Title: Identification of phage-induced genomic islands in the 13 Streptococcus pyogenes strains using genome barcodes

Authors: Chunbao Zhou; Jiaxin Wang; Yao Wang; Yanchun Liang

Addresses: College of Computer Science and Technology, Key Laboratory of Symbol Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun 130012, China; Supercomputing Center, Computer Network Information Center, Chinese Academy of Sciences, Beijing 100190, China ' College of Computer Science and Technology, Key Laboratory of Symbol Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun 130012, China ' College of Computer Science and Technology, Key Laboratory of Symbol Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun 130012, China ' College of Computer Science and Technology, Key Laboratory of Symbol Computation and Knowledge Engineering of Ministry of Education, Jilin University, Changchun 130012, China

Abstract: With the revolutionary invention of the high-throughput sequencing technique, the production of bacterial genomes is significantly sped up. The in silico characterisation of genomic islands (GIs) in the pathogenic bacterium becomes increasingly needed, due to the time consumption and the high cost of the experimental techniques. A GI can be computationally detected through the DNA composition. Barcode, a dimension reduction and visualisation technique of genomic DNA composition, was recently applied to detect different DNA compositions effectively. In this work, we proposed a Barcode-based technique to detect Phage-induced Genomic Islands (PGIs) in the 13 completely sequenced strains of Streptococcus pyogenes. Our experimental results showed that the detected PGIs are highly consistent with the known GIs, the novel PGIs are promising candidates for the clinical diagnosis of S. pyogenes.

Keywords: Streptococcus pyogenes; horizontal gene transfer; genomic islands; genome barcodes; high-throughput sequencing; DNA composition; bioinformatics.

DOI: 10.1504/IJDMB.2014.064524

International Journal of Data Mining and Bioinformatics, 2014 Vol.10 No.3, pp.269 - 284

Received: 12 Dec 2011
Accepted: 22 May 2012

Published online: 21 Oct 2014 *

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