Thomas H. Ehrich

Diet-Dependent Genetic and Genomic Imprinting Effects on Obesity in Mice

Although the current obesity epidemic is of environmental origin, there is substantial genetic variation in individual response to an obesogenic environment. In this study, we perform a genome‐wide scan for quantitative trait loci (QTLs) affecting obesity per se, or an obese response to a high‐fat diet in mice from the LG/J by SM/J Advanced Intercross (AI) Line (Wustl:LG, SM‐G16). A total of 1,002 animals from 78 F16 full sibships were weaned at 3 weeks of age and half of each litter placed on high‐ and low‐fat diets. Animals remained on the diet until 20 weeks of age when they were necropsied and the weights of the reproductive, kidney, mesenteric, and inguinal fat depots were recorded. Effects on these phenotypes, along with total fat depot weight and carcass weight at necropsy, were mapped across the genome using 1,402 autosomal single‐nucleotide polymorphism (SNP) markers. Haplotypes were reconstructed and additive, dominance, and imprinting genotype scores were derived every 1 cM along the F16 map. Analysis was performed using a mixed model with additive, dominance, and imprinting genotype scores, their interactions with sex, diet, and with sex‐by‐diet as fixed effects and with family and its interaction with sex, diet, and sex‐by‐diet as random effects. We discovered 95 trait‐specific QTLs mapping to 40 locations. Most QTLs had additive effects with dominance and imprinting effects occurring at two‐thirds of the loci. Nearly every locus interacted with sex and/or diet in important ways demonstrating that gene effects are primarily context dependent, changing depending on sex and/or diet.

The importance of context to the genetic architecture of diabetes-related traits is revealed in a genome-wide scan of a LG/J × SM/J murine model.

Variations in diabetic phenotypes are caused by complex interactions of genetic effects, environmental factors, and the interplay between the two. We tease apart these complex interactions by examining genome-wide genetic and epigenetic effects on diabetes-related traits among different sex, diet, and sex-by-diet cohorts in a Mus musculus model. We conducted a genome-wide scan for quantitative trait loci that affect serum glucose and insulin levels and response to glucose stress in an F16 Advanced Intercross Line of the LG/J and SM/J intercross (Wustl:LG,SM-G16). Half of each sibship was fed a high-fat diet and half was fed a relatively low-fat diet. Context-dependent genetic (additive and dominance) and epigenetic (parent-of-origin imprinting) effects were characterized by partitioning animals into sex, diet, and sex-by-diet cohorts. We found that different cohorts often have unique genetic effects at the same loci, and that genetic signals can be masked or erroneously assigned to specific cohorts if they are not considered individually. Our data demonstrate that the effects of genes on complex trait variation are highly context-dependent and that the same genomic sequence can affect traits differently depending on an individual’s sex and/or dietary environment. Our results have important implications for studies of complex traits in humans.

Genetic, epigenetic, and gene-by-diet interaction effects underlie variation in serum lipids in a LG/JxSM/J murine model.

Variation in serum cholesterol, free-fatty acids, and triglycerides is associated with cardiovascular disease (CVD) risk factors. There is great interest in characterizing the underlying genetic architecture of these risk factors, because they vary greatly within and among human populations and between the sexes. We present results of a genome-wide scan for quantitative trait loci (QTL) affecting serum cholesterol, free-fatty acids, and triglycerides in an F16 advanced intercross line of LG/J and SM/J (Wustl:LG,SM-G16). Half of the population was fed a high-fat diet and half was fed a relatively low-fat diet. Context-dependent genetic (additive and dominance) and epigenetic (imprinting) effects were characterized by partitioning animals into sex, diet, and sex-by-diet cohorts. Here we examine genetic, environmental, and genetic-by-environmental interactions of QTL overlapping previously identified loci associated with CVD risk factors, and we add to the serum lipid QTL landscape by identifying new loci.

Genetic variation and correlation of dietary response in an advanced intercross mouse line produced from two divergent growth lines

Levels of human obesity have increased over the past 20 years worldwide, primarily due to changes in diet and activity levels. Although environmental changes are clearly responsible for the increasing prevalence of obesity, individuals may show genetic variation in their response to an obesogenic environment. Here, we measure genetic variation in response to a high-fat diet in a mouse model, an F16 Advanced Intercross Line derived from the cross of SM/J and LG/J inbred mouse strains. The experimental population was separated by sex and fed either a high-fat (42% of energy from fat) or low-fat (15% of energy from fat) diet. A number of phenotypic traits related to obesity and diabetes such as growth rate, glucose tolerance traits, organ weights and fat pad weights were collected and analysed in addition to serum levels of insulin, free fatty acids, cholesterol and triglycerides. Most traits are different between the sexes and between dietary treatments and for a few traits, including adult growth, fat pad weights, insulin and glucose tolerance, the dietary effect is stronger in one sex than the other. We find that fat pad weights, liver weight, serum insulin levels and adult growth rates are all phenotypically and genetically correlated with one another in both dietary treatments. Critically, these traits have relatively low genetic correlations across environments (average r =0.38). Dietary responses are also genetically correlated across these traits. We found substantial genetic variation in dietary response and low cross environment genetic correlations for traits aligned with adiposity. Therefore, genetic effects for these traits are different depending on the environment an animal is exposed to.