Aphidius ervi appears to be inefficient. We investigated whether this inefficiency may have both genetic and ecological bases comparing wild and commercial populations of A. ervi. We used two complementary genetic approaches: one based on the mitochondrial marker COI and one based on microsatellite markers. COI analysis showed a genetic differentiation within the A. ervi species, but the structure was neither associated with the commercial/wild status nor with host species factors. On the other hand, using microsatellite markers, we showed a genetic differentiation between commercial and wild A. ervi populations associated with a loss of genetic diversity within the mass-reared populations. Our ecological genetics study may potentially explain the weak efficiency of biological control of aphids in protected strawberry crops and enable to provide some insights to improve biological control.Due to their ability to parasitize various insect species, generalist parasitoids are widely used as biological control agents. They can be mass-reared and released in agroecosystems to control several pest species in various crops. However, the existence of genetic differentiation among populations of generalist parasitoid species is increasingly recognized and this can be associated with an adaptation to local conditions or to a reduced range of host species. Moreover, constraints of mass-rearing conditions can alter genetic variation within parasitoid populations released. These features could be associated with a reduced efficiency of the control of targeted pest species. Here, we focused on strawberry greenhouses where the control of aphids with the generalist parasitoid  Due to their ability to switch among host species, generalist parasitoids are particularly interesting for inundative biological control  as they Aphidius ervi  (Hymenoptera: Braconidae: Aphidiinae) is a generalist species described on more than twenty host species [Macrosiphum euphorbiae (Thomas) or Aulacorthum solani  in greenhouse crops [A. ervi have been reported [A. ervi coexist, the more frequent being Acyrthosiphon malvae (Mosley), M. euphorbiae and Rhodobium porosum (Sanderson) [A. ervi was observed on its three major aphid hosts on strawberry, suggesting that some wild populations of A. ervi would be more effective at controlling aphids in strawberry crops than mass-reared commercial ones [The aphid parasitoid  species . This hyse crops . Howeverreported . This isnderson) . Howeverial ones .A. ervi may have a genetic basis, with two non-exclusive hypotheses. (1) There is a genetic differentiation between commercial and wild populations of A. ervi resulting from different levels of host specialization, the mass-reared parasitoids having a distinct and narrowest host range compared to wild ones. To test this hypothesis, we compared genetic diversity between mass-reared populations and wild populations from aphids on strawberries and on other cultivated and wild plants, using a fragment of the COI mitochondrial gene that allows to resolve high level of intraspecific differentiation. The association of such differences to host specialization has already been demonstrated in several species of Aphidiinae [A. ervi genetically by using microsatellite markers to identify finer levels of differentiation. The wild individuals came from aphids on strawberries and on other crops, sampled at a large scale, in order to assess the effects of the aphid host plant, the aphid host species, and the geographic distance on genetic variability. Considering diverse wild putative populations, defined on the basis of their wild/commercial origin, their region and their aphid host, we investigated whether commercial and wild parasitoids differ in terms of both genetic structure and diversity.Here, we investigated whether the inefficiency of inundative biological control in mass-reared populations of hidiinae , 15. We A. ervi individuals. Commercial A. ervi were mass-reared individuals bought from three different suppliers in 2016, 2017 and 2019. Wild A. ervi individuals were specimens sampled in protected strawberry and cucumber crops and specimens from previous studies sampled on open fields. A. ervi individuals from each origin and the number of individuals used for each analysis.We considered both ‘commercial’ and ‘wild’ i.e. dead aphids containing an immature parasitoid) in strawberry greenhouses in 2017 and 2018, in five regions of France, using the sampling design described in [Cucumis sativus) greenhouses in ‘West’ region. The collected mummies were placed individually into 1.5 mL plastic tubes waiting for parasitoids emergence in the laboratory. After emergence, adult parasitoids were placed in 96% ethanol and the parasitoid species was identified using morphological criteria before DNA extraction [Aphidius ervi were considered. Their aphid hosts were also identified based on morphological traits of the mummy [We sampled aphid mummies  and a salting-out protocol  for indiA. ervi individuals, a phylogenetic placement was performed using 450 sequences of Aphidiinae from Genebank and BOLD (A. ervi to take into account the intraspecific genetic variability. Phylogeny was constructed using Bayesian inference (hereafter noted BI) using MrBayes 3.2.6 [6, burn-in length: 105) and by Maximum Likelihood (hereafter noted ML) using PhyML 3.0 with 1000 bootstrap replicates [Cotesia flavipes was used as an outgroup [A. ervi by their position on the tree, were discarded from further analyses.The 615-bp sequences were edited using Geneious Prime 2019.2.1 and aligned with MUSCLE v. 3.8 . Alignmees 3.2.6   (GenBank: JN620613.1) as outgroup. The best evolutionary model of sequences (HKY + I) was determined using jModelTest with the Akaike information criteria corrected for small sample sizes. To represent the genetic diversity of COI in A. ervi, a Median Joining haplotype network [To detect putative clades within  network  was cons network .Aphidius ervi is a haplodiploid species , so only females were used for genotyping. Seven loci developed by Zepeda-Paulo et al. [o et al.  were ampA. ervi individuals were considered. First, we distinguished ‘commercial’ individuals from all ‘wild’ ones. Secondly, the ‘wild’ individuals were split into four putative subpopulations according to the crop where they were sampled: (1) ‘Cucumis’ (cucumber), (2) ‘Fragaria’ (strawberry), (3) ‘Medicago’ , and (4) ‘Trifolium’ (clover). Finally, we considered individuals sampled in strawberry greenhouses (i.e. ‘Fragaria’) and split them according to the sampled region  or to the aphid host species .For microsatellite data analyses, different putative populations and subpopulations of IS), and the standardized allelic richness (using a resampling method) (Ar) were calculated with the R package ‘diveRsity’ [IS were estimated using 1000 bootstrap replicates.For all putative populations and subpopulations, we estimated the average observed (Ho) and expected (He) heterozygosity using GenAlEx (v. 6.5) . The aveveRsity’ , 33. ConST and Jost’s D with the R package ‘diveRsity’ [ST can be biased downward for loci with many alleles, Jost’s D [The differentiation between each pair of putative populations and subpopulations was estimated using FveRsity’ . While FJost’s D  is best Jost’s D . Bias coa priori on the defined putative populations, we used the Bayesian clustering algorithm implemented in STRUCTURE v. 2.3.4 [Q was averaged for each individual on all the runs performed. As the reliable detection of population structure might be affected by uneven sampling [A. ervi and composed of parasitoids from Fragaria with the same parameters as on the whole dataset with values of K from 1 to 10.To explore population structure without v. 2.3.4  on the wv. 2.3.4  implemenv. 2.3.4 . To accosampling , we alsoFragaria’ subsamples, we used a Discriminant Analysis of Principal Components (DAPC) [adegenet’ [Additionally, to visualize the structure of the whole dataset and the ‘wild’ and ‘s (DAPC) . DAPC wadegenet’ , using chome/Lmax likelihood computation, where Lhome is the likelihood of an individual being assigned to the population from which it was sampled and Lmax is the maximum likelihood for all populations considered. We used the Bayesian method of Rannala and Mountain [In some sampled strawberry and cucumber greenhouses, releases of commercial parasitoids were done by producers before our sampling. To detect putative commercial parasitoids among the ‘wild’ parasitoids sampled in greenhouses of strawberries and cucumber, we performed an assignment test using GENECLASS2  with twoMountain  with an Mountain .A. ervi COI sequences from BOLD / GenBank formed a single cluster in the BI and ML trees . Within this main cluster, BI tree (and ML tree to a lesser extent) identifies clades with a posterior probability of 0.9. Three haplotypes  from databases were not grouped inside the main cluster. Parasitoids identified morphologically as A. ervi belonged to 16 COI haplotypes. Four haplotypes , including 16 individuals from strawberry greenhouses, were highly different from others and were not grouped in the main cluster of A. ervi sequences from databases. H13 grouped with another sequence of A. ervi from databases within a cluster composed of Aphidius gifuensis and Aphidius matricariae. H14, H15 and H16 formed a cluster differentiated from all other Aphidius species. As their assignment to the A. ervi species was unsure, these four haplotypes were not included in the following analyses.Most of Fig 2A). Commercial parasitoids were not structured strictly by the supplier. About 94% of commercial A. ervi belonged to the main haplotype H01  and only two individuals belonged to the haplotypes H08 and H09 . ‘Wild’ A. ervi belonged to 11 haplotypes. No clear pattern of mtDNA differentiation was associated with host plants. However, neither individuals from Fabaceae  nor from Poaceae  belonged to the most differentiated haplotypes . We found neither geographic differentiation, independently of the geographical scale considered nor genetic pattern associated with the aphid host species on haplotype networks .Among the 12 remaining haplotypes  ranged from 0.39 to 0.69 in the different putative populations  compared to ‘wild’ ones (0.50) and slightly lower compared to ‘wild’ parasitoids sampled in strawberry greenhouses (0.47). In both cases, standard errors of Ho overlapped between commercial and wild parasitoids. In all cases, Ho was lower than unbiased expected heterozygosity (uHe). Standardized allelic richness (Ar) was much lower in ‘commercial’ A. ervi (4.4) compared to ‘wild’ parasitoids (10.2) (Ar = 8.4). However, no inbreeding was detected in the ‘commercial’ population (FIS = 0.14) contrary to the ‘wild’ populations (FIS = 0.30) (Ar was similar (from 5.2 to 6.4). Inbreeding was detected in all the putative subpopulations except the ‘Cucumis’ one (Ar was slightly lower in ‘Southeast’ (3.6) and ‘Center’ (4.2) compared to ‘Southwest’ (5.0) and ‘West’ (5.2). Inbreeding was detected in all the subpopulations except the ‘Southwest’ one .Observed heterozygosity (ulations . Ho was s (10.2) . This wa = 0.30) . Among tmis’ one . Among test’ one . Among tST = 0.118; D = 0.173; Fig 3A). With a threshold of coefficient of ancestry Q > 0.8, most ‘commercial’ individuals were assigned to K1 . On the other hand, ‘wild’ parasitoids were mostly assigned to other clusters or undetermined . Using DAPC, 97% of individuals were assigned to their putative population of origin .Considering the whole dataset, differentiation indices between the ‘commercial’ and the ‘wild’ populations were high  but significantly different from zero except between the ‘Medicago’ and the ‘Trifolium’ putative subpopulations. The highest differentiation was observed for ‘Fragaria’ compared to both ‘Medicago’ and ‘Trifolium’  and 2 (ΔKwild = 12.6), then we present results for Kwild = 4 (see wild = 2 and Kwild = 3). Parasitoids from the ‘Fragaria’ putative subpopulation were mainly assigned to the cluster K1wild , this was mostly due to individuals from ‘Southeast’ and ‘Southwest’ . In ‘Cucumis’, ‘Medicago’ and ‘Trifolium’ putative subpopulations most individuals were not assigned to any cluster . DAPC confirmed that the main source of structure occurred between ‘Fragaria’ and other putative subpopulations , 82% of individuals from ‘Fragaria’ were assigned to their putative population of origin against 53% for ‘Cucumis’, 61% for ‘Medicago’ and 62% for ‘Trifolium’.Considering the ‘wild’ parasitoid individuals sampled on four different plants, differentiation indices were low . Conversely, individuals from the two northern regions ‘Center’ and ‘West’ were mostly assigned to the cluster K2Fragaria . DAPC also showed a differentiation between northern and southern regions . The percentages of assignment to the region of origin were 88% for ‘Southeast’, 97% for ‘Southwest’, 94% for ‘West’ and 93% for ‘Center’.Among pairs of locations within ‘uthwest’ . The optFragaria’, differentiation was very low  and significantly different from zero only between ‘R. porosum’ and ‘M. euphorbiae’. A similar proportion of individuals emerging from each species was assigned to K1Fragaria (47 to 52%) and to K2Fragaria . DAPC showed stronger differentiation between aphid species than STRUCTURE , 75% of individuals from ‘R. porosum’ were assigned to the correct cluster, 78% for ‘M. euphorbiae’ putative population and 71% for ‘A. malvae’ putative population.Finally, among pairs of aphid hosts within ‘A. ervi had been released. Using assignment with GENECLASS2, one individual from the ‘commercial’ putative population was considered as ‘wild’ and 13 individuals from greenhouses were considered as ‘commercial’. Among these 13 parasitoids, 7 came from greenhouses with a commercial release.Among the 171 parasitoids sampled in strawberry and cucumber greenhouses, 41 individuals were sampled in greenhouses where commercial i.e. neither the commercial/wild status, the geography, the aphid host species nor the crop plant), confirming the generalist status of A. ervi. On the other hand, using microsatellite markers, we showed a differentiation between ‘commercial’ and ‘wild’ A. ervi that may potentially explain the weak efficiency of biological control of aphids in protected strawberry crops. The hypothesis of a loss of genetic diversity in mass-reared populations leading to a low adaptation ability of the commercial A. ervi to control aphids on strawberries appeared the most likely, but further research would be needed to explore the phenotypical outcomes of such genetic diversity loss. From these results, we provide some insights to improve biological control with aphid parasitoids in greenhouse crops.Studying genetics of mass-reared and wild parasitoid populations may have implications for biological control, explaining its failure in some contexts. Here, we identified some genetic differentiation in aphid parasitoid individuals using the mitochondrial marker COI, but factors leading to this genetic structure have not been identified  [A. ervi seemed to be a complex of species, although this differentiation was observed among geographically distant populations (Europe and the Mediterranean region / Japan / Pakistan).COI gene is widely used to infer the phylogeny of species  or to exite easy . Distantdogenes)  but the dogenes) . An altedogenes) . Unruh edogenes)  already A. ervi clade, mtDNA analysis revealed low genetic variation for most individuals. Indeed, most of the parasitoids from strawberry crops and commercial insectaries but also from diverse habitats belonged to a single haplotype and nine very closely related haplotypes. However, we also identified two differentiated haplotypes that were not associated with the region, the aphid host plant, the aphid host species or the commercial/wild status. In a different portion of mtDNA (a portion of COI and COII), Hufbauer et al. [A. ervi and hypothesized the existence of subspecies or different species in A. ervi without any link to a particular host. The lack of genetic differentiation correlated with aphid host species confirms the generalism of A. ervi, which seems to be uncommon within Aphidiinae [Besides, considering only individuals belonging to the r et al.  also fouhidiinae , 51.A. ervi. Moreover, a difference in genetic diversity was found: allelic richness was reduced in ‘commercial’ parasitoids compared to the ‘wild’ ones. However, observed heterozygosity was not significantly different between ‘commercial’ and ‘wild’ parasitoids. When founding a mass-reared population, allelic richness is more sensitive to bottlenecks compared to heterozygosity while heterozygosity is highly sensitive to inbreeding [As already observed with other parasitoid species , we showbreeding . Both thA. ervi that tends to reproduce locally [A. ervi populations could be the result of a sampling bias. By sampling in several greenhouses within a given region, we could have sampled subdivided populations, artificially increasing FIS values.Interestingly, inbreeding was observed in ‘wild’ putative populations. This differential pattern can be explained by the size of the parasitoid populations and the behavior of  locally . Thus, iA. ervi collected in various agroecosystems, a differentiation among specimens from strawberry greenhouses and specimens from other plants was observed. However, this genetic differentiation among crops would be mostly related to the sampling region as no differentiation was further found when considering all specimens from northern regions. Thus, the highest differentiation identified was found between putative populations from Northern regions (‘Center’ and ‘West’) and putative populations from Southern regions of France (‘Southeast’ and ‘Southwest’). This may be the result of isolation by distance, as found by Hufbauer et al. [In r et al.  among poA. ervi specimens collected in protected strawberry crops, a weak genetic differentiation correlated with the host species was observed. This was supported by DAPC only, where individuals emerging from the three major aphid species colonizing strawberry crops clustered together with some overlap. Further sampling of individuals from each aphid species in the same location is needed to disentangle the effect of the aphid host from the sampling location. Host-associated genetic differentiation might be common in parasitoids [A. ervi parasitizing different biotypes of the pea aphid A. pisum and cereal aphids Sitobion avenae and Rhopalosiphum padi [A. ervi, host-associated differentiation might be prevented by its high phenotypic plasticity [Considering asitoids  but was hum padi , 56. In asticity  and by iasticity .A. ervi efficiency as a biological control agent [We need to be cautious not to over-interpret the consequences of the observed structure on ol agent . Geneticol agent . But we A. ervi was proposed to be a ‘true’ generalist at the scale of an agroecosystem [A. ervi providing control to strawberry greenhouses. Identifying the reservoirs of parasitoids around greenhouses would be a first step to enhance this colonization.In greenhouses where commercial parasitoids were released before sampling, we mostly found ‘wild’ parasitoids. This supports the hypothesis that most parasitism is due to wild individuals rather than released ones, even if greenhouses are relatively closed agroecosystems . Contrarcosystem . As no dA. ervi is not differentiated from its sister species A. microlophii although A. microlophii has a much more restricted host range than A. ervi [The mtDNA analysis suggested that low efficiencies in greenhouses cannot be related to the use of a highly differentiated population, with a different host range. However, differences in host ranges are not always visible using COI region . Indeed, A. ervi .A. ervi does not equally use its potential host range [A. ervi may be correlated with a reduction in the range of aphid species efficiently parasitized. It would be necessary to test experimentally the host ranges of populations to verify this assumption. Besides, released parasitoids must overcome the aphid’s defenses, mostly conferred by bacterial symbionts [A. malvae from strawberry crops infected with the bacterial symbiont Hamiltonella defensa were resistant to commercial parasitoids [A. ervi can adapt in a few generations to the protection conferred by H. defensa in aphids [A. ervi and its performance on the range of aphids present in strawberry crops (i.e. multiple aphid species and multiple symbiotic infection statuses). If this relationship is demonstrated, regular checking of genetic diversity in commercial insectaries might help to anticipate supplementation with wild individuals to maintain the potential for adaptation of commercial parasitoids.Even though no host-associated genetic differentiation has been observed here, it has been shown that st range , 57, 60.st range . So, assymbionts . It has asitoids . HoweverS1 Fig(PDF)Click here for additional data file.S2 FigCoefficient of ancestry is an average on ten runs. (a) K = 2, (b) K = 3.(PDF)Click here for additional data file.S1 Table(XLSX)Click here for additional data file.S2 Table(CSV)Click here for additional data file.


Fusarium is associated with a number of wilt, blight, scab, and rot diseases in a range of economically important staple food crops worldwide. An assessment of the genetic structure and population stratification of Fusarium incarnatum‐equiseti species complex (FIESC) pathogen populations is important to understand the evolutionary potential of such populations in adapting to environmental change. Based on intersimple sequence repeat polymerase chain reaction (ISSR‐PCR), it was found that the pathogen population was structured into three genetic clusters for which genetic differentiation was higher within than among populations. There was high intrapopulation genetic diversity for population 1 (94.63%) which consisted largely of isolates collected from North Trinidad. Populations 2 and 3 had a low level of admixture among the populations based on overall population differentiation. Population 1 accounted for the highest amount of genetic variation (95.82%) followed by populations 2 and 3. Population stratification was reflected in the dendrogram topology, which consisted of three main genetic clusters and which coincided with the outcome of Bayesian and PCoA analyses. The populations were isolated by distance, and Voronoi tessellations indicated physical or structural barriers to gene flow which contributed to restricted admixture between two of three populations. These findings suggest a high evolutionary potential for this FIESC pathogen population, the implications of which directly affect disease management strategies. High evolutionary potential for FIESC pathogen population directly affects disease management strategies in bell pepper. Recently, Xia et al. (Incarnatum species are Fusarium irregulare (FIESC 15), Fusarium sulawesiensis (FIESC 16), and Fusarium hainanense (FIESC 26); Equiseti species are Fusarium ipomoeae (FIESC 1) and Fusarium longifundum (FIESC 11). Fusarium sulawesiensis (FIESC 16) is the most common species, and F. ipomoeae (FIESC 1) is the least common species isolated from infected Trinidad bell pepper fruit  is situated off the northeast coast of South America at the southernmost end of the Lesser Antilles in the Caribbean and has a land size of 4,768 kma et al.  publisheIn view of the severity of the disease in bell pepper in Trinidad, the dispersal of fusaria via Saharan dust storms, poor management of the disease, and inability to reduce pathogen populations through chemical means, there are several biological questions that must be answered through population genetics analyses for example: Are FIESC populations differentiated? Is there gene flow among populations? Are populations clonal, sexual, or mixed? It is hypothesized that FIESC populations in bell pepper fields would be connected by some level of contemporary gene flow partly because seed and seedlings are commonly sourced and the comparatively short distance (km) among fields may not facilitate isolation by distance. As such, the level of population differentiation and genetic diversity may vary according to region, that is, North and South Trinidad but not necessarily at a finer scale, that is, according to field location. One expectation is that the genetic structure of pathogen populations would be subjected to local extinction‐recolonization events as the host is harvested, destroyed, and then re‐planted during the growing season. Trans‐Atlantic spore movement which although stochastic may be representative of unrestricted gene flow and leads to less differentiated populations. Related to these expectations is the “monoculture effect” where the association between low host species diversity and high disease incidence is a result of high homogeneity in the host population  was 0.1006, and the mean within‐population gene diversity (SH) was 0.0729. Population 1 had the highest gene diversity (h = 0.1202) followed by population 2 (h = 0.0599) and population 3 (h = 0.0386). Demographic variables such as population size appeared to be a factor in the gene diversity indices for populations. Pairwise comparisons of Nei's unbiased measures of genetic identity and genetic distance estimated for three inferred populations are given in Table ST, as it relates to nearness to fixation, for the Trinidad population (GST) was 0.2755 which indicated that the total genetic variation mainly exists within the population.The overall mean gene diversity (2.5p < 0.01) after 999 permutations based on Mantel's test  population  in the three deduced populations. These results suggest significant clonality within each of the three populations with population 3 having the highest AI value and population 1 having the lowest AI value  which consisted largely of isolates collected from North Trinidad compared to populations 2 and 3, perhaps due to larger sample size. It was reported that for o et al.  also repThere was a significant correlation between genetic distance and geographical distance based on two models assessed in this study. Infected seeds and/or host plants would have been distributed to different growing areas through anthropological agricultural activities. Mishra et al. suggesteRosenberg et al.  noted thF. graminearum in Germany and asserted that sexually produced, wind‐dispersed ascospores supported gene flow which (a) prevented substructuring within the saprophytic F. graminearum population, (b) enabled mixing between saprophytic and pathogenic populations of F. graminearum located in fields 100 km apart, and (c) resulted in shared genetic similarity of saprophytic and pathogenic F. graminearum population. Schmale and Bergstrom (Giberella zeae (Schwein.) Petch (anamorph F. graminearum Schwabe) could have originated from several locations over large geographical area and were transported through the atmosphere over long distances. Attendant to this finding, however, Cowger et al. . According to Wright  throughout the genome is indicative of population history, the breeding system, and the pattern of geographic subdivision in populations Slatkin, . PathogeF. graminearum, Fusarium pseudograminearum, and F. culmorum enabled greater adaptive flexibility of these pathogens exemplified by population shift from F. culmorum to F. graminearum in the Netherlands . Ten FIESC isolates were used in a preliminary screen to determine those ISSR primers that enabled generation of a high number of polymorphic (>100) and reproducible markers  that could be used to generate polymorphic DNA fragments for all isolates. Twenty‐two ISSR primers (Integrated DNA Technologies Inc.) were screened which included an assessment of optimal primer annealing temperature by gradient annealing temperature analysis , 0.5 μl (10 μM) of each primer (Integrated DNA Technologies Inc.), 6.5 μl of nuclease‐free water (Promega), and 5 μl of DNA template. Standard PCR amplification conditions were an initial denaturation of 5 min at 95℃; followed by 35 cycles of 30 s at 95℃, 30 s at 41℃ to 60℃, and 90 s at 72℃, with a final extension of 5 min at 72℃. The PCR reactions were carried out on Thermal Cycler 2720 (Thermo Scientific). PCR products were separated on 1.4% agarose gels stained with ethidium bromide. PCR reactions were conducted twice to confirm reproducibility of the fingerprints. Those primers that generated reproducible, distinct, polymorphic bands in repeated experiments were selected for subsequent amplification of genomic DNA from all isolates. Bands were computationally scored by gel image analysis using GelAnalyzer 2010a software . Only consistently scored bands of size range 100–2,500 bp were used under the assumption that each band represented a distinct locus and amplicons sharing the same molecular weight shared the same locus. Scored bands were transformed into a binary character matrix .Total genomic DNA was extracted from single‐spore cultures of FIESC isolates grown in potato dextrose broth for 7 days in the dark using the Maxwell‐16s Tables . These p4.3K = 1 to K = 5 where ΔK is predicted as that number of populations or genetic groups with the highest likelihood in the dataset. STUCTURE HARVESTER  was compared to determine the best fit of a set of Bayesian hierarchical models ; Data curation (lead); Formal analysis (lead); Funding acquisition (lead); Investigation (lead); Methodology (lead); Project administration (lead); Resources (lead); Software (lead); Supervision (lead); Validation (lead); Visualization (lead); Writing‐original draft (lead); Writing‐review & editing (lead).Supplementary MaterialClick here for additional data file.


There are currently over a thousand indigenous cattle breeds well adapted to local habitat conditions thanksto their long history of evolution and breeding. Identification of the genetic variations controlling the adaptation oflocal cattle breeds for their further introduction into the genome of highly productive global breeds is a matter of greatrelevance. Studying individual populations of the same breed with the use of microsatellite markers makes it possibleto assess their genetic diversity, relationships, and breed improvement potential. Although the Black Pied breed is themost common dairy cattle breed in Russia, there are only a few studies on genetic diversity in local Black Pied populationsin some Russian regions. The goal of the present study was to analyze the genetic diversity in Black Pied cattlepopulations in the Novosibirsk Region and compare them with other Russian populations; to identify significantly divergentpopulations with a view to preserving them under the programs aimed at maintaining the genetic diversity ofthe domestic Black Pied breed. DNA samples from 4788 animals of the Black Pied breed from six breeding enterprisesin the Novosibirsk Region have been studied using 11 microsatellite markers. No significant differences in geneticvariability parameters were found between individual populations. Private alleles have been identified in five out ofsix populations. Five populations have shown inbreeding coefficient values (FIS) below zero, which indicates heterozygosityexcess. The population distribution test, principal component analysis, FST and DEST values, cluster analysis,and phylogenetic analysis have revealed two populations genetically distinct from the others. Essentially, the geneticdiversity parameters of the six studied Black Pied cattle populations from the Novosibirsk Region show no significantdifferences from other Russian populations of the breed. Excess heterozygosity is observed in most breeding enterprises,which is a sign of a low inbreeding rate. To maintain the genetic diversity of the Russian Black Pied cattle, werecommend focusing on the two populations with significant genetic distinctions from the others. There are currently over a thousand indigenous cattlebreeds well adapted to local habitat conditions thanks totheir long history of evolution and breeding . All these breeds are of high economic,scientific, historical, and cultural value . Meanwhile, we can see a globaleconomically-driven replacement of local breeds by severalhigh-productivity global breeds .However, these breeds are typically poorly adapted to localhabitats and are thus unable to reveal their outstandingqualities . As a result, identificationof the genetic variations controlling the adaptationof local cattle breeds for their further introduction into thegenome of highly productive global breeds is a matter ofgreat relevance . Eventually, it will make thedevelopment of new breeds combining great productivitytraits with adaptability to various geographical regionspossible. For example, the H100Q mutation in gene NRAPdiscovered recently in Yakutian cattle seems to affect itsadaptation to extreme cold . Thisapproach has become increasingly effective since the promisingCRISPR/Cas genome editing technology was introducedinto animal husbandry .The Black Pied breed is the most common dairy cattlein Russia .Intense breeding efforts involving the four approved BlackPied cattle types well adapted to extreme climatic conditions andlocal feeds are currently ongoing in Siberia . Composite cross-breeding of Black Pied cowswith Holstein breeding bulls in 12 breeding enterprisesin Westernand Eastern Siberia has recently producedSibiryachka, a brand new high-productivity dairy breed.Highly polymorphic microsatellite loci have been widelyused as genetic markers in population and conservationgenetics for relationship identification and other purposes. In particular, microsatellites are used to analyze the origin and phylogenetic relationships of local cattlebreeds . Studying individualpopulations of the same breed makes it possible to assesstheir genetic diversity, relationships, and breed improvementpotential . However, studies on genetic diversityin local Black Pied breed populations are very few ; this is especially truefor the Novosibirsk Region, which remains poorly studiedin this regard.The goals of the present study were: to analyze the geneticdiversity of six Black Pied cattle populations fromthe Novosibirsk Region and to compare them with otherRussian populations; to identify significantly divergentpopulations to be preserved under the programs aimedat maintaining the genetic diversity of the Russian BlackPied breed.Blood samples were taken from 4788 Black Pied cows andbulls from six breeding enterprises located in the NovosibirskRegion (referred to below as populations A–F). Toanalyzethe populations’ structure and phylogenetic relationships,the Holstein cattle breed was used as a controlgroup (referred to below as HOL) .The total DNA was isolated using the COrDIS SPRINTreagent  as per the manufacturer’sinstructions. PCRs for 11 microsatellite markers  wereperformed using the COrDIS Cattle kit  as per the manufacturer’s protocol. Fragment analysisof amplified DNA was carried out using an automatedgenetic analyzer NANOPHORE-05 .The sizes of microsatellite DNA markers were calculatedin GeneMapper Software 5 .The genetic diversity parameters, F-statistics, populationdistribution test, and the significance of genotype distributiondeviation from expected Hardy–Weinberg equilibrium(HWE) were calculated using the GenAlEx 6.5 software . The allelic richness (AR) wasassessed via the rarefaction algorithm in HP-Rare software. Calculation of the pairwise FST valuesand significance check of the nonzero FIS values wereperformed using the bootstrap method adjusted for multiplecomparisons in the FSTAT software .Cluster analysis was carried out in the STRUCTURE software. The significance of differencesbetween populations was analyzed using Student’s t-testor one-way ANOVA with post hoc Bonferroni correctionin Statistica 8.0.The phylogenetic tree was built using the UPGMA approachbased on Nei’s genetic distances in the POPTREE2software . The statistical reliabilityof the phylogenetic tree was analyzed using bootstrapvalues based on 1000 permutations .The confidence threshold was set at 70 .The results of genetic variability analysis for the Black Piedcattle populations of the Novosibirsk Region can be seen inTable 1. All the microsatellite loci turned out to be highlypolymorphic and contained 105 alleles in general. The averagenumber of alleles per locus was 7.606, and the effectivenumber – 3.604. The observed heterozygosity (0.729) wasstatistically similar to the expected one (0.694).The pairwise comparison of genetic differences forbreeding enterprises, performed using Fischer’s exact testin the Genepop software, demonstrated that the cattle ofeach enterprise could be considered as a separate populationstatistically different from the others 1. The genetic variability parameters for eachof the populations can be seen in Table 2. The maximumnumber of alleles per locus (8.455) was observed in populationA, and the minimum one (6.273) – in population B.The allele enrichment and the effective number of allelesbetween populations varied between 6.087 (C) – 6.863(F) and 3.437 (B) 3.873 (D), respectively. The observedand expected heterozygosities varied from 0.701 (F) to0.755 (B) and from 0.682 (C) to 0.714 (D), respectively.The values of all the above indicators did not significantlydiffer between individual populations."http://vavilov.elpub.ru/jour/manager/files/Suppl_Aitnazarov_Engl.pdf"Supplementary Materials 1–4 are available in the online version of the paper:The private alleles, i. e. the unique alleles characteristicfor a particular animal population, were found in five ofthe six populations. In populations A–E, the inbreedingcoefficient FIS was statistically below zero. These were thepopulations where in particular loci statistically significantgenotype deviations from HWE were observed . The highest number of such loci (six) wasspotted in populations A and D. Meanwhile, the genotypedistribution of the ETH225 and TGLA126 loci matchedHWE in all the populations investigated.Analysis of the results of a population distribution testdemonstrated that, on average, 45.7 % of the animals hadbeen properly assigned . However, forpopulation B this score reached 70.8 %, which evidences this population being significantly different from the others.Principle component analysis (PCA) of the FST valuesshowed that population B was significantly different fromthe others in the first component reflecting 36.73 % of thegenetic variability of the whole dataset . As for thesecond-component distribution responsible for 27.61 % ofgenetic variability, it was most prominent for population D.The highest degree of genetic differentiation, both forJost’s differentiation and the FST fixation indices, was betweenpopulations B and D . The closestpopulations in this respect were A and C.The results of genetic clustering in STRUCTURE demonstratedthat at k = 2, the population of Black Pied andHOL breeds was distributed between two different clusters(Table 3), where HOL had the highest values of similaritycoefficient Q in one of the clusters. The Q values for allthe Black Pied populations (except for D) were statisticallylower than those for the HOL animals.In the UPGMA phylogenetic tree built using the Nei distances,populations B and D belonged to different branches,which was statistically confirmed . All the otherpopulations including the control HOL population formeda single clusterAnalysis of 11 microsatellite loci from the whole sampleof Black Pied cattle of the Novosibirsk Region revealed105 alleles, which is lower than the number obtained afterinvestigating 13 224 Holsteinized Black Pied animals inthe Sverdlovsk Region . The 15 locithat included the microsatellites investigated in our studycontained 164 alleles, but the frequency of 38 of them didnot exceed 0.1 %. On the other hand, a study of 36 animals from Poland produced just 76 alleles for a similar set of loci(10 out of 11 markers matched) . Thus,the observed differences may be related to the sample sizeand/or the number of microsatellite loci used.The TGLA122 locus was characterized by the highestaverage number of alleles per locus (12.833). A similarscore for this locus  was obtained in a studyinvestigating the Black Pied breed from the Pskov Region. The lowest average number ofalleles per locus (5.333) was found in TGLA126, whichcorrelates with the analogous parameter in the Black Piedbreed from the Sverdlov Region  . The highest (5.760) and lowest (2.160) numbers ofeffective alleles were detected in the TGLA122 and SPS115loci, which also correlates with the results obtained byM.V. Modorov et al. (2021). The values of observed andexpected heterozygosity (0.729 and 0.694) obtained for oursample were similar to those for the Black Pied cattle fromthe Sverdlovsk Region (0.73 and 0.72)  but lower than the numbers for the pedigree bulls ofthe same breed (0.779 and 0.751) .It is known that the genetic data of 25–30 randomly selectedanimals from a population are sufficient for reliableestimation of the population’s allele frequency, expectedheterozygosity and genetic distances .In our study, the sampling size significantly exceeded thementioned threshold. The results of Fischer’s exact testdemonstrated that all the six samples investigated could beregarded as separate populations ,which enabled us to shift to a more detailed analysis oftheir genetic differences.Such parameters as the number of effective alleles, alleleenrichment, observed/expected heterozygosity are widelyused to estimate genetic variations between populationssince they do not depend on a sampling size . In our study, these parametersdid not have statistically significant differences between any population pairs investigated (see Table 2),which may be since all the considered breeding enterprisesrely upon semen production from the same sources.In this respect, our results are in good correlation withthose of M.V. Modorov et al. (2021) who investigated29 herds of Holsteinized Black Pied cattle from the SverdlovskRegion and found no statistically significant geneticdifferencesfor 27 of them. Unfortunately, using microsatellitemarkers within a single breed for cattle populationmonitoring, the authors, as a rule, ignore statistical methodswhen comparing the genetic variability parameters . In our study, private alleleswere found in all populations, except population B, which isprobably due to the size of the population (N = 65). In thisrespect, the Black Pied cattle from the Novosibirsk Regionsignificantly outmatched the Black Pied animals from theRepublic of Belarus, where private alleles were detectedonly in three populations out of nine .Inbreeding coefficient FIS is known to indicate heterozygosityreduction due to nonrandom coupling . At FIS > 0, there is a deficiency of heterozygousindividuals (inbreeding); while at FIS < 0, such individualsare in excess (outbreeding). At FIS = 0, mating becomesHWE-random. In our study for most of the populations(A–E), the inbreeding coefficient was significantly belowzero, meaning the heterozygotes were excessive. Consequently,populations A–E demonstrated statisticallysignificant deviations from HWE in some of the locusgenotypes , which is a good correlationwith the result presented above. The most probablereason for this effect might be implementation of a matingsystem  aimed toreduce inbreeding . At the same time,such factors as population’s finite size, nonrandom mating,selection effect, etc. can not be completely excluded.In the population distribution test performed in ourstudy, on average 45.7 % of animals were correctly distributedin their original groups ,which matched well with the 48 % distribution in a studyof 16 herds of the Limousin breed in Hungary . However, for population B, the distributionparameter was 70.8 %, which evidenced this populationbeing significantly different from the others.The results of subpopulation fixation index (FST)PCA analysis demonstrated that populations А, С, Е and Fformed a compact group , for which the FSTvalues varied from 0.004 to 0.008 .Populations B and D are further from this group for thefirst and second components, respectively. The longestgenetic distance, as per fixation index, was observedbetween populations B and D and comprised 0.013. Theobtained genetic distances range was in good correlationwith the data for single nucleotide polymorphisms (SNPs) obtained with an Illumina BovineSNP50 chip assay for theHolsteinized Black Pied cattle of six breeding enterprisesin the Leningrad Region (0.002–0.012) and the populations of Jersey cattle in the USA, Canadaand the UK (0.006–0.016) .According to S. Write’s classification, genetic differentiationis considered insignificant, if FST does not exceed0.05 . However, V.M. Kuznetsov statesthat it is a differentiation of less than 0.01 that can be regardedas ‘insignificant and negligible’, so interpretationof the above-mentioned results can be a complex issue. Nevertheless, T.V. Galinskaya et al.assume that interpretation of the FST value is more complexthan just referring to the mentioned authors . In their opinion ‘what is more important iswhether we could detect a statistically significant geneticdifferentiation (FST >0) or not’.The permutation test in our study demonstrated that allthe obtained FST values were statistically valid ( p < 0.01), which confirms the genetic isolationof populations B and D.Although FST is widely used to assess genetic populationdifferentiation, its application for multiallelic and multilocusmarkers such as microsatellites is often criticized. For thesemarkers, several alternative statistical methods have beensuggested such as Jost’s differentiation index (DEST), whichaccounts for changes in effective number of alleles . FST and DEST are believed to complementeach other and be applied jointly . In our study, the DEST distancesstatistically correlated with the FST estimations . For both parameters, populations B and Dwere genetically the most distant.Cluster analysis revealed that the Black Pied and Holstein(HOL) populations were distributed between two differentclusters (see Table 3), which confirms their genetic affinity. The similaritycoefficient values for all the populations except D turnedout to be much lower than that of HOL, which evidencesdifferent HOL pedigree levels in the investigated BlackPied populations .Phylogenetic analysis distributed the Black Pied populationsinto three groups . One group includedpopulations А, С, Е and F that were close to HOL. PopulationsB and D formed two independent statistically verifiedbranches. The result confirmed the genetic insulation ofpopulationsB and D, which we also confirmed with theresults of population distribution test, PCA, FST/DESTindex analysis and the results of cluster analysis presentedabove.It is generally believed that to preserve a breed as a selectionmaterial, one has to sustain all its genetic pool becausein most cases it is unknown which particular genes andtheir combination determine the economic characteristicsof the breed . According to the authors, the purposeof a biodiversity preservation program is to ‘sustain thediversity of the alleles a species (breed) has as well as tosupport the process of accumulation and potential preservationof newly appearing mutant alleles as an importantsource of constant evolution and improvement in animals’.The results of the tests performed in our study confirmthe genetic insulation of populations B and D from theother populations investigated, so these two populations,above all else, have to be used to preserve the genetic poolof the Black Pied breed.Thus, the genetic variability parameters of the six populationsof Black Pied cattle from the Novosibirsk Regionhave had no significant differences from other Russianpopulations of this breed. Most of the breeding enterprisesinvolved in the study have heterozygote excess due to lowlevelinbreeding. Our recommendation to those developingthe programs aimed at preserving the genetic diversityof the Russian Black Pied cattle is to use animals of twopopulations, the genetic characteristics of which differsignificantly from all others.The authors declare no conflict of interest.Agung P.P., Saputra F., Septian W.A., Lusiana Zein M.S., SulandariS., Anwar S., Wulandari A.S., Said S., Tappa B. Study ofgenetic diversity among Simmental cross cattle in West Sumatrabased on microsatellite markers. Asian-Australas. J. Anim. Sci.2016;29(2):176-183. DOI 10.5713/ajas.15.0155.Arzhankova Yu.V., Mosachikhina I.A., Kharitonov A.V. Genetic featuresof Black Pied and cross-breeding cattle by microsatellite loci.Izvestiya Velikolukskoy Gosudarstvennoy Sel’skokhozyaystvennoyAkademii= Bulletin of the Velikie Luki State Agricultural Academy.2015;1:7-11. 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Trans-Eurasian or Altaic language family, most of the Mongolic and Tungusic languages were mainly spoken in northern China, Mongolia, and southern Siberia, but some were also found in southern China. Previous genetic surveys only focused on the dissection of genetic structure of northern Altaic-speaking populations; however, the ancestral origin and genomic diversification of Mongolic and Tungusic–speaking populations from southwestern East Asia remain poorly understood because of the paucity of high-density sampling and genome-wide data. Here, we generated genome-wide data at nearly 700,000 single-nucleotide polymorphisms (SNPs) in 26 Mongolians and 55 Manchus collected from Guizhou province in southwestern China. We applied principal component analysis (PCA), ADMIXTURE, f statistics, qpWave/qpAdm analysis, qpGraph, TreeMix, Fst, and ALDER to infer the fine-scale population genetic structure and admixture history. We found significant genetic differentiation between northern and southern Mongolic and Tungusic speakers, as one specific genetic cline of Manchu and Mongolian was identified in Guizhou province. Further results from ADMIXTURE and f statistics showed that the studied Guizhou Mongolians and Manchus had a strong genetic affinity with southern East Asians, especially for inland southern East Asians. The qpAdm-based estimates of ancestry admixture proportion demonstrated that Guizhou Mongolians and Manchus people could be modeled as the admixtures of one northern ancestry related to northern Tungusic/Mongolic speakers or Yellow River farmers and one southern ancestry associated with Austronesian, Tai-Kadai, and Austroasiatic speakers. The qpGraph-based phylogeny and neighbor-joining tree further confirmed that Guizhou Manchus and Mongolians derived approximately half of the ancestry from their northern ancestors and the other half from southern Indigenous East Asians. The estimated admixture time ranged from 600 to 1,000 years ago, which further confirmed the admixture events were mediated via the Mongolians Empire expansion during the formation of the Yuan dynasty.As a major part of the modern  Based oquencing . Especiaquencing . Becausequencing . Previou1, while the settlement of the Tungusic-speaking Manchus in Guizhou was related to the implementation of military plans by the Qing Dynasty. However, the genetic profile of the Manchus and Mongolian speakers in southern China is still very much in its infancy. Here, we generated genome-wide data at nearly 700,000 SNPs in 26 Mongolian and 55 Manchu individuals collected from three populations in Guizhou province and compared with available data of both modern and ancient East Asian individuals to explore their fine-scale population genetic structure.Guizhou province, located at the eastern end of the Yunnan-Guizhou Plateau, harbors a diverse array of ethnic groups and linguistic backgrounds including the Mongolic and Tungusic languages . Accordivia the Nanodrop-2000. Infinium® Global Screening Array  was used to genotype approximately 700,000 SNPs, which covered SNPs from the autosome, Y-chromosome, and merohedral DNA. Raw data in the binary form  were initial filtered using PLINK 1.9  dataset  and the ulations . The 124We carried out the principal component analysis (PCA) using the smartpca package built-in EIGENSOFT . We perfK = 2 and K = 20 in 100 bootstraps with different random seeds. We used the unsupervised ADMIXTURE approach, in which allele frequencies for unadmixed ancestral populations are unknown and are computed during the analysis. We used point estimation and terminated the block relaxation algorithm when the objective function delta < 0.0001. We chose the best run according to the highest log-likelihood. We used cross-validation to identify an “optimal” number of clusters. We observed the lowest CV error at K = 11.To further explore the ancestry composition and genetic similarity of our studied groups with geographically close ancient and present-day populations, we carried out model-based clustering analysis using ADMIXTURE 1.23  by combiqp3pop in ADMIXTOOLS  to assess the shared genetic drift between reference populations 2 and reference populations 2 since their separation from an African outgroup population of Mbuti using the default parameters. Then, we used the qp3pop to perform the admixture-f3  to explore the admixture signatures in our studied Guizhou Manchus and Mongolian samples with different Eurasian ancestral source candidates, where a significant negative-f3 value with |Z-score| larger than three denoted that the targeted population was an admixture between two parental populations.We used the MIXTOOLS  to perfof4 statistics of the form f4 using the qpDstat program in ADMIXTOOLS with default parameters and estimated standard errors using the block jackknife  to assign the Y-chromosomal paternal lineage following the basic regulations reaccommodated via the International Society of Genetic Genealogy3. We classified the maternal mitochondrial haplogroups used HaploGrep 2 , Guizhou Manchus shared more alleles with Han Chinese, She, Ami, and Miao. When X represented ancient individuals, Guizhou Manchus was found to share more alleles with Neolithic-Iron Age Yellow River farming populations including Haojiatai, followed by Jiaozuoniecun and Luoheguxiang ancients. Guizhou Mongolians shared more alleles with Han Chinese, Ami, ancient Gongguan samples from Taiwan, She, and Miao  to model possible admixtures, where X and Y were East Asian populations that might be the source candidates for modeling the admixture in Guizhou Manchus or Mongolians when getting negative Z scores. However, we observed only one significant signal of admixture (Z < −3) in the Mongolian_Bijie when using Tibetan as the northern East Asian source and Austronesian-speaking Igorot people as the southern East Asian source . We observed significant negative f4 values in f4      when we , Mbuti) , suggest, Mbuti) .f4     . Further, Mbuti) . Compare, Mbuti) . Similar, Mbuti) .qpWave and qpAdm methods to model their ancestry. We used all available ancient northern populations  as the northern sources and Iron Age Hanben samples from Taiwan as the southern sources to estimate the admixture proportions. The Southern East Asian Hanben-like ancestry proportion spanned from 16.5 to 35.7% when using Yellow River farmers as the northern source, whereas the proportion reached 56.7% when using Yumin_EN (hunter–gatherers in Inner Mongolia)  . To explongolia) .f statistics–based analysis that Guizhou Manchus and Mongolians had experienced genetic influence from surrounding southern Indigenous populations since their separation from northern ancestors and migrated to Guizhou.In the TreeMix analysis , we obseqpGraph to reconstruct the deep evolutionary history of the Mongolians group in Guizhou. We used two ancient Neolithic samples from the Mongolians Plateau as the northern source and used the samples from the middle Neolithic Xiaowu site as a representative of the ancient Yellow River millet farmers. We used Iron Age Hanben samples from Taiwan as the southern source. The reconstructed phylogeny showed that the genetic contribution of the ancient northern East Asians to the Bijie Mongolians is 44%, whereas the proportion from the southern East Asians is approximately 56% , and B4, B5a, F, D4, and M7 were the dominant maternal lineages. We obtained 14 terminal paternal lineages among 43 males with frequencies ranging from 0.0233 to 0.3953 (O1b1a2a1-F1759/F2064/CTS5847/CTS8414/Z24393/F3314/F3323/CTS118 90/F3478′: 17). We also identified some Manchus samples with paternal haplogroup C2c1b7∼-Z45293′. For the studied Mongolians, we identified 23 different maternal lineages with frequencies ranging from 0.0384 to 0.0769 (M7b1a1e1: 3), with A5b1, B5a1c1, and M7b1a1 identified at least twice among the Mongolian samples. The high-frequency paternal lineages of our Mongolian samples are O1b1a1a1a1a2a1-Z24050′ (11) and O1a1a2a1-Z23266 (6) . We alsoStrong associations between population genetic structure and linguistic similarity were subsequently evidenced among Afroasiatic, Nilo-Saharan, Niger-Congo, and Khoisan language families in Africa , as wellf3 statistics that Guizhou Manchus and Mongolians derived ancestry from both northern and southern East Asia. But for the northern Mongolic and Tungusic–speaking populations, we can find significant admixture signatures with one source from East Asians and the other from western Eurasians or northern Siberians. The genetic distance-related indexes (Fst and outgroup f3 statistics) consistently supported the studied Guizhou populations having a strong southern East Asian affinity, but northern Mongolic and Tungusic speakers showing a clear northern East Asian affinity. We observed the Y-chromosome and mtDNA haplogroups in Guizhou Manchus and Mongolians are the lineages that are frequent in southern China, showing a different genetic profile from that in northern Mongolic and Tungusic speakers. Recent genetic studies focused on northern Mongolian and Manchu populations found that paternal lineages of C2a and C2b were widely distributed in these populations, which is rarely found in our focused Guizhou Manchus and Mongolians.Here, we presented the fine-scale genetic structure of Mongolic and Tungusic–speaking populations (Mongolians and Manchus) in Guizhou and reconstructed their demographic history. We observed significant genetic differences between southern Mongolic and Tungusic speakers from Guizhou and their counterparts from northern East Asia . We observed two different genetic clines among all Mongolic and Tungusic–speaking populations in the PCA plots, and Guizhou populations have deviated to the southern East Asian clusters comprising Austronesian, Austroasiatic, and Tai-Kadai populations, as well as close to Hmong-Mien clines. However, northern Mongolic and Tungusic speakers formed another genetic cluster that was located far away from the southern ones. We identified different ancestry components in northern and southern populations in the model-based ADMIXTURE results with the studied Guizhou populations sharing similar genetic profiles with southern East Asians. We observed suggestive evidence in f4 values in f4 . The qpGraph-based phylogeny with admixture events further showed a large proportion of the ancestry of Guizhou Mongolians derived from Yellow River farmers, who were genetically close to Mongolians Neolithic populations. The ALDER-based estimates of admixture times ranged from 500 to 1,500 years ago, which was consistent with the time of Mongolians Empire expansion and the formation of the Yuan dynasty. The excess affinity of Guizhou Manchus and Mongolians with northern populations, when compared with Guizhou Indigenous groups, highlights the role of the southern expansion of northern Mongolians.Furthermore, we also identified the genetic differences between studied Manchus and Mongolians with southern East Asians. Our studied Manchus and Mongolians did not group together with geographically close Guizhou populations, such as Guizhou Han, Chuanqing, Gejia, Gongjia, and Xijia. Compared with southern East Asians, Guizhou Manchus and Mongolians shared excess alleles with northern Mongolic/Tungusic–speaking populations, as shown in significant negative via genome-wide data or traditional genetic markers from southwestern populations  can be found below: The studies involving human participants were reviewed and approved by the Medical Ethics Committee of Guizhou Medical University and Xiamen University . The patients/participants provided their written informed consent to participate in this study.C-CW and JH designed this study. JC, GH, and C-CW wrote the manuscript. QW, ZR, HLZ, YL, MY, JJ, and JH collected the samples. QW, ZR, HZ, JJ, YL, MY, JC, and JH conducted the experiment. JZ, GH, JG, XY, JC, KZ, RW, HM, and C-CW analyzed the data. All authors reviewed the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


The Hui minority is predominantly composed of Chinese-speaking Islamic adherents distributed throughout China, of which the individuals are mainly concentrated in Northwest China. In the present study, we employed the length and sequence polymorphisms-based typing system of 231 molecular markers, i.e., amelogenin, 22 phenotypic-informative single nucleotide polymorphisms (PISNPs), 94 identity-informative single nucleotide polymorphisms (IISNPs), 24 Y-chromosomal short tandem repeats (Y-STRs), 56 ancestry-informative single nucleotide polymorphisms (AISNPs), 7 X-chromosomal short tandem repeats (X-STRs), and 27 autosomal short tandem repeats (A-STRs), into 90 unrelated male individuals from the Chinese Northwest Hui group to comprehensively explore its forensic characteristics and genetic background. Total of 451 length-based and 652 sequence-based distinct alleles were identified from 58 short tandem repeats (STRs) in 90 unrelated Northwest Hui individuals, denoting that the sequence-based genetic markers could pronouncedly provide more genetic information than length-based markers. The forensic characteristics and efficiencies of STRs and IISNPs were estimated, both of which externalized high polymorphisms in the Northwest Hui group and could be further utilized in forensic investigations. No significant departure from the Hardy–Weinberg equilibrium (HWE) expectation was observed after the Bonferroni correction. Additionally, four group sets of reference population data were exploited to dissect the genetic background of the Northwest Hui group separately from different perspectives, which contained 26 populations for 93 IISNPs, 58 populations for 17 Y-STRs, 26 populations for 55 AISNPs (raw data), and 109 populations for 55 AISNPs . As a result, the analyses based on the Y-STRs indicated that the Northwest Hui group primarily exhibited intimate genetic relationships with reference Hui groups from Chinese different regions except for the Sichuan Hui group and secondarily displayed close genetic relationships with populations from Central and West Asia, as well as several Chinese groups. However, the AISNP analyses demonstrated that the Northwest Hui group shared more intimate relationships with current East Asian populations apart from reference Hui group, harboring the large proportion of ancestral component contributed by East Asia. For recent years, the extensive applications of DNA analysis technologies have made it a crucial tool in forensic investigations. To date, the genomic DNA from biological samples is predominantly dissected by PCR and capillary electrophoresis (CE)-based method to reveal the length variations in genetic markers, such as short tandem repeats (STRs). Further, the DNA sequencing technology also serves as an important role in providing comprehensive information of the target DNA in forensic applications. Conventional Sanger sequencing, initially introduced in the 1970s, has enabled enormous progress in the fields of molecular biology, genomics, and genetics and been regarded as the standard sequencing technology in the forensic investigations . Yet, thThe ForenSeq™ DNA Signature Prep Kit , a newly developed MPS-based commercial kit, is a length and sequence polymorphisms-based typing system for three kinds of STRs and three types of single nucleotide polymorphisms (SNPs), which can simultaneously detect 231 genetic molecular markers in a single reaction on MiSeq FGx™ Forensic Genomics System . This kit provides two different primer mixes, including primer mixes A and B. Primer mix A is designed to detect amelogenin, 27 autosomal STRs (A-STRs), 24 Y-chromosomal STRs (Y-STRs), 7 X-chromosomal STRs (X-STRs), and 94 identity informative SNPs (IISNPs); and primer mix B contains primer mix A plus the primers for 22 phenotypic informative SNPs (PISNPs) and 56 biogeographical ancestry informative SNPs (AISNPs) . To dateThe Chinese Hui ethnic group is one of the national minorities officially recognized by the People’s Republic of China and widespread throughout China, including 34 provincial-level administrative regions. According to the population distribution, the Chinese Hui group is more concentrated in Northwest China. Intriguingly, the Hui group occupies a special existence among the Chinese ethnic minorities, of which the individuals are portrayed as Muslims who appear culturally and linguistically similar to the Han population. Currently, population genetic studies concentrated on limited kinds of genetic markers have been conducted on Hui groups from Chinese different regions. For example, Zou et al. detected the genetic polymorphisms of 30 insertion/deletion (InDels) in the Guangxi Hui group . HLA claIn fact, different opinions on the genetic origin and ancestral history of the Chinese Hui group have existed for years. Two kinds of hypotheses have been proposed to infer the historical formation of the Chinese Hui group, which are demic diffusion and cultural diffusion hypotheses . In addiIn total, 90 blood samples from unrelated healthy Hui male individuals from Northwest China were collected. All the participants provided their written informed consents prior to sample collection. The present research was conducted according to the ethical guidelines of the Xi’an Jiaotong University Health Science Center and further authorized by the Ethical committees of the Xi’an Jiaotong University Health Science Center .Library preparation was performed in accordance with the recommendation of the ForenSeq™ DNA Signature Prep Kit  . The firobs), expected heterozygosity (Hexp), polymorphism information content (PIC), power of discrimination (PD), exclusion probability (PE), match probability (PM), typical paternity index (TPI), and the Hardy–Weinberg equilibrium (HWE). Specifically, the Hobs was utilized to measure the genetic polymorphic degree of a specific loci, which is described as the observed proportion of heterozygous genotypes detected in a population , interpretation threshold (IT), stutter filter (SF), and intra-locus balance (IB) were utilized to estimate the data quality . The optpulation . The Hexnder HWE . The PICnder HWE , which inder HWE . The PM nder HWE . Closelynder HWE . The PE nder HWE . For X-Snder HWE . In termhttps://www.internationalgenome.org/data), raw data of 17 Y-STRs for 58 populations collected from previous studies or the Y Chromosome Haplotype Reference Database (YHRD) database (https://yhrd.org/), raw data of 26 populations for 55 AISNPs gathered from the 1000 Genomes Project, and allele frequencies of 109 populations for 55 AISNPs assembled from previously published studies  based on the allele frequencies of these 93 IISNPs. We also conducted a PCA plot of these populations at the individual level using the PLINK software v1.9 based on the raw data of these 93 IISNPs , and a rooted neighbor-joining (NJ) tree was further constructed using the MEGA software v6.0  statistic based on the allele frequencies of 93 IISNPs . Rst is developed based on a stepwise mutation model to assess the genetic differentiations among populations  16.0 software. Eventually, the ancestral structure of the Northwest Hui group based on 55 AISNPs was explored using two sets of population data as the references. The PCA plot on individual level and STRUCTURE analysis were performed using the XLSTAT program (https://www.xlstat.com/en/) and ADMIXTURE software v1.3  based on both length- and sequence-based polymorphisms are presented in obs values for length- and sequence-based STRs ranged from 0.6000 to 0.9222 and from 0.6000 to 0.9556, respectively, of which the lowest values were all observed at TPOX locus and the highest at D12S391 locus. The Hexp values for the length-based STRs spanned from 0.604 at TPOX locus to 0.906 at Penta E locus, and for sequence-based STRs varied from 0.604 at TPOX locus to 0.9200 at D12S391 locus. The average Hobs and Hexp values for the length-based polymorphisms were 0.7798 (±0.0744) and 0.7845 (±0.0670), respectively. For the sequence polymorphism level, the average Hobs and Hexp values were 0.7999 (±0.0829) and 0.8073 (±0.0747), respectively. The lowest PIC values were detected at TPOX locus with the value of 0.5387 for both length- and sequence-based polymorphisms, whereas the highest values of length- and sequence-based polymorphisms were 0.8928 at PentaE locus and 0.9095 at D12S391 locus, respectively. The TPOX locus revealed the lowest PE value for both length- and sequence-based STRs with the value of 0.2909, and the D12S391 locus exhibited the highest PE values for both length- and sequence-based STRs with values of 0.8410 and 0.9096, respectively. The combined PE values for the length- and sequence-based genotypes were 1–3.4332 × 10–11 and 1–1.0266 × 10–12, respectively. The PD values of all A-STR loci were larger than 0.7760 at TPOX locus for both length- and sequence-based polymorphisms, while all the PD values were less than 0.9741 at PentaE locus based on length polymorphisms and less than 0.9788 at D21S11 locus based on sequence polymorphisms. Additionally, the combined PD value observed at the length and sequence levels were 1–3.0634 × 10–30 and 1–8.0118 × 10–33, respectively. The PM values were in the range from 0.0259 (PentaE) to 0.2240 (TPOX) for length-based STRs and from 0.0212 (D21S11) to 0.2240 (TPOX) for sequence-based STRs. The TPOX locus showed the lowest TPI value as 1.2500 for both length- and sequence-based STRs, and the D12S391 locus presented the highest TPI values as 6.4286 for length-based STRs and 11.25 for sequence-based STRs.For the Northwest Hui group, the allelic polymorphisms and forensic parameters of 27 A-STR loci calculated on the basis of sequence- and length-based polymorphisms are presented in Further, the haplotypic results and forensic parameters of 24 Y-STRs revealed from the perspective of length and sequence levels are presented in obs and Hexp values varied from 0.1889  to 0.5778 (rs722290) and from 0.1900 (rs2056277 and rs740910) to 0.5030  with the average values of 0.4249 (±0.0958) and 0.4330 (±0.0842), respectively. The PIC values varied from 0.1710 at rs2056277 and rs740910 loci to 0.3750 at rs891700 locus with an average value of 0.3343 (±0.0532). The PD values spanned from 0.3242 (rs2056277) to 0.6649 (rs214955) with average value of 0.5708 (±0.0795), and the combined PD value for the 94 IISNPs was 1–7.3652 × 10–36. The PE values ranged from 0.0268  to 0.2651 (rs722290) with average value of 0.1403 (±0.0579). The lowest PM value was 0.3351 at rs214955 locus, whereas the highest value was 0.6758 at rs2056277 locus; and the average value was 0.4292 (±0.0795). The TPI values were in the range from 0.6164  to 1.1842 (rs722290), and the average value was 0.8916 (±0.1354).The allele frequencies and forensic parameters of 94 IISNPs are presented in The sequence- and length-based alleles and corresponding frequencies of 58 STRs  for the Northwest Hui group are listed in The phenotypic SNPs utilized in this study mainly focus on pigmentation, including hair and eye colors. The predicted phenotype results for male individuals from the Northwest Hui group are displayed in In statistic, were constructed, with the intention of determining the genetic discrimination abilities of these 93 IISNPs among the Northwest Hui group and reference populations, as well as the individual identification performances of these IISNPs in the Northwest Hui group.The genetic differentiations between the Northwest Hui group and worldwide reference populations were analyzed based on the overlapping IISNPs loci. The reference data were obtained from 2,504 individuals of 26 populations in the 1000 Genomes Project. In contrast with the 94 IISNPs provided by the ForenSeq™ DNA Signature Prep Kit, one locus named rs938283 was not found in the 1000 Genomes Project, thus leading to the use of 93 overlapping IISNPs in the following analyses. Serial plots, including a heatmap of ancestral allele frequencies, a NJ tree, two PCA plots, and a plot of population-specific divergences based on The allele frequencies of 93 IISNPs were utilized to generate a cluster heatmap, facilitating the intuitive visualization of polymorphic distributions for these 93 same IISNPs in the Northwest Hui group and reference populations. As presented in DA values in DA = 0.0068) and CHS (DA = 0.0069) populations. Obviously, populations from Africa revealed the largest genetic distances from the Northwest Hui group with the DA values ranging from 0.0199 to 0.0307.To further inspect whether the IISNP genetic markers could reveal the genetic relationships between the Northwest Hui group and worldwide reference populations, two PCA plots and one NJ tree were constructed. As presented in In statistic. In In value at each IISNP locus, thus, there were five intercontinental In values at each IISNP locus. African populations generated the largest In values at 30 IISNP loci, ranging from 0.0200 at rs901398 locus to 0.2105 at rs1335873 locus, in comparison with the remaining intercontinental populations. African populations with relatively high In values always tended to separate from American, East Asian, European, and South Asian populations, especially at four loci  revealing the highest discrepancy In values (In > 0.1). Additionally, American populations encompassed 13 loci showing the largest discrepancy values, and the In values of American populations at these 13 loci varied from 0.0004 at rs13218440 locus to 0.0219 at rs354439 locus. A total of 19 loci showed the largest discrepancy values in East Asian populations, ranging from 0.0005 at rs576261 locus to 0.0715 at rs2040411 locus. European and South Asian populations exhibited the largest discrepancy values at 11 and 20 loci, respectively, of which the In values were in the range from 0.0015 (rs6955448) to 0.0623 (rs1886510) and from 0.0018 (rs722290) to 0.0403 (rs987640), respectively. The In values in American populations were in the range from 0.0000 at six loci  to 0.0389 at rs740910 locus with an average value of 0.0052 (±0.0084). East Asian populations generated In values ranging from 0.0000 at seven loci  to 0.0715 at rs2040411 locus with an average value of 0.0091 (±0.0157). Nine loci, including rs2831700, rs2107612, rs445251, rs2342747, rs13218440, rs321198, rs993934, rs3780962, and rs2830795, presented the lowest discrepancy values (In = 0.0000) in European populations, while rs722098 locus yielded the highest discrepancy value (In = 0.0858), and the average In value was 0.0245 (±0.0190). The In values in South Asian populations varied from 0.0000 at eight loci  to 0.0500 at rs1335873 locus with an average value of 0.0140 (±0.0118). The African populations offered the lowest discrepancy value (In = 0.0000) at eight loci , whereas the highest value was observed at rs1335873 locus (In = 0.2105), and the average value was 0.0198 (±0.0373).Eventually, to determine the ability of the 93 IISNP loci on distinguishing populations, a plot of population-specific divergences for the five intercontinental clusters was constructed based on the The patrilineal genetic data of 59 populations, the Northwest Hui group and 58 reference populations, were employed in this study, which could be classified into six different biogeographical group sets, including 44 populations from East Asia, seven populations from West Asia, three populations from Central Asia, two populations from Africa, two populations from Europe, and one population from Australia. A total of 17 shared Y-STR loci were employed from these 59 populations, including DYS19, DYS389I, DYS389II, DYS390, DYS391, DYS392, DYS393, DYS385a, DYS385b, DYS437, DYS438, DYS439, DYS448, DYS456, DYS458, DYS635, and YGATAH4. It is worth mentioning that three loci  from the abovementioned 17 Y-STR loci were absent in the 24 Y-STR markers from the ForenSeq™ DNA Signature Prep Kit. The genotype profiles of these three loci in the Northwest Hui group were replenished using the PCR and CE-based method.Rst values calculated based on the raw Y-STR data from the worldwide populations. The gradually deepening yellow indicated the increasing Rst values, whereas the deepening blue indicated the decreasing Rst values. In the heatmap, populations were labeled according to different linguistic families, containing eight populations from the Altaic family in yellow, two populations from the Afro-Asiatic family in grey, five populations from the Indo-European family in red, 42 populations from the Sino-Tibetan family in blue, and two populations from the Niger-Congo family in pink. All the Hui groups from Chinese different regions, including the studied Northwest Hui group (NWH), Ningxia Hui (NXH), Shaanxi Hui (SAXH), Henan Hui (HNH), Gansu Hui (GSH), Qinghai Hui (QHH) and Yunnan Hui (YNH), except for Sichuan Hui (SCH) were primarily clustered together, then gathered with the populations from East Asia, and subsequently grouped with Central and West Asian populations in deeper blue color.As shown in Rst values between the Northwest Hui group and the reference populations was plotted on the right-hand side of the heatmap. The Northwest Hui group retained extremely low genetic distances (Rst < 0.01) with other reference Hui groups from Chinese different regions, with the exception of SCH. In detail, four reference Hui groups from Chinese different regions, including GSH (Rst = −0.0068), HNH (Rst = −0.0022), QHH (Rst = −0.0082), and YNH (Rst = −0.0081), displayed negative Rst values; two reference Hui groups, NXH (Rst = 0.0041) and SAXH (Rst = 0.0062), showed extremely low genetic distances; and one reference Hui group, SCH (Rst = 0.0371), exhibited the lower genetic differentiation (0.01 < Rst < 0.05) from the Northwest Hui group. Intriguingly, the studied Hui group revealed clearly lower genetic differentiations from the Central and West Asian populations, especially for East Anatolian Turkey (EAT) (Rst = 0.0038). It is worth mentioning that one Chinese group named Gansu Dongxiang (GSDX) (Rst = 0.0072) also exhibited extremely low genetic distance with the Northwest Hui group.To display the genetic relationships more clearly, a histogram of pairwise Rst values. In To further verify the genetic relationships between the Northwest Hui group and the reference populations, we conducted a MDS analysis for all the populations without the reference Hui groups based on pairwise In the present study, we employed two sets of population data on the basis of the 55 overlapping AISNPs to uncover biogeographical ancestral information for the Northwest Hui group, including 26 reference populations from the 1000 Genomes Project and 109 reference populations from previous studies.The PCA analysis of the Northwest Hui group and the 26 reference populations was constructed, from which the raw population data of 55 same AISNPs were available. To obtain a more intuitive display, the first two principal components were adopted to perform the PCA plot. As presented in K = 2 to K = 6 for the 26 reference populations and the Northwest Hui group based on the raw population data of 55 AISNPs in K values were equivalent to the number of predicted ancestral components in different colors. Each individual was denoted by a vertical line partitioned into several segments corresponding to the contributions of different ancestral components. For example, when K = 2 , America (orange and brown sub-branches), South Asia , Europe (purple sub-branches), and Africa (red sub-branches). The Northwest Hui group was chiefly assembled with populations from East Asia. In detail, many Chinese populations exhibited extremely low genetic differentiations (DA < 0.01) with the Northwest Hui group. The smallest genetic distance was observed between the studied Hui group and the reference Hui group with DA = 0.0029, followed by the Xibe group with DA = 0.0050, the Tu group with DA = 0.0052, the Southern Han population with DA = 0.0059, the Mongolian group with DA = 0.0060, the Yi group with DA = 0.0080, the Tibetan group with DA = 0.0081, the Hakka group with DA = 0.0083, and the Bai group with DA = 0.0091. In addition, three Southeast Asian populations  and two East Asian populations (Japanese and Korean) also displayed extremely low genetic distances with the Northwest Hui group. Populations from North America, South America, North Asia, and Europe predominantly manifested moderate differentiations (0.05 < DA < 0.15) from the Northwest Hui group, whereas most populations from Africa primarily differentiated from the Northwest Hui group with large genetic distances (0.15 < DA < 0.25).To comprehensively dissect the genetic structure of the Northwest Hui group, we subsequently implemented the data from 109 worldwide populations as the references, from which the population frequency data of 55 AISNPs were available. The Nei’s To gain more insight into the population clustering pattern, a PCA plot of the Northwest Hui group and 109 reference populations was performed based on the frequency data of 55 identical AISNPs? . The firConsidering all 231 genetic markers, the sequencing depths for Northwest Hui individuals roughly fluctuated from 77.14 (±21.23) at rs1736442 IISNP locus to 12,535.64  at TH01 locus. A disequilibrium in sequencing depth was clearly observed among the different kinds of genetic markers. These sequencing results were within the acceptable criteria defined by the manufacturer and approximately consistent with previous MPS-related studies . Specifiobs and Hexp values at both length and sequence levels were suitably informative for genetic studies. Additionally, we also discovered that the average Hobs values were close to, although slightly lower than, the average Hexp values from either the length or sequence perspective, possibly indicating no overall loss in heterozygosity  for selecting ancestral markers could be acquired from a previous study  Dynasty ruled by the Mongolians. It was believed that these Muslims entered China via two routes: from Northwest China via the Silk Road and from Southeastern coastal areas via the Maritime Silk Road. The Silk Road served as a series of extensive inland trade routes connecting East and West Eurasia and promoted the exchanges of economies, cultures, politics, and religions between civilizations during the 2nd century BCE to the 18th century . It was During the formation of a population, the genetic structure might be changed due to different historical events, such as migrations or intermarriages , and chaK = 3 or K = 4. Thus, the above results demonstrated that these 55 AISNPs could perform well in the estimation of the individual ancestral components, especially for individuals from East Asia, South Asia, Africa, and Europe.The raw data of 26 reference populations were initially utilized to estimate the performance of 55 AISNPs in ancestral estimation and further disclose the genetic structure and ancestral bioinformation of the Northwest Hui group. As presented in K = 3, the studied Hui group shared the similar proportion of genetic components with East Asian populations with a large area of yellow component; a trace amount of genetic component in purple which was mainly found in European populations was also detected in the studied Hui group. We further performed ancestral component prediction of the 90 Hui individuals. In K = 3 in the STRUCTURE analysis (In terms of the studied Hui group, the Hui individuals were largely assembled with East Asians in the PCA plot, demonstrating that the Northwest Hui group might retain a significant amount of genetic components from East Asia. This opinion was also congruent with the results of the STRUCTURE analyses. At analysis .In order to have a more comprehensive genetic interpretation of the Northwest Hui group, a phylogenetic tree was further delineated based on the allelic frequency data of the Northwest Hui group and 109 reference populations. In the phylogenetic tree plot, the Northwest Hui group was initially clustered with East Asian populations, exhibiting extremely low genetic differentiations from the Tu, Xibe, Yi, Bai, Han, Hakka, and Mongolian groups, etc. The intimate genetic relationships between the Hui group and some abovementioned Chinese populations were also reported in previous studies . For exaThe relatively intimate genetic relationships between the Northwest Hui and East Asian populations were subsequently certificated by two PCA plots. The genetic affinities between the Hui group and East Asian populations were further supported by previously published studies . In detaHowever, the genetic background of the Northwest Hui group estimated using AISNPs showed certain divergence from that assessed using Y-STRs. In addition to the reference Hui groups from Chinese different regions, the Northwest Hui group depicted using Y-STRs was more prone to display closer genetic relationships with populations from Central and West Asia, as well as several Chinese groups. Additionally, our previous research based on the complete mitochondrial genome illustrated that the Northwest Hui group typically exhibited closer genetic relationships with East Asian populations, roughly concordant with the genetic result provided by 55 AISNPs in this study . BrieflyIn this study, a total of 231 genetic markers were originally applied in 90 Hui male individuals dwelling in Northwest China. According to the current research, the studied genetic markers displayed satisfactory forensic performances in the Northwest Hui group, especially for the application of sequence polymorphisms which significantly enhanced the genetic diversities of STR genetic markers. Both 27 A-STRs and 94 IISNPs were polymorphic enough and could yield high forensic efficiencies in the forensic applications, such as paternity testings and individual identifications. Four of 94 IISNP loci, the rs1335873, rs1528460, rs722098, and rs1028528 loci, exhibited relatively larger discrepancies in the distributions of allelic frequencies among intercontinental populations, demonstrating that these loci might contain certain potential for the ancestry inferences. Studies based on the Y-STRs illustrated that the Northwest Hui group initially presented closest genetic relationships with reference Hui groups from Chinese different regions except for SCH and also externalized closer genetic relationships with populations from Central and West Asia, as well as several Chinese groups. Yet, the genetic structure revealed using the AISNPs indicated that the Northwest Hui group evidently displayed genetic affinities with populations from East Asia rather than those from Central or West Asia. In combination with the ancestral component estimation, it was proven that the Northwest Hui group contained a large proportion of ancestral components from East Asia and relatively little from Europe. The aforementioned results possibly indicated that the sex bias phenomenon of intermarriages might have existed in the formation of the Northwest Hui group, involving more intermarriages between males from Central and West Asia and females from East Asia.