Dataset Information

Network analysis of functional genomics data: application to avian sex-biased gene expression.

ABSTRACT: Gene expression analysis is often used to investigate the molecular and functional underpinnings of a phenotype. However, differential expression of individual genes is limited in that it does not consider how the genes interact with each other in networks. To address this shortcoming we propose a number of network-based analyses that give additional functional insights into the studied process. These were applied to a dataset of sex-specific gene expression in the chicken gonad and brain at different developmental stages. We first constructed a global chicken interaction network. Combining the network with the expression data showed that most sex-biased genes tend to have lower network connectivity, that is, act within local network environments, although some interesting exceptions were found. Genes of the same sex bias were generally more strongly connected with each other than expected. We further studied the fates of duplicated sex-biased genes and found that there is a significant trend to keep the same pattern of sex bias after duplication. We also identified sex-biased modules in the network, which reveal pathways or complexes involved in sex-specific processes. Altogether, this work integrates evolutionary genomics with systems biology in a novel way, offering new insights into the modular nature of sex-biased genes.

SUBMITTER: Frings O

PROVIDER: S-EPMC3540752 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Network analysis of functional genomics data: application to avian sex-biased gene expression.

Frings Oliver O Mank Judith E JE Alexeyenko Andrey A Sonnhammer Erik L L EL

TheScientificWorldJournal 20121223

Gene expression analysis is often used to investigate the molecular and functional underpinnings of a phenotype. However, differential expression of individual genes is limited in that it does not consider how the genes interact with each other in networks. To address this shortcoming we propose a number of network-based analyses that give additional functional insights into the studied process. These were applied to a dataset of sex-specific gene expression in the chicken gonad and brain at dif ...[more]

PMID: 23319882

Similar Datasets

Project description:BACKGROUND:Functional genomics employs several experimental approaches to investigate gene functions. High-throughput techniques, such as loss-of-function screening and transcriptome profiling, allow to identify lists of genes potentially involved in biological processes of interest (so called hit list). Several computational methods exist to analyze and interpret such lists, the most widespread of which aim either at investigating of significantly enriched biological processes, or at extracting significantly represented subnetworks. RESULTS:Here we propose a novel network analysis method and corresponding computational software that employs the shortest path approach and centrality measure to discover members of molecular pathways leading to the studied phenotype, based on functional genomics screening data. The method works on integrated interactomes that consist of both directed and undirected networks - HIPPIE, SIGNOR, SignaLink, TFactS, KEGG, TransmiR, miRTarBase. The method finds nodes and short simple paths with significant high centrality in subnetworks induced by the hit genes and by so-called final implementers - the genes that are involved in molecular events responsible for final phenotypic realization of the biological processes of interest. We present the application of the method to the data from miRNA loss-of-function screen and transcriptome profiling of terminal human muscle differentiation process and to the gene loss-of-function screen exploring the genes that regulates human oxidative DNA damage recognition. The analysis highlighted the possible role of several known myogenesis regulatory miRNAs (miR-1, miR-125b, miR-216a) and their targets (AR, NR3C1, ARRB1, ITSN1, VAV3, TDGF1), as well as linked two major regulatory molecules of skeletal myogenesis, MYOD and SMAD3, to their previously known muscle-related targets (TGFB1, CDC42, CTCF) and also to a number of proteins such as C-KIT that have not been previously studied in the context of muscle differentiation. The analysis also showed the role of the interaction between H3 and SETDB1 proteins for oxidative DNA damage recognition. CONCLUSION:The current work provides a systematic methodology to discover members of molecular pathways in integrated networks using functional genomics screening data. It also offers a valuable instrument to explain the appearance of a set of genes, previously not associated with the process of interest, in the hit list of each particular functional genomics screening.

Project description:BACKGROUND:The fucoid brown algae (Heterokontophyta, Phaeophyceae) are increasingly the focus of ecological genetics, biodiversity, biogeography and speciation research. The molecular genetics underlying mating system variation, where repeated dioecious - hermaphrodite switches during evolution are recognized, and the molecular evolution of sex-related genes are key questions currently hampered by a lack of genomic information. We therefore undertook a comparative analysis of male and female reproductive tissue transcriptomes against a vegetative background during natural reproductive cycles in Fucus vesiculosus. RESULTS:Over 300 k reads were assembled and annotated against public protein databases including a brown alga. Compared with the vegetative tissue, photosynthetic and carbohydrate metabolism pathways were under-expressed, particularly in male tissue, while several pathways involved in genetic information processing and replication were over-expressed. Estimates of sex-biased gene (SBG) expression were higher for male (14% of annotated orthologues) than female tissue (9%) relative to the vegetative background. Mean expression levels and variance were also greater in male- than female-biased genes. Major female-biased genes were carbohydrate-modifying enzymes with likely roles in zygote cell wall biogenesis and/or modification. Male-biased genes reflected distinct sperm development and function, and orthologues for signal perception (a phototropin), transduction (several kinases), and putatively flagella-localized proteins (including candidate gamete-recognition proteins) were uniquely expressed in males. Overall, the results suggest constraint on female-biased genes (possible pleiotropy), and less constrained male-biased genes, mostly associated with sperm-specific functions. CONCLUSIONS:Our results support the growing contention that males possess a large array of genes regulating male fitness, broadly supporting findings in evolutionarily distant heterogametic animal models. This work identifies an annotated set of F. vesiculosus gene products that potentially regulate sexual reproduction and may contribute to prezygotic isolation, one essential step towards developing tools for a functional understanding of species isolation and differentiation.

Project description:The evolution of sex-specific phenotypes is an important dimension of diversification and local adaptation. The sex-dependent regulation of gene expression is considered a key genomic mechanism facilitating sex-dependent adaptation. In many species, genes with male-biased expression evolve faster in DNA sequence and expression level than genes with female-biased or sexually monomorphic expression. While positive selection may be responsible for rapid DNA sequence evolution, why expression of male-biased genes also evolves rapidly remains unclear. Beyond sex differences in selection, some aspects of the genetic architecture of gene expression could contribute to the rapid evolution of male-biased gene expression. First, male-biased genes might simply have greater standing genetic variance than female-biased genes. Second, male-biased genes could be less constrained by pleiotropy, either within or between sexes. Here, we evaluate these alternative explanations on an intraspecific scale using a series of quantitative genetic experiments conducted on natural variation in male and female gene expression in the fly Drosophila serrata Male-biased genes had significantly higher genetic variance than female-biased genes and were generally more narrowly expressed across tissues, suggesting lower within-individual pleiotropy. However, consistent with stronger constraints due to between-sex pleiotropy, their between-sex genetic correlations, rMF, were higher than for female-biased genes and more strongly negatively associated with sex bias. Using an extensive clinal dataset, we tested whether sex differences in gene expression divergence among populations have been shaped by pleiotropy. Here too, male-biased gene divergence was more strongly associated with between-sex pleiotropy than was female-biased gene divergence. Systematic differences in genetic variance and pleiotropy may be important factors influencing sex-specific adaptation arising through changes in gene expression.This article is part of the theme issue 'Linking local adaptation with the evolution of sex differences'.

Dataset Information

Network analysis of functional genomics data: application to avian sex-biased gene expression.

Publications

Network analysis of functional genomics data: application to avian sex-biased gene expression.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets