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Genetic dissection of the biotic stress response using a genome-scale gene network for rice.

ABSTRACT: Rice is a staple food for one-half the world's population and a model for other monocotyledonous species. Thus, efficient approaches for identifying key genes controlling simple or complex traits in rice have important biological, agricultural, and economic consequences. Here, we report on the construction of RiceNet, an experimentally tested genome-scale gene network for a monocotyledonous species. Many different datasets, derived from five different organisms including plants, animals, yeast, and humans, were evaluated, and 24 of the most useful were integrated into a statistical framework that allowed for the prediction of functional linkages between pairs of genes. Genes could be linked to traits by using guilt-by-association, predicting gene attributes on the basis of network neighbors. We applied RiceNet to an important agronomic trait, the biotic stress response. Using network guilt-by-association followed by focused protein-protein interaction assays, we identified and validated, in planta, two positive regulators, LOC_Os01g70580 (now Regulator of XA21; ROX1) and LOC_Os02g21510 (ROX2), and one negative regulator, LOC_Os06g12530 (ROX3). These proteins control resistance mediated by rice XA21, a pattern recognition receptor. We also showed that RiceNet can accurately predict gene function in another major monocotyledonous crop species, maize. RiceNet thus enables the identification of genes regulating important crop traits, facilitating engineering of pathways critical to crop productivity.

SUBMITTER: Lee I

PROVIDER: S-EPMC3215029 | biostudies-literature | 2011 Nov

REPOSITORIES: biostudies-literature

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Genetic dissection of the biotic stress response using a genome-scale gene network for rice.

Lee Insuk I Seo Young-Su YS Coltrane Dusica D Hwang Sohyun S Oh Taeyun T Marcotte Edward M EM Ronald Pamela C PC

Proceedings of the National Academy of Sciences of the United States of America 20111031 45

Rice is a staple food for one-half the world's population and a model for other monocotyledonous species. Thus, efficient approaches for identifying key genes controlling simple or complex traits in rice have important biological, agricultural, and economic consequences. Here, we report on the construction of RiceNet, an experimentally tested genome-scale gene network for a monocotyledonous species. Many different datasets, derived from five different organisms including plants, animals, yeast, ...[more]

PMID: 22042862

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Project description:BackgroundFunctional annotations of large plant genome projects mostly provide information on gene function and gene families based on the presence of protein domains and gene homology, but not necessarily in association with gene expression or metabolic and regulatory networks. These additional annotations are necessary to understand the physiology, development and adaptation of a plant and its interaction with the environment.ResultsRiceCyc is a metabolic pathway networks database for rice. It is a snapshot of the substrates, metabolites, enzymes, reactions and pathways of primary and intermediary metabolism in rice. RiceCyc version 3.3 features 316 pathways and 6,643 peptide-coding genes mapped to 2,103 enzyme-catalyzed and 87 protein-mediated transport reactions. The initial functional annotations of rice genes with InterPro, Gene Ontology, MetaCyc, and Enzyme Commission (EC) numbers were enriched with annotations provided by KEGG and Gramene databases. The pathway inferences and the network diagrams were first predicted based on MetaCyc reference networks and plant pathways from the Plant Metabolic Network, using the Pathologic module of Pathway Tools. This was enriched by manually adding metabolic pathways and gene functions specifically reported for rice. The RiceCyc database is hierarchically browsable from pathway diagrams to the associated genes, metabolites and chemical structures. Through the integrated tool OMICs Viewer, users can upload transcriptomic, proteomic and metabolomic data to visualize expression patterns in a virtual cell. RiceCyc, along with additional species-specific pathway databases hosted in the Gramene project, facilitates comparative pathway analysis.ConclusionsHere we describe the RiceCyc network development and discuss its contribution to rice genome annotations. As a case study to demonstrate the use of RiceCyc network as a discovery environment we carried out an integrated bioinformatic analysis of rice metabolic genes that are differentially regulated under diurnal photoperiod and biotic stress treatments. The analysis of publicly available rice transcriptome datasets led to the hypothesis that the complete tryptophan biosynthesis and its dependent metabolic pathways including serotonin biosynthesis are induced by taxonomically diverse pathogens while also being under diurnal regulation. The RiceCyc database is available online for free access at http://www.gramene.org/pathway/.

Project description:The Flaviviridae are a family of viruses that cause severe human diseases. For example, dengue virus (DENV) is a rapidly emerging pathogen causing an estimated 100 million symptomatic infections annually worldwide. No approved antivirals are available to date and clinical trials with a tetravalent dengue vaccine showed disappointingly low protection rates. Hepatitis C virus (HCV) also remains a major medical problem, with 160 million chronically infected patients worldwide and only expensive treatments available. Despite distinct differences in their pathogenesis and modes of transmission, the two viruses share common replication strategies. A detailed understanding of the host functions that determine viral infection is lacking. Here we use a pooled CRISPR genetic screening strategy to comprehensively dissect host factors required for these two highly important Flaviviridae members. For DENV, we identified endoplasmic-reticulum (ER)-associated multi-protein complexes involved in signal sequence recognition, N-linked glycosylation and ER-associated degradation. DENV replication was nearly completely abrogated in cells deficient in the oligosaccharyltransferase (OST) complex. Mechanistic studies pinpointed viral RNA replication and not entry or translation as the crucial step requiring the OST complex. Moreover, we show that viral non-structural proteins bind to the OST complex. The identified ER-associated protein complexes were also important for infection by other mosquito-borne flaviviruses including Zika virus, an emerging pathogen causing severe birth defects. By contrast, the most significant genes identified in the HCV screen were distinct and included viral receptors, RNA-binding proteins and enzymes involved in metabolism. We found an unexpected link between intracellular flavin adenine dinucleotide (FAD) levels and HCV replication. This study shows notable divergence in host-depenency factors between DENV and HCV, and illuminates new host targets for antiviral therapy.

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Genetic dissection of the biotic stress response using a genome-scale gene network for rice.

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Genetic dissection of the biotic stress response using a genome-scale gene network for rice.

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