Christian A. Grove

WormBase 2012: more genomes, more data, new website

Since its release in 2000, WormBase (http://www.wormbase.org) has grown from a small resource focusing on a single species and serving a dedicated research community, to one now spanning 15 species essential to the broader biomedical and agricultural research fields. To enhance the rate of curation, we have automated the identification of key data in the scientific literature and use similar methodology for data extraction. To ease access to the data, we are collaborating with journals to link entities in research publications to their report pages at WormBase. To facilitate discovery, we have added new views of the data, integrated large-scale datasets and expanded descriptions of models for human disease. Finally, we have introduced a dramatic overhaul of the WormBase website for public beta testing. Designed to balance complexity and usability, the new site is species-agnostic, highly customizable, and interactive. Casual users and developers alike will be able to leverage the public RESTful application programming interface (API) to generate custom data mining solutions and extensions to the site. We report on the growth of our database and on our work in keeping pace with the growing demand for data, efforts to anticipate the requirements of users and new collaborations with the larger science community.

A compendium of Caenorhabditis elegans regulatory transcription factors: a resource for mapping transcription regulatory networks

BackgroundTranscription regulatory networks are composed of interactions between transcription factors and their target genes. Whereas unicellular networks have been studied extensively, metazoan transcription regulatory networks remain largely unexplored. Caenorhabditis elegans provides a powerful model to study such metazoan networks because its genome is completely sequenced and many functional genomic tools are available. While C. elegans gene predictions have undergone continuous refinement, this is not true for the annotation of functional transcription factors. The comprehensive identification of transcription factors is essential for the systematic mapping of transcription regulatory networks because it enables the creation of physical transcription factor resources that can be used in assays to map interactions between transcription factors and their target genes.ResultsBy computational searches and extensive manual curation, we have identified a compendium of 934 transcription factor genes (referred to as wTF2.0). We find that manual curation drastically reduces the number of both false positive and false negative transcription factor predictions. We discuss how transcription factor splice variants and dimer formation may affect the total number of functional transcription factors. In contrast to mouse transcription factor genes, we find that C. elegans transcription factor genes do not undergo significantly more splicing than other genes. This difference may contribute to differences in organism complexity. We identify candidate redundant worm transcription factor genes and orthologous worm and human transcription factor pairs. Finally, we discuss how wTF2.0 can be used together with physical transcription factor clone resources to facilitate the systematic mapping of C. elegans transcription regulatory networks.ConclusionwTF2.0 provides a starting point to decipher the transcription regulatory networks that control metazoan development and function.

WormBase 2014: new views of curated biology

WormBase (http://www.wormbase.org/) is a highly curated resource dedicated to supporting research using the model organism Caenorhabditis elegans. With an electronic history predating the World Wide Web, WormBase contains information ranging from the sequence and phenotype of individual alleles to genome-wide studies generated using next-generation sequencing technologies. In recent years, we have expanded the contents to include data on additional nematodes of agricultural and medical significance, bringing the knowledge of C. elegans to bear on these systems and providing support for underserved research communities. Manual curation of the primary literature remains a central focus of the WormBase project, providing users with reliable, up-to-date and highly cross-linked information. In this update, we describe efforts to organize the original atomized and highly contextualized curated data into integrated syntheses of discrete biological topics. Next, we discuss our experiences coping with the vast increase in available genome sequences made possible through next-generation sequencing platforms. Finally, we describe some of the features and tools of the new WormBase Web site that help users better find and explore data of interest.

WormBase 2016: expanding to enable helminth genomic research

WormBase (www.wormbase.org) is a central repository for research data on the biology, genetics and genomics of Caenorhabditis elegans and other nematodes. The project has evolved from its original remit to collect and integrate all data for a single species, and now extends to numerous nematodes, ranging from evolutionary comparators of C. elegans to parasitic species that threaten plant, animal and human health. Research activity using C. elegans as a model system is as vibrant as ever, and we have created new tools for community curation in response to the ever-increasing volume and complexity of data. To better allow users to navigate their way through these data, we have made a number of improvements to our main website, including new tools for browsing genomic features and ontology annotations. Finally, we have developed a new portal for parasitic worm genomes. WormBase ParaSite (parasite.wormbase.org) contains all publicly available nematode and platyhelminth annotated genome sequences, and is designed specifically to support helminth genomic research.

Insight into transcription factor gene duplication from Caenorhabditis elegans Promoterome-driven expression patterns

BackgroundThe C. elegans Promoterome is a powerful resource for revealing the regulatory mechanisms by which transcription is controlled pan-genomically. Transcription factors will form the core of any systems biology model of genome control and therefore the promoter activity of Promoterome inserts for C. elegans transcription factor genes was examined, in vivo, with a reporter gene approach.ResultsTransgenic C. elegans strains were generated for 366 transcription factor promoter/gfp reporter gene fusions. GFP distributions were determined, and then summarized with reference to developmental stage and cell type. Reliability of these data was demonstrated by comparison to previously described gene product distributions. A detailed consideration of the results for one C. elegans transcription factor gene family, the Six family, comprising ceh-32, ceh-33, ceh-34 and unc-39 illustrates the value of these analyses. The high proportion of Promoterome reporter fusions that drove GFP expression, compared to previous studies, led to the hypothesis that transcription factor genes might be involved in local gene duplication events less frequently than other genes. Comparison of transcription factor genes of C. elegans and Caenorhabditis briggsae was therefore carried out and revealed very few examples of functional gene duplication since the divergence of these species for most, but not all, transcription factor gene families.ConclusionExamining reporter expression patterns for hundreds of promoters informs, and thereby improves, interpretation of this data type. Genes encoding transcription factors involved in intrinsic developmental control processes appear acutely sensitive to changes in gene dosage through local gene duplication, on an evolutionary time scale.

Matrix and Steiner-triple-system smart pooling assays for high-performance transcription regulatory network mapping

Yeast one-hybrid (Y1H) assays provide a gene-centered method for the identification of interactions between gene promoters and regulatory transcription factors (TFs). To date, Y1H assays have involved library screens that are relatively expensive and laborious. We present two Y1H strategies that allow immediate prey identification: matrix assays that use an array of 755 individual Caenorhabditis elegans TFs, and smart-pool assays that use TF multiplexing. Both strategies simplify the Y1H pipeline and reduce the cost of protein-DNA interaction identification. We used a Steiner triple system (STS) to create smart pools of 4–25 TFs. Notably, we uniplexed a small number of highly connected TFs to allow efficient assay deconvolution. Both strategies outperform library screens in terms of coverage, confidence and throughput. These versatile strategies can be adapted both to TFs in other systems and, likely, to other biomolecules and assays as well.

Using a structural and logics systems approach to infer bHLH–DNA binding specificity determinants

Numerous efforts are underway to determine gene regulatory networks that describe physical relationships between transcription factors (TFs) and their target DNA sequences. Members of paralogous TF families typically recognize similar DNA sequences. Knowledge of the molecular determinants of protein–DNA recognition by paralogous TFs is of central importance for understanding how small differences in DNA specificities can dictate target gene selection. Previously, we determined the in vitro DNA binding specificities of 19 Caenorhabditis elegans basic helix-loop-helix (bHLH) dimers using protein binding microarrays. These TFs bind E-box (CANNTG) and E-box-like sequences. Here, we combine these data with logics, bHLH–DNA co-crystal structures and computational modeling to infer which bHLH monomer can interact with which CAN E-box half-site and we identify a critical residue in the protein that dictates this specificity. Validation experiments using mutant bHLH proteins provide support for our inferences. Our study provides insights into the mechanisms of DNA recognition by bHLH dimers as well as a blueprint for system-level studies of the DNA binding determinants of other TF families in different model organisms and humans.

WormBase 2017: molting into a new stage

Abstract WormBase (http://www.wormbase.org) is an important knowledge resource for biomedical researchers worldwide. To accommodate the ever increasing amount and complexity of research data, WormBase continues to advance its practices on data acquisition, curation and retrieval to most effectively deliver comprehensive knowledge about Caenorhabditis elegans, and genomic information about other nematodes and parasitic flatworms. Recent notable enhancements include user-directed submission of data, such as micropublication; genomic data curation and presentation, including additional genomes and JBrowse, respectively; new query tools, such as SimpleMine, Gene Enrichment Analysis; new data displays, such as the Person Lineage browser and the Summary of Ontology-based Annotations. Anticipating more rapid data growth ahead, WormBase continues the process of migrating to a cutting-edge database technology to achieve better stability, scalability, reproducibility and a faster response time. To better serve the broader research community, WormBase, with five other Model Organism Databases and The Gene Ontology project, have begun to collaborate formally as the Alliance of Genome Resources.

Using WormBase: A Genome Biology Resource for Caenorhabditis elegans and Related Nematodes

WormBase ( www.wormbase.org ) provides the nematode research community with a centralized database for information pertaining to nematode genes and genomes. As more nematode genome sequences are becoming available and as richer data sets are published, WormBase strives to maintain updated information, displays, and services to facilitate efficient access to and understanding of the knowledge generated by the published nematode genetics literature. This chapter aims to provide an explanation of how to use basic features of WormBase, new features, and some commonly used tools and data queries. Explanations of the curated data and step-by-step instructions of how to access the data via the WormBase website and available data mining tools are provided.