Here we introduce a new algorithm for transforming a genetic distance matrix that reduces the within-population variation considerably. Extensive computer simulations revealed that the transformed matrix captured the genetic population differentiation better than the original one which was based on the T1 statistic. In an empirical genomic data set comprising 2,457 individuals from 23 different European subpopulations, the proportion of individuals that were determined as a genetic neighbour to another individual from the same sampling location increased from 25% with the original matrix to 52% with the transformed matrix. Similarly, the percentage of genetic variation explained between populations by means of Analysis of Molecular Variance (AMOVA) increased from 1.62% to 7.98%. Furthermore, the first two dimensions of a classical multidimensional scaling (MDS) using the transformed matrix explained 15% of the variance, compared to 0.7% obtained with the original matrix. Application of MDS with Mclust, SPA with Mclust, and GemTools algorithms to the same dataset also showed that the transformed matrix gave a better association of the genetic clusters with the sampling locations, and particularly so when it was used in the AMOVA framework with a genetic algorithm. Overall, the new matrix transformation introduced here substantially reduces the within population genetic differentiation, and can be broadly applied to methods such as AMOVA to enhance their sensitivity to reveal population substructure. We herewith provide a publically available  to overcome current limitations in reliably detecting population substructure from genetic and genomic data in humans, which can also be applied to any other species. The method was validated by means of extensive demographic simulations. When applied to a real, human genome-wide SNP microarray dataset covering a reasonable proportion of the European continent, we identified previously undetected fine-scale genetic population substructure. Overall, our study thus not only introduces a new method for investigating genetic population substructure in humans and other species, but also highlights that fine population substructure can be detected among European humans. PLOS Computational Biology Methods article.This is a At what degree genetically homogeneous groups of human individuals exist is a long-standing and yet unsolved debate in the scientific community However, detecting genetic population substructure can be complex depending on the evolutionary history of the species in question, and certainly in the case of humans. Certain processes such as isolation by geographic distance Overall, the fact that the vast majority of human genetic variation exists among individuals within populations In the present study, we propose a new matrix distance transformation with the aim to reduce the within-population variation. We conducted extensive computer simulations under two demographic models to test if this aim is achieved. We additionally implemented a genetic algorithm which, in combination with AMOVA statistics, allows searching for the optimal genetic clustering configuration of specimens and populations. We practically test the performance of this new, model-free approach using a genome-wide dataset comprising 2,457 individuals from 23 geographically dispersed subpopulations of Europe. We make this new method for improved genetic population substructure detection publically available as software package for free use.Our algorithm starts with a genetic distance matrix D computed for each possible pair among N individuals, which in this study is derived from the T1 statistic xx,yy denotes the number of SNPs of a particular genotype pattern  and the second individual is homozygous for the alternative allele (1)). Under Hardy-Weinberg equilibrium (HWE), the expectancy E(T1)  = 2/3 if both individuals are unrelated from the same population, E(T1) < 2/3 if the individuals are from different populations and E(T1) > 2/3 if they are more related than by chance. We define the distance matrix as D = 1-T1. That is, we set di,j = 1-T1i,j in order to obtain a genetic distance between individuals i and j.where nIndividuals can then be classified into populations, and the genetic differentiation between populations quantified using this individual distance by applying the Analysis of Molecular Variance AMOVA  frameworwhere K is the number of groups.The estimated values of population differentiation can be transformed into Fst-like statistics, and reflect demographic parameters such as migration rate or time of population split, among others a priori knowledge of the clusters  and without any distance restriction. We do this by transforming the genetic distance D matrix into a new dissimilarity one V, where Vij = Vji = var[di.–dj.] taking into account that dii – dij and djj – dji are excluded during the variance computation. The rationale for proposing the V matrix transformation is as follows:Here we attempt to reduce the within-population variation and maximize the between-population variation without i,j can be decomposed in within- and between-population distances i,I is the distance of individual i to his group I . The mean of the difference between distances is then:with expected variance:ij becomes:Therefore, the variance of the difference of distances for a given pair of individuals from the same group to all the other individuals becomes independent of the distance of each individual to his group, and it is the same for all the elements of the group. In contrast, it can be expected that the distances between individuals from different populations will depend on the topology of the graph and the number of individuals that belong to the same population. For example, consider the simplest case of a graph of two populations ; if i anAndij = d2I,J + 2σ2. Also, notice that if ij = 2σ2. Therefore, in this example population differentiation could only be detected by this statistic when there are at least two individuals in each population so that the distance of each individual to his population can be estimated.Where The pseudocode for computing V is provided in The AMOVA framework has been previously applied to identifying the best genetically homogeneous sets of geographically related populations In order to test the V matrix transformation in a known graph model, we performed simulations on four populations of 10 individuals each, modelling a situation of three parental populations and one admixed population see . In each−8 per nucleotide and generation We also conducted two sets of simulations of increasing demographic complexity to check whether V is more sensitive for detecting population substructure than D and to analyse to what extent the use of V improves the geographic sampling location prediction compared to the use of D. Both demographic models were implemented with the ms software plink --indep 50 5 2 command, and was used for method-comparison analyses. Also, since multivariate techniques such as PCA have shown that unequal sample size can affect the outcome We used a previously published dataset comprising 309,790 SNPs and 2,457 individuals from 23 European subpopulations genotyped with the Affymetrix 250K Xba and 250K Sty SNP microarrays, clusterGem algorithm implemented in the GemTools package which uses spectral graph theory to propose clusters of individuals a priori  has precluded its use for comparative purposes, as all the other used algorithms are unsupervised. We also aimed to run fineSTRUCTURE, another software that uses LD patterns The first analysis consisted of a Classical Multidimensional Scaling MDS; performemap and mapplots.Pie map plots were constructed for each method and each proposed clustering using the R packages The Cramer's V value 2 is the chi-squared value from Pearson's chi-squared test, N is the total of observations, k is the number of rows or the number of columns if less than the number of rows. Cramer's V ranges from 0, which corresponds to random assignment of the individuals of each population to the different clusters, to 1, meaning that each proposed individual cluster perfectly matches one population.where χn) statistic Also, in order to quantify how well the genetic clusters proposed by each method differentiate each sampling location or subpopulation from all the others, we computed the Informativeness of Ancestry  to log(2), indicating that the two sampling locations are perfectly differentiable based on the proposed clusters. Therefore, if a sampling location is perfectly differentiated from any other sampling location based on the proposed clusters, the minimum value that is going to be obtained for all the possible (sub)population comparisons of that particular sampling site is log(2). In contrast, if the sampling location is identical based on the proposed clusters to at least one of the other sampling locations, the minimum In value is going to be 0.IThe complete methodological pipeline is depicted in In the present study, we propose the use of V, the variance in the difference of distances between two individuals to all the other tested individuals, in order to homogenize and minimize the genetic distance within each (sub)population, thus enhancing the between-(sub)population genetic differentiation. This matrix conversion, coupled to a genetic algorithm that uses the AMOVA framework, is then employed to highlight the presence of hidden genetic relationships between individuals and provide clusters of genetically related individuals. We have named this newly developed approach Genetic Algorithm for Genetic Ancestry (GAGA).We started comparing V and D matrices in explaining the between-population variation in a simple case modelling four populations under different scenarios of distances between individuals and populations. As can be seen in Next, we analysed the behaviour of the V and D matrix in genetic data by means of extensive simulations using two of the most commonly applied models in human populations, considering either 10,000 SNPs  see  or 100,0Overall, our simulation experiments demonstrate that V can be used to detect further genetic-geographic population substructure in the cases where the amount of genetic differentiation is particularly small compared to within each population, such as is expected and partly known already in human populations from the European continent.Given these promising results obtained in the computer simulations, we applied our newly developed approach to a previously collected dataset comprising 2,457 individuals from 23 European subpopulations using 133,363 LD pruned genome-wide SNPs n = 0.642, see n = 0). In contrast, Mclust using the first 10 MDS dimensions from the V matrix proposed 37 different genetic clusters, all the populations sharing at least one of the proposed clusters   = 0.122 compared to In using the V matrix (In–V)  = 0.434) and Rome-Italy (In–D = 0.122 to In–V = 434). Running Mclust on SPA based on the original genotype matrix suggested 13 clusters  was smaller than the one obtained when running MDS-V+Mclust. Compared to MDS-V+Mclust, the proposed clusters by GemTools increased the differentiation of Barcelona-Spain, Ancona-Italy, Augsburg-Germany, and Innsbruck-Austria but reduced it in Belgrade-Serbia, Bucharest-Romania, North Greece, Forde-Norway, and particularly in Warsaw-Poland  with equal sample size of 40 individuals. The percentage of closest genetic neighbours in the same (sub)population is similar to the ones when considering all the individuals . Nevertheless, the association between the proposed clusters and the (sub)population samples increases in all the methods. This is particularly pronounced in the case of GemTools see . We wonda priori the (sub)populations, and have shown, by means of computer simulations and application to real European genetic data, that this new approach improves the differentiation among (sub)populations compared to the original distance matrix. A practical result of our analyses is that this matrix transformation improves the output of MDS, both at the level of explained variance and resolution, as well as from the AMOVA estimations. In the present paper we show that GAGA performs reasonably well when using the K proposed by GemTools. One could also consider estimating the K based on parameterized Gaussian mixture models http://www.erasmusmc.nl/fmb/resources/GAGA.We have described a new matrix distance transformation that tends to minimize the within-population variance without knowing Figure S1A) Model of three parental populations and one admixed population, each one with 10 individuals . Eight different possible situations where considered. The edge of each individual to his adjacency population vertex were either all of the same length  or of variable length . The edges connecting two populations were either all of the same length  or of variable length  and also larger than the minimum distance of any individual to his population (GDLI) or smaller (GDSI). For each possible combination, 1000 simulations were conducted. The edge distance of an individual to the adjacency vertex population was randomly modelled using a uniform distribution U. The assumed error in the estimation was computed following a Normal distribution N. The distance between adjacent populations was simulated from a uniform distribution with parameters U if the distance was larger than the minimum individual distance to his population (m) or U if the distance between two adjacent populations was smaller. B) Boxplot of the SS(AP)/SS(T) computed for each of the 1000 simulations conducted for each of the eight possible combinations. In grey, SS(AP)/SS(T) estimations considering the original Distance matrix, computed as the path between two points given their simulated distances to their population of origin and the distances between populations. In black, SS(AP)/SS(T) estimations considering the transformed V matrix, computed out of the original Distance matrix. As can be seen, in all the simulated cases SS(AP)/SS(T) of the V matrix is > SS(AP)/SS(T) of the D matrix.(EPS)Click here for additional data file.Figure S2a priori unknown) (sub)populations. A genetic algorithm is then applied to search for the optimal clustering configuration (procedure 8). The clustering results from GAGA can also be compared with those from other algorithms such as MDS and SPA through procedures 4 and 5.Analysis pipeline applied to the genome-wide data from 2,457 individuals from 23 European subpopulations (EPS)Click here for additional data file.Figure S3Demographic scenarios used to test the performance of V and D matrices. Each simulation consists of 10,000 randomly ascertained SNPs see . A.3 Per(EPS)Click here for additional data file.Figure S4Percentage of variation explained by each eigenvalue from a classical Multidimensional Scaling analysis when using the D (based on the T1 statistic) or the transformed V distance matrix on 2,457 European individuals sampled at 133,363 Linkage Disequilibrium (LD) pruned SNPs.(EPS)Click here for additional data file.Figure S5Best proposed clusters using GAGA setting K = 2, 5, 10, 15 and 23 on 2,457 European individuals sampled at 133,363 Linkage Disequilibrium (LD) pruned SNPs.(EPS)Click here for additional data file.Table S12457 European samples from 23 sampling locations/subpopulations used in the study after the data cleaning performed in (DOCX)Click here for additional data file.Table S2Counts of European individuals showing a mean D < 1/3 (indicating more relatedness to the population than the expected by random mating) and mean D > 1/3 .(DOCX)Click here for additional data file.Table S3Table showing the individuals with the best overall genetic match (BOM) in the same population of sampling or in a different population when using the D statistic based on T1 similarity as measure of genetic dissimilarity.(DOCX)Click here for additional data file.Table S4Table showing the individuals with the BOM in the same population of sampling or in a different population when using the V statistic as measure of genetic dissimilarity.(DOCX)Click here for additional data file.Text S1Supplementary information describing the Pseudocode for the Computation of the V matrix, implementation of the Genetic algorithm for exploring the space of solutions and demographic simulations.(DOC)Click here for additional data file.


Theba on the two Canary Islands of Lanzarote and Fuerteventura. Due to the geological history of both islands, this study system provides ideal conditions to investigate the interplay of biogeography, dispersal ability and differentiation in generating species diversity. Our analyses demonstrated extensive cryptic diversification of Theba on these islands, probably driven mainly by non-adaptive allopatric differentiation and secondary gene flow. In a few cases, we observed a complete absence of gene flow among sympatrically distributed forms suggesting an advanced stage of speciation. On the Jandía peninsula genome scans suggested genotype-environment associations and potentially adaptive diversification of two closely related Theba species to different ecological environments. We found support for the idea that genetic differentiation was enhanced by divergent selection in different environments. The diversification of Theba on both islands is therefore best explained by a mixture of non-adaptive and adaptive speciation, promoted by ecological and geomorphological factors.Island radiations have played a major role in shaping our current understanding of allopatric, sympatric and parapatric speciation. However, the fact that species divergence correlates with island size emphasizes the importance of geographic isolation  in speciation. Based on molecular and morphological data, we investigated the diversification of the land snail genus  A major problem for the study of speciation is that the formation of new and genetically isolated species is in most cases a slow and continuous process, lasting many generations. The direct observation of the entire process of speciation is usually impossible, except in the case of polyploid or hybrid speciation, which can occur in one or a few generations ThebaTheba populations on these two islands are found in allopatry, parapatry and sympatry, displaying different levels of molecular and morphological differentiation Here, we analyzed the divergence of the land snail genus The volcanic archipelago of the Canary Islands is located in the east Atlantic Ocean with Fuerteventura lying approximately 100 km off the West Saharan coast of NW Africa. The archipelago has never been connected to continental landmasses. The eastern-most islands, Lanzarote and Fuerteventura, emerged 24 million years ago (mya) and form one large volcanic edifice separated by shallow waters less than 50 m deep. During periods of glaciation and low sea level in the Quaternary, they were periodically connected by land bridges Theba on the islands has been intra-archipelago diversification, rather than independent colonization of the islands from the African continent Theba species on Fuerteventura and Lanzarote is more extensive than previously thought Theba species of Lanzarote and Fuerteventura, we expand existing COI sequence data and additionally conducted comprehensive morphological and population genetic (AFLP) analyses. As a null hypothesis, we assumed that the long and dynamic history of both islands and the relatively uniform ecological situation along with the low dispersal abilities of land snails, led to isolation by distance (IBD) and eventually allopatric speciation within and among islands. The greater habitat diversity on the southern Jandía peninsula of Fuerteventura Despite the close proximity of NW Africa to the Canary Islands, the main speciation mode of the genus Theba populations extensively on Fuerteventura and Lanzarote. Snails were collected on these islands in December 2009. In total, forty-one populations were sampled along a north-south transect, covering all known genetically distinguishable clades of Theba on Fuerteventura and Lanzarote T. cf. arinagae and T. grasseti from Gran Canaria and T. macandrewiana from the Selvagens Islands  following the manufacturer's protocol. Vouchers are available at the Zoologisches Forschungsmuseum Alexander Koenig, Bonn, Germany.Based on the preliminary results of Greve et al.  Islands . T. macac oxidase subunit I (COI). The COI fragment was amplified by the polymerase chain reaction (PCR) using the primer combination LCO-1490 [5′-GGTCAACAAATCATAAAGATATTGG-3′5′-CCCGGTAAAATTAAAATATAAACTTC-3′At least two specimens per population were sequenced for a fragment of the mitochondrial cytochrome The variation of standard nuclear genes in pulmonates does not provide enough resolution to sort taxa below genus level EcoRI-ACA/MseI-CTG, EcoRI-ACA/MseI-CTT, EcoRI-ACC/MseI-CAC, EcoRI-AGG/MseI-CTG, EcoRI-AGG/MseI-CTC and EcoRI-ACT/MseI-CAG. The fluorescently labeled fragments were separated by electrophoresis on a CEQ™ 8800 capillary sequencer , with an internal size standard . Signal detection, processing and binning of the AFLP electropherograms were carried out using the CEQ™ System Fragment Analysis module of the manufacturer's software . The fluorescence threshold for an accepted signal was set to 1% of the height of the second largest peak detected in the AFLP profile. Choosing a relative threshold instead of the frequently used fixed threshold minimizes artifacts resulting from differences in total profile strength among individuals as well as those resulting from unequal detection among capillaries AFLP markers were obtained with a slightly modified version of the original protocol of Vos et al. To ensure high reliability of AFLP genotyping, 11% of the samples were genotyped twice for all primer combinations; these replicates were taxonomically representative of the whole data set. A perl script was written to fully automate the following marker selection procedure and to estimate the average genotyping error rate per marker . We further tested accurate MOTU assignments among specimens of the COI data set by using the cluster module of TaxonDNA v.1.7.8 T. grasseti and T. impugnata did we include samples from localities that remained genetically uninvestigated.Samples used for morphometrics largely consisted of empty shells . Howeverhttp://www3.Canisius.edu/~sheets/morphsoft.html) and PAST 2.0 Shell morphology was analyzed using geometric morphometrics Single population samples were treated as units only if they were apparently morphologically different, for example FU23 and FU25. Samples composed of two species (hereafter referred to as “mixed samples”) were only used in morphological assignment tests based on foregoing CVAs  to estimate the proportion of each species involved. Similarly, FU17 was only used in a morphological assignment test because of its ambiguous topological position. Except for the genetically identified individuals of LZ23, shells from mixed samples were not included in the overall analysis based on the results of the morphological assignment tests, because of the high rate of incorrect allocations.a priori model of population arrangement, unlike AMOVA, and generates a graph describing the high-dimensional genetic covariance relationships among all populations simultaneously. The Population graph contains the minimal number of edges that sufficiently describe the among population genetic covariance structure, with node size representing the within population genetic variance and edge lengths representing the among population component of genetic variation. As the sample size cut-off value per population is three for Population graphs, populations with fewer than three individuals were excluded from the analysis . We plotted the mean likelihood L(K) over 10 runs for each K and used the statistic ΔK proposed by Evanno et al. We also used Genetic structure of the AFLP data was further investigated using analysis of molecular variance (AMOVA) as implemented in Arlequin v3.5 ST values for all populations of Lanzarote and Fuerteventura were calculated using Arlequin v3.5 To test for IBD, a simple Mantel test Outlier detection among AFLPs was performed with BayeScan 2 = 127.11, d.f. = 372, p>0.999). Phylogenies obtained from ML and BA analyses were highly consistent, with only slight topological differences (T. impugnata and Theba sp. 2 from Lanzarote formed a monophyletic group (Bayesian posterior probability (BPP) = 100%; bootstrap (BS) = 95%) and were sister to all other MOTUs . The monophyletic group of the remaining MOTUs  fell into two subgroups. One subgroup  comprised all populations of the Jandía peninsula on Fuerteventura with Theba cf. clausoinflata “Rock” sister to Theba sp. 5 “Sand”. The other subgroup  consisted of six monophyletic lineages: T. geminata, Theba sp. 4, T. cf. arinagae, T. grasseti, Theba sp. 1a and Theba sp. 1b. Population FU3 was split with one individual belonging to Theba sp. 1a and the other to Theba sp. 1b. Phylogenetic relationships in this subgroup were only weakly supported.In total, 125 specimens were sequenced for COI resulting in a data set of 606 aligned positions. This included the 11 COI sequences from the previously published data set ferences . Both apT. impugnata and Theba sp. 2 formed a monophyletic group (BS = 100%) and were sister to all other MOTUs (BS = 100%), as in the COI tree. In the cluster comprising all remaining MOTUs (BS = 90%), most splits were only weakly supported with BS values <50%. This cluster comprised T. grasseti, T. geminata, Theba sp.1a, Theba sp. 1b, Theba sp. 4, T. cf. arinagae, Theba sp. 5 “Sand” and Theba cf. clausoinflata “Rock”. In the AFLP tree, specimens of FU3 were monophyletic and neither belonged to Theba sp. 1a nor to Theba sp. 1b. In contrast to COI, Theba sp.1b was paraphyletic as specimens of FU7 formed an independent monophyletic lineage in the AFLP phylogeny. In the Jandía group, Theba cf. clausoinflata “Rock” was not monophyletic. FU13, FU18, FU23, and FU25 formed a separate lineage and were closely related to Theba sp. 5 “Sand”. Moreover, FU17 was placed within Theba sp. 5 “Sand” and did not belong to Theba cf. clausoinflata “Rock” as suggested by COI. Most of the basal nodes within the Jandía subgroup had a BS value <50%.The AFLP data set consisted of 625 specimens, each scored for 1964 loci. Though the AFLP topology was different from that of COI, it supported nearly the same MOTUs . T. impuT. grasseti, T. geminata, Theba sp.1a, Theba sp. 1b, T. cf. arinagae, Theba sp. 5 “Sand” and Theba cf. clausoinflata “Rock”) fully agreed with the a priori identified MOTUs of the phylogenetic reconstruction of the COI sequences  . We preferred the F-test over an ANOVA due to unequal variances. In Tukey's pairwise post-hoc tests, only <0.0001) .Theba sp. 1a) to 95.2% (T. cf. arinagae). However, the assignments were unambiguous and statistically significant in only 141 of the 961 (14.7%) cases, reflecting the high degree of morphological similarity among the MOTUs  and all remaining populations (subgraph 2).The Population graph of 34 ubgraphs , indicatStructure v2.3.2 were largely congruent with those of previous molecular analyses of the present study. The mean likelihood L(K) increased from K = 1 to a maximum value at K = 13 (−340259.27) and then decreased to a minimum value at K = 45 (−4266627.79), whereas the variance of L(K) between runs increased for larger Ks , K = 3 (ΔK = 550.49) and K = 4 (ΔK = 194.65). The highest mean likelihood value of L(K) at K = 13 was confirmed by a fourth peak of ΔK = 20.26 (Structure (from the run at each K with the highest likelihood) for K = 2, 3, 4 and 13 are shown in K = 2, individuals of Theba sp. 2 and T. impugnata grouped into one cluster and all remaining individuals into the other cluster. At K = 3, individuals of T. geminata were assigned to a separate third cluster. At K = 4, a fourth cluster comprised all individuals sampled on the Jandía peninsula. In the run that had the highest likelihood at K = 13, nine clusters corresponded to MOTUs identified by the prior molecular analyses (above): Theba sp. 5 “Sand”, T. cf. clausoinflata “Rock”, Theba sp. 4, Theba sp. 1a, Theba sp. 1b, T. grasseti, T. geminata, T. impugnata and Theba sp. 2. Individuals of LZ18 and of Theba sp. 2 of LZ23 were assigned to an additional cluster, as were individuals of Theba sp. 1a of LZ23. Furthermore, individuals of FU26 grouped into a separate cluster. Another cluster did not correspond to any population or MOTU and comprised two individuals of FU4 and one specimen of T. macandrewianaResults of the Bayesian clustering analyses using arger Ks . The sta = 20.26 . The graK = 13, most individuals were assigned to one cluster with 70% to 99% probability. Nevertheless, some individuals showed high levels of admixture and had proportions much lower than this. Individuals of the cluster T. impugnata were highly admixed and showed proportions of up to 62% of the cluster Theba sp. 2. Theba sp. 2 included populations  in which individuals had levels of admixture >49% with cluster LZ18 & LZ23. The assignment of FU7 and FU5 to a single cluster was not obvious. FU7 showed mixed ancestry with proportions of the clusters Theba sp. 4 (24–48%) and Theba sp. 1b (24–75%). Though individuals of the population FU5 were mainly assigned to the cluster Theba sp. 1a, some individuals showed levels of admixture of up to 68% of the cluster Theba sp. 1b. Mainly assigned to Theba sp. 5 “Sand”, FU17 were admixed and showed proportions of the cluster T. grasseti. Corresponding to the COI phylogeny, FU25, FU23, FU18 and FU13 were associated with T. cf. clausoinflata “Rock”, but additionally had proportions of the clusters Theba sp. 5 “Sand” and T. grasseti. Both specimens of FU3 grouped into Theba sp. 1b, although one individual was admixed and showed proportions of the clusters Theba sp. 1a and T. geminata. Neither specimens of T. cf. arinagae nor those of T. macandrewiana were assigned to a discrete genetic cluster. T. cf. arinagae grouped with highest proportion into T. cf. clausoinflata “Rock”, but it was highly admixed and showed proportions of the clusters Theba sp. 4, T. grasseti and Theba sp. 1b. T. macandrewiana was split with one individual assigned to the cluster T. grasseti and the other to the cluster, which did not correspond to any population or MOTU  T. geminata and populations of T. impugnata and Theba sp. 2 (FCT = 0.28). On Fuerteventura, a hierarchical AMOVA showed the highest among group variation between populations of T. cf. clausoinflata “Rock” and Theba sp. 5 “Sand” (14.8%). Whereas genetic differentiation between populations of Theba sp. 5 “Sand” was moderate (FST = 0.05), it was low between populations of T. cf. clausoinflata “Rock” (FST = 0.04). A hierarchical AMOVA indicated moderate genetic differentiation between Jandía populations and populations of the main part of Fuerteventura (FCT = 0.08). Genetic divergence between populations of Theba sp. 1a and Theba sp. 1b was low (FCT = 0.04). A hierarchical AMOVA between Lanzarote and Fuerteventura populations revealed that only 8.4% of the variation was explained by between-group differences. The variation among groups increased to 21.3%, by associating T. geminata from Lanzarote with populations of Fuerteventura. The AMOVA, structured according to the MOTUs suggested by the phylogenetic analyses and the MOTU assignment test, attributed 19.2% of the global variation to differences among MOTUs, and 7.1% to differentiation among populations within MOTUs. All fixation indices were significant. Conversely, hierarchical AMOVA among populations of Theba sp. 2 and T. impugnata revealed no significant genetic differentiation. In the light of the results of the Population graphs and Structure analyses, we further investigated genetic structure within Theba sp. 1a. LZ23 of Lanzarote and FU26 of the Isle of Lobos  and b) Theba sp. 5 “Sand”  from the data set. Finally removing T. geminata induced the highest correlation value  and indicated strong patterns of IBD among populations of Theba sp. 1a, Theba sp. 1b, Theba sp. 4 and T. cf. clausoinflata “Rock” on Fuerteventura. A separate Mantel test of all populations from Lanzarote yielded the lowest correlation value . Excluding T. geminata from this data set, increased the correlation value to r = 0.75 (p<0.001).A Mantel test including all populations of Lanzarote and Fuerteventura indicated evidence for IBD  . The corTheba sp. 4 and T. impugnata, however, were each represented by only one population. Thus, consistent outlier loci detected in the three MOTU pairs Theba sp. 4/Theba sp. 1b, T. impugnata/Theba sp. 4, and T. geminata/Theba sp. 4 were not further considered, as they were potentially linked to population-specific demographic history, unrelated to ecological pressure. BayeScan identified three consistent outlier loci  between populations of Theba sp. 5 “Sand” and populations of T. cf. clausoinflata “Rock”, indicating genotype-environment associations (GEAs) on the Jandía peninsula. Population comparisons within MOTU pair Theba sp. 5 “Sand”/Theba sp. 1b revealed one (1488) and within MOTU pair Theba sp. 5 “Sand”/Theba sp. 4 three consistent outlier loci . Though MOTU pair Theba sp. 5 “Sand”/Theba sp. 4 involved always the same population of Theba sp. 4 in each comparison (as explained above), two of the three consistent outlier loci were 1488 and 1801. These loci were apparently linked to populations of Theba sp. 5 “Sand”.BayeScan detected outlier loci in almost every population comparison. The average number of outlier loci was highest in MOTU pairs of Fuerteventura and lowest in those of Lanzarote . ConsistTheba are described from Fuerteventura and Lanzarote - the flat-shelled T. impugnata and the globular-shelled T. geminataTheba populations on Lanzarote and Fuerteventura displayed little divergence in shell morphology. Apart from the flat-shelled T. grasseti from Gran Canaria, a PCA based on ten shell parameters largely separated only the flat-shelled T. impugnata (Lanzarote) and snails from the Pico de la Zarza (FU25) from all remaining globular-shelled snails  and northern populations (LZ14 and LZ15). The populations in between  displayed mixed ancestry suggesting gene flow among adjacent populations due to the lack of reproductive isolation   among populations on Fuerteventura . Structuand FU7) , the ranJandía populations were distinct from populations on the main part of the island , indicatTheba on Fuerteventura and Lanzarote were probably driven mainly by non-adaptive allopatric differentiation.In all cases the BayeScan analyses did not found any consistent outlier loci, suggesting that differentiation processes of Speciation in non-adaptive radiations is often slow. It depends on the accidental occurrence and fixation of different alleles in allopatric populations in ecologically similar environments. Many allopatric populations hybridize when they meet in secondary contact zones Theba sp. 5 “Sand” and T. cf. clausoinflata “Rock” are parapatrically distributed on the Jandía peninsula without any obvious geographical barriers. Both formed stable genetic clusters with great genetic differentiation from all other Fuerteventuran MOTUs  and possibly ecologically driven differentiation  and the upper parts of Degollada de Vinamar (FU23) as well as in rocky areas near the coast (FU13 and FU18) were associated with 5 “Sand”  and 6. HDataset S1AFLP binary character matrix including replicates.(TXT)Click here for additional data file.Figure S1Box plots of centroid size for each Theba MOTU. The horizontal line represents the mean, box margins are at the 25th and 75th percentiles, and bars extend to the 5th and 95th percentiles.(DOC)Click here for additional data file.Figure S2Estimation criteria for the number of genetic clusters in the AFLP data set. (A) K vs. mean L(K) with standard deviation (SD) from 10 replicates for each K. (B) K vs. ΔK Click here for additional data file.Table S1Summary of specimens used in the present study.(DOC)Click here for additional data file.Table S2Summary of AMOVA with and without different hierarchies. Populations with fewer than 5 individuals were excluded from analysis due to small sample size (see size see . MOTUs c(DOC)Click here for additional data file.Table S3Canonical variates analysis (CVA) based assignment success.Theba MOTUs along rows, CVA groups along columns.(DOC)Click here for additional data file.Table S4Results of the simple Mantel test analyses. In the analyses matrices of geographical distance (km) were compared to genetic distances (FST).(DOC)Click here for additional data file.


Atelomastix bamfordi, found on five of these Banded Iron Formations at two mitochondrial loci and 11 microsatellite loci. Strong phylogeographic structuring indicated the five populations became isolated during the Pleistocene, a period of intensifying aridity in this landscape, when it appears populations have been restricted to pockets of moist habitat provided by the formations. The pattern of reciprocal monophyly identified within the mtDNA and strong differentiation within the nuclear microsatellite data highlight the evolutionary significance of these divergent populations and we suggest the degree of differentiation warrants designation of each as a conservation unit.The Yilgarn Banded Iron Formations of Western Australia are topographical features that behave as terrestrial islands within the otherwise flat, semi-arid landscape. The formations are characterised by a high number of endemic species, some of which are distributed across multiple formations without inhabiting the intervening landscape. These species provide an ideal context for phylogeographic analysis, to investigate patterns of genetic variation at both spatial and temporal scales. We examined genetic variation in the spirostreptid millipede,  Islands provide a unique context for studying the evolutionary processes that drive species distributions. They are natural laboratories, allowing examination of processes of speciation, and patterns of colonisation, persistence, dispersal and extinction Inferring the evolutionary history of terrestrial island endemics can be difficult given that isolation is not always absolute, either spatially and temporally. Dispersal events can occur across valleys and lowlands for mountain-top endemics or over mountains for valley floor endemics, depending on the vagility of the organism and their environmental requirements Eucalyptus caesia, endemic to granite outcrop ‘islands’ of Western Australia. This species has high levels of genetic divergence with little geographic pattern to the distribution of chloroplast haplotypes, reflecting long-term isolation and persistence without connectivity and emphasising the role of genetic drift in this landscape Restricted gene flow between island populations over long periods of time, will result in substantial genetic divergence due to genetic drift and/or, local adaptation The Yilgarn Banded Iron Formations (BIFs) of south-western Australia are ancient, island-like rock outcrops that provide an ideal system in which to investigate island population dynamics. They border the transitional rainfall zone, a biogeographic region separating the high rainfall forest region from the arid interior and are characterised by high species endemism and richness Historically, the altitudinal relief of BIFs and their complex structure, including deep valleys and shaded gullies as well as exposed outcrops and talus slopes Atelomastix bamfordi, known to occur on five BIFs on the Yilgarn Plateau in Western Australia. Millipedes lack the waxy cuticle that protects other arthropods from desiccation and are reliant on moist environments for survival Atelomastix from the family Iulomorphidae, is a predominantly south-western Australian genus with many species distributed across the wetter parts of the southern and south-western coastline and mesic inland Ranges, including the Stirling and Porongorup Ranges 2) Atelomastix bamfordi is the most easterly occurring member of this genus. It inhabits moist habitats provided by BIFs, such as the base of rocky slopes, under large rocks and under dense leaf litter. The life cycle is probably annual with adult millipedes dying prior to, or during the harsh summer months (pers. comm. M Harvey). The species has been reported as abundant on the large Koolyanobbing Range We investigated phylogeographic pattern in the spirostreptid millipede A. bamfordi may have repeatedly come into contact through population expansion associated with historical climate change in this landscape. If this were the case, we would expect periods of gene exchange between neighbouring BIF populations to result in a pattern of isolation-by-distance, where proximate populations are more genetically related, or, if gene exchange has been extensive, to genetic homogeneity of populations Although unconnected today, BIF populations of A. bamfordi to investigate evolutionary relationships and patterns of genetic diversity and structure across BIF populations. Our goals were:We evaluated the genetic variation present in To determine patterns of genetic differentiation among the five known BIF populations and to use those data to infer the impact of historical processes on the distribution of millipedes across the landscape.To assess genetic diversity and structure to determine how limited dispersal capabilities affects structure within BIF millipede populations.To use patterns of genetic differentiation, both within and among BIFs to inform conservation and management of this species.A. bamfordi had been recorded from four of the Yilgarn BIFs: Koolyanobbing (KOO), Windarling (WIN), Mt Jackson (MTJ) and the Die Hardy Range (DH)  A. bamfordi . We also searched any water-gaining or densely vegetated sites between BIFs and although these recovered other millipedes from the genus Antichiropus, A. bamfordi was not found. Thus, to the best of our knowledge, A. bamfordi populations are restricted to BIF habitat and are not presently connected by populations in intervening habitat. The field study did not involve any endangered or protected species and none of the field sites from which we sampled (i.e. excluding KOO and WIN) required access permission, with the exception of Mt Jackson  and Mt Manning ). A license to take fauna for scientific purposes was obtained prior to sampling from DPaW. GPS coordinates of the sampling locations are provided in In total, 77 individuals from five BIFs were sequenced at two mitochondrial regions  and genotyped at 11 nuclear microsatellite loci. DNA was extracted from the legs or from the crushed heads of juvenile specimens stored in 100% ethanol using a Qiagen DNeasy Kit, or a salt-based DNA extraction protocol 5′TAAACTTCAGGGTGACCAAAAAATCA3′) 5′CGCCTGTTTTTCAAAAACAT3′) and 16Sbr (5′CCGGTTTGAACTCAGATCATGT3′) 2, 200 μM dNTP's, 0.4 μM of each forward and reverse primer, 0.25 μg of Bovine Serum Albumin (Fisher Biotech), 0.3 U of Platinum Taq DNA Polymerase (Invitrogen) and approximately 20 ng/μl DNA. The thermal cycler profile for both CO1 and 16 S involved an initial denaturation at 94°C for 3 min, followed by 35 cycles of 94°C for 30 sec, 46°C for 30 sec and 72°C for 30 sec followed by a final extension at 72°C for 2 min. PCR products were purified using an UltraClean PCR Cleanup kit  and the cleaned product was quantified using a Nanodrop (Nanodrop Technologies). Sequencing reactions (1/8) were carried out in 10 μl volumes containing 1 μl of Big Dye Terminator, 1.5 μl of 5× sequencing buffer, 1 μl of 3.2 pmol primer and approximately 40 ng of purified PCR product. Thermal cycling conditions for sequencing reactions involved an initial denaturation at 96°C for 2 min, followed by 25 cycles of 96°C for 10 sec, 46°C for 5 sec and 60°C for 4 min. Sequenced products were cleaned prior to electrophoresis using a standard ethanol precipitation method (Applied Biosystems). Products were sequenced on an Applied Biosystems 3730 capillary sequencer (Murdoch University).We sequenced two partial regions of the mitochondria, the Cytochrome Oxidase Subunit 1 (CO1) and the large Ribosomal Subunit 16 S. For amplification of CO1 we used the Folmer primers LCO1490 (5′GGTCAACAAATCATAAAGATATTGG3′) and HCO2198 , and nucleotide divergence (Jukes and Cantor) between populations were calculated in DnaSP v. 5.10 To test for isolation by distance within BIF populations using the combined sequence data, we conducted mantel tests in R using the Vegan package A. bamfordi. This was confirmed with all populations showing significant deviation from Hardy-Weinberg equilibrium, with the exception of Windarling, where individuals had been sampled in close proximity to one another. Rarefied allelic richness provided a better estimator of genetic diversity, given the sampling, and was calculated in HP-Rare v 1.0 Genotyping of the 11 microsatellite markers was carried out according to Nistelberger et al. C) To further reconstruct the phylogenetic relationships of populations using microsatellite data we generated Cavalli-Sforza chord distances . The variation was composed of 54 transitions, eight transversions and two multistate substitutions. The 16 S region yielded 24 haplotypes from the 77 individuals sequenced and included 21 transitions, one transversion and one single base pair indel. Combining the two regions resulted in a total, aligned sequence length of 1114 bp and 48 haplotypes. The most prevalent haplotype (Hap 47 WIN) had a frequency of 23%, followed by Hap 35 (MTJ) and Hap 39 (HA) with frequencies of 8%, and Hap 33 (MTJ) and Hap 40 (HA) with 6%. The remaining haplotypes were only found in one or two individuals. Measures of genetic diversity were consistently lowest in the Windarling population and highest in Koolyanobbing. Haplotype diversity ranged from 0.295 (WIN) to 0.986 (KOO) with an average of 0.794. Nucleotide diversity ranged from 0.06% (WIN) to 8.5% (KOO) with an average of 4%. No populations departed from the neutral model of evolution except for Windarling (D = −1.775) . MeasureThere was a large and highly significant degree of genetic structuring of the mitochondrial genetic diversity, with most variation (AMOVA) occurring among BIF populations (71.56%) rather than within (28.4%). The greatest genetic divergence occurred between the Mt Jackson and Helena Aurora populations (approx. 40 km apart) and the least between the two most spatially isolated populations, Koolyanobbing and Die Hardy (approx. 100 km apart) , Fig. 1.Microsatellite genetic diversity was low, both within and amongst BIF populations. Rarefied allelic richness ranged from 1.89 (HA) to 3.28 (KOO) with an average of 2.47. There was a highly significant degree of structuring of the microsatellite diversity with the majority of variation (68.11%) maintained within populations, compared to (31.89%) among populations.A. bamfordi, with minimal sharing of CO1 and 16 S haplotypes amongst individuals within BIF populations and no sharing of haplotypes between populations. Bayesian analysis identified five genetic clades in which populations were reciprocally monophyletic, with the exception of Koolyanobbing and Helena Aurora for which some samples were paraphyletic  or gene flow (migration). The three models with the highest AIC support all indicated there was no historical migration between the two populations .Mantel tests of pairwise sequence differences against geographic distance indicated significant isolation by distance within the Koolyanobbing (r = 0.740 p = 0.0001), Mt Jackson (r = 0.225 p = 0.0375) and Helena Aurora (r = 0.399 p = 0.0025) populations.Bayesian cluster analysis identified four genetic clusters in the microsatellite data. The first corresponded to the Die Hardy and Mt Jackson populations, and the remaining clusters to each of the three other populations  . FurtherA. bamfordi has revealed strong genetic differentiation between BIF populations, with mtDNA genetic lineages corresponding to each of the five BIF populations except for six individuals from Koolyanobbing that were paraphyletic with the Helena Aurora Range due to incomplete lineage sorting. Microsatellite data were broadly consistent with this result, identifying four genetic clusters, the first of which was further broken down into individual populations.Phylogeographic analysis of A. bamfordi, these studies emphasise the role of genetic drift in driving population differentiation. For example, mitochondrial and nuclear sequence data revealed extraordinarily strong phylogeographic structure in populations of trapdoor spiders (Moggridgea tingle) in south-western Australia, often situated just kilometres apart. Molecular dating suggested these populations became isolated in the mesic valleys and uplands of the Porongorup and Stirling Ranges following the onset of aridity in the late Miocene A. bamfordi, reciprocally monophyletic lineages across three geographic locations highlighted the reproductive isolation of M. tingle populations but the pattern emphasized a more ancient division, with monophyly observed in both mtDNA and the more slowly evolving nuclear genome Geocrinia lutea and G. rosea, also described patterns of extremely low dispersal and long-term isolation between habitat ‘islands’, with divergence attributed to isolation via range changes resulting from climate change rather than geographical barriers Habronattus pugillis occupies woodland habitat at altitudes above 1400 m but is absent from the lowlands. Using mtDNA, Masta A. bamfordi, smaller populations of H. pugillis formed monophyletic clades whereas larger Ranges showed evidence of paraphyly. Like A. bamfordi, this was ascribed to incomplete lineage sorting rather than resulting from migration The lack of correlation between genetic divergence and geographic distance, with the two most spatially isolated populations showing the least genetic divergence, suggests there has been little, to no connectivity of BIF populations following their separation. This result was emphasized in the Bayesian analysis which showed high support for genetic clades but poor support for the relationships between clades . It is aA. bamfordi clades at 0.7 to 1.1 million years ago during the Pleistocene. The timing coincides with known increases in aridity in the transitional rainfall zone (TRZ) due to climatic fluctuations associated with Milankovitch cycles during this period Molecular dating with the arthropod clock rate has placed the separation of The process of genetic drift acting independently on each BIF population is reflected in different patterns of genetic divergence and diversity seen in the mtDNA data. The smaller populations, Mt Jackson and Windarling, and the larger population Helena Aurora, which had less suitable millipede habitat, showed lower genetic diversity and higher levels of genetic divergence than the larger populations (KOO and DH). These three BIFs have probably harboured historically small effective population sizes, owing to the limited availability of moist sites, increasing their susceptibility to forces of genetic drift driving divergence Rapidly evolving microsatellite markers can provide a more contemporary view of BIF population dynamics. The information we gained from these markers was limited by a lack of Hardy-Weinberg equilibrium within our BIF populations yet we still identified patterns in genetic diversity that appear to support the impact of genetic drift on populations: lower genetic diversity in BIF's likely to have had small effective population sizes . Signals of isolation by distance (IBD) were seen in some of the BIF populations , but these were weak and likely to be heavily influenced by limited sample sizes. The small pairwise distances between samples at Windarling explains the lack of IBD seen in this BIF, but we were surprised to see evidence of IBD in the Helena Aurora and Mt Jackson individuals. Here, we expected limited gene flow to result in a pattern of ‘islands within islands’, where significant isolation has resulted in genetically divergent populations within BIFs that do not correlate with geographic distance. An increased number of samples from more locations would be required to determine whether IBD is really occurring at these spatial scales.The evolutionary significance of geographically isolated genetic lineages has long been recognised and conservation biologists have attempted to formalise this by delineating conservation units within a species such as Evolutionary Significant Units (ESUs) and Management Units (MUs) st century indicate increasing temperature, decreasing rainfall and a greater incidence of fire Although it is difficult to predict future climate change at such fine scales, broad-scale models for this region over the 21This is the first phylogeographic study conducted on a species inhabiting multiple Banded Iron Formations in this landscape and provides evidence that the disjunct populations have experienced long-term isolation following their separation during the Pleistocene. The divergence of populations during this period coincides with increases in aridity and emphasizes the role of climatic instability along with topographic features in driving differentiation and ultimately speciation in this landscape. We consider the strong phylogeographic structure and evidence of restricted gene flow between BIF populations warrant the designation of all five populations as distinct conservation units.Table S1Specimen information, including spatial coordinates from UTM zone 50 J and haplotype number based on combined CO1 and 16 S mtDNA data. Samples from Windarling and Kooylanobbing (bold) are from specimens lodged at the Western Australian Museum, registration numbers shown (WAM_T).(DOCX)Click here for additional data file.Table S2The three, best-fit models determined in IMa2 for tests of migration versus isolation between the paraphyletic populations Koolyanobbing and Helena Aurora. Results are based on mtDNA variation.(DOCX)Click here for additional data file.


Brachyteles hypoxanthus) is a critically endangered New World monkey and a flagship species for the conservation of the Atlantic Forest hotspot. Yet, like other neotropical primates, little is known about its population history and the genetic structure of remnant populations. We analyzed the mitochondrial DNA control region of 152 northern muriquis, or 17.6% of the 864 northern muriquis from 8 of the 12 known extant populations and found no evidence of phylogeographic partitions or past population shrinkage/expansion. Bayesian and classic analyses show that this finding may be attributed to the joint contribution of female-biased dispersal, demographic stability, and a relatively large historic population size. Past population stability is consistent with a central Atlantic Forest Pleistocene refuge. In addition, the best scenario supported by an Approximate Bayesian Computation analysis, significant fixation indices , and population-specific haplotypes, coupled with the extirpation of intermediate populations, are indicative of a recent geographic structuring of genetic diversity during the Holocene. Genetic diversity is higher in populations living in larger areas , but it is remarkably low in the species overall (θ = 0.018). Three populations occurring in protected reserves and one fragmented population inhabiting private lands harbor 22 out of 23 haplotypes, most of which are population-exclusive, and therefore represent patchy repositories of the species' genetic diversity. We suggest that these populations be treated as discrete units for conservation management purposes.Social, ecological, and historical processes affect the genetic structure of primate populations, and therefore have key implications for the conservation of endangered species. The northern muriqui ( The genetic structure of primate populations is affected by a number of intrinsic and extrinsic factors, including grouping patterns, sex-biased dispersal, dispersal distances, genetic drift, effective population size and past demographic events such as bottlenecks www.iucnredlist.org). The history of the forest is marked by contraction/expansion cycles thought to be caused by climatic oscillations during the Pliocene and Pleistocene, which likely resulted in three distinct biogeographic domains, or Pleistocene refuges, according to analyses of phylogeography and niche modeling The Brazilian Atlantic Forest is known for its rich biodiversity, which includes 20 endemic primate species (Brachyteles spp.), one of the endemic primates found in the Atlantic Forest Ateles, Lagothrix, and Oreonax). The genus Brachyteles includes probably the largest living neotropical primate, which reach over 1.0 m in body length B. hypoxanthus, the northern muriqui, and B. arachnoides, the southern muriqui The muriqui (www.sosmatatlantica.org.br). This recent disturbance has had inevitable consequences for the biome’s fauna and flora The Atlantic Forest is known as the fourth ranked global biodiversity hotspot Social structure, sex-biased dispersal, fission-fusion patterns, group and population sizes are known to contribute to different patterns of genetic structure in social mammals Genetic diversity is key for a species to persist and maintain evolutionary potential in the long run Fecal samples were collected noninvasively between July 2002 and December 2004 from 151 free-ranging animals in eight geographic sites , Table 1Two of these populations are composed of multiple social groups and some of these groups have been the subjects of long-term studies . Whenever information on groups was available, and the sampling of groups was adequate, we were able to evaluate and compare the genetic differentiation among them .Total genomic DNA was extracted using the QIAamp DNA Stool Mini Kit (Qiagen) following the manufacturer’s protocol. PCR amplification using the species-specific primers Mono1 and Mono2 produced an internal section of 366 bp that bears the first hypervariable segment (HVSI) of mtDNA as previously described B. hypoxanthus sequence from GenBank (AF213966) was used as a reference for alignment and haplotype determination. Haplotype determination and population comparisons were performed in ARLEQUIN 3.01 h) and nucleotide diversity (π) The sequences were aligned using CLUSTAL W versus small habitat patches was significantly different. We first inferred accumulation curves of haplotype richness for two sets of populations that were represented by at least 10 individuals. The first group was comprised of the populations found in areas larger than 2,000 ha . The SMJ population is comprised of small forest fragments interconnected with the total size of the area exceeding 2,000 ha  2,000 ha . The secCT), among social groups within populations (ΦSC), and within social groups among populations (ΦST). Statistical significance was assessed with 16,000 permutation steps. Populations represented by a small number of samples  were excluded from this analysis. Because an exploratory phylogenetic analysis (not shown) indicated that there were no population sub-aggregations, the AMOVA included no division of groups of populations .Analysis of Molecular Variance (AMOVA) was implemented in ARLEQUIN 3.01 using the model of Tamura and Nei P-value of the test. We repeated this analysis for each social group assuming the expected frequencies of each haplotype to be equal to the observed population frequencies. In addition, to evaluate the contribution of group structure to the distribution of genetic variation we ran 16 AMOVAs, as described above, between these two populations. We removed one social group from each population at a time to detect groups that maximized the ΦSC. We used the serial goodness-of-fit plus method http://webs.uvigo.es/acraaj/SGoFMethod.htm).Because the RPPN-FMA and SMJ populations were sampled across different social groups, we tested whether both their overall and within-group haplotype compositions were randomly distributed. First, we compared the haplotype frequencies in the overall sample with a chi-square test. We assumed an extrinsic expectation in which all haplotypes should be found in equal frequencies proportionate to sample size (i.e. expected haplotype frequency  =  N haplotypes/N samples). To control for small sample size we first generated 10,000 random replicates from the sample frequencies (N = 64 for RPPN-FMA and N = 32 for SMJ) and then recalculated the chi-square for each replicate. The proportion of replicates with chi-square values greater than or equal to the observed value is the STTo evaluate whether social groups within the SMJ and RPPN-FMA populations are homogenous as a result of female dispersal, we used pairwise ΦST) and geographic distances (Km) as implemented in IBDWS 3.15 http://www.fluxus-engineering.com/sharenet.htm) in order to depict haplotype relationships and explore the association of haplotype groups with geography.Genetic differentiation due to isolation by distance was tested using the Mantel test SFFD and F2Rg) in a coalescent framework using the Bayesian module in LAMARC 2.1.3 Ateles (see Substitution rate) was used in BEAST. We ran the program for 100 million generations, with a sampling interval of 5,000 generations. Finally, we tested nine alternative scenarios for the diversification of four muriqui populations using the Approximate Bayesian Computation (ABC) approach implemented in DIYABC 1.0.4.38beta We adopted a four-step approach to infer changes in the population size of northern muriquis. First, we calculated the neutrality tests efN) was estimated using the formula ef = θ/2μN, where μ is the substitution rate per site per generation and θ is the mutation-scaled effective population size. θ was estimated with the coalescent-based methods implemented both in LAMARC and MIGRATE-N 3.2.1 th step. In MIGRATE, we ran 50 replicates of one long chain containing 10,000 samples each, sampling every 500th step. The prior distribution of θ was set as exponential with window . This analysis had a static heating strategy to explore the parameter space more effectively . The initial 10% genealogies were discarded as burn-in in all coalescent runs. Convergence for the coalescent analyses was assessed by inspecting the effective sample sizes and the stationarity of posterior distributions in TRACER 1.4.1 The long-term female effective population size (μ) more suitable for atelids using the Ateles HVSI sequences, the topology, the split dates from Collins & Dubach A. geoffroyi subspecies . The probable maximum age of this event is likely to coincide with the closure of the Panama Isthmus about 2.8 mybp −7 to 5.5×10−7 substitutions/site/year (s/s/y). Multiple runs incorporating the recommended adjustments from the output were carried out to check for convergence. The outputs were inspected in TRACER.Fossil and molecular data suggest that the New World monkeys split from Old World monkeys roughly 35-65 mybp numts. All BLAST searches yielded E-values that were very close to zero with the platyrrhine HVSI sequences available, again reinforcing the lack of contamination.It is likely that an orthologous mtDNA copy was sequenced instead of exogenous contaminants or nuclear insertions because: (i) we used a species-specific pair of primers that successively failed to amplify high-quality human DNA; (ii) we detected one single PCR amplicon of the expected size in all individuals; and (iii) no extremely variant sequences were detected. Moreover, fecal samples are richer in mtDNA molecules than they are in nuclear DNA, and the natural degradation of fecal DNA makes nuclear copies even scarcer, reducing the likelihood of amplifying We successfully aligned the 366-bp HVSI segment from 151 newly sequenced northern muriqui individuals from 8 populations with the additional GenBank sequence from FE. Twenty-tree haplotypes (22 newly described) were resolved based on 21 segregating sites . Thirteen sites were parsimony-informative. Haplotype sequences are available in GenBank under accession numbers JF769864-JF769886 .h = 0.905), and the nucleotide diversity was remarkably low (π = 0.0135). Haplotype h16 was found with the highest frequency in the overall sample set (22%) and was twice as frequent as h17, the second most frequent. Both h16 and 17 were exclusive to RPPN-FMA  revealing a finer pattern of genetic structure and indicating that only 51% of the total variation can be found within the social groups sampled. At first glance, a significant amount of the genetic variation seems to be partitioned among social groups within each population . However, when we excluded the group SSB (SMJ), this index dropped substantially and became nonsignificant,  could be a consequence of isolation by distance, however the Mantel test  and RMA analysis (not shown) do not support IBD.The AMOVA yielded high fixation indices between populations . Likewise, although the exponential growth rate estimated in LAMARC has a broad confidence interval, the point estimation indicates at most a rather modest growth. We could not reject a nongrowing population scenario with the LAMARC results because the 95% most probable estimate interval includes zero . The demographic scenario recovered in the BSP . The median substitution rate estimated for Ateles was μ = 3.7×10−8 s/s/y . Assuming a generation time range of 15–20 years  we estimated a point efN = 13,923 females .The coalescent analyses yielded nearly perfect overlap between the LAMARC and MIGRATE estimates of h and very low π both in the total samples and within populations. The low π can be seen directly in the mtDNA sequences with few polymorphic sites, which is likely a consequence of relatively low substitution rate in HVSI and the muriqui long generation times. It is notable that in SMJ, RPPN-FMA and RPPN-MS haplotype diversities are comparatively low (i.e. h<0.8). While RPPN-FMA and RPPN-MS were extensively sampled relative to their respective population sizes, some less sampled populations exhibited a far greater ratio of haplotypes to sample size. This discrepancy was most evident in PESB (7/17), PERD (8/23), and SMJ (7/32), and suggests that genetic variation is associated with habitat size but not necessarily with current population size, as confirmed by the rarefaction analysis.We found high Our results agree with previous works showing that the number of social groups is inversely proportional to the rate of loss of genetic variation owing to increased effects of inbreeding B. hypoxanthus is comparatively low. For instance, after rescaling the HVSI sequences of Alouatta caraya to match the segment of northern muriquis, we found 31 haplotypes in half as many samples as the present study, with comparable indices of h but lower π  and high FST (0.413) in 32 allozyme loci from two Brachyteles populations that are currently considered to be representative of the two species . The results from Pope's analysis suggest that the rapid and recent decline in population size has still not affected the heterozygosity, a result that is corroborated by our high h value.In a study of allozyme diversity, Pope The degree of genetic differentiation among social groups depends on the interaction of processes affecting them when they are first formed and between their onset and their eventual dissolution ST and the complex pattern of formation and distribution of groups in this population. At the onset of the systematic monitoring in 1982, only two groups, the Matão and Jaó groups, were present. The Matão group grew from its original 22 members, including six adult males and eight adult females, to 77 individuals as of January 2005, and it has never fissioned. The Jaó group, by contrast, underwent its first fission event in 1998, which resulted in the Matão 2 (M2) group and a second fission in 2002, which resulted in the Nadir group and included a male unit that still maintained transient associations with both the Jaó and Nadir groups when the genetic samples used in the present study were collected The high field-observed migration rate in RPPN-FMA is in agreement with pairwise ΦAlouatta guariba, S.L. Mendes pers. obs.). Low dispersal rates appear to be associated with isolation by landscape resistance, which includes distance between social groups, forest connectivity, topographic features, and the presence of barriers such as rivers, roads, and pastures in SMJ. They can be also influenced by the small number of females able to disperse.By contrast, SMJ has a total confirmed population size of at least 84 individuals distributed into 13 social groups that occupy small forest fragments from 60 to 350 ha in size. Systematic monitoring of the SMJ population began in 2005, and aerial pictures from the 1970’s and 2002 indicate that fragmentation and deforestation was more severe 40 years ago, when the groups were more isolated than they are today. Dispersal events between SMJ groups are reduced compared to RPPN-FMA groups, which may have contributed to the fixation of haplotype h20 in the SSB group. Although the migration rates estimated with mtDNA should not be regarded as “true” estimates of current gene flow, all indices, and a closer inspection of the raw genetic data, clearly suggest that successful migration among some SMJ groups is either very low when or negligible when compared to RPPN-FMA. The constraints on dispersal in SMJ muriquis are also implied by the sightings of two solitary females on the periphery of their natal groups, where they have been seen engaging in unorthodox interspecific associations with brown howling monkeys , do not share haplotypes with other groups in SMJ, and no females have been observed immigrating into this group. Roads or forest fragmentation may play a role in limiting gene flow between this and other muriqui groups in this population. As is common in atelids, muriquis are extremely adapted to suspensory locomotion via brachiation and by using their prehensile tail as fifth limb; they are also known to cross short distances on the ground The shallow genetic structure observed in muriquis is probably driven by female dispersal and the absence of long-term geographic barriers that could have isolated the populations analyzed in the present study. This is strengthened by the fact that a deeply diverged haplotype (h3) is found in three distant populations . Haplotype sharing between the SMJ and FE populations, which are in the same latitude and span roughly the widest longitudinal distance between any two populations (∼227 km), and the lack of isolation by distance with the ABC analysis results suggest that gene flow existed along forested routes that are no longer available. Nonetheless, the high AMOVA (Φ) fixation indices indicate that the apportionment of genetic diversity within social groups and populations is higher than would be predicted for a species in which females disperse. This implies that at least some level of past genetic structure, higher levels of within-population admixture, random genetic drift in the more recent past effective population size is consistent with previous reports that indicate a past census population size at least one order of magnitude higher than the current size eN = 27,846 individuals, which seems quite high for a species with such a restricted geographic distribution compared to other primates  long-term persistence of forest refugia during Pleistocene climate changes; (ii) female-biased dispersal; (iii) the ability to disperse over significant distances relative to the species’ distribution when the habitat is continuous; and (iv) relatively large effective population size. The recent elimination of intermediate populations because of habitat loss may have created the current lack of clear phylogeographic partitioning even though there are significant differences in haplotype frequencies among populations . We acknowledge, however, that these conclusions are based on a single locus and alternative explanations would also be possible if the mtDNA has been influenced by idiosyncratic processes (e.g. selective sweeps) Given the evidence from this and other studies Brachyteles hypoxanthus has the lowest HVSI diversity hitherto reported for a neotropical primate Click here for additional data file.Table S1Absolute and relative frequencies of haplotypes per population .(DOC)Click here for additional data file.Table S2Polymorphic sites for the HSVI segment in the northern muriqui.(DOC)Click here for additional data file.Table S3Series of 16 AMOVAs excluding one group from both RPPN-FMA and SMJ at a time.(DOC)Click here for additional data file.Table S4Tamura-Nei pairwise genetic distances between haplotypes.Click here for additional data file.Table S5Summary table of genetic diversity parameters of HVSI sequences in northern muriquis and available neotropical primates.(DOC)Click here for additional data file.


Knowledge of human origins, migrations, and expansions is greatly enhanced by the availability of large datasets of genetic information from different populations and by the development of bioinformatic tools used to analyze the data. We present Ancestry Mapper, which we believe improves on existing methods, for the assignment of genetic ancestry to an individual and to study the relationships between local and global populations. The principle function of the method, named Ancestry Mapper, is to give each individual analyzed a genetic identifier, made up of just 51 genetic coordinates, that corresponds to its relationship to the HGDP reference population. As a consequence, the Ancestry Mapper Id (AMid) has intrinsic biological meaning and provides a tool to measure similarity between world populations. We applied Ancestry Mapper to a dataset comprised of the HGDP and HapMap data. The results show distinctions at the continental level, while simultaneously giving details at the population level. We clustered AMids of HGDP/HapMap and observe a recapitulation of human migrations: for a small number of clusters, individuals are grouped according to continental origins; for a larger number of clusters, regional and population distinctions are evident. Calculating distances between AMids allows us to infer ancestry. The number of coordinates is expandable, increasing the power of Ancestry Mapper. An R package called Ancestry Mapper is available to apply this method to any high density genomic data set. Human genetic diversity is a fundamental question in biology, relevant to population genetics, and genome wide association studies. Studies aiming to identify causal disease alleles increase power by including multi-ethnic designs while taking stratification into account – as reported among others by Haiman et al Human diversity and ancestry assignment have been studied by two main methodologies: clustering and principal component analysis (PCA) In this work we present Ancestry Mapper (AM), a new methodology to analyze ancestry. Each individual is characterized by an Ancestry Mapper Id (AMid) which consists of a set of coordinates, each being a measure of similarity to a particular reference population. Distinctive characteristics of AM include: 1) reducing the information needed to characterize an individual from several thousand SNPs to a small, fixed set of numbers, 2) providing built-in ancestry and admixture information, easily assigning continental and regional ancestry, 3) being amenable to clustering with no need to include individuals of known ancestry for cluster labeling, 4) producing barcodes for populations indicating inter and intra-population similarity, 5) assessing the degree of isolation of populations, 6) being data set independent and allowing for inter data set comparisons, and 7) providing global and regional information simultaneously. In Ancestry Mapper each individual is characterized by a small, fixed and meaningful set of numbers, which is comparable across data-sets and allows individuals to be assigned to their genetic ancestry.Ancestry Mapper Ids (AMids) are produced by comparing each individual against population references. We chose the Human Genome Diversity Project (HGDP) as the basis of population references. HGDP is inspired in the work of Cavalli Sforza, who used genetics and linguistics to study populations We applied AM to a joint dataset of HGDP and HapMap to examine global and regional relationships, exploring intra and inter-population heterogeneity, isolation and admixture. The global relationships provide insights about continental groups while information on local relationships were obtained by AMIds of geographical neighbors, identifying the main reasons for similarities and subtle differences .The AMids characterizes individuals by a vector of fixed length (51) with values in a similar range, thereby making it optimal for clustering algorithms. We clustered the AMids of HGDP and HapMap using a robust method, PAM – Partition Around Medoids http://hagsc.org/hgdp/files.htmlhttp://hapmap.ncbi.nlm.nih.govThe HGDP data set is composed of 938 individuals of 51 populations, genotyped using the Illumina platform  and is available at Ancestry Mapper uses a single individual as the reference for each HGDP population; therefore 51 references form the basis of AM. We selected the references by calculating the Euclidean distances between individuals in each population using all selected 289,160 SNPs and then choosing the individual with the smallest median of the distances to all other members.The main blocks are also clear in an hierarchical clustering of the 51 individuals selected as references . The firThese findings illustrate that the references accurately represent the relationships between populations and support the use of references as a world-wide genomic ancestry map.The Ancestry Mapper Id (AMid) is the Euclidean distances of an individual to the 51 references (one per HGDP population); for visualization purposes we normalize AMids . Normalized AMids for HGDP and HapMap individuals are shown in AMids of seven individuals of different origins are shown in AMids of individuals of the same origin, but from different datasets (HGDP/HapMap) show similar results. Both Yoruba have the highest AMid for Yoruba, high values for African references and much lower for other populations. The Japanese show the highest AMid for the Japanese, high values for Asian references and much lower for others. In addition to exploring the ancestry of an individual, AM can be used to examine relative levels of population isolation: the relative isolation of the San and the Papuan is shown as they are the most similar to their own reference and have large distances to the second closest reference.Bi-plots of one AMid against another produce information centered around specific populations. French vs. Mandenka AMids separates the world continental regions quite clearly see , while pAM is dataset-context independent, in the sense that AMids are always the same, regardless of other elements in the dataset. However, AMids could be dependent on the number of SNPs used to calculate the distance to the references or on the actual SNPs used. To investigate this issue we calculated AMids for several individuals using randomly selected SNPs. We observe that for 1,000 SNPs the variance is quite substantial, decreasing when the number of SNPs is increased up to 20,000 SNPs see . We calcFrom the combined data of HGDP and HapMap see  we visuaAfrica has two sub-blocks: the hunter gatherers  and agriculturalists . The distance to the six African references provides a global view of human migration and the out-of-Africa expansion of modern humans The populations from NA, ME, Europe and CSA form a large block with 3 sub-blocks . The Mozabites, the single North African population in HGDP, are closer to the Middle East than to the sub-Saharan populations. Many Europeans have several high AMids showing their low degree of isolation. CSA individuals have the lowest AMids to their own references, reflecting high gene flow during the last 80,000 years, with populations migrating and settling from many directions and contributing to numerous expansions The East Asians show several high AMids with a South/North Asia pattern, which is gradual and continuous, suggesting gene flow between these populations. Although not geographically close neighbors, the Hazaran and Uygur are very similar to one another, as previously reported Isolated populations can be identified in AMids of individuals of African origin show that HG differ from the other African populations see  as previThe agriculturalists are similar to each other, with the Bantu the closest to the HG. The gene flow between agriculturalists and HG is the highest between Bantu and Biaka Pygmies as suggested by the reciprocal genetic similarity.The African Americans from the Southwest of the US (ASW) and the Masai, from Kenya (MKK) show the highest ME/European/CSA AMids. For MKK this could be explained by a Neolithic farming migration from ME to Africa, or a more recent Arab migration The closest populations to the sub-Saharan block are the Mozabite, Palestinian, Bedouin and the Makrani. The first three populations are geographically close to sub-Saharan Africa, while the similarity with the Makrani, from Balochistan, Pakistan, may be explained by historical factors, supported by genetic studies, because the Makrani are the descendants from slaves brought to Pakistan by the Arabs, especially from areas in present day Mozambique The Yoruba from HapMap and from HGDP show indistinguishable AMids, indicating that both datasets can be analyzed together.AM analysis of HGDP and HapMap provides higher resolution than previously published using Frappe and PCA North Africa and the Middle East are represented in HGDP by the Mozabite, Bedouin, Druze, and Palestinians . The onlThe genetic distance to Africa is larger in Europeans than in CSA or ME individuals, as reflected by smaller African AMids for Europeans . This fiStrong gene flow within Europe is indicated by the several high European AMids for Europeans, with the only exception being the Adygean. Each population can be distinguished not only by its highest AMid, but by the overall “barcode”, provided by the full set of AMids see .The Basques, the Adygean and the Sardinians show the highest isolation of European populations see also . Basque Of the three Italian populations, the Sardinians show differences in many AMids from Italians and Tuscan, which are closer to one another. The Tuscan from the HGDP are indistinguishable from the Tuscan from the HapMap (TSI).Many populations in the CSA block show the smallest AMids to their own references and to any other references  is Pathan, the closest geographically population to Gujarat. The African AMids of GIH individuals are the highest of all non-African populations. This is consistent with the delayed expansion hypothesis, in which the GIH are the descendants of an ancestral Eurasian founding population, isolated long after the out-of-Africa diaspora, before expanding throughout Eurasia The East Asian block is composed of 18 populations, the highest number of any block. The populations in EA are similar to each other with several high AMids see . DisregaThe Yakut from Sakha, Yakutia, an autonomous republic of Russia, are shown to be strong isolates. The Cambodian, the Lahu and the Japanese are relative isolates.The population from the Americas have the highest AMids for Native-American references see . The MayAM identifies the Mexican from HapMap (MXL) as the most heterogeneous, with varying barcodes in the European and American AMids. This reflects the mixed origin of Mexicans, who have a history of admixture between Europeans and native Americans . Some Mexicans have the highest African AMids of Americans, likely due to admixture introduced through African slaves, brought to Mexico in the early part of XVIII century. Ancestry Mapper is able to correctly highlight this three-way admixture in Latino populations, which previous work has noted as particularly challenging The Oceanic block contains the Papuan and Melanesian, both of which are shown as isolated see . The larClustering ancestry data highlights relationships between individuals: a) individuals of different populations clustering together, indicate similarity of populations, b) individuals of the same population not clustering together, indicate heterogeneity in the population, and c) clusters exclusively of individuals from a single population, indicate a genetic isolate.We clustered AMids with PAM, For K = 2 we observe the big genetic difference of Africa vs. the rest of the world: all individuals of African origin (except for 3 ASW) are in one cluster and all non-African individuals in the other. K = 7 separates individuals into broad continental groups. The African are in two clusters (MKK/ASW vs. the remaining African). ME and European are in a single cluster; as are the Pakistani/Indian populations; individuals from CSA populations are split between these two clusters. Individuals of East Asia, of Americas and Oceania are each in their own cluster. For K = 40 we observe a division of the continental groups into several close clusters see . The AfrThe ASW are African Americans living in the Southwest of the US. For K = 2 three ASW are placed in the non-African cluster, the only individuals with African origin in that cluster. For K = 40, ASW fall into 6 clusters, each with different levels of African and European AMids, indicating individuals with different degrees of admixture see . In manyMXL is composed of Mexicans, collected in LA, US. At K = 40, MXL individuals are mostly present in three clusters see , showingAMids can be used to assign ancestries, in a “guilt by association” approach, comparing the AMids of an individual to the AMids of individuals of known ancestry. To investigate the use of AMids in ancestry assignment we selected ten individuals and calculated the Euclidean distances of the AMids to all individuals in HGDP/HapMap. The ancestry of the closest individuals is indeed a clear indication of ancestry see . For somWe present Ancestry Mapper, which gives individuals an Ancestry Mapper Id (AMid), providing world-wide representation, by calculating the Euclidean distance to references of HGDP. The advantages of AMids include: a small, stable and fixed vector of 51 numbers which can be used in data mining and clustering algorithms; intrinsic ancestry information; local and global information in the same analysis; dataset context-independence; and dataset independence . Ancestry Mapper can provide greater detail than other methods, such as Frappe, or characterization by Principal Components. For instance, in the context of a single global analysis of HGDP, Ancestry Mapper distinguishes clearly between hunter gatherer and agriculturalist African populations while analysis performed by other methods result in less discrimination and often require secondary analysis.AMids provide genetic distances to close and distant populations, e.g., a Mongolian is compared to a neighbor population such as the Daur, but also to the geographically and genetically distant African Yoruba population. Admixtures are easily observed, e.g., an individual with both African and Asian ancestry will have high AMids in both Asian and African references.Ancestry Mapper analysis of the HGDP and HapMap produces distinct blocks , reflecting human history, highlighting the relationships between populations and recapitulating human migrations. We differentiate between the different populations of the African block, with a clear distinction between HG and agriculturalists. The block NA/ME/EUR/CSA shows that the Indo-European populations are similar to each other, providing genetic evidence to the long history of migrations and confluences within this region. Population-specific characteristics and regional relationships are observed, e.g., individuals from ME show intra-regional diversity and similarity to Africa and Europe. In Europe we observe similarity between geographically close populations , while others are confirmed to be isolates (Basques and Sardinians). The Russians have strong eastern Asia coordinates. Central South Asia has the highest overall similarity to all other blocks , validating that CSA is positioned as a confluence of migrations from many different parts of the world.Ancestry Mapper genetic distances correlate well with geographical distances in Africa mimicking the out-of-Africa human migration see . We obseClustering AMids recapitulates what is known about human migrations. The number of clusters correlates with migration time and historical events: for a small number of clusters we observe continental differences; more recent events, such as population isolates, appear for a larger number of clusters. Clusters are labelled by the highest AMids of its members with no need to include in the dataset individuals of known ancestry to serve as labels. For K = 40 some clusters are composed almost entirely of a single population, including the San, Mbuti and Biaka Pygmies, Mozabite, Kalash, Yakut, Maya, Pima, Surui, Melanesian, and Papuan, all known to be genetic isolates , 3 (cases of 1 2 and 2 1) and 4 (both genotypes 2). This makes for a smaller data set and provides the same code for the heterozygous SNPs (1 2 and 2 1 will be the same). In this way, every individual is characterized by a vector of integers, easily comparable.To obtain the individual which will be used as reference for each population we 1) calculate the Euclidean distance between all individuals in each population, and 2) select the individual with the smallest median distances to all other individuals.We calculate the distances amongst the 51 individuals selected as references. We produce a clustering plot using the hclust function in R.We calculate the Euclidean distance, normalized by the number of SNPs, between each individual and the 51-HGDP-based references. This process is independently done for each reference. Also each individual is independently calculated, as a stand-alone process, regardless of its data set. We can obtain AMids for a single individual coming from any dataset provided we have a reasonable overlap of SNPs with the 51 individuals used as references.We normalize AMids by making the highest AMids 100, the lowest 0, and adjusting all others accordingly. Normalized AMids place the individual in the genomic map, forcing it to be committed to one reference, even if the absolute similarities, as indicated by the Euclidean distances, are not very big. They provide a global overview on the number of relevant references for each individual. The R Package Ancestry Mapper is available to produce AMIds.http://www.movable-type.co.uk/scripts/latlong.html to calculate the geographical distances. We used the distances in straight lines, always by land. For instance the distance of Bantu to the Pima was obtained by adding three different steps. The median distances of every population to the San references were calculated and plotted against the geographical distances. A local correlation line was calculated using “loess”, an R local polynomial regression fitting function.We used the site http://colorbrewer2.org/), via the RColorBrewer R package. The R Package Ancestry Mapper is available to visualize AMIds.We produce plots to visualize AMids, which are color coded depending on the value. Also shown is the individual’s origin. The plots use the function “image” in R and the color code from Color Brewer 2.0  We calculated the Euclidean distances between AMids of selected individuals and all HapMap/HGDP individuals. We sorted the individuals by the smallest distance, indicating proximity and analyzed the ancestry of the ten closest individuals.Plink was used http://cran.r-project.org/.The R Package Ancestry Mapper with functions to analyze data sets using the 51-coordinate system is available at CRAN: Figure S1Hierarchical cluster of HGDP references. The hierarchical clustering of the references for Ancestry Mapper shows the African populations as one of two major branches of the tree. Within the African branch we observe the agriculturalists (Bantu/Mandenka/Yoruba) separated from the hunter gatherers (San and both Pygmies). The second branch contains two sub-branches: one is composed of American and Eastern Asia references, the other with the references from Central South Asia, Europe, Middle East and Oceania. The Oceanic are quite distant from the other references in its sub-branch. The branch containing the Indo-european references, is divided into CSA and Europe/Middle East. The Mozabite reference, from North Africa, is in a separate branch from the sub-Saharan populations, and closer to the Middle East.(PDF)Click here for additional data file.Figure S2AMids calculated using for each individual a randomly selected set of 20,000 SNPs. We calculated each AMid with a different, randomly selected set of 20,000 SNPs. The overall results are quite similar to the results using the original set of over 200,000 SNPs shown in (PDF)Click here for additional data file.Figure S3Non-normalized AMids of all HGDP and HapMap individuals. We show for every HapMap and HGPD individual the Euclidean distances to all 51 references. This non-normalized AMids and the normalized AMIds shown in (PDF)Click here for additional data file.Figure S4AMids of Middle East and North Africa. The Mozabites from Algeria, North Africa are the most similar to all sub-Saharan Africa, even if they have large differences to the San and the Mbuti Pygmies and higher European than African AMIds. Mozabite are isolated as indicated by the high values for their own Mozabite reference, which could also reflect a bias in HGDP, as Mozabite are the only representative of North Africa and this negatively impacts Ancestry Mapper results for this region. The Bedouins are much less similar to Africa than the Mozabite. They have few high AMids, show similarity to European references and heterogeneity. Druze and Palestinians show several high AMids and are closer to the European references than to the Mozabite.(PDF)Click here for additional data file.Figure S5AMids of Europe. Many populations show several high European AMids, with Sardinians, Basques and Adygey the most isolated. The barcode makes each population unique. Russians and Adygey have strong East Asian AMids, which correlates with their geographical position between Europe and Asia. Italians are similar to Tuscans (both TSI/HapMap and Tuscans/HGDP) and it is difficult to distinguish between the two populations, with individuals showing high AMids for Italian, Sardinian and Tuscan. The third Italian population, from the isle of Sardinian, is clearly distinguishable and much more homogeneous, with high Sardinian and lower CSA/ME AMids. The HapMap CEU group shows heterogeneity, with Basque, French and Orcadian AMids producing distinctive barcodes that differentiates between individuals.(PDF)Click here for additional data file.Figure S6AMids of Central South Asia. Many populations show several high AMids, reflecting the many influences and migrations to and from CSA. The Kalash show isolation and are as similar to Europe as to CSA. The Makrani and the Balochi have a high level of intra-population heterogeneity. The EA references distinguish between the populations . Although Balochi, Makrani and Brahui live in the same region, Balochistan in Pakistan, differences can be identified. Brahui have stronger Brahui references. The Makrani have high levels of Brahui, Balochi and Makrani, and are heterogeneous with many individuals having different barcodes, but with the strongest influence being their own Makrani reference. The Balochi show even greater heterogeneity, with equally high coordinates for Balochi, Brahui and Makrani. Basque and Burusho languages have some similarity, but our data doesn’t show genetic similarity Click here for additional data file.Figure S7AMids of East Asia. We distinguish several blocks according to the population barcodes, which follow a South/North gradient: Hazara/Uygur, Lahu/Cambodian/Dai/She/Miaozu, Tujia/Han/Yizu/Naxia, Japanese/Tu, Xibo/Mongolia/Hezhen/Daur/Oroqen, and Yakut. The Hazaran and Uygur show similarities to both CSA and EA. Hazara and Uygur are close to Northern EA AMids; Hazarian history mentions a link to the Mongolians, which has been confirmed in two genetic studies (PDF)Click here for additional data file.Figure S8AMids of the Americas. The HapMap MXL population is more heteregeneous than the Native American populations. The Maya also has more high AMids than the other populations, indicating that they have the highest diversity and gene flow. The Surui population is quite isolated, being the most distant to many populations in the whole genomic map. Northern East Asia AMids are relatively high in Maya, probably reflecting the origin of the settlers of the American continent.(PDF)Click here for additional data file.Figure S9AMids of Oceania. The Papuan and the Melanesians are quite isolated, as shown by high AMids for their own references and low AMids for all others. Papuan and Melanesian AMids are high for the other Oceanic reference, with the lowest AMids for Africa. Melanesians have relatively high AMids for the South East Asia references , probably reflecting the settlement of Oceania from individuals coming from South East Asia.(PDF)Click here for additional data file.Table S1AMIds for HGDP and HapMap individuals. Ancestry Mapper Ids for HGDP and HapMap individuals.(XLS)Click here for additional data file.Table S2Genetic and geographical distance to the Bantu. Genetic and geographical distance to the Bantu.(XLS)Click here for additional data file.Table S3Ancestry assignment distances between AMids For HGDP and HapMap individuals. Distances between AMIds For HGDP and HapMap individuals.(XLS)Click here for additional data file.Movie S1Animated GIF Figure For HapMap/HGDP clustering, fast.(GIF)Click here for additional data file.Movie S2Animated GIF Figure For HapMap/HGDP clustering, slow.(GIF)Click here for additional data file.