Journal of
Computational Biology and Bioinformatics Research

  • Abbreviation: J. Comput. Biol. Bioinform. Res
  • Language: English
  • ISSN: 2141-2227
  • DOI: 10.5897/JCBBR
  • Start Year: 2009
  • Published Articles: 33

Full Length Research Paper

Development of genodynamic metrics for exploring the biophysics of DNA polymorphisms

James Lindesay
  • James Lindesay
  • Computational Physics Laboratory, Department of Physics and Astronomy, Howard University, Washington, DC, 20059, U.S
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Tshela E Mason
  • Tshela E Mason
  • National Human Genome Center, Howard University, Washington, DC, 20060, U.S
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William Hercules
  • William Hercules
  • Computational Physics Laboratory, Department of Physics and Astronomy, Howard University, Washington, DC, 20059, U.S
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Georgia M Dunston*
  • Georgia M Dunston*
  • 2. National Human Genome Center, Howard University, Washington, DC, 20060, U.S; 3. Department of Microbiology, Howard University, Washington, DC, 20059, U.S.
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  •  Received: 19 March 2014
  •  Accepted: 02 September 2014
  •  Published: 30 November 2014

Abstract

Single nucleotide polymorphisms (SNPs) represent an important type of dynamic sites within the human genome. These common variants often locally correlate within more complex multi-SNP haploblocks that are maintained throughout generations in a stable population. Information encoded in the structure of SNPs and SNP haploblock variation can be characterized through a normalized information content metric. Genodynamics is being developed as the analogous “thermodynamics” characterizing the state variables for genomic populations that are stable under stochastic environmental stresses. Since living systems have not been found to develop in the absence of environmental influences, this paper describes the analogous genomic free energy metrics in a given environment. SNP haploblocks were constructed by Haploview v4.2 for five chromosomes from phase III HapMap data, and the genomic state variables for each chromosome were calculated. An in silico analysis was performed on SNP haploblocks with the lowest genomic energy measures. Highly favorable genomic energy measures were found to correlate with highly conserved SNP haploblocks. Moreover, the most conserved haploblocks were associated with an evolutionarily conserved regulatory element and domain.

Key words: Information theory, entropy, genomic variation, biological information, genodynamics.