Discovery of core biotic stress responsive genes in Arabidopsis by weighted gene co-expression network analysis.
Intricate signal networks and transcriptional regulators translate the recognition of pathogens into defense responses. In this study, we carried out a gene co-expression analysis of all currently publicly available microarray data, which were generated in experiments that studied the interaction of...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Public Library of Science (PLoS)
2015-01-01
|
| Series: | PLoS ONE |
| Online Access: | https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0118731&type=printable |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850190615093968896 |
|---|---|
| author | Katherine C H Amrine Barbara Blanco-Ulate Dario Cantu |
| author_facet | Katherine C H Amrine Barbara Blanco-Ulate Dario Cantu |
| author_sort | Katherine C H Amrine |
| collection | DOAJ |
| description | Intricate signal networks and transcriptional regulators translate the recognition of pathogens into defense responses. In this study, we carried out a gene co-expression analysis of all currently publicly available microarray data, which were generated in experiments that studied the interaction of the model plant Arabidopsis thaliana with microbial pathogens. This work was conducted to identify (i) modules of functionally related co-expressed genes that are differentially expressed in response to multiple biotic stresses, and (ii) hub genes that may function as core regulators of disease responses. Using Weighted Gene Co-expression Network Analysis (WGCNA) we constructed an undirected network leveraging a rich curated expression dataset comprising 272 microarrays that involved microbial infections of Arabidopsis plants with a wide array of fungal and bacterial pathogens with biotrophic, hemibiotrophic, and necrotrophic lifestyles. WGCNA produced a network with scale-free and small-world properties composed of 205 distinct clusters of co-expressed genes. Modules of functionally related co-expressed genes that are differentially regulated in response to multiple pathogens were identified by integrating differential gene expression testing with functional enrichment analyses of gene ontology terms, known disease associated genes, transcriptional regulators, and cis-regulatory elements. The significance of functional enrichments was validated by comparisons with randomly generated networks. Network topology was then analyzed to identify intra- and inter-modular gene hubs. Based on high connectivity, and centrality in meta-modules that are clearly enriched in defense responses, we propose a list of 66 target genes for reverse genetic experiments to further dissect the Arabidopsis immune system. Our results show that statistical-based data trimming prior to network analysis allows the integration of expression datasets generated by different groups, under different experimental conditions and biological systems, into a functionally meaningful co-expression network. |
| format | Article |
| id | doaj-art-c4ece8d685954c60bb4c46a1a910d14a |
| institution | OA Journals |
| issn | 1932-6203 |
| language | English |
| publishDate | 2015-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj-art-c4ece8d685954c60bb4c46a1a910d14a2025-08-20T02:15:15ZengPublic Library of Science (PLoS)PLoS ONE1932-62032015-01-01103e011873110.1371/journal.pone.0118731Discovery of core biotic stress responsive genes in Arabidopsis by weighted gene co-expression network analysis.Katherine C H AmrineBarbara Blanco-UlateDario CantuIntricate signal networks and transcriptional regulators translate the recognition of pathogens into defense responses. In this study, we carried out a gene co-expression analysis of all currently publicly available microarray data, which were generated in experiments that studied the interaction of the model plant Arabidopsis thaliana with microbial pathogens. This work was conducted to identify (i) modules of functionally related co-expressed genes that are differentially expressed in response to multiple biotic stresses, and (ii) hub genes that may function as core regulators of disease responses. Using Weighted Gene Co-expression Network Analysis (WGCNA) we constructed an undirected network leveraging a rich curated expression dataset comprising 272 microarrays that involved microbial infections of Arabidopsis plants with a wide array of fungal and bacterial pathogens with biotrophic, hemibiotrophic, and necrotrophic lifestyles. WGCNA produced a network with scale-free and small-world properties composed of 205 distinct clusters of co-expressed genes. Modules of functionally related co-expressed genes that are differentially regulated in response to multiple pathogens were identified by integrating differential gene expression testing with functional enrichment analyses of gene ontology terms, known disease associated genes, transcriptional regulators, and cis-regulatory elements. The significance of functional enrichments was validated by comparisons with randomly generated networks. Network topology was then analyzed to identify intra- and inter-modular gene hubs. Based on high connectivity, and centrality in meta-modules that are clearly enriched in defense responses, we propose a list of 66 target genes for reverse genetic experiments to further dissect the Arabidopsis immune system. Our results show that statistical-based data trimming prior to network analysis allows the integration of expression datasets generated by different groups, under different experimental conditions and biological systems, into a functionally meaningful co-expression network.https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0118731&type=printable |
| spellingShingle | Katherine C H Amrine Barbara Blanco-Ulate Dario Cantu Discovery of core biotic stress responsive genes in Arabidopsis by weighted gene co-expression network analysis. PLoS ONE |
| title | Discovery of core biotic stress responsive genes in Arabidopsis by weighted gene co-expression network analysis. |
| title_full | Discovery of core biotic stress responsive genes in Arabidopsis by weighted gene co-expression network analysis. |
| title_fullStr | Discovery of core biotic stress responsive genes in Arabidopsis by weighted gene co-expression network analysis. |
| title_full_unstemmed | Discovery of core biotic stress responsive genes in Arabidopsis by weighted gene co-expression network analysis. |
| title_short | Discovery of core biotic stress responsive genes in Arabidopsis by weighted gene co-expression network analysis. |
| title_sort | discovery of core biotic stress responsive genes in arabidopsis by weighted gene co expression network analysis |
| url | https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0118731&type=printable |
| work_keys_str_mv | AT katherinechamrine discoveryofcorebioticstressresponsivegenesinarabidopsisbyweightedgenecoexpressionnetworkanalysis AT barbarablancoulate discoveryofcorebioticstressresponsivegenesinarabidopsisbyweightedgenecoexpressionnetworkanalysis AT dariocantu discoveryofcorebioticstressresponsivegenesinarabidopsisbyweightedgenecoexpressionnetworkanalysis |