Xu Shizhong | PubMed Health

PubMed2004

[Maximum likelihood analysis for mapping dynamic trait QTL in outbred population. I . Methodology].

The quantitative traits whose phenotypic values change with time in life or other quantitative factors, were defined as dynamic traits. Based on the idea about random regression test-day model for estimating breeding values in animal evaluation, a mathematic model was constructed for mapping dynamic trait loci by using Legendre polynomials to model dynamic changes of each genetic effect. The Maximum likelihood analysis implemented via EM algorithm was used to estimate the parameters, including QTL position, fixed genetic regression effects for dynamic trait QTL mapping in outbred population. Compared with the existing method for dynamic trait mapping QTL, the new method presented here not only allowed to sample dynamic trait in disequillibrium way, but also can achieve to map dynamic traits QTL in any resource population by just one step. The further study on dynamic trait mapping QTL was theoretically discussed by incorporating genetic analysis of dynamic trait into general mapping QTL.

Likelihood Functions↗

PubMed2004

[Maximum likelihood analysis for mapping dynamic trait QTL in outbred population II. Simulation].

Based on the maximum likelihood analysis principle for dynamic trait QTL mapping, selecting three orders Legendre polynomial as sub-model,the effects of the individual number, the frequency of test day,the marker density and heritability on detecting power are investigated by Monte-Carlo simulation. Each factor is divided into three levels such as the high,middle and low,the combinations of which are arranged by using orthologal design. The simulating result shows that the high heritability needs less number of individuals and frequency of test day than the low one, but the number of individuals of more than 300 and the frequency of test day of 5% above can guarantee sufficient detecting power no matter what the heritability is like. The number of individuals has almost the same effect as the frequency of test day in dynamic traits QTL mapping and the number of individuals and the frequency of test day compensate each other under the same size of samples. As to the QTL detection for a dynamic point,simulation indicates that the presented dynamic trait QTL mapping method that focuses on the whole dynamic process is significantly superior to the classical mapping methods on each individual dynamic point.

Humans↗