Alongside the rise of animal-protection awareness in Taiwan, the public has been paying more attention to dog genetic deficiencies due to inbreeding in the pet market. The goal of this study was to isolate novel microsatellite markers for monitoring the genetic structure of domestic dog populations in Taiwan.A total of 113 DNA samples from three dog breeds—beagles (BEs), bichons (BIs), and schnauzers (SCs)—were used in subsequent polymorphic tests applying the 14 novel microsatellite markers that were isolated in this study.(ID)) and the probability of identity among sibs (P(ID)sib) for the 14 novel microsatellite markers were 1.7×10−12 and 1.6×10−5, respectively. Furthermore, the power of exclusion for the 14 novel microsatellite markers was 99.98%. The neighbor-joining trees constructed among the three breeds indicated that the 14 sets of novel microsatellite markers were sufficient to correctly cluster the BEs, BIs, and SCs. The principal coordinate analysis plot showed that the dogs could be accurately separated by these 14 loci based on different breeds; moreover, the Beagles from different sources were also distinguished. The first, the second, and the third principal coordinates could be used to explain 44.15%, 26.35%, and 19.97% of the genetic variation.The results showed that the high level of genetic diversity observed in these novel microsatellite markers provided strong discriminatory power. The estimated probability of identity (PThe results of this study could enable powerful monitoring of the genetic structure of domestic dog populations in Taiwan. The previous roles of companion animals, such as hunting, security, and assistance, have gradually shifted towards them being regarded as family members. With the improvement of the status of pets, owners are increasingly paying attention to their quality of life. Therefore, the demand for various goods and services aimed at companion animals is also increasing. In the early stage of the Taiwan dog-sales market, the characteristics prioritised included the ability to guard, search, attack, and hunt; more recently, these ideals have been superseded by the need to provide companionship and prestige, which have made a recognized pedigree a major factor for buyers. In Taiwan, some legal purebreed grounds used closed flock breeding to keep their dog broodlines, including those three breeds in this study. Especially the Beagles, which have been used to hunt hares in the British Isles for centuries, and which were brought to the United States in 1880 to breed in large numbers. The modern Beagles have been modified to become a pet dog, and were often used as experimental dogs [After strong artificial selection for over 150 years, morphological variation has been created in dog populations and more than 400 canine breeds are currently registered worldwide by the Fédération Cynologique Internationale (FCI), and other federations such as the American and British Kennel Clubs . In Taiwtal dogs . It has So far, many dog breeds have been developed in order to meet appearance standards and maintain the purity of their bloodlines. Breeding companies usually adopt inbreeding methods, which can lead to the occurrence of many genetic diseases. Generally, in the natural state—unlike with experimental animals for which it can be essential to reduce individual differences for study purposes—inbreeding approaches have seldom been used, in order to avoid inbreeding depression . The RoyRegarding the research on dog microsatellite markers, a lot of information has been discovered in conjunction with the elucidation of DNA sequences . As earlTo date, only a few domestic biotechnology companies in Taiwan use foreign dog microsatellite commercial kits, such as the StockMarks for dogs genotyping kit, for individual genetic analysis or genetic structure analysis at dog breeding sites. So, are they applicable to Taiwan? To our knowledge, there are no relevant published reports on existing dog breeds for reference and analysis. Therefore, the development of microsatellite markers suitable for the companion animal population in Taiwan is a crucial task to establish a molecular-detection platform for domestic dogs. Moreover, such a platform will make it possible to evaluate the inbreeding level of the dog population in Taiwan. In addition to assisting with the formulation of domestic dog breeding-management policies, this could also enhance Taiwan’s positive governance perspectives on animal protection and animal welfare.In total, five populations of dogs from legal breeding ground were investigated in this study. Blood samples were collected from 113 individuals belonging to these three populations which were popular in Taiwan: 17 bichons (BIs); 14 schnauzers (SCs); 74 Taiwanese beagles (BETs); and eight Japanese beagles (BEJs), two of which were distinguished as group A (BEJAs) and six of which were distinguished as group B (BEJBs) . For eacRsaI and XmnI  until most of the DNA fragments were between 300 and 1,000 base pairs (bp) in length. Re-naturing of single-strand SuperSNX24 forward (5′GTTTAAGGCCTAGCTAGCAGAATC3′) and SuperSNX24+4P reverse (5′pGATTCTGCTAGCTAGGC CTTAAACAAAA3′) formed SuperSNX24 linkers that were ligated to the digested DNA fragments. Linked DNA fragments were then amplified with SuperSNX24. Next, microsatellite markers including fragments with biotinated probes were isolated and enriched. The following three probe compositions were used: i) (TG)12, (ACT)12, (ACTG)6, and (ACAG)6; ii) (AG)12, (ACAT)8, (AACT)8, and (AAGT)8; and iii) (AAG)8, (AAAC)6, (AATC)6, and (AGAT)6. The biotinated probes were then annealed to fragments of gDNA containing complementary regions. Finally, the microsatellite-containing fragments were enriched using streptavidin-labeled metal beads . The enriched segments were then cloned into pGEM-T Easy vector  and sequenced with an ABI 3730XL DNA Analyzer . The fragments with higher numbers of repeats were selected for polymorphism testing.The gDNA was isolated from blood samples taken from one male and one female BI using the following steps, which were slightly modified from the procedure described by Glenn and Schable . The iso2), 0.2 mM deoxyribose nucleotide triphosphate (dNTP), 0.2 μM unlabeled primer, 0.04 μM tag-labeled primer, 0.16 μM dye-labeled tag, and 50 ng gDNA. The PCR cycling program was as follows: 95°C for 5 min, 35 cycles of 95°C for 30 s, 50°C to 65°C for 40 s, 72°C for 40 s, and a final elongation at 72°C for 7 min. The amplified microsatellite PCR products were analyzed with a DNA analyzer . Allelic sizes of all loci were estimated relative to the in-line GeneScan500 LIZ Size Standard marker . The fragment size was calibrated and analyzed with Peak Scanner Software version 1.0 . Those loci that had an allele number greater than two and similar annealing temperatures were selected for whole-population analysis.The selected highly repeated fragments were subjected to PCR and polymorphism testing, which would verify whether the microsatellite loci could be amplified and used to show diversity in the investigated populations. Primers for loci amplification were designed using Primer3plus. CAG-tag (5′-CAGTCGGGCGTCATCA-3′) or M13Reverse (5′-GGAA ACAGCTATGACCAT-3′) was added to the 5′ end of one of each primer pair. Following the protocol described by Schuelke , a fluorTaq DNA polymerase , 1×PCR buffer (1.5 mM MgCl2), 0.3 mM dNTP, 0.3 μM forward and reverse primer, and a 100-ng DNA template. The steps of the PCR program and genotype detection were as described above.In total, 14 microsatellite loci were selected . The 5′ E), and the polymorphic information content (PIC), were calculated with the Microsatellite Toolkit. The Hardy–Weinberg equilibrium test was performed using the GENEPOP computer program [F-statistics  for each locus, the pairwise FST between populations, and the average inbreeding coefficient (FIS). Nei’s genetic distance (DA) [For each locus and population, and across populations, commonly derived statistics from the microsatellite genotypic data, including allele frequencies, the observed number of alleles (No), the observed heterozygosity (Ho), the expected heterozygosity   between nce (DA) . A phylonce (DA)  using thnce (DA) .The model-based approach proposed for the population structure analysis of the dog populations was carried out with the software STRUCTURE 2.3.1 , which w(ID)), which is the probability that two individuals are randomly selected from the population and the genotypes of the two are identical at a single locus. The theoretical expectations are as follows:The effectiveness of individual identification is expressed by the probability of identity sib) is applied:where pj is the frequency of the jth allele [where h allele . The calh allele .The 14 microsatellite markers were used to perform genotyping on 113 samples from the three dog breeds . Polymorphism was clearly observed at most of the microsatellite loci in the three breeds. The genetic characteristics of the 14 microsatellite loci are listed in E among the 14 microsatellite loci ranged from 0.293 (SEL094) to 0.873 (SEL005), with an average of 0.662. The HO among the 14 microsatellite loci ranged from 0.248 (SEL094) to 0.814 (SEL005), with an average of 0.567  for each locus are shown in FIS for all the loci was 0.002, and the FIS per locus varied from −0.191 (SEL093) to 0.328 (SEL115). The average FIT for all the loci was 0.209, and the FIT per locus varied from −0.070 (SEL034) to 0.506 (SEL115). The mean FST for all the loci was 0.212. This value implied that around 21.2% of the total genetic variation was caused by population differences and that 78.8% of the total genetic variation was due to genetic differentiation among the individuals within each population.The Wright’s E, HO, PIC, the mean observed number of alleles, and the mean effective number of alleles, were calculated to estimate the allelic diversity at each locus of the population. These genetic parameters across the 14 loci for the three dog populations are listed in E varied from 0.480 (SCs) to 0.624 (BEs), whereas the HO varied from 0.485 (SCs) to 0.587 (BEs), and the PIC ranged from 0.407 (SCs) to 0.567 (BEs). The SC population had the lowest values of HO, HE, and PIC.The genetic statistics relating to polymorphism, including HFIS values were observed in the BI and SC populations, indicating an insufficient degree of inbreeding. The deviation from the Hardy–Weinberg proportions within populations (FIS) varied from −0.032 to 0.045. The highest inbreeding effects were found in the BE population (0.045), which significantly deviated from the Hardy–Weinberg equilibrium (p<0.01)  (5.3), followed by the BI (4.0) and SC (3.3) populations, while the latter had the smallest observed MNA. Negative (p<0.01)  in compaFST and genetic distance (D) calculated by the gene frequency of each animal at each microsatellite locus—were evaluated in this study. The values of FST and D for each test population pair are summarized in FST for each population pair was highly significant (p< 0.05). The FST values of the population pairs varied from 0.165 (for the BET and BEJB population pair) to 0.405 (for the SC and BEJB population pair). The genetic distances between the dog population pairs varied from 0.400 (for the BET and BEJB population pair) to 0.993 (for the SC and BEJA population pair). Surprisingly, the second relatively low genetic distance and FST value were not between other BE populations. The genetic distances and FST values of the BI–BET and SC–BET population pairs were less than the BEJA–BEJB and BEJA–BET population pairs.To estimate genetic variation among the five dog populations, two parameters—A distance matrix was used to build an individual phylogenetic tree with the NJ method , second (PC2), and third (PC3) PCos accounted for 44.15%, 26.35%, and 19.97% of the total variation, respectively . The disThe STRUCTURE software program using Bayesian model-based clustering algorithms of multi-locus genotypes was utilized to assign individuals to populations via estimated individual admixture proportions and to infer the number of populations (K) for a given sample. The results of the analysis are shown in (ID)) and the identification rate of close relatives (P(ID)sib) of the 14 single new microsatellite markers. The results are listed in (ID) of BE populations per locus varied from 0.042 (SEL005) to 0.491 (SEL094). The combined P(ID) values for all loci was 3.7×10−11. The P(ID) of each locus in BIs ranged from 0.060 (SEL005) to 1.000 (SEL094). The combined P(ID) values for all loci was 7.8×10−9. The P(ID) of SC populations per locus varied from 0.097 (SEL005) to 0.869 (SEL115). The combined P(ID) values for all loci was 1.2×10−7. In addition, the P(ID) of the 14 novel microsatellite loci for all dog populations ranged from 0.031 (SEL005) to 0.843 (SEL094), and the comprehensive P(ID) was 1.7×10−12.The analysis of probability of identity involved three dog populations, respectively, and all populations together was calculated by the probability of identity (P(ID)sib. The P(ID)sib of BE populations per locus varied from 0.337 (SEL005) to 0.701 (SEL094). The combined P(ID)sib values for all loci was 3.9×10−5. In BIs, the P(ID)sib ranged from 0.358 (SEL005) to 1.000 (SEL094), and the combined P(ID)sib values for all loci was 2.6×10−4. The P(ID)sib of SC populations per locus varied from 0.403 (SEL005) to 0.933 (SEL115). The combined P(ID)sib values of SC for all loci was 7.1×10−4.When individuals in the population to be explored have close relatives, such as full-sib or half-sib, it is more appropriate to evaluate the proportion of identification using the PIn the paternity test for dogs, according to the formula of power of exclusion (PE) proposed by Jamieson , the valIn this study, 14 sets of novel microsatellite markers were developed and used to analyze the genetic variation of three dog breeds—SC, BI, and BE. The results showed that the Na of the 14 novel microsatellite loci was 6.3, and the Ne was 3.6 . The Na E, HO, and PIC are commonly used to assess the polymorphism of microsatellite loci in the analyzed population. The HO refers to the observed heterozygosity of each locus, which represents the actual proportion of heterozygous individuals in the population. The HE is the expected heterozygosity of each locus, which is the expected proportion of heterozygous individuals in the population that is calculated according to the Hardy–Weinberg Law. The PIC is the degree of polymorphism of each locus. Using the 14 novel microsatellite markers to analyze our dog populations, the average HE was 0.662, which showed that the values of most of the microsatellite markers were within high expected heterozygosity (HE>0.5). The average value of HO was 0.567, which also fell within the range of high observed heterogeneity (0.7>HO>0.5) [E was 0.643, the average HO was 0.645, the average PIC was 0.598, and the values of the three variables were all greater than 0.5. Therefore, their study indicated that the tested Tatra shepherd dog population was highly polymorphic. In another study [The H>HO>0.5) . The ave>HO>0.5)  (Table 3>HO>0.5)  using 18er study , eight bE (0.412 and 0.293) and HO (0.451 and 0.248) values of loci SEL093 and SEL094 were both less than 0.5, as were the respective PIC (0.326 and 0.249) values. The cause of this result, for which there were only two alleles in two loci, was supposed to be sampling error. However, some reports have suggested that the number of alleles for microsatellite markers should be three or more to reduce the standard deviation of distance calculation [The Hculation . The reaFIS, FST, and FIT statistics to evaluate the distribution of genetic variation within and between populations. The average FIS value of the 14 new microsatellite markers was 0.002. This value was positive and low. The percentage of heterozygotes in the overall tested dog population was less than expected—that is, there was an inbreeding phenomenon—but the average value of FIS was around 0.002, which indicated that the situation in the dog population was not serious. The mean FST for all the loci was 0.212. This fell within the range of high differentiation (0.15<FST<0.25), according to the Sewall Wright rules [In terms of the analysis of population genetic structure, we applied the ht rules , indicatO, HE, and PIC. Between nine and 11 microsatellite loci were used for genetic analysis of two local breeds from South Korea and three exotic dog breeds in their study. The sample selection criterion was at least one generation of unrelated dog individuals. The results showed that the average HO for each breed ranged from 0.65 to 0.78; the HE ranged from 0.71 to 0.85; and the PIC ranged from 0.66 to 0.82. In this study, the average value of HE for the three varieties ranged from 0.480 (SCs) to 0.624 (BEs), and average HO ranged from 0.485 (SCs) to 0.587 (BEs). The average PICs ranged between 0.407 (SCs) and 0.567 (BEs)  . CompareFIS, only the average value for BEs (0.045) was positive. The results showed that although BEs in this experiment had high genetic variation, the positive value of FIS indicated that the proportion of heterozygous individuals was still too small to achieve the Hardy–Weinberg balance; Iindeed, it deviated significantly from the expected value (p<0.01). This result may reflect the fact that the fathers of the BE population in this experiment comprised a small number of male dogs, which was not reflective of the situation of mating by chance. The BIs and SCs did not deviate from the Hardy–Weinberg equilibrium, and the FIS values of these two breeds were negative. It can thus be inferred that these two breeds had no inbreeding issues, the genetic backgrounds of the parents were different, and the number of male and female animals was equal [Among the different varieties of as equal . TherefoThe individual phylogenetic tree of the dogs  was consThe PCoA draws a 3D stereogram based on the genetic distance between the populations , and dis(ID)) of the 14 new microsatellite loci for the entire dog population was 1.7×10−12 (6 [(ID) of a single dog breed, the credibility is still high. There are no statistics on the numbers of dogs of different breeds currently in Taiwan; however, it can be ascertained that the number of dogs in any single breed cannot exceed the total number of dogs. Therefore, the P(ID) of the three dog populations respectively in this study should cover the total number of dogs in Taiwan in 2019. It was confirmed that the probability of the same genotype being identified in two individuals with 14 the sets of novel microsatellite markers was very low.In the individual analysis, the combined probability of identification sib) was 1.6×10−5 ((ID)sib was between 10−3 and 10−4. The P(ID)sib values of the three breeds of dogs in this experiment generally met this recommended standard. This confirmed that the 14 novel microsatellite markers were applicable in the individual identification of close relatives of BEs, BIs, and SCs in Taiwan.The combined probability of identity among sibs  was 3.2×10−8. The American Kennel Association considered that 17 microsatellite markers were sufficient for ordinarily paternity identification [O was 0.74, the average PIC was 0.82, and the combined P(ID)sib was 8.5×10−8, showing that these 15 microsatellite markers are sufficient for individual identification of dogs in Austria. Kang et al [O for each breed was between 0.65 and 0.78; the average PIC was between 0.66 and 0.82; and the average PE was more than 99% in all breeds. The average HO value (0.57) of the 14 new microsatellite markers in this study near the range of the research results of the previous countries (0.60 to 0.74). The average value of PIC (0.61) was also within the range of the results of the aforementioned countries (0.56 to 0.82). According to the researches before, the 14 new microsatellite markers developed in this study were highly polymorphic and suitable to analyze the three breeds of dogs in Taiwan.At present study, many countries used microsatellite markers to analyze dog populations. For developing a platform of paternity and individual identification, the American Kennel Club (AKC) analyzed 108 dog breeds using 17 microsatellite markers. The results show that the average Hfication . Eichmanfication . The resng et al  used 9 tIn conclusion, using 14 novel microsatellite markers to analyze the beagle, bichon, and schnauzer populations in Taiwan, the results showed that their average expected heterozygosity, observation heterozygosity, and polymorphism information content were all at high levels. Therefore, these new microsatellite markers have high applicability to the analyzed populations. These results indicate that the new microsatellite markers have good resolution when applied to the detection of differences among dog breeds. It was confirmed that the opportunity of identifying the exact same genotype among the analysis of the 14 new microsatellite markers was very low. In addition, the power exclusion was enough high to be a good tool for paternity testing.


Rhampholeon represent a moderately diverse, geographically circumscribed radiation, with most species (18 out of 19 extant taxa) limited to East Africa. The one exception is Rhampholeon spectrum, a species restricted to West-Central African rainforests. We set out to characterize the geographic basis of genetic variation in this disjunctly distributed Rhampholeon species using a combination of multilocus Sanger data and genomic sequences to explore population structure and range-wide phylogeographic patterns. We also employed demographic analyses and niche modeling to distinguish between alternate explanations to contextualize the impact of past geological and climatic events on the present-day distribution of intraspecific genetic variation. Phylogenetic analyses suggest that R. spectrum is a complex of five geographically delimited populations grouped into two major clades (montane vs. lowland). We found pronounced population structure suggesting that divergence and, potentially, speciation began between the late Miocene and the Pleistocene. Sea level changes during the Pleistocene climatic oscillations resulted in allopatric divergence associated with dispersal over an ocean channel barrier and colonization of Bioko Island. Demographic inferences and range stability mapping each support diversification models with secondary contact due to population contraction in lowland and montane refugia during the interglacial period. Allopatric divergence, congruent with isolation caused by geologic uplift of the East African rift system, the “descent into the Icehouse,” and aridification of sub-Saharan Africa during the Eocene-Oligocene are identified as the key events explaining the population divergence between R. spectrum and its closely related sister clade from the Eastern Arc Mountains. Our results unveil cryptic genetic diversity in R. spectrum, suggesting the possibility of a species complex distributed across the Lower Guinean Forest and the Island of Bioko. We highlight the major element of species diversification that modelled today’s diversity and distributions in most West-Central African vertebrates.Pygmy Chameleons of the genus  Rhampholeon, occurs in lowland, sub-montane, and montane forest patches from West to East Africa [Rhampholeon into three subgenera: Rhampholeon, Rhinodigitum, and Bicuspis. Rhampholeon species are forest leaf-litter specialists with notably reduced vagility [Rhampholeon (Rhampholeon) spectrum [Rhampholeon [Pygmy, or Leaf Chameleons, genus t Africa . This get Africa , with 18t Africa . Mattheet Africa  partitiovagility . As a povagility –7. Rhampmpholeon . It is tmpholeon .R. spectrum; the Niger River in the east, the Adamawa plateau in the north, and finally the Congo River in the south and the east. This distribution encompasses one of the most diverse regions of continental Africa [Rhampholeon spectrum has never been the subject of a range-wide genomic characterization of geographic variation. Due to their distribution spanning many recognized landscape features of West-Central Africa, R. spectrum is an ideal focal species to independently assess the significance of the variable Central African geographical template as part of the diversification history of this virtually unstudied endemic vertebrate lineage.Three major geographic features surround the current distribution range of l Africa . Within l Africa , river bl Africa , mountail Africa , and repl Africa , 15 havel Africa , 17. Thel Africa , 19  to infer the first robust, comprehensive molecular phylogeny for populations referred to R. spectrum; (2) to test for congruence of the time-calibrated phylogenetic analysis with current knowledge of geological events in West-Central Africa; (3) to test for recent population admixture and its potential impact on the resulting population structure; and (4) to test of whether the geographic template and landscape features  have led to detectable geographically-based genetic structure in R. spectrum.The overall objective of this work is to provide an evolutionary framework for the diversification of Pygmy Chameleons across the range of Rhampholeon spectrum samples were obtained from field expeditions to Cameroon between January 2017 and August 2018, and via tissue grants from the California Academy of Science and the Museum of Comparative Zoology, Harvard University . Research permit number 005/MINRESI/B00/C00/C10/C14 was granted respectively by the Ministry of Scientific Research and Innovation of Cameroon. Research permit numbers 1261/PRS/MINFOF/SG/DFAP/SDVEF/SC and CITES permits number 0723-5/P/MINFOF/SG/DFAP/SVDEF/SC/BJ were granted by the Ministry of Forestry and Wildlife of Cameroon.16S and ND4) and one nuclear gene (RAG1) were amplified following standard protocols [All tissue samples (liver) had been field-preserved in 95% ethanol. DNA extractions were performed using a Promega Maxwell RSC extraction robot and a modified version of the bead DNA extraction protocol from Phyletica Lab at Auburn University . Two mitrotocols –25. The de novo assembled and edited in Geneious Prime v2021.0.3 using default parameters. We used MAFFT v1.4.0 Multiple Alignment [16S, ND4, and RAG1) from 17 of the 18 remaining species from the genus Rhampholeon and three species of Rieppeleon obtained from GenBank were used as outgroups. To characterize genetic divergences among species and R. spectrum’s populations, we computed the pairwise genetic distances (16S and ND4) using net sequence divergences (uncorrected p-distances) in MEGA 11 [PCR products were sequenced at GENEWIZ. The complementary reads were lignment  implemen MEGA 11 .We sequenced genome-wide anonymous nuclear markers for 28 individuals, following a modified version of the ddRADseq protocol of Peterson et al.  to procede novo assembly of ddRADseq data can vary widely across taxa [We tested a range of assembly parameters in STACKS to optimize recovery of putative single-copy, orthologous loci, because the optimal oss taxa , 32. The16S+ND4+RAG1) partitioned by marker using BEAST 2.6.3 [We conducted Bayesian divergence-dating analyses with our concatenated mtDNA and nuclear dataset  was conducted in R  using R We used the likelihood-based method Structure 2.3.4 , 50 to iR. spectrum populations and to identify population boundaries, we used the R package delimitR [To test for present-day and historical gene flow between delimitR . We defidelimitR  implemendelimitR . In the delimitR .DelimitR uses a binned multidimensional folded site frequency spectrum (bSFS)  and a raHistorical demography and gene flow were inferred with two separated sets of analysis. The first set consisted of a demographic analysis for species delimitation and gene flow among all four identified populations . The second set consisted of six distinct demographic analyses to test for secondary contact and divergence with gene flow between one population and another .We simulated 10,000 datasets, using the default parameters for 89 models for the first set and four models for the second set of analyses. Priors for all models were drawn from a uniform distribution for population size: 1,000–1,000,000 haploid individuals . The divergence time: , , and  in millions of generations for the three internal nodes were overlapping and the command myrules was used to specify the order; and migration rates of 0.00000001–0.000005, corresponding to 0.0001–0.05 migrants per generation. Then, we constructed a random-forest classifier using 500 decision trees for 10,000 pseudo-observed data sets for each model. We calculated the out-of-bag error rates, selected the best model given the data and the set of models tested, and approximated the posterior probability of the best model among the 89 simulated models for our overall dataset and the four simulated models.We compiled occurrence data obtained from our field expeditions and records from museum and citizen science platforms , 317 occurrences records were obtained overall . These o16S  and ND4  loci, and for the nuclear RAG1  marker. The net genetic distance among populations unveiled lower uncorrected p-distance among all populations composing the CCVL (R. spectrum (RADset1). The second dataset, used for phylogenetic analysis, consisted of the 28 samples listed above, plus one sample of Trioceros cristatus as the outgroup (RADset 2). RADset1 consisted of 16,354 loci with 54.9% missing data. RADset2 consisted of 16,365 loci with 56.4% missing data.We generated new sequences for the mitochondrial the CCVL . Our conthe CCVL  consisteR. spectrum populations from the Lower Guinean Forest are sister to the montane endemic chameleons  from the Eastern Arc Mountains (Pare and Usambara Mts) in Tanzania  form the Korup population. The montane clade is composed of three populations. Samples from Mt. Biao on Bioko Island form the Bioko population, samples from Mt. Cameroon comprise the second montane population, and samples from the geographically proximate Kupe, Nlonako, and Manengouba mountains form the third population  is estimated to have occurred in the late Miocene (~6.9 Mya). The earliest divergence within the CCVL lineage happened during the Miocene-Pliocene transition (~5.2 Mya) and produced the Mt. Cameroon population and the Kupe, Nlonako, and Manengouba populations. Overall, all five newly discovered lineages within R. spectrum arose between the middle- and late-Miocene . The second set consisted of six distinct pairwise demographic analyses to test for secondary contact and divergence with gene flow between pairs of populations .R. spectrum into four distinct populations as identified above, followed by secondary contact between Gabon and Korup populations, between CCVL and Korup, and between Bioko and CCVL populations  was constructed (after down sampling) using five samples for CCVL, three from Bioko, four from Korup, and two from Gabon. Our mSFS was built from 1,220 unlinked SNPs sequenced across all four populations. DelimitR produced 89 models to test for species-level divergences with gene flow and with secondary contact. Sixty-six of the 89 models support four distinct populations hypothesis, and they share 428 of the 500 votes . Model 6ulations . The conFor the second set of analysis, six mSFS were built using four samples from Bioko, five from Korup, six from CCVL, and two from Gabon. The numbers of unlinked SNPs used to build each of the six interactions are listed in We used ecological niche modeling to explore changes in the potential geographic distribution over the last 20,000 years . First, despite the presence of suitable conditions in the Upper Guinea region and on the islands of São Tomé and Principe, this species has not been recorded from these areas. Most likely, these species were never able to cross the Niger Delta or the intervening parts of the Gulf of Guinea .During the LGM, the area highly suitable for the species was quite small and associated with areas identified as putative Pleistocene refugia by Maley . It is iR. spectrum. All high-stability surfaces encompass part or the entirety of previously proposed Pleistocene refugia [Our species distributional modeling predicts three main high-stability habitats: north of the Sanaga River, south of the Mbini River, and east of the Congo River . The reg refugia  Fig 8)..R. spectRhampholeon of West-Central Africa using phylogeographic analyses and historical demographic model selection techniques in order to test predictions derived from alternate hypotheses of mechanisms of diversification and possible speciation. To relate diversification to the variable topography and environments of West-Central Africa, we considered historical isolation-by-barriers such as elevational relief (mountains) and major rivers (Sanaga and Ogooué), hypothetical montane and lowland forest refugia, climatic oscillation, and temporary oceanic land bridges in the genetic structure of our extant populations.In this study, we characterized the temporal and geographical framework for diversification in R. spectrum. Despite the lack of genetic samples from southern and eastern Cameroon, continental Equatorial Guinea, southern Gabon, and the Republic of Congo, we found corroboration with past geographic events and climatic fluctuation, which appears to explain the surprising and previously undocumented concordance between genetic structure and geographical features in this anomalously distributed Pygmy Chameleon. We interpret geographically based genetic variation elucidated here as clearly associated with (1) the Last Glacial Maximum refugia, (2) a temporary land bridge that connected Bioko Island and the African continent, (3) the uplift of the Cameroon Volcanic Line (lowland vs. highlands) and (4) the major rivers of the Lower Guinean Forest . Below, we summarize these major findings and discuss the implications, representing research and conservation priorities for future work on diversification of vertebrates in the central African tropics.Our results suggest that these factors may have jointly combined in complex ways to influence diversification, ultimately giving rise to geographically structured genetic variation across the variable and disjunct geographical distribution of Rhampholeon recovered the same topology reported in previous studies [Rhinodigitum  between R. spectrum and its sister clade from Tanzania, these two clades (R. spectrum group and the Rhinodigitum subgenus) are polyphyletic [Chamaeleo [Our phylogenetic analyses of the genus  studies , 36, 66.phyletic , 5. Simihamaeleo , 36.R. spectrum reveals the previously unknown existence of five genetically divergent, geographically circumscribed lineages/populations, nested within two major ecologically defined clades: a montane clade, and a lowland clade , similar to those reported here in R. spectrum complex. Thus, this study sets the stage for a comprehensive taxonomic investigation of the species, based on robust statistical species delimitation analyses of genomic data, consideration of name-bearing type specimens, and recently accumulated specimens and their associated data from West-Central Africa.Systematic studies of East African members of the genus mpholeon ,6 and otmpholeon , 71 haveRhampholeon spectrum split from the South Pare and Usambara Mountains group of East Africa  during the late Eocene around 40 Mya. This period corresponded to the break-up of West-Central and East African forests [R. spectrum clade likely took place in the Miocene  and identified divergence with secondary contact as the most likely demographic scenario. This result could be explained by temperature oscillations and habitat contraction during the Pliocene-Pleistocene [R. spectrum on the island of Bioko and the continental populations.Demographic modeling supports the four distinct populations of istocene . Taking istocene , 87 and istocene –91. TogeR. spectrum, over the last 22,000 years, encompasses several areas of stability at high elevation. Previous studies have asserted that topologically complex mountains with pronounced geodiversity, may be correlated with high levels of biodiversity [Rhampholeon spectrum is a leaf-litter dwelling chameleon found exclusively in the rainforest of West-Central Africa. We identified three major population contractions, and their geographic locations overlap with hypothesized refugia. The suitable habitat identified in the heart of the Congo could suggest that a paucity of genetic material from this region may be to blame for our inferred lack of Eocene–Miocene diversification in our time-calibrated phylogenetic estimate.Our species distribution model for iversity , 92–94. R. spectrum’s contemporary phylogeographic patterns. Forest fragmentation-induced vicariance within Rhampholeon apparently initiated during the mid-Eocene with the subdivision of sub-Saharan rainforest into small patches during the Paleocene-Eocene. Within the West-Central African R. spectrum, the diversification into two main lineages during the mid-Miocene corresponds with the uplift of the Cameroon Volcanic Line [R. spectrum in South-East Cameroon, the Republic of Congo, and farther west. In a general sense, these findings highlight the importance of combining genomically informed demographic model selection, dated molecular phylogenies, and distributional stability mapping to draw inferences about the mechanisms that contribute to present-day patterns of the distribution of biological diversity.Two distinct mechanisms, vicariance on the African continent and dispersal via ephemeral land bridges toward the continental island of Bioko, are the main explanations for nic Line . These dOur work represents one of a few recently emerging studies considering alternate processes of diversification and potentially speciation in the Lower Guinean Forest and adjacent islands in the Gulf of Guinea , 21, 96.S1 FigNumbers near nodes denote median value of node age in millions of years. Letters indicate the nodes used for calibration . Quat = (TIF)Click here for additional data file.S2 FigNumerical node support values represent percentages of 100,000 ultrafast bootstrap replicates. Branch lengths are proportional to expected substitutions per site. * Denotes nodes with UFbootsrap >95%.(TIF)Click here for additional data file.S3 FigNumerical node support values represent percentages of 500 non-parametric bootstrap replicates.(TIF)Click here for additional data file.S4 Fig(TIF)Click here for additional data file.S5 FigR. spectrum during the mid-Holocene, (B) suitable habitat during the last glacial maximum (LGM), (C) Stability map representing suitable habitat for Rhampholeon spectrum persistent across LGM and current climate regimes. In (A) and (B), the shades of green represent agreement between global climate models (GCMs) with the darkest green indicating agreement between all three GCMs and the lightest green indicating support from only one GCM. In (C) Dark green represents the highest habitat stability inferred.(A) suitable habitat for (TIF)Click here for additional data file.S1 TableN/A = data, specimen, or information not available.(DOCX)Click here for additional data file.S2 Table(DOCX)Click here for additional data file.S3 TableNode letters correspond to those in Bayesian tree in supplemental (DOCX)Click here for additional data file.S4 Table(DOCX)Click here for additional data file.S5 Table(DOCX)Click here for additional data file.S6 TableValues along the diagonal indicate the number out of 10,000 simulated data sets that were correctly classified by the random forest classifiers. Model 1: no divergence, model 2: divergence without gene flow, model 3: divergence with secondary contact, and model 4: divergence with gene flow.(DOCX)Click here for additional data file.S7 TableModel 1: no divergence, model 2: divergence without gene flow, model 3: divergence with secondary contact, and model 4: divergence with gene flow.(DOCX)Click here for additional data file.S8 Table(DOCX)Click here for additional data file.S1 File(DOCX)Click here for additional data file.S2 File(XLSX)Click here for additional data file.


Anisakis nematodes infecting Indian mackerel (Rastrelliger kanagurta) were initially discovered in Thailand in our preliminary investigation. Nevertheless, the species of Anisakis collected has not been determined nor has its genetic variation been researched. Thus, this study aimed to molecularly identify the species of Anisakis specimens using the internal transcribed spacer (ITS) region of ribosomal DNA sequences. In addition, the intraspecific genetic variation was also determined using mitochondrial cytochrome oxidase subunit II (COII) gene sequences. The phylogenetic relationships of the ITS region classified all samples into Anisakis typica; however, the genetic variation between them could not be distinguished. By contrast, the phylogenetic tree analysis of the COII region identified all samples as A. typica, with 17 different haplotypes by 66 polymorphic sites and five of the substitutions resulted in amino acid change. Additionally, the distribution pattern of the COII region can be separated into two groups between South America and Asian countries. All our haplotypes belong to Asian countries. Compared with the two genetic markers used in this investigation, COII appears to be a better candidate for studying genetic variation sensitive to environmental changes and intermediate or definitive host behavioral changes. Anisakis, Pseudoterranova, and Contracaecum belonging to the phylum Nemathelminthes, class Nematoda, order Ascarida, and family Anisakidae [Anisakis, particularly Anisakis simplex (sensu lato) complex, and A. pegreffii most frequently infect and cause diseases in humans [Anisakis spp. is the transmission mode, a high prevalence of anisakiasis has been observed in countries where raw seafood is consumed culturally, including other countries worldwide [Anisakids are gastrointestinal fish-borne parasitic nematodes causing anisakiasis, first reported in the 1960s in the Netherlands . These nisakidae . Accordin humans , 5. BecaAnisakis spp. is related to several factors, such as global warming, oceanographic conditions, water circulation, salinity percentages, and host density and migration [Anisakis spp., with the L3 encyst residing in internal tissues awaiting ingestion by marine mammals (definitive host) or humans  [Anisakis infection in marine fish can provide crucial information for preventing disease outbreaks by alerting seafood vendors and consumers of the risk [The distribution of igration . Additioal host) . Therefothe risk , 9, 10.Anisakis epidemiology in humans and marine fish has been restricted. Although Thailand is not an epidemic area, global warming and environmental changes may affect the infection and spread of several parasitic diseases, including anisakiasis [Anisakis infections and found that approximately seven marine fish species were infected with these parasites, including Muraenesox spp., Epinephelus areolatus, Rachycentron canadum, Trichiurus lepturus [Priacanthus tayenus [Nemipterus hexodon, and Nemipterus japonicus [Anisakis infection in Indian mackerel (Rastrelliger kanagurta), a commercial fish in Southeast Asia [Anisakis spp. in Thailand remains unclear.Thailand is a peninsular country whose over 3,500 km territory is connected to coastlines. The first case of intestinal anisakiasis in Thailand was reported in 1993 . Howeversakiasis . In the lepturus , Priacan tayenus , Nemipteaponicus . Furtherast Asia . HoweverAnisakis parasites are the molecular biological methods, including polymerase chain reaction (PCR), polymerase chain reaction–restriction fragment length polymorphism, and next-generation sequencing [The parasitic nematodes in the Anisakidae family are very similar and are known as the complex parasitic group that is difficult to distinguish by morphological techniques. Consequently, the most accurate methods of identifying quencing . Presentquencing , 14, 16.Anisakis larvae from Indian mackerel (R. kanagurta) for the DNA amplification and sequencing of the ITS region and COII gene. Additionally, phylogenetic trees were constructed to estimate the evolutionary relationships, which are crucial for understanding parasite population dynamics in the ecosystem and their hosts.This study utilized This study was performed strictly according to the guidelines of the Suan Sunandha Rajabhat University, Thailand, on animal care and use. All animal use protocols were reviewed and approved by the Suan Sunandha Rajabhat University' Institutional Animal Care and Use Committee (ref. LACUC 002/2021).Anisakis specimens detected in a previous study in Indian mackerel (R. kanagurta) [Anisakis specimen using FavorPrep™ Tissue Genomic DNA Extraction Mini Kit , according to the manufacturer's instructions. The DNA concentration was measured using a Nanodrop One-c spectrophotometer .nagurta)  were useAnisakis specimens was performed following previous publications with some modifications [μL) comprised of 5 μL of gDNA and 45 μL of PCR mix containing 1x reaction buffer, 1.5 mM MgCl2, 200 μM dNTPs, 0.25 μM of each primer, 1.5 U of Taq polymerase, and the remaining volume of distilled water up to 45 μL. PCR conditions included an initial denaturation step for 10 min at 95°C, followed by 30 cycles of 30 s at 95°C, 30 s at 55°C, 75 s at 72°C, and a final extension step of 7 min at 72°C. For COII gene, the reaction mixture (50 μL) contained 5 μL of gDNA and 45 μL of PCR mix containing 1x reaction buffer, 2.5 mM MgCl2, 0.4 mM dNTPs, 0.3 μM of each primer, 5 U of Taq polymerase, and the remaining volume of distilled water up to 45 μL. The PCR conditions consisted of an initial denaturation step for 3 min at 94°C, followed by 34 cycles of 30 s at 94°C, 60 s at 46°C, 90 s at 72°C, and a final extension step of 10 min at 72°C. The PCR products were analyzed by 1.5% agarose gel electrophoresis prior to be submitted for DNA sequencing .The amplification of ITS regions  and COII gene of ications , 18. Theications . The lenhttps://blast.ncbi.nlm.nih.gov/Blast.cgi for species identification based on measuring sequence similarities [After nucleotide sequencing, the trace files/chromatograms of ITS and COII sequences were checked manually in BioEdit . Both folarities , 23.Anisakis sequences using MEGA X. Conversely, the number of mutations, parsimony informative sites, haplotypes, genetic diversity indices (haplotype diversity and nucleotide diversity), and neutrality tests (Tajima's D and Fu's FS) were calculated using the DNA Sequences Polymorphism software version 6 [The sequences of ITS and COII of our samples and other related sequences recruited from the NCBI database . The phylogenetic analysis of COII sequences indicated that A. typica divided into two clusters on the basis of geographical locations, including Asia Pacific and American regions  is a pelagic schooling fish widely distributed in the Indian Ocean and Indo-West Pacific region [Anisakis parasite was found in Indian mackerel in some countries, including China [Anisakis infections in Indian mackerel fish from the Samut Songkhram fish market [Anisakis parasite and genetic variability in Indian mackerel from the Gulf of Thailand.The Indian mackerel c region . In sevec region , 28. In ng China , Indonesng China , 31, andng China  but has h market . Food coAnisakis parasites was difficult to identify with a light microscope because of their similar morphology characteristics [Anisakis species were mysterious. Nowadays, however, molecular techniques act as tools to assist in identifying Anisakis species effectively with a gene that represents specific species. Generally, the ITS region of ribosomal DNA  and the mitochondrial COII gene were widely used for identifying Anisakis species. Moreover, both genes have an advantage to differentiate phylogenetic trees as well [In the past, at least before molecular techniques, the species of eristics , 34; thu as well .Anisakis samples from Indian mackerels captured in Thailand are A. typica , also documented in several surveillances of Indian mackerels caught in Indonesia [Anisakis typica has not yet been reported to cause disease in humans, although A. simplex, A. physeteris, and A. pegreffii are the most common human pathogens [In our investigation, molecular analysis using ITS and COII revealed that 17 ndonesia , 31. Theathogens . Howeverathogens .Anisakis sequences with A. typica sequences retrieved from GenBank. Additionally, the results of the comparison with the GenBank database by BLAST showed more than 98% best match from more than 50 A. typica sequences of both ITS region and COII gene. These results conclusively confirm that all of our samples were A. typica. In Thailand, there were definite reports based on molecular species identification of A. typica parasite detected in purple-spotted big eye fish (Priacanthus tayenus) with only one gene that is COII gene but not ITS region [Nemipterus hexodon and N. japonicus) with ITS region but not COII gene [Anisakis species to each other. The investigation of nucleotide compositions of COII sequences of A. typica indicated high A + T richness (>60%), differing from nucleotide compositions of ITS sequences in which both A + T and G + C contents had a similar number, approximately 50%. These results are consistent with previous studies that found high A + T rich of the mitochondrial gene in several parasitic nematodes such as Radopholus similis [Toxocara spp. [Contracaecum osculatum [The analysis of the phylogenetic relationships of ITS and COII based on maximum likelihood trees revealed the grouping between our S region  and threOII gene . By cont similis  and Toxoara spp.  and founsculatum .A. typica samples. Although there was no variation in our group, phylogenetic tree based on ITS region revealed our A. typica differed from the samples of the American region  but similar to the Asia-Pacific continent composed of China, Papua New Guinea, and Indonesia. The result of our ITS phylogenetic tree was consistent with a study on A. typica from threadfin breams in the Gulf of Thailand that found no genetic variation in this group as well (genetic distance = 0%), but a group separation between sequences from Asia, Europe, and America [A. typica with a selection of suitable and standardized genes compared to other samples worldwide [Our study found no genetic variation in ITS regions among our  America . There a America . Chan's orldwide .A. typica in the present study. These results were consistent with those of the Eamsobhana et al. report in which A. typica in purple-spotted big eye fish from the Gulf of Thailand reported high variation of COII by detecting nine haplotypes from a total of 15 samples [Apart from that, the phylogenetic results of the COII gene showed genetic variation in all samples with high levels. An analysis of COII identified 17 distinct haplotypes, which were representative sequences of  samples . The hapA. typica infection [A. typica found in the definitive hosts such as the Delphinoidea superfamily mainly inhabits deep water in tropical and warm temperate waters where their food lived within these areas [Scombridae. Thus, they have been mostly found in Indian Oceans, which correlated with each other according to the COII haplotype pattern in our sample. However, the study of Pekmezci and his colleagues [A. typica from marine fishes collected in Turkish waters (Mediterranean Sea). The presence of A. typica in the eastern Mediterranean Sea (Aegean Sea) could be a consequence of the migration of paratenic or definitive hosts from the Indian Ocean to Mediterranean waters through the Suez Channel [Scomber japonicus marine fish) found on South America clade were possibly eaten by definitive host such as Delphinidae and taken far away; however, there are no clearly evidence. Additionally, we have not found that our 17 COII haplotype patterns linked to South American countries or Atlantic Ocean might be associated with long migration distances and habitat of Indian mackerel fish unsuitable for this area zone, including water temperature and changing tides.Following the results of COII variation found in Indian mackerel fish of the Gulf of Thailand with 17 haplotypes, geographical distributions were shown. However, on the phylogenetic tree , the disnfection . Generalse areas . Consequlleagues  show the Channel . HoweverA. typica larvae molecular identification. At the same time, the COII gene could be suitable for investigating genetic variations linked to different environments due to intraspecific genetic variability that occurs easily.Our analytical results showed that the ITS region of rDNA was less variable than the COII gene. Hence, this study indicated the ITS region as the appropriate genetic marker for A. typica. Nonetheless, A. typica infection in Thai people is quite rare because Indian mackerel is not commonly consumed raw. However, the current trend of eating raw seafood in Thailand is continuously emerging from the popularity of Japanese and Korean foods. Consequently, the results of this investigation will support dietary precautions, especially marine fish, which should not be consumed raw and must be properly cooked to prevent harm from this parasite. Additionally, this research promotes the molecular parasite species identification using the ITS region of rDNA more than the COII gene on the basis of intraspecific genetic variability. Moreover, because of intraspecific genetic variability, COII gene stability may be linked to different environment changes and intermediate and definitive host behavior. However, several factors affecting COII variations of A. typica should be addressed later.This study is a report from Thailand with Indian mackerel (an important popular fish dish) infected with


The chromosomal region 17q21.31 harbors a 900 kb inversion polymorphism named after the microtubule-associated protein tau (MAPT) gene. Since no recombination occurs, two haplotypes are recognized: a directly oriented variant (H1) and an inverted variant (H2). The H2 haplotype features a distribution pattern with high frequencies in the Near East and Europe, medium levels in South Asia and North Africa, and low levels elsewhere. Studies of this genomic region are relevant owing to its likely association with numerous neurodegenerative diseases. However, the causes underlying the geographic distribution of the haplotype frequencies remain a bone of contention among researchers. With this work, we have intended to outline a plausible hypothesis on the origin of the high European H2 frequencies. To that end, we have analyzed an extensive population database (including three new Iberian populations) to explore potential clinal variations of H2 frequencies. We found a sigmoidal frequency cline with an upward trend from South Asia to Europe. The maximum value was detected in the Basques from Gipuzkoa province (0.494) with the curve’s inflection point in the Near East. From our results, we suggest that the most likely scenario for high H2 frequencies in Europe would be a founding event in the Near East during the late Paleolithic or early Neolithic. Subsequently, such H2 overrepresentation would have reached Europe with the arrival of the first Neolithic farmers. The current frequencies and geographic distribution of the 17q21.31 inversion suggest that the founding events mainly affected the H2D subhaplotype.The online version contains supplementary material available at 10.1007/s00438-022-01969-0. The chromosomal region 17q21.31 harbors a 900 kb inversion polymorphism  of the inversion have been obtained so far, leading to divergent hypotheses on the origin of the H2 ancestral haplotype. These estimates range from 3 million years , namely rs10514879 and rs199451 (see Supplementary Table 1), using the high-resolution melting (HRM) assay  located within the boundaries of the inversion of the MAPT gene, following the protocol developed by Donnelly et al.  . As mentioned, these geographic regions show higher Phylogenetic relationships were examined by constructing a genealogy of STR/SNPs haplotypes using the median-joining network approach , aiming to elucidate which of these two subhaplotypes could account for the origin of the high G test) to evaluate population differentiation. Thus, we found statistically significant differences for H2 haplotype frequencies between the pool of Basque collections and the Valencian sample . This genetic heterogeneity was determined by Gipuzkoa Basques. In this way, while H2 frequencies between Navarrese Basques and Valencians did not show significant differences , we found statistically significant differences between Gipuzkoan and Navarrese Basques .Table MAPT*H2 haplotype frequency distribution throughout the territory from Europe to South Asia , slope (P < 10–3), midpoint (P < 10–6), and F ratio (P < 10–6).An analysis of the spatial structuring of haplotype frequencies using the GenoCline program revealed a sigmoid cline with a Southeast-Northwest orientation, specifically with an azimuth of 312° to the North. All sigmoid function parameters were statistically significant, including the ordinate scaling factor  appeared around the Near East, indicating a shift in the function's trend in this region. As a result, populations from the eastern portion of the Near East showed frequencies below 0.15 (Kuwait: 0.09 and Yemenite Jews: 0.12), while those in the western area featured frequencies above this value. .P < 10–5 , thus confirming genetic heterogeneity between Europe and South Asia in terms of MAPT*H2 frequencies. Further analysis based only on European populations revealed a significant cline for MAPT*H2 , but in this case, spatial variation in H2 frequencies matched the linear regression model . All of the fixation indices obtained were highly significant at MAPT*H2 frequencies in the non-Basque collections ranged from 0.21 to 0.26, whereas the Basque collections exhibited figures between 0.31 and 0.49. Non-native Basques (residing population of the Basque Country), with a high admixture level between both groups, recorded an intermediate frequency (0.28). Earlier studies have suggested that the French-Basque population has traditionally experienced substantial gene flow from neighbouring non-Basque communities  is noteworthy. Such value represents a maximum among the world populations analyzed to date.Southern European samples, especially Spanish groups, exhibited high levels of genetic heterogeneity. Spanish populations evidenced a wide range of H2 haplotype frequencies, varying from 0.21 in Catalonia to 0.49 in Gipuzkoa. Overall, such a wide variability could be attributable to the differences between autochthonous Basques and the remaining Spanish samples. In this way, a is the most frequent one (0.075) and presumably the ancestor of all Iberian H2 haplotypes. For this reason, we based on data for haplotype a to perform MRCA estimates.To delve into the causes of the high frequency of H2 in Europe, we analyzed four STRs from the MAPT region , that is, around the beginning of the Last Glacial Maximum.A set of previous studies provide genome-wide data on ancient European populations (references in the Methods section). A molecular polymorphism commonly examined in those studies based on ancient DNA from human remains is the SNP rs10514879, a diagnostic marker for MAPT haplotype assignment. Unfortunately, Iberian samples with identifiable genotypes proved rare, then all European individuals pooled. Table MAPT haplotype assignment was also feasible on ancient Central and South Asian populations from data published by Narasimhan et al. . The numUnlike African populations, where H2D is generally less frequent than H2'  stands out as the highest among all human groups analyzed to date. Gipuzkoa Basques are exceptional because their H2 frequencies are practically equal to H1 (0.51). As a result, we could detect significant genetic heterogeneity between a pool of the Basque samples (Gipuzkoa and Navarre) and the Mediterranean collection , on the one hand, and also between the two native Basque groups, most likely due to the unusually high H2 frequency in Gipuzkoa. There has been plenty of evidence that autochthonous Basques from Gipuzkoa are unique in terms of language , topography, inbreeding patterns and consanguinity structures, among other traits, relative to other neighboring Basque groups . Thus, we could postulate the impact of genetic drift by cumulative effects of founder events during the Last Glacial Maximum in the Franco-Cantabrian refugium and a subsequent spreading associated with the postglacial recolonization of central and northern Europe , whose population gene pool still shares substantial similarities with the early European farming groups Below is the link to the electronic supplementary material.


Bos gaurus) is found throughout mainland South and Southeast Asia but is listed as an endangered species in Thailand with a decreasing population size and a reduction in suitable habitat. While gaur have shown a population recovery from 35 to 300 individuals within 30 years in the Khao Phaeng Ma (KPM) Non-Hunting Area, this has caused conflict with villagers along the border of the protected area. At the same time, the ecotourism potential of watching gaurs has boosted the local economy. In this study, 13 mitochondrial displacement-loop sequence samples taken from gaur with GPS collars were analyzed. Three haplotypes identified in the population were defined by only two parsimony informative sites . One haplotype was shared among eleven individuals located in different subpopulations/herds, suggesting very low genetic diversity with few maternal lineages in the founder population. Based on the current small number of sequences, neutrality and demographic expansion test results also showed that the population was likely to contract in the near future. These findings provide insight into the genetic diversity and demography of the wild gaur population in the KPM protected area that can inform long-term sustainable management action plans.The gaur ( Bos gaurus Smith, 1827) also known as “Indian bison” or “seladang” is the largest living wild cattle species [Gaur  measure the genetic diversity in the extant population of wild gaurs in the KPM, and (2) detect the signatures of past and present demographic events in the wild gaur population and predict their future course. The mitochondrial displacement-loop (mt D-loop) region offers a powerful genetic marker that is useful for investigating the origin, genetic diversity, and relationships among cattle populations and species –26. Here2 (2.83 x 2.83 km) area of restored montane forest bordering Khao Yai National Park and part of the Dong Phayayen-Khao Yai Forest Complex [2 of the gaur populations has well-developed infrastructure characterized by an agricultural matrix and lacks noteworthy patches of natural vegetation. Land use includes farming of corn, cassava, and other crops; orchards and gardens; plantations; fallows; and various animal farms. The climate in the area is tropical-monsoonal, with a dry season from November to March followed by a hot inter-monsoonal period until May, and a wet season from May to October.We captured 13 gaurs from the main population in the KPM protected area , an 8 km Complex . Detaile Complex . The gau Complex . The lanThe gaurs were captured by darting from a vehicle or tree platform, and capture and handling were overseen by qualified veterinarians. Satellite collars  were fitted to 13 adult gaurs , and data were collected from both sexes and the different subpopulations –31. All 2, 0.2 mM dNTPs, 5.0 μM primers, 0.5 U Taq polymerase , and 25 ng genomic DNA. The PCR conditions were as follows: initial denaturation at 94°C for 3 min, followed by 35 cycles of 94°C for 30 s, 55°C for 30 s, 72°C for 30 s, and a final extension at 72°C for 5 min. The PCR products were detected by electrophoresis through 1% agarose gel. The DNA fragments were extracted from the ethidium bromide stained gel and purified using a QIAquick Gel Extraction Kit . Nucleotide sequences of the DNA fragments were determined by the DNA sequencing service of First Base Laboratories Sdn Bhd . The blastn and blastx programs (http://blast.ncbi.nlm.nih.gov/Blast.cgi) were used to search nucleotide sequences in the National Center for Biotechnology Information database (nr) to confirm the identity of the amplified DNA fragments. The sequences generated were deposited in the DNA Data Bank of Japan (DDBJ) (https://www.ddbj.nig.ac.jp/) (Accession numbers: LC707734 –LC707746)  .B. gaurus sequences retrieved from GenBank . The sequences were aligned using the “Clustal” default parameters of the Molecular Evolutionary Genetics Analysis 11 (MEGA11) software [h) diversity and nucleotide (π) diversity [H), the estimator theta (S), the overall haplotype, and the average number of nucleotide differences (k) were calculated based on the mt D-loop sequences, as implemented in DnaSP version 6 [Multiple sequence alignment was performed for 19 sequences in the mt D-loop dataset including nine males, four females, and six software . All unaersion 6 .D [D* and F* tests [Fs [R2, which has greater statistical power for small sample sizes, was calculated using DnaSP version 6 [Demographic history was examined using statistical tests of neutrality as Tajima’s D , Fu and F* tests , Fu’s Fsests [Fs , Ewens-Wests [Fs . Ramos-Oersion 6 . The sigersion 6 , 45. Theersion 6 , 47. Thiersion 6 , 49. TRAersion 6 . The EBSTo simulate guar population genetic scenarios, individual-based forward genetic simulations were performed using the simulation program quantiNEMO an individual-based sequence data input . The sim2.Based on observation by DNP officers, the original herd (Group 1) inhabiting the KPM protected area has separated into four herds (Groups 1–4) within the protected area and two satellite herds (Groups 5 and 6) living outside KPM as well as two solitary adult males . ThirteeD value was -2.134, p < 0.01; the Fu’s FS value was 7.165, p = 0.993; the Fu and Li’s F* value was -2.814, p < 0.05; the Fu and Li’s D* value was -2.615, p < 0.05; the Ewens-Watterson value was 1.000, p = 1.000; and the Ramos-Onsins and Rozas’s R2 value was 0.211. Mismatch distribution analysis indicated a multimodal distribution (p = 0.900). The EBSPs suggested that population size remained constant over a long period Click here for additional data file.S2 TableAll sequences were deposited in the DNA Data Bank of Japan (DDBJ).(DOCX)Click here for additional data file.S1 FigThe x-axis represents the number of pairwise differences (mismatches), while the y-axis represents the frequency of these differences. The observed mismatch distribution (red line) is compared to the expected distribution (blue line) for a stable population.(TIFF)Click here for additional data file.


Opsariichthys hainanensis on Hainan Island and mainland China, using mtDNA cyt b gene (1140 bp) and D-loop (926 bp), nuclear RAG1 gene (1506 bp), and 12 microsatellite loci. Mitochondrial phylogenetic analysis identified five major lineages according to the geographical distribution from different populations. We suggested that two dispersal events occurred: the population in the Changhua River migrated to the Red River (Lineage B), and the populations in the South Hainan region moved northwards to the North Hainan region. However, populations in Northwest Hainan Island dispersed to the populations around the Gulf of Tonkin (Lineage A1) and populations in Northeast Hainan Island dispersed to the populations in mainland China (Lineage A2). Our results indicated that the populations of O. hainanensis suffered a bottleneck event followed by a recent population expansion supported by the ABC analysis. We suggest that O. hainanensis populations were found mostly in the lowlands and a lack of suitable freshwater habitat in southern mainland China and Hainan during the Last Interglacial period, and then expansion occurred during the Last Glacial Maximum.The ichthyofauna of continental islands is characterized by immigration through a land bridge due to fluctuating sea levels. Hainan Island is adjacent to the southern margin of mainland China and provides opportunities for understanding the origin and diversification of freshwater fishes. The aim of our study was to evaluate the level of genetic variation and phylogeographic structure of  Onychostoma barbatulus ). bidens ; Opsariientalis, ). Howeve pulcher  and Linidisparis . Accordidisparis ). The Redisparis ,10. Intedisparis . Our preeage A2) .O. hainanensis following a recent population demographic expansion and population range expansion [Fs analysis were used for neutral evolution, and Bayesian skyline plot analyses were increasingly used to reconstruct the historical demographic expansions of O. hainanensis. In this study, the significantly negative values of Fu’s Fs tests and the nonsignificantly negative values of Tajima’s D test were investigated. Fu’s Fs test is much more sensitive in detecting population growth than Tajima’s D test [O. hainanensis might follow the post-LGM  expansion pattern, whose effective population size rapidly increased approximately 15 Kya. After the Last Glacial Maximum, we speculated that the warm climate was suitable for O. hainanensis survival and provided more suitable habitat for supporting the occurrence of a recent population expansion in mainland China. Population expansion that occurred in mainland China has been reported in freshwater fishes such as Sinibrama macrops [Hemiculter leucisculus [R. ocellatus [O. hainanensis indicated population decline based on mitochondrial data. These results indicated that O. hainanensis experienced a complex demographic history, and we focused on the demographic changes in recent time frames in the ABC scenarios. However, the results of our ABC 1 analyses indicate that the population size was constant and conflict with the results from other methods. Therefore, we defined two biologically meaningful scenarios of the competing demographic history in ABC 2 analyses. Our results revealed that the populations of O. hainanensis suffered a bottleneck event followed by a recent population expansion. We suggest that O. hainanensis populations were found mostly in the lowlands and a lack of suitable freshwater habitat in southern mainland China and Hainan during the Last Interglacial, with the greatest range expansion during the Last Glacial Maximum (High haplotype diversity, low nucleotide diversity values, and star-like networks were observed that indicate xpansion . In addis D test . Bayesia macrops , the shacisculus , and thecellatus . A highe Maximum .


Anopheles minimus is an important malaria vector throughout its wide geographic range across Southeast Asia. Genome sequencing could provide important insights into the unique malaria transmission dynamics in this region, where many vector species feed and rest outdoors. We describe results from a study using Illumina deep whole-genome sequencing of 302 wild-caught An. minimus collected from three Cambodian provinces over several years  and seasons to examine the level of population structure and genetic diversity within this species. These specimens cluster into four distinct populations of An. minimus s.s., with two populations overlapping geographically. We describe the underlying genetic diversity and divergence of these populations and investigated the genetic variation in genes known to be involved in insecticide resistance. We found strong signals of selection within these An. minimus populations, most of which were present in the two Northeastern Cambodian populations and differ from those previously described in African malaria vectors. Cambodia is the focus of the emergence and spread of drug-resistant malaria parasites, so understanding the underlying genetic diversity and resilience of the vectors of these parasites is key to implementing effective malaria control and elimination strategies. These data are publicly available as part of the MalariaGEN Vector Observatory, an open access resource of genome sequence data. An. minimus across Cambodia is described.Using whole genome sequencing and broad sampling across the nation, the genetic diversity of the malaria mosquito  An. minimus is a small mosquito that plays a major role in sustaining malaria transmission across the Greater Mekong Subregion (GMS). This species is commonly associated with human-altered habitats, able to breed in rice paddies and forest-fringe habitats. The GMS is becoming increasingly fragmented as deforestation and agriculture create patchwork landscapes3. Historically, malaria transmission in this region has been dominated by the major vector species An. dirus, a forest-dwelling, highly competent vector, and human-attracted mosquito. More recently, land use change has resulted in the decline of An. dirus populations and has shed light on the role of other vectors in malaria transmission, species like An. minimus, that are able to breed in human-associated habitats and quickly adapt to changing environments6. Vectors that occupy different seasonal and ecological niches can also sustain malaria transmission and change the dynamics of seasonal transmission patterns. While An. dirus is considered the major vector in the GMS, there are many other species that have been shown to be susceptible to malaria parasites that play a role in local transmission9.13 and spread through the GMS. Lab infection experiments have shown that Anopheles minimus is able to be infected by and transmit the parasites in Cambodia that have been shown to have slow clearance in response to the Artemisinin combined therapy drug treatment14, and these parasites are co-circulating in areas where An. minimus is active and abundant. All five human malarias are transmitted in Cambodia15, with Plasmodium vivax infections about as prevalent as those from Plasmodium falciparum16. An. minimus is known to transmit P. falciparum and P. vivax throughout its wide geographic range, which spans from China down into the Malay archipelago, and from western India to Vietnam17.To further complicate malaria transmission in this region, successful lineages of multi-drug resistant malaria parasites have continued to emerge from the area along the Thai-Cambodian borderAnopheles species in Southeast Asia are members of cryptic species complexes, groups of isomorphic species that are molecularly and often behaviorally distinct. In other Anopheles cryptic species groups like the Gambiae complex, some closely related cryptic species have been shown to exchange genetic material from almost every region of the genome, described as having “porous species boundaries”18. The level of gene flow between what is typically thought of as isolated species has important implications for the spread of genes relevant to malaria transmission, such as insecticide resistance alleles, or genes that confer susceptibility or resistance to malaria parasites. Population genomic studies of An. gambiae s.l. across the African continent have shown that geographically distinct populations have similar signatures of selection in response to decades of insecticide-based vector control19, sharing common haplotypes that confer insecticide resistance over thousands of kilometers. Anopheles minimus is a member of such a species complex with at least three recognized cryptic species: An. minimus s.s. (An. minimus A), An. harrisoni (An. minimus C), and An. yaeyamaensis (An. minimus E)21 and is also in the Funestus group, somewhat closely related to An. funestus, an important African malaria vector. Only An. minimus s.s. has been reported from collections in Cambodia5, and is considered to have greater indoor and human biting preferences than other members of this species complex. We currently know very little about the population structure of An. minimus and other important vectors occurring across Southeast Asia.Many P. vivax infections, and outdoor malaria transmission are all factors that complicate the goal of malaria elimination in this country. Despite outdoor biting behaviors of many local vector species, insecticide-treated nets are still the primary vector control method implemented in the GMS and do have some protective efficacy against P. falciparum infection22. Investigations into baseline rates of insecticide resistance have shown that An. minimus from different regions has varying levels of susceptibility to DDT and pyrethroid insecticides, with some evidence of resistance in populations in Cambodia, Thailand, Laos, India, and Vietnam25. Additionally, there is very limited regulation of the use of insecticides for public health and agriculture in Cambodia26.Cambodia is transitioning from focusing on malaria control to malaria pre-elimination, with a goal of eradicating malaria from the country within the next five years. Drug-resistant parasites, prevalent An. minimus that were active during the rise and spread of drug-resistant parasites in Cambodia. We hope to contribute to a better understanding of malaria transmission in Southeast Asia.In the context of the spread of parasites that threaten our best and last-line defense against malaria, we need to know what the population history of the vectors of these parasites looks like across this same space. In this study, we seek to describe the population structure, diversity, and divergence of populations of An. minimus female mosquitoes collected from five different field sites in Cambodia using the Illumina HiSeq 2000 platform with 150 bp paired-end reads with a target coverage of 30X for each. Mosquito collections in Thmar Da, in Eastern Cambodia, were done in 2010. Longitudinal monthly collections were performed from February 2014 to January 2015 in two sites in each of the Preah Vihear, and Ratanakiri provinces. Quarterly collections were also done in 2016 in one site in Preah Vihear province, Cambodia.We generated whole genome sequence data from 302 wild-caught individual 27. Sequence reads were aligned to the An. minimus reference genome AminM128. We restricted our analysis to the largest 40 contigs, which cover 96.6% of the AminM1 reference genome, as many smaller-sized contigs can confound diversity and divergence calculations. We found that 138,161,075 (75.4%) of sites within these 40 largest contigs pass our site filters and thus were accessible to SNP calling. Of these, we discovered 38,000,285 segregating single nucleotide polymorphisms (SNPs) that passed all of our quality control filters of 55,307,039 total segregating SNPs. 13.4% of these SNPs were multiallelic, with 32,906,471 biallelic SNPs. There were 4,807,355 triallelic and 286,459 quadriallelic SNPs. A total of 100,160,790 sites were invariant. The median genome-wide coverage was 35X.The methods for sequencing and variant calling closely follow those of the Anopheles gambiae 1000 Genomes project phase 2 (Ag1000G)An. minimus in Cambodia. Samples collected from five sites in three provinces split into three distinct clusters; here, we report on 283 individuals that could be clearly assigned to these clusters  over biallelic SNPs distributed over the genome of 302 individual field-collected mosquitoes showed that there is clear population structure of ers Fig. , excludiAn. minimus in Cambodia , on the Thai-Cambodian border, PV from the Northern province Preah Vihear (n = 156), and the two distinct populations collected in Ratanakiri province in the Northeast, each including individuals collected at both collection sites, these are designated as populations RK1 (n = 58) and RK2 (n = 28).To further explore this population structure, we performed the same PCA over individual contigs from different regions of the genome. Performing PCA over the largest X-chromosomal contig KB664054 resulted in a splitting of the western and northern samples, indicating four distinct populations of dia Fig. . PCA froK = 2, the samples from Northeastern Cambodia split from Northern and Western Cambodia samples. At K = 3, the two different groups in Ratanakiri were separated, consistent with the PCA results. At K = 4, there was some evidence for geographical population structure between the Western TD and Northern PV populations, but the admixture results did not perfectly correspond with geographic sampling, with some evidence of mixed ancestry in the PV samples. Again, this is consistent with the PCA groupings, with the generally weaker evidence of geographic population structure between TD and PV. A cross-validation analysis showed the lowest cross-validation error for K = 2 and K = 3, consistent with the strongest evidence for population structure between the two RK groups and other populations. Cross-validation error was higher at K = 4, consistent with the weaker differentiation between TD and PV. At no point was their an indication of admixture between RK1 and RK2.To confirm our results from PCA, we also performed an admixture analysis. We ran admixture on each of the largest 10 contigs for values of K between 2 and 6 , Watterson’s Theta (θW), and Tajima’s D statistics were calculated over 4-fold degenerate sites on autosomal contigs larger than 2 megabases with 100 bootstrap replicates over samples. These 17 contigs represent 80% of the Anopheles minimus genome .To characterize population diversity among these populations, nucleotide diversity , Watterson’s Theta (θW), and Tajima’s D over the largest 14 contigs (representing 80% of the An. minimus genome). As with the Fst scans, there were no large regions of higher differentiation in any of the populations that might indicate major structural variants or inversions  is near a Carbohydrate sulfotransferase, which is involved in detoxification processes. Comparing TD to RK1 and RK2 reveals multiple strong signals of selection, some which are present in both Northeastern populations, as well as many unique RK2-specific signals  and topical repellents. New control tools are needed in this region and in the context of outdoor, residual malaria transmission. The population structure within this single Southeast Asian vector species in a small country like Cambodia may indicate barriers to implementing vector control methods centered around genetic modification or sterile insect release. If populations of vectors are diverging with limited gene flow, despite being in the same place, genetic control based on any assumption of a single population of vectors would be unlikely to penetrate vector populations in this region.Anopheles species represented in whole genome population data. This resource of An. minimus whole genome data will be a starting point to explore Anopheles genome variation in important transmission contexts such as Southeast Asia. This study is the foundation for further delving into the population structure and history of An. minimus, which acts as an important malaria vector across all of Southeast Asia.This study expands the An. minimus in Cambodia includes an adaptive, resilient, and diverse set of populations that can thrive in human-created habitats and potentially contribute to epidemics of drug-resistant malaria as we work toward malaria elimination. It is crucial that we appreciate the evolutionary history and ecology of this important and widespread malaria vector.Examining the population structure in a single species over its range and through time will help us to better understand the potential risk associated with multiple insecticide-resistant populations of vectors and how best to approach managing and monitoring insecticide resistance. An. minimus female mosquitoes were selected from several previous field collections in Cambodia with the goal of including a subsample of An. minimus specimens from different field sites and time points for population genomic analysis. These anophelines were collected using CDC light traps, human landing collections, cow-baited tents, and barrier fences from five different locations in Cambodia. Collections in Thmar Da took place in 2010, while collections in two sites in Preah Vihear and Ratanakiri provinces took place monthly from February 2014 to January 2015 and in four quarterly collections during 2016. These five sites had enough An. minimus individuals to include in population genomic analyses.35. Multiple Anopheles species were collected in each of these studies, including the An. minimus A specimens that have been included in this study. GPS coordinates for each collection site are available in the sample metadata  and in the North in Preah Vihear province (Chean Mok pagoda and Preah Kleang village), and in the Northeast Ratanakiri (Sayas and Chamkar San villages)37. These were stored individually in 1.5 ml tubes with silica gel desiccant. DNA was extracted from the head and thorax of collected mosquitoes using either a CTAB extraction method or in Nextec plates. Individual mosquitoes were molecularly identified using Sanger sequencing of the rDNA ITS2 region using primers ITS2A and ITS2B from38 and compared to voucher reference rDNA ITS2 sequences in NCBI.Specimens were morphologically identified immediately after collection using keys from40. This low-input sequencing pipeline uses enzymatic fragmentation and less than 10 nanograms of input DNA. In our sequence and population QC, these low-input samples did not appear to be of lower quality or influence the clustering of whole genome sequences in our PCA analysis. 144 individual An. minimus mosquitoes were sequenced using the standard Illumina pipeline, and 158 individuals were sequenced using the low-input pipeline.Individual samples were sequenced at the Wellcome Trust Sanger Institute using whole-genome sequencing on the Illumina HiSeq 2000 platform. Paired-end multiplex libraries were prepared as per the manufacturer’s specifications, with DNA fragmented using Covaris Adaptive Focused Acoustics. Multiplexes comprised 12 tagged individual mosquitoes. Three lanes of sequencing were used for each multiplex to control for variation between sequencing runs. Sequencing and cluster generation was done using the manufacturer’s protocol for paired-end reads of 150 bp with insert sizes from 100 to 200 bp. The target coverage for each individual was 30X. To include some samples that had DNA concentration that was too low to run through the standard Illumina pipeline, we whole genome sequenced a set of specimens using a new low-input DNA sequencing pipeline as inAnopheles reference genome AminM1 using BWA version 0.7.1542. using bwa mem. A BAM file was constructed for each individual using merged alignments from multiple lanes. Duplicate reads were marked using Picard version 2.6.043.Illumina whole genome sequence reads were aligned to the For each sample, the depth of coverage was computed at all genome positions. Samples were excluded if median coverage across all chromosomes was less than 10×, or if less than 80% of the reference genome was covered by at least 1X.We used PCA to identify and exclude individual samples that were population outliers. SNPs were down-sampled to use 100,000 segregating non-singleton sites from autosomal contigs. PCA was computed using scikit-allel version 1.2.0. We iteratively identified and excluded any individual samples that were outliers along a single principal component. We then identified and excluded any individual samples or small sample groups that clustered together with other samples in a way that was not plausible, given metadata regarding their collection location. We initially performed a PCA with all of the 302 samples that passed our QC filters. We identified a group of 9 mosquitoes labeled as being collected in Preah Vihear province, but clustering with RK2. To be extremely conservative, the Preah Vihear samples that grouped with RK2 samples were removed from our final population-level assignment in case of potential mislabelling or plate mix-up or DNA contamination. Another 10 individual mosquitoes were excluded due to being isolated outliers in the PCA (not part of any cluster), driving PC2 and PC3. In all, we did not give a population assignment to 19 mosquitoes from our data set.39. For each of the ten largest contigs in the reference genome, we identified biallelic SNPs with a minor allele frequency above 1% and then thinned these SNPs to select 50,000 per contig. We then ran ADMIXTURE on each contig separately for values of K from 2 to 6 inclusive. For each contig and value of K we repeated the ADMIXTURE analysis twice with different random seeds. All runs were performed with five-fold cross-validation to compute cross-validation error, which provides some guidance regarding the confidence of the fitted ancestry fractions.We performed an analysis of population structure using ADMIXTURE version 1.3.0An. minimus AminM1 genome using scikit-allel version 1.3.3. and custom code in Python.Diversity statistics Pairwise Fst, nucleotide diversity, Tajima’s D, and Watterson’s Theta were calculated in windows across the largest 40 contigs on the W), and Tajima’s D statistics were calculated over 4-fold degenerate sites on autosomal contigs larger than 2,000,000 bases. These 17 contigs represent 80% of the Anopheles minimus genome. These statistics were calculated as an average over sliding windows with 100 bootstrap replicates over samples. Populations were downsampled to the size of the smallest population RK2 (n = 28) for these calculations.Nucleotide diversity (π), Watterson’s Theta  using the Genome Browser tool in VEuPathDB Vectorbase28 and walking in both directions from the location signal to see which annotated genes were present in that location. Gene IDs and gene functional predictions were recorded.Genes potentially associated with these signals were identified by going to the location of the peak of each signal on the Ace1, Rdl, KDR, and Gste2 (Supplementary Data We report in this study variants at known insecticide resistance-associated alleles. Variants occurring at a frequency of more than 2% in at least one of the four populations are reported in the known insecticide-resistance-associated genes Further information on research design is available in the Supplementary materialsDescription of Additional Supplementary FilesSupplementary data 1-5Reporting Summary


Mus musculus domesticus) is a widespread human commensal that has recently been introduced to North America. Its introduction to the Americas is thought to have resulted from the transatlantic movements of Europeans that began in the early 16th century. To study the details of this colonization history, we examine population structure, explore relevant demographic models, and infer the timing of divergence among house mouse populations in the eastern United States using published exome sequences from five North American populations and two European populations. For North American populations of house mice, levels of nucleotide variation were lower, and low-frequency alleles were less common than for European populations. These patterns provide evidence of a mild bottleneck associated with the movement of house mice into North America. Several analyses revealed that one North American population is genetically admixed, which indicates at least two source populations from Europe were independently introduced to eastern North America. Estimated divergence times between North American and German populations ranged between ∼1,000 and 7,000 years ago and overlapped with the estimated divergence time between populations from Germany and France. Demographic models comparing different North American populations revealed that these populations diverged from each other mostly within the last 500 years, consistent with the timing of the arrival of Western European settlers to North America. Together, these results support a recent introduction of Western European house mice to eastern North America, highlighting the effects of human migration and colonization on the spread of an invasive human commensal.The Western European house mouse ( Untangling the invasion histories of human commensals helps to understand the impact of human migration on global ecosystems. Rats, pigeons, sparrows, zebra mussels, and fruit flies are a few of the many invasive species that humans have accidentally or intentionally helped disperse around the world  Was the colonization of eastern North America associated with a population bottleneck? (2) Do North American populations show mixed ancestry, as would be expected if multiple colonization events occurred from different source populations? (3) When did house mice begin to colonize North America? We discovered reduced genetic diversity and fewer rare alleles in North America than in Europe, consistent with a bottleneck. One population of house mice from Florida showed a strong signature of admixture, consistent with multiple introductions of mice to this region. Demographic modeling revealed recent split times between eastern North American populations, consistent with the timing of human migrants from Europe. These results highlight the close association between the movement of mice and humans and provide perspective into one of the world's most successful invasive species.M. m. domesticus samples from two European populations  and eight samples of M. spretus (Spain) were obtained via the European Nucleotide Archive (ENA: PRJEB9450); these were sequenced with an average depth of ∼20× .Exomes were extracted from whole genome samples using bedtools . The samvariants , filterivcftools . After tM. spretus as an outgroup.We estimated phylogenetic relationships among individuals using RAxML . A maximM. m. domesticus populations included in the PCA and one population of M. spretus. M. spretus was included in all admixture analyses since introgression between M. musculus and M. spretus is known to occur in Europe  using PLINK to examine population structure . ADMIXTUFst was used to quantify the extent of genetic divergence observed between populations in relation to the amount of variation observed within populations. Cockerman–Weir's weighted Fst was computed using vcftools “—weir-fst-pop” flag on filtered exomic SNPs from French, German, and eastern North American samples of M. m. domesticus.π) and Watterson's theta (θ) are estimators of the neutral mutation parameter, 4Neµ, where eN is the effective population size and µ is the neutral mutation rate. Tajima's D , summarize present levels of variation and can be used to illuminate past demographic processes. We estimated π and θ using ANGSD  to infer the best fit demographic model. Parameter values in dadi are scaled to θ = 4Nancμ, the neutral mutation parameter as a function of the ancestral effective population size and mutation rate per generation. We used this relationship to convert the output to standard units  using the per-site mutation rate μ = 4 × 10−9 and a generation time of 1 year  and Watterson's theta (θ) from allele frequencies computed in ANGSD. The populations from Germany and France had substantially higher levels of nucleotide diversity (average π = 0.28%) than any of the North American populations  than any of the North American populations  possible f3 statistics using the seven population samples of M. m. domesticus and the single population sample of M. spretus. Of these 56 tests, eight returned a negative value, all involving the Florida population, suggesting that this population is admixed . From the decay rate, we estimated a time to admixture from France (or a related population) of 102.08 ± 45.83 years, assuming one generation per year. We estimated a time to admixture from New Hampshire/Vermont (or a related population) of 87.25 ± 19.31 years.We further investigated the details of admixture in Florida using ALDER. ALDER estimates the dates of plausible admixture events while also providing a formal 2-reference weighted LD statistic to test if the two potential source populations are the probable contributors to the admixed population. This analysis returned no significant 2-reference weighted LD statistics using any two pairs of populations as the contributing populations for Florida's admixture . We did,GADMA to infer divergence times and effective population sizes under a variety of two-population models for all pairs of populations from Germany, France, and North America. First, we estimated demographic parameters between Germany and France. Next, we compared each North American population with each European population, constraining the inferred divergence time to the recent history during which house mice are known to have emerged from the Middle East . Finally, we compared North American populations with each other, again using a constraint on divergence time of 7,500 years. In all cases, we compared results under a simple divergence model without migration to a divergence model including migration , and a model with migration suggested a divergence time (856 years ago) whose confidence interval substantially overlaps the divergence times estimated from other populations pairs  was only 60% of that seen in European populations (π = 0.28%). Second, Tajima's D was more positive in North American populations than in European populations, consistent with the loss of rare alleles. Finally, demographic modeling using dadi revealed smaller population sizes for most North American populations compared to the German populations   , 2020. S,000 AD) .Human colonization history suggests that source populations for North American mice are likely to have come from northern Europe . VirginiDespite the strong British influence, the Spanish were the first Europeans to establish consistent transatlantic exchanges with North America and thereby had the earliest opportunities to introduce non-native organisms. A recent study by We conclude that house mice in the eastern United States arrived and dispersed largely within the past 500 years. Their arrival was associated with a genetic bottleneck, as US populations harbor only 60% of the average genetic variation seen within European populations. Since the arrival of the initial source population, at least one other source population successfully mixed with an established population in Florida. Notably, Florida was also colonized by different Western European settlers within the past few centuries. The overall similarity in the estimated divergence times of North American populations of house mice with the known timing of human colonization of eastern North America suggests a very close association between the movements of humans and mice and suggests that the earliest European settlers may have brought mice with them.jkac332_Supplementary_DataClick here for additional data file.