ABSTRACT
Phenotypic complexity results from the contributions of environmental factors and multiple genetic loci, interacting or acting independently. Studies of yeast and Arabidopsis found that the majority of natural variation across phenotypes is attributable to independent additive quantitative trait loci. Detected loci in these organisms explain most of the estimated heritable variation. By contrast, many heritable components underlying phenotypic variation in metazoan models remain undetected. Before the relative impacts of additive and interactive variance components on metazoan phenotypic variation can be dissected, high replication and precise phenotypic measurements are required to obtain sufficient statistical power to detect loci contributing to this missing heritability. Here, we used a panel of 296 recombinant inbred advanced intercross lines of Caenorhabditis elegans and a high-throughput fitness assay to detect loci underlying responses to 16 different toxins, including heavy metals, chemotherapeutic drugs, pesticides, and neuropharmaceuticals. Using linkage mapping, we identified 114 distinct genomic regions that underlie variation in responses to these toxins and predicted the relative contributions of additive loci and genetic interactions across various growth parameters. Additionally, we identified three genomic regions that impact responses to multiple classes of toxins. These quantitative trait loci hotspots could represent common factors impacting toxin responses. We went further to both generate near-isogenic lines and chromosome-substitution strains and then experimentally validate these QTL hotspots, implicating additive and interactive loci that underlie toxin-response variation. The discovery of these QTL hotspots indicate that pleiotropic loci that control responses to multiple conditions could underlie the means by which large regions of the genome were swept across the C. elegans species.
Article summary A panel of recombinant Caenorhabditis elegans lines was exposed to 16 toxins, and responses were quantified using a high-throughput fitness assay. We identified 114 distinct quantitative trait loci (QTL), including three hotspots where QTL were enriched across the conditions tested. These hotspots could represent common loci underlying toxin responses. Additionally, we found that both additive and epistatic genetic factors control toxin responses. We go on to validate additive QTL and inter-and intra-chromosomal interaction QTL based on toxin responses assays of near-isogenic lines (NILs) and chromosome-substitution strains (CSSs), going further to delineate genetic causes than most experiments of this scale.
