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Science China Life Sciences

, Volume 57, Issue 11, pp 1121–1130 | Cite as

Understanding the commonalities and differences in genomic organizations across closely related bacteria from an energy perspective

  • Qin Ma
  • Xin Chen
  • Chao Liu
  • XiZeng Mao
  • HanYuan Zhang
  • Fei Ji
  • ChunGuo Wu
  • Ying XuEmail author
Open Access
Research Paper

Abstract

The availability of a large number of sequenced bacterial genomes facilitates in-depth studies about why genes (operons) in a bacterial genome are globally organized the way they are. We have previously discovered that (the relative) transcription- activation frequencies among different biological pathways encoded in a genome have a dominating role in the global arrangement of operons. One complicating factor in such a study is that some operons may be involved in multiple pathways with different activation frequencies. A quantitative model has been developed that captures this information, which tends to be minimized by the current global arrangement of operons in a bacterial (and archaeal) genome compared to possible alternative arrangements. A study is carried out here using this model on a collection of 52 closely related E. coli genomes, which revealed interesting new insights about how bacterial genomes evolve to optimally adapt to their environments through adjusting the (relative) genomic locations of the encoding operons of biological pathways once their utilization and hence transcription activation frequencies change, to maintain the above energy-efficiency property. More specifically we observed that it is the frequencies of the transcription activation of pathways relative to those of the other encoded pathways in an organism as well as the variation in the activation frequencies of a specific pathway across the related genomes that play a key role in the observed commonalities and differences in the genomic organizations of genes (and operons) encoding specific pathways across different genomes.

Keywords

genomic organization transcription activation frequency pathway modeling comparative genomics analysis 

Supplementary material

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Supplementary material, approximately 102 KB.
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Copyright information

© The Author(s) 2014

Authors and Affiliations

  • Qin Ma
    • 1
    • 2
  • Xin Chen
    • 1
    • 3
  • Chao Liu
    • 1
    • 4
  • XiZeng Mao
    • 1
    • 2
  • HanYuan Zhang
    • 1
    • 3
  • Fei Ji
    • 1
    • 2
  • ChunGuo Wu
    • 1
    • 3
  • Ying Xu
    • 1
    • 2
    • 3
    Email author
  1. 1.Computational Systems Biology Laboratory, Department of Biochemistry and Molecular Biology and Institute of BioinformaticsUniversity of GeorgiaAthensUSA
  2. 2.BioEnergy Science CenterOak Ridge National LaboratoryOak RidgeUSA
  3. 3.College of Computer Science and TechnologyJilin UniversityChangchunChina
  4. 4.Provincial Hospital Affiliated to Shandong UniversityJinanChina

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