Churchill G A, Giovannoni J J, Tanksley S D
Department of Plant Breeding and Biometry, Cornell University, Ithaca, NY 14853.
Proc Natl Acad Sci U S A. 1993 Jan 1;90(1):16-20. doi: 10.1073/pnas.90.1.16.
A pooled-sample approach to the construction of high-resolution genetic maps is described. The strategy depends on the existence of an easily selectable target locus and the ability to produce large segregating populations. If these requirements are met, the pooled-sample mapping approach allows tightly linked markers (e.g., restriction fragment length polymorphisms) to be mapped relative to the target with a great economy of effort. The recombination fractions among loci can be estimated by the maximum likelihood method and a simple approximate estimator is derived. The order of loci is deduced using a Bayesian statistical framework to yield posterior probabilities for all possible orderings of a marker set. Optimal pooling strategies and the effects of misclassification of selected individuals are discussed and studied by computer simulation. The feasibility of this method is demonstrated by the high-resolution mapping of a region on chromosome 5 of tomato that contains a gene regulating fruit ripening.
本文描述了一种用于构建高分辨率遗传图谱的混合样本方法。该策略依赖于一个易于选择的目标基因座的存在以及产生大型分离群体的能力。如果满足这些要求，混合样本作图方法能够以极大的省力方式将紧密连锁的标记（如限制性片段长度多态性）相对于目标进行定位。基因座间的重组率可以通过最大似然法估计，并推导出一个简单的近似估计器。使用贝叶斯统计框架推导基因座顺序，以得出标记集所有可能顺序的后验概率。通过计算机模拟讨论并研究了最优混合策略以及所选个体误分类的影响。通过对番茄5号染色体上一个包含调控果实成熟基因的区域进行高分辨率作图，证明了该方法的可行性。
