Discovering functional DNA elements using population genomic information: a proof of concept using human mtDNA.

Area of Science:

• Genomics and Evolutionary Biology
• Population Genetics
• Molecular Biology

Background:

• Identifying functional genomic elements is vital for understanding human health, disease, and evolution.
• Purifying selection leaves detectable signatures in functional elements, historically exploited through interspecies comparisons.
• Genome function evolves, necessitating methods to detect current purifying selection in human populations.

Purpose of the Study:

• To assess the potential of dense population genetic data to identify currently functional genomic regions in humans.
• To investigate whether within-species genetic variation can reveal elements under purifying selection.

Main Methods:

• Analysis of an ultradeep sample of 16,411 human mitochondrial genomes.
• Examination of polymorphism density to delineate regions under purifying selection.
• Correlation analysis between segregating alleles and interspecies divergence, controlling for mutational biases.

Main Results:

• High polymorphism density in the mitochondrial genome data precisely identified regions under purifying selection.
• The number of segregating alleles strongly correlated with interspecies divergence (ρ = 0.51, P < 2.2 × 10(-16)).
• This correlation was observed at a fine scale, indicating it is a direct result of natural selection.

Conclusions:

• Genetic variation within a species can precisely reveal currently functional genomic regions.
• These functional regions are likely to have deleterious fitness effects when mutated.
• The approach holds promise for identifying functional elements in the human nuclear genome as sequencing data increases.