Predicting prokaryotic ecological niches using genome sequence analysis.

@article{citeulike:1718941, abstract = {Automated DNA sequencing technology is so rapid that analysis has become the rate-limiting step. Hundreds of prokaryotic genome sequences are publicly available, with new genomes uploaded at the rate of approximately 20 per month. As a result, this growing body of genome sequences will include microorganisms not previously identified, isolated, or observed. We hypothesize that evolutionary pressure exerted by an ecological niche selects for a similar genetic repertoire in those prokaryotes that occupy the same niche, and that this is due to both vertical and horizontal transmission. To test this, we have developed a novel method to classify prokaryotes, by calculating their Pfam protein domain distributions and clustering them with all other sequenced prokaryotic species. Clusters of organisms are visualized in two dimensions as 'mountains' on a topological map. When compared to a phylogenetic map constructed using 16S rRNA, this map more accurately clusters prokaryotes according to functional and environmental attributes. We demonstrate the ability of this map, which we term a "niche map", to cluster according to ecological niche both quantitatively and qualitatively, and propose that this method be used to associate uncharacterized prokaryotes with their ecological niche as a means of predicting their functional role directly from their genome sequence.}, address = {Department of Biology, Syracuse University, Syracuse, New York, United States of America.}, author = {Suen, G. and Goldman, B. S. and Welch, R. D. }, citeulike-article-id = {1718941}, doi = {10.1371/journal.pone.0000743}, issn = {1932-6203}, journal = {PLoS ONE}, keywords = {ecological-niches, genomics, prokaryotes, sequence-analysis}, number = {1}, posted-at = {2008-01-24 16:30:32}, priority = {4}, title = {Predicting prokaryotic ecological niches using genome sequence analysis.}, url = {http://dx.doi.org/10.1371/journal.pone.0000743}, volume = {2}, year = {2007} }

TY - JOUR ID - citeulike:1718941 L3 - citeulike-article-id:1718941 TI - Predicting prokaryotic ecological niches using genome sequence analysis. JF - PLoS ONE VL - 2 IS - 1 AD - Department of Biology, Syracuse University, Syracuse, New York, United States of America. SN - 1932-6203 N2 - Automated DNA sequencing technology is so rapid that analysis has become the rate-limiting step. Hundreds of prokaryotic genome sequences are publicly available, with new genomes uploaded at the rate of approximately 20 per month. As a result, this growing body of genome sequences will include microorganisms not previously identified, isolated, or observed. We hypothesize that evolutionary pressure exerted by an ecological niche selects for a similar genetic repertoire in those prokaryotes that occupy the same niche, and that this is due to both vertical and horizontal transmission. To test this, we have developed a novel method to classify prokaryotes, by calculating their Pfam protein domain distributions and clustering them with all other sequenced prokaryotic species. Clusters of organisms are visualized in two dimensions as 'mountains' on a topological map. When compared to a phylogenetic map constructed using 16S rRNA, this map more accurately clusters prokaryotes according to functional and environmental attributes. We demonstrate the ability of this map, which we term a "niche map", to cluster according to ecological niche both quantitatively and qualitatively, and propose that this method be used to associate uncharacterized prokaryotes with their ecological niche as a means of predicting their functional role directly from their genome sequence. KW - ecological-niches KW - genomics KW - prokaryotes KW - sequence-analysis AU - Suen, G AU - Goldman, BS AU - Welch, RD PY - 2007/// UR - http://dx.doi.org/10.1371/journal.pone.0000743 ER -