A quantitative genetics model for viability selection

被引:43
作者
Luo, L [1 ]
Zhang, YM [1 ]
Xu, S [1 ]
机构
[1] Univ Calif Riverside, Dept Bot & Plant Sci, Riverside, CA 92521 USA
关键词
EM algorithm; liability model; maximum likelihood; segregation distortion; viability locus;
D O I
10.1038/sj.hdy.6800615
中图分类号
Q14 [生态学(生物生态学)];
学科分类号
071012 ; 0713 ;
摘要
Viability selection will change gene frequencies of loci controlling fitness. Consequently, the frequencies of marker loci linked to the viability loci will also change. In genetic mapping, the change of marker allelic frequencies is reflected by the departure from Mendelian segregation ratio. The non-Mendelian segregation of markers has been used to map viability loci along the genome. However, current methods have not been able to detect the amount of selection (s) and the degree of dominance ( h) simultaneously. We developed a method to detect both s and h using an F2 mating design under the classical fitness model. We also developed a quantitative genetics model for viability selection by proposing a continuous liability controlling the viability of individuals. With the liability model, mapping viability loci has been formulated as mapping quantitative trait loci. As a result, nongenetic systematic environmental effects can be easily incorporated into the model and subsequently separated from the genetic effects of the viability loci. The quantitative genetic model has been verified with a series of Monte Carlo simulation experiments.
引用
收藏
页码:347 / 355
页数:9
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