Loci on Chromosomes 2, 4, 9, and 16 for body weight,body length,and adiposity identified in a genome scan of an F<Subscript>2</Subscript> intercross between the 129P3/J and C57BL/6ByJ mouse strains

Mice have proved to be a powerful model organism for understanding obesity in humans. Single gene mutants and genetically modified mice have been used to identify obesity genes, and the discovery of loci for polygenic forms of obesity in the mouse is an important next step. To pursue this goal, the inbred mouse strains 129P3/J (129) and C57BL/6ByJ (B6), which differ in body weight, body length, and adiposity, were used in an F₂ cross to identify loci affecting these phenotypes. Linkages were determined in a two-phase process. In the first phase, 169 randomly selected F₂ mice were genotyped for 134 markers that covered all autosomes and the X Chromosome (Chr). Significant linkages were found for body weight and body length on Chr 2. In addition, we detected several suggestive linkages on Chr 2 (adiposity), 9 (body weight, body length, and adiposity), and 16 (adiposity), as well as two suggestive sex-dependent linkages for body length on Chrs 4 and 9. In the second phase, 288 additional F₂ mice were genotyped for markers near these regions of linkage. In the combined set of 457 F₂ mice, six significant linkages were found: Chr 2 (Bwq5, body weight and Bdln3, body length), Chr 4 (Bdln6, body length, males only), Chr 9 (Bwq6, body weight and Adip5, adiposity), and Chr 16 (Adip9, adiposity), as well as several suggestive linkages (Adip2, adiposity on Chr 2; Bdln4 and Bdln5, body length on Chr 9). In addition, there was a suggestive linkage to body length in males on Chr 9 (Bdln4). For adiposity, there was evidence for epistatic interactions between loci on Chr 9 (Adip5) and 16 (Adip9). These results reinforce the concept that obesity is a complex trait. Genetic loci and their interactions, in conjunction with sex, age, and diet, determine body size and adiposity in mice.     

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.     

Obesity QTLs on Mouse Chromosomes 2 and 17

The inheritance of obesity has been analyzed in an intercross between the mouse strains AKR/J and C57L/J. Two novel obesity quantitative trait loci (QTLs) have been identified using the strategy of selective DNA pooling. One QTL affecting adiposity,Obq3,was mapped to a 39-cM segment near the middle of Chromosome 2, with a peak lod score (5.1) just distal to theD2Mit15locus. The AKR/JObq3allele confers increased adiposity in a nearly additive manner, and males are more affected than females. A second obesity QTL (Obq4) maps to the centromeric end of Chromosome 17, with a lod score peak of 4.6 atD17Mit143.The obesity-conferring allele is contributed by C57L/J and acts in a recessive or an additive manner.Obq4also has more influence in males and affects the inguinal fat depot differentially.Obq3andObq4account for 7.0 and 6.1% of the phenotypic variance in adiposity (gender-merged data), respectively. The possible relationships between these QTLs and previously described obesity QTLs and candidate genes are discussed. The large number of different obesity QTLs that have been described in mice and the relatively small effects contributed by individual loci suggest considerable genetic complexity.     

Detection of Obesity QTLs on Mouse Chromosomes 1 and 7 by Selective DNA Pooling

The inheritance of obesity has been analyzed in an intercross between the lean 129/Sv mouse strain and the obesity-prone EL/Suz mouse strain. The weights of three major fat pads were determined on 4-month-old mice, and the sum of these weights, divided by body weight, was used as an adiposity index. The strategy of selective DNA pooling was used as a primary screen to identify putative quantitative trait loci (QTLs) affecting adiposity index. DNA pools representing the leanest 15% and fattest 15% of the F2 progeny were compared for differential allelic enrichment using widely dispersed microsatellite variants. To evaluate putative QTLs, individual genotyping and interval mapping were employed to estimate QTL effects and assess statistical significance. One QTL affecting adiposity index, which accounted for 12.3% of phenotypic variance in gender-merged data, was mapped to the central region of Chromosome (Chr) 7. The QTL allele inherited from EL conferred increased adiposity. A second QTL that accounts for 6.3% of phenotypic variance was identified on Chr 1 nearD1Mit211.At both QTLs, the data are consistent with dominant inheritance of the allele contributing to obesity. The possible relationships between these QTLs and previously described obesity QTLs, major obesity mutations, and candidate genes are discussed.     

Multiple obesity QTLs identified in an intercross between the NZO (New Zealand obese) and the SM (small) mouse strains

The inheritance of adiposity levels has been investigated in an intercross of the obese, diabetes-prone NZO and the small, lean SM mouse strains. Adiposity index (AI) was defined as the sum of four fat pad weights divided by body weight. DNA pools from fat and lean mice were analyzed with microsatellite variants to screen the genome for quantitative trait loci (QTLs) affecting AI. Ten significant QTLs affecting AI were identified on Chromosome (Chr) 1 (three loci), Chr 2, Chr 5 (two loci), Chr 6 (two loci), Chr 7, and Chr 17. Most of the QTLs appear to be novel. Several QTLs differentially affect specific fat depots. Thus, Chr 2 and Chr 7 QTLs affect gonadal more than inguinal fat, while the converse is true for the Chr 17 QTL. Gender influences the expression of several of the QTLs. For example, effects of the proximal Chr 1 QTL (Obq7) on AI appears to be primarily in males. The proximal AI QTL on Chr 6 (Obq13) maps near the neuropeptide Y (Npy) locus. Sequence analysis of the Npy gene revealed a 1-nucleotide deletion within a highly conserved portion of the 3′ untranslated region in strain NZO. However, the deletion is polymorphic among mouse strains. Furthermore, lack of association between this same variant and AI in previously analyzed crosses raises doubt that it is the basis of Obq13. The present cross is the fourth in a series of intercrosses among 10 inbred strains arranged such that each strain is crossed with each adjacent strain within a circle. This design affords multiple opportunities to analyze each segregating QTL. Received: 17 July 2000 / Accepted: 9 October 2000     

Genetic architecture of adiposity and organ weight using combined generation QTL analysis

We present here a detailed study of the genetic contributions to adult body size and adiposity in the LG,SM advanced intercross line (AIL), an obesity model. This study represents a first step in fine-mapping obesity quantitative trait loci (QTLs) in an AIL. QTLs for adiposity in this model were previously isolated to chromosomes 1, 6, 7, 8, 9, 12, 13, and 18. This study focuses on heritable contributions and the genetic architecture of fatpad and organ weights. We analyzed both the F(2) and F(3) generations of the LG,SM AIL population single-nucleotide polymorphism (SNP) genotyped with a marker density of approximately 4 cM. We replicate 88% of the previously identified obesity QTLs and identify 13 new obesity QTLs. Nearly half of the single-trait QTLs were sex-specific. Several broad QTL regions were resolved into multiple, narrower peaks. The 113 single-trait QTLs for organs and body weight clustered into 27 pleiotropic loci. A large number of epistatic interactions are described which begin to elucidate potential interacting molecular networks. We present a relatively rapid means to obtain fine-mapping details from AILs using dense marker maps and consecutive generations. Analysis of the complex genetic architecture underlying fatpad and organ weights in this model may eventually help to elucidate not only heritable contributions to obesity but also common gene sets for obesity and its comorbidities.     

Fine‐mapping of Obesity‐related Quantitative Trait Loci in an F9/10 Advanced Intercross Line

Obesity develops in response to a combination of environmental effects and multiple genes of small effect. Although there has been significant progress in characterizing genes in many pathways contributing to metabolic disease, knowledge about the relationships of these genes to each other and their joint effects upon obesity lags behind. The LG,SM advanced intercross line (AIL) model of obesity has been used to characterize over 70 loci involved in fatpad weight, body weight, and organ weights. Each of these quantitative trait loci (QTLs) encompasses large regions of the genome and require fine‐mapping to isolate causative sequence changes and possible mechanisms of action as indicated by the genetic architecture. In this study we fine‐map QTLs first identified in the F₂ and F_2/3 populations in the combined F_9/10 advanced intercross generations. We observed significantly narrowed QTL confidence regions, identified many single QTL that resolve into multiple QTL peaks, and identified new QTLs that may have been previously masked due to opposite gene effects at closely linked loci. We also present further characterization of the pleiotropic and epistatic interactions underlying these obesity‐related traits.     

Genetics of dietary obesity in AKR/JxSWR/J mice: segregation of the trait and identification of a linked locus on Chromosome 4

We describe a new multiple gene mouse model of differential sensitivity to dietary obesity that provides a tool for dissecting the genetic basis for body composition and obesity. AKR/J and SWR/J male mice, as well as male progeny of intercrosses between these strains, were fed a high-fat diet for 12 weeks beginning at 5 weeks of age. Body weight and energy intake were assessed weekly. At the conclusion of the dietary manipulation, an adiposity index was calculated by dividing the weight of seven dissected adipose depots by the carcass weight. AKR/J mice had approximately sixfold greater adiposity than SWR/J mice. Examination of the segregation of the adiposity trait in the progeny of crosses between these strains indicates that the trait is determined by a minimum of one to four genetic loci and that there is significant dominance of the AKR/J genotype. A preliminary analysis with markers linked to the known mouse obesity genes ob, db, tub, and fat showed no linkage with these loci. However, a quantitative trait locus was found that maps distal to the db gene on Chromosome (Chr) 4. This locus has been designated dietary obese 1 or Do1.     

Genetic variation in pleiotropy: differential epistasis as a source of variation in the allometric relationship between long bone lengths and body weight

Pleiotropy is an aspect of genetic architecture underlying the phenotypic covariance structure. The presence of genetic variation in pleiotropy is necessary for natural selection to shape patterns of covariation between traits. We examined the contribution of differential epistasis to variation in the intertrait relationship and the nature of this variation. Genetic variation in pleiotropy was revealed by mapping quantitative trait loci (QTLs) affecting the allometry of mouse limb and tail length relative to body weight in the mouse-inbred strain LG/J by SM/J intercross. These relationship QTLs (rQTLs) modify relationships between the traits affected by a common pleiotropic locus. We detected 11 rQTLs, mostly affecting allometry of multiple bones. We further identified epistatic interactions responsible for the observed allometric variation. Forty loci that interact epistatically with the detected rQTLs were identified. We demonstrate how these epistatic interactions differentially affect the body size variance and the covariance of traits with body size. We conclude that epistasis, by differentially affecting both the canalization and mean values of the traits of a pleiotropic domain, causes variation in the covariance structure. Variation in pleiotropy maintains evolvability of the genetic architecture, in particular the evolvability of its modular organization.     

Genetic Modifiers ofLeprAssociated with Variability in Insulin Production and Susceptibility to NIDDM

In an attempt to identify the genetic basis for susceptibility to non-insulin-dependent diabetes mellitus within the context of obesity, we generated 401 genetically obeseLepr^fa/Lepr^faF2 WKY13M intercross rats that demonstrated wide variation in multiple phenotypic measures related to diabetes, including plasma glucose concentration, percentage of glycosylated hemoglobin, plasma insulin concentration, and pancreatic islet morphology. Using selective genotyping genome scanning approaches, we have identified three quantitative trait loci (QTLs) on Chr. 1 (LOD 7.1 for pancreatic morpholology), Chr. 12 (LOD 5.1 for body mass index and LOD 3.4 for plasma glucose concentration), and Chr. 16 (P< 0.001 for genotype effect on plasma glucose concentration). The obese F2 progeny demonstrated sexual dimorphism for these traits, with increased diabetes susceptibility in the males appearing at approximately 6 weeks of age, as sexual maturation occurred. For each of the QTLs, the linked phenotypes demonstrated sexual dimorphism (more severe affection in males). The QTL on Chr. 1 maps to a region vicinal to that previously linked to adiposity in studies of diabetes susceptibility in the nonobese Goto–Kakizaki rat, which is genetically closely related to the Wistar counterstrain we employed. Several candidate genes, including tubby (tub), multigenic obesity 1 (Mob1), adult obesity and diabetes (Ad), and insulin-like growth factor-2 (Igf2), map to murine regions homologous to the QTL region identified on rat Chr. 1.     

Using mouse models to dissect the genetics of obesity

Mice have proved to be powerful models for understanding obesity in humans and farm animals. Single-gene mutants and genetically modified mice have been used successfully to discover genes and pathways that can regulate body weight. For polygenic obesity, the most common pattern of inheritance, many quantitative trait loci (QTLs) have been mapped in crosses between selected and inbred mouse lines. Most QTL effects are additive, and diet, age and gender modify the genetic effects. Congenic, recombinant inbred, advanced intercross, and chromosome substitution strains are needed to map QTLs finely, to identify the genes underlying the traits, and to examine interactions between them.     

Quantitative trait loci for bone density in C57BL/6J and CAST/EiJ inbred mice

Genetic analyses for loci regulating bone mineral density have been conducted in a cohort of F₂ mice derived from intercross matings of (C57BL/6J × CAST/EiJ)F₁ parents. Femurs were isolated from 714 4-month-old females when peak adult bone density had been achieved. Bone mineral density (BMD) data were obtained by peripheral quantitative computed tomography (pQCT), and genotype data were obtained by Polymerase Chain Reaction (PCR) assays for polymorphic markers carried in genomic DNA of each mouse. Genome-wide scans for co-segregation of genetic marker data with high or low BMD revealed loci on eight different chromosomes, four of which (Chrs 1, 5, 13, and 15) achieved conservative statistical criteria for suggestive, significant, or highly significant linkage with BMD. These four quantitative trait loci (QTLs) were confirmed by a linear regression model developed to describe the main effects; none of the loci exhibited significant interaction effects by ANOVA. The four QTLs have been named Bmd1 (Chr 1), Bmd2 (Chr 5), Bmd3 (Chr 13), and Bmd4 (Chr 15). Additive effects were observed for Bmd1, recessive for Bmd3, and dominant effects for Bmd2 and Bmd4. The current large size of the QTL regions (6→31 cM) renders premature any discussion of candidate genes at this time. Fine mapping of these QTLs is in progress to refine their genetic positions and to evaluate human homologies. Received: 5 May 1999 / Accepted: 22 June 1999     

Genetic loci affecting body weight and fatness in a C57BL/6J × 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, F₁, and F₂ 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) F₂ 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 × 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.     

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 × 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.     

Mapping murine loci for seizure response to kainic acid

Mature DBA/2J (D2) mice are very sensitive to seizures induced by various chemical and physical stimuli, whereas C57BL/6J (B6) mice are relatively seizure resistant. We have conducted a genome-wide search for quantitative trait loci (QTLs) influencing the differential sensitivity of these strains to kainic acid (KA)-induced seizures by studying an F₂ intercross population. Parental, F₁, and F₂ mice (8–10 weeks of age) were injected subcutaneously with 25 mg/kg of KA and observed for 3 h. Latencies to focal and generalized seizures and status epilepticus were recorded and used to calculate an overall seizure score. Results of seizure testing indicated that the difference in susceptibility to KA-induced seizures between D2 and B6 mice is a polygenic phenomenon with at least 65% of the variance due to genetic factors. First-pass genome screening (10-cM marker intervals) in F₂ progeny (n = 257) documented a QTL of moderate effect on Chromosome (Chr) 1 with a peak LOD score of 5.5 (17% of genetic variance explained) localized between D1Mit30 and D1Mit16. Provisional QTLs of small effect were detected on Chr 11 (D11Mit224–D11Mit14), 15 (D15Mit6–D15Mit46) and 18 (D18Mit9–D18Mit144). Multiple locus models generally confirmed the Mapmaker/QTL results and also provided evidence for another QTL on Chr 4 (D4Mit9). Multilocus analysis of seizure severity suggested that additional loci on Chrs 5 (D5Mit11), 7 (D7Mit66), and 15 (D15Nds2) might also contribute to KA-induced seizure response. Overall, our results document a complex genetic determinism for KA-induced seizures in these mouse strains with contributions from as many as eight QTLs. Received: 16 April 1996 / Accepted: 21 October 1996     

Genetic variation in the pleiotropic association between physical activity and body weight in mice

Background

A sedentary lifestyle is often assumed to lead to increases in body weight and potentially obesity and related diseases but in fact little is known about the genetic association between physical activity and body weight. We tested for such an association between body weight and the distance, duration, and speed voluntarily run by 310 mice from the F₂ generation produced from an intercross of two inbred lines that differed dramatically in their physical activity levels.

Methods

We used a conventional interval mapping approach with SNP markers to search for QTLs that affected both body weight and activity traits. We also conducted a genome scan to search for relationship QTLs (relQTLs), or chromosomal regions that affected an activity trait variably depending on the phenotypic value of body weight.

Results

We uncovered seven quantitative trait loci (QTLs) affecting body weight, but only one co-localized with another QTL previously found for activity traits. We discovered 19 relQTLs that provided evidence for a genetic (pleiotropic) association of physical activity and body weight. The three genotypes at each of these loci typically exhibited a combination of negative, zero, and positive regressions of the activity traits on body weight, the net effect of which was to produce overall independence of body weight from physical activity. We also demonstrated that the relQTLs produced these varying associations through differential epistatic interactions with a number of other epistatic QTLs throughout the genome.

Conclusion

It was concluded that individuals with specific combinations of genotypes at the relQTLs and epiQTLs might account for some of the variation typically seen in plots of the association of physical activity with body weight.     

Genetic resistance to diet-induced obesity in chromosome substitution strains of mice

Discovery of genes that confer resistance to diseases such as diet-induced obesity could have tremendous therapeutic impact. We previously demonstrated that the C57BL/6J-Chr^A/J/NaJ panel of chromosome substitution strains (CSSs) is a unique model for studying resistance to diet-induced obesity. In the present study, three replicate CSS surveys showed remarkable consistency, with 13 A/J-derived chromosomes reproducibly conferring resistance to high-fat-diet-induced obesity. Twenty CSS intercrosses, one derived from each of the 19 autosomes and chromosome X, were used to determine the number and location of quantitative trait loci (QTLs) on individual chromosomes and localized six QTLs. However, analyses of mean body weight in intercross progeny versus C57BL/6J provided strong evidence that many QTLs discovered in the CSS surveys eluded detection in these CSS intercrosses. Studies of the temporal effects of these QTLs suggest that obesity resistance was dynamic, with QTLs acting at different ages or after different durations of diet exposure. Thus, these studies provide insight into the genetic architecture of complex traits such as resistance to diet-induced obesity in the C57BL/6J-Chr^A/J/NaJ CSSs. Because some of the QTLs detected in the CSS intercrosses were not detected using a traditional C57BL/6J × A/J intercross, our results demonstrate that surveys of CSSs and congenic strains derived from them are useful complementary tools for analyzing complex traits.     

Quantitative trait loci for growth traits in C57BL/6J × DBA/2J mice

Quantitative trait loci (QTLs) for body weight and tail length are mapped in an F₂ population of 927 C57BL/6J × DBA/2J mice. We test the concordance between the locations of the mapped QTLs with those detected by changes of marker frequency under artificial selection in a previous experiment with the same base population. The directions of effects of the QTLs are generally in agreement, and in many cases significant QTLs are found in similar map positions, but there are also discrepancies between the two experiments. There are indications of age-specific QTL effects on growth. For body weight traits, the genetic variation in the F₂ appears to result from many loci with relatively small effects. For tail length at 10 weeks, however, a single QTL on Chromosome (Chr) 1 with a peak LOD score of ∼33 contributes most of the genetic variation detected, changes the trait value by about 6%, and explains about 20% of the phenotypic variance of the trait. Received: 4 August 1998 / Accepted: 17 November 1998     

Mapping and characterization of quantitative trait loci for non-insulin-dependent diabetes mellitus with an improved genetic map in the Otsuka Long-Evans Tokushima Fatty rat

The Otsuka Long-Evans Tokushima Fatty (OLETF) rat is an animal model for obese-type, non-insulin-dependent diabetes mellitus (NIDDM) in humans. We have previously reported four quantitative trait loci (QTLs) responsible for NIDDM on Chromosomes (Chrs) 7, 14, 8, and 11 (Nidd1–4/of for Non-insulin-dependent diabetes1–4/oletf) by a whole-genome search in 160 F₂ progenies obtained by mating the OLETF and the Fischer-344 (F344) rats. Our present investigation was designed to identify and characterize novel QTLs affecting NIDDM by performing a genome-wide linkage analysis of genes for glucose levels and body weight and analysis for gene-to-gene and gene-to-body-weight interactions on an improved genetic map with a set of 382 informative markers in the 160 F₂ progenies. We have identified seven novel QTLs on rat Chrs 1 (Nidd5 and 6/of), 5 (Nidd7/of), 9 (Nidd8/of), 12 (Nidd9/of), 14 (Nidd10/of) and 16 (Nidd11/of) which, together with the Nidd1–4/of, account for a total of ∼60% and ∼75% of the genetic variance of the fasting and postprandial glucose levels, respectively, in the F₂. While the OLETF allele corresponds with increased glucose levels as expected for the novel QTLs except Nidd8 and 9/of, the Nidd8 and 9/of exhibit heterosis: heterozygotes showing significantly higher glucose levels than OLETF or F344 homozygotes. There are epistatic interactions between Nidd1 and 10/of and between Nidd2 and 8/of. Additionally, our results indicated that the Nidd6 and 11/of could also contribute to an increase of body weight, and that the other five QTLs could show no linkage with body weight, but Nidd8,9, and 10/of have an interaction with body weight. Received: 10 August 1998 / Accepted: 17 November 1998     

Quantitative trait loci that harbor genes regulating muscle size in (MRL/MPJ x SJL/J) F(2) mice

The genetic mechanisms that determine muscle size have not been elucidated, even though it is a key musculoskeletal parameter that reflects muscle strength. In this study, we performed a high-density genome-wide scan using 633 (MRL/MPJ × SJL/J) F₂ intercross 7-week-old mice to identify quantitative trait loci (QTL) involved in the determination of muscle size. Significant QTL were identified for muscle size and body length. Muscle size (adjusted by body length) QTL were identified on chromosomes 7, 9, 11, 14 (two QTL) and 17, which together explained 19.2% of phenotypic variance in F₂ mice, while body length QTL were located on chromosome 2 (two QTL), 9, 11 and 17 which accounted for 28.3% of phenotypic variance in F₂ mice. Three significant epistatic interactions between different QTL positions from muscle size and body length were identified (P <0.01) on chromosomes 2, 9, 14 and 17, which explained 16.1% of the variance in F₂ mice. Electronic Publication