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Genome-wide association analyses for yield and yield-related traits in bread wheat (Triticum aestivum L.) under pre-anthesis combined heat and drought stress in field conditions

机译:田间条件下花前结合热与干旱胁迫的面包小麦(Triticum aestivum L.)产量和产量相关性状的全基因组关联分析

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摘要

Understanding the genetic basis of heat and drought stress tolerance in wheat is prerequisite for wheat breeding program. In the present study, a wheat panel comprising of 192 elite bread wheat genotypes was phenotyped in eight environments for yield and related traits in field conditions. Four stress environments were created by implying four different treatments differing in sowing date and water availability, panel was evaluated for two years in field conditions. The panel was genotyped with 15K Illumina chip and 9236 polymorphic markers concentrated on B genome were employed in GWAS analysis. Consistent, fast LD decay was observed on D genome and structure analysis germplasm divided panel into three major populations. GWAS was performed using BLUEs values of combined environment data in R package GAPIT using log10(P) = 3.96 as significance threshold. The significance of association was further checked using FDR<0.05 threshold. The GWAS identified 487 loci associated with the traits and were significant at log10(p) threshold out of these 350 loci were significant at FDR threshold. For two stress indices 108 associations were significant at FDR threshold. Nine genomic regions were shared among all treatment, while multiple pleiotropic regions were present on chromosome 7D followed by unmapped chromosome. The present study validated many marker trait associations for yield and other traits, MTAs significant under combined drought and heat stress were novel. These regions are important and can be used for fine mapping and marker assisted selection to discover new genes responsible for heat and drought tolerance in wheat.
机译:了解小麦耐热和干旱胁迫耐受性的遗传基础是小麦育种计划的前提。在本研究中,在田间条件下,在八个环境中对由192种面包小麦基因型组成的小麦表型进行了表型分析。通过暗示四种不同的处理方法(播期和水分利用率不同)来创建四个胁迫环境,在田间条件下对面板进行了两年的评估。用15K Illumina芯片对面板进行基因分型,并在GWAS分析中使用集中在B基因组上的9236个多态性标记。在D基因组和结构分析种质上将一致,快速的LD衰变分为三个主要种群。 GWAS是使用R包GAPIT中组合环境数据的BLUEs值执行的,其中log10(P)= 3.96作为显着性阈值。使用FDR <0.05阈值进一步检查关联的显着性。 GWAS确定了487个与性状相关的基因座,并且在log10(p)阈值时显着,在这350个基因座中在FDR阈值时显着。对于两个压力指数,在FDR阈值下108个关联显着。在所有处理中共有9个基因组区域,而7D染色体上存在多个多效性区域,随后是未映射的染色体。本研究验证了许多标记性状与产量和其他性状的关联,在干旱和高温胁迫下显着的MTA是新颖的。这些区域很重要,可用于精细作图和标记辅助选择,以发现负责小麦耐热和耐旱的新基因。

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