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Weighted gene co-expression network analysis identifies genes related to HG Type 0 resistance and verification of hub gene GmHg1

INTRODUCTION: The soybean cyst nematode (SCN) is a major disease in soybean production thatseriously affects soybean yield. At present, there are no studies on weighted geneco-expression network analysis (WGCNA) related to SCN resistance. METHODS: Here, transcriptome data from 36 soybean roots under...

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Autores principales: Jiang, Haipeng, Zhou, Changjun, Ma, Jinglin, Qu, Shuo, Liu, Fang, Sun, Haowen, Zhao, Xue, Han, Yingpeng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9911859/
https://www.ncbi.nlm.nih.gov/pubmed/36777536
http://dx.doi.org/10.3389/fpls.2022.1118503
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author Jiang, Haipeng
Zhou, Changjun
Ma, Jinglin
Qu, Shuo
Liu, Fang
Sun, Haowen
Zhao, Xue
Han, Yingpeng
author_facet Jiang, Haipeng
Zhou, Changjun
Ma, Jinglin
Qu, Shuo
Liu, Fang
Sun, Haowen
Zhao, Xue
Han, Yingpeng
author_sort Jiang, Haipeng
collection PubMed
description INTRODUCTION: The soybean cyst nematode (SCN) is a major disease in soybean production thatseriously affects soybean yield. At present, there are no studies on weighted geneco-expression network analysis (WGCNA) related to SCN resistance. METHODS: Here, transcriptome data from 36 soybean roots under SCN HG Type 0 (race 3) stresswere used in WGCNA to identify significant modules. RESULTS AND DISCUSSION: A total of 10,000 differentially expressed genes and 21 modules were identified, of which the module most related to SCN was turquoise. In addition, the hub gene GmHg1 with high connectivity was selected, and its function was verified. GmHg1 encodes serine/threonine protein kinase (PK), and the expression of GmHg1 in SCN-resistant cultivars (‘Dongnong L-204’) and SCN-susceptible cultivars (‘Heinong 37’) increased significantly after HG Type 0 stress. Soybean plants transformed with GmHg1-OX had significantly increased SCN resistance. In contrast, the GmHg1-RNAi transgenic soybean plants significantly reduced SCN resistance. In transgenic materials, the expression patterns of 11 genes with the same expression trend as the GmHg1 gene in the ‘turquoise module’ were analyzed. Analysis showed that 11genes were co-expressed with GmHg1, which may be involved in the process of soybean resistance to SCN. Our work provides a new direction for studying the Molecular mechanism of soybean resistance to SCN.
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spelling pubmed-99118592023-02-11 Weighted gene co-expression network analysis identifies genes related to HG Type 0 resistance and verification of hub gene GmHg1 Jiang, Haipeng Zhou, Changjun Ma, Jinglin Qu, Shuo Liu, Fang Sun, Haowen Zhao, Xue Han, Yingpeng Front Plant Sci Plant Science INTRODUCTION: The soybean cyst nematode (SCN) is a major disease in soybean production thatseriously affects soybean yield. At present, there are no studies on weighted geneco-expression network analysis (WGCNA) related to SCN resistance. METHODS: Here, transcriptome data from 36 soybean roots under SCN HG Type 0 (race 3) stresswere used in WGCNA to identify significant modules. RESULTS AND DISCUSSION: A total of 10,000 differentially expressed genes and 21 modules were identified, of which the module most related to SCN was turquoise. In addition, the hub gene GmHg1 with high connectivity was selected, and its function was verified. GmHg1 encodes serine/threonine protein kinase (PK), and the expression of GmHg1 in SCN-resistant cultivars (‘Dongnong L-204’) and SCN-susceptible cultivars (‘Heinong 37’) increased significantly after HG Type 0 stress. Soybean plants transformed with GmHg1-OX had significantly increased SCN resistance. In contrast, the GmHg1-RNAi transgenic soybean plants significantly reduced SCN resistance. In transgenic materials, the expression patterns of 11 genes with the same expression trend as the GmHg1 gene in the ‘turquoise module’ were analyzed. Analysis showed that 11genes were co-expressed with GmHg1, which may be involved in the process of soybean resistance to SCN. Our work provides a new direction for studying the Molecular mechanism of soybean resistance to SCN. Frontiers Media S.A. 2023-01-27 /pmc/articles/PMC9911859/ /pubmed/36777536 http://dx.doi.org/10.3389/fpls.2022.1118503 Text en Copyright © 2023 Jiang, Zhou, Ma, Qu, Liu, Sun, Zhao and Han 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
Jiang, Haipeng
Zhou, Changjun
Ma, Jinglin
Qu, Shuo
Liu, Fang
Sun, Haowen
Zhao, Xue
Han, Yingpeng
Weighted gene co-expression network analysis identifies genes related to HG Type 0 resistance and verification of hub gene GmHg1
title Weighted gene co-expression network analysis identifies genes related to HG Type 0 resistance and verification of hub gene GmHg1
title_full Weighted gene co-expression network analysis identifies genes related to HG Type 0 resistance and verification of hub gene GmHg1
title_fullStr Weighted gene co-expression network analysis identifies genes related to HG Type 0 resistance and verification of hub gene GmHg1
title_full_unstemmed Weighted gene co-expression network analysis identifies genes related to HG Type 0 resistance and verification of hub gene GmHg1
title_short Weighted gene co-expression network analysis identifies genes related to HG Type 0 resistance and verification of hub gene GmHg1
title_sort weighted gene co-expression network analysis identifies genes related to hg type 0 resistance and verification of hub gene gmhg1
topic Plant Science
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9911859/
https://www.ncbi.nlm.nih.gov/pubmed/36777536
http://dx.doi.org/10.3389/fpls.2022.1118503
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