Evidence map›Paper›PMID 29996771›Full record

ArticleBMC genomics2018

Novel metrics for quantifying bacterial genome composition skews.

Lena M Joesch-Cohen, Max Robinson, Neda Jabbari, Christopher G Lausted, Gustavo Glusman

Abstract read
In one paragraph

Article in BMC genomics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Lena M Joesch-CohenInstitute for Systems Biology, 401 Terry Ave N, Seattle, WA, 98109, USA.ORCID http://orcid.org/0000-0002-9129-6809
Max RobinsonInstitute for Systems Biology, 401 Terry Ave N, Seattle, WA, 98109, USA.ORCID http://orcid.org/0000-0003-0878-114X
Neda JabbariInstitute for Systems Biology, 401 Terry Ave N, Seattle, WA, 98109, USA.
Christopher G LaustedInstitute for Systems Biology, 401 Terry Ave N, Seattle, WA, 98109, USA.ORCID http://orcid.org/0000-0003-3073-9212
Gustavo GlusmanInstitute for Systems Biology, 401 Terry Ave N, Seattle, WA, 98109, USA. Gustavo@SystemsBiology.org.ORCID http://orcid.org/0000-0001-8060-5955

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundBacterial genomes have characteristic compositional skews, which are differences in nucleotide frequency between the leading and lagging DNA strands across a segment of a genome. It is thought that these strand asymmetries arise as a result of mutational biases and selective constraints, particularly for energy efficiency. Analysis of compositional skews in a diverse set of bacteria provides a comparative context in which mutational and selective environmental constraints can be studied. These analyses typically require finished and well-annotated genomic sequences.

resultsWe present three novel metrics for examining genome composition skews; all three metrics can be computed for unfinished or partially-annotated genomes. The first two metrics, (dot-skew and cross-skew) depend on sequence and gene annotation of a single genome, while the third metric (residual skew) highlights unusual genomes by subtracting a GC content-based model of a library of genome sequences. We applied these metrics to 7738 available bacterial genomes, including partial drafts, and identified outlier species. A phylogenetically diverse set of these outliers (i.e., Borrelia, Ehrlichia, Kinetoplastibacterium, and Phytoplasma) display similar skew patterns but share lifestyle characteristics, such as intracellularity and biosynthetic dependence on their hosts.

conclusionsOur novel metrics appear to reflect the effects of biosynthetic constraints and adaptations to life within one or more hosts on genome composition. We provide results for each analyzed genome, software and interactive visualizations at http://db.systemsbiology.net/gestalt/ skew_metrics .

Indexed as

Genome, BacterialBacteriaComputational BiologyInternet AccessModels, GeneticUser-Computer InterfaceCompositional biasGenome metricsLagging strandLeading strandLyme diseaseNucleotide skewObligate intracellular

Identifiers

PMID29996771
PMCPMC6042203

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LicenceCC BY
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.