User:Jt3

'On the redundancy of duplicated genes and the evolutionary conservation of genetic interactions in C. elegans'' ''' Julia Tischler, Ben Lehner and Andrew G Fraser The Wellcome Trust Sanger Institute, Hinxton, Cambridge, United Kingdom, CB10 1SA

Systematic analyses of loss-of-function phenotypes have been carried out for almost all genes in S. cerevisiae, C. elegans, and D. melanogaster, and there are major efforts to make a comprehensive collection of mouse knockouts. While such studies greatly expand our knowledge of single gene function, they do not address redundancy in genetic networks, nor do they attempt to identify genetic interactions. Developing tools for the systematic mapping of genetic interactions is thus a key step for exploring the relationship between genotype and phenotype. We thus sought to establish protocols for targeting multiple genes simultaneously by RNA interference (RNAi) in C. elegans to provide a platform for the systematic identification of genetic interactions in this key animal model system. We set up conditions for RNAi that allow us to target multiple genes in the same animal (‘combinatorial RNAi’) in a high throughput setting and to detect the great majority of a subset of previously known synthetic genetic interactions. We then used this assay to test the redundant functions of genes that have been duplicated in the genome of C. elegans since divergence from either S. cerevisiae or D. melanogaster, and identified 16 pairs of duplicated genes that are at least partially functionally redundant. Intriguingly, 14 of these redundant gene pairs were duplicated before the split of C. elegans and C. briggsae 80-110 million years ago. Our data provide the first systematic investigation into the redundancy of duplicated genes in any organism and strongly support population genetics models, which suggest that redundancy can be maintained over substantial periods of evolutionary time. Furthermore, we set out to test whether systematically compiled yeast genetic interaction data can predict genetic interactions in the worm. We will present these data.