PIPE4: Ultra-Fast PPI prediction for comprehensive Inter- and Cross- species interactomes

Citation

Bahram Samanfar, Kevin Dick, Brad Barnes, Elroy Cober, Stephen Molnar, Frank Dehne, Ashkan Golshani, James Green: PIPE4: Ultra-Fast PPI prediction for comprehensive Inter- and Cross- species interactomes. Plant and Animal Genome (PAG) 2019, San Diego, USA.

Abstract

Soybean is one of the major Canadian grain crops and its production is expanding in Canada. In particular, the majority of the increase is in short season areas (Western Canada and Northern Regions) where the Soybean Cyst Nematode (SCN) is an emerging issue.
The Protein-protein Interaction Prediction Engine (PIPE) is a highly efficient sequence-based computational tool used to predict protein-protein interactions (PPI) in many organisms, including soybean. PPIs are essential molecular interactions that define the biology of a cell, its development and its responses to various stimuli. Theoretically, if a gene interacts with groups of genes involved in one specific pathway, that gene might also be involved in that specific pathway (“guilt by association”). Our knowledge of global PPI networks in complex organisms such as human and plants is restricted by technical limitations of current methods.
The need for larger-scale and increasingly complex PPI prediction tasks demands that state-of-the-art predictors be highly efficient and adapted to inter- and cross-species predictions. Here, PIPE4 was used to predict the comprehensive interactomes for two prediction schemas: 1) cross-species predictions, where Arabidopsis thaliana is used as a proxy to predict the first comprehensive Glycine max interactome; and 2) a combined schema involving both cross- and inter-species predictions, where both Arabidopsis thaliana and Caenorhabditis elegans are used as proxy species to predict the interactome between Glycine max (the soybean legume) and Heterodera glycines (SCN).
With increasingly accurate and efficient PPI predictors applicable to complex prediction schemas, researchers can now generate comprehensive interactomes that were originally prohibitive. For example, generating the H. glycines-G. max interactome can offer unprecedented insight into the molecular mechanisms between these species, generating novel therapeutic leads related to the host-pathogen interactions. These interactomes may have far-reaching agricultural and economic impact for diverse goals including Molecular Breeding and Marker Assisted Selection.

Publication date

2019-01-11