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Analysis of drought-responsive signalling network in two contrasting rice cultivars using transcriptome-based approach

Traditional cultivars of rice in India exhibit tolerance to drought stress due to their inherent genetic variations. Here we present comparative physiological and transcriptome analyses of two contrasting cultivars, drought tolerant Dhagaddeshi (DD) and susceptible IR20. Microarray analysis revealed...

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Autores principales: Borah, Pratikshya, Sharma, Eshan, Kaur, Amarjot, Chandel, Girish, Mohapatra, Trilochan, Kapoor, Sanjay, Khurana, Jitendra P.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5299611/
https://www.ncbi.nlm.nih.gov/pubmed/28181537
http://dx.doi.org/10.1038/srep42131
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author Borah, Pratikshya
Sharma, Eshan
Kaur, Amarjot
Chandel, Girish
Mohapatra, Trilochan
Kapoor, Sanjay
Khurana, Jitendra P.
author_facet Borah, Pratikshya
Sharma, Eshan
Kaur, Amarjot
Chandel, Girish
Mohapatra, Trilochan
Kapoor, Sanjay
Khurana, Jitendra P.
author_sort Borah, Pratikshya
collection PubMed
description Traditional cultivars of rice in India exhibit tolerance to drought stress due to their inherent genetic variations. Here we present comparative physiological and transcriptome analyses of two contrasting cultivars, drought tolerant Dhagaddeshi (DD) and susceptible IR20. Microarray analysis revealed several differentially expressed genes (DEGs) exclusively in DD as compared to IR20 seedlings exposed to 3 h drought stress. Physiologically, DD seedlings showed higher cell membrane stability and differential ABA accumulation in response to dehydration, coupled with rapid changes in gene expression. Detailed analyses of metabolic pathways enriched in expression data suggest interplay of ABA dependent along with secondary and redox metabolic networks that activate osmotic and detoxification signalling in DD. By co-localization of DEGs with QTLs from databases or published literature for physiological traits of DD and IR20, candidate genes were identified including those underlying major QTL qDTY(1.1) in DD. Further, we identified previously uncharacterized genes from both DD and IR20 under drought conditions including OsWRKY51, OsVP1 and confirmed their expression by qPCR in multiple rice cultivars. OsFBK1 was also functionally validated in susceptible PB1 rice cultivar and Arabidopsis for providing drought tolerance. Some of the DEGs mapped to the known QTLs could thus, be of potential significance for marker-assisted breeding.
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spelling pubmed-52996112017-02-13 Analysis of drought-responsive signalling network in two contrasting rice cultivars using transcriptome-based approach Borah, Pratikshya Sharma, Eshan Kaur, Amarjot Chandel, Girish Mohapatra, Trilochan Kapoor, Sanjay Khurana, Jitendra P. Sci Rep Article Traditional cultivars of rice in India exhibit tolerance to drought stress due to their inherent genetic variations. Here we present comparative physiological and transcriptome analyses of two contrasting cultivars, drought tolerant Dhagaddeshi (DD) and susceptible IR20. Microarray analysis revealed several differentially expressed genes (DEGs) exclusively in DD as compared to IR20 seedlings exposed to 3 h drought stress. Physiologically, DD seedlings showed higher cell membrane stability and differential ABA accumulation in response to dehydration, coupled with rapid changes in gene expression. Detailed analyses of metabolic pathways enriched in expression data suggest interplay of ABA dependent along with secondary and redox metabolic networks that activate osmotic and detoxification signalling in DD. By co-localization of DEGs with QTLs from databases or published literature for physiological traits of DD and IR20, candidate genes were identified including those underlying major QTL qDTY(1.1) in DD. Further, we identified previously uncharacterized genes from both DD and IR20 under drought conditions including OsWRKY51, OsVP1 and confirmed their expression by qPCR in multiple rice cultivars. OsFBK1 was also functionally validated in susceptible PB1 rice cultivar and Arabidopsis for providing drought tolerance. Some of the DEGs mapped to the known QTLs could thus, be of potential significance for marker-assisted breeding. Nature Publishing Group 2017-02-09 /pmc/articles/PMC5299611/ /pubmed/28181537 http://dx.doi.org/10.1038/srep42131 Text en Copyright © 2017, The Author(s) http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/
spellingShingle Article
Borah, Pratikshya
Sharma, Eshan
Kaur, Amarjot
Chandel, Girish
Mohapatra, Trilochan
Kapoor, Sanjay
Khurana, Jitendra P.
Analysis of drought-responsive signalling network in two contrasting rice cultivars using transcriptome-based approach
title Analysis of drought-responsive signalling network in two contrasting rice cultivars using transcriptome-based approach
title_full Analysis of drought-responsive signalling network in two contrasting rice cultivars using transcriptome-based approach
title_fullStr Analysis of drought-responsive signalling network in two contrasting rice cultivars using transcriptome-based approach
title_full_unstemmed Analysis of drought-responsive signalling network in two contrasting rice cultivars using transcriptome-based approach
title_short Analysis of drought-responsive signalling network in two contrasting rice cultivars using transcriptome-based approach
title_sort analysis of drought-responsive signalling network in two contrasting rice cultivars using transcriptome-based approach
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5299611/
https://www.ncbi.nlm.nih.gov/pubmed/28181537
http://dx.doi.org/10.1038/srep42131
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