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Prediction of cassava protein interactome based on interolog method
Cassava is a starchy root crop whose role in food security becomes more significant nowadays. Together with the industrial uses for versatile purposes, demand for cassava starch is continuously growing. However, in-depth study to uncover the mystery of cellular regulation, especially the interaction...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5722940/ https://www.ncbi.nlm.nih.gov/pubmed/29222529 http://dx.doi.org/10.1038/s41598-017-17633-2 |
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author | Thanasomboon, Ratana Kalapanulak, Saowalak Netrphan, Supatcharee Saithong, Treenut |
author_facet | Thanasomboon, Ratana Kalapanulak, Saowalak Netrphan, Supatcharee Saithong, Treenut |
author_sort | Thanasomboon, Ratana |
collection | PubMed |
description | Cassava is a starchy root crop whose role in food security becomes more significant nowadays. Together with the industrial uses for versatile purposes, demand for cassava starch is continuously growing. However, in-depth study to uncover the mystery of cellular regulation, especially the interaction between proteins, is lacking. To reduce the knowledge gap in protein-protein interaction (PPI), genome-scale PPI network of cassava was constructed using interolog-based method (MePPI-In, available at http://bml.sbi.kmutt.ac.th/ppi). The network was constructed from the information of seven template plants. The MePPI-In included 90,173 interactions from 7,209 proteins. At least, 39 percent of the total predictions were found with supports from gene/protein expression data, while further co-expression analysis yielded 16 highly promising PPIs. In addition, domain-domain interaction information was employed to increase reliability of the network and guide the search for more groups of promising PPIs. Moreover, the topology and functional content of MePPI-In was similar to the networks of Arabidopsis and rice. The potential contribution of MePPI-In for various applications, such as protein-complex formation and prediction of protein function, was discussed and exemplified. The insights provided by our MePPI-In would hopefully enable us to pursue precise trait improvement in cassava. |
format | Online Article Text |
id | pubmed-5722940 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-57229402017-12-12 Prediction of cassava protein interactome based on interolog method Thanasomboon, Ratana Kalapanulak, Saowalak Netrphan, Supatcharee Saithong, Treenut Sci Rep Article Cassava is a starchy root crop whose role in food security becomes more significant nowadays. Together with the industrial uses for versatile purposes, demand for cassava starch is continuously growing. However, in-depth study to uncover the mystery of cellular regulation, especially the interaction between proteins, is lacking. To reduce the knowledge gap in protein-protein interaction (PPI), genome-scale PPI network of cassava was constructed using interolog-based method (MePPI-In, available at http://bml.sbi.kmutt.ac.th/ppi). The network was constructed from the information of seven template plants. The MePPI-In included 90,173 interactions from 7,209 proteins. At least, 39 percent of the total predictions were found with supports from gene/protein expression data, while further co-expression analysis yielded 16 highly promising PPIs. In addition, domain-domain interaction information was employed to increase reliability of the network and guide the search for more groups of promising PPIs. Moreover, the topology and functional content of MePPI-In was similar to the networks of Arabidopsis and rice. The potential contribution of MePPI-In for various applications, such as protein-complex formation and prediction of protein function, was discussed and exemplified. The insights provided by our MePPI-In would hopefully enable us to pursue precise trait improvement in cassava. Nature Publishing Group UK 2017-12-08 /pmc/articles/PMC5722940/ /pubmed/29222529 http://dx.doi.org/10.1038/s41598-017-17633-2 Text en © The Author(s) 2017 Open Access This 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Thanasomboon, Ratana Kalapanulak, Saowalak Netrphan, Supatcharee Saithong, Treenut Prediction of cassava protein interactome based on interolog method |
title | Prediction of cassava protein interactome based on interolog method |
title_full | Prediction of cassava protein interactome based on interolog method |
title_fullStr | Prediction of cassava protein interactome based on interolog method |
title_full_unstemmed | Prediction of cassava protein interactome based on interolog method |
title_short | Prediction of cassava protein interactome based on interolog method |
title_sort | prediction of cassava protein interactome based on interolog method |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5722940/ https://www.ncbi.nlm.nih.gov/pubmed/29222529 http://dx.doi.org/10.1038/s41598-017-17633-2 |
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