A large-sample QTL study in mice: II. Body composition

Discovery of genomic loci for liver health and steatosis reveals overlap with glutathione redox genetics

Non-alcoholic fatty liver disease (NAFLD) is the most common chronic liver condition in the United States, encompassing a wide spectrum of liver pathologies including steatosis, steatohepatitis, fibrosis, and cirrhosis. Despite its high prevalence, there are no medications currently approved by the Food and Drug Administration for the treatment of NAFLD. Recent work has suggested that NAFLD has a strong genetic component and identifying causative genes will improve our understanding of the molecular mechanisms contributing to NAFLD and yield targets for future therapeutic investigations. Oxidative stress is known to play an important role in NAFLD pathogenesis, yet the underlying mechanisms accounting for disturbances in redox status are not entirely understood. To better understand the relationship between the glutathione redox system and signs of NAFLD in a genetically-diverse population, we measured liver weight, serum biomarkers aspartate aminotransferase (AST) and alanine aminotransferase (ALT), and graded liver pathology in a large cohort of Diversity Outbred mice. We compared hepatic endpoints to those of the glutathione redox system previously measured in the livers and kidneys of the same mice, and we screened for statistical and genetic associations using the R/qtl2 software. We discovered several novel genetic loci associated with markers of liver health, including loci that were associated with both liver steatosis and glutathione redox status. Candidate genes within each locus point to possible new mechanisms underlying the complex relationship between NAFLD and the glutathione redox system, which could have translational implications for future studies targeting NAFLD pathology.

Generation of embryonic stem cells derived from the inner cell mass of blastocysts of outbred ICR mice

Embryonic stem cells (ESCs) derived from outbred mice which share several genetic characteristics similar to humans have been requested for developing stem cell-based bioengineering techniques directly applicable to humans. Here, we report the generation of ESCs derived from the inner cell mass of blastocysts retrieved from 9-week-old female outbred ICR mice mated with 9-week-old male outbred ICR mice (_ICRESCs). Similar to those from 129/Ola mouse blastocysts (_E14ESCs), the established _ICRESCs showed inherent characteristics of ESCs except for partial and weak protein expression and activity of alkaline phosphatase. Moreover, _ICRESCs were not originated from embryonic germ cells or pluripotent cells that may co-exist in outbred ICR strain-derived mouse embryonic fibroblasts (_ICRMEFs) used for deriving colonies from inner cell mass of outbred ICR mouse blastocysts. Furthermore, instead of outbred _ICRMEFs, hybrid _B6CBAF1MEFs as feeder cells could sufficiently support in vitro maintenance of _ICRESC self-renewal. Additionally, _ICRESC-specific characteristics (self-renewal, pluripotency, and chromosomal normality) were observed in _ICRESCs cultured for 40th subpassages (164 days) on _B6CBAF1MEFs without any alterations. These results confirmed the successful establishment of ESCs derived from outbred ICR mice, and indicated that self-renewal and pluripotency of the established _ICRESCs could be maintained on _B6CBAF1MEFs in culture.

Development, diagnosis and therapy of ketosis in non-gravid and non-lactating Guinea pigs

Background

Ketosis is a metabolic disorder often triggered by anorexia in animals fed on high energy diets. Although mostly described in pregnant female guinea pigs, under the name of pregnancy toxicosis; there is limited information on ketosis in males and non-pregnant females, often presented to clinics with anorexia or inappetence. The objective of this study was to observe progression of ketosis in guinea pigs, document the changes and evaluate diagnostic methods and a therapeutic approach.

Results

Twenty eight adult guinea pigs (Cavia porcellus), castrated males and intact females of obese and slim body condition were fasted for 3 days and refed afterwards. The slim animals served as control group for body condition. Either slim and fat animals were divided into two treatment groups: half of them received fluid replacements with glucose subcutaneously, the other half did not receive any injection and served as treatment control. Serum beta-hydroxybutyrate, and urine acetoacetate and acetone were measured during and after fasting. Serum ALT, bile acids and liver histology were also analyzed after 7 days of refeeding (and therapy). Females and obese guinea pigs showed a significantly higher increase in ketone bodies in serum and urine. Obese, female, or animals not receiving therapy needed more time to regulate ketone bodies to normal levels than slim animals, males or animals receiving therapy. Liver histology revealed increased hepatocyte degeneration and higher glycogen content in obese animals and animals receiving therapy, and additionally more glycogen content in males. Only minor hepatic fat accumulation was documented. Bile acids showed good correlation to histological liver changes whereas ALT did not.

Conclusions

Female and obese animals react more intensively to fasting. As preventive management, animals should be kept in adequate body condition, fasting should be avoided, and anorexia should be treated immediately. In such a case, urinary dip sticks to detect ketone bodies are a useful diagnostic tool. Glucose therapy leads to faster cessation of ketogenesis and should be recommended in cases of ketosis. However, it needs to be adjusted to avoid hepatocyte glycogen overload and degeneration. Measuring bile acids presents a valuable indicator of liver damage.

Effects of quantitative trait loci determining testicular weight in DDD/Sgn inbred mice are strongly influenced by circulating testosterone levels

Objective

Testicular growth and development are strongly influenced by androgen. Although both testis weight and plasma testosterone level are inherited traits, the interrelationship between them is not fully established. Males of DDD/Sgn (DDD) mice are known to have extremely heavy testes and very high plasma testosterone level among inbred mouse strains. We dissected the genetic basis of testis weight and analyzed the potential influence of plasma testosterone level in DDD mice.

Methods

Quantitative trait loci (QTL) mapping of testis weight was performed with or without considering the influence of plasma testosterone level in reciprocal F2 intercross populations between DDD and C57BL/6J (B6) mice, thereby assessing the influence of testosterone on the effect of testis weight QTL. Candidate genes for testis weight QTL were investigated by next-generation sequencing analysis.

Results

Four significant QTL were identified on chromosomes 1, 8, 14, and 17. The DDD-derived allele was associated with increased testis weight. The F2 mice were then divided into two groups according to the plasma testosterone level (F2 mice with relatively "low" and "high" testosterone level), and QTL scans were again performed. Although QTL on chromosomes 1 was shared in both F2 mice, QTL on chromosomes 8 and 17 were identified specifically in F2 mice with relatively high testosterone levels. By whole-exome sequencing analysis, we identified one DDD-specific missense mutation Pro29Ser in Atat1.

Conclusion

Most of the testis weight QTL expressed stronger phenotypic effect when they were placed on circumstance with high testosterone level. High testosterone influenced the QTL by enhancing the effect of DDD-derived allele and diminishing the effects of B6-derived allele. Since Pro29Ser was not identified in other inbred mouse strains, and since Pro29 in Atat1 has been strongly conserved among mammalian species, Atat1 is a plausible candidate for testis weight QTL on chromosome 17.

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.

Burly1 is a mouse QTL for lean body mass that maps to a 0.8-Mb region of chromosome 2

To fine map a mouse QTL for lean body mass (Burly1), we used information from intercross, backcross, consomic, and congenic mice derived from the C57BL/6ByJ (host) and 129P3/J (donor) strains. The results from these mapping populations were concordant and showed that Burly1 is located between 151.9 and 152.7 Mb (rs33197365 to rs3700604) on mouse chromosome 2. The congenic region harboring Burly1 contains 26 protein-coding genes, 11 noncoding RNA elements (e.g., lncRNA), and 4 pseudogenes, with 1949 predicted functional variants. Of the protein-coding genes, 7 have missense variants, including genes that may contribute to lean body weight, such as Angpt41, Slc52c3, and Rem1. Lean body mass was increased by the B6-derived variant relative to the 129-derived allele. Burly1 influenced lean body weight at all ages but not food intake or locomotor activity. However, congenic mice with the B6 allele produced more heat per kilogram of lean body weight than did controls, pointing to a genotype effect on lean mass metabolism. These results show the value of integrating information from several mapping populations to refine the map location of body composition QTLs and to identify a short list of candidate genes.

Genome-wide association for testis weight in the diversity outbred mouse population

Testis weight is a genetically mediated trait associated with reproductive efficiency across numerous species. We sought to evaluate the genetically diverse, highly recombinant Diversity Outbred (DO) mouse population as a tool to identify and map quantitative trait loci (QTLs) associated with testis weight. Testis weights were recorded for 502 male DO mice and the mice were genotyped on the GIGAMuga array at ~ 143,000 SNPs. We performed a genome-wide association analysis and identified one significant and two suggestive QTLs associated with testis weight. Using bioinformatic approaches, we developed a list of candidate genes and identified those with known roles in testicular size and development. Candidates of particular interest include the RNA demethylase gene Alkbh5, the cyclin-dependent kinase inhibitor gene Cdkn2c, the dynein axonemal heavy chain gene Dnah11, the phospholipase D gene Pld6, the trans-acting transcription factor gene Sp4, and the spermatogenesis-associated gene Spata6, each of which has a human ortholog. Our results demonstrate the utility of DO mice in high-resolution genetic mapping of complex traits, enabling us to identify developmentally important genes in adult mice. Understanding how genetic variation in these genes influence testis weight could aid in the understanding of mechanisms of mammalian reproductive function.

Quantitative trait mapping in Diversity Outbred mice identifies two genomic regions associated with heart size

Heart size is an important factor in cardiac health and disease. In particular, increased heart weight is predictive of adverse cardiovascular outcomes in multiple large community-based studies. We use two cohorts of Diversity Outbred (DO) mice to investigate the role of genetics, sex, age, and diet on heart size. DO mice (n = 289) of both sexes from generation 10 were fed a standard chow diet, and analyzed at 12-15 weeks of age. Another cohort of female DO mice (n = 258) from generation 11 were fed either a high-fat, cholesterol-containing (HFC) diet or a low-fat, high-protein diet, and analyzed at 24-25 weeks. We did not observe an effect of diet on body or heart weight in generation 11 mice, although we previously reported an effect on other cardiovascular risk factors, including cholesterol, triglycerides, and insulin. We do observe a significant genetic effect on heart weight in this population. We identified two quantitative trait loci for heart weight, one (Hwtf1) at a genome-wide significance level of p ≤ 0.05 on MMU15 and one (Hwtf2) at a genome-wide suggestive level of p ≤ 0.1 on MMU10, that together explain 13.3% of the phenotypic variance. Hwtf1 contained collagen type XXII alpha 1 chain (Col22a1), and the NZO/HlLtJ and WSB/EiJ haplotypes were associated with larger hearts. This is consistent with heart tissue Col22a1 expression in DO founders and SNP patterns within Hwtf1 for Col22a1. Col22a1 has been previously associated with cardiac fibrosis in mice, suggesting that Col22a1 may be involved in pathological cardiac hypertrophy.

The mouse Char10 locus regulates severity of pyruvate kinase deficiency and susceptibility to malaria

Pyruvate kinase (PKLR) deficiency protects mice and humans against blood-stage malaria. Although mouse strain AcB62 carries a malaria-protective Pklr^I90N genetic mutation, it is phenotypically susceptible to blood stage malaria induced by infection with Plasmodium chabaudi AS, suggesting a genetic modifier of the Pklr^I90N protective effect. Linkage analysis in a F2 cross between AcB62 (Pklr^I90N) and another PK deficient strain CBA/Pk (Pklr^G338D) maps this modifier (designated Char10) to chromosome 9 (LOD = 10.8, 95% Bayesian CI = 50.7–75Mb). To study the mechanistic basis of the Char10 effect, we generated an incipient congenic line (Char10C) that harbors the Char10 chromosome 9 segment from AcB62 fixed on the genetic background of CBA/Pk. The Char10 effect is shown to be highly penetrant as the Char10C line recapitulates the AcB62 phenotype, displaying high parasitemia following P. chabaudi infection, compared to CBA/Pk. Char10C mice also display a reduction in anemia phenotypes associated with the Pklr^G338D mutation including decreased splenomegaly, decreased circulating reticulocytes, increased density of mature erythrocytes, increased hematocrit, as well as decreased iron overload in kidney and liver and decreased serum iron. Erythroid lineage analyses indicate that the number of total TER119⁺ cells as well as the numbers of the different CD71⁺/CD44⁺ erythroblast sub-populations were all found to be lower in Char10C spleen compared to CBA/Pk. Char10C mice also displayed lower number of CFU-E per spleen compared to CBA/Pk. Taken together, these results indicate that the Char10 locus modulates the severity of pyruvate kinase deficiency by regulating erythroid responses in the presence of PK-deficiency associated haemolytic anemia.

Complex Genetics of Cardiovascular Traits in Mice: F2-Mapping of QTLs and Their Underlying Genes

In this chapter, we will use the example of the identification of Tnni3k as a modulator of cardiac conduction to introduce you to the use of a murine F2-generation intercross as a powerful method for the identification of novel genes relevant for cardiovascular traits. Murine F2-progeny is a genetically diverse panel of mice with differences in phenotype manifestations, e.g. cardiovascular traits such as cardiomyopathy and ECG parameters. This chapter discusses the best strategies for using F2-mice for genetic mapping. Moreover, we provide an example of the feasibility of identification of new genes modulating cardiac function utilizing the technique of mapping quantitative trait loci (QTLs) and a systems genetics integration of available genetic, gene expression, and phenotypic data.

Overlapping mouse subcongenic strains successfully separate two linked body fat QTL on distal MMU 2

BACKGROUND

Mouse chromosome 2 is linked to growth and body fat phenotypes in many mouse crosses. With the goal to identify the underlying genes regulating growth and body fat on mouse chromosome 2, we developed five overlapping subcongenic strains that contained CAST/EiJ donor regions in a C57BL/6J (hg/hg) background (hg is a spontaneous deletion of 500 Kb on mouse chromosome 10). To fine map QTL on distal mouse chromosome 2 a total of 1,712 F2 mice from the five subcongenic strains, plus 278 F2 mice from the HG2D founder congenic strain were phenotyped and analyzed. Interval mapping (IM) and composite IM (CIM) were performed on body weight and body fat traits on a combination of SNP and microsatellite markers, which generated a high-density genotyping panel.

RESULTS

Phenotypic analysis and interval mapping of total fat mass identified two QTL on distal mouse chromosome 2. One QTL between 150 and 161 Mb, Fatq2a, and the second between 173.3 and 175.6 Mb, Fatq2b. The two QTL reside in different congenic strains with significant total fat differences between homozygous cast/cast and b6/b6 littermates. Both of these QTL were previously identified only as a single QTL affecting body fat, Fatq2. Furthermore, through a novel approach referred here as replicated CIM, Fatq2b was mapped to the Gnas imprinted locus.

CONCLUSIONS

The integration of subcongenic strains, high-density genotyping, and CIM succesfully partitioned two previously linked QTL 20 Mb apart, and the strongest QTL, Fatq2b, was fine mapped to a ~2.3 Mb region interval encompassing the Gnas imprinted locus.

Quantitative trait loci for energy balance traits in an advanced intercross line derived from mice divergently selected for heat loss

Obesity in human populations, currently a serious health concern, is considered to be the consequence of an energy imbalance in which more energy in calories is consumed than is expended. We used interval mapping techniques to investigate the genetic basis of a number of energy balance traits in an F₁₁ advanced intercross population of mice created from an original intercross of lines selected for increased and decreased heat loss. We uncovered a total of 137 quantitative trait loci (QTLs) for these traits at 41 unique sites on 18 of the 20 chromosomes in the mouse genome, with X-linked QTLs being most prevalent. Two QTLs were found for the selection target of heat loss, one on distal chromosome 1 and another on proximal chromosome 2. The number of QTLs affecting the various traits generally was consistent with previous estimates of heritabilities in the same population, with the most found for two bone mineral traits and the least for feed intake and several body composition traits. QTLs were generally additive in their effects, and some, especially those affecting the body weight traits, were sex-specific. Pleiotropy was extensive within trait groups (body weights, adiposity and organ weight traits, bone traits) and especially between body composition traits adjusted and not adjusted for body weight at sacrifice. Nine QTLs were found for one or more of the adiposity traits, five of which appeared to be unique. The confidence intervals among all QTLs averaged 13.3 Mb, much smaller than usually observed in an F₂ cross, and in some cases this allowed us to make reasonable inferences about candidate genes underlying these QTLs. This study combined QTL mapping with genetic parameter analysis in a large segregating population, and has advanced our understanding of the genetic architecture of complex traits related to obesity.

Dominance and epistasis are the main contributors to heterosis for plant height in rice

The genetic basis of heterosis has been debated for over 100 years regarding whether dominance or overdominance plays a more important role and the answer is still unclear. The major limitation to assess the contribution of a single locus has been the genetic background noise due to genome-wide segregation of multiple loci. To dissect the genetic basis of heterosis at a single locus for plant height, we developed a set of 202 chromosome segment substitution lines (CSSLs) of an elite hybrid, Shanyou 63, the best hybrid rice in China in the 1990s. Fifteen CSSLs had varied plant heights within lines. A total of 15 partial dominance QTLs for plant height were detected in these 15 CSSL-F2 populations. All hybrids between the 15 CSSLs and the recurrent parent, Zhenshan 97, were shorter than the corresponding CSSLs, but taller than Zhenshan 97. These indicated that these 15 QTLs were also heterosis loci (HLs) contributed to heterosis acted in dominance. Each HL contributed from -7.4 to 14.4% of midparent heterosis. Additive by additive (AA) and additive by dominance (AD) interactions were detected in the Tetra-F2 population segregating at the four major QTLs with the largest effects on plant height. Substantial negative AA effects were detected between two major QTLs QPH7.2 and QPH7.3, which increased heterosis in the study. Thus we concluded that dominance and epistasis are the major genetic basis of plant height heterosis, which could explain the better parent heterosis in Shanyou 63.

Associations of PrP genotype with lamb production traits in three commercial breeds of British hill sheep

The National Scrapie Plan (NSP) was launched in Great Britain in 2001, with the aim of eventually eradicating scrapie, a small ruminant transmissible spongiform encephalopathy, from the national sheep flock. Specifically, a selective breeding programme, the Ram Genotyping Scheme, was devised enabling pedigree ram breeders to reduce the number of scrapie-susceptible genotypes from their flocks. The effect of large-scale manipulation of PrP genotypes on commercially important traits within the sheep industry is, however, unknown. We have therefore examined production traits in a total of 43 968 lambs from 32 pedigree breeders across three British hill breeds, comprising 8163 North Country Cheviot (Hill), 21 366 Scottish Blackface and 14 439 Welsh Mountain lambs. Traits examined included: weights at birth, 8 and 20 weeks; ultrasonic fat and muscle depth, and average daily weight gain from 8 to 20 weeks. Linear mixed models were fitted for each trait, including animal (direct) genetic effects and up to three maternal effects. Potential associations with the PrP gene were assessed by fitting either PrP genotype or number of copies of individual alleles as fixed effects. A number of breed-specific significant associations between production traits and the PrP gene were found, but no consistent significant effects were detected across the three breeds. Breed-specific effects were as follows: (i) 0.37 kg higher birth weights (BWTs) in AHQ homozygous North Country Cheviot (Hill) lambs (P < 0.01); (ii) 0.16 kg higher BWTs in ARR homozygous Scottish Blackface lambs (P < 0.05); (iii) 0.5 kg higher 8-week weights in VRQ heterozygous Scottish Blackface lambs (P < 0.01); (iv) a 0.72 kg decrease in scan weight associated with homozygous ARR Welsh Mountain lambs (P < 0.01); (v) 0.51 mm higher ultrasonic muscle depths in AHQ homozygous Welsh Mountain lambs (P < 0.01); (vi) 0.48 mm lower ultrasonic muscle depths in Welsh Mountain lambs carrying one or more copies of the ARR allele (P < 0.05) and (vii) 0.2 mm higher ultrasonic fat depths in heterozygous VRQ Welsh Mountain lambs (P < 0.05). The use of a Bonferroni correction to define appropriate significance thresholds across the three datasets, which account for the large number of independent comparisons made, resulted in breed-specific comparisons, with P < 0.01 becoming significant at P0.05, and the remaining breed-specific comparisons no longer being significant. The absence of a common effect across the three breeds suggests that any true association found may be due to breed-specific alleles of neighbouring genes in linkage disequilibrium with the PrP locus.

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.

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.

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.

A proximal genomic region of mouse chromosome 10 contains quantitative trait loci affecting fatness

Body weight and fatness are quantitative traits of agricultural and medical importance. In previous genome-wide quantitative trait locus (QTL) analyses, two QTLs for body weight and weight gain at an early postnatal growth period were discovered on mouse chromosome 10 from a gene pool of wild subspecies mice, Mus musculus castaneus. In this study, we developed a congenic strain with an approximately 63-Mb wild-derived genomic region on which the two growth QTLs could be located, by recurrent backcrossing to the common inbred strain C57BL/6J. We compared body weights at 1-10 weeks of age, body weight gains at 1-3, 3-6 and 6-10 weeks, internal organ weights and body lengths between the congenic strain developed and C57BL/6J. Unfortunately, no effects of the two growth QTLs on body weights and weight gains were confirmed. However, at least two new QTLs affecting fatness traits were discovered within the introgressed congenic region. The wild-derived allele at one QTL increased body mass index, whereas at another one it decreased white fat pad weight and adiposity index. Thus, the congenic mouse strain developed here is a useful model animal for understanding the genetic and molecular basis of fat deposition in livestock as well as humans.

Genomic mapping of social behavior traits in a F2 cross derived from mice selectively bred for high aggression

BACKGROUND

Rapid response to selection was previously observed in mice selected for high levels of inter-male aggression based on number of attacks displayed in a novel social interaction test after isolation housing. Attack levels in this high aggression line (NC900) increased significantly within just four generations of selective breeding, suggesting the presence of a locus with large effect. We conducted an experiment using a small (n ≈ 100) F2 cross between the ICR-derived, non-inbred NC900 strain and the low aggression inbred strain C57BL/6J, genotyped for 154 fully informative SNPs, to determine if a locus with large effect controls the high-aggression selection trait. A second goal was to use high density SNP genotyping (n = 549,000) in the parental strains to characterize residual patterns of heterozygosity within NC900, and evaluate regions that are identical by descent (IBD) between NC900 and C57BL/6J, to determine what impacts these may have on accuracy and resolution of quantitative trait locus (QTL) mapping in the F2 cross.

RESULTS

No evidence for a locus with major effect on aggressive behavior in mice was identified. However, several QTL with genomewide significance were mapped for aggression on chromosomes 7 and 19 and other social behavior traits on chromosomes 4, 7, 14, and 19. High density genotyping revealed that 28% of the genome is still segregating among the six NC900 females used to originate the F2 cross, and that segregating regions are present on every chromosome but are of widely different sizes. Regions of IBD between NC900 and C57BL/6J are found on every chromosome but are most prominent on chromosomes 10, 16 and X. No significant differences were found for amounts of heterozygosity or prevalence of IBD in QTL regions relative to global analysis.

CONCLUSIONS

While no major gene was identified to explain the rapid selection response in the NC900 line, transgressive variation (i.e. where the allele from the C57BL/6J increased attack levels) and a significant role for dominant gene action were hallmarks of the genetic architecture for aggressive behavior uncovered in this study. The high levels of heterozygosity and the distribution of minor allele frequency observed in the NC900 population suggest that maintenance of heterozygosity may have been under selection in this line.

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.

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.

The use of plasmodes as a supplement to simulations: A simple example evaluating individual admixture estimation methodologies

With the advent of powerful computers, simulation studies are becoming an important tool in statistical methodology research. However, computer simulations of a specific process are only as good as our understanding of the underlying mechanisms. An attractive supplement to simulations is the use of plasmode datasets. Plasmodes are data sets that are generated by natural biologic processes, under experimental conditions that allow some aspect of the truth to be known. The benefit of the plasmode approach is that the data are generated through completely natural processes, thus circumventing the common concern of the realism and accuracy of computer simulated data. The estimation of admixture, or the proportion of an individual's genome that originates from different founding populations, is a particularly difficult research endeavor that is well suited to the use of plasmodes. Current methods have been tested with simulations of complex populations where the underlying mechanisms such as the rate and distribution of recombination are not well understood. To demonstrate the utility of this method data derived from mouse crosses is used to evaluate the effectiveness of several admixture estimation methodologies. Each cross shares a common founding population so that the ancestry proportion for each individual is known, allowing for the comparison of true and estimated individual admixture values. Analysis shows that the different estimation methodologies (Structure, AdmixMap and FRAPPE) examined all perform well with simple datasets. However, the performance of the estimation methodologies varied greatly when applied to a plasmode consisting of three founding populations. The results of these examples illustrate the utility of plasmodes in the evaluation of statistical genetics methodologies.

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.

Pleiotropic patterns of quantitative trait loci for 70 murine skeletal traits

Quantitative trait locus (QTL) studies of a skeletal trait or a few related skeletal components are becoming commonplace, but as yet there has been no investigation of pleiotropic patterns throughout the skeleton. We present a comprehensive survey of pleiotropic patterns affecting mouse skeletal morphology in an intercross of LG/J and SM/J inbred strains (N = 1040), using QTL analysis on 70 skeletal traits. We identify 798 single-trait QTL, coalescing to 105 loci that affect on average 7-8 traits each. The number of traits affected per locus ranges from only 1 trait to 30 traits. Individual traits average 11 QTL each, ranging from 4 to 20. Skeletal traits are affected by many, small-effect loci. Significant additive genotypic values average 0.23 standard deviation (SD) units. Fifty percent of loci show codominance with heterozygotes having intermediate phenotypic values. When dominance does occur, the LG/J allele tends to be dominant to the SM/J allele (30% vs. 8%). Over- and underdominance are relatively rare (12%). Approximately one-fifth of QTL are sex specific, including many for pelvic traits. Evaluating the pleiotropic relationships of skeletal traits is important in understanding the role of genetic variation in the growth and development of the skeleton.

Efficient control of population structure in model organism association mapping

Genomewide association mapping in model organisms such as inbred mouse strains is a promising approach for the identification of risk factors related to human diseases. However, genetic association studies in inbred model organisms are confronted by the problem of complex population structure among strains. This induces inflated false positive rates, which cannot be corrected using standard approaches applied in human association studies such as genomic control or structured association. Recent studies demonstrated that mixed models successfully correct for the genetic relatedness in association mapping in maize and Arabidopsis panel data sets. However, the currently available mixed-model methods suffer from computational inefficiency. In this article, we propose a new method, efficient mixed-model association (EMMA), which corrects for population structure and genetic relatedness in model organism association mapping. Our method takes advantage of the specific nature of the optimization problem in applying mixed models for association mapping, which allows us to substantially increase the computational speed and reliability of the results. We applied EMMA to in silico whole-genome association mapping of inbred mouse strains involving hundreds of thousands of SNPs, in addition to Arabidopsis and maize data sets. We also performed extensive simulation studies to estimate the statistical power of EMMA under various SNP effects, varying degrees of population structure, and differing numbers of multiple measurements per strain. Despite the limited power of inbred mouse association mapping due to the limited number of available inbred strains, we are able to identify significantly associated SNPs, which fall into known QTL or genes identified through previous studies while avoiding an inflation of false positives. An R package implementation and webserver of our EMMA method are publicly available.

Genotype X diet interactions in mice predisposed to mammary cancer. I. Body weight and fat

High dietary fat intake and obesity may increase susceptibility to certain forms of cancer. To study the interactions of dietary fat, obesity, and metastatic mammary cancer, we created a population of F(2) mice cosegregating obesity QTL and the MMTV-PyMT transgene. We fed the F(2) mice either a very-high-fat or a matched-control-fat diet and measured growth, body composition, age at mammary tumor onset, tumor number and severity, and formation of pulmonary metastases. SNP genotyping across the genome facilitated analyses of QTL and QTL x diet interaction effects. Here we describe development of the F(2) population (n = 615) which resulted from a cross between the polygenic obesity model M16i and FVB/NJ-TgN (MMTV-PyMT)(634Mul), effects of diet on growth and body composition, and QTL and QTL x diet and/or gender interaction effects for growth and obesity-related phenotypes. We identified 38 QTL for body composition traits that were significant at the genome-wide 0.05 level, likely representing nine distinct loci after accounting for pleiotropic effects. QTL x diet and/or gender interactions were present at 15 of these QTL, indicating that such interactions play a significant role in defining the genetic architecture of complex traits such as body weight and obesity.

Genetic regulation of hypothalamic cocaine and amphetamine-regulated transcript (CART) in BxD inbred mice

Cocaine and Amphetamine-Regulated Transcript (CART) peptides are implicated in a wide range of behaviors including in the reinforcing properties of psychostimulants, feeding and energy balance and stress and anxiety responses. We conducted a complex trait analysis to examine natural variation in the regulation of CART transcript abundance (CARTta) in the hypothalamus. CART transcript abundance was measured in total hypothalamic RNA from 26 BxD recombinant inbred (RI) mouse strains and in the C57BL/6 (B6) and DBA/2J (D2) progenitor strains. The strain distribution pattern for CARTta was continuous across the RI panel, which is consistent with this being a quantitative trait. Marker regression and interval mapping revealed significant quantitative trait loci (QTL) on mouse chromosome 4 (around 58.2 cM) and chromosome 11 (between 20-36 cM) that influence CARTta and account for 31% of the between strain variance in this phenotype. There are numerous candidate genes and QTL in these chromosomal regions that may indicate shared genetic regulation between CART expression and other neurobiological processes referable to known actions of this neuropeptide.

Quantitative trait Loci for regional adiposity in mouse lines divergently selected for food intake

OBJECTIVE

Obesity is thought to result from an interaction between genotype and environment. Excessive adiposity is associated with a number of important comorbidities; however, the risk of obesity-related disease varies with the distribution of fat throughout the body. The aim of this study was to map quantitative trait loci (QTLs) associated with regional fat depots in mouse lines divergently selected for food intake corrected for body mass.

RESEARCH METHODS AND PROCEDURES

Using an F2 intercross design (n = 457), the dry mass of regional white (subcutaneous, gonadal, retroperitoneal, and mesenteric) adipose tissue (WAT) and brown adipose tissue (BAT) depots were analyzed to map QTLs.

RESULTS

The total variance explained by the mapped QTL varied between 12% and 39% for BAT and gonadal fat depots, respectively. Using the genome-wide significance threshold, nine QTLs were associated with multiple fat depots. Chromosomes 4 and 19 were associated with WAT and BAT and chromosome 9 with WAT depots. Significant sex x QTL interactions were identified for gonadal fat on chromosomes 9, 16, and 19. The pattern of QTLs identified for the regional deposits showed the most similarity between retroperitoneal and gonadal fat, whereas BAT showed the least similarity to the WAT depots. Analysis of total fat mass explained in excess of 40% of total variance.

DISCUSSION

There was limited concordance between the QTLs mapped in our study and those reported previously. This is likely to reflect the unique nature of the mouse lines used. Results provide an insight into the genetic basis of regional fat distribution.

Genetic loci affecting body weight and fatness in a C57BL/6J x PWK/PhJ mouse intercross

To determine the genetic variation that contributes to body composition in the mouse, we interbred a wild-derived strain (PWK/PhJ; PWK) with a common laboratory strain (C57BL/6J; B6). The parental, F(1), and F(2) mice were phenotyped at 18 weeks old for body weight and composition using dual-energy X-ray absorptiometry (DEXA). A total of 479 (244 male and 235 female) F(2) mice were genotyped for 117 polymorphic markers spanning the autosomes. Twenty-eight suggestive or significant linkages for four traits (body weight, adjusted lean and fat weight, and percent fat) were detected. Of these, three QTLs were novel: one on the proximal portion of Chr 5 for body weight (Bwq8; LOD = 4.7), one on Chr 3 for lean weight (Bwtq13; LOD = 3.6), and one on Chr 11 for percent fat (Adip19; LOD = 5.8). The remaining QTLs overlapped previously identified linkages, e.g., Adip5 on Chr 9. One QTL was sex-specific (present in males only) and seven were sex-biased (more prominent in one sex than the other). Most alleles that increased body weight were contributed by the B6 strain, and most alleles that increased percent fat were contributed by the PWK strain. Eight pairs of interacting loci were identified, none of which exactly overlapped the main-effect QTLs. Many of the QTLs found in the B6 x PWK cross map to the location of previously reported linkages, suggesting that some QTLs are common to many strains (consensus QTLs), but three new QTLs appear to be particular to the PWK strain. The location and type of QTLs detected in this new cross will assist in future efforts to identify the genetic variation that determines the ratio of lean to fat weight as well as body size in mice.

Identification of positional candidate genes for body weight and adiposity in subcongenic mice

We previously constructed a congenic mouse, B6.S-D2Mit194-D2Mit311 (B6.S-2) with 27 Mb of SPRET/Ei donor DNA on distal chromosome 2 in a C57BL/6J background that captured an obesity quantitative trait locus (QTL). Mice homozygous for SPRET/Ei alleles at the donor region had decreased body weight and obesity-related phenotypes (Diament AL, Farahani P, Chiu S, Fisler J, Warden CH. Mamm Genome 15: 452-459, 2004). In this study, we constructed five overlapping subcongenics with smaller SPRET/Ei donor regions to fine map the underlying gene(s). One of the five subcongenic lines derived from the B6.S-2 founding congenic, B6.S-2A, captured the body weight and adiposity phenotypes in a donor region with a maximum size of 7.4 Mb. Homozygous SPRET/Ei donor alleles in both the founding congenic and the derived B6.S-2A subcongenic exhibited significant decreases in body weight, multiple fat pad weights, and adiposity index (total fat pad weight divided by body weight). Interval-specific microarray analysis in four tissues for donor region genes from the founding B6.S-2 congenic identified several differentially expressed genes mapping to the B6.S-2A subcongenic donor region, including prohormone convertase 2 (PC2; gene name: Pcsk2). Quantitative real-time PCR confirmed a modest decrease of PC2 expression in brains of mice homozygous for SPRET/Ei donor alleles. Analysis of the relative levels of mRNA for B6 and SPRET/Ei in heterozygous congenic mice showed differentially higher expression of the C57BL/6J allele over the SPRET/Ei allele, indicating a cis regulation of differential expression. Using subcongenic mapping, we successfully narrowed a body weight and obesity QTL interval and identified PC2 as a positional candidate gene.

Mouse bone marrow and peripheral blood erythroid cell counts are regulated by different autosomal genetic loci

Erythropoiesis is under fine control and genetic loci that affect it are likely to be important in a range of conditions. To assess the relative contributions of different genetic loci to parameters of erythropoiesis, we have measured RBC counts in the peripheral circulation and committed erythroid cells (RBC and small normoblasts) in the bone marrow in a cohort of (CBA/H x C57BL/6) F2 mice to map quantitative trait loci (QTL). Candidate genes were assessed using bioinformatics and DNA sequencing. Different autosomal loci affect bone marrow (chromosomes 5, 11 and 19) and peripheral blood (chromosome 4) erythroid cell counts but there may be a common chromosome X locus. Spleen weight QTL were found on chromosomes 3, 15 and 17. Surprisingly, erythropoietin (Epo) is the best candidate quantitative trait gene (QTG) in the chromosome 5 locus that affects bone marrow but not peripheral blood erythroid cell counts. Epo gene expression is known to be genetically regulated in mice, but our data suggest a tissue-specific role for epo in mouse erythropoiesis that is also genetically determined. The identity of the other QTG will be important both to further knowledge of the control of erythropoiesis and as potential modifier genes for haematological disorders.

Identification of quantitative trait loci affecting body composition in a mouse intercross

Gravimetric analysis and dual energy x-ray absorptiometry densitometry were used to determine lean, fat, and bone tissue traits in a F(2) mouse population from a C57BL/6J and CASA/Rk intercross (B6CASAF2). These traits were used in a linkage analysis to identify quantitative trait loci that affect body composition. Linkage mapping showed that body weight (BW) loci on proximal chromosome 2 occurred in the same region as body length, lean tissue mass, and bone mineral content and on chromosome 13 in the same region as lean tissue mass, bone mineral density, and bone mineral content. Fat-related loci occurring on mid-chromosome 2 near 60 cM, proximal chromosome 6, and mid-chromosome 10 were distinct from BW, lean tissue, and bone tissue loci. In B6CASAF2 females, heterozygotes and CASA/Rk homozygotes at the chromosome 6 locus marker had higher body fat percentages, and this locus was responsible for 11% of the variance for body fat percentage. Female heterozygotes and C57BL/6J homozygotes at the chromosome 15 locus marker had higher bone mineral densities, and this locus could explain 8% of that trait's variance. A survey of the literature did not reveal any previous reports of fat-specific loci in the chromosomal 10 region near 42 cM reported in this study. The results of this study indicate that BW and BMI have limited usefulness as phenotypes in linkage or association studies when used as obesity phenotypes.

Substitution mapping in dahl rats identifies two distinct blood pressure quantitative trait loci within 1.12- and 1.25-mb intervals on chromosome 3

Substitution mapping was used to refine the localization of blood pressure (BP) quantitative trait loci (QTL) within the congenic region of S.R-Edn3 rats located at the q terminus of rat chromosome 3 (RNO3). An F2(SxS.R-Edn3) population (n=173) was screened to identify rats having crossovers within the congenic region of RNO3 and six congenic substrains were developed that carry shorter segments of R-rat-derived RNO3. Five of the six congenic substrains had significantly lower BP compared to the parental S rat. The lack of BP lowering effect demonstrated by the S.R(ET3x5) substrain and the BP lowering effect retained by the S.R(ET3x2) substrain together define the RNO3 BP QTL-containing region as approximately 4.64 Mb. Two nonoverlapping substrains, S.R(ET3x1) and S.R(ET3x6), had significantly lower BP compared to the S strain, indicating the presence of two distinct BP QTL in the RNO3 q terminus. The RNO3 q terminus was fine mapped with newly developed polymorphic markers to characterize the extent of the congenic regions. The two RNO3 BP QTL regions were thus defined as within intervals of 0.05-1.12 and 0.72-1.25 Mb, respectively. Also important was our difficulty in fine mapping and marker placement in this portion of the rat genome (and thus candidate gene identification) using the available genomic data, including the rat genome sequence.

A genome-wide linkage scan for quantitative trait loci underlying obesity related phenotypes in 434 Caucasian families

To identify quantitative trait loci (QTLs) that contribute to obesity, we performed a large-scale whole genome linkage scan (WGS) involving 4,102 individuals from 434 Caucasian families. The most pronounced linkage evidence was found at the genomic region 20p11-12 for fat mass (LOD = 3.31) and percentage fat mass (PFM) (LOD = 2.92). We also identified several regions showing suggestive linkage signals (threshold LOD = 1.9) for obesity phenotypes, including 5q35, 8q13, 10p12, and 17q11.

A meta-analysis of quantitative trait loci associated with body weight and adiposity in mice

OBJECTIVE

Cross-breeding experiments with different mouse strains have successfully been used by many groups to identify genetic loci that predispose for obesity. In order to provide a statistical assessment of these quantitative trait loci (QTL) as a basis for a systematic investigation of candidate genes, we have performed a meta-analysis of genome-wide linkage scans for body weight and body fat.

DATA

From a total of 34 published mouse cross-breeding experiments, we compiled a list of 162 non-redundant QTL for body weight and 117 QTL for fat weight and body fat percentage. Collectively, these studies include data from 42 different parental mouse strains and >14,500 individual mice.

METHODS

The results of the studies were analyzed using the truncated product method (TPM).

RESULTS

The analysis revealed significant evidence (logarithm of odds (LOD) score >4.3) for linkage of body weight and adiposity to 49 different segments of the mouse genome. The most prominent regions with linkage for body weight and body fat (LOD scores 14.8-21.8) on chromosomes 1, 2, 7, 11, 15, and 17 contain a total of 58 QTL for body weight and body fat. At least 34 candidate genes and genetic loci, which have been implicated in regulation of body weight and body composition in rodents and/or humans, are found in these regions, including CCAAT/enhancer-binding protein alpha (C/EBPA), sterol regulatory element-binding transcription factor 1 (SREBP-1), peroxisome proliferator activator receptor delta (PPARD), and hydroxysteroid 11-beta dehydrogenase 1 (HSD11B1). Our results demonstrate the presence of numerous distinct consensus QTL regions with highly significant LOD scores that control body weight and body composition. An interactive physical map of the QTL is available online at (http://www.obesitygenes.org).

Genome-Wide Linkage Analysis to Identify Chromosomal Regions Affecting Phenotypic Traits in the Chicken. II. Body Composition

Two informative chicken F(2) populations based on crosses between a broiler breeder male line and dams from genetically distinct, highly inbred (>99%) chicken lines, the Leghorn G-B2 and Fayoumi M15.2, have been used for genome-wide linkage and QTL analysis. Phenotypic data on 12 body composition traits (breast muscle weight, breast muscle weight percentage, abdominal fat weight, abdominal fat weight percentage, heart weight, heart weight percentage, liver weight, liver weight percentage, spleen weight, spleen weight percentage, and drumstick weight, and drumstick weight percentage) were collected. Birds were genotyped for 269 microsatellite markers across the genome. The QTL Express program was used to detect QTL for body composition traits. Significant levels were obtained using the permutation test. For the twelve traits, a total of 61 (Gga 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 15, 18, 24, and Z) and 45 (Gga 1, 2, 3, 4, 6, 7, 8, 9, 10, 12, 15, 17, and E46) significant QTL were detected at the 5% chromosome-wise significance level, of which 19 and 11 were significant at the 5% genome-wise level for the broiler-Leghorn cross and broiler-Fayoumi cross, respectively. Phenotypic variation for each trait explained by all QTL across the genome ranged from 3.22 to 33.31% in the broiler-Leghorn cross and 4.83 to 47.12% in broiler-Fayoumi cross. Distinct QTL profiles between the 2 crosses were observed for most traits. Cryptic alleles were detected for each trait. Potential candidate genes within the QTL region for body composition traits at the 1% chromosome-wise significance level were identified from databases for future association study. The results of the current study will increase the knowledge of genetic markers associated with body composition traits and aid the process of identifying causative genes. Knowledge of beneficial genetic variation can be incorporated in breeding programs to enhance genetic improvement through marker-assisted selection in chickens.

A genome scan for loci affecting pork quality in a Duroc-Landrace F population

A genome scan was conducted on 370 F2 Duroc-Landrace pigs. Microsatellite markers (n = 182) were genotyped across the entire F2 population, all F1 parents and the paternal grandparents. Breed of origin of all chromosomal segments inherited in F2 progeny were predicted using GenoProb, where genotypic data, genetic maps and extended pedigrees were used as inputs. Statistical tests for quantitative trait loci (QTL) associations were conducted on 41 phenotypes with SAS using output from GenoProb for genotypic data. Fixed effects included sex and age at slaughter. For certain analyses carcass weight, RYR1 genotype and/or PRKAG3 genotype were also included as covariates. Subjective and objective measures of pork colour, marbling and tenderness were recorded, as well as measures of carcass fatness and muscularity. Test results were adjusted to a genome-wide level of significance. Five genomic regions presented significant evidence for QTL at chromosome 1 positions 6 cM (intramuscular fat) and 67 cM (Hunter L*), chromosome 2 position 62 cM (taste panel tenderness), chromosome 17 position 50 (loineye area and image analysis estimated loineye area) and X position 87 cM (carcass weight). Sixty-six suggestive associations were detected. Fourteen of these associations were within the regions with significant QTL on chromosomes 2, 17 and X, and the remaining 52 associations resided in 29 other regions on 13 different chromosomes of the porcine genome. The chromosome 2 region of 60-66 cM was associated with all measures of pork tenderness and the region on chromosome 17 (32-39 cM) was associated with both measures of intramuscular fat and loineye area. After verification, the QTL for marbling and tenderness should be useful in commercial production to improve pork quality as the population was developed from two of the three most utilized breeds of swine in the USA.

Overdominant quantitative trait loci for yield and fitness in tomato

Heterosis, or hybrid vigor, is a major genetic force that contributes to world food production. The genetic basis of heterosis is not clear, and the importance of loci with overdominant (ODO) effects is debated. One problem has been the use of whole-genome segregating populations, where interactions often mask the effects of individual loci. To assess the contribution of ODO to heterosis in the absence of epistasis, we carried out quantitative genetic and phenotypic analyses on a population of tomato (Solanum lycopersicum) introgression lines (ILs), which carry single marker-defined chromosome segments from the distantly related wild species Solanum pennellii. The ILs revealed 841 quantitative trait loci (QTL) for 35 diverse traits measured in the field on homozygous and heterozygous plants. ILs showing greater reproductive fitness were characterized by the prevalence of ODO QTL, which were virtually absent for the nonreproductive traits. ODO can result from true ODO due to allelic interactions of a single gene or from pseudoODO that involves linked loci with dominant alleles in repulsion. The fact that we detected dominant and recessive QTL for all phenotypic categories but ODO only for the reproductive traits indicates that pseudoODO due to random linkage is unlikely to explain heterosis in the ILs. Thus, we favor the true ODO model involving a single functional Mendelian locus. We propose that the alliance of ODO QTL with higher reproductive fitness was selected for in evolution and was domesticated by man to improve yields of crop plants.

Genetic determinants of weight of fast- and slow-twitch skeletal muscles in old mice

The main goal of the study was to explore the genetic architecture underlying muscle weight in old mice. Weight of soleus, tibialis anterior (TA), extensor digitorum longus (EDL), and gastrocnemius muscles was measured in the C57BL/6J (B6) and DBA/2J (D2) strains and derivative generations: a panel of the BXD recombinant inbred (RI) strains and a B6D2 F(2) intercross at the age of 800 days. The between-strain difference in muscle weight (B6 > D2) ranged between 16% and 38%. Linkage analysis identified suggestive quantitative trait loci (QTL) on Chromosomes (Chr) 2, 6, 7, 8, 19, and X that influenced muscle weight in the 800-day-old group. Comparison of weights at 200, 500, and 800 days revealed a variable effect of age among the four muscles. Linkage analysis in the B6D2 F(2) population combined across the three different age groups identified muscle-, sex-, and age-specific QTL on Chr 1, 2, 3, 5, 6, 8, 9, 11, 13, 17, X, and Y. Genetic factors that influence the rate of weight change (within-strain weight difference at two ages) over the lifespan of BXD RIs were mapped to the markers D2Mit369 and D3Mit130 at the genome-wide p < 0.05 for TA muscle in males (between 200 and 800 days) and females (between 500 and 800 days), respectively. Analysis of all age groups supported previous findings that the genetic effects may be muscle-, age-, and sex-specific.

Quantitative trait loci for body size components in mice

Do body size components, such as weights of internal organs and long bone lengths, with different functions and different developmental histories also have different genetic architectures and pleiotropic patterns? We examine murine quantitative trait loci (QTL) for necropsy weight, four long bone lengths, and four organ weights in the LG/J x SM/J intercross. Differences between trait categories were found in number of QTL, dominance, and pleiotropic patterns. Ninety-seven QTLs for individual traits were identified: 52 for long bone lengths, 30 for organ weights, and 15 for necropsy weight. Results for long bones are typically more highly significant than for organs. Organ weights were more frequently over- or underdominant than long bone lengths or necropsy weight. The single-trait QTLs map to 35 pleiotropic loci. Long bones are much more frequently affected in groups while organs tend to be affected singly or in pairs. Organs and long bones are found at the same locus in only 11 cases, 8 of which also include necropsy weight. Our results suggest mainly separate genetic modules for organ weights and long bone lengths, with a few loci that affect overall body size. Antagonistic pleiotropy, in which a locus has opposite effects on different characteristics, is uncommon.

Bayesian analyses of multiple epistatic QTL models for body weight and body composition in mice

To comprehensively investigate the genetic architecture of growth and obesity, we performed Bayesian analyses of multiple epistatic quantitative trait locus (QTL) models for body weights at five ages (12 days, 3, 6, 9 and 12 weeks) and body composition traits (weights of two fat pads and five organs) in mice produced from a cross of the F1 between M16i (selected for rapid growth rate) and CAST/Ei (wild-derived strain of small and lean mice) back to M16i. Bayesian model selection revealed a temporally regulated network of multiple QTL for body weight, involving both strong main effects and epistatic effects. No QTL had strong support for both early and late growth, although overlapping combinations of main and epistatic effects were observed at adjacent ages. Most main effects and epistatic interactions had an opposite effect on early and late growth. The contribution of epistasis was more pronounced for body weights at older ages. Body composition traits were also influenced by an interacting network of multiple QTLs. Several main and epistatic effects were shared by the body composition and body weight traits, suggesting that pleiotropy plays an important role in growth and obesity.

Functional genomic characterization of delipidation elicited by trans-10, cis-12-conjugated linoleic acid (t10c12-CLA) in a polygenic obese line of mice

Gene expression was measured during t10c12-CLA-induced body fat reduction in a polygenic obese line of mice. Adult mice (n = 185) were allotted to a 2 x 2 factorial experiment consisting of either nonobese (ICR-control) or obese (M16-selected) mice fed a 7% fat, purified diet containing either 1% linoleic acid (LA) or 1% t10c12-CLA. Body weight (BW) by day 14 was 12% lower in CLA- compared with LA-fed mice (P < 0.0001). By day 14, t10c12-CLA reduced weights of epididymal, mesenteric, and brown adipose tissues, as a percentage of BW, in both lines by 30, 27, and 58%, respectively, and increased liver weight/BW by 34% (P < 0.0001). Total RNA was isolated and pooled (4 pools per tissue per day) from epididymal adipose (days 5 and 14) of the obese mice to analyze gene expression profiles using Agilent mouse oligo microarray slides representing > 20,000 genes. Numbers of genes differentially expressed by greater than or equal to twofold in epididymal adipose (days 5 and 14) were 29 and 125, respectively. It was concluded that, in adipose tissue, CLA increased expression of uncoupling proteins (1 and 2), carnitine palmitoyltransferase system, tumor necrosis factor-alpha (P < 0.05), and caspase-3 but decreased expression of peroxisome proliferator-activated receptor-gamma, glucose transporter-4, perilipin, caveolin-1, adiponectin, resistin, and Bcl-2 (P < 0.01). In conclusion, this experiment has revealed candidate genes that will be useful in elucidating mechanisms of adipose delipidation.

The human obesity gene map: the 2005 update

This paper presents the 12th update of the human obesity gene map, which incorporates published results up to the end of October 2005. 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 (QTL) from animal cross-breeding experiments, association studies with candidate genes, and linkages from genome scans is reviewed. As of October 2005, 176 human obesity cases due to single-gene mutations in 11 different genes have been reported, 50 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 244 genes that, 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 408. The number of human obesity QTLs derived from genome scans continues to grow, and we now have 253 QTLs for obesity-related phenotypes from 61 genome-wide scans. A total of 52 genomic regions harbor QTLs supported by two or more studies. The number of studies reporting associations between DNA sequence variation in specific genes and obesity phenotypes has also increased considerably, with 426 findings of positive associations with 127 candidate genes. A promising observation is that 22 genes are each supported by at least five positive studies. The obesity gene map shows putative loci on all chromosomes except Y. The electronic version of the map with links to useful publications and relevant sites can be found at http://obesitygene.pbrc.edu.

Genetics of canid skeletal variation: size and shape of the pelvis

The mammalian skeleton presents an ideal system in which to study the genetic architecture of a set of related polygenic traits and the skeleton of the domestic dog (Canis familiaris) is arguably the best system in which to address the relationship between genes and anatomy. We have analyzed the genetic basis for skeletal variation in a population of >450 Portuguese Water Dogs. At this stage of this ongoing project, we have identified >40 putative quantitative trait loci (QTLs) for heritable skeletal phenotypes located on 22 different chromosomes, including the "X." A striking aspect of these is the regulation of suites of traits representing bones located in different parts of the skeleton but related by function. Here we illustrate this by describing genetic variation in postcranial morphology. Two suites of traits are involved. One regulates the size of the pelvis relative to dimensions of the limb bones. The other regulates the shape of the pelvis. Both are examples of trade-offs that may be prototypical of different breeds. For the size of the pelvis relative to limb bones, we describe four QTLs located on autosome CFA 12, 30, 31, and X. For pelvic shape we describe QTLs on autosome CFA 2, 3, 22, and 36. The relation of these polygenic systems to musculoskeletal function is discussed.

Quantitative trait locus analysis for obesity reveals multiple networks of interacting loci

Obesity is a highly heritable and genetically complex trait with hundreds of potential loci identified. An intercross of 513 F2 progeny between the SM/J x NZB/BINJ inbred mouse strains was generated to identify quantitative trait loci (QTL) that are involved in the weight of four fat pads: mesenteric, inguinal, gonadal, and retroperitoneal. Sex and lean body weight were treated as covariates in the analysis of these fat pads. This analysis uncoupled genetic effects related to overall body size from those influencing the adiposity of a mouse. We identified multiple significant QTL. QTL alleles associated with increased lean body weight and individual fat pad weights are contributed by the NZB background. Adiposity loci are distinct from these body size QTLs and high-adiposity alleles are contributed by the SM background. An extended network of epistatic QTL is also observed. A QTL on Chr 19 is the center of a network of eight interacting QTL, Chr 4 is the center of six, and Chr 17 the center of four interacting QTL. We conclude that interacting networks of multiple genes characterize the regulation of fat pad depots and body weight. Haplotype patterns and a literature-driven approach were used to generate hypotheses regarding the identity of the genes and pathways underlying the QTL.

Quantitative trait loci for baseline white blood cell count, platelet count, and mean platelet volume

A substantial genetic contribution to baseline peripheral blood counts has been established. We performed quantitative trait locus/loci (QTL) analyses to identify chromosome (Chr) regions harboring genes influencing the baseline white blood cell (WBC) count, platelet (Plt) count, and mean platelet volume (MPV) in F(2) intercrosses between NZW/LacJ, SM/J, and C57BLKS/J inbred mice. We identified six significant WBC QTL: Wbcq1 (peak LOD score at 38 cM, Chr 1), Wbcq2 (42 cM, Chr 3), Wbcq3 (0 cM, Chr 15), Wbcq4 (58 cM, Chr 1), Wbcq5 (82 cM, Chr 1), and Wbcq6 (8 cM, Chr 14). Three significant Plt QTL were identified: Pltq1 (24 cM, Chr 2), Pltq2 (36 cM, Chr 7), and Pltq3 (10 cM, Chr 12). Two significant MPV QTL were identified, Mpvq1 (62 cM, Chr 15) and Mpvq2 (44 cM, Chr 8). In total, the WBC QTL accounted for up to 31% of the total variance in baseline WBC count, while the Plt and MPV QTL accounted for up to 30% and 49% of the total variance, respectively. These analyses underscore the genetic complexity underlying these traits in normal populations and provide the basis for future studies to identify novel genes involved in the regulation of mammalian hematopoiesis.

Genomic mapping of direct and correlated responses to long-term selection for rapid growth rate in mice

Understanding the genetic architecture of traits such as growth, body composition, and energy balance has become a primary focus for biomedical and agricultural research. The objective of this study was to map QTL in a large F(2) (n = 1181) population resulting from an intercross between the M16 and ICR lines of mice. The M16 line, developed by long-term selection for 3- to 6-week weight gain, is larger, heavier, fatter, hyperphagic, and diabetic relative to its randomly selected control line of ICR origin. The F(2) population was phenotyped for growth and energy intake at weekly intervals from 4 to 8 weeks of age and for body composition and plasma levels of insulin, leptin, TNFalpha, IL6, and glucose at 8 weeks and was genotyped for 80 microsatellite markers. Since the F(2) was a cross between a selection line and its unselected control, the QTL identified likely represent genes that contributed to direct and correlated responses to long-term selection for rapid growth rate. Across all traits measured, 95 QTL were identified, likely representing 19 unique regions on 13 chromosomes. Four chromosomes (2, 6, 11, and 17) harbored loci contributing disproportionately to selection response. Several QTL demonstrating differential regulation of regional adipose deposition and age-dependent regulation of growth and energy consumption were identified.