关键词: 四向杂交设计, QTL作图, 极大似然估计, EM算法

Abstract:

In recent years, there has been a great deal of interests in the development of methodology to map quantitative trait loci (QTLs) relative to known marker map in population derived from inbred line crosses. However, mapping populations that can be handled by most of developed methods must be derived from the cross of two inbred lines. The drawback of these designs is that the statistical inference space is quite narrow and thus results from one cross cannot be generalized to other crosses derived from different inbred lines. Xu first proposed the four-way cross design of QTL mapping intended to increase the statistical inference space and the opportunity for detecting more QTL. Four-way cross design is a mating design that is derived from the cross of four inbred lines. Although iteratively reweighted least squares (IRWLS) method for mapping QTL in four-way cross design has been proposed, low efficiency of this method was predicted due to neglecting the mixture distribution of QTL genotypes within flanking marker genotypes. In this paper, based on the quantitative genetic model of four-way cross design and the mixture distribution theory, a new method of QTL mapping for four-way cross design was proposed. At first, the conditional probability of QTL genotype at a putative QTL position on chromosome was calculated jointly by using all of marker genotypes on this chromosome; and then a maximum likelihood method implemented via EM algorithm was proposed. The effects of the power of detection, accuracy and precision of QTL mapping in different QTL heritabilities, sample size and molecular marker polymorphism information contents on the proposed method were studied based on simulated data. The results showed: (1) In the power of QTL detection, four-way cross with incomplete genotypic information of DNA molecular markers is slightly lower than that complete marker information. (2) The accuracy and precision of estimates of QTL position and effects will be enhanced as the increasing of QTL heritability, sample size and polymorphism information content of molecular marker.

Key words: Four-fay cross design, QTL mapping, Maximum likelihood estimation, EM algorithm