Toxicological SciencesPharmacology & ToxicologyPeer-reviewed journal article
Natural variation suggests candidate genes underlying Caenorhabditis elegans susceptibility to diverse toxicants
Timothy A. CrombieiD, Ryan McKeowniD, Samuel J. WidmayeriD, Amanda O. ShaveriD, Nicolas D. MoyaiD, J.B. CollinsiD, Janneke WitiD, Robyn E. TannyiD, Christian BraendleiD, Lewis StevensiD, Lisa van SluijsiD, Matthew V. RockmaniD, Mark G. SterkeniD, Marie‐Anne FélixiD, Erik C. AnderseniD
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Abstract
Genetic differences among individuals shape how they respond to environmental toxicants, but the identification and validation of the genes responsible for this variation is difficult, particularly in humans. Consequently, our limited knowledge of the genes that influence susceptibility constrains our ability to accurately predict the risks posed by environmental toxicants. To identify genes underlying natural differences in toxicant susceptibilities, we measured the effects of 23 environmental toxicants on larval development across 195 genetically diverse Caenorhabditis elegans strains using a high-throughput imaging platform. We then combined these response data with whole-genome sequences to perform genome-wide association mappings, identifying 40 genomic regions where genetic variants are correlated with susceptibility differences. Many of these regions are enriched for genes involved in biological processes previously linked with toxicant responses, supporting the potential contributions of these genes to natural variation in susceptibility. Using a set of heuristics, we identified 94 candidate susceptibility genes, offering targets for experimental validation that could ultimately inform toxicant risk prediction and regulatory assessment by linking genetic variation to differences in susceptibility. Impact StatementAnalysis of natural genetic variation among 195 wild C. elegans strains identified 94 candidate genes putatively linked to differences in susceptibility to 23 environmental toxicants. These findings can inform the discovery of conserved susceptibility genes and the development of biomarkers that improve chemical risk assessment by accounting for genetic differences among humans.
- organism: C. elegans
- assay: whole-genome sequencing
- research focus: gene regulatory network inference
- approach: statistical model
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