Table_7_Uncovering Genomic Regions Associated With 36 Agro-Morphological Traits in Indian Spring Wheat Using GWAS.xlsx
收藏NIAID Data Ecosystem2026-03-11 收录
下载链接:
https://figshare.com/articles/dataset/Table_7_Uncovering_Genomic_Regions_Associated_With_36_Agro-Morphological_Traits_in_Indian_Spring_Wheat_Using_GWAS_xlsx/8082134
下载链接
链接失效反馈官方服务:
资源简介:
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.
整合先进基因组学技术开展小麦遗传改良,是提升作物生产效率的重要途径之一。为助力小麦重要经济性状的遗传育种工作,本研究针对由404份基因型材料构成的多样性群体,开展了与36个农艺形态性状相关的单核苷酸多态性位点(SNP loci)及潜在候选基因的筛选分析。本研究采用育种家35K Axiom基因芯片(Breeders’ 35K Axiom array),针对覆盖小麦基因组4364.79厘摩的区间开展全基因组关联分析,并结合压缩混合线性模型(compressed mixed linear model)进行统计检验,最终在36个被测性状中,鉴定到与23个性状显著关联的146个单核苷酸多态性位点,这些位点可解释3.7%~47.0%的表型变异(-log10P ≥ 4)。为进一步解析相关遗传机制,本研究针对其中260份基因型材料,在5个环境下完成了6个数量性状的表型鉴定,包括抽穗天数(DTH)、成熟天数(DTM)、株高(PH)、穗长(SL)、芒长(Awn_L)及叶长(Leaf_L)。通过基因注释分析,本研究共挖掘得到约38个推定候选基因,并通过组织特异性与发育阶段特异性的RNA测序(RNA Seq)基因表达数据对其进行了验证。本研究在1B染色体24.64 cM区间内,检测到颖壳茸毛、穗长、株高及芒色4个性状的强共定位位点,并注释得到5个推定候选基因。本研究不仅对已报道的性状关联染色体区域进行了精细定位,还鉴定得到若干此前未被报道的、针对较少研究性状(如叶鞘蜡质、芒姿及颖壳茸毛)的遗传位点。本研究为芒型等性状的遗传位点及潜在功能基因提供了宝贵的研究数据,而芒型被认为是提升小麦产量的重要贡献性状。
创建时间:
2019-05-06



