C. gloeosporioides sensu lato is one of the most economically important post-harvest diseases affecting papaya production worldwide. There is currently no information concerning the genetic structure or demographic history of this pathogen in any of the affected countries. Knowledge of molecular demographic parameters for different populations will improve our understanding of the biogeographic history as well as the evolutionary and adaptive potential of these pathogens. In this study, sequence data for ACT, GPDH, β-TUB and ITS gene regions were analyzed for C. gloeosporioides sensu lato and C. truncatum isolates infecting papaya in Trinidad and Mexico in order to determine the genetic structure and demographic history of these populations.C. gloeosporioides sensu lato population with asymmetrical migration to Trinidad. Mexico also had the larger effective population size but, both Mexico and Trinidad populations exhibited population expansion. Mexico also had greater nucleotide diversity and high levels of diversity for each gene. There was significant sub-division of the Trinidad and Mexico populations and low levels of genetic divergence among populations for three of the four gene regions; β-TUB was shown to be under positive selection. There were also dissimilar haplotype characteristics for both populations. Mutation may play a role in shaping the population structure of C. gloeosporioides sensu lato isolates from Trinidad and from Mexico, especially with respect to the ACT and GPDH gene regions. There was no evidence of gene flow between the C. truncatum populations and it is possible that the Mexico and Trinidad populations emerged independently of each other.The data indicated that Mexico is the ancestral C. gloeosporioides sensu lato and C. truncatum, in Trinidad and Mexico. Understanding the genetic structure of pathogen populations will assist in determining the evolutionary potential of the pathogen and in identifying which evolutionary forces may have the greatest impact on durability of resistance. Intervention strategies that target these evolutionary forces would prove to be the most practical.The study revealed relevant information based on the genetic structure as well as the demographic history of two fungal pathogens infecting papaya,  Colletotrichum gloeosporioides is one of the most common and widely distributed plant pathogens in the world [C. gloeosporioides is considered to be a species complex but for practical reasons, it may be simpler to refer to the taxa as a species complex rather than using intra-specific designations [he world ,2 and hahe world . The funhe world . C. gloegnations ,6.Carica papaya L.) production worldwide [C. gloeosporioides sensu lato is the pathogen most commonly associated with anthracnose of papaya. C. acutatum from papaya in Australia was identified as an ex-epitype strain by Simmonds in 1965, but it has not been reported in papaya since that time. There have been reports of C. truncatum , gene flow, linkage disequilibrium and migration [rpoB, ndhJ, accD, atpB, COX1, 5.8S rRNA) [Colletotrichum species relationships [C. gloeosporioides sensu lato and concluded that species relationships could be resolved.One approach for deriving meaningful information on population genetics is by comparing multiple nucleotide sequences, including arbitrary regions , and subigration . Many po8S rRNA) . A compa8S rRNA) ,23. Multionships -28. For Knowledge of molecular demographic parameters, such as the effective population sizes, levels of species divergence, and rates of gene flow and migration patterns between populations will elucidate the biogeographic histories of the species, the evolutionary and adaptive potential of these pathogens; information on the genetic structure of these populations can also assist in the development of disease management strategies i.e. pesticide use, predicting resistance breakdown, production of disease resistant transgenics and in streamlining cultural practices -32. UndeC. gloeosporioides sensu lato and C. truncatum from Mexico and Trinidad and (ii) determine the demographic history of these isolates based on multi-locus sequence data.The objectives of this study were to (i) compare the genetic and population structure of isolates of Isolate collection data for Trinidad and Mexico is summarized in Table C. gloeosporioides sensu lato isolates from Trinidad had more segregating sites (S) in the ACT and ITS sequences than those from Mexico as well as a greater number of mutations (Eta) and haplotypes (h) than Mexico. Haplotype diversity (HdT) was highest for ACT but there were near equivalent values for the other three genes. The highest number of haplotypes (hT) was obtained for the ACT gene, followed by GPDH, β-TUB and ITS (Table Measures of DNA divergence enabled gene-by-gene comparisons of the level of genetic diversity in each population under study. C. gloeosporioides sensu lato isolates from Mexico had a higher number of nucleotide differences (k) and consequentially, higher nucleotide diversity (Pi) than Trinidad for all four genes. A comparison of DNA divergence parameters for the four genes indicated that GPDH had the highest cumulative number of polymorphic sites, total number of mutations and the highest average number of nucleotide differences followed by ACT, ITS and β-TUB had the lowest. There were no fixed differences among the four genes. Watterson’s theta (θ-W per site and per sequence) was also higher for ACT and ITS (Trinidad) while theta was higher for GPDH and β-TUB (Mexico). Generally, the conservation threshold (CT) was highest for β-TUB and ITS genes (Trinidad and Mexico) and lowest for GPDH (Mexico). There were no shared mutations in the β-TUB gene; GPDH and ITS had a near equivalent number of shared mutations and ACT had the least number. The average and net number of nucleotide substitutions per site between populations were highest for GPDH, followed by ACT, β-TUB and ITS (Da and Dxy(JC)). The average number of nucleotide differences (KT) and consequentially, nucleotide diversity (PiT) were highest for GPDH, followed by ACT  analyzed and as such certain population genetics statistics could not be computed. The Mexico population had greater diversity for all parameters. None of the haplotypes were shared between the two populations except for one haplotype of the GPDH gene. The conservation threshold was highest for β-TUB and ITS and near equivalent for Trinidad and Mexico. GPDH had the lowest conservation threshold value for both populations . The Snn value for the GPDH gene region was intermediate between 0.5 and 1.0  for ACT, β-TUB and ITS gene regions but, the Snn value for the GPDH gene region was close to 0.5  and ranged from 0.454 to 0.656 suggesting a high level of genetic differentiation between C. truncatum populations. However, AMOVA identified that of the total observed variation in the ACT gene, 57% was between populations and 43% was within populations; in the GPDH gene it was 5% and 95%; in the β-TUB gene it was 71% and 24%; in the ITS gene it was 82% and 18%, respectively  for the Trinidad population than for the Mexico population. For Mexico, the highest percentage of LD was found in the GPDH gene (54.29%). For the Trinidad population, the highest percentage of LD was found in the β-TUB gene (100.00%)  Table . LD coulD and Fu and Li’s F* and D* tests(a) Tests of neutrality-Tajima’s D values were negative for all four genes in the C. gloeosporioides sensu lato Mexico population and for three genes  in the C. gloeosporioides sensu lato Trinidad population. Only β-TUB (Trinidad) had positive D-values but these were not significant at P ≤ 0.05. For both Trinidad and Mexico populations, three genes, ACT, GPDH and ITS, had Tajima’s D-values that were less than zero and were significantly different from the neutral assumption which suggest recent population expansion or selection. The F* statistic was negative and significantly (P ≤ 0.02) deviated from the assumption of neutrality for three genes  in the Trinidad population. The D* statistic significantly deviated from the null hypothesis for ITS (Trinidad) at P ≤ 0.02, but ACT (Trinidad) and GPDH (Mexico) deviated significantly at P ≤ 0.05 and were large negative values  was analyzed, but none of the tests of neutrality were significant at the stipulated alpha levels. Tajima’s D and Fu and Li’s F* and D* statistics were negative and significant at P ≤ 0.05 and P ≤ 0.02 levels respectively for the β-TUB (Mexico) (Table The (b) Mismatch distribution and demographic expansionC. gloeosporioides sensu lato isolates, none of the sums of squared deviations (SSD) of mismatch distribution was significant for the ACT and GPDH gene regions indicating a fit to the demographic expansion model tested. These results suggest that the deviation from neutrality was due to recent population expansion. For both populations, the sums of squared deviations (SSD) of mismatch distribution for β-TUB and ITS gene regions were significant which provides evidence to reject the null hypothesis of recent population expansion . These results in conjunction with the non-significant SSD model values obtained from mismatch distribution tests suggest that this gene may be under positive selection in both populations. Although the ITS region is transcribed, putatively conserved domains as a translated protein were not detected and no coding regions were identified thus, the Ka:Ks ratio could not be determined. However, the demographic data and the large significant negative values obtained for Fu and Li’s Conservative estimates of the putative time of population expansion from tau (t), calculated by ARLEQUIN after 1,000 re-samplings, indicate that the Trinidad population has a more recent evolutionary history and that the Mexico population is older and would have diverged earlier than the Trinidad population based on analysis of ACT, GPDH and β-TUB gene regions.C. truncatum population indicating a fit to the demographic expansion model tested. The sum of squared deviations (SSD) of mismatch distribution was not significant for the GPDH and ITS gene regions of the Mexico population which provides evidence to reject the null hypothesis of recent population expansion (Table The sum of squared deviations (SSD) of mismatch distribution was significant for ACT and β-TUB gene regions of the Mexico C. gloeosporioides sensu lato isolates, there was evidence of asymmetrical migration from Mexico to Trinidad for three gene regions  as migration rates were higher for the Mexico to Trinidad direction than in the opposite direction. β-TUB was shown to be under positive selection and would not be exchanged in gene flow events. The effective population size was also larger for Mexico than for Trinidad. The number of immigrants was higher for the Trinidad population for the three genes than for the Mexico population. The 2.5%, 97.5% and the mean likelihood estimates are presented  determine the migration pattern of these isolates based on multi-locus sequence data.The objectives of this study were to (i) compare the genetic and population structure of isolates of C. gloeosporioides sensu lato population for all genes and greater haplotype diversity in the Trinidad C. gloeosporioides sensu lato population for ACT and GPDH genes alone. The measures of haplotype diversity, Hd, can range from zero, meaning no diversity, to 1.000, which indicates high levels of haplotype diversity [C. gloeosporioides sensu lato populations as an historical event that occurred prior to isolation and divergence.A higher degree of haplotype and nucleotide diversity is expected in an ancestral population -35. We fiversity . With reGST values) in the β-TUB gene region which was under selection and was not exchanged in gene flow events.Divergent selection can impose variable genome-wide effects. For example, gene flow can override genetic differentiation at all loci except those that are directly under selection or are linked to selection ,37. ThisC. gloeosporioides sensu lato populations and low levels of genetic divergence among populations for three of the four gene regions (β-TUB was the exception). Hudson’s Snn statistic indicated that the C. truncatum populations were highly sub-divided for ACT, β-TUB and ITS gene regions.We also examined the data for the occurrence of sub-division in our study isolates based Bayesian posterior probability, AMOVA, and Hudson’s test statistics. We found significant within-population sub-division of the Trinidad and Mexico C. gloeosporioides sensu lato isolates in Trinidad and in Mexico especially with respect to the ACT and GPDH gene regions. The lowest number of mutations was obtained for the β-TUB gene region which is expected as this region was shown to be under positive selection. Strong positive selection causes a reduction in levels of nucleotide diversity (37) and the β-TUB gene region had the lowest level of nucleotide diversity of all four gene regions in the Trinidad population. Mutation in the ITS region would be tolerated once the transcribed product is not negatively affected and compensation mechanisms would be engaged because of the multi-copy number nature of this region.Mutation rates are usually low but can vary according to loci and pathogen and the effects are detectable when operating in conjunction with other evolutionary forces e.g. population size . In thisC. gloeosporioides sensu lato population appeared to have a higher LD than the Mexico population.Linkage disequilibrium (LD) can be influenced by a number of evolutionary factors including selection by selective sweeps in which the alleles at flanking a locus under selection are rapidly swept to high frequency or fixation due to genetic hitchhiking . PopulatC. gloeosporioides sensu lato three neutrality test statistics  were used in this study to examine the sequence data for departure from neutrality. D* and F* test statistics for all except the β-TUB gene were significant and negative in the Trinidad population, which we cautiously interpreted as rejection of the null hypothesis of constant population size. Other evolutionary processes such as genetic hitchhiking or extinction and recolonization events [To further examine evolutionary forces acting on the populations of n events ,32 can cC. truncatum isolates had higher haplotype and nucleotide diversity than the Trinidad population. But, again, there was only one shared haplotype (for the GPDH gene region) between the two populations. There was no evidence of gene flow, however, for these populations and it is likely that the haplotype characteristics reflect distinct populations that shared no past or historical migration events. Watterson’s estimator of mutation rate was also lower for all four genes for C. truncatum isolates than for C. gloeosporioides sensu lato isolates. It is likely that the C. truncatum populations emerged independently of each other. Tapia-Tussel et al. [C. truncatum infecting a range of different hosts (including pepper) would reveal more information of the possible introduction of this species to Trinidad and Mexico.The Mexico population of l et al.  suggesteStructural and metabolic genes that are transcribed and then translated into protein products are often used in phylogenetic analysis and for taxonomic demarcation, but their use in population genetics studies may result in a bias in the evolution of genes that are under strong selection. Nucleotides in third or wobble codon position may not be subject to positive selection but, their frequency in a given population could be affected by proximity to selected regions through genetic hitchhiking ,30. In sThe relative migration rates of hosts and pathogens play a key role in determining patterns of local adaptation, which can in turn influence patterns of disease. Migration influences the evolution and sustainability of genetic diversity in host resistance, pathogen virulence genes, and fungicide resistance -31. It iC. gloeosporioides sensu lato isolates, population expansion has been detected for both populations in this study, however, the effective population size was found to be greater for the Mexico population. There was also evidence of asymmetrical migration from Mexico to Trinidad for three gene regions . Mexico appeared to be the older ancestral population and Trinidad the more recent population based on the estimated demographic parameters. This would explain the differences in nucleotide diversity in the two populations. There were also dissimilar haplotype characteristics for both populations. Watterson’s estimator of mutation rate indicated that mutation may have some role in shaping the population structure of C. gloeosporioides sensu lato isolates in Trinidad and in Mexico especially with respect to the ACT and GPDH gene regions. The data suggests that C. gloeosporioides sensu lato isolates may have co-migrated with the host to Trinidad. There was no evidence of gene flow between the C. truncatum populations and it is possible that these populations emerged independently of each other.With respect to Pathogen populations may be bound by differently-acting evolutionary processes including recent or historical migration events, selective sweeps and extinction-recolonization processes typical of agroecosystems . Strong 3 block of tissue was removed from advancing edge of each lesion and was placed in the centre of 2% water agar -WA  amended with 50 mg L-1 streptomycin and 50 mg L-1 tetracycline (Sigma-Aldrich Co. Ltd. USA). Plates were incubated for five days at 25°C in the dark. After incubation, a block of agar (4 mm3) taken from the advancing mycelial edge of an actively growing culture was removed and placed in the centre of a PDA plate  supplemented with 50 mg L-1 streptomycin and 50 mg L-1 tetracycline). Cultures were incubated for five days at 25°C in the dark. Isolates were maintained as conidial suspensions in 50% glycerol at −70°C for long-term storage . PCR amplification conditions consisted of an initial denaturation of 5 min at 94°C followed by 35 cycles of 1 min at 94°C, 1 min at 55°C, 1 min at 72°C with a final extension of 5 min at 72°C. PCR products were sequenced directly .Isolates were grown in PDB (potato dextrose broth) in the dark for nine days at 25°C in a rotary shaker at 150 rpm. The mycelial mat was removed and dried on sterile filter paper. DNA was extracted using the E.Z.N.A. DNA extraction kit . Four gene regions were amplified by PCR: ITS rDNA, partial β-tubulin (β-TUB), partial actin (ACT) and glycerol-3-phosphate dehydrogenase (GPDH) gene regions. PCR reactions were carried out using the universal primer pair ITS4/5 to amplify the ITS region (496 bp) of the nuclear ITS1-5.8S-ITS2 rDNA , Bt2a/b C. gloeosporioides and were identified as belonging to the C. gloeosporioides sensu lato circumscription before inclusion in subsequent analyses. Sequences of representative isolates were deposited in GenBank. A total of 204 sequences was used in the final dataset for C. gloeosporioides sensu lato isolates: 120 sequences from the Trinidad population (n = 30 for each of the four gene regions) and 68 sequences from the Mexico population (n = 17 for each of the four gene regions). A total of 84 sequences was used in the final dataset for C. truncatum isolates: 32 sequences from the Trinidad population (n = 8 for each of the four gene regions) and 52 sequences from the Mexico population (n = 13 for each of the four gene regions).The identity of the sequences of isolates and comparisons of cognate sequences available in the GenBank and EMBL public databases were made using the gapped BLASTn algorithm. Sequences of all isolates were compared to cognate sequences of epitype and ex-epitype strains of http://tree.bio.ed.ac.uk), the alignment was then visually inspected, edited, and trimmed to common nucleotide lengths for ACT, GPDH, β-TUB and ITS gene regions.Alignments were performed using MUSCLE  under dea priori assumptions about the isolates and their assignments to populations or sub-populations other than in the operational sense as isolates collected from a particular country i.e. isolates collected from Mexico constituted the Mexico population and those collected from Trinidad constituted the Trinidad population.Standard population genetic analyses were performed using DNASP version 5.10 ,44 and Ak), nucleotide diversity (pi and pi(JC)) for each population were computed. Watterson’s estimator of mutation rate (θ-W) on a per site and per sequence basis was also calculated for all four genes for each population. The conservation threshold was also determined.Measures of DNA divergence including the average number of nucleotide differences  [Genetic differentiation between pairs of populations (GST)  adapted GST) ,44 was cGST) . PopulatSnn) is a measure of how often the “nearest neighbors” (in sequence space) of sequences are from the same locality in geographic space. The statistic is applicable when genetic data are collected on individuals sampled from two or more localities. If a population is strongly structured, one expects to find the nearest neighbor of a sequence in the same locality. Thus, Snn is expected to be near 1.0 when the populations at the two localities are highly structured because the majority of sequences would be similar to other sequences of the same population and near 0.5 when the populations at the two localities are not genetically structured because the most similar sequences could come from either population with equal probability [The nearest-neighbor statistic  according to the method of Ramdeen and Rampersad [in silico restriction digestion, a virtual 1.5% agarose gel electrophoresis image was captured as a device-independent plot by the program pDRAW32  of every sample [tter V.2  and WEB-ampersad . Twelve one.com, ). Binaryone.com, -55 was uP ≤ 0.05). The test was implemented in DNASP. Two loci were considered to be in LD when their associated P-value was less than 0.05. Only parsimony informative polymorphic sites were considered.Linkage disequilibrium (LD)  was deteD[D* and F*[D does not consider. As a result, it may be less powerful and may not be as efficient at detecting departures from neutrality as other alternative statistics hence the reason for implementing Fu and Li’s tests. Neutrality tests were used as an indication of recent population expansion when the null hypothesis of neutrality was rejected due to significant negative values where Tajima’s D statistic was significant at P ≤ 0.05; and Fu and Li’s D* and F* statistic were significant at P ≤ 0.02 [D was tested by random permutation using 1,000 replicates in ARLEQUIN. Significantly negative values of these neutrality statistics although indicative of population expansion, may be due to other evolutionary forces such as background selection and genetic hitch-hiking associated with selective sweeps.To determine whether a model of the population expansion was applicable to both populations we performed the neutrality tests of Tajima’s D and Fu aD* and F*-59 statiD* and F* pointed P ≤ 0.02  under 10We also used analysis of mismatch distribution ,62 to heWe estimated the putative time of population expansion most of the populations from the tau (t) statistic  which was calculated in ARLEQUIN. An estimate of Tau = 2ut is given where u = mTμ and t is the estimated time of expansion, mT is the number of nucleotide sequences under study and μ is the mutation rate per time.0 some T generations in the past and have remained isolated from each other ever since. From the average number of pairwise difference between and within populations the divergence time scaled by mutation rate is estimated and a conservative interpretation can be explained [The divergence time (tau) between populations of unequal size was estimated . The modxplained .M) between population pairs. Estimates of gene flow among populations were obtained using the maximum likelihood approach, full migration matrix model of 10 short chains, each with a total of 50,000 genealogies and with a sampling increment of 100 genealogies and 10 long chains, each with a total of 100,000 genealogies and a sampling increment of 100 genealogies. The first 10,000 genealogies in each chain were discarded. All other settings were default to the program. The confidence interval for θ and migration parameter M was calculated using a percentile approach [Historical migration between populations was estimated with MIGRATE-n version 3.0.3 . MIGRATEapproach . The prohttp://dx.doi.org/10.6070/H4BZ63Z8.The data set supporting the results of this article is available in the LabArchives LLC repository, Representative sequences, as their assigned GenBank accession numbers, can be accessed using the following links:-http://www.ncbi.nlm.nih.gov/nuccore/JF749805JF749805, http://www.ncbi.nlm.nih.gov/nuccore/JF749806JF749806, http://www.ncbi.nlm.nih.gov/nuccore/JQ218143JQ218143, http://www.ncbi.nlm.nih.gov/nuccore/JQ218144JQ218144, http://www.ncbi.nlm.nih.gov/nuccore/JQ218145JQ218145, http://www.ncbi.nlm.nih.gov/nuccore/JQ218146JQ218146, http://www.ncbi.nlm.nih.gov/nuccore/HQ287579HQ287579, http://www.ncbi.nlm.nih.gov/nuccore/HQ287580HQ287580, http://www.ncbi.nlm.nih.gov/nuccore/HQ287581HQ287581, http://www.ncbi.nlm.nih.gov/nuccore/HM450128HM450128, http://www.ncbi.nlm.nih.gov/nuccore/HM450129HM450129, http://www.ncbi.nlm.nih.gov/nuccore/HM562709HM562709, http://www.ncbi.nlm.nih.gov/nuccore/HM562710HM562710, http://www.ncbi.nlm.nih.gov/nuccore/HM562711HM562711, http://www.ncbi.nlm.nih.gov/nuccore/JX982230JX982230, http://www.ncbi.nlm.nih.gov/nuccore/JX870645JX870645, http://www.ncbi.nlm.nih.gov/nuccore/JX878500JX878500, http://www.ncbi.nlm.nih.gov/nuccore/JX870646JX870646, The authors declare that they have no competing interests.SR collected the fungal isolates and performed the experiments for Trinidad; DP-B, CT-C and RT-T collected the fungal isolates and performed the experiments for Mexico. CC carried out all of the alignments. SR analyzed the data and wrote the manuscript. All authors read and approved the final manuscript.


Calophyllum Braziliense Camb. , also know as guanandi, jacareúba or landim, is a canopy tree species typical of waterlogged areas from South and Central America. This species occurs in the humid tropical forests of Central America, Amazon Forests, Atlantic Forest (including restingas); and in the riverines forests of the Cerrado biome (brazilian savannah) [C. Braziliense shows none of the morphological features common to flood-adapted plants. Calophyllum Braziliense is a hermaphroditic tree pollinated by bees. Its seeds are animal (mainly by bats) or water dispersed. The timber has excellent characteristics and is widely used. Calophyllum. Braziliense is also used in vegetation restoration programs and its leaves extract presents anti-inflammatory activity [C. Braziliense based on the cpDNA intergenic region psbA-trnH.Past climate changes have severely influenced the current distribution of species and their genetic diversity. Phylogeography is the study of the principles and processes governing the geographic distributions of genealogical lineages . South Aavannah) ,6. Howevactivity . This stC. Braziliense were sampled from Costa Rica  to the Paraná State in Brazil . Samples were collected from about 5-10 adult trees in each population, totaling 192 individuals. Total DNA was extracted from leaves or cambium using the CTAB procedure described by Doyle & Doyle [C. Braziliense, the psbA-trnH intergenic regions was selected [Twenty four populations of psbA-trnH locus. Twenty-eight variable characters were analyzed resulting in seven cpDNA haplotypes  for each population ranged from 0.0 to 0.533 and the nucleotide diversity (π) from 0.0 to 0.01882. Similar levels of genetic diversity were observed for other tropical species [k=7, Fct = 0,926), one consisting of 13 monomorphic populations from the Brazilian Atlantic rain forest and more three populations from de Cerrado biome. Most of the others populations constitute different phylogroups. Neutrality tests suggest expansion for the Atlantic rain forest populations. The AMOVA analysis reveals that most of the variation was found between populations . A great genetic distance was observed between Central America (Costa Rica) and the others populations, even from the Brazilian Amazon forest. Similar results were observed when Swietenia macrophylla (mahogany) populations from Central and South America were compared [A total of 263 aligned positions were obtained for the s Figure . The hap species ,11. Mostcompared .C. Braziliense based on chloroplast DNA diversity indicate a recent expansion for the Atlantic rain forest populations. Our results suggest that the Northeast of Brazil maintained large populations during the last glacial period and that the Southeast and South populations may have undergone a pronounced retraction process, followed by a recolonization process with a strong founder effect. Thus, the recolonization of the South and Southeast region of the Atlantic rain forest probably occurred from these more stable areas in the Northeast.The genetic data obtained here for


To evaluate Y-chromosomal diversity of the Moravian Valachs of the Czech Republic and compare them with a Czech population sample and other samples from Central and South-Eastern Europe, and to evaluate the effects of genetic isolation and sampling.The first sample set of the Valachs consisted of 94 unrelated male donors from the Valach region in northeastern Czech Republic border-area. The second sample set of the Valachs consisted of 79 men who originated from 7 paternal lineages defined by surname. No close relatives were sampled. The third sample set consisted of 273 unrelated men from the whole of the Czech Republic and was used for comparison, as well as published data for other 27 populations. The total number of samples was 3244. Y-short tandem repeat (STR) markers were typed by standard methods using PowerPlex® Y System (Promega) and Yfiler® Amplification Kit (Applied Biosystems) kits. Y-chromosomal haplogroups were estimated from the haplotype information. Haplotype diversity and other intra- and inter-population statistics were computed.The Moravian Valachs showed a lower genetic variability of Y-STR markers than other Central European populations, resembling more to the isolated Balkan populations  than the surrounding populations . We illustrated the effect of sampling on Valach paternal lineages, which includes reduction of discrimination capacity and variability inside Y-chromosomal haplogroups. Valach modal haplotype belongs to R1a haplogroup and it was not detected in the Czech population.The Moravian Valachs display strong substructure and isolation in their Y chromosomal markers. They represent a unique Central European population model for population genetics. Y-chromosomal variation of Central European populations and the possible appearance of genetic isolates in these populations are of increasing interest to forensic and human population geneticists.Y-chromosomal data for the population of the Czech Republic is still fractional. Kráčmarová et al published a short report on paleolithic and neolithic Y chromosomal haplogroups in the Czech population  and LucaSo far, a limited number of studies that illustrate the variety of Y-chromosomal polymorphisms in the countries and populations supposedly connected or similar to the Moravian Valachs – the supposed isolate – have been published. Rebala et al  focused The Valachs  are one of the most distinct ethnographic and cultural subpopulations of Central Europe. Today, they can be found not only in the Czech Republic – in its eastern border mountain ranges and highlands (Beskydy in Moravia) – but also in south-southeast Poland and several parts of Slovakia . Originally, this group spread from the Maramures region of Romania, roughly following the Carpathian Mountain range. The arrival of the Valachs to the area of today’s Czech Republic took place at the very end of the 15th or beginning of the 16th century . The migUntil the beginning of the 20th century, the Moravian Valachs’ way of life was similar to other Romanian ethnic groups in the Balkans, especially the Aromuns . An admixture of the newly-arrived Valachs with autochthonous (Slavic and German) Moravian population also began soon after the arrival of the first immigrants – so we can assume a steady genetic and cultural flow between these two populations. Nonetheless, the core of the Valach settlement was located in a previously uninhabited high altitude region, neighboring with the indigenous population from lowlands. The result of the admixture process was a complete merging of both populations, and the disappearance of any distinction between “new” Valachs and indigenous Moravians during the 18th century, and the creation of one ethnogeographic region with all its properties and people – the Moravian Valachs.Demographic data ,14 show To investigate how severe this isolation effect was on Y chromosomal polymorphisms in the Moravian Valachs and whether it is still detectable in modern Valach population is the main aim of our study. Another topic of interest was how the intra-population variability and the sampling bias can affect forensic and population analyses performed on these data.Hundred and seventy-three DNA samples of male Valachs from the Czech Republic were analyzed. These samples were divided into two groups because of the important differences in sampling procedure and are consistently referred to separately throughout this article.The first group consisted of 94 samples of unrelated donors . All donors identified themselves as belonging to the Valach ethnic group in a short interview that was held immediately before DNA sampling in the form of mouth swabs. Only donors whose paternal lineage was present in the region of the Valach country for at 3 generations were included into the study. Informed consent was provided by the donors and no other data  were gathered. The data were rendered fully anonymous.The second Valach sample set consisted of 79 samples . The sampling process in this case differed significantly from the VALACH sample set. VLIN sample set came from 7 Valach paternal lineages. These were defined primarily by surname, as well as by geographic localization in the Valach region and self-identification of the donors. Although the samples came from broad families, no first, second, third, and fourth degree relatives were included in the study, virtually making this Valach sample set composed of unrelated, non-randomly selected Valachs, carrying 7 different surnames.http://www.yhrd.org/) database.The control sample set consisted of 273 unrelated male donors from the whole Czech Republic. Donors did not identify themselves as having the Valach origin, however, there was no other information gathered about their ethnicity or origin. Data are available on request and will be submitted to the Y-chromosome haplotype reference database (We gathered published samples for Y-short tandem repeat (STR) loci from other populations, concentrating on Eastern European and Balkan populations. Our total set, Moravian Valachs included, consisted of 30 populations encompassing 3244 individuals . Due to The Y-chromosomal STRs of VALACH samples were assessed using PowerPlex® Y System . It contained 12 microsatellite polymorphic sites , including all recommended minimal haplotype loci (minHT), and all extended haplotype loci .CZE samples and VLIN samples were typed using AmpFiSTR Yfiler® PCR Amplification Kit , that included all of the above mentioned loci plus DYS456, DYS458, DYS635, Y GATA H4, DYS448. All 17 markers were used only in evaluating discrimination capacity of Y-STR haplotypes in CZE and VLIN sample sets.http://www.hprg.com/hapest5/)  ,16. We wapest5/) , thus fohttp://www.fluxus-engineering.com) (Genetic intra-population indices were computed in Arlequin v3.1 software . For coning.com) ,20. We uing.com) . The resThe multidimensional scaling analysis was performed in Statistica 9.0 software .The Moravian Valachs of the Czech Republic showed remarkably low values of intra-population genetic diversity. This low differentiation, as compared with other populations in our study, is shown by the haplotype (gene) diversity values ± standard deviation (0.9792 ± 0.0075), the average gene diversity per locus (0.476607 ± 0.268081), and the mean number of pairwise differences (3.812857 ± 1.936064) . This isTo assess the power of discrimination of the used Y-STR markers, we computed the discrimination capacity for both of the Valach sample sets  and Czech sample set (CZE) for 9, 12, and 17 Y-STR marker haplotypes . DiscrimST distances between the Valachs and other populations were all significant at 0.10% level (10 000 permutations). The RST distances displayed a more random pattern, which could have been caused by small allele length differences between the populations. We computed the complete FST and RST genetic distances between the selected populations (Table 4). The FST genetic distances were visualized by multidimensional scaling analysis (MDS). Its results for first and second MDS dimensions are plotted in The values of intra-population statistics showed a decrease in Y-chromosomal diversity as the result of isolation. Further evidence of the isolation are the pairwise genetic distances between the Valachs  and other surrounding populations from our sample set: Czechs (CZE), Slovaks (SLO), Saxons (SAX), Hungarians (HUN), and Poles from Central and Southeast Poland . The pairwise FDistribution of Y chromosomal haplogroups in the VALACH, VLIN, and CZE populations was not uniform . While oVariation within selected haplogroups is displayed in R1a is the most prevalent and the most diverse haplogroup in the Valach and Czech population. Therefore, we selected this haplogroup for further analysis and identification of its modal haplotype.The Y-chromosome haplotype that is common in the Euro-Atlantic populations is called “Atlantic Modal Haplotype” . We propST pairwise distances. Non-significant pairwise FST genetic distances based on 12 Y-STRs were shown between the regions surrounding the Valach country  and CZE, but highly significant between the Valach samples and both CZE and Zastera’s data . Thus the Valachs are isolated not only from the general Czech population, but also from the non-Valach Czech population from the regions neighboring the Valach region.We found the traces of isolation and substructure in the Moravian Valachs’ Y-chromosomal genetic variation. Studies with well defined Y-chromosomal data for Central Europe are scarce. Previously mentioned studies of Czech population Y-STR variability reported no inner differentiation of the population ,3. A subY-STR analysis of the VALACH population sample revealed a previously unnoted modal haplotype within the haplogroup R1a (VMH). The reason for comparing the VMH with the European metapopopulation of Y-chromosome haplotype reference database was to test whether the VMH was specific just for the typical Moravian Valach region or can be found in populations where we expect the occurrence of Valach individuals. The majority of close and neighbor matches were from the populations and geographic locations where the migration of the Romanian or Moravian Valachs was recorded. The matches in non-Slavic regions  are in concordance with the emigration waves of the Valachs in the 19th and 20th century.Forensic analysis of Y-chromosome loci requires the highest possible haplotype diversity. Some studies have shown  that comBesides the genetic or forensic aspects, the ethical aspects of data gathering and presentation should be predominant, especially if we want to investigate not-so-distant paternal lineages. Moreover, genealogical, linguistic, and historical information is also of foremost interest to the researcher. The optimal number of Y-chromosomal STR polymorphic loci to be used in such a study differs vastly according to the objectives. We confirmed that 17 loci of Yfiler kit could be insufficient for forensic application if we were to analyze a cluster of related paternal lineages. On the other hand, for population genetic applications, a set of a few precisely defined core Y-STR could very well describe the population and could be used for interpopulation comparison. Properties of the sample set under examination are also strongly influenced by the sampling procedure, which is not always known or properly administered. We demonstrated this sampling effect on the differences between our Moravian Valach sample sets (VALACH vs VLIN).Our analyses confirmed that the Moravian Valachs represent a unique population data set from the Czech Republic and the whole region of Central Europe due to their ethnographic coherence and isolation that is clearly detectable in their Y-chromosomal diversity. The VMH can be used for further studies on Valach migration or in the evaluation of forensic analysis results.


ObStruct evaluates the extent of structural similarity between sampled and inferred populations, tests the significance of population differentiation, provides information on the contribution of sampled and inferred populations to the observed structure and crucially determines whether the predetermined factor of interest correlates with inferred population structure. Analyses of simulated and experimental data highlight ObStruct's ability to objectively assess the nature of structure in populations. We show the method is capable of capturing an increase in the level of structure with increasing time since divergence between simulated populations. Further, we applied the method to a highly structured dataset of 1,484 humans from seven continents and a less structured dataset of 179 Saccharomyces cerevisiae from three regions in New Zealand. Our results show that ObStruct provides an objective metric to classify the degree, drivers and significance of inferred structure, as well as providing novel insights into the relationships between sampled populations, and adds a final step to the pipeline for population structure analyses.Bayesian inference methods are extensively used to detect the presence of population structure given genetic data. The primary output of software implementing these methods are ancestry profiles of sampled individuals. While these profiles robustly partition the data into subgroups, currently there is no objective method to determine whether the fixed factor of interest (e.g. geographic origin) correlates with inferred subgroups or not, and if so, which populations are driving this correlation. We present O A widely used, newer and more powerful approach utilises Bayesian MCMC methods to test for population structure and dispenses with the need to assign individuals a priori to populations, and thus circumvents this issue When there is a lack of free gene flow within sexual populations, neutral and selective forces will erode population homogeneity and tend to establish population structure structure is the most widely-used software package for Bayesian analysis and clusters individuals by attempting to create inferred populations that are in, or as close as possible to, Hardy-Weinberg equilibrium structure produces ancestry profiles for each individual showing the proportion of time each individual is present in each of the inferred populations. The methods implemented in InStructdistructbaps itself. The ancestry profiles represent an objective estimation of structure and admixture within the data, and distruct visualises groupings by colouring each inferred population uniquely so that a highly structured dataset will show sampled populations mostly containing a single colour. While this approach produces a figure that is readable, it only allows a subjective visual interpretation of whether any patterns in the ancestry profiles correlate with the fixed factor of interest (e.g. geographic origin of samples). In clear-cut cases of striking population subdivision this might be sufficient, however not all datasets will show clear differentiation. Factors such as high admixture, recent divergence and inadequate sampling will create noise in the data which renders plots of ancestry profiles difficult to interpret. Presently, there is no method to objectively analyse these ancestry profiles. The method presented here addresses the interpretation of signals for population structure by analysing ancestry profiles generated by Bayesian methods, and is not concerned with the Bayesian method itself, which we consider robust.The optimal number of inferred populations may be estimated from these analyses The main aspect we consider here is how the assignment of individuals to inferred populations relates to the factor of interest. The Bayesian methods derive and assign individuals to subgroups without knowledge of the origin of individuals. Imagine one samples individuals from three geographic locations, and hence location is hypothesised to be a driver of structure. An analysis of the genotypes obtained using Bayesian methods suggest the optimal number of inferred populations is four. What does this mean? Any number of possibilities are biologically feasible: one location might harbor two or more populations, or perhaps geographic origin bears no relationship to the inferred populations, but some other factor does. The issue is that the current visualisation methods, while informative, do not allow population assignments and ancestry profiles to be objectively analysed: a subjective assessment of the plots is only possible. Our method statistically analyses these ancestry profiles and allows one to determine whether inferred population assignment and the factor of interest  are significantly correlated. Having determined the extent to which a factor of interest defines observed population structure, one may then conduct finer scale analyses to ascertain the relative contribution of each sampled and inferred population to overall population structure. Which sampled and inferred populations are most differentiated or contribute the most to overall structure? We set about applying a statistical procedure which can objectively quantify the level of structure in these ancestry profiles, test the sources of structure, and determine statistical significance using a permutation approach. Our method complements visualization with distruct, adds a final step to the pipeline for population structure analyses, and allows one to analyse factors driving population structure within ancestry profiles and the extent to which these factors are explaining the variability seen within ancestry profiles as a whole.bStruct directly takes structurenStructbapsbStruct can either use the optimal value of nStruct using Deviance Information Criterion (DIC) or a value specified by the user. baps can estimate structure does not estimate an optimal Ol  e.g., .bStruct tests whether the population structure represented by the ancestral profiles is correlated to the structure given by the predefined populations (sampled populations). Predefined populations are discrete sampling units within the data based on the factor of choice. For example, predefined populations in a geographic study would be different sampled regions. Predefined populations can be specified at different categorical scales to explore a single dataset in multiple ways, e.g. by language, continent, altitude, salinity, region, pH, etc. If inferred structure correlates with predefined populations, individuals within each of the predefined populations will tend to have high values of ancestry in a small number of unique inferred populations.OOur aim is to determine the extent to which the factor of interest (encoded as the predefined populations) is reflected in the ancestry profiles. We use the Our null hypothesis states that the inferred ancestries do not reflect our predefined populations, i.e. individuals inferred to share a high proportion of ancestry (forming a population within the data) appear randomly scattered among the predefined populations or, alternatively, all individuals have equal ancestries to all inferred populations. In short, this indicates the factor of interest does not account for or drive inferred population structure. An established way of assessing how well the predefined populations are represented by the inferred populations is by evaluating the variation within and across predefined populations e.g., . The sumThe where i.e., we assess how much of the total variability in the data is accounted for by grouping the data points according to the predefined populations. The The usual way of assessing the amount of evidence against the null hypothesis is by computing a ls e.g., . If our Since we assess the null hypothesis using the variability in the data, and the data are proportions, we have to account for heterogeneity in variance. Proportions close to 0 or close 1 tend to have a smaller variance than proportions close to 0.5. Not accounting for this can lead to observing effects that are due to the heterogeneity in the variance rather than similarities in the population structure. To address this problem we follow the common approach and use the logit transform on the proportions, i.e. we replace Having established the overall level of structure within the dataset, we can apply the statistic to examine the relative contributions of each of the predefined and inferred populations to this structure. To assess the contribution we remove one predefined or one inferred population at a time and recalculate The primary units of interest are populations deriving from the predefined factor level (e.g. geographic location) so we next focus on further analysing the patterns of structure between them. This allows us to identify similarities and differences between predefined populations and test the significance of these relationships. To do this we apply the An integral part of every statistical analysis is plotting the data to visualise the outcome of the analysis. To visualise the structure derived from the inferred populations and their relation to the predefined populations we use canonical discriminant analysis , using the R-specific packages candisc and heplots The output of OThe first figure visualises all individuals coloured according to the predefined population they belong to. The two axes are labelled with the two variables explaining the highest proportion of variability in the data. This proportion is part of the axis label, thus providing the user with information about the amount of variability visualised in the 2D-plot. Further, the plot shows two ellipsoids centred at the hypothetical average over all data points. The inner ellipse contains approximately 50% of the individuals while the outer ellipse contains about 95% of the individuals.The second figure summarises the information of the first by drawing 66% ellipsoids for every predefined population centred at the respective population mean. This type of plot indicates the position of the predefined populations relative to each other when given the transformed variables.The final figure is called an HE plot. Here, the H stands for hypothesis, and E stands for error. The plot will post the same axis labels as the previous plots. However, the predefined populations are reduced to simply show their centres. In addition, inferred populations are visualised by arrows indicating their relation to the transformed variables. Possibly the most important feature of the plot are the two ellipsoids. The one labeled group indicates the range of individuals, while the red ellipsoid labeled error indicates the range of variation between the group means if predefined and inferred populations do not resemble each other. If there is no resemblance in structure the red ellipsoid will be large and potentially exceed the group ellipsoid, while a strong resemblance will lead to a small error ellipsoid within the group ellipsoid.To test the effectiveness of our method, we applied it to simulated and experimental data. Simulations using coalescent theory allow the demographic modeling of population structure backwards in time. This means we can directly compare the divergence of populations with known parameters with the performance of our method to describe population division processes throughout the simulation. The application of our method to experimental data then serves to illustrate the practical benefits of the method and provides further useful information on the data.nStruct and structure  isolates sampled from three regions of the North Island of New Zealand and genotyped at 9 microsatellite loci S. cerevisiae also has an extensive history of human association We chose to analyse two published datasets showing high and low levels of population structure in order to evaluate the effectiveness of our method across a range of conditions encountered in nature. The first of these datasets comprises 1,484 humans genotyped at 678 microsatellite loci in 78 worldwide populations from 7 distinct geographic continents S. cerevisiae, InStruct was run on this dataset for 100,000 iterations of burn-in and a further 100,000 iterations of sampling using the admixture model from The human data were analysed with structure as per bStruct method is implemented in a Perl script called ObStruct.pl which, along with documentation, is available from http://goddardlab.auckland.ac.nz/ObStruct. The script takes outputs from structure, InStruct and baps directly to calculate The Ostructure and InStruct. As expected, both figures show an increase in the level of inferred population structure through time after the initial divergence event. Since no gene flow occurred between populations and the rate of mutation is the same for all populations, the only variability in the simulations should be that of sampling. 5,000 individuals are present in each population but just 100 are sampled at each time point. This variability gives rise to stochasticity in the levels of population structure which is further operated on by their analyses leading to variation in the The nStruct gave rise to a consistent relationship between time and structure with little variability seen within each sample for the three replicate simulations Click here for additional data file.Table S2Pairwise matrix of  values between regions for the Saccharomyces cerevisiae dataset.(PDF)Click here for additional data file.


To analyze the haplotype of the Ezhava population of Kerala, south India, using 8 short tandem repeat (STR) loci on the Y chromosome and trace the paternal genetic lineage of the population.www.yhrd.org.Whole blood samples (n = 104) were collected from unrelated healthy men of the Ezhava population over a period of one year from October 2009. Genomic DNA was extracted by salting out method. All samples were genotyped for the 8 Y-STR loci by the AmpFiSTR Y-filer PCR Amplification Kit. The haplotype and allele frequencies were determined by direct counting and analyzed using Arlequin 3.1 software, and molecular variance was calculated with the Y-chromosome haplotype reference database online analysis tool, Among the 104 examined haplotypes, we found 98 unique ones. The average gene diversity was 0.669, with the highest diversity of 0.9462 observed for the biallelic Y-STR marker DYS 385. The allele frequency among DYS loci varied between 0.0096 and 0.75. Out of the 104 haplotypes, 10 were identical to the Jat Sikh population of Punjab, which is the greatest number among the Indian populations, and 4 to the Turkish population, which is the greatest number among the European populations. According to the allele frequency of Y-STR, the Ezhavas were genetically more similar to the Europeans (60%) than to the East Asians (40%).The vast majority of haplotypes were observed only once, reflecting the enormous genetic heterogeneity of the Ezhavas. Based on the genotype, the Ezhavas showed more resemblance to Jat Sikh population of Punjab and the Turkish populations than to the East Asians, hence indicating a paternal lineage of European origin. Due to the geographical position of the Indian Peninsula between Africa, the Pacific, and west and east Eurasia, different populations have moved through its territory. This is why ethnic Indian population shows enormous cultural, linguistic, and genetic diversity. Indian tribal and caste populations derive heritage largely from the Pleistocene southern and western Asians, receiving limited gene flow from external regions since the Holocene . Also, IThe long seacoast of Kerala on the southern-most part of India has provided a gateway to India for many Asian, European, and Srilankan missionaries and traders. Non-tribal communities of Kerala, as shown by a human leukocyte antigen (HLA) analysis, were influenced by Dravidian, Indo-European, and East Asian gene pools . The EzhDue to the unique biology of the Y-chromosome, its genetic markers have been used in many forensic and evolutionary studies to determine patrilineal relationships within and between population groups. It has been suggested that, due to different distribution of region-specific allele frequencies, Y-short tandem repeats (STR) can be used to compare closely related populations ,6. PreviWhole blood samples (n = 104) were collected from unrelated healthy male individuals of the Ezhava population of Kerala over a period of one year from October 2009. The familial histories of the participants were recorded to exclude related individuals before sample collection. Blood samples were collected using standard procedures in ethylene diamine tetra aceticacid (EDTA)-coated tubes. The individuals gave their written informed consent and the ethical approval was received from the Ethics Committee of the institution.www.yhrd.org).DNA was extracted from EDTA blood samples with the salting out method . All sam2) / N-1, where N is the population size and Pi is the allele frequency of the i-th haplotype. Furthermore, we used YHRD (www.yhrd.org) in order to determine the similarity of the Y-STR markers with the other publicly available population data. The Ezhava population was compared with other Indian populations and with selected world populations in order to investigate the pattern of paternal contributions. A total of 1890 samples were analyzed: German population sample with 685 haplotypes, Turkish population sample with 160 haplotypes, Ezhava population (our sample) with 104 haplotypes, Haryana Jat population sample with 91 haplotypes, Punjab Jat Sikh population with 108 haplotypes, Andhra Pradesh, India (Brahmin) with 109 haplotypes, Himachal Pradesh, India (Saraswat Brahmin) with 61 haplotypes, Jammu, India (Saraswat Brahmin) with 61 haplotypes, Jharkhand, India (Munda) with 68 haplotypes, Jharkhand, India  with 65 haplotypes, Madhya Pradesh, India (Kanyakubja Brahmin) with 78 haplotypes, Punjab, India  with 62 haplotypes, Tamil Nadu, India (Iyengar) with 67 haplotypes, and Tamil Nadu, India (Kuruman) with 67 haplotypes. Analysis of molecular variance (AMOVA) was used to establish the total variance among and within groups. AMOVA was done using fixation index analysis and with 10 000 permutations. From the AMOVA calculation, we obtained pairwise difference and genetic distance between populations .Allelic and haplotype frequencies were estimated by direct counting. Gene diversities were calculated using Arlequin 3.1 software , accordiThe haplotypes of 104 unrelated men from the Ezhava population of Kerala were investigated for 8 markers included in the European minimal haplotype set . The majAllele frequencies at DYS loci varied between 0.75 to 0.0096 . Gene diThe haplotypes of the Ezhavas were compared with the haplotypes of other Indian populations . The paiSimilarities in the Y-STR data were found between the Ezhavas, north Indian, and Turkish population . Out of Allelic distribution of the Y-STR markers of the Ezhavas was compared with the European and East Asian populations . The hisThis study found that the Ezhavas showed more genotypic resemblance to the Jat Sikh population of Punjab and the Turkish populations than to East Asians, hence indicating a paternal lineage of European origin.To our knowledge, there are no published data about the genetic structure of Y-chromosome in Kerala population, although data on various other ethnic groups have been reported in the last decade -19. Y-STDuplications, though rare in the Ezhava population, have been observed in monoallelic markers like DYS19, DYS389I, DYS389II, and DYS393 loci in other populations ,24. DuplThe present study established the European paternal lineage of the Ezhavas, as well as contributed to the creation of a database of 8 Y-STR markers in the population. A limitation of the study is the non-availability of comparative Y-STR-based data for other Kerala communities. Also, the study was limited to a particular geographic area with the predominant Ezhava community. The sample size was limited to 104 participants as it was a pioneering study to establish the sample size for a study with a larger sample size and wider geographic coverage. Future studies are planned to create a database for 17 Y-STR markers in all the communities in Kerala population and to enhance the sample number and geographic area of the study.


Thea section of the Camellia genus can be processed for drinking and have been domesticated. However, few investigations have focused on the genetic consequence of domestication and geographic origin of landraces on tea plants using credible wild and planted populations of a single species. Here, C. taliensis provides us with a unique opportunity to explore these issues.Tea is one of the most popular beverages in the world. Many species in the C. taliensis, which were represented by 587 individuals from 25 wild, planted and recently domesticated populations. C. taliensis showed a moderate high level of overall genetic diversity. The greater reduction of genetic diversity and stronger genetic drift were detected in the wild group than in the recently domesticated group, indicating the loss of genetic diversity of wild populations due to overexploitation and habitat fragmentation. Instead of the endangered wild trees, recently domesticated individuals were used to compare with the planted trees for detecting the genetic consequence of domestication. A little and non-significant reduction in genetic diversity was found during domestication. The long life cycle, selection for leaf traits and gene flow between populations will delay the emergence of bottleneck in planted trees. Both phylogenetic and assignment analyses suggested that planted trees may have been domesticated from the adjacent central forest of western Yunnan and dispersed artificially to distant places.Fourteen nuclear microsatellite loci were employed to determine the genetic diversity and domestication origin of C. taliensis and provides new insights into genetic consequence of domestication and geographic origin of planted trees of this species. As an endemic tea source plant, wild, planted and recently domesticated C. taliensis trees should all be protected for their unique genetic characteristics, which are valuable for tea breeding.This study contributes to the knowledge about levels and distribution of genetic diversity of  Plant domestication is one of the most important events in human history. People still depend on the staple cereal crops that were domesticated more than 6000 years ago in Central America , the NeaCamellia[C. sinensis (L.) O. Kuntze. Since about 400 years ago when the first tea was introduced into Europe [C. sinensis has been gradually familiar to worldwide people. However, C. taliensis (W. W. Smith) Melchior, an important plant for use in producing tea, has only been recognized outside of its native areas for a few decades [C. taliensis[C. sinensis is cultivated worldwide, there has been almost no genetic research conducted to answer the domestication questions of it, because the credible wild population of C. sinensis has been seldom found [C. taliensis provides a unique opportunity to document the domestication origin of tea plants.Both vital food plants and species that can be used for medicine or beverages, such as tea, have been domesticated for convenience. Tea was used at least as far back as 2,000 years ago in China . It is oCamellia, but teao Europe , C. sine decades ,23. Sevetaliensis-26, and taliensis,26. But om found . HoweverC. taliensis, a shrub or small tree (2–10 m) native to the subtropical mountain evergreen forests at altitudes of 1300–2700 m, is endemic from western Yunnan province of China to northern Myanmar [C. sinensis by its glabrous or sparsely pubescent terminal buds and five-loculed ovary  or ‘ben shan cha’  by the local people  , and the lowest in the JCW population . Inbreeding coefficient (Fis) values of 25 populations ranged from 0.029 to 0.275. The global Fis was 0.160, suggesting a low inbreeding rate in the populations of C. taliensis.7) Table . For eac2 = 25.30, df = 1, P < 0.001) and 44 were absent from the recently domesticated individuals . There was no significant difference in the number of rare alleles between the planted and recently domesticated groups   in the wild group (4.400) than in the planted (4.911) or recently domesticated (4.993) groups. HS was significantly higher (Pone tailed = 0.017) in the recently domesticated group (0.634) than in the wild group (0.583). The group comparison tests of A and HS indicated that wild populations had a lower level of genetic diversity compared with recently domesticated and planted populations. The observed heterozygosity (HO) and Fis showed no significant differences between the three groups (Pone tailed > 0.05). The genetic differentiation (Fst) was 70% higher in the wild group than in the planted or recently domesticated groups (Pone tailed ≤ 0.01)  or in OJW and YJW versus OJD and YJD . No significant difference was found in the comparisons to the other genetic parameters, including A, HS, HO, Fis and Fst , no variation was found among wild, planted and primary domesticated groups, suggesting the same genetic basis of these groups. Most of variation was detected within populations  and 12.9% of variation was found among populations Table .F values of the wild populations ranged from 0.0991 (MHW) to 0.2686 (JCW) with an average of 0.1656. The mean F values of the recently domesticated populations ranged from 0.0673 (YJD) to 0.1221 (LXD) with an average of 0.1072. Population YXP (0.0677) and DLP (0.1702) had the maximum and minimum mean F values, respectively, of the planted populations, and the average F value for this group was 0.1108  (Table C. japonica (0.84) [C. taliensis (0.606) was lower than that analysed in the cultivars and six of eight landraces of C. sinensis in Japan (0.617-0.723) [C. sinensis (0.588) [Camellia, which had higher gene diversity than C. taliensis.Microsatellites had a high variation in the tea plants ,37,38 asCamellia,40. The taliensis. In the 7) Table  was lowea (0.84) . The gen7-0.723)  but high (0.588) . The lan (0.588)  were comC. taliensis to collect leaves for producing the wild tea . About 30% of total data was performed additionally on the gel for cross and repeated scoring.2 contingency table test [A), the observed heterozygosity (HO), the gene diversity (HS) and the F-statistics were determined in FSTAT V2.9.3.2 [P values were estimated using the random permutation method.The differences between the number of rare alleles (frequency ≤ 0.05)  present ble test . The allV2.9.3.2 . This prIn the group comparison tests, the wide differences in number of trees between wild and planted groups as well as between wild and recently domesticated groups may bias the results. The subsample tests had been developed for avoiding this potential statistic bias and achieving the more detailed results. Certain adjacent populations in different groups were selected to perform the subsample comparisons: YXP and LLP versus YXW and GSW, OJW and YJW versus OJD and YJD Figure . These gF model, performed with the program STRUCTURE V2.3.3 [F values). For all pairs of wild, planted and recently domesticated populations, we set the prior mean F to 0.1. Three parallel Markov chains were run with a burn-in of 104 iterations and a run length of 105 iterations for each comparison. Regions of 90% credibility were computed from the distribution of F values estimated in the final run. The mean F values for each population were calculated across all runs and all other populations that belonged to different groups [The E V2.3.3 , was uset groups .C. taliensis to which we would assign the planted trees. Both the wild and recently domesticated samples were included to estimate the genetic clusters, because the recently domesticated trees came directly from the natural forest and the broader natural samples would make the subsequence assignment analysis more accurate. We used the admixture model and assumed that the allele frequencies were correlated among the populations. The simulations were run with a burn-in of 500,000 iterations and a run length of 106 iterations from K = 1 through 20. Runs for each K were replicated 10 times and the true K was determined according to the method described by Evanno et al. [K value, the wild and recently domesticated individuals were specified as belonging to each of K clusters but no prior information was specified as to the origin of planted trees, which established a new dataset. Using this new dataset and the admixture model, ten parallel Markov chains were run for the correlated allele frequency models with a burn-in of 500,000 iterations and a run length of 106 iterations to estimate the proportion of every planted tree’s genome possessing ancestry in each of K clusters [Using the program STRUCTURE V2.3.3 ,59, we eo et al. . After dclusters . The resclusters  and DISTclusters .DA) [DA, the program MEGA 5.1 [Genetic distances (DA)  between DA)  with 100MEGA 5.1  was implAnalysis of molecular variance (AMOVA) was performed with GENALEX 6.501 ,66 to deThe authors declare that they have no competing interests.DWZ participated in the field sample collection, carried out the molecular genetic studies, performed the statistical analysis and drafted the manuscript. JBY participated in the molecular genetic studies and statistical analysis. SXY designed the research, collected samples, participated in the molecular genetic studies and revised the manuscript. KK involved the molecular genetic studies and revised the manuscript. JPL involved the molecular genetic studies. All authors read and approved the final manuscript.Description of the microsatellite loci.Click here for fileResults of the F model comparisons. F1, F2 and F3 refer to the F values of the wild, planted and recently domesticated populations, respectively.Click here for fileResults of detecting the true K.Click here for fileSampling localities of Camellia taliensis. Population LXW is located in Myanmar and the other populations are located in Yunnan province of China.Click here for file


Styela plicata is a solitary ascidian distributed worldwide. Although its origin remains unclear, this species is believed to have spread worldwide by travelling on ship's hulls. The goals of this study were to infer the genetic structure and global phylogeography of S. plicata and to look for present-day and historical genetic patterns. Two genetic markers were used: a fragment of the mitochondrial gene Cytochrome Oxidase subunit I (COI) and a fragment of the nuclear gene Adenine Nucleotide Transporter/ADP-ATP Translocase (ANT). A total of 368 individuals for COI and 315 for ANT were sequenced from 17 locations worldwide. The levels of gene diversity were moderate for COI to high for ANT. The Mediterranean populations showed the least diversity and allelic richness for both markers, while the Indian, Atlantic and Pacific Oceans had the highest gene and nucleotide diversities. Network and phylogenetic analyses with COI and ANT revealed two groups of alleles separated by 15 and 4 mutational steps, respectively. The existence of different lineages suggested an ancient population split. However, the geographic distributions of these groups did not show any consistent pattern, indicating different phylogeographic histories for each gene. Genetic divergence was significant for many population-pairs irrespective of the geographic distance among them. Stochastic introduction events are reflected in the uneven distribution of COI and ANT allele frequencies and groups among many populations. Our results confirmed that S. plicata has been present in all studied oceans for a long time, and that recurrent colonization events and occasional shuffling among populations have determined the actual genetic structure of this species.Genetic tools have greatly aided in tracing the sources and colonization history of introduced species. However, recurrent introductions and repeated shuffling of populations may have blurred some of the genetic signals left by ancient introductions.  Biological introductions have notably increased during the last century, posing a major threat to global biodiversity and altering the structure and function of many communities Genetic diversity plays a crucial role on the successful establishment of an introduced species or variant in a new area The increasing pace of introductions has also fostered increased awareness. Monitoring and control programs have been established, and recent introductions are more easily detected and inventoried than in the past The paramount importance of ascidians for the study of marine introductions is well recognized, as they represent one of the most common invaders Styela plicata   is a solitary ascidian commonly found inhabiting marinas and harbours of warm and temperate oceans, usually at high-densities. In spite of its broad geographical distribution, the native range of this species is not yet elucidated S. plicata is native to the NW Pacific Ocean S. plicata are based on observations of man-made structures, except in Japan, where this species has been observed to grow in natural habitats S. plicata to thrive in these diverse environments and outcompete other benthic invertebrates. S. plicata can physiologically adapt to widely fluctuating environments, particularly to changes in temperature and salinity S. plicata's distribution range. Using a mitochondrial (COI) and a nuclear (ANT) marker, we attempted to infer the global phylogeography of S. plicata, understand its dispersion patterns, and assess the diversity and connectivity of introduced populations.To gain insight into the invasive potential of this species, we analyzed the genetic structure of seventeen populations covering most of Styela plicata were collected in 2009 and 2010 from seventeen localities . Samples were dissected COI) from 368 individuals. The primer set designed by Jarman et al. ANT) gene. Based on the resulting sequences, we also designed the specific primers ANTf_Splic (5′-TTG GCA GCT GAT ATT GGA AAA GG-3′) and ANTr_Splic (5′-CCA GAC TGC ATC ATC ATK CG-3′), using the software Primer 3 v.0.4.0. Total DNA was extracted using the REDExtract-N-Amp Tissue PCR Kit (Sigma-Aldrich). The universal primers LCO1490 and HCO2198 described in Folmer et al. ANT or 0.8 µL for COI, and 2 µL of template DNA. The PCR program for ANT consisted of an initial denaturing step at 94°C for 2 min, 30 amplification cycles , and a final extension at 72°C for 6 min, on a PCR System 9700 (Applied Biosystems). The PCR program for COI was as described above, except for the amplification cycles, which were done at 94°C for 45 seconds, 50°C for 45 seconds and 72°C for 50 seconds. PCR products were purified using MultiScreen® filter plates (Millipore), labelled using BigDye® Terminator v.3.1 (Applied Biosystems) and sequenced on an ABI 3730 Genetic Analyzer (Applied Biosystems) at the Scientific and Technical Services of the University of Barcelona (Spain). Other samples were directly sent for purification and sequencing to Macrogen Inc. . From the resulting sequences, we discarded low quality reads for ANT, hence the lower number of specimens sequenced for this marker.For both genes, amplifications were performed in a final volume of 20 µL using 10 µL of REDExtract-N-amp PCR reaction mix (Sigma-Aldrich), 1 µL of each primer (10 µM) for ® v.7.0.5.3 ANT sequences showed a deletion of 22 amino acids, thus heterozygotes had unequal lengths and had to be manually reconstructed by carefully analyzing both forward and reverse chromatograms. The allelic phase for ANT genotypic data was analyzed using fastPHASE 1.1 COI, and HQ916363 to HQ916423 for ANT).Sequences were edited and aligned using BioEditNh), gene diversity (Hd), and nucleotide diversity (π) were computed with DnaSP v.5 ANT data obtained with fastPHASE. The nearly unbiased estimation of allelic differentiation between populations was based on the adjusted Dest measure described by Jost Number of alleles  ANT network were solved using criteria derived from the coalescent theory COI network, only one loop was observed but it could not be resolved.The complete dataset was used to construct a median-joining network for each marker using Network v.4.5.1.6 Styela gibbsii as an outgroup (acc. number HQ916447 for COI and HQ916424 for ANT). The best-fit model of nucleotide substitution for each marker was selected using jModeltest v.0.1.1 COI, and the corrected version for small samples (AICc) for ANT. The positions corresponding to the indel detected for ANT were not included in the analysis , 6 of which corresponded to non-synonymous substitutions. The majority of haplotypes obtained (68%) corresponded to private haplotypes, most of which were found in the north-western Atlantic Ocean (Hd) were 0.497 (±0.266 SD) and 0.810 (±0.010 SD), respectively. Mean nucleotide diversity was 0.0055 (±0.005 SD), while total nucleotide diversity (π) was 0.0135 (±0.0006 SD). Variation in haplotype and nucleotide diversity between populations within basins was considerable. For instance, the populations of Knysna (KNY) and Port Elizabeth (PE) located in the Indian Ocean, had a haplotype diversity of 0.668 and 0.205 respectively. The California population (CAL) presented the highest haplotype and nucleotide diversity values  was used to assess the allelic differentiation between populations for each marker, showing high values of differentiation (mean Dest = 0.660). The COI data revealed high differentiation between many population-pairs, as 88 comparisons out of 136 resulted in significant differences after correction for multiple comparisons , and among populations within basins . However, no significant differences in genetic structure were detected between basins .The results of the hierarchical AMOVA showed higher within population variability (58.41%) than the one between populations , with a significant raggedness index . Sequences from both Group 1 and 2 are found in all basins and coexist in most populations; except for the absence of Group 2 in the Mediterranean. Judging by their high frequency, wide geographical distribution, and central position in the network, H_2 may be the ancestral haplotype of Group I. No clear result was obtained for group 2, as the most abundant haplotype (H_5) occupied a distal position within the group.  were 0.761 (±0.011 SD) and 0.820 (±0.012 SD), respectively. Mean nucleotide diversity was 0.0295 (±0.008 SD), while total nucleotide diversity (π) was 0.0321 (±0.0006 SD). Gene and nucleotide diversity did not differ between basins, except for the Mediterranean . Interestingly, 9 populations had an excess of heterozygotes (and negative Fis), and in 4 of them  these inbreeding coefficients were significant. Per basins, there was a heterozygote deficit in all populations except for the Pacific, and this deficit was most marked for the Mediterranean group of populations (0.282 obs vs.H 0.554 expH).For the erranean . The Souerranean . Port Elerranean . Eight pANT (mean Dest = 0.324) than for the mitochondrial COI. Dest values obtained for the ANT gene revealed fewer significant differences in pair-wise comparisons (45 out of 136). As before, the North Carolina population was significantly different from all the others , and among populations within basins . No significant differences in genetic structure were detected between basins . Regarding the neutrality test, the same trend of COI was observed for ANT, with most tests being non-significant. However, Fu's sF were significant for the Atlantic Ocean and the Port Elizabeth population , and only a small but significant 9.4% (p<0.001) of variability was found among these populations . When grpulation .COI data, the ANT network also showed a distinction in two groups of sequences separated by 4 mutational steps . This pattern explains the lower genetic diversity found in the Mediterranean basin compared with that of the other oceans. Group B seems to be a highly successful derived clade that has spread in most populations. Interestingly, in all localities in which there was an excess of heterozygotes (negative Fis), there was also a higher than expected proportion of individuals having one allele of each group . This is especially noteworthy in the Pacific populations, where we found twice the number of “mixed” genotypes than expected. The only exception was for North Carolina, which had a significant deficit of heterozygotes and less than expected genotypes with an allele from each group.The private allele H_41 from North Carolina appeared genetically distinct from all the others in both the network and the BI analyses . This saCOI and ANT. In order to avoid cluttering of populations, a first DAPC was performed with 3 groups: the North Carolina population , the Sakushima population  and the remaining populations. The PCA components retained explained 98.6% of the total variance observed. The scatterplot of the first two components of the DA  and ANT (group A and B) is that they have arisen concomitantly in a past fragmentation event within the native area of the species. We cannot, however, exclude an independent origin of these genetic splits. At present, the distribution of the groups obtained with the two markers is totally unrelated. Sequences of the Group A for ANT were found in ascidians having mitochondrial sequences of both lineages (Groups 1 and 2), and in direct proportion to their relative abundances. The same trend was observed for individuals having sequences of Group B for ANT , we found sequences of the two groups of COI and ANT in the same populations and, for ANT, even in the same individual.The most parsimonious explanation for the presence of two groups of sequences for  for ANT . If the COI haplotypes for Styela plicata, 8 belonging to our Group 1 and one to our Group 2. Based on this divergent haplotype, these authors suggested that there could be a cryptic species within what is known as Styela plicata. Our results did not lend support to this hypothesis, as the nuclear marker showed a distribution unrelated to these two groups of mitochondrial sequences. Furthermore, when comparing our mitochondrial sequences with other species of the genus, the resulting genetic divergence was much higher than that found between our two COI groups . The divergent sequences of S. plicata reported from Australia (Lake Conjola) by Pérez-Portela et al. COI and FH897323 for 18S rRNA) were likely the result of sample mislabelling . We sequenced 4 further specimens from the same locality and verified that they all had typical S. plicata COI sequences .Barros et al. Styela plicata is not known with certainty, the prevailing hypothesis is that it comes from the NW Pacific area S. plicata would have then dispersed to other tropical and warm-water regions by ship fouling, likely since the early transoceanic navigation times S. plicata is well mixed among basins, with most genetic variability found within populations. Moreover, high genetic variability and the putatively most ancient alleles have not only been found in the NW Pacific populations  but also in other oceanic basins  were genetically similar, while closer populations such as Knysna and Port Elizabeth (South Africa) were significantly divergent. The stochasticity of main transport events through international ship traffic could determine the observed patterns among basins. However, our sampling design was inappropriate to assess the degree of connectivity among closely located populations  and ANT (Group A and B). For COI, haplotypes from Group 1 were considerably more frequent and diverse than haplotypes from Group 2. It is possible that these groups stand for differential adaptive capabilities of the individuals to stressful environments. This adaptive capability does not need to be directly linked to our studied gene , but to other mitochondrial genes. Differential adaptation to environmental factors  of mitochondrial sequences within one species is not a rare phenomenon, and has been described in many species Besides recurrent introductions through ship transport, population differentiation could also be due to selection. Here, we found uneven abundances for each major group obtained for ANT gene, selection may be favouring heterozygotes that have an allele of each group (A and B). In fact, the excess of heterozygotes found in most populations is due to the number of individuals with an allele each of A and B. Accordingly, the number of individuals with both alleles from the same group (A or B) was lower than expected. Homozygotes for the basal Group A occurred ca. 5 times less than expected based on allele frequencies. Thus, it is possible that populations that originally had only one group of ANT sequences were seeded with arriving individuals featuring the other group. The mingling of both groups may have favoured the heterozygotes with an allele from each group, and if this combination had an adaptive value, enhanced the fitness of those individuals. As for the COI lineages, this new adaptive capability to the environment is not necessarily linked to the ANT gene itself. Admixture between lineages can foster the emergence of novel genetic combinations with different physiological attributes and invasive characteristics For the S. plicata's biological cycle, interactions with other marine species, and local-scale genetic structure are necessary to understand the biology, ecology and post-border dispersal of this species and prevent ecosystem alterations.Early invasions should not be considered “naturalized,” rather, their impacts, potential for further spread, and degree of integration in local processes and interactions should be assessed. A throughout knowledge of introduced species is required to understand and interpret the present-day structure, function, and conservation of marine communities Table S1COI gene. Numbers in bold are private haplotypes.Haplotype frequencies observed for the (DOC)Click here for additional data file.Table S2ANT gene. Sequences with a 22 amino acid deletion are indicated with an asterisk.Allele frequencies observed for the (DOC)Click here for additional data file.Table S3ANT allelic phase and COI haplotypes for each individual analyzed.(DOC)Click here for additional data file.


Blissus insularis Barber (Heteroptera: Blissidae), is the most destructive insect pest of St. Augustine grass, Stenotaphrum secundatum Waltz (Kuntze), in the southern United States. The present study is focused on assessing genetic variability in five populations of B. insularis collected from Texas and Florida where St. Augustine grass is widely grown. The amplified fragment length polymorphism technique was used to DNA fingerprint individuals from each population  using five primer combinations (EcoRI/MSeI). Analysis of molecular variance results show no evidence to support significant genetic variability among Texas and Florida populations of B. insularis. Nearly all genetic variation was found to reside within populations (95%), with only approximately 3% residing among populations between regions. Low GST values obtained from POPGENE and low FST values obtained from the analysis of molecular variance both support the conclusion for high levels of gene flow resulting from interbreeding and/or migratory events among the populations. A Mantel test of Euclidean squared distances showed no correlation between the genetic distance and geographic distance matrices of tested populations of B. insularis. The results of the present study suggests that gene flow is occurring among populations of B. insularis and, therefore, breeders need to be aware that this resistance will most likely not remain localized, and it has the potential to spread as a result of migratory events.Southern chinch bug,  Blissus), B. insularis, are common pests of agronomic crops and turfgrasses. The four most economically important species of chinch bugs prevalent in the United States are the southern chinch bug, B. insularis Barber; the common chinch bugs, B. leucopterus leucopterus; the hairy chinch bug, B. l. hirtus; and the western chinch bug, B. occiduus. Although germplasms resistant to individual species of chinch bugs have been identified  marker system has been successfully used in several population genetics studies of insects  of variability is present within species andapproximately 37% variability is present between species. To our knowledge, the genetic structure of populations within and among species of chinch bugs has yet to be reported.All four economically important species of chinch bugs have been reported to have extensive and overlapping host range and geographic distributions , throughout the southern United States was investigated. B. insularis has also been reported on other warm-season turfgrasses such as bermuda grass, Cynadon dactylon; bahia grass, Paspalum notatum; centipede grass, Eremochloa ophiuroides; and zoysia grass, Zoysia spp.  and low oviposition rates  that had overcome the resistance expressed in Floratam  are susceptible to populations of B. insularis collected from south Texas with <20% of the chinch bugs killed by these cultivars within a 7-day feeding period in laboratory studies . Based on these herbivory studies, there appears to be differences among populations of B. insularis.In the present study, the level of genetic variability in sia spp. . ‘Floratsia spp.  primarilon rates . Howeverreakdown . Since 1ectively , and proFloratam . PrelimiB. insularis using AFLP marker system. AFLP was chosen for this study because it does not require any prior knowledge of the genome (The objective of the present study was to assess the genetic variability between different populations of e genome  and genee genome .B. insularis were vacuum collected using a modified Echo leaf vacuum (www.echo-usa.com) from S. secundatum lawns growing in three geographically different locations in Texas and two locations in Florida (Populations of  Florida . In the  Florida . QuantifThe AFLP procedure was performed in three steps: 1) DNA template preparation, 2) DNA template pre-amplification, and 3) AFLP selective amplification.DNA template preparation. A total of 7 µl of genomic DNA (1.0 µg) was incubated with EcoRI and MseI restriction endonucleases for 2.5 h at 37° C followed by 15 min at 70° C in a total volume of 12.5 µl of restriction digestion mixture per reaction, which contained 0.0625 µl of EcoRI , 0.125 µl of MseI (50000 U/ml), 1.25 µl of 10× One-phor-all, 0.125 µl of BSA (10 mg/mL), and 3.938 µl of autoclaved nanopure water to make up the final volume. A total of 5 µl of adapter ligation mixture; consisting of 0.5 µl of 10× T4 DNA ligase buffer, 0.15 µl of T4 DNA ligase , 0.5 µl of EcoRI adapter mix (5 µM), 0.5 µl of MseI adapter mix (50 µM) (www.neb.com). Adaptors were synthesized by Integrated DNA Technologies (www.idtdna.com) (50 µM) , and 3.3Pre-amplification of DNA template. A 22 µl master mix containing 2.5 µl 10× Taq buffer, 0.1 µl of Taq polymerase (5 U/µl), 1.5 µl of MgCl2 (25 mM), 0.3 µl of dNTP mix (10 mM), 0.5 µl of EcoRI-C (10 µM), 0.5 µl of MseI—A (10 µM), and 16.6 µl of autoclaved nanopure water was added to 3 µl of diluted ligation product obtained from the previous step. Each reaction tube was then placed in a thermal cycler and amplified using 30 PCR cycles of 72° C for 2 min, 94° C for 30 s, 56° C for 30 s, and 72° C for 2 min followed by 60° C for 10 min. The pre-selective PCR product was diluted with 167 µl of TE buffer and stored at -20° C or immediately used in selective PCR. The oligonucleotide primers used in the pre-amplification of the DNA template are complementary to the adapter/restriction site with MseI primer containing one selective nucleotide and EcoRI primer containing no selective nucleotide (www.appliedbiosystems.com). Primers were synthesized by Integrated DNA Technologies.cleotide . All PCRAFLP selective amplification. A total of 7 µl of PCR master mix was made consisting of 1.25 µl of 10× Taq buffer, 0.1 µl of Taq polymerase (5 U/ul), 1 µl of MgCl2 (25 mM), 0.15 µl of dNTP mix (10 mM), 1 µl of BSA (10 mg/ml), and 3.5 µl of autoclaved nanopure water per reaction. A selective primer master mix was made for each of the five primer combination (MseI (100 µM) selective primer and 0.5 µl of 6FAM labeled EcoRI (100 µM) selective primer. The PCR master mix and 3 µl of the primer master mix were then mixed with 2.5 µl of pre-selective PCR products in PCR tubes. The tubes were placed in a thermal cycler and amplified using following parameters: 94° C for 2 min, 1 cycle of 94° C for 30 s, 65° C for 30 s , 72° C for 2 min; then 23 cycles of 94° C for 30 s, 56° C for 30 s, and 72° C for 2 min, and finally 72° C for 10 min before holding at 4° C. After selective PCR amplification was complete, the selective PCR products were stored at - 20° C or were immediately prepared for AFLP analysis. In preparation of AFLP analysis, 0.5 µl of GeneScan - 500 ROX Size Standard (ABI), 8.5 µl of Hi-Di Formamide (Applied Biosystems), and 1 µl of selective PCR product were mixed and placed in 96-well plates. The plates were analyzed using the ABI3130 capillary system.bination  used conA total of 501 AFLP markers were scored for each individual bug. For each individual bug, AFLP markers were scored as Is when present and 0s when absent. Data was scored using Genographer version 2.1 using file type — Gene Mapper Filter and Sizing Algorithm — Cubic Spline Interpolator. Bands with a peak height 300 or greater and 70 bp or larger were scored. All band sizes were rounded down to the nearest whole basepair and placed in a basepair length bin. Bins with multiple bands were considered stutters and only counted once. All bins with bands were converted to 1 and all empty bins were converted to 0.Gene diversity and gene flow. The resulting data was analyzed using POPGENE version 1.32 (T) based on Nei (ST), and gene flow estimates (Nm). Assuming Hardy-Weinberg equilibrium, the analyses were conducted at three levels: individuals, regions, and whole population using dominant marker data. HT values were estimated for each individual population and GST values were estimated for populations within region and all five populations. GST is expressed as HT — HS/HT where HT is gene diversity of the total population and Hs is gene diversity of the single population. Gene flow was estimated from GST expressed as Nm = 0.5 (1- GST/ GST)  .Analysis of molecular variance. Analysis of molecular variance (AMOVA) (ST). (AMOVA)  was cond (AMOVA)  to assesPhylogenetic analysis. A phylogenetic analysis was conducted using PAUP 4.0 Beta version Principle components analysis was conducted using NTSYSpc version 2.1  values calculated from all sub-populations, was high and ranged from 0.1898 for the Gainesville, FL population to 0.2574 for the Highland Park, TX population with an average gene diversity of 0.21844  indicate that a majority of the genetic variability resides within a given population. In the present study, GST value among all sampled populations was low (0.0261) indicating a high degree of genetic variability within population (97.4%) and low variation among populations (2.61%)  . These rm where N is the number of individuals in a population and M is the proportion of individuals in the population as a result of immigration. Nm values >1 indicate a high level of gene flow and that the effects of gene flow on population differentiation is greater than the effect of random genetic drift , but that the amounts of genetic variation among populations within groups and within populations were significant at P = 0.00293 and 0.0000, respectively (P = 0.7682) indicating that there was no genetic isolation in regions of southern chinch bug populations tested in this study. Genetic divergence (FST) values less than 0.2 indicates high gene flow and in the present study FST for five subpopulations was 0.05080 indicating low differentiation among populations  and the difference in genetic variation among populations within groups and within populations were both significant at P = 0.03226 and 0.0000, respectively. Without the inclusion of the Longview, TX population, the AMOVA showed that 93.4% of the variation in the data set was from genotypic variation within populations, 2.4% of the variation was attributed to differences among populations within regions, while the remaining 4.2% was due to the variation among regions. Therefore, an AMOVA either with or without the inclusion of the Longview, TX population gave similar results, in that, there was no significant genetic variability present among regions, and that the majority of the geneticAFLP variability measured was found to be present within populations.As expected, a phylogenetic neighbor-joining tree based on Euclidian-squared, pairwise genetic distance of 46 samples of nsularis  shows nonsularis  appearednsularis  was grapS. secundatum to B. insularis do not appear to be related to specific population differences in B. insularis, but rather it is more likely that such resistance results from the expression and regulation of specific genes from individual bugs. The present study also suggests that gene flow is occurring among populations of B. insularis and, therefore, breeders need to be aware that this resistance will most likely not remain localized and it has the potential to spread as a result of migratory events. In the future, a more detailed investigation might be performed by increasing the number of populations of B. insularis from the geographic distribution of S. secundatum; especially - a few more populations collected and analyzed from the Longview, TX region might be informative and useful in better understanding the population genetic structure of B. insularis.Based on the results of the present study the resistance mechanisms of