The current inhabitants of the Canary Islands have a unique genetic makeup in the European diversity landscape due to the existence of African footprints from recent admixture events, especially of North African components (> 20%). The underrepresentation of non-Europeans in genetic studies and the sizable North African ancestry, which is nearly absent from all existing catalogs of worldwide genetic diversity, justify the need to develop CIRdb, a population-specific reference catalog of natural genetic variation in the Canary Islanders. Based on array genotyping of the selected unrelated donors and comparisons against available datasets from European, sub-Saharan, and North African populations, we illustrate the intermediate genetic differentiation of Canary Islanders between Europeans and North Africans and the existence of within-population differences that are likely driven by genetic isolation. Here we describe the overall design and the methods that are being implemented to further develop CIRdb. This resource will help to strengthen the implementation of Precision Medicine in this population by contributing to increase the diversity in genetic studies. Among others, this will translate into improved ability to fine map disease genes and simplify the identification of causal variants and estimate the prevalence of unattended Mendelian diseases. This and subsequent historic events, including the European colonization of diverse origins and the slave trade from western sub-Saharan African populations4, have shaped the genetic makeup of Canary Islanders, as has been established by the historical burial remains and the diverse ancient DNA studies7. Early genetic studies have supported that the current Canary Islanders could be modeled as descendants of a recent three-way admixture event. Note, however, that these studies just considered the major continental populations and did not assess the substructure components in the parental populations. Sexual asymmetry in the admixture event has been invoked to explain the observed unbalanced proportions of indigenous parental lineages from the non-recombining portion of the Y chromosome (NRY) and the mitochondrial DNA (mtDNA) in current inhabitants8. This has been explained by a steady increase of European male lineages soon after the conquest, whereas the indigenous founder mtDNA lineages have remained at roughly constant frequencies until the present days10. Overall, while there is a large interindividual variability in the ancestry proportions in the current inhabitants, they have been estimated to an average of 75–83% European (EUR), 17–23% North African (NAF), and 3% or less sub-Saharan Africa (SSA)12. The most recent analyses based on genome-wide single nucleotide polymorphism (SNP) array data evidenced that these numbers can be as high as up to 29.9% NAF and 9.2% SSA ancestries in some individuals13. Most importantly, they have also evidenced broad genomic regions of Canary Islanders that tend to concentrate African alleles and that are enriched in genes involved in diverse complex diseases, which is highly suggestive of characteristic footprints of local adaptations.The Canary Islands are a Spanish archipelago of seven main islands located in the Atlantic Ocean, a hundred kilometers off the Northwest African coast, with Cape Juby (Morocco) being the closest mainland point. Before the XV century, when the archipelago was fully incorporated into the European world, it was inhabited by aborigines14. Nevertheless, the genetic knowledge of human traits and diseases remain to be almost entirely based on results from studies in European populations16. This results in an underrepresentation of ethnic diversity and a conspicuous lack of accuracy in the understanding of the genetic architecture and the biology of human traits, thus challenging the translation of this knowledge into generalizable clinical applications19. While there are differences in allele frequencies across populations20, the rarer the variant, the more likely for it to be more locally circumscribed to populations21. The estimations indicate that while the proportion of rare variants  shared among populations from the same continent is 70–80%, the proportion of shared rare variants drops down to 10–30% among populations from different continents, and are, therefore, poorly represented in the reference catalogs of genetic variation23. Most importantly, deleteriousness is known to accumulate on the lower end of the allele frequency spectrum24. The application of NGS, both through whole-exome sequencing (WES) and whole-genome sequencing (WGS), has drastically increased the diagnostic yield in patients of European ancestry, such as for autosomal dominant retinitis pigmentosa25, severe intellectual disability26, and Mendelian conditions in a broad sense28. Because of that, the substantial benefits of incorporating participants from diverse ancestries and recently admixed populations to improve the discovery of disease genes have been evidenced15. This highlights the urgent need for building local population reference catalogs of genetic diversity to efficiently facilitate the identification of disease genes29. Developing these population catalogs of genetic variation is such of importance that multiple countries have made huge efforts to develop their own based on the study of a representative control strata of the populations while preserving genetic diversity specificities, many of which have been recently integrated in the Genome Aggregation Database (gnomAD)30. Iran31, Japan32, Korea33, Finland34, Spain35, the United Kingdom36, or the Netherlands37 are some of the countries which have seen the necessity to develop their own catalogs of genetic variation. The availability of population-specific catalogs of variation allows to identify genetic peculiarities of the population38 as is key for identifying disease-causing variants in both rare diseases and complex human traits36. This has been recently exemplified by the striking detection of recessive deficiencies in two genes of the type I interferon pathway, critically involved in life-threatening viral diseases including COVID-19, at relatively high frequency (> 1%) in Polynesia and Inuits, while these deficient are extremely rare or absent from other regions of the world40. For the particular case of the Canary Islands, one of the early examples of its benefit has been recently demonstrated to support the underdiagnosis of Wilson disease, a rare difficult-to-diagnose disease41. The benefits have been also shown for complex traits, which is more evident for the case of isolated populations, as the cases of the Northern Greek populations of the Pomak villages and the Mylopotamos villages in Crete43, or the population of Cilento from Southern Italy44, highlighting for example the increase in allele frequency of variants involved in haematological traits, among others. Besides these applications, there are substantial gains of incorporating information from the population of interest to reference panels during variant imputation, as it improves the power to identify disease variants and enables fine-mapping in genome-wide association studies of complex traits45. Thus, developing a population-specific catalog of genetic variation is an essential step to optimally develop generalizable clinical applications.The success of Next Generation DNA Sequencing (NGS) represents a milestone in how genetic variation is discovered and analyzed nowadays. It has opened new horizons to improve disease diagnosis, prognosis, and treatment, and constitutes a central element of the Precision Medicine paradigm13. Despite the increase in awareness of the necessity of including more diversity in the genetic studies47, the currently available catalogs of genetic variation have a strong bias towards the representation of northern, western, and central European populations. In particular, it has been shown that the African genomic ancestry has important biomedical implications for European populations12 and it has been associated with risk in cardiovascular, renal, and respiratory diseases, as well as in diabetes, among others51. Strikingly, for some of them, the estimates of prevalence and/or their complications are higher in the Canary Islands than in other mainland regions of Spain. This is the case of asthma and allergic diseases in children53, and of diabetes, obesity, and hypertension in all age groups53. Besides, not only the morbidity but also the mortality due to diabetes is increased, being three-fold higher among Canary Islands compared to the rest of the Spanish populations54. Despite the interest considering that the Canary Islanders exhibit the largest proportion of NAF ancestry known to date in the European diversity landscape13, there is a lack of data from North African populations on the public catalogs representing human genetic diversity55, not even being covered by the African Genome Variation Project46.The historical conquest and admixture events, jointly with the isolation and inbreeding, as well as the likely local adaptation processes, have shaped the current genetic background of the Canary Islands population, constituting the population with the largest proportion of North African ancestry among Southwestern Europeans56.Here we aimed to establish the foundations to develop a reference genetic catalog of the Canary Islands population (termed CIRdb). Providing an unbiased catalog of natural genetic variation of this population, preserving unique genetic African ancestry footprints, is a first necessary resource for optimal development of Precision Medicine in this populationThe study was approved by the Research Ethics Committee of the Hospital Universitario Nuestra Señora de Candelaria and performed according to The Code of Ethics of the World Medical Association (Declaration of Helsinki).57, which constitutes the most extensive general population cohort for epidemiological studies of the Canary Islands archipelago. Briefly, this cohort involves health survey data and samples from nearly 7000 randomly selected donors providing informed consent through personal interviews, aged between 18 and 75 years from the seven main islands and without gender bias. Despite it is well-known to properly represent the Islands’ population58, the CDC cohort lacks deep genetic assessment despite the recognized necessity53. A subset of 416 individuals from the cohort was previously assessed to characterize inbreeding, selection, and the mosaic nature of the Canarian genomes13. We nested the current study in that cohort, particularly focusing on a subset of 1024 donors , fulfilling that they self-reported absence of cardiovascular, metabolic, immunologic, or cancer diseases, and that the four grandparents were born on the same island. The latter criterion was relaxed to accommodate donors from Fuerteventura, where the selection imposed self-reporting three grandparents born on the island. The samples were pseudonymized for the purposes of this study.The samples were obtained from the cohort study ‘CDC of the Canary Islands’59 was used to process the image files and to run the first genotyping quality controls (QCs) based on a Dish-QC  with values higher than 0.82, and samples with call rate (CR) above 0.93. Additionally, after running AffyPipe, more SNP QCs were implemented to select accurate variants by means of SNPolisher package in R 3.2.2 environment60 and according to next parameters which were extracted from ‘ps.performance.txt’ file: Fisher’s Linear Discriminant (FLD) > 4.375, Heterozygous Strength Offset (HetSO) ≥  − 0.5, SNP CR ≥ 95, and variants with assigned rsID. Next, the R environment and PLINK v1.0761 were used for additional standard QC steps, including the identification of variants in non-autosomal chromosomes, and variants with large deviations from Hardy–Weinberg equilibrium (p < 1.0 × 10−6), large missingness rate (CR < 0.95), or MAF < 0.01, and the identification of samples with gender discordances , outlier heterozygosity rate, and family relationships with other study donors (PIHAT > 0.2). For the purpose of this particular study, we only considered the donors declaring four grandparents born on the same island (three grandparents in the context of Fuerteventura). After variant and sample QCs, the dataset was ready for ulterior population analysis.DNA was extracted from peripheral blood using the Blood genomicPrep Mini Spin Kit  following the manufacturer’s recommendations. We relied on the Axiom® Genome-Wide Human CEU 1 Array  to obtain genotypes from 587,352 variants with the support of the National Genotyping Center (CeGen), Universidad de Santiago de Compostela Node. The AffyPipe v2.10.0 open-source pipelineThe genetic background of the Canary Islanders was evaluated under two different scenarios: one focusing only the Canary Islanders, and another comparing the Canary Islanders against reference populations. Each scenario involved a different number of samples and variants (based on the use of different filters) Table .Table 1S62 for EUR and SSA populations. Europeans included data from Finnish in Finland (FIN) (N = 99), British in England and Scotland (GBR) (N = 91), and Utah Residents with Northern and Western European ancestry (CEU) (N = 99). Note, however, that for specific analysis , we also included other European populations from the south of the continent . Given that using alternative African populations from 1KGP or smaller subsets of individuals from the parental populations provide equivalent admixture results in Canary Islanders13, we used only the Yoruba population in Ibadan (Nigeria) (YRI) (N = 108) as representatives of the SSA populations. NAF populations were represented by the 125-individual dataset that is publicly available and genotyped using Genome-Wide Human SNP Array 6.0 (Affymetrix) for 732,532 variants63. The intersection of the reference datasets (N = 522) with those of Canary Islanders (N = 863) was implemented using ‘–bmerge’ command on PLINK v1.964 to merge into one file including only the variants that were shared among populations. This process left us with data from 1385 individuals and 114,929 variants as the final filtered dataset for the downstream analyses involving both Canary Islanders and the reference population datasets.To place the genetic variation of Canary Islanders in context, we accessed reference data from The 1000 Genomes Project (1KGP) Phase 3N = 1385) was computed with PLINK based on a dataset of 101,271 variants, which excluded variants in high linkage disequilibrium (LD) and those that were located in regions of long-range LD as performed elsewhere13. For the comparisons within the Canary Islands populations, a pairwise r2 threshold of 0.15 was used to maintain 116,959 variants for the analyses in the 863 individuals collected from the archipelago.Principal Component Analysis (PCA) among Canary Islanders and reference population datasets  a global ancestry estimation from local ancestry inference for admixed individuals by means of ELAI v1.0166. We have shown that, compared to other local ancestry estimators, ELAI offers the least biased estimates for this population67. Note that ancestry estimations inferred for the reference populations  should be considered with caution due to the existence of genetic drift effects that have not been properly modelled13. Nevertheless, this does not affect the ancestry inferences obtained for the Canary Islanders.Two approaches were conducted to assess the genetic ancestry partitions of the subjects under study: 1) a direct global ancestry estimation using ADMIXTURE v1.3.013, we further pruned the Canary Islands dataset to be considered for this particular analysis. For that, we calculated the runs of homozygosity (ROHs) with PLINK following a sliding window approach68. We allowed that a minimum window density of 50 kb/SNP was asserted, as well as one heterozygous variant and up to five missing calls per window. For tracts with a minimum length of 500 kb, 50 was the minimum number of homozygous SNPs to consider a tract as a ROH, and 100 kb was the maximum gap allowed between two consecutive SNPs to include them in the same ROH. The hit rate of all scanning windows containing a variant must be at least 0.05 to comprise a certain ROH. Finally, the samples with ROH lengths above the 80th percentile (1.08 Mb) were excluded from the analysis. This left us with 690 Canary Islanders for this particular analysis, providing a final dataset of 1212 samples  and the 101,271 pruned variants which have been previously used for the PCA. Additionally, some European populations from the south of the continent (TSI and IBS from 1KGP) were included into the ADMIXTURE analysis as a sanity check.ADMIXTURE implements a maximum likelihood estimation to calculate the individual ancestries averaged across the genome. For this approach, 2 to 7 ancestral populations (K) and 10-times cross-validation were tested to estimate the best fitting K. In order to avoid spurious clusters in the ADMIXTURE results due to the existence of inbreeding, which we have evidenced in the populations from smaller islands13. Moreover, 14 generations since the last admixture event was assumed based on our previous findings13. We excluded SNPs with MAF < 0.01 or with missing position information in any of the reference datasets. Subsequently, the global ancestry estimation was calculated considering the average of each ancestry per individual per chromosome and summarizing all the information into a unique value per individual per ancestry. Therefore, global inferences based on ELAI algorithm were implemented using 1212 individuals  and 114,929 variants (given that independence of SNPs is not a requirement for this approach).For local ancestry estimation, ELAI uses a two-layer hidden Markov model to assess the local ancestry in the individuals. The same subset of 690 Canary Islanders was evaluated to match the results from both ancestry inferences approaches. Based on our previous observations, we assumed a three-way admixture model of EUR, NAF, and SSA to calculate the structure of local haplotypes given that both approaches  provided similar estimatesSamples from a total of 1024 donors were selected and utilized for SNP array genotyping. After QC filters based on the obtained genotypes  while others situated closer to EUR .In the PCA, including Canary Islanders and the reference populations , the first two principal components (PCs) encompassed 67.1% of the variation and revealed a distinctive separation in four main clusters , followed by NAF (20.8%), and SSA (2.8%) (Table ADMIXTURE ancestries for the dataset indicated that the best fitting model was obtained for %) Table  online. When island populations were considered individually, the largest average NAF ancestries were obtained for El Hierro, La Gomera, Fuerteventura, and Lanzarote for both admixture estimators. La Gomera was also the island population with the largest SSA proportion on average Table .Table 3M70. Laboratory intercomparisons and updates are deposited in a publicly available repository (https://github.com/genomicsITER/benchmarking).Considering SNP array data analyses as the starting point, the design for the reference genetic catalog of the Canary Islands population (CIRdb) is presented here for the first time. This catalog will be based on all the unrelated individuals identified in this study (irrespective of whether they declared that the four grandparents were born in the same island) and has been envisaged as a combination of data from three different technologies where each one provides its advantages for the genetic characterization of Canary Islanders. The conceptual design of CIRdb is shown in Fig. 13, we identify genetic peculiarities that differentiate the current Canary Islands populations from mainland populations12. Besides, with a larger sample size, we now evidence a clear pattern of genetic differentiation among islands not observed previously, where donors from El Hierro, La Gomera, Fuerteventura, and Lanzarote exhibited the largest average ancestry that can be assigned to NAF. We also evidenced the existence of more extreme individual NAF ancestries in the population  compared to previous estimates. An important isolation pattern of the populations from El Hierro and La Gomera, and the existence of further substructuring in the Canaries was also evident in this study. Taken together, this study evidenced the unique admixed makeup of current Canary Islanders and thus, establish the grounds for developing a catalog of genetic variation for this population that will be useful for the transition to Precision Medicine in the region.This study provides the largest genomic study of current Canary Islanders conducted to date, revealing unique population features and particular ancestry patterns based on SNP array data. In line with our previous studies with fewer samples71 and the precursors of Precision Medicine, through one of the first examples of prevention, detection, and treatment of diseases tailored to individual profiles based on pharmacokinetics 72, nowadays this paradigm encompasses diverse areas such as epigenetics, environmental exposures, imaging and radiology, and genetics and genomics, among others74. In this context, Genomic Medicine has emerged as a key discipline that has demonstrated important benefits in oncology75, pharmacology76, and rare and undiagnosed diseases77, to name a few, and including the possibility to improve the turnaround time, and in reducing the costs and the uncertainty of the diagnostic odyssey of the patients and their relatives79. In this context, many countries have seen the benefits of the pioneering implementation of genomic medicine within their healthcare system82. The first successful use of whole-exome sequencing to identify a disease-causing genetic mutation was reported about ten years ago, by Worthey in 201183. A 15-month-old child was diagnosed with presumptive Crohn’s disease and treated accordingly without improvements in symptoms. After several years of diagnostic odyssey, a WES analysis identified a novel, hemizygous missense mutation in the X-linked inhibitor of apoptosis. This landmark study was followed by others based on the same concept and techniques but considering more patients and controls, sometimes without a clear clinical diagnosis in place before the analysis88. For whole-genome sequencing, several fruitful studies have also been carried out91. Nowadays, the routine implementation of NGS in clinical settings has drastically improved the average diagnostic yield from 10 to 36% (WES) or 41% (WGS), and the rate of clinical utility from 6 to 17% (WES) or 27% (WGS). Based on these benefits, many countries have extended these studies to comprise global, population-scale analyses including population controls, so that the natural genetic variation of the population could be also deeply characterized. In some cases, population classification is not entirely accurate and a more fine-scale analysis, based on ancestry, is needed92.There have been significant advances in Precision Medicine. From Archibald Garrod93. Using WES at population scale, it has been possible to detect an enrichment of risk variants for Panic Disorder in the Faroese population94, specific genetic loci associated with longevity in Bulgarian centenarians95, or study the metabolic impact of candidate effector genes in Southwestern American Indian population96, to name a few. WGS theoretically targets the entire DNA sequence of donors, offering the optimal solution for unbiased genetic studies although at higher costs per sample. Because of that, the use of WGS is projected in CIRdb as a complementary approach that will be used in subsets of the samples to improve the catalog and allowing to improve the imputation of genetic variation97 in the biomedical studies conducted in the Canary Islanders, as has been evidenced in Estonian and Native Hawaiian populations38. CIRdb aims to leverage two technologies for WGS, namely short-read sequencing (SRS)  and long-read sequencing (LRS) . The former will allow us to enrich the catalog with genetic information beyond the exome regions with high accuracy while containing the project costs. The latter will specifically enable the analysis of other types of genetic variation 99, particularly beneficial for medically-relevant genes100 and assess the benefits of de novo assembly of genomes to assist in improving the population102. Studies in patients with Bardet-Biedl syndrome103 or Carney complex104 have shown the benefits of using LRS which would still be unsolved otherwise using SRS technologies.Following on this idea, here we present the study sample for the establishment of a reference genetic catalog for the current Canary Islanders. As the greatest fraction of rare genetic variation, which accumulates the most clinically relevant genetic variation, would remain understudied unless NGS technologies are in place, with CIRdb we envisage the use of a combination of several technologies to efficiently develop the population-specific catalog. As a starting point, we have assessed all samples to be included with the Axiom® Genome-Wide Human CEU 1 array as a first stage to efficiently characterize the global and local ancestry components, local substructure and inbreeding patterns, but also for the detection of samples that could be difficult to sequence or that had unknown family relationships with others in the cohort, allowing us to prioritize the samples for more expensive ulterior approaches. Considering the next steps, CIRdb plans to run WES in all the prioritized samples to efficiently examine the fraction of the genome that includes ~ 85% of all described disease-causing variants105 in the ancestry analyses. This is the main reason for us to focus on the three continental ancestry components following our previous observations13. Forthcoming studies incorporating a much higher number of variants and the analysis of maternal (mtDNA) or paternal (NRY) lineages will be optimal to assess the subcontinental components of the admixture. Secondly, although relying on SNP arrays benefits from standardized pipelines and highly reproducible and reliable genotyping data, one of the most pronounced drawbacks of the study is the focus on one type of genetic variation  and on alleles in the higher end of frequency spectrum. Information from structural and rare variation will provide new clues for disentangling the recent evolutionary history of this population and identify novel genetic links with disease. Filling these gaps will be the aim of leveraging different sequencing technologies for the establishment of the CIRdb catalog.Despite the forthcoming studies to build CIRdb will deepen in the genetic characterization of this population, we recognize some major issues of the study. Firstly, the number of evaluated SNPs  and a focus on autosomal variation limited our ability to assess the existent subcontinental influencesIn summary, here we deepen into the genetic characterization of current Canary Islanders and establish the grounds for developing CIRdb to put forward a catalog of genetic variation for this population. CIRdb will be developed with complementary technologies and the tools and resources are currently under active development to create a precise public and available database for researchers and healthcare professionals.Supplementary Information.


Rhynchocypris lagowskii) widely distributed in the cold freshwaters of the Qinling Mountains was examined. A total of 464 specimens from 48 localities were sequenced at a 540‐bp region of the mitochondrial cytochrome b (Cytb) gene, and 69 haplotypes were obtained. The mean ratio of the number of synonymous and nonsynonymous substitutions per site (dN/dS) was 0.028 and indicated purifying selection. Haplotype diversity (h) and nucleotide diversity (π) of natural populations of R. lagowskii varied widely between distinct localities. Phylogenetic trees based on Bayesian inference (BI), maximum likelihood (ML), and maximum parsimony (MP) methods, and network analysis showed five well‐differentiated lineages, but these did not completely correspond to localities and geographic distribution. Meanwhile, analysis of molecular variances (AMOVA) indicated the highest proportion of genetic variation was attributed to the differentiation between populations rather than by our defined lineages. In addition, there was no significant correlation between the pairwise Fst values and geographic distance (p > .05). Based on the molecular clock calibration, the time to the most recent common ancestor (TMRCA) was estimated to have emerged from the Late Miocene to the Early Pleistocene. Finally, the results of demographic history based on the neutrality test, mismatch distribution, and Bayesian skyline plot (BSP) analyses showed that collectively, the populations were stable during the Pleistocene while one lineage (lineage E) probably underwent a slight contraction during the Middle Pleistocene and a rapid expansion from the Middle to the Late Pleistocene. Therefore, the study suggests the current phylogeographical pattern of R. lagowskii was likely shaped by geological events that led to vicariance followed by dispersal and secondary contact, river capture, and climatic oscillation during the Late Miocene to the Early Pleistocene in the Qinling Mountains.In this study, the phylogeographical pattern of the Amur minnow ( The study suggests that the current phylogeographical pattern of R. lagowskii was likely shaped by geological events that led to the past vicariance followed by the dispersal and secondary contact, river capture, and climatic oscillation during the Late Miocene to the Early Pleistocene in the Qinling Mountains. It can The Qinling Mountains represent a natural boundary between the northern and southern regions of the country and separate the Chinese temperate and subtropical climatic zones   gene sequences of 464 specimens from 48 geographical localities in the main Qinling Mountains. In addition, the study also assessed genetic differentiation between populations, demographic history, and the effects of geological events or climate oscillation during the Pleistocene.The Amur minnow  Figure  is a sma) Figure . R. lago22.1https://www.iucnredlist.org). None of the species sampled are endangered or protected in China . The forward primer Cytb‐F (5’‐ATGGCAAGCCTACGAAAAAC‐3’) and the reverse primer Cytb‐R (5’‐GATTACAAGACCGATGCTTT‐3’) designed based on the same species  gene by polymerase chain reaction (PCR) for each specimen. PCR amplification was performed in a total volume of 25 µL, containing 3 mM MgCl2, 10 mM Tris‐HCl (pH 8.3), 50 mM KCl, 0.25 mM of each dNTP, 1.25 U rTaq polymerase , 0.4 μM of each primer, 45 ng gDNA, tapped with Milli‐Q water. The following cycling conditions were applied: initial denaturation for 1 min at 93°C followed by 35 cycles of denaturation for 10 s at 92°C, annealing for 1.5 min at 51°C, and extension for 2 min at 60°C with a final extension for 6 min at 72°C , haplotype diversity (h), and nucleotide diversity (π) were calculated using DnaSP v5.10.1 , maximum likelihood (ML), and maximum parsimony (MP) methods. The congeneric species R. percnurus was selected as an outgroup  in jModelTest v2.2.10 .The mean genetic distances among the lineages identified in our phylogenetics analysis (see results) were calculated by an uncorrected p‐distance model using MEGA v6.06  for all parameters larger than 200 were checked with Tracer v1.7.1  and nucleotide diversity (π) across the samples were obtained  samples, respectively, while the lowest values of h and π were obtained in four localities samples . In addition, the most common haplotype (Hap10) was distributed in ten localities and were accounted for in 18.5% of the individuals (86 of 464), including 75 samples in the Han River, a sample in the Wei River, and ten samples in the Jialing River, respectively. Interestingly, the relationship between the genetic diversity and the population latitude and longitude was uncorrelated.The haplotype diversity   and divergence times of the five lineages. TMRCA of the whole ingroup dated to 7.03 Mya. The divergence times among lineages diverged from 5.63 Mya to 2.38 Mya  followed by a dispersal and secondary contact. The mean genetic distance among haplotypes of R. lagowskii ranged from 3.5% to 13.9% . This was higher than that found in amphibians S. ningshanensis (2.4% to 4.2%) and B. tibetanus (0.0% to 3.7%) but similar to values found in other fish and amphibian species, including R. oxycephalus (6.5% to 7.4%) and Odorrana schmackeri (3.4% to 21.1%) in the Qinling Mountains  followed by dispersal and secondary contact.Furthermore, there was no significant positive correlation between the pairwise Fst values and geographic distance (km) of R. lagowskii, we found that as R. lagowskii is primarily found in clear cold freshwater from the midstream to upstream in East Asia . The dN/dS value from coding protein genes has been used to detect patterns of selection in molecular evolution  against nonsynonymous substitutions often observed with 13 mitochondrial oxidative phosphorylation (OXPHOS) genes among other cyprinid species ; Formal analysis (lead); Investigation ; Methodology ; Software (lead); Writing – original draft (lead); Writing – review & editing (lead). Li Jiao: Investigation ; Methodology . Lili Ni: Investigation ; Methodology .The authors declare that they have no competing interests.Table S1Click here for additional data file.


Lycoris aurea complex throughout its range and attempted to explore the association between aneuploidy and species diversification. The karyotypes of this complex presented aneuploidy variations mainly divided into four cytotypes: I (2n = 10m + 2T), II (2n = 8m + 6T), III (2n = 7m + 8T), and IV (2n = 6m + 10T). Cytotype distributions were highly structured geographically. Two main cytotypes, II and IV, are geographically allopatric. The populations with cytotype II are mainly distributed in central China and the southern islands of Japan. Cytotypes IV is disjunctly distributed in southwestern and southeastern China. The cytotypes with fewer chromosome numbers tend to occur at high latitudes. For analyzing the phylogeographic pattern and genetic structure of this complex, we sequenced four chloroplast DNA fragments  of 241 individuals from 42 populations. Extremely high diversity of cpDNA haplotypes was found, with genetic diversity index (Hd) being 0.932 and 98.61% of the genetic variation occurring among populations, indicating that this complex has undergone strong intraspecific differentiation. The cytotype II had the highest haplotype diversity (Hd = 0.885), while cytotype IV harbored the highest nucleotide diversity (π = 4.09 × 10–3). We detected significant leaf morphological differences not only between cytotype II and IV but also between west lineage and east lineage within cytotype IV. These results illustrated that aneuploidy contributed to extensive morphological and genetic differentiation in L. aurea complex. It was suggested that L. aurea complex should comprise multiple independent evolutionary lineages, and accurate species delimitation needs to be established further in an integrative taxonomic approach.Polyploidy has received considerable interest in the past, but aneuploidy and partial rearrangements may also influence genomic divergence. In this study, we reported a comprehensive cytogeographic, morphological and genetic analysis of  Variations of karyotype and chromosome number, such as polyploidy and aneuploidy, can drive genomic novelty and intraspecific diversification and act as a mode of immediate and sympatric species . UnrecogLycoris aurea (L’Hér.) Herb., a member of the family Amaryllidaceae, is a typical aneuploid complex with the chromosome numbers of 2n = 12–16, including L. aurea var. aurea, L. aurea var. angustitepala and L. traubii  because of its broad pharmacological activities of Amaryllidaceae alkaloids  How many different cytotypes and what cytogeographic patterns are present across the entire distribution range of the complex? (2) Is the cytogeographic pattern concordant with the population genetic structure revealed in cpDNA variation? (3) Are the different cytotypes recognizable using morphological characters? To achieve these goals, we undertook a large-scale screening covering most of the distribution range of the L. aurea aneuploid complex, assessing the association between aneuploidy and intraspecific diversification.The current study examined the cytotype diversity and distribution of L. aurea complex through its distribution range in East Asia, including forty-five populations in China and one population in Japan were collected. To avoid biasing sampling, bulbs were collected apart from more than five meters each other and then transplanted in an experimental common-garden in Anhui Normal University. Detailed information for populations sampled in this study is listed in Forty-six natural populations of The karyotypes were determined at mitotic metaphase for a total of 264 bulbs from the 46 populations (2–6 bulbs for each population) using conventional karyotype analysis methods . The karL. aurea complex in East Asia, we chose 7 previously published populations with precise chromosome number data and geographical localities, of which 3 populations  rpl32-trnL was amplified and sequenced with primers rpl32-F and trnL-R. (3) psbA-trnH was amplified and sequenced with primers psbA-F and trnH-R. (4) ndhF was amplified with primers ndhF-1F and ndhF-R, and the more than 2000 base-pair PCR products were sequenced with primers ndhF-1F, ndhF-2F, ndhF-3F, and ndhF-4F. The Primer sequences were listed in 1 All sequences newly obtained have been deposited in GenBank. The accession numbers are OP021502–OP021631.After karyotypic analysis, we analyzed the plastid nanensis , in addirecently . All samL. aurea complex, we calculated the number of haplotypes, haplotype diversity (Hd) and nucleotide diversity (π) at species and cytotype levels using Dnasp v.5.1  and Bayesian inference (BI) methods, respectively. The ML analyses were performed using RAxML-HPC v8.2.10  with 100°C, and then sliced after the materials were solidified. The section thickness was set to be ∼18 μm, during specific operation, appropriate adjustments of the thickness were made according to the differences of leaves from different populations. Then the sections were stained with 5% safranin and made into tablets. The sections were observed with a computer-equipped Leica microscope (Leica DMi8). Stomatal and epidermal cell densities were estimated from abaxial leaf surface impressions of six leaf segments. The photographs were taken under a biological microscope (Olympus) at 100 × magnification for morphological measurements. Micrographs were analyzed with Olympus-affiliated software to determine stomatal and epidermal cell densities. Stomatal index was calculated by using the formula [S/(E + S)] × 100, where S and E indicate the number of stomata and epidermal cells per unit area of leaf, respectively.To measure the length and width of the leaves, randomly selected six leaves from 6 plants  within one population were measured using a metric ruler. For anatomical measurements, three leaf segments from the middle of leaves of three individuals for each population were fixed in FAA . The samples of leaves were embedded on the sample holder with OCT compound (SAKURA) as an embedding medium, and the temperature in the cryostat microtome (Leica CM1950) chamber was set to –20n = 12 to 2n = 16. Of the 46 populations analyzed, four cytotypes of four different chromosome numbers were identified: (1) 2n = 12 = 10m + 2T , followed by ndhF , matK  and psbA-trnH .The combined sequences of four cpDNA regions were aligned with a consensus length of 4,748 bp. Indels were excluded in the analysis given their proneness to homoplasy. Thus, a total of 4,635 sites excluding sites with gaps/missing data were found in the cpDNA dataset, 76 sites of which were single nucleotide polymorphisms (SNPs) and parsimony-informative . The regn = 14 = 8m + 6T (cytotype II), followed by H15 (5/42) and H10 (4/42). Cytotype I having only one population fixed one haplotype (H23). The group of cytotype II, comprising 28 populations surveyed, had the highest number of haplotypes (21/32). Each population within cytotype III fixed a different haplotype, respectively. Cytotype IV with 10 populations harbored 8 haplotypes. Only one haplotype (H15) was shared between cytotypes II and IV.These SNPs identified 32 different chloroplast haplotypes (H1-32) across the 42 surveyed populations (Hd = 0.932) and nucleotide diversity (π = 3.96 × 10–3). At the cytotype scale, the degrees of cpDNA haplotype diversity and nucleotide diversity were unequal. The cytotype II had the highest haplotype diversity (Hd = 0.885), with the nucleotide diversity (π) being 3.35 × 10–3. The cytotype IV harbored the highest nucleotide diversity (π = 4.09 × 10–3), with its haplotype diversity (Hd) being 0.809 , 3 populations with cytotype III (2n = 15) and 9 populations with cytotype IV (2n = 16).To identify if morphological characters in different populations or cytotypes of this complex show significant differences, only the populations cultivated in the experimental common garden for more than 4 years to eliminate the influence of environmental factors were selected. The only one population with cytotype I was also excluded. Eventually, 38 populations were analyzed, comprising 25 populations with cytotype II  and three southeastern populations (East) . Howevern = 15). For example, the population 11 from Tongde Town has the thinnest leaf (on average 364.2 μm), even among all populations of this complex. Population 1 from Laizhou Town, Fujian has the narrowest leaf among the three populations, with the average leaf width being 2.7 cm, significantly lower than that in population 11 (4.1 cm). We also found that in nature and cultivation, the cytotype III is nearly sterile, and produces no seeds with intact reproductive organs.We also observed significant differences in leaf characters among three populations with cytotype III  was ancestral. In the course of the karyotype evolution, m-type chromosomes changed successively into T-type chromosomes by centromeric fission. Therefore, the genome composed of three m- and five T-type chromosomes (2n = 6m + 10T) is a derivative  may be ancestral.Based on an extensive cytogenetical study on rivative . HoweverL. aurea is also distributed in Anhui, southern Jiangsu, southern Shanxi and Zhejiang. However, based on comprehensive sampling and morphological analyses of Lycoris species, we found no wild L. aurea populations in these regions. For a long time, taxonomists have confused this taxon with another similar yellow-flowered species, L. chinensis, which is widespread in these regions. But the leaves of L. chinensis appear in early spring, differing from L. aurea.Previous records  showed tL. aurea complex revealed two areas with a high diversity of cytotypes: the junction of Guizhou, Yunnan and Guangxi provinces and the junction of the three provinces, namely Hunan, Jiangxi and Guangdong. It was possible that continuous hybridization and aneuploidization events might have occurred, which would have led to such diversity of cytotypes in these areas.Cytogeographic patterns may reveal significant amounts of diversity by identifying multiple chromosomal races among related species or within a single taxonomic species and, therefore, contribute to the conservation of rare species and ecological restoration . The cytL. chinensis with 2n = 16, an extremely low proportion of examined bulbs of L. aurea complex has B chromosomes. Our previous work has shown that approximately 10.64% of the total 188 bulbs of L. chinensis studied have one or more B chromosomes , then we might also conclude that there were a minimum of three independent origins of the sterile cytotypes in the evolutionary history of this complex. If the sterile cytotype was evolved from the fertile cytotypes, II and/or IV, assuming that the haplotype relationship constructed  revealed by cpDNA data was higher than the mean value of 26 species in the Sino-Japanese Floristic Region (SJFR) of East Asia summarized and reported by Cardiocrinum (Endlicher) Lindley, a genus containing three species and one variety of bulbous perennial herbs in the SJFR (Hd = 0.792) than that at the L. aurea species-level.Consistent with extensive karyotypic polymorphism, wide genetic variation was uncovered in the the SJFR , has a mL. aurea complex was not monophyletic and differentiated into two distinct major lineages. Three other Lycoris species, i.e., L. radiata, L. chinensis, and L. longituba, were grouped within lineage I with high support , and another two Lycoris species, L. sprengeri and L. sanguinea, were also close to lineage I, despite relatively low support . When cultivated in the common environment for a long time, significant leaf character differences between and within cytotypes were found, suggesting that high variation in leaf morphological characters within the L. aurea complex is mainly the product of genetic variation. Moreover, different cytotypes and/or different lineages with the same chromosome number had non-overlapping distribution ranges. These results implied that L. aurea complex had experienced marked bio-geographical diversification and might contain multiple species. The taxonomic and evolutionary problems, which should be addressed in future, are the accurate species delimitation through an integrative taxonomic approach and the trend of karyotypic evolution by combining phylogenomics and fluorescence in situ hybridization analyses.AMOVA analysis showed that the majority of genetic variation (98.61%) in cpDNA was attributed to inter-population variability, indicating that this complex has undergone strong population differentiation and very limited gene flow. Our cpDNA phylogenetic trees demonstrated that L. aurea comprised more than two monophyletic lineages with a deep divergence. Moreover, several morphological diagnostic characteristics were discovered from the field and common garden that corresponded to these independent evolutionary lineages. For example, the fertile cytotype (2n = 16) contained two main independent lineages, which are also geographically allopatric. The populations having 2n = 16 from Guangdong province have obtuse leaf apex, whereas the leaf apex of all other L. aurea populations is acute, suggesting the former was a distinct species. Taking into account all of this evidence, we considered L. aurea complex should comprise multiple independent evolutionary lineages. Accurate species delimitation needs to be established, both for assisting wild resource conservation and reasonable utilization. There has been more long-standing interest in polyploidy than aneuploidy in plants. The importance of polyploidization in plant evolution has been highlighted. Future studies should focus on trying to understand the role of aneuploidization in flowering plant evolution and speciation.Our cytogeographic and plastid DNA haplotype analysis indicated that OP021502 – OP021631.The data presented in this study are deposited in the GenBank repository, accession number: KL conceived and designed the article. KL, WM, and DZ contributed to the sampling. JW, LS, HZ, YL, and GL performed the experiment. JW, LS, and KL analyzed the data and wrote the manuscript. All authors contributed to the article and approved the submitted version.


One hundred and six Rétköz and 48 Váh valley samples were collected from the contact zones of Hungarian-Slovakian territories and were genotyped for Y-chromosomal haplotypes and haplogroups. The results were compared with contemporary and archaic data from published sources. The genetic composition of the Rétköz population from Hungary and the Váh valley population from Slovakia indicates different histories. In the Rétköz population, the paternal lineages that were also found in the Hungarian Conquerors, such as R1a-Z93, N-M46, Q-M242, and R1b-L23, were better preserved. These haplogroups occurred in 10% of the population. The population of the Váh valley, however, is characterized by the complete absence of these haplogroups. Our study did not detect a genetic link between the Váh valley population and the Hungarian Conquerors; the genetic composition of the Váh valley population is similar to that of the surrounding Indo-European populations. The Hungarian Rétköz males shared common haplotypes with ancient Xiongnu, ancient Avar, Caucasian Avar, Abkhazian, Balkarian, and Circassian males within haplogroups R1a-Z93, N1c-M46, and R1b-L23, indicating a common genetic footprint. Another difference between the two studied Hungarian populations can be concluded from the Fst-based MDS plot. The Váh valley, in the western part of the Hungarian-Slovakian contact zone, is genetically closer to the Western Europeans. In contrast, Rétköz is in the eastern part of that zone and therefore closer to the Eastern Europeans. The Carpathian Basin was historically the destination for several nomadic tribes that migrated westwards from Inner and Central Asia towards Europe. The ancient Hungarians (Steppe Magyars) entered the Carpathian Basin from the east in the ninth century CE and settled there . The genBased on published uniparental genetic data, the contemporary Hungarians possess some genetic similarities to ancient conquerors in the Carpathian Basin, as well as to Central/Inner Asian populations and populations in the Ural Mountains . The corThus, the present-day Hungarian speakers have a very complex genetic history. Moreover, the population consists of several ethnic groups in the Carpathian Basin, such as the Székely, Csángó, Palóc, Jász, and Kun. However, Y-chromosomal studies about them and other regional population groups are still limited.In our previous study, we studied paternal genetic composition of the Bodrogköz population in Eastern Hungary and found genetic similarities to that of ancient Hungarians . To contThe Rétköz is a region in Eastern Hungary, whereas the Váh valley is in Western Slovakia. The populations of both places live within the Hungarian-Slovakian contact zone and are Hungarian-speakers. The Rétköz is near the Bodrogköz , but genIn this study, we present new Y-STR and Y-SNP data of two Hungarian-speaking populations in the contact zone of Hungarian-Slovakian territories and compare them to contemporary Eurasian and available aDNA data to gain further knowledge about the genetic history of these populations.We collected samples from 106 unrelated males from Rétköz, Hungary and 48 males from the Váh valley, Slovakia . InformeGenomic DNA was extracted from buccal swabs using the Investigator kit and EZ1 robotic system , as described in the manufacturer’s instructions. The samples were quantified using the Quantifiler Human kit and the ABI 7500 Real-time PCR System .DNAfrom the Rétköz and Váh valley populations was surveyed for genetic variation using the Promega PowerPlex Y23 kit. Allele sizing and calling were determined with the ABI3500 Genetic Analyzer and GeneMapper ID-X v.1.4 software. To test for Y-SNP markers , we performed amplifications of 1–2 ng genomic DNA with Custom TaqMan probes and analyzed the relative fluorescence of the PCR productsin an ABI 7500 Real-time PCR instrument using SDS.1.2.3 software. The SNP markers tested were CT-M168, KT-M9, PR-M45, T-M170, I-M170, I1-M253, I2b-M223, I2a-P37, J-M304, J1-M267, J2-M172, J2-M67, J2b-M12, R-M207, R1-M173, R2-M124, R1a-M198, R1a-SRY1083.1, R1a-M458, R1a-Z93, R1a-Z280, R1b-M343, R1b-P25, R1b-U106, R1b-P312, R1b-M412, R1b-Z2103, D-M174, N-M231, N1-LLy22g, N-L708, N-M46, N-L1034, N-VL29, N-Z1936, N-F4205, R1a-Y2633, and N-Y24365. The haplogroups are described in accordance with the generally accepted nomenclature, as is common practice  haplotypes in this study were sent to the YHRD .−4/locus/25 years  genetic distances were computed with YHRD. org’s online AMOVA, and the MDS plot constructed (release 66) . PairwisHaplotype and haplogroup frequencies and their diversity values were calculated using the formula from The haplogroup frequencies of the two populations from the Hungarian-Slovakian contact zone are presented in In the case of the Váh valley males, the most frequent haplogroups were I2a-P37 and R1a-Z280 (both at 16.67%). The frequencies of the remaining haplogroups were as follows: E1b1-M78 (14.58%), R1a-M458 (6.25%), R1b-P25/M343 (6.25%), E1b1-M123 (4.17%), G2a-L156 (4.17%), I1-M253 (4.17%), J2a1-M67 (4.17%), and the remaining haplogroups (2.08%). However, nearly 10% of the present-day Rétköz population may be related to the ancient Hungarians based on haplogroup composition, but the modern Hungarians in the Váh valley lack such relatedness.The haplotype and haplogroup diversities of the Rétköz group were 1.00 and 0.901, respectively, whereas these values for the Váh valley were 0.998 and 0.904, respectively. The results show that, in both populations, haplotypes are more diverse than haplogroups.Based on the Y-STR haplotypes, networks were constructed for haplogroups that may be linked to those of the Hungarian Conquerors, because these haplogroups can be found in ancient Hungarians and originated from Inner/Central Asia. We also included 10 Y-STR haplotypes from other Eurasian populations and aDNA results from published sources to widen the geographical context. We have included six networks  that are potentially helpful in uncovering the genetic legacy of the populations being studied. Other networks, which were constructed for haplogroups of European origin  and could not be related to Hungarian Conquerors, were not included in the study. www.yfull.com).The other studied samples in the network either form independent clusters, such as Altaians, Khakassians, Khanties, and Uzbek Madjars, or are scattered within the network. Other aDNA samples . One Hungarian aDNA haplotype  within N-M46 lineage for 179 samples is estimated as 11.3 ± 3.3 kya (95% CI = 8.0–14.6 kya), considering cluster one is the founder haplotype, which is similar to its sequence-based calculation of 13 kya (95% CI:11.3–14.6 kya) .A median-joining network of 153 R1b-M343/P25 (Eastern R1b-L23) haplotypes was generated using samples from FTDNA, populations we previously studied  Figure . The fouyfull.com). For the R1b (xM412) branch, the age of accumulated STR variation is 17.7 ± 5.2 kya (95% CI = 12.5–22.9 kya), which is much higher than whtat The other population samples in the network formed independent clusters, such as Lezgian, Ossetian, and Circassian from the Caucasus or were scattered in the network. Primarily Balkarian (Caucasus) and Uzbek males form an independent branch (R1b-M73) on the right side of the network . The ageThe median-joining network of 167 Q-M242 haplotypes from 12 populations does not show a star-like pattern, but rather a more diverse one. However, it was simple to analyze the genetic relationship of the Hungarian samples . The larThe Rétköz 80 (R80) sample shares the same haplotype as an Uzbek male, and the Rétköz 101 (R101) sample clusters with a Mongolian male. The third Rétköz male (R58) is located six steps away from an Uzbek sample and is an outlier.It is noteworthy that some Hungarian samples, primarily Hungarian-speaking Csángó and Székely males in Transylvania, Romania form a separate branch with the ancient Xiongnu males  (see the black and red circles within the dashed circle in the lower left part of The age of accumulated STR variation within the Q-M242 lineage for 167 samples is estimated to be 17.7 ± 3.6 kya (95% CI = 14.1–21.3 kya), considering that the modal haplotype  is the fThe MJ network of 189 G2a-L156 haplotypes is depicted in The age of accumulated STR variation within the G2a1-L156 lineage for 189 samples is estimated to be 19.2 ± 3.7 kya (95% CI = 15.5–22.9 kya), considering the modal haplotype  is the fThe age of accumulated STR variation within the E1b1-M78 lineage for 183 samples is estimated to be 6.7 ± 1.3 kya (95% CI = 5.4–8.0 kya), considering the modal haplotype see M in  is the fwww.yhrd.org). The Rst-genetic distances and Rst p-values of the studied populations are presented in We constructed a non-metric multidimensional scaling (MDS) based on Y-chromosomal haplotypes  that consisted of 23 STR loci available from 14 populations (The cluster one populations showed close genetic affinities (<0.05) with most of the European populations that were compared, such as Croatian, Czech, and Polish. Interestingly, cluster one population is closely related to the Xinjiang Uighur population in China. Finnish (0.2844), Bashkirian Mari (0.1722), and Estonian (0.1181) populations, however, are genetically farthest from cluster 1.p-values for 61 populations, including Rétköz, Váh valley, and other Eurasian populations from published sources were calculated as shown in p > 0.05)  . FurtherThe location of the studied populations on the MDS plot is consistent with the geographical distances between them . PopulatThe primary objectives of this study were to create a male phylogeny of the Hungarian-speakers in Rétköz and the Váh valley and to compare them with other Eurasian populations, with aDNA samples from their probable ancestral geographical origin, and with previously studied populations.To examine the genetic variation within the Hungarian groups, we used evolutionarily stable binary markers (SNPs) to define the haplogroup of each Y-chromosome, and then examined the STR-defined variation within each haplogroup. The established geographical specificity of Y haplogroups means that the haplogroups observed in the Hungarian-speakers may be attributed to their geographical origins or may be related to the Hungarian Conquerors. These conclusions, however, remain uncertain.The overall pattern of haplogroup distributions in the studied populations was similar, but haplogroups R1a-Z93, N1c-L1034, N1c-VL29, N1c-Z1936, and Q-M242 appeared only in the Rétköz population . HaplogrUnderhill et al. state that the paragroup R1a-Z93 was most common in the South Siberian Altai region but that it also occurred in Kyrgyzstan and, in all Iranian populations. R1a-Z2125 occurred at highest frequencies in Kyrgyzstan and among Afghan Pashtuns. Additionally, the R1a-Z93 haplogroup was also common in Afghan (Tajik) and Caucasian ethnic groups (Tajik). As such, we included the populations (Z93 haplotypes) from the regions analyzed by other researchers , ancientIt is surprising that the present-day Hungarian, ancient Hungarian and Xiongnu samples are located adjacent to each other on this branch, indicating that 1-1 mutation step separates them. aDNA studies showed that the Hungarian King Béla III, and another sample (II54) from Royal Basillica belonged to haplogroup R1a-Z93 , and twoThe Y-chromosomal haplogroup N-M231 is widespread from Scandinavia to the Kamchatka in North Eurasia and is the most frequent single haplogroup in Siberia . Based oThe Hungarian Y-chromosomal gene pool has only a small percentage of N-M46  and has a distribution typical of East-Central Europe . HoweverThe Rétköz N-M46 sample 1 (R1) from this study and four other Hungarian samples belong to haplotype cluster one and share 31 haplotypes with 8 Eurasian populations , indicating they may all share a common genetic history . The secThe most frequent Western European lineage, haplogroup R1b-M269, was originally thought to have originated in the Palaeolithic. Recent analysis, however, suggests a Neolithic origin . Most R1Our network analysis showed that the R1b*-M343 (xM412) haplotypes are divided into two subclades: R1b-L23 (xM412) and R1b-M73. The Rétköz and other Hungarian haplotypes cluster with the L23 samples included in the study and share haplotypes with Hungarian, Abkhazian, and Avar males from the Caucasus, suggesting a genetic link between them see . These AThe haplotype analysis revealed a genetic relationship between the contemporary Hungarian-speakers and Caucasian populations  included in this study. It should be noted, however, that the peoples of East-Central Europe received Central-Inner Asian and Caucasian genes before and after the ancient Hungarians settled in the Carpathian Basin  . Based oThe human Y-chromosome haplogroup Q-M242 likely originated in Central Asia and Southern Siberia 15–25 kya , and theBased on the network analysis of haplogroup Q-M242, is that Hungarian-speaking populations living in more isolated areas (no admixture), such as Csángó and Székely males in Transylvania, Romania, clustered on the same branch as the ancient Xiongnu people lived in Inner Asia about 2000 years ago, suggesting these males are genetically related see . An UzbeThe remaining two Rétköz Q samples (R101 and R58) cluster with Central  and Inner Asian (Mongolian) samples in a subbranch of the main branch, which indicates that these samples are distant from the Hungarian-Xiongnu subbranch but that they nevertheless originate from a common branch .Another interesting observation is that three Hungarian males on the Hungarian-Xiongnu branch  form a cwww.phylotree.org/Y/tree/G.htm). Rootsi et al. analyzed 113 Hungarian males, of which 2 belonged to haplogroup G-M201 (1.8%) and to subgroups G-L497 (0.9%) and G-M406 (0.9%). These authors showed that SNP P303 defines the most frequent and widespread subhaplogroup G, whereas P303-related L497 lineages occur in Europe, where they likely originated. The highest frequency of G2a-P303 is detected in populations from the Caucasus, specifically among South Caucasian Abkhazians (24%), Northwest Caucasian Adyghe (39.7%), and Cherkessians (36.5%)  . Another (36.5%) . The G2a (36.5%) .Based on our network analysis, four subclades can be distinguished as L497, P303, M406, and P18 (under P16), as the samples with known haplogroups in the network are clustered on the same branches. Hungarians are included in L497, P303, and M406 subclades, except for P18 (1 Csángo sample), indicating that the gene flow from the P18 subclade of the Caucasus has been negligible. We included nine samples from the Rétköz and Váh valley populations, each of which falls into these three subgroups. The results indicate a close genetic relationship between the Hungarian-Balkar/Karachay and Hungarian-Avar males, because they share common haplotypes (cluster 1–3) or cluster in similar haplotypes . Thus, these observations likely suggest a common genetic origin, rather than coicidence.http://www.phylotree.org/Y/tree/G.htm). This indicates that SNPs L293 and L30 are older than SNPs M406 and P303, whereas SNPs U1 and L497 are the youngest.The results of the aDNA studies in the Carpathian Basin show the haplogroup G2a-L156. One ancient Avar and four Hungarian Conqueror samples belong to the subgroup G2a-L293, two Hungarian Conqueror samples belong to haplogroup G2a-U1, and one ancient Hungarian sample belongs to haplogroup G2a-L30 . SNPs L2As such, the modern and ancient DNA results support the case for a common genetic origin of the Hungarian and Caucasion populations.www.phylotree.org/tree/E/htm). From downstream SNPs of haplogroup E, the E1b1-M35 mutation and M78 below it are two of the most frequent markers in European males. E-V13, a single clade within E, highlights a series of expansions duirng the Bronze Age in Southern Europe (www.phylotree.org/tree/E/htm). The highest frequency values for the M78 lineage are detected in populations from the Balkans, such as Albanians (32.29%), Bulgarians (16.67%), Macedonians (18.18%), continental Greeks (19.05%), and Southern Italians (13.07%) , is the most common human Y-chromosome clade in Africa (n Europe . All Eur(13.07%) . The fre(13.07%)  and 9.43(13.07%) , and it (13.07%) .As shown in Xth century) , as well as among the Hungarian Conquerors (895-mid century) . HoweverBased on the network topologies, the most diverse haplogroups are Q-M242, G2a-L156 and R1b-L23, which can be seen from the pattern of the networks, that is, the number of unique haplotypes of a male within the network is significant as well as the age of the accumulated STR variation (TMRCA) also supports it. The divergence times of haplogroups N-M46 and R1a-Z93 are almost the same (TMRCA) and within the network there are many clusters where several males share the same haplotype. Haplogroup E-M78 is the youngest, as the number of unique haplotypes is less than in the other networks.Based on Fst analysis, the Váh valley population shows a stronger genetic similarity to Balkan populations than does the Rétköz population. This is primarily due to the relatively high E and I2a haplogroup frequencies. Both haplogroups are common in Balkan populations but are less frequently found in Eastern Europeans . The RstIn summary, the results obtained by us, which show that the genetic relationships between modern Hungarians, Hungarian Conquerors, Asian Huns (Xiongnu) and ancient Avars are continuous, are fully supported by the results of the whole genome sequencing data performed by Hungarian researchers .The genetic composition of the Rétköz (Hungary) and Váh valley (Slovakia) populations indicate different histories. In the Rétköz population, the paternal lineages that were also found in the Hungarian Conquerors, such as haplogroups R1a-Z93, N-M46, Q-M242, R1b-L23, and G2a-L156, were better preserved. The genetic composition of the Váh valley population is similar to that of the surrounding Indo-European populations.The Hungarian males shared common haplotypes with ancient Xiongnu, ancient Avar, Caucasian Avar, Abkhazian, Balkarian, and Circassian males within haplogroups R1a-Z93, N1c-M46, and R1b-L23, suggesting a common genetic footprint. Additionally, Hungarians cluster on a common branch with the ancient Asian Huns (Xiongnu), ancient Avars, and several modern Caucasian populations  within the haplogroups R1a-Z93, R1b-L23, and Q-M242, implying a close genetic relationship.Further studies are needed to clarify if the common genetic footprints were acquired directly or indirectly. Comprehensive studies from European, Central Asian, and Caucasian populations should be conducted for the haplogroups using more downstream SNPs and NGS sequencing to learn more about the origins, expansion, and ethno-linguistic affiliations of the populations.


To use the method of meta-analysis to assess the influence of island population isolation on the sub-structuring of the Croatian population, as well as the influence of regional population groups on the sub-structuring of the Southeastern European population with regard to basic population genetic statistical parameters calculated by using STR locus analysis.Bio-statistical analyses were performed for 2877 unrelated participants of both sexes from Southeastern Europe. Nine autosomal STR loci  were analyzed by using standard F-statistics and population structure analysis (Structure software).ST method was higher at the level of the Croatian population (0.005) than at the level of Southeastern Europe (0.002). The island of Vis showed the most pronounced separation in the Croatian population, and Albanians from Kosovo in the population of Southeast Europe, followed by Croatia, Bosnia and Herzegovina, and Hungary.Genetic differentiation of Croatian subpopulations assessed with the FThe higher structure of Croatian subpopulations in relation to Southeastern Europe suggest a certain degree of genetic isolation, most likely due to the influence of endogamy within rural island populations. The island populations of the eastern Adriatic have been the subject of multidisciplinary anthropological research for almost 50 years, starting with the pioneering work of Rudan et al in 1972 . The redSoutheastern Europe was one of Europe’s glacial refugia during the ice age, and the origin of postglacial resettlement of Europe in the Paleolithic and Neolithic. Due to this specific role and its position at the crossroads of migrations to and from Europe, this area was extensively investigated in the field of population genetics -7. DiffeThis study represents a continuation of previous anthropogenetic research ,13-16. WThe aim of this study was to determine the genetic characteristics of populations from Southeastern Europe, with special reference to Croatian island populations, and to investigate the effect of specific intrapopulation genetic structure on interpopulation relationships. Namely, a specific aim was to investigate the influence of island population isolation on the sub-structuring of the Croatian population, and the influence of regional population groups on the sub-structuring of Southeastern Europe with regard to basic population genetic statistical parameters calculated by using STR locus analysis.The samples used were the same as described in a previous article by our research group . CertainSTR marker analysis was performed by salting out method  as descrSince data for 2877 samples were unavailable for all the loci included in the AmpFLSTR Identifiler PCR Amplification Kit, to allow data comparison, bio-statistical analyses were conducted for nine autosomal STR loci .IS), between subpopulations (FST), and within the total population (FIT), was used as a measure of correlation between alleles. Clustering was performed with the Ward hierarchical method , excluding the mainland population. The analysis conducted at the level of Southeastern Europe included a sample of Southeastern European populations (n = 1805). The Croatian sample analyzed in the broader Southeastern European context was reduced from n = 1230 to n = 158 to mirror the portions of these populations in the actual sample of Croatia and to avoid sample bias .ST) for the compared population pairs (ST = 1.6%), followed by Cres-Vis, and Korčula-Vis, with the same degree of FST = 1.4%. Vis showed the highest values of genetic differentiation compared with all other analyzed populations. The observed values for this island ranged from 0.7%, when compared with the mainland and NDI to 1.6%, when compared with Hvar.The total genetic differentiation coefficients ) obtained using the Structure program was highest for K = 1 and gradually decreased for each subsequent K. According to the second criterion for determining the most reliable K , taking ST) among all analyzed subpopulations of Croatia was low and amounted to 0.005, which means that only 0.5% of genetic diversity was influenced by differences between subpopulations. Since these geographically close populations share a common evolutionary history but have biological and socio-cultural specifics that have differently shaped their genetic structure, this study investigated how these populations related to each other and what the degree of their isolation was.The total genetic differentiation coefficient   would be more appropriate.When looking at individual pairs of populations, 86% of population pairs were genetically different from each other as much as any two randomly selected European populations. Namely, among the largest European countries, the conservative upper limit of Fil (NRC) . This waountries . HoweverST values >1% were Cres and Vis, Korčula and Vis, and Cres and Hvar, which also indicates the genetic diversity of these population pairs. On the other hand, allelic frequencies on the island of Brač and mainland, and Krk and NDI, which according to historical demographic data were founded by genetically similar ancestors, did not differ significantly. Previous studies of Eastern Adriatic islands observed a high degree of diversity (FST) among most of the investigated population pairs. The diversity within the islands, ie, their settlements (subpopulations), has, for example, been established on Hvar, Krk, Brač, and Korčula  at any of the analyzed loci. This finding might be explained by the fact that Brač and Krk are close to the mainland with good transportation connections and therefore less isolated than outer islands. Of the remaining population pairs, 14% differed in a slightly higher percentage. Thus, the highest degree of genetic differentiation was observed between Hvar and Vis (1.6%), which indicates an extremely high genetic diversity of these two populations. The remaining three population pairs with F Korčula . The greST index. Due to the reduced impact of endogamy at a higher level of population grouping, a lower coefficient of genetic diversity was found among the populations of Southeastern Europe – only 0.16%, which indicates a homogeneous distribution of alleles of the studied loci at the level of “general” populations of Southeast Europe. Similar FST values (0.28%) were found among 11 European countries in an analysis based on microsatellite markers  (ST) between defined  populations of Croatia (from 0.001 to 0.016), the “LocPrior” model was used  , despitewas used .Furthermore, the mainland population was represented by a significantly larger number of participants (N = 497) than island populations (N = 82-137). Since disproportionate sample sizes may affect the determination of population structure , we hypoThe established and most reliable value of K = 6 shows that these seven pre-defined island populations are grouped into six predicted, genetically different founder populations. This speaks in favor of the continued isolation of the eastern Adriatic Island communities and their mutual genetic diversity, and the existence of weak, but existing sub-structuring at the Croatian population level.ST analysis. This finding is not surprising, since they are geographically neighboring populations.The analysis showed greater homogeneity of the populations of this hierarchical group. Namely, while island subpopulations were separated into six predicted genetically different founder populations (K = 6), populations of Southeastern Europe split into only three different founder populations (K = 3). Due to the reduced influence of endogamy, lower genetic differentiation was found in Southeastern Europe than at the level of the Croatian subpopulations. To a lesser extent, the segregation of the populations of Croatia and Bosnia and Herzegovina and Hungary was visible, which is in line with their grouping into a common cluster based on FThe isolation of the Albanian population from Kosovo confirms the results of previous analyses , where tThis meta-analysis provides a systematic overview of the genetic sub-structuring in Croatia and in a wider Southeast-European context. It also highlights the importance of isolated island population in the making of a population’s genetic landscape. There are certain limitations to this study. A meta-analysis includes data from many different sources, which has certain disadvantages. Among others, the number of STRs included in the study had to be reduced in order to enable comparisons. However, even with a limited number of STRs (only nine) a sub-structure was detected.ST method was higher at the level of the Croatian population (0.005) than at the level of Southeast Europe (0.002). Namely, the assessment of the genetic population structure for Croatia defined 6, and for the population of Southeastern Europe 3 genetically different clusters. In the population of Croatia, the subpopulation of the island of Vis showed the most pronounced separation, and in the population of Southeastern Europe the population of Albanians from Kosovo, followed by the populations of Croatia, Bosnia and Herzegovina, and Hungary. The established higher structure of Croatian subpopulations in relation to Southeastern Europe suggests the existence of a certain degree of genetic isolation, most likely due to the influence of endogamy within rural island populations.The total genetic differentiation coefficient of Croatian subpopulations calculated by the F


Amblygaster sirm , is a commercial sardine commonly caught in Malaysia. Lack of management of these marine species in Malaysian waters could lead to overfishing and potentially declining fish stock populations. Therefore, sustainable management of this species is of paramount importance to ensure its longevity. As such, molecular information is vital in determining the A. sirm population structure and management strategy. In the present study, mitochondrial DNA Cytochrome b was sequenced from 10 A. sirm populations: the Andaman Sea (AS) (two), South China Sea (SCS) (six), Sulu Sea (SS) (one), and Celebes Sea (CS) (one). Accordingly, the intra-population haplotype diversity (Hd) was high (0.91–1.00), and nucleotide diversity (π) was low (0.002–0.009), which suggests a population bottleneck followed by rapid population growth. Based on the phylogenetic trees, minimum spanning network (MSN), population pairwise comparison, and FST,and supported by analysis of molecular variance (AMOVA) and spatial analysis of molecular variance (SAMOVA) tests, distinct genetic structures were observed (7.2% to 7.6% genetic divergence) between populations in the SCS and its neighboring waters, versus those in the AS. Furthermore, the results defined A. sirm stock boundaries and evolutionary between the west and east coast (which shares the same waters as western Borneo) of Peninsular Malaysia. In addition, genetic homogeneity was revealed throughout the SCS, SS, and CS based on the non-significant FSTpairwise comparisons. Based on the molecular evidence, separate management strategies may be required for A. sirm of the AS and the SCS, including its neighboring waters.The spotted sardinella,  The delineation of marine resources’ population or stock structure is critical for fisheries management and conservation , particuAccording to Genetic data is now being incorporated, albeit slowly, in designing marine protected area networks, stock restoration, and fisheries management policies . These sAmblygaster and Sardinella, with three species in the former and 22 in the latter. The Amblygaster sirm  or spotted sardinella is one of the small pelagic fishes commonly caught in Southeast Asia. This species is locally known as “Tamban Beluru” in Malaysia , such as herrings, sprats, shads, wolf-herrings, and anchovies from the clupeoid fishes (suborder Clupeoidei and order Clupeiformes) are abundant throughout the Atlantic, Indian, and Pacific oceans . They arMalaysia  and “SirMalaysia . The A. ishermen . In addiishermen . Recent a waters . This sin waters , a populn waters , and a on waters .A. sirm population at 30%. In Malaysia, the A. sirm stock in the South China Sea decreased from 1,729.95 metric tons (mt) in 2017 to 1,326.58 mt in 2018  gene was utilized to elucidate the population genetic structure of spotted sardinella, A. sirm, in Malaysian waters and to establish a management plan for this species. This protein-coding gene has been proven to be highly efficient in determining intra and inter-specific and higher-level phylogenetic relationships  ionships . The mtDc levels .Thunnus tonggol  list of endangered or protected species.Since only dead specimens were sampled, no permit was required, and no ethical consideration were required for this study. In addition, A. sirm were collected from ten landing sites from vessels that used purse seine fishing gears in Peninsular Malaysia, Sabah, and Sarawak from 2015 to 2019. These sampling locations cover the southern region of the SCS, SS, CS, and AS. The species were morphologically identified by of 10 to 20 series of black spots down the flank, according to A total of 179 specimens of A. sirm pectoral fin was collected during the sampling activity. Each clipping was fixed in a separate vial containing 95% ethanol and stored at −20 °C until further use.In addition, a small clipping of A. sirm is absent from this location (N = 2), the data was only used in the phylogenetic analysis.The sampling locations were divided into four regions following location . Meanwhilocation . Due to Cyt b was targeted using the following primers; F: WMA15-F (5′ACC GTT GTA ATT CAA CTA TAG AAA C 3′) and R: TruCytb-R (5′ CCG ACT TCC GGA TTA CAA GAC CG 3′) , 0.2 µL of each primer, 2.0 µL of genomic DNA (50 ng/mL), followed by nuclease-free water to achieve the final reaction volume. The thermal cycling conditions were as follows: initial denaturation at 95 °C for 2 min, followed by 35 cycles of denaturation at 94 °C for 10 s, annealing at 56.8 °C for 10 s, and extension at 72 °C for 15 s. The quality of PCR products was visualised on 1.5% agarose gels stained with 1 to 3 µL of GelRedTM Nucleic Acid Gel Stain . The unpurified PCR amplicons were sent to Repfon Technologies Sdn Bhd for purification and sequencing in forward and reverse directions in an automated sequencer .Genomic DNA extraction of 179 samples was performed using the DNeasy Blood & Tissue Kit  according to the manufacturer’s protocol. The quality of extracted DNA was assessed using UV spectrophotometer Q3000  and diluted to a final concentration of 50 ng/µL. The mtDNA C CG 3′) . The PCRπ) (p > 0.05) therefore, further analysis could be proceeded , S. lemuru (NC039553), and S. gibbosa (NC037131) were employed as outgroups in the analysis for both trees. A phylogenetic network of all haplotypes was constructed to view haplotype relationships based on the median-joining calculation in a minimum spanning network (MSN) implemented in the population analysis with reticulate trees (POPART) v1.7 (The RAxML  and maxiRT) v1.7 .Genetic distances within and among populations based on the best nucleotide substitution model of Kimura 2P (K2P), which depicts the lowest Bayesian information criterion (BIC) score, were estimated using MEGA v7.0. These values also assessed the possibility of sub-species or cryptic species occurrence if intra-species variation within marine species exceeds the threshold (2%) .FST) were calculated using ARLEQUIN v3.5  was performed to estimate molecular variance among populations at different hierarchical levels using ARLEQUIN v3.5 . The rel and FCT . The spa and FCT  to ident and FCT  was cond2 in DnaSP v6.0  with a given mutation rate of 1–2% per million years for Cyt b  was high ranging from 0.91 to 1.00, while nucleotide diversity (π) was low, ranging from 0.002 to 0.009  were detected as singletons (haplotypes found in a single gene copy), where 11/122 (9.02%) were shared haplotypes or found in more than a single population. The Pearson correlation test  confirmed that sample sizes did not significantly affect the nucleotide diversity and haplotype diversity (Hd) therefore, further analyses could be performed.The 1,016 bp segment of mtDNA .009 see . A totalThe ML tree and BI analysis revealed a similar topology of two geographically separate mtDNA lineages see ; (1) AS The minimum spanning network (MSN) showed two distinct lineages similar to the phylogenetic trees, separated by 63 genetic mutations see . LineageThe genetic diversity or distance was converted to percentages and revealed intrapopulation genetic diversity ranging from 0.2% to 0.9%, the lowest being in Kudat and the highest in Kuala Perlis . MeanwhiFST values in the AS  populations were significantly different (p < 0.05) (p > 0.05) values were also detected in cases where high genetic distance in some between Lineage 1 and Lineage 2 populations, such as AS vs Semporna Kuantan vs Kuching (both in SCS), Labuan (SCS) vs Kudat (SS), and Semporna (CS) vs Kuantan (SCS).Most  < 0.05) , which aFCT = 0.0066, p = 0.257; FST = 0.0265, p = 0.0009), with 97.34% of the total genetic variation of A. sirm contributed by genetic differences among the total populations. This result indicated a subdivision or structuring within the tested populations. Notably, populations may be contribute the non-significant (p > 0.05) observation within the SCS, represented by more than two populations compared to other seas. Genetic differentiation among populations within groups/seas was significant .The AMOVA indicated no significant differences among populations (between seas) even for the highest variance  signifying two genetically distinct A. sirm stocks among sampled populations: Lineage 1  and Lineage 2   and geographical distance  among tested populations.The result from the SAMOVA paralleled other analyses, with emporna) . The Manp < 0.05) values for all populations  supported the recent population growth hypothesis. Meanwhile, the mismatch distributions of combined populations detected two highly divergent peaks, representing the two lineages , Scarus ghonnan (Blue-barred parrotfish), and Sepioteuths lessoniana (Bigfin reef squid)  , althougFST) were also observed for several pairwise comparisons within Lineage 2 involving Kuching, Kudat, Kuantan, Kota Kinabalu, and Pulau Kambing. In contrast, non-significance was observed between Lineage 1 and Semporna (Lineage 2). Upon weighing other evidence, such as the phylogenetic tree and MSN, it was predicted that the statistical sensitivity of FST was contributed by the small sample sizes rather than genetic isolation or other biological factors.In addition to the two disparate lineages, significant divergences . The non-significant FST values among Lineage 2 populations indicated low genetic divergence and high gene flow. This condition results from the active exchange of genetic material between populations through unrestricted breeding, concordant with this migratory species’ pelagic migratory behavior. High genetic affinity was also observed between the AS populations in Kuala Perlis and Ranong. Similar findings have been recorded in other pelagic fishes in the region, such as ornate threadfin bream, Nemipterus hexodon  movement barriers, the adult and larval pelagic movement characteristics are sufficient for homogenising populations, as observed in the panmictic  hexodon ; crescenn jarbua , Japanesmaruadsi , Russellrusselli ; lesser argyreus  and crimropterus . Furtheroastline . Larval oastline . NonetheA. sirm.π for A. sirm propose a recent population expansion from a low effective size, a probable consequence of rapid population growth after a bottleneck event resulting in a high occurrence of new mutations  in the present may have influenced the statistical strength of the observed population structuring. Nevertheless, MSN, AMOVA and SAMOVA analysis validated this hypothesis. Furthermore, there was no haplotype sharing between the two lineages. Future studies should consider larger sample sizes and populations from the AS to verify the present findings since this research had limited geographical coverage. Furthermore, sampling could be extended to include other areas, such as the Bay of Bengal, where close genetic relatedness with the AS had been identified in several species. This observation was exemplified in the widely distributed Central Indo-Pacific surgeonfishes, Naso brevirostris and N. unicornis  in future studies should be explored. However, the current findings are based solely on a maternally inherited gene. Thus, co-dominant markers such as microsatellites, single nucleotide polymorphisms (SNPs), or whole genome sequencing should be integrated into future studies.The small sample size (in Semporna) and number of populations  exceeded the threshold (2%) of intra-species variation within marine species (S. tawillis (>3%) Taiwan sardinella, S. hualensis (>4%)  (The present of cryptic species or sub-species due to high genetic differentiation is not uncommon among  species . Furtheris (>4%)  and the ination) . Nonetheination)  and morpA. sirm in waters. It is recommended that separate management systems be implemented for the waters fringing the western coasts, Lineage 1 (AS) and eastern coasts, Lineage 2 (the SCS and the neighboring waters). Despite focusing on only one country, it is worth notingy that all the major seas in Southeast Asia are represented in this study.This study has provided novel insights into the population structure and proposed several processes that could define the stock boundaries and evolutionary units of Genetic data should be an important component for fishery managers to make informed decisions on a target species . FurtherA. sirm. A fine example of how regional bodies co-operate in regional fishery management strategies is the ZoNéCo  in New Caledonia that integrated genetic and complementary non-genetic data to manage the Spanish mackerel, Scomberomorus commerson stocks in Bélep, North Province of New Caledonia . The genetic variability data could be used as an indicator to control the harvesting activities between participating countries, besides regulating the number of fish landing at a particular time and the fishing capacity of fishing vessels  specifically SDG14 to combat the global adverse effects of overfishing by 2030  is also crucial for the sustainable fishery management of highly economically important species. This information could guide the fishery managers in determining potential fishing or spawning areas and planning a sustainable fishery policy strategy. For example, the population stock structure determination of spawning areas through DNA metabarcoding could be a way forward in sustaining broodstock management. In addition, the information could facilitate site recommendations for implementing closed areas during the critical life cycle, including spawning and nursery seasons, as suggested by Malaysia . DespiteMalaysia . FurtherMalaysia , therefot policy  would pe by 2030  and effeCyt b marker revealed two highly differentiated A. sirm in the AS and the SCS and the neighboring waters. Demographic history and contemporary factors are identified as possible underlying reasons for the structuring observed. Meanwhile, cryptic diversity could explain the genetic disparity in the A. sirm population. Since two discrete stocks have been identified in this study, different management strategies would benefit the A. sirm population in the Southeast Asia.The mtDNA 10.7717/peerj.13706/supp-1Supplemental Information 1Click here for additional data file.