Fine-mapping of obesity-related quantitative trait loci in an F9/10 advanced intercross line

C57BL/6J mice as a polygenic developmental model of diet-induced obesity

Susceptibility to obesity changes during the course of life. We utilized the C57BL/6J (B6) and 129S mouse as a genetic model for variation in diet‐induced obesity to define the adiposity phenotypes from birth to maturity at 8 weeks‐of‐age. From birth to 8 weeks‐of‐age, both male and female 129S mice had significantly higher fat mass and adiposity index than B6 mice, although they were not obese. After 8 weeks‐of‐age, B6 had greater adiposity/obesity than 129S mice in response to a high fat (HF). We sought to determine the mechanism activating the fat accumulation in B6 mice at 8‐weeks‐of‐age. We used microarray analysis of gene expression during development of inguinal fat to show that molecular networks of lipogenesis were maximally expressed at 8 weeks‐of‐age. In addition, the DNA methylation analysis of the Sfrp5 promoter and binding of acetylated histones to Sfrp5 and Acly promoter regions showed that major differences in the expression of genes of lipogenesis and chromatin structure occur during development. Differences in lipogenesis networks could account for the strain‐dependent differences in adiposity up to 8 weeks‐of‐age; however, changes in the expression of genes in these networks were not associated with the susceptibility to DIO in B6 male mice beyond 8 weeks‐of‐age.

Identification of Genomic Somatic Variants in Cancer: From Discovery to Actionability

The perfect method to discover and validate actionable somatic variants in cancer has not yet been developed, yet significant progress has been made toward this goal. There have been huge increases in the throughput and cost of deoxyribonucleic acid (DNA) and ribonucleic acid (RNA) sequencing technologies that have led to the burgeoning possibility of using sequencing data in clinical settings. Discovery of somatic mutations is relatively simple and has been improved recently due to laboratory methods optimization, bioinformatics algorithms development, and the expansion of various databases of population genomic information. Tiered systems of evidence evaluation are currently being used to classify genomic variants for clinicians to more rapidly and accurately determine actionability of these aberrations. These efforts are complicated by the intricacies of communicating sequencing results to physicians and supporting its biological relevance, emphasizing the need for increasing education of clinicians and administrators, and the ongoing development of ethical standards for dealing with incidental results. This chapter will focus on general aspects of DNA and RNA tumor sequencing technologies, data analysis and interpretation, assessment of biological and clinical relevance of genomic aberrations, ethical aspects of germline sequencing, and how these factors impact cancer personalized care.

Using whole-genome sequences of the LG/J and SM/J inbred mouse strains to prioritize quantitative trait genes and nucleotides

Background

The laboratory mouse is the most commonly used model for studying variation in complex traits relevant to human disease. Here we present the whole-genome sequences of two inbred strains, LG/J and SM/J, which are frequently used to study variation in complex traits as diverse as aging, bone-growth, adiposity, maternal behavior, and methamphetamine sensitivity.

Results

We identified small nucleotide variants (SNVs) and structural variants (SVs) in the LG/J and SM/J strains relative to the reference genome and discovered novel variants in these two strains by comparing their sequences to other mouse genomes. We find that 39% of the LG/J and SM/J genomes are identical-by-descent (IBD). We characterized amino-acid changing mutations using three algorithms: LRT, PolyPhen-2 and SIFT. We also identified polymorphisms between LG/J and SM/J that fall in regulatory regions and highly informative transcription factor binding sites (TFBS). We intersected these functional predictions with quantitative trait loci (QTL) mapped in advanced intercrosses of these two strains. We find that QTL are both over-represented in non-IBD regions and highly enriched for variants predicted to have a functional impact. Variants in QTL associated with metabolic (231 QTL identified in an F₁₆ generation) and developmental (41 QTL identified in an F₃₄ generation) traits were interrogated and we highlight candidate quantitative trait genes (QTG) and nucleotides (QTN) in a QTL on chr13 associated with variation in basal glucose levels and in a QTL on chr6 associated with variation in tibia length.

Conclusions

We show how integrating genomic sequence with QTL reduces the QTL search space and helps researchers prioritize candidate genes and nucleotides for experimental follow-up. Additionally, given the LG/J and SM/J phylogenetic context among inbred strains, these data contribute important information to the genomic landscape of the laboratory mouse.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1592-3) contains supplementary material, which is available to authorized users.

Fine-mapping QTLs in advanced intercross lines and other outbred populations

Quantitative genetic studies in model organisms, particularly in mice, have been extremely successful in identifying chromosomal regions that are associated with a wide variety of behavioral and other traits. However, it is now widely understood that identification of the underlying genes will be far more challenging. In the last few years, a variety of populations have been utilized in an effort to more finely map these chromosomal regions with the goal of identifying specific genes. The common property of these newer populations is that linkage disequilibrium spans relatively short distances, which permits fine-scale mapping resolution. This review focuses on advanced intercross lines (AILs) which are the simplest such population. As originally proposed in 1995 by Darvasi and Soller, an AIL is the product of intercrossing two inbred strains beyond the F2 generation. Unlike recombinant inbred strains, AILs are maintained as outbred populations; brother-sister matings are specifically avoided. Each generation of intercrossing beyond the F2 further degrades linkage disequilibrium between adjacent makers, which allows for fine-scale mapping of quantitative trait loci (QTLs). Advances in genotyping technology and techniques for the statistical analysis of AILs have permitted rapid advances in the application of AILs. We review some of the analytical issues and available software, including QTLRel, EMMA, EMMAX, GEMMA, TASSEL, GRAMMAR, WOMBAT, Mendel, and others.

The effect of dietary fat intake on hepatic gene expression in LG/J AND SM/J mice

Background

The liver plays a major role in regulating metabolic homeostasis and is vital for nutrient metabolism. Identifying the genetic factors regulating these processes could lead to a greater understanding of how liver function responds to a high-fat diet and how that response may influence susceptibilities to obesity and metabolic syndrome. In this study we examine differences in hepatic gene expression between the LG/J and SM/J inbred mouse strains and how gene expression in these strains is affected by high-fat diet. LG/J and SM/J are known to differ in their responses to a high-fat diet for a variety of obesity- and diabetes-related traits, with the SM/J strain exhibiting a stronger phenotypic response to diet.

Results

Dietary intake had a significant effect on gene expression in both inbred lines. Genes up-regulated by a high-fat diet were involved in biological processes such as lipid and carbohydrate metabolism; protein and amino acid metabolic processes were down regulated on a high-fat diet. A total of 259 unique transcripts exhibited a significant diet-by-strain interaction. These genes tended to be associated with immune function. In addition, genes involved in biochemical processes related to non-alcoholic fatty liver disease (NAFLD) manifested different responses to diet between the two strains. For most of these genes, SM/J had a stronger response to the high-fat diet than LG/J.

Conclusions

These data show that dietary fat impacts gene expression levels in SM/J relative to LG/J, with SM/J exhibiting a stronger response. This supports previous data showing that SM/J has a stronger phenotypic response to high-fat diet. Based upon these findings, we suggest that SM/J and its cross with the LG/J strain provide a good model for examining non-alcoholic fatty liver disease and its role in metabolic syndrome.

QTL mapping in outbred populations: successes and challenges

Quantitative trait locus (QTL) mapping in animal populations has been a successful strategy for identifying genomic regions that play a role in complex diseases and traits. When conducted in an F2 intercross or backcross population, the resulting QTL is frequently large, often encompassing 30 Mb or more and containing hundreds of genes. To narrow the locus and identify candidate genes, additional strategies are needed. Congenic strains have proven useful but work less well when there are multiple tightly linked loci, frequently resulting in loss of phenotype. As an alternative, we discuss the use of highly recombinant outbred models for directly fine-mapping QTL to only a few megabases. We discuss the use of several currently available models such as the advanced intercross (AI), heterogeneous stocks (HS), the diversity outbred (DO), and commercially available outbred stocks (CO). Once a QTL has been fine-mapped, founder sequence and expression QTL mapping can be used to identify candidate genes. In this regard, the large number of alleles found in outbred stocks can be leveraged to identify causative genes and variants. We end this review by discussing some important statistical considerations when analyzing outbred populations. Fine-resolution mapping in outbred models, coupled with full genome sequence, has already led to the identification of several underlying causative genes for many complex traits and diseases. These resources will likely lead to additional successes in the coming years.

Weak genetic relationship between trabecular bone morphology and obesity in mice

Obesity, in addition to being associated with metabolic diseases, such as diabetes, has also been found to lower the risk of osteoporotic fractures. The relationship between obesity and bone trabecular structure is complex, involving responses to mechanical loading and the effects of adipocyte-derived hormones, both directly interacting with bone tissue and indirectly through central nervous system signaling. Here we examine the effects of sex, a high fat diet, and genetics on the trabecular density and structure of the lumbar and caudal vertebra and the proximal tibia along with body weight, fat pad weight, and serum leptin levels in a murine obesity model, the LGXSM recombinant inbred (RI) mouse strains. The sample included 481 mice from 16 RI strains. We found that vertebral trabecular density was higher in males while the females had higher tibial trabecular density. The high fat diet led to only slightly higher trabecular density in both sexes despite its extreme effects on obesity and serum leptin levels. Trait heritabilities are moderate to strong and genetic correlations among trabecular features are high. Most genetic variation contrasts strains with large numbers of thick, closely-spaced, highly interconnected, plate-like trabeculae with a high bone volume to total volume ratio against strains displaying small numbers of thin, widely-spaced, sparsely connected, rod-like trabeculae with a low bone volume to total volume ratio. Genetic correlations between trabecular and obesity-related traits were low and not statistically significant. We mapped trabecular properties to 20 genomic locations. Only one-quarter of these locations also had effects on obesity. In this population obesity has a relatively minor effect on trabecular bone morphology.

Synchronizing allelic effects of opposing quantitative trait loci confirmed a major epistatic interaction affecting acute lung injury survival in mice

Increased oxygen (O₂) levels help manage severely injured patients, but too much for too long can cause acute lung injury (ALI), acute respiratory distress syndrome (ARDS) and even death. In fact, continuous hyperoxia has become a prototype in rodents to mimic salient clinical and pathological characteristics of ALI/ARDS. To identify genes affecting hyperoxia-induced ALI (HALI), we previously established a mouse model of differential susceptibility. Genetic analysis of backcross and F₂ populations derived from sensitive (C57BL/6J; B) and resistant (129X1/SvJ; X1) inbred strains identified five quantitative trait loci (QTLs; Shali1-5) linked to HALI survival time. Interestingly, analysis of these recombinant populations supported opposite within-strain effects on survival for the two major-effect QTLs. Whereas Shali1 alleles imparted the expected survival time effects (i.e., X1 alleles increased HALI resistance and B alleles increased sensitivity), the allelic effects of Shali2 were reversed (i.e., X1 alleles increased HALI sensitivity and B alleles increased resistance). For in vivo validation of these inverse allelic effects, we constructed reciprocal congenic lines to synchronize the sensitivity or resistance alleles of Shali1 and Shali2 within the same strain. Specifically, B-derived Shali1 or Shali2 QTL regions were transferred to X1 mice and X1-derived QTL segments were transferred to B mice. Our previous QTL results predicted that substituting Shali1 B alleles onto the resistant X1 background would add sensitivity. Surprisingly, not only were these mice more sensitive than the resistant X1 strain, they were more sensitive than the sensitive B strain. In stark contrast, substituting the Shali2 interval from the sensitive B strain onto the X1 background markedly increased the survival time. Reciprocal congenic lines confirmed the opposing allelic effects of Shali1 and Shali2 on HALI survival time and provide unique models to identify their respective quantitative trait genes and to critically assess the apparent bidirectional epistatic interactions between these major-effect loci.

Advances in comparative genetics: influence of genetics on obesity

Obesity has reached epidemic proportions and is recognised as a significant global health problem. Increased food intake and decreased physical activity are traditionally to blame for the development of obesity; however, many variables such as behaviour, diet, environment, social structures and genetics also contribute to this multifactorial disease. Complex interactions among these variables (for example, gene-environment, gene-diet and gene-gene) contribute not only to individual differences in the development of obesity, but also in treatment response. Mouse models have historically played valuable roles in understanding the genetics of traits related to energy balance and obesity. In the present review, we survey past use and examine new advances in mouse models designed to uncover the genetic architecture of obesity and its component traits. We discuss traditional models such as inbred strains and selectively bred lines and their contributions and shortcomings. We consider the evolution of mouse models into more informative resources such as outbred crosses and the Hybrid Mouse Diversity Panel, as well as novel next-generation approaches such as the Collaborative Cross. Moreover, the genetic architecture of voluntary exercise and the interactive relationship between host genetics and the gut microbiome are presented as novel phenotypes that augment studies using body weight and body fat percentage as endpoints. Understanding the intricate network of phenotypic, genotypic and environmental variables that predispose individuals to obesity will elucidate biological networks involved in the development of obesity. Knowledge obtained from advances in mouse models will inform human health and provide insight into inter-individual variability in the aetiology of obesity-related diseases.

Fine-mapping alleles for body weight in LG/J × SM/J F₂ and F(34) advanced intercross lines

The present study measured variation in body weight using a combined analysis in an F(2) intercross and an F(34) advanced intercross line (AIL). Both crosses were derived from inbred LG/J and SM/J mice, which were selected for large and small body size prior to inbreeding. Body weight was measured at 62 (± 5) days of age. Using an integrated GWAS and forward model selection approach, we identified 11 significant QTLs that affected body weight on ten different chromosomes. With these results we developed a full model that explained over 18% of the phenotypic variance. The median 1.5-LOD support interval was 5.55 Mb, which is a significant improvement over most prior body weight QTLs. We identified nonsynonymous coding SNPs between LG/J and SM/J mice in order to further narrow the list of candidate genes. Three of the genes with nonsynonymous coding SNPs (Rad23b, Stk33, and Anks1b) have been associated with adiposity, waist circumference, and body mass index in human GWAS, thus providing evidence that these genes may underlie our QTLs. Our results demonstrate that a relatively small number of loci contribute significantly to the phenotypic variance in body weight, which is in marked contrast to the situation in humans. This difference is likely to be the result of strong selective pressure and the simplified genetic architecture, both of which are important advantages of our system.

Genetic effects at pleiotropic loci are context-dependent with consequences for the maintenance of genetic variation in populations

Context-dependent genetic effects, including genotype-by-environment and genotype-by-sex interactions, are a potential mechanism by which genetic variation of complex traits is maintained in populations. Pleiotropic genetic effects are also thought to play an important role in evolution, reflecting functional and developmental relationships among traits. We examine context-dependent genetic effects at pleiotropic loci associated with normal variation in multiple metabolic syndrome (MetS) components (obesity, dyslipidemia, and diabetes-related traits). MetS prevalence is increasing in Western societies and, while environmental in origin, presents substantial variation in individual response. We identify 23 pleiotropic MetS quantitative trait loci (QTL) in an F₁₆ advanced intercross between the LG/J and SM/J inbred mouse strains (Wustl:LG,SM-G16; n = 1002). Half of each family was fed a high-fat diet and half fed a low-fat diet; and additive, dominance, and parent-of-origin imprinting genotypic effects were examined in animals partitioned into sex, diet, and sex-by-diet cohorts. We examine the context-dependency of the underlying additive, dominance, and imprinting genetic effects of the traits associated with these pleiotropic QTL. Further, we examine sequence polymorphisms (SNPs) between LG/J and SM/J as well as differential expression of positional candidate genes in these regions. We show that genetic associations are different in different sex, diet, and sex-by-diet settings. We also show that over- or underdominance and ecological cross-over interactions for single phenotypes may not be common, however multidimensional synthetic phenotypes at loci with pleiotropic effects can produce situations that favor the maintenance of genetic variation in populations. Our findings have important implications for evolution and the notion of personalized medicine.

We look at gene-by-diet and gene-by-sex interactions underlying natural variation in multiple metabolic traits mapping to the same regions of the genome in a mouse model. We find that the underlying genetic architecture of these traits is different in different sex and diet contexts. We further use expression data and whole-genome polymorphism data to identify compelling candidates for experimental follow-up. We use these results to examine theoretical evolutionary predictions about how variation in populations can be maintained. There has been much discussion of late on how to use evolutionary theory to inform medical genomics. Mouse models may be especially appropriate for bridging the divide between evolutionary and biomedical research, because they allow the study of the effects of natural alleles on normal variation and because human-mouse homology is well defined. Our study is unique in examining quantitative trait loci from both evolutionary and biomedical perspectives, and we highlight the complex connections of the traits comprising the metabolic syndrome and the evolutionary implications of their underlying genetic architecture. This is important for understanding disease etiology and is relevant to personalized medicine.

Identification of quantitative trait loci influencing skeletal architecture in mice: emergence of Cdh11 as a primary candidate gene regulating femoral morphology

Bone strength is influenced by many properties intrinsic to bone, including its mass, geometry, and mineralization. To further advance our understanding of the genetic basis of bone-strength-related traits, we used a large (n = 815), moderately (G(4) ) advanced intercross line (AIL) of mice derived from a high-runner selection line (HR) and the C57BL/6J inbred strain. In total, 16 quantitative trait loci (QTLs) were identified that affected areal bone mineral density (aBMD) and femoral length and width. Four significant (p < .05) and one suggestive (p < .10) QTLs were identified for three aBMD measurements: total body, vertebral, and femoral. A QTL on chromosome (Chr.) 3 influenced all three aBMD measures, whereas the other four QTLs were unique to a single measure. A total of 10 significant and one suggestive QTLs were identified for femoral length (FL) and two measures of femoral width, anteroposterior (AP) and mediolateral (ML). FL QTLs were distinct from loci affecting AP and ML width, and of the 7 AP QTLs, only three affected ML. A QTL on Chr. 8 that explained 7.1% and 4.0% of the variance in AP and ML, respectively, was mapped to a 6-Mb region harboring 12 protein-coding genes. The pattern of haplotype diversity across the QTL region and expression profiles of QTL genes suggested that of the 12, cadherin 11 (Cdh11) was most likely the causal gene. These findings, when combined with existing data from gene knockouts, identify Cdh11 as a strong candidate gene within which genetic variation may affect bone morphology.

Joint analysis of quantitative trait loci and major-effect causative mutations affecting meat quality and carcass composition traits in pigs

Background

Detection of quantitative trait loci (QTLs) affecting meat quality traits in pigs is crucial for the design of efficient marker-assisted selection programs and to initiate efforts toward the identification of underlying polymorphisms. The RYR1 and PRKAG3 causative mutations, originally identified from major effects on meat characteristics, can be used both as controls for an overall QTL detection strategy for diversely affected traits and as a scale for detected QTL effects. We report on a microsatellite-based QTL detection scan including all autosomes for pig meat quality and carcass composition traits in an F2 population of 1,000 females and barrows resulting from an intercross between a Pietrain and a Large White-Hampshire-Duroc synthetic sire line. Our QTL detection design allowed side-by-side comparison of the RYR1 and PRKAG3 mutation effects seen as QTLs when segregating at low frequencies (0.03-0.08), with independent QTL effects detected from most of the same population, excluding any carrier of these mutations.

Results

Large QTL effects were detected in the absence of the RYR1 and PRKGA3 mutations, accounting for 12.7% of phenotypic variation in loin colour redness CIE-a* on SSC6 and 15% of phenotypic variation in glycolytic potential on SSC1. We detected 8 significant QTLs with effects on meat quality traits and 20 significant QTLs for carcass composition and growth traits under these conditions. In control analyses including mutation carriers, RYR1 and PRKAG3 mutations were detected as QTLs, from highly significant to suggestive, and explained 53% to 5% of the phenotypic variance according to the trait.

Conclusions

Our results suggest that part of muscle development and backfat thickness effects commonly attributed to the RYR1 mutation may be a consequence of linkage with independent QTLs affecting those traits. The proportion of variation explained by the most significant QTLs detected in this work is close to the influence of major-effect mutations on the least affected traits, but is one order of magnitude lower than effect on variance of traits primarily affected by these causative mutations. This suggests that uncovering physiological traits directly affected by genetic polymorphisms would be an appropriate approach for further characterization of QTLs.

The effect of a population bottleneck on the evolution of genetic variance/covariance structure

It is well known that standard population genetic theory predicts decreased additive genetic variance (V(a) ) following a population bottleneck and that theoretical models including interallelic and intergenic interactions indicate such loss may be avoided. However, few empirical data from multicellular model systems are available, especially regarding variance/covariance (V/CV) relationships. Here, we compare the V/CV structure of seventeen traits related to body size and composition between control (60 mating pairs/generation) and bottlenecked (2 mating pairs/generation; average F = 0.39) strains of mice. Although results for individual traits vary considerably, multivariate analysis indicates that V(a) in the bottlenecked populations is greater than expected. Traits with patterns and amounts of epistasis predictive of enhanced V(a) also show the largest deviations from additive expectations. Finally, the correlation structure of weekly weights is not significantly different between control and experimental lines but correlations between necropsy traits do differ, especially those involving the heart, kidney and tail length.

Dark matter: are mice the solution to missing heritability?

Genome-wide association studies (GWAS) in humans have identified hundreds of single nucleotide polymorphisms associated with complex traits, yet for most traits studied, the sum total of all these identified variants fail to explain a significant portion of the heritable variation. Reasons for this “missing heritability” are thought to include the existence of rare causative variants not captured by current genotyping arrays, structural variants that go undetected by existing technology, insufficient power to identify multi-gene interactions, small sample sizes, and the influence of environmental and epigenetic effects. As genotyping technologies have evolved it has become inexpensive and relatively straightforward to perform GWAS in mice. Mice offer a powerful tool for elucidating the genetic architecture of behavioral and physiological traits, and are complementary to human studies. Unlike F₂ crosses of inbred strains, advanced intercross lines, heterogeneous stocks, outbred, and wild-caught mice have more rapid breakdown of linkage disequilibrium which allow for increasingly high resolution mapping. Because some of these populations are created using a small number of founder chromosomes they are not expected to harbor rare alleles. We discuss the differences between these mouse populations and examine their potential to overcome some of the pitfalls that have plagued human GWAS studies.

Architecture of energy balance traits in emerging lines of the Collaborative Cross

The potential utility of the Collaborative Cross (CC) mouse resource was evaluated to better understand complex traits related to energy balance. A primary focus was to examine if genetic diversity in emerging CC lines (pre-CC) would translate into equivalent phenotypic diversity. Second, we mapped quantitative trait loci (QTL) for 15 metabolism- and exercise-related phenotypes in this population. We evaluated metabolic and voluntary exercise traits in 176 pre-CC lines, revealing phenotypic variation often exceeding that seen across the eight founder strains from which the pre-CC was derived. Many phenotypic correlations existing within the founder strains were no longer significant in the pre-CC population, potentially representing reduced linkage disequilibrium (LD) of regions harboring multiple genes with effects on energy balance or disruption of genetic structure of extant inbred strains with substantial shared ancestry. QTL mapping revealed five significant and eight suggestive QTL for body weight (Chr 4, 7.54 Mb; CI 3.32-10.34 Mb; Bwq14), body composition, wheel running (Chr 16, 33.2 Mb; CI 32.5-38.3 Mb), body weight change in response to exercise (1: Chr 6, 77.7Mb; CI 72.2-83.4 Mb and 2: Chr 6, 42.8 Mb; CI 39.4-48.1 Mb), and food intake during exercise (Chr 12, 85.1 Mb; CI 82.9-89.0 Mb). Some QTL overlapped with previously mapped QTL for similar traits, whereas other QTL appear to represent novel loci. These results suggest that the CC will be a powerful, high-precision tool for examining the genetic architecture of complex traits such as those involved in regulation of energy balance.

Evolution of pleiotropy: epistatic interaction pattern supports a mechanistic model underlying variation in genotype-phenotype map

The genotype-phenotype (GP) map consists of developmental and physiological mechanisms mapping genetic onto phenotypic variation. It determines the distribution of heritable phenotypic variance on which selection can act. Comparative studies of morphology as well as of gene regulatory networks show that the GP map itself evolves, yet little is known about the actual evolutionary mechanisms involved. The study of such mechanisms requires exploring the variation in GP maps at the population level, which presently is easier to quantify by statistical genetic methods rather than by regulatory network structures. We focus on the evolution of pleiotropy, a major structural aspect of the GP map. Pleiotropic genes affect multiple traits and underlie genetic covariance between traits, often causing evolutionary constraints. Previous quantitative genetic studies have demonstrated population-level variation in pleiotropy in the form of loci, at which genotypes differ in the genetic covariation between traits. This variation can potentially fuel evolution of the GP map under selection and/or drift. Here, we propose a developmental mechanism underlying population genetic variation in covariance and test its predictions. Specifically, the mechanism predicts that the loci identified as responsible for genetic variation in pleiotropy are involved in trait-specific epistatic interactions. We test this prediction for loci affecting allometric relationships between traits in an advanced intercross between inbred mouse strains. The results consistently support the prediction. We further find a high degree of sign epistasis in these interactions, which we interpret as an indication of adaptive gene complexes within the diverged parental lines.

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 F(16) 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.

Intersubspecific subcongenic mouse strain analysis reveals closely linked QTLs with opposite effects on body weight

A previous genome-wide QTL study revealed many QTLs affecting postnatal body weight and growth in an intersubspecific backcross mouse population between the C57BL/6J (B6) strain and wild Mus musculus castaneus mice captured in the Philippines. Subsequently, several closely linked QTLs for body composition traits were revealed in an F(2) intercross population between B6 and B6.Cg-Pbwg1, a congenic strain on the B6 genetic background carrying the growth QTL Pbwg1 on proximal chromosome 2. However, no QTL affecting body weight has been duplicated in the F(2) population, except for mapping an overdominant QTL that causes heterosis of body weight. In this study, we developed 17 intersubspecific subcongenic strains with overlapping and nonoverlapping castaneus regions from the B6.Cg-Pbwg1 congenic strain in order to search for and genetically dissect QTLs affecting body weight into distinct closely linked loci. Phenotypic comparisons of several developed subcongenic strains with the B6 strain revealed that two closely linked but distinct QTLs that regulate body weight, named Pbwg1.11 and Pbwg1.12, are located on an 8.9-Mb region between D2Mit270 and D2Mit472 and on the next 3.6-Mb region between D2Mit205 and D2Mit182, respectively. Further analyses using F(2) segregating populations obtained from intercrosses between B6 and each of the two selected subcongenic strains confirmed the presence of these two body weight QTLs. Pbwg1.11 had an additive effect on body weight at 6, 10, and 13 weeks of age, and its castaneus allele decreased it. In contrast, the castaneus allele at Pbwg1.12 acted in a dominant fashion and surprisingly increased body weight at 6, 10, and 13 weeks of age despite the body weight of wild castaneus mice being 60% of that of B6 mice. These findings illustrate the complex genetic nature of body weight regulation and support the importance of subcongenic mouse analysis to dissect closely linked loci.

The biological control of voluntary exercise, spontaneous physical activity and daily energy expenditure in relation to obesity: human and rodent perspectives

Mammals expend energy in many ways, including basic cellular maintenance and repair, digestion, thermoregulation, locomotion, growth and reproduction. These processes can vary tremendously among species and individuals, potentially leading to large variation in daily energy expenditure (DEE). Locomotor energy costs can be substantial for large-bodied species and those with high-activity lifestyles. For humans in industrialized societies, locomotion necessary for daily activities is often relatively low, so it has been presumed that activity energy expenditure and DEE are lower than in our ancestors. Whether this is true and has contributed to a rise in obesity is controversial. In humans, much attention has centered on spontaneous physical activity (SPA) or non-exercise activity thermogenesis (NEAT), the latter sometimes defined so broadly as to include all energy expended due to activity, exclusive of volitional exercise. Given that most people in Western societies engage in little voluntary exercise, increasing NEAT may be an effective way to maintain DEE and combat overweight and obesity. One way to promote NEAT is to decrease the amount of time spent on sedentary behaviours (e.g. watching television). The effects of voluntary exercise on other components of physical activity are highly variable in humans, partly as a function of age, and have rarely been studied in rodents. However, most rodent studies indicate that food consumption increases in the presence of wheels; therefore, other aspects of physical activity are not reduced enough to compensate for the energetic cost of wheel running. Most rodent studies also show negative effects of wheel access on body fat, especially in males. Sedentary behaviours per se have not been studied in rodents in relation to obesity. Several lines of evidence demonstrate the important role of dopamine, in addition to other neural signaling networks (e.g. the endocannabinoid system), in the control of voluntary exercise. A largely separate literature points to a key role for orexins in SPA and NEAT. Brain reward centers are involved in both types of physical activities and eating behaviours, likely leading to complex interactions. Moreover, voluntary exercise and, possibly, eating can be addictive. A growing body of research considers the relationships between personality traits and physical activity, appetite, obesity and other aspects of physical and mental health. Future studies should explore the neurobiology, endocrinology and genetics of physical activity and sedentary behaviour by examining key brain areas, neurotransmitters and hormones involved in motivation, reward and/or the regulation of energy balance.

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.

Mapping the epistatic network underlying murine reproductive fatpad variation

Genome-wide mapping analyses are now commonplace in many species and several networks of interacting loci have been reported. However, relatively few details regarding epistatic interactions and their contribution to complex trait variation in multicellular organisms are available and the identification of positional candidate loci for epistatic QTL (epiQTL) is hampered, especially in mammals, by the limited genetic resolution inherent in most study designs. Here we further investigate the genetic architecture of reproductive fatpad weight in mice using the F(10) generation of the LG,SM advanced intercross (AI) line. We apply multiple mapping techniques including a single-locus model, locus-specific composite interval mapping (CIM), and tests for multiple QTL per chromosome to the 12 chromosomes known to harbor single-locus QTL (slQTL) affecting obesity in this cross. We also perform a genome-wide scan for pairwise epistasis. Using this combination of approaches we detect 199 peaks spread over all 19 autosomes, which potentially contribute to trait variation including all eight original F(2) loci (Adip1-8), novel slQTL peaks on chromosomes 7 and 9, and several novel epistatic loci. Extensive epistasis is confirmed involving both slQTL confidence intervals (C.I.) as well as regions that show no significant additive or dominance effects. These results provide important new insights into mapping complex genetic architectures and the role of epistasis in complex trait variation.

Congenic and bioinformatics analyses resolved a major-effect Fob3b QTL on mouse Chr 15 into two closely linked loci

We previously identified a Chr 15 quantitative trait locus (QTL) Fob3b in lines of mice selected for high (Fat line) and low (Lean line) body fat content that represent a unique model of polygenic obesity. Here we genetically dissected the Fob3b interval by analyzing the phenotypes of eight overlapping congenic lines and four F(2) congenic intercrosses and prioritized candidates by bioinformatics approaches. Analyses revealed that the Fob3b QTL consists of at least two separate linked QTLs Fob3b1 and Fob3b2. They exhibit additive inheritance and are linked in coupling with alleles originating from the Lean line, decreasing obesity-related traits. In further analyses, we focused on Fob3b1 because it had a larger effect on obesity-related traits than Fob3b2, e.g., the difference between homozygotes for adiposity index (ADI) percentage was 1.22 and 0.77% for Fob3b1 and Fob3b2, respectively. A set of bioinformatics tools was used to narrow down positional candidates from 85 to 4 high-priority Fob3b1 candidates. A previous single Fob3b QTL was therefore resolved into another two closely linked QTLs, confirming the fractal nature of QTLs mapped at low resolution. The interval of the original Fob3b QTL was narrowed from 22.39 to 4.98 Mbp for Fob3b1 and to 7.68 Mbp for Fob3b2, which excluded the previously assigned candidate squalene epoxidase (Sqle) as the causal gene because it maps proximal to refined Fob3b1 and Fob3b2 intervals. A high-resolution map along with prioritization of Fob3b1 candidates by bioinformatics represents an important step forward to final identification of the Chr 15 obesity QTL.

Metabolic syndrome components in murine models

Animal models have enriched understanding of the physiological basis of metabolic disorders and advanced identification of genetic risk factors underlying the metabolic syndrome (MetS). Murine models are especially appropriate for this type of research, and are an excellent resource not only for identifying candidate genomic regions, but also for illuminating the possible molecular mechanisms or pathways affected in individual components of MetS. In this review, we briefly discuss findings from mouse models of metabolic disorders, particularly in light of issues raised by the recent flood of human genome-wide association studies (GWAS) results. We describe how mouse models are revealing that genotype interacts with environment in important ways, indicating that the underlying genetics of MetS is highly context dependant. Further we show that epistasis, imprinting and maternal effects each contribute to the genetic architecture underlying variation in metabolic traits, and mouse models provide an opportunity to dissect these aspects of the genetic architecture that are difficult if not impossible to ascertain in humans. Finally we discuss how knowledge gained from mouse models can be used in conjunction with comparative genomic methods and bioinformatic resources to inform human MetS research.

Genes unlinked to the leptin receptor influence urinary albumin excretion in obese Zucker rats

We have previously shown that 90% of outbred obese Zucker Lepr(fa/fa) rats die prematurely of renal disease. Thus, renal disease in obese Zucker Lepr(fa/fa) rats may be caused by the LEPR mutation on chromosome 5, by the obesity, or it may be influenced by Zucker susceptibility alleles of genes on other chromosomes. We have searched for susceptibility genes on other chromosomes using urinary albumin excretion (UAE) as an early indicator of altered renal function in a backcross of (Brown Norway × inbred Zucker) F1 × inbred Zucker, which we name the BZZ cross. We killed 237 BZZ backcross animals at 15 wk of age. All included animals were homozygous for the fatty mutation of LEPR and were obese. Urinary creatinine measurements were used to calculate the albumin-to-creatinine ratio (ACR). We identified direct effect quantitative trait loci (QTLs) for UAE and ACR on chromosome 1 (LOD scores = 3.6 and 2.86, respectively) in males, and chromosome 4 (LOD score = 2.9) in females. Significant QTLs were identified for left kidney weight for females on chromosomes 3 and 12. We also demonstrated that kidneys from 15 wk old obese inbred Zucker rats already show evidence of kidney pathology: tubular dilation, proteinaceous fluid accumulation, evidence for inflammation, and mild mesangial and tubular membrane basement membrane thickening. Both lean Zucker rats and the Brown Norway rats showed no evidence for these changes. Thus, by removing the influence of the Lepr(fa/fa) mutation from analysis we have identified UAE QTLs unlinked to LEPR.