Gene context analysis in the Integrated Microbial Genomes (IMG) data management system.
Computational methods for determining the function of genes in newly sequenced genomes have been traditionally based on sequence similarity to genes whose function has been identified experimentally. Function prediction methods can be extended using gene context analysis approaches such as examining the conservation of chromosomal gene clusters, gene fusion events and co-occurrence profiles across genomes. Context analysis is based on the observation that functionally related genes are often having similar gene context and relies on the identification of such events across phylogenetically diverse collection of genomes. We have used the data management system of the Integrated Microbial Genomes (IMG) as the framework to implement and explore the power of gene context analysis methods because it provides one of the largest available genome integrations. Visualization and search tools to facilitate gene context analysis have been developed and applied across all publicly available archaeal and bacterial genomes in IMG. These computations are now maintained as part of IMG's regular genome content update cycle. IMG is available at: http://img.jgi.doe.gov.
Mavromatis
Konstantinos
K
Genome Biology Program, Department of Energy Joint Genome Institute, Walnut Creek, California, United States of America. KMavrommatis@lbl.gov
Chu
Ken
K
Ivanova
Natalia
N
Hooper
Sean D
SD
Markowitz
Victor M
VM
Kyrpides
Nikos C
NC
D000465:Algorithms; D002876:Chromosomes, Bacterial / Q000235:genetics; D019295:Computational Biology / Q000379:methods*; D030541:Databases, Genetic; D030562:Databases, Protein; D019143:Evolution, Molecular; D016678:Genome; D016680:Genome, Bacterial; D023281:Genomics; D008957:Models, Genetic; D015233:Models, Statistical; D010802:Phylogeny; D016415:Sequence Alignment; D020539:Sequence Analysis, Protein; D012984:Software