Gene action, genetic variation, and GWAS: A user-friendly web tool

Area of Science:

• Quantitative Genetics
• Genomics
• Statistical Genetics

Background:

• Fisher's partitioning of genetic variance is fundamental to understanding trait inheritance.
• Misconceptions persist regarding the role of nonadditive genetic effects (dominance, epistasis) in complex traits.
• Genome-Wide Association Studies (GWASs) increasingly rely on accurate genetic variance partitioning.

Purpose of the Study:

• To develop an accessible web tool (Falconer ShinyApp) for visualizing genetic variance components.
• To illustrate the relationship between single nucleotide polymorphism (SNP) effect sizes from GWAS and population-level variation.
• To clarify the contributions of gene action, allele frequencies, and interactions to genetic variance.

Main Methods:

• Development of a user-friendly web application (ShinyApp).
• Utilizing simulations to demonstrate the translation of gene action and allele frequencies into genetic variance.
• Visualizing the impact of SNP effect sizes and genetic interactions on complex traits.

Main Results:

• The Falconer ShinyApp effectively demonstrates how locus-specific effects contribute to individual trait differences.
• Nonadditive genetic effects (dominance and epistasis) generally account for a smaller proportion of genetic variance compared to additive effects.
• Interactions between loci typically do not significantly explain individual differences in complex traits.

Conclusions:

• The developed web tool aids in understanding fundamental concepts of quantitative genetics and GWAS.
• Additive genetic variance is often the primary driver of individual differences in complex traits.
• Clarification of nonadditive genetic effects' limited role improves the interpretation of GWAS findings.