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PubMed1999

A test of transmission/disequilibrium for quantitative traits in pedigree data, by multiple regression.

The transmission/disequilibrium (TD) test (TDT), proposed, by Spielman et al., for binary traits is a powerful method for detection of linkage between a marker locus and a disease locus, in the presence of allelic association. As a test for linkage disequilibrium, the TDT makes the assumption that any allelic association present is due to linkage. Allison proposed a series of TD-type tests for quantitative traits and calculated their power, assuming that the marker locus is the disease locus. All these tests assume that the observations are independent, and therefore they are applicable, as a test for linkage, only for nuclear-family data. In this report, we propose a regression-based TD-type test for linkage between a marker locus and a quantitative trait locus, using information on the parent-to-offspring transmission status of the associated allele at the marker locus. This method does not require independence of observations, thus allowing for analysis of pedigree data as well, and allows adjustment for covariates. We investigate the statistical power and validity of the test by simulating markers at various recombination fractions from the disease locus.

Computer Simulation↗
PubMed1998

Mapping of quantitative trait loci on porcine chromosome 4.

A F2 population derived from a cross between European Large White and Chinese Meishan pigs was established in order to study the genetic basis of breed differences for growth and fat traits. Chromosome 4 was chosen for initial study as previous work had revealed quantitative trait loci (QTLs) on this chromosome affected growth and fat traits in a Wild Boar x Large White cross. Individuals in the F2 population were typed for nine markers spanning a region of approximately 124 CM. We found evidence for QTLs affecting growth between weaning and the end of test (additive effect: 43.4 g/day) and fat depth measured in the mid-back position (additive effect: 1.82 mm). There was no evidence of interactions between the QTLs and sex, grandparents or F1 sires, suggesting that the detected QTLs were fixed for alternative alleles in the Meishan and Large White breeds. Comparison of locations suggests that these QTLs could be the same as those found in the Wild Boar x Large White cross.

Animals↗
PubMed1999

Quantitative trait loci affecting survival and fertility-related traits in Caenorhabditis elegans show genotype-environment interactions, pleiotropy and epistasis.

We have identified, using composite interval mapping, quantitative trait loci (QTL) affecting a variety of life history traits (LHTs) in the nematode Caenorhabditis elegans. Using recombinant inbred strains assayed on the surface of agar plates, we found QTL for survival, early fertility, age of onset of sexual maturity, and population growth rate. There was no overall correlation between survival on solid media and previous measures of survival in liquid media. Of the four survival QTL found in these two environments, two have genotype-environment interactions (GEIs). Epistatic interactions between markers were detected for four traits. A multiple regression approach was used to determine which single markers and epistatic interactions best explained the phenotypic variance for each trait. The amount of phenotypic variance accounted for by genetic effects ranged from 13% (for internal hatching) to 46% (for population growth). Epistatic effects accounted for 9-11% of the phenotypic variance for three traits. Two regions containing QTL that affected more than one fertility-related trait were found. This study serves as an example of the power of QTL mapping for dissecting the genetic architecture of a suite of LHTs and indicates the potential importance of environment and GEIs in the evolution of this architecture.

Animals↗
PubMed2006

A quantitative trait locus for body fat on chromosome 1q43 in French Canadians: linkage and association studies.

OBJECTIVE: To explore a quantitative trait locus (QTL) on human chromosome 1q affecting BMI, adiposity, and fat-free mass phenotypes in the Quebec Family Study cohort. RESEARCH METHODS AND PROCEDURES: Non-parametric sibpair and variance component linkage analyses and family-based association studies were performed with a dense set of chromosome 1q43 microsatellites and single-nucleotide polymorphism markers in 885 adult individuals. RESULTS: Linkage was observed between marker D1S184 and BMI (p = 0.0004) and with body fat mass or percentage body fat (p < or = 0.0003), but no linkage was detected with fat-free mass. Furthermore, significant linkages (p < 0.0001) were achieved with subsamples of sibpairs at both ends of phenotype distributions. Association studies with quantitative transmission disequilibrium tests refined the linkage to a region overlapping the regulator of G-protein signaling 7 (RGS7) gene and extending to immediate upstream gene loci. DISCUSSION: The present study indicates that the QTL on chromosome 1q43 specifically affects total adiposity and provides a genetic mapping framework for the dissection of this adiposity locus.

Adipose Tissue↗
PubMed2003

Quantitative trait locus analysis of serum insulin, triglyceride, total cholesterol and phospholipid levels in the (SM/J x A/J)F2 mice.

Quantitative trait locus (QTL) analysis of serum insulin, triglyceride, total cholesterol and phospholipid levels at 10 weeks of age was performed in 321 F2 offspring from SM/J and A/J mice. Interval mapping revealed a total of 22 suggestive QTLs affecting the four traits: two insulin QTLs on Chromosomes (Chrs) 6 and 8; six triglyceride QTLs on Chrs 4, 8, 9, 11, 12 and 19; six total-cholesterol QTLs on Chrs 1, 3, 4, 14, 17 and 19; and eight phospholipid QTLs on Chrs 2, 3, 4, 6, 8, 10 and 19. Gender influenced the expression of eight of the suggestive QTLs. The total-cholesterol QTLs on Chrs 4, 14 and 17, the triglyceride QTL on Chr 9 and the phospholipid QTL on Chr 4 were specific to females. The phospholipid QTLs on Chrs 2 and 6 and the insulin QTL on Chr 8 were specific to males. In addition, common QTLs involved in the regulation of some of the traits were identified. The female-specific QTL on Chr 4 appeared to be involved in the regulation of total cholesterol and phospholipid levels. The QTL on Chr 8 affected insulin and phospholipid levels, whereas the Chr 19 QTL was common to the three lipid parameters.

Animals↗
PubMed2003

Fine mapping of three quantitative trait loci for late blight resistance in tomato using near isogenic lines (NILs) and sub-NILs.

An earlier study identified quantitative trait loci (QTLs) lb4, lb5b, and lb11b for quantitative resistance to Phytophthora infestans (late blight) in a backcross population derived from crossing susceptible cultivated tomato ( Lycopersicon esculentum) with resistant L. hirsutum. The QTLs were located in intervals spanning 28-47 cM. Subsequently, near-isogenic lines (NILs) were developed for lb4, lb5b, and lb11b by marker-assisted backcrossing to L. esculentum. Sub-NILs containing overlapping L. hirsutum segments across each QTL region were selected and used to validate the QTL effects, fine-map QTLs, and evaluate potential linkage drag between resistance QTLs and QTLs for horticultural traits. The NILs and sub-NILs were evaluated for disease resistance and eight horticultural traits at three field locations. Resistance QTLs were detected in all three sets of NIL lines, confirming the BC(1) mapping results. Lb4 mapped near TG609, and between TG182 and CT194, on chromosome 4, a 6.9-cM interval; lb5b mapped to an 8.8-cM interval between TG69a and TG413 on chromosome 5, with the most likely position near TG23; and lb11b mapped to a 15.1-cM interval on chromosome 11 between TG194 and TG400, with the peak centered between CT182 and TG147. Most QTLs for horticultural traits were identified in intervals adjacent to those containing the late blight resistance QTLs. Fine mapping of these QTLs permits the use of marker-assisted selection for the precise introgression of L. hirsutum segments containing late blight resistance alleles separately from those containing deleterious alleles at horticulturally important QTLs.

Analysis of Variance↗
PubMed2006

A review of statistical methods for expression quantitative trait loci mapping.

With high-throughput technologies now widely available, investigators can easily measure thousands of phenotypes for quantitative trait loci (QTL) mapping. Microarray measurements are particularly amenable to QTL mapping, as evidenced by a number of recent studies demonstrating utility across a broad range of biological endeavors. The early success stories have impelled a rapid increase in both the number and complexity of expression QTL (eQTL) experiments. Consequently, there is a need to consider the statistical principles involved in the design and analysis of these experiments and the methods currently being used. In this article we review these principles and methods and discuss the open questions most likely to yield significant progress toward increasing the amount of meaningful information obtained from eQTL mapping experiments.

Animals↗
PubMedDate not supplied

Mapping quantitative trait loci affecting fatness and breast muscle weight in meat-type chicken lines divergently selected on abdominal fatness.

Quantitative trait loci (QTL) for abdominal fatness and breast muscle weight were investigated in a three-generation design performed by inter-crossing two experimental meat-type chicken lines that were divergently selected on abdominal fatness. A total of 585 F2 male offspring from 5 F1 sires and 38 F1 dams were recorded at 8 weeks of age for live body, abdominal fat and breast muscle weights. One hundred-twenty nine microsatellite markers, evenly located throughout the genome and heterozygous for most of the F1 sires, were used for genotyping the F2 birds. In each sire family, those offspring exhibiting the most extreme values for each trait were genotyped. Multipoint QTL analyses using maximum likelihood methods were performed for abdominal fat and breast muscle weights, which were corrected for the effects of 8-week body weight, dam and hatching group. Isolated markers were assessed by analyses of variance. Two significant QTL were identified on chromosomes 1 and 5 with effects of about one within-family residual standard deviation. One breast muscle QTL was identified on GGA1 with an effect of 2.0 within-family residual standard deviation.

Abdominal Fat↗
PubMed2001

Mapping of quantitative trait loci with knockout/congenic strains.

Recently we have explored the use of knockout/congenic mouse strains for isolating and mapping quantitative trait loci (QTLs). Because most knockout strains have been bred to be B6.129 congenic strains, they can be used to test for QTLs in the targeted chromosomal area as long as there is a genetic difference between B6 and 129. Thus, we have tested a number of knockout/congenic strains in a series of behavioral tests in which mouse performance has a significant genetic component. We have also developed a breeding scheme for distinguishing the effects of background flanking genes from the targeted ablation. In screening several knockout/congenics, we have found at least one that harbors a behavioral QTL in the 129 chromosomal segment. The position of this QTL was confirmed subsequently by several F1 crosses.

Animals↗
PubMed2004

Epistasis in quantitative trait locus linkage analysis: interaction or main effect?

This paper explores a two-locus variance components model of quantitative trait locus (QTL) linkage for sib-pairs that incorporates epistasis. For a range of epistatic models the expected variance components and noncentrality parameter per sib-pair can be calculated, to indicate the power to detect epistasis. In QTL linkage analysis, additive and epistatic effects are in fact partially confounded; as a result, variance components under incorrect submodels can be distorted, with two main implications. First, the analysis of a single locus can in fact detect a QTL that has no main effect but interacts epistatically with another (unmeasured) locus. That is, single-locus approaches do not necessarily preclude the detection of purely epistatically interacting loci. Second, because the nonepistatic variance component estimates in submodels can partially absorb epistatic variance when it is not explicitly modeled, power to formally detect epistasis is low.

Alleles↗
PubMed2001

Detection of quantitative trait loci for meat quality in a commercial slaughter pig cross.

The primary goal of this study was to localize quantitative trait loci (QTL) affecting meat quality traits in swine. In total, 42 traits were scored on 305 F2 individuals from a commercial slaughter pig cross in Norway. F1 and F2 individuals were genotyped for 29 markers on Chromosomes (Chrs) 4, 6, and 7, since previous studies had revealed QTL affecting meat quality traits on these chromosomes. The most evident result was detection of a QTL affecting amount of intramuscular fat on Chr 6. The QTL might also influence tenderness, whereas no effect was observed for back-fat thickness. Additionally, suggestive evidence for QTL affecting other meat quality traits was found on Chr 4 and Chr 7.

Animals↗
PubMed2001

Using the mixed model for interval mapping of quantitative trait loci in outbred line crosses.

Interval mapping by simple regression is a powerful method for the detection of quantitative trait loci (QTLs) in line crosses such as F2 populations. Due to the ease of computation of the regression approach, relatively complex models with multiple fixed effects, interactions between QTLs or between QTLs and fixed effects can easily be accommodated. However, polygenic effects, which are not targeted in QTL analysis, cannot be treated as random effects in a least squares analysis. In a cross between true inbred lines this is of no consequence, as the polygenic effect contributes just to the residual variance. In a cross between outbred lines, however, if a trait has high polygenic heritability, the additive polygenic effect has a large influence on variation in the population. Here we extend the fixed model for the regression interval mapping method to a mixed model using an animal model. This makes it possible to use not only the observations from progeny (e.g. F2), but also those from the parents (F1) to evaluate QTLs and polygenic effects. We show how the animal model using parental observations can be applied to an outbred cross and so increase the power and accuracy of QTL analysis. Three estimation methods, i.e. regression and an animal model either with or without parental observations, are applied to simulated data. The animal model using parental observations is shown to have advantages in estimating QTL position and additive genotypic value, especially when the polygenic heritability is large and the number of progeny per parent is small.

Animals↗
PubMed2001

Quantitative trait loci for body weight in the intercross between SM/J and A/J mice.

We performed a genome-wide quantitative trait locus (QTL) analysis of body weight at 10 weeks of age in a population of 321 intercross offspring from SM/J and A/J mice, progenitor strains of SMXA recombinant inbred strains. Interval mapping revealed two significant QTLs, Bwq3 (body weight QTL3) and Bwq4, on Chromosomes (Chrs) 8 and 18 respectively, and five suggestive QTLs on Chrs 2, 6, 7, 15 and 19. Bwq3 and Bwq4 explained 6% of the phenotypic variance. The SM/J alleles at both QTLs increased body weight, though the SM/J mouse was smaller than the A/J mouse. On the other hand, four of the five suggestive QTLs detected had male-specific effects on body weight and the remainder was female-specific. These suggestive QTLs explained 5-6% of the phenotypic variance and all the SM/J alleles decreased body weight.

Alleles↗
PubMed2006

Identification of diabetes susceptibility loci in db mice by combined quantitative trait loci analysis and haplotype mapping.

To identify the disease-susceptibility genes of type 2 diabetes, we performed quantitative trait loci (QTL) analysis in F(2) populations generated from a BKS.Cg-m+/+Lepr(db) and C3H/HeJ intercross, taking advantage of genetically determined obesity and diabetes traits associated with the db gene. A genome-wide scan in the F(2) populations divided by sex and db genotypes identified 14 QTLs in total and 3 major QTLs on chromosome (Chr) 3 (LOD 5.78) for fat pad weight, Chr 15 (LOD 6.64) for body weight, and Chr 16 (LOD 8.15) for blood glucose concentrations. A linear-model-based genome scan using interactive covariates allowed us to consider sex- or sex-by db-specific effects of each locus. For the most significant QTL on Chr 16, the high-resolution haplotype comparison between BKS and C3H strains reduced the critical QTL interval from 20 to 4.6 Mb by excluding shared haplotype regions and identified 11 nonsynonymous single-nucleotide polymorphisms in six candidate genes.

Animals↗
PubMed2004

Multivariate analysis of quantitative trait loci influencing variation in anxiety-related behavior in laboratory mice.

The number and mode of action of quantitative trait loci (QTL) that contribute to behavioral variation in rodents is still largely unknown. On theoretical grounds, multivariate techniques are expected to yield new insights into this problem, but there are only a few examples of its application in practice. Here we explore the power of multivariate approaches to uncover the genetic architecture of 23 anxiety-related phenotypes in 1636 F2 laboratory mice. We detected QTL with a genome-wide significance threshold of P < 0.05 on 14 chromosomes, of which 10 correspond to those identified by univariate analysis. Novel QTL were found on Chromosomes 3, 9, 13, and 17. Thus, multivariate analyses increased the yield of QTL exceeding a genome-wide significance threshold by 40%. On the basis of these results and by the application of a QTL estimator, we show that the mean number of QTL influencing anxiety-related behavior in mice is 6, with a 95% upper limit of 14.

Animals↗
PubMed2001

Quantitative trait loci associated with reversal learning and latent inhibition in honeybees (Apis mellifera).

A study was conducted to identify quantitative trait loci (QTLs) that affect learning in honeybees. Two F1 supersister queens were produced from a cross between two established lines that had been selected for differences in the speed at which they reverse a learned discrimination between odors. Different families of haploid drones from two of these F1 queens were evaluated for two kinds of learning performance--reversal learning and latent inhibition--which previously showed correlated selection responses. Random amplified polymorphic DNA markers were scored from recombinant, haploid drone progeny that showed extreme manifestations of learning performance. Composite interval mapping procedures identified two QTLs for reversal learning (lrn2 and lrn3: LOD, 2.45 and 2.75, respectively) and one major QTL for latent inhibition (lrn1: LOD, 6.15). The QTL for latent inhibition did not map to either of the linkage groups that were associated with reversal learning. Identification of specific genes responsible for these kinds of QTL associations will open up new windows for better understanding of genes involved in learning and memory.

Animals↗
PubMed2004

Influence of sex and diet on quantitative trait loci for HDL cholesterol levels in an SM/J by NZB/BlNJ intercross population.

To investigate the dependence of HDL quantitative trait loci (QTL) on sex and diet, we generated a large intercross population of mice from parental strains SM/J and NZB/BlNJ. We measured HDL levels in progeny fed a chow diet and measured them again after 6, 12, and 16 weeks of feeding a high-fat, high-cholesterol diet. QTL analysis was performed on the 260 female and 253 male F(2) progeny. A total of 13 significant QTL were found. Four QTL were specific to female mice: Hdlq23 (Chr 6, 26 cM), Hdlq26 (Chr 10, 70 cM), Hdlq27 (Chr 15, 48 cM), and Hdlq32 (Chr 19, 40 cM). One significant QTL was specific to male mice: Hdlq29 (Chr 17, 36 cM). In addition, several QTL were found to have effects that were dependent on diet. Sex- and diet-dependent effects were characterized using a linear model-based genome scan method that avoids the potential pitfalls of subdivided data analysis. The dependence of QTL effects on sex suggests an important role for the sex hormones in HDL regulation. We recommend that sex should be explicitly accounted for in future studies in the genetics of HDL regulation in both mice and humans.

Animals↗
PubMed2005

Multiple quantitative trait loci for blood pressure interacting epistatically and additively on Dahl rat chromosome 2.

Our previous work demonstrated 2 quantitative trait loci (QTLs), C2QTL1 and C2QTL2, for blood pressure (BP) located on chromosome (Chr) 2 of Dahl salt-sensitive (DSS) rats. However, for a lack of markers, the 2 congenic strains delineating C2QTL1 and C2QTL2 could not be separated. The position of the C2QTL1 was only inferred by comparing 2 congenic strains, one having and another lacking a BP effect. Furthermore, it was not known how adjacent QTLs would interact with one another on Chr 2. In the current investigation, first, a critical chromosome marker was developed to separate 2 C2QTLs. Second, a congenic substrain was created to cover a chromosome fragment thought to harbor C2QTL1. Finally, a series of congenic strains was produced to systematically and comprehensively cover the entire Chr 2 segment containing C2QTL2 and other regions previously untested. Consequently, a total of 3 QTLs were discovered, with C2QTL3 located between C2QTL1 and C2QTL2. C2QTL1, C2QTL2, and C2QTL3 reside in chromosome segments of 5.7 centiMorgan (cM), 3.5 cM, and 1.5 cM, respectively. C2QTL1 interacted epistatically with either C2QTL2 or C2QTL3, whereas C2QTL2 and C2QTL3 showed additive effects to each other. These results suggest that BP QTLs closely linked in a segment interact epistatically and additively to one another on Chr 2.

Animals↗