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为了研究双亲杂交衍生的多个群体QTL作图分析的方法，对两个亲本通过任意杂交设计衍生的任意多个相关群体联合分析的方法进行了探讨。其要点是：首先利用染色体上所有标记基因型联合计算该染色体上任一假定位置QTL的条件概率，然后根据混合分布理论建立基于EM算法实现的QTL作图的极大似然估计方法。以双亲杂交衍生的F2和BC群体联合分析为例，用计算机模拟数据研究了QTL遗传力和样本容量两个因素对方法的影响。结果表明，在染色体水平模拟时，相同的遗传力下，F2和BC群体联合分析的统计功效明显高于这两个群体单独分析的统计功效。此外，即使两个群体联合分析时的样本容量与两个群体单独分析时的样本容量相等，联合分析的统计功效亦明显高于单独分析的统计功效。且随着遗传力和样本容量的提高，本方法的统计功效逐步提高。在参数估计的准确度和精确度上，相同的遗传力下，F2和BC群体联合分析普遍高于这2个群体的单独分析，尤其是在低遗传力（5%）和较少样本容量下（50），这种优势更为明显。且随着遗传力和样本容量的提高，各参数估计的准确度和精确度亦逐步提高。为了验证本方法的效用，在全基因组水平进行了模拟分析，同样得到了预期的结果。

英文摘要:

Most of the current methods for QTL mapping are designed for the single segregation population derived from the cross of two inbred lines. Incorporating the existing populations derived from two parents may improve QTL mapping and QTL based breeding programs. However, no general maximum likelihood method has been available for this strategy. In this paper, the general mapping method that can combine multiple related populations derived from two parents was proposed. Computer simulations were performed to validate the proposed method. Taking the joint analysis of F2 and BC populations for example, the results showed that: (1) under the same heritability, the method jointing two populations obtained higher power than the one treating the two populations respectively. Moreover, when the sample size of jointing analysis amounted to that of single population analysis, the statistical power of joint analysis was also higher than that of single population analysis. The same conclusion was observed in parameter estimation. Under the same heritability, the accuracy and precision of method jointing two populations were higher than that of method analyzing the population respectively, especially for those treatments with lower heritabilities and smaller sample sizes. Moreover, higher QTL heritability and larger sample sizes can lead to not only higher statistical power, but also more accurate and precise estimates. (2) A whole genome was simulated to further verify the utility of this method. Satisfactory results were also observed.

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