Bayesian Shrinkage Analysis of Quantitative Trait Loci
for Dynamic Traits
Runqing Yang 1 and Shizhong Xu 2*
1 Shanghai Jiaotong University
2 University of California, Riverside
* To whom correspondence should be addressed. E-mail: xu{at}genetics.ucr.edu.
Submitted on August 1, 2006
Revised on November 6, 2006
Accepted on 23 March 2007
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Abstract |
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Many quantitative traits are measured repeatedly during life of an organism. Such traits are called dynamic traits. The pattern of the changes of a dynamic trait is called the growth trajectory. Studying the growth trajectory may enhance our understanding of the genetic architecture of the growth trajectory. Recently, we developed an interval mapping procedure to map QTL for dynamic traits under the maximum likelihood framework. We fit the growth trajectory by Legendre polynomials. The method intended to map one QTL at a time and the entire QTL analysis involved scanning the entire genome by fitting multiple single QTL models. In this study, we propose a Bayesian shrinkage analysis for estimating and mapping multiple QTL in a single model. The method is a combination between the shrinkage mapping for individual quantitative traits and the Legendre polynomial analysis for dynamic traits. The multiple QTL model is implemented in two ways: (1) a fixed interval approach where a QTL is placed in each marker interval; and (2) a moving interval approach where the position of a QTL can be searched in a range that covers many marker intervals. Simulation study shows that the Bayesian shrinkage method generates much better signals for QTL than the interval mapping approach. We propose several alternative methods to present the results of the Bayesian shrinkage analysis. In particular, we found that the Wald-test statistic profile can serve as a mechanism to test the significance of a putative QTL.
Key Words:
Bayes, Dynamic trait, Legendre polynomial, MCMC, QTL
