%0 Journal Article
%T Mathematical Modeling the Biology of Single Nucleotide Polymorphisms (SNPs) in Whole Genome Adaptation
%A James Lindesay
%A Tshela E. Mason
%A William Hercules
%A Georgia M. Dunston
%J Advances in Bioscience and Biotechnology
%P 520-533
%@ 2156-8502
%D 2018
%I Scientific Research Publishing
%R 10.4236/abb.2018.910036
%X As a living information and communications system,
the genome encodes patterns in single nucleotide polymorphisms (SNPs)
reflecting human adaptation that optimizes population survival in differing
environments. This paper mathematically models environmentally induced adaptive
forces that quantify changes in the distribution of SNP frequencies between
populations. We make direct connections between biophysical methods (e.g.
minimizing genomic free energy) and concepts in population genetics. Our
unbiased computer program scanned a large set of SNPs in the major
histocompatibility complex region and flagged an altitude dependency on a SNP
associated </span><span style=\"font-family:Verdana;\">with response to oxygen
deprivation. The statistical power of our</span><span style=\"font-family:Verdana;\"> double-blind approach is
demonstrated in the flagging of mathematical functional correlations of SNP
information-based potentials in multiple populations with specific
environmental parameters. Furthermore, our approach provides insights for new
discoveries on the biology of common variants. This paper demonstrates the
power of biophysical modeling of population diversity for better understanding
genome-environment interactions in biological phenomenon.
%K Genome-Environment Interactions
%K Genomic Adaptation
%K SNP Functional Correlations
%U http://www.scirp.org/journal/PaperInformation.aspx?PaperID=87887