Scutellaria baicalensis Georgi (Huang-qin or Chinese skullcap) is a very important medicinal plant in China. Over the past several decades, wild resource of this species has suffered rapid declines and large-scale cultivation was initiated to meet the increasing demand for its root. However, the genetic impacts of recent cultivation on S. baicalensis have never been evaluated. In this study, the genetic diversity and genetic structure of 28 wild and 22 cultivated populations were estimated using three polymorphic chloroplast fragments. The objectives of this study are to provide baseline data for preserving genetic resource of S. baicalensis and to evaluate the genetic impacts of recent cultivation on medicinal plants, which may be instructive to future cultivation projects of traditional Chinese medicinal plants.Cultivation of medicinal plants is not only a means for meeting current and future demands for large volume production of plant-based drug and herbal remedies, but also a means of relieving harvest pressure on wild populations. S. baicalensis (HapA-Y and Hap1-7) were identified when three chloroplast spacers were combined. These haplotypes constituted a shallow gene tree without obvious clusters for cultivated populations, suggesting multiple origins of cultivated S. baicalensis. Cultivated populations (hT = 0.832) maintained comparable genetic variation with wild populations (hT = 0.888), indicating a slight genetic bottleneck due to multiple origins of cultivation. However, a substantial amount of rare alleles (10 out of 25 haplotypes within wild populations) lost during the course of S. baicalensis cultivation. The genetic differentiation for cultivated group (GST = 0.220) was significantly lower than that of wild group (GST = 0.701). Isolation by distance analysis showed that the effect of geographical isolation on genetic structure was significant in wild populations , but not in cultivated populations . These genetic distribution patterns suggest that a transient cultivation history and the extensive seed change among different geographical areas during the course of S. baicalensis cultivation.Thirty-two haplotypes of S. baicalensis maintains comparable genetic diversity relative to wild populations, recent cultivation has still imposed profound impacts on genetic diversity patterns of the cultivated S. baicalensis populations, i.e., the loss of rare alleles and homogenization of cultivated populations. This study suggests that conservation-by-cultivation is an effective means for protecting genetic resources of S. baicalensis, however, the wild resources still need to be protected in situ and the evolutionary consequences of extensive seed exchange mediated by human being should be monitored carefully.Although cultivated  The World Health Organization has estimated that more than 80% of the world's population depends on herbal medicine for primary healthcare needs . Most maHowever, cultivation can also have impacts on conservation, which need to be better understood . MedicinMedicinal plants play inherent and prominent roles in the general health service in China. Due to long-term exploitation of wild medicinal herbs, many important Chinese traditional medicinal plants are becoming rare and endangered . In ordeScutellaria baicalensis Georgi (Huang-qin or Chinese skullcap) is a perennial herb of the family Lamiaceae with fleshy root, branched stems, papery leaves, purple-red to blue flowers, and black-brown ovoid nutlets . Thirty-two haplotypes of S. baicalensis (HapA-Y and Hap1-7) and 2 haplotypes of S. rehderiana (HapZ1-Z2) were identified when atpB-rbcL, trnL-trnF, and psbA-trnH sequences were combined  evenly distributed across the haplotype network, not showing any clusters.In the haplotype network Fig. , the 32 Haplotype frequencies in each population and geographical distribution are presented in Fig. S. baicalensis, 25  were recovered in wild populations and 22  were carried by cultivated individuals  of cultivated S. baicalensis was significantly higher than that (hS = 0.265) of wild Huang-qin  was significantly higher than that of the cultivated , and most genetic variance were among populations (56.61%) and within populations  between the cultivated and wild groups calculated by DNASP 4.00 was well consistent with the result of AMOVA analysis.Consistent with the haplotype distribution Fig. , populatOryza rufipogon and O. sativa were recovered in the cultivated rice [S. baicalensis were revealed  were found in both wild and cultivated populations and these shared haplotypes were recovered from different wild populations , althoupurpurea ,44). In ons Fig. , 3. Thisons Fig. , indicatgenitors .S. baicalensis. Other population genetic studies on recently-cultivated Chinese medicinal plants also suggested that high genetic diversity in cultivated populations is due to their slight cultivation bottlenecks [According to the tremendous literature of traditional Chinese medicine, Huang-qin was rarely cultivated until the foundation of the People's Republic of China in 1949 . Howevertlenecks -17, whicS. baicalensis have been officially registered in China [S. baicalensis populations because relaxation of selective constraint allow the accumulation of mutations that may otherwise be deleterious in nature [S. baicalensis, the relaxation of selective constraint might play limited role in molding the genetic diversity pattern of cultivated Huang-qin.Apart from demographic factors, selection is another important element in shaping the genetic diversity pattern of cultivated species. Artificial selection for desired traits can decrease genetic diversity of target loci and their linked loci beyond that caused by the bottlenecks . The facin China  suggestsn nature ,51. HoweS. baicalensis populations displayed a lower proportion of genetic variation among populations (GST = 0.220) than wild populations (GST = 0.701). In addition, Mantel test analyses showed that the effect of geographical isolation on genetic structure was significant in wild populations  is higher than that of noncrop species (GST = 0.212).Cultivation impacts not only the amount of genetic variation contained in cultivated populations but also the structure of this variation ,52,53. IS. baicalensis. First, there has been insufficient time for artificial selection and breeding to exert influence on the genetic divergence of cultivated S. baicalensis. The crop species  summarized in the review of Hamrick and Godt [S. baicalensis, due to its short cultivation history, artificial selection and breeding cultivars are unlikely to promote the genetic differentiation of cultivated populations as suggested by few S. baicalensis cultivars in China [S. baicalensis [Two possible reasons may account for the unusual pattern revealed in and Godt  almost hand Godt ,54,55. Hin China . This faSolanum muricatum), a herbaceous Andean domesticate, suggested that human interchange among communities and countries in the past 50 years or so has considerably weakened the geographic differentiation of genetic diversity of cultivated pepinos [Coptis chinensis, Magnolia officinalis, the bulking and mixing of seeds from different geographic locations are the common practice, which produced lower genetic differentiation among cultivated populations [r = 0.4346, P < 0.0010; Fig. r = 0.0599, P = 0.2710; Fig. S. baicalensis than in wild populations. For example, HapG in wild populations  is mainly restricted to the central range of this species, whereas this haplotype occurred in 17 of 22 cultivated populations , a small tree that bears fruit similar to tiny mongo in Mesoamerica, out of its natural, wild habitats and planting them in yards and other means of cultivation, farmers in the Mesoamerican region have helped to preserve the jocote's diversity [et al. [et al. [S. baicalensis are also in traditional ways. Usually, farmers collected the seeds of S. baicalensis directly from local wild resources and then cultivated in the field. Sometimes, the germplasm can be dispersed to other places by their relatives or friends or by sale in the markets. Slight reduction of genetic diversity and little change of genetic composition in cultivated S. baicalensis, as well as a few specific haplotypes of cultivated group, confirm the effectiveness of saving plant diversity through local cultivation. This study further suggests that bringing wild medicinal plants into cultivation from different locations may help to widen the genetic background of cultivated populations, which will be beneficial for the sustainable utilization of natural resources.It has long been argued that traditional agriculture can serve as an important reservoir of genetic variability ,56. For iversity . Likewis [et al.  and He e [et al. . AccordiS. baicalensis, the wild resources still need to be protected in situ. This study did not find significant reduction of genetic diversity and apparent change of genetic composition in cultivated S. baicalensis, however, this pattern reflects mainly the changes of common haplotypes rather than rare alleles. In fact, 10 out of 25 haplotypes within wild populations have lost during the course of S. baicalensis cultivation. The results conform to the theoretical expectation that bottlenecks of short duration may have little effect on heterozygosity  but will reduce severely the number of rare alleles [S. baicalensis through in situ conservation of wild populations.Although cultivation is an effective strategy for preserving genetic resources of  alleles . Rare al alleles . It is tS. baicalensis cultivation exerts a significant impact on the genetic architecture of cultivated S. baicalensis and may also have profound implications for the conservation and utility of S. baicalensis germplasm. Genetic mixture induced by extensive seed exchange means that a fraction of cultivated populations may be sufficient to preserve most genetic variation of S. baicalensis. This will undoubtedly facilitate the conservation of genetic diversity of S. baicalensis through cultivation. However, numerous theoretical and empirical studies have suggested that genetic mixture of populations that are adapted to different local conditions could result in outbreeding depression, the reduction in fitness caused by the breakdown of coadapted gene complexes [S. baicalensis are unknown so far, more studies are crucially needed to monitor the potentially negative impacts of seed exchange on the adaptation of wild populations and the growth of cultivated populations.Seed exchange during the course of omplexes . Extensiomplexes . The evoS. baicalensis is comparable to wild populations due to the large initial population size and the short cultivation history, substantial rare alleles have lost and extensive seed exchange has caused the homogenization of cultivated populations during the course of cultivation. This study not only provides baseline data for preserving genetic resource of S. baicalensis through conservation-by-cultivation approach, but also represents a paradigm for evaluating the genetic impacts of recent cultivation on medicinal plants, which may be instructive to future cultivation projects of traditional Chinese medicinal plants.Facing the rapidly growing demands for medicinal plants, domestic cultivation is a viable and long-term way of protecting wild medicinal plant resources . HoweverL-QH conceived of the study and revised the manuscript. Q-JY performed sample collection, molecular experiment, data analysis and drafted the manuscript. Z-YZ contributed to the conception of the study, the writing and revision of the manuscript. JH participated in DNA extraction, PCR and sequencing. L-PG helped to coordinate the study and finish statistical tests. A-JS carried out partial sample collection. All authors read and approved the final manuscript.Trichosanthes. Dr. Qing-Jun Yuan is interested in conservation genetics and domestication of cultivated medicinal plants. Prof. Zhi-Yong Zhang is working on molecular phylogeography and molecular systematics in the subtropical plants. Juan Hu is a master student studying the application of molecular markers in authentication of Chinese Materia Medica. Prof. Lan-Ping Guo and Ai-Juan Shao are with special concerns about the sustainable utilization and conservation of natural medicinal resources.Prof. Lu-Qi Huang specializes in molecular pharmaceutics and the taxonomy of some systematically uncertain taxa in Chinese herbal medicine, such as Scutellaria baicalensis and 1 wild population of Scutellaria rehderiana.Chloroplast haplotype frequencies in 28 wild populations of Click here for fileScutellaria baicalensis.Chloroplast haplotype frequencies in 22 cultivated populations of Click here for file


Mestizo populations (i.e. in regions of mainly European and Native settlement) from seven countries in Latin America based on data for 678 autosomal and 29 X-chromosome microsatellites. We found extensive variation in Native American and European ancestry  among populations and individuals, and evidence that admixture across Latin America has often involved predominantly European men and both Native and African women. An admixture analysis allowing for Native American population subdivision revealed a differentiation of the Native American ancestry amongst Mestizos. This observation is consistent with the genetic structure of pre-Columbian populations and with admixture having involved Natives from the area where the Mestizo examined are located. Our findings agree with available information on the demographic history of Latin America and have a number of implications for the design of association studies in population from the region.The large and diverse population of Latin America is potentially a powerful resource for elucidating the genetic basis of complex traits through admixture mapping. However, no genome-wide characterization of admixture across Latin America has yet been attempted. Here, we report an analysis of admixture in thirteen  The history of Latin America has entailed a complex process of population mixture between Native and recent immigrants across a vast geographic region. Few details are known about this process or about how it has shaped the genetic makeup of contemporary Latin American populations. To perform a broad exploration of the genetic diversity of Latin America we carried out genome-wide analyses in 13 mestizo populations sampled from 7 countries across the region. We observe a marked variation in ancestry both within and between mestizo populations. This variation in ancestry correlates with pre-Columbian Native population density in the areas examined and with recent patterns of demographic growth of the sites sampled. We also find evidence that the mixture at the origin of these populations involved mainly immigrant European men and Native and African women. Finally, mestizo populations show a differentiated Amerindian genetic background, consistent with a predominantly local Native ancestry. Mestizos thus still reveal the genetic imprint of the pre-Columbian Native American population diversification. Our study helps delineate the genetic landscape of Latin America and has a number of implications for gene identification analyses in populations from the region. There is growing interest in the application of admixture mapping to the identification of genes influencing complex traits (including disease) in populations tracing their ancestry to genetically differentiated populationsth century) have been settled mainly by Natives and Europeans (thus roughly corresponding to the term “Mestizo” populations).To help draw a more detailed picture of the genetic landscape of Latin America, here we report genetic diversity and admixture analyses based on microsatellite genome scan data for 249 individuals from 13 urban centers sampled in seven countries across the region . For thiP = 0.04). The highest African ancestry (∼10%) occurs in Mestizo in relative proximity to circum-Caribbean areas (Oriente and Medellin) and in Southern Brazil (RGS), and thus at the periphery of regions with large past African immigration. Based on the autosomal data, estimates of the mean time since admixture in the 13 Mestizo populations range between ∼6–14 generations  is observed between autosomal heterozygosity and European ancestry . This pattern is consistent with admixture involving predominantly European men and Native women. Such a sex bias in European-Native admixture has been inferred in Mestizo populations mainly based on mtDNA and Y-chromosome polymorphismsP<0.001). Such a sex bias in African admixture has been inferred African Americans from the USP<0.01). This suggests that the sex bias of admixture has been more pronounced in areas with lower Native population density, consistent with the observation that Mestizo populations from areas with low Native population density (such as Medellin and CVCR) can have a predominantly European autosomal background and at the same time an almost exclusively Native American mtDNA ancestryAt the X-chromosome level, the proportions of African and Native American ancestry estimated are usually larger than those based on autosomal markers, with a concomitant reduction in European ancestry  for Euclidean distances and −0.570 (R2 = 0.325) for effective distances.The congruence between pre-Columbian genetic structure and the genetic differentiation of the Mestizo is also evidenced in the correlation of the logarithm of the geographic distance between Mestizo and Native populations, and the size of the corresponding ancestry components (as shown in P<0.05) and in the population-based analysis (P<0.05). The more heterogeneous Native American ancestry of larger urban agglomerations is consistent with them having attracted immigrants from relatively distant areas, thus potentially tracing their ancestry to various, differentiated Native groups. By contrast, smaller urban centers appear to trace their ancestry to fairly defined Native groups, with subsequent maintenance of greater isolation than larger agglomerations. This genetic pattern agrees with demographic data showing that the expansion of major cities in Latin America has often been driven by regional immigration rather than by internal growthThe analysis of admixture considering a structured ancestral Native American population also suggests that a stronger regional ancestry is present in the smaller urban centers sampled. The variance of the estimated Native ancestry components is negatively correlated with the logarithm of population size , both inThe large variation amongst the Mestizo examined in the mean Native American ancestry and in individual admixture proportions, and the regionally differentiated Native American ancestry, testify to the marked genetic heterogeneity of Latin American populations. These observations have a number of implications for the application of admixture mapping in the region. The large variation in mean Native American ancestry between populations implies that the power of admixture mapping will vary considerably in studies targeting different geographic areasIn conclusion, this initial genome-wide analysis of admixture across Latin America has revealed a hitherto undetected differentiation of the Native American ancestry in Mestizos. This fact, together with the extensive variation observed in rates of admixture across populations, and sometimes also between individuals within populations, needs to be considered when designing admixture mapping studies in specific Latin American populations. Despite these complications, we anticipate that admixture mapping in Mestizos should prove a fruitful strategy for analyzing the genetic basis of phenotypic traits, including disease, differing between Native Americans and Europeans.http://www.cephb.fr/hgdp-cephdb/)A total of 249 unrelated individuals from 13 Mestizo populations were examined . The indhttp://research.marshfieldclinic.org/genetics/) for 751 microsatellites distributed across all 22 autosomes and 35 markers on the X-chromosome. The markers examined are included in Marshfield Screening Sets 16 and 54, commonly employed in linkage studies. Standardization of allele calls for compilation of datafiles combining genotypes for 678 autosomal and 29 X-chromosome markers in Mestizos, Europeans, Africans and Native Americans was performed as detailed in Wang et. al. Individual genotype data were collected by the Marshfield Foundation Mammalian Genotyping Service (http://www.r-project.org). STRUCTURE runs used an admixture model with correlated allele frequencies and with individuals from ancestral populations assigned to K predetermined clusters . K was varied in order to examine different groupings of Native American populations while considering Europeans and Africans as single independent clusters: K = 3 when grouping all Native American data into a single cluster, K = 7 when Native American populations were grouped into five linguistic stocks and K = 28 when each Native American population was considered independently. Population assignment to linguistic stocks followed the linguistic classification proposed by Ruhlen (1991)Estimation of individual ancestry proportions was performed with the programs STRUCTUREFST was performed using eq. 5.3 of Weir (1996)I) for the Mestizo was calculated using the expression of Rosenberg and Huang :AI and BI are the observed heterozygosities of European and Native American populations, F the FST estimated between Europeans and Africans, and γ the proportion of European ancestry in the Mestizo. A related expression for the expected heterozygosity after admixture of three populations (i.e. including Africa) did not produce a significantly better fit with the data analysed here.For each population, heterozygosity was computed for each locus using the unbiased estimator of Weir (1996)et al. (2007)For each Mestizo population, we computed a Pearson correlation coefficient between the Native American ancestry components Click here for additional data file.Table S113;14. Population size information from compilation in(http://www.citypopulation.de/cities.html).Location of sampling site, current population size and relative pre-Columbian population density in the region. * Representing about 10, 5 and 1 individuals per square mile, according to available estimates(0.03 MB XLS)Click here for additional data file.Table S2Mean ancestry proportions, variance (var.) and standard errors (s.e.) for individuals from thirteen Mestizo populations.(0.03 MB XLS)Click here for additional data file.Table S3Mean number of generations (s.d.) to admixture in 13 mestizo populations based on 678 autosomal microsatellite markers.(0.03 MB XLS)Click here for additional data file.Table S4Mean ancestry proportions, variance (var.) and standard errors (s.e.) for individuals from thirteen Mestizo populations estimated with Native Americans subdivided according to linguistic affiliation.(0.03 MB XLS)Click here for additional data file.Table S5Mean ancestry proportions, variance (var.) and standard errors (s.e.) for individuals from thirteen Mestizo populations estimated with each Native American population considered individually.(0.05 MB XLS)Click here for additional data file.Dataset S1Genotype data used in Geographic patterns of genome admixture in Latin American Mestizos.(1.51 MB ZIP)Click here for additional data file.


Spodoptera frugiperda (J.E. Smith) (Lepidoptera: Noctuidae), the fall armyworm is the most economically important maize pest in the western hemisphere. This research focused on the genetic variability of the maize host strain because there is a lack of information in this area of S. frugiperda research. Amplified fragment length polymorphism (AFLP) was used to assess the genetic variability of S. frugiperda over a large geographic area. Twenty populations were collected from the maize, one population was collected from princess tree, one population was collected from lemon tree, and one population was collected from bermudagrass. The 23 populations were from Mexico, the continental United States, Puerto Rico, Brazil, and Argentina. The objective of this research was to evaluate whether the majority of genetic variability was within populations or between populations. The AFLP results showed that the majority of the genetic variability is within populations and not between populations, indicating minor gene flow and suggesting that S. frugiperda in the Western Hemisphere are an interbreeding population. Spodoptera frugiperda (J.E. Smith) (Lepidoptera: Noctuidae) is a migratory pest endemic to the Western Hemisphere that occurs from Southern Canada to Argentina .AFLP markers were originally developed for plants with small genomes but also became highly effective for plants with larger genomes. AFLP is a tool that generates highly polymorphic molecular markers that aid in building linkage maps and assessing genetic variation. AFLP has been successfully used for the study of insects , includiS. frugiperda are relatively large and provided the amounts of DNA needed. AFLP products are sorted according to size using gel electrophoresis. Two types of gels are used: agarose gels may be used to separate fragments from 300 base pairs (bp) to 1 kilobase (kb) pairs in size; and polyacrylamide are the best choice for smaller fragments (10 bp to 20 kb)  .S. frugiperda populations over a large geographic area. AFLP markers were selected to measure genetic variability between 20 S. frugiperda populations collected from maize (Zea mays), one population collected from lemon tree (Citrus limon), one population collected from princess tree (Paulownia tomentosa), and one population collected from bermudagrass (Cynodon dactylon).The objective of this research was to assess the genetic variability of S. frugiperda DNA for future analysis. The results showed that lyophilized S. frugiperda larvae yielded amounts of DNA suitable for molecular analysis similar to fresh S. frugiperda larvae. Populations were collected from the Southern United States, Puerto Rico, Mexico, Brazil, and Argentina for this study. Larvae were collected from maize during the vegetative to early reproductive growth stage. Larvae were identified as S. frugiperda in the field at the time of collection and again at the Insect Genetics Laboratory at the University of Nebraska using morphological characteristics.Samples were collected from each location . Samples2O and stored at -80° C and; 3) Larvae were lyophilized in the country of collection then shipped at ambient temperature and stored dry at -80° C. Larvae were homogenized in 500 µl extraction buffer . Proteinase K (concentration of 200 µg/ml extraction buffer) was added to the homogenate for 2 hrs at 65°C. RNase A (500 µg/ml) was added to the homogenate and held for 3 hrs at 37°C. After RNA and protein were removed from each sample, the homogenate was centrifuged at 13,000 rpm for 5 min at room temperature. The supernatant was extracted with 500 µl of chloroform: isoamyl alcohol (24:1) by centrifugation at 14,000 rpm for 20 min. to separate the phases. The aqueous phase was transferred into an autoclaved 1.5ml micro centrifuge tube and the chloroform: isoamyl step was repeated. DNA was precipitated by adding 400 µl chilled (-20° C) isopropanol to the aqueous phase and incubated at 4°C for 8 h. After incubation the precipitate was centrifuged at 13,000 rpm at 4°C for 30 min. The isopropanol was decanted off; the DNA pellet was rinsed with 500 µl 100% ETOH and centrifuged at 13,000 rpm at 4° C for 5 min and repeated a second time. The ETOH was decanted off and the pellet was air dried at 24°C for 45 min. 50 µl 1X TE buffer  was poured onto the DNA pellet and stored at 4°C for 8 hours. After the DNA was re-suspended in 1X TE buffer, each sample was quantified by running a 1% agarose gel with a λDNA marker (22.2 ng/µl). TE buffer (1X) was added to DNA samples until they reached a concentration of 22.2 ng/µl concentration of genomic DNA. The agarose gels were visualized using Genomics Solutions software.DNA was isolated from seven larvae  per population using a modification of Black & Duteau's  CTAB extS. frugiperda populations. The AFLP procedure was carried out in 3 steps: 1) DNA template preparation; 2) DNA template preamplification and; 3) AFLP Selective amplificationA modified AFLP  procedurMseI restriction endonucleases  for 2.5 hrs at 37°C in solution containing 1.25 µl of 10X One-Phor-All buffer , 0.125 µl of 10 U/µl MseI enzyme (1.25U/reaction), 0.0625 µl of 20 U/µl EcoRI enzyme (1.25 U/reaction), 0.125 µl of 10 ng/ml BSA  (New England Biolabs), and autoclaved nanopure H2O. Five µl of ligation mixture containing 0.15 µl of T4 DNA ligase and 0.5 µl of 10X T4 ligase buffer (New England Biolabs), 0.5 µl of 5 pmoles/µl EcoRI adapter, 0.5 µl of 5 pmoles/µl MseI adapter , and 3.35 µl autoclaved nanopure water was added to the restriction digestion product and was incubated for 10 hrs at 25°C using an MJ Research (www.operon.com) PTC-200 Peltier Thermo Cycler ; the ligation mixture was diluted by adding 135 µl of 1X TE buffer to each sample.DNA Template Preparation. Restriction digestion was completed using 7 µl of quantified genomic DNA (155.5 ng) that was incubated with EcoRI and EcoRI adapted ends and MseI ends , 1.0 µl of 10X PCR buffer containing 15mM MgCl2 and 0.20 µl of 5 U/µl AmpliTaq DNA polymerase (1.25 U/reaction)  were added to each reaction tube containing 1 µl of diluted ligation product and amplified using 20 PCR cycles of 30s at 94°C, 1 min at 56°C, and 1 min 72°C. The oligonucleotide primers in the pre-amp primer mix II are complementary to the adapter/restriction site with MseI primer containing one selective nucleotide (M+1 primer) and EcoRI primer containing no selective nucleotide (E+o primer). Each preamplification product was diluted with 190 µl of nanopure H2O.Preamplification of DNA Template. A master mix of 8 µl pre-amp primer mix II containing two oligonucleotide primers, 2, 0.08 µl of 5 U/µl AmpliTaq polymerase (Applied Biosystems), 2.0 µl of MseI primer  and 0.3 µl of 1.0 pmol/µl IRD-700 labeled EcoRI primer . The “Touchdown” PCR program: 1 cycle of 30s at 94° C, 30s at 65° C, and 1 min at 72° C; 12 cycles of 30s at 94° C, 30s at 65° C  and 1 min at 72°C; 23 cycles of 30s at 94°C, 30s at 56°C, 1 min at 72°C; then hold at 4°C was used for selective amplification. Reactions were stopped prior to loading the selective amplification product on polyacrylamide gels by adding 2.5 µl stop solution (LI-COR) to each reaction tube, then holding at 95°C for 3 min., then cooling to 4° C prior to loading the PAGE gel. 42 samples were run per gel (6 populations of 7 samples each), and IRD-labeled 50-700 bp size marker (LI-COR) in two lanes, 1 µl of marker was loaded into lanes 1 and 44, lanes 2 through 43 contained 1 µl of selective amplification product. Electrophoresis through KBplus 6.5% ready-to-use gel matrix (LI-COR) was used to separate the DNA and the bands were detected by a LI-COR Gene Read IR 4200 sequencer.AFLP Selective Amplification. Five primers were selected, in four primer pair combinations for selective amplification . A selecAFLP bands were evaluated using an IRD-700 labeled 50-700bp marker as a reference and scored using SAGA Generation 2 Software Version 3.2 . The data set consisted of 1's and 0's (presence or absence respectively) as analyzed from each AFLP gel.Coefficient of variation is a tool used to assess whether enough data were used  for proper genetic analysis. DBOOT version 1.1  was usedS. frugiperda. Genetic variation (h) between populations was measured using Nei's gene diversity index. Popgene considered a locus polymorphic if the frequency of the most common allele fell below a 0.95 threshold. Genetic variation between populations was assessed using GST. GST is expressed as the heterozygosity (H) of a single population subtracted from the heterozygosity of the total population, divided by the heterozygosity of the total population  = 0.5 (1- GST) . Popgene assesses heterozygosity as differences in banding patterns or polymorphisms between individuals or populations.Popgene version 1.32  was usedA binary data matrix was used to estimate genetic similarity using the Jaccard index through the SIMQUAL procedure using NTSYSpc . The simWhere:a = number of cases where a band occurs simultaneously in both individualsb = number of cases when a band occurs only in the ith individualc = number of cases where the band occurs on in the jth individualThe Jaccard index was chosen because the coefficient of similarity considers only shared 1s as contributing to the similarity of individuals and disregards shared os. However, there is no general consensus between the various coefficients  for analyzing AFLP fingerprints .S. frugiperda and was run using the Arlequin program  markers per population (based on population consensus). The primer pair combinations were chosen for their consistency of scorable bands over all populations, polymorphisms, and reproducible banding patterns. Bootstrap analysis of markers indicated that the coefficient of variation of the data (Jaccard index) was 12% explaining 88% of the total variation of the populations, indicating high precision. The coefficient of variation program indicated that the minimum AFLP markers needed per population was 733. Therefore the 833 AFLP markers per population used for the analysis were sufficient for the stability of the UPGMA (unweighted pair group method with arithmetic mean) (AFLP provided a large number of useable and reproducible markers  to studyic mean)  dendrogrThe mean genetic diversity  within aS. frugiperda populations or between the S. frugiperda populations. S. frugiperda with GST values approaching 1.0 have a majority of genetic variability between populations. Conversely, a lower GST value (< 0.5) infers a majority of the genetic variability is within a given population. The GST value of 0.4172 /GST . N is thThe UPGMA consensus tree based on the Jaccard index after bootstrap analysis  shows geThe AMOVA results  revealedThe genetic isolation by distance was evaluated by a Mantel  test andPrinciple component analysis  showed tS. frugiperda is highly genetically variable and that future studies should incorporate more populations from a large geographic area to obtain more genetic information on host strain, geographic isolation, and reproductive incompatibility. All populations in this study were distinguishable by the selected AFLP markers by calculating a similarity matrix using the Jaccard similarity coefficient. Furthermore, the majority of the genetic variability is within individual populations and not between populations, indicating minor gene flow. This type of molecular research has practicalapplications for pest control in agriculture. The better we understand the population genetics of this pest, the better we can answer questions about whether or not a control method will work on the entire population or just a segment. Future research of S. frugiperda using AFLP and the markers selected from this study could become useful in tracking populations over time.This work proves that


Major population movements, social structure, and caste endogamy have influenced the genetic structure of Indian populations. An understanding of these influences is increasingly important as gene mapping and case-control studies are initiated in South Indian populations.ST = 0.96% for 45 autosomal short tandem repeat (STR) markers), reflecting a largely common origin. Nonetheless, caste- and continent-specific patterns are evident. For 32 lineage-defining Y-chromosome SNPs, Tamil castes show higher affinity to Europeans than to eastern Asians, and genetic distance estimates to the Europeans are ordered by caste rank. For 32 lineage-defining mitochondrial SNPs and hypervariable sequence (HVS) 1, Tamil castes have higher affinity to eastern Asians than to Europeans. For 45 autosomal STRs, upper and middle rank castes show higher affinity to Europeans than do lower rank castes from either Tamil Nadu or Andhra Pradesh. Local between-caste variation  exceeds the estimate of variation between these geographically separated groups (RST = 0.12%). Low, but statistically significant, correlations between caste rank distance and genetic distance are demonstrated for Tamil castes using Y-chromosome, mtDNA, and autosomal data.We report new data on 155 individuals from four Tamil caste populations of South India and perform comparative analyses with caste populations from the neighboring state of Andhra Pradesh. Genetic differentiation among Tamil castes is low (RGenetic data from Y-chromosome, mtDNA, and autosomal STRs are in accord with historical accounts of northwest to southeast population movements in India. The influence of ancient and historical population movements and caste social structure can be detected and replicated in South Indian caste populations from two different geographic regions. The origins and genetic affinities of India's populations have been debated extensively -6. ArchaA number of studies have addressed the genetic contribution of other Eurasian populations to Indian caste and tribal populations ,6,13-18.Several trends regarding the origin and affinities of Indian populations have emerged. The predominantly south and east Asian mtDNA haplogroup M is found in more than half of individuals from a wide sampling of castes ,6,13,22 The genetic affinities among the more than 2000 extant caste populations of India, however, are complex. Genetic distances between caste populations from the state of Andhra Pradesh, India, are correlated with differences in caste rank, suggesting that endogamy and differential inter-caste gene flow influences genetic structure . SeveralThese results support historical accounts of nomadic pastoralists from central and northwestern Eurasia integrating with existing local populations, and either introducing a system of social stratification or becoming members of the existing upper castes ,9,35. YeA broad study of 24 castes from various locations throughout India concluded that genetic data were not congruent with "sociocultural" affinities due to high rates of gene flow . Yet, thIn this study we analyze four castes of different rank sampled from Tamil Nadu, the southern-most state of the Indian subcontinent. The genetic relationship among the Tamil castes, their relationship to castes from the neighboring state of Andhra Pradesh, and their affinity to other Eurasian populations are examined using Y-chromosome, mtDNA, and autosomal polymorphisms. We show that the genetic affinities between Indian castes from Tamil Nadu and other Eurasians are broadly congruent with patterns observed previously for castes from Andhra Pradesh. These results strengthen the conclusions drawn from our previous analyses regarding caste relationships in South India and suggest reproducible patterns regarding the genetic influence of ancient and historical events on the Indian caste system.We evaluated the genetic relationship between Tamil castes, eastern Asians, and Europeans using 32 lineage-specific Y-chromosome SNPs. The sampling locations for the Tamil castes and a comparative set of castes from the neighboring state of Andhra Pradesh are shown in Figure p < 0.05). These trends appear in castes from both Tamil Nadu and Andhra Pradesh. Lineage H also reaches substantial frequency in the Tamil lower caste but is less common in upper and middle castes. Lineage J2, previously shown to be distributed in a northwest to southeast gradient, [Some between-caste trends are suggested by the data. The F* lineage is found at higher frequencies in lower castes than in upper or middle castes. The R1a1 lineage occurs at a higher frequency in upper vs. lower castes and differed significantly in frequency in Andhra upper vs. Andhra lower  or middle castes. This trend is also present in the Andhra sample, but it is not significant.To further examine potential western and central Eurasian contributions to South Indian castes, mitochondrial U lineages, defined by coding variant 12308G, were analyzed in greater detail Table . U haploWe calculated genetic distances between Tamil castes, Europeans, and East Asians and compared these results to those from upper, middle, and lower caste groups from the neighboring state of Andhra Pradesh. The genetic distance estimates reveal several distinct patterns Table .For Y-chromosome polymorphisms, all castes have smaller distances to Europeans than to eastern Asians. For mtDNA polymorphisms, all castes have smaller distance estimates to eastern Asians than to Europeans. For Y-chromosome data, the genetic distance estimates to the Europeans is ordered by caste rank. These trends appear in castes from both geographic regions.A neighbor-joining network depicts the between-population relationships based on Y-chromosome data Figure . The NTSA neighbor-joining network based on distance estimates from 45 STRs shows a greater affinity of all castes to Europeans than to eastern Asians Figure . With thThe network based on mitochondrial distance estimates shows little between-caste rank organization, yet reveals the greater affinity of all castes to eastern Asians for maternal lineages Figure . Basal UThe proportion of genetic variation distributed within and between South Indian castes was assessed by an analysis of molecular variance (AMOVA) Table . The Tamwithin populations.Y-chromosome and mtDNA estimates of molecular variance between castes samples from either Tamil Nadu or Andhra Pradesh also exceed the estimate for between-group variation for the two geographic regions. Between-caste variation for mtDNA in Tamil populations is greater than that for Andhra populations. This may be partly due to regionally high female mobility in Andhra castes as previously reported ,30. As eST values for these populations but may also reflect the limited power of 45 STRs to distinguish such closely related populations. Estimates for heterozygosity and repeat variance in these populations also indicate no substantial between-caste differences or excess homozygosity in these caste groups (Table The degree of population subdivision among Indian castes was estimated using a model-based clustering method implemented in STRUCTURE (ver. 2.1). The best estimate of the number of clusters (K) was consistently one for the Tamil Indians. The best estimate of the K clusters was also one for Tamil and Andhra castes together. This result indicates that individuals from castes spanning the Indian social hierarchy from two independent geographic regions are not sufficiently differentiated to allow clustering into groups based on genetic data from 45 STR polymorphisms alone. This finding is consistent with the low Rps Table .ρ = 0.26, p < 0.01). Inclusion of the non-Tamil speaking Brahmins decreases the correlation for all systems.We evaluated the correlation between caste rank and genetic distance using a Mantel test Table . For eacUsing a geographically well-defined sample of caste populations from Tamil Nadu, India, this study arrives at many conclusions similar to those from our previous studies of caste populations from Andhra Pradesh, India ,20,30. IPaternally-inherited Y-chromosome SNPs show that caste populations have greater affinity to a sample of Europeans than to a sample of eastern Asians. Unlike the Y-chromosome data, maternally-inherited mtDNA polymorphisms demonstrate a contrasting pattern – castes, regardless of rank, have higher affinity to eastern Asians than to Europeans. These patterns were present in samples from both geographical locations suggesting that South Indian paternal lineages have been more substantially influenced by western or central Eurasians compared to South Indian maternal lineages. Unlike our previous study of Andhra castes,  direct hUsing Y-chromosome data, Tamil castes of different rank have differential affinities to our sample of Europeans, with upper castes demonstrating greater affinity than lower castes. Genetic distances are weakly correlated with caste rank distances and correlations from Y-chromosome data are stronger than correlations based on mtDNA or autosomal data. This pattern argues for a differential contribution of male lineages to castes of different rank and limited male mobility between castes in South India.An interesting difference between the data sets from Andhra Pradesh and Tamil Nadu is also observed. For the former sample, inter-caste distance based on mtDNA polymorphisms (HVS1 sequence) demonstrated a strong relationship to caste rank, while distances based on Y-chromosome data did not. This was interpreted as evidence of historical upward female mobility in the caste system .  presented evidence that the R1a haplogroup has attained high frequencies and high diversity in northern India, central Asia, and eastern Europe. They also reported high frequencies of Y-chromosome haplogroup H in caste and tribal populations and provided compelling evidence for an origin of haplogroup H in South India. Upon further analysis, their data show that, as in our study, the frequency of haplogroup R lineages is higher in Brahmins (upper rank) than in lower-rank castes (0.53 vs. 0.41), while the frequency of H lineages is lower in Brahmins than in lower castes (0.15 vs. 0.34).In a study of broadly distributed Indo-European and Dravidian castes, Sengupta et al. (2006) suggested that the majority of Indian Y-chromosome haplogroups are at least 10,000 to 15,000 years old as gauged by Y-chromosome microsatellite diversity, thus predating the origin of the caste system. The antiquity and complex geographic distribution of the R1a1 and R2 haplogroups led these authors to conclude that the majority of the subcontinent Y-chromosomes arrived in or before the early Holocene  rather than in a later Indo-European expansion. Likewise, and concordant with other studies of tribal Indian populations, .An examination of the R and H haplogroup frequencies of Indo-European-speaking castes reported by Sengupta et al. (2006) shows that, as in our study, R haplogroup frequencies in upper castes exceeded those of middle and lower castes , while H haplogroup frequencies were lowest in upper castes (0.14), intermediate in middle castes (0.38), and most frequent in lower castes (0.44). For Dravidian castes, R (0.62) was more frequent than H (0.14) in upper castes while R and H had similar (within 6%) frequencies in middle and lower castes.A recent analysis of caste and tribal populations from eastern India (Orissa) demonstrated Indo-European influences on paternal caste lineages . BrahminIndian mtDNA lineages demonstrate high diversity, suggesting that a majority of Indian maternal lineages are also relatively old and likely predate historically documented expansion events ,42. OldeWhile Y-chromosome and mtDNA polymorphisms yield valuable information, it must be borne in mind that they each represent a single linkage group. Estimates based on these systems are thus subject to a high level of stochastic variability ,45. In aAlu and L1 insertion polymorphisms [Our analysis of 45 unlinked autosomal STRs reveals that in Tamil Nadu, genetic distances between castes are positively correlated with caste rank. A similar pattern was detected in upper, middle, and lower rank castes of Andhra Pradesh using these STRs  and Alu orphisms . An analorphisms . Majumdeorphisms ,48 preseorphisms . Similarorphisms ,33,49. Aorphisms ,50,51.Although significant correlations between caste-rank and genetic distances are apparent, model-based clustering algorithms did not detect structure within the Tamil or Andhra populations. We suggest that this finding results from the low amount of differentiation between all caste groups but also from a lack of sufficient power in 45 unlinked STRs to detect high-resolution population structure. With ~250 K SNPs typed in a subset of the Andhra upper and Andhra lower castes, individuals can be clustered into these population groups using genotype information alone . Likewisin situ) or other factors, such as a very wide geographic dispersion of the study populations, may confound correlations if they exist. Admixture and gene flow can also vary substantially between caste populations in the various regions of India. Linguistic differences may influence the genetic structure of local caste populations [Considering the complex history of Indian populations, it is not surprising that some studies demonstrate an association between caste rank and genetic distance, whereas others do not. A recent study of 15 geographically dispersed Indian populations residing in the United States using 1200 markers found little evidence for caste or geographic structure . Howeverulations . The linulations ,53 a larulations ,55. Ancein situ, spreading to the Indo-Gangetic plain, and then southward over the Deccan plateau. A strong patrilineal social structure, accompanied by a developing practice of caste endogamy, may have contributed to an asymmetric apportioning of Y-chromosome, autosomal, and to a lesser extent, mtDNA lineages. Remnants of these patterns can still be detected in some of the inhabitants of peninsular South India.The results presented here underscore the complexity of the Indian caste system. Although other interpretations may be possible, our data are consistent with a model in which nomadic populations from northwest and central Eurasia intercalated over millennia into an already complex, genetically diverse set of subcontinental populations. As these populations grew, mixed, and expanded, a system of social stratification likely developed ST = 0.0096). Tamil caste Y-chromosomes and STR alleles are more similar to Europeans than to eastern Asians, and genetic distance estimates to Europeans are ordered by caste rank. In contrast, Tamil caste mtDNA shows greater similarity to eastern Asians than to Europeans. Low, but statistically significant, correlations between genetic distance and caste rank can be demonstrated for the Tamil-speaking populations. These patterns likely reflect asymmetric influences of ancient and historical processes on the caste system as it developed. These findings provide a general replication of our analysis of ranked castes from the neighboring state of Andhra Pradesh, India [Genetic variation between South Indian castes from Tamil Nadu is low , Mudaliars (43), and Dalits (Harijans) (34) were sampled in Chennai or from rural locations near Chennai. Caste rank was assigned using the traditional varna of Brahmin , Mudaliar , and Dalit . A second sampling of Brahmins (37) was obtained in Kanchipuram, located ~70 km southwest of Chennai. The Kanchipuram Brahmin group is linguistically diverse, containing Kannada- and Telugu-speaking Brahmins that relocated from the neighboring states of Andhra Pradesh and Karnataka. This group of upper castes individuals is referred to subsequently as the non-Tamil speaking (NTS) Upper caste. This study was approved by the Schizophrenia Research Foundation, Chennai, India and by the Wolston Park Hospital Ethics Committee, Brisbane. Approvals were also obtained from the Indian Council of Medical Research and the Indian Ministry of Commerce. Written, informed consent was obtained from all participants.A comparative European sample of northern European and French ancestry 57), and eastern Asians of Chinese, Japanese, and S.E. Asian ancestry 28) have been previously described [ have bee, and easDNA was extracted from venous blood using standard procedures. Hypervariable sequence 1 (HVS1), corresponding to base pairs 16000 – 16410, was amplified by PCR and sequenced using BigDye 3.1 dye-terminator fluorescent sequencing chemistry and an Applied Biosystems (ABI) 3100 automated sequencer.Lineage and sub-lineage identifying single nucleotide polymorphisms (SNPs) for the mitochondria (32 markers) and Y-chromosome (32 markers) were selected from the literature ,59-64. LMitochondrial and Y-chromosome SNPs were genotyped by fluorescent primer extension using SNaPshot chemistry (ABI). Primers were annealed to amplification products adjacent to the polymorphic site and extended by one nucleotide using the manufacturer's recommendations. Extension products were pooled and resolved on a 36-cm capillary array. Four to eight SNPs were assayed per multiplex. Forty-five STRs, predominantly tetranucleotide repeats, were amplified using 5'-NED, -PET, -VIC, or -6-FAM labeled primers using standard PCR conditions and resolved in 5 fluorescent multiplex runs on an ABI 3100. STR loci are UT1091, UT1201, UT1205, UT1220, UT1227, UT1228, UT1232, UT1239, UT1243, UT1257, UT1313, UT1352, UT1357, UT1376, UT1674, UT1708, UT1740, UT1747, UT1880, UT1885, UT1917, UT1950, UT1985, UT2021, UT2081, UT2092, UT2127, UT2203, UT5022, UT5027, UT5029, UT5030, UT5033, UT5048, UT5492, UT6507, UT6516, UT6540, UT7131, UT8067, UT868, UT871, UT901, UT919, and vWFII. These STRs and mtDNA polymorphisms, were typed in comparative populations as described previously . Y-chromTo allow a direct comparison of Y-chromosome haplogroups from Tamil Nadu castes to those from Andhra Pradesh castes, we typed individuals from Andhra Pradesh for 26 of the 32 lineage-defining SNPs. A Y-haplogroup was assigned to each sample by the presence of one or more derived-state alleles, and the remaining alleles were inferred. This SNP panel allowed further refinement of the haplogroups previously reported for the Andhra Pradesh samples ,30.Haplogroups for the Y-chromosome (32 SNPs) and mtDNA (32 SNPs and 411bp HVS1 sequence) were assigned using SNP data. Mitochondrial haplogroups were assigned to a haplogroup based on the most probable consensus of polymorphic changes or resolved using previously published mtDNA HVS1 motifs as a guide . Thirty-ST, RST, and AMOVA) for Y-chromosome, mtDNA, and autosomal STRs were calculated using the ARLEQUIN 3.0 software package [-7 substitutions/site/year [Diversity estimates  [The correlation between genetic distance and caste rank was assessed by Mantel matrix tests using Spearman's rank correlation. For all possible pairs of caste individuals, inter-individual genetic distance estimates were calculated using DNADIST (Y and mtDNA)  or the Dm (STRs) . Next, eWSW carried out the molecular studies, performed data analysis, and drafted the manuscript. RT performed analysis and sample collection in India. BJM and DN designed and partially funded the study. YZ performed genotyping and laboratory experiments. DJW provided statistical consultation. WT performed genotyping and other laboratory experiments. MJB helped acquire and analyze samples from Andhra Pradesh. ST and RP performed sample collection in Tamil Nadu. HS and CF performed sample extraction and laboratory analysis of samples from Tamil Nadu. LBJ designed, coordinated, and funded the study. All authors read and approved the final manuscript.Y-chromosome, STR, and mtDNA genotype data. Genotype data for South Indians, Europeans, and eastern Asians.Click here for file


In this study, we aimed to reveal the structure and diversity of dimeric α-amylase inhibitor genes in wild emmer wheat from Israel and to elucidate the relationship between the emmer wheat genes and ecological factors using single nucleotide polymorphism (SNP) markers. Another objective of this study was to find out whether there were any correlations between SNPs in functional protein-coding genes and the environment.P (5%), the expected heterozygosity He, and Shannon's information index in the 16 populations were 0.887, 0.404, and 0.589, respectively. The populations of wild emmer wheat showed great diversity in gene loci both between and within populations. Based on the SNP marker data, the genetic distance of pair-wise comparisons of the 16 populations displayed a sharp genetic differentiation over long geographic distances. The values of P, He, and Shannon's information index were negatively correlated with three climatic moisture factors, whereas the same values were positively correlated by Spearman rank correlation coefficients' analysis with some of the other ecological factors.The influence of ecological factors on the genetic structure of dimeric α-amylase inhibitor genes was evaluated by specific SNP markers. A total of 244 dimeric α-amylase inhibitor genes were obtained from 13 accessions in 10 populations. Seventy-five polymorphic positions and 74 haplotypes were defined by sequence analysis. Sixteen out of the 75 SNP markers were designed to detect SNP variations in wild emmer wheat accessions from different populations in Israel. The proportion of polymorphic loci The populations of wild emmer wheat showed a wide range of diversity in dimeric α-amylase inhibitors, both between and within populations. We suggested that SNP markers are useful for the estimation of genetic diversity of functional genes in wild emmer wheat. These results show significant correlations between SNPs in the α-amylase inhibitor genes and ecological factors affecting diversity. Ecological factors, singly or in combination, explained a significant proportion of the variations in the SNPs, and the SNPs could be classified into several categories as ecogeographical predictors. It was suggested that the SNPs in the α-amylase inhibitor genes have been subjected to natural selection, and ecological factors had an important evolutionary influence on gene differentiation at specific loci. Triticum dicoccoides, the progenitor of bread and pasta wheats, presumably originated in and adaptively diversified from, northeastern Israel into the Near East Fertile Crescent [T. dicoccoides and other cereals have shown significant nonrandom adaptive molecular genetic differentiation at single and multilocus structures in either protein-coding regions or randomly amplified polymorphic DNAs among micro-ecological environments [Wild emmer wheat, Crescent . In thisCrescent . Previouronments ,3. It waronments . Geneticronments .The estimates of molecular diversity derived from PCR-based techniques such as amplified restriction fragment length polymorphism (AFLP), microsatellites (short sequence repeats or SSR), single nucleotide polymorphism (SNP), and sequence comparisons are several-fold higher than enzymatic diversity . A substα-Amylase is a family of enzymes that hydrolyze α-D--glucan linkages and play an important role in the carbohydrate metabolism of many autotrophic and heterotrophic organisms . HeterotEvolutionary pressures of various kinds have often been hypothesized to cause active and rapid evolutionary changes. In a co-evolving system of plant-insect interactions, plants synthesize a variety of toxic proteinaceous and nonproteinaceous molecules for their protection against insects ,21. ProtIn vitro and in vivo trials using α-amylase inhibitors, including those made under field conditions, have now fully confirmed their potential for increasing yields by controlling insect populations [It is well established that multiple forms of proteins are active on exogenous or endogenous α-amylases in the wheat kernel, and proteinaceous dimeric α-amylase inhibitors could function against α-amylase from various origins . It is kulations .Aegilops section sitopsis, respectively, have been characterized. A Phylogenetic Median-Joining network of the haplotypes and a neighbor-joining tree analysis have indicated that the inhibitor gene sequences from common wheat and T. dicoccoides are closely related to those from Ae. speltoides [Two conflicting views confront ecologists and evolutionary biologists on the degree of symmetry in interactions between plants and phytophagous insects . The symeltoides . HoweverAegilops section Sitopsis , Ae. tauschii, einkorn wheats, and common wheat clearly indicated that the emmer wheat sequences were derived from the B genome [Using two cloning primers, genomic PCR amplifications were conducted, and one desired DNA band was detected in each accession of wild emmer wheat. Cloning the fragments yielded 244 positive clones from 13 accessions (randomly selected from 10 populations), which were subsequently sequenced (data not shown). Only three out of 244 dimeric α-amylase inhibitor genes had a common three bp deletion, and those three genes were obtained from one accession derived from Mt. Hermon, whereas the other cloned fragments had 426 bp long (data not shown). It was predicted that all of the 426-bp sequences would encode functional dimeric α-amylase inhibitors. Alignment of the gene sequences from emmer wheat with sequences from the species of B genome .The frequency of SNPs in the dimeric α-amylase inhibitor genes in emmer wheat was 1 out of 5.7 bases, which was higher than the SNPs observed for kunitz-type α-amylase inhibitor and α-amylase/subtilisin inhibitor genes in barley and dimeric α-amylase inhibitor genes in common wheat -30. AmonA total of 74 haplotypes were revealed by sequence analysis Figure ; 53 of tThe relationship between SNPs and amino acid changes in the α-amylase inhibitor proteins is summarized in Table Using the information from the 75 SNPs identified in the α-amylase inhibitor genes, 16 primers  were successfully designed to detect the SNPs in 205 accessions from 18 populations. The primers, with the SNP (bold letters) at the 3' end and an extra mismatched nucleotide (underline) on the third nucleotide from the end are listed in Table There were only 5 and 2 accessions from Yehudiyya and Achihood, respectively. Thus, the data for Yehudiyya and Achihood were not used in further analyses. Positive fragment frequency for each primer in the 16 populations is listed Additional file P (5%), the expected heterozygosity He, and Shannon's information index of the 16 populations of wild emmer wheat were 0.887, 0.404, and 0.589, respectively. The values of He ranged from 0.182 to 0.437, and the population of Kokhav Hashahar had the highest value of He (0.437), followed by the population of Rosh-Pinna, whereas the population from Daliyya was characterized by the lowest He value of 0.182.Some genetic parameters of the 16 populations of wild emmer wheat are summarized in Table D) were calculated for comparisons of all 16 populations based on the positive fragment of SNP markers among all population pairs  were observed between some populations from different areas, and, for the most part, the estimates of D value were geographically independent. Large genetic distances and sharp genetic differentiation over long geographic distances could be found. For example, Kokhav Hashahar in southern Israel had higher D values with the populations from Gamla (0.221), Nahef (0.247), Beit-Oren (0.215), Daliyya (0.263), and Bat-Shelomo (0.224) in northeast Israel.The genetic distances  was carried out using 23 ecological factors as variables. A combination of the first four components could give us a high cumulative percent (88.81%) according to the eigenvalues of the correlation matrix  accounted significantly (p < 0.05) for about 0.55 of the genetic diversity. The addition of a fourth variable predictor, Rad , or Sh (mean number of Sharav days) to the first three factors accounted for approximately 0.65 of the diversity (significant at p < 0.05)  water : W24A, W46A, W47AT, W127G, W190C, W276A; (2) temperature : W19G, W35A, W207T, W263TC, W263TA, W288CG; (3) geographic : W125G, W288AG; and (4) solar radiation (Rad): W195T; W259A. It was obvious that water factors were the best variable predictors, singly or in combination, with other ecological factors  and He of each of the SNP positions with ecogeographical variables appear in Table P, He, and Shannon's information index were negatively correlated with the three water factors: mean annual humidity (Hu-an), mean humidity at 14:00 h (Hu-14), and mean number of dew nights in summer (Dw). However, they correlated positively with other factors: latitude (Ln), seasonal temperature difference (Td), estimate of population size (Sz), marginality (Ma), mean inter-annual variability of rainfall (Rv), and total solar radiation per year (Rad). The correlation matrix between He in the SNPs and geographic variables contained 30 significant (p < 0.05) correlations. Five SNPs  positively correlated with Sz (rs = 0.556–0.687), and four SNPs  positively correlated with Ln (rs = 0.508–0.567). Four SNPs: W24A, W127G, W190C, and W263TA negatively correlated with two water factors, Hu-an or Rn  or both of these factor  and 0.53 (WDAI-0.53). The predicted protein sequence of the 244 cloned α-amylase inhibitor genes from wild emmer wheat showed the presence of 10 Cys, which were the amino acids most important to the structure and function of the mature protein . Changeshe His47 , whereasGenetic diversity of the α-amylase inhibitor genes of 198 wild emmer wheat accessions from 16 populations in Israel were revealed by 16 SNP markers. Individual accessions from different populations could not be distinguished clearly by the sequences of their α-amylase inhibitor genes; whereas, using the SNP-specific primers, all wild emmer wheat populations were distinguishable, even within closely related populations originating in proximate geographic locations Table . Our resThe genetic diversity profiles in this study were compared with earlier allozyme studies , RAPD loP), expected heterozygosity (He), and Shannon's information index  populations were collected from the western border of wild emmer distribution ,39. The ex Table . These rD) were geographically independent, as was previously found for allozymes, RAPD loci, and microsatellite analyses [D) over very short geographic distances against small genetic divergence  between large geographically distances were observed in wild emmer populations . In other words, the distance between the first 2 populations was 1/16 of the distance between the second 2 populations  and key water variables  plus latitude [Isa locus in the seed [The SNPs that could determine the amino acid changes in the mature protein of α-amylase inhibitors were of great importance. Six specific primers  were designed, based on the SNPs at five positions associated with amino acids changes  over very short geographic distances against small genetic divergence  between large geographical distance was found in wild emmer populations. It was suggested that the SNPs in the α-amylase inhibitor genes were subjected to natural selection, and ecological factors had an important evolutionary role in gene differentiation at the gene loci.The populations of wild emmer wheat showed great diversity in dimeric α-amylase inhibitors, both between and within populations. We suggest that SNP markers are useful for the estimation of genetic diversity of protein-coding genes in wild emmer wheat. These results show significant correlations between SNPs in the α-amylase inhibitor genes and ecological diversities. Ecological factors, singly or in combination, explained a significant proportion of the variations in the SNPs, and the SNPs could be classified into several categories as ecogeographical predictors. A sharp genetic divergence  . The cenT. dicoccoides accessions representing 18 populations collected from various locations in Israel, which represent a wide range of ecological conditions of soil, temperature, altitude, and water availability. The populations used in this study, along with their geographic origin and climatic conditions, are listed in Table et al. [In this study we examined 205 e et al. , and theTaq polymerase, 1.5 mM Mg2+, and 1×PCR buffer. The cycling parameters were 95°C for 5 min to pre-denature, followed by 35 cycles of 95°C for 1 min, 60°C for 30 sec and 72°C for 1 min, and a final extension at 72°C for 5 min.Ten seeds of each accession were germinated in the dark at room temperature. Genomic DNA was extracted from plant leaves at about 2 weeks of age with a modified CTAB protocol, as described in Murray and Thompson . Two priAmplification products were separated in 2% agarose gels. The desired DNA fragments were recovered from gels and ligated to the pBluescript SK (+) T-vector plasmid (Stratagene), and then the positive clones were screened and sequenced. The analysis of full-length sequence and the construction of subsequent nucleotide sequence were carried out under DNAman 5.2.2 , and thePolymorphic positions were identified by MEGA version 3.1 . Sixteent approximately 0.005), we assumed 100% homozygosity. The identification of 16 SNP positions led to the construction of a 198 accessions  × 16 loci data matrix, which was analyzed for diversity within and between populations.The gels were scored for the presence or absence of bands that showed a reproducible pattern among genotypes, and for each band with a SNP position with two alternative alleles: present (1) or absent (0). For wild emmer wheat, which is a self-pollinating species with a quite limited rate of outcrossing (estimated P), expected heterozygosity (Nei's gene diversity) (He), and Shannon's information index (I) for each SNP position and population. Spearman rank correlation coefficients were used to assess differences in genetic indices P, He, and Shannon's information index and climatic variables in 16 populations. STATISTICA version 6.0 [P, He, and Shannon's information index in the 16 populations using these genetic indices as dependent variables and the eco-geographic factors as independent variables at each of the polymorphic SNP loci.POPGENE 1.32  was usedsion 6.0  was usedWJR designed and carried out the experiment and wrote the manuscript. WYM designed the experiment, formulated the questions, and contributed to writing the manuscript. LXY participated in the experiment. YZH carried out sequence alignment analysis. BB contributed to the data analysis and writing. EN formulated the questions, retrieved and analyzed the data, and planned the experiments. ZYL planned the study and participated in the design of the experiments.Positive fragment and the frequency of each primer in 16 Population of wild emmer wheat. This data showed the frequency of each specific primer in the 16 populations calculated by POPGENE 1.32.Click here for fileD) based on the positive fragment of SNP markers among all population pairs.Nei's genetic distance of the inhibitor genes in the 16 populations. This data showed the genetic distances (Click here for filePrincipal components analysis. This data showed the eigenvalues of correlation matrix, eigenvectors and factor coodinates of 16 populations.Click here for filePrincipal components analysis of the ecological factors. This data showed the projection of the variables on the ecological factor-plane and eigenvalues of correlation matrix.Click here for fileCorrelations of the Factors. This data showed the correlation of the 20 ecological factors that separated into four groups.Click here for file


High rates of esophageal cancer (EC) are found in people of the Henan Taihang Mountain, Fujian Minnan, and Chaoshan regions of China. Historical records describe great waves of populations migrating from north-central China (the Henan and Shanxi Hans) through coastal Fujian Province to the Chaoshan plain. Although these regions are geographically distant, we hypothesized that EC high-risk populations in these three areas could share a common ancestry. Accordingly, we used 16 East Asian-specific Y-chromosome biallelic markers  and six Y-chromosome short tandem repeat (Y-STR) loci to infer the origin of the EC high-risk Chaoshan population (CSP) and the genetic relationship between the CSP and the EC high-risk Henan Taihang Mountain population (HTMP) and Fujian population (FJP). The predominant haplogroups in these three populations are O3*, O3e*, and O3e1, with no significant difference between the populations in the frequency of these genotypes. Frequency distribution and principal component analysis revealed that the CSP is closely related to the HTMP and FJP, even though the former is geographically nearer to other populations (Guangfu and Hakka clans). The FJP is between the CSP and HTMP in the principal component plot. The CSP, FJP and HTMP are more closely related to Chinese Hans than to minorities, except Manchu Chinese, and are descendants of Sino-Tibetans, not Baiyues. Correlation analysis, hierarchical clustering analysis, and phylogenetic analysis (neighbor-joining tree) all support close genetic relatedness among the CSP, FJP and HTMP. The network for haplogroup O3  showed that the HTMP have highest STR haplotype diversity, suggesting that the HTMP may be a progenitor population for the CSP and FJP. These findings support the potentially important role of shared ancestry in understanding more about the genetic susceptibility in EC etiology in high-risk populations and have implications for determining the molecular basis of this disease. The non-recombining portion of the Y chromosome (NRY) has unique characteristics, including paternal inheritance, absence of recombination at meiosis, and a relatively low probability of recurrent mutations, thus endowing it with population- and area-specific polymorphisms. Thus, NRY is particularly useful for the study of human evolution and population genetics. Two types of polymorphisms exist on the NRY: single nucleotide polymorphisms (SNPs) and short tandem repeat (STR) loci, each with different mutation rates and mechanisms. Accordingly, combined analysis using these 2 types of polymorphic markers increases the power of the NRY for use in tracing human evolution as well as migration through different geographic locales and time scales, and therefore could also be effective in depicting the paternal structures of populations.Indeed, in 1999, Su et al. Esophageal cancer (EC) is one of the most common fatal cancers worldwide The geographies of south-littoral (Chaoshan and Fujian areas) and north-central China (Henan and Shanxi) are distinct, but populations within these regions share a high risk of EC Therefore, we hypothesized that these three EC high-risk populations may be genetically related. To test our hypothesis of common ancestry, we analyzed 16 East Asian-specific biallelic markers X2 = 4.213, p = 0.122). These results provide evidence for genetic affinity between these three EC high-risk populations. O*, O1*, O2a*, and O2a1, the four common haplogroups in the southern East Asians, were more frequent in the CSP and HTMP than in the FJP . The C*, D1, and F* haplogroups were more common in the northern than southern group, and their combined frequencies were significantly lower in the CSP than in the other two . These results support the hypothesis of gene flow between the HTMP, FJP, and CSP.The haplogroup frequencies of the three EC high-risk populations were based on Y-SNP typing. As shown in PC plots of Y-SNP and Y-STR frequencies are shown in To further elucidate the relationship between populations, we performed correlation analysis based on Y-SNP haplogroup and Y-STR haplotype frequencies . BecauseTo delineate the genetic relationship among the three EC high-risk populations and populations based on other language families, we performed a further principal component analysis using data, provided by the State Key Laboratory of Genetic Engineering and Center for Anthropological Studies , which include Y-SNP data for 64 Chinese populations belonging to the 5 language families: Sino-Tibetan, Hmong-Mien, Daic (Baiyue), Austronesian, and Austroasiatic.The Y-chromosome haplogroup profiles identified in these populations were treated as input vectors for PC analysis. The cumulative contribution of PC1 and PC2 accounted for 54.85% of the total variance. A PC dot plot was drawn with values for PC1 and PC2 as the X and Y axes, respectively. As shown in P<0.001). Analysis of PC1 showed that the number of negatively correlated haplogroups, despite their weak correlations, was larger than that of the positive groups. O3e* is the only haplogroup with a significantly positive correlation with PC1 . For PC2, the number of positively and negatively correlated haplogroups was similar. O2a* and O1 represent the southern aboriginal haplogroups in the East Asian population and O3e* is probably a northern haplogroup. As shown in Correlation analysis was carried out to seek the origin of each PC . PC1 shoTo further elucidate the affinity among the three EC high-risk populations and other Chinese populations, hierarchical cluster analysis was carried out with average linkage (between groups) based on Y-SNP data. To illustrate the cluster of the three high-risk populations and its relationship with other Hans, Baiyue, and Hmong-Mien groups, we included 20 Chinese Hans To further investigate the genetic relationships between the three EC high-risk populations, Rst distances between pairs of populations were calculated on the basis of seven Y-STRs by use of Alrequin 3.1 software. Six additional Chinese populations were included in this analysis: Zhejiang www.fluxus-engineering.com) based on all of haplogroup O3  individuals for analyzing the relationship among CSP, FJP and HTMP. As shown in The highest haplogroup frequency shared by the CSP, FJP and HTMP was haplogroup O3. The network for haplogroup O3 was further constructed using Network 4.516 software  the Baiyue populations formed the earliest settlement in modern history. Before 2200 BC, one branch of the Baiyue population—the Minyue—was the main group living in the Chaoshan littoral areas. The north-to-south strategic expansion started by Emperor Qin Shi Huang initiated large southward migrations of central China Hans from 214 BC onward The incidence and mortality rate for EC is very high in the CSP, FJP, and HTMP areas. We propose that the Chaoshan littoral region is an EC high-risk area because of the genetic background of the CSP and FJP shared with those in north-central China. The ancestors of the EC high-risk CSP may have derived from the EC high-risk HTMP via the FJP. This study provides genetic evidence to support this hypothesisIn general, populations sharing similar patterns of haplogroup distribution are likely to have a relatively close genetic relationship. In this study, the three EC high-risk populations resemble one another in distribution of haplogroups O3*, O3e* and O3e1 , which sAs historically recorded 2 millennia ago, southern China was originally inhabited by the southern natives, including those speaking Daic (Baiyue), Austro-Asiatic, and Hmong-Mien languages Although we used two types of Y-chromosome polymorphic markers and demonstrated consistent results from multiple analyses, populations from other EC high-risk areas were not included in this study, so we cannot ascertain whether all the EC high-risk populations share a common genetic background. To further explore this aspect, a large-scale study of EC high-risk populations is necessary.In summary, the patrilineal genetic structure of the EC high-risk CSP, HTMP, and FJP suggests an origin in genetic background of the EC high-risk CSP. The three EC high-risk populations in this study appear to share a similar patrilineal genetic background that may explain, at least in part, the high incidence of EC in these areas in China. The extent to which other factors such as environment and customs may contribute to the high incidence of EC remains to be explored.Blood samples of 211 unrelated healthy males were collected from the the three EC high-risk areas in China during 2002 to 2004; 89 samples were from the Chaoshan area, 48 from the Henan Taihang mountain area and 74 from the Fujian area (Minnan area). All individuals gave their informed consent before being included in the study. The study was approved by the ethical review committees of the Medical College of Shantou University. Genomic DNA was extracted from whole blood by standard phenol/chloroform methods Three strategies were used to type Y-SNPs and Y-STRs. SNPs without length changes (base substitutions) were genotyped by a PCR-based restriction fragment length polymorphism (PCR-RFLP) method  and southern East Asian populations (SEAPs) according to their geographic locations. The Yangtze River was used as the geographic border to separate the NEAPs and SEAPs; NEAPs were further divided into northern Hans (NHs) and northern minority nationalities (NMNs), and SEAPs were defined as southern Hans (SHs) and southern minority nationalities (SMNs). Additional Y-SNP data allowed for dividing the major Chinese Han populations into 2 groups  with Y-STR data from individuals of the EC high risk CSP, FJP and HTMP based on Y-SNP information. In the network map, individuals with the same mutations of Y-STRs were present in the same node and one node can generate other nodes below due to gradual Y-STR mutations.STRs can infer minute genetic diversity within a haplogroup in different populations, so the network was constructed using Network 4.516 software (


In this study, we used genetic data that we collected in Central Asia, in addition to data from the literature, to understand better the origins of Central Asian groups at a fine-grained scale, and to assess how ethnicity influences the shaping of genetic differences in the human species. We assess the levels of genetic differentiation between ethnic groups on one hand and between populations of the same ethnic group on the other hand with mitochondrial and Y-chromosomal data from several populations per ethnic group from the two major linguistic groups in Central Asia.Our results show that there are more differences between populations of the same ethnic group than between ethnic groups for the Y chromosome, whereas the opposite is observed for mtDNA in the Turkic group. This is not the case for Tajik populations belonging to the Indo-Iranian group where the mtDNA like the Y-chomosomal differentiation is also significant between populations within this ethnic group. Further, the Y-chromosomal analysis of genetic differentiation between populations belonging to the same ethnic group gives some estimation of the minimal age of these ethnic groups. This value is significantly higher than what is known from historical records for two of the groups and lends support to Barth's hypothesis by indicating that ethnicity, at least for these two groups, should be seen as a constructed social system maintaining genetic boundaries with other ethnic groups, rather than the outcome of common genetic ancestryOur analysis of uniparental markers highlights in Central Asia the differences between Turkic and Indo-Iranian populations in their sex-specific differentiation and shows good congruence with anthropological data. Central Asia is located on the Silk Road, where numerous ethnic groups characterised by different languages and historical modes of subsistence co-exist. These include the Tajik populations, who speak an Indo-Iranian language and are sedentary agriculturalists, and several Turkic populations, who speak an Altaic language and are traditionally nomadic herders ,2. HowevHowever, the level at which Central Asian groups are genetically differentiated, in particular for the Y chromosome, remains unclear. Indeed, it remains to be understood whether the genetic variation differentiates primarily ethnic groups  or whether it differentiates primarily populations within ethnic groups . More generally, the underlying question is whether ethnicity is the major determinant of genetic differences between populations. We are also interested in understanding better the processes leading to the emergence of ethnic groups, and in understanding the extent to which constituted ethnic groups are endogamous. One focus of this study was to assess the levels of genetic differentiation between ethnic groups on one hand and between populations of the same ethnic group on the other hand in order to understand better how ethnicity shapes the genetic diversity of human populations, and to give insights on the processes leading to the formation of ethnic groups. To address this question, we sampled several populations per ethnic group (from 2 to 6 populations per ethnic group) from the two major linguistic groups in Central Asia.An additional aim of this study was to use genetic data to understand better the history and formation of particular Central Asian ethnic groups. Indeed, parts of their history remain controversial. Among the Turkic groups, the Karakalpaks, Uzbeks and Kazakhs are thought to be subgroups of the same Uzbek confederation that emerged during the fifteenth century following the collapse of the Golden Horde after the dissolution of Genghis Khan's empire. The Karakalpak group emerged more recently and resulted from a split from the Kazakh confederation in the seventeenth century. However, the origin of the Kyrgyz living in Kyrgyzstan is still a matter of debate in the scholarly literature. Late in the eighth century the Kyrgyz state was a major rival of the Great Turkic Empire and later defeated the Uighur in the ninth century. The prevailing current opinion is that part of this Kyrgyz population moved from South Siberia to Kyrgyzstan in the fifteenth century and included some nomadic groups that inhabited the region for several centuries. Turkmen tribal genealogies trace their origin to the Oghuz who lived in the area in the sixth century. The agriculturalist Tajik sedentary populations speak a western Indo-Iranian language that entered the area through the Muslim invasion in the tenth century, and are perhaps descendants of former eastern Indo-Iranian speakers who have lived there for more than two millennia. For all historical references see ,2. In thWe investigated how the genetic variance, based on mtDNA haplotype frequencies (HVS-I sequences) was distributed in a hierarchical mode using an AMOVA analysis . The oveTABLE 1When taking into account all populations, no correlation between genetic and geographical distances was detected at the global level . This lack of correlation remains if we test separately for each language family.With respect to the Y chromosome, the AMOVA analysis performed using the 20 populations showed that about 5.6% of genetic differentiation is due to differences among ethnic groups (P < 0.02) and that the overall differentiation between populations is RST = 0.186 (P < 0.001). When populations were grouped by language affiliation/mode of subsistence -- Turkic versus Tajik -- ~9.1% of the genetic variability was due to differences between these two groups. In addition, the analysis at the intra-group level revealed a high degree of differentiation both for Tajik and Turkic populations except for the two Uzbek populations. List of suage. 1: , 4: 14]List of sClick here for file


A fundamental question in ecology is whether microorganisms follow the same patterns as multicellular organisms when it comes to population structure and levels of genetic diversity. Enormous population sizes, predominately asexual reproduction and presumably high dispersal because of small body size could have profound implications on their genetic diversity and population structure. Here, we have analysed the population genetic structure in a lake-dwelling microbial eukaryote (dinoflagellate) and tested the hypothesis that there is population genetic differentiation among nearby lake subpopulations. This dinoflagellate occurs in the marine-derived saline lakes of the Vestfold Hills, Antarctica, which are ice-covered most of the year. Clonal strains were isolated from four different lakes and were genotyped using amplified fragment length polymorphism (AFLP). Our results show high genetic differentiation among lake populations despite their close geographic proximity (<9 km). Moreover, genotype diversity was high within populations. Gene flow in this system is clearly limited, either because of physical or biological barriers. Our results discard the null hypothesis that there is free gene flow among protist lake populations. Instead, limnetic protist populations may differentiate genetically, and lakes act as ecological islands even on the microbial scale. Eukaryotic microorganisms (protists) are a very large and diverse group of organisms that are comparatively little studied within ecology and evolutionary ecology e.g. . ProtistPopulation genetic theory predicts high genetic diversity in microbial populations because of their population size, which has been confirmed by population genetic simulations . In contPseudo-nitzschia pungens that spans across a 100 km region of the North Sea  strains per lake on 379 AFLP loci, we were able to calculate the necessary population genetics statistics to make inferences regarding genetic structure and gene flow. We specifically tested the hypothesis that there is population genetic structure among nearby lake populations of dinoflagellates. The null hypothesis was no genetic differentiation because of unlimited gene flow. The alternative hypothesis was that population genetic differentiation would be found among the lakes.Here, we have analysed the population genetic structure and differentiation in the photosynthetic dinoflagellate Dinoflagellates were collected from four different lakes in the Vestfold Hills area , Eastern Antarctica during the Antarctic summer of 2009. The lakes sampled range in salinity from 5 to 18  to a salinity of approximately 6–7 to mimic the salinity in the Antarctic lakes. Cultures were harvested when a total of 50 mL of exponentially growing culture was available. Cells were centrifuged at 500 g for 10 min, the supernatant was removed, and the pellet was stored at −80 °C until extraction.Single cells of DNA was extracted using a CTAB protocol based on All strains were genotyped by AFLP using a fluorescein protocol based on  was usedDinoflagellates typically do not grow well without the presence of bacteria, which is why our cultures were nonaxenic (not bacteria-free). We checked that bacterial DNA did not affect the downstream analyses by performing three different tests. First, we compared AFLP band patterns from cells isolated by centrifugation as above (unfiltered), and cells harvested by filtering through a 10-μm nylon mesh to remove bacteria but retain dinoflagellate cells (filtered). In a second test, we applied an antibiotic procedure to reduce bacteria in the dinoflagellate cultures. Four strains (one from each lake) were split into two flasks during exponential growth. One flask was treated with 0.2 mg/mL penicillin G potassium salt (Fluka). Four days later the cultures were harvested. The untreated sample was harvested according to the standard procedure and the other by filtering through a 10-μm nylon mesh to remove any remaining bacteria, followed by centrifugation. The supernatant (collected after centrifugation) from both the untreated and penicillin-treated strains was analysed to detect any bands caused by bacteria. DNA extractions and AFLP analyses were performed as above, except that AFLP fragments were analysed visually using acrylamide gel electrophoresis as in . Moreovestructure 2.3.3.  was determined manually by choosing the lowest K where posterior probabilities (log Pr(X/K)) values reached a plateau.Population structure was analysed using G) divided by the total number (N) of strains analysed (G/N).The number of haplotypes was calculated using Arlequin v 3.5 (FST) between lake populations, and amova to calculate global genetic differentiation , genetic differentiation between groups (FCT) and within groups (FSC). AFLP-survey v 1.0 was used to determine the number and percentage of polymorphic loci and Nei’s gene diversity (H) within populations , distributed among the four lakes. The AFLP analyses yielded 379 AFLP loci after normalization of data based on a 5% Bayesian error rate in AFLPScore. One hundred per cent unique genotypes were identified, suggesting that none of the strains belonged to the same clonal lineage. The percentage of polymorphic loci varied between 17.4% and 28.2% within each of the lake populations  between lakes was moderate to high ranging between 0.117 and 0.376 . The highest FST values were found in the pairwise comparisons with McNeil, all of these being around 0.3.Genetic differentiation between the lake populations was measured by calculating nd 0.376 . All FSTstructure. All the ancestry and allele frequency models yielded the highest likelihood for a model with two genetic populations (K = 2), regardless of whether admixture  was allowed , we performed an amova. The global FST, that is, the genetic differentiation explained by all variation within and among groups or populations, amounted to 0.299. FCT, which explains the genetic variation between populations, was 0.177, and the variation within groups, FSC, was 0.148.Based on the FST values. Both when the analysis was run with four populations (in accordance with sampling and Arlequin results) and with two populations (based on structure results), a single outlier with a FST higher than the 95% quantile (P < 0.05), indicating a locus under divergent selection, was found. A number of loci with low FST values suggesting balancing selection were found significant (P < 0.05).To detect potential loci under divergent selection, that is, loci involved in potential local adaptation, the software Arlequin was used to identify loci with higher than expected Using population genetic tools and molecular markers, we investigated whether gene flow is unlimited and whether population genetic structure was present in an aquatic free-living protist species (Dinophyceae) found in Antarctic saline lakes. Our results show a clear population structure and high genetic differentiation among lake populations despite the close proximity (<10 km) of the lakes. We also found high genetic diversity within the lakes. Our results and conclusions are discussed in detail later.Scrippsiella aff. hangoei (hereafter Scrippsiella) could potentially belong to one single metapopulation with free gene flow among them. Our data, however, show high genetic differentiation among the four lake populations studied. The range of the values are similar to those found for populations of freshwater diatoms at much larger geographic distances (>100 km) (FST (genetic differentiation) values among the dinoflagellates lake populations are much higher than, for example, freshwater fish, where FST values in the 0.06 range are considered as substantial genetic differentiation , two genetically distinct populations were identified in our data set. One population included all the strains from Lake McNeil, and the other consisted mainly of strains from the other three lakes. Regardless of whether a model allowing for sexual recombination (admixture) or for strictly clonal reproduction (no admixture) was used, the same two populations were identified. Whether the Scrippsiella Antarctic metapopulation really consists of four separate or two populations is a question of interpretation. While FST values are based on predefined information that strains belong to different lake populations, the structure analyses search for genetic clusters that maximize the likelihood that individual genotypes belong to them. In that sense, the Bayesian method can be considered less biased and more conservative. On the other hand, it is considered that this method does not deal adequately with genetic data from organisms that reproduce asexually to a large extent because they may not be under Hardy–Weinberg equilibrium . By choosing a more conservative interpretation, we conclude that there are at least two genetically distinct populations, of which the McNeil strains form a unique population.Using the Bayesian-based clustering method , we observe that there are about 10% of individuals in the population including lakes Highway, Abraxas, Vereteno, that are mostly (but not entirely) assigned to the McNeil population . Differentiation has subsequently resulted because of random mutations and/or natural selection, and by chance, the McNeil population is the one that has diverged most. The other scenario is that the founder population of Scrippsiella in McNeil was different from those of the other three lakes, and because of restricted gene flow either because of physical barriers or biological barriers (Monopolization Hypothesis), it has maintained its difference.In the present study, the McNeil population was identified as the most divergent of the four lake populations based on both the bp) and was present (ice free or with thin ice) during the Last Glacial Maximum (20 000 bp) and is thus at least 20 000 years old and perhaps as much as 125 000 years old   resulted in a total of 24 loci under divergent selection (FST below expected levels, which indicates balancing selection (In an attempt to determine whether some loci were under selection, we performed an outlier analysis of the AFLP loci. AFLP loci can include both regions in coding and noncoding genes, which is why bands may be connected to genes under selection. Whether we compared all four lake populations or retained the more conservative two populations identified by the genetic structure analyses, we only found one locus that was a significant outlier indicating that it may be under divergent selection. In comparison, a genome scan for loci under selection using 440 AFLP loci in four populations of lake whitefish (election . OutlierOur data confirmed earlier findings that genetic diversity within protist populations is high (e.g. Scrippsiella has not been described, but in the Baltic Sea Scrippsiella hangoei, both the formation of asexual and to a lesser extent sexual cysts have been observed (Scrippsiella divide approximately every 6 days in culture (The high genotype diversity observed in our study can be explained by population genetic theory, which predicts that even a small amount of sexual reproduction should yield high genotype diversity in populations that otherwise reproduce mainly asexually . The amoobserved . AntarctOur results discard the null hypothesis that there is free gene flow among protist lake populations, despite close geographic proximity. Instead, population genetic analyses showed that gene flow among lakes was restricted and that the four lakes clustered into two or four separate genetic populations. The mechanisms for differentiation remain to be investigated further and environmental effects cannot be ruled out. However, our data suggest that lake age, and thereby isolation time, is a major factor determining population genetic structure, indicating persistent founder effects. To conclude, we suggest that these polar lakes act as ecological islands, not only for macroorganisms but also for microorganisms.