Final Report Summary - DOSE (Dosage sensitive genes in evolution and disease)
We are in an era of “big data”. We now have genome sequences for lots of different species, and for lots of individual humans. The challenge and the opportunity of this era is to make sense of these data and to harness the information they contain to further our understanding of biology. In this project we took an evolutionary approach to reading and interpreting these genome sequences. By comparing across individuals and across species we can form a picture of the genome changes that have occurred over vertebrate evolution and also infer changes that were not possible because of biological constraints. A particular constraint that we were interested in was dosage constraint: this describes a situation where the amount of the gene product, as well as the correct gene sequence, is critical to the correct functioning of the gene. We reasoned that such constraints ought to be visible in tell-tale patterns of evolution over the vertebrate tree, and that identifying these dosage sensitive genes in this manner would be informative in the identification of dosage-sensitive human disease genes.
In the course of this project we were successful in identifying these evolutionary hallmarks of dosage-sensitive genes and showed that they are indeed often associated with human disease when there is a mutation that changes the number of copies. This is a powerful and efficient approach to quickly identify candidate human disease genes which can then be investigated further. In the course of this project we also developed new methods for the analysis of genome evolution which will be useful for many other projects.
In the course of this project we were successful in identifying these evolutionary hallmarks of dosage-sensitive genes and showed that they are indeed often associated with human disease when there is a mutation that changes the number of copies. This is a powerful and efficient approach to quickly identify candidate human disease genes which can then be investigated further. In the course of this project we also developed new methods for the analysis of genome evolution which will be useful for many other projects.