Ne), inbreeding levels, and the runs of homozygosity (ROHs) are effective tools for exploring the genetic diversity and understanding the demographic history in efforts to support breeding strategies to use and conserve genetic resources. Across populations, the current Ne of Gauteng was the lowest at 371 animals, while the historical Ne across populations suggests that the ancestor Ne has decreased by 53.86%, 44.58%, 42.16%, and 41.16% in Free State (FS), North West (NW), Limpopo (LP), and Gauteng (GP), respectively, over the last 971 generations. Genomic inbreeding levels related to ancient kinship (FROH > 5 Mb) were highest in FS (0.08 ± 0.09) and lowest in the Eastern Cape (EC) (0.02 ± 0.02). A total of 871 ROH island regions which include important environmental adaptation and hermo-tolerance genes such as IL10RB, IL23A, FGF9, IGF1, EGR1, MTOR, and MAPK3 were identified (occurring in over 20% of the samples) in FS (n = 37), GP (n = 42), and NW (n = 2) populations only. The mean length of ROH across populations was 7.76 Mb and ranged from 1.61 Mb in KwaZulu-Natal (KZN) to 98.05 Mb (GP and NW). The distribution of ROH according to their size showed that the majority (n = 1949) of the detected ROH were > 5 Mb in length compared to the other categories. Assuming two hypothetical ancestral populations, the populations from KZN and LP are revealed, supporting PC 1. The genomes of KZN and LP share a common origin but have substantial admixture from the EC and NW populations. The findings revealed that the occurrence of high Ne and autozygosity varied largely across breeds in communal indigenous goat populations at recent and ancient events when a genome-wide single-nucleotide polymorphism (SNP) marker was used. The use of Illumina goat SNP50K BeadChip shows that there was a migration route of communal indigenous goat populations from the northern part (LP) of South Africa to the eastern areas of the KZN that confirmed their historical relatedness and coincides with the migration periods of the Bantu nation.Indigenous goats form the majority of populations in smallholder, low input, low output production systems and are considered an important genetic resource due to their adaptability to different production environments and support of communal farming. Effective population size ( There are currently 15 South African goat genetic resources listed on the DAD-IS of FAO and 13 on the Domestic Animal Genetic Resources Information System (DAGRIS) of the International Livestock Research Institute, including those listed in DAD-IS. In the country, indigenous goat ecotypes have been used as triple-purpose animals ; and depending on the region, the animal characteristics, and the geographical isolation, they have begun to diverge into breeds/populations . These eImprovement of indigenous livestock has been practiced through the introduction of high-performing breeds (exotic and improved breeds), and as a result of indiscriminate mating and breeding, the majority of communal indigenous goat populations are crossbreds . The majIn South Africa, more extensive research studies on genetic diversity analyses were done using microsatellite markers that were instrumental in providing an insight into the genetic structure and variation among South African goat populations . Kotzé  observedThe completion of the first draft of the goat genome  made it Ne) is an important population genetic parameter that has recently received a great deal of research attention  in populations  over generations leads to a reduction in genetic diversity  and ROH have been studied in humans , Gauteng (n = 28), Limpopo (n = 30) and North West (n = 35) provinces of South Africa (n = 20), KwaZulu-Natal (n = 30), Limpopo (n = 30) and North West (n = 20) provinces were included for further analysis.A total of 117 communal indigenous goat populations were sampled from the Free State , had no assigned genomic locations, and on sex chromosomes were also excluded from the analysis. The parameter “–cow” was used to indicate the number  of autosomes in the goat genome since cows and goats have the same number of autosomes. The final dataset included 47,778 SNPs and 207 individuals.All animals were genotyped using the Illumina GoatSNP50 BeadChip  using the Infinium assay compatible with the Illumina HiScanSQ genotyping platform at the Agricultural Research Council—Biotechnology Platform in South Africa. A number of quality control measures were applied to all SNPs as follows: SNPs were removed if they had a call rate < 95%, a minor allele frequency (MAF) < 0.05, and if they deviated from the Hardy-Weinberg equilibrium (for a Ne) for each breed were estimated with the SNeP  in the past as ½c. To verify the accuracy of the coefficient of inbreeding, the genomic coefficient was estimated via two methods. 1) PLINK (FHOM) using the function –het. The calculation formula was as follows: L is the number of genotyped autosomal SNPs, EHOM is the number of expected homozygous genotypes, and OHOM is the number of observed homozygous genotypes. The inbreeding coefficient based on the proportion of autosomes covered in runs of homozygosity per individual (FROH) was determined using detectRUNs  PLINK  was usedtectRUNs . FROHdetectRUNS (detectRUNS. The genomic inbreeding coefficient based on ROHs (FROH) was also calculated as the sum of the length of the autosome covered by ROHs divided by the overall length of the autosome covered by SNPs as described by  were identified in every individual using tectRUNS  using a tectRUNS ; and 4) ribed by . The meahttp://www.genome.jp/kegg/) database and literature search.To identify the genomic regions that were most commonly associated with ROH, the percentage of the occurrences of a SNP in ROH was calculated by counting the number of times the SNP was detected in those ROH across individuals, and this was plotted against the position of the SNP along the chromosome. This percentage threshold was normalized to 70%, 50%, and 20% of individuals per population to be an indication of a possible hotspot of ROH in the genome. The functions of these genes and pathways in which they are involved were assessed using the Kyoto Encyclopedia of Genes and Genomes  was used to subject the whole genotype data set to linkage disequilibrium (LD) pruning  was calculated and plotted in Golden Helix SNP and Variation Suite (SVS) V8.1 . For the analysis of ancestry proportions (admixture) with K set from 2 to 10, the ADMIXTURE  program  was used pruning  prior to pruning .Ne at t generations ago (from 12 to 983) is presented in Ne decreased progressively across generations, however, Ne was higher than 150 for all breeds 12 generations ago. The variation in Ne across generations was smallest for Gauteng (Ne = 371) and the Free State (Ne = 386), whilst Limpopo had the highest (Ne = 723). Ancestral populations exhibited considerably larger Ne values, with the largest historical Ne values .Variation of the estimated FIS) was lowest in Free State (FIS = 0.03 ± 0.09), followed by 0.04 ± 0.09 in Gauteng, 0.05 ± 0.01 in the North West and the highest in Limpopo (FIS = 0.09 ± 0.05). Overall, the inbreeding level was 0.06 ± 0.08. The average FROH, its range of variation across populations and its distribution are summarized in FROH) based on the distribution of the length of runs of homozygosity by class are described in FROH differed significantly among populations across the length categories. The genomic inbreeding coefficients of the shortest ROH  per animal ranged from 0.02 ± 0.02 in the Eastern Cape population to 0.08 ± 0.10 in the North West population. The FROH of Eastern Cape, Limpopo populations increased with category size, whilst decreased in Free State. Gauteng FROH decreased from 0.07 ± 0.09 to 0.05 ± 0.09 for FROH >20 Mb and increased at >20 Mb. In KwaZulu-Natal, FROH increased to up to 0.08 ± 0.09 at <20 Mb and decreased for > 20 Mb category.The average inbreeding coefficient  had at least one ROH longer than 1 Mb. The mean number of ROH per population was 24.36, 23.92, 21.47, 9.13, and 9 in Gauteng, Free State, North West, KwaZulu-Natal, Limpopo, and Eastern Cape, respectively .n = 1949) across all populations , KwaZulu-Natal , Gauteng , North West , and Free State .The mean ROH length was 7.76 Mb across the population. The longest segment (SNP position 39467151–137516937) was observed in the Gauteng and North West populations and was 98.05 Mb in length (1992 SNPs) found on chromosome 1. In KwaZulu-Natal, Free State and Eastern Cape, the longest segments were found on chromosome 9 , chromosome 7  and chromosome 7 , respectively. ROH shorter than 5 Mb predominated  and Gauteng (n = 29) provinces. No ROH islands were observed in the Eastern Cape, KwaZulu-Natal, North West, and Limpopo at the set thresholds. The ROH hotspot with the highest occurrences (SNPs = 149) in Gauteng was located on chr7 (7.69 Mb). Chromosome position, start and end position of ROH, ROH length and number of SNPs within the genomic regions of extended homozygosity are reported in IL10RB, IL23A, FGF9, IGF1, EGR1, MTOR and MAPK3. An additional file 1 shows the KEGG 292 pathways associated with the genes , and this was plotted against the position of the SNP along the chromosome . The thrhe genes  that inc--indep-pairwise 50 5 0.5 command and related individuals (IBS > 0.65). The database for population structure included 32886 SNPs and 189 individuals across populations. The plot of the first (PC1) and second eigenvectors (PC2)   shows weFor the further understanding of the degree of admixture within the populations, the ADMIXTURE 1.3  softwareIn this study, the genetic diversity and population structure of goat populations in South Africa were revealed. The main links to the development of commercial goat populations are represented by indigenous goat populations and may potentially be relevant as a future source of untapped adaptable genetic material . TherefoNe) is a crucial population genetic parameter because of its relationship to the loss of genetic variation, increases in inbreeding, the accumulation of mutations, and the determination of the accuracy of genomic selection  showed a reduction to 132 in the Kingdom of Eswatini and the highest in South Africa 12 generations ago . Furthermore, a study by  values found in the study for the Ethiopian goats were FROH > 1 Mb values  can disclose the genetic relationships among individuals, estimating with high accuracy the autozygosity at the individual and population levels and can elucidate about selection pressure events . If longb values . Similarb values  with morb values  reportede cattle . Long see cattle . A recene cattle . The lowe cattle .PPP1R36 and Heat Shock Protein A2 (HSPA2)  identified in these communal indigenous goats are involved in heat stress response and, in other studies, HSPA2, DNAJC24, and DNAJC13 are associated with the heat shock family of genes  of South Africa to the eastern areas of KwaZulu-Natal, which confirmed their historical relatedness and coincides with the migration periods of the Bantu nation. The communal-traditional indigenous goat farming system and adaptation to different climatic conditions had an influence on the results in this study. The study deepened the understanding of the conservation status and selection mechanisms of goats in a communal indigenous goat production setting. For effective conservation programs and utilization of South African communal indigenous goat populations, effort should be made to establish a conservation program for the unique genetic resources of indigenous goat populations.The results of this study indicated a greater negative impact of inbreeding in recent times, which is important for planning conservation strategies. It was revealed that the occurrence of high


Columba rupestris) are close to local extinction  in South Korea where a variety of conservation management procedures are urgently required.Hill pigeons , Gurye (GR), and Uiryeong (UR), and domestic pigeons cohabiting with hill pigeon populations. Genetic diversity, pairwise Fst values of the three populations indicated low genetic differentiation. The GH and GR populations were confirmed to lack hybridization, relatively, whereas the UR population was found to exhibit some degrees of hybridization.Hill pigeons that inhabited South Korea were not genetically distinct from Mongolian and Russian populations and showed relatively low genetic diversity compared with other endangered species in Columbidae. The GR population that exhibited the largest population size showed lower genetic diversity, compared to the other populations, although the pairwise To conserve hill pigeons with low genetic diversity and differentiation in South Korea, the conservation process of captive propagation and reintroduction may require artificial gene flows among genetically verified populations in captivity and wildness. The introduction of foreign individuals from surrounding countries is also considered an alternative strategy for maintaining genetic diversity.The online version contains supplementary material available at 10.1007/s13258-021-01212-x. Endangered birds are threatened, and their locally fragmented populations have been decreasing due to numerous factors, including habitat degradation, overexploitation, negative interspecific interaction, and climate change, which have affected their survival and reproduction  has an extremely large range  , which are a closely related species have been found while small numbers inhabited with hill pigeons, resulting in reproduction and resource competition  should also be provided for the reintroduction of species and captive propagation.For the long-term conservation of endangered species, the maintenance of genetic diversity and the determination of meaningful management based on genetic structure are essential . To this end, we verified (1) the genetic diversity in the three wild populations  of South Korea, (2) the genetic distance and differentiation among the three global populations , and (3) the haplotype network among the three populations of hill pigeons and cohabiting domestic pigeons to evaluate the extent of hybridization.C. rupestris, from Goheung , Gurye , and Uiryeong , and C. livia domestica  from the three wild populations. The collected samples were stored at -30 °C before DNA extraction. DNA was extracted using the DNeasy Blood & Tissue Kit  followed by the manufacturer’s protocol. Cytochrome oxidase subunit 1 (COI), cytochrome b (cyt b), and D-loop sequences of the Hill pigeon and Rock pigeon were downloaded from the NCBI database (https://www.ncbi.nlm.nih.gov/)  and Geneious Prime . Although COI has generally been chosen as the standard barcoding marker due to its high interspecific variation, it can also provide clues about ongoing speciation processes and direct attention to species or species complexes , Russia (n = 3), and South Korea (n = 47), which was based on COI sequences. Haplotype diversity (h), nucleotide diversity (π), the number of polymorphic sites (S), and the average number of nucleotide differences (k) were calculated using DNA SP V.6.12.03. The population pairwise genetic distance Fst values and their significance were calculated in Arlequin 3.5.2. using 1,000 permutations of haplotypes among populations used to construct a null distribution for significance testing. Heat maps of the population pairwise Fst values were generated using R statistical software v4.1.0. An analysis of molecular variance (AMOVA) was implemented in Arlequin 3.5.2. to test whether a significant proportion of genetic variation was present. Haplotype network analysis was conducted in PopART 1.7 using a median-joining network.All analyses were based on concatenated cyt b and D-loop sequences , except that of pairwise h = 0.917, Table h of GR was the lowest  in South Korea was 0.874, and the π value was 0.00226 ; the pairwise Fst value of the South Korean and Russian populations was 0.400, but this was non-significant (P = 0.261). The Russian population was genetically distinct from the Mongolian population . Second, the pairwise Fst values of the three populations of hill pigeons in South Korea . The UR population was not significantly different from the GR population (Fst = 0.02); these populations showed a significant relationship but low genetic differentiation (Fst = 0.08). Overall, the results of AMOVA   that is closely related to C. rupestris (reference sequence), formed exclusive clades. All GH and GR individuals appeared in the C. rupestris clade, whereas all LD individuals appeared in the C. livia clade. Most UR individuals appeared in the C. rupestris clade, but 2 individuals labeled as Hap_2 and Hap_6 appeared in the C. livia clade. GR and UR had 4 identical haplotypes, and Haplotype_4 was identified as an identical type possessed by South Korea populations.To evaluate the extent of hybridization in South Korea populations, haplotype relationships were visualized using wild populations (ca) Fig. . C. livih = 0.874; Table C. janthina nitens)  showed an h value of 0.48 (Young and Allard C. janthina) showed an h range of 0.10–0.53 and a π range of 0.0009–0.0023  rule was suggested to offset genetic deterioration Wright . The OMPons Fig. . The Fstion Fig. , and thaC. livia)  Fig. . Thus, wia) Fig. . CompareFst showed that the South Korean populations were not genetically distinct from the Mongolian and Russian populations and the Fst value of the Korean populations showed low genetic differentiation. To increase the number of individuals, considering the enhancement in genetic diversity, a small amount of gene flow among the three populations in South Korea is required. In addition, introduction of Mongolian and Russian populations to make a new population in South Korea will also be a helpful conservation plan to increase the hill pigeon populations. The GH and GR populations were confirmed to be purebred hill pigeons, but the UR population was hybridized. We confirmed the hybridization of the UR population at the population level using mtDNA, but more accurate marker development using nuclear DNA is required.To suggest a conservation management strategy for the endangered hill pigeon populations in South Korea, we verified their genetic structure information using mtDNA. The nucleotide diversity of the South Korean populations indicated lower genetic diversity with respect to other endangered species of the Columbidae family. The GR population may be facing an increasing risk of inbreeding depression due to low genetic diversity. Our results of pairwise Supplementary file1 (DOCX 46 KB)Below is the link to the electronic supplementary material.


Echinostoma revolutum (sensu stricto) is a widely distributed member of the Echinostomatidae, a cosmopolitan family of digenetic trematodes with complex life cycles involving a wide range of definitive hosts, particularly aquatic birds. Integrative taxonomic studies, notably those utilising nad1 barcoding, have been essential in discrimination of E. revolutum (s.s.) within the ‘Echinostoma revolutum’ species complex and investigation of its molecular diversity. No studies, however, have focussed on factors affecting population genetic structure and connectivity of E. revolutum (s.s.) in Eurasia. Here, we used morphology combined with nad1 and cox1 barcoding to determine the occurrence of E. revolutum (s.s.) and its lymnaeid hosts in England for the first time, in addition to other echinostomatid species Echinoparyphium aconiatum, Echinoparyphium recurvatum and Hypoderaeum conoideum. Analysis of genetic diversity in E. revolutum (s.s.) populations across Eurasia demonstrated haplotype sharing and gene flow, probably facilitated by migratory bird hosts. Neutrality and mismatch distribution analyses support possible recent demographic expansion of the Asian population of E. revolutum (s.s.) (nad1 sequences from Bangladesh and Thailand) and stability in European  and Eurasian (combined data sets from Europe and Asia) populations with evidence of sub-population structure and selection processes. This study provides new molecular evidence for a panmictic population of E. revolutum (s.s.) in Eurasia and phylogeographically expands the nad1 database for identification of echinostomatids. The Echinostomatidae is a diverse, widely distributed family of hermaphrodite digenetic trematodes comprising 37 nominal genera, typically characterized by a circumoral collar of spines and a spiny tegument . The aduEchinostoma revolutum’ group has been particularly difficult to resolve [reviewed in 10]. Integrative taxonomic studies utilising morphological and molecular methods have discriminated genetically distinct echinostomatids worldwide  USA. K/θ≥4 confirmed Eurasian E. revolutum (s.s) as a genetically separate species from USA E. revolutum , Radix auricularia, Lymnaea stagnalis and a mixed cluster of Stagnicola fuscus + Stagnicola palustris  infected all four species of snails identified. Echinoparyphium aconiatum was hosted by three species: A. balthica, R. auricularia, L. stagnalis. Echinoparyphium recurvatum and H. conoideum were found in A. balthica and R. auricularia. Prevalence of infection in snails was variable and influenced by low sample sizes due to difficulty in locating snails in some freshwater sites (Echinostomatids infected 8.1% (81/995) of sampled snails. The 81 alustris , S1 Fig.er sites .E. revolutum (s.s.). Many haplotypes were shared between European countries and between Europe and Asia (sub-population 1). The most common haplotype, representing 21/73 E. revolutum (s.s.) sequences, was shared between the UK, Czech Republic, Germany, Iceland, Poland, Thailand and Bangladesh. The haplotype network illustrated a low number of mutations between each haplotype with the majority of haplotypes separated by only 2–5 mutations, indicating high levels of gene flow and/or potential radiation. Furthermore, the haplotype network revealed some evidence of a potential second subpopulation made up of a cluster of unique haplotypes from Finland, Germany, Czech Republic and Bulgaria, separated from the main population by 8–11 mutations. The Mantel test for genetic isolation by distance revealed no significant correlation between genetic and geographical distance between E. revolutum (s.s.) isolates across Europe and Asia   . There wD values were negative for the Eurasia, Europe and Asia nad1 datasets, and were significant (P<0.001) for Eurasia and Europe  but not Asia (P = 0.039). Fu’s Fs was negative and significant across all datasets . These parameters indicate an excess of low frequency haplotypes compared to that expected under neutrality due to historical expansion in the E. revolutum (s.s.) population across Eurasia or selection processes (Tajima’s rocesses .E. revolutum (s.s.) populations in Eurasia and Europe, however, appeared bimodal  and therefore the Eurasian and European populations represent stable populations that have not undergone any major population expansion events; the pattern seen could be caused by selection and/or sub-population structuring. The Asia dataset was characterised by a high frequency of haplotypes and a non-significant raggedness index, suggesting a unimodal distribution  and supporting a hypothesis of population expansion having recently occurred in Asia.The pairwise mismatch distributions for  bimodal . The ragE. revolutum (s.s.) alignments showed that all geographical isolates appeared to be under purifying selection with dN/dS<1 . Owing to low sensitivity of simple alignment based dN/dS ratios, analyses per sequence were performed to identify if individual sequences differed from each other in terms of their content of synonymous and non-synonymous mutations across the Eurasian dataset. Synonymous mutations appeared to have the greatest contribution to p-distance across the data sets with substantially more synonymous mutations than non-synonymous mutations at higher p-distance values i (dN>dS) (E. revolutum (s.s.) sequence data set.Initial analyses of standard dN/dS ratios across the Eurasian, European and Asian e values . The cod (dN>dS) . Signifi (dN>dS) . Provean (dN>dS) . Protter (dN>dS) . The twoE. revolutum (s.s.) in England, in addition to other echinostomatid species Ep. aconiatum, Ep. recurvatum and H. conoideum. Snail host ranges concur with data from previous molecular sampling programmes in Europe [A. balthica and R. auricularia are reported as new hosts for Ep. aconiatum and H. conoideum, respectively. Previous molecular studies on cercariae of trematodes in the UK have reported E. recurvatum from A. balthica, Isthmiophora melis [Echinostoma sp. IG from Planorbis sp. in Wales [Echinostoma revolutum, Ep. recurvatum and H. conoideum are agents of human echinostomiasis [Knowledge of the factors that affect the genetic structure within and among populations of zoonotic parasites and their phylogenetics is important for understanding their ecological and evolutionary processes and has consequences for monitoring of disease and parasite control . Here, wn Europe , 27, 46,ra melis  and Echiin Wales . The echtomiasis , but no nad1 barcoding that there is lack of gene flow between Eurasian E. revolutum (s.s.) and USA E. revolutum and they are, therefore, genetically separate lineages [E. revolutum as a new species when adults are available for examination [E. revolutum (s.s.) has a panmictic population in which genetic mixing occurs across Eurasia, probably due to movement of migratory avian hosts. There was low diversity within and between E. revolutum (s.s.) populations from Europe and Asia and no significant relationship between genetic divergence and geographical distance between isolates as revealed by the Mantel test. Furthermore, the haplotype network analyses illustrated that there were no geographically distinct genetic lineages of E. revolutum (s.s.) with a substantial number of haplotypes being shared not only across Europe, but between European and Asian populations of E. revolutum (s.s.), indicating gene flow. This lack of differentiation between E. revolutum (s.s.) populations most likely reflects the flyways of aquatic avian hosts. Many species of ducks, geese and swans overwinter in Southeast Asia and then migrate to breed in Northern Eurasia, mixing with birds from Europe [Trichobilharzia querquedulae has been demonstrated by lack of phylogenetic structuring between populations [Application of the K/θ species criterion supports previous studies using lineages , 18. Themination . We havem Europe . The impm Europe , 49. Traulations .E. revolutum (s.s.) sequence data sets for Europe and Asia were analysed independently from each other, the European dataset showed the same patterns as the combined Eurasian sequences. Significant negative values for Tajima’s D and Fu’s Fs suggested demographic population expansion, but mismatch distribution analyses supported a stable population. The conflict between the Tajima’s D, Fu’s Fs and raggedness scores can occur as a result of sub-population structuring and/or the presence of selection. The haplotype network analyses indicated the presence of a potential sub-population composed of haplotypes specific to central and northern Europe. Similarly, the codon-based Z test for the detection of selection indicated that the majority of significant differences in dN/dS occurred through comparisons of haplotypes within sub-population 2. This sub-population may be the result of local adaptations in a population of E. revolutum (s.s.) which is resident to central and northern Europe. Although the Eurasian population is panmictic, it could be argued that even with gene flow between countries across Asia and Europe, sub-populations could have emerged as the parasites establish in non-migratory bird and mammal populations. This pattern of local adaptation and emergence of sub-populations has also been observed in other parasites which use migratory animals as hosts. The same trend was seen in populations of Schistosoma turkestanicum with evidence of continued migration and gene flow from Asia, but also local adaptation showing periods of isolation and establishment in local host populations [Interestingly, when ulations .Fs and a unimodal mismatch distribution analysis supported recent expansion of the Asia population. There is no direct evidence to explain this possible demographic change, but there may be a connection between the importance of free grazing ducks as reservoir hosts for echinostomes, including E. revolutum [E. revolutum (s.s.), further intensive sampling of the parasites from an increased number of countries across Eurasia is required with deeper and more extensive genome sequencing, considering genetic signals from multiple genes in the mitochondrial genome and across the nuclear genomes of these parasites [Significant negative values for Fu’s evolutum , and intevolutum . In Thaievolutum , 54. Thearasites .nad1 protein within domains that are exposed to the interior of the mitochondria, indicating the presence of a potential adaptive response. The nad1 is part of the oxidative phosphorylation (OXPHOS) system complex1 of the mitochondria and is the first protein in the electron transport chain. Studies have illustrated adaptation in this gene as an adaptive response in organisms to either cold temperatures, seasonal change or living at different altitudes [S. turkestanicum [Schistosoma indicum group [E. revolutum (s.s.) dataset as central and northern Europe are known to experience cold winters, thus any established populations within these areas would have adapted to local conditions, ultimately giving rise to sub-population 2. Similarly, this may also account for some of the differences seen between the sequences of E. revolutum (s.s.) from the UK and Bangladesh, with some local adaptations to the cooler temperate environments of the UK versus the subtropical monsoon climate of Bangladesh. Although E. revolutum (s.s.) may represent a large interconnected panmictic population in Eurasia, there is some local adaptation occurring potentially as a result of balancing selection despite constant gene flow.The codon-based Z test for positive selection identified the presence of some positive selection associated with comparisons between individual haplotypes between sub-populations 1 and 2 and between haplotypes from UK and Bangladesh. Provean and Protter analyses revealed possible function-altering mutations in the ltitudes –60. Adapstanicum  and withum group , 60. ThiE. revolutum (s.s.) in Eurasia in which genetic flow is probably due to movements of migratory waterfowl. We present evidence for likely recent demographic expansion of E. revolutum (s.s.) in Asia, although the Eurasian population appears to be stable with evidence of sub-population structure and some selection. In addition, we provide novel molecular data on species richness of echinostomatids and their snail hosts in England and phylogeographically expand the nad1 database for identification of echinostomatids. Collectively, the data offer important insights into the molecular epidemiology of E. revolutum (s.s.) in the context of disease dynamics and contribute a valuable framework for further studies into the parasite and factors affecting its distribution.The present study provides new molecular evidence for a panmictic population of the zoonotic parasite S1 FigShaded clades indicate inclusion of newly generated sequences. The scale shows the number of nucleotide substitutions per site between DNA sequences. Species clades shown as collapsed.(TIF)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(DOCX)Click here for additional data file.


The Kurds as an ethnic group are believed to be a combination of earlier Indo-European tribes who migrated and inhabited a mountainous area thousands of years ago. However, as it is difficult to describe the precise history of their origin, it is necessary to investigate their population relationship with other geographical and ethnic groups.Seventeen Short Tandem Repeat markers on the Y chromosome (Y-STR) included in the AmpFLSTR™ Yfiler™ PCR Amplification Kit  were used to type DNA samples from the Sorani  Kurdish population in Sulaymaniyah province. One hundred fifty-seven haplotypes were obtained from 162 unrelated male individuals. The highest and lowest gene diversities were DYS385a/b (GD = 0.848) and DYS392 (GD = 0.392), respectively. The haplotypes were used to predict the most likely haplogroups in the Sulaymaniyah population.Haplogroup prediction indicated predominance (28%) of subclade J2 (44/157) in the Sorani Kurds, northeast of Iraq. The pairwise genetic distance results showed that the Kurdish group clustered along with Asian populations, whereas the furthest countries were Europeans and Africans.The online version contains supplementary material available at 10.1186/s12864-022-09005-6. The Kurds constitute the largest stateless nation in the world , 2. AlthThe origin of the Kurds is uncertain , 9. TradResearchers are interested in using genetic information to extend knowledge about population histories and bio-geographic ancestry , 13. BecThere is little genetic data available about the diversity of the Kurdish population. Furthermore, most previous studies collected DNA samples from Kurds as a single group for comparative analysis , 20. TheThe majority of the haplotypes obtained in this study occur only once. A total number of 157 haplotypes were observed out of 162 samples; only five were shared among 5 individuals. Haplotype data is presented in Table SSeveral variant alleles were observed in different samples Fig. S. DuplicaMicrovariant alleles were observed in the Sorani Kurd males with a total percentage of 15.2% (24/157). Most were obtained at the locus DYS458, with 20 out of the 157 samples (12.7%); three samples were also observed at the locus DYS385a/b (1.9%) and one at the locus DYS19. Most of the microvariant samples (20/24) are predicted to belong to haplogroup J (J1 = 17 and J2 = 3).Twelve samples (7.6%) were observed as mono-allele for the bi-allelic DYS385a/b locus. Several variant alleles were observed in our dataset that migrated outside the range of the allelic ladder of the AmpFLSTR™ Yfiler™ PCR Amplification Kit. The off-ladder alleles were at locus DYS635 allele 27 (three samples), predicted to belong to haplogroup R2-M124; and at locus Y GATA H4 allele 14 (two samples) predicted to belong to haplogroup E1b1b-M35.Y-haplogroups were inferred by using Whit Athey’s Haplogroup Predictor tool (31-haplogroup-2021 version). The major sub-haplogroups of the Sorani Kurd were E1b1b-M35 (16.5%), J1-M267 14%), J2a-M410 (12.7%), G2a-P15 (10.8%), J2a (8.9%), R1a-M17 (7.6%) and R1b-M343 (7%). The haplogroup distributions in the Sorani Kurdish population are shown in Fig. S%, J2a-M4Median-joining Y-STR network was calculated for the Sorani Kurd haplotypes using NETWORK v5.0.1.0 and edited by NETWORK publisher v2.1.1.2 (Fluxus Technology Ltd.). The median-joining calculation was based on Whit Athey’s haplogroup prediction results and six major clusters were obtained from the haplotypes of the present study: J2a, E1b1b, J1, G2a, R1a and R1b Fig. .Fig. 3Mest) were calculated between the studied population and the previously reported populations , Lebanon (Rst = 0.0078), Iraqi Arabs (Rst = 0.008) and Iran (Rst = 0.0084). The furthest populations were Denmark (Rst = 0.1575), Sweden (Rst = 0.1467), Afghanistan (Rst = 0.1136) and Ethiopia (Rst = 0.0951).The haplotypes of the Sorani Kurd were compared to fifteen other population haplotypes using YHRD databases: Iraqi (Arabs), Iran, Qatar, Saudi Arabia, Lebanon, Yemen, Israel, Turkey, Afghanistan, Azerbaijan, Egypt, Ethiopia, Greece, Denmark and Sweden. The population pairwise genetic distances  and DYS458 (0.828) loci. The lowest genetic diversity for the Sorani Kurdish population was DYS392 (0.406). These results are similar to those previously reported for the Iraqi Arab population and Kurdish people in northern Iraq , 19, 20.STR duplicates were confirmed in two individuals at two loci, DYS19 and Y GATA H4. A double allele at locus DYS19 was observed in one sample. Double alleles at the same locus were previously observed in the Iraqi population with the same duplicated alleles  . Other sIn this study, off-ladder alleles were observed at locus DYS635 allele 27 (three samples) and locus Y GATA H4 allele 14 (two samples). However, these off-ladder alleles of the Yfiler kit are present in the allelic ladder of other commercial kits such as a Yfiler™ Plus and PowerPlex® Y23 System . This adY-STR haplogroups were inferred using Whit Athey’s Haplogroup predictor. The samples of the Sorani Kurds were classified into 18 different haplogroups. The major ones (> 10%) were J (42.67%), R (18.47%), E 17.19%) and G (10.83%). The subclades of these haplogroups were J2 28%), E1 (17.19%), R1 (14.64%), J1 (14%), G2 (10.83%) and R2 (3.8%). The results of the present study are in agreement with previous results that the most common haplogroups in the Kurdish population are J and R. Previous studies concluded that the haplogroup J is a common male lineage in West Asia . However% and G  in Iraq, separated from the Kurmanji Kurdish group in the northwest of Iraq on the border with Turkey. In addition, a higher number of population samples were collected than in the previous paternal lineage studies of the Kurdish population , 20, 47,st) revealed significant differences between Sorani Kurds and populations from western Europe and Africa, while similarities were observed with the west and central Asian countries. However, genetic distance results are strongly influenced by the loci number and sample sizes. Increasing the loci numbers will improve the precision estimates of the genetic differences. In addition, larger sample sizes per population can provide more accurate mean values if insufficient loci are available  males. Table S2. Allele frequencies and sample size by locus of the 17-STR loci for the 157 males of the Sorani Kurd. Table S3. Gene diversity (GD), polymorphism information content (PIC), match probability (PM) and power of discrimination (PD) of the Sorani Kurd males. Table S4. Haplogroup distribution in Sorani Kurdish population. Table S5. Sum of squared size difference (Rst) in 15 populations.Additional file 2: Fig. S1. Chart showing match probability and gene diversity for each of the 17 loci in the Sorani Kurdish population. Fig. S2. Variant alleles, duplications and deletions, at different loci in four different individuals. Fig. S3. Chart showing Y-haplogroup distribution in the Sorani Kurdish population. Fig. S4. Multidimensional scaling plots of fifteen different populations based on Rst values.


Fine-scale genetic structure of ethnolinguistically diverse Chinese populations can fill the gap in the missing diversity and evolutionary landscape of East Asians, particularly for anthropologically informed Chinese minorities. Hmong–Mien (HM) people were one of the most significant indigenous populations in South China and Southeast Asia, which were suggested to be the descendants of the ancient Yangtze rice farmers based on linguistic and archeological evidence. However, their deep population history and biological adaptative features remained to be fully characterized.To explore the evolutionary and adaptive characteristics of the Miao people, we genotyped genome-wide SNP data in Guizhou HM-speaking populations and merged it with modern and ancient reference populations via a comprehensive population genetic analysis and evolutionary admixture modeling.The overall genetic admixture landscape of Guizhou Miao showed genetic differentiation between them and other linguistically diverse Guizhou populations. Admixture models further confirmed that Miao people derived their primary ancestry from geographically close Guangxi Gaohuahua people. The estimated identity by descent and effective population size confirmed a plausible population bottleneck, contributing to their unique genetic diversity and population structure patterns. We finally identified several natural selection candidate genes associated with several biological pathways.Guizhou Miao possessed a specific genetic structure and harbored a close genetic relationship with geographically close southern Chinese indigenous populations and Guangxi historical people. Miao people derived their major ancestry from geographically close Guangxi Gaohuahua people and experienced a plausible population bottleneck which contributed to the unique pattern of their genetic diversity and structure. Future ancient DNA from Shijiahe and Qujialing will provide new insights into the origin of the Miao people.The online version contains supplementary material available at 10.1186/s40246-023-00452-0. The complex human admixture history in Eastern Eurasia has resulted in the formation of Mongolic-, Turkic-, and Tungusic-speaking populations in present-day northern East Asia, Sino-Tibetan (ST)-speaking populations across East Asia, Hmong–Mien (HM), Tai–Kadai (TK), Austronesian (AN), and Austroasiatic (AA)-speaking populations in southern East Asia and Southeast Asia. Several comprehensive studies have been conducted to characterize East Asia’s linguistic and genetic history –7. TheseSouthwest China possessed rich archaeological cultures, including the Shijiahe, Qujialing, Daxi cultures and others. Much evidence has linked the origin of HM people and the ancient ancestors of Yangtze Rice farmers. Li et al. conducted a Y-chromosome-based ancient DNA study to explore the genetic relationship between HM-speaking  and geographically close modern and ancient East Asians . Their iResearch on the mystery of HM people and their language family has increased with advances in computational biology and molecular biology techniques. Previous studies have primarily focused on forensic-related autosomal short tandem repeats (STRs), insertion/deletions (Indels), Y-chromosomal, and mitochondrial single nucleotide polymorphisms (SNPs) markers , 22–26. Although there are many studies on the genetic origins, admixture history and biological adaptations of Miao populations, limited genetic studies focused on the fine-scale genetic structure and admixture processes of geographically diverse Guizhou Miao people have been performed, especially complex admixture modeling based on the haplotype information. Guizhou, located on the Yungui Plateau with a high topography in the west and a low topography in the east, is known to be one of the provinces rich in ethnic diversity. Its complex topography has laid the foundation for its ethnic diversity. For example, the Miao people in Congjiang/Nayong/Longli/Duyun County from Guizhou Province are excellent sites for studying and supplementing genetic data of HM-speaking populations. Many villages still preserve the traditional Hmong language and culture, which have not been reported in detail. We collected genetic data from the Guizhou Miao people and conducted deep genomic research, which allowed Miao and other ethnic minorities to benefit from participating in precision medicine and achieve clinical precision treatment . GeneralWe genotyped approximately 669,896 genome-wide SNPs in 67 Miao individuals from four populations   in Guizhou Province Fig. a. We theK = 13, five ancestral components  were found in HM populations  to test mixed signals using all possible ancestral source pairs. LLM produced significant negative Z-values (Z < −3) when combined with the northern sources related to ST , Altaic , and southern sources related to Guizhou aborigines  and Southeast Asian populations  and southern East Asians  or some Guizhou aboriginals (Shui_Duyun and Dong_Congjiang) as two ancestral sources, tests focused on LLM could produce significant negative Z-values  . The studied Miaos showed more allele sharing with geographically close populations compared to the Han_Northern  to analyze whether genetic substructure existed among the four Miao populations  were observed in any pairs of f4, suggesting that the HM populations were genetically homogeneous relative to the northern East Asian, Southeast Asian, and southeast coastal Chinese populations. We observed significant negative Z-values in the f4, indicating that LLM/NYM shared more alleles with Chuanqing_Nayong compared to CJM. And we observed that previously reported Yi and Miao shared more alleles with LLM compared with CJM, as the observed negative values in f4. We also found that Dai shared more alleles with CJM compared to NYM, with significant positive Z-values for f4. These results suggested the existence of a genetic substructure among the four studied HM populations.We performed We further inferred the fine-scale genetic structure of studied HM populations using fineSTRUCTURE Fig. . The PCAf-statistics. We further performed two-way qpAdm models to explore the ancestral composition of our studied Miao people, with southern East Asians as the southern surrogates and ancient northern East Asians as the northern surrogates. We tested two-way admixture models and found that ancestry proportion from the ancient southern populations ranged from 0.864 ± 0.077 in the AR14K-Yiyang model to 0.372 ± 0.036 in the China_YR_LN-Cebuano_Philippines model  and found that Miao people had the most significant ROH values compared with other populations. The estimated IBD fragments in different length ranges showed that Miao people had high genetic communication with each other in the past two thousand years as the more shared IBD in different categories Fig. a–e. The CDK18 gene, which maintains genomic stability [SMYD1 gene associated with hypertrophic cardiomyopathy stability [KCNJ3. We also screened for its overexpression on chromosome 4 related to the cancer gene PALLD [MUC22, PSORS1C1, PSORS1C3, PSORS1C1|PSORS1C2, CDSN|PSORS1C1, CCHCR1, TCF19, KHDRBS2. Among them, PSORS1C1, PSORS1C3, PSORS1C1|PSORS1C2, CDSN|PSORS1C1, and CCHCR1 are genes involved in autoimmune diseases and are expressed in psoriasis, rheumatoid arthritis ankylosing spondylitis [PSORS1C3 is also linked to major depressive disorder suicide [MUC22 is upregulated or downregulated in lung adenocarcinoma and squamous cell carcinoma [TCF19 may act as a susceptibility gene for non-small cell carcinoma in the Chinese populations, interacting with tumor suppressor protein (P53) and playing a role in various metabolic pathways, including cancer and diabetes [KHDRBS2 has a regulatory role in microenvironmental permeability, hereditary retinopathy, and cancer [DLC1) on chromosome 8 [ZNF25, ZNF248, ZNF33BP|ZNF248, ZNF33A) on chromosome 10 [ABCC8) gene on chromosome 11, a variant that causes hereditary diabetes and hyperinsulinemia [SLC15A1, a peptide transporter protein associated with digestion and absorption, on chromosome 13 [NIPA1 gene, which causes neurodegenerative diseases in chromosome 15 [Genetic evidence has identified many biologically adaptive genes or pathways between ethnolinguistically diverse populations. With the increase in initial allele frequencies, adaptive mutations could confer higher immunity in target populations relative to other unexposed populations. More pathogen exposure will inevitably result in more frequent adaptive gene mutations. We screened candidate genes subjected to positive selection using integrated haplotype score (iHS) and cross-population extended haplotype homozygosity (XPEHH). We first computed XPEHH values for the Miaos with the Northern Han Chinese as a reference population and identified selection signatures on chromosomes 1, 2, 4, 6, 8, 10, 11, 13, and 15 , actin filament-based process (GO:0030029), regulation of membrane potential (GO:0042391), regulation of cell morphogenesis (GO:0022604), regulation of cell adhesion (GO:0030155), Neuronal System (R-HSA-112316), metal ion transport (GO:0030001), cell–cell adhesion (GO:0098609), circulatory system process (GO:0003013), cell morphogenesis (GO:0000902), heart development (GO:0007507), positive regulation of locomotion (GO:0040017), NABA CORE MATRISOME (M5884), transmembrane receptor protein tyrosine kinase signaling pathway (GO:0007169), antigen processing and presentation of peptide antigen (GO:0048002), and iHS shows a strong positive selection signal for extracellular matrix organization (R-HSA-1474244), developmental cell growth (GO:0048588), modulation of chemical synaptic transmission (GO:0050804), head development (GO:0060322), regulation of axonogenesis (GO:0050770).We further counted XPEHH values with the southern Han Chinese as the reference group and iHS values of four Miao populations to exploit all potential candidate genes and adaptive pathways Fig. b–e. We sIt is well known that East Asian populations account for one-fifth of the worldwide populations and have high genetic diversity. Although studies on the genetic structure and population admixture history of East Asians have increased significantly in the last two decades, the genetic diversity of East Asian populations has been studied with fewer representative populations compared to European populations. Human genomic studies have promoted a better understanding of the benefit of personal genomics and precision medicine , 50. UndWCH , we are conducting comprehensive genetic screening for the basic background of ethnolinguistically diverse populations. Here, we collected 67 Miao samples from four regions in Guizhou. Our analysis revealed genetic characteristics unique to the HM populations in Guizhou, including the genetic affinity and genetic structure of the studied HM populations with ancient and modern East Asian people as determined by PCA, East Asian-scale ADMIXTURE, and Fst. It showed that our studied HM populations were influenced by north–south gene flow. The tight clustering pattern of HM-speaking populations and the relationship between HM and Gaohuahua people were confirmed by f4-statistics, out-group f3-statistics, shared IBD fragments, and fineSTRUCTURE, and the genetic substructure among studied HM populations was determined by f4-statistics and TreeMix phylogeny.To comprehensively characterize the genetic diversity of East Asians and develop a next-step sampling plan in the genomic cohorts in the 10K_CPGDP  and GSRD100KCDK18, SMYD1, KCNJ3, PALLD, MUC22, PSORS1C1|PSORS1C2, PSORS1C1, CCHCR1, TCF19, PSORS1C3, KHDRBS2, CDSN|PSORS1C1, DLC1, ZNF25, ZNF248, ZNF33BP1|ZNF248, ZNF33A, and ABCC ). More Denisovan ancient adaptive infiltration signals associated with immune function [AGER gene on chromosome 6 , and the RHOH gene on chromosome 4 (3.833187 in rs73808637). Rachel et al. showed that OCA2 and BNC2 are genes that affect the skin pigmentation phenotype [LCT) [ALDH2 and ADH1B are strongly associated with alcohol metabolism [ADH1B gene showed a strong selectivity, reaching a maximum XPEHH score at position rs1229984 on chromosome 4 for 2.7829. The genomic selection processes observed in HM-speaking populations are related to the unique demographic history of Southwest China and the specific living environment of the Yungui Plateau. Therefore, comprehensive sampling and sequencing of the various ethnic groups in Southwest China will help us gain new insights into the genetic landscape of Southwest China and the history of migratory and adaptive changes in HM populations.We defined candidate genes associated with several different biological functions  in the HM populations (function  have beepe [LCT)  gene in tabolism , and we CETP, LDLR, APOE, and ABCA1) were selected in HM populations. Cholesteryl ester transfer protein (CETP)  is a liver-synthesized glycoprotein, and some studies have shown that CETP inhibitors can be used for the prevention and treatment of coronary heart disease and atherosclerosis [LDLR) was selected when using the population from southern East Asia as a reference ; LDLR was selected in the HM populations when using the northern East Asian population as a reference , and LDLR achieves modulation of atherosclerosis by regulating cholesterol homeostasis . ATP-binding cassette subfamily A member 1 (ABCA1) was selected in the HM populations when southern East Asians were used as a reference , and ABCA1 prevents cardiovascular disease by promoting the efflux of intracellular cholesterol and phospholipids, controlling the rate-limiting step of reverse cholesterol transport and by inhibiting inflammation and maintaining lipid homeostasis.Interestingly, we found that genes closely associated with coronary heart disease . We generated three combined datasets that was used in subsequent analysis. The merged HO-based dataset with more present-day reference populations covered 95,342 SNPs variants, and the merged 1240K-based dataset covered 245,627 SNPs variants. We also merged other recently published ancient East Asian people in our analysis [f3-statistics and f4-statistics.We merged our newly generated data of 67 samples with the previously published Human HO and the 1240K datasets from the Allen Ancient DNA Resource (AADR) via the mergeit tool in the EIGENSOFT  with theanalysis , 70, 71.analysis  and usedWe performed three levels of PCA analyses, focusing on the relationship between East and Southeast Asian populations and the HM populations. We used the smartpca program of the EIGENSOFT package  with defK = 2 to K = 10 in bootstrap sequences with different random seeds. We selected the best run based on the highest log-likelihood and used CV values to identify an “optimal” number of clusters. We then used AncestryPainter [We performed ADMIXTURE  based onyPainter  to visuaf3-statistics in the form f3. Target populations with negative f3-values and Z-scores less than − 3 were regarded as mixed populations of two ancestral people related to X and Y. We then evaluated the genetic affinity between studied Miao and other reference populations via the out-group f3-statistics in the form f3.We used the qp3Pop (version 435) package in ADMIXTOOLS software  to evaluf4-statistics with default parameters [f4-statistics in the form f4 to test whether the studied Miao shared more gene flow with the reference1 population compared with the reference2 population or shared more alleles with Reference2 compared with Reference1. A significant negative Z-score smaller than − 3 indicated that the studied Miao shared more alleles with reference2 populations compared with reference1 populations. The f4-statistics in the form f4 were used to test the genetic difference among the studied geographically different Miao.We employed the qpDstat program in ADMIXTOOLS to obtain rameters . We calcTo explore the admixture signatures and fit the potential admixture model with admixture times, we used MALDER to estimate the generations since the admixture events occurred  with theWe used ancient northern East Asians as the northern surrogate of the ancestral source and used southern East Asians as the southern surrogate of the ancestral source to model the formation of studied Miao people via qpAdm . We usedWe phased 1049 genomes from 47 populations with the default parameters using the SHAPEIT software  as well We used ChromoPainter v2  to estimWe generated the ML admixture graph, with the migration events from 1 to 10, through TreeMix to further explore the relationship between the newly studied Miao and modern southern Chinese and Southeast Asian populations .We used the refined IBD  to estimWe used the R package of REHH  to compuAdditional file 1. Table S1. Z-scores of admixture-f3 in the form f3. Table S2. Z-scores of admixture-f3 in the form f3. Table S3. Z-scores of admixture-f3 in the form f3. Table S4. Z-scores of admixture-f3 in the form f3. Table S5. Results of f4-statistics in the form f4. Table S6. Results of f4-statistics in the form f4. Table S7. Results of f4-statistics in the form f4. Table S8. Two-way admixture models for the formation of Miao people. Table S9. Three-way admixture models for the formation of Miao people. Table S10. MALDER results showed the admixture times of Miao people.


Biological and cultural connectedness within the Aegean is also supported by the finding of consanguineous endogamy practiced at high frequencies, unprecedented in the global ancient DNA record. Our results highlight the potential of archaeogenomic approaches in the Aegean for unravelling the interplay of genetic admixture, marital and other cultural practices.The Neolithic and Bronze Ages were highly transformative periods for the genetic history of Europe but for the Aegean—a region fundamental to Europe’s prehistory—the biological dimensions of cultural transitions have been elucidated only to a limited extent so far. We have analysed newly generated genome-wide data from 102 ancient individuals from Crete, the Greek mainland and the Aegean Islands, spanning from the Neolithic to the Iron Age. We found that the early farmers from Crete shared the same ancestry as other contemporaneous Neolithic Aegeans. In contrast, the end of the Neolithic period and the following Early Bronze Age were marked by ‘eastern’ gene flow, which was predominantly of Anatolian origin in Crete. Confirming previous findings for additional Central/Eastern European ancestry in the Greek mainland by the Middle Bronze Age, we additionally show that such genetic signatures appeared in Crete gradually from the seventeenth to twelfth centuries  The authors generate a genome-wide dataset of 102 individuals who lived in Crete, the Greek mainland and the Aegean islands between the Neolithic and the Iron Age, identifying high levels of biological and cultural connectedness within the ancient Aegean. The next major transformation in Aegean prehistory took place during the Early Bronze Age . Complex societies emerged, characterized by sophisticated architecture, metallurgy, sealing systems and the integration of the Aegean in the Bronze Age Eastern Mediterranean networks of exchange. During the late third millennium bc, the Greek mainland witnessed a severe societal breakdown (at the end of Early Helladic II) with lasting impact until the later Middle Helladic period of the early second millennium3. This disruption has been attributed to various factors, among them dramatic climatic changes5 and the arrival of new groups8. Crete does not seem to have suffered a comparable period of decline10. With the emergence of the first palaces during the nineteenth century bc in the Middle Minoan period, the island’s societies transformed into a hitherto unknown sophistication in art, architecture and social practices.The Aegean has long been recognized as a region of major importance for understanding transregional societal transformations between Europe and the Near East. Already during the seventh millennium 11. The competition between rising elites during the Shaft Grave period led to regional conflicts and culminated in the decline of many local dominions on the Greek mainland and possibly a first mainland military expedition to Crete during the fifteenth century12. At the end of this conflict, the palatial period (Late Helladic IIIA-B) started with a few eminent polities centred in Mycenae, Tiryns, Pylos, Athens, Hagios Vasileios in Laconia, Thebes, Orchomenos and Dimini—to name only the most prominent ones15. During this time, the influence on Crete by mainland centres intensified and Cretan resources were systematically exploited with the help of turning key palatial centres and cities like Knossos, Hagia Triada and Chania into outposts for the administration of large parts of the island16. So far, past human migrations in the Aegean were primarily reconstructed on the basis of archaeological and textual evidence but bioarchaeological studies have been adding new information during recent decades22.Only a few centuries later, during the late Middle Bronze Age , the first rich shaft graves of local elites appeared in southern mainland Greece, often displaying Minoan influences23, emphasizing autochthonous developments rather than migration from outside Crete. Subsequent studies generated nuclear aDNA data and showed a common gene pool for the Aegean Neolithic populations, indicating that the southern Greek mainland differed from the northern in its higher genetic affinity to early Holocene populations from the Iran/Caucasus25. Others reported the presence of this ‘eastern’ (Iran/Caucasus-associated) genetic component in both Bronze Age (BA) Cretan (Minoan) and southern Greek mainland (Mycenaean) populations26. However, the last carried additional ancestry linked to the Western Eurasian Steppe herders (WES)28 or Armenia. Recently, Clemente and colleagues expanded the sampling scope of the BA Aegean to the northern mainland and the Aegean Islands corroborating the previous findings but also reporting higher WES-related ancestry in MBA individuals from northern Greece29.Biomolecular approaches based on ancient DNA (aDNA) have been introduced in prehistoric Aegean research during the last decade. The first aDNA study analysed mitochondrial genomes33, whereby it is necessary to acknowledge that relational identities are not determined only through biological kinship34. Most approaches to past kinship in the Aegean were based on morphometric and non-metric analyses35 and first PCR-based studies were unsuccessful36. However, the potential of this line of evidence from the Aegean BA is outstanding due to the richness of collective burials as an expression and constitution of social belonging within local communities37.Recent archaeogenetic studies outside the Aegean have engaged into integrating biological information as elements of the past social organization and structuresn = 6), BA (n = 95), as well as Iron Age contexts  . The remaining individuals from the mainland and the islands are attributed to the Mycenaean culture of the Late Bronze Age (LBA) . Most of the data come from Crete , in a time transect that covers early phases of the Neolithic  and the BA . With the exception of Aposelemis and XAN035 from Chania (about 1700–1450 bc), all other Late Minoan individuals date between about 1400 and 1100 bc (LMII–III). All the analysed skeletal remains from Nea Styra, Mygdalia, BA Aposelemis, Krousonas, Aidonia and Hagios Charalambos belonged to the same within-site collective burial context; for the latter, Yersinia pestis and Salmonella enterica were also recently detected38. Extracted aDNA was immortalized into genomic libraries, part of which were enriched for 1,233,013 ancestry-informative single nucleotide polymorphisms (SNPs) (1240K)   and sequ on modern West Eurasian populations and projected onto the first two PCs the ancient individuals from the Aegean and nearby regions Fig. . The sixf-statistics of the form f4  (Z ≥ 3) on the EBA group from Nea Styra and then prevail for most of the later Aegean BA groups. However, the LBA ones additionally share alleles with contemporaneous or earlier (Mesolithic) populations from Central and Eastern Europe . In addition, evidence of admixture from these groups was confirmed with admixture f3 test   that conf-statistics, we explored formal admixture models using the software qpAdm (bc)—but not earlier—as well as most of the EBA individuals from Euboea, Aegina and Koufonisia. Overall, the genetic heterogeneity among the Late Neolithic (LN) to EBA is not correlated with time alone, since within the Nea Styra grave male individuals carried substantially varying proportions of Iranian-related ancestry. By applying DATES on the LN and EBA individuals from the mainland and the islands (bc (Supplementary Table bc). This variance in admixture dates also corroborates ongoing biological admixing with incoming individuals from the east of the Aegean following the establishment of the first Neolithic Aegean communities.Informed by the re qpAdm . First, re qpAdm . Substan islands , we obtaP < 0.05), highlighting substantial genetic variation among coeval groups. In stark contrast, in Early Middle Bronze Age (EMBA) Crete the rate of non-cladal pairs (25 of 741) was the one expected for true models of cladal pairs to be rejected with a cutoff of 5% given a uniform distribution of the P values.We further evaluated genetic heterogeneity with cladality tests using qpWave , ‘S. Mainland-Islands LN-EBA’ (n = 13) and ‘Crete EMBA’ (n = 29) following a ‘competing’ approach described in previous studies (P = 9.32 × 10−5) ; however this model only became adequate as a three-way with an additional minute component (5%) from ‘W. Iran N’  were more frequent (~10%) and were predominantly driven from specific individuals lying at the two ends of the EBA-LBA cline in the PCA  and several European populations dated between around 3500 and 1000 P ≥ 0.01 cutoff. Therefore, at the moment it is not possible to more closely identify the region(s) from where this genetic affinity was derived. Among the groups of the southern mainland, the estimated coefficients of the WES-related ancestry are overlapping (±1 s.e.) and average to 22.3%  harbour some of the highest amounts. However, within the ancient city of Chania, individuals spanning a short period of about three centuries display the entire range, a pattern consistent with an early phase of mixing between divergent populations.We found various sources ranging from East Europe, to Central and South Europe adequately fitting most models for the LBA Aegean groups. The smaller and heterogeneous sample of BA Bulgarian individuals or BA Sicily did not fit. Models with Serbia (EBA), Croatia (MBA) and Italy (EMBA) were adequate most of the time, while those with ‘W. Eurasian Steppe En-BA’  or some Central European source  were adequate for all groups at the .3% Fig.  but wereP ≤ 5.80 × 10−3), whereas models with Central or Eastern European sources remained adequate. However, two-way models with all of the above sources as well as ‘Mainland MLBA’ fit the allele frequencies of all the LBA individuals from Crete (‘Crete LBA’). This also applied when we modelled the two clusters from LBA Crete separately  carry the R1b1a1b Y haplogroup. The remaining—as well as the EBA/MBA ones—attest to the high prevalence of Y haplogroups J and G/G2  settlement in Mygdalia, a small cist grave was the primary inhumation of at least eight perinatal infants and one of the six child burials under the houses of the settlement  . Due to the low SNP coverage in all the individuals, uniparental markers can neither rule out nor confirm such a pedigree but its high specificity places it as a less likely scenario. Finally, long-term reduction of population size (bottlenecks) can cause lower population heterozygosity and such a signal has been previously reported for instance in hunter-gatherer groups and Cardial Neolithic Iberians52. Individuals from such drifted populations are expected to exhibit shorter ROH (4–8 cM), which are currently not detectable in low-coverage individuals such as APO004. Further supporting this scenario, the inferred heterozygosity (h) within the Aposelemis individuals was also reduced (mean h ≈ 0.1) and close to the expectation when assuming that the average pairwise diversity (P0 ≈ 0.2) represents the diversity of the population and not pairs of close relatives. Summarizing, the current evidence is most consistent with the scenario of the Aposelemis early farmers descending from a small-sized population.Finally, we observe a lowered genetic diversity among the Neolithic Aposelemis individuals, measured by a substantially reduced rate of mismatching alleles between pairs of samples  since the LN but seems more episodic and oriented to populations from the Caucasus. In addition, although Y haplogroups are unresolved, male exogamy should be discussed as a plausible contributing factor to the heterogenous genetic profiles among the male individuals from Nea Styra, in line with evidence from biodistance on a neighbouring site35. Overall, while a more even sampling would be critical, current data seem to support that the eastern gene flow was not symmetric across the Aegean.Subsequently, our findings indicate that the genetic landscape of Crete changed substantially since the early sixth millenium bc could be related to a breakdown of social structures and/or climatic challenges56. The finding of ‘northern’ ancestry in the MBA and LBA populations from the Greek mainland, does not support a large-scale population displacement but the north–south gradient indicates the directionality of this migration and population mingling. Some putatively proximal sources like ‘Serbia EBA’ or ‘Bulgaria BA’ failed to model this ‘incoming’ ancestry in many groups and R1b Y haplogroups were rather infrequent among LBA Aegean groups, all of which points to different migration dynamics in the BA Balkans and Greece, compared to other parts of Central and Western Europe.The disruption of life that is manifested in the Aegean and the Balkans via settlement dislocation during the late third millenium 57, material culture, funerary architecture and burial practices are believed to express innovations with features traditionally ascribed to the Mycenaean culture. On these grounds, an invasion of the island by people from the Greek mainland (around fifteenth century bc) has been proposed but remains highly contested60. While unable to settle this debate decisively, the genetic analyses demonstrate that Cretan populations at larger port cities biologically mixed with populations coming to the island during the course of a few centuries. The presence of individuals with some of the highest WES-related ancestry proportions within LBA Aegean (Crete LBA group C), despite fitting with a scenario that the Greek mainland was the only source of incoming people, it could also suggest that populations from more distant areas  contributed to the Crete LBA transition, a possibility that is supported in the material culture as well63.A more direct demographic connection can be proposed regarding the LBA Cretan and Greek mainland populations. Following an horizon of destructions targeting palatial centres and elite symbols in Crete (Late Minoan IB)All different migrations proposed here  differ in their bioarchaeological evidence, which, therefore, must not be seen as a simple proof of an archaeological hypothesis but as an additional perspective enabling us to unravel the complexity of past mobilities.65. Different social, economic and ecological arguments have been brought forward as underlying reasons, for example, geographic isolation, endemic pathogen stress, integrity of inherited land and so on66. A combination of several factors combined with subsistence-specific needs  might have shaped this practice in the Aegean. However, small population size was probably not a major reason in the Aegean as the reduced short-range ROH shown in our analyses is consistent with larger population sizes. Moreover, cross-cousin unions were practiced in different geographic contexts—on islands of different sizes as well as the Greek mainland and are not evident at some places during the second millennium . Future studies need to further elucidate the factors that were responsible for the emergence, continuity and disappearance of marital practices. So far, the importance of cross-cousin unions in the prehistoric Aegean is unique among the currently available data for prehistoric endogamy, which is otherwise rarely evidenced69. This might indicate different standpoints with respect to marital practices of rural versus urban societies and/or that those were amenable to cultural influences and changed over time. Studying the interplay between past mortuary practices and social structure—including marital or residence rules—from an integrative bioarchaeological perspective has just become possible and future studies will help to refine our understanding of past social belonging.Finally, the evidence for consanguinity adds another layer regarding human mobility and social practices. Since the fundamental work by ref. No statistical methods were applied for the determination of sample size and randomization.The overall burial record from the Aegean Bronze Age is a corpus which underwent specific selection criteria in the past and has been subject to specific modes of preservation and excavation since then . The corpus of samples analysed in this study represents a broad variety of burial contexts  through time and none of the burials would be termed ‘elite’ or ‘outstanding’ in its respective archaeological/historical context. There is also no sampling bias with respect to sex, age or locality of the burials and diverse cultural settings were included .70. The aDNA extraction from most of the bone powder samples was performed with a modified silica-based protocol71. A detailed description of the steps is given in 10.17504/protocols.io.baksicwe. Genomic libraries were prepared from these extracts according to a double-stranded (ds) library protocol72 with an initial step of partial UDG treatment73 (10.17504/protocols.io.bmh6k39e), followed by Illumina dual indexing (10.17504/protocols.io.bakticwn). For a portion of the samples, we used an extraction-to-indexed library protocol supported by an automated liquid-handling system75 which constructs libraries from single-stranded (ss) molecules. From every extract, at least one of the produced libraries was initially sequenced at a low depth (5–10 million reads) on an Illumina HiSeq400 platform with a setup of 50 cycles and paired-end or 75 cycles and single-read sequencing. Raw FastQC files were processed through EAGER pipeline76 for removal of adaptors , which would make sequencing of the whole human genome cost-efficient and doing so could address additional research questions . Only part of the immortalized libraries was used to produce enrichment data. The remaining libraries are permanently stored at the MPI-SHH/EVA laboratory facilities and future studies can use this resource to generate whole-genome data from these libraries.For the purpose of this study, we sampled 385 skeletal elements originally assigned to 357 ancient individuals. Teeth and petrous bones made >95% of the sample corpus but when these elements were missing other parts such as tibia and femora were chosen. All sampling took place in a dedicated aDNA laboratory of MPI-SHH in Jena, following the laboratory’s archived protocols 10.17504/protocols.io.bqebmtan and 10.17504/protocols.io.bdyvi7w6, the latter being an adaptation of a published protocol84, which relies on heterozygosity on polymorphic SNPs on the X chromosome. We previously trimmed bams for terminal damage with trimBam (https://genome.sph.umich.edu/wiki/BamUtil:_trimBam) and reported the method 1 estimation. Finally, we analysed all libraries with schmutzi85 after mapping mitochondrial reads with CircularMapper (v.1.93.5) and removing duplicates76 and downsampling to 30,000 reads. Run modules contDeam and schmutzi estimated endogenous deamination, called an endogenous consensus and, based on this, computed the contamination rate. Ratios of mitochondrial/nuclear DNA that are very high (>200) can be unreliable for mitochondrial contamination estimates86. Therefore, when applicable, we relied on other methods and/or the behaviour of such samples in population genetic analyses.Following the 1240K enrichment, the selected libraries were sequenced at standard ~20 million reads. For the evaluation of the post-1240K capture data, we rerun EAGER and mapDamage with the same settings. We also used the bed file of 1240K SNP positions to estimate on-target endogenous before-and-after 1240K capture and evaluate the performance of the protocol. We used Preseq  and the option randomHaploid, which randomly chooses an allele to represent the genotype at a given SNP position. For the final genotype file, we kept transitions from the masked version and transversions from the original version. We genotyped the pileups from ss-library bams by activating the option singleStrandMode in pileupCaller which filters out forward-mapping reads with a C-T polymorphism and reverse-mapping reads with a G-A polymorphism, thereby effectively removing bias due to damage. Because of the differences in data production between ds and ss libraries, when applicable, we merged such libraries on the genotype level by randomly choosing a non-missing genotype at every position. Individuals with <20,000 SNPs, ≥10% contamination estimate or absence of such estimate were excluded from subsequent analyses. For selected individuals, we run pileupCaller with the option -randomDiploid and calculated within individual heterozygosity as number of ht sites/number of all sites.We extracted genotypes from the pileups of original and trimmed bam files of ds libraries using the tool pileupCaller , to which we added the recently published aDNA data from Italy87 and based our inferences on a subset of the published data older than 2,000 years from across Eurasia. For the merging with the worldwide modern populations on the Human Origins array (~0.5 million SNPs) we kept the intersection of SNPs between the two panels. For downstream analyses we restricted all data to the 22 autosomes.We merged our final dataset with the release of publicly available genotype datasets of ancient and modern individuals (v.50.0)  generated by schmutzi and the software Haplogrep  and projected ancient individuals with the option lsqproject.We performed PCA using the smartpca program from the EIGENSOFT (v.6.01) packagef-statistics using the package ADMIXTOOLS —for X and Test non-African populations—produces high values when X and Test share common drift, f4 tests whether X and Y or Test and Y share more alleles than expected from the null hypothesis . Therefore, f4-statistics under given settings can provide useful hints for admixture and the possible sources. In addition, computation of f4-statistics comes with a framework for block jackknife estimation of Z-scores, which we use for annotation of significant results (|Z| ≥ 3). We also run admixture f3 that tests whether the allele frequencies of population A are intermediate between B and C, with negative value indicating admixture. Using the information from the f-statistics results we built a framework for running tools qpWave and qpAdm from the same package. A detailed description of the machinery behind these tools is provided in ref. f4-statistics that relate a set of reference (right) populations with a set of targets (left) populations. Specifically, qpWave is used to estimate the minimum number of independent gene pools that explain a set of targets from the references. In practice, if two targets are related with the references as one gene pool, then they are cladal (undistinguishable) to the resolution of the references. In qpAdm, which is a derivative of qpWave, this principle is leveraged to model a target population as a mixture of contributions from n source populations. The fit of the full model and the nested simpler models are evaluated and P < 0.05 or 0.01 is generally interpreted as an inadequate explanation of the data. Admixture coefficients outside of the  range are also evidence of a poor fit of the full model. For the comparison of admixture coefficients from different chromosomes, we computed Z = (coefficientA − coefficientX)/√(s.e.A2 + s.e.X2), where A was any of the 22 autosomes, X the sex chromosome X, s.e. the jackknife standard deviation from the qpAdm and applied a significance threshold of Z ≥ 3.We estimated 93. In this approach, candidate source populations are interchanged between the reference (right) and source (left) populations in the qpAdm setting. If the one placed in the right population is a better proxy for the real source than the one tested in the left ones, the model is expected to fit poorly the data .To further discern differences in ancestries and their admixture coefficients by exploring source populations that potentially serve as proxies of the real sources in terms of time, space as well as the archaeological evidence, we applied a ‘competing’ approach described in previous studieshttps://github.com/priyamoorjani/DATES) to test for exponential decay of local ancestry in a source population given two admixing sources. The decay rate is informative about the time since admixture; thus, the method can effectively date recent admixture events. A detailed explanation of the method is provided95. We run the method with standard parameters: in Morgan units binsize = 0.001 and fit of decay curve from 0.0045  to 1 (maxdist) distance bins.We used the software DATES (v.753)  normalized with the pairwise allele differences among unrelated individuals within the population (α), which is by default calculated as the median from the provided dataset. In this way, the method corrects for SNP ascertainment, marker density, genetic drift and inbreeding. An important implication from this formula is that for given α, the P0 for two identical individuals will be α/2 and hence aDNA data from samples belonging to the same individual can be easily detected. The method also calculates P0 on non-overlapping windows of the genome and computes standard errors.For detection of closely related individuals, we applied the method READ97 on the masked versions of bam files with the options -l phred and -g best. This method uses a maximum likelihood framework to infer identical by descent (IBD) on low-coverage DNA sequencing data from genotype likelihoods computed with bcftools. The coefficient of relatedness r is then calculated as k1/2 + k2, with k1 and k2 the probabilities to share one or both alleles IBD, respectively. The method can also distinguish between parent–offspring (k0 = 0) and siblings  and in theory infer relatedness as distant as fifth degree. However, in low-quality data such as aDNA discrepancies from the expected k0, k1, k2 values are common especially for comparisons relying on <10,000 SNPs31.To detect relatives at a more distant degree, we run lcMLkinTo resolve pedigrees that differ in the IBD probabilities , we performed gene imputations with GeneImp v.1.3; ref. ; ref. 3.https://github.com/hringbauer/hapROH), a method designed to analyse low-coverage aDNA data by leveraging linkage disequilibrium from a panel of modern haplotype references. On 1240K data of at least 0.3× coverage, the method can successfully recover ROH longer than 4 cM. In cases of close parental relatedness, which produce long ROH in the offspring, the method can be efficient for detecting very long ROHs at an even lower coverage. Here, we called ROH in 65 of the Aegean samples (including previously published) with >250,000 SNPs. We simulated individual ROH for a given degree of parental relatedness using the software pedsim (https://github.com/williamslab/ped-sim) as described in Supplementary Section We inferred ROH using hapROH . The calibration was done using the datasets IntCal13  and freeze-dried. Collagen was combusted to COl13 ref.  and IntCWe produced all graphs and maps with Rstudio (v.1.1.383), python (v.3.7) and Inkscape (v.0.92.4).Further information on research design is available in the Supplementary InformationSupplementary Note 1: Details on the archaeological background of the human skeletal material analysed for DNA, with embedded Supplementary Figs. 1–35. Note 2: Modelling and dating of genetic admixture. Note 3: Genotype imputations and pedigree reconstruction for Mygdalia individuals, with embedded Supplementary Figs. 36–38.Reporting SummaryPeer Review FileSupplementary Tablesmt) contamination estimates from libraries with nu/mt >200, mt haplogroup assignments with low-quality score (0.65–0.8) and X-contamination estimated from <200 polymorphic positions are annotated in italics. Supplementary Table 14C) dating of 43 samples with calibrated dates presented in 2-sigma range. With few exceptions, the same skeletal element was sampled for aDNA and 14C dating analyses. Samples with <0.5% collagen are typically not analysed as it might alter the 14C ages. The few cases with low collagen are annotated in bold and italics. Supplementary Table f4-statistics of the form  that capture excessive allele sharing of Aegean populations with the Test populations . Published Aegean groups are annotated with an asterisk. Supplementary Table f3. Signals of admixture are detected for LBA Aegean groups with significantly negative f3 values (Z ≥ −3) highlighted in bold. Evidence of admixture of weaker statistical significance (−3 < Z ≤ −2) for the Late Neolithic individuals from Peloponnese is also shown in bold. Published Aegean groups are annotated with an asterisk. Supplementary Table P ≤ 0.01) and/or infeasible coefficients (±1 s.e.) are annotated in italics, whereas those best fitting in bold. Supplementary Table P ≤ 0.01), infeasible coefficients (±1 s.e.), and low number of SNPs  are annotated in italics. Fitting models are annotated in bold, and those including the corresponding local source or one-way from a non-local source are enclosed in rectangles. Published Aegean groups are annotated with an asterisk. Supplementary Table Supplementary Table score 0.6–0.8 and


Schistosoma japonicum. With its great achievement in schistosomiasis control, the government of China has set the goal to eliminate the parasitic disease at the country level by 2030. However, one major challenge is the remaining huge areas of habitats for the intermediate host Oncomelania hupensis. This is further exacerbated by an increasing number of new emerging snail habitats reported each year. Therefore, population genetics on snails in such areas will be useful in evaluation of snail control effect and/or dispersal. We then sampled snails from new emerging habitats in Taicang of Jiangsu, China, a currently S. japonicum non-endemic area from 2014 to 2017, and performed population genetic analyses based on nine microsatellites. Results showed that all snail populations had low genetic diversity, and most genetic variations originated from within snail populations. The estimated effective population size for the 2015 population was infinitive. All snails could be separated into two clusters, and further DIYABC analysis revealed that both the 2016 and the 2017 populations may derive from the 2015, indicating that the 2017 population must have been missed in the field survey performed in 2016. These findings may have implications in development of more practical guidelines for snail monitoring and control.Schistosomiasis is still one of the most significant neglected tropical diseases worldwide, and China is endemic for  Schistosoma japonicum. In the 1950s, more than 11.6 million were infected and millions of people died of the disease [Oncomelania hupensis snails are the sole intermediate host of S. japonicum and the distribution area of the hosts directly determines the epidemic range of the disease [2 investigated for snails, an area of about 2.06 billion m2 of snail habitats were recognized, including 1.17 million m2 of habitats where snails were detected for the first time (hereinafter referred to as newly emerging snail habitats) [Schistosomiasis is a tropical parasitic disease that has imposed a severe burden on public health and socioeconomic development with over 250 million people currently infected all over the world. China is one of the major endemic countries of schistosomiasis, caused by the zoonotic  disease . A recenabitats) ,5), snai2 snail habitats found during 2011–2018 [Jiangsu province, China is in the region along the middle and lower reaches of the Yangtze River. The province was once heavily endemic with schistosomiasis japonica. After more than forty years of successful control, the whole region has reached the criteria for schistosomiasis elimination since 1995 . However011–2018 . Indeed O. hupensis snails on the impact of geographical variation, migrant individuals and population diversification [Microsatellites, known as short tandem repeats or simple sequence repeats, are sensitive neutral markers. Due to their ubiquitous occurrence, high copy numbers, heterozygosity and easy detection, as well as inherent potential for variation , microsafication ,14,15. Hfication . It woulS. japonicum, we still checked all sampled snails for schistosome cercariae in the laboratory following standard protocols of cercarial shedding [Annual field surveys for snails, according to the Chinese national monitoring program, had been performed in all suspected habitats in Taicang city of Jiangsu province, China. New-emerged snail habitats were found each year from 2014 to 2017 along a canal, which is connected to the Yangtze River and runs through the Northeast of Taicang . Snail dTM Mollusc gDNA kit  to extract DNA from each snail according to the manufacturer’s guidelines, and then stored it at −25 °C. Snails were genotyped with nine polymorphic microsatellites [A total of 157 snails, with 38 from 2014, 40 from 2015, 37 from 2016 and 42 from 2017 (hereinafter referred to as four populations) were sampled for molecular analysis. A small fraction of the head-foot muscle of a snail was obtained for DNA extraction. We used an EZgeneIS).Microsatellite data of genotyped snails were exported into an Excel table. The genetic diversity of each population, based on multi-locus, was calculated with GeneAlex 6.5 . The desST values and pairwise Nei genetic distances were calculated with ARLEQUIN 3.0 and GeneAlex 6.5 to estimate genetic difference between populations.The analysis of molecular variance (AMOVA) was performed with ARLEQUIN 3.0  to show To construct the genetic substructure of the four snail populations, a Bayesian multi-locus clustering analysis was run with STRUCTURE 2.3  and the To estimate the effective population size , we useST, and other indicators as summary statistics, and each generated 1,000,000 simulated data sets. Following that, we calculated the Euclidian distance between the observed data set and each simulated data set, which had previously been standardized. We calculated the posterior probability for each scenario and its 95% CIs through a local linear regression procedure [The Approximate Bayesian Computation method was run with DIYABC  to analyrocedure ,35. The IS values were greater than zero, indicating a loss of heterozygosity.As seen in ST values ranged from 0.066 to 0.320 with all p values <0.05. The 2014 population was clearly separated from all other three populations  for the 2015 population. Among the other three populations, the point estimates of Ne varied greatly (from 20.7 in 2016 to 3687.7 in 2017) with NeEst, but not with LDNe (from 43.0 in 2014 to 53.9 in 2016) .With DIYABC analysis the posterior probability for each of the assumed 33 scenarios was calculated and presented in Schistosoma mansoni, population genetic perturbations resulted in a reduced intrapopulation diversity [In this study, the genetic diversities  of snails in new-emerged habitats were generally lower when compared to those in the previously established and persistent snail habitat ,16. For iversity . We predST) observed among the four snail populations was from low  to great (0.320), based on Wright’s criterion [O. hupensis, the 2014 snail population in the new emerging habitat might come from its upper reaches nearby, as Taicang of Jiangsu is connected via several canals to the river and snail dispersal may occur along the waterways [The genetic difference  may not prove logistically feasible or practical, control and removal of the intermediate host snails may be an alternative with the ongoing focus on molluscides and/or environment management. Therefore, our understanding of the genetic characteristics and dispersal potential of O. hupensis in new emerging snail habitats in Taicang of Jiangsu, China may provide a basis for formulating targeted prevention measures, which would exert epidemiological implications for final schistosomiasis elimination across the country [Elimination of a human parasitic disease such as schistosomiasis japonica is challenging, as  country ,46.This study, based on microsatellite analyses, demonstrated that in newly emerging snail habitats in Taicang of Jiangsu, China, all snail populations (from 2014 to 2017) generally had low genetic diversity. The estimated effective population size for the 2015-population was infinitive, whereas those for all other three populations did not vary greatly when computed with LDNe. Four populations of snails could be separated into two clusters, and further DIYABC analysis revealed that both the 2016 and the 2017 populations derived from the 2015, indicating that the 2017 population must have been missed in the field survey performed in 2016.Our study sampled snails from newly emerged snail habitats within a canal in Taicang of Jiangsu, China. The results of population genetic analyses with microsatellites showed a low genetic diversity in all snail populations when compared to persistent populations. For the first time, we did provide genetic evidence that snails had been overlooked in annual field surveys. These findings may have implications in the development of more practical guidelines for local snail monitoring and control.