Inclusive composite interval mapping of quantitative trait genes.
Inclusive composite interval mapping of quantitative trait genes.
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DOI：
10.3724/sp.j.1006.2009.00239
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发表时间：
2009-01-01
期刊：
影响因子：
--
通讯作者：
Wang, J. K.
中科院分区：
文献类型：
--
作者：
Wang JianKang, Wang JianKang;Wang, J. K.
随着精细遗传标记图谱的快速发展，数量性状基因座（QTL）定位在数量性状遗传研究中的应用日益广泛。复合区间作图（CIM）是利用双亲杂交群体进行QTL定位的最常用方法之一。但CIM算法不能完全保证QTL在当前检测区间的效应不被背景标记变量吸收，可能导致QTL效应的估计有偏。提出了一种QTL定位的统计方法--包容复合区间作图法（ICIM）。ICIM包括两个步骤。在第一步中，应用逐步回归来确定最显著的回归变量。在第二步中，进行一维扫描或区间作图以检测加性（和显性）QTL，并进行二维扫描以检测双基因上位性。ICIM为加性、显性和上位性检验提供了直观的统计方法，可用于大多数由2个自交系组成的试验群体。ICIM中使用的EM算法具有快速收敛速度，因此计算量较小。ICIM保留了CIM相对于区间映射的所有优点，并避免了CIM中可能增加的采样方差和复杂的背景标记选择过程。以大麦双单倍体群体为研究对象，探讨了ICIM在定位加性QTL和加性互作QTL中的应用。
Rapid increase in the availability of fine-scale genetic marker maps has led to the intensive use of quantitative trait loci (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 the 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. A statistical method for QTL mapping was proposed, which was called inclusive composite interval mapping (ICIM). Two steps were included in the 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. The ICIM provides intuitive statistics for testing additive, dominance and epistasis, and can be used for most experimental populations derived from 2 inbred parental lines. The EM algorithm used in ICIM has a fast convergence speed and is therefore less computing intensive. The ICIM retains all the advantages of the CIM over interval mapping, and avoids the possible increase of sampling variance and the complicated background marker selection process in the CIM. A doubled haploid (DH) population in barley was used to demonstrate the application of the ICIM in mapping additive QTL and additive by additive interacting QTL.