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SkewIT: The Skew Index Test for large-scale GC Skew analysis of bacterial genomes

GC skew is a phenomenon observed in many bacterial genomes, wherein the two replication strands of the same chromosome contain different proportions of guanine and cytosine nucleotides. Here we demonstrate that this phenomenon, which was first discovered in the mid-1990s, can be used today as an ana...

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Autores principales: Lu, Jennifer, Salzberg, Steven L.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7717575/
https://www.ncbi.nlm.nih.gov/pubmed/33275607
http://dx.doi.org/10.1371/journal.pcbi.1008439
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author Lu, Jennifer
Salzberg, Steven L.
author_facet Lu, Jennifer
Salzberg, Steven L.
author_sort Lu, Jennifer
collection PubMed
description GC skew is a phenomenon observed in many bacterial genomes, wherein the two replication strands of the same chromosome contain different proportions of guanine and cytosine nucleotides. Here we demonstrate that this phenomenon, which was first discovered in the mid-1990s, can be used today as an analysis tool for the 15,000+ complete bacterial genomes in NCBI’s Refseq library. In order to analyze all 15,000+ genomes, we introduce a new method, SkewIT (Skew Index Test), that calculates a single metric representing the degree of GC skew for a genome. Using this metric, we demonstrate how GC skew patterns are conserved within certain bacterial phyla, e.g. Firmicutes, but show different patterns in other phylogenetic groups such as Actinobacteria. We also discovered that outlier values of SkewIT highlight potential bacterial mis-assemblies. Using our newly defined metric, we identify multiple mis-assembled chromosomal sequences in previously published complete bacterial genomes. We provide a SkewIT web app https://jenniferlu717.shinyapps.io/SkewIT/ that calculates SkewI for any user-provided bacterial sequence. The web app also provides an interactive interface for the data generated in this paper, allowing users to further investigate the SkewI values and thresholds of the Refseq-97 complete bacterial genomes. Individual scripts for analysis of bacterial genomes are provided in the following repository: https://github.com/jenniferlu717/SkewIT.
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spelling pubmed-77175752020-12-09 SkewIT: The Skew Index Test for large-scale GC Skew analysis of bacterial genomes Lu, Jennifer Salzberg, Steven L. PLoS Comput Biol Research Article GC skew is a phenomenon observed in many bacterial genomes, wherein the two replication strands of the same chromosome contain different proportions of guanine and cytosine nucleotides. Here we demonstrate that this phenomenon, which was first discovered in the mid-1990s, can be used today as an analysis tool for the 15,000+ complete bacterial genomes in NCBI’s Refseq library. In order to analyze all 15,000+ genomes, we introduce a new method, SkewIT (Skew Index Test), that calculates a single metric representing the degree of GC skew for a genome. Using this metric, we demonstrate how GC skew patterns are conserved within certain bacterial phyla, e.g. Firmicutes, but show different patterns in other phylogenetic groups such as Actinobacteria. We also discovered that outlier values of SkewIT highlight potential bacterial mis-assemblies. Using our newly defined metric, we identify multiple mis-assembled chromosomal sequences in previously published complete bacterial genomes. We provide a SkewIT web app https://jenniferlu717.shinyapps.io/SkewIT/ that calculates SkewI for any user-provided bacterial sequence. The web app also provides an interactive interface for the data generated in this paper, allowing users to further investigate the SkewI values and thresholds of the Refseq-97 complete bacterial genomes. Individual scripts for analysis of bacterial genomes are provided in the following repository: https://github.com/jenniferlu717/SkewIT. Public Library of Science 2020-12-04 /pmc/articles/PMC7717575/ /pubmed/33275607 http://dx.doi.org/10.1371/journal.pcbi.1008439 Text en © 2020 Lu, Salzberg http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Lu, Jennifer
Salzberg, Steven L.
SkewIT: The Skew Index Test for large-scale GC Skew analysis of bacterial genomes
title SkewIT: The Skew Index Test for large-scale GC Skew analysis of bacterial genomes
title_full SkewIT: The Skew Index Test for large-scale GC Skew analysis of bacterial genomes
title_fullStr SkewIT: The Skew Index Test for large-scale GC Skew analysis of bacterial genomes
title_full_unstemmed SkewIT: The Skew Index Test for large-scale GC Skew analysis of bacterial genomes
title_short SkewIT: The Skew Index Test for large-scale GC Skew analysis of bacterial genomes
title_sort skewit: the skew index test for large-scale gc skew analysis of bacterial genomes
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7717575/
https://www.ncbi.nlm.nih.gov/pubmed/33275607
http://dx.doi.org/10.1371/journal.pcbi.1008439
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