Using species distribution models and information on genetic structure and within-population variance observed in a series of common garden trials, we reconstructed a historical biogeography of trembling aspen in North America. We used an ensemble classifier modelling approach (RandomForest) to reconstruct palaeoclimatic habitat for the periods 21,000, 14,000, 11,000 and 6,000 years before present. Genetic structure and diversity in quantitative traits was evaluated in common garden trials with 43 aspen collections ranging from Minnesota to northern British Columbia. Our main goals were to examine potential recolonisation routes for aspen from southwestern, eastern and Beringian glacial refugia. We further examined if any refugium had stable habitat conditions where aspen clones may have survived multiple glaciations. Our palaeoclimatic habitat reconstructions indicate that aspen may have recolonised boreal Canada and Alaska from refugia in the eastern United States, with separate southwestern refugia for the Rocky Mountain regions. This is further supported by a southeast to northwest gradient of decreasing genetic variance in quantitative traits, a likely result of repeated founder effects. Stable habitat where aspen clones may have survived multiple glaciations was predicted in Mexico and the eastern United States, but not in the west where some of the largest aspen clones have been documented. Populus tremuloides Michx.) is the most frequent and genetically diverse forest tree in North America, occupying many ecological site types from Mexico to Alaska in the west, and across Canada and the United States to the Atlantic ocean in the east3. Aspen is capable of colonizing newly available habitat, yet differs from typical pioneer species in that it can persist in colonised environments for thousands of years through clonal reproduction. Due to its life history, large range, and wide ecological amplitude, aspen is an interesting organism to address questions concerning ecological genetics, physiology, and biogeography.Trembling aspen  covers 43 ha and comprises 47,000 stems with an estimated biomass of 6,000 t8. In the eastern United States, the average clone size has been estimated to be approximately 0.04 ha, with exceptional individuals reaching 14 ha10. In central Canada, average clone sizes were reported around 0.08 ha, with the largest clones reaching 1.5 ha11.Aspen can colonise marginal habitat and survive disturbance events by root suckering21. The highest levels of genetic diversity with an expected heterozygosity (He) of 0.42 were reported for Alberta by12, but other studies in the region showed more typical levels of genetic diversity for the species with an He of 0.2922. Electrophoretic surveys of aspen in eastern populations (e.g. Minnesota and Ontario) were lower with He rates of 0.22 and 0.25, respectively16.Several genetic studies have also shown that trembling aspen shows exceptionally high levels of genetic diversity, but little among-population genetic differentiation in neutral genetic markers, such as isozymes, microsatellites or other molecular markerset al.20 identified a pronounced geographic differentiation into a genetically more diverse northern cluster  and a slightly less diverse southwestern cluster (western US and Mexico) while showing no evidence of higher genetic diversity in Alberta. However, due to different rates and mechanisms of mutations in isozyme versus microsatellite marker systems the outlined results may not be contradictory23.In a recent range-wide study of genetic structure and diversity based on microsatellite markers, Callahan, et al.24 showed evidence for strong suboptimality in adaptive traits, and suboptimality in quantitative traits could potentially be explained by considering aspen’s clonal life history, with populations being adapted to fossil climate conditions25.A different approach to investigate genetic structure and diversity is to assess genetic differences of quantitative traits in common garden experiments. Such data usually does not provide insight into the biogeographic history of a species, because the traits evolve too quickly in response to current environments. In the case of aspen, however, where clones may have persisted for thousands of years, genetic variance in quantitative traits or adaptational lag may provide additional clues regarding the migration history of the species. In a reciprocal transplant experiment, Schreiber, 5. Although precise dating of aspen clones remains an elusive task, recent studies have drawn some boundaries. Ally, et al.26 found that the upper boundary for the age of aspen clones at two study sites in British Columbia is approximately 4,000 and 10,000 years, which corresponds well with the timing of glacial retreat at those two sites. Relating clone size with age, however, proved not possible. Speculations about very large clones that may have persisted through repeated glacial cycles are also not supported by Mock, et al.17, who studied the largest known clone “Pando” and concluded that it has a low frequency of somatic mutations at microsatellite loci and is not likely to be more than several thousand years old.In fact, it has been speculated that aspen clones may be millions of years old and have survived dozens or hundreds of glacial cycles27. Although more typically used as a risk assessment tool for future climate change e.g. ref. Another valuable approach to address questions concerning biogeography and species migration are species distribution models. These models use observed species range data in combination with environmental predictors  to generate statistical relationships, which can be used to project probabilities of species presence from new environmental dataet al.20’s more diverse northern cluster and a less diverse southwestern cluster suggests two refugia for the species south of the ice sheet, but others have proposed that boreal species may also had refugia in ice-free Beringia, allowing for southward post-glacial recolonisation routes35. Secondly, we investigate whether habitat reconstructions support the possibility of very old clones that may have persisted through multiple glaciations by climate conditions staying within their environmental tolerances. Last, we contribute an analysis of genetic diversity and adaptational lag in quantitative traits based on field trials. Since aspen clones may have persisted for thousands of years in many current locations, their adaptational lag would provide additional insight as to what climate conditions they have experienced in the past and what migration paths would be consistent with observed lags and gradients in genetic diversity.In this study, we contribute reconstructions of glacial refugia and post-glacial migration histories for aspen by means of species distribution models. Our primary goal is to use habitat reconstructions to augment inferences of putative glacial refugia that are based on geographic patterns in neutral genetic markers. Callahan Because aspen clones may have persisted for thousands of years, any adaptational lag relative to current environments may provide additional clues as to what climate conditions they have experienced in the past and what migration direction would be consistent with the observed lag.To concisely summarize multi-trait measurements at five test sites as well as climate conditions at seed source locations Fig. , we use cf. Fig. Regarding genetic structure of populations Fig. , only twcf. Fig. Residual variance components of growth and adaptive traits by region of origin reveal the Alberta Foothills and Minnesota as the most genetically diverse regions in quantitative traits Table . If we i39. The reason may be that pollen identification for poplar is difficult beyond the genus level and that poplar pollen is also fragile and prone to disintegration, which may also lead to false negatives in sediment records40.While an out-of-bag validation indicated excellent model fit to modern plot data with an AUC of 0.91, a model validation against pollen and fossil data yielded an AUC of only 0.67. Although truly independent model validation statistics are always much lower than out-of-bag validations e.g. refs Our historical projections of aspen habitat for 6,000, 11,000, 14,000 and 21,000 years before present (BP) show three potential glacial refugia in which aspen may have found suitable habitat during the last glacial maximum Fig. . The preFigure Palaeoclimatic habitat reconstructions suggest three potential glacial refugia for trembling aspen from which recolonisation may have occurred. The eastern United States represents the largest refugium with the highest probabilities of presence, followed by the low elevation areas of the southwestern United States, and Alaska. Although the modelled Alaska refugium was very small with a low-probability of presence, the possibility of aspen recolonisation from the north should not be excluded based on habitat reconstructions alone. This leaves three conceivable recolonisation scenarios for aspen: (Scenario 1) recolonisation of the boreal north almost exclusively from the southeast to northwest up into Alaska; (Scenario 2) recolonisation predominantly from the east but with contributions from either the southwestern or Alaskan refugia, and (Scenario 3) simultaneous recolonisation from all three glacial refugia with a contact zone in Alberta, Canada, potentially explaining high levels of genetic diversity documented by one study for this region.42, and many interior plant species show genetic clusters that can be attributed to a further sub-structure of southwestern refugia. For example, Godbout et al.43 propose two well separated refugia in the Columbia River basin and the eastern Rocky Mountains to explain genetic structure within the interior variety of Pinus contorta. Northeastern refugia, just south of the ice sheet have also been well documented for several boreal tree species reviewed by42, implying either exclusive northwestern recolonisation paths (e.g. Pinus banksiana), or recolonisation from both the southwest and east (e.g. Picea mariana). In addition, there is evidence from both genetic data and fossil pollen records that several boreal species may also have found refuge in ice-free Beringia, allowing for southward post-glacial recolonisation routes35. For aspen, two main genetic clusters in today’s populations have been identified: a northern group comprised of the Alaskan, Canadian and eastern United States populations, and a second group of southern Rocky Mountain populations presumably originating from a separate southwestern refugium20.Southwestern coastal and interior refugia are well documented for many western North American species e.g. reviewed byet al.20. In fact, they also confirm that an observed outlier in the southern cluster (a Yellowstone population), which according to the microsatellite data grouped into the northern cluster could have plausibly been recolonised from the east. Although westward extending habitat from eastern refugia at 14,000 years BP did not reach all the way to the Yellowstone region, it does extend well into Montana  is further supported by our finding of a southeast to northwest gradient of decreasing genetic variance in quantitative traits  seems therefore unlikely based on molecular genetic information and habitat reconstructions. Consequently, while a Beringian refugium for aspen should not be excluded, it does not appear to be the origin of today’s boreal aspen populations.We should note that a southwards expansion from an isolated and genetically depauperate refugial population in Alaska could also explain the observed high degree of suboptimality in the British Columbia populations. However, data reported by ref. 12. While we did find high levels of genetic diversity in quantitative traits in the Alberta Foothills region  with populations from three refugia making contact in Alberta could potentially explain relatively high levels of genetic diversity observed in one study in this region5. On the other hand, molecular studies suggest that Pando may in fact be of relatively young age17.The apparent continuity of suitable habitat conditions for aspen populations in montane areas of Wyoming, Utah, Colorado, Arizona and New Mexico Fig.  raises tOur climate habitat reconstructions support the view that ancient aspen clones are unlikely to be found in the southwestern Rocky Mountains. While suitable climate habitat for aspen was available in the general area at all times since the last glaciation, our model hindcasts suggest that the difference between today’s climate conditions and those of the last glacial maximum were too large to stay within the climatic tolerances of aspen at any single location . This is illustrated in Fig. 46. In our reconstructions shown in Fig. It should be noted that species distribution models are generally not considered reliable enough to reconstruct species distributions at small scales for various reasons that are discussed in depth elsewhere e.g.,Our inferences, however, do not rely on precise spatial reconstructions of past aspen distributions. Rather, Figs et al.47, available for anonymous download at http://tinyurl.com/ClimateNA. We use a 1961–1990 climate normal baseline dataset generated with the Parameter-elevation Regressions on Independent Slopes Model (PRISM) for monthly average minimum temperature, monthly average maximum temperature and monthly precipitation48. From 36 monthly variables, six biologically relevant climate variables were derived that account for most of the variance in climate data while avoiding multicollinearity: the number of growing degree days above 5 °C, mean maximum temperature of the warmest month, temperature difference between mean January and mean July temperatures, mean annual precipitation, April to September growing season precipitation, and November to February winter precipitation. The procedure of selecting these climate variables is described in more detail in Worrall, et al.49, Supplement 1. The algorithms to estimate biologically relevant variables from monthly temperature and precipitation surfaces are explained in detail by Rehfeldt50. To represent palaeoclimatic conditions, we overlaid the 1961–1990 baseline climate with temperature and precipitation anomalies for 6,000, 11,000, 14,000 and 21,000 years before present, generated by the Community Climate Model (CCM1) developed by the National Center for Atmospheric Research (NCAR)51. Subsequently the same derived variables were generated as above.Climate data were generated according to Hamann, 49. This model employs a regression tree ensemble classifier to relate climate variables to aspen census data, implemented by the randomForest package52 for the R programming environment53. Model hindcasts were validated, using the area under the curve (AUC) of the receiver operating characteristic54, against 9,568 records of combined fossil pollen, macrofossil, and pack rat midden (Neotoma species) data, drawn from the Neotoma Palaeoecology Database (www.neotomadb.com) for the time periods considered. Further details on fossil data sources and validation methods can be found in Roberts & Hamann38. To identify areas where aspen clones may have found continuously suitable habitat throughout glacial cycles, we multiplied projected aspen probability of presence layers for the 1961–1990 baseline period with projected aspen probability of presence for 21,000 years BP.Past aspen habitat was reconstructed using a species distribution model for aspen based on more than 600,000 presence/absence data points from forest inventory plots, ecology plots and herbarium accessions throughout North America24. The measured traits were tree height, timing of bud break and timing of leaf senescence. Tree height was measured for 6,450 trees after nine growing seasons in the field in autumn of 2006 for all five test sites. Phenological measurements, i.e. timing of bud break and timing of leaf senescence were taken on 1,290 trees at the central Alberta test site.In this paper, we also reanalyze data from a large-scale common garden trial in a different context. We use a standard statistical design widely used in provenance testing, implementing a randomised complete block (RCB) design with 43 provenances planted in 5-tree row plots, in 6 blocks, at each of 5 sites. Provenances are open-pollinated single-tree seed collections from six ecological regions in the northern portion of the species range Fig. ; for furFactoMineR package55 for the R programming environment53. For the genetic ordination, traits summarised into principal components were height at five sites plus bud break and leaf abscission measured at one site (7 variables). For the climatic ordination, nine variables were used to describe the multivariate climate space more completely  grown in the j-th test site (S), in the k-th block (B) within a test site. A genotype × environment effect is given by the interaction between provenance and test site (P × S) as well as provenance and block within test site (P × B(S)). The overall mean is indicating by μ, and el(ijk) represents the residual environmental error plus the within-family variation in each plot. The model was run separately for each region and each trait for a total of 18 model implementations. Bud break and leaf senescence were only measured at one test site , and in this case the test site effect does not apply and the block within site effect becomes a simple block effect. Standard errors of variance components were generated with the COVTEST option of PROC MIXED56.The common garden trial was primarily meant as a provenance experiment to investigate genetic differentiation in adaptive traits among populations. However, it can also be used to estimate regional within-population phenotypic variation by calculating residual variance components. Since all provenances experience the same environmental conditions at a given test site, differences in the residual phenotypic variance components can be attributed to different levels of genetic variance (including dominance and epistatic genetic effects that we cannot quantify). We therefore refer to differences in the residual variance components as differences in within-population genetic variation hereafter. Strictly speaking, they are differences in within-population phenotypic variation with the environmental variance component held constant . To estimate variance components, we use a random-term linear model implemented with PROC MIXED of the SAS statistical software package


Stemphylium lycopersici is an important pathogen causing leaf spot of tomatoes worldwide. Although much information is available about the pathogen, little is known about dynamics of S. lycopersici in tomato fields. Seventy-nine symptomatic leaf samples were collected from two tomato cultivars grown in a farm . Fungal species associated with the disease were isolated on potato dextrose agar. Seventy-nine isolates were obtained and identified as S. lycopersici based on sequence analysis of combined dataset of the internal transcribed spacer and glyceraldehyde-3-phosphate dehydrogenase regions. The 79 isolates were subjected to amplified fragment length polymorphism analysis using three primer combinations. The Stemphylium lycopersici population from the two cultivars was found to have a very low level of genetic diversity (H = 0.0948). Cluster analysis showed intermixing of isolates from the two cultivars. In addition, analysis of molecular variance showed the presence of a very low level of genetic differentiation between populations obtained from the two cultivars (Fst = 0.0206). These findings indicate the presence of a high rate of gene flow between the two populations and may suggest that the two populations originated from the same inoculum source. The implications of these findings on the management of Stemphylium-induced leaf spot of tomatoes are discussed. Tomato is among the top vegetable crops in production in different parts of the world FAO . In OmanStemphylium is an important and destructive pathogen causing leaf spot diseases in several agricultural crops  regions could help resolve Stemphylium to the species level  and ISSR (inter simple sequence repeat) markers, respectively. However, no information is available concerning the level of genetic diversity of S. lycopersici in a single field or from other locations of the world. This makes our knowledge limited about the level of diversity as well as dynamics and the level of gene flow of the pathogen within the same field.Population genetic analysis of S. lycopersici in a single field. Specific objectives were: (1) to identify Stemphylium species associated with leaf spot of tomato in a field in Oman using sequence analysis of combined dataset of the ITS and gpd regions, and (2) estimate the levels of genetic diversity and genetic differentiation in S. lycopersici populations obtained from two tomato cultivars. Knowledge into these areas will help characterize the potential level of S. lycopersici spread within tomato fields and provide a basis for establishing effective management strategies.The main purpose of this study was to analyze the population genetic structure of In January 2014, a total of 79 leaf samples developing leaf spot symptoms were collected from two tomato cultivars: Miral and an Inbred line. The cultivars were grown in a completely randomized block design in farm that is located in Barka city, approx. 50 km to the north of capital area of Oman. The number of plants grown in the field was 600 and 420 for Miral and Inbred line, respectively. No pesticides were applied on the two cultivars. The spots were characterized by grey to dark brown and black color, surrounded with yellow hallo. Miral cultivar had a high incidence of the disease, affecting 87 % of the tomato plants grown in the field. However, the Inbred line had a lower incidence level, with 31 % of the plants developing leaf spot symptoms. Out of the 79 collected samples, 55 were from the severely affected cultivar “Miral”, while 24 were from the “Inbred line” which was less affected.−1 rifampicin and 200 mg L−1 ampicillin. The plates were incubated at 25 °C with 12 h photoperiod for 10 days. Colonies of Stemphylium were identified to the genus level based on the morphology of spores (Ellis and Gibson Stemphylium isolates were obtained (one per leaf sample) of which 55 from Miral and 24 from the inbred line.Isolations were established by cutting the symptomatic leaves into small pieces (approx. 5–7 mm). The leaf pieces were disinfected using 1 % sodium hypochlorite for 2–3 min. After that, the pieces were rinsed with sterile distilled water and then blotted dry on sterile filter paper. Isolation of fungi was established on 2.5 % potato dextrose agar (PDA) amended with 10 mg LStemphylium isolates was extracted using a modified protocol of Lee and Taylor  was used as an out-group. A neighbor-joining tree was constructed based on the matrix of pairwise distances obtained using the Kimura 2-parameter evolutionary model , 0.65 µl MseI+C (5′-GATGAGTCCTGAGTAAC-3′), 3.70 µl R/L mix and 20 µl Milli-Q water. The cycling profile was as described by Al-Sadi et al. . Genotypic diversity within each population was determined as described by Stoddart and Taylor  followedgpd regions for the 79 isolates  produced fragments of ca. 484 and 504 bp, respectively. The final sequence alignment of the combined data sets comprising 103 taxa had 1038 characters, of which 785 characters were constant, 223 were variable, and 94 characters were parsimony informative. The 79 isolates clustered with reference isolates of S. lycopersici with a high bootstrap support  and KU556787 (gpd) for isolate SQU pop01 and KU556788 (ITS) and KU556789 (gpd) for isolate SQU pop06.PCR amplification of the ITS and The three primer combinations E+AGA/M+CAA, E+AGA/M+CAT and E+AGA/M+CTG generated 11, 40 and 44 alleles, of which 10, 39 and 44 alleles were polymorphic, respectively. Nei’s gene diversity  was founPopulation genetic analysis of the population from ‘Miral’ cultivar and the ‘inbred line’ cultivar showed that both populations have a very low level of genetic diversity . The populations from ‘Miral’ cultivar the ‘inbred line’ cultivar produced 55 and 24 genotypes, respectively. The total number of polymorphic alleles was 93 within all isolates (Table st = 0.0206). The rate of gene flow of isolates between the two cultivars was high (Nm = 23.8). These data were consistent with UPGMA analysis, which grouped 79 S. lycopersici isolates obtained from the two tomato cultivars into subclusters of 79 AFLP genotypes  and S. xanthosomatis (EGS 17-137) by a strong bootstrap value (100 %). However, Câmara et al. Stemphylia et al.  suggesteTomatoes have been grown in the field for at least the last 10 years. Leaf spot symptoms have been observed in the field in the past, but at low levels. However, the incidence was very high during this season. Although this could be related to growing the susceptible cultivar “Miral” for the first time in the farm, this hypothesis needs to be investigated in future studies by doing pathogenicity tests on this cultivar and the other cultivars grown in the farm.S. lycopersici from the two tomato cultivars. This could be related to several factors. Firstly, the population of S. lycopersici in the farm could have originated from a single source in the past. Fungal species originating from a single source have been reported to have a relatively low level of genetic diversity (Al-Sa’di et al. S. lycopersici at low levels (McDermott and McDonald S. lycopersici in the field is a hypothesis which deserves investigation in future studies.A low level of genetic diversity was observed within populations of S. lycopersici isolates and the cultivars from which they were obtained. These findings are in agreement with the results of Mehta (S. solani isolates and cotton and tomato cultivars from which the isolates were collected. They are also in agreement with findings which showed the lack of relationship between clustering of Ceratocystis radicicola isolates and the cultivars from which they were obtained (Al-Sadi No relationship was found between clustering of of Mehta , who did Al-Sadi .S. lycopersici populations from tomato cultivars is consistent with the nature of this pathogen which is airborne and can be transmitted by several means including wind and rain splash (Rossi et al. S. lycopersici within the tomato field represents a challenge for the management of the pathogen. Management strategies aimed at eliminating the spread of the pathogen may not be very effective during windy or rainy seasons. However, continuous inspection of primary inoculum infestations in fields and removal of primary inoculum may help reduce the chance of disease establishment. The use of resistant cultivars is an important strategy. Resistance genes have been incorporated in tomatoes against several pathogens, including S. lycopersici (Parlevliet The low level of genetic differentiation and the presence of high gene flow among the two gpd regions helped identify 79 S. lycopersici isolates to the species level. Population genetic analysis indicated frequent movement of S. lycopersici within fields. This may result in high disease epidemics under the most favorable environmental conditions. Since temperature, wind speed, tomato cultivars and other factors may affect the population structure of fungi (McDermott and McDonald S. lycopersici under different growing conditions. In addition, studies are required to address pathogen specialization on different cultivars.The combined dataset of the ITS and


Quercus aliena Blume, Quercus dentata Thunb. ex Murray, and Quercus variabilis Blume) in their northern distribution in China using 17 bi-parentally inherited nSSRs markers and five maternally inherited chloroplast DNA (cpDNA) fragments. Both the cpDNA and the nSSRs show a high level of genetic differentiation between different oak sections. The chloroplast haplotypes are clustered into two lineages. Clear species boundaries are detected between Q. variabilis and either Q. aliena or Q. dentata. The sharing of chloroplast haplotype H1 between Q. aliena and Q. dentata suggests very recent speciation and incomplete lineage sorting or introgression of H1 from one species to another. The nSSRs data indicate a complete fixation of variation within sites for all three oak species, and that extensive gene flow occurs within species whereas only limited gene flow is detected between Q. aliena and Q. dentata and nearly no gene flow can be detected between Q. aliena and Q. variabilis and between Q. dentata and Q. variabilis. Prezygotic isolation may have contributed to the species boundaries of these three sympatric oak species.Oaks are important timber trees with wide distributions in China, but few genetic studies have been conducted on a fine scale. In this study, we seek to investigate the genetic diversity and differentiation of three sympatric oak species ( Transfer of genetic material across closely related species is common, especially in coexisting taxa  Ohashi, Quercus dentata Thunb. ex Murray, and Quercus aliena Blume in Japan, Korea, China, and Russia  in Japan  which are bi-parentally inherited and transfer extensive gene flow through both pollen and seeds , and gene flow among them in their northern distribution in China. All three oak species are widely distributed across China , with densely grayish brown stellate tomentose on the abaxial surface and usually are very big . Quercus variabilis belongs to section Cerris . Shangfang Mountain is a branch of the Taihang Mountains with fold-thrust geological structures. It has a mean altitude of 400 m and a summit of over 880 m. The mountain slopes range from 20 to 70°, forming very steep terrain with dozens of valleys. Within this region, hundreds of ancient Taoist and Buddhist temples scatter throughout the forest, with the oldest one being dated back to the Eastern Wei period (535 AD). The forest here is a well-preserved secondary forest in north China covering an area of approximately 340 hectares. Tree species of Shangfang Mountain mainly belong to Quercus, Pinus, and Platycladus with Quercus including mostly Q. aliena, Q. dentata, and Q. variabilis and a limited number of <20 individuals of Q. mongolica.Three sympatric oak species: Q. aliena (six sites), 68 Q. dentata (three sites), 156 Q. variabilis (five sites) and only one individual with intermediate morphology between Q. aliena and Q. dentata (at site TK). The latitude, longitude, and altitude of each individual sampled were recorded by GPS .Leaf material was collected from seven 50 by 50 m sites in this region Figure . The sitGenomic DNA was extracted from silica gel dried leaves using a plant genomic DNA kit  following the manufacturer's instructions. The quality of DNA was initially assessed by a 1.00% (w/v) agarose gel. Then, the quantity of DNA was measured by an ultramicro-spectrophotometer . Genomic DNA of each sample was adjusted to a final concentration of 20–30 ng/μL for subsequent use.accD-psaI-75R, trnH-psbA, rpS12-rpL20, rpS16, and trnQ-trnS) that exhibited polymorphisms in this first scan were subsequently used to analyze all 432 individuals, out of which 343 individuals with high quality were taken forward for further investigation. Each polymerase chain reaction (PCR) amplification mixture contained 20 ng of genomic DNA, 67 mM Tris-HCL, 16 mM ammonium sulfate, 100 μM of each of the four dNTPs, 2 mM MgCl2, 1 ng of BSA, 0.2% mercaptoethanol, 0.2 μM of each primer, and 0.2 units of Taq polymerase . The amplification was carried out using 1 cycle of 3 min at 94°C, 35 cycles of 30 s at 94°C, 45 s at 50 to 55°C, 45 s at 72°C, and 1 cycle of 10 min at 72°C as modified by Du et al. (KY751544-KY751561.For the chloroplast DNA (cpDNA) study, 14 individuals from the seven sites  were initially used to identify polymorphisms with 13 pairs of universal primers described in Shaw et al. , 2007 anu et al. . The PCRu et al.  with manTwenty-seven nSSRs primers reported by Dow et al. , SteinkeHT), the genetic diversity within populations (HS), the interspecies differentiation (GST) and the interspecies differentiation taking similarities between haplotypes into account (NST). Comparisons between GST and NST were carried out with 1,000 random permutations of haplotype identity. Haplotype frequency was calculated and graphed for each species and sampling site. Analysis of molecular variance (AMOVA) was performed using Arlequin V3.5  was constructed for all the individuals we analyzed. The haplotype diversity parameters were calculated by Permut 2.0  was set to 1–10. The program was set to run 1,000,000 Markov Chain Monte Carlo iterations (MCMC), following 100,000 burn-in iterations without any species identification information (USEPOPINFO = 0). The best K-value was evaluated using mean LnP(K) and ΔK  values were analyzed. The Q-value of purebreds should near to 0 or 1 and that of F1 hybrids should be close to 0.5. Based on our results and literature references, threshold values of Q ≤ 0.9  to cross-validate the results of STRUCTURE using GenAlEx version 6.5 , observed heterozygosity (Ho), and the observed number of alleles (Na) were estimated by GenAlEx V6.5 . A continuous Brownian motion model and the default FST was used to generate initial theta and migration values. Next, five independent MCMC chains, each with 5, 000, 000 generations were set to run. We sampled every 100 steps under a constant mutation model, discarding the first 10,000 records as burn-in. The mode and 95% highest posterior density were then estimated after checking for convergence. Ten different models  and Q. dentata (47 out of 48), and in the single individual with intermediate morphology. H2 was the dominant haplotype in Q. variabilis, being found across all sites. H3 and H7 were restricted to Q. variabilis at site YSD. H4, H5, and H6 were only found at site XSL in Q. aliena, Q. dentate, and Q. variabilis, respectively   and H2, H3, H6, and H7 formed the second lineage, that of Q. variabilis  and more than ten times greater than the genetic diversity within populations , suggesting the existence of phylogeography structure  varying from 9.18 to 12.29  ranged from 0.59 (Q. variabilis) to 0.70 (Q. dentata) (Table Na of Q. variabilis ranged from 5.06 (site TL) to 7.59 (site XSL). The expected heterozygosity (He) ranged from 0.55 (site TZF) to 0.64 (site XSL), and the Ho from 0.53 (site TZF) to 0.62 (site XSL)  to 9.47 (site XSL). The highest He was 0.68 at site ZL and the highest Ho was 0.69 at sites ZL and XSL (Table Na (9.53) and He (0.71) for Q. dentata had their highest values at site ZL and the Ho ranged from 0.68 (site XSL) to 0.77 (site TZF) (Table FST = 0.21), and only 20.6% of the variation was due to interspecies differences  revealed a high level of genetic variation within species (Table Two nSSRs loci (QmC00196 and WAG066) presenting null alleles detected by Micro-Checker and 18 individuals showing poor amplifications were excluded from further analysis. In total, genetic diversity of 414 individuals was estimated based on 17 loci. All 17 nSSRs loci were polymorphic with the mean number of different alleles per locus . However, the statistics also gave some support for K = 3 , and the other one included Q. aliena and Q. dentata (green). When K equaled to 3 (ΔK = 1280.58), each species was classified into a distinct cluster with red, green and blue representing Q. variabilis, Q. aliena and Q. dentata, respectively  at XSL and three  at site ZL. Hence, hybrids accounted for 1.7% of the total samples with only one individual being inferred to be an F1 hybrid    was the best model for evaluating the historical gene flow .A comparison of different models calculated by Migrate-n based on Bayesian factor values showed that model 2, with three population sizes and two migration rates  which may due to large proportion of individuals sharing haplotype H1 between the two species. Our results indicate chloroplast haplotypes are less species-specific than nuclear markers, probably because chloroplast DNA is more susceptible to drift than is nuclear DNA  detected by Migrate-n in K = 2 or K = 3, only one individual was identified as a hybrid between Q. aliena and Q. variabilis (Q = 0.16) and no hybrids between Q. dentata and Q. variabilis were detected (Figure Q. aliena and Q. variabilis or between Q. dentata and Q. variabilis. Nearly no gene flow was detected between Q. variabilis and either Q. aliena or Q. dentata by Migrate-n (Table For either -n Table . CombiniQ. aliena, Q. dentata, and Q. variabilis. The cpDNA results show high genetic differentiation between different oak sections. The nSSRs data indicate complete fixation of variation within sites for all three oak species and extensive gene flow occurs within species whereas interspecific gene flow between Q. aliena and Q. dentata is limited and almost no gene flow was detected between either Q. aliena and Q. variabilis or Q. dentata and Q. variabilis. The reasons for the low level of genetic exchange between Q. aliena and Q. dentata may include reproductive isolation, such as differences in the flowering time and in the relative abundance of parental species. Samples of seeds and seedlings should be included in future studies in order to gain a comprehensive understanding of the mechanism of genetic exchange; for example, to determine whether postzygotic reproductive isolation is the reason for the species boundaries of the three oak species in this area (Widmer et al., In our study, we conducted a fine-scale exploration of genetic diversity, differentiation and gene flow in FD and JuL designed the research. FD, JiL, JS, YL, and YW collected the samples. JiL, JS, and YL performed the experiments and analysis. FD and JiL wrote the manuscript. All authors revised the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


MTHFR 677C>T in all populations, and differences between the homocysteine concentrations according to the genotypes of MTHFR 677C>T were observed regardless of folate level.Folate and other B vitamins are essential co-factors of one-carbon metabolism, and genetic variants, such as polymorphisms, can alter the metabolism. Furthermore, the adoption of food fortification with folic acid showed a decrease of homocysteine concentration. The aim of this study was to investigate the frequencies of the polymorphisms of enzymes and carrier proteins involved in one-carbon metabolism, and to evaluate homocysteine concentrations in the presence of these genetic variants in a population exposed to mandatory food fortification with folic acid. Using data from a population-based cross-sectional study in São Paulo, Brazil, the study population comprised 750 participants above 12 years of age of both genders. A linear regression model was used to evaluate the homocysteine concentrations according to genetic variants and folate level. The results showed that the minor allelic frequencies were 0.33 for MTHFR (rs1801133), 0.24 for MTHFR (rs1801131), 0.19 for MTR (rs1805087), 0.42 for MTRR (rs1801394), 0.46 for RFC1 (rs1051266), and 0.47 for DHFR (19-bp deletion). The genetic variants of MTHFR 677C>T, MTRR 66A>G and RFC-1 80G>A were different according to race. The homocysteine concentrations increased in the CT and TT compared to CC genotypes of polymorphism  One-carbon metabolism plays an important role in complex and essential metabolic pathways, as hundreds of intracellular transmethylation reactions, including DNA methylation and DNA synthesis, have been implicated in carcinogenesis  and procStudies have shown that the elevation of homocysteine levels is an important risk marker for the occurrence of adverse events, such as dementia, Alzheimer’s disease, bone fractures, cancers, and particularly cardiovascular diseases ,5. EnvirThis observation highlights the importance of adequate nutrient intake, knowledge concerning genetic variant frequencies, and evaluation of country conditions in which the mandatory policy is to fortify foods with folic acid, as has occurred in Brazil since 2002. Furthermore, despite the accumulated evidence, there are gaps in the knowledge of the frequencies of genetic variants in several primarily healthy populations, and the impact of individual responses to diseases remains unknown. The objective of the present study was to investigate the frequency of the genetic variants involved in one-carbon metabolism and to evaluate homocysteine concentrations in accordance with the presence of these genetic variants considering the folate plasma level. We used the data from ‘Health Survey of Sao Paulo’ , a population-based and cross-sectional household health survey conducted in 2008 . The stuIn the present study, we considered all participants aged 12 years or older at the time of collection. A total of 750 individuals  responded to a social-economic survey and underwent anthropometric measurement, and subsequently, blood samples were collected for genotyping. The Ethical and Research Committee of the School of Public Health University of São Paulo (Protocol number 2001) approved this study, and informed consent was obtained from all participants.In 2008, household information was obtained from randomly selected residents using structured questionnaires applied by previously trained interviewers. Demographic, social-economic, lifestyle, referred morbidity, family-history diseases, supplementation, medicine, and diet information were collected. In a subsequent home visit, blood samples were collected and anthropometric measurements were recorded.Two 24-h recalls (24hR) were performed as a dietary survey. Food consumption described in both recalls was converted into energy and nutrient values using the Nutrition Data System for Research , University of Minnesota, Minneapolis, MN, USA). This software is used to calculate the folate quantity in three different ways: (1) natural folate—the vitamin naturally present in food; (2) synthetic folate (folic acid)—vitamin added to fortified food and dietary supplements; and (3) dietary folate equivalents (DFE)—sum of the dietary quantity of natural folate and synthetic folate, considering the difference in the bioavailability of both forms. Additionally, synthetic folate values and, consequently, the DFE values were corrected, considering the mandatory fortification of wheat and corn flour in Brazil since 2004. Moreover, the Multiple Source Method (MSM) was used to measure folate intake to estimate the usual consumption distribution of nutrients, mitigating the effects of intra-individual variation when at least two dietary measurements per individual are available . 2; eutrophic—BMI 18.5–24.9 kg/m2, and overweight—BMI ≥ 25 kg/m2. A previously trained nurse technician performed all measurements. Weight and height were measured and the anthropometric data were used to calculate Body Mass Index (BMI), and the individuals were classified, according to the BMI cut-off points of the World Health Organization (WHO) , as undeA trained nurse technician performed blood collection at home using disposable needles and syringes according to the standardized procedures described in the Guidelines for the Assessment of Food Consumption in population studies which reported an experience of the Health Survey in São Paulo . The bloApproximately 20 mL of blood were collected in tubes containing EDTA (ethylenediaminetetraacetic acid) and plastic serum tubes which had spray-coated silica through venipuncture. The tubes were stored in Styrofoam packages with recyclable ice packs and were transported to the Laboratory of Human Nutrition at School of Public Health, followed by centrifugation and processing into aliquots of serum and plasma, and storage at −80 °C.® HPLC-Analytik system [® . The immunoassay method of chemiluminescence microparticles using the ARCHITECT Homocysteine Reagent Kit  was used to analyze the plasma concentrations of homocysteine. All tests were performed according to the manufacturer’s instructions. The folate dosage was determined through High-Performance Liquid Chromatography (HPLC) with electrochemical detection . The B6 k system . VitaminMean intra-assay coefficients of variation (CVs) for B6, B12, folate, and homocysteine, respectively, were 7.2%, 7.0%, 2.0%, and 2.3%, and mean inter-assay CVs were 5.9%, 8.5%, 3.4%, and 4.0%, respectively. ® 1000 Spectrophotometer . The DNA was extracted using the DNA salt extraction method . SubsequThe PCR-allele technique was used for genotyping in duplicates with 100% of concordance . This asThe following six polymorphisms in the genes involved in folate metabolism were analyzed: 677C>T (rs1801133) and 1298A>C (rs1801131) of methylenetetrahydrofolate reductase—MTHFR; 2756A>G (rs1805087) of methionine synthase—MTR; 66A>G (rs1801394) of methionine synthase reductase—MTRR; 80G>A (rs1051266) of reduced folate carrier 1-RFC-1; and a 19-bp deletion in dihydrofolate reductase—DHFR. In this study, the genotyping call rate was >97% for the polymorphisms. For each polymorphism in the population, the minimum allele frequency was calculated, and the Hardy-Weinberg equilibrium was verified. The frequencies of female and male, age group, and self-declared races, and median of folate and homocysteine concentrations were stratified according to genotypes for each of the gene encoding enzymes or carrier proteins. The chi-square test and Kruskal-Wallis test were performed to verify differences between frequencies and medians, respectively. The folate concentration was also considered to evaluate the differences in homocysteine concentrations in the presence of genetic variants. Therefore, the population was divided into tertiles of the folate plasma concentration with mean, respectively: first (14.9 nmol/L), second (27.5 nmol/L), and third (50.7 nmol/L). A linear regression model was used to evaluate differences in the homocysteine concentrations in accordance with genetic variants by total population and folate concentration tertiles. The model considered the log-transformed homocysteine concentration as a dependent variable and the genetic variants as independent variables, divided into three categories: (1) homozygous wild-type, (2) heterozygous mutation, and (3) homozygous mutation for enzyme or carrier genotypes. The models were adjusted according to race, sex, age, estimated consumption of total folate (mcg of DFE/day), body mass index, serum concentrations of vitamins, folate, B6, and B12. In addition, we used the interaction terms of genotypes and folate plasma concentration in these linear regression models. ® software . A significance level of 5% was considered in all analyses. All statistical analyses were done using the STATA2). Moreover, in terms of race, most of the participants were self-declared Whites (59.2%), followed by Mixed (white/black) (30.7%), Blacks (8.3%), and Asians/Indigenous (1.9%). Non-smokers represented 85.2% of the population. The median of homocysteine and folate concentrations in the studied population were 8.8 μmol/L and 27.4 nmol/L, respectively. The present study involved a total of 750 participants as a representative sample of the population of São Paulo, Brazil, of which 58.1% of the participants were women and 41.9% of the participants were men, averaging 46.7 years of age (95% CI: 45.0–48.4 years). In relation to the nutritional status of the population according to the BMI classification, 46.1% of the population was overweight (BMI > 25 kg/mp > 0.05) revealed that the population was in Hardy-Weinberg equilibrium for all of the alleles studied. The genotype frequencies of the genetic variants in the studied population according to sex, age group, and self-declared race, and the respective homocysteine and folate concentrations according to genotypes are listed in p = 0.026), whereas individuals presenting genotypes GA and GG for the MTR 2756A>G polymorphism presented lower folate concentrations than individuals with genotype AA (p = 0.015). Race was observed to show statistically significant differences in the genotypes of MTHFR 677>T (p = 0.035), MTRR 66A>G (p = 0.000), and RFC-1 80G>A (p = 0.003).The primary information concerning the polymorphisms studied in this population, such as gene location, change of DNA molecule bases and consequent amino acid alterations, Hardy-Weinberg equilibrium, and minor allele frequencies, are listed in p = 0.000). The increasing risk allele (T) was related to the increase in Hcy concentration. In the presence of genetic variants stratified by folate level tertiles, the same effect was observed in MTHFR 677C>T. The individuals carrying the risk allele had higher Hcy concentrations than those of non-carriers in the first tertile (p = 0.006) and third tertile (p = 0.038) of folate concentration. However, no interaction was observed between genotypes and folate concentration on homocysteine concentration (p > 0.05).The association between genetic variants involved in one-carbon metabolism and homocysteine concentration was assessed . Only MTHerein, we conducted a population-based study of individuals in the city of São Paulo, Brazil, to evaluate the frequencies of the primary polymorphisms associated with one-carbon metabolism, the associations between these genotypes and sex, age, and self-declared race, and the differences in metabolic responses considering genetic variants. The results showed that (1) the allele frequencies in the population were in equilibrium and similar to those in other populations; (2) the genotype frequencies of MTHFR 677C>T, MTRR 66A>G, and RFC-1 80G>A were significantly different according to race; and (3) statistically significant differences between the mean homocysteine concentrations according to the genotypes of MTHFR 677C>T were observed independently of folate level. n = 1041) [Among the described polymorphisms of the enzyme MTHFR, the variants 677C>T and 1298A>C are the most well studied. Americans of Hispanic origin presented a higher prevalence of homozygotes TT for MTHFR 677C>T, which was found in 25% of the population. The prevalence of this genotype among white Americans was between 10% and 15%, and a lower prevalence of this genotype was observed for African and African-Americans, with 0% and 1%, respectively ,17,18. T = 1041) . The prevalence of 3.7% homozygotes GG and 19.7% heterozygotes AG for the MTR variant 2756A>G was observed in the control individuals from a Brazilian population , whereasThe RFC-1 genetic variant is a mutation with high prevalence among the studied populations. Homozygotes AA showed a prevalence of 22.3% and heterozygotes AG showed a prevalence of 48.4% among a Brazilian population that attended a public health care center . In contp < 0.05) in individuals with wild-type compared to the increasing risk allele (T) for the MTHFR 677C>T polymorphism regardless of folate concentrations tertiles. Similar results were found in other studies of folic acid supplementation. The mutation MTHFR TT was associated with lower folate concentrations and higher homocysteine concentration, and the trend of TT compared to CC was maintained even at different folic acid doses [In relation to the homocysteine concentration, several studies have shown that an increase in folate consumption, particularly folic acid via fortification or supplementation, consequently increases folate intake and serum vitamin concentrations, and decreases homocysteine concentrations . Additioid doses . Indeed,id doses . The resid doses . It has id doses . The synid doses ,30. On tid doses . Thus, wp < 0.05) among MTHFR 677>T, MTRR 66A>G, and RFC-1 80G>A genotypes. Some researchers criticize the use and limitations of self-declared race and consider the use of individual genetic ancestry to be the best measure of racial differences in genetic variations [Another important finding is related to differences in genetic variations according to race. In the present study, race was differently presented (riations . Neverthriations . Thereforiations ,37. Accordingly, the knowledge of genetic variability in epidemiological studies remains scarce in Brazil, primarily in representative samples of healthy populations. However, several studies have attempted to associate disease outcomes with genetic variability among individual populations. In the last two decades, several studies have reported that MTHFR polymorphisms, particularly 677C>T and 1298A>C, are associated with an increased risk for neural tube defects , cardiovDespite these findings, a potential limitation of the present study was the use of self-declared race, as this variable reflects the influence of social-economic and cultural status, although, until recently, genetic ancestry analysis was not performed in population-based studies in the city of São Paulo. Accordingly, even self-declared race is not an adequate genetic indicator, but rather this variable could represent an exposition indicator of social factors . TherefoIn conclusion, adequate folate levels are an important point in this discussion, as Brazil is a country that has a public health policy of mandatory folic acid fortification. Folic acid fortification considerably reduces the inadequacy of folate prevalence within levels considered to be safe in the inhabitant population of São Paulo ; however


We analyzed the genetic polymorphisms of 15 autosomal and 10 Y-chromosomal STR loci in 214 individuals of Han population from Southern Shaanxi of China and studied the genetic relationships between Southern Shaanxi Han and other populations. We observed a total of 150 alleles at 15 autosomal STR loci with the corresponding allelic frequencies ranging from 0.0023 to 0.5210, and the combined power of discrimination and exclusion for the 15 autosomal STR loci were 0.99999999999999998866 and 0.999998491, respectively. For the 10 Y-STR loci, totally 100 different haplotypes were obtained, of which 94 were unique. The discriminatory capacity and haplotype diversity values of the 10 Y-STR loci were 0.9259 and 0.998269, respectively. The results demonstrated high genetic diversities of the 25 STR loci in the population for forensic applications. We constructed neighbor-joining tree and conducted principal component analysis based on 15 autosomal STR loci and conducted multidimensional scaling analysis and constructed neighbor-joining tree based on 10 Y-STR loci. The results of population genetic analyses based on both autosomal and Y-chromosome STRs indicated that the studied Southern Shaanxi Han population had relatively closer genetic relationship with Eastern Han population, and distant relationships with Croatian, Serbian and Moroccan populations. Short tandem repeats (STRs) are widely distributed in human genome and play a significant role in forensic DNA analysis. Autosomal STRs have been the most common genetic markers in forensic applications and could be used to solve most of the personal identification and paternity testing cases , 2. HoweSouthern Shaanxi region is the south part of Shaanxi province, covering the area from the south of Qinling Mountains to the north of Ba Mountain with the Han River flowing through from west to east; Southern Shaanxi consists of three cities: Hanzhong, Ankang and Shangluo, from west to east where mainly reside the Han population , 10. To p>0.05). Tests of linkage disequilibrium (LD) were performed for all pairs of autosomal STR loci and the results were shown in Table According to the results of Hardy-Weinberg equilibrium (HWE) tests  were found between the Southern Shaanxi Han population and Serbian, Moroccan, Croatian, Miao, Shandong Han, Yi, Bangladeshis, Nepalese, Uygur and Dong populations at 11, 11, 10, 4, 3, 2, 2, 2, 1 and 1 loci, respectively. And then there was no significant difference obtained between Southern Shaanxi Han population and Eastern Han, Liaoning Han, Jilin Han, Hui, Salar, Tibetan, Xibe, Maonan and Korean populations, which indicated there were relatively close genetic distances among them.Fst statistics is one of the most widely used measures for genetic differentiation and plays a central role in genetic studies . ReferenThe principal component analysis (PCA) was performed among the Southern Shaanxi Han population and other 19 populations using the allelic frequencies of the 15 overlapping autosomal STR loci. The PCA result was shown in Figure The neighbor-joining tree (NJ tree) of the Southern Shaanxi Han and other 19 populations based on allelic frequencies of 15 overlapping autosomal STR loci was shown in Figure http://www.yhrd.org) . Forty-one haplotypes detected in the Southern Shaanxi Han population were found with no matches in 131889 Haplotypes. Sixty-three haplotypes were found with matches in 31445 East Asian-Sino-Tibetan-Chinese and 17 haplotypes were found with matches in 3248 East Asian-Sino-Tibetan-Tibeto-Burman.Allelic frequencies and Gene diversity (GD) values of the 10 Y-STR loci in 108 Southern Shaanxi Han male individuals were shown in Table Rst values at the 10 overlapping Y-STR loci in order to address population relationships, and the result was shown in Figure The multidimensional scaling analysis (MDS) analysis was performed among the Southern Shaanxi Han population and 19 other populations based on As shown in Figure Southern Shaanxi Han speak Chinese, which belongs to Sino-Tibetan. Although settling in different areas, Southern Shaanxi Han and Eastern Han have a relatively close genetic relationship. However, for populations from other continents or races, such as Serbian, Moroccan, and Croatian, the genetic relationships with Southern Shaanxi Han would be quite distant because of their different origins and genetic structures. At present, there is little research on Southern Shaanxi Han population; more population genetic studies would help us get a better understanding of this population genetic backgroud in the future.We collected 214 blood samples  from unrelated healthy Han individuals living in the south of Shaanxi province (Southern Shaanxi), China. All the samples were collected according to the criteria for selection as follows: their ancestors within three generations should be unrelated individuals and members of Han ethnic group, with no migration. All volunteers without diseases signed informed consents. The present study followed the human rights and the ethical principle of Xinjiang Medical University and approved by institutional ethics committee, Xinjiang medical university, China. Genomic DNA was extracted using the Chelex-100 method as described by Walsh et al .The 25 STR loci  and Amelogenin locus were co-amplified in a new single multiplex reaction in a 25μL PCR reaction volume using the Expressmarker 16+10Y fluorescence amplification reagents , according to the manufacturer's instructions. DNA samples were amplified on a GeneAmp PCR System 9700 Thermal Cycler  following the manufacturer's instructions.Electrophoresis was performed using an ABI 3130 Genetic Analyzer . Fragment sizing was supported using the AGCU Marker SIZ-500  internal size standard and allelic ladder as basis for comparison. Alleles were identified using the GeneMapper® ID V3.2 . The 9948 cell-line  DNA was also genotyped using the reagent as control.http://genepop.curtin.edu.au/). The pairwise Fst and p values between the studied Han population and reference populations at 15 overlapping autosomal STR loci were estimated by the program ARLEQUIN v3.1 (http://cmpg.unibe.ch/software/arlequin3). Principal component analysis was performed with MVSP 3.1 (http://www.kovcomp.com) based on allelic frequencies of 15 overlapping autosomal STR loci, which was used to explore the extent of correlation genetic relationships. Neighbor-joining tree based on allelic frequencies of 15 overlapping autosomal STR loci were calculated using the Phylip-3.69 Software (http://evolution.gs.washington.edu/phylip.html). Based on the 10 overlapping Y-STR loci, another NJ tree was obtained by Phylip-3.69 Software (http://evolution.gs.washington.edu/phylip.html). Multidimensional scaling analysis of Y-STR based on Rst values was constructed by statistical software SPSS version 13.0 . Gene diversity and haplotype diversity were calculated using Nei's formula [Fifteen autosomal STRs were statistically analyzed as follows. We calculated the allelic frequencies and tested the Hardy-Weinberg equilibrium using the modified powerstat v1.2 spreadsheet . The lin formula .In summary, the results demonstrated high genetic diversities of the 15 autosomal STR loci and 10 Y-STR loci in the Southern Shaanxi Han population and the studied polymorphic markers were suitable for forensic DNA cases, which could offer a new tool for forensic investigation. In this study, 15 autosome and 10 Y chromosome STR loci were amplified by the multi-color fluorescence technique in a single PCR reaction, and genotyping profile of both autosomal STR and Y chromosome STR loci could be obtained simultaneously. This made it possible for forensic geneticists to get the information of personal identification, gender determination and pedigree investigation in one step, which is a time, labor and cost saving strategy. The results of population differentiation, principal component analysis, multidimensional scaling analysis and phylogenic analysis indicated the Southern Shaanxi Han population had closer genetic relationship with the Eastern Han population and more distant relationships with populations from other races. The present data which combined autosomal STR loci and Y-STR loci will be useful for the enrichment of Chinese genetic information resources and provide valuable forensic data for forensic DNA cases.


Picea glauca) as a model and controlled, replicated experimental harvesting and regeneration experiment at the EMEND project site (http://www.emendproject.org). We used two approaches. First, genetic diversity and population structure of postharvest natural regeneration after five harvesting treatments  were assessed and compared with those of the unharvested control (pristine preharvest old‐growth) in two replicates each of conifer‐dominated (CD) and mixed‐wood (MW) forest, using 10 (six EST (expressed sequence tag) and four genomic) microsatellite markers. Second, genetic diversity and population structure of preharvest old‐growth were compared with those of postharvest natural regeneration after five harvesting treatments in the same treatment blocks in one replicate each of CD and MW forests. Contrary to our expectations, genetic diversity, inbreeding levels, and population genetic structure were similar between unharvested control or preharvest old‐growth and postharvest natural regeneration after five harvesting treatments, with clearcut showing no negative genetic impacts. The potential effects of genetic drift and inbreeding resulting from harvesting bottlenecks were counterbalanced by predominantly outcrossing mating system and high gene flow from the residual and/or surrounding white spruce. CD and MW forests responded similarly to harvesting of increasing intensities. Simulated data for 10, 50, and 100 microsatellite markers showed the same results as obtained empirically from 10 microsatellite markers. Similar patterns of genetic diversity and population structure were observed for EST and genomic microsatellites. In conclusion, harvesting of increasing intensities did not show any significant negative impact on genetic diversity, population structure, and evolutionary potential of white spruce in CD and MW forests. Our first of its kind of study addresses the broad central forest management question how forest harvesting and regeneration practices can best maintain genetic biodiversity and ecosystem integrity.Forest harvesting of increasing intensities is expected to have intensifying impacts on the genetic diversity and population structure of postharvest naturally regenerated stands by affecting the magnitude of evolutionary processes, such as genetic drift, gene flow, mating system, and selection. We have tested this hypothesis for the first time by employing widely distributed boreal white spruce ( Genetic diversity is essential for adaptation, evolution, and the long‐term survival of all living organisms    , shelterwood harvesting caused reduction in heterozygosity  (Perry and Bousquet Pinus contorta)   Neale  and amab) Rajora .Eucalyptus consideniana  showed reduction in genetic diversity , subjected to different management regimes. Cloutier et al. , of which, one of us (O.P.R.) is a founding member, provides an ideal and unique experimental design to examine genetic effects of increasing harvesting intensities in forest trees using both approaches. The details of the experimental design are provided in Materials and Methods below. The EMEND project uses the multidisciplinary ecosystem approach to address the central forest management question how forest harvesting and regeneration practices can best maintain biodiversity, forest structure and function, and ecosystem integrity of conifer‐dominated (CD) and mixed‐wood (MW) landscapes that have originated from wildfires and other inherent natural disturbances (http://www.emendproject.org). The main areas of research are biodiversity of various organisms, genetic diversity of trees, forest productivity, forest ecosystem processes and patterns, silvicultural systems, forest fire ecology, forest soils and nutrient cycling, forest hydrology and microclimate, and socio‐economics. Therefore, a variety of research has been and is being conducted on a single land base so that it could be integrated to address a very broad forest management question about biodiversity conservation and sustainable ecosystem management. Because genetic diversity is the basis of all biodiversity and foundation of ecosystem stability, our study contributes significantly to the broad goal of the EMEND project. White spruce and trembling aspen (Populus tremuloides) are the dominant species in the EMEND project forest. We have chosen white spruce as a model species for our study. White spruce occurs in CD and MW forest types at the EMEND project site and in the rest of North America.The Ecosystem Management Emulating Natural Disturbance (EMEND) project  Does harvesting of increased intensities result in proportional reduction in genetic diversity levels and increased inbreeding levels, and altered population genetic structure of the postharvest natural regeneration of white spruce? (ii) Does white spruce in CD and MW stands respond similarly to harvesting of increased intensities? We have used two approaches to address these questions. First, we have examined the genetic diversity and population structure of unharvested old‐growth control and the postharvest young natural regeneration of white spruce after harvesting of five intensities in two replicates each of the CD and MW forest, using 10 (six EST (expressed sequence tag) and four genomic) microsatellite markers. Second, we have assessed the genetic diversity and population structure of the preharvest old‐growth and postharvest young natural regeneration of white spruce in the same treatment blocks in one replicate each of CD and MW forests.http://www.emendproject.org) project experimental site was used for this study. The EMEND site is located in the Upper Boreal‐Cordilleran Ecoregion in the boreal forest in northern Alberta, approximately 90 km northwest of Peace River . The experiment was established in 1997 and is expected to run for 80–100 years (one stand rotation). The EMEND experimental design consists of four forest types  with three replicates within each forest types, and five harvesting treatments  within each replicate. Additionally, it followed a compact blocking system, where populations under different harvesting treatments and in the four forest types were expected to grow in basically uniform conditions. Each of the treatment blocks is approximately 10 ha in size. Harvesting was carried out in the winter of 1998. Blocks were harvested in a modified uniform shelterwood pattern so that a recommended amount of original basal area could be preserved. The feller‐buncher and wheeled skidder were used to harvest the compartments (see www.emendproject.org for a complete description). In brief, harvest operations were accomplished in 5‐m‐wide machine corridors. An interval of 20 m was maintained between machine corridors, which left a 15‐m‐wide green tree retention strip between each corridor. The retention levels, 10%, 20%, 50%, and 75%, were accomplished by systematic tree removal from the retention strips. Trees in the clearcut treatment (2% retention) were harvested in the conventional manner instead of in the designated machine corridors. Our white spruce study focused on two replicates in each of the CD and MW stands  in two replicates (R1 and R2) each of the CD and MW forest types  and high‐throughput magnetic fishing protocol , 1 ×  GoTaq flexi clear reaction buffer, and 0.25 units of GoTaq Flexi DNA Polymerase .One primer in each pair carried a standard M13 tail sequence  to facilitate fluorescent labeling and detection. Amplification reactions were performed in a 10‐μL reaction volume containing 5–10 ng of template genomic DNA, 0.2 mThe PCR conditions to amplify the microsatellite loci RPGSE2, RPGSE17, and RPGSE44 were as follows: 95°C for 2 min followed by 30 cycles of 95°C for 20 s, 56°C for 20 s, 72°C for 30 s, and final extension at 72°C for 3 min. The PCR conditions to amplify the microsatellite loci RPGSE5, RPGSE 34, and RPGSE35 were as follows: denaturation at 94°C for 2 min followed by 35 cycles of 94°C for 20 s, 56°C for 20 s, 72°C for 1 min, and final extension at 72°C for 4 min. For SPAG003, touchdown protocol was used . Genotypes of the sampled individuals were first scored by using SAGA GT/MX software and then verified manually.DC  and Duncan's multiple range test (DMRT) were performed to test the significance of differences in genetic diversity parameters and fixation index due to forest types and harvesting treatments, and between pre‐ and postharvest populations using SAS 9.1 software package , Hj is the effect of the jth harvesting treatment , and eijk is the random error component.The neighbor‐joining trees from 10 microsatellite loci with 1000 bootstrap iterations were constructed based on both Nei's  and chorAll of the above data analyses were performed for all 10 microsatellite loci and separately for six EST and four genomic microsatellite loci to check whether the patterns of the results were the same for the EST and genomic microsatellites.n = 10 000) with 100 freely recombining loci. These populations followed an island model of migration. The parameters set to create these populations are as follows: migration rate 0.1; selfing rate 0.05; mutation rate (2 × 10−4) with K‐allele mutation model; all loci with 50 possible allelic states. These populations were permitted to evolve under the above‐listed evolutionary setups for 20 000 generations. Of the two populations, one population was selected for the random subsampling of 23 populations with 35 individuals for each of 100, 50, and 10 microsatellite loci. Number of alleles per locus, observed heterozygosity, expected heterozygosity, and inbreeding coefficient were calculated for each data set using the FSTAT program  for individual preharvest and postharvest subpopulations for the CD forest are provided in Table S1 and those for the MW forest in Table S2. The means of allelic genetic diversity, heterozygosity, and F for different harvesting treatments in the CD and MW forest types are provided in Table F for preharvest control and postharvest natural regeneration after five harvesting treatments are in Table The number of alleles ranged from 3 to 29, with a mean of 11.5 alleles per locus for EST microsatellite loci, whereas the number of alleles ranged from 23 to 48, with a mean of 31.75 alleles per locus for the genomic microsatellite loci .All 23 white spruce subpopulations showed high microsatellite genetic diversity (Tables S1 and S2). As expected, genetic diversity was higher for genomic than for EST microsatellites (Tables S5–S7 and S10–S12). Although there was some variation in allelic genetic diversity measures of subpopulations between replicates and within and between the CD and MW forests, overall genetic diversity was similar among 23 populations. The variation in the genetic diversity measures among subpopulations was not related to the harvesting treatments. For example, the preharvest old‐growth control subpopulation had the highest allelic diversity in R2 of the MW forest and the lowest in R1 of the same forest type (Table S2). Unharvested old‐growth subpopulations and postharvest natural regeneration (seedlings) after five harvesting treatments showed similar levels of genetic diversity Tables , with noP > 0.05) between the CD and MW stands (Table S3).A similar level of genetic diversity was recorded for CD and MW stands in the preharvest control as well as postharvest natural regeneration , but were significant for effective number of alleles (P = 0.038). However, the differences for Ae were not related to a specific harvesting treatment (Table S7); the most contrasting treatments (clearcut and unharvested old‐growth) had nonsignificant differences. All genetic diversity measures and F from genomic microsatellites were not significantly different between harvesting treatments (P > 0.05).We also analyzed data for all 23 subpopulations separately for six EST microsatellite and four genomic microsatellite loci. Although EST microsatellites showed lower levels of allelic diversity (Tables S5–S7) than genomic microsatellites (Tables S10–S12), the patterns for genetic diversity and F‐statistics parameters  were similar among unharvested control and postharvest naturally regenerated subpopulations after harvesting of different intensities , revealing a departure from Hardy–Weinberg equilibrium with deficiency of heterozygotes. The FST estimates for harvesting treatments ranged from 0.020 for 75R to 0.028 for 20R, with an overall mean FST of 0.032 among all 23 subpopulations .For all 10 microsatellite loci, the mean es Table . The meaGenetic distances Nei  were lowA neighbor‐joining tree, based on Nei's  genetic F‐statistic estimates calculated from six EST and four genomic microsatellites were consistent between themselves (Tables S8 and S13) as well as with that observed from combined 10 microsatellites . The patterns of genetic distances among subpopulations within and among harvesting treatments were consistent for the EST and genomic microsatellites (Tables S9 and S14). However, the genetic distances calculated from the genomic microsatellites were higher than those calculated from the EST microsatellites. This may be due to higher allelic diversity and wider allele frequency distribution for the genomic than for the EST microsatellites. The neighbor‐joining trees constructed from Nei's (The patterns of es Table . Howeverom Nei's  as well om Nei's  genetic om Nei's .FST/(1−FST)] and geographical distances (km) was r = 0.002, P = 0.0.301 .The isolation‐by‐distance analysis showed that the correlation between interpopulation genetic differentiation [The simulated data sets results showed that 10 microsatellite loci were as efficient as 50 or 100 in estimating genetic diversity levels and fixation indices .F levels were similar between the preharvest old‐growth and postharvest naturally regenerated seedlings in the same treatment blocks undergone five harvesting treatments in each of CD and MW forests (Table F was significantly different (P > 0.05) between the preharvest and postharvest subpopulations and between the CD and MW forest types (Table S16).The genetic diversity and ts Table . This waFIS, FIT, and FST estimates were slightly higher for the postharvest seedling subpopulations than for the preharvest old‐growth subpopulations (Table P > 0.05). The mean FIS was 0.198 for the preharvest old‐growth populations and 0.232 for the postharvest seedling subpopulations, with an overall mean of 0.215 . The mean FST was 0.018 for the preharvest old‐growth populations and 0.023 for the postharvest seedling subpopulations, with an overall mean of 0.028 . Higher than expected homozygosity may be due to inbreeding and selection against heterozygotes. White spruce has significant levels of self‐fertilization (6.2%) and biparental inbreeding (3.2%) , the effects of inbreeding causing an excess of homozygotes could be discounted because inbreeding would affect all loci. We do not exactly know the cause of deficiency of heterozygotes in the studied populations. Further investigations are required to address this issue. Overall FST of 0.032 suggests that most (~97%) of the genetic variation resides among individuals within subpopulations and only about 3% among populations.Consistent deficiency of heterozygotes relative to the Hardy–Weinberg expectation was observed in all of the studied subpopulations, and The results of our study from both approaches demonstrate that genetic diversity and inbreeding levels of white spruce are similar between the preharvest old‐growth and postharvest naturally regenerated seedling populations after harvesting of five intensities. Therefore, contrary to our expectation, our study reveals that harvesting of increasing intensities of 25% cut to clearcut in 10‐ha blocks has no negative impacts on genetic diversity and fixation index of white spruce. As such, evolutionary potential for white spruce was maintained in the postharvest naturally regenerated populations.F in the post‐clearcut regenerated populations were similar to those of the preharvest old‐growth populations.Harvesting creates bottlenecks in population size, which can reduce genetic diversity in postbottleneck populations by affecting genetic drift, gene flow, and mating system , genetic differentiation (FST), and genetic distances were similar among preharvest old‐growth and postharvest naturally regenerated seedling subpopulations. In addition, grouping of the subpopulations in our study from genetic distances was almost random and unrelated to forest harvesting treatments, and there was low bootstrap support for any of the grouping. These results suggest that harvesting of five intensities had not altered the inbreeding levels, genetic constitution, and population structure of the postharvest populations.Inbreeding coefficients (NM) calculated from the FST estimates in the studied white spruce populations were high . The soils of the EMEND experimental site are usually well‐drained luvisolic, and soil properties  over the entire EMEND experimental site are equally consistent . We expect that the SNP markers from neutral sequences as well as from adaptive genes involved in height, adaptation, and other traits should provide the same patterns because white spruce trees were harvested randomly rather than based on their age, height, or other adaptive traits. No differential selective pressures among different harvesting treatments are evident that would result in divergent selection. We also think that being hypervariable markers, microsatellites should be able to pick subtle genetic differences among harvesting treatments more efficiently than biallelic SNP markers.Among different commercial forest harvesting methods, clearcutting is the most prevalent in the region. However, other EMEND studies suggest that variable retention harvest better preserves the boreal forest ecosystems and is an increasingly popular management alternative to clearcutting  and clearcut harvesting and natural regeneration system in 10‐ha blocks surrounded by natural white spruce forest without any genetic degradation. However, by taking into account the results of other studies at the EMEND site, we suggest variable retention harvesting systems over clearcutting for ecologically sustainable forest management. This is the first study of its kind examining the genetic impacts of harvesting of five increasing intensities in a forest tree by using a long‐term well‐designed controlled, replicated experimental harvesting experiment and comparing genetic impacts of harvesting in a dominant boreal conifer species in CD and MW forests. Also, it is the first study where two approaches  have been used at the same time at the same sites, providing more scientifically sound outcomes. Our study results have significant implications and applications for the conservation and sustainable management of white spruce genetic resources and should be widely applicable to other tree species. Our study addresses the broad central forest management question how forest harvesting and regeneration practices can best maintain biodiversity, forest structure and function, and ecosystem integrity.In this study, four‐year‐old or younger naturally regenerated populations of white spruce were sampled. We suggest resampling the populations from the same treatment blocks periodically and genotyping using a larger number of both neutral and adaptive markers. This information would be helpful in better understanding the long‐term impacts of harvesting treatments on evolutionary processes of white spruce.MSF was involved in field sampling, partial microsatellite genotyping, data analysis under the directions of OPR, initial manuscript draft preparation and revision. OPR developed the study concept and experimental design, provided overall study direction and supervision, and contributed to data interpretation, and manuscript writing and revision.10.5061/dryad.hj06k.We have submitted the data underlying the reported results to Dryad data repository. doi:Table S1. Genetic diversity parameters and fixation index (F) of unharvested control and post‐harvest natural regeneration subpopulations of white spruce in the conifer‐dominated forest based on 10 microsatellite loci.Table S2. Genetic diversity parameters and fixation index (F) of unharvested control and post‐harvest natural regeneration subpopulations of white spruce in the mixed‐wood forest based on 10 microsatellite loci.Table S3. Analysis of variance results for different genetic diversity parameters for testing the differences due to harvesting treatments and forest types (Approach 1).Table S4. Locus‐wise mean F‐statistic estimates calculated for 23 subpopulations.Table S5. Genetic diversity parameters and fixation index (F) of unharvested control and post‐harvest natural regeneration Subpopulations of white spruce in the conifer‐dominated forest based on six EST microsatellite loci.Table S6. Genetic diversity parameters and fixation index (F) of unharvested control and post‐harvest natural regeneration Subpopulations of white spruce in the mixed‐wood forest based on six EST microsatellite loci.Table S7. Overall means for genetic diversity parameters and fixation index for unharvested control and post‐harvest natural regeneration of white spruce in the conifer‐dominated and mixed‐wood forests based on six EST microsatellite loci.Table S8. Mean F‐statistic estimates from six EST microsatellite loci, calculated over all subpopulations and separately by harvesting treatments.Table S9. Mean and (range) of genetic distances  of genetic distances  (Approach 2).Figure S1. A neighbor‐joining tree, based on Cavalli‐Sforza and Edwards' chord distance DC  and geographical distance.Figure S3. A neighbor‐joining tree, based on genetic distances (Nei nces Nei  from sixFigure S4. A neighbor‐joining tree, based on Cavalli‐Sforza and Edwards' chord distance DC (Cavalli‐Sforza and Edwards Figure S5. A neighbor joining tree, based on genetic distances (Nei nces Nei  from fouFigure S6. A neighbor‐joining tree, based on Cavalli‐Sforza and Edwards' chord distance DC (Cavalli‐Sforza and Edwards Click here for additional data file.


Increased agricultural production is an urgent issue. Projected global population is 9 million people by mid of this century. Estimation projects death of 1 million people for lack of food quality (micronutrient deficit) and quantity (protein deficit). Majority of these people will be living in developing countries. Other global challenges include shrinking cultivable lands, salinity, and flooding due to climate changes, new emerging pathogens, and pests. These affect crop production. Furthermore, they are major threats to crop genetic resources and food security. Genetic diversity in cultivated crops indicates gene pool richness. It is the greatest resource for plant breeders to select lines that enhance food security. This study was conducted by Masinde Muliro University to evaluate genetic diversity in 19 cowpea accessions from Kenya national gene bank. Accessions clustered into two major groups. High divergence was observed between accessions from Ethiopia and Australia and those from Western Kenya. Upper Volta accessions were closely related to those from Western Kenya. Low variation was observed between accessions from Eastern and Rift Valley than those from Western and Coastal regions of Kenya. Diversity obtained in this study can further be exploited for the improvement of cowpea in Kenya as a measure of food security. Vigna unguiculata (L.) Walp. (2n = 22), is one of the most ancient human food sources [Cowpea, sources . It is o.) Walp. n = 22, i sources . As a re sources . Cowpea  sources –7.The world's cowpea production as at 2013 was estimated at 5,718,144.66 tonnes of which 5,421,561 tonnes were from Africa, with East Africa contributing 532,901 tonnes .Traditionally, diversity in cowpea is estimated by measuring variation in phenotypic or qualitative traits such as flower colour, growth habit, or quantitative agronomic traits such as yield potential and stress tolerance  that do Seedlings of each cowpea accession  were groμL containing 2.5 μL 10x PCR buffer, 1 μL of both primers, 1 mM of each dNTPs, 0.5 U Taq DNA polymerase, and 50 ng DNA. The tubes were placed in an Eppendorf Mastercycler Gradient thermocycler programmed for initial denaturation at 94°C for 1 minute, followed by 35 cycles for 30 seconds at 94°C, 30 seconds at 55°C, 1 minute at 75°C, and final extension for 10 minutes at 72°C.PCR was carried out in 0.2 mL tubes with a reaction volume of 25 The PCR products were resolved on a agarose gel (1%) using 0.5x TBE containing 1 mg/mL ethidium bromide with a vertical electrophoresis apparatus. The gel was photographed using Alphaimager 2200 under UV transilluminator . The resThe sequences obtained were first edited by BioEdit version (version 7) and then nucleotide alignments were generated using ClustalW software. The evolutionary history was inferred using the Neighbor-Joining method. Analyses were conducted using the Jukes-Cantor model . The anaNineteen cowpea accessions gave PCR products of ~300 bp  for the These accessions were clustered into two main groups: A and B, as indicated in Cluster B is comprised of four accessions that exhibit moderate level of divergence, forming four subclusters with bootstrap support of 91 (Western_047119), 88 (Western_047111), and 99 (Western_047082 and Upper_Volta_022436).Genetic diversity is the extent to which material differs within a group of plants . The lowThe low genetic divergence observed in this study is in agreement with the findings of Padulosi and Ng , who attSimilarly, two Western Kenya accessions (Western_047102 and Western_044082) exhibited a closer relationship with Rift Valley_032108. The low genetic distances observed between these accessions could possibly reflect the initial bottleneck during domestication maintained by the inherent self-pollination mechanism of cowpea crop .On the other hand, the genetic distances of the accessions from Western Kenya to the accessions from Australia, Ethiopia, and Upper Volta revealed that there was greater divergence between Western_047082 and the accession from Australia and Ethiopia, but this accession was genetically closely related with the accession from Upper Volta which is in agreement with Ba et al. . This co