A general statistical framework for unifying interval and linkage disequilibrium mapping: Toward high-resolution mapping of quantitative traits

被引:18
|
作者
Lou, XY [1 ]
Casella, G
Todhunter, RJ
Yang, MCK
Wu, RL
机构
[1] Univ Florida, Dept Stat, Gainesville, FL 32611 USA
[2] Cornell Univ, New York State Coll Vet Med, James A Baker Inst Anim Hlth, Ithaca, NY 14853 USA
[3] Zhejiang Forestry Univ, Lin An 311300, Zhejiang, Peoples R China
基金
中国国家自然科学基金; 美国国家科学基金会;
关键词
EM algorithm; interval mapping; linkage disequilibrium; maximum liklihood estimate; quantitative trait loci;
D O I
10.1198/016214504000001295
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
The nonrandom association between different genes, termed linkage disequilibrium (LD), provides a powerful tool for high-resolution mapping of quantitative trait loci (QTL) underlying complex traits. This LD-based mapping approach can be made more efficient when it is coupled with interval mapping characterizing the genetic distance between markers and QTL. This article describes a general statistical framework for simultaneously estimating the linkage and LD that are related in a two-stage hierarchical sampling scheme. This framework is constructed within a maximum likelihood context and can be expanded to fine-scale mapping of complex traits for different population structures and reproductive behaviors. We provide a closed-form solution for joint estimation of quantitative genetic parameters describing QTL effects, QTL position and residual variances, and population genetic parameters describing allele frequencies and QTL-marker LD. We perform simulation studies to investigate the statistical properties of our joint analysis model for interval and LD mapping. An example using body weights of dogs from a multifamily outcrossed pedigree illustrates the use of the model.
引用
收藏
页码:158 / 171
页数:14
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