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Mining synergistic genes for nutrient utilization and disease resistance in maize based on co-expression network and consensus QTLs

Nutrient restrictions and large-scale emergence of diseases are threatening the maize production. Recent findings demonstrated that there is a certain synergistic interaction between nutrition and diseases pathways in model plants, however there are few studies on the synergistic genes of nutrients...

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Autores principales: Luo, Bowen, Li, Jiaqian, Li, Binyang, Zhang, Haiying, Yu, Ting, Zhang, Guidi, Zhang, Shuhao, Sahito, Javed Hussain, Zhang, Xiao, Liu, Dan, Wu, Ling, Gao, Duojiang, Gao, Shiqiang, Gao, Shibin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9650340/
https://www.ncbi.nlm.nih.gov/pubmed/36388550
http://dx.doi.org/10.3389/fpls.2022.1013598
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author Luo, Bowen
Li, Jiaqian
Li, Binyang
Zhang, Haiying
Yu, Ting
Zhang, Guidi
Zhang, Shuhao
Sahito, Javed Hussain
Zhang, Xiao
Liu, Dan
Wu, Ling
Gao, Duojiang
Gao, Shiqiang
Gao, Shibin
author_facet Luo, Bowen
Li, Jiaqian
Li, Binyang
Zhang, Haiying
Yu, Ting
Zhang, Guidi
Zhang, Shuhao
Sahito, Javed Hussain
Zhang, Xiao
Liu, Dan
Wu, Ling
Gao, Duojiang
Gao, Shiqiang
Gao, Shibin
author_sort Luo, Bowen
collection PubMed
description Nutrient restrictions and large-scale emergence of diseases are threatening the maize production. Recent findings demonstrated that there is a certain synergistic interaction between nutrition and diseases pathways in model plants, however there are few studies on the synergistic genes of nutrients and diseases in maize. Thus, the transcriptome data of nitrogen (N) and phosphorus (P) nutrients and diseases treatments in maize, rice, wheat and Arabidopsis thaliana were collected in this study, and four and 22 weighted co-expression modules were obtained by using Weighted Gene Co-expression Network Analysis (WGCNA) in leaf and root tissues, respectively. With a total of 5252 genes, MFUZZ cluster analysis screened 26 clusters with the same expression trend under nutrition and disease treatments. In the meantime, 1427 genes and 22 specific consensus quantitative trait loci (scQTLs) loci were identified by meta-QTL analysis of nitrogen and phosphorus nutrition and disease stress in maize. Combined with the results of cluster analysis and scQTLs, a total of 195 consistent genes were screened, of which six genes were shown to synergistically respond to nutrition and disease both in roots and leaves. Moreover, the six candidate genes were found in scQTLs associated with gray leaf spot (GLS) and corn leaf blight (CLB). In addition, subcellular localization and bioinformatics analysis of the six candidate genes revealed that they were primarily expressed in endoplasmic reticulum, mitochondria, nucleus and plasma membrane, and were involved in defense and stress, MeJA and abscisic acid response pathways. The fluorescence quantitative PCR confirmed their responsiveness to nitrogen and phosphorus nutrition as well as GLS treatments. Taken together, findings of this study indicated that the nutrition and disease have a significant synergistic response in maize.
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spelling pubmed-96503402022-11-15 Mining synergistic genes for nutrient utilization and disease resistance in maize based on co-expression network and consensus QTLs Luo, Bowen Li, Jiaqian Li, Binyang Zhang, Haiying Yu, Ting Zhang, Guidi Zhang, Shuhao Sahito, Javed Hussain Zhang, Xiao Liu, Dan Wu, Ling Gao, Duojiang Gao, Shiqiang Gao, Shibin Front Plant Sci Plant Science Nutrient restrictions and large-scale emergence of diseases are threatening the maize production. Recent findings demonstrated that there is a certain synergistic interaction between nutrition and diseases pathways in model plants, however there are few studies on the synergistic genes of nutrients and diseases in maize. Thus, the transcriptome data of nitrogen (N) and phosphorus (P) nutrients and diseases treatments in maize, rice, wheat and Arabidopsis thaliana were collected in this study, and four and 22 weighted co-expression modules were obtained by using Weighted Gene Co-expression Network Analysis (WGCNA) in leaf and root tissues, respectively. With a total of 5252 genes, MFUZZ cluster analysis screened 26 clusters with the same expression trend under nutrition and disease treatments. In the meantime, 1427 genes and 22 specific consensus quantitative trait loci (scQTLs) loci were identified by meta-QTL analysis of nitrogen and phosphorus nutrition and disease stress in maize. Combined with the results of cluster analysis and scQTLs, a total of 195 consistent genes were screened, of which six genes were shown to synergistically respond to nutrition and disease both in roots and leaves. Moreover, the six candidate genes were found in scQTLs associated with gray leaf spot (GLS) and corn leaf blight (CLB). In addition, subcellular localization and bioinformatics analysis of the six candidate genes revealed that they were primarily expressed in endoplasmic reticulum, mitochondria, nucleus and plasma membrane, and were involved in defense and stress, MeJA and abscisic acid response pathways. The fluorescence quantitative PCR confirmed their responsiveness to nitrogen and phosphorus nutrition as well as GLS treatments. Taken together, findings of this study indicated that the nutrition and disease have a significant synergistic response in maize. Frontiers Media S.A. 2022-10-28 /pmc/articles/PMC9650340/ /pubmed/36388550 http://dx.doi.org/10.3389/fpls.2022.1013598 Text en Copyright © 2022 Luo, Li, Li, Zhang, Yu, Zhang, Zhang, Sahito, Zhang, Liu, Wu, Gao, Gao and Gao 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
Luo, Bowen
Li, Jiaqian
Li, Binyang
Zhang, Haiying
Yu, Ting
Zhang, Guidi
Zhang, Shuhao
Sahito, Javed Hussain
Zhang, Xiao
Liu, Dan
Wu, Ling
Gao, Duojiang
Gao, Shiqiang
Gao, Shibin
Mining synergistic genes for nutrient utilization and disease resistance in maize based on co-expression network and consensus QTLs
title Mining synergistic genes for nutrient utilization and disease resistance in maize based on co-expression network and consensus QTLs
title_full Mining synergistic genes for nutrient utilization and disease resistance in maize based on co-expression network and consensus QTLs
title_fullStr Mining synergistic genes for nutrient utilization and disease resistance in maize based on co-expression network and consensus QTLs
title_full_unstemmed Mining synergistic genes for nutrient utilization and disease resistance in maize based on co-expression network and consensus QTLs
title_short Mining synergistic genes for nutrient utilization and disease resistance in maize based on co-expression network and consensus QTLs
title_sort mining synergistic genes for nutrient utilization and disease resistance in maize based on co-expression network and consensus qtls
topic Plant Science
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9650340/
https://www.ncbi.nlm.nih.gov/pubmed/36388550
http://dx.doi.org/10.3389/fpls.2022.1013598
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