Within-population genetic diversity is greatest within Africa, while between-population genetic diversity is directly proportional to geographic distance. The most divergent contemporary human populations include the click-speaking forager peoples of southern Africa, broadly defined as Khoesan. Both intra- (Bantu expansion) and inter-continental migration (European-driven colonization) have resulted in complex patterns of admixture between ancient geographically isolated Khoesan and more recently diverged populations. Using gender-specific analysis and almost 1 million autosomal markers, we determine the significance of estimated ancestral contributions that have shaped five contemporary southern African populations in a cohort of 103 individuals. Limited by lack of available data for homogenous Khoesan representation, we identify the Ju/'hoan (n = 19) as a distinct early diverging human lineage with little to no significant non-Khoesan contribution. In contrast to the Ju/'hoan, we identify ancient signatures of Khoesan and Bantu unions resulting in significant Khoesan- and Bantu-derived contributions to the Southern Bantu amaXhosa (n = 15) and Khoesan !Xun (n = 14), respectively. Our data further suggests that contemporary !Xun represent distinct Khoesan prehistories. Khoesan assimilation with European settlement at the most southern tip of Africa resulted in significant ancestral Khoesan contributions to the Coloured (n = 25) and Baster (n = 30) populations. The latter populations were further impacted by 170 years of East Indian slave trade and intra-continental migrations resulting in a complex pattern of genetic variation (admixture). The populations of southern Africa provide a unique opportunity to investigate the genomic variability from some of the oldest human lineages to the implications of complex admixture patterns including ancient and recently diverged human lineages. The Khoesan have received recent attention, as they are the most genetically diverse contemporary human populations. However, Khoesan populations are poorly defined, while archeological evidence suggests a once broader dispersal of click-speaking southern African foragers. Migrations into the regions populated by contemporary Khoesan involved agro-pastoral Bantu around 1,500 years ago, followed over a millennium later by the arrival of European colonists establishing a halfway station for a maritime route between Europe and the East, which led to unions between diverse global populations. Using almost a million genetic markers for 103 individuals, we confirmed a significant Khoesan contribution to five southern African populations. The Ju/'hoan show genetic isolation , carry no significant non-Khoesan contributions, and unlike most global populations lack signatures of gene-based adaption to agriculture. The !Xun show two distinct Khoesan prehistories; while comparable to the female-derived Khoesan contribution to the amaXhosa Bantu, the male-derived Bantu contribution to the !Xun most likely represents cultural-driven gender-biased gene-flow. Emanating largely from male-derived European ancestral contributions, the Basters showed the highest maternal Khoesan contribution, while the Coloured showed the largest within population and regional-associated variability. The unique admixture fractions of the two latter populations reflect both early diverged and recently diverged human lineages. Southern Africa is home to populations carrying significant human genomic variation. The analysis of patterns of DNA variation, have placed modern human origins within Africa Determining the ancestral origins of contemporary southern African admixture is limited by a number of factors including the availability of well-characterized subjects, limited availability of genomic data for appropriate founder populations, biases in current content genotyping arrays and analytical challenges. Lack of genomic data for southern African populations defined based on linguistics and culture broadly as Bantu and Khoesan, has perpetuated biases. To minimize these limitations, we leveraged genotype information from the largest current content array dataset that was available at the time the study was initiated in 2010, interrogating over 1 million genome-wide data points (Illumina HumanOmni1-Quad BeadChips). The 103 individuals in this study represent five southern African populations defined as Khoesan, specifically Ju/'hoan and !Xun, Southern Bantu, specifically amaXhosa, and European-initiated admixed populations, specifically Coloured and the newly described Baster population . At the Before one can assess complex admixture fractions, it is critical to determine the validity of the study sample to be tested, paying particular attention to the potential for sampling biases, while assessing limitations within available genotyping content. Additionally, the identification of the most homogenous founder representative populations is critical. While the availability of globally relevant datasets allows for the assessment of non-regional founders, the identification of a homogenous indigenous founder population is currently not available. We provide evidence that supports the Ju/'hoan in this study as a likely representation of a homogenous Khoesan ancestral lineage. Using this data we provide multiple complimentary approaches to assess southern African admixture fractions.http://www.jcvi.org/cms/research/projects/southern-african-genome-diversity-study/. Individuals were excluded for reported relatedness and sourced from eleven remote sampling sites in Namibia  for further clarification see  Namibia . Cultura Namibia .Subjects were excluded if they reported at least one parent and/or one grandparent having belonged to an alternative population grouping, and included in the study based on heritage and geographical origins. Using 927,298 autosomal genotypes generated for 105 individuals, we performed identity-by-descent (IBD) allele sharing to assess cryptic non-self-identified relatedness among individuals. This resulted in the exclusion of two Ju/'hoan due to first cousin relations. No other subjects were excluded. Notably, three of the !Xun were originally from Angola and referred to themselves as Angolan !Xun or ‘Vasekela’. The genetic relationship of the self-identified distinction between Namibian and Angolan !Xun is currently unknown.Gender-specific markers are an ideal tool to rapidly ascertain likely ancestral contributions, providing a means of sample source validation using unique population-specific mitochondrial (mt)DNA and Y-chromosomal haplogroup identifiers. Khoesan-derived maternal and paternal lineages include the deepest rooting L0d and L0k mtDNA Y-haplogroup analysis suggested a predominant Khoesan paternal contribution to the Ju/'hoan , specifically A2/A3b (10/11) and B2 (1/11), with remarkably minimal contribution to the !Xun . No data was available for the female contributing amaXhosa, while the Khoesan-derived paternal lineages were absent in the Coloured and Baster subjects. Non-Khoesan contribution to the !Xun was dominated by E1b1b . Defined by the M215 marker (previously E3b), E1b1b is reportedly a common contributor to East African Nilotic speakers Caution is needed in the interpretation of calculations of allele sharing between southern Africans using available genotyping arrays due to biases in content, which is typically derived from studies on recently diverged populations. Determining the overall mean percentage autosomal heterozygosity for the 927,298 variants provides an estimate of bias for the largest array content at the time. The assumption is that percentage heterozygosity should decrease as one moves away from human origins in Africa, factoring in additional contributions such as time since dispersal and admixture events. The most significant contributions to current array content including European, Asian and Yoruba, show heterozygosity percentages of 27.7% (n = 175), 25.7% (n = 44) and 29% (n = 90), respectively. The amaXhosa was well represented at 28.5% heterozygosity, although whole genome sequencing for a single Southern Bantu individual suggested overall heterozygosity reaching almost 60% We used PCA to provide an interpretable assessment of homogeneity and geographic origins of our study subjects (n = 103) in relation to globally relevant and platform-matched publically available data (n = 237). Merged data allowed for the interrogation of 33,207 overlapping genetic variants within 15 population identifiers. PCA shows clustering of the amaXhosa close to their Bantu ancestral roots, the Ju/'hoan and !Xun (exception NF2) show clustering defined by their Khoesan ancestral heritage, while the Coloured and Baster, as well as the published #Khomani, are highly admixed, suggesting ‘African non-Khoesan’, ‘African Khoesan’ and ‘non-African’ ancestral fractions . The YorFurther insight into the relationships of the southern African populations was provided using STRUCTURE analysis GAMOVA is a powerful tool to quantify the explanatory power of population identifiers based on genome variability among a set of individuals grouped into categories based on those identifiers Our data suggests that the Ju/'hoan represent the most likely homogenous contemporary Khoesan population. Two factors that set the Khoesan apart from other global populations include early divergence and forager substituted by hunting existence. We use genomic data to look for signatures that differentiate the Ju/'hoan in this study based on these criteria.Pan genome as the outgroup. Represented as a rooted circular tree  phylogenetic trees on the basis of identity by state (IBS) similarity of the individuals, with the lar tree , we confDetermining the fraction of ROH provides a demographic history of a population, which differs significantly between small forager populations and large agricultural communities. We plotted the total length of ROH against the number of ROH (greater than 500 kb) for each population identifier in our study against the Yoruba, representing an outbred African ancestral agricultural lineage, and Europeans, representing inbreeding impacted by genetic drift and a significant bottleneck The conversion to agriculture over 10 thousand years ago was a global event PLRP2 variant appropriately reflects forager root-based diets and lack of adaption to cultivated grains (TAS2R38 variants forming the non-taster (C-T-T or AVI) haplotype have been associated with an inability to sense a bitter taste from the compound phenylthiocarbamide NAT2 variants have been associated with acetylation of exogenous chemicals found in the diet and environment, with the fast acetylation haplotype (G-T-G-G) advantageous to forager societies FMO2 variant causing protein inactivation COMT has been associated with increased enzymatic activity The event of agriculture undoubtedly impacted the genomic differences between contemporary global populations, contributing to significant selective pressures on the human genome d grains . While rPan genome resulted in 30 corresponding allelic positions, of which 25 (83%) were ancestral and five (17%) derived in the Ju/'hoan (http://geneticassociationdb.nih.gov/) http://sift.jcvi.org) defined three variants as potentially ‘damaging’, including tobacco-associated loci PKD1L2 (V308G) and EIF4G3 (Q500H). The 1,162 AIMs found to lie within a gene region using the MetaCore pathway analysis and data mining tool from GeneGO (http://www.genego.com/), were further ranked by significance based on gene ontology to biological processes , show the greatest similarity with the !Xun  and #Khomani  and the greatest dissimilarity with non-African populations, namely Han Chinese  and European . Although clearly both Khoesan, compared with the Ju/'hoan, the !Xun show greater similarity with Bantu populations , while the #Khomani show greatest similarity with non-Africans . The amaXhosa exhibit the greatest similarity with the West and Eastern Bantu populations  and Khoesan populations . The Baster and Coloured show the strongest overall between-population similarity  and the largest similarity for all populations tested with Europeans .Calculating Fst values using a supervised Admixture run and identity by state (IBS) distance sharing using PLINK (the latter for within and between population identifiers) was used to estimate population identity clusters for similarity (or dissimilarity) for 588 individuals from 15 populations using 24,402 markers . The Ju/STRUCTURE analysis assuming five ancestral clusters (the best fit model based on log likelihood estimations) and considering clusters defined as ‘African Khoesan’ (Ju/'hoan), ‘African non-Khoesan’ (Yoruba), ‘European’, ‘Asian’ (Han Chinese) and ‘Hadza’ , provideThe !Xun and amaXhosa show ancient African ancestral contributions defined as ‘non-Khoesan’ and ‘Khoesan’, respectively. Expanding the STRUCTURE analysis from five to nine ancestral population clusters  confirmsABCC11 rs17822931-AA) ALDH2 rs671 A-allele) p-value 0.002 and 0.04, respectively). All the EC-Coloured showed a significant ‘African non-Khoesan’ contribution, while the ‘European’ contribution reached significance within the Coloured , Baster (100%) and in about half the #Khomani. We confirm negligible Han Chinese contribution to regional populations, with significant ‘Indian’ contribution to 29% of the #Khomani, while overall contributing 28% ‘Indian’ and 24% ‘Indonesian’ significance to the Coloured. The ‘Indian’ and ‘Indonesian’ fractions were contributed overwhelming to 63%  and 50%  of the D6-Coloured, respectively. Previously we demonstrate the Indonesian contribution to include Makassar, Bugi and a lesser extent Javanese To provide a more accurate assessment of the ‘Asian’ ancestral contribution, we expanded our analysis to include published data that reflects historical accounts of Indian (36.4%) and Indonesian (31.5%) derived slave contributions Abolished in 1980, District Six was once the center of the Coloured nation at the heart of European settlement and Dutch-East Indian Company (VOC) slave trade Although previous studies have considered the role of admixture in shaping the genetic diversity among southern Africans, in particular the Coloured, no study has assessed (i) the significance of these contributions, (ii) how this admixture has shaped or contributed to distinct population subgroups among southern Africans, or (iii) the possibility that southern Africans may be harboring ancient vestiges of a ‘lost’ or understudied source of genetic diversity. The extent of admixture within people today defined broadly as Khoesan complicates these analyses, further compounded by subject heterogeneity. We attempt to assess sources of admixture and heterogeneity and ultimately identify and characterize a Khoesan-representative population that displays little to no significant non-Khoesan ancestral contribution. Such a population we identify as the Ju/'hoan.This study suggests that the Ju/'hoan form a unique ancestral population for the human lineage, distinct  from all contemporary populations for which data is currently available, including other forager populations. Gender-specific analysis confirms genetic isolation of the Ju/'hoan from non-Khoesan populations, while autosomal analysis shows no significant non-Ju/'hoan ancestral contribution. While the rest of the world was driven into agriculture at the end of the Last Glacial Maximum Unlike the Ju/'hoan, the !Xun exhibit significant male-derived non-Khoesan African ancestral contribution to their gene pool. While autosomal marker analysis suggests roughly 20.5% non-Khoesan admixture, Y-chromosomal analysis suggests a possible East African Nilotic contribution, although extended autosomal substructure analysis suggests a proto-Bantu and Sandawe contributions while excluding for a Nilotic contribution. Evidence for Bantu migration into the northern Kalahari region of Namibia appears as early as the 7th century Ne). Unlike cosmopolitan societies, the maintenance of population size is an essential survival mechanism for foragers. As a result of varied contribution of ancestrally distinct chromosomal segments, contemporary southern African populations would display admixture-based recombination, decreasing total ROH. The complex ‘Khoesan-African-Asian-European’ ancestral admixture fractions of the Baster and Coloured would be further impacted by gender-specific meiotic recombination rates While the !Xun and amaXhosa show evidence for historical admixture, inter-continental migrations to the region has led to the emergence of more recent admixture. Considering a highly variable non-Khoesan contribution to the #Khomani, the Coloued and Baster populations represent a complex admixture pattern that transverses both the earliest and the most recently diverged human lineages. Defining and tracing such significant ancestral contributions provides a unique model not only to track human expansion and prehistories, but also define gene regions undergoing selection http://www.statssa.gov.za)). The most significant ‘Asian’ contribution was found within persons who were residents of District Six. Previously a residential region of Cape Town, District Six was geographically located at the heart of the Dutch-East Indian slave trade Although previous studies have looked at the ancestral contributions to the Coloured Since the submission of this paper, two publications have emerged that have addressed genomic variation within the southern African region we studied. The first assessed ∼500 K custom designed variants including study subjects described as Ju/'hoan and !Xun (!Xuun) and grouped together as Kx'a speakers This study demonstrates both ancient and recent admixture within southern Africans. Cautionary concerns include: (i) bias in current content arrays towards non-African populations will greatly impact inferences about diversity among southern Africans, while lack of rare allele representation would diminish an ability to separate southern African subpopulations, (ii) lack of an available common ancestral genome that truly represents the earliest modern humans results in biases in methods used to attain divergence times among populations, (iii) inferences regarding population structure and recent admixture events are currently based on analyses of data reflecting contemporary genetic variation between populations, which is still largely lacking for the region of Southern Africa, and (iv) this is confounded by lack of data for populations that may actually be extinct. Taking these cautionary observations into consideration, we present an analysis of a set of individuals that, to the best of our knowledge, most accurately defines a homogenous ancestral Khoesan contribution, the Ju/'hoan. Additional cultural differences that may have restricted interbreeding between our Ju/'hoan and local agro-pastoral groups include; economic distinction (those without and those with possessions), language (Khoesan versus Bantu), social practices , kinship , marital locality , and marital practices . While a recent study acknowledges western influences as a result of the establishment of a Ju/'hoan ‘reserve’ near Tsumkwe The study was approved by the Ministry of Health and Social Services in Namibia, the human Research Ethics Committee at the University of Stellenbosch, South Africa (Project # N08/03/072), the Institutional Review Board Committee at the J. Craig Venter Institute (IRB# 2010-126) and previously the Human Research Ethics Committee at the University of New South Wales Australia (HREC# 08244). Consents were acquired either via verbal or written documentation with the understanding that the data generated will be made freely available to the scientific community as a collective. There are no known cultural limitations that would prohibit open access of the data.o+i does not exist in the Khoekhoegowab language) is used in this study to represent southern African foragers. Academically, Khoesan more accurately reflects two unique cultural identities the hunter-gatherer (San) and herder-gatherer (Khoe), while locally ‘Bossiesman’ (Afrikaans for Bushmen) is the more accepted collective identifier. The Working Group of Indigenous Minorities within Southern Africa  identifies 13 Bushmen or ‘San’ language groups, which include the Ju/'hoan and the !Xun (or !Kung). Representing Ju languages http://www.jcvi.org/cms/research/projects/southern-african-genome-diversity-study/.The symbols represent dental (/), alveolar (!), palatal (≠), and the lateral (//) clicks used in the Khoesan languages. Although historically the Ju/'hoan (n = 19) and !Xun (n = 14) have had no collective name for themselves The amaXhosa are a Southern Bantu people who speak isiXhosa from the Nguni classification. Bantu migrations are believed to have originated from north-western Cameroon/southern Nigeria around 5-3 thousand years ago Population admixture involving the Khoesan and additional founder populations started shortly after the arrival of the Dutch-East Indian Company in 1652 at the Cape of Good Hope . These early migrants included European settlers  and slaves from the East , Madagascar, and coastal Africa  http://www.statssa.gov.za/census2011/). Based on our survey, the 2011 census and in agreement with the two self-identified Coloured co-authors, we conclude that Coloured is still the most widely recognized population-specific identifier within the community. The use of the term Baster (or Rehoboth Baster) is regarded with immense pride within the community, establishing themselves as a Republic with a national flag The terms Bantu and Coloured have different meanings to different people, the latter exasperated by the use of a parallel term within the United States (Colored). Until 1991 South African law divided the country into four official ethnic groups, defined as ‘Black (or Bantu)’, ‘Coloured’, ‘Indian’ and White’. Although may South Africans still use these population identifiers, these classifications undoubtedly have negative connotations for certain people. The use of Bantu or Southern Bantu in this paper refers to the widely accepted linguistic identifier. The continued use of the term Coloured in this study was based on a survey of 521 persons who self-identified as Coloured (91.2%), including the use of terms ‘South African Coloured’ and ‘Cape Coloured’, while the remaining 8.8% referred to themselves as Admixed/mixed ancestry or Other. Interviews were unprompted and performed by one of the Coloured co-authors. Of the 51.8 million South Africans registered in the 2011 census, 4.62 million (11.2%) self-identified as ‘Coloured’ (http://www.jcvi.org/cms/research/projects/southern-african-genome-diversity-study/ for the complete dataset of 103 subjects according to population identifiers.Genomic DNA was isolated from whole blood using the QIAamp DNA Blood Mini kit or the FlexiGene DNA kit (QIAGEN) and quantified on the NanoDrop spectrophotometer (Thermo Scientific). A total of 105 subjects were genotyped using the Illumina HumanOmni1-Quad Beadchips. The Illumina GenomeStudio software (version1.7.4) was used for the data analysis with a GenTrain score of 0.5 as the minimum for inclusion. Excluding indels, mtDNA, Y-chromosome markers and no-calls resulted in 927,298 variants. Two subjects (both Ju/'hoan) were excluded as a result of likely first cousin relatedness based on the estimation of the probable number of shared alleles at any given marker, identity by descent (IBD) values of 0.4351 and 0.4129. Genotype calls have been made available without restrictions at www.phylotree.org) build 13 MT-haplogroup specific markers  were idehttp://www.illumina.com/) including Human Omni1-quad data, specifically Yoruba (n = 90), European (n = 175) and Han Chinese (n = 44), and allowing for an autosomal overlap of 927,298 autosomal markers and (ii) the published dataset of Henn et al., 2011 2 value greater than 0.1 or less stringent 0.2 with any other variant within a 50-variant sliding window, advanced by 5 variants at a time. The total number of variants interrogated for LD-pruned datasets are highlighted throughout the main text.The sample base  was merged with two publically available datasets namely, (i) the Illumina iControl database  published Affymetrix SNP6.0 data for 20 Indonesians representing 4 population identifiers, specifically Makassar, Bugi, Javanese and Batak Toba http://www.goldenhelix.com/), considering the first two eigenvectors. STRUCTURE 2.3.3 analyses http://cmgm.stanford.edu/phylip/). The trees were rooted to the Chimpanzee (Pan troglodytes) genome . A single circular tree is represented. Determining the fraction of ROH using SVS 7.5, we first removed from the large 928,799 merged dataset markers with a minor allele frequency (MAF) less than 5% and markers with a Hardy Weinberg Equilibrium (HWE) P value less than 0.0001, leaving a total number of 716,734 markers . Parameters included a minimum run length of 500 kb with a minimum number of 25 variants and runs containing no more than 1 heterozygote and up to 5 missing genotypes. The minimum number of samples to contain a run was set to 1 with the maximum gap of 100 kb between variants and a minimum density of 1 variant per 50 kb in a run. The supervised mode of ADMIXTURE v1.22 Multiple analytical methods were used in this study. Each method is described in brief. PCA was performed using the PCA tool in the HelixTree module of the ‘SNP and Variation Suite’ in the SVS 7.5 software available from Golden Helix (DARC) promoter variant rs2814778 −46 A>G  PLRP2) nonsynonymous variant rs4751995 G>A, Trp358X (associated with an adaptation to grain cultivation) TAS2R38) gene  NAT2) gene, rs1801279 G>A (Arg64Gln), rs1801280 T>C (Ile114Thr), rs1799930 G>A (Arg197Gln) and rs1799931 G>A (Gly286Glu)  FMO2) gene  COMT) gene, rs4680 G>A, Val158Met  ABCC11) gene (associated with dry earwax in East Asians) ALDH2) gene  Markers specifically associated with human adaptations that further define population ancestry were identified from the literature and include; (i) the African-specific Duffy antigen receptor gene (2) allowing for the analysis of 70,733 autosomal markers from 19 Ju/'hoan and 90 Yoruba. The variables (phenotypes) selection was based on population identifiers, namely Ju/'hoan versus Yoruba, allowing for the identification of alleles at significantly represented between the populations. A conservative threshold was set at −log10 P>5 for significance resulting in 2,687 AIMs. STRUCTURE analysis was performed on a reduced subset of Yoruba (n = 20) to facilitate visualization of the data generated. Further inclusion of all 90 Yoruba did not impact the overall ancestral contributions (data not shown). The MetaCore suite from GeneGo (http://www.genego.com/) was used to rank the list of generated AIMs based on gene ontology.The Manhatton plot analysis function in SVS 7.5 was used to generate the Ju/'hoan-Yoruba AIMs after LD pruning using parameters 50 (sliding window), 5 (variant advance) and 0.1  or !Xun . IBD allele sharing resulted in the exclusion of two Ju/'hoan from our study as a result of possible relatedness .(PDF)Click here for additional data file.Figure S2Gender-specific ancestral haplotype contributions to the regionally defined South African populations, amaXhosa, Coloured and Basters. Marker analysis with contributions from ancestral populations shown as percentages for (A) ‘African Khoesan’ (L0d), ‘African non-Khoesan’  and ‘non-African’ (N/M) mtDNA haplogroups and (B) ‘African non-Khoesan’ (E) and ‘non-African’ (R/I/G/N/O/J) Y-chromosome haplogroups. Distribution correlates with geographical distribution around the southern coast of Africa from the northwesterly Basters, to the westerly NC-Coloured, southerly D6-Coloured and the easterly located EC-Coloured and amaXhosa. This west to east distribution is correlated with a decrease in maternal ‘Khoesan’ and increase in ‘African non-Khoesan’ contribution, and a decrease in paternal ‘non-African’ and increase in ‘African non-Khoesan’ contribution. ‘Asian’ derived maternal contributions are highest at the geographical location of colonization and slave trade, at the most southerly region represented by the District Six Coloured.(PDF)Click here for additional data file.Figure S3Relatedness of the Ju/'hoan (n = 19) and !Xun (n = 14) in our study to published data for African populations defined as hunter-gatherer/click-speakers. PCA plot for 31,271 autosomal markers for 144 individuals from 7 populations defined as hunter-gatherer and/or click-speaking from within Africa. The Tanzanian and Pygmy lineages form independent population clusters to the Southern African Khoesan populations. The Ju/'hoan and !Xun form tight population clusters . The #Khomani show a diversity in ancestral contributions, likely as a result of recent admixture.(PDF)Click here for additional data file.Figure S4Functionally relevant alleles/haplotypes associated with forager versus non-forager societies and their distribution within the Ju/'hoan and !Xun foragers and the agriculturalist amaXhosa. (A) The Duffy antigen receptor gene promoter variant  associated with protection against malaria infection in Africa, (B) the pancreatic lipase-related protein 2 nonsynonymous variant  associated with a diet rich in grains, (C) the taste receptor type 2 member 38 ‘taster’ (PAV) or ‘non-taster’ (AVI) haplotype associated with an ability or inability to taste toxins, (D) the arylamine N-acetyltransferase 2 ‘fast’ acetylation (G-T-G-G) haplotype associated with toxin irradication, (E) the flavin-containing monooxygenase 2 truncating inactive variant  is absent in our forager groups, while the active full length C-allele is present enabling metablization of foreign toxins, and (F) the catechol-O-methyltransferase nonsynonymous variant  decreased enzymatic activity associated with increase in anxiety-related conditions, while the ancestral G-allele is associated with a need for instinctive behavior. Note the English spelling with omits the prefix has been used to identify the amaXhosa.(PDF)Click here for additional data file.Figure S5Manhattan plot analysis for Ancestry Informative Marker (AIM) identification. A total of 70,733 LD-pruned Illumina Omni-quad 1M array markers were used to identify 2687 AIMs distinguishing the Ju/'hoan from our study (n = 19) to the Illumina iControl database Yoruba (n = 90), defined as a significant allele frequency difference between these population identifiers at −log10 P>5.(PDF)Click here for additional data file.Figure S6Significantly enriched biologically relevant pathways of genes that distinguish Ju/'hoan and Yoruba. Significant ancestry informative markers that distinguish the hunter-gatherer Ju/'hoan in our study from a representative of agriculturally-defined Yoruba, defined by a −log P value greater than 5, that are most significantly represented within genes grouped within biologically relevant pathways.(PDF)Click here for additional data file.Figure S7Regional distribution of the study sample and autosomal ancestral contributions. While the ‘African non-Khoesan’ (Bantu and Sandawe) contribution increases from west to east, the ‘European’ contribution decreases. Although maternal ‘Khoesan’ contributions decrease from west to east, autosomal analyses, although showing highest frequencies in the western populations, shows decreased frequency of contributions at the southern point and an inverse ‘Asian’ contribution.(PDF)Click here for additional data file.Figure S8Ju/'hoan and Yoruba ancestral contributions to the !Xun and amaXhosa. STRUCTURE analysis using the 2687 Ju/'hoan-Yoruba AIMs assuming two (estimated log likelihood of probability of data −160813.9) and three (−161042.6) population clusters (10000 burn-ins and 20000 iterations). K = 3 is also presented in the main text .(PDF)Click here for additional data file.Figure S9Structure analysis for 9,317 LD pruned autosomal SNPs using K = 2 to K = 5 for ancestral populations with 5000 burn-in iterations and 10000 iterations. Indian populations listed as 1 to 10 in accordance with (PDF)Click here for additional data file.Figure S10Principal component analysis (PCA) including 9,317 LD pruned autosomal markers for (A) D6 Coloured, Han Chinese, European and 10 Indian populations (B) D6 Coloured, Han Chinese and five Indian populations (GC1 and GC2) that were not impacted by colonization (C) D6 Coloured, European and five Indian populations (GC3 and GC4) that were impacted by colonization.(PDF)Click here for additional data file.Table S1Mitochondrial DNA haplogroups screened.(PDF)Click here for additional data file.Table S2Y-chromosomal haplogroup and subclade representation within the Baster and Coloured sample from our study.(PDF)Click here for additional data file.Table S3Multiple regression GAMOVA defines the contribution of variation explained by population identifiers.(PDF)Click here for additional data file.Table S4Pan (Chimp) genome.Fixed Ju/'hoan-specific alleles. Of the 2,687 ancestry informative Ju/'hoan-Yoruba markers (AIMs), 32 were found to be fixed in the Ju/'hoan (n = 19), 16 occurring in gene regions of potential functional relevance. Of the 16 fixed Ju/'hoan alleles, 13 are defined as ancestral against the (PDF)Click here for additional data file.Table S5Alleles with a highly significant −log10P>14 Ju/'hoan versus Yoruba population-specific association.(PDF)Click here for additional data file.Table S6Of the 2687 Ju/'hoan versus Yoruba AIMs (−log10P>5) 33 are nonsynonymous variants and are ordered in descending order from most significant.(PDF)Click here for additional data file.Table S7Ju/'hoan versus Yoruba differentiating AIMs located within genes ranked according to significance of genes enriched for biological processes.(PDF)Click here for additional data file.Table S8Ju/'hoan versus Yoruba differentiating AIMs located within genes ranked according to significance of genes enriched for molecular functions.(PDF)Click here for additional data file.Table S9Ju/'hoan versus Yoruba differentiating AIMs located within genes ranked according to significance of genes enriched for cellular localization.(PDF)Click here for additional data file.Table S10Ju/'hoan versus Yoruba differentiating AIMs located within genes ranked according to significance of genes enriched for disease associations.(PDF)Click here for additional data file.Table S11Allele sharing distances within (gray blocks) and between populations using identity-by-state (IBS) and including Fst distance values.(PDF)Click here for additional data file.Table S12Contribution of four ancestral populations to the amaXhosa, Baster and Coloured populations displayed as a percentage for both the average and range distributions.(PDF)Click here for additional data file.Table S13Significance of ancestral contributions within southern Africans from our study.(PDF)Click here for additional data file.Table S14Primer sequences and amplification conditions for gender-specific markers.(PDF)Click here for additional data file.


Calanthe tsoongiana is a rare terrestrial orchid endemic to China, and this species has experienced severe habitat loss and fragmentation. Inter-simple sequence repeat (ISSR) markers were employed to assess the genetic diversity and differentiation of six populations of C. tsoongiana. Based on 124 discernible fragments yielded by eleven selected primers, high genetic diversity was revealed at the species level; however, genetic diversity at the population level was relatively low. High-level genetic differentiation among populations was detected based on analysis of molecular variance (AMOVA), indicating potential limited gene flow. No significant relationship was observed between genetic and geographic distances among the sampled populations. These results suggested that restricted gene flow might be due to habitat fragmentation and reduced population size as a result of human activities. Based on the findings, several conservation strategies were proposed for the preservation of this threatened species. Br., is widely distributed in tropical, subtropical and warm temperate regions from Africa to Asia and the Pacific Islands. It is characterized by distichous plicate leaves, basal or lateral inflorescences, pseudobulbous or cane-like stems made up of several internodes, similar petals and sepals, normally spurred lips and possession of eight pollinia . Th. ThHt) o2.3.C. tsoongiana populations ranged from 0.229 (between LA and WYS) to 0.638 (between WN and WYS)  (K (127.2) at K = 2  . The Man= 0.306) . The UPG= 0.306) . The firat K = 2 . Therefoclusters , but the3.3.1.Calanthe genus. Chung et al.  anbs H = 0.40 [12,13 0.1240) . This maglaciers , the curglaciers .C. tsoongiana (H = 0.1826) was lower than the average value of plant genetic diversity reported by Nybom [H = 0.22). This pattern could be attributed to several factors. Firstly, the population sizes of C. tsoongiana were small, with only 15 (WN) to 33 (SZ) individuals found, due to habitat destruction and illegal collection. In some cases, plants had become locally extinct in locations recorded in previous literature. Prolonged periods of small population size and population fragmentation can lead to loss in genetic diversity due to the founder effect, genetic bottlenecks and loss of rare alleles [C. tsoongiana is self-compatible. Additionally, decreased genetic diversity can occur due to geitonogamy if flowers on an inflorescence are receptive at the same time, and pollinators frequently interpollinate consecutive flowers on the same inflorescence [C. tsoongiana within populations [Genetic diversity within populations is influenced by many factors, such as mating systems, population size, extended time periods with low numbers of individuals, genetic drift and gene flow ,27. The by Nybom  based on alleles . A popul alleles . The rel alleles . Secondl alleles . Accordi3.2.C. tsoongiana (Gst = 0.55) populations was higher than the average value (Gst= 0.187) obtained from 76 orchid species reviewed by Forrest et al. [Gst ranged from 0.04 to 0.92, with an average of 0.39. Accordingly, C. tsoongiana exhibited relatively high population differentiation compared with other orchids performed by similar markers. This finding supported the low genetic diversity results within populations and the discreet UPGMA clustering of individuals from the same population. The greater similarity of individuals within rather than among the populations indicated that these populations were probably founded by one or a few individuals and that gene flow may be restricted among populations [C. tsoongiana populations (Nm = 0.4084) was below one, a level of migration that will not prevent continued divergence among populations [et al. [C. tsoongiana populations. Genetic drift in continually small population sizes might also play an important role in shaping the present level of population differentiation [C. tsoongiana populations were separated into two groups, further confirming that there was no genetic correlation of individuals with their spatial distribution. Similar results were also found in Liparis loeselii [Liparis japonica [Differentiation among the locations of t et al. ; howeverGst= 0.18 obtainedt et al. . Consequulations . Gene flulations . Pollen ulations . Li et a [et al. . Therefontiation . The Manntiation . Using t Gst = 0.5 populatjaponica , with th3.3.C. tsoongiana maintains low within-population genetic diversity and high genetic differentiation among populations and that many of its native habitats and ecosystems have been destroyed by human disturbance, great effort should be made to preserve all extant populations and their habitats to prevent a further decrease in population size and to conserve the overall genetic base of this species. Collection of this orchid should be prohibited. Li and Ge [ex situ conservation is also recommended for C. tsoongiana. As discussed by Li et al. [C. tsoongiana, including demographic dynamics, pollination biology, vegetative propagation and identification of fungal associates and germination ecology, should be conducted to achieve comprehensive conservation for this rare endemic orchid [The ultimate goal of conservation is to ensure the continuous survival of populations and to maintain their evolutionary potential by preserving natural levels of genetic diversity . In a spi and Ge  suggestei and Ge . Transfei et al. , populatc orchid .4.4.1.C. tsoongiana populations scattered throughout Fujian, Guizhou, Hunan, Jiangxi and Zhejiang provinces in south China , according to the manufacturer’s recommendations. The integrity of DNA samples were assessed through 0.7% agarose gels electrophoresis, and DNA quantification was performed in a Quawell Q5000 UV-Vis spectrophotometer . The DNA samples were diluted to 20 ng/μL in Tris-EDTA buffer solution and then stored at −20 °C until further analysis.2+, 0.3 mM dNTP, 0.4 μM primer, 60 ng of DNA template and 1 U of Taq DNA polymerase . Negative controls, containing all ingredients except the DNA template, were included in each reaction to check the absence of contamination. Amplifications were carried out in a Vapo-protect Gradient thermal cycler  using the following conditions: 94 °C for 5 min for initial denaturation, 40 cycles of denaturation at 94 °C for 1 min, the appropriate annealing temperature (w/v) agarose gels in 1× TBE buffer (pH = 8.0) at 100 V for 90 min, with DL2000 ladder  used as the DNA molecular weight. After running, the gels were visualized and photographed under UV light using a gel analysis system . Each PCR reaction was repeated twice to ensure the reproducibility of the banding pattern.Initially, 100 ISSR primers  synthesized by Sangon Biotech  were screened. Eleven primers  that properature  for 1 mi4.3.Na); effective number of alleles (Ne); Nei’s gene diversity (H); Shannon’s Information index (I); percentage of polymorphic loci (PPL); total genetic diversity (Ht), genetic diversity within populations (Hs), genetic differentiation among populations (Gst); gene flow (Nm); and Nei’s genetic identity and genetic distance. The same matrix was then used to perform cluster analysis, and an individual-level unweighted pair group was constructed with an arithmetic average (UPGMA) dendrogram using SAHN from NTSYS-pc version 2.20 [The ISSR bands were scored as present (1) or absent (0) for each DNA sample to form a binary matrix. Only fragments showing consistent amplification were considered, while weak and smeared ones were excluded. The following genetic diversity parameters were determined for each population under the assumption that the populations were in Hardy-Weinberg equilibrium using POPGENE version 1.32 : observeion 2.20 .pt values were also calculated and are considered analogous to Fst, describing the proportion of total variance among populations [Analysis of molecular variance (AMOVA) was used to estimate the variance components and their significance levels of genetic variation within and among the populations using GenAlEx version 6.5  based onulations . PrincipA Mantel test for geographic and genetic distances of population pairs was performed to determine if a relationship existed between the two data matrices using TFPGA version 1.3  with 999K was set from 1 to 6, and ten independent runs were performed, each with a Markov Chain Monte Carlo (MCMC) of 100,000 repetitions following a burn-in period of 50,000 iterations. Default values were kept for all other parameters. To identify the optimal value of K, the STRUCTURE output file was implemented in Structure Harvester version 0.6.93 [et al. [To infer population structure and estimate genetically homogeneous groups (K) that best fit the data, the Bayesian Method was implemented in STRUCTURE version 2.3.4 , assuminn 0.6.93 , as per  [et al. .5.C. tsoongiana genetic diversity was high at the species level, but relatively low at the population level. High genetic differentiation was found among populations, which may be attributed to habitat fragmentation, due to anthropopression, geographic isolation, restricted gene flow and genetic drift. Based on these findings, several strategies were proposed for the conservation of this rare orchid.Our results indicated that


Aedes albopictus has recently been implicated as a major vector in the emergence of dengue and chikungunya in several parts of India, like Orissa, which is gradually gaining endemicity for arboviral diseases. Ae. albopictus is further known to be naturally infected with Wolbachia , which causes cytoplasmic incompatibility (CI) in mosquitoes leading to sperm-egg incompatibility inducing the death of embryo. Knowledge of genetic diversity of Ae. albopictus, along with revealing the type of Wolbachia infection in Ae. albopictus is important to explore the genetic and biological characteristics of Ae. albopictus, prior to exploring the uses of CI-based vector control strategies. In this study, we assessed the population genetic structure and the pattern of Wolbachia infection in Ae. albopictus mosquitoes of Orissa.Ae. albopictus mosquitoes were collected from 15 districts representing the four physiographical regions of Orissa from 2010–2012, analyzed for genetic variability at seven microsatellite loci and genotyped for Wolbachia strain detection using wsp gene primers. Most microsatellite markers were successfully amplified and were polymorphic, showing moderate genetic structure among all geographic populations (FST = 0.088). Genetic diversity was high (FST = 0.168) in Coastal Plains populations when compared with other populations, which was also evident from cluster analyses that showed most Coastal Plains populations consisted of a separate genetic cluster. Genotyping analyses revealed that Wolbachia-infected Ae. albopictus field populations of Orissa were mostly superinfected with wAlbA and wAlbB strains. Wolbachia superinfection was more pronounced in the Coastal Plain populations.Wolbachia superinfection, observed in the Coastal Plain populations of Orissa suggested it to be genetically and biologically more unique than other populations, and hence could influence their vectorial attributes. Such high genetic diversity observed among Coastal Plains populations could be attributed to multiple introductions of Ae. albopictus in this region.High genetic structure and  Aedes albopictus (Skuse 1884) is a highly invasive species and has been implicated as one of the major vectors of arboviral diseases in many parts of India. Ae. albopictus has been reported to be naturally infected with dengue and chikungunya virus during several outbreaks that flourished throughout India in recent past Ae. albopictus exhibits strong physiological and ecological flexibility, allowing it to thrive in wide climatic ranges and habitats. Previously known to be forest dweller, Ae. albopictus has now adapted itself to human environments and is preferentially found in rural and suburban areas Ae. albopictus vary with the geographical locations of mosquito populations Ae. albopictus enhances not only its biological traits like fecundity and survival, but also its capacity to propagate zoonotic pathogens across animal species and to humans, thereby rendering it to be a potential vector of arboviral diseases The Asian tiger mosquito, Exploring the pattern and magnitude of genetic differentiation among vector populations is essential to evaluate the risk of pathogen transfer Wolbachia (Family: Anaplasmataceae), which induces crossing sterility known as cytoplasmic incompatibility (CI) in arthropods Ae. albopictusWolbachia infected males. Thus, in host populations that include both infected and uninfected individuals, CI provides a reproductive advantage to infected females since they can mate successfully with all male types. However, the mating between male and female mosquitoes infected with different and incompatible strains of Wolbachia will lead to considerable reduction in fecundity and egg hatching rate Ae. albopictus is naturally infected by two types of Wolbachia, A and B Ae. albopictus can be single-infected with wAlbA/wAlbB strain or superinfected with wAlbA and wAlbB strains Wolbachia strains, thereby increasing bacterial diversity Wolbachia infections in wild Ae. albopictus populations is crucial for understanding the CI mechanism and Wolbachia evolution in Ae. albopictus mosquitoes.The maternally inherited bacterium Ae. albopictus, Ae. aegypti and Ae. vittatus were the main Aedes vectors found here Ae. albopictus to be the major vector responsible for the arboviral outbreaks Ae. albopictus found in varied landscapes of Orissa. Furthermore, it is crucial to reveal the infection pattern of Wolbachia strains thriving in Ae. albopictus mosquitoes of Orissa, prior to exploring the potential uses of CI based strategies for control programmes. Hence the study was carried out with two objectives: Firstly to reveal the pattern of genetic differentiation and secondly to elucidate the type of Wolbachia infection in naturally occurring populations of Ae. albopictus mosquitoes collected from different topographical regions of Orissa.Orissa, in the eastern part of India has been a malaria endemic region for a long period. It has different types of landscapes that are adjacent to each other: Coastal Plains (near to sea level), Central Tableland (about 150 m above sea level), Eastern Ghats and Northern Plateau (about 800 m above sea level) , which aAe. albopictus species from 2010–2012 , 0.8 μl of 10 mM dNTP mix , 25 pmol of each primer, 1 U of Taq polymerase  and nuclease free water. The 5′ end of each forward primer was labeled with a fluorescent dye  . Cycling conditions were as follows: 5 min at 94°C, followed by 35 cycles of 94°C for 40 secs, annealing temperature (TA)   for 40 sAe. albopictus populations was assessed at each locus by estimating allele frequencies, number of alleles A, allele richness Rs, inbreeding coefficient FIS, expected heterozygosity He, and observed heterozygosity Ho Genetic diversity within STST as the distance measure, with 10,000 randomizations and missing data for loci set at 10%. The model for analysis partitioned variation among geographical regions, among and within populations. Since geographical isolation is often considered as the main driving force for population differentiation, the logarithm of geographical distances [Fst/(1-Fst)] was calculated between sampling sites by employing a Mantel test Population genetic differentiation was measured by the fixation index, FHeq were computed using two mutation models for microsatellites evolution: Two- Phased Mutation model (TPM) Since demographic instability such as recent population bottleneck and/or expansion might bias genetic differentiation estimates to a significant extent A Bayesian approach was used to deduce the number of clusters (K) in the data set without prior information of the sampling locations in STRUCTURE 2.3 Wolbachia infection by PCR using wsp gene, , which amplified 615 bp product. This served as positive control for Wolbachia genotyping. Then, Wolbachia genotyping in Ae. albopictus samples was performed by a multiplex PCR using Wolbachia-specific primers, 328F/691R for wAlb A and 183F/691R for wAlb B  2, 0.2 mM primers and 1 U Taq DNA polymerase (Sigma) with the following thermal cycler conditions: 95°C for 5 mins, followed by 35 cycles of 95°C for 1 min, 54.4°C for 1 min and 72°C for 2 min, followed by 72°C for 10 min. Out of the Wolbachia positive Ae. albopictus specimens, confirmation of Wolbachia strains in 5 mosquito samples representing the four physiographical regions was accomplished through sequencing and phylogenetic analyses.The quality of DNA extracted from individual mosquitoes collected from different regions of Orissa  was assewsp gene were excised from gel, purified using QIAquick Spin Column  and sequencing PCR done. For each sequencing reaction, 50 ng of purified PCR product was mixed with a reaction mixture containing 2.5 X sequencing buffer, 5 X big dye terminator and 20 μM of either forward/reverse primers of wAlb A and wAlb B genes in two separate sets of reaction. Cycle sequencing parameters used were: 96°C for 1 min followed by 25 cycles of 96°C for 10 secs, 50°C for 5 sec, and 60°C for 4 min. The PCR product was purified by EDTA/ethanol precipitation. The dried pellet was resuspended in 10 μl of Hi-Di-formamide, and sequenced in a 16 capillary (90 cm) automated DNA sequencer  using performance optimized polymer 7 following the manufacturer’s instructions. The nucleotide sequences obtained after sequencing were edited and analyzed by the Sequencing analysis software . The wsp gene sequences generated have been deposited in GenBank with accession nos. JX475999–JX476007 (wAlbA isolates), JX629463–JX629467 (wAlbB isolates). Multiple sequence alignments and phylogenetic analysis were performed using partial wsp gene sequences of the mosquito isolates obtained from Orissa and other regions in Mega 5 software  wsp gene was employed to compare the wsp sequences obtained from Wolbachia strains thriving in natural populations of Ae. albopictus of Orissa with the HVR profiles of the wsp gene available in PubMLST database The PCR products were visualized on a 1.5% low melting point agarose gel at 300 nm under UV transilluminator. The PCR products of wAlb A (379 bp) and wAlb B (501 bp) using 328F/691R and 183F/691R primers of the Wolbachia infection/superinfection rates were estimated for Ae. albopictus mosquitoes in each of the surveyed districts belonging to the four topographical regions of Orissa. Comparison was done between Wolbachia superinfection in Ae. albopictus mosquitoes of the 4 regions using non parametric Kruskal Wallis ANOVA, which calculated the two-tailed p values using the Graphpad Prism (version 6) software. A p value <0.05 was considered to be statistically significant.Ae. albopictus mosquitoes collected from 15 districts of 4 different physiographical regions of Orissa. Polymorphism at the 7 microsatellite loci varied, with number of alleles as 18 , 11 , 7 , 6 (AEDC), 5  and 4  respectively (IS) were detected in 2 of 7 (28.5%) loci when all samples were pooled and considered as a single gene pool, suggesting population substructure. At the population level, 8 out of 105 (7.6%) comparisons did not conform to Hardy-Weinberg expectations after sequential Bonferroni correction, and the deviations were associated with positive inbreeding coefficient (FIS), reflecting heterozygosity deficits  within each of the 15 collections. Out of 105 comparisons only three pairs (2.81%) were at LD (P<0.05). The three pairs were detected in NAY , ANG  and GAJ  populations respectively. No pair of loci appeared in LD in more than one population, suggesting genetic independence between loci. When the test was performed in the pooled populations, no pairs of loci out of 10 possible combinations showed significant P values (P.0.05).ST = 0.088, P = 0.001). Pairwise analysis of populations indicated significant genetic differentiation for most sample pairs (91/105), associated with FST estimates ranging from 0.009 (KEO-KOR) to 0.223 (GAN/KEO). The FST values were non-significant for most of the Northern Plateau and Eastern Ghats population comparisons, such as KEO/MAY, KOR/MAL, etc. (ST = 0.052), indicating high genetic similarity between them. However, high and statistically significant genetic differentiation (average FST = 0.144) was recorded when comparison was performed between coastal plain populations and other populations. Genetic divergence was maximum when comparison was performed between any coastal plain population with Northern Ghats populations  . FurtherAe. albopictus populations and compliance to MDE. No signature of a recent bottleneck event (population reduction/expansion) was detected by TPM in any populations. Significant deviations (P<0.01) from MDE (He<Heq) (in 3 loci showing significant heterozygote deficiency) were found in ANG and GAJ populations under the SMM  likelihood score optimal for k = 3 clusters) . More thAe.albopictus collected from different regions of Orissa, 1281  (99.2%) mosquitoes showed band at 615 bp (wsp), thereby indicating to be infected with Wolbachia. Multiplex PCR analysis of 1281 individuals using group specific primers depicted that 41 (3.2%) specimens exhibited band at 379 bp, thus infected with wAlbA strain and 1240 (96.8%) specimens exhibited bands at 379 bp and 501 bp, thereby indicating to be super-infected with wAlbA and wAlbB strains. Furthermore, 100% Wolbachia superinfection (wAlbA+wAlbB) was detected in Ae. albopictus mosquitoes collected from the Coastal Plains. Northern Plateau, Eastern Ghats and Central Tablelands populations recorded super-infection rates of 95%, 96% and 96% in the mosquitoes . Of the Wolbachia infected males, 95.7% (652/681) were super infected with wAlbA and wAlbB strains and 4.3% (29/681) infected with only wAlbA. Superinfection of wAlbA and wAlbB strains was detected in 98% females (588/600), while only wAlbA infection was observed in 2% (12/600) females. We did not detect any mosquito specimen to be singly infected with wAlbB.Out of 1291  squitoes . Statistwsp gene sequences of Wolbachia extracted from Ae. albopictus mosquitoes of Orissa and other regions confirmed the circulation of wAlbA and wAlbB strains. High genetic divergence (GD: 0.234) was observed between the supergroup A and B that resulted in population subdivision, which was also supported by high bootstrap values at each node. There was low genetic variability in the populations within group A (GD: 0.0043) as well as populations within group B (GD: 0.0042). The phylogenetic tree confirmed the co-infection of wAlbA and wAlbB in Ae. albopictus mosquitoes collected from different regions of Orissa , with small number of deviations from HWE and thus were useful for exploring Ae. albopictus population genetic structure. The set of microsatellite makers used here had already been successfully tested on habitat structuring Ae. albopictus in Reunion islands Understanding the patterns of gene flow and population genetic structure of invasive vectors like Ae. albopictus populations in Orissa. No obvious correlation between genetic and geographic distances was found, suggesting that the genetic structure has been shaped by additional biotic or abiotic factors. However, some evidence of correlation  was observed when the coastal plain populations were taken as a unit and compared with other populations. Such findings indicated that the coastal plain populations were genetically more differentiated than the other populations. This was also supported by high genetic differentiation (FST >0.125) when comparison was done between Coastal Plains populations with other populations  as unique genetic cluster, thereby rendering to be genetically divergent from other populations. Such type of genetic uniqueness of the Coastal Plains populations can be attributed to the ecological landscapes that form geographical barriers and separate it from other populations and thus act as a source for genetic diversity in Ae. albopictus mosquitoes. Within the Coastal Plains populations, GAN and JAG were the most genetically structured population comprising of more than 95% of cluster I, which suggest that GAN and JAG were highly differentiated from other geographic populations, possibly reflecting distinct introduction events with different geographic origins. This may be attributed to the frequent movements (in and out) of people from both the districts for trade related purposes like importation of materials etc., which in turn has modulated the genetic architecture of Ae. albopictus, thereby increasing the chances of transmission of arboviral diseases. Both the districts are on the verge of urbanization, which has led to the formation of ideal breeding sources, host availability, etc. that conferred an advantage to Ae. albopictus for rapid colonization and hence becoming more genetically structured. Similar results were obtained in La Reunion, which depicted that Ae. albopictus preferred to breed more in urban areas than in rural areas, thereby increasing its genetic diversity Ae. albopictus circulating in these regions. The NJ tree also supported the cluster analysis since GAN and JAG grouped together in the phylogenetic tree. In a broader view, the Coastal Plains populations were grouped together, with one exception of BAL (which grouped with ANG and DHE), while the Northern Plateau populations (MAY/KEO) and Eastern Ghats populations (KOR/MAL) grouped together in the NJ tree as another distinct clade.The pattern of genetic differentiation estimated from the microsatellite data indicated a significant level of genetic structuring among ulations . FurtherWolbachia-based vector control strategies to complement the existing vector control methods are currently being investigated by several researchers Wolbachia strains, their mating can be 1. compatible and produce viable offspring; 2. incompatible in both directions and produce infertile eggs  or 3. incompatible in one direction while the reciprocal cross is fertile . These attributes are now being studied by many researchers with the aim of developing new technologies and strategies to achieve significant improvements in vector control Wolbachia in mosquitoes is crucial to evaluate the possibility of utilizing Wolbachia-based vector control strategies. The present study based on PCR based genotyping of Wolbachia infection in Ae. albopictus mosquitoes of Orissa indicated widespread infection in the populations screened. This study revealed the infection/super-infection of two types of Wolbachia strains, i.e., wAlbA and wAlbB in Ae. albopictus mosquitoes of Orissa. Superinfection was more pronounced in Coastal Plains populations than other populations, which can thus modulate the vector dynamics for transmission of arboviral diseases in the Coastal regions. More detailed analyses revealed that 98% females were superinfected with wAlbA and wAlbB strains, which is in compliance with many studies that suggested both A and B strains in natural female Ae. albopictus are common and virtually fixed in a population and hence can be vertically transmitted efficiently Ae. albopictus mosquitoes, which suggests that the loss of wAlbB is hardly adaptive and hence the same vertical transmission of wAlbA+wAlbB will be maintained in the populations. The observed distribution of wAlbA and wAlbA+wAlbB infections in Ae. albopictus populations could be explained by the replacement of an uninfected population by the wAlbA+wAlbB superinfection Ae. albopictus mosquitoes of Odisha, which is in conformity to other studies that have documented similar findings Wolbachia in natural Ae. albopictus populations of Orissa and emphasize the influence of genetic diversity of Ae. albopictus in different topographical regions, which will help to initiate vector control programmes. Since Wolbachia infection has substantial influence on host fitness, the potential impact of Wolbachia on host population genetics and geographical patterns is extensive. Wolbachia can alter host population genetics through its CI inducing behavior that causes infected females to produce more offspring than uninfected ones. Thus, our findings emphasize the need for further investigation with deeper sampling and more genetic loci in order to thoroughly elucidate the forces that shape and maintain the population structure.The findings of this study will provide a benchmark to the State vector control authorities on the pattern of infection of Table S1Microsatellite primer sequences, repeat motives, size ranges and annealing temperatures used in this study.(DOC)Click here for additional data file.Table S2Analysis of Molecular Variance (AMOVA).(DOC)Click here for additional data file.


Zea mays L.) grain. One approach is through traditional breeding using recurrent selection. Using divergent selection, genetically related populations with extreme differences in grain methionine content were produced. In order to better understand the molecular mechanisms controlling grain methionine content, we examined seed proteins, transcript levels of candidate genes, and genotypes of these populations.Methionine is an important nutrient in animal feed and several approaches have been developed to increase methionine concentration in maize (Cys2 and CgS1 showed substantial differences in allele frequencies when two selected populations were compared to the starting populations. Major genes identified across cycles of selection by a high-stringency association analysis included dzs18, wx, dzs10, and zp27.Two populations were selected for high or low methionine concentration for eight generations and 40 and 56% differences between the high and low populations in grain methionine concentration were observed. Mean values between the high and low methionine populations differed by greater than 1.5 standard deviations in some cycles of selection. Other amino acids and total protein concentration exhibited much smaller changes. In an effort to understand the molecular mechanisms that contribute to these differences, we compared transcript levels of candidate genes encoding high methionine seed storage proteins involved in sulfur assimilation or methionine biosynthesis. In combination, we also explored the genetic mechanisms at the SNP level through implementation of an association analysis. Significant differences in methionine-rich seed storage protein genes were observed in comparisons of high and low methionine populations, while transcripts of seed storage proteins lacking high levels of methionine were unchanged. Seed storage protein levels were consistent with transcript levels. Two genes involved in sulfur assimilation, Cys2 and CgS1.We hypothesize that transcriptional changes alter sink strength by altering the levels of methionine-rich seed storage proteins. To meet the altered need for sulfur, a cysteine-rich seed storage protein is altered while sulfur assimilation and methionine biosynthesis throughput is changed by selection for certain alleles of  Zea mays L.) grain would reduce the level of supplementation required, decreasing the cost of animal diets. These approaches would be facilitated by an understanding of molecular mechanisms controlling methionine deposition in the grain.Methionine is an essential amino acid that is frequently supplemented in animal diets, especially those of poultry. Genetic approaches to increase the level of methionine in maize  from each plant and placing it in an individual well of a 96-well plate. This process was repeated with 10 plants from each selected population. Leaf tissue was collected from all seedlings that emerged in the starting populations.Samples were then processed through Monsanto’s high throughput genotyping facility in Ankeny, Iowa. Fully automated genotyping systems were used to process samples from DNA extraction through allele calling. DNA samples were genotyped for a set of biallelic single-nucleotide polymorphism (SNP) markers using the Taqman assay described by Livak . For quaThe molecular markers used were chosen from the Monsanto consensus map based on their polymorphic information content value. This consensus linkage map utilizes an intermated B73 × Mo17 population to map the locations of individual SNPs on each of maize’s ten chromosomes . Two groE. coli strain, which is auxotrophic for methionine [Methionine in mature maize grain was quantified using a high-throughput microbiological method described by Scott et al. . In the thionine . This plthionine  followedPrincipal components analysis (PCA) was used to explore the divergence across populations used in this study. In order to compute PCA, a common SNP marker set across the BS11- and BS31-derived populations was identified and merged. The final data set used for PCA consisted of 102 SNPS and 1,055 lines. By using this approach for PCA, the derived populations and cycles of selection could be easily compared.Y = mean + Ms + Pv + Zu + e where Y is a vector of classification for the HM or LM populations, s is a vector of SNP effects, and u is a vector of polygenic random effects. The variances of the random polygenic effects is assumed to be Var(u) = 2KVg where K is a square matrix of relative kinship coefficients and Vg is the genetic variance. A classification was used as the response variable, Y, because methionine level was not measured for each genotyped line individually. The Benjamini and Hochberg false discover rate (FDR) of 0.01 was applied for multiple testing of significant SNPs. Such a high stringency was used due the fact that the association analysis was conducted by means of a candidate gene approach. The model for association analysis was implemented in the rrBLUP [Association analysis  was imple rrBLUP  package e rrBLUP . For the2 test.Genomic DNA from approximately 50 individual plants from the cycle 6 populations was extracted from individual maize seedlings using a protocol scaled for 96-well plates . This DNA was used as template for a PCR using primers specific for the candidate genes of interest. The resulting PCR products were sequenced from both ends at the Iowa State University DNA Facility using the Applied Biosystems 3730×l DNA Analyzer  and the resulting sequences were aligned using the BioEdit Sequence Alignment Editor . The CluIn 2005, 2008 and 2010 corresponding to cycles 4, 6 and 8 respectively, immature endosperm tissue was collected at 18 days after pollination from between 3 and 10 plants from each population  thermocycler and consisted of a first strand synthesis of 45°C for 45 min, followed by 95°C for 10 min, followed by 40 cycles of 95°C for 30 sec, 59°C for 1 min, 72°C for 45 sec, followed by a dissociation curve. The delta-delta Ct value was calculated using either actin or the 18S ribosomal RNA as the internal control .Alcohol-soluble proteins were analyzed by high pressure liquid chromatography as described previously . Grain fIn order to generate populations with highly contrasting values for methionine, we continued the previously described recurrent selection program  using thGrain methionine concentration was initially evaluated after three cycles of recurrent divergent selection where large differences between HM and LM were observed . In cyclTo verify the observations made with the microbial assay and to obtain absolute values of methionine content, we evaluated the most advanced populations using the standard AOAC method of analysis Table . The amiOne way to increase methionine concentration would be to increase the total protein concentration of the seed. Summation of the amino acid concentrations in Table In order to better understand the genetic control of methionine content, we set out to identify genetic loci associated with this trait. We first set out to obtain an overview of the genetic architecture of the derived populations across cycles of selection. We did this by genotyping each population using single nucleotide polymorphisms (SNPs) from C0 to C6 depending on the derived population. Principal component analysis (PCA) was used to explore the divergence of the HM and LM populations for the BS11- and BS31-derived populations using a set of SNPs common to both populations. The first three principal components accounted for 22.00, 5.25, and 3.72% of the variation in the data, respectively. Interestingly, the BS11- and BS31-derived populations were separated by PC1, the HM and LM populations within the BS11-derived population were separated by PC2, and the HM and LM populations within the BS31-derived population were separated by PC3  of several genes known to be involved in sulfur assimilation, methionine synthesis, and deposition. Since the seed storage protein transcripts showed differential expression in some cases, we examined levels of the corresponding proteins and other alcohol-soluble proteins Figure . SeveralCys2 and CgS1 in the BS11-derived population and after 6 cycles of selection for high and low methionine (Table Cys2 and two alleles at CgS1. One consequence of selection could be a departure from Hardy-Weinberg equilibrium at loci controlling the methionine concentration. CgS1 did not have any alleles that differed significantly from the expected frequencies. In contrast, Cys2 had alleles that differed from the expected frequencies in both the C0 and the HM populations.Since our starting populations were broad-based synthetics, it is likely that multiple alleles are present at some of our candidate gene loci. We examined allele frequencies at two loci, ne Table . We idenCys2 locus, one of the alleles that started at 25% was reduced to 1% in the HM population while the same allele was increased to 74% in the LM population. This allele would be considered an unfavorable allele when selecting for high methionine concentration. Similarly, a Cys2 allele that started at 8% was increased to 29% in the HM population and was not detectable in the LM population. This allele would be considered a favorable allele. The situation is less clear at the CgS1 allele. An allele that started at 45% was increased to 93%, but the allele frequency of the LM population was nearly the same as the starting population.Recurrent selection would be expected to alter allele frequencies at loci that influence the trait under selection. Further, alleles that are enriched by selection for high methionine may be desirable alleles for increasing methionine concentration while alleles that are enriched by selection for low methionine may be undesirable. Changes in allele frequency were evident at both loci Figure . At the Recurrent selection has been shown to be an effective method for altering methionine concentration in maize grain . PopulatMechanisms controlling grain methionine concentration can be divided into source and sink effects. We attempted to study both types of effects, including transcript levels and allele frequencies of candidate genes involved in sulfur assimilation and methionine biosynthesis as well as seed storage protein transcript and protein levels. We observed differences in both source and sink candidate genes, leading us to conclude that selection for grain methionine concentration resulted in differences for both source and sink systems. We did not characterize enough genes to draw general conclusions about relative importance of source and sink effects. Analysis of other tissues would also be helpful in assigning relative importance to source and sink effects.Cys2 and CgS1 with changes in allele frequency, while in sink genes transcript and protein level differences were identified. Interestingly, Cys2 was a gene identified as lacking genetic diversity in a study of 14 inbred lines selected for maximum allelic diversity [Cys2 that we sequenced in BS11HMC6. Several of these alleles are present at low frequency. This result illustrates that collections of inbred lines may not represent the diversity present in breeding populations.The most striking difference in source genes occurred for iversity . In contdzr1[We characterized grain composition to understand the effects of selection on the methionine sink. Several changes were evident when comparing amino acid levels between the high and low methionine populations. Methionine was changed by the largest amount, with increases in the HM/LM ratio in both populations. The amino acid with the next largest change was cysteine, also a sulfur containing amino acid, however the direction of change in cysteine content was not consistent across populations. Methionine shares a common biosynthetic pathway with lysine and threonine. Interestingly, the HM/LM ratio for lysine is less than one in both the BS11- and BS31- derived populations, while the HM/LM ratio for threonine is less than one in the BS11- derived population. These reductions could be because nitrogen is limited in the seed, requiring resources to be shifted from the lysine and threonine branches of the pathway to support increased synthesis of methionine. The HM/LM ratio for nitrogen was greater than one in one selection program and less than one in the other, indicating that an increase in nitrogen is not a strict requirement for increasing methionine content. On the other hand, sulfur had HM/LM ratios greater than one in both selection programs. This is consistent with the increase in methionine content, and suggests that either sulfur uptake and/or assimilation are increased in the HM populations relative to the LM populations or that sulfur is differentially distributed in the plant between the HM and LM populations. Within the seed, the cysteine-rich 27 kDa gamma zein had lower transcript levels in the HM population in one season, and levels of this protein were lower as well. The two methionine-rich delta zein genes had the greatest increase in transcript levels comparing HM to LM and the corresponding proteins were increased as well. The 18 kDa delta zein showed the greatest increase in both transcript and protein levels. Transcript and protein levels of the 10 kDa delta zein both increased. This protein is increased in a high methionine mutant called dzr1. Interesdzr1 resultindzr1. The twoWe chose to focus this study on grain tissues, but it is very likely that biochemical changes in other tissues play a role in determining grain methionine concentration. Roots and leaves are known to be key organs for sulfur assimilation and would therefore be expected to influence grain methionine concentration. This may explain why we saw only minor differences in transcript levels of sulfur assimilation and methionine biosynthesis genes in grain, while the same genes showed large differences in allele distribution. It may be that the different alleles have different expression in tissues where sulfur assimilation is more active, such as roots and leaves. Selection for a trait on the basis of one tissue has been shown to influence other tissues. One example of this is that selection for long ears resulted in changes in plant height . Many phCys2 that was enriched from 8% to 29% in the course of selection for HM, while it was reduced to 0% in the course of selection for LM. The low frequency of this allele in the starting population makes it unlikely that this allele would be identified as a favorable allele in a study of association between methionine content and genetic loci in the starting population, but it clearly exhibits the characteristics of an allele that was altered by selection such as this study. Thus, selection experiments provide an excellent complement to association studies for the identification of valuable rare alleles.Caution should be exercised when attributing the observed differences between HM and LM populations to selection, because it is very difficult to rule out genetic drift as a possible mechanism. Changes that were observed in both the BS11- and BS31-derived experiments are consistent with the responses to selection observed, but even in these cases we cannot rigorously rule out genetic drift. This does not eliminate the value of these observations for development of further hypotheses about the role of different genes in determining grain methionine concentration. For example, selection experiments are particularly valuable for identifying rare alleles of potential importance. We observed an allele of The use of PCA as a tool for visual representation of genetic data can contribute useful insight into selection processes over time and has been used in various forms for population structure inference ,32. Prindzs18 and dzs10 showed a consistently strong association with methionine concentration for the BS11-derived population across cycles of selection. The lack of identified SNPs for the BS31-derived population is most likely due to the fewer number of SNPs used for that population. Another possible explanation is that the variation within BS31, separated by PC3, is considerably lower as compared within BS11. Thus, the few number of SNPs identified as significant could be explained by the lower level of variation within the BS31-derived population. There was commonality for significant SNPs within BS31 where zp27.4 was significant in two cycles of selection. This SNP is in the gene encoding the 27 kDa gamma zein. The separation of the derived populations with respect to PC1 indicates that selection within the derived populations occurs by different mechanisms. Thus, this could explain the lack of common significant SNPs between derived populations.In agreement with our candidate regions, results for r2, was calculated for the significant SNPs in the BS11-derived population and various LD blocks were observed depending on the particular cycle of selection. As expected, high LD existed between unlinked loci in all cycles of selection for the significant SNPs. In the calculation of LD between significant SNPs, two of the significant SNPs were fixed in C5, an indication of selection at those loci.Linkage disequilibrium blocks between SNPs can represent regions in the genome with a high level of co-inheritance and therefore co-selective pressure. The level of LD, measured as CgS1 locus was associated with HM/LM classification. In addition, some sulfur assimilation genes were transcriptionally up-regulated in the endosperm for one experiment and different alleles of CgS1 and Cys2 are present in the high and low populations. More research is needed to definitively establish the source of sulfur that accumulates in the high methionine zeins.Taken together, our data support a model in which selection for high grain methionine concentration increased sink strength though transcriptional up-regulation of methionine-rich zein. We cannot rule out the possibility of changes in free methionine or compounds related to S-adenosylmethionine. The additional sulfur required for this increased sink may have come from cysteine contained in the 27 kDa gamma zein gene, since the level of this protein is reduced. However, since levels of total cysteine are not reduced substantially and total sulfur levels are increased, reduction of cysteine-rich storage proteins is not a sufficient explanation. Additional sulfur in the seed is probably contributed by increased sulfur uptake and/or assimilation or from other sulfur sources within the plant. In support of this idea, a SNP near the SNP: Single nucleotide polymorphism; HM: High methionine; LM: Low methionine; LD: Linkage disequilibrium; PC: Principal component; C#: Cycle of selection; FDR: False discovery rate; PCA: Principal component analysis.The authors declare that they have no competing interests.MN carried out the association analysis. KV coordinated genotyping and analyzed genotype data. MA carried out RT-PCR. NA Sequenced alleles of candidate genes. AB analyzed alcohol soluble proteins by HPLC. MA carried out RT-PCR. AL carried out RT-PCR, methionine assays and sequencing of candidate genes. PS conceived the study and coordinated the work. All authors contributed to writing and approved the final manuscript.Populations used in this study and genotyping strategy.Click here for fileMap of SNP markers used in study.Click here for file


Telopea speciosissima (Proteaceae) is an excellent subject for studying the effect of geographic, edaphic and phenological heterogeneity on genotypic differentiation because previous studies show that these factors are correlated with morphological variation. Molecular, morphological and environmental datasets were combined to characterise the relative influence of these factors on inter-population differentiation, and Bayesian analyses were used to investigate current levels of admixture between differentiated genomes.Inter-population distance and differences in breeding times are barriers to reproduction that can contribute to genotypic differentiation between populations. Temporal changes in environmental conditions and local selective processes can further contribute to the establishment of reproductive barriers. Telopea speciosissima was shown to maintain a temporally unstable reproductive barrier between coastal and upland populations.A landscape genetic approach involving molecular and morphological analyses identified three endpoints of differentiated population groups: coastal, upland and southern. The southern populations, isolated from the other populations by an edaphic barrier, show low migration and no evidence of admixture with other populations. Amongst the northern populations, coastal and upland populations are connected along a skewed altitudinal gradient by genetically intermediate populations. The strong association between temperature and flowering time in Substrate-mediated allopatry appears to be responsible for long-term genetic isolation of the southern populations. However, the temperature-dependent reproductive barrier between upland and coastal populations bears the genetic signature of temporal adjustments. The extreme climatic events of the last glacial maximum are likely to have caused more complete allochronic isolation between upland and coastal populations, as well as exerting increased selective pressure upon local genomes. However, at intermediate altitudes, current climatic conditions allow for the incorporation of alleles from previously distinct genomes, generating new, intermediate genomic assemblages and possibly increasing overall adaptive potential. The identification of reproductive boundaries between genetically differentiated populations can provide useful cues to the factors influencing population-level connectivity and micro-evolutionary processes. Geographic and/or habitat isolation are among the most important factors responsible for establishing the levels of reproductive segregation that lead to measurable genetic differentiation . As dispLocal selective processes can further contribute to the development of pre- or post-zygotic barriers to reproduction. In such circumstances gene flow is restricted by assortative mating caused by the reduced competitiveness of migrants and/or admixed individuals within differentiated habitats ,6. OftenTemporal changes in local environmental conditions, such as those experienced during the climatic cycles of the Quaternary, can cause localised bottlenecks and extinctions of populations that were previously part of a continuous distributional range . Such peUnravelling the sequence and tempo of the events establishing reproductive barriers and affecting genetic structure can provide interesting insights into micro- and macro-evolutionary processes, as well as support the development of improved conservation strategies that are mindful of evolutionary potential. This is particularly relevant in a climate change context where predicted climatic shifts could have a significant impact on inter-population connectivity and micro-evolutionary potential.Telopea speciosissima R.Br.  is a particularly good model for studying the relative influence of climatic and environmental conditions on between-population connectivity: it is distributed along altitudinal and latitudinal gradients; it has a limited flowering season and marked differences in flowering times between populations [T. speciosissima sensu lato [T. speciosissima on sandstones of the Sydney Basin and T. aspera on the northern granites of the Gibraltar Range . The major axis of variation from ordinations separated these two species as distinct clusters but secondary ordination axes revealed considerable residual variation, suggesting that differentiation was also present among southern T. speciosissima populations.ulations ; and itsnsu lato  showed tIn this study we aim to detect the genetic signatures that identify the geographic, edaphic and climatic factors leading to differentiation between Waratah populations. In particular, we ask the following questions: is there congruence between morphological and genetic differentiation; how do environmental variables  differentially impact on genetic structure; and can we use species-wide analyses to identify directionality of gene flow among differentiated population groups, and investigate the temporal strength of reproductive barriers?Telopea speciosissima occurs sporadically in small populations, of rarely more than a few hundred plants around the Sydney region in south-eastern Australia . Seven simple sequence repeat (SSR) loci specifically developed for T. speciosissima [et al. [We aimed to obtain a suitable account of the genetic diversity across the entire distribution of the species, as well as obtain a sample that would overlap with that of previous morphological studies . Leaf maosissima  were use [et al. . To teste) and observed (Ho) heterozygosities, and the inbreeding coefficient  were alPOP 3.2a , and sigPOP 3.2a .SHUA, was used to obtain an estimate of between-population dispersal based on an average effective population size of 100 individuals (N100m). SHUA provides a robust estimation of genetic exchange over a wider range of dispersal values than FST, because it is more sensitive to rare alleles, it can incorporate unequal numbers of individuals per population and shows no dependence between measures at different hierarchical levels [Shannon's information index of population subdivision, l levels ,25.et al. [K and the optimal burn-in period, we tested K from 1 to 18 through five independent runs. All runs were based on 7.5 × 105 Markov chain Monte Carlo iterations after a burn-in period of 3 × 105 iterations without prior information on the locality of origin of the individuals sampled. The admixture frequency model was run under the assumption of correlated allele frequencies to improve clustering of closely related populations [K statistical approach suggested by Evanno et al. [We used the Bayesian clustering method described by Pritchard et al.  and implulations . The opto et al. .ST values (FST/(1- FST) andAnalysis of molecular variance  was useSHUA were run using GenAlEx6.3 [ln-adjusted pairwise geographical distances. AMOVA, PCoA, Mantel and nAlEx6.3 .ST >0.2 (as is the case in this study) a smaller number of loci is sufficient for detecting admixture events [We used the Bayesian model implemented in NewHybrids  to detece events .5 sweeps followed by 7.5 × 105 sweeps. Posterior probability of assignment as pure, F1s, F2s, and backcrosses were initially measured and than combined to obtain proportions of admixture vs. pure.Our objective was not to identify and quantify specific admixture categories but rather to ascertain the mixing of differentiated upland and coastal genomes. To do this we conducted a series of preliminary analyses that culminated in a run using seven populations: the three with highest PP of assignment to the upland group, the three with highest PP of assignment to the coastal group, and the four at intermediate altitude. Jeffreys priors were used with a burn-in of 3.5 × 10We selected morphometric variables that had high loadings (>|0.95|) on the second axis of the PCoA of Crisp & Weston  and scorT. speciosissima  was recorded during previous site visits (n= 256). Flowering dates were converted to day of the year and correlated to altitude of collection site. Data on flowering time of mixed seedlings grown in three plantations at different altitudes in the Sydney region  were extracted from Dupree & Goodwin [n = 731). Finally, flowering date of plants collected from wild sites and grown in a common garden environment  was recorded and compared with altitude of provenance .The date of first flowering of individual plants from six populations across the altitudinal range of  Goodwin  and simi2 - equivalent to 930 m vertical × 750-775 m horizontal resolution).The climatic and environmental data presented in Figures T. speciosissima populations. Allelic richness ranged from R10 = 3.6 to 6.0 , and from Ho = 0.586 to 0.762 . Turpentine Range and Waterfall Flat showed heterozygotic deficits and West Head heterozygotic excess (Table IS = 0.024 (P < 0.05), FIT = 0.148 (P < 0.001) and FST = 0.127 (P < 0.001). Pairwise tests of linkage disequilibrium showed one combination (TS03bgt and TS18bgt) to be out of equilibrium but not after Bonferroni correction.The seven SSR loci amplified a total of 98 alleles mean A = 14.0) across the 18 4.0 acrosLnP(D) values at K = 2 and K = 3, and the ΔK statistic preferentially supported K = 3 . At K = 3, populations were grouped into coastal (located within 30 km of the coast), upland  and southern . Average genetic divergence between upland and southern population was FST = 0.228, while average FST among all other populations was FST = 0.068. Average pairwise FST values and SHUA-based estimates of between-population dispersal (based on Ne = 100) suggest high levels of gene flow within population groups  and between pairings of upland vs. intermediate, and coastal vs. intermediate populations , but not across the 10 populations used for the NewHybrid analysis , suggesting that the differentiation measured along the altitudinal gradient was not caused by geographic distance alone.AMOVA supported significant segregation between the three population groups. High levels of genetic variance were partitioned to between-group differentiation, although most of the genetic differentiation was partitioned to within-population differentiation (as expected for outcrossing species). Table Strong patterns of pure (ie. with PP > 80% of being assigned to one of the three distinct groups) and admixed genotypes were detected across populations Figure . F2 was et al. [A recent study by Roberts et al.  showed tPCoA of the morphometric data produced a similar ordination to the PCoA of genetic data in that specimens from upland, southern and coastal groups of populations formed clusters that occupied the same relative positions to the corresponding clusters in the genetic analysis, albeit with some overlap as would be expected from characters that are both phenotypically labile and ontogenetically variable , regardless of altitude. The timing of the temperature shift necessary for flowering varied across the altitudinal gradient, and corresponded to the genetic differentiation observed between coastal and upland populations . For instance, average flowering time at Evans Lookout (980 m) was on Julian day 312, while at the coastal site at Patonga (180 m) it was on day 261. There was a weaker but significant relationship between flowering time and altitude in three cultivated populations sourced from mixed genotypes , and data from the common garden environment suggested that altitude of original collection  had no influence on flowering within a controlled environment .The analysis of flowering time from 256 flowering events from seven natural locations distributed along the altitudinal gradient showed a very strong association between altitude and flowering time , andkeriana; ).T. speciosissima. PCoA and Bayesian assignment identified three major population groups  supported by AMOVA and between-group FST values. Morphological analysis discovered similar patterns of geographic variation, confirming strong differentiation in the south and identifying a previously unreported upland morphotype.Although high gene flow maintains equilibrium at a local scale, between-population connectivity appears to be less consistent in Understanding the processes leading to genetic and morphological differentiation requires the identification of the barriers that cause partial or complete reproductive isolation . EdaphicT. speciosissima are not easily dispersed and tend to germinate in proximity to the maternal plant [Although the terminally winged seeds of al plant , it is ual plant  and our T. speciosissima. Flowering in the Waratah is triggered by a shift in average maximum temperature to around 20°C, and this shift occurs gradually along the altitudinal gradient  suggests that vertebrate-mediated pollen dispersal is not uniform across what is fairly continuous habitat. Such pattern suggests that habitat isolation might also contribute to the genetic differentiation observed between upland and coastal populations, a hypothesis we are currently testing via cross-pollination, reciprocal transplant and controlled-environment experiments.Our study on a long-lived woody shrub distributed along altitudinal and latitudinal gradients, provides evidence for the contrasting temporal stability of different reproductive barriers. While the association between geographic and genetic isolation appears to be stable, the temperature-dependent reproductive barrier between upland and coastal population bears the genetic signature of temporal adjustments. The detection of localised admixture events and the availability of morphological, phenological and climatic  information helped us identify a transitional zone established as a result of the post-glacial alleviation of extreme differences in climatic conditions.These temporal changes resulted in the merger of reproductively isolated and differentiated genomes, a process that can have deleterious  or beneficial (the incorporation of novel diversity favouring adaptation to changing conditions) evolutionary consequences . The lonMR and PHW conceived and designed the study; KAGT, CAO, CBA, PHW respectively contributed the genetic, phenological, environmental and morphological data; MR analysed the molecular data and prepared the manuscript with all authors editing and approving the final manuscript.