Using ortholog information from multiple species to predict barley protein-protein interaction network

Abstract

Barley (Hordeum vulgare) is one of the most important crops worldwide; however, the information on protein level and, especially, protein-protein interaction datasets of barley is still lacking. Although there are several reports on protein expression for some model organisms under the conditions of interest, the progress of protein-protein interaction detection in plants is rather slow. Here, we present the first predicted protein-protein interaction network of barley by applying interolog method and using available interactome data and evolutionary information from a variety of species (272 organisms). The final predicted barley protein-protein interaction network contained 9530 proteins with 313,191 interactions. The quality of our network was evaluated using the GO annotation. We hope that the predicted barley interactome will help to better understand signal transduction pathways and facilitate the identification of new proteins involved in a special process. Furthermore, the availability of the barley protein-protein interaction network can boost the knowledge of protein level and help to breed barley crops.