CaeNDR, the Caenorhabditis Natural Diversity Resource.

Studies of model organisms have provided important insights into how natural genetic differences shape trait variation. These discoveries are driven by the growing availability of genomes and the expansive experimental toolkits afforded to researchers using these species. For example, Caenorhabditis elegans is increasingly being used to identify and measure the effects of natural genetic variants on traits using quantitative genetics. Since 2016, the C. elegans Natural Diversity Resource (CeNDR) has facilitated many of these studies by providing an archive of wild strains, genome-wide sequence and variant data for each strain, and a genome-wide association (GWA) mapping portal for the C. elegans community. Here, we present an updated platform, the Caenorhabditis Natural Diversity Resource (CaeNDR), that enables quantitative genetics and genomics studies across the three Caenorhabditis species: C. elegans, C. briggsae and C. tropicalis. The CaeNDR platform hosts several databases that are continually updated by the addition of new strains, whole-genome sequence data and annotated variants. Additionally, CaeNDR provides new interactive tools to explore natural variation and enable GWA mappings. All CaeNDR data and tools are accessible through a freely available web portal located at caendr.org.

C. elegans toxicant responses vary among genetically diverse individuals.

The genetic variability of toxicant responses among indisviduals in humans and mammalian models requires practically untenable sample sizes to create comprehensive chemical hazard risk evaluations. To address this need, tractable model systems enable reproducible and efficient experimental workflows to collect high-replication measurements of exposure cohorts. Caenorhabditis elegans is a premier toxicology model that has revolutionized our understanding of cellular responses to environmental pollutants and boasts robust genomic resources and high levels of genetic variation across the species. In this study, we performed dose-response analysis across 23 environmental toxicants using eight C. elegans strains representative of species-wide genetic diversity. We observed substantial variation in EC10 estimates and slope parameter estimates of dose-response curves of different strains, demonstrating that genetic background is a significant driver of differential toxicant susceptibility. We also showed that, across all toxicants, at least one C. elegans strain exhibited a significantly different EC10 or slope estimate compared to the reference strain, N2 (PD1074), indicating that population-wide differences among strains are necessary to understand responses to toxicants. Moreover, we quantified the heritability of responses (phenotypic variance attributable to genetic differences between individuals) to each toxicant exposure and observed a correlation between the exposure closest to the species-agnostic EC10 estimate and the exposure that exhibited the most heritable response. At least 20% of the variance in susceptibility to at least one exposure level of each compound was explained by genetic differences among the eight C. elegans strains. Taken together, these results provide robust evidence that heritable genetic variation explains differential susceptibility across an array of environmental pollutants and that genetically diverse C. elegans strains should be deployed to aid high-throughput toxicological screening efforts.

Evaluating the power and limitations of genome-wide association studies in Caenorhabditis elegans.

Quantitative genetics in Caenorhabditis elegans seeks to identify naturally segregating genetic variants that underlie complex traits. Genome-wide association studies scan the genome for individual genetic variants that are significantly correlated with phenotypic variation in a population, or quantitative trait loci. Genome-wide association studies are a popular choice for quantitative genetic analyses because the quantitative trait loci that are discovered segregate in natural populations. Despite numerous successful mapping experiments, the empirical performance of genome-wide association study has not, to date, been formally evaluated in C. elegans. We developed an open-source genome-wide association study pipeline called NemaScan and used a simulation-based approach to provide benchmarks of mapping performance in collections of wild C. elegans strains. Simulated trait heritability and complexity determined the spectrum of quantitative trait loci detected by genome-wide association studies. Power to detect smaller-effect quantitative trait loci increased with the number of strains sampled from the C. elegans Natural Diversity Resource. Population structure was a major driver of variation in mapping performance, with populations shaped by recent selection exhibiting significantly lower false discovery rates than populations composed of more divergent strains. We also recapitulated previous genome-wide association studies of experimentally validated quantitative trait variants. Our simulation-based evaluation of performance provides the community with critical context to pursue quantitative genetic studies using the C. elegans Natural Diversity Resource to elucidate the genetic basis of complex traits in C. elegans natural populations.

easyXpress: An R package to analyze and visualize high-throughput C. elegans microscopy data generated using CellProfiler.

High-throughput imaging techniques have become widespread in many fields of biology. These powerful platforms generate large quantities of data that can be difficult to process and visualize efficiently using existing tools. We developed easyXpress to process and review C. elegans high-throughput microscopy data in the R environment. The package provides a logical workflow for the reading, analysis, and visualization of data generated using CellProfiler's WormToolbox. We equipped easyXpress with powerful functions to customize the filtering of noise in data, specifically by identifying and removing objects that deviate from expected animal measurements. This flexibility in data filtering allows users to optimize their analysis pipeline to match their needs. In addition, easyXpress includes tools for generating detailed visualizations, allowing the user to interactively compare summary statistics across wells and plates with ease. Researchers studying C. elegans benefit from this streamlined and extensible package as it is complementary to CellProfiler and leverages the R environment to rapidly process and analyze large high-throughput imaging datasets.

Xenobiotic metabolism and transport in Caenorhabditis elegans.

Caenorhabditis elegans has emerged as a major model in biomedical and environmental toxicology. Numerous papers on toxicology and pharmacology in C. elegans have been published, and this species has now been adopted by investigators in academic toxicology, pharmacology, and drug discovery labs. C. elegans has also attracted the interest of governmental regulatory agencies charged with evaluating the safety of chemicals. However, a major, fundamental aspect of toxicological science remains underdeveloped in C. elegans: xenobiotic metabolism and transport processes that are critical to understanding toxicokinetics and toxicodynamics, and extrapolation to other species. The aim of this review was to initially briefly describe the history and trajectory of the use of C. elegans in toxicological and pharmacological studies. Subsequently, physical barriers to chemical uptake and the role of the worm microbiome in xenobiotic transformation were described. Then a review of what is and is not known regarding the classic Phase I, Phase II, and Phase III processes was performed. In addition, the following were discussed (1) regulation of xenobiotic metabolism; (2) review of published toxicokinetics for specific chemicals; and (3) genetic diversity of these processes in C. elegans. Finally, worm xenobiotic transport and metabolism was placed in an evolutionary context; key areas for future research highlighted; and implications for extrapolating C. elegans toxicity results to other species discussed.

Age and Genetic Background Modify Hybrid Male Sterility in House Mice.

Hybrid male sterility (HMS) contributes to reproductive isolation commonly observed among house mouse (Mus musculus) subspecies, both in the wild and in laboratory crosses. Incompatibilities involving specific Prdm9 alleles and certain Chromosome (Chr) X genotypes are known determinants of fertility and HMS, and previous work in the field has demonstrated that genetic background modifies these two major loci. We constructed hybrids that have identical genotypes at Prdm9 and identical X chromosomes, but differ widely across the rest of the genome. In each case, we crossed female PWK/PhJ mice representative of the M. m. musculus subspecies to males from a classical inbred strain representative of M. m. domesticus: 129S1/SvImJ, A/J, C57BL/6J, or DBA/2J. We detected three distinct trajectories of fertility among the hybrids using breeding experiments. The PWK129S1 males were always infertile. PWKDBA2 males were fertile, despite their genotypes at the major HMS loci. We also observed age-dependent changes in fertility parameters across multiple genetic backgrounds. The PWKB6 and PWKAJ males were always infertile before 12 weeks and after 35 weeks. However, some PWKB6 and PWKAJ males were transiently fertile between 12 and 35 weeks. This observation could resolve previous contradictory reports about the fertility of PWKB6. Taken together, these results point to multiple segregating HMS modifier alleles, some of which have age-related modes of action. The ultimate identification of these alleles and their age-related mechanisms will advance understanding both of the genetic architecture of HMS and of how reproductive barriers are maintained between house mouse subspecies.

Novel Neuroprotective Loci Modulating Ischemic Stroke Volume in Wild-Derived Inbred Mouse Strains.

To identify genes involved in cerebral infarction, we have employed a forward genetic approach in inbred mouse strains, using quantitative trait loci (QTL) mapping for cerebral infarct volume after middle cerebral artery occlusion. We had previously observed that infarct volume is inversely correlated with cerebral collateral vessel density in most strains. In this study, we expanded the pool of allelic variation among classical inbred mouse strains by utilizing the eight founder strains of the Collaborative Cross and found a wild-derived strain, WSB/EiJ, that breaks this general rule that collateral vessel density inversely correlates with infarct volume. WSB/EiJ and another wild-derived strain, CAST/EiJ, show the highest collateral vessel densities of any inbred strain, but infarct volume of WSB/EiJ mice is 8.7-fold larger than that of CAST/EiJ mice. QTL mapping between these strains identified four new neuroprotective loci modulating cerebral infarct volume while not affecting collateral vessel phenotypes. To identify causative variants in genes, we surveyed nonsynonymous coding SNPs between CAST/EiJ and WSB/EiJ and found 96 genes harboring coding SNPs predicted to be damaging and mapping within one of the four intervals. In addition, we performed RNA-sequencing for brain tissue of CAST/EiJ and WSB/EiJ mice and identified 79 candidate genes mapping in one of the four intervals showing strain-specific differences in expression. The identification of the genes underlying these neuroprotective loci will provide new understanding of genetic risk factors of ischemic stroke, which may provide novel targets for future therapeutic intervention of human ischemic stroke.