EDAR were associated with the diversity of facial morphology in XJU. Interestingly, the interaction of functional variants between SLC24A5 and OCA2 likely influences the diversity of skin pigmentation. Notably, selection has seemingly been relaxed or canceled in several genes with significantly biased ancestry, such as HERC2–OCA2. Moreover, signatures of post-admixture adaptation in XJU were identified, including genes related to metabolism (e.g. CYP2D6), digestion (e.g. COL11A1), olfactory perception (e.g. ANO2) and immunity (e.g. HLA). Our results demonstrated population admixture as a driving force, locally or globally, in shaping human genetic and phenotypic diversity as well as in adaptive evolution.Population admixture results in genome-wide combinations of genetic variants derived from different ancestral populations of distinct ancestry, thus providing a unique opportunity for understanding the genetic determinants of phenotypic variation in humans. Here, we used whole-genome sequencing of 92 individuals with high coverage (30–60×) to systematically investigate genomic diversity in the Uyghurs living in Xinjiang, China (XJU), an admixed population of both European-like and East-Asian-like ancestry. The XJU population shows greater genetic diversity, especially a higher proportion of rare variants, compared with their ancestral source populations, corresponding to greater phenotypic diversity of XJU. Admixture-induced functional variants in  Here, we proposed ‘rules of admixture’, which refer to the general consequences of admixture in shaping the genetic variation in the admixed population.The allele frequency (AF) of the admixed population is expected to be the average of those in the ancestral source populations weighted by the global admixture proportions. Analysis of the site frequency spectrum (SFS) of XJU, EAS and EUR populations showed that XJU had an overall frequency profile close to the expected distribution, while the SFS of EAS and EUR were highly diverged  >0.1 . Interestingly, more conserved SNVs showed relatively lower AFde , while intron regions were more likely enriched for SNVs with large AFde  . Analysis of the ancestry-divergent SNVs recorded in the Genome-Wide Association Studies (GWAS) Catalog [LCT–MCM6, SLC45A2 and HERC2 , haplotype diversity (H), number of segregating sites (Kθ) and effective population size (Ne) were higher in XJU than in the reference populations . Principally, divergent ancestral components introduced by admixture can result in a novel ‘mosaic’ genome and a high level of genetic diversity of the admixed population Fig. A. We fouons Fig. C, followtatistic    . The mechanism of admixture-driven genetic diversity of the admixed population was further illustrated by the east–west cline of varying effective population size of regional XJU subgroups (P < 4.86 × 10–2).In addition, we estimated the genetic diversity and effective population size for regional XJU subgroups using the imputed microarray data of ∼1000 XJU individuals with known birthplace information  (MethodsP < 0.03) , suggesting the admixture-driven genetic diversity of the population.To investigate the effects of admixture on functional variants, we compared the individual accumulation of LoF SNVs (high impact) and missense SNVs (moderate impact) representing deleterious mutations among XJU, EAS and EUR (Methods). We found that XJU individuals had the most deleterious SNVs among the three populations and were followed by EAS individuals under the dominant model . In contrast, the number of total deleterious alleles and of homozygotes of XJU individuals are both between EAS and EUR under both the additive and recessive models, while EAS individuals had the most deleterious alleles and homozygotes. These patterns were also observed when the deleteriousness of LoF SNVs and missense SNVs were weighted by their effect size of conservation. The same results were achieved by using all genetic variations, but not only LoF SNVs and missense SNVs, with Combined Annotation-Dependent Depletion (CADD) scores  and the P < 0.05, Wilcoxon rank-sum test) (Tables S4 and S5). For example, pathways related to metabolism, digestion and immunity were identified with higher genetic load in XJU , suggesting their importance in the local adaptation of XJU post admixture in a new environment. The accumulation of deleterious SNVs in these pathways reflected the admixture-driven genetic diversity in XJU, resulting from the deleterious SNVs introduced by genetic admixture.Analysis of pathways from Kyoto Encyclopedia of Genes and Genomes (KEGG) database  revealede of the pathway genes, indicating a potential mechanism of polygenic adaptation.High genetic diversity in XJU is expected to further influence the adaptation of XJU. The high genetic load observed in pathways related to metabolism, digestion and immunity suggested the post-admixture accumulation of deleterious variants in local genetic components; this was further supported by the high AFde. For example, the metabolism pathway ranked at the top of the enrichment with genes of high AFde (BH-corrected P < 9.79 × 10–4) . There were 699 out of a total 1494 (46.8%) genes in the metabolism pathway that were identified as leading-edge genes, i.e. genes that led to the maximum enrichment score of the corresponding pathway. Among the 699 leading-edge genes, some genes showed significant EAS-biased ancestry (n = 16) and EUR-biased ancestry (n = 11) based on local ancestry inference. For example, FUCA2 (6q24.2) , coding an exoglycosidase and related to glycan degradation, was of 65% EAS ancestry which is much higher than the genome-wide average . A EUR-biased example is FHIT (3p14.2), related to the purine metabolism, which is of only 36% EAS ancestry . Notably, the derived allele frequency (DAF) of the missense variant rs6446104 at FHIT in XJU (0.522) was lower than that of both EAS (0.592) and EUR (0.566). The signature of a selective sweep on FHIT was also identified in XJU by comparing the extended haplotype homozygosity (EHH) between XJU and EUR (Methods), and a significantly higher genetic load at FHIT was observed in XJU compared with the reference populations (Table S5).We applied a modified method based on Gene Set Enrichment Analysis (mGSEA)  , which encodes components of type XI collagen and is associated with the structure and strength of muscle and skin, was identified with signatures of selection in XJU based on both within- and between-population methods . Higher allele sharing was observed between XJU and EAS at the missense variant rs11164663. The haplotype carrying the derived allele (DA) has nearly been lost in XJU (0.016), and this deviated from expectation based on the DA in EAS (0.034) and EUR (0.101). Interestingly, previous studies reported that the DA of rs11164663 is associated with a lower gene expression level of COL11A1, and this may be related to some phenotypic variation of muscle and skin in XJU and EAS [Moreover, genes in pathways including ‘amino acid metabolism’, ‘lipid metabolism’ and ‘protein digestion and absorption’ were also identified with high AFd and EAS .PharmaADME (http://www.pharmaadme.org/). We observed enrichment of genes with high AFde (BH-corrected P < 1.97 × 10–3) . A total of 157 out of the 283 core/extended ADME genes (55.5%) were identified as leading-edge genes. Frequency profile analysis of the core variants in the leading-edge genes indicated relatively low AFde and small effects of individual ADME genes, suggesting the polygenic adaptation of the metabolism-related pathways in the post-admixture adaptation of XJU. Interestingly, there were two variants of CYP2D6 (22q13.2), rs1065852 (CYP2D6*10) and rs1080985, ranking among the top 0.5% for their high AFde. CYP2D6 is preferentially expressed in the liver [CYP2D6  is another missense variant that may contribute to the decreased metabolic ratio [The mGSEA approach was further applied to the genes related to absorption, distribution, metabolism, and excretion (ADME) from he liver  and beloCYP2D6 was observed in XJU; this enzyme is responsible for the metabolism and elimination of ∼25% of commonly prescribed drugs [CYP2C19 based on the frequency profiles of the core variant, i.e. rs4986893, which is also a liver enzyme and processes ∼10% of drugs, including clopidogrel, according to MedlinePlus (https://medlineplus.gov/).In particular, the cytochromes P450 (CYPs) are important for the oxidization and clearance of various compounds in the human body, including clinically used drugs. The genetic basis of the metabolic activities in XJU was determined by both admixture of the divergent genetic components and post-admixture adaptation, meaning that the dose of a drug should be adjusted to take into account the individual's unique metabolism. Decreased metabolic activity of ed drugs . DecreasEDAR (2q12.3) [LIMS1 (2q12.3) [EDAR is well known for its association with hair thickness [The early contacts of Eurasian populations shaped the phenotypic diversity of the admixed populations in Northwest China during the Bronze Age . Archaeo(2q12.3)  and rs18(2q12.3)  that arehickness ,35, ear hickness , incisorhickness  and sweahickness ,38 in EaEDAR is an admixture-representative (AR) gene (∼47% EAS ancestry) in XJU, as those genes follow the ‘rules of admixture’ and their local ancestry is consistent with the global ancestry estimated from genome-wide data. The AR component was identified by the estimator of population branch statistic (PBS) [EDAR in XJU clustered into two major groups in a network analysis [EDAR had DAF values of 0.418, 0.937 and 0 in XJU, EAS and EUR, respectively [Our analysis confirmed that ic (PBS)  . However, no signature of natural selection was detected in XJU, as was also proposed in a previous study [EDAR. Selection relaxation in XJU was further confirmed by comparison between the EAS population and the ancestral EAS population (aEAS) reconstructed from the inferred EAS-ancestry components in XJU . High AFde along the region related to EDAR was observed between EAS and aEAS, suggesting the post-admixture differentiation of EAS-ancestry components between EAS and XJU as well as the relaxation of selection in XJU.A strong selection signal was found for us study , indicatLIMS1 (2q12.3), PCDH7 (4p15.1), DCHS2 (4q31.3), COL23A1 (5q35.3), SUPT3H-RUNX2 (6p21.1) and GLI3 (7p14.1) were all significantly associated with geographic location; each of the above genes has been reported to be associated with the facial morphology in XJU [Other genes related to the facial morphology of XJU were also investigated. The frequency profiles of y in XJU ,44 , ALDH2 (12q24.12) and the AGO gene cluster (1p34.3)  . ADH1B and ALDH2 may be responsible for alcoholism protection in Asian populations [AGO gene cluster is related to RNA interference and silencing [Apart from the functional components related to facial morphology, AR components related to other biological functions were identified, including ulations ,46, and ilencing .SLC24A5 (15q21.1) [OCA2 (15q13.1) [Light skin pigmentation in Eurasian populations has been considered to be the result of convergent evolution during out-of-Africa dispersal. The key components related to skin pigmentation across Eurasian populations were confirmed by GWAS and by experiments on model animals. The identified genetic components include 15q21.1) –50 and O15q13.1) –53, whic15q13.1) .SLC24A5 was identified as an AR component in XJU with ∼44% EAS ancestry. Both frequency profiles of the key variant rs1426654 and the haplotype network of SLC24A5 also revealed the balanced contributions from EAS and EUR ancestries . Similar to EDAR, a significant correlation between DAF and the geographic coordinate was also observed for SLC24A5 . Another AR component mapped to SLC12A1 (15q21.1) was located ∼50 Kb downstream of SLC24A5, and the intron variant rs11636073 of SLC12A1 is associated with the pigmentation in EUR populations [r2 = 0.3 in XJU. Accordingly, signatures of selection were detected in the SLC24A5–SLC12A1 region based on within-population analysis in XJU and cross-population analysis between XJU and EAS . Interestingly, we observed even higher EHH in XJU than in EUR . Accordingly, relatively lower genetic diversity was also estimated in XJU compared with EAS  .ulations . The linHERC2–OCA2, which had high EAS ancestry  . The key variant rs12913832 in HERC2, associated with eye pigmentation in EUR populations [OCA2 were associated with skin color in EAS [HERC2–OCA2 was relatively weak (r2 < 0.03) in all three populations. The DAF distributions of both rs1800414 and rs74653330 were slightly biased, i.e. the DAF of rs1800414 was 0.147 in XJU, 0.592 in EAS and 0 in EUR, while the values were 0.076, 0.019 and 0.005 at rs74653330 in XJU, EAS and EUR, respectively. Although the ancestry make-up of HERC2–OCA2 in XJU was biased towards EAS, the DAF profile at the key variants revealed relatively low allele sharing between XJU and EAS. This was likely due to the relaxation of selection post admixture. The onset of selection on rs1800414 was dated back 15 000 years [SLC24A5 and the expression level of OCA2 . However, this pattern was not found in HERC2, indicating the differences between HERC2 and OCA2 in XJU for both AF and expression profiles. This may suggest a new mechanism of local adaptation in the admixed population due to the combination of divergent genetic components with similar biological functions.An ancestry-biased (AB) component (Methods) was identified in the region of ulations ,57, showulations . Polymorr in EAS –53. The 00 years , and a hHLA) as well as the sensory perception of smell, e.g. OR10V1 (11q12.1) and OR10D3 (11q24.2). There were two LoF/missense variants, rs499037 and rs2466584, in OR10V1 and OR10D3, respectively, with frequency profiles significantly biased toward the EAS ancestry. The DAF of rs499037 in XJU (0.060) is higher than that in both EAS (0.029) and EUR (0); similarly, the DAF of rs2466584 in XJU (0.266) was also higher than in both EAS (0.150) and EUR (0.111). The observation of the highest DAF in XJU compared with the reference populations suggested admixture gain of the functional components and post-admixture local adaptation.Enrichment analysis was conducted for genetic components identified with either EAS- or EUR-biased ancestry. Gene ontology (GO)  and KEGGOR8U1 (11q12.1) and ANO2 (12p13.31)  was biased toward EAS (0.641) and was much higher than that in EUR (0.369), indicating the large differentiation between XJU and EUR.Enrichment of ancestry-biased components for genes related to sensory and immune systems indicated the shared driving forces between XJU and the ancestral populations, and these genetic components may play important roles in the local adaptation of XJU. The enrichment of the EAS-biased components for pathway genes related to olfactory perception could be confirmed by the differentiation between the contemporary EUR population and the ancestral EUR population (aEUR) that was reconstructed from the inferred EUR-ancestry components in XJU . Genetic components that were highly differentiated between EUR and aEUR were also enriched toward olfactory receptor (OR) genes (Table S9), e.g. 31) Fig. E. The DAMany OR genes identified as having biased ancestry in our study are physically close to each other. A large cluster of OR genes is located downstream of the centromere of chromosome 11 (chr11: 55350000–59600000), while some of them are associated with the variation in human olfactory perception of particular volatile chemicals ,62. UsinBoth OR genes and immune-related genes had the highest levels of genetic variability across the genome . This co 000 YBP between modern humans and archaic populations may have provided selective advantages, such as the high-altitude adaptation [It has been suggested that ancient admixture ∼40aptation ,66. Otheaptation  and Latiaptation , which aWe investigated the ‘rules of admixture’, i.e. how admixture shapes genome-wide variation in the admixed population. It is expected that admixture on large spatial and temporal scales results in high levels of genetic diversity in the admixed population, due to the genetic components contributed by all the ancestral populations, including both common and rare variants Fig. A. In linIn our data, the majority of genetic components of the admixed population follow the ‘rules of admixture’ and this pattern can be well explained by the ancestral populations. In contrast, local adaptation would result in ancestry-biased local genetic components Fig. A. The adOCA2 in XJU that may be associated with the potential interaction of pigmentation-related genes inherited from distinct ancestries, e.g. SLC24A5. Population admixture provided a unique opportunity to study genetic components of divergent ancestry with similar or different biological functions in the same genome. In addition, the admixture gain of genetic components related to immunity and olfactory perception from EAS ancestry indicates the local adaptation of XJU. Both the high genetic diversity and accumulation of mutations in pathways related to metabolism and immunity indicate the potential mechanism of polygenic adaptation post admixture. Both the combination of ancestry-specific genetic components and enrichment of functional components in an admixed population provides new insights into the impact of admixture in human micro-evolution. Driving forces from both the external environment and potentially the compatibility of the admixed genome would further influence the genetic variation present in the admixed genome. We expect that our findings will advance the understanding of admixed genomes, and the results in this study should facilitate further studies of other admixed populations.A genome-wide scan of the genetic components in XJU revealed that local ancestral components may have had different fates due to their biological properties in both ancestral and admixed populations. For example, EAS-biased local ancestry along with low derived allele sharing indicates the relaxation of selection on Peripheral blood samples of 92 Uyghur individuals were collected from nine prefectures  and one prefecture-level city (Urumqi) in the Xinjiang Uyghur Autonomous Region, China. The individuals enrolled in this study were randomly chosen, with sample sizes roughly balanced across all regions. Each individual was the offspring of a non-consanguineous marriage of members of the same nationality within three generations.All procedures performed in studies involving human participants were approved by the Biomedical Research Ethics Committee of Shanghai Institutes for Biological Sciences (no. ER-SIBS-261408), and were in accordance with the 1964 Helsinki Declaration, its later amendments or comparable ethical standards. Informed consent was obtained from all individual participants included in the study. The personal identifiers of all samples, if any existed, were stripped off before sequencing and analysis.Whole-genome sequencing, with high target coverage (30–60×) for 150 bp paired-end reads, was carried out on an Illumina HiSeq X Ten platform according to Illumina-provided protocols with standard library preparation at WuXi NextCODE (Shanghai). Each sample was run on a unique lane with at least 90 GB of data that had passed filtering, and read data were quality controlled so that 80% of the bases achieved at least a base quality score of 30. Reads were merged, adaptors were trimmed and sequences were mapped to the human reference genome (GRCh37) using the Burrows-Wheeler Aligner . Variante from the genome-wide variation of XJU was quantified based on the difference between the observed allele frequencies (AFobs) and those expected (AFexp) in XJU. The genetic diversity was estimated using various statistics, including nucleotide diversity (πθ), haplotype diversity (H), numbers of segregating sites (Kθ), the proportion of rare SNVs (AF < 0.05), Tajima's D [Ne). Genetic load was estimated based on the SNVs of ‘high’ and ‘moderate’ impact as annotated by VEP (version 96) [We applied ADMIXTURE  to the mjima's D  and effesion 96) . The locsion 96) . Gene Sesion 96)  was modision 96) . We applsion 96)  as an ession 96) , cross-psion 96) , H12 [73sion 96) . Detailehttps://www.biosino.org/node) with the accession number OEP001377. Software for calculating genetic diversity is available at https://github.com/Shuhua-Group/Theta_D_H.Est/. Software for merging the replicates of ADMIXTURE analysis is available at https://github.com/Shuhua-Group/ADMIXTURE.merge/.Genome data of 92 Xinjiang Uygur samples are available at NODE (nwab124_Supplemental_FileClick here for additional data file.


Genetic diversity in wildlife is a matter of growing concern in contexts related to disease transmission and human health. Tuberculosis is a zoonotic disease with relevant consequences and can present high prevalence in wild boar and red deer populations. Here, we review studies on the genetic diversity of ungulates, wild boar, and red deer, and assess to what extent these studies consider its importance in the spread of disease. The relationship between host genetic diversity and the probability of disease spread is illustrated in Spanish populations of wild boar and red deer.Sus scrofa) and red deer (Cervus elaphus) are important zoonotic hosts that can be precursors to disease emergence and spread in humans. Tuberculosis is a zoonotic disease with relevant consequences and can present high prevalence in wild boar and red deer populations. Here, we review studies on the genetic diversity of ungulates and determine to what extent these studies consider its importance on the spread of disease. This assessment also focused on wild boar, red deer, and tuberculosis. We found a disconnection between studies treating genetic diversity and those dealing with infectious diseases. Contrarily, genetic diversity studies in ungulates are mainly concerned with conservation. Despite the existing disconnection between studies on genetic diversity and studies on disease emergence and spread, the knowledge gathered in each discipline can be applied to the other. The bidirectional applications are illustrated in wild boar and red deer populations from Spain, where TB is an important threat for wildlife, livestock, and humans.Host genetic diversity tends to limit disease spread in nature and buffers populations against epidemics. Genetic diversity in wildlife is expected to receive increasing attention in contexts related to disease transmission and human health. Ungulates such as wild boar ( Genetic diversity favors population conservation and individual survival. At population level, loss of genetic variation compromises evolutionary response to environmental change ,2,3. At Most human infectious diseases originate from animals ,12,13,14A positive relationship between host genetic diversity of genetic markers and pathogen resistance (heterozygosity–fitness correlation) has been detected in different species ,30,31,32Studies on the relationship between diversity of immune genes and pathogen resistance have focused on the major histocompatibility complex (MHC). MHC genes drive the adaptive immune response, and their diversity promotes the number of pathogens recognized ,36. DiveMicrotus agrestis). Amino acid variation in the prion protein gene has been related to the probability of infection with chronic wasting disease and its progression following infection [Capra ibex) affect Brucella infection status. Despite the fact that MHC genes have been the focus of considerable research ,42, theynfection ,45. Quémnfection  have recDue to its relationship with pathogen resistance, host genetic diversity reduces pathogen prevalence, rate of pathogen adaptation to host, and pathogen virulence ,49,50,51Patterns of genetic diversity have been broadly studied in population conservation contexts ,57,58,59Throughout generations, interactions with pathogens produce evolutionary changes in host populations ,72. In aMate choice is a behavioral process highly influenced by the action of pathogens. For instance, individuals can avoid infected mates to reduce pathogen transmission ,78,79. HStudies have also investigated the effects of infectious diseases on dispersal behavior that, in turn, influence the genetic structure of populations ,89. DemoPathogen–host coevolutionary dynamics may be characterized by fluctuating selection (FS), where host genotypes may be at any moment more resistant to contemporary, compared to past or future pathogens, or by arms races (AR), where both hosts and pathogens tend to increase resistance/infectivity over time . The FS These coevolutionary dynamics can obviously be affected by human management of populations and environments (see below), but also might have effects on the interaction between dispersal and mating behavior. Since spatial variation causes the evolution of locally adaptive immunity, individuals might tend to reduce the contact or refuse mating with genetically different conspecifics harboring dangerous pathogens ,94. GeneMany human infectious diseases originate from mammals ,96. AmonGenetic diversity of ungulates is being altered by human-mediated processes acting on gene flow or effective size of populations. Due to hunting, competition with livestock, and lost habitat, many ungulates occur in small or bottleneck populations ,107. AntDespite human-mediated alterations of gene flows and effective population sizes, studies addressing genetic diversity of ungulate populations focus primarily on conservation prospects, rather than on its effects on disease emergence and spread . The seaMycobacterium tuberculosis complex  is a zoonotic infectious disease that affects domestic ungulates and a wide range of wild animals, but it can also be transmitted to humans ,140. Becex MTBC ,144). My. MyMycobservoirs . Additiothe MTBC ,146,147 the MTBC . M. bovis and M. caprae have been detected in humans [Mycobacterium bacilli, mainly wild boar and red deer [The relevance of the triad wild boar, red deer, and tuberculosis can be illustrated by the situation in Spanish populations. In Spain, TB caused by n humans ,150, andn humans . This hired deer ,156,157.red deer ,158,159.M. bovis infection and modulates TB progression in wild boar [Genetic diversity of wild boar and red deer populations influences both susceptibilities to TB infection and risk of disease progression. Genetic diversity confers significant resistance to ild boar ,161. Genild boar . These sild boar ,163 and ild boar ,117,120.ild boar ,160,161,ild boar ,163. Sciild boar ,142. AutDespite the existing disconnection between studies on genetic diversity and those on the emergence and spread of diseases, the knowledge gathered in each discipline can be applied to the other. Current knowledge regarding factors affecting genetic diversity can be used by managers to fight the spread of disease. Factors that tend to reduce genetic diversity of wildlife present challenges for controlling the prevalence and transmission of infectious diseases. On the other hand, the evolutionary context of disease emergence and transmission might help to understand processes related to genetic diversity. Hereinafter, we will illustrate bidirectional applications in wild boar and red deer populations in Spain, where TB is an important threat for wildlife, livestock, and humans. These applications might be extrapolated to other populations, mainly to those with similar environmental and management conditions. Wild boar and red deer are important game species in Spain, where most populations are in private hunting estates . In these private estates, wild boar and red deer can coexist with other wild ungulates, such as fallow deer, or domestic ungulates, such as cattle ,164. DifA management action, presumably affecting genetic diversity, is the placement of high perimetral fences around the estates to maintain wild ungulates inside the owned land ,170,171.To our knowledge, there is no study showing lower levels of genetic diversity of wild boar populations located in fenced and open estates. Additionally, studies comparing red deer populations in open and fenced estates have found that there are not differences in genetic diversity between both types of estates ,168,169.Translocations are relatively common actions in ungulates’ management, mainly to reinforce (or ‘improve’) existing populations or (re)introduce new populations ,177. OwnIn open estates, migration tends to avoid loss of genetic diversity. Wild boar and red deer can move along large distances. Dispersal distances bigger than 50 km have been found for both species ,188. HowIn addition to fences and population structure, landscape might also influence dispersal and gene flow in wild boar and red deer. Wild boars have high abilities to surpass barriers  and theiIn addition to processes related to dispersal, game management affects the mating system of Spanish red deer and wild boar populations. Altered red deer population structures in open estates with mostly young males and female-biased sex ratios cause a decrease in male mate competition during the rut . On the Another mating system related behavior that can be affected by game management is dissimilar mating. Red deer females tend to mate with genetically dissimilar males, predominantly when they produce daughters . This reInbreeding depression is an important selective pressure affecting behavioral processes related to mating system ,195. TheIn wild boar, mating system related processes affecting genetic diversity have been found. Firstly, multiple paternity  tends to maintain genetic diversity ,197 and Finally, dissimilar mating has been also assessed for wild boar, but it has not been found. On the contrary, offspring genetic diversity tends to be lower than that expected under random mating . This re-Isolated wild boar and red deer populations are potentially dangerous populations.-When translocations are unavoidable, managers should select individuals from populations that occur nearby, in similar habitats, and with low genetic divergence.-Mainly in red deer, the continuity of vegetation refuges should be maintained to facilitate individual movements between distant areas.-Mainly in red deer, sex ratios and male age structures should be equilibrated to favor the natural dispersal of males and the action of evolutionary processes related to the mating system and effective population size.-In wild boar, the decrease in contact between wild boar and domestic pigs might reduce the selective pressures boosting outbreeding avoidance.Studies on genetic diversity of wild boar and red deer populations may yield conclusions applicable by wildlife managers to confront TB. Some recommendations might be summarized as follows: In central and southwestern Spain, red deer and wild boar coexist in the same habitat and share resources. TB affects both species in which high prevalence and mortality rates have been detected ,204,205.When inbred individuals or those with lower levels of genetic diversity have lower fitness, the dissimilar mating of red deer is expected ,195, butLow precipitation and high temperatures during summer have important consequences on resource availability of the Spanish Mediterranean ecosystem ,207. DurRed deer also uses water points to drink, wallow, or brush. Mating behavior in red deer may also take place near these locations ,211, whiHigh rates of pathogen excretion and the sharing of behaviors, natural cycles, and ecological niche of all individuals of the same species can make wild boar present high levels of contact with pathogens. Accordingly, the prevalence of TB in wild boar populations tends to be higher than that in other ungulates, including red deer ,204,212.The high exposure of wild boar populations to TB may have evolutionary consequences. For instance, wild boar is expected to present high levels of disease resistance and tolerance. Accordingly, studies show higher levels of TB resistance in wild boar than in red deer ; infecteDue to the existence of inbreeding depression ,161, genIn wild boar, the outcome of the trade-off regarding mating with genetically dissimilar or similar individuals might depend on the prevalence of infectious diseases, such as TB , and thi


Prunus microcarpa Boiss. is usually found in dry calcareous and rocky mountain slopes and is well adapted to severe winter and dry-hot summer conditions. Morphological and pomological diversity among 81 accessions of P. microcarpa species selected from natural habitats was assessed.The accessions investigated were significantly different from each other in terms of the traits recorded. Tree growth habit was highly variable, including weeping, spreading, open, semi-erect, and erect. Most of the accessions had very small leaves, a probable adaptation to the xerophytic conditions. Ripening date ranged from mid-June to early August. Fruit weight as the first character considering in domestication process ranged from 0.21 to 0.44 g. Principal component analysis (PCA) could describe the evaluated traits as the 11 main components that were able to justify 76.29% of total variance. Also, the accessions were clustered into two major clusters by the Ward dendrogram.P. microcarpa germplasm that reflected the necessity for the conservation of this germplasm, and it is expected that the results gained in this study will assist current Cerasus breeding efforts and will maintain the genetic integrity of P. microcarpa.Significant diversity was revealed, regarding the morphological traits in the evaluated The online version contains supplementary material available at 10.1186/s12870-022-03572-2. Forest trees have hard and long-lasting organisms that thrive in the diverse environments in terms of time and space. Also, such trees are always exposed to various environmental stresses that result from human activities such as pollution, climate change, and habitat fragmentation. To survive these risks and threats, as well as long-term resistance, these plants need to have adaptive potential, which is largely determined by intraspecific genetic diversity –3. ReseaPrunus species is highly variable and is related to several factors such as self-fertility or self-sterility, as well as whether it is domesticated or wild. Genetic diversity within a domesticated species is typically less, thus limiting the distribution and production of Prunus in specific areas and environmental conditions [Prunus is usually low, the use of wild genetic resources is an important way to achieve breeding goals. Also, it is better to use the available gene pool [Prunus microcarpa Boiss. is one of the wild stone fruits that is a suitable choice for research. This species is commonly found in rocky and dry mountains at altitudes of 400 to 1800 m and has a very high adaptation with hot summers and cold winters. This species is an important part of the forest along with the resistant species such as oak. Today, most of the natural forests of P. microcarpa have been destroyed, and its populations are increasingly declining. Although this plant has a very high resistance to various conditions, but uncontrolled human activities as well as animal stress have caused genetic erosion and this has reduced its diversity [Genetic diversity in nditions . Becauseene pool . Prunus iversity .Cerasus subgenus has been performed in some countries and has had significant results [Evaluation of phenotypic structure and diversity is important for determining important traits as well as germplasm collection and level of genetic variation within a species , 11. Mor results –17.Cerasus germplasm in Iran is under threat due to habitat limitations, diseases, pests, reduced natural regeneration, competition with other species, climate change, pollution, and deforestation. In the present study, phenotypic diversity of wild P. microcarpa in the important areas of its distribution in northern and central Iran was studied using morphological traits. The information obtained can be used to establish preservation strategies as well as breeding programs.Genetic diversity of P. microcarpa species selected from natural habitats of Isfahan, Mazandaran, and Azerbaijan-e-Gharbi provinces, Iran was assessed. We have permission to collect P. microcarpa from Agricultural and Natural Resources, Iran. The plants (either cultivated or wild) including the collection of plant material, are complied with relevant institutional, national, and international guidelines and legislation. The appropriate distances were considered between the accessions in each collection site to avoid the possibility of sampling and collecting clones of the selected accessions. Geographical coordinates and altitude corresponding to surveyed areas are presented in Table Morphological and pomological diversity among 81 accessions of wild In total, 41 morphological and pomological variables were applied to investigate phenotypic variability among the accessions selected Table . MorpholAnalysis of variance (ANOVA) was performed to evaluate the variation among accessions based on the traits measured using SAS software . Simple The accessions investigated were significantly different from each other in terms of the traits recorded. The CV ranged from 8.33 (in stone thickness) to 131.35% (in young shoot spine). Out of 41 characters measured, the CV in six characters was less than 20.00%, while it was more than 20.00% in 35 characters, and it was more than 50.00% in nine traits , spreading 12), open (21), semi-erect (17), and erect 13). Tree growth vigor, tree height, branching, branch density, branch flexibility, trunk diameter, and canopy density were predominantly moderate. Lanceolate leaf shape was predominant (66 accessions), while leaf apex shape was predominantly blate (70 accessions) , cordate 34), and elongate (39). Fruit color showed strong variability, including yellow-orange (2 accessions), orange (8), light red (5), red (8), red–black (16), purple-black (20), and black 22). Also, high diversity was observed in terms of fruit flesh color, ranging from yellow to brown. Fruit taste was highly variable, including bitter (29), very astringent (3), astringent (35), astringent-sweet (7), sweet (5), and sour–sweet (2) , ovate (54), oval (11), and stick (5). The range of fruit stone-related traits was as follows: stone length: 5.43–9.62 mm, stone width: 4.12–6.32 mm, stone thickness: 3.75–5.32 mm, and stone weight: 0.05–0.18 g. Mohammadi et al.  reported1, ovate r = 0.69) and agreed with previous work in Cerasus [r = 0.65) and fruit width (r = 0.66) and agreed with previous work in Cerasus [Significant positive or negative correlations were observed between the measured characters (data not shown). Leaf length showed close correlation with leaf width , branch flexibility (0.59), trunk color (-0.71), young shoot spine (-0.76), leaf length (0.65), ripening date (-0.68), and fruit taste (-0.77), which explained 12.37% of the contribution of variance. The traits, including branching (0.77), branch density (0.69), canopy density (0.85), the tendency to form suckers (0.71), and leaf density (0.77) were found in the PC2, which accounted for 11.29% of the variance. Five traits, including petiole length (0.73), fruit stalk length (0.53), fruit color (-0.79), fruit flesh color (-0.84), and fruit juice color (-0.84) were placed into the PC3 and included 10.44% of the variance. These components played a major role in distinguishing the accessions studied.The PCA could describe the evaluated traits as the 11 main components that were able to justify 76.29% of total variance Table . MohammaBi-plot analysis was performed using PC1 and PC2 which accounted for 23.66% of the variance Fig. . Group IPrunus germplasm [Morphological characterization is the first step in plant resource discovery and conservation . The evaermplasm , 23, 26.The main objective in any plant genetic resource conservation program should be to maintain the highest possible level of genetic variability . The ricP. microcarpa germplasm in Iran, including efforts for preserving biodiversity. Furthermore, the present findings give useful indications on how to act for more rational planning of the management of reproductive material. Significant diversity was revealed, regarding the morphological traits in the evaluated P. microcarpa germplasm. This diversity allows the effective parental selection in various breeding programs, referring to fruit quality and aiming at different aspects of postharvest utilization, besides high yield and resistance to diseases. The high genetic diversity observed within P. microcarpa species reflected the necessity for the conservation of this germplasm, and it is expected that the results gained in this study will assist current Cerasus breeding efforts and will maintain the genetic integrity of P. microcarpa.The results of the study contribute to a better understanding of genetic variation of wild Additional file 1.


Cereal landraces are a very valuable resource in contemporary agriculture. A renewed focus for breeding purposes could ameliorate some negative consequences of modern agriculture and conventional breeding, such as the loss of genetic diversity. One strategy combining molecular genotyping and characterization of morpho-agronomic traits related to productivity is proposed to assess a group of tetraploid wheat landraces named Bufala, historically cultivated in the mountain areas of Sicily and characterized by adaptability in terms of cold tolerance, ability to grow in marginal soils, weed competitiveness and resistance to diseases. A total of 55 SSR molecular markers were used to detect patterns of diversity in 30 rivet and durum wheat genotypes. Furthermore, phenotyping was then conducted for 8 morpho-agronomic traits. Discriminant analysis of principal components (DAPC), STRUCTURE and phylogenetical analysis allowed to identify three groups, two of them genetically close and including both Bufala and Bufala-related rivet landraces. To the third group, old and more recent durum wheat varieties, constituting the outgroup, were assigned. Clustering was confirmed by Principal Component Analysis (PCA). Finally, a correlation analysis showed that Bufala genotypes are characterized by lower ear density, major ear length and later earing time compared with the other studied genotypes. The levels of diversity and population structure could be an important contribution to parent selection in tetraploid wheat breeding programs, as well as to germplasm conservation and management. Wheat landraces are a very valuable genetic resource for the different contemporary cereal-based farming systems. Camacho Villa and collaborators  proposedTriticum genus that constitute the wheats of the world. Among polyploid species, tetraploid wheats (Triticum turgidum L.) belong to a taxonomic category that includes genetically and morphologically different entities, and their evolution under domestication has not been fully explained. Archaeological findings and genetic studies indicate that emmer (Triticum turgidum L. subsp. dicoccum (Schrank) Thell.), the first domesticated form of tetraploid hulled wheat, originated from the tetraploid wild ancestor in the western half of the Fertile Crescent. Tetraploid naked wheats and rivet, also called “poulard, cone or english wheat” (Triticum turgidum L. subsp. turgidum) and, successively, durum (Triticum turgidum L. subsp. durum (Desf.) Husn.), evolved from emmer in the Near East and spread through the north side of the Mediterranean area, reaching the Iberian Peninsula and Algeria from Italy. Through the evolution in mountain environments, rivet wheat has acquired rusticity in terms of cold tolerance, ability to grow in marginal soils, weed competitiveness and resistance to diseases [Triticum turgidum L. subspecies [Triticum turgidum subsp. turgidum were included in the analysis , not including the Sicilian rivet landraces. For the above-mentioned reasons, in this study a strategy combining molecular genotyping and morpho-agronomic traits is proposed to characterize a restricted group of rivet wheats named Bufala, historically cultivated in the mountain areas of Sicily (from 800 to 1200 m a.s.l.). This group of underutilized rivet genotypes represents an important agronomic option to preserve and maintain an agricultural activity in agro-ecological conditions typical of mountain areas, usually considered marginal and unsuitable for elite durum wheat cultivation. In particular, a total of 55 SSR molecular markers were utilized to analyze 30 tetraploid wheat genotypes, a collection of twenty Bufala and seven Bufala-related rivet landraces, in comparison with an outgroup of three improved durum wheat varieties. The aim of our work was to detect patterns of diversity between Bufala and the improved varieties in order to identify the underutilized landraces in the durum wheat germplasm scenario. Furthermore, phenotyping was then conducted for a set of significant morpho-agronomic traits, potentially useful for breeding purposes to obtain new genotypes suitable for low-input farming systems.There are a number of wild species, landraces, and traditional cultivars within the diseases . Fortunadiseases . The knodiseases . Furtherdiseases , and stadiseases . This isdiseases . In Italdiseases . Moleculdiseases ,11,12,13diseases ,16,17,18diseases ,20,21. Tdiseases ,23, and diseases ,25, reladiseases , and combspecies  used a sbspecies  describee) across the total genotypes was 0.60 (o) was 0.34  rivet wheat landraces, the outgroup of improved durum wheat varieties . The list of the accessions and their origins is reported in was 0.60 , and ranwas 0.34 , with a was 0.34 . When cowas 0.34 . The subA list of private alleles, alleles that are found only in a single population among the broader collection, of each genotype is also reported in The BIC analysis used to assess the optimal number of clusters identified three genetic clusters (K = 3). A scatterplot of the first two principal components of the DAPC, accounting for 16% of the total variance, is shown in Cluster 1 and 2 (C1 and C2) resulted to be genetically similar and partially overlapped. In these two clusters, both distributed Bufala and Bufala-related genotypes are distributed. Thirteen out of twenty Bufala landraces (65%) were grouped in C2, thus representing the main Bufala cluster, together with four Bufala-related landraces . Five Bufala landraces  and the three Ciciredda landraces  were grouped in C3, suggesting a genetic differentiation from the Bufale core cluster. Cluster 3 (C3) is clearly separated from the other clusters; it includes the outgroup of durum wheat varieties  and two Bufala landraces (BRCa-01 and BRCb-01). Due to the low discriminant power of the DAPC analysis and the partial overlapping when considering C2 and C3 clusters, a STRUCTURE analysis was further performed. The analysis consists of a Bayesian model-based clustering method. The number of subpopulations (K) was identified based on Delta K values . The higAs shown in A phylogenetic analysis was also carried out. The analysis, based on Nei  genetic The Principal Component Analysis (PCA) performed on a set of morpho-agronomic traits related to productivity showed some differences among the phylogenetic groups . The firp value < 0.05) of all the genotypes, considering also the group membership. The analysis confirms that there was a negative correlation between ear length (EL) and group membership (GR) (from Group I to Group III) (−0.78) and between time of earing (E) and group membership (GR) (−0.6), as wells as a positive correlation between ear density (ED) and group membership (GR) (0.64). A negative correlation between ear length (EL) and ear density (ED) (−0.71) was also found, indicating that, as expected, an increased ear length is associated with a lower seed density. When considering the trait correlations within groups, .Indeed, genotypes belonging to Group III  were associated with a higher ear density, an earlier earing time, and lower ear length. An opposite condition was noted in the genotypes belonging to Group I . Group II is characterized by a high variability of traits such as habitus (HA) and ear shape (ES), which were the traits described by the PC2. This evidence was confirmed by Pearson correlations . Figure  groups, b, as wel groups, c were al groups, d. All thTriticum species, resulting in a genetic relationship estimation among genetically, temporally and geographically distant varieties and accessions, obtaining useful information for breeding purposes [e = 0.60) [e (0.55) of the Bufala rivet landraces compared with the improved varieties group (He = 0.42). Thirty-six loci with an average PIC ≥ 0.44 were then selected for the subsequent analysis in order to have good discriminant power. Among the germplasm under study, Bufala Bianca 04 (BB-04), Ciciredda 03 (CIC-03) and Bivona 04 (BIV-04) evidenced the highest number of private alleles, making these landraces eligible genetic resource for characterization and genotypes traceability. Discriminant Analysis of Principal Components (DAPC) and STRUCTURE analysis, providing information about genetic structure, both grouped the studied genotypes into three different clusters. The same approach was carried out by Marzario and co-workers [p < 0.05) between habitus and time of earing (0.94) and between ear length and ear cross shape (0.76) in Bufala and Bufala-related wheats. Furthermore, the improved cultivars had a smaller (ear length vs. group = −0.78), but more ear density (ear density vs. group = 0.64). The high variability of habitus in the Bufala and Bufala-related rivet landraces could present an obstacle to mechanized harvesting. Therefore, further investigations are needed in order to elucidate the genetic source of this variability, with the aim of obtaining greater higher homogeneity of this characteristic.In Italy, tetraploid wheats, particularly durum wheat, have a long tradition of growing and breeding, and the germplasm of local populations collected in situ and ex situ in Southern Italy represents a valuable resource to preserve cereal genetic diversity, ensuring food security in the future. For this reason, the identification of precious traits, diversity estimates, and genetic relationship assessments are essential in order to take advantage of these wheat landraces. Genetic selection decreases variability over time, as highlighted by Marzario and co-workers . In factpurposes ,11,17,33purposes ,27. Here-workers . Neverthp He = 0.2. ThirtyTriticum turgidum L. ssp. turgidum convar. durum (Desf.), 2n = 4x = 28; genomes AABB), including 27 rivet wheat landraces belonging to Bufala and Bufala-related  groups, and an outgroup of three improved varieties of durum wheat, two old (Bidì03 and Capeiti) and one more recent (Simeto), which have in common the old variety released in 1915 Senatore Cappelli in their pedigree, were chosen for this study. The rivet landraces came from the Sicily region, a major island with several archipelagos of minor islands, with a total territorial extension of only 25,711 km2. These accessions represent more than half of all wheat landraces present in Sicily . The list of the accessions and their origin is reported in ® Plant Mini Kit  was used for the DNA extraction and the purity and concentration of DNA were determined spectrophotometrically at 260 and 280 nm by using a Nano Drop® ND 1000 Spectrophotometer .A total of 30 Sicilian tetraploid wheat genotypes  and on the Polymorphic Information Content (PIC) reported in the previous studies ,20, in oPCR amplification of genomic DNA was performed with a final volume of 15 µL containing 50 ng of genomic DNA, 0.5 mM of each dNTP, 0.25 µM of each primer, and 0.75 U of HSTaq polymerase as follows: 5 min at 95 °C, 30 cycles with 30 s at 95 °C, 30 s at either 55 or 60 °C (depending on the locus) and 30 s at 72 °C, followed by a final extension step of 30 min at 60 °C. The PCR products were sequenced at CD Genomics  using 3730XL Sequencer . To each well of a 96-well plate, 9 μL of a molecular weight internal standard and a mixture of formamide (0.5:8.5), and 1.0 μL PCR product was added. The detected raw data “.fsa” file was imported into the analysis software GENEMAPPER v3.2  for analysis.https://www.rstudio.com/products/team/), accessed on 13 April 2021 [find.clusters function, which implements successive K-means clustering. The rate of decrease of the Bayesian Information Criterion (BIC) was examined, and the number of clusters was determined as the value of K above which BIC values decreased or increased only subtly. The dapc function was then applied to describe the relationship between the inferred groups. In order to obtain reliable group membership probabilities and to avoid overfitting, we retained only the three first principal components (PCs) from the preliminary data transformation step . A model-based approach was further applied. This approach was implemented with STRUCTURE software [Data from sequencing were used to calculate statistical parameters such as number of alleles (Na), observed heterozygosity (Ho), expected heterozygosity (He) and polymorphism information content (PIC) of each SSR locus. The software used to obtain these parameters was Cervus 3.0.7 . Private alleles were also calculated using GenAlEx 6.503, a package for population genetic analysis that runs within Microsoft Excel . The popril 2021 . The optsoftware . At firssoftware , with whOnce the genetic structure of the genotypes was obtained, an examination of their degree of differentiation was performed. DARwin 6.0 software was used to calculate the Nei’s unbiased genetic distance. Through the neighbor joining method (NJ) , a dendrp < 0.05) was also calculated using the round(cor) R function and a scatter plot with the correlation coefficients were developed with the R/corrplot package (https://cran.r-project.org/web/packages/Corrplot/index.html) accessed on 20 April 2021.During the growing cycle, a sample of ten plants of each genotype was subjected to measurements of morpho-agronomic traits related to crop productivity, following both the Zadoks and DUS scale systems. After the harvest, ear-specific traits were analyzed on a sample of ten ears. The evaluated traits, scored according to descriptors for wheat defined by the CPVO protocol (CPVO-TP/120/3) and the DUS protocol and reported in Wheat landraces are a very precious genetic resource in the transition of cereal-based farming systems towards greater sustainability. A renewed focus on this germplasm for a new breeding approach could mitigate certain negative consequences of intensive agriculture and conventional breeding, such as the excessive use of chemical inputs, loss of genetic diversity due to the high crop homogeneity based on monoculture farming and the limited yield increase in marginal cereal areas. For their high polymorphism, codominance and locus specificity, simple sequence repeats or microsatellite (SSRs) markers have proved to be highly efficient molecular tools for detecting genetic variation and characterizing germplasm collections. In wheat, SSRs usually give a unique fragment specific to each homoeologous copy and show a high level of polymorphism compared with other types of molecular markers, including SNPs . Moreove


The objective of this study was to estimate the genetic parameters and various litter trait trends of Danish pigs in South Vietnam, including the number born alive (NBA), number weaned (NW), and litter weight at the 21st day (LW21).Records of 936 Yorkshire sows with 3361 litters and 973 Landrace sows with 3161 litters were used to estimate the variance components, genetic parameters, and trends of NBA, NW, and LW21. The restricted maximum likelihood method was applied using VCE6 software to obtain the variance components and genetic parameters. Thereafter, the best linear unbiased prediction procedure with an animal model was applied using PEST software to estimate the breeding values of the studied traits.The heritability estimates were low, ranging from 0.12 to 0.21 for NBA, 0.03 to 0.04 for NW, and from 0.11 to 0.13 for LW21. The genetic correlation between the NBA and NW was relatively strong in both breeds, at 0.77 and 0.60 for Yorkshire and Landrace, respectively. Similarly, the genetic correlation between the NW and LW21 was considerably stronger in Landrace pigs (0.71) than in Yorkshire pigs (0.48). The estimates of annual genetic progress were 0.0431, 0.0233, and 0.0461 for NBA, NW, and LW21 in Landrace pigs and 0434, 0.0202, and 0.0667 for NBA, NW, and LW21 in Yorkshire pigs, respectively.The positive genetic trends estimated for the additive genetic values of the selected traits indicated that the current breeding system has achieved favorable results. Genetic parameters are influenced by the genetic structure of animal populations and may, therefore, differ from one population to another . In pigsFor organized breeding programs, estimates of the genetic trends of selection traits achieved after several generations through selection schemes are crucial to describe the genetic progress, assess selection effectiveness, and adjust the breeding objectives if necessary. In most cases, the annual means of the predicted breeding values of selected lines can be used to estimate the genetic trends of objective traits in selection programs .In recent decades, the genetics of Yorkshire, Landrace, Duroc and Pietrain pigs have been imported into Vietnam from the USA, Canada, Australia, and other countries . The varSamples collected were used only for routine diagnostic purpose of the breeding programs and not specifically for the purpose of this project. Therefore, approval of an ethics committee was not mandatory. Sample collection and data recording were conducted strictly according to the Vietnamese law on animal protection and welfare.The research was conducted on purebred Danish Yorkshire and Landrace pigs (DanAvl Yorkshire and DanAvl Landrace) imported from Denmark in 2013, with an initial number of 233 animals, including 122 Yorkshire pigs  and 156 Landrace pigs . Since then, the pig genetics have been nurtured and purebred in the Binh Minh National Pig Breeding Farm in South Vietnam. Gilts, boars, and pregnant sows were maintained in individual stalls in a closed-house system, with an ambient temperature of 28°C to 30°C and relative humidity of 60% to 70%. Farrowing sows were maintained in both closed-house and open-house systems. The open-house system was naturally ventilated with a day and night temperature amplitude of 24°C to 34°C and a relative humidity ranging from 50% to 60% during the dry season (November to May) and 80% to 90% during the wet season (June to October). Gilts and non-lactating sows were fed 2.4 to 2.6 kg of feed containing 16% crude protein and total calories of 13.44 to 14.70 MJ/kg twice daily (06:00 and 14:00 h). All nursing sows were fed 6 to 7 kg of feed daily; the feed was composed of 18% concentrated crude protein and 17.52 MJ/kg, and was divided into four feeding times . The piglets were weaned between 22 and 28 days of age. Sow and litter records were collected between 2014 and 2019. The dataset consisted of sow identification, sow birth date, sow breed, sire identification, dam identification, parity, farrowing date, number of piglets born alive, number of piglets weaned, and litter weight at weaning. The database for the genetic evaluation of Danish pig genetics was fitted using PEST [The best linear unbiased prediction (BLUP) procedure was applied for the genetic evaluation of purebred sows based on the reproduction traits number born alive (NBA), number weaned (NW), and litter weight on the 21st day (LW21), which were combined into the sow productivity index (SPI):For young boars and gilts, the maternal line selection index (MLI) was applied in the evaluation:NBA, EBVNW, EBVLW21, EBVD100, and EBVBF100 are the estimated breeding values of NBA, NW, LW21, days of age to 100 kg (D100), and backfat thickness (ML100). SD is a breed-specific standard deviation. The average values of these indexes are 100 for each test group, with a SD of approximately 25.where, EBVVariance components, heritability, and correlations for litter traits were estimated using the restricted maximum likelihood method with VCE6 software . The breb represents fixed effects, including HYS effect (herd×year×season interaction by birthdate), housing fixed effect (closed or opened), effect of age (months) of sow at farrowing treated as the covariant for litter traits with a regression coefficient. Vectors a, p, and e represent random animal genetic effects, random permanent non-genetic effects, and random residual effects, respectively. X, Z, and W are incidence matrices associating vectors b, a, and p, respectively, with vector y.Where y is a vector of observations for NBA, NW, and LW21, Vector Variances were defined as follows:A is the additive relationship matrix; Ipe, Ie are identity matrices; and Where The genetic trends of the additive genetic values were determined by linear regression of the average predicted breeding values of NBA, NW, and LW21 traits, using INDEX as a function of dam’s birth year between 2013 and 2018.The three reproduction traits NBA, NW, and LW21 were analyzed in this study. The genetic variance and heritability of litter traits are presented in As these estimates depend on the population, study time, and data collected for each trait, it is difficult to interpret the differences in variance component estimates obtained in different studies. For the NBA in both breeds, the estimates of additive genetic variance in this study were considerably larger than those in some previous studies ,11–13, bSome differences in the heritability of litter traits were observed between this study and previous studies. According to a previous study, the heritability estimate was 0.22 for NBA, which is consistent with that obtained in the present study for Yorkshire pigs (0.21) . In contFor Polish pigs, a previous study reported heritability estimates of 0.023, 0.027, and 0.030 in the Polish Landrace line and 0.061, 0.058, and 0.075 in the PL-23 line for NBA, NW21, and LW21, respectively . For IriFor Landrace and Large White pigs raised in a tropical climate in Thailand, a very low heritability of 0.05 was reported for both NBA and litter weight weaned (LWW) . RecentlFor different litters of Dutch Landrace pigs, heritability estimates of 0.084 and 0.089 for NBA in litter one and litters two to six, respectively, have been reported . ConversEven in studies related to the same genetic groups as Danish pigs, research conducted in different periods of time showed different results. For instance, data collected by a study on Danish Landrace and Yorkshire pigs in Denmark from 1985 to 1989) reported heritability estimates of 0.11 to 0.14 in Landrace pigs and 0.10 to 0.11 in Yorkshire pigs for the total number of piglets born . Moreove5 to 1989Thus, the heritability estimates for litter traits depend on the genetic structure of the studied populations, study period, dataset size, and estimation methods. In this study, the heritability of NBA was low (0.12 to 0.21), but still significantly higher than that reported for the same genetic groups of Danish pigs. This means that improvement in the studied traits in Danish Landrace and Yorkshire pigs will be feasible in the coming years through selection.Genetic, environmental, and phenotypic correlations between the NBA and NW (NBA-NW), NBA and LW21 (NBA-LW21), and NW and LW21 (NW-LW21) are indicated in In previous studies, a large difference was observed in the genetic correlations between the NBA and NW, NBA and LW21, and NW and LW21 in pigs. These correlations depend on the studied traits, genetics, populations, time, and statistical methods. One of the main reasons for the differences between current study and others is the statistical model for litter traits with the additive genetic effect adjusted by sow’s age (months). Some studies have reported negative correlations between −0.07 and −0.99 in Australian pigs and Polish Landrace pigs ,18. AnotFor pig genetics originating from Denmark, the genetic variance and covariance components for litter size and litter weight in Danish Landrace pigs have been estimated using a multivariate mixed model, which indicated genetic correlations of 0.79 between the NBA and NW as well as between the NBA and LW21 . FurtherAs discussed above, the genetic correlations estimated in this study between NBA and NW and between NBA and LW21 were positive and relatively high in both breeds, which is consistent with the results of previous studies, especially those conducted in the same Danish pig genetics. Thus, there is an advantage in improving NBA and NW simultaneously in Danish Landrace and Yorkshire pigs through genetic evaluation programs.2) values: 77.5% in Landrace and 78.5% in Yorkshire. For NW (2 values of 78.6% and 73.4% in the Landrace and Yorkshire herds, respectively. For LW21 (2 value of 88.4% in Landrace and 80.0% in Yorkshire. The annual regression coefficients for NBA (The genetic trend estimates for selected traits reveal whether selection decisions made during the breeding program resulted in effective improvements. This is important for assessing and adjusting current breeding schemes. For NBA , negativ. For NW , negativFor LW21 , a conti for NBA , NW (Fig for NBA , and LW2 for NBA  were 0.02 values of close to 100%: 94.9% for Landrace and 94.3% for Yorkshire. The average annual INDEX values increased by 2.1092 in Landrace pigs and 1.6976 in Yorkshire pigs, indicating the genetic progress of INDEX in the studied animals.As presented in Regarding reproduction traits in pigs, different programs of genetic improvement may result in different levels of genetic progress, which can depend on the selection strategy, population size, evaluation methods, and procedures. In French Large White pigs, the annual genetic trends from 1977 to 1998 revealed estimates of 0.15 and 0.13 piglets for total piglets born and NBA, respectively . In PoliIn the United States, the estimated average genetic trends of 0.029, 0.008, and 0.279 have been reported for NBA, NW, and LW21, respectively, in Yorkshire pigs . These vHowever, the genetic progress for litter traits in this study was much lower as compared with some pig populations selected in China or Thailand. For instance, a study on 6,363 sows in Chinese Landrace pigs during 2000 to 2012 reported an annual genetic gain of 0.08 piglets per litter per year for NBA . AnotherAs mentioned in method section, a breeding program has set up for Danish Landrace and Yorkshire pigs in this study since 2013 with objectives to improve litter traits and to maintain growth rate as well as backfat thickness. The BLUP statistical procedure was applied for estimating the breeding values and genetic evaluation for selective traits. The MLI was constructed including growth rate, backfat thickness and three litter traits to select young boars and gilts after finishing individual performance test. And then, SPI including three litter traits was applied for sow’s productivity evaluation. During 2013 and 2018, the annual genetic progress determined for litter traits NBA, NW, and LW21 in two these populations was relatively small. However, the positive values of these genetic trends confirmed the validity of the breeding program and the suitability of the selection strategy for these genetics. The large number of selected traits in the breeding program, the small population size, and the within-herd selection scheme could be the main factors influencing the low selection efficiency and slow genetic progress in these genetics. Therefore, the BLUP procedure should be retained for further genetic evaluation, and the selective population size should be increased by a cross-herd selection, which will enable more precise estimates of the breeding values.Low heritability values were observed for litter traits in Danish Landrace and Yorkshire pigs. The genetic variances in number born alive and litter weight at the 21st day were sufficiently large for improvements these traits through selection. The favorable genetic correlations showed that the simultaneous improvements in the litter traits number born alive, litter weight at the 21st day, number weaned, and litter weight at the 21st day could be promising breeding goals for these pig genetics. The positive genetic trends estimated for the additive genetic values of the selected traits indicated that the current breeding system has achieved favorable results. From these findings, it is evident that the best linear unbiased prediction procedure should be implemented in both within-farm and across-farm genetic evaluation programs.


Ancient DNA studies have revealed how human migrations from the Neolithic to the Bronze Age transformed the social and genetic structure of European societies. Present-day Croatia lies at the heart of ancient migration routes through Europe, yet our knowledge about social and genetic processes here remains sparse. To shed light on these questions, we report new whole-genome data for 28 individuals dated to between ~ 4700 BCE–400 CE from two sites in present-day eastern Croatia. In the Middle Neolithic we evidence first cousin mating practices and strong genetic continuity from the Early Neolithic. In the Middle Bronze Age community that we studied, we find multiple closely related males suggesting a patrilocal social organisation. We also find in that community an unexpected genetic ancestry profile distinct from individuals found at contemporaneous sites in the region, due to the addition of hunter-gatherer-related ancestry. These findings support archaeological evidence for contacts with communities further north in the Carpathian Basin. Finally, an individual dated to Roman times exhibits an ancestry profile that is broadly present in the region today, adding an important data point to the substantial shift in ancestry that occurred in the region between the Bronze Age and today. Thus, this region was a significant corridor for the first migrating farmers from western Anatolia, who dispersed throughout the rest of Europe via inland and littoral routes along the Danube River and eastern Adriatic coast respectively3. While this region is important for understanding population and cultural transitions in Europe, limited availability of human remains means that in-depth knowledge about the genetic ancestry and social complexity of prehistoric populations here remains sparse.Croatia in southeast Europe is home to a diverse landscape of contiguous ecoregions, with steep mountains separating the eastern Adriatic coast from the temperate Pannonian Plain in the north. Its central location at the interface of Central Europe, the Balkan Peninsula and the Mediterranean has long promoted it as a conduit to Anatolia, the Aegean and the steppe region as far as the Black Sea, with the northern lowlands connecting it to passes through the Carpathian Basin to Europe beyond3. Published genome-wide data from a small number of ancient individuals from present-day Croatia have shown how Neolithic and Copper Age genomes share similar ancestry with early farmers from Anatolia, but some Copper Age and coastal Bronze Age individuals display additional ancestry associated with steppe pastoralist populations2 that dispersed into Europe during the third millennium BCE. The beginnings of social complexity in southeast Europe has also been an area of intensive study among archaeologists4. Increasingly, ancient DNA studies have explored intracommunity social organisation, revealing residency patterns, biological kinship and the social status of past societies10. For example, closely related individuals have been identified in Late Neolithic and Bronze Age communities from across Europe, often in association with high mitochondrial and low Y chromosomal diversity, indicating female exogamy and a patrilocal social organisation7. However, few in-depth, site-specific studies such as these have been conducted in this region to date.Previous studies have demonstrated genetic discontinuity following the Mesolithic in west Eurasia, associated with the migration of early farmers and the spread of agriculture12. The emergence of the Neolithic here can be traced to the arrival of the Starčevo culture, which spread from present-day Serbia west and northwards into the Carpathian Basin13, while at coastal sites the Early Neolithic was marked by the presence of the Impressed Ware culture from about 6000 BCE15 , and is intersected by the Danube river, Sava, Drava and other large tributaries that are the site of many prehistoric settlements and formed an important part of communication and exchange networks in this area18. This was accompanied by growing social distinctions among burials23, signalling an important change in people’s relationship with the dead18. The Croatian Copper Age (4500/4300 BCE—2400 BCE) saw the settlement of the Lasinja, Baden, Kostolac and Vučedol cultures, among others, in what is present-day continental Croatia26, which witnessed the growth of trade networks and more pronounced social hierarchy as seen in the appearance of high status burials28. The development of more marked social stratification appears to be linked with the growing use of metals in the Bronze Age, which spanned in present-day Croatia from about 2400—800 BCE, and saw a further increase in migrations from the eastern European steppes, the Aegean and Anatolia along with a rise in social ranking26. One of the numerous Middle Bronze Age cultures to co-exist in the Pannonian Plain was the Transdanubian Encrusted Pottery culture , and data from 1102 published ancient individuals . We generated whole-genome shotgun data from petrous bone to ~ 1X coverage and aligned fragments to the reference human genome (Methods). We then called pseudo-haploid genotypes using the positions of approximately 1.24 million genome-wide single nucleotide polymorphisms (SNPs) (Methods). As samples were non-UDG treated, we limited analyses to transversion-only SNP sites to mitigate against erroneous genotype calls caused by ancient DNA damage. We confirmed DNA molecules were ancient by observing short read lengths and damage patterns at the ends of reads typical in ancient molecules Table , Methods30  (Methods) by projecting the new shotgun data and published ancient datasets onto the first two principal components constructed from 920 individuals selected from contemporary West Eurasian populations in the Human Origins (HO) datasetf3-statistics of the form f3  and a small contribution of Western European hunter-gatherer (WHG)-related ancestry  (Z = 6.95) (Supplementary Table 2. Replacing WHG with Iron_Gates_HG harbours comparable results (Supplementary Table We considered the newly-reported Middle Bronze Age genomes from Jagodnjak (Croatia_Jag_MBA) a single group for further population genetic analysis based on common archaeological context and clustering on the PCA Fig. . We obseTo further characterise differential genetic affinities of the Jagodnjak group to the Dalmatian Bronze Age and other genomes, we visualised genetic substructures among post-Neolithic genomes from the region with increased resolution using UMAP and default parameters Fig. . Croatia29. Based on its date and core distribution in the Carpathian Basin32, as well as its clustering with Croatia_Jag_MBA in UMAP and PCA space, we considered Hungary_Makó_EBA the most suitable candidate source of ancestry. This choice is further supported by Hungary_Makó_EBA sharing similar amounts of drift with WHG to Croatia_Jag_MBA  Fig. a–c.Individual ancestry modelling with qpAdm confirms high genetic homogeneity among all Middle Neolithic individuals, with a large majority exhibiting either no or low Western hunter-gatherer ancestry introgression at p > 0.01 (given multiple testing) and no significant differences between burial rites Fig. . Jagodnj3, while almost 60% of haplotypes belong to branches K and T2. These, together with clades N1a and J account for most of the variation reported in early Neolithic Starčevo and Linearbandkeramik farming communities of northern Croatia and the adjacent Carpathian Basin3, pointing to genetic continuity. Y chromosomal haplogroups assigned with Yleaf (Methods), similarly show a high degree of diversity, with seven males represented by four different haplogroups  identified high haplotypic diversity in the Neolithic Table . A singlps Table . Two of Pairwise genome-wide mismatch rates Fig. , MethodsWe did not identify first or second degree genetic kin among the Middle Neolithic individuals, however POP05 has a lowered pairwise mismatch rate indicative of a more distant consanguineous relationship with another two subadults (POP02 and POP04), all buried in the same pit house. POP05 also has a lowered pairwise mismatch rate with POP24, an older adult male deposited in the channel. Three of these individuals also share the same maternal K1a haplogroup Table  and S9. 34. A further three individuals have fewer long ROH > 20 cM indicative of their parents being second cousins or equivalent, while the remainder display ROH pointing to relatedness within the last ten generations. Contrastingly, individuals from Jagodnjak exhibit much lower sums of ROH, with no long runs > 20 cM, and some short runs among all individuals suggestive of more distant relatedness. Infant JAG93 and JAG58 have ROH > 12 cM suggestive of parental relatedness up to five generations ago, although shorter ROH is found in JAG58’s first degree relative JAG06, demonstrating some heterogeneity that is mirrored in their admixture profiles. Copper Age and Roman Period individuals show few to no ROH greater than 4 cM.We estimated runs of homozygosity greater than 4 cM (centiMorgans) with hapROH (Methods) to assess levels of inbreeding and infer past mating practices Fig. . Long RO40  40, suggesting they may not have been able to digest lactose as adults, and is concordant with previous findings that lactose tolerance in Europe remained at low frequency into the Bronze Age39.Finally we analysed a panel of functional SNPs associated with phenotypic traits under recent selection3, and displays low levels of WHG-related ancestry that persist into the Copper Age, mirroring the genetic profile of some other contemporaneous populations of the Carpathian Basin31. In addition, the Copper Age individuals from Popova zemlja represent an early presence of people with steppe-associated ancestry in this region, who would have co-existed with pre-steppe Copper Age individuals only 60 km away at Vučedol2.With this study we have extended the spatio-temporal genomic transect of present-day Croatia, shedding light on the genetic history of people living in its diverse ecoregions. The distribution of genomes along the European cline in PCA space attests to the importance of this region as a contact zone for migrating peoples across continental Europe over millennia. The Sopot community of Popova zemlja exhibits genetic continuity from Early Neolithic Starčevo predecessors, supporting previous findings2 are broadly contemporaneous with the latest contextual date for Jagodnjak, yet carry ancestry similar to Copper Age Popova zemlja. This profile persists in a third Dalmatian individual who postdates the genetically distinct Jagodnjak individuals by almost a thousand years2. The shared genetic affinities between individuals of Jagodnjak and the contemporaneous Vatya culture further north, distinguished by high WHG-related ancestry, supports archaeological evidence for close interaction and exchange networks between various groups in the Carpathian Basin and the southern Transdanubian Encrusted Pottery communities in present-day eastern Croatia, whose ceramic wares have been found in neighbouring Vatya communities and other contemporaneous groups along the Danube in the Carpathian Basin29. Moreover, their shared affinities are congruent with archaeological evidence for a common immediate predecessor, widely accepted to be the Late EBA Kisapostag culture, which itself was partly founded upon the widely distributed Makó-Kosihy-Čaka cultural complex29. These insights thus contribute to long-standing debates about the relationships between the different Middle Bronze Age cultural units that co-existed along the Danube and the Carpathian Basin, and reveal genetic affinities between populations of present-day eastern Croatia and the adjacent Carpathian Basin over multiple time periods.In the Bronze Age we again observe two genetically distinct yet concurrent ancestries in different ecoregions. Two Dalmatian individuals associated with the Cetina culture4. Within this context however, we detect a few individuals scattered across the site who exhibit very close parental relatedness. Four of the five belong to the same mtDNA haplogroup clade K1a, while two of these, POP02 and POP05, also have elevated kinship coefficients and are buried next to each other in the largest pit house. Taken together, it is possible these individuals were contemporaneous, and we could be witnessing an example of occasional close relative unions within the same matrilineal pedigree. No other detectable differences distinguish these individuals from others buried at the site in terms of their genetic profile or mortuary rites, suggesting this was a socially acceptable alternative mating choice.Beyond these spatio-temporal relationships, we have gained valuable insights into the demography and social organisation of these communities. The unstructured and homogeneous ancestry across the Middle Neolithic site, together with high haplotypic diversity and low or no signs of inbreeding in many unrelated individuals is consistent with this community being part of a large, stable and exogamous population, supporting archaeological evidence for high population density in this region4. This may not have been the only form of burial practice however, with biological kin buried elsewhere20. The high representation of children, in particular girls, as well as burials of neonates, likely signifies age and sex selection and an ascribed status based around the community’s belief systems, for which various explanations have been put forth regarding similar Neolithic intramural sites in the region41. For example, buildings have been associated with ideas of matrilineality and ancestor worship, and as spaces linked to the reproduction and continuity of society, where the burials within would have provided protection and prosperity 41. In addition, we do not detect genetic structuring in relation to mortuary practices here. In terms of grave goods, the expression of interpersonal distinctions is limited, with the majority of burials containing few objects such as ceramic vessels or fragments. However a small number of individuals  from different age and sex categories have abundant grave good items associated with everyday activity that appear to signal some limited social differentiation based on social and economic status. The youngest of these individuals is estimated to have been 13–15 years old, thus all were old enough to participate in adult work, and it is therefore difficult to know whether they achieved or inherited their status. Finally, flexed burials in the habitation area versus predominantly male, extended depositions in the channel also do not correlate with detected genetic ancestry. While the reason for the different channel depositions cannot be known, the presence of mixed body positions such as found here has been recorded at other Sopot sites in the Pannonian Basin42, where it has been suggested that it may represent social groupings adhering to different mortuary customs. Considering the highly exogamous genetic profile at this site within a high population density region, we cannot exclude this as one possible explanation. Indeed, Neolithic mortuary rites and population composition have been shown to vary greatly43, therefore more localised studies such as this will help further our understanding of the diversity of this phenomenon.This first genome-wide study of an intramural burial site in this region also reveals no first or second degree relatives, with only a few individuals like POP05 and POP24 sharing more distant consanguineous relationships as well as mtDNA haplogroups. While this could indicate the presence of some distant matrilineal relationships, which also interestingly suggests connections between those deposited in the channel (POP24) and others buried in the main intramural site, close biological kinship does not form the foundation for selection to be buried here, questioning suggestions that those buried together in buildings represent extended families44. Similar to other Transdanubian Encrusted Pottery burial sites  with IntCal13 calibration curve45 and OxCal version 4.2.447, from the Penn State AMS 14C Facility for POP35  with IntCal13 calibration curve45 and OxCal version 4.3.248; from University of California Irvine Keck-Carbon Cycle AMS facility for JAG34  with IntCal20 calibration curve49 and OxCal version 4.448  and POP39  using IntCal13 calibration curve48 Table .Group labels generally follow the format “Country_SiteName/Region_TimePeriod”, with the site name contracted to a short form, for example Croatia_Pop_MN; Pop Popova zemlja, Jag Jagodnjak, Dal Dalmatia. Time periods are labelled as: BA Bronze Age, CA Copper Age, EBA Early Bronze Age, EN Early Neolithic, IA Iron Age, LBA Late Bronze Age, LCA Late Copper Age, MBA Middle Bronze Age, MN Middle Neolithic, N Neolithic and RomanP Roman Period.We processed all samples in dedicated ancient DNA laboratories at the University College Dublin, Ireland. Petrous bones were UV irradiated for 10 to 15 min on each side followed by light sandblasting of the outer surface to remove loose debris. The cochlea was then excavated from the petrous bone using a sandblaster, and UV irradiated on each side for 10 min before it was finely powdered in a mixer-mill (Retsch).50. In a pre-digestion step aimed at reducing contamination51, the bone powders were digested for one hour at 56 °C without rotation in 1 ml of extraction buffer containing 0.45 M EDTA and 0.25 mg/ml Proteinase K. The bone powder was spun down to a pellet by centrifugation and re-suspended in fresh extraction buffer. Samples were digested for one hour at 56 °C followed by 18 h at 37 °C with rotation. Samples were centrifuged at 13,000 rpm, and the 1 ml supernatant added to the reservoir of a Roche High Pure extender assembly tube containing 13 ml of binding buffer. Binding buffer consisted of 5 M Guanidine Hydrochloride, 40% isopropanol, 90 mM sodium acetate and 0.05% Tween-20. Tubes were centrifuged for four minutes at 1500 rcf, the spin column detached and placed in a collection tube and dry spun at 6000 rpm for one minute to remove remaining binding buffer. After placing the spin column in a fresh collection tube, 650 μl of PE wash buffer was added, centrifuged for one minute at 6000 rpm and the flow-through discarded. This step was repeated once followed by dry spinning at 13,000 rpm to remove remaining wash buffer. The column was placed in a clean Eppendorf tube and the sample eluted with 25 μl TET which had been incubated at 37–56 °C. Samples were then incubated at 37 °C for ten minutes followed by centrifugation for 30 s at maximum speed. The elution step was repeated, resulting in a total volume of 50 μl DNA extract. One negative control containing only extraction buffer was processed for every seven samples.DNA was extracted from about 50 to 70 mg of bone powder following a modified silica column based method optimised for ancient DNA samples52. Blunt-end repair was carried out by adding NEBNext End- Repair module (New England Biolabs) to 12.5 μl of each DNA extract, which was incubated at 25 °C for 15 min, followed by 12 °C for 5 min. Samples were then incubated at 25 °C for 30 min for adapter ligation with T4 DNA Ligase (ThermoFisher Scientific). Adapter fill-in was performed with Bst Polymerase (New England Biolabs) with an incubation at 37 °C for 30 min and 80 °C for 20 min to inactivate the enzyme. Purification steps following blunt-end repair and adapter ligation was performed with the MinElute PCR purification kit from Qiagen. A negative control was processed for every seven samples, and a final library volume of 40 μl obtained.Non-UDG-treated, double-stranded libraries were constructed followingSingle indexing PCR was performed by adding a unique seven-base-pair index to 3 μl of each library using Accuprime Pfx Supermix (Life Technology) and IS4 primer to a total reaction volume of 25 μl. The PCR temperature profile consisted of initial denaturation at 95ºC for five minutes, a further 15 s of denaturation at 95ºC, twelve cycles of annealing at 60 ºC for 30 s, elongation at 68 ºC for 30 s and a final extension at 68 ºC for five minutes. A negative PCR control was included with every batch. The PCR amplification and subsequent clean-up steps were performed in a separate lab in a different part of the building from the clean labs. MinElute PCR purification kit spin columns were used for purification of amplified libraries following Qiagen instructions. Quantification of amplified product was performed using Qubit 2.0 Fluorometer (Thermo Fischer Scientific) and Agilent 2100 Bioanalyser DNA 1000 assay. Single-end shotgun sequencing was performed by pooling samples in equimolar amounts onto an Illumina NextSeq500 platform using 75-cycle kits for 1 × 76 cycles and 1 × 7 cycles for de-multiplexing.53 discarding reads under 17 bp (-m 17) and allowing an overlap of 1 bp between the read and adapter (-O 1). Reads were then mapped to the UCSC genome browser human reference hg19 (GRCh37) to produce BAM files with BWA aln/samse (version 0.7.15-r1140)54, replacing the mitochondrial genome with the revised Cambridge Reference Sequence 55. Seed length was disabled (–l 1000) and the default number of differences (-n 0.04) and minimum Phred scale mapping quality of 30 (-q 30) were used. PCR duplicates were removed with SAMtools rmdup (v.0.1.19-96b5f2294a)56.Adapter sequences were trimmed from reads using Cutadapt (version 1.15)56 with the quality flags –q30, -Q30 and –B. This file was used to genotype individuals whereby a single base call was chosen at random from each SNP site to produce pseudo-haploid calls with transversion SNPs only using the flag –t SkipTransitions in pileupCaller (https://github.com/stschiff/sequenceTools) in order to remove variants affected by post-mortem damage in non-UDG treated samples. A second genotype dataset was produced that included all SNPs for use in functional SNP and ROH analyses (see below) 57, to merge the new genotype data to reference datasets101, Supplementary Table 61, and, for tests involving present-day comparisons, a panel of worldwide present-day populations containing 1311 individuals genotyped at 597,573 nuclear SNP positions on the Affymetrix Human Origins (HO) array30, of which 66,880–94,317 transversion-only SNP positions are covered by the newly-reported individuals (Supplementary Table We used mergeit (version 2450) from the package ADMIXTOOLS56 with a minimum mapping and base quality of 30  and –B to turn off base alignment quality for five phenotypically informative SNPs that are included in the 1240 K panel. This included lactase persistence40 and skin and eye pigmentation37. Numbers of reads supporting each allele are reported in Supplementary Table We produced a pileup from BAM files using SAMtools mpileup (version 1.3)https://github.com/TCLamnidis/Sex.DetERRmine to determine genetic sex of each individual with standard errors. Males should have an x-rate of 0.5 and y-rate of 0.5. Females should have an x-rate of one and y-rate of zero 63. Results based on new Method1 are reported for a minimum of 200 SNPs on the X chromosome that are covered at least twice ce Table .64. To do this, we used EAGER (version 1.92.55)65 to remap all reads for each individual to the mitochondrial rCRS (Gen bank accession no. NC_012920.1)55 with CircularMapper (version 1.93.4)65, filtering on a minimum mapping quality of 30 and removing duplicates. Schmutzi confidence intervals are given as est.high and est.low  for automated mitochondrial haplogroup assignment based on phylotree mtDNA tree build 17 (http://www.phylotree.org/) (Table We used Schmutzi/) Table . We manu67 to infer the Y chromosomal haplogroup in males in an automated way based on haplogroup-defining SNP positions in the ISOGG 2016 nomenclature. We filtered results on derived alleles and transversion-only SNPs, and the most downstream haplogroup was selected (Table 56. We used Integrative Genomics Viewer (Broad Institute)68 to visually inspected reads in order to verify if defining variants were in the middle or at the end of a read to assess reliability, and to confirm mutations among individuals with shared haplotypes. Four of the Jagodnjak males share the same mutations (G2a2a-Z31430) while no reads covered the defining position for this haplotype in the fifth male, JAG82.We used Yleaf version 1.0).067 to ied Table . Haplogrhttps://github.com/TCLamnidis/pMMRCalculator) and READ69 with default parameters. READ provides an upper and lower Z score to help assess the certainty of the results, with the upper Z score indicating the distance to a lower degree of relationship, and a lower Z score indicating the distance to a higher degree of relationship. There was a minimum overlap of 92,000 SNPs between pairs of individuals, and both methods produced comparable results  using default parameters for the dataset containing all SNPs. A global dataset of 5008 haplotypes were used as a reference panel taken from the 1000 Genomes Project. The total sum ROH is reported for each length category of 4-8 cM, 8-12 cM, 12-20 cM and > 20 cM  greater than four centimorgans (cM) were identified with the Python package hapROH cM Fig. .70 with a set of 59 present-day west Eurasian populations from the Human Origins dataset30 to construct the first two principal components, and projected the ancient genomes with options lsqproject:YES, shrinkmode:YES and outliermode:2  in the EIGENSOFT package (version 6.0.1)umap (version 0.2.3.1)71 using default parameters 57 for performing f-based statistics. Outgroup f3-statistics was calculated with qp3Pop (version 435) 74 to estimate the age of past population admixture events between two source populations by inferring time since mixture from the average size of ancestry blocks, assuming a generation time of 29 years (Supplementary Table We used DATES (Supplementary Information 1.Supplementary Information 2.