A comparison between methods for linkage disequilibrium fine mapping of quantitative trait loci

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.

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The use of linkage disequilibrium to map quantitative trait loci

Australian Journal of Experimental Agriculture ◽

10.1071/ea05066 ◽

2005 ◽

Vol 45 (8) ◽

pp. 837 ◽

Cited By ~ 20

Author(s):

M. E. Goddard ◽

T. H. E. Meuwissen

Keyword(s):

Linkage Disequilibrium ◽

Quantitative Trait Loci ◽

Statistical Model ◽

Quantitative Trait ◽

Linear Models ◽

Chromosome Segment ◽

Identical By Descent ◽

Trait Loci ◽

Linkage Disequilibrium Information ◽

Chromosome Segments

This paper reviews the causes of linkage disequilibrium and its use in mapping quantitative trait loci. The many causes of linkage disequilibrium can be understood as due to similarity in the coalescence tree of different loci. Consideration of the way this comes about allows us to divide linkage disequilibrium into 2 types: linkage disequilibrium between any 2 loci, even if they are unlinked, caused by variation in the relatedness of pairs of animals; and linkage disequilibrium due to the inheritance of chromosome segments that are identical by descent from a common ancestor. The extent of linkage disequilibrium due to the latter cause can be logically measured by the chromosome segment homozygosity which is the probability that chromosome segments taken at random from the population are identical by descent. This latter cause of linkage disequilibrium allows us to map quantitative trait loci to chromosome regions. The former cause of linkage disequilibrium can cause artefactual quantitative trait loci at any position in the genome. These artefacts can be avoided by fitting the relatedness of animals in the statistical model used to map quantitative trait loci. In the future it may be convenient to estimate this degree of relatedness between individuals from markers covering the whole genome. The statistical model for mapping quantitative trait loci also requires us to estimate the probability that 2 animals share quantitative trait loci alleles at a particular position because they have inherited a chromosome segment containing the quantitative trait loci identical by descent. Current methods to do this all involve approximations. Methods based on concepts of coalescence and chromosome segment homozygosity are useful, but improvements are needed for practical analysis of large datasets. Once these probabilities are estimated they can be used in flexible linear models that conveniently combine linkage and linkage disequilibrium information.

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Maximum likelihood mapping of quantitative trait loci using full-sib families.

Genetics ◽

10.1093/genetics/132.4.1211 ◽

1992 ◽

Vol 132 (4) ◽

pp. 1211-1222 ◽

Cited By ~ 2

Author(s):

S A Knott ◽

C S Haley

Keyword(s):

Quantitative Trait Loci ◽

Maximum Likelihood ◽

Quantitative Trait ◽

Simulated Data ◽

Likelihood Method ◽

Parameter Estimates ◽

Random Component ◽

Test Statistic ◽

Trait Loci ◽

Sib Families

Abstract A maximum likelihood method is presented for the detection of quantitative trait loci (QTL) using flanking markers in full-sib families. This method incorporates a random component for common family effects due to additional QTL or the environment. Simulated data have been used to investigate this method. With a fixed total number of full sibs power of detection decreased substantially with decreasing family size. Increasing the number of alleles at the marker loci (i.e., polymorphism information content) and decreasing the interval size about the QTL increased power. Flanking markers were more powerful than single markers. In testing for a linked QTL the test must be made against a model which allows for between family variation (i.e., including an unlinked QTL or a between family variance component) or the test statistic may be grossly inflated. Mean parameter estimates were close to the simulated values in all situations when fitting the full model (including a linked QTL and common family effect). If the common family component was omitted the QTL effect was overestimated in data in which additional genetic variance was simulated and when compared with an unlinked QTL model there was reduced power. The test statistic curves, reflecting the likelihood of the QTL at each position along the chromosome, have discontinuities at the markers caused by adjacent pairs of markers providing different amounts of information. This must be accounted for when using flanking markers to search for a QTL in an outbred population.

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TIGER: A software system for fine-mapping quantitative trait loci

Archives Animal Breeding ◽

10.5194/aab-51-402-2008 ◽

2008 ◽

Vol 51 (4) ◽

pp. 402-412

Author(s):

C. Baes ◽

N. Reinsch

Keyword(s):

Linkage Disequilibrium ◽

Quantitative Trait Loci ◽

Fine Mapping ◽

Quantitative Trait ◽

Variance Component Analysis ◽

Software System ◽

Linkage Disequilibrium Analysis ◽

Domestic Species ◽

Trait Loci ◽

Trait Locus

Abstract. The localisation of quantitative trait loci which contribute significantly to phenotype variation of economically important traits in domestic species has become an important goal in animal genomics. Several such loci have been roughly identified using linkage analyses; however the focus has now shifted towards fine mapping and pinpointing causal mutations. In the context of a cooperative national research project, the software system TIGER was developed. TIGER is a UNIX script linking several individual Fortran programmes and is used for comprehensive variance component analysis of fine mapping data. Starting with raw genotype data, pedigree and marker map information and ending with a residual maximum likelihood-based test for each putative quantitative trait locus position, the software provides the user with an "all in one" package capable of linkage analysis, linkage disequilibrium analysis and combined linkage/linkage disequilibrium analysis. The software system has been employed in 4 fine mapping projects on 4 distinct cattle chromosomes.

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Joint Linkage and Linkage Disequilibrium Mapping of Quantitative Trait Loci in Natural Populations

Genetics ◽

10.1093/genetics/160.2.779 ◽

2002 ◽

Vol 160 (2) ◽

pp. 779-792 ◽

Cited By ~ 5

Author(s):

Rongling Wu ◽

Chang-Xing Ma ◽

George Casella

Keyword(s):

Linkage Disequilibrium ◽

Quantitative Trait Loci ◽

Linkage Analysis ◽

Quantitative Trait ◽

Genome Mapping ◽

Linkage Disequilibrium Mapping ◽

Allelic Association ◽

Mapping Strategy ◽

Trait Loci ◽

New Strategy

AbstractLinkage analysis and allelic association (also referred to as linkage disequilibrium) studies are two major approaches for mapping genes that control simple or complex traits in plants, animals, and humans. But these two approaches have limited utility when used alone, because they use only part of the information that is available for a mapping population. More recently, a new mapping strategy has been designed to integrate the advantages of linkage analysis and linkage disequilibrium analysis for genome mapping in outcrossing populations. The new strategy makes use of a random sample from a panmictic population and the open-pollinated progeny of the sample. In this article, we extend the new strategy to map quantitative trait loci (QTL), using molecular markers within the EM-implemented maximum-likelihood framework. The most significant advantage of this extension is that both linkage and linkage disequilibrium between a marker and QTL can be estimated simultaneously, thus increasing the efficiency and effectiveness of genome mapping for recalcitrant outcrossing species. Simulation studies are performed to test the statistical properties of the MLEs of genetic and genomic parameters including QTL allele frequency, QTL effects, QTL position, and the linkage disequilibrium of the QTL and a marker. The potential utility of our mapping strategy is discussed.

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