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Genome-wide association mapping of Hagberg falling number, protein content, test weight, and grain yield in U.K. wheat
Crop Science ( IF 2.3 ) Pub Date : 2021-12-28 , DOI: 10.1002/csc2.20692
Jon White 1, 2 , Rajiv Sharma 3 , David Balding 2, 4 , James Cockram 1 , Ian J Mackay 3
Affiliation  

Association mapping using crop cultivars allows identification of genetic loci of direct relevance to breeding. Here, 150 U.K. wheat (Triticum aestivum L.) cultivars genotyped with 23,288 single nucleotide polymorphisms (SNPs) were used for genome-wide association studies (GWAS) using historical phenotypic data for grain protein content, Hagberg falling number (HFN), test weight, and grain yield. Power calculations indicated experimental design would enable detection of quantitative trait loci (QTL) explaining ≥20% of the variation (PVE) at a relatively high power of >80%, falling to 40% for detection of a SNP with an R2≥ .5 with the same QTL. Genome-wide association studies identified marker-trait associations for all four traits. For HFN (h= .89), six QTL were identified, including a major locus on chromosome 7B explaining 49% PVE and reducing HFN by 44 s. For protein content (h= 0.86), 10 QTL were found on chromosomes 1A, 2A, 2B, 3A, 3B, and 6B, together explaining 48.9% PVE. For test weight, five QTL were identified (one on 1B and four on 3B; 26.3% PVE). Finally, 14 loci were identified for grain yield (h= 0.95) on eight chromosomes (1A, 2A, 2B, 2D, 3A, 5B, 6A, 6B; 68.1% PVE), of which five were located within 16 Mbp of genetic regions previously identified as under breeder selection in European wheat. Our study demonstrates the utility of exploiting historical crop datasets, identifying genomic targets for independent validation, and ultimately for wheat genetic improvement.

中文翻译:

英国小麦 Hagberg 下降数、蛋白质含量、容重和籽粒产量的全基因组关联作图

使用作物品种的关联作图可以识别与育种直接相关的基因位点。在这里,使用谷物蛋白含量、Hagberg 下降数 (HFN)、容重的历史表型数据,对150 个英国小麦 ( Triticum aestivum L.) 品种进行了全基因组关联研究 (GWAS),这些品种对 23,288 个单核苷酸多态性 (SNP) 进行了基因分型。 , 和粮食产量。功效计算表明,实验设计将能够检测数量性状基因座 (QTL),以 >80% 的相对高功效检测解释≥20% 的变异 (PVE),对于检测具有R 2 ≥ 的 SNP 下降至 40%。 5 具有相同的 QTL。全基因组关联研究确定了所有四个性状的标记-性状关联。对于 HFN ( h = .89),鉴定出 6 个 QTL,包括 7B 号染色体上的一个主要基因座,解释 49% PVE 并将 HFN 减少 44 秒。对于蛋白质含量(h = 0.86),在染色体 1A、2A、2B、3A、3B 和 6B 上发现了 10 个 QTL,共同解释了 48.9% 的 PVE。对于容重,鉴定了五个 QTL(一个在 1B 上,四个在 3B 上;26.3% PVE)。最后,在 8 条染色体(1A、2A、2B、2D、3A、5B、6A、6B;68.1% PVE)上鉴定了 14 个谷物产量位点 ( h = 0.95),其中 5 个位于遗传基因的 16 Mbp 范围内。以前在欧洲小麦中被确定为育种者选择的区域。我们的研究证明了利用历史作物数据集、确定基因组目标以进行独立验证并最终用于小麦遗传改良的效用。
更新日期:2021-12-28
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