrate robust clinical responses. A key limitation may be the lack of patient selection strategies to identify those most likely to respond to treatment. To overcome this limitation, we screened a DR5 agonist Nanobody across >600 cell lines representing 21 tumor lineages and assessed molecular features associated with response. High expression of DR5 and Casp8 were significantly associated with sensitivity, but their expression thresholds were difficult to translate due to low dynamic ranges. To address the translational challenge of establishing thresholds of gene expression, we developed a classifier based on ratios of genes that predicted response across lineages. The ratio classifier outperformed the DR5+Casp8 classifier, as well as standard approaches for feature selection and classification using genes, instead of ratios. This classifier was independently validated using 11 primary patient-derived pancreatic xenograft models showing perfect predictions as well as a striking linearity between prediction probability and anti-tumor response. A network analysis of the genes in the ratio classifier captured important biological relationships mediating drug response, specifically identifying key positive and negative regulators of DR5 mediated apoptosis, including DR5, CASP8, BID, cFLIP, XIAP and PEA15. Importantly, the ratio classifier shows translatability across gene expression platforms (from Affymetrix microarrays to RNA-seq) and across model systems (in vitro to in vivo). Our approach of using gene expression ratios presents a robust and novel method for constructing translatable biomarkers of compound response, which can also probe the underlying biology of treatment response.

Gene Expression Ratios Lead to Accurate and Translatable Predictors of DR5 Agonism across Multiple Tumor Lineages

PubMed Central

Reddy, Anupama; Growney, Joseph D.; Wilson, Nick S.; Emery, Caroline M.; Johnson, Jennifer A.; Ward, Rebecca; Monaco, Kelli A.; Korn, Joshua; Monahan, John E.; Stump, Mark D.; Mapa, Felipa A.; Wilson, Christopher J.; Steiger, Janine; Ledell, Jebediah; Rickles, Richard J.; Myer, Vic E.; Ettenberg, Seth A.; Schlegel, Robert; Sellers, William R.

2015-01-01

Death Receptor 5 (DR5) agonists demonstrate anti-tumor activity in preclinical models but have yet to demonstrate robust clinical responses. A key limitation may be the lack of patient selection strategies to identify those most likely to respond to treatment. To overcome this limitation, we screened a DR5 agonist Nanobody across >600 cell lines representing 21 tumor lineages and assessed molecular features associated with response. High expression of DR5 and Casp8 were significantly associated with sensitivity, but their expression thresholds were difficult to translate due to low dynamic ranges. To address the translational challenge of establishing thresholds of gene expression, we developed a classifier based on ratios of genes that predicted response across lineages. The ratio classifier outperformed the DR5+Casp8 classifier, as well as standard approaches for feature selection and classification using genes, instead of ratios. This classifier was independently validated using 11 primary patient-derived pancreatic xenograft models showing perfect predictions as well as a striking linearity between prediction probability and anti-tumor response. A network analysis of the genes in the ratio classifier captured important biological relationships mediating drug response, specifically identifying key positive and negative regulators of DR5 mediated apoptosis, including DR5, CASP8, BID, cFLIP, XIAP and PEA15. Importantly, the ratio classifier shows translatability across gene expression platforms (from Affymetrix microarrays to RNA-seq) and across model systems (in vitro to in vivo). Our approach of using gene expression ratios presents a robust and novel method for constructing translatable biomarkers of compound response, which can also probe the underlying biology of treatment response. PMID:26378449

Correlated gene expression and anatomical communication support synchronized brain activity in the mouse functional connectome.

PubMed

Mills, Brian D; Grayson, David S; Shunmugavel, Anandakumar; Miranda-Dominguez, Oscar; Feczko, Eric; Earl, Eric; Neve, Kim; Fair, Damien A

2018-05-22

Cognition and behavior depend on synchronized intrinsic brain activity that is organized into functional networks across the brain. Research has investigated how anatomical connectivity both shapes and is shaped by these networks, but not how anatomical connectivity interacts with intra-areal molecular properties to drive functional connectivity. Here, we present a novel linear model to explain functional connectivity by integrating systematically obtained measurements of axonal connectivity, gene expression, and resting state functional connectivity MRI in the mouse brain. The model suggests that functional connectivity arises from both anatomical links and inter-areal similarities in gene expression. By estimating these effects, we identify anatomical modules in which correlated gene expression and anatomical connectivity support functional connectivity. Along with providing evidence that not all genes equally contribute to functional connectivity, this research establishes new insights regarding the biological underpinnings of coordinated brain activity measured by BOLD fMRI. SIGNIFICANCE STATEMENT Efforts at characterizing the functional connectome with fMRI have risen exponentially over the last decade. Yet despite this rise, the biological underpinnings of these functional measurements are still largely unknown. The current report begins to fill this void by investigating the molecular underpinnings of the functional connectome through an integration of systematically obtained structural information and gene expression data throughout the rodent brain. We find that both white matter connectivity and similarity in regional gene expression relate to resting state functional connectivity. The current report furthers our understanding of the biological underpinnings of the functional connectome and provides a linear model that can be utilized to streamline preclinical animal studies of disease. Copyright © 2018 the authors.

Expression of selected genes escaping from X inactivation in the 41, XX(Y)* mouse model for Klinefelter's syndrome.

PubMed

Werler, Steffi; Poplinski, Andreas; Gromoll, Jörg; Wistuba, Joachim

2011-06-01

We hypothesized that patients with Klinefelter's syndrome (KS) not only undergo X inactivation, but also that genes escape from inactivation. Their transcripts would constitute a significant difference, as male metabolism is not adapted to a 'female-like' gene dosage. We evaluated the expression of selected X-linked genes in our 41, XX(Y)* male mice to determine whether these genes escape inactivation and whether tissue-specific differences occur. Correct X inactivation was identified by Xist expression. Relative expression of X-linked genes was examined in liver, kidney and brain tissue by real-time PCR in adult XX(Y)* and XY* males and XX females. Expression of genes known to escape X inactivation was analysed. Relative mRNA levels of Pgk1 (control, X inactivated), and the genes Eif2s3x, Kdm5c, Ddx3x and Kdm6a escaping from X inactivation were quantified from liver, kidney and brain. Pgk1 mRNA expression showed no difference, confirming correct X inactivation. In kidney and liver, XX(Y)* males resembled the female expression pattern in all four candidate genes and were distinguishable from XY* males. Contrastingly, in brain tissue XX(Y)* males expressed all four genes higher than male and female controls. Altered expression of genes escaping X inactivation probably contributes directly to the XX(Y)* phenotype. © 2011 The Author(s)/Acta Paediatrica © 2011 Foundation Acta Paediatrica.

A probabilistic framework for microarray data analysis: fundamental probability models and statistical inference.

PubMed

Ogunnaike, Babatunde A; Gelmi, Claudio A; Edwards, Jeremy S

2010-05-21

Gene expression studies generate large quantities of data with the defining characteristic that the number of genes (whose expression profiles are to be determined) exceed the number of available replicates by several orders of magnitude. Standard spot-by-spot analysis still seeks to extract useful information for each gene on the basis of the number of available replicates, and thus plays to the weakness of microarrays. On the other hand, because of the data volume, treating the entire data set as an ensemble, and developing theoretical distributions for these ensembles provides a framework that plays instead to the strength of microarrays. We present theoretical results that under reasonable assumptions, the distribution of microarray intensities follows the Gamma model, with the biological interpretations of the model parameters emerging naturally. We subsequently establish that for each microarray data set, the fractional intensities can be represented as a mixture of Beta densities, and develop a procedure for using these results to draw statistical inference regarding differential gene expression. We illustrate the results with experimental data from gene expression studies on Deinococcus radiodurans following DNA damage using cDNA microarrays. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

Understanding Transcription Factor Regulation by Integrating Gene Expression and DNase I Hypersensitive Sites.

PubMed

Wang, Guohua; Wang, Fang; Huang, Qian; Li, Yu; Liu, Yunlong; Wang, Yadong

2015-01-01

Transcription factors are proteins that bind to DNA sequences to regulate gene transcription. The transcription factor binding sites are short DNA sequences (5-20 bp long) specifically bound by one or more transcription factors. The identification of transcription factor binding sites and prediction of their function continue to be challenging problems in computational biology. In this study, by integrating the DNase I hypersensitive sites with known position weight matrices in the TRANSFAC database, the transcription factor binding sites in gene regulatory region are identified. Based on the global gene expression patterns in cervical cancer HeLaS3 cell and HelaS3-ifnα4h cell (interferon treatment on HeLaS3 cell for 4 hours), we present a model-based computational approach to predict a set of transcription factors that potentially cause such differential gene expression. Significantly, 6 out 10 predicted functional factors, including IRF, IRF-2, IRF-9, IRF-1 and IRF-3, ICSBP, belong to interferon regulatory factor family and upregulate the gene expression levels responding to the interferon treatment. Another factor, ISGF-3, is also a transcriptional activator induced by interferon alpha. Using the different transcription factor binding sites selected criteria, the prediction result of our model is consistent. Our model demonstrated the potential to computationally identify the functional transcription factors in gene regulation.

Revealing cell cycle control by combining model-based detection of periodic expression with novel cis-regulatory descriptors

PubMed Central

Andersson, Claes R; Hvidsten, Torgeir R; Isaksson, Anders; Gustafsson, Mats G; Komorowski, Jan

2007-01-01

Background We address the issue of explaining the presence or absence of phase-specific transcription in budding yeast cultures under different conditions. To this end we use a model-based detector of gene expression periodicity to divide genes into classes depending on their behavior in experiments using different synchronization methods. While computational inference of gene regulatory circuits typically relies on expression similarity (clustering) in order to find classes of potentially co-regulated genes, this method instead takes advantage of known time profile signatures related to the studied process. Results We explain the regulatory mechanisms of the inferred periodic classes with cis-regulatory descriptors that combine upstream sequence motifs with experimentally determined binding of transcription factors. By systematic statistical analysis we show that periodic classes are best explained by combinations of descriptors rather than single descriptors, and that different combinations correspond to periodic expression in different classes. We also find evidence for additive regulation in that the combinations of cis-regulatory descriptors associated with genes periodically expressed in fewer conditions are frequently subsets of combinations associated with genes periodically expression in more conditions. Finally, we demonstrate that our approach retrieves combinations that are more specific towards known cell-cycle related regulators than the frequently used clustering approach. Conclusion The results illustrate how a model-based approach to expression analysis may be particularly well suited to detect biologically relevant mechanisms. Our new approach makes it possible to provide more refined hypotheses about regulatory mechanisms of the cell cycle and it can easily be adjusted to reveal regulation of other, non-periodic, cellular processes. PMID:17939860

Genome-wide prediction and analysis of human tissue-selective genes using microarray expression data

PubMed Central

2013-01-01

Background Understanding how genes are expressed specifically in particular tissues is a fundamental question in developmental biology. Many tissue-specific genes are involved in the pathogenesis of complex human diseases. However, experimental identification of tissue-specific genes is time consuming and difficult. The accurate predictions of tissue-specific gene targets could provide useful information for biomarker development and drug target identification. Results In this study, we have developed a machine learning approach for predicting the human tissue-specific genes using microarray expression data. The lists of known tissue-specific genes for different tissues were collected from UniProt database, and the expression data retrieved from the previously compiled dataset according to the lists were used for input vector encoding. Random Forests (RFs) and Support Vector Machines (SVMs) were used to construct accurate classifiers. The RF classifiers were found to outperform SVM models for tissue-specific gene prediction. The results suggest that the candidate genes for brain or liver specific expression can provide valuable information for further experimental studies. Our approach was also applied for identifying tissue-selective gene targets for different types of tissues. Conclusions A machine learning approach has been developed for accurately identifying the candidate genes for tissue specific/selective expression. The approach provides an efficient way to select some interesting genes for developing new biomedical markers and improve our knowledge of tissue-specific expression. PMID:23369200

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.

Alteration of Gene Expression, DNA Methylation, and Histone Methylation in Free Radical Scavenging Networks in Adult Mouse Hippocampus following Fetal Alcohol Exposure.

PubMed

Chater-Diehl, Eric J; Laufer, Benjamin I; Castellani, Christina A; Alberry, Bonnie L; Singh, Shiva M

2016-01-01

The molecular basis of Fetal Alcohol Spectrum Disorders (FASD) is poorly understood; however, epigenetic and gene expression changes have been implicated. We have developed a mouse model of FASD characterized by learning and memory impairment and persistent gene expression changes. Epigenetic marks may maintain expression changes over a mouse's lifetime, an area few have explored. Here, mice were injected with saline or ethanol on postnatal days four and seven. At 70 days of age gene expression microarray, methylated DNA immunoprecipitation microarray, H3K4me3 and H3K27me3 chromatin immunoprecipitation microarray were performed. Following extensive pathway analysis of the affected genes, we identified the top affected gene expression pathway as "Free radical scavenging". We confirmed six of these changes by droplet digital PCR including the caspase Casp3 and Wnt transcription factor Tcf7l2. The top pathway for all methylation-affected genes was "Peroxisome biogenesis"; we confirmed differential DNA methylation in the Acca1 thiolase promoter. Altered methylation and gene expression in oxidative stress pathways in the adult hippocampus suggests a novel interface between epigenetic and oxidative stress mechanisms in FASD.

Generation of a foveomacular transcriptome

PubMed Central

Bernstein, Steven; Wong, Paul W.

2014-01-01

Purpose Organizing molecular biologic data is a growing challenge since the rate of data accumulation is steadily increasing. Information relevant to a particular biologic query can be difficult to extract from the comprehensive databases currently available. We present a data collection and organization model designed to ameliorate these problems and applied it to generate an expressed sequence tag (EST)–based foveomacular transcriptome. Methods Using Perl, MySQL, EST libraries, screening, and human foveomacular gene expression as a model system, we generated a foveomacular transcriptome database enriched for molecularly relevant data. Results Using foveomacula as a gene expression model tissue, we identified and organized 6,056 genes expressed in that tissue. Of those identified genes, 3,480 had not been previously described as expressed in the foveomacula. Internal experimental controls as well as comparison of our data set to published data sets suggest we do not yet have a complete description of the foveomacula transcriptome. Conclusions We present an organizational method designed to amplify the utility of data pertinent to a specific research interest. Our method is generic enough to be applicable to a variety of conditions yet focused enough to allow for specialized study. PMID:24991187

Differential gene expression detection and sample classification using penalized linear regression models.

PubMed

Wu, Baolin

2006-02-15

Differential gene expression detection and sample classification using microarray data have received much research interest recently. Owing to the large number of genes p and small number of samples n (p > n), microarray data analysis poses big challenges for statistical analysis. An obvious problem owing to the 'large p small n' is over-fitting. Just by chance, we are likely to find some non-differentially expressed genes that can classify the samples very well. The idea of shrinkage is to regularize the model parameters to reduce the effects of noise and produce reliable inferences. Shrinkage has been successfully applied in the microarray data analysis. The SAM statistics proposed by Tusher et al. and the 'nearest shrunken centroid' proposed by Tibshirani et al. are ad hoc shrinkage methods. Both methods are simple, intuitive and prove to be useful in empirical studies. Recently Wu proposed the penalized t/F-statistics with shrinkage by formally using the (1) penalized linear regression models for two-class microarray data, showing good performance. In this paper we systematically discussed the use of penalized regression models for analyzing microarray data. We generalize the two-class penalized t/F-statistics proposed by Wu to multi-class microarray data. We formally derive the ad hoc shrunken centroid used by Tibshirani et al. using the (1) penalized regression models. And we show that the penalized linear regression models provide a rigorous and unified statistical framework for sample classification and differential gene expression detection.

Differential maturation of rhythmic clock gene expression during early development in medaka (Oryzias latipes).

PubMed

Cuesta, Ines H; Lahiri, Kajori; Lopez-Olmeda, Jose Fernando; Loosli, Felix; Foulkes, Nicholas S; Vallone, Daniela

2014-05-01

One key challenge for the field of chronobiology is to identify how circadian clock function emerges during early embryonic development. Teleosts such as the zebrafish are ideal models for studying circadian clock ontogeny since the entire process of development occurs ex utero in an optically transparent chorion. Medaka (Oryzias latipes) represents another powerful fish model for exploring early clock function with, like the zebrafish, many tools available for detailed genetic analysis. However, to date there have been no reports documenting circadian clock gene expression during medaka development. Here we have characterized the expression of key clock genes in various developmental stages and in adult tissues of medaka. As previously reported for other fish, light dark cycles are required for the emergence of clock gene expression rhythms in this species. While rhythmic expression of per and cry genes is detected very early during development and seems to be light driven, rhythmic clock and bmal expression appears much later around hatching time. Furthermore, the maturation of clock function seems to correlate with the appearance of rhythmic expression of these positive elements of the clock feedback loop. By accelerating development through elevated temperatures or by artificially removing the chorion, we show an earlier onset of rhythmicity in clock and bmal expression. Thus, differential maturation of key elements of the medaka clock mechanism depends on the developmental stage and the presence of the chorion.

Interplay of bistable kinetics of gene expression during cellular growth

NASA Astrophysics Data System (ADS)

Zhdanov, Vladimir P.

2009-02-01

In cells, the bistable kinetics of gene expression can be observed on the level of (i) one gene with positive feedback between protein and mRNA production, (ii) two genes with negative mutual feedback between protein and mRNA production, or (iii) in more complex cases. We analyse the interplay of two genes of type (ii) governed by a gene of type (i) during cellular growth. In particular, using kinetic Monte Carlo simulations, we show that in the case where gene 1, operating in the bistable regime, regulates mutually inhibiting genes 2 and 3, also operating in the bistable regime, the latter genes may eventually be trapped either to the state with high transcriptional activity of gene 2 and low activity of gene 3 or to the state with high transcriptional activity of gene 3 and low activity of gene 2. The probability to get to one of these states depends on the values of the model parameters. If genes 2 and 3 are kinetically equivalent, the probability is equal to 0.5. Thus, our model illustrates how different intracellular states can be chosen at random with predetermined probabilities. This type of kinetics of gene expression may be behind complex processes occurring in cells, e.g., behind the choice of the fate by stem cells.

Sex-Biased Temporal Gene Expression in Male and Female Floral Buds of Seabuckthorn (Hippophae rhamnoides).

PubMed

Chawla, Aseem; Stobdan, Tsering; Srivastava, Ravi B; Jaiswal, Varun; Chauhan, Rajinder S; Kant, Anil

2015-01-01

Seabuckthorn is an economically important dioecious plant in which mechanism of sex determination is unknown. The study was conducted to identify seabuckthorn homologous genes involved in floral development which may have role in sex determination. Forty four putative Genes involved in sex determination (GISD) reported in model plants were shortlisted from literature survey, and twenty nine seabuckthorn homologous sequences were identified from available seabuckthorn genomic resources. Of these, 21 genes were found to differentially express in either male or female flower bud stages. HrCRY2 was significantly expressed in female flower buds only while HrCO had significant expression in male flowers only. Among the three male and female floral development stages (FDS), male stage II had significant expression of most of the GISD. Information on these sex-specific expressed genes will help in elucidating sex determination mechanism in seabuckthorn.

Sex-Biased Temporal Gene Expression in Male and Female Floral Buds of Seabuckthorn (Hippophae rhamnoides)

PubMed Central

Chawla, Aseem; Stobdan, Tsering; Srivastava, Ravi B.; Jaiswal, Varun; Chauhan, Rajinder S.; Kant, Anil

2015-01-01

Seabuckthorn is an economically important dioecious plant in which mechanism of sex determination is unknown. The study was conducted to identify seabuckthorn homologous genes involved in floral development which may have role in sex determination. Forty four putative Genes involved in sex determination (GISD) reported in model plants were shortlisted from literature survey, and twenty nine seabuckthorn homologous sequences were identified from available seabuckthorn genomic resources. Of these, 21 genes were found to differentially express in either male or female flower bud stages. HrCRY2 was significantly expressed in female flower buds only while HrCO had significant expression in male flowers only. Among the three male and female floral development stages (FDS), male stage II had significant expression of most of the GISD. Information on these sex-specific expressed genes will help in elucidating sex determination mechanism in seabuckthorn. PMID:25915052

Gene selection for tumor classification using neighborhood rough sets and entropy measures.

PubMed

Chen, Yumin; Zhang, Zunjun; Zheng, Jianzhong; Ma, Ying; Xue, Yu

2017-03-01

With the development of bioinformatics, tumor classification from gene expression data becomes an important useful technology for cancer diagnosis. Since a gene expression data often contains thousands of genes and a small number of samples, gene selection from gene expression data becomes a key step for tumor classification. Attribute reduction of rough sets has been successfully applied to gene selection field, as it has the characters of data driving and requiring no additional information. However, traditional rough set method deals with discrete data only. As for the gene expression data containing real-value or noisy data, they are usually employed by a discrete preprocessing, which may result in poor classification accuracy. In this paper, we propose a novel gene selection method based on the neighborhood rough set model, which has the ability of dealing with real-value data whilst maintaining the original gene classification information. Moreover, this paper addresses an entropy measure under the frame of neighborhood rough sets for tackling the uncertainty and noisy of gene expression data. The utilization of this measure can bring about a discovery of compact gene subsets. Finally, a gene selection algorithm is designed based on neighborhood granules and the entropy measure. Some experiments on two gene expression data show that the proposed gene selection is an effective method for improving the accuracy of tumor classification. Copyright © 2017 Elsevier Inc. All rights reserved.

Oligonucleotide Microarray Analysis of Dietary-Induced Hyperlipidemia Gene Expression Profiles in Miniature Pigs

PubMed Central

Takahashi, Junko; Waki, Shiori; Matsumoto, Rena; Odake, Junji; Miyaji, Takayuki; Tottori, Junichi; Iwanaga, Takehiro; Iwahashi, Hitoshi

2012-01-01

Background Hyperlipidemia animal models have been established, but complete gene expression profiles of the transition from normal lipid levels have not been obtained. Miniature pigs are useful model animals for gene expression studies on dietary-induced hyperlipidemia because they have a similar anatomy and digestive physiology to humans, and blood samples can be obtained from them repeatedly. Methodology Two typical dietary treatments were used for dietary-induced hyperlipidemia models, by using specific pathogen-free (SPF) Clawn miniature pigs. One was a high-fat and high-cholesterol diet (HFCD) and the other was a high-fat, high-cholesterol, and high-sucrose diet (HFCSD). Microarray analyses were conducted from whole blood samples during the dietary period and from white blood cells at the end of the dietary period to evaluate the transition of expression profiles of the two dietary models. Principal Findings Variations in whole blood gene expression intensity within the HFCD or the HFCSD group were in the same range as the controls provide with normal diet at all periods. This indicates uniformity of dietary-induced hyperlipidemia for our dietary protocols. Gene ontology- (GO) based functional analyses revealed that characteristics of the common changes between HFCD and HFCSD were involved in inflammatory responses and reproduction. The correlation coefficient between whole blood and white blood cell expression profiles at 27 weeks with the HFCSD diet was significantly lower than that of the control and HFCD diet groups. This may be due to the effects of RNA originating from the tissues and/or organs. Conclusions No statistically significant differences in fasting plasma lipids and glucose levels between the HFCD and HFCSD groups were observed. However, blood RNA analyses revealed different characteristics corresponding to the dietary protocols. In this study, whole blood RNA analyses proved to be a useful tool to evaluate transitions in dietary-induced hyperlipidemia gene expression profiles in miniature pigs. PMID:22662175

Comparison of virulence factors and expression of specific genes between uropathogenic Escherichia coli and avian pathogenic E. coli in a murine urinary tract infection model and a chicken challenge model.

PubMed

Zhao, Lixiang; Gao, Song; Huan, Haixia; Xu, Xiaojing; Zhu, Xiaoping; Yang, Weixia; Gao, Qingqing; Liu, Xiufan

2009-05-01

Avian pathogenic Escherichia coli (APEC) and uropathogenic E. coli (UPEC) establish infections in extraintestinal habitats of different hosts. As the diversity, epidemiological sources and evolutionary origins of extraintestinal pathogenic E. coli (ExPEC) are so far only partially defined, in the present study,100 APEC isolates and 202 UPEC isolates were compared by their content of virulence genes and phylogenetic groups. The two groups showed substantial overlap in terms of their serogroups, phylogenetic groups and virulence genotypes, including their possession of certain genes associated with large transmissible plasmids of APEC. In a chicken challenge model, both UPEC U17 and APEC E058 had similar LD(50), demonstrating that UPEC U17 had the potential to cause significant disease in poultry. To gain further information about the similarities between UPEC and APEC, the in vivo expression of 152 specific genes of UPEC U17 and APEC E058 in both a murine urinary tract infection (UTI) model and a chicken challenge model was compared with that of these strains grown statically to exponential phase in rich medium. It was found that in the same model (murine UTI or chicken challenge), various genes of UPEC U17 and APEC E058 showed a similar tendency of expression. Several iron-related genes were upregulated in the UTI model and/or chicken challenge model, indicating that iron acquisition is important for E. coli to survive in blood or the urinary tract. Based on these results, the potential for APEC to act as human UPEC or as a reservoir of virulence genes for UPEC should be considered. Further, this study compared the transcriptional profile of virulence genes among APEC and UPEC in vivo.

[Differential gene expression profile in ischemic myocardium of Wistar rats with acute myocardial infarction: the study on gene construction, identification and function].

PubMed

Guo, Chun Yu; Yin, Hui Jun; Jiang, Yue Rong; Xue, Mei; Zhang, Lu; Shi, Da Zhuo

2008-06-18

To construct the differential genes expressed profile in the ischemic myocardium tissue reduced from acute myocardial infarction(AMI), and determine the biological functions of target genes. AMI model was generated by ligation of the left anterior descending coronary artery in Wistar rats. Total RNA was extracted from the normal and the ischemic heart tissues under the ligation point 7 days after the operation. Differential gene expression profiles of the two samples were constructed using Long Serial Analysis of Gene Expression(LongSAGE). Real time fluorescence quantitative PCR was used to verify gene expression profile and to identify the expression of 2 functional genes. The activities of enzymes from functional genes were determined by histochemistry. A total of 15,966 tags were screened from the normal and the ischemic LongSAGE maps. The similarities of the sequences were compared using the BLAST algebra in NCBI and 7,665 novel tags were found. In the ischemic tissue 142 genes were significantly changed compared with those in the normal tissue (P<0.05). These differentially expressed genes represented the proteins which might play important roles in the pathways of oxidation and phosphorylation, ATP synthesis and glycolysis. The partial genes identified by LongSAGE were confirmed using real time fluorescence quantitative PCR. Two genes related to energy metabolism, COX5a and ATP5e, were screened and quantified. Expression of two functional genes down-regulated at their mRNA levels and the activities of correlative functional enzymes decreased compared with those in the normal tissue. AMI causes a series of changes in gene expression, in which the abnormal expression of genes related to energy metabolism could be one of the molecular mechanisms of AMI. The intervention of the expressions of COX5a and ATP5e may be a new target for AMI therapy.

Comparative Analysis of AhR-Mediated TCDD-Elicited Gene Expression in Human Liver Adult Stem Cells

PubMed Central

Kim, Suntae; Dere, Edward; Burgoon, Lyle D.; Chang, Chia-Cheng; Zacharewski, Timothy R.

2009-01-01

Time course and dose-response studies were conducted in HL1-1 cells, a human liver cell line with stem cell–like characteristics, to assess the differential gene expression elicited by 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) compared with other established models. Cells were treated with 0.001, 0.01, 0.1, 1, 10, or 100nM TCDD or dimethyl sulfoxide vehicle control for 12 h for the dose-response study, or with 10nM TCDD or vehicle for 1, 2, 4, 8, 12, 24, or 48 h for the time course study. Elicited changes were monitored using a human cDNA microarray with 6995 represented genes. Empirical Bayes analysis identified 144 genes differentially expressed at one or more time points following treatment. Most genes exhibited dose-dependent responses including CYP1A1, CYP1B1, ALDH1A3, and SLC7A5 genes. Comparative analysis of HL1-1 differential gene expression to human HepG2 data identified 74 genes with comparable temporal expression profiles including 12 putative primary responses. HL1-1–specific changes were related to lipid metabolism and immune responses, consistent with effects elicited in vivo. Furthermore, comparative analysis of HL1-1 cells with mouse Hepa1c1c7 hepatoma cell lines and C57BL/6 hepatic tissue identified 18 and 32 commonly regulated orthologous genes, respectively, with functions associated with signal transduction, transcriptional regulation, metabolism and transport. Although some common pathways are affected, the results suggest that TCDD elicits species- and model-specific gene expression profiles. PMID:19684285

HCV IRES-Mediated Core Expression in Zebrafish

PubMed Central

Zhang, Jing-Pu; Hu, Zhan-Ying; Tong, Jun-Wei; Ding, Cun-Bao; Peng, Zong-Gen; Zhao, Li-Xun; Song, Dan-Qing; Jiang, Jian-Dong

2013-01-01

The lack of small animal models for hepatitis C virus has impeded the discovery and development of anti-HCV drugs. HCV-IRES plays an important role in HCV gene expression, and is an attractive target for antiviral therapy. In this study, we report a zebrafish model with a biscistron expression construct that can co-transcribe GFP and HCV-core genes by human hepatic lipase promoter and zebrafish liver fatty acid binding protein enhancer. HCV core translation was designed mediated by HCV-IRES sequence and gfp was by a canonical cap-dependent mechanism. Results of fluorescence image and in situ hybridization indicate that expression of HCV core and GFP is liver-specific; RT-PCR and Western blotting show that both core and gfp expression are elevated in a time-dependent manner for both transcription and translation. It means that the HCV-IRES exerted its role in this zebrafish model. Furthermore, the liver-pathological impact associated with HCV-infection was detected by examination of gene markers and some of them were elevated, such as adiponectin receptor, heparanase, TGF-β, PDGF-α, etc. The model was used to evaluate three clinical drugs, ribavirin, IFNα-2b and vitamin B12. The results show that vitamin B12 inhibited core expression in mRNA and protein levels in dose-dependent manner, but failed to impact gfp expression. Also VB12 down-regulated some gene transcriptions involved in fat liver, liver fibrosis and HCV-associated pathological process in the larvae. It reveals that HCV-IRES responds to vitamin B12 sensitively in the zebrafish model. Ribavirin did not disturb core expression, hinting that HCV-IRES is not a target site of ribavirin. IFNα-2b was not active, which maybe resulted from its degradation in vivo for the long time. These findings demonstrate the feasibility of the zebrafish model for screening of anti-HCV drugs targeting to HCV-IRES. The zebrafish system provides a novel evidence of using zebrafish as a HCV model organism. PMID:23469178

GENE-Counter: A Computational Pipeline for the Analysis of RNA-Seq Data for Gene Expression Differences

PubMed Central

Di, Yanming; Schafer, Daniel W.; Wilhelm, Larry J.; Fox, Samuel E.; Sullivan, Christopher M.; Curzon, Aron D.; Carrington, James C.; Mockler, Todd C.; Chang, Jeff H.

2011-01-01

GENE-counter is a complete Perl-based computational pipeline for analyzing RNA-Sequencing (RNA-Seq) data for differential gene expression. In addition to its use in studying transcriptomes of eukaryotic model organisms, GENE-counter is applicable for prokaryotes and non-model organisms without an available genome reference sequence. For alignments, GENE-counter is configured for CASHX, Bowtie, and BWA, but an end user can use any Sequence Alignment/Map (SAM)-compliant program of preference. To analyze data for differential gene expression, GENE-counter can be run with any one of three statistics packages that are based on variations of the negative binomial distribution. The default method is a new and simple statistical test we developed based on an over-parameterized version of the negative binomial distribution. GENE-counter also includes three different methods for assessing differentially expressed features for enriched gene ontology (GO) terms. Results are transparent and data are systematically stored in a MySQL relational database to facilitate additional analyses as well as quality assessment. We used next generation sequencing to generate a small-scale RNA-Seq dataset derived from the heavily studied defense response of Arabidopsis thaliana and used GENE-counter to process the data. Collectively, the support from analysis of microarrays as well as the observed and substantial overlap in results from each of the three statistics packages demonstrates that GENE-counter is well suited for handling the unique characteristics of small sample sizes and high variability in gene counts. PMID:21998647

Arabidopsis Gene Family Profiler (aGFP)--user-oriented transcriptomic database with easy-to-use graphic interface.

PubMed

Dupl'áková, Nikoleta; Renák, David; Hovanec, Patrik; Honysová, Barbora; Twell, David; Honys, David

2007-07-23

Microarray technologies now belong to the standard functional genomics toolbox and have undergone massive development leading to increased genome coverage, accuracy and reliability. The number of experiments exploiting microarray technology has markedly increased in recent years. In parallel with the rapid accumulation of transcriptomic data, on-line analysis tools are being introduced to simplify their use. Global statistical data analysis methods contribute to the development of overall concepts about gene expression patterns and to query and compose working hypotheses. More recently, these applications are being supplemented with more specialized products offering visualization and specific data mining tools. We present a curated gene family-oriented gene expression database, Arabidopsis Gene Family Profiler (aGFP; http://agfp.ueb.cas.cz), which gives the user access to a large collection of normalised Affymetrix ATH1 microarray datasets. The database currently contains NASC Array and AtGenExpress transcriptomic datasets for various tissues at different developmental stages of wild type plants gathered from nearly 350 gene chips. The Arabidopsis GFP database has been designed as an easy-to-use tool for users needing an easily accessible resource for expression data of single genes, pre-defined gene families or custom gene sets, with the further possibility of keyword search. Arabidopsis Gene Family Profiler presents a user-friendly web interface using both graphic and text output. Data are stored at the MySQL server and individual queries are created in PHP script. The most distinguishable features of Arabidopsis Gene Family Profiler database are: 1) the presentation of normalized datasets (Affymetrix MAS algorithm and calculation of model-based gene-expression values based on the Perfect Match-only model); 2) the choice between two different normalization algorithms (Affymetrix MAS4 or MAS5 algorithms); 3) an intuitive interface; 4) an interactive "virtual plant" visualizing the spatial and developmental expression profiles of both gene families and individual genes. Arabidopsis GFP gives users the possibility to analyze current Arabidopsis developmental transcriptomic data starting with simple global queries that can be expanded and further refined to visualize comparative and highly selective gene expression profiles.

Identification of human circadian genes based on time course gene expression profiles by using a deep learning method.

PubMed

Cui, Peng; Zhong, Tingyan; Wang, Zhuo; Wang, Tao; Zhao, Hongyu; Liu, Chenglin; Lu, Hui

2018-06-01

Circadian genes express periodically in an approximate 24-h period and the identification and study of these genes can provide deep understanding of the circadian control which plays significant roles in human health. Although many circadian gene identification algorithms have been developed, large numbers of false positives and low coverage are still major problems in this field. In this study we constructed a novel computational framework for circadian gene identification using deep neural networks (DNN) - a deep learning algorithm which can represent the raw form of data patterns without imposing assumptions on the expression distribution. Firstly, we transformed time-course gene expression data into categorical-state data to denote the changing trend of gene expression. Two distinct expression patterns emerged after clustering of the state data for circadian genes from our manually created learning dataset. DNN was then applied to discriminate the aperiodic genes and the two subtypes of periodic genes. In order to assess the performance of DNN, four commonly used machine learning methods including k-nearest neighbors, logistic regression, naïve Bayes, and support vector machines were used for comparison. The results show that the DNN model achieves the best balanced precision and recall. Next, we conducted large scale circadian gene detection using the trained DNN model for the remaining transcription profiles. Comparing with JTK_CYCLE and a study performed by Möller-Levet et al. (doi: https://doi.org/10.1073/pnas.1217154110), we identified 1132 novel periodic genes. Through the functional analysis of these novel circadian genes, we found that the GTPase superfamily exhibits distinct circadian expression patterns and may provide a molecular switch of circadian control of the functioning of the immune system in human blood. Our study provides novel insights into both the circadian gene identification field and the study of complex circadian-driven biological control. This article is part of a Special Issue entitled: Accelerating Precision Medicine through Genetic and Genomic Big Data Analysis edited by Yudong Cai & Tao Huang. Copyright © 2017. Published by Elsevier B.V.

Doxycycline affects gene expression profiles in aortic tissues in a rat model of vascular calcification.

PubMed

Lu, Hailin; Jiang, Wenhong; Yang, Han; Qin, Zhong; Guo, Si-En; Hu, Ming; Qin, Xiao

2017-11-01

Vitamin D 3 -induced vascular calcification (VC) in rats shares many phenotypical similarities with calcification occurring in human atherosclerosis, diabetes mellitus and chronic kidney disease, thereby it is a reliable model for identifying chemopreventive agents. Doxycycline has been shown to effectively attenuated VC. This study aimed to explore the effects of doxycycline on gene expression profiles in VC rats. The model of VC in rats was established by subcutaneous injection of vitamin D3 for 3days. Doxycycline at 120mgkg -1 day -1 was given via subcutaneous injection for 14days. Rat pathological changes, calcium deposition and calcium content in aortic tissues were measured by Hematoxylin-eosin, von Kossa staining and colorimetry, respectively. The gene change profile of aortic tissues after doxycycline treatment was assessed by Gene Microarray analysis using the Agilent Whole Rat Genome Oligo Microarray. The results showed that doxycycline significantly decreased the deposition of calcium, reduced the relative calcification area and alleviated pathological injury in aortic tissues. In addition, doxycycline treatment altered 88 gene expressions compared with untreated VD group. Of these, 61 genes were down-regulated and 27 genes were up-regulated. The functions of differentially expressed (DE) genes were involved in neutrophil chemotaxis, chronic inflammatory response, negative regulation of apoptotic process, cellular response to mechanical stimulus and immune response, etc. In conclusions, this study might provide the potential novel insights into the molecular mechanisms of doxycycline on VC. Copyright © 2017. Published by Elsevier Inc.

Gene expression analysis predicts insect venom anaphylaxis in indolent systemic mastocytosis.

PubMed

Niedoszytko, M; Bruinenberg, M; van Doormaal, J J; de Monchy, J G R; Nedoszytko, B; Koppelman, G H; Nawijn, M C; Wijmenga, C; Jassem, E; Elberink, J N G Oude

2011-05-01

Anaphylaxis to insect venom (Hymenoptera) is most severe in patients with mastocytosis and may even lead to death. However, not all patients with mastocytosis suffer from anaphylaxis. The aim of the study was to analyze differences in gene expression between patients with indolent systemic mastocytosis (ISM) and a history of insect venom anaphylaxis (IVA) compared to those patients without a history of anaphylaxis, and to determine the predictive use of gene expression profiling. Whole-genome gene expression analysis was performed in peripheral blood cells. Twenty-two adults with ISM were included: 12 with a history of IVA and 10 without a history of anaphylaxis of any kind. Significant differences in single gene expression corrected for multiple testing were found for 104 transcripts (P < 0.05). Gene ontology analysis revealed that the differentially expressed genes were involved in pathways responsible for the development of cancer and focal and cell adhesion suggesting that the expression of genes related to the differentiation state of cells is higher in patients with a history of anaphylaxis. Based on the gene expression profiles, a naïve Bayes prediction model was built identifying patients with IVA. In ISM, gene expression profiles are different between patients with a history of IVA and those without. These findings might reflect a more pronounced mast cells dysfunction in patients without a history of anaphylaxis. Gene expression profiling might be a useful tool to predict the risk of anaphylaxis on insect venom in patients with ISM. Prospective studies are needed to substantiate any conclusions. © 2010 John Wiley & Sons A/S.

Impact of Cigarette Smoke on the Human and Mouse Lungs: A Gene-Expression Comparison Study

PubMed Central

Morissette, Mathieu C.; Lamontagne, Maxime; Bérubé, Jean-Christophe; Gaschler, Gordon; Williams, Andrew; Yauk, Carole; Couture, Christian; Laviolette, Michel; Hogg, James C.; Timens, Wim; Halappanavar, Sabina; Stampfli, Martin R.; Bossé, Yohan

2014-01-01

Cigarette smoke is well known for its adverse effects on human health, especially on the lungs. Basic research is essential to identify the mechanisms involved in the development of cigarette smoke-related diseases, but translation of new findings from pre-clinical models to the clinic remains difficult. In the present study, we aimed at comparing the gene expression signature between the lungs of human smokers and mice exposed to cigarette smoke to identify the similarities and differences. Using human and mouse whole-genome gene expression arrays, changes in gene expression, signaling pathways and biological functions were assessed. We found that genes significantly modulated by cigarette smoke in humans were enriched for genes modulated by cigarette smoke in mice, suggesting a similar response of both species. Sixteen smoking-induced genes were in common between humans and mice including six newly reported to be modulated by cigarette smoke. In addition, we identified a new conserved pulmonary response to cigarette smoke in the induction of phospholipid metabolism/degradation pathways. Finally, the majority of biological functions modulated by cigarette smoke in humans were also affected in mice. Altogether, the present study provides information on similarities and differences in lung gene expression response to cigarette smoke that exist between human and mouse. Our results foster the idea that animal models should be used to study the involvement of pathways rather than single genes in human diseases. PMID:24663285

Stability-driven nonnegative matrix factorization to interpret spatial gene expression and build local gene networks.

PubMed

Wu, Siqi; Joseph, Antony; Hammonds, Ann S; Celniker, Susan E; Yu, Bin; Frise, Erwin

2016-04-19

Spatial gene expression patterns enable the detection of local covariability and are extremely useful for identifying local gene interactions during normal development. The abundance of spatial expression data in recent years has led to the modeling and analysis of regulatory networks. The inherent complexity of such data makes it a challenge to extract biological information. We developed staNMF, a method that combines a scalable implementation of nonnegative matrix factorization (NMF) with a new stability-driven model selection criterion. When applied to a set ofDrosophilaearly embryonic spatial gene expression images, one of the largest datasets of its kind, staNMF identified 21 principal patterns (PP). Providing a compact yet biologically interpretable representation ofDrosophilaexpression patterns, PP are comparable to a fate map generated experimentally by laser ablation and show exceptional promise as a data-driven alternative to manual annotations. Our analysis mapped genes to cell-fate programs and assigned putative biological roles to uncharacterized genes. Finally, we used the PP to generate local transcription factor regulatory networks. Spatially local correlation networks were constructed for six PP that span along the embryonic anterior-posterior axis. Using a two-tail 5% cutoff on correlation, we reproduced 10 of the 11 links in the well-studied gap gene network. The performance of PP with theDrosophiladata suggests that staNMF provides informative decompositions and constitutes a useful computational lens through which to extract biological insight from complex and often noisy gene expression data.

Transgenic over-expression of YY1 induces pathologic cardiac hypertrophy in a sex-specific manner

PubMed Central

Stauffer, Brian L.; Dockstader, Karen; Russell, Gloria; Hijmans, Jamie; Walker, Lisa; Cecil, Mackenzie; Demos-Davies, Kimberly; Medway, Allen; McKinsey, Timothy A.; Sucharov, Carmen C.

2015-01-01

YY1 can activate or repress transcription of various genes. In cardiac myocytes in culture YY1 has been shown to regulate expression of several genes involved in myocyte pathology. YY1 can also acutely protect the heart against detrimental changes in gene expression. In this study we show that cardiac over-expression of YY1 induces pathologic cardiac hypertrophy in male mice, measured by changes in gene expression and lower ejection fraction/fractional shortening. In contrast, female animals are protected against pathologic gene expression changes and cardiac dysfunction. Furthermore, we show that YY1 regulates, in a sex-specific manner, the expression of mammalian enable (Mena), a factor that regulates cytoskeletal actin dynamics and whose expression is increased in several models of cardiac pathology, and that Mena expression in humans with heart failure is sex-dependent. Finally, we show that sex differences in YY1 expression are also observed in human heart failure. In summary, this is the first work to show that YY1 has a sex-specific effect in the regulation of cardiac pathology. PMID:25935483

Beta-Poisson model for single-cell RNA-seq data analyses.

PubMed

Vu, Trung Nghia; Wills, Quin F; Kalari, Krishna R; Niu, Nifang; Wang, Liewei; Rantalainen, Mattias; Pawitan, Yudi

2016-07-15

Single-cell RNA-sequencing technology allows detection of gene expression at the single-cell level. One typical feature of the data is a bimodality in the cellular distribution even for highly expressed genes, primarily caused by a proportion of non-expressing cells. The standard and the over-dispersed gamma-Poisson models that are commonly used in bulk-cell RNA-sequencing are not able to capture this property. We introduce a beta-Poisson mixture model that can capture the bimodality of the single-cell gene expression distribution. We further integrate the model into the generalized linear model framework in order to perform differential expression analyses. The whole analytical procedure is called BPSC. The results from several real single-cell RNA-seq datasets indicate that ∼90% of the transcripts are well characterized by the beta-Poisson model; the model-fit from BPSC is better than the fit of the standard gamma-Poisson model in > 80% of the transcripts. Moreover, in differential expression analyses of simulated and real datasets, BPSC performs well against edgeR, a conventional method widely used in bulk-cell RNA-sequencing data, and against scde and MAST, two recent methods specifically designed for single-cell RNA-seq data. An R package BPSC for model fitting and differential expression analyses of single-cell RNA-seq data is available under GPL-3 license at https://github.com/nghiavtr/BPSC CONTACT: yudi.pawitan@ki.se or mattias.rantalainen@ki.se Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Integrating machine learning techniques into robust data enrichment approach and its application to gene expression data.

PubMed

Erdoğdu, Utku; Tan, Mehmet; Alhajj, Reda; Polat, Faruk; Rokne, Jon; Demetrick, Douglas

2013-01-01

The availability of enough samples for effective analysis and knowledge discovery has been a challenge in the research community, especially in the area of gene expression data analysis. Thus, the approaches being developed for data analysis have mostly suffered from the lack of enough data to train and test the constructed models. We argue that the process of sample generation could be successfully automated by employing some sophisticated machine learning techniques. An automated sample generation framework could successfully complement the actual sample generation from real cases. This argument is validated in this paper by describing a framework that integrates multiple models (perspectives) for sample generation. We illustrate its applicability for producing new gene expression data samples, a highly demanding area that has not received attention. The three perspectives employed in the process are based on models that are not closely related. The independence eliminates the bias of having the produced approach covering only certain characteristics of the domain and leading to samples skewed towards one direction. The first model is based on the Probabilistic Boolean Network (PBN) representation of the gene regulatory network underlying the given gene expression data. The second model integrates Hierarchical Markov Model (HIMM) and the third model employs a genetic algorithm in the process. Each model learns as much as possible characteristics of the domain being analysed and tries to incorporate the learned characteristics in generating new samples. In other words, the models base their analysis on domain knowledge implicitly present in the data itself. The developed framework has been extensively tested by checking how the new samples complement the original samples. The produced results are very promising in showing the effectiveness, usefulness and applicability of the proposed multi-model framework.

Effects of an Antimutagenic 1,4-Dihydropyridine AV-153 on Expression of Nitric Oxide Synthases and DNA Repair-related Enzymes and Genes in Kidneys of Rats with a Streptozotocin Model of Diabetes Mellitus.

PubMed

Ošiņa, Kristīne; Rostoka, Evita; Isajevs, Sergejs; Sokolovska, Jelizaveta; Sjakste, Tatjana; Sjakste, Nikolajs

2016-11-01

Development of complications of diabetes mellitus (DM), including diabetic nephropathy, is a complex multi-stage process, dependent on many factors including the modification of nitric oxide (NO) production and an impaired DNA repair. The goal of this work was to study in vivo effects of 1,4-dihydropyridine AV-153, known as antimutagen and DNA binder, on the expression of several genes and proteins involved in NO metabolism and DNA repair in the kidneys of rats with a streptozotocin (STZ)-induced model of DM. Transcription intensity was monitored by means of real-time RT-PCR and the expression of proteins by immunohistochemistry. Development of DM significantly induced PARP1 protein expression, while AV-153 (0.5 mg/kg) administration decreased it. AV-153 increased the expression of Parp1 gene in the kidneys of both intact and diabetic animals. Expression of H2afx mRNA and γH2AX histone protein, a marker of DNA breakage, was not changed in diabetic animals, but AV-153 up-regulated the expression of the gene without any impact on the protein expression. Development of DM was followed by a significant increase in iNOS enzyme expression, while AV-153 down-regulated the enzyme expression up to normal levels. iNos gene expression was also found to be increased in diabetic animals, but unlike the protein, the expression of mRNA was found to be enhanced by AV-153 administration. Expression of both eNOS protein and eNos gene in the kidneys was down-regulated, and the administration of AV-153 normalized the expression level. The effects of the compound in the kidneys of diabetic animals appear to be beneficial, as a trend for the normalization of expression of NO synthases is observed. © 2016 Nordic Association for the Publication of BCPT (former Nordic Pharmacological Society).

Identification of pathogenic genes related to rheumatoid arthritis through integrated analysis of DNA methylation and gene expression profiling.

PubMed

Zhang, Lei; Ma, Shiyun; Wang, Huailiang; Su, Hang; Su, Ke; Li, Longjie

2017-11-15

The purpose of our study was to identify new pathogenic genes used for exploring the pathogenesis of rheumatoid arthritis (RA). To screen pathogenic genes of RA, an integrated analysis was performed by using the microarray datasets in RA derived from the Gene Expression Omnibus (GEO) database. The functional annotation and potential pathways of differentially expressed genes (DEGs) were further discovered by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Afterwards, the integrated analysis of DNA methylation and gene expression profiling was used to screen crucial genes. In addition, we used RT-PCR and MSP to verify the expression levels and methylation status of these crucial genes in 20 synovial biopsy samples obtained from 10 RA model mice and 10 normal mice. BCL11B, CCDC88C, FCRLA and APOL6 were both up-regulated and hypomethylated in RA according to integrated analysis, RT-PCR and MSP verification. Four crucial genes (BCL11B, CCDC88C, FCRLA and APOL6) identified and analyzed in this study might be closely connected with the pathogenesis of RA. Copyright © 2017. Published by Elsevier B.V.

Differential gene expression induced by exposure of captive mink to fuel oil: A model for the sea otter

USGS Publications Warehouse

Bowen, Lizabeth; Riva, F.; Mohr, C.; Aldridge, B.; Schwartz, J.; Miles, A. Keith; Stott, J.L.

2007-01-01

Free-ranging sea otters are subject to hydrocarbon exposure from a variety of sources, both natural and anthropogenic. Effects of direct exposure to unrefined crude oil, such as that associated with the Exxon Valdez oil spill, are readily apparent. However, the impact of subtle but pathophysiologically relevant concentrations of crude oil on sea otters is difficult to assess. The present study was directed at developing a model for assessing the impact of low concentrations of fuel oil on sea otters. Quantitative PCR was used to identify differential gene expression in American mink that were exposed to low concentrations of bunker C fuel oil. A total of 23 genes, representing 10 different physiological systems, were analyzed for perturbation. Six genes with immunological relevance were differentially expressed in oil-fed mink. Interleukin-18 (IL-18), IL-10, inducible nitric oxide synthase (iNOS), cyclooxygenase 2 (COX-2), and complement cytolysis inhibitor (CLI) were down-regulated while IL-2 was up-regulated. Expression of two additional genes was affected; heat shock protein 70 (HSP70) was up-regulated and thyroid hormone receptor (THR) was down-regulated. While the significance of each perturbation is not immediately evident, we identified differential expression of genes that would be consistent with the presence of immune system-modifying and endocrine-disrupting compounds in fuel oil. Application of this approach to identify effects of petroleum contamination on sea otters should be possible following expansion of this mink model to identify a greater number of affected genes in peripheral blood leukocytes.

An incoherent feedforward loop facilitates adaptive tuning of gene expression.

PubMed

Hong, Jungeui; Brandt, Nathan; Abdul-Rahman, Farah; Yang, Ally; Hughes, Tim; Gresham, David

2018-04-05

We studied adaptive evolution of gene expression using long-term experimental evolution of Saccharomyces cerevisiae in ammonium-limited chemostats. We found repeated selection for non-synonymous variation in the DNA binding domain of the transcriptional activator, GAT1, which functions with the repressor, DAL80 in an incoherent type-1 feedforward loop (I1-FFL) to control expression of the high affinity ammonium transporter gene, MEP2. Missense mutations in the DNA binding domain of GAT1 reduce its binding to the GATAA consensus sequence. However, we show experimentally, and using mathematical modeling, that decreases in GAT1 binding result in increased expression of MEP2 as a consequence of properties of I1-FFLs. Our results show that I1-FFLs, one of the most commonly occurring network motifs in transcriptional networks, can facilitate adaptive tuning of gene expression through modulation of transcription factor binding affinities. Our findings highlight the importance of gene regulatory architectures in the evolution of gene expression. © 2018, Hong et al.

Functional redundancy and/or ongoing pseudogenization among F-box protein genes expressed in Arabidopsis male gametophyte.

PubMed

Ikram, Sobia; Durandet, Monique; Vesa, Simona; Pereira, Serge; Guerche, Philippe; Bonhomme, Sandrine

2014-06-01

F-box protein genes family is one of the largest gene families in plants, with almost 700 predicted genes in the model plant Arabidopsis. F-box proteins are key components of the ubiquitin proteasome system that allows targeted protein degradation. Transcriptome analyses indicate that half of these F-box protein genes are found expressed in microspore and/or pollen, i.e., during male gametogenesis. To assess the role of F-box protein genes during this crucial developmental step, we selected 34 F-box protein genes recorded as highly and specifically expressed in pollen and isolated corresponding insertion mutants. We checked the expression level of each selected gene by RT-PCR and confirmed pollen expression for 25 genes, but specific expression for only 10 of the 34 F-box protein genes. In addition, we tested the expression level of selected F-box protein genes in 24 mutant lines and showed that 11 of them were null mutants. Transmission analysis of the mutations to the progeny showed that none of the single mutations was gametophytic lethal. These unaffected transmission efficiencies suggested leaky mutations or functional redundancy among F-box protein genes. Cytological observation of the gametophytes in the mutants confirmed these results. Combinations of mutations in F-box protein genes from the same subfamily did not lead to transmission defect either, further highlighting functional redundancy and/or a high proportion of pseudogenes among these F-box protein genes.

Transcriptomic Analysis in a Drosophila Model Identifies Previously Implicated and Novel Pathways in the Therapeutic Mechanism in Neuropsychiatric Disorders

PubMed Central

Singh, Priyanka; Mohammad, Farhan; Sharma, Abhay

2011-01-01

We have taken advantage of a newly described Drosophila model to gain insights into the potential mechanism of antiepileptic drugs (AEDs), a group of drugs that are widely used in the treatment of several neurological and psychiatric conditions besides epilepsy. In the recently described Drosophila model that is inspired by pentylenetetrazole (PTZ) induced kindling epileptogenesis in rodents, chronic PTZ treatment for 7 days causes a decreased climbing speed and an altered CNS transcriptome, with the latter mimicking gene expression alterations reported in epileptogenesis. In the model, an increased climbing speed is further observed 7 days after withdrawal from chronic PTZ. We used this post-PTZ withdrawal regime to identify potential AED mechanism. In this regime, treatment with each of the five AEDs tested, namely, ethosuximide, gabapentin, vigabatrin, sodium valproate, and levetiracetam, resulted in rescuing of the altered climbing behavior. The AEDs also normalized PTZ withdrawal induced transcriptomic perturbation in fly heads; whereas AED untreated flies showed a large number of up- and down-regulated genes which were enriched in several processes including gene expression and cell communication, the AED treated flies showed differential expression of only a small number of genes that did not enrich gene expression and cell communication processes. Gene expression and cell communication related upregulated genes in AED untreated flies overrepresented several pathways – spliceosome, RNA degradation, and ribosome in the former category, and inositol phosphate metabolism, phosphatidylinositol signaling, endocytosis, and hedgehog signaling in the latter. Transcriptome remodeling effect of AEDs was overall confirmed by microarray clustering that clearly separated the profiles of AED treated and untreated flies. Besides being consistent with previously implicated pathways, our results provide evidence for a role of other pathways in psychiatric drug mechanism. Overall, we provide an amenable model to understand neuropsychiatric mechanism in cellular and molecular terms. PMID:21503142

Gene Expression Profiling in Rodent Models for Schizophrenia

PubMed Central

Schijndel, Jessica E. Van; Martens, Gerard J.M

2010-01-01

The complex neurodevelopmental disorder schizophrenia is thought to be induced by an interaction between predisposing genes and environmental stressors. In order to get a better insight into the aetiology of this complex disorder, animal models have been developed. In this review, we summarize mRNA expression profiling studies on neurodevelopmental, pharmacological and genetic animal models for schizophrenia. We discuss parallels and contradictions among these studies, and propose strategies for future research. PMID:21629445

Complex Expression of the Cellulolytic Transcriptome of Saccharophagus degradans † ▿

PubMed Central

Zhang, Haitao; Hutcheson, Steven W.

2011-01-01

Saccharophagus degradans is an aerobic marine bacterium that can degrade cellulose by the induced expression of an unusual cellulolytic system composed of multiple endoglucanases and glucosidases. To understand the regulation of the cellulolytic system, transcript levels for the genes predicted to contribute to the cellulolytic system were monitored by quantitative real-time PCR (qRT-PCR) during the transition to growth on cellulose. Four glucanases of the cellulolytic system exhibited basal expression during growth on glucose. All but one of the predicted cellulolytic system genes were induced strongly during growth on Avicel, with three patterns of expression observed. One group showed increased expression (up to 6-fold) within 4 h of the nutritional shift, with the relative expression remaining constant over the next 22 h. A second group of genes was strongly induced between 4 and 10 h after nutritional transfer, with relative expression declining thereafter. The third group of genes was slowly induced and was expressed maximally after 24 h. Cellodextrins and cellobiose, products of the predicted basally expressed endoglucanases, stimulated expression of representative cellulase genes. A model is proposed by which the activity of basally expressed endoglucanases releases cellodextrins from Avicel that are then perceived and transduced to initiate transcription of each of the regulated cellulolytic system genes forming an expression pattern. PMID:21705539

Expression analysis of some genes regulated by retinoic acid in controls and triadimefon-exposed embryos: is the amphibian Xenopus laevis a suitable model for gene-based comparative teratology?

PubMed

Di Renzo, Francesca; Rossi, Federica; Bacchetta, Renato; Prati, Mariangela; Giavini, Erminio; Menegola, Elena

2011-06-01

The use of nonmammal models in teratological studies is a matter of debate and seems to be justified if the embryotoxic mechanism involves conserved processes. Published data on mammals and Xenopus laevis suggest that azoles are teratogenic by altering the endogenous concentration of retinoic acid (RA). The expression of some genes (Shh, Ptch-1, Gsc, and Msx2) controlled by retinoic acid is downregulated in rat embryos exposed at the phylotypic stage to the triazole triadimefon (FON). In order to propose X. laevis as a model for gene-based comparative teratology, this work evaluates the expression of Shh, Ptch-1, Gsc, and Msx2 in FON-exposed X. laevis embryos. Embryos, exposed to a high concentration level (500 µM) of FON from stage 13 till 17, were examined at stages 17, 27, and 47. Stage 17 and 27 embryos were processed to perform quantitative RT-PCR. The developmental rate was never affected by FON at any considered stage. FON-exposed stage 47 larvae showed the typical craniofacial malformations. A significant downregulation of Gsc was observed in FON-exposed stage 17 embryos. Shh, Ptch-1, Msx2 showed a high fluctuation of expression both in control and in FON-exposed samples both at stages 17 and 27. The downregulation of Gsc mimics the effects of FON on rat embryos, showing for this gene a common effect of FON in the two vertebrate classes. The high fluctuation observed in the gene expression of the other genes, however, suggests that X. laevis at this stage has limited utility for gene-based comparative teratology. © 2011 Wiley-Liss, Inc.

RNA-Seq analysis and annotation of a draft blueberry genome assembly identifies candidate genes involved in fruit ripening, biosynthesis of bioactive compounds, and stage-specific alternative splicing.

PubMed

Gupta, Vikas; Estrada, April D; Blakley, Ivory; Reid, Rob; Patel, Ketan; Meyer, Mason D; Andersen, Stig Uggerhøj; Brown, Allan F; Lila, Mary Ann; Loraine, Ann E

2015-01-01

Blueberries are a rich source of antioxidants and other beneficial compounds that can protect against disease. Identifying genes involved in synthesis of bioactive compounds could enable the breeding of berry varieties with enhanced health benefits. Toward this end, we annotated a previously sequenced draft blueberry genome assembly using RNA-Seq data from five stages of berry fruit development and ripening. Genome-guided assembly of RNA-Seq read alignments combined with output from ab initio gene finders produced around 60,000 gene models, of which more than half were similar to proteins from other species, typically the grape Vitis vinifera. Comparison of gene models to the PlantCyc database of metabolic pathway enzymes identified candidate genes involved in synthesis of bioactive compounds, including bixin, an apocarotenoid with potential disease-fighting properties, and defense-related cyanogenic glycosides, which are toxic. Cyanogenic glycoside (CG) biosynthetic enzymes were highly expressed in green fruit, and a candidate CG detoxification enzyme was up-regulated during fruit ripening. Candidate genes for ethylene, anthocyanin, and 400 other biosynthetic pathways were also identified. Homology-based annotation using Blast2GO and InterPro assigned Gene Ontology terms to around 15,000 genes. RNA-Seq expression profiling showed that blueberry growth, maturation, and ripening involve dynamic gene expression changes, including coordinated up- and down-regulation of metabolic pathway enzymes and transcriptional regulators. Analysis of RNA-seq alignments identified developmentally regulated alternative splicing, promoter use, and 3' end formation. We report genome sequence, gene models, functional annotations, and RNA-Seq expression data that provide an important new resource enabling high throughput studies in blueberry.

Adult mouse brain gene expression patterns bear an embryologic imprint

PubMed Central

Zapala, Matthew A.; Hovatta, Iiris; Ellison, Julie A.; Wodicka, Lisa; Del Rio, Jo A.; Tennant, Richard; Tynan, Wendy; Broide, Ron S.; Helton, Rob; Stoveken, Barbara S.; Winrow, Christopher; Lockhart, Daniel J.; Reilly, John F.; Young, Warren G.; Bloom, Floyd E.; Lockhart, David J.; Barlow, Carrolee

2005-01-01

The current model to explain the organization of the mammalian nervous system is based on studies of anatomy, embryology, and evolution. To further investigate the molecular organization of the adult mammalian brain, we have built a gene expression-based brain map. We measured gene expression patterns for 24 neural tissues covering the mouse central nervous system and found, surprisingly, that the adult brain bears a transcriptional “imprint” consistent with both embryological origins and classic evolutionary relationships. Embryonic cellular position along the anterior–posterior axis of the neural tube was shown to be closely associated with, and possibly a determinant of, the gene expression patterns in adult structures. We also observed a significant number of embryonic patterning and homeobox genes with region-specific expression in the adult nervous system. The relationships between global expression patterns for different anatomical regions and the nature of the observed region-specific genes suggest that the adult brain retains a degree of overall gene expression established during embryogenesis that is important for regional specificity and the functional relationships between regions in the adult. The complete collection of extensively annotated gene expression data along with data mining and visualization tools have been made available on a publicly accessible web site (www.barlow-lockhart-brainmapnimhgrant.org). PMID:16002470

Smad1 and WIF1 genes are downregulated during saccular stage of lung development in the nitrofen rat model.

PubMed

Fujiwara, Naho; Doi, Takashi; Gosemann, Jan-Hendrik; Kutasy, Balazs; Friedmacher, Florian; Puri, Prem

2012-02-01

The exact pathogenesis of pulmonary hypoplasia in the nitrofen-induced congenital diaphragmatic hernia (CDH) still remains unclear. Smad1, one of the bone morphogenesis protein (BMP) receptor downstream signaling proteins, plays a key role in organogenesis including lung development and maturation. Smad1 knockout mice display reduced sacculation, an important feature of pulmonary hypoplasia. Wnt inhibitor factor 1 (Wif1) is a target gene of Smad1 in the developing lung epithelial cells (LECs). Smad1 directly regulates Wif1 gene expression and blockade of Smad1 function in fetal LECs is reported to downregulate Wif1 gene expression. We designed this study to test the hypothesis that pulmonary Smad1 and Wif1 gene expression is downregulated during saccular stage of lung development in the nitrofen CDH model. Pregnant rats were exposed to either olive oil or nitrofen on day 9 of gestation (D9). Fetuses were harvested on D18, and D21. Fetal lungs were dissected and divided into 2 groups: control and nitrofen (n = 9 at each time point, respectively). Pulmonary gene expression of Smad1 and Wif1 were analyzed by real-time RT-PCR. Immunohistochemistry was performed to evaluate protein expression/distribution of Smad1 and Wif1. The relative mRNA expression levels of Smad1 and Wif1 were significantly downregulated in the nitrofen group compared to controls on D18 and D21 (*p < 0.01, **p < 0.05). Immunoreactivity of Smad1 and Wif1 was also markedly decreased in nitrofen lungs compared to controls on D18 and D21. We provide evidence, for the first time, that the pulmonary gene expression of Smad1 and Wif1 is downregulated on D18 and D21 (saccular stage of lung development) in the nitrofen-induced hypoplastic lung. These findings suggest that the downregulation of Smad1/Wif1 gene expression may contribute to pulmonary hypoplasia in the nitrofen CDH model by retardation of lung development during saccular stage.

Exercise differentially affects metabolic functions and white adipose tissue in female letrozole- and dihydrotestosterone-induced mouse models of polycystic ovary syndrome.

PubMed

Marcondes, Rodrigo R; Maliqueo, Manuel; Fornes, Romina; Benrick, Anna; Hu, Min; Ivarsson, Niklas; Carlström, Mattias; Cushman, Samuel W; Stenkula, Karin G; Maciel, Gustavo A R; Stener-Victorin, Elisabet

2017-06-15

Here we hypothesized that exercise in dihydrotestosterone (DHT) or letrozole (LET)-induced polycystic ovary syndrome mouse models improves impaired insulin and glucose metabolism, adipose tissue morphology, and expression of genes related to adipogenesis, lipid metabolism, Notch pathway and browning in inguinal and mesenteric fat. DHT-exposed mice had increased body weight, increased number of large mesenteric adipocytes. LET-exposed mice displayed increased body weight and fat mass, decreased insulin sensitivity, increased frequency of small adipocytes and increased expression of genes related to lipolysis in mesenteric fat. In both models, exercise decreased fat mass and inguinal and mesenteric adipose tissue expression of Notch pathway genes, and restored altered mesenteric adipocytes morphology. In conclusion, exercise restored mesenteric adipocytes morphology in DHT- and LET-exposed mice, and insulin sensitivity and mesenteric expression of lipolysis-related genes in LET-exposed mice. Benefits could be explained by downregulation of Notch, and modulation of browning and lipolysis pathways in the adipose tissue. Copyright © 2017 Elsevier B.V. All rights reserved.

Expression analysis in a rat psychosis model identifies novel candidate genes validated in a large case–control sample of schizophrenia

PubMed Central

Ingason, A; Giegling, I; Hartmann, A M; Genius, J; Konte, B; Friedl, M; Ripke, S; Sullivan, P F; St. Clair, D; Collier, D A; O'Donovan, M C; Mirnics, K; Rujescu, D

2015-01-01

Antagonists of the N-methyl-D-aspartate (NMDA)-type glutamate receptor induce psychosis in healthy individuals and exacerbate schizophrenia symptoms in patients. In this study we have produced an animal model of NMDA receptor hypofunction by chronically treating rats with low doses of the NMDA receptor antagonist MK-801. Subsequently, we performed an expression study and identified 20 genes showing altered expression in the brain of these rats compared with untreated animals. We then explored whether the human orthologs of these genes are associated with schizophrenia in the largest schizophrenia genome-wide association study published to date, and found evidence for association for 4 out of the 20 genes: SF3B1, FOXP1, DLG2 and VGLL4. Interestingly, three of these genes, FOXP1, SF3B1 and DLG2, have previously been implicated in neurodevelopmental disorders. PMID:26460480

In Vivo Gene Therapy of Hemophilia B: Sustained Partial Correction in Factor IX-Deficient Dogs

NASA Astrophysics Data System (ADS)

Kay, Mark A.; Rothenberg, Steven; Landen, Charles N.; Bellinger, Dwight A.; Leland, Frances; Toman, Carol; Finegold, Milton; Thompson, Arthur R.; Read, M. S.; Brinkhous, Kenneth M.; Woo, Savio L. C.

1993-10-01

The liver represents a model organ for gene therapy. A method has been developed for hepatic gene transfer in vivo by the direct infusion of recombinant retroviral vectors into the portal vasculature, which results in the persistent expression of exogenous genes. To determine if these technologies are applicable for the treatment of hemophilia B patients, preclinical efficacy studies were done in a hemophilia B dog model. When the canine factor IX complementary DNA was transduced directly into the hepatocytes of affected dogs in vivo, the animals constitutively expressed low levels of canine factor IX for more than 5 months. Persistent expression of the clotting. factor resulted in reductions of whole blood clotting and partial thromboplastin times of the treated animals. Thus, long-term treatment of hemophilia B patients may be feasible by direct hepatic gene therapy in vivo.

Expression analysis in a rat psychosis model identifies novel candidate genes validated in a large case-control sample of schizophrenia.

PubMed

Ingason, A; Giegling, I; Hartmann, A M; Genius, J; Konte, B; Friedl, M; Ripke, S; Sullivan, P F; St Clair, D; Collier, D A; O'Donovan, M C; Mirnics, K; Rujescu, D

2015-10-13

Antagonists of the N-methyl-D-aspartate (NMDA)-type glutamate receptor induce psychosis in healthy individuals and exacerbate schizophrenia symptoms in patients. In this study we have produced an animal model of NMDA receptor hypofunction by chronically treating rats with low doses of the NMDA receptor antagonist MK-801. Subsequently, we performed an expression study and identified 20 genes showing altered expression in the brain of these rats compared with untreated animals. We then explored whether the human orthologs of these genes are associated with schizophrenia in the largest schizophrenia genome-wide association study published to date, and found evidence for association for 4 out of the 20 genes: SF3B1, FOXP1, DLG2 and VGLL4. Interestingly, three of these genes, FOXP1, SF3B1 and DLG2, have previously been implicated in neurodevelopmental disorders.

Histone Modifications around Individual BDNF Gene Promoters in Prefrontal Cortex Are Associated with Extinction of Conditioned Fear

ERIC Educational Resources Information Center

Bredy, Timothy W.; Wu, Hao; Crego, Cortney; Zellhoefer, Jessica; Sun, Yi E.; Barad, Mark

2007-01-01

Extinction of conditioned fear is an important model both of inhibitory learning and of behavior therapy for human anxiety disorders. Like other forms of learning, extinction learning is long-lasting and depends on regulated gene expression. Epigenetic mechanisms make an important contribution to persistent changes in gene expression; therefore,…

In silico selection of expression reference genes with demonstrated stability in barley among a diverse set of tissues and cultivars

USDA-ARS?s Scientific Manuscript database

Premise of the study: Reference genes are selected based on the assumption of temporal and spatial expression stability and on their widespread use in model species. They are often used in new target species without validation, presumed as stable. For barley, reference gene validation is lacking, bu...

Reference gene identification for reliable normalisation of quantitative RT-PCR data in Setaria viridis.

PubMed

Nguyen, Duc Quan; Eamens, Andrew L; Grof, Christopher P L

2018-01-01

Quantitative real-time polymerase chain reaction (RT-qPCR) is the key platform for the quantitative analysis of gene expression in a wide range of experimental systems and conditions. However, the accuracy and reproducibility of gene expression quantification via RT-qPCR is entirely dependent on the identification of reliable reference genes for data normalisation. Green foxtail ( Setaria viridis ) has recently been proposed as a potential experimental model for the study of C 4 photosynthesis and is closely related to many economically important crop species of the Panicoideae subfamily of grasses, including Zea mays (maize), Sorghum bicolor (sorghum) and Sacchurum officinarum (sugarcane). Setaria viridis (Accession 10) possesses a number of key traits as an experimental model, namely; (i) a small sized, sequenced and well annotated genome; (ii) short stature and generation time; (iii) prolific seed production, and; (iv) is amendable to Agrobacterium tumefaciens -mediated transformation. There is currently however, a lack of reference gene expression information for Setaria viridis ( S. viridis ). We therefore aimed to identify a cohort of suitable S. viridis reference genes for accurate and reliable normalisation of S. viridis RT-qPCR expression data. Eleven putative candidate reference genes were identified and examined across thirteen different S. viridis tissues. Of these, the geNorm and NormFinder analysis software identified SERINE / THERONINE - PROTEIN PHOSPHATASE 2A ( PP2A ), 5 '- ADENYLYLSULFATE REDUCTASE 6 ( ASPR6 ) and DUAL SPECIFICITY PHOSPHATASE ( DUSP ) as the most suitable combination of reference genes for the accurate and reliable normalisation of S. viridis RT-qPCR expression data. To demonstrate the suitability of the three selected reference genes, PP2A , ASPR6 and DUSP , were used to normalise the expression of CINNAMYL ALCOHOL DEHYDROGENASE ( CAD ) genes across the same tissues. This approach readily demonstrated the suitably of the three selected reference genes for the accurate and reliable normalisation of S. viridis RT-qPCR expression data. Further, the work reported here forms a highly useful platform for future gene expression quantification in S. viridis and can also be potentially directly translatable to other closely related and agronomically important C 4 crop species.

Bioinformatics approaches for cross-species liver cancer analysis based on microarray gene expression profiling

PubMed Central

Fang, H; Tong, W; Perkins, R; Shi, L; Hong, H; Cao, X; Xie, Q; Yim, SH; Ward, JM; Pitot, HC; Dragan, YP

2005-01-01

Background The completion of the sequencing of human, mouse and rat genomes and knowledge of cross-species gene homologies enables studies of differential gene expression in animal models. These types of studies have the potential to greatly enhance our understanding of diseases such as liver cancer in humans. Genes co-expressed across multiple species are most likely to have conserved functions. We have used various bioinformatics approaches to examine microarray expression profiles from liver neoplasms that arise in albumin-SV40 transgenic rats to elucidate genes, chromosome aberrations and pathways that might be associated with human liver cancer. Results In this study, we first identified 2223 differentially expressed genes by comparing gene expression profiles for two control, two adenoma and two carcinoma samples using an F-test. These genes were subsequently mapped to the rat chromosomes using a novel visualization tool, the Chromosome Plot. Using the same plot, we further mapped the significant genes to orthologous chromosomal locations in human and mouse. Many genes expressed in rat 1q that are amplified in rat liver cancer map to the human chromosomes 10, 11 and 19 and to the mouse chromosomes 7, 17 and 19, which have been implicated in studies of human and mouse liver cancer. Using Comparative Genomics Microarray Analysis (CGMA), we identified regions of potential aberrations in human. Lastly, a pathway analysis was conducted to predict altered human pathways based on statistical analysis and extrapolation from the rat data. All of the identified pathways have been known to be important in the etiology of human liver cancer, including cell cycle control, cell growth and differentiation, apoptosis, transcriptional regulation, and protein metabolism. Conclusion The study demonstrates that the hepatic gene expression profiles from the albumin-SV40 transgenic rat model revealed genes, pathways and chromosome alterations consistent with experimental and clinical research in human liver cancer. The bioinformatics tools presented in this paper are essential for cross species extrapolation and mapping of microarray data, its analysis and interpretation. PMID:16026603

dbMDEGA: a database for meta-analysis of differentially expressed genes in autism spectrum disorder.

PubMed

Zhang, Shuyun; Deng, Libin; Jia, Qiyue; Huang, Shaoting; Gu, Junwang; Zhou, Fankun; Gao, Meng; Sun, Xinyi; Feng, Chang; Fan, Guangqin

2017-11-16

Autism spectrum disorders (ASD) are hereditary, heterogeneous and biologically complex neurodevelopmental disorders. Individual studies on gene expression in ASD cannot provide clear consensus conclusions. Therefore, a systematic review to synthesize the current findings from brain tissues and a search tool to share the meta-analysis results are urgently needed. Here, we conducted a meta-analysis of brain gene expression profiles in the current reported human ASD expression datasets (with 84 frozen male cortex samples, 17 female cortex samples, 32 cerebellum samples and 4 formalin fixed samples) and knock-out mouse ASD model expression datasets (with 80 collective brain samples). Then, we applied R language software and developed an interactive shared and updated database (dbMDEGA) displaying the results of meta-analysis of data from ASD studies regarding differentially expressed genes (DEGs) in the brain. This database, dbMDEGA ( https://dbmdega.shinyapps.io/dbMDEGA/ ), is a publicly available web-portal for manual annotation and visualization of DEGs in the brain from data from ASD studies. This database uniquely presents meta-analysis values and homologous forest plots of DEGs in brain tissues. Gene entries are annotated with meta-values, statistical values and forest plots of DEGs in brain samples. This database aims to provide searchable meta-analysis results based on the current reported brain gene expression datasets of ASD to help detect candidate genes underlying this disorder. This new analytical tool may provide valuable assistance in the discovery of DEGs and the elucidation of the molecular pathogenicity of ASD. This database model may be replicated to study other disorders.

Reconstruction of the regulatory network for Bacillus subtilis and reconciliation with gene expression data

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

Faria, Jose P.; Overbeek, Ross; Taylor, Ronald C.

Here, we introduce a manually constructed and curated regulatory network model that describes the current state of knowledge of transcriptional regulation of B. subtilis. The model corresponds to an updated and enlarged version of the regulatory model of central metabolism originally proposed in 2008. We extended the original network to the whole genome by integration of information from DBTBS, a compendium of regulatory data that includes promoters, transcription factors (TFs), binding sites, motifs and regulated operons. Additionally, we consolidated our network with all the information on regulation included in the SporeWeb and Subtiwiki community-curated resources on B. subtilis. Finally, wemore » reconciled our network with data from RegPrecise, which recently released their own less comprehensive reconstruction of the regulatory network for B. subtilis. Our model describes 275 regulators and their target genes, representing 30 different mechanisms of regulation such as TFs, RNA switches, Riboswitches and small regulatory RNAs. Overall, regulatory information is included in the model for approximately 2500 of the ~4200 genes in B. subtilis 168. In an effort to further expand our knowledge of B. subtilis regulation, we reconciled our model with expression data. For this process, we reconstructed the Atomic Regulons (ARs) for B. subtilis, which are the sets of genes that share the same “ON” and “OFF” gene expression profiles across multiple samples of experimental data. We show how atomic regulons for B. subtilis are able to capture many sets of genes corresponding to regulated operons in our manually curated network. Additionally, we demonstrate how atomic regulons can be used to help expand or validate the knowledge of the regulatory networks by looking at highly correlated genes in the ARs for which regulatory information is lacking. During this process, we were also able to infer novel stimuli for hypothetical genes by exploring the genome expression metadata relating to experimental conditions, gaining insights into novel biology.« less

Reconstruction of the regulatory network for Bacillus subtilis and reconciliation with gene expression data

DOE PAGES

Faria, Jose P.; Overbeek, Ross; Taylor, Ronald C.; ...

2016-03-18

Here, we introduce a manually constructed and curated regulatory network model that describes the current state of knowledge of transcriptional regulation of B. subtilis. The model corresponds to an updated and enlarged version of the regulatory model of central metabolism originally proposed in 2008. We extended the original network to the whole genome by integration of information from DBTBS, a compendium of regulatory data that includes promoters, transcription factors (TFs), binding sites, motifs and regulated operons. Additionally, we consolidated our network with all the information on regulation included in the SporeWeb and Subtiwiki community-curated resources on B. subtilis. Finally, wemore » reconciled our network with data from RegPrecise, which recently released their own less comprehensive reconstruction of the regulatory network for B. subtilis. Our model describes 275 regulators and their target genes, representing 30 different mechanisms of regulation such as TFs, RNA switches, Riboswitches and small regulatory RNAs. Overall, regulatory information is included in the model for approximately 2500 of the ~4200 genes in B. subtilis 168. In an effort to further expand our knowledge of B. subtilis regulation, we reconciled our model with expression data. For this process, we reconstructed the Atomic Regulons (ARs) for B. subtilis, which are the sets of genes that share the same “ON” and “OFF” gene expression profiles across multiple samples of experimental data. We show how atomic regulons for B. subtilis are able to capture many sets of genes corresponding to regulated operons in our manually curated network. Additionally, we demonstrate how atomic regulons can be used to help expand or validate the knowledge of the regulatory networks by looking at highly correlated genes in the ARs for which regulatory information is lacking. During this process, we were also able to infer novel stimuli for hypothetical genes by exploring the genome expression metadata relating to experimental conditions, gaining insights into novel biology.« less

Transcriptional Changes in the Transition from Vegetative Cells to Asexual Development in the Model Fungus Aspergillus nidulans

PubMed Central

Garzia, Aitor; Etxebeste, Oier; Rodríguez-Romero, Julio; Fischer, Reinhard; Espeso, Eduardo A.

2013-01-01

Morphogenesis encompasses programmed changes in gene expression that lead to the development of specialized cell types. In the model fungus Aspergillus nidulans, asexual development involves the formation of characteristic cell types, collectively known as the conidiophore. With the aim of determining the transcriptional changes that occur upon induction of asexual development, we have applied massive mRNA sequencing to compare the expression pattern of 19-h-old submerged vegetative cells (hyphae) with that of similar hyphae after exposure to the air for 5 h. We found that the expression of 2,222 (20.3%) of the predicted 10,943 A. nidulans transcripts was significantly modified after air exposure, 2,035 being downregulated and 187 upregulated. The activation during this transition of genes that belong specifically to the asexual developmental pathway was confirmed. Another remarkable quantitative change occurred in the expression of genes involved in carbon or nitrogen primary metabolism. Genes participating in polar growth or sexual development were transcriptionally repressed, as were those belonging to the HogA/SakA stress response mitogen-activated protein (MAP) kinase pathway. We also identified significant expression changes in several genes purportedly involved in redox balance, transmembrane transport, secondary metabolite production, or transcriptional regulation, mainly binuclear-zinc cluster transcription factors. Genes coding for these four activities were usually grouped in metabolic clusters, which may bring regulatory implications for the induction of asexual development. These results provide a blueprint for further stage-specific gene expression studies during conidiophore development. PMID:23264642

Identification of Reference Genes and Analysis of Heat Shock Protein Gene Expression in Lingzhi or Reishi Medicinal Mushroom, Ganoderma lucidum, after Exposure to Heat Stress.

PubMed

Liu, Yong-Nan; Lu, Xiao-Xiao; Ren, Ang; Shi, Liang; Jiang, Ai-Liang; Yu, Han-Shou; Zhao, Ming-Wen

2017-01-01

Ganoderma lucidum has been considered an emerging model species for studying how environmental factors regulate the growth, development, and secondary metabolism of Basidiomycetes. Heat stress, which is one of the most important environmental abiotic stresses, seriously affects the growth, development, and yield of microorganisms. Understanding the response to heat stress has gradually become a hotspot in microorganism research. But suitable reference genes for expression analysis under heat stress have not been reported in G. lucidum. In this study, we systematically identified 11 candidate reference genes that were measured using reverse transcriptase quantitative polymerase chain reaction, and the gene expression stability was analyzed under heat stress conditions using geNorm and NormFinder. The results show that 5 reference genes-CYP and TIF, followed by UCE2, ACTIN, and UBQ1-are the most stable genes under our experimental conditions. Moreover, the relative expression levels of 3 heat stress response genes (hsp17.4, hsp70, and hsp90) were analyzed under heat stress conditions with different normalization strategies. The results show that use of a gene with unstable expression (SAND) as the reference gene leads to biased data and misinterpretations of the target gene expression level under heat stress.

Arabidopsis gene expression patterns during spaceflight

NASA Astrophysics Data System (ADS)

Paul, A.-L.; Ferl, R. J.

The exposure of Arabidopsis thaliana (Arabidopsis) plants to spaceflight environments resulted in the differential expression of hundreds of genes. A 5 day mission on orbiter Columbia in 1999 (STS-93) carried transgenic Arabidopsis plants engineered with a transgene composed of the alcohol dehydrogenase (Adh) gene promoter linked to the β -Glucuronidase (GUS) reporter gene. The plants were used to evaluate the effects of spaceflight on two fronts. First, expression patterns visualized with the Adh/GUS transgene were used to address specifically the possibility that spaceflight induces a hypoxic stress response, and to assess whether any spaceflight response was similar to control terrestrial hypoxia-induced gene expression patterns. (Paul et al., Plant Physiol. 2001, 126:613). Second, genome-wide patterns of native gene expression were evaluated utilizing the Affymetrix ATH1 GeneChip? array of 8,000 Arabidopsis genes. As a control for the veracity of the array analyses, a selection of genes identified with the arrays was further characterized with quantitative Real-Time RT PCR (ABI - TaqmanTM). Comparison of the patterns of expression for arrays of hybridized with RNA isolated from plants exposed to spaceflight compared to the control arrays revealed hundreds of genes that were differentially expressed in response to spaceflight, yet most genes that are hallmarks of hypoxic stress were unaffected. These results will be discussed in light of current models for plant responses to the spaceflight environment, and with regard to potential future flight opportunities.

A transcriptome-wide association study of 229,000 women identifies new candidate susceptibility genes for breast cancer.

PubMed

Wu, Lang; Shi, Wei; Long, Jirong; Guo, Xingyi; Michailidou, Kyriaki; Beesley, Jonathan; Bolla, Manjeet K; Shu, Xiao-Ou; Lu, Yingchang; Cai, Qiuyin; Al-Ejeh, Fares; Rozali, Esdy; Wang, Qin; Dennis, Joe; Li, Bingshan; Zeng, Chenjie; Feng, Helian; Gusev, Alexander; Barfield, Richard T; Andrulis, Irene L; Anton-Culver, Hoda; Arndt, Volker; Aronson, Kristan J; Auer, Paul L; Barrdahl, Myrto; Baynes, Caroline; Beckmann, Matthias W; Benitez, Javier; Bermisheva, Marina; Blomqvist, Carl; Bogdanova, Natalia V; Bojesen, Stig E; Brauch, Hiltrud; Brenner, Hermann; Brinton, Louise; Broberg, Per; Brucker, Sara Y; Burwinkel, Barbara; Caldés, Trinidad; Canzian, Federico; Carter, Brian D; Castelao, J Esteban; Chang-Claude, Jenny; Chen, Xiaoqing; Cheng, Ting-Yuan David; Christiansen, Hans; Clarke, Christine L; Collée, Margriet; Cornelissen, Sten; Couch, Fergus J; Cox, David; Cox, Angela; Cross, Simon S; Cunningham, Julie M; Czene, Kamila; Daly, Mary B; Devilee, Peter; Doheny, Kimberly F; Dörk, Thilo; Dos-Santos-Silva, Isabel; Dumont, Martine; Dwek, Miriam; Eccles, Diana M; Eilber, Ursula; Eliassen, A Heather; Engel, Christoph; Eriksson, Mikael; Fachal, Laura; Fasching, Peter A; Figueroa, Jonine; Flesch-Janys, Dieter; Fletcher, Olivia; Flyger, Henrik; Fritschi, Lin; Gabrielson, Marike; Gago-Dominguez, Manuela; Gapstur, Susan M; García-Closas, Montserrat; Gaudet, Mia M; Ghoussaini, Maya; Giles, Graham G; Goldberg, Mark S; Goldgar, David E; González-Neira, Anna; Guénel, Pascal; Hahnen, Eric; Haiman, Christopher A; Håkansson, Niclas; Hall, Per; Hallberg, Emily; Hamann, Ute; Harrington, Patricia; Hein, Alexander; Hicks, Belynda; Hillemanns, Peter; Hollestelle, Antoinette; Hoover, Robert N; Hopper, John L; Huang, Guanmengqian; Humphreys, Keith; Hunter, David J; Jakubowska, Anna; Janni, Wolfgang; John, Esther M; Johnson, Nichola; Jones, Kristine; Jones, Michael E; Jung, Audrey; Kaaks, Rudolf; Kerin, Michael J; Khusnutdinova, Elza; Kosma, Veli-Matti; Kristensen, Vessela N; Lambrechts, Diether; Le Marchand, Loic; Li, Jingmei; Lindström, Sara; Lissowska, Jolanta; Lo, Wing-Yee; Loibl, Sibylle; Lubinski, Jan; Luccarini, Craig; Lux, Michael P; MacInnis, Robert J; Maishman, Tom; Kostovska, Ivana Maleva; Mannermaa, Arto; Manson, JoAnn E; Margolin, Sara; Mavroudis, Dimitrios; Meijers-Heijboer, Hanne; Meindl, Alfons; Menon, Usha; Meyer, Jeffery; Mulligan, Anna Marie; Neuhausen, Susan L; Nevanlinna, Heli; Neven, Patrick; Nielsen, Sune F; Nordestgaard, Børge G; Olopade, Olufunmilayo I; Olson, Janet E; Olsson, Håkan; Peterlongo, Paolo; Peto, Julian; Plaseska-Karanfilska, Dijana; Prentice, Ross; Presneau, Nadege; Pylkäs, Katri; Rack, Brigitte; Radice, Paolo; Rahman, Nazneen; Rennert, Gad; Rennert, Hedy S; Rhenius, Valerie; Romero, Atocha; Romm, Jane; Rudolph, Anja; Saloustros, Emmanouil; Sandler, Dale P; Sawyer, Elinor J; Schmidt, Marjanka K; Schmutzler, Rita K; Schneeweiss, Andreas; Scott, Rodney J; Scott, Christopher G; Seal, Sheila; Shah, Mitul; Shrubsole, Martha J; Smeets, Ann; Southey, Melissa C; Spinelli, John J; Stone, Jennifer; Surowy, Harald; Swerdlow, Anthony J; Tamimi, Rulla M; Tapper, William; Taylor, Jack A; Terry, Mary Beth; Tessier, Daniel C; Thomas, Abigail; Thöne, Kathrin; Tollenaar, Rob A E M; Torres, Diana; Truong, Thérèse; Untch, Michael; Vachon, Celine; Van Den Berg, David; Vincent, Daniel; Waisfisz, Quinten; Weinberg, Clarice R; Wendt, Camilla; Whittemore, Alice S; Wildiers, Hans; Willett, Walter C; Winqvist, Robert; Wolk, Alicja; Xia, Lucy; Yang, Xiaohong R; Ziogas, Argyrios; Ziv, Elad; Dunning, Alison M; Pharoah, Paul D P; Simard, Jacques; Milne, Roger L; Edwards, Stacey L; Kraft, Peter; Easton, Douglas F; Chenevix-Trench, Georgia; Zheng, Wei

2018-06-18

The breast cancer risk variants identified in genome-wide association studies explain only a small fraction of the familial relative risk, and the genes responsible for these associations remain largely unknown. To identify novel risk loci and likely causal genes, we performed a transcriptome-wide association study evaluating associations of genetically predicted gene expression with breast cancer risk in 122,977 cases and 105,974 controls of European ancestry. We used data from the Genotype-Tissue Expression Project to establish genetic models to predict gene expression in breast tissue and evaluated model performance using data from The Cancer Genome Atlas. Of the 8,597 genes evaluated, significant associations were identified for 48 at a Bonferroni-corrected threshold of P < 5.82 × 10 -6 , including 14 genes at loci not yet reported for breast cancer. We silenced 13 genes and showed an effect for 11 on cell proliferation and/or colony-forming efficiency. Our study provides new insights into breast cancer genetics and biology.

Functional categorization of gene expression changes in the cerebellum of a Cln3-knockout mouse model for Batten disease.

PubMed

Brooks, Andrew I; Chattopadhyay, Subrata; Mitchison, Hannah M; Nussbaum, Robert L; Pearce, David A

2003-01-01

Juvenile neuronal ceroid lipofuscinosis (JNCL or Batten Disease) is the most common progressive neurodegenerative disorder of childhood. The disease is inherited in an autosomal recessive manner and is the result of mutations in the CLN3 gene. One brain region severely affected in Batten disease is the cerebellum. Using a mouse model for Batten disease which shares pathological similarities to the disease in humans we have used oligonucleotide arrays to profile approximately 19000 mRNAs in the cerebellum. We have identified reproducible changes of twofold or more in the expression of 756 gene products in the cerebellum of 10-week-old Cln3-knockout mice as compared to wild-type controls. We have subsequently divided these genes with altered expression into 14 functional categories. We report a significant alteration in expression of genes associated with neurotransmission, neuronal cell structure and development, immune response and inflammation, and lipid metabolism. An apparent shift in metabolism toward gluconeogenesis is also evident in Cln3-knockout mice. Further experimentation will be necessary to understand the contribution of these changes in expression to a disease state. Detailed analysis of the functional consequences of altered expression of genes in the cerebellum of the Cln3-knockout mice may provide valuable clues in understanding the molecular basis of the pathological mechanisms underlying Batten disease.

Blood expression profiles of fragile X premutation carriers identify candidate genes involved in neurodegenerative and infertility phenotypes.

PubMed

Mateu-Huertas, Elisabet; Rodriguez-Revenga, Laia; Alvarez-Mora, Maria Isabel; Madrigal, Irene; Willemsen, Rob; Milà, Montserrat; Martí, Eulàlia; Estivill, Xavier

2014-05-01

Male premutation carriers presenting between 55 and 200 CGG repeats in the Fragile-X-associated (FMR1) gene are at risk of developing Fragile X Tremor/Ataxia Syndrome (FXTAS), and females undergo Premature Ovarian Failure (POF1). Here, we have evaluated gene expression profiles from blood in male FMR1 premutation carriers and detected a strong deregulation of genes enriched in FXTAS relevant biological pathways, including inflammation, neuronal homeostasis and viability. Gene expression profiling distinguished between control individuals, carriers with FXTAS and carriers without FXTAS, with levels of expanded FMR1 mRNA being increased in FXTAS patients. In vitro studies in a neuronal cell model indicate that expression levels of expanded FMR1 5'-UTR are relevant in modulating the transcriptome. Thus, perturbations of the transcriptome may be an interplay between the CGG expansion size and FMR1 expression levels. Several deregulated genes (DFFA, BCL2L11, BCL2L1, APP, SOD1, RNF10, HDAC5, KCNC3, ATXN7, ATXN3 and EAP1) were validated in brain samples of a FXTAS mouse model. Downregulation of EAP1, a gene involved in the female reproductive system physiology, was confirmed in female carriers. Decreased levels were detected in female carriers with POF1 compared to those without POF1, suggesting that EAP1 levels contribute to ovarian insufficiency. In summary, gene expression profiling in blood has uncovered mechanisms that may underlie different pathological aspects of the premutation. A better understanding of the transcriptome dynamics in relation with expanded FMR1 mRNA expression levels and CGG expansion size may provide mechanistic insights into the disease process and a more accurate FXTAS diagnosis to the myriad of phenotypes associated with the premutation. Copyright © 2014. Published by Elsevier Inc.

Validation of the β-amy1 transcription profiling assay and selection of reference genes suited for a RT-qPCR assay in developing barley caryopsis.

PubMed

Ovesná, Jaroslava; Kučera, Ladislav; Vaculová, Kateřina; Štrymplová, Kamila; Svobodová, Ilona; Milella, Luigi

2012-01-01

Reverse transcription coupled with real-time quantitative PCR (RT-qPCR) is a frequently used method for gene expression profiling. Reference genes (RGs) are commonly employed to normalize gene expression data. A limited information exist on the gene expression and profiling in developing barley caryopsis. Expression stability was assessed by measuring the cycle threshold (Ct) range and applying both the GeNorm (pair-wise comparison of geometric means) and Normfinder (model-based approach) principles for the calculation. Here, we have identified a set of four RGs suitable for studying gene expression in the developing barley caryopsis. These encode the proteins GAPDH, HSP90, HSP70 and ubiquitin. We found a correlation between the frequency of occurrence of a transcript in silico and its suitability as an RG. This set of RGs was tested by comparing the normalized level of β-amylase (β-amy1) transcript with directly measured quantities of the BMY1 gene product in the developing barley caryopsis. This panel of genes could be used for other gene expression studies, as well as to optimize β-amy1 analysis for study of the impact of β-amy1 expression upon barley end-use quality.

Hidden among the crowd: differential DNA methylation-expression correlations in cancer occur at important oncogenic pathways.

PubMed

Mosquera Orgueira, Adrián

2015-01-01

DNA methylation is a frequent epigenetic mechanism that participates in transcriptional repression. Variations in DNA methylation with respect to gene expression are constant, and, for unknown reasons, some genes with highly methylated promoters are sometimes overexpressed. In this study we have analyzed the expression and methylation patterns of thousands of genes in five groups of cancer and normal tissue samples in order to determine local and genome-wide differences. We observed significant changes in global methylation-expression correlation in all the neoplasms, which suggests that differential correlation events are frequent in cancer. A focused analysis in the breast cancer cohort identified 1662 genes whose correlation varies significantly between normal and cancerous breast, but whose DNA methylation and gene expression patterns do not change substantially. These genes were enriched in cancer-related pathways and repressive chromatin features across various model cell lines, such as PRC2 binding and H3K27me3 marks. Substantial changes in methylation-expression correlation indicate that these genes are subject to epigenetic remodeling, where the differential activity of other factors break the expected relationship between both variables. Our findings suggest a complex regulatory landscape where a redistribution of local and large-scale chromatin repressive domains at differentially correlated genes (DCGs) creates epigenetic hotspots that modulate cancer-specific gene expression.

Targeting pancreatic expressed PAX genes for the treatment of diabetes mellitus and pancreatic neuroendocrine tumors.

PubMed

Martin-Montalvo, Alejandro; Lorenzo, Petra I; López-Noriega, Livia; Gauthier, Benoit R

2017-01-01

Four members of the PAX family, PAX2, PAX4, PAX6 and PAX8 are known to be expressed in the pancreas. Accumulated evidences indicate that several pancreatic expressed PAX genes play a significant role in pancreatic development/functionality and alterations in these genes are involved in the pathogenesis of pancreatic diseases. Areas covered: In this review, we summarize the ongoing research related to pancreatic PAX genes in diabetes mellitus and pancreatic neuroendocrine tumors. We dissect the current knowledge at different levels; from mechanistic studies in cell lines performed to understand the molecular processes controlled by pancreatic PAX genes, to in vivo studies using rodent models that over-express or lack specific PAX genes. Finally, we describe human studies associating variants on pancreatic-expressed PAX genes with pancreatic diseases. Expert opinion: Based on the current literature, we propose that future interventions to treat pancreatic neuroendocrine tumors and diabetes mellitus could be developed via the modulation of PAX4 and/or PAX6 regulated pathways.

From Saccharomyces cerevisiae to human: The important gene co-expression modules.

PubMed

Liu, Wei; Li, Li; Ye, Hua; Chen, Haiwei; Shen, Weibiao; Zhong, Yuexian; Tian, Tian; He, Huaqin

2017-08-01

Network-based systems biology has become an important method for analyzing high-throughput gene expression data and gene function mining. Yeast has long been a popular model organism for biomedical research. In the current study, a weighted gene co-expression network analysis algorithm was applied to construct a gene co-expression network in Saccharomyces cerevisiae . Seventeen stable gene co-expression modules were detected from 2,814 S. cerevisiae microarray data. Further characterization of these modules with the Database for Annotation, Visualization and Integrated Discovery tool indicated that these modules were associated with certain biological processes, such as heat response, cell cycle, translational regulation, mitochondrion oxidative phosphorylation, amino acid metabolism and autophagy. Hub genes were also screened by intra-modular connectivity. Finally, the module conservation was evaluated in a human disease microarray dataset. Functional modules were identified in budding yeast, some of which are associated with patient survival. The current study provided a paradigm for single cell microorganisms and potentially other organisms.

Mechanisms of gap gene expression canalization in the Drosophila blastoderm.

PubMed

Gursky, Vitaly V; Panok, Lena; Myasnikova, Ekaterina M; Manu; Samsonova, Maria G; Reinitz, John; Samsonov, Alexander M

2011-01-01

Extensive variation in early gap gene expression in the Drosophila blastoderm is reduced over time because of gap gene cross regulation. This phenomenon is a manifestation of canalization, the ability of an organism to produce a consistent phenotype despite variations in genotype or environment. The canalization of gap gene expression can be understood as arising from the actions of attractors in the gap gene dynamical system. In order to better understand the processes of developmental robustness and canalization in the early Drosophila embryo, we investigated the dynamical effects of varying spatial profiles of Bicoid protein concentration on the formation of the expression border of the gap gene hunchback. At several positions on the anterior-posterior axis of the embryo, we analyzed attractors and their basins of attraction in a dynamical model describing expression of four gap genes with the Bicoid concentration profile accounted as a given input in the model equations. This model was tested against a family of Bicoid gradients obtained from individual embryos. These gradients were normalized by two independent methods, which are based on distinct biological hypotheses and provide different magnitudes for Bicoid spatial variability. We showed how the border formation is dictated by the biological initial conditions (the concentration gradient of maternal Hunchback protein) being attracted to specific attracting sets in a local vicinity of the border. Different types of these attracting sets (point attractors or one dimensional attracting manifolds) define several possible mechanisms of border formation. The hunchback border formation is associated with intersection of the spatial gradient of the maternal Hunchback protein and a boundary between the attraction basins of two different point attractors. We demonstrated how the positional variability for hunchback is related to the corresponding variability of the basin boundaries. The observed reduction in variability of the hunchback gene expression can be accounted for by specific geometrical properties of the basin boundaries. We clarified the mechanisms of gap gene expression canalization in early Drosophila embryos. These mechanisms were specified in the case of hunchback in well defined terms of the dynamical system theory.

Noise-induced multistability in the regulation of cancer by genes and pseudogenes

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

Petrosyan, K. G., E-mail: pkaren@phys.sinica.edu.tw; Hu, Chin-Kun, E-mail: huck@phys.sinica.edu.tw; National Center for Theoretical Sciences, National Tsing Hua University, Hsinchu 30013, Taiwan

2016-07-28

We extend a previously introduced model of stochastic gene regulation of cancer to a nonlinear case having both gene and pseudogene messenger RNAs (mRNAs) self-regulated. The model consists of stochastic Boolean genetic elements and possesses noise-induced multistability (multimodality). We obtain analytical expressions for probabilities for the case of constant but finite number of microRNA molecules which act as a noise source for the competing gene and pseudogene mRNAs. The probability distribution functions display both the global bistability regime as well as even-odd number oscillations for a certain range of model parameters. Statistical characteristics of the mRNA’s level fluctuations are evaluated.more » The obtained results of the extended model advance our understanding of the process of stochastic gene and pseudogene expressions that is crucial in regulation of cancer.« less

UP-REGULATION OF IL-6, IL-8 AND CCL2 GENE EXPRESSION AFTER ACUTE INFLAMMATION: CORRELATION TO CLINICAL PAIN

PubMed Central

Wang, Xiao-Min; Hamza, May; Wu, Tai-Xia; Dionne, Raymond A.

2012-01-01

Tissue injury initiates a cascade of inflammatory mediators and hyperalgesic substances including prostaglandins, cytokines and chemokines. Using microarray and qRT-PCR gene expression analyses, the present study evaluated changes in gene expression of a cascade of cytokines following acute inflammation and the correlation between the changes in the gene expression level and pain intensity in the oral surgery clinical model of acute inflammation. Tissue injury resulted in a significant up-regulation in the gene expression of Interleukin-6 (IL-6; 63.3-fold), IL-8 (8.1-fold), chemokine (C-C motif) ligand 2 (CCL2; 8.9-fold), chemokine (C-X-C motif) ligand 1 (CXCL1; 30.5-fold), chemokine (C-X-C motif) ligand 2 (CXCL2; 26-fold) and annexin A1 (ANXA1; 12-fold). The up-regulation of IL-6 gene expression was significantly correlated to the up-regulation on the gene expression of IL-8, CCL2, CXCL1 and CXCL2. Interestingly, the tissue injury induced up-regulation of IL-6 gene expression, IL-8 and CCL2 were positively correlated to pain intensity at 3 hours post-surgery, the onset of acute inflammatory pain. However, ketorolac treatment did not have a significant effect on the gene expression of IL-6, IL-8, CCL2, CXCL2 and ANXA1 at the same time point of acute inflammation. These results demonstrate that up-regulation of IL-6, IL-8 and CCL2 gene expression contributes to the development of acute inflammation and inflammatory pain. The lack of effect for ketorolac on the expression of these gene products may be related to the ceiling analgesic effects of non-steroidal anti-inflammatory drugs. PMID:19233564

Quantitative structure-activity relationships studies of CCR5 inhibitors and toxicity of aromatic compounds using gene expression programming.

PubMed

Shi, Weimin; Zhang, Xiaoya; Shen, Qi

2010-01-01

Quantitative structure-activity relationship (QSAR) study of chemokine receptor 5 (CCR5) binding affinity of substituted 1-(3,3-diphenylpropyl)-piperidinyl amides and ureas and toxicity of aromatic compounds have been performed. The gene expression programming (GEP) was used to select variables and produce nonlinear QSAR models simultaneously using the selected variables. In our GEP implementation, a simple and convenient method was proposed to infer the K-expression from the number of arguments of the function in a gene, without building the expression tree. The results were compared to those obtained by artificial neural network (ANN) and support vector machine (SVM). It has been demonstrated that the GEP is a useful tool for QSAR modeling. Copyright 2009 Elsevier Masson SAS. All rights reserved.

Evaluation of in vitro spermatogenesis system effectiveness to study genes behavior: monitoring the expression of the testis specific 10 (Tsga10) gene as a model.

PubMed

Miryounesi, Mohammad; Nayernia, Karim; Mobasheri, Maryam Beigom; Dianatpour, Mahdi; Oko, Richard; Savad, Shahram; Modarressi, Mohammad Hossein

2014-10-01

In vitro generation of germ cells introduces a novel approach to male infertility and provides an effective system in gene tracking studies, however many aspects of this process have remained unclear. We aimed to promote mouse embryonic stem cells (mESC) differentiation into germ cells and evaluate its effectiveness with tracking the expression of the Tsga10 during this process. mESCs were differentiated into germ cells in the presence of Retinoic Acid. Based on developmental schedule of the postnatal testis, samples were taken on the 7th, 12th, and 25th days of the culture and were subjected to expression analysis of a panel of germ cell specific genes. Expression of Tsga10 in RNA and protein levels was then analyzed. Transition from mitosis to meiosis occurred between 7th and 12th days of mESC culture and post-meiotic gene expression did not occur until the 25th day of the culture. Results showed low level of Tsga10expression in undifferentiated stem cells. During transition from meiotic to post-meiotic phase, Tsga10 expression increased in 6.6 folds. This finding is in concordance with in vivo changes during transition from pre-pubertal to pubertal stage. Localization of processed and unprocessed forms of the related protein was similar to those in vivo as well. Expression pattern of Tsga10, as a gene with critical function in spermatogenesis, is similar during in vitro and in vivo germ cell generation. The results suggest that in vitro derived germ cells could be a trusted model to study genes behavior during spermatogenesis.

ICG: a wiki-driven knowledgebase of internal control genes for RT-qPCR normalization.

PubMed

Sang, Jian; Wang, Zhennan; Li, Man; Cao, Jiabao; Niu, Guangyi; Xia, Lin; Zou, Dong; Wang, Fan; Xu, Xingjian; Han, Xiaojiao; Fan, Jinqi; Yang, Ye; Zuo, Wanzhu; Zhang, Yang; Zhao, Wenming; Bao, Yiming; Xiao, Jingfa; Hu, Songnian; Hao, Lili; Zhang, Zhang

2018-01-04

Real-time quantitative PCR (RT-qPCR) has become a widely used method for accurate expression profiling of targeted mRNA and ncRNA. Selection of appropriate internal control genes for RT-qPCR normalization is an elementary prerequisite for reliable expression measurement. Here, we present ICG (http://icg.big.ac.cn), a wiki-driven knowledgebase for community curation of experimentally validated internal control genes as well as their associated experimental conditions. Unlike extant related databases that focus on qPCR primers in model organisms (mainly human and mouse), ICG features harnessing collective intelligence in community integration of internal control genes for a variety of species. Specifically, it integrates a comprehensive collection of more than 750 internal control genes for 73 animals, 115 plants, 12 fungi and 9 bacteria, and incorporates detailed information on recommended application scenarios corresponding to specific experimental conditions, which, collectively, are of great help for researchers to adopt appropriate internal control genes for their own experiments. Taken together, ICG serves as a publicly editable and open-content encyclopaedia of internal control genes and accordingly bears broad utility for reliable RT-qPCR normalization and gene expression characterization in both model and non-model organisms. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

A Systems' Biology Approach to Study MicroRNA-Mediated Gene Regulatory Networks

PubMed Central

Kunz, Manfred; Vera, Julio; Wolkenhauer, Olaf

2013-01-01

MicroRNAs (miRNAs) are potent effectors in gene regulatory networks where aberrant miRNA expression can contribute to human diseases such as cancer. For a better understanding of the regulatory role of miRNAs in coordinating gene expression, we here present a systems biology approach combining data-driven modeling and model-driven experiments. Such an approach is characterized by an iterative process, including biological data acquisition and integration, network construction, mathematical modeling and experimental validation. To demonstrate the application of this approach, we adopt it to investigate mechanisms of collective repression on p21 by multiple miRNAs. We first construct a p21 regulatory network based on data from the literature and further expand it using algorithms that predict molecular interactions. Based on the network structure, a detailed mechanistic model is established and its parameter values are determined using data. Finally, the calibrated model is used to study the effect of different miRNA expression profiles and cooperative target regulation on p21 expression levels in different biological contexts. PMID:24350286

Analysis of the Nicotiana tabacum Stigma/Style Transcriptome Reveals Gene Expression Differences between Wet and Dry Stigma Species1[W][OA

PubMed Central

Quiapim, Andréa C.; Brito, Michael S.; Bernardes, Luciano A.S.; daSilva, Idalete; Malavazi, Iran; DePaoli, Henrique C.; Molfetta-Machado, Jeanne B.; Giuliatti, Silvana; Goldman, Gustavo H.; Goldman, Maria Helena S.

2009-01-01

The success of plant reproduction depends on pollen-pistil interactions occurring at the stigma/style. These interactions vary depending on the stigma type: wet or dry. Tobacco (Nicotiana tabacum) represents a model of wet stigma, and its stigmas/styles express genes to accomplish the appropriate functions. For a large-scale study of gene expression during tobacco pistil development and preparation for pollination, we generated 11,216 high-quality expressed sequence tags (ESTs) from stigmas/styles and created the TOBEST database. These ESTs were assembled in 6,177 clusters, from which 52.1% are pistil transcripts/genes of unknown function. The 21 clusters with the highest number of ESTs (putative higher expression levels) correspond to genes associated with defense mechanisms or pollen-pistil interactions. The database analysis unraveled tobacco sequences homologous to the Arabidopsis (Arabidopsis thaliana) genes involved in specifying pistil identity or determining normal pistil morphology and function. Additionally, 782 independent clusters were examined by macroarray, revealing 46 stigma/style preferentially expressed genes. Real-time reverse transcription-polymerase chain reaction experiments validated the pistil-preferential expression for nine out of 10 genes tested. A search for these 46 genes in the Arabidopsis pistil data sets demonstrated that only 11 sequences, with putative equivalent molecular functions, are expressed in this dry stigma species. The reverse search for the Arabidopsis pistil genes in the TOBEST exposed a partial overlap between these dry and wet stigma transcriptomes. The TOBEST represents the most extensive survey of gene expression in the stigmas/styles of wet stigma plants, and our results indicate that wet and dry stigmas/styles express common as well as distinct genes in preparation for the pollination process. PMID:19052150

Comparative Genomics of Non-TNL Disease Resistance Genes from Six Plant Species.

PubMed

Nepal, Madhav P; Andersen, Ethan J; Neupane, Surendra; Benson, Benjamin V

2017-09-30

Disease resistance genes (R genes), as part of the plant defense system, have coevolved with corresponding pathogen molecules. The main objectives of this project were to identify non-Toll interleukin receptor, nucleotide-binding site, leucine-rich repeat (nTNL) genes and elucidate their evolutionary divergence across six plant genomes. Using reference sequences from Arabidopsis , we investigated nTNL orthologs in the genomes of common bean, Medicago , soybean, poplar, and rice. We used Hidden Markov Models for sequence identification, performed model-based phylogenetic analyses, visualized chromosomal positioning, inferred gene clustering, and assessed gene expression profiles. We analyzed 908 nTNL R genes in the genomes of the six plant species, and classified them into 12 subgroups based on the presence of coiled-coil (CC), nucleotide binding site (NBS), leucine rich repeat (LRR), resistance to Powdery mildew 8 (RPW8), and BED type zinc finger domains. Traditionally classified CC-NBS-LRR (CNL) genes were nested into four clades (CNL A-D) often with abundant, well-supported homogeneous subclades of Type-II R genes. CNL-D members were absent in rice, indicating a unique R gene retention pattern in the rice genome. Genomes from Arabidopsis , common bean, poplar and soybean had one chromosome without any CNL R genes. Medicago and Arabidopsis had the highest and lowest number of gene clusters, respectively. Gene expression analyses suggested unique patterns of expression for each of the CNL clades. Differential gene expression patterns of the nTNL genes were often found to correlate with number of introns and GC content, suggesting structural and functional divergence.

Comparative Genomics of Non-TNL Disease Resistance Genes from Six Plant Species

PubMed Central

Andersen, Ethan J.; Neupane, Surendra; Benson, Benjamin V.

2017-01-01

Disease resistance genes (R genes), as part of the plant defense system, have coevolved with corresponding pathogen molecules. The main objectives of this project were to identify non-Toll interleukin receptor, nucleotide-binding site, leucine-rich repeat (nTNL) genes and elucidate their evolutionary divergence across six plant genomes. Using reference sequences from Arabidopsis, we investigated nTNL orthologs in the genomes of common bean, Medicago, soybean, poplar, and rice. We used Hidden Markov Models for sequence identification, performed model-based phylogenetic analyses, visualized chromosomal positioning, inferred gene clustering, and assessed gene expression profiles. We analyzed 908 nTNL R genes in the genomes of the six plant species, and classified them into 12 subgroups based on the presence of coiled-coil (CC), nucleotide binding site (NBS), leucine rich repeat (LRR), resistance to Powdery mildew 8 (RPW8), and BED type zinc finger domains. Traditionally classified CC-NBS-LRR (CNL) genes were nested into four clades (CNL A-D) often with abundant, well-supported homogeneous subclades of Type-II R genes. CNL-D members were absent in rice, indicating a unique R gene retention pattern in the rice genome. Genomes from Arabidopsis, common bean, poplar and soybean had one chromosome without any CNL R genes. Medicago and Arabidopsis had the highest and lowest number of gene clusters, respectively. Gene expression analyses suggested unique patterns of expression for each of the CNL clades. Differential gene expression patterns of the nTNL genes were often found to correlate with number of introns and GC content, suggesting structural and functional divergence. PMID:28973974

Genetically engineered cardiac pacemaker: Stem cells transfected with HCN2 gene and myocytes—A model

NASA Astrophysics Data System (ADS)

Kanani, S.; Pumir, A.; Krinsky, V.

2008-01-01

One of the successfully tested methods to design genetically engineered cardiac pacemaker cells consists in transfecting a human mesenchymal stem cell (hMSC) with a HCN2 gene and connecting it to a myocyte. We develop and study a mathematical model, describing a myocyte connected to a hMSC transfected with a HCN2 gene. The cardiac action potential is described both with the simple Beeler Reuter model, as well as with the elaborate dynamic Luo Rudy model. The HCN2 channel is described by fitting electrophysiological records, in the spirit of Hodgkin Huxley. The model shows that oscillations can occur in a pair myocyte-stem cell, that was not observed in the experiments yet. The model predicted that: (1) HCN pacemaker channels can induce oscillations only if the number of expressed I channels is low enough. At too high an expression level of I channels, oscillations cannot be induced, no matter how many pacemaker channels are expressed. (2) At low expression levels of I channels, a large domain of values in the parameter space (n, N) exists, where oscillations should be observed. We denote N the number of expressed pacemaker channels in the stem cell, and n the number of gap junction channels coupling the stem cell and the myocyte. (3) The expression levels of I channels observed in ventricular myocytes, both in the Beeler Reuter and in the dynamic Luo Rudy models are too high to allow to observe oscillations. With expression levels below ˜1/4 of the original value, oscillations can be observed. The main consequence of this work is that in order to obtain oscillations in an experiment with a myocyte-stem cell pair, increasing the values of n, N is unlikely to be helpful, unless the expression level of I has been reduced enough. The model also allows us to explore levels of gene expression not yet achieved in experiments, and could be useful to plan new experiments, aimed at improving the robustness of the oscillations.

Distribution and regulation of stochasticity and plasticity in Saccharomyces cerevisiae

DOE PAGES

Dar, R. D.; Karig, D. K.; Cooke, J. F.; ...

2010-09-01

Stochasticity is an inherent feature of complex systems with nanoscale structure. In such systems information is represented by small collections of elements (e.g. a few electrons on a quantum dot), and small variations in the populations of these elements may lead to big uncertainties in the information. Unfortunately, little is known about how to work within this inherently noisy environment to design robust functionality into complex nanoscale systems. Here, we look to the biological cell as an intriguing model system where evolution has mediated the trade-offs between fluctuations and function, and in particular we look at the relationships and trade-offsmore » between stochastic and deterministic responses in the gene expression of budding yeast (Saccharomyces cerevisiae). We find gene regulatory arrangements that control the stochastic and deterministic components of expression, and show that genes that have evolved to respond to stimuli (stress) in the most strongly deterministic way exhibit the most noise in the absence of the stimuli. We show that this relationship is consistent with a bursty 2-state model of gene expression, and demonstrate that this regulatory motif generates the most uncertainty in gene expression when there is the greatest uncertainty in the optimal level of gene expression.« less

Characterization of stem cells and cancer cells on the basis of gene expression profile stability, plasticity, and robustness: dynamical systems theory of gene expressions under cell-cell interaction explains mutational robustness of differentiated cells and suggests how cancer cells emerge.

PubMed

Kaneko, Kunihiko

2011-06-01

Here I present and discuss a model that, among other things, appears able to describe the dynamics of cancer cell origin from the perspective of stable and unstable gene expression profiles. In identifying such aberrant gene expression profiles as lying outside the normal stable states attracted through development and normal cell differentiation, the hypothesis explains why cancer cells accumulate mutations, to which they are not robust, and why these mutations create a new stable state far from the normal gene expression profile space. Such cells are in strong contrast with normal cell types that appeared as an attractor state in the gene expression dynamical system under cell-cell interaction and achieved robustness to noise through evolution, which in turn also conferred robustness to mutation. In complex gene regulation networks, other aberrant cellular states lacking such high robustness are expected to remain, which would correspond to cancer cells. Copyright © 2011 WILEY Periodicals, Inc.

Systems biology definition of the core proteome of metabolism and expression is consistent with high-throughput data.

PubMed

Yang, Laurence; Tan, Justin; O'Brien, Edward J; Monk, Jonathan M; Kim, Donghyuk; Li, Howard J; Charusanti, Pep; Ebrahim, Ali; Lloyd, Colton J; Yurkovich, James T; Du, Bin; Dräger, Andreas; Thomas, Alex; Sun, Yuekai; Saunders, Michael A; Palsson, Bernhard O

2015-08-25

Finding the minimal set of gene functions needed to sustain life is of both fundamental and practical importance. Minimal gene lists have been proposed by using comparative genomics-based core proteome definitions. A definition of a core proteome that is supported by empirical data, is understood at the systems-level, and provides a basis for computing essential cell functions is lacking. Here, we use a systems biology-based genome-scale model of metabolism and expression to define a functional core proteome consisting of 356 gene products, accounting for 44% of the Escherichia coli proteome by mass based on proteomics data. This systems biology core proteome includes 212 genes not found in previous comparative genomics-based core proteome definitions, accounts for 65% of known essential genes in E. coli, and has 78% gene function overlap with minimal genomes (Buchnera aphidicola and Mycoplasma genitalium). Based on transcriptomics data across environmental and genetic backgrounds, the systems biology core proteome is significantly enriched in nondifferentially expressed genes and depleted in differentially expressed genes. Compared with the noncore, core gene expression levels are also similar across genetic backgrounds (two times higher Spearman rank correlation) and exhibit significantly more complex transcriptional and posttranscriptional regulatory features (40% more transcription start sites per gene, 22% longer 5'UTR). Thus, genome-scale systems biology approaches rigorously identify a functional core proteome needed to support growth. This framework, validated by using high-throughput datasets, facilitates a mechanistic understanding of systems-level core proteome function through in silico models; it de facto defines a paleome.

The anabolic/androgenic steroid nandrolone exacerbates gene expression modifications induced by mutant SOD1 in muscles of mice models of amyotrophic lateral sclerosis

PubMed Central

Galbiati, Mariarita; Onesto, Elisa; Zito, Arianna; Crippa, Valeria; Rusmini, Paola; Mariotti, Raffaella; Bentivoglio, Marina; Bendotti, Caterina; Poletti, Angelo

2012-01-01

Anabolic/androgenic steroids (AAS) are drugs that enhance muscle mass, and are often illegally utilized in athletes to improve their performances. Recent data suggest that the increased risk for amyotrophic lateral sclerosis (ALS) in male soccer and football players could be linked to AAS abuse. ALS is a motor neuron disease mainly occurring in sporadic (sALS) forms, but some familial forms (fALS) exist and have been linked to mutations in different genes. Some of these, in their wild type (wt) form, have been proposed as risk factors for sALS, i.e. superoxide dismutase 1 (SOD1) gene, whose mutations are causative of about 20% of fALS. Notably, SOD1 toxicity might occur both in motor neurons and in muscle cells. Using gastrocnemius muscles of mice overexpressing human mutant SOD1 (mutSOD1) at different disease stages, we found that the expression of a selected set of genes associated to muscle atrophy, MyoD, myogenin, atrogin-1, and transforming growth factor (TGF)β1, is up-regulated already at the presymptomatic stage. Atrogin-1 gene expression was increased also in mice overexpressing human wtSOD1. Similar alterations were found in axotomized mouse muscles and in cultured ALS myoblast models. In these ALS models, we then evaluated the pharmacological effects of the synthetic AAS nandrolone on the expression of the genes modified in ALS muscle. Nandrolone administration had no effects on MyoD, myogenin, and atrogin-1 expression, but it significantly increased TGFβ1 expression at disease onset. Altogether, these data suggest that, in fALS, muscle gene expression is altered at early stages, and AAS may exacerbate some of the alterations induced by SOD1 possibly acting as a contributing factor also in sALS. PMID:22178654

The anabolic/androgenic steroid nandrolone exacerbates gene expression modifications induced by mutant SOD1 in muscles of mice models of amyotrophic lateral sclerosis.

PubMed

Galbiati, Mariarita; Onesto, Elisa; Zito, Arianna; Crippa, Valeria; Rusmini, Paola; Mariotti, Raffaella; Bentivoglio, Marina; Bendotti, Caterina; Poletti, Angelo

2012-02-01

Anabolic/androgenic steroids (AAS) are drugs that enhance muscle mass, and are often illegally utilized in athletes to improve their performances. Recent data suggest that the increased risk for amyotrophic lateral sclerosis (ALS) in male soccer and football players could be linked to AAS abuse. ALS is a motor neuron disease mainly occurring in sporadic (sALS) forms, but some familial forms (fALS) exist and have been linked to mutations in different genes. Some of these, in their wild type (wt) form, have been proposed as risk factors for sALS, i.e. superoxide dismutase 1 (SOD1) gene, whose mutations are causative of about 20% of fALS. Notably, SOD1 toxicity might occur both in motor neurons and in muscle cells. Using gastrocnemius muscles of mice overexpressing human mutant SOD1 (mutSOD1) at different disease stages, we found that the expression of a selected set of genes associated to muscle atrophy, MyoD, myogenin, atrogin-1, and transforming growth factor (TGF)β1, is up-regulated already at the presymptomatic stage. Atrogin-1 gene expression was increased also in mice overexpressing human wtSOD1. Similar alterations were found in axotomized mouse muscles and in cultured ALS myoblast models. In these ALS models, we then evaluated the pharmacological effects of the synthetic AAS nandrolone on the expression of the genes modified in ALS muscle. Nandrolone administration had no effects on MyoD, myogenin, and atrogin-1 expression, but it significantly increased TGFβ1 expression at disease onset. Altogether, these data suggest that, in fALS, muscle gene expression is altered at early stages, and AAS may exacerbate some of the alterations induced by SOD1 possibly acting as a contributing factor also in sALS. Copyright © 2011 Elsevier Ltd. All rights reserved.

Regulation of glutamate transporter 1 (GLT-1) gene expression by cocaine self-administration and withdrawal.

PubMed

Kim, Ronald; Sepulveda-Orengo, Marian T; Healey, Kati L; Williams, Emily A; Reissner, Kathryn J

2018-01-01

Downregulation of the astroglial glutamate transporter GLT-1 is observed in the nucleus accumbens (NAc) following administration of multiple drugs of abuse. The decrease in GLT-1 protein expression following cocaine self-administration is dependent on both the amount of cocaine self-administered and the length of withdrawal, with longer access to cocaine and longer withdrawal periods leading to greater decreases in GLT-1 protein. However, the mechanism(s) by which cocaine downregulates GLT-1 protein remains unknown. We used qRT-PCR to examine gene expression of GLT-1 splice isoforms (GLT-1A, GLT-1B) in the NAc, prelimbic cortex (PL) and basolateral amygdala (BLA) of rats, following two widely used models of cocaine self-administration: short-access (ShA) self-administration, and the long-access (LgA) self-administration/incubation model. While downregulation of GLT-1 protein is observed following ShA cocaine self-administration and extinction, this model did not lead to a change in GLT-1A or GLT-1B gene expression in any brain region examined. Forced abstinence following ShA cocaine self-administration also was without effect. In contrast, LgA cocaine self-administration and prolonged abstinence significantly decreased GLT-1A gene expression in the NAc and BLA, and significantly decreased GLT-1B gene expression in the PL. No change was observed in NAc GLT-1A gene expression one day after LgA cocaine self-administration, indicating withdrawal-induced decreases in GLT-1A mRNA. In addition, LgA cocaine self-administration and withdrawal induced hypermethylation of the GLT-1 gene in the NAc. These results indicate that a decrease in NAc GLT-1 mRNA is only observed after extended access to cocaine combined with protracted abstinence, and that epigenetic mechanisms likely contribute to this effect. Copyright © 2017 Elsevier Ltd. All rights reserved.

Evaluation of normalization reference genes for RT-qPCR analysis of spo0A and four sporulation sigma factor genes in Clostridium botulinum Group I strain ATCC 3502.

PubMed

Kirk, David G; Palonen, Eveliina; Korkeala, Hannu; Lindström, Miia

2014-04-01

Heat-resistant spores of Clostridium botulinum can withstand the pasteurization processes in modern food processing. This poses a risk to food safety as spores may germinate into botulinum neurotoxin-producing vegetative cells. Sporulation in Bacillus subtilis, the model organism for sporulation, is regulated by the transcription factor Spo0A and four alternative sigma factors, SigF, SigE, SigG, and SigK. While the corresponding regulators are found in available genomes of C. botulinum, little is known about their expression. To accurately measure the expression of these genes using quantitative reverse-transcriptase PCR (RT-qPCR) during the exponential and stationary growth phases, a suitable normalization reference gene is required. 16S rrn, adK, alaS, era, gluD, gyrA, rpoC, and rpsJ were selected as the candidate reference genes. The most stable candidate reference gene was 16S ribosomal RNA gene (rrn), based on its low coefficient of variation (1.81%) measured during the 18-h study time. Using 16S rrn as the normalization reference gene, the relative expression levels of spo0A, sigF, sigE, sigG, and sigK were measured over 18h. The pattern of expression showed spo0A expression during the logarithmic growth phase, followed by a drop in expression upon entry to the stationary phase. Expression levels of sigF, sigE, and sigG peaked simultaneously at the end of the exponential growth phase. Peak expression of sigK occurred at 18h, however low levels of expression were detected during the exponential phase. These findings suggest these sigma factors play a role in C. botulinum sporulation that is similar, but not equal, to their role in the B. subtilis model. Copyright © 2013 Elsevier Ltd. All rights reserved.

Genomics of Mature and Immature Olfactory Sensory Neurons

PubMed Central

Nickell, Melissa D.; Breheny, Patrick; Stromberg, Arnold J.; McClintock, Timothy S.

2014-01-01

The continuous replacement of neurons in the olfactory epithelium provides an advantageous model for investigating neuronal differentiation and maturation. By calculating the relative enrichment of every mRNA detected in samples of mature mouse olfactory sensory neurons (OSNs), immature OSNs, and the residual population of neighboring cell types, and then comparing these ratios against the known expression patterns of >300 genes, enrichment criteria that accurately predicted the OSN expression patterns of nearly all genes were determined. We identified 847 immature OSN-specific and 691 mature OSN-specific genes. The control of gene expression by chromatin modification and transcription factors, and neurite growth, protein transport, RNA processing, cholesterol biosynthesis, and apoptosis via death domain receptors, were overrepresented biological processes in immature OSNs. Ion transport (ion channels), presynaptic functions, and cilia-specific processes were overrepresented in mature OSNs. Processes overrepresented among the genes expressed by all OSNs were protein and ion transport, ER overload response, protein catabolism, and the electron transport chain. To more accurately represent gradations in mRNA abundance and identify all genes expressed in each cell type, classification methods were used to produce probabilities of expression in each cell type for every gene. These probabilities, which identified 9,300 genes expressed in OSNs, were 96% accurate at identifying genes expressed in OSNs and 86% accurate at discriminating genes specific to mature and immature OSNs. This OSN gene database not only predicts the genes responsible for the major biological processes active in OSNs, but also identifies thousands of never before studied genes that support OSN phenotypes. PMID:22252456

Early gene expression during natural spinal cord regeneration in the salamander Ambystoma mexicanum.

PubMed

Monaghan, James R; Walker, John A; Page, Robert B; Putta, Srikrishna; Beachy, Christopher K; Voss, S Randal

2007-04-01

In contrast to mammals, salamanders have a remarkable ability to regenerate their spinal cord and recover full movement and function after tail amputation. To identify genes that may be associated with this greater regenerative ability, we designed an oligonucleotide microarray and profiled early gene expression during natural spinal cord regeneration in Ambystoma mexicanum. We sampled tissue at five early time points after tail amputation and identified genes that registered significant changes in mRNA abundance during the first 7 days of regeneration. A list of 1036 statistically significant genes was identified. Additional statistical and fold change criteria were applied to identify a smaller list of 360 genes that were used to describe predominant expression patterns and gene functions. Our results show that a diverse injury response is activated in concert with extracellular matrix remodeling mechanisms during the early acute phase of natural spinal cord regeneration. We also report gene expression similarities and differences between our study and studies that have profiled gene expression after spinal cord injury in rat. Our study illustrates the utility of a salamander model for identifying genes and gene functions that may enhance regenerative ability in mammals.

Precision-cut liver slices as a model for the early onset of liver fibrosis to test antifibrotic drugs

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

Westra, Inge M.; Oosterhuis, Dorenda; Groothuis, Geny M.M.

Induction of fibrosis during prolonged culture of precision-cut liver slices (PCLS) was reported. In this study, the use of rat PCLS was investigated to further characterize the mechanism of early onset of fibrosis in this model and the effects of antifibrotic compounds. Rat PCLS were incubated for 48 h, viability was assessed by ATP and gene expression of PDGF-B and TGF-β1 and the fibrosis markers Hsp47, αSma and Pcol1A1 and collagen1 protein expressions were determined. The effects of the antifibrotic drugs imatinib, sorafenib and sunitinib, PDGF-pathway inhibitors, and perindopril, valproic acid, rosmarinic acid, tetrandrine and pirfenidone, TGFβ-pathway inhibitors, were determined.more » After 48 h of incubation, viability of the PCLS was maintained and gene expression of PDGF-B was increased while TGF-β1 was not changed. Hsp47, αSma and Pcol1A1 gene expressions were significantly elevated in PCLS after 48 h, which was further increased by PDGF-BB and TGF-β1. The increased gene expression of fibrosis markers was inhibited by all three PDGF-inhibitors, while TGFβ-inhibitors showed marginal effects. The protein expression of collagen 1 was inhibited by imatinib, perindopril, tetrandrine and pirfenidone. In conclusion, the increased gene expression of PDGF-B and the down-regulation of fibrosis markers by PDGF-pathway inhibitors, together with the absence of elevated TGF-β1 gene expression and the limited effect of the TGFβ-pathway inhibitors, indicated the predominance of the PDGF pathway in the early onset of fibrosis in PCLS. PCLS appear a useful model for research of the early onset of fibrosis and for testing of antifibrotic drugs acting on the PDGF pathway. - Highlights: • During culture, fibrosis markers increased in precision-cut liver slices (PCLS). • Gene expression of PDGF-β was increased, while TGFβ was not changed in rat PCLS. • PDGF-pathway inhibitors down-regulated this increase of fibrosis markers. • TGFβ-pathway inhibitors had only minor effects on fibrosis markers. • Rat PCLS can be used to study the early onset of fibrosis.« less

Signaling pathways regulating the expression of Prx1 and Prx2 in the Chick Mandibular Mesenchyme

PubMed Central

Doufexi, Aikaterini-El; Mina, Mina

2009-01-01

Prx1 and Prx2 are members of the aristaless-related homeobox genes shown to play redundant but essential roles in morphogenesis of the mandibular processes. To gain insight into the signaling pathways that regulate expression of Prx genes in the mandibular mesenchyme, we used the chick as a model system. We examined the patterns of gene expression in the face and the roles of signals derived from the epithelium on the expression of Prx genes in the mandibular mesenchyme. Our results demonstrated stage-dependent roles of mandibular epithelium on the expression of Prx in the mandibular mesenchyme and provide evidence for positive roles of members of the fibroblast and hedgehog families derived from mandibular epithelium on the expression of Prx genes in the mandibular mesenchyme. Our studies suggest that endothelin-1 signaling derived from the mesenchyme is involved in restricting the expression of Prx2 to the medial mandibular mesenchyme. PMID:18942149

microRNA as a Potential Vector for the Propagation of Robustness in Protein Expression and Oscillatory Dynamics within a ceRNA Network

PubMed Central

Gérard, Claude; Novák, Béla

2013-01-01

microRNAs (miRNAs) are small noncoding RNAs that are important post-transcriptional regulators of gene expression. miRNAs can induce thresholds in protein synthesis. Such thresholds in protein output can be also achieved by oligomerization of transcription factors (TF) for the control of gene expression. First, we propose a minimal model for protein expression regulated by miRNA and by oligomerization of TF. We show that miRNA and oligomerization of TF generate a buffer, which increases the robustness of protein output towards molecular noise as well as towards random variation of kinetics parameters. Next, we extend the model by considering that the same miRNA can bind to multiple messenger RNAs, which accounts for the dynamics of a minimal competing endogenous RNAs (ceRNAs) network. The model shows that, through common miRNA regulation, TF can control the expression of all proteins formed by the ceRNA network, even if it drives the expression of only one gene in the network. The model further suggests that the threshold in protein synthesis mediated by the oligomerization of TF can be propagated to the other genes, which can increase the robustness of the expression of all genes in such ceRNA network. Furthermore, we show that a miRNA could increase the time delay of a “Goodwin-like” oscillator model, which may favor the occurrence of oscillations of large amplitude. This result predicts important roles of miRNAs in the control of the molecular mechanisms leading to the emergence of biological rhythms. Moreover, a model for the latter oscillator embedded in a ceRNA network indicates that the oscillatory behavior can be propagated, via the shared miRNA, to all proteins formed by such ceRNA network. Thus, by means of computational models, we show that miRNAs could act as vectors allowing the propagation of robustness in protein synthesis as well as oscillatory behaviors within ceRNA networks. PMID:24376695

Sex-Specific Selection and Sex-Biased Gene Expression in Humans and Flies.

PubMed

Cheng, Changde; Kirkpatrick, Mark

2016-09-01

Sexual dimorphism results from sex-biased gene expression, which evolves when selection acts differently on males and females. While there is an intimate connection between sex-biased gene expression and sex-specific selection, few empirical studies have studied this relationship directly. Here we compare the two on a genome-wide scale in humans and flies. We find a distinctive "Twin Peaks" pattern in humans that relates the strength of sex-specific selection, quantified by genetic divergence between male and female adults at autosomal loci, to the degree of sex-biased expression. Genes with intermediate degrees of sex-biased expression show evidence of ongoing sex-specific selection, while genes with either little or completely sex-biased expression do not. This pattern apparently results from differential viability selection in males and females acting in the current generation. The Twin Peaks pattern is also found in Drosophila using a different measure of sex-specific selection acting on fertility. We develop a simple model that successfully recapitulates the Twin Peaks. Our results suggest that many genes with intermediate sex-biased expression experience ongoing sex-specific selection in humans and flies.

Regulation of human genome expression and RNA splicing by human papillomavirus 16 E2 protein.

PubMed

Gauson, Elaine J; Windle, Brad; Donaldson, Mary M; Caffarel, Maria M; Dornan, Edward S; Coleman, Nicholas; Herzyk, Pawel; Henderson, Scott C; Wang, Xu; Morgan, Iain M

2014-11-01

Human papillomavirus 16 (HPV16) is causative in human cancer. The E2 protein regulates transcription from and replication of the viral genome; the role of E2 in regulating the host genome has been less well studied. We have expressed HPV16 E2 (E2) stably in U2OS cells; these cells tolerate E2 expression well and gene expression analysis identified 74 genes showing differential expression specific to E2. Analysis of published gene expression data sets during cervical cancer progression identified 20 of the genes as being altered in a similar direction as the E2 specific genes. In addition, E2 altered the splicing of many genes implicated in cancer and cell motility. The E2 expressing cells showed no alteration in cell growth but were altered in cell motility, consistent with the E2 induced altered splicing predicted to affect this cellular function. The results present a model system for investigating E2 regulation of the host genome. Copyright © 2014 Elsevier Inc. All rights reserved.

Aging and Gene Expression in the Primate Brain

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

Fraser, Hunter B.; Khaitovich, Philipp; Plotkin, Joshua B.

2005-02-18

It is well established that gene expression levels in many organisms change during the aging process, and the advent of DNA microarrays has allowed genome-wide patterns of transcriptional changes associated with aging to be studied in both model organisms and various human tissues. Understanding the effects of aging on gene expression in the human brain is of particular interest, because of its relation to both normal and pathological neurodegeneration. Here we show that human cerebral cortex, human cerebellum, and chimpanzee cortex each undergo different patterns of age-related gene expression alterations. In humans, many more genes undergo consistent expression changes inmore » the cortex than in the cerebellum; in chimpanzees, many genes change expression with age in cortex, but the pattern of changes in expression bears almost no resemblance to that of human cortex. These results demonstrate the diversity of aging patterns present within the human brain, as well as how rapidly genome-wide patterns of aging can evolve between species; they may also have implications for the oxidative free radical theory of aging, and help to improve our understanding of human neurodegenerative diseases.« less

Cotransduction with MGMT and Ubiquitous or Erythroid-Specific GFP Lentiviruses Allows Enrichment of Dual-Positive Hematopoietic Progenitor Cells In Vivo

PubMed Central

Roth, Justin C.; Ismail, Mourad; Reese, Jane S.; Lingas, Karen T.; Ferrari, Giuliana; Gerson, Stanton L.

2012-01-01

The P140K point mutant of MGMT allows robust hematopoietic stem cell (HSC) enrichment in vivo. Thus, dual-gene vectors that couple MGMT and therapeutic gene expression have allowed enrichment of gene-corrected HSCs in animal models. However, expression levels from dual-gene vectors are often reduced for one or both genes. Further, it may be desirable to express selection and therapeutic genes at distinct stages of cell differentiation. In this regard, we evaluated whether hematopoietic cells could be efficiently cotransduced using low MOIs of two separate single-gene lentiviruses, including MGMT for dual-positive cell enrichment. Cotransduction efficiencies were evaluated using a range of MGMT : GFP virus ratios, MOIs, and selection stringencies in vitro. Cotransduction was optimal when equal proportions of each virus were used, but low MGMT : GFP virus ratios resulted in the highest proportion of dual-positive cells after selection. This strategy was then evaluated in murine models for in vivo selection of HSCs cotransduced with a ubiquitous MGMT expression vector and an erythroid-specific GFP vector. Although the MGMT and GFP expression percentages were variable among engrafted recipients, drug selection enriched MGMT-positive leukocyte and GFP-positive erythroid cell populations. These data demonstrate cotransduction as a mean to rapidly enrich and evaluate therapeutic lentivectors in vivo. PMID:22888445

Unravelling proximate cues of mass flowering in the tropical forests of South-East Asia from gene expression analyses.

PubMed

Yeoh, Suat Hui; Satake, Akiko; Numata, Shinya; Ichie, Tomoaki; Lee, Soon Leong; Basherudin, Norlia; Muhammad, Norwati; Kondo, Toshiaki; Otani, Tatsuya; Hashim, Mazlan; Tani, Naoki

2017-10-01

Elucidating the physiological mechanisms of the irregular yet concerted flowering rhythm of mass flowering tree species in the tropics requires long-term monitoring of flowering phenology, exogenous and endogenous environmental factors, as well as identifying interactions and dependencies among these factors. To investigate the proximate factors for floral initiation of mast seeding trees in the tropics, we monitored the expression dynamics of two key flowering genes, meteorological conditions and endogenous resources over two flowering events of Shorea curtisii and Shorea leprosula in the Malay Peninsula. Comparisons of expression dynamics of genes studied indicated functional conservation of FLOWERING LOCUS T (FT) and LEAFY (LFY) in Shorea. The genes were highly expressed at least 1 month before anthesis for both species. A mathematical model considering the synergistic effect of cool temperature and drought on activation of the flowering gene was successful in predicting the observed gene expression patterns. Requirement of both cool temperature and drought for floral transition suggested by the model implies that flowering phenologies of these species are sensitive to climate change. Our molecular phenology approach in the tropics sheds light on the conserved role of flowering genes in plants inhabiting different climate zones and can be widely applied to dissect the flowering processes in other plant species. © 2017 John Wiley & Sons Ltd.

Estimating intrinsic and extrinsic noise from single-cell gene expression measurements

PubMed Central

Fu, Audrey Qiuyan; Pachter, Lior

2017-01-01

Gene expression is stochastic and displays variation (“noise”) both within and between cells. Intracellular (intrinsic) variance can be distinguished from extracellular (extrinsic) variance by applying the law of total variance to data from two-reporter assays that probe expression of identically regulated gene pairs in single cells. We examine established formulas [Elowitz, M. B., A. J. Levine, E. D. Siggia and P. S. Swain (2002): “Stochastic gene expression in a single cell,” Science, 297, 1183–1186.] for the estimation of intrinsic and extrinsic noise and provide interpretations of them in terms of a hierarchical model. This allows us to derive alternative estimators that minimize bias or mean squared error. We provide a geometric interpretation of these results that clarifies the interpretation in [Elowitz, M. B., A. J. Levine, E. D. Siggia and P. S. Swain (2002): “Stochastic gene expression in a single cell,” Science, 297, 1183–1186.]. We also demonstrate through simulation and re-analysis of published data that the distribution assumptions underlying the hierarchical model have to be satisfied for the estimators to produce sensible results, which highlights the importance of normalization. PMID:27875323

Identification and Validation of Selected Universal Stress Protein Domain Containing Drought-Responsive Genes in Pigeonpea (Cajanus cajan L.)

PubMed Central

Sinha, Pallavi; Pazhamala, Lekha T.; Singh, Vikas K.; Saxena, Rachit K.; Krishnamurthy, L.; Azam, Sarwar; Khan, Aamir W.; Varshney, Rajeev K.

2016-01-01

Pigeonpea is a resilient crop, which is relatively more drought tolerant than many other legume crops. To understand the molecular mechanisms of this unique feature of pigeonpea, 51 genes were selected using the Hidden Markov Models (HMM) those codes for proteins having close similarity to universal stress protein domain. Validation of these genes was conducted on three pigeonpea genotypes (ICPL 151, ICPL 8755, and ICPL 227) having different levels of drought tolerance. Gene expression analysis using qRT-PCR revealed 6, 8, and 18 genes to be ≥2-fold differentially expressed in ICPL 151, ICPL 8755, and ICPL 227, respectively. A total of 10 differentially expressed genes showed ≥2-fold up-regulation in the more drought tolerant genotype, which encoded four different classes of proteins. These include plant U-box protein (four genes), universal stress protein A-like protein (four genes), cation/H(+) antiporter protein (one gene) and an uncharacterized protein (one gene). Genes C.cajan_29830 and C.cajan_33874 belonging to uspA, were found significantly expressed in all the three genotypes with ≥2-fold expression variations. Expression profiling of these two genes on the four other legume crops revealed their specific role in pigeonpea. Therefore, these genes seem to be promising candidates for conferring drought tolerance specifically to pigeonpea. PMID:26779199

dictyExpress: a Dictyostelium discoideum gene expression database with an explorative data analysis web-based interface.

PubMed

Rot, Gregor; Parikh, Anup; Curk, Tomaz; Kuspa, Adam; Shaulsky, Gad; Zupan, Blaz

2009-08-25

Bioinformatics often leverages on recent advancements in computer science to support biologists in their scientific discovery process. Such efforts include the development of easy-to-use web interfaces to biomedical databases. Recent advancements in interactive web technologies require us to rethink the standard submit-and-wait paradigm, and craft bioinformatics web applications that share analytical and interactive power with their desktop relatives, while retaining simplicity and availability. We have developed dictyExpress, a web application that features a graphical, highly interactive explorative interface to our database that consists of more than 1000 Dictyostelium discoideum gene expression experiments. In dictyExpress, the user can select experiments and genes, perform gene clustering, view gene expression profiles across time, view gene co-expression networks, perform analyses of Gene Ontology term enrichment, and simultaneously display expression profiles for a selected gene in various experiments. Most importantly, these tasks are achieved through web applications whose components are seamlessly interlinked and immediately respond to events triggered by the user, thus providing a powerful explorative data analysis environment. dictyExpress is a precursor for a new generation of web-based bioinformatics applications with simple but powerful interactive interfaces that resemble that of the modern desktop. While dictyExpress serves mainly the Dictyostelium research community, it is relatively easy to adapt it to other datasets. We propose that the design ideas behind dictyExpress will influence the development of similar applications for other model organisms.

dictyExpress: a Dictyostelium discoideum gene expression database with an explorative data analysis web-based interface

PubMed Central

Rot, Gregor; Parikh, Anup; Curk, Tomaz; Kuspa, Adam; Shaulsky, Gad; Zupan, Blaz

2009-01-01

Background Bioinformatics often leverages on recent advancements in computer science to support biologists in their scientific discovery process. Such efforts include the development of easy-to-use web interfaces to biomedical databases. Recent advancements in interactive web technologies require us to rethink the standard submit-and-wait paradigm, and craft bioinformatics web applications that share analytical and interactive power with their desktop relatives, while retaining simplicity and availability. Results We have developed dictyExpress, a web application that features a graphical, highly interactive explorative interface to our database that consists of more than 1000 Dictyostelium discoideum gene expression experiments. In dictyExpress, the user can select experiments and genes, perform gene clustering, view gene expression profiles across time, view gene co-expression networks, perform analyses of Gene Ontology term enrichment, and simultaneously display expression profiles for a selected gene in various experiments. Most importantly, these tasks are achieved through web applications whose components are seamlessly interlinked and immediately respond to events triggered by the user, thus providing a powerful explorative data analysis environment. Conclusion dictyExpress is a precursor for a new generation of web-based bioinformatics applications with simple but powerful interactive interfaces that resemble that of the modern desktop. While dictyExpress serves mainly the Dictyostelium research community, it is relatively easy to adapt it to other datasets. We propose that the design ideas behind dictyExpress will influence the development of similar applications for other model organisms. PMID:19706156

3D confocal reconstruction of gene expression in mouse.

PubMed

Hecksher-Sørensen, J; Sharpe, J

2001-01-01

Three-dimensional computer reconstructions of gene expression data will become a valuable tool in biomedical research in the near future. However, at present the process of converting in situ expression data into 3D models is a highly specialized and time-consuming procedure. Here we present a method which allows rapid reconstruction of whole-mount in situ data from mouse embryos. Mid-gestation embryos were stained with the alkaline phosphotase substrate Fast Red, which can be detected using confocal laser scanning microscopy (CLSM), and cut into 70 microm sections. Each section was then scanned and digitally reconstructed. Using this method it took two days to section, digitize and reconstruct the full expression pattern of Shh in an E9.5 embryo (a 3D model of this embryo can be seen at genex.hgu.mrc.ac.uk). Additionally we demonstrate that this technique allows gene expression to be studied at the single cell level in intact tissue.

Multiway modeling and analysis in stem cell systems biology

PubMed Central

2008-01-01

Background Systems biology refers to multidisciplinary approaches designed to uncover emergent properties of biological systems. Stem cells are an attractive target for this analysis, due to their broad therapeutic potential. A central theme of systems biology is the use of computational modeling to reconstruct complex systems from a wealth of reductionist, molecular data (e.g., gene/protein expression, signal transduction activity, metabolic activity, etc.). A number of deterministic, probabilistic, and statistical learning models are used to understand sophisticated cellular behaviors such as protein expression during cellular differentiation and the activity of signaling networks. However, many of these models are bimodal i.e., they only consider row-column relationships. In contrast, multiway modeling techniques (also known as tensor models) can analyze multimodal data, which capture much more information about complex behaviors such as cell differentiation. In particular, tensors can be very powerful tools for modeling the dynamic activity of biological networks over time. Here, we review the application of systems biology to stem cells and illustrate application of tensor analysis to model collagen-induced osteogenic differentiation of human mesenchymal stem cells. Results We applied Tucker1, Tucker3, and Parallel Factor Analysis (PARAFAC) models to identify protein/gene expression patterns during extracellular matrix-induced osteogenic differentiation of human mesenchymal stem cells. In one case, we organized our data into a tensor of type protein/gene locus link × gene ontology category × osteogenic stimulant, and found that our cells expressed two distinct, stimulus-dependent sets of functionally related genes as they underwent osteogenic differentiation. In a second case, we organized DNA microarray data in a three-way tensor of gene IDs × osteogenic stimulus × replicates, and found that application of tensile strain to a collagen I substrate accelerated the osteogenic differentiation induced by a static collagen I substrate. Conclusion Our results suggest gene- and protein-level models whereby stem cells undergo transdifferentiation to osteoblasts, and lay the foundation for mechanistic, hypothesis-driven studies. Our analysis methods are applicable to a wide range of stem cell differentiation models. PMID:18625054

Chamber Specific Gene Expression Landscape of the Zebrafish Heart

PubMed Central

Singh, Angom Ramcharan; Sivadas, Ambily; Sabharwal, Ankit; Vellarikal, Shamsudheen Karuthedath; Jayarajan, Rijith; Verma, Ankit; Kapoor, Shruti; Joshi, Adita; Scaria, Vinod; Sivasubbu, Sridhar

2016-01-01

The organization of structure and function of cardiac chambers in vertebrates is defined by chamber-specific distinct gene expression. This peculiarity and uniqueness of the genetic signatures demonstrates functional resolution attributed to the different chambers of the heart. Altered expression of the cardiac chamber genes can lead to individual chamber related dysfunctions and disease patho-physiologies. Information on transcriptional repertoire of cardiac compartments is important to understand the spectrum of chamber specific anomalies. We have carried out a genome wide transcriptome profiling study of the three cardiac chambers in the zebrafish heart using RNA sequencing. We have captured the gene expression patterns of 13,396 protein coding genes in the three cardiac chambers—atrium, ventricle and bulbus arteriosus. Of these, 7,260 known protein coding genes are highly expressed (≥10 FPKM) in the zebrafish heart. Thus, this study represents nearly an all-inclusive information on the zebrafish cardiac transcriptome. In this study, a total of 96 differentially expressed genes across the three cardiac chambers in zebrafish were identified. The atrium, ventricle and bulbus arteriosus displayed 20, 32 and 44 uniquely expressing genes respectively. We validated the expression of predicted chamber-restricted genes using independent semi-quantitative and qualitative experimental techniques. In addition, we identified 23 putative novel protein coding genes that are specifically restricted to the ventricle and not in the atrium or bulbus arteriosus. In our knowledge, these 23 novel genes have either not been investigated in detail or are sparsely studied. The transcriptome identified in this study includes 68 differentially expressing zebrafish cardiac chamber genes that have a human ortholog. We also carried out spatiotemporal gene expression profiling of the 96 differentially expressed genes throughout the three cardiac chambers in 11 developmental stages and 6 tissue types of zebrafish. We hypothesize that clustering the differentially expressed genes with both known and unknown functions will deliver detailed insights on fundamental gene networks that are important for the development and specification of the cardiac chambers. It is also postulated that this transcriptome atlas will help utilize zebrafish in a better way as a model for studying cardiac development and to explore functional role of gene networks in cardiac disease pathogenesis. PMID:26815362

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

Normal uniform mixture differential gene expression detection for cDNA microarrays

PubMed Central

Dean, Nema; Raftery, Adrian E

2005-01-01

Background One of the primary tasks in analysing gene expression data is finding genes that are differentially expressed in different samples. Multiple testing issues due to the thousands of tests run make some of the more popular methods for doing this problematic. Results We propose a simple method, Normal Uniform Differential Gene Expression (NUDGE) detection for finding differentially expressed genes in cDNA microarrays. The method uses a simple univariate normal-uniform mixture model, in combination with new normalization methods for spread as well as mean that extend the lowess normalization of Dudoit, Yang, Callow and Speed (2002) [1]. It takes account of multiple testing, and gives probabilities of differential expression as part of its output. It can be applied to either single-slide or replicated experiments, and it is very fast. Three datasets are analyzed using NUDGE, and the results are compared to those given by other popular methods: unadjusted and Bonferroni-adjusted t tests, Significance Analysis of Microarrays (SAM), and Empirical Bayes for microarrays (EBarrays) with both Gamma-Gamma and Lognormal-Normal models. Conclusion The method gives a high probability of differential expression to genes known/suspected a priori to be differentially expressed and a low probability to the others. In terms of known false positives and false negatives, the method outperforms all multiple-replicate methods except for the Gamma-Gamma EBarrays method to which it offers comparable results with the added advantages of greater simplicity, speed, fewer assumptions and applicability to the single replicate case. An R package called nudge to implement the methods in this paper will be made available soon at . PMID:16011807

Short-term hyperglycaemia causes non-reversible changes in arterial gene expression in a fully 'switchable' in vivo mouse model of diabetes.

PubMed

Zervou, S; Wang, Y-F; Laiho, A; Gyenesei, A; Kytömäki, L; Hermann, R; Abouna, S; Epstein, D; Pelengaris, S; Khan, M

2010-12-01

Irreversible arterial damage due to early effects of hypo- or hyperglycaemia could account for the limited success of glucose-lowering treatments in preventing cardiovascular disease (CVD) events. We hypothesised that even brief hypo- or hyperglycaemia could adversely affect arterial gene expression and that these changes, moreover, might not be fully reversible. By controlled activation of a 'switchable' c-Myc transgene in beta cells, adult pIns-c-MycER(TAM) mice were rendered transiently hypo- and then hyperglycaemic, after which they were allowed to recover for up to 3 months. Immediate and sequential changes in aortic global gene expression from normal glycaemia through hypo- and hyperglycaemia to recovery were assessed. Gene expression was compared with that of normoglycaemic transgenic and tamoxifen-treated wild-type controls. Overall, expression of 95 genes was significantly affected by moderate hypoglycaemia (glucose down to 2.5 mmol/l), whereas over 769 genes were affected by hyperglycaemia. Genes and pathways activated included several involved in atherogenic processes, such as inflammation and arterial calcification. Although expression of many genes recovered to initial pre-exposure levels when hyperglycaemia was corrected (74.9%), in one in four genes this did not occur. Quantitative reverse transcriptase PCR and immunohistochemistry verified the gene expression patterns of key molecules, as shown by global gene arrays. Short-term exposure to hyperglycaemia can cause deleterious and persistent changes in arterial gene expression in vivo. Brief hypoglycaemia also adversely affects gene expression, although less substantially. Together, these results suggest that early correction of hyperglycaemia and avoidance of hypoglycaemia may both be necessary to avoid excess CVD risk in diabetes.

Gene Expression Signatures Based on Variability can Robustly Predict Tumor Progression and Prognosis

PubMed Central

Dinalankara, Wikum; Bravo, Héctor Corrada

2015-01-01

Gene expression signatures are commonly used to create cancer prognosis and diagnosis methods, yet only a small number of them are successfully deployed in the clinic since many fail to replicate performance on subsequent validation. A primary reason for this lack of reproducibility is the fact that these signatures attempt to model the highly variable and unstable genomic behavior of cancer. Our group recently introduced gene expression anti-profiles as a robust methodology to derive gene expression signatures based on the observation that while gene expression measurements are highly heterogeneous across tumors of a specific cancer type relative to the normal tissue, their degree of deviation from normal tissue expression in specific genes involved in tissue differentiation is a stable tumor mark that is reproducible across experiments and cancer types. Here we show that constructing gene expression signatures based on variability and the anti-profile approach yields classifiers capable of successfully distinguishing benign growths from cancerous growths based on deviation from normal expression. We then show that this same approach generates stable and reproducible signatures that predict probability of relapse and survival based on tumor gene expression. These results suggest that using the anti-profile framework for the discovery of genomic signatures is an avenue leading to the development of reproducible signatures suitable for adoption in clinical settings. PMID:26078586

Expression Profile of Drug and Nutrient Absorption Related Genes in Madin-Darby Canine Kidney (MDCK) Cells Grown under Differentiation Conditions.

PubMed

Quan, Yong; Jin, Yisheng; Faria, Teresa N; Tilford, Charles A; He, Aiqing; Wall, Doris A; Smith, Ronald L; Vig, Balvinder S

2012-06-18

The expression levels of genes involved in drug and nutrient absorption were evaluated in the Madin-Darby Canine Kidney (MDCK) in vitro drug absorption model. MDCK cells were grown on plastic surfaces (for 3 days) or on Transwell® membranes (for 3, 5, 7, and 9 days). The expression profile of genes including ABC transporters, SLC transporters, and cytochrome P450 (CYP) enzymes was determined using the Affymetrix® Canine GeneChip®. Expression of genes whose probe sets passed a stringent confirmation process was examined. Expression of a few transporter (MDR1, PEPT1 and PEPT2) genes in MDCK cells was confirmed by RT-PCR. The overall gene expression profile was strongly influenced by the type of support the cells were grown on. After 3 days of growth, expression of 28% of the genes was statistically different (1.5-fold cutoff, p < 0.05) between the cells grown on plastic and Transwell® membranes. When cells were differentiated on Transwell® membranes, large changes in gene expression profile were observed during the early stages, which then stabilized after 5-7 days. Only a small number of genes encoding drug absorption related SLC, ABC, and CYP were detected in MDCK cells, and most of them exhibited low hybridization signals. Results from this study provide valuable reference information on endogenous gene expression in MDCK cells that could assist in design of drug-transporter and/or drug-enzyme interaction studies, and help interpret the contributions of various transporters and metabolic enzymes in studies with MDCK cells.

Expression Profile of Drug and Nutrient Absorption Related Genes in Madin-Darby Canine Kidney (MDCK) Cells Grown under Differentiation Conditions

PubMed Central

Quan, Yong; Jin, Yisheng; Faria, Teresa N.; Tilford, Charles A.; He, Aiqing; Wall, Doris A.; Smith, Ronald L.; Vig, Balvinder S.

2012-01-01

The expression levels of genes involved in drug and nutrient absorption were evaluated in the Madin-Darby Canine Kidney (MDCK) in vitro drug absorption model. MDCK cells were grown on plastic surfaces (for 3 days) or on Transwell® membranes (for 3, 5, 7, and 9 days). The expression profile of genes including ABC transporters, SLC transporters, and cytochrome P450 (CYP) enzymes was determined using the Affymetrix® Canine GeneChip®. Expression of genes whose probe sets passed a stringent confirmation process was examined. Expression of a few transporter (MDR1, PEPT1 and PEPT2) genes in MDCK cells was confirmed by RT-PCR. The overall gene expression profile was strongly influenced by the type of support the cells were grown on. After 3 days of growth, expression of 28% of the genes was statistically different (1.5-fold cutoff, p < 0.05) between the cells grown on plastic and Transwell® membranes. When cells were differentiated on Transwell® membranes, large changes in gene expression profile were observed during the early stages, which then stabilized after 5–7 days. Only a small number of genes encoding drug absorption related SLC, ABC, and CYP were detected in MDCK cells, and most of them exhibited low hybridization signals. Results from this study provide valuable reference information on endogenous gene expression in MDCK cells that could assist in design of drug-transporter and/or drug-enzyme interaction studies, and help interpret the contributions of various transporters and metabolic enzymes in studies with MDCK cells. PMID:24300234

Transcriptome profiling analysis reveals biomarkers in colon cancer samples of various differentiation

PubMed Central

Yu, Tonghu; Zhang, Huaping; Qi, Hong

2018-01-01

The aim of the present study was to investigate more colon cancer-related genes in different stages. Gene expression profile E-GEOD-62932 was extracted for differentially expressed gene (DEG) screening. Series test of cluster analysis was used to obtain significant trending models. Based on the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes databases, functional and pathway enrichment analysis were processed and a pathway relation network was constructed. Gene co-expression network and gene signal network were constructed for common DEGs. The DEGs with the same trend were clustered and in total, 16 clusters with statistical significance were obtained. The screened DEGs were enriched into small molecule metabolic process and metabolic pathways. The pathway relation network was constructed with 57 nodes. A total of 328 common DEGs were obtained. Gene signal network was constructed with 71 nodes. Gene co-expression network was constructed with 161 nodes and 211 edges. ABCD3, CPT2, AGL and JAM2 are potential biomarkers for the diagnosis of colon cancer. PMID:29928385

Gene expression profiling data of Schizosaccharomyces pombe under nitrosative stress using differential display.

PubMed

Biswas, Pranjal; Majumdar, Uddalak; Ghosh, Sanjay

2016-03-01

Excess production of nitric oxide (NO) and reactive nitrogen intermediates (RNIs) causes nitrosative stress on cells. Schizosaccharomyces pombe was used as a model to study nitrosative stress response. In the present data article, we have used differential display to identify the differentially expressed genes in the fission yeast under nitrosative stress conditions. We have used pure NO donor compound detaNONOate at final concentrations of 0.1 mM and 1 mM to treat the cells for 15 min alongside control before studying their gene expression profiles. At both the treated conditions, we identified genes which were commonly repressed while several genes were induced upon both 0.1 mM and 1 mM treatments. The differentially expressed genes were further analyzed in DAVID and categorized into several different pathways.

Unravelling the neurophysiological basis of aggression in a fish model

PubMed Central

2010-01-01

Background Aggression is a near-universal behaviour with substantial influence on and implications for human and animal social systems. The neurophysiological basis of aggression is, however, poorly understood in all species and approaches adopted to study this complex behaviour have often been oversimplified. We applied targeted expression profiling on 40 genes, spanning eight neurological pathways and in four distinct regions of the brain, in combination with behavioural observations and pharmacological manipulations, to screen for regulatory pathways of aggression in the zebrafish (Danio rerio), an animal model in which social rank and aggressiveness tightly correlate. Results Substantial differences occurred in gene expression profiles between dominant and subordinate males associated with phenotypic differences in aggressiveness and, for the chosen gene set, they occurred mainly in the hypothalamus and telencephalon. The patterns of differentially-expressed genes implied multifactorial control of aggression in zebrafish, including the hypothalamo-neurohypophysial-system, serotonin, somatostatin, dopamine, hypothalamo-pituitary-interrenal, hypothalamo-pituitary-gonadal and histamine pathways, and the latter is a novel finding outside mammals. Pharmacological manipulations of various nodes within the hypothalamo-neurohypophysial-system and serotonin pathways supported their functional involvement. We also observed differences in expression profiles in the brains of dominant versus subordinate females that suggested sex-conserved control of aggression. For example, in the HNS pathway, the gene encoding arginine vasotocin (AVT), previously believed specific to male behaviours, was amongst those genes most associated with aggression, and AVT inhibited dominant female aggression, as in males. However, sex-specific differences in the expression profiles also occurred, including differences in aggression-associated tryptophan hydroxylases and estrogen receptors. Conclusions Thus, through an integrated approach, combining gene expression profiling, behavioural analyses, and pharmacological manipulations, we identified candidate genes and pathways that appear to play significant roles in regulating aggression in fish. Many of these are novel for non-mammalian systems. We further present a validated system for advancing our understanding of the mechanistic underpinnings of complex behaviours using a fish model. PMID:20846403

Gene expression signature of cerebellar hypoplasia in a mouse model of Down syndrome during postnatal development

PubMed Central

Laffaire, Julien; Rivals, Isabelle; Dauphinot, Luce; Pasteau, Fabien; Wehrle, Rosine; Larrat, Benoit; Vitalis, Tania; Moldrich, Randal X; Rossier, Jean; Sinkus, Ralph; Herault, Yann; Dusart, Isabelle; Potier, Marie-Claude

2009-01-01

Background Down syndrome is a chromosomal disorder caused by the presence of three copies of chromosome 21. The mechanisms by which this aneuploidy produces the complex and variable phenotype observed in people with Down syndrome are still under discussion. Recent studies have demonstrated an increased transcript level of the three-copy genes with some dosage compensation or amplification for a subset of them. The impact of this gene dosage effect on the whole transcriptome is still debated and longitudinal studies assessing the variability among samples, tissues and developmental stages are needed. Results We thus designed a large scale gene expression study in mice (the Ts1Cje Down syndrome mouse model) in which we could measure the effects of trisomy 21 on a large number of samples (74 in total) in a tissue that is affected in Down syndrome (the cerebellum) and where we could quantify the defect during postnatal development in order to correlate gene expression changes to the phenotype observed. Statistical analysis of microarray data revealed a major gene dosage effect: for the three-copy genes as well as for a 2 Mb segment from mouse chromosome 12 that we show for the first time as being deleted in the Ts1Cje mice. This gene dosage effect impacts moderately on the expression of euploid genes (2.4 to 7.5% differentially expressed). Only 13 genes were significantly dysregulated in Ts1Cje mice at all four postnatal development stages studied from birth to 10 days after birth, and among them are 6 three-copy genes. The decrease in granule cell proliferation demonstrated in newborn Ts1Cje cerebellum was correlated with a major gene dosage effect on the transcriptome in dissected cerebellar external granule cell layer. Conclusion High throughput gene expression analysis in the cerebellum of a large number of samples of Ts1Cje and euploid mice has revealed a prevailing gene dosage effect on triplicated genes. Moreover using an enriched cell population that is thought responsible for the cerebellar hypoplasia in Down syndrome, a global destabilization of gene expression was not detected. Altogether these results strongly suggest that the three-copy genes are directly responsible for the phenotype present in cerebellum. We provide here a short list of candidate genes. PMID:19331679

Effect of resveratrol analogue, DMU-212, on antioxidant status and apoptosis-related genes in rat model of hepatocarcinogenesis.

PubMed

Piotrowska, H; Kujawska, M; Nowicki, M; Petzke, E; Ignatowicz, E; Krajka-Kuźniak, V; Zawierucha, P; Wierzchowski, M; Murias, M; Jodynis-Liebert, J

2017-02-01

The aim of the study was to examine whether antioxidant properties of 3,4,4',5-tetramethoxystilbene (DMU-212) contribute to its anticarcinogenic activity and whether DMU-212 affects the expression of apoptosis-related genes. Two-stage model of hepatocarcinogenesis was used; male Wistar rats were challenged with N-nitrosodiethylamine (NDEA), 200 mg/kg body weight (b.w.), intraperitoneal, then phenobarbital (PB) in drinking water (0.05%) was administered. Simultaneously, DMU-212 was given per os at a dose 20 or 50 mg/kg b.w. two times a week for 16 weeks. DMU-212 caused a moderate decrease in hepatic thiobarbituric acid reactive substances and protein carbonyls concentration elevated in rats treated with NDEA/PB. The activity of antioxidant enzymes examined reduced by NDEA/PB treatment was not restored in rats coadministered with DMU-212. Effects of DMU-212 on messenger RNA (mRNA) expression of antioxidant enzymes in rats challenged with NDEA/PB were diversified; no changes in their protein expression were noted in any of the groups. The expression of 17,000 genes was analyzed by Affymetrix® Rat Gene 1.1 ST Array; 15 apoptosis-related genes were selected and validated by RT-q PCR. The combined treatment with NDEA/PB and DMU-212 increased the mRNA level of some genes driving mitochondria-mediated apoptosis, whereas the mRNA expression of some anti-apoptotic genes triggering receptor-mediated apoptosis was reduced. The expression of genes encoding caspases-4, -8, -9, and -12 was also increased in rats treated with DMU-212. Although antioxidant effect of DMU-212 in rats challenged with NDEA/PB was moderate, its potential anticarcinogenic properties were demonstrated as evidenced by modulation of apoptosis-related genes.

Effect of simulated microgravity on oxidation-sensitive gene expression in PC12 cells

NASA Astrophysics Data System (ADS)

Kwon, Ohwon; Sartor, Maureen; Tomlinson, Craig R.; Millard, Ronald W.; Olah, Mark E.; Sankovic, John M.; Banerjee, Rupak K.

2006-01-01

Oxygen utilization by and oxygen dependence of cellular processes may be different in biological systems that are exposed to microgravity (micro-g). A baseline in which cellular changes in oxygen sensitive molecular processes occur during micro-g conditions would be important to pursue this question. The objective of this research is to analyze oxidation-sensitive gene expression in a model cell line [rat pheochromocytoma (PC12)] under simulated micro-g conditions. The PC12 cell line is well characterized in its response to oxygen, and is widely recognized as a sensitive model for studying the responses of oxygen-sensitive molecular and cellular processes. This study uses the rotating wall vessel bioreactor (RWV) designed at NASA to simulate micro-g. Gene expression in PC12 cells in response to micro-g was analyzed by DNA microarray technology. The microarray analysis of PC12 cells cultured for 4 days under simulated micro-g under standardized oxygen environment conditions revealed more than 100 genes whose expression levels were changed at least twofold (up-regulation of 65 genes and down-regulation of 39 genes) compared with those from cells in the unit gravity (unit-g) control. This study observed that genes involved in the oxidoreductase activity category were most significantly differentially expressed under micro-g conditions. Also, known oxidation-sensitive transcription factors such as hypoxia-inducible factor-2α, c-myc, and the peroxisome proliferator-activated receptor-γ were changed significantly. Our initial results from the gene expression microarray studies may provide a context in which to evaluate the effect of varying oxygen environments on the background of differential gene regulation of biological processes under variable gravity conditions.