Structured and graphical queries for Drosophila neuroscience data

Disorders of the nervous system account for the single biggest cost to the National Health Service and affect one in three people in the developed world at some point in their life. Designing treatment therapies requires us to understand first how the brain works yet it is the most complex organ known and thus simpler models are essential. The brain of the fruit fly, Drosophila melanogaster, provides an excellent model system for studying how brains function. It is orders of magnitude smaller and simpler than a mammalian brain, yet genetically it is remarkably similar. Moreover, like mammalian brains, is capable of learning and is remodelled in response to experience and environmental context. There is a large history of research into the brain of Drosophila and other insects. This gives a firm foundation to modern studies of the genetic basis of how the Drosophila brain is built and functions. Such studies take advantage of an increasingly powerful array of genetic techniques that allow specific regions, cells and genes to be disrupted thus measuring their function. At the same time, increasingly sophisticated imaging techniques are revealing the structure of the Drosophila brain in ever-finer detail. The sheer volume and microscopic detail of the data being collected poses a problem to researchers wanting to build and communicate coherent models of brain function or to share the tools they use for their experiments. Navigating through the blizzard of new information is made particularly difficult by the varying and often confusing nomenclature that is an inevitable feature of a complicated field with such a long history. We aim to remedy this by building a web-based atlas and search tool - Virtual Fly Brain. Users will be able to navigate by clicking on labelled regions in a 3D reference image of a brain, or by searching and browsing a structured vocabulary which names brain regions and the brain cells which connect them. Users will be able to highlight brain regions in various colours by choosing terms in the vocabulary they find through browsing and searching. Choosing a term will also prompt the display of various information related to that term: links to additional images; written definitions with references to the scientific papers they come from; synonyms and comments to help disambiguate confusing or conflicting usage of terms. Users will be able to use the lists of terms generated by these queries to search for related data stored in FlyBase, the main genetic database of the Drosophila community. This will allow them to find genes expressed in structures on the list or which are known to be involved in the construction or function of these structures. It will also allow them to search for sophisticated genetic reagents which target these structures. Finally, we will provide tools to help new researchers and students to explore and learn how the brain is organised and allow expert users to label their own data using our structured vocabulary and for.

The amount and complexity of data being produced on the structure, development and connectivity of the Drosophila brain means that biologists will increasingly need tools to help them search, integrate and synthesise this data into models of how the brain works. The neuroanatomical working group is about to agree upon a new set of defined terms and boundaries for the major neuropil of the adult fly brain and presumably will follow with the tract systems and developmental histories. This is an essential first step but these conclusions need to be integrated into a formal ontology that extends the existing whole body/organism ontology currently embedded in FlyBase. Further, the ontology needs to be augmented with the development of appropriate data structures, query tools and visualisation software. Hence, we do not propose a new atlas or database of expression patterns (these already exist, or will be developed by others), rather a means to integrate any such resource with a centralised query system. We will also have to extend the FlyBase anatomy ontology to support neural specific features (particularly connectivity information). This will allow new more complex queries to be developed returning data on information flow in the CNS. The centralised query system will also link terms to phenotypic and gene information within FlyBase as well as images from external databases or atlases that use the ontology terms agreed by the nomenclature working group. We will develop a series of tools for building and visualising queries based on neuroanatomical terms. All software/tools produced will be open-source so that they can be re-used or extended by the community. As part of the study we will also revise and extend the annotation of Drosophila neuroscience studies indexed in FlyBase which is currently lagging behind other areas. Joint with BB/G02233X/1.