iBeetle-Base: Building an Interconnected, Interactive and Extendable Repository for Phenotypic Data

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The development of an organism and its physiology are governed by genes. Hence, understanding how genes function and how they are regulated is required to understand arthropod development, physiology and evolution. Such knowledge then allows devising strategies to fight insect pests and vectors, for instance revealing novel target genes for pest control. Genomic sequences are available for many organisms and integrated genomic databases allow for cross-species comparisons of gene sequences. However, large scale data on the function of genes (phenotypic data) had been restricted to very few highly established model systems with the fly Drosophila melanogaster being the only representative of arthropods. With the DFG funded iBeetle screen we have been using RNA interference (RNAi) in the red flour beetle Tribolium castaneum to generate a genome wide dataset on gene function. This represents the first large scale phenotypic dataset in any arthropod outside of Drosophila. Indeed, the iBeetle screen has led to the identification of unexpected gene functions and to the detection of novel target genes for pest control. This phenotypic dataset is stored and presented at iBeetle-Base. Beyond project related data iBeetle-Base provides additional information useful for studying gene functions within and outside the community like for instance an integrated genome browser, sequence data, homology information and tools, links and resources for the community. In order to integrate iBeetle-Base (http://ibeetle-base.uni-goettingen.de) with other resources we have established mutual links with FlyBase and we have installed a function where specialists of the community can contribute GO terms for their genes of interest.With this project, we plan to ensure long-term availability, interoperability and extendability of iBeetle-Base fulfilling the need for phenotypic data repositories. Updating the software architecture to microservices providing open APIs for the data, make it easier to extend and to maintain. Integration of ontologies and other measures will allow for interoperability with other data, opening the possibility of cross species comparisons for instance with the fly. Further, we plan to enrich the data with GO terms and other information taking into consideration the needs of the community. Importantly, for the database to grow with the constant flow of new results in the field, we want to allow the community to add data (Community Edition). Together, these measures significantly increase the value of the data for the Tribolium community and beyond. Further, the developed structure and tools can be used as template for other arthropod phenotypic data repositories, the common APIs of which will allow for cross species queries and research.