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

dictyBase, the model organism database for Dictyostelium discoideum

dictyBase () 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

The Actinome of Dictyostelium discoideum in Comparison to Actins and Actin-Related Proteins from Other Organisms

Actin belongs to the most abundant proteins in eukaryotic cells which harbor usually many conventional actin isoforms as well as actin-related proteins (Arps). To get an overview over the sometimes confusing multitude of actins and Arps, we analyzed the Dictyostelium discoideum actinome in detail and compared it with the genomes from other model organisms. The D. discoideum actinome comprises 41 actins and actin-related proteins. The genome contains 17 actin genes which most likely arose from consecutive gene duplications, are all active, in some cases developmentally regulated and coding for identical proteins (Act8-group). According to published data, the actin fraction in a D. discoideum cell consists of more than 95% of these Act8-type proteins. The other 16 actin isoforms contain a conventional actin motif profile as well but differ in their protein sequences. Seven actin genes are potential pseudogenes. A homology search of the human genome using the most typical D. discoideum actin (Act8) as query sequence finds the major actin isoforms such as cytoplasmic beta-actin as best hit. This suggests that the Act8-group represents a nearly perfect actin throughout evolution. Interestingly, limited data from D. fasciculatum, a more ancient member among the social amoebae, show different relationships between conventional actins. The Act8-type isoform is most conserved throughout evolution. Modeling of the putative structures suggests that the majority of the actin-related proteins is functionally unrelated to canonical actin. The data suggest that the other actin variants are not necessary for the cytoskeleton itself but rather regulators of its dynamical features or subunits in larger protein complexes

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

Text mining in the biocuration workflow: applications for literature curation at WormBase, dictyBase and TAIR

WormBase, dictyBase and The Arabidopsis Information Resource (TAIR) are model organism databases containing information about Caenorhabditis elegans and other nematodes, the social amoeba Dictyostelium discoideum and related Dictyostelids and the flowering plant Arabidopsis thaliana, respectively. Each database curates multiple data types from the primary research literature. In this article, we describe the curation workflow at WormBase, with particular emphasis on our use of text-mining tools (BioCreative 2012, Workshop Track II). We then describe the application of a specific component of that workflow, Textpresso for Cellular Component Curation (CCC), to Gene Ontology (GO) curation at dictyBase and TAIR (BioCreative 2012, Workshop Track III). We find that, with organism-specific modifications, Textpresso can be used by dictyBase and TAIR to annotate gene productions to GO's Cellular Component (CC) ontology

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

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

RNAcentral : a hub of information for non-coding RNA sequences

RNAcentral is a comprehensive database of non-coding RNA (ncRNA) sequences, collating information on ncRNA sequences of all types from a broad range of organisms. We have recently added a new genome mapping pipeline that identifies genomic locations for ncRNA sequences in 296 species. We have also added several new types of functional annotations, such as tRNA secondary structures, Gene Ontology annotations, and miRNA-target interactions. A new quality control mechanism based on Rfam family assignments identifies potential contamination, incomplete sequences, and more. The RNAcentral database has become a vital component of many workflows in the RNA community, serving as both the primary source of sequence data for academic and commercial groups, as well as a source of stable accessions for the annotation of genomic and functional features. These examples are facilitated by an improved RNAcentral web interface, which features an updated genome browser, a new sequence feature viewer, and improved text search functionality. RNAcentral is freely available at https://rnacentral.org