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Transcriptome Analysis Revealed the Molecular Response Mechanism of High-Resistant and Low-Resistant Alfalfa Varieties to Verticillium Wilt

Following infestation by Verticillium wilt, alfalfa (Medicago sativa L.) often shows symptoms such as disease spots, leaf loss, stem, and leaf yellowing, resulting in the decline of alfalfa yield and quality and causing significant losses to the alfalfa industry. The popularization and planting of d...

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Autores principales: Li, Fang, Chen, Xi, Yang, Bo, Guang, Yingjie, Wu, Dandan, Shi, Zunji, Li, Yanzhong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9243768/
https://www.ncbi.nlm.nih.gov/pubmed/35783960
http://dx.doi.org/10.3389/fpls.2022.931001
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author Li, Fang
Chen, Xi
Yang, Bo
Guang, Yingjie
Wu, Dandan
Shi, Zunji
Li, Yanzhong
author_facet Li, Fang
Chen, Xi
Yang, Bo
Guang, Yingjie
Wu, Dandan
Shi, Zunji
Li, Yanzhong
author_sort Li, Fang
collection PubMed
description Following infestation by Verticillium wilt, alfalfa (Medicago sativa L.) often shows symptoms such as disease spots, leaf loss, stem, and leaf yellowing, resulting in the decline of alfalfa yield and quality and causing significant losses to the alfalfa industry. The popularization and planting of disease-resistant varieties is the most effective method to prevent and control Verticillium wilt of alfalfa. Therefore, it is particularly important to reveal the resistance mechanism of Verticillium wilt resistant varieties of alfalfa. In this study, the physiological and biochemical indexes were measured on days 7, 14, 21, and 28 after inoculation with Verticillium alfalfae for investigating the response mechanisms of two alfalfa varieties, high-resistant WL343HQ, and low-resistant Dryland. Transcriptome sequencing of alfalfa samples infected with V. alfalfae and uninfected alfalfa samples was performed to analyze the potential functions and signaling pathways of differentially expressed genes (DEGs) by GO classification and KEGG enrichment analysis. Meanwhile, weighted gene co-correlation network analysis (WGCNA) algorithm was used to construct a co-expression network of DEGs. Inoculation with V. alfalfae significantly affected net photosynthetic rate, stomatal conductance, chlorophyll content, MDA content, JA and SA concentrations, and NO and H(2)O(2) contents in both WL343HQ and Dryland inoculated with V. alfalfae. Most of the transcription factors in plants were classified in the WRKY, NAC, and bHLH families. WGCNA analysis showed that the number of transcription factors related to plant growth and disease resistance was higher in the corresponding modules of WL343HQ disease groups on days 7 and 28 (WVa) and (WVd) than in the corresponding modules of Dryland disease groups on days 7 and 21 (HVa) and (HVc). These findings provide data for further gene function validation and also provide a reference for in-depth studies on interactions between plants and pathogens.
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spelling pubmed-92437682022-07-01 Transcriptome Analysis Revealed the Molecular Response Mechanism of High-Resistant and Low-Resistant Alfalfa Varieties to Verticillium Wilt Li, Fang Chen, Xi Yang, Bo Guang, Yingjie Wu, Dandan Shi, Zunji Li, Yanzhong Front Plant Sci Plant Science Following infestation by Verticillium wilt, alfalfa (Medicago sativa L.) often shows symptoms such as disease spots, leaf loss, stem, and leaf yellowing, resulting in the decline of alfalfa yield and quality and causing significant losses to the alfalfa industry. The popularization and planting of disease-resistant varieties is the most effective method to prevent and control Verticillium wilt of alfalfa. Therefore, it is particularly important to reveal the resistance mechanism of Verticillium wilt resistant varieties of alfalfa. In this study, the physiological and biochemical indexes were measured on days 7, 14, 21, and 28 after inoculation with Verticillium alfalfae for investigating the response mechanisms of two alfalfa varieties, high-resistant WL343HQ, and low-resistant Dryland. Transcriptome sequencing of alfalfa samples infected with V. alfalfae and uninfected alfalfa samples was performed to analyze the potential functions and signaling pathways of differentially expressed genes (DEGs) by GO classification and KEGG enrichment analysis. Meanwhile, weighted gene co-correlation network analysis (WGCNA) algorithm was used to construct a co-expression network of DEGs. Inoculation with V. alfalfae significantly affected net photosynthetic rate, stomatal conductance, chlorophyll content, MDA content, JA and SA concentrations, and NO and H(2)O(2) contents in both WL343HQ and Dryland inoculated with V. alfalfae. Most of the transcription factors in plants were classified in the WRKY, NAC, and bHLH families. WGCNA analysis showed that the number of transcription factors related to plant growth and disease resistance was higher in the corresponding modules of WL343HQ disease groups on days 7 and 28 (WVa) and (WVd) than in the corresponding modules of Dryland disease groups on days 7 and 21 (HVa) and (HVc). These findings provide data for further gene function validation and also provide a reference for in-depth studies on interactions between plants and pathogens. Frontiers Media S.A. 2022-06-16 /pmc/articles/PMC9243768/ /pubmed/35783960 http://dx.doi.org/10.3389/fpls.2022.931001 Text en Copyright © 2022 Li, Chen, Yang, Guang, Wu, Shi and Li. 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
Li, Fang
Chen, Xi
Yang, Bo
Guang, Yingjie
Wu, Dandan
Shi, Zunji
Li, Yanzhong
Transcriptome Analysis Revealed the Molecular Response Mechanism of High-Resistant and Low-Resistant Alfalfa Varieties to Verticillium Wilt
title Transcriptome Analysis Revealed the Molecular Response Mechanism of High-Resistant and Low-Resistant Alfalfa Varieties to Verticillium Wilt
title_full Transcriptome Analysis Revealed the Molecular Response Mechanism of High-Resistant and Low-Resistant Alfalfa Varieties to Verticillium Wilt
title_fullStr Transcriptome Analysis Revealed the Molecular Response Mechanism of High-Resistant and Low-Resistant Alfalfa Varieties to Verticillium Wilt
title_full_unstemmed Transcriptome Analysis Revealed the Molecular Response Mechanism of High-Resistant and Low-Resistant Alfalfa Varieties to Verticillium Wilt
title_short Transcriptome Analysis Revealed the Molecular Response Mechanism of High-Resistant and Low-Resistant Alfalfa Varieties to Verticillium Wilt
title_sort transcriptome analysis revealed the molecular response mechanism of high-resistant and low-resistant alfalfa varieties to verticillium wilt
topic Plant Science
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9243768/
https://www.ncbi.nlm.nih.gov/pubmed/35783960
http://dx.doi.org/10.3389/fpls.2022.931001
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