To predict how widely distributed species will perform under future climate change, it is crucial to understand and reveal their underlying phylogenetics. However, detailed information about plant adaptation and its genetic basis and history remains scarce and especially widely distributed species receive little attention despite their putatively high adaptability.Silene vulgaris across Europe. In a greenhouse experiment, we exposed the offspring of these populations to a climate change scenario for central Europe and revealed the population structure through whole‐genome sequencing. Plants were grown under two temperatures (18°C and 21°C) and three precipitation regimes  to measure their response in biomass and fecundity‐related traits. To reveal the population genetic structure, ddRAD sequencing was employed for a whole‐genome approach. We found three major genetic clusters in S. vulgaris from Europe: one cluster comprising Southern European populations, one cluster of Western European populations, and another cluster containing central European populations. Population genetic diversity decreased with increasing latitude, and a Mantel test revealed significant correlations between FST and geographic distances as well as between genetic and environmental distances. Our trait analysis showed that the genetic clusters significantly differed in biomass‐related traits and in the days to flowering. However, half of the traits showed parallel response patterns to the experimental climate change scenario. Due to the differentiated but parallel response patterns, we assume that phenotypic plasticity plays an important role for the adaptation of the widely distributed species S. vulgaris and its intraspecific genetic lineages.To examine the adaptation potential of a widely distributed species, we sampled the model plant  Silene vulgaris were sequenced and exposed to a possible climate change scenario. The results reveal three cryptic genetic lineages in Europe with significant differences in morphological traits and parallel response patterns under climate change conditions. This suggests a compensatory strategy through phenotypic plasticity in the genetic lineages of S. vulgaris.Twenty‐five European populations of  Species are able to deal with environmental changes through migration, phenotypic plasticity, and/or genetic adaptation   to examine their phenotypic response. For the evaluation of phenotypic responses, nine different plant traits were measured. We chose those plant traits that are known to strongly react to temperature and precipitation changes and are proxies for plant fitness  to test whether putatively different genetic lineages of S. vulgaris showed a different response to a simulated climate change scenario for central Europe.It was the aim of the study (a) to reveal the genetic population structure of the sampled 22.1Silene vulgaris (Moench) Garcke is a diploid (2n = 24), perennial plant of the family of Caryophyllaceae with a self‐compatible reproductive system. Its native range covers the entire European continent including islands and expands toward Russia, North Africa , to the Middle East and parts of Asia  as described in Kahl et al. . Individual adapters were ligated on to 50 ng of digested DNA for a final pooling of 48 individuals . The library preparation was performed as in Peterson et al.  with somls Table . Size se2.3process_radtags command in STACKS (v1.47)   was used to calculate observed heterozygosity (Ho), expected heterozygosity (HE), inbreeding coefficient of populations (FIS), nucleotide diversity (π), and the interpopulation component FST. Population structure was estimated using fastSTRUCTURE . The phylogenetic analysis was done using the maximum likelihood approach in RAxML (v8.2.9) , geographic and genetic distances, and environmental and geographic distances with 100,000 repetitions . Linear mixed models were employed for the statistical analyses of plant traits that fitted a normal distribution . For binary data  and count data , we used generalized mixed models with a binomial and Poisson distribution, respectively. Furthermore, we also tested whether the genetic clusters responded differently to the climate change conditions by including the interaction term  was close to zero for all populations ranging from 0.024 (A1) to 0.087 . We also found a trend toward a decline of expected heterozygosity and nucleotide diversity with increasing latitude; however, this was not significant  and one southern French population (F3) formed one major monophyletic cluster of South‐Western Europe (hereafter referred to as cluster “South”), whereas the second monophyletic branch comprised the German , Austrian (A1), Swedish , and one Southern Swiss population (CH2) of central Europe . The third cluster will be referred to as cluster “West” comprising most French populations  and the remaining Swiss alpine population . Within the South cluster, the Spanish populations formed a monophyletic group with one French population as a sister group with 100% bootstrap support. The central European populations of S. vulgaris formed one distinct cluster with comparably low resolution. Within this cluster, no further geographic differentiation was possible with the data available, and the position of each population showed low bootstrap support. We found two Swedish populations (S1 and S2) that formed sister groups (S1 and S2) as well as many of the German populations . However, the remaining genetic relationships did not correspond to a geographic pattern within this central European cluster  and French  S. vulgaris populations analyzed in this study appear in separate clusters. A similar pattern was also found in the population analysis by Sebasky et al.  did not stand out from the remaining central European populations. The two Swedish populations (S1 and S2) clustered together in a well‐supported branch within the third cluster. The phylogenetic analysis has shown that S. vulgaris, a species widely distributed in Europe, shows a considerable range of phylogenetic diversity but can be structured in three major clusters. This phylogenetic pattern can be of different origin. One possibility is that this pattern is a result of the recolonization of Europe from distinct refugia after the LGM. In the sampled S. vulgaris populations, indicators for genetic diversity  declined with increasing latitude. The most southern populations of S. vulgaris showed the highest values of observed heterozygosity. Similar observations were found for nucleotide diversity in the present study: Nucleotide diversity was lower in populations from higher latitudes compared to populations from lower latitudes. These findings may indicate that Southern European populations have been functioning as refugia during the LGM. During that time, populations in the south of Europe remained larger as they were not disrupted by snow‐covered areas or glaciers. When temperatures were increasing, again, a subsequent recolonization of central and northern Europe was likely to start from these southern refugia. The discovered pattern in S. vulgaris of decreased genetic diversity with increasing latitude is a commonly found pattern in different species after the last ice age  and time to flowering that differed significantly among the three genetic lineages. Possibly, these trait differences are an adaptation to different environmental habitat conditions of the genetic lineages. It is known from S. vulgaris that it possesses several different ecotypes with strong genetic differentiation that are adapted to extremely unfavorable habitat conditions  . With the currently ongoing climatic changes, mean temperatures are rising in Europe and precipitation patterns are changing drastically . Because we used one climate change scenario for all S. vulgaris plants, it is possible that the highest precipitation treatment is out of the optimum range for the West cluster. Hence, the number of flowers or branches decreased with an increased precipitation of 90 mm. With the knowledge we gained from the phylogeographic analysis, it would be of interest to expose plants from the different clusters to differing climate change scenarios specified for the region they originate from. This approach could further facilitate the understanding of climate adaption in the genetic lineages of S. vulgaris. In general, we found that under most treatments, the clusters’ responses point in the same direction ; Data curation (lead); Formal analysis (lead); Investigation (lead); Methodology (lead); Visualization (lead); Writing‐original draft (lead); Writing‐review & editing (lead). Christian Kappel: Formal analysis (supporting); Visualization (supporting); Writing‐original draft (supporting); Writing‐review & editing (supporting). Jasmin Joshi: Conceptualization (supporting); Methodology (supporting); Supervision (lead); Writing‐original draft (supporting); Writing‐review & editing (supporting). Michael Lenhard: Conceptualization (supporting); Methodology (supporting); Supervision (lead); Writing‐original draft (supporting); Writing‐review & editing (supporting).Figure S1Click here for additional data file.Figure S2Click here for additional data file.Tables S1‐S2Click here for additional data file.


Candidatus Endoriftia persephone on the Juan de Fuca Ridge. Mixed symbiont populations of Ca. Endoriftia persephone were sampled across individual Ridgeia piscesae hosts from contrasting habitats in order to determine if environmental conditions rather than barriers to connectivity are more important drivers of symbiont diversity. We showed that CRISPR revealed a much higher symbiont genetic diversity than the other housekeeping genes. Several lines of evidence imply this diversity is indicative of environmental strains. Finally, we found with both CRISPR and gene markers that local symbiont populations are strongly differentiated across sites known to be isolated by deep-sea circulation patterns. This research showed the high power of CRISPR to resolve the genetic structure of uncultured bacterial populations and represents a step towards making keystone microbial species an integral part of conservation policies for upcoming mining operations on the seafloor.Many foundation species in chemosynthesis-based ecosystems rely on environmentally acquired symbiotic bacteria for their survival. Hence, understanding the biogeographic distributions of these symbionts at regional scales is key to understanding patterns of connectivity and predicting resilience of their host populations (and thus whole communities). However, such assessments are challenging because they necessitate measuring bacterial genetic diversity at fine resolutions. For this purpose, the recently discovered clustered regularly interspaced short palindromic repeats (CRISPR) constitutes a promising new genetic marker. These DNA sequences harboured by about half of bacteria hold their viral immune memory, and as such, might allow discrimination of different lineages or strains of otherwise indistinguishable bacteria. In this study, we assessed the potential of CRISPR as a hypervariable phylogenetic marker in the context of a population genetic study of an uncultured bacterial species. We used high-throughput CRISPR-based typing along with multi-locus sequence analysis (MLSA) to characterize the regional population structure of the obligate but environmentally acquired symbiont species  Raw sequences used in this paper were deposited on GenBank under the BioProject PRJNA641184. Python scripts, R scripts, and the implementation of Kupczok and Bollback [Ca. E. persephone, a keystone bacterial species, which enables high-biomass faunal communities to develop around deep-sea hydrothermal vents in the eastern Pacific Ocean. Sequences of the CRISPR array and other gene markers were obtained by high-throughput amplicon sequencing of heterogeneous assemblages of host-associated symbiont populations. The CRISPR marker revealed an unprecedented strain-level diversity for this species and its architecture accurately retraced the known symbiont phylogeny. At the local scale, the CRISPR-based population structure corroborated that of other hypervariable genes and indicated that limitations to dispersal contribute to the genetic partitioning of the free-living symbiont pools. Hence, we underscore the importance of fine-scale structure assessments for marine microbial populations and for this purpose, provide an implementation of Kupczok and Bollback’s probabilistic algorithm to estimate genetic distances between unique CRISPR arrays [CRISPR-based genotyping of bacterial strains is increasingly being used to track isolates of many human pathogens but can the CRISPR array be used for assessing the structure of natural populations of uncultured bacteria? In this study, we addressed this question by examining the local population structure of R arrays .Marine bacteria and archaea perform vital marine ecosystem functions including primary productivity at the sunlit surface, remineralization and storage of carbon in the water column and the ocean’s interior through the biological carbon pump. They are also primary producers within the ocean’s dark interior, inhabiting environments such as hydrothermal vents and hydrocarbon seeps, where they utilize geochemical energy rather than sunlight to fix carbon. Given their fundamental roles in marine ecosystems, understanding the processes that govern microbial biogeographic distributions, community assembly and ecosystem function is a primary pursuit of marine microbial ecology. To achieve this goal, we need to understand how microbial distributions are determined by the interaction of physical and biological factors. Indeed, the paradigm formulated by Baas–Becking  that ‘evet al. [Streptococcus in the span of a few years, whilst Savitskaya et al. [Escherichia coli compared with one recovered from the guts of a 42 000 year-old frozen woolly mammoth. Yet, if CRISPR can be used for fine-scale strain typing, characterizing the local structure of bacterial populations may become possible even for uncultivated bacterial species and mixed populations.Assessments of the structure of bacterial populations are limited by the resolution of genetic markers. Gene markers with high conservation and low diversity lack the resolution to reveal fine-scale population structure. Previous studies have shown the very conserved 16S rRNA gene typically used to assess bacterial diversity is not variable enough to detect genetic diversity at the population level . It is cet al.  discovera et al.  observedFine-scale strain typing would be particularly useful in conservation applications requiring knowledge of the structure and connectivity of populations of symbiotic bacteria. For example, in deep-sea chemosynthetic ecosystems such as hydrothermal vents, estimating symbiont population connectivity could inform the development of conservation strategies to mitigate the impacts of future deep-sea mining of polymetallic sulfide deposits. Estimations of macrofaunal connectivity are already an integral part of several frameworks aimed at assessing the resilience of proposed mining sites and developing preservation areas . AssessmCandidatus Endoriftia persephone [de novo from the surrounding environment at each generation [One such environment exists in the eastern Pacific Ocean, where hydrothermal vent communities are dominated by various species of gutless siboglinid polychaetes whose dense aggregations create niches for other faunal species. These tubeworms all rely on a single species of uncultured chemolithoautotrophic Gammaproteobacteria coined rsephone  for theineration  by youngCa. E. persephone showed the symbionts associated with the species of the East Pacific Rise  at tropical latitudes, and those associated with worms of the Juan de Fuca Ridge  in the northeast Pacific, belong to two vicariant populations [in situ hybridization of colonization blocks (deployed for 1 year) [Ca. E. persephone are most abundant in close proximity to host aggregations and almost undetectable away from zones of hydrothermal activity. Taken together, these observations suggest the genetic diversity of the symbionts is spatially structured and can be uncovered from host-associated populations with a suitable hypervariable genetic marker.Genetic studies investigating the phylogeography of ulations . At diffulations , have coulations , potentiulations  and fluo 1 year)  revealedCa. E. persephone. To address this objective, we used CRISPR along with four other gene markers to characterize the structure of Ca. E. persephone populations along the Juan de Fuca Ridge, where the symbiont species is associated with the host tubeworm species Ridgeia piscesae. Doing so, we assessed if the physicochemical conditions of the worm habitat contributed to symbiont population structure, and the extent to which the populations along the Juan de Fuca Ridge were connected.The goal of this study was therefore to evaluate the CRISPR sequence as an appropriate genetic marker for distinguishing multiple environmental strains of the uncultured vestimentiferan symbiont Ca. E. persephone were sampled from their R. piscesae hosts in three active hydrothermal venting regions separated by increasing N-S distances along the Juan de Fuca Ridge: Main Endeavour Field (MEF), Clam-Bed (CB) and Middle Valley (MV). Within each region we sampled contrasting habitats, which were identified from the morphotypic appearance of the individual R. piscesae hosts, which exhibit environmentally driven phenotypic plasticity [Populations of environmentally acquired asticity   from research vessels. The first, on board the R/V Thomas G. Thompson, used the ROV Oceaneering Millennium, whilst the second, on the CCGS John P. Tully, used the ROV ROPOS (Table S1). Worms collected in 2013 were processed upon recovery to the surface vessel, whereas those collected in 2016 were individually packed, frozen at −80 °C and later dissected in the laboratory. The individual worms were carefully removed from their tubes and treated with lysozyme and DNAse according to Elsaied and Nagamura  to removCa. E. persephone was the only symbiont species within R. piscesae, we amplified and sequenced the hypervariable region V4 of the bacterial 16 s rRNA gene using universal primers. To assess the intra-specific genetic diversity of the symbionts we amplified and sequenced a complete CRISPR array previously found on the scaffold KQ557120 (48 218.48978) (start-end positions) in the assembly ‘Ridgeia 1 symbionts’ (GenBank accession LDXT01). Additionally, we performed a multi-locus sequence analysis (MLSA) by sequencing three additional protein-coding genomic regions. Rather than using genes typically employed in MLSA analyses  category, have multiple SNPs within 600 bp of each other but no indels. Six genes fitted these criteria but only three were successfully amplified: lpxA, pleD and tufB.To confirm that EL, atpD ), we selEL, atpD . CandidalpxA, pleD and tufB) were then sent to Génome Québec for sequencing on the Illumina MiSeq 2500 platform (1 % of a lane), and 41 libraries for the CRISPR PCR products were sequenced on one PacBio SMRT cell.Libraries were prepared according to Génome Québec guidelines. A first PCR was performed to amplify the genomic regions of interest. We used gene-specific primers that carried the CS1 and CS2 universal overhangs. These extra 22 bp sequences allowed for the attachment of sample-specific barcodes during a second PCR round. Primer sequences and PCR conditions are presented in Table S2. Ultimately, 35 libraries of pooled barcoded amplicons (one barcode per sample) for the polymorphic gene fragments  yielded between 1385 and 3199 reads per sample. Of these, 70 % were concordantly mapped to the reference genome. In order to isolate the amplicons of different loci, the paired-end reads were mapped onto the reference genome using bowtie2 v2.3.2 [Sequencing of the four pooled gene amplicons . For the other housekeeping genes , polymorphic positions across all mapped reads were initially detected with VarScan v2.3.9 using the following parameters: --min-coverage 100 --min-reads2 10 --min-avg-qual 25 --min-var-freq 0.01 [Ca. E. persephone associated with tubeworms of the East Pacific Rise [tufB amplicon, which failed to amplify, the final minimum coverage on the gene markers reached 94X For the hypervariable region V4 of the bacterial 16 s rRNA gene, we extracted both the reads that mapped to the 16S rRNA gene and those that did not map to the reference at all. These sequences were then together processed with the software package Divisive Amplicon Denoising Algorithm 2 (DADA2 v1.17.0)  in R, acreq 0.01 . All SNPfic Rise . Then, efic Rise  using 3′fic Rise . FinallyA total of 35 840 high-quality PacBio reads from CRISPR amplicons were generated through circular consensus sequencing (CCS). Initial attempts at direct spacer detection in the CCS reads using two available methods designed for Illumina reads, Crass v0.3.12  and Meta. a maximum of 5 nucleotide mismatches) between the spacer sequence and the read were tolerated to account for sequencing errors and mutations. We discarded from further analysis dubious reads, which were missing at least one of the primer sequences, were less than 33 bp (the approximate size of a single spacer), or whose mapped seed spacers did not all have the same orientation or were properly ordered. Discarded reads represented 59–70 %  of the CCS libraries and most (>90 %) were excluded because of missing primer sequences. To assess whether additional spacers  were present in the samples, we flagged all reads for which mapped seed spacers were not regularly interspaced , as putatively containing new spacers. The sequences of these putative new spacers including their bordering repeats were extracted to a new fastq file and processed with Crass v0.3.12 using the same parameters as for the initial seed spacer search [First, we established read-length distributions for each sample. A small subset of reads representative of the most abundant size classes was then extracted and a set of seed spacers were identified with Crass v0.3.12  using alr search . Only thWe estimated the genetic distance between pairs of CRISPR haplotypes by implementing the probabilistic algorithm described by Kupczok and Bollback  for estiAnalyses of population structure were performed for the CRISPR array and each gene amplicon independently in R using the package ‘Proppr’ v2.8.6 . Each repoppr.msn. The function first computes a minimum spanning tree from a graph representation of an adjacency matrix  and then adds population parameters as attributes to this tree.Minimum-spanning trees based on the previously estimated genetic distances between CRISPR haplotypes were constructed using the function poppr.amova, which uses the amova function from the ‘ade4’ package [ade4:randtest) was used to assess the statistical significance of the various covariance components . To assess the concordance of the symbiont population structures according to the CRISPR array and each of the other gene fragments, we performed Mantel tests on their respective matrices of pairwise population differentiation. For the gene amplicons, the FST index computed in Arlequin v3.5 [FST values were treated as 0 (function mantel.test from the ‘ape’ R package) or removed from the correlation coefficient computation (function mantel from the ‘vegan’ R package).Hierarchical AMOVAs  were per package . The foluin v3.5  was usedThe sequencing of the 16S rRNA gene- V4 amplicon yielded 8571 paired-end reads in total. The average per-sample coverage was 226X but there were important disparities across samples . Using tR. piscesae. Although great precaution was taken to reduce contamination, it is unclear given their low abundance and considerable divergence to the dominant endosymbiont phylotype if these alternative rare taxa are truly from host-associated bacteria. Regardless, these observations support the hypothesis that host-symbiont molecular interactions and microbial competition prevent the infection and intra-host proliferation of excessively divergent phylotypes [We identified four bacterial phylotypes with a minimum nucleotide identity of 81 % between V4_1 and V4_4 . The phyylotypes .Ca. E. persephone.With 123 distinct CRISPR arrays detected, the hypervariable CRISPR region revealed a much higher symbiont genetic diversity than the 16S marker. Between 3 and 32 (median=11) distinct CRISPR haplotypes were found in each individual host. The majority of these haplotypes were in very low abundance; two thirds or more of the haplotypes were represented in fewer than 5 % of the reads. Nonetheless, rare haplotypes could not be identified as somatic variants (i.e. strains resulting from within-host mutations). Indeed, examination of a minimum spanning tree showed most CRISPR haplotypes were shared amongst host worms . FurtherExamining the structure of all the CRISPR arrays recovered from the Juan de Fuca Ridge tubeworms, we found that the genetic diversity amongst the symbiont haplotypes is defined by various spacer deletions from the longest array. The longest array thus represents the most ancestral state amongst the CRISPR arrays we sampled .E. coli, Salmonella and Klebsiella species [R. pachyptila the CRISPR-cas operon of Ca. E. persephone does not seem to be expressed within the trophosome [Ca. E. persephone the maintenance of the structural integrity of the arrays suggests the CRISPR/cas system may not be completely defunct and could hold instead an alternative function, notably during the free-living stage of the symbionts. Indeed, CRISPR/cas systems in free-living Ca. E. persephone may be involved in a number of physiological responses to environmental stress [Surprisingly, we observed no new spacers at the array’s leading end where insertions would be indicative of recent viral infections. Other known examples of deletion-driven CRISPR polymorphism are found in  species . It is p species . Furtherophosome . Yet, inl stress  and proml stress .purT gene, we are confident they are DNA fragments of Ca. E. persephone. The oldest identified spacer (spacer 295) in our dataset was also present in contigs from three metagenomes of bacterial communities sampled from the surface of three species of polychaete worms from the East Pacific Rise: T. jerichonana, R. pachyptila and Alvinella pompejana. Hence, spacer 295, the most ancient spacer in the array was most likely acquired before the vicariance of the Juan de Fuca Ridge and East Pacific Rise symbiont populations, following separation of the two ridges by the fragmentation of the Farallon plate about 30 million years ago [We then assessed if any of the 15 identified spacers had previously been sequenced by blasting them against JGI’s IMG-MER database. Three spacers found a match in contigs from other bacterial genomes and metagenomes. Because these contigs possessed the conserved end of the CRISPR array up to the ears ago .Tevnia- and Riftia-associated symbionts [Given the presence of spacer 295 in many samples from the East Pacific Rise, it is surprising this spacer was not found in the reference genomes of ymbionts . We suspR. piscesae host [The next two most ancient spacers (spacers 58 and 55) were both detected in a contig from a metagenome of diffuse hydrothermal fluids at Axial Seamount, a shallower site on the Juan de Fuca Ridge located about 200 km south of the Main Endeavour field. None of the other spacers inserted at the leader end of the arrays were shared between Axial Seamount and the northern Juan de Fuca Ridge populations, suggesting a lack of connectivity between these populations which is supported by genetic analyses of their sae host . TogethelpxA, pleD and tufB . These genes were specifically chosen because they exhibited polymorphism in metagenomic data [tufB was characterized by two pairs of haplotypes in similar proportions, which we suspect results from sequencing two recombining paralogous sequences [lpxA and pleD) and the CRISPR array were used to compute matrices of population differentiation based on pairwise F-statistics. Mantel tests  confirmed the haplotypes across lpxA and pleD markers exhibit a significant degree of covariation and revealed strong concordance to the symbiont population structure uncovered with CRISPR.Three additional housekeeping gene fragments were amplified from the same individual hosts examined for CRISPR; mic data  but onlyequences ; the secCRISPR-based inferences are presented here and corroborating AMOVA results for the other gene amplicons are provided in the Supplementary Material. Within the Main Endeavour Field (MEF) region, two independent tubeworm aggregations for each of the high- and low-flow environmental conditions were sampled to discriminate between habitat and aggregation-specific variation . FurtherSignificant variation in the composition of the symbiont strain assemblages was found across the length of the trophosome with the gene markers but not with CRISPR, the marker displaying a greater allelic diversity. This indicates that small contrasts in the symbiont composition along the length of the trophosome are likely exacerbated when genetic resolution is low and probably result from the random distribution of the different symbiont strains in the trophosome. In other words, even though the different symbiont strains may not be homogeneously distributed within the host housing organ, they are not partitioned in a specific way along its antero-posterior axis.AMOVA analyses within MEF revealed that individual worms from the same aggregation could host markedly different strains; between-hosts variance accounted for nearly 25 % of the total variation . This diCa. E. persephone were uniquely sustained in high abundance amongst the free-living population at this site. However, our fine-scale genetic survey revealed that while the symbiont populations were structured at the scale of a vent field, this structure was not driven by differences between habitats.At Clam-Bed (CB), the allelic composition of symbionts from the high-flow and basalt-hosted worm populations was markedly different  and could be the result of larger differences in age between the two tubeworm populations. The basalt-hosted worms at this site are known to be at least several decades old , and cloIndeed, broad environmental conditions associated with the concentration of hydrothermal discharge in the worms’ habitat generally did not significantly explain the variation observed in the data even when controlling for regional variation or excluding the highly homogeneous Middle Valley sites .Variance in the symbiont strain diversity appears to reflect general patterns of connectivity along the Juan de Fuca Ridge rather than environmental selection. Regional differences between Middle Valley and the two Endeavour sites (CB and MEF) accounted for most of the regional variance 67 %,  whereas et al. [Our results interpreted alongside those of the host populations suggest that both host larvae and symbiont cell dispersal depend on patterns of deep-sea circulation that restrict connectivity across disjointed axial rift valleys but maintain it within them. Young et al.  and Puetet al.  found a et al. , were diet al.  showed hlpxA and pleD) (R. piscesae recruitment in Middle Valley is dependent on this symbiont strain or if robust host populations must be present to seed and maintain the symbiont populations, these worms and the associated communities that depend on them could be extremely vulnerable to disturbance from mining activities. Hence, our results highlight the fundamental importance of better understanding the diversity and connectivity of natural populations of obligate microbial symbionts. As the International Seabed Authority is drafting the first regulations for hydrothermal vent mining, we argue that it is imperative for such keystone bacterial species to be taken into account within conservation schemes.It is noteworthy that in addition to their apparent isolation, symbiont populations from Middle Valley exhibited a surprisingly low diversity. All host individuals in this region were associated with a single symbiont strain identified by all three of the suitable hypervariable markers (CRISPR, Ca. E. persephone. In our study, the CRISPR array retraced the known symbiont phylogeny over millions of years but also allowed for discrimination amongst very closely related lineages. The CRISPR haplotypes we identified only varied through spacer deletions and yet they revealed 30 times more diversity than any of the other gene markers specifically selected for their polymorphism. Furthermore, unlike MLSA methods, which require multiple gene primers and may be biassed by paralogous sequences and homologous recombination if the gene markers are not carefully chosen, working with CRISPR requires a single set of primers, the orthology of the marker can be guaranteed through genomic context, and while homologous recombination within CRISPR has been observed, it appears to be extremely rare [Characterizing and comparing natural heterogeneous bacterial populations at the strain level is challenging. We have demonstrated that the CRISPR array is a genetic marker fit-for-purpose for the uncultured chemoautrophic symbiont species ely rare . As an aNonetheless, there are a number of limitations to the use of CRISPR for DNA barcoding. First, not all prokaryote species possess the marker. The CRISPR-cas immunity is only present in about half of bacteria  and the Click here for additional data file.


Araucaria araucana is an emblematic conifer species from southern South America, with important ethnic value for the Mapuche people (Pehuenche); the Chilean Government has catalogued its conservation status as vulnerable. Climatic fluctuations were potentially a major impact in the genetic variation within many tree species. In this context, the restricted geographic distribution of A. araucana in Chile appears to be a consequence of the Last Glacial Maximum (LGM). During the past two centuries, strong human intervention has also affected the geographical distribution and population sizes of A. araucana. Reduction of population size may cause loss of genetic diversity, which could affect frequency of adaptive loci. The aims of this study were to know the existence of potential loci under selection and populations with genetic, demographic disequilibrium in the Chilean distribution of A. araucana. Based on 268 polymorphic AFLP loci, we have investigated potential loci under selection and genetic, demographic disequilibrium within seven Chilean populations of Araucaria araucana. Correlation of 41 outlier loci with the environmental variables of precipitation and temperature reveals signatures of selection, whereas 227 neutral loci provide estimates of demographic equilibrium and genetic population structure. Three populations are recommended as priorities for conservation.Loss of genetic diversity reduces the ability of species to evolve and respond to environmental change.  Molecular data have helped to identify the effects that natural history traits, phylogeographic history, and environmental factors have had on the population genetic structure of plants4. Climatic parameters are key to determining the distribution of plant species5, especially in the current context of climate change7.Genetic structure within and among populations is modeled by the interaction of genetic drift, gene flow, mutation, and natural selection8, resulting in historical demographic events such as population contractions or expansions9.In fact, the present geographical distribution and genetic variation within and among populations of tree species may have been a consequence of climate fluctuations during the Quaternary10. Using paleobotanical information and geomorphic evidence, the existence of plant refugia in Europe as well as in North and South America during the Quaternary has been proposed11. These refugia would have been areas that remained as patches free of ice12, and recolonization of glaciated areas would have occurred from refugia after glacial retreat13, as demonstrated in conifers in the Northern Hemisphere during Quaternary LGM14. Inferences from the fossil record during the LGM in Chile, in the high elevation forests of the Coastal and Andean ranges, suggest discontinuous plant distributions for species such as Fitzroya cupressoides, Austrocedrus chilensis and Araucaria araucana15. For this latter species, the LGM would likely have modified not only its geographical distribution but also number and sizes of populations17, which might be reflected in current patterns of genetic variation22. Three groups of structured Chilean populations of Araucaria araucana, based on isozymes, have been shown to be congruent with the glacial refugia hypothesis19. Fragmented populations of the species in Argentina, based on five haplotypes of non-coding chloroplast DNA, show low genetic differentiation and structure22.The Last Glacial Maximum (LGM) modified the geographical distribution of many plant species because of ice advancing on both hemispheresA. araucana from both neutral and adaptive loci. Neutral loci, e.g. from RAPDs, cannot detect adaptive genetic divergence across the Andean Ranges. Adaptive variability can be estimated using outlier loci that show signals of selection25, such as in relation to drought tolerance, which would be important for conservation18. Potential loci under selection (outlier loci) are portions of the genome that show different patterns of variation from those of neutral loci and can be identified through statistical methods31. Statistical correlation between the presence of outlier loci and environmental parameters allows assessment of environmental factors driving selection36. Therefore, it is possible not only to identify potential loci under selection but also to correlate these loci with environmental parameters, which vary greatly within the geographical distribution  of Araucaria araucana.Genetic diversity studies with different markers have allowed estimation of genetic diversity in Araucaria araucana displays a disjointed geographical distribution , being found in the Andes between 37°24′S and 40°03′S, and in the Coastal range only in two small locations, between 37°30′S and 38°S and about 38°30′. The Longitudinal Chilean Valley (Intermediate Depression) separates the Coastal and Andean ranges .As a result of unsustainable management during the past two centuriesAraucaria araucana. In the Southern Hemisphere, it has been proposed that the LGM took place ca. 20.000 years bp, termed Llanquihue III45. This last glacial period not only caused important climatic changes, such as decrease in maximum temperature and rainfall patterns, but it also would have affected plant distributions15. Araucaria araucana populations appear to have been disturbed in the LGM , not only in their geographical distribution46, but also in their genetic patterns22. During this period, important climatic variations occurred that influenced the distribution of flora in the South-Central areas of Chile47. However, based on geomorphological and palynological evidence, some places in both the Coastal and Andean regions have been proposed as glacial refugia48. The consequences of climate change during the Quaternary have been evaluated in several species, and the existence of multiple refugia in the temperate forests of Southern Chile and marginal zones with Argentina has been hypothesized. An example is Fitzroya cupressoides (Cupressaceae), which has been studied using isozyme49 and RAPD markers11. These studies concluded that multiple refugia existed during the LGM north of Patagonia. In Araucaria araucana the existence of glacial refugia has also been proposed because of evidence gathered from RAPD markers18 and allozyme studies19.Multiple glacial events have historically impacted habitats of A. araucana50, and considering environmental and geographical differences in the distributions where this species grows, different genetic diversity patterns might be expected between populations in Coastal and Andean ranges. This information is important for conservation strategies24. In this context, we hypothesize that distributions of outlier loci in Araucaria araucana, might be correlated with environmental factors, such as temperature and humidity, which are known to have high impact on distributions of plant species35. On the other hand, because of climatic changes caused by glaciation, it might be expected to find populations in recolonized areas due to expansion from populations acting as refugia52. This is an important aspect to consider in these populations because they might have been more susceptible to loss of alleles56, including outlier loci with adaptative significance. Based on this background information, amplified fragment length polymorphism (AFLP) markers were employed for the following objectives: (1) to detect potential loci under selection, (2) to correlate loci under selection with climatic parameters, and (3) to assess if existing populations of A. araucana are in genetic demographic disequilibrium.Taking into account the available information on genetic variation in p < 0.05 and p < 0.01). A list of outlier loci is available in Supplementary Table Fst values than expected under neutrality , 25 loci were distributed at lower Fst values than expected under neutrality . Correlation among Fst and He values of loci is available in Supplementary Fig. http://www.cru.uea.ac.uk/ and http://badc.nerc.ac.uk/data/cru/)57. The selected variables were correlated with outlier loci. From the 41 outlier loci, 6 of them  showed significant correlation with precipitation ; each fragment represents an AFLP locus , validating the model used for structure analyses. Figure The reduced data matrix with 227 loci, by excluding outlier loci, was employed for estimating genetic groups and population structure (AMOVA). From the resulting data it was determined that three is the most probable number of genetically homogeneous groups , with .79%, witFs test58 proved to be consistent with those of mismatch distribution analysis, showing P values near to 0.02, for demographic expansion in the two sites, which displayed unimodal distributions  shows that the distribution of frequencies of the number of differences between pairs of haplotypes was unimodal in two localities VLA and PNC and multimodal distribution was found in the remaining localities 37. Lara et al.59, established that only 52% of the native Araucaria araucana forest that existed prior to the colonization by Europeans is still present, accounting for 261,073 hectares, 47% of which are currently protected by the Chilean Government60. In this context, important results have been obtained from several studies that have estimated genetic distribution patterns for conservation purposes50. However, two aspects are important to consider in population/species conservation: loss of haplotypes of loci under selection61, and current genetic demographic equilibrium62.The current distribution of The results from the present work show the existence of loci under selection that are correlated with climatic variables of temperature and precipitation. On the other hand, some localities are revealed to be in genetic demographic disequilibrium. These two aspects have high relevance for making decisions on the establishment of protected areas for this species.23 and that allow species to adapt to environmental changes26. Habitat reduction and population size reduction are important factors in the loss of diversity, with loci under selection, generally being haplotypes or alleles in low frequency, within a population24. Identification of loci under selection within a population, therefore, becomes an important criterion for development of conservation strategies63. Considering that environmental parameters are key in determining plant distributions64, the correlation between genetic and environmental parameters is also relevant for conservation. In this context, 32 outlier loci were shared in both geographic distributional ranges of Araucaria araucana. Five outlier loci  were found only in the Andean range and four  were found in the Coastal range. For Araucaria araucana, locus 53 was correlated with the temperature variable (BIO2). Temperature has been recognized as an important factor in selection, responsible for population differentiation on altitudinal and latitudinal clines4. Within the Andean distribution, temperatures range from −5 °C to −10 °C in the winter to 30 °C in the summer. On Nahuelbuta Mountain (PNN), the range of temperature variation is lower than that in the Andes Mountains, from −1 °C in the winter to 9 °C in the summer .Loci under selection can be defined as those portions of the genome that are under selective pressures43. The second source of differentiation relates to marked differences in precipitation within the Andes. On the westernmost areas, precipitation varies between 2000 to 4500 mm, however, on higher altitude (Eastern areas) near the limit with Argentina, the annual rainfall average is 1000 to 1900 mm 66, and snow is more prevalent than rain. Differences in environmental variables found in the coastal range are less pronounced than in the Andean range, potentially favoring the selection of alleles correlated with such environmental traits as has been hypothesized in the mountain rainy neotropical forest17. In the Andes, local adaptation to specific different climatic conditions favors a higher degree of structure among the different sites within this range , possibly related to two sources of differentiation. The first is variation in precipitation registered between the Andean and Coastal ranges. For the Andes an annual rainfall between 1000 and 4500 mm is observed, depending on altitude. On Nahuelbuta Mountain, rainfall ranges from 1300 to 3000 mm annually67. Correlation of outlier loci or adaptive loci with temperature has been demonstrated in conifer species under conditions of global climate change68.Outlier loci could be important for adaptation to local environmental conditions, which are highly variable between geographical ranges. Our results showed five outlier loci  distributed only in the Andean range , Group 2 includes localities from both Andean and Coastal ranges , and Group 3 contains only Andean populations . These results are consistent with the existence of multiple glacial refuges within the Andean Range. This hypothesis is in accordance with those of other studies on different animal and plant species, in which the existence of multiple refugia in the Andes has been postulated71. In addition, two of the evaluated localities are in demographic disequilibrium (expansion), and one of them comprises a unique genetic group (PNC). The grouping of some Andean and Coastal populations of A. araucana in the same genetic set, based on neutral genes, seems not very logical. However, the above could be explained by referring to probable distributional dynamics associated with glacial periods, which historically would have allowed gene flow between populations of both mountain ranges. During glacial periods, highland vegetation would have colonized the lower areas of the Intermediate Depression, bringing together populations from the Andes and the Coast. For example, according to this, for certain lineages of the lizard Liolaemus pictus, closely associated with Nothofagus and Araucaria forests, there is phylogeographic evidence of the absence of reciprocal monophyly between currently disjunct populations in both mountain ranges, which suggests that historically they would have experienced Andes-Costa gene exchange72. The results of selection signals, and the distribution of neutral genetic variation within and among Coastal and Andean populations (Group 2), strengthen the need for conservation strategies within the species.The detection of loci correlated with different environmental conditions, usually found in low frequencies, is important for confronting rapid changes in climatic conditions58 values for these sites are the lowest and probably in demographic disequilibrium (Table 22.The distribution of frequencies of differences between haplotype pairs (mismatch) for two sampled sites, Araucaria Village and Conguillio National Park, was unimodal , which was declared “Patrimonio Nacional” by the Chilean government in 2020 (http://patrimonio.bienes.cl/patrimonio/villa-las-araucarias/), and their individuals have been declared an endangered species by the Government of Chile. This population has experienced a demographic expansion (demographic disequilibrium) that affected the allele frequence patterns. This site is the lowest altitude within the range of distribution of the species, which could have important adaptive consequences due to outlier loci present only in the Coastal range (Nahuelbuta Mountain and Villa Las Araucarias). This would be important in terms of global climate change, as well as conservation priorities, because this site could be regarded as a “genetic sink” for adaptation within the range of the species. Furthermore, high levels of genetic diversity have been documented for this area, compared to other sites19. Araucaria Village is in a non-protected area and hence completely exposed to human intervention, which could lead to serious negative factors for reproductive dynamics of this species, resulting in loss of loci with adaptive value.Based on these results, there are three important geographical areas of 19. This site exhibits an important difference between the effective population size before and after the beginning of the expansion (Ѳ0–Ѳ1), suggesting the occurrence of a genetic bottleneck, as reported by Martin et al.22, which has been corroborated by previously documented low levels of genetic variation19. Such genetic particularity is relevant, considering that outlier loci (probably under selection) were documented for this locality in the present research.Second, Cañicú (CAÑ) is another important geographical area, the northernmost distribution for this species, and which presents the lowest genetic diversity indicesAraucaria Forest because of demographic characteristics that make this area susceptible to climate change73.Third, another important area is Conguillio National Park (PNC), due to genetic differences found in this area that constitute a different genetic group also in demographic disequilibrium. Although some of this area is under protection , it may be necessary for conservation purposes to increase the size of the reserve in this zone of 22  for allowing removal of leaf samples from Araucaria araucana22 and considering that this species is catalogued as vulnerable42, only some of the existing localities were considered in this study. The localities were selected based on the following criteria: first, both Coastal and Andean distributional ranges are highly structured, with different patterns of genetic diversity22. Due to very different environmental conditions between both distributional ranges, adaptative variation could be postulated between Coastal and Andean populations24, and the Coastal range has been postulated as having harbored glacial refugia48.Based on previous results of genetic structure in A. araucana grows were selected, Villa Las Araucarias (unprotected area) and Nahuelbuta Mountain, specifically Nahuelbuta National Park (a protected area). Different patterns of genetic diversity have been postulated for these sites. Villa las Araucaria is located in the southernmost border of the coastal distributional range and Nahuelbuta Mountain is in the center of the Coastal distribution of this species45. Villa Las Araucarias showed lower genetic diversity and higher genetic structure than Nahuelbuta Mountain74.Second, in the Coastal range, the unique two places where 48 and have been postulated as glacial refugia for some tree species . Westernmost Andean localities as Conguillio National Park and Malalcahuello could have been recolonized from these refugial areas22. Different patterns of genetic diversity have been documented between glacial refugia and recolonized areas with the former exhibiting higher genetic diversity than the latter75. Information about outlier loci from different sites with different genetic patterns is listed in Table Third, some areas of distribution in the Andes were free of ice during the LGM, specifically, the northernmost Andean distribution and Galletué-Icalma ValleyA. araucana were obtained from 119 trees from seven sites in the Chilean distributional range, five sites within the Andean distributional range, and two sites within the Coastal range  and another is an unprotected site (Villa Las Araucarias). In the Andean range one site included a protected site  and four are unprotected sites, two of them having been proposed as ice-free sites during the LGM 77 and supported by genetic evidence19.Young leaves of ge Table ; Fig. 1.78 with some modifications79. Before extraction, pulverized leaves obtained by grinding the tissue with liquid nitrogen were suspended in HEPES buffer and centrifuged at 10,000 rpm for 5 min. Extracted DNA was treated with RNase at 37 °C for 30 min. The quality of the extracted DNA was assessed by running an aliquot on a 1% agarose gel. DNA concentration was quantified by UV spectrophotometry  and samples were stored at −20 °C until needed.Total DNA was extracted following the CTAB method80, which consists of three steps. First, digestion-ligation of 0.5 µg genomic DNA was carried out using EcoRI and MseI at 37 °C for 2 h. Adaptors were ligated to the ends of each digested DNA fragment (EcoRI and MseI adaptors). Second, a preselective PCR was performed using primers complementary to the adaptors plus one selective base . Third, the final (selective) PCR with primers containing three selective bases (EcoRI + 3 and MseI + 3) was performed using the preselective PCR product as template (diluted 1:10 in 1xTE buffer). Sixteen combinations of selective primers were tested, from which EcoRI-ACT/MseI-CAG and EcoRI-ACC/MseI-CTG were selected because they resulted in the clearest and most reproducible amplification patterns. Both amplification reactions were performed in an Eppendorf Master Cycler Gradient thermalcycler. PCR fragments from the selective step were sized on an Applied Biosystems Prism 310 sequencer with an internal standard and analyzed on GeneScan 2.1 (Applied Biosystems). Results were then imported to Genographer . Each AFLP fragment was coded as either present = 1 or absent = 0 in all samples, yielding a binary data matrix. All AFLP experiments were done in the Department of Botany and Biodiversity Research, University of Vienna, Vienna, Austria.AFLP was performed according to protocol described by81. Outlier loci with higher or lower FST values than under neutral expectations, and which fell outside 95% confidence levels, were assumed to be under directional or balancing selection.Identification of potential loci under selection and their frequencies was performed using Arlequin 3.5.257. To select environmental variables with less correlation with each other, a Principal Component Analysis (PCA) was carried out. The PCA and the standardization of the data were performed in R, versión 4.0.282. Using the “prcomp” function. The variables selected from the PCA analysis  were correlated with the allele frequencies in each of the loci under selection and tests with Pearson’s or Spearman’s correlation coefficient depending on whether the data were or not normally distributed. Analysis was performed in R, version 4.0.2 using the Rcomdr package82  between 2 and 8, were done  package for R-project was then used to test the null autocorrelation of Gibbs chains85. Bayesian credible intervals (95%) for Fst values were calculated.After removal of outlier loci from the original data matrix, analyses of genetic structure were made with STRUCTURE 2.3.381. These included: (1) the number of generations since expansion (τ), (2) pre-expansion population size (θ0), and (3) post-expansion population size (θ1)86. Additionally, selective neutrality using Fu’s Fs statistic58, which is sensitive to signals of population expansion, was tested.Demographic parameters were estimated from a Mismatch Distribution analysis using the program Arlequin 3.59 state that the current genetic structure and variability of many species has been defined by historical demographic events such as population retractions or expansions, deriving from climatic changes or bottlenecks. From studies of genetic variation in natural populations, tools have been developed, such as the analysis of distributional frequencies of paired differences of haplotypes (Mismatch Distribution)87, which allow detection of historical population variations that may have been a consequence of events such as glaciations88. This analysis allows the construction of a histogram, where multimodal-type distributions represent populations that have not undergone changes in their population sizes, which has been considered demographic equilibrium. Unimodal-type distributions are typical of populations that have recently experienced variations in their size or genetic demographic disequilibrium87.Storz and BeaumontSupplementary Information.


African pangolins are currently experiencing unprecedented levels of harvesting, feeding both local demands and the illegal international trade. So far, the lack of knowledge on the population genetics of African pangolins has hampered any attempts at assessing their demographic status and tracing their trade at the local scale. We conducted a pioneer study on the genetic tracing of the African pangolin trade in the Dahomey Gap (DG). We sequenced and genotyped 189 white-bellied pangolins from 18 forests and 12 wildlife markets using one mitochondrial fragment and 20 microsatellite loci.Tree-based assignment procedure showed that the pangolin trade is endemic to the DG region, as it was strictly fed by the the Dahomey Gap lineage (DGL). DGL populations were characterized by low levels of genetic diversity, an overall absence of equilibrium, important inbreeding levels, and lack of geographic structure. We identified a 92–98% decline in DGL effective population size 200–500 ya—concomitant with major political transformations along the ‘Slave Coast’—leading to contemporaneous estimates being inferior to minimum viable population size (< 500). Genetic tracing suggested that wildlife markets from the DG sourced pangolins through the entire DGL range. Our loci provided the necessary power to distinguish among all the genotyped pangolins, tracing the dispatch of a same individual on the markets and within local communities. We developed an approach combining rarefaction analysis of private allele frequencies with cross-validation of observed data that traced five traded pangolins to their forest origin, c. 200–300 km away from the markets.Although the genetic toolkit that we designed from traditional markers can prove helpful to trace the illegal trade in pangolins, our tracing ability was limited by the lack of population structure within the DGL. Given the deleterious combination of genetic, demographic, and trade-related factors affecting DGL populations, the conservation status of white-bellied pangolins in the DG should be urgently re-evaluated.The online version contains supplementary material available at 10.1186/s12862-022-01971-5. Pangolins (Order Pholidota) are considered the most trafficked wild mammals in the world, with c. 900,000 individuals seized over the last 20 years . AlthougPhataginus tricuspis) is the species with the largest range in tropical Africa and is the pangolin most frequently sold in the African bushmeat markets [The white-bellied pangolin  and lik markets , 12.DGL populations currently suffer from intense levels of deforestation and hunting. Populations are fragmented into generally small patches of forest islands, and have drastically decreased in abundance through the last decades , 12. In The genetic toolkit has been successfully applied to trace the illegal wildlife trade, by providing accurate information on the species traded and their geographic origins , 15. RecWe collected a total of 189 WBP samples across Benin 6° 10′–11° 00′ N), Togo (8° 10–9° 0′) and southwestern Nigeria (6° 10′–11° 00′ N). Our sampling effort included all of the species occurrence zones in Benin ° 00′ N, . Free coDNA extraction from fresh and scale connective tissues was performed using the NucleoSpin® Tissue Kit , following manufacturer’s recommendations. The final elution step was repeated twice in 50 µl Elution buffer to increase DNA yield. The samples treated with chemicals were extracted following a modified CTAB protocole including upstream TE washing baths and Dithiothreitol (DTT ). Elutiohttps://www.genoscreen.fr/en; Lille, France) and Macrogen Europe . Sequences were aligned manually with BioEdit v7.0.5 [We amplified a mitochondrial fragment of 432 bp from Control Region 1 (CR1) following Gaubert et al. . PCR prot v7.0.5  and the https://get.genotoul.fr/; INRAE, Toulouse, France).We amplified 20 microsatellite markers developed from the genome of WBP in four multiplexes following Aguillon et al. . PCR triWe assessed the ‘endemicity’ of the pangolins from Togo, Benin and Nigeria (N = 168) through a distance-tree analysis including all the CR1 sequences of WBP available in Genbank (N = 100). All the sequences were aligned by-eye with BioEdit v7.0.5 . Phylogeh), haplotype diversity (Hd) and nucleotide diversity (π) . We used DnaSP v6.12  to compu6. We useMismatch analysis was performed in Arlequin 3.5.2  to test r [We also tested for deviation from neutrality by computing a series of statistics in DnaSP, including Tajima’s D , Fu’s Fsr  and Ramor . We ran r , to calchttps://www.geneious.com/features/microsatellite-genotyping/). Only the DGL individuals with at least 75% of genotyping success were considered for the analyses (N = 169). This arbitrary threshold coincides with ≥ 15 microsatellite markers, tripling the minimum number of loci needed to discriminate among individuals in the white-bellied pangolin lineage from western central Africa [Ho) and expected (He) heterozysity as computed from GenAlEx 6.5 [R) and FIS as estimated from FSTAT 2.9.4 [Genious 9.0.5  was usedl Africa . GeneticAlEx 6.5 , (ii) alAT 2.9.4 . DeviatiAT 2.9.4  using a Global genetic variance within the DGL was visualized through a Principal Coordinates Analysis (PCoA), using pairwise population matrix unbiased genetic distances in GenAlEx.FST) among forest populations (N = 104) was computed in Arlequin 3.5 [FIS) in FSTAT.Pairwise differentiation (quin 3.5  using th5 Markov chain Monte Carlo (MCMC) iterations and burnin = 104, assuming admixture model and correlated allele frequencies. STRUCTURE HARVESTER 0.6.94 [We used STRUCTURE 2.3.4  to conduR 0.6.94  was usedR 0.6.94 . We alsoR 0.6.94 .Geneland package [R Team Development Core 2021). Following Coulon et al. (2006), we first allowed K to vary from 1 to 10 and launched five runs of 5 × 105 MCMC iterations (500 thinning and 500 burn-in) under a frequence-correlated model and 1 km of uncertainty for spatial coordinates. Second, we fixed the number of estimated populations on the basis of the first analysis (K = 6–7), to perform 20 independant runs using the same parameters. We also performed 20 independent runs fixing K = 3 as obtained from STRUCTURE  between genetic (Edward’s) and geographic (Euclidean) distances through 10,000 permutations. The geographic distances among populations were calculated from the center of each forest.We tested isolation-by-distance (IBD) among (i) forest individuals and (ii) populations  by running a Mantel test in the R package pegas , where wpoppr  counting the number of identical genotypes among samples with the Multilocus tagging option in GenAlEx (suboption Matches), (ii) computing the probability of encoutering the same genotype more than once by chance using the R package  single; ), and  and the Two Phase Model (TPM) in BOTTLENECK 1.2.02 . We applvarEff [–4 based on published average mutation rate [Demographic history was also assessed through the R package varEff , an apprvarEff , 49. Mution rate . The anaOur ML tree based on 268 mitochondrial DNA (mtDNA) sequences recovered the six WBP geographic lineages with robust nodal support, including Western Africa, Ghana, Dahomey Gap, Western Central Africa, Gabon and Central Africa Fig. . All theWe identified fourteen CR1 haplotypes in the DGL. The median-joining network did not show any specific geographic structure in haplotype distribution  and R2 (0.0710) showed no significant deviation from a scenario of large and constant population size through time (p > 0.10), whereas Fs  significantly rejected the model.Mismatch analysis of CR1 haplotypes showed a bimodal distribution significantly deviating from the sudden expansion demographic model (P(Sim. Rag. ≥  Obs. Rag.) = 0.005), whereas the spatial expansion model could not be rejected (P(Sim. Rag. ≥ Obs. Rag.) = 0.15). The statistics D (− 0.56496), R) ranged from 1.86 to 8.04 , and observed heterozygosity (Ho) and expected heterozygosity (He) from 0.072 to 0.775 (mean = 0.414) and 0.069 to 0.842 (mean = 0.498), respectively. Eleven loci deviated significantly from HWE (P < 0.05). Six of them showed significant levels of heterozygote deficiency (P < 0.0025) and three of them were involved in LD . Null alleles were identified in ten loci, including seven that deviated from HWE  varied from 2 to 11 (mean = 5.3). Allelic richness , whether individuals from wildlife markets were considered or not  to moderate . In partition scheme (i), differentiations among the six forest populations were the greatest, all significant (p < 0.05), and ranged from low/moderate  to high   in the six DGL populations was 0.172 and varied from 0.098 to 0.317  and (iii) ranged from low . The geographic delineation of the populations did not show any spatially exclusive distribution. Assignment probabilities to populations varied greatly among the best five runs (data not shown). Similar results were observed when fixing K = 3  across the study area.The eigenvalues observed from the spCA analysis Fig.  suggester = 0.128; p = 0.001) and between populations    Fig. .Fig. 5Is−13; PIsibs = 9.22 e−06). At least seven microsatellite loci were needed to reach the conservative value of PIsibs < 0.01  had a unique genotype. Five samples shared a genotype with four other samples, including three pairs  and one triplet  using ADZE ranged from 0.10 to 0.24. Within the 11 loci that presented appropriate private allele signatures for one or several populations  for both SMM and TPM models.The bottleneck analysis on the DGL across 20 loci was not significant  of the DGL regardless of the models  to 78–135 (contemporaneous Ne) individuals as harmonic means (95% CI 263 to 487). The decrease in Ne was estimated to occur c. 200–500 years ago.els Fig. . Our resOur mtDNA tree-based assignment procedure indicated that all the white-bellied pangolins (WBP) collected and traded in the Dahomey Gap—from Togo, Benin and southwestern Nigeria—belong to the Dahomey Gap lineage . With 1Contrary to the bushmeat markets in Têgon (Benin), Hounkpogon (Benin) and Asejire (southwestern Nigeria) that are known to source the game from nearby forests  haplotype and nucleotide diversity was lower compared to all the other WBP lineages. Mean allelic richness based on microsatellites was also lower than what was found in WBP from Cameroon using the same markers . Comparely; see ).Low levels of genetic diversity are assumed to be negatively correlated with fitness and adaptability . The oveNe) of the DGL c. 200–500 years ago (100–250 generations), leading to a 92–98% reduction in the current Ne. This is below the conservative thresholds of minimum viable population size . Asiversity , the staiversity , 66. Wheiversity . Becauseiversity , it is piversity . Such deiversity .Ne through time, indicating long-term matrilineal stability. The only exception was the Fu’s statistics, which has maximum power to detect sudden demographic decline events [Earlier events such as the expansion of agriculture in West Africa c. 4200 BP  and natue events  and thuse events . The Dahe events .Our analyses generally suggested that there was no geographic structuring across the Dahomey Gap, against the expectation that habitat fragmentation leads to genetic isolation . The samAlthough we could not find any clear population structure in the DGL, we detected significant levels of differentiation and isolation-by-distance among both individuals and populations. We observed the strongest differentiations between the most distant Togolese and Beninese populations, and some cases of moderate differentiation between geographically close populations . Genetic differentiation among populations is determined by the interplay between homogenizing processes such as gene flow and differentiating processes including local adaptation, different adaptive responses to shared environmental conditions, and genetic drift . If we pA more plausible scenario would relate to a former, possibly recent, spatial expansion in subdivided populations across the DGL range, as mtDNA did not reject this model. It is possible that forest-restricted DGL populations underwent a spatial expansion following the last recent increase in rainforest cover during the last Interglacial or early Holocene periods . Such evThe genetic diversity of WBP sold on the markets was reflective of the overall genetic diversity  observed in DGL forest populations, suggesting a widespread sourcing of pangolins through the entire Dahomey Gap. Our 20 microsatellite loci provided the necessary power to confidently distinguish among all the DGL indivuals, and only seven microsatellite loci were needed to reach the conservative value of probability of identity < 0.01 . The proGiven the lack of population structure in the DGL and the negative autocorrelation between geographic and genetic distances , classical assignment procedures , 90 are Despite a relatively fair number of loci (20) and an exhaustive sample set across Benin, we could only trace c. 8% of the WBP genotyped from TMMs. Such performance could be improved with additional geographic sampling, notably from Togo and southwestern Nigeria, and denser sampling of populations, although the ideal standards for reaching confident estimates of allele frequencies when applied to forensic use might be unreachable in our case . FutureOur study is the first to provide a comprehensive population genetic assessment of an African pangolin species/lineage, filling an important knowledge gap for the future conservation of pangolins in Africa . OverallAdditional file 1: Table S1. General database including geographic references and detailed information on sequenced and genotyped individuals. Empty lines indicate unsuccessful sequencing/genotyping. Haplotypes of CR1 sequences used to compute genetic diversity are provided (H1 to H14). Individuals sequenced successfully but not used to compute genetic diversity—because of missing data—are indicated by “yes”Additional file 2: Table S2. Diversity indices calculated from the control region (CR1) among the white-bellied pangolin lineages. Table S3.FST values  and associated levels of significance  for the different partition schemes (i), (ii) and (iii). South and North in the partition schemes refer to Benin country. Table S4. Inbreeding coefficient in white-belled pangolin populations as delineated in the 6-partition scheme (i). Figure S1. Haplotype network (control region) within the Dahomey Gap lineage. Haplotype numbers refer to Table S1. Short bars correspond to mutation numbers. Figure S2. Assignment plots among the white-bellied pangolins from the Dahomey Gap as assessed with STRUCTURE for K = 2 (top) and K = 3 (bottom). Each individual is represented by a vertical bar. Figure S3. Geographic partition schemes used for computing pairwise differentiations (FST). (i) 6-partition scheme including the forest habitats with at least 7 individuals, (ii) 3-partition scheme among South Benin-Central Benin-Togo, (iii) gradient-based 3-partition scheme within Benin. Figure S4. Spatial clustering of white-belled pangolins in the Dahomey Gap obtained using Geneland for K = 7  and K = 3 . Figure S5. Unbiased probability of identity (uPI) and probability of identity among siblings (PIsibs) for increasing, optimized combinations among the 20 microsatellite markers. Figure S6. Mean private allelic richness per locus in white-bellied pangolin populations (6-partition scheme), as estimated from ADZE (N = 7). FGN: Gnanhouizounmè, FL: Lama, FMK: Mont Koufé, FOS: Ouémé Supérieur, FWM: Wari Maro and TG: forests of central Togo. Figure S7. Mean private allelic frequencies per population (forest habitat), as estimated by rarefaction from ADZE. FGN: Gnanhouizounmè, FL: Lama, FMK: Mont Koufé, FOS: Ouémé Supérieur, FWM: Wari Maro and TG: forests of central Togo. The names of the three loci cross-validated (ADZE and GenAlEx) and used for the tracing  appear in green. The four loci cross-validated (ADZE and GenAlEx) but not used for the tracing  appear in blue. The other four loci revealed using rarefaction but not observed in the actual dataset (GenAlEx) appear in orange.Additional file 3: Figure S8. Neighbor joining tree inferred from the control region and including the six lineages of white-bellied pangolins. The tree includes 181 sequences from the Dahomey Gap, 59 sequences from Western Central Africa, 12 sequences from Western Africa, 9 sequences from Central Africa, 3 sequences from Ghana and 1 sequence from Gabon.


Phytophthora species are well-known invasive pathogens of natural ecosystems, including Phytophthora multivora. Following the description of P. multivora from dying native vegetation in Australia in 2009, the species was subsequently found to be common in South Africa where it does not cause any remarkable disease. There are now reports of P. multivora from many other countries worldwide, but not as a commonly encountered species in natural environments.global trade in living plants and plant material has significantly increased the geographic distribution of many plant pathogens. As a consequence, several pathogens have been first found and described in their introduced range where they may cause severe damage on naïve host species. Knowing the center of origin and the pathways of spread of a pathogen is of importance for several reasons, including identifying natural enemies and reducing further spread. Several P. multivora, using 10 microsatellite markers for all isolates and sequence data from five loci from 94 representative isolates. Our population genetic analysis revealed an extremely low heterozygosity, significant non-random association of loci and substantial genotypic diversity suggesting the spread of P. multivora readily by both asexual and sexual propagules. The P. multivora populations in South Africa, Australia, and New Zealand show the most complex genetic structure, are well established and evolutionary older than those in Europe, North America and the Canary Islands.a global collection of 335 isolates from North America, Europe, Africa, Australia, the Canary Islands, and New Zealand was used to unravel the worldwide invasion history of P. multivora most likely commenced from South Africa, which can be considered the center of origin of the species. The pathogen was then introduced to Australia, which acted as bridgehead population for Europe and North America. Our study highlights a complex global invasion pattern of P. multivora, including both direct introductions from the native population and secondary spread/introductions from bridgehead populations.according to the conducted analyses, the world invasion of The online version contains supplementary material available at 10.1186/s12864-022-08363-5. Global trade in plants and plant products has inadvertently spread numerous plant pathogens worldwide, resulting in severe disease epidemics –3. For mPhytophthora species  are devastating plant pathogens in agriculture [P. citricola sensu lato complex [P. citricola sensu stricto, P. plurivora [P. multivora [P. pini [P. capansis [P. pachypleura [P. acerina [, P. caryae [P. emzansi [P. citricola s.l. have now been reassigned to other species within the complex, mainly P. plurivora and P. multivora, making its host range and species distribution narrower than previously thought [.Many iculture  and natuiculture , includi complex . The comlurivora , P. multultivora , P. pini[P. pini , P. capacapansis , P. pachhypleura , P. acer acerina , P. cary. caryae  and P. e emzansi . Many re thought , 12.Phytophthora plurivora is a widespread pathogen in temperate forests of the northern hemisphere, where it is frequently associated with root and stem diseases [P. plurivora had been introduced to North America from Europe [P. multivora is reported to be rare and somewhat restricted to nurseries and urban plantations [.diseases , 20. Thediseases , 22, andm Europe . Moderatntations , suggestPhytophthora multivora was the first pathogenic Phytophthora species to be described from natural ecosystems in Australia. As it is widely distributed and associated with significant plant mortality, it was initially hypothesized to be native to Western Australia [P. multivora brings into doubt the assumption that it is native to Western Australia.ustralia . The speustralia , 25, 26,ustralia –30 and rustralia , 32 are ustralia , North Australia  and Japaustralia , 35. TheP. multivora, we obtained a global collection of isolates from North America, Europe, Africa, Australia, the Canary Islands, New Zealand, and examined them with two sets of genetic markers; firstly, 10 single sequences repeats (SSR) and secondly sequences of three mitochondrial and three nuclear loci. Specifically, we addressed the following questions. (1) How genetically diverse are the studied populations? (2) How does the genetic structure differ among the populations? (3) What was the most likely demographic history of the populations’ establishment? (4) What is the geographic origin of the isolate harboring the ancestral state sequences according to coalescent phylogenetic analysis? and (5) What was the most likely global invasion history of P. multivora?Investigations about the genetic diversity and comparative analysis of population structure combined with a coalescent approach can decipher demographic history and gene flow among geographic populations, which may shed light on the possible origin of a species , 36–38. All 10 screened SSR loci were formally polymorphic, i.e. minor allele frequencies were > 5% in the global population and > 1% in each geographic population, and minor alleles were observed in more than two samples per geographic population. Pairwise linkage disequilibrium and deviation from Hardy-Weinberg equilibrium were not consistent across loci and populations  loci for 93 P. multivora DNA isolates. Additionally, we cloned 24 ENOLASE gene variants from 8 isolates and 10 HSP90 gene variants from 3 isolates. Alignment of sequences, including cloned loci, revealed 106 informative nucleotide sites in 113 genotypes. Clone-censored per geographic population data set resulted in 60 unique genotype sequences used for further phylogeographic investigation. Sequence and site diversities between mitochondrial and nuclear gene regions were comparable; however, they differed substantially among populations . The highest diversity estimates  were observed in the South African and Australian populations, followed by the New Zealand population  and the standardized index of association (rD) indicated a significant (P < 0.05) non-random association of loci and departure from panmixia in all populations . The lowest but statistically significant differentiation (FST = 0.05) was observed between the South African and Australian populations. The European population did not show any statistically significant differentiation with the other populations but New Zealand.Significant population differentiation , whereas the North American population included two MLGs assigned to the fourth (yellow) and one to the third (grey) cluster. Noteworthy, no admixed MLGs  were observed in these last three populations.Overall, multivariate discriminant analysis and the Sora Fig. C. MLGs fST values, three-center clustering in the multivariate discriminant analysis, and diverse genetic population structure in the South African, Australian, and New Zealand populations, we assumed these populations were older and likely source of the other three populations. Indeed, populations of Europe, the Canary Islands, and North America showed a lower diversity and no or few private alleles and unique MLGs.Considering the high diversity estimates, relatively low FP. multivora. Despite the possible uncertainty in the analysis of the specific quantitative results, the topology of our ABC analysis clearly showed the South African population is most likely the global source and place of origin of the species, and the two populations of New Zealand and Australia directly originated from it.Six different scenarios of the demographic history  and NADHI (mtDNA) as well as ASF, ENOLASE, HSP90 (nDNA), were as follows: HKY (Hasegawa-Kishino-Yano) for both mtDNA loci, JC69 (Jukes-Cantor) for the ASF locus and TN93 (Tamura-Nei) for the other two nDNA loci. Both Bayesian coalescent analysis we conducted, i.e. StarBeast with multilocus mitochondrial data and phylogeographic MASCOT with three nuclear and three mitochondrial loci, showed with high posterior probabilities that MLGs from South Africa are likely representing an ancestral lineage to the current global population of P. multivora  Australian clade, and might be the consequence of repeated introductions of P. multivora to Australia, mainly from South Africa.The best-fit models for each of the sequenced loci, specifically COI , indicating nonrandom association of loci. Among several reasons for the deviation from the random association of gametes (panmixia), the most common for oomycetes or fungi are asexual and clonal reproduction [P. multivora, like many other species in the genus, grows clonally and produces asexual sporangia, releasing zoospores. Zoospores dispersed through the soil water are the main infective propagules [P. multivora readily propagates both from oospores through homothallic self-fertilization and asexual zoospores, but gene flow among studied populations is restricted.Our analyses shed light on the population diversity, reproductive biology, and invasion history of P. sojae  and P. plurivora . Homothalurivora . Howeverlurivora . We alsooduction . Indeed,opagules , 46. Howopagules . Hence, P. multivora populations, specifically in South Africa, Australia, and New Zealand. Correspondingly, all MLGs clustered around three centers associated with these geographic locations in the multivariate non-parametric analysis  [ustralia , 24. Latustralia . The samortality , 47–49, ortality . In the m Europe . The sprm Europe . For exak import , 55, P. modities , the traovo-ulmi , 56, andipennis) . Furtheripennis) , 59. Theipennis) .P. multivora most likely commenced from South Africa. We detected the most complex genetic structure in this particular population, i.e. local MLGs were assigned to all four genetic clusters defined in STRUCTURE analysis in nearly equal proportion , originated most likely from Mexico [C. parasitica, the causal agent of chestnut blight, was first detected in North America and Europe and not in its native range in Eastern Asia [Hymenoscyphus fraxineus , the ascomycete responsible for the epidemic of ash dieback in Europe [Overall, the results obtained with Bayesian coalescent analyses of both nuclear and mitochondrial sequences confirmed our findings in population structure and ABC history analysis of 10 SSR genetic markers. In particular, both analyses are in accordance with South Africa being the center of origin of osystems . Hence, ern Asia , as it hn Europe .P. multivora, our analyses of a large collection of isolates from six geographic populations suggest a complex spread of this species throughout the world with possible multiple introductions to specific continents  from geographic regions where P. multivora is currently known as widely distributed and abundant, or/and where it has a severe phytopathological impact. In future, new P. multivora populations might be discovered and our results will have to be updated.To summarize, our genetic analysis of the global population revealed the invasive history of P. multivora from six distinct geographic locations: North America, Europe, South Africa, Australia, the Canary Islands, and New Zealand (Table S1).We obtained 335 isolates of P. multivora using the DNeasy Plant Mini kit  according to the manufacturer’s protocol. All isolates were then genotyped at 10 microsatellite loci  that were previously developed by [Genomic DNA was extracted from the selected pure cultures of loped by . All locP. multivora  between cytochrome oxidase 2 and cytochrome oxidase 1 [coxI) [Enolase (ENOLASE) [https://datadryad.org).Genomic DNA was extracted from isolates as described previously . For proxidase 1 , and the1 [coxI) , NADH de1 [coxI) , EnolaseENOLASE) , Heat shENOLASE) , and theENOLASE) . The reaENOLASE) , and 6–1ENOLASE) . All seqP. multivora. We used 10 SSR loci to study current population genetic diversity, structure, and demographic history of the global spread of P. multivora with Approximate Bayesian Computation (ABC). The SSR is generally considered neutral genetic markers [P. multivora global population with Bayesian coalescent analysis using sequences of the three nuclear and three mitochondrial loci. In order to remove a putative clonal effect on the genetic structure, only one representative of each multilocus genotype (MLG) per population was considered.We considered samples collected from each of the six geographically distinct locations as a single population of  markers  and therpoppr v 2.9.0 [FST-values [P-values (α = 0.05) with Arlequin 3.5.2.1. Multilocus linkage disequilibrium was evaluated based on the P-values from one-sided permutation tests with the R-package poppr v 2.9.0 for the indices of association IA and rD (Agapow & Burt 2001).Summary statistics on MLG, diversity indexes  and expe v 2.9.0 . Allelic v 2.9.0 . The dev v 2.9.0 . Pairwis v 2.9.0 . The staT-values  and corrP. multivora isolates recovered from different continents was examined using a multivariate clustering method, i.e. discriminant analysis of principle components (DAPC), implemented in the R-package adegenet [P. multivora isolates with correspondent PCs were plotted along with the first two discriminant functions.Genetic kinship of the adegenet . First, adegenet . Then P.P. multivora global population with six assigned populations corresponding to the isolate’s geographic origin  was studied with the Bayesian model-based cluster analysis, as implemented in STRUCTURE v 2.3.4. The isolates were probabilistically assigned to genetic clusters using allele frequencies at each SSR locus. We used sampling locations of the populations as prior geographic information (LOCPRIOR = 1 option) and the admixture ancestral model with correlated allele frequencies. Analyses were run with 200,000 burn-in iterations, followed by the same number of iterations for Markov chain Monte Carlo (MCMC) in 10 independent runs for each number of clusters (K) from 1 to 20. The most likely K was determined, as suggested in [The genetic structure of the ested in , by (1) ested in , (2) appested in , using Sested in , and (3)ested in  using thP. multivora spread among continents and the Canary Islands and New Zealand were investigated using a coalescent approximate Bayesian computation approach implemented in DIYABC v.2.1.0 [P. multivora were tested using the three most genetically diverse, and thus most likely oldest populations (see Results); populations from South Africa, Australia, and New Zealand. Then, a range of sequential runs of determining the most probable alternative scenario was performed by adding one of the remaining less diverse populations; European, North American, and the Canary Islands’ population (data not shown). Finally, considering population genetics results and assessments of intermediate evaluations of the alternative scenario for three minor populations, six most likely scenarios of the global distribution of P. multivora were hypothesized and tested. ABC analysis was conducted following [ST ratio between sampled populations, and field observations; 2) simulate 1 × 106 pseudo-observed datasets (PODs) for each scenario and compute correspondent summary statistics; 3) evaluate posterior probabilities of each scenario on 1000 PODs with the closest summary statistic to the observed dataset and identify the best scenario in 95% confidence interval; 4) assess the confidence level of the chosen scenario as the proportion of times this scenario was falsely rejected (type-I error) or accepted (type-II error); 5) evaluate the goodness-of-fit of the selected scenario to the data.The demographic history of the  v.2.1.0 . The demollowing , and incP. multivora global population, we used sequences of three mitochondrial loci and three nuclear loci for each specimen of the studied geographic locations. The alignments of each molecular locus were done using the ClustalW method, then the substitution model that best fitted to the locus data based on the lowest BIC scores (Bayesian Information Criterion) was selected using MEGA7 software [In order to study the phylogeographic evolution of the software . For eacsoftware .P. multivora global population were conducted by sampling trees with BEAST v2.6.2 package [7 iterations were carried out. The effective sample size estimates were assessed in Tracer v1.7.1 [P. multivora specimens in total, using their mitochondrial multilocus data, specifically COI (concatenated coxI and coxIGS) and NADH1, following the statistical methodology implemented in StarBeast [− 6 per site and per year, which was previously estimated for mitochondrial genomes of P. infestans [Phytophthora. We defined ancestral geographic location states following Marginal Approximation of the Structured Coalescent method [P. multivora  and the three mitochondrial genes mentioned above. The mutation rate was set as a constant 1.0 and the estimation of branch lengths was calculated in substitutions per site. The summarizing trees for the phylogeographic origin of the P. multivora populations were executed using the location of origin as discrete states. The substitution rate and the substitution model that best fit according to the lowest BIC were set for each locus. The default priors for the StarBeast and the MASCOT trees with Log Normal options and exponential population models were generated using Beauti v2.6.6 [Bayesian inferences about the evolution of the  package , 93. MCMr v1.7.1 . The subtarBeast , 96. In nfestans . Given tnfestans , we assut method , 98. Spei v2.6.6 , 93.. Mai v2.6.6  and thenAdditional file 1.