The use of linkage disequilibrium to map quantitative trait loci

2005 ◽  
Vol 45 (8) ◽  
pp. 837 ◽  
Author(s):  
M. E. Goddard ◽  
T. H. E. Meuwissen

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.

2004 ◽  
Vol 83 (1) ◽  
pp. 41-47 ◽  
Author(s):  
JIHAD M. ABDALLAH ◽  
BRIGITTE MANGIN ◽  
BRUNO GOFFINET ◽  
CHRISTINE CIERCO-AYROLLES ◽  
MIGUEL PÉREZ-ENCISO

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.


2004 ◽  
Vol 4 (5) ◽  
pp. 315-321 ◽  
Author(s):  
Y Gong ◽  
Z Wang ◽  
T Liu ◽  
W Zhao ◽  
Y Zhu ◽  
...  

Genetics ◽  
2002 ◽  
Vol 160 (2) ◽  
pp. 779-792 ◽  
Author(s):  
Rongling Wu ◽  
Chang-Xing Ma ◽  
George Casella

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.


2019 ◽  
Vol 225 (3) ◽  
pp. 1218-1233 ◽  
Author(s):  
Wenjie Lu ◽  
Liang Xiao ◽  
Mingyang Quan ◽  
Qingshi Wang ◽  
Yousry A. El‐Kassaby ◽  
...  

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