Sphyrna lewini, is a Critically Endangered, migratory species known for its tendency to form iconic and visually spectacular large aggregations. Herein, we investigated the population genetic dynamics of the scalloped hammerhead across much of its distribution in the Eastern Tropical Pacific (ETP), ranging from Costa Rica to Ecuador, focusing on young‐of‐year animals from putative coastal nursery areas and adult females from seasonal aggregations that form in the northern Galápagos Islands. Nuclear microsatellites and partial mitochondrial control region sequences showed little evidence of population structure suggesting that scalloped hammerheads in this ETP region comprise a single genetic stock. Galápagos aggregations of adults were not comprised of related individuals, suggesting that kinship does not play a role in the formation of the repeated, annual gatherings at these remote offshore locations. Despite high levels of fisheries exploitation of this species in the ETP, the adult scalloped hammerheads here showed greater genetic diversity compared with adult conspecifics from other parts of the species' global distribution. A phylogeographic analysis of available, globally sourced, mitochondrial control region sequence data (n = 1818 sequences) revealed that scalloped hammerheads comprise three distinct matrilines corresponding to the three major world ocean basins, highlighting the need for conservation of these evolutionarily unique lineages. This study provides the first view of the genetic properties of a scalloped hammerhead aggregation, and the largest sample size‐based investigation of population structure and phylogeography of this species in the ETP to date.The scalloped hammerhead shark,  The scalloped hammerhead shark is a Critically Endangered (IUCN Red List), circumglobally distributed species in warm temperate and tropical seas. This species exhibits both periods of restricted movements as well a strong migratory propensity and is known to form iconic, large seasonal aggregations at offshore oceanic islands. In this manuscript, we report on the population genetic dynamics of scalloped hammerheads within the Eastern Tropical Pacific , and the mitochondrial phylogeography of this species worldwide. Twelve of these subpopulations were sampled within the ETP .2.2Sphyrna lewini  previously described by Nance et al. , 0.165–0.25 μl MgCl2, 0.2–0.25 μl of 10 nM Forward primer with a 5′‐M13 tail, 0.2–0.5 μl of 10 nM Reverse primer, and 0.1–0.4 μl of 10 nM fluorescently labeled universal M13 primer  of 500. Final POWSIM estimates were derived from 100 simulations per run, and Fisher's exact test analyses implemented 1000 dememorizations, 100 batches, and 1000 iterations per batch.To ensure that no sample duplicates  were included in downstream analyses, match analysis was performed as implemented in the Excel Microsatellite Toolkit Park, . Pairs o2.3A), allelic richness (AR), inbreeding coefficient (FIS)] were determined for each locus and subpopulation using the program FSTAT 2.9.4  adult shark subpopulations  and (2) all ETP subpopulations . Pairwise metrics ST Jost,  were estST Jost,  among ETST Jost,  by meansST Jost, . Two DAP2.4We tested for relatedness and familial relationships in ETP scalloped hammerheads using a multi‐tiered approach. Potential parent‐offspring relationships among adult female sharks from the Galápagos aggregations and YOY sharks sampled from ETP nurseries were assessed using the programs Cervus 3.0.7  and was therefore selected for use herein (data not shown). Overall mean relatedness  among ETP sharks were assessed using Colony 2.0, which uses pedigree reconstruction to infer likelihood of genetic relationships, rather than a pairwise approach. Analyses were performed assuming female and male polygamy  was amplified in 25 μl polymerase chain reactions (PCR) using the Forward and Reverse primers CR‐F6 and DAS‐R2 as well as the reaction conditions and amplification protocols outlined in Clarke et al. . PCR purAll sequences were imported into Geneious 9.0.5 , and YOY sharks from two nursery sites on the Colombian coast: Sanquianga  and Tribugá   Figure , these wWorldwide phylogeography samples: We assessed scalloped hammerhead matrilineal evolutionary relationships worldwide by combining our ETP‐CR‐Expanded mitochondrial sequence dataset trimmed to match the same 515‐bp stretch of DNA sequence available from previously published control region‐based studies of this species worldwide, regardless of shark age class . Prior to analysis, the control region datasets from each of these published studies was first curated and reconstructed , resulting in a worldwide dataset containing 1818 control region sequences (hereafter the Worldwide‐CR‐Dataset).2.6h, haplotype diversity; π, nucleotide diversity) using Arlequin 3.5  by estimating standard diversity indices .Evolutionary relationships among haplotypes at two different geographic scales were visualized via median‐joining haplotype networks  in Figure Across the entire genotyped dataset, six pairs of likely duplicate samples were found ; five of these six putative pairs were comprised of individuals sampled from the same geographic location and had the same mitochondrial control region haplotype, suggesting inadvertent duplicate sampling of YOY market‐derived sharks (no duplicates were found among adult samples). A single individual from each of these five pairs  was discarded from both control region and microsatellite datasets. The individuals comprising the sixth pair, however, were collected from different locations and processed at separate times in the laboratory so both were retained for analysis given the low likelihood of repeat sampling of the same individual and/or sample mix‐up. Species misidentifications in the field or sample labeling errors made during collection  resulted in the discarding of another 30 individuals from the microsatellite dataset. Final sample sizes  were retained for statistical analysis. The final percentage of missing data for the nine‐locus microsatellite dataset was 5.55%. Loci were polymorphic in all locations and the number of alleles per locus ranged from 6–52  and the inbreeding coefficient (FIS) for all global samples collected for this study, including adults and YOY (n = 549), were 22.81 and 0.058, while observed (HO) and expected heterozygosity (HE) were 0.714, and 0.785, respectively.Of the 10 microsatellite loci assessed, one locus (SLE018) demonstrated widespread evidence of null alleles, with 11 of the 14 sample collections exhibiting null allele frequencies greater than 10% (10.09–25.52%). Across the remaining nine loci, no single locus demonstrated a frequency of null alleles >10% in more than three subpopulations Table . Hardy–Won Table . Linkage52 Table . Both mi3 Figure . Mean ovh) and nucleotide diversity (π) were 0.672 ± 0.016 and 0.0078 ± 0.0043, respectively.Following duplicate and mis‐identified samples removal (see above), a final scalloped hammerhead control region sequence (548 bp) dataset from 515 individuals was obtained: 415 from the ETP (131 GAL adults plus 284 YOY), 50 adults from SEY, and 50 adults from FLA Figure A–D. Over3.2AR = 12.0–12.7, HO = 0.758–0.759, HE = 0.759–0.796; Table AR = 9.5, HO = 0.597, HE = 0.612). Similarly, mitochondrial DNA yielded variable comparative estimates of diversity (Table h = 0.550 ± 0.027) and the lowest within the SEY sharks (h = 0.184 ± 0.068). Nucleotide diversity was largely similar across sites  identified large and statistically significant genetic differentiation between the three adult subpopulations . Genetic differentiation between sharks from the western Atlantic (FLA) and the two Indo‐Pacific locations was 2–3 times higher for FST and 4–5 times higher for GST″ and DEST, than the differentiation between sharks from the Indian (SEY) and Pacific (GAL) Oceans  .The overall microsatellite diversity estimates from nine loci (averaged) for 423 scalloped hammerheads comprising GAL adults and all YOY sampled from 12 ETP subpopulations were: 3.3.2n = 31) were consistently differentiated from all other ETP subpopulations after FDR correction .Analysis of 478 control region sequences from 13 ETP locations  and central Pacific (represented by Hawai'i sharks) showed no evidence of matrilineal population structure in the broader eastern Pacific, except for YOY from the South Galápagos (SGA) (as above), but significant differentiation between Hawaii and all broader eastern Pacific sharks Table .3.4−4 and 2.72 × 10−3 when one parent or no parents of the offspring are known, respectively, and the probability of exclusion that a pair taken at random from the population are excluded as both parents was estimated as 1.48 × 10−7 for the dataset. Among the 134 genotyped adult female Galápagos aggregating sharks, no full‐sibling pairs were consistently identified across all six “very long" Colony runs with a probability exceeding 95%; however, one “possible” full‐sibling pair was identified in five of six runs at 91% probability  that were consistently detected across the six “very long" runs with probabilities greater than 95% . Each of these pairs possessed pairwise estimates of relatedness that were higher than the overall mean value Table , and thr3.5A median‐joining network of scalloped hammerhead control region haplotype sequences (515 bp) from all age groups across 12 worldwide locations , illustrated three primary phylogeographic lineages consisting of samples from the: (1) Atlantic, (2) western Indian, and (3) eastern Indian‐Pacific regions with minor haplotype sharing between the latter two Figure . No phyl4n = 221), allowing increased confidence in study inferences; and (3) we provide the first population genetic characterization of a scalloped hammerhead aggregation, in this case the large and iconic aggregations that form at the northern Galápagos Darwin and Wolf Islands. We discuss our findings in the context of each study objective.This study complements and expands on previous studies of scalloped hammerheads from the ETP and broader eastern Pacific  compared with adults from the SEY and FLA, respectively. Furthermore, GAL adult samples also had much higher nuclear genetic diversity  than adult scalloped hammerheads sampled from the broader western Atlantic  Figure A–D. ThisThe strong nuclear and mitochondrial pairwise genetic differentiation observed among adult scalloped hammerheads from the GAL, SEY, and FLA, along with the distinct, ocean basin, matrilineal phylogeographic lineages they form with no haplotype sharing Figure , is consOur phylogeographic results showing Atlantic (FLA) and Indian Ocean (SEY) scalloped hammerheads as having the closest mitochondrial evolutionary relationship of the three adult populations assessed Figure  is consiIn contrast to the mitochondrial DNA results, nuclear differentiation between the Seychelles and Galápagos adults was much smaller than between these two populations and Florida adults. This contrast in differentiation between the two organelle markers may be attributed to their mutation rate and mode of inheritance. Biparentally inherited microsatellites mutate faster than matrilineally inherited mtDNA, and can be used to detect population structure, or conversely male‐mediated gene flow, on a relatively contemporary timescale (10–100 generations ago)  in the ETP scalloped hammerheads (both YOY and adults collected for the present study), were similar to those reported by Nance et al.  for the same general geographic region, even though our sample size was nearly twice as large. The similar values from two studies using different sample sets suggest that these estimates are likely reliable indicators of genetic diversity of scalloped hammerheads in the ETP biogeographic region. Akin to our findings from Galápagos adults, the overall nuclear diversity estimated across all demographic groups sampled in the ETP , but not individual level analyses, across seven coastal sampling sites spanning Baja, Mexico to Ecuador. While they also found little pairwise genetic differentiation across their sampling sites using mitochondrial control region sequences, they did detect a marginally significant IBD signal. Given these marked inconsistent results and only subtle statistical differentiation where it existed, Nance et al.  between scalloped hammerheads from the ETP and Hawai'i —and all other sampling locations save the South Ecuador (SEC) nursery. This marker disparity may reflect the differences in mitochondrial versus microsatellite loci evolutionary rates, but also keeps open the possibility that some scalloped hammerhead females show philopatry to this insular nursery site or the stochastic use of this site by only a small subset of females. Temporal sampling of sharks at this Galápagos nursery is needed to resolve if YOY here represent a differentiated population.While our results do not support female philopatry to nursery sites along the length of ETP continental coastline examined here, regional philopatry in scalloped hammerheads has been inferred from matrilineal population structure in some other parts of the species distribution. Indeed, Rangel‐Morales et al. , utilizi4.3Cetorhinus maximus) which aggregate seasonally in the Northeast Atlantic demonstrated that within group relatedness was higher than expected by chance, especially among the females  aggregating at sites in the western Indian Ocean were more related than expected by chance and suggested that kinship did not play a role in visits to aggregation sites. Furthermore, no correlation between kinship and social networks  was found in blacktip reef sharks (Carcharhinus melanopterus) in French Polynesia  lineages in each ocean basin order to conserve their biodiversity.This study represents the first genetic investigation of the iconic Galápagos scalloped hammerhead aggregation, and the largest sample size‐based investigation of population structure and phylogeography of this species in the ETP to date. Our results, using both matrilineal and nuclear genetic markers, indicate high connectivity between the Galápagos aggregation and all coastal nursery sites, and no convincing evidence of philopatry within the ETP. This extensive connectivity in a region known for high IUU fishing points to the need for coordinated, multinational management cooperation among ETP jurisdictions in order to conserve Sydney P. Harned: Data curation (lead); formal analysis (lead); writing – original draft (lead). Andrea M. Bernard: Data curation (supporting); formal analysis (supporting); writing – original draft (supporting); writing – review and editing (lead). Pelayo Salinas de Leon: Conceptualization (lead); data curation (lead); writing – review and editing (supporting). Marissa R. Mehlrose: Data curation (supporting). Jenifer Suarez: Data curation (supporting); writing – review and editing (supporting). Yolani Robles: Data curation (supporting); writing – review and editing (supporting). Sandra Bessudo: Data curation (supporting); writing – review and editing (supporting). Felipe Ladino: Data curation (supporting); writing – review and editing (supporting). Andrés López Garo: Data curation (supporting); writing – review and editing (supporting). Ilena Zanella: Data curation (supporting); writing – review and editing (supporting). Kevin A. Feldheim: Formal analysis (supporting); writing – review and editing (supporting). Mahmood S. Shivji: Conceptualization (lead); data curation (supporting); writing ‐ original draft (supporting); writing ‐ review and editing (lead).The authors report no conflict of interest.Appendix S1:Click here for additional data file.


The Izumi plain in the Kagoshima Prefecture, Japan, is known as an overwintering site for more than 30,000 migratory waterfowl, including endangered crane species. We previously reported that environmental water samples, from artificial wet paddies created as crane roost sites on the Izumi plain, are useful for avian influenza virus (AIV) surveillance. During the 2019/20 winter season, we collected 238 water samples from the crane roost sites and isolated 22 AIVs of six subtypes: one H1N1, one H3N2, seven H3N8, four H4N6, nine H6N6, and one H11N2 subtypes. Genetic analyses revealed that AIVs of the same subtype isolated from the Izumi plain during a single winter season exhibited multiple genetic constellations. Furthermore, phylogenetic analyses suggested that our H3N2 isolate may be a genetic reassortant between close relatives to our H3N8 and H11N2 isolates. Our study highlighted the importance of monitoring AIV circulation to better understand AIV ecology in migratory waterfowl populations. Influenza A viruses, members of the family Orthomyxoviridae, have eight-segmented RNA genomes. Based on the antigenicity of two surface glycoproteins, hemagglutinin (HA) and neuraminidase (NA), avian influenza viruses (AIVs) are classified into 16 HA and 9 NA subtypes ,3. This Grus vipio) and the hooded crane (Grus monacha). To protect these endangered cranes, artificial wet paddies are created as crane roost sites during the winter season on the Izumi plain. In addition to these cranes, many other migratory waterfowl, including more than 20,000 wild ducks, visit the Izumi plain every winter. Importantly, migratory waterfowl, especially wild ducks of the orders Anseriformes and Charadriiformes, are known as natural reservoirs of AIVs [The Izumi plain in the Kagoshima Prefecture, Japan, is known to be an overwintering site for over 10,000 endangered cranes, including the white-naped crane , three (H4N6-I to -IV), and two (H6N6-I and -II) genotypes, respectively . These rIn this study, we revealed the transition of genetic constellations of AIVs among wild waterfowl overwintering on the Izumi plain during the 2019/20 winter season. We isolated 23 AIVs, including one isolate containing multiple subtypes, from 238 water samples collected from crane roost sites. The AIV-positive rate was not as high during the 2019/20 winter season  as it was during the previous season  . Of the Genetic analyses revealed that the 22 AIVs isolated from crane roost site water during the 2019/20 winter season could be classified into six subtypes: H1N1, H3N2, H3N8, H4N6, H6N6, and H11N2 subtypes. As the Izumi plain is located on the East-Australian Flyway, most AIV strains invading the Izumi plain via migratory birds, especially wild ducks, during the winter season belong to the Eurasian lineage ,10,12. IIn conclusion, broad genetic variations were observed in AIVs isolated from the Izumi plain during the 2019/20 winter season. Furthermore, one isolate appears to be a reassortant emerging on the Izumi plain. Our study highlighted the importance of monitoring AIV circulation to better understand AIV ecology in migratory waterfowl populations.Environmental water samples (50 mL for each sample) were collected from the crane roost sites on the Izumi plain during the 2019/20 winter season. A total of 238 samples were collected; 14 samples were collected every week from November 2019 to the end of February 2020, except for the first week of January. The collected water samples were stored at approximately 4 °C until use.AIVs were isolated from the water samples according to a previous study . BrieflyRNA was extracted from allantoic fluids that showed hemagglutination activity, using an InnuPREP virus DNA/RNA Kit . The RNA was then subjected to real time RT-PCR-based influenza A viral gene detection with an iTaq Universal SYBR Green One-Step Kit  and primer sets specific for a conserved region of influenza viral M genes . The virhttp://platform.gisaid.org/) on 2 September 2022 , as previously described . Brieflyber 2022 .Various AIV strains which reflect the temporal and spatial distribution were retrieved from the GISAID database. The sequences of the viral gene segments from our AIV isolates were phylogenetically analyzed with the downloaded AIVs. The nucleotide sequences were aligned using the MUSCLE program . Phyloge


Amphiprion percula). Using a laboratory population of wild‐caught A. percula, we measured the size and swimming speed of larvae from 24 half‐sibling families. Phenotypic variance was partitioned into genetic and environmental components using a linear mixed‐effects model. Importantly, by including half‐siblings in the breeding design, we ensured that our estimates of genetic variance do not include nonheritable effects shared by clutches of full‐siblings, which could lead to significant overestimates of heritability. We find unequivocal evidence for the heritability of larval body size (estimated between 0.21 and 0.34) and equivocal evidence for the heritability of swimming speed (between 0.05 and 0.19 depending on the choice of prior). From a methodological perspective, this work demonstrates the importance of evaluating sensitivity to prior distribution in Bayesian analysis. From a biological perspective, it advances our understanding of potential dispersal‐related larval traits by quantifying the extent to which they can be inherited and thus have the potential for adaptive evolution.A major goal of marine ecology is to identify the drivers of variation in larval dispersal. Larval traits are emerging as an important potential source of variation in dispersal outcomes, but little is known about how the evolution of these traits might shape dispersal patterns. Here, we consider the potential for adaptive evolution in two possibly dispersal‐related traits by quantifying the heritability of larval size and swimming speed in the clown anemonefish , and equivocal evidence for heritability of swimming speed (between 0.05 and 0.19 depending on the choice of prior).A major goal of marine ecology is to identify the drivers of variation in larval dispersal. Here, we investigate the heritability of two key larval dispersal traits, body size and swimming speed, in  Most marine fishes and invertebrates undergo early development in open water, sometimes moving long distances from their origin in the process. For many species, this larval dispersal phase is the primary driver of population connectivity and an essential component of spatial structure : the proportion of phenotypic variance that is due to additive genetic effects , a reef fish that has been the focus of an enormous amount of work on marine larval dispersal  at approximately 24 pellets per pair per day, a food ration that results in pairs reproducing at a rate and quantity consistent with the reproduction observed in the field  to account for potential developmental differences among larvae due to their length of incubation. Clutches of eggs were collected from breeding pairs the night before hatching and moved to separate 20‐gallon tanks maintained at 34 ppt salinity and 27–28°C. Hatching tank water was tinted with nc = 30), maternal ID (nd = 12), and paternal ID (ns = 12) for each larva, and these were included as random effects in the statistical model (see below). Clutch ID was included to account for similarities among clutch‐mates due to shared conditions experienced during development and early life. Maternal ID represents any effect of the mother beyond the additive effect of the alleles passed down to her offspring; this includes factors such as nutritional state  and inherited epigenetic patterns of gene expression. Similarly, paternal ID represents any effect of the father beyond the additive genetic; we expect this to be particularly important in clownfish because males provide extensive parental care to their eggs  were removed from the experiment, and additional larvae were trialed to reach a total of 30 successful trials per parental pair. After acclimation, the water velocity was increased to 2 cm s−1 and maintained for 2 min, then increased by an additional 2 cm s−1 every 2 min thereafter. The trial ended when the larva was unable to successfully swim against the current and was expelled out the back of the flume. Critical swimming speed was calculated asU is the penultimate speed (in cm s−1), and t equals the time (in minutes) the larva swam at the final speed —defined for preflexion larvae as the distance from the tip of the snout to the end of the notochord , and μ is the mean trait value over all larvae. X is the n‐vector of incubation times and β is the effect of incubation time. The n‐vector a contains the additive genetic effects; a has a multivariate normal distribution with a variance–covariance structure G = σA2A, where σA2 is the additive genetic variance and A is the n × n relatedness matrix among larvae . Each Zi is an incidence matrix relating larvae to the corresponding vector of random effects c (clutch), d , or s . The residual term r captures all contributions to phenotype not explicitly accounted for by other factors: This includes environmental sources of variation among members of the same clutch, as well as nonadditive genetic effects . Vectors c, d, s, and r are normally distributed with variances σC2,σD2,σS2, and σR2, respectively, and covariances equal to zero.where y = μ + Xβ + a + Zcc + r). The reason for considering both models is that, in our breeding design, maternal ID, paternal ID, and additive genetic effect are highly collinear. All larvae in our sample that share genes  also share maternal ID, paternal ID, or both. This means that the full model may inaccurately attribute additive genetic variance to maternal or paternal ID, while the reduced model almost certainly attributes some parental effects (if they exist) to the additive genetic effect. Examining both models gives us a more realistic range for the strength of the additive genetic effect in this population.We also fit a second, reduced model that did not include parental effects  of each prior was chosen such that the mode of the distribution was equal to 1/k of the total phenotypic variance, where k is the number of variance components. To test the sensitivity of our results to the choice of prior, we also fit each model using a second set of priors, representing the alternative hypothesis that our proposed effects do not contribute to phenotypic variance. These priors were close to zero for all variance components: parameter‐expanded inverse gamma distributions with V = 1, nu = 1000, αμ = 0, αV = 1. To quantify the impact of the alternative priors, we calculated the percentage deviation of the mean estimates from the alternative priors, compared with the mean estimates from the default priors  we used a diffuse inverse gamma prior with nu = 0.001   in the model without parental effects and 0.0051 (0.0005–0.0130) in the model that included parental effects. Heritability of standard length was 34% (8–63%) in the model without parental effects . For additional details on alternative priors, see the Appendix 3.2−1, with a mean of 3.91 cm s−1 and a standard error of 0.09 cm s−1. The total phenotypic variance in swimming speed was 4.67 cm2 s−2. The estimated additive genetic variance was 1.03 (0.23–2.24) cm2 s−2  in the model without parental effects, and 1.16 (0.14–2.98) when parental effects were included in the model. The heritability of swimming speed was 19% (47–83%) in the model without parental effects , there is high collinearity between maternal ID, paternal ID, and additive genetic effect, and thus considerable uncertainty in quantifying the effects of shared parents versus the effects of shared genes. The difference between estimates of heritability in the models with and without parental effects can be explained by the fact that similarities between siblings due to shared parents increase the overall resemblance among relatives in the dataset. In the simpler model, resemblance among relatives can be attributed to the additive genetic effect  or to the clutch effect (for members of the same clutch). In the more complex model, some of the resemblance among siblings that share a parent is accounted for by maternal or paternal effects, which decreases the amount of resemblance that is attributed to their shared genes. A breeding design that included more mates per parent, or relatives that do not share a parent (such as cousins), would help to more precisely quantify the relative contributions of parental and genetic effects.Our evidence for genetic variance in larval swimming speed is equivocal. Although our default estimates  indicated a substantial role for additive genetic variance in larval swimming speed, those estimates were sensitive to the prior used to generate them. Our alternative prior yielded heritability estimates very close to zero. Since we do not have an a priori reason to be much more confident in the default prior than in the alternative, we can conclude only that, if the genetic variance in larval swimming speed exists in this population, our breeding design was unable to consistently detect it. This could perhaps be remedied by the modifications to the breeding design described above . In any case, the magnitude of genetic variance in swimming speed (if it exists) is small in comparison to the genetic variance in larval body size that we were able to detect with the same breeding design and individuals. There are at least two possible reasons for this. Critical swimming speed, as a behavioral trait, will have more phenotypic variability than a morphological trait such as standard length due to variation in the internal state of the larva. Genetic variation, if it exists, will then be a smaller proportion of the total and will be harder to detect. Alternatively, selection can reduce genetic diversity, particularly in traits closely associated with fitness Fisher, . If swimWe did not find either genetic or phenotypic covariance between size and swimming speed, after controlling for the effects of the clutch. Genetic covariance might be expected as the result of a fitness tradeoff between growth and swimming performance  and the denominator  of the heritability quantity depend on the particular set of individuals whose traits were measured. In this lab‐based experiment, we expect the genetic diversity of the study population to be relatively realistic: All larvae were offspring of parents wild‐caught from various locations in Papua New Guinea. However, the difference between environmental conditions in the wild and those in the lab means that applying our results uncritically to wild populations would be a mistake. The relatively standardized conditions in the lab probably reduce overall environmental variance, thus inflating heritability estimates over what they would be in the wild. In addition, systematic differences between experimental and natural habitats  likely affect trait variation in ways we cannot predict, with unknown consequences for heritability. Although this means our results must be interpreted with caution, the fact that we were able to detect genetic variance in larval body size indicates that this trait has one of the prerequisites for evolutionary change in response to selection.More work is needed to understand the implications of parental effects on evolution. Without the reliable mechanism of genetic transmission, a continuity of parental effects is not guaranteed from one generation to the next. Nevertheless, there are an increasing number of documented instances of inter‐ and transgenerational parental effects ; formal analysis (lead); funding acquisition ; investigation (lead); writing – original draft (lead); writing – review and editing . CaitLynn Klawon: Formal analysis (supporting); funding acquisition ; investigation (supporting); writing – review and editing . Colleen Webb: Conceptualization ; formal analysis (supporting); funding acquisition ; supervision ; writing – review and editing . Peter Buston: Conceptualization ; formal analysis (supporting); funding acquisition ; investigation (supporting); resources (lead); supervision ; writing – original draft (supporting); writing – review and editing .https://doi.org/10.6084/m9.figshare.19623825.v1.This article has earned the Open Data badge only. Data, materials and the preregistered design and analysis plan are available at Appendix S1Click here for additional data file.


Our knowledge of the genetic relatedness and structure of ancient hunter-gatherers is however limited, owing to the scarceness and poor molecular preservation of human remains from that period3. Here we analyse 356 ancient hunter-gatherer genomes, including new genomic data for 116 individuals from 14 countries in western and central Eurasia, spanning between 35,000 and 5,000 years ago. We identify a genetic ancestry profile in individuals associated with Upper Palaeolithic Gravettian assemblages from western Europe that is distinct from contemporaneous groups related to this archaeological culture in central and southern Europe4, but resembles that of preceding individuals associated with the Aurignacian culture. This ancestry profile survived during the Last Glacial Maximum  in human populations from southwestern Europe associated with the Solutrean culture, and with the following Magdalenian culture that re-expanded northeastward after the Last Glacial Maximum. Conversely, we reveal a genetic turnover in southern Europe suggesting a local replacement of human groups around the time of the Last Glacial Maximum, accompanied by a north-to-south dispersal of populations associated with the Epigravettian culture. From at least 14,000 years ago, an ancestry related to this culture spread from the south across the rest of Europe, largely replacing the Magdalenian-associated gene pool. After a period of limited admixture that spanned the beginning of the Mesolithic, we find genetic interactions between western and eastern European hunter-gatherers, who were also characterized by marked differences in phenotypically relevant variants.Modern humans have populated Europe for more than 45,000 years Combined analysis of new genomic data from 116 ancient hunter-gatherer individuals together with previously published data provides insights into the genetic structure and demographic shifts of west Eurasian forager populations over a period of 30,000 years. Genomic data have shown that modern humans were present in western Eurasia2 at least 45 ka. Some of those early groups from more than 40 ka further admixed with Neanderthals, as shown by signals of recent introgression in individuals from Bacho Kiro in Bulgaria—associated with an Initial Upper Palaeolithic (IUP) archaeological culture—and from Peştera cu Oase in Romania6. Other individuals from that period, such as Zlatý kůň from Czechia and Ust’Ishim from Russia, do not carry significantly more Neanderthal ancestry than other non-African groups7, indicating differential interactions between Neanderthals and early modern humans during their initial expansions across Eurasia. Surprisingly, however, none of those pre-40 ka individuals left substantial traces in the genetic makeup of present-day Eurasian populations7. The oldest genomes carrying ancestries that derive primarily from the lineage leading to present-day Europeans are Kostenki 14 , Goyet Q116-1  and Bacho Kiro 1653 8. These data suggest that the genetic ancestries identified in the pre-40 ka individuals analysed so far went largely extinct or were assimilated by subsequent expansions9. The Kostenki genetic signature  contributed to the later Věstonice genetic cluster , named after the Dolní Věstonice site in Czechia4. This genetic signature is shared among individuals associated with the archaeologically defined Gravettian culture (33–26 ka) in central and southern Europe and seemingly disappeared after the Last Glacial Maximum4 (LGM). However, the genetic profile of contemporaneous Gravettian-associated individuals from western Europe remains unknown, as is their contribution to populations after the LGM. Known to have been the coldest phase of the last Ice Age, the LGM is considered to have caused a demographic decline in large parts of Europe10, with populations retracting to southern latitudes as attested—for example—by the contemporaneity of the Solutrean culture (24–19 ka) in the Iberian peninsula and southern France. Other proposed climatic refugia for human survival during this period are the Italian peninsula, the Balkans and the southeastern European Plain, but the actual genetic contribution of populations from these regions to post-LGM Europeans is highly debated13.Modern humans left sub-Saharan Africa at least 60 thousand years ago (ka), and during their initial expansion into Eurasia, they genetically mixed with Neanderthals, resulting in 2–3% Neanderthal ancestry in the majority of present-day non-African populations14, but the geographic extension of this ancestry is still unclear. Instead, in southern Europe, a distinct hunter-gatherer genetic profile was found as early as 17 ka in individuals associated with the Epigravettian culture15 . This ‘Villabruna’ ancestry  showed connections to ancient and present-day Near Eastern populations16, but the mode and tempo of its expansion into the Italian peninsula remain unexplored. The Villabruna ancestry later appeared in central Europe and it is thought to have largely replaced groups related to the GoyetQ2 ancestry4. However, its formation, diffusion and interaction with contemporaneous hunter-gatherers from eastern Europe and their interplay with later expansions of Neolithic farmers from southeastern Europe are not well characterized.After the LGM, a genetic component distantly linked to the Goyet Q116-1 individual from Belgium dated to 35 ka—named GoyetQ2 ancestry —reappeared in individuals from southwestern and central Europe associated with the Magdalenian culture  and in an admixed form in subsequent Final Palaeolithic and Mesolithic hunter-gatherersIn this study, we analyse 356 ancient hunter-gatherer genomes including new genomic data of 116 individuals dated to 35–5 ka alongside a novel contamination-estimation method based on runs of homozygosity. We provide a systematic description of the genomic transformations that hunter-gatherer groups experienced from the early Upper Palaeolithic onwards across western and central Eurasia and how those are possibly linked to cultural and climatic changes.4. These data cover a time span of around 30,000 years from the Upper Palaeolithic to the Late Neolithic (defined here by the presence of pottery rather than by farming subsistence economy if not indicated), derive from multiple prehistoric cultural contexts, and originate from 54 archaeological sites in 14 countries: 1 Aurignacian-associated individual from Belgium and 1 culturally unassigned individual from Romania (35–33 ka), 15 Gravettian-associated individuals from Spain, France, Belgium, Czechia and Italy (31–26 ka), 2 Solutrean-associated individuals from Spain and France (23–21 ka), 9 Magdalenian-associated individuals from France, Germany, and Poland (18–15 ka), 4 Epigravettian-associated individuals from Italy (17–13 ka), 2 Federmesser-associated individuals from Germany (14 ka), and 81 Mesolithic to Neolithic foragers from across western Eurasia (11–5 ka), together with 1 central Eurasian Neolithic individual from Tajikistan (8 ka) , which were then sequenced and yielded 0.04- to 7.64-fold coverage on average over the targeted SNPs. Genetic sexing revealed 78 male individuals and 38 female individuals  . Notably, and contrary to the report by Fu et al.4, another Gravettian-associated population from central–western Europe  is both geographically and genetically intermediate between the Věstonice and Fournol clusters. The similarity between Goyet Q116-1 and Goyet Q376-3 and the Fournol cluster is also observed at the mtDNA level, with both groups including individuals who carried mtDNA haplogroup M, which has not been found in European individuals from after the LGM24  to plot a dissimilarity matrix of pairwise outgroup p2) Fig. . This plf4-statistics (Supplementary Data n = 4), and the Věstonice-cluster individuals show higher affinity to the Sunghir group than to Goyet Q116-1  from Bulgaria, Muierii 1 (34 ka) and Cioclovina 1 (32 ka) from Romania, and Paglicci 133 (33 ka) from southern Italy are equally related to Goyet Q116-1 and Sunghir. We further tested whether individuals included in the Věstonice and Fournol clusters share similar allele frequencies with the main representatives of those two clusters. With the statistics f4 and f4, we show that all Věstonice-cluster individuals are significantly closer (|Z|>3) to the Věstonice group (n = 5) and the Fournol-cluster individuals are closer to Fournol 85, whereas the geographically intermediate Gravettian-associated Goyet group shows extra affinity to both clusters  shares ancestry with multiple early modern human lineages2 , which are consistent with zero for all other pre-LGM hunter-gatherers , which are significantly positive for all the individuals included in the Věstonice cluster  ancestry contributed to the previously described Věstonice cluster represented by Gravettian-associated individuals from central-eastern and southern Europe26. However, the extent to which groups associated with the Solutrean culture are in genetic continuity with earlier and later populations from the same region is unknown because no genomic data from Solutrean-associated individuals have been reported previously. Both newly sequenced genomes from Solutrean-associated individuals (Le Piage II (23 ka) from southwestern France and La Riera  from northern Spain) show a generalized affinity with members of the Fournol and GoyetQ2 clusters in outgroup f3-statistics  ≫ 0, Z = 6.58). We also compared its affinity to El Mirón (northern Spain), the oldest Magdalenian-associated individual sequenced to date (19 ka). F-statistics suggest that Le Piage II is genetically intermediate between Fournol 85 and El Mirón  cultures, and is found in southwestern and western Europe, which are considered to have been climatic refugia for human populations during the LGM28, the Epigravettian culture has been traditionally assumed to be the result of a transition from the preceding local Gravettian29. However, the level of genetic continuity between individuals associated with these cultures and the population structure among Epigravettian-associated individuals have not been fully explored. Here, we report genomic data from 4 individuals, including 3 approximately 13,000-year-old genomes from northeastern Italy (Pradis 1), northwestern Italy (Arene Candide 16) and Sicily (San Teodoro 2), as well as increased genome-wide coverage from Tagliente 215 dated to 17 ka.After the LGM, the Epigravettian culture was widespread in southern and southeastern Europe. In spite of growing discussions about its nature4  or non-local preceding ancestries   that is consistent with 0  (Supplementary Data 30 (n = 2) than with the almost contemporaneous San Teodoro 2 individual from eastern Sicily.Next, we investigated the genetic relationships between Epigravettian-associated individuals across the Italian peninsula, by reconstructing a phylogeny based on a matrix of pairwise ces Fig.  and testt-test, P < 0.001)  on pseudo-haploid genotypes and individual heterozygosity levels on pseudo-diploid genotypes (Supplementary Data 01) Fig. . Moreove01) Fig. . A simil01) Fig. . We dete01) Fig. , causing31. We show that all analysed Epigravettian-associated individuals carry a homogeneous Villabruna ancestry, with the intra-group genetic structure mainly determined by their geographical, and not temporal, distribution. The phylogenetic reconstruction of Epigravettian-associated genomes, with Pradis 1 diverging more deeply than all others, indicates that the turnover took place much earlier than 17 ka—the date of the more derived Tagliente 2 genome. This, together with the evidence of Villabruna ancestry in El Mirón 19 ka, further suggests that this genetic discontinuity could be the result of palaeogeographic and palaeoecological transformations connected to the LGM32, rather than to the Bølling–Allerød warming period15 (14.7–12.9 ka). In addition, our phylogeographic analysis points to northeastern Italy as the possible entry point of the Epigravettian-associated gene pool in the Italian peninsula. This finding, in conjunction with the genetic affinity of the Villabruna cluster to ancient and present-day Near Eastern ancestries16 , and the ancestry of the El Mirón individual from Spain14 from around 19 ka. Both of these ancestries carry a genetic component distantly related to the Goyet Q116-1 individual dated to 35 ka, with the Iberian individual also showing an affinity to the Villabruna cluster14. By co-analysing previously published data with our newly reported genomes associated with the Magdalenian from La Marche (18 ka) and Pincevent (15 ka) in western and northern France, respectively, and Maszycka (18–16 ka) in southern Poland, we confirm that the Goyet Q116-1 ancestry survived in all studied Magdalenian-associated genomes besides in Gravettian and Solutrean-associated individuals from southwestern and western Europe , which is significantly positive only for El Mirón, whereas all other tested individuals and Goyet Q-2 are symmetrically related with respect to Arene Candide 16  ancestry, related to the Villabruna cluster, and the eastern hunter-gatherer (EHG) ancestry, showing affinity to both the Villabruna and the ancient north Eurasian (ANE) ancestry found in Upper Palaeolithic Siberian individuals4. On the basis of f4-statistics, we find that individuals assigned to the Oberkassel cluster are closer to the Arene Candide 16 genome than any other Epigravettian-associated group from Italy . The genetic distinction between the Oberkassel and Sidelkino clusters is also clearly noticeable in the diversity of uniparentally inherited markers, as the Oberkassel cluster is dominated by mtDNA haplogroup U5 and Y-chromosome haplogroup I, whereas individuals from the Sidelkino cluster show a higher frequency of mtDNA haplogroups U2, U4 and R1b, and carry uniquely Y-chromosome haplogroups Q, R and J 43 and the newly reported Minino individuals (11 ka)—showed extra affinity to the Oberkassel cluster, possibly owing to variability in this ancestry proportion during the initial formation phase of the Sidelkino-ancestry profile. Using DATES software, we estimated the admixture between Villabruna/Oberkassel and ANE ancestries in these old Sidelkino-cluster-related individuals to around 15–13 ka , as a considerable portion of the sequenced hunter-gatherer genomes date after around 8 ka, when ANF ancestry started spreading across Europe. Our results show that the contact zone and the admixture patterns between the Oberkassel and Sidelkino ancestries changed over time  and Mal’ta 1), and roughly contemporaneous West Siberian hunter-gatherers (Tyumen and Sosnoviy), both carrying high proportions of ANE ancestry45 ), individuals from the Villabruna cluster, Oberkassel cluster, Baltic HG and SHG groups show high frequencies of the derived allele (>90%), which is responsible for the green or blue eye phenotype, whereas Sidelkino cluster, Ukraine HG and Iron Gates HG groups show low occurrence of this allele (10–25%). Instead, for the two SNPs associated with skin colour (SLC24A5 (rs1426654) and SLC45A2 (rs16891982)), Sidelkino cluster and Ukraine HG groups show a higher frequency (>90% for SLC24A5 and 29–61% for SLC45A2) of the derived alleles related to light skin colour, compared with Oberkassel and Villabruna clusters, where those alleles are almost completely absent (<1%). On the basis of the genetic variation of present-day Europeans, this could imply phenotypic differences between post-14 ka hunter-gatherer populations across Europe, with individuals in the Oberkassel cluster possibly exhibiting darker skin and lighter eyes, and individuals in the Sidelkino cluster possibly lighter skin and darker eye colour.Leveraging the substantially increased sample size, we investigated genetically distinct hunter-gatherer groups for allele frequencies at selected loci that are known to be associated with specific phenotypic traits in present-day Europeans Fig.  and 28. The data generated in this study enabled us to investigate genomic transformations of and interactions between Eurasian hunter-gatherers at high resolution  gave rise to Gravettian-associated individuals from western and southwestern Europe. This derived ancestry—the Fournol cluster—survived during the LGM in Solutrean-associated individuals, possibly within the Franco-Cantabrian climatic refugium25, leading to later populations associated with the Magdalenian culture (GoyetQ2 cluster and El Mirón). Conversely, the ancestry found in pre-30 ka eastern European individuals (Kostenki cluster and Sunghir group) contributed to Gravettian-associated individuals from central and southern Europe (Věstonice cluster), the latter without descendants retrieved in post-LGM populations from those regions.First, we show that individuals associated with the Gravettian culture across Europe were not a biologically homogeneous population. Culturally, however, we see both widespread general tendencies, such as weaponry and some portable art15 and possibly as early as the Gravettian–Epigravettian transition. A phylogeographic reconstruction of different lineages carrying this ancestry further suggests its entry point into northeastern Italy from the Balkans followed by a north-to-south expansion into the Italian peninsula alongside a population decline through sequential bottlenecks.Second, the ancestry of individuals associated with the Epigravettian culture (Villabruna cluster), which was found to genetically connect European and Near Eastern hunter-gatherers, reached southern Europe well before the transition between the Early and Late Epigravettian35, the spread of the Magdalenian across Europe is linked to southwestern to northern and northeastern post-LGM population expansions and not to movements from southeastern refugia34.Third, Magdalenian-associated individuals not only from Iberia but also from the rest of Europe carry Epigravettian-associated ancestry (Villabruna cluster). Genetic analyses of western European individuals associated with the preceding Badegoulian culture might provide clues on the processes that led to the formation of the GoyetQ2 cluster. As inferred from the archaeological record4—despite considerable technological continuity with the preceding late Magdalenian. This broadly distributed ancestry ) is most closely related to an Epigravettian-associated individual from northwestern Italy, suggesting that its expansion into continental Europe might have started from the west—and not the east—side of the Alps. Moreover, the almost complete genetic replacement of the Magdalenian-associated gene pool raises the hypothesis that parts of Europe were differentially populated during the abrupt climatic variation starting around 14.7 ka with the Bølling–Allerød warming period, creating areas where southern European populations could expand. This might also explain the genetic uniformity of the Oberkassel cluster across large parts of western Eurasia but genomic data from between 15 and 14 ka is needed to understand the exact dynamics of this turnover.Fourth, we extend the finding of a large-scale genetic turnover as early as 14 ka in central and western European hunter-gatherers associated with multiple techno-complexes—Federmesser, Azilian and other Final Palaeolithic groups49 and around 7.5 ka in the upper Volga region, possibly linked to the spread of pottery in the region50.Fifth, the Oberkassel ancestry in western and central Europe and the Sidelkino ancestry in eastern Europe remained largely isolated for almost 6,000 years until genetic interactions were first observed—around 8 ka in northeastern Germany, possibly associated with cultural exchanges along the BalticsIn conclusion, our study reveals that western and southwestern Europe served as climatic refugia for the persistence of human groups during the coldest phase of the last Ice Age whereas populations in the Italian peninsula and the eastern European plain were genetically overturned, challenging the role of these regions as glacial refugia for humans. The incoming Villabruna ancestry later became the most widespread hunter-gatherer ancestry across Europe. Further palaeogenomic studies on Upper Palaeolithic individuals from the Balkans will be essential for understanding whether southeastern Europe represents the source of the Villabruna ancestry and a climatic refugium for human populations during the LGM.Note added in proof: A companion paper51 describes genome-wide data of a 23,000-year-old Solutrean-associated individual from southern Iberia that extend the evidence of genetic continuity across the LGM in southwestern Europe.The ancient human specimens analysed in this work derive from multiple scientific collaborations. All remains were sampled with the approval of the institutions responsible for the analysis of archaeological material. This was achieved through collaboration with local curators and scientists from the countries where the skeletal material is preserved and who are listed among the authors of this study. The responsible co-authors for the material from each archaeological site are listed in Supplementary Information, section The analysed individuals span from the Upper Palaeolithic to the Neolithic. While terms such as lithic industry, techno-complex, prehistoric tradition, and so on might be more appropriate to refer to the various associated chrono-cultural subdivisions, they concern different levels of discussion and are not applicable to all contexts investigated here. Therefore, the broader terms ‘archaeological culture’ or simply ‘culture’ are used here to refer to archaeologically defined material cultures without implying links to modern anthropological and/or ethnographical concepts of culture.n = 29), Center for Isotope Research, University of Groningen , University of Aarhus , Beta Analytics , Zürich , International Chemical Analysis , Natural History Museum in Paris  and Vilnius   in Supplementary Data We report 47 new radiocarbon dates performed on skeletal elements of 40 individuals by the Curt-Engelhorn-Zentrum Archaeometrie in Mannheim ) were used. After 2 washing steps using the manufacturer’s wash buffer, DNA was eluted in TET  in two steps for a final volume of 100 μl. After DNA lysis, a subset of samples was extracted using silica-coated magnetic particles on an automated liquid handling system (Agilent Technologies Bravo NGS Workstation)57. Double-stranded DNA libraries were built from 25 μl of DNA extract, without the presence of uracil DNA glycosylase (ds_nonUDG) or in the presence of uracil DNA glycosylase , following a double-stranded ‘UDG-half’ library preparation to reduce, but not eliminate, the amount of deamination-induced damage towards the ends of ancient DNA (aDNA) fragments58. Negative and positive controls were carried alongside each experiment. Libraries were quantified using the IS7 and IS8 primers59 in a quantification assay using a DyNAmo SYBR Green qPCR Kit (Thermo Fisher Scientific) on the LightCycler 480 (Roche). Each aDNA library was double indexed60 in 1–4 parallel 100 μl reactions using PfuTurbo DNA Polymerase (Agilent). The indexed products for each library were pooled, purified over MinElute columns (Qiagen), eluted in 50 μl TET and again quantified using the IS5 and IS6 primers59 using the quantification method described above. The purified products were amplified in multiple 100 μl reactions using Herculase II Fusion DNA Polymerase (Agilent) following the manufacturer’s specifications with 0.3 μM of the IS5/IS6 primers. After another MinElute purification, the product was quantified using the Agilent 2100 Bioanalyzer DNA 1000 chip. An equimolar pool of all libraries was then prepared for shotgun sequencing on Illumina Hiseq4000 platform using 75bp single-end reads for screening. Single-stranded DNA libraries were built from 30 μl of DNA extract in the absence of uracil DNA glycosylase (ss_nonUDG) followed by double indexing, using an automated version of the protocols described in61 on the liquid handling system mentioned before. The single-stranded library of Cuiry Les Chaudardes 1 was produced with partial UDG treatment 62 (Supplementary Data The human remains were processed in dedicated laboratories at the Max Planck Institute for the Science of Human History in Jena (Germany), University of Tübingen (Germany), University of Florence , Leiden University Medical Center (the Netherlands) and University of Tartu (Estonia). Human bones and teeth were sampled in clean room facilities to minimize the inclusion of modern human DNA contamination during this procedure. DNA was extracted from the generated bone or tooth powder following established protocols. A subset of samples (GER002 and GER003) were pre-treated with a washing step to reduce surface contamination6. mtDNA capture63 was also performed for those libraries where mtDNA coverage was not high enough to assess mtDNA haplogroup and contamination. Illumina sequencing platforms were also used to sequence the 1240k and mtDNA captured libraries (Supplementary Data Both double-stranded and single-stranded libraries were further amplified with IS5/IS6 primers to reach a concentration of 200–400 ng/μl as measured on a NanoDrop spectrophotometer (Thermo Fisher Scientific). The libraries underwent shallow shotgun sequencing on an Illumina HiSeq 4000 instrument with 75 single-end-run cycles using the manufacturer’s protocol, to evaluate the human endogenous DNA content and quality. Samples with a percentage of human DNA in shotgun data around 0.1% or greater were enriched for a set of 1,237,207 targeted SNPs (1240k capture) across the human genome64. Within the pipeline, the adapters were removed by AdapterRemoval 2.2.065, reads were mapped with BWA 0.7.12 aln/samse algorithm66, duplications were removed by DeDup 0.12.1 (https://github.com/apeltzer/DeDup) and damage patterns of each library were checked with mapDamage 2.0.6 and 2.0.967. The deduplicated bam files were filtered using PMDtools 0.6068 with a threshold of 3, to reduce potential modern DNA contamination based on postmortem DNA deamination. For ds_halfUDG libraries, we masked 2 bp from both ends of the reads with trimBam in bamUtil 1.0.13 (https://github.com/statgen/bamUtil) to remove the damaged sites.The de-multiplexed capture sequencing reads were cleaned and mapped to human reference genome hs37d5 using EAGER pipeline 1.92.55NC_012920.1 with BWA 0.7.12 aln/samse algorithm  and realigned with CircularMapper64. The mapped reads from the same individual and library set-up were merged and duplications were removed with DeDup. Reads with a mapping quality below 30 were then filtered with samtools, and the consensus sequences were generated by Schmutzi69.The mitochondrial capture sequencing reads were cleaned by AdapterRemoval 2.2.0 to remove the adapters and reads with lengths below 30 bp. Then the cleaned reads together with cleaned reads from 1240k capture sequencing were mapped to human reference mitochondrial sequence 4  under random haploid calling mode. For ds_halfUDG libraries, we called genotypes on all targeted sites from 2bp-masked bam files; for ds_nonUDG libraries, we called genotypes on transversion sites only; for ss_nonUDG libraries, we called genotypes with single-strand mode, which ignores forward reads at C/T polymorphisms and reverse reads at G/A polymorphisms.The cleaned reads with base quality and mapping quality over 30 were piled up with mpileup in SAMtools 1.378. Then we combined our newly generated genotypes with published genotypes from ancient and modern individuals from AADR v42.4  version 42.4) for downstream analysis94.Then we merged the genotypes from different libraries of the same individual, by randomly picking alleles from available genotype calls, using a custom script. After merging, individuals with less than 6,000 SNPs on 1240k sites were excluded from further analysis because of low coverage. We also genotyped a selection of previously published individuals with the same approach . Inconsistent haplogroup assignments were manually verified as indicated24 . We built a Maximum Parsimony tree with 103 mtDNA sequences plus an African sequence as the outgroup (not shown) after the removal of individuals younger than 6.5 ka and mtDNAs from the same site with an identical placement. The tree was calculated on 16,528 positions  and with 500 bootstrap iterations using MEGA1097.The mitochondrial haplogroups were determined using HaploGrep 298  to avoid arbitrarily placing low-coverage samples at the root of major haplogroups. This results in a tree with 57 newly reported and previously published ancient individuals while present-day sequences are collapsed in the major Y-chromosome haplogroups . The tentative placements of low-coverage ancient individuals based on their haplogroup assignment  from the International Society of Genetic Genealogy (ISOGG) dataset, ignoring C-to-T and G-to-A transitions on the forward and reverse reads, respectively. This procedure allowed us to manually traverse the ISOGG Y-Haplogroup Tree, checking in a semi-automatic way which positions were covered. This process allowed us to assign an ancestral or derived haplogroup for covered branches, and to make corrections to calls in cases where, for instance, a more derived haplogroup was called because of residual ancient damage (C-to-T or G-to-A mismatches) in terminal read positions at diagnostic SNPs5.73 fromr) based on PMR on the autosomal SNPs  were then estimated using a maximum likelihood method, after filtering individuals with a signal of close-kin inbreeding   and performed with classical MDS algorithm  implemented in R 3.5.1. The hunter-gatherers were grouped based on their geographic origins and dates (Supplementary Information, section f3-statistics were calculated with qp3Pop 435 in ADMIXTOOLS 5.1 package103.The MDS analysis showing the genetic affinity among European hunter-gatherers was based on the distance matrix derived from outgroup f2 distance matrix of Epigravettian-associated groups was generated with qpfstats 200 in ADMIXTOOLS 7.0.2 package, with parameters “allsnps: YES, scale: NO”, and Mbuti.DG set as the outgroup. The neighbour-joining tree was then reconstructed using the neighbour-joining method implemented in Ape 5.3 package104 of R 3.5.1.The pairwise f4-statistics were calculated by qpDstat 755 with parameter “f4 mode: YES”, with the Mbuti.DG population from Africa used as outgroup in all f-statistics analyses. The tool qpAdm 810 in ADMIXTOOLS 5.1 was applied to model the ancestries of admixed populations, with “allsnps” mode and the outgroup set selection described in Supplementary Information, section 105, with a bin size of 0.1 cM for covariance calculation and the start of exponential fitting at d ≥ 0.5cM.The 37. Details on individuals involved in the analysis, read counts processing and allele frequency computation are provided in the Supplementary Information, section As the coverage for most ancient samples was not sufficient for diploid genotype calling, we counted the reads covering selected phenotypic SNPs on reference or alternative alleles and computed the group-based allele frequencies following a maximum likelihood approach described in Mathieson et al.Further information on research design is available in the Any methods, additional references, Nature Portfolio reporting summaries, source data, extended data, supplementary information, acknowledgements, peer review information; details of author contributions and competing interests; and statements of data and code availability are available at 10.1038/s41586-023-05726-0.Supplementary InformationArchaeological background, method descriptions and discussions additional to the main text, including sections 1–13, Figs. 1–32, Tables 1–4 and references.Reporting SummarySupplementary Data 1Metadata information of studied individuals.Supplementary Data 2f-statistics analyses.Raw data of Supplementary Data 3Raw data of other types of analyses.


In situ conserved wild rice (Oryza rufipogon Griff.) is a promising source of alleles for improving rice production worldwide. In this study, we conducted a genomic analysis of an in situ conserved wild rice population (Guiping wild rice) growing at the center of wild rice genetic diversity in South China. Differences in the plant architecture in this population were investigated. An analysis using molecular markers revealed the substantial genetic diversity in this population, which was divided into subgroups according to the plant architecture. After resequencing representative individuals, the Guiping wild rice population was compared with other O. rufipogon and Oryza sativa populations. The results indicated that this in situ conserved wild rice population has a unique genetic structure, with genes that were introgressed from aromatic and O. sativa ssp. indica and japonica populations. The QTLs associated with plant architecture in this population were detected via a pair-wise comparison analysis of the sequencing data for multiple DNA pools. The results suggested that a heading date-related gene (DHD1) might be associated with variations in plant architecture and may have originated in cultivated rice. Our findings provide researchers with useful insights for future genomic analyses of in situ conserved wild rice populations. Oryza sativa) is one of the oldest staple food crops widely consumed by half of the global population, which is expected to grow by 25% and reach 10 billion over the next 30 years. Developing new rice varieties that are higher yielding and more nutritious than current cultivated varieties as well as resistant to pests and diseases and ideal for climate-smart agricultural production is critical for avoiding widespread malnutrition or starvation , but their continued growth is at risk because of recent human activities and natural degradation  and nuclear intron targeting (InDel), were used to evaluate the genetic diversity in different crop wild relative species  assess the genetic diversity within an in situ conserved population; (2) detect genes that were introgressed from other wild rice populations or local landraces; and (3) identify natural variations associated with plant architecture in the in situ conserved population. Our results provide useful information regarding plant architectural diversity and new insights for optimizing the in situ conservation of wild rice in China.In this study, we performed an extensive field and genomic investigation of a typical natural in situ conservation site, placed in a plastic bag, and stored at –20°C. Collection of 30 samples in the mixing pool were performed also using a 5 m-distance rule. For the 20 re-sequenced samples, including 3 erect types samples, 4 semi-erect samples, 5 tilt samples, and 8 creep samples, same type individual collection distance of more than 20 m.To ensure the collected samples fully represented the genetic diversity of the population and to avoid collecting clones of the same individual, irregular grid lines were applied. Specifically, using an individual collection distance of about 5 m, a total of 184 randomly selected leaves were collected from their original habitat, Guiping 2O, 0.6 μL forward and reverse primers, 2 μL DNA, and 7.5 μL 2× Es Taq MasterMix. The PCR program was as follows: 95°C for 5 min; 35 cycles of 94°C for 30 s, 57°C for 30 s, and 72°C for 30 s; and 72°C for 2 min. The amplified products were separated in 6% denaturing polyacrylamide gels.The collected leaves were ground to a powder in liquid nitrogen using the SPEX Sample Prep Geno/Grinder. Genomic DNA was extracted according to the CTAB method . A PCR aI), observed heterozygosity (He), and expected heterozygosity (Ho) (The simple sequence repeat (SSR) data format was converted to readable input files for STRUCTURE, PowerMarker, and POPGENE. We used POPGENE 1.31  to calcuity (Ho) . STRUCTUity (Ho) . We evality (Ho)  was usedity (Ho)  of Powerity (Ho) .Sequences were aligned using the MUSCLE program in MEGA 7. A phylogenetic analysis involving nucleotide sequences was conducted using the maximum likelihood method, with 1,000 bootstrap replicates. A model-based estimation of the ancestry coefficient was performed using ADMIXTURE . High-quin situ conservation site. The sample detection, library construction, library quality detection, and onboard sequencing were performed according to the standard Illumina protocols. After confirming the quality of the genomic DNA was sufficient for the subsequent analysis, the DNA was fragmented via a mechanical method. The ends of the fragmented DNA were repaired and a poly-A tail was added to the 3’ end. After adding a sequencing adapter, a PCR amplification was performed and the resulting products were purified to complete the construction of the sequencing library. The high-quality library was sequenced using an Illumina system. We used the BWA software to align the short reads of the DNA bulks to the Nipponbare reference genome (MSU_v7.0)  . The GATSU_v7.0) . On the SU_v7.0)  was usedmut, Cmut, Gmut, and Tmut, respectively represent the frequency of A, C, G, and T bases in the mixed mutant pool, whereas Awt, Cwt, Gwt, and Twt respectively represent the frequency of A, C, G, and T bases in the mixed wild-type pool. During the analysis, there was a SNP site that differed between the two mixed genotypes. Additionally, the depth of the individual bases in the different mixed pools was statistically significant and the ED value for each site was calculated. The background noise was eliminated by applying the 5th power of the original ED as the correlation value   . This sin plants . An examn plants , which aAe , He, Ho, and I across all loci were 1.204, 0.852, 0.148, and 0.259, respectively . After aligning the reads to the rice reference genome sequence, we identified 5,037,497 non-singleton SNPs. On the basis of the SNP data, the sequence diversity (π) of O. rufipogon was estimated to be about 0.003, which is higher than that of O. sativa (0.0024), O. sativa ssp. indica (0.0016), and O. sativa ssp. japonica (0.0006) (indica (Twenty (0.0006) . A princ(0.0006) . We also(0.0006) . Interes , XI-1B (about 20%), and XI-1A (about 15%), but a small percentage was from Aromatic. In contrast, the genetic components of the accessions with a tilted phenotype were primarily from wild rice (about 80%) and Aromatic (about 10%), but a small proportion was from XI-1A. The genetic components of the accessions with a creeping phenotype were mostly from wild rice (about 90%), with approximately 10% from Aromatic. The ABBA results also indicated that the 20 Guiping wild rice accessions had genetic components from Aromatic, XI-1A, and XI-1B  were downloaded from the Genome Variation Map database.cessions . Germplacessions , with thcessions . The ress K = 9, . They wend XI-1B .A PCAMP protocol  was usedDHD1 gene on chromosome 11 had the highest ED value in the R01–R04 comparison. In a recent study, DHD1 was revealed to regulate the rice heading date, while also influencing the plant architecture  accessions were from China.To identify candidate genomic regions responsible for the plant architecture of the Guiping wild rice population, we compared the SNPs and InDels between DNA pools. We used ED-based methods involving SNPs and InDels to identify candidate regions. The overlapping physical positions on the same chromosome were selected in each comparison . The intitecture . No othed OsDHD1 . Using dd OsMOC1 , which sd OsMOC1 , 3. Thirhenotype . The culOryza rufipogon is an important germplasm resource for food security, but it is seriously endangered worldwide. Almost all studies on the in situ conservation of wild rice have been conducted in China. Most of these studies focused on the related policy, techniques, and methods for establishing in situ conservation sites. Thus, there are relatively few reports describing genetic analyses of the introgression involving other populations, including cultivated rice and other wild rice accessions.in situ conserved Chinese wild rice population in Guiping county of Guangxi province was investigated. The genetic diversity was first elucidated on the basis of 40 molecular markers  banks or gardens . The genetic diversity indictors Ho and I in the current study were consistent with the corresponding values in these earlier studies. Considering the materials from ex situ conservation sites were collected from their original habitats 10 or 20 years ago, the in situ conservation site in Guiping was suitable for maintaining wild rice genetic diversity. Moreover, the sequence diversity (π) determined according to the SNP data (about 0.003) was similar to that of wild rice and much higher than that of cultivated rice in an earlier study (In this study, a typical  markers . Compareer study . Accordiin situ conservation of wild rice is to prevent human activities from affecting genetic diversity and cultivated rice gene flow. We re-sequenced 20 individuals from this conservation site that varied in terms of plant architecture (in situ conserved wild rice population in Guiping has a special plant architecture-related population structure. On the basis of published data (indica rice (The central goal of the itecture . The PCAitecture . Additioitecture . These rhed data , all of hed data , indicathed data . Howeverica rice .in situ conserved wild rice population, grows in the central Pearl River region, which is where rice was first domesticated (OsDHD1. The PCAMP results also suggested that OsDHD1 may be a candidate gene associated with plant type variations. We also detected variations in major plant architecture-related genes, such as PROG1 and LAZY1, in the wild rice population, but they did not affect plant architecture. An examination of the cultivated rice accessions that were the source of the introgressed genes in Guiping wild rice revealed a lack of accessions in Guiping with OsDHD1 haplotypes 1, 3, or 4, but a few cultivated rice varieties or landraces native to Guangxi province with these haplotypes were identified.The Guiping wild rice population, which is the largest sticated . There wOryza species may result in wild rice pollen infiltration, we speculated that the plant architecture variations may have been caused by the introgression of genes from Guiping landraces, but also by the infiltration of pollen from major commercially cultivated rice varieties. A good plant structure may positively affect the planting density and photosynthetic efficiency, while also providing plants with a competitive advantage. Therefore, variations in plant architecture may be the result of natural genomic modifications that enable adaptations to environmental conditions. The Guiping in situ wild rice conservation site has metal fences to keep out livestock and is surrounded by many fields containing cultivated rice varieties. Accordingly, we strongly recommend that the in situ conservation site should be surrounded by a fence that can appropriately isolate the area and prevent the infiltration of alien pollen. Furthermore, in future related genomic investigations, additional individuals should be collected for ex situ conservation, identification, and evaluation to conserve the genetic integrity of the population and to identify elite genes in the population relevant for improving rice production.Because only growing closely related SRR19425523–SRR19425542.The data presented in this study are deposited in NCBI repository, accession number: ZY and YZ performed most of the experiments, including phenotyping, data analysis, and haplotype analysis. YZ, MX, and XW participated in the genomic comparison. JH and ZX participated in some of the phenotyping and genetic diversity analysis. FL, YW, YN, JG, DL, ZL, ZH, YL, and XZ participated in the field investigation and logistic work. QY supervised the study. HH and WQ designed the study and wrote the manuscript. All authors contributed to the article and approved the submitted version.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Phytophthora infestans in the major potato cultivation region of north-western Russia, where potato is grown primarily by small households with limited chemical treatment of late blight. In this study, the mating type, sensitivity to metalaxyl, and genotype and population genetic diversity (based on 12 simple sequence repeat (SSR) markers) of 238 isolates of P. infestans from the Pskov region during the years 2010–2013 were characterized. The aim was to examine the population structure, phenotypic and genotypic diversity, and the prevalent reproductive mode of P. infestans, as well as the influence of the location, time, and agricultural management practices on the pathogen population. The frequency of the A2 mating was stable over the four seasons and ranged from 33 to 48% of the sampled population. Both mating types occurred simultaneously in 90% of studied fields, suggesting the presence of sexual reproduction and oospore production in P. infestans in the Pskov region. Metalaxyl-sensitive isolates prevailed in all four years (72%), however, significantly fewer sensitive isolates were found in samples from large-scale conventional fields. A total of 50 alleles were detected in the 141 P. infestans isolates analyzed for genetic diversity. Amongst the 83 SSR multilocus genotypes (MLGs) detected, 65% were unique and the number of MLGs varied between locations from 3 to 20. These results, together with the high genotypic diversity observed in all the locations and the lack of significance of linkage disequilibrium, suggest that sexual recombination is likely responsible for the unique MLGs and the high genetic diversity found in the Pskov region population, resembling those of north-eastern European populations.There is limited understanding of the genetic variability in  Phytophthora infestans, is a long studied pathogen that has been claimed to be the most destructive agent for potato production worldwide. This pathogen was responsible for the Irish famine in the mid-1840s and is a re-emerging disease that still constitutes a major threat to potato cultivation [P. infestans infections due to yield losses and disease control of the pathogen has been estimated at around €1 billion in Europe alone [The late blight pathogen, pe alone . This hepe alone .P. infestans across many countries, except in Mexico which was considered the center of origin where the A1 and A2 mating types co-existed [P. infestans and enhanced the spread and severity of the disease [P. infestans [P. infestans constitutes a good example of adaptation for survival with resultant difficulties in the management of the disease.Until 1980, only A1 mating type isolates were known to occur in Europe and other parts of the world, which has prevented the sexual reproduction of -existed . However-existed , and fir-existed , then in-existed , England-existed , the Net-existed . The pre disease . The incnfestans . The enhP. infestans in the period 2002–2017 were 33.6%, with the largest being in 2013 with a 66% loss [In the study period of 2010–2013, Russia ranked third in the world’s potato production, after China and India . In Russ66% loss .P. infestans populations is dependent on hybridization during the sexual process, the intensive exchange of low-quality infected seed materials, and the dispersal of sporangia in the atmosphere [P. infestans population’s genetic structure increase the pathogen’s epidemiological potential [P. infestans’ population characteristics and genotypic structure is needed to gain an insight into the migration, evolution, and virulence of the pathogen, allowing there to be updates to management advice for potato cultivation and disease protection [P. infestans with an increase of the frequency of the A2 mating type over time [P. infestans has been analyzed based on SSR using a limited set of data from potato fields (65 isolates) for the period 2008–2011 in five regions: the Kostroma, Leningrad, Moscow, Nizhnii Novgorod, and Smolensk regions, where the highest diversity was in the potato population in the Moscow region and similarities with other European populations were not identified [P. infestans have never been studied in this part of north-western Russia, that borders the intensive large-scale potato cultivation areas in the northern Baltics. Such information is important for identifying suitable sources of resistance and pathogen isolates for use in resistance screening in potato breeding programs.Increased genotypic diversity in mosphere . Rapid cotential . Thus, totection . Long-tever time ,22. The entified . A more entified . The useentified , is chalP. infestans in the European part of Russia and neighboring countries, such as Estonia and Latvia [P. infestans populations in the Pskov region of Russia. Therefore, in this four year study, P. infestans isolates were collected from ten locations in the Pskov region in Russia and characterized with 12 SSR markers [Potato late blight has considerable importance in Russian potato production. As described above, the populations of d Latvia ,26,27, a markers  and phenP. infestans populations are in the Pskov region, as well as the diversity level caused by the sexually recombined strains; (2) what the phenotypic variation is within the Pskov population of P. infestans, indicated by the mating type and metalaxyl resistance; and (3) how the location, year, and agricultural management practices influence the genotypic diversity of the pathogen. Briefly, we also tried to compare the Pskov region’s P. infestans population with other Russian and European populations. We hypothesized that the P. infestans populations in the region are sexually and genetically diverse.More specifically, it was necessary to find out: (1) how genetically diverse the P. infestans were collected over four years from 10 locations at the Pskov region in north-west Russia. A total of 238 isolates were collected from 20 sites located at Lakomtsevo (two sites), Pechory and Styagly in 2010; Strugi Krasnye, and Styagly (two sites) in 2011; Gusinets (two sites), Lezgi, Styagly (two sites), Tyamsha, and Zatrub’ye-Lebedy in 2012; and Bereznyuk, Bulatnovo, Gusinets (two sites), Lezgi, and Zatrub’ye-Lebedy in 2013  farm fields and a minority from large-scale conventional (LSC) production fields . In 2011Mating types were determined by the method described in Runno-Paurson et al. . The met−1, prepared from technical grade mefenoxam , CGA 329351A). The inoculum was incubated for two hours at 4 °C to induce the zoospore release. The inoculation and trial incubation was done as described by Runno-Paurson et al. [−1 metalaxyl [−1, but not on leaves floating in 100 mg L−1 were rated intermediate, and those sporulating only in water were rated sensitive.Resistance to metalaxyl was tested using a modification of the floating leaflet method , as descetalaxyl . Those sP. infestans isolates were grown on rye B agar plates for 2–4 weeks at 17 °C in the dark. Mycelium was scraped off from Petri plates with a sterile scalpel blade and frozen at −80 °C. DNeasy Plant Mini Kit  was used to extract DNA following the manufacturer’s instructions. Genotyping of 141 isolates was performed at The James Hutton Institute , following Li et al.’s [−1 and within a range of 5–200 ng µL−1). Amplification reactions were carried out on a Bio-Rad T100 Thermal Cycler  under the following conditions: 95 °C for 5 min followed by 28 cycles of 95 °C for 30 s, 58 °C for 90 s, and 72 °C for 20 s, and a final extension at 60 °C for 30 min. PCR products were diluted 0–100 times depending on the initial DNA concentration in the PCR reaction mix. The diluted PCR product (0.6 µL) was added to a mix containing 10.14 µL of deionized formamide  and 0.06 µL of GeneScan-500LIZ standard (Applied Biosystems). A detailed protocol is provided on the EuroBlight website  (accessed on 10 April 2022). The fluorescent-labeled PCR products were analyzed using an ABI3730 DNA Analyzer (Applied Biosystems) according to the manufacturer’s instructions. The size of the alleles was determined using GeneMapper v3.7 (Applied Biosystems) software.Pure-culture et al.’s  SSR market al.’s ,32. One Phytophthora infestans isolates collected from 20 sites in Pskov region of Russia during 2010–2013 were analyzed for mating type (238 isolates), metalaxyl response (189 isolates), and a representative selection of 141 isolates was chosen from of 238 P. infestans isolates for SSR marker genotyping, keeping the A1 and A2 mating type frequencies within fields and in the whole population about the same as previously published by Runno-Paurson et al., 2016 [P. infestans isolates between years, study sites, locations, and agricultural management practices were tested using a logistic analysis  with a poppr (ver. 2.9.3) [poppr. Simpson’s index of genotypic diversity , corrected for sample size (N) by multiplying lambda by N/(N−1), was also calculated using the package poppr for the locations, years, and agricultural management practices. Simpson’s index (λ) was also used to measure the gene diversity of the SSR loci. To eliminate the bias imposed by the large asexual reproductive capacity , a clone corrected dataset [poppr package to include only one representative isolate of each multilocus genotype [poppr. As many genetic distance measures are not always euclidean, this was corrected for before analysis of AMOVA. Poppr automates this with three methods implemented in ade4 [P. infestans populations were genetically differentiated and assesses how genetic variation was distributed among and within populations based on 1000 permutations. A linkage disequilibrium (LD) analysis was used to infer the reproductive strategy of P. infestans based on the index of association (AI) and standardized index of association (r¯d). The null model for AI is random recombination [poppr for clone-corrected datasets. As the index of association is dependent on the sample size of loci, we removed this dependency and used the standardized index of association (r¯d) that accounts for the number of loci sampled and is less biased [P. infestans was investigated using discriminant analysis of principal components (DAPC). DAPC can determine any clusters of genetically related isolates, and display differences between clusters of genetically distinct individuals while minimizing variations within clusters [adegenet [poppr (function bruvo. msn) and visualized using a minimum spanning network (MSN) [Nei’s  measure . 2.9.3)  in R (ve. 2.9.3) . GenAlEx. 2.9.3)  was used dataset ,39 was cgenotype ,41,42. T in ade4 . An analbination . They webination  to simuls biased . The popclusters . The optclusters . The numclusters . Furtherclusters . All theadegenet . The DAPadegenet ,49, or eadegenet  in the aadegenet ,49 and iadegenet . In addiadegenet . In anotadegenet . Finallyrk (MSN) .HT − HS)/HT, where HT corresponds to the total gene diversity, and HS corresponds to the gene diversity within sub-populations [GST and D measure differentiation in very different ways. Jost [GST and its relatives do not really measure differentiation and that GST depends on average within-population heterozygosity (HS), which prevents GST from taking values larger than average homozygosity. Though GST is mathematically constrained by HS, there is no such constraint on D, implying that D can take any value in the range 0–1 regardless of HS [D still shares the same problems of dependence on HS and mutation rate as GST and its relatives, and the problems are even more pronounced for D than for GST. The author concluded that GST is still a very useful measure of genetic differentiation [GST as a measure of genetic differentiation.The coefficient of genetic differentiation (GST) at population level was estimated as GST =  as well as between locations , where a higher frequency of the A2 mating type was found among isolates collected from Gusinets, Pechory, Strugi Krasnye, and Lezgi . In 2011, the frequency of A2 was low (33%), possibly due to the low number of isolates tested, compared to other years. Both mating types were present at 17 of the 19 sites (90%) where more than one isolate was tested. There were no significant differences between different agricultural management practices  fields vs. small-scale conventional (SSC) fields; χ2 = 2.47, df = 1, p = 0.16).The overall distribution of A1 and A2 mating type isolates were nearly equal to 1:1 as, among the 238 isolates, 131 (55%) were the A1 mating type and 107 (45%) were the A2 mating type A. Both And Lezgi B. The frnd Lezgi C, howeve2 = 90.42, df = 38, p < 0.0001) and locations . Among the isolates, metalaxyl-sensitive phenotypes predominated in Pechory, Strugi Krasnye, and Tyamsha with 100%, and in Stagly with 92% . Significant differences were found between different agricultural management practices , where a higher proportion of resistant isolates (25%) were found on LSC fields compared to SSC fields (9%). Metalaxyl-sensitive isolates dominated on SSC fields (83%), while the frequency of sensitive isolates on LSC fields was considerably lower (54%). All three categories of responses to metalaxyl were found in both A1 and A2 mating types .Of the 189 isolates tested, 29 (15%) were classified as resistant, 24 (13%) intermediate, and 136 (72%) as sensitive A. Highlywith 92% B. The mewith 92% C. The prwith 92% C. The asng types D. The maHe estimates the mean expected heterozygosity at the locus. The locus Pi70 only had two alleles, and the locus also had a low genetic diversity (0.094), and low expected heterozygosity (0.095). This is a sign that this might be a phylogenetically uninformative locus, while the loci G11 (He = 0.802 and genetic diversity = 0.799) and SSR4 (He = 0.769 and genetic diversity = 0.766) were the most informative loci with 8 alleles per locus  to 8 alleles (G11 and SSR4) per locus, and an average of 4.17 ± 0.65 alleles . The miner locus . Of locier locus . Not aller locus , as expeer locus . Eighty-P. infestans according to location  performed with the SSR datasets showed no clear pattern of grouping among isolates of location . Memberslocation . Howeverlocation , did notlocation . This MLlocation , MSN  supported random mating for locations, years, and agricultural management practices, respectively, for the clone-corrected data set (HS) and total gene diversity (HT) were 0.478 and 0.533, respectively  and small-scale farms (λc = 0.97). The result of genotypic evenness (5E) indicates that the MLGs observed in Tyamsha were equal in abundance with an 5E value of 1.0 (5E = 0.48). MLGs observed in the year 2013 were closest to equal the genotype abundance (5E = 0.89) compared to the year 2010 (5E = 0.83) and the year 2011 (5E = 0.84), while the year 2012 was more dominated by a single genotype (5E = 0.58). A comparison of agricultural management practices showed that MLGs were more evenly distributed (5E = 0.87) in LSC compared to SSC (5E = 0.61). Overall, the value of genetic diversity across the location was moderately high, He = 0.533 (He = 0.234). The gene diversity across the years was also high, ranging from 0.489 in the year 2012, 0.507 in 2010, and 0.521 in 2011 to 0.551 in the year 2013, with an overall value of 0.533, and a mean of 0.517 ± 0.01. The populations of P. infestans isolates had high levels of genetic diversity in both LSC (He = 0.532) and SSC (He = 0.531), with an overall value of 0.533, and a mean of 0.532 ± 0.00.The number of expected multilocus genotypes, corrected for sample size (eMLG), was used to compare the genotypic richness among the locations, years, and agricultural management practices. Zatrub’ye-Lebedy was genotypically richer (9.36) than the other locations , while te of 1.0 , while o = 0.533 , except P. infestans population will help to improve late blight control, as it could provide information on the improved choice of control strategy and/or fungicides, as well as direct resistance breeding efforts [P. infestans population were investigated in the unstudied Pskov region of Russia, to determine how the pathogen populations differed by location, year, and agricultural management practices.In-depth knowledge of the traits, composition, and dynamics of a changing  efforts . Russia P. infestans populations from different locations is valuable in enhancing the understanding of the biology of the pathogen and the potentially adaptive genotypic diversity in the species. The structural analysis indicated an admixture of isolates among the populations. No separation of isolates into distinct isolated subpopulations by location was observed. This may be attributed to gene flow among the locations, which is reflected by the high migration rate estimates. A high genetic exchange or high gene flow will lead to low genetic differentiation, as evidenced by the GST value. The migration may be due to the long-distance dispersal of spore and/or anthropogenic activities, such as the movement and exchange of infected plant material [P. infestans and the evolutionary forces responsible for its diversity has also been investigated in China using molecular population genetics approaches [P. infestans. This illustrates an example of a source–sink dynamic of the populations and diversification patterns shaped by gene flow. However, on a global scale, the geographic barrier and minimum cross-border trade can disturb the gene flow between pathogen populations, even between neighboring countries. There are reported cases of a lack of gene flow of P. infestans populations between China and India, which may be attributed to the presence of the Himalaya Plateau and the minimum cross-border trade of potato and tomato products between these neighboring countries [Gene flow is an important evolutionary force that positively influences the adaptive responses of plant pathogens to changes in the environment and plant disease management strategies . Pathogematerial . The latmaterial . The genproaches . The autountries .P. infestans mating types was close to 1:1, with no significant differences in the proportion between years. This observation is common for a sexually reproducing population and consistent with the local production of oospores [P. infestans can reproduce clonally even if both mating types are present in a region or location. Therefore, other pieces of evidence were sought to confirm this observation [P. infestans are produced by sexual recombination, giving high levels of genetic diversity [P. infestans in some regions of Russia had not been documented [P. infestans population of Scandinavia, the Baltic states, eastern Europe (including Russia), and Mexico [We detected both the A1 and A2 mating types in all locations and all years and the overall ratio of oospores ,62. Howeervation . We failiversity . A very iversity . The resiversity ,32,66. Ucumented ,20,67. Sd Mexico ,69,70.P. infestans populations was very high. This was also combined with many observed unique multilocus genotypes (MLGs). The high genotypic diversity with SSR markers and the RG57 fingerprints also confirms the previous result from Moscow [P. infestans, which will help to identify new genotypes. Crop rotation rules are not usually strictly adhered to by small-scale farmers, as they tend to grow potatoes every year on the same field with inadequate control of late blight. Thus the risk of oospore-derived infections is high, resulting in a genotypically diverse inoculum in fields, which is confirmed by the current results of several unique MLGs observed in small conventional fields.The genotypic diversity among the Russian m Moscow ,71 and sm Moscow ,20. The m Moscow ,32,68, bm Moscow ,73,74, am Moscow ,76, Asiam Moscow ,77, and m Moscow ,79. Howem Moscow ,81. Mostm Moscow ,62. Highm Moscow . Dominanm Moscow . InteresPhytophthora spp. [P. infestans strains can vary and the triploids can change to a diploid genome constitution upon stress [It is interesting to note that some of the genotypes with isolates from the same location, as well as genotypes with isolates from different locations that had similar SSR profiles were of different mating types. We have proposed a mating-type switching at the mating-type locus as an explanation for this observation. Mating-type switching had been observed in ora spp.  and otheora spp. . This asn stress . It is un stress .P. infestans genotypes can flourish in addition to those that infect commercial crops [For effective disease management in some European countries, repetitive chemical spraying, more than ten times per season, needs to be applied per season . Furtheral crops . Altogetal crops ,93. Thisal crops ,89,90,91al crops , recordeal crops  and Cookal crops . In Russal crops . In Nordal crops ,32,93,96P. infestans [P. infestans observed may have resulted from moderate use of metalaxyl fungicide on the fields from which the samples were collected [It is clear from this study that isolates sensitive to metalaxyl prevailed in the population, as also observed in Moscow and other Russian populations of nfestans . These fnfestans , Latvia nfestans , Poland nfestans ,97, Lithnfestans , the Czenfestans , and Nornfestans . Howevernfestans ,100,101,ollected ,27.P. infestans population in the Pskov region. This is supported by the presence of both mating types in all locations studied and in several fields where multiple samples were taken, as well as evidence from the genetic analysis of the population structure, tests of linkage among loci, and other analyses of the genotypic data. Resistance to metalaxyl was present, although the metalaxyl-sensitive isolates predominated. The genotypic and phenotypic variation is consistent with regular sexual reproduction within this pathogen population and this should be considered in future disease control strategies, for instance, the consideration of longer potato crop rotations.Sexual reproduction likely takes place in the