Dataset Information

Predicted functional interactome of Caenorhabditis elegans and a web tool for the functional interpretation of differentially expressed genes.

ABSTRACT:

Background

The nematode worm, Caenorhabditis elegans, is a saprophytic species that has been emerging as a standard model organism since the early 1960s. This species is useful in numerous fields, including developmental biology, neurobiology, and ageing. A high-quality comprehensive molecular interaction network is needed to facilitate molecular mechanism studies in C. elegans.

Results

We present the predicted functional interactome of Caenorhabditis elegans (FIC), which integrates functional association data from 10 public databases to infer functional gene interactions on diverse functional perspectives. In this work, FIC includes 108,550 putative functional associations with balanced sensitivity and specificity, which are expected to cover 21.42% of all C. elegans protein interactions, and 29.25% of these associations may represent protein interactions. Based on FIC, we developed a gene set linkage analysis (GSLA) web tool to interpret potential functional impacts from a set of differentially expressed genes observed in transcriptome analyses.

Conclusion

We present the predicted C. elegans interactome database FIC, which is a high-quality database of predicted functional interactions among genes. The functional interactions in FIC serve as a good reference interactome for GSLA to annotate differentially expressed genes for their potential functional impacts. In a case study, the FIC/GSLA system shows more comprehensive and concise annotations compared to other widely used gene set annotation tools, including PANTHER and DAVID. FIC and its associated GSLA are available at the website http://worm.biomedtzc.cn .

SUBMITTER: Chen PC

PROVIDER: S-EPMC7574172 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature

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Publications

Predicted functional interactome of Caenorhabditis elegans and a web tool for the functional interpretation of differentially expressed genes.

Chen Peng-Cheng PC Ruan Li L Jin Jie J Tao Yu-Tian YT Ding Xiao-Bao XB Zhang Hai-Bo HB Guo Wen-Ping WP Yang Qiao-Lei QL Yao Heng H Chen Xin X

Biology direct 20201019 1

<h4>Background</h4>The nematode worm, Caenorhabditis elegans, is a saprophytic species that has been emerging as a standard model organism since the early 1960s. This species is useful in numerous fields, including developmental biology, neurobiology, and ageing. A high-quality comprehensive molecular interaction network is needed to facilitate molecular mechanism studies in C. elegans.<h4>Results</h4>We present the predicted functional interactome of Caenorhabditis elegans (FIC), which integrat ...[more]

PMID: 33076954

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Project description:BackgroundAn important objective of DNA microarray-based gene expression experimentation is determining inter-relationships that exist between differentially expressed genes and biological processes, molecular functions, cellular components, signaling pathways, physiologic processes and diseases.ResultsHere we describe GeneMesh, a web-based program that facilitates analysis of DNA microarray gene expression data. GeneMesh relates genes in a query set to categories available in the Medical Subject Headings (MeSH) hierarchical index. The interface enables hypothesis driven relational analysis to a specific MeSH subcategory (e.g., Cardiovascular System, Genetic Processes, Immune System Diseases etc.) or unbiased relational analysis to broader MeSH categories (e.g., Anatomy, Biological Sciences, Disease etc.). Genes found associated with a given MeSH category are dynamically linked to facilitate tabular and graphical depiction of Entrez Gene information, Gene Ontology information, KEGG metabolic pathway diagrams and intermolecular interaction information. Expression intensity values of groups of genes that cluster in relation to a given MeSH category, gene ontology or pathway can be displayed as heat maps of Z score-normalized values. GeneMesh operates on gene expression data derived from a number of commercial microarray platforms including Affymetrix, Agilent and Illumina.ConclusionsGeneMesh is a versatile web-based tool for testing and developing new hypotheses through relating genes in a query set (e.g., differentially expressed genes from a DNA microarray experiment) to descriptors making up the hierarchical structure of the National Library of Medicine controlled vocabulary thesaurus, MeSH. The system further enhances the discovery process by providing links between sets of genes associated with a given MeSH category to a rich set of html linked tabular and graphic information including Entrez Gene summaries, gene ontologies, intermolecular interactions, overlays of genes onto KEGG pathway diagrams and heatmaps of expression intensity values. GeneMesh is freely available online at http://proteogenomics.musc.edu/genemesh/.

Project description:BackgroundStenotrophomonas maltophilia is an emerging nosocomial pathogen that causes infection in immunocompromised patients. S. maltophilia isolates are genetically diverse, contain diverse virulence factors, and are variably pathogenic within several host species. Members of the Stenotrophomonas genus are part of the native microbiome of C. elegans, being found in greater relative abundance within the worm than its environment, suggesting that these bacteria accumulate within C. elegans. Thus, study of the C. elegans-Stenotrophomonas interaction is of both medical and ecological significance. To identify host defense mechanisms, we analyzed the C. elegans transcriptomic response to S. maltophilia strains of varying pathogenicity: K279a, an avirulent clinical isolate, JCMS, a virulent strain isolated in association with soil nematodes near Manhattan, KS, and JV3, an even more virulent environmental isolate.ResultsOverall, we found 145 genes that are commonly differentially expressed in response to pathogenic S. maltophilia strains, 89% of which are upregulated, with many even further upregulated in response to JV3 as compared to JCMS. There are many more JV3-specific differentially expressed genes (225, 11% upregulated) than JCMS-specific differentially expressed genes (14, 86% upregulated), suggesting JV3 has unique pathogenic mechanisms that could explain its increased virulence. We used connectivity within a gene network model to choose pathogen-specific and strain-specific differentially expressed candidate genes for functional analysis. Mutations in 13 of 22 candidate genes caused significant differences in C. elegans survival in response to at least one S. maltophilia strain, although not always the strain that induced differential expression, suggesting a dynamic response to varying levels of pathogenicity.ConclusionsVariation in observed pathogenicity and differences in host transcriptional responses to S. maltophilia strains reveal that strain-specific mechanisms play important roles in S. maltophilia pathogenesis. Furthermore, utilizing bacteria closely related to strains found in C. elegans natural environment provides a more realistic interaction for understanding host-pathogen response.

Dataset Information

Predicted functional interactome of Caenorhabditis elegans and a web tool for the functional interpretation of differentially expressed genes.

Background

Results

Conclusion

Publications

Predicted functional interactome of Caenorhabditis elegans and a web tool for the functional interpretation of differentially expressed genes.

Similar Datasets

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