This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5).
Researchers at Rice University have been awarded a grant for an interdisciplinary project in software development, evolutionary biology and comparative genomics that will create new computational methods and web-based resources for comparing and interpreting how genes are organized in the chromosomes of humans, other animals, plants and other complex organisms. Biologists studying the large-scale organization of genomes -- the arrangement of genes on chromosomes -- recently discovered that species that had diverged more than 500 million years ago still have genomes that are organized in similar ways. It is not known whether the conservation is due to a very slow decay of a neutral feature of genome organization, or due to the action of selection through an unknown functional link between genome organization and phenotype. The project will take two new approaches to the problem. The first approach uses a heuristic search procedure to identify the most parsimonious historical scenario explaining the data. The second approach uses Bayesian Markov-chain Monte Carlo to estimate the probabilities of historical scenarios given a model of genome evolution. The tools and databases created by this project will allow scientists to more easily compare and contrast the structure of genomes. In particular, the tools will allow scientists to do side-by-side studies of both modern and reconstructed ancient genomes.
By comparing and contrasting the organizational structure of genomes, scientists hope to better understand evolution, biodiversity and the mechanisms species use to fight stress and disease. This project will provide interdisciplinary training in software development, evolutionary biology and comparative genomics to the researchers and students who participate. The web-based interface to the results will be used as a source of projects and exercises in an undergraduate course in evolution and bioinformatics taught by the project leader. To learn more about this project, including the most recent progress, visit the project web site at http://putnamlab.org/genome-evolution.
