Literature DB >> 15033867

A systematic method to identify genomic islands and its applications in analyzing the genomes of Corynebacterium glutamicum and Vibrio vulnificus CMCP6 chromosome I.

Ren Zhang1, Chun-Ting Zhang.   

Abstract

MOTIVATION: Some genomic islands contain horizontally transferred genes, which play critical roles in altering the genotypes and phenotypes of organisms, and horizontal gene transfer has been recognized as a universal event throughout bacterial evolution. A windowless method to display the distribution of genomic GC content, the cumulative GC profile, is proposed to identify genomic islands in genomes whose complete genome sequences are available. Two new indices are proposed to assess the codon usage bias and amino acid usage bias in genomic islands.
RESULTS: A 211 kb genomic island (CGGI-1) has been identified in the genome of Corynebacterium glutamicum, and three genomic islands VVGI-1, VVGI-2 and VVGI-3, with lengths 167, 40 and 33 kb, respectively, have been identified in the genome of Vibrio vulnificus CMCP6 chromosome I. The CGGI-1 is flanked by two approximately 500 bp direct repeats, and utilizes a Val-tRNA as the integration site. For the VVGI-1 and VVGI-2, each has an integrase gene at 5' junction. All the identified genomic islands show unusual GC content, codon usage and amino acid usage, compared with the rest of the genomes. In addition, it is found that genomic islands are fairly homogenous in terms of GC content variation. An index, h, to quantify the homogeneity of GC content for genomic islands is proposed, and it is shown that h is less than 0.1 for all the genomic islands analyzed. The cumulative GC profile, as well as various indices to assess the codon usage bias, amino acid usage bias and homogeneity of the genomic islands, will be useful in the analysis of other genomes. AVAILABILITY: Programs used in this work and numerical results are available upon request.

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Year:  2004        PMID: 15033867     DOI: 10.1093/bioinformatics/btg453

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  35 in total

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