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Computational analysis of microarray data of Arabidopsis thaliana challenged with Alternaria brassicicola for identification of key genes in Brassica

BACKGROUND: Alternaria blight, a recalcitrant disease caused by Alternaria brassicae and Alternaria brassicicola, has been recognized for significant losses of oilseed crops especially rapeseed-mustard throughout the world. Till date, no resistance source is available against the disease; hence, pla...

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Autores principales: Pathak, Rajesh Kumar, Baunthiyal, Mamta, Pandey, Dinesh, Kumar, Anil
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7326868/
https://www.ncbi.nlm.nih.gov/pubmed/32607787
http://dx.doi.org/10.1186/s43141-020-00032-y
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author Pathak, Rajesh Kumar
Baunthiyal, Mamta
Pandey, Dinesh
Kumar, Anil
author_facet Pathak, Rajesh Kumar
Baunthiyal, Mamta
Pandey, Dinesh
Kumar, Anil
author_sort Pathak, Rajesh Kumar
collection PubMed
description BACKGROUND: Alternaria blight, a recalcitrant disease caused by Alternaria brassicae and Alternaria brassicicola, has been recognized for significant losses of oilseed crops especially rapeseed-mustard throughout the world. Till date, no resistance source is available against the disease; hence, plant breeding methods cannot be used to develop disease-resistant varieties. Therefore, in the present study, efforts have been made to identify resistance and defense-related genes as well as key components of JA-SA-ET-mediated pathway involved in resistance against Alternaria brasscicola through computational analysis of microarray data and network biology approach. Microarray profiling data from wild type and mutant Arabidopsis plants challenged with Alternaria brassicicola along with control plant were obtained from the Gene Expression Omnibus (GEO) database. The data analysis, including DEGs extraction, functional enrichment, annotation, and network analysis, was used to identify genes associated with disease resistance and defense response. RESULTS: A total of 2854 genes were differentially expressed in WT9C9; among them, 1327 genes were upregulated and 1527 genes were downregulated. A total of 1159 genes were differentially expressed in JAM9C9; among them, 809 were upregulated and 350 were downregulated. A total of 2516 genes were differentially expressed in SAM9C9; among them, 1355 were upregulated and 1161 were downregulated. A total of 1567 genes were differentially expressed in ETM9C9; among them, 917 were upregulated and 650 were downregulated. Besides, a total of 2965 genes were differentially expressed in contrast WT24C24; among them, 1510 genes were upregulated and 1455 genes were downregulated. A total of 4598 genes were differentially expressed in JAM24C24; among them, 2201 were upregulated and 2397 were downregulated. A total of 3803 genes were differentially expressed in SAM24C24; among them, 1819 were upregulated and 1984 were downregulated. A total of 4164 genes were differentially expressed in ETM24C24; among them, 1895 were upregulated and 2269 were downregulated. The upregulated genes of Arabidopsis thaliana were mapped and annotated with CDS sequences of Brassica rapa obtained from PlantGDB database. Additionally, PPI network of these genes were constructed to investigate the key components of hormone-mediated pathway involved in resistance during pathogenesis. CONCLUSION: The obtained information from present study can be used to engineer resistance to Alternaria blight caused by Alternaria brasscicola through molecular breeding or genetic manipulation-based approaches for improving Brassica oilseed productivity.
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spelling pubmed-73268682020-07-07 Computational analysis of microarray data of Arabidopsis thaliana challenged with Alternaria brassicicola for identification of key genes in Brassica Pathak, Rajesh Kumar Baunthiyal, Mamta Pandey, Dinesh Kumar, Anil J Genet Eng Biotechnol Research BACKGROUND: Alternaria blight, a recalcitrant disease caused by Alternaria brassicae and Alternaria brassicicola, has been recognized for significant losses of oilseed crops especially rapeseed-mustard throughout the world. Till date, no resistance source is available against the disease; hence, plant breeding methods cannot be used to develop disease-resistant varieties. Therefore, in the present study, efforts have been made to identify resistance and defense-related genes as well as key components of JA-SA-ET-mediated pathway involved in resistance against Alternaria brasscicola through computational analysis of microarray data and network biology approach. Microarray profiling data from wild type and mutant Arabidopsis plants challenged with Alternaria brassicicola along with control plant were obtained from the Gene Expression Omnibus (GEO) database. The data analysis, including DEGs extraction, functional enrichment, annotation, and network analysis, was used to identify genes associated with disease resistance and defense response. RESULTS: A total of 2854 genes were differentially expressed in WT9C9; among them, 1327 genes were upregulated and 1527 genes were downregulated. A total of 1159 genes were differentially expressed in JAM9C9; among them, 809 were upregulated and 350 were downregulated. A total of 2516 genes were differentially expressed in SAM9C9; among them, 1355 were upregulated and 1161 were downregulated. A total of 1567 genes were differentially expressed in ETM9C9; among them, 917 were upregulated and 650 were downregulated. Besides, a total of 2965 genes were differentially expressed in contrast WT24C24; among them, 1510 genes were upregulated and 1455 genes were downregulated. A total of 4598 genes were differentially expressed in JAM24C24; among them, 2201 were upregulated and 2397 were downregulated. A total of 3803 genes were differentially expressed in SAM24C24; among them, 1819 were upregulated and 1984 were downregulated. A total of 4164 genes were differentially expressed in ETM24C24; among them, 1895 were upregulated and 2269 were downregulated. The upregulated genes of Arabidopsis thaliana were mapped and annotated with CDS sequences of Brassica rapa obtained from PlantGDB database. Additionally, PPI network of these genes were constructed to investigate the key components of hormone-mediated pathway involved in resistance during pathogenesis. CONCLUSION: The obtained information from present study can be used to engineer resistance to Alternaria blight caused by Alternaria brasscicola through molecular breeding or genetic manipulation-based approaches for improving Brassica oilseed productivity. Springer Berlin Heidelberg 2020-07-01 /pmc/articles/PMC7326868/ /pubmed/32607787 http://dx.doi.org/10.1186/s43141-020-00032-y 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
Pathak, Rajesh Kumar
Baunthiyal, Mamta
Pandey, Dinesh
Kumar, Anil
Computational analysis of microarray data of Arabidopsis thaliana challenged with Alternaria brassicicola for identification of key genes in Brassica
title Computational analysis of microarray data of Arabidopsis thaliana challenged with Alternaria brassicicola for identification of key genes in Brassica
title_full Computational analysis of microarray data of Arabidopsis thaliana challenged with Alternaria brassicicola for identification of key genes in Brassica
title_fullStr Computational analysis of microarray data of Arabidopsis thaliana challenged with Alternaria brassicicola for identification of key genes in Brassica
title_full_unstemmed Computational analysis of microarray data of Arabidopsis thaliana challenged with Alternaria brassicicola for identification of key genes in Brassica
title_short Computational analysis of microarray data of Arabidopsis thaliana challenged with Alternaria brassicicola for identification of key genes in Brassica
title_sort computational analysis of microarray data of arabidopsis thaliana challenged with alternaria brassicicola for identification of key genes in brassica
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7326868/
https://www.ncbi.nlm.nih.gov/pubmed/32607787
http://dx.doi.org/10.1186/s43141-020-00032-y
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