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利用美国农业部水稻迷你核心库进行谷物品质的表型和分子剖析。

Phenotypic and molecular dissection of grain quality using the USDA rice mini-core collection.

机构信息

Department of Soil and Crop Sciences, Texas A&M University, College Station, TX 77843-2474, USA; Crop Research Institute, Shandong Academy of Agricultural Sciences, Jinan, Shandong 250100, China.

Department of Soil and Crop Sciences, Texas A&M University, College Station, TX 77843-2474, USA; Agricultural Biotechnology Division, National Institute for Biotechnology and Genetic Engineering (NIBGE), Jhang Road, P.O. Box 577, Faisalabad, Pakistan.

出版信息

Food Chem. 2019 Jun 30;284:312-322. doi: 10.1016/j.foodchem.2019.01.009. Epub 2019 Jan 25.

DOI:10.1016/j.foodchem.2019.01.009
PMID:30744863
Abstract

Grain quality is a major breeding objective and paramount to food production. This study was aimed to phenotypically and molecularly dissect the rice grain quality, especially amylose content (AC), grain protein content (GPC) and alkali spreading value (ASV), using the USDA rice mini-core collection representing the world-wide rice germplasm lines. Grain chemical analysis combined with genome-wide association study (GWAS) was used for the study. A wide genetic variation was observed for these grain quality traits in the mini-core collection. Germplasm lines unique in AC, GPC and ASV and desirable for grain quality improvement were identified. The genetic diversity of the collection was re-analyzed using new SNPs, thus providing a more precise genotypic information about the collection. Furthermore, ten loci significantly associated with these grain quality traits were identified through GWAS using 22947 high-quality SNPs. These results, therefore, provide knowledge, resources and molecular tools for efficient rice grain quality improvement.

摘要

稻米品质是一个主要的育种目标,对粮食生产至关重要。本研究旨在通过表型和分子手段解析稻米品质,特别是直链淀粉含量(AC)、蛋白质含量(GPC)和碱消值(ASV),使用美国农业部的稻米迷你核心种质库代表全球稻米种质资源。利用全基因组关联研究(GWAS)进行了谷物化学分析。在迷你核心库中观察到这些谷物品质性状具有广泛的遗传变异。鉴定了在 AC、GPC 和 ASV 方面具有独特性和改良谷物品质的理想种质资源。利用新的 SNP 重新分析了该种质资源的遗传多样性,从而提供了有关该资源的更精确的基因型信息。此外,通过使用 22947 个高质量 SNP 进行 GWAS,鉴定出与这些谷物品质性状显著相关的 10 个位点。因此,这些结果为高效的稻米品质改良提供了知识、资源和分子工具。

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