Construction and comparison of gene co-expression networks shows complex plant immune responses

Gene co-expression networks (GCNs) are graphic representations that depict the coordinated transcription of genes in response to certain stimuli. GCNs provide functional annotations of genes whose function is unknown and are further used in studies of translational functional genomics among species....

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Bibliographic Details
Published in:PeerJ (San Francisco, CA) CA), 2014-10, Vol.2, p.e610-e610
Main Authors: Leal, Luis Guillermo, López, Camilo, López-Kleine, Liliana
Format: Article
Language:English
Subjects:
Analysis
Arabidopsis
Arabidopsis thaliana
Bioinformatics
Biology
Computational Biology
Gene co-expression networks
Gene expression
Genes
Genetic aspects
Genomes
Genomics
Immune response
Kinases
Multivariate analysis
Networks comparison
Oryza
Plant immunity
Principal Component Analysis
Proteins
Similarity measures
Similarity threshold
Software
Soybeans
Statistical methods
Statistics
Studies
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Summary:Gene co-expression networks (GCNs) are graphic representations that depict the coordinated transcription of genes in response to certain stimuli. GCNs provide functional annotations of genes whose function is unknown and are further used in studies of translational functional genomics among species. In this work, a methodology for the reconstruction and comparison of GCNs is presented. This approach was applied using gene expression data that were obtained from immunity experiments in Arabidopsis thaliana, rice, soybean, tomato and cassava. After the evaluation of diverse similarity metrics for the GCN reconstruction, we recommended the mutual information coefficient measurement and a clustering coefficient-based method for similarity threshold selection. To compare GCNs, we proposed a multivariate approach based on the Principal Component Analysis (PCA). Branches of plant immunity that were exemplified by each experiment were analyzed in conjunction with the PCA results, suggesting both the robustness and the dynamic nature of the cellular responses. The dynamic of molecular plant responses produced networks with different characteristics that are differentiable using our methodology. The comparison of GCNs from plant pathosystems, showed that in response to similar pathogens plants could activate conserved signaling pathways. The results confirmed that the closeness of GCNs projected on the principal component space is an indicative of similarity among GCNs. This also can be used to understand global patterns of events triggered during plant immune responses.
ISSN:2167-8359
2167-8359
DOI:10.7717/peerj.610