Reference : A Semi-Quantitative, Synteny-Based Method to Improve Functional Predictions for Hypot...
Scientific journals : Article
Life sciences : Environmental sciences & ecology
http://hdl.handle.net/10993/7788
A Semi-Quantitative, Synteny-Based Method to Improve Functional Predictions for Hypothetical and Poorly Annotated Bacterial and Archaeal Genes
English
Yelton, Alexis P. [> >]
Thomas, Brian C. [> >]
Simmons, Sheri L. [> >]
Wilmes, Paul mailto [University of Luxembourg > Luxembourg Centre for Systems Biomedicine (LCSB) > >]
Zemla, Adam [> >]
Thelen, Michael P. [> >]
Justice, Nicholas [> >]
Banfield, Jillian F. [> >]
2011
PLoS Computational Biology
Public Library of Science
7
10
e1002230
Yes (verified by ORBilu)
International
1553-734X
1553-7358
San Francisco
CA
[en] During microbial evolution, genome rearrangement increases with increasing sequence divergence. If the relationship between synteny and sequence divergence can be modeled, gene clusters in genomes of distantly related organisms exhibiting anomalous synteny can be identified and used to infer functional conservation. We applied the phylogenetic pairwise comparison method to establish and model a strong correlation between synteny and sequence divergence in all 634 available Archaeal and Bacterial genomes from the NCBI database and four newly assembled genomes of uncultivated Archaea from an acid mine drainage (AMD) community. In parallel, we established and modeled the trend between synteny and functional relatedness in the 118 genomes available in the STRING database. By combining these models, we developed a gene functional annotation method that weights evolutionary distance to estimate the probability of functional associations of syntenous proteins between genome pairs. The method was applied to the hypothetical proteins and poorly annotated genes in newly assembled acid mine drainage Archaeal genomes to add or improve gene annotations. This is the first method to assign possible functions to poorly annotated genes through quantification of the probability of gene functional relationships based on synteny at a significant evolutionary distance, and has the potential for broad application.
http://hdl.handle.net/10993/7788
10.1371/journal.pcbi.1002230

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