Genetic control of soybean seed isoflavone content: importance of statistical model and epistasis in complex traits.

Genetic control of soybean seed isoflavone content: importance of statistical model and epistasis in complex traits.
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DOI:
10.1007/s00122-009-1109-z
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发表时间:
2009-10
影响因子:
5.4
通讯作者:
Sleper, David A.
Sleper, David A.
中科院分区:
农林科学1区
文献类型:
--
作者:
Gutierrez-Gonzalez, Juan Jose;Wu, Xiaolei;Zhang, Juan;Lee, Jeong-Dong;Ellersieck, Mark;Shannon, J. Grover;Yu, Oliver;Nguyen, Henry T.;Sleper, David A.

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遗传学家的一个主要目标是破译与农艺重要性相关的性状的遗传结构。然而,这些性状大多是复杂的,它们的遗传解剖传统上不仅受到小效定量性状位点(QTL)数量的限制,而且受到全基因组相互作用位点很少或没有个体效应的限制。大豆(甘氨酸max) [L];[Merr.]种子类黄酮表现出广泛的变异,即使在生长在固定环境中的遗传稳定品系中也是如此,因为它们的合成和积累受到许多生物和非生物因素的影响。由于这种复杂性,异黄酮QTL定位经常产生冲突的结果,特别是在不同的生长条件下。本文采用区间映射、复合区间映射、多重区间映射和基于混合模型的复合区间映射等几种最常用的映射方法,对大豆异黄酮染料木素、大豆黄酮和glycitein进行了比较。在埃塞克斯与PI 437654杂交的rls群体中,共发现26个qtl(包括许多新区域)具有加性主效应。我们的比较方法表明,统计映射方法对于复杂性状的QTL发现至关重要。尽管之前已经了解了添加性QTL对异黄酮产生的影响,但上位性的作用尚未得到很好的确定。结果表明,上位性虽然在很大程度上依赖于环境,但却是影响种子异黄酮含量的一个非常重要的遗传因素,并提示上位性是导致这些性状在不同环境下表型变异的关键因素。本文的在线版本(doi:10.1007/s00122-009-1109-z)包含补充材料,可供授权用户使用。
A major objective for geneticists is to decipher genetic architecture of traits associated with agronomic importance. However, a majority of such traits are complex, and their genetic dissection has been traditionally hampered not only by the number of minor-effect quantitative trait loci (QTL) but also by genome-wide interacting loci with little or no individual effect. Soybean (Glycine max [L.] Merr.) seed isoflavonoids display a broad range of variation, even in genetically stabilized lines that grow in a fixed environment, because their synthesis and accumulation are affected by many biotic and abiotic factors. Due to this complexity, isoflavone QTL mapping has often produced conflicting results especially with variable growing conditions. Herein, we comparatively mapped soybean seed isoflavones genistein, daidzein, and glycitein by using several of the most commonly used mapping approaches: interval mapping, composite interval mapping, multiple interval mapping and a mixed-model based composite interval mapping. In total, 26 QTLs, including many novel regions, were found bearing additive main effects in a population of RILs derived from the cross between Essex and PI 437654. Our comparative approach demonstrates that statistical mapping methodologies are crucial for QTL discovery in complex traits. Despite a previous understanding of the influence of additive QTL on isoflavone production, the role of epistasis is not well established. Results indicate that epistasis, although largely dependent on the environment, is a very important genetic component underlying seed isoflavone content, and suggest epistasis as a key factor causing the observed phenotypic variability of these traits in diverse environments. The online version of this article (doi:10.1007/s00122-009-1109-z) contains supplementary material, which is available to authorized users.
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