APPROACHES TO DETECTING GENE-ENVIRONMENT INTERACTIONS IN ENVIRONMENTAL ADAPTABILITY USING GENETIC ENGINEERING, REMOTE SENSING AND GEOGRAPHIC INFORMATION SYSTEMS
Material and Methods. With the data obtained from these analyses based on genetic engineering/RS/GIS data, we then used spatial statistical analysis to evaluate gene-environment interactions. We assessed the relationship between the SNPs at candidate genes involved in human skin pigmentation and seasonal UVR exposure in the three regions representing the birthplaces of the human race (Africa, European, and East Asia) while conducting PCA using the correlation matrix to determine the relationships between SNP frequencies for heterozygous subjects and the seasonal UVR data.
Results. The correlation matrix results showed very high correlations between the G/T SNP and the mean seasonal 310-nm UVR levels. The mean 310-nm UVR levels in fall and winter were more highly correlated with the G/T SNP than were the mean seasonal 310-nm UVR levels in spring and summer. The biplots of the PCA show the principal component scores of each population represented as points on the first two principal components axes. The points of the principal component scores of each distinct population were distributed separately, dividing the data into two groups: one group of Africans and another group of Europeans and East Asians.
Discussion. The results suggest that skin pigmentation may be affected by mutations induced by ultraviolet radiation while indicating that mutation may occur due to modification of bases with 8-oxoguanine (8-oxoG) and support the hypothesis that global variation in skin pigmentation may be the result of localized adaptation to different ultraviolet radiation conditions via natural selection. Our findings suggest that the G/T SNP and the seasonal 310-nm UVR contribute to the separation of Africans and Europeans/East Asians.