Van Arendonk J A, Tier B, Kinghorn B P
Department of Animal Breeding, Wageningen Agricultural University, The Netherlands.
Genetics. 1994 May;137(1):319-29. doi: 10.1093/genetics/137.1.319.
Genotypes at a marker locus give information on transmission of genes from parents to offspring and that information can be used in predicting the individuals' additive genetic value at a linked quantitative trait locus (MQTL). In this paper a recursive method is presented to build the gametic relationship matrix for an autosomal MQTL which requires knowledge on recombination rate between the marker locus and the MQTL linked to it. A method is also presented to obtain the inverse of the gametic relationship matrix. This information can be used in a mixed linear model for simultaneous evaluation of fixed effects, gametic effects at the MQTL and additive genetic effects due to quantitative trait loci unlinked to the marker locus (polygenes). An equivalent model can be written at the animal level using the numerator relationship matrix for the MQTL and a method for obtaining the inverse of this matrix is presented. Information on several unlinked marker loci, each of them linked to a different locus affecting the trait of interest, can be used by including an effect for each MQTL. The number of equations per animal in this case is 2m + 1 where m is the number of MQTL. A method is presented to reduce the number of equations per animal to one by combining information on all MQTL and polygenes into one numerator relationship matrix. It is illustrated how the method can accommodate individuals with partial or no marker information. Numerical examples are given to illustrate the methods presented. Opportunities to use the presented model in constructing genetic maps are discussed.
标记位点的基因型提供了基因从亲本传递到后代的信息,该信息可用于预测个体在连锁数量性状位点(MQTL)上的加性遗传值。本文提出了一种递归方法,用于构建常染色体MQTL的配子关系矩阵,这需要了解标记位点与其相连的MQTL之间的重组率。还提出了一种获取配子关系矩阵逆矩阵的方法。该信息可用于混合线性模型,以同时评估固定效应、MQTL处的配子效应以及与标记位点不连锁的数量性状位点(多基因)引起的加性遗传效应。使用MQTL的分子关系矩阵可以在个体水平上写出一个等效模型,并提出了一种获取该矩阵逆矩阵的方法。通过纳入每个MQTL的效应,可以使用几个不连锁的标记位点的信息,每个标记位点都与影响目标性状的不同位点相连。在这种情况下,每个个体的方程数为2m + 1,其中m是MQTL的数量。提出了一种方法,通过将所有MQTL和多基因的信息组合成一个分子关系矩阵,将每个个体的方程数减少到一个。阐述了该方法如何适用于具有部分标记信息或无标记信息的个体。给出了数值示例来说明所提出的方法。讨论了在所构建的遗传图谱中使用所提出模型的机会。