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QTL analysis of important agronomic traits and metabolites in foxtail millet (Setaria italica) by RIL population and widely targeted metabolome

As a bridge between genome and phenotype, metabolome is closely related to plant growth and development. However, the research on the combination of genome, metabolome and multiple agronomic traits in foxtail millet (Setaria italica) is insufficient. Here, based on the linkage analysis of 3,452 meta...

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Autores principales: Wei, Wei, Li, Shuangdong, Li, Peiyu, Yu, Kuohai, Fan, Guangyu, Wang, Yixiang, Zhao, Fang, Zhang, Xiaolei, Feng, Xiaolei, Shi, Gaolei, Zhang, Weiqin, Song, Guoliang, Dan, Wenhan, Wang, Feng, Zhang, Yali, Li, Xinru, Wang, Dequan, Zhang, Wenying, Pei, Jingjing, Wang, Xiaoming, Zhao, Zhihai
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9872001/
https://www.ncbi.nlm.nih.gov/pubmed/36704173
http://dx.doi.org/10.3389/fpls.2022.1035906
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author Wei, Wei
Li, Shuangdong
Li, Peiyu
Yu, Kuohai
Fan, Guangyu
Wang, Yixiang
Zhao, Fang
Zhang, Xiaolei
Feng, Xiaolei
Shi, Gaolei
Zhang, Weiqin
Song, Guoliang
Dan, Wenhan
Wang, Feng
Zhang, Yali
Li, Xinru
Wang, Dequan
Zhang, Wenying
Pei, Jingjing
Wang, Xiaoming
Zhao, Zhihai
author_facet Wei, Wei
Li, Shuangdong
Li, Peiyu
Yu, Kuohai
Fan, Guangyu
Wang, Yixiang
Zhao, Fang
Zhang, Xiaolei
Feng, Xiaolei
Shi, Gaolei
Zhang, Weiqin
Song, Guoliang
Dan, Wenhan
Wang, Feng
Zhang, Yali
Li, Xinru
Wang, Dequan
Zhang, Wenying
Pei, Jingjing
Wang, Xiaoming
Zhao, Zhihai
author_sort Wei, Wei
collection PubMed
description As a bridge between genome and phenotype, metabolome is closely related to plant growth and development. However, the research on the combination of genome, metabolome and multiple agronomic traits in foxtail millet (Setaria italica) is insufficient. Here, based on the linkage analysis of 3,452 metabolites via with high-quality genetic linkage maps, we detected a total of 1,049 metabolic quantitative trait loci (mQTLs) distributed in 11 hotspots, and 28 metabolite-related candidate genes were mined from 14 mQTLs. In addition, 136 single-environment phenotypic QTL (pQTLs) related to 63 phenotypes were identified by linkage analysis, and there were 12 hotspots on these pQTLs. We futher dissected 39 candidate genes related to agronomic traits through metabolite-phenotype correlation and gene function analysis, including Sd1 semidwarf gene, which can affect plant height by regulating GA synthesis. Combined correlation network and QTL analysis, we found that flavonoid-lignin pathway maybe closely related to plant architecture and yield in foxtail millet. For example, the correlation coefficient between apigenin 7-rutinoside and stem diameter reached 0.98, and they were co-located at 41.33-44.15 Mb of chromosome 5, further gene function analysis revealed that 5 flavonoid pathway genes, as well as Sd1, were located in this interval . Therefore, the correlation and co-localization between flavonoid-lignins and plant architecture may be due to the close linkage of their regulatory genes in millet. Besides, we also found that a combination of genomic and metabolomic for BLUP analysis can better predict plant agronomic traits than genomic or metabolomic data, independently. In conclusion, the combined analysis of mQTL and pQTL in millet have linked genetic, metabolic and agronomic traits, and is of great significance for metabolite-related molecular assisted breeding.
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spelling pubmed-98720012023-01-25 QTL analysis of important agronomic traits and metabolites in foxtail millet (Setaria italica) by RIL population and widely targeted metabolome Wei, Wei Li, Shuangdong Li, Peiyu Yu, Kuohai Fan, Guangyu Wang, Yixiang Zhao, Fang Zhang, Xiaolei Feng, Xiaolei Shi, Gaolei Zhang, Weiqin Song, Guoliang Dan, Wenhan Wang, Feng Zhang, Yali Li, Xinru Wang, Dequan Zhang, Wenying Pei, Jingjing Wang, Xiaoming Zhao, Zhihai Front Plant Sci Plant Science As a bridge between genome and phenotype, metabolome is closely related to plant growth and development. However, the research on the combination of genome, metabolome and multiple agronomic traits in foxtail millet (Setaria italica) is insufficient. Here, based on the linkage analysis of 3,452 metabolites via with high-quality genetic linkage maps, we detected a total of 1,049 metabolic quantitative trait loci (mQTLs) distributed in 11 hotspots, and 28 metabolite-related candidate genes were mined from 14 mQTLs. In addition, 136 single-environment phenotypic QTL (pQTLs) related to 63 phenotypes were identified by linkage analysis, and there were 12 hotspots on these pQTLs. We futher dissected 39 candidate genes related to agronomic traits through metabolite-phenotype correlation and gene function analysis, including Sd1 semidwarf gene, which can affect plant height by regulating GA synthesis. Combined correlation network and QTL analysis, we found that flavonoid-lignin pathway maybe closely related to plant architecture and yield in foxtail millet. For example, the correlation coefficient between apigenin 7-rutinoside and stem diameter reached 0.98, and they were co-located at 41.33-44.15 Mb of chromosome 5, further gene function analysis revealed that 5 flavonoid pathway genes, as well as Sd1, were located in this interval . Therefore, the correlation and co-localization between flavonoid-lignins and plant architecture may be due to the close linkage of their regulatory genes in millet. Besides, we also found that a combination of genomic and metabolomic for BLUP analysis can better predict plant agronomic traits than genomic or metabolomic data, independently. In conclusion, the combined analysis of mQTL and pQTL in millet have linked genetic, metabolic and agronomic traits, and is of great significance for metabolite-related molecular assisted breeding. Frontiers Media S.A. 2023-01-10 /pmc/articles/PMC9872001/ /pubmed/36704173 http://dx.doi.org/10.3389/fpls.2022.1035906 Text en Copyright © 2023 Wei, Li, Li, Yu, Fan, Wang, Zhao, Zhang, Feng, Shi, Zhang, Song, Dan, Wang, Zhang, Li, Wang, Zhang, Pei, Wang and Zhao 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
Wei, Wei
Li, Shuangdong
Li, Peiyu
Yu, Kuohai
Fan, Guangyu
Wang, Yixiang
Zhao, Fang
Zhang, Xiaolei
Feng, Xiaolei
Shi, Gaolei
Zhang, Weiqin
Song, Guoliang
Dan, Wenhan
Wang, Feng
Zhang, Yali
Li, Xinru
Wang, Dequan
Zhang, Wenying
Pei, Jingjing
Wang, Xiaoming
Zhao, Zhihai
QTL analysis of important agronomic traits and metabolites in foxtail millet (Setaria italica) by RIL population and widely targeted metabolome
title QTL analysis of important agronomic traits and metabolites in foxtail millet (Setaria italica) by RIL population and widely targeted metabolome
title_full QTL analysis of important agronomic traits and metabolites in foxtail millet (Setaria italica) by RIL population and widely targeted metabolome
title_fullStr QTL analysis of important agronomic traits and metabolites in foxtail millet (Setaria italica) by RIL population and widely targeted metabolome
title_full_unstemmed QTL analysis of important agronomic traits and metabolites in foxtail millet (Setaria italica) by RIL population and widely targeted metabolome
title_short QTL analysis of important agronomic traits and metabolites in foxtail millet (Setaria italica) by RIL population and widely targeted metabolome
title_sort qtl analysis of important agronomic traits and metabolites in foxtail millet (setaria italica) by ril population and widely targeted metabolome
topic Plant Science
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9872001/
https://www.ncbi.nlm.nih.gov/pubmed/36704173
http://dx.doi.org/10.3389/fpls.2022.1035906
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