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BioMed Research International
Volume 2016 (2016), Article ID 7215379, 7 pages
http://dx.doi.org/10.1155/2016/7215379
Research Article

Genomic Analysis of a Marine Bacterium: Bioinformatics for Comparison, Evaluation, and Interpretation of DNA Sequences

1School of Life Sciences, Swami Ramanand Teerth Marathwada University, Nanded 431606, India
2Institute of Natural Resources and Agrobiology, Spanish National Research Council, IRNAS-CSIC, Avda. Reina Mercedes 10, 41012 Sevilla, Spain

Received 11 July 2016; Revised 10 October 2016; Accepted 13 October 2016

Academic Editor: Marco Bazzicalupo

Copyright © 2016 Bhagwan N. Rekadwad et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

A total of five highly related strains of an unidentified marine bacterium were analyzed through their short genome sequences (AM260709–AM260713). Genome-to-Genome Distance (GGDC) showed high similarity to Pseudoalteromonas haloplanktis (X67024). The generated unique Quick Response (QR) codes indicated no identity to other microbial species or gene sequences. Chaos Game Representation (CGR) showed the number of bases concentrated in the area. Guanine residues were highest in number followed by cytosine. Frequency of Chaos Game Representation (FCGR) indicated that CC and GG blocks have higher frequency in the sequence from the evaluated marine bacterium strains. Maximum GC content for the marine bacterium strains ranged 53-54%. The use of QR codes, CGR, FCGR, and GC dataset helped in identifying and interpreting short genome sequences from specific isolates. A phylogenetic tree was constructed with the bootstrap test (1000 replicates) using MEGA6 software. Principal Component Analysis (PCA) was carried out using EMBL-EBI MUSCLE program. Thus, generated genomic data are of great assistance for hierarchical classification in Bacterial Systematics which combined with phenotypic features represents a basic procedure for a polyphasic approach on unambiguous bacterial isolate taxonomic classification.