Repetitive element signature-based visualization, distance computation, and classification of 1766 microbial genomes

Kang Hoon Lee, Kyung Seop Shin, Debora Lim, Woo Chan Kim, Byung Chang Chung, Gyu Bum Han, Jeongkyu Roh, Dong Ho Cho, Kiho Cho

Research output: Contribution to journalArticle

Abstract

The genomes of living organisms are populated with pleomorphic repetitive elements (REs) of varying densities. Our hypothesis that genomic RE landscapes are species/strain/individual-specific was implemented into the Genome Signature Imaging system to visualize and compute the RE-based signatures of any genome. Following the occurrence profiling of 5-nucleotide REs/words, the information from top-50 frequency words was transformed into a genome-specific signature and visualized as Genome Signature Images (GSIs), using a CMYK scheme. An algorithm for computing distances among GSIs was formulated using the GSIs' variables (word identity, frequency, and frequency order). The utility of the GSI-distance computation system was demonstrated with control genomes. GSI-based computation of genome-relatedness among 1766 microbes (117 archaea and 1649 bacteria) identified their clustering patterns; although the majority paralleled the established classification, some did not. The Genome Signature Imaging system, with its visualization and distance computation functions, enables genome-scale evolutionary studies involving numerous genomes with varying sizes.

Original languageEnglish (US)
Pages (from-to)30-42
Number of pages13
JournalGenomics
Volume106
Issue number1
DOIs
StatePublished - Jul 1 2015

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Keywords

  • Genome distance
  • Genome signature
  • Genome visualization
  • Genome-scale classification
  • Microbial genomes
  • Repetitive element

ASJC Scopus subject areas

  • Genetics

Cite this

Lee, K. H., Shin, K. S., Lim, D., Kim, W. C., Chung, B. C., Han, G. B., Roh, J., Cho, D. H., & Cho, K. (2015). Repetitive element signature-based visualization, distance computation, and classification of 1766 microbial genomes. Genomics, 106(1), 30-42. https://doi.org/10.1016/j.ygeno.2015.04.004