Fan Ruzong, Xiong Momiao
Department of Statistics, The Texas A&M University, 447 Blocker Building, College Station, Texas 77843-3143, USA.
Eur J Hum Genet. 2003 Feb;11(2):125-37. doi: 10.1038/sj.ejhg.5200941.
In this paper, we investigate variance component models of both linkage analysis and high resolution linkage disequilibrium (LD) mapping for quantitative trait loci (QTL). The models are based on both family pedigree and population data. We consider likelihoods which utilize flanking marker information, and carry out an analysis of model building and parameter estimations. The likelihoods jointly include recombination fractions, LD coefficients, the average allele substitution effect and allele dominant effect as parameters. Hence, the model simultaneously takes care of the linkage, LD or association and the effects of the putative trait locus. The models clearly demonstrate that linkage analysis and LD mapping are complementary, not exclusive, methods for QTL mapping. By power calculations and comparisons, we show the advantages of the proposed method: (1) population data can provide information for LD mapping, and family pedigree data can provide information for both linkage analysis and LD mapping; (2) using family pedigree data and a sparse marker map, one may investigate the prior suggestive linkage between trait locus and markers to obtain low resolution of the trait loci, because linkage analysis can locate a broad candidate region; (3) with the prior knowledge of suggestive linkage from linkage analysis, both population and family pedigree data can be used simultaneously in high resolution LD mapping based on a dense marker map, since LD mapping can increase the resolution for candidate regions; (4) models of high resolution LD mappings using two flanking markers have higher power than that of models of using only one marker in the analysis; (5) excluding the dominant variance from the analysis when it does exist would lose power; (6) by performing linkage interval mappings, one may get higher power than by using only one marker in the analysis.
在本文中,我们研究了用于数量性状基因座(QTL)的连锁分析和高分辨率连锁不平衡(LD)定位的方差成分模型。这些模型基于家系谱系和群体数据。我们考虑利用侧翼标记信息的似然性,并进行模型构建和参数估计分析。似然性共同包含重组率、LD系数、平均等位基因替代效应和等位基因显性效应作为参数。因此,该模型同时兼顾了连锁、LD或关联性以及假定性状基因座的效应。这些模型清楚地表明,连锁分析和LD定位是QTL定位中互补而非相互排斥的方法。通过功效计算和比较,我们展示了所提出方法的优势:(1)群体数据可为LD定位提供信息,家系谱系数据可为连锁分析和LD定位两者提供信息;(2)使用家系谱系数据和稀疏标记图谱,人们可以研究性状基因座与标记之间的先验提示性连锁,以获得性状基因座的低分辨率,因为连锁分析可以定位一个宽泛的候选区域;(3)基于连锁分析的先验提示性连锁知识,群体和家系谱系数据可同时用于基于密集标记图谱的高分辨率LD定位,因为LD定位可以提高候选区域的分辨率;(4)在分析中,使用两个侧翼标记的高分辨率LD映射模型比仅使用一个标记的模型具有更高的功效;(5)当存在显性方差时将其排除在分析之外会降低功效;(6)通过进行连锁区间映射,可能比在分析中仅使用一个标记获得更高的功效。