Data on chemical-gene interactions and biological categories enriched with genes sensitive to chemical exposures

Abstract

A dataset of chemical-gene interactions was created by extracting data from the Comparative Toxicogenomics Database (CTD) with the following filtering criteria: data was extracted only from experiments that used human, rat, or mouse cells/tissues and used high-throughput approaches for gene expression analysis. Genes not present in genomes of all three species were filtered out. The resulting dataset included 591,084 chemical-gene interaction. All chemical compounds in the database were annotated for their major uses. For every gene in the database number of chemical-gene interactions was calculated and used as a metric of gene sensitivity to a variety of chemical exposures. The lists of genes with corresponding numbers of chemical-gene interactions were used in gene-set enrichment analysis (GSEA) to identify potential sensitivity to chemical exposures of molecular pathways in Hallmark, KEGG and Reactome collections. Thus, data presented here represent unbiased and searchable datasets of sensitivity of genes and molecular pathways to a broad range of chemical exposures. As such the data can be used for a diverse range of toxicological and regulatory applications. Approach for the identification of molecular mechanisms sensitive to chemical exposures may inform regulatory toxicology about best toxicity testing strategies. Analysis of sensitivity of genes and molecular pathways to chemical exposures based on these datasets was published in Chemosphere (Suvorov et al., 2021) [1].

Keywords

• Toxicity pathway
• Adverse outcome pathway
• Toxicogenomics
• Computational toxicology