One of the major challenges facing biomedical researchers is how to effectively utilize the growing tsunami of genome-wide data that is becoming available as DNA sequencing costs plunge and volumes of available data expand. One solution to this challenge is the development of robust databases that organize, integrate, curate and validate this data, while providing tools to search, visualize and explore this extremely valuable data. dictyBase is the model organism database that uses the genome sequence of Dictyostelium discoiedum to organize biological knowledge resulting from studies using Dictyostelium and related species. Investigators using Dictyostelium in bench research comprise a vibrant community of over 1500 researchers. Dictyostelium's position on the tree of life provides a unique evolutionary perspective that provides great value for evolutionary and computational biologists wishing to employ comparative genomics approaches. Dictyostelium has contributed to improving biological understanding of a variety of fundamental processing including cell migration, phagocytosis, cell-cell and intracellular signaling, cellular differentiation, self-nonself recognition and multicellular morphogenesis. Dictyostelium research has important medical relevance, having contributed, for example, to our understanding of mitochondrial-related diseases, host-pathogen interactions, especially for intracellular pathogens, and the mode of action of mood stabilizing drugs and defining the pathways targeted by bisphosphonates. dictyBase has become the trusted resource for investigators seeking Dictyostelium genome information, annotations, and functional data, having been accessed over 6 million times by over 280,000 independent IP addresses. This application seeks continued funding for dictyBase to allow completion of the annotation of all gene models and integration of important new data types. dictyBase seeks to provide innovative tools, strategies and high quality annotations that enable bench researchers to effectively benefit from rapidly increasing collection of available data.
Specific aims for the next funding period are to (1) Annotate the D. discoideum genome and curate experimental results from the literature, (2) Integrate and display novel large data sets including genome sequences for strains and related species, RNAseq based expression data, proteomics data and protein-protein interactions;(3) Maximize the utility of dictyBase to the biomedical research community. Successful completion of these aims will provide a critical resource for biomedical research and will maximize the investment of the NIH in research using Dictyostelium.

Public Health Relevance

dictyBase enables efficient biomedical research by organizing, integrating, and validating genome-wide data such as genome sequences, proteomics data, RNAseq transciptomics data and functional data captured by automated and manual literature curation and making this data available in a readily searchable format. The work proposed in this application is focused on increasing the variety and extent of datasets that dictyBase integrates, improving interfaces and searchability of the data and making that data widely available to the biomedical research community.

National Institute of Health (NIH)
National Institute of General Medical Sciences (NIGMS)
Research Project (R01)
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Genomics, Computational Biology and Technology Study Section (GCAT)
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Maas, Stefan
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Northwestern University at Chicago
Anatomy/Cell Biology
Schools of Medicine
United States
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