The ubiquity of genetic mixing in nature has eluded unified explanation since the time of Darwin. Conditions that promote the evolution of genetic mixing (recombination) are fairly well understood: it is favored when genomes tend to contain more selectively mismatched combinations of alleles than can be explained by chance alone. Yet, while a variety of theoretical approaches have been put forth to explain why such conditions would have an overarching tendency to prevail in natural populations, each has turned out to be of limited scope and applicability. In our two-part study, we show that, simply and surprisingly, the action of natural selection acting on standing heritable variation creates conditions favoring the evolution of recombination. In this paper, we focus on the mean selective advantage created by recombination between individuals from the same population. We find that the mean selective advantages of recombinants and recombination are non-negative, in expectation, independently of how genic fitnesses in the standing variation are distributed. We further find that the expected asymptotic frequency of a recombination-competent modifier is effectively equal to the probability that the fittest possible genotype is a virtual recombinant; remarkably, expected asymptotic modifier frequency is independent of the strength of selection. Taken together, our findings indicate that the evolution of recombination should be promoted in expectation wherever natural selection is operating.

In the context of the ongoing SARS-CoV-2 pandemic, health officials warn that vaccines must be uniformly distributed within and among countries if we are to quell the pandemic. Yet there has been little critical assessment of the underlying reasons for this warning. Here, we explicitly show why vaccine equity is necessary. We begin by drawing an analogy to studies showing how disparities in drug concentration within a single host can promote the evolution of drug resistance, and we then proceed to mathematical modeling and simulation of vaccine escape evolution in structured host populations. Perhaps counter-intuitively, we find that vaccine escape mutants are less likely to come from vaccinated regions where there is strong selection pressure for vaccine escape and more likely to come from a neighboring unvaccinated region where there is no selection for escape. Unvaccinated geographic regions thus provide evolutionary reservoirs from which vaccine escape mutants can arise and infect neighboring vaccinated regions, causing new local epidemics within those regions and beyond. Our findings have timely implications for vaccine rollout strategies and public health policy.

Shuffling one's genetic material with another individual seems a risky endeavor more likely to decrease than to increase offspring fitness. This intuitive argument is commonly employed to explain why the ubiquity of sex and recombination in nature is enigmatic. It is predicated on the notion that natural selection assembles selectively well-matched combinations of genes that recombination would break up resulting in low-fitness offspring -- a notion so intuitive that it is often stated in the literature as a self-evident premise. We show, however, that this common premise is only self evident on the surface and that, upon closer examination, it is fundamentally flawed: we find that natural selection in fact has an encompassing tendency to assemble selectively mismatched combinations of alleles; recombination breaks up these selectively mismatched combinations (on average), assembles selectively matched combinations, and should thus be favored. The new perspective our findings offer suggests that sex and recombination are not so enigmatic but are instead natural and unavoidable byproducts of natural selection.

Exchanging genetic material with another individual seems risky from an evolutionary standpoint, and yet living things across all scales and phyla do so quite regularly. The pervasiveness of such genetic exchange, or recombination, in nature has defied explanation since the time of Darwin1–4. Conditions that favor recombination, however, are well-understood: recombination is advantageous when the genomes of individuals in a population contain more selectively mismatched combinations of alleles than can be explained by chance alone. Recombination remedies this imbalance by shuffling alleles across individuals. The great difficulty in explaining the ubiquity of recombination in nature lies in identifying a source of this imbalance that is comparably ubiquitous. Intuitively, it would seem that natural selection should reduce the imbalance by favoring selectively matched combinations of high-fitness alleles. We show, however, that this widely-held intuition is wrong; to the contrary, we find that natural selection has an encompassing tendency to assemble selectively mismatched combinations of alleles, thereby increasing the imbalance and promoting the evolution of recombination across demes in a structured population. We further show that, on average, selection-driven changes in allele frequencies over time within a single evolving population generate a net imbalance that promotes recombination, and additive fitness effects drive this imbalance. Our findings provide a novel theoretical point of departure from which the enormous body of established work on the evolution of sex and recombination may be viewed anew. They further suggest that recombination evolved and is maintained more as a byproduct of natural selection than as a catalyst.

The fraction of the human genome that is functional is a question of both evolutionary and practical importance. Studies of sequence divergence have suggested that the functional fraction of the human genome is likely to be no more than ∼15%. In contrast, the ENCODE project, a systematic effort to map regions of transcription, transcription factor association, chromatin structure, and histone modification, assigned function to 80% of the human genome. In this article, we examine whether and how an analysis based on mutational load might set a limit on the functional fraction. In order to do so, we characterize the distribution of fitness of a large, finite, diploid population at mutation-selection equilibrium. In particular, if mean fitness is ∼1, the fitness of the fittest individual likely to occur cannot be unreasonably high. We find that at equilibrium, the distribution of log fitness has variance nus, where u is the per-base deleterious mutation rate, n is the number of functional sites (and hence incorporates the functional fraction f), and s is the selection coefficient of deleterious mutations. In a large (N=109) reproducing population, the fitness of the fittest individual likely to exist is ∼e5nus. These results apply to both additive and recessive fitness schemes. Our approach is different from previous work that compared mean fitness at mutation-selection equilibrium with the fitness of an individual who has no deleterious mutations; we show that such an individual is exceedingly unlikely to exist. We find that the functional fraction is not very likely to be limited substantially by mutational load, and that any such limit, if it exists, depends strongly on the selection coefficients of new deleterious mutations.