Key Laboratory of Forest Genetics and Biotechnology of the Ministry of Education, Nanjing Forestry University, Nanjing, China.
Genet Mol Biol. 2012 Jul;35(3):622-31. doi: 10.1590/S1415-47572012005000044. Epub 2012 Jul 13.
Statistical methods for mapping quantitative trait loci (QTLs) in full-sib forest trees, in which the number of alleles and linkage phase can vary from locus to locus, are still not well established. Previous studies assumed that the QTL segregation pattern was fixed throughout the genome in a full-sib family, despite the fact that this pattern can vary among regions of the genome. In this paper, we propose a method for selecting the appropriate model for QTL mapping based on the segregation of different types of markers and QTLs in a full-sib family. The QTL segregation patterns were classified into three types: test cross (1:1 segregation), F(2) cross (1:2:1 segregation) and full cross (1:1:1:1 segregation). Akaike's information criterion (AIC), the Bayesian information criterion (BIC) and the Laplace-empirical criterion (LEC) were used to select the most likely QTL segregation pattern. Simulations were used to evaluate the power of these criteria and the precision of parameter estimates. A Windows-based software was developed to run the selected QTL mapping method. A real example is presented to illustrate QTL mapping in forest trees based on an integrated linkage map with various segregation markers. The implications of this method for accurate QTL mapping in outbred species are discussed.
在全同胞林木中定位数量性状基因座（QTL）的统计方法仍然不够完善，因为其等位基因数量和连锁相位在不同位点可能会有所不同。先前的研究假设 QTL 分离模式在全同胞家系的整个基因组中是固定的，尽管实际上这种模式可能在基因组的不同区域中有所不同。在本文中，我们提出了一种基于全同胞家系中不同类型标记和 QTL 的分离来选择合适的 QTL 作图模型的方法。QTL 分离模式分为三种类型：测交（1:1 分离）、F2 杂交（1:2:1 分离）和全同胞杂交（1:1:1:1 分离）。采用赤池信息量准则（AIC）、贝叶斯信息量准则（BIC）和拉普拉斯经验准则（LEC）来选择最可能的 QTL 分离模式。模拟用于评估这些标准的功效和参数估计的精度。开发了一个基于 Windows 的软件来运行所选的 QTL 作图方法。用一个带有各种分离标记的综合连锁图谱，提出了一个真实的例子来说明林木中的 QTL 作图。讨论了这种方法对异交物种中准确 QTL 作图的意义。
