Elucidating the role of gonadal hormones in sexually dimorphic gene coexpression networks.

We previously used high-density expression arrays to interrogate a genetic cross between strains C3H/HeJ and C57BL/6J and observed thousands of differences in gene expression between sexes. We now report analyses of the molecular basis of these sex differences and of the effects of sex on gene expression networks. We analyzed liver gene expression of hormone-treated gonadectomized mice as well as XX male and XY female mice. Differences in gene expression resulted in large part from acute effects of gonadal hormones acting in adulthood, and the effects of sex chromosomes, apart from hormones, were modest. We also determined whether there are sex differences in the organization of gene expression networks in adipose, liver, skeletal muscle, and brain tissue. Although coexpression networks of highly correlated genes were largely conserved between sexes, some exhibited striking sex dependence. We observed strong body fat and lipid correlations with sex-specific modules in adipose and liver as well as a sexually dimorphic network enriched for genes affected by gonadal hormones. Finally, our analyses identified chromosomal loci regulating sexually dimorphic networks. This study indicates that gonadal hormones play a strong role in sex differences in gene expression. In addition, it results in the identification of sex-specific gene coexpression networks related to genetic and metabolic traits.

[1]  S. Horvath,et al.  Conservation and evolution of gene coexpression networks in human and chimpanzee brains , 2006, Proceedings of the National Academy of Sciences.

[2]  A. Arnold,et al.  Sex chromosomes and brain gender , 2004, Nature Reviews Neuroscience.

[3]  A. Barabasi,et al.  Hierarchical Organization of Modularity in Metabolic Networks , 2002, Science.

[4]  Andy M. Yip,et al.  Gene network interconnectedness and the generalized topological overlap measure , 2007, BMC Bioinformatics.

[5]  B. Mittendorfer.  Sexual dimorphism in human lipid metabolism. , 2005, The Journal of nutrition.

[6]  R. Albert,et al.  The large-scale organization of metabolic networks , 2000, Nature.

[7]  J. Castle,et al.  An integrative genomics approach to infer causal associations between gene expression and disease , 2005, Nature Genetics.

[8]  E. Blaak,et al.  Gender differences in fat metabolism , 2001, Current opinion in clinical nutrition and metabolic care.

[9]  A. Barabasi,et al.  Network biology: understanding the cell's functional organization , 2004, Nature Reviews Genetics.

[10]  D. Federman,et al.  The biology of human sex differences. , 2006, The New England journal of medicine.

[11]  R. Karas,et al.  Molecular and Cellular Basis of Cardiovascular Gender Differences , 2005, Science.

[12]  J. Rinn,et al.  Sexual dimorphism in mammalian gene expression. , 2005, Trends in genetics : TIG.

[13]  R. Tibshirani,et al.  Significance analysis of microarrays applied to the ionizing radiation response , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[14]  M. Campbell,et al.  PANTHER: a library of protein families and subfamilies indexed by function. , 2003, Genome research.

[15]  Robin Lovell-Badge,et al.  A Model System for Study of Sex Chromosome Effects on Sexually Dimorphic Neural and Behavioral Traits , 2002, The Journal of Neuroscience.

[16]  R. Simerly.  Wired on hormones: endocrine regulation of hypothalamic development , 2005, Current Opinion in Neurobiology.

[17]  Douglas A. Hosack,et al.  Identifying biological themes within lists of genes with EASE , 2003, Genome Biology.

[18]  A. Arnold.  Concepts of Genetic and Hormonal Induction of Vertebrate Sexual Differentiation in the Twentieth Century, with Special Reference to the Brain , 2002 .

[19]  S. Horvath,et al.  Evidence for anti-Burkitt tumour globulins in Burkitt tumour patients and healthy individuals. , 1967, British Journal of Cancer.

[20]  Paul A Clemons,et al.  The Connectivity Map: Using Gene-Expression Signatures to Connect Small Molecules, Genes, and Disease , 2006, Science.

[21]  A. Lusis,et al.  Testosterone inhibits early atherogenesis by conversion to estradiol: Critical role of aromatase , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[22]  A. Arnold,et al.  Are XX and XY brain cells intrinsically different? , 2004, Trends in Endocrinology & Metabolism.

[23]  Karl H. Clodfelter,et al.  Role of STAT5a in regulation of sex-specific gene expression in female but not male mouse liver revealed by microarray analysis. , 2007, Physiological genomics.

[24]  John D. Storey.  A direct approach to false discovery rates , 2002 .

[25]  R. Pasquali.  Obesity and androgens: facts and perspectives. , 2006, Fertility and sterility.

[26]  John D. Storey,et al.  Statistical significance for genomewide studies , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[27]  J. Gustafsson,et al.  Sex and the Liver – A Journey Through Five Decades , 2006, Drug metabolism reviews.

[28]  Aiqing He,et al.  Identification of inflammatory gene modules based on variations of human endothelial cell responses to oxidized lipids , 2006, Proceedings of the National Academy of Sciences.

[29]  Hans Ellegren,et al.  The evolution of sex-biased genes and sex-biased gene expression , 2007, Nature Reviews Genetics.

[30]  D. Roff,et al.  The quantitative genetics of sexual dimorphism: assessing the importance of sex-linkage , 2006, Heredity.

[31]  Donald W. Pfaff,et al.  Hormones, brain, and behavior , 2009 .

[32]  Brad T. Sherman,et al.  DAVID: Database for Annotation, Visualization, and Integrated Discovery , 2003, Genome Biology.

[33]  Eric J Topol,et al.  The genetics of health , 2006, Nature Genetics.

[34]  Albert,et al.  Emergence of scaling in random networks , 1999, Science.

[35]  G. J. Mitchell,et al.  Principles and procedures of statistics: A biometrical approach , 1981 .

[36]  A. Lusis,et al.  Dissection of multigenic obesity traits in congenic mouse strains , 2003, Mammalian Genome.

[37]  S. Horvath,et al.  A General Framework for Weighted Gene Co-Expression Network Analysis , 2005, Statistical applications in genetics and molecular biology.

[38]  K. H. Albrecht,et al.  Supplemental Experimental Procedures cRNA Probe and Radioactive In Situ Hybridization , 2022 .

[39]  P. Björntorp,et al.  Fat cell metabolism in different regions in women. Effect of menstrual cycle, pregnancy, and lactation. , 1985, The Journal of clinical investigation.

[40]  Massimo Marchiori,et al.  Error and attacktolerance of complex network s , 2004 .

[41]  E. Schadt,et al.  Genetic and Genomic Analysis of a Fat Mass Trait with Complex Inheritance Reveals Marked Sex Specificity , 2006, PLoS genetics.

[42]  Markus Perola,et al.  Lessons from studying monogenic disease for common disease. , 2006, Human molecular genetics.

[43]  Zhenjun Hu,et al.  Visant: an Integrative Framework for Networks in Systems Biology , 2008 .

[44]  Aldons J. Lusis,et al.  A thematic review series: systems biology approaches to metabolic and cardiovascular disorders , 2006, Journal of Lipid Research.

[45]  S. Horvath,et al.  Weighted gene coexpression network analysis strategies applied to mouse weight , 2007, Mammalian Genome.

[46]  Christina Kendziorski,et al.  Combined Expression Trait Correlations and Expression Quantitative Trait Locus Mapping , 2006, PLoS genetics.

[47]  E. Vallender,et al.  How mammalian sex chromosomes acquired their peculiar gene content. , 2004, BioEssays : news and reviews in molecular, cellular and developmental biology.

[48]  M. Abney,et al.  The sex-specific genetic architecture of quantitative traits in humans , 2006, Nature Genetics.

[49]  A. Arnold,et al.  Tissue-specific expression and regulation of sexually dimorphic genes in mice. , 2006, Genome research.