The golden snub-nosed monkey (Rhinopithecus roxellana), an endangered primate endemic to China, has experienced a rapid reduction in numbers and severe population fragmentation over recent years. For this study, we measured the DRB diversity among 122 monkeys from three populations in the Qinling Mountains, and estimated the relative importance of different agents of selection in maintaining variation of DRB genes.Maintaining variation in immune genes, such as those of the DRB sequences, in which five alleles were novel. We found high DRB variation in R. roxellana and three branches of evidence suggesting that balancing selection has contributed to maintaining MHC polymorphism over the long term in this species: i) different patterns of both genetic diversity and population differentiation were detected at MHC and neutral markers; ii) an excess of non-synonymous substitutions compared to synonymous substitutions at antigen binding sites, and maximum-likelihood-based random-site models, showed significant positive selection; and iii) phylogenetic analyses revealed a pattern of trans-species evolution for DRB genes.We identified a total of 19 DRB diversity in these R. roxellana populations may reflect strong selection pressure in this species. Patterns of genetic diversity and population differentiation, positive selection, as well as trans-species evolution, suggest that pathogen-mediated balancing selection has contributed to maintaining MHC polymorphism in R. roxellana over the long term. This study furthers our understanding of the role pathogen-mediated balancing selection has in maintaining variation in MHC genes in small and fragmented populations of free-ranging vertebrates.High levels of The online version of this article (10.1186/s12862-018-1148-7) contains supplementary material, which is available to authorized users. The DR β (DRB) genes, especially exon 2, which encodes functionally important antigen binding sites (ABS), has been extensively studied in mammals [MHC alleles defines the range of antigens that the immune system can identify and fight-off [MHC polymorphism as a consequence of an arms-race between pathogens and the host’s immune system [The e genome . This mue genome , 3. Specectively , 5. The  mammals –8. Variaight-off . Thus, pe system .MHC have been recognized: heterozygote advantage, negative frequency dependent selection, and fluctuating selection [MHC variation.Three forms of balancing selection that may maintain variation in the election , 10, 11.ω  and is the most common method used [ω should not significantly deviate from one [ω is significantly greater than one this indicates positive selection, and in the case of MHC genes, balancing selection due to host/pathogen coevolution [ω is significantly less than one, this indicates negative/purifying selection [MHC genes, in which the same advantageous MHC alleles are conserved across distinct evolutionary units in spite of differentiating evolutionary processes [Three methods are often used to detect balancing selection. First, natural selection can be estimated via calculating the selection parameter hod used , 12. Accfrom one . When ω volution . Converselection . Second,rocesses . Third, rocesses .MHC is still unclear, because various evolutionary factors can affect MHC variation and may mask any effects of balancing selection [MHC diversity [In practice, the role of balancing selection in maintaining adaptive variation in the election . More spiversity , 20.Rhinopithecus roxellana) is an endangered primate endemic to China. Although once widespread in China, wild R. roxellana populations now only occur in fragmented populations in Sichuan, Gansu, Hubei and Shaanxi provinces. This study was conducted in the Qinling Mountains, Shaanxi province, the major east-west mountain range of China. These mountains provide a natural boundary between northern and southern China, and support much biodiversity. Within the Qinling Mountains, there are 39 known R. roxellana populations comprising a total of ~ 4000 individuals [R. roxellana population by more than 50% over the past 40 years, with R. roxellana being classified as endangered since 2008 by the IUCN [The golden snub-nosed monkey  to assess genetic diversity have provided much information on phylogenetic relationships and demographic history [R. roxellana [MHC variation under pathogen-mediated coevolution in different Qinling Mountains R. roxellana populations is unknown.Previous studies of  history , 27. Foroxellana . UnfortuMHC genes and microsatellite loci in three Qinling Mountains R. roxellana populations, ii) identify different agents of selection (including positive selection and trans-species evolution) and the roles they may play in maintaining variation in MHC diversity, and iii) evaluate the potential for balancing selection for MHC genes in R. roxellana populations. This study furthers our understanding of pathogen-mediated balancing selection at MHC genes in small and/or fragmented populations of free-ranging vertebrates.In this study, we i) measure genetic variation of R. roxellana samples were collected from three populations in the Qinling Mountains, including 32 hair samples from Foping (FP), 36 fecal samples from Ningshan (NS), and 54 hair samples from Zhouzhi (ZZ)  at − 20 °C. Both individual identification and sample collections complied with the animal welfare laws and constitutions of China. DNA was extracted from hair samples according to a Chelex protocol  . Fecal DDRB exon 2 fragments. To amplify the exon 2 of the DRB genes in R. roxellana, a primer pair  was used [DRB exon 2 is 270 base pairs (bp). The primer pair amplified a 270 bp product, which contains 247 bp of exon 2 and 23 bp of intron 1. PCR was performed in 50 μL of reaction mix containing 10 mM Tris-HCl (pH 8.4), 50 mM KCl, 2.5 mM MgCl2, 0.4 μM of forward and reverse primers, 0.2 mM of each dNTP, 1 unit of ExTaq DNA polymerase , and 10–100 ng of genomic DNA. Amplification was carried out in a Veriti™ 96-Well Fast Thermal Cycler  under the following conditions: initial denaturation at 94 °C for 5 min, followed by 35 cycles of denaturation at 94 °C for 30 s, annealing at 60 °C for 30 s and extension at 72 °C for 30 s, finishing with a final extension at 72 °C for 10 min.Overall genetic diversity was assessed based on 19 microsatellites. All individuals were genotyped at these microsatellites following the previously established methods , using twas used . The lenAmplification products were purified using an AxyPrep™ DNA Gel Extraction Kit (AXYGEN Biosciences) according to the manufacturer’s protocol. Purified PCR product was then ligated into a pMD 18-T Vector  and transformed into a DH5α competent cell . Twenty positive clones containing inserts from each individual were sequenced in both directions using an ABI-Prism™ 3100 Genetic Analyzer (Applied Biosystems Inc.).clustalx V2.0 [Rhro-DRB*01–37 (GenBank accession numbers: JQ863322-JQ863358) [R. roxellana [https://blast.ncbi.nlm.nih.gov/Blast.cgi) of the NCBI.All sequences were aligned by alx V2.0 . To prevQ863358)  and veriDRB genotypes. We used mhc-typer V1.0 , a new method for assigning alleles to different loci based on the calculation of likelihood of loci, to assign each allele to a specific locus.Because our sampling was limited to a narrow time window Table  only sammhc-typer V1.0 uses a simulated annealing algorithm to find the optimal allele configuration, which is defined as a partition of the alleles into several loci [ral loci . The seaxDRB sequences were translated into amino acid sequences using mega V7 [mega V7.0 [genepop V4.3 [AR) based on minimal sample size and inbreeding coefficient (FIS) per locus were both calculated using fstat V2.9.3 [HE), observed heterozygosity (HO), polymorphism information content (PIC) and the frequency of null alleles (Pnull) were calculated using cervus V3.0 [AE) per locus and F-statistics (FST) were both computed using genalex V6.5 [dnasp V5.10.01 [D value means a heterozygous advantage or population reduction, while a negative value represents selection on a specific allele or population expansion [BEV81148 mega V7 . Variablega V7.0 . Deviatipop V4.3  for eacht V2.9.3 . Expectevus V3.0 . The efflex V6.5 . In addiV5.10.01 . A positxpansion .MHC loci were behaving differently from neutral loci, allelic richness (AR), inbreeding coefficient (FIS), expected heterozygosity (HE), observed heterozygosity (HO), polymorphism information content (PIC) and population differentiation (FST) were estimated for both MHC and microsatellite loci. We used Mann-Whitney U test to compare the HE and PIC between these two types of loci. Data were analyzed using spss V22.0 (IBM). All P-values are two tailed, and the level significance was 0.05.To test whether Rhro-DRB alleles  as outgroups. Orthologous sequences from Macacafascicularis (Mafa-DRB), Macacamulatta (Mamu-DRB), Mandrillussphinx (Masp-DRB), Pantroglodytes (Patr-DRB), Gorillagorilla (Gogo-DRB) and Homo sapiens (HLA-DRB)  were included in the analysis. Best-fit models for nucleotide substitution (assuming a gamma distribution) were determined using the Akaike Information Criterion (AIC) in jmodeltest V2.1.3 [mrbayes V3.0 [phyml V3.0 [mega V7 [Phylogenetic relationships among research )  allowing different selection intensity among sites were compared using likelihood-ratio tests in paml V4.7 [We calculated  mega V7  using th mega V7  and 1000RB genes . The sta mega V7 . Evidencaml V4.7 . The hetaml V4.7 , 46. PosDRB genes of 122 R. roxellana monkeys from three populations . Twenty clones were sequenced from both strands for each individual. Nineteen different DRB sequences were obtained with 270 bp, including 247 bp exon 2 and partial intron 1.We examined the variation of Rhro-DRB*01–37 (GenBank accession numbers: JQ863322-JQ863358) [Rhro-DRB*02, 03, 04, 05, 06, 07, 08, 09, 14, 16, 17, 18, 23 and 26, respectively. Five novel DRB sequences were identified and labeled as Rhro-DRB*38, 39, 40, 41 and 42 (GenBank accession numbers: MF434639-MF434643) according to the nomenclature reported by Klein et al. [Rhro-DRB*23, first detected by Luo and Pan [mhc-typer V1.0, 11 alleles were assigned to Rhro-DRB1 and 8 alleles were assigned to Rhro-DRB2 .After performing alignments with Q863358) , fourteen et al. . Each of and Pan , lost th and Pan . AccordiDRB genes. The characteristics of these loci are presented in Tables DRB loci varied among the three study populations, ranging from 10 in FP to 14 in ZZ (Table DRB*03 and DRB*04), whilst others were detected at low frequencies (less than 10%) and/or only in one population .DNA extracts were amplified at 19 microsatellite loci and two ZZ Table . Some ofHO are generally lower than HE in these three populations at both DRB loci, with the exception of the DRB2 locus in the FP population , in which a high frequency of null alleles was detected (Pnull = 0.202). The levels of HE were all above 0.5 among the three populations at two loci  and 19 microsatellite loci (0.512–0.535), indicating a high level of genetic diversity at both types of markers in all three populations. The values of PIC were generally over 0.5 for MHC genes, with the exception of the DRB2 gene in the FP population (0.479), suggesting that other combinations had high polymorphism. For microsatellites, the values of PIC were all less than 0.5 (0.451–0.466), indicating that microsatellites had moderate polymorphism. Allelic richness (AR) also varied at two types of loci, with DRB1 ranging from 5.994 to 6.993, DRB2 ranging from 4.000 to 5.993, with microsatellites ranging from 3.340 to 3.606  is higher than that of microsatellites . Mann-Whitney U tests showed that the difference in HE between two types of loci are not significantly different , whereas the PIC of MHC loci are significantly higher than that of microsatellites .The genetic diversity of DRB1 and 44 (18.1%) for DRB2, corresponding to 30 (37.0%) amino acid residue changes in DRB1 and 23 (28.4%) changes in DRB2 (Table DRB1 and 12/18 in DRB2), with the overall mean distance 0.104 ± 0.015 at the DRB1 locus and 0.082 ± 0.014 at DRB2. Thus, both loci exhibit high levels of sequence divergence.We identified 67 27.1%) variable nucleotide positions in a 247 bp sequence. These sequences showed wide-ranging levels of divergence with an average of 24.7 (10%) nucleotide differences  among sequences. We detected 33 (40.1%) variable positions in the 81 amino acid sequence. The number of pairwise amino acid differences between sequences ranged from 2 to 22 with an average of 15.3 (18.9%). For locus-specific variation, we found 60 (24.7%) variable nucleotides for % variablDRB loci for most parameters , the variable nucleotide sites , the PIC  and HE  in the FP population were all lower than in the other two populations (Table HO = 0.415) at DRB2 locus in the ZZ population is lower than the other combinations  was calculated for the ABS, non-ABS and all amino acid positions , indicating that there was a strong positive selection at these sites in the Rhro-DRB sequences. For the non-ABS sites, ω was less than one , suggesting negative/purifying selection at the non-ABS sites.The selection parameter ns Table . For thepaml V4.7 , we found several homologous sequences in other primate species which have lost the same three bases as has Rhro-DRB*23. Many of these sequences were expressional mRNA sequences, such as Mafa-DRB ; Mamu-DRB (GenBank accession number: KF880635.1); Mane-DRB ; Paur-DRB  and Caja-DRB . We thus conclude that Rhro-DRB*23 is functional and was present in the common ancestor of all species in which it is currently present.We measured the genetic variation of the l allele . After pDRB loci were sequenced in this study. In addition, a high similarity of alleles between two loci were found, suggesting that gene duplication plays a role in increasing copy numbers of DRB genes. Gene duplication among MHC genes has also been observed in other mammals [MHC class II genes in mammals that are found to have high duplication rates [DRB*03 and 04 among all three R. roxellana populations used for this study, it is possible that these alleles may be subject to particular selective pressures that allow the sequences to persist longer than expected under neutrality [Two to four alleles were detected within each individual, indicating at least two  mammals –50. Threon rates . Given tutrality .MHC class II genes of several primate species has been investigated over the past two decades, especially those in the rhesus macaque (Macaca mulatta) [Mamu-DRB haplotype, and compared with humans, revealed high levels of polymorphism at the Mamu-DRB region configurations [DRB sequences were detected in 30 chacma baboons (Papio ursinus) [Microcebus murinus) also shows high levels of sequence divergence. In this species, 12 different DRB alleles were found in 145 individuals, with 58 (33.9%) variable positions in the 171 bp sequence and 29 (50.9%) variable positions out of 57 amino acids [Cheirogaleus medius), with 50 different DRB alleles differing at one to 42 positions from each other, and 33 (57.9%) out of 57 amino acid positions being variable. In this study, we found that the DRB sequence divergence in the three study R. roxellana populations is relatively low compared with Ma. mulatta, P. ursinus, Mi. murinus and C. medius. We identified 67 (27.1%) variable nucleotide positions with an average of 24.7 (10%) differences among sequences corresponding to 33 (40.1%) variable amino acid positions with an average of 15.3 (18.9%) differences among sequences were detected. The proportion of variable amino acids at the ABS for both loci is more than 50% (16/18 in DRB1 and 12/18 in DRB2), meaning that most residual changes occurred in functionally important regions. This is similar to other MHC loci not only in other primates species [Fundulus heteroclitus: [Agalychnis callidryas: [Falco naumanni: [Ailuropoda melanoleuca: [The diversity of mulatta) , 54. Thiurations . More reursinus) . These eursinus) . The mouno acids . Schwensoclitus: ), the relidryas: ), the leaumanni: ) and thenoleuca: ).HE of two DRB loci both exceed 0.5 , indicating a high genetic diversity for DRB genes, which is congruent with results obtained for two other MHC genes  [DRB sequences covered only 247 bp in the exon.The PIC and = 0.713) . In factDRB genes in most parameters except HO  [HO is equal to HE and any difference is due to random error being rejected (P = 0.0007). We suggest that the most parsimonoious explanation for the excess of homozygotes in the ZZ population is the presence of null alleles. These are alleles that cannot be amplified, usually due to the mutations at the primers binding sites [DRB2 locus in the ZZ population is the highest out of the three study populations (Pnull = 0.202), which increases the levels of observed homozygosity. Hence, the inbreeding coefficient in the ZZ population is over-estimated, and the genotypic frequencies deviate significantly to those expected from the HWE at the DRB2 locus  . Howeverulation) . The obsulation) , 67. Theng sites . The freus Table .MHC is an ideal model gene family for studying host-pathogen coevolution [MHC diversity after past population decline [DRB diversity in Qinling R. roxellana populations that suffered a rapid reduction in numbers and severe population fragmentation over the past several decades. We found several lines of evidence that suggest balancing selection has been acting on DRB variation in this species.Key aspects of a species’ adaptations to challenging environments are likely to have been pathogen-mediated . Immunitvolution . Many wi decline , 70, 71.MHC genes. The different diversity patterns of MHC and neutral genes suggest that selection rather than neutral demographic processes  results in a high level of genetic diversity for adaptive MHC genes [R. roxellana populations suffered a rapid reduction in population size [R. roxellana at the mitochondrial control region (D-loop), suggesting that any influence of a founder effect on genetic diversity is weak. Despite the strength of influence of genetic drift, past bottlenecks and/or founder effects in our study populations, these factors will reduce genetic diversity. Similar patterns of high variability of MHC genes coupled with relatively low microsatellite variability occurs in natural populations of other vertebrate species. For example, the house finch (Carpodacus mexicanus), a species that has experienced past population decline due to a disease epidemic, has high multi-locus MHC diversity but relatively moderate levels of variability at microsatellites [Urocyon littoralis dickeyi), a critically endangered species that has high MHC heterozygosity but has little if any microsatellite genetic variation [First, in all three populations, population genetics analysis showed that neutral variation is relatively lower than variation for adaptive HC genes , 9, 17. HC genes , althougion size , there iion size  found mutellites . A more ariation .MHC allele frequencies of the three populations were less differentiated than the microsatellite allele frequencies . In thiMHC genes play an important role in adaptive immunology, and are ideal markers to study adaptive evolution [MHC diversity after population decline [DRB diversity in three R. roxellana populations that have suffered a rapid reduction in numbers and severe population fragmentation over the past several decades. We also found evidence of pathogen-mediated balancing selection, which is likely to have contributed to maintaining MHC polymorphism over time. Our study adds to information on MHC genes and may assist in developing effective management strategies for R. roxellana. Our new data furthers our understanding of the role pathogen-mediated balancing selection has in maintaining variation in MHC genes in small and fragmented populations of free-ranging vertebrates.Many wild species are threatened by a dramatic reduction in and fragmentation of habitat, geographic isolation, small and declining populations and a decrease in genetic diversity , 79–82. volution . Many wi decline . HoweverAdditional file 1:Figure S1. Sequence alignments of the deduced amino acid sequences for exon 2 of Rhro-DRB sequences. DRB sequences were taken from this study and previously published research (Luo and Pan 2013) and were included in sequence alignments. Dots indicate identity with the first sequence.”+” and “*“on the alignment represents putative ABS and sites contact to TCR, respectively. The putative ABS and sites contact to TCR were both derived according to the structure of human DRB genes . (PDF 308 kb)Additional file 2:Figure S2. Phylogenetic tree of Rhro-DRB alleles using the maximum parsimony method. Orthologous sequences from Ovisaries (Ovar-DRB1*0101),Macacafascicularis (Mafa-DRB), Macacamulatta (Mamu-DRB), Mandrillussphinx (Masp-DRB), Pantroglodytes (Patr-DRB), Gorillagorilla (Gogo-DRB) and Homo sapiens (HLA-DRB) were include in the analysis. Values on the branch are represented for the support rate of the MP tree. Sequences labeled with solid circles are DRB alleles from R. roxellana. Colored circles indicate sequences detected in the three study populations. Red ones indication Rhro-DRB1 alleles, while blue ones indicate Rhro-DRB2 alleles. (PDF 183 kb)


Anopheles sinensis is a primary vector for Plasmodium vivax malaria in most regions of China. A comprehensive understanding of genetic variation and structure of the mosquito would be of benefit to the vector control and in a further attempt to contribute to malaria elimination in China. However, there is only inadequate population genetic data pertaining to An. sinensis currently.An. sinensis was examined and analyzed based on the nucleotide sequences of a 662 nt variable region of the mitochondrial cox1 gene among 15 populations from 20 collection sites in China.Genetic variations and structure among populations of cox1 gene sequences were aligned, and 247 haplotypes were detected, 41 of these shared between populations. The range of haplotype diversity was from 0.709 (Yunnan) to 0.998 (Anhui). The genealogic network showed that the haplotypes were divided into two clusters, cluster I was at a high level of homoplasy, while cluster II included almost all individuals from the Yunnan population. The Yunnan population displayed a significantly high level of genetic differentiation (0.452−0.622) and a restricted gene flow with other populations. The pairwise FST values among other populations were lower. The AMOVA result showed that the percentage of variation within populations (83.83%) was higher than that among populations (16.17%). Mantel test suggested that geographical distance did not significantly contribute to the genetic differentiation . Neutral test and mismatch analysis results showed that the An. sinensis population has undergone demographic expansions.A total of 453 individuals in 15 populations were analyzed. The Anopheles sinensis populations showed high genetic polymorphism by cox1 gene. The weak genetic structure may be a consequence of low genetic differentiation and high gene flow among populations, except the Yunnan samples. The Yunnan population was isolated from the other populations, gene flow limited by geographical distance and barriers. These findings will provide a theoretical basis for vector surveillance and vector control in China.The online version of this article (doi:10.1186/s13071-017-2013-z) contains supplementary material, which is available to authorized users. Anopheles sinensis Wiedemann is an Oriental species with a wide distribution in China ) between localities was estimated from pairwise FST [D and Fu’s Fs, which was estimated using the DnaSP software program [The genetic structure was analyzed with 15 populations. The percentage of sequence divergence within and between populations was calculated based on Nei & Li . The pai Slatkin  and testise FST . Mismatcise FST . Signifiise FST . The neu program .An. sinensis mosquitoes, which were identified by PCR assay.Mosquito samples were collected from 20 sites in 15 provinces in China. Fifteen populations were analyzed, in which HEN, SD and LN consisted of specimens collected from two or three sites in proximity to each other  ranged from 2.61 (LN) to 6.97 (HAN), corresponding with the range of nucleotide diversity (Pi) and average number of mutations (θ), which were 0.00394 ± 0.00084  (LN) - 0.01054 ± 0.00145 (HAN) and 0.007 (LN/GX) - 0.019 (HB), respectively  was from 0.709 ± 0.091  (YN) to 0.998 ± 0.010 (AH), corresponding to the percentage of the haplotype from 35.71% (YN) to 96.55% (AH). There were five abundant haplotypes, containing more than 10 individuals, as Hap_41 (n = 37), Hap_122 (n = 16), Hap_23 (n = 14), Hap_6 (n = 13) and Hap_26 (n = 10). Forty-one haplotypes occurred in more than one population, the frequency of which was 16.6% (41/247). Few haplotypes were not detected. The genealogic network showed that the haplotypes were divided into two clusters  were detected in 453  of the FST) was used to evaluate the genetic distance among populations. In this study there were seven negative FST values, comprising AH/FJ, CQ/JX, FJ/GZ, FJ/HEN, FJ/JS, HB/GZ and HB/JS, which indicated genetic differentiation among these populations was very limited  of the YN population were all much less than 1.0. In theory, it was hard to prevent genetic divergence caused by genetic drift if the gene flow (Nm) value was less than 1.0 [The fixation index  contributing more to total variances than the former Table . The meaP = 0.59). The results suggested that geographical distance does not significantly contribute to the genetic differentiation observed in An. sinensis populations.Tests of isolation by distance were performed for all of the populations. No statistically significant correlations were detected between genetic differentiation and geographical distances based on the Mantel test Fig. . The corD and Fu’s Fs values were all negative (Table Fs were observed (P < 0.01) in each population, which would be more sensitive in detecting deviations from neutrality.The Tajima’s ve Table  by DnaSPP = 0.24) and raggedness index (Rag) (0.03) were not statistically significant in almost all the populations except the SSD value for the HEN population  values , which covered almost the entire distribution range of An. sinensis in China [. Sample sizes and site distribution throughout China were adequate and provided an ample dataset to study. The results should be an objective representation, since sampling strategy and geographical coverage greatly influence the analysis and interpretation of the data generated from the samples.In this study, the population genetic diversity was analyzed on cox1 gene nucleotide diversity in anopheline mosquitoes, which has been used to explore population genetic structure [An. sinensis populations have a high haplotype diversity (Hd = 0.709–0.998) and nucleotide diversity (Pi = 0.004–0.011), in turn suggesting that cox1 can be considered a suitable molecular marker for calculating genetic variation and detecting genetic structure. The high level of genetic diversity indicated that the species could maintain a relatively large effective population size by a broad tolerance to environmental and habitat pressure. Due to the evolutionary rates of different molecular markers, the genetic divergence showed different degrees, e.g. Pi values as 0.61−1.00 of cox1 gene, compared to 0.24−0.65 of cox2 in An. sinensis samples [θs values as 0.58−4.285 of cox2, while as 0.274−3.545 of cytb in An. lesteri populations [There is considerable tructure –26 and Dtructure , 40–44.  samples ; θs valuAn. sinensis populations in China using microsatellites and other molecular markers. There was also no correlation between genetic differences and geographical distance [An. sinensis in China was wide, with a large population size and similar ecological habit [An. sinensis was relatively unique in this study as in other reports [An. sinensis populations represented positive and significant isolation-by-distance patterns by microsatellites and mtDNA control region, and both molecular markers showed the Taebaek and Sobaek Mountain ranges to be barriers between the northern and southern parts of the ROK [Overall, the results showed that there were low genetic differences and high gene flow among different populations except in the case of the YN population, which was similar with that previously detected in distance , 19, 46.al habit , 47. Yunal habit , 49. It  reports , 46. The reports . Therefo the ROK , 51.An. sinensis were divided into two clusters. Cluster I included all samples from 15 populations and cluster II included most samples from the YN population, this supported by the phylogenetic findings showing the YN populations also as an independent clade . Anopheles sinensis population size was large owing to the recent expansion of these populations in China.A better understanding of genetic diversity of local Additional file 1: Table S1.Anopheles sinensis haplotypes among populations. (PDF 2557 kb)GenBank accession numbers for the Additional file 2: Figure S1.Anopheles sinensis using DnaSP 5.10. The X axis shows the observed distribution of pairwise nucleotide differences and the Y axis shows the frequencies. The dotted lines represent the observed frequency of pairwise differences, and the solid lines show the expected values under the sudden population expansion model. (TIF 8 kb)Graphs of the mismatch distributions analysis for total populations of Additional file 3: Figure S2.Anopheles sinensis populations based on mitochondrial cox1 gene. (TIF 512 kb)Phylogenetic tree of


Genotyping data indicated tropical japonica alleles were captured at every queried locus despite the presence of segregation distortion factors. Several distortion loci were mapped, both shared and unique, among the 10 populations. Using two-point and multi-point genetic map calculations, our datasets achieved the ∼1500 cM expected map size in rice. Finally, we highlighted the utility of the NAM lines for QTL mapping, including joint analysis across the 10 populations, by confirming known QTL locations for the trait days to heading.Describing the genetic diversity in the gene pool of crops will provide breeders with novel resources for varietal improvement. Nested Association Mapping (NAM) populations are uniquely suited for characterizing parental diversity through the shuffling and fixation of parental haplotypes. Here, we describe a set of 1879 rice NAM lines created through the selfing and single-seed descent of F Currently, one in eight people is estimated to be suffering from malnourishment, primarily in developing countries . DomestiOryza sativa, has been subjected to distinct trajectories of domestication and cultivation, resulting in separate reservoirs of genetic diversity. Domestication of the two major clades of rice, the japonica and indica subspecies, began ∼9000 yr ago, in the river valleys of East Asia and (concurrently or possibly afterward) across the foothills of the Himalayas  the shuffling of parental alleles over several generations through segregation and genetic recombination, and (2) historical recombination of haplotypes present in the various diversity donors. This combination allows for joint mapping of traits across multiple NAM-RILs, greatly increasing the accuracy and precision of QTL discovery, especially when combined with high-density genotyping. Detection power is increased when weak QTL signals in NAM lines  are accumulated from several populations into a stronger signal. Statistical methods such as joint stepwise regression , each representing a different “diversity donor” parent crossed with a common “reference” parent  for future breeding initiatives. Ten tropical japonica diversity donor parentals were selected to be crossed with IR64 indica and create 10 recombinant inbred populations of ∼200 lines each for a total of 1879 NAM lines. The allelic segregation and recombination patterns in the 10 populations were described to aid future trait mapping and breeding endeavors. As a demonstration of the usefulness of our populations for mapping traits, we explored the genetic architecture of a well-characterized agronomic trait and show, through joint analysis, that combining QTL test statistics from multiple populations can provide additional mapping precision in rice NAM lines.In this current study, we developed and characterized rice NAM lines to facilitate the identification of beneficial tropical japonica diversity donors was constructed according to the protocol of the original NAM design for maize , France, has been previously genotyped and described by Simple Sequence Repeats (SSRs)  rice collection exhibiting drought resistance . Tropical japonica parentals were then chosen to represent as many individual clades of this phylogeny as possible.A NAM population using bspecies . The divtropical japonica diversity donors were crossed with the common indica parent IR64. About three hundred F2 individuals were derived from each F1 cross. Whenever possible, all 300 samples were taken from a single F1 plant, with additional F1 plants used only when necessary. Approximately 3000 F2 plants were advanced to the F7 generation by single-seed descent, and to the F10 generation for the IR64 × Azucena population. Due to environmental conditions in the field and to partial genetic sterility in indica × japonica-wide crosses, some of the plants exhibited reduced fertility at different generations. As a result, just under 200 NAM lines were created for each lineage  libraries were prepared according a published protocol (File S1). LB-Impute was chosen for its ability to perform parental imputation and for its high imputation accuracy in regions of low-coverage residual heterozygosity. The final imputed dataset represents high-confidence markers present in each population with low-confidence markers left as missing.GBS paired-end reads were aligned with Novoalign  to versiFile S1), was developed to improve the precision of genotyping in regions containing recombination breakpoints. BP-Impute calculates a Markov chain across the missing regions, with chains in either direction constrained to the flanking parental state. The transition probability was the proportion of recombinant genotypes across each interval. Emission probabilities were the binomial probabilities of emitting genotypes given read coverage and the constrained parental state. The probabilities from both chains were normalized to sum to one, and the weighted average genotype is thus summed from these probabilities.The missing, low-confidence markers were often present in transition regions of recombination breakpoints. Therefore, a second algorithm, Breakpoint Imputation .In each BP-Impute population dataset, a limited number of lines with excess heterozygosity (> 10%), representing potential outcrossing, were removed so that estimations of recombination would be more representative of the rest of the population. The resulting dataset was comprised of genotype probabilities, with each data point representing the probability of a genotype being homozygous for the diversity donor allele. The genotype probabilities were used for measuring segregation distortion and trait mapping. For measuring local recombination rates and the genetic map, discrete genotypes were assigned to genotype probabilities by applying least squares through a separate, custom R script . The filtered WGS variant data were trimmed by randomly selecting a marker within bins of 5 kb. For this set of 72,193 markers, the SNP-Seek database  , a France Genomique project by whole-genome Illumina paired-end sequencing at an average coverage of 35 ×. Whole-genome sequencing (WGS) datasets of parental lines were subject to the same read alignment, variant calling, and variant filtering as the GBS data, but with slightly different parameter settings  since sowing date was selected to demonstrate the utility of the NAM design for trait mapping in individual populations, and jointly across all 10 populations. Days to heading was phenotyped at CIAT between 2011 and 2013, with sowing dates in January, February, March, May, June, July, and November. All populations were phenotyped for the trait; two lines were excluded from QTL mapping for erroneous data entries.y intercept as the best explanation of the phenotype). The alternative hypothesis was that the genotypes explain some variance of the phenotype. The F statistic value , from the R lm function, was stored for each marker. The F value is asymptotically equivalent to the LOD score  was used for trait mapping. With single marker linear regression, each marker in each population was tested for the null hypothesis of no additive genetic effect at the locus  was applied to P values from χ2 goodness of fit tests  and to locus-specific P values from trait mapping. According to Fisher’s method, the natural logs of P values were summed for each of the markers in the local joint marker set. This sum, when multiplied by −2, has a χ2 distribution with degrees of freedom equal to twice the number of summed log P values under the null hypothesis. In order to create the joint marker set for these analyses, P values (segregation distortion) or F values (trait mapping) were linearly interpolated by physical position. This allowed for each population to have a test statistic at the same set of positions representing the region of interest. Joint analysis was performed on a targeted basis at these specified regions.For P values were calculated. This refers to the proportion of pooled P values obtained from random permutations that are as extreme as the observed pooled value. For each of the populations subject to pooling, locus-specific P values were calculated for every permuted F value at a given marker. A locus-specific P value was then randomly selected at every marker, from each population, to create a random pooling. This permuted pooling was performed 1000 times, and the genome-wide adjusted P value was estimated by the proportion of the permuted pooled values larger than the pooled observed data. The threshold for significance was the 95th percentile of permuted poolings.For the joint trait mapping analysis, genome-wide adjusted F value or 3-F value support intervals [comparable to the 1-LOD, 1.5-LOD, or 1.8-LOD interval commonly used  from Yale University via stephen.dellaporta@yale.edu and the germplasm through a MTA from the International Center of Tropical Agriculture, via the corresponding author. LB-Impute . Azucena and ITA164 clustered as expected with tropical japonica at the far left of the japonica axis, whereas CT8556-37-1-3-1-M and CT10035-26-4-2-M were located within the indica cluster closer to the right of the axis.The 10  Project . PCA on bspecies . The firtropical japonica diversity donor × IR64 indica recombinant inbred population. Genotyping metrics describing these populations were summarized in RsaI to create GBS libraries . The first round of imputation resulted in ∼99% of variants being imputed via LB-Impute (File S1) for each population. These complete datasets were used for trait mapping and genetic map construction.The 1879 NAM lines were sequenced and genotyped with a customized GBS method and informatics pipeline of variant calling, variant filtering, and imputation. Ten genotype datasets were created, one for each Dense genotyping was achieved in all 10 populations . There wFile S1). Diversity donor alleles were present at all sites, indicating a full capture of genetic diversity from our tropical japonica parental lines.We examined whether each genomic region of the diversity parent was present in at least one member of the respective NAM subset. In all 10 NAM populations, there was no fixation of IR64 reference parent alleles at any genotyped location (File S1).We did find evidence of shared and population-specific signals of segregation distortion when examining parental contributions in the 10 NAM populations. The proportion of diversity donor to reference parent alleles deviated from the expected 1:1 in several locations. Depending on the diversity donor of a respective NAM population, some of the population exhibited shared or unique trends in the segregation ratio. There were shared signals of IR64 alleles being favored in chromosomes 3, 7, and 9. In these regions, many of the populations experience diversity donor allele proportions < 15% . For populations exhibiting similar trends in segregation distortion, the natural logs of χ2P values were summed for each of the markers in the joint marker set.Applying Fisher’s method to pool File S1). These regions all experienced distortion favoring the IR64 allele. There existed a population-specific locus on chromosome 6 and shared peaks on chromosomes 7 and 9. The minimum diversity donor allele frequencies for markers at these peaks ranged from 0.07 to 0.15. Finally, only chromosomes 1, 4, and 6 presented substantial evidence of segregation distortion in the direction of the diversity donor allele, with extended regions of distortion for one of the 10 populations.The strongest evidence of segregation distortion was found on chromosomes 3, 6, 7, and 9 (Table S1 in File S1). The 1.5 χ2 interval for the population-specific peak was 94,269 bp, containing 16 genes centered at 7.6 Mb. At this population-specific peak, the minimum diversity donor allele frequency at a genotyped marker was 0.13. Two genes in this interval that could potentially contribute to pollen tube growth include the ras-related protein LOC_Os03g13860 . When we examined the average number of recombination events in the 10 populations, ANOVA suggested that the differences between the population means were significant, with an F value of 4.5 and a P value of 6.8 × 10−6. The population with the greatest average number of recombination events was IR64 × CT10006-7-2-M-2, with 21.6 events. The fewest average number was IR64 × Azucena, at 16.1 events.To assess the accuracy of our genotyping and imputation methods, we surveyed the number of recombination events in each NAM line, and used this information to calculate total genetic maps for every population. Across all NAM lines, the average number of recombination events was 18.9 with a SD of 10.9 . The population with the greatest map with BP-Impute and heterozygosity was IR64 × CT10006-7-2-M-2 at 1612.0 cM and the smallest was IR64 × CT10035-26-4-2-M at 1255.8 cM.Of the three genetic map construction strategies, multipoint Mapmaker/EXP3.0 . R/QTL aFile S1).In the joint population dataset, where all NAM lines from the 10 populations were imputed together by R/QTL argmax  as a sinAlthough the genetic maps calculated from imputed data of each population globally approximated the map size for rice, there were local variations in recombination rate. Each of the 10 populations demonstrated deviations from the expected average recombination rate [1 cM per 0.244 Mb, or 4.1 cM:Mb . As expeearly heading date 4 (Ehd4) (MADS-box 50 gene (OsMADS50) LOC_Os03g03070 (DNA-binding with one finger 12 (OsDof12) LOC_Os03g07360 (rice phytochrome B (OsPhyB) LOC_Os03g19590 (File S1). The greatest mean days to heading, for an individual population, was IR64 × CT10035-26-4-2-M at 99.90 d. The fewest mean days to heading was IR64 × Azucena at 88.82 d. ANOVA suggests that differences between the population means were statistically significant, with an F value of 55.00 and a P value < 2.2 × 10−16.Days to heading, defined as the number of days from sowing until the emergence of inflorescences, is a complex trait of agronomic significance. The short arm of chromosome 3 features four genes, the CCCH-type zinc finger gene LOC_Os03g02160, Ehd4, OsMADS50, and OsDof12. The peak that aligned with OsMADS50 had the smallest P value encountered through joint permutation testing; Ehd4 was located adjacent to a nearby subpeak of OsMADS50. OsDof12, located further downstream, aligned to the second highest peak. The OsPhyB gene coordinates were positioned beneath the 17.79  95th percentile of permuted pooling replicates. In order to identify gene candidates, the MSU Rice Genome Annotation Project  for entire interval containing the three jointly segregating genes, Ehd4, OsMADS50, and OsDof12. The other populations either demonstrated weaker peaks or troughs in between the three genes. No population exhibited clear evidence for a peak at the OsPhyB gene.Of the individual population locus-specific P values , IR64 × F values differed greatly among the populations . IR64 × Azucena had the greatest F values by far, with a maximum of 69.79, and a complex QTL peak structure in the vicinity of Ehd4 and OsMADS50. IR64 × CT10035-42-4-4-M had the second highest F values and a similar QTL peak structure. Other populations, despite demonstrating clear peaks in the permutation analysis, had much smaller F values as compared to IR64 × Azucena.The OsMADS50 was subjected to more in depth analysis to better understand the individual contributions of each population to the joint peak  within this interval. IR64 × Azucena was the primary driver of this consensus region. Homeobox genes and protein kinases are found in this region, including a receptor-like protein kinase LOC_Os03g03280 homologous to CURVY1 that controls flowering time in Arabidopsis  , deviates 90.8 cM from the expected map size of 1521.6 cM  are slightly shorter (1430.8 cM ± SD 94.4 cM) than expected, because BP-Impute assumes that there is only one recombination event within an ambiguous interval and it is possible that in some intervals there are multiple recombination events. R/QTL  imputes File S1). Since the joint dataset was imputed with R/QTL argmax  than the average of the 10 populations (1430.8 cM) , whereas there were japonica-favored regions on chromosomes 1, 4, and 6 that favored one population. In order to demonstrate the ability of the NAM populations to identify gene candidates for distortion factors, both within an individual population and jointly across several, we further inspected two loci on chromosome 3. Gene candidates identified by this study may contribute to the architecture of previously known segregation distortion on chromosome 3.The 10 populations described in this study are well suited for detailed study of segregation distortion, on an individual or joint population basis. As an example, we focused on two regions on chromosome 3. Chromosome 3 is known to contain a multitude of segregation distortion loci, especially in the context of 2 support intervals for these two regions from population-specific and pooled χ2 tests were 94,269 bp  and 16,015 . Under the assumption that there is only one shared distortion factor in this interval, we examined the support interval for the pooled χ2 values. In the vicinity of 13.3 Mb, the pooled 1.5-χ2 support interval included two genes, one of which, LOC_Os03g23030, is homologous to the maize pollen gene aberrant pollen 1  LOC_Os03g13950. The actin cytoskeleton is a crucial component of pollen tube elongation . The short arm of chromosome 3 is especially rich with photoperiod genes and days to heading QTL (Ed3a and RFT1 (OsGI–Hd1–Hd3a flowering pathway (DNA-binding with one finger 12 gene (OsDof12) is a transcription factor that controls the expression of Hd3a (Rice phytochrome B (OsPhyB), one of three phytochrome genes found in rice  implicated in flowering time control (F value support intervals were used, an expanded consensus interval of 235,514 bp containing OsMADS50 was identified. Notably, in a previous genome-wide association study of days to heading in elite tropical rice lines, a peak association signal was also detected 800 kb downstream from OsMADS50 (OsMADS50 may therefore contain additional gene candidates that have not yet been described.Significant QTL peaks adjacent to three of the four known photoperiod genes in this region were identified. For one of those genes, OsPhyB did not reach significant QTL thresholds in joint analysis, and no population exhibited strong marginal effects. This lack of signal is interesting because of OsPhyB’s previous implication in flowering time control by repressing flowering under long day conditions (tropical japonica diversity donors and the indica common parent. Reasons for a lack of QTL signal may include both environmental and genetic factors, in addition to reduced detection power brought about by segregation distortion. The NAM lines were grown and phenotyped in Cali, Colombia, at a latitude of just 3.42° N, where days and nights are nearly equal all year round. This is likely to reduce the effect of long day flowering inhibition by OsPhyB. For genetic causes, nonadditive and epistatic effects have been shown to mask single QTL (OsPhyB exists in a region of segregation distortion on chromosome 3. In future studies of the NAM populations, phenotyping will occur in a variety of environments, and nonadditive genetic effects will be investigated to further explain the genetic basis of complex traits such as days to heading.ngle QTL , and OsPThe genotypes and germplasm used in this study are freely available for use in research. All imputation software is available online. Any auxiliary scripts used to process the data are also available upon request. Parental, offspring, and breakpoint imputation used here have also been included as part of the latest release of MapDisto 2.0 (www.g3journal.org/lookup/suppl/doi:10.1534/g3.117.041608/-/DC1.Supplemental material is available online at Click here for additional data file.


Recent aDNA studies are progressively focusing on various Neolithic and Hunter - Gatherer (HG) populations, providing arguments in favor of major migrations accompanying European Neolithisation. The major focus was so far on the Linear Pottery Culture (LBK), which introduced the Neolithic way of life in Central Europe in the second half of 6th millennium BC. It is widely agreed that people of this culture were genetically different from local HGs and no genetic exchange is seen between the two groups. From the other hand some degree of resurgence of HGs genetic component is seen in late Neolithic groups belonging to the complex of the Funnel Beaker Cultures (TRB). Less attention is brought to various middle Neolithic cultures belonging to Late Danubian sequence which chronologically fall in between those two abovementioned groups. We suspected that genetic influx from HG to farming communities might have happened in Late Danubian cultures since archaeologists see extensive contacts between those two communities.Here we address this issue by presenting 5 complete mitochondrial genomes of various late Danubian individuals from modern-day Poland and combining it with available published data. Our data show that Late Danubian cultures are maternally closely related to Funnel Beaker groups instead of culturally similar LBK.We assume that it is an effect of the presence of individuals belonging to U5 haplogroup both in Late Danubians and the TRB. The U5 haplogroup is thought to be a typical for HGs of Europe and therefore we argue that it is an additional evidence of genetic exchange between farming and HG groups taking place at least as far back as in middle Neolithic, in the Late Danubian communities.The online version of this article (doi:10.1186/s12862-017-0924-0) contains supplementary material, which is available to authorized users. The Danubian Neolithic is a sequence of archaeological cultures that emerged around 5600/5500 BC in the Transdanubia region of western Hungary from the preceding Vinca, Starcevo and Köros cultures . The NeoThe archaeologists see the LBK as one of the stages of migration process originating in Near East, that spread north- and west-wards gradually introducing the Neolithic way of life in Europe . HoweverGeneticists have been trying to directly address questions related to the origins and spread of Neolithic populations in Central Europe. The investigation of hypervariable region (HVR) of mitochondrial (mt) DNA from LBK individuals from present-day Germany, Austria and Hungary , 19, ledThe genomic data supported the idea about lack of genetic continuity between the LBK and the local Hunter - Gathers , 27, 28.The main aim of our study was to analyze genetic affinities of LDN populations looking for potential genomic influx from HGs. We generated complete mt genomes from individuals belonging to LBK and late Danubian contexts excavated in modern-day Poland and combined these data with available partial and complete ancient European mt genomes to investigate haplogroup differences between LBK, its successors from the LDN sequence, Central European Hunter-Gatherers and other post-Danubian populations.n = 7) or various LDN contexts, including Lengyel culture (n = 12), Brześć Kujawski Group  and Malice Culture . Additionally, one Mesolithic individual from Janisławice in central Poland was included. Detailed archaeological information for all the individuals can be found in supplementary material  or, where available, complete mitochondrial genomes retrieved from web depositories http://www.ncbi.nlm.nih.gov/genbank, http://www.ebi.ac.uk/ena; (n = 192). For analyses based on haplogroup frequencies, we grouped available data following [For comparative population analyses, we used either published mt haplogroup frequencies , Near Eastern Neolithic (NEN), Yamnaya and major central European Neolithic cultures where all data for populations associated with the Funnel Beaker Culture were merged into one group (TRB) . The inner part of teeth roots and cortical bone of long bones were targeted. Total DNA was extracted from the powder using a silica-based method  modifiedTwenty microliters of DNA extract were converted into blunt-end Illumina genomic library, following , omittinThe DNA libraries that yielded insufficient mitochondrial genome coverage (<9 X) through the initial Illumina screening and generated more than 25 mitochondrial reads were enriched for mtDNA sequences, amplified and sequenced as in . This way) [To process Illumina’s HiSeq2500 shotgun sequencing data, we followed the procedure described in . MergeRey) .Ion Torrent PGM data from the mtDNA capture was processed as follows. The scripts fastx_barcode_splitter.pl and fastx_trimmer (from the FASTX toolkit) were used to demultiplex the reads by barcode, using a one mismatch threshold. Cutadapt v1.8.1 software  was thenAll Illumina and PGM data for each sample were then merged using samtools merge option . MisincoThe Biomatters IGV software v2.3.66  was usedMitochondrial haplotypes were determined based on the PhyloTree phylogenetic tree  build 17We have computed PCA using RapidMiner Studio 7 . The PCA results and variable haplogroup loadings were plotted using Matplotlib 1.5.1 Python package/MS Excel/. To keep the PCA results graph transparent, we only display loadings of the 10 most important haplogroups that predominantly influence the PCA scores.To explore the clustering properties of PCA results based on haplogroup frequencies without the bias of knowing the archaeological background of the populations, we have used the k-means clustering method on the PCA results. After testing several configurations with k = {4, 5,…, 9}, the best clustering for our dataset according to Davies Bouldin Index  was obtaPairwise genetic distances were computed in the Arlequin 3.5 software  using thST matrix (10 000 permutations). This test was primarily used to infer the affiliation of populations into broader defined clusters of populations. AMOVA was used to assess the likelihood that any of the other cultures was a continuous population with LDN, a total of 8 population structures were tested. LDN was grouped consecutively with one from the other 7 populations  while remaining 6 populations were kept separately   was usedThe pairwise genetic distances between populations were used to compute the multidimensional scaling (MDS). Python scikit-learn 0.17 package  was usedhttps://github.com/EdaEhler/bioutils_python) in the following manner: the most frequent polymorphism (or group of polymorphisms) was given the weight of 1, the second most common polymorphism was given the weight of 2, the third most common polymorphism was given the weight of 3, etc. up to 10. All remaining polymorphic loci retained the default weight of 10. Computations consisted of using Reduced Median algorithm [With the use of the Networks 4.614 software (fluxus-engineering.com) we have calculated the median networks. To reduce possible bias and noise in the data, we have removed all polymorphic positions with unknown SNPs (“Ns”). Following , 58, thelgorithm  followedlgorithm .Out of 22 samples screened by shotgun sequencing, only one yielded enough data to reconstruct the whole mitochondrial genome and assign haplogroups  and TRB (FST = 0.00523) populations as well as with BBC (0.00721) population. At the same time the Hunter-Gatherers are set apart from late Danubians (FST = 0.09772).The F Slatkin  linearizST based MDS plot  haplotypes belong to Central Europe HG while the haplotypes found in LDN, TRB, LBK, BBC and CWC samples form the outer part of the network, which suggests that they constitute a derived version of haplotypes, with more accumulated substitutions compared to the U5b haplogroups from HG.Assuming that HG groups were the source of U5 haplotypes in LDN populations it would be interesting to speculate on exact source and nature of this gene flow. The fact that out of four U5 individuals found in LDN populations 3 belong to U5b while one belongs to U5a haplogroup . One posThe two new U5b haplotypes, recovered in this and our previous study , come frOur data, from this and the previous study , shows tWe acquired 5 new complete mitochondrial genomes from Late Danubian populations from modern day Poland. Population genetic analyses run on our data combined with published haplotypes show that Late Danubian populations are maternally closer related to TRB groups instead of culturally similar LBK. We assume that U5 haplotypes found by us and other researchers in those populations are responsible for this affinity. Since U5 is thought to be one of haplogroups characteristic for HG component of European gene pool, we argue that its presence points to gene flow from HG to both Late Danubian and TRB populations.


Lepadogaster lepadogaster, along the southwest Iberian Peninsula, in 2011 and 2012. We predicted high levels of self-recruitment and distinct populations, due to short pelagic larval duration and because all its developmental stages have previously been found near adult habitats. Genetic analyses based on microsatellites countered our prediction and a biophysical dispersal model showed that oceanographic transport was a good explanation for the patterns observed. Adult sub-populations separated by up to 300 km of coastline displayed no genetic differentiation, revealing a single connected population with larvae potentially dispersing long distances over hundreds of km. Despite this, parentage analysis performed on recruits from one focal site within the Marine Park of Arrábida , revealed self-recruitment levels of 2.5% and 7.7% in 2011 and 2012, respectively, suggesting that both long- and short-distance dispersal play an important role in the replenishment of these populations. Population differentiation and patterns of dispersal, which were highly variable between years, could be linked to the variability inherent in local oceanographic processes. Overall, our measures of connectivity based on genetic and oceanographic data highlight the relevance of long-distance dispersal in determining the degree of connectivity, even in species with short pelagic larval durations.Adults of most marine benthic and demersal fish are site-attached, with the dispersal of their larval stages ensuring connectivity among populations. In this study we aimed to infer spatial and temporal variation in population connectivity and dispersal of a marine fish species, using genetic tools and comparing these with oceanographic transport. We focused on an intertidal rocky reef fish species, the shore clingfish  Adults of most marine benthic and demersal fish are site-attached, with the dispersal of their larval stages ensuring connectivity (e.g. ). Due toSeveral types of methods have been developed to overcome the knowledge deficit in marine fish larval connectivity. Indirect approaches include genetic connectivity studies e.g. , 23), mi, mi23]),Lepadogaster lepadogaster, a temperate clingfish, for which there is evidence from a combination of biological, ecological and oceanographic features, suggesting high population structure and low connectivity among populations. These features include short pelagic larval duration , 36Lepadion  a Gobiesocidae, is a small cryptobenthic temperate reef fish, strictly restricted to smooth boulders and stones with little biological cover in the intertidal zone of rocky coasts [L. lepadogaster has an embryonic development of 16 days and hatches well-developed larvae with an open mouth and anus, fully pigmented eyes and with lengths of 5.2–5.3 mm [L. lepadogaster lasts 11–18 days [The shore clingfish y coasts , 40. It y coasts , 41. Eggy coasts . L. lepa2–5.3 mm . The PLD–18 days , 35; com–18 days .The MPA, in central Portugal, was the location selected for this study since several rocky reef fish species there occur very near-shore and near-reef, indicating potential for larval retention close to the adult habitat , 13, 37.In 2012, adult fish were sampled at a focal site (ARR) within the MPA and in areas to the north and south. Northerly sites included rocky coasts close to Lisbon (LIS), Peniche (PEN) and São Martinho do Porto (MAR), while southerly sites included Sines (SIN), Almograve (ALM) and Barranco (BAR) , Table 1L. lepadogaster at ARR was determined via a field survey of all suitable boulder habitat, and this was extrapolated to the other sites. ARR was chosen for this field survey because of its suitable habitat and high fish density.Adults and juveniles were collected at low tide during spring tides under boulders and stones in large boulder fields and in tide pools between rocky platforms. Adult fish were sampled before the recruitment season (February-June), while recruits were collected in autumn after recruitment (August-September). In order to roughly estimate population size, the density of 3 tissue sample from the dorsal fin was clipped from adult L. lepadogaster and stored in 96% ethanol. Adult fish were released directly back into the same location where they were collected. Several adult fish were placed into aquaria after this procedure; no mortality due to handling was observed and fin regeneration occurred within weeks. At ARR, juvenile fish were euthanized and fixed in 96% ethanol. L. lepadogaster is not a species of conservation concern  and thus no specific permits were required, except for sampling at ARR. This permit was issued by the Portuguese Nature Conservation Institute (ICNF).For this study, approximately a 0.03 cmIn 2011 and 2012, when the field work of this study was carried out, the ethics legislation that existed in Portugal  did not specify methods of euthanasia for fish. An ethics committee approval for the animal procedure was not required and animal suffering was considered negligible when immersing juvenile fish in ethanol as death occurred quickly (1–2 sec). Since 2013, an approval for animal procedures by a specific ethic committee is required, and specific euthanasia procedures are regulated (decree 113/2013).Genomic DNA from fin- (adults) and muscle tissue (juveniles) was extracted as in , excludiE) and observed (HO) heterozygosity, and the inbreeding coefficient (FIS) were determined with GENETIX, 4.05 [The mean number of alleles across loci (A), expected . Additionally, significant differentiation was confirmed by 95% confidence intervals (CI) above zero [FST between our raw microsatellite data and a corrected version after applying the excluding null alleles (ENA) correction method with 1,000 bootstrap repetitions. Furthermore, Jost’s D, a differentiation index that is not affected by the number of alleles per locus [GENETIX was used to estimate ove zero , calculaove zero  was useder locus , 50, werer locus . Here, per locus .FST and Jost’s D-values independently in R by using the mantel.randtest function in the R package ade4 and 10,000 permutations. For these analyses, shoreline distance was calculated with the R-package “gdistance” [Isolation-by-distance (IBD) analyses were conducted for both pairwise istance” .The software STRUCTURE version 2.1  was usedA Discriminant Analysis of Principal Components (DAPC) was also used to infer population structure. A DAPC can assign individual genotypes to predefined groups using different criteria than STRUCTURE, while being as sensitive . The dapTo assign or exclude recruits to/from the 7 sampled populations, we used a partial Bayesian classification method  in GENECTo further infer the possible origin of the parents and offspring, we used the maximum likelihood approach implemented in COLONY v.2.0 , 65, whiL. lepadogaster were inferred by developing individual-based Lagrangian Numerical Simulations  usiiewed by , utiliziiewed by . This moiewed by , 69.L. lepadogaster by incorporating a maximum PLD of 18 days [2) spatial resolution. Particles were released from each cell every 6 hours during the spawning season of L. lepadogaster .th day of PLD, which is when the larvae acquire competence for settlement [L. lepadogaster. This model was used to estimate potential distances and patterns of dispersal and not to quantify larval dispersal.Contrasting transport experiments  were performed based on the early life history of this species. In the passive transport experiments, particles used the surface (0 meters) or the bottom (10 meters) layers independently. In the vertical transport experiments, particles were allowed to move from the surface to the bottom layers on the 10ttlement , 70. AddSimulations were run independently per year, with data for 2002 to 2012. The resulting aggregated trajectories allowed the production of connectivity matrices between all pairs of cells. Paired probabilities were inferred by determining the number of steps in the path of a single particle, released from cell i, that achieved cell j, divided by the overall simulated time steps (18 days PLD * 24 steps a day). The annual matrices resulting from the different experiments were averaged to account for interannual variability. This allowed the determination of the maximum and average distance travelled by particles connecting pairs of cells. The mean proportion of retention and effective settlement were also determined and differences between experiment types were tested using a Kruskal-Wallis Rank Sum test followed by a post-hoc pairwise test for multiple comparisons of mean rank sums (Nemenyi-test). Lagrangian dispersal simulations were developed in R  using thL. lepadogaster with a mean standard length of 51.2±8.8 mm and 18.2±4.1 mm, respectively, were successfully genotyped for 12 polymorphic microsatellites. The estimated proportion of population analyzed ranged from 7.0 to 54.9% (rich), standardized to 24 individuals as the minimum common sample size, ranged from 7.5  to 10.0 . Unbiased expected (HE) and observed heterozygosity (HO) ranged from 0.72 to 0.81 and 0.56 to 0.74, respectively. All populations had low but significantly positive FIS values, indicating a departure from Hardy-Weinberg equilibrium   .FST for all loci and pairwise FST were very similar, either when estimated from raw allele frequencies or from allele frequencies corrected for null alleles  was significantly different (p<0.01) from all other populations and SIN was different to all populations north of ARR. In general, there was an increasing differentiation with distance, which coincided with the significant result of the isolation by distance analysis with pairwise FST and D values  and ΔK methods. All studied populations contained these three genetic populations in different proportions . The comA similar pattern could be described from the DAPC analysis, whereby 2011 and 2012 populations were differentiated along the first discriminant function that comprised most of the genetic variation . This teThe assignment test detected only very few significant assignments, supporting low genetic structure among these populations. From the 2012 recruits collected at ARR, one was assigned to the population of BAR and one immigrant was not assigned to any of the analyzed populations. In 2011, one recruit was assigned to LIS and another one to ARR.The parentage analysis identified 6 and 8 parent-offspring pairs in 2011 and 2012, respectively. In 2011 parents originated from ARR (3), SIN (2) and ALM (1) and in 2012 from LIS (5), ARR (1) and ALM (2). This means that over these two years, 5% of recruits came back to their natal population (ARR) and, 13% had a parent from either the next northern or the two next southern populations sampled. Recruits that self-recruited to ARR in 2011 (n = 3) were identified to be the offspring of just one adult fish with a 100% probability. Also, 4 out of the 5 recruits originating from LIS in 2012 shared a parent.The numerical simulations using HYCOM velocity fields for an entire 11-year period allowed us to track the fate of 7,920 particles released from 93 distinct coastal cells . Trajectories were obtained for particles that had successfully settlement in any site within 18 days of PLD and these resulted in two types of connectivity matrices: 1) on a yearly basis including 2010, 2011, and 2012 and 2) averaged for an 11-year period. Simulations ran over 11 years revealed that particles spending their entire pelagic phase in a deeper water layer (10 m) had a significantly higher probability of retention compared to particles staying at the surface, or migrating vertically from the surface to the bottom layer at the 10th day of PLD, when the larvae acquired competence for settlement  ..L. lepadThis study further demonstrates that it can be misleading to make assumptions on the degree of population connectivity based solely on a few known early life history traits, such as egg type and PLD. This supports previous studies that showed either higher than expected connectivity (e.g. ) or, on L. lepadogaster have a low critical swimming speed and it is hypothesized that strong swimming abilities are not needed since they can be retained nearshore on the benthic layer where currents are expected to be weaker due to bottom friction [L. lepadogaster larvae to disperse and eventually reach other populations. This would contribute to a flattening of genetic differences among them, as suggested for a functional dispersal group of organisms with longer dispersal distances, estimated from genetics [Larvae of friction . Howeverfriction ). Thus, genetics .All analyses in this study revealed strong temporal genetic divergence, with adult gene pools having significantly different compositions between years. This annual difference was even larger than the spatial genetic difference between the two most distant sites (700 km). Moreover, the spatial genetic divergence was also different between years. Although in 2012 all populations (excluding the most southern one: BAR) had a very similar genetic composition, in 2011 the nearby populations of LIS and ARR were more differentiated from each other.Our findings of temporal variability suggest caution in the interpretation of single dispersal estimates, even when using genetic data which tend to integrate temporal scales. Few genetic studies on reef fish included temporal comparisons and those that did, mostly showed no interannual differences , 81, 82,L. lepadogaster, which could lead to larval pools arriving to adult habitats from different source populations in different years [We propose two possible hypotheses to explain this strong interannual difference in the adult gene pools: i) oceanographic transport; and ii) density dependent recruitment, influenced by storms. The first could be due to differences in coastal currents during the spawning season of nt years , 86, 87.During late spring and summer months, in addition to the predominant upwelling derived southward currents, inner-shelf northward counter-currents transporting warm water can occur from the south of Portugal to ARR . These cL. lepadogaster occurs in discrete patchy habitats [L. lepadogaster fish could thus be an explanation for the decrease of allelic diversity in the adult populations from 2011 to 2012.The second hypothesis to explain the observed temporal differences could be an effect of storms combined with density dependent recruitment success. habitats . In theshabitats ; S6 FileResults of the dispersal model were consistent with the genetic results , 91. HowL. lepadogaster populations might be strongly affected by short-term events such as storms and that populations are highly influenced by the larval pool composition recruiting to the adult habitats. These larval pools would need to be a mixture of fish originating from a variety of source populations to allow for a decrease in the spatial genetic structure within years. But larval pool composition might differ interannually, due to stochastic processes such as highly variable alongshore currents, resulting in adult populations that differ genetically from the previous year.Overall, the genetic population structure supported by the dispersal model indicate significant gene flow due to long-distance larval dispersal that would lead to a homogenization of allele frequencies among sites over an evolutionary time scale. However, the occurrence of temporal genetic divergence in adult and recruit populations suggests that L. lepadogaster population of ARR is not as closed as expected; not only does it depend on the supply of recruits from other populations but it can also provide other sites with larvae, thus functioning simultaneously as a source and sink. A long-term analysis of adults and recruits from all populations over several years would be ideal to follow the temporal dynamics of these source-sink patterns, something that cannot be revealed in studies focused on a single sampling event. The results of this study show that these temporal scales are of great importance in understanding connectivity patterns of coastal reef fish species, thereby providing important information for the design of a network of protected areas.The S1 FileLepadogaster lepadogaster collected along the Portuguese west coast. Shown are expected and observed heterozygosities (HE and HO), heterozygote deficiency (FIS) and p-values of FIS for each population and loci.Summary statistics for adult and recruit samples of (PDF)Click here for additional data file.S2 FileTable A in S2 File. Estimated null allele frequency for sampled populations (first row) at each locus (first column). Table B in S2 File. Comparison of global FST per locus derived from raw microsatellite data and after applying the excluding null alleles (ENA) correction method from [Table C in S2 File. Comparison of pairwise FST derived from raw microsatellite data and after applying the excluding null alleles (ENA) correction method from [hod from . Table Chod from .(PDF)Click here for additional data file.S3 FileFig A in S3 File. Principal Component Analysis of the DAPC; red line indicates number of PCs retained (52) for the DAPC and the genetic information comprised by this number. Fig B in S3 File. Correct assignment of adult fish to their geographical population in 2012 and 2011, with recruits being excluded from the DAPC.(PDF)Click here for additional data file.S4 FileFST (A) and Jost’s D values (B) as a function of shoreline distance.Linear regression analysis of genetic distance, estimated from pairwise (PDF)Click here for additional data file.S5 FileFig A in S5 File. Coastline distance related to the probability of connectivity averaged over simulations ran from 2002–2012 per particle type surface (a), deep (b) and migration (c); notice different scales of y-axis. Table A in S5 File. Paired probabilities of connectivity among genetic sample sites for particles of type deep, migration and surface, averaged over simulations ran from 2002–2012 and yearly averages for 2010, 2011 and 2012. Shaded rows indicate retention probabilities. Fig B in S5 File. Connectivity map with probabilities of where particles settle after being released from the MPA (framed) in 2010 (a), 2011 (b) and 2012 (c) and probabilities of the origin of particles that settled into the MPA in 2010 (d), 2011 (e) and 2012 (f).(PDF)Click here for additional data file.S6 FilePattern of wave height for the area of Lisbon (black line) and the MPA (red line) and wind speed of Lisbon during winter 2011/12, retrieved from an oceanographic model ; shaded (PDF)Click here for additional data file.


Despite the increase in our knowledge about the factors that shaped the genetic structure of the human population in Europe, the demographic processes that occurred during and after the Early Bronze Age (EBA) in Central-East Europe remain unclear. To fill the gap, we isolated and sequenced DNAs of 60 individuals from Kowalewko, a bi-ritual cemetery of the Iron Age (IA) Wielbark culture, located between the Oder and Vistula rivers (Kow-OVIA population). The collected data revealed high genetic diversity of Kow-OVIA, suggesting that it was not a small isolated population. Analyses of mtDNA haplogroup frequencies and genetic distances performed for Kow-OVIA and other ancient European populations showed that Kow-OVIA was most closely linked to the Jutland Iron Age (JIA) population. However, the relationship of both populations to the preceding Late Neolithic (LN) and EBA populations were different. We found that this phenomenon is most likely the consequence of the distinct genetic history observed for Kow-OVIA women and men. Females were related to the Early-Middle Neolithic farmers, whereas males were related to JIA and LN Bell Beakers. In general, our findings disclose the mechanisms that could underlie the formation of the local genetic substructures in the South Baltic region during the IA. Homo sapiens sapiens. So far, such population scale studies have most frequently been concentrated on mitochondrial DNA (mtDNA) due to its high copy number, small size and lack of recombination. Consequently, the analyses of ancient mtDNA substantially contribute to unraveling the history of human settlement around the world.One of the consequences of the rapid development of DNA isolation, enrichment and sequencing technologies is currently observed: the substantial increase of our knowledge about the prehistory of anatomically modern humans (AMH). The first projects that focused on ancient DNA (aDNA) isolated from singular individuals gave a rough idea of when the first representatives of AMH appeared in Africa and how global human expansion occurred. Currently, the genetic studies on a population scale are a pressing need. Together with archaeological and anthropological research, genetic studies can provide new insight into the natural history of 4.The genetic structure of the European population has been shaped by a series of consecutive or partly concurrent processes that form the following chain of events: (i) Europe colonization by AMH during the Upper Paleolithic Period; (ii) the Late Glacial and Post-glacial recolonization; (iii) introduction of agriculture (Neolithization); (iv) genetic continuation through the Middle Neolithic (MN) and the progressive intermix of the Early European Farmers (EEF) with endogenous hunters-gatherers (HG); (v) the inflow of new genetic components from the southwest and southeast to Central Europe in the Late Neolithic (LN), and formation of separate cultures in the Early Bronze Age (EBA)7. This colonization was connected to the extinction of Homo sapiens neanderthalensis and a spread of AMH HG. One of the characteristics of the HG populations was the domination of mtDNA haplogroup U represented mainly by U2, U4, U5a, U5b, and U88. However, the Last Glacial Maximum (LGM), dated 27–16 tya, forced populations living in north Europe to leave this region. Approximately 19 tya, together with climate warming, a recolonization of Europe by indigenous HG was initiated7. They came from southwestern and eastern refugia where they survived the ice age. Interestingly, approximately 14.5 tya indigenous HG were replaced by the new incoming people, who diverged from the ancestral HG population prior to the beginning of the LGM (29 tya)9. Another major inflow of AMH to Europe occurred during the so-called Neolithic revolution, approximately 12 tya4. This period is inextricably linked with the introduction of agriculture  and a change from a nomadic to sedentary lifestyle. The Neolithic revolution, the so-called “Neolithization”, most likely proceeded in two ways10. First, it resulted from cultural changes initiated in the Mediterranean region that spread towards the southwest part of the continent11. Second, it was connected with the inflow of the EEF from Central Anatolia along the Danube and towards Central Europe13.The initial colonization of Europe by AMH began approximately forty-five thousand years ago (tya)14. Interestingly, during the MN, an increase in the occurrence of haplogroups typical for the HG was observed throughout Europe16. In the central part of the continent this phenomenon is believed to be connected with the expansion of the population associated with the Funnel Beaker Culture (TRB ger. Trichterrandbecherkultur)17. The TRB was mainly spread within the northern areas of Central Europe and Scandinavia.Neolithization was accompanied by the introduction of new mtDNA haplogroups , currently called the “Neolithic package”15. A consequence of the inflow was the formation and spread of the Corded Ware Culture (CWC)18 and the occurrence of new mtDNA haplogroups  in Central and Eastern Europe2. The second event was the formation of the Bell Beaker Culture (BBC), most likely in Western Europe, and its propagation in Central Europe2. The most significant differences that have been identified so far between the BBC and CWC populations at the mtDNA level are in the lower frequency of I and U2 haplogroups and the significant prevalence of haplogroup H in BBC2. Other substantial changes in the mtDNA haplogroup frequency were found in the population associated with the Unetice Culture (UC) that appeared in Central Europe during the EBA; thus, right after the LN. The UC replaced the BBC and CWC; however, its population did not seem to be a direct genetic continuity of the population associated with the two former cultures. The analysis of mtDNA indicated closer similarity of the UC to CWC rather than to BBC2.Next, two events that significantly affected the mtDNA structure in Europe occurred in the LN. They both coexisted for approximately 300 years across Central Europe. The first one was a migration of the Yamnaya steppe herders from the Eurasian Steppe2. This was despite the latter being chronologically closer to contemporary times than the BBC. These findings suggest that after the EBA, there were significant demographic changes in Central Europe and, consequently, changes in the genetic structure of the Central Europe population. To elucidate this problem, more detailed studies of the populations living in Central Europe between the EBA and present day are necessary. These studies require careful selection of samples with reference not only to time but also to geographical distribution. First, when the contemporary genetic structure of Central and Eastern Europe was formed will be identified. Presently, it is unknown whether this genetic structure was finally shaped by prehistorical or Early Medieval events. The second issue concerns the representativeness of the samples used to define the genetic structure of the Central European population in the EBA and after this period. Thus far, most of the ancient mtDNA analyses were based on samples from Mittelelbe-Saale in Saxony-Anhalt. Genetic studies of the prehistory of populations inhabiting the region of contemporary Poland are sparse. They are based on a very limited number of samples and focused usually on fragments of mtDNA21.Considering the above history, one can expect that the genetic profile of mtDNA of the present-day Central Europe populations should be especially highly influenced by the population related to the UC. However, this is not the case. The analysis of contemporary mtDNA showed that the population associated with the BBC had a more considerable impact on the genetic landscape of present-day Central Europe than the populations associated with the eastern CWC and UC22. Additionally, preliminary genetic20 and metagenomic studies23 of these remains have been performed.To obtain a more thorough view of the demographic processes that affected the genetic profile of Central European populations after EBA, we analyzed mtDNA extracted from individuals living in the area between Oder and Vistula rivers (east of Saxony) at the time of the Iron Age (IA). From several burial grounds, we selected a particularly rich and well-characterized one, located in central Wielkopolska  in Kowalewko, near Poznan (52°35′24″N 16°46′44″E). According to the archaeological and anthropological studies, approximately 500 people who had lived on that area from 1 until 200 A.D. were buried there. Most of the burial sites have previously been thoroughly examined archaeologically and anthropologicallyHere, we present the first analysis of mtDNA obtained from a large group of individuals living between the Oder and Vistula rivers during the IA. We identified mtDNA haplogroups for 40 individuals, and sequenced a complete mtDNA genome for 33 individuals. The performed analyses revealed a high genetic diversity of the studied group. Interestingly, women and men from Kowalewko had a significantly different genetic history. The collected data shed new light on the processes that shaped the specific, local genetic substructure of the human population in the South Baltic region during the IA.The studied group included people whose remains were excavated from the IA Wielbark culture cemetery, located in Kowalewko . In total, 63 aDNA samples were obtained. The NGS libraries were successfully obtained for 60 samples . To estimate the amount of human DNA, all of the obtained libraries were subjected to shallow sequencing (the average coverage of mtDNA genome was 3.62x and ranged between 1 and 11x). The average amount of human DNA in the examined samples was 12% and ranged from 0.1 to 91.9%  with high amounts of endogenous DNA (over 10%) were subjected to deep sequencing (the average coverage was 163x and ranged between 6x and 1092x). As a result, a full sequence of mtDNA genomes was determined for 22 additional individuals  and 4 pairs of individuals with only one different nucleotide in the mtDNA sequences . To exclude the possibility that the presence of two potentially maternally related individuals in relatively small dataset will affect the results of our consecutive analyses, we removed from the tested group three individuals - one from each pair with identical mtDNA sequences. For the comparison, the results obtained with the dataset containing potentially related individuals were shown in the Supplementary Figures The intrapopulation diversity of Kow-OVIA was analyzed using the full length mtDNA sequences obtained for 33 individuals  was only slightly lower than the average value obtained for the present-day European populations (0.00929)  based on two fragments of the HVS (hypervariable sequence) region (HVS-I between 16033 and 16365 np (nucleotide positions) and HVS-II between 73 and 340 np) . Our analysis involved a fragment of mtDNA HVS-I sequence (the region between 16064 and 16400 np) Fig. . The estIn the second step, we determined the genetic distances between Kow-OVIA and populations living in the whole of Europe from the Mesolithic age to the IA. To this end, we selected 26 populations from the EPT group for which sequences of the mtDNA HVS-I region between 16064 and 16400 np . Accordingly, we allocated all EN/MN populations to one group and analyzed 18 different combinations of population grouping . In the first step, we determined an optimal division of the populations from CEPT excluding the HG and CEM. The division was considered to be optimal if intragroup variability (Fsc) was minimal and intergroup variability (Fct) maximal. In our analysis, we took advantage of earlier observations made byNext, we performed an analogous analysis but the studied group was extended by CEM (CEPT with excluded HG populations). Once again, we assumed that the populations of the EN/MN  are a homogenous group, and we analyzed 33 combinations of the other fossil populations and CEM . The studied group initially comprised 60 individuals; for 40 individuals, we assigned the mtDNA haplogroup, and for 33 of them, we determined the sequence of the entire mitochondrial genome. This dataset is particularly important to understand demographic processes that occurred in Central Europe during the IA and in the context of migrations between the 3rd and 6th centuries AD that are believed to have shaped the genetic landscape of contemporary Europe31.Despite tremendous progress that has recently been made in archaeogenomic studies of European populations, our knowledge of the changes that occurred in the genetic structure of the peoples inhabiting Central Europe between the LN/EBA and Middle Ages is still very limited. One major problem is the scarcity of genetic data describing individuals who occupied the region east of the Oder river. To fill this gap, we performed an analysis of the mitochondrial genomes of a large group of people who lived in the area between the Oder and Vistula rivers (present-day western Poland) during the IA  and followed by the UC (EBA). In the new tree, Kow-OVIA was clustered with the LN/EBA populations. The present-day European population (CEM) was clustered with the JIA that was contemporary to Kow-OVIA and inhabited Jutland.Based on our results of mtDNA haplogroup frequency analysis, we were able to update a phylogenetic tree describing the history of see Fig. . CompareBased on the results presented above one can assume that there are some discrepancies between the hierarchical clustering Fig.  and PCA 2. This hypothesis is additionally strengthened by the results of AMOVA analysis indicating that there is some inconsistency between genetic distances and the chronology of the appearance of the studied populations in Central Europe, i.e., the older populations  contributed more to the genetic structure of CEM than the younger ones (UC).Analysis of genetic distances see Fig.  showed t2. The second conversion indicated by our results suggests another crucial demographic event that should occur between the IA and present.Changes in the occurrence of mtDNA haplogroups U5a/U5b in Central Europe are also worth noting. At LN and EBA, the prevailing haplogroup was U5a for BBC/CWC/UC. Next, there was a dominance of U5b for the Kow-OVIA/JIA during IA and now U5a is again more popular (CEM). The first alteration in the U5a/U5b prevalence between the LN/EBA and the IA supports the hypothesis of demographic changes right after the LN, proposed by34, it is worth considering the range of the observed changes. These considerations should also take into account the hypothesis on the migrations that most likely occurred between the 3rd and 6th century AD. In this context, it seems necessary to compare Kow-OVIA and JIA with other populations from the IA, in particular those located east of Vistula, and with the populations that inhabited this region during the Middle Ages.On the basis of the above observations, one may assume that in the IA, specific genetic substructures were formed in Central Europe. Because the demographic history of fossil populations often has a local character32. However, despite close genetic distance between Kow-OVIA and the JIA, PCA placed them asymmetrically in relation to other ancient populations . For the JIA, the same origin is observed for only 19% of ancestral haplotypes.The process of demographic change in Central and Northern Europe after the LN/EBA appears to have a complex nature. Genetic proximity of the Kow-OVIA and JIA is consistent with the Kow-OVIA’s affiliation to the Wielbark archaeological culture, strictly connected with Baltic regionssee Fig. . Accordisee Fig. , JIA was36. This is, however, not the case. We found that the genetic differences between women and men were maintained for the entire observation period, i.e., for 200 years (approximately 8 generations). Such a composition of the genetic structure of Kow-OVIA could exist only if at least one subgroup (Kow-OVIA-F or -M) was periodically exchanged. It would further mean that Kowalewko played some specific roles in that region. According to the recent archaeological studies, the colonization pattern in IA Greater Poland could be linked with the existence of a centralized organization system32. Kowalewko could have been one of the important elements of this system. For example, it could have functioned as a garrison for the population closely associated with the JIA, such that warriors stayed in the garrison for only a few years and were then replaced by others. Other scenarios are also possible; however, verification of any hypothesis requires more detailed studies.Finally, we found that the genetic structures of female and male subpopulations of Kow-OVIA were significantly different. This fact cannot be explicitly determined based on the results of individual analyses; however, it is quite evident if one considers the whole set of data presented here including the Fisher test on haplogroup frequencies. The analyses of both mtDNA haplogroups and genetic distances indicated that women from Kowalewko were related closer to the EN/MN populations, and the men were closer to the CWC and UC. This observation may explain why the genetic relationships of Kow-OVIA with other ancient European populations were more complex and more difficult to define as it was in the case of JIA. In analyzing Kow-OVIA, we observed multiple overlapping effects of two subpopulations with different genetic affinities. One would speculate that the genetic profile of Kow-OVIA-F resulted from exogamy that was described for the CWC population24 and37. Genomic libraries were prepared following a protocol from38 omitting the initial sonication step, due to the natural fragmentation of aDNA. Six separate PCR reactions were set up for each library. PCR amplifications were performed in 25 µl with 3 µl of the DNA library template, 12.5 µl of 1x AmpliTaq Gold® 360 Master Mix , 0.5 µl of indexing primer (10 µM) and 0.5 µl of PCR primer IS4 (10 µM) . The PCR profile was as follows: initial denaturation , 12–16 cycles of 94 °C (30 s), 60 °C (30 s), 72 °C (45 s) and final extension . PCR reactions for the same library were pooled and purified with AMPure® XP beads (Agencourt-Beckman Coulter) following39. Quality and size distribution of the libraries were verified with a High Sensitivity DNA kit and 2100 Bioanalyzer system (Agilent) while DNA concentration was determined with a Qubit fluorimeter and Qubit dsDNA HS Assay Kit (ThermoFisher Scientific), according to the manufacturers’ protocols.For the purposes of this study, 63 samples (teeth) were obtained from 60 individuals from the Kowalewko archaeological site  and TruSeq SBS Kits v5-GA (Illumina) were applied. Seven to nine libraries were pooled per lane. On average, 4.75 mln 75 bp-long reads were collected per library. The libraries with the highest human DNA content were sent for deep sequencing to Macrogen Inc., Korea, with the use of HiSeq4000 (Illumina). On average, 87 mln 101 bp-long reads were collected per library on the HiSeq4000 (Illumina)  were filtered with AdapterRemoval46 to estimate human DNA damage parameters typical for aDNA for each sample: (i) λ, the fraction of nucleotides positioned in the single-stranded DNA overhang context; (ii) δs, C→T substitution rate in the single-stranded overhang context; and (iii) δd, C→T substitution rate in the double-stranded DNA context  49. Only samples with a haplogroup score ≥ 0.8 and average coverage ≥ 3 were used in downstream analyses. To assess temporal mtDNA haplogroup frequency changes from Mesolithic to the present day, we performed Ward clustering with Euclidean distance on 23 haplogroups . We used a set of 40 samples from this study and 13 populations from Central/North Europe , with public data from 73 extant populations (Supplementary Table http://R-project.org).Cluster significance was tested by performing 10,000 permutations with the pvclust package in R ver. 3.3.0. PCA was conducted with prcomp of the vegan package in R ver. 3.3.0 . Additionally, for newly reported samples from this study, no missing nucleotides were allowed in the selected HVS-I range, and at least 3x coverage was expected for 95% of the nucleotides. To examine genetic affinities on the sequence level, we calculated genetic distances (Fst)51 values were calculated in Arlequin ver. 3.5.1 for both datasets separately, with associated substitution model and gamma values selected with jModel test 0.1 AIC and BIC52. P values were calculated by performing 10,000 permutations. Genetic distances were visualized on an MDS plot with metaMDS function from the vegan package in R ver. 3.3.0.Pairwise and Slatkin’s FstTo examine if genetic affinities between particular populations from CEPT were a result of shared genetic structure, we conducted AMOVA analysis in 18 combinations of CEPT populations (excluding HG and CEM) (Supplementary Table 10 in CEPT (Supplementary Table 30 in LN/EBA and IA populations (Supplementary Table To further test genetic affinities and account for temporal succession of archaeological cultures in Central Europe, we conducted an analysis of shared ancestral haplotypes as described inFor details, see the Supplementary Materials.The data supporting the results of this article are available at SRA, BioProject PRJNA354503.Supplementary datasetSupplementary information