1- Scientific context and project objectives

In accordance with the E-nnovergne document, section 7.2, Re-source Auvergne, in the framework of the Modelling Unit, offers to develop a programme for pooling national and international transcriptome resources for enhancing the skills of life science laboratories and biotechnological businesses in Auvergne. This data is of particular interest for the pharmaceutical and food processing industries as it concerns specific diseases or highly specific aspects. National and international studies previously conducted by the University of Auvergne and INFOBIOGEN have identified some 2,000 sources of transcriptome data, 990 of which have been deemed useable. The collection of sources only concerns unprocessed data obtained from converting the image (analogical) into a digital value. Since this is characterised by a very precise data format, only this criterion will be used to select the useable sources. For information, this data mainly concerns the analysis of the level of gene expression, which involves measuring a person’s level of gene expression at a given moment. The type of sources points to a prospect of combining data in an information system of specialist databases. The models of bases defined during the implementation of the system architecture may be exported for secondary bases so as to preserve the uniformity of the data structures. This platform will enable considerable savings, with the possibility for each user to access the results of his work directly and to achieve a critical mass to obtaining international recognition.

2- Project description

The project comprises 5 successive stages: updating the catalogue of useable data sources, selecting the useful bioinformatics data sources, defining and programming the structure of the regional database, creating a platform of transcriptome data processing algorithms and forming local structures for using this sytem. More precisely, depending on the needs of local businesses and laboratories, this data may be grouped into 5 families based on technology (microarrays or SAGE) and type of analysis (Static, Dynamic or as a separate component). The compilation of this data set is particularly innovative. It has already been requested by a Cluster Euréka programme called INSYSBIO, involving all of the stakeholders in the pharmaceutical sector. It has two major advantages that will be exploited: merging data that is useful but currently not very accessible for laboratories and businesses, and constructing models of data from high-speed analysis platforms specific to local businesses and laboratories. This project will therefore make it possible to combine past, present and future data in local businesses’ and laboratories’ own transcriptome application programs.

3- Public or controlled use

The stored data will be for public use and the information system created may be duplicated for future applications. The main idea of the project is to give local structures exclusive use of the data.

4- Expected results

Transcriptome knowledge is entirely relevant when setting up the medical research platform. Indeed, it seems increasingly likely that one of the future pathways of medical diagnosis lies in the development of transcriptome technologies. Accordingly, the presence of a transcriptome analysis platform would enhance the data owned by laboratories and businesses and future subsequent developments (Jean Perrin Centre, U 384, CIC, etc..) and put together diagnosis kits (Jean Perrin Centre, U 384, CIC, etc.), thereby boosting the creation of businesses (U 384). Lastly, the transfer of technology should create a competence cluster for teaching statistics applied to transcriptome analysis problems. The statistical component seems instrumental in the effective control of the bioinformatics tools presented in this document.

LifeGrid, the regional information system