Jansen, Raubeson, and Warnow A Biocomplexity grant has been awarded to an interdisciplinary team of researchers from the University of Texas, Central Washington University, University of New Mexico, the DoE Joint Genomics Institute, and Penn State University to undertake comparative evolutionary analyses of complete chloroplast genomes from more than 50 representative land plants. The team of four biologists (Jansen, Raubeson, Boore and dePamphilis) and five computer scientists (Warnow, Moret, Bader, Sankoff and Miller) will address a number of important issues in three areas at the intersection of biology and computer science: phylogeny of land plants, chloroplast genome evolution, and computational genomics. Fifty-five complete genomic sequences will be generated (greatly augmenting the 10 or so now known), new computational approaches for examining relationships using genomic data will be designed and implemented, and bioinformatic tools and resources for genomics will be developed. Then, the data and approaches will be used to study the relationships of plants and the patterns and processes of mutation as they affect the chloroplast genome. These results will be made available to both the scientific and lay communities. In addition, students in the fields of computational biology, bioinformatics, phylogenetic analysis, and genomics will be trained. Understanding relationships among organisms is an essential prerequisite for all areas of Biological Science, including such diverse fields as ecology, evolution, forensics, medicine, and molecular biology. Land plants, the focus of this study, include over 300,000 species and form the basis of terrestrial ecosystems. The phylogenetic history of this important group of organisms, only imperfectly understood, will be clarified by this research. This project also will make major contributions to our understanding of the mutational mechanisms and evolutionary processes acting within the chloroplast genome. This genome contains genes essential to plant function; studying its evolution should provide basic information of fundamental importance to plant scientists. Finally, this project will have important implications for computational biology, one of the fastest growing fields of science today. This includes the development and testing of new algorithms in comparative genomics, such as gene-order changes, that will increase the scope of theoretical computational biology. All software developed by the team will be made freely available.
