scholarly journals Improved Power Offered by a Score Test for Linkage Disequilibrium Mapping of Quantitative-Trait Loci by Selective Genotyping

2006 ◽  
Vol 78 (3) ◽  
pp. 498-504 ◽  
Author(s):  
Chris Wallace ◽  
Juliet M. Chapman ◽  
David G. Clayton
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.


BMC Genetics ◽  
2014 ◽  
Vol 15 (1) ◽  
pp. 20 ◽  
Author(s):  
Jie Yang ◽  
Wei Zhu ◽  
Jiansong Chen ◽  
Qiao Zhang ◽  
Song Wu

2016 ◽  
Vol 18 (2) ◽  
pp. 195-204
Author(s):  
Soyoun Lee ◽  
Jie Yang ◽  
Jiayu Huang ◽  
Hao Chen ◽  
Wei Hou ◽  
...  

2004 ◽  
Vol 13 (2) ◽  
pp. 216-231 ◽  
Author(s):  
Ruzong Fan ◽  
Christie Spinka ◽  
Lei Jin ◽  
Jee Sun Jung

Genetics ◽  
2003 ◽  
Vol 163 (4) ◽  
pp. 1533-1548 ◽  
Author(s):  
Xiang-Yang Lou ◽  
George Casella ◽  
Ramon C Littell ◽  
Mark C K Yang ◽  
Julie A Johnson ◽  
...  

AbstractFor tightly linked loci, cosegregation may lead to nonrandom associations between alleles in a population. Because of its evolutionary relationship with linkage, this phenomenon is called linkage disequilibrium. Today, linkage disequilibrium-based mapping has become a major focus of recent genome research into mapping complex traits. In this article, we present a new statistical method for mapping quantitative trait loci (QTL) of additive, dominant, and epistatic effects in equilibrium natural populations. Our method is based on haplotype analysis of multilocus linkage disequilibrium and exhibits two significant advantages over current disequilibrium mapping methods. First, we have derived closed-form solutions for estimating the marker-QTL haplotype frequencies within the maximum-likelihood framework implemented by the EM algorithm. The allele frequencies of putative QTL and their linkage disequilibria with the markers are estimated by solving a system of regular equations. This procedure has significantly improved the computational efficiency and the precision of parameter estimation. Second, our method can detect marker-QTL disequilibria of different orders and QTL epistatic interactions of various kinds on the basis of a multilocus analysis. This can not only enhance the precision of parameter estimation, but also make it possible to perform whole-genome association studies. We carried out extensive simulation studies to examine the robustness and statistical performance of our method. The application of the new method was validated using a case study from humans, in which we successfully detected significant QTL affecting human body heights. Finally, we discuss the implications of our method for genome projects and its extension to a broader circumstance. The computer program for the method proposed in this article is available at the webpage http://www.ifasstat.ufl.edu/genome/~LD.


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