  As a living information and communications system, the genome encodes
patterns in single nucleotide polymorphisms (SNPs) reflecting human adaption
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 with response to oxygen
deprivation. The statistical power of our 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.
