Department of Electrical and Computer Engineering, University of Miami, Coral Gables, Florida, United State of America.
Department of Botany and Plant Sciences, University of California Riverside, Riverside, California, United State of America.
PLoS One. 2014 Jan 29;9(1):e87330. doi: 10.1371/journal.pone.0087330. eCollection 2014.
Although rice yield has been doubled in most parts of the world since 1960s, thanks to the advancements in breeding technologies, the biological mechanisms controlling yield are largely unknown. To understand the genetic basis of rice yield, a number of quantitative trait locus (QTL) mapping studies have been carried out, but whole-genome QTL mapping incorporating all interaction effects is still lacking. In this paper, we exploited whole-genome markers of an immortalized F2 population derived from an elite rice hybrid to perform QTL mapping for rice yield characterized by yield per plant and three yield component traits. Our QTL model includes additive and dominance main effects of 1,619 markers and all pair-wise interactions, with a total of more than 5 million possible effects. The QTL mapping identified 54, 5, 28 and 4 significant effects involving 103, 9, 52 and 7 QTLs for the four traits, namely the number of panicles per plant, the number of grains per panicle, grain weight, and yield per plant. Most identified QTLs are involved in digenic interactions. An extensive literature survey of experimentally characterized genes related to crop yield shows that 19 of 54 effects, 4 of 5 effects, 12 of 28 effects and 2 of 4 effects for the four traits, respectively, involve at least one QTL that locates within 2 cM distance to at least one yield-related gene. This study not only reveals the major role of epistasis influencing rice yield, but also provides a set of candidate genetic loci for further experimental investigation.
尽管自 20 世纪 60 年代以来，得益于育种技术的进步，世界上大多数地区的水稻产量已经翻了一番，但控制产量的生物学机制在很大程度上仍是未知的。为了了解水稻产量的遗传基础，已经进行了许多数量性状位点（QTL）作图研究，但仍缺乏包含所有互作效应的全基因组 QTL 作图。在本文中，我们利用一个由精英水稻杂种衍生的永生 F2 群体的全基因组标记，对以单株产量和三个产量构成性状为特征的水稻产量进行 QTL 作图。我们的 QTL 模型包括 1619 个标记的加性和显性主效以及所有的双效互作，总共有超过 500 万个可能的效应。QTL 作图确定了 54、5、28 和 4 个显著效应，涉及 103、9、52 和 7 个 QTL，分别对应于每个植株的穗数、每穗粒数、粒重和单株产量。大多数鉴定出的 QTL 涉及双基因互作。对与作物产量相关的实验鉴定基因的广泛文献调查表明，在四个性状中，分别有 54 个效应中的 19 个、5 个效应中的 4 个、28 个效应中的 12 个和 4 个效应中的 2 个，涉及至少一个 QTL，该 QTL 位于至少一个与产量相关基因的 2cM 距离内。这项研究不仅揭示了影响水稻产量的上位性的主要作用，还为进一步的实验研究提供了一组候选遗传基因座。
