Single QTL effects, epistasis, and pleiotropy account for two-thirds of the phenotypic F(2) variance of growth and obesity in DU6i x DBA/2 mice

High-density genotyping reveals candidate genomic regions for chicken body size in breeds of Asian origin

Body size is one of the main selection indices in chicken breeding. Although often investigated, knowledge of the underlying genetic mechanisms is incomplete. The aim of the current study was to identify genomic regions associated with body size differences between Asian Game and Asian Bantam type chickens. In this study, 94 and 107 chickens from 4 Asian Game and 5 Asian Bantam type breeds, respectively, were genotyped using the chicken 580K single nucleotide polymorphism (SNP) array. A genome-wide association study (GWAS) and principal component analyses (PCA) were performed to identify genomic regions associated with body size related-traits such as wing length, shank length, shank thickness, keel length, and body weight. Hierarchical clustering of genotype data showed a clear genetic difference between the investigated Asian Game and Asian Bantam chicken types. GWAS identified 16 genomic regions associated with wing length (2, FDR ≤ 0.018), shank thickness (6, FDR ≤ 0.008), keel length (5, FDR ≤ 0.023), and body weight (3, FDR ≤ 0.041). PCA showed that the first principal component (PC1) separated the 2 chicken types and significantly correlated with the measured body size related-traits (P ≤ 2.24e-40). SNPs contributing significantly to PC1 were subjected to a more detailed investigation. This analysis identified 11 regions potentially associated with differences in body size related-traits. A region on chromosome 4 (GGA4) (17.3-21.3 Mb) was detected in both analyses GWAS and PCA. This region harbors 60 genes. Among them are myotubularin 1 (MTM1) and secreted frizzled-related protein 2 (SFPR2) which can be considered as potential candidate genes for body size related-traits. Our results clearly show that the investigated Asian Game type chicken breeds are genetically different from the Asian Bantam breeds. A region on GGA4 between 17.3 and 21.3 Mb was identified which contributes to the phenotypic difference, though further validation of candidate genes is necessary.

Genetics of murine type 2 diabetes and comorbidities

ABSTRAC

Type 2 diabetes (T2D) is a polygenic and multifactorial complex disease, defined as chronic metabolic disorder. It's a major global health concern with an estimated 463 million adults aged 20-79 years with diabetes and projected to increase up to 700 million by 2045. T2D was reported to be one of the four leading causes of non-communicable disease (NCD) deaths in 2012. Environmental factors play a part in the development of polygenic forms of diabetes. Polygenic forms of diabetes often run-in families. Fortunately, T2D, which accounts for 90-95% of the entire four types of diabetes including, Type 1 diabetes (T1D), T2D, monogenic diabetes syndromes (MGDS), and Gestational diabetes mellitus, can be prevented or delayed through nutrition and lifestyle changes as well as through pharmacologic interventions. Typical symptom of the T2D is high blood glucose levels and comprehensive insulin resistance of the body, producing an impaired glucose tolerance. Impaired glucose tolerance of T2D is accompanied by extensive health complications, including cardiovascular diseases (CVD) that vary in morbidity and mortality among populations. The pathogenesis of T2D varies between populations and/or ethnic groupings and is known to be attributed extremely by genetic components and environmental factors. It is evident that genetic background plays a critical role in determining the host response toward certain environmental conditions, whether or not of developing T2D (susceptibility versus resistant). T2D is considered as a silent disease that can progress for years before its diagnosis. Once T2D is diagnosed, many metabolic malfunctions are observed whether as side effects or as independent comorbidity. Mouse models have been proven to be a powerful tool for mapping genetic factors that underline the susceptibility to T2D development as well its comorbidities. Here, we have conducted a comprehensive search throughout the published data covering the time span from early 1990s till the time of writing this review, for already reported quantitative trait locus (QTL) associated with murine T2D and comorbidities in different mouse models, which contain different genetic backgrounds. Our search has resulted in finding 54 QTLs associated with T2D in addition to 72 QTLs associated with comorbidities associated with the disease. We summarized the genomic locations of these mapped QTLs in graphical formats, so as to show the overlapping positions between of these mapped QTLs, which may suggest that some of these QTLs could be underlined by sharing gene/s. Finally, we reviewed and addressed published reports that show the success of translation of the identified mouse QTLs/genes associated with the disease in humans.

'Fat's chances': Loci for phenotypic dispersion in plasma leptin in mouse models of diabetes mellitus

Background

Leptin, a critical mediator of feeding, metabolism and diabetes, is expressed on an incidental basis according to satiety. The genetic regulation of leptin should similarly be episodic.

Methodology

Data from three mouse cohorts hosted by the Jackson Laboratory– 402 (174F, 228M) F₂ Dilute Brown non-Agouti (DBA/2)×DU6i intercrosses, 142 Non Obese Diabetic (NOD/ShiLtJ×(NOD/ShiLtJ×129S1/SvImJ.H2^g7) N₂ backcross females, and 204 male Nonobese Nondiabetic (NON)×New Zealand Obese (NZO/HlLtJ) reciprocal backcrosses–were used to test for loci associated with absolute residuals in plasma leptin and arcsin-transformed percent fat (‘phenotypic dispersion’; PD_pLep and PD_AFP). Individual data from 1,780 mice from 43 inbred strains was also used to estimate genetic variances and covariances for dispersion in each trait.

Principal findings

Several loci for PD_pLep were detected, including possibly syntenic Chr 17 loci, but there was only a single position on Chr 6 for PD_AFP. Coding SNP in genes linked to the consensus Chr 17 PD_pLep locus occurred in immunological and cancer genes, genes linked to diabetes and energy regulation, post-transcriptional processors and vomeronasal variants. There was evidence of intersexual differences in the genetic architecture of PD_pLep. PD_pLep had moderate heritability (hs2=0.29) and PD_AFP low heritability (hs2=0.12); dispersion in these traits was highly genetically correlated r = 0.8).

Conclusions

Greater genetic variance for dispersion in plasma leptin, a physiological trait, may reflect its more ephemeral nature compared to body fat, an accrued progressive character. Genetic effects on incidental phenotypes such as leptin might be effectively characterized with randomization-detection methodologies in addition to classical approaches, helping identify incipient or borderline cases or providing new therapeutic targets.

Using tree-based methods for detection of gene-gene interactions in the presence of a polygenic signal: simulation study with application to educational attainment in the Generation Scotland Cohort Study

Motivation

The genomic architecture of human complex diseases is thought to be attributable to single markers, polygenic components and epistatic components. No study has examined the ability of tree-based methods to detect epistasis in the presence of a polygenic signal. We sought to apply decision tree-based methods, C5.0 and logic regression, to detect epistasis under several simulated conditions, varying strength of interaction and linkage disequilibrium (LD) structure. We then applied the same methods to the phenotype of educational attainment in a large population cohort.

Results

LD pruning improved the power and reduced the type I error. C5.0 had a conservative type I error rate whereas logic regression had a type I error rate that exceeded 5%. Despite the more conservative type I error, C5.0 was observed to have higher power than logic regression across several conditions. In the presence of a polygenic signal, power was generally reduced. Applying both methods on educational attainment in a large population cohort yielded numerous interacting SNPs; notably a SNP in RCAN3 which is associated with reading and spelling and a SNP in NPAS3, a neurodevelopmental gene.

Availability and implementation

All methods used are implemented and freely available in R.

Supplementary information

Supplementary data are available at Bioinformatics online.

Dusp6 is a genetic modifier of growth through enhanced ERK activity

Like other single-gene disorders, muscular dystrophy displays a range of phenotypic heterogeneity even with the same primary mutation. Identifying genetic modifiers capable of altering the course of muscular dystrophy is one approach to deciphering gene-gene interactions that can be exploited for therapy development. To this end, we used an intercross strategy in mice to map modifiers of muscular dystrophy. We interrogated genes of interest in an interval on mouse chromosome 10 associated with body mass in muscular dystrophy as skeletal muscle contributes significantly to total body mass. Using whole-genome sequencing of the two parental mouse strains combined with deep RNA sequencing, we identified the Met62Ile substitution in the dual-specificity phosphatase 6 (Dusp6) gene from the DBA/2 J (D2) mouse strain. DUSP6 is a broadly expressed dual-specificity phosphatase protein, which binds and dephosphorylates extracellular-signal-regulated kinase (ERK), leading to decreased ERK activity. We found that the Met62Ile substitution reduced the interaction between DUSP6 and ERK resulting in increased ERK phosphorylation and ERK activity. In dystrophic muscle, DUSP6 Met62Ile is strongly upregulated to counteract its reduced activity. We found that myoblasts from the D2 background were insensitive to a specific small molecule inhibitor of DUSP6, while myoblasts expressing the canonical DUSP6 displayed enhanced proliferation after exposure to DUSP6 inhibition. These data identify DUSP6 as an important regulator of ERK activity in the setting of muscle growth and muscular dystrophy.

Mapping novel genetic loci associated with female liver weight variations using Collaborative Cross mice

BACKGROUND

Liver weight is a complex trait, controlled by polygenic factors and differs within populations. Dissecting the genetic architecture underlying these variations will facilitate the search for key role candidate genes involved directly in the hepatomegaly process and indirectly involved in related diseases etiology.

METHODS

Liver weight of 506 mice generated from 39 different Collaborative Cross (CC) lines with both sexes at age 20 weeks old was determined using an electronic balance. Genomic DNA of the CC lines was genotyped with high-density single nucleotide polymorphic markers.

RESULTS

Statistical analysis revealed a significant (P < 0.05) variation of liver weight between the CC lines, with broad sense heritability (H 2) of 0.32 and genetic coefficient of variation (CVG) of 0.28. Subsequently, quantitative trait locus (QTL) mapping was performed, and results showed a significant QTL only for females on chromosome 8 at genomic interval 88.61-93.38 Mb (4.77 Mb). Three suggestive QTL were mapped at chromosomes 4, 12 and 13. The four QTL were designated as LWL1-LWL4 referring to liver weight loci 1-4 on chromosomes 8, 4, 12 and 13, respectively.

CONCLUSION

To our knowledge, this report presents, for the first time, the utilization of the CC for mapping QTL associated with baseline liver weight in mice. Our findings demonstrate that liver weight is a complex trait controlled by multiple genetic factors that differ significantly between sexes.

Adiposity QTL Adip20 decomposes into at least four loci when dissected using congenic strains

An average mouse in midlife weighs between 25 and 30 g, with about a gram of tissue in the largest adipose depot (gonadal), and the weight of this depot differs between inbred strains. Specifically, C57BL/6ByJ mice have heavier gonadal depots on average than do 129P3/J mice. To understand the genetic contributions to this trait, we mapped several quantitative trait loci (QTLs) for gonadal depot weight in an F2 intercross population. Our goal here was to fine-map one of these QTLs, Adip20 (formerly Adip5), on mouse chromosome 9. To that end, we analyzed the weight of the gonadal adipose depot from newly created congenic strains. Results from the sequential comparison method indicated at least four rather than one QTL; two of the QTLs were less than 0.5 Mb apart, with opposing directions of allelic effect. Different types of evidence (missense and regulatory genetic variation, human adiposity/body mass index orthologues, and differential gene expression) implicated numerous candidate genes from the four QTL regions. These results highlight the value of mouse congenic strains and the value of this sequential method to dissect challenging genetic architecture.

Additive genetic variation in the craniofacial skeleton of baboons (genus Papio) and its relationship to body and cranial size

OBJECTIVES

Determining the genetic architecture of quantitative traits and genetic correlations among them is important for understanding morphological evolution patterns. We address two questions regarding papionin evolution: (1) what effect do body and cranial size, age, and sex have on phenotypic (V_P ) and additive genetic (V_A ) variation in baboon crania, and (2) how might additive genetic correlations between craniofacial traits and body mass affect morphological evolution?

MATERIALS AND METHODS

We use a large captive pedigreed baboon sample to estimate quantitative genetic parameters for craniofacial dimensions (EIDs). Our models include nested combinations of the covariates listed above. We also simulate the correlated response of a given EID due to selection on body mass alone.

RESULTS

Covariates account for 1.2-91% of craniofacial V_P . EID V_A decreases across models as more covariates are included. The median genetic correlation estimate between each EID and body mass is 0.33. Analysis of the multivariate response to selection reveals that observed patterns of craniofacial variation in extant baboons cannot be attributed solely to correlated response to selection on body mass, particularly in males.

DISCUSSION

Because a relatively large proportion of EID V_A is shared with body mass variation, different methods of correcting for allometry by statistically controlling for size can alter residual V_P patterns. This may conflate direct selection effects on craniofacial variation with those resulting from a correlated response to body mass selection. This shared genetic variation may partially explain how selection for increased body mass in two different papionin lineages produced remarkably similar craniofacial phenotypes.

Body Composition QTLs Identified in Intercross Populations Are Reproducible in Consomic Mouse Strains

Genetic variation contributes to individual differences in obesity, but defining the exact relationships between naturally occurring genotypes and their effects on fatness remains elusive. As a step toward positional cloning of previously identified body composition quantitative trait loci (QTLs) from F2 crosses of mice from the C57BL/6ByJ and 129P3/J inbred strains, we sought to recapture them on a homogenous genetic background of consomic (chromosome substitution) strains. Male and female mice from reciprocal consomic strains originating from the C57BL/6ByJ and 129P3/J strains were bred and measured for body weight, length, and adiposity. Chromosomes 2, 7, and 9 were selected for substitution because previous F2 intercross studies revealed body composition QTLs on these chromosomes. We considered a QTL confirmed if one or both sexes of one or both reciprocal consomic strains differed significantly from the host strain in the expected direction after correction for multiple testing. Using these criteria, we confirmed two of two QTLs for body weight (Bwq5-6), three of three QTLs for body length (Bdln3-5), and three of three QTLs for adiposity (Adip20, Adip26 and Adip27). Overall, this study shows that despite the biological complexity of body size and composition, most QTLs for these traits are preserved when transferred to consomic strains; in addition, studying reciprocal consomic strains of both sexes is useful in assessing the robustness of a particular QTL.

Genetic Regulation of Female Sexual Maturation and Longevity Through Circulating IGF1

We previously reported that insulin-like growth factor 1 (IGF1) was involved in coregulating female sexual maturation and longevity. To understand the underlying genetic mechanisms, based on the strain survey assays of development and aging traits, we crossed two mouse strains, KK/HIJ and PL/J, and produced 307 female F2 mice. We observed the age of vaginal patency (AVP) and the life span of these females. We also measured circulating IGF1 level at 7, 16, 24, 52, and 76 weeks. IGF1 level at 7 weeks significantly correlated with AVP. IGF1 levels at ages of 52 and 76 weeks negatively correlated with longevity (p ≤ .05). A gene mapping study found 22, 4 ,and 3 quantitative trait loci for IGF1, AVP, and life span, respectively. Importantly, the colocalization of IGF1, AVP, and life span quantitative trait loci in the distal region of chromosome 2 suggests this locus carries gene(s) that could regulate IGF1, AVP, and life span. In this region, proprotein convertase subtilisin/kexin type 2 has been found to be associated with female sexual maturation in a human genome-wide association study. We verified the roles of proprotein convertase subtilisin/kexin type 2 in regulating IGF1 and AVP by showing that depletion of proprotein convertase subtilisin/kexin type 2 significantly reduced IGF1 and delayed AVP in mice, suggesting that it also might be involved in the regulation of aging.

Discovery and refinement of muscle weight QTLs in B6 × D2 advanced intercross mice

The genes underlying variation in skeletal muscle mass are poorly understood. Although many quantitative trait loci (QTLs) have been mapped in crosses of mouse strains, the limited resolution inherent in these conventional studies has made it difficult to reliably pinpoint the causal genetic variants. The accumulated recombination events in an advanced intercross line (AIL), in which mice from two inbred strains are mated at random for several generations, can improve mapping resolution. We demonstrate these advancements in mapping QTLs for hindlimb muscle weights in an AIL (n = 832) of the C57BL/6J (B6) and DBA/2J (D2) strains, generations F8-F13. We mapped muscle weight QTLs using the high-density MegaMUGA SNP panel. The QTLs highlight the shared genetic architecture of four hindlimb muscles and suggest that the genetic contributions to muscle variation are substantially different in males and females, at least in the B6D2 lineage. Out of the 15 muscle weight QTLs identified in the AIL, nine overlapped the genomic regions discovered in an earlier B6D2 F2 intercross. Mapping resolution, however, was substantially improved in our study to a median QTL interval of 12.5 Mb. Subsequent sequence analysis of the QTL regions revealed 20 genes with nonsense or potentially damaging missense mutations. Further refinement of the muscle weight QTLs using additional functional information, such as gene expression differences between alleles, will be important for discerning the causal genes.

Body composition and gene expression QTL mapping in mice reveals imprinting and interaction effects

BACKGROUND

Shifts in body composition, such as accumulation of body fat, can be a symptom of many chronic human diseases; hence, efforts have been made to investigate the genetic mechanisms that underlie body composition. For example, a few quantitative trait loci (QTL) have been discovered using genome-wide association studies, which will eventually lead to the discovery of causal mutations that are associated with tissue traits. Although some body composition QTL have been identified in mice, limited research has been focused on the imprinting and interaction effects that are involved in these traits. Previously, we found that Myostatin genotype, reciprocal cross, and sex interacted with numerous chromosomal regions to affect growth traits.

RESULTS

Here, we report on the identification of muscle, adipose, and morphometric phenotypic QTL (pQTL), translation and transcription QTL (tQTL) and expression QTL (eQTL) by applying a QTL model with additive, dominance, imprinting, and interaction effects. Using an F2 population of 1000 mice derived from the Myostatin-null C57BL/6 and M16i mouse lines, six imprinted pQTL were discovered on chromosomes 6, 9, 10, 11, and 18. We also identified two IGF1 and two Atp2a2 eQTL, which could be important trans-regulatory elements. pQTL, tQTL and eQTL that interacted with Myostatin, reciprocal cross, and sex were detected as well. Combining with the additive and dominance effect, these variants accounted for a large amount of phenotypic variation in this study.

CONCLUSIONS

Our study indicates that both imprinting and interaction effects are important components of the genetic model of body composition traits. Furthermore, the integration of eQTL and traditional QTL mapping may help to explain more phenotypic variation than either alone, thereby uncovering more molecular details of how tissue traits are regulated.

Genetic and genomic analyses of musculoskeletal differences between BEH and BEL strains

Berlin high (BEH) and Berlin low (BEL) strains selected for divergent growth differ threefold in body weight. We aimed at examining muscle mass, which is a major contributor to body weight, by exploring morphological characteristics of the soleus muscle (fiber number and cross sectional area; CSA), by analyzing the transcriptome of the gastrocnemius and by initiating quantitative trait locus (QTL) mapping. BEH muscles were four to eight times larger than those of BEL. In substrain BEH+/+, mutant myostatin was replaced with a wild-type allele; however, BEH+/+muscles still were two to four times larger compared with BEL. BEH soleus muscle fibers were two times more numerous (P < 0.0001) and CSA was two times larger (P < 0.0001) compared with BEL. In addition, soleus femoral attachment anomaly (SFAA) was observed in all BEL mice. One significant (Chr 1) and four suggestive (Chr 3, 4, 6, and 9) muscle weight QTLs were mapped in a 21-day-old F2 intercross (n = 296) between BEH and BEL strains. The frequency of SFAA incidence in the F2 and in the backcross to BEL strain (BCL) suggested the presence of more than one causative gene. Two suggestive SFAA QTLs were mapped in BCL; however, their peak markers were not associated with the phenotype in F2. RNA-Seq analysis revealed 2,148 differentially expressed (P < 0.1) genes and 45,673 single nucleotide polymorphisms and >2,000 indels between BEH+/+ and BEL males. In conclusion, contrasting muscle traits and genomic and gene expression differences between BEH and BEL strains provide a promising model for the search for genes involved in muscle growth and musculoskeletal morphogenesis.

ATR-FTIR spectroscopy reveals genomic loci regulating the tissue response in high fat diet fed BXD recombinant inbred mouse strains

Background

Obesity-associated organ-specific pathological states can be ensued from the dysregulation of the functions of the adipose tissues, liver and muscle. However, the influence of genetic differences underlying gross-compositional differences in these tissues is largely unknown. In the present study, the analytical method of ATR-FTIR spectroscopy has been combined with a genetic approach to identify genetic differences responsible for phenotypic alterations in adipose, liver and muscle tissues.

Results

Mice from 29 BXD recombinant inbred mouse strains were put on high fat diet and gross-compositional changes in adipose, liver and muscle tissues were measured by ATR-FTIR spectroscopy. The analysis of genotype-phenotype correlations revealed significant quantitative trait loci (QTL) on chromosome 12 for the content of fat and collagen, collagen integrity, and the lipid to protein ratio in adipose tissue and on chromosome 17 for lipid to protein ratio in liver. Using gene expression and sequence information, we suggest Rsad2 (viperin) and Colec11 (collectin-11) on chromosome 12 as potential quantitative trait candidate genes. Rsad2 may act as a modulator of lipid droplet contents and lipid biosynthesis; Colec11 might play a role in apoptopic cell clearance and maintenance of adipose tissue. An increased level of Rsad2 transcripts in adipose tissue of DBA/2J compared to C57BL/6J mice suggests a cis-acting genetic variant leading to differential gene activation.

Conclusion

The results demonstrate that the analytical method of ATR-FTIR spectroscopy effectively contributed to decompose the macromolecular composition of tissues that accumulate fat and to link this information with genetic determinants. The candidate genes in the QTL regions may contribute to obesity-related diseases in humans, in particular if the results can be verified in a bigger BXD cohort.

Positional cloning of diabetes genes

Several mouse strains are diabetic already at the juvenile age or develop diabetes mellitus during their life. Before these strains become diabetic, they often show several or all features of the metabolic syndrome, which is very similar to the etiology of diabetes in humans. Under the assumption that natural mutations are responsible for the development of diabetes in those mouse strains, they are valuable resources for the identification of diabetes genes and modifiers. Usually, several steps are necessary to detect the causative genes in the genome. These include the initial identification of the genomic regions contributing to the disease which is typically done by linkage mapping in an F(2) intercross or backcross population, fine mapping of the identified chromosomal interval to narrow down the target region carrying the causative genetic variation and subsequent functional and genetic characterization of the target gene or a small subset of genes. Here, we give a general overview on genetic models and the strategy for identifying diabetes genes and provide a specific protocol for the mapping and fine mapping of chromosomal regions carrying diabetes genes.

Resolving candidate genes of mouse skeletal muscle QTL via RNA-Seq and expression network analyses

Background

We have recently identified a number of Quantitative Trait Loci (QTL) contributing to the 2-fold muscle weight difference between the LG/J and SM/J mouse strains and refined their confidence intervals. To facilitate nomination of the candidate genes responsible for these differences we examined the transcriptome of the tibialis anterior (TA) muscle of each strain by RNA-Seq.

Results

13,726 genes were expressed in mouse skeletal muscle. Intersection of a set of 1061 differentially expressed transcripts with a mouse muscle Bayesian Network identified a coherent set of differentially expressed genes that we term the LG/J and SM/J Regulatory Network (LSRN). The integration of the QTL, transcriptome and the network analyses identified eight key drivers of the LSRN (Kdr, Plbd1, Mgp, Fah, Prss23, 2310014F06Rik, Grtp1, Stk10) residing within five QTL regions, which were either polymorphic or differentially expressed between the two strains and are strong candidates for quantitative trait genes (QTGs) underlying muscle mass. The insight gained from network analysis including the ability to make testable predictions is illustrated by annotating the LSRN with knowledge-based signatures and showing that the SM/J state of the network corresponds to a more oxidative state. We validated this prediction by NADH tetrazolium reductase staining in the TA muscle revealing higher oxidative potential of the SM/J compared to the LG/J strain (p<0.03).

Conclusion

Thus, integration of fine resolution QTL mapping, RNA-Seq transcriptome information and mouse muscle Bayesian Network analysis provides a novel and unbiased strategy for nomination of muscle QTGs.

Quantitative trait locus mapping of genes that control body length and plasma insulin-like growth factor 1 level in mice

BACKGROUND

The Ay allele at the agouti locus causes obesity and promotes linear growth in mice. The effect of the Ay allele on obesity has been extensively investigated, whereas its effect on body length is only poorly analyzed. To gain insight into the genetic control of body length, quantitative trait locus (QTL) analysis was performed in F2 female mice produced by crossing C57BL/6 J females and DDD.Cg-Ay males. A congenic DDD.Cg-Ay strain was established by introgressing the Ay allele from the B6.Cg-Ay strain by backcrossing for 12 generations. DDD.Cg-Ay females were longer than B6.Cg-Ay females; therefore, QTLs that interact with the Ay allele may be identified for body length. In addition, QTL analysis was also performed for plasma insulin-like growth factor 1 (IGF1) levels because IGF1 is known to play essential roles in growth and development. If QTLs for IGF1 levels coincide with those for body length, we can gain endocrinological insight into the QTLs for body length.

RESULTS

Correlations between body length and IGF1 levels were statistically significant in F2 populations. For body length, two significant QTLs were identified on chromosomes 15 and 17. For IGF1 levels, three significant QTLs were identified on chromosomes 10, 12, and 19. QTLs on chromosomes 12 and 19 appeared to be novel, and the latter interacted with the Ay allele.

CONCLUSION

QTLs for body length and IGF1 levels contained candidate genes that were components of the growth hormone/insulin-like growth factor axis. However, there was no overlap between QTLs for these two traits. Contrary to our expectations, QTLs that interacted with the Ay allele were identified not for body length but for IGF1 levels. Body length and IGF1 levels were, thus, controlled by different sets of genes.

Extrinsic and intrinsic regulation of DOR/TP53INP2 expression in mice: effects of dietary fat content, tissue type and sex in adipose and muscle tissues

Background

DOR/TP53INP2 acts both at the chromosomal level as a nuclear co-factor e.g. for the thyroid hormone receptor and at the extrachromosomal level as an organizing factor of the autophagosome. In a previous study, DOR was shown to be down-regulated in skeletal muscle of obese diabetic Zucker fa/fa rats.

Methods

To identify sites of differential DOR expression in metabolically active tissues, we measured differences in DOR expression in white adipose tissue (WAT), brown adipose tissue (BAT), skeletal muscle (SM) and heart muscle (HM) by qPCR. To assess whether DOR expression is influenced in the short term by nutritional factors, NMRI mice were fed different fat rich diets (fat diet, FD: 18% or high fat diet, HFD: 80% fat) for one week and DOR expression was compared to NMRI mice fed a control diet (normal diet, ND: 3.3% fat). Additionally, DOR expression was measured in young (45 days old) and adult (100 days old) genetically obese (DU6/DU6i) mice and compared to control (DUKs/DUKsi) animals.

Results

ANOVA results demonstrate a significant influence of diet, tissue type and sex on DOR expression in adipose and muscle tissues of FD and HFD mice. In SM, DOR expression was higher in HFD than in FD male mice. In WAT, DOR expression was increased compared to BAT in male FD and HFD mice. In contrast, expression levels in female mice were higher in BAT for both dietary conditions.

DOR expression levels in all tissues of 100 days old genetically obese animals were mainly influenced by sex. In HM, DOR expression was higher in male than female animals.

Conclusions

DOR expression varies under the influence of dietary fat content, tissue type and sex. We identified target tissues for further studies to analyze the specific function of DOR in obesity. DOR might be part of a defense mechanism against fat storage in high fat diets or obesity.

The Human Obesity Gene Map: The 2003 Update

This is the tenth update of the human obesity gene map, incorporating published results up to the end of October 2003 and continuing the previous format. Evidence from single-gene mutation obesity cases, Mendelian disorders exhibiting obesity as a clinical feature, quantitative trait loci (QTLs) from human genome-wide scans and animal crossbreeding experiments, and association and linkage studies with candidate genes and other markers is reviewed. Transgenic and knockout murine models relevant to obesity are also incorporated (N = 55). As of October 2003, 41 Mendelian syndromes relevant to human obesity have been mapped to a genomic region, and causal genes or strong candidates have been identified for most of these syndromes. QTLs reported from animal models currently number 183. There are 208 human QTLs for obesity phenotypes from genome-wide scans and candidate regions in targeted studies. A total of 35 genomic regions harbor QTLs replicated among two to five studies. Attempts to relate DNA sequence variation in specific genes to obesity phenotypes continue to grow, with 272 studies reporting positive associations with 90 candidate genes. Fifteen such candidate genes are supported by at least five positive studies. The obesity gene map shows putative loci on all chromosomes except Y. Overall, more than 430 genes, markers, and chromosomal regions have been associated or linked with human obesity phenotypes. The electronic version of the map with links to useful sites can be found at http://obesitygene.pbrc.edu.

The Human Obesity Gene Map: The 2004 Update

This paper presents the eleventh update of the human obesity gene map, which incorporates published results up to the end of October 2004. Evidence from single-gene mutation obesity cases, Mendelian disorders exhibiting obesity as a clinical feature, transgenic and knockout murine models relevant to obesity, quantitative trait loci (QTLs) from animal cross-breeding experiments, association studies with candidate genes, and linkages from genome scans is reviewed. As of October 2004, 173 human obesity cases due to single-gene mutations in 10 different genes have been reported, and 49 loci related to Mendelian syndromes relevant to human obesity have been mapped to a genomic region, and causal genes or strong candidates have been identified for most of these syndromes. There are 166 genes which, when mutated or expressed as transgenes in the mouse, result in phenotypes that affect body weight and adiposity. The number of QTLs reported from animal models currently reaches 221. The number of human obesity QTLs derived from genome scans continues to grow, and we have now 204 QTLs for obesity-related phenotypes from 50 genome-wide scans. A total of 38 genomic regions harbor QTLs replicated among two to four studies. The number of studies reporting associations between DNA sequence variation in specific genes and obesity phenotypes has also increased considerably with 358 findings of positive associations with 113 candidate genes. Among them, 18 genes are supported by at least five positive studies. The obesity gene map shows putative loci on all chromosomes except Y. Overall, >600 genes, markers, and chromosomal regions have been associated or linked with human obesity phenotypes. The electronic version of the map with links to useful publications and genomic and other relevant sites can be found at http://obesitygene.pbrc.edu.

Genomic imprinting and genetic effects on muscle traits in mice

BACKGROUND

Genomic imprinting refers to parent-of-origin dependent gene expression caused by differential DNA methylation of the paternally and maternally derived alleles. Imprinting is increasingly recognized as an important source of variation in complex traits, however, its role in explaining variation in muscle and physiological traits, especially those of commercial value, is largely unknown compared with genetic effects.

RESULTS

We investigated both genetic and genomic imprinting effects on key muscle traits in mice from the Berlin Muscle Mouse population, a key model system to study muscle traits. Using a genome scan, we first identified loci with either imprinting or genetic effects on phenotypic variation. Next, we established the proportion of phenotypic variation explained by additive, dominance and imprinted QTL and characterized the patterns of effects. In total, we identified nine QTL, two of which show large imprinting effects on glycogen content and potential, and body weight. Surprisingly, all imprinting patterns were of the bipolar type, in which the two heterozygotes are different from each other but the homozygotes are not. Most QTL had pleiotropic effects and explained up to 40% of phenotypic variance, with individual imprinted loci accounting for 4-5% of variation alone.

CONCLUSION

Surprisingly, variation in glycogen content and potential was only modulated by imprinting effects. Further, in contrast to general assumptions, our results show that genomic imprinting can impact physiological traits measured at adult stages and that the expression does not have to follow the patterns of paternal or maternal expression commonly ascribed to imprinting effects.

Extensive epistasis for olfactory behaviour, sleep and waking activity in Drosophila melanogaster

Epistasis is an important feature of the genetic architecture of quantitative traits, but the dynamics of epistatic interactions in natural populations and the relationship between epistasis and pleiotropy remain poorly understood. Here, we studied the effects of epistatic modifiers that segregate in a wild-derived Drosophila melanogaster population on the mutational effects of P-element insertions in Semaphorin-5C (Sema-5c) and Calreticulin (Crc), pleiotropic genes that affect olfactory behaviour and startle behaviour and, in the case of Crc, sleep phenotypes. We introduced Canton-S B (CSB) third chromosomes with or without a P-element insertion at the Crc or Sema-5c locus in multiple wild-derived inbred lines of the Drosophila melanogaster Genetic Reference Panel (DGRP) and assessed the effects of epistasis on the olfactory response to benzaldehyde and, for Crc, also on sleep. In each case, we found substantial epistasis and significant variation in the magnitude of epistasis. The predominant direction of epistatic effects was to suppress the mutant phenotype. These observations support a previous study on startle behaviour using the same D. melanogaster chromosome substitution lines, which concluded that suppressing epistasis may buffer the effects of new mutations. However, epistatic effects are not correlated among the different phenotypes. Thus, suppressing epistasis appears to be a pervasive general feature of natural populations to protect against the effects of new mutations, but different epistatic interactions modulate different phenotypes affected by mutations at the same pleiotropic gene.

QTL Analysis of Type I and Type IIA Fibers in Soleus Muscle in a Cross between LG/J and SM/J Mouse Strains

Properties of muscle fibers, i.e., their type, number and size, are important determinants of functional characteristics of skeletal muscle, and of the quality of meat in livestock. Genetic factors play an important role in determining variation in fiber properties, however, specific genes remain largely elusive. We examined histological properties of soleus muscle fibers in two strains of mice exhibiting a twofold difference in muscle mass, LG/J and SM/J, and their F2 intercross. The total number of muscle fibers (555 ± 106; mean ± SD) did not differ between the strains or between males and females. A higher percentage of type I fibers was observed in the LG/J compared to the SM/J strain (P < 0.001) in both males (45 ± 3 vs. 37 ± 4%) and females (58 ± 4 vs. 41 ± 3%). Across strains, females had a higher percentage of type I fibers than males (P < 0.001), and the sex effect was greater in the LG/J strain (strain-by-sex interaction, P < 0.001). The cross-sectional area (CSA) did not differ between type I and type IIA fibers, but was greater in the LG/J than the SM/J strain (1365 ± 268 vs. 825 ± 229 μm(2), P < 0.001). Three significant quantitative trait locus (QTL) affecting CSA for type I and type IIA fibers mapped to chromosomes (Chr) 1, 6, and 11 and three suggestive QTL for percentage of type I fibers mapped to Chr 2, 3, and 4. Within each significant QTL, regions of conserved synteny were also implicated in variation of similar traits in an analogous study in pigs. Our results provide the evidence that the intercross between the SM/J and LG/J strains is a promising model to search for genes affecting muscle fiber properties.

Sex-, diet-, and cancer-dependent epistatic effects on complex traits in mice

The genetic basis of quantitative traits such as body weight and obesity is complex, with several hundred quantitative trait loci (QTLs) known to affect these and related traits in humans and mice. It also has become increasingly evident that the single-locus effects of these QTLs vary considerably depending on factors such as the sex of the individuals and their dietary environment, and we were interested to know whether this context-dependency also applies to two-locus epistatic effects of QTLs as well. We therefore conducted a genome scan to search for epistatic effects on 13 different weight and adiposity traits in an F₂ population of mice (created from an original intercross of the FVB strain with M16i, a polygenic obesity model) that were fed either a control or a high-fat diet and half of which harbored a transgene (PyMT) that caused the development of metastatic mammary cancer. We used a conventional interval mapping approach with SNPs to scan all 19 autosomes, and found extensive epistasis affecting all of these traits. More importantly, we also discovered that the majority of these epistatic effects exhibited significant interactions with sex, diet, and/or presence of PyMT. Analysis of these interactions showed that many of them appeared to involve QTLs previously identified as affecting these traits, but whose single-locus effects were variously modified by two-locus epistatic effects of other QTLs depending on the sex, diet, or PyMT environment. It was concluded that this context-dependency of epistatic effects is an important component of the genetic architecture of complex traits such as those contributing to weight and obesity.

Metabolic responses to high-fat diets rich in n-3 or n-6 long-chain polyunsaturated fatty acids in mice selected for either high body weight or leanness explain different health outcomes

Background

Increasing evidence suggests that diets high in polyunsaturated fatty acids (PUFA) confer health benefits by improving insulin sensitivity and lipid metabolism in liver, muscle and adipose tissue.

Methods

The present study investigates metabolic responses in two different lines of mice either selected for high body weight (DU6) leading to rapid obesity development, or selected for high treadmill performance (DUhTP) leading to a lean phenotype. At 29 days of age the mice were fed standard chow (7.2% fat, 25.7% protein), or a high-fat diet rich in n-3 PUFA (n-3 HFD, 27.7% fat, 19% protein) or a high-fat diet rich in n-6 PUFA (n-6 HFD, 27.7% fat, 18.6% protein) for 8 weeks. The aim of the study was to determine the effect of these PUFA-rich high-fat diets on the fatty acid profile and on the protein expression of key components of insulin signalling pathways.

Results

Plasma concentrations of leptin and insulin were higher in DU6 in comparison with DUhTP mice. The high-fat diets stimulated a strong increase in leptin levels and body fat only in DU6 mice. Muscle and liver fatty acid composition were clearly changed by dietary lipid composition. In both lines of mice n-3 HFD feeding significantly reduced the hepatic insulin receptor β protein concentration which may explain decreased insulin action in liver. In contrast, protein kinase C ζ expression increased strongly in abdominal fat of n-3 HFD fed DUhTP mice, indicating enhanced insulin sensitivity in adipose tissue.

Conclusions

A diet high in n-3 PUFA may facilitate a shift from fuel deposition in liver to fuel storage as fat in adipose tissue in mice. Tissue specific changes in insulin sensitivity may describe, at least in part, the health improving properties of dietary n-3 PUFA. However, important genotype-diet interactions may explain why such diets have little effect in some population groups.

Mapping genetic loci that interact with myostatin to affect growth traits

Myostatin, or GDF8, is an inhibitor of skeletal muscle growth. A non-functional myostatin mutation leads to a double muscling phenotype in some species, for example, mice, cattle and humans. Previous studies have indicated that there are loci in the genome that interact with myostatin to control backfat depth and other complex traits. We now report a quantitative trait loci (QTL) mapping study designed to identify loci that interact with myostatin to impact growth traits in mice. Body weight and average daily gain traits were collected on F2 progeny derived from a myostatin-null C57BL/6 strain by M16i cross. In all, 44 main effect QTL were detected above a 5% genome-wide significance threshold when an interval mapping method was used. An additional 37 QTL were identified to significantly interact with myostatin, sex or reciprocal cross. A total of 12 of these QTL interacted with myostatin genotype. These results provide a foundation for the further fine mapping of genome regions that harbor loci that interact with myostatin.

Body fat distribution and organ weights of 14 common strains and a 22-strain consomic panel of rats

The goal of this study was to determine the adiposity of a range of rat strains, including a panel of consomics, to estimate heritability. To that end, we assessed the body fat distribution and organ weights of groups of adult male rats from 3 outbred strains, 11 inbred strains and 22 consomic strains. We measured the weights of the gonadal, retroperitoneal, mesenteric, femoral, subscapular and pericardial white fat depots, the subscapular brown fat depot, the kidneys, liver, heart, spleen, and brain. Strains were compared for the measured weight of each of these adipose depots and organs, and also for these weights adjusted statistically for body size. All individual adipose depot and organ weights were highly heritable, in most cases h(2)>0.50. The fourteen inbred and outbred rat strains were not very different in body length but there was a three-fold difference in body weight, and up to a twenty-fold difference in the weight of some adipose depots. Comparison of the FHH-Chr n(BN) consomic strains with the FHH host strain revealed 98 quantitative trait loci (QTLs) for body composition and organ weight, with the introgressed chromosome reducing weight or adiposity in most cases. These results can be used to guide the choice of appropriate rat strains for future studies of the genetic architecture of obesity and body size.

Genetic analysis of complex traits in the emerging Collaborative Cross

The Collaborative Cross (CC) is a mouse recombinant inbred strain panel that is being developed as a resource for mammalian systems genetics. Here we describe an experiment that uses partially inbred CC lines to evaluate the genetic properties and utility of this emerging resource. Genome-wide analysis of the incipient strains reveals high genetic diversity, balanced allele frequencies, and dense, evenly distributed recombination sites-all ideal qualities for a systems genetics resource. We map discrete, complex, and biomolecular traits and contrast two quantitative trait locus (QTL) mapping approaches. Analysis based on inferred haplotypes improves power, reduces false discovery, and provides information to identify and prioritize candidate genes that is unique to multifounder crosses like the CC. The number of expression QTLs discovered here exceeds all previous efforts at eQTL mapping in mice, and we map local eQTL at 1-Mb resolution. We demonstrate that the genetic diversity of the CC, which derives from random mixing of eight founder strains, results in high phenotypic diversity and enhances our ability to map causative loci underlying complex disease-related traits.

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.

Epistatic QTL pairs associated with meat quality and carcass composition traits in a porcine Duroc × Pietrain population

Background

Quantitative trait loci (QTL) analyses in pig have revealed numerous individual QTL affecting growth, carcass composition, reproduction and meat quality, indicating a complex genetic architecture. In general, statistical QTL models consider only additive and dominance effects and identification of epistatic effects in livestock is not yet widespread. The aim of this study was to identify and characterize epistatic effects between common and novel QTL regions for carcass composition and meat quality traits in pig.

Methods

Five hundred and eighty five F₂ pigs from a Duroc × Pietrain resource population were genotyped using 131 genetic markers (microsatellites and SNP) spread over the 18 pig autosomes. Phenotypic information for 26 carcass composition and meat quality traits was available for all F₂ animals. Linkage analysis was performed in a two-step procedure using a maximum likelihood approach implemented in the QxPak program.

Results

A number of interacting QTL was observed for different traits, leading to the identification of a variety of networks among chromosomal regions throughout the porcine genome. We distinguished 17 epistatic QTL pairs for carcass composition and 39 for meat quality traits. These interacting QTL pairs explained up to 8% of the phenotypic variance.

Conclusions

Our findings demonstrate the significance of epistasis in pigs. We have revealed evidence for epistatic relationships between different chromosomal regions, confirmed known QTL loci and connected regions reported in other studies. Considering interactions between loci allowed us to identify several novel QTL and trait-specific relationships of loci within and across chromosomes.

Identification of genetic determinants of IGF-1 levels and longevity among mouse inbred strains

The IGF-1 signaling pathway plays an important role in regulating longevity. To identify the genetic loci and genes that regulate plasma IGF-1 levels, we intercrossed MRL/MpJ and SM/J, inbred mouse strains that differ in IGF-1 levels. Quantitative trait loci (QTL) analysis of IGF-1 levels of these F2 mice detected four QTL on chromosomes (Chrs) 9 (48 Mb), 10 (86 Mb), 15 (18 Mb), and 17 (85 Mb). Haplotype association mapping of IGF-1 levels in 28 domesticated inbred strains identified three suggestive loci in females on Chrs 2 (13 Mb), 10 (88 Mb), and 17 (28 Mb) and in four males on Chrs 1 (159 Mb), 3 (52 and 58 Mb), and 16 (74 Mb). Except for the QTL on Chr 9 and 16, all loci co-localized with IGF-1 QTL previously identified in other mouse crosses. The most significant locus was the QTL on Chr 10, which contains the Igf1 gene and which had a LOD score of 31.8. Haplotype analysis among 28 domesticated inbred strains revealed a major QTL on Chr 10 overlapping with the QTL identified in the F2 mice. This locus showed three major haplotypes; strains with haplotype 1 had significantly lower plasma IGF-1 and extended longevity (P < 0.05) than strains with haplotype 2 or 3. Bioinformatic analysis, combined with sequencing and expression studies, showed that Igf1 is the most likely QTL gene, but that other genes may also play a role in this strong QTL.

Fine-mapping of muscle weight QTL in LG/J and SM/J intercrosses

Genetic variation plays a substantial role in variation in strength, but the underlying mechanisms remain poorly understood. The objective of the present study was to examine the mechanisms underlying variation in muscle mass, a predictor of strength, between LG/J and SM/J strains, which are the inbred progeny of mice selected, respectively, for high and low body weight. We measured weight of five hindlimb muscles in LG/J and SM/J males and females, in F(1) and F(2) intercrosses, and in an advanced intercross (AI), F(34), between the two. F(2) mice were genotyped using 162 SNPs throughout the genome; F(34) mice were genotyped at 3,015 SNPs. A twofold difference in muscle mass between the LG/J and SM/J mouse strains was observed. Integrated genome-wide association analysis in the combined population of F(2) and AI identified 22 quantitative trait loci (QTL; genome-wide P < 0.05) affecting muscle weight on Chr 2 (2 QTL), 4, 5, 6 (7 QTL), 7 (4 QTL), 8 (4 QTL), and 11 (3 QTL). The LG/J allele conferred greater muscle weight in all cases. The 1.5-LOD QTL support intervals ranged between 0.3 and 13.4 Mb (median 3.7 Mb) restricting the list of candidates to between 5 and 97 genes. Selection for body weight segregated the alleles affecting skeletal muscle, the most abundant tissue in the body. Combination of analyses in an F(2) and AI was an effective strategy to detect and refine the QTL in a genome-wide manner. The achieved resolution facilitates further elucidation of the underlying genetic mechanisms affecting muscle mass.

A unique genetic defect on chromosome 3 is responsible for juvenile obesity in the Berlin Fat Mouse

OBJECTIVE

This study aimed at the mapping and estimation of genetic and sex effects contributing to the obese phenotype of the Berlin Fat Mouse Inbred line 860 (BFMI860). This mouse line is predisposed for juvenile obesity. BFMI860 mice accumulate 24% total fat mass at 10 weeks of age under a standard maintenance diet.

DESIGN

A total of 471 mice of a (BFMI860 x C57BL/6NCrl) F₂ intercross population were fed a standard maintenance diet and were analysed for body composition at 10 weeks when they finished their rapid growth phase.

RESULTS

The most striking result was the identification of a novel obesity locus on chromosome 3 (Chr 3) at 40 Mb, explaining 39% of the variance of total fat mass in the F₂ population under a standard diet. This locus was named jObes1 (juvenile obesity 1). The BFMI860 allele effect was recessive. Males and females homozygous at jObes1 had on average 3.0 and 3.3 g more total fat mass at 10 weeks than the other two genotype classes, respectively. The effect was evident in all white adipose tissues, brown adipose tissue and also in liver. The position of the Chr 3 effect is syntenic to an obesity locus in humans. Additional loci for total fat mass and different white adipose tissue weights with minor effects were detected on mouse Chr 5 and 6. Another locus on Chr 4 had influence especially on liver weight. Many loci including jObes1 affected males and females to a different extent.

CONCLUSION

The major locus on Chr 3 for juvenile obesity and its interaction with sex is unique and makes the BFMI860 mice an interesting resource for the discovery of novel genetic factors predisposing obesity, which might also contribute to obesity in humans. The results suggested that metabolic and regulatory pathways differed between the sexes.

Chromosomal mapping of excessive physical activity in mice in response to a restricted feeding schedule

Excessive physical activity plays an important role in the progression of anorexia nervosa (AN) by accelerating weight loss during dietary restriction. To search for mechanisms underlying this trait, a panel of mouse chromosome substitution strains derived from C57BL/6J and A/J strains was exposed to a scheduled feeding paradigm and to voluntary running wheel (RW) access. Here, we showed that A/J chromosomes 4, 12 and 13 contribute to the development of a disrupted RW activity in response to daily restricted feeding. This pattern is characterized by intense RW activity during the habitual rest phase and leads to accelerated body weight loss. Regions on mouse chromosomes 4, 12 and 13 display homology with regions on human chromosomes linked with anxiety and obsessionality in AN cohorts. Therefore, our data open new roads for interspecies genetic studies of AN and for unraveling novel mechanisms and potential effective treatment strategies for these neurobehavioral traits.

Epistatic analysis of carcass characteristics in pigs reveals genomic interactions between quantitative trait loci attributable to additive and dominance genetic effects

The present study focused on the identification of epistatic QTL pairs for body composition traits (carcass cut, lean tissue, and fat tissue weights) measured at slaughter weight (140 kg of BW) in a 3-generation full-sib population developed by crossing Pietrain sires with a crossbred dam line. Depending on the trait, phenotypic observations were available for 306 to 315 F(2) animals. For the QTL analysis, 386 animals were genotyped for 88 molecular markers covering chromosomes SSC1, SSC2, SSC4, SSC6, SSC7, SSC8, SSC9, SSC10, SSC13, and SSC14. In total, 23 significant epistatic QTL pairs were identified, with the additive x additive genetic interaction being the most prevalent. Epistatic QTL were identified across all chromosomes except for SSC13, and epistatic QTL pairs accounted for between 5.8 and 10.2% of the phenotypic variance. Seven epistatic QTL pairs were between QTL that resided on the same chromosome, and 16 were between QTL that resided on different chromosomes. Sus scrofa chromosome 1, SSC2, SSC4, SSC6, SSC8, and SSC9 harbored the greatest number of epistatic QTL. The epistatic QTL pair with the greatest effect was for the entire loin weight between 2 locations on SSC7, explaining 10.2% of the phenotypic variance. Epistatic associations were identified between regions of the genome that contain the IGF-2 or melanocortin-4 receptor genes, with QTL residing in other genomic locations. Quantitative trait loci in the region of the melanocortin-4 receptor gene and on SSC7 showed significant positive dominance effects for entire belly weight, which were offset by negative dominance x dominance interactions between these QTL. In contrast, the QTL in the region of the IGF-2 gene showed significant negative dominance effects for entire ham weight, which were largely overcompensated for by positive additive x dominance genetic effects with a QTL on SSC9. The study shows that epistasis is of great importance for the genomic regulation of body composition in pigs and contributes substantially to the variation in complex traits.

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.

Mapping main, epistatic and sex-specific QTL for body composition in a chicken population divergently selected for low or high growth rate

Background

Delineating the genetic basis of body composition is important to agriculture and medicine. In addition, the incorporation of gene-gene interactions in the statistical model provides further insight into the genetic factors that underlie body composition traits. We used Bayesian model selection to comprehensively map main, epistatic and sex-specific QTL in an F₂ reciprocal intercross between two chicken lines divergently selected for high or low growth rate.

Results

We identified 17 QTL with main effects across 13 chromosomes and several sex-specific and sex-antagonistic QTL for breast meat yield, thigh + drumstick yield and abdominal fatness. Different sets of QTL were found for both breast muscles [Pectoralis (P) major and P. minor], which suggests that they could be controlled by different regulatory mechanisms. Significant interactions of QTL by sex allowed detection of sex-specific and sex-antagonistic QTL for body composition and abdominal fat. We found several female-specific P. major QTL and sex-antagonistic P. minor and abdominal fatness QTL. Also, several QTL on different chromosomes interact with each other to affect body composition and abdominal fatness.

Conclusions

The detection of main effects, epistasis and sex-dimorphic QTL suggest complex genetic regulation of somatic growth. An understanding of such regulatory mechanisms is key to mapping specific genes that underlie QTL controlling somatic growth in an avian model.

A bi-dimensional genome scan for prolificacy traits in pigs shows the existence of multiple epistatic QTL

BACKGROUND

Prolificacy is the most important trait influencing the reproductive efficiency of pig production systems. The low heritability and sex-limited expression of prolificacy have hindered to some extent the improvement of this trait through artificial selection. Moreover, the relative contributions of additive, dominant and epistatic QTL to the genetic variance of pig prolificacy remain to be defined. In this work, we have undertaken this issue by performing one-dimensional and bi-dimensional genome scans for number of piglets born alive (NBA) and total number of piglets born (TNB) in a three generation Iberian by Meishan F(2) intercross.

RESULTS

The one-dimensional genome scan for NBA and TNB revealed the existence of two genome-wide highly significant QTL located on SSC13 (P < 0.001) and SSC17 (P < 0.01) with effects on both traits. This relative paucity of significant results contrasted very strongly with the wide array of highly significant epistatic QTL that emerged in the bi-dimensional genome-wide scan analysis. As much as 18 epistatic QTL were found for NBA (four at P < 0.01 and five at P < 0.05) and TNB (three at P < 0.01 and six at P < 0.05), respectively. These epistatic QTL were distributed in multiple genomic regions, which covered 13 of the 18 pig autosomes, and they had small individual effects that ranged between 3 to 4% of the phenotypic variance. Different patterns of interactions (a x a, a x d, d x a and d x d) were found amongst the epistatic QTL pairs identified in the current work.

CONCLUSIONS

The complex inheritance of prolificacy traits in pigs has been evidenced by identifying multiple additive (SSC13 and SSC17), dominant and epistatic QTL in an Iberian x Meishan F(2) intercross. Our results demonstrate that a significant fraction of the phenotypic variance of swine prolificacy traits can be attributed to first-order gene-by-gene interactions emphasizing that the phenotypic effects of alleles might be strongly modulated by the genetic background where they segregate.

Epistatic interactions attenuate mutations affecting startle behaviour in Drosophila melanogaster

Epistasis is an important feature of the genetic architecture of quantitative traits. Previously, we showed that startle-induced locomotor behaviour of Drosophila melanogaster, a critical survival trait, is highly polygenic and exhibits epistasis. Here, we characterize epistatic interactions among homozygous P-element mutations affecting startle-induced locomotion in the Canton-S isogenic background and in 21 wild-derived inbred genetic backgrounds. We find pervasive epistasis for pairwise combinations of homozygous P-element insertional mutations as well as for mutations in wild-derived backgrounds. In all cases, the direction of the epistatic effects is to suppress the mutant phenotypes. The magnitude of the epistatic interactions in wild-derived backgrounds is highly correlated with the magnitude of the main effects of mutations, leading to phenotypic robustness of the startle response in the face of deleterious mutations. There is variation in the magnitude of epistasis among the wild-derived genetic backgrounds, indicating evolutionary potential for enhancing or suppressing effects of single mutations. These results provide a partial glimpse of the complex genetic network underlying the genetic architecture of startle behaviour and provide empirical support for the hypothesis that suppressing epistasis is the mechanism underlying genetic canalization of traits under strong stabilizing selection. Widespread suppressing epistasis will lead to underestimates of the main effects of quantitative trait loci (QTLs) in mapping experiments when not explicitly accounted for. In addition, suppressing epistasis could lead to underestimates of mutational variation for quantitative traits and overestimates of the strength of stabilizing selection, which has implications for maintenance of variation of complex traits by mutation-selection balance.

A new mouse model of metabolic syndrome and associated complications

Metabolic syndrome (MS) encompasses a clustering of risk factors for cardiovascular disease, including obesity, insulin resistance, and dyslipidemia. We characterized a new mouse model carrying a dominant mutation, C57BL/6J-Nmf15/+ (B6-Nmf15/+), which develops additional complications of MS such as adipose tissue inflammation and cardiomyopathy. A backcross was used to genetically map the Nmf15 locus. Mice were examined in the comprehensive laboratory animal monitoring system, and dual energy X-ray absorptiometry and blood chemistry analyses were performed. Hypothalamic LEPR, SOCS1, and STAT3 phosphorylation were examined. Cardiac function was assessed by echo- and electrocardiography. Adipose tissue inflammation was characterized by in situ hybridization and measurement of Jun kinase activity. The Nmf15 locus mapped to distal mouse chromosome 5 with an LOD (logarithm of odds) score of 13.8. Nmf15 mice developed obesity by 12 weeks of age. Plasma leptin levels were significantly elevated in pre-obese Nmf15 mice at 8 weeks of age and an attenuated STAT3 phosphorylation in the hypothalamus suggests a primary leptin resistance. Adipose tissue from Nmf15 mice showed a remarkable degree of inflammation and macrophage infiltration as indicated by expression of the F4/80 marker and increased phosphorylation of JUN N-terminal kinase 1/2. Lipidosis was observed in tubular epithelial cells and glomeruli of the kidney. Nmf15 mice demonstrate both histological and pathophysiological evidence of cardiomyopathy. The Nmf15 mouse model provides a new entry point into pathways mediating leptin resistance and obesity. It is one of few models that combine many aspects of MS and can be useful for testing new therapeutic approaches for combating obesity complications, particularly cardiomyopathy.

Genes on rat chromosomes 3, 5, 10, and 16 are linked with facets of metabolic syndrome

WOKW (Wistar Ottawa Karlsburg W) rats develop metabolic syndrome closely resembling human disorder. In crossing studies between disease-prone WOKW and disease-resistant DA (Dark Agouti) rats, several quantitative trait loci (QTLs) were mapped. To prove the in vivo relevance of QTLs, congenic DA.WOKW rats, briefly termed DA.3aW, DA.3bW, DA.5W, DA.10W, and DA.16W, were generated by transferring chromosomal regions of WOKW chromosomes 3, 5, 10, and 16 onto DA genetic background. Male (n=12) and female (n=12) rats of each congenic strain and their parental strain DA were characterized for adiposity index (AI), serum leptin, and serum insulin as well as serum cholesterol and serum triglycerides as single facets of metabolic syndrome at the age of 30 weeks. The data showed a significant higher AI for male and female DA.3aW and female DA.16W compared with DA. Serum leptin was significantly elevated in male and female DA.3aW, DA.10W, and DA.16W rats in comparison with DA. Rats of both sexes of DA.10W and female DA.16W showed significantly elevated serum insulin in comparison to DA. Female rats of all congenics had significantly higher serum cholesterol compared with DA, while males did not differ. Finally, triglycerides were only elevated in male DA.16W. The results demonstrate an involvement of WOKW chromosomes 3, 5, 10, and 16 in developing facets of the metabolic syndrome.

Genetic architecture of quantitative traits in mice, flies, and humans

We compare and contrast the genetic architecture of quantitative phenotypes in two genetically well-characterized model organisms, the laboratory mouse, Mus musculus, and the fruit fly, Drosophila melanogaster, with that found in our own species from recent successes in genome-wide association studies. We show that the current model of large numbers of loci, each of small effect, is true for all species examined, and that discrepancies can be largely explained by differences in the experimental designs used. We argue that the distribution of effect size of common variants is the same for all phenotypes regardless of species, and we discuss the importance of epistasis, pleiotropy, and gene by environment interactions. Despite substantial advances in mapping quantitative trait loci, the identification of the quantitative trait genes and ultimately the sequence variants has proved more difficult, so that our information on the molecular basis of quantitative variation remains limited. Nevertheless, available data indicate that many variants lie outside genes, presumably in regulatory regions of the genome, where they act by altering gene expression. As yet there are very few instances where homologous quantitative trait loci, or quantitative trait genes, have been identified in multiple species, but the availability of high-resolution mapping data will soon make it possible to test the degree of overlap between species.

Evidence of maternal QTL affecting growth and obesity in adult mice

Most quantitative trait loci (QTL) studies fail to account for the effect that the maternal genotype may have on an individual's phenotypes, even though maternal effect QTL have been shown to account for considerable variation in growth and obesity traits in mouse models. Moreover, the fetal programming theory suggests that maternal effects influence an offspring's adult fitness, although the genetic nature of fetal programming remains unclear. Within this context, our study focused on mapping genomic regions associated with maternal effect QTL by analyzing the phenotypes of chromosomes 2 and 7 subcongenic mice from genetically distinct dams. We analyzed 12 chromosome 2 subcongenic strains that spanned from 70 to 180 Mb with CAST/EiJ donor regions on the background of C57BL/6 J, and 14 chromosome 7 subcongenic strains that spanned from 81 to 111 Mb with BALB/cByJ donor regions on C57BL/6ByJ background. Maternal QTL analyses were performed on the basis of overlapping donor regions between subcongenic strains. We identified several highly significant (P < 5 x 10(-4)) maternal QTL influencing total body weight, organ weight, and fat pad weights in both sets of subcongenics. These QTL accounted for 1.9-11.7% of the phenotypic variance for growth and obesity and greatly narrowed the genomic regions associated with the maternal genetic effects. These maternal effect QTL controlled phenotypic traits in adult mice, suggesting that maternal influences at early stages of development may permanently affect offspring performance. Identification of maternal effects in our survey of two sets of subcongenic strains, representing approximately 5% of the mouse genome, supports the hypothesis that maternal effects represent significant sources of genetic variation that are largely ignored in genetic studies.

Genetic influences on growth and body composition in mice: multilocus interactions

BACKGROUND

The genetic architecture of body weight and body composition is complex because these traits are normally influenced by multiple genes and their interactions, even after controlling for the environment. Bayesian methodology provides an efficient way of estimating these interactions.

SUBJECTS AND MEASUREMENTS

We used Bayesian model selection techniques to simultaneously estimate the main effects, epistasis and gene-sex interactions on age-related body weight (at 3, 6 and 10 weeks, denoted as WT3wk, WT6wk and WT10wk) and body composition (organ weights and fat-related traits) in an F(2) sample obtained from a cross between high-growth (M16i) mice and low-growth (L6) mice.

RESULTS

We observed epistatic and main-effect quantitative trait loci (QTL) that controlled both body weight and body composition. Epistatic effects were generally more significant for WT6wk than WT10wk. Chromosomes 5 and 13 interacted strongly to control body weight at 3 weeks. A pleiotropic QTL on chromosome 2 was associated with body weight and some body composition phenotypes. Testis weight was regulated by a QTL on chromosome 13 with a significantly large main effect (2log(e)BF approximately 15).

CONCLUSION

By analyzing epistatic interactions, we detected QTL not found in a previous analysis of this mouse population. Hence, the detection of gene-gene interactions may provide new information about the genetic architecture of complex obesity-related traits and may lead to the detection of additional obesity genes.

Animal models of gene-nutrient interactions

Food intake of humans is governed by the food's nutritional value and pleasing taste, but also by other factors such as food cost and availability, cultural imperatives, and social status. The biological determinants of human food intake are not easily parsed from these other factors, making them hard to study against the whirligig aspects of human life in a modern age. The study of animals provides a useful alternative. Humans have a history of studying animal food intake, for agricultural reasons (e.g., pigs and cows), and for personal reasons (e.g., dogs and cats), and these practical concerns have been joined with the appreciation that other models can teach us the principles of behavior, genetics, and nutrition. Thus there is a steady use of the traditional animal models in this type of research, as well as growth in the use of other systems such as worms and flies. Rats and mice occupy a special niche as animal models for two reasons; first, they share with humans a love of the same types of food, and second, they are the target of a number of well-developed genetic tools. The available genetic tools that make mice a popular model include a well-annotated genome (Mouse Build 37), profiles of RNA expression from many tissues, a diverse panel of inbred strains, and the ability to manipulate genes in the whole animal, including removing a gene only in specific tissues (e.g., Cre-lox system). Mice have been harnessed to find genotypes that contribute to sweet-liking, and other studies are underway to understand how genetic variation might at least partially explain other puzzles of human appetites. Animal models provide a way to study the genetic determinants of food selection with experimental rigor and therefore complement human genetics studies.

Genetic factors contributing to obesity and body weight can act through mechanisms affecting muscle weight, fat weight, or both

Genetic loci for body weight and subphenotypes such as fat weight have been mapped repeatedly. However, the distinct effects of different loci and physiological interactions among different traits are often not accounted for in mapping studies. Here we used the method of structural equation modeling to identify the specific relationships between genetic loci and different phenotypes influencing body weight. Using this technique, we were able to distinguish genetic loci that affect adiposity from those that affect muscle growth. We examined the high body weight-selected mouse lines NMRI8 and DU6i and the intercross populations NMRI8 x DBA/2 and DU6i x DBA/2. Structural models help us understand whether genetic factors affect lean mass and fat mass pleiotropically or nonpleiotropically. Sex has direct effects on both fat and muscle weight but also influences fat weight indirectly via muscle weight. Three genetic loci identified in these two crosses showed exclusive effects on fat deposition, and five loci contributed exclusively to muscle weight. Two additional loci showed pleiotropic effects on fat and muscle weight, with one locus acting in both crosses. Fat weight and muscle weight were influenced by epistatic effects. We provide evidence that significant fat loci in strains selected for body weight contribute to fat weight both directly and indirectly via the influence on lean weight. These results shed new light on the action of genes in quantitative trait locus regions potentially influencing muscle and fat mass and thus controlling body weight as a composite trait.

A dominant X-linked QTL regulating pubertal timing in mice found by whole genome scanning and modified interval-specific congenic strain analysis

BACKGROUND

Pubertal timing in mammals is triggered by reactivation of the hypothalamic-pituitary-gonadal (HPG) axis and modulated by both genetic and environmental factors. Strain-dependent differences in vaginal opening among inbred mouse strains suggest that genetic background contribute significantly to the puberty timing, although the exact mechanism remains unknown.

METHODOLOGY/PRINCIPAL FINDINGS

We performed a genome-wide scanning for linkage in reciprocal crosses between two strains, C3H/HeJ (C3H) and C57BL6/J (B6), which differed significantly in the pubertal timing. Vaginal opening (VO) was used to characterize pubertal timing in female mice, and the age at VO of all female mice (two parental strains, F1 and F2 progeny) was recorded. A genome-wide search was performed in 260 phenotypically extreme F2 mice out of 464 female progeny of the F1 intercrosses to identify quantitative trait loci (QTLs) controlling this trait. A QTL significantly associated was mapped to the DXMit166 marker (15.5 cM, LOD = 3.86, p<0.01) in the reciprocal cross population (C3HB6F2). This QTL contributed 2.1 days to the timing of VO, which accounted for 32.31% of the difference between the original strains. Further study showed that the QTL was B6-dominant and explained 10.5% of variation to this trait with a power of 99.4% at an alpha level of 0.05.The location of the significant ChrX QTL found by genome scanning was then fine-mapped to a region of approximately 2.5 cM between marker DXMit68 and rs29053133 by generating and phenotyping a panel of 10 modified interval-specific congenic strains (mISCSs).

CONCLUSIONS/SIGNIFICANCE

Such findings in our study lay a foundation for positional cloning of genes regulating the timing of puberty, and also reveal the fact that chromosome X (the sex chromosome) does carry gene(s) which take part in the regulative pathway of the pubertal timing in mice.

A meta-analysis of QTL for diabetes-related traits in rodents

Crossbreeding studies in rodents have identified numerous quantitative trait loci (QTL) that are linked to diabetes-related component traits. To identify genetic consensus regions implicated in insulin action and glucose homeostasis, we have performed a meta-analysis of genomewide linkage scans for diabetes-related traits. From a total of 43 published genomewide scans we assembled a nonredundant collection of 153 QTL for glucose levels, insulin levels, and glucose tolerance. Collectively, these studies include data from 48 different parental strains and >11,000 individual animals. The results of the studies were analyzed by the truncated product method (TPM). The analysis revealed significant evidence for linkage of glucose levels, insulin levels, and glucose tolerance to 27 different segments of the mouse genome. The most prominent consensus regions [localized to chromosomes 2, 4, 7, 9, 11, 13, and 19; logarithm of odds (LOD) scores 10.5-17.4] cover approximately 11% of the mouse genome and collectively contain the peak markers for 47 QTL. Approximately half of these genomic segments also show significant linkage to body weight and adiposity, indicating the presence of multiple obesity-dependent and -independent consensus regions for diabetes-related traits. At least 84 human genetic markers from genomewide scans and >80 candidate genes from human and rodent studies map into the mouse consensus regions for diabetes-related traits, indicating a substantial overlap between the species. Our results provide guidance for the identification of novel candidate genes and demonstrate the presence of numerous distinct consensus QTL regions with highly significant LOD scores that control glucose homeostasis. An interactive physical map of the QTL is available online at http://www.diabesitygenes.org.