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Prediction of cassava protein interactome based on interolog method
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Document Title
Prediction of cassava protein interactome based on interolog method
Author
Thanasomboon R, Kalapanulak S, Netrphan S, Saithong T
Name from Authors Collection
Affiliations
King Mongkuts University of Technology Thonburi; King Mongkuts University of Technology Thonburi; King Mongkuts University of Technology Thonburi; National Science & Technology Development Agency - Thailand; National Center Genetic Engineering & Biotechnology (BIOTEC)
Type
Article
Source Title
SCIENTIFIC REPORTS
ISSN
2045-2322
Year
2017
Volume
7
Page
-
Open Access
Green Published, gold
Publisher
NATURE PORTFOLIO
DOI
10.1038/s41598-017-17633-2
Format
Abstract
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), genomescale 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.
Industrial Classification
Knowledge Taxonomy Level 1
Knowledge Taxonomy Level 2
Funding Sponsor
National Center for Genetic Engineering and Biotechnology (BIOTEC, NSTDA); National Research Council of Thailand (NRCT); National Science and Technology Development Agency (NSTDA) under Thailand Research Organizations Network [P-13-50437, P-16-51275]
License
CC-BY
Rights
Authors
Publication Source
WOS