Functional genomics, systems biology and genetic medicine
The increasing availability of genomic and allied data for many organisms is revolutionising the way that biological and medical research is carried out. Functional genomics aims to define gene function, often making use of the vast amount of information now available through high-throughput experimental methods for mapping and sequencing genomes and approaches for characterising genes' function, their organisation and expression under different conditions. This field has benefitted from the development of 'omic' approaches, including transcriptomics, proteomics and metabolomics, for the parallel analysis of biological intermediates. Together these functional genomic techniques contribute to the growing field of systems biology. These techniques are also being increasingly applied to understanding disease in human populations as part of genetic medicine.
The functional genomic tools of transcriptomics, proteomics and metabolomics have the potential to provide a way for understanding biological processes at a systems level. In addition, these techniques also provide the raw data for mathematical modelling approaches. Underpinning all aspects of this revolution is a computational infrastructure that embraces computer science, automation and statistics. Researchers draw on the high performance (HPC) and grid (CamGrid) computing resources in the University. In addition there is a lively scientific computing community in the form of SciCompCam. There are links to almost all other themes, as the new technology is applied to a wide range of research.
The Cambridge Systems Biology Centre was created to bring together experience in high-throughput 'omics, computational biology and mathematical modelling. It houses the FlyChip microarray facility, the Cambridge Centre for Proteomics and other research groups. Many other microarray and genotyping facilities are housed elsewhere. Methylation assays, comparative genomic hybridization and SNP analyses are amongst the techniqes exploited. We expect microarrays to be replaced with the latest high throughput sequencing technologies for looking at areas such as gene expression and DNA and chromatin modifications. Proteomics uses difference gel electrophoresis, differential stable isotope labelling, multidimensional chromatographic fractionation and protein identification using mass spectrometry and a range of other methods. Metabolites may contain a wide range of chemical groups, and have a huge range of concentrations within the cell. Currently no one technique can provide a complete snapshot of metabolism in anything but the simplest cases. Approaches used include high field NMR spectroscopy including hyperpolarized carbon-13, gas chromatography mass spectrometry, liquid chromatography mass spectrometry and capillary electrophoresis. Ongoing studies in this area include understanding gene function in yeast, modifying plant metabolism to produce biofuels more efficiently, quorum sensing in bacteria and understanding the multifactorial effects of complex diseases such as type II diabetes and obesity.
Increased integration between experimental science and theoretical biology is also being achieved through the Cambridge Computational Biology Institute (CCBI). A key goal is to develop the interactions between researchers in the physical, mathematical and computing sciences with biologists and medical researchers to ensure world class data analysis and experimental design as well as providing theoretical researchers with access to validated high quality data sets. Bioinformatics research covers all aspects of computational genomics including sequence analysis, database development, data analysis, computational structural biology and theoretical modelling. There is a long-standing bioinformatics service providing core databases and software together with specialised training.
Genetic medicine is the subject of study in several departments and institutes. There are close interactions between the University and NHS departments, with many investigators holding clinical positions as well as being active researchers. There is a broad range of projects involving functional biology of genetic disease, as well as the applications of genetics to diagnostic and therapeutic approaches to disease. Population genetic studies, linked to the epidemiology and public health theme, feed into genetic medicine both in terms of hypothesis generation and testing. Major areas of research include autoimmune disease, diabetes, obesity, cancer, renal and musculoskeletal diseases, and neurodegeneration.