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Prediction of cassava protein interactome based on interolog method
Ratana Thanasomboon1,2, Saowalak Kalapanulak2,3, Supatcharee Netrphan4
1Biological Engineering Program, Faculty of Engineering, King Mongkut's University of Technology Thonburi, Bangkok, 10140, Thailand.
Scientific Reports
|December 10, 2017
Summary
Researchers mapped cassava
Area of Science:
- Plant biology
- Genomics
- Bioinformatics
Background:
- Cassava is a vital food security crop with growing industrial demand.
- Understanding cellular regulation, particularly protein-protein interactions (PPIs), is crucial but underexplored in cassava.
- A knowledge gap exists in cassava's protein-protein interaction landscape.
Purpose of the Study:
- To construct a genome-scale protein-protein interaction (PPI) network for cassava.
- To reduce the knowledge gap in cassava's cellular regulatory mechanisms.
- To provide a resource for understanding cassava's biological functions and trait improvement.
Main Methods:
- Utilized an interolog-based method (MePPI-In) using data from seven template plants.
- Constructed a network comprising 90,173 interactions among 7,209 proteins.
- Integrated gene/protein expression data and domain-domain interaction information to enhance network reliability.
Main Results:
- Generated the MePPI-In network, a comprehensive resource for cassava PPIs.
- 39% of predicted interactions were supported by gene/protein expression data.
- Identified 16 highly promising PPIs through co-expression analysis.
- Cassava's network topology and function were comparable to Arabidopsis and rice.
Conclusions:
- The MePPI-In network offers valuable insights into cassava's cellular regulation.
- This resource can aid in understanding protein complex formation and predicting protein function.
- MePPI-In facilitates precise trait improvement strategies for cassava.
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