Partamona seridoensis is an endemic stingless bee from the Caatinga, a Neotropical dry forest in northeastern Brazil. Like other stingless bees, this species plays an important ecological role as a pollinator. The aim of the present study was to investigate the genetic structure and evolutionary history of P. seridoensis across its current geographic range. Workers from 84 nests from 17 localities were analyzed for COI and Cytb genic regions. The population structure tests  consistently characterized two haplogroups (northwestern and eastern), with little gene flow between them, generating a high differentiation between them as well as among the populations within each haplogroup. The Mantel test revealed no isolation by distance. No evidence of a potential geographic barrier in the present that could explain the diversification between the P. seridoensis haplogroups was found. However, Pleistocene climatic changes may explain this differentiation, since the initial time for the P. seridoensis lineages diversification took place during the mid-Pleistocene, specifically the interglacial period, when the biota is presumed to have been more associated with dry conditions and had more restricted, fragmented geographical distribution. This event may have driven diversification by isolating the two haplogroups. Otherwise, the climatic changes in the late Pleistocene must not have drastically affected the population dynamics of P. seridoensis, since the Bayesian Skyline Plot did not reveal any substantial fluctuation in effective population size in either haplogroup. Considering its importance and the fact that it is an endemic bee from a very threatened Neotropical dry forest, the results herein could be useful to the development of conservation strategies for P. seridoensis. Social bees from the tribe Meliponini, known as stingless bees, are distributed in tropical and southern subtropical areas throughout the world, with greater diversity in Neotropical and Indo-Malayan regions ,2. So faPartamona seridoensis [Caatinga (phytogeographic domain), a Neotropical dry forest in the northeastern region of Brazil. This species nests only in active arboreal termite nests, mainly those of Constrictotermes cyphergaster.  and Microcerotermes spp [Partamona seridoensis has been poorly studied and only one report is found in the literature on its population genetics, in which two populations were analyzed using allozymic and microsatellite markers [Caatinga, which is a threatened region. A recent study involving Partamona rustica has suggested the importance of concentrating efforts on the conservation of endemic stingless bees from Brazilian dry forests, due to bee hunters and deforestation, which have threatened these populations [The stingless bee idoensis  occupiesrmes spp ,10,11. P markers . There hulations .Caatinga covers nearly 85,000 Km2 and is a highly heterogeneous phytogeographical domain, being the second largest center of endemism of xeric environments in South America [Caatinga have shown that this environment harbors high levels of species richness and specific interactions between insects and plants [Caatinga is one of the least protected areas by conservation policies in Brazil, with only 5.9% of its area included within conservation units [Chaco, Cerrado and Caatinga phytogeographic domains [Caatinga has led to a process of desertification in many areas, making this phytogeographical domain severely threatened by climate changes [The  America ,15. Studd plants ,14,16,17on units , and one changes .Caatinga. A recent study analyzed the genetic structure and evolutionary processes involved in the current genetic variation of Melipona subnitida, an endemic species in northeastern Brazil, and suggested that the paleoclimatic changes of the Pleistocene could have played an important role in the diversification of this species [Partamona rustica, an endemic stingless bee from the Neotropical dry forest in Brazil, and identified two groups of populations with no evidence of substantial changes in effective population size during the late Pleistocene [Many studies have shown the effects of Pleistocene climatic events on the population structure and demography of bees around the world ,21,22. H species . Anotheristocene .Caatinga. Given the potentially serious consequences of inbreeding in stingless bees due the complementary sex determination mechanism [P. seridoensis across its current geographic range.Understanding the evolutionary history of a species and its genetic structure is essential to the development of effective conservation strategies ,24, espeechanism ,26, it iP. seridoensis nests from March 2008 to August 2014. Through active searches, 84 nests were sampled from 17 localities in the northeastern region of Brazil, with an average of five nests per locality  and in the Laboratório de Genética Evolutiva de Himenópteros at the Universidade Federal de São Carlos (LGEH–UFSCar). All necessary research permits for fieldwork and collection of samples were issued by the Brazilian Institute for Biodiversity Conservation (Instituto Chico Mendes de Conservação da Biodiversidade—ICMBio) recorded by SISBio (permit number 31750). Field studies did not involve endangered or protected species.Adult workers were collected from locality . The samb (Cytb) [2 and 1 U of Platinum Taq DNA polymerase  in a final volume of 25 μL. The PCR conditions for all gene regions were as follows: initial denaturation at 94°C for 5 minutes, followed by 40 cycles of denaturation at 94°C for 30 s, annealing at 50°C and extension at 72°C for 1 min, and completed with an additional extension step at 72°C for 10 min. The PCR products were electrophoresed in agarose gel stained with GelRedTM. The PCR product was purified using the Illustra ExoProStar 1-Step Kit . The mitochondrial genes were sequenced in both directions with the same amplification primers using the BigDye v 3.0 Dye Terminator Cycle Sequencing Kit  in an automated sequencer ABI 3730 XL (Applied Biosystems).Total DNA was extracted from one worker per colony using a phenol-chloroform protocol . Fragmenb (Cytb) , commonlThe electropherograms were edited using the Codon Code v3.7.1 program . Sequences were aligned using the Clustal W algorithm with the aid of the BioEdit 7.0.9.0 program . All aliP. seridoensis lineages based on the concatenated mitochondrial haplotypes. The model with the best fit was selected with the aid of the MrModeltest v2.2 program [tree.bio.ed.ac.uk/software/figtree/). For this analysis, Partamona cupira and Partamona ailyae were used as the outgroup, since these species are part of the same group as P. seridoensis.Bayesian inference was used to estimate the phylogeny of  program  based on program . Chain c program  and resuTo check if the haplogroups observed are not cryptic species and assess uncertainty in phylogenetic tree estimation and model parameters, a Bayesian implementation of the generalized mixed Yule coalescent model (bGMYC) was used, which integrates over these potential sources of error via MCMC simulation . The R pwww.fluxus-engineering.com/sharenet.htm). Analysis of molecular variance (AMOVA) was performed to estimate the degree of population genetic differentiation among populations using three hierarchical levels. The ΦST and ΦCT indexes were also estimated. These analyses were implemented using the ARLEQUIN 3.11 program [Haplotype networks were constructed employing a median-joining network  in the N program  and sign program  to test A Bayesian approach implemented in BEAST 1.8.0 program  was usedA Bayesian Skyline Plot (BSP) reconstruction was implemented for possible groups identified in the phylogenetic reconstruction to evaluate population size dynamics over time using the BEAST 1.8.0 program . All theM (m/μ). Four migration models were tested and compared by the bayes factor: (1) a full model with two population sizes and two migration rates; (2) a model with two population sizes and one migration rate (gene flow into the northwestern population); (3) a model with two population sizes and one migration rate (gene flow into the eastern population); (4) a model considering eastern and northwestern as a panmictic population. We used a Bayesian approach and thermodynamic integration of four chains with a static heating swap scheme , with two independent runs, sampling at every 600th step for a total of 600,000 of recorded steps and a burn-in of 150,000 steps.We evaluated the gene flow between haplogroups by the structure tests using Migrate-n v3.6 . The migP. seridoensis and no indels occurred in these amplicons. We have no ambiguous bases or missing data in our dataset. Sixteen variable sites and 14 haplotypes were identified. The species exhibited low nucleotide diversity (π = 0.00266 ± 0.00019) and high haplotype diversity (Hd = 0.756 ± 0.044)  was obtained for the concatenated genes of ± 0.044) .CT = 0.740, p < 0.0001; ΦST = 0.984; p < 0.0001, respectively).Based on the AIC, the evolutionary model selected for the Bayesian Inference, including the outgroup, was GTR + I. p = 0.097) and populations in each haplogroup separately , indicating no isolation by distance among populations.The Mantel test demonstrated no correlation between genetic and geographic distances considering all populations , suggesting that this could be the initial diversification time for the two P. seridoensis lineages analyzed herein. The TMRCA for each group indicated a recent age for these two lineages, with coalescence of northwestern and eastern groups respectively occurring 84.5 kya (HPD 95%: 35.7–149.6 kya) and 106.9 kya (HPD 95%: 49.3–180.5 kya). The BSP did not reveal any substantial fluctuations in the effective population size (Ne) in either haplogroup  of 0.63 . All these parameters showed posterior probability curves with unique peaks and effective sample sizes (ESS) higher than 1,000, indicating convergence in the run.We detected little gene flow between the eastern and northwestern populations in all models. Migration from the eastern to the northwestern populations was the most probable model (0.72) of gene flow , with thP. seridoensis populations in the state of Paraíba (Brazil) [Partamona are philopatric, remaining in the place of origin and not flying more than 300 meters from the maternal nest during the swarming process [P. seridoensis builds its nests on specific substrates, nesting in arboreal termite nests [The population structure tests  consistently characterized two haplogroups (northwestern and eastern). The results revealed a high number of privative haplotypes and a high level of differentiation between haplogroups as well as among all populations, with little gene flow mainly from the eastern to the northwestern haplogroup when the population genetic structure is assessed by mitochondrial genes. Moreover, the bGMYC analysis recovered a single evolutionary entity, suggesting that these haplogroups are not different species or even cryptic species. Previous study involving allozymic and microsatellite loci found a low population differentiation between two geographically close (Brazil) , suggest process ,44,45. Mte nests ,10,11. Ste nests .P. seridoensis. Moreover, no correlation was found between genetic and geographical distances, suggesting no isolation by distance among the populations analyzed. However, the differentiation that resulted in the two haplogroups may be explained by climatic changes in the mid-Pleistocene, since the initial diversification time for these lineages was estimated at approximately 163 kya, specifically in the interglacial period [P. seridoensis depends on plant resources, such as pollen, nectar and resins, as well the existence of suitable sites for nesting, such as termite nests. Such resources may also have had restricted geographical distribution due to climatic changes. These aspects and the presumed limited dispersal capacity of this stingless bee lend support to the hypothesis that mid-Pleistocene climatic changes may have driven the diversification of P. seridoensis into at least two haplogroups.There is no evidence of potential geographic barriers  in the present that could explain the diversification found between the two haplogroups of l period , a time l period . This evMelipona subnitida, a stingless bee with a similar distribution area in the Caatinga [Similar results were observed to populations of Caatinga . The autCaatinga ,48,49,50Caatinga ,52,53. MCaatinga ,55 as weCaatinga ,21,56.Caatinga, at least locally, during the wettest periods [M. subnitida in the Caatinga during the Pleistocene period was reported [P. seridoensis groups, since the BSP did not reveal any substantial fluctuations in the effective size of the populations in either haplogroup analyzed herein , oscillations occurred in the late Pleistocene must not have drastically affected the population dynamics. A putative refuge area for Seasonally Dry Tropical Forests in the Caatinga between the Last Glacial Maximum and the present, which covers most of the current distribution area [P. rustica populations in Brazilian dry forests [Studies have suggested that forests expanded into the  periods ,58. Popureported . Howeverd herein . As the ion area  was rece forests .Drosophila [Unfortunately, there are no substitution rates yet available for the mtDNA (such as COI or Cytb genes) of bees. Therefore, recent studies involving bees ,23,24 puosophila , as wellosophila  0.8–1.3 osophila  and 2.1 osophila . TherefoP. seridoensis found with mitochondrial genes is expected to be lower when assessed using nuclear genes, as observed in a previous study involving the population genetics of P. seridoensis using nuclear markers [The population differentiation of  markers . Like mo markers ,69,70, i markers . Thus, t markers ,23,72, a markers ,73,74,. Caatinga during the Pleistocene, as we have shown that the lineages of P. seridoensis diversified during the mid-Pleistocene likely due to climatic changes, resulting in two haplogroups. The conservation of different evolutionary lineages is important to preserving better adapted genotypes for greater survival during drought periods in the Caatinga [P. seridoensis populations, especially its two evolutionary lineages. Conservation policies directed at preserving pollinating species may be an effective mechanism for preserving the biodiversity of Neotropical biomes, which is an urgent task that must be pursued.Recent study stressed the need for further, more detailed investigations of dry environments of the Neotropical region, since few phylogeographical studies have considered the biota of this area . The preCaatinga . MoreoveCaatinga ,76. ReceCaatinga ,23,77. SCaatinga . Given i


Orbicella faveolata is one of the most important reef‐building corals in the Caribbean and has recently experienced severe population reductions. Here, we utilize a panel of nine microsatellite loci to evaluate the genetic structure of O. faveolata and to infer connectivity across ten sites spanning the wider Caribbean region. Populations are generally well‐mixed throughout the basin (FST = 0.038), although notable patterns of substructure arise at local and regional scales. Eastern and western populations appear segregated with a genetic break around the Mona Passage in the north, as has been shown previously in other species; however, we find evidence for significant connectivity between Curaçao and Mexico, suggesting that the southern margin of this barrier is permeable to dispersal. Our results also identify a strong genetic break within the Mesoamerican Barrier Reef System associated with complex oceanographic patterns that promote larval retention in southern Belize. Additionally, the diverse genetic signature at Flower Garden Banks suggests its possible function as a downstream genetic sink. The findings reported here are relevant to the ongoing conservation efforts for this important and threatened species, and contribute to the growing understanding of large‐scale coral reef connectivity throughout the wider Caribbean.As coral reefs continue to decline worldwide, it becomes ever more necessary to understand the connectivity between coral populations to develop efficient management strategies facilitating survival and adaptation of coral reefs in the future.  This study contributes to a growing understanding of the dispersal capabilities of marine invertebrates in the wider Caribbean. In doing so, it helps to further inform regional conservation strategies for an endangered reef‐building coral and provides a foundation for future investigations into the mechanisms that underlie the observed patterns of population genetics.With the findings of this investigation, we specifically seek to achieve three primary goals: (i) quantifying the extent to which populations of 22.12) of the mountainous star coral, Orbicella faveolata, were collected from 10 sites that span the extent of the wider Caribbean seascape , fragments of tissue were excised from adult colonies using a hammer and chisel and were placed in individual plastic bags filled with seawater. Tissue samples collected at Sugarloaf Key were siphoned from the coral surface using a plastic syringe to minimize physical damage, in compliance with permit requirements. The filter paper containing each tissue sample was placed in a labeled plastic bag filled with a 96% ethanol (EtOH) solution. At all sites, colonies of  Knowton . Care waAll samples were then transported in an insulated cooler to the laboratory for preservation. Samples from the Bahamas, Barbados, Belize, Florida Keys, and USVI were transferred to DMSO buffer (20% dimethyl sulfoxide and 0.25 ethylenediaminetetraacetic acid (EDTA) in NaCl‐saturated water), while those from the FGB were transferred to 96% EtOH. All of the above were stored at −20°C. Samples from Curaçao, Mexico, Panama, and Puerto Rico were flash‐frozen in liquid nitrogen and stored at −80°C.sampling site, site and population will be used interchangeably to refer to the 10 sampling sites discussed above and outlined in Table region will refer to four specific groups of these sampling sites that are identified statistically, as described below and in Table Note, to maintain consistent terminology throughout the manuscript, the terms 2.2In preparation for DNA isolation, tissue was removed from storage solution, submerged in digest buffer  and was heated to 42°C for 1 hr. DNA was then isolated following a standard phenol–chloroform extraction protocol , or the probability that two independently sampled individuals within a population share an identical multilocus genotype by chance, was calculated using GenAlEx v6.502 . Clone mates were only found within the same geographic site. Additionally, samples with data missing for more than three loci were removed, leaving 369 unique genets for downstream analysis.Before further analysis, the probability of identity (n = 11). Genepop v4.5.1  procedure was implemented in GenAlEx v6.502 using an infinite allele model and 9999 random permutations. The demarcation of four discrete regions across the sampling range was guided by the apparent clustering of populations based on pairwise estimates of differentiation, which were also calculated via AMOVA. Pairwise FST was calculated to enable comparisons to past research; however, Hedrick's (2005) GST″ statistic is also reported, as it incorporates standardized estimates for total and within‐population expected heterozygosity developed by Nei and Chesser  and to test for the presence of isolation by distance. Both estimates were calculated using GenAlEx v6.502.Global  Chesser  in order Chesser . Thus, wGST″/(1−GST″) and the natural logarithm of over‐water distance using a Mantel test in R (9999 permutations), as recommended by Rousset  are calculated for each individual, which describe the likelihood that an individual belongs to each of the inferred populations. The clustering algorithm was assisted using the 10 sampling sites as a prior  was calculated for each sampling site to describe qualitatively the evenness of representation from each of the inferred genetic clusters: Lastly, Simpson's index , and n is the total number of clusters. This index ranges from 1/Dmax  to 1, which would indicate an equal proportion of all clusters.where 33.1p = .113). Similarly, while ANOVA results provide evidence that heterozygosity may differ between populations , the more statistically stringent Tukey's HSD test revealed no significant pairwise differences between populations. Thus, there is no sufficient evidence to conclude that heterozygosity in any population was greater or less than that of any other.Genetic diversity as measured by expected heterozygosity and mean allelic richness were moderately high in all populations, with values ranging from 0.582 to 0.694 and from 5.433 to 6.940, respectively Table . Allelicγ^ = 0.22; Table Twenty‐two of 90 locus‐by‐population tests revealed evidence of heterozygote deficiency after sequential Bonferroni correction, of which 18 were associated with four particular microsatellite loci: Mfav5_CGA, Mfav4_TTTG, Mfav6_CA, and Mfav8_CAA Table . This paSignificant linkage disequilibrium (LD) was observed in ~10% (33 of 360) of locus pair comparisons after sequential Bonferroni adjustment. No locus pairs were significantly associated across more than three sampling sites, suggesting that the observed disequilibrium is likely not a result of physical linkage of the markers Table . Interes3.2FST was low but significantly different from zero . Pairwise FST and GST″ estimates between localities ranged from 0.009 to 0.065 and 0.013 to 0.290, respectively ; however, all other comparisons except Panama‐FGB were significant.Global y Figure . Only seGST″ values reveals four distinct clusters segregated along principal coordinate (PC) 1, which explains 62.59% of the variation in these data ] was correlated with pairwise over‐water distance  and lowest in Mexico, Belize, and Puerto Rico . All other populations exhibited intermediate values within this range  and Tan (Mexico) cluster with <3% of each population associating with the dominant cluster of the other population, highlighting significant differentiation across these two populations.44.1Orbicella faveolata are relatively well‐mixed across the wider Caribbean (FST = 0.038), although within this broad setting, we find complex patterns of substructure arising at both local and regional scales. Our analysis indicates that eastern populations diverge considerably from populations to the west, which reflects patterns of connectivity previously described for Acropora palmata  annularis , two sites within the Mesoamerican Barrier Reef System (MBRS) separated by only 470 km. With the use of five microsatellites, Porto‐Hannes et al.  to inshore regions of the southern Belize shelf. This provides compelling support for a genetic break between Carrie Bow Cay and Puerto Morelos. However, further research is needed to determine whether such a barrier to dispersal could persist over the timescale required to generate the level of population divergence observed here.We hypothesize that certain features of the prevailing oceanographic patterns in this area may underlie the strong local differentiation observed here as well as the overall genetic isolation of the Belize population from the rest of the wider Caribbean. Notably, the MBRS is characterized by two divergent flow regimes originating where the Caribbean Current encounters the Yucatan Peninsula . The authors propose that such a stark difference between two closely related taxa may have arisen through the accumulation of chance differences in recruitment success across years. Additionally, such contrasting patterns could result from genetic introgression or the unintended inclusion of sibling species in their analysis. To be sure, future work is needed to elucidate these species‐specific dynamics.A strong signal of connectivity between populations in Mexico, the Florida Keys, and the Bahamas is consistent with previous findings of virtually no genetic structure across this range in FST = 0.009) suggests relatively strong connectivity between these two sites. The net direction of larval transport between the sites remains unknown; however, a recently developed biophysical model demonstrates a mechanism by which larvae of O. franksi are able to disperse from FGB to reefs in the Florida Keys and Bahamas , a significant Wahlund effect is relatively unlikely. Furthermore, while it is possible that inbreeding may play a role, it would be expected to affect all loci relatively equally  have been shown to amplify in other Orbicella species with ≥80% success  also account for the large majority (~82%) of clonal individuals removed from the dataset prior to analysis. This uneven geographic distribution of multilocus clones may reflect underlying ecological circumstances at these locations. However, to confirm the true extent and dynamics of hybridization and a possible association with asexual reproduction, a more comprehensive investigation of allele frequencies within these populations that includes all possible parental genotypes is required.5O. faveolata. Within the context of strong overall connectivity across the seascape, we find further support for a genetic break between eastern and western populations as has been observed for other coral species. We discover evidence for strong differentiation between neighboring populations within the MBRS and also find evidence that the FGB may function as a genetic sink for the Caribbean basin.The results of this study advance the current understanding of population connectivity throughout the wider Caribbean and offer insight into local and regional patterns of genetic structure for the important reef‐building coral O. faveolata, and we therefore encourage the use of the genetic patterns discussed here to inform future investigations into the magnitude of larval dispersal throughout the wider Caribbean seascape.From a management perspective, it is essential to bear in mind that the findings and interpretations presented here describe patterns of population connectivity that have arisen over an evolutionary timescale (thousands of generations). Accordingly, we can use these data to infer the extent to which genetic material is shared between populations, which can have important implications for overall genetic variation and potential for adaptation. However, estimates of genetic divergence alone provide little information on demographic connectivity, that is, whether or not the per‐generation rate of migration between populations is large enough to significantly affect population growth. Understanding both the genetic and demographic connectivity among populations is critical to the management of SWD, MVM, and MM conceived and designed the study and sampling scheme. SWD, MVM, EAG, MM, NZK, TP, and JHPC acquired permits, collected coral tissue samples, or isolated DNA. SWD, NZK, and TP completed all microsatellite multiplex assays. JPR analyzed the microsatellite data. All authors contributed to writing of the manuscript. The authors thank Carly Kenkel, Marissa Nuttall, Eli Meyer, Bill Fitt, Dan Thornhill and Scott Santos for their contribution to sample collection and preservation. This research was supported by the National Science Foundation  and by the NOAA National Undersea Research Program through both the Caribbean Marine Research Center on Lee Stocking Island, Bahamas and the Florida Keys Dayboat Program run by the University of North Carolina at Wilmington. We also acknowledge all permitting authorities for previously assembled coral collections.https://doi.org/10.5061/dryad.15qf2.Microsatellite genotype data and STRUCTURE output files are made available via the DRYAD Digital Repository;  Click here for additional data file. Click here for additional data file. Click here for additional data file. Click here for additional data file. Click here for additional data file. Click here for additional data file. Click here for additional data file. Click here for additional data file. Click here for additional data file.


Understanding the genetic structure of Native American populations is important to clarify their diversity, demographic history, and to identify genetic factors relevant for biomedical traits. Here, we show a demographic history reconstruction from 12 Native American whole genomes belonging to six distinct ethnic groups representing the three main described genetic clusters of Mexico . Effective population size estimates of all Native American groups remained below 2,000 individuals for up to 10,000 years ago. The proportion of missense variants predicted as damaging is higher for undescribed (~ 30%) than for previously reported variants (~ 15%). Several variants previously associated with biological traits are highly frequent in the Native American genomes. These findings suggest that the demographic and adaptive processes that occurred in these groups shaped their genetic architecture and could have implications in biological processes of the Native Americans and Mestizos of today. People of Mexico have diverse historical and genetic background. Here, Romero-Hidalgo and colleagues sequence whole genomes of Native Americans of Mexico, and show demographic history and genetic variation shared among subgroups of Native Americans. The inhabitants of the Americas of today are the result of several ongoing migration, admixture, and adaptive processes that have varied throughout the continent over several centuries. In the fifteenth century, prior to the Conquest of Mexico, Mexican territory was inhabited by many different Native groups located mainly in Mesoamerica, but also in Northern Mexico, inhabited by nomadic or semi-nomadic peoples3. The Mexican population of today is the result of complex and ongoing admixture processes that began with the Conquest of Mexican territory by the Spaniards in 15214. The admixture process occurred mainly between Native Americans and Europeans, although there was a smaller contribution of the African population introduced by slave traders during the colonial period6. Currently, there are 68 acknowledged Native American languages in Mexico. Native populations not only contributed very importantly to the admixture process of the Mexican population, but currently up to 21% of Mexicans identify themselves as members of one of the acknowledged Indigenous groups of Mexico. Moreover, according to a recent survey, approximately 7% of the Mexican population, that is over 7 million Mexicans, speak a Native language7.The peopling of the Americas was the most recent continental occupation to occur in human history. Although still a matter of controversy, according to the most widely accepted model based on archaeological and genetic evidence, American Natives originated in Eastern Asia no earlier than 23 thousand years ago (kya), reached America through the Bering Strait and expanded across the Americas along the North–South direction8. Much of what we know comes from analyzing patterns of common, and, therefore, ancient genetic polymorphisms via genotyping across diverse human populations10. Recent studies have used sequencing approaches to reveal a more complete and genome-wide picture of variation, including low frequency variants of a more recent origin12. However, only a few whole genome sequences from NA individuals have been reported, and the genetic variation of NA remains largely unexplored14.The genetic structure of Native Americans (NAs) of Mexico has been previously analyzed using microarray technology, shedding light on peopling and migration processes, and more recently on the high diversity of the NA populations15. Thus, to better understand the genetic variability of NA and the genetic factors that may contribute to biological traits in this population, high coverage whole-genome sequences of 12 NA individuals from six distinct ethnic groups and a trio of Mexican Mestizos were analyzed, together with microarray data from 312 NA individuals. These data shed light on recent demographic history, better define the diversity of the populations of Mexico, and discover genetic variation shared among these populations, which may have an impact on health and other phenotypic traits.Understanding human genomic variation is a central focus of medical and population genomics8 Estimated NA ancestry using genome-wide data was over 98% in all indigenous participants, except for both Tepehuanos who were selected for having the highest NA ancestry (91%) among those available for whole-genome sequencing (WGS).Whole genomes of a total of 15 Mexican individuals were sequenced, including 12 NAs from six distinct ethnic groups  and a trio of Mexican Mestizos  7, it is necessary to obtain genomic data from different Nahua populations to identify whether Nahuatl-speaking individuals share the Nahua component here identified.Reference NA and continental populations were used to generate multidimensional scaling (MDS) plots. Figure 8 Fig. . Three-h8 Fig. . Thus, t19. The distribution of insertions/deletions (indels), copy number variations (CNVs) and mobile element insertions (MEIs) are described in Supplementary Tables The mean coverage for all genomes was 40×  as compared to the NA genomes (51.8%)  populations excluding the Americas (AMR) populations  haplogroups24. Thus, these uniparental marker analyses confirm the demographic history of the Mexican Mestizo and Native populations, where the contribution of the European gene pool to the admixture process was mainly of male origin25.As shown in Table 26, and 4 ancient individuals 28. The inferred tree recapitulates the North to South differentiation gradients for the NA groups observed from the MDS analysis. Southern NA populations of Mexico are grouped in a major clade , while Northern NA populations of Mexico (Tarahumaras and Tepehuanos) branch from the same initial split. In addition, this analysis confirms the gene flow from the Mal’ta lineage, (known to have genetic affinities of both European and NA populations), to the ancestors of all present day NAs29.A maximum likelihood tree was generated to ascertain the population history of present day NA in relation to worldwide populations by Treemix  between 50–60 thousand years ago (kya)  model showed evidence of a strong bottleneck in the European, Asian and NA populations, reaching the lowest effective population size (ya) Fig. . Althoug33, multiple sequentially Markovian coalescent (MSMC) analyses were performed combining four and eight phased haplotypes. Figure Ne remained close to 2000 individuals in all groups for another 10 thousand years (10–20 kya). We then performed MSMC analysis combining four individuals from Northern NA groups (Tarahumaras and Tepehuanos), and four individuals from Southern NA groups (Nahuas and Zapotecas). Figure Ne up to 2 kya. Ne of Southern NA groups increased constantly between 9 and 2 kya, in contrast with Northern groups who continued to decline from 9 to 4 kya. This is consistent with the previously reported higher effective population sizes for Southern and Mayas compared to Northern NAs of Mexico34. In addition, this population growth concurs with the time estimated for domestication of maize in Southwestern Mexico, approximately 6000–10,000 kya37.Because PSMC can only infer population size estimates beyond 20 kya38. Seeking for incidental findings within the 56 genes recommended by the ACMG, we found a total of 90 non-synonymous variants in the 12 NA genomes. Sixty-eight of these variants were polymorphisms (MAF > 1% in at least one of the 1KG populations). The 22 remainder variants were absent from the 1KG project (phase 3), three of which are annotated in the ClinVar database. One individual carried a mutation in the KCNH2 gene  previously found in a patient with congenital long QT syndrome;39 another carried a BRCA2 variant annotated as of uncertain clinical significance in ClinVar (rs80358606), and a third mutation (T187S) was identified in the SCN5A gene, in the same position as a loss of function mutation (T187I) found in a patient with Brugada syndrome40. Because the phenotypes of these individuals and the penetrance of the variants annotated as pathogenic are unknown, it is not possible to determine whether the 19 remainder variants predicted as deleterious or probably damaging are in fact pathogenic.We analyzed all NA genomes for the presence of potentially pathogenic alleles as defined by the publication of the American College of Medical Genetics and Genomics (ACMG)loci associated to many different phenotypes. The vast majority of the studies have been performed in populations of European descent and few loci have been replicated in the Mexican population using designs that simultaneously analyze a broad number of single-nucleotide polymorphisms (SNPs)43. Based on the NHGRI GWAS catalog, which contains all the SNP-trait associations with a significance threshold of 10−5, a total of 10,347 variants were present in at least one of the 12 genomes and 1,888 variants were shared among the 12 individuals. The latter shared variants were grouped based on their experimental factor ontology (EFO) and their frequencies were compared with other continental populations, particularly Europeans (CEU) and Asians (CHB and JPT) from 1KG project. Notably, variants whose frequency in the 12 genomes most differed from European or Asian populations have been previously associated with human morphology and clinical traits  most differed from Europeans, but was similar to that in Asians. Earlier studies have highlighted SLC24A5 as one of the top candidate genes demonstrating evidence for positive selection in Europeans, suggesting that the fixation of the “A” allele is related with adaptive processes45. Moreover, the allele frequency of the rs765132 “T” allele, previously associated with response to anti-tumor necrosis factor alpha therapy in inflammatory bowel disease46, was 87.5% in the 12 NA whole genomes, 59% in the 312 additional NA samples with microarray genotyping data, but only 5% in Europeans (5%) and not found in Asians. Thirteen additional SNVs with high population allele frequency differences were also available in the 312 NA samples. Overall, allele frequencies of these SNVs were similar in the 12 NA whole genomes and the 312 NA samples, although differences ranged from 0.01 to 0.19  have been published reporting over 20,000 47. We clustered the genes with novel non-synonymous and promoter region SNVs  approved this project. Written informed consent was obtained from all participants. For participants not fluent in Spanish, a translator was used. Blood samples were drawn with the permission of local authorities. The ethical duty to return individual research results or incidental findings is currently a matter of debate, depending on characteristics of the finding such as analytical and clinical validity, clinical actionability and significance as well as magnitude of potential damage. Because the samples included were donated anonymously, it was not possible to inform the participants about the incidental findings found here.8  procedures, where K = 10 showed the lowest CV error  as well as additional NA samples included with SNP 6.0 microarray (Affymetrix) data.Sampling locations are described in Fig. 54. Sequence reads were mapped to the reference human genome (GRCh37) and variants were called using version 2.4 of the Complete Genomics software. All variant information  and structural variation] was obtained from the master variation files reported by Complete Genomics. Only variants classified as “PASS” were considered for analyses. Variants not reported in dbSNP v137 were considered novel. SNVs within the 7.5 kb region upstream of the 5′ transcription initiation site of genes were considered as promoter variants. The functional consequences of nonsynonymous SNVs were predicted using PolyPhen-2 (Polymorphism Phenotyping v2)55. The mean concordance rate between SNP 6.0 microarray and WGS data was 99.2% , and biallelic for at least one genome. Kinship coefficients between parents and offspring of the trio were 0.251 and 0.253.Relatedness between among the 12 NA individuals was inferred by the kinship coefficient using KING v2.057, GATK was used for variant calling58, and snpEff was used for variant annotation59.Samples of three additional Tarahumaras known to have participated in high resistance physical activity events were prepared using Agilent SureSelect V4 All Exome kit  and were sequenced on an Illumina NextSeq 500 system  at the Sequencing Unit of INMEGEN. Reads were mapped to the reference human genome (GRCh37) with BWA60 using Phylotree61 and the nomenclature adopted by the International Society for Forensic Genetics62. Haplogrep software was used to assign haplogroups63. Y chromosome sequences were merged with a set of 19 worldwide Y chromosomes made publicly available by Complete Genomics, in order to determine their broad haplogroup affiliation.mtDNA sequences were compared to the revised Cambridge Reference SequenceThe distribution of SNVs along genomes was analyzed dividing the genome into 20 Kb windows, and reporting the mean number of SNVs per window in the 12 NA genomes and in all non-AMR individuals from the 1KG project.64. A total of 21 individuals were used to infer admixture graphs, 17 present-day individuals including the 12 NA genomes sequenced in this study, and 4 ancient individuals 28. Transitions were excluded from the data set to prevent biases introduced by the four ancient genomes. Only SNVs called in all genomes were included in the analysis. A maximum likelihood tree was inferred including 336,272 autosomal SNVs, using the default parameters and fitted allowing two migration edges.History of population splits and mixtures was inferred with TreeMixhttp://www.completegenomics.com/public-data/69-genomes/.) Bootstrapping analysis was performed to validate the inference as described by Li et al.31  analysis was used to reconstruct the demographic history of the NA populations here analyzed. Only data from highly covered regions were used. Reference population genomes were obtained from Complete Genomics  and the four genomes from Southern Mexico (Zapotecas and Nahuas). All genomes were previously phased with SHAPEIT V2.1265, using all individuals from 1KG project as reference panel. Demographic history of world populations was inferred using phased variants from the last release of the 1KG project.Secondly, MSMC models were used to analyze multiple genomes38. Non-synonymous variants in the 12 NA genomes absent from the 1KG project (phase 3) were annotated using ClinVar database to identify potential pathogenicity.The list of 56 genes recommended for reporting incidental findings by the ACMG was used as reference to identify potentially pathogenic variants−5, we identified GWAS variants present in each genome66. Variants shared by the 12 NA individuals in heterozygous or homozygous form were grouped based on their EFO. The allele frequency of these variants was compared with that of other continental populations, particularly Europeans (CEU) and Asians (CHB and JPT) from the 1KG project (phase 3) 68. Human genome data (hsapiens_genome) was used as reference set, the Benjamini-Hochberg multiple test was used to adjust for multiple testing69. Statistical significance was considered at P < 0.01. Three annotation matrix for enriched disease-associated genes were tested: (A) all genes with novel non-synonymous variants; (B) protein-coding genes with highest number of SNVs in the promoter region (above 95th percentile); and (C) genes from groups A and B combined. All analyses were performed seperately in each ethnic group.Functional enrichment  was performed using the WebGestalt online toolwww.12g-data.inmegen.gob.mx, upon request to the corresponding authors.In consistency with the respective Institutional Review Board approval and individual informed consents, genome and exome variation files will be available at Supplementary InformationPeer Review File


Nicrophorus) are relatively rare among insects in providing sophisticated parental care. Consequently, they have become model species in research analysing social evolution, the evolution of parental care and mating systems. We used the recently published N. vespilloides genome and transcriptome to develop microsatellite markers. Specifically, we developed 14 polymorphic markers with five to 13 alleles per locus and used them to investigate levels of genetic differentiation in four south Cambridgeshire (UK) populations of N. vespilloides, separated by 21 km at most. The markers revealed significant genetic structuring among populations  with all but one of the pairwise comparisons among populations being significant. The single exception was the comparison between the two closest populations, which are approximately 2.5 km apart. In general, the microsatellite markers showed lower observed heterozygosity than expected. We infer that there is limited dispersal between populations and potentially also some inbreeding within them and suggest that this may be due to habitat fragmentation. We discuss these results in the context of recent laboratory experiments on inbreeding and beetle flight.Burying beetles (genus  Nicrophorus) are relatively unusual among insects in providing elaborate parental care for their developing larvae. Reproduction centres on the fresh carcass of a small vertebrate (like a songbird or mouse), which adults locate by flight. If more than one adult of the same sex finds the carcass, they will commonly fight to determine ownership , Waresley (n = 40), Byron’s Pool (n = 33) and Madingley (n = 26) were collected during May–October 2016 using Japanese beetle traps. Male and female beetles, sampled in equal numbers, were brought back to the laboratory alive and preserved in absolute ethanol for genetic analysis. In order to avoid collecting related individuals, periodical sampling was performed and only adult beetles (not larvae) were analysed. These were males and females attracted at random to the mouse carcasses provided in the beetle traps.Adult beetles from the four south Cambridgeshire populations : GamlingN. quadripunctatus . We therefore developed new markers specifically for N. vespilloides.In an earlier pilot study, we tested microsatellite markers from unctatus , in N. vn = 139) was extracted individually from beetle heads using the DNeasy Tissue Kit . Molecular markers were developed with the program msatcommander  and expected heterozygosity (HE)). Tests for deviations from Hardy-Weinberg proportions and genotypic linkage equilibrium were estimated using GENEPOP  for microsatellite markers with at least 8 repeats for di- and trinucleotides and at least 6 repeats for tetra-, penta- and hexanucleotides, and identified 1818 sequences containing repeats. A total of 5,547 microsatellites were present and 4515 primer pairs were obtained using Primer3  per locus ranged from 0.272 to 0.841, and the observed heterozygosity (HO) ranged from 0.247 to 0.825 (E = 0.714 and HO = 0.652). The expected heterozygosity across all loci per population ranged from 0.696 to 0.706, while the observed heterozygosity ranged from 0.638 to 0.679 (All of the 139 l sample . The levto 0.825 . All indto 0.679 .Tests for concordance with Hardy-Weinberg equilibrium (HWE) revealed deviations from HWE in locus Nvesp_D, Nvesp_F, Nvesp_I, Nvesp_G and Nvesp_H . TestingFIS value was 0.085, suggesting some heterozygous deficiency. A pattern of genetic differentiation  was observed in the sampling area, with all but one significant population-pairwise FST after Bonferroni correction (α = 0.008333). In order to assess whether there were potential biases in the markers that exhibit deviations from HWE or the presence of potential null alleles, the analyses were run with and without these markers. We found that the two runs rendered similar results  also suggested some heterozygosity deficiency. We infer from these findings that there is limited gene flow between our study populations, and potentially some inbreeding as well. The consequences of inbreeding in N. vespilloides have recently been analysed experimentally in the laboratory  was Nvesp_E. However, the high number of homozygotes for this marker is unlikely to be due to null alleles because it is in HWE . We are ry e.g.,  but to ounctatus .N. vespilloides.Consistent with our interpretation of limited gene flow between populations, we found significant pairwise population differentiation between all but one pair of populations  despite the low geographical separation between the sampling sites (maximum 20.3 km). This genetic differentiation may be the result of neutral population differentiation, or the effects of selection acting on functional genes correlated with the neutral markers e.g., . We thinN. vespilloides showed that these beetles have a wide distribution of flight distances in the laboratory ranging from 68 m to 26 km. Furthermore, flight durations ranged from 61 s to 6.5 h under laboratory conditions  found that the size of these woodland fragments affects the abundance and reproductive success of the resident burying beetle population (N. americanus) have collapsed so spectacularly in recent years following substantial deforestation, causing it to become endangered  are starting to be the tool of choice for population genetics/genomics studies, microsatellites still provide a cheaper alternative. Nevertheless, we anticipate that the microsatellites we have developed will prove most useful in future work for assigning parentage  because the large brood size typically seen in ry e.g.,  and in nry e.g., . Althougry e.g., , parenta10.7717/peerj.3278/supp-1Data S1Click here for additional data file.10.7717/peerj.3278/supp-2Supplemental Information 1Click here for additional data file.


Jaera albifrons and J. praehirsuta) that occur in mixed populations and where past morphological descriptions suggested that the two species are generally reproductively isolated except in rare populations where hybridization may be happening. Using field surveys and microsatellite genetic structure analyses in two regions from France (Normandy and Brittany), we confirmed that introgressive hybridization occurs in a subset of mixed J. albifrons/J. praehirsuta populations (region Normandy) where the two species are found in the same habitat (pebbles on the shore). Moreover, we found that introgression in these populations is differential, 21 of 23 microsatellite markers showing little genetic divergence between species  while the remaining two loci were strongly differentiated (FCT = 0.428). By contrast, J. albifrons and J. praehirsuta in mixed populations from region Brittany occupied distinct habitats  with little overlap and showed stronger genetic divergence (FCT = 0.132). In hybridizing populations, the majority of individuals show morphological traits that are characteristic of one or the other species. This raises the question of the forces that act to maintain this polymorphism, noting that hybridizing populations seem to be geographically isolated from potential source parental populations and show no detectable habitat divergence between species.Sympatric species that in some populations hybridize and in other populations remain reproductively isolated open interesting research possibilities for the study of hybridization and speciation. Here, we test for such a situation in two littoral isopods ( The archetypal hybrid zone structure is a region of contact between two otherwise allopatric species. In such hybrid zones, flanked on one side by populations of one species and on the other side by the other species, the dynamics of the system is most often driven by a balance between immigration from pure parental populations and selection against hybrids . More complex spatial structures are found when the environment induces differential selection on hybridizing species and the distribution of habitats is discrete  or otherwise heterogeneous, leading to patchy hybrid zones . Fish studies have provided a few other related examples where a pair of species shows contrasted levels of reproductive isolation when in sympatry . All five species occupy a narrow but geographically extended belt in the intertidal zone and they have largely overlapping distribution ranges. In short, individuals from one species frequently coexist with individuals from at least one other species throughout their distribution range, and mixed populations are the rule rather than the exception. In this context, the five species of the Jaera albifrons group were shown to be reproductively isolated by at least three types of barriers: (1) ecological isolation , (2) sexual isolation , and (3) genetic incompatibilities  where the analysis of male secondary sexual traits and experimental crosses led them to conclude that this population contained an exceptional proportion of hybrids  to investigate the geographic structure of hybridizing populations and the nature of the isolating mechanisms, and (3) to compare genetic patterns within hybridizing vs. nonhybridizing mixed populations. For this purpose, we searched for mixed populations and morphologically intermediate individuals as described in Normandy ca. 50 years ago, analyzed the genetic structure of local populations using a panel of 23 microsatellite loci, and compared it with mixed populations from another French region (Brittany) where the two species had been described as reproductively isolated.With this study, our objectives were (1) to test for hybridization between 22.1Jaera albifrons complex are small marine crustaceans  or the European coast (J. forsmani), while the three others are more widely distributed on both sides of the Northern Atlantic  in the intertidal zone. Animals found on rocks were collected in the field using a small brush. By contrast, samples of seaweeds were brought back to the laboratory where we checked for the presence of Jaera individuals by shaking algae repeatedly in freshwater , we looked for individuals of the J. albifrons, J. praehirsuta, or “hybrid” if it gave birth to a series of males bearing J. albifrons, J. praehirsuta or intermediate morphological traits, respectively).Finally, one sampling site  or departure from random mating within sampling sites. The occurrence of null alleles, already detected in the Jaera albifrons complex with these microsatellites  is based upon estimates of genetic differentiation. We estimated the distribution of genetic variance among sampling sites within a species (FSC) and between species (FCT) in a hierarchical analysis of molecular variance . These analyses were performed using both allelic frequencies (FST‐like) and the distance between alleles (RST‐like), and significance was assessed using 10,100 permutations as implemented in arlequin. We ran these analyses first using all markers  and then for each microsatellite locus independently (locus‐by‐locus AMOVA).Our test of reproductive isolation or hybridization between FCT) in Normandy vs. Brittany , and (2) to investigate genetic structure within each species separately, in particular by testing for isolation by distance between sampling sites with spagedi 1.4  was determined via harvester v.0.6.1  gave us an estimate of the precision of membership values. Second, we performed a principal component analysis (PCA) based on all individual genotypes using the R package ade4  with and without these two loci.Finally, the distribution of genetic variance was also investigated using individual analyses without a priori grouping of samples. We first ran a clustering analysis within each region using .1 Earl,  using ΔKd Goudet . The Anc33.1J. albifrons and 80 J. praehirsuta in six sites where the two species were co‐occurring . In this region, all individuals could be morphologically identified at the species level without any overlap of traits .In Brittany, we sampled 142 J. albifrons and 57 J. praehirsuta from the three mixed populations that we found  further East  showed that individuals  of the two species and intermediate phenotypes were largely intermingled, with r Figure .3.2Ho  was on average lower than within population gene diversity He , resulting in a significant departure from Hardy–Weinberg equilibrium . These loci, except Ja94, showed signs of a null allele in more than half of populations, as tested using microchecker. While we did not detect locus‐specific HW disequilibrium patterns that were consistent across populations, the main downstream quantitative analysis  was run with and without the four loci cited above (and we report locus‐specific results as well). Genotyping error rates estimated from replicated individuals ranged from 0% to 5.88% per locus (average 1.7%) and were due roughly equally to allelic dropouts and false alleles.All microsatellite loci could be amplified in individuals of the two species  than in Normandy . Accordingly, the locus‐by‐locus AMOVA showed that most loci were less differentiated between species in Normandy than in Brittany  in Normandy region while the remaining 21 loci showed no or little differentiation . The difference in FCT between regions was significant at these two loci . We therefore checked whether the patterns found in the AMOVA  were consistent across sites. Tables FST values calculated in a simple nonhierarchical framework. Most importantly, it shows that the between‐species differentiation was consistent across sites, both in Normandy  and in Brittany . These results consider all loci, but the same geographical consistency is observed when considering the locus‐specific patterns described above (data not shown). That is, the global AMOVA results are repeatable across sites  and 0.396 (site 8) when considering only loci Ja41 and Ja64, and FST = 0.05 (site 7) and 0.056 (site 8) with all other loci).Because we studied only three mixed populations in Normandy, and one of them contained nearly only structure with K = 2, we found that J. albifrons and J. praehirsuta cluster into two clearly identified groups both in Brittany and Normandy using a panel of 23 loci , the uncertainty associated with q was larger in Normandy  than Brittany . As it turned out, the apparent genetic clustering in Normandy was almost entirely due to the effect of two loci only (Ja41 and Ja64), while a structure analysis using the remaining 21 loci showed that the two species were genetically homogeneous . Running i Figure . HoweverJ. praehirsuta traits.The results from molecular analyses of variance and clustering analyses could be well visualized using PCA performed with all 23 loci Figure . The twoThe particular geographical distribution of individuals  when considering only J. praehirsuta.Because there is ongoing hybridization and introgression between the two species in Normandy see , the wites Table , rangingJ. albifrons  and in J. praehirsuta . In line with the pairwise FST results, genetic differentiation increased more rapidly with distance in J. albifrons than in J. praehirsuta, although 95% confidence intervals calculated in genepop overlapped  and the two remaining loci where strongly differentiated (FCT = 0.384 and 0.462). Moreover, these two loci were also significantly more differentiated in the hybridizing populations (Normandy) than in reproductively isolated ones (Brittany) while showing no differentiation within each species . While this is theoretically possible, a more parsimonious hypothesis is that the two loci are encompassed in one or two genomic regions where interspecific gene flow is hampered because these regions are linked with one or several isolating barriers.The genetic homogeneity observed across species in Normandy further shows that hybridization has been introgressive, as correctly concluded by Solignac  from theAdditional indicators of a semi‐permeable barrier to gene flow are two other markers (Ja66 and Ja80) also showing a heterogeneous pattern. As most markers, they are more differentiated in Brittany than in Normandy, but, interestingly, they show a stronger differentiation than the other loci in Brittany Figure . We cann4.3J. praehirsuta x male J. albifrons) than the other. This result was obtained from experimental crosses with individuals from a hybridizing population , and the asymmetry was further confirmed by Solignac . That is, the four European species form a polyphyletic clade , and the cyto‐nuclear discordance, also certainly interesting in its own right, is not informative of recent introgression directionality. The symmetry of introgression can in some cases be evaluated by taking advantage of differences between nuclear loci , but our microsatellite dataset is too limited for this approach. Nevertheless, results of admixture analyses show that individuals showing an intermediate phenotype share more genetic background with J. praehirsuta . This can also be seen by looking at allelic frequencies at loci Ja41 and Ja64 for the phenotypically intermediate individuals, which are similar to that of individuals bearing J. praehirsuta traits and different from the frequencies observed in J. albifrons  showing intermediate morphological traits. While this figure depends on what one recognizes as morphologically pure or intermediate individuals, the majority of males clearly show strict J. albifrons that we found was located at more than 30 km from the hybridizing populations. Moreover, the mixed populations that we found in this region are geographically isolated from one another  populations at dispersal distance from our hybridizing populations, but we feel that it is unlikely. Given that these crustaceans do not have a dispersive larval phase, and given the patchy distribution of habitats, we infer from our surveys that hybridizing populations are replicated and patchily distributed.The closest population containing only J. praehirsuta  is thus most likely not one of the forces acting to stabilize the system. This interpretation needs further testing , as if this hypothesis is confirmed, it would exclude dispersal‐dependent models of hybrid zones, chief among them the tension zone model . Other classical models are also inappropriate, for they combine the tension zone balance with ecological variation, either through environmentally induced selection against hybrids  but, interestingly, parental forms coexist despite introgression in hybridizing populations in Normandy where there is probably no habitat specialization.The hybridizing populations analyzed in this study do not seem to be flanked by—or otherwise functionally connected to—pure parental populations. They seem to be independent replicates of hybridizing populations potentially distributed on a much larger geographical area than the one studied here . The influx of individuals from pure parental populations of  Endler,  or a pat Endler, . The lit Endler, . In the J. albifrons and J. praehirsuta phenotypes to coexist in hybridizing populations? Past work suggests two strong candidates. First, the strongest isolating barrier between species of the Jaera albifrons complex is sexual isolation  sexual isolation and selection against certain recombined genotypes. This situation seems to be infrequent and the conditions of persistence for such a system deserve further inquiry. In particular, it is a potential empirical example of the model proposed by M'Gonigle, Mazzucco, Otto, and Dieckmann  is acting to lower the likelihood of extinction of one or the two morphs.The second candidate is selection against hybrids. This hypothesis is supported by Solignac , p. 186,ieckmann , in whic4.5J. praehirsuta and J. albifrons hybridize when in contact in some populations and not in others? There are two obvious differences between our studied populations from Brittany and Normandy. First, where the two species were found to be nonhybridizing, they live on clearly different habitats . The two habitats are located centimeters to meters away, and a few individuals of each species were found on the habitat favored by the other species, meaning that J. albifrons and J. praehirsuta meet each other frequently in these sites . Yet these two habitats are radically different and are bound to impose a serious barrier to gene flow between species . While neither species is restricted to one of these habitats in other parts of their range, the availability of distinct habitats may play an important role facilitating the coexistence of the two species and reducing hybridization opportunities. Appropriate seaweeds can also be found in hybridizing populations from Normandy, but they may not represent a suitable habitat there . Whatever the reason, there are no Jaera on algae in the hybridizing populations reported here. One plausible hypothesis is thus that ecological diversification facilitates the coexistence and divergence of J. albifrons and J. praehirsuta wherever this is possible. Another interesting idea, suggested by an anonymous reviewer, is that hybridization allows the hybrid and subsequently J. praehirsuta to acquire adaptations to the array of challenges presented in switching from a seaweed to a rocky habitat. One avenue of research to tackle these questions will be to search for pure J. praehirsuta populations occupying rocky habitats .Why do J. albifrons and J. praehirsuta  and similar in intensity to the genetic differentiation between species observed in Brittany. This is also apparent on the PCA where the first axis partitions the genotypes in function of their geographic origin (Brittany on the left, Normandy on the right, Figure The second difference between hybridizing and reproductively isolated populations is their geographic location. Contrary to the idea that natural hybridization is the exception and not the rule in this system (Solignac, Testing these ideas will require analyzing the genetic structure of the two species over a large geographical scale and surveying mixed populations for morphological or genetic signs of hybridization in different habitat conditions.https://doi.org/10.5061/dryad.st557.Multilocus genotypes at each sampling location are available in Dryad, None declared. Click here for additional data file.


Lepeophtheirus salmonis, frustrating efforts to track louse populations and improve targeted control measures. The aim of this study was to test the power of reduced representation library sequencing (IIb-RAD sequencing) coupled with random forest machine learning algorithms to define markers for fine-scale discrimination of louse populations. We identified 1286 robustly supported SNPs among four L. salmonis populations from Ireland, Scotland and Northern Norway. Only weak global structure was observed based on the full SNP dataset. The application of a random forest machine-learning algorithm identified 98 discriminatory SNPs that dramatically improved population assignment, increased global genetic structure and resulted in significant genetic population differentiation. A large proportion of SNPs found to be under directional selection were also identified to be highly discriminatory. Our data suggest that it is possible to discriminate between nearby L. salmonis populations given suitable marker selection approaches, and that such differences might have an adaptive basis. We discuss these data in light of sea lice adaption to anthropogenic and environmental pressures as well as novel approaches to track and predict sea louse dispersal.Caligid sea lice represent a significant threat to salmonid aquaculture worldwide. Population genetic analyses have consistently shown minimal population genetic structure in North Atlantic  Lepeophtheirus salmonis) is the species most commonly infecting farmed and wild salmonids1, at considerable cost to animal health, biodiversity security, and economic growth. Conservative estimates of costs and losses attributed to sea louse infections, , significant but weak (0.0022) FST was detected across the Atlantic, with no evidence for population genetic structuring within geographic regions. More recently a genome-wide SNP array was developed and deployed using 5091 variable markers, and showed similar results in terms of population structure, alongside extensive evidence of selective sweeps and linkage disequilibrium attributable, at least in part, by the use of chemotherapeutics in aquaculture13. Besnier et al., 2014 also included a linkage map for these markers onto which the current assemble of the louse genome has been superimposed . Thus, although significant progress has been made in determining population genetic signatures of selection in L. salmonis, the goal of distinguishing louse populations occurring in different regions - a valuable component of detecting dispersal of lice between farms – remains expensive and difficult.Understanding and predicting salmon louse dispersal is a crucial element for predicting infestation, connectivity and the spread of salmon lice and associated drug resistance alleles. There have been several attempts to characterize population genetic structure in 15.). In extreme cases like Anguilla rostrata, where the organism’s reproductive ecology predicts and the genetic data support panmixia among different populations, the challenge of determining genetic differences between different populations is even greater17. Screening thousands of variable SNP markers against population genetic summary statistics may be able to detect outliers, however the identification of which markers might best assign individuals to their appropriate populations, groups, or ecomorphs necessitates further computational approaches. To this end, population genetics can usefully borrow from machine learning algorithms developed in the context of genome-wide association studies18. Such approaches have been successfully used in A. rostrata, to identify SNPs that predict rearing habitat as the result of intra-generational selection19, for example. More recently similar approaches have been employed to successfully discriminate Salmo salar populations20.Determining genetic structure in pelagic marine species has always been challenging. High rates of adult and larval dispersal impede the accumulation of neutral variation among populations and regions. Nonetheless, several studies have achieved genetic stock delineation by focusing on non-neutral or putative adaptive markers in conjunction with high numbers of SNP markers  and generated genomic SNP data using a IIB restriction-enzyme associated library preparation approach21. We then tested the power of Random Forest machine learning to reveal population structure and find the method reveals previously un-recognized population differences and fine-scale population differentiation.In this study, we identify population structure and loci under selection in Lepeophtheirus salmonis were collected in four sites around the North-East Atlantic from 18–24 month old Atlantic Salmon from commercial pens in 2015. Sites included Finnkirka (NF), Lebesby, Norway; Loch Duart (LD), Scotland, UK; Kenmare Bay (SWI), Kenmare, Ireland and Kilkieran Bay (KB), Galway, Ireland  two enzymes were selected based on potential coverage: AlfI (restrictions site ^5′(10/12)GCA(N)6 TGC(12/10)3′^) and CspCI (restriction site ^5′(11/12)CAANNNNNGTGG(12/13)3′^). Digested DNA of each sample was ligated to a pair of partially double-stranded adaptors with compatible and fully degenerated overhangs (5′NNN3′). Finally, the obtained IIb-RAD tags were amplified to introduce a sample-specific 7 bp barcode and the Illumina NGS annealing sites using two different pairs of sequencing primers. A 1.8% agarose gel electrophoresis of the PCR products was performed to verify the presence of the expected 150 bp target band . In order to ensure an approximately equimolar contribution of each sample to the library, the concentration of each PCR product was measured from the intensity of the target band in a digital image of the 1.8% agarose gel. We prepared two libraries in total, one for each IIB-REase. The purification of the libraries from high-molecular weight fragments and primer-dimers was achieved first by removing the target band on agarose gel library and eluting them in water overnight; followed by DNA capture with magnetic beads (SPRIselect® Beckman Coulter). The DNA concentration in the purified libraries was quantified with a Qubit® Fluorometer (Invitrogen) and the libraries were combined in one single pool. Two library pools were sequenced, first on a NextSeq 500, then on a MiSeq  with a single 1 × 50 bp setup using ‘Version2’ chemistry at Glasgow Polyomics (www.polyomics.gla.ac.uk), which also implemented the read demultiplexing and quality-filtering.Library preparation was undertaken as described in Wang 22 and SNPs were called using the STACKS v1.42 package with a minimum read depth of 323. The rxstacks module was used to further screen SNPs and the population module filter and export genotypes with a minimum depth of coverage of 6, minimum minor allele frequency of 0.05, maximum observed heterozygosity of 0.5 and present in at least 60% of individuals. To avoid sequence artefacts generated by low complexity in restriction enzyme recognition site, SNPs at positions 12–26 were excluded from the analysis. For those RAD tags that retained diversity after screening for artefacts, only a single SNP per locus was selected for subsequent analysis.Short reads were aligned to the reference genome in bowtie 2adegenet24. Analyses of molecular variance (AMOVA), Weir and Cockerham estimators of FST, and summary statistics  were calculated in Genodive25. P-values for FST were FDR adjusted for multiple comparisons using a Benjamini-Hochberg correction in the R-package p-adjust. Isolation-by-distance was assessed using a Mantel test implemented in the vegan R-package. Loci putatively under positive selection were identified in Lositan26 using a FDR < 0.1 significance threshold and localised on the L. salmonis linkage map  to assess genomic correspondence with a previous population genomic study13. Lositan results were plotted using in R. Further, we performed a second outlier analysis using BayeScan, as it has a lower type I error rate compared to Lositan27). We ran BayeScan with prior odds of 100 due to the small number of SNPs and detected significant outliers with a FDR threshold of 0.05 and putative outliers with a FDR threshold of 0.1. Finally, we post hoc identified overlapping outlier SNPs between BayeScan and Lositan.Principal components analysis (PCA), discriminant analysis of principal components (DAPC), and population assignment probabilities were calculated in L. salmonis reference genome using the blastn function in the EnsemblMetazoa database. We identified all genes within those 10 kb regions and when possible determined their function using the UniprotKB database.In order to identify genes potentially under positive selection we identified all genes within a 10 kb region around each outlier SNP by blasting the sequence against the randomForest package in R. Populations were numerically coded and missing data imputed using the na.roughfix command. Three independent random forest runs with 100,000 trees each were conducted and checked for convergence between runs by performing Pearson correlation between SNP importance values. The random forest algorithm randomly subdivides the full dataset into a training dataset (66.6%), which is used to train the algorithm, and a test dataset  that is used to test the classification success of a tree. For each tree, the dataset gets subdivided into new subsets and the number of trees for which the out-of-bag (OOB) error rate stabilises was chosen, reducing the risk of overfitting. The resultant ranked dataset (R2 > 0.95) was used to select a final dataset for the backwards purging approach. As in Laporte et al., all loci with an importance < 0 were removed as non-discriminatory19. Backwards purging was performed on the remaining 317 SNPs. As such each random forest run was re-implemented (three independent iterations) and after each run the SNP with the lowest importance was removed until only two SNPs were left. We determined the subset of SNPs with the highest discriminatory power based on the lowest OOB error rate, meaning the highest rank reliability of important markers, and we used this subset for further downstream analysis19.In order to detect SNPs characteristic of each population we employed a tree-based ensemble machine learning approach using the adegenet in R to visualise population structuring and assess the population assignment accuracy. Second, we performed an AMOVA and estimated pairwise Weir and Cockerham’s Fst in Genodive. We also identified the overlap between highly discriminatory SNPs and SNPs potentially under positive selection to assess the impact of selection on discriminating L. salmonis populations.In order to assess the population discriminatory power of the random forest selected SNPs we used the same methods as for the full SNP dataset. First, we performed a PCA and DAPC in et al. (2014)13. Besnier et al. (2014)13 genotyped 547 salmon lice from 12 sampling sites from 6 geographic regions for 5091 SNPs using a custom SNP array. Missing data were imputed using the na.roughfix command. We assessed the population assignment success using the DAPC approach for the full dataset before using the random forest algorithm to identify the subset of SNPs with the highest discriminatory power between sampling regions . We ran three independent random forests with 10,000 trees each and ranked SNPs based on their average importance, measured by the ‘Mean Decrease Accuracy’ (MDA). Due to the larger number of SNPs, we selected all SNPs above the lower end of the elbow in the importance value distribution . No significant isolation-by-distance was detected .In a first approach, we assessed population genetic structure using the full dataset of 1286 SNPs by several different approaches. A PCA did not reveal any population structuring across the entire range, however using pre-defined populations in the DAPC approach revealed a weak population structuring . All pairwise comparisons showed highly significant Fst-values (range = 0.081–0.096), confirming the significant discriminatory power of the random forest detected SNP subset.In order to detect population structuring among populations we utilised a random forest machine learning approach. We detected a subset of 93–101 SNPs that minimised the out-of-bag error rate to 0.1 (compared to 0.76 for the full dataset) and maximised the discriminatory power among populations Fig. . From thst of 0.233 ± 0.083 between populations  or could not be assigned to a linkage group. We further detected 46 SNPs under balancing selection .One factor that might explain the strong discrimination of sea louse populations using the subset of random forest-selected SNPs would be divergent selection pressures, such as adaptation to different drug treatments, or local adaptation to natural environmental factors. Therefore, we performed two different tests for selecting SNPs under significant positive selection. An FDist approach implemented in Lositan detected 19 SNPs under strong positive selection (FDR < 0.1) with an average Fst = 0.507). The other two putative SNPs in BayeScan were also highly significant in Lositan (p < 0.001) and were located on linkage group 1 and 4.An analysis in BayeScan detected only one SNP (FDR < 0.01) under significant positive selection and two more putatively under selection (FDR < 0.05). All three of these SNPs were also detected to be under selection by Lositan and the significant one was also the top outlier in Lositan and located on linkage group 1  detected to be under positive selection using Lositan were also identified being highly discriminatory between populations using random forest. Locus 3621, which was also identified using BayeScan, had the highest importance in the random forest analysis, suggesting that strong local adaptation and selection distinguishes sea louse populations.L. salmonis genome. Five of the 19 SNPs were in regions containing annotated genes within 10 kb, but only one of the annotated genes has been characterized. Two of the contigs with annotated genes were on linkage group 01, two on linkage group 14 and one on linkage group 6. Contig LSalAtl2s80 (linkage group 01) contained the characterized gene PSA2, which codes for the proteasome subunit alpha type protein.In order to identify specific genes potentially involved in local adaptation and under positive selection in sea lice, we explored these regions in the annotated 13. The assignment success to the geographic region of origin increased on average by 1.9% from 94.4% to 96.6% based on only this small subset of SNPs . 43 out of those 357 SNPs (12%) were labelled as ‘diagnostic’ SNPs that were included in the SNP array  to potentially distinguish populations across the Atlantic. 43 out et al. (2014), the random forest approach improved the assignment success for each population, supporting the applicability of this approach to different datasets.Even though the variation in population assignment success was greater for the larger dataset from Besnier L. salmonis populations in the North-East Atlantic and to detect signatures of selection. We were able to achieve this using a relatively small (n = 50) number of individuals genotyped across only a limited portion of the genome (c.2.3Mbp = 0.34%). An important set of discriminatory loci was identified against a background of high genetic connectivity via a random forest machine-learning algorithm and these can be exploited to distinguish between nearby sea louse populations. A high degree of overlap between loci under positive selection using genome-scan approaches and loci with high discriminatory power from random forest analysis was also observed.In this study, we used a IIb-RAD sequencing approach coupled with advanced and sensitive population genetic analyses to genetically ‘fingerprint’ Salmo salar) or resident  anadromous salmonids1. Previous population genetic studies were consistent with such high levels of dispersal12, finding no significant genetic differentiation in our study region when utilizing a set of neutral microsatellite loci. Inclusion of putatively non-neutral loci can improve population discrimination across the Atlantic (e.g10.). However, the same studies could not distinguish populations on a small geographic scale as our data and approach suggest is possible.Sea lice are known to disperse rapidly among aquaculture sites as part of the larval zooplankton as well as via the movements of migratory , in agreement with patterns that have been found previously13. The use of anti-parasitic drugs has been shown to be a strong selective pressure in sea lice and several genomic regions under selection have been linked to drug treatment13. In particular linkage groups 1 and 5 in the study showed evidence of selective sweeps, with the same region on linkage group 5 being implicated in drug resistance in a QTL analysis13. Other linkage groups, such as 14 also showed signal of positive selection in that study13. Our study similarly found that 11 out of the 19 outlier loci we identified also lay in linkage groups 1 & 14, which represents an important independent validation. Spatio-temporal variation in treatment regimes, such as rotations of different drugs or the alternative use of warm-water or freshwater treatments28, may drive the heterogeneity observed in our and previous studies. This is partly as a result of cost, perceived efficacy, as well as different regulatory conditions in the countries concerned. Even though spatio-temporal variation in drug resistance is likely to be the strongest driver of differential selection among populations, local environmental conditions can constitute further selective pressures driving allele frequency differences among populations. Local environmental variables such as temperature (e.g29.) and salinity (e.g30.), for example, can have profound effects on sea louse survival and development. Furthermore, a combination of drug treatment and increased host density is shown to influence the evolution of reproductive and life history traits31, as well as virulence in sea lice32 among different populations. However, such local adaptation is most likely linked to subtle allele frequency differences, compared to strong selective sweeps caused by drug treatments, as the selective pressure is comparably low. The combination of a few outlier loci under strong positive selection and a wide range of loci showing subtle allele frequency differences fits the expected pattern. Independent of the cause for allele frequency differences among populations, we show that a random forest machine learning approach can be used to cost-effectively distinguish even near-by sea louse populations, even with a low number of samples and genotyping density.More recent genome wide analysis of SNP variation in PSA2). The association of genomic response to selection, natural environmental conditions, and drug treatment profiles will be important considerations for future work.The use of  samples from the same site at different time points, differing in treatment regimes, could be used to disentangle the effects of drug regime and local adaption on allele frequency differences among populations and signatures of selection. Genome-scale population genetic profiling, alongside robust phenotyping, may also eventually reveal the genetic architecture underlying drug resistance and local adaptation. Here we have identified signals of selection across the genome, including markers closely associated with functional genes 34. However, biological (or genetic) confirmation of larger scale dispersal models (i.e. between lochs (=fjord) and loch systems) within and across regions is also required to assess long-range re-infestation risks for aquaculture sites. Such a strategy is of particular relevance in the light of an increasing control focus on loch-wide fallowing practices35. Furthermore, integration of genetic connectivity data with hydrographic larval dispersal models – so called ‘seascape genetics’ (e.g36.) - is likely to be more fruitful in defining any spatial-genetic correlations than crude map distances and represents an interesting further avenue for study. In this context, our data show that it may be possible to genetically ‘fingerprint’ louse populations in nearby regions to understand connectivity between them and provide a valuable tool for disease surveillance.Tools to enable parasite traceability and molecular epidemiology are an important requirement for rational sea louse control. Hydrographic modelling has been successfully deployed to understand short-range dispersal Supplementary Dataset 1