Kolbehdari D, Schaeffer L R, Robinson J A B
Center for Genetic Improvement of Livestock, Department of Animal and Poultry Science, University of Guelph, Guelph, Ontario, Canada.
J Anim Breed Genet. 2007 Dec;124(6):356-61. doi: 10.1111/j.1439-0388.2007.00698.x.
Genome-wide estimated breeding values can be computed from the simultaneous estimates of the effects of small intervals of DNA throughout the genome on a trait or traits of interest. Small intervals or segments of DNA can be created by the use of thousands of single nucleotide polymorphisms (SNP) available in panels of 10, 25 and 50 thousand SNP. A simulation study was conducted to compare factors that could influence the accuracy of genome-wide selection. Factors studied were the heritability of the trait, dispersion of quantitative trait loci (QTL) across the genome and size of the QTL effects. A 100-cM genome was assumed with 100 equally spaced SNP markers and 10 QTL. A granddaughter design was constructed with 20 sires and 100 sons per sire. Population-wide linkage disequilibrium was assumed to be sufficient after 25 generations of random mating starting with 30 sires and 400 dams. Best linear unbiased prediction was used to simultaneously estimate the effects of 99 SNP intervals, based on determining the SNP haplotype of each son inherited from the sire. Indicator variables were used in the model to indicate haplotype transmission. A genome-wide estimated breeding value was calculated as the sum of the appropriate haplotype interval estimates for each son. Correlations between estimated and true breeding values ranged from 0.60 to 0.79. Situations with unequally sized QTL effects and randomly dispersed QTL gave higher correlations. QTL positions could be estimated to within 2 cM or less.
全基因组估计育种值可根据对整个基因组中DNA小间隔对一个或多个目标性状的影响的同时估计来计算。DNA的小间隔或片段可通过使用包含1万个、2.5万个和5万个单核苷酸多态性(SNP)的面板来创建。进行了一项模拟研究,以比较可能影响全基因组选择准确性的因素。研究的因素包括性状的遗传力、数量性状位点(QTL)在基因组中的分布以及QTL效应的大小。假设基因组长度为100厘摩,有100个等间距的SNP标记和10个QTL。构建了一个孙女设计,有20个父本,每个父本有100个儿子。假设从30个父本和400个母本开始随机交配25代后,全群体的连锁不平衡足够。基于确定每个儿子从父本继承的SNP单倍型,使用最佳线性无偏预测来同时估计99个SNP间隔的效应。模型中使用指示变量来指示单倍型传递。每个儿子的全基因组估计育种值计算为适当单倍型间隔估计值的总和。估计育种值与真实育种值之间的相关性在0.60至0.79之间。QTL效应大小不等且随机分布的情况具有更高的相关性。QTL位置可估计在2厘摩或更小的范围内。