A Case for Evolutionary Genomics and the Comprehensive Examination of Sequence Biodiversity

TitleA Case for Evolutionary Genomics and the Comprehensive Examination of Sequence Biodiversity
Publication TypeJournal Articles
Year of Publication2000
AuthorsPollock DD, Eisen JA, Doggett NA, Cummings MP
JournalMolecular Biology and EvolutionMol Biol Evol
Pagination1776 - 1788
Date Published2000/12/01/
ISBN Number0737-4038, 1537-1719

Comparative analysis is one of the most powerful methods available for understanding the diverse and complex systems found in biology, but it is often limited by a lack of comprehensive taxonomic sampling. Despite the recent development of powerful genome technologies capable of producing sequence data in large quantities (witness the recently completed first draft of the human genome), there has been relatively little change in how evolutionary studies are conducted. The application of genomic methods to evolutionary biology is a challenge, in part because gene segments from different organisms are manipulated separately, requiring individual purification, cloning, and sequencing. We suggest that a feasible approach to collecting genome-scale data sets for evolutionary biology (i.e., evolutionary genomics) may consist of combination of DNA samples prior to cloning and sequencing, followed by computational reconstruction of the original sequences. This approach will allow the full benefit of automated protocols developed by genome projects to be realized; taxon sampling levels can easily increase to thousands for targeted genomes and genomic regions. Sequence diversity at this level will dramatically improve the quality and accuracy of phylogenetic inference, as well as the accuracy and resolution of comparative evolutionary studies. In particular, it will be possible to make accurate estimates of normal evolution in the context of constant structural and functional constraints (i.e., site-specific substitution probabilities), along with accurate estimates of changes in evolutionary patterns, including pairwise coevolution between sites, adaptive bursts, and changes in selective constraints. These estimates can then be used to understand and predict the effects of protein structure and function on sequence evolution and to predict unknown details of protein structure, function, and functional divergence. In order to demonstrate the practicality of these ideas and the potential benefit for functional genomic analysis, we describe a pilot project we are conducting to simultaneously sequence large numbers of vertebrate mitochondrial genomes.