The Monarch Initiative in 2019: an integrative data and analytic platform connecting phenotypes to genotypes across species.

In biology and biomedicine, relating phenotypic outcomes with genetic variation and environmental factors remains a challenge: patient phenotypes may not match known diseases, candidate variants may be in genes that haven't been characterized, research organisms may not recapitulate human or veterinary diseases, environmental factors affecting disease outcomes are unknown or undocumented, and many resources must be queried to find potentially significant phenotypic associations. The Monarch Initiative (https://monarchinitiative.org) integrates information on genes, variants, genotypes, phenotypes and diseases in a variety of species, and allows powerful ontology-based search. We develop many widely adopted ontologies that together enable sophisticated computational analysis, mechanistic discovery and diagnostics of Mendelian diseases. Our algorithms and tools are widely used to identify animal models of human disease through phenotypic similarity, for differential diagnostics and to facilitate translational research. Launched in 2015, Monarch has grown with regards to data (new organisms, more sources, better modeling); new API and standards; ontologies (new Mondo unified disease ontology, improvements to ontologies such as HPO and uPheno); user interface (a redesigned website); and community development. Monarch data, algorithms and tools are being used and extended by resources such as GA4GH and NCATS Translator, among others, to aid mechanistic discovery and diagnostics.

RNAcentral: a comprehensive database of non-coding RNA sequences.

RNAcentral is a database of non-coding RNA (ncRNA) sequences that aggregates data from specialised ncRNA resources and provides a single entry point for accessing ncRNA sequences of all ncRNA types from all organisms. Since its launch in 2014, RNAcentral has integrated twelve new resources, taking the total number of collaborating database to 22, and began importing new types of data, such as modified nucleotides from MODOMICS and PDB. We created new species-specific identifiers that refer to unique RNA sequences within a context of single species. The website has been subject to continuous improvements focusing on text and sequence similarity searches as well as genome browsing functionality. All RNAcentral data is provided for free and is available for browsing, bulk downloads, and programmatic access at http://rnacentral.org/.

dictyBase 2015: Expanding data and annotations in a new software environment.

dictyBase is the model organism database for the social amoeba Dictyostelium discoideum and related species. The primary mission of dictyBase is to provide the biomedical research community with well-integrated high quality data, and tools that enable original research. Data presented at dictyBase is obtained from sequencing centers, groups performing high throughput experiments such as large-scale mutagenesis studies, and RNAseq data, as well as a growing number of manually added functional gene annotations from the published literature, including Gene Ontology, strain, and phenotype annotations. Through the Dicty Stock Center we provide the community with an impressive amount of annotated strains and plasmids. Recently, dictyBase accomplished a major overhaul to adapt an outdated infrastructure to the current technological advances, thus facilitating the implementation of innovative tools and comparative genomics. It also provides new strategies for high quality annotations that enable bench researchers to benefit from the rapidly increasing volume of available data. dictyBase is highly responsive to its users needs, building a successful relationship that capitalizes on the vast efforts of the Dictyostelium research community. dictyBase has become the trusted data resource for Dictyostelium investigators, other investigators or organizations seeking information about Dictyostelium, as well as educators who use this model system.

DictyBase 2013: integrating multiple Dictyostelid species.

dictyBase (http://dictybase.org) is the model organism database for the social amoeba Dictyostelium discoideum. This contribution provides an update on dictyBase that has been previously presented. During the past 3 years, dictyBase has taken significant strides toward becoming a genome portal for the whole Amoebozoa clade. In its latest release, dictyBase has scaled up to host multiple Dictyostelids, including Dictyostelium purpureum [Sucgang, Kuo, Tian, Salerno, Parikh, Feasley, Dalin, Tu, Huang, Barry et al.(2011) (Comparative genomics of the social amoebae Dictyostelium discoideum and Dictyostelium purpureum. Genome Biol., 12, R20)], Dictyostelium fasciculatum and Polysphondylium pallidum [Heidel, Lawal, Felder, Schilde, Helps, Tunggal, Rivero, John, Schleicher, Eichinger et al. (2011) (Phylogeny-wide analysis of social amoeba genomes highlights ancient origins for complex intercellular communication. Genome Res., 21, 1882-1891)]. The new release includes a new Genome Browser with RNAseq expression, interspecies Basic Local Alignment Search Tool alignments and a unified Basic Local Alignment Search Tool search for cross-species comparisons.

dictyBase update 2011: web 2.0 functionality and the initial steps towards a genome portal for the Amoebozoa.

dictyBase (http://www.dictybase.org), the model organism database for Dictyostelium, aims to provide the broad biomedical research community with well integrated, high quality data and tools for Dictyostelium discoideum and related species. dictyBase houses the complete genome sequence, ESTs, and the entire body of literature relevant to Dictyostelium. This information is curated to provide accurate gene models and functional annotations, with the goal of fully annotating the genome to provide a 'reference genome' in the Amoebozoa clade. We highlight several new features in the present update: (i) new annotations; (ii) improved interface with web 2.0 functionality; (iii) the initial steps towards a genome portal for the Amoebozoa; (iv) ortholog display; and (v) the complete integration of the Dicty Stock Center with dictyBase.

The Gene Ontology knowledgebase in 2023.

The Gene Ontology (GO) knowledgebase (http://geneontology.org) is a comprehensive resource concerning the functions of genes and gene products (proteins and noncoding RNAs). GO annotations cover genes from organisms across the tree of life as well as viruses, though most gene function knowledge currently derives from experiments carried out in a relatively small number of model organisms. Here, we provide an updated overview of the GO knowledgebase, as well as the efforts of the broad, international consortium of scientists that develops, maintains, and updates the GO knowledgebase. The GO knowledgebase consists of three components: (1) the GO-a computational knowledge structure describing the functional characteristics of genes; (2) GO annotations-evidence-supported statements asserting that a specific gene product has a particular functional characteristic; and (3) GO Causal Activity Models (GO-CAMs)-mechanistic models of molecular "pathways" (GO biological processes) created by linking multiple GO annotations using defined relations. Each of these components is continually expanded, revised, and updated in response to newly published discoveries and receives extensive QA checks, reviews, and user feedback. For each of these components, we provide a description of the current contents, recent developments to keep the knowledgebase up to date with new discoveries, and guidance on how users can best make use of the data that we provide. We conclude with future directions for the project.

dictyBase--a Dictyostelium bioinformatics resource update.

dictyBase (http://dictybase.org) is the model organism database for Dictyostelium discoideum. It houses the complete genome sequence, ESTs and the entire body of literature relevant to Dictyostelium. This information is curated to provide accurate gene models and functional annotations, with the goal of fully annotating the genome. This dictyBase update describes the annotations and features implemented since 2006, including improved strain and phenotype representation, integration of predicted transcriptional regulatory elements, protein domain information, biochemical pathways, improved searching and a wiki tool that allows members of the research community to provide annotations.

Annotating Putative D. discoideum Proteins Using I-TASSER.

Using Gene Ontology annotation in any aspect or using any evidence code, we found that approximately 14% percent of predicted D. discoideum proteins have no GO annotations and no obvious similarity to any annotated protein across diverse organisms. We have been systematically examining these unannotated protein sequences using software that predicts a protein structure and then compares the predicted structure to known structures.

SadA, a novel adhesion receptor in Dictyostelium.

Little is known about cell-substrate adhesion and how motile and adhesive forces work together in moving cells. The ability to rapidly screen a large number of insertional mutants prompted us to perform a genetic screen in Dictyostelium to isolate adhesion-deficient mutants. The resulting substrate adhesion-deficient (sad) mutants grew in plastic dishes without attaching to the substrate. The cells were often larger than their wild-type parents and displayed a rough surface with many apparent blebs. One of these mutants, sadA-, completely lacked substrate adhesion in growth medium. The sadA- mutant also showed slightly impaired cytokinesis, an aberrant F-actin organization, and a phagocytosis defect. Deletion of the sadA gene by homologous recombination recreated the original mutant phenotype. Expression of sadA-GFP in sadA-null cells restored the wild-type phenotype. In sadA-GFP-rescued mutant cells, sadA-GFP localized to the cell surface, appropriate for an adhesion molecule. SadA contains nine putative transmembrane domains and three conserved EGF-like repeats in a predicted extracellular domain. The EGF repeats are similar to corresponding regions in proteins known to be involved in adhesion, such as tenascins and integrins. Our data combined suggest that sadA is the first substrate adhesion receptor to be identified in Dictyostelium.

The dictyostelium kinome--analysis of the protein kinases from a simple model organism.

Dictyostelium discoideum is a widely studied model organism with both unicellular and multicellular forms in its developmental cycle. The Dictyostelium genome encodes 285 predicted protein kinases, similar to the count of the much more advanced Drosophila. It contains members of most kinase classes shared by fungi and metazoans, as well as many previously thought to be metazoan specific, indicating that they have been secondarily lost from the fungal lineage. This includes the entire tyrosine kinase-like (TKL) group, which is expanded in Dictyostelium and includes several novel receptor kinases. Dictyostelium lacks tyrosine kinase group kinases, and most tyrosine phosphorylation appears to be mediated by TKL kinases. About half of Dictyostelium kinases occur in subfamilies not present in yeast or metazoa, suggesting that protein kinases have played key roles in the adaptation of Dictyostelium to its habitat. This study offers insights into kinase evolution and provides a focus for signaling analysis in this system.

dictyBase and the Dicty Stock Center (version 2.0) - a progress report.

After serving the Dictyostelium community for many years, the first version of dictyBase (Chisholm et al., 2006; Fey et al., 2006) was in need of a decisive update. The original dictyBase software was not adaptable to more current demands such as handling the import of large-scale data from recently sequenced genomes, keeping up with changes in the Gene Ontology (GO), or handling the automatic annotation of over 20,000 new strains. Therefore, we have embarked on a complete overhaul of dictyBase. The new infrastructure will allow the introduction of new data, such as more expressive GO annotations and Dictyostelium disease orthologs. A modern user interface aims to streamline usage of the database including orders from the Dicty Stock Center (DSC). New displays will allow novel views including the combination of data in two new tools. With the underlying software infrastructure now in place, dictyBase software engineers and curators are currently adding the user interfaces, new tools and content pages for the evolving version 2.0 of dictyBase. This review highlights the emerging status of the new dictyBase, updated pages and annotations that will soon be available in the new environment, an overview of our annotation procedures, and plans to involve the community in curation efforts.

Annotation of gene product function from high-throughput studies using the Gene Ontology.

High-throughput studies constitute an essential and valued source of information for researchers. However, high-throughput experimental workflows are often complex, with multiple data sets that may contain large numbers of false positives. The representation of high-throughput data in the Gene Ontology (GO) therefore presents a challenging annotation problem, when the overarching goal of GO curation is to provide the most precise view of a gene's role in biology. To address this, representatives from annotation teams within the GO Consortium reviewed high-throughput data annotation practices. We present an annotation framework for high-throughput studies that will facilitate good standards in GO curation and, through the use of new high-throughput evidence codes, increase the visibility of these annotations to the research community.

An anatomy ontology to represent biological knowledge in Dictyostelium discoideum.

BACKGROUND: Dictyostelium discoideum is a model system for studying many important physiological processes including chemotaxis, phagocytosis, and signal transduction. The recent sequencing of the genome has revealed the presence of over 12,500 protein-coding genes. The model organism database dictyBase hosts the genome sequence as well as a large amount of manually curated information. RESULTS: We present here an anatomy ontology for Dictyostelium based upon the life cycle of the organism. CONCLUSION: Anatomy ontologies are necessary to annotate species-specific events such as phenotypes, and the Dictyostelium anatomy ontology provides an essential tool for curation of the Dictyostelium genome.

dictyBase, the model organism database for Dictyostelium discoideum.

dictyBase (http://dictybase.org) is the model organism database (MOD) for the social amoeba Dictyostelium discoideum. The unique biology and phylogenetic position of Dictyostelium offer a great opportunity to gain knowledge of processes not characterized in other organisms. The recent completion of the 34 MB genome sequence, together with the sizable scientific literature using Dictyostelium as a research organism, provided the necessary tools to create a well-annotated genome. dictyBase has leveraged software developed by the Saccharomyces Genome Database and the Generic Model Organism Database project. This has reduced the time required to develop a full-featured MOD and greatly facilitated our ability to focus on annotation and providing new functionality. We hope that manual curation of the Dictyostelium genome will facilitate the annotation of other genomes.

A tripeptidyl peptidase 1 is a binding partner of the Golgi pH regulator (GPHR) in Dictyostelium.

Mutations in tripeptidyl peptidase 1 (TPP1) have been associated with late infantile neuronal ceroid lipofuscinosis (NCL), a neurodegenerative disorder. TPP1 is a lysosomal serine protease, which removes tripeptides from the N-terminus of proteins and is composed of an N-terminal prodomain and a catalytic domain. It is conserved in mammals, amphibians, fish and the amoeba Dictyostelium discoideum. D. discoideum harbors at least six genes encoding TPP1, tpp1A to tpp1F We identified TPP1F as binding partner of Dictyostelium GPHR (Golgi pH regulator), which is an evolutionarily highly conserved intracellular transmembrane protein. A region encompassing the DUF3735 (GPHR_N) domain of GPHR was responsible for the interaction. In TPP1F, the binding site is located in the prodomain of the protein. The tpp1F gene is transcribed throughout development and translated into a polypeptide of ∼65 kDa. TPP1 activity was demonstrated for TPP1F-GFP immunoprecipitated from D. discoideum cells. Its activity could be inhibited by addition of the recombinant DUF3735 domain of GPHR. Knockout tpp1F mutants did not display any particular phenotype, and TPP1 activity was not abrogated, presumably because tpp1B compensates as it has the highest expression level of all the TPP1 genes during growth. The GPHR interaction was not restricted to TPP1F but occurred also with TPP1B. As previous reports show that the majority of the TPP1 mutations in NCL resulted in reduction or loss of enzyme activity, we suggest that Dicyostelium could be used as a model system in which to test new reagents that could affect the activity of the protein and ameliorate the disease.

dictyBase and the Dicty Stock Center.

dictyBase is the model organism database that houses all the sequence and associated data for Dictyostelium discoideum, including literature, researchers, and strains from the Dicty Stock Center. The database makes it possible to connect genes, proteins, and publications and is designed to address the needs of biologists and bioinformaticists alike. We provide tools for retrieving and analyzing data and strive to compile the highest quality, most up-to-date information. Here we will describe how to navigate the website and mine the extensive database to help users make optimal use of this invaluable resource.

dictyBase: a new Dictyostelium discoideum genome database.

Dictyostelium discoideum is a powerful and genetically tractable model system used for the study of numerous cellular molecular mechanisms including chemotaxis, phagocytosis and signal transduction. The past 2 years have seen a significant expansion in the scope and accessibility of online resources for Dictyostelium. Recent advances have focused on the development of a new comprehensive online resource called dictyBase (http://dictybase.org). This database not only provides access to genomic data including functional annotation of genes, gene products and chromosomal mapping, but also to extensive biological information such as mutant phenotypes and corresponding reference material. In conjunction with additional sites (http://genome. imb-jena.de/dictyostelium/, http://dictyensembl. bioch.bcm.tmc.edu and http://www.sanger.ac.uk/Projects/D_discoideum/) from the genome sequencing and assembly centers, these improvements have expanded the scope of the Dictyostelium databases making them accessible and useful to any researcher interested in comparative and functional genomics in metazoan organisms.

One stop shop for everything Dictyostelium: dictyBase and the Dicty Stock Center in 2012.

dictyBase (http://dictybase.org), the model organism database for Dictyostelium discoideum, includes the complete genome sequence and expression data for this organism. Relevant literature is integrated into the database, and gene models and functional annotation are manually curated from experimental results and comparative multigenome analyses. dictyBase has recently expanded to include the genome sequences of three additional Dictyostelids and has added new software tools to facilitate multigenome comparisons. The Dicty Stock Center, a strain and plasmid repository for Dictyostelium research, has relocated to Northwestern University in 2009. This allowed us integrating all Dictyostelium resources to better serve the research community. In this chapter, we will describe how to navigate the Web site and highlight some of our newer improvements.

An overview of the BioCreative 2012 Workshop Track III: interactive text mining task.

In many databases, biocuration primarily involves literature curation, which usually involves retrieving relevant articles, extracting information that will translate into annotations and identifying new incoming literature. As the volume of biological literature increases, the use of text mining to assist in biocuration becomes increasingly relevant. A number of groups have developed tools for text mining from a computer science/linguistics perspective, and there are many initiatives to curate some aspect of biology from the literature. Some biocuration efforts already make use of a text mining tool, but there have not been many broad-based systematic efforts to study which aspects of a text mining tool contribute to its usefulness for a curation task. Here, we report on an effort to bring together text mining tool developers and database biocurators to test the utility and usability of tools. Six text mining systems presenting diverse biocuration tasks participated in a formal evaluation, and appropriate biocurators were recruited for testing. The performance results from this evaluation indicate that some of the systems were able to improve efficiency of curation by speeding up the curation task significantly (∼1.7- to 2.5-fold) over manual curation. In addition, some of the systems were able to improve annotation accuracy when compared with the performance on the manually curated set. In terms of inter-annotator agreement, the factors that contributed to significant differences for some of the systems included the expertise of the biocurator on the given curation task, the inherent difficulty of the curation and attention to annotation guidelines. After the task, annotators were asked to complete a survey to help identify strengths and weaknesses of the various systems. The analysis of this survey highlights how important task completion is to the biocurators' overall experience of a system, regardless of the system's high score on design, learnability and usability. In addition, strategies to refine the annotation guidelines and systems documentation, to adapt the tools to the needs and query types the end user might have and to evaluate performance in terms of efficiency, user interface, result export and traditional evaluation metrics have been analyzed during this task. This analysis will help to plan for a more intense study in BioCreative IV.