Genetic Diversity in the Interference Selection Limit

Pervasive natural selection can strongly influence observed patterns of genetic variation, but these effects remain poorly understood when multiple selected variants segregate in nearby regions of the genome. Classical population genetics fails to account for interference between linked mutations, which grows increasingly severe as the density of selected polymorphisms increases. Here, we describe a simple limit that emerges when interference is common, in which the fitness effects of individual mutations play a relatively minor role. Instead, similar to models of quantitative genetics, molecular evolution is determined by the variance in fitness within the population, defined over an effectively asexual segment of the genome (a “linkage block”). We exploit this insensitivity in a new “coarse-grained” coalescent framework, which approximates the effects of many weakly selected mutations with a smaller number of strongly selected mutations that create the same variance in fitness. This approximation generates accurate and efficient predictions for silent site variability when interference is common. However, these results suggest that there is reduced power to resolve individual selection pressures when interference is sufficiently widespread, since a broad range of parameters possess nearly identical patterns of silent site variability.Author Summary: A central goal of evolutionary genetics is to understand how natural selection influences DNA sequence variability. Yet while empirical studies have uncovered significant evidence for selection in many natural populations, a rigorous characterization of these selection pressures has so far been difficult to achieve. The problem is that when selection acts on linked loci, it introduces correlations along the genome that are difficult to disentangle. These “interference” effects have been extensively studied in simulation, but theory still struggles to account for interference in predicted patterns of sequence variability, which limits the quantitative conclusions that can be drawn from modern sequence data. Here, we show that in spite of this complexity, simple behavior emerges in the limit that interference is common. Patterns of molecular evolution depend on the variance in fitness within the population, and are only weakly influenced by the fitness effects of individual mutations. We leverage this “emergent simplicity” to establish a new framework for predicting genetic diversity in these populations. Our results have important practical implications for the interpretation of natural sequence variability, particularly in regions of low recombination, and suggest an inherent “resolution limit” for the quantitative inference of selection pressures from sequence polymorphism data.