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PubMed2004

[Two approaches of quantitative-trait linkage analysis].

ln this article, we discussed two model-free methods for detecting genetic linkage for quantitative traits, Haseman-Elston regression approach and variance components approach. The former is a regression approach for detecting linkage based on the squared difference or squared sums in quantitative trait values of sib-pairs and their estimated marker IBD scores. The latter can jointly model covariate effects along with variance components, including genetic component and non-genetic sources of variability. We have outlined the model assumption, the algorithm and the extensions for the both methods.

Computer Simulation↗
PubMed2004

Genetic dissection of a behavioral quantitative trait locus shows that Rgs2 modulates anxiety in mice.

Here we present a strategy to determine the genetic basis of variance in complex phenotypes that arise from natural, as opposed to induced, genetic variation in mice. We show that a commercially available strain of outbred mice, MF1, can be treated as an ultrafine mosaic of standard inbred strains and accordingly used to dissect a known quantitative trait locus influencing anxiety. We also show that this locus can be subdivided into three regions, one of which contains Rgs2, which encodes a regulator of G protein signaling. We then use quantitative complementation to show that Rgs2 is a quantitative trait gene. This combined genetic and functional approach should be applicable to the analysis of any quantitative trait.

Animals↗
PubMed2000

Mapping a quantitative trait locus via the EM algorithm and Bayesian classification.

Mapping a locus controlling a quantitative genetic trait (e.g., blood pressure) to a specific genomic region is of considerable interest. Data on the quantitative trait under consideration and several codominant genetic markers with known genomic locations are collected from members of families and statistically analyzed to draw inferences on the genomic position of the trait locus. The vector of parameters of interest comprises the pairwise recombination fractions, theta, between the putative quantitative trait locus and the marker loci. One of the major complications in estimating theta for a quantitative trait in humans is the lack of haplotype information on members of families. The purpose of this study was to devise a computationally simple and efficient method of estimation of theta in the absence of haplotype information. We have proposed a two-stage estimation procedure using the expectation-maximization (EM) algorithm. In the first stage, parameters of the QTL are estimated based on data of a sample of unrelated individuals. From estimates thus obtained, we have used a Bayes' rule to infer QTL genotypes of parents in families. Finally, in the second stage of the procedure, we have proposed an EM algorithm for obtaining the maximum likelihood estimate of theta based on data of informative families (which are identified upon inferring parental QTL genotypes performed in the first stage). We have shown, using simulated data, that the proposed procedure is cost-effective, computationally simple, and statistically efficient. As expected, analysis of data on multiple markers jointly is more efficient than the analysis based on single markers.

Algorithms↗
PubMed2003

Genome-wide searches for blood pressure quantitative trait loci in the stroke-prone spontaneously hypertensive rat of a Japanese colony.

OBJECTIVES: Although several quantitative trait loci for blood pressure have been reported in stroke-prone spontaneously hypertensive rats (SHRSP), the results are not always concordant among different crosses. To evaluate potential confounding factors in linkage analysis, we performed genome-wide screens in F2 populations derived from SHRSP and Wistar-Kyoto rats of a Japanese colony. METHODS: Two F cohorts were independently produced: F2-1 (110 male and 110 female rats), and F2-2 (174 male and 184 female rats). Blood pressure was measured longitudinally (from 2 to 5 months of age and 1 month after salt-loading) in F2-1, while it was measured at 13 weeks of age in F2-2. Subsequent to an initial screen with 251 markers in F2-1 male progeny, 170 markers were selected and characterized in the remaining populations. RESULTS: When 578 rats were analyzed together, markers from five chromosomal regions showed significant linkage to blood pressure at 13 weeks of age. The strongest and the most consistent linkage was found on rat chromosome 1 (a maximal log of the odds score reached 8.3). In the other regions, the degree of linkage was more prominent in either of sexes. Some evidence of age-specific and sex-specific linkage was detected in five additional regions in the F2-1 cohort. In the Japanese colony, however, there was no significant linkage to several chromosomal regions previously reported in other SHRSP colonies. CONCLUSIONS: Our data provide solid evidence of a chromosome-1 linkage and demonstrate the importance of aging, sex, and dietary manipulation in linkage analysis. Also, the combination of parental rat strains seems to be critical when searching for blood pressure quantitative trait loci.

Aging↗
PubMed1998

Mapping of serum amylase-1 and quantitative trait loci for milk production traits to cattle chromosome 4.

The present study was undertaken to confirm and refine the mapping of a quantitative trait locus in cattle for milk fat percentage that had earlier been reported to be linked to the serum amylase-1 locus, AM1. Five half-sib families from the previous study and 7 new ones were genotyped for nine microsatellite markers spanning chromosome 4. AM1 was mapped between the microsatellite markers BMS648 and BR6303. In a granddaughter design, interval mapping based on multiple-marker regression was utilized for an analysis of five milk production traits: milk yield, fat percentage and yield, and protein percentage and yield. In the families reported on previously, significant effects for fat and protein percentages were detected. In the new families, an effect on milk and fat yields was found. The most likely positions of the quantitative trait locus in both groups of families were in the same area of chromosome 4 in the vicinity of the obese locus. Direct effects of the obese locus were tested for using polymorphism in two closely linked microsatellites located 2.5 and 3.6 top downstream of the coding sequence. No firm evidence was found for an association between the obese locus and the tested traits.

Amylases↗
PubMed1993

Tests for major genes affecting quantitative traits in wild radish, Raphanus raphanistrum.

The number of gene loci coding for quantitative traits is an important issue in genetics. However, there are still very few empirical data on this point, especially in natural populations. I tested for major gene effects on ten quantitative traits in wild radish, using an indirect method based on the patterns of family means and within and between family variances for traits. This method should reveal whether a single locus is responsible for most of the variation in a trait. Eight of the traits measured were morphological dimensions of leaves and flowers; no strong evidence for major gene effects on these traits was found. In contrast, evidence for major gene effects was found in the other two traits, emergence time and flowering time.

Brassica↗
PubMed2001

A combinatorial partitioning method to identify multilocus genotypic partitions that predict quantitative trait variation.

Recent advances in genome research have accelerated the process of locating candidate genes and the variable sites within them and have simplified the task of genotype measurement. The development of statistical and computational strategies to utilize information on hundreds -- soon thousands -- of variable loci to investigate the relationships between genome variation and phenotypic variation has not kept pace, particularly for quantitative traits that do not follow simple Mendelian patterns of inheritance. We present here the combinatorial partitioning method (CPM) that examines multiple genes, each containing multiple variable loci, to identify partitions of multilocus genotypes that predict interindividual variation in quantitative trait levels. We illustrate this method with an application to plasma triglyceride levels collected on 188 males, ages 20--60 yr, ascertained without regard to health status, from Rochester, Minnesota. Genotype information included measurements at 18 diallelic loci in six coronary heart disease--candidate susceptibility gene regions: APOA1--C3--A4, APOB, APOE, LDLR, LPL, and PON1. To illustrate the CPM, we evaluated all possible partitions of two-locus genotypes into two to nine partitions (approximately 10(6) evaluations). We found that many combinations of loci are involved in sets of genotypic partitions that predict triglyceride variability and that the most predictive sets show nonadditivity. These results suggest that traditional methods of building multilocus models that rely on statistically significant marginal, single-locus effects, may fail to identify combinations of loci that best predict trait variability. The CPM offers a strategy for exploring the high-dimensional genotype state space so as to predict the quantitative trait variation in the population at large that does not require the conditioning of the analysis on a prespecified genetic model.

Adult↗
PubMed2003

Estimation and testing of parent-of-origin effects for quantitative traits.

Recent progress in developing family-based association methods has extended their use to the analysis of quantitative traits in the offspring and to the estimation, for dichotomous traits, of the relative contribution of genetic and environmental mechanisms for parent-of-origin effects. However, many traits of interest are not naturally measured on a binary scale yet are suspected or known to be influenced by imprinted genes, and there is consequent interest in seeking evidence for parent-of-origin effects at these loci. Here we show how simple linear models can be used to estimate these parent-of-origin effects for a broad class of phenotypes; in particular, normally distributed quantitative traits are easily dealt with.

Female↗
PubMed2006

A genome scan for quantitative trait loci affecting growth-related traits in an F1 family of Asian seabass (Lates calcarifer).

BACKGROUND: Body weight and length are economically important traits in foodfish species influenced by quantitative trait loci (QTL) and environmental factors. It is usually difficult to dissect the genetic and environmental effects. Asian seabass (Lates calcarifer) is an important marine foodfish species with a compact genome (approximately 700 Mb). The recent construction of a first generation linkage map of Asian seabass with 240 microsatellites provides a good opportunity to determine the number and position of QTL, and the magnitude of QTL effects with a genome scan. RESULTS: We conducted a genome scan for QTL affecting body weight, standard length and condition factors in an F1 family containing 380 full-sib individuals from a breeding stock by using 97 microsatellites evenly covering 24 chromosomes. Interval mapping and multiple QTL model mapping detected five significant and 27 suggestive QTL on ten linkage groups (LGs). Among the five significant QTL detected, three (qBW2-a, qTL2-a and qSL2-a) controlling body weight, total and standard length respectively, were mapped on the same region near Lca287 on LG2, and explained 28.8, 58.9 and 59.7% of the phenotypic variance. The other two QTL affecting body weight, qBW2-b and qBW3, were located on LG2 and 3, and accounted for 6.4 and 8.8% of the phenotypic variance. Suggestive QTL associated with condition factors are located on six different LGs. CONCLUSION: This study presents the first example of QTL detection for growth-related traits in an F1 family of a marine foodfish species. The results presented here will enable further fine-mapping of these QTL for marker-assisted selection of the Asian seabass, eventually identifying individual genes responsible for growth-related traits.

Animals↗
PubMed2002

Mapping epigenetic quantitative trait loci (QTL) altering a developmental trajectory.

Genetic variation in a quantitative trait that changes with age is important to both evolutionary biologists and breeders. A traditional analysis of the dynamics of genetic variation is based on the genetic variance-covariance matrix among different ages estimated from a quantitative genetic model. Such an analysis, however, cannot reveal the mechanistic basis of the genetic variation for a growth trait during ontogeny. Age-specific genetic variance at time t conditional on the causal genetic effect at time t - 1 implies the generation of episodes of new genetic variation arising during the interval t - 1 to t. In the present paper, the conditional genetic variance estimated from Zhu's (1995) conditional model was partitioned into its underlying individual quantitative trait loci (QTL) using molecular markers in an F2 progeny of poplars (Populus trichocarpa and Populus deltoides). These QTL, defined as epigenetic QTL, govern the alterations of growth trajectory in a population. Three epigenetic QTL were detected to contribute significantly to variation in growth trajectory during the period from the establishment year to the subsequent year in the field. It is suggested that the activation and expression of epigenetic QTL are influenced by the developmental status of trees and the environment in which they are grown.

Analysis of Variance↗
PubMed2003

Mapping loci influencing blood pressure in the Framingham pedigrees using model-free LOD score analysis of a quantitative trait.

This paper presents a method of performing model-free LOD-score based linkage analysis on quantitative traits. It is implemented in the QMFLINK program. The method is used to perform a genome screen on the Framingham Heart Study data. A number of markers that show some support for linkage in our study coincide substantially with those implicated in other linkage studies of hypertension. Although the new method needs further testing on additional real and simulated data sets we can already say that it is straightforward to apply and may offer a useful complementary approach to previously available methods for the linkage analysis of quantitative traits.

Adult Children↗
PubMed1999

Genetic variation maintained in multilocus models of additive quantitative traits under stabilizing selection.

Stabilizing selection for an intermediate optimum is generally considered to deplete genetic variation in quantitative traits. However, conflicting results from various types of models have been obtained. While classical analyses assuming a large number of independent additive loci with individually small effects indicated that no genetic variation is preserved under stabilizing selection, several analyses of two-locus models showed the contrary. We perform a complete analysis of a generalization of Wright's two-locus quadratic-optimum model and investigate numerically the ability of quadratic stabilizing selection to maintain genetic variation in additive quantitative traits controlled by up to five loci. A statistical approach is employed by choosing randomly 4000 parameter sets (allelic effects, recombination rates, and strength of selection) for a given number of loci. For each parameter set we iterate the recursion equations that describe the dynamics of gamete frequencies starting from 20 randomly chosen initial conditions until an equilibrium is reached, record the quantities of interest, and calculate their corresponding mean values. As the number of loci increases from two to five, the fraction of the genome expected to be polymorphic declines surprisingly rapidly, and the loci that are polymorphic increasingly are those with small effects on the trait. As a result, the genetic variance expected to be maintained under stabilizing selection decreases very rapidly with increased number of loci. The equilibrium structure expected under stabilizing selection on an additive trait differs markedly from that expected under selection with no constraints on genotypic fitness values. The expected genetic variance, the expected polymorphic fraction of the genome, as well as other quantities of interest, are only weakly dependent on the selection intensity and the level of recombination.

Alleles↗
PubMed2005

Strategies for mapping and cloning quantitative trait genes in rodents.

Over the past 15 years, more than 2,000 quantitative trait loci (QTLs) have been identified in crosses between inbred strains of mice and rats, but less than 1% have been characterized at a molecular level. However, new resources, such as chromosome substitution strains and the proposed Collaborative Cross, together with new analytical tools, including probabilistic ancestral haplotype reconstruction in outbred mice, Yin-Yang crosses and in silico analysis of sequence variants in many inbred strains, could make QTL cloning tractable. We review the potential of these strategies to identify genes that underlie QTLs in rodents.

Animals↗
PubMed1989

Mapping mendelian factors underlying quantitative traits using RFLP linkage maps.

The advent of complete genetic linkage maps consisting of codominant DNA markers [typically restriction fragment length polymorphisms (RFLPs)] has stimulated interest in the systematic genetic dissection of discrete Mendelian factors underlying quantitative traits in experimental organisms. We describe here a set of analytical methods that modify and extend the classical theory for mapping such quantitative trait loci (QTLs). These include: (i) a method of identifying promising crosses for QTL mapping by exploiting a classical formula of SEWALL WRIGHT; (ii) a method (interval mapping) for exploiting the full power of RFLP linkage maps by adapting the approach of LOD score analysis used in human genetics, to obtain accurate estimates of the genetic location and phenotypic effect of QTLs; and (iii) a method (selective genotyping) that allows a substantial reduction in the number of progeny that need to be scored with the DNA markers. In addition to the exposition of the methods, explicit graphs are provided that allow experimental geneticists to estimate, in any particular case, the number of progeny required to map QTLs underlying a quantitative trait.

Chromosome Mapping↗
PubMed2006

The X chromosome in quantitative trait locus mapping.

The X chromosome requires special treatment in the mapping of quantitative trait loci (QTL). However, most QTL mapping methods, and most computer programs for QTL mapping, have focused exclusively on autosomal loci. We describe a method for appropriate treatment of the X chromosome for QTL mapping in experimental crosses. We address the important issue of formulating the null hypothesis of no linkage appropriately. If the X chromosome is treated like an autosome, a sex difference in the phenotype can lead to spurious linkage on the X chromosome. Further, the number of degrees of freedom for the linkage test may be different for the X chromosome than for autosomes, and so an X chromosome-specific significance threshold is required. To address this issue, we propose a general procedure to obtain chromosome-specific significance thresholds that controls the genomewide false positive rate at the desired level. We apply our methods to data on gut length in a large intercross of mice carrying the Sox10Dom mutation, a model of Hirschsprung disease. We identified QTL contributing to variation in gut length on chromosomes 5 and 18. We found suggestive evidence of linkage to the X chromosome, which would be viewed as strong evidence of linkage if the X chromosome was treated as an autosome. Our methods have been implemented in the package R/qtl.

Animals↗
PubMed2002

Mapping quantitative trait loci in inbred backcross lines of Lycopersicon pimpinellifolium (LA1589).

Although tomato has been the subject of extensive quantitative trait loci (QTLs) mapping experiments, most of this work has been conducted on transient populations (e.g., F2 or backcross) and few homozygous, permanent mapping populations are available. To help remedy this situation, we have developed a set of inbred backcross lines (IBLs) from the interspecific cross between Lycopersicon esculentum cv. E6203 and L. pimpinellifolium (LA1589). A total of 170 BC2F1 plants were selfed for five generations to create a set of homozygous BC2F6 lines by single-seed descent. These lines were then genotyped for 127 marker loci covering the entire tomato genome. These IBLs were evaluated for 22 quantitative traits. In all, 71 significant QTLs were identified, 15% (11/71) of which mapped to the same chromosomal positions as QTLs identified in earlier studies using the same cross. For 48% (34/71) of the detected QTLs, the wild allele was associated with improved agronomic performance. A number of new QTLs were identified including several of significant agronomic importance for tomato production: fruit shape, firmness, fruit color, scar size, seed and flower number, leaf curliness, plant growth, fertility, and flowering time. To improve the utility of the IBL population, a subset of 100 lines giving the most uniform genome coverage and map resolution was selected using a randomized greedy algorithm as implemented in the software package MapPop (http://www.bio.unc.edu/faculty/vision/lab/ mappop/). The map, phenotypic data, and seeds for the IBL population are publicly available (http://soldb.cit.cornell.edu) and will provide tomato geneticists and breeders with a genetic resource for mapping, gene discovery, and breeding.

Genome, Plant↗
PubMed1998

Association of endogenous viral genes with quantitative traits in chickens selected for high egg production and susceptibility or resistance to Marek's disease.

1. The association of endogenous viral (ev) genes with quantitative traits in 2 genetically distinct sets of White Leghorn strains were investigated. Strain S had been selected for susceptibility to Marek's disease (MD) whereas strain K had been selected for resistance to MD and high egg production and egg weight. 2. In all, 8 ev genes were typed. Ev10, ev19 and 'newB' occurred exclusively in strain S, 'newA' occurred only in strain K, and ev1, ev3, ev6 and ev8 occurred in both strains. 3. Whereas ev6 and ev8 were associated with reduction in egg production rate in strain S, in strain K, the presence of ev3 was associated with increased group specific antigen. 4. The genetic background of the chicken strain may play a role in the way certain ev genes affect traits. 5. It was thought that the position of ev genes on the chromosome may be important and their association with traits of economic importance make them potential genetic markers for uncovering quantitative trait loci.

Animals↗
PubMed1998

Levels of genetic polymorphism: marker loci versus quantitative traits.

Species are the units used to measure ecological diversity and alleles are the units of genetic diversity. Genetic variation within and among species has been documented most extensively using allozyme electrophoresis. This reveals wide differences in genetic variability within, and genetic distances among, species, demonstrating that species are not equivalent units of diversity. The extent to which the pattern observed for allozymes can be used to infer patterns of genetic variation in quantitative traits depends on the forces generating and maintaining variability. Allozyme variation is probably not strictly neutral but, nevertheless, heterozygosity is expected to be influenced by population size and genetic distance will be affected by time since divergence. The same is true for quantitative traits influenced by many genes and under weak stabilizing selection. However, the limited data available suggest that allozyme variability is a poor predictor of genetic variation in quantitative traits within populations. It is a better predictor of general phenotypic divergence and of postzygotic isolation between populations or species, but is only weakly correlated with prezygotic isolation. Studies of grasshopper and planthopper mating signal variation and assortative mating illustrate how these characters evolve independently of general genetic and morphological variation. The role of such traits in prezygotic isolation, and hence speciation, means that they will contribute significantly to the diversity of levels of genetic variation within and among species.

Alleles↗