Reconciling quantitative genetics and molecular population genetics to understand polygenic adaptation

Molecular population genetics and quantitative genetics use different approaches to study adaptive evolution. Molecular population genetics assumes that adaptation occurs primarily through selective sweeps, i.e., through the frequency increase of a single new beneficial allele until it becomes fixed. Quantitative genetics traditionally assumes an underlying genetic architecture with an infinite number of loci each of infinitesimal effect, i.e., the infinitesimal model. However, it is becoming clear that both “sweeps” and “polygenic adaptation” are the endpoints of a scale, rather than mutually exclusive alternatives. This leaves considerable room for adaptive scenarios that lie between the extremes. To understand adaptation, we need to go beyond the distinction between selective sweeps and polygenic adaptation. Rather, a generalized framework for the description of adaptive processes is needed. A helpful concept is the adaptive architecture, which focuses on how the realized architecture of adaptation (i.e. the numbers, effect sizes, and interactions of alleles contributing to adaptation) is shaped by selection scenarios and population attributes (e.g. pleiotropic constraints, initial frequencies, and associations between alleles).

A key goal of this STN is to overcome the traditional divide between molecular population genetics and quantitative genetics and to integrate the two fields to better understand polygenic adaptation. With the help of this STN, we intend to facilitate the synergy between empirical and theoretical studies of polygenic adaptation. Polygenic adaptation is being investigated by many groups (including members of this STN) from either a theoretical or empirical aspect using different study systems, natural or experimental populations. But greater progress in understanding polygenic adaptation requires an open and active discussion among different research groups, and the goal of this STN is to create such a community. In this STN, we aim to engage the scientific community and emphasize that to achieve a unified framework to study adaptation more realistic theoretical models and new suitable empirical datasets are needed. We have organized a series of workshops and symposia throughout the years (see Resources). In this STN, we aim for careful consideration of the conceptual frameworks and assumptions underlying both fields, along with time to discuss different views and common concepts.

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