Dataset Information

Prediction and functional analysis of the sweet orange protein-protein interaction network.

ABSTRACT:

Background

Sweet orange (Citrus sinensis) is one of the most important fruits world-wide. Because it is a woody plant with a long growth cycle, genetic studies of sweet orange are lagging behind those of other species.

Results

In this analysis, we employed ortholog identification and domain combination methods to predict the protein-protein interaction (PPI) network for sweet orange. The K-nearest neighbors (KNN) classification method was used to verify and filter the network. The final predicted PPI network, CitrusNet, contained 8,195 proteins with 124,491 interactions. The quality of CitrusNet was evaluated using gene ontology (GO) and Mapman annotations, which confirmed the reliability of the network. In addition, we calculated the expression difference of interacting genes (EDI) in CitrusNet using RNA-seq data from four sweet orange tissues, and also analyzed the EDI distribution and variation in different sub-networks.

Conclusions

Gene expression in CitrusNet has significant modular features. Target of rapamycin (TOR) protein served as the central node of the hormone-signaling sub-network. All evidence supported the idea that TOR can integrate various hormone signals and affect plant growth. CitrusNet provides valuable resources for the study of biological functions in sweet orange.

SUBMITTER: Ding YD

PROVIDER: S-EPMC4236729 | biostudies-literature | 2014 Aug

REPOSITORIES: biostudies-literature

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Publications

Prediction and functional analysis of the sweet orange protein-protein interaction network.

Ding Yu-Duan YD Chang Ji-Wei JW Guo Jing J Chen Dijun D Li Sen S Xu Qiang Q Deng Xiu-Xin XX Cheng Yun-Jiang YJ Chen Ling-Ling LL

BMC plant biology 20140805

<h4>Background</h4>Sweet orange (Citrus sinensis) is one of the most important fruits world-wide. Because it is a woody plant with a long growth cycle, genetic studies of sweet orange are lagging behind those of other species.<h4>Results</h4>In this analysis, we employed ortholog identification and domain combination methods to predict the protein-protein interaction (PPI) network for sweet orange. The K-nearest neighbors (KNN) classification method was used to verify and filter the network. The ...[more]

PMID: 25091279

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Project description:We have used the citrus GeneChip array (GPL5731) to survey the transcription profiles of sweet orange in response to the bacterial pathogens Xanthomonas axonopodis pv. citri (Xac) and Xanthomonas axonopodis pv. aurantifolii (Xaa). Xac is the causal agent of the citrus canker disease on a wide range of citrus species, including sweet oranges (Citrus sinensis). On the other hand, Xaa is pathogenic to Mexican lime (Citrus aurantifolia) only, and in sweet orange it triggers a defense response. In order to identify the genes induced during the defense response (Xaa-responsive genes) or citrus canker development (Xac-responsive genes), we conducted microarrays hybridization experiments at 6 and 48 hours after bacterial infiltration (habi). The analysis revealed that genes commonly modulated by Xac and Xaa are associated with basal defenses normally triggered by pathogen-associated molecular patterns, including those involved in reactive oxygen species production and lignification. Significantly, Xac-infected leaves showed considerable changes in the transcriptional profiles of defense-, cell wall-, vesicle trafficking- and cell growth-related genes between 6 and 48 habi. This is consistent with the notion that Xac suppresses host defenses near the beginning of the infection and simultaneously changes the physiological status of the host to promote cell enlargement and division. Finally, Xaa triggered a MAP kinase signaling pathway involving WRKY and ethylene-responsive transcriptional factors known to activate downstream defense genes. Keywords: Comprehensive transcriptional analysis of the Citrus-Xanthomonas interaction Adult leaves of sweet orange were infiltrated with the bacterial suspensions or water (mock control). Two stages were selected after bacterial infiltration for RNA extraction and hybridization on Affymetrix microarrays. In total, these experiments consist of two biological replicates of six samples: water-infiltrated leaves, Xaa-infiltrated leaves and Xac-infiltrated leaves, at both 6 and 48 (habi).

Dataset Information

Prediction and functional analysis of the sweet orange protein-protein interaction network.

Background

Results

Conclusions

Publications

Prediction and functional analysis of the sweet orange protein-protein interaction network.

Similar Datasets

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