Software for computing skew metrics on bacterial genomes.
More information, datasets and interactive visualizations: http://db.systemsbiology.net/gestalt/skew_metrics
Preprint: https://www.biorxiv.org/content/early/2017/08/15/176370
Joesch-Cohen LM, Robinson M, Jabbari N, Lausted C and Glusman G. Novel metrics for quantifying bacterial genome skews. 2017.
We present three novel metrics for quantifying bacterial genome composition skews. Skews are asymmetries in nucleotide usage that arise as a result of mutational biases and selective constraints, particularly for energy efficiency. The first two metrics (cross-skew and dot-skew) evaluate sequence and gene annotation of the genome of a single species, while the third metric (residual skew) discovers patterns only discernable from studying genomes of thousands of species. The three metrics can be computed for genomes not yet finished and fully annotated. We studied the genomes of 7738 bacterial species, including completed genomes and partial drafts, and identified multiple species with unusual skew parameters. A number of these outliers (i.e., Borrelia, Ehrlichia, Kinetoplastibacterium, and Phytoplasma) display similar skew patterns despite a lack of phylogenetic relation. These disparate bacterial species share lifestyle characteristics, suggesting that our novel metrics successfully capture effects on genome composition of biosynthetic constraints and of interaction with the hosts.