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1.  Decreased Obesity and Atherosclerosis in Human Paraoxonase 3 Transgenic Mice 
Circulation research  2007;100(8):1200-1207.
Paraoxonase 3 (PON3) is a member of the PON family, which includes PON1, PON2, and PON3. Recently, PON3 was shown to prevent the oxidation of low-density lipoprotein in vitro. To test the role of PON3 in atherosclerosis and related traits, 2 independent lines of human PON3 transgenic (Tg) mice on the C57BL/6J (B6) background were constructed. Human PON3 mRNA was detected in various tissues, including liver, lung, kidney, brain, adipose, and aorta, of both lines of Tg mice. The human PON3 mRNA levels in the livers of PON3 Tg mice were 4- to 7-fold higher as compared with the endogenous mouse Pon3 mRNA levels. Human PON3 protein and activity were detected in the livers of Tg mice as well. No significant differences in plasma total, high-density lipoprotein, and very-low-density lipoprotein/low-density lipoprotein cholesterol and triglyceride and glucose levels were observed between the PON3 Tg and non-Tg mice. Interestingly, atherosclerotic lesion areas were significantly smaller in both lines of male PON3 Tg mice as compared with the male non-Tg littermates on B6 background fed an atherogenic diet. When bred onto the low-density lipoprotein receptor knockout mouse background, the male PON3 Tg mice also exhibited decreased atherosclerotic lesion areas and decreased expression of monocyte chemoattractant protein-1 in the aorta as compared with the male non-Tg littermates. In addition, decreased adiposity and lower circulating leptin levels were observed in both lines of male PON3 Tg mice as compared with the male non-Tg mice. In an F2 cross, adipose Pon3 mRNA levels inversely correlated with adiposity and related traits. Our study demonstrates that elevated PON3 expression significantly decreases atherosclerotic lesion formation and adiposity in male mice. PON3 may play an important role in protection against obesity and atherosclerosis.
doi:10.1161/01.RES.0000264499.48737.69
PMCID: PMC3740095  PMID: 17379834
atherosclerosis; obesity; genetics
2.  Origins of the E. coli Strain Causing an Outbreak of Hemolytic–Uremic Syndrome in Germany 
The New England journal of medicine  2011;365(8):709-717.
BACKGROUND
A large outbreak of diarrhea and the hemolytic–uremic syndrome caused by an unusual serotype of Shiga-toxin–producing Escherichia coli (O104:H4) began in Germany in May 2011. As of July 22, a large number of cases of diarrhea caused by Shiga-toxin–producing E. coli have been reported — 3167 without the hemolytic–uremic syndrome (16 deaths) and 908 with the hemolytic–uremic syndrome (34 deaths) — indicating that this strain is notably more virulent than most of the Shiga-toxin–producing E. coli strains. Preliminary genetic characterization of the outbreak strain suggested that, unlike most of these strains, it should be classified within the enteroaggregative pathotype of E. coli.
METHODS
We used third-generation, single-molecule, real-time DNA sequencing to determine the complete genome sequence of the German outbreak strain, as well as the genome sequences of seven diarrhea-associated enteroaggregative E. coli serotype O104:H4 strains from Africa and four enteroaggregative E. coli reference strains belonging to other serotypes. Genomewide comparisons were performed with the use of these enteroaggregative E. coli genomes, as well as those of 40 previously sequenced E. coli isolates.
RESULTS
The enteroaggregative E. coli O104:H4 strains are closely related and form a distinct clade among E. coli and enteroaggregative E. coli strains. However, the genome of the German outbreak strain can be distinguished from those of other O104:H4 strains because it contains a prophage encoding Shiga toxin 2 and a distinct set of additional virulence and antibiotic-resistance factors.
CONCLUSIONS
Our findings suggest that horizontal genetic exchange allowed for the emergence of the highly virulent Shiga-toxin–producing enteroaggregative E. coli O104:H4 strain that caused the German outbreak. More broadly, these findings highlight the way in which the plasticity of bacterial genomes facilitates the emergence of new pathogens.
doi:10.1056/NEJMoa1106920
PMCID: PMC3168948  PMID: 21793740
3.  Copy number variation influences gene expression and metabolic traits in mice 
Human Molecular Genetics  2009;18(21):4118-4129.
Copy number variants (CNVs) are genomic segments which are duplicated or deleted among different individuals. CNVs have been implicated in both Mendelian and complex traits, including immune and behavioral disorders, but the study of the mechanisms by which CNVs influence gene expression and clinical phenotypes in humans is complicated by the limited access to tissues and by population heterogeneity. We now report studies of the effect of 19 CNVs on gene expression and metabolic traits in a mouse intercross between strains C57BL/6J and C3H/HeJ. We found that 83% of genes predicted to occur within CNVs were differentially expressed. The expression of most CNV genes was correlated with copy number, but we also observed evidence that gene expression was altered in genes flanking CNVs, suggesting that CNVs may contain regulatory elements for these genes. Several CNVs mapped to hotspots, genomic regions influencing expression of tens or hundreds of genes. Several metabolic traits including cholesterol, triglycerides, glucose and body weight mapped to three CNVs in the genome, in mouse chromosomes 1, 4 and 17. Predicted CNV genes, such as Itlna, Defcr-1, Trim12 and Trim34 were highly correlated with these traits. Our results suggest that CNVs have a significant impact on gene expression and that CNVs may be playing a role in the mechanisms underlying metabolic traits in mice.
doi:10.1093/hmg/ddp360
PMCID: PMC2758141  PMID: 19648292
4.  Identification and validation of genes affecting aortic lesions in mice 
The Journal of Clinical Investigation  2010;120(7):2414-2422.
Atherosclerosis represents the most significant risk factor for coronary artery disease (CAD), the leading cause of death in developed countries. To better understand the pathogenesis of atherosclerosis, we applied a likeli­hood-based model selection method to infer gene-disease causality relationships for the aortic lesion trait in a segregating mouse population demonstrating a spectrum of susceptibility to developing atherosclerotic lesions. We identified 292 genes that tested causal for aortic lesions from liver and adipose tissues of these mice, and we experimentally validated one of these candidate causal genes, complement component 3a receptor 1 (C3ar1), using a knockout mouse model. We also found that genes identified by this method overlapped with genes progressively regulated in the aortic arches of 2 mouse models of atherosclerosis during atherosclerotic lesion development. By comparing our gene set with findings from public human genome-wide association studies (GWAS) of CAD and related traits, we found that 5 genes identified by our study overlapped with published studies in humans in which they were identified as risk factors for multiple atherosclerosis-related pathologies, including myocardial infarction, serum uric acid levels, mean platelet volume, aortic root size, and heart failure. Candidate causal genes were also found to be enriched with CAD risk polymorphisms identified by the Wellcome Trust Case Control Consortium (WTCCC). Our findings therefore validate the ability of causality testing procedures to provide insights into the mechanisms underlying atherosclerosis development.
doi:10.1172/JCI42742
PMCID: PMC2898611  PMID: 20577049
5.  Variations in DNA elucidate molecular networks that cause disease 
Nature  2008;452(7186):429-435.
Identifying variations in DNA that increase susceptibility to disease is one of the primary aims of genetic studies using a forward genetics approach. However, identification of disease-susceptibility genes by means of such studies provides limited functional information on how genes lead to disease. In fact, in most cases there is an absence of functional information altogether, preventing a definitive identification of the susceptibility gene or genes. Here we develop an alternative to the classic forward genetics approach for dissecting complex disease traits where, instead of identifying susceptibility genes directly affected by variations in DNA, we identify gene networks that are perturbed by susceptibility loci and that in turn lead to disease. Application of this method to liver and adipose gene expression data generated from a segregating mouse population results in the identification of a macrophage-enriched network supported as having a causal relationship with disease traits associated with metabolic syndrome. Three genes in this network, lipoprotein lipase (Lpl), lactamase β (Lactb) and protein phosphatase 1-like (Ppm1l), are validated as previously unknown obesity genes, strengthening the association between this network and metabolic disease traits. Our analysis provides direct experimental support that complex traits such as obesity are emergent properties of molecular networks that are modulated by complex genetic loci and environmental factors.
doi:10.1038/nature06757
PMCID: PMC2841398  PMID: 18344982
6.  Validation of Candidate Causal Genes for Abdominal Obesity Which Affect Shared Metabolic Pathways and Networks 
Nature genetics  2009;41(4):415-423.
A major task in dissecting the genetics of complex traits is to identify causal genes for disease phenotypes. We previously developed a method to infer causal relationships among genes through the integration of DNA variation, gene transcription, and phenotypic information. Here we validated our method through the characterization of transgenic and knockout mouse models of candidate genes that were predicted to be causal for abdominal obesity. Perturbation of eight out of the nine genes, with Gas7, Me1 and Gpx3 being novel, resulted in significant changes in obesity related traits. Liver expression signatures revealed alterations in common metabolic pathways and networks contributing to abdominal obesity and overlapped with a macrophage-enriched metabolic network module that is highly associated with metabolic traits in mice and humans. Integration of gene expression in the design and analysis of traditional F2 intercross studies allows high confidence prediction of causal genes and identification of involved pathways and networks.
doi:10.1038/ng.325
PMCID: PMC2837947  PMID: 19270708
7.  Disruption of the Aortic Elastic Lamina and Medial Calcification Share Genetic Determinants in Mice 
Background
Disruption of the elastic lamina, as an early indicator of aneurysm formation, and vascular calcification frequently occur together in atherosclerotic lesions of humans.
Methods and Results
We now report evidence of shared genetic basis for disruption of the elastic lamina (medial disruption) and medial calcification in an F2 mouse intercross between C57BL/6J and C3H/HeJ on a hyperlipidemic apolipoprotein E (ApoE−/−) null background. We identified 3 quantitative trait loci (QTLs) on chromosomes 6, 13, and 18, which are common to both traits, and 2 additional QTLs for medial calcification on chromosomes 3 and 7. Medial disruption, including severe disruptions leading to aneurysm formation, and medial calcification were highly correlated and occurred concomitantly in the cross. The chromosome 18 locus showed a striking male sex-specificity for both traits. To identify candidate genes, we integrated data from microarray analysis, genetic segregation, and clinical traits. The chromosome 7 locus contains the Abcc6 gene, known to mediate myocardial calcification. Using transgenic complementation, we show that Abcc6 also contributes to aortic medial calcification.
Conclusions
Our data indicate that calcification, though possibly contributory, does not always lead to medial disruption and that in addition to aneurysm formation, medial disruption may be the precursor to calcification.
doi:10.1161/CIRCGENETICS.109.860270
PMCID: PMC2836127  PMID: 20031637
aneurysm vascular calcification; Abcc6; Alox5; genetics; gene expression
8.  Genetic Regulation of Atherosclerotic Plaque Size and Morphology in the Innominate Artery of Hyperlipidemic Mice 
Objective
We sought to determine the genetic factors contributing to atherosclerotic plaque size and cellular composition in the innominate artery, a murine model of advanced atherosclerosis.
Methods and Results
We examined genetic contributions to innominate atherosclerotic plaque size and cellular composition in an intercross between C57BL/6J.Apoe-/-, a strain susceptible to aortic lesions, and C3H/HeJ.Apoe-/-, a strain resistant to aortic lesions. Surprisingly, total innominate lesion size was similar in the two strains. Genetic analyses identified one novel locus on Chromosome 2 for innominate artery lesion size, a significant locus for fibrous cap thickness on Chromosome 15, and several suggestive loci for cellular composition, all distinct from loci influencing aortic lesions. The Chromosome 2 locus contains a candidate, CD44. We show that CD44 is expressed in the innominate artery and differs strikingly in expression between the parental strains.
Conclusion
Multiple aspects of innominate lesion composition are genetically determined, but in a manner largely independent of the genetic contributions to aortic lesions.
doi:10.1161/ATVBAHA.108.176685
PMCID: PMC2704985  PMID: 19122174
Innominate artery; QTL; Atherosclerosis; Plaque stability
9.  Concept, Design and Implementation of a Cardiovascular Gene-Centric 50 K SNP Array for Large-Scale Genomic Association Studies 
PLoS ONE  2008;3(10):e3583.
A wealth of genetic associations for cardiovascular and metabolic phenotypes in humans has been accumulating over the last decade, in particular a large number of loci derived from recent genome wide association studies (GWAS). True complex disease-associated loci often exert modest effects, so their delineation currently requires integration of diverse phenotypic data from large studies to ensure robust meta-analyses. We have designed a gene-centric 50 K single nucleotide polymorphism (SNP) array to assess potentially relevant loci across a range of cardiovascular, metabolic and inflammatory syndromes. The array utilizes a “cosmopolitan” tagging approach to capture the genetic diversity across ∼2,000 loci in populations represented in the HapMap and SeattleSNPs projects. The array content is informed by GWAS of vascular and inflammatory disease, expression quantitative trait loci implicated in atherosclerosis, pathway based approaches and comprehensive literature searching. The custom flexibility of the array platform facilitated interrogation of loci at differing stringencies, according to a gene prioritization strategy that allows saturation of high priority loci with a greater density of markers than the existing GWAS tools, particularly in African HapMap samples. We also demonstrate that the IBC array can be used to complement GWAS, increasing coverage in high priority CVD-related loci across all major HapMap populations. DNA from over 200,000 extensively phenotyped individuals will be genotyped with this array with a significant portion of the generated data being released into the academic domain facilitating in silico replication attempts, analyses of rare variants and cross-cohort meta-analyses in diverse populations. These datasets will also facilitate more robust secondary analyses, such as explorations with alternative genetic models, epistasis and gene-environment interactions.
doi:10.1371/journal.pone.0003583
PMCID: PMC2571995  PMID: 18974833
10.  Mapping the Genetic Architecture of Gene Expression in Human Liver 
PLoS Biology  2008;6(5):e107.
Genetic variants that are associated with common human diseases do not lead directly to disease, but instead act on intermediate, molecular phenotypes that in turn induce changes in higher-order disease traits. Therefore, identifying the molecular phenotypes that vary in response to changes in DNA and that also associate with changes in disease traits has the potential to provide the functional information required to not only identify and validate the susceptibility genes that are directly affected by changes in DNA, but also to understand the molecular networks in which such genes operate and how changes in these networks lead to changes in disease traits. Toward that end, we profiled more than 39,000 transcripts and we genotyped 782,476 unique single nucleotide polymorphisms (SNPs) in more than 400 human liver samples to characterize the genetic architecture of gene expression in the human liver, a metabolically active tissue that is important in a number of common human diseases, including obesity, diabetes, and atherosclerosis. This genome-wide association study of gene expression resulted in the detection of more than 6,000 associations between SNP genotypes and liver gene expression traits, where many of the corresponding genes identified have already been implicated in a number of human diseases. The utility of these data for elucidating the causes of common human diseases is demonstrated by integrating them with genotypic and expression data from other human and mouse populations. This provides much-needed functional support for the candidate susceptibility genes being identified at a growing number of genetic loci that have been identified as key drivers of disease from genome-wide association studies of disease. By using an integrative genomics approach, we highlight how the gene RPS26 and not ERBB3 is supported by our data as the most likely susceptibility gene for a novel type 1 diabetes locus recently identified in a large-scale, genome-wide association study. We also identify SORT1 and CELSR2 as candidate susceptibility genes for a locus recently associated with coronary artery disease and plasma low-density lipoprotein cholesterol levels in the process.
Author Summary
Genome-wide association studies seek to identify regions of the genome in which changes in DNA in a given population are correlated with disease, drug response, or other phenotypes of interest. However, changes in DNA that associate with traits like common human diseases do not lead directly to disease, but instead act on intermediate, molecular phenotypes that in turn induce changes in the higher-order disease traits. Therefore, identifying molecular phenotypes that vary in response to changes in DNA that also associate with changes in disease traits can provide the functional information necessary to not only identify and validate the susceptibility genes directly affected by changes in DNA, but to understand as well the molecular networks in which such genes operate and how changes in these networks lead to changes in disease traits. To enable this type of approach we profiled the expression levels of 39,280 transcripts and genotyped 782,476 SNPs in 427 human liver samples, identifying thousands of DNA variants that strongly associated with liver gene expression. These relationships were then leveraged by integrating them with genotypic and expression data from other human and mouse populations, leading to the direct identification of candidate susceptibility genes corresponding to genetic loci identified as key drivers of disease. Our analysis is able to provide much needed functional support for these candidate susceptibility genes.
Identifying changes in DNA that associate with changes in gene expression in human tissues elucidates the genetic architecture of gene expression in human populations and enables the direct identification of functionally supported candidate susceptibility genes in genomic regions associated with disease.
doi:10.1371/journal.pbio.0060107
PMCID: PMC2365981  PMID: 18462017
11.  Dosage compensation is less effective in birds than in mammals 
Journal of Biology  2007;6(1):2.
Background
In animals with heteromorphic sex chromosomes, dosage compensation of sex-chromosome genes is thought to be critical for species survival. Diverse molecular mechanisms have evolved to effectively balance the expressed dose of X-linked genes between XX and XY animals, and to balance expression of X and autosomal genes. Dosage compensation is not understood in birds, in which females (ZW) and males (ZZ) differ in the number of Z chromosomes.
Results
Using microarray analysis, we compared the male:female ratio of expression of sets of Z-linked and autosomal genes in two bird species, zebra finch and chicken, and in two mammalian species, mouse and human. Male:female ratios of expression were significantly higher for Z genes than for autosomal genes in several finch and chicken tissues. In contrast, in mouse and human the male:female ratio of expression of X-linked genes is quite similar to that of autosomal genes, indicating effective dosage compensation even in humans, in which a significant percentage of genes escape X-inactivation.
Conclusion
Birds represent an unprecedented case in which genes on one sex chromosome are expressed on average at constitutively higher levels in one sex compared with the other. Sex-chromosome dosage compensation is surprisingly ineffective in birds, suggesting that some genomes can do without effective sex-specific sex-chromosome dosage compensation mechanisms.
doi:10.1186/jbiol53
PMCID: PMC2373894  PMID: 17352797
12.  Cis-regulatory variations: A study of SNPs around genes showing cis-linkage in segregating mouse populations 
BMC Genomics  2006;7:235.
Background
Changes in gene expression are known to be responsible for phenotypic variation and susceptibility to diseases. Identification and annotation of the genomic sequence variants that cause gene expression changes is therefore likely to lead to a better understanding of the cause of disease at the molecular level. In this study we investigate the pattern of single nucleotide polymorphisms (SNPs) in genes for which the mRNA levels show cis-genetic linkage (gene expression quantitative trait loci mapping in cis, or cis-eQTLs) in segregating mouse populations. Such genes are expected to have polymorphisms near their physical location (cis-variations) that affect their mRNA levels by altering one or more of the cis-regulatory elements. This led us to characterize the SNPs in promoter (5 Kb upstream) and non-coding gene regions (introns and 5 Kb downstream) (cis-SNPs) and the effects they may have on putative transcription factor binding sites.
Results
We demonstrate that the cis-eQTL genes (CEGs) have a significantly higher frequency of cis-SNPs compared to non-CEGs (when both sets are taken from the non-IBD regions, i.e. regions not identical by descent). Most CEGs having cis-SNPs do not contain these SNPs in the phylogenetically conserved regions. In those CEGs that contain cis-SNPs in the phylogenetically conserved regions, enrichment of cis-SNPs occurs both within and outside of the conserved sequences. A higher fraction of CEGs are also seen to harbor cis-SNP that affect predicted transcription factor binding sites, a likely consequence of the higher cis-SNPs density in these genes.
Conclusion
This present study provides the first genome-wide investigation of the putative cis-regulatory variations in a large set of genes whose levels of expression give rise to cis-linkage in segregating mammalian populations. Our results provide insights into the challenges that exist in identifying polymorphisms regulating gene expression using bioinformatic sequence analysis approaches. The data provided herein should benefit future investigations in this area.
doi:10.1186/1471-2164-7-235
PMCID: PMC1618400  PMID: 16978413
13.  Integrating Genetic and Network Analysis to Characterize Genes Related to Mouse Weight 
PLoS Genetics  2006;2(8):e130.
Systems biology approaches that are based on the genetics of gene expression have been fruitful in identifying genetic regulatory loci related to complex traits. We use microarray and genetic marker data from an F2 mouse intercross to examine the large-scale organization of the gene co-expression network in liver, and annotate several gene modules in terms of 22 physiological traits. We identify chromosomal loci (referred to as module quantitative trait loci, mQTL) that perturb the modules and describe a novel approach that integrates network properties with genetic marker information to model gene/trait relationships. Specifically, using the mQTL and the intramodular connectivity of a body weight–related module, we describe which factors determine the relationship between gene expression profiles and weight. Our approach results in the identification of genetic targets that influence gene modules (pathways) that are related to the clinical phenotypes of interest.
Synopsis
Obesity is a major pub lic health concern in many developed countries. While some people appear to stay lean no matter what or how much they eat, others appear to be genetically predisposed to obesity. The genetic similarity between mouse and human makes the mouse a promising mammalian model system to study obesity. Advantages of mouse models include the ability to control diet/environment and easy access to relevant tissues for gene expression studies. Mouse cross studies have implicated dozens of chromosomal regions that contain weight-predisposing genes, and gene expression studies have yielded hundreds of body weight–related genes. In this study, the authors use a gene network–based approach for integrating clinical traits, genetic marker data, and gene expression data. Instead of focusing on individual genes, the authors provide a systems-level view of a module of genes related to body weight. The resulting model allows them to characterize weight-related genes utilizing network concepts (intramodular connectivity) and genetic concepts (module quantitative trait locus). This integrative genomics approach provides new insights into the relationship between gene expression and body weight.
doi:10.1371/journal.pgen.0020130
PMCID: PMC1550283  PMID: 16934000
14.  Integrating Genetic and Network Analysis to Characterize Genes Related to Mouse Weight 
PLoS Genetics  2006;2(8):e130.
Systems biology approaches that are based on the genetics of gene expression have been fruitful in identifying genetic regulatory loci related to complex traits. We use microarray and genetic marker data from an F2 mouse intercross to examine the large-scale organization of the gene co-expression network in liver, and annotate several gene modules in terms of 22 physiological traits. We identify chromosomal loci (referred to as module quantitative trait loci, mQTL) that perturb the modules and describe a novel approach that integrates network properties with genetic marker information to model gene/trait relationships. Specifically, using the mQTL and the intramodular connectivity of a body weight–related module, we describe which factors determine the relationship between gene expression profiles and weight. Our approach results in the identification of genetic targets that influence gene modules (pathways) that are related to the clinical phenotypes of interest.
Synopsis
Obesity is a major pub lic health concern in many developed countries. While some people appear to stay lean no matter what or how much they eat, others appear to be genetically predisposed to obesity. The genetic similarity between mouse and human makes the mouse a promising mammalian model system to study obesity. Advantages of mouse models include the ability to control diet/environment and easy access to relevant tissues for gene expression studies. Mouse cross studies have implicated dozens of chromosomal regions that contain weight-predisposing genes, and gene expression studies have yielded hundreds of body weight–related genes. In this study, the authors use a gene network–based approach for integrating clinical traits, genetic marker data, and gene expression data. Instead of focusing on individual genes, the authors provide a systems-level view of a module of genes related to body weight. The resulting model allows them to characterize weight-related genes utilizing network concepts (intramodular connectivity) and genetic concepts (module quantitative trait locus). This integrative genomics approach provides new insights into the relationship between gene expression and body weight.
doi:10.1371/journal.pgen.0020130
PMCID: PMC1550283  PMID: 16934000
15.  Genetic and Genomic Analysis of a Fat Mass Trait with Complex Inheritance Reveals Marked Sex Specificity 
PLoS Genetics  2006;2(2):e15.
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.
Synopsis
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.
doi:10.1371/journal.pgen.0020015
PMCID: PMC1359071  PMID: 16462940
16.  Genetic and Genomic Analysis of a Fat Mass Trait with Complex Inheritance Reveals Marked Sex Specificity 
PLoS Genetics  2006;2(2):e15.
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.
Synopsis
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.
doi:10.1371/journal.pgen.0020015
PMCID: PMC1359071  PMID: 16462940

Results 1-16 (16)