Gahlaut Vijay, Jaiswal Vandana, Balyan Harindra S, Joshi Arun Kumar, Gupta Pushpendra K
Department of Genetics and Plant Breeding, Chaudhary Charan Singh University, Meerut, India.
Council of Scientific & Industrial Research-Institute of Himalayan Bioresource Technology, Palampur, India.
Front Plant Sci. 2021 Oct 21;12:758631. doi: 10.3389/fpls.2021.758631. eCollection 2021.
In wheat, a multi-locus genome-wide association study (ML-GWAS) was conducted for the four grain weight-related traits (days to anthesis, grain filling duration, grain number per ear, and grain weight per ear) using data recorded under irrigated (IR) and rain-fed (RF) conditions. Seven stress-related indices were estimated for these four traits: (i) drought resistance index (DI), (ii) geometric mean productivity (GMP), (iii) mean productivity index (MPI), (iv) relative drought index (RDI), (v) stress tolerance index (STI), (vi) yield index, and (vii) yield stability index (YSI). The association panel consisted of a core collection of 320 spring wheat accessions representing 28 countries. The panel was genotyped using 9,627 single nucleotide polymorphisms (SNPs). The genome-wide association (GWA) analysis provided 30 significant marker-trait associations (MTAs), distributed as follows: (i) IR (15 MTAs), (ii) RF (14 MTAs), and (iii) IR+RF (1 MTA). In addition, 153 MTAs were available for the seven stress-related indices. Five MTAs co-localized with previously reported QTLs/MTAs. Candidate genes (CGs) associated with different MTAs were also worked out. Gene ontology (GO) analysis and expression analysis together allowed the selection of the two CGs, which may be involved in response to drought stress. These two CGs included: TraesCS1A02G331000 encoding RNA helicase and TraesCS4B02G051200 encoding microtubule-associated protein 65. The results supplemented the current knowledge on genetics for drought tolerance in wheat. The results may also be used for future wheat breeding programs to develop drought-tolerant wheat cultivars.
在小麦中,利用在灌溉(IR)和雨养(RF)条件下记录的数据,对四个与粒重相关的性状(开花天数、灌浆持续时间、每穗粒数和每穗粒重)进行了多位点全基因组关联研究(ML-GWAS)。针对这四个性状估算了七个与胁迫相关的指标:(i)抗旱指数(DI),(ii)几何平均生产力(GMP),(iii)平均生产力指数(MPI),(iv)相对干旱指数(RDI),(v)胁迫耐受指数(STI),(vi)产量指数,以及(vii)产量稳定性指数(YSI)。关联群体由代表28个国家的320份春小麦种质核心收集品组成。使用9627个单核苷酸多态性(SNP)对该群体进行基因分型。全基因组关联(GWA)分析提供了30个显著的标记-性状关联(MTA),分布如下:(i)IR(15个MTA),(ii)RF(14个MTA),以及(iii)IR+RF(1个MTA)。此外,有153个MTA可用于七个与胁迫相关的指标。5个MTA与先前报道的QTL/MTAs共定位。还确定了与不同MTA相关的候选基因(CG)。基因本体(GO)分析和表达分析共同筛选出了两个可能参与干旱胁迫响应的CG。这两个CG包括:编码RNA解旋酶的TraesCS1A02G331000和编码微管相关蛋白65的TraesCS4B02G051200。这些结果补充了当前关于小麦耐旱性遗传学的知识。这些结果也可用于未来的小麦育种计划,以培育耐旱小麦品种。