Mapping Quantitative Trait Loci Using Linkage Disequilibrium: Marker- versus Trait-based Methods (original) (raw)
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A comparison between methods for linkage disequilibrium fine mapping of quantitative trait loci
Genetical Research, 2004
We present a maximum likelihood method for mapping quantitative trait loci that uses linkage disequilibrium information from single and multiple markers. We made paired comparisons between analyses using a single marker, two markers and six markers. We also compared the method to single marker regression analysis under several scenarios using simulated data. In general, our method outperformed regression (smaller mean square error and confidence intervals of location estimate) for quantitative trait loci with dominance effects. In addition, the method provides estimates of the frequency and additive and dominance effects of the quantitative trait locus.
Linkage disequilibrium fine mapping of quantitative trait loci: A simulation study
Genetics Selection Evolution, 2003
Recently, the use of linkage disequilibrium (LD) to locate genes which affect quantitative traits (QTL) has received an increasing interest, but the plausibility of fine mapping using linkage disequilibrium techniques for QTL has not been well studied. The main objectives of this work were to (1) measure the extent and pattern of LD between a putative QTL and nearby markers in finite populations and (2) investigate the usefulness of LD in fine mapping QTL in simulated populations using a dense map of multiallelic or biallelic marker loci. The test of association between a marker and QTL and the power of the test were calculated based on singlemarker regression analysis. The results show the presence of substantial linkage disequilibrium with closely linked marker loci after 100 to 200 generations of random mating. Although the power to test the association with a frequent QTL of large effect was satisfactory, the power was low for the QTL with a small effect and/or low frequency. More powerful, multi-locus methods may be required to map low frequent QTL with small genetic effects, as well as combining both linkage and linkage disequilibrium information. The results also showed that multiallelic markers are more useful than biallelic markers to detect linkage disequilibrium and association at an equal distance.
A new method to fine map a quantitative trait locus using linkage disequilibrium
A new approach was developed to fine map a biallelic QTL using linkage disequilibrium (LD). It uses the probability that a maternal (paternal) QTL allele of each individual is the mutant QTL allele, conditional on the pedigree and marker information. These probabilities were derived recursively from the haplotype-specific mutant QTL allele frequencies in the founders. As the haplotypes of founders are not known, their probabilities were estimated by MCMC methods. This model has fewer parameters than the usual model, because it relates the means and covariances of the QTL gametic values to the QTL allele effect and their frequencies. Consequently, this approach is expected to be more acccurate. To overcome the computing difficulties in exact calculation of IBD probabilities, an MCMC method was used to derive approximate conditional probabilities of inheriting maternal and paternal QTL alleles. A residual maximum likelihood method (REML) was implemented to map the QTL, using a Newton-Raphson algorithm. The QTL position, QTL effect, haplotype-specific mutant QTL allele frequencies and polygenic and residual variance components were jointly estimated for each interval. The derivatives of the residual likelihood were obtained by automated differentiation. A simulated population was analyzed to compare the ability of this technique to fine map a QTL with two others methods. In the first method, identity by descent QTL covariances are used to model LD and cosegregation of the alleles at linked loci. In the second, identity by descent QTL covariances are used only to model the cosegregation of the alleles, and LD is modeled by including the marker haplotypes as fixed effects in the model. LD was simulated by introducing a mutation at the QTL followed by 100 generations of random mating. Different genetic designs were simulated, under linkage and linkage disequilibrium and with various QTL effects, to obtain power and accuracy of the parameter estimates.
High resolution mapping of quantitative trait loci by linkage disequilibrium analysis
European Journal of Human Genetics, 2002
Two methods, linkage analysis and linkage disequilibrium (LD) mapping or association study, are usually utilised for mapping quantitative trait loci (QTL). Linkage mapping is appropriate for low resolution mapping to localise trait loci to broad chromosome regions within a few cM (510 cM), and is based on family data. Linkage disequilibrium mapping, on the other hand, is useful in high resolution or fine mapping, and is based on both population and family data. Using only one marker, one may carry out single-point linkage analysis and linkage disequilibrium mapping. Using two or more markers, it is possible to flank the QTL by multipoint analysis. The development and thus availability of dense marker maps, such as single nucleotide polymorphisms (SNP) in human genome, presents a tremendous opportunity for multipoint fine mapping. In this article, we propose a regression approach of mapping QTL by linkage disequilibrium mapping based on population data. Assuming that two marker loci flank one quantitative trait locus, a two-point linear regression is proposed to analyse population data. We derive analytical formulas of parameter estimations, and non-centrality parameters of appropriate tests of genetic effects and linkage disequilibrium coefficients. The merit of the method is shown by the power calculation and comparison. The two-point regression model can capture much more linkage and linkage disequilibrium information than that derived when only one marker is used. For a complex disease with heritability h 2 50.15, a study with sample size of 250 can provide high power for QTL detection under moderate linkage disequilibria.
Linkage Disequilibrium Mapping of Quantitative-Trait Loci by Selective Genotyping
American Journal of Human Genetics, 2005
The principles of linkage disequilibrium mapping of dichotomous diseases can be well applied to the mapping of quantitative-trait loci through the method of selective genotyping. In 1999, M. Slatkin considered a truncation selection (TS) approach. We propose in this report an extended TS approach and an extreme-rank-selection (ERS) approach. The properties of these selection approaches are studied analytically. By using a simulation study, we demonstrate that both the extended TS approach and the ERS approach provide remarkable improvements over Slatkin's original TS approach.
High-Resolution Association Mapping of Quantitative Trait Loci: A Population-Based Approach
Genetics, 2005
In this article, population-based regression models are proposed for high-resolution linkage disequilibrium mapping of quantitative trait loci (QTL). Two regression models, the “genotype effect model” and the “additive effect model,” are proposed to model the association between the markers and the trait locus. The marker can be either diallelic or multiallelic. If only one marker is used, the method is similar to a classical setting by Nielsen and Weir, and the additive effect model is equivalent to the haplotype trend regression (HTR) method by Zaykin et al. If two/multiple marker data with phase ambiguity are used in the analysis, the proposed models can be used to analyze the data directly. By analytical formulas, we show that the genotype effect model can be used to model the additive and dominance effects simultaneously; the additive effect model takes care of the additive effect only. On the basis of the two models, F-test statistics are proposed to test association between t...
Combined high resolution linkage and association mapping of quantitative trait loci
European Journal of Human Genetics, 2003
In this paper, we investigate variance component models of both linkage analysis and high resolution linkage disequilibrium (LD) mapping for quantitative trait loci (QTL). The models are based on both family pedigree and population data. We consider likelihoods which utilize flanking marker information, and carry out an analysis of model building and parameter estimations. The likelihoods jointly include recombination fractions, LD coefficients, the average allele substitution effect and allele dominant effect as parameters. Hence, the model simultaneously takes care of the linkage, LD or association and the effects of the putative trait locus. The models clearly demonstrate that linkage analysis and LD mapping are complementary, not exclusive, methods for QTL mapping. By power calculations and comparisons, we show the advantages of the proposed method: (1) population data can provide information for LD mapping, and family pedigree data can provide information for both linkage analysis and LD mapping; (2) using family pedigree data and a sparse marker map, one may investigate the prior suggestive linkage between trait locus and markers to obtain low resolution of the trait loci, because linkage analysis can locate a broad candidate region; (3) with the prior knowledge of suggestive linkage from linkage analysis, both population and family pedigree data can be used simultaneously in high resolution LD mapping based on a dense marker map, since LD mapping can increase the resolution for candidate regions; (4) models of high resolution LD mappings using two flanking markers have higher power than that of models of using only one marker in the analysis; (5) excluding the dominant variance from the analysis when it does exist would lose power; (6) by performing linkage interval mappings, one may get higher power than by using only one marker in the analysis.
The American Journal of Human Genetics, 2006
Selective genotyping is used to increase efficiency in genetic association studies of quantitative traits by genotyping only those individuals who deviate from the population mean. However, selection distorts the conditional distribution of the trait given genotype, and such data sets are usually analyzed using case-control methods, quantitative analysis within selected groups, or a combination of both. We show that Hotelling's T 2 test, recently proposed for association studies of one or several tagging single-nucleotide polymorphisms in a prospective (i.e., trait given genotype) design, can also be applied to the retrospective (i.e., genotype given trait) selective-genotyping design, and we use simulation to demonstrate its improved power over existing methods.