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An Integrated Approach of Proteomics and Computational Genetic Modification Effectiveness Analysis to Uncover the Mechanisms of Flood Tolerance in Soybeans
Flooding negatively affects the growth of soybeans. Recently, omic approaches have been used to study abiotic stress responses in plants. To explore flood-tolerant genes in soybeans, an integrated approach of proteomics and computational genetic modification effectiveness analysis was applied to the...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5983631/ https://www.ncbi.nlm.nih.gov/pubmed/29701710 http://dx.doi.org/10.3390/ijms19051301 |
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author | Wang, Xin Sakata, Katsumi Komatsu, Setsuko |
author_facet | Wang, Xin Sakata, Katsumi Komatsu, Setsuko |
author_sort | Wang, Xin |
collection | PubMed |
description | Flooding negatively affects the growth of soybeans. Recently, omic approaches have been used to study abiotic stress responses in plants. To explore flood-tolerant genes in soybeans, an integrated approach of proteomics and computational genetic modification effectiveness analysis was applied to the soybean (Glycine max L. (Merrill)). Flood-tolerant mutant and abscisic acid (ABA)-treated soybean plants were used as the flood-tolerant materials. Among the primary metabolism, glycolysis, fermentation, and tricarboxylic acid cycle were markedly affected under flooding. Fifteen proteins, which were related to the affected processes, displayed similar protein profiles in the mutant and ABA-treated soybean plants. Protein levels of glyceraldehyde-3-phosphate dehydrogenase (GAPDH), aconitase 1, and 2-oxoglutarate dehydrogenase were higher in flood-tolerant materials than in wild-type soybean plants under flood conditions. These three proteins were positioned in each of the three enzyme groups revealed by our computational genetic modification effectiveness analysis, and the three proteins configured a candidate set of genes to promote flood tolerance. Additionally, transcript levels of GAPDH were similar in flood-tolerant materials and in unstressed plants. These results suggest that proteins related to energy metabolism might play an essential role to confer flood tolerance in soybeans. |
format | Online Article Text |
id | pubmed-5983631 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-59836312018-06-05 An Integrated Approach of Proteomics and Computational Genetic Modification Effectiveness Analysis to Uncover the Mechanisms of Flood Tolerance in Soybeans Wang, Xin Sakata, Katsumi Komatsu, Setsuko Int J Mol Sci Article Flooding negatively affects the growth of soybeans. Recently, omic approaches have been used to study abiotic stress responses in plants. To explore flood-tolerant genes in soybeans, an integrated approach of proteomics and computational genetic modification effectiveness analysis was applied to the soybean (Glycine max L. (Merrill)). Flood-tolerant mutant and abscisic acid (ABA)-treated soybean plants were used as the flood-tolerant materials. Among the primary metabolism, glycolysis, fermentation, and tricarboxylic acid cycle were markedly affected under flooding. Fifteen proteins, which were related to the affected processes, displayed similar protein profiles in the mutant and ABA-treated soybean plants. Protein levels of glyceraldehyde-3-phosphate dehydrogenase (GAPDH), aconitase 1, and 2-oxoglutarate dehydrogenase were higher in flood-tolerant materials than in wild-type soybean plants under flood conditions. These three proteins were positioned in each of the three enzyme groups revealed by our computational genetic modification effectiveness analysis, and the three proteins configured a candidate set of genes to promote flood tolerance. Additionally, transcript levels of GAPDH were similar in flood-tolerant materials and in unstressed plants. These results suggest that proteins related to energy metabolism might play an essential role to confer flood tolerance in soybeans. MDPI 2018-04-26 /pmc/articles/PMC5983631/ /pubmed/29701710 http://dx.doi.org/10.3390/ijms19051301 Text en © 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Wang, Xin Sakata, Katsumi Komatsu, Setsuko An Integrated Approach of Proteomics and Computational Genetic Modification Effectiveness Analysis to Uncover the Mechanisms of Flood Tolerance in Soybeans |
title | An Integrated Approach of Proteomics and Computational Genetic Modification Effectiveness Analysis to Uncover the Mechanisms of Flood Tolerance in Soybeans |
title_full | An Integrated Approach of Proteomics and Computational Genetic Modification Effectiveness Analysis to Uncover the Mechanisms of Flood Tolerance in Soybeans |
title_fullStr | An Integrated Approach of Proteomics and Computational Genetic Modification Effectiveness Analysis to Uncover the Mechanisms of Flood Tolerance in Soybeans |
title_full_unstemmed | An Integrated Approach of Proteomics and Computational Genetic Modification Effectiveness Analysis to Uncover the Mechanisms of Flood Tolerance in Soybeans |
title_short | An Integrated Approach of Proteomics and Computational Genetic Modification Effectiveness Analysis to Uncover the Mechanisms of Flood Tolerance in Soybeans |
title_sort | integrated approach of proteomics and computational genetic modification effectiveness analysis to uncover the mechanisms of flood tolerance in soybeans |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5983631/ https://www.ncbi.nlm.nih.gov/pubmed/29701710 http://dx.doi.org/10.3390/ijms19051301 |
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