Eucalyptus moluccana), a common and widespread tree species of the family Myrtaceae in eastern Australian woodlands, and its previously proposed four subspecies moluccana, pedicellata, queenslandica, and crassifolia. A range of phylogeographic analyses were conducted to examine the population genetic differentiation and subspecies genetic structure in E. moluccana in relation to biogeographic barriers. Slow evolving markers uncovering long term processes (chloroplast DNA) were used to generate a haplotype network and infer phylogeographic barriers. Additionally, fast evolving, hypervariable markers (microsatellites) were used to estimate demographic processes and genetic structure among five geographic regions (29 populations) across the entire distribution of E. moluccana. Morphological features of seedlings, such as leaf and stem traits, were assessed to evaluate population clusters and test differentiation of the putative subspecies. Haplotype network analysis revealed twenty chloroplast haplotypes with a main haplotype in a central position shared by individuals belonging to the regions containing the four putative subspecies. Microsatellite analysis detected the genetic structure between Queensland (QLD) and New South Wales (NSW) populations, consistent with the McPherson Range barrier, an east‐west spur of the Great Dividing Range. The substructure was detected within QLD and NSW in line with other barriers in eastern Australia. The morphological analyses supported differentiation between QLD and NSW populations, with no difference within QLD, yet some differentiation within NSW populations. Our molecular and morphological analyses provide evidence that several geographic barriers in eastern Australia, including the Burdekin Gap and the McPherson Range have contributed to the genetic structure of E. moluccana. Genetic differentiation among E. moluccana populations supports the recognition of some but not all the four previously proposed subspecies, with crassifolia being the most differentiated.We have investigated the impact of recognized biogeographic barriers on genetic differentiation of grey box ( E. moluccana and the formation of the four subspecies.Our molecular and morphological analyses provide evidence that several geographic barriers in eastern Australia, including the Burdekin Gap, the McPherson Range and the Sydney Sandstone Belt, have contributed to the genetic structure of  Eucalyptus moluccana, across its wide distribution in eastern Australia. Using genetic and morphological analyses, we found that geographic and biological barriers have shaped its population genetic structure and contributed to the formation of subspecies. However, admixture among four proposed subspecies was detected, suggesting recent divergence. Our findings are important for conservation and revegetation efforts as this species occurs across a large climatic gradient with potential for local climatic adaptation.Landscapes include barriers to dispersal and gene flow, and their effects on species vary over evolutionary time. We have assessed the impact of known barriers on the ecologically important woodland tree, 1In contrast to the generally low topographic relief of Australia, eastern Australia has a moderate elevation profile provided by the Great Dividing Range (GDR), which was formed through several periods of tectonic uplift over the past 70 Myr  have influenced the genetic structure of widely distributed animals such as the sedge frog  based on morphological differences, including the number of flowers per peduncle, inflorescence type, capsule shape, presence of capsule pedicel, leaf shape, and proportion of box‐type bark  identified which particular geographic and habitat barriers contributed to the genetic structure, and (c) assessed whether the suggested subspecies are isolated by these barriers. We hypothesized that there is genetic differentiation among the subspecies of E. moluccana and that this differentiation might be due to biogeographic barriers reducing connectivity among subspecies. Moreover, if this genetic differentiation is strong, we would be able to see morphological differentiation of seedlings (in particular juvenile leaves) among the subspecies grown in the same environment.In this study, we (a) evaluated whether biogeographic barriers have played a role in the genetic structure of 22.1Eucalyptus moluccana Roxburgh, E. hemiphloia F. Muell. 1866), commonly known as the grey box or gum‐topped box, is a member of the eastern grey boxes   were plotted on a map using the ALA interface. Excluded were very old records and records lacking coordinate decimals and records of specimens that were not within woodlands or woodland fragments. Then records of occurrence for E. moluccana were used to determine whether this species occurs within regions defined as habitat barriers.2.2E. moluccana, from localities at least 50 km apart from each other. In NSW, the distribution of E. moluccana is clustered in open grassy woodlands found in the plains and valleys; however, in QLD, populations are scattered, with substantial gaps within the northern part of its range  was obtained from the NSW Seed Bank  and The Australian Tree Seed Centre (CSIRO). Seed collection included a total of 17 localities. Seeds were germinated as specified before, and leaves were collected from seedlings. For our genetic analyses, a single seedling was sampled from each mother tree.2.3Eucalyptus species have heteroblastic leaves (leaf type depends on tree age), and juvenile leaf morphology is a taxonomically informative feature  protocol was followed Doyle,  to extra2.5psbA‐trnH is among the most variable regions of the chloroplast in E. moluccana .The intergenic region 2.6Eucalyptus species was performed: 52 were designed based on the nuclear genomes available for E. globulus, E. grandis, E. gunnii, and E. urophylla . The number of Ks in the dataset was evaluated by using ΔK values estimated with the software STRUCTURE Harvester. The software CLUMPP 1.1 was used to find optimal alignments of independent runs  and putative southern subspecies (moluccana and pedicellata) , whereas the southern putative subspecies moluccana and pedicellata seemed to have narrower leaves  grouped together on one side of the plot and samples from NSW (putative subspecies moluccana and pedicellata) on the other side . From the 253 samples, 113 were misidentified by the analysis, mostly due to incorrect assignments to putative subspecies queenslandica and crassifolia, suggesting that there is no clear morphological differentiation among these two putative subspecies at young stages. At 18 months, there was an even greater overlap among subspecies  and southern (NSW) populations, representing putative northern subspecies  Figure . Furthers Figure . Interese Figure . The pets Figure .3.3psbA‐trnH revealed twenty haplotypes with a main haplotype in a central position shared by individuals belonging to the five regions and the four subspecies . Similarly, Haplotypes 11 and 13 were shared between samples of Regions 4 and 5 (putative subspecies pedicellata and moluccana). Haplotype 11 included individuals from northern NSW (Bom State Forest) and from the Sydney Basin (Bellevue Park), whereas Haplotype 13 included samples from near the Hunter Valley  and the Sydney Basin   corresponding to regions that contained the putative subspecies pedicellata and moluccana. The structure was detected between the QLD and NSW populations separated by the BVB biogeographic barrier. Notably, the second best number of clusters estimated by the Evanno method was K = 5 . The putative subspecies pedicellata was represented by one cluster with high admixture (mainly samples with a high proportion of red). Finally, the putative subspecies moluccana was represented by one cluster with individuals that had a high proportion in orange. Further substructuring  and was more distant from the other clusters. Cluster 2 was predominantly formed by individuals from Regions 2 and some of 3, hypothesized to be subspecies queenslandica, and a low proportion of the other subspecies. Cluster 3 was formed mainly by individuals from Region 3. Cluster 4 was formed mainly by individuals of Regions 4 and 5 (subspecies pedicellata and moluccana)  Regions 1 to 5 and (b) QLD and NSW populations following results represented in Figure crassifolia was most distant). Although the PCoA analysis , there was a high overlap between all regions. The Mantel test revealed that there was a significant correlation between the geographic and genetic distance .DAPC detected four genetic groups: Cluster 1 contained all the samples from the subspecies ) Figure . Clusters Figure  showed ts Figure  showed s4E. moluccana that matches some biogeographic barriers described for eastern Australia  compared with other species of Eucalyptus  to the north of the BG were the most differentiated ones. A similar pattern was found in E. grandis and C. citriodora  contains dry woodlands and lowland savanna that separate the northern wet tropics rainforests and monsoonal habitats from the southern mesic habitats. Populations of E. moluccana in the region north of the StLG, which corresponds to a different bioregion  and with a different vegetation community that may act as a barrier for E. moluccana.The St Lawrence Gap (StLG) between Mackay and Rockhampton in central QLD contains open woodlands and savannah  is a mountain block of rainforest along the border of QLD and NSW. The structure analysis (K = 2) supports McR acting as a barrier to gene flow between the putative northern and southern subspecies of E. moluccana grows abundantly throughout this area, including also populations to the west of the HVB. Therefore, it is unlikely a barrier to grey box, but rather the more mesic vegetation  on the ranges to the south may reduce gene flow between the Hunter Valley and the Sydney Basin. Furthermore, populations of E. moluccana in the Sydney region are surrounded by an elevated sandstone belt formed by the Blue Mountains and the Hornsby Plateau on which E. moluccana does poorly, and these formations may form a barrier against populations further north. Moreover, the population from Putty close to the Hunter Valley, but part of the Hawkesbury–Nepean catchment of the Sydney Basin, clustered with samples of the Sydney Region, an indication that river systems may influence the structure of this species.The Hunter Valley (HVB) is a dry habitat and acts as a biological barrier  from the NSW subspecies (pedicellata and moluccana) was the leaf ratio and one of the vectors further separating subspecies pedicellata from the other species was the pedicel length at 6 months of age. However, despite the small sample size of subspecies pedicellata, it had the highest variance suggesting inclusion of more samples could reduce this separation. The lack of genetic and morphological differentiation between subspecies moluccana and subspecies pedicellata suggest they are likely just one subspecies. At 18 months, the slight differences in morphology decreased, and this is expected as leaves of Eucalyptus are heteroblastic, and they seem to exhibit significant differences during seedling stage but change during the development to be more uniform at maturity. Thus, leaf morphology of seedlings does not seem to be as effective to differentiate among subspecies as it has been found when comparing different species  from southern (NSW) populations which are divided by the BVB/McR. Additionally, the subspecies crassifolia which was more genetically distant is also more isolated. Admixture among the subspecies was readily detected, suggesting recent divergence or contact. Our study provides the first in‐depth genetic characterization of E. moluccana, a widely distributed and ecologically important tree species that is dominant in grassy woodlands of eastern Australia. Its population genetic diversity and structure are important in the context of conservation and revegetation efforts of grassy woodlands as highlighted for a close relative, the inland grey box Eucalyptus microcarpa ; Formal analysis (lead); Investigation ; Software (lead); Validation (lead); Visualization (lead); Writing‐original draft (lead); Writing‐review & editing (lead). Paul D. Rymer: Conceptualization (supporting); Data curation (supporting); Funding acquisition (supporting); Project administration (supporting); Resources (supporting); Supervision (supporting); Validation (supporting); Writing‐review & editing (supporting). Niveditha Ramadoss: Formal analysis (supporting); Software (supporting); Visualization (supporting); Writing‐original draft (supporting); Writing‐review & editing (supporting). Markus Riegler: Conceptualization (lead); Data curation (supporting); Funding acquisition (lead); Investigation ; Project administration (lead); Resources (supporting); Supervision (lead); Validation (supporting); Writing‐review & editing (supporting).Supplementary MaterialClick here for additional data file.


Bombina orientalis). The results showed that the strong seismic activity of the Yilan–Yitong fault zone in the late Quaternary period was the main reason for the population differentiation of Oriental fire‐bellied toad in northeast China. The Quaternary Pleistocene glacial interglacial cycles led to the significant bottleneck effect of the western population located in the Maoer mountain area. As a result, the western population has low genetic diversity. Recent gene flow between eastern and western populations and historical evidence of population expansion proved that the dispersal behavior of the western populations was the main cause of the low genetic diversity and mitochondrial and nuclear discordance. Human economic activity may be the mainly driving factor. These evidences showed that the comprehensive influence of geology, climate, human activities and other factors should be considered in the process of exploring the evolutionary history of species.The evolutionary history of a species is generally affected by the combination of geological events and climate fluctuations. By analyzing the population features, genetic structure and the effective population historical dynamics of existing species, the population evolutionary history can be reestablished. In recent years, geological evidence shows that the Yilan–Yitong fault zone located in Northeast Asia experienced strong and frequent geological changes in the late Quaternary period. Species population history has been shaped by the combination of the complex climatic conditions of the Quaternary and Pleistocene glacial interglacial cycles and palaeogeological events in Northeast Asia and it has become a research focus for evolutionary biology researchers. In this study, mitochondrial and microsatellite molecular markers were used to reveal the population features, genetic structure, and the effective population historical dynamics of the Oriental fire‐bellied toad  in northeast China. Our study showed that the strong seismic activity of the Yilan–Yitong fault zone in the late Quaternary period was the main reason for the population differentiation of Oriental fire‐bellied toad in northeast China. Further research in this direction will provide important insights into forecasting population dynamics in the face of global change, such as the identification of key population‐specific traits for maintaining the evolutionary potential or assessing differences in population vulnerability depending on spatial patterns of biodiversity.In this work, we use mitochondrial and microsatellite molecular markers to reveal the evolutionary history of the Oriental fire‐bellied toad ( Geological events lead to changes in the topography of the original habitat of organisms, forming obstacles such as mountains and rivers, which lead to population diffusion, reduction of gene flow between populations and result in the differentiation of a population's genetic structure  in northeast China. Different branches were in refuges in different regions during the Pleistocene glacial epoch, which resulted in genetic differentiation among the lineages, but the warm and humid climate of the interglacial period led to population expansion and the two lineages had secondary contact in the eastern Liaoning Province, which resulted in strong gene flow  showed that all lineages of G. brevicaudus seemed to be unaffected by glacial cycles during the Late Pleistocene and vicariance patterns dominated its history  population to prove this point, and to provide a reference for other biological groups that share a sympatric distribution.The climate change created by Quaternary and Pleistocene glacial interglacial cycles was an important historical factor affecting the distribution of species in Northeast Asia. Frequent climate fluctuation cause changes in the distribution of species, especially in temperature sensitive species , and (3) linkage disequilibrium (LD) of 12 microsatellite loci. The Hwe and null allele frequencies tests were performed for each microsatellite loci in each sample site. Tests for LD were performed based on each pair of microsatellite loci. A sequential Bonferroni method was used to calibrate the p‐values. The microsatellite loci with no high null allele frequency conformed to Hwe and without linkage inheritance in each population were selected to further determine the genetic structure and diversity of populations.The DNA from toe tissue samples was extracted using the phenol‐chloroform extraction method  and mitochondrial cytochrome b (Cytb) genes were based on the COI and Cytb sequences published on GenBank and designed using Primer Premier v.5.0  and reverse primer (5’‐GATACGACATAGTGGAAGTGGGCTAC‐3’). The Cytb was amplified using forward primer (5’‐GTATGTCACCCAACCTCCGAAAATC‐3’) and reverse primer (5’‐CAACTGGTTGTCCTCCAATTCATG‐3’).The specific primers used to amplify mitochondrial cytochrome c oxidase subunit I  included 20ng of template DNA, 0.2 µl Taq DNA polymerase (5 U/µl), 1 µl MgCl2 (25 mM), 1µl dNTP Mixture (2.5 mM each), and 0.80 µl of each primer (10 µM) in 2.5 µl 10 × PCR buffer. All PCRs were conducted with the following reaction profile of 5 min for initial denaturation at 95°C, followed by 30 cycles of 95°C denaturing for 1 min, 56°C annealing for 1 min, 72°C extension for 1 min and a final additional extension step at 72°C for 10 min. PCR products were sequenced in both directions using an ABI3730XL machine (Applied Biosystems). Complete sequences were compared visually to the original chromatograms to avoid reading errors. Sequences were aligned manually with BioEdit v.7.0.9 Hall, .2.2K values between 1 and 10 were examined. Each K value was set to run ten independent simulations and a burn‐in period of 106 iterations followed by 105 Markov Chain Monte Carlo (MCMC) iterations. The posterior probability of K from each independent run was used to infer the optimum number of clusters. As the ∆K method of Evanno et al.  haplotypes were constructed using median‐joining networks with Network v.10.1  + I + G substitution model was used with a Yule process tree prior. We set priors for calibration points based on the divergence between B.bombina  and B.variegata  following a previous study of Bombina  of 3.3–3.9 Mya. Tracer v.1.6 , number of haplotypes (H), haplotype diversity (Hd), nucleotide diversity (π) and average number of nucleotide differences (K) were estimated with DnaSP v.5.0 , mean number of effective alleles (Ne), expected heterozygosities (He) and observed heterozygosities (Ho) in GenAlEx v.6.5 software  in Bottleneck v1.2.2  between populations in different regions were estimated by the Bayesian algorithm implemented in Migrate‐n v 4.4.3  and Cytb (885 bp) sequences were obtained. The results of LD test showed that there was no LD across any pair of loci. The null allele frequency of loci 19, 141 and 23 in each sampling site was significantly higher than that in other loci (Table Hwe (p < 0.01)  Table . Therefo3.2K) among the 13 sample sites, the program Structure was used with microsatellite DNA. Our analysis revealed that the microsatellite DNA were divided into two populations (K = 2), with ∆K value at this time as the largest. As described earlier, cluster I incorporated the western population and cluster II incorporated the eastern population  was 38, number of polymorphic sites (S) was 42, haplotype diversity (Hd) was 0.774, nucleotide diversity (π) was 0.00182 and the mean number of nucleotide differences (K) was 3.245. The level of genetic diversity of the eastern population was significantly higher than that of the western population. In general, Oriental fire‐bellied toad in northeast China showed high haplotype diversity and low nucleotide diversity . The western population showed low haplotype diversity and low nucleotide diversity  and the eastern population was the same as the overall level, showing high haplotype diversity and low nucleotide diversity . The genetic diversity of each sample site is shown in Table The results of populations genetic diversity calculation based on microsatellite and mitochondrial gene data are shown in Table Na) and effective alleles (Ne), observed heterozygosity (Ho) and the expected heterozygosity (He) were used as indicators to measure the genetic diversity based on 9 polymorphic microsatellite loci of 523 individuals from 13 sample sites. For the overall population, Na was 8.611, Ne was 3.710, Ho was 0.540 and He was 0.610. The western population  had a lower genetic diversity than the eastern population . The genetic diversity of each sample site is shown in Table The mean number of alleles , indicating that it had experienced the bottleneck effect, while the western population had a significant p‐value in all models except the IAM model, also showing that it had experienced the bottleneck effect.The bottleneck effect test results are shown in Table p < 0.01) and −6.831 (p < 0.01) respectively, indicating that there was expansion event in the recent history of the western population. The eastern population showed a multi‐peak distribution in the mismatch distribution curve, and the values of Tajima' D and Fu's Fs were −1.104 (p = 0.115) and −14.164 (p < 0.01), indicating that the eastern population was stable in the recent history.The western population showed a unimodal Poisson distribution in the mismatch distribution curve Figure , and the3.5west→east = 390.622 ≈ Meast→west = 394.758), while the nuclear genes mainly flowed from the western population to east (Mwest→east = 3.175 > Meast→west = 0.427). The gene flow value of the mitochondrial genes was significantly higher than that of nuclear genes.Migrate was used to analyze gene flow and migration between the eastern and western populations of Oriental fire‐bellied toad. The results showed that there was symmetrical gene flow of mitochondrial genes between the two populations ; Data curation ; Formal analysis ; Investigation ; Visualization ; Writing‐original draft (lead); Writing‐review & editing (lead). Shuai Zhao: Data curation ; Formal analysis ; Investigation . Yanshuang Shi: Investigation ; Validation . Fanbing Meng: Investigation ; Validation . Chunzhu Xu: Conceptualization (lead); Funding acquisition (lead); Project administration (lead); Resources (lead); Supervision (lead); Writing‐review & editing (lead).Table S1‐S5Click here for additional data file.


Ticks cause substantial production losses for beef and dairy cattle. Cattle resistance to ticks is one of the most important factors affecting tick control, but largely neglected due to the challenge of phenotyping. In this study, we evaluate the pooling of tick resistance phenotyped reference populations from multi-country beef cattle breeds to assess the possibility of improving host resistance through multi-trait genomic selection. Data consisted of tick counts or scores assessing the number of female ticks at least 4.5 mm length and derived from seven populations, with breed, country, number of records and genotyped/phenotyped animals being respectively: Angus (AN), Brazil, 2,263, 921/1,156, Hereford (HH), Brazil, 6,615, 1,910/2,802, Brangus (BN), Brazil, 2,441, 851/851, Braford (BO), Brazil, 9,523, 3,062/4,095, Tropical Composite (TC), Australia, 229, 229/229, Brahman (BR), Australia, 675, 675/675, and Nguni (NG), South Africa, 490, 490/490. All populations were genotyped using medium density Illumina SNP BeadChips and imputed to a common high-density panel of 332,468 markers. The mean linkage disequilibrium (LD) between adjacent SNPs varied from 0.24 to 0.37 across populations and so was sufficient to allow genomic breeding values (GEBV) prediction. Correlations of LD phase between breeds were higher between composites and their founder breeds (0.81 to 0.95) and lower between NG and the other breeds (0.27 and 0.35). There was wide range of estimated heritability (0.05 and 0.42) and genetic correlation (-0.01 and 0.87) for tick resistance across the studied populations, with the largest genetic correlation observed between BN and BO. Predictive ability was improved under the old-young validation for three of the seven populations using a multi-trait approach compared to a single trait within-population prediction, while whole and partial data GEBV correlations increased in all cases, with relative improvements ranging from 3% for BO to 64% for TC. Moreover, the multi-trait analysis was useful to correct typical over-dispersion of the GEBV. Results from this study indicate that a joint genomic evaluation of AN, HH, BN, BO and BR can be readily implemented to improve tick resistance of these populations using selection on GEBV. For NG and TC additional phenotyping will be required to obtain accurate GEBV. Ticks and tick-borne diseases are among the most important causes of production losses for beef and dairy cattle. Recent estimates of those losses range from US$22 to 30 billion per year . Cattle Genomic selection is typically suggested as a solution for improvement of traits that are hard or costly to measure. However, in the case of tick resistance, the trait is so labor intensive and expensive to measure that only small reference populations have been recorded in countries where ticks prevail –5. ThereIn this study, we pool tick resistance phenotyped reference populations from beef cattle breeds in Australia, Brazil, and South Africa. Firstly an assessment is made of the extent of phase of linkage disequilibrium shared between the breeds, as a predictor of how much information might be transferred from breed to breed in genomic predictions when a high density SNP array is used e.g. , 8]. We . We 8)].Rhipicephalus microplus and R. australis), whereas cattle in South Africa are additionally infested with the multi-host tick species Amblyomma hebraeum and Hyalomma rufipes and H. truncatum. Tick counts in South Africa were obtained from the Rhipicephalus (53%), Amblyomma (42%) and Hyalomma (5%) species.Tick datasets were obtained from seven different cattle populations generated in Brazil, Australia and South Africa Table 1.Brazilian data consisted of log-transformed tick counts. Measurements were performed on occasions when large phenotypic variation existed in tick numbers, by manually counting adult female ticks that were at least 4.5 mm length on one whole side of the animal’s body . One to For South African Nguni (NG) cattle, adult ticks were counted from the perineum body part under natural grazing for a continuous period of two years (2012 to 2014) from 490 Nguni animals. At least 23 tick counts were conducted for each animal throughout a two-year period, meaning at times there was little phenotypic variation for tick counts across animals. Tick counts (x) were log transformed using log10 (x + 1) to approximate normality. Data available for NG cattle was summarized as the average animal tick effect obtained in ASREML  and Tropical Composite (TC) animals had estimates of tick counts derived from tick scores. Tick scores of adult female ticks that were > 4.5 mm in diameter on the left side of each animal, were on a 0 - 5 scale where 0 was no ticks, 1 was ≤ 10 ticks, 2 was 11 - 30 ticks, 3 was 31 - 80 ticks, 4 was 81 - 150 ticks, and 5 > 150 ticks. Tick scores are less accurate and less informative than tick counts, however there is a high genetic correlation between the two (−7) were considered in the analyses. In addition, only the SNP with highest MAF was retained when SNPs were observed in the exact same position or the genotypes were highly correlated (r > 0.98). Similar quality control steps were applied to the Australian populations and NG, with the addition that genotype calls with a GC score below 0.6 were set to missing and were filled in with imputation using FImpute  with marker densities varying from 27k to 150k given by commercially available chips. Genotype quality control (QC) was implemented for all populations. In the case of Brazilian data QC was performed by R/SNPStats package . Samples FImpute . After q FImpute  and an H FImpute , and fin FImpute .2) (Linkage disequilibrium (LD) was estimated for each chromosome between adjacent pairs of SNPs as the squared correlation statistic (r2) , which cAρ, aρ, Bρ and bρ are the frequencies of alleles A, a, B and b, respectively; ABρ, abρ, Abρ and aBρ are the haplotype frequencies among alleles in the population.where ij(A)r and ij(B)r for a common set of adjacent SNPs between populations A and B was calculated using the following equation r in population A and ij(B)r in population B, AS and BS are the standard deviation of ij(A)r and ij(B)r respectively, and ijr across adjacent SNP i and j within the interval l for populations A and B for a common set of markers. The 2r and r values were estimated using adjacent SNPs with the ld_estimate R scripts  plot of all animals by breed was obtained from genotype data using PreGSf90 software .Data quality checks for the Brazilian populations were performed using R program . ContempThe statistical models for all populations except NG included the fixed effect of contemporary groups; the linear covariate effects of individual zebu breed composition and heterozygosity, according to their expected values based on pedigree information, and the linear and quadratic covariate effects of animal age. For pre-adjusted NG data only an overall mean was fitted as fixed effect. Additionally, direct additive genetic, permanent environmental and residual random effects were included for the Brazilian populations that had repeated tick count measures and only the direct additive genetic and residual effects were considered for Australian and South African populations with single measurements. The models can be represented in matrix notation by the following equations:yb’s are vectors of the tick infestation trait for each bth breed, b=AN, HH, BN, BO, TC, BR, and NG, respectively for Angus, Hereford, Brangus, Braford, Tropical Composite, Brahman and Nguni breeds. Similarly, for each bth breed, βb’s are the vectors of systematic effects, ub’s are the vectors of random direct additive genetic effects, pb’s are the vector of random permanent environmental effects , and the eb’s are the corresponding vectors of random residual effects. Additionally, each bth breed also has its own incidence matrices of systematic, direct additive genetic, and animal permanent environmental effects, respectively represented by Xb’s, Zb’s, and Wb’s.where: the As Brazilian populations had ungenotyped individuals with phenotype, we used a multi-trait single step genomic BLUP (ssGBLUP) approach , 20, witbth breed, bth and cth breeds, ⊗ denotes the direct product between the matrices, and H is a relationship matrix constructed by combining the pedigree and genomic relationship matrices variance components and genetic parameters were estimated using Bayesian inference by Gibbs sampling, with the Gibbs2f90 program  in multibth breed derived from multi-trait model described above (Equation [3]), as follows:Univariate breed-specific analyses were performed considering the records and the marginal model for each Similarly, the marginal distributional assumptions were derived from equations [4], [6], and [7] as:These single trait/breed analyses were used as controls to check the advantages of jointly analyzing all breeds, and they used the same variance component estimates as the multi-trait analyses to maintain equivalent dispersion of breeding values for each breed under both strategies (single and multi population predictions).û) between whole (w) and partial (p) datasets between subsequent genetic evaluations when phenotypes are added for validation animals,The utility of our reference populations to predict tick resistance and future phenotypes in single and multiple trait/breed genomic analyses was evaluated using the linear regression (LR) approach proposed by Legarra and Reverter . This meE≈ pacc/wacc. Here acc is the “population accuracy”, i.e. the correlation between true and estimated breeding values in the candidates for selection, which is a property of a population, not of an individual  in the multivariate analyses and the full set of genotyped and phenotyped animals for each breeds for univariate analyses. The partial datasets were derived for each population by two strategies, the first was the old-young where only 2/3 of the phenotypes pertaining to the older animals were retained in the partial data and the remaining 1/3 younger animals had their phenotypes set to missing and served as the validation group in both, uni and multivariate analyses. Additionally, for multivariate analyses only, a second strategy referred as other-pops consisted of removing from the analysis all phenotypes of the target population for validation and deriving predictions exclusively from the genetic correlations of the target with the other populations/breeds with full datasets included. When the w,pP is large (closer to one), the partial data reliably predicts the whole data. As additional validation statistics, we calculated the predictive ability defined as the correlation between phenotypes adjusted for fixed and permanent environmental effects (y*=yb-Xbβb-Wbpb) and ûp ) , which was used to evaluate the degree of inflation/deflation of the genomic predictions.which is a function of the prediction accuracy with expected value of dividual . Here, t) , where ûG matrix  of the G matrix Figure 1The clusters for the NG and AN samples have low dispersion reflecting their genetic homogeneity as opposed to more scattered and therefore heterogeneous samples of composite breeds  and HH Figure 1r2 between adjacent SNPs ranged from 0.24 ± 0.34 to 0.37 ± 0.35 across all chromosomes for cattle populations from Brazil, Australia, and South Africa. The r2 among chromosomes was similar within all breeds as observed in The mean ± standard deviation r2 values. Conversely, the NG (0.24 ± 0.34) and BR (0.24 ± 0.27) breeds had lower r2 among the studied breeds. Lower LD estimates at short distances are an indication of large ancestral population sizes and have been reported for indicine cattle compared to taurine cattle  and HH (0.37 ± 0.35), had higher LD values than the other populations. The composite breeds from Brazil, BN 0.30 ± 0.28) and BO (0.31 ± 0.27) and TC (0.30 ± 0.29) from Australia had intermediate  ± 0.28 ae cattle . This is ± 0.35 ar2 was > 0.3 for more than 40% of neighboring SNPs only in HH and BO breeds (data not shown). In relation to the other breeds, the mean r2 > 0.3 were about 30% for NG and BR and, around 38% for BN, AN, and TC.Furthermore, the 2r between adjacent markers of 0.20 would suffice [e.g.  of linkage phase were used to estimate the haplotype-sharing between pairs of adjacent SNPs across breeds  to 0.95 (HH vs. BO)  to 0.87 (HH vs. TC). The smallest values were found for NG vs. all other breeds  Table 2.A,BR was relatively low for several breed pairs, especially those including the NG breed, and between taurine AN and HH and indicine BR  of 0.001 or less.All 39 estimated variance components passed a convergence test based on the Geweke’s criterion . The meais trait . The Ausis trait . Nonethemont Red  and depeThe largest genetic correlation among all studied populations was observed between BN and BO. These two breeds are composites with about 3/8 of zebu composition, mostly Nelore in our samples, and the other 5/8 being taurine of British origin, Angus or Hereford. This result indicates a very similar additive genetic mechanism for tick resistance in both populations. The second largest relationship was observed between AN and its composite with zebu, the BN breed, and this is not surprising because the average expected contribution of AN to BN is approximately 62.5%. Even though AN and BN are more closely related than BN and BO, the higher genetic correlation between the latter pair could be related to greater indicine impact on tick resistance , 41. BraPredictive ability, as a measure of the GEBV to predict the observed phenotype, was improved under the old-young validation for three of the seven populations using the multi-trait approach compared to a single trait within-population prediction. Moreover, we observed improvement for the partial and whole data GEBV correlation in all cases by using multi-trait analysis under old-young Table 4,The multivariate validations based on data of other populations only (other-pops), which were included to evaluate the possibility of predicting tick resistance for populations that do not have a reference population for this trait, had in general a poorer predictive performance compared to uni and multivariate old-young validations for all parameters evaluated Table 4.Braford was the breed with highest predictive ability in all criteria in all analyses: uni or multivariate Table 4.h2 for tick counts of this breed  for tick resistance, which if developed and validated, could be used to greatly enlarge the reference populations for genomic prediction and to improve the accuracy of GEBV for this trait, as well as potentially improving tick control through cattle management .Even though more extensive phenotyping should be a continuous effort to improve the accuracy of GEBV for tick resistance, old-young validation results from this study 4 indicafernando.cardoso@embrapa.br.The data analyzed in this study is subject to the following licenses/restrictions: The raw datasets cannot be made available because they are the property of the Breeders and Institutions involved in generating them and this information is commercially sensitive. For scientific research purposes, the data requests should be forwarded along with the research proposal to the corresponding author email: Ethical review and approval was not required for the animal study because it was developed using already existing datasets. Written informed consent was obtained from the owners for the participation of their animals in this study.FC, OM, AD, NM, HB, MY, RP-W and BH conceived and designed the study. FC, OM, MY, RP-W, GC, and BH performed data analyses. FC wrote the manuscript draft. C-GG, NM and AM participated in the design and acquisition of data. All authors contributed to the article and approved the submitted version.http://www.beefcrc.com/). Australian contributions were funded by the Commonwealth Government funding through the CRC program, Meat and Livestock Australia and the Australian Centre for International Agricultural Research. The cattle used in the research were contributed by producers from the Northern Pastoral Group, and their financial support of this project is also gratefully acknowledged. This research was funded in part by the Bill & Melinda Gates Foundation and with UK aid from the UK Foreign, Commonwealth and Development Office (Grant Agreement OPP1127286) under the auspices of the Centre for Tropical Livestock Genetics and Health (CTLGH), established jointly by the University of Edinburgh, SRUC , and the International Livestock Research Institute. The findings and conclusions contained within are those of the authors and do not necessarily reflect positions or policies of the Bill & Melinda Gates Foundation nor the UK Government. Work at The Roslin Institute was funded by Biotechnology and Biological Sciences Research Council through Institute Strategic Programme Grant funding (BBS/E/D/30002275). Nguni data collection and genotyping was supported through research grants from the Red Meat Research and Development of South Africa (RMRD-SA), Technology Innovation Agency (TIA) and the National Research Foundation (NRF) Grant No: CPRR14071676305.Brazilian contributions and data funded by Conselho Nacional de Desenvolvimento Científico e Tecnológico, Grant/Award Number 305102/2018-4 and Empresa Brasileira de Pesquisa Agropecuária, Grant/Award Numbers 02.12.02.008.00, 02.13.10.002, and 12.13.14.014.00. Australian contributions and data were funded through Phases 2 and 3 of the Beef Cooperative Research Centre (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 western honey bee is one of the most ecologically and economically important pollinator species. Due to human interference, it faces serious challenges, not only in number decline and habitat loss, but also in natural subspecies diversity and distribution. The conservation of genetic diversity and perseverance of locally adapted populations and subspecies becomes a crucial task in the face of rapid environmental changes. In order to further assess present genetic variability in Serbian honey bee populations, we analyzed 14 microsatellite loci and then compared nine of them with previously published data. Our results suggest that Serbia now harbors a distinct, relatively homogenous honey bee population, although some local differences are still preserved.A. m. macedonica subspecies from its historical distribution range in southern Serbia as well as the lack of distinctive geographical groups suggest that selective breeding, queen import, and migratory beekeeping practices strongly influence the genetic structure and diversity of honey bees, leading to the genetic uniformization and creation of the admixture population.Socioeconomic interests and beekeeper preferences have often taken precedence over the conservation of locally native honey bee subspecies, leading to the predominance of admixture populations in human-dominated areas. To assess the genetic diversity of contemporary managed Serbian honey bee colonies, we used 14 microsatellite loci and analyzed 237 worker bees from 46 apiaries in eight localities of northern and southern Serbia. Furthermore, we compared data for nine microsatellite loci with 338 individuals from Italy, Hungary, Poland, and Spain. The standard parameters of genetic diversity in Serbian honey bee populations were in line with other analyses, although somewhat smaller. STRUCTURE analysis showed the existence of two equally distributed genetic clusters and Analysis of molecular variances could not confirm the presence of a geographically discrete population but showed local differences. Discriminant analysis of principal components showed overlapping of worker bees from different parts of Serbia. Clear genetic differentiation can be observed when comparing all populations between geographical regions and their corresponding subspecies. The absence of the  Apis mellifera Linnaeus, 1758) is one of the species that is a subject of constant human interference. Although its domestication began more than 10,000 years ago, this species has never become truly domesticated despite all efforts, mainly due to its complex mating behavior [The western honey bee  have been hybridized in varying degrees in most of their native areas and in some parts, such as Germany, have been almost replaced by A. m. carnica because local beekeepers preferred this subspecies [Since the classical Ruttner categorization of the bspecies , there hbspecies ,7,8,9, ibspecies ,11, but bspecies  showed abspecies  and divibspecies ,14,15,16bspecies . When suontinent ,19,20,21ontinent ,24,25,26bspecies . The losbspecies .Due to the spread of Varroa mites in the last decades of the twentieth century, it was believed that wild honey bee colonies became extinct in Europe, but now new evidence is emerging that some areas have thriving feral or even possibly wild honey bee colonies ,30,31,32A. mellifera subspecies, natural hybridization occurs [A. m. macedonica and A. m. carnica) which are clinaly distributed from the northwest (carnica) to the southeast (macedonica) with a hybrid zone between them [leu-cox2tRNA of which two are novel [A. mellifera in this region. In the past 30 years, the variability of Serbian honey bees has been extensively described on morphological [A. m. carnica and A. m. macedonica in the central part of Serbia can be detected, populations from the northwest and southeast retain a distinctive subspecies genetic footprint [leu-cox2 mtDNA variability [carnica-2 ecotype, and those from southern Serbia forming a different distinct genetic cluster characterized as the macedonica-1 ecotype.It is noted that in areas that are natural contact zones of different n occurs ,41 and tn occurs ,26,42,43een them ,26,44,45re novel  and threre novel  reflect ological , etiologological ,50, and ological ,51,52,53iability  confirmeA. m. carnica queens intensified, and the number of queen breeding institutions focused on its desired traits is growing. Serbia is one of the countries that has embedded in its legislation the preservation of autochthonous species, subspecies, and races, and as per the Law on Animal Breeding from 2009, breeding and keeping of only A. m. carnica are allowed in its territory [leu-cox2 mtDNA region [However, beekeeping practices in Serbia have changed dramatically in the last decade. First, the number of managed beehives has doubled since 2009 , partly erritory . Recent A region  suggestsA. mellifera subspecies [A. m. mellifera, A. m. carnica, A. m. iberiensis, A. m. ligustica, and the Buckfast hybrid.Biparental inherited microsatellite loci proved to be an excellent genetic marker for inferring overall population genetic variability, deciphering the distribution of different bspecies ,56, detebspecies ,26, and bspecies ,57. Largbspecies  for 338 A. m. mellifera, A. m. carnica, A. m. iberiensis, A. m. ligustica, and Buckfast hybrid from Péntek-Zakar 2015 were obtained for comparison.A total of 237 worker bees were collected from 46 stationary apiaries during late August and early September in 2020 and stored in 95% ethanol at −20 °C for further analysis. Eight localities from southern and northern parts of Serbia were chosen, four in the south (Leskovac (L), Vlasina (V), Stara Planina (SP), and Tromeđa (T)) and four in the north (Subotica (S), Vršac (Vr), Deliblatska pesščcara (DS), and Fruška Gora (FG) . ApproxiWhole-genomic DNA was extracted using the protocol described in . The conA. m. carnica from A. m. macedonica. For the amplification of mtDNA COI fragment, the following primers were used: 5′-GATTACTTCCTCCCTCATTA-3′ [NcoI and StyI restriction enzymes were performed according to the protocol described in [The PCR-RFLP method described by  was usedCATTA-3′  and 5′-ACATTA-3′ . The PCRribed in ,61.4)2SO4, 2.5 mM MgCl2, 0.8 mM dNTP mix, 1 U of reverse Taq polymerase , and 5 pmol of each forward and reverse primer. For the amplification of the microsatellite loci, 1.5–1.9 ng of DNA was used. To verify the reliability of the data, 10% of samples were reamplified for the second time.For comparison of different honey bee colonies on the autosomal level, we have 14 microsatellite loci described in . The choTo use data from the study  we perfoFor fragment analysis, the first and second multiplex reactions were multipooled, and the third and fourth multiplex reactions were multipooled. All reactions were mixed in equal volumes and plated as one reaction in a volume of 1 μL. Each amplification mix contained seven different loci. GeneScan 600 LIZ size standard was used to score alleles . Fragment analysis was performed on the 3130 Genetic Analyzer . Data were analyzed using Gene Mapper Software .O) and expected (HE) heterozygosity, random match probability (RMP), and the mean number of pairwise differences (MPD)) were calculated using Arlequin ver. 3.5.2.2 software [STF and ISF values. The statistical significance of all performed tests was assessed with 10,000 permutations. The matrix of pairwise population STF values was visualized using a multidimensional scaling method (nonmetric MDS) implemented in the PAST 3.25 software [The standard parameters of genetic diversity for microsatellite loci , number of private alleles based on a minimal sample size (obtained by rarefaction), observed  . This meNcoI and StyI did not show a restriction pattern characteristic for mtDNA lineage found in A. m. macedonica. Since no restriction sites were observed after RFLP analysis, we presume that all individuals in our sample belong to A. m. carnica [The size of the PCR-amplified COI segment for the RFLP analysis was 1029 bp. Digestion with both  carnica ,61.ISF values varied between −0.04 in T and 0.19 in Vr , all north and south/north  comparisons . OverallThe AMOVA performed across all 14 loci showed a low but significant value of genetic variance between localities (0.047), with 1.42% of the genetic variance being attributed to the variation among localities . When lop ranging 0.2–0.3, indicating admixture. The MDS plot placed localities separately from each other, which is in correlation with AMOVA, suggesting the presence of distinct genetic variability in all analyzed localities. However, there is no clear grouping of localities according to their geographical region, which is also in concordance with AMOVA.The results of the analysis performed by the DAPC method are shown in K = 2 is the most likely scenario  with 10.79% of the genetic variance being attributed to the variation among the localities . A negatThe results of AMOVA were further corroborated by DAPC analysis  and the K = 8 is the most likely scenario . Together with the equal distribution of two clusters inferred by STRUCTURE analysis in all localities and cluster overlapping inferred by DAPC analysis, the presented results indicate population admixture and a relatively homogenous population. However, local differences are still preserved since significant STF values can be observed between pairs of localities, and some differentiation may be observed according to the position of population in DAPC and MDS landscapes.Although significant A. m. macedonica and north/south differences between individuals from different parts of the country previously reported for the Serbian honey bee population [leu-cox2 for the same sample [A. m. carnica and A. m. macedonica subspecies in the central part of Serbian territory was previously described [A. m. carnica subspecies can be present in apiaries which, with a growing number of A. m. carnica queen manufacturers, may also contribute to the observed loss of A. m. macedonica and the admixture of the Serbian honey bee population.Our results could not confirm the presence of pulation ,26,53 bue sample . Both unescribed ,26, and A. m. iberica from Spain is represented by its own cluster in STRUCTURE analysis as well as clearly separated in MDS and DAPC plots. The Italian A. m. ligustica is represented by its own structure cluster which is present in the Hungarian Buckfast sample as expected. The same result was obtained from DAPC and MDS analysis. The Polish populations of A. m. carnica and A. m. mellifera were located close to each other but still separated. The Hungarian population is well separated from the other populations studied, and although relatively homogeneous, some A. m. ligustica introgression may be observed, as previously reported by [STF value can be observed. Structure analysis showed weak but still detectable introgression of A. m. ligustica alleles, which is in concordance with our field data that some illegal importation of Italian bees occurred in the past, since this subspecies has been one of beekeepers’ favorites. Two distinct clusters can be observed in the Serbian honey bee population, and they are almost equally distributed among localities, suggesting population admixture.Population structure analysis showed that each geographical region and each corresponding subspecies are separated. orted by . SerbianA. mellifera subspecies within any given geographical region. However, this genetic diversity is under constant anthropogenic influence due to the modernization of beekeeping practices, such as migratory beekeeping, importation of foreign queens, and even legal practices [A. m. macedonica and colder ones preferring A. m. carnica and, although relief and ecological differences exist between these two parts of the country, climate conditions are favorable for both subspecies, and the main reason between their distinct distribution may lie in isolation by distance. The distances between the southern and northern parts of Serbia may be too great for bees, but for beekeepers they are rather small and they readily travel 500 km in the flowering season for different plants. Together with a vast increase in the number of beehives and beekeepers in the past decade [Our results suggest that, as already shown in many studies , geograpractices ,33,35,37t decade  and legiUnfortunately, socioeconomic interests and beekeeper preferences for more productive and gentler individuals have often taken precedence over the conservation of locally native subspecies ,37,39, l


Mus musculus) populations on four islands along with paired putative source populations to test genetic predictions of island colonization and characterize locally fixed Cas9 genomic targets. Patterns of variation across the genome reflected marked reductions in allelic diversity in island populations and moderate to high degrees of differentiation from nearby source populations despite relatively recent colonization. Locally fixed Cas9 sites in female fertility genes were observed in all island populations, including a small number with multiplexing potential. In practice, rigorous sampling of presumptive LFA will be essential to fully assess risk of resistance alleles. These results should serve to guide development of improved, spatially limited gene drive design in future applications.Introduced rodent populations pose significant threats worldwide, with particularly severe impacts on islands. Advancements in genome editing have motivated interest in synthetic gene drives that could potentially provide efficient and localized suppression of invasive rodent populations. Application of such technologies will require rigorous population genomic surveys to evaluate population connectivity, taxonomic identification, and to inform design of gene drive localization mechanisms. One proposed approach leverages the predicted shifts in genetic variation that accompany island colonization, wherein founder effects, genetic drift, and island‐specific selection are expected to result in locally fixed alleles (LFA) that are variable in neighboring nontarget populations. Engineering of guide RNAs that target LFA may thus yield gene drives that spread within invasive island populations, but would have limited impacts on nontarget populations in the event of an escape. Here we used pooled whole‐genome sequencing of invasive mouse ( House mice are comprised of three primary subspecies: the western house mouse (M. m. domesticus), eastern house mouse (M. m. musculus), and the southeast Asian house mouse (M. m. castaneus), with varying levels of gene flow among lineages at contact zones , a recent survey identified at least 35 islands with endangered or critically endangered species where house mice were the only invasive rodent present . At present, control of invasive mice on islands relies almost exclusively on anticoagulant rodenticides, which can often be effective, but also face limitations due to lack of species specificity, high costs of application, and persistence in the environment , Sand Island 510 ha), Thevenard Island (550 ha), and Whitlock–Boullanger Islands  , followed by mapping to the GRCm38/mm10 mouse reference assembly (https://www.ncbi.nlm.nih.gov/grc) using bwa v0.7.12  across all autosomal biallelic sites following the method proposed by Fischer et al. , which ranges from 0 (complete panmixis) to 1 (no shared genetic diversity), between paired population samples was estimated in R using the ANOVA method in the poolfstat package  samples from three populations , 22 M. m. musculus (Mmm) samples from three populations , and 10 M. m. castaneus (Mmc) samples from India  were filtered for autosomal biallelic SNPs that had less than 10% missing genotypes and were present in all three species datasets, resulting in a total of 4,527,839 loci. Allele frequencies were estimated using VCFtools v0.1.16  was set at 20, the proportion of sites used to estimate the AFS (‐r) was set to 0.0005, the per‐site transition probability (‐k) was set to 1e‐10, and the starting value for AFS estimation  was set at 0.0018. Only regions supported by high posterior probabilities (>0.9999 for the hidden state “selection”) were retained. To further characterize the role of selection in shaping island population genetic variation, we used BEDtools v2.28.0  implemented in the Python program Pool‐hmm , and jvarkit  or occurred anywhere within the “core” of a putative gRNA target site  using the regioneR package  based on 32,273 exons in the mm10 annotation showed the similar patterns of reduced diversity in island mice  was more than twice that observed for any other population pair. Using Wright’s  for 18 terms. Notably, four of the top ten terms were related to hormone activity, of which two involve somatotropin (growth hormone).Analysis with Pool‐hmm identified hundreds to thousands of potential selective sweeps in each population (range 988–4756) with an average of 135.5 (SD = 59.7) sweeps inferred per autosome per population. We note that this method, which infers selective sweeps based only on deviations from genome‐wide AFS, is agnostic with respect to underlying genomic features and likely includes a proportion of false positives. Thus, because we were particularly interested in the consequences of selective sweeps on islands, we evaluated the intersection of these regions across the four island study populations, resulting in a total of 336 selective sweep regions with a combined length of 34.5 Mbp that were common to all island populations. Among these island selective sweeps, 249 overlapped with 608 protein‐coding genes in the mm10 annotation Table . Gene on3.5S. pyogenes Cas9 PAM site or were located within the core of a potential gRNA target (nucleotide positions +4 to +7 bp upstream of existing PAM), (3) occurred within a genic CDS or 5’UTR, and (4) were associated with genes that caused female infertility (in knockout experiments). While a large number of locally fixed Cas9 target sites were observed in genic regions (mean = 8597 SNPs across islands), <2% of these were in genes associated with female infertility.Results of genomic scans of pool‐seq data for LFA targets in each population pair are summarized in Table Filtering of remaining SNPs for varying allele frequency cutoffs in the “source” population had substantial effects on the final numbers of LFA identified Table . ApplyinZ = 3.17, p < 0.003; Midway: 3 (37.5%), Z = 2.89, p < 0.028; Thevenard: 6 (60.0%), Z = 2.18, p = 0.041; and Whitlock–Boullanger: 137 (77.8%), Z = 2.52, p = 0.010.Filtering for loci with intermediate allele frequencies (≤0.50) in the “source” population resulted in counts ranging from 8 (Midway Island) to 22 (Whitlock–Boullanger Islands). Genomic locations, alleles, flanking sequences, and estimated allele frequency for each SNP are provided in Table Zar1), for which we identified a 2‐plex set of LFA in the Thevenard Island population; hexokinase 1 (Hk1), which harbored LFA in both Thevenard and Whitlock–Boullanger Islands; and desmoglein 3 (Dsg3), for which two LFA in close proximity (552 bp) were identified in both Thevenard and Whitlock–Boullanger Islands.Detailed characterization of candidate genes that harbored LFA was carried out only for the loci with intermediate (≤0.50) “source” population allele frequencies, as this threshold arguably provides the most reasonable balance of gene drive design flexibility with minimized risk to nontarget populations. Overall, we identified 40 unique female fertility genes with Cas9 targets (either PAM‐forming SNPs or SNP‐containing gRNA core sequences) in the CDS or 5′UTR that were fixed in the island population Table . Further4The application of homing endonuclease gene drives to management of rodent pest populations has attracted considerable attention  were more similar to continental populations compared to other islands in the dataset  release sites for a gene drive biocontrol. Consistent with predictions of invasive populations on small and isolated oceanic islands, mice from island sites exhibited reduced genome‐wide allelic diversity. In the Honolulu population, which was established from anthropogenic introductions to the island of Oahu, both measures of allelic diversity , likely due to historical demographic linkages or a direct island colonization event. At the same time, our estimates of Rattus spp.) into the niche vacated by suppressing mouse populations.Our results also provide several insights regarding the feasibility of the LFA approach for spatially limiting gene drive on islands. This strategy requires identification of Cas9 binding sites with genetic variants that are fixed within the target island population and preferably at a low allele frequency in nontarget populations. To counteract resistance alleles, LFA targets should be clustered closely together to facilitate multiplexed gRNA and occur within critical regions of haplosufficient female fertility genes that have minimal pleiotropic effects. Our results from analysis of four island–source population pairs suggest that, in practice, there may often be only a small number of sites that fit all of these criteria. The number of LFA targets identified was notably sensitive to the allele frequency cutoff in the “source” population. The absence of any suitable LFA when applying the strict filter (≤0.15) suggests that, for these islands, ongoing migration, insufficient time since colonization, stabilizing selection, or some combination of factors has prevented dramatic shifts in allele frequencies that are often observed on islands. At the other extreme, allowing for high allele frequencies (≤0.95) in the “source” population resulted in an expanded number of potential targets with multiple multiplex gRNA options. The trade‐off, however, is an increased risk of effects on nontarget populations in the event of a gene drive escape due to a higher frequency of susceptible alleles. While the gene drive is expected to rapidly be eliminated in such a scenario due to the presence of resistance alleles  were common across all populations. However, the absolute numbers of LFA identified were largely concordant across the four island–source pairs studied, which, with the exception of Broome and Thevenard Island, all showed similar levels of moderate population differentiation. The abundance of LFA is expected to increase with island population genetic differentiation, suggesting that the LFA approach may prove most relevant for extremely isolated and genetically differentiated islands. We also note that our analysis here considered only the canonical PAM for Dsg3 are able to birth pups, but subsequently unable to maintain viable litters (Kountikov et al., Hk1 leads to complete infertility in homozygous females, but also has broader deleterious effects on both sexes due to severe anemia (Peters et al., Zar1 have normal ovary development and oogenesis, but embryos fail to develop past the single cell stage (Wu et al., Despite relatively low numbers of LFA targets overall, our analyses identified 40 genes that harbored LFA Cas9 targets. Further characterization highlighted three potential candidate genes with attractive properties for a population suppression gene drive application. All three candidate genes are associated with female infertility in homozygous knockouts, though evidence from the literature suggests that females lacking The reduced island allelic diversity observed across islands in our study suggests a strong role for genetic drift and founder effects in generating LFA. At the same time, we also detected a significant association between potential selective sweeps and LFA, with 38%–78% of LFA SNPs occurring within putative selective sweeps in each population. This is in itself perhaps unsurprising given that selective sweeps are characterized by regions of reduced diversity, but it does suggest a contributing role for selection in the presence of LFA in island mouse genomes. Selection could lead to LFA in island mouse genomes if positive selection for island‐selected phenotypes results in selective sweeps in associated regions. Our analysis of selective sweeps shared among island populations highlighted a gene set that was enriched for hormone function in general and growth hormone specifically. This result is interesting given that behaviors and body size are among the most commonly observed differences associated with insularity in rodent populations (i.e., “island syndrome,” Adler & Levins, In evaluating the overall feasibility of the LFA approach, there are several important considerations highlighted by our study. On the one hand, targeting LFA is attractive in part due to its relative technical simplicity, as it arguably would require no more sophisticated molecular components beyond the CRISPR‐Cas homing gene drive construct with a gRNA for each allele targeted. On the other hand, as with many other proposed gene drive strategies, the approach is sensitive to resistance alleles in the target population, as even low frequencies will dramatically undermine drive efficacy on islands (Unckless et al., In conclusion, we note that, while only a small fraction of sites fit the criteria for LFA given the gene drive design considered, our scans of genomic variation in island mice identified thousands of SNPs within Cas9 target sites in genic CDS and 5’UTR that were fixed in the island populations. This result is similar to a recent study of wild mosquito populations that found abundant fixed Cas9 targets in protein‐coding regions (Schmidt et al., Supplementary MaterialClick here for additional data file.Table S4Click here for additional data file.Table S6Click here for additional data file.


Periparus ater) hybrid zone in Nepal. Intermediate phenotypes between the distinctive western “spot‐winged tit” (P. a. melanolophus) and Eastern Himalayan coal tits (P. a. aemodius) occur across a narrow range of <100 km in western Nepal. As a peculiarity, another distinctive cinnamon‐bellied form is known from a single population so far. Genetic admixture of western and eastern mitochondrial lineages was restricted to the narrow zone of phenotypically intermediate populations. The cline width was estimated 46 km only with a center close to the population of the cinnamon‐bellied phenotype. In contrast, allelic introgression of microsatellite loci was asymmetrical from eastern P. a. aemodius into far western populations of phenotypic P. a. melanolophus but not vice versa. Accordingly, the microsatellite cline was about 3.7 times wider than the mitochondrial one.In the Himalayas, a number of secondary contact zones have been described for vicariant vertebrate taxa. However, analyses of genetic divergence and admixture are missing for most of these examples. In this study, we provide a population genetic analysis for the coal tit ( In our study, we analysed patterns of divergence and admixture in the Himalayan hybrid zone of coal tits across a transect of about 1400 km from Afghanistan to East Nepal. Due to the scarcity of study material from that region only a few phylogeographic or population genetic studies exist from this area. In these cases, museum collections are a valuable source of genetic material, such as the large collections from Afghanistan and Nepal from the 1960ies to 1970ies at ZFMK Bonn used in this study. We used DNA extracts from previous studies  from frozen tissue samples using primers L16700 (5′‐ATCATAAATTCTCGCCGGGACTCT‐3′) and H636  and Far East Russian populations (P. a. ater) from Pentzold et al. , and another sequence of the blue tit, Cyanistes caeruleus (JF828052) as a more distantly related relative. The best‐fit model estimated with MrModeltest v.2  and to the gamma‐shape parameter . For inference of divergence times estimates, we applied a molecular clock calibration using mean substitution rates for different domains of the CR estimated by Lerner et al. , haplotype diversity (Hd), nucleotide diversity (π), and Tajima's D with DNASP v. 5.10.01  following the manufacturer's instructions. For each of the two multiplex approaches a primer premix was prepared containing 10 µl primer solution (10 ng/µl) for each primer filled up to a total volume of 500 µl. For each sample, a total multiplex reaction volume of 13.5 µl contained 6.25 µl Master‐Mix (Type‐it Kit), 1.25 µl primer mix, 4 µl ddH2O, and 2 µl DNA. The thermo‐cycling protocol for both multiplex sets was (i) denaturation at 95°C for 5 min followed by 30 cycles for fresh DNA extracts (35 cycles for toe pad DNA extracts) with (ii) denaturation at 95°C for 30 s, (iii) annealing at 56°C for 1 min 30 s, and (iv) elongation at 72°C for 45 s and a final elongation phase at 60°C for 30 min. Fragment length analysis was performed on a 16‐column ABI 3130xl capillary sequencer (Applied Biosystems™) for total volumes of 10 µl containing 1 µl diluted muliplex PCR products (1:10 for toe pad samples and 1:25 for frozen tissue/blood samples), 8.5 µl Hi‐Di™ Formamid (Applied Biosystems™), 0.25 μl GeneScan™‐600 LIZ® dye size standard, and 0.25 μl ddH2O.We performed pilot analyses using a set of 13 microsatellite loci developed for European coal tit populations by Tritsch et al. . We desiParus major) populations  we repeated the microsatellite genotyping for that locus in a separate PCR to account for possible allelic dropout that can typically occur with degraded DNA from historical samples . We converted raw allele size data from Excel sheets to generate input files for various population genetic software packages using CONVERT v. 1.31  spot‐winged‐type hybrids from Dolpa and Baglung Districts , (3) cinnamon‐bellied hybrids from Dhorpatan, (4) pale‐bellied hybrids from Myagdi District, (5) P. a. martensi from Mustang and Parbat Districts, (6) P. a. aemodius from Rasuwa and Sindhupalchok Districts. We calculated locus specific observed and expected heterozygosities , mean allele numbers per locus, mean allelic richness (AR) and inbreeding coefficients (FIS) for each sample population with the software FSTAT v. 2.9.3.2  eastern lineage: P. a. aemodius and P. a. martensi, and (3) admixed: all phenotypic hybrids.In addition to STRUCTURE analyses, we examined our microsatellite data with Principal Component Analysis (PCA) using the R package Jombart,  executedJombart,  for thre2.5pmin and pmax fixed at 0 and 1, set to estimated values or fit to observed values) and five possible tail fittings . Previous applications of HZAR for cline analyses focused, for example, on hybrid zones of newts . Local admixture of the two haplotype lineages was found across all phenotypic hybrid populations from western Nepal Myagdi District  and pale‐bellied hybrids from Myagdi District.Local mitochondrial gene pools in Afghanistan and mid‐western Nepal (Humla District) comprised only haplotypes of the western t Figure . HaplotyP. a. melanolophus and eastern P. a. aemodius. PCA for 10 loci distinguished two separate clusters of western and eastern parental lineages with hybrid populations from western Nepal showing a greater overlap with the western P. a. melanolophus cluster  showed signs of admixture between the two genetic clusters  or to the western lineage (5 out of 16 spot‐winged‐type hybrids). Even phenotypical P. a. melanolophus from Afghanistan (who represented an unadmixed mtDNA gene pool of the western lineage) showed evidence of strong introgression of eastern P. a. aemodius alleles for more than half of the sampling . For microsatellite data the best‐fit model was model 11 with observed pmin and pmax of 0.048 and 0.950, respectively (log likelihood = −8.220), reflecting a strong differentiation between westernmost P. a. melanolophus and easternmost P. a. aemodius anyway. Nevertheless, cline parameters differed significantly between the two data sets. The mean cline width estimate was 3.7 times larger for microsatellite data as compared to mitochondrial CR data (172 vs. 46 km). The center of the cline was estimated at 11 km east of Dhorpatan based on the CR data set and at 8 km east of Dhorpatan based on the microsatellite data set . The distinct color phenotypes of coal tit hybrids are confined to the same mountain valleys like, for example, distinct genetic lineages of Himalayan ground beetles in the catchments of Marsyandi Khola, Kali Gandaki and its side river valley Myagdi Khola . That distance roughly corresponds to the east‐west extent of the European crow (Corvus corone) hybrid zone , especially the left tail is clearly shallower in the microsattelite cline. Discongruity of clines inferred from different sets of molecular markes is a common phenomenon of terrestrial vertebrate hybrid zones: For several Nearctic avian taxon pairs, mitochondrial clines were about 1.9 to 20 times narrower than those inferred from neutral nuclear markers  were shown to differ in body size and plumage proportions , territorial song plays a key role not only in territorial defense  but also in mate choice . In contrast, the western Himalayan “spot‐winged tit” was often treated as a species of its own, Periparus melanolophus ; Investigation ; Methodology ; Validation ; Visualization ; Writing‐original draft ; Writing‐review & editing . Jochen Martens: Conceptualization ; Data curation ; Funding acquisition ; Investigation ; Resources ; Writing‐review & editing . Till Töpfer: Data curation ; Resources ; Writing‐review & editing . Melita Vamberger: Formal analysis ; Investigation ; Methodology ; Software ; Supervision ; Writing‐review & editing . Abhinaya Pathak: Resources ; Supervision ; Validation ; Writing‐review & editing . Heiko Stuckas: Conceptualization ; Investigation ; Methodology ; Software ; Supervision ; Validation ; Writing‐review & editing . Martin Päckert: Conceptualization ; Data curation (lead); Investigation (lead); Project administration (lead); Resources ; Supervision ; Validation ; Visualization ; Writing‐original draft (lead); Writing‐review & editing .Supplementary MaterialClick here for additional data file.


ST values of 23 SNPs. Use Arlequin (version 3.5.2.2) software to analyze molecular variance (AMOVA) among 31 populations. The results showed that there was haplotype diversity of VDR, angiotensin-converting enzyme, ACTN3, EPO and IGF1 genes in the five ethnic groups, and there were genetic differences in the distribution of these genes in the five ethnic groups. Among them, the average gene heterozygosity (AVE_HET) of the 23 SNPs in the five populations was 0.398. The FST values of the 23 SNPs among the five ethnic groups varied from 0.0011 to 0.0137. According to the principal component analysis, the genetic distance of Daur, Mongolian and Ewenki is relatively close. According to the phylogenetic tree, the five ethnic groups are clustered together with the Asian population. These data will enrich existing genetic information of ethnic minorities.Musculoskeletal performance is a complex trait influenced by environmental and genetic factors, and it has different manifestations in different populations. Heilongjiang province, located in northern China, is a multi-ethnic region with human cultures dating back to the Paleolithic Age. The Daur, Hezhen, Ewenki, Mongolian and Manchu ethnic groups in Heilongjiang province may have strong physical fitness to a certain extent. Based on the genetic characteristics of significant correlation between some important genes and skeletal muscle function, this study selected 23 SNPs of skeletal muscle strength-related genes and analyzed the distribution of these loci and genetic diversity in the five ethnic groups. Use Haploview (version 4.1) software to calculate the chi-square and the Hardy-Weinberg equilibrium to assess the difference between the two ethnic groups. Use R (version 4.0.2) software to perform principal component analysis of different ethnic groups. Use MEGA (version 7.0) software to construct the phylogenetic tree of different ethnic groups. Use POPGENE (version 1.32) software to calculate the heterozygosity and the F Skeletal muscle is one of the most dynamic and plastic tissues of the human body, and it is an important part of the human body. The skeletal muscles are involved in various functions of human life. From a mechanical perspective, the main function of skeletal muscle is to convert the body’s chemical energy into mechanical energy, so that the body can generate force and strength, and then generate movement to maintain or benefit human health. From a metabolic perspective, the roles of skeletal muscle include promoting basal energy metabolism, storing important substrates such as amino acids and carbohydrates, and providing most of the oxygen and energy for human movement .VDR gene may have a positive effect on skeletal muscle  were 25, 50, and 25%, respectively, in Caucasian populations , PPARG rs3856806, IL6 rs2066992, ACE , ACTN3 , EPO , IGF1 , VDR  genes. We analyzed the allele frequency of these loci in Daur, Hezhen, Ewenki, Mongolian and Manchu, and compared with the 26 populations from 1,000 genome project, to investigate the genetic polymorphism of skeletal muscle strength related genes in the five ethnic groups and to provide theoretical support for explaining the genetic polymorphism of skeletal muscle strength related genes between different populations.Single nucleotide polymorphisms (SNPs) refer to DNA sequence polymorphisms caused by a single nucleotide variation at the genome level, with a frequency generally greater than 1% in the population. SNP is closely related to the genetic traits of populations and can be used as genetic markers for the genetic structure of different populations . Based oBlood samples were collected from 882 unrelated individuals  belonging to five Chinese ethnic minorities in Heilongjiang province at least three generations. These individuals include 233 Daur individuals, 106 Mongolian individuals, 73 Ewenki individuals, 220 Manchu individuals, and 250 Hezhen individuals. The geographical distribution on the map is shown in Genomic DNA was extracted from 200 μl blood using the QIAamp DNA Blood Mini Kit  according to the manufacturer’s instructions. Genotyping was performed using the SNPscan™ Kit  according to the manufacturer’s instructions.http://grch37.ensembl.org/Homo_sapiens/Tools/DataSlicer The abbreviations and full names of the 26 populations in the world were downloaded from the https://www.ncbi.nlm.nih.gov/variation/tools/1000genomes.The genotype and allele frequency data of individuals from the 26 populations in the world were downloaded from the ensemble database at r2 threshold was 0.8. Phylogenetic tree was generated using the UPGMA dendrogram method in MEGA7 . The minimum allele frequencies and genotype frequencies of 23 SNPs in five populations are summarized in The genotype distribution in the study is summarized in p < 0.05).The SNPs with statistical differences in the comparison between the two ethnic groups are summarized in ST values of the 23 SNPs among the five populations varied from 0.0009 to 0.0137, with an average of 0.0049, that is, 0.49% genetic variation existed between populations and 99.51% genetic variation existed within populations (The average gene heterozygosity (AVE_HET) of the 23 SNPs in the five populations was 0.398 . The aveulations . The genr2 threshold of haplotype blocks were 0.8 Five blocks were distributed in VDR, ACE, ACTN3, EPO and IGF1 genes  and between Daur and Mongolian (P = 0.0101). The frequency distribution of AT in Daur and Ewenki (P = 0.0045), Daur and Manchu (P = 1.00E-04), and Daur and Mongolian (P = 0.0071) were statistically significant. The frequency distribution of AC in Daur and Hezhen (P = 1.00E-04), Daur and Manchu (P = 0.0012), Ewenki and Manchu (P = 0.004) has statistical significance. The block2 containing three SNPs was constructed in the ACE gene. The most common haplotype was GCC, followed by AGT and GCT. The frequency distribution of AGT in Daur and Manchu (P = 0.0073), Ewenki and Manchu (P = 0.0475) is statistically significant, GCT in Daur and Hezhen (P = 0.0311), Daur and Manchu (P = 0.0013), Daur and Mongolian (P = 0.0339). Ewenki and Manchu (P = 0.0206) is statistically significant.There were five blocks in 23 SNPs, the F1 genes . The fivST value between five populations based on 23 SNPs indicated that the FST values of Daur and Mongolian (0.0026), Daur and Ewenki (0.0027), Mongolian and Ewenki (0.0006) are relatively small  and is related to muscle growth  gene is associated with superior muscle metabolic performance and muscle endurance (IL-6), the prototype of muscle factor, was identified as a muscle-derived cytokine 15 years ago (ST plays a core role in population and evolutionary genetics, it can reflect the degree of genetic differentiation between populations (ST values of the 23 SNPs among the five ethnic groups varied from 0.0009 to 0.0137. There is almost no genetic differentiation in each population. According to the mean value of Nm, indicating that genetic differentiation did not occur between populations, but was mainly caused by genetic differentiation within populations, this is consistent with the population genetic differentiation results shown by the FST value of this study. We found that there was little difference in genetic distance between the five populations studied on the whole, this may because the five ethnic groups are all located in Heilongjiang province. which is consistent with the geographical location of the population (ST values (VDR gene was related to the obesity and diabetes, it is also as the genetic makers of them. rs7975232 polymorphism of VDR gene was found to be positively correlated with obesity according to skin fold thickness and body fat rate in Chinese Han population (ST values between the five ethnic groups. There are also studies showing that from the perspective of linguistic kinship, immigration history and origin, the kinship between the Mongolian and the Daur is very close, which indicates that the two groups in each pair may be of the same origin (Different nations have formed specific genetic structures of different cultures, phenotypes and languages under the natural selection of different environments, material conditions and various pathogens. In East Asia, China has the largest Han population in the world, with 55 officially recognized ethnic groups making up their specific cultural backgrounds. They speak more than nine language families in China . Among te growth . IGF1 isfe cycle . Vitaminfe cycle . The angndurance . Erythrondurance . Interleears ago . FST plaulations . The FSTpulation . In addipulation . We concT values . The sampulation . Anotherpulation . The fivpulation . Interespulation . Therefopulation , which we origin . Accordie origin .In Conclusion, geographical and linguistic divisions have shaped the genetic structure of modern populations. Cluster analysis shows that the five ethnic groups in Heilongjiang province are clustered together with the East Asian ethnic groups. The genetic distance between Daur, Mongolian and Ewenki is closer, in order to better study the genetic characteristics of skeletal muscle strength related genes in different population, in addition to the more national, cultural, geographical and linguistic diversity group, also need more genome data combining with archaeological data and population history for further analysis and validation.


Cambodia harbours a variety of human aboriginal populations that have scarcely been studied in terms of genetic diversity of entire mitochondrial genomes. Here we present the matrilineal gene pool of 299 Cambodian refugees from three different ethnic groups  deriving from 16 Cambodian districts. After establishing a DNA-saving high-throughput strategy for mitochondrial whole-genome Sanger sequencing, a HaploGrep based workflow was used for quality control, haplogroup classification and phylogenetic reconstruction. The application of diverse phylogenetic algorithms revealed an exciting picture of the genetic diversity of Cambodia, especially in relation to populations from Southeast Asia and from the whole world. A total of 224 unique haplotypes were identified, which were mostly classified under haplogroups B5a1, F1a1, or categorized as newly defined basal haplogroups or basal sub-branches of R, N and M clades. The presence of autochthonous maternal lineages could be confirmed as reported in previous studies. The exceptional homogeneity observed between and within the three investigated Cambodian ethnic groups indicates genetic isolation of the whole population. Between ethnicities, genetic barriers were not detected. The mtDNA data presented here increases the phylogenetic resolution in Cambodia significantly, thereby highlighting the need for an update of the current human mtDNA phylogeny. Indigenous minority groups of Hmong, Pong, Austronesian and Tai are collectively known as Khmer Loeu. Minority groups living in the lowlands, often among or adjacent to Khmers, include Chinese, Vietnamese and Cham. Austro-Asiatic languages are predominant in Cambodia. Being one of the most ancient language families in eastern Asia, Austro-Asiatic is also spoken in India, Bangladesh and South-western China, implying that the Austro-Asiatic speaking populations may represent the descendants of the earliest settlers of modern humans who migrated from Africa and entered into eastern Asia about 60,000 years ago4.Cambodia is located in the southern portion of the Indochina Peninsula in Southeast Asia. The Buddhist country with a population of over 15 million people  is bordered by Thailand to the northwest, Laos to the northeast, and Vietnam to the east. As a result of the historic expansion of the Khmer Empire in the twelfth century, the majority (96%) of Cambodia’s present-day population belongs to Khmer9, mostly in Thailand12 and Vietnam14, with very limited samples from Cambodia2. Besides various control region sequencing projects in populations from Southeast Asia , only one publication sequenced the mtDNA HVS-I  and HVS-II (range 65–417) from 1,054 unrelated Cambodians2. From these partial sequences, Zhang and colleagues analysed the complete mitochondrial genome from 98 Cambodian individuals and identified eight new and basal mitochondrial DNA haplogroups, which led to the conclusion that present-day Cambodians still carry ancient genetic polymorphisms in their maternal lineages, and most of the common Cambodian haplogroups probably originated locally before expanding to the surrounding areas during prehistory2.Genetic studies of complete mitochondrial DNA (mtDNA) have been conducted previously in populations from Southeast Asia (SEA)23, Bayesian evolutionary analysis with BEAST 224, Median-Joining Networks with Network.exe (v.4)25 as well as Maximum Parsimony trees.The aim of our study was to provide a high quality mtDNA data set from Cambodia in order to understand the complex history of Southeast Asian mtDNA evolution and diversity. This was accomplished by genotyping the so far largest population set of complete mitochondrial genomes of 299 Cambodian individuals, with a cost-efficient, DNA-saving, and reliable high-throughput strategy for mitochondrial whole-genome Sanger sequencing, and by distilling ~ 7,000 mtDNA samples from studies on neighbouring- and global populations. Post-processing of the data was carried out in HaploGrep 2, estimating haplogroups and performing additional quality control steps. Phylogenetic trees were directly generated within HaploGrep 2, data exported in multiple alignment format for maximum likelihood phylogenetic tree inference with RamXL-NG26, six forward primers and 20 reverse primers were new and replaced old sequencing primers. In addition, all liquid handling steps were performed by liquid handling platforms, thereby reducing potential pitfalls such as contamination or sample mix-up. Finally, the strategy was also economic in terms of DNA consumption, as less than 1 µg of DNA  was needed for generating a high-quality mtDNA profile.The study included 299 DNA samples from Cambodian citizens, who lived in Northern Thailand at the time of sample collection. Blood samples were originally collected from 300 individuals, but one sample (C228) showed obvious signs of contamination and was therefore excluded from further analysis. Detailed descriptions of the samples including sex, age, places of birth of the sampled individuals and of their mothers, the mtDNA haplogroup affiliations and the GenBank accession numbers are given in Table 2 and gives an overview of the geographic origin of samples analysed.Out of the 299 Samples, the majority of individuals (79.3%) were born in four provinces of Cambodia Fig. , Table 11. The large proportion of Cham individuals sampled in this study (20.4%) could therefore be explained by the fact that the samples were collected in refugee camps in Thailand, where ethnic minorities, who were prosecuted or expelled by the Khmer rouge, found shelter.The largest part of participating refugees declared themselves as belonging to the ethnic group of Khmer , R9 (F1 and R9b), as well as R22 and R23 , as well as in the complete mtDNA genomes described in Thailand12, in Vietnam13 (only one sample out of 607 sequences), Myanmar18 and Laos16. Supplemental Table Additionally, we performed the same procedure to fine-scale haplogroup F1a1, which also includes four subgroups F1a1a to F1a1d, totalling to nine subgroups. Most samples herein could be placed in F1a1a , with East Asian ancestries (EAS) are listed individually. Figure We compiled a data set comprising 7,178 complete mtDNA sequences as a representative data set of populations in Southeast Asia  when clustering on macrohaplogroups. The close relation between Southeast Asian populations (EAS cluster) and Americans (AMR cluster) is based on the mutual presence of haplogroup lineages A, B, C, and D in both EAS and AMR super populations.Based on the HaploGrep results , which allowed the calculation of pairwise FST values based on a dataset compiled from the complete mtDNA sequences. Supplemental Material Table 2  and Myanmar samples from Summerer et al.18 (327 control region sequences with only 44 full mt-genomes). Supplementary Figure ST values, calculated with MitoBench 1.7 beta. The variation within the herein presented population was higher than between the three ethnicities , which however can also be the result from uneven sample sizes (Khmer (n = 201), (Cham n = 55) and Khmer Loeu (n = 8). Additionally, pairwise FST values were verified for Cham and Khmer (as Khmer Loeu had only eight samples) over all samples, showing a Weir and Cockerham mean FST estimate of 0.0027702, confirming the high homogeneity between the two groups. The populations with the lowest FST values compared to our 264 Cambodian samples were the 1,234 samples from Thailand and Laos  and the 609 Vietnamese samples .Additionally, we prepared the data for MitoBenchThe aim of the present study was to corroborate and extend previous phylogenetic analyses on the evolution of mitochondrial genomes in Cambodia. By whole-mitochondrial genome sequencing of 299 Cambodian individuals living in Thailand, we could define several new mtDNA haplogroups , compared to R (n = 165), including B (n = 322) and F (n = 104). Nevertheless, in phylogenetic studies of Southeast Asia new deep rooting M-haplogroups with many seemingly private mutations are frequently found, indicating a still significant undersampling of macrohaplogroup M. On the other hand, the large clusters under B5a1 and F1a1 correspond to 38% of all samples, indicating that Cambodia harbours autochthonous populations with relatively recent expansions, as previously observed by Zhang and colleaguesST statistics  showed an extremely similar haplogroup distribution, which we did not expect to this degree. As the samples derived from different regions of Cambodia, this indicates a stable gene flow between the Cambodian ethnicities, and a lower diversity than expected, compared to populations in Mainland Southeast Asia. Considering that the data derived from Cambodian refugees, it nevertheless matches the general population from different regions .Besides the phylogeographic analysis, an important aspect of this work was to ease the handling of mtDNA data. Therefore we adapted HaploGrep 2 to directly generate haplogroup overview plots such as in Fig. Finally, the presented dataset allows a much better fine scaling of the phylogenetic tree based on the complete mtDNA sequences. Most of the new haplogroups explored within this work are defined by variants in the coding region, with only a few new haplogroups including control region variants. The presented data also highlights the need for an update of the underlying phylogenetic tree.Blood samples were collected from 300 Cambodian individuals, who came from 16 of the 22 regions of Cambodia .The entire mitochondrial genome was amplified in two overlapping fragments of approximately 9 kb each26. PCR products were purified with the QiaVac . The post-PCR pipetting steps were performed with a Plate Mate 2 × 2 Automated Liquid Pipettor .The DNA was amplified in a total reaction volume of 50 µl, containing approximately 280 ng (fragment A) or 120 ng (fragment B) of DNA, 1 µl of Herculase II Fusion DNA Polymerase , 10 µl of 5xPCR reaction buffer, 250 µM each dNTP , and 0.25 µM each primer. The PCR reaction was done in a 96-well thermal cycler . A incubation at 95 °C for two minutes was used for initial denaturation. For a high specificity 10 touch-down cycles were applied with 95 °C for 20 s, 69 °C–0.5C°/cycle for 20 s, and 72 °C for 4 min 30 s. Subsequently, amplification was performed using 40 PCR cycles Each sample was sequenced with 96 primers . Validation was performed by a senior mtDNA scientist using the mtDNA management software eCOMPAGT32. MtDNA haplotypes were assigned to haplogroups based on PhyloTree Build 1733 with HaploGrep 234. In addition, the phylogenetic tree was generated directly with HaploGrep 2. HaploGrep 2 was also used for data exports in multiple alignment format, for which we also applied MAFFT on a dataset of 6,500 fasta sequences. Additionally different trees for the 264 samples (35 samples removed due to direct kinship relations) including the Reconstructed Sapiens Reference Sequence (RSRS)35 were generated with maximum-likelihood approaches (modeltest-ng and RAxML-NG23), maximum parsimony (mtphyl—https://sites.google.com/site/mtphyl/) and Bayesian evolutionary analysis 24. The RSRS sequence was included for rooting the tree, representing the most common maternal ancestor, while we always use the rCRS for representing mutations with their according alternative nucleobase. The data was prepared for storage in MitoDB and MitoBench30. The latter was used for the analysis of molecular variance (AMOVA—pairwise FST) in Supplemental Table 36. The analysis of the data was performed in R, with libraries corrplot, corrr, ggbiplot, ggpubr and reshape2. Also the PCA was carried out in R with the standard library and the ggbiplot package. Visualization of the trees were additionally generated in the interactive Tree of Life37 web-application (https://itol.embl.de). Mtphyl was used for the Ro(Sigma) calculations Supplementary Information 1.Supplementary Information 2.