Plotosus canius  is a significant marine species in Malaysia from nutritional and commercial perspectives. Despite numerous fundamental research on biological characteristics of P. canius, there are various concerns on the level of population differentiation, genomic structure, and the level of genetic variability among their populations due to deficiency of genetic-based studies. Deficiency on basic contexts such as stock identification, phylogenetic relationship and population genetic structure would negatively impact their sustainable conservation. Hence, this study was conducted to characterize the genetic structure of P. canius for the first time through the application of mitochondrial Cytochrome Oxidase I (COI) gene, cross amplification of Tandanus tandanus microsatellites, and a total of 117 collected specimens across five selected populations of Malaysia. The experimental results of the mitochondrial analysis revealed that the haplotype diversity and nucleotide diversity varied from 0.395–0.771 and 0.033–0.65 respectively. Moreover, the statistical analysis of microsatellites addressed a considerable heterozygote insufficiency in all populations, with average observed heterozygosity (oH) value of 0.2168, which was lower than the standard heterozygosity in marine populations (oH = 0.79). This alongside the high Fis values estimation, high pairwise differentiation among populations and low within population variations are supposed to be associated with small sample size, and inbreeding system. Besides, the significant finding of this study was the sharing of common haplotype KR086940, which reflects a historical genetic connectivity between Peninsular Malaysia and Borneo populations due to the geological history of Southeast Asia during Pleistocene era. Demographic analyses showed that all populations were in an equilibrium state with no significant evidence of population expansion. To put it briefly, the current study has managed to provide an initial genomic database toward understanding of the genetic characterization, phylogenetic, molecular diversification and population structure in P. canius, and should be necessary highlighted for appropriate management and conservation of species. Further studies must be carried out involving more geographical and sampling sites, larger population size per site, and utilization of species specific microsatellites loci. Plotosus canius  that is known as grey eel-catfish, black eel-tail catfish, canine catfish or Indian catfish  gene and Tandanus tandanus microsatellites, in order to examine the accuracy of employed markers in phylogenetic study, genetic variation assignment, and population genetic structure of P. canius in Malaysia.The same conservation obstacle is hypothetically threatening ast Asia , a few risheries , fecundiisheries , feedingisheries , proteinisheries  and pharisheries . Such dePlotosus canius and 13 samples of Plotosus lineatus. Sample collection of P. canius were performed in five various districts throughout Malaysia including: Negeri Sembilan (NSN), Selangor (SGR), Johor (JHR), Sarawak (SWK) and Sabah (SBH) , Kuala Selangor (Selangor), Kukup (Johor), Bintulu (Sarawak) and Putatan (Sabah). DNA extraction protocol was performed upon sample collection in laboratory via the Wizard® SV Genomic DNA Purification System , according to manufacturer’s protocol instructions by using roughly 20 mg of specimens.Total of 130 catfish samples demonstrating two species of family Plotosidae were directly collected, including of 117 samples of ah (SBH)  from May2, 0.25 μl of each primers, 2 μl of concentrated genomic DNA, 2.5 μl of Taq buffer and 18 μl of distilled H2O as stated by To accurately amplify a 655 bp fragment of mitochondrial DNA, PCR amplification were performed by using C_Fish1 primer set  on the 5Trace files were manually end-trimmed using BioEdit software 7.2.5  regardinP. canius and P. lineatus was prompted in comparison to one haplotype of African sharp tooth catfish Clarias gariepinus (ANGBF8254-12) from Thailand as an outgroup through Neighbor-Joining (NJ) and Maximum Likelihood (ML) methods using a mutual 1,000 replication bootstrap. Next, Minimum Spanning Network (MSN) was computed using PopART  step for 10 min and a routine 4 °C final hold . AfterwaoH) was estimated using GENALEX 6.5 (eH), with 15,000 permutation and MolKin 3.0  employing admixture model and its associated frequency of allelic data was carried out using the STRUCTURE program 2.1  were identified. Once the sequencing was completed, the C_Fish1 accordingly confirmed as suitable primer set amplifying in n 600 bp . TherefoP. canius and 3 haplotypes in one population of P. lineatus , while the N. Sembilan and the Sabah populations had five and four haplotypes respectively.Preliminary evaluation of verified sequences was mainly generated 20 haplotypes in five populations of lineatus . Based oP. canius was 29% T, 27.6% C, 25.2% A and 18.3% G, while the average C + G content of selected positions was calculated as 45.9%, in P. lineatus though, calculation was 28, 28.6, 25, 18.4 and 47% respectively. Translation of all 23 haplotypes for conserved 655 bp fragment was produced 165 amino acids, which presented no signal of pseudogene in their structure. However, the sample size noticeably varied, ranging from 13–30 in collected samples of P. lineatus and P. canius from five different districts in Malaysia; in regard to the fact that original sample sizes were moderate and some sequences were failed, the actual sample collection is in the desired range recommended by P. lineatus to 54 in P. canius samples from Sarawak, While the degree of nucleotide diversity was relatively low (0.00067–0.0391) and as its consequence, the level of polymorphism and genetic variation in populations reasonably presented small portion. Besides, the degree of haplotypes diversity waved from 0.395 (Sabah) to 0.771 (Sarawak).For the 655 available COI nucleotides, 509 sites (roughly 78%) were detected as conserved sites, 146 (22%) as variable sites and 136 (21%) identified as parsim-informative sites. The average nucleotide composition in P. canius from Sarawak and Selangor. Nevertheless, the majority of P. canius pairwise distances displayed low levels of conspecific divergence roughly around 1%. The greatest genetic differences was observed between the Selangor and Sarawak (KR086937–KP221604) samples (9.7%), which is moderately reasonable due to their geographical distance. The next significantly high variances was detected between the Sabah-Sarawak pair (KP258656–KP221604) and Negeri Sembilan-Sarawak (KP258654–KP221604), although in later occasion, distance between Sarawak-Sabah sites is extraordinarily closer than Sarawak-Negeri Sembilan.The Tamura-Nei pairwise distance matrix  indicatePlotosus and one haplotype of C. gariepinus showed monophyletic status between P. canius and P. lineatus via the Neighbour-Joining method  have the lowest distance to KP258654 (SGR) and highest to KP221604 (SWK), while KR086939  have the greatest divergence from KP221604 (SWK) and smallest amount from KP258648 (NSN), as their subdivision clades illustrated.Phylogenetic analysis using the 23 haplotypes of the genus g method . As statP. canius and P. lineatus with exception of some negligible changes in topology of clades and branches.Similarly, application of Maximum Likelihood algorithm  have beeP. canius . However, there were significant distance diversity in genetic variations of almost entire evaluations among populations of Malaysia especially between the Sabah and the Negeri Sembilan populations. As expected, the most diversity were identified between P. canius populations from the Negeri Sembilan and the Sabah with the rate of 0.62504, which basically means they are nearly genetically divided due to their distance and subsequent decrease in gene flow. However, the lowest genetic distance was detected between Selangor cluster and the Johor clade by the STF values of 0.05417. Hence, it was considered that maximum sharing of genetic material occurred between Johor and Selangor Populations, while the minimum genetic similarity identified among Sabah and Negeri Sembilan sequences.Analysis of population differentiation inferred from pairwise distance of Hierarchical statistics of AMOVA  was cleaP. canius populations in Malaysia. Moreover, Tajima’s D test was negative for Selangor, Sabah and N. Sembilan populations, but not significant , the sequence of each primers and associate annealing temperatures in Fragment analysis were estimated DNA band sizes in P < 0.05). Thus, all the five microsatellites loci were considered useful for genetic applications based on the absence of consistent linkage disequilibrium in locus pairs among the studied populations.Genotyping results did not found any signal of null allele nor large allele failure, hence nor scoring inaccuracies due to stuttering. All the five microsatellites loci showed accurate and successful amplification in all populations, although heterozygous alleles were not found in all populations. One microsatellite loci (Tan 3-27), was evidently monomorphic in all populations while Tan 1-2, Tan 1-10, Tan 1-7 and Tan 3-28 were polymorphic in at least one population. After implementing the sequential Bonferroni adjustment , only foFurthermore, after Bonferroni adjustment, nine out of the 25 (36%) microsatellite loci still showed deviation from Hardy-Weinberg Equilibrium (HWE), which might be owing to heterozygote deficiency effects . HeterozP. canius populations. The fact that the two loci did not show any signal of deviation from HWE in three populations may imply the probability that the estimated deviations could have been originated from either the occurrence of uncertain structure or inbreeding among these three population divisions (Fis (P < 0.05) estimations have been considerably diverse from zero, except in locus Tan 1-2 from Sabah. This alongside with substantial departure from HWE indicates the damaging effect of heterozygote deficiency within associated populations. However, the positive calculated estimations could be translated as decrease in heterozygous levels among offspring in population, mostly owning to non-random mating and its subsequent inbreeding. On the other hand, negative Fis estimates might be indication of increasing in heterozygosity level, which could usually occur as a result of random mating system, hence genes should be probably more different  showed relatively lower values, even in comparison with their neighbouring populations, theoretically demonstrating the populations that endured inbreeding or genetic drift since their isolation from other populations. Similarly, the Negeri Sembilan and Sabah  populations also showed small but significant variances in relation to their close neighbour populations.nd Johor . The curnd Johor , suggestP. canius populations owning to eH and Ar oscillation on which eH extending from 0.0000–0.6769 (Selangor) and Ar varied from 1–3 (Negeri Sembilan and Selangor). Obviously, two significant clusters could be seen among established populations of P. canius in this study, one cluster with low allelic richness and eH estimations (Johor samples using locus Tan 1-2 and locus Tan 1-10), and another cluster with relatively acceptable eH and allelic richness (the other four populations using locus Tan 3-28 and locus Tan 1-7). However, the genetic variation in the current study was highly reliant on microsatellites and their sequences as the engaged loci did not specifically develop for P. canius. Moreover, allelic frequencies among virtually each combination of population pairs showed highly significant differentiation (STF < 0.05) (Levels of genetic variations seem to be widely fluctuated between  < 0.05) , implyinP. canius were basically distributed into five minor clusters using Bayesian analysis. Consequently, the initial highest membership value (q) of the studied populations including Negeri Sembilan, Sabah, Selangor, Sarawak, Johor was estimated as 0.941, 0.983, 0.968, 0.988, and 0.986 respectively (K (isolated clusters)  . Regarditforward , Bayesia Sarawak .P > 0.05  estimations . Furtherulations .P. canius to be submitted into barcoding data set. The first and the most common outcome of the undergone experiment could be the involvement of two common haplotype. While the most common sequence was KR086940 between populations of Selangor (n = 7), Sarawak (n = 6), and Johor (n = 9), the KR086939 identified as second common haplotype sharing between Johor (n = 6) and Negeri Sembilan (n = 4). Nevertheless, the most significant finding should be the occurrence of shared haplotype between Selangor, Johor  populations and the Sarawak (Borneo) population. The haplotype sharing and their consequent gene flow could practically happen due to several reasons such as breeding migration, mutation, pelagic larvae, and sharing of common ancestors  and South China Sea currents (Sarawak) might also be questionable. In the Strait of Melaka, circulation of currents (particularly in surface) are due to effects of tidal patterns and wind, while the route of both surface and deep layer currents are shown to be relatively the same and toward northwest  could not be estimated but the P. canius populations were regarded as being in a stable state, possibly for a long period of time. Nevertheless, comparison of θ1 and θ0 parameters for all populations indicates a relatively slow growth rate in female populations of P. canius except in the Sabah population.Demographic history analyses did not found any evidence of recent population expansion in all P. canius, while the lowest level was detected in Tan 3-27. Moreover, the Selangor population showed maximum number of alleles (9), whereas the Johor and Sarawak populations exhibited the lowest (6). Similar instance of low allelic variation have been described in Bolbometopon muricatum  and anadromous fish species (oH = 0.68)   . In factn Island  and Clarephalous , while i44–0.57) . Several44–0.57) . Certaintructure . Alternatructure  at whichP. canius used for population genetic analysis purposes should be quite small based on Fis values and inbreeding have been practically assessed and documented in many studies (P < 0.05) of Fis estimations. This alongside with substantial departure from HWE would indicate the damaging effect of heterozygosity deficit within the populations.Small sample size of collected populations might also be measured as a major parameter in detection of low heterozygosity variation because of the failure to accurately detect the entire extant alleles of the selected populations, hence, deficiency in heterozygote identification . Indeed, studies . The posP. canius ranging from 0.05417–0.62504, showing significantly high structuring among studied populations except differences between Johor–Selangor samples (STF = 0.05417) and Selangor–Negeri Sembilan (STF = 0.09806). Moreover, AMOVA statistics evidently revealed that approximately 64% of genetic variations were due to within population variations. Hence, the fairly high STF rates, significant hierarchical molecular results and consequent higher genetic variances among P. canius populations in Peninsular Malaysia and their relatives in Borneo, in addition to the detection of only one sharing haplotype (KR086940), would suggest the absence of contemporary gene flow among them most probably due to the geological modification, consequential rise in marine water levels and historical continental separation during the Pleistocene era . The present patterns of differentiation among catchments is believed to be significantly as a consequence of the Pleistocene associated historical and geological continental and sea level distraction and its subsequent isolation of lands and populations  high sensibility of mitochondrial COI gene in detection of variation  weaariation  and (3) ariation .P. canius used for population genetic analysis is ostensibly quite small based on One of the most common practical problems, which is believed to be mostly associated with microsatellite primers (due to higher mutation rate) is well-known as homoplasy . HomoplaeN) comparing to freshwater species  as observed in the Sabah population. Nevertheless, the COI gene revealed sufficient informative interpretation of relationships among the five populations, supporting by reasonable bootstrapping values (> 85%). The sharing of haplotypes between a few samples from Peninsular Malaysia and their Sarawak counterpart of Borneo showed the sensitivity of the COI marker to infer the biogeographical history of P. canius and potentially other marine taxa in the region.The current genetic characterization of P. canius showed slightly different patterns of structuring in comparison with the COI findings. Nevertheless, both markers detected higher level of among population differentiations than within population variability. In addition, four main clusters or genetic stocks of P. canius were identified using the cross species amplification study of T. tandanus microsatellites.Microsatellites analyses on the population structure of P. canius, in particular, and the genus Plotosus, in general. However, further studies must be conducted using more geographical and sampling sites, larger population sizes per site. Furthermore, designing species specific hypervariable nuclear markers such as microsatellite for P. canius must be considered in order to accurately analyze the population structure and genetic diversity of P. canius before implementation of advanced fisheries and conservation strategies.Finally, the results from this study has provided valuable understandings on the genetic characterization, molecular phylogeny, evolutionary kinship, and population structuring of 10.7717/peerj.1930/supp-1Supplemental Information 1Phylogenetic Analysis and Population Genetic Study of Plotosus canius  from Malaysian coastal waters.Click here for additional data file.10.7717/peerj.1930/supp-2Supplemental Information 2Click here for additional data file.


The origin of the Etruscan civilization  is a long-standing subject of debate among scholars from different disciplines. The bulk of the information has been reconstructed from ancient texts and archaeological findings and, in the last few years, through the analysis of uniparental genetic markers.N = 98) with other population groups from the main hypothetical source populations, namely, Europe and the Middle East.By meta-analyzing genome-wide data from The 1000 Genomes Project and the literature, we were able to compare the genomic patterns  of present day Tuscans  values and genetic distances point to Eastern Anatolia/Southern Caucasus as the most likely geographic origin of the main Middle Eastern genetic component observed in the genome of modern Tuscans.The data indicate that the admixture event between local Tuscans and Middle Easterners could have occurred in Central Italy about 2,600–3,100 years ago (y.a.). On the whole, the results validate the theory of the ancient historian Herodotus on the origin of Etruscans. Herodotus says that the Etruscans came from Lydia. The question is whether this is correct. My answer is: yes, but the Lydians lived at that time  in another area. The question of the origin of the Etruscans is one of the most debated problems of antiquity. Nowadays most scholars are convinced that they came from Asia Minor (Turkey); only in Italy does a large number of scholars deny or doubt this. The eastern origin seems certain to me, for reasons that I will present below (2.i). However, an important part of the problem has not been solved: where exactly in Asia Minor did they come from, and was this in Lydian territory, as Herodotus says?”. Other historians, such as the Hellenistic scholar Dionysius of Halicarnassus (30 BC) contended that the Etruscans were an indigenous population that developed in situ from the so-called Villanovan culture (autochthonous theory). In the same line, the archaeologists Barker & Rasmussen The Etruscan civilization refers to the ancient culture inhabiting the territories of Etruria in the Early Iron Age, approximately 700 to 200 BC  which could be dated to 2,300 y.a., and noted that approximately 10% of the Tuscans in their sample actually belong to this branch of the typical Middle Eastern haplogroup U7 – thus adding further support to the results by Achilli et al. The recent study by Ghirotto et al. Genetics has recently contributed to our understanding of the origin of Etruscans through the analysis of DNA markers from present-day people from Tuscany and ancient DNA recovered from Etruscans or their presumable descendants. Most of these studies have targeted the mitochondrial DNA (mtDNA) molecule, in particular portions of its control region. One of the pioneering genetic studies, Francalacci et al. When all the genetic evidence obtained so far are taken together, it seems clear that the Etruscans cannot be regarded as ancestral of all modern-day Tuscans; however, almost all the studies agree that there is a proportion of their mtDNA pool that could be traced to somewhere in the Middle East, thus testifying to an ancient connection between both regions. While the age of the Middle Eastern founding U7b1 lineage http://www.1000genomes.org; The present study aims to further investigate the controversial biological origin of the Etruscans by analyzing genome-wide SNP data (>540.000 SNPs) from 98 Tuscans genome-wide genotyped within The 1000 Genomes Project ; PC1 separates Central Europeans (GBR+CEU) from Tuscans in two well-differentiated clusters and occupying two opposite poles of the plot; in between fall the Iberians (IBS and SPA) and North Italians (NIT). This analysis indicates the distinctive nature of the Tuscans in the context of Europe, even when compared to other neighboring North Italians. Corroborating evidence comes from further exploring patterns of IBS values between European population sets, Figure S1B shows that IBS values are statistically different when comparing TSI against North Italians ; while other comparisons such as CEU vs. GBR are not statistically significant  ; which is consistent with the PCA analysis . A third PCA was carried out in order to further explore the genomic affinities of Tuscans with the bMEA and Europe  for each population set.IBS values were computed for all the genome population datasets Table 1.ST values between TSI and all the other population groups from Europe and bMEA are shown in ST values are for the population pair TSI-EUR, followed by the pairs TSI-ARM, TSI-GRG, TSI-IRN, TSI-SPH, TSI-LZG, and TSI-SYR, and TSI-TRK  the results clearly reveals a major differentiation of AFR, CHB, bMEA and EUR, but also the admixture nature of TSI regarding EUR and bMEA. A second analysis of ADMIXTURE was carried out for EUR, TSI, and different bMEA populations considering K = 2 We used ALDER to estimate the date of admixture between TSI and bMEA populations. The first analysis was carried out using bMEA. ALDER yields a range of age for the admixture event with bMEA of 53–103 generations (average: 78), which considering a generation age of 30 years, equates to 1,590–3,090 y.a. ; Text S1), these values range from 26.7  to 18 ; 22% on average. These estimates are comparable to the values obtained using ADMIXTURE (∼30%).ALDER also estimates the membership proportions in TSI with respect to the source populations. The contribution from Middle East to TSI when comparing to bMEA is 26.2% (±7.9), but it drops to 21.1% (±8.4) when using the most likely source populations from bMEA (Turkey and South Caucasus). When excluding the Jews profiles from the analysis  indicate that these few North Italians differentiate from Tuscans but the analysis is also compatible with recent gene flow between them.The present study aimed to add further insight into the origin of the Etruscans by analyzing present-day Tuscans, which are assumed to be at least in part their descendants. There are several lines of evidence in the literature indicating that the DNA of modern populations in Tuscany as well as DNA from ancient Etruscans have genetic signatures of a recent historical ancestry from the Middle East. All of this evidence, however, comes from the analysis of uniparental markers (mtDNA). The present study goes beyond previous work in that it presents the first genome-wide based approach aimed to disentangle the origin of Tuscans and their presumable genetic connections with the ancient Etruria and the Middle East. The few Tuscans analyzed before by Chaubey et al. ST values), which point to a closer genetic proximity of TSI with the CAU , and Turkey (TRK and SPH). The fact that the main non-European signal in Tuscan genomes comes from CAU (and not from e.g. West Turkey) cannot be explained only by a geographic gradient across Eurasia related to geographic distance.Admixture analyses carried out on autosomal SNPs corroborates the admixture nature of Tuscans between Europe and the Middle East; with values of Middle Eastern ancestry of about 22–30%; this component is substantially larger than that previously detected using mtDNA data  and TRK recurrently appear in most of our analyses as the most closely genetically related to TSI, it can be tentatively suggested that the most likely source population in the bMEA contributing to (at least part of) the Middle Eastern component observed in modern Tuscans (TSI) could have inhabited the territories located between Turkey and the CAU. Given the proximity of Lydia (West Turkey) to this region and the age admixture estimates obtained in the present study, the hypothesis formulated by Herodotus on the geographic origin of Etruscans could not be fully disregarded.http://admixturemap.paintmychromosomes.com) indicates that the proportion of admixture coming from Armenia, Georgia, Syria and Jordania is 27.6% in total; being Armenia the main source population (10.7%). Their estimate for the admixture event is younger  than the age obtained in our study, but these estimates were obtained using other datasets (including e.g. Morocco).The present findings on admixture proportions in Tuscans fit quite well with the information extracted from the atlas of human admixture recently published by Hellenthal et al. The dating calculated in the present study is in good agreement with the age of the Middle Eastern haplogroup U7 lineages  identified in the Isle of Elba (Tuscany) by Brisighelli et al. Figure S5): (i) the emergence of a distinctive population (proto-Etruscans) in south/southeast Middle East ∼5000 y.a., (ii) this small group of Middle Easterners could have travelled westwards to a region located in South Caucasus/East Turkey and from here further West crossing Anatolia and arriving at Lydia (West Turkey); this process would involve an interval of time allowing for assimilation of genetic features from indigenous people, and (iii) this population could have left the West Mediterranean shores and journeyed towards Central Italy before 2,600–3,100 y.a. The Etruscan culture could have emerged at about the time of arrival of these Middle Easterners. This model integrates the different elements observed in the genomes of present-day Tuscans: notable in features of the mtDNA variation inherited from the Proto-Etruscan sources, and a clear signature from South Caucasus and Turkey in their patterns of autosomal variation.In order to accommodate the different findings, we propose the following multi-step demographic scenario , we took advantage of previous bioinformatic developments ftp://ftp.1000genomes.ebi.ac.uk/vol1/ftp/release/20110521/). All the rs codes defined on Behar et al.'s article n = 13) North Italians analyzed in Chaubey et al. Figure S1); this analysis involved 542,305 SNPs (as a result of merging NIT with the other Europeans).Genome population data were downloaded from two different repositories. SNP data representing different Middle Eastern populations were firstly obtained from Behar et al. Text S1). A summary of the populations used in the present study is given in Text S1.Individuals having a familial relationship were detected as done in Gómez-Carballa et al. PLINK was also used to deal with strand differences between SNP sets. For some analyses and for the sake of simplicity, the Middle Eastern population sets (including South Caucasus) were grouped in a single group, namely, “broad Middle East” (bMEA).ST estimator Identity-by-state (IBS) values were computed from SNP data using PLINK ST values. PCA was carried out using the function cmdscale (library stats) from R (http://www.r-project.org).In order to discriminate clusters of genetic variation in the population sets analyzed, principal component analyses (PCA) were carried out on a matrix of pairwise individual IBS and FAdmixture in Tuscans was estimated using different source populations in Europe and bMEA. ADMIXTURE software Dating of admixture was carried out using ALDER ST and IBS values between TSI and Middle Eastern populations was carried out using SAGA v. 2.1.1 (http://www.saga-gis.org/). We followed the commonly used ordinary Kriging method for interpolating FST and IBS values; other interpolated methods yielded virtually the same results.The spatial geographical representation of Fhttp://www.perl.org) scripts were used to display results obtained from the different software packages used.In-house R and Perl Click here for additional data file.Figure S2PCA carried out as in  but highlighting the gravity center for each population group ; individual profiles are displayed in grey color.(TIF)Click here for additional data file.Figure S3ST values between TSI Histograms of Weir and Cockerham's Fvs. CEU and different populations in MEA. Population colors in histograms are as in the rest of the figures. The inset histograms show more detail for the distribution of FST values ranging from 0.05 and 0.40.(TIF)Click here for additional data file.Figure S4Bar-plots of individual ancestries as computed using ADMIXTURE for different values of K considering TSI and main continental groups, AFR, EAS, EUR, and bMEA  and cons(TIF)Click here for additional data file.Figure S5The map shows IBS interpolated values between TSI and Middle Eastern populations with colors ranging from dark green  to yellow . The non-colored map regions were not interpolated.(TIF)Click here for additional data file.Text S1Estimation of familial relationship between the individuals analyzed in the present project, and statistical analysis removing Jewish subject and considering a Finnish population, FIN, collected from The 1000 genome Project).(DOCX)Click here for additional data file.


Phoebastria nigripes), a Near-Threatened philopatric seabird, are still controversial. Here, we employ double digest RADseq to quantify the extent of genomewide divergence and gene flow in this species. Our genomewide data set of 9760 loci containing 3455 single nucleotide polymorphisms yielded estimates of genetic diversity and gene flow that were generally robust across seven different filtering and sampling protocols and suggest a low level of genomic variation (θ per site = ∼0.00002–0.00028), with estimates of effective population size (Ne = ∼500–15 881) falling far below current census size. Genetic differentiation was small but detectable between Japan and Hawaii (FST ≈ 0.038–0.049), with no FST outliers. Additionally, using museum specimens, we found that effect sizes of morphological differences by sex or population rarely exceeded 4%. These patterns suggest that the Hawaiian and Japanese populations exhibit small but significant differences and should be considered separate management units, although the evolutionary and adaptive consequences of this differentiation remain to be identified.Evaluating the genetic and demographic independence of populations of threatened species is important for determining appropriate conservation measures, but different technologies can yield different conclusions. Despite multiple studies, the taxonomic status and extent of gene flow between the main breeding populations of Black-footed Albatross ( Given limited resources for nature conservation, it is important to develop criteria for the prioritization of species protection efforts and a taxonomy that adequately reflects underlying genetic diversity. The concepts of evolutionary significant units (ESUs) and management units (MUs) were proposed nearly 30 years ago Ryder  as heuriFST values between pairs of populations are often lower when based on microsatellites than when based on sequence-based markers, with the latter better reflecting population subdivision when it exists or being less constrained due to heterozygosity or statistical effects.Different types of genetic data can be used to determine and delimit ESUs and MUs, each with its own set of advantages and disadvantages. Each marker will estimate the demographic history of that marker, and, as a result, findings and implications for conservation may differ from marker to marker  is a seabird endemic to the North Pacific, with an age of first breeding of 6–7 years and a demographic generation time of approximately 18 years  taxonomy working group rejected a petition for these Japanese and Hawaiian populations to be considered separate subspecies due to a lack of supporting data ACAP , but thiIn the current project, we investigate the seeming contradictions between these previous studies using a comprehensive nuclear data set obtained through double digest RADseq. For the reasons discussed above, we argue that this methodology can provide more reliable population parameter estimates for conservation purposes than other markers. Our principal aim, partially motivated by the need to provide the ACAP with the additional information required to determine the phylogenetic status of the Japanese population, is to resolve whether and to what extent the Hawaiian and Japanese populations of the Black-footed Albatross represent two distinct populations. Based on previous studies and high levels of breeding philopatry  in three different breeding areas, during the breeding period: 19 in 1996 from Izu-Torishima Island, sometimes also referred to as Torishima, , 11 in 1994 from Midway Island  and 17 in 2000 from Tern Island   inline barcode, and equimolar concentrations of eight uniquely barcoded individuals were pooled and double-indexed by 16 cycles of high-fidelity PCR  with Illumina barcodes, resulting in a unique combination of inline and Illumina barcodes for each individual. The PCR products were pooled in equimolar quantities and sequenced in one lane of a rapid run of an Illumina HiSeq 2500 sequencer at the Bauer Core facility at Harvard University, producing 100-bp paired-end reads.DNA was extracted from the blood samples using the Qiagen DNeasy  and Omega E.Z.N.A . DNA extraction kits, following the manufacturers’ protocols for blood samples, except for an increased enzyme digestion time (overnight). DNA concentrations were measured with fluorometric quantification . Double digest RAD sequencing libraries for each individual sample were prepared according to the protocol of Peterson et al. , using eprocess_radtags in Stacks 1.06  due to low sequence coverage. Finally, we used the populations module in Stacks to create data matrices  for subsequent analyses, with a minimum stack depth of 30. To study the effects on genetic estimates of different SNP filtering protocols, removal of low-frequency alleles and differences in sample sizes among populations, we analysed seven different data sets (numbered 1 through 7) produced from different SNP filtering protocols (Tables S2 and S3) with varying numbers of individuals and minor allele frequency (MAF) and heterozygosity requirements  with Ensembl assembly number 4.0  with Ensembl assembly number 3.2.4  and 300 000 Markov chain Monte Carlo samples (NUMREPS = 300 000). We combined the replicate result files using CLUMPP v 1.1.2  between sites for loci in data set 1 with more than one SNP, to determine the level of non-independence of SNPs. For these calculations, we randomly chose eight individuals from each population because an imbalanced sample size can bias the calculation of r2.In addition to the summary statistics estimated with Stacks, we estimated additional related population genetic estimates both to confirm trends suggested by Stacks and to provide additional resolution to the demographic history. We first used STRUCTURE 2.3.4 . To minimize bias due to different people performing the measurements, we took great care to describe the measuring protocol to the measurer in detail. Specimens were classified as belonging to either the Hawaiian or Japanese population, and as male or female. A specimen was assigned to a given population if it had been ringed there as a chick or caught there as an adult during the Black-footed Albatross’ breeding period (November to June). Birds caught at sea or caught at locations of interest outside of the breeding period were excluded from the analysis. The aim was to obtain measurements of wing chord, beak width, culmen length and tarsus length for all specimens, but, depending on the preparation method, certain measurements could sometimes not be taken. Sample sizes for wing chord, tarsus length, culmen length and beak width, respectively, are as follows: Japan males: 8, 9, 9, 9; Japan females: 7, 7, 8, 8; Hawaii males: 9, 8, 9, 8; and Hawaii females: 9, 10, 8, 7 (Table S4).anova) to determine whether Japanese Black-footed Albatrosses differed significantly in size from Hawaiian Black-footed Albatrosses for the different measures, controlling for sex.We used R Commander 2.0–3 to perform a factorial analysis of variance . From this set of loci, a total of 3455 SNPs (variable sites) were found among 2769 (28.4%) of the loci, resulting in a data matrix that was 80.4% complete across all SNPs and individuals . Of these 2769 loci, 2234 had only one SNP, 418 had two, 91 had three, 21 had four, and 5 had five or more. Additional information on the results based on data set 1 can be found in TableWe obtained a total of 78 803 224 paired-end reads, each 100 bp, across 47 individuals in the three albatross populations. The catalogue built from Stacks contained a raw total of 115 359 loci. Filtering procedures in R2 = 0.961, P-value <0.0001), suggesting that the SNPs are randomly distributed across the avian genome  mapped more than once. The higher percentage of mapped loci to the Zebra Finch genome is likely because the Black-footed Albatross and Zebra Finch share a more recent common ancestor than either does with the chicken  exhibiting –0.3 Fig. confirmeπTern = 0.165, πMidway = 0.160 and πTorishima = 0.152. Examining both variant and invariant loci, values varied from πTorishima = 0.00060 to πTern = 0.00065 (Table S2). All other data sets also had π values of 0.0006, except data set 7, for which π = 0.0008  and 0.040 . Pairwise FST values were consistent among data sets, with FST-Midway-Tern always being lower than the two other FST values .Estimates for genetic diversity as calculated by Stacks in each population for data set 1, examining polymorphic loci only, were as follows: K = 1–5 (not shown), but maximized at K = 3 clusters, whereas K = 5 was favoured by the Delta K test , because STRUCTURE can be sensitive to linked loci. The results of the other six data sets were qualitatively similar. The log-likelihood of the model was very similar across For data sets 1–6, using the first three PC axes and two discriminant axes, the DAPC plot shows that individuals from Hawaii cluster together as one population, while the Japanese individuals cluster as a distinct population Fig.B. EigenvUsing MIGRATE, estimates of genetic diversity (Θ = 4Nμ) varied depending on the model and on the data set used, ranging from 0.025  to 0.0029 . In general, in contrast to the results for π from Stacks, Θ decreased with the number of SNPs in the data set. However, results are consistent in that they all indicate similar levels of genetic diversity in all three populations. Across data sets and models, there was no population with consistently lower or higher estimates of Θ. Estimates of Θ for the entire species were sometimes higher but sometimes lower than estimates for individual populations, and ranged from 0.0102 to 0.0067, with a mean of 0.0088 (0.0001 per bp). Even the highest estimates of Θ suggest a low level of genetic diversity in the species as a whole.π and Θ, because under neutrality, both of these parameters estimate 4Nμ. Assuming a mutation rate for noncoding DNA in birds of 1.5 × 10−9 per site per year .Using standard population genetic theory for a single population at equilibrium, we estimated the effective population size of the species from our estimates of Ellegren  and a vaEllegren  yields aMaximum-likelihood estimates of gene flow measured on the scale of mutations (m/μ) for all data sets varied from 10.0  to 210.0  . All Izu-Torishima individuals were assigned to a single population, and almost all individuals from both Tern and Midway were assigned to the Midway population, with two of the Midway individuals assigned to Tern. Overall, these results corroborate the pattern of high gene flow between Japanese and Hawaiian colonies, with little differentiation within Hawaii.anova . No statistically significant differences in size between males and females were found, except for slight differences in beak length and width: on average, males’ beaks were 1.3 mm broader  and 3.2 mm longer  than females’. This represents a difference of 4.5% and 3.1% in width and length, respectively. Between Japan and Hawaii, the tarsus of Japanese individuals was, on average, 11.9 mm longer than that of Hawaiian individuals , representing a 12% difference in length. The wing chord of the Japanese individuals was on average 9.1 mm shorter, a 1.8% difference, although this result was not statistically significant at the 0.05 level . Japanese albatrosses also had shorter beaks, by 3.2 mm on average , representing a 3.1% difference in length  was ten times that in our study , exhibit genetically very distinct breeding populations with little dispersal between sites , falls in this second category, according to a study by Young based on mitochondrial DNA (b evolution were lower in large bodied Procellariformes such as albatrosses, suggesting that slow rates of molecular evolution might be part of a general syndrome of this clade.Our results are applicable to other albatross species, due to distinctive shared life-history traits that can influence evolutionary rates. For example, albatrosses have an exceptionally long life expectancy that is 20–40 times higher than that of a typical songbird. Among albatross species other than rial DNA . Nunn anrial DNA  found thAfter evaluating the genetic differentiation between the Japanese and Hawaiian Black-footed Albatrosses, we compared these two populations morphologically. In particular, we tested the claim that Japanese individuals are smaller than their Hawaiian counterparts. Contrary to what is commonly found in the literature, we did not find Japanese Black-footed Albatrosses to be uniformly smaller than their Hawaiian counterparts. We did find some statistically significant morphological differences among geographical categories of birds (longer tarsus in Japan, longer culmen in Hawaii; TableIn summary, our results indicate that the absolute level of genetic differentiation between the Hawaiian and Japanese Black-footed Albatross population is small, that estimated levels of gene flow are high and that individuals from the two populations do not differ markedly in size. Despite this, our study does show that the Japanese and Hawaiian populations are detectably genetically differentiated. These results illustrate the challenges faced when interpreting population dynamics estimates based on genetic data for the purpose of species management. From an evolutionary perspective, which focuses on long timescales, the two populations are unlikely to constitute separate ESUs, especially considering our estimate of gene flow, which is high enough to prevent genetic drift and population divergence Wright . This coNevertheless, because of low levels of genetic and morphological differentiation, we reject our initial hypothesis that the Japanese population is sufficiently differentiated to deserve subspecific status, and support the ACAP’s decision not to consider the Japanese population a separate subspecies of the Black-footed Albatross. Radio telemetry or banding data on individual birds’ movements between the different Black-footed Albatross colonies would help refine our understanding of gene flow in this species and patterns of philopatry. Between 1980 and 2007, 13 854 chicks were banded on Tern Island, and recaptures of breeding birds in Hawaii started in 1992 (Véran et al.


Polysiphonia morrowii, native to the North Pacific (Northeast Asia), has recently been reported worldwide. To determine the origin of the French and Argentine populations of this introduced species, we compared samples from these two areas with samples collected in Korea and at Hakodate, Japan, the type locality of the species. Combined analyses of chloroplastic (rbcL) and mitochondrial (cox1) DNA revealed that the French and Argentine populations are closely related and differ substantially from the Korean and Japanese populations. The genetic structure of P. morrowii populations from South Atlantic and North Atlantic, which showed high haplotype diversity compared with populations from the North Pacific, suggested the occurrence of multiple introduction events from areas outside of the so‐called native regions. Although similar, the French and Argentine populations are not genetically identical. Thus, the genetic structure of these two introduced areas may have been modified by cryptic and recurrent introduction events directly from Asia or from other introduced areas that act as introduction relays. In addition, the large number of private cytoplasmic types identified in the two introduced regions strongly suggests that local populations of P. morrowii existed before the recent detection of these invasions. Our results suggest that the most likely scenario is that the source population(s) of the French and Argentine populations was not located only in the North Pacific and/or that P. morrowii is a cryptogenic species.The red alga  Interoceanic human activities  have favored interconnected seas and oceans, enhancing species dispersal and increasing the risk of introduction into coastal marine ecosystems  originating from Asia; however, patterns of genetic diversity suggest that shipping is the main vector of recurrent introductions in Australasia, and aquaculture is responsible for the introduction and the spread of the species in Europe  described by Harvey in 1853 based on the individuals collected in the East Sea at Hokkaido , has been reported in various marine ecoregions of the world , the South Atlantic , and the North Atlantic . In addition, 105 specimens sampled in France for a previous study  according to the manufacturer's protocol. The chloroplastic rbcL gene and the mitochondrial cox1 gene were amplified using an Eppendorf thermocycler following the protocols described in Guillemin et al. (rbcL gene was amplified with the pair of primers rbcL‐F (5′‐CWAAAATGGGATATTGGGAT‐3′) and rbcL‐R (5′‐CTATACAYTHGYTGTTGGAGTTTC‐3′). cox1 gene was amplified with the pair of primers GazF1 (5′‐TCAACAAATCATAAAGATATTGG‐3′) and GazR1 (5′‐ACTTCTGGATGTCCAAAAAAYCA‐3′). Reaction mixtures  contained 0.5× PCR buffer (Abgene), 125 μmol/L each dNTP, 1 pmol each primer, 2.5 mmol/L MgCl2, 1 U Taq polymerase (Abgene), and 3 μL of DNA (1:25 dilution); PCR cycling included an initial denaturing step at 94°C for 3 min, followed by 35 cycles at 94°C for 45 sec, 50°C for 60 sec, and 72°C for 90 sec with a final elongation step of 72°C for 7 min. The same thermocycler conditions were used for both loci. Finally, PCR products were purified and sequenced by LGC genomics . The sequences were edited and aligned using Codoncode Aligner v. 3.7 (www.codoncode.com).DNA was extracted from 5 to 10 mg of dry algal tissue using the Nucleospinn et al.  and Saunn et al. , respectrbcL and cox1 sequences were obtained for 521 Polysiphonia morrowii individuals including 353 individuals from introduced populations and 168 from its native range. Molecular diversity indices, haplotype diversity  and nucleotide diversity , were calculated for each sampled location and for each region using Arlequin v 3.11  in France based on n = 25, excluding two locations for which sample size was too small (Perros‐Guirec and Mediterranean), (2) in Argentina with n = 11, and (3) in Korea with n = 7 excluding one location (Seogeondo). To compare haplotype diversities across sampling locations, rarefaction was used to correct for unequal sample sizes (n = 10). Haplotype richness estimates were calculated using EstimateS 9.1.0  was implemented in Arlequin v 3.11  were observed . Chlorotypes differed by 1–4 bp  were unique to a single region: C2 was found only in the North Atlantic, C10 was found only in the North Pacific, and four chlorotypes  were found only in the South Atlantic  defining 10 mitotypes were observed . Pairs of mitotypes were separated by 1–7 bp  and greater haplotype richness (rh ranged from 1.4 to 2.5) than the other sites . We identified the same unique cytoplasmic type C1_M3 in Rothéneuf, Saint‐Malo, Perros‐Guirec, and the Mediterranean Sea : Both the sample data and the Chao1 estimate curves leveled off , in the South Atlantic, which was not the case in the other two regions. Finally, the analysis indicated that the diversity of the cytoplasmic types was not described in its entirety for any of the three regions.Rarefaction analysis of the off Fig. . HoweverH) and nucleotide diversity (π) for the chloroplastic and the mitochondrial markers are given in Table H) were similar for rbcL and cox1, regardless of the region considered . The genetic diversity of the native populations (North Pacific) varied widely among locations. The populations of the Dugok, in GyeongNam Province, Korea, showed relatively high diversity (H = 0.69 for rbcL and H = 0.56 for cox1), whereas the populations from locations on Jeju island were much less variable (H = 0.00 for rbcL and H = 0.00–0.56 for cox1) (Table H = 0.48 for rbcL and H = 0.43 for cox1), whereas the populations of Saint‐Malo showed no variation at all (H = 0.00 for rbcL and H = 0.00 for cox1). In introduced regions, a reduction in genetic diversity was observed in the South Atlantic region compared with the North Atlantic region  is given in supplementary material (Table S1).Over the whole dataset, the number of chlorotypes was similar to that of mitotypes, regardless of the region: 5, 5, and 5 chlorotypes versus 6, 8, and 2 mitotypes, for the North Pacific, North Atlantic, and South Atlantic regions, respectively , where it was accidentally introduced  was identical to that detected in Thau lagoon on the French Mediterranean coast  suggests that P. morrowii may have been accidentally introduced during the deliberate import of Pacific oysters Crassostrea gigas. Oyster transport has been shown to be a major vector of recurrent seaweed introduction in Europe  and four private chlorotypes C5, C6, C7, and C8 detected only in Argentina contradicts this scenario. There are at least three possible origins of these private cytoplasmic types in Brittany and Argentina. First, the phylogenetic analysis indicated that these cytoplasmic types derive from other Asian populations that were not sampled, requiring additional, extensive sampling to detect them. Second, these chlorotypes may correspond to a previous, older introduction in the North Atlantic during the last two centuries. Third, chlorotypes C2, C5, C6, C7, and C8 are all associated with five different mitotypes, possibly corresponding to native lineages of P. morrowii that have gone unnoticed in Brittany .Click here for additional data file.Appendix S1. Sampling and genetic information for 521 individuals.Click here for additional data file.Appendix S2. Unique DNA sequences for each mtDNA and cpDNA haplotype.Click here for additional data file.


Linearbandkeramik-Alföldi Vonaldiszes Kerámia and Cardial/Epicardial cultures. We also searched for possible signatures of the original Neolithic expansion over the modern Near Eastern and South European genetic pools, and tried to infer possible routes of expansion by comparing the obtained results to a database of 60 modern populations from both regions. Comparisons performed among the 3 ancient datasets allowed us to identify K and N-derived mitochondrial DNA haplogroups as potential markers of the Neolithic expansion, whose genetic signature would have reached both the Iberian coasts and the Central European plain. Moreover, the observed genetic affinities between the PPNB samples and the modern populations of Cyprus and Crete seem to suggest that the Neolithic was first introduced into Europe through pioneer seafaring colonization.The genetic impact associated to the Neolithic spread in Europe has been widely debated over the last 20 years. Within this context, ancient DNA studies have provided a more reliable picture by directly analyzing the protagonist populations at different regions in Europe. However, the lack of available data from the original Near Eastern farmers has limited the achieved conclusions, preventing the formulation of continental models of Neolithic expansion. Here we address this issue by presenting mitochondrial DNA data of the original Near-Eastern Neolithic communities with the aim of providing the adequate background for the interpretation of Neolithic genetic data from European samples. Sixty-three skeletons from the Pre Pottery Neolithic B (PPNB) sites of Tell Halula, Tell Ramad and Dja'de El Mughara dating between 8,700–6,600 cal. B.C. were analyzed, and 15 validated mitochondrial DNA profiles were recovered. In order to estimate the demographic contribution of the first farmers to both Central European and Western Mediterranean Neolithic cultures, haplotype and haplogroup diversities in the PPNB sample were compared using phylogeographic and population genetic analyses to available ancient DNA data from human remains belonging to the  Since the original human expansions out of Africa 200,000 years ago, different prehistoric and historic migration events have taken place in Europe. Considering that the movement of the people implies a consequent movement of their genes, it is possible to estimate the impact of these migrations through the genetic analysis of human populations. Agricultural and husbandry practices originated 10,000 years ago in a region of the Near East known as the Fertile Crescent. According to the archaeological record this phenomenon, known as “Neolithic”, rapidly expanded from these territories into Europe. However, whether this diffusion was accompanied or not by human migrations is greatly debated. In the present work, mitochondrial DNA –a type of maternally inherited DNA located in the cell cytoplasm- from the first Near Eastern Neolithic populations was recovered and compared to available data from other Neolithic populations in Europe and also to modern populations from South Eastern Europe and the Near East. The obtained results show that substantial human migrations were involved in the Neolithic spread and suggest that the first Neolithic farmers entered Europe following a maritime route through Cyprus and the Aegean Islands. Linearbandkeramic (LBK) cultural complex, brought the Neolithic to the central European plains and from there to the British Islands and Scandinavia  while the Mediterranean one, associated to the Cardial-Impressa cultural complex, spread it along the Mediterranean coast up to the Atlantic façade of Iberia The term “Neolithic” refers to the profound cultural and technical changes that accompanied the transition from a hunter-gatherer subsistence economy to an agro-pastoral producing system The nature of the diffusion of the Neolithic and the possible demographic input associated to it have been widely debated. In this regard, two extreme hypotheses representing opposite views have been formulated: the demic diffusion model (DDM) and the cultural diffusion model (CDM) Genetic analyses from modern and ancient populations have contributed extensively to this debate providing discordant results. Principal component analysis and spatial autocorrelation of allele frequencies of “classic” genetic markers in modern European populations showed a South East to North West cline compatible with a Neolithic DDM. The Neolithic contribution to the modern genetic pool was estimated in this case to be around 27% In the light of these results, the usefulness of modern genetic variability to reconstruct the Neolithic dynamics in Europe has been questioned vs assignment of mtDNA haplogroup dating categories respectively) could be responsible of the observed differences During the last decade, ancient DNA analyses of Neolithic populations have provided a more reliable picture of the Neolithic transition process at a local scale. Studies have concentrated at the two edges of the two routes of the Neolithic wave of advance: Central/Northern Europe and the Iberian Peninsula/Southern France. In Central Europe and Scandinavia a DDM has been proposed to explain the observed genetic discontinuity between hunter-gatherers and the first farmer populations In this framework, the knowledge of the original Neolithic genetic pool in the Near East seems essential to correctly identify the variants associated to the Neolithic spread and also to provide a more global picture of the Neolithic dynamics in Europe.In order to examine the genetic background existing in the first Neolithic communities and its impact over the European genetic pool, we have studied 3 archaeological sites in Syria located in two geographic areas in which agricultural practices were first documented: the middle Euphrates valley and the oasis of Damascus . These sThe obtained results allowed us to put into context ancient DNA results from available European Early Neolithic populations, to draft a general model of the Neolithization in Europe and to propose probable routes of expansion of the first Neolithic communities.DNA preservation at the studied samples was assessed at three levels: (1) Estimating the number of copies of the target mtDNA in some of the extracts using a specific Real Time PCR design, (2) estimating the percentage of reproducible Hypervariable Segment I mitochondrial DNA (mtDNA-HVS1) sequences out of all the analyzed samples and (3) computing the miscoding lesions in clone sequences.4 in Tell Halula and 1.1×106 in Tell Ramad, corresponding respectively to 7.44×10−5 and 7.60×10−4 ng/µl  to 0.0303 (sample H68) in Tell Halula and from 0.0006 to 0.0101 in Tell Ramad, indicating a differential preservation across the samples . Damage http://www.ncbi.nlm.nih.gov/genbank) with accession numbers KF601411- KF601425.Reproducible mtDNA HVS1 sequences were obtained from 15 out of 63 skeletons from the archaeological sites of Tell Halula and Tell Ramad . The aliIn 10 cases it was possible to reconstruct the complete haplotype , while the extent of degradation of the remaining 5 samples only allowed the recovery of partial haplotypes. Nine different haplotypes were identified. Two of them were shared between 2 individuals of Tell Halula (16311C) and among 3 individuals of Tell Ramad (16224C 16311C 16366T). Motif 16293C, though, was present at both sites, pointing at a pre-existing common genetic pool in the region.The complete haplotypes were compared to a database of 9,821 mtDNA profiles from 59 modern populations from the Near East and South Eastern Europe and 2 Early Neolithic populations from Central Europe  were not represented in any of the modern and ancient populations of the database. From the remaining haplotypes only 16224C 16311C, the basal node of haplogroup K, was shared with the other two ancient populations, displaying a frequency of 9.52% in the Cardial/Epicardial dataset and of 23.08% in the LBK-AVK. This haplotype is distributed nowadays both in South Eastern Europe and the Near East with an average frequency of 4%. However, some populations such as Ashkenazi Jews, Csángó and Cyprus exhibit frequencies of this haplotype higher than 10% .The remaining haplotypes had a very limited geographic distribution, being only documented in 1 individual from Bulgaria (16311C-K); 3 individuals from Turkey, Qatar and Yemen (16223T-L3); 4 Irani, Karakalpak, Turkish and Bedouin individuals (16256T-H) and 3 Druze from Israel (16224C 16311C 16366T-K).MtDNA haplogroups could be assigned to 14 out of the 15 skeletons according to the HVS1 sequences obtained and on the diagnostic Single Nucleotide Positions (SNPs) typed following Phylotree rCRS oriented version 15  and S6.N = 6, 42.8%) followed by R0  and H . The observed haplogroup frequencies were compared to those of 59 modern populations from the Near East and South Eastern Europe and 2 Early Neolithic populations from Central Europe   .Haplogroup K was present in almost all populations compared, and its mean frequency in South Eastern Europe and the Near East was around 7%. It reached its highest frequencies in certain populations that have experienced recent population bottlenecks, such as the Askhenazi Jews and the Csángó in Transylvania, Romania Finally, the skeleton H8 belonged to the African L3 lineage, this being the most prevalent African haplogroup found in present-day Near Eastern populations.Principal Component Analysis with Hierarchical Clustering (PCA-HCA) was used to compare mean haplogroup frequencies of our dataset  with theThe first six Principal Components (PCs), accounting for a 90.6% of the variance, were selected for Hierarchical Clustering Analysis. Six clusters (1–6) were defined based on the topology of the hierarchical tree . The decThe two biggest groups detected were Clusters 1 and 3, joining 43 of the 60 populations of the database. Cluster 1 mainly included European populations and it was distinguished by high frequencies of haplogroups H, U5, U4 and HV0 and by low frequencies of Asian and African types . Near EaCluster 2 included our PPNB sample, grouped together with Ashkenazi Jews, Csángó, Cyprus and Cardial/Epicardial populations. High frequencies of haplogroups K and N* characterized this cluster , pinpoinCluster 4 included populations from Africa or with a strong African component and it was defined by high frequencies of African haplogroups (L and U6) and low frequencies of haplogroup H. Western Asian populations were clearly separated from Near Eastern datasets in clusters 5 and 6. Both were distinguished by a high frequency of Asian haplogroups and a low frequency of European types. The inclusion of Romani population within cluster 5 is in agreement with its Asian origins The partition model proposed here supports the existence of geographic barriers for mitochondrial markers. Major geographic zones like Europe, the Near East and Eastern Asia are clearly distinguished. However, populations at boundary zones such as the Caucasus are clustered both with European and Near Eastern pools.The PCA-HCA for the two first PC factors, accounting respectively for 48.32% and 19.78% total genetic variation, is represented in Cluster 2 was clearly distinguished from the other 5 clusters by PC4, which summed up a 6.64% of the global genetic variability . The graST genetic distances were computed between the PPNB and the other populations of the database , Ashkenazi Jews , Csángó  and Khoremian . These populations also exhibited the lowest FST values. The highest significant distances corresponded to Gilaki, Caucasian Jews and Mazandarian populations (FST>0.2).Pairwise Fdatabase . Non-sigST values with the modern Near Eastern pool, as previously stated ST index between LBK-AVK and the pooled Southern European populations was lower than the one reported by When modern populations were grouped in geographic regions, the PPNB population was genetically closer to Near Eastern and Caucasian than to Southern European populations . The CarST distances between the PPNB and the modern populations were plotted in a contour map  and Cyprus. From this region genetic distances gradually increased westwards across the Balkans, southwards to the Arabic Peninsula and eastwards through the northern Zagros to the Caspian Sea. Peaks of low distance were also detected in the Carpathian basin, Yemen and in North Uzbekistan, South from the Aral Sea.Ftour map . The mapi.e contaminant, endogenous and damaged) could be ruled out through replication, as they occur at random and are not reproducible in different amplifications and extractions from the same or different skeletal samples i.e. H4, H7, H28, H25; H3, R64-4II, R69(2) and R65-14, R65-C8-SEB, R65-1S) could be also discarded as they were processed in different extraction and amplification batches and validated through independent replications, some of them conducted in two different laboratories.One of the inherent limitations of ancient DNA human studies is the possibility of contamination with exogenous DNA, a risk that is enhanced when human DNA is studied and a PCR approach is used. As a result a series of authentication criteria were proposed early at the beginning of the discipline Even though the success recovery ratio is low (23.8%), this study demonstrates that it is feasible to recover ancient DNA genetic information from temperate environments and suggests that other variables rather than the temperature operate in the DNA preservation through several millennia.Ancient DNA preservation in Near Eastern open-air sites has been previously stated In recent years, the body of ancient DNA data of Neolithic populations has increased dramatically, providing a more accurate picture of local Neolithic dynamics. Some of these studies have also explored the Mesolithic genetic background, interpreting the results in terms of continuity or genetic break with the predecessor hunter-gatherer communities of the area The present study shows that even though the mitochondrial variability of the PPNB population is within the limits of modern Near Eastern, Caucasian and South Eastern European populations , both haAll the detected haplotypes but one -the basal node of haplogroup K- have a null or limited distribution in the modern genetic pool, suggesting that a great bulk of ancient Neolithic lineages were not integrated into their succeeding populations or were erased by subsequent population movements in the region. This is in agreement with previous observations from other Early Neolithic populations Our PPNB population includes a high percentage (80%) of lineages with a Palaeolithic coalescence age  and differs from the current populations from the same area, which exhibit a high frequency of mitochondrial haplogroups J, T1 and U3 . The latHaplogroup J is present in moderate frequencies in Central European LBK-AVK populations (11.75%) and it has been proposed as part of the Central European “mitochondrial Neolithic package” These findings suggest that (1) late Neolithic or post-Neolithic demographic processes rather than the original Neolithic expansion might have been responsible for the current distribution of mitochondrial haplogroups J, T1 and U3 in Europe and the Near East and (2) lineages with Late Paleolithic coalescent times might have played an important role in the Neolithic expansive process. The first suggestion alerts against the use of modern Near Eastern populations as representative of the genetic stock of the first Neolithic farmers while the second will be explored in depth in the following section.The sharing of mitochondrial haplotypes and haplogroups between pre-pottery farmers from the Fertile Crescent and European Neolithic populations, suggests a genetic contribution of the first Neolithic communities in the European mitochondrial genetic pool.Haplogroup composition and PCA-HCA of the three ancient datasets compared here allow us to identify K and N*-derived haplogroups as potential Neolithic genetic contributors. Haplogroup K is present in all Early Neolithic datasets published so far with frequencies ranging from 7.7 to 43% . MoreoveStarčevo-Criş-Körös cultures) should be considered in order to explain the available data for Neolithic populations of Central and Northern Europe. To solve this uncertainty, ancient DNA analysis from the Balkans region seems of vital importance.Haplogroup N1a, representing 12.75% of LBK-AVK samples The signal of both rare N-derived haplogroups over the Neolithic genetic pool must have been erased by subsequent genetic drift events after the consolidation of Neolithic practices, as it has been suggested in other works In the absence of ancient genetic data from populations in the primary and secondary Neolithization areas, a detailed comparison of the genetic composition of the PPNB population with modern adjacent populations can shed light on possible routes of Neolithic expansion.As for modern Near Eastern populations, the frequency distribution of PPNB mitotypes in modern South Western European populations is limited see  and S7. The absence of an equivalent detectable genetic pattern in modern South-Western Anatolia suggests a primary role of pioneer seafaring colonization through Cyprus and the Aegean islands along the southern coast of Anatolia to the western coast of Greece.This observation is supported by three facts:The archaeological parallels found between the pre-pottery Neolithic of the Levant and those of Cyprus and the Aegean islands in terms of radiocarbon dating, settlement architecture, material culture, cereal and domestic animal species provide evidence for a sea-mediated arrival of Levantine people to Cyprus soon after the development of the agriculture, during the late PPNA or early PPNB, and a further expansion towards the Aegean The finding of PPNB lineages (U*) together with a high frequency of haplogroup K (16%) in a recent survey of Minoan mtDNA indicates a pre-Bronze arrival of these genetic traits of the island. Moreover, this result is in agreement with the archaeological information pointing at a Near Eastern Neolithic origin of the Bronze Age Cretan culture Spatial interpolation of radiocarbon dates has identified the Middle Euphrates-South Turkey region as the original centre of Neolithic expansion, and the maritime route through Cyprus, Crete and the Aegean islands as the primary route of Neolithic expansion from the Near East An alternative scenario of land-mediated expansion through Western Anatolia would assume a survival of the genetic traits observed in the PPNB sample until the end of the period, when Middle-PPNB descendant populations would have expanded to secondary, adjacent areas of Neolithization around 7,500–7,000 years B.C. In conclusion, the study of ancient DNA from the original geographic areas of Neolithic expansion performed here suggests a demic contribution of the first Near Eastern Neolithic in both main European routes of Neolithic expansion. Moreover, the population comparative analysis performed here points out at a leading role of seafaring colonization events in the first Neolithic expansions reaching the European continent. Further ancient DNA data from other primary and secondary areas of Neolithization and new data from frontier zones will be needed to add more resolution over the routes of expansion and the extent and nature of the genetic impact of the Neolithic over the European genetic pool.The studied material consisted of 63 ancient human skeletons from 3 different archaeological sites dating back to the PPNB time period .2 documented more than 40 occupation levels with thousands of stratigraphic units. A continuous occupation of the site can be assumed between 7,900–5,700 cal. B.C., spanning from the PPNB to the Neolithic-Chalcolithic transition  Tell Halula is located in the Middle Euphrates basin, 150 Km East of the city of Aleppo in the present territory of Syria. Excavations in the site, 8 hectares in area, have been in progress for the last 18 years by a Spanish Archaeological Mission in Syria. The excavations performed over an area of 2,500 mThe Tell Ramad archaeological site is located 20 Km south of Damascus on the slopes of Mount Hermon, in a basaltic plateau 830 m in height at the end of the river Wadi Sherkass, which flows in the Damascus basin. Human occupation was documented from early PPNB to ceramic Neolithic Dja'de El Mughara is located on the left bank of the Middle Euphrates, also in Syria. The excavations revealed three historical horizons corresponding to Early PPNB , Pre-Halaf ceramic Neolithic  and Early Bronze Age . The burial patterns found at the PPNB levels are very similar to those documented at Tell Halula and Tell Ramad with the graves located under the floor of the houses, but big collective funerary practices were also documented All the collected samples were neither washed nor treated after excavation. After collection, the samples were sent directly to the laboratory, where they were immediately studied. Contamination prevention measures were taken during all the selection processes, including the use of gloves and face shields. All the researchers involved in the handling of the samples during and after the excavation were typed for mtDNA .Whenever possible two samples -preferably teeth- were taken from each individual. Clean and unbroken samples without visible fissures were selected, and then deposited in a sterile container until processed. The surface of all samples was removed with a sandblaster  and subsequently UV-irradiated (254 nm) for 30 minutes on all sides. Cleaned samples were finally ground to a fine powder in a cryogenic impact grinder filled with liquid Nitrogen .Approximately 600 mg of the obtained powder was washed a minimum of 3 times with 8 ml 0.5 M EDTA pH 8, and then incubated over-night at 37°C in 10 ml of lysis buffer solution  in a hybridization oven. Tissue remains were removed by centrifugation and DNA was extracted from the supernatant with Phenol/Chloroform. The aqueous phase was concentrated by centrifugation dialysis using Centriplus 30,000 micro-concentrators (Millipore) and desalted with 15 ml sterile water (Braun) to a final volume of 300 µl. Extraction controls without powdered sample were processed in parallel to detect contamination during the extraction process.A region of 305 base pairs (bp)  of the mtDNA-HVS1 was amplified in the obtained extracts in two overlapping fragments. HVS1 fragment amplification was used as a screening method to detect the presence of amplifiable DNA in the studied samples. Samples were discarded if two consecutive amplifications produced no results.PCR amplification. In the laboratory at the Universitat de Barcelona, nested-PCR reactions using outer and inner primers (Taq Expand High Fidelity PCR buffer (Roche), 2 mM MgCl2 (Roche), 0.2 mM dNTP mix (Biotools), 0.4 µM of each primer and 0.06 U of Taq Expand High Fidelity (Roche). Nested amplification reactions were subjected to 30 cycles (first reaction) and 40 cycles (second reaction from the first amplified DNA solution) in a Perkin Elmer TC1 Thermocycler , with an initial denaturation step at 94 °C for 5 min and a final elongation step at 72 °C for 5 min. In the laboratory at Universidad Complutense de Madrid, one-round PCR reactions were set up in a final volume of 25 µl using the Multiplex PCR Kit (Qiagen)  and 0.2 µM of each outer primer). This kit has proven to be extremely efficient for the amplification of ancient DNA Two strategies were adopted for the HVS1  primers  were perPCR purification Kit according to the manufacturer's instructions.In this case, the cycling conditions using an Eppendorf Mastercycler consisted of 40 cycles of 30 s at 95°C, 90 s at 54°C and 60 s at 72°C, with a previous activation cycle of 15 min at 95°C and a final extension cycle of 10 min at 72°C. Amplicons were visualized in a 2% agarose gel stained with Ethidium Bromide and purification was performed directly from the amplification reaction using the Qiagen PCR product were added to a final volume of 10 µl containing 3 µl of the kit and 16 pmol of the selected primer. Cycling sequencing was performed in an Eppendorf Mastercycler according to the supplier's recommendations. Amplification products were analyzed on an automated sequencer ABI PRISM™ 310 .Sequencing reactions were performed with the Dye-Terminator Cycle Sequencing Reaction Kit vs 1.2  with one internal primer . Six microlitres of the A detailed account of the extractions and amplifications performed can be seen in PCR Kit (Qiagen)  and 0.2 µM of each primer). The cycling conditions using an Eppendorf Mastercycler consisted on 40 cycles of 30 s at 94°C, 90 s at 50–54°C  using mitochondrial primers (Only consistent HVS1 amplifications displaying the same mutation pattern between different extractions and PCRs were cloned using the pGEM-T Easy Vector System (Promega).  primers . The cycDirect and clone sequences were aligned to the revised Cambridge Reference Sequence rCRS,  and diffMitochondrial haplogroups were assigned to the amplified samples considering the information of both the HVS1 and the coding region SNPs according to the rCRS oriented version of PhyloTree Build 15 and Haplogrep The number and type of miscoding lesions per sample were computed from the clone alignments manually in the PPNB sample excluding priming sites. The values were normalized by dividing for the number of clones per PCR and the number of sequenced base pairs. Mutations and insertions/deletions within poly-C tracts  were not considered.To provide a frame of comparison for our results, miscoding lesion values were computed in the same way in the clone alignments of two datasets of Mesolithic and Early Neolithic temperate environments Taq-Man Real Time assay was used for the specific quantification of mtDNA HVS1  in the obtained extracts using a Taq-Man-MGB probe 5′ - AATACTTGACCACCTGTAGTAC  and primers L16123 (forward)  and H16209 (reverse) . PCR reactions were performed using TaqMan Universal PCR Master Mix (Applied Biosystems). The samples were loaded onto a standard 96-Well Reaction Plate (Applied Biosystems) and fluorescence detection was performed in a Sequence Detection System ABI Prism 7700 (Applied Biosystems). Four negative controls were included per plate. The DNA concentrations of the extracts were derived from comparison with serial dilutions of a known concentration of human mtDNA standard . All extracts were quantified twice and the average values were considered.A PCR reactions and post-PCR procedures were physically separated. (4) Access to extraction and PCR laboratories was restricted to two researchers (EF and CG), who wore clean-room protective clothes, gloves and facemasks. (5) The laboratories were routinely cleaned with bleach and UV-irradiated. (6) The samples and reagents were manipulated in laminar flow hoods, which were previously cleaned with bleach and irradiated with UV light (254 nm) for 30 minutes. (7) Exclusive material for ancient DNA analysis was employed in every experimental process. (8) Before the analysis, plastic material and pipettes were placed in the cabinet and UV-irradiated for 30 minutes. (9) All individuals were independently extracted at least twice in two independent laboratories except in two cases  Samples were collected on the field by staff trained in ancient DNA analysis. (2) Collected samples were unwashed to prevent pre-laboratory contamination. (3) All the analyses were performed in exclusive ancient DNA laboratories in which extraction, preparation of ases see , S3. (10ases see . (13) Th SeThese criteria not only meet but exceed in different aspects other ancient DNA reports from Neolithic populations ad hoc (Python). Haplotypes were converted into sequences using Haplosearch A database of 9821 mtDNA-HVS1 haplotypes from 59 modern populations from the Near East and South Eastern Europe and 2 Early Neolithic datasets from Central Europe An additional database of haplogroup frequencies was built using published haplogroup data of 11,610 individuals. The same populations used for the haplotype database were included when haplogroups where known. Haplogroup frequencies from other populations not including published haplotypes were also used.A description of the populations included in both databases is provided in The 95% confident interval was calculated for the frequencies of the mitochondrial haplogroups found in the PPNB sample in the three ancient population datasets , in the three modern meta-populations  and in the pooled modern population using non-parametric bootstrap with replacement in SPSSvs21.0 The number and percentage of shared haplotypes between our PPNB population and the other populations in the database, and the number and percentage of individuals in the database carrying PPNB haplotypes, were estimated using the Arlequin software, version 3.5 ST genetic distances post-hoc to correct for multiple comparisons with the Benjamini-Hochberg method p.adjust in R Pairwise FST values calculated between the PPNB population and the other populations in the database were graphically plotted in a map using Surfer version 9 (Golden Software). Ethnic groups with disperse geographic location were not considered in the analysis , DECISIA, France; The 15 mtDNA sequences reported in this paper have been deposited in Genbank with accession numbers KF601411- KF601425.Figure S1Geographic location of modern populations used for phylogenetic and statistical comparisons. Ethnic groups with unclear or disperse geographic location are not represented. Population labels are described in (TIF)Click here for additional data file.Figure S2Hierarchical tree built using haplogroup frequencies from PPNB, modern and ancient populations from the database. Cluster partitions are indicated in colors.(TIF)Click here for additional data file.Figure S3Plot of the third and fourth principal components of the PCA-HCA performed using population haplogroup frequencies. Population grouping in 6 clusters after HCA is indicated in colors: Cluster 1 (green), Cluster 2 (red), Cluster 3 (orange), Cluster 4 (light blue), Cluster 5 (grey), Cluster 6 (dark blue). Population labels are described in (TIF)Click here for additional data file.Table S1PCR quantification results of extracted ancient DNA. Rn: Normalized Reporter; Ct: Threshold cycle. SD: Standard Deviation; CV: Coefficient of Variation.Real time (DOCX)Click here for additional data file.Table S2DNA extractions and HVS1 amplifications performed. The number of amplifications per mtDNA HVS1 is indicated. Fragment 1: HVS1 positions 16,126–16,258. Fragment 2: HVS1 positions 16,258–16,369. Laboratory 1: Universitat de Barcelona, Laboratory 2: Universidad Complutense de Madrid, c Cloned amplifications. * Reproducible amplifications not cloned.(DOCX)Click here for additional data file.Table S3Sequence alignment of direct sequences and clones of the studied samples. Direct and clone sequences have been aligned to rCRS PCRnumber/C followed by the clone number. In direct sequences, the clone number is replaced by “DIR”. Boxes in the reference sequence indicate primer annealing regions. Different types of DNA molecules are highlighted in colors. Pink: Endogenous sequence; Grey: Staff contaminant DNA; Yellow, green and violet: Carry-over contaminant sequences. Miscoding lesions and Taq polymerase errors are also highlighted as follows: Blue: Type I miscoding lesions; Green: Type II miscoding lesions; Orange: Other lesions. The last sheet contains the estimated number and percentage of miscoding lesions per position and skeleton.(XLS)Click here for additional data file.Table S4Description of the 60 modern and 2 ancient Near Eastern and European populations used for comparison.(XLSX)Click here for additional data file.Table S5Distribution of the PPNB haplotypes in the populations included in the haplotype database.(XLSX)Click here for additional data file.Table S6DNA extractions and coding region SNP amplifications performed.(DOCX)Click here for additional data file.Table S7MtDNA haplogroup frequencies of PPNB and populations of the database. Sheet 1: Absolute frequencies, Sheet 2: Relative frequencies, Sheet 3: 95% confident interval (CI) for haplogroup frequencies found in the PPNB sample, Sheet 4: Plots of haplogroup frequencies in modern and ancient populations from the database. Only haplogroups present in the PPNB, Cardial/Epicardial and LBK populations are displayed. Population labels are described in (XLSX)Click here for additional data file.Table S8Details of the PCA-HCA performed over haplogroup frequencies of the PPNB sample and the other populations of the database. Population labels are described in (XLSX)Click here for additional data file.Table S9ST values between the PPNB sample and the populations included in the haplotype database.Pairwise F Sheet 1: FST values, Sheet 2: P values corrected by the Benjamini-Hochberg method (XLSX)Click here for additional data file.Table S10Archaeological and anthropological information of the studied samples. Tooth samples are labeled according to FDI World Dental Federation nomenclature when the type of tooth is known. Other cases are labeled as follows: I: Incisor, C: Canine, P: Premolar, M: Molar. Definitive teeth are labeled in upper-case letters and deciduous teeth in lower-case letters. Dental germs are indicated by “g” before the tooth nomenclature.(DOCX)Click here for additional data file.Table S11HVS1 mtDNA sequences of the research and laboratory staff involved in sample handling. Only positions 16,126–16,369 are presented.(DOCX)Click here for additional data file.Table S12Mitochondrial DNA primers used in this study.(DOCX)Click here for additional data file.