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通过荟萃 QTL 和基因型-表型关联分析揭示的控制小麦产量及其构成的主要基因组区域。

Major genomic regions responsible for wheat yield and its components as revealed by meta-QTL and genotype-phenotype association analyses.

机构信息

School of Plant Biology, Faculty of Science and The UWA Institute of Agriculture, The University of Western Australia, Perth, WA, 6009, Australia.

InterGrain Pty Ltd, 19 Ambitious Link, Bibra Lake, WA, 6163, Australia.

出版信息

Planta. 2020 Sep 24;252(4):65. doi: 10.1007/s00425-020-03466-3.

Abstract

Meta-QTL (MQTL) analysis was done for yield-related traits in wheat. Candidate genes were identified within the refined MQTL and further validated by genotype-phenotype association analysis. Extensive studies have been undertaken on quantitative trait locus/loci (QTL) for wheat yield and its component traits. This study conducted a meta-analysis of 381 QTL related to wheat yield under various environments, including irrigated, drought- and/or heat-stressed conditions. Markers flanking meta-QTL (MQTL) were mapped on the wheat reference genome for their physical positions. Putative candidate genes were examined for MQTL with a physical interval of less than 20 Mbp. A total of 86 MQTL were identified as responsible for yield, of which 34 were for irrigated environments, 39 for drought-stressed environments, 36 for heat-stressed environments, and 23 for both drought- and heat-stressed environments. The high-confidence genes within the physical positions of the MQTL flanking markers were screened in the reference genome RefSeq V1.0, which identified 210 putative candidate genes. The phenotypic data for 14 contrasting genotypes with either high or low yield performance-according to the Australian National Variety Trials-were associated with their genotypic data obtained through ddRAD sequencing, which validated 18 genes or gene clusters associated with MQTL that had important roles for wheat yield. The detected and refined MQTL and candidate genes will be useful for marker-assisted selection of high yield in wheat breeding.

摘要

对小麦产量相关性状进行了元数量性状位点(MQTL)分析。在精细化的 MQTL 内鉴定出候选基因,并通过基因型-表型关联分析进一步验证。已经对小麦产量及其组成性状的数量性状位点(QTL)进行了广泛的研究。本研究对 381 个与各种环境下小麦产量相关的 QTL 进行了元分析,包括灌溉、干旱和/或热胁迫条件。将侧翼元数量性状位点(MQTL)的标记映射到小麦参考基因组上,以确定其物理位置。对物理间隔小于 20 Mbp 的 MQTL 进行了推定候选基因检测。总共鉴定出 86 个 MQTL 负责产量,其中 34 个是灌溉环境,39 个是干旱胁迫环境,36 个是热胁迫环境,23 个是干旱和热胁迫环境。在侧翼标记的 MQTL 物理位置内的高可信度基因在参考基因组 RefSeq V1.0 中进行了筛选,共鉴定出 210 个推定候选基因。根据澳大利亚国家品种试验,对具有高或低产量表现的 14 个对比基因型的表型数据与通过 ddRAD 测序获得的基因型数据进行了关联,验证了与 MQTL 相关的 18 个基因或基因簇,这些基因或基因簇对小麦产量有重要作用。检测和精细化的 MQTL 和候选基因将有助于小麦育种中的高产标记辅助选择。

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