Information Dynamics of Whole Genome Adaptation


The human genome is a complex, dynamic information system that encodes principles of life and living systems. These principles are incorporated in the structure of human genome sequence variation and are foundational for the continuity of life and human survival. Using first principles of thermodynamics and statistical physics, we have developed analogous “genodynamic tools” for population genomic studies. Characterizing genomic information through the lens of physics has allowed us to develop energy measures for modeling genome-environment interactions. In developing biophysical parameters for genome-environment homeostasis, we found that stable genomic free energy trades off low genomic energy (genomic conservation and increased order) and high genomic entropy (genomic variation) with an environmental potential that drives the variation. In our approach, we assert that common variants are dynamic sites in the genome of a population and that the stability of whole genome adaptation is reflected in the frequencies of maintained diversity in common variants for the population in its environment. In this paper, we address the relativity of whole genome adaptation towards homeostasis. By this we mean that adaptive forces are directly reflected in the frequency distribution of alleles and/or haplotypes of the population relative to its environment, with adaptive forces driving the genome towards homeostasis. The use of genomic energy units as a biophysical metric in DNA sequence variation analyses provides new insights into the foundations of population biology and diversity. Using our biophysical tools, population differences directly reflect the adaptive influences of the environment on populations.

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Hercules, W. , Lindesay, J. , Mason, T. and Dunston, G. (2014) Information Dynamics of Whole Genome Adaptation. Natural Science, 6, 1228-1231. doi: 10.4236/ns.2014.615110.

Conflicts of Interest

The authors declare no conflicts of interest.


[1] Eid, N.A., Hussein, A.A., Elzein, A.M., Mohamed, H.S., Rockett, K.A., Kwiatkowski, D.P. and Ibrahim, M.E. (2010) Candidate Malaria Susceptibility/Protective SNPs in Hospital and Population-Based Studies: The Effect of Sub-Structuring. Malaria Journal, 9, 119.
[2] Kwiatkowski, D.P. (2005) How Malaria Has Affected the Human Genome and What Human Genetics Can Teach Us about Malaria. The American Journal of Human Genetics, 77, 171-190.
[3] Modiano, D., Petrarca, V., Sirima, B.S., Nebie, I., Diallo, D., Esposito, F. and Coluzzi, M. (1996) Different Response to Plasmodium falciparum Malaria in West African Sympatric Ethnic Groups. Proceedings of the National Academy of Sciences of the USA, 93, 13206-13211.
[4] Rihet, P., Traore, Y., Abel, L., Aucan, C., Leroux, T.T. and Fumoux, F. (1998) Malaria in Humans: Plasmodium falciparum Blood Infection Levels Are Linked to Chromosome 5q31-q33. The American Journal of Human Genetics, 63, 498-505.
[5] Driss, A., Hibbert, J.M., Wilson, N.O., Iqbal, S.A., Adamkiewicz, T.V. and Stiles, J.K. (2011) Genetic Polymorphisms Linked to Susceptibility to Malaria. Malaria Journal, 10, 271.

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