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Identification and validation of stable quantitative trait loci for yield component traits in wheat

Authors :
Lingli Li
Yingjie Bian
Yan Dong
Jie Song
Dan Liu
Jianqi Zeng
Fengju Wang
Yong Zhang
Zhonghu He
Xianchun Xia
Yan Zhang
Shuanghe Cao
Source :
Crop Journal, Vol 11, Iss 2, Pp 558-563 (2023)
Publication Year :
2023
Publisher :
KeAi Communications Co., Ltd., 2023.

Abstract

Grain weight and grain number are important yield component traits in wheat and identification of underlying genetic loci is helpful for improving yield. Here, we identified eight stable quantitative trait loci (QTL) for yield component traits, including five loci for thousand grain weight (TGW) and three for grain number per spike (GNS) in a recombinant inbred line population derived from cross Yangxiaomai/Zhongyou 9507 across four environments. Since grain size is a major determinant of grain weight, we also mapped QTL for grain length (GL) and grain width (GW). QTGW.caas-2D, QTGW.caas-3B, QTGW.caas-5A and QTGW.caas-7A.2 for TGW co-located with those for grain size. QTGW.caas-2D also had a consistent genetic position with QGNS.caas-2D, suggesting that the pleiotropic locus is a modulator of trade-off effect between TGW and GNS. Sequencing and linkage mapping showed that TaGL3-5A and WAPO-A1 were candidate genes of QTGW.caas-5A and QTGW.caas-7A.2, respectively. We developed Kompetitive allele specific PCR (KASP) markers linked with the stable QTL for yield component traits and validated their genetic effects in a diverse panel of wheat cultivars from the Huang-Huai River Valley region. KASP-based genotyping analysis further revealed that the superior alleles of all stable QTL for TGW but not GNS were subject to positive selection, indicating that yield improvement in the region largely depends on increased TGW. Comparative analyses with previous studies showed that most of the QTL could be detected in different genetic backgrounds, and QTGW.caas-7A.1 is likely a new QTL. These findings provide not only valuable genetic information for yield improvement but also useful tools for marker-assisted selection.

Details

Language :
English
ISSN :
22145141
Volume :
11
Issue :
2
Database :
Directory of Open Access Journals
Journal :
Crop Journal
Publication Type :
Academic Journal
Accession number :
edsdoj.b47fc76bf7bb418fabe7550311d19716
Document Type :
article
Full Text :
https://doi.org/10.1016/j.cj.2022.09.012