The Epstein–Barr Virus (EBV) infects the vast majority of human individuals worldwide (~90%) and is associated with several diseases, including different types of cancer and multiple sclerosis, which show wide variation in incidence among global geographical regions. Genetic variants in EBV genomic sequences have been used to determine the geographical structure of EBV isolates, but our understanding of EBV diversity remains highly incomplete. We generated sequences for 13 pivotal EBV genes derived from 103 healthy individuals, expanding current EBV diversity datasets with respect to both geographic coverage and number of isolates per region. These newly generated sequences were integrated with the more than 250 published EBV genomes, generating the most geographically comprehensive data set of EBV strains to date. We report remarkable variation in single-gene phylogenies that, when analysed together, show robust signals of population structure. Our results not only confirm known major global patterns of geographic variation, such as the clear separation of Asian isolates from the rest, and the intermixed relationships among African, European and Australian isolates, but yield novel phylogenetic relationships with previously unreported populations. We provide a better understanding of EBV’s population structure in South America, Africa and, by the inclusion of Turkey and Georgia, we also gain insight into EBV diversity in Western Asia, a crossroads connecting Europe, Africa and Asia. In summary, our results provide a detailed world-wide characterisation of EBV genetic clusters, their enrichment in specific geographic regions, novel inter-population relationships, and a catalogue of geographically informative EBV genetic variants. Epstein–Barr virus (EBV) is a human herpesvirus chronically infecting 90% of the adult population worldwide . While tDuring the last decade, advances in next generation sequencing and target DNA enrichment have critically expanded our understanding of global patterns of EBV genomic diversity. Phylogeographic analysis performed on increasingly large datasets of EBV sequences derived from different locations, adding up to over 400 sequenced genomes, have provided insights into the geographic distribution of EBV variants ,25,26,27Larger population samples, as illustrated by Xu et al., also allow for virome wide association analysis or VWAS, where EBV variants are associated with host phenotypes  , in SoutEBNAs, EBERs and LMP-2A. Latency genes have been consistently shown to be among the most variable genes in the EBV genome, with many exhibiting evidence of persistent positive selection and geographic stratification [BDLF4, BGLF4, BHRF1, BRLF1 and, BZLF1. These additional genes have crucial roles in the establishment of the lytic phase of EBV’s life cycle, and have also particular clinical interest for their potential associations with a wide range of EBV-related diseases [In this study we generated genetic sequences for 13 selected EBV genes derived from 103 healthy individuals from a wide range of geographic locations. Samples were derived from individuals originating from 9 geographic locations, 5 of which have not been studied to date at the level of whole coding regions , expandification ,27,28. Afication ,32, whicfication ,23,27,28diseases ,35,36,37We integrated our dataset with sequences from over 250 publicly available EBV whole genomes and also with the available DNA sequence information from an ancient EBV isolate obtained from ~5700 year old chewed birch pitch from Denmark . We per® Taq 2× Master Mix (New England BioLabs) following manufacturer guidelines with an annealing temperature of 61 °C. Blanks were added to each PCR reaction batch to insure the absence of contamination. Amplicons lengths were checked by electrophoresis on a 1.5% agarose gel together with a 200–10,000 bp DNA ladder . The amplicons were purified using Solid Phase Reversible Immobilization (SPRI) as described in Meyer & Kircher 2010 [DNA extracted from saliva samples of 103 healthy individuals from nine different geographic locations , were obher 2010  with a 1her 2010 . Amplicons derived from a single individual were equimolarly pooled and transformed into a DNA library following the Blunt-End Single Tube protocol (B.E.S.T. protocol) . SubsequIllumina adapters were trimmed from the sequencing data using Trimmomatic . TrimmedFor each gene, an individuals’ callable region was retained if it covered at least 90% of the target coding region. All callable regions retained were then intersected. Comparative analyses were carried out on these intersected callable regions. Variants were called using VarScan 2  using deAll published and verified EBV complete genomes at the beginning of the project were downloaded from NCBI and separately aligned using MAFFT  to the r-d nt -b 1000 - k80 -v e -c 1 -a e -o n). Trees were joined to generate supertrees using Accurate Species TRee ALgorithm (ASTRAL) [For each gene, sequences filtered for callability from both newly generated and published sequences were aligned using MAFFT. Alignments were input to PhyML  to gener(ASTRAL)  using deFor each gene, two bootstrapped pairwise distance matrixes were generated by calculating the median values of the median pairwise nucleotide distances, based on the number of pairwise nucleotide substitutions, between all individuals of one population against all individuals of a second population in each one of the 1000 bootstrap trees. The two matrixes were calculated, one using countries of origin to define populations and a second using broader geographic regions . Using the ggplot2 R package , heatmapn−1: tree divided in n clusters). In all groupings, clusters containing less than 3 isolates were excluded from the analysis of the correspondent grouping. We then measured the degree of correspondence between the isolates within clusters and the population of origin of the isolates. To obtain that metric of correspondence we calculated 4 indexes: true positive (TP) = number of intra-cluster isolates with the same geographic origin; true negative (TN) = number of isolates in different clusters and with a different origin; false positive (FP) = number of intra-cluster isolates with a different origin; false negative (FN) = number of isolates in different clusters but with the same origin. These values were used to calculate the Matthews correlation coefficient (MCC) using the mcc function of the mltools R package [In order to define phylogenetic groups based on phylogenetic distances, trees were transformed to be ultrametric and midpoint-rooted, and hierarchical clustering was applied using the hclust function of the R package stats. Each tree was sequentially divided from k = 2 clusters up to k = number of isolates, generating one grouping per each dendrogram, “cut” . Normality of data was tested prior to the application of comparisons tests with the Shapiro–Wilk test (R base package). For both normality and difference tests the significance threshold was set at 0.05.Statistical significances of the comparisons of means between groups were determined with either a Student’s Our sequencing effort covered a total of 13 genes , with special focus on the latency group . For these putatively multi-infected samples only the dominant strain was considered, since variants of low allele balance were systematically excluded in our filtering procedure.EBNA-2 and the EBNA-3s. We used genetic variants from EBNA-2 and EBNA-3s for EBV typing and identified 23 type 2 and 305 type 1 isolates. No type 2 strains were found among the new isolates described in this study. Four individuals presented inter-typic recombinant strains of type 1 EBNA-2 and type 2 EBNA-3s, none of which belonged to our dataset of 103 individuals. Two of the four individuals were previously identified as inter-typic recombinants in Correia et al. 2018 [EBNA-2, EBNA-3A, EBNA-3B, and EBNA-3C.EBV can be classified in two genetic types by attending at the extreme dissimilarity in the sequence of 4 genes: al. 2018 , but theMany of the following analyses were performed at two geographic resolutions: country of origin, and broader regions . Below, we will sometimes refer to the broader regions as “continents”, even though this is not precise for all mentioned broad regions .p-value = 0.009). Latency genes include two short RNAs (EBERs) that have been shown to be, in contrast to the rest of this category of genes, very conserved [EBERs are excluded from the polymorphism comparison between latency and lytic gene variation, the difference between the two categories becomes more pronounced . Direct measures of genetic diversity, including the Watterson’s estimator, can be influenced by sample size [We observed a wide range of genetic diversity in our entire data set across genes using the Watterson estimator  with divergence . The comparison was carried out by calculating, for each gene, the pairwise genetic distances between or within populations in each one of the 1000 bootstraps of the phylogeny. The median of these values for each gene was used as the estimate of genetic divergence or diversity for each pair of populations or within each population respectively, and for each gene. Genetic divergences and diversities were then compared between genes.p-value = 0.07) but significantly higher values of divergence were observed when grouped by country of origin . We calculated the ratio of divergence/diversity for each gene and the grouping by country yielded significantly higher values than using broad regions . This suggests that geographic stratification has a relevant role in shaping EBV’s phylogenies, in particular when considering small geographic scales. Despite considerable variation among genes, there was a substantial difference between divergence and diversity, both estimated as the median the genetic distances observed in 1000 bootstrap trees for each gene. Divergence was always higher than diversity, suggesting stratification . When coEBNA-1, which had a high dropout rate among published datasets, limiting the overall analysis to 164 samples. We thus repeated the analysis excluding EBNA-1, which allowed for a total of 227 isolates to be included. We used the same isolates to generate supertrees allowing for the comparison of the two approaches (EBNA-1), the supertrees appear to better separate the isolates per geographic origin than the phylogenies based on gene concatenation, in particular the split between Asian individuals from the rest, which is the most clearly replicated split described to date [EBNA-1, the correlation was higher in the supertrees than in the trees derived from concatenated sequences . The second concatenation-based approach, based on the substitution of missing data with Ns, allowed for the use of 367 isolates. The resulting phylogenies (repeated both with and without the EBNA-1 gene), showed a similar scenario to the previous analysis, and groups that were almost monophyletic in the supertree, such as the Asian group, were observed to be divided in the concatenation-based approach .To identify global and recurrent patterns among the phylogenies based on individual genes, we tested three approaches: two based on gene sequence concatenation, and a coalescence-based supertree algorithm (ASTRAL)  Supplem. The twoproaches . In both to date ,27. In oapproach . When thThese results showed that the supertree approach lead to similar performances in classifying isolates by geographical origin, and that it was more flexible in the handling of missing data with minimum loss of information. Given this, we proceeded with the supertree approach. EBNA-3s and EBNA-2 genes, we excluded type 2 isolates from subsequent analysis. Type 2 isolates were included in the analyses of the remaining genes. We carried out a formal analysis of the isolates’ relationships, clustering and population structure derived from the phylogenetic trees. When generating a supertree, the most representative relationships among isolates are established from a measure of topological recurrence given by the weighted number of times a split appears in the single gene phylogenies. In order to process the information provided by the tree and systematically analyse genetic distances among populations, we calculated the median value of the pairwise distances between all individuals in one population to all individuals in another population. Each of those pairwise distance values were themselves calculated as the median of 1000 bootstrap iterations (see Methods). This median-based approach tolerates the presence of isolates in any particular population that are grouped with another population and that might represent population outliers to the former group. As mentioned before, since classification in type1 and type 2 was the strongest clustering factor for In addition to the median inter-population distances described above, we devised a method to analyse the degree of clustering in each population. We cut gene trees and the supertree at multiple “k”s and calculated enrichments of individuals from each population into the resulting clusters. For some populations, significant clusters appeared at deeper cuts, indicating an older coalescence, while other populations were only enriched at shallow cuts or more recent coalescences. Leveraging this information with the proportion of individuals from each population included in a significantly enriched cluster provides a computational framework for the interpretation of the trees.p-value: 5.7 × 10−10). This continental heterogeneity is primarily defined by two sub-splits. The first sub-split is between mainland East Asia , and the easternmost insular and peninsular populations . This is well distinguishable in the bootstrapped genetic distances and hierarchical clustering analyses, but less conspicuous in the phylogeny. The second sub-split is between South-East Asian isolates  and the other East Asian populations. More than half of the Papua New Guinea isolates consistently group close to the South-East Asian isolates . Noticeably, isolates from a single South American country of origin, Bolivia, are found together with East Asian isolates, clustering close to the insular and peninsular subgroup .The analysis of recurrent patterns across genes showed distinct patterns of population stratification . A firstAs observed in previous EBV whole-genome phylogenetic analysis, non-Asian samples showed more intermingled relationships and lower genetic distances among themselves ,27. OfteConversely, isolates from North-America (USA) and Australia displayed low genetic distance with European countries. USA and UK clustered together in the hierarchical clustering analysis of the median phylogenetic distance B.Interestingly, we observed four groups of EBV isolates from the Western Asia, a group poorly described to date both in terms of sequence characterisation and phylogenetic relationships with other EBV strains. The groups comprised 10%, 13%, 15% and 19% of the total number of isolates from the Western Asia in the supertree. Those groups composed by samples from Turkey and West Georgia appeared closely related to other European and Sub-Saharan African groups. Hierarchical clustering on median inter-population genetic distances resulted in the same pattern B, but clp-value: 0.0035 and 0.004, latent and lytic genes respectively). The two supertrees also reaches significance when the same test is performed at the level of continents, with the lytic one showing higher statistical support . To notice that when the two non-coding genes (EBERs) are excluded from the analysis, the statistical support for the diversity and divergence comparisons in the latent supertree increases of an order of magnitude. It is interesting to notice how South American isolates show limited grouping in either the latency or the lytic supertrees, but come together in the supertree based on the complete gene-set, which illustrates the advantage of gene stacking approaches to reveal global patterns that are otherwise obscured. In order to understand the contribution of latency and lytic genes to the supertree, we compared two additional supertrees stacking genes from each class . The resp-value = 6.1 × 10−8). This points towards a limited confounding effect of the recombination on the results obtained with our approach, and lead to the recombination region to be kept in the analyses. EBV is known to be highly recombinant ,29,60, wBDLF4, or very short ones such as the EBERs, allowed only for the recognition of some major splits, while finer scale stratification became more difficult to resolve. While general stratification patterns become clear when the data from single genes are combined, we observe abundant inter-gene variation among the phylogenetic distances between individuals and populations ; for the remaining genes the East Asian individuals were grouped in different and various layouts. Despite multiple differences among trees, individual genes also showed some consistent relationships; for example, the majority of the East Asian isolates are routinely found in groups with low within population genetic distances, and the mainland/peninsular separation we observed in the supertree was evident in the individual trees for several genes . In particular, the mainland East Asian isolates (China and Hong Kong), were found grouped together in 7/13 genes, as were Indonesia and Papua New Guinea isolates . Despite the apparent lack of stratification within non-Asian isolates, when we increased the geographic resolution and considered countries instead of continents, the statistical support for lower values of diversity compared to divergence was found in all genes, and with an increase in nominal p-value in average of one order of magnitude , again a signal of more defined stratification at the level of countries, as we observed in the supertree. Interestingly, we observed a high level of variability in which countries dominated in detected clusters among different genes. An example of this involves the African isolates, which for certain genes showed little country-level specific clustering but for other genes showed Kenya-dominated clusters, which occurred much more frequently than clusters dominated by Ghana or Uganda , statistical support for stratification is found in 7/13 genes, even if narrowly significant at the level of nominal r Uganda . The isolates derived from Western Asian hosts also showed inter-gene variability, from the observed distribution in 4 paraphyletic groups in the supertree. For most genes, the hierarchical clustering of the genetic distances revealed close relationships among these populations, but some genes clustered them closer to African isolates while others clustered them with Europe . Taken tWe tested if geographical patterns displayed by individual genes were correlated with the physical distance among those genes in the EBV genome which would suggests an effect of recombination. A Mantel test  between p-values corrected by multiple testing).We found signals of stratification in our data set characterized by remarkable phylogeographic variability among genes, despite showing general recurrent patterns. We set out to pinpoint the variation originating the stratification signals in each gene identifying the polymorphisms characterizing the geographical population. In order to do so, we choose the cut in the tree maximising the combination of the geographical segregation and the resolution of the obtained clusters. For this, we applied separately to each gene the workflow outlined in Lastly, the polymorphisms in significant population/cluster associations were analysed to determine which variants are significantly over-represented in each significant sub-population cluster. Of note, one cluster can present enrichment in multiple populations. Although this approach can be applied systematically across genes, a tree split based on global optimal CGS might not be equally suitable for all populations, and this could apply to any possible tree-cut optimization method. We decided to complement our analysis with an alternative tree-cut optimization method, and we derived an additional set of clusters using the same set of filters but basing the selection of the tree split only on the maximum MCC score, instead of CGS. This resulted in an alternative grouping, partially overlapping, generally presenting smaller clusters. Heatmaps showing odds ratios for significant cluster/population associations are shown in Subsequent steps to identify genetic variants enriched in population sub-clusters were applied in both sets. The resulting variants per group per gene are reported in BHRF1 lytic gene is an exception, with a remarkably high nonsynonymous/synonymous ratio of 2.47. When this gene is excluded from the comparison of gene categories, statistical significance was reached . When only considering variants significantly enriched for the population of origin/cluster in each gene, we found a similar scenario in the ratios of nonsynonymous/synonymous changes, with the latency genes showing significant higher value. The difference between nonsynonymous/synonymous ratios measured in all polymorphisms or measured only in variants enriched for origin/cluster pairs was analysed  in at least one cluster , most of which were identified in both the max MCC and max CGS clusters. The overall nonsynonymous/synonymous ratio in the complete data set was 1.55. This ratio varied among genes , with lyEBNA-3C gene , we devised a set of filters based on the proportion of individuals from a given population represented in a given cluster (>30%), the proportion of that population in the cluster  and the difference in allele frequency between the population/cluster and all populations (difference in frequencies > 0.6). This approach yielded multiple instances of population-structured variants and haplotypes. An illustrative example can be found in the -3C gene A, where EBNA-1, where a single amino acid change is used to classify subtypes that are known to have differential geographic distribution [BHRF1 gene, where the change at position 42,349 (reference strain coordinates), which results in either Leucine or Valine at residue 88, is commonly investigated in sequence analyses of this gene. In our analysis this position characterised different cluster/population pairs from Asian , concordantly with its distribution  [EBNA-1 tree topology nicely  . Both tyy nicely B. EBNA-1er group B The P-AEBNA-2 insertion. EBNA-2, the product of which is essential for B-cell immortalisation, has been another pivotal gene for EBV classification, since it shows both high genetic diversity and several population informative sites. A commonly interrogated variant in this gene is the “CTC” insertion described by Aitken et al. [EBNA-2 phylogeny, Western Asian isolates divided into two well-separated groups. The more “European-like” group presented the insertion, while the more intermixed did not, supporting a polyphyletic origin of these populations.n et al. . The insEBERs variation. EBV encodes two small RNAs that are abundantly expressed in latency, and that play a range of significant roles in EBV-infected cancer cells [EBER-2 versions among the isolates in our dataset: almost all region of origins showed the exact fixed haplotypes. The exception were the isolates from Asia and Oceania, that showed varying base proportions, including notably all the ones originating from Hong Kong, show an almost identical pattern of SNPs, different from all the other isolates . These authors tested 132 isolates derived from Chinese hosts, and classified them in 3 subtypes, showing the predominance of 79V88V. Our expanded data set showed how 79V88V was indeed one of the predominant subtypes, but only in Asian isolates, followed by 79L88L, that was found also in most Western Asians and Papua new Guineans , and to support and systematically produce inferences from the relative genetic distances between and within populations. Collectively, our analyses confirmed an elevated gene-to-gene variation, with the presence of recurrent, as well as gene-specific phylogeographic patterns. In type 1 isolates, the clearest split divides Asian isolates from the rest, confirming the scenario found in most studies of the geographic variability of EBV ,27,28,29The data set we generated allowed us to identify variants and haplotypes localized to specific populations or geographic regions. We showed how a systematic and statistically supported characterisation of EBV variation can provide useful information on the complex population structure of this virus and pinpoint variants with strong geographic structure (caused by genetic drift and/or selection) that are thus potentially relevant for EBV’s biology, local adaptation and pathology.EBER-2, this ancient EBV strain matched the fixed haplotype world-wide, with the exception of a little part of few populations, mostly Asian. The only exception for this gene is Hong Kong, for which all isolates showed a completely alternative haplotype. EBNA-1 haplotype composition is highly variable world-wide but also within Europe, and the Syltholm_1 presented the P-Ala variant in residue 487. This variant is present in continental Europe, as well as in countries with a demographic history of European immigration and/or colonization [Paleo-genomics studies have proven critical to understand current patterns of genetic variation in humans, while informing us about multiple aspects, including past migrations, instances of selection and even sociocultural characteristics of ancient populations. The reconstruction of archaic sequences of EBV will be critical to understand the historical dynamics of EBV variants across the world as well as past episodes of selection and adaptation in the context of an also adapting host immune system through geography and time. In this analysis we included EBV sequence data derived from an isolate found to be infecting a 5700 year old Danish woman (Sylthom_1 sample in nization ,74,75. IFinally, this study reflects an effort to systematically define statistically supported geographic clusters in EBV genes, thereby providing insights into population structure and a catalogue of geographically-informative variants. These new resource and workflow should facilitate the comparison of EBV populations in future sequencing efforts.


Mitochondrial DNA (mtDNA), coupled with maternal inheritance and relatively high mutation rates, provides a pivotal way for us to investigate the formation histories of populations. The Hui minority with Islamic faith is one of the most widely distributed ethnic groups in China. However, the exploration of Hui’s genetic architecture from the complete mitochondrial genome perspective has not been detected yet. Therefore, in this study, we employed the complete mitochondrial genomes of 98 healthy and unrelated individuals from Northwest China, as well as 99 previously published populations containing 7274 individuals from all over the world as reference data, to comprehensively dissect the matrilineal landscape of Hui group. Our results demonstrated that Hui group exhibited closer genetic relationships with Chinese Han populations from different regions, which was largely attributable to the widespread of haplogroups D4, D5, M7, B4, and F1 in these populations. The demographic expansion of Hui group might occur during the Late Pleistocene. Finally, we also found that Hui group might have gene exchanges with Uygur, Tibetan, and Tajik groups in different degrees and retain minor genetic imprint of European-specific lineages, therefore, hinting the existence of multi-ethnic integration events in shaping the genetic landscape of Chinese Hui group. The Hui minority is one of the largest and widespread Chinese ethnic groups with Muslim followers. Unlike many Muslim populations, such as Uygur and Kazak, the Hui people exhibit a greater degree of assimilation with the majority of Han people in terms of language and culture. According to historical documents, the ancestors of the Hui minority in China could be traced back to the Tang dynasty 618–907 AD), but it was in the Yuan dynasty 1271–1368 AD) that the Hui really started the multi-ethnic integration [8–907 AD,68 AD thaIn recent reports, some genetic evidences have been employed to dissect the demographic history and genetic landscape of the Hui ethnic group. For example, the origin of Hui group was attributed to the substantial assimilation of East Asians and minor assimilation of West Eurasians based on the paternal Y chromosome analyses . MeanwhiIn this study, we employed the complete mitochondrial genomes of 98 healthy and unrelated individuals from Hui group, Northwest China, which were sequenced by the massively parallel sequencing (MPS) technique on the HiSeq X Ten system . In order to obtain an extensive understanding of the maternal genetic structure of Hui group, we collected 7274 complete mitochondrial sequences from 99 previously published populations around the world for a comparative study. The genetic history of one population reflected by mitochondrial genome may not be exactly the same as the true history, but through the extensive study of mtDNA variations of Hui individuals, it can still obtain some insights into the genetic structure of the contemporary Hui groups and the demographic episodes they might have experienced.The whole blood samples of 98 Hui individuals without consanguineous relationships were collected from Northwest China. Written informed consents and demographic information were acquired from all the participants concerned. This study was conducted with the approval of the Ethics Committee of Xi’an Jiaotong University Health Science Center  and followed the ethical principles proposed by the World Medical Association . 2O in a volume of 30 μL system. The PCR cycling reaction was carried out as: 98 °C for 3 min; 13 cycles including 98 °C for 20 s, 58 °C for 4 min; seven cycles including 98 °C for 20 s, 72 °C for 1 min; then, 72 °C for 2 min and holding at 10 °C. The amplified products were further purified by magnetic beads. Secondly, the indexes were appended to the purified products by reamplification and the target DNA regions were enriched as well. The index-adding reaction was performed in a 30 μL system, containing 18 μL purified PCR products, 10 μL 3×EnzymeHF, 1 μL I5MRBar, and 1 μL I7MRBar. The corresponding PCR procedure was 98 °C for 2 min, then six cycles with 98 °C for 15 s, 58 °C for 15 s, and 72 °C for 15 s, lastly 72 °C for 2 min, and stop reaction in 10 °C. The reamplified products were purified again utilizing magnetic beads. Finally, the constructed library was quantified by the Qubit 2.0 Fluorometer platform  with the Qubit dsDNA HS Assay Kit . The agarose gel electrophoresis was carried out to evaluate the quality of constructed library. After quantification, the library was implemented for paired-end sequencing on an Illumina HiSeq X Ten instrument.The library was constructed based on the MultipSeqTm AImumiCap Panel provided by Enlighten Biotechnology Company  with the following steps. Initially, the target DNA regions were acquired by multiplex PCR amplification, which contained a 5 μL RealCapChrMT mix, 10 μL 3×EnzymeHF, 1 μL template DNA (5 ng/μL), and 14 μL nuclease-free Hhttp://cutadapt.readthedocs.org/), and low-quality reads were filtered by the Trimmonmatic software (http://www.usadellab.org/cms/index.php?page=trimmomatic/). The final cleaned data were mapped to the revised Cambridge Reference Sequence [http://bio-bwa.sourceforge.net/) to generate the binary alignment/map (BAM) file. In order to escape false positives from contaminations of nuclear mitochondrial DNA (NUMTs ), the sequences were also compared with the human reference genome hg19 [https://bedtools.readthedocs.io/en/latest/) and realigned to rCRS + 64 bp to produce new BAM files using the Bowtie2 software (http://bowtie-bio.sourceforge.net/bowtie2/). Finally, the variation sites in the BAM file were identified by SAMtools v1.8 (http://samtools.sourceforge.net/) and VarScan v2.4.0 (http://varscan.sourceforge.net/), which were stored as a variant call format (VCF) file. The final consistent sequences were yielded by BCFtools v1.9 (https://samtools.github.io/bcftools/) in the FASTA file.The original image data obtained from high-throughput sequencing were automatically analyzed by base recognition and converted into the original sequences in FASTQ format. To ensure the accuracy of subsequent analyses, redundant primers and indexes in initial FASTQ files were removed by the Cutadapt software  based on PhyloTree build 17 (http://www.phylotree.org/index.htm). The haplogroups of all mtDNA sequences were also rechecked and aligned manually by Snapgene (https://www.snapgene.com/), and compared with the rCRS [Quality control was carried out according to the previous study . The hapD and Fu’s Fs tests), and analysis of molecular variance (AMOVA) were evaluated by Arlequin 3.5.1.3 [F-statistics, STF) between Hui group and reference populations were also calculated by Arlequin 3.5.1.3 [R statistical package (https://www.r-project.org/) was implemented to plot the circle histogram for the pairwise STF values between Hui and reference populations. The principal component analysis (PCA) of all populations was plotted based on the mitochondrial haplogroup frequencies using the Statistical Package for the Social Sciences (SPSS) 16.0 software. We further generated Bayesian skyline plots (BSP) from BEAST 1.6.1 [https://www.fluxus-engineering.com/), and the plots were subsequently visualized in the Network Publisher (http://www.fluxus-engineering.com/index.htm).All the haplogroup frequencies utilized in this study were generated from complete mitochondrial sequences and calculated by the direct counting method. Statistical indexes, including haplotype diversity (Hd), nucleotide diversity (pi), number of segregating sites (s), and average number of pairwise nucleotide differences (k) were estimated using DnaSP v5  based on 3.5.1.3 ,12 using 3.5.1.3 ,12 basedST 1.6.1  for Hui ST 1.6.1 . Each MaST 1.6.1 . The timST 1.6.1 . The medA total of 98 individuals, including 52 females and 46 males, were successfully sequenced on the Illumina HiSeq X Ten system. The average read depth was 3280× ± 1033× (mean ± SD) per individual. The sequencing depth for all individuals were portrayed in a box plot. As shown in https://haplogrep.i-med.ac.at) based on PhyloTree build 17 (http://www.phylotree.org/index.htm) and rechecked manually. According to the previous studies, the European-specific lineages commonly encompassed haplogroups H, HV, R0, R1, R2, JT, U, N1, N2, W, and X [http://www.phylotree.org/index.htm); and into various clades of macrohaplogroup M, including haplogroups D4 (18.37%), C (10.20%), D5 (9.18%), M’ (8.16%), G (7.14%), and Z4 (1.02%). As shown in W, and X ,19. WherW, and X ,21 In FiAs depicted in As for the European-specific lineages  in the present Hui group, haplogroup U2 accounted for the majority (3.06%), which was a rare lineage spread across Central Asia, Europe, the Middle East, and North Africa . In detaThe historical researches and previous studies implied that Hui group might have intimate relationships with Han populations from Chinese different regions . TherefoD  and Fu’s SF test . Mismatch distributions were also implemented to infer the history of Hui group with a unimodal pattern (p = 0.520) and HRI  in Hui group failed to significantly deviate from the model expectation of demographic expansion. For the selected references, four Han populations, containing CHB, CHS, MIN, and HAK, yielded significantly negative values for both Tajima’s D and Fu’s SF neutrality tests and no significant p-values for both SSD and HRI statistics, which was concordant with the neutrality test and mismatch distribution of Hui group. As shown in  pattern , and theBriefly, the unequivocally significant departure of neutrality tests found in Hui group could be primarily explained by an excess of new and low-frequency mutations due to evolutionary forces, such as population expansion. The distribution curve of Hui group also supported the demographic history of sudden expansion with the unimodal mismatch distribution and non-significant model fit statistics (SSD and Hri). Four Han populations  exhibited similar results of neutrality tests and unimodal mismatch distributions with Hui group, implying recent population expansions.It was reported that AMOVA could generate estimates of variance components, representing a correlation of haplotype diversities at different levels of hierarchical subdivision . To someTo estimate the genetic relationships between Hui group and 99 worldwide populations, PCA was implemented based on the haplogroup frequencies of 7372 complete mitochondrial sequences. A scree plot presenting the variance of each principal component was captured in Briefly, the above results hinted that Hui group might have intimate genetic relationships with Han populations, which might attribute to the phenomenon that they had more sharing haplogroups. In detail, several haplogroups predominately distributed in Hui minority such as D4 (18.37%), F1 (10.20%), D5 (9.18%), M7 (6.12%), and B4 (5.10%) were also detected to be widespread in Han populations . The preSTF values) were computed among the Hui group and 99 worldwide populations according to the haplogroup frequencies. Then, a circle histogram of pairwise STF values was depicted to get a more intuitive insight of the genetic relationships between populations. According to the genetic differentiation criteria of Wright [STF <0.05 for low differentiation, 0.05 < STF < 0.15 for moderate differentiation, 0.15 < STF < 0.25 for high differentiation, and STF > 0.25 for very high differentiation [STF values between Hui and other reference populations were ranged from 0.0052 to 0.2252 with the median value 0.0363. As shown in STF = 0.0052), followed by MIN (STF = 0.0073), HAK (STF = 0.0073), and CHS (STF = 0.0079). The Hui group also showed very low genetic distances (STF < 0.01) with LU1, LU2, HMR, CTT, and LAO populations. In addition, the Hui group generally had relatively distant genetic relationships with the majority of Niger–Congolese- and Austronesian-speaking populations. Three populations from America (PEL = 0.1509), Africa (PGM = 0.2096), and North Asia (NVR = 0.2252) were identified as highly divergent populations with the Hui group, when the STF value of 0.15 was set as the threshold.To obtain a deeper understanding of Hui’s maternal origin, genetic distances  with the complete mitochondrial sequences of Hui group and Han populations to compare their population size dynamics. As presented in To further explore the genetic sharing between the studied Hui group and reference populations around the world, we conducted extensively haplotypic comparisons of complete mitogenome of 7372 individuals and finally determined 1578 sequences intimate to Hui haplotypes to perform the median networks. Given the limited size and the widespread haplotype distributions of sampled Hui individuals, we had to take all the haplotypes from the Hui group into account, and according to the network results, the reference individuals within one mutation difference with Hui haplotypes were simply counted. For the East Asia-specific haplogroups, Hui individuals predominantly clustered with individuals from Han, Uygur, and Tibetan populations. In detail, Hui individuals displaying the same haplotypes with Han individuals or differing from Han individuals by only one mutation accounted for 45.92%, reflecting close genetic relatedness between Hui and Han individuals. These Hui individuals fell within 35 different haplotypes, including haplotypes belonging to macrohaplogroup M  and to macrohaplogroup N . For example, the median network of mtDNA haplogroup D4, the most typical linage in Hui group, was presented in From the perspective of historical development, it was recorded that the Hui group were of varied ancestries, many of whom descended from Central Asians and West Asians, such as Persians, Arabs, and Turks who intermarried with the local Han individuals ,4,41. ItThe result of median networks hinted that the maternal genetic components of Hui minority might be relatively abundant and complex. Initially, the extensive gene components from the Han population might have been assimilated into the Hui group during the formation process. The present notions were further supported by the previously published researches. For example, Xie et al. investigated the genetic and forensic characteristics of nine different geographical Hui groups using 157 Y-SNPs and 27 Y-STRs and finally found that Hui groups from the Northwest China, Sichuan, and Shandong provinces displayed close genetic affinities with Chinese Han . He et aThe present study provided the first set of complete mitochondrial genome data of 98 Hui individuals residing in Northwest China. According to the present research, most of the mtDNA haplogroups of Hui group were classified into the lineages peculiar to East Asia, while a few haplogroups into the lineages peculiar to Europe. This notion might imply a dominant contribution of East Eurasian to Hui’s maternal gene pool and a concomitant dilution of its West Eurasian provenance. In detail, the Hui group exhibited greater genetic affinities with Chinese Han populations, largely ascribing to the widespread haplogroups D4, D5, M7, B4, and F1 in these populations. Further, the expansion time of Hui group was during the Late Pleistocene. Compared with Northern Han, the Hui group tended to display a closer expansion time with Southern Han populations. Finally, we also found that the present Hui group might contain different degrees of genetic imprints from the Uygur, Tibetan, and Tajik groups, suggesting the existence of multi-ethnic integration events in the process of forming the maternal genetic landscape of Hui group. Overall, due to the genetic complexity of Hui group in China, more Hui samples from different regions need to be taken into consideration to obtain a more comprehensive sight of its maternal genetic compositions.


In) and pairwise fixation index (Fst) values, multidimensional scaling analysis, and success ratio of estimation with cross-validation showed that the novel panel could well reveal the genetic structural differentiations of the East Asian, European, African, and South Asian populations. Besides, the biogeographical ancestry origin inference both at the individual and population levels was conducted on the Chinese Hui group by principal component analysis and STRUCTURE analysis, and the results revealed that the Hui group had the East Asian origin, and the East Asian component ratio of Hui group was approximately 88.87%. Furthermore, the population genetic analyses among the Hui group and reference populations were performed based on the insertion allele frequency heat map, population pairwise Fst values and phylogenetic tree, and the results indicated that the Hui group was genetically closer to East Asian populations, especially two Chinese Han populations (CHS and CHB populations).In the present study, we investigated the genetic polymorphisms of 39 ancestry informative marker-insertion/deletion (AIM-InDel) loci in the Chinese Hui group using a previously self-developed panel, further clarified the genetic relationships between the Hui group and other reference populations, and assessed the ancestry inference efficiency of the AIM-InDel panel based on the worldwide population data from 1000 Genomes Phase 3. The results of the locus-specific informativeness ( In recent years, ancestry informative inference has uncovered important information and provided a new perspective in biomedical fields such as anthropological research, forensic genetic application, and genetic epidemiology study –3. In paIn the past decade, several panels on single nucleotide polymorphisms (SNPs) were developed for ancestry informative inference applications based on capillary electrophoresis (CE) platform, as well as massively parallel sequencing (MPS) technology , 9. SNPsInDel is proposed as a new kind of genetic marker which combines the advantages of both short tandem repeats (STRs) and SNPs, i.e., extensive distribution, short amplicon size, and low mutation rate; besides, the length polymorphic characteristic makes it easy to be genotyped on the CE platform by fragment size differentiations , 13. AnoChina is a multiethnic country with 56 populations, and the Hui group is one of the largest ethnic minorities which lives in Chinese many regions such as the Ningxia, Gansu, Qinghai, Xinjiang, Henan, Anhui, Liaoning, Heilongjiang, and Shaanxi provinces. There were few previously genetic polymorphic studies of different genetic markers on the Hui group, so the Hui group was chosen as the research object in this study. Genetic evidences of ancestry inference markers such as SNPs indicated that the Hui group had closer genetic relationships with East Asian populations . But to In this study, the 509 adults of the Hui group who lived in the Xinjiang Uyghur Autonomous region were involved, and all the volunteers who had given their written informed consents were healthy, unrelated, and selected from the local Hui group randomly. The collection procedure of all the samples was conducted under the human and ethical research principles of Southern Medical University and Xi'an Jiaotong University Health Science Center.Besides, the reference population data were from the 1000 Genomes Phase 3 , and theμl volume of the reaction system, and all the reagent dosages as well as PCR reaction condition were performed according to the previous study [In the present study, 509 DNA samples were prepared and amplified using the novel 39 AIM-InDel directed amplification kit without the DNA extraction step, and the PCR amplifications were conducted using the GeneAmp PCR System 9700  with the total 25 us study . The AIMP values for Hardy–Weinberg equilibrium (HWE) tests of 39 AIM-InDel loci in the Hui group were calculated by the STRAF online program (version 1.0.5) [Fst values of five intercontinental populations in pairs, herein, the same intercontinental populations as a whole, were assessed using by Arlequin software (version 3.5) on the basis of 38 InDel loci, respectively. The success ratio of population origin with cross-validation estimation, the population-specific divergence (PSD) values, and the principal component analysis (PCA) of the same 38 AIM-InDel loci among the different populations were performed in the online Snipper software (version 2.5) , and the informativeness (In) values which also called Rosenberg's In values were calculated by the PSD values multiplied with 0.693, i.e., converting the natural log to log(2) [K value was determined by the online software Harvester program (http://taylor0.biology.ucla.edu/structureHarvester/). The bar plots based on the results of STRUCTURE analysis were conducted by DISTRUCT software (version 1.1) [Fst values based on the same 38 InDel loci among 22 worldwide populations (American populations excluded) and the Hui group were assessed using Genepop software (version 4.0). The pairwise DA distances of the above populations were conducted by DISPAN software, and the phylogenetic tree was conducted using MEGA software version 7.0 on the basis of population pairwise DA distances. The box plot conducted based on Rosenberg's In values, the heat maps , and the scatter diagram of MDS analysis were drawn by R software (version 3.4.4).The allele frequencies, forensic parameters, and n 1.0.5) . Since to log(2) , 20. Theo log(2)  was condo log(2) . Besidesion 1.1) . And theFst and locus-specific Rosenberg's In values, the cross-validation estimation success ratios, and the MDS analysis were involved in these populations.In the present study, the ancestry inference synthetic efficiency and forensic practicability of this novel panel were conducted by assigning the population genotype data of the same 38 AIM-InDel loci in the 2504 worldwide individuals from the 1000 Genomes Phase 3, and the pairwise In values [In values at the same 38 AIM-InDel loci showed distribution differences in five intercontinental populations from 1000 Genomes Phase 3, and the essential information of the total 39 AIM-InDel loci and Rosenberg's In values of the same 38 AIM-InDel loci in five intercontinental populations were shown in Supplementary Table In values (>0.1) in East Asians; and eight AIM-InDel loci including the rs10569275, rs3029066, rs3216799, rs34477782, rs34921138, rs3840222, rs5891435, and rs5896844 could be regarded as African-informative markers with higher In values (>0.1) in Africans. As for Europeans, seven loci, i.e., rs11273905, rs147090496, rs3047538, rs34477782, rs35434967, rs57406754, and rs5891435 showed relatively higher In values (>0.06), which contributed greatly to differentiate the European populations and other intercontinental populations. In this panel, the locus-specific In values of South Asians and Americans were relatively lower than those of other three intercontinental populations mentioned above.The PSD values of all the AIM-InDel loci were calculated by the online software Snipper, and then, these values were converted to the more widely used Rosenberg's n values , 20. As Fst values were calculated among five intercontinental populations in pairs by the Arlequin software, and the pairwise Fst value results were reflected by a heat map conducted by R software. A heat map of pairwise Fst values in the five intercontinental populations was shown in Fst values were represented by different depths of various colors in these grids. When Fst values over 0.25, there were 10 loci in the EAS-AMR pair, 7 loci in the EAS-SAS pair, 27 loci in the EAS-AFR pair, 24 loci in the EAS-EUR pair, only one locus in the AMR-SAS pair, 13 loci in the AMR-AFR pair, 15 loci in the SAS-AFR pair, and 17 loci in the AFR-EUR pair, whereas there was no locus with the Fst value over 0.25 in the AMR-EUR pair and SAS-EUR pair.The pairwise The success ratios of population origin estimation with cross-validation of this panel were calculated using the Snipper software, and the results were shown in The MDS analysis of five different intercontinental populations was conducted on the population level via SPSS software, and the MDS result was shown in The allelic frequencies and forensic parameters of the total 39 AIM-InDel loci in the Hui group were shown in K = 2-7, herein, only shown at K = 3-5. In K = 3, the African populations were occupied mostly with color pink, European populations were almost blue, and East Asian populations were purple, but the American and South Asian populations showed mixed colors with blue and purple. The Hui group was accordant with East Asian populations which occupied mostly with color purple. When K = 4 and 5, the Hui group was still consistent with the ancestry information components with East Asian populations, while the American and South Asian populations could be distinguished with each other to a certain extent. The optimum K value was considered based on both the biogeographical factor and the result of delta K calculated by the online software Harvester program on the basis of the same 38 InDel loci in the total 27 populations from five different intercontinental populations, and the K value was finally determined at 3. As shown in Supplementary Table K = 3, the Hui group showed the ratios of ancestral informative components with the values of 0.8887 of cluster 1, 0.0786 and 0.0327 of cluster 2 and cluster 3, respectively, which were very similar to those of East Asian populations. The present study further assumed the Europeans, East Asians, and Africans as the three main ancestral origins to explore the ancestry proportions of unknown individuals and populations. As shown in In order to explore the ancestry components of the Hui group, population genetic structure analysis was conducted by STRUCTURE software based on the 26 reference populations. Firstly, the bar plots were conducted based on the raw genotype data of the total 3013 individual samples at A scatter PCA plot of the total 3013 individuals from 27 populations in five continents was conducted at the individual level by the online software Snipper based on raw genotype data of the same 38 AIM-InDel loci. As shown in The population genetic analyses were conducted among the Hui group and reference DA distances using the MEGA software, showing the genetic relationships among the Hui group and the other 23 reference populations. As shown in A phylogenetic tree was conducted based on pairwise Fst genetic distances were calculated among the 24 populations in pairs using the Genepop software, and a heat map intuitively represented the pairwise Fst value differences in Fst values ranged from 0.0116 (Hui-KHV) to 0.3885 (Hui-YRI). In the heat map, the pairwise Fst values were displayed by the different colors, and the blue color meant lower Fst values; however, the pink color represented higher Fst values. When considering the four main intercontinental populations, the East Asian populations showed the largest genetic differentiations with African populations, followed by the pairwise populations between the European and African populations. The studied Hui group had the smallest genetic differentiations with East Asian populations, especially with the KHV, CHB, and CHS populations, whereas it presented larger genetic differentiations with African populations such as the YRI, ACB, and LWK populations.In this study, the population pairwise Fst values could be also regarded as a measure of population differentiation [Fst values were conducted to further support the above results.This study chose the Xinjiang Hui group as the research object, and the Hui group is one of the largest ethnic minorities in China that spread across several provinces. The Xinjiang province was an important region along the historic Silk Road, and the Hui group was documented as being descended from Silk Road travelers according to the records , 25. Expntiation . And thentiation . FurtherFst analyses among five intercontinental populations in pairs and Rosenberg's In values in five intercontinental populations were calculated on the same 38 AIM-InDel loci, and the obtained results showed that most of the 39 loci in the AIM-InDel system had high discrimination ability in four intercontinental populations except the American populations. In addition, the MDS analysis and success ratios of estimation with cross-validation verified that the novel panel could give satisfactory results in the population stratification of four intercontinental populations, i.e., the African, East Asian, European, and South Asian populations. Although the American populations showed relatively lower success ratios (61.96%) of estimation with cross-validation and pairwise Fst values, it might be due to the genetic background or structure of these reference American populations themselves, rather than the AIM-InDel loci we chose. The previously reported researches indicated that American populations have mixed and complex ancestral origins due to extensive gene exchange and population migration [In values of some loci and the ancestral inference efficiency of the AIM-InDel panel in the American populations were largely due to the mixed ancestral origins of the American populations. In general, the 39 AIM-InDel panel developed by ourselves was an effective, practical, and easy-operated tool, which could be successfully used to infer the ancestral informative inference of five intercontinental populations except the relatively lower efficiency in American populations. At the same time, it could be well applied in the current forensic DNA laboratory.It has been pointed out that the small-scale panels with highly ancestral informative genetic markers could achieve the same effect on ancestral inference efficiency as the system with a great many of loci , 30. Theigration , 32. TheBesides, many genetic studies conducted by different genetic markers such as STR, Y chromosome haplogroup, and HLA-DRB1 also revealed that the Hui group had closer genetic relationships with East Asian populations –35. As fIn this study, we assessed the ancestral inference efficiency of a self-developed 39 AIM-InDel panel and also explored the ancestral components of the Hui group. Multiple statistical analyses were conducted in order to assess the efficiency and to validate ancestry inference of this novel AIM-InDel panel. And this panel showed the satisfactory distinctions in four intercontinental populations and could be applied in forensic genetic analysis, anthropological research, and genetic epidemiology. The results of ancestral inference and population genetic analyses revealed that the Hui group shared relatively higher East Asian ancestry proportion (88.87%) and was genetically closer to East Asian populations . As for the Chinese Hui group in different regions, to further reveal its genetic background and migration history, more reference populations need to be involved in our future study.


Biological control—the use of organisms  for the suppression of insect pest species—is a well-established, ecologically sound and economically profitable tactic for crop protection. This approach has served as a sustainable solution for many insect pest problems for over a century in North America. However, all pest management tactics have associated risks. Specifically, the ecological non-target effects of biological control have been examined in numerous systems. In contrast, the need to understand the short- and long-term evolutionary consequences of human-mediated manipulation of biological control organisms for importation, augmentation and conservation biological control has only recently been acknowledged. Particularly, population genomics presents exceptional opportunities to study adaptive evolution and invasiveness of pests and biological control organisms. Population genomics also provides insights into (1) long-term biological consequences of releases, (2) the ecological success and sustainability of this pest management tactic and (3) non-target effects on native species, populations and ecosystems. Recent advances in genomic sequencing technology and model-based statistical methods to analyze population-scale genomic data provide a much needed impetus for biological control programs to benefit by incorporating a consideration of evolutionary consequences. Here, we review current technology and methods in population genomics and their applications to biological control and include basic guidelines for biological control researchers for implementing genomic technology and statistical modeling. Biological control—the use of natural enemies or biological control organisms such as terrestrial arthropods, microorganisms and invertebrates  to suppress populations of agricultural pests—has been a successful pest management tactic for over a century ,2,3. MotHowever, human-mediated release of biological control organisms may have short- and long-term consequences for the evolution of (a) prey/hosts , as well as (b) released populations of biological control organisms, (c) native (resident) populations, that may compete with released biological control organisms and (d) associated endosymbiont/microbial diversity (collectively termed as ‘non-target’ effects) which could detrimentally affect other species that interact with the biological control organisms . At the With the advent of modern sequencing technologies and statistical methods to analyze large-scale genetic data, agriculturalists and geneticists are increasingly applying population genomics as a means to enhance our understanding of the evolution of biological control organisms and insect pests ,15,16. SThis review focuses on a range of fundamental issues that have been addressed using population genomics in general but have yet to be applied to gain a better understanding of biological control. We first summarize different methods of biological control and population genetic models that can be used to describe them. We then focus on four core issues involving population genomics and biological control—(1) population size change, (2) natural selection and adaptive evolution in novel environments, (3) gene flow and (4) inbreeding. Finally, we provide recommendations and an outline of suggested steps (a ‘pipeline’) for researchers to facilitate use of available genomics methods to assess biological control. The emphasis of this review is on entomophagous species, that is, predators and parasitoids that attack insect pests.Coccinella septempunctata [Biological control of insect pests can be classified broadly into three methods, based on the mode(s) of manipulation of biological control organisms—importation, augmentation and conservation. In this review, we discuss importation and augmentation, the two methods in which arthropod biological control organisms are released into the environment. Most introduction histories of entomophagous species are complex sequences of demographic events. These sequences of events in turn determine current genomic diversity, population densities, sustainability and thus success of biological control. Also, although detailed historical introduction records have been maintained for many species of biological control organisms —specificpunctata —the qualpunctata ,21. Howe(a) Importation biological control is defined as the introduction of biological control organisms in a single or repeated pulse(s) into a previously unoccupied environment [Rodolia cardinalis [ironment . Examplerdinalis  and manyrdinalis ,6. Imporrdinalis , Figure Trissolcus japonicus) of an introduced insect pest species, Halyomorpha halys [Harmonia axyridis [Coccinella septempunctata [Apis mellifera scutellata, in hybrid zones in North and South America and found no significant reduction in genetic diversity due to bottlenecks and rapid expansion. They combine these findings with a study of differential fitness, showing that natural selection has played a role in maintaining high genetic diversity in hybrid bees.Serial founding of biological control organisms can occur naturally due to invasiveness or be anthropogenically mediated due to importation. Examples of serially founded biological control organism populations include an egg parasitoid : The size of the population that is evolving neutrally due to random genetic drift. In a randomly mating population of constant size and in the absence of natural selection, this Ne should be equivalent to the census size, Nc. The Ne of a population is often approximated as a measure of its genetic diversity.Census Population Size (Nc): The number of individuals in a population of a species. Changes in the census size  will also affect the rate of evolution by genetic drift and therefore the population’s effective population size, Ne. Nc is difficult to measure in nature, especially in natural enemies.Natural Selection: Changes in allele frequencies in a population due to differential fitness of alleles or combinations of alleles.Genetic Drift: Fluctuation in allele frequencies in a population due to random sampling of alleles from one generation to the next.Bottleneck: Decrease in the census size, Nc of a population, owing to importation or augmentation, leading to a decrease in its effective population size, Ne.Genetic Diversity: The diversity of alleles across genomic loci in a population  or the average heterozygosity across genomic loci. Genetic diversity of a population is directly affected by is Nc (and therefore Ne), mating processes (random versus non-random mating), geographical population structure and natural selection.Hybrid Vigor: Increased fitness of hybrid strains. In natural enemies, this could be quantified as increased fecundity, mating success, range expansion and invasiveness, competition success, resource utility.Deleterious Mutations: Alleles that confer lower absolute fitness and thereby lower relative fitness of genotypes that carry this allele in a population.Adaptation: Survival, reproduction and viability of heritable advantageous traits due to natural selection.Meiotic Recombination: Exchange of genetic material between maternal and paternal chromosomes during meiosis. Recombination landscape is affected by genetic drift and natural selection.Sexual Selection: Pre-mating barrier to gene flow, owing to differential mate choice. In arthropods, this could include wing or elytral patterning, chemical cues, vocalizations and size variation.Inbreeding: Non-random mating between close relatives within a population. Inbreeding could be opportunistic  or due to sexual selection.Inbreeding Depression: Accumulation of deleterious mutations in inbred populations, leading to decreased fitness.Migration/Gene Flow/Admixture/Introgression: Physical movement and reproduction (therefore recombination) of migrant individuals from one population into another.Genetic Linkage: Co-inheritance of collinear segments of DNA owing to reduced recombination between them.Linked Selection: Co-inheritance of non-recombinant segments of DNA due to natural selection on a linked genetic locus.Genetic Hitchhiking: Process of co-inheritance of variants in non-recombinant segments of DNA due to positive natural selection on a linked genetic locus.Selective Sweep: Pattern of reduced genetic diversity in non-recombinant segments due to genetic hitchhiking.Quantitative Trait Loci: Genomic loci that control variability in quantitative phenotypes.Epistasis: Interaction across variants at different genomic loci, contributing towards variability in a trait.Sequencing Depth/Coverage: The average number of times every single nucleotide has been sequenced.Sequencing Read: A contiguous piece of DNA that is obtained from a sequencer, that have to be assembled to form contigs or often chromosome-size scaffolds.SNP’s: Single Nucleotide Polymorphisms - variants at a single nucleotide locus.(b) Augmentation biological control embodies biological control organisms that were originally imported but failed to persist in their new environment and have their populations augmented through repeated releases, typically annually [Encasia formosa and egg parasitoids in the genus Trichogramma [Cryptolaemus montrouzieri and over 230 commercially available arthropod species [en masse) can also be repeatedly introduced into an environment where they have already been established  Successful biological control programs can result in the establishment of introduced populations over a broad geographic range, sometimes through non-anthropogenic assisted range expansions. Examples of this process have been noted in the literature, including parasitoid Aphelinidae and Braconidae hymenopterans ,32, the  conicus  and nume conicus ). This s conicus ,36, Figu conicus  could po(b) Introduced populations of biological control organisms are often small. Thus their successful establishment depends on numerous factors, including adaptability to local environments, availability of hosts/prey and competitors. Modeling effective population size declines are thus informative of changes in genomic diversity in introduced populations and of potential utility in conservation biological control. Alternatively, unsuccessful introductions summarized in References ,38, are Importantly, numerous statistical methods use population genomic data to rigorously identify the best-fitting demographic model for a particular biological control system see . FurtherPost-introductory demographic history of biological control organisms can be complex to model but can be characterized by estimating four major “parameters” of populations using genomic data—population size change, adaptation, admixture or migration and inbreeding , Box 1)Box 1). HBottlenecks and change in effective population sizes both influence genomic diversity of species. Species utilized for biological control are subject to both these processes, depending on their natural history and interactions. Newly introduced populations of biological control organisms often undergo bottlenecks, where a relatively small sample of founder individuals from a larger population is introduced into a novel environment ,76,77,78Harmonia axyridis—[Conversely, population size growth can be enhanced in introduced populations via “invasiveness” or the uncontrolled growth of a population in a non-native (introduced) environment  and provides a much more informative alternative to otherwise detailed and labor intensive census size estimation. Applied in combination with other population genomics statistics, effective population size estimation is a means to building hypotheses to explain the success or failure of biological control programs see .Populations of biological control organisms in new environments, apart from undergoing population size change, are also subject to adaptive evolution in response to selection. Broadly, selection nudges populations towards fitness peaks .The genetics of adaptive evolution in introduced and invasive species have been studied extensively but not in the context of biological control ,86,87,88Multiple introductions of the same species, including populations from different geographic sources, can play a prominent role in local adaptation, invasiveness and boosting genomic diversity in populations of biological control organisms. Biological control has the distinction of having extensive introduction records over recent time scales ,19, thusGene flow can occur to varying extents between proximal established populations of biological control organisms and even between established populations and newly introduced populations of biological control organisms.Ongoing gene flow between newly introduced and established populations of biological control organisms ,100,101 Beyond gene flow per se, reduced fitness of hybrid populations (outbreeding depression) has been observed during reintroduction episodes  due to eNon-random mating of close relatives in a population reduces genetic diversity, elevates homozygosity and fixes deleterious mutations (genetic load) ,95,106. Hippodamia convergens [Harmonia axyridis [Inbreeding, although widely expected during primary introductions of species for biological control, is yet to be characterized in most species at the genetic level. Some cases of inbreeding have been reported in field populations of the convergent lady beetle, nvergens  and in taxyridis . HoweverH. convergens, lack phenotypic variability despite genetic differences and exhibit equitable success in pea aphid utilization [Estimating inbreeding using genetic data from populations of biological control organisms in conjunction with assays of fecundity, competition and efficiency of feeding on pests can inform success of biological control programs. For example, lab-inbred (Eastern and Western USA) populations compared to outbred (augmented Eastern-Western USA hybrid) populations of lization . Tools tWhat comprises a successful biological control program? As summarized by  based onRodolia cardinalis, to suppress the cottony-cushion scale, Icerya purchasi, has been employed for over a century. Vedalia beetles are specialists, multivoltine, long-lived and highly efficient in obtaining prey [C. septempunctata [H. axyridis , are underway. Additionally, a growing literature on landscape genomics methods  establish, persist and grow in an introduced environment, (ii) withstand environmental and genomic pressures and evolve adaptively, (iii) avoid “escaping” into invasiveness and (iv), broadly, limit differential non-target effects. These factors are phenotypic differences in traits, which have underlying genomic differences within and between populations and ecological variation across geographically distinct populations of the species. Drawing on a classic example, the successful introduction of the vedalia beetle, ing prey . Importaing prey ,111. Thupunctata ,113 and rized in ,115 highrized in . UltimatRendering biological control more predictable, thus increasing the estimated 10 percent of reported attempts being successful, has been a long-term goal of applied ecologists and entomologists Gurr & Wratten, 1999 and Gurr et al., 2012  argue thH. axyridis has successfully established populations across the world owing to importation for biological control and invasiveness. Due to its known historical record of introduction, Lombaert et al., 2010 [Define biological questions about the system and build a hypothesized quantitative model of evolution based on mode of biological control. Is there a historical record of introductions in other regions, trophic-level interactions and ecological success parameters  [Conduct genotyping/sequencing. Strategies for obtaining molecular sequence or genotype information are contingent primarily on previously available genomic information from the species of interest. For example, many arthropod genomes are currently available (476 as of May 2020), with more in the works  . Alternaat_ncbi)  via techat_ncbi)  and Poolat_ncbi)  offer opat_ncbi) ,98,127.www.galaxyproject.org) [Undertake preliminary bioinformatics steps involved in sequence/genotype clean-up, assembly, alignment and variant calling. Pipelines and tools have been developed to ease processing genomic/genotypic/sequencing data, including GATK , vcftoolect.org) ,134.Perform exploratory analyses. Calculate Method of Moments estimates of summary statistics, including heterozygosity, polymorphism, diversity indices, differentiation, allelic richness and inbreeding coefficients. Tools that bundle methods to estimate most basic summary statistics from genomic data include STACKS , VCFToolPerform secondary analyses. Build data-sets  that satisfy assumptions of the model or method of choice. Each method listed in st—[Simulate/estimate parameters under the model. The choice of programs for estimating demographic parameters depends on the type of genomic data . Genotypst— and othest—,141, D sst—,142 can Model selection. Demographic models often oversimplify the irrefutably complex reality of how populations evolve. However, statistics allow us to rigorously identify a model that explains the data better. Depending on the statistical methods applied, commonly utilized model-selection paradigms include likelihood ratio tests  and AkaiInterpret estimated parameters under the “best” model, reconciling assumptions and biology of the system. The final step involves using a statistically informed explanation of the biological processes affecting populations of introduced biological control organisms and discussing the caveats of using model-based population genomics.Beginning with the development of biological control as a major tactic for pest management during the 20th century, an appreciation that biological control was not only applied ecology but also had a foundation in genetics and evolution, was gained. Still, for most of the 1900s, the major emphasis of the discipline remained on ecological principles, with notable exceptions ,153,154.


Ovisaries) breeds: Pantaneira, Bergamácia, Dorper, White Dorper, Ile deFrance and Hampshire Down, to obtain their population genetic parameters andinvestigate the origin of these sheep populations reared in the State of MatoGrosso do Sul. The analysis of mitochondrial DNA allowed to infer theirphylogenetic relationships and revealed significant differences among them whencompared with each other and with sequences obtained from GenBank. Through theformation of haplotypes, it was noted that the Pantaneira breed served as thematernal basis for the formation of the other breeds reared in the region, andit was possible to suggest a European origin for the sheep populationsstudied.Recent molecular tools and technologies have marked the discovery of the originand domestication processes of a wide variety of species, using either genomicor mitochondrial molecular markers to provide input for selection programs, aswell as the management and conservation of animal breeds. This study aimed toanalyze genes of mitochondrial DNA of the following sheep ( Ovis aries), including thosethat were developed from breeds imported by settlers soon after their discovery.Over the years, these animals underwent natural selection, resulting in breeds thatare now considered naturalized, locally adapted, or native . Therefore, this study aimed to evaluate different genes ofmitochondrial DNA in naturalized and exotic breeds of sheep in tropical altituderegions to obtain population genetic parameters and investigate the origin of theseBrazilian populations.The study of locally adapted breeds by menas of mitochondrial markers allows torecognize the origin and to genetically characterize the different populations thatpossibly comprise them. Several studies were made to determine the phylogeneticorigin of criollo or endemic breeds from a particular country (Ovis aries) breedsreared in the central west tropical altitude region in the State of Mato Grossodo Sul (MS), Brazil, were collected and used for DNA extraction and sequencing, cytochrome b gene(CytB) and control region (D-loop), were amplified . The ampST), haplotype (H) and nucleotide (π) diversity wereall calculated in ARLEQUIN 3.5 software  with the reference sequence AF010406 identified by Data related to haplotype (H) and nucleotide (π) diversity for each studiedbreed, based on the analysis of different genes of mitochondrial DNA, aredescribed in vs. exotic breeds, the molecular variance withinpopulations was higher than among populations, as expected. However, when AMOVAwas performed comparing MS populations vs. representatives ofGenBank reference sequences, the percentage of variation was inverse, that is,higher between populations (> 60%) than between individuals (> 30%).The results of AMOVA for the three groups, analyzed using different genes ofmitochondrial DNA, are shown in p < 0.05), but the differentiation was notobserved when the comparison was done between naturalized and exotic breeds.Higher values of Fst  were observed when the Brazilian breedswere compared with the five exotic GenBank sequences that represented thedistinct haplogroups.It was possible to observe a genetic differentiation between the different breedsraised in MS (Variability in mtDNA was found in populations of the State of Mato Grosso do Sul(MS), as individuals were distributed in 19 haplotypes . Each WhST: 0-0.05(negligible), 0.05-0.15 (moderate), 0.15-0.25 (significant), and above 0.25(high genetic differentiation). According to these authors, the FSTvalue for Group 1, where only the populations of the State of Mato Grosso do Sulwere analyzed, indicated a moderate genetic differentiation (0.08). In Group 2 there was slight geneticdifferentiation between animals (0.04). In Group 3, where the GenBank referencesequences were included, the FST value was 0.66 indicating highgenetic differentiation. In group 3, the high observed variation between thepopulations evaluated in this study and the populations represented in GenBankmay have been generated by the absence of haplotypes that represent thehaplogroups described in the ovine species in the MS breeds. In groups wheregenetic differentiation was moderate (Group 1) and high (Group 3) there was alsoa significant genetic distance between the individuals , thus elucidating the genetic distanceobserved when compared to the Pantaneira breed. The Brazilian Bergamácia breedis the result of processes of adaptation and natural selection of animalsimported into Brazil, with the last import occurring during the 1930s. Sincethen, the animals of the Brazilian Bergamácia breed have been isolated fromtheir Italian ancestors and, although they have been on Brazilian land forseveral years, the breed standard was created only in 1977 . Dorperis an exotic breed, also originating from South Africa, with maternal heritageof Asian origin in its mitochondrial genome, which may be the reason for thedistance found.With the exception of the Hampshire Down breed, all breeds evaluated havedifferent haplotypes. In the most frequent haplotypes , it can Ovis aries)sampled from various geographically disperse regions. Among these five, A and Bare the haplogroups identified with greater frequency, and they grouped with theanimals of Asian and European origin, respectively. Both were first identifiedby Ovis aries was sampled.When comparing the Pantaneira breed with animals of the Creole breed of SouthernBrazil, using the ND5 gene of mitochondrial DNA, Haplotypes H14 and H15 , formed The analysis of mitochondrial DNA provided an overview of phylogeneticrelationships among populations of sheep in the State of Mato Grosso do Sul, aswell as significant differences between them when compared with each other andwith the sequences obtained from GenBank.Through the formation of the haplotypes, it was observed that the Pantaneirabreed served as the maternal basis for the formation of other breeds reared inthe region. This puts in evidence the urgent need to maintain conservationnuclei of the Pantaneira breed to safeguard the genetic basis of thispopulation, avoiding that it can be used indiscriminately in absorbent crosses.Although it was possible to suggest a European origin for the sheep populationsstudied, further studies using more representative sequences are needed todetermine their origins.