Abstract
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 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.
Highlights
As a complex, dynamic information system, the human genome encodes and perpetuates the principles of life
This paper demonstrates the power of biophysical modeling of population diversity for better understanding genome-environment interactions in biological phenomenon
As dynamic sites in the human genome, single nucleotide polymorphisms (SNPs) are often highly correlated into combinations referred to as haploblocks whose haplotypes are maintained throughout generations with fixed frequencies within a given population
Summary
Dynamic information system, the human genome encodes and perpetuates the principles of life. As dynamic sites in the human genome, SNPs are often highly correlated into combinations referred to as haploblocks whose haplotypes are maintained throughout generations with fixed frequencies within a given population. Such combinations of SNPs are said to be in linkage disequilibrium (LD). Using measures of genomic information that reflect the interplay of statistical variations due to the environmental baths within which stable populations exist motivates the development of “genodynamics” as an analog to macro-physical “thermodynamics” [2]. We mathematically model genome-environment interactions and demonstrate straightforward environmental influences upon common genomic variants
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