We evaluated the sensitivity of the D-statistic, a parsimony-like method widely used to detect gene flow between closely related species. This method has been applied to a variety of taxa with a wide range of divergence times. However, its parameter space and thus its applicability to a wide taxonomic range has not been systematically studied. Divergence time, population size, time of gene flow, distance of outgroup and number of loci were examined in a sensitivity analysis. The sensitivity study shows that the primary determinant of the D-statistic is the relative population size, i.e. the population size scaled by the number of generations since divergence. This is consistent with the fact that the main confounding factor in gene flow detection is incomplete lineage sorting by diluting the signal. The sensitivity of the D-statistic is also affected by the direction of gene flow, size and number of loci. In addition, we examined the ability of the f-statistics, $$ {\widehat{f}}_G $$ and $$ {\widehat{f}}_{hom} $$ , to estimate the fraction of a genome affected by gene flow; while these statistics are difficult to implement to practical questions in biology due to lack of knowledge of when the gene flow happened, they can be used to compare datasets with identical or similar demographic background. The D-statistic, as a method to detect gene flow, is robust against a wide range of genetic distances (divergence times) but it is sensitive to population size. The D-statistic should only be applied with critical reservation to taxa where population sizes are large relative to branch lengths in generations.

Multigene families—immunity genes or sensory receptors, for instance—are often subject to diversifying selection. Allelic diversity may be favored not only through balancing or frequency-dependent selection at individual loci but also by associating different alleles in multicopy gene families. Using a combination of analytical calculations and simulations, we explored a population genetic model of epistatic selection and unequal recombination, where a trade-off exists between the benefit of allelic diversity and the cost of copy abundance. Starting from the neutral case, where we showed that gene copy number is Gamma distributed at equilibrium, we derived also the mean and shape of the limiting distribution under selection. Considering a more general model, which includes variable population size and population substructure, we explored by simulations mean fitness and some summary statistics of the copy number distribution. We determined the relative effects of selection, recombination, and demographic parameters in maintaining allelic diversity and shaping the mean fitness of a population. One way to control the variance of copy number is by lowering the rate of unequal recombination. Indeed, when encoding recombination by a rate modifier locus, we observe exactly this prediction. Finally, we analyzed the empirical copy number distribution of 3 genes in human and estimated recombination and selection parameters of our model.

Selective sweeps, the genetic footprint of positive selection, have been extensively studied in the past decades, with dozens of methods developed to identify swept regions. However, these methods suffer from both false positive and false negative reports, and the candidates identified with different methods are often inconsistent with each other. We propose that a biological cause of this problem can be population subdivision, and a technical cause can be incomplete, or inaccurate, modeling of the dynamic process associated with sweeps. Here we used simulations to show how these effects interact and potentially cause bias. In particular, we show that sweeps maybe misclassified as either hard or soft, when the true time stage of a sweep and that implied, or pre-supposed, by the model do not match. We call this “temporal misclassification”. Similarly, “spatial misclassification (softening)” can occur when hard sweeps, which are imported by migration into a new subpopulation, are falsely identified as soft. This can easily happen in case of local adaptation, i.e. when the sweeping allele is not under positive selection in the new subpopulation, and the underlying model assumes panmixis instead of substructure. The claim that most sweeps in the evolutionary history of humans were soft, may have to be reconsidered in the light of these findings. Identifying the traces of adaptive evolution is still difficult, in particular when populations are not in equilibrium. Using forward-in-time simulations, we studied adaptation by selective sweeps in populations that are divided into demes with limited migration among them. We applied different sweep tests, whose sensitivities are found to vary widely across demographic scenarios and temporal stages. First, the temporal stage of a sweep (ongoing vs completed) significantly affects detection, especially when machine learning algorithms are used and training and test stages do not match. Second, imported alleles from a neighboring deme with local adaptation can result in spurious sweep signals. In both cases, signals are often detected as “soft sweeps” (adaptation from standing variation) while in fact they are “hard sweeps” (adaptation from single mutation), originating in the same subpopulation in the former case and in some other subpopulation in the latter case. We call these phenomena “temporal” and “spatial softening”. Finally, under low migration, the time window in which a sweep can be detected becomes very narrow, and power tends to be low. Generally, however, haplotype-based methods seem to be less affected than frequency-spectrum-based tests.

Some unique asexual species persist over time and contradict the consensus that sex is a prerequisite for long-term evolutionary survival. How they escape the dead-end fate remains enigmatic. Here, we generated a haplotype-resolved genome assembly on the basis of a single individual and collected genomic data from worldwide populations of the parthenogenetic diploid oribatid mite Platynothrus peltifer to identify signatures of persistence without sex. We found that haplotypes diverge independently since the transition to asexuality at least 20 million years ago in European lineages, contrasting Japanese and Canadian lineages. Multiple lines of evidence indicate conservation of one haplotype copy and relaxed selection in the other for the ancient asexual lineages. These findings highlight the evolutionary genomic singularities of ancient asexual oribatid mites that may have contributed to escaping the early demise typically associated with asexuality.

Some unique asexual species persist over time and contradict the consensus that sex is a prerequisite for long-term evolutionary survival. How they escape the dead-end fate remains enigmatic. Here, we generated a haplotype-resolved genome assembly based on a single individual and collected genomic data from worldwide populations of the parthenogenetic diploid oribatid mite Platynothrus peltifer to identify signatures of persistence without sex. We found that haplotypes diverge independently since the transition to asexuality at least 20 my ago. Multiple lines of evidence indicate disparate evolutionary trajectories between haplotypic blocks. Our findings imply that such haplotypic independence can lead to non-canonical routes of evolvability, helping some species to adapt, diversify and persist for millions of years in the absence of sex. One-Sentence Summary: Functionally different chromosome sets in an asexual mite species showcase a survival strategy spanning millions of years.