A set of microsatellite markers with high polymorphism from Tsaiya duck were used for the genetic monitoring and genetic structure analysis of Brown and White Tsaiya duck populations in Taiwan.The synthetic short tandem repeated probes were used to isolate new microsatellite markers from the genomic DNA of Tsaiya ducks. Eight populations, a total of 566 samples, sourced from Ilan Branch, Livestock Research Institute were genotyped through novel and known markers. The population genetic variables were calculated using optional programs in order to describe and monitor the genetic variability and the genetic structures of these Tsaiya duck populations.In total 24 primer pairs, including 17 novel microsatellite loci from this study and seven previously known loci, were constructed for the detection of genetic variations in duck populations. The average values for the allele number, the effective number of alleles, the observed heterozygosity, the expected heterozygosity, and the polymorphism information content were 11.29, 5.370, 0.591, 0.746, and 0.708, respectively. The results of analysis of molecular variance and principal component analysis indicated a contracting Brown Tsaiya duck cluster and a spreading White Tsaiya duck cluster. The Brown Tsaiya ducks and the White Tsaiya ducks with Pekin ducks were just split to six clusters and three clusters when K was set equal to 6 and 3 in the Bayesian cluster analysis. The individual phylogenetic tree revealed eight taxa, and each individual was assigned to its own population.According to our study, the 24 novel microsatellite markers exhibited a high capacity to analyze relationships of inter- and intra-population in those populations with a relatively limited degree of genetic diversity. We suggest that duck farms in Taiwan could use the new (novel) microsatellite set to monitor the genetic characteristics and structures of their Tsaiya duck populations at various intervals in order to ensure quality breeding and conservation strategies. Anas platyrhynchos, which is widely distributed over the northern hemisphere. Since more than 4,000 years ago, duck domestications have been occurred on many places of worldwide [The domestic duck was derived from the characteristically green-headed Mallard, orldwide . Asia keorldwide . Howeverorldwide . Recent,orldwide . Before orldwide .The Livestock Research Institute (LRI), Council of Agriculture, Executive Yuan is the only institute to do research and provide assistance to the duck industry in Taiwan. Genetic selection, improvement and conservation of duck breeds are their major responsibilities. The relationship and characteristics of the eight LRI populations in this study are shown in The four new and two original egg-production duck breeds should be maintained and conserved for economic needs in Taiwan. Traditionally, the breeding strategies for a closed population were managed on the basis of visible phenotypic traits. However, the significance of breed is not just their specific identities. The separated genetic composition of each breed is the matter . The infMicrosatellites, also known as simple sequence repeats (SSRs), represent a class of repetitive sequences widely distributed in all genomes. They are abundant, ubiquitous, easy to automate, codominant, universal, robust, reliable and reproducible markers. Polymorphism patterns exhibited by microsatellites are greater than any other contemporary DNA molecular marker system . In receThe fitness of Tsaiya duck to their environment is the results of natural selection for centuries in Taiwan. Before replacing them with “improved breeds”, we ought to think about the irreversible loss of genetic diversity or has a certain conservation strategy to be developed in Taiwan. Before formulating these conservation strategies, it is one of the most important missions to clearly understand and define the genetic structure of the population of Tsaiya (strains) currently in Taiwan. The aim of this study was to create and collect a set of microsatellite markers with high polymorphism for the genetic monitoring and genetic structure analysis of Tsaiya (strains) duck populations.A total of eight populations of LRI were investigated in this study. Six of these populations were Tsaiya ducks. There are two major breeds of Tsaiya duck: White Tsaiya and Brown Tsaiya duck. After a period of selection and breeding, two populations of White Tsaiya and four populations of Brown Tsaiya were raised in LRI, including the GBT , BI Fig, BII Fi, BIII F, Ilan WhBlood samples were collected from 566 individuals from these 8 populations, including 43 GBT, 69 BI, 95 BII, 72 BIII, 80 GWT, 72 WI, 96 H, and 39 P individuals. For each bird, 3 mL of blood were drawn from the superficial plantar metatarsal vein or wing vein. Whole genomic DNA was then extracted with Genomic DNA Isolation Reagent  using the standard phenol-chloroform method.RsaI and XmnI  until most of the DNA fragments were between 300–1,000 bp in length. Re-naturing of single strand SuperSNX24 forward (5′GTTTAAGGCCTAGCTAGCAG AATC3′) and SuperSNX24+4P reverse (5′pGATTCTGCTA GCTAGGCCTTAAACAAAA3′) 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. 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 then were 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 PRISM 3730XL DNA Analyzer . The fragments with higher repeats were then selected for polymorphism testing.Genomic DNA was isolated from blood taken from one male and one female Tsaiya duck using a previously described method; the following steps were slightly modified from the procedure previously described by Glenn and Schable . The isoSeven published microsatellite markers were added to the marker set in this study, including APT004, APT005, APT008, APT015, APT020, APT025, and APT031.Taq DNA polymerase , 1×PCR buffer (1.5 mM MgCl2), 0.2 mM 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 in-line GeneScan500 LIZ Size Standard marker . The fragment size was calibrated and analyzed with Peak Scanner Software version 1.0 . The loci which had an allele number (Na) greater than two and similar annealing temperatures were selected for whole population analysis.The selected highly repeated fragments were subjected to polymerase chain reaction (PCR) and polymorphism testing which would verify if the microsatellite loci could be amplified and used to show diversity in the investigated populations. Primers for loci amplification were designed using Primer3plus . CAG-tagO), the expected heterozygosity (HE), and the polymorphic information content (PIC) were calculated with the Microsatellite Toolkit. The Hardy-Weinberg equilibrium (HWE) test was performed using the GENEPOP computer program, which also was used to estimate F-statistics  for each locus, the pairwise FST between populations, and the average inbreeding coefficient (FIS). Nei’s genetic distance (DA) between populations was measured with Microsatellite Analyzer. The phylogenetic tree was generated via the PHYLIP program using the neighbor-joining (NJ) method with bootstrap test of 1,000 resamplings of loci with replacement. The genetic distances of the proportion of shared alleles (POSA) was used to estimate and draw a POSA individual phylogenetic tree [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  procedure, as implemented in the ARLEQUIN 3.5 package. Principal component analysis (PCA) was performed with GENALEX v.6.501 software in order to spatially plot clusters and individuals based on the distance matrix with data standardization .The model-based approach proposed for population structure analysis of the eight populations was carried out with the software STRUCTURE 2.3.1  which asOver 50 DNA fragments containing STRs were cloned. A polymorphism test was performed using the LRI populations, and 17 loci which had allele numbers more than two were picked. The 17 novel markers included three complex repeats . In simple repeat markers, there was one dinucleotide unit (T1P1075), and four trinucleotide units , while others contained tetranucleotide units. These novel markers were then combined with the seven previously known markers , and toga) was 11.292. The actual number of alleles ranged from 2 (T3P1027) to 36 (TYD029). The average number of effective alleles per locus (Ne) ranged from 1.816 (T3P2090) to 16.588 (TYD029), with an average across loci of 5.370. The PIC value ranged from 0.375 (T3P1027) to 0.937 (TYD029), with an overall average of 0.708. All of the selected microsatellite loci in this study were sufficiently polymorphic, indicating that these loci were suitable for the genetic analysis of ducks.Polymorphism was clearly observed at all the microsatellite loci in all eight of the LRI duck populations. The genetic characteristics of the 24 microsatellite loci are listed in E being 0.746. The HO among the 24 microsatellite loci had a range of 0.347 (T3P2080) to 0.808 (TYD024), with the average value of HO being 0.591 (The HE among the 24 microsatellite loci had a range of 0.450 (T3P2090) to 0.941 (TYD029), with the average value of Hng 0.591 . HoweverF-statistic values  for each locus are shown in FIS for all the loci was 0.043, and the FIS per locus varied from −0.093 (APT020) to 0.304 (TYD025). The average FIT for all the loci was 0.233, and the FIT per locus varied from 0.095 (T1P1075) to 0.397 (TYD006). The mean FST for all the loci was 0.197. This value implied that around 19.7% of the total genetic variation was caused by population differences and that 80.3% of total genetic variation was due to genetic differentiation among individuals within each population.The Wright’s E, HO, PIC, the mean observed number of alleles, and the mean effective number of alleles (Ne), were calculated to estimate the allelic diversity at each locus of population. These genetic parameters across the 24 loci for the eight duck populations are listed in E varied from 0.535 (WI) to 0.686 (BIII), whereas HO varied from 0.482 (WI) to 0.707 (H) and PIC ranged from 0.461 (WI) to 0.633 (BIII). The WI population had the lowest values of HO, HE, and PIC. The BIII population exhibited the highest values of HE, and PIC. The H population exhibited the highest values of HO, and the smallest value of FIS , indicating an insufficient degree of inbreeding. The deviation from the Hardy-Weinberg proportions within populations (FIS) varied from −0.047 to 0.103. The highest inbreeding effects were found in the BI population (0.103). The H population contained 16 loci that were significantly deviated from the HWE (p<0.01)  (6.542), followed by the hybrid (6.500) and BIII (5.833) populations, while the WI population had the smallest observed MNA (3.708). Negative (p<0.01) , and werFST 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 were varied from 0.083 (for the BI and H population pair) to 0.322 (for the WI and BII population pair). There were several pairs of population have sub-lowest FST of which around 0.09 .The values of The genetic distances between the duck population pairs varied from 0.157 (for the BI and H population pair) to 0.582 (for the BII and WI population pair). There were relatively high genetic distance among the white duck populations  and between the other populations (p>0.3) except for GWT and H pair while GWT was paternal of H.In this study, the results of the differentiation of the eight duck populations using the NJ tree are shown in A PCA of pair-wise genetic distances among the eight examined goose populations was used to represent the relative positions of the populations. The first (PC1), second (PC2), and third (PC3) principal components accounted for 25.95%, 23.62%, and 20.60% of the total variation, respectively . The resThe results of the degree of variance in the duck populations via AMOVA are summarized in The results of the STRUCTRE program analysis of all the populations are shown in a among known loci was 9.71±2.43, and the average of Na among novel loci was 11.94±9.20. Although the average of Na among novel loci was larger than known loci, the deviation of Na of novel loci was much large (Na was 2 to 36). Among those loci, a number of hypervariable loci with more than 20 alleles in the LRI populations, including TYD005, TYD024, and TYD029, were found. Such complex and hypervariable loci have previously been found in human CODIS loci and some canine microsatellite loci [(ID) (probability of identity) values [−5, which means these three markers alone could be used to differentiate more than ten thousand individuals.In this study, we used the 24 higher polymorphism microsatellite markers (loci) to test the genetic structure of the eight duck populations. The results showed that the average of Nite loci  as well.) values  of TYD00O values of all the markers were higher than 0.3. A previous report suggested that microsatellite markers used in studies of genetic variation and distance should have HO values of between 0.3 and 0.8 in the population [a, Ne, and PIC values across all the loci were 11.29, 5.370, and 0.708, respectively, indicating higher genetic variability and diversity in the investigated ducks than among domestic ducks from other areas [To examine the diversity of the 17 novel microsatellite makers and the seven published markers in Taiwan Tsaiya ducks, several indicators were calculated from randomly selected samples from the LRI. The Hpulation . The Na,er areas . SignifiO lower than HE) were exhibited by almost all the populations. Only the H population had excess heterozygosity, while the GBT and GWT populations each had roughly equal HO and HE values. The sources of heterozygous deficit probably included inbreeding, null allele, aneuploidy, misscoring and Wahlund effect [E = 0.676, HO = 0.707), far from inbreeding (FIS = −0.047) and departure HWE (16 of 24 markers HWE departure). In general, except for H, every Tsaiya duck population in LRI was a relatively low FIS , and the numbers of loci departing from the HWE were less than 7. It can thus be concluded that the Tsaiya ducks in LRI probably have good breeding programs. The results of the intra-population diversity analyses for the Pekin populations from the LRI were similar, including relatively high variation  and FIS values of 0.08. WI was selected for crossing Muscovy drakes to improve the carcass appearances of mule ducks. WI had related low diversity  and little more inbreeding (FIS = 0.098). This was probably caused by the multiple and long-term selection.In d effect . There wd effect . The majBrown Tsaiya and White Tsaiya ducks are the two major domestic breeds in this study, in addition of P and a hybrid population. According to the AMOVA results , the proO  and PIC   . High po= 0.623) . SelectiO (0.482) and observed MNA (3.708)  were dispersal in PCA than brown ducks, that WI was split away from GWT at PC3 . The sep (3.708) . Chang e (3.708) . It showFIS, inter-population with low genetic distance and POSA or model-based approach with proper assigning and almost single portion individuals indicated the breeding conditions of Tsaiya ducks in LRI is generally fit demand. At last, the suggestion was that LRI and other duck farms in Taiwan could use the new microsatellite set to genetic monitor their Tsaiya populations at intervals for quality breeding and conservation strategies.The present study verified that the 24 high polymorphic microsatellite loci, including the 17 novel loci isolated in this study, were useful in studying the relationships and genetic diversities among the Tsaiya duck populations in LRI even there were almost similar genetically content. In addition, these markers could be applied continually in genetic monitoring for quality analysis and breeding of ducks in Taiwan. Analysis through 24 microsatellite markers, the intra-population with high diversity and low


Saccharomyces eubayanus strains, the cryotolerant ancestor of lager yeast, from ten sampling sites in Patagonia along 2,000 km of Nothofagus forests. Frequency of S. eubayanus isolates was higher towards southern and colder regions, demonstrating the cryotolerant nature of the species. We sequenced the genome of 82 strains and, together with 23 available genomes, performed a comprehensive phylogenetic analysis. Our results revealed the presence of five different lineages together with dozens of admixed strains. Various analytical methods reveal evidence of gene flow and historical admixture between lineages from Patagonia and Holarctic regions, suggesting the co-occurrence of these ancestral populations. Analysis of the genetic contribution to the admixed genomes revealed a Patagonian genetic origin of the admixed strains, even for those located in the North Hemisphere. Overall, the Patagonian lineages, particularly the southern populations, showed a greater global genetic diversity compared to Holarctic and Chinese lineages, in agreement with a higher abundance in Patagonia. Thus, our results are consistent with a likely colonization of the species from peripheral glacial refugia from South Patagonia. Furthermore, fermentative capacity and maltose consumption resulted negatively correlated with latitude, indicating better fermentative performance in northern populations. Our genome analysis, together with previous reports in the sister species S. uvarum suggests that a S. eubayanus ancestor was adapted to the harsh environmental conditions of Patagonia, a region that provides the ecological conditions for the diversification of these ancestral lineages.Population‐level sampling and whole‐genome sequences of different individuals allow one to identify signatures of hybridization, gene flow and potential molecular mechanisms of environmental responses. Here, we report the isolation of 160  S. eubayanus, the lager yeast ancestor, represents an unprecedented opportunity to extend our knowledge on yeast phylogeography and the origins of the S. pastorianus lager hybrid. However, the genetic, phenotypic and evolutionary history of this species remains poorly known. Our work demonstrates that S. eubayanus isolates from Patagonia have the greatest genetic diversity, comprising the largest number of lineages within a single geographic region and experienced ancestral and recent admixture between lineages, likely suggesting co-occurrence in Patagonia. Importantly, some isolates exhibited significant phenotypic differences for traits such as high temperature and ethanol tolerance, together with fermentation performance, demonstrating their potential in the brewing industry for the generation of new styles of lager beers. Furthermore, our results support the idea of colonization from peripheral glacial refugia from the South, as responsible for the high genetic diversity observed in southern Chilean Patagonia. Our results allow hypothesizing a successful physiological adjustment of the species to the local conditions in Patagonia, explaining its wide distribution in the southern hemisphere.Lager yeast history has intrigued scientists for decades. The recent isolation of  Saccharomyces genus is an ideal model to investigate genomic variation and admixture, since within the clade isolates occupy a broad range of environments. Currently, the clade is composed of eight species ),ee genus , 29. Undthe year . Howeverubayanus , thus insurveyed –25. Our so found . The genast Asia , 32. At ast Asia ). Subseqmisphere , 32.S. eubayanus  reveals a higher genetic diversity for the PB South American lineages than that reported for S. eubayanus in the Northern Hemisphere [S. uvarum, where similar sequence divergence among S. uvarum populations was described [S. cerevisiae, a much higher genetic diversity is observed compared to other regions of the world [S. eubayanus from Tierra del Fuego is the most represented population in Patagonia, and likely within the species . This lineage shows high levels of hybridization/introgression into northern populations. The higher nucleotide diversity of PB-1 was supported by a trend of greater genetic diversity among individuals sampled from Coyhaique, Torres del Paine, Magallanes and Karukinka sites , where the dispersal of N. pumilio is also greater than in more northern regions. However, since the three different lineages were geographically segregated, it is not possible to attribute increased genetic diversity exclusively to latitude or to the nature of PB-1, as all samples isolated at latitudes higher than 45°S were consistently assigned to PB-1. Nevertheless, our dense sampling procedure, together with other findings, suggest that other lineages are not present in the extreme south, therefore, we cannot determine whether the observed increment of genetic diversity with latitude is a general pattern [The phylogenomic analysis presented here of wild misphere , 25. Indescribed , whereashe world . Interes pattern , 23. A sS. eubayanus cryotolerance evolved recently, as N. pumilio (its preferred environment) became secondarily adapted to cold during the orogenesis of the Andes [Nothofagus (and subsequently S. eubayanus) was already established in Patagonia before the onset of the last glacial maximum , when ice sheets covered most landmasses south of 43º. After this glacial period, there was massive floristic recolonization and ecological succession [S. eubayanus genetic diversity north of 43°, where different populations congregate in a single geographic location [This scenario is also consistent with the idea that he Andes , 29. Alsccession . Our resccession . Indeed,location .Fig 2B). Overall, all of the admixed strains from Chile, New Zealand and North America contained regions from the PB-1 lineage, that together with our population genetics analysis and admixture model between populations, suggest that PB-1 could be the most widespread lineage reported to date, including admixture with the Holarctic lineage. Indeed, higher Fis values are found in the PB-1 cluster, compared to PB-2 and PB-3, suggesting that meiosis and inbreeding are more frequent in PB-1. Our admixture analysis demonstrates recurrent hybridization between ancestral lineages, supporting a scenario in which gene flow among Patagonian and Holarctic ancestral populations took place, and that is consistent with the co-occurrence of these populations in the past . Similar evidence of admixture in other yeast species, such as S. cerevisiae, S. uvarum, and S. paradoxus was previously reported [S. cerevisiae (or a close sister species) and the S. eubayanus HOL lineage. This demonstrates a pervasive contact between Saccharomyces populations and constant admixture, likely facilitated by their dispersal by insect’s in nutrient-rich periods of the year [Our STRUCTURE analyses provide evidence of contact and admixture between PB-1 and the other two PB lineages .Nothofagus pumilio), coigüe (N.dombeyi) and ‘ñirre’ (N. Antarctica) and Araucaria araucana were obtained aseptically from ten sampling sites in Chile : Sampling was performed as previously described [Bark samples from ‘lenga’  to identify colonies to the genus level . Sacchartails in ). In mantails in .Saccharomyces eubayanus CBS12357T reference genome [One isolate per tree was considered for DNA sequencing. DNA was obtained using a Qiagen Genomic-tip 20/G kit . The library prep reaction used was a 100x miniaturized version of the Illumina Nextera method. Samples were sequenced on a NextSeq 500/550 High Output Kit v2.5 (300 Cycles) flow cell. Reads were processed with fastp 0.19.4 (-l 37–3) , 39. Reae genome  using BWe genome .http://broadinstitute.github.io/picard/). Variant calling and filtering was done with GATK version 4.0.10.1 [S. eubayanus gene annotations [Mapping files were tagged for duplicates using Picard tools 2.18.14 . For STRUCTURE analysis, a thinned VCF file was generated with vcftools 0.1.15 (—thin 1000)[S. eubayanus strains. Structure was run five times (K ranging from 3 to 7), with 10,000 burn-in and 100,000 replications for each run. Optimal K values were obtained using structure-selector (http://lmme.qdio.ac.cn/StructureSelector/) [http://omicsspeaks.com/strplot2/) [S. cerevisae average recombination rate , containlector/)  accordinlector/) . The reslector/)  and visurplot2/) . We perfrplot2/) . For finrplot2/) , a non-trplot2/) . We used cM/kbp, ). ChromoS. eubayanus was tested with Treemix [S2 Text) [S. eubayanus individuals that did not show any sign of recent admixture according to STRUCTURE results, plus the S. uvarum and a S. cerevisiae individual were kept as outgroups. In addition, we pruned out SNPs that were in linkage disequilibrium using PLINK (—indep-pairwise 50 10 0.2). We dissected the five S. eubayanus populations into subpopulations according to geographical locality and clusters obtained with fineSTRUCTURE as criteria. Treemix was first run ten times for each value of m (migration events) ranging from 1 to 6 (-noss–k 500) and two optimal m values (2 and 4) were estimated using the optM R package (https://cran.r-project.org/web/packages/OptM/index.html) (S3 Table). Treemix was subsequently run 100 times  after which a consensus tree and bootstrap values were obtained using the BITE R package [S5D Table).Historical and recent admixture between populations of  Treemix  and ADMIS2 Text) . For Tre package . We calc package . Admixtu package . Seven mFst were calculated with StAMPP 1.5.1 Weir and Cockerham's unbiased estimator [We estimated π and Tajima’s D using the R packages PopGenome 2.6.0 . Values stimator , 61 to ostimator , for whiS. eubayanus strains showing recent genetic admixture were split to bins of 100 SNPs and each bin was assigned to target populations using adegenet’s hyb.pred function [The variants of the function . GLOBETRFis, Hs, and Ho by using the basic.stats function. To perform a Mantel test, first the Nei’s genetic distances between subpopulations  was calculated with the R package StAMPP [The R package hierfstat  was usede StAMPP .https://y1000plus.wei.wisc.edu/). SMART (Simple Modular Architecture Research Tool), used in GENOMIC mode, was used to identify known PFAM protein domains and homologies [Isolates were assembled with Spades using k from 21 to 67. To detect the non-reference material we used the custom pipeline based on the method described in . Potentimologies  using alS. eubayanus strains was performed as previously described [6 viable cells/mL and fermentations were maintained for 14 days and weighed every day to calculate the CO2 output. At the end of the fermentation, metabolites were determined using HPLC.The microcultivation phenotyping assay of the escribed . Brieflyescribed . FermentS1 Fig(A) Fluorescence values for each sample are shown in grey. (*red): haploid CL609.1; (*green): diploid CL1004.1; (*blue): tetraploid CL1005.1. (B) Number of cell vs propidium iodide intensity is shown. Haploid (n), diploid (2n) and tetraploid (4n) examples are shown for the same strains as above (*).(PDF)Click here for additional data file.S2 FigA heatmap was obtained using fineSTRUCTURE chunkcounts. Each row and column represent an isolate and the colour scale indicates genetic sharing . The tree shows the clusters inferred from the coancestry matrix. Populations and subpopulations can be inferred from the presence of darker colours in the diagonal(PDF)Click here for additional data file.S3 FigFST between lineages. (C) Pairwise genetic distance between individuals versus geographic distance. Genetic distances were estimated using the Nei’s distance method. Geographic distances were estimated based on map coordinates in google maps (https://www.google.com/maps). A positive correlation between genetic distance and geographic distance was found.(A) Tajima’s D values along the genome for PB-1 (top), PB-2 (middle) and PB-3 (bottom) lineages. Tajima’s D were estimated using the R packages PopGenome 2.6.0. (B). Individual example of extremely low Tajima’s D values in Chromosome V for PB-1 and PB-2. The close-up denotes the genes located within the low Tajima’s D region suggesting a common genetic ancestry.(B) (PDF)Click here for additional data file.S4 Fig(A) Phylogenetic network obtained with Treemix allowing 0 (A) and 2 (C) migration events. Lines are coloured according to the migration weight which indicates the fraction of ancestry from the donor population. Arrows indicate the direction of the admixture event. The scale bar shows ten times the average standard error of the entries in the sample covariance matrix. (B) and (D) Residual fit of the trees in A and C respectively. (E) Admixture graphs of all models tested. Seven admixture graphs models were tested for their goodness of fit to f4 statistics. Continuous edges indicate direct ancestry; numbers at these edges denote scaled drift (f2-statistic). Dotted edges indicate admixture; numbers at these edges show the percentage of ancestry contribution. Graphs were constructed using the R package admixturegraph and were exported as qpgraph format.(PDF)Click here for additional data file.S5 Fig(A) Principal component analysis using only non-admixed 83 isolates from all populations shows partial concordance with the phylogenetic tree. The first component clearly separates the Chinese/North American branch from the South American lineages. Second component identifies the PB-3 as the most separated lineage, suggesting a lower level of outbreeding, while a partial overlap can be identified between the other lineages. The middle positioning of PB-1 using the third component mirrors the shape of the un-rooted phylogenetic tree based on the sequence divergence . (B) Nin(PDF)Click here for additional data file.S6 Fig(PDF)Click here for additional data file.S1 Text(DOCX)Click here for additional data file.S2 Text(DOCX)Click here for additional data file.S1 Table(XLSX)Click here for additional data file.S2 Table(A) Bioinformatics Summary statistics and (B) Sequence identity matrix between strains.(XLSX)Click here for additional data file.S3 Table(XLSX)Click here for additional data file.S4 Table(A) Population genetics summary statistics for each lineage & locality, (B) Fst values.(XLSX)Click here for additional data file.S5 TableS. eubayanus and number of strains containing each gene, (G) Domains found in the candidate LGT in the PB-2 lineage, (H) Accessory ORFs found in the HOL lineage.(A) Globetrotter analysis, (B) Optimal migration events for Treemix analysis, (C) f4 statistics, (D) Admixture graphs tested and their best error values, (E) de Novo assembly statistics, (F) Accessory genes in (XLSX)Click here for additional data file.S6 Table(A). Raw phenotypic values. (B) Phenotype's correlations and (C). Phenotype comparison across localities.(XLSX)Click here for additional data file.S7 Table2 lost in all strains. (B) Dunn's multiple comparisons test across localities and (C) Physical Chemical parameters after wort fermentation.(A) CO(XLSX)Click here for additional data file.


Salmo trutta L.) sampled from 16 rivers along the south coast of Cornwall in southwest England. This region is characterized by many small coastal streams with a few larger catchments. At a regional level, genetic structuring of contemporary populations has been influenced by a combination of events, including the last Ice Age and also more recent human activities over the last millennium. All populations are shown to have gone through strong genetic bottlenecks, coinciding with increased exploitation of mineral resources within catchments, beginning during the Medieval period. At more local levels, contemporary human‐induced habitat fragmentation, such as weir and culvert construction, has disproportionally affected trout populations in the smaller catchments within the study area. However, where small catchments are relatively unaffected by such activities, they can host trout populations with diversity levels comparable to those found in larger rivers in the region. We also predict significant future loses of diversity and heterozygosity in the trout populations inhabiting small, isolated catchments. Our study highlights how multiple factors, especially the activity of humans, have and continue to affect the levels and structuring of genetic diversity in trout over long timescales.We used microsatellite markers to investigate levels and structuring of genetic diversity in trout ( Structuring and levels of genetic diversity in brown trout populations along the south Cornwall stretch has been influenced by multiple natural and anthropogenic factors. At a regional scale, factors since the last glacial maximum have left their imprint. At finer local scales, the main driver of evolutionary change appears to be human activity. This area of southwest Britain has a long history of mining for metal ores. This mining would have affected fish populations in many ways, including the construction of weirs to divert water to ore processing mills and the release of mine water contaminated with heavy metals into rivers. It is clear that both historical events, such as the Quaternary glaciations  is not well understood  and were therefore useful for the identification of trout x salmon hybrids. Polymerase chain reactions (PCRs) and genotyping were performed as described in Paris et al. ) were calculated using GenAlEx v6.502 , estimated using the rarefaction method, was implemented in HP‐RARE 1.0  derived from each of the K partitions. STRUCTURE was run for 250,000 iterations following a burn‐in of 100,000 iterations with the number of inferred populations (K) ranging from one to 12. To identify finer levels of structure, hierarchical analyses were performed based on the optimum K value from the first run. Analysis parameters for the hierarchical analyses were as given above except that the maximum K was set at n + 1, where n represents the number of populations in the analysis. Ten independent runs of the program were performed using the admixture model with correlated allele frequencies and not using the population of origin information. The most likely number of clusters was calculated using the ΔK method of Evanno, Regnaut, and Goudet ] and geographical distances (km) between populations . The Mantel test was performed with 999 permutations using GenAlEx v6.502 , a Mantel test Mantel,  was usedRousset, . Pairwis2.6M (Mc), the expected value of M in a population at mutation‐drift equilibrium, was calculated based on multiple values of the prebottleneck effective population size  and a mean mutation rate (µ) of 5 × 10–4  varied from 0.1 to 2.Evidence for the presence of genetic bottlenecks in each of the sampled rivers and groups identified in the STRUCTURE analyses was assessed using both the heterozygote excess  using VarEff v1.2  and M . We used a Brownian motion mutation model with starting parameters based on FST calculations and a constant mutation rate for each locus. We used uniform priors for both theta  and M . To estimate recent migration rates of trout between rivers, we used BayesAss 3.0.4  and a sampling interval of 1,000 iterations. Migration rates were calculated as the average of the three runs.Two methods were used to estimate historical and contemporary gene flow between rivers. Migrate‐n v3.7.2  at 10, 50, and 100 generations in the future were calculated as:HO is the current observed heterozygosity, Ne is the current effective population size, and t is time in the future in generations. The model assumes random mating and that reductions in heterozygosity are due solely to genetic drift. Effective population size was calculated using two methods: the linkage disequilibrium method as implemented in NEESTIMATOR v.2  were identified as trout × salmon hybrids and were removed from the data set. COLONY identified a total of 67 full‐sib families  and highest in the Lerryn  to 50 (SsaD58). Allelic richness ranged from 6.06 (PER.TRE) to 12.68  for the full data set and 0.024 (p < .0001) for the “core” data set . Population pairwise FST values ranged from 0.0026 (FAL.TGY v FAL.TRE to 0.217 (GWE.MER v PER.TRE). After Bonferroni correction, ten out of 325 pairwise FST comparisons were nonsignificant.Global 3.3K method identified K = 2 as the most likely partition of the data  constituting a group and the other small streams being distinct entities  and a set of generally larger rivers. For the STRUCTURE analysis, the Evanno ΔAs the STRUCTURE analyses showed a lack of genetic structuring of trout within rivers, the DAPC analysis was performed at the river level, combining multiple collections from the same river into a single sample. Successive hierarchical DAPC analyses also showed that six of the small streams were distinct. Analysis of the whole data set showed trout in the Helford, Portmellon, Percuil, and Kennall rivers to be distinct Figure , with thr2 = .003, p = .327). However, a Mantel test on a data set comprising only the generally larger, nonoutlying populations showed a significant positive correlation between geographic and genetic distances . For the River Fowey—the largest river in the study—there was no evidence of IBD between trout populations within the Fowey .A Mantel test showed a nonsignificant relationship between geographical and genetic distances for the full data set ; however, at local levels this structure was more complex  and that this was partly due to fragmentation of rivers by dams.At smaller geographical scales, the genetic structure is often locally complex. Trout populations in the larger catchments and some of the smaller streams display significant isolation by distance, with fish in geographically proximal rivers tending to be genetically similar. However, it is clear that trout in six of the rivers studied here do not fit this pattern and that a mixture of evolutionary, anthropogenic, and environmental processes have acted to alter the levels of genetic diversity and differentiation between them and the generally larger, more “characteristic” rivers of the region. Similar patterns have been found in other fish species. For example, clear regional structure was found in Baltic populations of pike  are probably distinct due to the presence of barriers such as culverts (Portmellon and Polperro) and weirs  caused by mining activities, these areas could have been readily recolonized by local fish. The lack of IDB in the River Fowey—one of the larger catchments included in this study—would tend to support the ready movement of trout within catchments.Southwest Britain has a long history of mining, spanning from the prehistoric, through the Roman and Medieval periods to the present day Gerrard, . Early mOncorhynchus clarki clarki) isolated above impassable waterfalls were highly differentiated from downstream populations, having much lower levels of diversity and heterozygosity  sampled downstream of dams in the Columbia River were significantly more diverse than resident rainbow trout populations from above the dams , there are no barriers to fish movement between the sampling sites and the sea and their distinctiveness is likely due to the effects of mining activities on their waters and associated polluting effects on the fish populations within them. DiBattista  found thThe genetic diversity of trout in the small streams that have been badly affected by mining practices within their catchments may have been further compromised due to a lack of gene flow. Our analyses showed substantial levels of historical gene flow between the rivers analyzed here which contrasted greatly with estimated levels of contemporary gene flow. However, high levels of dissolved metal in river water could act as a chemical barrier to fish movement in much the same way as physical barriers, such as weirs. Laboratory experiments have shown that metal‐naïve fish generally avoid sublethal concentrations of toxic metals  that differed in their exposure to polychlorinated biphenyls (PCBs).Together, these multiple processes have resulted in genetic erosion of trout in small streams across the region. Exposure to industrial pollution can elicit multiple possible responses including migration, local extinction, or adaptation . Genetic erosion has serious negative effects at the population level, over both short and long timescales and could potentially impede adaptive responses of small populations to future stressors , while there was an increased risk of extinction in populations of the Glanville fritillary (Melitaea cinxia) with reduced heterozygosity  have lower numbers of deleterious mutations than smaller, more inbred populations, highlighting that purifying selection may be less effective in such populations , compromise their reproductive fitness and elevate the risk of extinctions  gene loci. It is also clear that some of the populations from the smallest streams are isolated from the main trout metapopulation along this stretch of coast. Future conservation efforts should investigate ways of increasing genetic diversity within the outlier populations, preferably by enabling natural reconnection with fish inhabiting proximal larger catchments.None declared.R. Andrew King: Data curation (lead); Formal analysis (lead); Visualization (lead); Writing‐original draft ; Writing‐review & editing . Jamie R. Stevens: Conceptualization ; Funding acquisition ; Supervision (lead); Writing‐original draft ; Writing‐review & editing . Bruce Stockley: Conceptualization ; Funding acquisition ; Writing‐original draft (supporting); Writing‐review & editing (supporting).


Acute Lymphoblastic Leukemia (ALL) is the most common cancer in children. Differences are found among ethnic groups in the results of the treatment of pediatric ALL. In general, children with a high level of native American ancestry tend to respond less positively to ALL treatments, which may be related to specific genomic variants found in native American groups. Despite the evidence, few data are available on the distribution of the pharmacogenomic variants relevant to the treatment of ALL in traditional Amerindian populations, such the those of the Amazon region. Given this, the present study investigated 27 molecular markers related to the treatment of ALL in Amerindians from Brazilian Amazonia and compared the frequencies with those recorded previously on five continents, that are available in the 1,000 Genomes database. The variation in the genotype frequencies among populations was evaluated using Fisher’s exact test. The False Discovery Rate method was used to correct the results of the multiple analyses. Significant differences were found in the frequencies of the majority of markers between the Amerindian populations and those of other regions around the world. These findings highlight the unique genetic profile of the indigenous population of Brazilian Amazonia, which may reflect a distinct therapeutic profile for the treatment of ALL in these populations. The treatment of ALL is based on the application of a combination of chemotherapeutic agents. Two drugs, 6-mercaptopurine (6-MP) and Methotrexate (MTX), are the principal types of medication used during the consolidation and maintenance phases of the treatment of ALL. Survival rates are relatively high, at approximately 80%, although around 20% of the children treated present serious toxicological complications that frequently lead to the interruption of the treatment. The variation in the toxicological response of patients to the treatment of ALL may be determined by different polymorphic variants of the genes involved in the pharmacokinetics and/or pharmacodynamics of these drugs4. Ethnic differences have been recognized in many clinical studies of the treatment of ALL10. In general, Hispanic children present worse results in the treatment of ALL than European children9. This difference may be related to an increase in the frequency of variants of the germinative lineage associated with native American ancestry in Hispanic patients, which have a negative influence on the treatment of ALL9.Acute Lymphoblastic Leukemia (ALL) is the most common cancer subtype found in children, accounting for almost 80% of cases11. The vast majority of the available studies have focused on European or American populations, which emphasizes the need to identify the genetic profile of Amerindian populations, in particular the variants that are significantly more common in these populations, as well as compiling a database for the development of clinical applications appropriate for this ethnic group and for populations admixed with this group, such as the general Brazilian population11.Despite the apparent influence of genetic variants linked to native American ancestry on the treatment of ALL in children, few data are available on the frequency of these variants in traditional Amerindian populations, such as those from the Amazon regionIn this context, the present study investigated 27 molecular markers related to the treatment of ALL in a combined Amerindian population from Brazilian Amazonia. These findings were compared with the data available on representative populations from five continents, that are available in the 1,000 Genomes database.https://www.1000genomes.org. This sample , through protocol 961,451. The informed consent was obtained from each study participant and all research methods in this study were performed in accordance with approved guidelines and regulations. The study sample consisted of 203 healthy individuals from three Amerindian groups resident in the Brazilian Amazon region: 25 individuals from the Asurini do Koatinemo group, 84 individuals from the Asurini do Trocará group, and 94 from the Kayapó-Xicrin group. These individuals were combined in a single sample, denominated NAT (or Native), for the statistical analyses. For the comparisons with populations from other continents, data were obtained from the database of the 1,000 Genomes project, available at Markers that showed a significantly different allelic distribution between Amerindian and of 1,000 Genomes populations were investigated in a sample of 42 patients diagnosed with B-cell ALL, from the Brazilian Amazon region and who had a high contribution of Amerindian genetic ancestry  participate in the pharmacokinetics and/or pharmacodynamics of one or both of the drugs (6-MP or MTX) used to treat ALL. The polymorphisms were selected based on the information available in the PharmGKB, NCBI, and Ensembl databases, and through a literature search. The polymorphisms selected for the present study have potentially functional effects, including alterations of amino acids and the alternative splicing of promoter regions or are present in regions linked to transcription factors, as well as markers included in previous studies of ALL or the drugs used to treat this cancer.A total of 27 genetic markers , following the manufacturer’s instructions, and quantified using a NanoDrop 1,000 spectrophotometer . The polymorphisms were genotyped using the TaqMan OpenArray Genotyping technology  in a QuantStudio 12 K Flex Real-Time PCR System , following the protocol published by Applied Biosystems. The Taqman Genotyper software was used to analyze the data from the plates and the precision of the genotype reads, as well as to control the quality of the genotyping.ATIC), rs4673993 (ATIC), rs9344 (CCND1), rs1800909 (GGH), rs3758149 (GGH), rs2236225 (MTHFD1), rs1801133 (MTHFR), rs1801394 (MTRR), rs2306283 (SLCO1B1), rs4149056 (SLCO1B1), rs1142345 (TPMT), and rs1800460 (TPMT).As fixed mutations are uninformative, the polymorphisms with Minor Allele Frequencies (MAFs) of less than 1% were omitted from the analyses, as were polymorphisms with no genotyping and absent genotyping rates of 20% or more. This left 12 of the 27 polymorphisms investigated originally: rs2372536  described by Santos et al.All the individuals included in the present study had more than 95% native American ancestry. The overall mean genomic ancestry of the study population was 0.022 European, 0.014 African, and 0.964 native American . The inter-population variability of the polymorphisms analyzed in the present study was evaluated using Wright’s Fixation Index (FST). The FST values were used to run a multidimensional scaling analysis to plot the genetic differentiation of the Amerindian population with those from the five continental populations being included for comparison. The differences between the genotype frequencies of the Amerindian populations and those from the 1,000 Genomes database were evaluated using Fisher’s exact test. The False Discovery Rate (FDR) was used to correct the multiple analysesCCND1, rs1800909_GGH, rs3758149_GGH, rs1801133 _MTHFR, rs1801394_MTRR, rs2306283_SLCO1B1, rs4149056_SLCO1B1, rs1142345_TPMT and rs1800460_TPMT  from either the AFR or the EAS population, while rs23725336 (ATIC gene) was only significantly different from the AFR population, and rs4673993 (ATIC), only from the AFR and SAS populations.The allele frequencies recorded for the 12 markers investigated in the NAT population and the continental populations  are shown in Table The plot of the Multidimensional Scaling (MDS) analysis of the FST values of the pairwise comparisons of the polymorphisms is presented in Fig. An additional analysis was performed to show whether the allelic variations of the 12 markers investigated in traditional Amerindian populations would show the same genetic profile in ALL patients with a high Amerindian genetic contribution. Thus, the genotypic distribution of these markers was compared between the Amerindian populations investigated in this study (NAT) and leukemic patients (ALL_NAT) with an average of 50% of Amerindian genetic ancestry  populations and five representative populations from the 1,000 Genomes database, using Fisher’s exact test with the standard statistical correction (FDR) being used to avoid misleading correlations.ATIC), which varied significantly only between the NAT and AFR populations, while the frequency of rs4673993 (ATIC) of the NAT population was significantly different only from those of the AFR and SAS populations. The third marker, rs2236225 (MTHFD1), was significantly different in the AMR, EUR, and SAS populations.The frequencies of all the pharmacogenomic markers analyzed in the present study were significantly different in the NAT population in comparison with all (in nine cases) or most of the continental populations . The least differentiated marker was rs23725336  and African (AFR) populations were the most genetically distinct. This analysis also found that the genetic profile of the Amerindian (NAT) population is most similar to those of the American (AMR) and South Asian (SAS) populations, which is consistent with their closer links through the history of human migrationsTPMT gene and an increased susceptibility to grave toxicity during the treatment of ALL with 6-MP22.The 6-MP drug is an anti-metabolic purine analog that interferes with the biosynthesis of nucleic acids and is a key medication for the successful treatment of children with ALL. This drug is the only anti-leukemia medication used in the treatment of ALL for which the FDA (Food and Drug Administration) recommends the prior determination of the patient’s genetic profile prior to the administration of the drug, to allow for the adjustment of the treatment. A number of studies have shown an association between the rs1142345 and rs1800460 markers of the MTHFR, MTHFD1, and MTRR genes and the treatment of ALL with MTX has been the focus of a number of studies. In particular, the rs1801133 (MTHFR)24, rs2236225 (MTHFD1)26, and rs1801394 (MTRR)28 polymorphisms have all been associated with relapses and toxicity in MTX-based treatments.The MTX is a folate inhibitor that is an important component of virtually all the pediatric ALL treatment protocols. The association between the 29 analyzed a number of polymorphisms of the SLCO1B gene, including rs4149056, and found a strong association with toxicity to MTX. Other studies have also recorded an association between the rs2306283 polymorphism of the SLCO1B gene and toxicity in MTX treatment32.In a Genome-Wide Association (GWA) study, Trevino et al.ATIC gene, which is involved in the synthesis of purines35 and polymorphisms of genes, such as CCND1 (rs9344), involved in the regulation of the cell cycle and the enzymes targeted by MTX37. In addition, the rs1800909 and rs3758149 polymorphisms of the GGH gene, which catalyzes the degradation of the active polyglutamates of the natural folate and the MTX, have also been identified as predictors of toxicity in MTX39.A number of other studies have found an association between variants of other genes involved the metabolic pathways of MTX and toxicity in treatments based on this drug. These variants include the rs2372536 and rs4673993 of the 10. In this study, the G allele of the rs2306283 variant of the SLCO1B1 gene was associated with an almost three-fold increase in the risk of developing severe central nervous system toxicity during the consolidation phase of ALL treatment. In addition, a strong, but not significant, association was identified between the rs1801133 variant of MTHFR gene and the risk of developing severe toxicity in the disease consolidation phase.Our work aimed to provide information on the distribution of pharmacogenomic variants relevant to the treatment of ALL in traditional Amerindian populations. It would be interesting to demonstrate whether the results observed for the markers investigated here would show the same profile in leukemic patients of the same ethnic group. However, samples from indigenous patients with ALL are difficult to obtain, given the rarity of the disease and due to these populations living in remote rural areas that are difficult to access, which reflects a difficulty in care and clinical monitoring, coupled with the cultural factor, in which the treatment is, mostly, based on traditional indigenous medicine. To get around this issue, we used, for statistical comparison purposes, sample data from 42 patients with ALL, from the Brazilian Amazon metropolitan region, who had a high Amerindian genetic contribution. Of the 12 markers investigated, eight of them  did not show statistically significant differences between traditional Amerindian populations (NAT) and patients with ALL (ALL_NAT). This outcome may allow us to suggest a genetic similarity between the two groups. These markers were investigated for the risk of developing severe toxicity in a study previously carried out by our research group involving an admixed population of the Brazilian Amazon region40 involving miscegenated populations from the Amazon. The rs2236225 variant of MTHFD1 gene was related to a protective effect against the development of ALL, while the rs4673993 variant of ATIC gene was associated with a risk effect of developing the disease. In a meta-analysis developed by Fang et al.41, the GG genotype of the rs1801394 variant of MTRR gene was associated with a reduced risk of developing ALL in a Caucasian population.In the current study, four markers were statistically different between Amerindian populations and samples of ALL patients . The statistical difference observed for these markers could be due to their strong relationship with the susceptibility to ALL development. These polymorphisms were investigated in a study developed by our research groupThe results of the present study indicate that the genotypic distribution of the markers analysed here in the Amerindian population is distinct from that of the other populations included here for comparison, from Africa, Europe, the Americas, and southern and eastern Asia. These findings highlight the unique nature of the genetic profile of the indigenous population of the Brazilian Amazon region, which also implies a distinct profile of efficacy and toxicity in the treatment of ALL in these populations, as well as other populations in Brazil formed through a high degree of admixture with this indigenous group, such as the Brazilian Amazonian populations.Supplementary information


Aporia crataegi , a common and widespread butterfly ranging from northwestern Africa to Europe and Asia, has been extinct in Britain since the 1920s and is on a steady decline in several other parts of its range. In order to investigate genetic diversity within A. crataegi and its correspondence with current subspecies-level taxonomy, we barcoded 173 specimens from across its range including, for the first time, extinct populations from Britain and Korea. Using next generation sequencing we also obtained a sequence for Aporia joubini, a peculiar taxon from China known only by its type specimen collected in the early twentieth century. Our phylogenetic analysis placed A. joubini sister to A. oberthuri, although further taxon sampling may reveal a different scheme. Within A. crataegi, we observed a shallow and weak mitogenomic structure with only a few distinct lineages in North Africa, Sicily, Iran, and Japan. Eurasian populations, including those extinct in Britain and Korea, clustered into a large set of closely allied lineages, consistent with a recent expansion during the Late Pleistocene glacial period. This study highlights the importance of museum collections and the unique opportunities they provide in documenting species diversity and helping conservation efforts.The Black-veined White  Each species contains immense amounts of genetic information within its geographical populations, and this intra-specific genetic diversity not only is a repository of past geological, climatic, and environmental information, but also influences population persistence and evolutionary potential3. Thus, the resulting permanent loss of genetic information due to local extinctions not only affects evolutionary potential under changing environmental conditions, but also impedes a full understanding of the evolutionary history of species. Natural history collections have long been used by morphologists and taxonomists to probe the evolutionary process and describe biological diversity. These biological archives also offer great opportunities for genetic research in taxonomy, conservation, systematics, and population biology and they represent an invaluable resource for studying extinct taxa.Human activities threaten considerable numbers of species and natural populations that, in turn, significantly affect ecosystem functioning5].Next Generation Sequencing (NGS) has revolutionized nearly every field of genetics, but few have profited from it as much as ancient DNA research. NGS has increased the amount of DNA sequence data available from extinct organisms by several orders of magnitude and is extensively used in phylogenetic studies using museum specimens [e.g.Aporia crataegi, is a well-known butterfly widespread in orchards and bushy places in the Palearctic region, from north-western Africa to Japan, across Europe and Asia, although very localized and uncommon in some areas8. Its larvae feed on Rosaceae such as Prunus, Pyrus, and especially Crataegus. Despite a very simple and uniform wing pattern, numerous local subspecies have been described under A. crataegi across its range, and the status of many remain doubtful: Della Bruna et al.9 listed 25 subspecies under A. crataegi, while Savela10 recognized 23. The Black-veined White belongs to a diverse genus composed of numerous other species, most of which are confined to southwest China and the Himalaya-Hengduan mountain regions. The phylogenetic position of Aporia within Pieridae has been well established12. However, its monophyly has been recently questioned by Ding and Zhang13, who found that the monotypic genus Mesapia Gray, 1856 , proposed either as a subgenus of Aporia15 or as a distinct genus17, is nested within Aporia sensu lato . This may highlight a need to synonymize Mesapia under Aporia. Moreover, Ding and Zhang18 found that another subgenus within Aporia, subgn. Metaporia  which includes species with a bifid apex of the uncus in male genitalia sensu Della Bruna et al.19, is also paraphyletic, and therefore subdivisions of Aporia into separate subgenera cannot be supported. Two studies have so far investigated the phylogeny and evolution of the species within this genus, using either a mitochondrial COI fragment alone20 or accompanied by a second nuclear gene18, although taxon sampling in both of these studies was incomplete. Aporia crataegi was once a fairly widespread and locally plentiful butterfly in southern England and Wales. By 1872 it had disappeared from Kent, and according to Allan21, the last authentic British record as a native species was a single specimen caught in New Forest in 1880, although it is more widely accepted that the last British specimens were those from Herne Bay in Kent caught during the 1920s. The reasons behind the extinction of A. crataegi in Britain remain unknown, and attempts to reintroduce it by releasing hundreds of continental specimens in Kent and elsewhere in Britain failed to re-establish A. crataegi on a permanent basis. The populations of A. crataegi can fluctuate greatly in numbers over time, but the reasons for this are not fully understood. Major endangerment factors for their decline include habitat destruction, climatic change, parasitism, bird predation, and the use of pesticides  in orchards23. In recent years, strong declines in distribution, or population size of more than 30%, have been recorded for A. crataegi from Austria, Romania, Ukraine, Albania, France, Latvia, Norway, Serbia, Algeria, and Morocco24, and the butterfly is also reported extinct from Netherlands, Luxembourg, Czech Republic25, and Korea (since 1997:23). In this study we analysed the mitochondrial COI barcode region for 23 out of 25 subspecies of A. crataegi as recognized by Della Bruna et al.9 from the Palearctic region, including, for the first time, the extinct British populations. We also obtained a COI barcode from the only known specimen of A. joubini, collected in 1902 from China and now hosted in the Natural History Museum of London (NHMUK type). We aimed to: (i) investigate the phylogenetic position of A. joubini within the Aporia genus, (ii) assess the phylogeographic patterns within A. crataegi, (iii) investigate if the current taxonomic entities correspond with these patterns, and (iv) evaluate a continental vs. an autochthon origin of the British specimens.The Black-veined White, A. crataegi individuals representing 23 subspecies out of the 25 recognized by Della Bruna et al.9 from sites across Eurasia and North Africa (Maghreb region)  and sachalinensis . We analysed ten British individuals: four collected between 1860 and 1870, before the extinction of the native populations, and six at the beginning of the twentieth century, supposedly re-introduced from the continent. In addition, we analysed four specimens from Iranian populations of A. leucodice, and the only known (type) specimen of A. joubini, collected in 1902 from China.We examined 173 on) Fig. . We were26 with glass fiber plates (PALL Acroprep 96 with 3 µm GF membrane over 0.2 µm Bioinert membrane). DNA was eluted in 30–40 µl of ddH20 pre-warmed to 56 °C and stored at − 80 °C.A single leg was removed from each specimen and sent to the Centre for Biodiversity Genomics in Guelph, Canada for DNA extraction, amplification, and sequencing. DNA was extracted from a single leg on a Biomek FX liquid handling robot using a semi-automated DNA extraction protocolA. joubini and the British A. crataegi, the 658 bp COI barcode region was recovered using an NGS-based protocol27. In brief, for each sample, multiple short, overlapping amplicons were generated using nested, multiplex PCR. In order to associate reads with their source specimen, the amplicons were tailed with sample-specific universal molecular identifiers (UMI) before being pooled for sequencing on an Ion Torrent PGM. The short sequence reads were attributed to a sample via the UMIs, and filtered for quality and length before being assembled into a single barcode sequence.Due to DNA degradation in the very old specimens of 29. Briefly, the 658 bp barcode region was amplified using the primers LepF1 (5′ ATTCAACCAATCATAAAGATATTGG 3′) and LepR1 (5′ TAAACTTCTGGATGTCCAAAAAATCA 3′) and sequenced on an ABI 3730XL (Applied Biosystems capillary sequencer). The trace files were edited using CodonCode Aligner 6.0.2  and all resulting mtDNA sequences were aligned using the same program. All sequences were submitted to GenBank (Accession Numbers in https://doi.org/10.5883/DS-APORIA).For the remaining (younger) specimens, PCR and Sanger sequencing were carried out following standard procedures for LepidopteraA. crataegi and the origin of the British specimens, we complemented the 173 specimens sequenced specifically for this study with an additional 24 sequences of A. crataegi from public DNA barcoding projects  from 12 species of Aporia and 6 outgroups, mainly selected from Ding and Zhang18, were thus added (see A. martineti (KU921265), A. genestieri (KU921259) and Mesapia peloria (KU921272) sequences from Ding and Zhang18 due to the questionable quality of the COI sequences in GenBank. All sequences were aligned using CodonCode Aligner 6.0.2. Haplotype and nucleotide diversity were calculated using DnaSP 5.030. The mean p-distance between groups and its variance  was calculated using MEGA 1031. To represent the genealogical relationships among mtDNA haplotypes, we calculated a Median Joining (MJ) network using NETWORK 532. Aporia relationships were assessed via Maximum Likelihood (ML). The software package ModelFinder33 in IQ-TREE 1.6.1134 was used to select the best fitting model of evolution by Bayesian information criterion scores (BIC). The ML analysis was carried out with RaxML 7.0.335, on the T-REX (Tree and reticulogram REConstruction) web server , with the rapid hill-climbing algorithm and 1,000 non-parametric bootstrap inferences. The highest bootstrap values were obtained setting the model of evolution to GTRCAT, searching for the best-scoring ML tree in a single run. The best ML tree was visualized and edited with FigTree version 1.437.To assess the phylogeographic patterns within ects see . The phydded see . We exclA. crataegi, different sets of mtDNA sequences were selected  and R2 (P < 0.05) respectively, and to test their statistical significance by simulating random samples  under the null hypothesis of selective neutrality and constant population size using coalescent algorithms (both modified from Hudson44). Expected mismatched distributions and parameters of sudden expansion τ = 2 μ t  were calculated using Arlequin 3.5 by a generalized least-squares approach45, under models of pure demographic expansion and spatial expansion47. The probability of the data under the given model was assessed by the goodness-of-fit test implemented in Arlequin 3.5. Parameter confidence limits were calculated in Arlequin 3.5 through a parametric bootstrap .To test demographic equilibrium or events of recent expansion in ed Table  considerWe declare that all samples analysed in this study were collected complying with institutional, national, and international guidelines.A. joubini and sequences of various lengths . Further confirmation of their validity was provided by the fact that they grouped with sequences from closely allied taxa. The missing data in NGS sequences . Sanger sequencing produced full-length DNA barcodes (658 bp) for all A. crataegi and one of the four Iranian A. leucodice samples, and sequences of various lengths were obtained for the remaining three samples of the Iranian A. leucodice  and the close relatedness to a clade (BS = 97) consisting of Aporia + Mesapia . Our findings do not corroborate with the morphological groups proposed by Della Bruna et al.19 based on shape of the uncus in male genitalia. For example, A. oberthuri and A. goutellei are closely related in our tree . Our analysis further highlighted that A. goutellei (BS = 92) is the sister taxon to a clade consisting of A. joubini and A. oberthuri (BS = 92). Furthermore, the Iranian populations of A. leucodice  appeared distinct, with an average COI barcode distance of 2.67% (± 0.64), from Kazakhstan and Kirghizstan populations , forming a highly supported clade (BS = 100).The ML tree confirmed the monophyly of A. crataegi  while the Sicilian populations had three haplotypes. The remaining Eurasian sequences, whose phylogenetic relationship were unresolved with ML analysis, were linked with Sicilian populations by three peculiar haplotypes from Iran  and China (H38), and the analysis highlighted two star-like configurations  widely distributed from Iberian Peninsula to South Korea, while the Mediterranean haplogroup , demographic expansion of the Eurasian and Mediterranean haplogroup could be traced back to about 67 thousand years ago (kya) (49–99 kya) and 116 kya (57–191 kya) respectively.The Fs and R2 statistics, calculated for the Eurasian haplogroup N = 114) and the Mediterranean haplogroup (N = 35) sequence sets of 14 and th18 on the systematic relationships within the genus Aporia  is not supported, since both Aporia (Aporia) and Aporia (Metaporia) (sensu19) are found to be paraphyletic, with Mesapia nested within Aporia sensu lato. The diagnostic morphological characters for these taxa include smaller wingspan, more rounded wings, and hairy genitalia for Mesapia49, and minor differences in wing pattern elements for Metaporia9, none of which, in our opinion, merit a separate subgeneric (sensu15) or generic (sensu17) status for these taxa. Metaporia has already been synonymized with Aporia9, and our results highlight a need to also synonymize Mesapia under Aporia (syn. nov). Within A. leucodice, the smaller, darker Iranian populations  appeared considerably distinct from the larger, lighter Kazakhstan and Kirghizstan populations . The average COI barcode distance between these two clusters (2.67 ± 0.64%) falls well within the average distance between most Aporia species. Despite this, we refrain from elevating illumina as a separate species until supporting ecological or morphological evidence become available. As for A. joubini, based on similarities in wing pattern, Della Bruna et al.9 suspected that this species may represent an aberrant form of A. harrietae paracraea, a closely related taxon that flies in the type locality of A. joubini. We agree with this assessment. If barcode sequences of A. hariettae become available and prove to be very close or identical to A. joubini, the latter should be downgraded to a junior synonym of A. hariettae.The results of our study based on mitochondrial DNA barcode data alone provide strong support for previous findings based on combined dataA. crataegi, from 23 to 25 subspecies have been described based on fragmented distribution and few morphological characters10, but our mtDNA analyses reveal a total of six distinct lineages  recognized by Della Bruna et al.9, confirming a pervasive phylogeographic pattern in European phylogeography51. The trace of demographic expansion model indeed dates a rapid expansion of the Mediterranean haplogroup to about 116 kya during the Late Pleistocene. The sea-level oscillations during this period, which created land bridges between the three main peninsulas52 and permitted faunal exchange, can explain the fragmented distribution of this haplogroup . Afterwards, in the post glacial period, gene flow among these populations became interrupted, and they experienced a second expansion towards the continent. It is worth noting that although one mutation separates the two main haplogroups, the present postglacial distribution of the Mediterranean haplogroup in A. crataegi . The grasshopper paradigm is expected for species showing difficulties in crossing the mountain barriers represented by the Alps and Pyrenees55. Indeed, in A. crataegi, the populations of the Mediterranean haplogroup from Italy and Iberia remained trapped by the Alps and Pyrenees. Conversely, the Greek populations did not expand to Central Europe despite the absence of conspicuous mountain chains that would otherwise impede such colonization. Although the validity of using mtDNA as a marker in molecular ecology has been questioned in the last decade57, a recent study has provided evidence that mtDNA spatial differentiation is correlated with species traits known to affect the dispersal and colonization capabilities of butterflies51. Nevertheless, considering that the mtDNA variation observed in this study is not representative of the whole genomic variation, we cannot exclude a recent expansion of the Greek populations in Central Europe. Nuclear genetic analyses are therefore needed to better investigate the genetic variability, particularly in the contact zones between the main haplogroups. Furthermore, additional sampling might reveal a different genetic pattern in A. crataegi.Within A. crataegi with identical mtDNA haplotypes will require a more in-depth analyses of morphological differences and examination of type materials.The extinct British and Korean populations appear to be genetically most closely related to the other specimens from Eurasia (Supplementary File 9) share an identical haplotype . As stated above, further sampling and nuclear genetic analyses particularly from Iran, Israel, Syria, Jordan, and Iraq will likely reveal additional haplotypes. Finally, our data supports the genetic peculiarity and evolutionary value of the populations from Japan and north-western Africa, previously recognized as two well-differentiated subspecies . Although our phylogenetic analysis doesn’t fully resolve the relationships between the North African and Sicilian populations (ssp. mauritanica and ssp. augusta respectively), the large differentiation between these populations of A. crataegi suggests a prolonged period of lack of genetic exchange between them, likely as a result of an early split in the range of the ancestral stock. Despite the small geographical distance between North Africa and Sicily, eight mutations divide these two subspecies  restored the barrier. This short period of connection between the two continents has been suggested as a plausible explanation for vicariance between the North African, Iberian, Sicilian and Italian lineages of many organisms, including butterflies . However, considering Brower’s48 proposed mutation rates for mtDNA in Lepidoptera (µ = 0.01 substitutions/site/lineage/Ma), demographic expansion of major Aporia crataegi haplogroups appear to have a much more recent (Late Pleistocene) origin and are possibly influenced by glaciations or other deterministic and stochastic events, as previously noted in other Lepidoptera .Our samples from five Sicilian populations showed three unique haplotypes, highlighting their significance for biodiversity in Sicily. In Iran, 15 samples from 12 localities encompassing four subspecies (sensuA. joubini and British populations of A. crataegi. These repositories allow us to fill the gap in genetic information and reconstruct the evolutionary history of species. For now, NGS-based analysis of COI barcodes has made efficient genomic studies of museum specimens possible, allowing the first look at the genetic traits of extinct species. Rapid advances in modern DNA technology will eventually allow complete reconstruction of genomes, uncovering the lost evolutionary history of these extinct populations and ushering us into a new age of Biological and Conservation Sciences.Natural history collections represent an invaluable source of information for species whose ranges are characterized by geomorphological or geopolitical impediments, but principally for storing specimens of extinct taxa when fresh biological material is no longer available, as the case of Supplementary InformationSupplementary Data


Arachnothera longirostra, Irena puella, Brachypodius atriceps, Niltava grandis, and Stachyris nigriceps. We accomplished relatively thorough sampling and data collection by sequencing ultraconserved elements (UCEs) using DNA extracted from modern and older  specimens. We obtained a genome‐wide set of 753–4,501 variable loci and 3,919–18,472 single nucleotide polymorphisms. The formation of major within‐species lineages occurred within a similar span of time (0.5–1.5 mya). Major patterns in population genetic structure are largely consistent with the dispersal potential and habitat requirements of the study species. A population break across the Isthmus of Kra was shared only by the two hill/submontane insectivores (N. grandis and S. nigriceps). Across Sundaland, there is little structure in B. atriceps, which is a eurytopic and partially frugivorous species that often utilizes forest edges. Two other eurytopic species, A. longirostra and I. puella, possess highly divergent populations in peripheral Sunda Islands  and India. These species probably possess intermediate dispersal abilities that allowed them to colonize new areas, and then remained largely isolated subsequently. We also observed an east–west break in Indochina that was shared by B. atriceps and S. nigriceps, species with very different habitat requirements and dispersal potential. By analyzing high‐throughput DNA data, our study provides an unprecedented comparative perspective on the process of avian population divergence across Southeast Asia, a process that is determined by geography, species characteristics, and the stochastic nature of dispersal and vicariance events.Indochina and Sundaland are biologically diverse, interconnected regions of Southeast Asia with complex geographic histories. Few studies have examined phylogeography of bird species that span the two regions because of inadequate population sampling. To determine how geographic barriers/events and disparate dispersal potential have influenced the population structure, gene flow, and demographics of species that occupy the entire area, we studied five largely codistributed rainforest bird species:  Phylogeography of taxa occupying Southeast Asia is poorly known despite its importance as a storehouse of tropical biological diversity. We use a combination of sequence capture, high‐throughput sequencing, and historical samples to conduct a region‐wide, multispecies comparative study that unveils phylogeographic patterns with unprecedented genetic resolution. This baIn Indochina, avian population research has been concentrated mainly on the eastern extension of the Himalayans and the southwestern Chinese mountain systems  comparisons , Asian fairy‐bluebird Irena puella (Irenidae), black‐headed bulbul Brachypodius atriceps (Pycnonotidae), large niltava Niltava grandis (Muscicapidae), and gray‐throated babbler Stachyris nigriceps . These species were selected because they (a) are widespread and largely codistributed in continental Southeast Asia, and are usually considered single species, as opposed to groups comprising allospecies ; (b) are common and thus well represented in collections, a necessity for historical sampling; and (c) represent distinct ecological types and thus vary in dispersal potential and potentially genetic differentiation across space. Arachnothera longirostra, I. puella, and B. atriceps are eurytopic nectarivorous/insectivorous or frugivorous/insectivorous species that range widely among habitats and in elevation  and nine outgroup taxa  to be used for downstream analyses. These failures were caused by poor template quality, failed library preparation, or unsuccessful target enrichment. Our final dataset contained high‐quality data for the 28 A. longirostra, 41 I. puella, 25 N. grandis, 30 P. atriceps, and 31 S. nigriceps  build a pseudoreference genome for each species using contigs from a subset of individuals  using Phyluce version 1 and Geneious version 7.0.6 , concatenating all the SNPs using PGDSpider version 2.1  in R  from each UCE locus using dplyr (K‐means method (find.cluster function in adegenet), locations of individuals on PCA plots, and geographic proximity among samples. Prior to running DAPC, we first performed stratified cross‐validation (n = 100 repetitions) to determine an optimal number of principal components to use for each analysis, which minimized the risk of model overfitting. Using the R package hierfstat version 0.04.22 , followed by discriminant analysis of principal components  from 1 to 8. For each K value, we conducted 10 independent runs, setting burn‐in and number of MCMC steps to 100,000 each.To simultaneously identify genetic cluster membership and genetic admixture of individuals, we analyzed the independent‐SNPs data with the MCMC‐based program Structure version 2.3.4  and focused on interpreting aspects of its outputs that are corroborated by other analyses and the geographic locations of individuals, while keeping in mind the limitations of Structure analyses . We used the resulting topologies to guide population lumping in BFD* analyses and tree building for G‐PhoCS analyses (see below). We ran each SNAPP analysis for at least one million generations, sampling every 1,000 generations. The first 10% of the MCMC chains were discarded as burn‐in, and log‐normal distributions were used for lambda and rate priors.We ran SNAPP species tree analysis in BEAST version 2.3.3 to infer branching patterns of populations in each species using the independent‐SNPs datasets and populations delineated in DAPC analyses . After inspection of histograms and distribution plots of summary statistics, we filtered UCE loci based on the following removal criteria to minimize the chance of including alignments that were made up of low‐quality or nonhomologous reads: (a) alignments that were less than 200 bp in length and (b) alignments that had a high number of polymorphic sites per bp . With the filtered alignment data, we conducted another round of mstatspop analyses to calculate population genetics summary statistics and generated input data for G‐PhoCS.To jointly estimate the demographic parameters related to the divergence history of populations in each species , we generated species‐specific haplotype data for each UCE locus and analyzed each set of alignments with the coalescent‐based tool G‐PhoCS version 1.2.3  and scale (β) parameters that define gamma prior distributions for each of the demographic parameters were as follows: α = 1 and β = 5,000 for both θ and τ, and α = 1 and β = 0.01 for migration rates. For each species, we conducted some initial MCMC runs with auto‐fine‐tuning to evaluate run speed, convergence, and mixing. To produce the final results for each species, we combined data from 4 to 6 MCMC runs, each up to 100,000 iterations long. We used Tracer version 1.6 to evaluate marginal posterior distributions and trace plots of parameters and likelihood values  topology was derived from the results of SNAPP analyses. We used population divergence models in which bidirectional gene flow between pairs of modern, geographically adjacent populations was allowed (migration model) and diffuse gamma priors were set for all demographic parameters. The shape  than our G‐PhoCS datasets but contained fewer loci (515 UCE loci). We calculated pairwise divergence time distances between branch tips in the Moyle et al. ; divergence time τ  between populations; and per‐generation migration rates between current populations MST/μ, in which MST is the proportion of individuals in the receiving population T that immigrated from the source population S  rather than in substitution‐rate‐scaled units, we estimated an approximate substitution rate for the UCE loci. To do this, we used the time‐calibrated phylogenetic tree of oscine songbirds by Moyle et al. . This tre et al.  tree usie et al. . We alsoe et al. . This es3SD = 4.86 million) quality‐trimmed and filtered reads per individual in our final dataset (N = 162). After SNP and genotype filtering, the total number of SNPs per species ranged from 3,919 to 18,472, and the number of variable UCE loci ranged from 753 to 4,051  to 53.6% (A. longirostra) of the total variance  population genetic patterns uncovered by the above analyses Figures . For A. FST is highest in S. nigriceps (0.338) and lowest in B. atriceps (0.061) , indicating relatively simultaneous divergence among populations.Overall, riceps 0.38 and lo3.3eBF) of the best model differs by at least 40 from other models, indicating “very strong” support . Comparison of relative branch lengths across the entire tree produced an inferred relative substitution rate of 1.94 × 10−10 substitutions/year (SD = 3.14 × 10−5) for our UCE dataset  for modern  populations tended to have higher ESS values compared to estimates of other parameters , followed by almost simultaneous divergence of the remaining three populations around 0.5–0.6 mya . The rate of gene flow is highest from the central Indochina/Malay Peninsula population  into India and then the Greater Sunda Islands. In N. grandis, the northern Indochinese population diverged first (c. 1 mya), followed by the two southern populations , some that were consistent with habitat requirements of the species . Sequencing of samples from areas that are previously unstudied also yields novel insights . We combined coalescent analyses and large amounts of data to produce highly resolved estimates of population demography and divergence parameters. These estimates support earlier findings that are largely based on mtDNA data.We conducted sequence capture and high‐throughput sequencing of historical and modern DNA samples from populations of five codistributed species of Southeast Asian rainforest birds: 4.1D and Fu and Li's D are negative in all populations for which we had large samples , or the region just north of it, forms the interface between Indochinese and Sundaic biogeographic regions  has intrigued biogeographers for generations Wallace, . The traPycnonotus and Brachypodius bulbuls that span the Isthmus of Kra. They found, within each species, that the transition between northern and southern lineages generally occurs well into northern Thailand (>18°N), not at the Isthmus of Kra. In our study, only the two hill and montane species—N. grandis and S. nigriceps—have populations that are split at the interface between Indochina and Sundaland  and central Thailand (16.8°N). The southern N. grandis lineage consists of individuals from Sundaland and southeastern Thailand. Range maps indicate that this southeastern Thailand population  is disjunct from other populations  or the Salween River, which runs along the western side of the Tenasserim Range into the Andaman Sea. In B. atriceps, the two northernmost individuals in the western Indochina group were collected in eastern Bangladesh and, therefore, the location of the split between the eastern and western groups is not as clear as in S. nigriceps. We suggest it may lie in the Tenasserim Range or the dry Irrawaddy Plains of central Myanmar.Two of the target species, a Figure . In S. nS. nigriceps in Indochina was identified in the past based on species or subspecies distributions of other taxa  meet in secondary contact in this transition zone, after A. pallidus underwent putative ring speciation around the drier lowland basin of east‐central Thailand. Manawatthana et al. , seasonal rainfall differences as well as southern stretches of the Tenasserim Range may contribute to geographic and ecological barriers. Southwestern Indochina receives much more rainfall than the southeast during the wettest months, when the southwest monsoons are active due to the orographic effects of the Tenasserim Range Figure . Given t4.2.3The Greater Sunda Islands and the mainland experienced repeated connection and disconnection during the Pleistocene because of eustatic sea‐level changes associated with periodic global glaciation events  show more pronounced population structure in Sundaland, with peripheral Sunda islands  containing populations that diverged the earliest  might have encouraged divergence of island populations through a combination of an ability to colonize islands while remaining relatively isolated  and I. viridescens (western Indochina), the deepest estimated population divergence times are 0.9 and 1.7 mya, respectively  drove the breakups in both species.The timing and topology of population divergence based on our UCE data are generally corroborated by previous molecular genetics studies of the same species, when such data exist. Using 10 nuclear loci and two mtDNA genes, Lim and Sheldon  estimatee Figure a. EstimaI. puella population  diverged from other populations c. 2 mya (vs. c. 1.5 mya obtained in our study). Although Palawan is part of the Sunda Shelf, its connection with the rest of the Sunda islands is tenuous due to the deep sea channel (140 m) that permanently separates it from Borneo, even during periods of extremely low sea level . Therefore, despite the long‐term separation of Palawan from the rest of Sundaland, some dispersive species appear to have moved between it and Borneo in the intervening years.Using mitochondrial data, Moltesen, Irestedt, Fjeldsa, Ericson, and Jonsson  estimateya Hall,  but likeya Hall, , which wya Hall,  reviewedN. grandis (north vs. south) diverged from one another c. 1 mya. There are no comparable data for this species, but judging from phylogeographic studies of other SE Asian avian taxa with similar distributions, this level of divergence is typical. In the bulbul species complex comprising Alophoixus ochraceus/pallidus, for example, the populations on the Malay Peninsula/Borneo are separated from the populations in Indochina by c. 1.1 mya , despite a low relative measure of population differentiation (FST = 0.061). This disparity may be caused by this species' unusually large Ne, which would have slowed the rate of genetic drift. Using mtDNA data, Dejtaradol et al. (B. atriceps populations was first noted by Chua et al. (hodiernus, Figure S. nigriceps lineages suggests the presence of expansive suitable habitats c. 1.3 mya ago, followed by rapid vicariance events. As in A. longirostra, these closely timed events may be related to large‐scale climatic changes. Although our estimates of divergence times largely agree with previous available studies, the comparability of absolute‐timing estimates from different studies depends on factors such as sample size, actual samples and genetic markers used, and assumptions related to substitution rates of the markers and generation times of the study species (e.g., Winker, Glenn, & Faircloth, The east–west divide of l et al. d estimata et al.  using mt is deep .4 mya, d4.4Because of poor sampling in Southeast Asia, species‐level studies usually present incomplete pictures of population structure and history across the region. To ameliorate this problem, researchers have turned to comparing mtDNA from historical museum specimens, but mtDNA comparisons can yield incorrect measures of genealogical relationships and they generally provide limited population genetic information (Funk & Omland, None declared.H.C.L. conceived and designed the project and conducted molecular laboratory work; H.C.L., S.B.S., and M.G.H. analyzed the data; H.C.L., F.H.S., S.B.S., and M.G.H wrote the manuscript with input from all other authors; F.H.S and R.G.M. provided modern tissue samples; and M.J.B. and R.C.F. contributed laboratory protocols and reagents. Click here for additional data file.