Lecture 10: The European Bioinformatics Institute - "Big data" for biomedical sciences

Part 1: Big data for biomedical sciences (Tom Hancocks) Ten years ago witnessed the completion of the first international 'Big Biology' project that sequenced the human genome. In the years since biological sciences, have seen a vast growth in data. In the coming years advances will come from integration of experimental approaches and the translation into applied technologies is the hospital, clinic and even at home. This talk will examine the development of infrastructure, physical and virtual, that will allow millions of life scientists across Europe better access to biological data Tom studied Human Genetics at the University of Leeds and McMaster University, before completing an MSc in Analytical Genomics at the University of Birmingham. He has worked for the UK National Health Service in diagnostic genetics and in training healthcare scientists and clinicians in bioinformatics. Tom joined the EBI in 2012 and is responsible for the scientific development and delivery of training for the BioMedBridges project. Part 2: EBI for non-biologists (Jose M. Dana)) Bioinformatics is a relatively new field and, as such, many computer scientists/engineers are reluctant to contribute to it as they feel that a high knowledge of biology is required. Although a good knowledge of the science behind the data is always preferable, it is not compulsory. In this talk I'll try to show, using my own experience, how it is possible to get involved without a degree in biology or bioinformatics; Jose studied at Universidad de Almeria (Spain) where he obtained a M.Eng. in Computer Engineering. He was selected for the CERN Summer Student Programme 2005, spending 3 months at the CERN openlab working on compilers and software optimization. In 2006 he joined the CERN openlab again, being involved in compilers, high performance computing, software optimization and Grid Computing development. He was also involved in the organization of the CERN openlab Summer Student Programme from 2007 to 2009. In 2010 he joined the European Bioinformatics Institute (EBI) as Senior Software Engineer

Epimutation profiling in Beckwith-Wiedemann syndrome:relationship with assisted reproductive technology

BACKGROUND: Beckwith-Wiedemann syndrome (BWS) is a congenital overgrowth disorder associated with abnormalities in 11p15.5 imprinted genes. The most common cause is loss of methylation (epimutation) at the imprinting control centre 2 (IC2/KvDMR1). Most IC2 epimutations occur sporadically but an association with conception after assisted reproductive technologies (ART) has been reported. A subgroup of IC2 epimutation cases also harbour epimutations at other imprinting centres (ICs) outside of 11p15.5. We have investigated the relationship between these multiple epimutation cases (ME+), history of ART and clinical phenotype in a cohort of 187 BWS IC2 epimutation patients. RESULTS: Methylation analysis at PLAGL1, MEST and IGF2R ICs demonstrated an over-representation of patients with abnormally low methylation (8.5%, 12% and 6% respectively). At IGF2R some patients (2%) had gain of methylation but this was also detected in controls. Though there were no significant correlations between the methylation index (MIs) at the three ICs tested, a subset of patients appeared to be susceptible to multiple epimutations (ME+) and 21.2% of ME + patients had been conceived by ART compared to 4.5% (P = 0.0033) without additional epimutations. Methylation array profiling (Illumina Goldengate®) of patients and controls (excluding 11p15.5 loci) demonstrated significant differences between patients and controls. No significant associations were found between aspects of the BWS phenotype and individual epimutations but we describe a case presenting with a post-ART BWS-like phenotype in which molecular analysis demonstrated loss of paternal allele methylation at the 11p15.5 IC1 locus (IC1 regulates imprinting of IGF2 and H19). Loss of paternal allele methylation at the IC1 is the molecular finding associated with Silver-Russell syndrome whereas BWS is associated with gain of maternal allele methylation at IC1. Further analysis demonstrated epimutations at PLAGL1 and MEST consistent with the hypothesis that the presence of multiple epimutations may be of clinical relevance. CONCLUSIONS: These findings suggest that the ME + subgroup of BWS patients are preferentially, but not exclusively, associated with a history of ART and that, though at present, there are no clear epigenotype-phenotype correlations for ME + BWS patients, non-11p15.5 IC epimutations can influence clinical phenotype