Major Genomic Regions for Wheat Grain Weight as Revealed by QTL Linkage Mapping and Meta-Analysis

被引:29
作者
Miao, Yongping [1 ,2 ]
Jing, Fanli [1 ,2 ]
Ma, Jingfu [1 ,2 ]
Liu, Yuan [1 ,2 ]
Zhang, Peipei [1 ]
Chen, Tao [1 ,2 ]
Che, Zhuo [3 ]
Yang, Delong [1 ,2 ]
机构
[1] State Key Lab Aridland Crop Sci, Lanzhou, Gansu, Peoples R China
[2] Gansu Agr Univ, Coll Life Sci & Technol, Lanzhou, Gansu, Peoples R China
[3] Plant Seed Master Stn Gansu Prov, Lanzhou, Gansu, Peoples R China
基金
中国国家自然科学基金;
关键词
wheat; thousand grain weight; quantitative trait loci; meta-analysis; candidate genes; QUANTITATIVE TRAIT LOCI; GENETIC-ANALYSIS; BREAD WHEAT; AGRONOMIC TRAITS; STRESS TOLERANCE; YIELD; RESISTANCE; ARCHITECTURE; ASSOCIATION; INTERVAL;
D O I
10.3389/fpls.2022.802310
中图分类号
Q94 [植物学];
学科分类号
071001 ;
摘要
Grain weight is a key determinant for grain yield potential in wheat, which is highly governed by a type of quantitative genetic basis. The identification of major quantitative trait locus (QTL) and functional genes are urgently required for molecular improvements in wheat grain yield. In this study, major genomic regions and putative candidate genes for thousand grain weight (TGW) were revealed by integrative approaches with QTL linkage mapping, meta-analysis and transcriptome evaluation. Forty-five TGW QTLs were detected using a set of recombinant inbred lines, explaining 1.76-12.87% of the phenotypic variation. Of these, ten stable QTLs were identified across more than four environments. Meta-QTL (MQTL) analysis were performed on 394 initial TGW QTLs available from previous studies and the present study, where 274 loci were finally refined into 67 MQTLs. The average confidence interval of these MQTLs was 3.73-fold less than that of initial QTLs. A total of 134 putative candidate genes were mined within MQTL regions by combined analysis of transcriptomic and omics data. Some key putative candidate genes similar to those reported early for grain development and grain weight formation were further discussed. This finding will provide a better understanding of the genetic determinants of TGW and will be useful for marker-assisted selection of high yield in wheat breeding.
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页数:19
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