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Robust Estimation of Recent Effective Population Size from Number of Independent Origins in Soft Sweeps.

ABSTRACT: Estimating recent effective population size is of great importance in characterizing and predicting the evolution of natural populations. Methods based on nucleotide diversity may underestimate current day effective population sizes due to historical bottlenecks, whereas methods that reconstruct demographic history typically only detect long-term variations. However, soft selective sweeps, which leave a fingerprint of mutational history by recurrent mutations on independent haplotype backgrounds, holds promise of an estimate more representative of recent population history. Here, we present a simple and robust method of estimation based only on knowledge of the number of independent recurrent origins and the current frequency of the beneficial allele in a population sample, independent of the strength of selection and age of the mutation. Using a forward-time theoretical framework, we show the mean number of origins is a function of ?=2N? and current allele frequency, through a simple equation, and the distribution is approximately Poisson. This estimate is robust to whether mutants preexisted before selection arose and is equally accurate for diploid populations with incomplete dominance. For fast (e.g., seasonal) demographic changes compared with time scale for fixation of the mutant allele, and for moderate peak-to-trough ratios, we show our constant population size estimate can be used to bound the maximum and minimum population size. Applied to the Vgsc gene of Anopheles gambiae, we estimate an effective population size of roughly 6×107, and including seasonal demographic oscillations, a minimum effective population size >3×107, and a maximum <6×109, suggesting a mean ?109.

SUBMITTER: Khatri BS

PROVIDER: S-EPMC6736332 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature

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Robust Estimation of Recent Effective Population Size from Number of Independent Origins in Soft Sweeps.

Khatri Bhavin S BS Burt Austin A

Molecular biology and evolution 20190901 9

Estimating recent effective population size is of great importance in characterizing and predicting the evolution of natural populations. Methods based on nucleotide diversity may underestimate current day effective population sizes due to historical bottlenecks, whereas methods that reconstruct demographic history typically only detect long-term variations. However, soft selective sweeps, which leave a fingerprint of mutational history by recurrent mutations on independent haplotype backgrounds ...[more]

PMID: 30968124

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Project description:BackgroundEffective population size (Ne) is a crucial parameter in conservation genetics and animal breeding. A recent method, implemented by the software GONE, has been shown to be rather accurate in estimating recent historical changes in Ne from a single sample of individuals. However, GONE estimations assume that the population being studied has remained isolated for a period of time, that is, without migration or confluence of other populations. If this occurs, the estimates of Ne can be heavily biased. In this paper, we evaluate the impact of migration and admixture on the estimates of historical Ne provided by GONE through a series of computer simulations considering several scenarios: (a) the mixture of two or more ancestral populations; (b) subpopulations that continuously exchange individuals through migration; (c) populations receiving migrants from a large source; and (d) populations with balanced systems of chromosomal inversions, which also generate genetic structure.ResultsOur results indicate that the estimates of historical Ne provided by GONE may be substantially biased when there has been a recent mixture of populations that were previously separated for a long period of time. Similarly, biases may occur when the rate of continued migration between populations is low, or when chromosomal inversions are present at high frequencies. However, some biases due to population structuring can be eliminated by conducting population structure analyses and restricting the estimation to the differentiated groups. In addition, disregarding the genomic regions that are involved in inversions can also remove biases in the estimates of Ne.ConclusionsDifferent kinds of deviations from isolation and panmixia of the populations can generate biases in the recent historical estimates of Ne. Therefore, estimation of past demography could benefit from performing population structure analyses beforehand, by mitigating the impact of these biases on historical Ne estimates.

Project description:The single celled eukaryote Trypanosoma cruzi, a parasite transmitted by numerous species of triatomine bug in the Americas, causes Chagas disease in humans. T. cruzi generally reproduces asexually and appears to have a clonal population structure. However, two of the six major circulating genetic lineages, TcV and TcVI, are TcII-TcIII inter-lineage hybrids that are frequently isolated from humans in regions where chronic Chagas disease is particularly severe. Nevertheless, a prevalent view is that hybridisation events in T. cruzi were evolutionarily ancient and that active recombination is of little epidemiological importance. We analysed genotypes of hybrid and non-hybrid T. cruzi strains for markers representing three distinct evolutionary rates: nuclear GPI sequences (n?=?88), mitochondrial COII-ND1 sequences (n?=?107) and 28 polymorphic microsatellite loci (n?=?35). Using Maximum Likelihood and Bayesian phylogenetic approaches we dated key evolutionary events in the T. cruzi clade including the emergence of hybrid lineages TcV and TcVI, which we estimated to have occurred within the last 60,000 years. We also found evidence for recent genetic exchange between TcIII and TcIV and between TcI and TcIV. These findings show that evolution of novel recombinants remains a potential epidemiological risk. The clearly distinguishable microsatellite genotypes of TcV and TcVI were highly heterozygous and displayed minimal intra-lineage diversity indicative of even earlier origins than sequence-based estimates. Natural hybrid genotypes resembled typical meiotic F1 progeny, however, evidence for mitochondrial introgression, absence of haploid forms and previous experimental crosses indicate that sexual reproduction in T. cruzi may involve alternatives to canonical meiosis. Overall, the data support two independent hybridisation events between TcII and TcIII and a recent, rapid spread of the hybrid progeny in domestic transmission cycles concomitant with, or as a result of, disruption of natural transmission cycles by human activities.

Project description:Characterizing the nature of the adaptive process at the genetic level is a central goal for population genetics. In particular, we know little about the sources of adaptive substitution or about the number of adaptive variants currently segregating in nature. Historically, population geneticists have focused attention on the hard-sweep model of adaptation in which a de novo beneficial mutation arises and rapidly fixes in a population. Recently more attention has been given to soft-sweep models, in which alleles that were previously neutral, or nearly so, drift until such a time as the environment shifts and their selection coefficient changes to become beneficial. It remains an active and difficult problem, however, to tease apart the telltale signatures of hard vs. soft sweeps in genomic polymorphism data. Through extensive simulations of hard- and soft-sweep models, here we show that indeed the two might not be separable through the use of simple summary statistics. In particular, it seems that recombination in regions linked to, but distant from, sites of hard sweeps can create patterns of polymorphism that closely mirror what is expected to be found near soft sweeps. We find that a very similar situation arises when using haplotype-based statistics that are aimed at detecting partial or ongoing selective sweeps, such that it is difficult to distinguish the shoulder of a hard sweep from the center of a partial sweep. While knowing the location of the selected site mitigates this problem slightly, we show that stochasticity in signatures of natural selection will frequently cause the signal to reach its zenith far from this site and that this effect is more severe for soft sweeps; thus inferences of the target as well as the mode of positive selection may be inaccurate. In addition, both the time since a sweep ends and biologically realistic levels of allelic gene conversion lead to errors in the classification and identification of selective sweeps. This general problem of "soft shoulders" underscores the difficulty in differentiating soft and partial sweeps from hard-sweep scenarios in molecular population genomics data. The soft-shoulder effect also implies that the more common hard sweeps have been in recent evolutionary history, the more prevalent spurious signatures of soft or partial sweeps may appear in some genome-wide scans.

Dataset Information

Robust Estimation of Recent Effective Population Size from Number of Independent Origins in Soft Sweeps.

Publications

Robust Estimation of Recent Effective Population Size from Number of Independent Origins in Soft Sweeps.

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