Evolutionary perspectives on polygenic selection, missing heritability, and GWAS.

Area of Science:

• Evolutionary genetics
• Statistical genetics
• Human genomics

Background:

• Genome-wide association studies (GWAS) identify trait-associated variants but do not fully explain complex trait heritability.
• The concept of "missing heritability" highlights a gap between identified genetic variants and observed trait variation.

Purpose of the Study:

• To reframe "missing heritability" as an evolutionary challenge.
• To investigate the impact of natural selection on the genetic architecture of complex traits.
• To assess how evolutionary processes affect the statistical inference of causal genetic variants.

Main Methods:

• Review of theoretical and empirical literature on selection and complex traits.
• Analysis of empirical findings on selection's role in shaping variant effect sizes and frequencies.
• Simulations incorporating selection, realistic genome structure, and human demography.

Main Results:

• Selection significantly influences the effect sizes and allele frequencies of causal variants for complex traits.
• Evolutionary processes, particularly selection, impede the detection of causal genetic loci in GWAS.
• The transferability of GWAS findings across different populations is constrained by selection acting on causal alleles.

Conclusions:

• "Missing heritability" is substantially an evolutionary problem, influenced by selection on complex traits.
• Future GWAS statistical methods should incorporate evolutionary models to better infer causal loci.
• Understanding the interplay between selection and genetic variation is crucial for advancing complex trait genetics.