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Table_8_Uncovering Genomic Regions Associated With 36 Agro-Morphological Traits in Indian Spring Wheat Using GWAS.xls

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https://figshare.com/articles/dataset/Table_8_Uncovering_Genomic_Regions_Associated_With_36_Agro-Morphological_Traits_in_Indian_Spring_Wheat_Using_GWAS_xls/8039300
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Wheat genetic improvement by integration of advanced genomic technologies is one way of improving productivity. To facilitate the breeding of economically important traits in wheat, SNP loci and underlying candidate genes associated with the 36 agro-morphological traits were studied in a diverse panel of 404 genotypes. By using Breeders’ 35K Axiom array in a comprehensive genome-wide association study covering 4364.79 cM of the wheat genome and applying a compressed mixed linear model, a total of 146 SNPs (-log10P ≥ 4) were found associated with 23 traits out of 36 traits studied explaining 3.7–47.0% of phenotypic variance. To reveal this a subset of 260 genotypes was characterized phenotypically for six quantitative traits [days to heading (DTH), days to maturity (DTM), plant height (PH), spike length (SL), awn length (Awn_L), and leaf length (Leaf_L)] under five environments. Gene annotations mined ∼38 putative candidate genes which were confirmed using tissue and stage specific gene expression data from RNA Seq. We observed strong co-localized loci for four traits (glume pubescence, SL, PH, and awn color) on chromosome 1B (24.64 cM) annotated five putative candidate genes. This study led to the discovery of hitherto unreported loci for some less explored traits (such as leaf sheath wax, awn attitude, and glume pubescence) besides the refined chromosomal regions of known loci associated with the traits. This study provides valuable information of the genetic loci and their potential genes underlying the traits such as awn characters which are being considered as important contributors toward yield enhancement.

通过整合先进基因组技术开展小麦遗传改良,是提升作物产量的有效途径之一。为助力小麦重要经济性状的遗传改良育种,本研究针对404份基因型构成的多样性关联群体中与36项农艺形态性状相关的单核苷酸多态性(SNP)位点及潜在候选基因展开了分析。本研究采用育种家35K Axiom基因芯片,针对覆盖小麦基因组4364.79厘摩(cM)的范围开展全面全基因组关联分析,并结合压缩混合线性模型进行统计检验,最终在36项研究性状中鉴定出146个与23个性状显著关联的SNP位点(-log10P ≥ 4),这些位点可解释3.7%~47.0%的表型变异。为进一步解析相关遗传机制,本研究在5种环境下对260份基因型子集的6个数量性状进行了表型鉴定,包括抽穗期(DTH)、成熟期(DTM)、株高(PH)、穗长(SL)、芒长(Awn_L)及叶长(Leaf_L)。通过基因注释分析,本研究挖掘得到约38个潜在候选基因,并通过组织特异性和发育阶段特异性的RNA测序(RNA Seq)基因表达数据对其进行了验证。研究人员在1B染色体24.64厘摩区域内,发现了与4个性状(颖毛性状、穗长、株高及芒色)显著共定位的位点,并注释得到5个潜在候选基因。本研究不仅明确了已知关联位点的精细染色体区域,还发掘出多个此前未被报道的、针对部分较少研究性状(如叶鞘蜡质、芒姿及颖毛性状)的遗传位点。本研究为芒性状等关键农艺性状的遗传位点及潜在调控基因提供了宝贵的研究数据,而芒性状被认为是提升小麦产量的重要贡献因子。
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2019-04-25
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