Cochlearia officinalis ecotypes, adapted to different habitats , are genetically differentiated and result from parallel ecotypic divergence in two distinct geographical regions. We obtained genetic data from thousands of single nucleotide polymorphisms (SNPs) from restriction-site associated DNA sequencing (RADseq) and from six microsatellite markers for 12 populations to assess genetic divergence at ecotypic, geographic and population level. The genetic patterns support differentiation among ecotypes as suggested by morphology and ecology. The data fit a scenario where the ancestral beach ecotype has recurrently and polytopically given rise to the estuary and spring ecotypes. Several ecologically-relevant loci with consistent non-random segregating patterns are identified across the recurrent origins, in particular around genes related to salt stress. Despite being ecologically distinct, the Cochlearia ecotypes still represent an early stage in the process of speciation, as reproductive isolation has not (yet) developed. A sequenced annotated genome is needed to specifically target candidate genes underlying local adaptation.Speciation encompasses a continuum over time from freely interbreeding populations to reproductively isolated species. Along this process, ecotypes – the result of local adaptation – may be on the road to new species. We investigated whether three autotetraploid  Along this continuum, ecotypes may be formed as a result of local adaptation to specific sets of environmental factors that define different habitats4. Even though the ecotype concept and its role in plant speciation have been subject to heavy debate during the last century2, several empirical studies show non-random organisation of morphological and genetic variation related to more or less steep ecological gradients6, supporting that ecotypes could be considered non-static entities along the speciation continuum. The study of adaptive divergence between ecotypes may, thus, be an important contribution for understanding the process of speciation. Instances of parallel ecotypic divergence where adaptation to similar conditions repeatedly cause similar phenotypic changes in closely related organisms are especially useful for disentangling the respective roles of drift and natural selection in shaping genomic divergence among genomes and for studying the genes underlying local adaptation7. The ecological variation found among populations of the autotetraploid Cochlearia officinalis in northern Norway potentially represents a highly valuable system to explore parallel ecotypic differentiation in plants.Speciation often occurs as a continuous process over time from freely interbreeding populations to reproductively isolated speciesCochlearia (Brassicaceae) constitutes a good example of a group of recently evolved, and in some cases not yet fully differentiated taxa, which most likely diversified during the mid or late Pleistocene10. The taxa inhabit coastal and inland  habitats and are distributed throughout Central and Northern Europe, extending the distribution of the genus into the arctic region11. Most taxa are dependent on a good supply of water or moist soil conditions throughout the year, and parallel adaptation to different types of moist habitats may be important for the diversification within the group13. The taxa together exhibit complex variation not only with regard to ecology and morphology, but constitute also a polyploid complex of diploids, tetraploids, hexaploids, and octoploids18.The genus C. officinalis is a cold-tolerant halophyte, widely distributed along the European coastline20. Gill suggested based on studies of chromosome associations during meiosis in F1 hybrids, that C. officinalis originated by autopolyploidy from the Central European C. pyrenaica17. Molecular data support an autotetraploid origin, although not directly from present day diploids10. Previous studies have found morphological and ecological variation in Northern Scandinavia, which has been suggested to represent differentiation at the ecotypic level, and several subspecies have been recognised21. The common beach ecotype, or ssp. officinalis, grows in gravel beaches  rosette leaves that are fleshier than those of the other two ecotypes. In the beach ecotype, the fruit (silicula) is more spherical in outline than in the estuary and spring ecotypes. The spring ecotype has a tendency to be perennial rather than biennial as is the case for the two other ecotypes. This is indicated by a branching rhizome that gives rise to more rosettes, and by the development of buds before the snow has melted. When comparing plants collected in the field with plants cultivated in common conditions, distinctiveness in flower and fruit characters tended to be stable, whereas the size and shape of rosette and stem leaves, as well as the branching and elongation of inflorescences, were highly plastic depending on environmental conditions16.Nordal and Stabbetorp found that the three ecotypes are not only ecologically differentiated but also to some degree morphologically distinctCochlearia so far25 have not included plants representing the ecotypic variation found in Northern Scandinavia. Using several thousand single nucleotide polymorphisms (SNPs) obtained from restriction-site associated DNA sequencing (RADseq), and microsatellite markers, we explore here whether and to what degree the ecotypes are genetically differentiated. We infer the genetic structure of the three ecotypes from two geographical areas of Northern Norway and we ask whether the ecological and morphological variation that we see today is the result of parallel evolution through local adaptation to different habitats.Genetic studies of C. officinalis ecotypes  were sampled in Northern Norway in two areas , and following the procedure in Lowry et al.27, the retained RAD loci density in the current study was estimated to be 5,329 RAD loci over 734 Mbp, i.e. 7.26 RAD loci/Mbp.From c. 428 million raw paired-end reads obtained from RADseq, c. 163 million forward reads were retained after demultiplexing and cleaning. The second reads in the pairs were only used in the process of demultiplexing based on combinatorial inline barcodes and for extending contigs for the annotation of outlier loci. After is Table . Given tIS) when calculated from the RADseq data, indicating an excess of heterozygotes, estimates confirmed also with our microsatellite analyses (see below). It should be noted that when analysing RADseq data in STACKS, FIS is calculated as 1-(Ho/He). For polyploids we would, however, expect higher levels of heterozygosity than for diploids28, meaning that in our calculations FIS is most likely underestimated by using this approach. The spring population from Sørfjorddalen in Lofoten (SL2) had a lower number of private alleles, and an inbreeding coefficient closer to zero than other populations. This population grows in a spring in an open forest area relatively far from the sea  compared to the estuary (603) and spring (494) ecotypes  was subunitary in all population pairs, suggesting an important role for drift  in shaping the genetic structure of the group. In general, the beach populations had highest connectivity, independent of geographic distance. The other ecotypes were less connected by gene flow (except for the estuary populations from Troms), with the number of migrants within ecotypes not different from that between ecotypes or between regions. The lowest levels of gene flow were found for the isolated spring population from Lofoten (SL2), followed by the two spring populations from Troms. Highest number of migrants was found between the two estuary populations from Troms, which are both geographically and genetically close, followed by the beach populations from both areas . Although only a small percentage (c. 5%) was explained by differences between ecotypes, this part was larger than the variation explained by the two geographic regions (2%).Analyses of molecular variance , based on 4,296 SNPs, the first three axes explained 11.3% of the variation in the data Fig. .Figure 3From a STRUCTURE analysis, based on 4,296 SNPs, K = 4 was selected based on the optimal deltaK and the mean likelihood value , a tree with no migration events was chosen  loci potentially differentiating the beach from the estuary ecotype identified 36 loci within Lofoten and 38 within Troms, with three of the loci in common , indicating slight excess of heterozygotes. A STRUCTURE analysis resulted in similar, though less distinct, patterns of genetic variation as obtained from RADseq data. The degree of admixture varied considerably between single individuals within a population. Based on deltaK, K = 3, followed by K = 7 were suggested as representative number of groups  or as a result of a single origin with subsequent dispersal to areas with suitable habitat7. In addition to the Grindelia example already mentioned31, other recent examples of parallel ecotypic differentiation have been shown in Eucalyptus globules39 and Senecio lautus7, with coastal ecotypes originating polytopically from more widespread, inland ecotypes. Our data, combined with previous morphological, ecological and eco-physiological studies of C. officinalis, build a good case of parallel ecotypic divergence as a result of repeated adaptation to the estuary and spring habitats. Analyses of both the SNP and the microsatellite data show differentiation among ecotypes, but also geographical separation within ecotypes, especially for the estuary and spring ecotypes which by the TREEMIX analysis are suggested to have originated polytopically from the ancestral beach ecotype. Cases of parallel evolution occurring within a species are important for understanding the interaction of natural selection, gene flow and geography on the origin of ecotypes. In our case, these factors or processes have most likely interplayed to produce the genetic patterns that we find among populations of the three ecotypes.Local adaptation occurs when a population evolves traits that support higher fitness in its native environment relative to populations from foreign environmentsST-based outlier tests, which assume neutral genetic drift to affect the entire genome, whereas adaptive loci would be expected to show excess differentiation (outliers) among populations43. A FST-based outlier test of pairwise comparisons between C. officinalis ecotypes (beach vs. estuary and beach vs. spring) for each sampling area resulted in several candidate loci. Many of these are most likely the result of drift but for some outlier loci, we found a match between comparisons in Troms and Lofoten as would be expected if these are adaptive loci, or linked to adaptive loci that have evolved in parallel in the two areas. A couple of outlier loci found in both beach-estuary comparisons , we were able to identify ecologically-relevant loci that could be involved in divergent adaptation.As RADseq is only a representation of the genome, important regions of the genome, and thus also several loci potentially involved in adaptive divergence, are most likely overlookedCochlearia ecotypes still represent a quite early stage in this process where reproductive isolation has not yet evolved. Whether or not the ecotypes may eventually become fully distinct species, studying them may give us the opportunity to observe the processes leading to diversification. In already diverged and well diagnosed species, these processes are usually even more obscured. Young incipient species are more likely to display signatures of selective sweeps that can point to asymmetry in selection between habitats52. Sequenced annotated genomes would open up for this and also for detailed investigations regarding the possible link between autopolyploidy and rapid phenotypic diversification. In this light, the autotetraploid Cochlearia in Northern Norway represents an interesting example of parallel ecotypic divergence, illustrated by non-random organisation of genetic variation across the landscape that may, or may not, in time become reproductively isolated species.Determining the genes and the genetic architecture of traits involved in adaptive divergence between ecotypes is crucial to understand the process of speciation. A common intermediate stage in the process towards reproductive isolation is the evolution of partially reproductively isolated ecotypes, resulting from adaptation to different habitats. Despite being isolated ecologically, or partly so, the Cochlearia ecotypes were collected from each of the two areas in Northern Norway: Troms and Lofoten , following the protocol for dry samples with minor modifications. Before extraction, the samples were crushed for 1–2 min at 20 Hz with two 3 mm tungsten carbide beads in a tissuelyser Retsch MM301 (Qiagen). In most cases, elution with 50 µl (run through once or twice) was used. Before RADseq, the DNA samples were cleaned with NucleoSpin gDNA Clean-up (Macherey-Nagel).PstI, combinatorial inline barcoding, and size selection with magnetic beads. The protocol was adapted from previous studies54, with modifications as indicated below. Altogether 120 Cochlearia samples were included in two libraries (60 samples in each); of these 91 , representing the 12 populations from Northern Norway, were included in the data analyses for this study. For each individual, 125 ng DNA was digested at 37 °C for 2 h with 15 U PstI-HF (NEB). To remove PstI-HF (which cannot be heat inactivated), all samples were cleaned using SPRIselect Reagent Kit (Beckman Coulter) with no size selection. After ligation of P5 adapters, samples with different P5 barcodes were pooled together in five sublibraries and sheared by sonication using a Bioruptor Pico (Diagenode) with three cycles of 45 s “on” and 60 s “off” at 4 °C to achieve an average size of c. 400 bp. Samples were purified with MinElute Reaction Cleanup Kit (Qiagen) followed by left (0.7x) and right (0.55x) side size selection with SPRIselect Reagent Kit. After ligation of P7 adapters, similar cleaning and size selection, this time only on the left side (0.65x), were performed both before and after PCR amplification with Phusion Master Mix (NEB). The libraries were sent to paired-end sequencing, each in one Illumina HiSeq2000/HiSeq2500 lane (100 bp/125 bp) at the Norwegian Sequencing Centre, Oslo, Norway (http://www.sequencing.uio.no/).RADseq libraries were prepared by single digest reactions using 56. To demultiplex the individuals and remove low quality data, the program process_radtags was run with the following settings: PstI as restriction enzyme, removal of any read with an uncalled base, discarding reads with low quality scores, and rescuing barcodes and RADtags. After reads from the two libraries were cut to the same length (94 bp), ustacks, cstacks and sstacks were run with only forward reads. Different values for m , M  and n  were tested to find the settings that maximised the number of reliable loci identified from the reads (see Supporting Information Methods S2 for further details). The settings used in the end were m = 3, M = 4 and n = 1. To further optimise the pipeline for tetraploids, each individual was allowed to have four alleles  by setting the–max_locus_stacks to 5 (default is 3 when expecting diploids). The export_sql.pl script was used to create a whitelist of loci that contained 1–10 SNPs (snps_l = 1 and snps_u = 10). The program populations was used to link the individuals to their respective population and to produce structure-, vcf-, phylip- and haplotype files, each optimised for a specific purpose. Except for the haplotype file, only one SNP per locus was retained (i.e. the first SNP on each locus) to minimise as much as possible linkage of markers. STACKS is, at least at this point, unable to write out full polyploid genotypes, hence our final filtered datasets were diploid-like. A great majority of SNPs are, however, expected to be bi-allelic at the population level, meaning that it is only information about partial heterozygotes which is lost. Information about the filters used  and the number of SNPs obtained in each case can be found in Supporting Information Table 57 for analyses done in GENEPOP v. 4.259 and ARLEQUIN v. 3.5.2.260.Raw Illumina reads were processed with STACKS v. 1.23IS) for ecotypes and single populations were obtained from running the program populations in STACKS. GENEPOP was used to calculate the number of migrants based on private alleles (Nm) for pairwise comparisons of single populations (corrected for size). Violin plots summarising Nm values were constructed using the library vioplot (available from https://CRAN.R-project.org/package=vioplot) in R v. 3.1.2. AMOVAs were run in ARLEQUIN to estimate genetic differentiation among populations and among higher level groups . Analyses using ecotypes were run separately for the two geographical areas. The analysis for Lofoten was done both with and without the spring population SL1 (Himmeltind), as this population turned out to be genetically more similar to the beach populations than to the other spring populations.The number of private alleles and the inbreeding coefficient  had a slight outlier position and was removed in the final PCA to allow for better resolution of the remaining individuals. Population structure was further investigated with STRUCTURE v. 2.3.364 using the admixture model and correlated frequencies. A tetraploid input file was constructed by using the recessive allele option65 and ploidy set to four to allow for ambiguity in partial polyploid heterozygotes66. The analysis was run with K = 1–13, 10 runs for each K, 1 million iterations and burn-in of 100,000 using the Lifeportal at the University of Oslo . Results were summarised in STRUCTURE HARVESTER web v. 0.9.9467 and CLUMPAK beta v.68, producing likelihood and deltaK graphs69. The optimal number of groups converged to the same solution for all replicate runs (confirmed by inspecting the plots) and was visualised using DISTRUCT v. 1.170 and as pie charts on a map of Northern Norway using QGIS v. 2.4.071. The map layer was extracted from GADM version 1.072.The structure file was used to perform a PCA with the R package 73. Splits were created from Jukes Cantor distances and visualised as a neighbour net with each end node representing an individual. TREEMIX v. 1.1274 was used to address historical relationships between populations. Using VCF-tools v. 0.1.1275 and PLINK v. 1.9076, the vcf file was converted to a frequency file that could be transformed to a treemix file using the plink2treemix script available for TREEMIX (https://bitbucket.org/nygcresearch/treemix/downloads). TREEMIX was run with a Scottish C. officinalis population from Aberdeenshire (included in the RADseq libraries) as outgroup, visualised in R and illustrated in combination with the STRUCTURE pie charts. The number of migration events was tested by starting at zero and adding one by one until the residual plot stopped improving.The phylip file was used to produce a phylogenetic network in SPLITSTREE477 was used with default settings. The haplotype file produced from populations was used together with a python script to create the input file (containing haplotype information) for BAYESCAN78. Ecotypes were tested in pairwise comparisons between the likely ancestral ecotype (beach) and the estuary and spring ecotypes, respectively. Tests were performed for each geographical area (Troms and Lofoten) separately and then compared to look for possible common outlier loci. The program sort_read_pairs.pl in STACKS was used to collect the reverse reads (the read pairs) of the outlier loci, and of 1,000 random loci of the catalog in order to construct a reference set for further enrichment analyses. The program exec_velvet.pl in STACKS was used to extend the contigs of the outlier and reference loci. The outlier loci for each comparison and the reference set were annotated and used for further GO enrichment analyses in BLAST2GO v.3.2.779. Fisher’s exact tests were implemented at a threshold p-value of 0.05. The enriched GO terms from each comparison were summarised, applying thinning based on semantic similarity, and visualised with REViGO80.To detect possible RADseq loci under selection, BAYESCAN v. 2.1The STACKS-pipeline as well as TREEMIX and BAYESCAN analyses were run on the Abel cluster, owned by the University of Oslo and the Norwegian metacentre for High Performance Computing (NOTUR).81 was used to test twenty primers developed for other Brassicaceae taxa  that offers a way to estimate the allele frequencies in polyploids by assuming that each of the alleles in a partial heterozygote has an equal likelihood of being present more than once66.Microsatellite genotypes  were assessed in GENEMAPPER v. 3.7 (Life Technologies/Applied Biosystems). The automated scoring was manually edited to make sure that the scoring was plausible, i.e. tetraploids had not more than four alleles, and replicates had identically scored profiles. The R package POLYSAT v. 1.3Supporting Information


There is a long-going debate on the genetic origin of Chinese Muslim populations, such as Uygur, Dongxiang, and Hui. However, genetic information for those Muslim populations except Uygur is extremely limited. In this study, we investigated the genetic structure and ancestry of Chinese Muslims by analyzing 15 autosomal short tandem repeats in 652 individuals from Dongxiang, Hui, and Han Chinese populations in Gansu province. Both genetic distance and Bayesian-clustering methods showed significant genetic homogeneity between the two Muslim populations and East Asian populations, suggesting a common genetic ancestry. Our analysis found no evidence of substantial gene flow from Middle East or Europe into Dongxiang and Hui people during their Islamization. The dataset generated in present study are also valuable for forensic identification and paternity tests in China. Chinese Muslim populations refer to ten officially recognized Muslim ethnic groups, which are Uygur, Dongxiang, Hui, Bo’an, Kazakh, Kirghiz, Salar, Tatar, Tajik, and Uzbek. The origin of those populations via demic diffusion involves mass movement of people or simple cultural diffusion is a long-going debate.According to historical materials, Islam was first introduced to China some 1,400 years ago in Tang Dynasty 618–907 AD) by a large number of soldiers, merchants and political emissaries from Arabia and Persia (nowadays Middle East)3418–907 ADThe origin of Chinese Muslim populations likely involved massive assimilation of indigenous ethnic groupsWe collected blood samples of 163 and 219 unrelated individuals from two Muslim populations Dongxiang and Hui in Linxia, Gansu province. We also collected blood samples of 270 unrelated individuals from Han Chinese in Linxia for comparison purpose. Our study was approved by the Ethical Committee of Gansu Institute of Political Science and Law. The study was conducted in accordance with the human and ethical research principles of Gansu Institute of Political Science and Law. All individuals were adequately informed and signed their informed content before their participation. For each sample, genomic DNA was extracted according to the Chelex-100 method and proteinase K protocolhttp://www.promega.com/) and Cervus 3.0131415161718192021222324252627282930313233343536373840Allele frequency, heterozygosity, polymorphism information content (PIC), power of discrimination (PD), probability of paternity exclusion (PPE), and other forensic parameters were calculated using PowerStatesV12 .Publisher's note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.


Rhodiola fastigiata, using sequences from chloroplast genome and nrITS region, as well as ecological niche modeling. The results of R. fastigiata were compared to other congeneric species that have been studied, especially to R. alsia and R. crenulata. We found that for both markers, two geographic groups could be revealed, corresponding to the QTP plateau and the Hengduan Mountains, respectively, indicating isolated refugia in those two areas. The two groups diverged 1.23 Mya during the Pleistocene. We detected no significant population expansion by mismatch distribution analysis and Bayesian Skyline Plot. We found that even these similar species with similar physiological and life history traits have had different demographic histories in the Quaternary glacial periods. Our comparative phylogeographic study sheds new lights into phylogeographic research that extrinsic environmental changes are not the only factor that can drive population demography, and other factors, such as coevolved interactions between plants and their specialized pathogens, that probably played a role need to be examined with more case studies.How geological events and climate oscillations in the Pleistocene glaciation shaped the geographic distribution of genetic variation of species on the Qinghai-Tibetan Plateau (QTP) and its adjacent areas has been extensively studied. However, little studies have investigated whether closely related species in the same genus with similar physiological and life history traits responded similarly to the glacial climatic oscillations. If this is not the case, we would expect that the population histories of studied species were not driven by extrinsic environmental changes alone. Here we conducted a phylogeographic study of a succulent alpine plant  How geological events and climate oscillations in the Pleistocene glaciation affected the distribution of genetic variation of species over time and space is a central issue in phylogeographic studies . As morePhylogeographic studies in the Qinghai-Tibetan Plateau  have increased in recent years , as thisRhodiola, a genus mainly distributed in the QTP area, provides us an ideal model to study how much plants from the same genus differs in glacial history. There are several species in Rhodiola that have been studied phylogeographically: Rhodiola alsia  and sect. Trifida  S.H. Fu is a perennial herb with a conspicuously elongated rhizome and dense persistent flower stems. It is distributed on rocky slopes at ca. 3500–5400 m in elevation of the QTP area  to extract DNA from silica-gel dried leaves. ITS-1 and ITS-4  primers r trnS-G . Polymerr trnS-G  to aligntrnS-G only occurred in one individual, respectively. To infer phylogenetic relationships among haplotypes and ribotypes, we implemented Maximum parsimony and Bayesian inference to reconstruct phylogeny with PAUP∗ 4.0b10  using DnaSP v5 . We igno∗ 4.0b10  and MrBa∗ 4.0b10 , respectus study . For theus study  were appus study . We set us study  to detecP > 0.05) for the ITS data set, we set the inference parameter as GTR + G model and a strict molecular clock, a constant population size coalescent tree prior and a UPGMA starting tree. We set 20,000,000 MCMC generations with sampling frequency as every 2,000 generations, and the first 5,000,000 generations as burn-in. Tracer  and nucleotide diversity (π) at both population and species level were calculated with DnaSP v5 (1 to estimate average gene diversity with a population (HS), total gene diversity (HT) and two population divergence index . We also performed 1,000 permutations replication to test the significant level. If NST value is significantly higher than GST, more close related haplotypes will cluster  by maximizing FCT value between K groups of geographically adjacent populations. In our study, we set K from 2 to 10. After defining geographic groups, the amount of variation among populations within a group and a population were calculated by the hierarchical analysis of molecular variance (AMOVA) in ARLEQUIN v 3.5  with SAMOVA v 1.0 . This prIN v 3.5 . A non-pD and Fu’s Fs values  and the raggedness index (HRag) of t = τ/2u , k is the average length of sequence data used, and g is the generation time (y). In this study, k was 1,593 bp, and the substitution rate was set to 2 × 10-9 s/s/y  analysis using BEAST2  to estimn Tracer , we drewn Tracer .R. fastigiata, we employed ENMs to model distribution change in response to glacial climatic oscillations. By combining our own data and online herbarium records , we obtained a total of 149 spatially unique localities for the modeling. Data from online databases were checked by the author to exclude misidentification. MAXENT 3.3.3e  for the Last Glacial Maximum (LGM) and the current time from the WorldClim website at a spatial resolution of 2.5 arc-minutes (Supplementary Table S4) with pairwise Pearson correlation coefficients below 0.7 were used. As other study stated, areas under the “receiver operating characteristic (ROC) curve” (AUC)   values we” (AUC) . Finallye” (AUC)  to draw Supplementary Table S2). Unique sequences from each fragment were deposited in GenBank with accession number MH023238-MH023277. Haplotype diversity at the species level was h = 0.852, varying in different populations from 0.000 to 0.803 (SJL-4) (Supplementary Table S1). At the species level, nucleotide diversity was π = 0.0029, with a range from 0.000 to 0.0036 in different populations (Supplementary Table S1). Within-population gene diversity (HS) was significantly lower than total gene diversity (HT) . Twenty-three of the 36 haplotypes were found in only one population (Supplementary Table S2), and others occurred in at least two or more populations with H2 found in 13 of the 22 sampled populations . In the 22 populations, 5 only harbored a single haplotype, while SJL-1 harbored 6 haplotypes .After alignment, the total length of the combined cpDNA sequence was 1,593 bp. Thirty-six haplotypes based on 36 nucleotide substitutions were detected . Sequences were uploaded to GenBank with accession number MH 023219-MH023237. At the species level, ribotype diversity was 0.703, ranging from 0.000 to 0.833 (Supplementary Table S1). Nucleotide diversity π = 0.0018 at the species level, varying from 0.000 to 0.0027 in different populations. Population BDL had the highest ribotype diversity, while BM-2 had the highest π value. Similar to the plastid dataset, within-population gene diversity (HS) was significantly lower than total gene diversity (HT) . Of the 19 ribotypes, 13 only occurred in one population (Supplementary Table S3). 14 out of the 22 populations only harbored one ribotypes, with population BDL had 6 ribotypes, the most in all populations .The aligned ITS sequences was 640 bp in length. We detected 19 ribotypes, defined by 18 nucleotide substitutions , indicating presence of phylogeographic structure. However, we failed to detect a significant phylogeographic structure from the ITS data. In the SAMOVA analysis for both cpDNA and ITS datasets FCT value reached a plateau when K = 3 . In the plastid dataset, the first group consisted of 11 populations on the QTP plateau, and group two comprised 10 populations in the Hengduan Mountains. Group three only had one population on the plateau and was thus merged to group 1 in the discussion hereafter . For the ITS data, we also detected three geographic groups, two of them corresponding to the QTP plateau and the Hengduan Mountains, respectively, and the third group with only two ribotypes was merged to group 1 hereafter as they were also on the QTP plateau. Average FST between revealed geographic groups are shown in Table 2. AMOVA analysis showed that for the cpDNA dataset, 31.89% of the total variations occurred among groups decided by SAMOVA, and 44.77% of the total variations were with populations. For the ITS dataset, variations among groups also accounted for 71.26% of the total variation (Table 3). The Mantel test based on both datasets showed a significant correlation between genetic distance and geographic distance: a pattern of isolation-by-distance .The permutation tests of plastid data demonstrated that Figures 3A, 4A). In the plastid data tree, all haplotypes of R. fastigiata formed a well-supported clade . Two clades (Clades A and B) could be found. Clade A comprised 13 haplotypes and clade B only 3. The haplotype network  depicted relationships between haplotypes more clearly: all haplotypes can be divided into two groups, corresponding to the two geographic groups determined by SAMOVA analysis .We only showed the Bayesian tree as MP and Bayesian methods yield largely congruent topology for both datasets . Similar to the plastid data, although our SAMOVA analysis revealed three geographic groups, group 3 only comprised two ribotypes that had the same distribution area with group 1. Dating analysis based on the ITS data showed that R. fastigiata diverged from its closest relatives at 3.47 Mya  in the Pliocene . Further divergence occurred after 2.41 May , in the Pleistocene.For the ITS data, ribotypes were also divided into two geographic groups . Furthermore, SSD and the raggedness index significantly differed from expected values if an expansion hypothesis is true (Table 4). No significantly negative value of Tajima’s D and Fu’s Fs were also revealed (Table 4). Our Extended Bayesian Skyline Plot (EBSP) analysis revealed a similar pattern: the effective population size of R. fastigiata remained stable in last 0.82 million years, with a slight increasing toward the present time .We did not detect any signal of population expansion of R. fastigiata of present day is generally the same as the actual distribution today . Our result also showed that the distribution of R. fastigiata during the LGM was slightly smaller than present distribution, especially in the eastern QTP and northern part of the Hengduan Mountains . This pattern is in accordance with the EBSP results shown in the last section.The AUC value  showed that our modeling was effectively predictive according to 20 MAXENT replicating runs. The predicted distribution of Rhodiola fastigiata inhabits the subnival belt a little below the permanent snowline, which represents the highest terrestrial habitat that an organism can occupy , indicating great difference among populations, and most variation was at group and population level (Table 3). In addition, NST was significantly greater than GST for the cpDNA data (Table 1), indicating significant phylogeographic structure. However, such phylogeographic structure was not detected in the ITS data. This results indicated that gene flow via pollen is more efficient than via seeds in R. fastigiata, which is congruent with its congeneric species R. kirilowii .n occupy . As specirilowii . AnotherTable 3), and confirmed by our pairwise FST calculation among three groups (Table 2). Molecular dating analysis showed that these two groups diverged at 1.23 Mya (95% HPD: 0.56–2.01 Mya) based on the ITS dataset. Thus we can infer that the Pleistocene climatic oscillations might have triggered the divergence of the two groups. Populations of R. fastigiata might have retreated to isolated glacial refugia in the HM and QTP area during the glacial period. We detected no range expansion both at the species level and in each of the clades of the cpDNA tree . Ecological niche modeling results also support the scenario that later glacial time has little to do with the distribution of the studies species . This result is in congruence with two recent studies focused on several subnival species in the same area , we detected two groups in both markers. The two groups largely corresponded to the Hengduan Mountains area and the QTP plateau platform. A high genetic differentiation among groups were detected by the AMOVA analysis  and ITS markers showed that there were probably three potential refugia, one in the Hengduan Mountain area and the other two on the QTP platform . Although there is overlap between the 95% HPDs, the intra-specific divergence time of R. fastigiata is slightly earlier than that of R. alsia. Besides, R. alsia, whereas such pattern was not revealed for R. fastigiata in current study. A relatively stable population demography was also demonstrated in our ENM data  and EBSP analysis . A recent study also showed that the Quaternary glacial had had little impact on four subnival plants on the QTP . However, mismatch distribution analysis showed that a recent population expansion happened in ca. 0.31 Mya. This expansion was also detected in the EBSP analysis.platform , 2012. T the QTP . Study oR. fastigiata and R. alsia have similar physiological and life history traits, they had different demographic histories in the Quaternary glacial periods, at least based on our analyses. Although previous literature has demonstrated that glacial histories of species with different features  were also distinct . Although this result needs to be treated with caution because of different sampling strategy in different studies, it provides evidence that dioecy in Rhodiola was not evolved to promote cross pollination. Therefore, the alternative hypothesis proposed by Rhodiola often grow on very high altitude and harsh environment where the growing season is very short.It is interesting to compare genetic diversity of hermaphrodite species and dioecious species, because Diocy is thought to evolve to promote outcrossing and increase heterozygosity . We compJ-QZ conceived the ideas and wrote the manuscript. D-LZ, R-WZ, and W-YS conducted the experiments and collected the data. W-JS and D-LZ analyzed the data.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


NE Atlantic), limpets have been extensively exploited probably since islands were first colonized. This has led to profound consequences in the dynamics of rocky shore communities. The Patella candei complex includes various subspecies of limpets that are ascribed to a particular archipelago and has been the focus of several taxonomic surveys without much agreement. Under a conservational perspective, we apply morphometric and genetic analyses to test subspecies boundaries in P. candei and to evaluate its current population connectivity throughout Macaronesia . A highly significant genetic break between archipelagos following isolation by distance was detected . Contrastingly, significant genetic differentiation among islands  was absent possibly indicating ongoing gene flow via larval exchange between populations. Significant shell‐shape differences among archipelagos were also detected using both distance‐based and geometric morphometric analyses. Adaptive processes associated with niche differentiation and strong barriers to gene flow among archipelagos may be the mechanisms underlying P. candei diversification in Macaronesia. Under the very probable assumption that populations of P. candei from each archipelago are geographically and/or ecologically isolated populations, the various subspecies within the P. candei complex may be best thought of as true species using the denomination: P. candei in Selvagens, Patella gomesii in Azores, Patella ordinaria in Madeira, and Patella crenata for Canaries. This would be in agreement with stock delimitation and units of conservation of P. candei sensu latu along Macaronesia.The uptake of natural living resources for human consumption has triggered serious changes in the balance of ecosystems. In the archipelagos of Macaronesia ( For insIn the last few decades, genetic methods have become a tool of excellence in investigating population differentiation estimates of a given species across its distributional range. Particularly, high‐resolution nuclear markers such as microsatellites have been widely applied to conservation genetics  in species of the genus Patella  and environmental variation  is known to occur in this species  form a well‐supported group, while individuals sampled in Selvagens and Canaries always grouped together in a different clade  during the summer of 2011 .Individuals of 1 Figure . In summP. candei morphotypes (“fly” and “smooth”) from Azores was also accessed by means of ANOVA. Given the difficulties in sorting all individuals into the “fly” and “smooth” categories, only distinctive shells of each morphotype were used in the analysis (n = 346). Note, however, that this criteria may upward bias the degree of differentiation between morphotypes.Examination of the spatial variation in shell morphometry among archipelagos was analyzed using a two‐way fully hierarchical analysis of variance (ANOVA) with the following factors: archipelago (fixed) and island (random and nested within archipelago). Analyses were performed using PERMANOVA+ .A total of 83 2 Rohlf,  was used2 Rohlf, . Specime2 Rohlf,  to remov2 Rohlf, . In this2 Rohlf, . A Procr2 Rohlf,  was used2 Rohlf, . Because2 Rohlf, , the ful2 Rohlf,  using th2 Rohlf, . Geometr2.22.2.1Patella candei from the three archipelagos were used for genetic analysis  on 10 μl reactions containing ~30 ng DNA template, 1 × QiagenTM Multiplex PCR Kit, 0.5–1.2 μmol/L of each primer and ddH2O. Genotyping was performed on an ABI 3730 (Applied Biosystems) automated DNA sequencer using an internal size standard  for accurate sizing and GENEMAPPERTM v.4.2 (Applied Biosystems) was used for allele calling.A total of 560 individuals of s Figure . Upon cos Figure . Briefly2.2.2HO and HE) were estimated in GenAlEx v.6.4.1 , linkage disequilibrium, and deviations from the Hardy–Weinberg equilibrium (HWE) were tested in GENEPOP v.4.2 . The effect of null alleles in FST estimates was assessed by comparing FST before and after correction for null alleles using the excluding null alleles (ENA) method implemented in FREENA. Genetic differentiation between populations was also determined using the Dest estimator . For all analyses involving multiple tests, significance levels were adjusted by the FDR method.Pairwise  Goudet, , and depor Jost,  implemenor Jost, , and p‐vK) and assign individuals to genetic clusters. Assignment is conducted in ways that minimize deviations from Hardy–Weinberg and linkage equilibrium within each cluster. No particular population structure was assumed a priori (LOCPRIOR = 0), and ten independent runs were carried out for each value of K (1–11). Length of the burn‐in period was set to 1 × 105 followed by 5 × 105 Markov chain Monte Carlo (MCMC) iterations. Correlated allele frequencies and admixed populations were assumed. Modifications in such parameters produced consistency and did not change the final results. Selection of the most likely number of genetic clusters (K) was based on checking the posterior probability of the data for a given K  was also performed to identify and describe clusters of genetically related individuals , among populations within archipelagos (FSC) and within populations (FST) was assessed, and significance of F‐statistics was tested using 10,000 permutations. Estimates of genetic differentiation were also determined among the “fly” and “smooth” morphotypes of P. candei from Azores.Tests for genetic differentiation among archipelagos were also conducted using analysis of molecular variation (AMOVA) in ARLEQUIN v.3.5.1.3  was regressed onto the natural log of geographic distances  among populations/clusters identified in STRUCTURE were estimated using the Bayesian multilocus genotyping procedure implemented in BAYESASS v.3.0.   between 1.35 and 6.35 cm, with a mean size of 3.25 ± 0.03 cm (mean ± SE). Although variable across islands (ANOVA p < .001), mean SL did not differ among archipelagos . Differences were only detected for shell conicity, with “fly limpets” being more conical then “smooth limpets.”Shell samples of 3.2P. candei . The amount of shape change per unit of size change differed among archipelagos and was greater in Azores (indicated by the lengths of slope vectors)  from Azores, the Procrustes ANOVA analysis revealed a significant interaction between morphotype and size, which is indicative of allometric growth. The null hypothesis for common allometries  among morphotypes was rejected , and differences were detected in the amount of shape change per unit of covariate change (size) between morphotypes; shape change per size unit is higher in “fly” limpets  Table . Yet, shs) Table . This cos) Table . Signifis) Table . For bots) Table . The firgos Fig. . As for ts Table . Overallell Fig. .3.3P. candei from the Azores  were relatively low and ranged from 0.157 to 0.364, while expected (HE) heterozygosity frequencies ranged from 0.304 to 0.484 (Table FIS) ranged from 0.073 to 0.746 denoting a heterozygous deficit in such loci. Overall, significant FIS values were often ascribed with the presence of null alleles. To check for any bias in the results, loci with a presence of null alleles >10% were removed from the analysis. Such removal did not affect genetic differentiation results (data not shown) and unless stated otherwise, all loci were included in subsequent genetic analyses. In fact, the influence of null alleles has been shown to be marginal when compared to other factors such as number of loci and strength of population differentiation  (Table p < .001)  Fig. . Furtherly Table .FST and Dest. In fact, the genetic structure inferred from the 560 individuals of P. candei and the 12 microsatellite loci using the Bayesian model‐based clustering algorithm, and the model‐free DAPC clustering algorithm, provided similar results  were identified when considering all locations, with Azores samples being separated from the Madeira and Canaries populations. Similarly, two well‐defined clusters were retrieved on the Madeira and Canaries assignment analysis. Both STRUCTURE and DAPC also suggested population homogeneity for P. candei in Azores (K = 1). In this case, for the STRUCTURE analysis, the estimated membership of individuals to any given cluster was roughly symmetric (~1/K in each population), indicating that individuals in Azores are widely admixed and belong to a single panmictic population , 0.2% among populations of the same archipelago (p = .268), and 63.1% within populations (p < .001). Furthermore, a significant positive relationship was observed between genetic differentiation estimators (FST and Dest) and geographic distance .The STRUCTURE and DAPC analyses provided support for the genetic differentiation indicated by e Figure . No geneP. candei were consistent across all preliminary trials and runs and showed mean values very close to 0 . The observed migration rates were independent of geographic distance as migration between archipelagos was similar and virtually absent.The results of the migration rates estimated in BAYESASS suggest a consistent restriction in contemporary gene flow between archipelagos Table . Yet, fr 0 Table . Such sm4P. candei complex across Macaronesia (NE Atlantic). Our results revealed highly structured populations among archipelagos, which are likely associated with strong barriers to gene flow. Although isolation by distance (IBD) was detected among archipelagos, connectivity within archipelago  does not follow IBD, with genetic homogeneity among populations  being maintained possibly via broad larval exchange. Moreover, shell shape differences among archipelagos were also detected and are likely the consequence of mixed effects of historical vicariance and recolonization events, genetic drift, and local adaptations.Here, we investigate current signs of population differentiation and connectivity in the Patella candei complex across Macaronesia is highly differentiated and that each subspecies (or species) endorsed to a given archipelago should be treated as a single conservation unit.Limitations to this study include the lack of samples from some Macaronesia islands , so that results among archipelagos cannot be fully explored in comparison with patterns within archipelagos. Despite this shortcome, the inclusion of samples from Madeira and Canaries allowed showing that the 4.1P. candei morphotypes among and within archipelagos. The differences found between both methods are likely associated to (1) the fact that distance‐based data contain relatively little information about shape because many of the measurements overlap and/or are correlated to each other, and shape can only be derived from ratios among particular measurements and (2) the inclusion of shell height to the distance‐based method provides a third dimension, which is absent in geometric morphometrics that only considers a two‐dimensional reduction of shape in current analyses. Depicting the results, distance‐based methods show that samples from Azores exhibit a more conical and elliptical shell shape compared to samples from the Canaries and Madeira, with the later descriptor being influenced by size. In fact, shell shape allometries derived from geometric morphometrics differ among archipelagos, and globally, differences are mostly found between Madeira samples and the remaining archipelagos; both small and large limpets from Azores and Canaries are more similar between them than with samples from Madeira. Whereas genetic data suggest a closer relationship between P. candei from Madeira and Canaries populations  , the minimum and maximum distances among any pair of adjacent islands that pelagic larvae must travel among islands are approximately 32 and 220 km, respectively. Such distances do not seem to offer an obstacle and allow populations’ gene pool across all islands to be homogenized via larval transport. Although genetic differentiation among archipelagos seems to be highly correlated with geographic distance, the unbalanced nature of sampling, the fact that connectivity within archipelago  does not follow IBD, and the results provided by BARRIER  and P. candei crenata in Canaries islands; although isolated specimens of P. candei candei were identified in El Hierro and Tenerife islands, this co‐occurrence is now mainly restricted to a single island: Fuerteventura . This is likely a consequence of overexploitation . Furthermore, both environmental awareness programs to general population and coastal enforcement by local authorities should be stimulated. Above all, we suggest the establishment of fully enforced closed zones to limit the access to rocky shore poachers and allow limpet populations to grow in numbers and individual sizes. These off‐limit areas should be regularly surveyed and take into consideration population connectivity patterns within archipelagos. Our data suggest that, at least for Azores, such areas should distance no more than ~200 km, to allow proper gene exchange between populations. Additional sampling throughout all Macaronesia islands can further sharpen our knowledge about connectivity patterns in P. candei and help better defining the establishment of such areas within each archipelago.Our results support the view that populations from each archipelago should be managed for conservation as distinct units. Within the P. candei from each archipelago forms a geographically and/or ecologically isolated population, the various subspecies within the P. candei complex as previously proposed by Christiaens , José Azevedo in Pico (Azores), André Amaral in Terceira (Azores), Pedro Raposeiro in Flores and Corvo (Azores), and Fernando Tuya and Manuel Rivas in Canarias. We thank Michael Collyer (Western Kentucky University) for help in geometric morphometrics. This research was partially supported by the European Regional Development Fund (ERDF) through the COMPETE—Operational Competitiveness Programme and national funds through FCT—Foundation for Science and Technology, under the projects PTDC/BIA‐BIC/115837/2009 and PEst‐C/MAR/LA0015/2013, by the Strategic Funding UID/Multi/04423/2013 through national funds provided by FCT—Foundation for Science and Technology and European Regional Development Fund (ERDF), in the framework of the programme PT2020 and by cE3c funding (Ref: UID/BIA/00329/2013). JF was funded by a PhD grant M3.1.2/ F/021/2011 by the Regional Government of the Azores. GMM was supported by postdoctoral grants awarded by FCT, Portugal (SFRH/ BDP/63040/2009). PAR was funded by the Portuguese Foundation for Science and Technology, through a postdoctoral grant ref. SFRH/BPD/69232/2010 funded through QREN and COMPETE, and the strategic project UID/MAR/04292/2013 granted to MARE.None declared.https://doi.org/datadryad.org/review?doi=10.5061/dryad.d3vk4.Data used for this article  have been deposited in Dryad, JF and GMM conceived the study and all co‐authors equally contributed to its final design. JF performed all the analyses. AP and PP assisted JF with the validation of genotypes and genetic analyses. GMM assisted JF with multivariate analysis. AIN coordinated sampling. JF and PR were involved in sample collection. JF interpreted the results with input from GMM, SJH, PP, and AIN. JF wrote the manuscript with input from all co‐authors. Click here for additional data file.


This geographical region is particularly interesting because of the extensive population flux following diverse migration routes, and the complex interactions between distinct population groups during the medieval period. We successfully amplified and typed the mitochondrial control region of 10 individuals. For five of them, we also reconstructed the complete mitochondrial genomes using hybridization-based DNA capture combined with Next Generation Sequencing. We have portrayed the genetic structure of the Capidava medieval population, represented by 10 individuals displaying 8 haplotypes . Remarkable for this site is the presence of both Central Asiatic (N9a) and common European mtDNA haplotypes, establishing Capidava as a point of convergence between East and West. The distribution of mtDNA lineages in the necropolis highlighted the existence of two groups of two individuals with close maternal relationships as they share the same haplotypes. We also sketch, using comparative statistical and population genetic analyses, the genetic relationships between the investigated dataset and other medieval and modern Eurasian populations.Given the paucity of archaeogenetic data available for medieval European populations in comparison to other historical periods, the genetic landscape of this age appears as a puzzle of dispersed, small, known pieces. In particular, Southeastern Europe has been scarcely investigated to date. In this paper, we report the study of mitochondrial DNA in 10 Greeks, Romans, Byzantines, Pechenegs, Tatars, etc.) [nd century AD when the Romans settled and became aware of its strategic importance, until the 11th century when the Pecheneg invasion ended the Byzantine inhabitation of this location [th century AD when Capidava is alternatively dominated, in the context of continuous conflicts between the Byzantine Empire, the Kievan Rus’ and the proto-Bulgarians, by each of them. Questions regarding the impact and extent of these past political and associated demographic events, that left imprints on the local genetic structure and influenced the current European gene pool remain unanswered, even though, the first elements of evidence could be inferred from the archaeological context [Dobruja is a historical region of Southeastern Europe, situated between the lower Danube River and the Black Sea. Today, this area is shared by Romania and Bulgaria, but in the historical past the territory surrounding the lower section of the Danube basin was a continuous territory and under the periodic domination and influence of distinct powerful state entities  , 2, beins, etc.) . A witnelocation . Capidav context . Additio context –8.Currently, most information on the genetic landscape of Romanian populations is based on mtDNA diversity in present-day inhabitants. A few studies attempted to evaluate their genetic relationship with other Eurasians –11, wherde facto result of an original genetic pool modeled by familial relationships and immigrants arriving on different migratory routes, in different historical periods.The aim of this study was to determine the genetic architecture of maternal lineages in a medieval population from Capidava, Dobruja, Romania, and also to evaluate the relationships to other medieval and modern populations from Europe and Asia. Medieval mtDNA information can be knitted together with archaeological and historical data to provide a better understanding of the impact of local events on the genetic structure of larger subsequent populations which are the extra muros), in the Dobruja region, Constanța county, Capidava village, during the 2010–2014 campaigns. Yearly systematic archaeological research is carried out at this site under the coordination of the National History and Archaeology Museum—Constanța and authorized by the Romanian Ministry of Culture and National Identity through the National Commission of Archaeology. Permit numbers for the 2010–2014 campaigns are: 33/2010, 105/2011, 52/2012, 69/2013 and 45/2014. Reports detailing all archaeological excavations are yearly published in the Cronica Cercetărilor Arheologice series, edited by the National Institute of Heritage, in Romanian (cronica.cimec.ro). All human remains excavated from the X extra muros zone in this time frame were transferred to a permanent collection deposited for research at the Molecular Biology Center, Interdisciplinary Research Institute on Bio-Nano Sciences, “Babeș-Bolyai” University in Cluj-Napoca and carry the above mentioned codes. The collection is open to researchers, upon request.In this study we processed eleven archaeological human remains sets, identified as: Cap-M1, Cap-M2, Cap-M3, Cap-M4, Cap-M5, Cap-M6, Cap-M8, Cap-M9, Cap-M11, Cap_M15, Cap_M17, retrieved from the Capidava necropolis . The filtration product was separated into two equal aliquots, for specific downstream applications regarding DNA and proteins. Further purification of DNA was performed using the Animal and Fungi DNA Preparation Kit  according to manufacturer’s specifications, resulting in a final total amount of 50 μl DNA extract.For results authentication, a second extraction was performed in the case of four samples , using an extraction method, designed in our laboratory, to co-purify DNA and proteins from archaeological remains. This protocol employs overnight decalcification of dental powder in 1.5 ml of 0.5 M EDTA solution pH 8.0 under permanent stirring, followed by the use of centrifugal filter units for concentration and purification of biological solutions , 1x MangoTaq™ Colored Reaction Buffer, 2.5 mM MgCl2, 0.2 mM dNTP mix, 0.5 μM each primer, and PCR-grade water  up to 25 μl. The applied thermocycling conditions were: initial denaturation at 95°C for 5 min, 35 amplification cycles consisting of three steps  and final elongation at 72°C for 5 min. PCR products were checked on 1.5% agarose gel and then purified using FavorPrep GEL/ PCR Purification Kit , according to the manufacturer’s protocol. All amplified target sequences were cloned , and a minimum of six clones per amplicon was commercially sequenced  using the standard primer pJET1.2R.Both hypervariable segments (HVS-I and HVS-II) of the mitochondrial genome were amplified using four overlapping fragments that span each of the HVS, with an average size of 141 bps . Additiopost-mortem damage and/or potential contamination. HVS-I (np range 16009–16390) and HVS-II (np range 57–357) mutational motifs and coding region polymorphic positions were inferred by comparison to the revised Cambridge Reference Sequence (rCRS: NC_012920.1) [MtDNA sequences were aligned using BioEdit Sequence Alignment Editor v. 7.2.5.0  in order12920.1) . Haplogr12920.1) .For results authentication, a subset of samples  were independently processed in the Laboratory of Molecular Anthropology and Paleogenetics, University of Florence, Italy, a facility exclusively dedicated to ancient DNA investigations. Instead of using the classical method for the retrieval of genetic information from degraded samples, Next-Generation Sequencing (NGS) approach was used and the whole mitochondrial genome of the individuals was reconstructed.DNA extraction was carried out using a commercial silica columns protocol designed to also recover very short DNA fragments, dominant in ancient samples . Prior tA specific pipeline developed for the analysis of aDNA NGS data was used to retrieve the genetic information of the individuals from Capidava necropolis and to test for the authenticity of the obtained sequences. Primary data analysis was completed by means of the SeqPrep tool : adapterMolecular analyses for another subset of samples  were replicated by another independent research group at the Department of Genetics, Physical Anthropology and Animal Physiology, University of the Basque Country UPV/EHU, Bizkaia, Spain. DNA was isolated from four teeth using the protocol based on guanidine thiocyanate and silica columns . The exthttp://www.mbio.ncsu.edu/BioEdit/bioedit.html) and the sequences were aligned manually [The processing of the ancient samples in the UPV/EHU laboratory involved the application of a series of strict criteria for the authentication of results, as detailed by several authors , 41. Seqmanually .Sequences corresponding to each medieval individual from Capidava were submitted to NCBI GenBank under the accession numbers MF320129-MF320142 and MF597774-MF597782.MtDNA profiles of medieval individuals from Capidava were compared with a data set of 15368 contemporary mtDNA sequences of the HVS-I region comprising European, Near Eastern and Asian populations. Another data set consisting of 495 medieval sequences corresponding to 13 populations originating from Europe and one from Asia was compiled in order to evaluate genetic relationships between the population analyzed in this study and other medieval populations. All sequence data were assembled from available published data, as listed in the electronic supplementary material Basic statistical methods were implemented for comparison and calculations of genetic distances between the examined population and other 14 ancient and 35 present-day populations. Diversity indices for the Romanian medieval population  were calculated in DNASP v5  using boPrincipal Component Analysis (PCA) was performed based on mtDNA haplogroup frequencies of medieval and modern populations  Tables. All PCs derived from the medieval PCA were used for hierarchical clustering, using Ward’s agglomerative method  and EuclST) among populations were computed based on control region haplotypes of uniform sequence length, ranging from nucleotide position 16050 to 16383. Cytosine insertions at position 16193 were excluded from statistical analyses and all comparisons. The best fitting evolutionary model and the estimate of the gamma parameter were inferred from jModeltest 2.1.10 [ST values were computed for both medieval and modern data sets, assuming a Tamura & Nei substitution model [ST values and significant p-values of the ancient populations  was performed in order to detect and compare the mtDNA haplotypes shared between the 15 medieval populations, by counting the absolute and relative shared haplotypes .post-mortem DNA damage in all cloned mtDNA inserts suggest the assigned haplotypes are authentic.MtDNA sequences obtained in all three laboratories during this study , originating from the medieval Capidava necropolis are detailed in The 10 sequences that were successfully retrieved for the Capidava skeletal remains, spanning positions 37–357 and 16009–16390 belong to 8 haplotypes (haplotype diversity of 0.956). The unstable length polymorphisms associated with poly-C stretches between sites 302–315 has been ignored. Identical haplotypes were identified in two groups of two individuals derived from neighboring burials. One group of adult individuals that might be maternally related (M3 and M4) belong to hg R0a2’3, even though a first attempt to characterize their mitochondrial genetic material yielded a faulty, at that stage unverified assignment . The othThe direct radiocarbon dating performed on the M4 human bones placed the remains at 880 and 990 cal. AD  which corresponds to the age estimated according to the archaeological record. The medieval Capidava population analyzed here has a predominantly Western Eurasian haplogroup composition , the Eastern Eurasian component being represented by hg N9a with a frequency of 12.5% . In contBesides confirming the polymorphism pattern uncovered in the control region, the complete mitogenomic data of five individuals allows for the refinement of haplogroup assignment that was initially described by the hypervariable regions mutational motifs. According to the high-resolution mitogenomic data, M2 sample belongs to V1a maternal lineage, a typical Western Eurasian V sub-clade, that is currently distributed, based on complete modern mitochondrial data, across all over Europe and European Russia. Information from whole mtDNA sequencing reveals that this medieval sample matches two other ancient samples, one Early Bronze Age specimen from Germany (MF498721)  and a NeThe PCAs of ancient and modern-day populations were computed based on mtDNA haplogroup frequencies  Tables. The PCA plot of the contemporary Eurasian populations and the Capidava population shows the agglomeration of the European ones on the PC1 (23.38% variance) and PC2 (15.73% variance) components, in contrast to modern Asian populations which are scattered . Along Pversus the investigated medieval Capidava population and, respectively, a set of present-day populations from Eurasia. When compared to other populations dating from similar historical periods, the medieval population from the current Southeastern territory of Romania showed non-significant differences from all populations (p>0.05), the smallest p-values, associated to the highest FST values, being observed in medieval population from Slovakia (SVK-med) with p = 0.08336±0.0028 and FST = 0.05047 and in medieval Italians (ITA-med) with p = 0.12999±0.0036and FST = 0.04055 (ST) values and significant p values of ancient populations are visualized on the Pairwise genetic distances were computed for 14 medieval populations  0.04055 . The linST values and their corresponding p-values are listed in the ST values on a multi-dimensional scaling plot  and also from a modern Turkish population (TUR), while the highest distances were noted relative to modern populations from Central and Southern Asia, as well as to current inhabitants of Dobruja. In either of these cases, the values were not significant (p>0.05) which is not quite surprising given the small sample size of the analyzed population and the different and very diverse haplotype composition. The exact Fing plot . This ilST calculation, showing that the medieval population from Romania shares most of the haplotypes with medieval populations from Spain and Italy  may be more informative than common genetic variants. The presence of the Central Asian N9a haplotype connected to ancient and conqueror Hungarian individuals, an ancient Siberian sample and modern Volga-Ural, Southwestern Russian, and Czech groups seem to place Capidava in a genetic landscape dominated by Turkic influences. Genetic affinities towards Central Asia are more straightforwardly illustrated by the high-resolution mitochondrial data as both M9 and M11 share their two private coding region variants with two modern individuals, one belonging to the Tubalar ethnic group (Altai Republic) and one belonging to the Kyrgyz ethnic group. The further classification of the common “European” lineages (H and V) into H5e1a1, H13a1a3, and V1a points out to genetic connections much more restricted to Central and Eastern Europe, decreasing thus the strength of the apparent link to medieval populations from Southern Europe which emerged from the analysis of low-resolution H haplotypes. Therefore, the phylogenetic and phylogeographic interpretation of the complete mitochondrial data, generated by NGS, counteracts to some extent the effects of the small sample size, emphasizing very precise and direct links among closely related old and modern mitogenomes.Low-resolution data obtained in this study suggest that in this particular case the haplogroups with low frequencies in modern populations Click here for additional data file.S2 FigPercentual AU p-values are given as red numbers on the dendogram.(TIFF)Click here for additional data file.S3 FigThe PCA is based on mtDNA haplogroup frequencies of the medieval population from Romania and 35 modern-day populations from Eurasia, and shows PC1 and PC3. The haplogroup frequencies and population information are listed in the (TIFF)Click here for additional data file.S4 FigThe levelplot is based on the percentage values of the relative shared haplotypes, also shown in the figure. The absolute values and the population information are given in (TIFF)Click here for additional data file.S1 Table(XLSX)Click here for additional data file.S2 Table(XLSX)Click here for additional data file.S3 Table(XLSX)Click here for additional data file.S4 Table(XLSX)Click here for additional data file.S5 Table(XLSX)Click here for additional data file.S6 Table(XLSX)Click here for additional data file.S7 Table(XLSX)Click here for additional data file.S8 Table(XLSX)Click here for additional data file.S9 Table(XLSX)Click here for additional data file.S10 TableHVS-I and HVS-II motifs of the researchers who had been in contact with the ancient samples.(XLSX)Click here for additional data file.


Rhipicephalus appendiculatus is the main vector of Theileria parva, wich causes the highly fatal cattle disease East Coast fever (ECF) in sub-Saharan Africa. Rhipicephalus appendiculatus populations differ in their ecology, diapause behaviour and vector competence. Thus, their expansion in new areas may change the genetic structure and consequently affect the vector-pathogen system and disease outcomes. In this study we investigated the genetic distribution of R. appendiculatus across agro-ecological zones (AEZs) in the African Great Lakes region to better understand the epidemiology of ECF and elucidate R. appendiculatus evolutionary history and biogeographical colonization in Africa.The ixodid tick cox1 and 12S rRNA) of 218 ticks collected from cattle across six AEZs along an altitudinal gradient in the Democratic Republic of Congo, Rwanda, Burundi and Tanzania. Phylogenetic relationships between tick populations were determined and evolutionary population dynamics models were assessed by mismach distribution.Sequencing was performed on two mitochondrial genes . We observed significant genetic variation segregating the two lineages and low structure among populations with high degree of migration. The observed high gene flow indicates population admixture between AEZs. However, reduced number of migrants was observed between lowlands and highlands. Mismatch analysis detected a signature of rapid demographic and range expansion of lineage A. The star-like pattern of isolated and published haplotypes indicates that the two lineages evolve independently and have been subjected to expansion across Africa.Population genetic analysis yielded 22 R. appendiculatus lineages occur in the Great Lakes region. Lineage A, the most diverse and ubiquitous, has experienced rapid population growth and range expansion in all AEZs probably through cattle movement, whereas lineage B, the less abundant, has probably established a founder population from recent colonization events and its occurrence decreases with altitude. These two lineages are sympatric in central and eastern Africa and allopatric in southern Africa. The observed colonization pattern may strongly affect the transmission system and may explain ECF endemic instability in the tick distribution fringes.Two sympatric The online version of this article (10.1186/s13071-018-2904-7) contains supplementary material, which is available to authorized users. Rhipicephalus appendiculatus is the main vector of the protozoan pathogen Theileria parva, the causative agent of a fatal lymphoproliferative cattle disease known as East Coast fever (ECF). East Coast fever is a highly pathogenic and the most economically important tick-borne disease of cattle in 12 sub-Saharan African countries, including Burundi, Democratic Republic of Congo and Rwanda [Rhipicephalus appendiculatus is the most abundant tick in the Great Lakes region of Central Africa, where its burden and distribution vary significantly among agro-ecological zones (AEZs) [The ixodid brown ear tick s (AEZs) . The geos (AEZs) , 6.R. appendiculatus, could play a significant role in spreading ticks and pathogens [The Great Lakes region of Central Africa is characterised by cattle movement within and between countries for trade, breeding and pasture , 8. Duriathogens –14. Therathogens –17. Thusathogens , 19.Ecological establishment and population genetic structure of ticks can be affected by founder events and gene flow, largely due to their dispersal across geographical zones through host migration , 20. ArtR. appendiculatus to changed environment suggests genetic divergence between geographical stocks and phenotypic variations, including diapause behaviour and vector competence to transmit T. parva [R. appendiculatus stocks acquire and transmit T. parva is partially genetically dependent because of the heritability of their susceptibility to infection [T. parva strains in the field associated with different clinical features and disease outcomes, and variable cross-immunity levels. Studies suggest that there are also specific interactions between R. appendiculatus and T. parva stocks in the transmission dynamic system, significantly affecting the epidemiology of ECF [R. appendiculatus populations; (ii) its dispersal pattern; and (iii) its demographic history [The adaptive mechanism of T. parva , 24. Thenfection . Furthery of ECF . Thus, p history , 28.R. appendiculatus has been studied in different African countries using various molecular tools, such as mitochondrial DNA [, namely the eastern and the southern African lineages [R. appendiculatus genetic groups may have a wide geographical range, with different ecological preferences and phenology in sub-Saharan Africa [The genetic diversity of rial DNA , 29 and rial DNA . Two dislineages  found thn Africa –34, due n Africa  and diapn Africa , 37.R. appendiculatus lineages in the Great Lakes region of Central Africa, where cattle mobility seems to be the main factor of tick dispersal and epidemic instability of ECF [R. appendiculatus, including ticks from distinct agro-ecological conditions of DR Congo, Burundi and Rwanda, are important to shed light on the intra and inter population variation, the dispersal pattern and the historical dynamics of the characterised lineages in various ecological situations of Africa. The objective of this study was to assess the evolutionary relationship between R. appendiculatus populations and to investigate the impact of geographical locations on its genetic structure, to better understand the epidemiology of ECF in the Great Lakes region. To achieve this objective, we sequenced and analysed fragments of the cytochrome c oxidase subunit 1 (cox1) and the 12S ribosomal RNA (12S rRNA) gene loci. The genetic structure of R. appendiculatus provides clues to a better understanding of the epidemiology of ECF and insight into the development of targeted selective management and control strategies.Major gaps in knowledge still exist concerning the agro-ecological colonization and establishment of the y of ECF , 38. ThuTicks were collected from cattle in six agro-ecological zones (AEZs) of the Central African Great Lakes region  Fig. . The thrIn eastern DRC, ticks were collected along an altitudinal transect in South-Kivu province. Based on elevation and geographical position within the transect, three major AEZs were defined from lowlands to highlands, namely, DRC AEZ1 (lowlands) in the Ruzizi Valley, DRC AEZ2 (midlands) in the administrative district of Walungu and DRC AEZ3 (highlands) in the district of Kabare and the highlands part of Walungu (Mulumemunene). The lowlands region (DRC AEZ1) is the warmest AEZ, characterised by a tropical dry climate (semi-arid), with a cool dry season of 4–5 months. Cattle are raised generally in an open grazing system in communal pastures of savannah grassland. In contrast, the “upland Kivu” (DRC AEZ2 and AEZ3) has a montane humid tropical climate and is much cooler. The warm dry season lasts for 3–4 months, with occasional and poorly distributed rainfall.Ticks from Burundi were collected from two AEZs. The sampled administrative districts included Rugombo and Gihanga in the Imbo lowlands (Burundi AEZ1) and Muramvya, Mwaro and Mugamba districts of the Congo-Nile highlands (Burundi AEZ3). The Imbo region extends along the Ruzizi River and the North of Lake Tanganyika. The vegetation is composed of savannah and small patches of forest.Ticks from Rwanda were obtained from the eastern low plateau in Nyagatare, Gatsibo and Kayonza districts (Rwanda AEZ2). This region includes the savannah of eastern province of Rwanda. The eastern semi-arid plateau zone is the most important pastoral region in Rwanda, holding 40% of the national herd raised in a communal grazing system. The vegetation type is largely savannah and some river bank woods.Ticks were collected from cattle during a cross-sectional survey conducted from February to April 2015 (late rainy season) in the six AEZs. In each AEZ, 8 to 12 cattle herds were selected randomly using a random number generator in Microsoft Excel. From ticks collected in each herd representing a location or village, 4 to 5 ticks were selected using the same random process for further analysis. The number of ticks sampled in each population is shown in Table Total genomic DNA was isolated from whole individual ticks using the DNeasy® Blood and Tissue Kit  according to the standard manufacturer’s protocol, except that an additional incubation of 10 min at 56 °C was added after mixing the sample with 200 μl buffer AL to ensure optimal cell lysis. Prior to extract DNA, ticks were washed twice in double distilled water and left to dry for 10 min at room temperature and homogenized by grinding.cox1 and 12S rRNA gene loci to assess the genetic diversity and phylogenetic relationships of R. appendiculatus populations. A 710 bp fragment of cox1 gene locus was amplified with the forward primer LCO1490 (5'-GGT CAA CAA ATC ATA AAG ATA TTG G-3') and the reverse primer HC02198 (5'-TAA ACT TCA GGG TGA CCA AAA AAT CA-3') as previously described by Folmer et al. [12S rRNA gene locus we used the primers SR-J-1499 (5'-TAC TAT GTT ACG ACT TAT-3') and SR-N-14594 (5'-AAA CTA GGA TTA GAT ACC C-3') with a fragment size of 380 bp, described in Simon et al. [cox1 and 12S rRNA gene fragments were performed using 50 ng of genomic DNA, 25 μl of 2× AccuPower® PCR PreMix , 0.2 μM each of forward and reverse primers, and nuclease free water added up to a final reaction volume of 50 μl. The thermal cycling program for cox1 consisted of an initial denaturation at 95 °C for 3 min followed by 35 cycles of denaturation at 94 °C for 1 min, annealing at 40 °C for 1 min and extension at 72 °C for 1 min. The final extension was carried out for 10 min at 72 °C. PCR parameters of 12S rRNA gene fragment were as described for cox1, except that the annealing temperature was 52 °C and the extension time was 90 s. PCR products were analysed by electrophoresis on a 1.8% agarose gel. Amplicons were purified using the QIAquick® PCR Purification Kit  following the manufacturer’s instructions. Both strands were sequenced directly with the same primers used for PCR, on an ABI 3730 capillary sequencer .Given the suitability of mitochondrial genes to discriminate intraspecific variation in ticks , 31, we r et al. ; for then et al. . PCR ampcox1 and 12S rRNA genes, respectively. Aligned and trimmed sequences were subjected to a BLAST search against all NCBI nucleotide databases, with default settings to confirm their species identity. A total of 219 sequences for cox1 and 126 for 12S were obtained after quality check processing. To check for amplification of nuclear pseudogenes and confirm protein coding, all cox1 nucleotide sequences were translated into their amino acid sequences to examine the presence of ambiguous stop codons for correct coding of invertebrate mitochondrial DNA.Forward and reverse chromatograms for each individual tick were visually checked. Sequences were manually edited and assembled using CLC Main Workbench software v7.8.1 . Multiple sequences were aligned with CrustalW algorithm using default settings in the same software. The sequences were then trimmed to exclude poor quality bases and obtain uniform sizes. The final sequence sizes were 586 bp and 346 bp for cox1 gene sequences. Population genetic indices represented by number of haplotypes (h), number of segregating sites (S), haplotype diversity (Hd), mean number of pairwise nucleotide differences within population (K) and nucleotide diversity (π) were calculated for each AEZs (named populations) and for the overall data set using Arlequin v3.5.2.2 [Nm) exchanged among populations, average number of nucleotide differences between populations (KXY) and population pairwise genetic differentiation (FST) also in Arlequin [Multiple sequences extracted from the alignments were used to construct haplotypes in DnaSP software v5.10.01 . Geneticv3.5.2.2  and DnaSArlequin . Their scox1 haplotypes implemented in Arlequin [SSD) were estimated to determine if the observed mismatch deviated significantly from a population expansion model, and the Harpending’s raggedness index (RI) were used to evaluate the smoothness of mismatch distribution [Fs [D [D test is based on the difference between the number of polymorphic sites and the mean number of nucleotide pairwise differences, while Fu’s Fs test is based on haplotype frequencies. The significance of all these statistics was tested by bootstrap resampling of 1000 coalescent simulations. Significant negative values of neutrality statistics should indicate a signature of historical event of population expansion, whereas significantly positive values indicate events such as recent population bottleneck, population subdivision or presence of some recent immigrants in a population. Values near zero and not significant, indicate that population size is constant.The historical population dynamics and structure was inferred from mismatch distribution of Arlequin , which cribution . In addition [Fs  and Tajin [Fs [D  statistiR. appendiculatus from South Africa, Kenya, Grande Comore, Zambia, Zimbabwe, Uganda and Rwanda were retrieved from the National Center for Biotechnology Information (NCBI) database  and Rhipicephalus turanicus obtained from the GenBank  were used as outgroup taxa. A Median-Joining (MJ) network was constructed to investigate the phylogenetic and ancestral relationship among haplotypes using PopArt Software [Different published haplotype sequences of EGA v7.0 . The nucSoftware .cox1 and 12S rRNA gene loci were successfully generated from 219 and 126 individual ticks, respectively, originating from the three AEZs of DRC, the two AEZs of Burundi, one AEZ of Rwanda and specimens from Tanzania. The 10 sequences from Tanzania and the sequences previously described in Rwanda were not included in the population genetic and structure analyses. Generated nucleotide sequences were aligned with the reference haplotype sequences retrieved from the GenBank  with known sequences of R. appendiculatus found in GenBank  obtained for each of the six AEZs were deposited and are available in GenBank .PCR fragments of the mitochondrial cox1 had 27 polymorphic sites, 21 of which were parsimony informative and 6 were singletons, yielding 22 haplotypes . The highest number of cox1 haplotypes was found in DRC AEZ1, while the lowest was observed in Burundi AEZ3 , CH2 (28%) and CH5 (19%) were shared between all AEZs and were by far the most ubiquitous in the region, accounting for 74% (154 sequences) of the overall dataset  were the most abundant, representing 90% of the 126 sequences analysed. Haplotypes 12SH4 and 12SH5 had together 8 (6%) out of the 126 analysed sequences. The presence of single haplotypes indicates high frequency of rare alleles, which suggests a recent population expansion.The distribution of haplotypes presented in Table cox1 nucleotide sequences and are shown in Table Hd) and nucleotide diversity (π) were 0.81 and 0.006, respectively. The haplotype diversity ranged from 0.72 in Burundi AEZ1 to 0.85 in Rwanda AEZ2 and the nucleotide diversity (π) values ranged from 0.002 in Burundi AEZ3 to 0.011 in Rwanda AEZ2. The average number of nucleotide pairwise differences (k) was 3.4 for the overall dataset, with the highest value observed in Rwanda AEZ2 (6.3). Altogether, these population genetic indices showed that the diversity of R. appendiculatus is quite different among AEZs. Ticks from Rwanda AEZ2 were more highly diverse than those from three AEZs of DRC and the two AEZs of Burundi. We also observed an excess of singleton mutations in Burundi AEZ1 (15 out of 18 polymorphic sites), suggesting a sudden population expansion. These data analysed separately by haplogroups  , the pairwise genetic distance (FST), and the number of migrants (Nm) showed evidence of differentiation between some R. appendiculatus populations. The population pairwise genetic distance (FST) varied from a negative and not significant value  with infinite value of Nm (between DRC AEZ2 and AEZ3) to the strongest differentiation  with low number of migrants (Nm = 2.1) between Burundi AEZ3 and Rwanda AEZ2. Pairwise FST values were found to be low and not significant between DRC AEZ3 and Burundi AEZ3 with infinite Nm and between DRC AEZ2 and Burundi AEZ3 associated to a high number of migrants , indicating an excess of gene flow between these zones. DRC AEZ1 did not differ significantly with Burundi AEZ1  and Rwanda AEZ2 . Tick populations from Rwanda AEZ2 showed a strong genetic differentiation with those from DRC AEZ3  and DRC AEZ2 , indicating reduced or lack of gene flow between these populations. These results were confirmed by inter-population nucleotide differences (KXY), which was significant when populations were significantly differentiated by the pairwise FST statistic. Tick populations were compared by analysing haplogroup A sequences alone. The findings showed that ticks from Rwanda AEZ2 and the two AEZs of Burundi were not genetically different. They shared more migrants belonging to haplogroup A  based on Zs Table . Both diD and Fu’s Fs were negative but not significant (Table SSD) and raggedness index (RI) for both demographic and range expansion did not deviate significantly from that expected under expansion model. The negative values of neutrality tests and the non-significance of SSD and RI indices, suggest a sudden expansion of R. appendiculatus populations in the Great Lakes region. The population dynamics history was also analysed separately for each of the six AEZs  and Fu’s Fs  statistics. A good fit of sudden population expansion was also observed in this haplogroup, based on sum of squared deviation values that were not significant in all the cases: demographic  and range  expansion, with no significant variation of the raggedness index for both models , implying that haplogroup B did not experience any historical population expansion. This group is characterised either by a constant population size (demographic equilibrium) or had experienced a weak signal of population bottleneck that reduced its diversity. When analysing the demographic dynamics for samples belonging to haplogroup A in each AEZ  and Fu’s Fs  statistics showed significant negative values and in Rwanda AEZ2 where Fu’s Fs was negative (Fs = -2.1) and significant (P = 0.041). According to the mismatch distribution and negative values for neutrality tests, the hypothesis of population growth and spatial expansion models could not be rejected in the six AEZs, which was consistent with a model of sudden expansion for each population subdivision.The population dynamics were then inferred for each haplogroup separately Table . A unimoR. appendiculatus in Africa, the haplotype sequences found in this study along with those retrieved from GenBank  well-supported by a ML bootstrap value of 100%  supported by 97% bootstrap value  was clustered in haplogroup A, showing that the haplogroup A is also present in Uganda. Unfortunately, we did not find its corresponding cox1 sequence.Similar findings were confirmed by R. appendiculatus, the main vector of T. parva in sub-Saharan Africa. We expected evidence of R. appendiculatus population expansion, gene flow and different colonization patterns of tick lineages, facilitated by the reported cattle mobility in the Great Lakes region.This study analysed the intraspecific variation of mitochondrial DNA to better understand how factors such as agro-ecological zones and anthropogenic movements of cattle may affect population genetic structure and population expansion history of the tick cox1 gene locus were clustered into two well-defined major groups, named haplogroup A (the most frequent) and haplogroup B. Similar grouping were obtained with 12S rRNA analyses. The two haplogroups identified in the present study have been previously described as “east African” and “southern African” genetic groups [R. appendiculatus in Africa [The 22 haplotypes identified by DNA polymorphic analysis of c groups , correspn Africa –37, 51. n Africa .The highest genetic variability was observed in lowlands, whereas a relatively lower diversity was observed in midlands and highlands. The high genetic diversity in lowlands can be explained by the strong presence of the two lineages A and B observed in these AEZs. The coexistence of these lineages could originate from the dispersal of the tick through livestock movement between AEZs , associacox1 gene variation in R. appendiculatus revealed low to moderate genetic differentiation values and high gene flow rates among AEZs. The two identified R. appendiculatus lineages were sympatric in the Great Lakes region, although lineage A was the most abundant and widely distributed in all AEZs and lineage B was particular confined to lowlands, where the climate is tropical dry, more arid with lower annual rainfall and longer dry season than in highlands . These climate conditions in lowlands are quite similar to the described ecological zones of lineage B in southern Africa [R. appendiculatus lineages is not only driven by geographical separation as described in previous studies [Population genetic analyses of n Africa , 52. In  studies , which m studies , 18. AnaR. appendiculatus that took place in the Great Lakes region. A strong evidence of recent spatial and demographic expansion was observed for lineage A in all AEZs included in the study. Analyses of cox1 sequences revealed relatively high haplotype diversity contrasted with low nucleotide diversity values for each population, suggesting a sudden population expansion [D and Fu’s Fs, the star-like radiation, the unimodal mismatch pattern and non-significant RI and SSD statistics, further support the recent evolutionary history and sudden population growth experienced by lineage A [R. appendiculatus lineages after recent colonization events or exchanging migrants [R. appendiculatus cox1 sequences available in Africa, the star radiation of the MJ network in each group suggests that the two lineages went through a demographic expansion and evolve independently of each other with limited gene exchange. Unfortunately, we were not able to test the hypothesis of crossbreeding events between the two lineages described here, because of the maternal inheritance of mitochondrial genes used in the present study. More studies, such as extensive biological characterisation, crossbreeding experiments and the use of biparental inheritance markers are necessary to investigate the panmixia of the two lineages and the genetic mechanisms driving their establishment and corresponding phenotypic variations in changed environments.The demographic and spatial dynamics were analysed using multiple algorithms, to elucidate colonization events of the tick xpansion , 55. Thiineage A –58. We dineage A , 59, 60.ineage A , 61. Howmigrants , 56, 62.R. appendiculatus has undergone spatial expansion was in accordance with the expectation that long and short distance movement of cattle are key factors of spreading ticks. The processes responsible for that evolutionary pattern may have resulted, not only from range expanding of the previously established haplotypes to proximate AEZs, but also from the recolonization events of ticks from other regions and countries [The fact that ountries , 63. In ountries –66.R. appendiculatus that have a wide distribution range in Africa, with large divergence in behavioural diapause [Phylogenetic trees produced two main genetic subpopulations of diapause , 37, spadiapause , 51, ecodiapause –34. Initdiapause . To datediapause . This codiapause . In Grandiapause . In areadiapause . The symdiapause , where adiapause , where adiapause , 37. We diapause .R. appendiculatus in the Great Lakes region and over its distribution range in sub-Saharan Africa. Our results highlighted the occurrence of two major genetic lineages (A and B) in the Great Lakes region. The two lineages are not spatially structured in the study region and they differ in their colonization histories and pattern. Lineage B, not previously reported, was probably introduced recently in the region and its occurrence decreases with increased altitude, whereas lineage A, widely distributed, has been longer established and subjected to sudden demographic and spatial expansion most likely related to short and long-distance cattle movement. Rhipicephalus appendiculatus ticks are more diverse in lowlands than highlands with moderate genetic differentiation between the two ecosystems, while more genetic similitude is found in zones with same agro-ecological profiles, in spite of their geographical distance. The genetic distribution of R. appendiculatus suggests two different eco-genetic zones in Africa, the sympatric zone  where the two lineages coexist and the allopatric zones (southern Africa) where they have clear geographical divergence. The range expansion pattern of lineages and the genetic admixture of R. appendiculatus populations observed in the Great Lakes region can strongly affect the epidemiological dynamics of ECF. This could partially explain the endemic instability and occasional epidemics due to the introduction and temporal subsistence of infected ticks mostly in fringes areas of lowlands.This study provided new insights into the genetic structure and colonization events of Additional file 1:Table S1.Rhipicephalus appendiculatus cox1 and 12S rRNA haplotype sequences retrieved from GenBank. (DOCX 16 kb)Additional file 2:Table S2.cox1 and 12S rRNA BLAST results for species identification and confirmation. (DOCX 16 kb)Additional file 3:Table S3. Polymorphism in the 22 haplotypes of the cox1 gene fragment of R. appendiculatus. (DOCX 21 kb)Additional file 4:Table S4. Population genetic structure inferred by analysis of molecular variance (AMOVA) based on cox1 sequences of R. appendiculatus from different agro-ecological zones. (DOCX 13 kb)Additional file 5:Table S5. Evolutionary neutrality, demographic and spatial history of mitochondrial cox1 gene. (DOCX 15 kb)Additional file 6:Figure S1.cox1 mismatch distribution pattern for R. appendiculatus haplogroup A in different agro-ecological zones. (DOCX 193 kb)Additional file 7:Table S6. Rhipicephalus appendiculatus 12S rRNA haplotypes and their distribution among agro-ecological zones of the Great lakes region and other sub-Saharan African countries. (DOCX 15 kb)Additional file 8:Figure S2. Neighbor-joining tree of 12S haplotype sequences for R. appendiculatus across African countries. (DOCX 18 kb)