摘要
采用蒙特卡罗方法分析了在孙女设计中不同的群体结构、性状遗传力、QTL效应大小和QTL在染色体上的位置等各个因素不同水平组合下4种标记密度（标记间隔5cM，10cM，20cM和50cM）对QTL定位精确性（以均方误MSE为衡量指标）的影响，并从经济学角度探讨了应用于标记辅助选择（MAS）的QTL定位的最佳标记密度。结果表明，一般说来，在各因素水平都较低时，MSE随标记密度加大而下降的相对幅度也较小；反之，在各因素的水平都较高时，MSE随标记密度加大而下降的相对幅度也较大。当样本含量达到一定水平时（如40个家系，每个家系100个儿子），或当QTL效应达到一个较高水平时（如QTL方差占加性遗传方差的50％），MSE随标记密度加大而下降的幅度几乎不受其他因素的影响，始终保持一个较高的水平（95％左右）。对于MAS可获得的最佳经济效益来说，在不同的各因素水平组合下QTL定位的最佳标记间隔分别为5cM（小样本、大QTL，或中等样本、中等遗传力和QTL，或大样本、小QTL）、10cM（中等样本、高遗传力或大QTL，或大样本、中等遗传力和QTL）和20cM（大样本、高遗传力或大QTL）。
Using Monte Carlo method, the effects of marker density on the accuracy of QTL mapping, measured with mean squared error (MSE) of QTL position estimates, were investigated for a granddaughter design under different population structures,heritabilities, sizes of QTL effect and QTL locations. The optimal marker densities for QTL mapping for applying to marker assisted selection, (MAS) were analyzed from an economic point of view. The results show that, in general, with the increase of marker density MSEs decrease much more rapidly when all other factors are at a high level than at a low level. When the sample size reaches a certain level (e.g. 40 families with 100 sons per family), or when the QTL effect is large (e.g. the QTL explains 50% of the genetic variance), the decrease of MSE will be only slightly affected by otrher factors. For the best benefits of MAS, the otihmal marker distances under different combinations of various factors were 5cM (small sample and large QTL, moderate sample, heritability and QTL, or large sample and small QTL), 10cM (moderate sample and high heritability or large QTL, or large sample and moderate heritability and QTL), and 20cM (large sample and high hetitability or large QTL).
基金
国家自然科学基金!39870587
