Prediction of cassava protein interactome based on interolog method
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Author list: Thanasomboon R., Kalapanulak S., Netrphan S., Saithong T.
Publisher: Nature Research
Publication year: 2017
Journal: Scientific Reports (2045-2322)
Volume number: 7
Issue number: 1
ISSN: 2045-2322
eISSN: 2045-2322
Languages: English-Great Britain (EN-GB)
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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), 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. ฉ 2017 The Author(s).
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