Meeting Abstract
The increasing ease of generating genome-scale data has led to a huge increase in the number of organisms being developed as models for studying human biology. Given this increase, it is important to evaluate whole-genome sequence data from a broad array of organisms to determine their possible utility in investigating a particular human phenotype or disease. To address this, we have taken an evolutionary genomics approach to investigate patterns of disease-gene emergence and loss across the Metazoa, with a particular focus on these patterns in non-bilaterians, a group that is relatively underexplored in relation to questions in human health. We have identified orthologs across 49 taxa using a phylogenetically aware algorithm, then used these data to infer the age of origin of orthogroups containing a known human disease gene. On average, human disease genes appear to have a more ancient origin than the human genome as a whole, suggesting that a broad range of metazoans may be suitable genomic models for understanding these phenotypes. Some non-bilaterians, such as the cnidarians, have approximately the same percentage of these disease genes as some well-established model organisms, suggesting that they may be more suitable models when studying certain genetic pathways. Our work confirms that distinct subclasses of genes have distinct evolutionary histories, reinforcing the importance of considering different taxa in the context of specific biological questions. Finally, we have investigated the effects of methodological choices such as whether or not to include splice variation on our final inferences. Our results suggest that a broader range of metazoans than those currently used may prove to be useful for understanding the genomic bases of human diseases.
