Journal Article

Elucidating Genome Structure Evolution by Analysis of Isoapostatic Gene Clusters using Statistics of Variance of Gene Distances

Naobumi V. Sasaki and Naoki Sato

in Genome Biology and Evolution

Published on behalf of Society for Molecular Biology and Evolution

Volume 2, issue , pages 1-12
Published in print January 2010 |
Published online December 2009 | e-ISSN: 1759-6653 | DOI:

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  • Bioinformatics and Computational Biology
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Identifying genomic regions that descended from a common ancestor is important for understanding the function and evolution of genomes. In related genomes, clusters of homologous gene pairs serve as evidence for candidate homologous regions, which make up genomic core. Previous studies on the structural organization of bacterial genomes revealed that basic backbone of genomic core is interrupted by genomic islands. Here, we applied statistics using variance of distances as a measure to classify conserved genes within a set of genomes according to their “isoapostatic” relationship, which keeps nearly identical distances of genes. The results of variance statistics analysis of cyanobacterial genomes including Prochlorococcus, Synechococcus, and Anabaena indicated that the conserved genes are classified into several groups called “virtual linkage groups (VLGs)” according to their positional conservation of orthologs over the genomes analyzed. The VLGs were used to define mosaic domain structure of the genomic core. The current model of mosaic genomic domains can explain global evolution of the genomic core of cyanobacteria. It also visualizes islands of lateral gene transfer. The stability and the robustness of the variance statistics are discussed. This method will also be useful in deciphering the structural organization of genomes in other groups of bacteria.

Keywords: comparative genomics; cyanobacteria; gene distance profile; genome core; isoapostatic genes

Journal Article.  5909 words.  Illustrated.

Subjects: Bioinformatics and Computational Biology ; Evolutionary Biology ; Genetics and Genomics

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