PRIN: a predicted rice interactome network

Abstract

BackgroundProtein-protein interactions play a fundamental role in elucidating the molecular mechanisms of biomolecular function, signal transductions and metabolic pathways of living organisms. Although high-throughput technologies such as yeast two-hybrid system and affinity purification followed by mass spectrometry are widely used in model organisms, the progress of protein-protein interactions detection in plants is rather slow. With this motivation, our work presents a computational approach to predict protein-protein interactions in Oryza sativa.ResultsTo better understand the interactions of proteins in Oryza sativa, we have developed PRIN, a Predicted Rice Interactome Network. Protein-protein interaction data of PRIN are based on the interologs of six model organisms where large-scale protein-protein interaction experiments have been applied: yeast (Saccharomyces cerevisiae), worm (Caenorhabditis elegans), fruit fly (Drosophila melanogaster), human (Homo sapiens), Escherichia coli K12 and Arabidopsis thaliana. With certain quality controls, altogether we obtained 76,585 non-redundant rice protein interaction pairs among 5,049 rice proteins. Further analysis showed that the topology properties of predicted rice protein interaction network are more similar to yeast than to the other 5 organisms. This may not be surprising as the interologs based on yeast contribute nearly 74% of total interactions. In addition, GO annotation, subcellular localization information and gene expression data are also mapped to our network for validation. Finally, a user-friendly web interface was developed to offer convenient database search and network visualization.ConclusionsPRIN is the first well annotated protein interaction database for the important model plant Oryza sativa. It has greatly extended the current available protein-protein interaction data of rice with a computational approach, which will certainly provide further insights into rice functional genomics and systems biology.PRIN is available online at http://bis.zju.edu.cn/prin/.

Cross-Species Network Analysis Uncovers Conserved Nitrogen-Regulated Network Modules in Rice

“…The N-regulated gene network includes expression data generated in this study and metabolic and protein-protein interactions from publicly available rice data (Rohila et al, 2006(Rohila et al, , 2009Ding et al, 2009;Gu et al, 2011;Dharmawardhana et al, 2013). Despite the fact that much of the genomic and systemic rice data have been generated over the past years, a lot of information is still missing.…”

“…For example, Arabidopsis has much more experimental data with regard to cis-binding sites and protein-protein interaction. To fill these gaps in rice network knowledge, we integrated orthology-based Arabidopsis interaction data (Palaniswamy et al, 2006;Yilmaz et al, 2009;Gu et al, 2011;Ho et al, 2012) and searched for functional Arabidopsis cis-binding sites in rice, to identify N-regulatory network modules and biological processes (network biomodules) conserved between dicots and monocots.…”

Techniques for the analysis of protein-protein interactions in vivo

“…There are a number of online resources where interactome data can be accessed (Table Box I ;Szklarczyk and Jensen, 2015). For example, the interactomes of Arabidopsis (Geisler-Lee et al, 2007;Lee et al, 2015), rice (Oryza sativa; Gu et al, 2011;Sapkota et al, 2011), and maize (Zea mays; Zhu et al, 2016) have been assembled through prediction algorithms and experimental evidence or a combination of the two.…”

A Survey on Evolutionary Analysis in PPI Networks

“…This multidimensional character of interolog inference has been extensively used to predict and build databases of the whole interactome for various species, either as a stand alone approach or in combination with other in silico methods, which often integrate multiple data types including the gene co-expression, co-localization, functional category, the occurrence of orthologs and other genomic context methods. In this way researchers could provide, for instance, the first sketch of human interactome (Lehner & Fraser, 2004), build the interactome of plants (Geisler- Lee et al, 2007;Gu et al, 2011), and improve the understanding of processes in a malarial parasite (Pavithra et al, 2007) or in cancer (Jonsson & Bates, 2006). Also, three, up-to-date, tools have been recently implemented and made available to perform this inference task (Gallone et al, 2011;Michaut et al, 2008;Pedamallu & Posfai, 2010).…”