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Manipulation and prediction of spike morphology traits for the improvement of grain yield in wheat

In wheat (Triticum spp.), modifying inflorescence (spike) morphology can increase grain number and size and thus improve yield. Here, we demonstrated the potential for manipulating and predicting spike morphology, based on 44 traits. In 12 wheat cultivars, we observed that detillering (removal of br...

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Autores principales: Guo, Zifeng, Zhao, Yusheng, Röder, Marion S., Reif, Jochen C., Ganal, Martin W., Chen, Dijun, Schnurbusch, Thorsten
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6158183/
https://www.ncbi.nlm.nih.gov/pubmed/30258057
http://dx.doi.org/10.1038/s41598-018-31977-3
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author Guo, Zifeng
Zhao, Yusheng
Röder, Marion S.
Reif, Jochen C.
Ganal, Martin W.
Chen, Dijun
Schnurbusch, Thorsten
author_facet Guo, Zifeng
Zhao, Yusheng
Röder, Marion S.
Reif, Jochen C.
Ganal, Martin W.
Chen, Dijun
Schnurbusch, Thorsten
author_sort Guo, Zifeng
collection PubMed
description In wheat (Triticum spp.), modifying inflorescence (spike) morphology can increase grain number and size and thus improve yield. Here, we demonstrated the potential for manipulating and predicting spike morphology, based on 44 traits. In 12 wheat cultivars, we observed that detillering (removal of branches), which alters photosynthate distribution, changed spike morphology. Our genome-wide association study detected close associations between carbon partitioning (e.g. tiller number, main shoot dry weight) and spike morphology (e.g. spike length, spikelet density) traits in 210 cultivars. Most carbon-partitioning traits (e.g. tiller dry weight, harvest index) demonstrated high prediction abilities (>0.5). For spike morphology, some traits (e.g. total and fertile spikelet number, spike length) displayed high prediction abilities (0.3–0.5), but others (e.g. spikelet fertility, spikelet density) exhibited low prediction abilities (<0.2). Grain size traits were closely correlated in field and greenhouse experiments. Stepwise regression analysis suggests that significantly associated traits in the greenhouse explain 35.35% of the variation in grain yield and 67.63% of the variation in thousand-kernel weight in the field. Therefore, the traits identified in this study affect spike morphology; these traits can be used to predict and improve plant architecture and thus increase yield.
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spelling pubmed-61581832018-09-28 Manipulation and prediction of spike morphology traits for the improvement of grain yield in wheat Guo, Zifeng Zhao, Yusheng Röder, Marion S. Reif, Jochen C. Ganal, Martin W. Chen, Dijun Schnurbusch, Thorsten Sci Rep Article In wheat (Triticum spp.), modifying inflorescence (spike) morphology can increase grain number and size and thus improve yield. Here, we demonstrated the potential for manipulating and predicting spike morphology, based on 44 traits. In 12 wheat cultivars, we observed that detillering (removal of branches), which alters photosynthate distribution, changed spike morphology. Our genome-wide association study detected close associations between carbon partitioning (e.g. tiller number, main shoot dry weight) and spike morphology (e.g. spike length, spikelet density) traits in 210 cultivars. Most carbon-partitioning traits (e.g. tiller dry weight, harvest index) demonstrated high prediction abilities (>0.5). For spike morphology, some traits (e.g. total and fertile spikelet number, spike length) displayed high prediction abilities (0.3–0.5), but others (e.g. spikelet fertility, spikelet density) exhibited low prediction abilities (<0.2). Grain size traits were closely correlated in field and greenhouse experiments. Stepwise regression analysis suggests that significantly associated traits in the greenhouse explain 35.35% of the variation in grain yield and 67.63% of the variation in thousand-kernel weight in the field. Therefore, the traits identified in this study affect spike morphology; these traits can be used to predict and improve plant architecture and thus increase yield. Nature Publishing Group UK 2018-09-26 /pmc/articles/PMC6158183/ /pubmed/30258057 http://dx.doi.org/10.1038/s41598-018-31977-3 Text en © The Author(s) 2018 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Guo, Zifeng
Zhao, Yusheng
Röder, Marion S.
Reif, Jochen C.
Ganal, Martin W.
Chen, Dijun
Schnurbusch, Thorsten
Manipulation and prediction of spike morphology traits for the improvement of grain yield in wheat
title Manipulation and prediction of spike morphology traits for the improvement of grain yield in wheat
title_full Manipulation and prediction of spike morphology traits for the improvement of grain yield in wheat
title_fullStr Manipulation and prediction of spike morphology traits for the improvement of grain yield in wheat
title_full_unstemmed Manipulation and prediction of spike morphology traits for the improvement of grain yield in wheat
title_short Manipulation and prediction of spike morphology traits for the improvement of grain yield in wheat
title_sort manipulation and prediction of spike morphology traits for the improvement of grain yield in wheat
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6158183/
https://www.ncbi.nlm.nih.gov/pubmed/30258057
http://dx.doi.org/10.1038/s41598-018-31977-3
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