QTL detection with bidirectional and unidirectional selective genotyping: marker-based and trait-based analyses
QTL detection with bidirectional and unidirectional selective genotyping: marker-based and trait-based analyses
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DOI：
10.1007/s00122-008-0904-2
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发表时间：
2009-01-01
影响因子：
5.4
通讯作者：
Atlin, G. N.
中科院分区：
文献类型：
--
作者：
Navabi, Alizera;Mather, D. E.;Atlin, G. N.
在全群体基因分型成本太高或不可行的情况下，或者在目标是快速筛选大量潜在供体以获得具有大效应的有用等位基因的情况下，可以使用群体的一个或两个表型极端的选择性基因分型来检测标记和数量性状基因座（QTL）之间的连锁。数据可以进行“基于性状的”分析，其中标记等位基因频率在基于性状值定义的后代类别之间进行比较，或者进行“基于标记的”分析，其中性状平均值在基于标记基因型定义的后代类别之间进行比较。在这里，双向和单向选择基因型进行了模拟，使用人口规模和选择强度有关的谷物育种。使用二项分布的正态近似，基于标记的方差分析或基于性状的检验通常足以控制I类错误。双向选择性基因分型比单向选择性基因分型更有效。基于性状的方差分析和基于标记的方差分析具有相同的效果。对500个品系中最好的30个品系（6%）进行基因分型，当在距离QTL 10 cM的标记处进行测试时，可以以0.8的功效检测到解释15%表型方差的QTL。利用双向选择基因分型，可以检测到效应较小的QTL和（或）距离最近标记较远的QTL。采用相似的QTL检测方法，对436个重组自交系群体的数据进行了干旱胁迫下影响产量的大效应QTL的分离。该QTL可靠地检测到基因分型少至20个选定的线（4.5%）。在实验群体中，选择性基因分型可以降低QTL检测的成本，允许筛选更多的潜在供体，以获得在不同背景下具有影响的有用等位基因。在植物育种程序中，选择性基因分型可以使得使用甚至有限数量的在选择后保留的后代来检测QTL成为可能。
Selective genotyping of one or both phenotypic extremes of a population can be used to detect linkage between markers and quantitative trait loci (QTL) in situations in which full-population genotyping is too costly or not feasible, or where the objective is to rapidly screen large numbers of potential donors for useful alleles with large effects. Data may be subjected to 'trait-based' analysis, in which marker allele frequencies are compared between classes of progeny defined based on trait values, or to 'marker-based' analysis, in which trait means are compared between progeny classes defined based on marker genotypes. Here, bidirectional and unidirectional selective genotyping were simulated, using population sizes and selection intensities relevant to cereal breeding. Control of Type I error was usually adequate with marker-based analysis of variance or trait-based testing using the normal approximation of the binomial distribution. Bidirectional selective genotyping was more powerful than unidirectional. Trait-based analysis and marker-based analysis of variance were about equally powerful. With genotyping of the best 30 out of 500 lines (6%), a QTL explaining 15% of the phenotypic variance could be detected with a power of 0.8 when tests were conducted at a marker 10 cM from the QTL. With bidirectional selective genotyping, QTL with smaller effects and ( or) QTL farther from the nearest marker could be detected. Similar QTL detection approaches were applied to data from a population of 436 recombinant inbred rice lines segregating for a large-effect QTL affecting grain yield under drought stress. That QTL was reliably detected by genotyping as few as 20 selected lines (4.5%). In experimental populations, selective genotyping can reduce costs of QTL detection, allowing larger numbers of potential donors to be screened for useful alleles with effects across different backgrounds. In plant breeding programs, selective genotyping can make it possible to detect QTL using even a limited number of progeny that have been retained after selection.