Literature DB >> 20865522

Taxonomic parsing of bacteriophages using core genes and in silico proteome-based CGUG and applications to small bacterial genomes.

Padmanabhan Mahadevan1, Donald Seto.   

Abstract

A combined genomics and in situ proteomics approach can be used to determine and classify the relatedness of organisms. The common set of proteins shared within a group of genomes is encoded by the "core" set of genes, which is increasingly recognized as a metric for parsing viral and bacterial species. These can be described by the concept of a "pan-genome", which consists of this "core" set and a "dispensable" set, i.e., genes found in one or more but not all organisms in the grouping. "CoreGenesUniqueGenes" (CGUG) is a web-based tool that determines this core set of proteins in a set of genomes as well as parses the dispensable set of unique proteins in a pair of viral or small bacterial genomes. This proteome-based methodology is validated using bacteriophages, aiding the reevaluation of current classifications of bacteriophages. The utility of CGUG in the analysis of small bacterial genomes and the annotation of hypothetical proteins is also presented.

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Year:  2010        PMID: 20865522     DOI: 10.1007/978-1-4419-5913-3_43

Source DB:  PubMed          Journal:  Adv Exp Med Biol        ISSN: 0065-2598            Impact factor:   2.622


  4 in total

1.  CoreGenes3.5: a webserver for the determination of core genes from sets of viral and small bacterial genomes.

Authors:  Dann Turner; Darren Reynolds; Donald Seto; Padmanabhan Mahadevan
Journal:  BMC Res Notes       Date:  2013-04-08

2.  Comparative analysis of multiple inducible phages from Mannheimia haemolytica.

Authors:  Yan D Niu; Shaun R Cook; Jiaying Wang; Cassidy L Klima; Yu-hung Hsu; Andrew M Kropinski; Dann Turner; Tim A McAllister
Journal:  BMC Microbiol       Date:  2015-08-30       Impact factor: 3.605

3.  Four Escherichia coli O157:H7 phages: a new bacteriophage genus and taxonomic classification of T1-like phages.

Authors:  Yan D Niu; Tim A McAllister; John H E Nash; Andrew M Kropinski; Kim Stanford
Journal:  PLoS One       Date:  2014-06-25       Impact factor: 3.240

4.  An Analysis of Adenovirus Genomes Using Whole Genome Software Tools.

Authors:  Padmanabhan Mahadevan
Journal:  Bioinformation       Date:  2016-08-30
  4 in total

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