Genetic architecture of aluminum tolerance in rice (Oryza sativa) determined through genome-wide association analysis and QTL mapping.
Genetic architecture of aluminum tolerance in rice (Oryza sativa) determined through genome-wide association analysis and QTL mapping.
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DOI：
10.1371/journal.pgen.1002221
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发表时间：
2011-08
期刊：
影响因子：
4.5
通讯作者：
McCouch SR
中科院分区：
文献类型：
--
作者：
Famoso AN;Zhao K;Clark RT;Tung CW;Wright MH;Bustamante C;Kochian LV;McCouch SR
铝毒是酸性土壤上作物生产的主要限制因素，水稻比其他谷类作物更耐铝。然而，水稻耐铝机制在很大程度上是未知的，没有基因的自然变异的报道。我们筛选了383个不同的水稻品种，进行了全基因组关联（GWA）的研究，并进行了QTL定位在两个双亲群体中使用三个估计铝耐性的基础上根的生长。亚群结构解释了57%的表型变异，粳稻的耐铝性是籼稻的2倍。GWA分析确定了48个与耐铝相关的区域，其中大部分是亚群特异性的。其中4个区域与先验候选基因共定位，2个高度显著的区域与先前鉴定的QTL共定位。通过双亲QTL定位或GWA分析，确定了3个水稻铝敏感突变体（ART 1、STAR 2和Nrat 1）的区域参与了耐铝性的自然变异。单倍型分析Nrat 1基因周围确定的易感和宽容的单倍型解释40%的AUS亚群内的铝耐受性的变化，和Nrat 1的序列分析确定了三个非同义突变预测铝敏感性在我们的多样性面板。GWA分析发现了更多的表型-基因型关联，并提供了更高的分辨率，但QTL定位确定关键罕见和/或亚群特异性等位基因没有检测到GWA分析。利用籼/粳稻群体作图，确定了与超亲变异相关的QTL，其中来自感铝亲本或籼稻亲本的等位基因在耐铝粳稻背景下增强了耐铝性。这项工作支持的假设，选择性渗入等位基因在亚群是一种有效的方法，性状增强植物育种计划，并证明了根本的重要性，亚群在解释和操纵水稻复杂性状的遗传。虽然水稻（Oryza sativa）比其他谷物更耐铝，但尚未报道水稻耐铝基因。利用全基因组关联（GWA）和双亲QTL定位技术，研究了水稻耐铝性的遗传结构。粳稻品种的耐铝性是籼稻和粳稻品种的2倍。总体而言，57%的表型变异与亚群相关，与观察结果一致，即不同的基因和基因组区域与不同亚群的耐铝性相关。通过GWA鉴定的4个区域与先验候选基因共定位，2个高度显著的区域与先前鉴定的数量性状位点（QTL）共定位。单倍型和序列分析的候选基因，Nrat 1，确定了一个易感单倍型解释40%的AUS亚群和三个非同义突变内Nrat 1铝耐受性的变化，预测铝敏感性。利用籼稻×粳稻作图群体，在耐铝的粳稻背景下，从感铝的籼稻或粳稻亲本中分离出耐铝的QTL，并进行了超亲变异的QTL定位。这项工作证明了亚群在解释和操纵水稻复杂性状方面的重要性，并为育种者提供了一个路线图，旨在从表型劣势品系中捕获遗传价值。
Aluminum (Al) toxicity is a primary limitation to crop productivity on acid soils, and rice has been demonstrated to be significantly more Al tolerant than other cereal crops. However, the mechanisms of rice Al tolerance are largely unknown, and no genes underlying natural variation have been reported. We screened 383 diverse rice accessions, conducted a genome-wide association (GWA) study, and conducted QTL mapping in two bi-parental populations using three estimates of Al tolerance based on root growth. Subpopulation structure explained 57% of the phenotypic variation, and the mean Al tolerance in Japonica was twice that of Indica. Forty-eight regions associated with Al tolerance were identified by GWA analysis, most of which were subpopulation-specific. Four of these regions co-localized with a priori candidate genes, and two highly significant regions co-localized with previously identified QTLs. Three regions corresponding to induced Al-sensitive rice mutants (ART1, STAR2, Nrat1) were identified through bi-parental QTL mapping or GWA to be involved in natural variation for Al tolerance. Haplotype analysis around the Nrat1 gene identified susceptible and tolerant haplotypes explaining 40% of the Al tolerance variation within the aus subpopulation, and sequence analysis of Nrat1 identified a trio of non-synonymous mutations predictive of Al sensitivity in our diversity panel. GWA analysis discovered more phenotype–genotype associations and provided higher resolution, but QTL mapping identified critical rare and/or subpopulation-specific alleles not detected by GWA analysis. Mapping using Indica/Japonica populations identified QTLs associated with transgressive variation where alleles from a susceptible aus or indica parent enhanced Al tolerance in a tolerant Japonica background. This work supports the hypothesis that selectively introgressing alleles across subpopulations is an efficient approach for trait enhancement in plant breeding programs and demonstrates the fundamental importance of subpopulation in interpreting and manipulating the genetics of complex traits in rice. While rice (Oryza sativa) is significantly more Al tolerant than other cereals, no genes underlying Al tolerance in rice have been reported. Using genome-wide association (GWA) and bi-parental QTL mapping, we investigated the genetic architecture of Al tolerance in rice. Japonica varieties were twice as Al tolerant as indica and aus varieties. Overall, 57% of the phenotypic variation was correlated with subpopulation, consistent with observations that different genes and genomic regions were associated with Al tolerance in different subpopulations. Four regions identified by GWA co-localized with a priori candidate genes, and two highly significant regions co-localized with previously identified quantitative trait loci (QTL). Haplotype and sequence analysis around the candidate gene, Nrat1, identified a susceptible haplotype explaining 40% of the Al tolerance variation within the aus subpopulation and three non-synonymous mutations within Nrat1 that were predictive of Al sensitivity. Using Indica × Japonica mapping populations, we identified QTLs associated with transgressive variation where alleles from a susceptible indica or aus parent enhanced Al tolerance in a tolerant japonica background. This work demonstrates the importance of subpopulation in interpreting and manipulating complex traits in rice and provides a roadmap for breeders aiming to capture genetic value from phenotypically inferior lines.
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