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Weighted Gene Co-Expression Network Coupled with a Critical-Time-Point Analysis during Pathogenesis for Predicting the Molecular Mechanism Underlying Blast Resistance in Rice

BACKGROUND: Rice blast, caused by the ascomycete fungus M. oryzae, is one of the most important diseases of rice. Although many blast resistance (R) genes have been identified and deployed in rice varieties, the molecular mechanisms responsible for the R gene-mediated defense responses are yet not f...

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Autores principales: Tian, Dagang, Chen, Zaijie, Lin, Yan, Chen, Ziqiang, Bui, Khuynh The, Wang, Zonghua, Wang, Feng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7732884/
https://www.ncbi.nlm.nih.gov/pubmed/33306159
http://dx.doi.org/10.1186/s12284-020-00439-8
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author Tian, Dagang
Chen, Zaijie
Lin, Yan
Chen, Ziqiang
Bui, Khuynh The
Wang, Zonghua
Wang, Feng
author_facet Tian, Dagang
Chen, Zaijie
Lin, Yan
Chen, Ziqiang
Bui, Khuynh The
Wang, Zonghua
Wang, Feng
author_sort Tian, Dagang
collection PubMed
description BACKGROUND: Rice blast, caused by the ascomycete fungus M. oryzae, is one of the most important diseases of rice. Although many blast resistance (R) genes have been identified and deployed in rice varieties, the molecular mechanisms responsible for the R gene-mediated defense responses are yet not fully understood. RESULTS: In this study, we used comparative transcriptomic analysis to explore the molecular mechanism involved in Piz-t-mediated resistance in a transgenic line containing Piz-t (NPB-Piz-t) compared to Nipponbare (NPB). Clustering and principal component analysis (PCA) revealed that the time-point at 24-h post inoculation (hpi) was the most important factor distinguishing the four time-points, which consisted of four genes of mitogen-activated protein kinases (MAPKs) signaling pathway, one gene related to WRKY DNA-binding domain containing protein, five pathogenesis-related protein (OsPR1s) genes, and three genes of R proteins involving in the most significant protein-protein interaction (PPI) pathway. Using weighted gene co-expression network analysis (WGCNA) to investigate RNA-seq data across 0, 24, 48, and 72 hpi, nine modules with similar patterns expression pattern (SEP) and three modules with differential expression pattern (DEP) between NPB-Piz-t and NPB across 0, 24, 48, and 72 hpi with KJ201 (referred to as Piz-t-KJ201 and NPB-KJ201) were identified. Among these the most representative SEP green-yellow module is associated with photosynthesis, and DEP pink module comprised of two specific expressed nucleotide-binding domain and leucine-rich repeat (NLR) genes of LOC_Os06g17900 and LOC_Os06g17920 of Pi2/9 homologous, three NLR genes of LOC_Os11g11810, LOC_Os11g11770, and LOC_Os11g11920 which are putatively associated with important agronomic traits, and a B3 DNA binding domain containing protein related genes (LOC_Os10g39190). Knockout of LOC_Os10g39190 via CRISPR-Cas9 resulted in plant death at the seedling stage. CONCLUSIONS: The research suggested that Piz-t and multiple NLR network might play important roles in the regulation of the resistance response in the Piz-t-KJ201 interaction system. The identified genes provide an NLR repository to study the rice-M. oryzae interaction system and facilitate the breeding of blast-resistant cultivars in the future.
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spelling pubmed-77328842020-12-21 Weighted Gene Co-Expression Network Coupled with a Critical-Time-Point Analysis during Pathogenesis for Predicting the Molecular Mechanism Underlying Blast Resistance in Rice Tian, Dagang Chen, Zaijie Lin, Yan Chen, Ziqiang Bui, Khuynh The Wang, Zonghua Wang, Feng Rice (N Y) Original Article BACKGROUND: Rice blast, caused by the ascomycete fungus M. oryzae, is one of the most important diseases of rice. Although many blast resistance (R) genes have been identified and deployed in rice varieties, the molecular mechanisms responsible for the R gene-mediated defense responses are yet not fully understood. RESULTS: In this study, we used comparative transcriptomic analysis to explore the molecular mechanism involved in Piz-t-mediated resistance in a transgenic line containing Piz-t (NPB-Piz-t) compared to Nipponbare (NPB). Clustering and principal component analysis (PCA) revealed that the time-point at 24-h post inoculation (hpi) was the most important factor distinguishing the four time-points, which consisted of four genes of mitogen-activated protein kinases (MAPKs) signaling pathway, one gene related to WRKY DNA-binding domain containing protein, five pathogenesis-related protein (OsPR1s) genes, and three genes of R proteins involving in the most significant protein-protein interaction (PPI) pathway. Using weighted gene co-expression network analysis (WGCNA) to investigate RNA-seq data across 0, 24, 48, and 72 hpi, nine modules with similar patterns expression pattern (SEP) and three modules with differential expression pattern (DEP) between NPB-Piz-t and NPB across 0, 24, 48, and 72 hpi with KJ201 (referred to as Piz-t-KJ201 and NPB-KJ201) were identified. Among these the most representative SEP green-yellow module is associated with photosynthesis, and DEP pink module comprised of two specific expressed nucleotide-binding domain and leucine-rich repeat (NLR) genes of LOC_Os06g17900 and LOC_Os06g17920 of Pi2/9 homologous, three NLR genes of LOC_Os11g11810, LOC_Os11g11770, and LOC_Os11g11920 which are putatively associated with important agronomic traits, and a B3 DNA binding domain containing protein related genes (LOC_Os10g39190). Knockout of LOC_Os10g39190 via CRISPR-Cas9 resulted in plant death at the seedling stage. CONCLUSIONS: The research suggested that Piz-t and multiple NLR network might play important roles in the regulation of the resistance response in the Piz-t-KJ201 interaction system. The identified genes provide an NLR repository to study the rice-M. oryzae interaction system and facilitate the breeding of blast-resistant cultivars in the future. Springer US 2020-12-11 /pmc/articles/PMC7732884/ /pubmed/33306159 http://dx.doi.org/10.1186/s12284-020-00439-8 Text en © The Author(s) 2020 Open AccessThis 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Original Article
Tian, Dagang
Chen, Zaijie
Lin, Yan
Chen, Ziqiang
Bui, Khuynh The
Wang, Zonghua
Wang, Feng
Weighted Gene Co-Expression Network Coupled with a Critical-Time-Point Analysis during Pathogenesis for Predicting the Molecular Mechanism Underlying Blast Resistance in Rice
title Weighted Gene Co-Expression Network Coupled with a Critical-Time-Point Analysis during Pathogenesis for Predicting the Molecular Mechanism Underlying Blast Resistance in Rice
title_full Weighted Gene Co-Expression Network Coupled with a Critical-Time-Point Analysis during Pathogenesis for Predicting the Molecular Mechanism Underlying Blast Resistance in Rice
title_fullStr Weighted Gene Co-Expression Network Coupled with a Critical-Time-Point Analysis during Pathogenesis for Predicting the Molecular Mechanism Underlying Blast Resistance in Rice
title_full_unstemmed Weighted Gene Co-Expression Network Coupled with a Critical-Time-Point Analysis during Pathogenesis for Predicting the Molecular Mechanism Underlying Blast Resistance in Rice
title_short Weighted Gene Co-Expression Network Coupled with a Critical-Time-Point Analysis during Pathogenesis for Predicting the Molecular Mechanism Underlying Blast Resistance in Rice
title_sort weighted gene co-expression network coupled with a critical-time-point analysis during pathogenesis for predicting the molecular mechanism underlying blast resistance in rice
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7732884/
https://www.ncbi.nlm.nih.gov/pubmed/33306159
http://dx.doi.org/10.1186/s12284-020-00439-8
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