COMPUTATIONAL GENOMICS ANALYSIS AND TRAINING (CGAT)AT THE MRC FUNCTIONAL GENOMICS UNIT

CGAT's mission will be to reveal the significance of high-throughput sequence in health and disease, whilst providing training opportunities for pre- and post-doctoral scientists. The Programme will provide access to genome analysis for those UK biologists and clinicians who are less used to managing, manipulating and analysing extremely large sequence data sets. CGAT will take advantage of the analytical expertise readily available both from within the MRC Functional Genomics Unit, and from strong interactions with others in the UK genomics research community. The Strategic Programme will aim both to fulfil the promise of high-throughput genome data in answering the most important questions in genetics and human disease, and to train a new generation of genomics researchers.

CGAT will provide expertise and analytical capacity to UK-based research groups planning to use or already using next-generation sequencing data. At the same time CGAT will train post-doctoral researchers in the analysis and biological interpretation of genome-scale data sets. Each project will be highly collaborative, and focused on gleaning important biological conclusions from large data sets. Recent years have seen an accelerating growth in sequencing capacity, whilst sequencing costs have plummeted. As a result, powerful techniques and assays based on DNA sequencing (ChIP-Seq, RNA-Seq, genome resequencing etc.) are being developed that add greatly to the experimental toolkit of biologists and clinicians. However, while becoming increasingly affordable, these new methods require substantial computational infrastructure and expertise that are not available, currently, in many experimental research groups. Indeed, UK-wide there remains a considerable shortage of bioinformaticians able to process these large data sets. CGAT aims to help meet these considerable needs. For each collaboration, CGAT provides expertise in computational genomics, the computational infrastructure and a dedicated post-doctoral researcher. Collaborators contribute sequence data sets and their unique knowledge of their specific research area. Taken together, the result will be high-quality research culminating in high-profile journals under a joint-authorship model. CGAT builds on the experience of the Ponting group in comparative genomics and next-generation sequencing analysis. The group has a strong back-ground in computational sequence analysis and evolutionary biology with a proven track record of translating large scale sequencing data into diverse biological contexts. Post-doctoral trainees in the CGAT group will benefit from in-house training, but also the biological insights of collaborators. Working on a variety of projects, trainees will accumulate expertise in genome sequencing-related fields, as well as high profile publications.