Cattleya liliputana (Orchidaceae). Nuclear microsatellite markers were used for genetic analyses. Spatial Bayesian clustering and population-based analyses revealed significant genetic structuring and high genetic diversity (He = 0.733 ± 0.03). Strong differentiation was found between populations over short spatial scales , reflecting the landscape discontinuity and isolation. Monmonier´s maximum difference algorithm, Bayesian analysis on STRUCTURE and principal component analysis identified one major genetic discontinuity between populations. Divergent genetic groups showed phenotypic divergence in flower traits and reproductive strategies. Increased sexual reproductive effort was associated with rock outcrop type and may be a response to adverse conditions for growth and vegetative reproduction. Here we discuss the effect of restricted gene flow, local adaptation and phenotypic plasticity as drivers of population differentiation in Neotropical montane rock outcrops.Knowledge of the role of Neotropical montane landscapes in shaping genetic connectivity and local adaptation is essential for understanding the evolutionary processes that have shaped the extraordinary species diversity in these regions. In the present study, we examined the landscape genetics, estimated genetic diversity, and explored genetic relationships with morphological variability and reproductive strategies in seven natural populations of  Tropical mountains play an important role in promoting regional and global biodiversity . MontaneTropical mountains are important models to test species radiation and the effects of landscape properties on genetic structure of natural populations –21. Trop2 in Minas Gerais state, southeastern Brazil (The Espinhaço Range Region (ERR) is an orographic formation that runs north-south over 1,000 km in the eastern tropical region of South America where there are high numbers of rock outcrop formations. Espinhaço Mountains are at the edge of important biomes, such as the Atlantic Rain Forest, Cerrado, and Caatinga. The Iron Quadrangle (IQ) makes up the southern end of the ERR and covers an area of approximately 7,200 kmn Brazil . The IQ The isolation of rock outcrop species is expected to constrain gene flow, enhancing the effects of genetic drift, selection, and population divergence ,38. DiveCattleya liliputana (Pabst) van den Berg, a rupicolous orchid restricted to high-altitude rock outcrops in the IQ. The objectives were: (i) to test how landscape factors affect genetic structure and the degree of isolation among disjointed populations; (ii) to test whether genetic structure is associated with divergence in floral and vegetative morphological traits and reproductive investment; and, (iii) to test whether genetic, morphological and reproductive differentiation is associated with climatic and edaphic factors (iron or quartzite outcrops). The results showed that genetic divergence is associated with landscape and edaphic factors. The genetically differentiated populations exhibited morphological and reproductive divergence. These genetic and ecological divergences are likely to influence the long-term success of conservation projects and may aid our understanding of the major evolutionary processes in Cattleya radiation in Neotropical montane habitats.In the present study, we examined the landscape genetics, morphological variation, and reproductive investment of The collection of the samples in the private conservation units RPPN Santuário do Caraça and RPPN Capanema were realized with authorization of local administrators . The collection of samples out of conservation units were realized with the legal authorization of the Instituto Brasileiro do Meio Ambiente e dos Recursos Naturais Renováveis IBAMA (Sisbio #23771).Cattleya liliputana (Pabst) van den Berg [den Berg ,42 is a den Berg ,44. IndiC. liliputana studied are found in iron and quartzite rock outcrops from 1483 to 2055 m a.s.l. Five populations  are found around the Rio das Velhas river valley having a U-shaped distribution. This region is characterised by large iron ore deposits and intensive mining activities. Populations grow predominantly on iron outcrops and are rarely found on small quartzite outcrops embedded in iron deposits. Two other populations (CRP and PSL) are located in a peripheral mountain named Serra do Caraça  . The popo Caraça , Table 1Cattleya coccinea [Cattleya liliputana , 1 × IB Phoneutria buffer with 1.5 mM MgClSchuelke , (S1 TabSchuelke  For micro) and expected (He) heterozygosities, the number of alleles, and deviations from Hardy–Weinberg equilibrium were estimated for each locus and each population using the software Arlequin, version 3.1 [R) with rarefaction and FIS estimates were performed in FSTAT 2.9.3 [Observed . Three AMOVAs were performed. One considered only two hierarchical levels and analysed the partition of total genetic diversity between and within populations. Two AMOVAs tested for barriers to gene flow. One AMOVA tested differentiation between two groups according to software STRUCTURE 2.3.4  and prinet al. [et al. [Bayesian analysis of population structure was performed using STRUCTURE , and modet al.  and the  [et al. . The occ [et al. .adegenet package [The number of populations, and the occurrence of genetic discontinuities among them, were also inferred by a spatial explicit Bayesian model based on simulations of microsatellite data and geographic information carried out in Geneland ,56. MCMC package  for R 2. package .Flowering pseudobulbs were collected in the field and preserved in 70% ethanol. Flowers were dissected under a stereo microscope, mounted on plastic cover slips with a reference scale, and scanned at 600 dpi. Dissected pseudobulbs were measured with a digital calliper. Digitalized images of flower parts were measured with software ImageTool 3.0. Thirty-two continuous characters, 24 floral and eight vegetative , were meCattleya liliputana population was estimated in the field through establishment of 12, 5 × 2-m plots along a transect placed at the centre of studied populations, and six 5 × 4-m plots randomly distributed throughout the population area, totalling an area of 240 m2 per population. The number of pseudobulbs and the number of inflorescence of each individual inside the plots were counted during the 2012 flowering season. The number of flowers per inflorescence was determined on randomly collected pseudobulbs used in the morphometric analysis. The effects of size and genetic clusters identified by STRUCTURE on inflorescence production were tested using a General Linear Model (GLM) on R software [The reproductive investment of each software .He and AR) variability was carried out using Statistica 6.1 [To test isolation by distance, a Mantel test was performed to determine the correlation between matrices of genetic and geographic distances. In order to verify association between genetic and morphological divergence and between morphological divergence and geographic distances, correlations between distance matrices were estimated. The analyses were performed with 10,000 randomizations in PASSaGE . A Speartica 6.1 . D2m wasTo test whether climatic differences may account for population divergence, we compared WorldClim data of major IQ mountain ranges. Random points were created on the study areas above 1,300 m a.s.l. using ArcGis 10.0. The minimum distance between points was set to 500 m, totalling 438 points. Points were separated according to the geographic region: west region (CAL and MOE), south region (OBR), east region (CAP and GAN) and Caraça region (CRP and PSL). Six poorly correlated climatic variables and altitude were extracted from WorldClim data: altitude; annual mean precipitation; annual mean temperature; mean diurnal temperature range; minimum temperature of the coldest month; predicted evapotranspiration; and vegetation index in July, the dry season. Climatic structure of areas was analysed using PCA on Statistica 6.1 .FIS ranging from 0.250 to 0.350, part of which may be due to the presence of null alleles.All loci were polymorphic with the number of alleles varying from 15 to 39 per locus . MICRO-CFST = 0.138, p < 0.001; r = 0.371, p = 0.071).Analysis of molecular variance (AMOVA) indicated significant genetic differentiation among populations  from the remaining populations occurring around the Rio das Velhas valley (core IQ populations) . Bayesiap < 0.001, The PCA performed on population allelic frequencies confirmed that Caraça populations constitute a group strongly differentiated . The neiThe first four axes in the canonical variance analysis (CVA) were statistically significant. The scatterplot of individual scores revealed the separation of the core IQ and Serra do Caraça populations in the first axis, which accumulated 56.2% of total variance . There wr = 0.422, p = 0.053). D2m  ranged from 14.73 (OBR) to 37.92 (GAN). Population GAN had the highest morphological diversity, consistent with genetic results . Morphological distance was not correlated with geographical distance between the populations .The paired group dendrogram showing Mahalanobis’ generalized distance of population centroids, revealed a topology of morphological clustering in accordance with genetic findings Figs.  and S3.  results . Geneticp < 0.01). However, column length (CL) was found to be shorter in the Serra do Caraça plants (p < 0.01).Density plots of column and lip morphometric characters revealed a phenotypic shift between genetic groups. Plants from the Serra do Caraça group produce flowers with wider and taller chambers than do plants from the core IQ group . Plants p < 0.001, p < 0.001, F = 5.068, p < 0.001)  analysis indicated a significant positive correlation between individual size (number of pseudobulbs) and production of inflorescences . The mea< 0.001) . Taken tCattleya liliputana-populated area, revealed that there is climatic heterogeneity between IQ regions , and moderate differentiation (FCT = 0.076) between the three groups, Serra do Caraça, the west and east IQ. Populations CAP and GAN, in the transition zone between Serra do Caraça and core IQ genetic clusters, showed the highest diversity and admixture, suggesting that gene flow may occur through these locations in a stepwise manner before the western mountains are reached.The most significant pattern revealed by the use of microsatellite markers was the deep population differentiation between the Serra do Caraça and core IQ groups. A combination of genetic analyses revealed a similar population structure. Bayesian modelling of microsatellite data using STRUCTURE, Monmonier´s maximum difference algorithm, PCA of population allelic frequencies, and neighbour-joining tree based on pairwise genetic differentiation, identified the presence of one major barrier separating populations of quartzite outcrops of Serra do Caraça from the core IQ populations predominantly at iron outcrops. A less remarkable barrier separating the west and east populations of the core IQ was detected by a neighbour-joining tree, suggesting that the Rio das Velhas valley can constitute a partial barrier to gene flow. AMOVA corroborated these analyses, showing a high differentiation between the Serra do Caraça and the core IQ populations (FC. liliputana can be considered high (FST = 0.138) in comparison with other orchid species on Neotropical mountains. Studies over a larger spatial scale using Cattleya species resulted in similar [C. liliputana is also considerably higher than that found for Laelia and Epidendrum [FST values found for the myophilous Bulbophyllum and Acianthera species on the northern Espinhaço mountains [Nuclear genetic differentiation of orchids tends to be low when compared with other plant taxa . The gen similar ,70 and l similar  fixationidendrum ,72,73 anountains ,75.C. liliputana may be due to low pollinator movement. C. liliputana is one of the smallest species in the Cattleya genus, restricting the pollinator size to get access to the flower chamber formed by the bending of the lip towards the column. C. liliputana flowers are visited by small solitary bees [Cattleya series Parviflorae species [Limited gene flow across the top of mountain showed by ary bees . Small bary bees . Moreove species  suggestsC. liliputana flower and vegetative traits revealed a similar grouping pattern to that found using genetic markers, with a remarkable separation of Serra do Caraça plants from the remaining populations  [We investigated some putative environmental factors that may elicit divergent selective pressures in the IQ landscape . IQ highartzite) , suggestC. liliputana found here is likely to influence the long-term success of managing efforts, as the genetic differentiation and local adaptation might aid or hinder the survival and reproduction of managed plants. Taking into account the genetic, morphological, and reproductive divergence of C. liliputana, we recommend that Serra do Caraça and core IQ populations should be managed separately as different evolutionary significant units. Conservation of C. liliputana would also benefit from the rescue of populations in areas directly affected by mining and oriented reintroduction in accordance with genetic background in order to minimize population impact of habitat degradation in the IQ.One environment particularly threatened by climate change is the Neotropical mountain area ,11,108. S1 FigC. liliputana individual growing on an iron outcrop. (d) Representative C. liliputana individual growing on a quartzite outcrop.(a) Iron outcrop and (b) quartzite outcrop at high-altitude areas of the Iron Quadrangle. (c) Representative (TIF)Click here for additional data file.S2 Fig(TIF)Click here for additional data file.S3 Fig(TIF)Click here for additional data file.S1 Table(DOCX)Click here for additional data file.S2 Table(DOCX)Click here for additional data file.


Microhyla fissipes. We examined three predictions based on ecological processes: (1) the correlation between temperature and call properties across M. fissipes populations; (2) the correlation between call properties and body size across M. fissipes populations; and (3) reproductive character displacement (RCD) in call properties between M. fissipes populations that are sympatric with and allopatric to a congener M. heymonsi. To test genetic drift, we examined correlations among call divergence, geographic distance, and genetic distance across M. fissipes populations. We recorded the advertisement calls from 11 populations of M. fissipes in Taiwan, five of which are sympatrically distributed with M. heymonsi. We found geographic variation in both temporal and spectral properties of the advertisement calls of M. fissipes. However, the call properties were not correlated with local temperature or the callers' body size. Furthermore, we did not detect RCD. By contrast, call divergence, geographic distance, and genetic distance between M. fissipes populations were all positively correlated. The comparisons between phenotypic Qst (Pst) and Fst values did not show significant differences, suggesting a role of drift. We concluded that genetic drift, rather than ecological processes, is the more likely driver for the geographic variation in the advertisement calls of M. fissipes.Acoustic signals for mating are important traits that could drive population differentiation and speciation. Ecology may play a role in acoustic divergence through direct selection , constraint of correlated traits , and/or interspecific competition . However, genetic drift alone can also drive acoustic divergence. It is not always easy to differentiate the role of ecology versus drift in acoustic divergence. In this study, we tested the role of ecology and drift in shaping geographic variation in the advertisement calls of  Acoustic signals are critical to species recognition and mate competition (Claridge and de Vrijer Hyla cinerea) becomes higher when sympatrically distributed with the closely related barking tree frogs (H. gratiosa)  and/or random (drift) processes. Selection can act upon call properties directly or indirectly through correlated traits. Many ecological factors are known to influence call transmission , and therefore, local adaptation can directly drive call divergence  the correlations between long‐term average temperature and call properties across M. fissipes populations; (2) the correlations between call properties and body size across M. fissipes populations; and (3) RCD between M. fissipes populations that are sympatric with and allopatric to M. heymonsi. To test the role of drift, we examined the correlations between geographic distance, genetic distance, and call divergence across M. fissipes populations.We first examined geographic variation in the advertisement calls and body size  of M. fissipes samples were collected from 11 geographic populations  using the localities' geographic coordinates (Appendix S1).A total of 146 Advertisement calls were recorded at a rate of 44.1 kHz, 16‐bit resolution using a digital recorder  with a shotgun microphone (Sony ECM‐CG50), which was placed as close to the caller as possible. We recorded at least 20 consecutive calls from each individual and used Raven pro v1.4  to characterize the acoustic traits.Microhyla fissipes typically produce a series of calls consecutively, with each call composed of numerous pulses (Appendix S2). For the temporal properties, we measured call duration, call interval, call rate, call rise time, and call fall time (Appendixes S2 and S3). We also counted the number of pulses inside a call as the pulse number. For the spectral properties, we measured the largest peak on the power spectrum  as the dominant frequency, the frequencies at the 25% and 75% of the power spectrum as the 1st and 3rd quartile frequencies, and the difference in frequency between the 1st and 3rd quartiles as the IQR bandwidth of frequencies (Appendixes S2 and S3). Individual call parameters were obtained by averaging the 20 calls from the same caller.™ Gel/PCR DNA Fragments Extraction Kit . The COI sequence was amplified using primer LCO020 (5′ TTT CAA CCA ACC ACA AAG ACA TGG G 3′) and HCO710 (5′ TAT ACT TCA GGG TGG CCA AAR AAT CA 3′) via polymerase chain reactions (PCR). We performed double‐stranded PCR in 20 μl volume with the following steps: 1 cycle denaturation at 94°C for 3 min, followed by 35 cycles at 94°C for 30 s, annealing at 50°C for 40 s, and 72°C for 60 s, with a final elongation at 72°C for 10 min in an iCycler Thermal Cycler . The PCR products were run on 1.2% agarose gels in 1×TBE buffer to confirm that the lengths of the particular fragments were correctly amplified. Automated PCR products were carried out with the same primers in both directions on ABI 3730 by Genomics BioSci & Tech Corp. .DNA was extracted with the EasyPureFst) among the populations using DnaSP v5.1  and aligned by ClustalX =MiL0LibSMA, where Mi and Li are the body mass and the linear body measurement of individual i, respectively; bSMA is the scaling exponent estimated by the SMA regression of M on L; L0 is an arbitrary value of L ; and M^l is the predicted body mass for individual i when the linear body measure is standardized to L0  reflects the temporal properties, whereas the second (PC2) reflects the spectral properties  as the fixed effect, ambient temperatures and SMI scores as two covariates, and sample locality nested in the type of populations as a random effect. To test genetic drift, we extracted the residuals from the linear regressions of the PCs against ambient temperatures and SMI scores to obtain the standardized call properties . We then used the residual PCs to calculate the dissimilarity matrices of the pairwise differences in the call properties among M. fissipes populations. We also calculated the shortest pairwise geographic distances between the sample localities using their geographic coordinates. Finally, we conducted Mantel tests with 1000 permutations to test correlations between acoustic differences, geographic distances, and genetic distances. We applied phenotypic Qst(Pst) − Fst comparison (Spitze Pst of acoustic traits (PC1 and PC2) equals genetic Fst, the pattern of acoustic variation is likely explained by genetic drift. If Pst is greater than Fst, directional selection or disruptive selection might contribute to the acoustic variation. When Pst is smaller than Fst, the pattern suggests the effect of uniform selection or stabilizing selection . Matrix permutation test using the Mantel–Haenszel method with 1000 permutations was conducted to compare the quantitative traits (Pst), the two acoustic PCs, to the neutral marker (Fst). Because we did not have SMI scores for three individuals, all statistical analyses involving individual SMI scores would have a total sample of 143 instead of 146. All statistical tests were conducted using either SAS 9.3  or R 3.11 .To test RCD, we compared the differences in the PCs between allopatric and sympatric populations of n Spitze  to distin Spitze . When Pon Storz . We estiM. fissipes, with a haplotype diversity (h) of 0.88. The M. fissipes populations are classified into four groups . The spectral properties of the calls and SMI scores, however, did not reflect the phylogenetic structure (Appendix S6).Both the temporal (PC1) and spectral PC2) properties of the advertisement calls of  propertins Table B and C. M. fissipes correlated with long‐term average temperature at the localities . Similarly, neither of the two call properties correlated with mean SMI scores of the populations .Neither the temporal (PC1) nor spectral (PC2) properties of the advertisement calls of M. fissipes.Neither the temporal properties (PC1) nor the spectral properties (PC2) of the advertisement calls differed between the sympatric and allopatric populations Table , indicatM. fissipes populations were positively correlated , indicating the presence of isolation by distance effect. Furthermore, the pairwise differences in the temporal properties of the advertisement calls  and geographic or genetic distances were also positively correlated . The matrix permutation test did not show significant differences between the quantitative traits  and the neutral marker  . Both the relationship test and Pst‐Fst comparisons suggest that the acoustic variation of M. fissipes was likely caused by genetic drift.The genetic and geographic distances among M. fissipes, suggesting that male call properties may not reflect male quality. In conclusion, we suggest that the geographic variation in the advertisement calls of M. fissipes is mainly shaped by drift, not ecology. Given their widespread distributions in lowland habitats throughout the subtropical and tropical Asia, M. fissipes and M. heymonsi can serve as valuable model species for studying contemporary evolution of acoustic signals under rapid environmental changes.This study provides an empirical case for which geographic variation of a sexual trait  in a frog is likely driven by a random process (genetic drift) rather than selection . For explosive‐breeding or lek‐breeding frogs, it has been suggested that male quality may be related to chorus attendance, and females that mate randomly are likely to mate with high‐quality males and thereby gain fitness without incurring costs of mate assessment , whether this amount of difference is sufficient for the females to distinguish between them in a mixed‐species chorus remains unclear. Alternatively, mate recognition in these two species may have been achieved through visual cues. Anurans as a group are highly sensitive to visual signals that are used for predation avoidance, communication, and mate choice, even in a low luminous environment , which could potentially contribute to their contemporary speciation.Acoustic divergence in mating calls among populations could reduce gene flow and facilitate population differentiation and speciation. The island of Taiwan is known for its steep topography and a highly fragmented landscape, which provide the backdrop for rapid genetic differentiation across very short distances ; the mitochondrial COI sequences can be found on GenBank (KT894589‐KT894670).The data on the original 10 call properties of the 146 None declared.Appendix S1. Locality, abbreviation, latitude, longitude, elevation, mean temperature and sample sizes of Microhyla fissipes and M. heymonsi for each sample locality used in this study.Appendix S2. Illustrations of the temporal and spectral properties of the advertisement call of a Microhyla fissipes individual.Appendix S3. Acoustic characteristics of the advertisement calls of Microhyla fissipes and M. heymonsi.Appendix S4. Pairwise comparisons of genetic differentiation (Fst) and genetic distance (Kimura‐2‐parameter) among populations of Microhyla fissipes.Appendix S5. Pairwise comparisons of Pst of first principal component (PC1) and second principal component (PC2) of acoustic characters among Microhyla fissipes populations.Appendix S6. Geographic variation in the advertisement calls and body size of Microhyla fissipes among different regional clades in Taiwan.Click here for additional data file.


Botrylloides nigrum  has been largely ignored. We sampled B. nigrum from 16 worldwide warm water locations, including around the Panama Canal, one of the largest shipping hubs in the world and a possible introduction corridor. Using mitochondrial (COI) and nuclear (ANT) markers, we discovered a single species with low genetic divergence and diversity that has established in the Atlantic, Pacific, Indo‐Pacific, and Mediterranean Oceans. The Atlantic Ocean contained the highest diversity and multilocus theta estimates and may be a source for introductions to other regions. A high frequency of one mitochondrial haplotype was detected in Pacific populations that may represent a recent introduction in this region. In comparison to temperate relatives, B. nigrum displayed lower (but similar to temperate Botrylloides violaceus) genetic divergence and diversity at both loci that may represent a more recent global spread or differences in introduction pressures in tropical regions. Additionally, chimeras  were detected in three populations by the mitochondrial locus and validated using cloning, and these individuals contained new haplotype diversity not detected in any other colonies.Little is known about the number and rate of introductions into terrestrial and marine tropical regions, and if introduction patterns and processes differ from temperate latitudes. Botryllid ascidians (marine invertebrate chordates) are an interesting group to study such introduction differences because several congeners have established populations across latitudes. While temperate botryllid invasions have been repeatedly highlighted, the global spread of tropical  Marine biological introductions have increased at an exponential rate of detection globally over the last two centuries in many temperate areas , first described in Bermuda, is currently reported in tropical and warm water regions across the globe. This broad and disjunct geographic pattern may include multiple unrecognized cryptic species, as botryllid species are particularly difficult to distinguish morphologically and many regions in the tropics have poor historical biodiversity records. The global distribution of Botryllus schlosseri shows both spatially restricted and broadly introduced evolutionary lineages  Does the environmentally broad and geographically disjunct distribution of this species reveal cryptic diversity or the global introduction of a single species? (2) What phylogeographic patterns characterize this understudied tropical introduced species? (3) And how do these patterns compare to introductions of temperate relatives?In this study, we investigated the global population structure and introduction history of the sessile marine invertebrate Botrylloides nigrum were collected from 16 locations . Genetic diversity was assessed using the mitochondrial cytochrome c oxidase I (COI) gene and nuclear adenine nucleotide translocate (ANT) gene because these markers have proven to be useful for identifying species diversity and phylogeographic patterns in invertebrates, including ascidians , and 20–300 ng of template DNA. Initial denaturing at 95°C for 3 min was followed by 35 amplification cycles  and a final extension at 72°C for 10 min. PCR products were cleaned with ExoSAP‐IT®  and sequenced using 1/8 BigDyeTerminator v3.1  cycle sequencing reactions and an ABI 3130 genetic analyzer (Applied Biosystems) at the Romberg Tiburon Center for Environmental Studies.Genomic DNA was extracted from individuals by dissecting a 0.5 cmB. nigrum collected from Panama and Brazil that were identified using the following diagnostic taxonomic features: a characteristic color pattern of living colonies that includes an orange or white horseshoe shaped line linking the siphons against a dark violet or black tunic, the cardiac end of the stomach is generally wide and truncated with the ends of the folds forming conspicuous and prominent rounded bulbous projections, a short cecum enlarged toward the blind distal end that was often curved but only slightly, and usually one oocyte at each side between the testis and the gut . To confirm species identity of collected samples, the COI marker was used to amplify specimens of Van Name .Samples amplified at the nuclear ANT locus were directly sequenced and secondary peaks from heterozygous individuals were called by eye in SEQUENCHER. Alleles were determined using PHASE v2.1 , and nucleotide diversity (π) were estimated in ARLEQUIN v3.5  and ocean basins  in CONTRIB v1.02 , gene diversity FST and ΦST (incorporating the Tamura‐Nei and Jukes‐Cantor models) comparisons for 13 populations were estimated in ARLEQUIN. For these two estimates, the online SISA program  with 10,000 permutations to test significance. Three separate AMOVA analyses were conducted by grouping sequences at different geographic scales, including (1) no grouping of populations, (2) grouping by local basin, and (3) grouping by ocean (see Table The online program FINDMODEL determined that the Tamura‐Nei and Jukes‐Cantor models were the best DNA substitution models for COI and ANT respectively. Pairwise NM = θm) entering and leaving each ocean basin. Since mitochondrial and nuclear organelles have different evolutionary histories, separate analyses for COI and ANT were conducted. To avoid effects of differences in sample size on gene flow estimates, the program randomly subsampled 30 COI alleles and 60 ANT alleles from each ocean population. The transition to transversion ratio of each locus was calculated in the program MEGA v5.2  between each ocean basin.To assess gene flow among ocean basins, we used the software package MIGRATE v3.5 Beerli,  to estimBotrylloides leachi (Genbank Accession FJ528644) was used as an outgroup since it is a closely related congener  in one location, Hawaii. The Atlantic Ocean contained the greatest number of haplotypes  compared to the Pacific  and Mediterranean .In our final set of 321 samples from 16 locations, a 527 nt fragment of COI was used for analysis. This study detected eight alleles with 10 (2%) polymorphic sites, where eight of these sites were synonymous and two sites were nonsynonymous substitutions. Both nonsynonymous substitutions were only found in chimeric individuals see . We deten = 15) and Panama (n = 27). Puerto Rico had the highest overall gene (0.6481 ± 0.071 SD) and nucleotide (0.0054 ± 0.0032 SD) diversity of any population. The highest allelic richness values (populations rarefied to a sample size of seven) were found in Puerto Rico (2.052) and Venezuela (2.000); the Pacific populations showed the lowest allelic richness (ocean comparisons were rarefied to a sample size of 32). When comparing oceans, the Atlantic had the highest allelic richness (2.328) followed by the Mediterranean (1.000) and Pacific (0.865). Overall mean divergence was 0.4% among COI haplotypes. Maximum likelihood analysis revealed two groupings of haplotypes  and total nucleotide diversity was 0.0038 ±0.0024 SD). Gene and nucleotide diversity varied considerably within and between regions (Table 4 SD. GenP < 0.001 for both).Results from AMOVA showed significant genetic structure among groups when populations were pooled into the Atlantic, Pacific, and Mediterranean Oceans Table . Howeverr = 0.125, P < 0.0001). When considering only Atlantic populations (the most heavily sampled region), the Mantel test also detected a correlation between genetic and geographic distance . Divergence between populations could result in false positives in this test  significant population comparisons were detected at both the s Tables  and 5. O1% signifWhen populations were pooled by ocean basin, the Pacific Ocean showed significantly negative values at Tajima's D, Fu and Li's F, and Fu and Li's D Table . PopulatCoalescent estimates of gene flow (effective number of migrants per generation) between ocean basins were high 4.4–433.7). Gene flow was lower from the Atlantic and Mediterranean to the Pacific , while all other directions showed very high gene flow  positions 100, 325, 336, and 410, which were consistent across three repeated extractions (Table S2). We interpret heteroplasmy detected in this study as chimerism for the following reasons: (1) extra alleles were detected in mtDNA and thus would not be an artifact of extracting DNA from fertilized eggs or larval tissue (2) some heteroplasmic individuals contained only common COI alleles, (3) fusion is common in some natural populations  represented new diversity only detected in chimeras. The substitution at position 325 was a synonymous mutation. Position 336 showed a nonsynonymous mutation that was found in one individual (HI19) and changed a leucine to phenylalanine (score of −3 Blosum 62 Amino Acid Similarity Matrix). Two individuals from the same location (PR11 & PR 24) also contained a nonsynonymous mutation at position 411 that changed arginine to serine (score of 1 Blosum 62 Amino Acid Similarity Matrix). This diversity represented three COI haplotypes . No more than two alleles were detected in any chimeric individuals at the ANT locus.n = 18) contained two chimeric individuals, and Hawaii  had one chimeric individual. When chimeric individuals were removed from population diversity analyses, Puerto Rico still remained one of the most diverse populations . Conversely, after removing chimeras, diversity greatly decreased in Hawaii  and Veracruz , which can affect interpretation of genetic diversity of these populations compared to other locations  and a smaller fragment from Styela plicata (Genbank Accession HQ916363). The ANT exon dataset contained 13 polymorphic sites (5%) that were all synonymous substitutions. No recombination events were detected within ANT sequences.We recovered a 265 nt fragment of the inferred ANT gene from 319 individuals from 16 locations. The ANT locus has an intron in some species, although not in the tunicates FIS coefficient revealed significant inbreeding at the ANT locus when considering all populations , Veracruz (0.271), Venezuela (1.000), Bocas (0.184), and Israel (0.167) each showed significant inbreeding. The Atlantic was the only ocean basin with a significant FIS (0.193) value. Texas (−0.189) and Hawaii (−0.251) showed significantly negative FIS values.The n = 66), allelic richness values were similar: the Atlantic Ocean had the highest allelic richness (4.194), followed by the Pacific (4.098) and the Mediterranean (4.000).We chose an inferred probability for phase acceptance of < 97% for all samples, which resulted in discarding two low‐resolution samples from the study . In total, 13 alleles were discovered and four of these were found in each sampled ocean basin Table , Fig. 3.r = 0.095, P = 0.001). Additionally, we did not detect high divergence among basins that could bias these results  significant comparisons between populations at the ANT locus than was found among COI comparisons . The lowest gene flow was detected from the Atlantic and Pacific to the Mediterranean : marinas in Oahu, Hawaii; marinas on the Pacific coast of Mexico from Mazatlan to Nayarit; and on buoys in shipping lanes off the coast of Singapore. Also, all samples from the Mediterranean coast of Israel genotyped as B. nigrum and not as Botrylloides leachii, as recently proposed  diversity of B. nigrum are low compared to Botryllus schlosseri  but similar to Botrylloides violaceus   and nucleotide (0.0099) diversity of B. nigrum are much lower than a confamilial, Styela plicata , which is thought to have established hundreds of year ago and now displays a global distribution with repeated genetic shuffling  across the southern hemisphere  and nucleotide  and Mediterranean . Furthermore, the coalescent‐based program MIGRATE estimated high theta values –a more robust measure of genetic diversity— for the Atlantic population at both loci . In comparison, theta values an order of magnitude lower were detected in the Pacific (COI locus = 0.0003) and Mediterranean (ANT locus = 0.0022) populations, a possible signal that these are introduced ranges. However, the West Atlantic is the most heavily sampled region in this study and the high diversity reported here could be biased by the over detection of rare alleles.For B. nigrum because: (1) This is the only region displaying a continuous distribution, (2) At both markers, we consistently detected high genetic diversity in Puerto Rico and nearby populations, and (3) Pacific and Mediterranean regions are likely not the native source because of very low population diversity and reports are few and geographically scattered. However, the distribution of this species is likely greater than what is currently reported, and broader sampling in the Eastern Atlantic, Red Sea, and Indo‐ and West‐Pacific with higher resolution loci may help resolve the native range.We hypothesize the Caribbean as the native range of Rare alleles were discovered in what we determined to be chimeric individuals from Hawaii, Puerto Rico, and Veracruz, Mexico that were not detected in nonchimeric colonies. Though low detection of these genotypes could be a result of limited sampling, chimerism may act to increase genetic diversity of populations by hiding the genotype of one individual within the tissues of the other after fusion of distinct, but closely related, individuals. Botryllid chimeras are capable of retaining the genotypes of each fused colony and shifting which genotype takes over somatic growth when exposed to varying environments, perhaps allowing the colony to express the best‐fit genotype for the environment  of a tropical botryllid. The role of fusion and its rates may differ between native and introduced populations. Microsatellite studies of adult B. nigrum across global warm waters has been largely unexplored to date. The geographically widespread and environmentally variable distribution of this species suggests that it may tolerate a wide range of suitable environmental conditions .Figure S2. Yellow on red color morphotype from Indian River Lagoon, FL, USA. Photo by: L Walters .Figure S3. Yellow on red color morphotype from Indian River Lagoon, FL, USA. Photo by: L Walters .Figure S4. White on black color morphotype from Indian River Lagoon, FL, USA. Photo by: L Walters .Figure S5. Bright orange on dark orange color morphotype from Oahu, Hawaii, USA. Photo by: C Craig (San Francisco State University).Figure S6. Orange on black color morphotype from Oahu, Hawaii. Photo by: C Craig (San Francisco State University).Figure S7. Yellow on black color morphotype from Veracruz, Mexico. Photo by: H Bahena .Figure S8. White on red color morphotype from Veracruz, Mexico. Photo by: H Bahena .Table S2. Chimeric individuals detected in this study.Click here for additional data file.


South Asia possesses a significant amount of genetic diversity due to considerable intergroup differences in culture and language. There have been numerous reports on the genetic structure of Asian Indians, although these have mostly relied on genotyping microarrays or targeted sequencing of the mitochondria and Y chromosomes. Asian Indians in Singapore are primarily descendants of immigrants from Dravidian-language–speaking states in south India, and 38 individuals from the general population underwent deep whole-genome sequencing with a target coverage of 30X as part of the Singapore Sequencing Indian Project (SSIP). The genetic structure and diversity of these samples were compared against samples from the Singapore Sequencing Malay Project and populations in Phase 1 of the 1,000 Genomes Project (1 KGP). SSIP samples exhibited greater intra-population genetic diversity and possessed higher heterozygous-to-homozygous genotype ratio than other Asian populations. When compared against a panel of well-defined Asian Indians, the genetic makeup of the SSIP samples was closely related to South Indians. However, even though the SSIP samples clustered distinctly from the Europeans in the global population structure analysis with autosomal SNPs, eight samples were assigned to mitochondrial haplogroups that were predominantly present in Europeans and possessed higher European admixture than the remaining samples. An analysis of the relative relatedness between SSIP with two archaic hominins  identified higher ancient admixture in East Asian populations than in SSIP. The data resource for these samples is publicly available and is expected to serve as a valuable complement to the South Asian samples in Phase 3 of 1 KGP. Indians of South Asia has long been a population of interest to a wide audience, due to its unique diversity. We have deep-sequenced 38 individuals of Indian descent residing in Singapore (SSIP) in an effort to illustrate their diversity from a whole-genome standpoint. Indeed, among Asians in our population panel, SSIP was most diverse, followed by the Malays in Singapore (SSMP). Their diversity is further observed in the population's chromosome Y haplogroup and mitochondria haplogroup profiles; individuals with European-dominant haplogroups had greater proportion of European admixture. Among variants  discovered in SSIP, 21.69% were novel with respect to previous sequencing projects. In addition, some 14 loss-of-function variants (LOFs) were associated to cancer, Type II diabetes, and cholesterol levels. Finally, D statistic test with ancient hominids concurred that there was gene flow to East Asians compared to South Asians. Next-generation sequencing (NGS) technologies have enabled an entire genome to be sequenced in a cost-effective manner The 1000 Genomes Project (1 KGP) intends to survey more than 2,500 individuals from at least 20 populations around the world South Asia comprises more than 20% of the total world population, of which the majority resides in India th century Singapore is home to more than 350,000 Indians, comprising 9.2% of the residing population http://www.statgen.nus.edu.sg/~SSIP.The SSIP aims to perform whole-genome sequencing of 38 healthy Singapore Indians, to provide insights into the genetic structure and diversity of Asian Indians in Singapore. With a target sequence depth of 30X, the SSIP presents another public resource of deep whole genome sequencing of multiple samples in a well-defined population, as with the SSMP. Here, we evaluated the genetic proximity of the SSIP to the SSMP and 14 populations from Phase 1 of the 1 KGP, and measured the degree of intra-population genetic diversity in each of the 16 populations. The ancestral origins of the SSIP samples were inferred by evaluating the mitochondria and chromosome Y haplogroup memberships of the relevant samples, and we performed an analysis of the relative relatedness between SSIP and two archaic hominins . The genetic resource for the SSIP is publicly available at South Asian Indians from the Singapore Population Health Study were sampled to be whole-genome sequenced with the Illumina HiSeq 2000 to a target 30-fold coverage, using paired-end sequencing with 100 basepairs (bp) reads and a target insert size of between 300 bp and 400 bp . This waThe data release for SSIP consisted of the consensus set of SNPs and indels called by both CASAVA and GATK to minimize false discovery. As each sample was also genotyped on the Illumina Omni2.5 M microarray, we compared the concordance of the genotype calls made by CASAVA and GATK with the genotypes at the same SNPs on the Omni2.5 M. CASAVA was observed to produce genotype calls with a higher concordance with the Omni2.5 M genotypes than GATK , we subsA total of 10,305,409 SNPs, 1,269,000 indels and 56,088 large deletions were detected in the 36 SSIP samples , where 2Bi-allelic SNPs and indels were further annotated with SNPEff which catalogued each variant into one of four categories according to the predicted level of impact to protein function When compared to the variants that have been reported by 1 KGP, there were more SNPs and indels present in 1 KGP than SSIP . HoweverPcorrected = 2.8×10−3, We identified 1,429 loss-of-function variants (LOFs) in the 36 SSIP samples, of which 635 LOFs were novel and 407 LOFs had AAF>5% . On averThe LOFs were also mapped to the Catalogue of Somatic Mutations In Cancer (COSMIC) database with SNPnexus, and 11 variants were found to be associated with ovarian, gastrointestinal, hepatic and pancreatic cancer . The risA PCA was performed with the SSIP samples and a panel of 132 South Asians from 25 well-defined groups from the Indian subcontinent ST analyses, where the Americans were found to be most similar to the SSIP  was performed to place these 36 Singapore Indians amongst global populations . The firthe SSIP . ExcludiK≥6, In an admixture analysis of the 16 populations, we observed that the SSIP were consistently inferred to be significantly admixed with the Europeans until at least six distinct groups were assumed K≥6, , where tOne measure of population diversity we investigated was the proportion of SNPs that was shared uniquely with only one other population when assessed across all 16 populations . We obseD that is scaled between 0 and 1, where a higher value indicated a greater degree of heterogeneity in SNP content between the two samples (or a lower degree of SNP sharing). As expected, the African populations exhibited the highest intra-population diversity while the East Asian populations exhibited the lowest , we similarly observed the highest ratio of heterozygous genotypes to homozygous genotypes (Het/Hom) in the SSIP samples among all Asians, and the levels present in the SSIP were comparable to those in Europeans . The treWe assigned the 36 SSIP mitochondria (mtDNA) sequences to known mitochondria haplogroups with HaploGrep P = 0.047) in the samples identified with European-dominant mitochondrial haplogroup assignment, despite this not being evident in the PCA with autosomal SNPs , where the SSIP is observed to possess an average of 53% European admixture  and a non-European dominant group  and compared the estimated degree of European admixture between these two groups when we assumed six distinct populations in the admixture analysis . We assumal SNPs . We obses K = 6, , which wdmixture , which iDstatistic metric to investigate the relative extent of admixture of two ancient hominid genomes, a Neanderthal and a Denisovan, into modern humans. As Dstatistic required the input of four genomes, the analysis was anchored with a specific SSIP sample (SSI033 as G1) together with an ancient hominid and the chimpanzee genome, and we varied only the sample that was used in this four-sample analysis , and also performed the same analyses on the populations sequenced by Complete Genomics (to a minimum coverage of 51X). These additional analyses indicated that our original observations were robust  and the United Kingdom , as well as two native South Asian groups in Bangladesh  and Pakistan (Punjabi). Similar to the Phase 1 design, these five groups have been sequenced at a low coverage of between 2- to 6-fold, and it can be useful to evaluate whether the availability of the SSIP data will benefit the process of variant calling for these populations that have undergone low-pass sequencing. The variants for the 36 SSIP samples are publicly available in the variant call format (VCF), and these can be accessed along with phased haplotypes for the SSIP samples at Subjects enrolled in the SSIP consisted of 38 subjects, 12 males and 26 females, from the Multi-Ethnic Cohort (MEC) of the Singapore Population Health Study who self-reported themselves as Singapore Indians. This is a cross-sectional survey on individuals of ages between 40 and 65 years old, the exclusion criteria at the time of the initial enrolment into the MEC were: (i) below 21 years of age; (ii) having any mental condition that may interfere with the participant's competency in giving informed consent; and were suffering from any of the following conditions (iii) renal failure; (iv) stroke; (v) cancer; (vi) heart disease . We confirmed the ethnic membership of each individual via a telephone survey to verify that both sets of grandparents similarly self-reported to be South Asian Indians. Informed consent was obtained from all participants and ethical approvals were obtained for the Singapore Population Health Study and the extension to perform whole-genome sequencing from two independent Institutional Review Boards at the National University Hospital (Singapore) and the National University of Singapore respectively.The blood samples of all 38 Singapore Indians were extracted from the Singapore BioBank, and DNA extraction was performed at the Defence Medical and Enviromental Research Institute according the protocol by Illumina, with DNA quantification performed using picogreen and the SpectraMax Gemini EM microplate reader (with spectrophometic set at 480/520 nm) to ensure DNA concentration for each sample was at least 50 ng/µl. Whole genome sequencing was performed at the Illumina facility at Hayward, California, USA, using the Illumina HiSeq 2000 sequencer, where each sample was run on a unique lane to achieve a target coverage of 30-fold with 2×100 paired-end reads and a target insert size of between 300–400 bp. To ensure consistent and quality sequencing, multiple quality control procedures were adopted: (i) in preparing the libraries, the Bioanalyzer was used to ensure DNA quality and size distribution; (ii) a short paired-end sequencing reaction was applied to each sample after library preparation to ensure the extent of GC bias and the observed sequencing quality were within normal ranges; (iii) sequencing of each sample was performed on a unique lane, with the condition that at least 80% of the generated bases must attain a quality score of at least 30, failing which the sample was re-sequenced. Each sample was also genotyped on the Illumina Omni2.5 M microarray, where genotype calling was performed with the proprietary GenomeStudio software by Illumina.Assembly and alignment of each individual genome to the human reference genome  was performed using the proprietary Illumina CASAVA version 1.9.0a1_110909 assembler. CASAVA aligned sequence reads using Eland v2e, and the aligned reads for each sample were then consolidated into the BAM format file Two methods were used to call SNPs and indels: (i) single sample calling by CASAVA; and (ii) multi sample calling by GATK version 2.1.8 pca option in the software eigenstratK) was set to range from 2 to 16.PCA was used to assess the population structure of the SSIP samples with samples from worldwide populations using the S1,S2) is the minimun number of SNPs in two samples denoted as S1 and S2, and S1 and S2. A high D value thus reflects a lower degree of SNP sharing, or greater genetic heterogeneity, between the two samples; a low D value indicates that SNPs present in S1 are likely to be present in S2, thus reflecting greater genetic homogeneity between the two samples. To evaluate whether the number of samples in each population influenced the comparison, we additionally performed the analysis with the same number of samples selected randomly from each population. To ensure that the results of this analysis were robust to sequencing coverage and the method used for variant calling, we also measured D for samples from six populations in 1 KGP  that were sequenced by Complete Genomics We measured the genetic diversity of SSIP, SSMP and 14 populations in Phase 1 of 1 KGP with a distance metric calculated between every possible pair of samples in each of the 16 populations, defined as mpileup in SAMTOOLS mpileup in SAMTOOLS, which was subsequently converted to the qcall input file used by Yfitter for haplogroup assignment. Default settings for Yfitter and haplogrep were used in our analyses.Every SSIP individual was assigned to a unique mitochondria haplogroup on the basis of the complete sequence of the mtDNA. This was performed with haplogrep with reference to PhyloTree mtDNA tree Build 15 Dstatistic metric A and B) sites from two modern human genomes , an ancient genome  and the chimpanzee genome, and BABAN denote the total number of sites where G1 and the ancient genome carried allele B while G2 and the chimpanzee genome carried allele A; and ABBAN denote the total number of sites where G1 and the chimpanzee genome carried allele A while G2 and the ancient genome carried allele B. At sites where the ancient genome carries different alleles to the chimpanzee genome, Dstatistic thus measures the deviation in similarity between the ancient genome and each of the two modern genomes. The genome was divided into M non-overlapping blocks of 5 Mb and a jack-knife approach was used to calculate the mean, standard error and Z score of Dstatistic. Two ancient genomes were considered: (i) the Denisovan genome, sequenced on the Illumina Genome Analyzer IIx at a coverage of 30-fold http://www.eva.mpg.de/neandertal/index.html).We evaluated the relative degree of relatedness between one SSIP sample  and a randomly chosen sample from each of the 15 populations  with an ancient genome using the A full description of the Figure S1Mean and standard deviation of insert sizes for each sample. The vertical blue bars represent mean insert sizes while the red line shows the standard deviation of insert sizes from the paired-end sequencing reads. No outliers were found.(TIF)Click here for additional data file.Figure S2Total number of reads for each sample. Total number of reads sequenced for all samples fall within an acceptable range. Blue bars represent reads that passed QC while red bars represent reads that failed QC.(TIF)Click here for additional data file.Figure S3Total paired reads for each sample. Vertical blue bars represent reads that passed QC while red bars represent reads that failed QC. No unusual trend observed.(TIF)Click here for additional data file.Figure S4th and 25th percentiles are represented by green line and blue line respectively.Read depth summary statistics for each sample. Sample SSI007 displayed a median read depth less than the targeted depth of 30X (red line) and is subsequently excluded from downstream analyses. 75(TIF)Click here for additional data file.Figure S5Principal Component Analysis (PCA) of samples from Singapore Sequencing Indians Project (SSIP) and Singapore Genome Variation Project (SGVP). A set of 420,817 SNPs common between the 38 samples from SSIP (blue circles) and 268 samples from the SGVP, which includes 96 Chinese (red), 89 Malays (green) and 83 Indians (sky blue) were used to generate a PCA plot. The analysis revealed one sample from SSIP (SSI016) to be of closer proximity to Malays (SGVP_MAS), this sample was removed from downstream analysis.(TIF)Click here for additional data file.Figure S6Genotype concordance rate for autosomes SNPs. Comparison of genotype concordance rate between CASAVA (blue) and GATK (red) SNPs calling with reference to Omni 2.5 M array for autosomal SNPs. Chromosome number is displayed at horizontal axis. CASAVA outperformed GATK across all chromosomes.(TIF)Click here for additional data file.Figure S7Pairwise populations FST between SSIP and other 15 populations on bi-allelic SNPs of autosomal chromosomes. Blue bar is the mean pairwise population FST for SSIP and another population for common SNPs between the two populations, green bar represents mean pairwise population FST for SSIP and another population for common SNPs across entire population panel , 4,360,323 for 36 samples each population in (B)). Red circle shows number of common SNPs between a pair of populations that was used for mean FST calculation.(TIF)Click here for additional data file.Figure S8Genetic diversity measured by distance metric. Intra population diversity measured for all possible pairs of sample in each population for (A) original sample size; (B) normalized sample size by randomly selecting 36 samples from each population. IBS was removed from the analysis because its sample size was less than 36 samples. We do not observe any deviation between original samples size and normalized samples size and thus this analysis is not sensitive to sample size variation.(TIF)Click here for additional data file.Figure S9D for 7 populations for (A) 1 KGP (average coverage of 5X) and (B) Complete Genomics (deep coverage of 51-89X). Label at axis X show information of continent, population, sample size and total number of pair. Identical trend was observed regardless of low or deep sequencing coverage. African populations have the highest intra-population diversity score while Asian populations have the lowest, GIH (Northern Indians) and SSIP are slightly above Europeans.Intra population diversity for 7 populations in 1 KGP and Complete Genomics. Intra population diversity base on distance measure (TIF)Click here for additional data file.Figure S10Heterozygous to homozygous ratio. (A) Boxplot of original sample sizes heterozygous to homozygous ratio in each population. (B) We randomly selected 36 samples from each population  to calculate single sample heterozygous to homozygous ratio. SSIP has the highest ratio than all other Asian populations, indicating SSIP is more diverse than East Asian populations  and Southeast Asian population (SSMP).(TIF)Click here for additional data file.Figure S11Heterozygous to homozygous ratio for Complete Genomics samples. Heterozygous to homozygous ratio for samples from Complete Genomics color coded by continent, red represents Africans, green for Asians while skyblue for Europeans. Het/Hom ratio obtained in deep sequencing samples (Complete Genomics) and shallow sequencing samples (1 KGP) are within the same ranges for all compatible populations. Axis X show information of sample id and population.(TIF)Click here for additional data file.Figure S12Principal component analysis of 16 world populations. PCA of 1,224 samples from SSIP, SSMP and 14 populations from Phase 1 of the 1 KGP, where the samples are grouped and color-coded by continents (legend). Blue circles are 26 SSIP samples and the remaining 8 SSIP individuals (yellow circles) are with European dominant mitochondria haplogroup assignment.(TIF)Click here for additional data file.Figure S13Principal component analysis of 83 Indians from Singapore Genome Variation Project and 85 Gujarathi from Hapmap 3. PCA on a set of 30,927 SNPs for 83 Singapore Indians (blue) from SGVP and 85 Gujarati Indians in Houston (skyblue) from Hapmap 3.(TIF)Click here for additional data file.Figure S14K is the number of distinct populations that varied between 2 and 5. Black windows highlights the position of the Chencu, Austro-Asiatic groups , Northern Indians and Southern Indians Click here for additional data file.Figure S15K from 2 to 15 performed on 16 populations. Cross-validation error in the admixture analysis at different values of ancestral groups (K), which we have allowed to range from 2 to 15. It was observed that while K = 7 yielded the lowest cross-validation error, K = 6 yielded a difference that was less than 0.01 and thus K = 6 was chosen for reporting in the main text on the basis of parsimony.Cross validation error for admixture analysis with (TIF)Click here for additional data file.Figure S16K indicates the number of ancestral populations. At K = 3, the three ancestral populations are African, European and Asian Click here for additional data file.Table S1Description of populations used for comparison with SSIP.(DOC)Click here for additional data file.Table S2Description of 25 Indian groups extracted from Reich et al. 2009.(DOC)Click here for additional data file.Table S3Transition to transversion ratio (Ts/Tv). (A) Ts/Tv for bi-allelic SNPs, (B) Ts/Tv after the removal of CpG exonic transition SNPs.(DOC)Click here for additional data file.Table S4Summary of single sample Loss-of-function (LOF) variants.(DOC)Click here for additional data file.Table S5List of pathways affected by Loss-of-function (LOF) variants.(DOC)Click here for additional data file.Table S6List of Loss-of-function (LOF) variants found in COSMIC database.(DOC)Click here for additional data file.Table S7List of Loss-of-function (LOF) variants related to GWAS studies.(DOC)Click here for additional data file.Table S8The proportions for 6 ancestral populations extracted from the output of ADMIXTURE program.(DOC)Click here for additional data file.Table S9D statistic analysis with ancient genome for 5 randomly selected pairwise samples, anchored with different SSIP sample (G1). (A) Neanderthal as ancient hominid, (B) Denisovan as ancient hominid.(DOC)Click here for additional data file.Text S1Supplementary methods.(DOC)Click here for additional data file.


This geographical region is interesting to study because its medieval multi-ethnic population lived in the so-called contact zone of the territory of the Great Moravian and later Hungarian state formations. We described 16 different mtDNA haplotypes in 19 individuals, which belong to the most widespread European mtDNA haplogroups: H, J, T, U and R0. Using comparative statistical and population genetic analyses, we showed the differentiation of the European gene pool in the medieval period. We also demonstrated the heterogeneous genetic characteristics of the investigated population and its affinity to the populations of modern Europe.The genetic composition of the medieval populations of Central Europe has been poorly investigated to date. In particular, the region of modern-day Slovakia is a blank spot in archaeogenetic research. This paper reports the study of mitochondrial DNA (mtDNA) in ancient samples from the 9 Hungarians arrived into Central Europe from across the Carpathian Mountains and settled in the Danubian Basin in 895–896 AD ,2. This d Gepids . At presd Gepids . Three gth–11th centuries and located in western Slovakia  of meSlovakia , was excThe observed archaeological material culture is open to widely different interpretations, and in particular it is unclear whether and to what extent the attributes  are indicators of ethnic and social identity, and which of these materials are linked to population movements . Ancientth–16th centuries from Hungary, Poland, Italy, Spain and Scandinavia [The European medieval period is poorly investigated genetically; only a few hundred data have been published for the 6ndinavia ,18–25. Fndinavia ,18–25. CThe aim of our study was to determine the genetic composition of maternal lineages in ancient populations from the medieval period of present-day Slovakia, and to characterize relationships to other medieval and modern human populations from Europe and Asia, using population genetics analysis. Genetic exploration of medieval populations in Central Europe is of paramount importance, because people from mixed populations of different ethnic origins lived contemporaneously in this area, making it difficult to distinguish them through archaeological records.The human skeletal remains (bones and teeth) used in this study were provided by the Institute of Archaeology of the Slovak Academy of Sciences in Nitra, and some of them are stored at the Slovak National Museum in Bratislava. Twenty-eight bone specimens were collected: 20 from Nitra-Šindolka and eight from Čakajovce . Burial Sampling was carried out using gloves, facemasks and body suits to minimize the risk of contamination from modern humans. Two bone fragments, usually one tooth and one compact bone fragment of a femur, or two compact bone tissues from different parts of long bones, were collected from each individual. All stages of the work were performed under sterile conditions in a dedicated ancient DNA (aDNA) laboratory  following well-established aDNA workflow protocols ,27. Labo2, 25 min). The surfaces of tooth samples were cleaned by sandblasting , while the surfaces of bone samples were removed with a fresh drilling bit at slow speed, followed by UV exposure for 20 min on each side. Bone and tooth pieces were mechanically ground into fine powder in a sterile mixer mill (Retsch MM301).The specimens were prepared following the protocols described by Kalmár et al.  and Shap4-acetate (4 M) and 700 μl absolute ethanol were added, and samples were incubated overnight at −20°C. The DNeasy Tissue Kit (Qiagen) was used for further purification of the aDNA extract following the manufacturer’s instructions: the mixture was transferred into a DNeasy Mini spin column and centrifuged at 6500 rpm for 1 min. The column was washed twice, DNA was eluted in a final volume of 70 μl and subsequently stored in the pre-PCR lab at −20°C.Standard DNA extraction methods were used as described by Tömöry et al.  and Kalm2O, 1 × AmpliTaq Gold buffer, 0.8 mM dNTP mix, 0.9 mM MgCl2, 0.16 mg/ml BSA, 0.625 μM primers and 1.5 U AmpliTaq Gold DNA polymerase. The HVR I region of mtDNA was amplified in two overlapping fragments with two sets of primers, and an additional six primer pairs were used to amplify haplogroup diagnostic nucleotide positions in the coding region  and the coding region were amplified in a total volume of 40 μl reaction mix, containing 6 μl of DNA extract, 20.4 μl Hgion see . The PCRwww.mtdnacommunity.org) [www.phylotree.org) considering polymorphic positions of HVR I and six haplogroup-diagnostic position of the coding region [http://empop.online/) [The sequence polymorphisms in mtDNA (the minimum range of HVR I of samples from Nitra-Šindolka is nucleotide positions (np) 16059–16421 and the maximum range is np 16041–16421; from Čakajovce, all of them are np 16040–16400) were compared with the revised Cambridge Reference Sequence (rCRS)  as well ity.org) . Haplogrg region . Obtaineonline/) . SequencOne sample from the medieval cemetery at Lébény (Hungary), dating from the same era  and descaDNA sequences were compared with a dataset of 24,096 present-day mtDNA sequences of the HVR I region including European, Near Eastern and Asian populations, as well as 400 medieval sequences. The sequences were collected from published data and are listed in ST) were calculated based on HVR I sequences (np 16050–16383) assuming a Tamura & Nei substitution model [ST values were tested by 10,000 permutations between 32 modern and 12 medieval populations and particularly between the medieval populations alone  of medieval and modern populations was applied on the matrix of linearized Slatkin FT values   was performed, based on mtDNA haplogroup frequencies of 12 medieval and 33 modern-day populations  Tables. Besides the medieval PCA, hierarchical clustering was done using the Ward type algorithm  and EuclShared haplotype analysis (SHA) was performed in order to detect and compare the mtDNA haplotypes shared between 12 medieval populations. Eleven populations from Europe and one from Asia were studied, and the absolute and relative shared haplotypes were counted .We obtained mtDNA sequences from 19 of 28 analyzed samples originating from the medieval Nitra-Šindolka and Čakajovce cemeteries (western Slovakia). We could not extract DNA from four samples, and we excluded a further three samples from Nitra-Šindolka and one sample from Čakajovce from the statistical analysis because of bad DNA preservation or ambiguous haplotype results.The HVR I sequences spanned the range of minimum np 16059–16400 and maximum np 16040–16421. The DNA of 19 individuals was extracted and amplified at least twice per individual from different skeletal elements, and the HVR I fragments and other coding region positions were reproduced in several PCR products per extracts. The results of these replicates along with the negative control results suggest the haplotypes are authentic.The medieval sequences encompass almost the entire range of Western Eurasian macro-haplogroups: H, J, T, R0 and U . HoweverThe haplogroup frequencies in the medieval population of Slovakia are the following: H 25%, J 20%, T 30% (T1 15% and T2 15%), R0 5% and U 20% .ST = 0.02702 and p = 0.08474 ± 0.0025  only between the medieval Slovakian population and the population from Iraq . The present-day Slovaks have a slightly larger genetic distance from medieval Slovaks than other Eastern and Central European modern populations: FST = 0.05492, p = 0.000 ± 0.000  with F± 0.0025 . Interes ± 0.000 .ST values contains aggregation of most of the medieval and modern European populations along coordinates 1 and 2; only the Asian populations of Pakistan, Uzbekistan, Kazakhstan and Kyrgyzstan are separated, forming an eastern cluster along coordinate 1. The ancient Xiongnu population from Mongolia is the farthest population along this coordinate. The medieval population from Slovakia is situated along coordinates 1 and 3 among modern European populations, but is differentiated from them along coordinate 2. In contrast, the other medieval European populations are close to modern populations along coordinates 1 and 2, and differentiated along coordinate 3, which implies their stronger affinity to modern European populations compared with the Slovakian dataset.The MDS plot  and Poland along the PC1 and PC2 components (39.6% of the variance is displayed) . The medThe PCA plots of modern Eurasian populations indicate alignment of the European populations (except Saami) including our investigated medieval population on the PC1 and PC2 components . However, the different frequencies of haplogroups J, T1, T2, U4, U5a and U8 result in differentiation from all present-day populations along the third component (variance PC3 = 10.71%) Figs .The SHA shows that the medieval population from Slovakia shares the majority of haplotypes with medieval populations from Spain and Italy, and that the relatively short genetic distance from the medieval Poles does not mean significant lineage sharing at the HVR I level .th–12th centuries AD. Using well established protocols for aDNA analysis, we have obtained the first mtDNA dataset (to the best of our knowledge) concerning the genetic variation of the HVR I region and six nucleotide polymorphisms in the coding region of mtDNA. These markers enabled us to assign the mtDNA haplogroups of the samples.In this study we investigated a population living in the Hungarian-Slavic contact zone of the Carpathian Basin in the 9th centuries two or three times more frequently than in present-day Europe [The representative haplogroups of the investigated medieval population belong to common modern European (West Eurasian) haplogroups. However, their frequencies are quite different from present-day populations. Contrarily, the detected frequency of haplogroup H in the medieval population from Slovakia was lower (25%) than it is in European modern-day populations (including the Slovaks), where this most frequent haplogroup has a frequency of 45.4% ,15,40. Ty Europe ,40,43.th century. The research team of Alt et al. [The same phenomenon is perceptible in the Lombard population from the western Hungarian site Szólád with regard to the haplogroups H and J, which have either lower (in case of H) or higher (in case of J) frequency compared to other modern European populations . This sit et al.  suggestet et al.  in contrt et al. .th century Hungarian samples from Hungary [th century samples from the region will probably result in a more accurate estimation of the affinity of the medieval populations.Furthermore, the PCA showed that the medieval population of Poland clusters with the medieval population of Slovakia and the Lombards from Hungary , which w Hungary . HoweverThe medieval population under study shares mtDNA haplogroups with common European populations, which is represented in the PCA of modern Eurasian populations. The connection is especially strong to modern Central and South Europeans .ST values were not statistically significant (p > 0.05)  .ST calculation a different result was obtained by the SHA, where a high frequency of shared haplotypes was shown between medieval populations from Slovakia, Spain and Italy. Summarizing, we consider the studied medieval population of Slovakia to be a mixture of groups of different genetic origins. However, more genetic data from Central Europe would be needed to investigate this epoch in detail.From the FThe comparative analysis of the medieval sample sets suggests that the present-day European gene pool could have been formed in the medieval era. This is supported by the presence of a majority of haplogroups and haplotypes in the medieval period which still exist in modern-day Europe. Genetic maternal lineages of the medieval population of present-day Slovakia were diverse and rather similar to medieval Lombards from Hungary and to medieval Slavs from Poland, as well as to modern Europeans, which supports the historical and archaeological standpoint of mixed populations of medieval Slavs and Magyars in the cemeteries investigated. However, the results could have been biased due to the small sample size, and genetic drift could also unnoticeably influence our results. Furthermore, we assessed population interactions and migrations only along the maternal lineages; the paternal side of the medieval population history remained unexamined in this study.th century cemeteries originated in the material culture of the preceding era, implying that Hungarian groups arriving in the territory blended in with the local population, genetically as well as culturally; this interaction produced the medieval population of the area.The collection of archaeological relics from genetically examined Slovakian cemeteries overlaps the image drawn by population genetics analysis. The finds of the 10Undoubtedly, further research, including the analysis of the whole mitochondrial genome and nuclear DNA markers, is necessary in the investigation of the genetic connections between medieval and modern populations and in the clarification of the genetic origin of Slavs and Hungarians. Nevertheless, the study presented here of the first successful description of medieval mtDNA variability from Slovakia contributes an important dataset to help reveal the genetic diversity of medieval Europe.S1 FigST values of 12 medieval and 32 modern Eurasian populations. Its stress value is 0.1130.The MDS plot was performed with linearized Slatkin F(TIF)Click here for additional data file.S2 FigThe PCA is based on mtDNA haplogroup frequencies of the medieval population from Slovakia and 33 modern-day populations from Eurasia, and shows PC1 and PC3. The haplogroup frequencies and the population information are shown in (TIF)Click here for additional data file.S3 FigThe levelplot is based on the percentage values of the relative shared haplotypes, which are also shown on the figure. The absolute values and the population information are given in (TIF)Click here for additional data file.S1 Table(XLSX)Click here for additional data file.S2 TableHaplotypes based on rCRS and RSRS, range of HVR I, haplogroup-diagnostic positions of mtDNA coding region and haplogroup definitions of the investigated samples used in statistical analysis.(XLSX)Click here for additional data file.S3 TablePCR primer pairs used for amplification of HVR I sequences and some SNPs in the coding region of mtDNA.(XLSX)Click here for additional data file.S4 Table(XLSX)Click here for additional data file.S5 TableST values, p values and Slatkin matrix of 12 medieval populations and 32 modern populations from Eurasia.F(XLSX)Click here for additional data file.S6 TableST values, p values and Slatkin matrix of 11 medieval populations from Europe and one population from Asia.F(XLSX)Click here for additional data file.S7 TablePopulation information and mtDNA haplogroup frequencies used for PCA with 12 medieval populations (11 from Europe and one from Asia).(XLSX)Click here for additional data file.S8 TablePopulation information and mtDNA haplogroup frequencies used for PCA with the medieval population from Slovakia and 33 modern-day Eurasian populations.(XLSX)Click here for additional data file.S9 TableThe frequencies of shared haplotypes of 12 medieval populations.(XLSX)Click here for additional data file.S10 TableHVR I haplotypes of the researchers who had been in contact with the ancient samples during the laboratory work.(XLSX)Click here for additional data file.


Dorcus hopei, a stag beetle species, using next generation sequencing and polymerase chain reaction (PCR)-based genotyping for regional populations. A total of 407,070,351 base pairs of genomic DNA containing >4000 microsatellite loci except AT repeats were sequenced. From 76 loci selected for primer design, 27 were polymorphic. Of these 27 markers, 10 were tested on three regional populations: two Chinese (Shichuan and Guangxi) and one Korean (Wanju). Three markers were excluded due to inconsistent amplification, genotyping errors, and Hardy-Weinberg equilibrium (HWE). By multi-locus genotyping, the allele number, observed heterozygosity and polymorphism information content of seven microsatellite loci were ranged 2‒10, 0.1333‒1.0000, and 0.1228‒0.8509, respectively. In an analysis on the genetic differentiation among regional populations including one Japanese population and one cross-breeding population, the individual colored bar-plots showed that both Chinese populations were closer to each other than to the Far East Asian populations. In Far East Asian populations, Wanju and Nirasaki populations could not be distinguished from each other because the frequency of genetic contents was very similar in some individuals of two populations. Moreover, the cross-breeding population contained all patterns of genetic contents shown in Chinese, Korean, and Japanese populations, compared with the genetic content frequency of each regional population. As a result, we examined whether the cross-breeding population might be a hybrid population, and might contain a possibility of interbreeding with Chinese populations in parental generations. Therefore, these markers will be useful for analyses of genetic diversity in populations, genetic relationships between regional populations, genetic structure analyses, and origin tests.We developed microsatellite markers for genetic structural analyses of  Dorcus hopei [D. hopei hopei, which is distributed throughout central China, and D. hopei binodulosus [D. hopei can be distinguished from other closely-related species by its mandible shape (thick mandible with one inner tooth) in males, and the elyral puncture line in females. D. hopei is one of the largest Coleoptera species in East Asia: males can grow up to 76 mm in the wild [us hopei   have been traded at high prices ,9,10. Thed Lists , and in ed Lists . More reed Lists . It was D. hopei in Korea. For this reason, we decided to analyze the genetic diversity among Chinese, Korean, and Japanese populations of D. hopei.In Korea, there is a thriving trade in foreign beetle populations for cross-breeding. This influx of foreign populations combined with indiscriminate collections of the insect could result in allele frequency change in native Korean populations. This fact caused several requests for developing a monitoring tool to investigate a change genetic diversity of D. hopei, and then microsatellite markers were developed from the results. NGS technique is very useful for the construction of microsatellite loci libraries at a lower cost and far more quickly than traditional cloning-based approaches [D. hopei populations.Analyses of genetic diversity using microsatellite loci have been carried out for various eukaryotes ,17,18. Mproaches ,28,30. TBy Illumina sequencing of genomic DNA, we generated 407,070,351 base pairs from 29,383,396 reads, with an average of 248 base pairs . Then thD. hopei populations (16 samples from Shichuan (China), 17 from Guangxi (China), 20 from Wanju (Korea)). However, one marker (33136) did not show stable amplification and could not be tested. Nine markers amplified DNA fragments containing allele numbers ranging from 2 to 14 in 53 stag beetles. The linkage disequilibrium analysis on each regional population was conducted. From the result, we did not detected linkage disequilibrium across loci over all samples. Then, we tested the present of null allele , their presence causes a slight underestimate of the average exclusion probability at a locus, but probably not of sufficient magnitude to warrant great concern, but, in p > 0.20, mean “estimated with null” exclusion probabilities can be much higher than the “true” and “estimated without null” values [p < 0.20 could be used for population genetic analysis in this study, but 638128 was excluded.We randomly selected 10 of the 27 primer sets, and tested for marker availability on 53 samples of three regional l allele . Five mi marker 336 did nop = 0.002). Through exact p-values of HWE on each locus, we examined that locus 76181 was out of HWE in all regional populations tested for marker assessment  ranged 0.1267‒0.8651, 0.1333‒1.0000, and 0.1228‒0.8509, respectively. Gene diversity and the PIC were highest in locus 10203, while heterozygosity was highest in locus 76181. Locus 951171 had the lowest values of all three indices . For thesessment . Thus, tectively . The staK was estimated with varying from one to 10, and the ad-hoc statistics Δ(K) [For analysis on genetic differentiation among regional populations, 37 samples from Nonsan, Korea and 6 samples from Nirasaki, Japan were included in this study based on a model-based Bayesian analysis. ics Δ(K)  indicateD. hopei. However, compared with the genetic content frequency of each regional population, the Nonsan population contained all patterns of genetic contents shown in Chinese, Korean, and Japanese populations  were used for a model-based Bayesian analysis. Among them, Nonsan population was provided from a Korean insect breeder. Interestingly, a specimen of Nonsan population showed the biggest body size among tested samples of this study . Compariulations E. As a rWe used a total of 97 specimens, including 16 from Shichuan, China, 17 from Guangxi, China, 21 from Wanju, Korea, 37 from Nonsan, Korea, and 6 from Nirasaki, Japan . Nonsan ® Tissue Kit . DNA quality was checked by electrophoresis on a 1% agarose gel and by spectrophotometry, after which 10 μg of genomic DNA was used for 2 × 300 paired-end sequencing of MiSeq Sequencer . The contigs obtained via Illumina sequencing were assembled to make a partial draft genome using the CLC Genomics Workbench .Genomic DNA for Illumina sequencing was extracted from the thoracic muscle of samples collected from Wanju , Korea, 2 was not added. The amplification profile was as follows: 5 min at 94 °C; 35 cycles of 20 s at 94 °C, 20 s at 60 °C, and 30 s at 72 °C; with a final 7-min extension at 72 °C.Phobos ver. 3.3.12 , a tande2 was not added. The amplification profile was as follows: 5 min at 95 °C; 35 cycles of 30 s at 95 °C, 30 s at 50–55 °C, and 1 min at 72 °C; with a final 7-min extension at 72 °C. Amplicons from each sample were genotyped using a 3730XL DNA analyzer . The sequences on the microsatellite loci of the developed markers were submitted to NCBI Genbank and provided with Genbank assession number (Each forward (sense) primer for genotyping was labeled with 6-carboxyflouorescein at the 5′ end . An avain number .K from 1 to 10; number of iterations 20, Second step: a correlated-allele model with 500,000 of burnin period and 750,000 of MCMC reps after burnin; set K from 2 to 8; Number of iterations 20). Then, ∆(K) was estimated with average of LnP(D). The ad-hoc statistics ∆(K) [The summary statistics and Hardy-Weinberg equilibrium of each locus were estimated using PowerMarker ver. 3.5 . We asceics ∆(K)  was usedD. hopei which had no genomic DNA information available. According to PCR efficiency tests, 27 showed polymorphic patterns in electrophoresis analyses. 10 of 27 markers were randomly selected for genotyping and results from seven markers were used on the final analysis.In this study, we used NGS to develop microsatellite markers, which is more cost-effective and quicker to construct a genomic DNA library using NGS than implementing traditional library-based strategies . We testD. hopei. Notably, relatively few studies exist on the population genetics of D. hopei, despite the high market value of the species as a pet in Korea and Japan. The microsatellite markers could be used for population structure analyses.As a result, we designed new species-specific microsatellite markers that could provide the basis for future conservation projects with