Lindsay C. Burrage

Genetic architecture of complex traits: Large phenotypic effects and pervasive epistasis

The genetic architecture of complex traits underlying physiology and disease in most organisms remains elusive. We still know little about the number of genes that underlie these traits, the magnitude of their effects, or the extent to which they interact. Chromosome substitution strains (CSSs) enable statistically powerful studies based on testing engineered inbred strains that have single, unique, and nonoverlapping genetic differences, thereby providing measures of phenotypic effects that are attributable to individual chromosomes. Here, we report a study of phenotypic effects and gene interactions for 90 blood, bone, and metabolic traits in a mouse CSS panel and 54 traits in a rat CSS panel. Two key observations emerge about the genetic architecture of these traits. First, the traits tend to be highly polygenic: across the genome, many individual chromosome substitutions each had significant phenotypic effects and, within each of the chromosomes studied, multiple distinct loci were found. Second, strong epistasis was found among the individual chromosomes. Specifically, individual chromosome substitutions often conferred surprisingly large effects (often a substantial fraction of the entire phenotypic difference between the parental strains), with the result that the sum of these individual effects often dramatically exceeded the difference between the parental strains. We suggest that strong, pervasive epistasis may reflect the presence of several phenotypically-buffered physiological states. These results have implications for identification of complex trait genes, developmental and physiological studies of phenotypic variation, and opportunities to engineer phenotypic outcomes in complex biological systems.

Deep congenic analysis identifies many strong, context-dependent QTLs, one of which, Slc35b4, regulates obesity and glucose homeostasis

Although central to many studies of phenotypic variation and disease susceptibility, characterizing the genetic architecture of complex traits has been unexpectedly difficult. For example, most of the susceptibility genes that contribute to highly heritable conditions such as obesity and type 2 diabetes (T2D) remain to be identified despite intensive study. We took advantage of mouse models of diet-induced metabolic disease in chromosome substitution strains (CSSs) both to characterize the genetic architecture of diet-induced obesity and glucose homeostasis and to test the feasibility of gene discovery. Beginning with a survey of CSSs, followed with genetic and phenotypic analysis of congenic, subcongenic, and subsubcongenic strains, we identified a remarkable number of closely linked, phenotypically heterogeneous quantitative trait loci (QTLs) on mouse chromosome 6 that have unexpectedly large phenotypic effects. Although fine-mapping reduced the genomic intervals and gene content of these QTLs over 3000-fold, the average phenotypic effect on body weight was reduced less than threefold, highlighting the fractal nature of genetic architecture in mice. Despite this genetic complexity, we found evidence for 14 QTLs in only 32 recombination events in less than 3000 mice, and with an average of four genes located within the three body weight QTLs in the subsubcongenic strains. For Obrq2a1, genetic and functional studies collectively identified the solute receptor Slc35b4 as a regulator of obesity, insulin resistance, and gluconeogenesis. This work demonstrated the unique power of CSSs as a platform for studying complex genetic traits and identifying QTLs.

Analyzing complex traits with congenic strains.

Congenic strains continue to be a fundamental resource for dissecting the genetic basis of complex traits. Traditionally, genetic variants (QTLs) that account for phenotypic variation in a panel of congenic strains are sought first by comparing phenotypes for each strain to the host (reference) strain, and then by examining the results to identify a common chromosome segment that provides the best match between genotype and phenotype across the panel. However, this “common-segment” method has significant limitations, including the subjective nature of the genetic model and an inability to deal formally with strain phenotypes that do not fit the model. We propose an alternative that we call “sequential” analysis and that is based on a unique principle of QTL analysis where each strain, corresponding to a single genotype, is tested individually for QTL effects rather than testing the congenic panel collectively for common effects across heterogeneous backgrounds. A minimum spanning tree, based on principles of graph theory, is used to determine the optimal sequence of strain comparisons. For two traits in two panels of congenic strains in mice, we compared results for the sequential method with the common-segment method as well as with two standard methods of QTL analysis, namely, interval mapping and multiple linear regression. The general utility of the sequential method was demonstrated with analysis of five additional traits in congenic panels from mice and rats. Sequential analysis rigorously resolved phenotypic heterogeneity among strains in the congenic panels and found QTLs that other methods failed to detect.

Genetic factors for resistance to diet-induced obesity and associated metabolic traits on mouse chromosome 17

Obesity is associated with increased susceptibility to dyslipidemia, insulin resistance, and hypertension, a combination of traits that comprise the traditional definition of the metabolic syndrome. Recent evidence suggests that obesity is also associated with the development of nonalcoholic fatty liver disease (NAFLD). Despite the high prevalence of obesity and its related conditions, their etiologies and pathophysiology remains unknown. Both genetic and environmental factors contribute to the development of obesity and NAFLD. Previous genetic analysis of high-fat, diet-induced obesity in C57BL/6J (B6) and A/J male mice using a panel of B6-ChrA/J/NaJ chromosome substitution strains (CSSs) demonstrated that 17 CSSs conferred resistance to high-fat, diet-induced obesity. One of these CSS strains, CSS-17, which is homosomic for A/J-derived chromosome 17, was analyzed further and found to be resistant to diet-induced steatosis. In the current study we generated seven congenic strains derived from CCS-17, fed them either a high-fat, simple-carbohydrate (HFSC) or low-fat, simple-carbohydrate (LFSC) diet for 16xa0weeks and then analyzed body weight and related traits. From this study we identified several quantitative trait loci (QTLs). On a HFSC diet, Obrq13 protects against diet-induced obesity, steatosis, and elevated fasting insulin and glucose levels. On the LFSC diet, Obrq13 confers lower hepatic triglycerides, suggesting that this QTL regulates liver triglycerides regardless of diet. Obrq15 protects against diet-induced obesity and steatosis on the HFSC diet, and Obrq14 confers increased final body weight and results in steatosis and insulin resistance on the HFSC diet. In addition, on the LFSC diet, Obrq 16 confers decreased hepatic triglycerides and Obrq17 confers lower plasma triglycerides on the LFSC diet. These congenic strains provide mouse models to identify genes and metabolic pathways that are involved in the development of NAFLD and aspects of diet-induced metabolic syndrome.

Resistance to diet-induced obesity in mice with a single substituted chromosome

Obesity and its comorbidities are taking an increasing toll on human health. Key pathways that were identified with single gene variants in humans and model organisms have led to improved understanding and treatment of rare cases of human obesity. However, similar progress remains elusive for the more common multifactorial cases of metabolic dysfunction and disease. A survey of mouse chromosome substitution strains (CSSs) provided insight into the complex genetic control of diet-induced obesity and related conditions. We now report a survey of 60 traits related to obesity and metabolic syndrome in mice with a single substituted chromosome as well as selected traits measured in congenic strains derived from the substituted strain. We found that each strain that was resistant to diet-induced obesity had a distinct phenotype that uniquely modeled different combinations of traits related to metabolic disease. For example, the chromosome 6 CSS remained insulin resistant in the absence of obesity, demonstrating an atypical relationship between body weight and insulin resistance. These results provide insights into the genetic control of constant components of this mouse model of diet-induced metabolic disease as well as phenotypes that vary depending on genetic background. A better understanding of these genotype-phenotype relationships may enable a more individualized diagnosis and treatment of obesity and the metabolic syndrome.

Increased mitochondrial oxidative phosphorylation in the liver is associated with obesity and insulin resistance

Obesity is the result of excess energy intake relative to expenditure, however little is known about why some individuals are more prone to weight gain than others. Inbred strains of mice also vary in their susceptibility to obesity and therefore represent a valuable model to study the genetics and physiology of weight gain and its co‐morbidities such as type 2 diabetes. C57BL/6J mice are susceptible to obesity and insulin resistance when fed an obesogenic diet, whereas A/J mice are resistant despite increased caloric intake. Analysis of B6‐ and A/J‐derived chromosome substitution strains and congenic strains revealed a complex genetic and physiological basis for this phenotype. To improve our understanding of the molecular mechanisms underlying susceptibility to metabolic disease we analyzed global gene expression patterns in 6C1 and 6C2 congenic strains. 6C1 is susceptible whereas 6C2 is resistant to diet‐induced obesity. In addition, we demonstrate that 6C1 is glucose intolerant and insulin resistant relative to 6C2. Pathway analysis of global gene expression patterns in muscle, adipose, and liver identified expression level differences between 6C1 and 6C2 in pathways related to basal transcription factors, endocytosis, and mitochondrial oxidative phosphorylation (OxPhos). The OxPhos expression differences were subtle but evident in each complex of the electron transport chain and were associated with a marked increase in mitochondrial oxidative capacity in the livers of the obese strain 6C1 relative to the obesity‐resistant strain 6C2. These data suggests the importance of hepatic mitochondrial function in the development of obesity and insulin resistance.