Statistical Genetics and Evolution of Quantitative Traits

TL;DR

This paper reviews the concept of Quasi-Linkage Equilibrium (QLE) in multilocus evolution, explaining its mathematical framework and implications for understanding the genetics of complex traits in sexual populations.

Contribution

It provides a simplified exposition of QLE and demonstrates how key quantitative genetics results emerge within this framework, clarifying its applicability and limitations.

Findings

QLE simplifies multilocus genetic dynamics under weak selection and recombination.

Key quantitative genetics principles are derived from QLE dynamics.

Breakdown of QLE affects population structure and evolutionary trajectories.

Abstract

The distribution and heritability of many traits depends on numerous loci in the genome. In general, the astronomical number of possible genotypes makes the system with large numbers of loci difficult to describe. Multilocus evolution, however, greatly simplifies in the limit of weak selection and frequent recombination. In this limit, populations rapidly reach Quasi-Linkage Equilibrium (QLE) in which the dynamics of the full genotype distribution, including correlations between alleles at different loci, can be parameterized by the allele frequencies. This review provides a simplified exposition of the concept and mathematics of QLE which is central to the statistical description of genotypes in sexual populations. We show how key results of Quantitative Genetics such as the generalized Fisher's "Fundamental Theorem", along with Wright's Adaptive Landscape, emerge within QLE from the dynamics of the genotype distribution. We then discuss under what circumstances QLE is applicable, and what the breakdown of QLE implies for the population structure and the dynamics of selection. Understanding of the fundamental aspects of multilocus evolution obtained through simplified models may be helpful in providing conceptual and computational tools to address the challenges arising in the studies of complex quantitative phenotypes of practical interest.