Geographical Genomics of Human Leukocyte Gene Expression Variation in Southern Morocco

PubMed Central

Idaghdour, Youssef; Czika, Wendy; Shianna, Kevin V.; Lee, S. Hong; Visscher, Peter M.; Martin, Hilary C.; Miclaus, Kelci; Jadallah, Sami J.; Goldstein, David B.; Wolfinger, Russell D.; Gibson, Greg

2009-01-01

Studies of the genetics of gene expression reveal expression SNPs that explain variation in transcript abundance. Here we address the robustness of eSNP associations to environmental geography and population structure in a comparison of 194 Arab and Amazigh individuals from a city and two villages in southern Morocco. Gene expression differed between pairs of locations for up to a third of all transcripts, with notable enrichment for ribosomal biosynthesis and oxidative phosphorylation. Robust associations were observed in the leukocyte samples with cis-eSNPs (P < 10−08) for 346 genes, and trans-eSNPs (P < 10−11) with 10 genes. All of these were consistent across the three sample locations and after controlling for ethnicity and relatedness. No evidence for large-effect trans-acting mediators of the pervasive environmental influence was found and instead genetic and environmental factors acted in a largely additive manner. PMID:19966804

Analysis of gene network robustness based on saturated fixed point attractors

PubMed Central

2014-01-01

The analysis of gene network robustness to noise and mutation is important for fundamental and practical reasons. Robustness refers to the stability of the equilibrium expression state of a gene network to variations of the initial expression state and network topology. Numerical simulation of these variations is commonly used for the assessment of robustness. Since there exists a great number of possible gene network topologies and initial states, even millions of simulations may be still too small to give reliable results. When the initial and equilibrium expression states are restricted to being saturated (i.e., their elements can only take values 1 or −1 corresponding to maximum activation and maximum repression of genes), an analytical gene network robustness assessment is possible. We present this analytical treatment based on determination of the saturated fixed point attractors for sigmoidal function models. The analysis can determine (a) for a given network, which and how many saturated equilibrium states exist and which and how many saturated initial states converge to each of these saturated equilibrium states and (b) for a given saturated equilibrium state or a given pair of saturated equilibrium and initial states, which and how many gene networks, referred to as viable, share this saturated equilibrium state or the pair of saturated equilibrium and initial states. We also show that the viable networks sharing a given saturated equilibrium state must follow certain patterns. These capabilities of the analytical treatment make it possible to properly define and accurately determine robustness to noise and mutation for gene networks. Previous network research conclusions drawn from performing millions of simulations follow directly from the results of our analytical treatment. Furthermore, the analytical results provide criteria for the identification of model validity and suggest modified models of gene network dynamics. The yeast cell-cycle network is used as an illustration of the practical application of this analytical treatment. PMID:24650364

FARO server: Meta-analysis of gene expression by matching gene expression signatures to a compendium of public gene expression data.

PubMed

Manijak, Mieszko P; Nielsen, Henrik B

2011-06-11

Although, systematic analysis of gene annotation is a powerful tool for interpreting gene expression data, it sometimes is blurred by incomplete gene annotation, missing expression response of key genes and secondary gene expression responses. These shortcomings may be partially circumvented by instead matching gene expression signatures to signatures of other experiments. To facilitate this we present the Functional Association Response by Overlap (FARO) server, that match input signatures to a compendium of 242 gene expression signatures, extracted from more than 1700 Arabidopsis microarray experiments. Hereby we present a publicly available tool for robust characterization of Arabidopsis gene expression experiments which can point to similar experimental factors in other experiments. The server is available at http://www.cbs.dtu.dk/services/faro/.

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

Robust, synergistic regulation of human gene expression using TALE activators.

PubMed

Maeder, Morgan L; Linder, Samantha J; Reyon, Deepak; Angstman, James F; Fu, Yanfang; Sander, Jeffry D; Joung, J Keith

2013-03-01

Artificial activators designed using transcription activator-like effector (TALE) technology have broad utility, but previous studies suggest that these monomeric proteins often exhibit low activities. Here we demonstrate that TALE activators can robustly function individually or in synergistic combinations to increase expression of endogenous human genes over wide dynamic ranges. These findings will encourage applications of TALE activators for research and therapy, and guide design of monomeric TALE-based fusion proteins.

Global transcriptional regulatory network for Escherichia coli robustly connects gene expression to transcription factor activities

PubMed Central

Fang, Xin; Sastry, Anand; Mih, Nathan; Kim, Donghyuk; Tan, Justin; Lloyd, Colton J.; Gao, Ye; Yang, Laurence; Palsson, Bernhard O.

2017-01-01

Transcriptional regulatory networks (TRNs) have been studied intensely for >25 y. Yet, even for the Escherichia coli TRN—probably the best characterized TRN—several questions remain. Here, we address three questions: (i) How complete is our knowledge of the E. coli TRN; (ii) how well can we predict gene expression using this TRN; and (iii) how robust is our understanding of the TRN? First, we reconstructed a high-confidence TRN (hiTRN) consisting of 147 transcription factors (TFs) regulating 1,538 transcription units (TUs) encoding 1,764 genes. The 3,797 high-confidence regulatory interactions were collected from published, validated chromatin immunoprecipitation (ChIP) data and RegulonDB. For 21 different TF knockouts, up to 63% of the differentially expressed genes in the hiTRN were traced to the knocked-out TF through regulatory cascades. Second, we trained supervised machine learning algorithms to predict the expression of 1,364 TUs given TF activities using 441 samples. The algorithms accurately predicted condition-specific expression for 86% (1,174 of 1,364) of the TUs, while 193 TUs (14%) were predicted better than random TRNs. Third, we identified 10 regulatory modules whose definitions were robust against changes to the TRN or expression compendium. Using surrogate variable analysis, we also identified three unmodeled factors that systematically influenced gene expression. Our computational workflow comprehensively characterizes the predictive capabilities and systems-level functions of an organism’s TRN from disparate data types. PMID:28874552

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.

(Im)Perfect robustness and adaptation of metabolic networks subject to metabolic and gene-expression regulation: marrying control engineering with metabolic control analysis.

PubMed

He, Fei; Fromion, Vincent; Westerhoff, Hans V

2013-11-21

Metabolic control analysis (MCA) and supply-demand theory have led to appreciable understanding of the systems properties of metabolic networks that are subject exclusively to metabolic regulation. Supply-demand theory has not yet considered gene-expression regulation explicitly whilst a variant of MCA, i.e. Hierarchical Control Analysis (HCA), has done so. Existing analyses based on control engineering approaches have not been very explicit about whether metabolic or gene-expression regulation would be involved, but designed different ways in which regulation could be organized, with the potential of causing adaptation to be perfect. This study integrates control engineering and classical MCA augmented with supply-demand theory and HCA. Because gene-expression regulation involves time integration, it is identified as a natural instantiation of the 'integral control' (or near integral control) known in control engineering. This study then focuses on robustness against and adaptation to perturbations of process activities in the network, which could result from environmental perturbations, mutations or slow noise. It is shown however that this type of 'integral control' should rarely be expected to lead to the 'perfect adaptation': although the gene-expression regulation increases the robustness of important metabolite concentrations, it rarely makes them infinitely robust. For perfect adaptation to occur, the protein degradation reactions should be zero order in the concentration of the protein, which may be rare biologically for cells growing steadily. A proposed new framework integrating the methodologies of control engineering and metabolic and hierarchical control analysis, improves the understanding of biological systems that are regulated both metabolically and by gene expression. In particular, the new approach enables one to address the issue whether the intracellular biochemical networks that have been and are being identified by genomics and systems biology, correspond to the 'perfect' regulatory structures designed by control engineering vis-à-vis optimal functions such as robustness. To the extent that they are not, the analyses suggest how they may become so and this in turn should facilitate synthetic biology and metabolic engineering.

(Im)Perfect robustness and adaptation of metabolic networks subject to metabolic and gene-expression regulation: marrying control engineering with metabolic control analysis

PubMed Central

2013-01-01

Background Metabolic control analysis (MCA) and supply–demand theory have led to appreciable understanding of the systems properties of metabolic networks that are subject exclusively to metabolic regulation. Supply–demand theory has not yet considered gene-expression regulation explicitly whilst a variant of MCA, i.e. Hierarchical Control Analysis (HCA), has done so. Existing analyses based on control engineering approaches have not been very explicit about whether metabolic or gene-expression regulation would be involved, but designed different ways in which regulation could be organized, with the potential of causing adaptation to be perfect. Results This study integrates control engineering and classical MCA augmented with supply–demand theory and HCA. Because gene-expression regulation involves time integration, it is identified as a natural instantiation of the ‘integral control’ (or near integral control) known in control engineering. This study then focuses on robustness against and adaptation to perturbations of process activities in the network, which could result from environmental perturbations, mutations or slow noise. It is shown however that this type of ‘integral control’ should rarely be expected to lead to the ‘perfect adaptation’: although the gene-expression regulation increases the robustness of important metabolite concentrations, it rarely makes them infinitely robust. For perfect adaptation to occur, the protein degradation reactions should be zero order in the concentration of the protein, which may be rare biologically for cells growing steadily. Conclusions A proposed new framework integrating the methodologies of control engineering and metabolic and hierarchical control analysis, improves the understanding of biological systems that are regulated both metabolically and by gene expression. In particular, the new approach enables one to address the issue whether the intracellular biochemical networks that have been and are being identified by genomics and systems biology, correspond to the ‘perfect’ regulatory structures designed by control engineering vis-à-vis optimal functions such as robustness. To the extent that they are not, the analyses suggest how they may become so and this in turn should facilitate synthetic biology and metabolic engineering. PMID:24261908

Robust and sparse correlation matrix estimation for the analysis of high-dimensional genomics data.

PubMed

Serra, Angela; Coretto, Pietro; Fratello, Michele; Tagliaferri, Roberto; Stegle, Oliver

2018-02-15

Microarray technology can be used to study the expression of thousands of genes across a number of different experimental conditions, usually hundreds. The underlying principle is that genes sharing similar expression patterns, across different samples, can be part of the same co-expression system, or they may share the same biological functions. Groups of genes are usually identified based on cluster analysis. Clustering methods rely on the similarity matrix between genes. A common choice to measure similarity is to compute the sample correlation matrix. Dimensionality reduction is another popular data analysis task which is also based on covariance/correlation matrix estimates. Unfortunately, covariance/correlation matrix estimation suffers from the intrinsic noise present in high-dimensional data. Sources of noise are: sampling variations, presents of outlying sample units, and the fact that in most cases the number of units is much larger than the number of genes. In this paper, we propose a robust correlation matrix estimator that is regularized based on adaptive thresholding. The resulting method jointly tames the effects of the high-dimensionality, and data contamination. Computations are easy to implement and do not require hand tunings. Both simulated and real data are analyzed. A Monte Carlo experiment shows that the proposed method is capable of remarkable performances. Our correlation metric is more robust to outliers compared with the existing alternatives in two gene expression datasets. It is also shown how the regularization allows to automatically detect and filter spurious correlations. The same regularization is also extended to other less robust correlation measures. Finally, we apply the ARACNE algorithm on the SyNTreN gene expression data. Sensitivity and specificity of the reconstructed network is compared with the gold standard. We show that ARACNE performs better when it takes the proposed correlation matrix estimator as input. The R software is available at https://github.com/angy89/RobustSparseCorrelation. aserra@unisa.it or robtag@unisa.it. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Robust transcriptional tumor signatures applicable to both formalin-fixed paraffin-embedded and fresh-frozen samples

PubMed Central

Cheng, Jun; He, Jun; Liu, Huaping; Cai, Hao; Hong, Guini; Zhang, Jiahui; Li, Na; Ao, Lu; Guo, Zheng

2017-01-01

Formalin-fixed paraffin-embedded (FFPE) samples represent a valuable resource for clinical researches. However, FFPE samples are usually considered an unreliable source for gene expression analysis due to the partial RNA degradation. In this study, through comparing gene expression profiles between FFPE samples and paired fresh-frozen (FF) samples for three cancer types, we firstly showed that expression measurements of thousands of genes had at least two-fold change in FFPE samples compared with paired FF samples. Therefore, for a transcriptional signature based on risk scores summarized from the expression levels of the signature genes, the risk score thresholds trained from FFPE (or FF) samples could not be applied to FF (or FFPE) samples. On the other hand, we found that more than 90% of the relative expression orderings (REOs) of gene pairs in the FF samples were maintained in their paired FFPE samples and largely unaffected by the storage time. The result suggested that the REOs of gene pairs were highly robust against partial RNA degradation in FFPE samples. Finally, as a case study, we developed a REOs-based signature to distinguish liver cirrhosis from hepatocellular carcinoma (HCC) using FFPE samples. The signature was validated in four datasets of FFPE samples and eight datasets of FF samples. In conclusion, the valuable FFPE samples can be fully exploited to identify REOs-based diagnostic and prognostic signatures which could be robustly applicable to both FF samples and FFPE samples with degraded RNA. PMID:28036264

The Influence of Assortativity on the Robustness of Signal-Integration Logic in Gene Regulatory Networks

PubMed Central

Pechenick, Dov A.; Payne, Joshua L.; Moore, Jason H.

2011-01-01

Gene regulatory networks (GRNs) drive the cellular processes that sustain life. To do so reliably, GRNs must be robust to perturbations, such as gene deletion and the addition or removal of regulatory interactions. GRNs must also be robust to genetic changes in regulatory regions that define the logic of signal-integration, as these changes can affect how specific combinations of regulatory signals are mapped to particular gene expression states. Previous theoretical analyses have demonstrated that the robustness of a GRN is influenced by its underlying topological properties, such as degree distribution and modularity. Another important topological property is assortativity, which measures the propensity with which nodes of similar connectivity are connected to one another. How assortativity influences the robustness of the signal-integration logic of GRNs remains an open question. Here, we use computational models of GRNs to investigate this relationship. We separately consider each of the three dynamical regimes of this model for a variety of degree distributions. We find that in the chaotic regime, robustness exhibits a pronounced increase as assortativity becomes more positive, while in the critical and ordered regimes, robustness is generally less sensitive to changes in assortativity. We attribute the increased robustness to a decrease in the duration of the gene expression pattern, which is caused by a reduction in the average size of a GRN’s in-components. This study provides the first direct evidence that assortativity influences the robustness of the signal-integration logic of computational models of GRNs, illuminates a mechanistic explanation for this influence, and furthers our understanding of the relationship between topology and robustness in complex biological systems. PMID:22155134

Systems analysis of transcriptome data provides new hypotheses about Arabidopsis root response to nitrate treatments

PubMed Central

Canales, Javier; Moyano, Tomás C.; Villarroel, Eva; Gutiérrez, Rodrigo A.

2014-01-01

Nitrogen (N) is an essential macronutrient for plant growth and development. Plants adapt to changes in N availability partly by changes in global gene expression. We integrated publicly available root microarray data under contrasting nitrate conditions to identify new genes and functions important for adaptive nitrate responses in Arabidopsis thaliana roots. Overall, more than 2000 genes exhibited changes in expression in response to nitrate treatments in Arabidopsis thaliana root organs. Global regulation of gene expression by nitrate depends largely on the experimental context. However, despite significant differences from experiment to experiment in the identity of regulated genes, there is a robust nitrate response of specific biological functions. Integrative gene network analysis uncovered relationships between nitrate-responsive genes and 11 highly co-expressed gene clusters (modules). Four of these gene network modules have robust nitrate responsive functions such as transport, signaling, and metabolism. Network analysis hypothesized G2-like transcription factors are key regulatory factors controlling transport and signaling functions. Our meta-analysis highlights the role of biological processes not studied before in the context of the nitrate response such as root hair development and provides testable hypothesis to advance our understanding of nitrate responses in plants. PMID:24570678

Robust diagnosis of non-Hodgkin lymphoma phenotypes validated on gene expression data from different laboratories.

PubMed

Bhanot, Gyan; Alexe, Gabriela; Levine, Arnold J; Stolovitzky, Gustavo

2005-01-01

A major challenge in cancer diagnosis from microarray data is the need for robust, accurate, classification models which are independent of the analysis techniques used and can combine data from different laboratories. We propose such a classification scheme originally developed for phenotype identification from mass spectrometry data. The method uses a robust multivariate gene selection procedure and combines the results of several machine learning tools trained on raw and pattern data to produce an accurate meta-classifier. We illustrate and validate our method by applying it to gene expression datasets: the oligonucleotide HuGeneFL microarray dataset of Shipp et al. (www.genome.wi.mit.du/MPR/lymphoma) and the Hu95Av2 Affymetrix dataset (DallaFavera's laboratory, Columbia University). Our pattern-based meta-classification technique achieves higher predictive accuracies than each of the individual classifiers , is robust against data perturbations and provides subsets of related predictive genes. Our techniques predict that combinations of some genes in the p53 pathway are highly predictive of phenotype. In particular, we find that in 80% of DLBCL cases the mRNA level of at least one of the three genes p53, PLK1 and CDK2 is elevated, while in 80% of FL cases, the mRNA level of at most one of them is elevated.

Configurations of a two-tiered amplified gene expression system in adenoviral vectors designed to improve the specificity of in vivo prostate cancer imaging

PubMed Central

Sato, M; Figueiredo, ML; Burton, JB; Johnson, M; Chen, M; Powell, R; Gambhir, SS; Carey, M; Wu, L

2009-01-01

Effective treatment for recurrent, disseminated prostate cancer is notably limited. We have developed adenoviral vectors with a prostate-specific two-step transcriptional amplification (TSTA) system that would express therapeutic genes at a robust level to target metastatic disease. The TSTA system employs the prostate-specific antigen (PSA) promoter/enhancer to drive a potent synthetic activator, which in turn activates the expression of the therapeutic gene. In this study, we explored different configurations of this bipartite system and discovered that physical separation of the two TSTA components into E1 and E3 regions of adenovirus was able to enhance androgen regulation and cell-discriminatory expression. The TSTA vectors that express imaging reporter genes were assessed by noninvasive imaging technologies in animal models. The improved selectivity of the E1E3 configured vector was reflected in silenced ectopic expression in the lung. Significantly, the enhanced specificity of the E1E3 vector enabled the detection of lung metastasis of prostate cancer. An E1E3 TSTA vector that expresses the herpes simplex virus thymidine kinase gene can effectively direct positron emission tomography (PET) imaging of the tumor. The prostate-targeted gene delivery vectors with robust and cell-specific expression capability will advance the development of safe and effective imaging guided therapy for recurrent metastatic stages of prostate cancer. PMID:18305574

Genome-wide screen identifies a novel prognostic signature for breast cancer survival

DOE PAGES

Mao, Xuan Y.; Lee, Matthew J.; Zhu, Jeffrey; ...

2017-01-21

Large genomic datasets in combination with clinical data can be used as an unbiased tool to identify genes important in patient survival and discover potential therapeutic targets. We used a genome-wide screen to identify 587 genes significantly and robustly deregulated across four independent breast cancer (BC) datasets compared to normal breast tissue. Gene expression of 381 genes was significantly associated with relapse-free survival (RFS) in BC patients. We used a gene co-expression network approach to visualize the genetic architecture in normal breast and BCs. In normal breast tissue, co-expression cliques were identified enriched for cell cycle, gene transcription, cell adhesion,more » cytoskeletal organization and metabolism. In contrast, in BC, only two major co-expression cliques were identified enriched for cell cycle-related processes or blood vessel development, cell adhesion and mammary gland development processes. Interestingly, gene expression levels of 7 genes were found to be negatively correlated with many cell cycle related genes, highlighting these genes as potential tumor suppressors and novel therapeutic targets. A forward-conditional Cox regression analysis was used to identify a 12-gene signature associated with RFS. A prognostic scoring system was created based on the 12-gene signature. This scoring system robustly predicted BC patient RFS in 60 sampling test sets and was further validated in TCGA and METABRIC BC data. Our integrated study identified a 12-gene prognostic signature that could guide adjuvant therapy for BC patients and includes novel potential molecular targets for therapy.« less

Genome-wide screen identifies a novel prognostic signature for breast cancer survival

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

Mao, Xuan Y.; Lee, Matthew J.; Zhu, Jeffrey

Large genomic datasets in combination with clinical data can be used as an unbiased tool to identify genes important in patient survival and discover potential therapeutic targets. We used a genome-wide screen to identify 587 genes significantly and robustly deregulated across four independent breast cancer (BC) datasets compared to normal breast tissue. Gene expression of 381 genes was significantly associated with relapse-free survival (RFS) in BC patients. We used a gene co-expression network approach to visualize the genetic architecture in normal breast and BCs. In normal breast tissue, co-expression cliques were identified enriched for cell cycle, gene transcription, cell adhesion,more » cytoskeletal organization and metabolism. In contrast, in BC, only two major co-expression cliques were identified enriched for cell cycle-related processes or blood vessel development, cell adhesion and mammary gland development processes. Interestingly, gene expression levels of 7 genes were found to be negatively correlated with many cell cycle related genes, highlighting these genes as potential tumor suppressors and novel therapeutic targets. A forward-conditional Cox regression analysis was used to identify a 12-gene signature associated with RFS. A prognostic scoring system was created based on the 12-gene signature. This scoring system robustly predicted BC patient RFS in 60 sampling test sets and was further validated in TCGA and METABRIC BC data. Our integrated study identified a 12-gene prognostic signature that could guide adjuvant therapy for BC patients and includes novel potential molecular targets for therapy.« less

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.

SpeCond: a method to detect condition-specific gene expression

PubMed Central

2011-01-01

Transcriptomic studies routinely measure expression levels across numerous conditions. These datasets allow identification of genes that are specifically expressed in a small number of conditions. However, there are currently no statistically robust methods for identifying such genes. Here we present SpeCond, a method to detect condition-specific genes that outperforms alternative approaches. We apply the method to a dataset of 32 human tissues to determine 2,673 specifically expressed genes. An implementation of SpeCond is freely available as a Bioconductor package at http://www.bioconductor.org/packages/release/bioc/html/SpeCond.html. PMID:22008066

An Optimal Mean Based Block Robust Feature Extraction Method to Identify Colorectal Cancer Genes with Integrated Data.

PubMed

Liu, Jian; Cheng, Yuhu; Wang, Xuesong; Zhang, Lin; Liu, Hui

2017-08-17

It is urgent to diagnose colorectal cancer in the early stage. Some feature genes which are important to colorectal cancer development have been identified. However, for the early stage of colorectal cancer, less is known about the identity of specific cancer genes that are associated with advanced clinical stage. In this paper, we conducted a feature extraction method named Optimal Mean based Block Robust Feature Extraction method (OMBRFE) to identify feature genes associated with advanced colorectal cancer in clinical stage by using the integrated colorectal cancer data. Firstly, based on the optimal mean and L 2,1 -norm, a novel feature extraction method called Optimal Mean based Robust Feature Extraction method (OMRFE) is proposed to identify feature genes. Then the OMBRFE method which introduces the block ideology into OMRFE method is put forward to process the colorectal cancer integrated data which includes multiple genomic data: copy number alterations, somatic mutations, methylation expression alteration, as well as gene expression changes. Experimental results demonstrate that the OMBRFE is more effective than previous methods in identifying the feature genes. Moreover, genes identified by OMBRFE are verified to be closely associated with advanced colorectal cancer in clinical stage.

Dual regulation of gene expression mediated by extended MAPK activation and salicylic acid contributes to robust innate immunity in Arabidopsis thaliana.

PubMed

Tsuda, Kenichi; Mine, Akira; Bethke, Gerit; Igarashi, Daisuke; Botanga, Christopher J; Tsuda, Yayoi; Glazebrook, Jane; Sato, Masanao; Katagiri, Fumiaki

2013-01-01

Network robustness is a crucial property of the plant immune signaling network because pathogens are under a strong selection pressure to perturb plant network components to dampen plant immune responses. Nevertheless, modulation of network robustness is an area of network biology that has rarely been explored. While two modes of plant immunity, Effector-Triggered Immunity (ETI) and Pattern-Triggered Immunity (PTI), extensively share signaling machinery, the network output is much more robust against perturbations during ETI than PTI, suggesting modulation of network robustness. Here, we report a molecular mechanism underlying the modulation of the network robustness in Arabidopsis thaliana. The salicylic acid (SA) signaling sector regulates a major portion of the plant immune response and is important in immunity against biotrophic and hemibiotrophic pathogens. In Arabidopsis, SA signaling was required for the proper regulation of the vast majority of SA-responsive genes during PTI. However, during ETI, regulation of most SA-responsive genes, including the canonical SA marker gene PR1, could be controlled by SA-independent mechanisms as well as by SA. The activation of the two immune-related MAPKs, MPK3 and MPK6, persisted for several hours during ETI but less than one hour during PTI. Sustained MAPK activation was sufficient to confer SA-independent regulation of most SA-responsive genes. Furthermore, the MPK3 and SA signaling sectors were compensatory to each other for inhibition of bacterial growth as well as for PR1 expression during ETI. These results indicate that the duration of the MAPK activation is a critical determinant for modulation of robustness of the immune signaling network. Our findings with the plant immune signaling network imply that the robustness level of a biological network can be modulated by the activities of network components.

Optimized Sleeping Beauty transposons rapidly generate stable transgenic cell lines.

PubMed

Kowarz, Eric; Löscher, Denise; Marschalek, Rolf

2015-04-01

Stable gene expression in mammalian cells is a prerequisite for many in vitro and in vivo experiments. However, either the integration of plasmids into mammalian genomes or the use of retro-/lentiviral systems have intrinsic limitations. The use of transposable elements, e.g. the Sleeping Beauty system (SB), circumvents most of these drawbacks (integration sites, size limitations) and allows the quick generation of stable cell lines. The integration process of SB is catalyzed by a transposase and the handling of this gene transfer system is easy, fast and safe. Here, we report our improvements made to the existing SB vector system and present two new vector types for robust constitutive or inducible expression of any gene of interest. Both types are available in 16 variants with different selection marker (puromycin, hygromycin, blasticidin, neomycin) and fluorescent protein expression (GFP, RFP, BFP) to fit most experimental requirements. With this system it is possible to generate cell lines from stable transfected cells quickly and reliably in a medium-throughput setting (three to five days). Cell lines robustly express any gene-of-interest, either constitutively or tightly regulated by doxycycline. This allows many laboratory experiments to speed up generation of data in a rapid and robust manner. Copyright © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Robust patterning of gene expression based on internal coordinate system of cells.

PubMed

Ogawa, Ken-ichiro; Miyake, Yoshihiro

2015-06-01

Cell-to-cell communication in multicellular organisms is established through the transmission of various kinds of chemical substances such as proteins. It is well known that gene expression triggered by a chemical substance in individuals has stable spatial patterns despite the individual differences in concentration patterns of the chemical substance. This fact reveals an important property of multicellular organisms called "robustness", which allows the organisms to generate their forms while maintaining proportion. Robustness has been conventionally accounted for by the stability of solutions of dynamical equations that represent a specific interaction network of chemical substances. However, any biological system is composed of autonomous elements. In general, an autonomous element does not merely accept information on the chemical substance from the environment; instead, it accepts the information based on its own criteria for reaction. Therefore, this phenomenon needs to be considered from the viewpoint of cells. Such a viewpoint is expected to allow the consideration of the autonomy of cells in multicellular organisms. This study aims to explain theoretically the robust patterning of gene expression from the viewpoint of cells. For this purpose, we introduced a new operator for transforming a state variable of a chemical substance from an external coordinate system to an internal coordinate system of each cell, which describes the observation of the chemical substance by cells. We then applied this operator to the simplest reaction-diffusion model of the chemical substance to investigate observation effects by cells. Our mathematical analysis of this extended model indicates that the robust patterning of gene expression against individual differences in concentration pattern of the chemical substance can be explained from the viewpoint of cells if there is a regulation field that compensates for the difference between cells seen in the observation results. This result provides a new insight into the investigation of the mechanism of robust patterning in biological systems composed of individual elements. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

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.

Using Public Data for Comparative Proteome Analysis in Precision Medicine Programs.

PubMed

Hughes, Christopher S; Morin, Gregg B

2018-03-01

Maximizing the clinical utility of information obtained in longitudinal precision medicine programs would benefit from robust comparative analyses to known information to assess biological features of patient material toward identifying the underlying features driving their disease phenotype. Herein, the potential for utilizing publically deposited mass-spectrometry-based proteomics data to perform inter-study comparisons of cell-line or tumor-tissue materials is investigated. To investigate the robustness of comparison between MS-based proteomics studies carried out with different methodologies, deposited data representative of label-free (MS1) and isobaric tagging (MS2 and MS3 quantification) are utilized. In-depth quantitative proteomics data acquired from analysis of ovarian cancer cell lines revealed the robust recapitulation of observable gene expression dynamics between individual studies carried out using significantly different methodologies. The observed signatures enable robust inter-study clustering of cell line samples. In addition, the ability to classify and cluster tumor samples based on observed gene expression trends when using a single patient sample is established. With this analysis, relevant gene expression dynamics are obtained from a single patient tumor, in the context of a precision medicine analysis, by leveraging a large cohort of repository data as a comparator. Together, these data establish the potential for state-of-the-art MS-based proteomics data to serve as resources for robust comparative analyses in precision medicine applications. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Bioinforrnatics of Gene Expression Profiling Data Provide Mechanistic Understanding of Acute Ozone-Induced Lung injury

EPA Science Inventory

Acute ozone-induced pulmonary injury and inflammation are well characterized. A few studies have used gene expression profiling to determine the types of changes induced by ozone; however the mechanisms or the pathways involved are less well understood. We presumed that robust bi...

Robust Gaussian Graphical Modeling via l1 Penalization

PubMed Central

Sun, Hokeun; Li, Hongzhe

2012-01-01

Summary Gaussian graphical models have been widely used as an effective method for studying the conditional independency structure among genes and for constructing genetic networks. However, gene expression data typically have heavier tails or more outlying observations than the standard Gaussian distribution. Such outliers in gene expression data can lead to wrong inference on the dependency structure among the genes. We propose a l1 penalized estimation procedure for the sparse Gaussian graphical models that is robustified against possible outliers. The likelihood function is weighted according to how the observation is deviated, where the deviation of the observation is measured based on its own likelihood. An efficient computational algorithm based on the coordinate gradient descent method is developed to obtain the minimizer of the negative penalized robustified-likelihood, where nonzero elements of the concentration matrix represents the graphical links among the genes. After the graphical structure is obtained, we re-estimate the positive definite concentration matrix using an iterative proportional fitting algorithm. Through simulations, we demonstrate that the proposed robust method performs much better than the graphical Lasso for the Gaussian graphical models in terms of both graph structure selection and estimation when outliers are present. We apply the robust estimation procedure to an analysis of yeast gene expression data and show that the resulting graph has better biological interpretation than that obtained from the graphical Lasso. PMID:23020775

Medium-throughput processing of whole mount in situ hybridisation experiments into gene expression domains.

PubMed

Crombach, Anton; Cicin-Sain, Damjan; Wotton, Karl R; Jaeger, Johannes

2012-01-01

Understanding the function and evolution of developmental regulatory networks requires the characterisation and quantification of spatio-temporal gene expression patterns across a range of systems and species. However, most high-throughput methods to measure the dynamics of gene expression do not preserve the detailed spatial information needed in this context. For this reason, quantification methods based on image bioinformatics have become increasingly important over the past few years. Most available approaches in this field either focus on the detailed and accurate quantification of a small set of gene expression patterns, or attempt high-throughput analysis of spatial expression through binary pattern extraction and large-scale analysis of the resulting datasets. Here we present a robust, "medium-throughput" pipeline to process in situ hybridisation patterns from embryos of different species of flies. It bridges the gap between high-resolution, and high-throughput image processing methods, enabling us to quantify graded expression patterns along the antero-posterior axis of the embryo in an efficient and straightforward manner. Our method is based on a robust enzymatic (colorimetric) in situ hybridisation protocol and rapid data acquisition through wide-field microscopy. Data processing consists of image segmentation, profile extraction, and determination of expression domain boundary positions using a spline approximation. It results in sets of measured boundaries sorted by gene and developmental time point, which are analysed in terms of expression variability or spatio-temporal dynamics. Our method yields integrated time series of spatial gene expression, which can be used to reverse-engineer developmental gene regulatory networks across species. It is easily adaptable to other processes and species, enabling the in silico reconstitution of gene regulatory networks in a wide range of developmental contexts.

The Use of a Dexamethasone-inducible System to Synchronize Xa21 Expression to Study Rice Immunity.

PubMed

Caddell, Daniel F; Wei, Tong; Park, Chang-Jin; Ronald, Pamela C

2015-05-05

Inducible gene expression systems offer researchers the opportunity to synchronize target gene expression at particular developmental stages and in particular tissues. The glucocorticoid receptor (GR), a vertebrate steroid receptor, has been well adopted for this purpose in plants. To generate steroid-inducible plants, a construct of GAL4-binding domain-VP16 activation domain-GR fusion (GVG) with the target gene under the control of upstream activation sequence (UAS) has been developed and extensively used in plant research. Immune receptors perceive conserved molecular patterns secreted by pathogens and initiate robust immune responses. The rice immune receptor, XA21 , recognizes a molecular pattern highly conserved in all sequenced genomes of Xanthomonas , and confers robust resistance to X. oryzae pv. oryzae ( Xoo ). However, identifying genes downstream of XA21 has been hindered because of the restrained lesion and thus limited defense response region in the plants expressing Xa21 . Inducible expression allows for a synchronized immune response across a large amount of rice tissue, well suited for studying XA21-mediated immunity by genome-wide approaches such as transcriptomics and proteomics. In this protocol, we describe the use of this GVG system to synchronize Xa21 expression.

The Use of a Dexamethasone-inducible System to Synchronize Xa21 Expression to Study Rice Immunity

PubMed Central

Caddell, Daniel F.; Wei, Tong; Park, Chang-Jin; Ronald, Pamela C.

2016-01-01

Inducible gene expression systems offer researchers the opportunity to synchronize target gene expression at particular developmental stages and in particular tissues. The glucocorticoid receptor (GR), a vertebrate steroid receptor, has been well adopted for this purpose in plants. To generate steroid-inducible plants, a construct of GAL4-binding domain-VP16 activation domain-GR fusion (GVG) with the target gene under the control of upstream activation sequence (UAS) has been developed and extensively used in plant research. Immune receptors perceive conserved molecular patterns secreted by pathogens and initiate robust immune responses. The rice immune receptor, XA21, recognizes a molecular pattern highly conserved in all sequenced genomes of Xanthomonas, and confers robust resistance to X. oryzae pv. oryzae (Xoo). However, identifying genes downstream of XA21 has been hindered because of the restrained lesion and thus limited defense response region in the plants expressing Xa21. Inducible expression allows for a synchronized immune response across a large amount of rice tissue, well suited for studying XA21-mediated immunity by genome-wide approaches such as transcriptomics and proteomics. In this protocol, we describe the use of this GVG system to synchronize Xa21 expression. PMID:27525297

Modeling stochasticity and robustness in gene regulatory networks.

PubMed

Garg, Abhishek; Mohanram, Kartik; Di Cara, Alessandro; De Micheli, Giovanni; Xenarios, Ioannis

2009-06-15

Understanding gene regulation in biological processes and modeling the robustness of underlying regulatory networks is an important problem that is currently being addressed by computational systems biologists. Lately, there has been a renewed interest in Boolean modeling techniques for gene regulatory networks (GRNs). However, due to their deterministic nature, it is often difficult to identify whether these modeling approaches are robust to the addition of stochastic noise that is widespread in gene regulatory processes. Stochasticity in Boolean models of GRNs has been addressed relatively sparingly in the past, mainly by flipping the expression of genes between different expression levels with a predefined probability. This stochasticity in nodes (SIN) model leads to over representation of noise in GRNs and hence non-correspondence with biological observations. In this article, we introduce the stochasticity in functions (SIF) model for simulating stochasticity in Boolean models of GRNs. By providing biological motivation behind the use of the SIF model and applying it to the T-helper and T-cell activation networks, we show that the SIF model provides more biologically robust results than the existing SIN model of stochasticity in GRNs. Algorithms are made available under our Boolean modeling toolbox, GenYsis. The software binaries can be downloaded from http://si2.epfl.ch/ approximately garg/genysis.html.

A comparative view of early development in the corals Favia lizardensis, Ctenactis echinata, and Acropora millepora - morphology, transcriptome, and developmental gene expression.

PubMed

Okubo, Nami; Hayward, David C; Forêt, Sylvain; Ball, Eldon E

2016-02-29

Research into various aspects of coral biology has greatly increased in recent years due to anthropogenic threats to coral health including pollution, ocean warming and acidification. However, knowledge of coral early development has lagged. The present paper describes the embryonic development of two previously uncharacterized robust corals, Favia lizardensis (a massive brain coral) and Ctenactis echinata (a solitary coral) and compares it to that of the previously characterized complex coral, Acropora millepora, both morphologically and in terms of the expression of a set of key developmental genes. Illumina sequencing of mixed age embryos was carried out, resulting in embryonic transcriptomes consisting of 40605 contigs for C.echinata (N50 = 1080 bp) and 48536 contigs for F.lizardensis (N50 = 1496 bp). The transcriptomes have been annotated against Swiss-Prot and were sufficiently complete to enable the identification of orthologs of many key genes controlling development in bilaterians. Developmental series of images of whole mounts and sections reveal that the early stages of both species contain a blastocoel, consistent with their membership of the robust clade. In situ hybridization was used to examine the expression of the developmentally important genes brachyury, chordin and forkhead. The expression of brachyury and forkhead was consistent with that previously reported for Acropora and allowed us to confirm that the pseudo-blastopore sometimes seen in robust corals such as Favia spp. is not directly associated with gastrulation. C.echinata chordin expression, however, differed from that seen in the other two corals. Embryonic transcriptomes were assembled for the brain coral Favia lizardensis and the solitary coral Ctenactis echinata. Both species have a blastocoel in their early developmental stages, consistent with their phylogenetic position as members of the robust clade. Expression of the key developmental genes brachyury, chordin and forkhead was investigated, allowing comparison to that of their orthologs in Acropora, Nematostella and bilaterians and demonstrating that even within the Anthozoa there are significant differences in expression patterns.

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

Analysis of bHLH coding genes using gene co-expression network approach.

PubMed

Srivastava, Swati; Sanchita; Singh, Garima; Singh, Noopur; Srivastava, Gaurava; Sharma, Ashok

2016-07-01

Network analysis provides a powerful framework for the interpretation of data. It uses novel reference network-based metrices for module evolution. These could be used to identify module of highly connected genes showing variation in co-expression network. In this study, a co-expression network-based approach was used for analyzing the genes from microarray data. Our approach consists of a simple but robust rank-based network construction. The publicly available gene expression data of Solanum tuberosum under cold and heat stresses were considered to create and analyze a gene co-expression network. The analysis provide highly co-expressed module of bHLH coding genes based on correlation values. Our approach was to analyze the variation of genes expression, according to the time period of stress through co-expression network approach. As the result, the seed genes were identified showing multiple connections with other genes in the same cluster. Seed genes were found to be vary in different time periods of stress. These analyzed seed genes may be utilized further as marker genes for developing the stress tolerant plant species.

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

PubMed Central

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

2010-01-01

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

Stability of gene expression in human T cells in different gravity environments is clustered in chromosomal region 11p15.4.

PubMed

Thiel, Cora S; Huge, Andreas; Hauschild, Swantje; Tauber, Svantje; Lauber, Beatrice A; Polzer, Jennifer; Paulsen, Katrin; Lier, Hartwin; Engelmann, Frank; Schmitz, Burkhard; Schütte, Andreas; Layer, Liliana E; Ullrich, Oliver

2017-01-01

In the last decades, a plethora of in vitro studies with living human cells contributed a vast amount of knowledge about cellular and molecular effects of microgravity. Previous studies focused mostly on the identification of gravity-responsive genes, whereas a multi-platform analysis at an integrative level, which specifically evaluates the extent and robustness of transcriptional response to an altered gravity environment was not performed so far. Therefore, we investigated the stability of gene expression response in non-activated human Jurkat T lymphocytic cells in different gravity environments through the combination of parabolic flights with a suborbital ballistic rocket and 2D clinostat and centrifuge experiments, using strict controls for excluding all possible other factors of influence. We revealed an overall high stability of gene expression in microgravity and identified olfactory gene expression in the chromosomal region 11p15.4 as particularly robust to altered gravity. We identified that classical reference genes ABCA5 , GAPDH , HPRT1 , PLA2G4A , and RPL13A were stably expressed in all tested gravity conditions and platforms, while ABCA5 and GAPDH were also known to be stably expressed in U937 cells in all gravity conditions. In summary, 10-20% of all transcripts remained totally unchanged in any gravitational environment tested (between 10 -4 and 9 g), 20-40% remained unchanged in microgravity (between 10 -4 and 10 -2  g) and 97-99% were not significantly altered in microgravity if strict exclusion criteria were applied. Therefore, we suppose a high stability of gene expression in microgravity. Comparison with other stressors suggests that microgravity alters gene expression homeostasis not stronger than other environmental factors.

Genetic divergence in the transcriptional engram of chronic alcohol abuse: A laser-capture RNA-seq study of the mouse mesocorticolimbic system.

PubMed

Mulligan, Megan K; Mozhui, Khyobeni; Pandey, Ashutosh K; Smith, Maren L; Gong, Suzhen; Ingels, Jesse; Miles, Michael F; Lopez, Marcelo F; Lu, Lu; Williams, Robert W

2017-02-01

Genetic factors that influence the transition from initial drinking to dependence remain enigmatic. Recent studies have leveraged chronic intermittent ethanol (CIE) paradigms to measure changes in brain gene expression in a single strain at 0, 8, 72 h, and even 7 days following CIE. We extend these findings using LCM RNA-seq to profile expression in 11 brain regions in two inbred strains - C57BL/6J (B6) and DBA/2J (D2) - 72 h following multiple cycles of ethanol self-administration and CIE. Linear models identified differential expression based on treatment, region, strain, or interactions with treatment. Nearly 40% of genes showed a robust effect (FDR < 0.01) of region, and hippocampus CA1, cortex, bed nucleus stria terminalis, and nucleus accumbens core had the highest number of differentially expressed genes after treatment. Another 8% of differentially expressed genes demonstrated a robust effect of strain. As expected, based on similar studies in B6, treatment had a much smaller impact on expression; only 72 genes (p < 0.01) are modulated by treatment (independent of region or strain). Strikingly, many more genes (415) show a strain-specific and largely opposite response to treatment and are enriched in processes related to RNA metabolism, transcription factor activity, and mitochondrial function. Over 3 times as many changes in gene expression were detected in D2 compared to B6, and weighted gene co-expression network analysis (WGCNA) module comparison identified more modules enriched for treatment effects in D2. Substantial strain differences exist in the temporal pattern of transcriptional neuroadaptation to CIE, and these may drive individual differences in risk of addiction following excessive alcohol consumption. Copyright © 2016 Elsevier Inc. All rights reserved.

Robustness of equations that define molecular subtypes of glioblastoma tumors based on five transcripts measured by RT-PCR.

PubMed

Castells, Xavier; Acebes, Juan José; Majós, Carles; Boluda, Susana; Julià-Sapé, Margarida; Candiota, Ana Paula; Ariño, Joaquín; Barceló, Anna; Arús, Carles

2015-01-01

Glioblastoma (Gb) is one of the most deadly tumors. Its molecular subtypes are yet to be fully characterized while the attendant efforts for personalized medicine need to be intensified in relation to glioblastoma diagnosis, treatment, and prognosis. Several molecular signatures based on gene expression microarrays were reported, but the use of microarrays for routine clinical practice is challenged by attendant economic costs. Several authors have proposed discriminant equations based on RT-PCR. Still, the discriminant threshold is often incompletely described, which makes proper validation difficult. In a previous work, we have reported two Gb subtypes based on the expression levels of four genes: CHI3L1, LDHA, LGALS1, and IGFBP3. One Gb subtype presented with low expression of the four genes mentioned, and of MGMT in a large portion of the patients (with anticipated high methylation of its promoter), and mutated IDH1. Here, we evaluate the robustness of the equations fitted with these genes using RT-PCR values in a set of 64 cases and importantly, define an unequivocal discriminant threshold with a view to prognostic implications. We developed two approaches to generate the discriminant equations: 1) using the expression level of the four genes mentioned above, and 2) using those genes displaying the highest correlation with survival among the aforementioned four ones, plus MGMT, as an attempt to further reduce the number of genes. The ease of equations' applicability, reduction in cost for raw data, and robustness in terms of resampling-based classification accuracy warrant further evaluation of these equations to discern Gb tumor biopsy heterogeneity at molecular level, diagnose potential malignancy, and prognosis of individual patients with glioblastomas.

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

PubMed Central

2012-01-01

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

Predicting effects of structural stress in a genome-reduced model bacterial metabolism

NASA Astrophysics Data System (ADS)

Güell, Oriol; Sagués, Francesc; Serrano, M. Ángeles

2012-08-01

Mycoplasma pneumoniae is a human pathogen recently proposed as a genome-reduced model for bacterial systems biology. Here, we study the response of its metabolic network to different forms of structural stress, including removal of individual and pairs of reactions and knockout of genes and clusters of co-expressed genes. Our results reveal a network architecture as robust as that of other model bacteria regarding multiple failures, although less robust against individual reaction inactivation. Interestingly, metabolite motifs associated to reactions can predict the propagation of inactivation cascades and damage amplification effects arising in double knockouts. We also detect a significant correlation between gene essentiality and damages produced by single gene knockouts, and find that genes controlling high-damage reactions tend to be expressed independently of each other, a functional switch mechanism that, simultaneously, acts as a genetic firewall to protect metabolism. Prediction of failure propagation is crucial for metabolic engineering or disease treatment.

Broad Integration of Expression Maps and Co-Expression Networks Compassing Novel Gene Functions in the Brain

PubMed Central

Okamura-Oho, Yuko; Shimokawa, Kazuro; Nishimura, Masaomi; Takemoto, Satoko; Sato, Akira; Furuichi, Teiichi; Yokota, Hideo

2014-01-01

Using a recently invented technique for gene expression mapping in the whole-anatomy context, termed transcriptome tomography, we have generated a dataset of 36,000 maps of overall gene expression in the adult-mouse brain. Here, using an informatics approach, we identified a broad co-expression network that follows an inverse power law and is rich in functional interaction and gene-ontology terms. Our framework for the integrated analysis of expression maps and graphs of co-expression networks revealed that groups of combinatorially expressed genes, which regulate cell differentiation during development, were present in the adult brain and each of these groups was associated with a discrete cell types. These groups included non-coding genes of unknown function. We found that these genes specifically linked developmentally conserved groups in the network. A previously unrecognized robust expression pattern covering the whole brain was related to the molecular anatomy of key biological processes occurring in particular areas. PMID:25382412

Gene Therapy for Fracture Repair

DTIC Science & Technology

2005-12-01

therapeutic benefits. We have identified a murine leukemia virus (MLV) vector that provides robust transgene expression in fracture tissues, and applied it to...During the second year of funding, we used the surgical technique to apply the murine leukemia virus (MLV)-based vector to the fracture tissues and...trochanter. ii ) Fracture Injection The therapeutic gene chosen was the BMP-2/4 hybrid gene. To most accurately establish the expression of the

Three gene expression vector sets for concurrently expressing multiple genes in Saccharomyces cerevisiae.

PubMed

Ishii, Jun; Kondo, Takashi; Makino, Harumi; Ogura, Akira; Matsuda, Fumio; Kondo, Akihiko

2014-05-01

Yeast has the potential to be used in bulk-scale fermentative production of fuels and chemicals due to its tolerance for low pH and robustness for autolysis. However, expression of multiple external genes in one host yeast strain is considerably labor-intensive due to the lack of polycistronic transcription. To promote the metabolic engineering of yeast, we generated systematic and convenient genetic engineering tools to express multiple genes in Saccharomyces cerevisiae. We constructed a series of multi-copy and integration vector sets for concurrently expressing two or three genes in S. cerevisiae by embedding three classical promoters. The comparative expression capabilities of the constructed vectors were monitored with green fluorescent protein, and the concurrent expression of genes was monitored with three different fluorescent proteins. Our multiple gene expression tool will be helpful to the advanced construction of genetically engineered yeast strains in a variety of research fields other than metabolic engineering. © 2014 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved.

A novel feature extraction approach for microarray data based on multi-algorithm fusion

PubMed Central

Jiang, Zhu; Xu, Rong

2015-01-01

Feature extraction is one of the most important and effective method to reduce dimension in data mining, with emerging of high dimensional data such as microarray gene expression data. Feature extraction for gene selection, mainly serves two purposes. One is to identify certain disease-related genes. The other is to find a compact set of discriminative genes to build a pattern classifier with reduced complexity and improved generalization capabilities. Depending on the purpose of gene selection, two types of feature extraction algorithms including ranking-based feature extraction and set-based feature extraction are employed in microarray gene expression data analysis. In ranking-based feature extraction, features are evaluated on an individual basis, without considering inter-relationship between features in general, while set-based feature extraction evaluates features based on their role in a feature set by taking into account dependency between features. Just as learning methods, feature extraction has a problem in its generalization ability, which is robustness. However, the issue of robustness is often overlooked in feature extraction. In order to improve the accuracy and robustness of feature extraction for microarray data, a novel approach based on multi-algorithm fusion is proposed. By fusing different types of feature extraction algorithms to select the feature from the samples set, the proposed approach is able to improve feature extraction performance. The new approach is tested against gene expression dataset including Colon cancer data, CNS data, DLBCL data, and Leukemia data. The testing results show that the performance of this algorithm is better than existing solutions. PMID:25780277

A novel feature extraction approach for microarray data based on multi-algorithm fusion.

PubMed

Jiang, Zhu; Xu, Rong

2015-01-01

Feature extraction is one of the most important and effective method to reduce dimension in data mining, with emerging of high dimensional data such as microarray gene expression data. Feature extraction for gene selection, mainly serves two purposes. One is to identify certain disease-related genes. The other is to find a compact set of discriminative genes to build a pattern classifier with reduced complexity and improved generalization capabilities. Depending on the purpose of gene selection, two types of feature extraction algorithms including ranking-based feature extraction and set-based feature extraction are employed in microarray gene expression data analysis. In ranking-based feature extraction, features are evaluated on an individual basis, without considering inter-relationship between features in general, while set-based feature extraction evaluates features based on their role in a feature set by taking into account dependency between features. Just as learning methods, feature extraction has a problem in its generalization ability, which is robustness. However, the issue of robustness is often overlooked in feature extraction. In order to improve the accuracy and robustness of feature extraction for microarray data, a novel approach based on multi-algorithm fusion is proposed. By fusing different types of feature extraction algorithms to select the feature from the samples set, the proposed approach is able to improve feature extraction performance. The new approach is tested against gene expression dataset including Colon cancer data, CNS data, DLBCL data, and Leukemia data. The testing results show that the performance of this algorithm is better than existing solutions.

iPcc: a novel feature extraction method for accurate disease class discovery and prediction

PubMed Central

Ren, Xianwen; Wang, Yong; Zhang, Xiang-Sun; Jin, Qi

2013-01-01

Gene expression profiling has gradually become a routine procedure for disease diagnosis and classification. In the past decade, many computational methods have been proposed, resulting in great improvements on various levels, including feature selection and algorithms for classification and clustering. In this study, we present iPcc, a novel method from the feature extraction perspective to further propel gene expression profiling technologies from bench to bedside. We define ‘correlation feature space’ for samples based on the gene expression profiles by iterative employment of Pearson’s correlation coefficient. Numerical experiments on both simulated and real gene expression data sets demonstrate that iPcc can greatly highlight the latent patterns underlying noisy gene expression data and thus greatly improve the robustness and accuracy of the algorithms currently available for disease diagnosis and classification based on gene expression profiles. PMID:23761440

A group LASSO-based method for robustly inferring gene regulatory networks from multiple time-course datasets.

PubMed

Liu, Li-Zhi; Wu, Fang-Xiang; Zhang, Wen-Jun

2014-01-01

As an abstract mapping of the gene regulations in the cell, gene regulatory network is important to both biological research study and practical applications. The reverse engineering of gene regulatory networks from microarray gene expression data is a challenging research problem in systems biology. With the development of biological technologies, multiple time-course gene expression datasets might be collected for a specific gene network under different circumstances. The inference of a gene regulatory network can be improved by integrating these multiple datasets. It is also known that gene expression data may be contaminated with large errors or outliers, which may affect the inference results. A novel method, Huber group LASSO, is proposed to infer the same underlying network topology from multiple time-course gene expression datasets as well as to take the robustness to large error or outliers into account. To solve the optimization problem involved in the proposed method, an efficient algorithm which combines the ideas of auxiliary function minimization and block descent is developed. A stability selection method is adapted to our method to find a network topology consisting of edges with scores. The proposed method is applied to both simulation datasets and real experimental datasets. It shows that Huber group LASSO outperforms the group LASSO in terms of both areas under receiver operating characteristic curves and areas under the precision-recall curves. The convergence analysis of the algorithm theoretically shows that the sequence generated from the algorithm converges to the optimal solution of the problem. The simulation and real data examples demonstrate the effectiveness of the Huber group LASSO in integrating multiple time-course gene expression datasets and improving the resistance to large errors or outliers.

Division rate, cell size and proteome allocation: impact on gene expression noise and implications for the dynamics of genetic circuits

PubMed Central

2018-01-01

The cell division rate, size and gene expression programmes change in response to external conditions. These global changes impact on average concentrations of biomolecule and their variability or noise. Gene expression is inherently stochastic, and noise levels of individual proteins depend on synthesis and degradation rates as well as on cell-cycle dynamics. We have modelled stochastic gene expression inside growing and dividing cells to study the effect of division rates on noise in mRNA and protein expression. We use assumptions and parameters relevant to Escherichia coli, for which abundant quantitative data are available. We find that coupling of transcription, but not translation rates to the rate of cell division can result in protein concentration and noise homeostasis across conditions. Interestingly, we find that the increased cell size at fast division rates, observed in E. coli and other unicellular organisms, buffers noise levels even for proteins with decreased expression at faster growth. We then investigate the functional importance of these regulations using gene regulatory networks that exhibit bi-stability and oscillations. We find that network topology affects robustness to changes in division rate in complex and unexpected ways. In particular, a simple model of persistence, based on global physiological feedback, predicts increased proportion of persister cells at slow division rates. Altogether, our study reveals how cell size regulation in response to cell division rate could help controlling gene expression noise. It also highlights that understanding circuits' robustness across growth conditions is key for the effective design of synthetic biological systems. PMID:29657814

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

PubMed

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

2011-05-01

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

Interdependence of cell growth and gene expression: origins and consequences.

PubMed

Scott, Matthew; Gunderson, Carl W; Mateescu, Eduard M; Zhang, Zhongge; Hwa, Terence

2010-11-19

In bacteria, the rate of cell proliferation and the level of gene expression are intimately intertwined. Elucidating these relations is important both for understanding the physiological functions of endogenous genetic circuits and for designing robust synthetic systems. We describe a phenomenological study that reveals intrinsic constraints governing the allocation of resources toward protein synthesis and other aspects of cell growth. A theory incorporating these constraints can accurately predict how cell proliferation and gene expression affect one another, quantitatively accounting for the effect of translation-inhibiting antibiotics on gene expression and the effect of gratuitous protein expression on cell growth. The use of such empirical relations, analogous to phenomenological laws, may facilitate our understanding and manipulation of complex biological systems before underlying regulatory circuits are elucidated.

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

PubMed

Liu, Yuhang; Zhang, Jinfeng; Qiu, Xing

2017-12-21

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

Identification of stable reference genes for gene expression analysis of three-dimensional cultivated human bone marrow-derived mesenchymal stromal cells for bone tissue engineering.

PubMed

Rauh, Juliane; Jacobi, Angela; Stiehler, Maik

2015-02-01

The principles of tissue engineering (TE) are widely used for bone regeneration concepts. Three-dimensional (3D) cultivation of autologous human mesenchymal stromal cells (MSCs) on porous scaffolds is the basic prerequisite to generate newly formed bone tissue. Quantitative reverse transcription polymerase chain reaction (qRT-PCR) is a specific and sensitive analytical tool for the measurement of mRNA-levels in cells or tissues. For an accurate quantification of gene expression levels, stably expressed reference genes (RGs) are essential to obtain reliable results. Since the 3D environment can affect a cell's morphology, proliferation, and gene expression profile compared with two-dimensional (2D) cultivation, there is a need to identify robust RGs for the quantification of gene expression. So far, this issue has not been adequately investigated. The aim of this study was to identify the most stably expressed RGs for gene expression analysis of 3D-cultivated human bone marrow-derived MSCs (BM-MSCs). For this, we analyzed the gene expression levels of n=31 RGs in 3D-cultivated human BM-MSCs from six different donors compared with conventional 2D cultivation using qRT-PCR. MSCs isolated from bone marrow aspirates were cultivated on human cancellous bone cube scaffolds for 14 days. Osteogenic differentiation was assessed by cell-specific alkaline phosphatase (ALP) activity and expression of osteogenic marker genes. Expression levels of potential reference and target genes were quantified using commercially available TaqMan(®) assays. mRNA expression stability of RGs was determined by calculating the coefficient of variation (CV) and using the algorithms of geNorm and NormFinder. Using both algorithms, we identified TATA box binding protein (TBP), transferrin receptor (p90, CD71) (TFRC), and hypoxanthine phosphoribosyltransferase 1 (HPRT1) as the most stably expressed RGs in 3D-cultivated BM-MSCs. Notably, genes that are routinely used as RGs, for example, beta actin (ACTB) and ribosomal protein L37a (RPL37A), were among the least stable genes. We recommend the combined use of TBP, TFRC, and HPRT1 for the accurate and robust normalization of qRT-PCR data of 3D-cultivated human BM-MSCs.

Identification of Stable Reference Genes for Gene Expression Analysis of Three-Dimensional Cultivated Human Bone Marrow-Derived Mesenchymal Stromal Cells for Bone Tissue Engineering

PubMed Central

Rauh, Juliane; Jacobi, Angela

2015-01-01

The principles of tissue engineering (TE) are widely used for bone regeneration concepts. Three-dimensional (3D) cultivation of autologous human mesenchymal stromal cells (MSCs) on porous scaffolds is the basic prerequisite to generate newly formed bone tissue. Quantitative reverse transcription polymerase chain reaction (qRT-PCR) is a specific and sensitive analytical tool for the measurement of mRNA-levels in cells or tissues. For an accurate quantification of gene expression levels, stably expressed reference genes (RGs) are essential to obtain reliable results. Since the 3D environment can affect a cell's morphology, proliferation, and gene expression profile compared with two-dimensional (2D) cultivation, there is a need to identify robust RGs for the quantification of gene expression. So far, this issue has not been adequately investigated. The aim of this study was to identify the most stably expressed RGs for gene expression analysis of 3D-cultivated human bone marrow-derived MSCs (BM-MSCs). For this, we analyzed the gene expression levels of n=31 RGs in 3D-cultivated human BM-MSCs from six different donors compared with conventional 2D cultivation using qRT-PCR. MSCs isolated from bone marrow aspirates were cultivated on human cancellous bone cube scaffolds for 14 days. Osteogenic differentiation was assessed by cell-specific alkaline phosphatase (ALP) activity and expression of osteogenic marker genes. Expression levels of potential reference and target genes were quantified using commercially available TaqMan® assays. mRNA expression stability of RGs was determined by calculating the coefficient of variation (CV) and using the algorithms of geNorm and NormFinder. Using both algorithms, we identified TATA box binding protein (TBP), transferrin receptor (p90, CD71) (TFRC), and hypoxanthine phosphoribosyltransferase 1 (HPRT1) as the most stably expressed RGs in 3D-cultivated BM-MSCs. Notably, genes that are routinely used as RGs, for example, beta actin (ACTB) and ribosomal protein L37a (RPL37A), were among the least stable genes. We recommend the combined use of TBP, TFRC, and HPRT1 for the accurate and robust normalization of qRT-PCR data of 3D-cultivated human BM-MSCs. PMID:25000821

mRNA-Seq Reveals Novel Molecular Mechanisms and a Robust Fingerprint in Graves' Disease

PubMed Central

Sachidanandam, Ravi; Morshed, Syed; Latif, Rauf; Shi, Ruijin; Davies, Terry F.

2014-01-01

Context: The immune response in autoimmune thyroid disease has been shown to occur primarily within the thyroid gland in which the most abundant antigens can be found. A variety of capture molecules are known to be expressed by thyroid epithelial cells and serve to attract and help retain an intrathyroidal immune infiltrate. Objective: To explore the entire repertoire of expressed genes in human thyroid tissue, we have deep sequenced the transcriptome (referred to as mRNA-Seq). Design and Patients: We applied mRNA-Seq to thyroid tissue from nine patients with Graves' disease subjected to total thyroidectomy and compared the data with 12 samples of normal thyroid tissue obtained from patients having a thyroid nodule removed. The expression for each gene was calculated from the sequencing data by taking the median of the coverage across the length of the gene. The expression levels were quantile normalized and a gene signature was derived from these. Results: On comparison of expression levels in tissues derived from Graves' patients and controls, there was clear evidence for overexpression of the antigen presentation pathway consisting of HLA and associated genes. We also found a robust disease signature and discovered active innate and adaptive immune signaling networks. Conclusions: These data reveal an active immune defense system in Graves' disease, which involves novel molecular mechanisms in its pathogenesis and development. PMID:24971664

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

Generation of a neurodegenerative disease mouse model using lentiviral vectors carrying an enhanced synapsin I promoter.

PubMed

Matsuzaki, Yasunori; Oue, Miho; Hirai, Hirokazu

2014-02-15

Certain inherited progressive neurodegenerative disorders, such as spinocerebellar ataxia (SCA), affect neurons in large areas of the central nervous system (CNS). The selective expression of disease-causing and therapeutic genes in susceptible regions and cell types is critical for the generation of animal models and development of gene therapies for these diseases. Previous studies have demonstrated the advantages of the short synapsin I (SynI) promoter (0.5 kb) as a neuron-specific promoter for robust transgene expression. However, the short SynI promoter has also shown some promoter activity in glia and a lack of transgene expression in significant areas of the CNS. New methods: To improve the SynI promoter, we used a SynI promoter that is twice as long (1.0 kb) as the short SynI promoter and incorporated a minimal CMV (minCMV) sequence. We observed that the 1.0 kb rat SynI promoter with minCMV [rSynI(1.0)-minCMV] exhibited robust promoter strength, excellent neuronal specificity and wide-ranging transgene expression throughout the CNS. Comparison with existing methods: Compared with the two previously reported short (0.5 kb) promoters, the new promoter was superior with respect to neuronal specificity and more efficiently transduced neurons. Moreover, transgenic mice expressing the mutant protein ATXN1[Q98], which causes SCA type 1 (SCA1), under the control of the rSynI(1.0)-minCMV promoter showed robust transgene expression specifically in neurons throughout the CNS and exhibited progressive ataxia. rSynI(1.0)-minCMV drives robust and neuron-specific transgene expression throughout the CNS and is therefore useful for viral vector-mediated neuron-specific gene delivery and generation of neuron-specific transgenic animals. Copyright © 2013 Elsevier B.V. All rights reserved.

Order Under Uncertainty: Robust Differential Expression Analysis Using Probabilistic Models for Pseudotime Inference

PubMed Central

Campbell, Kieran R.

2016-01-01

Single cell gene expression profiling can be used to quantify transcriptional dynamics in temporal processes, such as cell differentiation, using computational methods to label each cell with a ‘pseudotime’ where true time series experimentation is too difficult to perform. However, owing to the high variability in gene expression between individual cells, there is an inherent uncertainty in the precise temporal ordering of the cells. Pre-existing methods for pseudotime estimation have predominantly given point estimates precluding a rigorous analysis of the implications of uncertainty. We use probabilistic modelling techniques to quantify pseudotime uncertainty and propagate this into downstream differential expression analysis. We demonstrate that reliance on a point estimate of pseudotime can lead to inflated false discovery rates and that probabilistic approaches provide greater robustness and measures of the temporal resolution that can be obtained from pseudotime inference. PMID:27870852

DeSigN: connecting gene expression with therapeutics for drug repurposing and development.

PubMed

Lee, Bernard Kok Bang; Tiong, Kai Hung; Chang, Jit Kang; Liew, Chee Sun; Abdul Rahman, Zainal Ariff; Tan, Aik Choon; Khang, Tsung Fei; Cheong, Sok Ching

2017-01-25

The drug discovery and development pipeline is a long and arduous process that inevitably hampers rapid drug development. Therefore, strategies to improve the efficiency of drug development are urgently needed to enable effective drugs to enter the clinic. Precision medicine has demonstrated that genetic features of cancer cells can be used for predicting drug response, and emerging evidence suggest that gene-drug connections could be predicted more accurately by exploring the cumulative effects of many genes simultaneously. We developed DeSigN, a web-based tool for predicting drug efficacy against cancer cell lines using gene expression patterns. The algorithm correlates phenotype-specific gene signatures derived from differentially expressed genes with pre-defined gene expression profiles associated with drug response data (IC 50 ) from 140 drugs. DeSigN successfully predicted the right drug sensitivity outcome in four published GEO studies. Additionally, it predicted bosutinib, a Src/Abl kinase inhibitor, as a sensitive inhibitor for oral squamous cell carcinoma (OSCC) cell lines. In vitro validation of bosutinib in OSCC cell lines demonstrated that indeed, these cell lines were sensitive to bosutinib with IC 50 of 0.8-1.2 μM. As further confirmation, we demonstrated experimentally that bosutinib has anti-proliferative activity in OSCC cell lines, demonstrating that DeSigN was able to robustly predict drug that could be beneficial for tumour control. DeSigN is a robust method that is useful for the identification of candidate drugs using an input gene signature obtained from gene expression analysis. This user-friendly platform could be used to identify drugs with unanticipated efficacy against cancer cell lines of interest, and therefore could be used for the repurposing of drugs, thus improving the efficiency of drug development.

Environmental Noise, Genetic Diversity and the Evolution of Evolvability and Robustness in Model Gene Networks

PubMed Central

Steiner, Christopher F.

2012-01-01

The ability of organisms to adapt and persist in the face of environmental change is accepted as a fundamental feature of natural systems. More contentious is whether the capacity of organisms to adapt (or “evolvability”) can itself evolve and the mechanisms underlying such responses. Using model gene networks, I provide evidence that evolvability emerges more readily when populations experience positively autocorrelated environmental noise (red noise) compared to populations in stable or randomly varying (white noise) environments. Evolvability was correlated with increasing genetic robustness to effects on network viability and decreasing robustness to effects on phenotypic expression; populations whose networks displayed greater viability robustness and lower phenotypic robustness produced more additive genetic variation and adapted more rapidly in novel environments. Patterns of selection for robustness varied antagonistically with epistatic effects of mutations on viability and phenotypic expression, suggesting that trade-offs between these properties may constrain their evolutionary responses. Evolution of evolvability and robustness was stronger in sexual populations compared to asexual populations indicating that enhanced genetic variation under fluctuating selection combined with recombination load is a primary driver of the emergence of evolvability. These results provide insight into the mechanisms potentially underlying rapid adaptation as well as the environmental conditions that drive the evolution of genetic interactions. PMID:23284934

Evolution of robustness to damage in artificial 3-dimensional development.

PubMed

Joachimczak, Michał; Wróbel, Borys

2012-09-01

GReaNs is an Artificial Life platform we have built to investigate the general principles that guide evolution of multicellular development and evolution of artificial gene regulatory networks. The embryos develop in GReaNs in a continuous 3-dimensional (3D) space with simple physics. The developmental trajectories are indirectly encoded in linear genomes. The genomes are not limited in size and determine the topology of gene regulatory networks that are not limited in the number of nodes. The expression of the genes is continuous and can be modified by adding environmental noise. In this paper we evolved development of structures with a specific shape (an ellipsoid) and asymmetrical pattering (a 3D pattern inspired by the French flag problem), and investigated emergence of the robustness to damage in development and the emergence of the robustness to noise. Our results indicate that both types of robustness are related, and that including noise during evolution promotes higher robustness to damage. Interestingly, we have observed that some evolved gene regulatory networks rely on noise for proper behaviour. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Identification of novel and robust internal control genes from Volvariella volvacea that are suitable for RT-qPCR in filamentous fungi.

PubMed

Tao, Yongxin; van Peer, Arend Frans; Huang, Qianhui; Shao, Yanping; Zhang, Lei; Xie, Bin; Jiang, Yuji; Zhu, Jian; Xie, Baogui

2016-07-12

The selection of appropriate internal control genes (ICGs) is a crucial step in the normalization of real-time quantitative PCR (RT-qPCR) data. Housekeeping genes are habitually selected for this purpose, despite accumulating evidence on their instability. We screened for novel, robust ICGs in the mushroom forming fungus Volvariella volvacea. Nine commonly used and five newly selected ICGs were evaluated for expression stability using RT-qPCR data in eight different stages of the life cycle of V. volvacea. Three different algorithms consistently determined that three novel ICGs (SPRYp, Ras and Vps26) exhibited the highest expression stability in V. volvacea. Subsequent analysis of ICGs in twenty-four expression profiles from nine filamentous fungi revealed that Ras was the most stable ICG amongst the Basidiomycetous samples, followed by SPRYp, Vps26 and ACTB. Vps26 was expressed most stably within the analyzed data of Ascomycetes, followed by HH3 and β-TUB. No ICG was universally stable for all fungal species, or for all experimental conditions within a species. Ultimately, the choice of an ICG will depend on a specific set of experiments. This study provides novel, robust ICGs for Basidiomycetes and Ascomycetes. Together with the presented guiding principles, this enables the efficient selection of suitable ICGs for RT-qPCR.

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

Epigenetic regulation of serotype expression antagonizes transcriptome dynamics in Paramecium tetraurelia

PubMed Central

Cheaib, Miriam; Dehghani Amirabad, Azim; Nordström, Karl J. V.; Schulz, Marcel H.; Simon, Martin

2015-01-01

Phenotypic variation of a single genotype is achieved by alterations in gene expression patterns. Regulation of such alterations depends on their time scale, where short-time adaptations differ from permanently established gene expression patterns maintained by epigenetic mechanisms. In the ciliate Paramecium, serotypes were described for an epigenetically controlled gene expression pattern of an individual multigene family. Paradoxically, individual serotypes can be triggered in Paramecium by alternating environments but are then stabilized by epigenetic mechanisms, thus raising the question to which extend their expression follows environmental stimuli. To characterize environmental adaptation in the context of epigenetically controlled serotype expression, we used RNA-seq to characterize transcriptomes of serotype pure cultures. The resulting vegetative transcriptome resource is first analysed for genes involved in the adaptive response to the altered environment. Secondly, we identified groups of genes that do not follow the adaptive response but show co-regulation with the epigenetically controlled serotype system, suggesting that their gene expression pattern becomes manifested by similar mechanisms. In our experimental set-up, serotype expression and the entire group of co-regulated genes were stable among environmental changes and only heat-shock genes altered expression of these gene groups. The data suggest that the maintenance of these gene expression patterns in a lineage represents epigenetically controlled robustness counteracting short-time adaptation processes. PMID:26231545

Tolerant industrial yeast Saccharomyces cerevisiae posses a more robust cell wall integrity signaling pathway against 2-furaldehyde and 5-(hydroxymethyl)-2-furaldehyde.

PubMed

Liu, Z Lewis; Wang, Xu; Weber, Scott A

2018-06-20

Cell wall integrity signaling pathway in Saccharomyces cerevisiae is a conserved function for detecting and responding to cell stress conditions but less understood for industrial yeast. We examined gene expression dynamics for a tolerant industrial yeast strain NRRL Y-50049 in response to challenges of furfural and HMF through comparative quantitative gene expression analysis using pathway-based qRT-PCR array assays. All tested genes from Y-50049, except for MLP2, demonstrated more resistant and significantly increased gene expression than that from a laboratory strain BY4741. While all five sensor encoding genes WSC1, WSC2, WSC3, MID2 and MTL1 from both strains were activated in response to the furfural-HMF treatment, WSC3 from Y-50049 demonstrated the most increased expression over time compared with any other sensor genes. These results suggested the industrial yeast poses more robust cell wall integrity pathway, and gene WSC3 could have the special capability for signal transmission against furfural and HMF. Among five single nucleotide variations discovered in WSC3 from Y-50049, three were found to be non-synonymous mutations resulting in amino acid alterations of Ser 158  → Tyr 158 , Val 186  → Ile 186 , and Glu 430  → Asp 430 . Our results suggest the industrial yeast as a more desirable delivery vehicle for the next-generation biocatalyst development. Published by Elsevier B.V.

A novel strategy of integrated microarray analysis identifies CENPA, CDK1 and CDC20 as a cluster of diagnostic biomarkers in lung adenocarcinoma.

PubMed

Liu, Wan-Ting; Wang, Yang; Zhang, Jing; Ye, Fei; Huang, Xiao-Hui; Li, Bin; He, Qing-Yu

2018-07-01

Lung adenocarcinoma (LAC) is the most lethal cancer and the leading cause of cancer-related death worldwide. The identification of meaningful clusters of co-expressed genes or representative biomarkers may help improve the accuracy of LAC diagnoses. Public databases, such as the Gene Expression Omnibus (GEO), provide rich resources of valuable information for clinics, however, the integration of multiple microarray datasets from various platforms and institutes remained a challenge. To determine potential indicators of LAC, we performed genome-wide relative significance (GWRS), genome-wide global significance (GWGS) and support vector machine (SVM) analyses progressively to identify robust gene biomarker signatures from 5 different microarray datasets that included 330 samples. The top 200 genes with robust signatures were selected for integrative analysis according to "guilt-by-association" methods, including protein-protein interaction (PPI) analysis and gene co-expression analysis. Of these 200 genes, only 10 genes showed both intensive PPI network and high gene co-expression correlation (r > 0.8). IPA analysis of this regulatory networks suggested that the cell cycle process is a crucial determinant of LAC. CENPA, as well as two linked hub genes CDK1 and CDC20, are determined to be potential indicators of LAC. Immunohistochemical staining showed that CENPA, CDK1 and CDC20 were highly expressed in LAC cancer tissue with co-expression patterns. A Cox regression model indicated that LAC patients with CENPA + /CDK1 + and CENPA + /CDC20 + were high-risk groups in terms of overall survival. In conclusion, our integrated microarray analysis demonstrated that CENPA, CDK1 and CDC20 might serve as novel cluster of prognostic biomarkers for LAC, and the cooperative unit of three genes provides a technically simple approach for identification of LAC patients. Copyright © 2018 Elsevier B.V. All rights reserved.

Neutrality and Robustness in Evo-Devo: Emergence of Lateral Inhibition

PubMed Central

Munteanu, Andreea; Solé, Ricard V.

2008-01-01

Embryonic development is defined by the hierarchical dynamical process that translates genetic information (genotype) into a spatial gene expression pattern (phenotype) providing the positional information for the correct unfolding of the organism. The nature and evolutionary implications of genotype–phenotype mapping still remain key topics in evolutionary developmental biology (evo-devo). We have explored here issues of neutrality, robustness, and diversity in evo-devo by means of a simple model of gene regulatory networks. The small size of the system allowed an exhaustive analysis of the entire fitness landscape and the extent of its neutrality. This analysis shows that evolution leads to a class of robust genetic networks with an expression pattern characteristic of lateral inhibition. This class is a repertoire of distinct implementations of this key developmental process, the diversity of which provides valuable clues about its underlying causal principles. PMID:19023404

A Bootstrap Based Measure Robust to the Choice of Normalization Methods for Detecting Rhythmic Features in High Dimensional Data.

PubMed

Larriba, Yolanda; Rueda, Cristina; Fernández, Miguel A; Peddada, Shyamal D

2018-01-01

Motivation: Gene-expression data obtained from high throughput technologies are subject to various sources of noise and accordingly the raw data are pre-processed before formally analyzed. Normalization of the data is a key pre-processing step, since it removes systematic variations across arrays. There are numerous normalization methods available in the literature. Based on our experience, in the context of oscillatory systems, such as cell-cycle, circadian clock, etc., the choice of the normalization method may substantially impact the determination of a gene to be rhythmic. Thus rhythmicity of a gene can purely be an artifact of how the data were normalized. Since the determination of rhythmic genes is an important component of modern toxicological and pharmacological studies, it is important to determine truly rhythmic genes that are robust to the choice of a normalization method. Results: In this paper we introduce a rhythmicity measure and a bootstrap methodology to detect rhythmic genes in an oscillatory system. Although the proposed methodology can be used for any high-throughput gene expression data, in this paper we illustrate the proposed methodology using several publicly available circadian clock microarray gene-expression datasets. We demonstrate that the choice of normalization method has very little effect on the proposed methodology. Specifically, for any pair of normalization methods considered in this paper, the resulting values of the rhythmicity measure are highly correlated. Thus it suggests that the proposed measure is robust to the choice of a normalization method. Consequently, the rhythmicity of a gene is potentially not a mere artifact of the normalization method used. Lastly, as demonstrated in the paper, the proposed bootstrap methodology can also be used for simulating data for genes participating in an oscillatory system using a reference dataset. Availability: A user friendly code implemented in R language can be downloaded from http://www.eio.uva.es/~miguel/robustdetectionprocedure.html.

A Bootstrap Based Measure Robust to the Choice of Normalization Methods for Detecting Rhythmic Features in High Dimensional Data

PubMed Central

Larriba, Yolanda; Rueda, Cristina; Fernández, Miguel A.; Peddada, Shyamal D.

2018-01-01

Motivation: Gene-expression data obtained from high throughput technologies are subject to various sources of noise and accordingly the raw data are pre-processed before formally analyzed. Normalization of the data is a key pre-processing step, since it removes systematic variations across arrays. There are numerous normalization methods available in the literature. Based on our experience, in the context of oscillatory systems, such as cell-cycle, circadian clock, etc., the choice of the normalization method may substantially impact the determination of a gene to be rhythmic. Thus rhythmicity of a gene can purely be an artifact of how the data were normalized. Since the determination of rhythmic genes is an important component of modern toxicological and pharmacological studies, it is important to determine truly rhythmic genes that are robust to the choice of a normalization method. Results: In this paper we introduce a rhythmicity measure and a bootstrap methodology to detect rhythmic genes in an oscillatory system. Although the proposed methodology can be used for any high-throughput gene expression data, in this paper we illustrate the proposed methodology using several publicly available circadian clock microarray gene-expression datasets. We demonstrate that the choice of normalization method has very little effect on the proposed methodology. Specifically, for any pair of normalization methods considered in this paper, the resulting values of the rhythmicity measure are highly correlated. Thus it suggests that the proposed measure is robust to the choice of a normalization method. Consequently, the rhythmicity of a gene is potentially not a mere artifact of the normalization method used. Lastly, as demonstrated in the paper, the proposed bootstrap methodology can also be used for simulating data for genes participating in an oscillatory system using a reference dataset. Availability: A user friendly code implemented in R language can be downloaded from http://www.eio.uva.es/~miguel/robustdetectionprocedure.html PMID:29456555

Query-based biclustering of gene expression data using Probabilistic Relational Models.

PubMed

Zhao, Hui; Cloots, Lore; Van den Bulcke, Tim; Wu, Yan; De Smet, Riet; Storms, Valerie; Meysman, Pieter; Engelen, Kristof; Marchal, Kathleen

2011-02-15

With the availability of large scale expression compendia it is now possible to view own findings in the light of what is already available and retrieve genes with an expression profile similar to a set of genes of interest (i.e., a query or seed set) for a subset of conditions. To that end, a query-based strategy is needed that maximally exploits the coexpression behaviour of the seed genes to guide the biclustering, but that at the same time is robust against the presence of noisy genes in the seed set as seed genes are often assumed, but not guaranteed to be coexpressed in the queried compendium. Therefore, we developed ProBic, a query-based biclustering strategy based on Probabilistic Relational Models (PRMs) that exploits the use of prior distributions to extract the information contained within the seed set. We applied ProBic on a large scale Escherichia coli compendium to extend partially described regulons with potentially novel members. We compared ProBic's performance with previously published query-based biclustering algorithms, namely ISA and QDB, from the perspective of bicluster expression quality, robustness of the outcome against noisy seed sets and biological relevance.This comparison learns that ProBic is able to retrieve biologically relevant, high quality biclusters that retain their seed genes and that it is particularly strong in handling noisy seeds. ProBic is a query-based biclustering algorithm developed in a flexible framework, designed to detect biologically relevant, high quality biclusters that retain relevant seed genes even in the presence of noise or when dealing with low quality seed sets.

Oscillatory Protein Expression Dynamics Endows Stem Cells with Robust Differentiation Potential

PubMed Central

Kaneko, Kunihiko

2011-01-01

The lack of understanding of stem cell differentiation and proliferation is a fundamental problem in developmental biology. Although gene regulatory networks (GRNs) for stem cell differentiation have been partially identified, the nature of differentiation dynamics and their regulation leading to robust development remain unclear. Herein, using a dynamical system modeling cell approach, we performed simulations of the developmental process using all possible GRNs with a few genes, and screened GRNs that could generate cell type diversity through cell-cell interactions. We found that model stem cells that both proliferated and differentiated always exhibited oscillatory expression dynamics, and the differentiation frequency of such stem cells was regulated, resulting in a robust number distribution. Moreover, we uncovered the common regulatory motifs for stem cell differentiation, in which a combination of regulatory motifs that generated oscillatory expression dynamics and stabilized distinct cellular states played an essential role. These findings may explain the recently observed heterogeneity and dynamic equilibrium in cellular states of stem cells, and can be used to predict regulatory networks responsible for differentiation in stem cell systems. PMID:22073296

Cardiomyocyte Circadian Oscillations Are Cell-Autonomous, Amplified by β-Adrenergic Signaling, and Synchronized in Cardiac Ventricle Tissue

PubMed Central

Welsh, David K.

2016-01-01

Circadian clocks impact vital cardiac parameters such as blood pressure and heart rate, and adverse cardiac events such as myocardial infarction and sudden cardiac death. In mammals, the central circadian pacemaker, located in the suprachiasmatic nucleus of the hypothalamus, synchronizes cellular circadian clocks in the heart and many other tissues throughout the body. Cardiac ventricle explants maintain autonomous contractions and robust circadian oscillations of clock gene expression in culture. In the present study, we examined the relationship between intrinsic myocardial function and circadian rhythms in cultures from mouse heart. We cultured ventricular explants or dispersed cardiomyocytes from neonatal mice expressing a PER2::LUC bioluminescent reporter of circadian clock gene expression. We found that isoproterenol, a β-adrenoceptor agonist known to increase heart rate and contractility, also amplifies PER2 circadian rhythms in ventricular explants. We found robust, cell-autonomous PER2 circadian rhythms in dispersed cardiomyocytes. Single-cell rhythms were initially synchronized in ventricular explants but desynchronized in dispersed cells. In addition, we developed a method for long-term, simultaneous monitoring of clock gene expression, contraction rate, and basal intracellular Ca2+ level in cardiomyocytes using PER2::LUC in combination with GCaMP3, a genetically encoded fluorescent Ca2+ reporter. In contrast to robust PER2 circadian rhythms in cardiomyocytes, we detected no rhythms in contraction rate and only weak rhythms in basal Ca2+ level. In summary, we found that PER2 circadian rhythms of cardiomyocytes are cell-autonomous, amplified by adrenergic signaling, and synchronized by intercellular communication in ventricle explants, but we detected no robust circadian rhythms in contraction rate or basal Ca2+. PMID:27459195

Maintenance and expression of the S. cerevisiae mitochondrial genome--from genetics to evolution and systems biology.

PubMed

Lipinski, Kamil A; Kaniak-Golik, Aneta; Golik, Pawel

2010-01-01

As a legacy of their endosymbiotic eubacterial origin, mitochondria possess a residual genome, encoding only a few proteins and dependent on a variety of factors encoded by the nuclear genome for its maintenance and expression. As a facultative anaerobe with well understood genetics and molecular biology, Saccharomyces cerevisiae is the model system of choice for studying nucleo-mitochondrial genetic interactions. Maintenance of the mitochondrial genome is controlled by a set of nuclear-coded factors forming intricately interconnected circuits responsible for replication, recombination, repair and transmission to buds. Expression of the yeast mitochondrial genome is regulated mostly at the post-transcriptional level, and involves many general and gene-specific factors regulating splicing, RNA processing and stability and translation. A very interesting aspect of the yeast mitochondrial system is the relationship between genome maintenance and gene expression. Deletions of genes involved in many different aspects of mitochondrial gene expression, notably translation, result in an irreversible loss of functional mtDNA. The mitochondrial genetic system viewed from the systems biology perspective is therefore very fragile and lacks robustness compared to the remaining systems of the cell. This lack of robustness could be a legacy of the reductive evolution of the mitochondrial genome, but explanations involving selective advantages of increased evolvability have also been postulated. Copyright © 2009 Elsevier B.V. All rights reserved.

Assessment of long-term transgene expression in barley: Ds-mediated delivery of bar results in robust, stable, and heritable expression

USDA-ARS?s Scientific Manuscript database

The utility of transgenic plants for both experimental and practical agronomic purposes is highly dependent on stable, predictable, and heritable expression of the introduced genes. This requirement is frequently unfulfilled, and transgenes are frequently subject to silencing. Studies of the charact...

Epigenetic regulation of serotype expression antagonizes transcriptome dynamics in Paramecium tetraurelia.

PubMed

Cheaib, Miriam; Dehghani Amirabad, Azim; Nordström, Karl J V; Schulz, Marcel H; Simon, Martin

2015-08-01

Phenotypic variation of a single genotype is achieved by alterations in gene expression patterns. Regulation of such alterations depends on their time scale, where short-time adaptations differ from permanently established gene expression patterns maintained by epigenetic mechanisms. In the ciliate Paramecium, serotypes were described for an epigenetically controlled gene expression pattern of an individual multigene family. Paradoxically, individual serotypes can be triggered in Paramecium by alternating environments but are then stabilized by epigenetic mechanisms, thus raising the question to which extend their expression follows environmental stimuli. To characterize environmental adaptation in the context of epigenetically controlled serotype expression, we used RNA-seq to characterize transcriptomes of serotype pure cultures. The resulting vegetative transcriptome resource is first analysed for genes involved in the adaptive response to the altered environment. Secondly, we identified groups of genes that do not follow the adaptive response but show co-regulation with the epigenetically controlled serotype system, suggesting that their gene expression pattern becomes manifested by similar mechanisms. In our experimental set-up, serotype expression and the entire group of co-regulated genes were stable among environmental changes and only heat-shock genes altered expression of these gene groups. The data suggest that the maintenance of these gene expression patterns in a lineage represents epigenetically controlled robustness counteracting short-time adaptation processes. © The Author 2015. Published by Oxford University Press on behalf of Kazusa DNA Research Institute.

Selection of reference genes for expression studies with fish myogenic cell cultures.

PubMed

Bower, Neil I; Johnston, Ian A

2009-08-10

Relatively few studies have used cell culture systems to investigate gene expression and the regulation of myogenesis in fish. To produce robust data from quantitative real-time PCR mRNA levels need to be normalised using internal reference genes which have stable expression across all experimental samples. We have investigated the expression of eight candidate genes to identify suitable reference genes for use in primary myogenic cell cultures from Atlantic salmon (Salmo salar L.). The software analysis packages geNorm, Normfinder and Best keeper were used to rank genes according to their stability across 42 samples during the course of myogenic differentiation. Initial results showed several of the candidate genes exhibited stable expression throughout myogenic culture while Sdha was identified as the least stable gene. Further analysis with geNorm, Normfinder and Bestkeeper identified Ef1alpha, Hprt1, Ppia and RNApolII as stably expressed. Comparison of data normalised with the geometric average obtained from combinations of any three of these genes showed no significant differences, indicating that any combination of these genes is valid. The geometric average of any three of Hprt1, Ef1alpha, Ppia and RNApolII is suitable for normalisation of gene expression data in primary myogenic cultures from Atlantic salmon.

Hacking DNA copy number for circuit engineering.

PubMed

Wu, Feilun; You, Lingchong

2017-07-27

DNA copy number represents an essential parameter in the dynamics of synthetic gene circuits but typically is not explicitly considered. A new study demonstrates how dynamic control of DNA copy number can serve as an effective strategy to program robust oscillations in gene expression circuits.

In silico Pathway Activation Network Decomposition Analysis (iPANDA) as a method for biomarker development.

PubMed

Ozerov, Ivan V; Lezhnina, Ksenia V; Izumchenko, Evgeny; Artemov, Artem V; Medintsev, Sergey; Vanhaelen, Quentin; Aliper, Alexander; Vijg, Jan; Osipov, Andreyan N; Labat, Ivan; West, Michael D; Buzdin, Anton; Cantor, Charles R; Nikolsky, Yuri; Borisov, Nikolay; Irincheeva, Irina; Khokhlovich, Edward; Sidransky, David; Camargo, Miguel Luiz; Zhavoronkov, Alex

2016-11-16

Signalling pathway activation analysis is a powerful approach for extracting biologically relevant features from large-scale transcriptomic and proteomic data. However, modern pathway-based methods often fail to provide stable pathway signatures of a specific phenotype or reliable disease biomarkers. In the present study, we introduce the in silico Pathway Activation Network Decomposition Analysis (iPANDA) as a scalable robust method for biomarker identification using gene expression data. The iPANDA method combines precalculated gene coexpression data with gene importance factors based on the degree of differential gene expression and pathway topology decomposition for obtaining pathway activation scores. Using Microarray Analysis Quality Control (MAQC) data sets and pretreatment data on Taxol-based neoadjuvant breast cancer therapy from multiple sources, we demonstrate that iPANDA provides significant noise reduction in transcriptomic data and identifies highly robust sets of biologically relevant pathway signatures. We successfully apply iPANDA for stratifying breast cancer patients according to their sensitivity to neoadjuvant therapy.

In silico Pathway Activation Network Decomposition Analysis (iPANDA) as a method for biomarker development

PubMed Central

Ozerov, Ivan V.; Lezhnina, Ksenia V.; Izumchenko, Evgeny; Artemov, Artem V.; Medintsev, Sergey; Vanhaelen, Quentin; Aliper, Alexander; Vijg, Jan; Osipov, Andreyan N.; Labat, Ivan; West, Michael D.; Buzdin, Anton; Cantor, Charles R.; Nikolsky, Yuri; Borisov, Nikolay; Irincheeva, Irina; Khokhlovich, Edward; Sidransky, David; Camargo, Miguel Luiz; Zhavoronkov, Alex

2016-01-01

Signalling pathway activation analysis is a powerful approach for extracting biologically relevant features from large-scale transcriptomic and proteomic data. However, modern pathway-based methods often fail to provide stable pathway signatures of a specific phenotype or reliable disease biomarkers. In the present study, we introduce the in silico Pathway Activation Network Decomposition Analysis (iPANDA) as a scalable robust method for biomarker identification using gene expression data. The iPANDA method combines precalculated gene coexpression data with gene importance factors based on the degree of differential gene expression and pathway topology decomposition for obtaining pathway activation scores. Using Microarray Analysis Quality Control (MAQC) data sets and pretreatment data on Taxol-based neoadjuvant breast cancer therapy from multiple sources, we demonstrate that iPANDA provides significant noise reduction in transcriptomic data and identifies highly robust sets of biologically relevant pathway signatures. We successfully apply iPANDA for stratifying breast cancer patients according to their sensitivity to neoadjuvant therapy. PMID:27848968

Natural breaking of the maternal silence at the mouse and human imprinted Prader-Willi locus: A whisper with functional consequences.

PubMed

Matarazzo, Valery; Muscatelli, Françoise

2013-01-01

Genomic imprinting is a normal process of epigenetic regulation leading some autosomal genes to be expressed from one parental allele only, the other parental allele being silenced. The reasons why this mechanism has been selected throughout evolution are not clear; however, expression dosage is critical for imprinted genes. There is a paradox between the fact that genomic imprinting is a robust mechanism controlling the expression of specific genes and the fact that this mechanism is based on epigenetic regulation that, per se, should present some flexibility. The robustness has been well studied, revealing the epigenetic modifications at the imprinted locus, but the flexibility has been poorly investigated.   Prader-Willi syndrome is the best-studied disease involving imprinted genes caused by the absence of expression of paternally inherited alleles of genes located in the human 15q11-q13 region. Until now, the silencing of the maternally inherited alleles was like a dogma. Rieusset et al. showed that in absence of the paternal Ndn allele, in Ndn +m/-p mice, the maternal Ndn allele is expressed at an extremely low level with a high degree of non-genetic heterogeneity. In about 50% of these mutant mice, this stochastic expression reduces birth lethality and severity of the breathing deficiency, correlated with a reduction in the loss of serotonergic neurons. Furthermore, using several mouse models, they reveal a competition between non-imprinted Ndn promoters, which results in monoallelic (paternal or maternal) Ndn expression, suggesting that Ndn monoallelic expression occurs in the absence of imprinting regulation. Importantly, specific expression of the maternal NDN allele is also detected in post-mortem brain samples of PWS individuals. Here, similar expression of the Magel2 maternal allele is reported in Magel2 +m/-p mice, suggesting that this loss of imprinting can be extended to other PWS genes. These data reveal an unexpected epigenetic flexibility of PWS imprinted genes that could be exploited to reactivate the functional but dormant maternal alleles in PWS.

Enhanced identification and biological validation of differential gene expression via Illumina whole-genome expression arrays through the use of the model-based background correction methodology

PubMed Central

Ding, Liang-Hao; Xie, Yang; Park, Seongmi; Xiao, Guanghua; Story, Michael D.

2008-01-01

Despite the tremendous growth of microarray usage in scientific studies, there is a lack of standards for background correction methodologies, especially in single-color microarray platforms. Traditional background subtraction methods often generate negative signals and thus cause large amounts of data loss. Hence, some researchers prefer to avoid background corrections, which typically result in the underestimation of differential expression. Here, by utilizing nonspecific negative control features integrated into Illumina whole genome expression arrays, we have developed a method of model-based background correction for BeadArrays (MBCB). We compared the MBCB with a method adapted from the Affymetrix robust multi-array analysis algorithm and with no background subtraction, using a mouse acute myeloid leukemia (AML) dataset. We demonstrated that differential expression ratios obtained by using the MBCB had the best correlation with quantitative RT–PCR. MBCB also achieved better sensitivity in detecting differentially expressed genes with biological significance. For example, we demonstrated that the differential regulation of Tnfr2, Ikk and NF-kappaB, the death receptor pathway, in the AML samples, could only be detected by using data after MBCB implementation. We conclude that MBCB is a robust background correction method that will lead to more precise determination of gene expression and better biological interpretation of Illumina BeadArray data. PMID:18450815

Distinct mechanisms coordinate transcription and translation under carbon and nitrogen starvation in Escherichia coli.

PubMed

Iyer, Sukanya; Le, Dai; Park, Bo Ryoung; Kim, Minsu

2018-05-14

Bacteria adapt to environmental stress by producing proteins that provide stress protection. However, stress can severely perturb the kinetics of gene expression, disrupting protein production. Here, we characterized how Escherichia coli mitigates such perturbations under nutrient stress through the kinetic coordination of transcription and translation. We observed that, when translation became limiting under nitrogen starvation, transcription elongation slowed accordingly. This slowdown was mediated by (p)ppGpp, the alarmone whose primary role is thought to be promoter regulation. This kinetic coordination by (p)ppGpp was critical for the robust synthesis of gene products. Surprisingly, under carbon starvation, (p)ppGpp was dispensable for robust synthesis. Characterization of the underlying kinetics revealed that under carbon starvation, transcription became limiting, and translation aided transcription elongation. This mechanism naturally coordinated transcription with translation, alleviating the need for (p)ppGpp as a mediator. These contrasting mechanisms for coordination resulted in the condition-dependent effects of (p)ppGpp on global protein synthesis and starvation survival. Our findings reveal a kinetic aspect of gene expression plasticity, establishing (p)ppGpp as a condition-dependent global effector of gene expression.

Targeting gene expression selectively in cancer cells by using the progression-elevated gene-3 promoter.

PubMed

Su, Zhao-Zhong; Sarkar, Devanand; Emdad, Luni; Duigou, Gregory J; Young, Charles S H; Ware, Joy; Randolph, Aaron; Valerie, Kristoffer; Fisher, Paul B

2005-01-25

One impediment to effective cancer-specific gene therapy is the rarity of regulatory sequences targeting gene expression selectively in tumor cells. Although many tissue-specific promoters are recognized, few cancer-selective gene promoters are available. Progression-elevated gene-3 (PEG-3) is a rodent gene identified by subtraction hybridization that displays elevated expression as a function of transformation by diversely acting oncogenes, DNA damage, and cancer cell progression. The promoter of PEG-3, PEG-Prom, displays robust expression in a broad spectrum of human cancer cell lines with marginal expression in normal cellular counterparts. Whereas GFP expression, when under the control of a CMV promoter, is detected in both normal and cancer cells, when GFP is expressed under the control of the PEG-Prom, cancer-selective expression is evident. Mutational analysis identifies the AP-1 and PEA-3 transcription factors as primary mediators of selective, cancer-specific expression of the PEG-Prom. Synthesis of apoptosis-inducing genes, under the control of the CMV promoter, inhibits the growth of both normal and cancer cells, whereas PEG-Prom-mediated expression of these genes kills only cancer cells and spares normal cells. The efficacy of the PEG-Prom as part of a cancer gene therapeutic regimen is further documented by in vivo experiments in which PEG-Prom-controlled expression of an apoptosis-inducing gene completely inhibited prostate cancer xenograft growth in nude mice. These compelling observations indicate that the PEG-Prom, with its cancer-specific expression, provides a means of selectively delivering genes to cancer cells, thereby providing a crucial component in developing effective cancer gene therapies.

Identification of Reference Genes for RT-qPCR Data Normalization in Cannabis sativa Stem Tissues.

PubMed

Mangeot-Peter, Lauralie; Legay, Sylvain; Hausman, Jean-Francois; Esposito, Sergio; Guerriero, Gea

2016-09-15

Gene expression profiling via quantitative real-time PCR is a robust technique widely used in the life sciences to compare gene expression patterns in, e.g., different tissues, growth conditions, or after specific treatments. In the field of plant science, real-time PCR is the gold standard to study the dynamics of gene expression and is used to validate the results generated with high throughput techniques, e.g., RNA-Seq. An accurate relative quantification of gene expression relies on the identification of appropriate reference genes, that need to be determined for each experimental set-up used and plant tissue studied. Here, we identify suitable reference genes for expression profiling in stems of textile hemp (Cannabis sativa L.), whose tissues (isolated bast fibres and core) are characterized by remarkable differences in cell wall composition. We additionally validate the reference genes by analysing the expression of putative candidates involved in the non-oxidative phase of the pentose phosphate pathway and in the first step of the shikimate pathway. The goal is to describe the possible regulation pattern of some genes involved in the provision of the precursors needed for lignin biosynthesis in the different hemp stem tissues. The results here shown are useful to design future studies focused on gene expression analyses in hemp.

Evaluation of two outlier-detection-based methods for detecting tissue-selective genes from microarray data.

PubMed

Kadota, Koji; Konishi, Tomokazu; Shimizu, Kentaro

2007-05-01

Large-scale expression profiling using DNA microarrays enables identification of tissue-selective genes for which expression is considerably higher and/or lower in some tissues than in others. Among numerous possible methods, only two outlier-detection-based methods (an AIC-based method and Sprent's non-parametric method) can treat equally various types of selective patterns, but they produce substantially different results. We investigated the performance of these two methods for different parameter settings and for a reduced number of samples. We focused on their ability to detect selective expression patterns robustly. We applied them to public microarray data collected from 36 normal human tissue samples and analyzed the effects of both changing the parameter settings and reducing the number of samples. The AIC-based method was more robust in both cases. The findings confirm that the use of the AIC-based method in the recently proposed ROKU method for detecting tissue-selective expression patterns is correct and that Sprent's method is not suitable for ROKU.

Growth-rate dependent global effects on gene expression in bacteria

PubMed Central

Klumpp, Stefan; Zhang, Zhongge; Hwa, Terence

2010-01-01

Summary Bacterial gene expression depends not only on specific regulations but also directly on bacterial growth, because important global parameters such as the abundance of RNA polymerases and ribosomes are all growth-rate dependent. Understanding these global effects is necessary for a quantitative understanding of gene regulation and for the robust design of synthetic genetic circuits. The observed growth-rate dependence of constitutive gene expression can be explained by a simple model using the measured growth-rate dependence of the relevant cellular parameters. More complex growth dependences for genetic circuits involving activators, repressors and feedback control were analyzed, and salient features were verified experimentally using synthetic circuits. The results suggest a novel feedback mechanism mediated by general growth-dependent effects and not requiring explicit gene regulation, if the expressed protein affects cell growth. This mechanism can lead to growth bistability and promote the acquisition of important physiological functions such as antibiotic resistance and tolerance (persistence). PMID:20064380

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.

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.

Gene expression profiling of single cells on large-scale oligonucleotide arrays

PubMed Central

Hartmann, Claudia H.; Klein, Christoph A.

2006-01-01

Over the last decade, important insights into the regulation of cellular responses to various stimuli were gained by global gene expression analyses of cell populations. More recently, specific cell functions and underlying regulatory networks of rare cells isolated from their natural environment moved to the center of attention. However, low cell numbers still hinder gene expression profiling of rare ex vivo material in biomedical research. Therefore, we developed a robust method for gene expression profiling of single cells on high-density oligonucleotide arrays with excellent coverage of low abundance transcripts. The protocol was extensively tested with freshly isolated single cells of very low mRNA content including single epithelial, mature and immature dendritic cells and hematopoietic stem cells. Quantitative PCR confirmed that the PCR-based global amplification method did not change the relative ratios of transcript abundance and unsupervised hierarchical cluster analysis revealed that the histogenetic origin of an individual cell is correctly reflected by the gene expression profile. Moreover, the gene expression data from dendritic cells demonstrate that cellular differentiation and pathway activation can be monitored in individual cells. PMID:17071717

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

Dynamics of Wolbachia pipientis Gene Expression Across the Drosophila melanogaster Life Cycle

PubMed Central

Gutzwiller, Florence; Carmo, Catarina R.; Miller, Danny E.; Rice, Danny W.; Newton, Irene L. G.; Hawley, R. Scott; Teixeira, Luis; Bergman, Casey M.

2015-01-01

Symbiotic interactions between microbes and their multicellular hosts have manifold biological consequences. To better understand how bacteria maintain symbiotic associations with animal hosts, we analyzed genome-wide gene expression for the endosymbiotic α-proteobacteria Wolbachia pipientis across the entire life cycle of Drosophila melanogaster. We found that the majority of Wolbachia genes are expressed stably across the D. melanogaster life cycle, but that 7.8% of Wolbachia genes exhibit robust stage- or sex-specific expression differences when studied in the whole-organism context. Differentially-expressed Wolbachia genes are typically up-regulated after Drosophila embryogenesis and include many bacterial membrane, secretion system, and ankyrin repeat-containing proteins. Sex-biased genes are often organized as small operons of uncharacterized genes and are mainly up-regulated in adult Drosophila males in an age-dependent manner. We also systematically investigated expression levels of previously-reported candidate genes thought to be involved in host-microbe interaction, including those in the WO-A and WO-B prophages and in the Octomom region, which has been implicated in regulating bacterial titer and pathogenicity. Our work provides comprehensive insight into the developmental dynamics of gene expression for a widespread endosymbiont in its natural host context, and shows that public gene expression data harbor rich resources to probe the functional basis of the Wolbachia-Drosophila symbiosis and annotate the transcriptional outputs of the Wolbachia genome. PMID:26497146

Fuzzy support vector machine: an efficient rule-based classification technique for microarrays.

PubMed

Hajiloo, Mohsen; Rabiee, Hamid R; Anooshahpour, Mahdi

2013-01-01

The abundance of gene expression microarray data has led to the development of machine learning algorithms applicable for tackling disease diagnosis, disease prognosis, and treatment selection problems. However, these algorithms often produce classifiers with weaknesses in terms of accuracy, robustness, and interpretability. This paper introduces fuzzy support vector machine which is a learning algorithm based on combination of fuzzy classifiers and kernel machines for microarray classification. Experimental results on public leukemia, prostate, and colon cancer datasets show that fuzzy support vector machine applied in combination with filter or wrapper feature selection methods develops a robust model with higher accuracy than the conventional microarray classification models such as support vector machine, artificial neural network, decision trees, k nearest neighbors, and diagonal linear discriminant analysis. Furthermore, the interpretable rule-base inferred from fuzzy support vector machine helps extracting biological knowledge from microarray data. Fuzzy support vector machine as a new classification model with high generalization power, robustness, and good interpretability seems to be a promising tool for gene expression microarray classification.

RNA-Stabilized Whole Blood Samples but Not Peripheral Blood Mononuclear Cells Can Be Stored for Prolonged Time Periods Prior to Transcriptome Analysis

PubMed Central

Debey-Pascher, Svenja; Hofmann, Andrea; Kreusch, Fatima; Schuler, Gerold; Schuler-Thurner, Beatrice; Schultze, Joachim L.; Staratschek-Jox, Andrea

2011-01-01

Microarray-based transcriptome analysis of peripheral blood as surrogate tissue has become an important approach in clinical implementations. However, application of gene expression profiling in routine clinical settings requires careful consideration of the influence of sample handling and RNA isolation methods on gene expression profile outcome. We evaluated the effect of different sample preservation strategies (eg, cryopreservation of peripheral blood mononuclear cells or freezing of PAXgene-stabilized whole blood samples) on gene expression profiles. Expression profiles obtained from cryopreserved peripheral blood mononuclear cells differed substantially from those of their nonfrozen counterpart samples. Furthermore, expression profiles in cryopreserved peripheral blood mononuclear cell samples were found to undergo significant alterations with increasing storage period, whereas long-term freezing of PAXgene RNA stabilized whole blood samples did not significantly affect stability of gene expression profiles. This report describes important technical aspects contributing toward the establishment of robust and reliable guidance for gene expression studies using peripheral blood and provides a promising strategy for reliable implementation in routine handling for diagnostic purposes. PMID:21704280

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

PubMed

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

2018-02-14

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

Gene Expression Dynamics Inspector (GEDI): for integrative analysis of expression profiles

NASA Technical Reports Server (NTRS)

Eichler, Gabriel S.; Huang, Sui; Ingber, Donald E.

2003-01-01

Genome-wide expression profiles contain global patterns that evade visual detection in current gene clustering analysis. Here, a Gene Expression Dynamics Inspector (GEDI) is described that uses self-organizing maps to translate high-dimensional expression profiles of time courses or sample classes into animated, coherent and robust mosaics images. GEDI facilitates identification of interesting patterns of molecular activity simultaneously across gene, time and sample space without prior assumption of any structure in the data, and then permits the user to retrieve genes of interest. Important changes in genome-wide activities may be quickly identified based on 'Gestalt' recognition and hence, GEDI may be especially useful for non-specialist end users, such as physicians. AVAILABILITY: GEDI v1.0 is written in Matlab, and binary Matlab.dll files which require Matlab to run can be downloaded for free by academic institutions at http://www.chip.org/ge/gedihome.html Supplementary information: http://www.chip.org/ge/gedihome.html.

The complexity of gene expression dynamics revealed by permutation entropy

PubMed Central

2010-01-01

Background High complexity is considered a hallmark of living systems. Here we investigate the complexity of temporal gene expression patterns using the concept of Permutation Entropy (PE) first introduced in dynamical systems theory. The analysis of gene expression data has so far focused primarily on the identification of differentially expressed genes, or on the elucidation of pathway and regulatory relationships. We aim to study gene expression time series data from the viewpoint of complexity. Results Applying the PE complexity metric to abiotic stress response time series data in Arabidopsis thaliana, genes involved in stress response and signaling were found to be associated with the highest complexity not only under stress, but surprisingly, also under reference, non-stress conditions. Genes with house-keeping functions exhibited lower PE complexity. Compared to reference conditions, the PE of temporal gene expression patterns generally increased upon stress exposure. High-complexity genes were found to have longer upstream intergenic regions and more cis-regulatory motifs in their promoter regions indicative of a more complex regulatory apparatus needed to orchestrate their expression, and to be associated with higher correlation network connectivity degree. Arabidopsis genes also present in other plant species were observed to exhibit decreased PE complexity compared to Arabidopsis specific genes. Conclusions We show that Permutation Entropy is a simple yet robust and powerful approach to identify temporal gene expression profiles of varying complexity that is equally applicable to other types of molecular profile data. PMID:21176199

Population Level Purifying Selection and Gene Expression Shape Subgenome Evolution in Maize.

PubMed

Pophaly, Saurabh D; Tellier, Aurélien

2015-12-01

The maize ancestor experienced a recent whole-genome duplication (WGD) followed by gene erosion which generated two subgenomes, the dominant subgenome (maize1) experiencing fewer deletions than maize2. We take advantage of available extensive polymorphism and gene expression data in maize to study purifying selection and gene expression divergence between WGD retained paralog pairs. We first report a strong correlation in nucleotide diversity between duplicate pairs, except for upstream regions. We then show that maize1 genes are under stronger purifying selection than maize2. WGD retained genes have higher gene dosage and biased Gene Ontologies consistent with previous studies. The relative gene expression of paralogs across tissues demonstrates that 98% of duplicate pairs have either subfunctionalized in a tissuewise manner or have diverged consistently in their expression thereby preventing functional complementation. Tissuewise subfunctionalization seems to be a hallmark of transcription factors, whereas consistent repression occurs for macromolecular complexes. We show that dominant gene expression is a strong determinant of the strength of purifying selection, explaining the inferred stronger negative selection on maize1 genes. We propose a novel expression-based classification of duplicates which is more robust to explain observed polymorphism patterns than the subgenome location. Finally, upstream regions of repressed genes exhibit an enrichment in transposable elements which indicates a possible mechanism for expression divergence. © 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.

Analyzing gene expression time-courses based on multi-resolution shape mixture model.

PubMed

Li, Ying; He, Ye; Zhang, Yu

2016-11-01

Biological processes actually are a dynamic molecular process over time. Time course gene expression experiments provide opportunities to explore patterns of gene expression change over a time and understand the dynamic behavior of gene expression, which is crucial for study on development and progression of biology and disease. Analysis of the gene expression time-course profiles has not been fully exploited so far. It is still a challenge problem. We propose a novel shape-based mixture model clustering method for gene expression time-course profiles to explore the significant gene groups. Based on multi-resolution fractal features and mixture clustering model, we proposed a multi-resolution shape mixture model algorithm. Multi-resolution fractal features is computed by wavelet decomposition, which explore patterns of change over time of gene expression at different resolution. Our proposed multi-resolution shape mixture model algorithm is a probabilistic framework which offers a more natural and robust way of clustering time-course gene expression. We assessed the performance of our proposed algorithm using yeast time-course gene expression profiles compared with several popular clustering methods for gene expression profiles. The grouped genes identified by different methods are evaluated by enrichment analysis of biological pathways and known protein-protein interactions from experiment evidence. The grouped genes identified by our proposed algorithm have more strong biological significance. A novel multi-resolution shape mixture model algorithm based on multi-resolution fractal features is proposed. Our proposed model provides a novel horizons and an alternative tool for visualization and analysis of time-course gene expression profiles. The R and Matlab program is available upon the request. Copyright © 2016 Elsevier Inc. All rights reserved.

A robust two-way semi-linear model for normalization of cDNA microarray data

PubMed Central

Wang, Deli; Huang, Jian; Xie, Hehuang; Manzella, Liliana; Soares, Marcelo Bento

2005-01-01

Background Normalization is a basic step in microarray data analysis. A proper normalization procedure ensures that the intensity ratios provide meaningful measures of relative expression values. Methods We propose a robust semiparametric method in a two-way semi-linear model (TW-SLM) for normalization of cDNA microarray data. This method does not make the usual assumptions underlying some of the existing methods. For example, it does not assume that: (i) the percentage of differentially expressed genes is small; or (ii) the numbers of up- and down-regulated genes are about the same, as required in the LOWESS normalization method. We conduct simulation studies to evaluate the proposed method and use a real data set from a specially designed microarray experiment to compare the performance of the proposed method with that of the LOWESS normalization approach. Results The simulation results show that the proposed method performs better than the LOWESS normalization method in terms of mean square errors for estimated gene effects. The results of analysis of the real data set also show that the proposed method yields more consistent results between the direct and the indirect comparisons and also can detect more differentially expressed genes than the LOWESS method. Conclusions Our simulation studies and the real data example indicate that the proposed robust TW-SLM method works at least as well as the LOWESS method and works better when the underlying assumptions for the LOWESS method are not satisfied. Therefore, it is a powerful alternative to the existing normalization methods. PMID:15663789

Differential gene expression analysis in glioblastoma cells and normal human brain cells based on GEO database.

PubMed

Wang, Anping; Zhang, Guibin

2017-11-01

The differentially expressed genes between glioblastoma (GBM) cells and normal human brain cells were investigated to performed pathway analysis and protein interaction network analysis for the differentially expressed genes. GSE12657 and GSE42656 gene chips, which contain gene expression profile of GBM were obtained from Gene Expression Omniub (GEO) database of National Center for Biotechnology Information (NCBI). The 'limma' data packet in 'R' software was used to analyze the differentially expressed genes in the two gene chips, and gene integration was performed using 'RobustRankAggreg' package. Finally, pheatmap software was used for heatmap analysis and Cytoscape, DAVID, STRING and KOBAS were used for protein-protein interaction, Gene Ontology (GO) and KEGG analyses. As results: i) 702 differentially expressed genes were identified in GSE12657, among those genes, 548 were significantly upregulated and 154 were significantly downregulated (p<0.01, fold-change >1), and 1,854 differentially expressed genes were identified in GSE42656, among the genes, 1,068 were significantly upregulated and 786 were significantly downregulated (p<0.01, fold-change >1). A total of 167 differentially expressed genes including 100 upregulated genes and 67 downregulated genes were identified after gene integration, and the genes showed significantly different expression levels in GBM compared with normal human brain cells (p<0.05). ii) Interactions between the protein products of 101 differentially expressed genes were identified using STRING and expression network was established. A key gene, called CALM3, was identified by Cytoscape software. iii) GO enrichment analysis showed that differentially expressed genes were mainly enriched in 'neurotransmitter:sodium symporter activity' and 'neurotransmitter transporter activity', which can affect the activity of neurotransmitter transportation. KEGG pathway analysis showed that the differentially expressed genes were mainly enriched in 'protein processing in endoplasmic reticulum', which can affect protein processing in endoplasmic reticulum. The results showed that: i) 167 differentially expressed genes were identified from two gene chips after integration; and ii) protein interaction network was established, and GO and KEGG pathway analyses were successfully performed to identify and annotate the key gene, which provide new insights for the studies on GBN at gene level.

Stress amplifies sex differences in primate prefrontal profiles of gene expression.

PubMed

Lee, Alex G; Hagenauer, Megan; Absher, Devin; Morrison, Kathleen E; Bale, Tracy L; Myers, Richard M; Watson, Stanley J; Akil, Huda; Schatzberg, Alan F; Lyons, David M

2017-11-02

Stress is a recognized risk factor for mood and anxiety disorders that occur more often in women than men. Prefrontal brain regions mediate stress coping, cognitive control, and emotion. Here, we investigate sex differences and stress effects on prefrontal cortical profiles of gene expression in squirrel monkey adults. Dorsolateral, ventrolateral, and ventromedial prefrontal cortical regions from 18 females and 12 males were collected after stress or no-stress treatment conditions. Gene expression profiles were acquired using HumanHT-12v4.0 Expression BeadChip arrays adapted for squirrel monkeys. Extensive variation between prefrontal cortical regions was discerned in the expression of numerous autosomal and sex chromosome genes. Robust sex differences were also identified across prefrontal cortical regions in the expression of mostly autosomal genes. Genes with increased expression in females compared to males were overrepresented in mitogen-activated protein kinase and neurotrophin signaling pathways. Many fewer genes with increased expression in males compared to females were discerned, and no molecular pathways were identified. Effect sizes for sex differences were greater in stress compared to no-stress conditions for ventromedial and ventrolateral prefrontal cortical regions but not dorsolateral prefrontal cortex. Stress amplifies sex differences in gene expression profiles for prefrontal cortical regions involved in stress coping and emotion regulation. Results suggest molecular targets for new treatments of stress disorders in human mental health.

Employing conservation of co-expression to improve functional inference

PubMed Central

Daub, Carsten O; Sonnhammer, Erik LL

2008-01-01

Background Observing co-expression between genes suggests that they are functionally coupled. Co-expression of orthologous gene pairs across species may improve function prediction beyond the level achieved in a single species. Results We used orthology between genes of the three different species S. cerevisiae, D. melanogaster, and C. elegans to combine co-expression across two species at a time. This led to increased function prediction accuracy when we incorporated expression data from either of the other two species and even further increased when conservation across both of the two other species was considered at the same time. Employing the conservation across species to incorporate abundant model organism data for the prediction of protein interactions in poorly characterized species constitutes a very powerful annotation method. Conclusion To be able to employ the most suitable co-expression distance measure for our analysis, we evaluated the ability of four popular gene co-expression distance measures to detect biologically relevant interactions between pairs of genes. For the expression datasets employed in our co-expression conservation analysis above, we used the GO and the KEGG PATHWAY databases as gold standards. While the differences between distance measures were small, Spearman correlation showed to give most robust results. PMID:18808668

A Gene Co-Expression Network in Whole Blood of Schizophrenia Patients Is Independent of Antipsychotic-Use and Enriched for Brain-Expressed Genes

PubMed Central

de Jong, Simone; Boks, Marco P. M.; Fuller, Tova F.; Strengman, Eric; Janson, Esther; de Kovel, Carolien G. F.; Ori, Anil P. S.; Vi, Nancy; Mulder, Flip; Blom, Jan Dirk; Glenthøj, Birte; Schubart, Chris D.; Cahn, Wiepke; Kahn, René S.; Horvath, Steve; Ophoff, Roel A.

2012-01-01

Despite large-scale genome-wide association studies (GWAS), the underlying genes for schizophrenia are largely unknown. Additional approaches are therefore required to identify the genetic background of this disorder. Here we report findings from a large gene expression study in peripheral blood of schizophrenia patients and controls. We applied a systems biology approach to genome-wide expression data from whole blood of 92 medicated and 29 antipsychotic-free schizophrenia patients and 118 healthy controls. We show that gene expression profiling in whole blood can identify twelve large gene co-expression modules associated with schizophrenia. Several of these disease related modules are likely to reflect expression changes due to antipsychotic medication. However, two of the disease modules could be replicated in an independent second data set involving antipsychotic-free patients and controls. One of these robustly defined disease modules is significantly enriched with brain-expressed genes and with genetic variants that were implicated in a GWAS study, which could imply a causal role in schizophrenia etiology. The most highly connected intramodular hub gene in this module (ABCF1), is located in, and regulated by the major histocompatibility (MHC) complex, which is intriguing in light of the fact that common allelic variants from the MHC region have been implicated in schizophrenia. This suggests that the MHC increases schizophrenia susceptibility via altered gene expression of regulatory genes in this network. PMID:22761806

GAPTrap: A Simple Expression System for Pluripotent Stem Cells and Their Derivatives.

PubMed

Kao, Tim; Labonne, Tanya; Niclis, Jonathan C; Chaurasia, Ritu; Lokmic, Zerina; Qian, Elizabeth; Bruveris, Freya F; Howden, Sara E; Motazedian, Ali; Schiesser, Jacqueline V; Costa, Magdaline; Sourris, Koula; Ng, Elizabeth; Anderson, David; Giudice, Antonietta; Farlie, Peter; Cheung, Michael; Lamande, Shireen R; Penington, Anthony J; Parish, Clare L; Thomson, Lachlan H; Rafii, Arash; Elliott, David A; Elefanty, Andrew G; Stanley, Edouard G

2016-09-13

The ability to reliably express fluorescent reporters or other genes of interest is important for using human pluripotent stem cells (hPSCs) as a platform for investigating cell fates and gene function. We describe a simple expression system, designated GAPTrap (GT), in which reporter genes, including GFP, mCherry, mTagBFP2, luc2, Gluc, and lacZ are inserted into the GAPDH locus in hPSCs. Independent clones harboring variations of the GT vectors expressed remarkably consistent levels of the reporter gene. Differentiation experiments showed that reporter expression was reliably maintained in hematopoietic cells, cardiac mesoderm, definitive endoderm, and ventral midbrain dopaminergic neurons. Similarly, analysis of teratomas derived from GT-lacZ hPSCs showed that β-galactosidase expression was maintained in a spectrum of cell types representing derivatives of the three germ layers. Thus, the GAPTrap vectors represent a robust and straightforward tagging system that enables indelible labeling of PSCs and their differentiated derivatives. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

An efficient method to identify differentially expressed genes in microarray experiments

PubMed Central

Qin, Huaizhen; Feng, Tao; Harding, Scott A.; Tsai, Chung-Jui; Zhang, Shuanglin

2013-01-01

Motivation Microarray experiments typically analyze thousands to tens of thousands of genes from small numbers of biological replicates. The fact that genes are normally expressed in functionally relevant patterns suggests that gene-expression data can be stratified and clustered into relatively homogenous groups. Cluster-wise dimensionality reduction should make it feasible to improve screening power while minimizing information loss. Results We propose a powerful and computationally simple method for finding differentially expressed genes in small microarray experiments. The method incorporates a novel stratification-based tight clustering algorithm, principal component analysis and information pooling. Comprehensive simulations show that our method is substantially more powerful than the popular SAM and eBayes approaches. We applied the method to three real microarray datasets: one from a Populus nitrogen stress experiment with 3 biological replicates; and two from public microarray datasets of human cancers with 10 to 40 biological replicates. In all three analyses, our method proved more robust than the popular alternatives for identification of differentially expressed genes. Availability The C++ code to implement the proposed method is available upon request for academic use. PMID:18453554

BFDCA: A Comprehensive Tool of Using Bayes Factor for Differential Co-Expression Analysis.

PubMed

Wang, Duolin; Wang, Juexin; Jiang, Yuexu; Liang, Yanchun; Xu, Dong

2017-02-03

Comparing the gene-expression profiles between biological conditions is useful for understanding gene regulation underlying complex phenotypes. Along this line, analysis of differential co-expression (DC) has gained attention in the recent years, where genes under one condition have different co-expression patterns compared with another. We developed an R package Bayes Factor approach for Differential Co-expression Analysis (BFDCA) for DC analysis. BFDCA is unique in integrating various aspects of DC patterns (including Shift, Cross, and Re-wiring) into one uniform Bayes factor. We tested BFDCA using simulation data and experimental data. Simulation results indicate that BFDCA outperforms existing methods in accuracy and robustness of detecting DC pairs and DC modules. Results of using experimental data suggest that BFDCA can cluster disease-related genes into functional DC subunits and estimate the regulatory impact of disease-related genes well. BFDCA also achieves high accuracy in predicting case-control phenotypes by using significant DC gene pairs as markers. BFDCA is publicly available at http://dx.doi.org/10.17632/jdz4vtvnm3.1. Copyright © 2016 Elsevier Ltd. All rights reserved.

Determining Physical Mechanisms of Gene Expression Regulation from Single Cell Gene Expression Data.

PubMed

Ezer, Daphne; Moignard, Victoria; Göttgens, Berthold; Adryan, Boris

2016-08-01

Many genes are expressed in bursts, which can contribute to cell-to-cell heterogeneity. It is now possible to measure this heterogeneity with high throughput single cell gene expression assays (single cell qPCR and RNA-seq). These experimental approaches generate gene expression distributions which can be used to estimate the kinetic parameters of gene expression bursting, namely the rate that genes turn on, the rate that genes turn off, and the rate of transcription. We construct a complete pipeline for the analysis of single cell qPCR data that uses the mathematics behind bursty expression to develop more accurate and robust algorithms for analyzing the origin of heterogeneity in experimental samples, specifically an algorithm for clustering cells by their bursting behavior (Simulated Annealing for Bursty Expression Clustering, SABEC) and a statistical tool for comparing the kinetic parameters of bursty expression across populations of cells (Estimation of Parameter changes in Kinetics, EPiK). We applied these methods to hematopoiesis, including a new single cell dataset in which transcription factors (TFs) involved in the earliest branchpoint of blood differentiation were individually up- and down-regulated. We could identify two unique sub-populations within a seemingly homogenous group of hematopoietic stem cells. In addition, we could predict regulatory mechanisms controlling the expression levels of eighteen key hematopoietic transcription factors throughout differentiation. Detailed information about gene regulatory mechanisms can therefore be obtained simply from high throughput single cell gene expression data, which should be widely applicable given the rapid expansion of single cell genomics.

Aberrant Gene Expression in Humans

PubMed Central

Yang, Ence; Ji, Guoli; Brinkmeyer-Langford, Candice L.; Cai, James J.

2015-01-01

Gene expression as an intermediate molecular phenotype has been a focus of research interest. In particular, studies of expression quantitative trait loci (eQTL) have offered promise for understanding gene regulation through the discovery of genetic variants that explain variation in gene expression levels. Existing eQTL methods are designed for assessing the effects of common variants, but not rare variants. Here, we address the problem by establishing a novel analytical framework for evaluating the effects of rare or private variants on gene expression. Our method starts from the identification of outlier individuals that show markedly different gene expression from the majority of a population, and then reveals the contributions of private SNPs to the aberrant gene expression in these outliers. Using population-scale mRNA sequencing data, we identify outlier individuals using a multivariate approach. We find that outlier individuals are more readily detected with respect to gene sets that include genes involved in cellular regulation and signal transduction, and less likely to be detected with respect to the gene sets with genes involved in metabolic pathways and other fundamental molecular functions. Analysis of polymorphic data suggests that private SNPs of outlier individuals are enriched in the enhancer and promoter regions of corresponding aberrantly-expressed genes, suggesting a specific regulatory role of private SNPs, while the commonly-occurring regulatory genetic variants (i.e., eQTL SNPs) show little evidence of involvement. Additional data suggest that non-genetic factors may also underlie aberrant gene expression. Taken together, our findings advance a novel viewpoint relevant to situations wherein common eQTLs fail to predict gene expression when heritable, rare inter-individual variation exists. The analytical framework we describe, taking into consideration the reality of differential phenotypic robustness, may be valuable for investigating complex traits and conditions. PMID:25617623

A stele-enriched gene regulatory network in the Arabidopsis root

PubMed Central

Brady, Siobhan M; Zhang, Lifang; Megraw, Molly; Martinez, Natalia J; Jiang, Eric; Yi, Charles S; Liu, Weilin; Zeng, Anna; Taylor-Teeples, Mallorie; Kim, Dahae; Ahnert, Sebastian; Ohler, Uwe; Ware, Doreen; Walhout, Albertha J M; Benfey, Philip N

2011-01-01

Tightly controlled gene expression is a hallmark of multicellular development and is accomplished by transcription factors (TFs) and microRNAs (miRNAs). Although many studies have focused on identifying downstream targets of these molecules, less is known about the factors that regulate their differential expression. We used data from high spatial resolution gene expression experiments and yeast one-hybrid (Y1H) and two-hybrid (Y2H) assays to delineate a subset of interactions occurring within a gene regulatory network (GRN) that determines tissue-specific TF and miRNA expression in plants. We find that upstream TFs are expressed in more diverse cell types than their targets and that promoters that are bound by a relatively large number of TFs correspond to key developmental regulators. The regulatory consequence of many TFs for their target was experimentally determined using genetic analysis. Remarkably, molecular phenotypes were identified for 65% of the TFs, but morphological phenotypes were associated with only 16%. This indicates that the GRN is robust, and that gene expression changes may be canalized or buffered. PMID:21245844

Network-Induced Classification Kernels for Gene Expression Profile Analysis

PubMed Central

Dror, Gideon; Shamir, Ron

2012-01-01

Abstract Computational classification of gene expression profiles into distinct disease phenotypes has been highly successful to date. Still, robustness, accuracy, and biological interpretation of the results have been limited, and it was suggested that use of protein interaction information jointly with the expression profiles can improve the results. Here, we study three aspects of this problem. First, we show that interactions are indeed relevant by showing that co-expressed genes tend to be closer in the network of interactions. Second, we show that the improved performance of one extant method utilizing expression and interactions is not really due to the biological information in the network, while in another method this is not the case. Finally, we develop a new kernel method—called NICK—that integrates network and expression data for SVM classification, and demonstrate that overall it achieves better results than extant methods while running two orders of magnitude faster. PMID:22697242

Brain region-specific gene expression changes after chronic intermittent ethanol exposure and early withdrawal in C57BL/6J mice

PubMed Central

Melendez, Roberto I.; McGinty, Jacqueline F.; Kalivas, Peter W.; Becker, Howard C.

2014-01-01

Neuroadaptations that participate in the ontogeny of alcohol dependence are likely a result of altered gene expression in various brain regions. The present study investigated brain region-specific changes in the pattern and magnitude of gene expression immediately following chronic intermittent ethanol (CIE) exposure and 8 hours following final ethanol exposure [i.e. early withdrawal (EWD)]. High-density oligonucleotide microarrays (Affymetrix 430A 2.0, Affymetrix, Santa Clara, CA, USA) and bioinformatics analysis were used to characterize gene expression and function in the prefrontal cortex (PFC), hippocampus (HPC) and nucleus accumbens (NAc) of C57BL/6J mice (Jackson Laboratories, Bar Harbor, ME, USA). Gene expression levels were determined using gene chip robust multi-array average followed by statistical analysis of microarrays and validated by quantitative real-time reverse transcription polymerase chain reaction and Western blot analysis. Results indicated that immediately following CIE exposure, changes in gene expression were strikingly greater in the PFC (284 genes) compared with the HPC (16 genes) and NAc (32 genes). Bioinformatics analysis revealed that most of the transcriptionally responsive genes in the PFC were involved in Ras/MAPK signaling, notch signaling or ubiquitination. In contrast, during EWD, changes in gene expression were greatest in the HPC (139 genes) compared with the PFC (four genes) and NAc (eight genes). The most transcriptionally responsive genes in the HPC were involved in mRNA processing or actin dynamics. Of the few genes detected in the NAc, the most representatives were involved in circadian rhythms. Overall, these findings indicate that brain region-specific and time-dependent neuroadaptive alterations in gene expression play an integral role in the development of alcohol dependence and withdrawal. PMID:21812870

Dynamic gene expression response to altered gravity in human T cells.

PubMed

Thiel, Cora S; Hauschild, Swantje; Huge, Andreas; Tauber, Svantje; Lauber, Beatrice A; Polzer, Jennifer; Paulsen, Katrin; Lier, Hartwin; Engelmann, Frank; Schmitz, Burkhard; Schütte, Andreas; Layer, Liliana E; Ullrich, Oliver

2017-07-12

We investigated the dynamics of immediate and initial gene expression response to different gravitational environments in human Jurkat T lymphocytic cells and compared expression profiles to identify potential gravity-regulated genes and adaptation processes. We used the Affymetrix GeneChip® Human Transcriptome Array 2.0 containing 44,699 protein coding genes and 22,829 non-protein coding genes and performed the experiments during a parabolic flight and a suborbital ballistic rocket mission to cross-validate gravity-regulated gene expression through independent research platforms and different sets of control experiments to exclude other factors than alteration of gravity. We found that gene expression in human T cells rapidly responded to altered gravity in the time frame of 20 s and 5 min. The initial response to microgravity involved mostly regulatory RNAs. We identified three gravity-regulated genes which could be cross-validated in both completely independent experiment missions: ATP6V1A/D, a vacuolar H + -ATPase (V-ATPase) responsible for acidification during bone resorption, IGHD3-3/IGHD3-10, diversity genes of the immunoglobulin heavy-chain locus participating in V(D)J recombination, and LINC00837, a long intergenic non-protein coding RNA. Due to the extensive and rapid alteration of gene expression associated with regulatory RNAs, we conclude that human cells are equipped with a robust and efficient adaptation potential when challenged with altered gravitational environments.

A Robust Unified Approach to Analyzing Methylation and Gene Expression Data

PubMed Central

Khalili, Abbas; Huang, Tim; Lin, Shili

2009-01-01

Microarray technology has made it possible to investigate expression levels, and more recently methylation signatures, of thousands of genes simultaneously, in a biological sample. Since more and more data from different biological systems or technological platforms are being generated at an incredible rate, there is an increasing need to develop statistical methods that are applicable to multiple data types and platforms. Motivated by such a need, a flexible finite mixture model that is applicable to methylation, gene expression, and potentially data from other biological systems, is proposed. Two major thrusts of this approach are to allow for a variable number of components in the mixture to capture non-biological variation and small biases, and to use a robust procedure for parameter estimation and probe classification. The method was applied to the analysis of methylation signatures of three breast cancer cell lines. It was also tested on three sets of expression microarray data to study its power and type I error rates. Comparison with a number of existing methods in the literature yielded very encouraging results; lower type I error rates and comparable/better power were achieved based on the limited study. Furthermore, the method also leads to more biologically interpretable results for the three breast cancer cell lines. PMID:20161265

Transcriptional Regulation of Pattern-Triggered Immunity in Plants.

PubMed

Li, Bo; Meng, Xiangzong; Shan, Libo; He, Ping

2016-05-11

Perception of microbe-associated molecular patterns (MAMPs) by cell-surface-resident pattern recognition receptors (PRRs) induces rapid, robust, and selective transcriptional reprogramming, which is central for launching effective pattern-triggered immunity (PTI) in plants. Signal relay from PRR complexes to the nuclear transcriptional machinery via intracellular kinase cascades rapidly activates primary immune response genes. The coordinated action of gene-specific transcription factors and the general transcriptional machinery contribute to the selectivity of immune gene activation. In addition, PRR complexes and signaling components are often transcriptionally upregulated upon MAMP perception to ensure the robustness and sustainability of PTI outputs. In this review, we discuss recent advances in deciphering the signaling pathways and regulatory mechanisms that coordinately lead to timely and accurate MAMP-induced gene expression in plants. Copyright © 2016 Elsevier Inc. All rights reserved.

Identification of expression quantitative trait loci by the interaction analysis using genetic algorithm.

PubMed

Namkung, Junghyun; Nam, Jin-Wu; Park, Taesung

2007-01-01

Many genes with major effects on quantitative traits have been reported to interact with other genes. However, finding a group of interacting genes from thousands of SNPs is challenging. Hence, an efficient and robust algorithm is needed. The genetic algorithm (GA) is useful in searching for the optimal solution from a very large searchable space. In this study, we show that genome-wide interaction analysis using GA and a statistical interaction model can provide a practical method to detect biologically interacting loci. We focus our search on transcriptional regulators by analyzing gene x gene interactions for cancer-related genes. The expression values of three cancer-related genes were selected from the expression data of the Genetic Analysis Workshop 15 Problem 1 data set. We implemented a GA to identify the expression quantitative trait loci that are significantly associated with expression levels of the cancer-related genes. The time complexity of the GA was compared with that of an exhaustive search algorithm. As a result, our GA, which included heuristic methods, such as archive, elitism, and local search, has greatly reduced computational time in a genome-wide search for gene x gene interactions. In general, the GA took one-fifth the computation time of an exhaustive search for the most significant pair of single-nucleotide polymorphisms.

Identification of expression quantitative trait loci by the interaction analysis using genetic algorithm

PubMed Central

Namkung, Junghyun; Nam, Jin-Wu; Park, Taesung

2007-01-01

Many genes with major effects on quantitative traits have been reported to interact with other genes. However, finding a group of interacting genes from thousands of SNPs is challenging. Hence, an efficient and robust algorithm is needed. The genetic algorithm (GA) is useful in searching for the optimal solution from a very large searchable space. In this study, we show that genome-wide interaction analysis using GA and a statistical interaction model can provide a practical method to detect biologically interacting loci. We focus our search on transcriptional regulators by analyzing gene × gene interactions for cancer-related genes. The expression values of three cancer-related genes were selected from the expression data of the Genetic Analysis Workshop 15 Problem 1 data set. We implemented a GA to identify the expression quantitative trait loci that are significantly associated with expression levels of the cancer-related genes. The time complexity of the GA was compared with that of an exhaustive search algorithm. As a result, our GA, which included heuristic methods, such as archive, elitism, and local search, has greatly reduced computational time in a genome-wide search for gene × gene interactions. In general, the GA took one-fifth the computation time of an exhaustive search for the most significant pair of single-nucleotide polymorphisms. PMID:18466570

Pregnancy Suppresses the Daily Rhythmicity of Core Body Temperature and Adipose Metabolic Gene Expression in the Mouse.

PubMed

Wharfe, Michaela D; Wyrwoll, Caitlin S; Waddell, Brendan J; Mark, Peter J

2016-09-01

Maternal adaptations in lipid metabolism are crucial for pregnancy success due to the role of white adipose tissue as an energy store and the dynamic nature of energy needs across gestation. Because lipid metabolism is regulated by the rhythmic expression of clock genes, it was hypothesized that maternal metabolic adaptations involve changes in both adipose clock gene expression and the rhythmic expression of downstream metabolic genes. Maternal core body temperature (Tc) was investigated as a possible mechanism driving pregnancy-induced changes in clock gene expression. Gonadal adipose tissue and plasma were collected from C57BL/6J mice before and on days 6, 10, 14, and 18 of pregnancy (term 19 d) at 4-hour intervals across a 24-hour period. Adipose expression of clock genes and downstream metabolic genes were determined by quantitative RT-PCR, and Tc was measured by intraperitoneal temperature loggers. Adipose clock gene expression showed robust rhythmicity throughout pregnancy, but absolute levels varied substantially across gestation. Rhythmic expression of the metabolic genes Lipe, Pnpla2, and Lpl was clearly evident before pregnancy; however, this rhythmicity was lost with the onset of pregnancy. Tc rhythm was significantly altered by pregnancy, with a 65% decrease in amplitude by term and a 0.61°C decrease in mesor between days 6 and 18. These changes in Tc, however, did not appear to be linked to adipose clock gene expression across pregnancy. Overall, our data show marked adaptations in the adipose clock in pregnancy, with an apparent decoupling of adipose clock and lipolytic/lipogenic gene rhythms from early in gestation.

Mining biological information from 3D short time-series gene expression data: the OPTricluster algorithm.

PubMed

Tchagang, Alain B; Phan, Sieu; Famili, Fazel; Shearer, Heather; Fobert, Pierre; Huang, Yi; Zou, Jitao; Huang, Daiqing; Cutler, Adrian; Liu, Ziying; Pan, Youlian

2012-04-04

Nowadays, it is possible to collect expression levels of a set of genes from a set of biological samples during a series of time points. Such data have three dimensions: gene-sample-time (GST). Thus they are called 3D microarray gene expression data. To take advantage of the 3D data collected, and to fully understand the biological knowledge hidden in the GST data, novel subspace clustering algorithms have to be developed to effectively address the biological problem in the corresponding space. We developed a subspace clustering algorithm called Order Preserving Triclustering (OPTricluster), for 3D short time-series data mining. OPTricluster is able to identify 3D clusters with coherent evolution from a given 3D dataset using a combinatorial approach on the sample dimension, and the order preserving (OP) concept on the time dimension. The fusion of the two methodologies allows one to study similarities and differences between samples in terms of their temporal expression profile. OPTricluster has been successfully applied to four case studies: immune response in mice infected by malaria (Plasmodium chabaudi), systemic acquired resistance in Arabidopsis thaliana, similarities and differences between inner and outer cotyledon in Brassica napus during seed development, and to Brassica napus whole seed development. These studies showed that OPTricluster is robust to noise and is able to detect the similarities and differences between biological samples. Our analysis showed that OPTricluster generally outperforms other well known clustering algorithms such as the TRICLUSTER, gTRICLUSTER and K-means; it is robust to noise and can effectively mine the biological knowledge hidden in the 3D short time-series gene expression data.

Systemic injection of AAV9 carrying a periostin promoter targets gene expression to a myofibroblast-like lineage in mouse hearts after reperfused myocardial infarction.

PubMed

Piras, B A; Tian, Y; Xu, Y; Thomas, N A; O'Connor, D M; French, B A

2016-05-01

Adeno-associated virus (AAV) has been used to direct gene transfer to a variety of tissues, including heart, liver, skeletal muscle, brain, kidney and lung, but it has not previously been shown to effectively target fibroblasts in vivo, including cardiac fibroblasts. We constructed expression cassettes using a modified periostin promoter to drive gene expression in a cardiac myofibroblast-like lineage, with only occasional spillover into cardiomyocyte-like cells. We compared AAV serotypes 6 and 9 and found robust gene expression when the vectors were delivered by systemic injection after myocardial infarction (MI), with little expression in healthy, non-infarcted mice. AAV9 provided expression in a greater number of cells than AAV6, with reporter gene expression visible in the cardiac infarct and border zones from 5 to 62 days post MI, as assessed by luciferase and Cre-activated green fluorescent protein expression. Although common myofibroblast markers were expressed in low abundance, most of the targeted cells expressed myosin IIb, an embryonic form of smooth muscle myosin heavy chain that has previously been associated with myofibroblasts after reperfused MI. This study is the first to demonstrate AAV-mediated expression in a potentially novel myofibroblast-like lineage in mouse hearts post MI and may open new avenues of gene therapy to treat patients surviving MI.

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.

Performance Assessment of Kernel Density Clustering for Gene Expression Profile Data

PubMed Central

Zeng, Beiyan; Chen, Yiping P.; Smith, Oscar H.

2003-01-01

Kernel density smoothing techniques have been used in classification or supervised learning of gene expression profile (GEP) data, but their applications to clustering or unsupervised learning of those data have not been explored and assessed. Here we report a kernel density clustering method for analysing GEP data and compare its performance with the three most widely-used clustering methods: hierarchical clustering, K-means clustering, and multivariate mixture model-based clustering. Using several methods to measure agreement, between-cluster isolation, and withincluster coherence, such as the Adjusted Rand Index, the Pseudo F test, the r2 test, and the profile plot, we have assessed the effectiveness of kernel density clustering for recovering clusters, and its robustness against noise on clustering both simulated and real GEP data. Our results show that the kernel density clustering method has excellent performance in recovering clusters from simulated data and in grouping large real expression profile data sets into compact and well-isolated clusters, and that it is the most robust clustering method for analysing noisy expression profile data compared to the other three methods assessed. PMID:18629292

Evaluation of Two Outlier-Detection-Based Methods for Detecting Tissue-Selective Genes from Microarray Data

PubMed Central

Kadota, Koji; Konishi, Tomokazu; Shimizu, Kentaro

2007-01-01

Large-scale expression profiling using DNA microarrays enables identification of tissue-selective genes for which expression is considerably higher and/or lower in some tissues than in others. Among numerous possible methods, only two outlier-detection-based methods (an AIC-based method and Sprent’s non-parametric method) can treat equally various types of selective patterns, but they produce substantially different results. We investigated the performance of these two methods for different parameter settings and for a reduced number of samples. We focused on their ability to detect selective expression patterns robustly. We applied them to public microarray data collected from 36 normal human tissue samples and analyzed the effects of both changing the parameter settings and reducing the number of samples. The AIC-based method was more robust in both cases. The findings confirm that the use of the AIC-based method in the recently proposed ROKU method for detecting tissue-selective expression patterns is correct and that Sprent’s method is not suitable for ROKU. PMID:19936074

Whole Blood Gene Expression Profiling Predicts Severe Morbidity and Mortality in Cystic Fibrosis: A 5-Year Follow-Up Study.

PubMed

Saavedra, Milene T; Quon, Bradley S; Faino, Anna; Caceres, Silvia M; Poch, Katie R; Sanders, Linda A; Malcolm, Kenneth C; Nichols, David P; Sagel, Scott D; Taylor-Cousar, Jennifer L; Leach, Sonia M; Strand, Matthew; Nick, Jerry A

2018-05-01

Cystic fibrosis pulmonary exacerbations accelerate pulmonary decline and increase mortality. Previously, we identified a 10-gene leukocyte panel measured directly from whole blood, which indicates response to exacerbation treatment. We hypothesized that molecular characteristics of exacerbations could also predict future disease severity. We tested whether a 10-gene panel measured from whole blood could identify patient cohorts at increased risk for severe morbidity and mortality, beyond standard clinical measures. Transcript abundance for the 10-gene panel was measured from whole blood at the beginning of exacerbation treatment (n = 57). A hierarchical cluster analysis of subjects based on their gene expression was performed, yielding four molecular clusters. An analysis of cluster membership and outcomes incorporating an independent cohort (n = 21) was completed to evaluate robustness of cluster partitioning of genes to predict severe morbidity and mortality. The four molecular clusters were analyzed for differences in forced expiratory volume in 1 second, C-reactive protein, return to baseline forced expiratory volume in 1 second after treatment, time to next exacerbation, and time to morbidity or mortality events (defined as lung transplant referral, lung transplant, intensive care unit admission for respiratory insufficiency, or death). Clustering based on gene expression discriminated between patient groups with significant differences in forced expiratory volume in 1 second, admission frequency, and overall morbidity and mortality. At 5 years, all subjects in cluster 1 (very low risk) were alive and well, whereas 90% of subjects in cluster 4 (high risk) had suffered a major event (P = 0.0001). In multivariable analysis, the ability of gene expression to predict clinical outcomes remained significant, despite adjustment for forced expiratory volume in 1 second, sex, and admission frequency. The robustness of gene clustering to categorize patients appropriately in terms of clinical characteristics, and short- and long-term clinical outcomes, remained consistent, even when adding in a secondary population with significantly different clinical outcomes. Whole blood gene expression profiling allows molecular classification of acute pulmonary exacerbations, beyond standard clinical measures, providing a predictive tool for identifying subjects at increased risk for mortality and disease progression.

Superior Cross-Species Reference Genes: A Blueberry Case Study

PubMed Central

Die, Jose V.; Rowland, Lisa J.

2013-01-01

The advent of affordable Next Generation Sequencing technologies has had major impact on studies of many crop species, where access to genomic technologies and genome-scale data sets has been extremely limited until now. The recent development of genomic resources in blueberry will enable the application of high throughput gene expression approaches that should relatively quickly increase our understanding of blueberry physiology. These studies, however, require a highly accurate and robust workflow and make necessary the identification of reference genes with high expression stability for correct target gene normalization. To create a set of superior reference genes for blueberry expression analyses, we mined a publicly available transcriptome data set from blueberry for orthologs to a set of Arabidopsis genes that showed the most stable expression in a developmental series. In total, the expression stability of 13 putative reference genes was evaluated by qPCR and a set of new references with high stability values across a developmental series in fruits and floral buds of blueberry were identified. We also demonstrated the need to use at least two, preferably three, reference genes to avoid inconsistencies in results, even when superior reference genes are used. The new references identified here provide a valuable resource for accurate normalization of gene expression in Vaccinium spp. and may be useful for other members of the Ericaceae family as well. PMID:24058469

A Luciferase Reporter Gene System for High-Throughput Screening of γ-Globin Gene Activators.

PubMed

Xie, Wensheng; Silvers, Robert; Ouellette, Michael; Wu, Zining; Lu, Quinn; Li, Hu; Gallagher, Kathleen; Johnson, Kathy; Montoute, Monica

2016-01-01

Luciferase reporter gene assays have long been used for drug discovery due to their high sensitivity and robust signal. A dual reporter gene system contains a gene of interest and a control gene to monitor non-specific effects on gene expression. In our dual luciferase reporter gene system, a synthetic promoter of γ-globin gene was constructed immediately upstream of the firefly luciferase gene, followed downstream by a synthetic β-globin gene promoter in front of the Renilla luciferase gene. A stable cell line with the dual reporter gene was cloned and used for all assay development and HTS work. Due to the low activity of the control Renilla luciferase, only the firefly luciferase activity was further optimized for HTS. Several critical factors, such as cell density, serum concentration, and miniaturization, were optimized using tool compounds to achieve maximum robustness and sensitivity. Using the optimized reporter assay, the HTS campaign was successfully completed and approximately 1000 hits were identified. In this chapter, we also describe strategies to triage hits that non-specifically interfere with firefly luciferase.

Gene expression in the liver of rainbow trout, Oncorhynchus mykiss, during the stress response

USGS Publications Warehouse

Momoda, T.S.; Schwindt, A.R.; Feist, G.W.; Gerwick, L.; Bayne, C.J.; Schreck, C.B.

2007-01-01

To better appreciate the mechanisms underlying the physiology of the stress response, an oligonucleotide microarray and real-time RT-PCR (QRT-PCR) were used to study gene expression in the livers of rainbow trout (Oncorhynchus mykiss). For increased confidence in the discovery of candidate genes responding to stress, we conducted two separate experiments using fish from different year classes. In both experiments, fish exposed to a 3 h stressor were compared to control (unstressed) fish. In the second experiment some additional fish were exposed to only 0.5 h of stress and others were sampled 21 h after experiencing a 3 h stressor. This 21 h post-stress treatment was a means to study gene expression during recovery from stress. The genes we report as differentially expressed are those that responded similarly in both experiments, suggesting that they are robust indicators of stress. Those genes are a major histocompatibility complex class 1 molecule (MHC1), JunB, glucose 6-phosphatase (G6Pase), and nuclear protein 1 (Nupr1). Interestingly, Nupr1 gene expression was still elevated 21 h after stress, which indicates that recovery was incomplete at that time.

Fetal-sex dependent genomic responses in the circulating lymphocytes of arsenic-exposed pregnant women in New Hampshire.

PubMed

Bommarito, Paige A; Martin, Elizabeth; Smeester, Lisa; Palys, Thomas; Baker, Emily R; Karagas, Margaret R; Fry, Rebecca C

2017-10-01

Exposure to inorganic arsenic (iAs) during pregnancy is associated with adverse health outcomes present both at birth and later in life. A biological mechanism may include epigenetic and genomic alterations in fetal genes involved in immune functioning. To investigate the role of the maternal immune response to in utero iAs exposure, we conducted an analysis of the expression of immune-related genes in pregnant women from the New Hampshire Birth Cohort Study. A set of 31 genes was identified with altered expression in association with levels of urinary total arsenic, urinary iAs, urinary monomethylated arsenic and urinary dimethylated arsenic. Notably, maternal gene expression signatures differed when stratified on fetal sex, with a more robust inflammatory response observed in male pregnancies. Moreover, the differentially expressed genes were also related to birth outcomes. These findings highlight the sex-dependent nature of the maternal iAs-induced inflammatory response in relationship to fetal outcomes. Copyright © 2017. Published by Elsevier Inc.

Identification of candidate genes for yeast engineering to improve bioethanol production in very high gravity and lignocellulosic biomass industrial fermentations.

PubMed

Pereira, Francisco B; Guimarães, Pedro Mr; Gomes, Daniel G; Mira, Nuno P; Teixeira, Miguel C; Sá-Correia, Isabel; Domingues, Lucília

2011-12-09

The optimization of industrial bioethanol production will depend on the rational design and manipulation of industrial strains to improve their robustness against the many stress factors affecting their performance during very high gravity (VHG) or lignocellulosic fermentations. In this study, a set of Saccharomyces cerevisiae genes found, through genome-wide screenings, to confer resistance to the simultaneous presence of different relevant stresses were identified as required for maximal fermentation performance under industrial conditions. Chemogenomics data were used to identify eight genes whose expression confers simultaneous resistance to high concentrations of glucose, acetic acid and ethanol, chemical stresses relevant for VHG fermentations; and eleven genes conferring simultaneous resistance to stresses relevant during lignocellulosic fermentations. These eleven genes were identified based on two different sets: one with five genes granting simultaneous resistance to ethanol, acetic acid and furfural, and the other with six genes providing simultaneous resistance to ethanol, acetic acid and vanillin. The expression of Bud31 and Hpr1 was found to lead to the increase of both ethanol yield and fermentation rate, while Pho85, Vrp1 and Ygl024w expression is required for maximal ethanol production in VHG fermentations. Five genes, Erg2, Prs3, Rav1, Rpb4 and Vma8, were found to contribute to the maintenance of cell viability in wheat straw hydrolysate and/or the maximal fermentation rate of this substrate. The identified genes stand as preferential targets for genetic engineering manipulation in order to generate more robust industrial strains, able to cope with the most significant fermentation stresses and, thus, to increase ethanol production rate and final ethanol titers.

Lhx2 Determines Odorant Receptor Expression Frequency in Mature Olfactory Sensory Neurons

PubMed Central

Zhang, Guangfan; Titlow, William B.; Biecker, Stephanie M.; Stromberg, Arnold J.

2016-01-01

Abstract A developmental program of epigenetic repression prepares each mammalian olfactory sensory neuron (OSN) to strongly express one allele from just one of hundreds of odorant receptor (OR) genes, but what completes this process of OR gene choice by driving the expression of this allele is incompletely understood. Conditional deletion experiments in mice demonstrate that Lhx2 is necessary for normal expression frequencies of nearly all ORs and all trace amine-associated receptors, irrespective of whether the deletion of Lhx2 is initiated in immature or mature OSNs. Given previous evidence that Lhx2 binds OR gene control elements, these findings indicate that Lhx2 is directly involved in driving OR expression. The data also support the conclusion that OR expression is necessary to allow immature OSNs to complete differentiation and become mature. In contrast to the robust effects of conditional deletion of Lhx2, the loss of Emx2 has much smaller effects and more often causes increased expression frequencies. Lhx2:Emx2 double mutants show opposing effects on Olfr15 expression that reveal independent effects of these two transcription factors. While Lhx2 is necessary for OR expression that supports OR gene choice, Emx2 can act differently; perhaps by helping to control the availability of OR genes for expression. PMID:27822500

Influence of socioeconomic status on the whole blood transcriptome in African Americans.

PubMed

Gaye, Amadou; Gibbons, Gary H; Barry, Charles; Quarells, Rakale; Davis, Sharon K

2017-01-01

The correlation between low socioeconomic status (SES) and poor health outcome or higher risk of disease has been consistently reported by many epidemiological studies across various race/ancestry groups. However, the biological mechanisms linking low SES to disease and/or disease risk factors are not well understood and remain relatively under-studied. The analysis of the blood transcriptome is a promising window for elucidating how social and environmental factors influence the molecular networks governing health and disease. To further define the mechanistic pathways between social determinants and health, this study examined the impact of SES on the blood transcriptome in a sample of African-Americans. An integrative approach leveraging three complementary methods (Weighted Gene Co-expression Network Analysis, Random Forest and Differential Expression) was adopted to identify the most predictive and robust transcriptome pathways associated with SES. We analyzed the expression of 15079 genes (RNA-seq) from whole blood across 36 samples. The results revealed a cluster of 141 co-expressed genes over-expressed in the low SES group. Three pro-inflammatory pathways (IL-8 Signaling, NF-κB Signaling and Dendritic Cell Maturation) are activated in this module and over-expressed in low SES. Random Forest analysis revealed 55 of the 141 genes that, collectively, predict SES with an area under the curve of 0.85. One third of the 141 genes are significantly over-expressed in the low SES group. Lower SES has consistently been linked to many social and environmental conditions acting as stressors and known to be correlated with vulnerability to chronic illnesses (e.g. asthma, diabetes) associated with a chronic inflammatory state. Our unbiased analysis of the blood transcriptome in African-Americans revealed evidence of a robust molecular signature of increased inflammation associated with low SES. The results provide a plausible link between the social factors and chronic inflammation.

Robust TLR4-induced gene expression patterns are not an accurate indicator of human immunity

PubMed Central

2010-01-01

Background Activation of Toll-like receptors (TLRs) is widely accepted as an essential event for defence against infection. Many TLRs utilize a common signalling pathway that relies on activation of the kinase IRAK4 and the transcription factor NFκB for the rapid expression of immunity genes. Methods 21 K DNA microarray technology was used to evaluate LPS-induced (TLR4) gene responses in blood monocytes from a child with an IRAK4-deficiency. In vitro responsiveness to LPS was confirmed by real-time PCR and ELISA and compared to the clinical predisposition of the child and IRAK4-deficient mice to Gram negative infection. Results We demonstrated that the vast majority of LPS-responsive genes in IRAK4-deficient monocytes were greatly suppressed, an observation that is consistent with the described role for IRAK4 as an essential component of TLR4 signalling. The severely impaired response to LPS, however, is inconsistent with a remarkably low incidence of Gram negative infections observed in this child and other children with IRAK4-deficiency. This unpredicted clinical phenotype was validated by demonstrating that IRAK4-deficient mice had a similar resistance to infection with Gram negative S. typhimurium as wildtype mice. A number of immunity genes, such as chemokines, were expressed at normal levels in human IRAK4-deficient monocytes, indicating that particular IRAK4-independent elements within the repertoire of TLR4-induced responses are expressed. Conclusions Sufficient defence to Gram negative immunity does not require IRAK4 or a robust, 'classic' inflammatory and immune response. PMID:20105294

Identifying gnostic predictors of the vaccine response.

PubMed

Haining, W Nicholas; Pulendran, Bali

2012-06-01

Molecular predictors of the response to vaccination could transform vaccine development. They would allow larger numbers of vaccine candidates to be rapidly screened, shortening the development time for new vaccines. Gene-expression based predictors of vaccine response have shown early promise. However, a limitation of gene-expression based predictors is that they often fail to reveal the mechanistic basis of their ability to classify response. Linking predictive signatures to the function of their component genes would advance basic understanding of vaccine immunity and also improve the robustness of vaccine prediction. New analytic tools now allow more biological meaning to be extracted from predictive signatures. Functional genomic approaches to perturb gene expression in mammalian cells permit the function of predictive genes to be surveyed in highly parallel experiments. The challenge for vaccinologists is therefore to use these tools to embed mechanistic insights into predictors of vaccine response. Copyright © 2012 Elsevier Ltd. All rights reserved.

Identifying gnostic predictors of the vaccine response

PubMed Central

Haining, W. Nicholas; Pulendran, Bali

2012-01-01

Molecular predictors of the response to vaccination could transform vaccine development. They would allow larger numbers of vaccine candidates to be rapidly screened, shortening the development time for new vaccines. Gene-expression based predictors of vaccine response have shown early promise. However, a limitation of gene-expression based predictors is that they often fail to reveal the mechanistic basis for their ability to classify response. Linking predictive signatures to the function of their component genes would advance basic understanding of vaccine immunity and also improve the robustness of outcome classification. New analytic tools now allow more biological meaning to be extracted from predictive signatures. Functional genomic approaches to perturb gene expression in mammalian cells permit the function of predictive genes to be surveyed in highly parallel experiments. The challenge for vaccinologists is therefore to use these tools to embed mechanistic insights into predictors of vaccine response. PMID:22633886

Association of DNA methylation and monoamine oxidase A gene expression in the brains of different dog breeds.

PubMed

Eo, JungWoo; Lee, Hee-Eun; Nam, Gyu-Hwi; Kwon, Yun-Jeong; Choi, Yuri; Choi, Bong-Hwan; Huh, Jae-Won; Kim, Minkyu; Lee, Sang-Eun; Seo, Bohyun; Kim, Heui-Soo

2016-04-15

The monoamine oxidase A (MAOA) gene is an important candidate gene for human behavior that encodes an enzyme regulating the metabolism of key neurotransmitters. The regulatory mechanisms of the MAOA gene in dogs are yet to be elucidated. We measured MAOA gene transcription and analyzed the VNTR genotype and methylation status of the gene promoter region in different dog breeds to determine whether MAOA expression is correlated with the MAOA genotype or epigenetic modification in dogs. We found brain-specific expression of the MAOA gene and different transcription levels in different dog breeds including Beagle, Sapsaree, and German shepherd, and also a robust association of the DNA methylation of the gene promoter with mRNA levels. However, the 90 bp tandem repeats that we observed near the transcription start site were not variable, indicating no correlation with canine MAOA activity. These results show that differential DNA methylation in the MAOA promoter region may affect gene expression by modulating promoter activity. Moreover, the distinctive patterns of MAOA expression and DNA methylation may be involved in breed-specific or individual behavioral characteristics, such as aggression, because behavioral phenotypes are related to different physiological and neuroendocrine responses. Copyright © 2016 Elsevier B.V. All rights reserved.

Regularization strategies for hyperplane classifiers: application to cancer classification with gene expression data.

PubMed

Andries, Erik; Hagstrom, Thomas; Atlas, Susan R; Willman, Cheryl

2007-02-01

Linear discrimination, from the point of view of numerical linear algebra, can be treated as solving an ill-posed system of linear equations. In order to generate a solution that is robust in the presence of noise, these problems require regularization. Here, we examine the ill-posedness involved in the linear discrimination of cancer gene expression data with respect to outcome and tumor subclasses. We show that a filter factor representation, based upon Singular Value Decomposition, yields insight into the numerical ill-posedness of the hyperplane-based separation when applied to gene expression data. We also show that this representation yields useful diagnostic tools for guiding the selection of classifier parameters, thus leading to improved performance.

A novel gene expression-based prognostic scoring system to predict survival in gastric cancer

DOE PAGES

Wang, Pin; Wang, Yunshan; Hang, Bo; ...

2016-07-11

Analysis of gene expression patterns in gastric cancer (GC) can help to identify a comprehensive panel of gene biomarkers for predicting clinical outcomes and to discover potential new therapeutic targets. Here, a multi-step bioinformatics analytic approach was developed to establish a novel prognostic scoring system for GC. We first identified 276 genes that were robustly differentially expressed between normal and GC tissues, of which, 249 were found to be significantly associated with overall survival (OS) by univariate Cox regression analysis. The biological functions of 249 genes are related to cell cycle, RNA/ncRNA process, acetylation and extracellular matrix organization. A networkmore » was generated for view of the gene expression architecture of 249 genes in 265 GCs. Finally, we applied a canonical discriminant analysis approach to identify a 53-gene signature and a prognostic scoring system was established based on a canonical discriminant function of 53 genes. The prognostic scores strongly predicted patients with GC to have either a poor or good OS. Our study raises the prospect that the practicality of GC patient prognosis can be assessed by this prognostic scoring system.« less

A novel gene expression-based prognostic scoring system to predict survival in gastric cancer

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

Wang, Pin; Wang, Yunshan; Hang, Bo

Analysis of gene expression patterns in gastric cancer (GC) can help to identify a comprehensive panel of gene biomarkers for predicting clinical outcomes and to discover potential new therapeutic targets. Here, a multi-step bioinformatics analytic approach was developed to establish a novel prognostic scoring system for GC. We first identified 276 genes that were robustly differentially expressed between normal and GC tissues, of which, 249 were found to be significantly associated with overall survival (OS) by univariate Cox regression analysis. The biological functions of 249 genes are related to cell cycle, RNA/ncRNA process, acetylation and extracellular matrix organization. A networkmore » was generated for view of the gene expression architecture of 249 genes in 265 GCs. Finally, we applied a canonical discriminant analysis approach to identify a 53-gene signature and a prognostic scoring system was established based on a canonical discriminant function of 53 genes. The prognostic scores strongly predicted patients with GC to have either a poor or good OS. Our study raises the prospect that the practicality of GC patient prognosis can be assessed by this prognostic scoring system.« less

TALE activators regulate gene expression in a position- and strand-dependent manner in mammalian cells.

PubMed

Uhde-Stone, Claudia; Cheung, Edna; Lu, Biao

2014-01-24

Transcription activator-like effectors (TALEs) are a class of transcription factors that are readily programmable to regulate gene expression. Despite their growing popularity, little is known about binding site parameters that influence TALE-mediated gene activation in mammalian cells. We demonstrate that TALE activators modulate gene expression in mammalian cells in a position- and strand-dependent manner. To study the effects of binding site location, we engineered TALEs customized to recognize specific DNA sequences located in either the promoter or the transcribed region of reporter genes. We found that TALE activators robustly activated reporter genes when their binding sites were located within the promoter region. In contrast, TALE activators inhibited the expression of reporter genes when their binding sites were located on the sense strand of the transcribed region. Notably, this repression was independent of the effector domain utilized, suggesting a simple blockage mechanism. We conclude that TALE activators in mammalian cells regulate genes in a position- and strand-dependent manner that is substantially different from gene activation by native TALEs in plants. These findings have implications for optimizing the design of custom TALEs for genetic manipulation in mammalian cells. Copyright © 2013 Elsevier Inc. All rights reserved.

Validation of Reference Genes for Real-Time Quantitative PCR (qPCR) Analysis of Avibacterium paragallinarum.

PubMed

Wen, Shuxiang; Chen, Xiaoling; Xu, Fuzhou; Sun, Huiling

2016-01-01

Real-time quantitative reverse transcription PCR (qRT-PCR) offers a robust method for measurement of gene expression levels. Selection of reliable reference gene(s) for gene expression study is conducive to reduce variations derived from different amounts of RNA and cDNA, the efficiency of the reverse transcriptase or polymerase enzymes. Until now reference genes identified for other members of the family Pasteurellaceae have not been validated for Avibacterium paragallinarum. The aim of this study was to validate nine reference genes of serovars A, B, and C strains of A. paragallinarum in different growth phase by qRT-PCR. Three of the most widely used statistical algorithms, geNorm, NormFinder and ΔCT method were used to evaluate the expression stability of reference genes. Data analyzed by overall rankings showed that in exponential and stationary phase of serovar A, the most stable reference genes were gyrA and atpD respectively; in exponential and stationary phase of serovar B, the most stable reference genes were atpD and recN respectively; in exponential and stationary phase of serovar C, the most stable reference genes were rpoB and recN respectively. This study provides recommendations for stable endogenous control genes for use in further studies involving measurement of gene expression levels.

IDP-ASE: haplotyping and quantifying allele-specific expression at the gene and gene isoform level by hybrid sequencing

PubMed Central

Deonovic, Benjamin; Wang, Yunhao; Weirather, Jason; Wang, Xiu-Jie; Au, Kin Fai

2017-01-01

Abstract Allele-specific expression (ASE) is a fundamental problem in studying gene regulation and diploid transcriptome profiles, with two key challenges: (i) haplotyping and (ii) estimation of ASE at the gene isoform level. Existing ASE analysis methods are limited by a dependence on haplotyping from laborious experiments or extra genome/family trio data. In addition, there is a lack of methods for gene isoform level ASE analysis. We developed a tool, IDP-ASE, for full ASE analysis. By innovative integration of Third Generation Sequencing (TGS) long reads with Second Generation Sequencing (SGS) short reads, the accuracy of haplotyping and ASE quantification at the gene and gene isoform level was greatly improved as demonstrated by the gold standard data GM12878 data and semi-simulation data. In addition to methodology development, applications of IDP-ASE to human embryonic stem cells and breast cancer cells indicate that the imbalance of ASE and non-uniformity of gene isoform ASE is widespread, including tumorigenesis relevant genes and pluripotency markers. These results show that gene isoform expression and allele-specific expression cooperate to provide high diversity and complexity of gene regulation and expression, highlighting the importance of studying ASE at the gene isoform level. Our study provides a robust bioinformatics solution to understand ASE using RNA sequencing data only. PMID:27899656

Hox gene expression in the specialized limbs of the Iberian mole (Talpa occidentalis).

PubMed

Bickelmann, Constanze; van der Vos, Wessel; de Bakker, Merijn A G; Jiménez, Rafael; Maas, Saskia; Sánchez-Villagra, Marcelo R

2017-01-01

Fossorial talpid moles use their limbs predominantly for digging, which explains their highly specialized anatomy. The humerus is particularly short and dorsoventrally rotated, with broadened distal and proximal parts where muscles attach and which facilitate powerful abductive movements. The radius and ulna are exceptionally robust and short. The ulna has an expanded olecranon process. The femur is generalized, but the fused tibia-fibula complex is short and robust. To understand the developmental bases of these specializations, we studied expression patterns of four 5' Hox genes in the fossorial Iberian mole (Talpa occidentalis). These genes are known to play major roles in patterning the developing limb skeleton in the mouse, with which comparisons were made (Mus musculus, C57BL/6Jico strain). We find that HoxA9 expression is spatially expanded in the developing stylopodial area in the mole forelimb, compared to the less specialized mouse forelimb and mole hind limb. HoxD9 expression does not extend into the thoracic body wall in the mole forelimb in contrast to the mouse, and is also reduced in the presumptive zeugopodium in mole forelimb, compared to mouse. Expression of HoxD11 is upregulated in the mole in the postaxial area of the hind limb zeugopod, compared to the mouse. On the other hand, HoxD13 is downregulated in the postaxial zeugopodial area in the forelimb of the mole, compared to the mouse. The differences in the expression patterns of these 5' Hox genes between Talpa and Mus are an indication of the developmental changes going hand in hand with anatomical digging adaptations in the mole adult. © 2016 Wiley Periodicals, Inc.

Knockdown of the schizophrenia susceptibility gene TCF4 alters gene expression and proliferation of progenitor cells from the developing human neocortex.

PubMed

Hill, Matthew J; Killick, Richard; Navarrete, Katherinne; Maruszak, Aleksandra; McLaughlin, Gemma M; Williams, Brenda P; Bray, Nicholas J

2017-05-01

Common variants in the TCF4 gene are among the most robustly supported genetic risk factors for schizophrenia. Rare TCF4 deletions and loss-of-function point mutations cause Pitt-Hopkins syndrome, a developmental disorder associated with severe intellectual disability. To explore molecular and cellular mechanisms by which TCF4 perturbation could interfere with human cortical development, we experimentally reduced the endogenous expression of TCF4 in a neural progenitor cell line derived from the developing human cerebral cortex using RNA interference. Effects on genome-wide gene expression were assessed by microarray, followed by Gene Ontology and pathway analysis of differentially expressed genes. We tested for genetic association between the set of differentially expressed genes and schizophrenia using genome-wide association study data from the Psychiatric Genomics Consortium and competitive gene set analysis (MAGMA). Effects on cell proliferation were assessed using high content imaging. Genes that were differentially expressed following TCF4 knockdown were highly enriched for involvement in the cell cycle. There was a nonsignificant trend for genetic association between the differentially expressed gene set and schizophrenia. Consistent with the gene expression data, TCF4 knockdown was associated with reduced proliferation of cortical progenitor cells in vitro. A detailed mechanistic explanation of how TCF4 knockdown alters human neural progenitor cell proliferation is not provided by this study. Our data indicate effects of TCF4 perturbation on human cortical progenitor cell proliferation, a process that could contribute to cognitive deficits in individuals with Pitt-Hopkins syndrome and risk for schizophrenia.

Optimal Scaling of Digital Transcriptomes

PubMed Central

Glusman, Gustavo; Caballero, Juan; Robinson, Max; Kutlu, Burak; Hood, Leroy

2013-01-01

Deep sequencing of transcriptomes has become an indispensable tool for biology, enabling expression levels for thousands of genes to be compared across multiple samples. Since transcript counts scale with sequencing depth, counts from different samples must be normalized to a common scale prior to comparison. We analyzed fifteen existing and novel algorithms for normalizing transcript counts, and evaluated the effectiveness of the resulting normalizations. For this purpose we defined two novel and mutually independent metrics: (1) the number of “uniform” genes (genes whose normalized expression levels have a sufficiently low coefficient of variation), and (2) low Spearman correlation between normalized expression profiles of gene pairs. We also define four novel algorithms, one of which explicitly maximizes the number of uniform genes, and compared the performance of all fifteen algorithms. The two most commonly used methods (scaling to a fixed total value, or equalizing the expression of certain ‘housekeeping’ genes) yielded particularly poor results, surpassed even by normalization based on randomly selected gene sets. Conversely, seven of the algorithms approached what appears to be optimal normalization. Three of these algorithms rely on the identification of “ubiquitous” genes: genes expressed in all the samples studied, but never at very high or very low levels. We demonstrate that these include a “core” of genes expressed in many tissues in a mutually consistent pattern, which is suitable for use as an internal normalization guide. The new methods yield robustly normalized expression values, which is a prerequisite for the identification of differentially expressed and tissue-specific genes as potential biomarkers. PMID:24223126

Cell-of-Origin in Diffuse Large B-Cell Lymphoma: Are the Assays Ready for the Clinic?

PubMed

Scott, David W

2015-01-01

Diffuse large B-cell lymphoma (DLBCL) is the most common lymphoma worldwide and consists of a heterogeneous group of cancers classified together on the basis of shared morphology, immunophenotype, and aggressive clinical behavior. It is now recognized that this malignancy comprises at least two distinct molecular subtypes identified by gene expression profiling: the activated B-cell-like (ABC) and the germinal center B-cell-like (GCB) groups-the cell-of-origin (COO) classification. These two groups have different genetic mutation landscapes, pathobiology, and outcomes following treatment. Evidence is accumulating that novel agents have selective activity in one or the other COO group, making COO a predictive biomarker. Thus, there is now a pressing need for accurate and robust methods to assign COO, to support clinical trials, and ultimately guide treatment decisions for patients. The "gold standard" methods for COO are based on gene expression profiling (GEP) of RNA from fresh frozen tissue using microarray technology, which is an impractical solution when formalin-fixed paraffin-embedded tissue (FFPET) biopsies are the standard diagnostic material. This review outlines the history of the COO classification before examining the practical implementation of COO assays applicable to FFPET biopsies. The immunohistochemistry (IHC)-based algorithms and gene expression-based assays suitable for the highly degraded RNA from FFPET are discussed. Finally, the technical and practical challenges that still need to be addressed are outlined before robust gene expression-based assays are used in the routine management of patients with DLBCL.

MacroBac: New Technologies for Robust and Efficient Large-Scale Production of Recombinant Multiprotein Complexes.

PubMed

Gradia, Scott D; Ishida, Justin P; Tsai, Miaw-Sheue; Jeans, Chris; Tainer, John A; Fuss, Jill O

2017-01-01

Recombinant expression of large, multiprotein complexes is essential and often rate limiting for determining structural, biophysical, and biochemical properties of DNA repair, replication, transcription, and other key cellular processes. Baculovirus-infected insect cell expression systems are especially well suited for producing large, human proteins recombinantly, and multigene baculovirus systems have facilitated studies of multiprotein complexes. In this chapter, we describe a multigene baculovirus system called MacroBac that uses a Biobricks-type assembly method based on restriction and ligation (Series 11) or ligation-independent cloning (Series 438). MacroBac cloning and assembly is efficient and equally well suited for either single subcloning reactions or high-throughput cloning using 96-well plates and liquid handling robotics. MacroBac vectors are polypromoter with each gene flanked by a strong polyhedrin promoter and an SV40 poly(A) termination signal that minimize gene order expression level effects seen in many polycistronic assemblies. Large assemblies are robustly achievable, and we have successfully assembled as many as 10 genes into a single MacroBac vector. Importantly, we have observed significant increases in expression levels and quality of large, multiprotein complexes using a single, multigene, polypromoter virus rather than coinfection with multiple, single-gene viruses. Given the importance of characterizing functional complexes, we believe that MacroBac provides a critical enabling technology that may change the way that structural, biophysical, and biochemical research is done. © 2017 Elsevier Inc. All rights reserved.

eMBI: Boosting Gene Expression-based Clustering for Cancer Subtypes.

PubMed

Chang, Zheng; Wang, Zhenjia; Ashby, Cody; Zhou, Chuan; Li, Guojun; Zhang, Shuzhong; Huang, Xiuzhen

2014-01-01

Identifying clinically relevant subtypes of a cancer using gene expression data is a challenging and important problem in medicine, and is a necessary premise to provide specific and efficient treatments for patients of different subtypes. Matrix factorization provides a solution by finding checker-board patterns in the matrices of gene expression data. In the context of gene expression profiles of cancer patients, these checkerboard patterns correspond to genes that are up- or down-regulated in patients with particular cancer subtypes. Recently, a new matrix factorization framework for biclustering called Maximum Block Improvement (MBI) is proposed; however, it still suffers several problems when applied to cancer gene expression data analysis. In this study, we developed many effective strategies to improve MBI and designed a new program called enhanced MBI (eMBI), which is more effective and efficient to identify cancer subtypes. Our tests on several gene expression profiling datasets of cancer patients consistently indicate that eMBI achieves significant improvements in comparison with MBI, in terms of cancer subtype prediction accuracy, robustness, and running time. In addition, the performance of eMBI is much better than another widely used matrix factorization method called nonnegative matrix factorization (NMF) and the method of hierarchical clustering, which is often the first choice of clinical analysts in practice.

eMBI: Boosting Gene Expression-based Clustering for Cancer Subtypes

PubMed Central

Chang, Zheng; Wang, Zhenjia; Ashby, Cody; Zhou, Chuan; Li, Guojun; Zhang, Shuzhong; Huang, Xiuzhen

2014-01-01

Identifying clinically relevant subtypes of a cancer using gene expression data is a challenging and important problem in medicine, and is a necessary premise to provide specific and efficient treatments for patients of different subtypes. Matrix factorization provides a solution by finding checker-board patterns in the matrices of gene expression data. In the context of gene expression profiles of cancer patients, these checkerboard patterns correspond to genes that are up- or down-regulated in patients with particular cancer subtypes. Recently, a new matrix factorization framework for biclustering called Maximum Block Improvement (MBI) is proposed; however, it still suffers several problems when applied to cancer gene expression data analysis. In this study, we developed many effective strategies to improve MBI and designed a new program called enhanced MBI (eMBI), which is more effective and efficient to identify cancer subtypes. Our tests on several gene expression profiling datasets of cancer patients consistently indicate that eMBI achieves significant improvements in comparison with MBI, in terms of cancer subtype prediction accuracy, robustness, and running time. In addition, the performance of eMBI is much better than another widely used matrix factorization method called nonnegative matrix factorization (NMF) and the method of hierarchical clustering, which is often the first choice of clinical analysts in practice. PMID:25374455

Ecological transcriptomics of lake-type and riverine sockeye salmon (Oncorhynchus nerka)

PubMed Central

2011-01-01

Background There are a growing number of genomes sequenced with tentative functions assigned to a large proportion of the individual genes. Model organisms in laboratory settings form the basis for the assignment of gene function, and the ecological context of gene function is lacking. This work addresses this shortcoming by investigating expressed genes of sockeye salmon (Oncorhynchus nerka) muscle tissue. We compared morphology and gene expression in natural juvenile sockeye populations related to river and lake habitats. Based on previously documented divergent morphology, feeding strategy, and predation in association with these distinct environments, we expect that burst swimming is favored in riverine population and continuous swimming is favored in lake-type population. In turn we predict that morphology and expressed genes promote burst swimming in riverine sockeye and continuous swimming in lake-type sockeye. Results We found the riverine sockeye population had deep, robust bodies and lake-type had shallow, streamlined bodies. Gene expression patterns were measured using a 16K microarray, discovering 141 genes with significant differential expression. Overall, the identity and function of these genes was consistent with our hypothesis. In addition, Gene Ontology (GO) enrichment analyses with a larger set of differentially expressed genes found the "biosynthesis" category enriched for the riverine population and the "metabolism" category enriched for the lake-type population. Conclusions This study provides a framework for understanding sockeye life history from a transcriptomic perspective and a starting point for more extensive, targeted studies determining the ecological context of genes. PMID:22136247

Ecological transcriptomics of lake-type and riverine sockeye salmon (Oncorhynchus nerka).

PubMed

Pavey, Scott A; Sutherland, Ben J G; Leong, Jong; Robb, Adrienne; von Schalburg, Kris; Hamon, Troy R; Koop, Ben F; Nielsen, Jennifer L

2011-12-02

There are a growing number of genomes sequenced with tentative functions assigned to a large proportion of the individual genes. Model organisms in laboratory settings form the basis for the assignment of gene function, and the ecological context of gene function is lacking. This work addresses this shortcoming by investigating expressed genes of sockeye salmon (Oncorhynchus nerka) muscle tissue. We compared morphology and gene expression in natural juvenile sockeye populations related to river and lake habitats. Based on previously documented divergent morphology, feeding strategy, and predation in association with these distinct environments, we expect that burst swimming is favored in riverine population and continuous swimming is favored in lake-type population. In turn we predict that morphology and expressed genes promote burst swimming in riverine sockeye and continuous swimming in lake-type sockeye. We found the riverine sockeye population had deep, robust bodies and lake-type had shallow, streamlined bodies. Gene expression patterns were measured using a 16 k microarray, discovering 141 genes with significant differential expression. Overall, the identity and function of these genes was consistent with our hypothesis. In addition, Gene Ontology (GO) enrichment analyses with a larger set of differentially expressed genes found the "biosynthesis" category enriched for the riverine population and the "metabolism" category enriched for the lake-type population. This study provides a framework for understanding sockeye life history from a transcriptomic perspective and a starting point for more extensive, targeted studies determining the ecological context of genes.

Preprocessing of gene expression data by optimally robust estimators

PubMed Central

2010-01-01

Background The preprocessing of gene expression data obtained from several platforms routinely includes the aggregation of multiple raw signal intensities to one expression value. Examples are the computation of a single expression measure based on the perfect match (PM) and mismatch (MM) probes for the Affymetrix technology, the summarization of bead level values to bead summary values for the Illumina technology or the aggregation of replicated measurements in the case of other technologies including real-time quantitative polymerase chain reaction (RT-qPCR) platforms. The summarization of technical replicates is also performed in other "-omics" disciplines like proteomics or metabolomics. Preprocessing methods like MAS 5.0, Illumina's default summarization method, RMA, or VSN show that the use of robust estimators is widely accepted in gene expression analysis. However, the selection of robust methods seems to be mainly driven by their high breakdown point and not by efficiency. Results We describe how optimally robust radius-minimax (rmx) estimators, i.e. estimators that minimize an asymptotic maximum risk on shrinking neighborhoods about an ideal model, can be used for the aggregation of multiple raw signal intensities to one expression value for Affymetrix and Illumina data. With regard to the Affymetrix data, we have implemented an algorithm which is a variant of MAS 5.0. Using datasets from the literature and Monte-Carlo simulations we provide some reasoning for assuming approximate log-normal distributions of the raw signal intensities by means of the Kolmogorov distance, at least for the discussed datasets, and compare the results of our preprocessing algorithms with the results of Affymetrix's MAS 5.0 and Illumina's default method. The numerical results indicate that when using rmx estimators an accuracy improvement of about 10-20% is obtained compared to Affymetrix's MAS 5.0 and about 1-5% compared to Illumina's default method. The improvement is also visible in the analysis of technical replicates where the reproducibility of the values (in terms of Pearson and Spearman correlation) is increased for all Affymetrix and almost all Illumina examples considered. Our algorithms are implemented in the R package named RobLoxBioC which is publicly available via CRAN, The Comprehensive R Archive Network (http://cran.r-project.org/web/packages/RobLoxBioC/). Conclusions Optimally robust rmx estimators have a high breakdown point and are computationally feasible. They can lead to a considerable gain in efficiency for well-established bioinformatics procedures and thus, can increase the reproducibility and power of subsequent statistical analysis. PMID:21118506

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.

Comparative Study of Regulatory Circuits in Two Sea Urchin Species Reveals Tight Control of Timing and High Conservation of Expression Dynamics

PubMed Central

Gildor, Tsvia; Ben-Tabou de-Leon, Smadar

2015-01-01

Accurate temporal control of gene expression is essential for normal development and must be robust to natural genetic and environmental variation. Studying gene expression variation within and between related species can delineate the level of expression variability that development can tolerate. Here we exploit the comprehensive model of sea urchin gene regulatory networks and generate high-density expression profiles of key regulatory genes of the Mediterranean sea urchin, Paracentrotus lividus (Pl). The high resolution of our studies reveals highly reproducible gene initiation times that have lower variation than those of maximal mRNA levels between different individuals of the same species. This observation supports a threshold behavior of gene activation that is less sensitive to input concentrations. We then compare Mediterranean sea urchin gene expression profiles to those of its Pacific Ocean relative, Strongylocentrotus purpuratus (Sp). These species shared a common ancestor about 40 million years ago and show highly similar embryonic morphologies. Our comparative analyses of five regulatory circuits operating in different embryonic territories reveal a high conservation of the temporal order of gene activation but also some cases of divergence. A linear ratio of 1.3-fold between gene initiation times in Pl and Sp is partially explained by scaling of the developmental rates with temperature. Scaling the developmental rates according to the estimated Sp-Pl ratio and normalizing the expression levels reveals a striking conservation of relative dynamics of gene expression between the species. Overall, our findings demonstrate the ability of biological developmental systems to tightly control the timing of gene activation and relative dynamics and overcome expression noise induced by genetic variation and growth conditions. PMID:26230518

Detection of growth hormone doping by gene expression profiling of peripheral blood.

PubMed

Mitchell, Christopher J; Nelson, Anne E; Cowley, Mark J; Kaplan, Warren; Stone, Glenn; Sutton, Selina K; Lau, Amie; Lee, Carol M Y; Ho, Ken K Y

2009-12-01

GH abuse is a significant problem in many sports, and there is currently no robust test that allows detection of doping beyond a short window after administration. Our objective was to evaluate gene expression profiling in peripheral blood leukocytes in-vivo as a test for GH doping in humans. Seven men and thirteen women were administered GH, 2 mg/d sc for 8 wk. Blood was collected at baseline and at 8 wk. RNA was extracted from the white cell fraction. Microarray analysis was undertaken using Agilent 44K G4112F arrays using a two-color design. Quantitative RT-PCR using TaqMan gene expression assays was performed for validation of selected differentially expressed genes. GH induced an approximately 2-fold increase in circulating IGF-I that was maintained throughout the 8 wk of the study. GH induced significant changes in gene expression with 353 in women and 41 in men detected with a false discovery rate of less than 5%. None of the differentially expressed genes were common between men and women. The maximal changes were a doubling for up-regulated or halving for down-regulated genes, similar in magnitude to the variation between individuals. Quantitative RT-PCR for seven target genes showed good concordance between microarray and quantitative PCR data in women but not in men. Gene expression analysis of peripheral blood leukocytes is unlikely to be a viable approach for the detection of GH doping.

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

Post-transcriptional regulation mediated by specific neurofilament introns in vivo.

PubMed

Wang, Chen; Szaro, Ben G

2016-04-01

Neurons regulate genes post-transcriptionally to coordinate the supply of cytoskeletal proteins, such as the medium neurofilament (NEFM), with demand for structural materials in response to extracellular cues encountered by developing axons. By using a method for evaluating functionality of cis-regulatory gene elements in vivo through plasmid injection into Xenopus embryos, we discovered that splicing of a specific nefm intron was required for robust transgene expression, regardless of promoter or cell type. Transgenes utilizing the nefm 3'-UTR but substituting other nefm introns expressed little or no protein owing to defects in handling of the messenger (m)RNA as opposed to transcription or splicing. Post-transcriptional events at multiple steps, but mainly during nucleocytoplasmic export, contributed to these varied levels of protein expression. An intron of the β-globin gene was also able to promote expression in a manner identical to that of the nefm intron, implying a more general preference for certain introns in controlling nefm expression. These results expand our knowledge of intron-mediated gene expression to encompass neurofilaments, indicating an additional layer of complexity in the control of a cytoskeletal gene needed for developing and maintaining healthy axons. © 2016. Published by The Company of Biologists Ltd.

Interrogating the topological robustness of gene regulatory circuits by randomization

PubMed Central

Levine, Herbert; Onuchic, Jose N.

2017-01-01

One of the most important roles of cells is performing their cellular tasks properly for survival. Cells usually achieve robust functionality, for example, cell-fate decision-making and signal transduction, through multiple layers of regulation involving many genes. Despite the combinatorial complexity of gene regulation, its quantitative behavior has been typically studied on the basis of experimentally verified core gene regulatory circuitry, composed of a small set of important elements. It is still unclear how such a core circuit operates in the presence of many other regulatory molecules and in a crowded and noisy cellular environment. Here we report a new computational method, named random circuit perturbation (RACIPE), for interrogating the robust dynamical behavior of a gene regulatory circuit even without accurate measurements of circuit kinetic parameters. RACIPE generates an ensemble of random kinetic models corresponding to a fixed circuit topology, and utilizes statistical tools to identify generic properties of the circuit. By applying RACIPE to simple toggle-switch-like motifs, we observed that the stable states of all models converge to experimentally observed gene state clusters even when the parameters are strongly perturbed. RACIPE was further applied to a proposed 22-gene network of the Epithelial-to-Mesenchymal Transition (EMT), from which we identified four experimentally observed gene states, including the states that are associated with two different types of hybrid Epithelial/Mesenchymal phenotypes. Our results suggest that dynamics of a gene circuit is mainly determined by its topology, not by detailed circuit parameters. Our work provides a theoretical foundation for circuit-based systems biology modeling. We anticipate RACIPE to be a powerful tool to predict and decode circuit design principles in an unbiased manner, and to quantitatively evaluate the robustness and heterogeneity of gene expression. PMID:28362798

Comparison of co-expression measures: mutual information, correlation, and model based indices.

PubMed

Song, Lin; Langfelder, Peter; Horvath, Steve

2012-12-09

Co-expression measures are often used to define networks among genes. Mutual information (MI) is often used as a generalized correlation measure. It is not clear how much MI adds beyond standard (robust) correlation measures or regression model based association measures. Further, it is important to assess what transformations of these and other co-expression measures lead to biologically meaningful modules (clusters of genes). We provide a comprehensive comparison between mutual information and several correlation measures in 8 empirical data sets and in simulations. We also study different approaches for transforming an adjacency matrix, e.g. using the topological overlap measure. Overall, we confirm close relationships between MI and correlation in all data sets which reflects the fact that most gene pairs satisfy linear or monotonic relationships. We discuss rare situations when the two measures disagree. We also compare correlation and MI based approaches when it comes to defining co-expression network modules. We show that a robust measure of correlation (the biweight midcorrelation transformed via the topological overlap transformation) leads to modules that are superior to MI based modules and maximal information coefficient (MIC) based modules in terms of gene ontology enrichment. We present a function that relates correlation to mutual information which can be used to approximate the mutual information from the corresponding correlation coefficient. We propose the use of polynomial or spline regression models as an alternative to MI for capturing non-linear relationships between quantitative variables. The biweight midcorrelation outperforms MI in terms of elucidating gene pairwise relationships. Coupled with the topological overlap matrix transformation, it often leads to more significantly enriched co-expression modules. Spline and polynomial networks form attractive alternatives to MI in case of non-linear relationships. Our results indicate that MI networks can safely be replaced by correlation networks when it comes to measuring co-expression relationships in stationary data.

DNA Microarray Gene Expression Profile of Marginal Zone versus Follicular B cells and Idiotype Positive Marginal Zone B cells Before and After Immunization with Streptococcus pneumoniae 1

PubMed Central

Liu, Jiabin; Behrens, Timothy W.; Kearney, John F.

2014-01-01

Marginal Zone (MZ) B cells play an important role in the clearance of blood-borne bacterial infections via rapid T-independent IgM responses. We have previously demonstrated that MZ B cells respond rapidly and robustly to bacterial particulates. To determine the MZ-specific genes that are expressed to allow for this response, MZ and Follicular (FO) B cells were sort-purified and analyzed via DNA microarray analysis. We identified 181 genes that were significantly different between the two B cell populations. 99 genes were more highly expressed in MZ B cells while 82 genes were more highly expressed in FO B cells. To further understand the molecular mechanisms by which MZ B cells respond so rapidly to bacterial challenge, idiotype positive and negative MZ B cells were sort-purified before (0 hour) or after (1 hour) i.v. immunization with heat killed Streptococcus pneumoniae, R36A, and analyzed via DNA microarray analysis. We identified genes specifically up regulated or down regulated at 1 hour following immunization in the idiotype positive MZ B cells. These results give insight into the gene expression pattern in resting MZ vs. FO B cells and the specific regulation of gene expression in antigen-specific MZ B cells following interaction with antigen. PMID:18453586

Robust Linear Models for Cis-eQTL Analysis.

PubMed

Rantalainen, Mattias; Lindgren, Cecilia M; Holmes, Christopher C

2015-01-01

Expression Quantitative Trait Loci (eQTL) analysis enables characterisation of functional genetic variation influencing expression levels of individual genes. In outbread populations, including humans, eQTLs are commonly analysed using the conventional linear model, adjusting for relevant covariates, assuming an allelic dosage model and a Gaussian error term. However, gene expression data generally have noise that induces heavy-tailed errors relative to the Gaussian distribution and often include atypical observations, or outliers. Such departures from modelling assumptions can lead to an increased rate of type II errors (false negatives), and to some extent also type I errors (false positives). Careful model checking can reduce the risk of type-I errors but often not type II errors, since it is generally too time-consuming to carefully check all models with a non-significant effect in large-scale and genome-wide studies. Here we propose the application of a robust linear model for eQTL analysis to reduce adverse effects of deviations from the assumption of Gaussian residuals. We present results from a simulation study as well as results from the analysis of real eQTL data sets. Our findings suggest that in many situations robust models have the potential to provide more reliable eQTL results compared to conventional linear models, particularly in respect to reducing type II errors due to non-Gaussian noise. Post-genomic data, such as that generated in genome-wide eQTL studies, are often noisy and frequently contain atypical observations. Robust statistical models have the potential to provide more reliable results and increased statistical power under non-Gaussian conditions. The results presented here suggest that robust models should be considered routinely alongside other commonly used methodologies for eQTL analysis.

Arborvitae (Thuja plicata) essential oil significantly inhibited critical inflammation- and tissue remodeling-related proteins and genes in human dermal fibroblasts.

PubMed

Han, Xuesheng; Parker, Tory L

2017-06-01

Arborvitae ( Thuja plicata ) essential oil (AEO) is becoming increasingly popular in skincare, although its biological activity in human skin cells has not been investigated. Therefore, we sought to study AEO's effect on 17 important protein biomarkers that are closely related to inflammation and tissue remodeling by using a pre-inflamed human dermal fibroblast culture model. AEO significantly inhibited the expression of vascular cell adhesion molecule 1 (VCAM-1), intracellular cell adhesion molecule 1 (ICAM-1), interferon gamma-induced protein 10 (IP-10), interferon-inducible T-cell chemoattractant (I-TAC), monokine induced by interferon gamma (MIG), and macrophage colony-stimulating factor (M-CSF). It also showed significant antiproliferative activity and robustly inhibited collagen-I, collagen-III, plasminogen activator inhibitor-1 (PAI-1), and tissue inhibitor of metalloproteinase 1 and 2 (TIMP-1 and TIMP-2). The inhibitory effect of AEO on increased production of these protein biomarkers suggests it has anti-inflammatory property. We then studied the effect of AEO on the genome-wide expression of 21,224 genes in the same cell culture. AEO significantly and diversely modulated global gene expression. Ingenuity pathway analysis (IPA) showed that AEO robustly affected numerous critical genes and signaling pathways closely involved in inflammatory and tissue remodeling processes. The findings of this study provide the first evidence of the biological activity and beneficial action of AEO in human skin cells.

Id expression in amphioxus and lamprey highlights the role of gene cooption during neural crest evolution

NASA Technical Reports Server (NTRS)

Meulemans, Daniel; McCauley, David; Bronner-Fraser, Marianne

2003-01-01

Neural crest cells are unique to vertebrates and generate many of the adult structures that differentiate them from their closest invertebrate relatives, the cephalochordates. Id genes are robust markers of neural crest cells at all stages of development. We compared Id gene expression in amphioxus and lamprey to ask if cephalochordates deploy Id genes at the neural plate border and dorsal neural tube in a manner similar to vertebrates. Furthermore, we examined whether Id expression in these cells is a basal vertebrate trait or a derived feature of gnathostomes. We found that while expression of Id genes in the mesoderm and endoderm is conserved between amphioxus and vertebrates, expression in the lateral neural plate border and dorsal neural tube is a vertebrate novelty. Furthermore, expression of lamprey Id implies that recruitment of Id genes to these cells occurred very early in the vertebrate lineage. Based on expression in amphioxus we postulate that Id cooption conferred sensory cell progenitor-like properties upon the lateral neurectoderm, and pharyngeal mesoderm-like properties upon cranial neural crest. Amphioxus Id expression is also consistent with homology between the anterior neurectoderm of amphioxus and the presumptive placodal ectoderm of vertebrates. These observations support the idea that neural crest evolution was driven in large part by cooption of multipurpose transcriptional regulators from other tissues and cell types.

Analysis of temporal gene expression profiles: clustering by simulated annealing and determining the optimal number of clusters.

PubMed

Lukashin, A V; Fuchs, R

2001-05-01

Cluster analysis of genome-wide expression data from DNA microarray hybridization studies has proved to be a useful tool for identifying biologically relevant groupings of genes and samples. In the present paper, we focus on several important issues related to clustering algorithms that have not yet been fully studied. We describe a simple and robust algorithm for the clustering of temporal gene expression profiles that is based on the simulated annealing procedure. In general, this algorithm guarantees to eventually find the globally optimal distribution of genes over clusters. We introduce an iterative scheme that serves to evaluate quantitatively the optimal number of clusters for each specific data set. The scheme is based on standard approaches used in regular statistical tests. The basic idea is to organize the search of the optimal number of clusters simultaneously with the optimization of the distribution of genes over clusters. The efficiency of the proposed algorithm has been evaluated by means of a reverse engineering experiment, that is, a situation in which the correct distribution of genes over clusters is known a priori. The employment of this statistically rigorous test has shown that our algorithm places greater than 90% genes into correct clusters. Finally, the algorithm has been tested on real gene expression data (expression changes during yeast cell cycle) for which the fundamental patterns of gene expression and the assignment of genes to clusters are well understood from numerous previous studies.

Identifying optimal reference genes for the normalization of microRNA expression in cucumber under viral stress

PubMed Central

Liang, Chaoqiong; Hao, Jianjun; Meng, Yan; Luo, Laixin; Li, Jianqiang

2018-01-01

Cucumber green mottle mosaic virus (CGMMV) is an economically important pathogen and causes significant reduction of both yield and quality of cucumber (Cucumis sativus). Currently, there were no satisfied strategies for controlling the disease. A better understanding of microRNA (miRNA) expression related to the regulation of plant-virus interactions and virus resistance would be of great assistance when developing control strategies for CGMMV. However, accurate expression analysis is highly dependent on robust and reliable reference gene used as an internal control for normalization of miRNA expression. Most commonly used reference genes involved in CGMMV-infected cucumber are not universally expressed depending on tissue types and stages of plant development. It is therefore crucial to identify suitable reference genes in investigating the role of miRNA expression. In this study, seven reference genes, including Actin, Tubulin, EF-1α, 18S rRNA, Ubiquitin, GAPDH and Cyclophilin, were evaluated for the most accurate results in analyses using reverse transcription-quantitative polymerase chain reaction (RT-qPCR). Gene expression was assayed on cucumber leaves, stems and roots that were collected at different days post inoculation with CGMMV. The expression data were analyzed using algorithms including delta-Ct, geNorm, NormFinder, and BestKeeper as well as the comparative tool RefFinder. The reference genes were subsequently validated using miR159. The results showed that EF-1α and GAPDH were the most reliable reference genes for normalizing miRNA expression in leaf, root and stem samples, while Ubiquitin and EF-1α were the most suitable combination overall. PMID:29543906

Enhancers and super-enhancers have an equivalent regulatory role in embryonic stem cells through regulation of single or multiple genes

PubMed Central

Moorthy, Sakthi D.; Davidson, Scott; Shchuka, Virlana M.; Singh, Gurdeep; Malek-Gilani, Nakisa; Langroudi, Lida; Martchenko, Alexandre; So, Vincent; Macpherson, Neil N.; Mitchell, Jennifer A.

2017-01-01

Transcriptional enhancers are critical for maintaining cell-type–specific gene expression and driving cell fate changes during development. Highly transcribed genes are often associated with a cluster of individual enhancers such as those found in locus control regions. Recently, these have been termed stretch enhancers or super-enhancers, which have been predicted to regulate critical cell identity genes. We employed a CRISPR/Cas9-mediated deletion approach to study the function of several enhancer clusters (ECs) and isolated enhancers in mouse embryonic stem (ES) cells. Our results reveal that the effect of deleting ECs, also classified as ES cell super-enhancers, is highly variable, resulting in target gene expression reductions ranging from 12% to as much as 92%. Partial deletions of these ECs which removed only one enhancer or a subcluster of enhancers revealed partially redundant control of the regulated gene by multiple enhancers within the larger cluster. Many highly transcribed genes in ES cells are not associated with a super-enhancer; furthermore, super-enhancer predictions ignore 81% of the potentially active regulatory elements predicted by cobinding of five or more pluripotency-associated transcription factors. Deletion of these additional enhancer regions revealed their robust regulatory role in gene transcription. In addition, select super-enhancers and enhancers were identified that regulated clusters of paralogous genes. We conclude that, whereas robust transcriptional output can be achieved by an isolated enhancer, clusters of enhancers acting on a common target gene act in a partially redundant manner to fine tune transcriptional output of their target genes. PMID:27895109

Cancer-cell intrinsic gene expression signatures overcome intratumoural heterogeneity bias in colorectal cancer patient classification

PubMed Central

Dunne, Philip D.; Alderdice, Matthew; O'Reilly, Paul G.; Roddy, Aideen C.; McCorry, Amy M. B.; Richman, Susan; Maughan, Tim; McDade, Simon S.; Johnston, Patrick G.; Longley, Daniel B.; Kay, Elaine; McArt, Darragh G.; Lawler, Mark

2017-01-01

Stromal-derived intratumoural heterogeneity (ITH) has been shown to undermine molecular stratification of patients into appropriate prognostic/predictive subgroups. Here, using several clinically relevant colorectal cancer (CRC) gene expression signatures, we assessed the susceptibility of these signatures to the confounding effects of ITH using gene expression microarray data obtained from multiple tumour regions of a cohort of 24 patients, including central tumour, the tumour invasive front and lymph node metastasis. Sample clustering alongside correlative assessment revealed variation in the ability of each signature to cluster samples according to patient-of-origin rather than region-of-origin within the multi-region dataset. Signatures focused on cancer-cell intrinsic gene expression were found to produce more clinically useful, patient-centred classifiers, as exemplified by the CRC intrinsic signature (CRIS), which robustly clustered samples by patient-of-origin rather than region-of-origin. These findings highlight the potential of cancer-cell intrinsic signatures to reliably stratify CRC patients by minimising the confounding effects of stromal-derived ITH. PMID:28561046

Transcriptional Regulation Patterns Revealed by High Resolution Chromatin Immunoprecipitation during Cardiac Hypertrophy*

PubMed Central

Sayed, Danish; He, Minzhen; Yang, Zhi; Lin, Lin; Abdellatif, Maha

2013-01-01

Cardiac hypertrophy is characterized by a generalized increase in gene expression that is commensurate with the increase in myocyte size and mass, on which is superimposed more robust changes in the expression of specialized genes. Both transcriptional and posttranscriptional mechanisms play fundamental roles in these processes; however, genome-wide characterization of the transcriptional changes has not been investigated. Our goal was to identify the extent and modes, RNA polymerase II (pol II) pausing versus recruitment, of transcriptional regulation underlying cardiac hypertrophy. We used anti-pol II and anti-histone H3K9-acetyl (H3K9ac) chromatin immunoprecipitation-deep sequencing to determine the extent of pol II recruitment and pausing, and the underlying epigenetic modifications, respectively, during cardiac growth. The data uniquely reveal two mutually exclusive modes of transcriptional regulation. One involves an incremental increase (30–50%) in the elongational activity of preassembled, promoter-paused, pol II, and encompasses ∼25% of expressed genes that are essential/housekeeping genes (e.g. RNA synthesis and splicing). Another involves a more robust activation via de novo pol II recruitment, encompassing ∼5% of specialized genes (e.g. contractile and extracellular matrix). Moreover, the latter subset has relatively shorter 3′-UTRs with fewer predicted targeting miRNA, whereas most miRNA targets fall in the former category, underscoring the significance of posttranscriptional regulation by miRNA. The results, for the first time, demonstrate that promoter-paused pol II plays a role in incrementally increasing housekeeping genes, proportionate to the increase in heart size. Additionally, the data distinguish between the roles of posttranscriptional versus transcriptional regulation of specific genes. PMID:23229551

Suboptimal evolutionary novel environments promote singular altered gravity responses of transcriptome during Drosophila metamorphosis

PubMed Central

2013-01-01

Background Previous experiments have shown that the reduced gravity aboard the International Space Station (ISS) causes important alterations in Drosophila gene expression. These changes were shown to be intimately linked to environmental space-flight related constraints. Results Here, we use an array of different techniques for ground-based simulation of microgravity effects to assess the effect of suboptimal environmental conditions on the gene expression of Drosophila in reduced gravity. A global and integrative analysis, using “gene expression dynamics inspector” (GEDI) self-organizing maps, reveals different degrees in the responses of the transcriptome when using different environmental conditions or microgravity/hypergravity simulation devices. Although the genes that are affected are different in each simulation technique, we find that the same gene ontology groups, including at least one large multigene family related with behavior, stress response or organogenesis, are over represented in each case. Conclusions These results suggest that the transcriptome as a whole can be finely tuned to gravity force. In optimum environmental conditions, the alteration of gravity has only mild effects on gene expression but when environmental conditions are far from optimal, the gene expression must be tuned greatly and effects become more robust, probably linked to the lack of experience of organisms exposed to evolutionary novel environments such as a gravitational free one. PMID:23806134

An Integrated Genomic Approach for Rapid Delineation of Candidate Genes Regulating Agro-Morphological Traits in Chickpea

PubMed Central

Saxena, Maneesha S.; Bajaj, Deepak; Das, Shouvik; Kujur, Alice; Kumar, Vinod; Singh, Mohar; Bansal, Kailash C.; Tyagi, Akhilesh K.; Parida, Swarup K.

2014-01-01

The identification and fine mapping of robust quantitative trait loci (QTLs)/genes governing important agro-morphological traits in chickpea still lacks systematic efforts at a genome-wide scale involving wild Cicer accessions. In this context, an 834 simple sequence repeat and single-nucleotide polymorphism marker-based high-density genetic linkage map between cultivated and wild parental accessions (Cicer arietinum desi cv. ICC 4958 and Cicer reticulatum wild cv. ICC 17160) was constructed. This inter-specific genetic map comprising eight linkage groups spanned a map length of 949.4 cM with an average inter-marker distance of 1.14 cM. Eleven novel major genomic regions harbouring 15 robust QTLs (15.6–39.8% R2 at 4.2–15.7 logarithm of odds) associated with four agro-morphological traits (100-seed weight, pod and branch number/plant and plant hairiness) were identified and mapped on chickpea chromosomes. Most of these QTLs showed positive additive gene effects with effective allelic contribution from ICC 4958, particularly for increasing seed weight (SW) and pod and branch number. One robust SW-influencing major QTL region (qSW4.2) has been narrowed down by combining QTL mapping with high-resolution QTL region-specific association analysis, differential expression profiling and gene haplotype-based association/LD mapping. This enabled to delineate a strong SW-regulating ABI3VP1 transcription factor (TF) gene at trait-specific QTL interval and consequently identified favourable natural allelic variants and superior high seed weight-specific haplotypes in the upstream regulatory region of this gene showing increased transcript expression during seed development. The genes (TFs) harbouring diverse trait-regulating QTLs, once validated and fine-mapped by our developed rapid integrated genomic approach and through gene/QTL map-based cloning, can be utilized as potential candidates for marker-assisted genetic enhancement of chickpea. PMID:25335477

Lack of robustness of life extension associated with several single-gene P element mutations in Drosophila melanogaster.

PubMed

Mockett, Robin J; Nobles, Amber C

2013-10-01

The hypothesis tested in this study was that single-gene mutations found previously to extend the life span of Drosophila melanogaster could do so consistently in both long-lived y w and standard w (1118) genetic backgrounds. GAL4 drivers were used to express upstream activation sequence (UAS)-responder transgenes globally or in the nervous system. Transgenes associated with oxidative damage prevention (UAS-hSOD1 and UAS-GCLc) or removal (EP-UAS-Atg8a and UAS-dTOR (FRB) ) failed to increase mean life spans in any expression pattern in either genetic background. Flies containing a UAS-EGFP-bMSRA (C) transgene associated with protein repair were found not to exhibit life extension or detectable enhanced green fluorescent protein (EGFP) activity. The presence of UAS-responder transgenes was confirmed by PCR amplification and sequencing at the 5' and 3' end of each insertion. These results cast doubt on the robustness of life extension in flies carrying single-gene mutations and suggest that the effects of all such mutations should be tested independently in multiple genetic backgrounds and laboratory environments.

Robust Selection Algorithm (RSA) for Multi-Omic Biomarker Discovery; Integration with Functional Network Analysis to Identify miRNA Regulated Pathways in Multiple Cancers.

PubMed

Sehgal, Vasudha; Seviour, Elena G; Moss, Tyler J; Mills, Gordon B; Azencott, Robert; Ram, Prahlad T

2015-01-01

MicroRNAs (miRNAs) play a crucial role in the maintenance of cellular homeostasis by regulating the expression of their target genes. As such, the dysregulation of miRNA expression has been frequently linked to cancer. With rapidly accumulating molecular data linked to patient outcome, the need for identification of robust multi-omic molecular markers is critical in order to provide clinical impact. While previous bioinformatic tools have been developed to identify potential biomarkers in cancer, these methods do not allow for rapid classification of oncogenes versus tumor suppressors taking into account robust differential expression, cutoffs, p-values and non-normality of the data. Here, we propose a methodology, Robust Selection Algorithm (RSA) that addresses these important problems in big data omics analysis. The robustness of the survival analysis is ensured by identification of optimal cutoff values of omics expression, strengthened by p-value computed through intensive random resampling taking into account any non-normality in the data and integration into multi-omic functional networks. Here we have analyzed pan-cancer miRNA patient data to identify functional pathways involved in cancer progression that are associated with selected miRNA identified by RSA. Our approach demonstrates the way in which existing survival analysis techniques can be integrated with a functional network analysis framework to efficiently identify promising biomarkers and novel therapeutic candidates across diseases.

Gene coexpression measures in large heterogeneous samples using count statistics.

PubMed

Wang, Y X Rachel; Waterman, Michael S; Huang, Haiyan

2014-11-18

With the advent of high-throughput technologies making large-scale gene expression data readily available, developing appropriate computational tools to process these data and distill insights into systems biology has been an important part of the "big data" challenge. Gene coexpression is one of the earliest techniques developed that is still widely in use for functional annotation, pathway analysis, and, most importantly, the reconstruction of gene regulatory networks, based on gene expression data. However, most coexpression measures do not specifically account for local features in expression profiles. For example, it is very likely that the patterns of gene association may change or only exist in a subset of the samples, especially when the samples are pooled from a range of experiments. We propose two new gene coexpression statistics based on counting local patterns of gene expression ranks to take into account the potentially diverse nature of gene interactions. In particular, one of our statistics is designed for time-course data with local dependence structures, such as time series coupled over a subregion of the time domain. We provide asymptotic analysis of their distributions and power, and evaluate their performance against a wide range of existing coexpression measures on simulated and real data. Our new statistics are fast to compute, robust against outliers, and show comparable and often better general performance.

An Efficient Method for Generation of Knockout Human Embryonic Stem Cells Using CRISPR/Cas9 System.

PubMed

Bohaciakova, Dasa; Renzova, Tereza; Fedorova, Veronika; Barak, Martin; Kunova Bosakova, Michaela; Hampl, Ales; Cajanek, Lukas

2017-11-01

Human embryonic stem cells (hESCs) represent a promising tool to study functions of genes during development, to model diseases, and to even develop therapies when combined with gene editing techniques such as CRISPR/CRISPR-associated protein-9 nuclease (Cas9) system. However, the process of disruption of gene expression by generation of null alleles is often inefficient and tedious. To circumvent these limitations, we developed a simple and efficient protocol to permanently downregulate expression of a gene of interest in hESCs using CRISPR/Cas9. We selected p53 for our proof of concept experiments. The methodology is based on series of hESC transfection, which leads to efficient downregulation of p53 expression even in polyclonal population (p53 Low cells), here proven by a loss of regulation of the expression of p53 target gene, microRNA miR-34a. We demonstrate that our approach achieves over 80% efficiency in generating hESC clonal sublines that do not express p53 protein. Importantly, we document by a set of functional experiments that such genetically modified hESCs do retain typical stem cells characteristics. In summary, we provide a simple and robust protocol to efficiently target expression of gene of interest in hESCs that can be useful for laboratories aiming to employ gene editing in their hESC applications/protocols.

Gene expression changes during short day induced terminal bud formation in Norway spruce.

PubMed

Asante, Daniel K A; Yakovlev, Igor A; Fossdal, Carl Gunnar; Holefors, Anna; Opseth, Lars; Olsen, Jorunn E; Junttila, Olavi; Johnsen, Øystein

2011-02-01

The molecular basis for terminal bud formation in autumn is not well understood in conifers. By combining suppression subtractive hybridization and monitoring of gene expression by qRT-PCR analysis, we aimed to identify genes involved in photoperiodic control of growth cessation and bud set in Norway spruce. Close to 1400 ESTs were generated and their functional distribution differed between short day (SD-12 h photoperiod) and long day (LD-24 h photoperiod) libraries. Many genes with putative roles in protection against stress appeared differentially regulated under SD and LD, and also differed in transcript levels between 6 and 20 SDs. Of these, PaTFL1(TERMINAL FLOWER LIKE 1) showed strongly increased transcript levels at 6 SDs. PaCCCH(CCCH-TYPE ZINC FINGER) and PaCBF2&3(C-REPEAT BINDING FACTOR 2&3) showed a later response at 20 SDs, with increased and decreased transcript levels, respectively. For rhythmically expressed genes such as CBFs, such differences might represent a phase shift in peak expression, but might also suggest a putative role in response to SD. Multivariate analyses revealed strong differences in gene expression between LD, 6 SD and 20 SD. The robustness of the gene expression patterns was verified in 6 families differing in bud-set timing under natural light with gradually decreasing photoperiod. © 2010 Blackwell Publishing Ltd.

The opportunities and challenges of large-scale molecular approaches to songbird neurobiology

PubMed Central

Mello, C.V.; Clayton, D.F.

2014-01-01

High-through put methods for analyzing genome structure and function are having a large impact in song-bird neurobiology. Methods include genome sequencing and annotation, comparative genomics, DNA microarrays and transcriptomics, and the development of a brain atlas of gene expression. Key emerging findings include the identification of complex transcriptional programs active during singing, the robust brain expression of non-coding RNAs, evidence of profound variations in gene expression across brain regions, and the identification of molecular specializations within song production and learning circuits. Current challenges include the statistical analysis of large datasets, effective genome curations, the efficient localization of gene expression changes to specific neuronal circuits and cells, and the dissection of behavioral and environmental factors that influence brain gene expression. The field requires efficient methods for comparisons with organisms like chicken, which offer important anatomical, functional and behavioral contrasts. As sequencing costs plummet, opportunities emerge for comparative approaches that may help reveal evolutionary transitions contributing to vocal learning, social behavior and other properties that make songbirds such compelling research subjects. PMID:25280907

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

Validation of endogenous reference genes for qRT-PCR analysis of human visceral adipose samples

PubMed Central

2010-01-01

Background Given the epidemic proportions of obesity worldwide and the concurrent prevalence of metabolic syndrome, there is an urgent need for better understanding the underlying mechanisms of metabolic syndrome, in particular, the gene expression differences which may participate in obesity, insulin resistance and the associated series of chronic liver conditions. Real-time PCR (qRT-PCR) is the standard method for studying changes in relative gene expression in different tissues and experimental conditions. However, variations in amount of starting material, enzymatic efficiency and presence of inhibitors can lead to quantification errors. Hence the need for accurate data normalization is vital. Among several known strategies for data normalization, the use of reference genes as an internal control is the most common approach. Recent studies have shown that both obesity and presence of insulin resistance influence an expression of commonly used reference genes in omental fat. In this study we validated candidate reference genes suitable for qRT-PCR profiling experiments using visceral adipose samples from obese and lean individuals. Results Cross-validation of expression stability of eight selected reference genes using three popular algorithms, GeNorm, NormFinder and BestKeeper found ACTB and RPII as most stable reference genes. Conclusions We recommend ACTB and RPII as stable reference genes most suitable for gene expression studies of human visceral adipose tissue. The use of these genes as a reference pair may further enhance the robustness of qRT-PCR in this model system. PMID:20492695

Validation of endogenous reference genes for qRT-PCR analysis of human visceral adipose samples.

PubMed

Mehta, Rohini; Birerdinc, Aybike; Hossain, Noreen; Afendy, Arian; Chandhoke, Vikas; Younossi, Zobair; Baranova, Ancha

2010-05-21

Given the epidemic proportions of obesity worldwide and the concurrent prevalence of metabolic syndrome, there is an urgent need for better understanding the underlying mechanisms of metabolic syndrome, in particular, the gene expression differences which may participate in obesity, insulin resistance and the associated series of chronic liver conditions. Real-time PCR (qRT-PCR) is the standard method for studying changes in relative gene expression in different tissues and experimental conditions. However, variations in amount of starting material, enzymatic efficiency and presence of inhibitors can lead to quantification errors. Hence the need for accurate data normalization is vital. Among several known strategies for data normalization, the use of reference genes as an internal control is the most common approach. Recent studies have shown that both obesity and presence of insulin resistance influence an expression of commonly used reference genes in omental fat. In this study we validated candidate reference genes suitable for qRT-PCR profiling experiments using visceral adipose samples from obese and lean individuals. Cross-validation of expression stability of eight selected reference genes using three popular algorithms, GeNorm, NormFinder and BestKeeper found ACTB and RPII as most stable reference genes. We recommend ACTB and RPII as stable reference genes most suitable for gene expression studies of human visceral adipose tissue. The use of these genes as a reference pair may further enhance the robustness of qRT-PCR in this model system.

The structure of a gene co-expression network reveals biological functions underlying eQTLs.

PubMed

Villa-Vialaneix, Nathalie; Liaubet, Laurence; Laurent, Thibault; Cherel, Pierre; Gamot, Adrien; SanCristobal, Magali

2013-01-01

What are the commonalities between genes, whose expression level is partially controlled by eQTL, especially with regard to biological functions? Moreover, how are these genes related to a phenotype of interest? These issues are particularly difficult to address when the genome annotation is incomplete, as is the case for mammalian species. Moreover, the direct link between gene expression and a phenotype of interest may be weak, and thus difficult to handle. In this framework, the use of a co-expression network has proven useful: it is a robust approach for modeling a complex system of genetic regulations, and to infer knowledge for yet unknown genes. In this article, a case study was conducted with a mammalian species. It showed that the use of a co-expression network based on partial correlation, combined with a relevant clustering of nodes, leads to an enrichment of biological functions of around 83%. Moreover, the use of a spatial statistics approach allowed us to superimpose additional information related to a phenotype; this lead to highlighting specific genes or gene clusters that are related to the network structure and the phenotype. Three main results are worth noting: first, key genes were highlighted as a potential focus for forthcoming biological experiments; second, a set of biological functions, which support a list of genes under partial eQTL control, was set up by an overview of the global structure of the gene expression network; third, pH was found correlated with gene clusters, and then with related biological functions, as a result of a spatial analysis of the network topology.

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.

Synthetic incoherent feedforward circuits show adaptation to the amount of their genetic template

PubMed Central

Bleris, Leonidas; Xie, Zhen; Glass, David; Adadey, Asa; Sontag, Eduardo; Benenson, Yaakov

2011-01-01

Natural and synthetic biological networks must function reliably in the face of fluctuating stoichiometry of their molecular components. These fluctuations are caused in part by changes in relative expression efficiency and the DNA template amount of the network-coding genes. Gene product levels could potentially be decoupled from these changes via built-in adaptation mechanisms, thereby boosting network reliability. Here, we show that a mechanism based on an incoherent feedforward motif enables adaptive gene expression in mammalian cells. We modeled, synthesized, and tested transcriptional and post-transcriptional incoherent loops and found that in all cases the gene product adapts to changes in DNA template abundance. We also observed that the post-transcriptional form results in superior adaptation behavior, higher absolute expression levels, and lower intrinsic fluctuations. Our results support a previously hypothesized endogenous role in gene dosage compensation for such motifs and suggest that their incorporation in synthetic networks will improve their robustness and reliability. PMID:21811230

Multiclass classification for skin cancer profiling based on the integration of heterogeneous gene expression series.

PubMed

Gálvez, Juan Manuel; Castillo, Daniel; Herrera, Luis Javier; San Román, Belén; Valenzuela, Olga; Ortuño, Francisco Manuel; Rojas, Ignacio

2018-01-01

Most of the research studies developed applying microarray technology to the characterization of different pathological states of any disease may fail in reaching statistically significant results. This is largely due to the small repertoire of analysed samples, and to the limitation in the number of states or pathologies usually addressed. Moreover, the influence of potential deviations on the gene expression quantification is usually disregarded. In spite of the continuous changes in omic sciences, reflected for instance in the emergence of new Next-Generation Sequencing-related technologies, the existing availability of a vast amount of gene expression microarray datasets should be properly exploited. Therefore, this work proposes a novel methodological approach involving the integration of several heterogeneous skin cancer series, and a later multiclass classifier design. This approach is thus a way to provide the clinicians with an intelligent diagnosis support tool based on the use of a robust set of selected biomarkers, which simultaneously distinguishes among different cancer-related skin states. To achieve this, a multi-platform combination of microarray datasets from Affymetrix and Illumina manufacturers was carried out. This integration is expected to strengthen the statistical robustness of the study as well as the finding of highly-reliable skin cancer biomarkers. Specifically, the designed operation pipeline has allowed the identification of a small subset of 17 differentially expressed genes (DEGs) from which to distinguish among 7 involved skin states. These genes were obtained from the assessment of a number of potential batch effects on the gene expression data. The biological interpretation of these genes was inspected in the specific literature to understand their underlying information in relation to skin cancer. Finally, in order to assess their possible effectiveness in cancer diagnosis, a cross-validation Support Vector Machines (SVM)-based classification including feature ranking was performed. The accuracy attained exceeded the 92% in overall recognition of the 7 different cancer-related skin states. The proposed integration scheme is expected to allow the co-integration with other state-of-the-art technologies such as RNA-seq.

Microarray Analysis Reveals Characteristic Changes of Host Cell Gene Expression in Response to Attenuated Modified Vaccinia Virus Ankara Infection of Human HeLa Cells

PubMed Central

Guerra, Susana; López-Fernández, Luis A.; Conde, Raquel; Pascual-Montano, Alberto; Harshman, Keith; Esteban, Mariano

2004-01-01

The potential use of the modified vaccinia virus Ankara (MVA) strain as a live recombinant vector to deliver antigens and elicit protective immune responses against infectious diseases demands a comprehensive understanding of the effect of MVA infection on human host gene expression. We used microarrays containing more than 15,000 human cDNAs to identify gene expression changes in human HeLa cell cultures at 2, 6, and 16 h postinfection. Clustering of the 410 differentially regulated genes identified 11 discrete gene clusters with altered expression patterns after MVA infection. Clusters 1 and 2 (accounting for 16.59% [68 of 410] of the genes) contained 68 transcripts showing a robust induction pattern that was maintained during the course of infection. Changes in cellular gene transcription detected by microarrays after MVA infection were confirmed for selected genes by Northern blot analysis and by real-time reverse transcription-PCR. Upregulated transcripts in clusters 1 and 2 included 20 genes implicated in immune responses, including interleukin 1A (IL-1A), IL-6, IL-7, IL-8, and IL-15 genes. MVA infection also stimulated the expression of NF-κB and components of the NF-κB signal transduction pathway, including p50 and TRAF-interacting protein. A marked increase in the expression of histone family members was also induced during MVA infection. Expression of the Wiskott-Aldrich syndrome family members WAS, WASF1, and the small GTP-binding protein RAC-1, which are involved in actin cytoskeleton reorganization, was enhanced after MVA infection. This study demonstrates that MVA infection triggered the induction of groups of genes, some of which may be involved in host resistance and immune modulation during virus infection. PMID:15140980

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

Paquette, Stéphane G.; Institute of Medical Science, Faculty of Medicine, University of Toronto, Toronto, Ontario; Banner, David

Pandemic H1N1 influenza A (H1N1pdm) elicits stronger pulmonary inflammation than previously circulating seasonal H1N1 influenza A (sH1N1), yet mechanisms of inflammatory activation in respiratory epithelial cells during H1N1pdm infection are unclear. We investigated host responses to H1N1pdm/sH1N1 infection and virus entry mechanisms in primary human bronchial epithelial cells in vitro. H1N1pdm infection rapidly initiated a robust inflammatory gene signature (3 h post-infection) not elicited by sH1N1 infection. Protein secretion inhibition had no effect on gene induction. Infection with membrane fusion deficient H1N1pdm failed to induce robust inflammatory gene expression which was rescued with restoration of fusion ability, suggesting H1N1pdm directlymore » triggered the inflammatory signature downstream of membrane fusion. Investigation of intra-virion components revealed H1N1pdm viral RNA (vRNA) triggered a stronger inflammatory phenotype than sH1N1 vRNA. Thus, our study is first to report H1N1pdm induces greater inflammatory gene expression than sH1N1 in vitro due to direct virus–epithelial cell interaction. - Highlights: • We investigated H1N1pdm/sH1N1 infection in primary epithelial cells. • H1N1pdm directly initiated a robust inflammatory gene signature, sH1N1 did not. • H1N1pdm viral RNA triggered a stronger response than sH1N1. • H1N1pdm induces greater response due to direct virus–cell interaction. • These results have potential to impact vaccine and therapeutic development.« less

Genome-wide characterization and expression profiling of NAC transcription factor genes under abiotic stresses in radish (Raphanus sativus L.)

PubMed Central

Muleke, Everlyne M’mbone; Jabir, Bashir Mohammed; Xie, Yang; Zhu, Xianwen; Cheng, Wanwan

2017-01-01

NAC (NAM, no apical meristem; ATAF, Arabidopsis transcription activation factor and CUC, cup-shaped cotyledon) proteins are among the largest transcription factor (TF) families playing fundamental biological processes, including cell expansion and differentiation, and hormone signaling in response to biotic and abiotic stresses. In this study, 172 RsNACs comprising 17 membrane-bound members were identified from the whole radish genome. In total, 98 RsNAC genes were non-uniformly distributed across the nine radish chromosomes. In silico analysis revealed that expression patterns of several NAC genes were tissue-specific such as a preferential expression in roots and leaves. In addition, 21 representative NAC genes were selected to investigate their responses to heavy metals (HMs), salt, heat, drought and abscisic acid (ABA) stresses using real-time polymerase chain reaction (RT-qPCR). As a result, differential expressions among these genes were identified where RsNAC023 and RsNAC080 genes responded positively to all stresses except ABA, while RsNAC145 responded more actively to salt, heat and drought stresses compared with other genes. The results provides more valuable information and robust candidate genes for future functional analysis for improving abiotic stress tolerances in radish. PMID:29259849

Directed natural product biosynthesis gene cluster capture and expression in the model bacterium Bacillus subtilis

NASA Astrophysics Data System (ADS)

Li, Yongxin; Li, Zhongrui; Yamanaka, Kazuya; Xu, Ying; Zhang, Weipeng; Vlamakis, Hera; Kolter, Roberto; Moore, Bradley S.; Qian, Pei-Yuan

2015-03-01

Bacilli are ubiquitous low G+C environmental Gram-positive bacteria that produce a wide assortment of specialized small molecules. Although their natural product biosynthetic potential is high, robust molecular tools to support the heterologous expression of large biosynthetic gene clusters in Bacillus hosts are rare. Herein we adapt transformation-associated recombination (TAR) in yeast to design a single genomic capture and expression vector for antibiotic production in Bacillus subtilis. After validating this direct cloning ``plug-and-play'' approach with surfactin, we genetically interrogated amicoumacin biosynthetic gene cluster from the marine isolate Bacillus subtilis 1779. Its heterologous expression allowed us to explore an unusual maturation process involving the N-acyl-asparagine pro-drug intermediates preamicoumacins, which are hydrolyzed by the asparagine-specific peptidase into the active component amicoumacin A. This work represents the first direct cloning based heterologous expression of natural products in the model organism B. subtilis and paves the way to the development of future genome mining efforts in this genus.

Directed natural product biosynthesis gene cluster capture and expression in the model bacterium Bacillus subtilis.

PubMed

Li, Yongxin; Li, Zhongrui; Yamanaka, Kazuya; Xu, Ying; Zhang, Weipeng; Vlamakis, Hera; Kolter, Roberto; Moore, Bradley S; Qian, Pei-Yuan

2015-03-24

Bacilli are ubiquitous low G+C environmental Gram-positive bacteria that produce a wide assortment of specialized small molecules. Although their natural product biosynthetic potential is high, robust molecular tools to support the heterologous expression of large biosynthetic gene clusters in Bacillus hosts are rare. Herein we adapt transformation-associated recombination (TAR) in yeast to design a single genomic capture and expression vector for antibiotic production in Bacillus subtilis. After validating this direct cloning "plug-and-play" approach with surfactin, we genetically interrogated amicoumacin biosynthetic gene cluster from the marine isolate Bacillus subtilis 1779. Its heterologous expression allowed us to explore an unusual maturation process involving the N-acyl-asparagine pro-drug intermediates preamicoumacins, which are hydrolyzed by the asparagine-specific peptidase into the active component amicoumacin A. This work represents the first direct cloning based heterologous expression of natural products in the model organism B. subtilis and paves the way to the development of future genome mining efforts in this genus.

The imprinted gene Magel2 regulates normal circadian output.

PubMed

Kozlov, Serguei V; Bogenpohl, James W; Howell, Maureen P; Wevrick, Rachel; Panda, Satchin; Hogenesch, John B; Muglia, Louis J; Van Gelder, Russell N; Herzog, Erik D; Stewart, Colin L

2007-10-01

Mammalian circadian rhythms of activity are generated within the suprachiasmatic nucleus (SCN). Transcripts from the imprinted, paternally expressed Magel2 gene, which maps to the chromosomal region associated with Prader-Willi Syndrome (PWS), are highly enriched in the SCN. The Magel2 message is circadianly expressed and peaks during the subjective day. Mice deficient in Magel2 expression entrain to light cycles and express normal running-wheel rhythms, but with markedly reduced amplitude of activity and increased daytime activity. These changes are associated with reductions in food intake and male fertility. Orexin levels and orexin-positive neurons in the lateral hypothalamus are substantially reduced, suggesting that some of the consequences of Magel2 loss are mediated through changes in orexin signaling. The robust rhythmicity of Magel2 expression in the SCN and the altered behavioral rhythmicity of null mice reveal Magel2 to be a clock-controlled circadian output gene whose disruption results in some of the phenotypes characteristic of PWS.

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

Seasonal Changes in Bacterial and Archaeal Gene Expression Patterns across Salinity Gradients in the Columbia River Coastal Margin

PubMed Central

Smith, Maria W.; Herfort, Lydie; Tyrol, Kaitlin; Suciu, Dominic; Campbell, Victoria; Crump, Byron C.; Peterson, Tawnya D.; Zuber, Peter; Baptista, Antonio M.; Simon, Holly M.

2010-01-01

Through their metabolic activities, microbial populations mediate the impact of high gradient regions on ecological function and productivity of the highly dynamic Columbia River coastal margin (CRCM). A 2226-probe oligonucleotide DNA microarray was developed to investigate expression patterns for microbial genes involved in nitrogen and carbon metabolism in the CRCM. Initial experiments with the environmental microarrays were directed toward validation of the platform and yielded high reproducibility in multiple tests. Bioinformatic and experimental validation also indicated that >85% of the microarray probes were specific for their corresponding target genes and for a few homologs within the same microbial family. The validated probe set was used to query gene expression responses by microbial assemblages to environmental variability. Sixty-four samples from the river, estuary, plume, and adjacent ocean were collected in different seasons and analyzed to correlate the measured variability in chemical, physical and biological water parameters to differences in global gene expression profiles. The method produced robust seasonal profiles corresponding to pre-freshet spring (April) and late summer (August). Overall relative gene expression was high in both seasons and was consistent with high microbial abundance measured by total RNA, heterotrophic bacterial production, and chlorophyll a. Both seasonal patterns involved large numbers of genes that were highly expressed relative to background, yet each produced very different gene expression profiles. April patterns revealed high differential gene expression in the coastal margin samples (estuary, plume and adjacent ocean) relative to freshwater, while little differential gene expression was observed along the river-to-ocean transition in August. Microbial gene expression profiles appeared to relate, in part, to seasonal differences in nutrient availability and potential resource competition. Furthermore, our results suggest that highly-active particle-attached microbiota in the Columbia River water column may perform dissimilatory nitrate reduction (both dentrification and DNRA) within anoxic particle microniches. PMID:20967204

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

RiceMetaSys for salt and drought stress responsive genes in rice: a web interface for crop improvement.

PubMed

Sandhu, Maninder; Sureshkumar, V; Prakash, Chandra; Dixit, Rekha; Solanke, Amolkumar U; Sharma, Tilak Raj; Mohapatra, Trilochan; S V, Amitha Mithra

2017-09-30

Genome-wide microarray has enabled development of robust databases for functional genomics studies in rice. However, such databases do not directly cater to the needs of breeders. Here, we have attempted to develop a web interface which combines the information from functional genomic studies across different genetic backgrounds with DNA markers so that they can be readily deployed in crop improvement. In the current version of the database, we have included drought and salinity stress studies since these two are the major abiotic stresses in rice. RiceMetaSys, a user-friendly and freely available web interface provides comprehensive information on salt responsive genes (SRGs) and drought responsive genes (DRGs) across genotypes, crop development stages and tissues, identified from multiple microarray datasets. 'Physical position search' is an attractive tool for those using QTL based approach for dissecting tolerance to salt and drought stress since it can provide the list of SRGs and DRGs in any physical interval. To identify robust candidate genes for use in crop improvement, the 'common genes across varieties' search tool is useful. Graphical visualization of expression profiles across genes and rice genotypes has been enabled to facilitate the user and to make the comparisons more impactful. Simple Sequence Repeat (SSR) search in the SRGs and DRGs is a valuable tool for fine mapping and marker assisted selection since it provides primers for survey of polymorphism. An external link to intron specific markers is also provided for this purpose. Bulk retrieval of data without any limit has been enabled in case of locus and SSR search. The aim of this database is to facilitate users with a simple and straight-forward search options for identification of robust candidate genes from among thousands of SRGs and DRGs so as to facilitate linking variation in expression profiles to variation in phenotype. Database URL: http://14.139.229.201.

Large Sex Differences in Chicken Behavior and Brain Gene Expression Coincide with Few Differences in Promoter DNA-Methylation

PubMed Central

Nätt, Daniel; Agnvall, Beatrix; Jensen, Per

2014-01-01

While behavioral sex differences have repeatedly been reported across taxa, the underlying epigenetic mechanisms in the brain are mostly lacking. Birds have previously shown to have only limited dosage compensation, leading to high sex bias of Z-chromosome gene expression. In chickens, a male hyper-methylated region (MHM) on the Z-chromosome has been associated with a local type of dosage compensation, but a more detailed characterization of the avian methylome is limiting our interpretations. Here we report an analysis of genome wide sex differences in promoter DNA-methylation and gene expression in the brain of three weeks old chickens, and associated sex differences in behavior of Red Junglefowl (ancestor of domestic chickens). Combining DNA-methylation tiling arrays with gene expression microarrays we show that a specific locus of the MHM region, together with the promoter for the zinc finger RNA binding protein (ZFR) gene on chromosome 1, is strongly associated with sex dimorphism in gene expression. Except for this, we found few differences in promoter DNA-methylation, even though hundreds of genes were robustly differentially expressed across distantly related breeds. Several of the differentially expressed genes are known to affect behavior, and as suggested from their functional annotation, we found that female Red Junglefowl are more explorative and fearful in a range of tests performed throughout their lives. This paper identifies new sites and, with increased resolution, confirms known sites where DNA-methylation seems to affect sexually dimorphic gene expression, but the general lack of this association is noticeable and strengthens the view that birds do not have dosage compensation. PMID:24782041

Synthetic dual-input mammalian genetic circuits enable tunable and stringent transcription control by chemical and light.

PubMed

Chen, Xianjun; Li, Ting; Wang, Xue; Du, Zengmin; Liu, Renmei; Yang, Yi

2016-04-07

Programmable transcription factors can enable precise control of gene expression triggered by a chemical inducer or light. To obtain versatile transgene system with combined benefits of a chemical inducer and light inducer, we created various chimeric promoters through the assembly of different copies of the tet operator and Gal4 operator module, which simultaneously responded to a tetracycline-responsive transcription factor and a light-switchable transactivator. The activities of these chimeric promoters can be regulated by tetracycline and blue light synergistically or antagonistically. Further studies of the antagonistic genetic circuit exhibited high spatiotemporal resolution and extremely low leaky expression, which therefore could be used to spatially and stringently control the expression of highly toxic protein Diphtheria toxin A for light regulated gene therapy. When transferring plasmids engineered for the gene switch-driven expression of a firefly luciferase (Fluc) into mice, the Fluc expression levels of the treated animals directly correlated with the tetracycline and light input program. We suggest that dual-input genetic circuits using TET and light that serve as triggers to achieve expression profiles may enable the design of robust therapeutic gene circuits for gene- and cell-based therapies. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Association of Protein Translation and Extracellular Matrix Gene Sets with Breast Cancer Metastasis: Findings Uncovered on Analysis of Multiple Publicly Available Datasets Using Individual Patient Data Approach.

PubMed

Chowdhury, Nilotpal; Sapru, Shantanu

2015-01-01

Microarray analysis has revolutionized the role of genomic prognostication in breast cancer. However, most studies are single series studies, and suffer from methodological problems. We sought to use a meta-analytic approach in combining multiple publicly available datasets, while correcting for batch effects, to reach a more robust oncogenomic analysis. The aim of the present study was to find gene sets associated with distant metastasis free survival (DMFS) in systemically untreated, node-negative breast cancer patients, from publicly available genomic microarray datasets. Four microarray series (having 742 patients) were selected after a systematic search and combined. Cox regression for each gene was done for the combined dataset (univariate, as well as multivariate - adjusted for expression of Cell cycle related genes) and for the 4 major molecular subtypes. The centre and microarray batch effects were adjusted by including them as random effects variables. The Cox regression coefficients for each analysis were then ranked and subjected to a Gene Set Enrichment Analysis (GSEA). Gene sets representing protein translation were independently negatively associated with metastasis in the Luminal A and Luminal B subtypes, but positively associated with metastasis in Basal tumors. Proteinaceous extracellular matrix (ECM) gene set expression was positively associated with metastasis, after adjustment for expression of cell cycle related genes on the combined dataset. Finally, the positive association of the proliferation-related genes with metastases was confirmed. To the best of our knowledge, the results depicting mixed prognostic significance of protein translation in breast cancer subtypes are being reported for the first time. We attribute this to our study combining multiple series and performing a more robust meta-analytic Cox regression modeling on the combined dataset, thus discovering 'hidden' associations. This methodology seems to yield new and interesting results and may be used as a tool to guide new research.

Association of Protein Translation and Extracellular Matrix Gene Sets with Breast Cancer Metastasis: Findings Uncovered on Analysis of Multiple Publicly Available Datasets Using Individual Patient Data Approach

PubMed Central

Chowdhury, Nilotpal; Sapru, Shantanu

2015-01-01

Introduction Microarray analysis has revolutionized the role of genomic prognostication in breast cancer. However, most studies are single series studies, and suffer from methodological problems. We sought to use a meta-analytic approach in combining multiple publicly available datasets, while correcting for batch effects, to reach a more robust oncogenomic analysis. Aim The aim of the present study was to find gene sets associated with distant metastasis free survival (DMFS) in systemically untreated, node-negative breast cancer patients, from publicly available genomic microarray datasets. Methods Four microarray series (having 742 patients) were selected after a systematic search and combined. Cox regression for each gene was done for the combined dataset (univariate, as well as multivariate – adjusted for expression of Cell cycle related genes) and for the 4 major molecular subtypes. The centre and microarray batch effects were adjusted by including them as random effects variables. The Cox regression coefficients for each analysis were then ranked and subjected to a Gene Set Enrichment Analysis (GSEA). Results Gene sets representing protein translation were independently negatively associated with metastasis in the Luminal A and Luminal B subtypes, but positively associated with metastasis in Basal tumors. Proteinaceous extracellular matrix (ECM) gene set expression was positively associated with metastasis, after adjustment for expression of cell cycle related genes on the combined dataset. Finally, the positive association of the proliferation-related genes with metastases was confirmed. Conclusion To the best of our knowledge, the results depicting mixed prognostic significance of protein translation in breast cancer subtypes are being reported for the first time. We attribute this to our study combining multiple series and performing a more robust meta-analytic Cox regression modeling on the combined dataset, thus discovering 'hidden' associations. This methodology seems to yield new and interesting results and may be used as a tool to guide new research. PMID:26080057

Expression of a chitin deacetylase gene, up-regulated in Cryptococcus laurentii strain RY1, under nitrogen limitation.

PubMed

Chakraborty, Writachit; Sarkar, Soumyadev; Chakravorty, Somnath; Bhattacharya, Semantee; Bhattacharya, Debanjana; Gachhui, Ratan

2016-05-01

This study reports the identification of a chitin deacetylase gene in Cryptococcus laurentii strain RY1 over-expressing under nitrogen limitation by differential display. The up-regulation took place in robustly growing cells rather than in starving quiescent autophagic cells. Quantitative Real Time-PCR, enzyme activity in cell lysate and cell wall analysis corroborated the up-regulation of chitin deacetylase under nitrogen limitation. These results suggest chitin deacetylase might play a significant role in nitrogen limiting growth of Cryptococcus laurentii strain RY1. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Honey bee aggression supports a link between gene regulation and behavioral evolution.

PubMed

Alaux, Cédric; Sinha, Saurabh; Hasadsri, Linda; Hunt, Greg J; Guzmán-Novoa, Ernesto; DeGrandi-Hoffman, Gloria; Uribe-Rubio, José Luis; Southey, Bruce R; Rodriguez-Zas, Sandra; Robinson, Gene E

2009-09-08

A prominent theory states that animal phenotypes arise by evolutionary changes in gene regulation, but the extent to which this theory holds true for behavioral evolution is not known. Because "nature and nurture" are now understood to involve hereditary and environmental influences on gene expression, we studied whether environmental influences on a behavioral phenotype, i.e., aggression, could have evolved into inherited differences via changes in gene expression. Here, with microarray analysis of honey bees, we show that aggression-related genes with inherited patterns of brain expression are also environmentally regulated. There were expression differences in the brain for hundreds of genes between the highly aggressive Africanized honey bee compared with European honey bee (EHB) subspecies. Similar results were obtained for EHB in response to exposure to alarm pheromone (which provokes aggression) and when comparing old and young bees (aggressive tendencies increase with age). There was significant overlap of the gene lists generated from these three microarray experiments. Moreover, there was statistical enrichment of several of the same cis regulatory motifs in promoters of genes on all three gene lists. Aggression shows a remarkably robust brain molecular signature regardless of whether it occurs because of inherited, age-related, or environmental (social) factors. It appears that one element in the evolution of different degrees of aggressive behavior in honey bees involved changes in regulation of genes that mediate the response to alarm pheromone.

Long-lasting dysregulation of gene expression in corticostriatal circuits after repeated cocaine treatment in adult rats: Effects on zif 268 and homer 1a

PubMed Central

Unal, Cagri T.; Beverley, Joel A.; Willuhn, Ingo; Steiner, Heinz

2009-01-01

Human imaging studies show that psychostimulants such as cocaine produce functional changes in several areas of cortex and striatum. These may reflect neuronal changes related to addiction. We employed gene markers (zif 268, homer 1a) that offer a high anatomical resolution to map cocaine-induced changes in 22 cortical areas and 23 functionally related striatal sectors, in order to determine the corticostriatal circuits altered by repeated cocaine exposure (25 mg/kg, 5 days). Effects were investigated 1 day and 21 days after repeated treatment to assess their longevity. Repeated cocaine treatment increased basal expression of zif 268 predominantly in sensorimotor areas of the cortex. This effect endured for 3 weeks in some areas. These changes were accompanied by attenuated gene induction by a cocaine challenge. In the insular cortex, the cocaine challenge produced a decrease in zif 268 expression after the 21-day, but not 1-day, withdrawal period. In the striatum, cocaine also affected mostly sensorimotor sectors. Repeated cocaine resulted in blunted inducibility of both zif 268 and homer 1a, changes that were still very robust 3 weeks later. Thus, our findings demonstrate that cocaine produces robust and long-lasting changes in gene regulation predominantly in sensorimotor corticostriatal circuits. These neuronal changes were associated with behavioral stereotypies, which are thought to reflect dysfunction in sensorimotor corticostriatal circuits. Future studies will have to elucidate the role of such neuronal changes in psychostimulant addiction. PMID:19419424

Brain selective transgene expression in zebrafish using an NRSE derived motif

PubMed Central

Bergeron, Sadie A.; Hannan, Markus C.; Codore, Hiba; Fero, Kandice; Li, Grace H.; Moak, Zachary; Yokogawa, Tohei; Burgess, Harold A.

2012-01-01

Transgenic technologies enable the manipulation and observation of circuits controlling behavior by permitting expression of genetically encoded reporter genes in neurons. Frequently though, neuronal expression is accompanied by transgene expression in non-neuronal tissues, which may preclude key experimental manipulations, including assessment of the contribution of neurons to behavior by ablation. To better restrict transgene expression to the nervous system in zebrafish larvae, we have used DNA sequences derived from the neuron-restrictive silencing element (NRSE). We find that one such sequence, REx2, when used in conjunction with several basal promoters, robustly suppresses transgene expression in non-neuronal tissues. Both in transient transgenic experiments and in stable enhancer trap lines, suppression is achieved without compromising expression within the nervous system. Furthermore, in REx2 enhancer trap lines non-neuronal expression can be de-repressed by knocking down expression of the NRSE binding protein RE1-silencing transcription factor (Rest). In one line, we show that the resulting pattern of reporter gene expression coincides with that of the adjacent endogenous gene, hapln3. We demonstrate that three common basal promoters are susceptible to the effects of the REx2 element, suggesting that this method may be useful for confining expression from many other promoters to the nervous system. This technique enables neural specific targeting of reporter genes and thus will facilitate the use of transgenic methods to manipulate circuit function in freely behaving larvae. PMID:23293587

Sex genes for genomic analysis in human brain: internal controls for comparison of probe level data extraction.

PubMed Central

Galfalvy, Hanga C; Erraji-Benchekroun, Loubna; Smyrniotopoulos, Peggy; Pavlidis, Paul; Ellis, Steven P; Mann, J John; Sibille, Etienne; Arango, Victoria

2003-01-01

Background Genomic studies of complex tissues pose unique analytical challenges for assessment of data quality, performance of statistical methods used for data extraction, and detection of differentially expressed genes. Ideally, to assess the accuracy of gene expression analysis methods, one needs a set of genes which are known to be differentially expressed in the samples and which can be used as a "gold standard". We introduce the idea of using sex-chromosome genes as an alternative to spiked-in control genes or simulations for assessment of microarray data and analysis methods. Results Expression of sex-chromosome genes were used as true internal biological controls to compare alternate probe-level data extraction algorithms (Microarray Suite 5.0 [MAS5.0], Model Based Expression Index [MBEI] and Robust Multi-array Average [RMA]), to assess microarray data quality and to establish some statistical guidelines for analyzing large-scale gene expression. These approaches were implemented on a large new dataset of human brain samples. RMA-generated gene expression values were markedly less variable and more reliable than MAS5.0 and MBEI-derived values. A statistical technique controlling the false discovery rate was applied to adjust for multiple testing, as an alternative to the Bonferroni method, and showed no evidence of false negative results. Fourteen probesets, representing nine Y- and two X-chromosome linked genes, displayed significant sex differences in brain prefrontal cortex gene expression. Conclusion In this study, we have demonstrated the use of sex genes as true biological internal controls for genomic analysis of complex tissues, and suggested analytical guidelines for testing alternate oligonucleotide microarray data extraction protocols and for adjusting multiple statistical analysis of differentially expressed genes. Our results also provided evidence for sex differences in gene expression in the brain prefrontal cortex, supporting the notion of a putative direct role of sex-chromosome genes in differentiation and maintenance of sexual dimorphism of the central nervous system. Importantly, these analytical approaches are applicable to all microarray studies that include male and female human or animal subjects. PMID:12962547

Sex genes for genomic analysis in human brain: internal controls for comparison of probe level data extraction.

PubMed

Galfalvy, Hanga C; Erraji-Benchekroun, Loubna; Smyrniotopoulos, Peggy; Pavlidis, Paul; Ellis, Steven P; Mann, J John; Sibille, Etienne; Arango, Victoria

2003-09-08

Genomic studies of complex tissues pose unique analytical challenges for assessment of data quality, performance of statistical methods used for data extraction, and detection of differentially expressed genes. Ideally, to assess the accuracy of gene expression analysis methods, one needs a set of genes which are known to be differentially expressed in the samples and which can be used as a "gold standard". We introduce the idea of using sex-chromosome genes as an alternative to spiked-in control genes or simulations for assessment of microarray data and analysis methods. Expression of sex-chromosome genes were used as true internal biological controls to compare alternate probe-level data extraction algorithms (Microarray Suite 5.0 [MAS5.0], Model Based Expression Index [MBEI] and Robust Multi-array Average [RMA]), to assess microarray data quality and to establish some statistical guidelines for analyzing large-scale gene expression. These approaches were implemented on a large new dataset of human brain samples. RMA-generated gene expression values were markedly less variable and more reliable than MAS5.0 and MBEI-derived values. A statistical technique controlling the false discovery rate was applied to adjust for multiple testing, as an alternative to the Bonferroni method, and showed no evidence of false negative results. Fourteen probesets, representing nine Y- and two X-chromosome linked genes, displayed significant sex differences in brain prefrontal cortex gene expression. In this study, we have demonstrated the use of sex genes as true biological internal controls for genomic analysis of complex tissues, and suggested analytical guidelines for testing alternate oligonucleotide microarray data extraction protocols and for adjusting multiple statistical analysis of differentially expressed genes. Our results also provided evidence for sex differences in gene expression in the brain prefrontal cortex, supporting the notion of a putative direct role of sex-chromosome genes in differentiation and maintenance of sexual dimorphism of the central nervous system. Importantly, these analytical approaches are applicable to all microarray studies that include male and female human or animal subjects.

A combined analysis of genome-wide expression profiling of bipolar disorder in human prefrontal cortex.

PubMed

Wang, Jinglu; Qu, Susu; Wang, Weixiao; Guo, Liyuan; Zhang, Kunlin; Chang, Suhua; Wang, Jing

2016-11-01

Numbers of gene expression profiling studies of bipolar disorder have been published. Besides different array chips and tissues, variety of the data processes in different cohorts aggravated the inconsistency of results of these genome-wide gene expression profiling studies. By searching the gene expression databases, we obtained six data sets for prefrontal cortex (PFC) of bipolar disorder with raw data and combinable platforms. We used standardized pre-processing and quality control procedures to analyze each data set separately and then combined them into a large gene expression matrix with 101 bipolar disorder subjects and 106 controls. A standard linear mixed-effects model was used to calculate the differentially expressed genes (DEGs). Multiple levels of sensitivity analyses and cross validation with genetic data were conducted. Functional and network analyses were carried out on basis of the DEGs. In the result, we identified 198 unique differentially expressed genes in the PFC of bipolar disorder and control. Among them, 115 DEGs were robust to at least three leave-one-out tests or different pre-processing methods; 51 DEGs were validated with genetic association signals. Pathway enrichment analysis showed these DEGs were related with regulation of neurological system, cell death and apoptosis, and several basic binding processes. Protein-protein interaction network further identified one key hub gene. We have contributed the most comprehensive integrated analysis of bipolar disorder expression profiling studies in PFC to date. The DEGs, especially those with multiple validations, may denote a common signature of bipolar disorder and contribute to the pathogenesis of disease. Copyright © 2016 Elsevier Ltd. All rights reserved.

Identification of reference genes for RT-qPCR in ovine mammary tissue during late pregnancy and lactation and in response to maternal nutritional programming.

PubMed

Paten, A M; Pain, S J; Peterson, S W; Blair, H T; Kenyon, P R; Dearden, P K; Duncan, E J

2014-08-01

The mammary gland is a complex tissue consisting of multiple cell types which, over the lifetime of an animal, go through repeated cycles of development associated with pregnancy, lactation and involution. The mammary gland is also known to be sensitive to maternal programming by environmental stimuli such as nutrition. The molecular basis of these adaptations is of significant interest, but requires robust methods to measure gene expression. Reverse-transcription quantitative PCR (RT-qPCR) is commonly used to measure gene expression, and is currently the method of choice for validating genome-wide expression studies. RT-qPCR requires the selection of reference genes that are stably expressed over physiological states and treatments. In this study we identify suitable reference genes to normalize RT-qPCR data for the ovine mammary gland in two physiological states; late pregnancy and lactation. Biopsies were collected from offspring of ewes that had been subjected to different nutritional paradigms during pregnancy to examine effects of maternal programming on the mammary gland of the offspring. We evaluated eight candidate reference genes and found that two reference genes (PRPF3 and CUL1) are required for normalising RT-qPCR data from pooled RNA samples, but five reference genes are required for analyzing gene expression in individual animals (SENP2, EIF6, MRPL39, ATP1A1, CUL1). Using these stable reference genes, we showed that TET1, a key regulator of DNA methylation, is responsive to maternal programming and physiological state. The identification of these novel reference genes will be of utility to future studies of gene expression in the ovine mammary gland. Copyright © 2014 the American Physiological Society.

The segment polarity network is a robust developmental module

NASA Astrophysics Data System (ADS)

von Dassow, George; Meir, Eli; Munro, Edwin M.; Odell, Garrett M.

2000-07-01

All insects possess homologous segments, but segment specification differs radically among insect orders. In Drosophila, maternal morphogens control the patterned activation of gap genes, which encode transcriptional regulators that shape the patterned expression of pair-rule genes. This patterning cascade takes place before cellularization. Pair-rule gene products subsequently `imprint' segment polarity genes with reiterated patterns, thus defining the primordial segments. This mechanism must be greatly modified in insect groups in which many segments emerge only after cellularization. In beetles and parasitic wasps, for instance, pair-rule homologues are expressed in patterns consistent with roles during segmentation, but these patterns emerge within cellular fields. In contrast, although in locusts pair-rule homologues may not control segmentation, some segment polarity genes and their interactions are conserved. Perhaps segmentation is modular, with each module autonomously expressing a characteristic intrinsic behaviour in response to transient stimuli. If so, evolution could rearrange inputs to modules without changing their intrinsic behaviours. Here we suggest, using computer simulations, that the Drosophila segment polarity genes constitute such a module, and that this module is resistant to variations in the kinetic constants that govern its behaviour.

Evaluation of RNA extraction methods and identification of putative reference genes for real-time quantitative polymerase chain reaction expression studies on olive (Olea europaea L.) fruits.

PubMed

Nonis, Alberto; Vezzaro, Alice; Ruperti, Benedetto

2012-07-11

Genome wide transcriptomic surveys together with targeted molecular studies are uncovering an ever increasing number of differentially expressed genes in relation to agriculturally relevant processes in olive (Olea europaea L). These data need to be supported by quantitative approaches enabling the precise estimation of transcript abundance. qPCR being the most widely adopted technique for mRNA quantification, preliminary work needs to be done to set up robust methods for extraction of fully functional RNA and for the identification of the best reference genes to obtain reliable quantification of transcripts. In this work, we have assessed different methods for their suitability for RNA extraction from olive fruits and leaves and we have evaluated thirteen potential candidate reference genes on 21 RNA samples belonging to fruit developmental/ripening series and to leaves subjected to wounding. By using two different algorithms, GAPDH2 and PP2A1 were identified as the best reference genes for olive fruit development and ripening, and their effectiveness for normalization of expression of two ripening marker genes was demonstrated.

Prediction of gene expression with cis-SNPs using mixed models and regularization methods.

PubMed

Zeng, Ping; Zhou, Xiang; Huang, Shuiping

2017-05-11

It has been shown that gene expression in human tissues is heritable, thus predicting gene expression using only SNPs becomes possible. The prediction of gene expression can offer important implications on the genetic architecture of individual functional associated SNPs and further interpretations of the molecular basis underlying human diseases. We compared three types of methods for predicting gene expression using only cis-SNPs, including the polygenic model, i.e. linear mixed model (LMM), two sparse models, i.e. Lasso and elastic net (ENET), and the hybrid of LMM and sparse model, i.e. Bayesian sparse linear mixed model (BSLMM). The three kinds of prediction methods have very different assumptions of underlying genetic architectures. These methods were evaluated using simulations under various scenarios, and were applied to the Geuvadis gene expression data. The simulations showed that these four prediction methods (i.e. Lasso, ENET, LMM and BSLMM) behaved best when their respective modeling assumptions were satisfied, but BSLMM had a robust performance across a range of scenarios. According to R 2 of these models in the Geuvadis data, the four methods performed quite similarly. We did not observe any clustering or enrichment of predictive genes (defined as genes with R 2  ≥ 0.05) across the chromosomes, and also did not see there was any clear relationship between the proportion of the predictive genes and the proportion of genes in each chromosome. However, an interesting finding in the Geuvadis data was that highly predictive genes (e.g. R 2  ≥ 0.30) may have sparse genetic architectures since Lasso, ENET and BSLMM outperformed LMM for these genes; and this observation was validated in another gene expression data. We further showed that the predictive genes were enriched in approximately independent LD blocks. Gene expression can be predicted with only cis-SNPs using well-developed prediction models and these predictive genes were enriched in some approximately independent LD blocks. The prediction of gene expression can shed some light on the functional interpretation for identified SNPs in GWASs.

A hybrid approach of gene sets and single genes for the prediction of survival risks with gene expression data.

PubMed

Seok, Junhee; Davis, Ronald W; Xiao, Wenzhong

2015-01-01

Accumulated biological knowledge is often encoded as gene sets, collections of genes associated with similar biological functions or pathways. The use of gene sets in the analyses of high-throughput gene expression data has been intensively studied and applied in clinical research. However, the main interest remains in finding modules of biological knowledge, or corresponding gene sets, significantly associated with disease conditions. Risk prediction from censored survival times using gene sets hasn't been well studied. In this work, we propose a hybrid method that uses both single gene and gene set information together to predict patient survival risks from gene expression profiles. In the proposed method, gene sets provide context-level information that is poorly reflected by single genes. Complementarily, single genes help to supplement incomplete information of gene sets due to our imperfect biomedical knowledge. Through the tests over multiple data sets of cancer and trauma injury, the proposed method showed robust and improved performance compared with the conventional approaches with only single genes or gene sets solely. Additionally, we examined the prediction result in the trauma injury data, and showed that the modules of biological knowledge used in the prediction by the proposed method were highly interpretable in biology. A wide range of survival prediction problems in clinical genomics is expected to benefit from the use of biological knowledge.

A Hybrid Approach of Gene Sets and Single Genes for the Prediction of Survival Risks with Gene Expression Data

PubMed Central

Seok, Junhee; Davis, Ronald W.; Xiao, Wenzhong

2015-01-01

Accumulated biological knowledge is often encoded as gene sets, collections of genes associated with similar biological functions or pathways. The use of gene sets in the analyses of high-throughput gene expression data has been intensively studied and applied in clinical research. However, the main interest remains in finding modules of biological knowledge, or corresponding gene sets, significantly associated with disease conditions. Risk prediction from censored survival times using gene sets hasn’t been well studied. In this work, we propose a hybrid method that uses both single gene and gene set information together to predict patient survival risks from gene expression profiles. In the proposed method, gene sets provide context-level information that is poorly reflected by single genes. Complementarily, single genes help to supplement incomplete information of gene sets due to our imperfect biomedical knowledge. Through the tests over multiple data sets of cancer and trauma injury, the proposed method showed robust and improved performance compared with the conventional approaches with only single genes or gene sets solely. Additionally, we examined the prediction result in the trauma injury data, and showed that the modules of biological knowledge used in the prediction by the proposed method were highly interpretable in biology. A wide range of survival prediction problems in clinical genomics is expected to benefit from the use of biological knowledge. PMID:25933378

Docosahexaenoic acid antagonizes the boosting effect of palmitic acid on LPS inflammatory signaling by inhibiting gene transcription and ceramide synthesis

PubMed Central

Jin, Junfei; Lu, Zhongyang; Li, Yanchun; Cowart, L. Ashley; Lopes-Virella, Maria F.

2018-01-01

It is well known that saturated fatty acids (SFAs) and unsaturated fatty acid, in particular omega-3 polyunsaturated fatty acids (n-3 PUFAs), have different effects on inflammatory signaling: SFAs are pro-inflammatory but n-3 PUFAs have strong anti-inflammatory properties. We have reported that palmitic acid (PA), a saturated fatty acid, robustly amplifies lipopolysaccharide (LPS) signaling to upregulate proinflammatory gene expression in macrophages. We also reported that the increased production of ceramide (CER) via sphingomyelin (SM) hydrolysis and CER de novo synthesis plays a key role in the synergistic effect of LPS and PA on proinflammatory gene expression. However, it remains unclear if n-3 PUFAs are capable of antagonizing the synergistic effect of LPS and PA on gene expression and CER production. In this study, we employed the above macrophage culture system and lipidomical analysis to assess the effect of n-3 PUFAs on proinflammatory gene expression and CER production stimulated by LPS and PA. Results showed that DHA strongly inhibited the synergistic effect of LPS and PA on proinflammatory gene expression by targeting nuclear factor kappa B (NFκB)-dependent gene transcription. Results also showed that DHA inhibited the cooperative effect of LPS and PA on CER production by targeting CER de novo synthesis, but not SM hydrolysis. Furthermore, results showed that myriocin, a specific inhibitor of serine palmitoyltransferase, strongly inhibited both LPS-PA-stimulated CER synthesis and proinflammatory gene expression, indicating that CER synthesis is associated with proinflammatory gene expression and that inhibition of CER synthesis contributes to DHA-inhibited proinflammatory gene expression. Taken together, this study demonstrates that DHA antagonizes the boosting effect of PA on LPS signaling on proinflammatory gene expression by targeting both NFκB-dependent transcription and CER de novo synthesis in macrophages. PMID:29474492

Docosahexaenoic acid antagonizes the boosting effect of palmitic acid on LPS inflammatory signaling by inhibiting gene transcription and ceramide synthesis.

PubMed

Jin, Junfei; Lu, Zhongyang; Li, Yanchun; Cowart, L Ashley; Lopes-Virella, Maria F; Huang, Yan

2018-01-01

It is well known that saturated fatty acids (SFAs) and unsaturated fatty acid, in particular omega-3 polyunsaturated fatty acids (n-3 PUFAs), have different effects on inflammatory signaling: SFAs are pro-inflammatory but n-3 PUFAs have strong anti-inflammatory properties. We have reported that palmitic acid (PA), a saturated fatty acid, robustly amplifies lipopolysaccharide (LPS) signaling to upregulate proinflammatory gene expression in macrophages. We also reported that the increased production of ceramide (CER) via sphingomyelin (SM) hydrolysis and CER de novo synthesis plays a key role in the synergistic effect of LPS and PA on proinflammatory gene expression. However, it remains unclear if n-3 PUFAs are capable of antagonizing the synergistic effect of LPS and PA on gene expression and CER production. In this study, we employed the above macrophage culture system and lipidomical analysis to assess the effect of n-3 PUFAs on proinflammatory gene expression and CER production stimulated by LPS and PA. Results showed that DHA strongly inhibited the synergistic effect of LPS and PA on proinflammatory gene expression by targeting nuclear factor kappa B (NFκB)-dependent gene transcription. Results also showed that DHA inhibited the cooperative effect of LPS and PA on CER production by targeting CER de novo synthesis, but not SM hydrolysis. Furthermore, results showed that myriocin, a specific inhibitor of serine palmitoyltransferase, strongly inhibited both LPS-PA-stimulated CER synthesis and proinflammatory gene expression, indicating that CER synthesis is associated with proinflammatory gene expression and that inhibition of CER synthesis contributes to DHA-inhibited proinflammatory gene expression. Taken together, this study demonstrates that DHA antagonizes the boosting effect of PA on LPS signaling on proinflammatory gene expression by targeting both NFκB-dependent transcription and CER de novo synthesis in macrophages.

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

BMP, Wnt and FGF signals are integrated through evolutionarily conserved enhancers to achieve robust expression of Pax3 and Zic genes at the zebrafish neural plate border

PubMed Central

Garnett, Aaron T.; Square, Tyler A.; Medeiros, Daniel M.

2012-01-01

Neural crest cells generate a range of cells and tissues in the vertebrate head and trunk, including peripheral neurons, pigment cells, and cartilage. Neural crest cells arise from the edges of the nascent central nervous system, a domain called the neural plate border (NPB). NPB induction is known to involve the BMP, Wnt and FGF signaling pathways. However, little is known about how these signals are integrated to achieve temporally and spatially specific expression of genes in NPB cells. Furthermore, the timing and relative importance of these signals in NPB formation appears to differ between vertebrate species. Here, we use heat-shock overexpression and chemical inhibitors to determine whether, and when, BMP, Wnt and FGF signaling are needed for expression of the NPB specifiers pax3a and zic3 in zebrafish. We then identify four evolutionarily conserved enhancers from the pax3a and zic3 loci and test their response to BMP, Wnt and FGF perturbations. We find that all three signaling pathways are required during gastrulation for the proper expression of pax3a and zic3 in the zebrafish NPB. We also find that, although the expression patterns driven by the pax3a and zic3 enhancers largely overlap, they respond to different combinations of BMP, Wnt and FGF signals. Finally, we show that the combination of the two pax3a enhancers is less susceptible to signaling perturbations than either enhancer alone. Taken together, our results reveal how BMPs, FGFs and Wnts act cooperatively and redundantly through partially redundant enhancers to achieve robust, specific gene expression in the zebrafish NPB. PMID:23034628

Selection and evaluation of reference genes for RT-qPCR expression studies on Burkholderia tropica strain Ppe8, a sugarcane-associated diazotrophic bacterium grown with different carbon sources or sugarcane juice.

PubMed

da Silva, Paula Renata Alves; Vidal, Marcia Soares; de Paula Soares, Cleiton; Polese, Valéria; Simões-Araújo, Jean Luís; Baldani, José Ivo

2016-11-01

Among the members of the genus Burkholderia, Burkholderia tropica has the ability to fix nitrogen and promote sugarcane plant growth as well as act as a biological control agent. There is little information about how this bacterium metabolizes carbohydrates as well as those carbon sources found in the sugarcane juice that accumulates in stems during plant growth. Reverse transcription quantitative PCR (RT-qPCR) can be used to evaluate changes in gene expression during bacterial growth on different carbon sources. Here we tested the expression of six reference genes, lpxC, gyrB, recA, rpoA, rpoB, and rpoD, when cells were grown with glucose, fructose, sucrose, mannitol, aconitic acid, and sugarcane juice as carbon sources. The lpxC, gyrB, and recA were selected as the most stable reference genes based on geNorm and NormFinder software analyses. Validation of these three reference genes during strain Ppe8 growth on the same carbon sources showed that genes involved in glycogen biosynthesis (glgA, glgB, glgC) and trehalose biosynthesis (treY and treZ) were highly expressed when Ppe8 was grown in aconitic acid relative to other carbon sources, while otsA expression (trehalose biosynthesis) was reduced with all carbon sources. In addition, the expression level of the ORF_6066 (gluconolactonase) gene was reduced on sugarcane juice. The results confirmed the stability of the three selected reference genes (lpxC, gyrB, and recA) during the RT-qPCR and also their robustness by evaluating the relative expression of genes involved in glycogen and trehalose biosynthesis when strain Ppe8 was grown on different carbon sources and sugarcane juice.

A regulatory sequence from the retinoid X receptor γ gene directs expression to horizontal cells and photoreceptors in the embryonic chicken retina.

PubMed

Blixt, Maria K E; Hallböök, Finn

2016-01-01

Combining techniques of episomal vector gene-specific Cre expression and genomic integration using the piggyBac transposon system enables studies of gene expression-specific cell lineage tracing in the chicken retina. In this work, we aimed to target the retinal horizontal cell progenitors. A 208 bp gene regulatory sequence from the chicken retinoid X receptor γ gene (RXRγ208) was used to drive Cre expression. RXRγ is expressed in progenitors and photoreceptors during development. The vector was combined with a piggyBac "donor" vector containing a floxed STOP sequence followed by enhanced green fluorescent protein (EGFP), as well as a piggyBac helper vector for efficient integration into the host cell genome. The vectors were introduced into the embryonic chicken retina with in ovo electroporation. Tissue electroporation targets specific developmental time points and in specific structures. Cells that drove Cre expression from the regulatory RXRγ208 sequence excised the floxed STOP-sequence and expressed GFP. The approach generated a stable lineage with robust expression of GFP in retinal cells that have activated transcription from the RXRγ208 sequence. Furthermore, GFP was expressed in cells that express horizontal or photoreceptor markers when electroporation was performed between developmental stages 22 and 28. Electroporation of a stage 12 optic cup gave multiple cell types in accordance with RXRγ gene expression in the early retina. In this study, we describe an easy, cost-effective, and time-efficient method for testing regulatory sequences in general. More specifically, our results open up the possibility for further studies of the RXRγ-gene regulatory network governing the formation of photoreceptor and horizontal cells. In addition, the method presents approaches to target the expression of effector genes, such as regulators of cell fate or cell cycle progression, to these cells and their progenitor.

LWD-TCP complex activates the morning gene CCA1 in Arabidopsis.

PubMed

Wu, Jing-Fen; Tsai, Huang-Lung; Joanito, Ignasius; Wu, Yi-Chen; Chang, Chin-Wen; Li, Yi-Hang; Wang, Ying; Hong, Jong Chan; Chu, Jhih-Wei; Hsu, Chao-Ping; Wu, Shu-Hsing

2016-10-13

A double-negative feedback loop formed by the morning genes CIRCADIAN CLOCK ASSOCIATED1 (CCA1)/LATE ELONGATED HYPOCOTYL (LHY) and the evening gene TIMING OF CAB EXPRESSION1 (TOC1) contributes to regulation of the circadian clock in Arabidopsis. A 24-h circadian cycle starts with the peak expression of CCA1 at dawn. Although CCA1 is targeted by multiple transcriptional repressors, including PSEUDO-RESPONSE REGULATOR9 (PRR9), PRR7, PRR5 and CCA1 HIKING EXPEDITION (CHE), activators of CCA1 remain elusive. Here we use mathematical modelling to infer a co-activator role for LIGHT-REGULATED WD1 (LWD1) in CCA1 expression. We show that the TEOSINTE BRANCHED 1-CYCLOIDEA-PCF20 (TCP20) and TCP22 proteins act as LWD-interacting transcriptional activators. The concomitant binding of LWD1 and TCP20/TCP22 to the TCP-binding site in the CCA1 promoter activates CCA1. Our study reveals activators of the morning gene CCA1 and provides an action mechanism that ensures elevated expression of CCA1 at dawn to sustain a robust clock.

LWD–TCP complex activates the morning gene CCA1 in Arabidopsis

PubMed Central

Wu, Jing-Fen; Tsai, Huang-Lung; Joanito, Ignasius; Wu, Yi-Chen; Chang, Chin-Wen; Li, Yi-Hang; Wang, Ying; Hong, Jong Chan; Chu, Jhih-Wei; Hsu, Chao-Ping; Wu, Shu-Hsing

2016-01-01

A double-negative feedback loop formed by the morning genes CIRCADIAN CLOCK ASSOCIATED1 (CCA1)/LATE ELONGATED HYPOCOTYL (LHY) and the evening gene TIMING OF CAB EXPRESSION1 (TOC1) contributes to regulation of the circadian clock in Arabidopsis. A 24-h circadian cycle starts with the peak expression of CCA1 at dawn. Although CCA1 is targeted by multiple transcriptional repressors, including PSEUDO-RESPONSE REGULATOR9 (PRR9), PRR7, PRR5 and CCA1 HIKING EXPEDITION (CHE), activators of CCA1 remain elusive. Here we use mathematical modelling to infer a co-activator role for LIGHT-REGULATED WD1 (LWD1) in CCA1 expression. We show that the TEOSINTE BRANCHED 1-CYCLOIDEA-PCF20 (TCP20) and TCP22 proteins act as LWD-interacting transcriptional activators. The concomitant binding of LWD1 and TCP20/TCP22 to the TCP-binding site in the CCA1 promoter activates CCA1. Our study reveals activators of the morning gene CCA1 and provides an action mechanism that ensures elevated expression of CCA1 at dawn to sustain a robust clock. PMID:27734958

Macromolecular Crowding Regulates the Gene Expression Profile by Limiting Diffusion

DOE PAGES

Golkaram, Mahdi; Hellander, Stefan; Drawert, Brian; ...

2016-11-28

We seek to elucidate the role of macromolecular crowding in transcription and translation. It is well known that stochasticity in gene expression can lead to differential gene expression and heterogeneity in a cell population. Recent experimental observations by Tan et al. have improved our understanding of the functional role of macromolecular crowding. It can be inferred from their observations that macromolecular crowding can lead to robustness in gene expression, resulting in a more homogeneous cell population. We introduce a spatial stochastic model to provide insight into this process. Our results show that macromolecular crowding reduces noise (as measured by themore » kurtosis of the mRNA distribution) in a cell population by limiting the diffusion of transcription factors (i.e. removing the unstable intermediate states), and that crowding by large molecules reduces noise more efficiently than crowding by small molecules. Finally, our simulation results provide evidence that the local variation in chromatin density as well as the total volume exclusion of the chromatin in the nucleus can induce a homogenous cell population« less

Induction of 9-cis-epoxycarotenoid dioxygenase in Arabidopsis thaliana seeds enhances seed dormancy

PubMed Central

Martínez-Andújar, Cristina; Ordiz, M. Isabel; Huang, Zhonglian; Nonogaki, Mariko; Beachy, Roger N.; Nonogaki, Hiroyuki

2011-01-01

Full understanding of mechanisms that control seed dormancy and germination remains elusive. Whereas it has been proposed that translational control plays a predominant role in germination, other studies suggest the importance of specific gene expression patterns in imbibed seeds. Transgenic plants were developed to permit conditional expression of a gene encoding 9-cis-epoxycarotenoid dioxygenase 6 (NCED6), a rate-limiting enzyme in abscisic acid (ABA) biosynthesis, using the ecdysone receptor-based plant gene switch system and the ligand methoxyfenozide. Induction of NCED6 during imbibition increased ABA levels more than 20-fold and was sufficient to prevent seed germination. Germination suppression was prevented by fluridone, an inhibitor of ABA biosynthesis. In another study, induction of the NCED6 gene in transgenic seeds of nondormant mutants tt3 and tt4 reestablished seed dormancy. Furthermore, inducing expression of NCED6 during seed development suppressed vivipary, precocious germination of developing seeds. These results indicate that expression of a hormone metabolism gene in seeds can be a sole determinant of dormancy. This study opens the possibility of developing a robust technology to suppress or promote seed germination through engineering pathways of hormone metabolism. PMID:21969557

Induction of 9-cis-epoxycarotenoid dioxygenase in Arabidopsis thaliana seeds enhances seed dormancy.

PubMed

Martínez-Andújar, Cristina; Ordiz, M Isabel; Huang, Zhonglian; Nonogaki, Mariko; Beachy, Roger N; Nonogaki, Hiroyuki

2011-10-11

Full understanding of mechanisms that control seed dormancy and germination remains elusive. Whereas it has been proposed that translational control plays a predominant role in germination, other studies suggest the importance of specific gene expression patterns in imbibed seeds. Transgenic plants were developed to permit conditional expression of a gene encoding 9-cis-epoxycarotenoid dioxygenase 6 (NCED6), a rate-limiting enzyme in abscisic acid (ABA) biosynthesis, using the ecdysone receptor-based plant gene switch system and the ligand methoxyfenozide. Induction of NCED6 during imbibition increased ABA levels more than 20-fold and was sufficient to prevent seed germination. Germination suppression was prevented by fluridone, an inhibitor of ABA biosynthesis. In another study, induction of the NCED6 gene in transgenic seeds of nondormant mutants tt3 and tt4 reestablished seed dormancy. Furthermore, inducing expression of NCED6 during seed development suppressed vivipary, precocious germination of developing seeds. These results indicate that expression of a hormone metabolism gene in seeds can be a sole determinant of dormancy. This study opens the possibility of developing a robust technology to suppress or promote seed germination through engineering pathways of hormone metabolism.

Cat odor exposure induces distinct changes in the exploratory behavior and Wfs1 gene expression in C57Bl/6 and 129Sv mice.

PubMed

Raud, Sirli; Sütt, Silva; Plaas, Mario; Luuk, Hendrik; Innos, Jürgen; Philips, Mari-Anne; Kõks, Sulev; Vasar, Eero

2007-10-16

129Sv and C57Bl/6 (Bl6) strains are two most widely used inbred mice strains for generation of transgenic animals. The present study confirms the existence of substantial differences in the behavior of these two mice strains. The exploratory behavior of Bl6 mice in a novel environment was significantly higher compared to 129Sv mice. The exposure of mice to cat odor-induced an anxiety-like state in Bl6, but not in 129Sv mice. The levels of Wfs1 gene expression did not differ in the prefrontal cortex, mesolimbic area and temporal lobe of experimentally naive Bl6 and 129Sv mice. However, after cat odor exposure the expression of Wfs1 gene was significantly lower in the mesolimbic area and temporal lobe of Bl6 mice compared to 129Sv strain. Dynamics of Wfs1 gene expression and exploratory behavior suggest that the down-regulation of Wfs1 gene in Bl6 mice might be related to the increased anxiety. Further studies are needed to test the robustness and possible causal relationship of this finding.

Transcriptomic response of Drosophila melanogaster pupae developed in hypergravity.

PubMed

Hateley, Shannon; Hosamani, Ravikumar; Bhardwaj, Shilpa R; Pachter, Lior; Bhattacharya, Sharmila

2016-10-01

Altered gravity can perturb normal development and induce corresponding changes in gene expression. Understanding this relationship between the physical environment and a biological response is important for NASA's space travel goals. We use RNA-Seq and qRT-PCR techniques to profile changes in early Drosophila melanogaster pupae exposed to chronic hypergravity (3g, or three times Earth's gravity). During the pupal stage, D. melanogaster rely upon gravitational cues for proper development. Assessing gene expression changes in the pupae under altered gravity conditions helps highlight gravity-dependent genetic pathways. A robust transcriptional response was observed in hypergravity-treated pupae compared to controls, with 1513 genes showing a significant (q<0.05) difference in gene expression. Five major biological processes were affected: ion transport, redox homeostasis, immune response, proteolysis, and cuticle development. This outlines the underlying molecular and biological changes occurring in Drosophila pupae in response to hypergravity; gravity is important for many biological processes on Earth. Published by Elsevier Inc.

Molecular Classifiers for Acute Kidney Transplant Rejection in Peripheral Blood by Whole Genome Gene Expression Profiling

PubMed Central

Kurian, S. M.; Williams, A. N.; Gelbart, T.; Campbell, D.; Mondala, T. S.; Head, S. R.; Horvath, S.; Gaber, L.; Thompson, R.; Whisenant, T.; Lin, W.; Langfelder, P.; Robison, E. H.; Schaffer, R. L.; Fisher, J. S.; Friedewald, J.; Flechner, S. M.; Chan, L. K.; Wiseman, A. C.; Shidban, H.; Mendez, R.; Heilman, R.; Abecassis, M. M.; Marsh, C. L.; Salomon, D. R.

2015-01-01

There are no minimally invasive diagnostic metrics for acute kidney transplant rejection (AR), especially in the setting of the common confounding diagnosis, acute dysfunction with no rejection (ADNR). Thus, though kidney transplant biopsies remain the gold standard, they are invasive, have substantial risks, sampling error issues and significant costs and are not suitable for serial monitoring. Global gene expression profiles of 148 peripheral blood samples from transplant patients with excellent function and normal histology (TX; n = 46), AR (n = 63) and ADNR (n = 39), from two independent cohorts were analyzed with DNA microarrays. We applied a new normalization tool, frozen robust multi-array analysis, particularly suitable for clinical diagnostics, multiple prediction tools to discover, refine and validate robust molecular classifiers and we tested a novel one-by-one analysis strategy to model the real clinical application of this test. Multiple three-way classifier tools identified 200 highest value probesets with sensitivity, specificity, positive predictive value, negative predictive value and area under the curve for the validation cohort ranging from 82% to 100%, 76% to 95%, 76% to 95%, 79% to 100%, 84% to 100% and 0.817 to 0.968, respectively. We conclude that peripheral blood gene expression profiling can be used as a minimally invasive tool to accurately reveal TX, AR and ADNR in the setting of acute kidney transplant dysfunction. PMID:24725967

The R148.3 Gene Modulates Caenorhabditis elegans Lifespan and Fat Metabolism

PubMed Central

Roy-Bellavance, Catherine; Grants, Jennifer M.; Miard, Stéphanie; Lee, Kayoung; Rondeau, Évelyne; Guillemette, Chantal; Simard, Martin J.; Taubert, Stefan; Picard, Frédéric

2017-01-01

Despite many advances, the molecular links between energy metabolism and longevity are not well understood. Here, we have used the nematode model Caenorhabditis elegans to study the role of the yet-uncharacterized gene R148.3 in fat accumulation and lifespan. In wild-type worms, a R148.3p::GFP reporter showed enhanced expression throughout life in the pharynx, in neurons, and in muscles. Functionally, a protein fusing a predicted 22 amino acid N-terminal signal sequence (SS) of R148.3 to mCherry displayed robust accumulation in coelomyocytes, indicating that R148.3 is a secreted protein. Systematic depletion of R148.3 by RNA interference (RNAi) at L1 but not at young-adult stage enhanced triglyceride accumulation, which was associated with increased food uptake and lower expression of genes involved in lipid oxidation. However, RNAi of R148.3 at both L1 and young-adult stages robustly diminished mean and maximal lifespan of wild-type worms, and also abolished the long-lived phenotypes of eat-2 and daf-2/InsR mutants. Based on these data, we propose that R148.3 is an SS that modulates fat mass and longevity in an independent manner. PMID:28620088

Viral delivery of genome-modifying proteins for cellular reprogramming.

PubMed

Mikkelsen, Jacob Giehm

2018-06-18

Following the successful development of virus-based gene vehicles for genetic therapies, exploitation of viruses as carriers of genetic tools for cellular reprogramming and genome editing should be right up the street. However, whereas persistent, potentially life-long gene expression is the main goal of conventional genetic therapies, tools and bits for genome engineering should ideally be short-lived and active only for a limited time. Although viral vector systems have already been adapted for potent genome editing both in vitro and in vivo, regulatable gene expression systems or self-limiting expression circuits need to be implemented limiting exposure of chromatin to genome-modifying enzymes. As an alternative approach, emerging virus-based protein delivery technologies support direct protein delivery, providing a short, robust boost of enzymatic activity in transduced cells. Is this potentially the perfect way of shipping loads of cargo to many recipients and still maintain short-term activity? Copyright © 2018 Elsevier Ltd. All rights reserved.

BloodSpot: a database of gene expression profiles and transcriptional programs for healthy and malignant haematopoiesis

PubMed Central

Bagger, Frederik Otzen; Sasivarevic, Damir; Sohi, Sina Hadi; Laursen, Linea Gøricke; Pundhir, Sachin; Sønderby, Casper Kaae; Winther, Ole; Rapin, Nicolas; Porse, Bo T.

2016-01-01

Research on human and murine haematopoiesis has resulted in a vast number of gene-expression data sets that can potentially answer questions regarding normal and aberrant blood formation. To researchers and clinicians with limited bioinformatics experience, these data have remained available, yet largely inaccessible. Current databases provide information about gene-expression but fail to answer key questions regarding co-regulation, genetic programs or effect on patient survival. To address these shortcomings, we present BloodSpot (www.bloodspot.eu), which includes and greatly extends our previously released database HemaExplorer, a database of gene expression profiles from FACS sorted healthy and malignant haematopoietic cells. A revised interactive interface simultaneously provides a plot of gene expression along with a Kaplan–Meier analysis and a hierarchical tree depicting the relationship between different cell types in the database. The database now includes 23 high-quality curated data sets relevant to normal and malignant blood formation and, in addition, we have assembled and built a unique integrated data set, BloodPool. Bloodpool contains more than 2000 samples assembled from six independent studies on acute myeloid leukemia. Furthermore, we have devised a robust sample integration procedure that allows for sensitive comparison of user-supplied patient samples in a well-defined haematopoietic cellular space. PMID:26507857

Estimating differential expression from multiple indicators

PubMed Central

Ilmjärv, Sten; Hundahl, Christian Ansgar; Reimets, Riin; Niitsoo, Margus; Kolde, Raivo; Vilo, Jaak; Vasar, Eero; Luuk, Hendrik

2014-01-01

Regardless of the advent of high-throughput sequencing, microarrays remain central in current biomedical research. Conventional microarray analysis pipelines apply data reduction before the estimation of differential expression, which is likely to render the estimates susceptible to noise from signal summarization and reduce statistical power. We present a probe-level framework, which capitalizes on the high number of concurrent measurements to provide more robust differential expression estimates. The framework naturally extends to various experimental designs and target categories (e.g. transcripts, genes, genomic regions) as well as small sample sizes. Benchmarking in relation to popular microarray and RNA-sequencing data-analysis pipelines indicated high and stable performance on the Microarray Quality Control dataset and in a cell-culture model of hypoxia. Experimental-data-exhibiting long-range epigenetic silencing of gene expression was used to demonstrate the efficacy of detecting differential expression of genomic regions, a level of analysis not embraced by conventional workflows. Finally, we designed and conducted an experiment to identify hypothermia-responsive genes in terms of monotonic time-response. As a novel insight, hypothermia-dependent up-regulation of multiple genes of two major antioxidant pathways was identified and verified by quantitative real-time PCR. PMID:24586062

A super gene expression system enhances the anti-glioma effects of adenovirus-mediated REIC/Dkk-3 gene therapy

NASA Astrophysics Data System (ADS)

Oka, Tetsuo; Kurozumi, Kazuhiko; Shimazu, Yosuke; Ichikawa, Tomotsugu; Ishida, Joji; Otani, Yoshihiro; Shimizu, Toshihiko; Tomita, Yusuke; Sakaguchi, Masakiyo; Watanabe, Masami; Nasu, Yasutomo; Kumon, Hiromi; Date, Isao

2016-09-01

Reduced expression in immortalized cells/Dickkopf-3 (REIC/Dkk-3) is a tumor suppressor and therapeutic gene in many human cancers. Recently, an adenovirus REIC vector with the super gene expression system (Ad-SGE-REIC) was developed to increase REIC/Dkk-3 expression and enhance therapeutic effects compared with the conventional adenoviral vector (Ad-CAG-REIC). In this study, we investigated the in vitro and in vivo effects of Ad-SGE-REIC on malignant glioma. In U87ΔEGFR and GL261 glioma cells, western blotting confirmed that robust upregulation of REIC/Dkk-3 expression occurred in Ad-SGE-REIC-transduced cells, most notably after transduction at a multiplicity of infection of 10. Cytotoxicity assays showed that Ad-SGE-REIC resulted in a time-dependent and significant reduction in the number of malignant glioma cells attaching to the bottom of culture wells. Xenograft and syngeneic mouse intracranial glioma models treated with Ad-SGE-REIC had significantly longer survival than those treated with the control vector Ad-LacZ or with Ad-CAG-REIC. This study demonstrated the anti-glioma effect of Ad-SGE-REIC, which may represent a promising strategy for the treatment of malignant glioma.

Expression profiling of chickpea genes differentially regulated during a resistance response to Ascochyta rabiei.

PubMed

Coram, Tristan E; Pang, Edwin C K

2006-11-01

Using microarray technology and a set of chickpea (Cicer arietinum L.) unigenes, grasspea (Lathyrus sativus L.) expressed sequence tags (ESTs) and lentil (Lens culinaris Med.) resistance gene analogues, the ascochyta blight (Ascochyta rabiei (Pass.) L.) resistance response was studied in four chickpea genotypes, including resistant, moderately resistant, susceptible and wild relative (Cicer echinospermum L.) genotypes. The experimental system minimized environmental effects and was conducted in reference design, in which samples from mock-inoculated controls acted as reference against post-inoculation samples. Robust data quality was achieved through the use of three biological replicates (including a dye swap), the inclusion of negative controls and strict selection criteria for differentially expressed genes, including a fold change cut-off determined by self-self hybridizations, Student's t-test and multiple testing correction (P < 0.05). Microarray observations were also validated by quantitative reverse transcriptase-polymerase chain reaction (RT-PCR). The time course expression patterns of 756 microarray features resulted in the differential expression of 97 genes in at least one genotype at one time point. k-means clustering grouped the genes into clusters of similar observations for each genotype, and comparisons between A. rabiei-resistant and A. rabiei-susceptible genotypes revealed potential gene 'signatures' predictive of effective A. rabiei resistance. These genes included several pathogenesis-related proteins, SNAKIN2 antimicrobial peptide, proline-rich protein, disease resistance response protein DRRG49-C, environmental stress-inducible protein, leucine-zipper protein, polymorphic antigen membrane protein, Ca-binding protein and several unknown proteins. The potential involvement of these genes and their pathways of induction are discussed. This study represents the first large-scale gene expression profiling in chickpea, and future work will focus on the functional validation of the genes of interest.

Comparative transcriptome analysis reveals different molecular mechanisms of Bacillus coagulans 2-6 response to sodium lactate and calcium lactate during lactic acid production.

PubMed

Qin, Jiayang; Wang, Xiuwen; Wang, Landong; Zhu, Beibei; Zhang, Xiaohua; Yao, Qingshou; Xu, Ping

2015-01-01

Lactate production is enhanced by adding calcium carbonate or sodium hydroxide during fermentation. However, Bacillus coagulans 2-6 can produce more than 180 g/L L-lactic acid when calcium lactate is accumulated, but less than 120 g/L L-lactic acid when sodium lactate is formed. The molecular mechanisms by which B. coagulans responds to calcium lactate and sodium lactate remain unclear. In this study, comparative transcriptomic methods based on high-throughput RNA sequencing were applied to study gene expression changes in B. coagulans 2-6 cultured in non-stress, sodium lactate stress and calcium lactate stress conditions. Gene expression profiling identified 712 and 1213 significantly regulated genes in response to calcium lactate stress and sodium lactate stress, respectively. Gene ontology assignments of the differentially expressed genes were performed. KEGG pathway enrichment analysis revealed that 'ATP-binding cassette transporters' were significantly affected by calcium lactate stress, and 'amino sugar and nucleotide sugar metabolism' was significantly affected by sodium lactate stress. It was also found that lactate fermentation was less affected by calcium lactate stress than by sodium lactate stress. Sodium lactate stress had negative effect on the expression of 'glycolysis/gluconeogenesis' genes but positive effect on the expression of 'citrate cycle (TCA cycle)' genes. However, calcium lactate stress had positive influence on the expression of 'glycolysis/gluconeogenesis' genes and had minor influence on 'citrate cycle (TCA cycle)' genes. Thus, our findings offer new insights into the responses of B. coagulans to different lactate stresses. Notably, our RNA-seq dataset constitute a robust database for investigating the functions of genes induced by lactate stress in the future and identify potential targets for genetic engineering to further improve L-lactic acid production by B. coagulans.

Modularity and evolutionary constraints in a baculovirus gene regulatory network

PubMed Central

2013-01-01

Background The structure of regulatory networks remains an open question in our understanding of complex biological systems. Interactions during complete viral life cycles present unique opportunities to understand how host-parasite network take shape and behave. The Anticarsia gemmatalis multiple nucleopolyhedrovirus (AgMNPV) is a large double-stranded DNA virus, whose genome may encode for 152 open reading frames (ORFs). Here we present the analysis of the ordered cascade of the AgMNPV gene expression. Results We observed an earlier onset of the expression than previously reported for other baculoviruses, especially for genes involved in DNA replication. Most ORFs were expressed at higher levels in a more permissive host cell line. Genes with more than one copy in the genome had distinct expression profiles, which could indicate the acquisition of new functionalities. The transcription gene regulatory network (GRN) for 149 ORFs had a modular topology comprising five communities of highly interconnected nodes that separated key genes that are functionally related on different communities, possibly maximizing redundancy and GRN robustness by compartmentalization of important functions. Core conserved functions showed expression synchronicity, distinct GRN features and significantly less genetic diversity, consistent with evolutionary constraints imposed in key elements of biological systems. This reduced genetic diversity also had a positive correlation with the importance of the gene in our estimated GRN, supporting a relationship between phylogenetic data of baculovirus genes and network features inferred from expression data. We also observed that gene arrangement in overlapping transcripts was conserved among related baculoviruses, suggesting a principle of genome organization. Conclusions Albeit with a reduced number of nodes (149), the AgMNPV GRN had a topology and key characteristics similar to those observed in complex cellular organisms, which indicates that modularity may be a general feature of biological gene regulatory networks. PMID:24006890

Time course of gene expression during mouse skeletal muscle hypertrophy

PubMed Central

Lee, Jonah D.; England, Jonathan H.; Esser, Karyn A.; McCarthy, John J.

2013-01-01

The purpose of this study was to perform a comprehensive transcriptome analysis during skeletal muscle hypertrophy to identify signaling pathways that are operative throughout the hypertrophic response. Global gene expression patterns were determined from microarray results on days 1, 3, 5, 7, 10, and 14 during plantaris muscle hypertrophy induced by synergist ablation in adult mice. Principal component analysis and the number of differentially expressed genes (cutoffs ≥2-fold increase or ≥50% decrease compared with control muscle) revealed three gene expression patterns during overload-induced hypertrophy: early (1 day), intermediate (3, 5, and 7 days), and late (10 and 14 days) patterns. Based on the robust changes in total RNA content and in the number of differentially expressed genes, we focused our attention on the intermediate gene expression pattern. Ingenuity Pathway Analysis revealed a downregulation of genes encoding components of the branched-chain amino acid degradation pathway during hypertrophy. Among these genes, five were predicted by Ingenuity Pathway Analysis or previously shown to be regulated by the transcription factor Kruppel-like factor-15, which was also downregulated during hypertrophy. Moreover, the integrin-linked kinase signaling pathway was activated during hypertrophy, and the downregulation of muscle-specific micro-RNA-1 correlated with the upregulation of five predicted targets associated with the integrin-linked kinase pathway. In conclusion, we identified two novel pathways that may be involved in muscle hypertrophy, as well as two upstream regulators (Kruppel-like factor-15 and micro-RNA-1) that provide targets for future studies investigating the importance of these pathways in muscle hypertrophy. PMID:23869057

Time course of gene expression during mouse skeletal muscle hypertrophy.

PubMed

Chaillou, Thomas; Lee, Jonah D; England, Jonathan H; Esser, Karyn A; McCarthy, John J

2013-10-01

The purpose of this study was to perform a comprehensive transcriptome analysis during skeletal muscle hypertrophy to identify signaling pathways that are operative throughout the hypertrophic response. Global gene expression patterns were determined from microarray results on days 1, 3, 5, 7, 10, and 14 during plantaris muscle hypertrophy induced by synergist ablation in adult mice. Principal component analysis and the number of differentially expressed genes (cutoffs ≥2-fold increase or ≥50% decrease compared with control muscle) revealed three gene expression patterns during overload-induced hypertrophy: early (1 day), intermediate (3, 5, and 7 days), and late (10 and 14 days) patterns. Based on the robust changes in total RNA content and in the number of differentially expressed genes, we focused our attention on the intermediate gene expression pattern. Ingenuity Pathway Analysis revealed a downregulation of genes encoding components of the branched-chain amino acid degradation pathway during hypertrophy. Among these genes, five were predicted by Ingenuity Pathway Analysis or previously shown to be regulated by the transcription factor Kruppel-like factor-15, which was also downregulated during hypertrophy. Moreover, the integrin-linked kinase signaling pathway was activated during hypertrophy, and the downregulation of muscle-specific micro-RNA-1 correlated with the upregulation of five predicted targets associated with the integrin-linked kinase pathway. In conclusion, we identified two novel pathways that may be involved in muscle hypertrophy, as well as two upstream regulators (Kruppel-like factor-15 and micro-RNA-1) that provide targets for future studies investigating the importance of these pathways in muscle hypertrophy.

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

PubMed

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

2017-11-02

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

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

PubMed Central

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

2017-01-01

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

Preparation of rAAV9 to Overexpress or Knockdown Genes in Mouse Hearts

PubMed Central

Ding, Jian; Lin, Zhi-Qiang; Jiang, Jian-Ming; Seidman, Christine E.; Seidman, Jonathan G.; Pu, William T.; Wang, Da-Zhi

2016-01-01

Controlling the expression or activity of specific genes through the myocardial delivery of genetic materials in murine models permits the investigation of gene functions. Their therapeutic potential in the heart can also be determined. There are limited approaches for in vivo molecular intervention in the mouse heart. Recombinant adeno-associated virus (rAAV)-based genome engineering has been utilized as an essential tool for in vivo cardiac gene manipulation. The specific advantages of this technology include high efficiency, high specificity, low genomic integration rate, minimalimmunogenicity, and minimal pathogenicity. Here, a detailed procedure to construct, package, and purify the rAAV9 vectors is described. Subcutaneous injection of rAAV9 into neonatal pups results in robust expression or efficient knockdown of the gene(s) of interest in the mouse heart, but not in the liver and other tissues. Using the cardiac-specific TnnT2 promoter, high expression of GFP gene in the heart was obtained. Additionally, target mRNA was inhibited in the heart when a rAAV9-U6-shRNA was utilized. Working knowledge of rAAV9 technology may be useful for cardiovascular investigations. PMID:28060283

Preparation of rAAV9 to Overexpress or Knockdown Genes in Mouse Hearts.

PubMed

Ding, Jian; Lin, Zhi-Qiang; Jiang, Jian-Ming; Seidman, Christine E; Seidman, Jonathan G; Pu, William T; Wang, Da-Zhi

2016-12-17

Controlling the expression or activity of specific genes through the myocardial delivery of genetic materials in murine models permits the investigation of gene functions. Their therapeutic potential in the heart can also be determined. There are limited approaches for in vivo molecular intervention in the mouse heart. Recombinant adeno-associated virus (rAAV)-based genome engineering has been utilized as an essential tool for in vivo cardiac gene manipulation. The specific advantages of this technology include high efficiency, high specificity, low genomic integration rate, minimal immunogenicity, and minimal pathogenicity. Here, a detailed procedure to construct, package, and purify the rAAV9 vectors is described. Subcutaneous injection of rAAV9 into neonatal pups results in robust expression or efficient knockdown of the gene(s) of interest in the mouse heart, but not in the liver and other tissues. Using the cardiac-specific TnnT2 promoter, high expression of GFP gene in the heart was obtained. Additionally, target mRNA was inhibited in the heart when a rAAV9-U6-shRNA was utilized. Working knowledge of rAAV9 technology may be useful for cardiovascular investigations.

Robust Lentiviral Gene Delivery But Limited Transduction Capacity of Commonly Used Adeno-Associated Viral Serotypes in Xenotransplanted Human Skin.

PubMed

Jakobsen, Maria; Askou, Anne Louise; Stenderup, Karin; Rosada, Cecilia; Dagnæs-Hansen, Frederik; Jensen, Thomas G; Corydon, Thomas J; Mikkelsen, Jacob Giehm; Aagaard, Lars

2015-08-01

Skin is an easily accessible organ, and therapeutic gene transfer to skin remains an attractive alternative for the treatment of skin diseases. Although we have previously documented potent lentiviral gene delivery to human skin, vectors based on adeno-associated virus (AAV) rank among the most promising gene delivery tools for in vivo purposes. Thus, we compared the potential usefulness of various serotypes of recombinant AAV vectors and lentiviral vectors for gene transfer to human skin in a xenotransplanted mouse model. Vector constructs encoding firefly luciferase were packaged in AAV capsids of serotype 1, 2, 5, 6, 8, and 9 and separately administered by intradermal injection in human skin transplants. For all serotypes, live bioimaging demonstrated low levels of transgene expression in the human skin graft, and firefly luciferase expression was observed primarily in neighboring tissue outside of the graft. In contrast, gene delivery by intradermally injected lentiviral vectors was efficient and led to extensive and persistent firefly luciferase expression within the human skin graft only. The study demonstrates the limited capacity of single-stranded AAV vectors of six commonly used serotypes for gene delivery to human skin in vivo.

Robust Lentiviral Gene Delivery But Limited Transduction Capacity of Commonly Used Adeno-Associated Viral Serotypes in Xenotransplanted Human Skin

PubMed Central

Jakobsen, Maria; Askou, Anne Louise; Stenderup, Karin; Rosada, Cecilia; Dagnæs-Hansen, Frederik; Jensen, Thomas G.; Corydon, Thomas J.; Mikkelsen, Jacob Giehm; Aagaard, Lars

2015-01-01

Skin is an easily accessible organ, and therapeutic gene transfer to skin remains an attractive alternative for the treatment of skin diseases. Although we have previously documented potent lentiviral gene delivery to human skin, vectors based on adeno-associated virus (AAV) rank among the most promising gene delivery tools for in vivo purposes. Thus, we compared the potential usefulness of various serotypes of recombinant AAV vectors and lentiviral vectors for gene transfer to human skin in a xenotransplanted mouse model. Vector constructs encoding firefly luciferase were packaged in AAV capsids of serotype 1, 2, 5, 6, 8, and 9 and separately administered by intradermal injection in human skin transplants. For all serotypes, live bioimaging demonstrated low levels of transgene expression in the human skin graft, and firefly luciferase expression was observed primarily in neighboring tissue outside of the graft. In contrast, gene delivery by intradermally injected lentiviral vectors was efficient and led to extensive and persistent firefly luciferase expression within the human skin graft only. The study demonstrates the limited capacity of single-stranded AAV vectors of six commonly used serotypes for gene delivery to human skin in vivo. PMID:26204415

Biomarkers of the Hedgehog/Smoothened pathway in healthy volunteers

PubMed Central

Kadam, Sunil K; Patel, Bharvin K R; Jones, Emma; Nguyen, Tuan S; Verma, Lalit K; Landschulz, Katherine T; Stepaniants, Sergey; Li, Bin; Brandt, John T; Brail, Leslie H

2012-01-01

The Hedgehog (Hh) pathway is involved in oncogenic transformation and tumor maintenance. The primary objective of this study was to select surrogate tissue to measure messenger ribonucleic acid (mRNA) levels of Hh pathway genes for measurement of pharmacodynamic effect. Expression of Hh pathway specific genes was measured by quantitative real time polymerase chain reaction (qRT-PCR) and global gene expression using Affymetrix U133 microarrays. Correlations were made between the expression of specific genes determined by qRT-PCR and normalized microarray data. Gene ontology analysis using microarray data for a broader set of Hh pathway genes was performed to identify additional Hh pathway-related markers in the surrogate tissue. RNA extracted from blood, hair follicle, and skin obtained from healthy subjects was analyzed by qRT-PCR for 31 genes, whereas 8 samples were analyzed for a 7-gene subset. Twelve sample sets, each with ≤500 ng total RNA derived from hair, skin, and blood, were analyzed using Affymetrix U133 microarrays. Transcripts for several Hh pathway genes were undetectable in blood using qRT-PCR. Skin was the most desirable matrix, followed by hair follicle. Whether processed by robust multiarray average or microarray suite 5 (MAS5), expression patterns of individual samples showed co-clustered signals; both normalization methods were equally effective for unsupervised analysis. The MAS5- normalized probe sets appeared better suited for supervised analysis. This work provides the basis for selection of a surrogate tissue and an expression analysis-based approach to evaluate pathway-related genes as markers of pharmacodynamic effect with novel inhibitors of the Hh pathway. PMID:22611475

Putative pathway of sex pheromone biosynthesis and degradation by expression patterns of genes identified from female pheromone gland and adult antenna of Sesamia inferens (Walker).

PubMed

Zhang, Ya-Nan; Xia, Yi-Han; Zhu, Jia-Yao; Li, Sheng-Yun; Dong, Shuang-Lin

2014-05-01

The general pathway of biosynthesis and degradation for Type-I sex pheromones in moths is well established, but some genes involved in this pathway remain to be characterized. The purple stem borer, Sesamia inferens, employs a pheromone blend containing components with three different terminal functional groups (Z11-16:OAc, Z11-16:OH, and Z11-16:Ald) of Type-I sex pheromones. Thus, it provides a good model to study the diversity of genes involved in pheromone biosynthesis and degradation pathways. By analyzing previously obtained transcriptomic data of the sex pheromone glands and antennae, we identified 73 novel genes that are possibly related to pheromone biosynthesis (46 genes) or degradation (27 genes). Gene expression patterns and phylogenetic analysis revealed that one desaturase (SinfDes4), one fatty acid reductase (SinfFAR2), and one fatty acid xtransport protein (SinfFATP1) genes were predominantly expressed in pheromone glands, and clustered with genes involved in pheromone synthesis in other moth species. Ten genes including five carboxylesterases (SinfCXE10, 13, 14, 18, and 20), three aldehyde oxidases (SinfAOX1, 2 and 3), and two alcohol dehydrogenases (SinfAD1 and 3) were expressed specifically or predominantly in antennae, and could be candidate genes involved in pheromone degradation. SinfAD1 and 3 are the first reported alcohol dehydrogenase genes with antennae-biased expression. Based on these results we propose a pathway involving these potential enzyme-encoding gene candidates in sex pheromone biosynthesis and degradation in S. inferens. This study provides robust background information for further elucidation of the genetic basis of sex pheromone biosynthesis and degradation, and ultimately provides potential targets to disrupt sexual communication in S. inferens for control purposes.

Rough set soft computing cancer classification and network: one stone, two birds.

PubMed

Zhang, Yue

2010-07-15

Gene expression profiling provides tremendous information to help unravel the complexity of cancer. The selection of the most informative genes from huge noise for cancer classification has taken centre stage, along with predicting the function of such identified genes and the construction of direct gene regulatory networks at different system levels with a tuneable parameter. A new study by Wang and Gotoh described a novel Variable Precision Rough Sets-rooted robust soft computing method to successfully address these problems and has yielded some new insights. The significance of this progress and its perspectives will be discussed in this article.

Complete TCRα gene locus control region activity in T cells derived in vitro from embryonic stem cells

PubMed Central

Lahiji, Armin; Kučerová-Levisohn, Martina; Lovett, Jordana; Holmes, Roxanne; Zúñiga-Pflücker, Juan Carlos; Ortiz, Benjamin D.

2013-01-01

Locus Control Regions (LCR) are cis-acting gene regulatory elements with the unique, integration site-independent ability to transfer the characteristics of their locus-of-origin’s gene expression pattern to a linked transgene in mice. LCR activities have been discovered in numerous T cell lineage expressed gene loci. These elements can be adapted to the design of stem cell gene therapy vectors that direct robust therapeutic gene expression to the T cell progeny of engineered stem cells. Currently, transgenic mice provide the only experimental approach that wholly supports all the critical aspects of LCR activity. Herein we report manifestation of all key features of mouse T cell receptor (TCR)-α gene LCR function in T cells derived in vitro from mouse embryonic stem cells (ESC). High level, copy number-related TCRα LCR-linked reporter gene expression levels are cell type-restricted in this system, and upregulated during the expected stage transition of T cell development. We further report that de novo introduction of TCRα LCR linked transgenes into existing T cell lines yields incomplete LCR activity. Together, these data indicate that establishing full TCRα LCR activity requires critical molecular events occurring prior to final T-lineage determination. This study additionally validates a novel, tractable and more rapid approach for the study of LCR activity in T cells, and its translation to therapeutic genetic engineering. PMID:23720809

Expression of short hairpin RNAs using the compact architecture of retroviral microRNA genes.

PubMed

Burke, James M; Kincaid, Rodney P; Aloisio, Francesca; Welch, Nicole; Sullivan, Christopher S

2017-09-29

Short hairpin RNAs (shRNAs) are effective in generating stable repression of gene expression. RNA polymerase III (RNAP III) type III promoters (U6 or H1) are typically used to drive shRNA expression. While useful for some knockdown applications, the robust expression of U6/H1-driven shRNAs can induce toxicity and generate heterogeneous small RNAs with undesirable off-target effects. Additionally, typical U6/H1 promoters encompass the majority of the ∼270 base pairs (bp) of vector space required for shRNA expression. This can limit the efficacy and/or number of delivery vector options, particularly when delivery of multiple gene/shRNA combinations is required. Here, we develop a compact shRNA (cshRNA) expression system based on retroviral microRNA (miRNA) gene architecture that uses RNAP III type II promoters. We demonstrate that cshRNAs coded from as little as 100 bps of total coding space can precisely generate small interfering RNAs (siRNAs) that are active in the RNA-induced silencing complex (RISC). We provide an algorithm with a user-friendly interface to design cshRNAs for desired target genes. This cshRNA expression system reduces the coding space required for shRNA expression by >2-fold as compared to the typical U6/H1 promoters, which may facilitate therapeutic RNAi applications where delivery vector space is limiting. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Gene set analysis approaches for RNA-seq data: performance evaluation and application guideline

PubMed Central

Rahmatallah, Yasir; Emmert-Streib, Frank

2016-01-01

Transcriptome sequencing (RNA-seq) is gradually replacing microarrays for high-throughput studies of gene expression. The main challenge of analyzing microarray data is not in finding differentially expressed genes, but in gaining insights into the biological processes underlying phenotypic differences. To interpret experimental results from microarrays, gene set analysis (GSA) has become the method of choice, in particular because it incorporates pre-existing biological knowledge (in a form of functionally related gene sets) into the analysis. Here we provide a brief review of several statistically different GSA approaches (competitive and self-contained) that can be adapted from microarrays practice as well as those specifically designed for RNA-seq. We evaluate their performance (in terms of Type I error rate, power, robustness to the sample size and heterogeneity, as well as the sensitivity to different types of selection biases) on simulated and real RNA-seq data. Not surprisingly, the performance of various GSA approaches depends only on the statistical hypothesis they test and does not depend on whether the test was developed for microarrays or RNA-seq data. Interestingly, we found that competitive methods have lower power as well as robustness to the samples heterogeneity than self-contained methods, leading to poor results reproducibility. We also found that the power of unsupervised competitive methods depends on the balance between up- and down-regulated genes in tested gene sets. These properties of competitive methods have been overlooked before. Our evaluation provides a concise guideline for selecting GSA approaches, best performing under particular experimental settings in the context of RNA-seq. PMID:26342128

Gene expression deficits in pontine locus coeruleus astrocytes in men with major depressive disorder.

PubMed

Chandley, Michelle J; Szebeni, Katalin; Szebeni, Attila; Crawford, Jessica; Stockmeier, Craig A; Turecki, Gustavo; Miguel-Hidalgo, Jose Javier; Ordway, Gregory A

2013-07-01

Norepinephrine and glutamate are among several neurotransmitters implicated in the neuropathology of major depressive disorder (MDD). Glia deficits have also been demonstrated in people with MDD, and glia are critical modulators of central glutamatergic transmission. We studied glia in men with MDD in the region of the brain (locus coeruleus; LC) where noradrenergic neuronal cell bodies reside and receive glutamatergic input. The expression of 3 glutamate-related genes (SLC1A3, SLC1A2, GLUL) concentrated in glia and a glia gene (GFAP) were measured in postmortem tissues from men with MDD and from paired psychiatrically healthy controls. Initial gene expression analysis of RNA isolated from homogenized tissue (n = 9-10 pairs) containing the LC were followed by detailed analysis of gene expressions in astrocytes and oligodendrocytes (n = 6-7 pairs) laser captured from the LC region. We assessed protein changes in GFAP using immunohistochemistry and immunoblotting (n = 7-14 pairs). Astrocytes, but not oligodendrocytes, demonstrated robust reductions in the expression of SLC1A3 and SLC1A2, whereas GLUL expression was unchanged. GFAP expression was lower in astrocytes, and we confirmed reduced GFAP protein in the LC using immunostaining methods. Reduced expression of protein products of SLC1A3 and SLC1A2 could not be confirmed because of insufficient amounts of LC tissue for these assays. Whether gene expression abnormalities were associated with only MDD and not with suicide could not be confirmed because most of the decedents who had MDD died by suicide. Major depressive disorder is associated with unhealthy astrocytes in the noradrenergic LC, characterized here by a reduction in astrocyte glutamate transporter expression. These findings suggest that increased glutamatergic activity in the LC occurs in men with MDD.

Novel application of multi-stimuli network inference to synovial fibroblasts of rheumatoid arthritis patients

PubMed Central

2014-01-01

Background Network inference of gene expression data is an important challenge in systems biology. Novel algorithms may provide more detailed gene regulatory networks (GRN) for complex, chronic inflammatory diseases such as rheumatoid arthritis (RA), in which activated synovial fibroblasts (SFBs) play a major role. Since the detailed mechanisms underlying this activation are still unclear, simultaneous investigation of multi-stimuli activation of SFBs offers the possibility to elucidate the regulatory effects of multiple mediators and to gain new insights into disease pathogenesis. Methods A GRN was therefore inferred from RA-SFBs treated with 4 different stimuli (IL-1 β, TNF- α, TGF- β, and PDGF-D). Data from time series microarray experiments (0, 1, 2, 4, 12 h; Affymetrix HG-U133 Plus 2.0) were batch-corrected applying ‘ComBat’, analyzed for differentially expressed genes over time with ‘Limma’, and used for the inference of a robust GRN with NetGenerator V2.0, a heuristic ordinary differential equation-based method with soft integration of prior knowledge. Results Using all genes differentially expressed over time in RA-SFBs for any stimulus, and selecting the genes belonging to the most significant gene ontology (GO) term, i.e., ‘cartilage development’, a dynamic, robust, moderately complex multi-stimuli GRN was generated with 24 genes and 57 edges in total, 31 of which were gene-to-gene edges. Prior literature-based knowledge derived from Pathway Studio or manual searches was reflected in the final network by 25/57 confirmed edges (44%). The model contained known network motifs crucial for dynamic cellular behavior, e.g., cross-talk among pathways, positive feed-back loops, and positive feed-forward motifs (including suppression of the transcriptional repressor OSR2 by all 4 stimuli. Conclusion A multi-stimuli GRN highly concordant with literature data was successfully generated by network inference from the gene expression of stimulated RA-SFBs. The GRN showed high reliability, since 10 predicted edges were independently validated by literature findings post network inference. The selected GO term ‘cartilage development’ contained a number of differentiation markers, growth factors, and transcription factors with potential relevance for RA. Finally, the model provided new insight into the response of RA-SFBs to multiple stimuli implicated in the pathogenesis of RA, in particular to the ‘novel’ potent growth factor PDGF-D. PMID:24989895

Differential responsiveness of Holstein and Angus dermal fibroblasts to LPS challenge occurs without major differences in the methylome.

PubMed

Benjamin, Aimee L; Green, Benjamin B; Crooker, Brian A; McKay, Stephanie D; Kerr, David E

2016-03-24

We have previously found substantial animal-to-animal and age-dependent variation in the response of Holstein fibroblast cultures challenged with LPS. To expand on this finding, fibroblast cultures were established from dairy (Holstein) and beef (Angus) cattle and challenged with LPS to examine breed-dependent differences in the innate immune response. Global gene expression was measured by RNA-Seq, while an epigenetic basis for expression differences was examined by methylated CpG island recovery assay sequencing (MIRA-Seq) analysis. The Holstein breed displayed a more robust response to LPS than the Angus breed based on RNA-Seq analysis of cultures challenged with LPS for 0, 2, and 8 h. Several immune-associated genes were expressed at greater levels (FDR < 0.05) in Holstein cultures including TLR4 at all time points and a number of pro-inflammatory genes such as IL8, CCL20, CCL5, and TNF following LPS exposure. Despite extensive breed differences in the transcriptome, MIRA-Seq unveiled relatively similar patterns of genome-wide DNA methylation between breeds, with an overall hypomethylation of gene promoters. However, by examining the genome in 3Kb windows, 49 regions of differential methylation were discovered between Holstein and Angus fibroblasts, and two of these regions fell within the promoter region (-2500 to +500 bp of the transcription start site) of the genes NTRK2 and ADAMTS5. Fibroblasts isolated from Holstein cattle display a more robust response to LPS in comparison to cultures from Angus cattle. Different selection strategies and management practices exist between these two breeds that likely give rise to genetic and epigenetic factors contributing to the different immune response phenotypes.

Gene Ranking of RNA-Seq Data via Discriminant Non-Negative Matrix Factorization.

PubMed

Jia, Zhilong; Zhang, Xiang; Guan, Naiyang; Bo, Xiaochen; Barnes, Michael R; Luo, Zhigang

2015-01-01

RNA-sequencing is rapidly becoming the method of choice for studying the full complexity of transcriptomes, however with increasing dimensionality, accurate gene ranking is becoming increasingly challenging. This paper proposes an accurate and sensitive gene ranking method that implements discriminant non-negative matrix factorization (DNMF) for RNA-seq data. To the best of our knowledge, this is the first work to explore the utility of DNMF for gene ranking. When incorporating Fisher's discriminant criteria and setting the reduced dimension as two, DNMF learns two factors to approximate the original gene expression data, abstracting the up-regulated or down-regulated metagene by using the sample label information. The first factor denotes all the genes' weights of two metagenes as the additive combination of all genes, while the second learned factor represents the expression values of two metagenes. In the gene ranking stage, all the genes are ranked as a descending sequence according to the differential values of the metagene weights. Leveraging the nature of NMF and Fisher's criterion, DNMF can robustly boost the gene ranking performance. The Area Under the Curve analysis of differential expression analysis on two benchmarking tests of four RNA-seq data sets with similar phenotypes showed that our proposed DNMF-based gene ranking method outperforms other widely used methods. Moreover, the Gene Set Enrichment Analysis also showed DNMF outweighs others. DNMF is also computationally efficient, substantially outperforming all other benchmarked methods. Consequently, we suggest DNMF is an effective method for the analysis of differential gene expression and gene ranking for RNA-seq data.

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.

Development of a gene synthesis platform for the efficient large scale production of small genes encoding animal toxins.

PubMed

Sequeira, Ana Filipa; Brás, Joana L A; Guerreiro, Catarina I P D; Vincentelli, Renaud; Fontes, Carlos M G A

2016-12-01

Gene synthesis is becoming an important tool in many fields of recombinant DNA technology, including recombinant protein production. De novo gene synthesis is quickly replacing the classical cloning and mutagenesis procedures and allows generating nucleic acids for which no template is available. In addition, when coupled with efficient gene design algorithms that optimize codon usage, it leads to high levels of recombinant protein expression. Here, we describe the development of an optimized gene synthesis platform that was applied to the large scale production of small genes encoding venom peptides. This improved gene synthesis method uses a PCR-based protocol to assemble synthetic DNA from pools of overlapping oligonucleotides and was developed to synthesise multiples genes simultaneously. This technology incorporates an accurate, automated and cost effective ligation independent cloning step to directly integrate the synthetic genes into an effective Escherichia coli expression vector. The robustness of this technology to generate large libraries of dozens to thousands of synthetic nucleic acids was demonstrated through the parallel and simultaneous synthesis of 96 genes encoding animal toxins. An automated platform was developed for the large-scale synthesis of small genes encoding eukaryotic toxins. Large scale recombinant expression of synthetic genes encoding eukaryotic toxins will allow exploring the extraordinary potency and pharmacological diversity of animal venoms, an increasingly valuable but unexplored source of lead molecules for drug discovery.

Exploration for the Salinity Tolerance-Related Genes from Xero-Halophyte Atriplex canescens Exploiting Yeast Functional Screening System

PubMed Central

Li, Jingtao; Sun, Xinhua; Liu, Yanzhi; Wang, Xueliang; Zhang, Hao; Pan, Hongyu

2017-01-01

Plant productivity is limited by salinity stress, both in natural and agricultural systems. Identification of salt stress-related genes from halophyte can provide insights into mechanisms of salt stress tolerance in plants. Atriplex canescens is a xero-halophyte that exhibits optimum growth in the presence of 400 mM NaCl. A cDNA library derived from highly salt-treated A. canescens plants was constructed based on a yeast expression system. A total of 53 transgenic yeast clones expressing enhanced salt tolerance were selected from 105 transformants. Their plasmids were sequenced and the gene characteristics were annotated using a BLASTX search. Retransformation of yeast cells with the selected plasmids conferred salt tolerance to the resulting transformants. The expression patterns of 28 of these stress-related genes were further investigated in A. canescens leaves by quantitative reverse transcription-PCR. In this study, we provided a rapid and robust assay system for large-scale screening of genes for varied abiotic stress tolerance with high efficiency in A. canescens. PMID:29149055

Towards a tolerance toolkit: Gene expression signatures enabling the emergence of resistant bacterial strains

NASA Astrophysics Data System (ADS)

Erickson, Keesha; Chatterjee, Anushree

2014-03-01

Microbial pathogens are able to rapidly acquire tolerance to chemical toxins. Developing next-generation antibiotics that impede the emergence of resistance will help avoid a world-wide health crisis. Conversely, the ability to induce rapid tolerance gains could lead to high-yielding strains for sustainable production of biofuels and commodity chemicals. Achieving these goals requires an understanding of the general mechanisms allowing microbes to become resistant to diverse toxins. We apply top-down and bottom-up methodologies to identify biological network changes leading to adaptation and tolerance. Using a top-down approach, we perform evolution experiments to isolate resistant strains, collect samples for transcriptomic and proteomic analysis, and use the omics data to inform mathematical gene regulatory models. Using a bottom-up approach, we build and test synthetic genetic devices that enable increased or decreased expression of selected genes. Unique patterns in gene expression are identified in cultures actively gaining resistance, especially in pathways known to be involved with stress response, efflux, and mutagenesis. Genes correlated with tolerance could potentially allow the design of resistance-free antibiotics or robust chemical production strains.

Adjusting for background mutation frequency biases improves the identification of cancer driver genes.

PubMed

Evans, Perry; Avey, Stefan; Kong, Yong; Krauthammer, Michael

2013-09-01

A common goal of tumor sequencing projects is finding genes whose mutations are selected for during tumor development. This is accomplished by choosing genes that have more non-synonymous mutations than expected from an estimated background mutation frequency. While this background frequency is unknown, it can be estimated using both the observed synonymous mutation frequency and the non-synonymous to synonymous mutation ratio. The synonymous mutation frequency can be determined across all genes or in a gene-specific manner. This choice introduces an interesting trade-off. A gene-specific frequency adjusts for an underlying mutation bias, but is difficult to estimate given missing synonymous mutation counts. Using a genome-wide synonymous frequency is more robust, but is less suited for adjusting biases. Studying four evaluation criteria for identifying genes with high non-synonymous mutation burden (reflecting preferential selection of expressed genes, genes with mutations in conserved bases, genes with many protein interactions, and genes that show loss of heterozygosity), we find that the gene-specific synonymous frequency is superior in the gene expression and protein interaction tests. In conclusion, the use of the gene-specific synonymous mutation frequency is well suited for assessing a gene's non-synonymous mutation burden.

snoU6 and 5S RNAs are not reliable miRNA reference genes in neuronal differentiation.

PubMed

Lim, Q E; Zhou, L; Ho, Y K; Wan, G; Too, H P

2011-12-29

Accurate profiling of microRNAs (miRNAs) is an essential step for understanding the functional significance of these small RNAs in both physiological and pathological processes. Quantitative real-time PCR (qPCR) has gained acceptance as a robust and reliable transcriptomic method to profile subtle changes in miRNA levels and requires reference genes for accurate normalization of gene expression. 5S and snoU6 RNAs are commonly used as reference genes in microRNA quantification. It is currently unknown if these small RNAs are stably expressed during neuronal differentiation. Panels of miRNAs have been suggested as alternative reference genes to 5S and snoU6 in various physiological contexts. To test the hypothesis that miRNAs may serve as stable references during neuronal differentiation, the expressions of eight miRNAs, 5S and snoU6 RNAs in five differentiating neuronal cell types were analyzed using qPCR. The stabilities of the expressions were evaluated using two complementary statistical approaches (geNorm and Normfinder). Expressions of 5S and snoU6 RNAs were stable under some but not all conditions of neuronal differentiation and thus are not suitable reference genes. In contrast, a combination of three miRNAs (miR-103, miR-106b and miR-26b) allowed accurate expression normalization across different models of neuronal differentiation. Copyright © 2011 IBRO. Published by Elsevier Ltd. All rights reserved.

A gene expression estimator of intramuscular fat percentage for use in both cattle and sheep

PubMed Central

2014-01-01

Background The expression of genes encoding proteins involved in triacyglyceride and fatty acid synthesis and storage in cattle muscle are correlated with intramuscular fat (IMF)%. Are the same genes also correlated with IMF% in sheep muscle, and can the same set of genes be used to estimate IMF% in both species? Results The correlation between gene expression (microarray) and IMF% in the longissimus muscle (LM) of twenty sheep was calculated. An integrated analysis of this dataset with an equivalent cattle correlation dataset and a cattle differential expression dataset was undertaken. A total of 30 genes were identified to be strongly correlated with IMF% in both cattle and sheep. The overlap of genes was highly significant, 8 of the 13 genes in the TAG gene set and 8 of the 13 genes in the FA gene set were in the top 100 and 500 genes respectively most correlated with IMF% in sheep, P-value = 0. Of the 30 genes, CIDEA, THRSP, ACSM1, DGAT2 and FABP4 had the highest average rank in both species. Using the data from two small groups of Brahman cattle (control and Hormone growth promotant-treated [known to decrease IMF% in muscle]) and 22 animals in total, the utility of a direct measure and different estimators of IMF% (ultrasound and gene expression) to differentiate between the two groups were examined. Directly measured IMF% and IMF% estimated from ultrasound scanning could not discriminate between the two groups. However, using gene expression to estimate IMF% discriminated between the two groups. Increasing the number of genes used to estimate IMF% from one to five significantly increased the discrimination power; but increasing the number of genes to 15 resulted in little further improvement. Conclusion We have demonstrated the utility of a comparative approach to identify robust estimators of IMF% in the LM in cattle and sheep. We have also demonstrated a number of approaches (potentially applicable to much smaller groups of animals than conventional methods) to using gene expression to rank animals for IMF% within a single farm/treatment, or to estimate differences in IMF% between two farms/treatments. PMID:25028604

Partially Redundant Enhancers Cooperatively Maintain Mammalian Pomc Expression Above a Critical Functional Threshold

PubMed Central

Lam, Daniel D.; de Souza, Flavio S. J.; Nasif, Sofia; Yamashita, Miho; López-Leal, Rodrigo; Meece, Kana; Sampath, Harini; Mercer, Aaron J.; Wardlaw, Sharon L.

2015-01-01

Cell-specific expression of many genes is conveyed by multiple enhancers, with each individual enhancer controlling a particular expression domain. In contrast, multiple enhancers drive similar expression patterns of some genes involved in embryonic development, suggesting regulatory redundancy. Work in Drosophila has indicated that functionally overlapping enhancers canalize development by buffering gene expression against environmental and genetic disturbances. However, little is known about regulatory redundancy in vertebrates and in genes mainly expressed during adulthood. Here we study nPE1 and nPE2, two phylogenetically conserved mammalian enhancers that drive expression of the proopiomelanocortin gene (Pomc) to the same set of hypothalamic neurons. The simultaneous deletion of both enhancers abolished Pomc expression at all ages and induced a profound metabolic dysfunction including early-onset extreme obesity. Targeted inactivation of either nPE1 or nPE2 led to very low levels of Pomc expression during early embryonic development indicating that both enhancers function synergistically. In adult mice, however, Pomc expression is controlled additively by both enhancers, with nPE1 being responsible for ∼80% and nPE2 for ∼20% of Pomc transcription. Consequently, nPE1 knockout mice exhibit mild obesity whereas nPE2-deficient mice maintain a normal body weight. These results suggest that nPE2-driven Pomc expression is compensated by nPE1 at later stages of development, essentially rescuing the earlier phenotype of nPE2 deficiency. Together, these results reveal that cooperative interactions between the enhancers confer robustness of Pomc expression against gene regulatory disturbances and preclude deleterious metabolic phenotypes caused by Pomc deficiency in adulthood. Thus, our study demonstrates that enhancer redundancy can be used by genes that control adult physiology in mammals and underlines the potential significance of regulatory sequence mutations in common diseases. PMID:25671638

Analysis of blood-based gene expression in idiopathic Parkinson disease.

PubMed

Shamir, Ron; Klein, Christine; Amar, David; Vollstedt, Eva-Juliane; Bonin, Michael; Usenovic, Marija; Wong, Yvette C; Maver, Ales; Poths, Sven; Safer, Hershel; Corvol, Jean-Christophe; Lesage, Suzanne; Lavi, Ofer; Deuschl, Günther; Kuhlenbaeumer, Gregor; Pawlack, Heike; Ulitsky, Igor; Kasten, Meike; Riess, Olaf; Brice, Alexis; Peterlin, Borut; Krainc, Dimitri

2017-10-17

To examine whether gene expression analysis of a large-scale Parkinson disease (PD) patient cohort produces a robust blood-based PD gene signature compared to previous studies that have used relatively small cohorts (≤220 samples). Whole-blood gene expression profiles were collected from a total of 523 individuals. After preprocessing, the data contained 486 gene profiles (n = 205 PD, n = 233 controls, n = 48 other neurodegenerative diseases) that were partitioned into training, validation, and independent test cohorts to identify and validate a gene signature. Batch-effect reduction and cross-validation were performed to ensure signature reliability. Finally, functional and pathway enrichment analyses were applied to the signature to identify PD-associated gene networks. A gene signature of 100 probes that mapped to 87 genes, corresponding to 64 upregulated and 23 downregulated genes differentiating between patients with idiopathic PD and controls, was identified with the training cohort and successfully replicated in both an independent validation cohort (area under the curve [AUC] = 0.79, p = 7.13E-6) and a subsequent independent test cohort (AUC = 0.74, p = 4.2E-4). Network analysis of the signature revealed gene enrichment in pathways, including metabolism, oxidation, and ubiquitination/proteasomal activity, and misregulation of mitochondria-localized genes, including downregulation of COX4I1 , ATP5A1 , and VDAC3 . We present a large-scale study of PD gene expression profiling. This work identifies a reliable blood-based PD signature and highlights the importance of large-scale patient cohorts in developing potential PD biomarkers. © 2017 American Academy of Neurology.

Tissue Gene Expression Analysis Using Arrayed Normalized cDNA Libraries

PubMed Central

Eickhoff, Holger; Schuchhardt, Johannes; Ivanov, Igor; Meier-Ewert, Sebastian; O'Brien, John; Malik, Arif; Tandon, Neeraj; Wolski, Eryk-Witold; Rohlfs, Elke; Nyarsik, Lajos; Reinhardt, Richard; Nietfeld, Wilfried; Lehrach, Hans

2000-01-01

We have used oligonucleotide-fingerprinting data on 60,000 cDNA clones from two different mouse embryonic stages to establish a normalized cDNA clone set. The normalized set of 5,376 clones represents different clusters and therefore, in almost all cases, different genes. The inserts of the cDNA clones were amplified by PCR and spotted on glass slides. The resulting arrays were hybridized with mRNA probes prepared from six different adult mouse tissues. Expression profiles were analyzed by hierarchical clustering techniques. We have chosen radioactive detection because it combines robustness with sensitivity and allows the comparison of multiple normalized experiments. Sensitive detection combined with highly effective clustering algorithms allowed the identification of tissue-specific expression profiles and the detection of genes specifically expressed in the tissues investigated. The obtained results are publicly available (http://www.rzpd.de) and can be used by other researchers as a digital expression reference. [The sequence data described in this paper have been submitted to the EMBL data library under accession nos. AL360374–AL36537.] PMID:10958641

A high-resolution transcriptome map of cell cycle reveals novel connections between periodic genes and cancer

PubMed Central

Dominguez, Daniel; Tsai, Yi-Hsuan; Gomez, Nicholas; Jha, Deepak Kumar; Davis, Ian; Wang, Zefeng

2016-01-01

Progression through the cell cycle is largely dependent on waves of periodic gene expression, and the regulatory networks for these transcriptome dynamics have emerged as critical points of vulnerability in various aspects of tumor biology. Through RNA-sequencing of human cells during two continuous cell cycles (>2.3 billion paired reads), we identified over 1 000 mRNAs, non-coding RNAs and pseudogenes with periodic expression. Periodic transcripts are enriched in functions related to DNA metabolism, mitosis, and DNA damage response, indicating these genes likely represent putative cell cycle regulators. Using our set of periodic genes, we developed a new approach termed “mitotic trait” that can classify primary tumors and normal tissues by their transcriptome similarity to different cell cycle stages. By analyzing >4 000 tumor samples in The Cancer Genome Atlas (TCGA) and other expression data sets, we found that mitotic trait significantly correlates with genetic alterations, tumor subtype and, notably, patient survival. We further defined a core set of 67 genes with robust periodic expression in multiple cell types. Proteins encoded by these genes function as major hubs of protein-protein interaction and are mostly required for cell cycle progression. The core genes also have unique chromatin features including increased levels of CTCF/RAD21 binding and H3K36me3. Loss of these features in uterine and kidney cancers is associated with altered expression of the core 67 genes. Our study suggests new chromatin-associated mechanisms for periodic gene regulation and offers a predictor of cancer patient outcomes. PMID:27364684

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

PubMed Central

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

2016-01-01

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

AUCTSP: an improved biomarker gene pair class predictor.

PubMed

Kagaris, Dimitri; Khamesipour, Alireza; Yiannoutsos, Constantin T

2018-06-26

The Top Scoring Pair (TSP) classifier, based on the concept of relative ranking reversals in the expressions of pairs of genes, has been proposed as a simple, accurate, and easily interpretable decision rule for classification and class prediction of gene expression profiles. The idea that differences in gene expression ranking are associated with presence or absence of disease is compelling and has strong biological plausibility. Nevertheless, the TSP formulation ignores significant available information which can improve classification accuracy and is vulnerable to selecting genes which do not have differential expression in the two conditions ("pivot" genes). We introduce the AUCTSP classifier as an alternative rank-based estimator of the magnitude of the ranking reversals involved in the original TSP. The proposed estimator is based on the Area Under the Receiver Operating Characteristic (ROC) Curve (AUC) and as such, takes into account the separation of the entire distribution of gene expression levels in gene pairs under the conditions considered, as opposed to comparing gene rankings within individual subjects as in the original TSP formulation. Through extensive simulations and case studies involving classification in ovarian, leukemia, colon, breast and prostate cancers and diffuse large b-cell lymphoma, we show the superiority of the proposed approach in terms of improving classification accuracy, avoiding overfitting and being less prone to selecting non-informative (pivot) genes. The proposed AUCTSP is a simple yet reliable and robust rank-based classifier for gene expression classification. While the AUCTSP works by the same principle as TSP, its ability to determine the top scoring gene pair based on the relative rankings of two marker genes across all subjects as opposed to each individual subject results in significant performance gains in classification accuracy. In addition, the proposed method tends to avoid selection of non-informative (pivot) genes as members of the top-scoring pair.

ROBUSTNESS OF SIGNALING GRADIENT IN DROSOPHILA WING IMAGINAL DISC

PubMed Central

Lei, Jinzhi; Wan, Frederic Y. M.; Lander, Arthur D.; Nie, Qing

2012-01-01

Quasi-stable gradients of signaling protein molecules (known as morphogens or ligands) bound to cell receptors are known to be responsible for differential cell signaling and gene expressions. From these follow different stable cell fates and visually patterned tissues in biological development. Recent studies have shown that the relevant basic biological processes yield gradients that are sensitive to small changes in system characteristics (such as expression level of morphogens or receptors) or environmental conditions (such as temperature changes). Additional biological activities must play an important role in the high level of robustness observed in embryonic patterning for example. It is natural to attribute observed robustness to various type of feedback control mechanisms. However, our own simulation studies have shown that feedback control is neither necessary nor sufficient for robustness of the morphogen decapentaplegic (Dpp) gradient in wing imaginal disc of Drosophilas. Furthermore, robustness can be achieved by substantial binding of the signaling morphogen Dpp with nonsignaling cell surface bound molecules (such as heparan sulfate proteoglygans) and degrading the resulting complexes at a sufficiently rapid rate. The present work provides a theoretical basis for the results of our numerical simulation studies. PMID:24098092

Signature gene expressions of cell wall integrity pathway concur with tolerance response of industrial yeast Saccharomyces cerevisiae against biomass pretreatment inhibitors

USDA-ARS?s Scientific Manuscript database

Traditional industrial ethanologenic yeast Saccharomyces cerevisiae has a robust performance under various environmental conditions and can be served as a candidate for the next-generation biocatalyst development for advanced biofuels production using lignocellulose mateials. Overcoming toxic compou...

RNA sequencing reveals sexually dimorphic gene expression before gonadal differentiation in chicken and allows comprehensive annotation of the W-chromosome

PubMed Central

2013-01-01

Background Birds have a ZZ male: ZW female sex chromosome system and while the Z-linked DMRT1 gene is necessary for testis development, the exact mechanism of sex determination in birds remains unsolved. This is partly due to the poor annotation of the W chromosome, which is speculated to carry a female determinant. Few genes have been mapped to the W and little is known of their expression. Results We used RNA-seq to produce a comprehensive profile of gene expression in chicken blastoderms and embryonic gonads prior to sexual differentiation. We found robust sexually dimorphic gene expression in both tissues pre-dating gonadogenesis, including sex-linked and autosomal genes. This supports the hypothesis that sexual differentiation at the molecular level is at least partly cell autonomous in birds. Different sets of genes were sexually dimorphic in the two tissues, indicating that molecular sexual differentiation is tissue specific. Further analyses allowed the assembly of full-length transcripts for 26 W chromosome genes, providing a view of the W transcriptome in embryonic tissues. This is the first extensive analysis of W-linked genes and their expression profiles in early avian embryos. Conclusion Sexual differentiation at the molecular level is established in chicken early in embryogenesis, before gonadal sex differentiation. We find that the W chromosome is more transcriptionally active than previously thought, expand the number of known genes to 26 and present complete coding sequences for these W genes. This includes two novel W-linked sequences and three small RNAs reassigned to the W from the Un_Random chromosome. PMID:23531366

Integrative Transcriptomic Analysis Uncovers Novel Gene Modules That Underlie the Sulfate Response in Arabidopsis thaliana

PubMed Central

Henríquez-Valencia, Carlos; Arenas-M, Anita; Medina, Joaquín; Canales, Javier

2018-01-01

Sulfur is an essential nutrient for plant growth and development. Sulfur is a constituent of proteins, the plasma membrane and cell walls, among other important cellular components. To obtain new insights into the gene regulatory networks underlying the sulfate response, we performed an integrative meta-analysis of transcriptomic data from five different sulfate experiments available in public databases. This bioinformatic approach allowed us to identify a robust set of genes whose expression depends only on sulfate availability, indicating that those genes play an important role in the sulfate response. In relation to sulfate metabolism, the biological function of approximately 45% of these genes is currently unknown. Moreover, we found several consistent Gene Ontology terms related to biological processes that have not been extensively studied in the context of the sulfate response; these processes include cell wall organization, carbohydrate metabolism, nitrogen compound transport, and the regulation of proteolysis. Gene co-expression network analyses revealed relationships between the sulfate-responsive genes that were distributed among seven function-specific co-expression modules. The most connected genes in the sulfate co-expression network belong to a module related to the carbon response, suggesting that this biological function plays an important role in the control of the sulfate response. Temporal analyses of the network suggest that sulfate starvation generates a biphasic response, which involves that major changes in gene expression occur during both the early and late responses. Network analyses predicted that the sulfate response is regulated by a limited number of transcription factors, including MYBs, bZIPs, and NF-YAs. In conclusion, our analysis identified new candidate genes and provided new hypotheses to advance our understanding of the transcriptional regulation of sulfate metabolism in plants. PMID:29692794

Integrative Transcriptomic Analysis Uncovers Novel Gene Modules That Underlie the Sulfate Response in Arabidopsis thaliana.

PubMed

Henríquez-Valencia, Carlos; Arenas-M, Anita; Medina, Joaquín; Canales, Javier

2018-01-01

Sulfur is an essential nutrient for plant growth and development. Sulfur is a constituent of proteins, the plasma membrane and cell walls, among other important cellular components. To obtain new insights into the gene regulatory networks underlying the sulfate response, we performed an integrative meta-analysis of transcriptomic data from five different sulfate experiments available in public databases. This bioinformatic approach allowed us to identify a robust set of genes whose expression depends only on sulfate availability, indicating that those genes play an important role in the sulfate response. In relation to sulfate metabolism, the biological function of approximately 45% of these genes is currently unknown. Moreover, we found several consistent Gene Ontology terms related to biological processes that have not been extensively studied in the context of the sulfate response; these processes include cell wall organization, carbohydrate metabolism, nitrogen compound transport, and the regulation of proteolysis. Gene co-expression network analyses revealed relationships between the sulfate-responsive genes that were distributed among seven function-specific co-expression modules. The most connected genes in the sulfate co-expression network belong to a module related to the carbon response, suggesting that this biological function plays an important role in the control of the sulfate response. Temporal analyses of the network suggest that sulfate starvation generates a biphasic response, which involves that major changes in gene expression occur during both the early and late responses. Network analyses predicted that the sulfate response is regulated by a limited number of transcription factors, including MYBs, bZIPs, and NF-YAs. In conclusion, our analysis identified new candidate genes and provided new hypotheses to advance our understanding of the transcriptional regulation of sulfate metabolism in plants.

Systematic genomic identification of colorectal cancer genes delineating advanced from early clinical stage and metastasis

PubMed Central

2013-01-01

Background Colorectal cancer is the third leading cause of cancer deaths in the United States. The initial assessment of colorectal cancer involves clinical staging that takes into account the extent of primary tumor invasion, determining the number of lymph nodes with metastatic cancer and the identification of metastatic sites in other organs. Advanced clinical stage indicates metastatic cancer, either in regional lymph nodes or in distant organs. While the genomic and genetic basis of colorectal cancer has been elucidated to some degree, less is known about the identity of specific cancer genes that are associated with advanced clinical stage and metastasis. Methods We compiled multiple genomic data types (mutations, copy number alterations, gene expression and methylation status) as well as clinical meta-data from The Cancer Genome Atlas (TCGA). We used an elastic-net regularized regression method on the combined genomic data to identify genetic aberrations and their associated cancer genes that are indicators of clinical stage. We ranked candidate genes by their regression coefficient and level of support from multiple assay modalities. Results A fit of the elastic-net regularized regression to 197 samples and integrated analysis of four genomic platforms identified the set of top gene predictors of advanced clinical stage, including: WRN, SYK, DDX5 and ADRA2C. These genetic features were identified robustly in bootstrap resampling analysis. Conclusions We conducted an analysis integrating multiple genomic features including mutations, copy number alterations, gene expression and methylation. This integrated approach in which one considers all of these genomic features performs better than any individual genomic assay. We identified multiple genes that robustly delineate advanced clinical stage, suggesting their possible role in colorectal cancer metastatic progression. PMID:24308539

Regulation of behaviorally associated gene networks in worker honey bee ovaries

PubMed Central

Wang, Ying; Kocher, Sarah D.; Linksvayer, Timothy A.; Grozinger, Christina M.; Page, Robert E.; Amdam, Gro V.

2012-01-01

SUMMARY Several lines of evidence support genetic links between ovary size and division of labor in worker honey bees. However, it is largely unknown how ovaries influence behavior. To address this question, we first performed transcriptional profiling on worker ovaries from two genotypes that differ in social behavior and ovary size. Then, we contrasted the differentially expressed ovarian genes with six sets of available brain transcriptomes. Finally, we probed behavior-related candidate gene networks in wild-type ovaries of different sizes. We found differential expression in 2151 ovarian transcripts in these artificially selected honey bee strains, corresponding to approximately 20.3% of the predicted gene set of honey bees. Differences in gene expression overlapped significantly with changes in the brain transcriptomes. Differentially expressed genes were associated with neural signal transmission (tyramine receptor, TYR) and ecdysteroid signaling; two independently tested nuclear hormone receptors (HR46 and ftz-f1) were also significantly correlated with ovary size in wild-type bees. We suggest that the correspondence between ovary and brain transcriptomes identified here indicates systemic regulatory networks among hormones (juvenile hormone and ecdysteroids), pheromones (queen mandibular pheromone), reproductive organs and nervous tissues in worker honey bees. Furthermore, robust correlations between ovary size and neuraland endocrine response genes are consistent with the hypothesized roles of the ovaries in honey bee behavioral regulation. PMID:22162860

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.

DNA methylation at differentially methylated regions of imprinted genes is resistant to developmental programming by maternal nutrition

PubMed Central

Ivanova, Elena; Chen, Jian-Hua; Segonds-Pichon, Anne; Ozanne, Susan E.; Kelsey, Gavin

2012-01-01

The nutritional environment in which the mammalian fetus or infant develop is recognized as influencing the risk of chronic diseases, such as type 2 diabetes and hypertension, in a phenomenon that has become known as developmental programming. The late onset of such diseases in response to earlier transient experiences has led to the suggestion that developmental programming may have an epigenetic component, because epigenetic marks such as DNA methylation or histone tail modifications could provide a persistent memory of earlier nutritional states. One class of genes that has been considered a potential target or mediator of programming events is imprinted genes, because these genes critically depend upon epigenetic modifications for correct expression and because many imprinted genes have roles in controlling fetal growth as well as neonatal and adult metabolism. In this study, we have used an established model of developmental programming—isocaloric protein restriction to female mice during gestation or lactation—to examine whether there are effects on expression and DNA methylation of imprinted genes in the offspring. We find that although expression of some imprinted genes in liver of offspring is robustly and sustainably changed, methylation of the differentially methylated regions (DMRs) that control their monoallelic expression remains largely unaltered. We conclude that deregulation of imprinting through a general effect on DMR methylation is unlikely to be a common factor in developmental programming. PMID:22968513

RNA-Seq Meta-analysis identifies genes in skeletal muscle associated with gain and intake across a multi-season study of crossbred beef steers.

PubMed

Keel, Brittney N; Zarek, Christina M; Keele, John W; Kuehn, Larry A; Snelling, Warren M; Oliver, William T; Freetly, Harvey C; Lindholm-Perry, Amanda K

2018-06-04

Feed intake and body weight gain are economically important inputs and outputs of beef production systems. The purpose of this study was to discover differentially expressed genes that will be robust for feed intake and gain across a large segment of the cattle industry. Transcriptomic studies often suffer from issues with reproducibility and cross-validation. One way to improve reproducibility is by integrating multiple datasets via meta-analysis. RNA sequencing (RNA-Seq) was performed on longissimus dorsi muscle from 80 steers (5 cohorts, each with 16 animals) selected from the outside fringe of a bivariate gain and feed intake distribution to understand the genes and pathways involved in feed efficiency. In each cohort, 16 steers were selected from one of four gain and feed intake phenotypes (n = 4 per phenotype) in a 2 × 2 factorial arrangement with gain and feed intake as main effect variables. Each cohort was analyzed as a single experiment using a generalized linear model and results from the 5 cohort analyses were combined in a meta-analysis to identify differentially expressed genes (DEG) across the cohorts. A total of 51 genes were differentially expressed for the main effect of gain, 109 genes for the intake main effect, and 11 genes for the gain x intake interaction (P corrected  < 0.05). A jackknife sensitivity analysis showed that, in general, the meta-analysis produced robust DEGs for the two main effects and their interaction. Pathways identified from over-represented genes included mitochondrial energy production and oxidative stress pathways for the main effect of gain due to DEG including GPD1, NDUFA6, UQCRQ, ACTC1, and MGST3. For intake, metabolic pathways including amino acid biosynthesis and degradation were identified, and for the interaction analysis the pathways identified included GADD45, pyridoxal 5'phosphate salvage, and caveolar mediated endocytosis signaling. Variation among DEG identified by cohort suggests that environment and breed may play large roles in the expression of genes associated with feed efficiency in the muscle of beef cattle. Meta-analyses of transcriptome data from groups of animals over multiple cohorts may be necessary to elucidate the genetics contributing these types of biological phenotypes.

The use of biodegradable PLGA nanoparticles to mediate SOX9 gene delivery in human mesenchymal stem cells (hMSCs) and induce chondrogenesis.

PubMed

Kim, Jae-Hwan; Park, Ji Sun; Yang, Han Na; Woo, Dae Gyun; Jeon, Su Yeon; Do, Hyun-Jin; Lim, Hye-Young; Kim, Jung Mo; Park, Keun-Hong

2011-01-01

In stem cell therapy, transfection of specific genes into stem cells is an important technique to induce cell differentiation. To perform gene transfection in human mesenchymal stem cells (hMSCs), we designed and fabricated a non-viral vector system for specific stem cell differentiation. Several kinds of gene carriers were evaluated with regard to their transfection efficiency and their ability to enhance hMSCs differentiation. Of these delivery vehicles, biodegradable poly (DL-lactic-co-glycolic acid) (PLGA) nanoparticles yielded the best results, as they complexed with high levels of plasmid DNA (pDNA), allowed robust gene expression in hMSCs, and induced chondrogenesis. Polyplexing with polyethylenimine (PEI) enhanced the cellular uptake of SOX9 DNA complexed with PLGA nanoparticles both in vitro and in vivo. The expression of enhanced green fluorescent protein (EGFP) and SOX9 increased up to 75% in hMSCs transfected with PEI/SOX9 complexed PLGA nanoparticles 2 days after transfection. SOX9 gene expression was evaluated by RT-PCR, real time-qPCR, glycosaminoglycan (GAG)/DNA levels, immunoblotting, histology, and immunofluorescence. Copyright © 2010 Elsevier Ltd. All rights reserved.

Identification of miRNA-Mediated Core Gene Module for Glioma Patient Prediction by Integrating High-Throughput miRNA, mRNA Expression and Pathway Structure

PubMed Central

Han, Junwei; Shang, Desi; Zhang, Yunpeng; Zhang, Wei; Yao, Qianlan; Han, Lei; Xu, Yanjun; Yan, Wei; Bao, Zhaoshi; You, Gan; Jiang, Tao; Kang, Chunsheng; Li, Xia

2014-01-01

The prognosis of glioma patients is usually poor, especially in patients with glioblastoma (World Health Organization (WHO) grade IV). The regulatory functions of microRNA (miRNA) on genes have important implications in glioma cell survival. However, there are not many studies that have investigated glioma survival by integrating miRNAs and genes while also considering pathway structure. In this study, we performed sample-matched miRNA and mRNA expression profilings to systematically analyze glioma patient survival. During this analytical process, we developed pathway-based random walk to identify a glioma core miRNA-gene module, simultaneously considering pathway structure information and multi-level involvement of miRNAs and genes. The core miRNA-gene module we identified was comprised of four apparent sub-modules; all four sub-modules displayed a significant correlation with patient survival in the testing set (P-values≤0.001). Notably, one sub-module that consisted of 6 miRNAs and 26 genes also correlated with survival time in the high-grade subgroup (WHO grade III and IV), P-value = 0.0062. Furthermore, the 26-gene expression signature from this sub-module had robust predictive power in four independent, publicly available glioma datasets. Our findings suggested that the expression signatures, which were identified by integration of miRNA and gene level, were closely associated with overall survival among the glioma patients with various grades. PMID:24809850

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

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

PubMed

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

2015-05-01

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

Gene Manipulation Strategies to Identify Molecular Regulators of Axon Regeneration in the Central Nervous System

PubMed Central

Ribas, Vinicius T.; Costa, Marcos R.

2017-01-01

Limited axon regeneration in the injured adult mammalian central nervous system (CNS) usually results in irreversible functional deficits. Both the presence of extrinsic inhibitory molecules at the injury site and the intrinsically low capacity of adult neurons to grow axons are responsible for the diminished capacity of regeneration in the adult CNS. Conversely, in the embryonic CNS, neurons show a high regenerative capacity, mostly due to the expression of genes that positively control axon growth and downregulation of genes that inhibit axon growth. A better understanding of the role of these key genes controlling pro-regenerative mechanisms is pivotal to develop strategies to promote robust axon regeneration following adult CNS injury. Genetic manipulation techniques have been widely used to investigate the role of specific genes or a combination of different genes in axon regrowth. This review summarizes a myriad of studies that used genetic manipulations to promote axon growth in the injured CNS. We also review the roles of some of these genes during CNS development and suggest possible approaches to identify new candidate genes. Finally, we critically address the main advantages and pitfalls of gene-manipulation techniques, and discuss new strategies to promote robust axon regeneration in the mature CNS. PMID:28824380

Effects of enhanced external counterpulsation on skeletal muscle gene expression in patients with severe heart failure.

PubMed

Melin, Michael; Montelius, Andreas; Rydén, Lars; Gonon, Adrian; Hagerman, Inger; Rullman, Eric

2018-01-01

Enhanced external counterpulsation (EECP) is a non-invasive treatment in which leg cuff compressions increase diastolic aortic pressure and coronary perfusion. EECP is offered to patients with refractory angina pectoris and increases physical capacity. Benefits in heart failure patients have been noted, but EECP is still considered to be experimental and its effects must be confirmed. The mechanism of action is still unclear. The aim of this study was to evaluate the effect of EECP on skeletal muscle gene expression and physical performance in patients with severe heart failure. Patients (n = 9) in NYHA III-IV despite pharmacological therapy were subjected to 35 h of EECP during 7 weeks. Before and after, lateral vastus muscle biopsies were obtained, and functional capacity was evaluated with a 6-min walk test. Skeletal muscle gene expression was evaluated using Affymetrix Hugene 1.0 arrays. Maximum walking distance increased by 15%, which is in parity to that achieved after aerobic exercise training in similar patients. Skeletal muscle gene expression analysis using Ingenuity Pathway Analysis showed an increased expression of two networks of genes with FGF-2 and IGF-1 as central regulators. The increase in gene expression was quantitatively small and no overlap with gene expression profiles after exercise training could be detected despite adequate statistical power. EECP treatment leads to a robust improvement in walking distance in patients with severe heart failure and does induce a skeletal muscle transcriptional response, but this response is small and with no significant overlap with the transcriptional signature seen after exercise training. © 2016 Scandinavian Society of Clinical Physiology and Nuclear Medicine. Published by John Wiley & Sons Ltd.

Validation of miRNA genes suitable as reference genes in qPCR analyses of miRNA gene expression in Atlantic salmon (Salmo salar).

PubMed

Johansen, Ilona; Andreassen, Rune

2014-12-23

MicroRNAs (miRNAs) are an abundant class of endogenous small RNA molecules that downregulate gene expression at the post-transcriptional level. They play important roles by regulating genes that control multiple biological processes, and recent years there has been an increased interest in studying miRNA genes and miRNA gene expression. The most common method applied to study gene expression of single genes is quantitative PCR (qPCR). However, before expression of mature miRNAs can be studied robust qPCR methods (miRNA-qPCR) must be developed. This includes identification and validation of suitable reference genes. We are particularly interested in Atlantic salmon (Salmo salar). This is an economically important aquaculture species, but no reference genes dedicated for use in miRNA-qPCR methods has been validated for this species. Our aim was, therefore, to identify suitable reference genes for miRNA-qPCR methods in Salmo salar. We used a systematic approach where we utilized similar studies in other species, some biological criteria, results from deep sequencing of small RNAs and, finally, experimental validation of candidate reference genes by qPCR to identify the most suitable reference genes. Ssa-miR-25-3p was identified as most suitable single reference gene. The best combinations of two reference genes were ssa-miR-25-3p and ssa-miR-455-5p. These two genes were constitutively and stably expressed across many different tissues. Furthermore, infectious salmon anaemia did not seem to affect their expression levels. These genes were amplified with high specificity, good efficiency and the qPCR assays showed a good linearity when applying a simple cybergreen miRNA-PCR method using miRNA gene specific forward primers. We have identified suitable reference genes for miRNA-qPCR in Atlantic salmon. These results will greatly facilitate further studies on miRNA genes in this species. The reference genes identified are conserved genes that are identical in their mature sequence in many aquaculture species. Therefore, they may also be suitable as reference genes in other teleosts. Finally, the systematic approach used in our study successfully identified suitable reference genes, suggesting that this may be a useful strategy to apply in similar validation studies in other aquaculture species.

Gene expression platform for synthetic biology in the human pathogen Streptococcus pneumoniae.

PubMed

Sorg, Robin A; Kuipers, Oscar P; Veening, Jan-Willem

2015-03-20

The human pathogen Streptococcus pneumoniae (pneumococcus) is a bacterium that owes its success to complex gene expression regulation patterns on both the cellular and the population level. Expression of virulence factors enables a mostly hazard-free presence of the commensal, in balance with the host and niche competitors. Under specific circumstances, changes in this expression can result in a more aggressive behavior and the reversion to the invasive form as pathogen. These triggering conditions are very difficult to study due to the fact that environmental cues are often unknown or barely possible to simulate outside the host (in vitro). An alternative way of investigating expression patterns is found in synthetic biology approaches of reconstructing regulatory networks that mimic an observed behavior with orthogonal components. Here, we created a genetic platform suitable for synthetic biology approaches in S. pneumoniae and characterized a set of standardized promoters and reporters. We show that our system allows for fast and easy cloning with the BglBrick system and that reliable and robust gene expression after integration into the S. pneumoniae genome is achieved. In addition, the cloning system was extended to allow for direct linker-based assembly of ribosome binding sites, peptide tags, and fusion proteins, and we called this new generally applicable standard "BglFusion". The gene expression platform and the methods described in this study pave the way for employing synthetic biology approaches in S. pneumoniae.

Robust expression of a bioactive mammalian protein in chlamydomonas chloroplast

DOEpatents

Mayfield, Stephen P.

2010-03-16

Methods and compositions are disclosed to engineer chloroplast comprising heterologous mammalian genes via a direct replacement of chloroplast Photosystem II (PSII) reaction center protein coding regions to achieve expression of recombinant protein above 5% of total protein. When algae is used, algal expressed protein is produced predominantly as a soluble protein where the functional activity of the peptide is intact. As the host algae is edible, production of biologics in this organism for oral delivery or proteins/peptides, especially gut active proteins, without purification is disclosed.

Robust expression of a bioactive mammalian protein in Chlamydomonas chloroplast

DOEpatents

Mayfield, Stephen P

2015-01-13

Methods and compositions are disclosed to engineer chloroplast comprising heterologous mammalian genes via a direct replacement of chloroplast Photosystem II (PSII) reaction center protein coding regions to achieve expression of recombinant protein above 5% of total protein. When algae is used, algal expressed protein is produced predominantly as a soluble protein where the functional activity of the peptide is intact. As the host algae is edible, production of biologics in this organism for oral delivery of proteins/peptides, especially gut active proteins, without purification is disclosed.

Integrative multi-platform meta-analysis of gene expression profiles in pancreatic ductal adenocarcinoma patients for identifying novel diagnostic biomarkers.

PubMed

Irigoyen, Antonio; Jimenez-Luna, Cristina; Benavides, Manuel; Caba, Octavio; Gallego, Javier; Ortuño, Francisco Manuel; Guillen-Ponce, Carmen; Rojas, Ignacio; Aranda, Enrique; Torres, Carolina; Prados, Jose

2018-01-01

Applying differentially expressed genes (DEGs) to identify feasible biomarkers in diseases can be a hard task when working with heterogeneous datasets. Expression data are strongly influenced by technology, sample preparation processes, and/or labeling methods. The proliferation of different microarray platforms for measuring gene expression increases the need to develop models able to compare their results, especially when different technologies can lead to signal values that vary greatly. Integrative meta-analysis can significantly improve the reliability and robustness of DEG detection. The objective of this work was to develop an integrative approach for identifying potential cancer biomarkers by integrating gene expression data from two different platforms. Pancreatic ductal adenocarcinoma (PDAC), where there is an urgent need to find new biomarkers due its late diagnosis, is an ideal candidate for testing this technology. Expression data from two different datasets, namely Affymetrix and Illumina (18 and 36 PDAC patients, respectively), as well as from 18 healthy controls, was used for this study. A meta-analysis based on an empirical Bayesian methodology (ComBat) was then proposed to integrate these datasets. DEGs were finally identified from the integrated data by using the statistical programming language R. After our integrative meta-analysis, 5 genes were commonly identified within the individual analyses of the independent datasets. Also, 28 novel genes that were not reported by the individual analyses ('gained' genes) were also discovered. Several of these gained genes have been already related to other gastroenterological tumors. The proposed integrative meta-analysis has revealed novel DEGs that may play an important role in PDAC and could be potential biomarkers for diagnosing the disease.

Indications for distinct pathogenic mechanisms of asbestos and silica through gene expression profiling of the response of lung epithelial cells

PubMed Central

Perkins, Timothy N.; Peeters, Paul M.; Shukla, Arti; Arijs, Ingrid; Dragon, Julie; Wouters, Emiel F.M.; Reynaert, Niki L.; Mossman, Brooke T.

2015-01-01

Occupational and environmental exposures to airborne asbestos and silica are associated with the development of lung fibrosis in the forms of asbestosis and silicosis, respectively. However, both diseases display distinct pathologic presentations, likely associated with differences in gene expression induced by different mineral structures, composition and bio-persistent properties. We hypothesized that effects of mineral exposure in the airway epithelium may dictate deviating molecular events that may explain the different pathologies of asbestosis versus silicosis. Using robust gene expression-profiling in conjunction with in-depth pathway analysis, we assessed early (24 h) alterations in gene expression associated with crocidolite asbestos or cristobalite silica exposures in primary human bronchial epithelial cells (NHBEs). Observations were confirmed in an immortalized line (BEAS-2B) by QRT-PCR and protein assays. Utilization of overall gene expression, unsupervised hierarchical cluster analysis and integrated pathway analysis revealed gene alterations that were common to both minerals or unique to either mineral. Our findings reveal that both minerals had potent effects on genes governing cell adhesion/migration, inflammation, and cellular stress, key features of fibrosis. Asbestos exposure was most specifically associated with aberrant cell proliferation and carcinogenesis, whereas silica exposure was highly associated with additional inflammatory responses, as well as pattern recognition, and fibrogenesis. These findings illustrate the use of gene-profiling as a means to determine early molecular events that may dictate pathological processes induced by exogenous cellular insults. In addition, it is a useful approach for predicting the pathogenicity of potentially harmful materials. PMID:25351596

Identification of growth stage molecular markers in Trichoderma sp. 'atroviride type B' and their potential application in monitoring fungal growth and development in soil.

PubMed

Mendoza-Mendoza, Artemio; Steyaert, Johanna; Nieto-Jacobo, Maria Fernanda; Holyoake, Andrew; Braithwaite, Mark; Stewart, Alison

2015-11-01

Several members of the genus Trichoderma are biocontrol agents of soil-borne fungal plant pathogens. The effectiveness of biocontrol agents depends heavily on how they perform in the complex field environment. Therefore, the ability to monitor and track Trichoderma within the environment is essential to understanding biocontrol efficacy. The objectives of this work were to: (a) identify key genes involved in Trichoderma sp. 'atroviride type B' morphogenesis; (b) develop a robust RNA isolation method from soil; and (c) develop molecular marker assays for characterizing morphogenesis whilst in the soil environment. Four cDNA libraries corresponding to conidia, germination, vegetative growth and conidiogenesis were created, and the genes identified by sequencing. Stage specificity of the different genes was confirmed by either Northern blot or quantitative reverse-transcriptase PCR (qRT-PCR) analysis using RNA from the four stages. con10, a conidial-specific gene, was observed in conidia, as well as one gene also involved in subsequent stages of germination (L-lactate/malate dehydrogenase encoding gene). The germination stage revealed high expression rates of genes involved in amino acid and protein biosynthesis, while in the vegetative-growth stage, genes involved in differentiation, including the mitogen-activated protein kinase kinase similar to Kpp7 from Ustilago maydis and the orthologue to stuA from Aspergillus nidulans, were preferentially expressed. Genes involved in cell-wall synthesis were expressed during conidiogenesis. We standardized total RNA isolation from Trichoderma sp. 'atroviride type B' growing in soil and then examined the expression profiles of selected genes using qRT-PCR. The results suggested that the relative expression patterns were cyclic and not accumulative.

Dose-related gene expression changes in forebrain following acute, low-level chlorpyrifos exposure in neonatal rats

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

Ray, Anamika; Department of Biochemistry and Molecular Biology, Oklahoma State University, Stillwater, OK 74078; Liu Jing

2010-10-15

Chlorpyrifos (CPF) is a widely used organophosphorus insecticide (OP) and putative developmental neurotoxicant in humans. The acute toxicity of CPF is elicited by acetylcholinesterase (AChE) inhibition. We characterized dose-related (0.1, 0.5, 1 and 2 mg/kg) gene expression profiles and changes in cell signaling pathways 24 h following acute CPF exposure in 7-day-old rats. Microarray experiments indicated that approximately 9% of the 44,000 genes were differentially expressed following either one of the four CPF dosages studied (546, 505, 522, and 3,066 genes with 0.1, 0.5, 1.0 and 2.0 mg/kg CPF). Genes were grouped according to dose-related expression patterns using K-means clusteringmore » while gene networks and canonical pathways were evaluated using Ingenuity Pathway Analysis (registered) . Twenty clusters were identified and differential expression of selected genes was verified by RT-PCR. The four largest clusters (each containing from 276 to 905 genes) constituted over 50% of all differentially expressed genes and exhibited up-regulation following exposure to the highest dosage (2 mg/kg CPF). The total number of gene networks affected by CPF also rose sharply with the highest dosage of CPF (18, 16, 18 and 50 with 0.1, 0.5, 1 and 2 mg/kg CPF). Forebrain cholinesterase (ChE) activity was significantly reduced (26%) only in the highest dosage group. Based on magnitude of dose-related changes in differentially expressed genes, relative numbers of gene clusters and signaling networks affected, and forebrain ChE inhibition only at 2 mg/kg CPF, we focused subsequent analyses on this treatment group. Six canonical pathways were identified that were significantly affected by 2 mg/kg CPF (MAPK, oxidative stress, NF{Kappa}B, mitochondrial dysfunction, arylhydrocarbon receptor and adrenergic receptor signaling). Evaluation of different cellular functions of the differentially expressed genes suggested changes related to olfactory receptors, cell adhesion/migration, synapse/synaptic transmission and transcription/translation. Nine genes were differentially affected in all four CPF dosing groups. We conclude that the most robust, consistent changes in differential gene expression in neonatal forebrain across a range of acute CPF dosages occurred at an exposure level associated with the classical marker of OP toxicity, AChE inhibition. Disruption of multiple cellular pathways, in particular cell adhesion, may contribute to the developmental neurotoxicity potential of this pesticide.« less

Rough Set Soft Computing Cancer Classification and Network: One Stone, Two Birds

PubMed Central

Zhang, Yue

2010-01-01

Gene expression profiling provides tremendous information to help unravel the complexity of cancer. The selection of the most informative genes from huge noise for cancer classification has taken centre stage, along with predicting the function of such identified genes and the construction of direct gene regulatory networks at different system levels with a tuneable parameter. A new study by Wang and Gotoh described a novel Variable Precision Rough Sets-rooted robust soft computing method to successfully address these problems and has yielded some new insights. The significance of this progress and its perspectives will be discussed in this article. PMID:20706619

A Tightly Regulated Genetic Selection System with Signaling-Active Alleles of Phytochrome B.

PubMed

Hu, Wei; Lagarias, J Clark

2017-01-01

Selectable markers derived from plant genes circumvent the potential risk of antibiotic/herbicide-resistance gene transfer into neighboring plant species, endophytic bacteria, and mycorrhizal fungi. Toward this goal, we have engineered and validated signaling-active alleles of phytochrome B (eYHB) as plant-derived selection marker genes in the model plant Arabidopsis (Arabidopsis thaliana). By probing the relationship of construct size and induction conditions to optimal phenotypic selection, we show that eYHB-based alleles are robust substitutes for antibiotic/herbicide-dependent marker genes as well as surprisingly sensitive reporters of off-target transgene expression. © 2017 American Society of Plant Biologists. All Rights Reserved.

A Tightly Regulated Genetic Selection System with Signaling-Active Alleles of Phytochrome B1[OPEN

PubMed Central

2017-01-01

Selectable markers derived from plant genes circumvent the potential risk of antibiotic/herbicide-resistance gene transfer into neighboring plant species, endophytic bacteria, and mycorrhizal fungi. Toward this goal, we have engineered and validated signaling-active alleles of phytochrome B (eYHB) as plant-derived selection marker genes in the model plant Arabidopsis (Arabidopsis thaliana). By probing the relationship of construct size and induction conditions to optimal phenotypic selection, we show that eYHB-based alleles are robust substitutes for antibiotic/herbicide-dependent marker genes as well as surprisingly sensitive reporters of off-target transgene expression. PMID:27881727

Does stress remove the HDAC brakes for the formation and persistence of long-term memory?

PubMed

White, André O; Wood, Marcelo A

2014-07-01

It has been known for numerous decades that gene expression is required for long-lasting forms of memory. In the past decade, the study of epigenetic mechanisms in memory processes has revealed yet another layer of complexity in the regulation of gene expression. Epigenetic mechanisms do not only provide complexity in the protein regulatory complexes that control coordinate transcription for specific cell function, but the epigenome encodes critical information that integrates experience and cellular history for specific cell functions as well. Thus, epigenetic mechanisms provide a unique mechanism of gene expression regulation for memory processes. This may be why critical negative regulators of gene expression, such as histone deacetylases (HDACs), have powerful effects on the formation and persistence of memory. For example, HDAC inhibition has been shown to transform a subthreshold learning event into robust long-term memory and also generate a form of long-term memory that persists beyond the point at which normal long-term memory fails. A key question that is explored in this review, from a learning and memory perspective, is whether stress-dependent signaling drives the formation and persistence of long-term memory via HDAC-dependent mechanisms. Copyright © 2013 Elsevier Inc. All rights reserved.

Does stress remove the HDAC brakes for the formation and persistence of long-term memory?

PubMed Central

White, André O.; Wood, Marcelo A.

2013-01-01

It has been known for numerous decades that gene expression is required for long-lasting forms of memory. In the past decade, the study of epigenetic mechanisms in memory processes has revealed yet another layer of complexity in the regulation of gene expression. Epigenetic mechanisms do not only provide complexity in the protein regulatory complexes that control coordinate transcription for specific cell function, but the epigenome encodes critical information that integrates experience and cellular history for specific cell functions as well. Thus, epigenetic mechanisms provide a unique mechanism of gene expression regulation for memory processes. This may be why critical negative regulators of gene expression, such as histone deacetylases (HDACs), have powerful effects on the formation and persistence of memory. For example, HDAC inhibition has been shown to transform a subthreshold learning event into robust long-term memory and also generate a form of long-term memory that persists beyond the point at which normal long-term memory fails. A key question that is explored in this review, from a learning and memory perspective, is whether stress-dependent signaling drives the formation and persistence of long-term memory via HDAC-dependent mechanisms. PMID:24149059

Effects of high temperature on photosynthesis and related gene expression in poplar

PubMed Central

2014-01-01

Background High temperature, whether transitory or constant, causes physiological, biochemical and molecular changes that adversely affect tree growth and productivity by reducing photosynthesis. To elucidate the photosynthetic adaption response and examine the recovery capacity of trees under heat stress, we measured gas exchange, chlorophyll fluorescence, electron transport, water use efficiency, and reactive oxygen-producing enzyme activities in heat-stressed plants. Results We found that photosynthesis could completely recover after less than six hours of high temperature treatment, which might be a turning point in the photosynthetic response to heat stress. Genome-wide gene expression analysis at six hours of heat stress identified 29,896 differentially expressed genes (15,670 up-regulated and 14,226 down-regulated), including multiple classes of transcription factors. These interact with each other and regulate the expression of photosynthesis-related genes in response to heat stress, controlling carbon fixation and changes in stomatal conductance. Heat stress of more than twelve hours caused reduced electron transport, damaged photosystems, activated the glycolate pathway and caused H2O2 production; as a result, photosynthetic capacity did not recover completely. Conclusions This study provides a systematic physiological and global gene expression profile of the poplar photosynthetic response to heat stress and identifies the main limitations and threshold of photosynthesis under heat stress. It will expand our understanding of plant thermostability and provides a robust dataset for future studies. PMID:24774695

Effects of high temperature on photosynthesis and related gene expression in poplar.

PubMed

Song, Yuepeng; Chen, Qingqing; Ci, Dong; Shao, Xinning; Zhang, Deqiang

2014-04-28

High temperature, whether transitory or constant, causes physiological, biochemical and molecular changes that adversely affect tree growth and productivity by reducing photosynthesis. To elucidate the photosynthetic adaption response and examine the recovery capacity of trees under heat stress, we measured gas exchange, chlorophyll fluorescence, electron transport, water use efficiency, and reactive oxygen-producing enzyme activities in heat-stressed plants. We found that photosynthesis could completely recover after less than six hours of high temperature treatment, which might be a turning point in the photosynthetic response to heat stress. Genome-wide gene expression analysis at six hours of heat stress identified 29,896 differentially expressed genes (15,670 up-regulated and 14,226 down-regulated), including multiple classes of transcription factors. These interact with each other and regulate the expression of photosynthesis-related genes in response to heat stress, controlling carbon fixation and changes in stomatal conductance. Heat stress of more than twelve hours caused reduced electron transport, damaged photosystems, activated the glycolate pathway and caused H2O2 production; as a result, photosynthetic capacity did not recover completely. This study provides a systematic physiological and global gene expression profile of the poplar photosynthetic response to heat stress and identifies the main limitations and threshold of photosynthesis under heat stress. It will expand our understanding of plant thermostability and provides a robust dataset for future studies.

BloodSpot: a database of gene expression profiles and transcriptional programs for healthy and malignant haematopoiesis.

PubMed

Bagger, Frederik Otzen; Sasivarevic, Damir; Sohi, Sina Hadi; Laursen, Linea Gøricke; Pundhir, Sachin; Sønderby, Casper Kaae; Winther, Ole; Rapin, Nicolas; Porse, Bo T

2016-01-04

Research on human and murine haematopoiesis has resulted in a vast number of gene-expression data sets that can potentially answer questions regarding normal and aberrant blood formation. To researchers and clinicians with limited bioinformatics experience, these data have remained available, yet largely inaccessible. Current databases provide information about gene-expression but fail to answer key questions regarding co-regulation, genetic programs or effect on patient survival. To address these shortcomings, we present BloodSpot (www.bloodspot.eu), which includes and greatly extends our previously released database HemaExplorer, a database of gene expression profiles from FACS sorted healthy and malignant haematopoietic cells. A revised interactive interface simultaneously provides a plot of gene expression along with a Kaplan-Meier analysis and a hierarchical tree depicting the relationship between different cell types in the database. The database now includes 23 high-quality curated data sets relevant to normal and malignant blood formation and, in addition, we have assembled and built a unique integrated data set, BloodPool. Bloodpool contains more than 2000 samples assembled from six independent studies on acute myeloid leukemia. Furthermore, we have devised a robust sample integration procedure that allows for sensitive comparison of user-supplied patient samples in a well-defined haematopoietic cellular space. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Inferring gene expression from ribosomal promoter sequences, a crowdsourcing approach

PubMed Central

Meyer, Pablo; Siwo, Geoffrey; Zeevi, Danny; Sharon, Eilon; Norel, Raquel; Segal, Eran; Stolovitzky, Gustavo; Siwo, Geoffrey; Rider, Andrew K.; Tan, Asako; Pinapati, Richard S.; Emrich, Scott; Chawla, Nitesh; Ferdig, Michael T.; Tung, Yi-An; Chen, Yong-Syuan; Chen, Mei-Ju May; Chen, Chien-Yu; Knight, Jason M.; Sahraeian, Sayed Mohammad Ebrahim; Esfahani, Mohammad Shahrokh; Dreos, Rene; Bucher, Philipp; Maier, Ezekiel; Saeys, Yvan; Szczurek, Ewa; Myšičková, Alena; Vingron, Martin; Klein, Holger; Kiełbasa, Szymon M.; Knisley, Jeff; Bonnell, Jeff; Knisley, Debra; Kursa, Miron B.; Rudnicki, Witold R.; Bhattacharjee, Madhuchhanda; Sillanpää, Mikko J.; Yeung, James; Meysman, Pieter; Rodríguez, Aminael Sánchez; Engelen, Kristof; Marchal, Kathleen; Huang, Yezhou; Mordelet, Fantine; Hartemink, Alexander; Pinello, Luca; Yuan, Guo-Cheng

2013-01-01

The Gene Promoter Expression Prediction challenge consisted of predicting gene expression from promoter sequences in a previously unknown experimentally generated data set. The challenge was presented to the community in the framework of the sixth Dialogue for Reverse Engineering Assessments and Methods (DREAM6), a community effort to evaluate the status of systems biology modeling methodologies. Nucleotide-specific promoter activity was obtained by measuring fluorescence from promoter sequences fused upstream of a gene for yellow fluorescence protein and inserted in the same genomic site of yeast Saccharomyces cerevisiae. Twenty-one teams submitted results predicting the expression levels of 53 different promoters from yeast ribosomal protein genes. Analysis of participant predictions shows that accurate values for low-expressed and mutated promoters were difficult to obtain, although in the latter case, only when the mutation induced a large change in promoter activity compared to the wild-type sequence. As in previous DREAM challenges, we found that aggregation of participant predictions provided robust results, but did not fare better than the three best algorithms. Finally, this study not only provides a benchmark for the assessment of methods predicting activity of a specific set of promoters from their sequence, but it also shows that the top performing algorithm, which used machine-learning approaches, can be improved by the addition of biological features such as transcription factor binding sites. PMID:23950146

Re-engineering adenovirus vector systems to enable high-throughput analyses of gene function.

PubMed

Stanton, Richard J; McSharry, Brian P; Armstrong, Melanie; Tomasec, Peter; Wilkinson, Gavin W G

2008-12-01

With the enhanced capacity of bioinformatics to interrogate extensive banks of sequence data, more efficient technologies are needed to test gene function predictions. Replication-deficient recombinant adenovirus (Ad) vectors are widely used in expression analysis since they provide for extremely efficient expression of transgenes in a wide range of cell types. To facilitate rapid, high-throughput generation of recombinant viruses, we have re-engineered an adenovirus vector (designated AdZ) to allow single-step, directional gene insertion using recombineering technology. Recombineering allows for direct insertion into the Ad vector of PCR products, synthesized sequences, or oligonucleotides encoding shRNAs without requirement for a transfer vector Vectors were optimized for high-throughput applications by making them "self-excising" through incorporating the I-SceI homing endonuclease into the vector removing the need to linearize vectors prior to transfection into packaging cells. AdZ vectors allow genes to be expressed in their native form or with strep, V5, or GFP tags. Insertion of tetracycline operators downstream of the human cytomegalovirus major immediate early (HCMV MIE) promoter permits silencing of transgenes in helper cells expressing the tet repressor thus making the vector compatible with the cloning of toxic gene products. The AdZ vector system is robust, straightforward, and suited to both sporadic and high-throughput applications.

NvERTx: a gene expression database to compare embryogenesis and regeneration in the sea anemone Nematostella vectensis.

PubMed

Warner, Jacob F; Guerlais, Vincent; Amiel, Aldine R; Johnston, Hereroa; Nedoncelle, Karine; Röttinger, Eric

2018-05-17

For over a century, researchers have been comparing embryogenesis and regeneration hoping that lessons learned from embryonic development will unlock hidden regenerative potential. This problem has historically been a difficult one to investigate because the best regenerative model systems are poor embryonic models and vice versa. Recently, however, there has been renewed interest in this question, as emerging models have allowed researchers to investigate these processes in the same organism. This interest has been further fueled by the advent of high-throughput transcriptomic analyses that provide virtual mountains of data. Here, we present N ematostella vectensis Embryogenesis and Regeneration Transcriptomics (NvERTx), a platform for comparing gene expression during embryogenesis and regeneration. NvERTx consists of close to 50 transcriptomic data sets spanning embryogenesis and regeneration in Nematostella These data were used to perform a robust de novo transcriptome assembly, with which users can search, conduct BLAST analyses, and plot the expression of multiple genes during these two developmental processes. The site is also home to the results of gene clustering analyses, to further mine the data and identify groups of co-expressed genes. The site can be accessed at http://nvertx.kahikai.org. © 2018. Published by The Company of Biologists Ltd.

Simulated maximum likelihood method for estimating kinetic rates in gene expression.

PubMed

Tian, Tianhai; Xu, Songlin; Gao, Junbin; Burrage, Kevin

2007-01-01

Kinetic rate in gene expression is a key measurement of the stability of gene products and gives important information for the reconstruction of genetic regulatory networks. Recent developments in experimental technologies have made it possible to measure the numbers of transcripts and protein molecules in single cells. Although estimation methods based on deterministic models have been proposed aimed at evaluating kinetic rates from experimental observations, these methods cannot tackle noise in gene expression that may arise from discrete processes of gene expression, small numbers of mRNA transcript, fluctuations in the activity of transcriptional factors and variability in the experimental environment. In this paper, we develop effective methods for estimating kinetic rates in genetic regulatory networks. The simulated maximum likelihood method is used to evaluate parameters in stochastic models described by either stochastic differential equations or discrete biochemical reactions. Different types of non-parametric density functions are used to measure the transitional probability of experimental observations. For stochastic models described by biochemical reactions, we propose to use the simulated frequency distribution to evaluate the transitional density based on the discrete nature of stochastic simulations. The genetic optimization algorithm is used as an efficient tool to search for optimal reaction rates. Numerical results indicate that the proposed methods can give robust estimations of kinetic rates with good accuracy.

Neonatal Systemic AAV Induces Tolerance to CNS Gene Therapy in MPS I Dogs and Nonhuman Primates

PubMed Central

Hinderer, Christian; Bell, Peter; Louboutin, Jean-Pierre; Zhu, Yanqing; Yu, Hongwei; Lin, Gloria; Choa, Ruth; Gurda, Brittney L; Bagel, Jessica; O'Donnell, Patricia; Sikora, Tracey; Ruane, Therese; Wang, Ping; Tarantal, Alice F; Casal, Margret L; Haskins, Mark E; Wilson, James M

2015-01-01

The potential host immune response to a nonself protein poses a fundamental challenge for gene therapies targeting recessive diseases. We demonstrate in both dogs and nonhuman primates that liver-directed gene transfer using an adeno-associated virus (AAV) vector in neonates induces a persistent state of immunological tolerance to the transgene product, substantially improving the efficacy of subsequent vector administration targeting the central nervous system (CNS). We applied this approach to a canine model of mucopolysaccharidosis type I (MPS I), a progressive neuropathic lysosomal storage disease caused by deficient activity of the enzyme α-l-iduronidase (IDUA). MPS I dogs treated systemically in the first week of life with a vector expressing canine IDUA did not develop antibodies against the enzyme and exhibited robust expression in the CNS upon intrathecal AAV delivery at 1 month of age, resulting in complete correction of brain storage lesions. Newborn rhesus monkeys treated systemically with AAV vector expressing human IDUA developed tolerance to the transgene, resulting in high cerebrospinal fluid (CSF) IDUA expression and no antibody induction after subsequent CNS gene therapy. These findings suggest that inducing tolerance to the transgene product during a critical period in immunological development can improve the efficacy and safety of gene therapy. PMID:26022732

A simplified immune suppression scheme leads to persistent micro-dystrophin expression in Duchenne muscular dystrophy dogs.

PubMed

Shin, Jin-Hong; Yue, Yongping; Srivastava, Arun; Smith, Bruce; Lai, Yi; Duan, Dongsheng

2012-02-01

Highly abbreviated micro-dystrophin genes have been intensively studied for Duchenne muscular dystrophy (DMD) gene therapy. Following adeno-associated virus (AAV) gene transfer, robust microgene expression is achieved in murine DMD models in the absence of immune suppression. Interestingly, a recent study suggests that AAV gene transfer in dystrophic dogs may require up to 18 weeks' immune suppression using a combination of three different immune-suppressive drugs (cyclosporine, mycophenolate mofetil, and anti-dog thymocyte globulin). Continued immune suppression is not only costly but also may cause untoward reactions. Further, some of the drugs (such as anti-dog thymocyte globulin) are not readily available. To overcome these limitations, we developed a novel 5-week immune suppression scheme using only cyclosporine and mycophenolate mofetil. AAV vectors (either AV.RSV.AP that expresses the heat-resistant human alkaline phosphatase gene, or AV.CMV.μDys that expresses the canine R16-17/H3/ΔC microgene) at 2.85×10(12) vg particles were injected into adult dystrophic dog limb muscles under the new immune suppression protocol. Sustained transduction was observed for nearly half year (the end of the study). The simplified immune suppression strategy described here may facilitate preclinical studies in the dog model.

Neonatal Systemic AAV Induces Tolerance to CNS Gene Therapy in MPS I Dogs and Nonhuman Primates.

PubMed

Hinderer, Christian; Bell, Peter; Louboutin, Jean-Pierre; Zhu, Yanqing; Yu, Hongwei; Lin, Gloria; Choa, Ruth; Gurda, Brittney L; Bagel, Jessica; O'Donnell, Patricia; Sikora, Tracey; Ruane, Therese; Wang, Ping; Tarantal, Alice F; Casal, Margret L; Haskins, Mark E; Wilson, James M

2015-08-01

The potential host immune response to a nonself protein poses a fundamental challenge for gene therapies targeting recessive diseases. We demonstrate in both dogs and nonhuman primates that liver-directed gene transfer using an adeno-associated virus (AAV) vector in neonates induces a persistent state of immunological tolerance to the transgene product, substantially improving the efficacy of subsequent vector administration targeting the central nervous system (CNS). We applied this approach to a canine model of mucopolysaccharidosis type I (MPS I), a progressive neuropathic lysosomal storage disease caused by deficient activity of the enzyme α-l-iduronidase (IDUA). MPS I dogs treated systemically in the first week of life with a vector expressing canine IDUA did not develop antibodies against the enzyme and exhibited robust expression in the CNS upon intrathecal AAV delivery at 1 month of age, resulting in complete correction of brain storage lesions. Newborn rhesus monkeys treated systemically with AAV vector expressing human IDUA developed tolerance to the transgene, resulting in high cerebrospinal fluid (CSF) IDUA expression and no antibody induction after subsequent CNS gene therapy. These findings suggest that inducing tolerance to the transgene product during a critical period in immunological development can improve the efficacy and safety of gene therapy.

Site-specific recombination in the chicken genome using Flipase recombinase-mediated cassette exchange.

PubMed

Lee, Hong Jo; Lee, Hyung Chul; Kim, Young Min; Hwang, Young Sun; Park, Young Hyun; Park, Tae Sub; Han, Jae Yong

2016-02-01

Targeted genome recombination has been applied in diverse research fields and has a wide range of possible applications. In particular, the discovery of specific loci in the genome that support robust and ubiquitous expression of integrated genes and the development of genome-editing technology have facilitated rapid advances in various scientific areas. In this study, we produced transgenic (TG) chickens that can induce recombinase-mediated gene cassette exchange (RMCE), one of the site-specific recombination technologies, and confirmed RMCE in TG chicken-derived cells. As a result, we established TG chicken lines that have, Flipase (Flp) recognition target (FRT) pairs in the chicken genome, mediated by piggyBac transposition. The transgene integration patterns were diverse in each TG chicken line, and the integration diversity resulted in diverse levels of expression of exogenous genes in each tissue of the TG chickens. In addition, the replaced gene cassette was expressed successfully and maintained by RMCE in the FRT predominant loci of TG chicken-derived cells. These results indicate that targeted genome recombination technology with RMCE could be adaptable to TG chicken models and that the technology would be applicable to specific gene regulation by cis-element insertion and customized expression of functional proteins at predicted levels without epigenetic influence. © FASEB.

mPeriod2 Brdm1 and other single Period mutant mice have normal food anticipatory activity.

PubMed

Pendergast, Julie S; Wendroth, Robert H; Stenner, Rio C; Keil, Charles D; Yamazaki, Shin

2017-11-14

Animals anticipate the timing of food availability via the food-entrainable oscillator (FEO). The anatomical location and timekeeping mechanism of the FEO are unknown. Several studies showed the circadian gene, Period 2, is critical for FEO timekeeping. However, other studies concluded that canonical circadian genes are not essential for FEO timekeeping. In this study, we re-examined the effects of the Per2 Brdm1 mutation on food entrainment using methods that have revealed robust food anticipatory activity in other mutant lines. We examined food anticipatory activity, which is the output of the FEO, in single Period mutant mice. Single Per1, Per2, and Per3 mutant mice had robust food anticipatory activity during restricted feeding. In addition, we found that two different lines of Per2 mutant mice (ldc and Brdm1) anticipated restricted food availability. To determine if FEO timekeeping persisted in the absence of the food cue, we assessed activity during fasting. Food anticipatory (wheel-running) activity in all Period mutant mice was also robust during food deprivation. Together, our studies demonstrate that the Period genes are not necessary for the expression of food anticipatory activity.

Avian influenza rapidly induces antiviral genes in duck lung and intestine

PubMed Central

Vanderven, Hillary A.; Petkau, Kristina; Ryan-Jean, Kieran E. E.; Aldridge, Jerry R.; Webster, Robert G.; Magor, Katharine E.

2012-01-01

Ducks are the natural reservoir of influenza A and survive infection by most strains. To characterize the duck immune response to influenza, we sought to identify innate immune genes expressed early in an infection. We used suppressive subtractive hybridization (SSH) to construct 3 libraries enriched in differentially expressed genes from lung RNA of a duck infected with highly pathogenic avian influenza virus A/Vietnam/1203/04 (H5N1), or lung and intestine RNA of a duck infected with low pathogenic avian influenza A/mallard/BC/500/05 (H5N2) compared to a mock-infected duck. Sequencing of 1687 clones identified a transcription profile enriched in genes involved in antiviral defense and other cellular processes. Major histocompatibility complex class I (MHC I), interferon induced protein with tricopeptide repeats 5 (IFIT5), and 2′–5′oligoadenylate synthetase-like gene (OASL) were increased more than 1000-fold in relative transcript abundance in duck lung at 1 dpi with highly pathogenic VN1203. These genes were induced much less in lung or intestine following infection with low pathogenic BC500. The expression of these genes following infection suggests that ducks initiate an immediate and robust response to a potentially lethal influenza strain, and a minimal response a low pathogenic strain. PMID:22534314

Genetic Contributions of Inflammation to Depression

PubMed Central

Barnes, Jacob; Mondelli, Valeria; Pariante, Carmine M

2017-01-01

This paper describes the effects of immune genes genetic variants and mRNA expression on depression's risk, severity, and response to antidepressant treatment, through a systematic review on all papers published between 2000 and 2016. Our results, based largely on case–control studies, suggest that common genetic variants and gene-expression pathways are involved in both immune activation and depression. The most replicated and relevant genetic variants include polymorphisms in the genes for interleukin (IL)-1β, IL-6, IL-10, monocyte chemoattractant protein-1, tumor necrosis factor-alpha, C-reactive protein, and phospholipase A2. Moreover, increased blood cytokines mRNA expression (especially of IL-1β) identifies patients that are less likely to respond to conventional antidepressants. However, even for the most replicated findings there are inconsistent results, not only between studies, but also between the immune effects of the genetic variants and the resulting effects on depression. We find evidence that these discrepant findings may be explained, at least in part, by the heterogeneity of the depression immunophenotype, by environmental influences and gene × environment interactions, and by the complex interfacing of genetic variants with gene expression. Indeed, some of the most robust findings have been obtained in patients developing depression in the context of treatment with interferon-alpha, a widely used model to mimic depression in the context of inflammation. Further ‘omics' approaches, through GWAS and transcriptomics, will finally shed light on the interaction between immune genes, their expression, and the influence of the environment, in the pathogenesis of depression. PMID:27555379

Advancing age is associated with gene expression changes resembling mTOR inhibition: evidence from two human populations.

PubMed

Harries, Lorna W; Fellows, Alexander D; Pilling, Luke C; Hernandez, Dena; Singleton, Andrew; Bandinelli, Stefania; Guralnik, Jack; Powell, Jonathan; Ferrucci, Luigi; Melzer, David

2012-08-01

Interventions which inhibit TOR activity (including rapamycin and caloric restriction) lead to downstream gene expression changes and increased lifespan in laboratory models. However, the role of mTOR signaling in human aging is unclear. We tested the expression of mTOR-related transcripts in two independent study cohorts; the InCHIANTI population study of aging and the San Antonio Family Heart Study (SAFHS). Expression of 27/56 (InCHIANTI) and 19/44 (SAFHS) genes were associated with age after correction for multiple testing. 8 genes were robustly associated with age in both cohorts. Genes involved in insulin signaling (PTEN, PI3K, PDK1), ribosomal biogenesis (S6K), lipid metabolism (SREBF1), cellular apoptosis (SGK1), angiogenesis (VEGFB), insulin production and sensitivity (FOXO), cellular stress response (HIF1A) and cytoskeletal remodeling (PKC) were inversely correlated with age, whereas genes relating to inhibition of ribosomal components (4EBP1) and inflammatory mediators (STAT3) were positively associated with age in one or both datasets. We conclude that the expression of mTOR-related transcripts is associated with advancing age in humans. Changes seen are broadly similar to mTOR inhibition interventions associated with increased lifespan in animals. Work is needed to establish whether these changes are predictive of human longevity and whether further mTOR inhibition would be beneficial in older people. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Gene expression profiles analysis identifies key genes for acute lung injury in patients with sepsis.

PubMed

Guo, Zhiqiang; Zhao, Chuncheng; Wang, Zheng

2014-09-26

To identify critical genes and biological pathways in acute lung injury (ALI), a comparative analysis of gene expression profiles of patients with ALI + sepsis compared with patients with sepsis alone were performed with bioinformatic tools. GSE10474 was downloaded from Gene Expression Omnibus, including a collective of 13 whole blood samples with ALI + sepsis and 21 whole blood samples with sepsis alone. After pre-treatment with robust multichip averaging (RMA) method, differential analysis was conducted using simpleaffy package based upon t-test and fold change. Hierarchical clustering was also performed using function hclust from package stats. Beisides, functional enrichment analysis was conducted using iGepros. Moreover, the gene regulatory network was constructed with information from Kyoto Encyclopedia of Genes and Genomes (KEGG) and then visualized by Cytoscape. A total of 128 differentially expressed genes (DEGs) were identified, including 47 up- and 81 down-regulated genes. The significantly enriched functions included negative regulation of cell proliferation, regulation of response to stimulus and cellular component morphogenesis. A total of 27 DEGs were significantly enriched in 16 KEGG pathways, such as protein digestion and absorption, fatty acid metabolism, amoebiasis, etc. Furthermore, the regulatory network of these 27 DEGs was constructed, which involved several key genes, including protein tyrosine kinase 2 (PTK2), v-src avian sarcoma (SRC) and Caveolin 2 (CAV2). PTK2, SRC and CAV2 may be potential markers for diagnosis and treatment of ALI. The virtual slide(s) for this article can be found here: http://www.diagnosticpathology.diagnomx.eu/vs/5865162912987143.

The Global Error Assessment (GEA) model for the selection of differentially expressed genes in microarray data.

PubMed

Mansourian, Robert; Mutch, David M; Antille, Nicolas; Aubert, Jerome; Fogel, Paul; Le Goff, Jean-Marc; Moulin, Julie; Petrov, Anton; Rytz, Andreas; Voegel, Johannes J; Roberts, Matthew-Alan

2004-11-01

Microarray technology has become a powerful research tool in many fields of study; however, the cost of microarrays often results in the use of a low number of replicates (k). Under circumstances where k is low, it becomes difficult to perform standard statistical tests to extract the most biologically significant experimental results. Other more advanced statistical tests have been developed; however, their use and interpretation often remain difficult to implement in routine biological research. The present work outlines a method that achieves sufficient statistical power for selecting differentially expressed genes under conditions of low k, while remaining as an intuitive and computationally efficient procedure. The present study describes a Global Error Assessment (GEA) methodology to select differentially expressed genes in microarray datasets, and was developed using an in vitro experiment that compared control and interferon-gamma treated skin cells. In this experiment, up to nine replicates were used to confidently estimate error, thereby enabling methods of different statistical power to be compared. Gene expression results of a similar absolute expression are binned, so as to enable a highly accurate local estimate of the mean squared error within conditions. The model then relates variability of gene expression in each bin to absolute expression levels and uses this in a test derived from the classical ANOVA. The GEA selection method is compared with both the classical and permutational ANOVA tests, and demonstrates an increased stability, robustness and confidence in gene selection. A subset of the selected genes were validated by real-time reverse transcription-polymerase chain reaction (RT-PCR). All these results suggest that GEA methodology is (i) suitable for selection of differentially expressed genes in microarray data, (ii) intuitive and computationally efficient and (iii) especially advantageous under conditions of low k. The GEA code for R software is freely available upon request to authors.

Finding differentially expressed genes in high dimensional data: Rank based test statistic via a distance measure.

PubMed

Mathur, Sunil; Sadana, Ajit

2015-12-01

We present a rank-based test statistic for the identification of differentially expressed genes using a distance measure. The proposed test statistic is highly robust against extreme values and does not assume the distribution of parent population. Simulation studies show that the proposed test is more powerful than some of the commonly used methods, such as paired t-test, Wilcoxon signed rank test, and significance analysis of microarray (SAM) under certain non-normal distributions. The asymptotic distribution of the test statistic, and the p-value function are discussed. The application of proposed method is shown using a real-life data set. © The Author(s) 2011.

Identification and temporal expression of putative circadian clock transcripts in the amphipod crustacean Talitrus saltator

PubMed Central

O’Grady, Joseph F.; Hoelters, Laura S.; Swain, Martin T.

2016-01-01

Background Talitrus saltator is an amphipod crustacean that inhabits the supralittoral zone on sandy beaches in the Northeast Atlantic and Mediterranean. T. saltator exhibits endogenous locomotor activity rhythms and time-compensated sun and moon orientation, both of which necessitate at least one chronometric mechanism. Whilst their behaviour is well studied, currently there are no descriptions of the underlying molecular components of a biological clock in this animal, and very few in other crustacean species. Methods We harvested brain tissue from animals expressing robust circadian activity rhythms and used homology cloning and Illumina RNAseq approaches to sequence and identify the core circadian clock and clock-related genes in these samples. We assessed the temporal expression of these genes in time-course samples from rhythmic animals using RNAseq. Results We identified a comprehensive suite of circadian clock gene homologues in T. saltator including the ‘core’ clock genes period (Talper), cryptochrome 2 (Talcry2), timeless (Taltim), clock (Talclk), and bmal1 (Talbmal1). In addition we describe the sequence and putative structures of 23 clock-associated genes including two unusual, extended isoforms of pigment dispersing hormone (Talpdh). We examined time-course RNAseq expression data, derived from tissues harvested from behaviourally rhythmic animals, to reveal rhythmic expression of these genes with approximately circadian period in Talper and Talbmal1. Of the clock-related genes, casein kinase IIβ (TalckIIβ), ebony (Talebony), jetlag (Taljetlag), pigment dispensing hormone (Talpdh), protein phosphatase 1 (Talpp1), shaggy (Talshaggy), sirt1 (Talsirt1), sirt7 (Talsirt7) and supernumerary limbs (Talslimb) show temporal changes in expression. Discussion We report the sequences of principle genes that comprise the circadian clock of T. saltator and highlight the conserved structural and functional domains of their deduced cognate proteins. Our sequencing data contribute to the growing inventory of described comparative clocks. Expression profiling of the identified clock genes illuminates tantalising targets for experimental manipulation to elucidate the molecular and cellular control of clock-driven phenotypes in this crustacean. PMID:27761341

Novel molecular subtypes of serous and endometrioid ovarian cancer linked to clinical outcome.

PubMed

Tothill, Richard W; Tinker, Anna V; George, Joshy; Brown, Robert; Fox, Stephen B; Lade, Stephen; Johnson, Daryl S; Trivett, Melanie K; Etemadmoghadam, Dariush; Locandro, Bianca; Traficante, Nadia; Fereday, Sian; Hung, Jillian A; Chiew, Yoke-Eng; Haviv, Izhak; Gertig, Dorota; DeFazio, Anna; Bowtell, David D L

2008-08-15

The study aim to identify novel molecular subtypes of ovarian cancer by gene expression profiling with linkage to clinical and pathologic features. Microarray gene expression profiling was done on 285 serous and endometrioid tumors of the ovary, peritoneum, and fallopian tube. K-means clustering was applied to identify robust molecular subtypes. Statistical analysis identified differentially expressed genes, pathways, and gene ontologies. Laser capture microdissection, pathology review, and immunohistochemistry validated the array-based findings. Patient survival within k-means groups was evaluated using Cox proportional hazards models. Class prediction validated k-means groups in an independent dataset. A semisupervised survival analysis of the array data was used to compare against unsupervised clustering results. Optimal clustering of array data identified six molecular subtypes. Two subtypes represented predominantly serous low malignant potential and low-grade endometrioid subtypes, respectively. The remaining four subtypes represented higher grade and advanced stage cancers of serous and endometrioid morphology. A novel subtype of high-grade serous cancers reflected a mesenchymal cell type, characterized by overexpression of N-cadherin and P-cadherin and low expression of differentiation markers, including CA125 and MUC1. A poor prognosis subtype was defined by a reactive stroma gene expression signature, correlating with extensive desmoplasia in such samples. A similar poor prognosis signature could be found using a semisupervised analysis. Each subtype displayed distinct levels and patterns of immune cell infiltration. Class prediction identified similar subtypes in an independent ovarian dataset with similar prognostic trends. Gene expression profiling identified molecular subtypes of ovarian cancer of biological and clinical importance.

Cold Induction of Arabidopsis CBF Genes Involves Multiple ICE (Inducer of CBF Expression) Promoter Elements and a Cold-Regulatory Circuit That Is Desensitized by Low Temperature1

PubMed Central

Zarka, Daniel G.; Vogel, Jonathan T.; Cook, Daniel; Thomashow, Michael F.

2003-01-01

The Arabidopsis CBF1, 2, and 3 genes (also known as DREB1b, c, and a, respectively) encode transcriptional activators that have a central role in cold tolerance. CBF1-3 are rapidly induced upon exposing plants to low temperature, followed by expression of CBF-targeted genes, the CBF regulon, resulting in an increase in plant freezing tolerance. At present, little is known about the cold-sensing mechanism that controls CBF expression. Results presented here indicate that this mechanism does not require a cold shock to bring about the accumulation of CBF transcripts, but instead, absolute temperature is monitored with a greater degree of input, i.e. lower temperature, resulting in a greater output, i.e. higher levels of CBF transcripts. Temperature-shift experiments also indicate that the cold-sensing mechanism becomes desensitized to a given low temperature, such as 4°C, and that resensitization to that temperature requires between 8 and 24 h at warm temperature. Gene fusion experiments identified a 125-bp section of the CBF2 promoter that is sufficient to impart cold-responsive gene expression. Mutational analysis of this cold-responsive region identified two promoter segments that work in concert to impart robust cold-regulated gene expression. These sequences, designated ICEr1 and ICEr2 (induction of CBF expression region 1 or 2), were also shown to stimulate transcription in response to mechanical agitation and the protein synthesis inhibitor, cycloheximide. PMID:14500791

Entrainment to feeding but not to light: circadian phenotype of VPAC2 receptor-null mice.

PubMed

Sheward, W John; Maywood, Elizabeth S; French, Karen L; Horn, Jacqueline M; Hastings, Michael H; Seckl, Jonathan R; Holmes, Megan C; Harmar, Anthony J

2007-04-18

The master clock driving mammalian circadian rhythms is located in the suprachiasmatic nuclei (SCN) of the hypothalamus and entrained by daily light/dark cycles. SCN lesions abolish circadian rhythms of behavior and result in a loss of synchronized circadian rhythms of clock gene expression in peripheral organs (e.g., the liver) and of hormone secretion (e.g., corticosterone). We examined rhythms of behavior, hepatic clock gene expression, and corticosterone secretion in VPAC2 receptor-null (Vipr2-/-) mice, which lack a functional SCN clock. Unexpectedly, although Vipr2-/- mice lacked robust circadian rhythms of wheel-running activity and corticosterone secretion, hepatic clock gene expression was strongly rhythmic, but advanced in phase compared with that in wild-type mice. The timing of food availability is thought to be an important entrainment signal for circadian clocks outside the SCN. Vipr2-/- mice consumed food significantly earlier in the 24 h cycle than wild-type mice, consistent with the observed timing of peripheral rhythms of circadian gene expression. When restricted to feeding only during the daytime (RF), mice develop rhythms of activity and of corticosterone secretion in anticipation of feeding time, thought to be driven by a food-entrainable circadian oscillator, located outside the SCN. Under RF, mice of both genotypes developed food-anticipatory rhythms of activity and corticosterone secretion, and hepatic gene expression rhythms also became synchronized to the RF stimulus. Thus, food intake is an effective zeitgeber capable of coordinating circadian rhythms of behavior, peripheral clock gene expression, and hormone secretion, even in the absence of a functional SCN clock.

Evidence of inflammatory immune signaling in chronic fatigue syndrome: A pilot study of gene expression in peripheral blood.

PubMed

Aspler, Anne L; Bolshin, Carly; Vernon, Suzanne D; Broderick, Gordon

2008-09-26

Genomic profiling of peripheral blood reveals altered immunity in chronic fatigue syndrome (CFS) however interpretation remains challenging without immune demographic context. The object of this work is to identify modulation of specific immune functional components and restructuring of co-expression networks characteristic of CFS using the quantitative genomics of peripheral blood. Gene sets were constructed a priori for CD4+ T cells, CD8+ T cells, CD19+ B cells, CD14+ monocytes and CD16+ neutrophils from published data. A group of 111 women were classified using empiric case definition (U.S. Centers for Disease Control and Prevention) and unsupervised latent cluster analysis (LCA). Microarray profiles of peripheral blood were analyzed for expression of leukocyte-specific gene sets and characteristic changes in co-expression identified from topological evaluation of linear correlation networks. Median expression for a set of 6 genes preferentially up-regulated in CD19+ B cells was significantly lower in CFS (p = 0.01) due mainly to PTPRK and TSPAN3 expression. Although no other gene set was differentially expressed at p < 0.05, patterns of co-expression in each group differed markedly. Significant co-expression of CD14+ monocyte with CD16+ neutrophil (p = 0.01) and CD19+ B cell sets (p = 0.00) characterized CFS and fatigue phenotype groups. Also in CFS was a significant negative correlation between CD8+ and both CD19+ up-regulated (p = 0.02) and NK gene sets (p = 0.08). These patterns were absent in controls. Dissection of blood microarray profiles points to B cell dysfunction with coordinated immune activation supporting persistent inflammation and antibody-mediated NK cell modulation of T cell activity. This has clinical implications as the CD19+ genes identified could provide robust and biologically meaningful basis for the early detection and unambiguous phenotyping of CFS.

A computational approach to identify cellular heterogeneity and tissue-specific gene regulatory networks.

PubMed

Jambusaria, Ankit; Klomp, Jeff; Hong, Zhigang; Rafii, Shahin; Dai, Yang; Malik, Asrar B; Rehman, Jalees

2018-06-07

The heterogeneity of cells across tissue types represents a major challenge for studying biological mechanisms as well as for therapeutic targeting of distinct tissues. Computational prediction of tissue-specific gene regulatory networks may provide important insights into the mechanisms underlying the cellular heterogeneity of cells in distinct organs and tissues. Using three pathway analysis techniques, gene set enrichment analysis (GSEA), parametric analysis of gene set enrichment (PGSEA), alongside our novel model (HeteroPath), which assesses heterogeneously upregulated and downregulated genes within the context of pathways, we generated distinct tissue-specific gene regulatory networks. We analyzed gene expression data derived from freshly isolated heart, brain, and lung endothelial cells and populations of neurons in the hippocampus, cingulate cortex, and amygdala. In both datasets, we found that HeteroPath segregated the distinct cellular populations by identifying regulatory pathways that were not identified by GSEA or PGSEA. Using simulated datasets, HeteroPath demonstrated robustness that was comparable to what was seen using existing gene set enrichment methods. Furthermore, we generated tissue-specific gene regulatory networks involved in vascular heterogeneity and neuronal heterogeneity by performing motif enrichment of the heterogeneous genes identified by HeteroPath and linking the enriched motifs to regulatory transcription factors in the ENCODE database. HeteroPath assesses contextual bidirectional gene expression within pathways and thus allows for transcriptomic assessment of cellular heterogeneity. Unraveling tissue-specific heterogeneity of gene expression can lead to a better understanding of the molecular underpinnings of tissue-specific phenotypes.

Validation of reference genes for gene expression analysis in olive (Olea europaea) mesocarp tissue by quantitative real-time RT-PCR

PubMed Central

2014-01-01

Background Gene expression analysis using quantitative reverse transcription PCR (qRT-PCR) is a robust method wherein the expression levels of target genes are normalised using internal control genes, known as reference genes, to derive changes in gene expression levels. Although reference genes have recently been suggested for olive tissues, combined/independent analysis on different cultivars has not yet been tested. Therefore, an assessment of reference genes was required to validate the recent findings and select stably expressed genes across different olive cultivars. Results A total of eight candidate reference genes [glyceraldehyde 3-phosphate dehydrogenase (GAPDH), serine/threonine-protein phosphatase catalytic subunit (PP2A), elongation factor 1 alpha (EF1-alpha), polyubiquitin (OUB2), aquaporin tonoplast intrinsic protein (TIP2), tubulin alpha (TUBA), 60S ribosomal protein L18-3 (60S RBP L18-3) and polypyrimidine tract-binding protein homolog 3 (PTB)] were chosen based on their stability in olive tissues as well as in other plants. Expression stability was examined by qRT-PCR across 12 biological samples, representing mesocarp tissues at various developmental stages in three different olive cultivars, Barnea, Frantoio and Picual, independently and together during the 2009 season with two software programs, GeNorm and BestKeeper. Both software packages identified GAPDH, EF1-alpha and PP2A as the three most stable reference genes across the three cultivars and in the cultivar, Barnea. GAPDH, EF1-alpha and 60S RBP L18-3 were found to be most stable reference genes in the cultivar Frantoio while 60S RBP L18-3, OUB2 and PP2A were found to be most stable reference genes in the cultivar Picual. Conclusions The analyses of expression stability of reference genes using qRT-PCR revealed that GAPDH, EF1-alpha, PP2A, 60S RBP L18-3 and OUB2 are suitable reference genes for expression analysis in developing Olea europaea mesocarp tissues, displaying the highest level of expression stability across three different olive cultivars, Barnea, Frantoio and Picual, however the combination of the three most stable reference genes do vary amongst individual cultivars. This study will provide guidance to other researchers to select reference genes for normalization against target genes by qPCR across tissues obtained from the mesocarp region of the olive fruit in the cultivars, Barnea, Frantoio and Picual. PMID:24884716

Dkk2/Frzb in the dermal papillae regulates feather regeneration

PubMed Central

Chu, Qiqi; Cai, Linyan; Fu, Yu; Chen, Xi; Yan, Zhipeng; Lin, Xiang; Zhou, Guixuan; Han, Hao; Widelitz, Randall B.; Chuong, Cheng-ming; Wu, Wei; Yue, Zhicao

2015-01-01

Avian feathers have robust growth and regeneration capability. To evaluate the contribution of signaling molecules and pathways in these processes, we profiled gene expression in the feather follicle using an absolute quantification approach. We identified hundreds of genes that mark specific components of the feather follicle: the dermal papillae (DP) which controls feather regeneration and axis formation, the pulp mesenchyme (Pp) which is derived from DP cells and nourishes the feather follicle, and the ramogenic zone epithelium (Erz) where a feather starts to branch. The feather DP is enriched in BMP/TGF-β signaling molecules and inhibitors for Wnt signaling including Dkk2/Frzb. Wnt ligands are mainly expressed in the feather epithelium and pulp. We find that while Wnt signaling is required for the maintenance of DP marker gene expression and feather regeneration, excessive Wnt signaling delays regeneration and reduces pulp formation. Manipulating Dkk2/Frzb expression by lentiviral-mediated overexpression, shRNA-knockdown, or by antibody neutralization resulted in dual feather axes formation. Our results suggest that the Wnt signaling in the proximal feather follicle is fine-tuned to accommodate feather regeneration and axis formation. PMID:24463139

Single-cell and coupled GRN models of cell patterning in the Arabidopsis thaliana root stem cell niche

PubMed Central

2010-01-01

Background Recent experimental work has uncovered some of the genetic components required to maintain the Arabidopsis thaliana root stem cell niche (SCN) and its structure. Two main pathways are involved. One pathway depends on the genes SHORTROOT and SCARECROW and the other depends on the PLETHORA genes, which have been proposed to constitute the auxin readouts. Recent evidence suggests that a regulatory circuit, composed of WOX5 and CLE40, also contributes to the SCN maintenance. Yet, we still do not understand how the niche is dynamically maintained and patterned or if the uncovered molecular components are sufficient to recover the observed gene expression configurations that characterize the cell types within the root SCN. Mathematical and computational tools have proven useful in understanding the dynamics of cell differentiation. Hence, to further explore root SCN patterning, we integrated available experimental data into dynamic Gene Regulatory Network (GRN) models and addressed if these are sufficient to attain observed gene expression configurations in the root SCN in a robust and autonomous manner. Results We found that an SCN GRN model based only on experimental data did not reproduce the configurations observed within the root SCN. We developed several alternative GRN models that recover these expected stable gene configurations. Such models incorporate a few additional components and interactions in addition to those that have been uncovered. The recovered configurations are stable to perturbations, and the models are able to recover the observed gene expression profiles of almost all the mutants described so far. However, the robustness of the postulated GRNs is not as high as that of other previously studied networks. Conclusions These models are the first published approximations for a dynamic mechanism of the A. thaliana root SCN cellular pattering. Our model is useful to formally show that the data now available are not sufficient to fully reproduce root SCN organization and genetic profiles. We then highlight some experimental holes that remain to be studied and postulate some novel gene interactions. Finally, we suggest the existence of a generic dynamical motif that can be involved in both plant and animal SCN maintenance. PMID:20920363

Systematic Integration of Brain eQTL and GWAS Identifies ZNF323 as a Novel Schizophrenia Risk Gene and Suggests Recent Positive Selection Based on Compensatory Advantage on Pulmonary Function

PubMed Central

Luo, Xiong-Jian; Mattheisen, Manuel; Li, Ming; Huang, Liang; Rietschel, Marcella; Børglum, Anders D.; Als, Thomas D.; van den Oord, Edwin J.; Aberg, Karolina A.; Mors, Ole; Mortensen, Preben Bo; Luo, Zhenwu; Degenhardt, Franziska; Cichon, Sven; Schulze, Thomas G.; Nöthen, Markus M.; Su, Bing; Zhao, Zhongming; Gan, Lin; Yao, Yong-Gang

2015-01-01

Genome-wide association studies have identified multiple risk variants and loci that show robust association with schizophrenia. Nevertheless, it remains unclear how these variants confer risk to schizophrenia. In addition, the driving force that maintains the schizophrenia risk variants in human gene pool is poorly understood. To investigate whether expression-associated genetic variants contribute to schizophrenia susceptibility, we systematically integrated brain expression quantitative trait loci and genome-wide association data of schizophrenia using Sherlock, a Bayesian statistical framework. Our analyses identified ZNF323 as a schizophrenia risk gene (P = 2.22×10–6). Subsequent analyses confirmed the association of the ZNF323 and its expression-associated single nucleotide polymorphism rs1150711 in independent samples (gene-expression: P = 1.40×10–6; single-marker meta-analysis in the combined discovery and replication sample comprising 44123 individuals: P = 6.85×10−10). We found that the ZNF323 was significantly downregulated in hippocampus and frontal cortex of schizophrenia patients (P = .0038 and P = .0233, respectively). Evidence for pleiotropic effects was detected (association of rs1150711 with lung function and gene expression of ZNF323 in lung: P = 6.62×10–5 and P = 9.00×10–5, respectively) with the risk allele (T allele) for schizophrenia acting as protective allele for lung function. Subsequent population genetics analyses suggest that the risk allele (T) of rs1150711 might have undergone recent positive selection in human population. Our findings suggest that the ZNF323 is a schizophrenia susceptibility gene whose expression may influence schizophrenia risk. Our study also illustrates a possible mechanism for maintaining schizophrenia risk variants in the human gene pool. PMID:25759474

GTA: a game theoretic approach to identifying cancer subnetwork markers.

PubMed

Farahmand, S; Goliaei, S; Ansari-Pour, N; Razaghi-Moghadam, Z

2016-03-01

The identification of genetic markers (e.g. genes, pathways and subnetworks) for cancer has been one of the most challenging research areas in recent years. A subset of these studies attempt to analyze genome-wide expression profiles to identify markers with high reliability and reusability across independent whole-transcriptome microarray datasets. Therefore, the functional relationships of genes are integrated with their expression data. However, for a more accurate representation of the functional relationships among genes, utilization of the protein-protein interaction network (PPIN) seems to be necessary. Herein, a novel game theoretic approach (GTA) is proposed for the identification of cancer subnetwork markers by integrating genome-wide expression profiles and PPIN. The GTA method was applied to three distinct whole-transcriptome breast cancer datasets to identify the subnetwork markers associated with metastasis. To evaluate the performance of our approach, the identified subnetwork markers were compared with gene-based, pathway-based and network-based markers. We show that GTA is not only capable of identifying robust metastatic markers, it also provides a higher classification performance. In addition, based on these GTA-based subnetworks, we identified a new bonafide candidate gene for breast cancer susceptibility.

Arabidopsis Ensemble Reverse-Engineered Gene Regulatory Network Discloses Interconnected Transcription Factors in Oxidative Stress[W

PubMed Central

Vermeirssen, Vanessa; De Clercq, Inge; Van Parys, Thomas; Van Breusegem, Frank; Van de Peer, Yves

2014-01-01

The abiotic stress response in plants is complex and tightly controlled by gene regulation. We present an abiotic stress gene regulatory network of 200,014 interactions for 11,938 target genes by integrating four complementary reverse-engineering solutions through average rank aggregation on an Arabidopsis thaliana microarray expression compendium. This ensemble performed the most robustly in benchmarking and greatly expands upon the availability of interactions currently reported. Besides recovering 1182 known regulatory interactions, cis-regulatory motifs and coherent functionalities of target genes corresponded with the predicted transcription factors. We provide a valuable resource of 572 abiotic stress modules of coregulated genes with functional and regulatory information, from which we deduced functional relationships for 1966 uncharacterized genes and many regulators. Using gain- and loss-of-function mutants of seven transcription factors grown under control and salt stress conditions, we experimentally validated 141 out of 271 predictions (52% precision) for 102 selected genes and mapped 148 additional transcription factor-gene regulatory interactions (49% recall). We identified an intricate core oxidative stress regulatory network where NAC13, NAC053, ERF6, WRKY6, and NAC032 transcription factors interconnect and function in detoxification. Our work shows that ensemble reverse-engineering can generate robust biological hypotheses of gene regulation in a multicellular eukaryote that can be tested by medium-throughput experimental validation. PMID:25549671

Arabidopsis ensemble reverse-engineered gene regulatory network discloses interconnected transcription factors in oxidative stress.

PubMed

Vermeirssen, Vanessa; De Clercq, Inge; Van Parys, Thomas; Van Breusegem, Frank; Van de Peer, Yves

2014-12-01

The abiotic stress response in plants is complex and tightly controlled by gene regulation. We present an abiotic stress gene regulatory network of 200,014 interactions for 11,938 target genes by integrating four complementary reverse-engineering solutions through average rank aggregation on an Arabidopsis thaliana microarray expression compendium. This ensemble performed the most robustly in benchmarking and greatly expands upon the availability of interactions currently reported. Besides recovering 1182 known regulatory interactions, cis-regulatory motifs and coherent functionalities of target genes corresponded with the predicted transcription factors. We provide a valuable resource of 572 abiotic stress modules of coregulated genes with functional and regulatory information, from which we deduced functional relationships for 1966 uncharacterized genes and many regulators. Using gain- and loss-of-function mutants of seven transcription factors grown under control and salt stress conditions, we experimentally validated 141 out of 271 predictions (52% precision) for 102 selected genes and mapped 148 additional transcription factor-gene regulatory interactions (49% recall). We identified an intricate core oxidative stress regulatory network where NAC13, NAC053, ERF6, WRKY6, and NAC032 transcription factors interconnect and function in detoxification. Our work shows that ensemble reverse-engineering can generate robust biological hypotheses of gene regulation in a multicellular eukaryote that can be tested by medium-throughput experimental validation. © 2014 American Society of Plant Biologists. All rights reserved.

Acetylcholine-induced activation of M3 muscarinic receptors stimulates robust matrix metalloproteinase gene expression in human colon cancer cells.

PubMed

Xie, Guofeng; Cheng, Kunrong; Shant, Jasleen; Raufman, Jean-Pierre

2009-04-01

Previously, we showed that ACh-induced proliferation of human colon cancer cells is mediated by transactivation of epidermal growth factor (EGF) receptors (EGFRs). In the present study, we elucidate the molecular mechanism underlying this action. ACh-induced proliferation of H508 colon cancer cells, which express exclusively M3 muscarinic receptors (M3Rs), was attenuated by anti-EGFR ligand binding domain antibody, a broad-spectrum matrix metalloproteinase (MMP) inhibitor, anti-MMP7 antibody, a diphtheria toxin analog that blocks release of an EGFR ligand [heparin-binding EGF-like growth factor (HBEGF)], and anti-HBEGF antibody. Conditioned media from ACh-treated H508 cells induced proliferation of SNU-C4 colon cancer cells that express EGFR but not M3R. These actions were attenuated by an EGFR inhibitor and by anti-EGFR and anti-HBEGF antibodies. In H508, but not SNU-C4, colon cancer cells, ACh caused a striking dose- and time-dependent increase in levels of MMP7 mRNA and MMP7 protein. Similarly, ACh induced robust MMP1 and MMP10 gene transcription. ACh-induced MMP1, MMP7, and MMP10 gene transcription was attenuated by atropine, anti-EGFR antibody, and chemical inhibitors of EGFR and ERK activation. In contrast, inhibitors of phosphatidylinositol 3-kinase and NF-kappaB activation did not alter MMP gene transcription. Collectively, these findings indicate that MMP7-catalyzed release of HBEGF mediates ACh-induced transactivation of EGFR and consequent proliferation of colon cancer cells. ACh-induced activation of EGFR and downstream ERK signaling also regulates transcriptional activation of MMP7, thereby identifying a novel feed-forward mechanism for neoplastic cell proliferation.

Acetylcholine-induced activation of M3 muscarinic receptors stimulates robust matrix metalloproteinase gene expression in human colon cancer cells

PubMed Central

Xie, Guofeng; Cheng, Kunrong; Shant, Jasleen; Raufman, Jean-Pierre

2009-01-01

Previously, we showed that ACh-induced proliferation of human colon cancer cells is mediated by transactivation of epidermal growth factor (EGF) receptors (EGFRs). In the present study, we elucidate the molecular mechanism underlying this action. ACh-induced proliferation of H508 colon cancer cells, which express exclusively M3 muscarinic receptors (M3Rs), was attenuated by anti-EGFR ligand binding domain antibody, a broad-spectrum matrix metalloproteinase (MMP) inhibitor, anti-MMP7 antibody, a diphtheria toxin analog that blocks release of an EGFR ligand [heparin-binding EGF-like growth factor (HBEGF)], and anti-HBEGF antibody. Conditioned media from ACh-treated H508 cells induced proliferation of SNU-C4 colon cancer cells that express EGFR but not M3R. These actions were attenuated by an EGFR inhibitor and by anti-EGFR and anti-HBEGF antibodies. In H508, but not SNU-C4, colon cancer cells, ACh caused a striking dose- and time-dependent increase in levels of MMP7 mRNA and MMP7 protein. Similarly, ACh induced robust MMP1 and MMP10 gene transcription. ACh-induced MMP1, MMP7, and MMP10 gene transcription was attenuated by atropine, anti-EGFR antibody, and chemical inhibitors of EGFR and ERK activation. In contrast, inhibitors of phosphatidylinositol 3-kinase and NF-κB activation did not alter MMP gene transcription. Collectively, these findings indicate that MMP7-catalyzed release of HBEGF mediates ACh-induced transactivation of EGFR and consequent proliferation of colon cancer cells. ACh-induced activation of EGFR and downstream ERK signaling also regulates transcriptional activation of MMP7, thereby identifying a novel feed-forward mechanism for neoplastic cell proliferation. PMID:19221016

Ribosomal frameshifting and dual-target antiactivation restrict quorum-sensing-activated transfer of a mobile genetic element.

PubMed

Ramsay, Joshua P; Tester, Laura G L; Major, Anthony S; Sullivan, John T; Edgar, Christina D; Kleffmann, Torsten; Patterson-House, Jackson R; Hall, Drew A; Tate, Warren P; Hynes, Michael F; Ronson, Clive W

2015-03-31

Symbiosis islands are integrative and conjugative mobile genetic elements that convert nonsymbiotic rhizobia into nitrogen-fixing symbionts of leguminous plants. Excision of the Mesorhizobium loti symbiosis island ICEMlSym(R7A) is indirectly activated by quorum sensing through TraR-dependent activation of the excisionase gene rdfS. Here we show that a +1 programmed ribosomal frameshift (PRF) fuses the coding sequences of two TraR-activated genes, msi172 and msi171, producing an activator of rdfS expression named Frameshifted excision activator (FseA). Mass-spectrometry and mutational analyses indicated that the PRF occurred through +1 slippage of the tRNA(phe) from UUU to UUC within a conserved msi172-encoded motif. FseA activated rdfS expression in the absence of ICEMlSym(R7A), suggesting that it directly activated rdfS transcription, despite being unrelated to any characterized DNA-binding proteins. Bacterial two-hybrid and gene-reporter assays demonstrated that FseA was also bound and inhibited by the ICEMlSym(R7A)-encoded quorum-sensing antiactivator QseM. Thus, activation of ICEMlSym(R7A) excision is counteracted by TraR antiactivation, ribosomal frameshifting, and FseA antiactivation. This robust suppression likely dampens the inherent biological noise present in the quorum-sensing autoinduction circuit and ensures that ICEMlSym(R7A) transfer only occurs in a subpopulation of cells in which both qseM expression is repressed and FseA is translated. The architecture of the ICEMlSym(R7A) transfer regulatory system provides an example of how a set of modular components have assembled through evolution to form a robust genetic toggle that regulates gene transcription and translation at both single-cell and cell-population levels.

Ribosomal frameshifting and dual-target antiactivation restrict quorum-sensing–activated transfer of a mobile genetic element

PubMed Central

Ramsay, Joshua P.; Tester, Laura G. L.; Major, Anthony S.; Sullivan, John T.; Edgar, Christina D.; Kleffmann, Torsten; Patterson-House, Jackson R.; Hall, Drew A.; Tate, Warren P.; Hynes, Michael F.; Ronson, Clive W.

2015-01-01

Symbiosis islands are integrative and conjugative mobile genetic elements that convert nonsymbiotic rhizobia into nitrogen-fixing symbionts of leguminous plants. Excision of the Mesorhizobium loti symbiosis island ICEMlSymR7A is indirectly activated by quorum sensing through TraR-dependent activation of the excisionase gene rdfS. Here we show that a +1 programmed ribosomal frameshift (PRF) fuses the coding sequences of two TraR-activated genes, msi172 and msi171, producing an activator of rdfS expression named Frameshifted excision activator (FseA). Mass-spectrometry and mutational analyses indicated that the PRF occurred through +1 slippage of the tRNAphe from UUU to UUC within a conserved msi172-encoded motif. FseA activated rdfS expression in the absence of ICEMlSymR7A, suggesting that it directly activated rdfS transcription, despite being unrelated to any characterized DNA-binding proteins. Bacterial two-hybrid and gene-reporter assays demonstrated that FseA was also bound and inhibited by the ICEMlSymR7A-encoded quorum-sensing antiactivator QseM. Thus, activation of ICEMlSymR7A excision is counteracted by TraR antiactivation, ribosomal frameshifting, and FseA antiactivation. This robust suppression likely dampens the inherent biological noise present in the quorum-sensing autoinduction circuit and ensures that ICEMlSymR7A transfer only occurs in a subpopulation of cells in which both qseM expression is repressed and FseA is translated. The architecture of the ICEMlSymR7A transfer regulatory system provides an example of how a set of modular components have assembled through evolution to form a robust genetic toggle that regulates gene transcription and translation at both single-cell and cell-population levels. PMID:25787256

Multi-focal control of mitochondrial gene expression by oncogenic MYC provides potential therapeutic targets in cancer

PubMed Central

Oran, Amanda R.; Adams, Clare M.; Zhang, Xiao-yong; Gennaro, Victoria J.; Pfeiffer, Harla K.; Mellert, Hestia S.; Seidel, Hans E.; Mascioli, Kirsten; Kaplan, Jordan; Gaballa, Mahmoud R.; Shen, Chen; Rigoutsos, Isidore; King, Michael P.; Cotney, Justin L.; Arnold, Jamie J.; Sharma, Suresh D.; Martinez, Ubaldo E.; Vakoc, Christopher R.; Chodosh, Lewis A.; Thompson, James E.; Bradner, James E.; Cameron, Craig E.; Shadel, Gerald S.; Eischen, Christine M.; McMahon, Steven B.

2016-01-01

Despite ubiquitous activation in human cancer, essential downstream effector pathways of the MYC transcription factor have been difficult to define and target. Using a structure/function-based approach, we identified the mitochondrial RNA polymerase (POLRMT) locus as a critical downstream target of MYC. The multifunctional POLRMT enzyme controls mitochondrial gene expression, a process required both for mitochondrial function and mitochondrial biogenesis. We further demonstrate that inhibition of this newly defined MYC effector pathway causes robust and selective tumor cell apoptosis, via an acute, checkpoint-like mechanism linked to aberrant electron transport chain complex assembly and mitochondrial reactive oxygen species (ROS) production. Fortuitously, MYC-dependent tumor cell death can be induced by inhibiting the mitochondrial gene expression pathway using a variety of strategies, including treatment with FDA-approved antibiotics. In vivo studies using a mouse model of Burkitt's Lymphoma provide pre-clinical evidence that these antibiotics can successfully block progression of MYC-dependent tumors. PMID:27590350

Multi-focal control of mitochondrial gene expression by oncogenic MYC provides potential therapeutic targets in cancer.

PubMed

Oran, Amanda R; Adams, Clare M; Zhang, Xiao-Yong; Gennaro, Victoria J; Pfeiffer, Harla K; Mellert, Hestia S; Seidel, Hans E; Mascioli, Kirsten; Kaplan, Jordan; Gaballa, Mahmoud R; Shen, Chen; Rigoutsos, Isidore; King, Michael P; Cotney, Justin L; Arnold, Jamie J; Sharma, Suresh D; Martinez-Outschoorn, Ubaldo E; Vakoc, Christopher R; Chodosh, Lewis A; Thompson, James E; Bradner, James E; Cameron, Craig E; Shadel, Gerald S; Eischen, Christine M; McMahon, Steven B

2016-11-08

Despite ubiquitous activation in human cancer, essential downstream effector pathways of the MYC transcription factor have been difficult to define and target. Using a structure/function-based approach, we identified the mitochondrial RNA polymerase (POLRMT) locus as a critical downstream target of MYC. The multifunctional POLRMT enzyme controls mitochondrial gene expression, a process required both for mitochondrial function and mitochondrial biogenesis. We further demonstrate that inhibition of this newly defined MYC effector pathway causes robust and selective tumor cell apoptosis, via an acute, checkpoint-like mechanism linked to aberrant electron transport chain complex assembly and mitochondrial reactive oxygen species (ROS) production. Fortuitously, MYC-dependent tumor cell death can be induced by inhibiting the mitochondrial gene expression pathway using a variety of strategies, including treatment with FDA-approved antibiotics. In vivo studies using a mouse model of Burkitt's Lymphoma provide pre-clinical evidence that these antibiotics can successfully block progression of MYC-dependent tumors.

Temperature regulates splicing efficiency of the cold-inducible RNA-binding protein gene Cirbp

PubMed Central

Gotic, Ivana; Omidi, Saeed; Fleury-Olela, Fabienne; Molina, Nacho; Naef, Felix; Schibler, Ueli

2016-01-01

In mammals, body temperature fluctuates diurnally around a mean value of 36°C–37°C. Despite the small differences between minimal and maximal values, body temperature rhythms can drive robust cycles in gene expression in cultured cells and, likely, animals. Here we studied the mechanisms responsible for the temperature-dependent expression of cold-inducible RNA-binding protein (CIRBP). In NIH3T3 fibroblasts exposed to simulated mouse body temperature cycles, Cirbp mRNA oscillates about threefold in abundance, as it does in mouse livers. This daily mRNA accumulation cycle is directly controlled by temperature oscillations and does not depend on the cells’ circadian clocks. Here we show that the temperature-dependent accumulation of Cirbp mRNA is controlled primarily by the regulation of splicing efficiency, defined as the fraction of Cirbp pre-mRNA processed into mature mRNA. As revealed by genome-wide “approach to steady-state” kinetics, this post-transcriptional mechanism is widespread in the temperature-dependent control of gene expression. PMID:27633015

Response to carbohydrate and fat refeeding in the expression of genes involved in nutrient partitioning and metabolism: striking effects on fibroblast growth factor-21 induction.

PubMed

Sánchez, J; Palou, A; Picó, C

2009-12-01

This study aimed to assess the effects of carbohydrate (CHO) and fat intake on the expression of key genes related with nutrient partitioning and metabolism in main tissues involved in energy metabolism (white adipose tissue, liver, and skeletal muscle). Rats were studied under different conditions: feeding state, 24 h fasting, and 12 h refeeding after 24 h fasting with isocaloric amounts of CHO or fat. Fat, but not CHO, refeeding was associated with an increase in serum and liver triglyceride content. Main changes in gene expression elicited by CHO compared with fat refeeding were: 1) higher expression levels of genes related with lipogenesis (PPARgamma2, ChREBP, FAS), glucose uptake and metabolism (GLUT4, HKII), fatty acid uptake (LPL, CD36), and lipolysis (ATGL, HSL) in white adipose tissue; 2) higher expression levels of genes related with lipogenesis (FAS, SCD1) but lower ones related with fatty acid uptake (CD36) and oxidation (PPARalpha, CPT1, PDK4) in liver; and 3) higher expression levels of GLUT4 but lower ones related with fatty acid oxidation (PDK4 and UCP3) in muscle. It is worth mentioning that both CHO and fat refeeding resulted in a robust increase in both hepatic mRNA and circulating levels of fibroblast growth factor-21, compared with fasted levels. In summary, these results, showing marked differences in gene expression after CHO and fat refeeding, can explain diet-associated differences in fuel handling and partitioning between tissues; in addition, a role of fibroblast growth factor-21 in metabolic adaptations, not only in the ketotic state but also to face an unbalanced nutritional situation, is suggested.

Comparative Transcriptome Analysis Reveals Different Molecular Mechanisms of Bacillus coagulans 2-6 Response to Sodium Lactate and Calcium Lactate during Lactic Acid Production

PubMed Central

Qin, Jiayang; Wang, Xiuwen; Wang, Landong; Zhu, Beibei; Zhang, Xiaohua; Yao, Qingshou; Xu, Ping

2015-01-01

Lactate production is enhanced by adding calcium carbonate or sodium hydroxide during fermentation. However, Bacillus coagulans 2-6 can produce more than 180 g/L L-lactic acid when calcium lactate is accumulated, but less than 120 g/L L-lactic acid when sodium lactate is formed. The molecular mechanisms by which B. coagulans responds to calcium lactate and sodium lactate remain unclear. In this study, comparative transcriptomic methods based on high-throughput RNA sequencing were applied to study gene expression changes in B. coagulans 2-6 cultured in non-stress, sodium lactate stress and calcium lactate stress conditions. Gene expression profiling identified 712 and 1213 significantly regulated genes in response to calcium lactate stress and sodium lactate stress, respectively. Gene ontology assignments of the differentially expressed genes were performed. KEGG pathway enrichment analysis revealed that ‘ATP-binding cassette transporters’ were significantly affected by calcium lactate stress, and ‘amino sugar and nucleotide sugar metabolism’ was significantly affected by sodium lactate stress. It was also found that lactate fermentation was less affected by calcium lactate stress than by sodium lactate stress. Sodium lactate stress had negative effect on the expression of ‘glycolysis/gluconeogenesis’ genes but positive effect on the expression of ‘citrate cycle (TCA cycle)’ genes. However, calcium lactate stress had positive influence on the expression of ‘glycolysis/gluconeogenesis’ genes and had minor influence on ‘citrate cycle (TCA cycle)’ genes. Thus, our findings offer new insights into the responses of B. coagulans to different lactate stresses. Notably, our RNA-seq dataset constitute a robust database for investigating the functions of genes induced by lactate stress in the future and identify potential targets for genetic engineering to further improve L-lactic acid production by B. coagulans. PMID:25875592

Characterisation, analysis of expression and localisation of circadian clock genes from the perspective of photoperiodism in the aphid Acyrthosiphon pisum.

PubMed

Barberà, Miquel; Collantes-Alegre, Jorge Mariano; Martínez-Torres, David

2017-04-01

Aphids are typical photoperiodic insects that switch from viviparous parthenogenetic reproduction typical of long day seasons to oviparous sexual reproduction triggered by the shortening of photoperiod in autumn yielding an overwintering egg in which an embryonic diapause takes place. While the involvement of the circadian clock genes in photoperiodism in mammals is well established, there is still some controversy on their participation in insects. The availability of the genome of the pea aphid Acyrthosiphon pisum places this species as an excellent model to investigate the involvement of the circadian system in the aphid seasonal response. In the present report, we have advanced in the characterisation of the circadian clock genes and showed that these genes display extensive alternative splicing. Moreover, the expression of circadian clock genes, analysed at different moments of the day, showed a robust cycling of central clock genes period and timeless. Furthermore, the rhythmic expression of these genes was shown to be rapidly dampened under DD (continuous darkness conditions), thus supporting the model of a seasonal response based on a heavily dampened circadian oscillator. Additionally, increased expression of some of the circadian clock genes under short-day conditions suggest their involvement in the induction of the aphid seasonal response. Finally, in situ localisation of transcripts of genes period and timeless in the aphid brain revealed the site of clock neurons for the first time in aphids. Two groups of clock cells were identified: the Dorsal Neurons (DN) and the Lateral Neurons (LN), both in the protocerebrum. Copyright © 2017 Elsevier Ltd. All rights reserved.

Characterization of the novel tumor-suppressor gene CCDC67 in papillary thyroid carcinoma.

PubMed

Yin, De Tao; Xu, Jianhui; Lei, Mengyuan; Li, Hongqiang; Wang, Yongfei; Liu, Zhen; Zhou, Yubing; Xing, Mingzhao

2016-02-02

Some studies showed an association of coiled-coil domain-containing (CCDC) genes with cancers. Our previous limited data specifically suggested a possible pathogenic role of CCDC67 in papillary thyroid cancer (PTC), but this has not been firmly established. The present study was to further investigate and establish this role of CCDC67 in PTC. The expression of CCDC67, both at mRNA and protein levels, was sharply down-regulated in PTC compared with normal thyroid tissues. Lower CCDC67 expression was significantly associated with aggressive tumor behaviors, such as advanced tumor stages and lymph node metastasis, as well as BRAF mutation. Introduced expression of CCDC67 in TPC-1 cells robustly inhibited cell proliferation, colony formation and migration, induced G1 phase cell cycle arrest, and increased cell apoptosis. Primary PTC tumors and matched normal thyroid tissues were obtained from 200 unselected patients at the initial surgery for detection of CCDC67 mRNA and protein by RT-PCR and Western blotting analyses, respectively. Genomic DNA sequencing was performed to detect BRAF mutation in PTC tumors. Clinicopathological data were retrospectively reviewed for correlation analyses. PTC cell line TPC-1 with stable transfection of CCDC67 was used to investigate the functions of CCDC67. This large study demonstrates down-regulation of CCDC67 in PTC, an inverse relationship between CCDC67 expression and PTC aggressiveness and BRAF mutation, and a robust inhibitory effect of CCDC67 on PTC cellular activities. These results are consistent with CCDC67 being a novel and impaired tumor suppressor gene in PTC, providing important prognostic and therapeutic implications for this cancer.

Modelling the influence of parental effects on gene-network evolution.

PubMed

Odorico, Andreas; Rünneburger, Estelle; Le Rouzic, Arnaud

2018-05-01

Understanding the importance of nongenetic heredity in the evolutionary process is a major topic in modern evolutionary biology. We modified a classical gene-network model by allowing parental transmission of gene expression and studied its evolutionary properties through individual-based simulations. We identified ontogenetic time (i.e. the time gene networks have to stabilize before being submitted to natural selection) as a crucial factor in determining the evolutionary impact of this phenotypic inheritance. Indeed, fast-developing organisms display enhanced adaptation and greater robustness to mutations when evolving in presence of nongenetic inheritance (NGI). In contrast, in our model, long development reduces the influence of the inherited state of the gene network. NGI thus had a negligible effect on the evolution of gene networks when the speed at which transcription levels reach equilibrium is not constrained. Nevertheless, simulations show that intergenerational transmission of the gene-network state negatively affects the evolution of robustness to environmental disturbances for either fast- or slow-developing organisms. Therefore, these results suggest that the evolutionary consequences of NGI might not be sought only in the way species respond to selection, but also on the evolution of emergent properties (such as environmental and genetic canalization) in complex genetic architectures. © 2018 European Society For Evolutionary Biology. Journal of Evolutionary Biology © 2018 European Society For Evolutionary Biology.

The food additive vanillic acid controls transgene expression in mammalian cells and mice.

PubMed

Gitzinger, Marc; Kemmer, Christian; Fluri, David A; El-Baba, Marie Daoud; Weber, Wilfried; Fussenegger, Martin

2012-03-01

Trigger-inducible transcription-control devices that reversibly fine-tune transgene expression in response to molecular cues have significantly advanced the rational reprogramming of mammalian cells. When designed for use in future gene- and cell-based therapies the trigger molecules have to be carefully chosen in order to provide maximum specificity, minimal side-effects and optimal pharmacokinetics in a mammalian organism. Capitalizing on control components that enable Caulobacter crescentus to metabolize vanillic acid originating from lignin degradation that occurs in its oligotrophic freshwater habitat, we have designed synthetic devices that specifically adjust transgene expression in mammalian cells when exposed to vanillic acid. Even in mice transgene expression was robust, precise and tunable in response to vanillic acid. As a licensed food additive that is regularly consumed by humans via flavoured convenience food and specific fresh vegetable and fruits, vanillic acid can be considered as a safe trigger molecule that could be used for diet-controlled transgene expression in future gene- and cell-based therapies.

mQTL-seq delineates functionally relevant candidate gene harbouring a major QTL regulating pod number in chickpea

PubMed Central

Das, Shouvik; Singh, Mohar; Srivastava, Rishi; Bajaj, Deepak; Saxena, Maneesha S.; Rana, Jai C.; Bansal, Kailash C.; Tyagi, Akhilesh K.; Parida, Swarup K.

2016-01-01

The present study used a whole-genome, NGS resequencing-based mQTL-seq (multiple QTL-seq) strategy in two inter-specific mapping populations (Pusa 1103 × ILWC 46 and Pusa 256 × ILWC 46) to scan the major genomic region(s) underlying QTL(s) governing pod number trait in chickpea. Essentially, the whole-genome resequencing of low and high pod number-containing parental accessions and homozygous individuals (constituting bulks) from each of these two mapping populations discovered >8 million high-quality homozygous SNPs with respect to the reference kabuli chickpea. The functional significance of the physically mapped SNPs was apparent from the identified 2,264 non-synonymous and 23,550 regulatory SNPs, with 8–10% of these SNPs-carrying genes corresponding to transcription factors and disease resistance-related proteins. The utilization of these mined SNPs in Δ (SNP index)-led QTL-seq analysis and their correlation between two mapping populations based on mQTL-seq, narrowed down two (CaqaPN4.1: 867.8 kb and CaqaPN4.2: 1.8 Mb) major genomic regions harbouring robust pod number QTLs into the high-resolution short QTL intervals (CaqbPN4.1: 637.5 kb and CaqbPN4.2: 1.28 Mb) on chickpea chromosome 4. The integration of mQTL-seq-derived one novel robust QTL with QTL region-specific association analysis delineated the regulatory (C/T) and coding (C/A) SNPs-containing one pentatricopeptide repeat (PPR) gene at a major QTL region regulating pod number in chickpea. This target gene exhibited anther, mature pollen and pod-specific expression, including pronounced higher up-regulated (∼3.5-folds) transcript expression in high pod number-containing parental accessions and homozygous individuals of two mapping populations especially during pollen and pod development. The proposed mQTL-seq-driven combinatorial strategy has profound efficacy in rapid genome-wide scanning of potential candidate gene(s) underlying trait-associated high-resolution robust QTL(s), thereby expediting genomics-assisted breeding and genetic enhancement of crop plants, including chickpea. PMID:26685680

Methodological study of affine transformations of gene expression data with proposed robust non-parametric multi-dimensional normalization method.

PubMed

Bengtsson, Henrik; Hössjer, Ola

2006-03-01

Low-level processing and normalization of microarray data are most important steps in microarray analysis, which have profound impact on downstream analysis. Multiple methods have been suggested to date, but it is not clear which is the best. It is therefore important to further study the different normalization methods in detail and the nature of microarray data in general. A methodological study of affine models for gene expression data is carried out. Focus is on two-channel comparative studies, but the findings generalize also to single- and multi-channel data. The discussion applies to spotted as well as in-situ synthesized microarray data. Existing normalization methods such as curve-fit ("lowess") normalization, parallel and perpendicular translation normalization, and quantile normalization, but also dye-swap normalization are revisited in the light of the affine model and their strengths and weaknesses are investigated in this context. As a direct result from this study, we propose a robust non-parametric multi-dimensional affine normalization method, which can be applied to any number of microarrays with any number of channels either individually or all at once. A high-quality cDNA microarray data set with spike-in controls is used to demonstrate the power of the affine model and the proposed normalization method. We find that an affine model can explain non-linear intensity-dependent systematic effects in observed log-ratios. Affine normalization removes such artifacts for non-differentially expressed genes and assures that symmetry between negative and positive log-ratios is obtained, which is fundamental when identifying differentially expressed genes. In addition, affine normalization makes the empirical distributions in different channels more equal, which is the purpose of quantile normalization, and may also explain why dye-swap normalization works or fails. All methods are made available in the aroma package, which is a platform-independent package for R.

Assessing the utility of gene co-expression stability in combination with correlation in the analysis of protein-protein interaction networks

PubMed Central

2011-01-01

Background Gene co-expression, in the form of a correlation coefficient, has been valuable in the analysis, classification and prediction of protein-protein interactions. However, it is susceptible to bias from a few samples having a large effect on the correlation coefficient. Gene co-expression stability is a means of quantifying this bias, with high stability indicating robust, unbiased co-expression correlation coefficients. We assess the utility of gene co-expression stability as an additional measure to support the co-expression correlation in the analysis of protein-protein interaction networks. Results We studied the patterns of co-expression correlation and stability in interacting proteins with respect to their interaction promiscuity, levels of intrinsic disorder, and essentiality or disease-relatedness. Co-expression stability, along with co-expression correlation, acts as a better classifier of hub proteins in interaction networks, than co-expression correlation alone, enabling the identification of a class of hubs that are functionally distinct from the widely accepted transient (date) and obligate (party) hubs. Proteins with high levels of intrinsic disorder have low co-expression correlation and high stability with their interaction partners suggesting their involvement in transient interactions, except for a small group that have high co-expression correlation and are typically subunits of stable complexes. Similar behavior was seen for disease-related and essential genes. Interacting proteins that are both disordered have higher co-expression stability than ordered protein pairs. Using co-expression correlation and stability, we found that transient interactions are more likely to occur between an ordered and a disordered protein while obligate interactions primarily occur between proteins that are either both ordered, or disordered. Conclusions We observe that co-expression stability shows distinct patterns in structurally and functionally different groups of proteins and interactions. We conclude that it is a useful and important measure to be used in concert with gene co-expression correlation for further insights into the characteristics of proteins in the context of their interaction network. PMID:22369639

Gene expression markers of age-related inflammation in two human cohorts.

PubMed

Pilling, Luke C; Joehanes, Roby; Melzer, David; Harries, Lorna W; Henley, William; Dupuis, Josée; Lin, Honghuang; Mitchell, Marcus; Hernandez, Dena; Ying, Sai-Xia; Lunetta, Kathryn L; Benjamin, Emelia J; Singleton, Andrew; Levy, Daniel; Munson, Peter; Murabito, Joanne M; Ferrucci, Luigi

2015-10-01

Chronically elevated circulating inflammatory markers are common in older persons but mechanisms are unclear. Many blood transcripts (>800 genes) are associated with interleukin-6 protein levels (IL6) independent of age. We aimed to identify gene transcripts statistically mediating, as drivers or responders, the increasing levels of IL6 protein in blood at older ages. Blood derived in-vivo RNA from the Framingham Heart Study (FHS, n=2422, ages 40-92 yrs) and InCHIANTI study (n=694, ages 30-104 yrs), with Affymetrix and Illumina expression arrays respectively (>17,000 genes tested), were tested for statistical mediation of the age-IL6 association using resampling techniques, adjusted for confounders and multiple testing. In FHS, IL6 expression was not associated with IL6 protein levels in blood. 102 genes (0.6% of 17,324 expressed) statistically mediated the age-IL6 association of which 25 replicated in InCHIANTI (including 5 of the 10 largest effect genes). The largest effect gene (SLC4A10, coding for NCBE, a sodium bicarbonate transporter) mediated 19% (adjusted CI 8.9 to 34.1%) and replicated by PCR in InCHIANTI (n=194, 35.6% mediated, p=0.01). Other replicated mediators included PRF1 (perforin, a cytolytic protein in cytotoxic T lymphocytes and NK cells) and IL1B (Interleukin 1 beta): few other cytokines were significant mediators. This transcriptome-wide study on human blood identified a small distinct set of genes that statistically mediate the age-IL6 association. Findings are robust across two cohorts and different expression technologies. Raised IL6 levels may not derive from circulating white cells in age related inflammation. Published by Elsevier Inc.

Fyn-Dependent Gene Networks in Acute Ethanol Sensitivity

PubMed Central

Farris, Sean P.; Miles, Michael F.

2013-01-01

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

Robust gene selection methods using weighting schemes for microarray data analysis.

PubMed

Kang, Suyeon; Song, Jongwoo

2017-09-02

A common task in microarray data analysis is to identify informative genes that are differentially expressed between two different states. Owing to the high-dimensional nature of microarray data, identification of significant genes has been essential in analyzing the data. However, the performances of many gene selection techniques are highly dependent on the experimental conditions, such as the presence of measurement error or a limited number of sample replicates. We have proposed new filter-based gene selection techniques, by applying a simple modification to significance analysis of microarrays (SAM). To prove the effectiveness of the proposed method, we considered a series of synthetic datasets with different noise levels and sample sizes along with two real datasets. The following findings were made. First, our proposed methods outperform conventional methods for all simulation set-ups. In particular, our methods are much better when the given data are noisy and sample size is small. They showed relatively robust performance regardless of noise level and sample size, whereas the performance of SAM became significantly worse as the noise level became high or sample size decreased. When sufficient sample replicates were available, SAM and our methods showed similar performance. Finally, our proposed methods are competitive with traditional methods in classification tasks for microarrays. The results of simulation study and real data analysis have demonstrated that our proposed methods are effective for detecting significant genes and classification tasks, especially when the given data are noisy or have few sample replicates. By employing weighting schemes, we can obtain robust and reliable results for microarray data analysis.

Identification and Validation of a Diagnostic and Prognostic Multi-Gene Biomarker Panel for Pancreatic Ductal Adenocarcinoma.

PubMed

Klett, Hagen; Fuellgraf, Hannah; Levit-Zerdoun, Ella; Hussung, Saskia; Kowar, Silke; Küsters, Simon; Bronsert, Peter; Werner, Martin; Wittel, Uwe; Fritsch, Ralph; Busch, Hauke; Boerries, Melanie

2018-01-01

Late diagnosis and systemic dissemination essentially contribute to the invariably poor prognosis of pancreatic ductal adenocarcinoma (PDAC). Therefore, the development of diagnostic biomarkers for PDAC are urgently needed to improve patient stratification and outcome in the clinic. By studying the transcriptomes of independent PDAC patient cohorts of tumor and non-tumor tissues, we identified 81 robustly regulated genes, through a novel, generally applicable meta-analysis. Using consensus clustering on co-expression values revealed four distinct clusters with genes originating from exocrine/endocrine pancreas, stromal and tumor cells. Three clusters were strongly associated with survival of PDAC patients based on TCGA database underlining the prognostic potential of the identified genes. With the added information of impact of survival and the robustness within the meta-analysis, we extracted a 17-gene subset for further validation. We show that it did not only discriminate PDAC from non-tumor tissue and stroma in fresh-frozen as well as formalin-fixed paraffin embedded samples, but also detected pancreatic precursor lesions and singled out pancreatitis samples. Moreover, the classifier discriminated PDAC from other cancers in the TCGA database. In addition, we experimentally validated the classifier in PDAC patients on transcript level using qPCR and exemplify the usage on protein level for three proteins (AHNAK2, LAMC2, TFF1) using immunohistochemistry and for two secreted proteins (TFF1, SERPINB5) using ELISA-based protein detection in blood-plasma. In conclusion, we present a novel robust diagnostic and prognostic gene signature for PDAC with future potential applicability in the clinic.

Identification and Validation of a Diagnostic and Prognostic Multi-Gene Biomarker Panel for Pancreatic Ductal Adenocarcinoma

PubMed Central

Klett, Hagen; Fuellgraf, Hannah; Levit-Zerdoun, Ella; Hussung, Saskia; Kowar, Silke; Küsters, Simon; Bronsert, Peter; Werner, Martin; Wittel, Uwe; Fritsch, Ralph; Busch, Hauke; Boerries, Melanie

2018-01-01

Late diagnosis and systemic dissemination essentially contribute to the invariably poor prognosis of pancreatic ductal adenocarcinoma (PDAC). Therefore, the development of diagnostic biomarkers for PDAC are urgently needed to improve patient stratification and outcome in the clinic. By studying the transcriptomes of independent PDAC patient cohorts of tumor and non-tumor tissues, we identified 81 robustly regulated genes, through a novel, generally applicable meta-analysis. Using consensus clustering on co-expression values revealed four distinct clusters with genes originating from exocrine/endocrine pancreas, stromal and tumor cells. Three clusters were strongly associated with survival of PDAC patients based on TCGA database underlining the prognostic potential of the identified genes. With the added information of impact of survival and the robustness within the meta-analysis, we extracted a 17-gene subset for further validation. We show that it did not only discriminate PDAC from non-tumor tissue and stroma in fresh-frozen as well as formalin-fixed paraffin embedded samples, but also detected pancreatic precursor lesions and singled out pancreatitis samples. Moreover, the classifier discriminated PDAC from other cancers in the TCGA database. In addition, we experimentally validated the classifier in PDAC patients on transcript level using qPCR and exemplify the usage on protein level for three proteins (AHNAK2, LAMC2, TFF1) using immunohistochemistry and for two secreted proteins (TFF1, SERPINB5) using ELISA-based protein detection in blood-plasma. In conclusion, we present a novel robust diagnostic and prognostic gene signature for PDAC with future potential applicability in the clinic. PMID:29675033

Structural and Functional Characterization of a Caenorhabditis elegans Genetic Interaction Network within Pathways

PubMed Central

Boucher, Benjamin; Lee, Anna Y.; Hallett, Michael; Jenna, Sarah

2016-01-01

A genetic interaction (GI) is defined when the mutation of one gene modifies the phenotypic expression associated with the mutation of a second gene. Genome-wide efforts to map GIs in yeast revealed structural and functional properties of a GI network. This provided insights into the mechanisms underlying the robustness of yeast to genetic and environmental insults, and also into the link existing between genotype and phenotype. While a significant conservation of GIs and GI network structure has been reported between distant yeast species, such a conservation is not clear between unicellular and multicellular organisms. Structural and functional characterization of a GI network in these latter organisms is consequently of high interest. In this study, we present an in-depth characterization of ~1.5K GIs in the nematode Caenorhabditis elegans. We identify and characterize six distinct classes of GIs by examining a wide-range of structural and functional properties of genes and network, including co-expression, phenotypical manifestations, relationship with protein-protein interaction dense subnetworks (PDS) and pathways, molecular and biological functions, gene essentiality and pleiotropy. Our study shows that GI classes link genes within pathways and display distinctive properties, specifically towards PDS. It suggests a model in which pathways are composed of PDS-centric and PDS-independent GIs coordinating molecular machines through two specific classes of GIs involving pleiotropic and non-pleiotropic connectors. Our study provides the first in-depth characterization of a GI network within pathways of a multicellular organism. It also suggests a model to understand better how GIs control system robustness and evolution. PMID:26871911

Stabilization of Foxp3 expression by CRISPR-dCas9-based epigenome editing in mouse primary T cells.

PubMed

Okada, Masahiro; Kanamori, Mitsuhiro; Someya, Kazue; Nakatsukasa, Hiroko; Yoshimura, Akihiko

2017-01-01

Epigenome editing is expected to manipulate transcription and cell fates and to elucidate the gene expression mechanisms in various cell types. For functional epigenome editing, assessing the chromatin context-dependent activity of artificial epigenetic modifier is required. In this study, we applied clustered regularly interspaced short palindromic repeats (CRISPR)-dCas9-based epigenome editing to mouse primary T cells, focusing on the Forkhead box P3 (Foxp3) gene locus, a master transcription factor of regulatory T cells (Tregs). The Foxp3 gene locus is regulated by combinatorial epigenetic modifications, which determine the Foxp3 expression. Foxp3 expression is unstable in transforming growth factor beta (TGF-β)-induced Tregs (iTregs), while stable in thymus-derived Tregs (tTregs). To stabilize Foxp3 expression in iTregs, we introduced dCas9-TET1CD (dCas9 fused to the catalytic domain (CD) of ten-eleven translocation dioxygenase 1 (TET1), methylcytosine dioxygenase) and dCas9-p300CD (dCas9 fused to the CD of p300, histone acetyltransferase) with guide RNAs (gRNAs) targeted to the Foxp3 gene locus. Although dCas9-TET1CD induced partial demethylation in enhancer region called conserved non-coding DNA sequences 2 (CNS2), robust Foxp3 stabilization was not observed. In contrast, dCas9-p300CD targeted to the promoter locus partly maintained Foxp3 transcription in cultured and primary T cells even under inflammatory conditions in vitro. Furthermore, dCas9-p300CD promoted expression of Treg signature genes and enhanced suppression activity in vitro. Our results showed that artificial epigenome editing modified the epigenetic status and gene expression of the targeted loci, and engineered cellular functions in conjunction with endogenous epigenetic modification, suggesting effective usage of these technologies, which help elucidate the relationship between chromatin states and gene expression.

Burkholderia mallei and Burkholderia pseudomallei Cluster 1 Type VI Secretion System Gene Expression Is Negatively Regulated by Iron and Zinc

PubMed Central

Burtnick, Mary N.; Brett, Paul J.

2013-01-01

Burkholderia mallei is a facultative intracellular pathogen that causes glanders in humans and animals. Previous studies have demonstrated that the cluster 1 type VI secretion system (T6SS-1) expressed by this organism is essential for virulence in hamsters and is positively regulated by the VirAG two-component system. Recently, we have shown that T6SS-1 gene expression is up-regulated following internalization of this pathogen into phagocytic cells and that this system promotes multinucleated giant cell formation in infected tissue culture monolayers. In the present study, we further investigated the complex regulation of this important virulence factor. To assess T6SS-1 expression, B. mallei strains were cultured in various media conditions and Hcp1 production was analyzed by Western immunoblotting. Transcript levels of several VirAG-regulated genes (bimA, tssA, hcp1 and tssM) were also determined using quantitative real time PCR. Consistent with previous observations, T6SS-1 was not expressed during growth of B. mallei in rich media. Curiously, growth of the organism in minimal media (M9G) or minimal media plus casamino acids (M9CG) facilitated robust expression of T6SS-1 genes whereas growth in minimal media plus tryptone (M9TG) did not. Investigation of this phenomenon confirmed a regulatory role for VirAG in this process. Additionally, T6SS-1 gene expression was significantly down-regulated by the addition of iron and zinc to M9CG. Other genes under the control of VirAG did not appear to be as tightly regulated by these divalent metals. Similar results were observed for B. pseudomallei, but not for B. thailandensis. Collectively, our findings indicate that in addition to being positively regulated by VirAG, B. mallei and B. pseudomallei T6SS-1 gene expression is negatively regulated by iron and zinc. PMID:24146925

Burkholderia mallei and Burkholderia pseudomallei cluster 1 type VI secretion system gene expression is negatively regulated by iron and zinc.

PubMed

Burtnick, Mary N; Brett, Paul J

2013-01-01

Burkholderia mallei is a facultative intracellular pathogen that causes glanders in humans and animals. Previous studies have demonstrated that the cluster 1 type VI secretion system (T6SS-1) expressed by this organism is essential for virulence in hamsters and is positively regulated by the VirAG two-component system. Recently, we have shown that T6SS-1 gene expression is up-regulated following internalization of this pathogen into phagocytic cells and that this system promotes multinucleated giant cell formation in infected tissue culture monolayers. In the present study, we further investigated the complex regulation of this important virulence factor. To assess T6SS-1 expression, B. mallei strains were cultured in various media conditions and Hcp1 production was analyzed by Western immunoblotting. Transcript levels of several VirAG-regulated genes (bimA, tssA, hcp1 and tssM) were also determined using quantitative real time PCR. Consistent with previous observations, T6SS-1 was not expressed during growth of B. mallei in rich media. Curiously, growth of the organism in minimal media (M9G) or minimal media plus casamino acids (M9CG) facilitated robust expression of T6SS-1 genes whereas growth in minimal media plus tryptone (M9TG) did not. Investigation of this phenomenon confirmed a regulatory role for VirAG in this process. Additionally, T6SS-1 gene expression was significantly down-regulated by the addition of iron and zinc to M9CG. Other genes under the control of VirAG did not appear to be as tightly regulated by these divalent metals. Similar results were observed for B. pseudomallei, but not for B. thailandensis. Collectively, our findings indicate that in addition to being positively regulated by VirAG, B. mallei and B. pseudomallei T6SS-1 gene expression is negatively regulated by iron and zinc.

The Regulatory Factor ZFHX3 Modifies Circadian Function in SCN via an AT Motif-Driven Axis

PubMed Central

Parsons, Michael J.; Brancaccio, Marco; Sethi, Siddharth; Maywood, Elizabeth S.; Satija, Rahul; Edwards, Jessica K.; Jagannath, Aarti; Couch, Yvonne; Finelli, Mattéa J.; Smyllie, Nicola J.; Esapa, Christopher; Butler, Rachel; Barnard, Alun R.; Chesham, Johanna E.; Saito, Shoko; Joynson, Greg; Wells, Sara; Foster, Russell G.; Oliver, Peter L.; Simon, Michelle M.; Mallon, Ann-Marie; Hastings, Michael H.; Nolan, Patrick M.

2015-01-01

Summary We identified a dominant missense mutation in the SCN transcription factor Zfhx3, termed short circuit (Zfhx3Sci), which accelerates circadian locomotor rhythms in mice. ZFHX3 regulates transcription via direct interaction with predicted AT motifs in target genes. The mutant protein has a decreased ability to activate consensus AT motifs in vitro. Using RNA sequencing, we found minimal effects on core clock genes in Zfhx3Sci/+ SCN, whereas the expression of neuropeptides critical for SCN intercellular signaling was significantly disturbed. Moreover, mutant ZFHX3 had a decreased ability to activate AT motifs in the promoters of these neuropeptide genes. Lentiviral transduction of SCN slices showed that the ZFHX3-mediated activation of AT motifs is circadian, with decreased amplitude and robustness of these oscillations in Zfhx3Sci/+ SCN slices. In conclusion, by cloning Zfhx3Sci, we have uncovered a circadian transcriptional axis that determines the period and robustness of behavioral and SCN molecular rhythms. PMID:26232227

Genome-scale transcriptional activation by an engineered CRISPR-Cas9 complex.

PubMed

Konermann, Silvana; Brigham, Mark D; Trevino, Alexandro E; Joung, Julia; Abudayyeh, Omar O; Barcena, Clea; Hsu, Patrick D; Habib, Naomi; Gootenberg, Jonathan S; Nishimasu, Hiroshi; Nureki, Osamu; Zhang, Feng

2015-01-29

Systematic interrogation of gene function requires the ability to perturb gene expression in a robust and generalizable manner. Here we describe structure-guided engineering of a CRISPR-Cas9 complex to mediate efficient transcriptional activation at endogenous genomic loci. We used these engineered Cas9 activation complexes to investigate single-guide RNA (sgRNA) targeting rules for effective transcriptional activation, to demonstrate multiplexed activation of ten genes simultaneously, and to upregulate long intergenic non-coding RNA (lincRNA) transcripts. We also synthesized a library consisting of 70,290 guides targeting all human RefSeq coding isoforms to screen for genes that, upon activation, confer resistance to a BRAF inhibitor. The top hits included genes previously shown to be able to confer resistance, and novel candidates were validated using individual sgRNA and complementary DNA overexpression. A gene expression signature based on the top screening hits correlated with markers of BRAF inhibitor resistance in cell lines and patient-derived samples. These results collectively demonstrate the potential of Cas9-based activators as a powerful genetic perturbation technology.

Robustness of synthetic oscillators in growing and dividing cells

NASA Astrophysics Data System (ADS)

Paijmans, Joris; Lubensky, David K.; Rein ten Wolde, Pieter

2017-05-01

Synthetic biology sets out to implement new functions in cells, and to develop a deeper understanding of biological design principles. Elowitz and Leibler [Nature (London) 403, 335 (2000), 10.1038/35002125] showed that by rational design of the reaction network, and using existing biological components, they could create a network that exhibits periodic gene expression, dubbed the repressilator. More recently, Stricker et al. [Nature (London) 456, 516 (2008), 10.1038/nature07389] presented another synthetic oscillator, called the dual-feedback oscillator, which is more stable. Detailed studies have been carried out to determine how the stability of these oscillators is affected by the intrinsic noise of the interactions between the components and the stochastic expression of their genes. However, as all biological oscillators reside in growing and dividing cells, an important question is how these oscillators are perturbed by the cell cycle. In previous work we showed that the periodic doubling of the gene copy numbers due to DNA replication can couple not only natural, circadian oscillators to the cell cycle [Paijmans et al., Proc. Natl. Acad. Sci. (USA) 113, 4063 (2016), 10.1073/pnas.1507291113], but also these synthetic oscillators. Here we expand this study. We find that the strength of the locking between oscillators depends not only on the positions of the genes on the chromosome, but also on the noise in the timing of gene replication: noise tends to weaken the coupling. Yet, even in the limit of high levels of noise in the replication times of the genes, both synthetic oscillators show clear signatures of locking to the cell cycle. This work enhances our understanding of the design of robust biological oscillators inside growing and diving cells.

Active FOXO1 is a Key Determinant of Isoform-Specific Progesterone Receptor Transactivation and Senescence Programming

PubMed Central

Diep, Caroline H.; Knutson, Todd P.; Lange, Carol A.

2015-01-01

Progesterone promotes differentiation coupled to proliferation and pro-survival in the breast, but inhibits estrogen-driven growth in the reproductive tract and ovaries. Herein, it is demonstrated, using progesterone receptor (PR) isoform-specific ovarian cancer model systems, that PR-A and PR-B promote distinct gene expression profiles that differ from PR-driven genes in breast cancer cells. In ovarian cancer models, PR-A primarily regulates genes independently of progestin, while PR-B is the dominant ligand-dependent isoform. Notably, FOXO1 and the PR/FOXO1 target-gene p21 (CDKN1A) are repressed by PR-A, but induced by PR-B. In the presence of progestin, PR-B, but not PR-A, robustly induced cellular senescence via FOXO1-dependent induction of p21 and p15 (CDKN2B). Chromatin immunoprecipitation (ChIP) assays performed on PR-isoform specific cells demonstrated that while each isoform is recruited to the same PRE-containing region of the p21 promoter in response to progestin, only PR-B elicits active chromatin marks. Overexpression of constitutively active FOXO1 in PR-A-expressing cells conferred robust ligand-dependent upregulation of the PR-B target genes GZMA, IGFBP1, and p21, and induced cellular senescence. In the presence of endogenous active FOXO1, PR-A was phosphorylated on Ser294 and transactivated PR-B at PR-B target genes; these events were blocked by the FOXO1 inhibitor (AS1842856). PR isoform-specific regulation of the FOXO1/p21 axis recapitulated in human primary ovarian tumor explants treated with progestin; loss of progestin sensitivity correlated with high AKT activity. PMID:26577046

Sexually dimorphic expression of the genes encoding ribosomal proteins L17 and L37 in the song control nuclei of juvenile zebra finches

PubMed Central

Tang, Yu Ping; Wade, Juli

2010-01-01

Studies evaluating the role of steroid hormones in sexual differentiation of the zebra finch song system have produced complicated and at times paradoxical results, and indicate that additional factors may be critical. Therefore, in a previous study we initiated a screen for differential gene expression in the telencephalon of developing male and female zebra finches. The use of cDNA microarrays and real-time quantitative PCR revealed increased expression of the genes encoding ribosomal proteins L17 and L37 (RPL17 and RPL37) in the male forebrain as a whole. Preliminary in situ hybridization data then indicated enhanced expression of both these genes in song control regions. Two experiments in the present study quantified the mRNA expression. The first utilized 25-day-old male and female zebra finches. The second compared a separate set of juveniles to adults of both sexes to both re-confirm enhanced expression in juvenile males and to determine whether it is limited to developing animals. In Experiment 1, males exhibited increased expression of both RPL17 and RPL37 compared to females in Area X, the robust nucleus of the arcopallium (RA), and the ventral ventricular zone (VVZ), which may provide neurons to Area X. Experiment 2 replicated the sexually dimorphic expression of these genes at post-hatching day 25, and documented that the sex differences are eliminated or greatly reduced in adults. The results are consistent with the idea that these ribosomal proteins may influence sexual differentiation of Area X and RA, potentially regulating the genesis and/or survival of neurons. PMID:16938280

Sexually dimorphic expression of the genes encoding ribosomal proteins L17 and L37 in the song control nuclei of juvenile zebra finches.

PubMed

Tang, Yu Ping; Wade, Juli

2006-12-18

Studies evaluating the role of steroid hormones in sexual differentiation of the zebra finch song system have produced complicated and at times paradoxical results, and indicate that additional factors may be critical. Therefore, in a previous study we initiated a screen for differential gene expression in the telencephalon of developing male and female zebra finches. The use of cDNA microarrays and real-time quantitative PCR revealed increased expression of the genes encoding ribosomal proteins L17 and L37 (RPL17 and RPL37) in the male forebrain as a whole. Preliminary in situ hybridization data then indicated enhanced expression of both these genes in song control regions. Two experiments in the present study quantified the mRNA expression. The first utilized 25-day-old male and female zebra finches. The second compared a separate set of juveniles to adults of both sexes to both re-confirm enhanced expression in juvenile males and to determine whether it is limited to developing animals. In Experiment 1, males exhibited increased expression of both RPL17 and RPL37 compared to females in Area X, the robust nucleus of the arcopallium (RA), and the ventral ventricular zone (VVZ), which may provide neurons to Area X. Experiment 2 replicated the sexually dimorphic expression of these genes at post-hatching day 25, and documented that the sex differences are eliminated or greatly reduced in adults. The results are consistent with the idea that these ribosomal proteins may influence sexual differentiation of Area X and RA, potentially regulating the genesis and/or survival of neurons.

Genome-wide patterns of promoter sharing and co-expression in bovine skeletal muscle.

PubMed

Gu, Quan; Nagaraj, Shivashankar H; Hudson, Nicholas J; Dalrymple, Brian P; Reverter, Antonio

2011-01-12

Gene regulation by transcription factors (TF) is species, tissue and time specific. To better understand how the genetic code controls gene expression in bovine muscle we associated gene expression data from developing Longissimus thoracis et lumborum skeletal muscle with bovine promoter sequence information. We created a highly conserved genome-wide promoter landscape comprising 87,408 interactions relating 333 TFs with their 9,242 predicted target genes (TGs). We discovered that the complete set of predicted TGs share an average of 2.75 predicted TF binding sites (TFBSs) and that the average co-expression between a TF and its predicted TGs is higher than the average co-expression between the same TF and all genes. Conversely, pairs of TFs sharing predicted TGs showed a co-expression correlation higher that pairs of TFs not sharing TGs. Finally, we exploited the co-occurrence of predicted TFBS in the context of muscle-derived functionally-coherent modules including cell cycle, mitochondria, immune system, fat metabolism, muscle/glycolysis, and ribosome. Our findings enabled us to reverse engineer a regulatory network of core processes, and correctly identified the involvement of E2F1, GATA2 and NFKB1 in the regulation of cell cycle, fat, and muscle/glycolysis, respectively. The pivotal implication of our research is two-fold: (1) there exists a robust genome-wide expression signal between TFs and their predicted TGs in cattle muscle consistent with the extent of promoter sharing; and (2) this signal can be exploited to recover the cellular mechanisms underpinning transcription regulation of muscle structure and development in bovine. Our study represents the first genome-wide report linking tissue specific co-expression to co-regulation in a non-model vertebrate.

Is chloroplastic class IIA aldolase a marine enzyme?

PubMed

Miyasaka, Hitoshi; Ogata, Takeru; Tanaka, Satoshi; Ohama, Takeshi; Kano, Sanae; Kazuhiro, Fujiwara; Hayashi, Shuhei; Yamamoto, Shinjiro; Takahashi, Hiro; Matsuura, Hideyuki; Hirata, Kazumasa

2016-11-01

Expressed sequence tag analyses revealed that two marine Chlorophyceae green algae, Chlamydomonas sp. W80 and Chlamydomonas sp. HS5, contain genes coding for chloroplastic class IIA aldolase (fructose-1, 6-bisphosphate aldolase: FBA). These genes show robust monophyly with those of the marine Prasinophyceae algae genera Micromonas, Ostreococcus and Bathycoccus, indicating that the acquisition of this gene through horizontal gene transfer by an ancestor of the green algal lineage occurred prior to the divergence of the core chlorophytes (Chlorophyceae and Trebouxiophyceae) and the prasinophytes. The absence of this gene in some freshwater chlorophytes, such as Chlamydomonas reinhardtii, Volvox carteri, Chlorella vulgaris, Chlorella variabilis and Coccomyxa subellipsoidea, can therefore be explained by the loss of this gene somewhere in the evolutionary process. Our survey on the distribution of this gene in genomic and transcriptome databases suggests that this gene occurs almost exclusively in marine algae, with a few exceptions, and as such, we propose that chloroplastic class IIA FBA is a marine environment-adapted enzyme. This hypothesis was also experimentally tested using Chlamydomonas W80, for which we found that the transcript levels of this gene to be significantly lower under low-salt (that is, simulated terrestrial) conditions. Expression analyses of transcriptome data for two algae, Prymnesium parvum and Emiliania huxleyi, taken from the Sequence Read Archive database also indicated that the expression of this gene under terrestrial conditions (low NaCl and low sulfate) is significantly downregulated. Thus, these experimental and transcriptome data provide support for our hypothesis.

Is chloroplastic class IIA aldolase a marine enzyme?

PubMed Central

Miyasaka, Hitoshi; Ogata, Takeru; Tanaka, Satoshi; Ohama, Takeshi; Kano, Sanae; Kazuhiro, Fujiwara; Hayashi, Shuhei; Yamamoto, Shinjiro; Takahashi, Hiro; Matsuura, Hideyuki; Hirata, Kazumasa

2016-01-01

Expressed sequence tag analyses revealed that two marine Chlorophyceae green algae, Chlamydomonas sp. W80 and Chlamydomonas sp. HS5, contain genes coding for chloroplastic class IIA aldolase (fructose-1, 6-bisphosphate aldolase: FBA). These genes show robust monophyly with those of the marine Prasinophyceae algae genera Micromonas, Ostreococcus and Bathycoccus, indicating that the acquisition of this gene through horizontal gene transfer by an ancestor of the green algal lineage occurred prior to the divergence of the core chlorophytes (Chlorophyceae and Trebouxiophyceae) and the prasinophytes. The absence of this gene in some freshwater chlorophytes, such as Chlamydomonas reinhardtii, Volvox carteri, Chlorella vulgaris, Chlorella variabilis and Coccomyxa subellipsoidea, can therefore be explained by the loss of this gene somewhere in the evolutionary process. Our survey on the distribution of this gene in genomic and transcriptome databases suggests that this gene occurs almost exclusively in marine algae, with a few exceptions, and as such, we propose that chloroplastic class IIA FBA is a marine environment-adapted enzyme. This hypothesis was also experimentally tested using Chlamydomonas W80, for which we found that the transcript levels of this gene to be significantly lower under low-salt (that is, simulated terrestrial) conditions. Expression analyses of transcriptome data for two algae, Prymnesium parvum and Emiliania huxleyi, taken from the Sequence Read Archive database also indicated that the expression of this gene under terrestrial conditions (low NaCl and low sulfate) is significantly downregulated. Thus, these experimental and transcriptome data provide support for our hypothesis. PMID:27058504

Tolerant industrial yeast Saccharomyces cerevisiae posses a more robust cell wall integrity signaling pathway against 2-furaldehyde and 5-(hydroxymethyl)-2-furaldehyde

USDA-ARS?s Scientific Manuscript database

Cell wall integrity signaling pathway in Saccharomyces cerevisiae is a conserved function for detecting and responding to cell stress conditions but less understood for industrial yeast. We dissected gene expression dynamics for a tolerant industrial yeast strain NRRL Y-50049 in response to challeng...

Revisiting overexpression of a heterologous β-glucosidase in Trichoderma reesei: fusion expression of the Neosartorya fischeri Bgl3A to cbh1 enhances the overall as well as individual cellulase activities.

PubMed

Xue, Xianli; Wu, Yilan; Qin, Xing; Ma, Rui; Luo, Huiying; Su, Xiaoyun; Yao, Bin

2016-07-11

The filamentous fungus Trichoderma reesei has the capacity to secret large amounts of cellulase and is widely used in a variety of industries. However, the T. reesei cellulase is weak in β-glucosidase activity, which results in accumulation of cellobiose inhibiting the endo- and exo-cellulases. By expressing an exogenous β-glucosidase gene, the recombinant T. reesei cellulase is expected to degrade cellulose into glucose more efficiently. The thermophilic β-glucosidase NfBgl3A from Neosartorya fischeri is chosen for overexpression in T. reesei due to its robust activity. In vitro, the Pichia pastoris-expressed NfBgl3A aided the T. reesei cellulase in releasing much more glucose with significantly lower amounts of cellobiose from crystalline cellulose. The NfBgl3A gene was hence fused to the cbh1 structural gene and assembled between the strong cbh1 promoter and cbh1 terminator to obtain pRS-NfBgl3A by using the DNA assembler method. pRS-NfBgl3A was transformed into the T. reesei uridine auxotroph strain TU-6. Six positive transformants showed β-glucosidase activities of 2.3-69.7 U/mL (up to 175-fold higher than that of wild-type). The largely different β-glucosidase activities in the transformants may be ascribed to the gene copy numbers of NfBgl3A or its integration loci. The T. reesei-expressed NfBgl3A showed highly similar biochemical properties to that expressed in P. pastoris. As expected, overexpression of NfBgl3A enhanced the overall cellulase activity of T. reesei. The CBHI activity in all transformants increased, possibly due to the extra copies of cbh1 gene introduced, while the endoglucanase activity in three transformants also largely increased, which was not observed in any other studies overexpressing a β-glucosidase. NfBgl3A had significant transglycosylation activity, generating sophorose, a potent cellulase inducer, and other oligosaccharides from glucose and cellobiose. We report herein the successful overexpression of a thermophilic N. fischeri β-glucosidase in T. reesei. In the same time, the fusion of NfBgl3A to the cbh1 gene introduced extra copies of the cellobiohydrolase 1 gene. As a result, we observed improved β-glucosidase and cellobiohydrolase activity as well as the overall cellulase activity. In addition, the endoglucanase activity also increased in some of the transformants. Our results may shed light on design of more robust T. reesei cellulases.

Acute Simian Varicella Virus Infection Causes Robust and Sustained Changes in Gene Expression in the Sensory Ganglia

PubMed Central

Arnold, Nicole; Girke, Thomas; Sureshchandra, Suhas

2016-01-01

ABSTRACT Primary infection with varicella-zoster virus (VZV), a neurotropic alphaherpesvirus, results in varicella. VZV establishes latency in the sensory ganglia and can reactivate later in life to cause herpes zoster. The relationship between VZV and its host during acute infection in the sensory ganglia is not well understood due to limited access to clinical specimens. Intrabronchial inoculation of rhesus macaques with simian varicella virus (SVV) recapitulates the hallmarks of VZV infection in humans. We leveraged this animal model to characterize the host-pathogen interactions in the ganglia during both acute and latent infection by measuring both viral and host transcriptomes on days postinfection (dpi) 3, 7, 10, 14, and 100. SVV DNA and transcripts were detected in sensory ganglia 3 dpi, before the appearance of rash. CD4 and CD8 T cells were also detected in the sensory ganglia 3 dpi. Moreover, lung-resident T cells isolated from the same animals 3 dpi also harbored SVV DNA and transcripts, suggesting that T cells may be responsible for trafficking SVV to the ganglia. Transcriptome sequencing (RNA-Seq) analysis showed that cessation of viral transcription 7 dpi coincides with a robust antiviral innate immune response in the ganglia. Interestingly, a significant number of genes that play a critical role in nervous system development and function remained downregulated into latency. These studies provide novel insights into host-pathogen interactions in the sensory ganglia during acute varicella and demonstrate that SVV infection results in profound and sustained changes in neuronal gene expression. IMPORTANCE Many aspects of VZV infection of sensory ganglia remain poorly understood, due to limited access to human specimens and the fact that VZV is strictly a human virus. Infection of rhesus macaques with simian varicella virus (SVV), a homolog of VZV, provides a robust model of the human disease. Using this model, we show that SVV reaches the ganglia early after infection, most likely by T cells, and that the induction of a robust innate immune response correlates with cessation of virus transcription. We also report significant changes in the expression of genes that play an important role in neuronal function. Importantly, these changes persist long after viral replication ceases. Given the homology between SVV and VZV, and the genetic and physiological similarities between rhesus macaques and humans, our results provide novel insight into the interactions between VZV and its human host and explain some of the neurological consequences of VZV infection. PMID:27681124

Comparison of normalization methods for differential gene expression analysis in RNA-Seq experiments

PubMed Central

Maza, Elie; Frasse, Pierre; Senin, Pavel; Bouzayen, Mondher; Zouine, Mohamed

2013-01-01

In recent years, RNA-Seq technologies became a powerful tool for transcriptome studies. However, computational methods dedicated to the analysis of high-throughput sequencing data are yet to be standardized. In particular, it is known that the choice of a normalization procedure leads to a great variability in results of differential gene expression analysis. The present study compares the most widespread normalization procedures and proposes a novel one aiming at removing an inherent bias of studied transcriptomes related to their relative size. Comparisons of the normalization procedures are performed on real and simulated data sets. Real RNA-Seq data sets analyses, performed with all the different normalization methods, show that only 50% of significantly differentially expressed genes are common. This result highlights the influence of the normalization step on the differential expression analysis. Real and simulated data sets analyses give similar results showing 3 different groups of procedures having the same behavior. The group including the novel method named “Median Ratio Normalization” (MRN) gives the lower number of false discoveries. Within this group the MRN method is less sensitive to the modification of parameters related to the relative size of transcriptomes such as the number of down- and upregulated genes and the gene expression levels. The newly proposed MRN method efficiently deals with intrinsic bias resulting from relative size of studied transcriptomes. Validation with real and simulated data sets confirmed that MRN is more consistent and robust than existing methods. PMID:26442135

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

Myoblast-mediated gene transfer for therapeutic angiogenesis and arteriogenesis.

PubMed

von Degenfeld, Georges; Banfi, Andrea; Springer, Matthew L; Blau, Helen M

2003-10-01

Therapeutic angiogenesis aims at generating new blood vessels by delivering growth factors such as VEGF and FGF. Clinical trials are underway in patients with peripheral vascular and coronary heart disease. However, increasing evidence indicates that the new vasculature needs to be stabilized to avoid deleterious effects such as edema and hemangioma formation. Moreover, a major challenge is to induce new vessels that persist following cessation of the angiogenic stimulus. Mature vessels may be generated by modulating timing and dosage of growth factor expression, or by combination of 'growth' factors with 'maturation' factors like PDGF-BB, angiopoietin-1 or TGF-beta. Myoblast-mediated gene transfer has unique characteristics that make it a useful tool for studying promising novel approaches to therapeutic angiogenesis. It affords robust and long-lasting expression, and can be considered as a relatively rapid form of 'adult transgenesis' in muscle. The combined insertion of different gene constructs into single myoblasts and their progeny allows the simultaneous expression of different 'growth' and 'maturation' factors within the same cell in vivo. The additional insertion of a reporter gene makes it possible to analyze the phenotype of the vessels surrounding the transgenic muscle fibers into which the myoblasts have fused. The effects of timing and duration of gene expression can be studied by using tetracycline-inducible constructs, and dosage effects by selecting subpopulations consistently expressing distinct levels of growth factors. Finally, the autologous cell-based approach using transduced myoblasts could be an alternative gene delivery system for therapeutic angiogenesis in patients, avoiding the toxicities seen with some viral vectors.

A biological network-based regularized artificial neural network model for robust phenotype prediction from gene expression data.

PubMed

Kang, Tianyu; Ding, Wei; Zhang, Luoyan; Ziemek, Daniel; Zarringhalam, Kourosh

2017-12-19

Stratification of patient subpopulations that respond favorably to treatment or experience and adverse reaction is an essential step toward development of new personalized therapies and diagnostics. It is currently feasible to generate omic-scale biological measurements for all patients in a study, providing an opportunity for machine learning models to identify molecular markers for disease diagnosis and progression. However, the high variability of genetic background in human populations hampers the reproducibility of omic-scale markers. In this paper, we develop a biological network-based regularized artificial neural network model for prediction of phenotype from transcriptomic measurements in clinical trials. To improve model sparsity and the overall reproducibility of the model, we incorporate regularization for simultaneous shrinkage of gene sets based on active upstream regulatory mechanisms into the model. We benchmark our method against various regression, support vector machines and artificial neural network models and demonstrate the ability of our method in predicting the clinical outcomes using clinical trial data on acute rejection in kidney transplantation and response to Infliximab in ulcerative colitis. We show that integration of prior biological knowledge into the classification as developed in this paper, significantly improves the robustness and generalizability of predictions to independent datasets. We provide a Java code of our algorithm along with a parsed version of the STRING DB database. In summary, we present a method for prediction of clinical phenotypes using baseline genome-wide expression data that makes use of prior biological knowledge on gene-regulatory interactions in order to increase robustness and reproducibility of omic-scale markers. The integrated group-wise regularization methods increases the interpretability of biological signatures and gives stable performance estimates across independent test sets.

On the Interplay between the Evolvability and Network Robustness in an Evolutionary Biological Network: A Systems Biology Approach

PubMed Central

Chen, Bor-Sen; Lin, Ying-Po

2011-01-01

In the evolutionary process, the random transmission and mutation of genes provide biological diversities for natural selection. In order to preserve functional phenotypes between generations, gene networks need to evolve robustly under the influence of random perturbations. Therefore, the robustness of the phenotype, in the evolutionary process, exerts a selection force on gene networks to keep network functions. However, gene networks need to adjust, by variations in genetic content, to generate phenotypes for new challenges in the network’s evolution, ie, the evolvability. Hence, there should be some interplay between the evolvability and network robustness in evolutionary gene networks. In this study, the interplay between the evolvability and network robustness of a gene network and a biochemical network is discussed from a nonlinear stochastic system point of view. It was found that if the genetic robustness plus environmental robustness is less than the network robustness, the phenotype of the biological network is robust in evolution. The tradeoff between the genetic robustness and environmental robustness in evolution is discussed from the stochastic stability robustness and sensitivity of the nonlinear stochastic biological network, which may be relevant to the statistical tradeoff between bias and variance, the so-called bias/variance dilemma. Further, the tradeoff could be considered as an antagonistic pleiotropic action of a gene network and discussed from the systems biology perspective. PMID:22084563

Sodium butyrate rescues dopaminergic cells from alpha-synuclein-induced transcriptional deregulation and DNA damage.

PubMed

Paiva, Isabel; Pinho, Raquel; Pavlou, Maria Angeliki; Hennion, Magali; Wales, Pauline; Schütz, Anna-Lena; Rajput, Ashish; Szego, Éva M; Kerimoglu, Cemil; Gerhardt, Ellen; Rego, Ana Cristina; Fischer, André; Bonn, Stefan; Outeiro, Tiago F

2017-06-15

Alpha-synuclein (aSyn) is considered a major culprit in Parkinson's disease (PD) pathophysiology. However, the precise molecular function of the protein remains elusive. Recent evidence suggests that aSyn may play a role on transcription regulation, possibly by modulating the acetylation status of histones. Our study aimed at evaluating the impact of wild-type (WT) and mutant A30P aSyn on gene expression, in a dopaminergic neuronal cell model, and decipher potential mechanisms underlying aSyn-mediated transcriptional deregulation. We performed gene expression analysis using RNA-sequencing in Lund Human Mesencephalic (LUHMES) cells expressing endogenous (control) or increased levels of WT or A30P aSyn. Compared to control cells, cells expressing both aSyn variants exhibited robust changes in the expression of several genes, including downregulation of major genes involved in DNA repair. WT aSyn, unlike A30P aSyn, promoted DNA damage and increased levels of phosphorylated p53. In dopaminergic neuronal cells, increased aSyn expression led to reduced levels of acetylated histone 3. Importantly, treatment with sodium butyrate, a histone deacetylase inhibitor (HDACi), rescued WT aSyn-induced DNA damage, possibly via upregulation of genes involved in DNA repair. Overall, our findings provide novel and compelling insight into the mechanisms associated with aSyn neurotoxicity in dopaminergic cells, which could be ameliorated with an HDACi. Future studies will be crucial to further validate these findings and to define novel possible targets for intervention in PD. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Single cell gene expression profiling of cortical osteoblast lineage cells.

PubMed

Flynn, James M; Spusta, Steven C; Rosen, Clifford J; Melov, Simon

2013-03-01

In tissues with complex architectures such as bone, it is often difficult to purify and characterize specific cell types via molecular profiling. Single cell gene expression profiling is an emerging technology useful for characterizing transcriptional profiles of individual cells isolated from heterogeneous populations. In this study we describe a novel procedure for the isolation and characterization of gene expression profiles of single osteoblast lineage cells derived from cortical bone. Mixed populations of different cell types were isolated from adult long bones of C57BL/6J mice by enzymatic digestion, and subsequently subjected to FACS to purify and characterize osteoblast lineage cells via a selection strategy using antibodies against CD31, CD45, and alkaline phosphatase (AP), specific for mature osteoblasts. The purified individual osteoblast lineage cells were then profiled at the single cell level via nanofluidic PCR. This method permits robust gene expression profiling on single osteoblast lineage cells derived from mature bone, potentially from anatomically distinct sites. In conjunction with this technique, we have also shown that it is possible to carry out single cell profiling on cells purified from fixed and frozen bone samples without compromising the gene expression signal. The latter finding means the technique can be extended to biopsies of bone from diseased individuals. Our approach for single cell expression profiling provides a new dimension to the transcriptional profile of the primary osteoblast lineage population in vivo, and has the capacity to greatly expand our understanding of how these cells may function in vivo under normal and diseased states. Copyright © 2012 Elsevier Inc. All rights reserved.

A formal concept analysis approach to consensus clustering of multi-experiment expression data

PubMed Central

2014-01-01

Background Presently, with the increasing number and complexity of available gene expression datasets, the combination of data from multiple microarray studies addressing a similar biological question is gaining importance. The analysis and integration of multiple datasets are expected to yield more reliable and robust results since they are based on a larger number of samples and the effects of the individual study-specific biases are diminished. This is supported by recent studies suggesting that important biological signals are often preserved or enhanced by multiple experiments. An approach to combining data from different experiments is the aggregation of their clusterings into a consensus or representative clustering solution which increases the confidence in the common features of all the datasets and reveals the important differences among them. Results We propose a novel generic consensus clustering technique that applies Formal Concept Analysis (FCA) approach for the consolidation and analysis of clustering solutions derived from several microarray datasets. These datasets are initially divided into groups of related experiments with respect to a predefined criterion. Subsequently, a consensus clustering algorithm is applied to each group resulting in a clustering solution per group. These solutions are pooled together and further analysed by employing FCA which allows extracting valuable insights from the data and generating a gene partition over all the experiments. In order to validate the FCA-enhanced approach two consensus clustering algorithms are adapted to incorporate the FCA analysis. Their performance is evaluated on gene expression data from multi-experiment study examining the global cell-cycle control of fission yeast. The FCA results derived from both methods demonstrate that, although both algorithms optimize different clustering characteristics, FCA is able to overcome and diminish these differences and preserve some relevant biological signals. Conclusions The proposed FCA-enhanced consensus clustering technique is a general approach to the combination of clustering algorithms with FCA for deriving clustering solutions from multiple gene expression matrices. The experimental results presented herein demonstrate that it is a robust data integration technique able to produce good quality clustering solution that is representative for the whole set of expression matrices. PMID:24885407

Gene expression profiling during asexual development of the late blight pathogen Phytophthora infestans reveals a highly dynamic transcriptome.

PubMed

Judelson, Howard S; Ah-Fong, Audrey M V; Aux, George; Avrova, Anna O; Bruce, Catherine; Cakir, Cahid; da Cunha, Luis; Grenville-Briggs, Laura; Latijnhouwers, Maita; Ligterink, Wilco; Meijer, Harold J G; Roberts, Samuel; Thurber, Carrie S; Whisson, Stephen C; Birch, Paul R J; Govers, Francine; Kamoun, Sophien; van West, Pieter; Windass, John

2008-04-01

Much of the pathogenic success of Phytophthora infestans, the potato and tomato late blight agent, relies on its ability to generate from mycelia large amounts of sporangia, which release zoospores that encyst and form infection structures. To better understand these stages, Affymetrix GeneChips based on 15,650 unigenes were designed and used to profile the life cycle. Approximately half of P. infestans genes were found to exhibit significant differential expression between developmental transitions, with approximately (1)/(10) being stage-specific and most changes occurring during zoosporogenesis. Quantitative reverse-transcription polymerase chain reaction assays confirmed the robustness of the array results and showed that similar patterns of differential expression were obtained regardless of whether hyphae were from laboratory media or infected tomato. Differentially expressed genes encode potential cellular regulators, especially protein kinases; metabolic enzymes such as those involved in glycolysis, gluconeogenesis, or the biosynthesis of amino acids or lipids; regulators of DNA synthesis; structural proteins, including predicted flagellar proteins; and pathogenicity factors, including cell-wall-degrading enzymes, RXLR effector proteins, and enzymes protecting against plant defense responses. Curiously, some stage-specific transcripts do not appear to encode functional proteins. These findings reveal many new aspects of oomycete biology, as well as potential targets for crop protection chemicals.

Heterologous Expression of Spinosyn Biosynthetic Gene Cluster in Streptomyces Species Is Dependent on the Expression of Rhamnose Biosynthesis Genes.

PubMed

Zhao, Chen; Huang, Ying; Guo, Chao; Yang, Bolei; Zhang, Yan; Lan, Zhou; Guan, Xiong; Song, Yuan; Zhang, Xiaolin

2017-01-01

Spinosyns are a group of macrolide insecticides produced by Saccharopolyspora spinosa. Although S. spinosa can be used for industrial-scale production of spinosyns, this might suffer from several limitations, mainly related to its long growth cycle, low fermentation biomass, and inefficient utilization of starch. It is crucial to generate a robust strain for further spinosyn production and the development of spinosyn derivatives. A BAC vector, containing the whole biosynthetic gene cluster for spinosyn (74 kb) and the elements required for conjugal transfer and site-specific integration, was introduced into different Streptomyces hosts in order to obtain heterologous spinosyn-producing strains. The exconjugants of different Streptomyces strains did not show spinosyn production unless the rhamnose biosynthesis genes from S. spinosa genomic DNA were present and expressed under the control of a strong constitutive ermE*p promoter. Using this heterologous expression system resulted in yields of 1 μg/mL and 1.5 μg/mL spinosyns in Streptomyces coelicolor and Streptomyces lividans, respectively. This report demonstrates spinosyn production in 2 Streptomyces strains and stresses the essential role of rhamnose in this process. This work also provides a potential alternative route for producing spinosyn analogs by means of genetic manipulation in the heterologous hosts. © 2017 S. Karger AG, Basel.

Subtle Changes in Motif Positioning Cause Tissue-Specific Effects on Robustness of an Enhancer's Activity

PubMed Central

Erceg, Jelena; Saunders, Timothy E.; Girardot, Charles; Devos, Damien P.; Hufnagel, Lars; Furlong, Eileen E. M.

2014-01-01

Deciphering the specific contribution of individual motifs within cis-regulatory modules (CRMs) is crucial to understanding how gene expression is regulated and how this process is affected by sequence variation. But despite vast improvements in the ability to identify where transcription factors (TFs) bind throughout the genome, we are limited in our ability to relate information on motif occupancy to function from sequence alone. Here, we engineered 63 synthetic CRMs to systematically assess the relationship between variation in the content and spacing of motifs within CRMs to CRM activity during development using Drosophila transgenic embryos. In over half the cases, very simple elements containing only one or two types of TF binding motifs were capable of driving specific spatio-temporal patterns during development. Different motif organizations provide different degrees of robustness to enhancer activity, ranging from binary on-off responses to more subtle effects including embryo-to-embryo and within-embryo variation. By quantifying the effects of subtle changes in motif organization, we were able to model biophysical rules that explain CRM behavior and may contribute to the spatial positioning of CRM activity in vivo. For the same enhancer, the effects of small differences in motif positions varied in developmentally related tissues, suggesting that gene expression may be more susceptible to sequence variation in one tissue compared to another. This result has important implications for human eQTL studies in which many associated mutations are found in cis-regulatory regions, though the mechanism for how they affect tissue-specific gene expression is often not understood. PMID:24391522

Inhibition of herpes simplex virus 1 gene expression and replication by RNase P-associated external guide sequences.

PubMed

Liu, Jin; Shao, Luyao; Trang, Phong; Yang, Zhu; Reeves, Michael; Sun, Xu; Vu, Gia-Phong; Wang, Yu; Li, Hongjian; Zheng, Congyi; Lu, Sangwei; Liu, Fenyong

2016-06-09

An external guide sequence (EGS) is a RNA sequence which can interact with a target mRNA to form a tertiary structure like a pre-tRNA and recruit intracellular ribonuclease P (RNase P), a tRNA processing enzyme, to degrade target mRNA. Previously, an in vitro selection procedure has been used by us to engineer new EGSs that are more robust in inducing human RNase P to cleave their targeted mRNAs. In this study, we constructed EGSs from a variant to target the mRNA encoding herpes simplex virus 1 (HSV-1) major transcription regulator ICP4, which is essential for the expression of viral early and late genes and viral growth. The EGS variant induced human RNase P cleavage of ICP4 mRNA sequence 60 times better than the EGS generated from a natural pre-tRNA. A decrease of about 97% and 75% in the level of ICP4 gene expression and an inhibition of about 7,000- and 500-fold in viral growth were observed in HSV infected cells expressing the variant and the pre-tRNA-derived EGS, respectively. This study shows that engineered EGSs can inhibit HSV-1 gene expression and viral growth. Furthermore, these results demonstrate the potential for engineered EGS RNAs to be developed and used as anti-HSV therapeutics.

Inhibition of herpes simplex virus 1 gene expression and replication by RNase P-associated external guide sequences

PubMed Central

Liu, Jin; Shao, Luyao; Trang, Phong; Yang, Zhu; Reeves, Michael; Sun, Xu; Vu, Gia-Phong; Wang, Yu; Li, Hongjian; Zheng, Congyi; Lu, Sangwei; Liu, Fenyong

2016-01-01

An external guide sequence (EGS) is a RNA sequence which can interact with a target mRNA to form a tertiary structure like a pre-tRNA and recruit intracellular ribonuclease P (RNase P), a tRNA processing enzyme, to degrade target mRNA. Previously, an in vitro selection procedure has been used by us to engineer new EGSs that are more robust in inducing human RNase P to cleave their targeted mRNAs. In this study, we constructed EGSs from a variant to target the mRNA encoding herpes simplex virus 1 (HSV-1) major transcription regulator ICP4, which is essential for the expression of viral early and late genes and viral growth. The EGS variant induced human RNase P cleavage of ICP4 mRNA sequence 60 times better than the EGS generated from a natural pre-tRNA. A decrease of about 97% and 75% in the level of ICP4 gene expression and an inhibition of about 7,000- and 500-fold in viral growth were observed in HSV infected cells expressing the variant and the pre-tRNA-derived EGS, respectively. This study shows that engineered EGSs can inhibit HSV-1 gene expression and viral growth. Furthermore, these results demonstrate the potential for engineered EGS RNAs to be developed and used as anti-HSV therapeutics. PMID:27279482

Generation of recombinant rotaviruses expressing fluorescent proteins using an optimized reverse genetics system.

PubMed

Komoto, Satoshi; Fukuda, Saori; Ide, Tomihiko; Ito, Naoto; Sugiyama, Makoto; Yoshikawa, Tetsushi; Murata, Takayuki; Taniguchi, Koki

2018-04-18

An entirely plasmid-based reverse genetics system for rotaviruses was established very recently. We improved the reverse genetics system to generate recombinant rotavirus by transfecting only 11 cDNA plasmids for its 11 gene segments under the condition of increasing the ratio of the cDNA plasmids for NSP2 and NSP5 genes. Utilizing this highly efficient system, we then engineered infectious recombinant rotaviruses expressing bioluminescent (NanoLuc luciferase) and fluorescent (EGFP and mCherry) reporters. These recombinant rotaviruses expressing reporters remained genetically stable during serial passages. Our reverse genetics approach and recombinant rotaviruses carrying reporter genes will be great additions to the tool kit for studying the molecular virology of rotavirus, and for developing future next-generation vaccines and expression vectors. IMPORTANCE Rotavirus is one of the most important pathogens causing severe gastroenteritis in young children worldwide. In this paper, we describe a robust and simple reverse genetics system based on only rotavirus cDNAs, and its application for engineering infectious recombinant rotaviruses harboring bioluminescent (NanoLuc) and fluorescent (EGFP and mCherry) protein genes. This highly efficient reverse genetics system and recombinant RVAs expressing reporters could be powerful tools for the study of different aspects of rotavirus replication. Furthermore, they may be useful for next-generation vaccine production for this medically important virus. Copyright © 2018 American Society for Microbiology.

Amelioration of murine beta-thalassemia through drug selection of hematopoietic stem cells transduced with a lentiviral vector encoding both gamma-globin and the MGMT drug-resistance gene.

PubMed

Zhao, Huifen; Pestina, Tamara I; Nasimuzzaman, Md; Mehta, Perdeep; Hargrove, Phillip W; Persons, Derek A

2009-06-04

Correction of murine models of beta-thalassemia has been achieved through high-level globin lentiviral vector gene transfer into mouse hematopoietic stem cells (HSCs). However, transduction of human HSCs is less robust and may be inadequate to achieve therapeutic levels of genetically modified erythroid cells. We therefore developed a double gene lentiviral vector encoding both human gamma-globin under the transcriptional control of erythroid regulatory elements and methylguanine methyltransferase (MGMT), driven by a constitutive cellular promoter. MGMT expression provides cellular resistance to alkylator drugs, which can be administered to kill residual untransduced, diseased HSCs, whereas transduced cells are protected. Mice transplanted with beta-thalassemic HSCs transduced with a gamma-globin/MGMT vector initially had subtherapeutic levels of red cells expressing gamma-globin. To enrich gamma-globin-expressing cells, transplanted mice were treated with the alkylator agent 1,3-bis-chloroethyl-1-nitrosourea. This resulted in significant increases in the number of gamma-globin-expressing red cells and the amount of fetal hemoglobin, leading to resolution of anemia. Selection of transduced HSCs was also obtained when cells were drug-treated before transplantation. Mice that received these cells demonstrated reconstitution with therapeutic levels of gamma-globin-expressing cells. These data suggest that MGMT-based drug selection holds promise as a modality to improve gene therapy for beta-thalassemia.

A piggyBac-based reporter system for scalable in vitro and in vivo analysis of 3′ untranslated region-mediated gene regulation

PubMed Central

Chaudhury, Arindam; Kongchan, Natee; Gengler, Jon P.; Mohanty, Vakul; Christiansen, Audrey E.; Fachini, Joseph M.; Martin, James F.; Neilson, Joel R.

2014-01-01

Regulation of messenger ribonucleic acid (mRNA) subcellular localization, stability and translation is a central aspect of gene expression. Much of this control is mediated via recognition of mRNA 3′ untranslated regions (UTRs) by microRNAs (miRNAs) and RNA-binding proteins. The gold standard approach to assess the regulation imparted by a transcript's 3′ UTR is to fuse the UTR to a reporter coding sequence and assess the relative expression of this reporter as compared to a control. Yet, transient transfection approaches or the use of highly active viral promoter elements may overwhelm a cell's post-transcriptional regulatory machinery in this context. To circumvent this issue, we have developed and validated a novel, scalable piggyBac-based vector for analysis of 3′ UTR-mediated regulation in vitro and in vivo. The vector delivers three independent transcription units to the target genome—a selection cassette, a turboGFP control reporter and an experimental reporter expressed under the control of a 3′ UTR of interest. The pBUTR (piggyBac-based 3′ UnTranslated Region reporter) vector performs robustly as a siRNA/miRNA sensor, in established in vitro models of post-transcriptional regulation, and in both arrayed and pooled screening approaches. The vector is robustly expressed as a transgene during murine embryogenesis, highlighting its potential usefulness for revealing post-transcriptional regulation in an in vivo setting. PMID:24753411

Necroptosis promotes cell-autonomous activation of proinflammatory cytokine gene expression.

PubMed

Zhu, Kezhou; Liang, Wei; Ma, Zaijun; Xu, Daichao; Cao, Shuangyi; Lu, Xiaojuan; Liu, Nan; Shan, Bing; Qian, Lihui; Yuan, Junying

2018-04-27

Necroptosis, a form of regulated necrotic cell death, is mediated by receptor interacting protein 1 (RIPK1), RIPK3, and mixed lineage kinase domain-like protein (MLKL). However, the mechanism by which necroptosis promotes inflammation is still unclear. Here we report that the expression of cytokines is robustly upregulated in a cell-autonomous manner during necroptosis induced by tumor necrosis factor alpha (TNFα). We demonstrate that TNFα-induced necroptosis leads to two waves of cytokine production. The first wave, more transient and weaker than the second, is in response to TNFα alone; whereas the second wave depends upon the necroptotic signaling. We show that necroptosis promotes the transcription of TNFα-target genes in a cell-intrinsic manner. The activation of both NF-κB and p38 by the necroptotic machinery, RIPK1, RIPK3, and MLKL, is involved in mediating the robust induction of cytokine expression in the second wave. In contrast, necroptosis induced by direct oligomerization of MLKL promotes cytokine production at much lower levels than that of necroptosis induced with TNFα. Thus, we conclude that TNFα-induced necroptosis signaling events mediated by RIPK1 and RIPK3 activation, in addition to the MLKL oligomerization, promotes the expression of cytokines involving multiple intracellular signaling mechanisms including NF-κB pathway and p38. These findings reveal that the necroptotic cell death machinery mounts an immune response by promoting cell-autonomous production of cytokines. Our study provides insights into the mechanism by which necroptosis promotes inflammation in human diseases.

Cytosolic ppGpp accumulation induces retarded plant growth and development.

PubMed

Ihara, Yuta; Masuda, Shinji

2016-01-01

In bacteria a second messenger, guanosine 5'-diphosphate 3'-diphosphate (ppGpp), synthesized upon nutrient starvation, controls many gene expressions and enzyme activities, which is necessary for growth under changeable environments. Recent studies have shown that ppGpp synthase and hydrolase are also conserved in eukaryotes, although their functions are not well understood. We recently showed that ppGpp-overaccumulation in Arabidopsis chloroplasts results in robust growth under nutrient-limited conditions, demonstrating that the bacterial-like stringent response at least functions in plastids. To test if ppGpp also functions in the cytosol, we constructed the transgenic Arabidopsis expressing Bacillus subtilis ppGpp synthase gene yjbM. Upon induction of the gene, the mutant synthesizes ∼10-20-fold higher levels of ppGpp, and its fresh weight was reduced to ˜80% that of the wild type. These results indicate that cytosolic ppGpp negatively regulates plant growth and development.

Passive immunization against HIV/AIDS by antibody gene transfer.

PubMed

Yang, Lili; Wang, Pin

2014-01-27

Despite tremendous efforts over the course of many years, the quest for an effective HIV vaccine by the classical method of active immunization remains largely elusive. However, two recent studies in mice and macaques have now demonstrated a new strategy designated as Vectored ImmunoProphylaxis (VIP), which involves passive immunization by viral vector-mediated delivery of genes encoding broadly neutralizing antibodies (bnAbs) for in vivo expression. Robust protection against virus infection was observed in preclinical settings when animals were given VIP to express monoclonal neutralizing antibodies. This unorthodox approach raises new promise for combating the ongoing global HIV pandemic. In this article, we survey the status of antibody gene transfer, review the revolutionary progress on isolation of extremely bnAbs, detail VIP experiments against HIV and its related virus conduced in humanized mice and macaque monkeys, and discuss the pros and cons of VIP and its opportunities and challenges towards clinical applications to control HIV/AIDS endemics.

Gene silencing by siRNAs and antisense oligonucleotides in the laboratory and the clinic

PubMed Central

Watts, Jonathan K.; Corey, David R.

2014-01-01

Synthetic nucleic acids are commonly used laboratory tools for modulating gene expression and have the potential to be widely used in the clinic. Progress towards nucleic acid drugs, however, has been slow and many challenges remain to be overcome before their full impact on patient care can be understood. Antisense oligonucleotides (ASOs) and small interfering RNAs (siRNAs) are the two most widely used strategies for silencing gene expression. We first describe these two approaches and contrast their relative strengths and weaknesses for laboratory applications. We then review the choices faced during development of clinical candidates and the current state of clinical trials. Attitudes towards clinical development of nucleic acid silencing strategies have repeatedly swung from optimism to depression during the past twenty years. Our goal is to provide the information needed to design robust studies with oligonucleotides, making use of the strengths of each oligonucleotide technology. PMID:22069063

Integrated Genomic Analysis Identifies Clinically Relevant Subtypes of Glioblastoma Characterized by Abnormalities in PDGFRA, IDH1, EGFR, and NF1

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

Verhaak, Roel GW; Hoadley, Katherine A; Purdom, Elizabeth

The Cancer Genome Atlas Network recently cataloged recurrent genomic abnormalities in glioblastoma multiforme (GBM). We describe a robust gene expression-based molecular classification of GBM into Proneural, Neural, Classical, and Mesenchymal subtypes and integrate multidimensional genomic data to establish patterns of somatic mutations and DNA copy number. Aberrations and gene expression of EGFR, NF1, and PDGFRA/IDH1 each define the Classical, Mesenchymal, and Proneural subtypes, respectively. Gene signatures of normal brain cell types show a strong relationship between subtypes and different neural lineages. Additionally, response to aggressive therapy differs by subtype, with the greatest benefit in the Classical subtype and no benefitmore » in the Proneural subtype. We provide a framework that unifies transcriptomic and genomic dimensions for GBM molecular stratification with important implications for future studies.« less

0610009K11Rik, a testis-specific and germ cell nuclear receptor-interacting protein

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

Zhang Heng; Denhard, Leslie A.; Zhou Huaxin

Using an in silico approach, a putative nuclear receptor-interacting protein 0610009K11Rik was identified in mouse testis. We named this gene testis-specific nuclear receptor-interacting protein-1 (Tnrip-1). Tnrip-1 was predominantly expressed in the testis of adult mouse tissues. Expression of Tnrip-1 in the testis was regulated during postnatal development, with robust expression in 14-day-old or older testes. In situ hybridization analyses showed that Tnrip-1 is highly expressed in pachytene spermatocytes and spermatids. Consistent with its mRNA expression, Tnrip-1 protein was detected in adult mouse testes. Immunohistochemical studies showed that Tnrip-1 is a nuclear protein and mainly expressed in pachytene spermatocytes and roundmore » spermatids. Moreover, co-immunoprecipitation analyses showed that endogenous Tnrip-1 protein can interact with germ cell nuclear receptor (GCNF) in adult mouse testes. Our results suggest that Tnrip-1 is a testis-specific and GCNF-interacting protein which may be involved in the modulation of GCNF-mediated gene transcription in spermatogenic cells within the testis.« less

Recommendations for Accurate Resolution of Gene and Isoform Allele-Specific Expression in RNA-Seq Data

PubMed Central

Wood, David L. A.; Nones, Katia; Steptoe, Anita; Christ, Angelika; Harliwong, Ivon; Newell, Felicity; Bruxner, Timothy J. C.; Miller, David; Cloonan, Nicole; Grimmond, Sean M.

2015-01-01

Genetic variation modulates gene expression transcriptionally or post-transcriptionally, and can profoundly alter an individual’s phenotype. Measuring allelic differential expression at heterozygous loci within an individual, a phenomenon called allele-specific expression (ASE), can assist in identifying such factors. Massively parallel DNA and RNA sequencing and advances in bioinformatic methodologies provide an outstanding opportunity to measure ASE genome-wide. In this study, matched DNA and RNA sequencing, genotyping arrays and computationally phased haplotypes were integrated to comprehensively and conservatively quantify ASE in a single human brain and liver tissue sample. We describe a methodological evaluation and assessment of common bioinformatic steps for ASE quantification, and recommend a robust approach to accurately measure SNP, gene and isoform ASE through the use of personalized haplotype genome alignment, strict alignment quality control and intragenic SNP aggregation. Our results indicate that accurate ASE quantification requires careful bioinformatic analyses and is adversely affected by sample specific alignment confounders and random sampling even at moderate sequence depths. We identified multiple known and several novel ASE genes in liver, including WDR72, DSP and UBD, as well as genes that contained ASE SNPs with imbalance direction discordant with haplotype phase, explainable by annotated transcript structure, suggesting isoform derived ASE. The methods evaluated in this study will be of use to researchers performing highly conservative quantification of ASE, and the genes and isoforms identified as ASE of interest to researchers studying those loci. PMID:25965996

Dynamic modelling of microRNA regulation during mesenchymal stem cell differentiation.

PubMed

Weber, Michael; Sotoca, Ana M; Kupfer, Peter; Guthke, Reinhard; van Zoelen, Everardus J

2013-11-12

Network inference from gene expression data is a typical approach to reconstruct gene regulatory networks. During chondrogenic differentiation of human mesenchymal stem cells (hMSCs), a complex transcriptional network is active and regulates the temporal differentiation progress. As modulators of transcriptional regulation, microRNAs (miRNAs) play a critical role in stem cell differentiation. Integrated network inference aimes at determining interrelations between miRNAs and mRNAs on the basis of expression data as well as miRNA target predictions. We applied the NetGenerator tool in order to infer an integrated gene regulatory network. Time series experiments were performed to measure mRNA and miRNA abundances of TGF-beta1+BMP2 stimulated hMSCs. Network nodes were identified by analysing temporal expression changes, miRNA target gene predictions, time series correlation and literature knowledge. Network inference was performed using NetGenerator to reconstruct a dynamical regulatory model based on the measured data and prior knowledge. The resulting model is robust against noise and shows an optimal trade-off between fitting precision and inclusion of prior knowledge. It predicts the influence of miRNAs on the expression of chondrogenic marker genes and therefore proposes novel regulatory relations in differentiation control. By analysing the inferred network, we identified a previously unknown regulatory effect of miR-524-5p on the expression of the transcription factor SOX9 and the chondrogenic marker genes COL2A1, ACAN and COL10A1. Genome-wide exploration of miRNA-mRNA regulatory relationships is a reasonable approach to identify miRNAs which have so far not been associated with the investigated differentiation process. The NetGenerator tool is able to identify valid gene regulatory networks on the basis of miRNA and mRNA time series data.

Upregulating endogenous genes by an RNA-programmable artificial transactivator

PubMed Central

Fimiani, Cristina; Goina, Elisa; Mallamaci, Antonello

2015-01-01

To promote expression of endogenous genes ad libitum, we developed a novel, programmable transcription factor prototype. Kept together via an MS2 coat protein/RNA interface, it includes a fixed, polypeptidic transactivating domain and a variable RNA domain that recognizes the desired gene. Thanks to this device, we specifically upregulated five genes, in cell lines and primary cultures of murine pallial precursors. Gene upregulation was small, however sufficient to robustly inhibit neuronal differentiation. The transactivator interacted with target gene chromatin via its RNA cofactor. Its activity was restricted to cells in which the target gene is normally transcribed. Our device might be useful for specific applications. However for this purpose, it will require an improvement of its transactivation power as well as a better characterization of its target specificity and mechanism of action. PMID:26152305

Psychological Well-Being and the Human Conserved Transcriptional Response to Adversity

PubMed Central

Fredrickson, Barbara L.; Grewen, Karen M.; Algoe, Sara B.; Firestine, Ann M.; Arevalo, Jesusa M. G.; Ma, Jeffrey; Cole, Steve W.

2015-01-01

Research in human social genomics has identified a conserved transcriptional response to adversity (CTRA) characterized by up-regulated expression of pro-inflammatory genes and down-regulated expression of Type I interferon- and antibody-related genes. This report seeks to identify the specific aspects of positive psychological well-being that oppose such effects and predict reduced CTRA gene expression. In a new confirmation study of 122 healthy adults that replicated the approach of a previously reported discovery study, mixed effect linear model analyses identified a significant inverse association between expression of CTRA indicator genes and a summary measure of eudaimonic well-being from the Mental Health Continuum – Short Form. Analyses of a 2- representation of eudaimonia converged in finding correlated psychological and social subdomains of eudaimonic well-being to be the primary carriers of CTRA associations. Hedonic well-being showed no consistent CTRA association independent of eudaimonic well-being, and summary measures integrating hedonic and eudaimonic well-being showed less stable CTRA associations than did focal measures of eudaimonia (psychological and social well-being). Similar results emerged from analyses of pooled discovery and confirmation samples (n = 198). Similar results also emerged from analyses of a second new generalization study of 107 healthy adults that included the more detailed Ryff Scales of Psychological Well-being and found this more robust measure of eudaimonic well-being to also associate with reduced CTRA gene expression. Five of the 6 major sub-domains of psychological well-being predicted reduced CTRA gene expression when analyzed separately, and 3 remained distinctively prognostic in mutually adjusted analyses. All associations were independent of demographic characteristics, health-related confounders, and RNA indicators of leukocyte subset distribution. These results identify specific sub-dimensions of eudaimonic well-being as promising targets for future interventions to mitigate CTRA gene expression, and provide no support for any independent favorable contribution from hedonic well-being. PMID:25811656

Demethylation regulation of BDNF gene expression in dorsal root ganglion neurons is implicated in opioid-induced pain hypersensitivity in rats.

PubMed

Chao, Yu-Chieh; Xie, Fang; Li, Xueyang; Guo, Ruijuan; Yang, Ning; Zhang, Chen; Shi, Rong; Guan, Yun; Yue, Yun; Wang, Yun

2016-07-01

Repeated administration of morphine may result in opioid-induced hypersensitivity (OIH), which involves altered expression of numerous genes, including brain-derived neurotrophic factor (BDNF) in dorsal root ganglion (DRG) neurons. Yet, it remains unclear how BDNF expression is increased in DRG neurons after repeated morphine treatment. DNA methylation is an important mechanism of epigenetic control of gene expression. In the current study, we hypothesized that the demethylation regulation of certain BDNF gene promoters in DRG neurons may contribute to the development of OIH. Real-time RT-PCR was used to assess changes in the mRNA transcription levels of major BDNF exons including exon I, II, IV, VI, as well as total BDNF mRNA in DRGs from rats after repeated morphine administration. The levels of exon IV and total BDNF mRNA were significantly upregulated by repeated morphine administration, as compared to that in saline control group. Further, ELISA array and immunocytochemistry study revealed a robust upregulation of BDNF protein expression in DRG neurons after repeated morphine exposure. Correspondingly, the methylation levels of BDNF exon IV promoter showed a significant downregulation by morphine treatment. Importantly, intrathecal administration of a BDNF antibody, but not control IgG, significantly inhibited mechanical hypersensitivity that developed in rats after repeated morphine treatment. Conversely, intrathecal administration of an inhibitor of DNA methylation, 5-aza-2'-deoxycytidine (5-aza-dC) markedly upregulated the BDNF protein expression in DRG neurons and enhanced the mechanical allodynia after repeated morphine exposure. Together, our findings suggest that demethylation regulation of BDNF gene promoter may be implicated in the development of OIH through epigenetic control of BDNF expression in DRG neurons. Copyright © 2016 Elsevier Ltd. All rights reserved.

Quantitative analysis of a deeply sequenced marine microbial metatranscriptome.

PubMed

Gifford, Scott M; Sharma, Shalabh; Rinta-Kanto, Johanna M; Moran, Mary Ann

2011-03-01

The potential of metatranscriptomic sequencing to provide insights into the environmental factors that regulate microbial activities depends on how fully the sequence libraries capture community expression (that is, sample-sequencing depth and coverage depth), and the sensitivity with which expression differences between communities can be detected (that is, statistical power for hypothesis testing). In this study, we use an internal standard approach to make absolute (per liter) estimates of transcript numbers, a significant advantage over proportional estimates that can be biased by expression changes in unrelated genes. Coastal waters of the southeastern United States contain 1 × 10(12) bacterioplankton mRNA molecules per liter of seawater (~200 mRNA molecules per bacterial cell). Even for the large bacterioplankton libraries obtained in this study (~500,000 possible protein-encoding sequences in each of two libraries after discarding rRNAs and small RNAs from >1 million 454 FLX pyrosequencing reads), sample-sequencing depth was only 0.00001%. Expression levels of 82 genes diagnostic for transformations in the marine nitrogen, phosphorus and sulfur cycles ranged from below detection (<1 × 10(6) transcripts per liter) for 36 genes (for example, phosphonate metabolism gene phnH, dissimilatory nitrate reductase subunit napA) to >2.7 × 10(9) transcripts per liter (ammonia transporter amt and ammonia monooxygenase subunit amoC). Half of the categories for which expression was detected, however, had too few copy numbers for robust statistical resolution, as would be required for comparative (experimental or time-series) expression studies. By representing whole community gene abundance and expression in absolute units (per volume or mass of environment), 'omics' data can be better leveraged to improve understanding of microbially mediated processes in the ocean.

A method to facilitate and monitor expression of exogenous genes in the rat kidney using plasmid and viral vectors

PubMed Central

Corridon, Peter R.; Rhodes, George J.; Leonard, Ellen C.; Basile, David P.; Gattone, Vincent H.; Bacallao, Robert L.

2013-01-01

Gene therapy has been proposed as a novel alternative to treat kidney disease. This goal has been hindered by the inability to reliably deliver transgenes to target cells throughout the kidney, while minimizing injury. Since hydrodynamic forces have previously shown promising results, we optimized this approach and designed a method that utilizes retrograde renal vein injections to facilitate transgene expression in rat kidneys. We show, using intravital fluorescence two-photon microscopy, that fluorescent albumin and dextrans injected into the renal vein under defined conditions of hydrodynamic pressure distribute broadly throughout the kidney in live animals. We found injection parameters that result in no kidney injury as determined by intravital microscopy, histology, and serum creatinine measurements. Plasmids, baculovirus, and adenovirus vectors, designed to express EGFP, EGFP-actin, EGFP-occludin, EGFP-tubulin, tdTomato-H2B, or RFP-actin fusion proteins, were introduced into live kidneys in a similar fashion. Gene expression was then observed in live and ex vivo kidneys using two-photon imaging and confocal laser scanning microscopy. We recorded widespread fluorescent protein expression lasting more than 1 mo after introduction of transgenes. Plasmid and adenovirus vectors provided gene transfer efficiencies ranging from 50 to 90%, compared with 10–50% using baculovirus. Using plasmids and adenovirus, fluorescent protein expression was observed 1) in proximal and distal tubule epithelial cells; 2) within glomeruli; and 3) within the peritubular interstitium. In isolated kidneys, fluorescent protein expression was observed from the cortex to the papilla. These results provide a robust approach for gene delivery and the study of protein function in live mammal kidneys. PMID:23467422

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.

MicroRNA function in Drosophila melanogaster.

PubMed

Carthew, Richard W; Agbu, Pamela; Giri, Ritika

2017-05-01

Over the last decade, microRNAs have emerged as critical regulators in the expression and function of animal genomes. This review article discusses the relationship between microRNA-mediated regulation and the biology of the fruit fly Drosophila melanogaster. We focus on the roles that microRNAs play in tissue growth, germ cell development, hormone action, and the development and activity of the central nervous system. We also discuss the ways in which microRNAs affect robustness. Many gene regulatory networks are robust; they are relatively insensitive to the precise values of reaction constants and concentrations of molecules acting within the networks. MicroRNAs involved in robustness appear to be nonessential under uniform conditions used in conventional laboratory experiments. However, the robust functions of microRNAs can be revealed when environmental or genetic variation otherwise has an impact on developmental outcomes. Copyright © 2016 Elsevier Ltd. All rights reserved.

SLC12A7 alters adrenocortical carcinoma cell adhesion properties to promote an aggressive invasive behavior.

PubMed

Brown, Taylor C; Murtha, Timothy D; Rubinstein, Jill C; Korah, Reju; Carling, Tobias

2018-06-08

Altered expression of Solute Carrier Family 12 Member 7 (SLC12A7) is implicated to promote malignant behavior in multiple cancer types through an incompletely understood mechanism. Recent studies have shown recurrent gene amplifications and overexpression of SLC12A7 in adrenocortical carcinoma (ACC). The potential mechanistic effect(s) of SLC12A7 amplifications in portending an aggressive behavior in ACC has not been previously studied and is investigated here using two established ACC cell lines, SW-13 and NCI-H295R. SW-13 cells, which express negligible amounts of SLC12A7, were enforced to express SLC12A7 constitutively, while RNAi gene silencing was performed in NCI-H295R cells, which have robust endogenous expression of SLC12A7. In vitro studies tested the outcomes of experimental alterations in SLC12A7 expression on malignant characteristics, including cell viability, growth, colony formation potential, motility, invasive capacity, adhesion and detachment kinetics, and cell membrane organization. Further, potential alterations in transcription regulation downstream to induced SLC12A7 overexpression was explored using targeted transcription factor expression arrays. Enforced SLC12A7 overexpression in SW-13 cells robustly promoted motility and invasive characteristics (p < 0.05) without significantly altering cell viability, growth, or colony formation potential. SLC12A7 overexpression also significantly increased rates of cellular attachment and detachment turnover (p < 0.05), potentially propelled by increased filopodia formation and/or Ezrin interaction. In contrast, RNAi gene silencing of SLC12A7 stymied cell attachment strength as well as migration and invasion capacity in NCI-H295R cells. Transcription factor expression analysis identified multiple signally pathways potentially affected by SLC12A7 overexpression, including osmotic stress, bone morphogenetic protein, and Hippo signaling pathways. Amplification of SLC12A7 observed in ACCs is shown here, in vitro, to exacerbate the malignant behavior of ACC cells by promoting invasive capacities, possibly mediated by alterations in multiple signaling pathways, including the osmotic stress pathway.

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

PubMed

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

2015-01-01

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

Compound-specific effects of diverse neurodevelopmental toxicants on global gene expression in the neural embryonic stem cell test (ESTn)

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

Theunissen, P.T., E-mail: Peter.Theunissen@rivm.nl; Department of Toxicogenomics, Maastricht University, Maastricht; Robinson, J.F.

Alternative assays for developmental toxicity testing are needed to reduce animal use in regulatory toxicology. The in vitro murine neural embryonic stem cell test (ESTn) was designed as an alternative for neurodevelopmental toxicity testing. The integration of toxicogenomic-based approaches may further increase predictivity as well as provide insight into underlying mechanisms of developmental toxicity. In the present study, we investigated concentration-dependent effects of six mechanistically diverse compounds, acetaldehyde (ACE), carbamazepine (CBZ), flusilazole (FLU), monoethylhexyl phthalate (MEHP), penicillin G (PENG) and phenytoin (PHE), on the transcriptome and neural differentiation in the ESTn. All compounds with the exception of PENG altered ESTnmore » morphology (cytotoxicity and neural differentiation) in a concentration-dependent manner. Compound induced gene expression changes and corresponding enriched gene ontology biological processes (GO–BP) were identified after 24 h exposure at equipotent differentiation-inhibiting concentrations of the compounds. Both compound-specific and common gene expression changes were observed between subsets of tested compounds, in terms of significance, magnitude of regulation and functionality. For example, ACE, CBZ and FLU induced robust changes in number of significantly altered genes (≥ 687 genes) as well as a variety of GO–BP, as compared to MEHP, PHE and PENG (≤ 55 genes with no significant changes in GO–BP observed). Genes associated with developmentally related processes (embryonic morphogenesis, neuron differentiation, and Wnt signaling) showed diverse regulation after exposure to ACE, CBZ and FLU. In addition, gene expression and GO–BP enrichment showed concentration dependence, allowing discrimination of non-toxic versus toxic concentrations on the basis of transcriptomics. This information may be used to define adaptive versus toxic responses at the transcriptome level.« less

Circadian physiology of metabolism.

PubMed

Panda, Satchidananda

2016-11-25

A majority of mammalian genes exhibit daily fluctuations in expression levels, making circadian expression rhythms the largest known regulatory network in normal physiology. Cell-autonomous circadian clocks interact with daily light-dark and feeding-fasting cycles to generate approximately 24-hour oscillations in the function of thousands of genes. Circadian expression of secreted molecules and signaling components transmits timing information between cells and tissues. Such intra- and intercellular daily rhythms optimize physiology both by managing energy use and by temporally segregating incompatible processes. Experimental animal models and epidemiological data indicate that chronic circadian rhythm disruption increases the risk of metabolic diseases. Conversely, time-restricted feeding, which imposes daily cycles of feeding and fasting without caloric reduction, sustains robust diurnal rhythms and can alleviate metabolic diseases. These findings highlight an integrative role of circadian rhythms in physiology and offer a new perspective for treating chronic diseases in which metabolic disruption is a hallmark. Copyright © 2016, American Association for the Advancement of Science.

High temporal-resolution view of transcription and chromatin states across distinct metabolic states in budding yeast

PubMed Central

Kuang, Zheng; Cai, Ling; Zhang, Xuekui; Ji, Hongkai; Tu, Benjamin P.; Boeke, Jef D.

2014-01-01

Under continuous, glucose-limited conditions, budding yeast exhibit robust metabolic cycles associated with major oscillations of gene expression. How such fluctuations are linked to changes in chromatin status is not well understood. Here we examine the correlated genome-wide transcription and chromatin states across the yeast metabolic cycle at unprecedented temporal resolution, revealing a “just-in-time supply chain” by which components from specific cellular processes such as ribosome biogenesis become available in a highly coordinated manner. We identify distinct chromatin and splicing patterns associated with different gene categories and determine the relative timing of chromatin modifications to maximal transcription. There is unexpected variation in the chromatin modification and expression relationship, with histone acetylation peaks occurring with varying timing and “sharpness” relative to RNA expression both within and between cycle phases. Chromatin modifier occupancy reveals subtly distinct spatial and temporal patterns compared to the modifications themselves. PMID:25173176

COX2 Inhibition Reduces Aortic Valve Calcification In Vivo

PubMed Central

Wirrig, Elaine E.; Gomez, M. Victoria; Hinton, Robert B.; Yutzey, Katherine E.

2016-01-01

Objective Calcific aortic valve disease (CAVD) is a significant cause of morbidity and mortality, which affects approximately 1% of the US population and is characterized by calcific nodule formation and stenosis of the valve. Klotho-deficient mice were used to study the molecular mechanisms of CAVD as they develop robust aortic valve (AoV) calcification. Through microarray analysis of AoV tissues from klotho-deficient and wild type mice, increased expression of the gene encoding cyclooxygenase 2/COX2 (Ptgs2) was found. COX2 activity contributes to bone differentiation and homeostasis, thus the contribution of COX2 activity to AoV calcification was assessed. Approach and Results In klotho-deficient mice, COX2 expression is increased throughout regions of valve calcification and is induced in the valvular interstitial cells (VICs) prior to calcification formation. Similarly, COX2 expression is increased in human diseased AoVs. Treatment of cultured porcine aortic VICs with osteogenic media induces bone marker gene expression and calcification in vitro, which is blocked by inhibition of COX2 activity. In vivo, genetic loss of function of COX2 cyclooxygenase activity partially rescues AoV calcification in klotho-deficient mice. Moreover, pharmacologic inhibition of COX2 activity in klotho-deficient mice via celecoxib-containing diet reduces AoV calcification and blocks osteogenic gene expression. Conclusions COX2 expression is upregulated in CAVD and its activity contributes to osteogenic gene induction and valve calcification in vitro and in vivo. PMID:25722432

Evaluation of a toxicogenomic approach to the local lymph node assay (LLNA).

PubMed

Boverhof, Darrell R; Gollapudi, B Bhaskar; Hotchkiss, Jon A; Osterloh-Quiroz, Mandy; Woolhiser, Michael R

2009-02-01

Genomic technologies have the potential to enhance and complement existing toxicology endpoints; however, assessment of these approaches requires a systematic evaluation including a robust experimental design with genomic endpoints anchored to traditional toxicology endpoints. The present study was conducted to assess the sensitivity of genomic responses when compared with the traditional local lymph node assay (LLNA) endpoint of lymph node cell proliferation and to evaluate the responses for their ability to provide insights into mode of action. Female BALB/c mice were treated with the sensitizer trimellitic anhydride (TMA), following the standard LLNA dosing regimen, at doses of 0.1, 1, or 10% and traditional tritiated thymidine ((3)HTdR) incorporation and gene expression responses were monitored in the auricular lymph nodes. Additional mice dosed with either vehicle or 10% TMA and sacrificed on day 4 or 10, were also included to examine temporal effects on gene expression. Analysis of (3)HTdR incorporation revealed TMA-induced stimulation indices of 2.8, 22.9, and 61.0 relative to vehicle with an EC(3) of 0.11%. Examination of the dose-response gene expression responses identified 9, 833, and 2122 differentially expressed genes relative to vehicle for the 0.1, 1, and 10% TMA dose groups, respectively. Calculation of EC(3) values for differentially expressed genes did not identify a response that was more sensitive than the (3)HTdR value, although a number of genes displayed comparable sensitivity. Examination of temporal responses revealed 1760, 1870, and 953 differentially expressed genes at the 4-, 6-, and 10-day time points respectively. Functional analysis revealed many responses displayed dose- and time-specific induction patterns within the functional categories of cellular proliferation and immune response, including numerous immunoglobin genes which were highly induced at the day 10 time point. Overall, these experiments have systematically illustrated the potential utility of genomic endpoints to enhance the LLNA and support further exploration of this approach through examination of a more diverse array of chemicals.

Biolistic Transformation of Wheat.

PubMed

Tassy, Caroline; Barret, Pierre

2017-01-01

The wheat genome encodes some 100,000 genes. To understand how the expression of these genes is regulated it will be necessary to carry out many genetic transformation experiments. Robust protocols that allow scientists to transform a wide range of wheat genotypes are therefore required. In this chapter, we describe a protocol for biolistic transformation of wheat that uses immature embryos and small quantities of DNA cassettes. An original method for DNA cassette purification is also described. This protocol can be used to transform a wide range of wheat genotypes and other related species.

NFκB pathway analysis: An approach to analyze gene co-expression networks employing feedback cycles.

PubMed

Dillenburg, Fabiane Cristine; Zanotto-Filho, Alfeu; Fonseca Moreira, José Cláudio; Ribeiro, Leila; Carro, Luigi

2018-02-01

The genes of the NFκB pathway are involved in the control of a plethora of biological processes ranking from inhibition of apoptosis to metastasis in cancer. It has been described that Gliobastoma multiforme (GBM) patients carry aberrant NFκB activation, but the molecular mechanisms are not completely understood. Here, we present a NFκB pathway analysis in tumor specimens of GBM compared to non-neoplasic brain tissues, based on the different kind of cycles found among genes of a gene co-expression network constructed using quantized data obtained from the microarrays. A cycle is a closed walk with all vertices distinct (except the first and last). Thanks to this way of finding relations among genes, a more robust interpretation of gene correlations is possible, because the cycles are associated with feedback mechanisms that are very common in biological networks. In GBM samples, we could conclude that the stoichiometric relationship between genes involved in NFκB pathway regulation is unbalanced. This can be measured and explained by the identification of a cycle. This conclusion helps to understand more about the biology of this type of tumor. Copyright © 2017 Elsevier Ltd. All rights reserved.

A reference gene set for sex pheromone biosynthesis and degradation genes from the diamondback moth, Plutella xylostella, based on genome and transcriptome digital gene expression analyses.

PubMed

He, Peng; Zhang, Yun-Fei; Hong, Duan-Yang; Wang, Jun; Wang, Xing-Liang; Zuo, Ling-Hua; Tang, Xian-Fu; Xu, Wei-Ming; He, Ming

2017-03-01

Female moths synthesize species-specific sex pheromone components and release them to attract male moths, which depend on precise sex pheromone chemosensory system to locate females. Two types of genes involved in the sex pheromone biosynthesis and degradation pathways play essential roles in this important moth behavior. To understand the function of genes in the sex pheromone pathway, this study investigated the genome-wide and digital gene expression of sex pheromone biosynthesis and degradation genes in various adult tissues in the diamondback moth (DBM), Plutella xylostella, which is a notorious vegetable pest worldwide. A massive transcriptome data (at least 39.04 Gb) was generated by sequencing 6 adult tissues including male antennae, female antennae, heads, legs, abdomen and female pheromone glands from DBM by using Illumina 4000 next-generation sequencing and mapping to a published DBM genome. Bioinformatics analysis yielded a total of 89,332 unigenes among which 87 transcripts were putatively related to seven gene families in the sex pheromone biosynthesis pathway. Among these, seven [two desaturases (DES), three fatty acyl-CoA reductases (FAR) one acetyltransferase (ACT) and one alcohol dehydrogenase (AD)] were mainly expressed in the pheromone glands with likely function in the three essential sex pheromone biosynthesis steps: desaturation, reduction, and esterification. We also identified 210 odorant-degradation related genes (including sex pheromone-degradation related genes) from seven major enzyme groups. Among these genes, 100 genes are new identified and two aldehyde oxidases (AOXs), one aldehyde dehydrogenase (ALDH), five carboxyl/cholinesterases (CCEs), five UDP-glycosyltransferases (UGTs), eight cytochrome P450 (CYP) and three glutathione S-transferases (GSTs) displayed more robust expression in the antennae, and thus are proposed to participate in the degradation of sex pheromone components and plant volatiles. To date, this is the most comprehensive gene data set of sex pheromone biosynthesis and degradation enzyme related genes in DBM created by genome- and transcriptome-wide identification, characterization and expression profiling. Our findings provide a basis to better understand the function of genes with tissue enriched expression. The results also provide information on the genes involved in sex pheromone biosynthesis and degradation, and may be useful to identify potential gene targets for pest control strategies by disrupting the insect-insect communication using pheromone-based behavioral antagonists.

A novel rapid and reproducible flow cytometric method for optimization of transfection efficiency in cells

PubMed Central

Homann, Stefanie; Hofmann, Christian; Gorin, Aleksandr M.; Nguyen, Huy Cong Xuan; Huynh, Diana; Hamid, Phillip; Maithel, Neil; Yacoubian, Vahe; Mu, Wenli; Kossyvakis, Athanasios; Sen Roy, Shubhendu; Yang, Otto Orlean

2017-01-01

Transfection is one of the most frequently used techniques in molecular biology that is also applicable for gene therapy studies in humans. One of the biggest challenges to investigate the protein function and interaction in gene therapy studies is to have reliable monospecific detection reagents, particularly antibodies, for all human gene products. Thus, a reliable method that can optimize transfection efficiency based on not only expression of the target protein of interest but also the uptake of the nucleic acid plasmid, can be an important tool in molecular biology. Here, we present a simple, rapid and robust flow cytometric method that can be used as a tool to optimize transfection efficiency at the single cell level while overcoming limitations of prior established methods that quantify transfection efficiency. By using optimized ratios of transfection reagent and a nucleic acid (DNA or RNA) vector directly labeled with a fluorochrome, this method can be used as a tool to simultaneously quantify cellular toxicity of different transfection reagents, the amount of nucleic acid plasmid that cells have taken up during transfection as well as the amount of the encoded expressed protein. Finally, we demonstrate that this method is reproducible, can be standardized and can reliably and rapidly quantify transfection efficiency, reducing assay costs and increasing throughput while increasing data robustness. PMID:28863132

Critical Dynamics in Genetic Regulatory Networks: Examples from Four Kingdoms

PubMed Central

Balleza, Enrique; Alvarez-Buylla, Elena R.; Chaos, Alvaro; Kauffman, Stuart; Shmulevich, Ilya; Aldana, Maximino

2008-01-01

The coordinated expression of the different genes in an organism is essential to sustain functionality under the random external perturbations to which the organism might be subjected. To cope with such external variability, the global dynamics of the genetic network must possess two central properties. (a) It must be robust enough as to guarantee stability under a broad range of external conditions, and (b) it must be flexible enough to recognize and integrate specific external signals that may help the organism to change and adapt to different environments. This compromise between robustness and adaptability has been observed in dynamical systems operating at the brink of a phase transition between order and chaos. Such systems are termed critical. Thus, criticality, a precise, measurable, and well characterized property of dynamical systems, makes it possible for robustness and adaptability to coexist in living organisms. In this work we investigate the dynamical properties of the gene transcription networks reported for S. cerevisiae, E. coli, and B. subtilis, as well as the network of segment polarity genes of D. melanogaster, and the network of flower development of A. thaliana. We use hundreds of microarray experiments to infer the nature of the regulatory interactions among genes, and implement these data into the Boolean models of the genetic networks. Our results show that, to the best of the current experimental data available, the five networks under study indeed operate close to criticality. The generality of this result suggests that criticality at the genetic level might constitute a fundamental evolutionary mechanism that generates the great diversity of dynamically robust living forms that we observe around us. PMID:18560561

The Zn finger protein Iguana impacts Hedgehog signaling by promoting ciliogenesis.

PubMed

Glazer, Andrew M; Wilkinson, Alex W; Backer, Chelsea B; Lapan, Sylvain W; Gutzman, Jennifer H; Cheeseman, Iain M; Reddien, Peter W

2010-01-01

Hedgehog signaling is critical for metazoan development and requires cilia for pathway activity. The gene iguana was discovered in zebrafish as required for Hedgehog signaling, and encodes a novel Zn finger protein. Planarians are flatworms with robust regenerative capacities and utilize epidermal cilia for locomotion. RNA interference of Smed-iguana in the planarian Schmidtea mediterranea caused cilia loss and failure to regenerate new cilia, but did not cause defects similar to those observed in hedgehog(RNAi) animals. Smed-iguana gene expression was also similar in pattern to the expression of multiple other ciliogenesis genes, but was not required for expression of these ciliogenesis genes. iguana-defective zebrafish had too few motile cilia in pronephric ducts and in Kupffer's vesicle. Kupffer's vesicle promotes left-right asymmetry and iguana mutant embryos had left-right asymmetry defects. Finally, human Iguana proteins (dZIP1 and dZIP1L) localize to the basal bodies of primary cilia and, together, are required for primary cilia formation. Our results indicate that a critical and broadly conserved function for Iguana is in ciliogenesis and that this function has come to be required for Hedgehog signaling in vertebrates.

Gene-Expression Signature Predicts Postoperative Recurrence in Stage I Non-Small Cell Lung Cancer Patients

PubMed Central

Lu, Yan; Wang, Liang; Liu, Pengyuan; Yang, Ping; You, Ming

2012-01-01

About 30% stage I non-small cell lung cancer (NSCLC) patients undergoing resection will recur. Robust prognostic markers are required to better manage therapy options. The purpose of this study is to develop and validate a novel gene-expression signature that can predict tumor recurrence of stage I NSCLC patients. Cox proportional hazards regression analysis was performed to identify recurrence-related genes and a partial Cox regression model was used to generate a gene signature of recurrence in the training dataset −142 stage I lung adenocarcinomas without adjunctive therapy from the Director's Challenge Consortium. Four independent validation datasets, including GSE5843, GSE8894, and two other datasets provided by Mayo Clinic and Washington University, were used to assess the prediction accuracy by calculating the correlation between risk score estimated from gene expression and real recurrence-free survival time and AUC of time-dependent ROC analysis. Pathway-based survival analyses were also performed. 104 probesets correlated with recurrence in the training dataset. They are enriched in cell adhesion, apoptosis and regulation of cell proliferation. A 51-gene expression signature was identified to distinguish patients likely to develop tumor recurrence (Dxy = −0.83, P<1e-16) and this signature was validated in four independent datasets with AUC >85%. Multiple pathways including leukocyte transendothelial migration and cell adhesion were highly correlated with recurrence-free survival. The gene signature is highly predictive of recurrence in stage I NSCLC patients, which has important prognostic and therapeutic implications for the future management of these patients. PMID:22292069

Genome-wide analysis of drought induced gene expression changes in flax (Linum usitatissimum).

PubMed

Dash, Prasanta K; Cao, Yongguo; Jailani, Abdul K; Gupta, Payal; Venglat, Prakash; Xiang, Daoquan; Rai, Rhitu; Sharma, Rinku; Thirunavukkarasu, Nepolean; Abdin, Malik Z; Yadava, Devendra K; Singh, Nagendra K; Singh, Jas; Selvaraj, Gopalan; Deyholos, Mike; Kumar, Polumetla Ananda; Datla, Raju

2014-01-01

A robust phenotypic plasticity to ward off adverse environmental conditions determines performance and productivity in crop plants. Flax (linseed), is an important cash crop produced for natural textile fiber (linen) or oilseed with many health promoting products. This crop is prone to drought stress and yield losses in many parts of the world. Despite recent advances in drought research in a number of important crops, related progress in flax is very limited. Since, response of this plant to drought stress has not been addressed at the molecular level; we conducted microarray analysis to capture transcriptome associated with induced drought in flax. This study identified 183 differentially expressed genes (DEGs) associated with diverse cellular, biophysical and metabolic programs in flax. The analysis also revealed especially the altered regulation of cellular and metabolic pathways governing photosynthesis. Additionally, comparative transcriptome analysis identified a plethora of genes that displayed differential regulation both spatially and temporally. These results revealed co-regulated expression of 26 genes in both shoot and root tissues with implications for drought stress response. Furthermore, the data also showed that more genes are upregulated in roots compared to shoots, suggesting that roots may play important and additional roles in response to drought in flax. With prolonged drought treatment, the number of DEGs increased in both tissue types. Differential expression of selected genes was confirmed by qRT-PCR, thus supporting the suggested functional association of these intrinsic genes in maintaining growth and homeostasis in response to imminent drought stress in flax. Together the present study has developed foundational and new transcriptome data sets for drought stress in flax.

A defined Oct4 level governs cell state transitions of pluripotency entry and differentiation into all embryonic lineages.

PubMed

Radzisheuskaya, Aliaksandra; Chia, Gloryn Le Bin; dos Santos, Rodrigo L; Theunissen, Thorold W; Castro, L Filipe C; Nichols, Jennifer; Silva, José C R

2013-06-01

Oct4 is considered a master transcription factor for pluripotent cell self-renewal, but its biology remains poorly understood. Here, we investigated the role of Oct4 using the process of induced pluripotency. We found that a defined embryonic stem cell (ESC) level of Oct4 is required for pluripotency entry. However, once pluripotency is established, the Oct4 level can be decreased up to sevenfold without loss of self-renewal. Unexpectedly, cells constitutively expressing Oct4 at an ESC level robustly differentiated into all embryonic lineages and germline. In contrast, cells with low Oct4 levels were deficient in differentiation, exhibiting expression of naive pluripotency genes in the absence of pluripotency culture requisites. The restoration of Oct4 expression to an ESC level rescued the ability of these to restrict naive pluripotent gene expression and to differentiate. In conclusion, a defined Oct4 level controls the establishment of naive pluripotency as well as commitment to all embryonic lineages.

Evaluation of reference genes for insect olfaction studies.

PubMed

Omondi, Bonaventure Aman; Latorre-Estivalis, Jose Manuel; Rocha Oliveira, Ivana Helena; Ignell, Rickard; Lorenzo, Marcelo Gustavo

2015-04-22

Quantitative reverse transcription PCR (qRT-PCR) is a robust and accessible method to assay gene expression and to infer gene regulation. Being a chain of procedures, this technique is subject to systematic error due to biological and technical limitations mainly set by the starting material and downstream procedures. Thus, rigorous data normalization is critical to grant reliability and repeatability of gene expression quantification by qRT-PCR. A number of 'housekeeping genes', involved in basic cellular functions, have been commonly used as internal controls for this normalization process. However, these genes could themselves be regulated and must therefore be tested a priori. We evaluated eight potential reference genes for their stability as internal controls for RT-qPCR studies of olfactory gene expression in the antennae of Rhodnius prolixus, a Chagas disease vector. The set of genes included were: α-tubulin; β-actin; Glyceraldehyde-3-phosphate dehydrogenase; Eukaryotic initiation factor 1A; Glutathione-S-transferase; Serine protease; Succinate dehydrogenase; and Glucose-6-phosphate dehydrogenase. Five experimental conditions, including changes in age,developmental stage and feeding status were tested in both sexes. We show that the evaluation of candidate reference genes is necessary for each combination of sex, tissue and physiological condition analyzed in order to avoid inconsistent results and conclusions. Although, Normfinder and geNorm software yielded different results between males and females, five genes (SDH, Tub, GAPDH, Act and G6PDH) appeared in the first positions in all rankings obtained. By using gene expression data of a single olfactory coreceptor gene as an example, we demonstrated the extent of changes expected using different internal standards. This work underlines the need for a rigorous selection of internal standards to grant the reliability of normalization processes in qRT-PCR studies. Furthermore, we show that particular physiological or developmental conditions require independent evaluation of a diverse set of potential reference genes.

Detection of histone modifications in plant leaves.

PubMed

Jaskiewicz, Michal; Peterhansel, Christoph; Conrath, Uwe

2011-09-23

Chromatin structure is important for the regulation of gene expression in eukaryotes. In this process, chromatin remodeling, DNA methylation, and covalent modifications on the amino-terminal tails of histones H3 and H4 play essential roles(1-2). H3 and H4 histone modifications include methylation of lysine and arginine, acetylation of lysine, and phosphorylation of serine residues(1-2). These modifications are associated either with gene activation, repression, or a primed state of gene that supports more rapid and robust activation of expression after perception of appropriate signals (microbe-associated molecular patterns, light, hormones, etc.)(3-7). Here, we present a method for the reliable and sensitive detection of specific chromatin modifications on selected plant genes. The technique is based on the crosslinking of (modified) histones and DNA with formaldehyde(8,9), extraction and sonication of chromatin, chromatin immunoprecipitation (ChIP) with modification-specific antibodies(9,10), de-crosslinking of histone-DNA complexes, and gene-specific real-time quantitative PCR. The approach has proven useful for detecting specific histone modifications associated with C(4;) photosynthesis in maize(5,11) and systemic immunity in Arabidopsis(3).

Programmable single-cell mammalian biocomputers.

PubMed

Ausländer, Simon; Ausländer, David; Müller, Marius; Wieland, Markus; Fussenegger, Martin

2012-07-05

Synthetic biology has advanced the design of standardized control devices that program cellular functions and metabolic activities in living organisms. Rational interconnection of these synthetic switches resulted in increasingly complex designer networks that execute input-triggered genetic instructions with precision, robustness and computational logic reminiscent of electronic circuits. Using trigger-controlled transcription factors, which independently control gene expression, and RNA-binding proteins that inhibit the translation of transcripts harbouring specific RNA target motifs, we have designed a set of synthetic transcription–translation control devices that could be rewired in a plug-and-play manner. Here we show that these combinatorial circuits integrated a two-molecule input and performed digital computations with NOT, AND, NAND and N-IMPLY expression logic in single mammalian cells. Functional interconnection of two N-IMPLY variants resulted in bitwise intracellular XOR operations, and a combinatorial arrangement of three logic gates enabled independent cells to perform programmable half-subtractor and half-adder calculations. Individual mammalian cells capable of executing basic molecular arithmetic functions isolated or coordinated to metabolic activities in a predictable, precise and robust manner may provide new treatment strategies and bio-electronic interfaces in future gene-based and cell-based therapies.

Sensory Cortical Plasticity Participates in the Epigenetic Regulation of Robust Memory Formation

PubMed Central

Phan, Mimi L.; Bieszczad, Kasia M.

2016-01-01

Neuroplasticity remodels sensory cortex across the lifespan. A function of adult sensory cortical plasticity may be capturing available information during perception for memory formation. The degree of experience-dependent remodeling in sensory cortex appears to determine memory strength and specificity for important sensory signals. A key open question is how plasticity is engaged to induce different degrees of sensory cortical remodeling. Neural plasticity for long-term memory requires the expression of genes underlying stable changes in neuronal function, structure, connectivity, and, ultimately, behavior. Lasting changes in transcriptional activity may depend on epigenetic mechanisms; some of the best studied in behavioral neuroscience are DNA methylation and histone acetylation and deacetylation, which, respectively, promote and repress gene expression. One purpose of this review is to propose epigenetic regulation of sensory cortical remodeling as a mechanism enabling the transformation of significant information from experiences into content-rich memories of those experiences. Recent evidence suggests how epigenetic mechanisms regulate highly specific reorganization of sensory cortical representations that establish a widespread network for memory. Thus, epigenetic mechanisms could initiate events to establish exceptionally persistent and robust memories at a systems-wide level by engaging sensory cortical plasticity for gating what and how much information becomes encoded. PMID:26881129

Disturbed Placental Imprinting in Preeclampsia Leads to Altered Expression of DLX5, a Human-Specific Early Trophoblast Marker

PubMed Central

Zadora, Julianna; Singh, Manvendra; Herse, Florian; Przybyl, Lukasz; Haase, Nadine; Golic, Michaela; Yung, Hong Wa; Huppertz, Berthold; Cartwright, Judith E.; Whitley, Guy; Johnsen, Guro M.; Levi, Giovanni; Isbruch, Annette; Schulz, Herbert; Luft, Friedrich C.; Müller, Dominik N.; Staff, Anne Cathrine

2017-01-01

Background: Preeclampsia is a complex and common human-specific pregnancy syndrome associated with placental pathology. The human specificity provides both intellectual and methodological challenges, lacking a robust model system. Given the role of imprinted genes in human placentation and the vulnerability of imprinted genes to loss of imprinting changes, there has been extensive speculation, but no robust evidence, that imprinted genes are involved in preeclampsia. Our study aims to investigate whether disturbed imprinting contributes to preeclampsia. Methods: We first aimed to confirm that preeclampsia is a disease of the placenta by generating and analyzing genome-wide molecular data on well-characterized patient material. We performed high-throughput transcriptome analyses of multiple placenta samples from healthy controls and patients with preeclampsia. Next, we identified differentially expressed genes in preeclamptic placentas and intersected them with the list of human imprinted genes. We used bioinformatics/statistical analyses to confirm association between imprinting and preeclampsia and to predict biological processes affected in preeclampsia. Validation included epigenetic and cellular assays. In terms of human specificity, we established an in vitro invasion-differentiation trophoblast model. Our comparative phylogenetic analysis involved single-cell transcriptome data of human, macaque, and mouse preimplantation embryogenesis. Results: We found disturbed placental imprinting in preeclampsia and revealed potential candidates, including GATA3 and DLX5, with poorly explored imprinted status and no prior association with preeclampsia. As a result of loss of imprinting, DLX5 was upregulated in 69% of preeclamptic placentas. Levels of DLX5 correlated with classic preeclampsia markers. DLX5 is expressed in human but not in murine trophoblast. The DLX5high phenotype resulted in reduced proliferation, increased metabolism, and endoplasmic reticulum stress-response activation in trophoblasts in vitro. The transcriptional profile of such cells mimics the transcriptome of preeclamptic placentas. Pan-mammalian comparative analysis identified DLX5 as part of the human-specific regulatory network of trophoblast differentiation. Conclusions: Our analysis provides evidence of a true association among disturbed imprinting, gene expression, and preeclampsia. As a result of disturbed imprinting, the upregulated DLX5 affects trophoblast proliferation. Our in vitro model might fill a vital niche in preeclampsia research. Human-specific regulatory circuitry of DLX5 might help explain certain aspects of preeclampsia. PMID:28904069

Disturbed Placental Imprinting in Preeclampsia Leads to Altered Expression of DLX5, a Human-Specific Early Trophoblast Marker.

PubMed

Zadora, Julianna; Singh, Manvendra; Herse, Florian; Przybyl, Lukasz; Haase, Nadine; Golic, Michaela; Yung, Hong Wa; Huppertz, Berthold; Cartwright, Judith E; Whitley, Guy; Johnsen, Guro M; Levi, Giovanni; Isbruch, Annette; Schulz, Herbert; Luft, Friedrich C; Müller, Dominik N; Staff, Anne Cathrine; Hurst, Laurence D; Dechend, Ralf; Izsvák, Zsuzsanna

2017-11-07

Preeclampsia is a complex and common human-specific pregnancy syndrome associated with placental pathology. The human specificity provides both intellectual and methodological challenges, lacking a robust model system. Given the role of imprinted genes in human placentation and the vulnerability of imprinted genes to loss of imprinting changes, there has been extensive speculation, but no robust evidence, that imprinted genes are involved in preeclampsia. Our study aims to investigate whether disturbed imprinting contributes to preeclampsia. We first aimed to confirm that preeclampsia is a disease of the placenta by generating and analyzing genome-wide molecular data on well-characterized patient material. We performed high-throughput transcriptome analyses of multiple placenta samples from healthy controls and patients with preeclampsia. Next, we identified differentially expressed genes in preeclamptic placentas and intersected them with the list of human imprinted genes. We used bioinformatics/statistical analyses to confirm association between imprinting and preeclampsia and to predict biological processes affected in preeclampsia. Validation included epigenetic and cellular assays. In terms of human specificity, we established an in vitro invasion-differentiation trophoblast model. Our comparative phylogenetic analysis involved single-cell transcriptome data of human, macaque, and mouse preimplantation embryogenesis. We found disturbed placental imprinting in preeclampsia and revealed potential candidates, including GATA3 and DLX5 , with poorly explored imprinted status and no prior association with preeclampsia. As a result of loss of imprinting, DLX5 was upregulated in 69% of preeclamptic placentas. Levels of DLX5 correlated with classic preeclampsia markers. DLX5 is expressed in human but not in murine trophoblast. The DLX5 high phenotype resulted in reduced proliferation, increased metabolism, and endoplasmic reticulum stress-response activation in trophoblasts in vitro. The transcriptional profile of such cells mimics the transcriptome of preeclamptic placentas. Pan-mammalian comparative analysis identified DLX5 as part of the human-specific regulatory network of trophoblast differentiation. Our analysis provides evidence of a true association among disturbed imprinting, gene expression, and preeclampsia. As a result of disturbed imprinting, the upregulated DLX5 affects trophoblast proliferation. Our in vitro model might fill a vital niche in preeclampsia research. Human-specific regulatory circuitry of DLX5 might help explain certain aspects of preeclampsia. © 2017 The Authors.

Microarray Analyses Reveal Marked Differences in Growth Factor and Receptor Expression Between 8-Cell Human Embryos and Pluripotent Stem Cells

PubMed Central

Vlismas, Antonis; Bletsa, Ritsa; Mavrogianni, Despina; Mamali, Georgina; Pergamali, Maria; Dinopoulou, Vasiliki; Partsinevelos, George; Drakakis, Peter; Loutradis, Dimitris

2016-01-01

Previous microarray analyses of RNAs from 8-cell (8C) human embryos revealed a lack of cell cycle checkpoints and overexpression of core circadian oscillators and cell cycle drivers relative to pluripotent human stem cells [human embryonic stem cells/induced pluripotent stem (hES/iPS)] and fibroblasts, suggesting growth factor independence during early cleavage stages. To explore this possibility, we queried our combined microarray database for expression of 487 growth factors and receptors. Fifty-one gene elements were overdetected on the 8C arrays relative to hES/iPS cells, including 14 detected at least 80-fold higher, which annotated to multiple pathways: six cytokine family (CSF1R, IL2RG, IL3RA, IL4, IL17B, IL23R), four transforming growth factor beta (TGFB) family (BMP6, BMP15, GDF9, ENG), one fibroblast growth factor (FGF) family [FGF14(FH4)], one epidermal growth factor member (GAB1), plus CD36, and CLEC10A. 8C-specific gene elements were enriched (73%) for reported circadian-controlled genes in mouse tissues. High-level detection of CSF1R, ENG, IL23R, and IL3RA specifically on the 8C arrays suggests the embryo plays an active role in blocking immune rejection and is poised for trophectoderm development; robust detection of NRG1, GAB1, -2, GRB7, and FGF14(FHF4) indicates novel roles in early development in addition to their known roles in later development. Forty-four gene elements were underdetected on the 8C arrays, including 11 at least 80-fold under the pluripotent cells: two cytokines (IFITM1, TNFRSF8), five TGFBs (BMP7, LEFTY1, LEFTY2, TDGF1, TDGF3), two FGFs (FGF2, FGF receptor 1), plus ING5, and WNT6. The microarray detection patterns suggest that hES/iPS cells exhibit suppressed circadian competence, underexpression of early differentiation markers, and more robust expression of generic pluripotency genes, in keeping with an artificial state of continual uncommitted cell division. In contrast, gene expression patterns of the 8C embryo suggest that it is an independent circadian rhythm-competent equivalence group poised to signal its environment, defend against maternal immune rejection, and begin the rapid commitment events of early embryogenesis. PMID:26493868

Function of GATA Factors in the Adult Mouse Liver

PubMed Central

Zheng, Rena; Rebolledo-Jaramillo, Boris; Zong, Yiwei; Wang, Liqing; Russo, Pierre; Hancock, Wayne; Stanger, Ben Z.; Hardison, Ross C.; Blobel, Gerd A.

2013-01-01

GATA transcription factors and their Friend of Gata (FOG) cofactors control the development of diverse tissues. GATA4 and GATA6 are essential for the expansion of the embryonic liver bud, but their expression patterns and functions in the adult liver are unclear. We characterized the expression of GATA and FOG factors in whole mouse liver and purified hepatocytes. GATA4, GATA6, and FOG1 are the most prominently expressed family members in whole liver and hepatocytes. GATA4 chromatin immunoprecipitation followed by high throughput sequencing (ChIP-seq) identified 4409 occupied sites, associated with genes enriched in ontologies related to liver function, including lipid and glucose metabolism. However, hepatocyte-specific excision of Gata4 had little impact on gross liver architecture and function, even under conditions of regenerative stress, and, despite the large number of GATA4 occupied genes, resulted in relatively few changes in gene expression. To address possible redundancy between GATA4 and GATA6, both factors were conditionally excised. Surprisingly, combined Gata4,6 loss did not exacerbate the phenotype resulting from Gata4 loss alone. This points to the presence of an unusually robust transcriptional network in adult hepatocytes that ensures the maintenance of liver function. PMID:24367609

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

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.

Early life social stress induced changes in depression and anxiety associated neural pathways which are correlated with impaired maternal care.

PubMed

Murgatroyd, Christopher A; Peña, Catherine J; Podda, Giovanni; Nestler, Eric J; Nephew, Benjamin C

2015-08-01

Exposures to various types of early life stress can be robust predictors of the development of psychiatric disorders, including depression and anxiety. The objective of the current study was to investigate the roles of the translationally relevant targets of central vasopressin, oxytocin, ghrelin, orexin, glucocorticoid, and the brain-derived neurotrophic factor (BDNF) pathway in an early chronic social stress (ECSS) based rodent model of postpartum depression and anxiety. The present study reports novel changes in gene expression and extracellular signal related kinase (ERK) protein levels in the brains of ECSS exposed rat dams that display previously reported depressed maternal care and increased maternal anxiety. Decreases in oxytocin, orexin, and ERK proteins, increases in ghrelin receptor, glucocorticoid and mineralocorticoid receptor mRNA levels, and bidirectional changes in vasopressin underscore related work on the adverse long-term effects of early life stress on neural activity and plasticity, maternal behavior, responses to stress, and depression and anxiety-related behavior. The differences in gene and protein expression and robust correlations between expression and maternal care and anxiety support increased focus on these targets in animal and clinical studies of the adverse effects of early life stress, especially those focusing on depression and anxiety in mothers and the transgenerational effects of these disorders on offspring. Copyright © 2015 Elsevier B.V. All rights reserved.

Reproducible detection of disease-associated markers from gene expression data.

PubMed

Omae, Katsuhiro; Komori, Osamu; Eguchi, Shinto

2016-08-18

Detection of disease-associated markers plays a crucial role in gene screening for biological studies. Two-sample test statistics, such as the t-statistic, are widely used to rank genes based on gene expression data. However, the resultant gene ranking is often not reproducible among different data sets. Such irreproducibility may be caused by disease heterogeneity. When we divided data into two subsets, we found that the signs of the two t-statistics were often reversed. Focusing on such instability, we proposed a sign-sum statistic that counts the signs of the t-statistics for all possible subsets. The proposed method excludes genes affected by heterogeneity, thereby improving the reproducibility of gene ranking. We compared the sign-sum statistic with the t-statistic by a theoretical evaluation of the upper confidence limit. Through simulations and applications to real data sets, we show that the sign-sum statistic exhibits superior performance. We derive the sign-sum statistic for getting a robust gene ranking. The sign-sum statistic gives more reproducible ranking than the t-statistic. Using simulated data sets we show that the sign-sum statistic excludes hetero-type genes well. Also for the real data sets, the sign-sum statistic performs well in a viewpoint of ranking reproducibility.

Identification of Development-Related Genes in the Ovaries of Adult Harmonia axyridis (Pallas) Lady Beetles Using a Time- Series Analysis by RNA-seq.

PubMed

Du, Wenxiao; Zeng, Fanrong

2016-12-14

Adults of the lady beetle species Harmonia axyridis (Pallas) are bred artificially en masse for classic biological control, which requires egg-laying by the H. axyridis ovary. Development-related genes may impact the growth of the H. axyridis adult ovary but have not been reported. Here, we used integrative time-series RNA-seq analysis of the ovary in H. axyridis adults to detect development-related genes. A total of 28,558 unigenes were functionally annotated using seven types of databases to obtain an annotated unigene database for ovaries in H. axyridis adults. We also analysed differentially expressed genes (DEGs) between samples. Based on a combination of the results of this bioinformatics analysis with literature reports and gene expression level changes in four different stages, we focused on the development of oocyte reproductive stem cell and yolk formation process and identified 26 genes with high similarity to development-related genes. 20 DEGs were randomly chosen for quantitative real-time PCR (qRT-PCR) to validate the accuracy of the RNA-seq results. This study establishes a robust pipeline for the discovery of key genes using high-throughput sequencing and the identification of a class of development-related genes for characterization.

Differential expression of the Slc4 bicarbonate transporter family in murine corneal endothelium and cell culture.

PubMed

Shei, William; Liu, Jun; Htoon, Hla M; Aung, Tin; Vithana, Eranga N

2013-01-01

To characterize the relative expression levels of all the solute carrier 4 (Slc4) transporter family members (Slc4a1-Slc4a11) in murine corneal endothelium using real-time quantitative (qPCR), to identify further important members besides Slc4a11 and Slc4a4, and to explore how close to the baseline levels the gene expressions remain after cells have been subjected to expansion and culture. Descemet's membrane-endothelial layers of 8-10-week-old C57BL6 mice were stripped from corneas and used for both primary cell culture and direct RNA extraction. Total RNA (from uncultured cells as well as cultured cells at passages 2 and 7) was reverse transcribed, and the cDNA was used for real time qPCR using specific primers for all the Slc4 family members. The geNorm method was applied to determine the most stable housekeeping genes and normalization factor, which was calculated from multiple housekeeping genes for more accurate and robust quantification. qPCR analyses revealed that all Slc4 bicarbonate transporter family members were expressed in mouse corneal endothelium. Slc4a11 showed the highest expression, which was approximately three times higher than that of Slc4a4 (3.4±0.3; p=0.004). All Slc4 genes were also expressed in cultured cells, and interestingly, the expression of Slc4a11 in cultured cells was significantly reduced by approximately 20-fold (0.05±0.001; p=0.000001) in early passage and by approximately sevenfold (0.14±0.002; p=0.000002) in late passage cells. Given the known involvement of SLC4A4 and SLC4A11 in corneal dystrophies, we speculate that the other two highly expressed genes in the uncultured corneal endothelium, SLC4A2 and SLC4A7, are worthy of being considered as potential candidate genes for corneal endothelial diseases. Moreover, as cell culture can affect expression levels of Slc4 genes, caution and careful design of experiments are necessary when undertaking studies of Slc4-mediated ion transport in cultured cells.

The oncogenic potential of BK-polyomavirus is linked to viral integration into the human genome.

PubMed

Kenan, Daniel J; Mieczkowski, Piotr A; Burger-Calderon, Raquel; Singh, Harsharan K; Nickeleit, Volker

2015-11-01

It has been suggested that BK-polyomavirus is linked to oncogenesis via high expression levels of large T-antigen in some urothelial neoplasms arising following kidney transplantation. However, a causal association between BK-polyomavirus, large T-antigen expression and oncogenesis has never been demonstrated in humans. Here we describe an investigation using high-throughput sequencing of tumour DNA obtained from an urothelial carcinoma arising in a renal allograft. We show that a novel BK-polyomavirus strain, named CH-1, is integrated into exon 26 of the myosin-binding protein C1 gene (MYBPC1) on chromosome 12 in tumour cells but not in normal renal cells. Integration of the BK-polyomavirus results in a number of discrete alterations in viral gene expression, including: (a) disruption of VP1 protein expression and robust expression of large T-antigen; (b) preclusion of viral replication; and (c) deletions in the non-coding control region (NCCR), with presumed alterations in promoter feedback loops. Viral integration disrupts one MYBPC1 gene copy and likely alters its expression. Circular episomal BK-polyomavirus gene sequences are not found, and the renal allograft shows no productive polyomavirus infection or polyomavirus nephropathy. These findings support the hypothesis that integration of polyomaviruses is essential to tumourigenesis. It is likely that dysregulation of large T-antigen, with persistent over-expression in non-lytic cells, promotes cell growth, genetic instability and neoplastic transformation. © 2015 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of Pathological Society of Great Britain and Ireland.

Distinctive gene expression profiles characterize donor biopsies from HCV-positive kidney donors.

PubMed

Mas, Valeria R; Archer, Kellie J; Suh, Lacey; Scian, Mariano; Posner, Marc P; Maluf, Daniel G

2010-12-15

Because of the shortage of organs for transplantation, procurement of kidneys from extended criteria donors is inevitable. Frequently, donors infected with hepatitis C virus (HCV) are used. To elucidate an initial compromise of molecular pathways in HCV graft, gene expression profiles were evaluated. Twenty-four donor allograft biopsies (n=12 HCV positive (+) and n=12 HCV negative (-)) were collected at preimplantation time and profiled using microarrays. Donors were age, race, gender, and cold and warm ischemia time matched between groups. Probe level data were read into the R programming environment using the affy Bioconductor package, and the robust multiarray average method was used to obtain probe set expression summaries. To identify probe sets exhibiting differential expression, a two sample t test was performed. Molecular and biologic functions were analyzed using Interaction Networks and Functional Analysis. Fifty-eight probe sets were differentially expressed between HCV (+) versus HCV (-) donors (P<0.001). The molecular functions associated with the two top scored networks from the analysis of the differentially expressed genes were connective tissue development and function and tissue morphology (score 34), cell death, cell signaling, cellular assembly, and organization (score 32). Among the differentially affected top canonical pathways, we found the role of RIG1-like receptors in antiviral innate immunity (P<0.001), natural killer cell signaling (P=0.007), interleukin-8 signaling (P=0.048), interferon signaling (P=0.0 11; INFA21, INFGR1, and MED14), ILK signaling (P=0.001), and apoptosis signaling. A unique gene expression pattern was identified in HCV (+) kidney grafts. Innate immune system and inflammatory pathways were the most affected.

Longitudinal Analysis of Whole Blood Transcriptomes to Explore Molecular Signatures Associated With Acute Renal Allograft Rejection

PubMed Central

Shin, Heesun; Günther, Oliver; Hollander, Zsuzsanna; Wilson-McManus, Janet E.; Ng, Raymond T.; Balshaw, Robert; Keown, Paul A.; McMaster, Robert; McManus, Bruce M.; Isbel, Nicole M.; Knoll, Greg; Tebbutt, Scott J.

2014-01-01

In this study, we explored a time course of peripheral whole blood transcriptomes from kidney transplantation patients who either experienced an acute rejection episode or did not in order to better delineate the immunological and biological processes measureable in blood leukocytes that are associated with acute renal allograft rejection. Using microarrays, we generated gene expression data from 24 acute rejectors and 24 nonrejectors. We filtered the data to obtain the most unambiguous and robustly expressing probe sets and selected a subset of patients with the clearest phenotype. We then performed a data-driven exploratory analysis using data reduction and differential gene expression analysis tools in order to reveal gene expression signatures associated with acute allograft rejection. Using a template-matching algorithm, we then expanded our analysis to include time course data, identifying genes whose expression is modulated leading up to acute rejection. We have identified molecular phenotypes associated with acute renal allograft rejection, including a significantly upregulated signature of neutrophil activation and accumulation following transplant surgery that is common to both acute rejectors and nonrejectors. Our analysis shows that this expression signature appears to stabilize over time in nonrejectors but persists in patients who go on to reject the transplanted organ. In addition, we describe an expression signature characteristic of lymphocyte activity and proliferation. This lymphocyte signature is significantly downregulated in both acute rejectors and nonrejectors following surgery; however, patients who go on to reject the organ show a persistent downregulation of this signature relative to the neutrophil signature. PMID:24526836

Integrative analysis of multi-omics data for identifying multi-markers for diagnosing pancreatic cancer

PubMed Central

2015-01-01

Background microRNA (miRNA) expression plays an influential role in cancer classification and malignancy, and miRNAs are feasible as alternative diagnostic markers for pancreatic cancer, a highly aggressive neoplasm with silent early symptoms, high metastatic potential, and resistance to conventional therapies. Methods In this study, we evaluated the benefits of multi-omics data analysis by integrating miRNA and mRNA expression data in pancreatic cancer. Using support vector machine (SVM) modelling and leave-one-out cross validation (LOOCV), we evaluated the diagnostic performance of single- or multi-markers based on miRNA and mRNA expression profiles from 104 PDAC tissues and 17 benign pancreatic tissues. For selecting even more reliable and robust markers, we performed validation by independent datasets from the Gene Expression Omnibus (GEO) and the Cancer Genome Atlas (TCGA) data depositories. For validation, miRNA activity was estimated by miRNA-target gene interaction and mRNA expression datasets in pancreatic cancer. Results Using a comprehensive identification approach, we successfully identified 705 multi-markers having powerful diagnostic performance for PDAC. In addition, these marker candidates annotated with cancer pathways using gene ontology analysis. Conclusions Our prediction models have strong potential for the diagnosis of pancreatic cancer. PMID:26328610

Inference of cancer-specific gene regulatory networks using soft computing rules.

PubMed

Wang, Xiaosheng; Gotoh, Osamu

2010-03-24

Perturbations of gene regulatory networks are essentially responsible for oncogenesis. Therefore, inferring the gene regulatory networks is a key step to overcoming cancer. In this work, we propose a method for inferring directed gene regulatory networks based on soft computing rules, which can identify important cause-effect regulatory relations of gene expression. First, we identify important genes associated with a specific cancer (colon cancer) using a supervised learning approach. Next, we reconstruct the gene regulatory networks by inferring the regulatory relations among the identified genes, and their regulated relations by other genes within the genome. We obtain two meaningful findings. One is that upregulated genes are regulated by more genes than downregulated ones, while downregulated genes regulate more genes than upregulated ones. The other one is that tumor suppressors suppress tumor activators and activate other tumor suppressors strongly, while tumor activators activate other tumor activators and suppress tumor suppressors weakly, indicating the robustness of biological systems. These findings provide valuable insights into the pathogenesis of cancer.

Dynamic interplay and function of multiple noncoding genes governing X chromosome inactivation

PubMed Central

Yue, Minghui; Richard, John Lalith Charles

2015-01-01

There is increasing evidence for the emergence of long noncoding RNAs (IncRNAs) as important components, especially in the regulation of gene expression. In the event of X chromosome inactivation, robust epigenetic marks are established in a long noncoding Xist RNA-dependent manner, giving rise to a distinct epigenetic landscape on the inactive X chromosome (Xi). The X inactivation center (Xic is essential for induction of X chromosome inactivation and harbors two topologically associated domains (TADs) to regulate monoallelic Xist expression: one at the noncoding Xist gene and its upstream region, and the other at the antisense Tsix and its upstream region. The monoallelic expression of Xist is tightly regulated by these two functionally distinct TADs as well as their constituting IncRNAs and proteins. In this review, we summarize recent updates in our knowledge of IncRNAs found at the Xic and discuss their overall mechanisms of action. We also discuss our current understanding of the molecular mechanism behind Xist RNA-mediated induction of the repressive epigenetic landscape at the Xi. PMID:26260844

Differential Network Analysis Reveals Evolutionary Complexity in Secondary Metabolism of Rauvolfia serpentina over Catharanthus roseus

PubMed Central

Pathania, Shivalika; Bagler, Ganesh; Ahuja, Paramvir S.

2016-01-01

Comparative co-expression analysis of multiple species using high-throughput data is an integrative approach to determine the uniformity as well as diversification in biological processes. Rauvolfia serpentina and Catharanthus roseus, both members of Apocyanacae family, are reported to have remedial properties against multiple diseases. Despite of sharing upstream of terpenoid indole alkaloid pathway, there is significant diversity in tissue-specific synthesis and accumulation of specialized metabolites in these plants. This led us to implement comparative co-expression network analysis to investigate the modules and genes responsible for differential tissue-specific expression as well as species-specific synthesis of metabolites. Toward these goals differential network analysis was implemented to identify candidate genes responsible for diversification of metabolites profile. Three genes were identified with significant difference in connectivity leading to differential regulatory behavior between these plants. These genes may be responsible for diversification of secondary metabolism, and thereby for species-specific metabolite synthesis. The network robustness of R. serpentina, determined based on topological properties, was also complemented by comparison of gene-metabolite networks of both plants, and may have evolved to have complex metabolic mechanisms as compared to C. roseus under the influence of various stimuli. This study reveals evolution of complexity in secondary metabolism of R. serpentina, and key genes that contribute toward diversification of specific metabolites. PMID:27588023

Differential Network Analysis Reveals Evolutionary Complexity in Secondary Metabolism of Rauvolfia serpentina over Catharanthus roseus.

PubMed

Pathania, Shivalika; Bagler, Ganesh; Ahuja, Paramvir S

2016-01-01

Comparative co-expression analysis of multiple species using high-throughput data is an integrative approach to determine the uniformity as well as diversification in biological processes. Rauvolfia serpentina and Catharanthus roseus, both members of Apocyanacae family, are reported to have remedial properties against multiple diseases. Despite of sharing upstream of terpenoid indole alkaloid pathway, there is significant diversity in tissue-specific synthesis and accumulation of specialized metabolites in these plants. This led us to implement comparative co-expression network analysis to investigate the modules and genes responsible for differential tissue-specific expression as well as species-specific synthesis of metabolites. Toward these goals differential network analysis was implemented to identify candidate genes responsible for diversification of metabolites profile. Three genes were identified with significant difference in connectivity leading to differential regulatory behavior between these plants. These genes may be responsible for diversification of secondary metabolism, and thereby for species-specific metabolite synthesis. The network robustness of R. serpentina, determined based on topological properties, was also complemented by comparison of gene-metabolite networks of both plants, and may have evolved to have complex metabolic mechanisms as compared to C. roseus under the influence of various stimuli. This study reveals evolution of complexity in secondary metabolism of R. serpentina, and key genes that contribute toward diversification of specific metabolites.

Comparing machine learning and logistic regression methods for predicting hypertension using a combination of gene expression and next-generation sequencing data.

PubMed

Held, Elizabeth; Cape, Joshua; Tintle, Nathan

2016-01-01

Machine learning methods continue to show promise in the analysis of data from genetic association studies because of the high number of variables relative to the number of observations. However, few best practices exist for the application of these methods. We extend a recently proposed supervised machine learning approach for predicting disease risk by genotypes to be able to incorporate gene expression data and rare variants. We then apply 2 different versions of the approach (radial and linear support vector machines) to simulated data from Genetic Analysis Workshop 19 and compare performance to logistic regression. Method performance was not radically different across the 3 methods, although the linear support vector machine tended to show small gains in predictive ability relative to a radial support vector machine and logistic regression. Importantly, as the number of genes in the models was increased, even when those genes contained causal rare variants, model predictive ability showed a statistically significant decrease in performance for both the radial support vector machine and logistic regression. The linear support vector machine showed more robust performance to the inclusion of additional genes. Further work is needed to evaluate machine learning approaches on larger samples and to evaluate the relative improvement in model prediction from the incorporation of gene expression data.

iGWAS: Integrative Genome-Wide Association Studies of Genetic and Genomic Data for Disease Susceptibility Using Mediation Analysis.

PubMed

Huang, Yen-Tsung; Liang, Liming; Moffatt, Miriam F; Cookson, William O C M; Lin, Xihong

2015-07-01

Genome-wide association studies (GWAS) have been a standard practice in identifying single nucleotide polymorphisms (SNPs) for disease susceptibility. We propose a new approach, termed integrative GWAS (iGWAS) that exploits the information of gene expressions to investigate the mechanisms of the association of SNPs with a disease phenotype, and to incorporate the family-based design for genetic association studies. Specifically, the relations among SNPs, gene expression, and disease are modeled within the mediation analysis framework, which allows us to disentangle the genetic effect on a disease phenotype into two parts: an effect mediated through a gene expression (mediation effect, ME) and an effect through other biological mechanisms or environment-mediated mechanisms (alternative effect, AE). We develop omnibus tests for the ME and AE that are robust to underlying true disease models. Numerical studies show that the iGWAS approach is able to facilitate discovering genetic association mechanisms, and outperforms the SNP-only method for testing genetic associations. We conduct a family-based iGWAS of childhood asthma that integrates genetic and genomic data. The iGWAS approach identifies six novel susceptibility genes (MANEA, MRPL53, LYCAT, ST8SIA4, NDFIP1, and PTCH1) using the omnibus test with false discovery rate less than 1%, whereas no gene using SNP-only analyses survives with the same cut-off. The iGWAS analyses further characterize that genetic effects of these genes are mostly mediated through their gene expressions. In summary, the iGWAS approach provides a new analytic framework to investigate the mechanism of genetic etiology, and identifies novel susceptibility genes of childhood asthma that were biologically meaningful. © 2015 WILEY PERIODICALS, INC.

Brief Report: A mass spectrometry assay to simultaneously analyze ROS1 and RET fusion gene expression in non-small cell lung cancer

PubMed Central

Wijesinghe, Priyanga; Bepler, Gerold

2014-01-01

Introduction ROS1 and RET gene fusions were recently discovered in non-small cell lung cancer (NSCLC) as potential therapeutic targets with small molecule kinase inhibitors. The conventional screening methods of these fusions are time consuming and require samples of high quality and quantity. Here, we describe a novel and efficient method by coupling the power of multiplexing PCR and the sensitivity of mass spectrometry. Methods The multiplex mass spectrometry platform simultaneously tests samples for the expression of nine ROS1 and six RET fusion genes. The assay incorporates detection of wild-type exon junctions immediately upstream and downstream of the fusion junction to exclude false negative results. To flag false positives, the system also comprises two independent assays for each fusion gene junction. Results The characteristic mass spectrometric peaks of the gene fusions were obtained using engineered plasmid constructs. Specific assays targeting the wild-type gene exon junctions were validated using cDNA from lung tissue of healthy individuals. The system was further validated using cDNA derived from NSCLC cell lines that express endogenous fusion genes. The expressed ROS1-SLC34A2 and CCDC6-RET gene fusions from the NSCLC cell lines HCC78 and LC-2/ad, respectively, were accurately detected by the novel assay. The assay is extremely sensitive, capable of detecting an event in test specimens containing 0.5% positive tumors. Conclusion The novel multiplexed assay is robustly capable of detecting 15 different clinically relevant RET and ROS1 fusion variants. The benefits of this detection method include exceptionally low sample input, high cost efficiency, flexibility, and rapid turnover. PMID:25384172

Positive radionuclide imaging of miRNA expression using RILES and the human sodium iodide symporter as reporter gene is feasible and supports a protective role of miRNA-23a in response to muscular atrophy

PubMed Central

Simion, Viorel; Sobilo, Julien; Clemoncon, Rudy; Natkunarajah, Sharuja; Ezzine, Safia; Abdallah, Florence; Lerondel, Stephanie; Pichon, Chantal

2017-01-01

MicroRNAs (miRNAs) are key players in many biological processes and are considered as an emerging class of pharmacology drugs for diagnosis and therapy. However to fully exploit the therapeutic potential of miRNAs, it is becoming crucial to monitor their expression pattern using medical imaging modalities. Recently, we developed a method called RILES, for RNAi-Inducible Luciferase Expression System that relies on an engineered regulatable expression system to switch-ON the expression of the luciferase gene when a miRNA of interest is expressed in cells. Here we investigated whether replacing the luciferase reporter gene with the human sodium iodide symporter (hNIS) reporter gene will be also suited to monitor the expression of miRNAs in a clinical setting context. We provide evidence that radionuclide imaging of miRNA expression using hNIS is feasible although it is not as robust as when the luciferase reporter gene is used. However, under appropriate conditions, we monitored the expression of several miRNAs in cells, in the liver and in the tibialis anterior muscle of mice undergoing muscular atrophy. We demonstrated that radiotracer accumulation in transfected cells correlated with the induction of hNIS and with the expression of miRNAs detected by real time PCR. We established the kinetic of miRNA-23a expression in mice and demonstrated that this miRNA follows a biphasic expression pattern characterized by a loss of expression at a late time point of muscular atrophy. At autopsy, we found an opposite expression pattern between miRNA-23a and one of the main transcriptional target of this miRNA, APAF-1, and as downstream target, Caspase 9. Our results report the first positive monitoring of endogenously expressed miRNAs in a nuclear medicine imaging context and support the development of additional work to establish the potential therapeutic value of miRNA-23 to prevent the damaging effects of muscular atrophy. PMID:28493972

Positive radionuclide imaging of miRNA expression using RILES and the human sodium iodide symporter as reporter gene is feasible and supports a protective role of miRNA-23a in response to muscular atrophy.

PubMed

Simion, Viorel; Sobilo, Julien; Clemoncon, Rudy; Natkunarajah, Sharuja; Ezzine, Safia; Abdallah, Florence; Lerondel, Stephanie; Pichon, Chantal; Baril, Patrick

2017-01-01

MicroRNAs (miRNAs) are key players in many biological processes and are considered as an emerging class of pharmacology drugs for diagnosis and therapy. However to fully exploit the therapeutic potential of miRNAs, it is becoming crucial to monitor their expression pattern using medical imaging modalities. Recently, we developed a method called RILES, for RNAi-Inducible Luciferase Expression System that relies on an engineered regulatable expression system to switch-ON the expression of the luciferase gene when a miRNA of interest is expressed in cells. Here we investigated whether replacing the luciferase reporter gene with the human sodium iodide symporter (hNIS) reporter gene will be also suited to monitor the expression of miRNAs in a clinical setting context. We provide evidence that radionuclide imaging of miRNA expression using hNIS is feasible although it is not as robust as when the luciferase reporter gene is used. However, under appropriate conditions, we monitored the expression of several miRNAs in cells, in the liver and in the tibialis anterior muscle of mice undergoing muscular atrophy. We demonstrated that radiotracer accumulation in transfected cells correlated with the induction of hNIS and with the expression of miRNAs detected by real time PCR. We established the kinetic of miRNA-23a expression in mice and demonstrated that this miRNA follows a biphasic expression pattern characterized by a loss of expression at a late time point of muscular atrophy. At autopsy, we found an opposite expression pattern between miRNA-23a and one of the main transcriptional target of this miRNA, APAF-1, and as downstream target, Caspase 9. Our results report the first positive monitoring of endogenously expressed miRNAs in a nuclear medicine imaging context and support the development of additional work to establish the potential therapeutic value of miRNA-23 to prevent the damaging effects of muscular atrophy.

Robustly detecting differential expression in RNA sequencing data using observation weights

PubMed Central

Zhou, Xiaobei; Lindsay, Helen; Robinson, Mark D.

2014-01-01

A popular approach for comparing gene expression levels between (replicated) conditions of RNA sequencing data relies on counting reads that map to features of interest. Within such count-based methods, many flexible and advanced statistical approaches now exist and offer the ability to adjust for covariates (e.g. batch effects). Often, these methods include some sort of ‘sharing of information’ across features to improve inferences in small samples. It is important to achieve an appropriate tradeoff between statistical power and protection against outliers. Here, we study the robustness of existing approaches for count-based differential expression analysis and propose a new strategy based on observation weights that can be used within existing frameworks. The results suggest that outliers can have a global effect on differential analyses. We demonstrate the effectiveness of our new approach with real data and simulated data that reflects properties of real datasets (e.g. dispersion-mean trend) and develop an extensible framework for comprehensive testing of current and future methods. In addition, we explore the origin of such outliers, in some cases highlighting additional biological or technical factors within the experiment. Further details can be downloaded from the project website: http://imlspenticton.uzh.ch/robinson_lab/edgeR_robust/. PMID:24753412

CAR/PXR provide directives for Cyp3a41 gene regulation differently from Cyp3a11.

PubMed

Anakk, S; Kalsotra, A; Kikuta, Y; Huang, W; Zhang, J; Staudinger, J L; Moore, D D; Strobel, H W

2004-01-01

This study reports that Cyp3a41 gene contains 13 exons and is localized on the chromosome 5. CYP3A41 is a female-specific isoform that is predominantly expressed in the liver. Estrogen signaling is not responsible for its female specificity. CYP3A41 expression in kidney and brain is observed only in 50% of mice examined. PXR mediates dexamethasone-dependent suppression of CYP3A41. In contrast to CYP3A11, CYP3A41 expression is not induced by pregnenolone-16alpha-carbonitrile (PCN) in wild-type mice, but is significantly suppressed by PCN in PXR(-/-) mice. Phenobarbital and TCPOBOP induce CYP3A11 expression only in the presence of CAR, but have no effect on CYP3A41 expression. Immunoblot and erythromycin demethylase activity analysis reveal robust CYP3A induction after PCN treatment, which is poorly correlated to CYP3A41. These findings suggest a differential role for CAR/PXR in regulating individual CYP3A isoforms by previously characterized CYP3A inducers.

Macrophage Activation Mechanisms in Human Monocytic Cell Line-derived Macrophages.

PubMed

Sumiya, Yu; Ishikawa, Mami; Inoue, Takahiro; Inui, Toshio; Kuchiike, Daisuke; Kubo, Kentaro; Uto, Yoshihiro; Nishikata, Takahito

2015-08-01

Although the mechanisms of macrophage activation are important for cancer immunotherapy, they are poorly understood. Recently, easy and robust assay systems for assessing the macrophage-activating factor (MAF) using monocytic cell line-derived macrophages were established. Gene-expression profiles of U937- and THP-1-derived macrophages were compared using gene expression microarray analysis and their responses against several MAFs were examined by in vitro experiments. Activated states of these macrophages could not be assigned to a specific sub-type but showed, however, different unique characteristics. The unique of monocytic cell line-derived macrophages could provide clues to understand the activation mechanism of macrophages and, therefore, help to develop effective cancer immunotherapy with MAFs. Copyright© 2015 International Institute of Anticancer Research (Dr. John G. Delinassios), All rights reserved.

COE loss-of-function analysis reveals a genetic program underlying maintenance and regeneration of the nervous system in planarians.

PubMed

Cowles, Martis W; Omuro, Kerilyn C; Stanley, Brianna N; Quintanilla, Carlo G; Zayas, Ricardo M

2014-10-01

Members of the COE family of transcription factors are required for central nervous system (CNS) development. However, the function of COE in the post-embryonic CNS remains largely unknown. An excellent model for investigating gene function in the adult CNS is the freshwater planarian. This animal is capable of regenerating neurons from an adult pluripotent stem cell population and regaining normal function. We previously showed that planarian coe is expressed in differentiating and mature neurons and that its function is required for proper CNS regeneration. Here, we show that coe is essential to maintain nervous system architecture and patterning in intact (uninjured) planarians. We took advantage of the robust phenotype in intact animals to investigate the genetic programs coe regulates in the CNS. We compared the transcriptional profiles of control and coe RNAi planarians using RNA sequencing and identified approximately 900 differentially expressed genes in coe knockdown animals, including 397 downregulated genes that were enriched for nervous system functional annotations. Next, we validated a subset of the downregulated transcripts by analyzing their expression in coe-deficient planarians and testing if the mRNAs could be detected in coe+ cells. These experiments revealed novel candidate targets of coe in the CNS such as ion channel, neuropeptide, and neurotransmitter genes. Finally, to determine if loss of any of the validated transcripts underscores the coe knockdown phenotype, we knocked down their expression by RNAi and uncovered a set of coe-regulated genes implicated in CNS regeneration and patterning, including orthologs of sodium channel alpha-subunit and pou4. Our study broadens the knowledge of gene expression programs regulated by COE that are required for maintenance of neural subtypes and nervous system architecture in adult animals.

Identification of Genes Whose Expression Profile Is Associated with Non-Progression towards AIDS Using eQTLs

PubMed Central

Le Clerc, Sigrid; van Manen, Daniëlle; Coulonges, Cédric; Ulveling, Damien; Laville, Vincent; Labib, Taoufik; Taing, Lieng; Delaneau, Olivier; Montes, Matthieu; Schuitemaker, Hanneke; Zagury, Jean-François

2015-01-01

Background Many genome-wide association studies have been performed on progression towards the acquired immune deficiency syndrome (AIDS) and they mainly identified associations within the HLA loci. In this study, we demonstrate that the integration of biological information, namely gene expression data, can enhance the sensitivity of genetic studies to unravel new genetic associations relevant to AIDS. Methods We collated the biological information compiled from three databases of expression quantitative trait loci (eQTLs) involved in cells of the immune system. We derived a list of single nucleotide polymorphisms (SNPs) that are functional in that they correlate with differential expression of genes in at least two of the databases. We tested the association of those SNPs with AIDS progression in two cohorts, GRIV and ACS. Tests on permuted phenotypes of the GRIV and ACS cohorts or on randomised sets of equivalent SNPs allowed us to assess the statistical robustness of this method and to estimate the true positive rate. Results Eight genes were identified with high confidence (p = 0.001, rate of true positives 75%). Some of those genes had previously been linked with HIV infection. Notably, ENTPD4 belongs to the same family as CD39, whose expression has already been associated with AIDS progression; while DNAJB12 is part of the HSP90 pathway, which is involved in the control of HIV latency. Our study also drew our attention to lesser-known functions such as mitochondrial ribosomal proteins and a zinc finger protein, ZFP57, which could be central to the effectiveness of HIV infection. Interestingly, for six out of those eight genes, down-regulation is associated with non-progression, which makes them appealing targets to develop drugs against HIV. PMID:26367535

Transcriptomic analysis reveals tomato genes whose expression is induced specifically during effector-triggered immunity and identifies the Epk1 protein kinase which is required for the host response to three bacterial effector proteins.

PubMed

Pombo, Marina A; Zheng, Yi; Fernandez-Pozo, Noe; Dunham, Diane M; Fei, Zhangjun; Martin, Gregory B

2014-01-01

Plants have two related immune systems to defend themselves against pathogen attack. Initially,pattern-triggered immunity is activated upon recognition of microbe-associated molecular patterns by pattern recognition receptors. Pathogenic bacteria deliver effector proteins into the plant cell that interfere with this immune response and promote disease. However, some plants express resistance proteins that detect the presence of specific effectors leading to a robust defense response referred to as effector-triggered immunity. The interaction of tomato with Pseudomonas syringae pv. tomato is an established model system for understanding the molecular basis of these plant immune responses. We apply high-throughput RNA sequencing to this pathosystem to identify genes whose expression changes specifically during pattern-triggered or effector-triggered immunity. We then develop reporter genes for each of these responses that will enable characterization of the host response to the large collection of P. s. pv. tomato strains that express different combinations of effectors. Virus-induced gene silencing of 30 of the effector-triggered immunity-specific genes identifies Epk1 which encodes a predicted protein kinase from a family previously unknown to be involved in immunity. Knocked-down expression of Epk1 compromises effector-triggered immunity triggered by three bacterial effectors but not by effectors from non-bacterial pathogens. Epistasis experiments indicate that Epk1 acts upstream of effector-triggered immunity-associated MAP kinase signaling. Using RNA-seq technology we identify genes involved in specific immune responses. A functional genomics screen led to the discovery of Epk1, a novel predicted protein kinase required for plant defense activation upon recognition of three different bacterial effectors.

RNA-Seq of Arabidopsis Pollen Uncovers Novel Transcription and Alternative Splicing1[C][W][OA

PubMed Central

Loraine, Ann E.; McCormick, Sheila; Estrada, April; Patel, Ketan; Qin, Peng

2013-01-01

Pollen grains of Arabidopsis (Arabidopsis thaliana) contain two haploid sperm cells enclosed in a haploid vegetative cell. Upon germination, the vegetative cell extrudes a pollen tube that carries the sperm to an ovule for fertilization. Knowing the identity, relative abundance, and splicing patterns of pollen transcripts will improve our understanding of pollen and allow investigation of tissue-specific splicing in plants. Most Arabidopsis pollen transcriptome studies have used the ATH1 microarray, which does not assay splice variants and lacks specific probe sets for many genes. To investigate the pollen transcriptome, we performed high-throughput sequencing (RNA-Seq) of Arabidopsis pollen and seedlings for comparison. Gene expression was more diverse in seedling, and genes involved in cell wall biogenesis were highly expressed in pollen. RNA-Seq detected at least 4,172 protein-coding genes expressed in pollen, including 289 assayed only by nonspecific probe sets. Additional exons and previously unannotated 5′ and 3′ untranslated regions for pollen-expressed genes were revealed. We detected regions in the genome not previously annotated as expressed; 14 were tested and 12 were confirmed by polymerase chain reaction. Gapped read alignments revealed 1,908 high-confidence new splicing events supported by 10 or more spliced read alignments. Alternative splicing patterns in pollen and seedling were highly correlated. For most alternatively spliced genes, the ratio of variants in pollen and seedling was similar, except for some encoding proteins involved in RNA splicing. This study highlights the robustness of splicing patterns in plants and the importance of ongoing annotation and visualization of RNA-Seq data using interactive tools such as Integrated Genome Browser. PMID:23590974

ck2-dependent phosphorylation of progesterone receptors (PR) on Ser81 regulates PR-B isoform-specific target gene expression in breast cancer cells.

PubMed

Hagan, Christy R; Regan, Tarah M; Dressing, Gwen E; Lange, Carol A

2011-06-01

Progesterone receptors (PR) are critical mediators of mammary gland development and contribute to breast cancer progression. Progestin-induced rapid activation of cytoplasmic protein kinases leads to selective regulation of growth-promoting genes by phospho-PR species. Herein, we show that phosphorylation of PR Ser81 is ck2 dependent and progestin regulated in intact cells but also occurs in the absence of PR ligands when cells enter the G(1)/S phase of the cell cycle. T47D breast cancer cells stably expressing a PR-B mutant receptor that cannot be phosphorylated at Ser79/81 (S79/81A) formed fewer soft agar colonies. Regulation of selected genes by PR-B, but not PR-A, also required Ser79/81 phosphorylation for basal and/or progestin-regulated (BIRC3, HSD11β2, and HbEGF) expression. Additionally, wild-type (wt) PR-B, but not S79/81A mutant PR, was robustly recruited to a progesterone response element (PRE)-containing transcriptional enhancer region of BIRC3; abundant ck2 also associated with this region in cells expressing wt but not S79/81A PR. We conclude that phospho-Ser81 PR provides a platform for ck2 recruitment and regulation of selected PR-B target genes. Understanding how ligand-independent PRs function in the context of high levels of kinase activities characteristic of breast cancer is critical to understanding the basis of tumor-specific changes in gene expression and will speed the development of highly selective treatments.

ck2-Dependent Phosphorylation of Progesterone Receptors (PR) on Ser81 Regulates PR-B Isoform-Specific Target Gene Expression in Breast Cancer Cells ▿

PubMed Central

Hagan, Christy R.; Regan, Tarah M.; Dressing, Gwen E.; Lange, Carol A.

2011-01-01

Progesterone receptors (PR) are critical mediators of mammary gland development and contribute to breast cancer progression. Progestin-induced rapid activation of cytoplasmic protein kinases leads to selective regulation of growth-promoting genes by phospho-PR species. Herein, we show that phosphorylation of PR Ser81 is ck2 dependent and progestin regulated in intact cells but also occurs in the absence of PR ligands when cells enter the G1/S phase of the cell cycle. T47D breast cancer cells stably expressing a PR-B mutant receptor that cannot be phosphorylated at Ser79/81 (S79/81A) formed fewer soft agar colonies. Regulation of selected genes by PR-B, but not PR-A, also required Ser79/81 phosphorylation for basal and/or progestin-regulated (BIRC3, HSD11β2, and HbEGF) expression. Additionally, wild-type (wt) PR-B, but not S79/81A mutant PR, was robustly recruited to a progesterone response element (PRE)-containing transcriptional enhancer region of BIRC3; abundant ck2 also associated with this region in cells expressing wt but not S79/81A PR. We conclude that phospho-Ser81 PR provides a platform for ck2 recruitment and regulation of selected PR-B target genes. Understanding how ligand-independent PRs function in the context of high levels of kinase activities characteristic of breast cancer is critical to understanding the basis of tumor-specific changes in gene expression and will speed the development of highly selective treatments. PMID:21518957

Circadian processes in the RNA life cycle.

PubMed

Torres, Manon; Becquet, Denis; Franc, Jean-Louis; François-Bellan, Anne-Marie

2018-05-01

The circadian clock drives daily rhythms of multiple physiological processes, allowing organisms to anticipate and adjust to periodic changes in environmental conditions. These physiological rhythms are associated with robust oscillations in the expression of at least 30% of expressed genes. While the ability for the endogenous timekeeping system to generate a 24-hr cycle is a cell-autonomous mechanism based on negative autoregulatory feedback loops of transcription and translation involving core-clock genes and their protein products, it is now increasingly evident that additional mechanisms also govern the circadian oscillations of clock-controlled genes. Such mechanisms can take place post-transcriptionally during the course of the RNA life cycle. It has been shown that many steps during RNA processing are regulated in a circadian manner, thus contributing to circadian gene expression. These steps include mRNA capping, alternative splicing, changes in splicing efficiency, and changes in RNA stability controlled by the tail length of polyadenylation or the use of alternative polyadenylation sites. RNA transport can also follow a circadian pattern, with a circadian nuclear retention driven by rhythmic expression within the nucleus of particular bodies (the paraspeckles) and circadian export to the cytoplasm driven by rhythmic proteins acting like cargo. Finally, RNA degradation may also follow a circadian pattern through the rhythmic involvement of miRNAs. In this review, we summarize the current knowledge of the post-transcriptional circadian mechanisms known to play a prominent role in shaping circadian gene expression in mammals. This article is categorized under: RNA Processing > Splicing Regulation/Alternative Splicing RNA Processing > RNA Editing and Modification RNA Export and Localization > Nuclear Export/Import. © 2018 Wiley Periodicals, Inc.

Stochasticity versus determinism: consequences for realistic gene regulatory network modelling and evolution.

PubMed

Jenkins, Dafyd J; Stekel, Dov J

2010-02-01

Gene regulation is one important mechanism in producing observed phenotypes and heterogeneity. Consequently, the study of gene regulatory network (GRN) architecture, function and evolution now forms a major part of modern biology. However, it is impossible to experimentally observe the evolution of GRNs on the timescales on which living species evolve. In silico evolution provides an approach to studying the long-term evolution of GRNs, but many models have either considered network architecture from non-adaptive evolution, or evolution to non-biological objectives. Here, we address a number of important modelling and biological questions about the evolution of GRNs to the realistic goal of biomass production. Can different commonly used simulation paradigms, in particular deterministic and stochastic Boolean networks, with and without basal gene expression, be used to compare adaptive with non-adaptive evolution of GRNs? Are these paradigms together with this goal sufficient to generate a range of solutions? Will the interaction between a biological goal and evolutionary dynamics produce trade-offs between growth and mutational robustness? We show that stochastic basal gene expression forces shrinkage of genomes due to energetic constraints and is a prerequisite for some solutions. In systems that are able to evolve rates of basal expression, two optima, one with and one without basal expression, are observed. Simulation paradigms without basal expression generate bloated networks with non-functional elements. Further, a range of functional solutions was observed under identical conditions only in stochastic networks. Moreover, there are trade-offs between efficiency and yield, indicating an inherent intertwining of fitness and evolutionary dynamics.

Upregulation of gene expression in reward-modulatory striatal opioid systems by sleep loss.

PubMed

Baldo, Brian A; Hanlon, Erin C; Obermeyer, William; Bremer, Quentin; Paletz, Elliott; Benca, Ruth M

2013-12-01

Epidemiological studies have shown a link between sleep loss and the obesity 'epidemic,' and several observations indicate that sleep curtailment engenders positive energy balance via increased palatable-food 'snacking.' These effects suggest alterations in reward-modulatory brain systems. We explored the effects of 10 days of sleep deprivation in rats on the expression of striatal opioid peptide (OP) genes that subserve food motivation and hedonic reward, and compared effects with those seen in hypothalamic energy balance-regulatory systems. Sleep-deprived (Sleep-Dep) rats were compared with yoked forced-locomotion apparatus controls (App-Controls), food-restricted rats (Food-Restrict), and unmanipulated controls (Home-Cage). Detection of mRNA levels with in situ hybridization revealed a subregion-specific upregulation of striatal preproenkephalin and prodynorhin gene expression in the Sleep-Dep group relative to all other groups. Neuropeptide Y (NPY) gene expression in the hippocampal dentate gyrus and throughout neocortex was also robustly upregulated selectively in the Sleep-Dep group. In contrast, parallel gene expression changes were observed in the Sleep-Dep and Food-Restrict groups in hypothalamic energy-sensing systems (arcuate nucleus NPY was upregulated, and cocaine- and amphetamine-regulated transcript was downregulated), in alignment with leptin suppression in both groups. Together, these results reveal a novel set of sleep deprivation-induced transcriptional changes in reward-modulatory peptide systems, which are dissociable from the energy-balance perturbations of sleep loss or the potentially stressful effects of the forced-locomotion procedure. The recruitment of telencephalic food-reward systems may provide a feeding drive highly resistant to feedback control, which could engender obesity through the enhancement of palatable feeding.

Gene expression profiling of immunomagnetically separated cells directly from stabilized whole blood for multicenter clinical trials

PubMed Central

2014-01-01

Background Clinically useful biomarkers for patient stratification and monitoring of disease progression and drug response are in big demand in drug development and for addressing potential safety concerns. Many diseases influence the frequency and phenotype of cells found in the peripheral blood and the transcriptome of blood cells. Changes in cell type composition influence whole blood gene expression analysis results and thus the discovery of true transcript level changes remains a challenge. We propose a robust and reproducible procedure, which includes whole transcriptome gene expression profiling of major subsets of immune cell cells directly sorted from whole blood. Methods Target cells were enriched using magnetic microbeads and an autoMACS® Pro Separator (Miltenyi Biotec). Flow cytometric analysis for purity was performed before and after magnetic cell sorting. Total RNA was hybridized on HGU133 Plus 2.0 expression microarrays (Affymetrix, USA). CEL files signal intensity values were condensed using RMA and a custom CDF file (EntrezGene-based). Results Positive selection by use of MACS® Technology coupled to transcriptomics was assessed for eight different peripheral blood cell types, CD14+ monocytes, CD3+, CD4+, or CD8+ T cells, CD15+ granulocytes, CD19+ B cells, CD56+ NK cells, and CD45+ pan leukocytes. RNA quality from enriched cells was above a RIN of eight. GeneChip analysis confirmed cell type specific transcriptome profiles. Storing whole blood collected in an EDTA Vacutainer® tube at 4°C followed by MACS does not activate sorted cells. Gene expression analysis supports cell enrichment measurements by MACS. Conclusions The proposed workflow generates reproducible cell-type specific transcriptome data which can be translated to clinical settings and used to identify clinically relevant gene expression biomarkers from whole blood samples. This procedure enables the integration of transcriptomics of relevant immune cell subsets sorted directly from whole blood in clinical trial protocols. PMID:25984272

Systematic Integration of Brain eQTL and GWAS Identifies ZNF323 as a Novel Schizophrenia Risk Gene and Suggests Recent Positive Selection Based on Compensatory Advantage on Pulmonary Function.

PubMed

Luo, Xiong-Jian; Mattheisen, Manuel; Li, Ming; Huang, Liang; Rietschel, Marcella; Børglum, Anders D; Als, Thomas D; van den Oord, Edwin J; Aberg, Karolina A; Mors, Ole; Mortensen, Preben Bo; Luo, Zhenwu; Degenhardt, Franziska; Cichon, Sven; Schulze, Thomas G; Nöthen, Markus M; Su, Bing; Zhao, Zhongming; Gan, Lin; Yao, Yong-Gang

2015-11-01

Genome-wide association studies have identified multiple risk variants and loci that show robust association with schizophrenia. Nevertheless, it remains unclear how these variants confer risk to schizophrenia. In addition, the driving force that maintains the schizophrenia risk variants in human gene pool is poorly understood. To investigate whether expression-associated genetic variants contribute to schizophrenia susceptibility, we systematically integrated brain expression quantitative trait loci and genome-wide association data of schizophrenia using Sherlock, a Bayesian statistical framework. Our analyses identified ZNF323 as a schizophrenia risk gene (P = 2.22×10(-6)). Subsequent analyses confirmed the association of the ZNF323 and its expression-associated single nucleotide polymorphism rs1150711 in independent samples (gene-expression: P = 1.40×10(-6); single-marker meta-analysis in the combined discovery and replication sample comprising 44123 individuals: P = 6.85×10(-10)). We found that the ZNF323 was significantly downregulated in hippocampus and frontal cortex of schizophrenia patients (P = .0038 and P = .0233, respectively). Evidence for pleiotropic effects was detected (association of rs1150711 with lung function and gene expression of ZNF323 in lung: P = 6.62×10(-5) and P = 9.00×10(-5), respectively) with the risk allele (T allele) for schizophrenia acting as protective allele for lung function. Subsequent population genetics analyses suggest that the risk allele (T) of rs1150711 might have undergone recent positive selection in human population. Our findings suggest that the ZNF323 is a schizophrenia susceptibility gene whose expression may influence schizophrenia risk. Our study also illustrates a possible mechanism for maintaining schizophrenia risk variants in the human gene pool. © The Author 2015. Published by Oxford University Press on behalf of the Maryland Psychiatric Research Center. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Genome-wide analyses of the bZIP family reveal their involvement in the development, ripening and abiotic stress response in banana

PubMed Central

Hu, Wei; Wang, Lianzhe; Tie, Weiwei; Yan, Yan; Ding, Zehong; Liu, Juhua; Li, Meiying; Peng, Ming; Xu, Biyu; Jin, Zhiqiang

2016-01-01

The leucine zipper (bZIP) transcription factors play important roles in multiple biological processes. However, less information is available regarding the bZIP family in the important fruit crop banana. In this study, 121 bZIP transcription factor genes were identified in the banana genome. Phylogenetic analysis showed that MabZIPs were classified into 11 subfamilies. The majority of MabZIP genes in the same subfamily shared similar gene structures and conserved motifs. The comprehensive transcriptome analysis of two banana genotypes revealed the differential expression patterns of MabZIP genes in different organs, in various stages of fruit development and ripening, and in responses to abiotic stresses, including drought, cold, and salt. Interaction networks and co-expression assays showed that group A MabZIP-mediated networks participated in various stress signaling, which was strongly activated in Musa ABB Pisang Awak. This study provided new insights into the complicated transcriptional control of MabZIP genes and provided robust tissue-specific, development-dependent, and abiotic stress-responsive candidate MabZIP genes for potential applications in the genetic improvement of banana cultivars. PMID:27445085

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

PubMed Central

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

2018-01-01

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

Quantitative comparison of microarray experiments with published leukemia related gene expression signatures.

PubMed

Klein, Hans-Ulrich; Ruckert, Christian; Kohlmann, Alexander; Bullinger, Lars; Thiede, Christian; Haferlach, Torsten; Dugas, Martin

2009-12-15

Multiple gene expression signatures derived from microarray experiments have been published in the field of leukemia research. A comparison of these signatures with results from new experiments is useful for verification as well as for interpretation of the results obtained. Currently, the percentage of overlapping genes is frequently used to compare published gene signatures against a signature derived from a new experiment. However, it has been shown that the percentage of overlapping genes is of limited use for comparing two experiments due to the variability of gene signatures caused by different array platforms or assay-specific influencing parameters. Here, we present a robust approach for a systematic and quantitative comparison of published gene expression signatures with an exemplary query dataset. A database storing 138 leukemia-related published gene signatures was designed. Each gene signature was manually annotated with terms according to a leukemia-specific taxonomy. Two analysis steps are implemented to compare a new microarray dataset with the results from previous experiments stored and curated in the database. First, the global test method is applied to assess gene signatures and to constitute a ranking among them. In a subsequent analysis step, the focus is shifted from single gene signatures to chromosomal aberrations or molecular mutations as modeled in the taxonomy. Potentially interesting disease characteristics are detected based on the ranking of gene signatures associated with these aberrations stored in the database. Two example analyses are presented. An implementation of the approach is freely available as web-based application. The presented approach helps researchers to systematically integrate the knowledge derived from numerous microarray experiments into the analysis of a new dataset. By means of example leukemia datasets we demonstrate that this approach detects related experiments as well as related molecular mutations and may help to interpret new microarray data.

Sort-Seq Approach to Engineering a Formaldehyde-Inducible Promoter for Dynamically Regulated Escherichia coli Growth on Methanol

PubMed Central

2017-01-01

Tight and tunable control of gene expression is a highly desirable goal in synthetic biology for constructing predictable gene circuits and achieving preferred phenotypes. Elucidating the sequence–function relationship of promoters is crucial for manipulating gene expression at the transcriptional level, particularly for inducible systems dependent on transcriptional regulators. Sort-seq methods employing fluorescence-activated cell sorting (FACS) and high-throughput sequencing allow for the quantitative analysis of sequence–function relationships in a robust and rapid way. Here we utilized a massively parallel sort-seq approach to analyze the formaldehyde-inducible Escherichia coli promoter (Pfrm) with single-nucleotide resolution. A library of mutated formaldehyde-inducible promoters was cloned upstream of gfp on a plasmid. The library was partitioned into bins via FACS on the basis of green fluorescent protein (GFP) expression level, and mutated promoters falling into each expression bin were identified with high-throughput sequencing. The resulting analysis identified two 19 base pair repressor binding sites, one upstream of the −35 RNA polymerase (RNAP) binding site and one overlapping with the −10 site, and assessed the relative importance of each position and base therein. Key mutations were identified for tuning expression levels and were used to engineer formaldehyde-inducible promoters with predictable activities. Engineered variants demonstrated up to 14-fold lower basal expression, 13-fold higher induced expression, and a 3.6-fold stronger response as indicated by relative dynamic range. Finally, an engineered formaldehyde-inducible promoter was employed to drive the expression of heterologous methanol assimilation genes and achieved increased biomass levels on methanol, a non-native substrate of E. coli. PMID:28463494

GO-PCA: An Unsupervised Method to Explore Gene Expression Data Using Prior Knowledge

PubMed Central

Wagner, Florian

2015-01-01

Method Genome-wide expression profiling is a widely used approach for characterizing heterogeneous populations of cells, tissues, biopsies, or other biological specimen. The exploratory analysis of such data typically relies on generic unsupervised methods, e.g. principal component analysis (PCA) or hierarchical clustering. However, generic methods fail to exploit prior knowledge about the molecular functions of genes. Here, I introduce GO-PCA, an unsupervised method that combines PCA with nonparametric GO enrichment analysis, in order to systematically search for sets of genes that are both strongly correlated and closely functionally related. These gene sets are then used to automatically generate expression signatures with functional labels, which collectively aim to provide a readily interpretable representation of biologically relevant similarities and differences. The robustness of the results obtained can be assessed by bootstrapping. Results I first applied GO-PCA to datasets containing diverse hematopoietic cell types from human and mouse, respectively. In both cases, GO-PCA generated a small number of signatures that represented the majority of lineages present, and whose labels reflected their respective biological characteristics. I then applied GO-PCA to human glioblastoma (GBM) data, and recovered signatures associated with four out of five previously defined GBM subtypes. My results demonstrate that GO-PCA is a powerful and versatile exploratory method that reduces an expression matrix containing thousands of genes to a much smaller set of interpretable signatures. In this way, GO-PCA aims to facilitate hypothesis generation, design of further analyses, and functional comparisons across datasets. PMID:26575370

GO-PCA: An Unsupervised Method to Explore Gene Expression Data Using Prior Knowledge.

PubMed

Wagner, Florian

2015-01-01

Genome-wide expression profiling is a widely used approach for characterizing heterogeneous populations of cells, tissues, biopsies, or other biological specimen. The exploratory analysis of such data typically relies on generic unsupervised methods, e.g. principal component analysis (PCA) or hierarchical clustering. However, generic methods fail to exploit prior knowledge about the molecular functions of genes. Here, I introduce GO-PCA, an unsupervised method that combines PCA with nonparametric GO enrichment analysis, in order to systematically search for sets of genes that are both strongly correlated and closely functionally related. These gene sets are then used to automatically generate expression signatures with functional labels, which collectively aim to provide a readily interpretable representation of biologically relevant similarities and differences. The robustness of the results obtained can be assessed by bootstrapping. I first applied GO-PCA to datasets containing diverse hematopoietic cell types from human and mouse, respectively. In both cases, GO-PCA generated a small number of signatures that represented the majority of lineages present, and whose labels reflected their respective biological characteristics. I then applied GO-PCA to human glioblastoma (GBM) data, and recovered signatures associated with four out of five previously defined GBM subtypes. My results demonstrate that GO-PCA is a powerful and versatile exploratory method that reduces an expression matrix containing thousands of genes to a much smaller set of interpretable signatures. In this way, GO-PCA aims to facilitate hypothesis generation, design of further analyses, and functional comparisons across datasets.

Multiplexed color-coded probe-based gene expression assessment for clinical molecular diagnostics in formalin-fixed paraffin-embedded human renal allograft tissue.

PubMed

Adam, Benjamin; Afzali, Bahman; Dominy, Katherine M; Chapman, Erin; Gill, Reeda; Hidalgo, Luis G; Roufosse, Candice; Sis, Banu; Mengel, Michael

2016-03-01

Histopathologic diagnoses in transplantation can be improved with molecular testing. Preferably, molecular diagnostics should fit into standard-of-care workflows for transplant biopsies, that is, formalin-fixed paraffin-embedded (FFPE) processing. The NanoString(®) gene expression platform has recently been shown to work with FFPE samples. We aimed to evaluate its methodological robustness and feasibility for gene expression studies in human FFPE renal allograft samples. A literature-derived antibody-mediated rejection (ABMR) 34-gene set, comprised of endothelial, NK cell, and inflammation transcripts, was analyzed in different retrospective biopsy cohorts and showed potential to molecularly discriminate ABMR cases, including FFPE samples. NanoString(®) results were reproducible across a range of RNA input quantities (r = 0.998), with different operators (r = 0.998), and between different reagent lots (r = 0.983). There was moderate correlation between NanoString(®) with FFPE tissue and quantitative reverse transcription polymerase chain reaction (qRT-PCR) with corresponding dedicated fresh-stabilized tissue (r = 0.487). Better overall correlation with histology was observed with NanoString(®) (r = 0.354) than with qRT-PCR (r = 0.146). Our results demonstrate the feasibility of multiplexed gene expression quantification from FFPE renal allograft tissue. This represents a method for prospective and retrospective validation of molecular diagnostics and its adoption in clinical transplantation pathology. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Characterization of visceral and subcutaneous adipose tissue transcriptome in pregnant women with and without spontaneous labor at term: implication of alternative splicing in the metabolic adaptations of adipose tissue to parturition.

PubMed

Mazaki-Tovi, Shali; Tarca, Adi L; Vaisbuch, Edi; Kusanovic, Juan Pedro; Than, Nandor Gabor; Chaiworapongsa, Tinnakorn; Dong, Zhong; Hassan, Sonia S; Romero, Roberto

2016-10-01

The aim of this study was to determine gene expression and splicing changes associated with parturition and regions (visceral vs. subcutaneous) of the adipose tissue of pregnant women. The transcriptome of visceral and abdominal subcutaneous adipose tissue from pregnant women at term with (n=15) and without (n=25) spontaneous labor was profiled with the Affymetrix GeneChip Human Exon 1.0 ST array. Overall gene expression changes and the differential exon usage rate were compared between patient groups (unpaired analyses) and adipose tissue regions (paired analyses). Selected genes were tested by quantitative reverse transcription-polymerase chain reaction. Four hundred and eighty-two genes were differentially expressed between visceral and subcutaneous fat of pregnant women with spontaneous labor at term (q-value <0.1; fold change >1.5). Biological processes enriched in this comparison included tissue and vasculature development as well as inflammatory and metabolic pathways. Differential splicing was found for 42 genes [q-value <0.1; differences in Finding Isoforms using Robust Multichip Analysis scores >2] between adipose tissue regions of women not in labor. Differential exon usage associated with parturition was found for three genes (LIMS1, HSPA5, and GSTK1) in subcutaneous tissues. We show for the first time evidence of implication of mRNA splicing and processing machinery in the subcutaneous adipose tissue of women in labor compared to those without labor.

A Guideline to Family-Wide Comparative State-of-the-Art Quantitative RT-PCR Analysis Exemplified with a Brassicaceae Cross-Species Seed Germination Case Study[W][OA

PubMed Central

Graeber, Kai; Linkies, Ada; Wood, Andrew T.A.; Leubner-Metzger, Gerhard

2011-01-01

Comparative biology includes the comparison of transcriptome and quantitative real-time RT-PCR (qRT-PCR) data sets in a range of species to detect evolutionarily conserved and divergent processes. Transcript abundance analysis of target genes by qRT-PCR requires a highly accurate and robust workflow. This includes reference genes with high expression stability (i.e., low intersample transcript abundance variation) for correct target gene normalization. Cross-species qRT-PCR for proper comparative transcript quantification requires reference genes suitable for different species. We addressed this issue using tissue-specific transcriptome data sets of germinating Lepidium sativum seeds to identify new candidate reference genes. We investigated their expression stability in germinating seeds of L. sativum and Arabidopsis thaliana by qRT-PCR, combined with in silico analysis of Arabidopsis and Brassica napus microarray data sets. This revealed that reference gene expression stability is higher for a given developmental process between distinct species than for distinct developmental processes within a given single species. The identified superior cross-species reference genes may be used for family-wide comparative qRT-PCR analysis of Brassicaceae seed germination. Furthermore, using germinating seeds, we exemplify optimization of the qRT-PCR workflow for challenging tissues regarding RNA quality, transcript stability, and tissue abundance. Our work therefore can serve as a guideline for moving beyond Arabidopsis by establishing high-quality cross-species qRT-PCR. PMID:21666000

Brg1 modulates enhancer activation in mesoderm lineage commitment

DOE PAGES

Alexander, Jeffrey M.; Hota, Swetansu K.; He, Daniel; ...

2015-03-26

The interplay between different levels of gene regulation in modulating developmental transcriptional programs, such as histone modifications and chromatin remodeling, is not well understood. Here, we show that the chromatin remodeling factor Brg1 is required for enhancer activation in mesoderm induction. In an embryonic stem cell-based directed differentiation assay, the absence of Brg1 results in a failure of cardiomyocyte differentiation and broad deregulation of lineage-specific gene expression during mesoderm induction. We find that Brg1 co-localizes with H3K27ac at distal enhancers and is required for robust H3K27 acetylation at distal enhancers that are activated during mesoderm induction. Brg1 is also requiredmore » to maintain Polycomb-mediated repression of non-mesodermal developmental regulators, suggesting cooperativity between Brg1 and Polycomb complexes. Thus, Brg1 is essential for modulating active and repressive chromatin states during mesoderm lineage commitment, in particular the activation of developmentally important enhancers. In conclusion, these findings demonstrate interplay between chromatin remodeling complexes and histone modifications that, together, ensure robust and broad gene regulation during crucial lineage commitment decisions.« less

Ectopic expression of miR-126*, an intronic product of the vascular endothelial EGF-like 7 gene, regulates prostein translation and invasiveness of prostate cancer LNCaP cells.

PubMed

Musiyenko, Alla; Bitko, Vira; Barik, Sailen

2008-03-01

MicroRNAs (miRNAs) are endogenous noncoding RNAs that down-regulate gene expression by promoting cleavage or translational arrest of target mRNAs. While most miRNAs are transcribed from their own dedicated genes, some map to introns of 'host' transcripts, the biological significance of which remains unknown. Here, we show that prostate cells are naturally devoid of EGF-like domain 7 (Egfl7) transcripts and hence also deficient in a miRNA, miR-126*, generated from splicing and processing of its ninth intron. Use of recombinant and synthetic miRNAs or a specific antagomir established a role of miR-126* in silencing prostein in non-endothelial cells. We mapped two miR-126*-binding sites in the 3'UTR of the prostein mRNA required for translational repression. Transfection of synthetic miR-126* into prostate cancer LNCaP cells strongly reduced the translation of prostein. Interestingly, loss of prostein correlated with reduction of LNCaP cell migration and invasion. Thus, the robust expression of prostein protein in the prostate cells results from a combination of transcriptional activation of the prostein gene and absence of intronic miRNA-126* due to the prostate-specific repression of the Egfl7 gene. We conclude that intronic miRNAs from tissue-specific transcripts, or their natural absence, make cardinal contributions to cellular gene expression and phenotype. These findings also open the door to tissue-specific miRNA therapy.

Natural genetic variation profoundly regulates gene expression in immune cells and dictates susceptibility to CNS autoimmunity

PubMed Central

Bearoff, Frank; del Rio, Roxana; Case, Laure K.; Dragon, Julie A.; Nguyen-Vu, Trang; Lin, Chin-Yo; Blankenhorn, Elizabeth P.; Teuscher, Cory; Krementsov, Dimitry N.

2016-01-01

Regulation of gene expression in immune cells is known to be under genetic control, and likely contributes to susceptibility to autoimmune diseases, such as multiple sclerosis (MS). How this occurs in concert across multiple immune cell types is poorly understood. Using a mouse model that harnesses the genetic diversity of wild-derived mice, more accurately reflecting genetically diverse human populations, we provide an extensive characterization of the genetic regulation of gene expression in five different naïve immune cell types relevant to MS. The immune cell transcriptome is shown to be under profound genetic control, exhibiting diverse patterns: global, cell-specific, and sex-specific. Bioinformatic analysis of the genetically-controlled transcript networks reveals reduced cell type-specificity and inflammatory activity in wild-derived PWD/PhJ mice, compared with the conventional laboratory strain C57BL/6J. Additionally, candidate MS-GWAS genes were significantly enriched among transcripts overrepresented in C57BL/6J cells compared to PWD. These expression level differences correlate with robust differences in susceptibility to experimental autoimmune encephalomyelitis, the principal model of MS, and skewing of the encephalitogenic T cell responses. Taken together, our results provide functional insights into the genetic regulation of the immune transcriptome, and shed light on how this in turn contributes to susceptibility to autoimmune disease. PMID:27653816

scEpath: Energy landscape-based inference of transition probabilities and cellular trajectories from single-cell transcriptomic data.

PubMed

Jin, Suoqin; MacLean, Adam L; Peng, Tao; Nie, Qing

2018-02-05

Single-cell RNA-sequencing (scRNA-seq) offers unprecedented resolution for studying cellular decision-making processes. Robust inference of cell state transition paths and probabilities is an important yet challenging step in the analysis of these data. Here we present scEpath, an algorithm that calculates energy landscapes and probabilistic directed graphs in order to reconstruct developmental trajectories. We quantify the energy landscape using "single-cell energy" and distance-based measures, and find that the combination of these enables robust inference of the transition probabilities and lineage relationships between cell states. We also identify marker genes and gene expression patterns associated with cell state transitions. Our approach produces pseudotemporal orderings that are - in combination - more robust and accurate than current methods, and offers higher resolution dynamics of the cell state transitions, leading to new insight into key transition events during differentiation and development. Moreover, scEpath is robust to variation in the size of the input gene set, and is broadly unsupervised, requiring few parameters to be set by the user. Applications of scEpath led to the identification of a cell-cell communication network implicated in early human embryo development, and novel transcription factors important for myoblast differentiation. scEpath allows us to identify common and specific temporal dynamics and transcriptional factor programs along branched lineages, as well as the transition probabilities that control cell fates. A MATLAB package of scEpath is available at https://github.com/sqjin/scEpath. qnie@uci.edu. Supplementary data are available at Bioinformatics online. © The Author(s) 2018. Published by Oxford University Press.

Transcriptional oscillation of canonical clock genes in mouse peripheral tissues

PubMed Central

Yamamoto, Takuro; Nakahata, Yasukazu; Soma, Haruhiko; Akashi, Makoto; Mamine, Takayoshi; Takumi, Toru

2004-01-01

Background The circadian rhythm of about 24 hours is a fundamental physiological function observed in almost all organisms from prokaryotes to humans. Identification of clock genes has allowed us to study the molecular bases for circadian behaviors and temporal physiological processes such as hormonal secretion, and has prompted the idea that molecular clocks reside not only in a central pacemaker, the suprachiasmatic nuclei (SCN) of hypothalamus in mammals, but also in peripheral tissues, even in immortalized cells. Furthermore, previous molecular dissection revealed that the mechanism of circadian oscillation at a molecular level is based on transcriptional regulation of clock and clock-controlled genes. Results We systematically analyzed the mRNA expression of clock and clock-controlled genes in mouse peripheral tissues. Eight genes (mBmal1, mNpas2, mRev-erbα, mDbp, mRev-erbβ, mPer3, mPer1 and mPer2; given in the temporal order of the rhythm peak) showed robust circadian expressions of mRNAs in all tissues except testis, suggesting that these genes are core molecules of the molecular biological clock. The bioinformatics analysis revealed that these genes have one or a combination of 3 transcriptional elements (RORE, DBPE, and E-box), which are conserved among human, mouse, and rat genome sequences, and indicated that these 3 elements may be responsible for the biological timing of expression of canonical clock genes. Conclusions The observation of oscillatory profiles of canonical clock genes is not only useful for physiological and pathological examination of the circadian clock in various organs but also important for systematic understanding of transcriptional regulation on a genome-wide basis. Our finding of the oscillatory expression of canonical clock genes with a temporal order provides us an interesting hypothesis, that cyclic timing of all clock and clock-controlled genes may be dependent on several transcriptional elements including 3 known elements, E-box, RORE, and DBPE. PMID:15473909

Novel Minicircle Vector for Gene Therapy in Murine Myocardial Infarction

PubMed Central

Huang, Mei; Chen, ZhiYing; Hu, Shijun; Jia, Fangjun; Li, Zongjin; Hoyt, Grant; Robbins, Robert C.; Kay, Mark A.; Wu, Joseph C.

2011-01-01

Background Conventional plasmids for gene therapy produce low-level and short-term gene expression. In this study, we develop a novel non-viral vector which robustly and persistently expresses the hypoxia inducible factor-1 alpha (HIF-1α) therapeutic gene in the heart, leading to functional benefits following myocardial infarction (MI). Methods and Results We first created minicircles carrying double fusion (MC-DF) reporter gene consisting of firefly luciferase and enhanced green fluorescent protein (Fluc-eGFP) for noninvasive measurement of transfection efficiency. Mouse C2C12 myoblasts and normal FVB mice were used for in vitro and in vivo confirmation, respectively. Bioluminescence imaging (BLI) showed stable minicircle gene expression in the heart for >12 weeks and the activity level was 5.6±1.2 fold stronger than regular plasmid at day 4 (P<0.01). Next, we created minicircles carrying hypoxia inducible factor-1 alpha (MC-HIF-1α) therapeutic gene for treatment of MI. Adult FVB mice underwent LAD ligation and were injected intramyocardially with (1) MC-HIF-1α, (2) regular plasmid carrying HIF-1α (PL-HIF-1α) as positive control, and (3) PBS as negative control (n=10/group). Echocardiographic study showed a significantly greater improvement of left ventricular ejection fraction (LVEF) in the minicircle group (51.3%±3.6%) compared to regular plasmid group (42.3%±4.1%) and saline group (30.5%±2.8%) at week 4 (P<0.05 for both). Histology demonstrated increased neoangiogenesis in both treatment groups. Finally, Western blot showed minicircles express >50% higher HIF-1α level than regular plasmid. Conclusion Taken together, this is the first study to demonstrate that minicircles can significantly improve transfection efficiency, duration of transgene expression, and cardiac contractility. Given the serious drawbacks associated with most viral vectors, we believe this novel non-viral vector can be of great value for cardiac gene therapy protocols. PMID:19752373

Multiple transcription factors directly regulate Hox gene lin-39 expression in ventral hypodermal cells of the C. elegans embryo and larva, including the hypodermal fate regulators LIN-26 and ELT-6.

PubMed

Liu, Wan-Ju; Reece-Hoyes, John S; Walhout, Albertha J M; Eisenmann, David M

2014-05-13

Hox genes encode master regulators of regional fate specification during early metazoan development. Much is known about the initiation and regulation of Hox gene expression in Drosophila and vertebrates, but less is known in the non-arthropod invertebrate model system, C. elegans. The C. elegans Hox gene lin-39 is required for correct fate specification in the midbody region, including the Vulval Precursor Cells (VPCs). To better understand lin-39 regulation and function, we aimed to identify transcription factors necessary for lin-39 expression in the VPCs, and in particular sought factors that initiate lin-39 expression in the embryo. We used the yeast one-hybrid (Y1H) method to screen for factors that bound to 13 fragments from the lin-39 region: twelve fragments contained sequences conserved between C. elegans and two other nematode species, while one fragment was known to drive reporter gene expression in the early embryo in cells that generate the VPCs. Sixteen transcription factors that bind to eight lin-39 genomic fragments were identified in yeast, and we characterized several factors by verifying their physical interactions in vitro, and showing that reduction of their function leads to alterations in lin-39 levels and lin-39::GFP reporter expression in vivo. Three factors, the orphan nuclear hormone receptor NHR-43, the hypodermal fate regulator LIN-26, and the GATA factor ELT-6 positively regulate lin-39 expression in the embryonic precursors to the VPCs. In particular, ELT-6 interacts with an enhancer that drives GFP expression in the early embryo, and the ELT-6 site we identified is necessary for proper embryonic expression. These three factors, along with the factors ZTF-17, BED-3 and TBX-9, also positively regulate lin-39 expression in the larval VPCs. These results significantly expand the number of factors known to directly bind and regulate lin-39 expression, identify the first factors required for lin-39 expression in the embryo, and hint at a positive feedback mechanism involving GATA factors that maintains lin-39 expression in the vulval lineage. This work indicates that, as in other organisms, the regulation of Hox gene expression in C. elegans is complicated, redundant and robust.

Development and application of a modified dynamic time warping algorithm (DTW-S) to analyses of primate brain expression time series

PubMed Central

2011-01-01

Background Comparing biological time series data across different conditions, or different specimens, is a common but still challenging task. Algorithms aligning two time series represent a valuable tool for such comparisons. While many powerful computation tools for time series alignment have been developed, they do not provide significance estimates for time shift measurements. Results Here, we present an extended version of the original DTW algorithm that allows us to determine the significance of time shift estimates in time series alignments, the DTW-Significance (DTW-S) algorithm. The DTW-S combines important properties of the original algorithm and other published time series alignment tools: DTW-S calculates the optimal alignment for each time point of each gene, it uses interpolated time points for time shift estimation, and it does not require alignment of the time-series end points. As a new feature, we implement a simulation procedure based on parameters estimated from real time series data, on a series-by-series basis, allowing us to determine the false positive rate (FPR) and the significance of the estimated time shift values. We assess the performance of our method using simulation data and real expression time series from two published primate brain expression datasets. Our results show that this method can provide accurate and robust time shift estimates for each time point on a gene-by-gene basis. Using these estimates, we are able to uncover novel features of the biological processes underlying human brain development and maturation. Conclusions The DTW-S provides a convenient tool for calculating accurate and robust time shift estimates at each time point for each gene, based on time series data. The estimates can be used to uncover novel biological features of the system being studied. The DTW-S is freely available as an R package TimeShift at http://www.picb.ac.cn/Comparative/data.html. PMID:21851598

Development and application of a modified dynamic time warping algorithm (DTW-S) to analyses of primate brain expression time series.

PubMed

Yuan, Yuan; Chen, Yi-Ping Phoebe; Ni, Shengyu; Xu, Augix Guohua; Tang, Lin; Vingron, Martin; Somel, Mehmet; Khaitovich, Philipp

2011-08-18

Comparing biological time series data across different conditions, or different specimens, is a common but still challenging task. Algorithms aligning two time series represent a valuable tool for such comparisons. While many powerful computation tools for time series alignment have been developed, they do not provide significance estimates for time shift measurements. Here, we present an extended version of the original DTW algorithm that allows us to determine the significance of time shift estimates in time series alignments, the DTW-Significance (DTW-S) algorithm. The DTW-S combines important properties of the original algorithm and other published time series alignment tools: DTW-S calculates the optimal alignment for each time point of each gene, it uses interpolated time points for time shift estimation, and it does not require alignment of the time-series end points. As a new feature, we implement a simulation procedure based on parameters estimated from real time series data, on a series-by-series basis, allowing us to determine the false positive rate (FPR) and the significance of the estimated time shift values. We assess the performance of our method using simulation data and real expression time series from two published primate brain expression datasets. Our results show that this method can provide accurate and robust time shift estimates for each time point on a gene-by-gene basis. Using these estimates, we are able to uncover novel features of the biological processes underlying human brain development and maturation. The DTW-S provides a convenient tool for calculating accurate and robust time shift estimates at each time point for each gene, based on time series data. The estimates can be used to uncover novel biological features of the system being studied. The DTW-S is freely available as an R package TimeShift at http://www.picb.ac.cn/Comparative/data.html.

Integrated multi-cohort transcriptional meta-analysis of neurodegenerative diseases.

PubMed

Li, Matthew D; Burns, Terry C; Morgan, Alexander A; Khatri, Purvesh

2014-09-04

Neurodegenerative diseases share common pathologic features including neuroinflammation, mitochondrial dysfunction and protein aggregation, suggesting common underlying mechanisms of neurodegeneration. We undertook a meta-analysis of public gene expression data for neurodegenerative diseases to identify a common transcriptional signature of neurodegeneration. Using 1,270 post-mortem central nervous system tissue samples from 13 patient cohorts covering four neurodegenerative diseases, we identified 243 differentially expressed genes, which were similarly dysregulated in 15 additional patient cohorts of 205 samples including seven neurodegenerative diseases. This gene signature correlated with histologic disease severity. Metallothioneins featured prominently among differentially expressed genes, and functional pathway analysis identified specific convergent themes of dysregulation. MetaCore network analyses revealed various novel candidate hub genes (e.g. STAU2). Genes associated with M1-polarized macrophages and reactive astrocytes were strongly enriched in the meta-analysis data. Evaluation of genes enriched in neurons revealed 70 down-regulated genes, over half not previously associated with neurodegeneration. Comparison with aging brain data (3 patient cohorts, 221 samples) revealed 53 of these to be unique to neurodegenerative disease, many of which are strong candidates to be important in neuropathogenesis (e.g. NDN, NAP1L2). ENCODE ChIP-seq analysis predicted common upstream transcriptional regulators not associated with normal aging (REST, RBBP5, SIN3A, SP2, YY1, ZNF143, IKZF1). Finally, we removed genes common to neurodegeneration from disease-specific gene signatures, revealing uniquely robust immune response and JAK-STAT signaling in amyotrophic lateral sclerosis. Our results implicate pervasive bioenergetic deficits, M1-type microglial activation and gliosis as unifying themes of neurodegeneration, and identify numerous novel genes associated with neurodegenerative processes.

Correlation of Biomarker Expression in Colonic Mucosa with Disease Phenotype in Crohn's Disease and Ulcerative Colitis.

PubMed

Bruno, Maria E C; Rogier, Eric W; Arsenescu, Razvan I; Flomenhoft, Deborah R; Kurkjian, Cathryn J; Ellis, Gavin I; Kaetzel, Charlotte S

2015-10-01

Inflammatory bowel diseases (IBD), including Crohn's disease (CD) and ulcerative colitis (UC), are characterized by chronic intestinal inflammation due to immunological, microbial, and environmental factors in genetically predisposed individuals. Advances in the diagnosis, prognosis, and treatment of IBD require the identification of robust biomarkers that can be used for molecular classification of diverse disease presentations. We previously identified five genes, RELA, TNFAIP3 (A20), PIGR, TNF, and IL8, whose mRNA levels in colonic mucosal biopsies could be used in a multivariate analysis to classify patients with CD based on disease behavior and responses to therapy. We compared expression of these five biomarkers in IBD patients classified as having CD or UC, and in healthy controls. Patients with CD were characterized as having decreased median expression of TNFAIP3, PIGR, and TNF in non-inflamed colonic mucosa as compared to healthy controls. By contrast, UC patients exhibited decreased expression of PIGR and elevated expression of IL8 in colonic mucosa compared to healthy controls. A multivariate analysis combining mRNA levels for all five genes resulted in segregation of individuals based on disease presentation (CD vs. UC) as well as severity, i.e., patients in remission versus those with acute colitis at the time of biopsy. We propose that this approach could be used as a model for molecular classification of IBD patients, which could further be enhanced by the inclusion of additional genes that are identified by functional studies, global gene expression analyses, and genome-wide association studies.

Quantitative Analyses of Core Promoters Enable Precise Engineering of Regulated Gene Expression in Mammalian Cells.

PubMed

Ede, Christopher; Chen, Ximin; Lin, Meng-Yin; Chen, Yvonne Y

2016-05-20

Inducible transcription systems play a crucial role in a wide array of synthetic biology circuits. However, the majority of inducible promoters are constructed from a limited set of tried-and-true promoter parts, which are susceptible to common shortcomings such as high basal expression levels (i.e., leakiness). To expand the toolbox for regulated mammalian gene expression and facilitate the construction of mammalian genetic circuits with precise functionality, we quantitatively characterized a panel of eight core promoters, including sequences with mammalian, viral, and synthetic origins. We demonstrate that this selection of core promoters can provide a wide range of basal gene expression levels and achieve a gradient of fold-inductions spanning 2 orders of magnitude. Furthermore, commonly used parts such as minimal CMV and minimal SV40 promoters were shown to achieve robust gene expression upon induction, but also suffer from high levels of leakiness. In contrast, a synthetic promoter, YB_TATA, was shown to combine low basal expression with high transcription rate in the induced state to achieve significantly higher fold-induction ratios compared to all other promoters tested. These behaviors remain consistent when the promoters are coupled to different genetic outputs and different response elements, as well as across different host-cell types and DNA copy numbers. We apply this quantitative understanding of core promoter properties to the successful engineering of human T cells that respond to antigen stimulation via chimeric antigen receptor signaling specifically under hypoxic environments. Results presented in this study can facilitate the design and calibration of future mammalian synthetic biology systems capable of precisely programmed functionality.

From cytoskeletal dynamics to organ asymmetry: a nonlinear, regulative pathway underlies left-right patterning.

PubMed

McDowell, Gary; Rajadurai, Suvithan; Levin, Michael

2016-12-19

Consistent left-right (LR) asymmetry is a fundamental aspect of the bodyplan across phyla, and errors of laterality form an important class of human birth defects. Its molecular underpinning was first discovered as a sequential pathway of left- and right-sided gene expression that controlled positioning of the heart and visceral organs. Recent data have revised this picture in two important ways. First, the physical origin of chirality has been identified; cytoskeletal dynamics underlie the asymmetry of single-cell behaviour and patterning of the LR axis. Second, the pathway is not linear: early disruptions that alter the normal sidedness of upstream asymmetric genes do not necessarily induce defects in the laterality of the downstream genes or in organ situs Thus, the LR pathway is a unique example of two fascinating aspects of biology: the interplay of physics and genetics in establishing large-scale anatomy, and regulative (shape-homeostatic) pathways that correct molecular and anatomical errors over time. Here, we review aspects of asymmetry from its intracellular, cytoplasmic origins to the recently uncovered ability of the LR control circuitry to achieve correct gene expression and morphology despite reversals of key 'determinant' genes. We provide novel functional data, in Xenopus laevis, on conserved elements of the cytoskeleton that drive asymmetry, and comparatively analyse it together with previously published results in the field. Our new observations and meta-analysis demonstrate that despite aberrant expression of upstream regulatory genes, embryos can progressively normalize transcriptional cascades and anatomical outcomes. LR patterning can thus serve as a paradigm of how subcellular physics and gene expression cooperate to achieve developmental robustness of a body axis.This article is part of the themed issue 'Provocative questions in left-right asymmetry'. © 2016 The Author(s).

From cytoskeletal dynamics to organ asymmetry: a nonlinear, regulative pathway underlies left–right patterning

PubMed Central

Rajadurai, Suvithan

2016-01-01

Consistent left–right (LR) asymmetry is a fundamental aspect of the bodyplan across phyla, and errors of laterality form an important class of human birth defects. Its molecular underpinning was first discovered as a sequential pathway of left- and right-sided gene expression that controlled positioning of the heart and visceral organs. Recent data have revised this picture in two important ways. First, the physical origin of chirality has been identified; cytoskeletal dynamics underlie the asymmetry of single-cell behaviour and patterning of the LR axis. Second, the pathway is not linear: early disruptions that alter the normal sidedness of upstream asymmetric genes do not necessarily induce defects in the laterality of the downstream genes or in organ situs. Thus, the LR pathway is a unique example of two fascinating aspects of biology: the interplay of physics and genetics in establishing large-scale anatomy, and regulative (shape-homeostatic) pathways that correct molecular and anatomical errors over time. Here, we review aspects of asymmetry from its intracellular, cytoplasmic origins to the recently uncovered ability of the LR control circuitry to achieve correct gene expression and morphology despite reversals of key ‘determinant’ genes. We provide novel functional data, in Xenopus laevis, on conserved elements of the cytoskeleton that drive asymmetry, and comparatively analyse it together with previously published results in the field. Our new observations and meta-analysis demonstrate that despite aberrant expression of upstream regulatory genes, embryos can progressively normalize transcriptional cascades and anatomical outcomes. LR patterning can thus serve as a paradigm of how subcellular physics and gene expression cooperate to achieve developmental robustness of a body axis. This article is part of the themed issue ‘Provocative questions in left–right asymmetry’. PMID:27821521

Robust extraction of functional signals from gene set analysis using a generalized threshold free scoring function

PubMed Central

2009-01-01

Background A central task in contemporary biosciences is the identification of biological processes showing response in genome-wide differential gene expression experiments. Two types of analysis are common. Either, one generates an ordered list based on the differential expression values of the probed genes and examines the tail areas of the list for over-representation of various functional classes. Alternatively, one monitors the average differential expression level of genes belonging to a given functional class. So far these two types of method have not been combined. Results We introduce a scoring function, Gene Set Z-score (GSZ), for the analysis of functional class over-representation that combines two previous analysis methods. GSZ encompasses popular functions such as correlation, hypergeometric test, Max-Mean and Random Sets as limiting cases. GSZ is stable against changes in class size as well as across different positions of the analysed gene list in tests with randomized data. GSZ shows the best overall performance in a detailed comparison to popular functions using artificial data. Likewise, GSZ stands out in a cross-validation of methods using split real data. A comparison of empirical p-values further shows a strong difference in favour of GSZ, which clearly reports better p-values for top classes than the other methods. Furthermore, GSZ detects relevant biological themes that are missed by the other methods. These observations also hold when comparing GSZ with popular program packages. Conclusion GSZ and improved versions of earlier methods are a useful contribution to the analysis of differential gene expression. The methods and supplementary material are available from the website http://ekhidna.biocenter.helsinki.fi/users/petri/public/GSZ/GSZscore.html. PMID:19775443

Sustained AAV9-mediated expression of a non-self protein in the CNS of non-human primates after immunomodulation

PubMed Central

Ramsingh, Arlene I.; Gray, Steven J.; Reilly, Andrew; Koday, Michael; Bratt, Debbie; Koday, Merika Treants; Murnane, Robert; Hu, Yuhui; Messer, Anne

2018-01-01

A critical issue in transgene delivery studies is immune reactivity to the transgene- encoded protein and its impact on sustained gene expression. Here, we test the hypothesis that immunomodulation by rapamycin can decrease immune reactivity after intrathecal AAV9 delivery of a transgene (GFP) in non-human primates, resulting in sustained GFP expression in the CNS. We show that rapamycin treatment clearly reduced the overall immunogenicity of the AAV9/GFP vector by lowering GFP- and AAV9-specific antibody responses, and decreasing T cell responses including cytokine and cytolytic effector responses. Spinal cord GFP protein expression was sustained for twelve weeks, with no toxicity. Immune correlates of robust transgene expression include negligible GFP-specific CD4 and CD8 T cell responses, absence of GFP-specific IFN-γ producing T cells, and absence of GFP-specific cytotoxic T cells, which support the hypothesis that decreased T cell reactivity results in sustained transgene expression. These data strongly support the use of modest doses of rapamycin to modulate immune responses for intrathecal gene therapies, and potentially a much wider range of viral vector-based therapeutics. PMID:29874260

A robust method for RNA extraction and purification from a single adult mouse tendon.

PubMed

Grinstein, Mor; Dingwall, Heather L; Shah, Rishita R; Capellini, Terence D; Galloway, Jenna L

2018-01-01

Mechanistic understanding of tendon molecular and cellular biology is crucial toward furthering our abilities to design new therapies for tendon and ligament injuries and disease. Recent transcriptomic and epigenomic studies in the field have harnessed the power of mouse genetics to reveal new insights into tendon biology. However, many mouse studies pool tendon tissues or use amplification methods to perform RNA analysis, which can significantly increase the experimental costs and limit the ability to detect changes in expression of low copy transcripts. Single Achilles tendons were harvested from uninjured, contralateral injured, and wild type mice between three and five months of age, and RNA was extracted. RNA Integrity Number (RIN) and concentration were determined, and RT-qPCR gene expression analysis was performed. After testing several RNA extraction approaches on single adult mouse Achilles tendons, we developed a protocol that was successful at obtaining high RIN and sufficient concentrations suitable for RNA analysis. We found that the RNA quality was sensitive to the time between tendon harvest and homogenization, and the RNA quality and concentration was dependent on the duration of homogenization. Using this method, we demonstrate that analysis of Scx gene expression in single mouse tendons reduces the biological variation caused by pooling tendons from multiple mice. We also show successful use of this approach to analyze Sox9 and Col1a2 gene expression changes in injured compared with uninjured control tendons. Our work presents a robust, cost-effective, and straightforward method to extract high quality RNA from a single adult mouse Achilles tendon at sufficient amounts for RT-qPCR as well as RNA-seq. We show this can reduce variation and decrease the overall costs associated with experiments. This approach can also be applied to other skeletal tissues, as well as precious human samples.

Exploiting the full power of temporal gene expression profiling through a new statistical test: application to the analysis of muscular dystrophy data.

PubMed

Vinciotti, Veronica; Liu, Xiaohui; Turk, Rolf; de Meijer, Emile J; 't Hoen, Peter A C

2006-04-03

The identification of biologically interesting genes in a temporal expression profiling dataset is challenging and complicated by high levels of experimental noise. Most statistical methods used in the literature do not fully exploit the temporal ordering in the dataset and are not suited to the case where temporal profiles are measured for a number of different biological conditions. We present a statistical test that makes explicit use of the temporal order in the data by fitting polynomial functions to the temporal profile of each gene and for each biological condition. A Hotelling T2-statistic is derived to detect the genes for which the parameters of these polynomials are significantly different from each other. We validate the temporal Hotelling T2-test on muscular gene expression data from four mouse strains which were profiled at different ages: dystrophin-, beta-sarcoglycan and gamma-sarcoglycan deficient mice, and wild-type mice. The first three are animal models for different muscular dystrophies. Extensive biological validation shows that the method is capable of finding genes with temporal profiles significantly different across the four strains, as well as identifying potential biomarkers for each form of the disease. The added value of the temporal test compared to an identical test which does not make use of temporal ordering is demonstrated via a simulation study, and through confirmation of the expression profiles from selected genes by quantitative PCR experiments. The proposed method maximises the detection of the biologically interesting genes, whilst minimising false detections. The temporal Hotelling T2-test is capable of finding relatively small and robust sets of genes that display different temporal profiles between the conditions of interest. The test is simple, it can be used on gene expression data generated from any experimental design and for any number of conditions, and it allows fast interpretation of the temporal behaviour of genes. The R code is available from V.V. The microarray data have been submitted to GEO under series GSE1574 and GSE3523.

Exploiting the full power of temporal gene expression profiling through a new statistical test: Application to the analysis of muscular dystrophy data

PubMed Central

Vinciotti, Veronica; Liu, Xiaohui; Turk, Rolf; de Meijer, Emile J; 't Hoen, Peter AC

2006-01-01

Background The identification of biologically interesting genes in a temporal expression profiling dataset is challenging and complicated by high levels of experimental noise. Most statistical methods used in the literature do not fully exploit the temporal ordering in the dataset and are not suited to the case where temporal profiles are measured for a number of different biological conditions. We present a statistical test that makes explicit use of the temporal order in the data by fitting polynomial functions to the temporal profile of each gene and for each biological condition. A Hotelling T2-statistic is derived to detect the genes for which the parameters of these polynomials are significantly different from each other. Results We validate the temporal Hotelling T2-test on muscular gene expression data from four mouse strains which were profiled at different ages: dystrophin-, beta-sarcoglycan and gamma-sarcoglycan deficient mice, and wild-type mice. The first three are animal models for different muscular dystrophies. Extensive biological validation shows that the method is capable of finding genes with temporal profiles significantly different across the four strains, as well as identifying potential biomarkers for each form of the disease. The added value of the temporal test compared to an identical test which does not make use of temporal ordering is demonstrated via a simulation study, and through confirmation of the expression profiles from selected genes by quantitative PCR experiments. The proposed method maximises the detection of the biologically interesting genes, whilst minimising false detections. Conclusion The temporal Hotelling T2-test is capable of finding relatively small and robust sets of genes that display different temporal profiles between the conditions of interest. The test is simple, it can be used on gene expression data generated from any experimental design and for any number of conditions, and it allows fast interpretation of the temporal behaviour of genes. The R code is available from V.V. The microarray data have been submitted to GEO under series GSE1574 and GSE3523. PMID:16584545

Development of an antibiotic marker-free platform for heterologous protein production in Streptomyces.

PubMed

Sevillano, Laura; Díaz, Margarita; Santamaría, Ramón I

2017-09-26

The industrial use of enzymes produced by microorganisms is continuously growing due to the need for sustainable solutions. Nevertheless, many of the plasmids used for recombinant production of proteins in bacteria are based on the use of antibiotic resistance genes as selection markers. The safety concerns and legal requirements surrounding the increased use of antibiotic resistance genes have made the development of new antibiotic-free approaches essential. In this work, a system completely free of antibiotic resistance genes and useful for the production of high yields of proteins in Streptomyces is described. This system is based on the separation of the two components of the yefM/yoeBsl (antitoxin/toxin) operon; the toxin (yoeBsl) gene, responsible for host death, is integrated into the genome and the antitoxin gene (yefMsl), which inactivates the toxin, is located in the expression plasmid. To develop this system, the toxin gene was integrated into the genome of a strain lacking the complete operon, and the antibiotic resistance gene integrated along with the toxin was eliminated by Cre recombinase to generate a final host strain free of any antibiotic resistance marker. In the same way, the antibiotic resistance gene from the final expression plasmid was removed by Dre recombinase. The usefulness of this system was analysed by checking the production of two hydrolases from different Streptomyces. Production of both proteins, with potential industrial use, was high and stable over time after strain storage and after serial subcultures. These results support the robustness and stability of the positive selection system developed. The total absence of antibiotic resistance genes makes this system a powerful tool for using Streptomyces as a host to produce proteins at the industrial level. This work is the first Streptomyces antibiotic marker-free system to be described. Graphical abstract Antibiotic marker-free platform for protein expression in Streptomyces. The antitoxin gene present in the expression plasmid counteracts the effect of the toxin gene in the genome. In absence of the expression plasmid, the toxin causes cell death ensuring that only plasmid-containing cells persist.

Bat Accelerated Regions Identify a Bat Forelimb Specific Enhancer in the HoxD Locus

PubMed Central

Mason, Mandy K.; VanderMeer, Julia E.; Zhao, Jingjing; Eckalbar, Walter L.; Logan, Malcolm; Illing, Nicola; Pollard, Katherine S.; Ahituv, Nadav

2016-01-01

The molecular events leading to the development of the bat wing remain largely unknown, and are thought to be caused, in part, by changes in gene expression during limb development. These expression changes could be instigated by variations in gene regulatory enhancers. Here, we used a comparative genomics approach to identify regions that evolved rapidly in the bat ancestor, but are highly conserved in other vertebrates. We discovered 166 bat accelerated regions (BARs) that overlap H3K27ac and p300 ChIP-seq peaks in developing mouse limbs. Using a mouse enhancer assay, we show that five Myotis lucifugus BARs drive gene expression in the developing mouse limb, with the majority showing differential enhancer activity compared to the mouse orthologous BAR sequences. These include BAR116, which is located telomeric to the HoxD cluster and had robust forelimb expression for the M. lucifugus sequence and no activity for the mouse sequence at embryonic day 12.5. Developing limb expression analysis of Hoxd10-Hoxd13 in Miniopterus natalensis bats showed a high-forelimb weak-hindlimb expression for Hoxd10-Hoxd11, similar to the expression trend observed for M. lucifugus BAR116 in mice, suggesting that it could be involved in the regulation of the bat HoxD complex. Combined, our results highlight novel regulatory regions that could be instrumental for the morphological differences leading to the development of the bat wing. PMID:27019019

Integration of Immune Cell Populations, mRNA-Seq, and CpG Methylation to Better Predict Humoral Immunity to Influenza Vaccination: Dependence of mRNA-Seq/CpG Methylation on Immune Cell Populations

PubMed Central

Zimmermann, Michael T.; Kennedy, Richard B.; Grill, Diane E.; Oberg, Ann L.; Goergen, Krista M.; Ovsyannikova, Inna G.; Haralambieva, Iana H.; Poland, Gregory A.

2017-01-01

The development of a humoral immune response to influenza vaccines occurs on a multisystems level. Due to the orchestration required for robust immune responses when multiple genes and their regulatory components across multiple cell types are involved, we examined an influenza vaccination cohort using multiple high-throughput technologies. In this study, we sought a more thorough understanding of how immune cell composition and gene expression relate to each other and contribute to interindividual variation in response to influenza vaccination. We first hypothesized that many of the differentially expressed (DE) genes observed after influenza vaccination result from changes in the composition of participants’ peripheral blood mononuclear cells (PBMCs), which were assessed using flow cytometry. We demonstrated that DE genes in our study are correlated with changes in PBMC composition. We gathered DE genes from 128 other publically available PBMC-based vaccine studies and identified that an average of 57% correlated with specific cell subset levels in our study (permutation used to control false discovery), suggesting that the associations we have identified are likely general features of PBMC-based transcriptomics. Second, we hypothesized that more robust models of vaccine response could be generated by accounting for the interplay between PBMC composition, gene expression, and gene regulation. We employed machine learning to generate predictive models of B-cell ELISPOT response outcomes and hemagglutination inhibition (HAI) antibody titers. The top HAI and B-cell ELISPOT model achieved an area under the receiver operating curve (AUC) of 0.64 and 0.79, respectively, with linear model coefficients of determination of 0.08 and 0.28. For the B-cell ELISPOT outcomes, CpG methylation had the greatest predictive ability, highlighting potentially novel regulatory features important for immune response. B-cell ELISOT models using only PBMC composition had lower performance (AUC = 0.67), but highlighted well-known mechanisms. Our analysis demonstrated that each of the three data sets (cell composition, mRNA-Seq, and DNA methylation) may provide distinct information for the prediction of humoral immune response outcomes. We believe that these findings are important for the interpretation of current omics-based studies and set the stage for a more thorough understanding of interindividual immune responses to influenza vaccination. PMID:28484452

Tumor-adjacent tissue co-expression profile analysis reveals pro-oncogenic ribosomal gene signature for prognosis of resectable hepatocellular carcinoma.

PubMed

Grinchuk, Oleg V; Yenamandra, Surya P; Iyer, Ramakrishnan; Singh, Malay; Lee, Hwee Kuan; Lim, Kiat Hon; Chow, Pierce Kah-Hoe; Kuznetsov, Vladamir A

2018-01-01

Currently, molecular markers are not used when determining the prognosis and treatment strategy for patients with hepatocellular carcinoma (HCC). In the present study, we proposed that the identification of common pro-oncogenic pathways in primary tumors (PT) and adjacent non-malignant tissues (AT) typically used to predict HCC patient risks may result in HCC biomarker discovery. We examined the genome-wide mRNA expression profiles of paired PT and AT samples from 321 HCC patients. The workflow integrated differentially expressed gene selection, gene ontology enrichment, computational classification, survival predictions, image analysis and experimental validation methods. We developed a 24-ribosomal gene-based HCC classifier (RGC), which is prognostically significant in both PT and AT. The RGC gene overexpression in PT was associated with a poor prognosis in the training (hazard ratio = 8.2, P = 9.4 × 10 -6 ) and cross-cohort validation (hazard ratio = 2.63, P = 0.004) datasets. The multivariate survival analysis demonstrated the significant and independent prognostic value of the RGC. The RGC displayed a significant prognostic value in AT of the training (hazard ratio = 5.0, P = 0.03) and cross-validation (hazard ratio = 1.9, P = 0.03) HCC groups, confirming the accuracy and robustness of the RGC. Our experimental and bioinformatics analyses suggested a key role for c-MYC in the pro-oncogenic pattern of ribosomal biogenesis co-regulation in PT and AT. Microarray, quantitative RT-PCR and quantitative immunohistochemical studies of the PT showed that DKK1 in PT is the perspective biomarker for poor HCC outcomes. The common co-transcriptional pattern of ribosome biogenesis genes in PT and AT from HCC patients suggests a new scalable prognostic system, as supported by the model of tumor-like metabolic redirection/assimilation in non-malignant AT. The RGC, comprising 24 ribosomal genes, is introduced as a robust and reproducible prognostic model for stratifying HCC patient risks. The adjacent non-malignant liver tissue alone, or in combination with HCC tissue biopsy, could be an important target for developing predictive and monitoring strategies, as well as evidence-based therapeutic interventions, that aim to reduce the risk of post-surgery relapse in HCC patients. © 2017 The Authors. Published by FEBS Press and John Wiley & Sons Ltd.