A proximity-based method to identify genomic regions correlated with a continuously varying environmental variable

Area of Science:

• Human Genetics
• Evolutionary Biology
• Population Genetics

Background:

• Understanding genetic markers linked to environmental factors is crucial for studying human evolution.
• Spatial patterns in the human genome can reflect adaptation to diverse environmental determinants.

Purpose of the Study:

• To identify specific regions in the human genome that exhibit strong correlations with environmental variables, specifically absolute latitude.
• To investigate the biological relevance of these identified genomic regions and associated genes.

Main Methods:

• Utilized genotype data from the Human Genome Diversity Panel (HGDP-CEPH) comprising over half a million single nucleotide polymorphisms (SNPs).
• Calculated Spearman's correlation between absolute latitude and allele frequencies for each SNP.
• Selected SNPs within the top 1% tail of the correlation distribution and applied proximity criteria to identify continuous genomic signals.

Main Results:

• Identified genomic regions showing significant correlation with absolute latitude.
• Demonstrated biological relevance for most identified regions using external information and genome annotations.
• Highlighted specific genes (e.g., DTNB, DOT1L, TPCN2, RELN, MSRA, NRG3) associated with traits like body size, height, hair color, and schizophrenia.

Conclusions:

• The novel method, incorporating proximity analysis, enhances the identification of environmentally correlated genomic regions.
• The findings provide insights into genetic adaptations related to environmental factors and their influence on human phenotypic variation.
• The approach is broadly applicable to studying associations between genetic polymorphisms and various continuous environmental variables.