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In silico modelling and characterization of eight blast resistance proteins in resistant and susceptible rice cultivars

BACKGROUND: Nucleotide-binding site-leucine-rich repeat (NBS-LRR) resistance genes are the largest class of plant resistance genes which play an important role in the plant defense response. These genes are better conserved than others and function as a recognition-based immune system in plants thro...

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Autores principales: Chandrakanth, R., Sunil, L., Sadashivaiah, L., Devaki, N. S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7688789/
https://www.ncbi.nlm.nih.gov/pubmed/33237489
http://dx.doi.org/10.1186/s43141-020-00076-0
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author Chandrakanth, R.
Sunil, L.
Sadashivaiah, L.
Devaki, N. S.
author_facet Chandrakanth, R.
Sunil, L.
Sadashivaiah, L.
Devaki, N. S.
author_sort Chandrakanth, R.
collection PubMed
description BACKGROUND: Nucleotide-binding site-leucine-rich repeat (NBS-LRR) resistance genes are the largest class of plant resistance genes which play an important role in the plant defense response. These genes are better conserved than others and function as a recognition-based immune system in plants through their encoded proteins. RESULTS: Here, we report the effect of Magnaporthe oryzae, the rice blast pathogen inoculation in resistant BR2655 and susceptible HR12 rice cultivars. Transcriptomic profiling was carried out to analyze differential gene expression in these two cultivars. A total of eight NBS-LRR uncharacterized resistance proteins (RP1, RP2, RP3, RP4, RP5, RP6, RP7, and RP8) were selected in these two cultivars for in silico modeling. Modeller 9.22 and SWISS-MODEL servers were used for the homology modeling of eight RPs. ProFunc server was utilized for the prediction of secondary structure and function. The CDvist Web server and Interpro scan server detected the motif and domains in eight RPs. Ramachandran plot of eight RPs confirmed that the modeled structures occupied favorable positions. CONCLUSIONS: From the present study, computational analysis of these eight RPs may afford insights into their role, function, and valuable resource for studying the intricate details of the plant defense mechanism. Furthermore, the identification of resistance proteins is useful for the development of molecular markers linked to resistance genes. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s43141-020-00076-0.
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spelling pubmed-76887892020-12-09 In silico modelling and characterization of eight blast resistance proteins in resistant and susceptible rice cultivars Chandrakanth, R. Sunil, L. Sadashivaiah, L. Devaki, N. S. J Genet Eng Biotechnol Research BACKGROUND: Nucleotide-binding site-leucine-rich repeat (NBS-LRR) resistance genes are the largest class of plant resistance genes which play an important role in the plant defense response. These genes are better conserved than others and function as a recognition-based immune system in plants through their encoded proteins. RESULTS: Here, we report the effect of Magnaporthe oryzae, the rice blast pathogen inoculation in resistant BR2655 and susceptible HR12 rice cultivars. Transcriptomic profiling was carried out to analyze differential gene expression in these two cultivars. A total of eight NBS-LRR uncharacterized resistance proteins (RP1, RP2, RP3, RP4, RP5, RP6, RP7, and RP8) were selected in these two cultivars for in silico modeling. Modeller 9.22 and SWISS-MODEL servers were used for the homology modeling of eight RPs. ProFunc server was utilized for the prediction of secondary structure and function. The CDvist Web server and Interpro scan server detected the motif and domains in eight RPs. Ramachandran plot of eight RPs confirmed that the modeled structures occupied favorable positions. CONCLUSIONS: From the present study, computational analysis of these eight RPs may afford insights into their role, function, and valuable resource for studying the intricate details of the plant defense mechanism. Furthermore, the identification of resistance proteins is useful for the development of molecular markers linked to resistance genes. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s43141-020-00076-0. Springer Berlin Heidelberg 2020-11-25 /pmc/articles/PMC7688789/ /pubmed/33237489 http://dx.doi.org/10.1186/s43141-020-00076-0 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 Research
Chandrakanth, R.
Sunil, L.
Sadashivaiah, L.
Devaki, N. S.
In silico modelling and characterization of eight blast resistance proteins in resistant and susceptible rice cultivars
title In silico modelling and characterization of eight blast resistance proteins in resistant and susceptible rice cultivars
title_full In silico modelling and characterization of eight blast resistance proteins in resistant and susceptible rice cultivars
title_fullStr In silico modelling and characterization of eight blast resistance proteins in resistant and susceptible rice cultivars
title_full_unstemmed In silico modelling and characterization of eight blast resistance proteins in resistant and susceptible rice cultivars
title_short In silico modelling and characterization of eight blast resistance proteins in resistant and susceptible rice cultivars
title_sort in silico modelling and characterization of eight blast resistance proteins in resistant and susceptible rice cultivars
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7688789/
https://www.ncbi.nlm.nih.gov/pubmed/33237489
http://dx.doi.org/10.1186/s43141-020-00076-0
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