Quantitative Trait Loci For Body Weight Research Articles

Identification of bovine QTL for growth and carcass traits in Japanese Black cattle by replication and identical-by-descent mapping

To map quantitative trait loci (QTL) for growth and carcass traits in a purebred Japanese Black cattle population, we conducted multiple QTL analyses using 15 paternal half-sib families comprising 7860 offspring. We identified 40 QTL with significant linkages at false discovery rates of less than 0.1, which included 12 for intramuscular fat deposition called marbling and 12 for cold carcass weight or body weight. The QTL each explained 2%-13% of the phenotypic variance. These QTL included many replications and shared hypothetical identical-by-descent (IBD) alleles. The QTL for CW on BTA14 was replicated in five families with significant linkages and in two families with a 1% chromosome-wise significance level. The seven sires shared a 1.1-Mb superior Q haplotype as a hypothetical IBD allele that corresponds to the critical region previously refined by linkage disequilibrium mapping. The QTL for marbling on BTA4 was replicated in two families with significant linkages. The QTL for marbling on BTA6, 7, 9, 10, 20, and 21 and the QTL for body weight on BTA6 were replicated with 1% and/or 5% chromosome-wise significance levels. There were shared IBD Q or q haplotypes in the marbling QTL on BTA4, 6, and 10. The allele substitution effect of these haplotypes ranged from 0.7 to 1.2, and an additive effect between the marbling QTL on BTA6 and 10 was observed in the family examined. The abundant and replicated QTL information will enhance the opportunities for positional cloning of causative genes for the quantitative traits and efficient breeding using marker-assisted selection.

Quantitative Trait Locus Analysis of Plasma Cholesterol Levels and Body Weight by Controlling the Effects of the Apoa2 Allele in Mice

Colleagues and I previously performed quantitative trait locus (QTL) analysis on plasma total-cholesterol (T-CHO) levels in C57BL/6J (B6) x RR F2 mice. We identified only one significant QTL (Cq6) on chromosome 1 in a region containing the Apoa2 gene locus, a convincing candidate gene for Cq6. Because Cq6 was a highly significant QTL, we considered that the detection of other potential QTLs might be hindered. In the present study, QTL analysis was performed in B6.KK-Apoa2b N(8) x RR F2 mice [B6.KK-Apoa2b N(8) is a partial congenic strain carrying the Apoa2b allele from the KK strain, and RR also has the Apoa2b allele] by controlling of the effects of the Apoa2 allele, for identifying additional QTLs. Although no significant QTLs were identified, 2 suggestive QTLs were found on chromosomes 2 and 3 in place of the effects of the Apoa2 allele. A significant body weight QTL was identified on chromosome 3 (Bwq7, peak LOD score 5.2); its effect on body weight was not significant in previously analyzed B6 x RR F2 mice. Suggestive body weight QTL that had been identified in B6 x RR F2 mice on chromosome 4 (LOD score 3.8) was not identified in B6.KK-Apoa2b N(8) x RR F2 mice. Thus, contrary to expectation, the genetic control of body weight was also altered significantly by controlling of the effects of the Apoa2 allele. The QTL mapping strategy by controlling of the effects of a major QTL facilitated the identification of additional QTLs.

Bodyweight QTL on mouse chromosomes 4 and 11 by selective genotyping: regression v. maximum likelihood

Two quantitative trait loci (QTL) for mouse bodyweight have previously been reported on mouse chromosomes (MMU) 4 and 11 from crosses of a highly fecund and large mouse strain, Inbred Quackenbush-Swiss 5 (QSi5) and C57Bl/6J. QSi5 has now been crossed with CBA/CaH to produce 1128 F2 mice to confirm the existence and effect of these QTL. In total, 226 mice from the upper and lower deciles for bodyweight were genotyped using 12 microsatellite markers covering MMU4 and MMU11. Regression and maximum likelihood based interval mapping by either including all mice (ungenotyped mice were treated as having missing genotypes) or including only selectively genotyped mice in the analyses were used to estimate the positions and effects of the QTL. The results confirmed the existence and effects of both QTL. Although all methods estimated the same QTL positions, the QTL effects were overestimated compared with the estimates using a suggested method (maximum likelihood by including all mice in the analysis). However, the overestimated QTL effects could be mathematically corrected. Since the confidence intervals of both QTL are still too large for positional cloning, an advanced intercross line is being bred for finely mapping these bodyweight QTL.

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

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

Quantitative trait loci analysis of mice administered the methionine–choline deficient dietary model of experimental steatohepatitis

Nonalcoholic steatohepatitis (NASH) is a common disease with a poorly understood etiology, and the methionine-choline-deficient (MCD) diet is a nutritional model of NASH. Quantitative trait loci (QTL) analysis is a standard method for chromosomal mapping of polygenic disease traits. The purpose of this study is to administer mice an MCD diet in order to determine the strain-specific susceptibility for developing steatohepatitis, and to apply a computational methodology of QTL analysis to identify associated chromosomal susceptibility loci. Inbred mice were fed an MCD diet and alanine aminotransferase (ALT), hepatic triglycerides, liver weight, and weight loss were measured as phenotypic markers of steatohepatitis. A/J mice developed the highest ALT and hepatic triglyceride levels. Using linear regression analysis, gene loci affecting serum ALT levels were identified on four chromosomes, and four loci that affect liver weight were also identified. In contrast, no QTLs for hepatic triglycerides or body weight were identified. Of note, loci for ALT and liver weight co-localized to proximal segments of chromosomes 2 and 15, in regions previously identified as QTLs for liver fibrosis. These data indicate that experimental steatohepatitis is a polygenic disease with genes determining ALT, liver weight, and liver fibrosis.

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.

Quantitative Trait Loci for Glomerulosclerosis, Kidney Weight and Body Weight in the Focal Glomerulosclerosis Mouse Model

In 183 male progeny derived from a backcross between the FGS/Kist strain, a new mouse model for focal glomerulosclerosis (FGS) in humans, and the standard normal strain, C57BL/6J, we performed a genome-wide scan for quantitative trait loci (QTLs) affecting the glomerulosclerosis index (GSI) based on histological observation as well as kidney and body weights. Two QTLs for GSI (Gsi1-2) located on chromosomes (Chrs) 8 and 10, a kidney weight QTL (Kdw1) on Chr 19, and a body weight QTL (Bdw1) on Chr 13 were detected at the genome-wide 5% or less level. The allele derived from FGS/Kist increased GSI at Gsi1, but decreased it at Gsi2. The mice homozygous for the FGS/Kist allele decreased body and kidney weights. The identified QTLs accounted for 5-8% of the phenotypic variance.

Confirmation of quantitative trait loci affecting fatness in chickens

In this report we describe the analysis of an advanced intercross line (AIL) to confirm the quantitative trait locus (QTL) regions found for fatness traits in a previous study. QTL analysis was performed on chromosomes 1, 3, 4, 15, 18, and 27. The AIL was created by random intercrossing in each generation from generation 2 (G2) onwards until generation 9 (G9) was reached. QTL for abdominal fat weight (AFW) and/or percentage abdominal fat (AF%) on chromosomes 1, 3 and 27 were confirmed in the G9 population. In addition, evidence for QTL for body weight at the age of 5 (BW5) and 7 (BW7) weeks and for the percentage of intramuscular fat (IF%) were found on chromosomes 1, 3, 15, and 27. Significant evidence for QTL was detected on chromosome 1 for BW5 and BW7. Suggestive evidence was found on chromosome 1 for AFW, AF% and IF%, on chromosome 15 for BW5, and on chromosome 27 for AF% and IF%. Furthermore, evidence on the chromosome-wise level was found on chromosome 3 for AFW, AF%, and BW7 and on chromosome 27 for BW5. For chromosomes 4 and 18, test statistics did not exceed the significance threshold.

A genome scan of a four-way tilapia cross supports the existence of a quantitative trait locus for cold tolerance on linkage group 23

A genome scan, searching for quantitative trait loci (QTL) for the traits cold tolerance and body weight in tilapia, was performed on a cross between a (Oreo- chromis niloticusSarotherodon galilaeus )m ale and a( O. mossambicusO. aureus) female. Fifty-four microsatellites and 23 ampli¢ed fragment length polymorphism (AFLP) primer combinations were genotyped and tested for marker^trait associations. Sex-speci¢c linkage maps were constructed from this data. Twenty-three point-wise signi¢cant marker^ trait associations were found in the genome scan, and putative QTL were subsequently tested in another (OnSg) � (OmOa) family. None of the putative QTL from the ¢rst experiment were signi¢- cant in the second experiment. However, one micro- satellite, UNH130, found to be associated to weight in the ¢rst experiment, was found to be strongly asso- ciated to cold tolerance in the second experiment. Since QTL for cold tolerance and body weight were recently found on the linkage group containing UNH130 (linkage group 23) in another study, this linkage group was investigated more closely using in- terval mapping. The results provide indications, but not conclusive evidence, of a QTL for cold tolerance on linkage group 23.

Linkage and QTL mapping for Sus scrofa chromosome 14

SummaryThe Sus scrofa chromosome 14 (SSC14) linkage maps, constructed using eight markers in three F2‐families based on Wild Boar (W), Meishan (M) and Pietrain (P) crosses, were similar for the different families. The detected quantitative trait loci (QTLs) explained up to 8.2% of the F2 phenotypic variance for carcass traits. They were located in the interval SW540 to SW2488 (containing the candidate loci ACTN2 and ACTA1) in the M × P and W × P families. A QTL for body weight at 35 days was mapped close to the candidate locus ACTN2 in the W × M family. In comparison with Pietrain QTL alleles, the effects of Meishan and Wild Boar alleles reduced meat content.

Testing the correspondence between map positions of quantitative trait loci.

There are several instances in which quantitative trait locus (QTL) mapping experiments have been independently carried out for similar traits in different laboratories. We develop a permutation test of the correspondence between the test statistics obtained from genome-wide QTL scans in two such experiments to test whether the same QTLs are segregating in the experimental pair. In simulations, we show that the permutation test has the desired properties if chromosomes are of equal length, but bias can occur if chromosomes are of unequal length, a problem connected with autocorrelation of test statistic values. We apply the test to data from three recent mouse body weight QTL mapping experiments. The results from the test are non-significant, and imply a lack of overall concordance between the QTLs that were segregating in these experiments.