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As a living information and communications system, the genome encodespatterns in single nucleotide polymorphisms (SNPs) reflecting human adaptionthat optimizes population survival in differing environments. This papermathematically models environmentally induced adaptive forces that quantifychanges in the distribution of SNP frequencies between populations. We makedirect connections between biophysical methods (e.g. minimizing genomic freeenergy) and concepts in population genetics. Our unbiased computer programscanned a large set of SNPs in the major histocompatibility complex region, andflagged an altitude dependency on a SNP associated with response to oxygendeprivation. The statistical power of our double-blind approach is demonstratedin the flagging of mathematical functional correlations of SNPinformation-based potentials in multiple populations with specificenvironmental parameters. Furthermore, our approach provides insights for newdiscoveries on the biology of common variants. This paper demonstrates thepower of biophysical modeling of population diversity for better understandinggenome-environment interactions in biological phenomenon.

Use of Genome Information-Based Potentials to Characterize Human Adaptation