Evidence for adaptive phenotypic differentiation in Baltic Sea sticklebacks

The evidence for adaptive phenotypic differentiation in mobile marine species remains scarce, partly due to the difficulty of obtaining quantitative genetic data to demonstrate the genetic basis of the observed phenotypic differentiation. Using a combination of phenotypic and molecular genetic approaches, we elucidated the relative roles of natural selection and genetic drift in explaining lateral plate number differentiation in threespine sticklebacks (Gasterosteus aculeatus) across the entire Baltic Sea basin (approximately 392 000 km²). We found that phenotypic differentiation (P_ST = 0.213) in plate number exceeded that in neutral markers (F_ST = 0.008), suggesting an adaptive basis for the observed differentiation. Because a close correspondence was found between plate phenotype and genotype at a quantitative trait loci (QTL; STN381) tightly linked to the gene (Ectodysplasin) underlying plate variation, the evidence for adaptive differentiation was confirmed by comparison of F_ST at the QTL (F_STQ = 0.089) with F_ST at neutral marker loci. Hence, the results provide a comprehensive demonstration of adaptive phenotypic differentiation in a high‐gene‐flow marine environment with direct, rather than inferred, verification for the genetic basis of this differentiation. In general, the results illustrate the utility of P_ST–F_ST–F_STQ comparisons in uncovering footprints of natural selection and evolution and add to the growing evidence for adaptive genetic differentiation in high‐gene‐flow marine environments, including that of the relatively young Baltic Sea.     

Calculations of population differentiation based on GST and D: forget GST but not all of statistics!

G _ST‐values and its relatives (F_ST) belong to the most used parameters to define genetic differences between populations. Originally, they were developed for allozymes with very low number of alleles. Using highly polymorphic microsatellite markers it was often puzzling that G_ST‐values were very low but statistically significant. In their papers, Jost (2008) and Hedrick (2005) explained that G_ST‐values do not show genetic differentiation, and Jost suggested calculating D‐values instead. Theoretical mathematical considerations are often difficult to follow; therefore, we chose an applied approach comparing two artificial populations with different number of alleles at equal frequencies and known genetic divergence. Our results show that even for more than one allele per population G_ST‐values do not calculate population differentiation correctly; in contrast, D‐values do reflect the genetic differentiation indicating that data based on G_ST‐values need to be re‐evaluated. In our approach, statistical evaluations remained similar. We provide information about the impact of different sample sizes on D‐values in relation to number of alleles and genetic divergence.     

Statistical power for detecting genetic divergence—organelle versus nuclear markers

Statistical power is critical in conservation for detecting genetic differences in space or time from allele frequency data. Organelle and nuclear genetic markers have fundamentally different transmission dynamics; the potential effect of these differences on power to detect divergence have been speculated on but not investigated. We examine, analytically and with computer simulations, the relative performance of organelle and nuclear markers under basic, ideal situations. We conclude that claims of a generally higher resolving power of either marker type are not correct. The ratio R = F _ST,organelle/F _ST,nuclear varies between 1 and 4 during differentiation and this greatly affects the power relationship. When nuclear F _ST is associated with organelle differentiation four times higher, the power of the organelle marker is similar to two nuclear loci with the same allele frequency distribution. With large sample sizes (n ≥ 50) and several populations or many alleles per locus (≥5), the power difference may typically be disregarded when nuclear F _ST > 0.05. To correctly interpret observed patterns of genetic differentiation in practical situations, the expected F _STs and the statistical properties (i.e., power analysis) of the genetic markers used should be evaluated, taking the observed allele frequency distributions into consideration.     

neogen: A tool to predict genetic effective population size (Ne) for species with generational overlap and to assist empirical Ne study design

Molecular genetic estimates of population effective size (N_e) lose accuracy and precision when insufficient numbers of samples or loci are used. Ideally, researchers would like to forecast the necessary power when planning their project. neogen (genetic N_e for Overlapping Generations) enables estimates of precision and accuracy in advance of empirical investigation and allows exploration of the power available in different user‐specified age‐structured sampling schemes. neogen provides a population simulation and genetic power analysis framework that simulates the demographics, genetic composition, and N_e, from species‐specific life history, mortality, population size, and genetic priors. neogen guides the user to establish a tractable sampling regime and to determine the numbers of samples and microsatellite or SNP loci required for accurate and precise genetic N_e estimates when sampling a natural population. neogen is useful at multiple stages of a study's life cycle: when budgeting, as sampling and locus development progresses, and for corroboration when empirical N_e estimates are available. The underlying model is applicable to a wide variety of iteroparous species with overlapping generations (e.g., mammals, birds, reptiles, long‐lived fishes). In this paper, we describe the neogen model, detail the workflow for the point‐and‐click software, and explain the graphical results. We demonstrate the use of neogen with empirical Australian east coast zebra shark (Stegostoma fasciatum) data. For researchers wishing to make accurate and precise genetic N_e estimates for overlapping generations species, neogen facilitates planning for sample and locus acquisition, and with existing empirical genetic N_e estimates neogen can corroborate population demographic and life history properties.     

A Beta-mixture model for assessing genetic population structure

Summary An important fraction of recently generated molecular data is dominant markers. They contain substantial information about genetic variation but dominance makes it impossible to apply standard techniques to calculate measures of genetic differentiation, such as F‐statistics. In this article, we propose a new Bayesian beta‐mixture model that more accurately describes the genetic structure from dominant markers and estimates multiple F_ST s from the sample. The model also has important application for codominant markers and single‐nucleotide polymorphism (SNP) data. The number of F_ST is assumed unknown beforehand and follows a random distribution. The reversible jump algorithm is used to estimate the unknown number of multiple F_ST s. We evaluate the performance of three split proposals and the overall performance of the proposed model based on simulated dominant marker data. The model could reliably identify and estimate a spectrum of degrees of genetic differentiation present in multiple loci. The estimates of F_ST s also incorporate uncertainty about the magnitude of within‐population inbreeding coefficient. We illustrate the method with two examples, one using dominant marker data from a rare orchid and the other using codominant marker data from human populations.     

Comparing Pool‐seq,Rapture, and GBS genotyping for inferring weak population structure: The American lobster (Homarus americanus) as a case study

Unraveling genetic population structure is challenging in species potentially characterized by large population size and high dispersal rates, often resulting in weak genetic differentiation. Genotyping a large number of samples can improve the detection of subtle genetic structure, but this may substantially increase sequencing cost and downstream bioinformatics computational time. To overcome this challenge, alternative, cost‐effective sequencing approaches, namely Pool‐seq and Rapture, have been developed. We empirically measured the power of resolution and congruence of these two methods in documenting weak population structure in nonmodel species with high gene flow comparatively to a conventional genotyping‐by‐sequencing (GBS) approach. For this, we used the American lobster (Homarus americanus) as a case study. First, we found that GBS, Rapture, and Pool‐seq approaches gave similar allele frequency estimates (i.e., correlation coefficient over 0.90) and all three revealed the same weak pattern of population structure. Yet, Pool‐seq data showed F_ST estimates three to five times higher than GBS and Rapture, while the latter two methods returned similar F_ST estimates, indicating that individual‐based approaches provided more congruent results than Pool‐seq. We conclude that despite higher costs, GBS and Rapture are more convenient approaches to use in the case of species exhibiting very weak differentiation. While both GBS and Rapture approaches provided similar results with regard to estimates of population genetic parameters, GBS remains more cost‐effective in project involving a relatively small numbers of genotyped individuals (e.g., <1,000). Overall, this study illustrates the complexity of estimating genetic differentiation and other summary statistics in complex biological systems characterized by large population size and migration rates.     

Geography disentangles introgression from ancestral polymorphism in Lake Malawi cichlids

Phenotypically diverse Lake Malawi cichlids exhibit similar genomes. The extensive sharing of genetic polymorphism among forms has both intrigued and frustrated biologists trying to understand the nature of diversity in this and other rapidly evolving systems. Shared polymorphism might result from hybridization and/or the retention of ancestrally polymorphic alleles. To examine these alternatives, we used new genomic tools to characterize genetic differentiation in widespread, geographically structured populations of Labeotropheus fuelleborni and Metriaclima zebra. These phenotypically distinct species share mitochondrial DNA (mtDNA) haplotypes and show greater mtDNA differentiation among localities than between species. However, Bayesian analysis of nuclear single nucleotide polymorphism (SNP) data revealed two distinct genetic clusters corresponding perfectly to morphologically diagnosed L. fuelleborni and M. zebra. This result is a function of the resolving power of the multi‐locus dataset, not a conflict between nuclear and mitochondrial partitions. Locus‐by‐locus analysis showed that mtDNA differentiation between species (F_CT) was nearly identical to the median single‐locus SNP F_CT. Finally, we asked whether there is evidence for gene flow at sites of co‐occurrence. We used simulations to generate a null distribution for the level of differentiation between co‐occurring populations of L. fuelleborni and M. zebra expected if there was no hybridization. The null hypothesis was rejected for the SNP data; populations that co‐occur at rock reef sites were slightly more similar than expected by chance, suggesting recent gene flow. The coupling of numerous independent markers with extensive geographic sampling and simulations utilized here provides a framework for assessing the prevalence of gene flow in recently diverged species.     

Evaluating the resolution power of new microsatellites for species identification and stock delimitation in the Cape hakes Merluccius paradoxus and Merluccius capensis (Teleostei: Merlucciidae)

The utility of 15 new and 17 previously published microsatellite markers was evaluated for species identification and stock delimitation in the deep‐water hake Merluccius paradoxus and the shallow‐water hake Merluccius capensis. A total of 14 microsatellites were polymorphic in M. paradoxus and 10 in M. capensis. Two markers could individually discriminate the species using Bayesian clustering methods and a statistical power analysis showed that the set of markers for each species is likely to detect subtle genetic differentiation (F_ST < 0·006) that will be valuable to delimit and characterize genetic stocks.     

Effects of life-history traits and species distribution on genetic structure at maternally inherited markers in European trees and shrubs

Aim To examine relationships between life‐history traits, ecological and chorological characteristics of woody plant species and patterns of genetic differentiation among populations as assessed by chloroplast DNA (cpDNA) markers, and to compare them with patterns previously described from nuclear markers. Location Europe. Methods Data on cpDNA variation were compiled for 29 temperate European broad‐leaved tree and shrub species. Six qualitative and three quantitative characters of the species were tested for their relationship with two parameters of genetic population differentiation (G_ST and N_ST). Both direct species comparisons and phylogenetically independent contrast analyses were performed. Results When the phylogeny was not taken into account, five characters were significantly related to levels of population differentiation. The relationship disappeared in all but two cases (distribution type and seed mass) when analyses controlled for phylogenetic relationships among species. Main conclusions The correlation between distribution type (boreal‐temperate or temperate) and cpDNA differentiation of temperate European woody plant species suggests that their Quaternary history, in particular the location and isolation of their glacial refugia, is an important determinant of their present‐day level of genetic structure. By contrast, the relationship between life‐history traits and genetic differentiation at maternally inherited markers is weaker, especially when phylogenetic effects are controlled for.     

Evidence for nonallopatric speciation among closely related sympatric Heliotropium species in the Atacama Desert

The genetic structure of populations of closely related, sympatric species may hold the signature of the geographical mode of the speciation process. In fully allopatric speciation, it is expected that genetic differentiation between species is homogeneously distributed across the genome. In nonallopatric speciation, the genomes may remain undifferentiated to a large extent. In this article, we analyzed the genetic structure of five sympatric species from the plant genus Heliotropium in the Atacama Desert. We used amplified fragment length polymorphisms (AFLPs) to characterize the genetic structure of these species and evaluate their genetic differentiation as well as the number of loci subject to positive selection using divergence outlier analysis (DOA). The five species form distinguishable groups in the genetic space, with zones of overlap, indicating that they are possibly not completely isolated. Among‐species differentiation accounts for 35% of the total genetic differentiation (F_ST = 0.35), and F_ST between species pairs is positively correlated with phylogenetic distance. DOA suggests that few loci are subject to positive selection, which is in line with a scenario of nonallopatric speciation. These results support the idea that sympatric species of Heliotropium sect. Cochranea are under an ongoing speciation process, characterized by a fluctuation of population ranges in response to pulses of arid and humid periods during Quaternary times.     

Detecting selection along environmental gradients: analysis of eight methods and their effectiveness for outbreeding and selfing populations

Thanks to genome‐scale diversity data, present‐day studies can provide a detailed view of how natural and cultivated species adapt to their environment and particularly to environmental gradients. However, due to their sensitivity, up‐to‐date studies might be more sensitive to undocumented demographic effects such as the pattern of migration and the reproduction regime. In this study, we provide guidelines for the use of popular or recently developed statistical methods to detect footprints of selection. We simulated 100 populations along a selective gradient and explored different migration models, sampling schemes and rates of self‐fertilization. We investigated the power and robustness of eight methods to detect loci potentially under selection: three designed to detect genotype–environment correlations and five designed to detect adaptive differentiation (based on F_ST or similar measures). We show that genotype–environment correlation methods have substantially more power to detect selection than differentiation‐based methods but that they generally suffer from high rates of false positives. This effect is exacerbated whenever allele frequencies are correlated, either between populations or within populations. Our results suggest that, when the underlying genetic structure of the data is unknown, a number of robust methods are preferable. Moreover, in the simulated scenario we used, sampling many populations led to better results than sampling many individuals per population. Finally, care should be taken when using methods to identify genotype–environment correlations without correcting for allele frequency autocorrelation because of the risk of spurious signals due to allele frequency correlations between populations.     

Comparison of genetic differentiation at marker loci and quantitative traits

The comparison of the degree of differentiation in neutral marker loci and genes coding quantitative traits with standardized and equivalent measures of genetic differentiation (F_ST and Q_ST, respectively) can provide insights into two important but seldom explored questions in evolutionary genetics: (i) what is the relative importance of random genetic drift and directional natural selection as causes of population differentiation in quantitative traits, and (ii) does the degree of divergence in neutral marker loci predict the degree of divergence in genes coding quantitative traits? Examination of data from 18 independent studies of plants and animals using both standard statistical and meta‐analytical methods revealed a number of interesting points. First, the degree of differentiation in quantitative traits (Q_ST) typically exceeds that observed in neutral marker genes (F_ST), suggesting a prominent role for natural selection in accounting for patterns of quantitative trait differentiation among contemporary populations. Second, the F_ST – Q_ST difference is more pronounced for allozyme markers and morphological traits, than for other kinds of molecular markers and life‐history traits. Third, very few studies reveal situations were Q_ST < F_ST, suggesting that selection pressures, and hence optimal phenotypes, in different populations of the same species are unlikely to be often similar. Fourth, there is a strong correlation between Q_ST and F_ST indices across the different studies for allozyme (r=0.81), microsatellite (r=0.87) and combined (r=0.75) marker data, suggesting that the degree of genetic differentiation in neutral marker loci is closely predictive of the degree of differentiation in loci coding quantitative traits. However, these interpretations are subject to a number of assumptions about the data and methods used to derive the estimates of population differentiation in the two sets of traits.     

Epigenetic variation reflects dynamic habitat conditions in a rare floodplain herb

Variation of DNA methylation is thought to play an important role for rapid adjustments of plant populations to dynamic environmental conditions, thus compensating for the relatively slow response time of genetic adaptations. However, genetic and epigenetic variation of wild plant populations has not yet been directly compared in fast changing environments. Here, we surveyed populations of Viola elatior from two adjacent habitat types along a successional gradient characterized by strong differences in light availability. Using amplified fragment length polymorphisms (AFLP) and methylation‐sensitive amplification polymorphisms (MSAP) analyses, we found relatively low levels of genetic (H′_gen = 0.19) and epigenetic (H′_epi = 0.23) diversity and high genetic (?_ST = 0.72) and epigenetic (?_ST = 0.51) population differentiation. Diversity and differentiation were significantly correlated, suggesting that epigenetic variation partly depends on the same driving forces as genetic variation. Correlation‐based genome scans detected comparable levels of genetic (17.0%) and epigenetic (14.2%) outlier markers associated with site specific light availability. However, as revealed by separate differentiation‐based genome scans for AFLP, only few genetic markers seemed to be actually under positive selection (0–4.5%). Moreover, principal coordinates analyses and Mantel tests showed that overall epigenetic variation was more closely related to habitat conditions, indicating that environmentally induced methylation changes may lead to convergence of populations experiencing similar habitat conditions and thus may play a major role for the transient and/or heritable adjustment to changing environments. Additionally, using a new MSAP‐scoring approach, we found that mainly the unmethylated (?_ST = 0.60) and CG‐methylated states (?_ST = 0.46) of epiloci contributed to population differentiation and putative habitat‐related adaptation, whereas CHG‐hemimethylated states (?_ST = 0.21) only played a marginal role.     

Low population genetic differentiation in the Orchidaceae: implications for the diversification of the family

A leading hypothesis for the immense diversity of the Orchidaceae is that skewed mating success and small, disjunct populations lead to strong genetic drift and switches between adaptive peaks. This mechanism is only possible under conditions of low gene flow that lead to high genetic differentiation among populations. We tested whether orchids typically exhibit high levels of population genetic differentiation by conducting a meta‐analysis to compare mean levels of population genetic differentiation (F_ST) between orchids and other diverse families and between rare and common orchids. Compared with other families, the Orchidaceae is typically characterized by relatively low genetic differentiation among populations (mean F_ST = 0.146) at allozyme loci. Rare terrestrial orchids showed higher population genetic differentiation than common orchids, although this value was still lower than the mean for most plant families. All lines of evidence suggest that orchids are typically characterized by low levels of population genetic differentiation, even in species with naturally disjunct populations. As such, we found no strong evidence that genetic drift in isolated populations has played a major role in the diversification of the Orchidaceae. Further research into the diversification of the family needs to unravel the relative roles of biotic and environmental selective pressures in the speciation of orchids.     

Comparing RADseq and microsatellites for estimating genetic diversity and relatedness — Implications for brown trout conservation

The conservation and management of endangered species requires information on their genetic diversity, relatedness and population structure. The main genetic markers applied for these questions are microsatellites and single nucleotide polymorphisms (SNPs), the latter of which remain the more resource demanding approach in most cases. Here, we compare the performance of two approaches, SNPs obtained by restriction‐site‐associated DNA sequencing (RADseq) and 16 DNA microsatellite loci, for estimating genetic diversity, relatedness and genetic differentiation of three, small, geographically close wild brown trout (Salmo trutta) populations and a regionally used hatchery strain. The genetic differentiation, quantified as F_ST, was similar when measured using 16 microsatellites and 4,876 SNPs. Based on both marker types, each brown trout population represented a distinct gene pool with a low level of interbreeding. Analysis of SNPs identified half‐ and full‐siblings with a higher probability than the analysis based on microsatellites, and SNPs outperformed microsatellites in estimating individual‐level multilocus heterozygosity. Overall, the results indicated that moderately polymorphic microsatellites and SNPs from RADseq agreed on estimates of population genetic structure in moderately diverged, small populations, but RADseq outperformed microsatellites for applications that required individual‐level genotype information, such as quantifying relatedness and individual‐level heterozygosity. The results can be applied to other small populations with low or moderate levels of genetic diversity.     

Selection on life‐history traits and genetic population divergence in rotifers

A combination of founder effects and local adaptation – the Monopolization hypothesis – has been proposed to reconcile the strong population differentiation of zooplankton dwelling in ponds and lakes and their high dispersal abilities. The role genetic drift plays in genetic differentiation of zooplankton is well documented, but the impact of natural selection has received less attention. Here, we compare differentiation in neutral genetic markers (F_ST) and in quantitative traits (Q_ST) in six natural populations of the rotifer Brachionus plicatilis to assess the importance of natural selection in explaining genetic differentiation of life‐history traits. Five life‐history traits were measured in four temperature × salinity combinations in common‐garden experiments. Population differentiation for neutral genetic markers – 11 microsatellite loci – was very high (F_ST = 0.482). Differentiation in life‐history traits was higher in traits related to sexual reproduction than in those related to asexual reproduction. Q_ST values for diapausing egg production (a trait related to sexual reproduction) were higher than their corresponding F_ST in some pairs of populations. Our results indicate the importance of divergent natural selection in these populations and suggest local adaptation to the unpredictability of B. plicatilis habitats.     

A landscape genetics approach reveals ecological‐based differentiation in populations of holm oak (Quercus ilex L.) at the northern limit of its range

The holm oak plays a relevant role in the functioning of Mediterranean forests. In the area north of Garda Lake, Italian Prealps, holm oak populations are at the northernmost edge of their distribution. Being peripheral, these populations are of particular interest for ecological, evolutionary and conservation studies. Through an explicit individual‐based landscape genetics approach, we addressed the following questions: (1) are levels of genetic variation reduced in these marginal populations compared with central populations?; (2) despite the narrow geographical scale, do individual‐based analyses have some power to detect genetic differentiation?; (3) do environmental and/or climatic factors exert a role in shaping patterns of genetic variation and differentiation? Through a Bayesian method, we identified three clusters whose genetic variability can be considered to be of the same order as that recorded in central Quercus ilex populations. Although being geographically very close (< 20 km), the differentiation was statistically significant (P < 0.05) with global F _st and Φ _Pt values of 0.019 and 0.038, respectively. Geography and phylogeography could not be invoked to explain this differentiation. A redundancy discriminant analysis revealed that relevant eco‐pedological and climatic features, such as soil depth, aspect, elevation and humidity, were correlated with the observed pattern of differentiation. Toblino was ecologically separated from the other clusters, as it lies on deep soil with subhumid conditions. The differentiation of the Brione–Ranzo–Val Busa cluster appeared to be related to superficial soils and drier conditions, whereas the Nanzone–Padaro cluster was differentiated mainly according to its mid‐elevation. Coupling spatial and genetic information on a local scale proved to be effective to investigate the evolutionary and demographic history of peripheral populations. © 2012 The Linnean Society of London, Biological Journal of the Linnean Society, 2012, ?? , ??–??.     

New SNPs for population genetic analysis reveal possible cryptic speciation of eastern Australian sea mullet (Mugil cephalus)

Sustainable management of sea mullet (Mugil cephalus) fisheries needs to account for recent observations of regional‐scale differentiation. Population genetic analysis is sought to assess the situation of this ecologically and economically important fish species in eastern Australian waters. Here, we report (i) new population genetic markers [single nucleotide polymorphisms (SNPs) and potential microsatellites], (ii) first estimates of spatial genetic differentiation and (iii) prospective power tests for designing more comprehensive studies. Six DNA samples from three sampling regions (North Queensland, South Queensland and central New South Wales) on the eastern coast of Australia were used to prepare restriction site associated DNA (RAD) tag libraries from genomic DNA digested with EcoRI and MseI. A pooled sample of regional RAD tag libraries was sequenced using the Roche GS‐FLX Titanium platform. A total of 172 837 raw reads (17.4 Mbp) were retrieved, 95 500 of which were used to discover 1267 SNPs and 1417 microsatellites. A subset of 161 SNPs was validated based on 63 additional DNA samples genotyped using the Sequenom MassArray (iPLEX Gold chemistry). Altogether 92 SNPs (57%) were confirmed, with 40% of these marking fixed variants between northern and southern sampling regions. Our preliminary findings indicate a multispecies fishery stock of M. cephalus in eastern Australian waters, but suggest that strong genetic differentiation occurs north of major fishing grounds. Low potential differentiation within major fishing grounds (e.g. F_ST = 0.0025) can be resolved with a likely power ≥67% by using standard sample sizes of 50 and validated subsets of available markers.     

Genome‐wide single‐generation signatures of local selection in the panmictic European eel

Next‐generation sequencing and the collection of genome‐wide data allow identifying adaptive variation and footprints of directional selection. Using a large SNP data set from 259 RAD‐sequenced European eel individuals (glass eels) from eight locations between 34 and 64^oN, we examined the patterns of genome‐wide genetic diversity across locations. We tested for local selection by searching for increased population differentiation using F_ST‐based outlier tests and by testing for significant associations between allele frequencies and environmental variables. The overall low genetic differentiation found (F_ST = 0.0007) indicates that most of the genome is homogenized by gene flow, providing further evidence for genomic panmixia in the European eel. The lack of genetic substructuring was consistent at both nuclear and mitochondrial SNPs. Using an extensive number of diagnostic SNPs, results showed a low occurrence of hybrids between European and American eel, mainly limited to Iceland (5.9%), although individuals with signatures of introgression several generations back in time were found in mainland Europe. Despite panmixia, a small set of SNPs showed high genetic differentiation consistent with single‐generation signatures of spatially varying selection acting on glass eels. After screening 50 354 SNPs, a total of 754 potentially locally selected SNPs were identified. Candidate genes for local selection constituted a wide array of functions, including calcium signalling, neuroactive ligand–receptor interaction and circadian rhythm. Remarkably, one of the candidate genes identified is PERIOD, possibly related to differences in local photoperiod associated with the >30° difference in latitude between locations. Genes under selection were spread across the genome, and there were no large regions of increased differentiation as expected when selection occurs within just a single generation due to panmixia. This supports the conclusion that most of the genome is homogenized by gene flow that removes any effects of diversifying selection from each new generation.