An accurate model for genetic hitch-hiking

We suggest a simple deterministic approximation for the growth of the favoured-allele frequency during a selective sweep. Using this approximation we introduce an accurate model for genetic hitch-hiking. Only when Ns < 10 (N is the population size and s denotes the selection coefficient), are discrepancies between our approximation and direct numerical simulations of a Moran model noticeable. Our model describes the gene genealogies of a contiguous segment of neutral loci close to the selected one, and it does not assume that the selective sweep happens instantaneously. This enables us to compute SNP distributions on the neutral segment without bias.Comment: 12 pages, 10 figure

Genealogies of two linked neutral loci after a selective sweep in a large population of stochastically varying size

We study the impact of a hard selective sweep on the genealogy of partially linked neutral loci in the vicinity of the positively selected allele. We consider a sexual population of stochastically varying size and, focusing on two neighboring loci, derive an approximate formula for the neutral genealogy of a sample of individuals taken at the end of the sweep. Individuals are characterized by ecological parameters depending on their genetic type and governing their growth rate and interactions with other individuals (competition). As a consequence, the "fitness" of an individual depends on the population state and is not an intrinsic characteristic of individuals. We provide a deep insight into the dynamics of the mutant and wild type populations during the different stages of a selective sweep

A coalescent model for the effect of advantageous mutations on the genealogy of a population

When an advantageous mutation occurs in a population, the favorable allele may spread to the entire population in a short time, an event known as a selective sweep. As a result, when we sample $n$ individuals from a population and trace their ancestral lines backwards in time, many lineages may coalesce almost instantaneously at the time of a selective sweep. We show that as the population size goes to infinity, this process converges to a coalescent process called a coalescent with multiple collisions. A better approximation for finite populations can be obtained using a coalescent with simultaneous multiple collisions. We also show how these coalescent approximations can be used to get insight into how beneficial mutations affect the behavior of statistics that have been used to detect departures from the usual Kingman's coalescent

Identifying Potentially Beneficial Genetic Mutations Associated with Monophyletic Selective Sweep and a Proof-of-Concept Study with Viral Genetic Data

Genetic mutations play a central role in evolution. For a significantly beneficial mutation, a one-time mutation event suffices for the species to prosper and predominate through the process called "monophyletic selective sweep." However, existing methods that rely on counting the number of mutation events to detect selection are unable to find such a mutation in selective sweep. We here introduce a method to detect mutations at the single amino acid/nucleotide level that could be responsible for monophyletic selective sweep evolution. The method identifies a genetic signature associated with selective sweep using the population genetic test statistic Tajima's D We applied the algorithm to ebolavirus, influenza A virus, and severe acute respiratory syndrome coronavirus 2 to identify known biologically significant mutations and unrecognized mutations associated with potential selective sweep. The method can detect beneficial mutations, possibly leading to discovery of previously unknown biological functions and mechanisms related to those mutations.IMPORTANCE In biology, research on evolution is important to understand the significance of genetic mutation. When there is a significantly beneficial mutation, a population of species with the mutation prospers and predominates, in a process called "selective sweep." However, there are few methods that can find such a mutation causing selective sweep from genetic data. We here introduce a novel method to detect such mutations. Applying the method to the genomes of ebolavirus, influenza viruses, and the novel coronavirus, we detected known biologically significant mutations and identified mutations the importance of which is previously unrecognized. The method can deepen our understanding of molecular and evolutionary biology

Identifying the favored mutation in a positive selective sweep.

Most approaches that capture signatures of selective sweeps in population genomics data do not identify the specific mutation favored by selection. We present iSAFE (for "integrated selection of allele favored by evolution"), a method that enables researchers to accurately pinpoint the favored mutation in a large region (∼5 Mbp) by using a statistic derived solely from population genetics signals. iSAFE does not require knowledge of demography, the phenotype under selection, or functional annotations of mutations

Localizing Recent Adaptive Evolution in the Human Genome

Identifying genomic locations that have experienced selective sweeps is an important first step toward understanding the molecular basis of adaptive evolution. Using statistical methods that account for the confounding effects of population demography, recombination rate variation, and single-nucleotide polymorphism ascertainment, while also providing fine-scale estimates of the position of the selected site, we analyzed a genomic dataset of 1.2 million human single-nucleotide polymorphisms genotyped in African-American, European-American, and Chinese samples. We identify 101 regions of the human genome with very strong evidence (p < 10−5) of a recent selective sweep and where our estimate of the position of the selective sweep falls within 100 kb of a known gene. Within these regions, genes of biological interest include genes in pigmentation pathways, components of the dystrophin protein complex, clusters of olfactory receptors, genes involved in nervous system development and function, immune system genes, and heat shock genes. We also observe consistent evidence of selective sweeps in centromeric regions. In general, we find that recent adaptation is strikingly pervasive in the human genome, with as much as 10% of the genome affected by linkage to a selective sweep

An Eco-Evolutionary approach of Adaptation and Recombination in a large population of varying size

We identify the genetic signature of a selective sweep in a population described by a birth-and-death process with density dependent competition. We study the limit behaviour for large K, where K scales the population size. We focus on two loci: one under selection and one neutral. We distinguish a soft sweep occurring after an environmental change, from a hard sweep occurring after a mutation, and express the neutral proportion variation as a function of the ecological parameters, recombination probability r\_K, and K. We show that for a hard sweep, two recombination regimes appear according to the order of r\_K log K.Comment: Accepted in SP

The effect of recurrent mutations on genetic diversity in a large population of varying size

Recurrent mutations are a common phenomenon in population genetics. They may be at the origin of the fixation of a new genotype, if they give a phenotypic advantage to the carriers of the new mutation. In this paper, we are interested in the genetic signature left by a selective sweep induced by recurrent mutations at a given locus from an allele A to an allele a, depending on the mutation frequency. We distinguish three possible scales for the mutation probability per reproductive event, which entail distinct genetic signatures. Besides, we study the hydrodynamic limit of the A- and a-population size dynamics when mutations are frequent, and find non trivial equilibria leading to several possible patterns of polymorphism