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BMC Genomics

, 9:519

First Online: 02 November 2008Received: 02 March 2008Accepted: 02 November 2008

Abstract

BackgroundProtein-protein interaction PPI maps are useful tools for investigating the cellular functions of genes. Thus far, large-scale PPI mapping projects have not been implemented for the rice blast fungus Magnaporthe grisea, which is responsible for the most severe rice disease. Inspired by recent advances in PPI prediction, we constructed a PPI map of this important fungus.

ResultsUsing a well-recognized interolog approach, we have predicted 11,674 interactions among 3,017 M. grisea proteins. Although the scale of the constructed map covers approximately only one-fourth of the M. grisea-s proteome, it is the first PPI map for this crucial organism and will therefore provide new insights into the functional genomics of the rice blast fungus. Focusing on the network topology of proteins encoded by known pathogenicity genes, we have found that pathogenicity proteins tend to interact with higher numbers of proteins. The pathogenicity proteins and their interacting partners in the entire network were then used to construct a subnet called a pathogenicity network. These data may provide further clues for the study of these pathogenicity proteins. Finally, it has been established that secreted proteins in M. grisea interact with fewer proteins. These secreted proteins and their interacting partners were also compiled into a network of secreted proteins, which may be helpful in constructing an interactome between the rice blast fungus and rice.

ConclusionWe predicted the PPIs of M. grisea and compiled them into a database server called MPID. It is hoped that MPID will provide new hints as to the functional genomics of this fungus. MPID is available at http:-bioinformatics.cau.edu.cn-zzd lab-MPID.html.

Electronic supplementary materialThe online version of this article doi:10.1186-1471-2164-9-519 contains supplementary material, which is available to authorized users.

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Autor: Fei He - Yan Zhang - Hao Chen - Ziding Zhang - You-Liang Peng

Fuente: https://link.springer.com/article/10.1186/1471-2164-9-519







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