数量性状基因的完备区间作图方法

结合分子标记和表型数据的QTL作图已成为数量性状遗传分析的常规方法。复合区间作图是近10多年来广泛应用的一种QTL定位方法，但它在算法上有一些缺陷，致使QTL效应可能会被侧连标记区间之外的标记变量吸收，同时不同的背景标记选择方法对作图结果的影响较大，并且难以推广到上位型互作QTL的定位。针对这些问题，笔者提出完备区间作图方法。本文介绍了该方法的遗传和统计原理，并通过一个大麦加倍单倍体群体说明其在定位加性QTL和加性×加性互作QTL中的应用。完备区间作图包含两个步骤：首先利用所有标记的信息，通过逐步回归选择重要的标记变量并估计其效应；然后利用逐步回归得到的线性模型校正表型数据，通过一维扫描定位加(显)性效应QTL，通过二维扫描定位上位型互作QTL。这种作图策略简化了复合区间作图中控制背景遗传变异的过程，提高了对QTL的检测功效。

Inclusive Composite Interval Mapping of Quantitative Trait Genes

Rapid increase in the availability of fine-scale genetic marker maps has led to the intensive use of QTL mapping in the genetic study of quantitative traits. Composite interval mapping (CIM) is one of the most commonly used methods for QTL mapping with populations derived from biparental crosses. However, the algorithm used in CIM cannot completely ensure that the effect of QTL at current testing interval is not absorbed by the background marker variables, and may result in biased estimation of QTL effect. We proposed a statistical method for QTL mapping, which was called inclusive composite interval mapping (ICIM). Two steps were included in ICIM. In the first step, stepwise regression was applied to identify the most significant regression variables. In the second step, a one-dimensional scanning or interval mapping was conducted for detecting additive (and dominance) QTL and a two-dimensional scanning was conducted for detecting digenic epistasis. ICIM provides intuitive statistics for testing additive, dominance and epistasis, and can be used for most experimental populations derived from two inbred parental lines. The EM algorithm used in ICIM has a fast convergence speed and is therefore less computing intensive. ICIM retains all advantages of CIM over interval mapping, and avoids the possible increase of sampling variance and the complicated background marker selection process in CIM. A doubled haploid (DH) population in barley was used to demonstrate the application of ICIM in mapping additive QTL and additive by additive interacting QTL.