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Association Mapping for Important Agronomic Traits in Core Collection of Rice (Oryza sativa L.) with SSR Markers

机译:利用SSR标记对水稻核心品种重要农艺性状的关联图谱

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摘要

Mining elite genes within rice landraces is of importance for the improvement of cultivated rice. An association mapping for 12 agronomic traits was carried out using a core collection of rice consisting of 150 landraces (Panel 1) with 274 simple sequence repeat (SSR) markers, and the mapping results were further verified using a Chinese national rice micro-core collection (Panel 2) and a collection from a global molecular breeding program (Panel 3). Our results showed that (1) 76 significant (P<0.05) trait-marker associations were detected using mixed linear model (MLM) within Panel 1 in two years, among which 32% were identical with previously mapped QTLs, and 11 significant associations had >10% explained ratio of genetic variation; (2) A total of seven aforementioned trait-marker associations were verified within Panel 2 and 3 when using a general linear model (GLM) and 55 SSR markers of the 76 significant trait-marker associations. However, no significant trait-marker association was found to be identical within three panels when using the MLM model; (3) several desirable alleles of the loci which showed significant trait-marker associations were identified. The research provided important information for further mining these elite genes within rice landraces and using them for rice breeding.
机译:在水稻地方品种中挖掘优良基因对于改良栽培水稻具有重要意义。使用由150个地方品种(第1组)和274个简单序列重复(SSR)标记组成的水稻核心集合,对12个农艺性状进行了关联定位,并使用中国国家水稻微核心集合进一步验证了定位结果(小组2)和全球分子育种计划的集合(小组3)。我们的结果表明(1)在两年内使用混合线性模型(MLM)检测到76个重要(P <0.05)特质标记关联,其中32%与先前映射的QTL相同,并且11个重要关联具有> 10%的遗传变异解释率; (2)当使用通用线性模型(GLM)和76个重要特征标记关联中的55个SSR标记时,在面板2和3中总共验证了七个上述特征标记关联。但是,使用MLM模型时,没有发现三个面板中的显着性状-标记关联相同。 (3)确定了几个显着的性状标记关联的理想等位基因。该研究为进一步挖掘水稻地方品种中的这些优良基因并将其用于水稻育种提供了重要信息。

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