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Major Genomic Regions for Wheat Grain Weight as Revealed by QTL Linkage Mapping and Meta-Analysis
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...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8866663/ https://www.ncbi.nlm.nih.gov/pubmed/35222467 http://dx.doi.org/10.3389/fpls.2022.802310 |
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author | Miao, Yongping Jing, Fanli Ma, Jingfu Liu, Yuan Zhang, Peipei Chen, Tao Che, Zhuo Yang, Delong |
author_facet | Miao, Yongping Jing, Fanli Ma, Jingfu Liu, Yuan Zhang, Peipei Chen, Tao Che, Zhuo Yang, Delong |
author_sort | Miao, Yongping |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-8866663 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-88666632022-02-25 Major Genomic Regions for Wheat Grain Weight as Revealed by QTL Linkage Mapping and Meta-Analysis Miao, Yongping Jing, Fanli Ma, Jingfu Liu, Yuan Zhang, Peipei Chen, Tao Che, Zhuo Yang, Delong Front Plant Sci Plant Science 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. Frontiers Media S.A. 2022-02-10 /pmc/articles/PMC8866663/ /pubmed/35222467 http://dx.doi.org/10.3389/fpls.2022.802310 Text en Copyright © 2022 Miao, Jing, Ma, Liu, Zhang, Chen, Che and Yang. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Plant Science Miao, Yongping Jing, Fanli Ma, Jingfu Liu, Yuan Zhang, Peipei Chen, Tao Che, Zhuo Yang, Delong Major Genomic Regions for Wheat Grain Weight as Revealed by QTL Linkage Mapping and Meta-Analysis |
title | Major Genomic Regions for Wheat Grain Weight as Revealed by QTL Linkage Mapping and Meta-Analysis |
title_full | Major Genomic Regions for Wheat Grain Weight as Revealed by QTL Linkage Mapping and Meta-Analysis |
title_fullStr | Major Genomic Regions for Wheat Grain Weight as Revealed by QTL Linkage Mapping and Meta-Analysis |
title_full_unstemmed | Major Genomic Regions for Wheat Grain Weight as Revealed by QTL Linkage Mapping and Meta-Analysis |
title_short | Major Genomic Regions for Wheat Grain Weight as Revealed by QTL Linkage Mapping and Meta-Analysis |
title_sort | major genomic regions for wheat grain weight as revealed by qtl linkage mapping and meta-analysis |
topic | Plant Science |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8866663/ https://www.ncbi.nlm.nih.gov/pubmed/35222467 http://dx.doi.org/10.3389/fpls.2022.802310 |
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