Genetic and Genomic Analysis of a Fat Mass Trait with Complex Inheritance Reveals Marked Sex Specificity
Open Access
- 3 February 2006
- journal article
- research article
- Published by Public Library of Science (PLoS) in PLoS Genetics
- Vol. 2 (2) , e15
- https://doi.org/10.1371/journal.pgen.0020015
Abstract
The integration of expression profiling with linkage analysis has increasingly been used to identify genes underlying complex phenotypes. The effects of gender on the regulation of many physiological traits are well documented; however, “genetical genomic” analyses have not yet addressed the degree to which their conclusions are affected by sex. We constructed and densely genotyped a large F2 intercross derived from the inbred mouse strains C57BL/6J and C3H/HeJ on an apolipoprotein E null (ApoE−/−) background. This BXH.ApoE−/− population recapitulates several “metabolic syndrome” phenotypes. The cross consists of 334 animals of both sexes, allowing us to specifically test for the dependence of linkage on sex. We detected several thousand liver gene expression quantitative trait loci, a significant proportion of which are sex-biased. We used these analyses to dissect the genetics of gonadal fat mass, a complex trait with sex-specific regulation. We present evidence for a remarkably high degree of sex-dependence on both the cis and trans regulation of gene expression. We demonstrate how these analyses can be applied to the study of the genetics underlying gonadal fat mass, a complex trait showing significantly female-biased heritability. These data have implications on the potential effects of sex on the genetic regulation of other complex traits. Although their genomes are nearly identical, the males and females of a species exhibit striking differences in many traits, including complex traits such as obesity. This study combines genetic and genomic tools to identify in parallel quantitative trait loci (QTLs) for a measure of gonadal fat mass and for expression of transcripts in the liver. The results are used to explore the relationship between genetic variation, sexual differentiation, and obesity in the mouse model. Using over 300 intercross progeny of two inbred mouse strains, five loci in the genome were found to be highly correlated with abdominal fat mass. Four of the five loci exhibited opposite effects on obesity in the two sexes, a phenomenon known as sexual antagonism. To identify candidate genes that may be involved in obesity through their expression in the liver, global gene expression analysis was employed using microarrays. Many of these expression QTLs also show sex-specific effects on transcription. A hotspot for trans-acting QTLs regulating the expression of transcripts whose abundance is correlated with gonadal fat mass was identified on Chromosome 19. This region of the genome colocalizes with a clinical QTL for gonadal fat mass, suggesting that it harbors a good candidate gene for obesity.Keywords
This publication has 41 references indexed in Scilit:
- Genetic Architecture of Transcript-Level Variation in Differentiating Xylem of a Eucalyptus HybridGenetics, 2005
- Highly multiplexed molecular inversion probe genotyping: Over 10,000 targeted SNPs genotyped in a single tube assayGenome Research, 2005
- Evidence for Sex-Specific Risk Alleles in Autism Spectrum DisorderAmerican Journal of Human Genetics, 2004
- Genetic Inheritance of Gene Expression in Human Cell LinesAmerican Journal of Human Genetics, 2004
- The Collaborative Cross, a community resource for the genetic analysis of complex traitsNature Genetics, 2004
- Genetic analysis of genome-wide variation in human gene expressionNature, 2004
- Influence of sex and diet on quantitative trait loci for HDL cholesterol levels in an SM/J by NZB/BlNJ intercross populationJournal of Lipid Research, 2004
- Genetic Factors in Cardiovascular Disease: 10 QuestionsTrends in Cardiovascular Medicine, 2003
- Trans-acting regulatory variation in Saccharomyces cerevisiae and the role of transcription factorsNature Genetics, 2003
- Genetic dissection of complex traits: guidelines for interpreting and reporting linkage resultsNature Genetics, 1995