Genetic mapping of multiple metabolic traits identifies novel genes for adiposity, lipids and insulin secretory capacity in outbred rats
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ABSTRACT:
ORGANISM(S): Rattus norvegicus
PROVIDER: GSE196572 | GEO | 2022/03/31
REPOSITORIES: GEO
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Project description:RNA-Seq was used in an attempt to identify candidate genes regulating metabolic and physiological traits
2022-08-15 | GSE200453 | GEO
Project description:Despite the successes of human genome-wide association studies, the causal genes underlying most metabolic traits remain unclear. We used outbred heterogeneous stock (HS) rats, coupled with expression data and mediation analysis, to identify quantitative trait loci (QTLs) and candidate gene mediators for adiposity, glucose tolerance, serum lipids, and other metabolic traits. Physiological traits were measured in 1,519 male HS rats, with liver and adipose transcriptomes measured in >410 rats. Genotypes were imputed from low-coverage whole-genome sequencing. Linear mixed models were used to detect physiological and expression QTLs (pQTLs and eQTLs, respectively), using both single nucleotide polymorphism (SNP)- and haplotype-based models for pQTL mapping. Genes with cis-eQTLs that overlapped pQTLs were assessed as causal candidates through mediation analysis. We identified 14 SNP-based pQTLs and 19 haplotype-based pQTLs, of which 10 were in common. Using mediation, we identified the following genes as candidate mediators of pQTLs: Grk5 for fat pad weight and serum triglyceride pQTLs on Chr1, Krtcap3 for fat pad weight and serum triglyceride pQTLs on Chr6, Ilrun for a fat pad weight pQTL on Chr20, and Rfx6 for a whole pancreatic insulin content pQTL on Chr20. Furthermore, we verified Grk5 and Ktrcap3 using gene knockdown/out models, thereby shedding light on novel regulators of obesity.
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Project description:Genetic mapping of multiple metabolic traits identifies novel genes for adiposity, lipids and insulin secretory capacity in outbred rats
| PRJNA805516 | ENA
Project description:Genetic mapping of multiple metabolic traits identifies novel genes for adiposity, lipids and insulin secretory capacity in outbred rats II
| PRJNA824529 | ENA
Project description:OBJECTIVE:Obesity is a major risk factor for multiple diseases and is in part heritable, yet the majority of causative genetic variants that drive excessive adiposity remain unknown. Here, outbred heterogeneous stock (HS) rats were used in controlled environmental conditions to fine-map novel genetic modifiers of adiposity. METHODS:Body weight and visceral fat pad weights were measured in male HS rats that were also genotyped genome-wide. Quantitative trait loci (QTL) were identified by genome-wide association of imputed single-nucleotide polymorphism (SNP) genotypes using a linear mixed effect model that accounts for unequal relatedness between the HS rats. Candidate genes were assessed by protein modeling and mediation analysis of expression for coding and noncoding variants, respectively. RESULTS:HS rats exhibited large variation in adiposity traits, which were highly heritable and correlated with metabolic health. Fine-mapping of fat pad weight and body weight revealed three QTL and prioritized five candidate genes. Fat pad weight was associated with missense SNPs in Adcy3 and Prlhr and altered expression of Krtcap3 and Slc30a3, whereas Grid2 was identified as a candidate within the body weight locus. CONCLUSIONS:These data demonstrate the power of HS rats for identification of known and novel heritable mediators of obesity traits.
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Project description:Genetic mapping on fully sequenced individuals is transforming understanding of the relationship between molecular variation and variation in complex traits. Here we report a combined sequence and genetic mapping analysis in outbred rats that maps 355 quantitative trait loci for 122 phenotypes. We identify 35 causal genes involved in 31 phenotypes, implicating new genes in models of anxiety, heart disease and multiple sclerosis. The relationship between sequence and genetic variation is unexpectedly complex: at approximately 40% of quantitative trait loci, a single sequence variant cannot account for the phenotypic effect. Using comparable sequence and mapping data from mice, we show that the extent and spatial pattern of variation in inbred rats differ substantially from those of inbred mice and that the genetic variants in orthologous genes rarely contribute to the same phenotype in both species.
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Project description:Recent developments in high-density genotyping and statistical analysis methods that have enabled genome-wide association studies in humans can also be applied to outbred mouse populations. Increased recombination in outbred populations is expected to provide greater mapping resolution than traditional inbred line crosses, improving prospects for identifying the causal genes. We carried out genome-wide association mapping by using 288 mice from a commercially available outbred stock; NMRI mice were genotyped with a high-density single-nucleotide polymorphism array to map loci influencing high-density lipoprotein cholesterol, systolic blood pressure, triglyceride levels, glucose, and urinary albumin-to-creatinine ratios. We found significant associations (P < 10(-5)) with high-density lipoprotein cholesterol and identified Apoa2 and Scarb1, both of which have been previously reported, as candidate genes for these associations. Additional suggestive associations (P < 10(-3)) identified in this study were also concordant with published quantitative trait loci, suggesting that we are sampling from a limited pool of genetic diversity that has already been well characterized. These findings dampen our enthusiasm for currently available commercial outbred stocks as genetic mapping resources and highlight the need for new outbred populations with greater genetic diversity. Despite the lack of novel associations in the NMRI population, our analysis strategy illustrates the utility of methods that could be applied to genome-wide association studies in humans.
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Project description:Historically our ability to identify genetic variants underlying complex behavioral traits in mice has been limited by low mapping resolution of conventional mouse crosses. The newly developed Diversity Outbred (DO) population promises to deliver improved resolution that will circumvent costly fine-mapping studies. The DO is derived from the same founder strains as the Collaborative Cross (CC), including three wild-derived strains. Thus the DO provides more allelic diversity and greater potential for discovery compared to crosses involving standard mouse strains. We have characterized 283 male and female DO mice using open-field, light-dark box, tail-suspension and visual-cliff avoidance tests to generate 38 behavioral measures. We identified several quantitative trait loci (QTL) for these traits with support intervals ranging from 1 to 3 Mb in size. These intervals contain relatively few genes (ranging from 5 to 96). For a majority of QTL, using the founder allelic effects together with whole genome sequence data, we could further narrow the positional candidates. Several QTL replicate previously published loci. Novel loci were also identified for anxiety- and activity-related traits. Half of the QTLs are associated with wild-derived alleles, confirming the value to behavioral genetics of added genetic diversity in the DO. In the presence of wild-alleles we sometimes observe behaviors that are qualitatively different from the expected response. Our results demonstrate that high-precision mapping of behavioral traits can be achieved with moderate numbers of DO animals, representing a significant advance in our ability to leverage the mouse as a tool for behavioral genetics.
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Project description:ObjectivesPrevious studies indicate that, in addition to the blood glucose level, the lipid level in the blood may affect functions of pancreatic beta cells. In this study, we aimed to examine whether there was a relationship between the serum level of total cholesterol (TC) and the insulin secretory capacity in healthy subjects.Subjects and methodsIn participants of health examinations conducted from 2006 to 2010, we analyzed data from a total of 2,499 subjects (1,057 men and 1,442 women) after exclusion of individuals with dyslipidemia, thyroid dysfunction, diabetes, HbA1c≥6.5%, or fasting blood glucose≥126 mg/dL. Homeostasis model assessment for beta cell function (HOMA-beta) was utilized as a model representing the pancreatic beta cell function.ResultsAlthough the serum TC level had a positive correlation with HOMA-beta in a univariate correlation analysis, after adjustment by confounding factors in a multiple regression analysis, HOMA-beta had a negative correlation with TC. This was further confirmed in a multiple logistic regression analysis, showing that higher TC was an independent risk factor for decreased insulin secretory capacity (defined as HOMA-beta≤30%) together with higher age, lower BMI, lower TG, male sex and regular alcohol intake. After the participants were stratified by BMI into three groups, the effect of TC on HOMA-beta increased along with the increase in BMI, and it was highly significant in the highest tertile.ConclusionThis cross-sectional study indicated that increased serum TC level might be related to the decrease of insulin secretory capacity in aged healthy population and that reduction of TC is more necessary in obese subjects to prevent diabetes.
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Project description:The vertebrate cranium is a prime example of the high evolvability of complex traits. While evidence of genes and developmental pathways underlying craniofacial shape determination is accumulating, we are still far from understanding how such variation at the genetic level is translated into craniofacial shape variation. Here we used 3D geometric morphometrics to map genes involved in shape determination in a population of outbred mice (Carworth Farms White, or CFW). We defined shape traits via principal component analysis of 3D skull and mandible measurements. We mapped genetic loci associated with shape traits at ~80,000 candidate single nucleotide polymorphisms in ~700 male mice. We found that craniofacial shape and size are highly heritable, polygenic traits. Despite the polygenic nature of the traits, we identified 17 loci that explain variation in skull shape, and 8 loci associated with variation in mandible shape. Together, the associated variants account for 11.4% of skull and 4.4% of mandible shape variation, however, the total additive genetic variance associated with phenotypic variation was estimated in ~45%. Candidate genes within the associated loci have known roles in craniofacial development; this includes 6 transcription factors and several regulators of bone developmental pathways. One gene, Mn1, has an unusually large effect on shape variation in our study. A knockout of this gene was previously shown to affect negatively the development of membranous bones of the cranial skeleton, and evolutionary analysis shows that the gene has arisen at the base of the bony vertebrates (Eutelostomi), where the ossified head first appeared. Therefore, Mn1 emerges as a key gene for both skull formation and within-population shape variation. Our study shows that it is possible to identify important developmental genes through genome-wide mapping of high-dimensional shape features in an outbred population.
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