WormBase: a modern Model Organism Information Resource

WormBase (https://wormbase.org/) is a mature Model Organism Information Resource supporting researchers using the nematode Caenorhabditis elegans as a model system for studies across a broad range of basic biological processes. Toward this mission, WormBase efforts are arranged in three primary facets: curation, user interface and architecture. In this update, we describe progress in each of these three areas. In particular, we discuss the status of literature curation and recently added data, detail new features of the web interface and options for users wishing to conduct data mining workflows, and discuss our efforts to build a robust and scalable architecture by leveraging commercial cloud offerings. We conclude with a description of WormBase's role as a founding member of the nascent Alliance of Genome Resources

WormBase: a modern Model Organism Information Resource

WormBase (https://wormbase.org/) is a mature Model Organism Information Resource supporting researchers using the nematode Caenorhabditis elegans as a model system for studies across a broad range of basic biological processes. Toward this mission, WormBase efforts are arranged in three primary facets: curation, user interface and architecture. In this update, we describe progress in each of these three areas. In particular, we discuss the status of literature curation and recently added data, detail new features of the web interface and options for users wishing to conduct data mining workflows, and discuss our efforts to build a robust and scalable architecture by leveraging commercial cloud offerings. We conclude with a description of WormBase's role as a founding member of the nascent Alliance of Genome Resources

Fast genetic mapping of complex traits in C. elegans using millions of individuals in bulk.

Genetic studies of complex traits in animals have been hindered by the need to generate, maintain, and phenotype large panels of recombinant lines. We developed a new method, C. elegans eXtreme Quantitative Trait Locus (ceX-QTL) mapping, that overcomes this obstacle via bulk selection on millions of unique recombinant individuals. We use ceX-QTL to map a drug resistance locus with high resolution. We also map differences in gene expression in live worms and discovered that mutations in the co-chaperone sti-1 upregulate the transcription of HSP-90. Lastly, we use ceX-QTL to map loci that influence fitness genome-wide confirming previously reported causal variants and uncovering new fitness loci. ceX-QTL is fast, powerful and cost-effective, and will accelerate the study of complex traits in animals

Evolutionary Codependency: Insights into the Mitonuclear interaction landscape from experimental and wild Caenorhabditis nematodes

Aided by new technologies, the upsurgence of research into mitochondrial genome biology during the past 15 years suggests that we have misunderstood, and perhaps dramatically underestimated, the ongoing biological and evolutionary significance of our long-time symbiotic partner. While we have begun to scratch the surface of several topics, many questions regarding the nature of mutation and selection in the mitochondrial genome, and the nature of its relationship to the nuclear genome, remain unanswered. Although best known for their contributions to studies of developmental and aging biology, Caenorhabditis nematodes are increasingly recognized as excellent model systems to advance understanding in these areas. We review recent discoveries with relevance to mitonuclear coevolution and conflict and offer several fertile areas for future work

Predicting gene essentiality in Caenorhabditis elegans by feature engineering and machine-learning

Defining genes that are essential for life has major implications for understanding critical biological processes and mechanisms. Although essential genes have been identified and characterised experimentally using functional genomic tools, it is challenging to predict with confidence such genes from molecular and phenomic data sets using computational methods. Using extensive data sets available for the model organism Caenorhabditis elegans, we constructed here a machine-learning (ML)-based workflow for the prediction of essential genes on a genome-wide scale. We identified strong predictors for such genes and showed that trained ML models consistently achieve highly-accurate classifications. Complementary analyses revealed an association between essential genes and chromosomal location. Our findings reveal that essential genes in C. elegans tend to be located in or near the centre of autosomal chromosomes; are positively correlated with low single nucleotide polymorphim (SNP) densities and epigenetic markers in promoter regions; are involved in protein and nucleotide processing; are transcribed in most cells; are enriched in reproductive tissues or are targets for small RNAs bound to the argonaut CSR-1. Based on these results, we hypothesise an interplay between epigenetic markers and small RNA pathways in the germline, with transcription-based memory; this hypothesis warrants testing. From a technical perspective, further work is needed to evaluate whether the present ML-based approach will be applicable to other metazoans (including Drosophila melanogaster) for which comprehensive data set (i.e. genomic, transcriptomic, proteomic, variomic, epigenetic and phenomic) are available

Newly identified nematodes from Mono Lake exhibit extreme arsenic resistance

Extremophiles have much to reveal about the biology of resilience, yet their study is limited by sampling and culturing difficulties [1, 2, 3]. The broad success and small size of nematodes make them advantageous for tackling these problems [4, 5, 6]. We investigated the arsenic-rich, alkaline, and hypersaline Mono Lake (CA, US) [7, 8, 9] for extremophile nematodes. Though Mono Lake has previously been described to contain only two animal species (brine shrimp and alkali flies) in its water and sediments [10], we report the discovery of eight nematode species from the lake, including microbe grazers, parasites, and predators. Thus, nematodes are the dominant animals of Mono Lake in species richness. Phylogenetic analysis suggests that the nematodes originated from multiple colonization events, which is striking, given the young history of extreme conditions at Mono Lake [7, 11]. One species, Auanema sp., is new, culturable, and survives 500 times the human lethal dose of arsenic. Comparisons to two non-extremophile sister species [12] reveal that arsenic resistance is a common feature of the genus and a preadaptive trait that likely allowed Auanema to inhabit Mono Lake. This preadaptation may be partly explained by a variant in the gene dbt-1 shared with some Caenorhabditis elegans natural populations and known to confer arsenic resistance [13]. Our findings expand Mono Lake’s ecosystem from two known animal species to ten, and they provide a new system for studying arsenic resistance. The dominance of nematodes in Mono Lake and other extreme environments and our findings of preadaptation to arsenic raise the intriguing possibility that nematodes are widely pre-adapted to be extremophiles

Diversification of the Caenorhabditis heat shock response by Helitron transposable elements.

Heat Shock Factor 1 (HSF-1) is a key regulator of the heat shock response (HSR). Upon heat shock, HSF-1 binds well-conserved motifs, called Heat Shock Elements (HSEs), and drives expression of genes important for cellular protection during this stress. Remarkably, we found that substantial numbers of HSEs in multiple Caenorhabditis species reside within Helitrons, a type of DNA transposon. Consistent with Helitron-embedded HSEs being functional, upon heat shock they display increased HSF-1 and RNA polymerase II occupancy and up-regulation of nearby genes in C. elegans. Interestingly, we found that different genes appear to be incorporated into the HSR by species-specific Helitron insertions in C. elegans and C. briggsae and by strain-specific insertions among different wild isolates of C. elegans. Our studies uncover previously unidentified targets of HSF-1 and show that Helitron insertions are responsible for rewiring and diversifying the Caenorhabditis HSR

Population Selection and Sequencing of Caenorhabditis elegans Wild Isolates Identifies a Region on Chromosome III Affecting Starvation Resistance

To understand the genetic basis of complex traits, it is important to be able to efficiently phenotype many genetically distinct individuals. In the nematode Caenorhabditis elegans, individuals have been isolated from diverse populations around the globe and whole-genome sequenced. As a result, hundreds of wild strains with known genome sequences can be used for genome-wide association studies (GWAS). However, phenotypic analysis of these strains can be laborious, particularly for quantitative traits requiring multiple measurements per strain. Starvation resistance is likely a fitness-proximal trait for nematodes, and it is related to metabolic disease risk in humans. However, natural variation in C. elegans starvation resistance has not been systematically characterized, and precise measurement of the trait is time-intensive. Here, we developed a population-selection-and-sequencing-based approach to phenotype starvation resistance in a pool of 96 wild strains. We used restriction site-associated DNA sequencing (RAD-seq) to infer the frequency of each strain among survivors in a mixed culture over time during starvation. We used manual starvation survival assays to validate the trait data, confirming that strains that increased in frequency over time are starvation-resistant relative to strains that decreased in frequency. Further, we found that variation in starvation resistance is significantly associated with variation at a region on chromosome III. Using a near-isogenic line (NIL), we showed the importance of this genomic interval for starvation resistance. This study demonstrates the feasibility of using population selection and sequencing in an animal model for phenotypic analysis of quantitative traits, documents natural variation of starvation resistance in C. elegans, and identifies a genomic region that contributes to such variation