Bacterial genomic G + C composition-eliciting environmental adaptation Mann, Scott and Chen, Yi-Ping Phoebe 2010, Bacterial genomic G + C composition-eliciting environmental adaptation, Genomics, vol. 95, no. 1, pp. 7-15, doi: 10.1016/j.ygeno.2009.09.002. Attached Files Name Description MIMEType Size Downloads chen-bacterialgenomic-2010.pdf Published version application/pdf 187.04KB 318 Title Bacterial genomic G + C composition-eliciting environmental adaptation Alternative title Review : Bacterial genomic G + C composition-eliciting environmental adaptation Author(s) Mann, Scott Chen, Yi-Ping Phoebe Journal name Genomics Volume number 95 Issue number 1 Start page 7 End page 15 Total pages 9 Publisher Elsevier Place of publication Amsterdam, The Netherlands Publication date 2010-01 ISSN 0888-7543 1089-8646 Keyword(s) genome profiling G + C content profiling bacteria pathogenicity genome reduction Summary Bacterial genomes reflect their adaptation strategies through nucleotide usage trends found in their chromosome composition. Bacteria, unlike eukaryotes contain a wide range of genomic G + C. This wide variability may be viewed as a response to environmental adaptation. Two overarching trends are observed across bacterial genomes, the first, correlates genomic G + C to environmental niches and lifestyle, while the other utilizees intra-genomic G + C incongruence to delineate horizontally transferred material. In this review, we focus on the influence of several properties including biochemical, genetic flows, selection biases, and the biochemical-energetic properties shaping genome composition. Outcomes indicate a trend toward high G + C and larger genomes in free-living organisms, as a result of more complex and varied environments (higher chance for horizontal gene transfer). Conversely, nutrient limiting and nutrient poor environments dictate smaller genomes of low GC in attempts to conserve replication expense. Varied processes including translesion repair mechanisms, phage insertion and cytosine degradation has been shown to introduce higher AT in genomic sequences. We conclude the review with an analysis of current bioinformatics tools seeking to elicit compositional variances and highlight the practical implications when using such techniques. Language eng DOI 10.1016/j.ygeno.2009.09.002 Field of Research 080301 Bioinformatics Software Socio Economic Objective 890299 Computer Software and Services not elsewhere classified HERDC Research category C1 Refereed article in a scholarly journal Copyright notice ©2009, Elsevier Free to Read? Yes Persistent URL http://hdl.handle.net/10536/DRO/DU:30034416 Document type: Journal Article Collections: Faculty of Science, Engineering and Built Environment School of Information Technology Open Access Collection Related Links Link Description Connect to published version (restricted access) Go to link with your DU access privileges     Unless expressly stated otherwise, the copyright for items in DRO is owned by the author, with all rights reserved. Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au. Versions Version Filter Type Wed, 27 Apr 2011, 17:20:54 EST Wed, 27 Apr 2011, 17:22:53 EST Fri, 29 Apr 2011, 09:47:22 EST Fri, 29 Apr 2011, 09:48:42 EST Wed, 15 Jun 2011, 14:07:37 EST Wed, 15 Jun 2011, 14:15:39 EST Wed, 15 Jun 2011, 14:27:09 EST Fri, 17 Jun 2011, 08:59:18 EST Mon, 15 Apr 2013, 15:20:56 EST Mon, 16 Jun 2014, 17:55:40 EST Tue, 06 Sep 2016, 16:59:44 EST Tue, 05 Dec 2017, 10:49:31 EST Fri, 07 Sep 2018, 15:24:31 EST Filtered Full Citation counts:   Cited 84 times in TR Web of Science Cited 86 times in Scopus Search Google Scholar Access Statistics: 2342 Abstract Views, 319 File Downloads  -  Detailed Statistics Created: Wed, 27 Apr 2011, 17:20:43 EST by Sandra Dunoon