Cases of evolutionary diversification can be characterized along a continuum from weak to strong genetic and phenotypic differentiation. Several factors may facilitate or constrain the differentiation process. Comparative analyses of replicates of the same taxon at different stages of differentiation can be useful to identify these factors. We estimated the number of distinct phenotypic groups in three‐spine stickleback populations from nine lakes in Iceland and in one marine population. Using the inferred number of phenotypic groups in each lake, genetic divergence from the marine population, and physical lake and landscape variables, we tested whether ecosystem size, approximated by lake size and depth, or isolation from the ancestral marine gene pool predicts the occurrence and the extent of phenotypic and genetic diversification within lakes. We find intralacustrine phenotypic diversification to be the rule rather than the exception, occurring in all but the youngest lake population and being manifest in ecologically important phenotypic traits. Neutral genetic data further indicate nonrandom mating in four of nine studied lakes, and restricted gene flow between sympatric phenotypic groups in two. Although neither the phenotypic variation nor the number of intralacustrine phenotypic groups was associated with any of our environmental variables, the number of phenotypic traits that were differentiated was significantly positively related to lake size, and evidence for restricted gene flow between sympatric phenotypic groups was only found in the largest lakes where trait specific phenotypic differentiation was highest. Instances of ecologically driven divergence between populations that may ultimately lead to speciation can be characterized along an evolutionary continuum from intraspecific variation with a single phenotypic and genotypic mode to bimodal distributions of phenotypic or genetic clusters with varying levels of reproductive isolation, and eventually phenotypically discrete and reproductively isolated species  lake populations with geographic isolation and physical properties of the respective lakes.The extent to which a species may diversify into several is thought to sometimes be limited by the number of available niches Simpson . While tThree‐spine stickleback repeatedly colonized and adapted to freshwater habitats after the last glacial retreat . Sex of each individual was determined using a molecular marker (Idh) yielding either one or two bands (separated by 30 bp) in females and males, respectively, following Peichel et al. . Nine microsatellite markers , each from a different chromosome, were amplified in one multiplex kit  and the marine population, the pairwise FST among all sites within each lake, and the FST between identified phenotypic groups within each lake were calculated using genodive 2.0 , all markers were pooled for all further genetic analyses. Linear models were then used to test for a linear relationship of heterozygosity or the pairwise FST between each lake and the marine population with environmental variables  was estimated for each lake and for the marine population using an AMOVA approach with 10,000 bootstrapping replicates to infer potential genetic substructure. Global FIS was also calculated for each identified phenotypic group of each sex. The genetic structure within each lake was estimated using an admixture model implemented in structure 2.3.3  axes, using all size‐corrected linear traits together. Relative ellipse size was calculated using a custom made script based on an implementation in the PST, unitless proportional measures of pairwise phenotypic differentiation that are analogous to the measure of pairwise genetic differentiation (FST) were calculated. PST was based on the scores of the first PC axis of each lake population and the marine population. Calculations followed Kaeuffer et al.  using an ANOVA. In addition, chi‐square tests were employed to test whether individuals assigned to distinct groups were not randomly distributed among sampling sites and substrate types in lakes where such information was available. Statistical phenotypic differentiation among groups was furthermore tested using a MANOVA, including all measured phenotypic traits and using ng Narum . The traFST of lake populations against the marine population showed a significant positive relationship with elevation of lakes above sea level , whereas the relationship of the observed heterozygosity within a lake with elevation was negative . Neither of these was significantly related to the distance of a lake from the sea, but elevation and distance from the sea were positively related to each other . The pairwise FST among the three lakes at relatively low elevation , whereas higher elevation lakes are all more strongly differentiated from the sea (FST > 0.15) and pairwise FST among these is high (FST > 0.30), with the exception of Galtaból and Mjóavatn . In the population tree, all geographically separated high‐elevation lakes reside on long branches, whereas the three low‐elevation lakes  and the marine population all sit on short branches . The Mývatn population showed the largest phenotypic variation, whereas the marine population and Hraunsfjördur, a recent marine isolate, were the least variable, occupying 42.5% and 31.7% of the size of Mývatn, respectively, on PC1 and PC2.The relative morphospace occupied by stickleback within each lake did not differ whether only females, males, or both sexes combined were analyzed, or whether the marine population was included or excluded from the PCA (results not shown). Therefore, only the average scaled estimates for the morphospace volume are shown that are based on the two main PC axes  of the PCA comprising all individuals , which was also true when each population was resampled to 25 individuals each (P = 0.030), when Hraunsfjördur was excluded  or treated as a marine population . The morphospace of lake populations was not significantly associated with the distance from the sea, elevation, lake surface area, the maximum lake depth or the observed heterozygosity, and none of these results changed when Hraunsfjördur was included or not .The colonization of lakes from the sea was associated with an increase in phenotypic diversity as lake stickleback occupied a larger amount of the common morphospace than the marine population  and Thingvallavatn . PST values were associated neither with the distance from the sea  nor with elevation .Phenotypic differentiation from the marine population, based on P > 0.300), which was also true when Hraunsfjördur was excluded (results not shown).Combining the dynamic tree cut method and lake‐specific MANOVAs, distinct phenotypic groups and hence a bimodal phenotypic distribution were identified among females in five of nine lakes Figs. , 4: ThinP < 0.05; Fig. F1,10 = 9.0, P = 0.013; Fig. P > 0.050), based on linear models using sex as a fixed factor.The trait‐based ANOVAs indicate evidence for parallelism in trait divergence between sympatric morphs in different lakes  and were nonrandomly distributed between mud and lava substrate . Individuals in the more abundant group derive mainly from the lava substrate and were smaller than individuals from the less abundant group where half of the individuals derived from the mud substrate. Individuals from the two male morphs were also nonrandomly distributed between substrate types . Males of the two morphs differed in age , where the mean age of the less abundant group was 2.1 years as opposed to 1.8 years in the more abundant group. For both sexes, individuals in the more common group (lava substrate) had longer heads and slender bodies, where males had moreover elongated first dorsal spines and gill rakers.In a few lakes, the phenotypic groups that we identified were differentiated in standard length, age, or the substrate type from which they were sampled: For Frostastaðavatn, individuals assigned to the different female morphs differed in size  and sampling site  were both significantly different between the morphs. Interestingly, individuals from the genetically distinct site Mý1 (Table S2 and below) were phenotypically almost exclusively assigned to a single phenotypic cluster , where individuals had shorter heads, snouts, fins, and spines and deeper bodies (Table S3). Lastly, age differed between the phenotypic groups that we found among females in the marine population , all collected at the same site over the same substrate.In Mývatn, substrate . However, no individual was entirely assigned to either cluster. structure failed to detect additional genetic clusters when K was further increased. Using K = 2, the pairwise FST between the individuals that were assigned with ≥75% probability to the less abundant cluster  and all other individuals was higher  than any pairwise comparison between sites within Mývatn . Individuals with high assignment probability to the less abundant genetic cluster were mainly sampled from the two sites with muddy substrate .Following a sequential Bonferroni correction, we found significant linkage disequilibrium only between the putatively neutral markers tn Table ; Fig. S2structure  when putatively QTL‐linked markers were excluded. Lastly, the FST between Thingvallavatn sites Th3 and Th5 (FST = 0.026) and the two sampling sites in Hraunsfjördur (FST = 0.007) were significant using all genetic markers (Table S2). The latter is in concordance with a previous study on stickleback from Hraunsfjördur collected at the same locations, where stickleback differed phenotypically between sites  of lake populations from the marine population increased with elevation of lakes above sea level . As a consequence, they may have experienced ecological release from interspecific competition and/or predation, facilitating the evolution of phenotypic diversity and phenotypic differentiation in this small and shallow lake . However, the power of structure to detect genetic clusters from a limited number of markers is constrained when genetic differentiation is weak . In the latter case, individuals from Mývatn 1 differ genetically from all other sites, which is congruent with the structure analysis . In contrast, we found significant genetic differentiation between phenotypic groups only in Thingvallavatn , Mývatn (B), and Thingvallavatn (C).Click here for additional data file.Figure S2. Structure analysis for Mývatn combining all sites and sexes.Click here for additional data file.Table S1. Pairwise genetic differentiation (FST) between stickleback from all lakes and the marine population (lower triangle) with the respective P values based on 1000 bootstrap replicates.Table S2. Pairwise genetic differentiation (FST) among sympatric lake sites (lower triangle) with the respective P values based on 1000 bootstrap replicates. Significant (P < 0.05) FST values are highlighted in bold.Table S3. Number of identified phenotypic modes and MANOVA results for phenotypic traits using modes as factors, calculated for each lake and for each sex separately.Click here for additional data file.


Picea chihuahuana Martínez is an endemic species listed as “Endangered” on the Red List. Forty populations of Chihuahua spruce have been identified. This species is often associated with tree species of eight genera in gallery forests. This rare Picea chihuahuana tree community covers an area no more than 300 ha and has been subject of several studies involving different topics such as ecology, genetic structure and climate change. The overall aim of these studies was to obtain a dataset for developing management tools to help decision makers implement preservation and conservation strategies. However, this unique forest tree community may also represent an excellent subject for helping us to understand the interplay between ecological and evolutionary processes in determining community structure and dynamics. The AFLP technique and species composition data were used together to test the hypothesis that species diversity is related to the adaptive genetic structure of some dominant tree species  of the Picea chihuahuana tree community at fourteen locations. The Hill numbers were used as a diversity measure. The results revealed a significant correlation between tree species diversity and genetic structure in Populus tremuloides. Because the relationship between the two levels of diversity was found to be positive for the putative adaptive AFLP detected, genetic and species structures of the tree community were possibly simultaneously adapted to a combination of ecological or environmental factors. The present findings indicate that interactions between genetic variants and species diversity may be crucial in shaping tree communities.Species diversity and genetic diversity, the most basic elements of biodiversity, have long been treated as separate topics, although populations evolve within a community context. Recent studies on community genetics and ecology have suggested that genetic diversity is not completely independent of species diversity. The Mexican  Species diversity and genetic diversity, the most basic elements of biodiversity, have long been treated as separate topics, although populations evolve within a community context Although several diversity indices have been described, very few are regularly applied in ecological studies, e.g. the species richness index Picea chihuahuana Martínez (Chihuahua spruce) is an endemic species listed as “Endangered” on the Red List and by the Mexican Official Standard Pinus, Quercus, Abies, Pseudotsuga, Populus, Prunus, Juniperus and Cupressus forming gallery forests Picea chihuahuana tree community) covers an area no more than 300 ha. It has remained in its original condition due to its isolated location at high elevations in very rugged mountains Picea chihuahuana tree community has been the subject of several studies involving different topics such as ecology The Picea chihuahuana, Pinus strobiformis, Pseudotsuga menziesii and Populus tremuloides) of the Picea chihuahuana tree community at fourteen locations.However, this unique forest tree community may also represent an excellent model for helping us to understand the interplay between ecological and evolutionary processes in determining community structure and dynamics http://www.semarnat.gob.mx/).We confirm that the field studies provide the specific location of study Table 1.Pinus strobiformis, Pseudotsuga menziesii and Populus tremuloides were not presented in all plots. For a complete list of the tree species composition and frequencies in the fourteen plots, see Quiñones-Pérez et al. The study area was located in the Sierra Madre Occidental, in the States of Durango and Chihuahua. In order to determine relationship between tree species diversity and genetic structure, fourteen study sites were considered Figure 1Picea chihuahuana was fully scored . For analysis of the genetic structure, needles were sampled from a total of 194 trees and 475 seedlings and saplings  of Picea chihuahuana in the fourteen selected plots , in 2010–2012. Further investigations were carried out on 44 trees and 85 saplings of Pinus strobiformis in twelve plots , 17 trees and 46 saplings obtained by natural regeneration of Pseudotsuga menziesii in six sites , and 18 trees and 58 saplings from natural regeneration of Populus tremuloides in seven sites  in the Picea chihuahuana tree community.The target tree species Picea chihuahuana and the fluorescent-labeled (FAM) primer pair E35 and M63+C (MseI-GAAC) for Pseudotsuga menziesii, Pinus strobiformis, and Populus tremuloides. The fourth selective base was added to reduce the high number of weak signals. The selective PCR cycling started at 94°C for 2 min, followed by 10 cycles, each consisting of 10 sec at 94°C, 30 sec at 65°C and 2 min at 72°C. The 65°C annealing temperature of the first cycle was subsequently reduced by 1°C for the next 10 cycles and continued at 56°C for 30 sec for the remaining 23 cycles, and finished with a final extension step at 60°C for 30 min. All PCR reactions were conducted in a Peltier Thermal Cycler . The amplified restriction products were resolved electrophoretically in a Genetic Analyzer (ABI 3100 16 capillaries), along with the internal size standard GeneScan 500 ROX (fluorescent dye ROX) from Applied Biosystems. The size of the AFLP fragments was determined with the GeneScan 3.7 and Genotyper 3.7 software packages (Applied Biosystems) DNA data were obtained by the amplified fragment length polymorphism (AFLP). AFLP fingerprints were established according to the protocol described by Vos et al. Although it is possible to poolplex AFLPs, we have found that the simultaneous analysis of AFLPs sometimes lowers the quality of patterns, leading to problems with scoring. Thus, we used only one primer combination in our first approach with the Mexican tree species under study.Scoring was fully automated and only strong and high quality fragments were considered. Only fragments above the signal threshold of 50 (minimum peak height)  and with a maximum peak width of 1.0, minimum peak size of 75, maximum peak size of 450, tolerance +/− bp of 0.4 and a minimum peak-peak distance of 0.5 were considered.Quality and reproducibility were checked by reference samples on each plate and independent repetition (replicate PCRs) of at least 16 samples . All replicates showed the same AFLP pattern as in the first analyses, particularly concerning the adaptive loci. Due to slight differences in PCR, the automatic scoring system identified fragments close to the minimum peak height of 50 as different. These fragments were not included in further analyses. To prevent mislabelling similarly sized fragments of different loci as one locus, we checked the adaptive loci manually and found that the size of the fragment varied by less than 0.1.f) were computed on the basis of the analysis of Picea chihuahuana, Pinus strobiformis, Pseudotsuga menziesii, and Populus tremuloides specimens from the above-mentioned plots.Finally, four binary AFLP matrices were created from the presence (code 1) or absence (code 0) at potential band positions. Each band detected corresponded to the presence of a dominant genetic variant (plus phenotype) with unknown mode of inheritance of this potential band position (detected fragment length) (named genetic variant ‘1’) a, Hill numbers (aν) a in such a diversity profile are a = 0, where the diversity equals the total number of variants, a = 2 as the effective number, and a = ∞, where only the most frequent variant determines the diversity  p is the relative frequency of a variant i. Hill numbers can be used as explicit diversity measures at both species and genetic levels of diversity Considered as a function of p is the relative frequency of a variant i.sp,av), we selected the described diversities applied to each location. Thus, each location of the P. chihuahuana tree community was characterized by the total number of tree species ), effective number of tree species ) and the number of prevalent tree species  in the sampling plots.To represent the tree species diversity profile  at each AFLP locus. A bias correction was carried out for g,2v, using the factor N/(N-1) mean,2v) was determined for each species, as an arithmetic average of g,2v values for all loci.α) and a posterior probability >0.95, we expected differential selection, whereas negative α values with posterior probabilities >0.95 indicated possible balancing or purifying selection isF (0) and the higher boundary for uniform prior on isF (1).Gene flow, random drift, selection, and mutation create patterns of genetic differentiation, although distinction between these factors by AFLP analysis may be difficult and additional information may be required, such as the use of different genetic markers (e.g. microsatellites). However, extremely high or low genetic differentiation at very few AFLP loci suggests that diversifying forces are acting non-randomly  or uniformly  δ and its P(Z≥δ) value as well as randomly chosen reassignments Picea chihuahuana tree community sampled.The differentiation parameter spνa,) and the genetic variant ‘2’ (vrf), genetic diversity  at each AFLP locus and mean genetic diversity per AFLP locus  for each species were measured separately by the covariation (C) described by Gregorius et al. C values between the number of the four tree species (DBH ≥7 cm) per plot (N) and the variables spνa,, mean,2ν, g,2ν, and vrf at putative outlier AFLP loci under differential selection were calculated. Because of the special mathematical structure of the diversity measures used and the frequency of genetic variant ‘2’ (vrf) at each AFLP locus, it was considered meaningful to look for methods of detecting types of covariation that were monotonous but not necessarily linear. The covariation C varied between -1 and 1, where C = 1 referred to an entirely positive covariation and C = −1 to a strictly negative covariation. When the denominator was zero, C was undefined The relationships between tree species diversity  In order to test the possibility that the observed degrees of covariation FDR] <0.05 and a posterior probability >0.95) with statistical significance of covariation (C) between species diversity  and both relative frequency of recessive genetic variant (vrf) and genetic diversity  and a positive value of the locus-specific component (α). Considering FDR as the expected proportion of false positives between outlier markers  critical p value (significance level*  = 0.01) was calculated by dividing the critical p value (here the significance level  = 0.05) by the number of comparisons (hypotheses) (m = 5).We preselected only putative outlier AFLP loci under differential selection , see below) in the two-sided permutation test, we expected non-randomly acting diversifying forces  as causes of the differentiation among the fourteen sampled plots , 25–149 per Pinus individual (on average 83), 37–140 per Pseudotsuga individual (on average 87), and 20–137 per Populus individual (on average 64).The AFLP primer combination yielded 243 polymorphic bands of 75–450 base pairs across all individuals of mean,2ν) in populations and across all population of the four tree species studied based on the AFLP loci recovered. The highest genetic diversities in Picea chihuahuana and Populus tremuloides were found in the northern locations, and the highest genetic diversities in Pinus strobiformis and Pseudotsuga menziesii was found in the southern populations.Picea chihuahuana, 1.1% in Pinus strobiformis, 4.9% of AFLPs in Populus tremuloides, and 0.5% in Pseudotsuga menziesii , we found only 16 probably adaptive AFLPs in Populus tremuloides  associated with tree species diversity. sp,a xνg,2]CC[ν were positive in Populus tremuloides  between species diversity  and genetic variant ‘2’ (vrf) as well as genetic diversity  were observed at the putatively adaptive AFLPs 209 and 210 in Populus tremuloides  between species diversities  and mean genetic diversity per AFLP locus  for Picea chihuahuana and moderately to strongly positive covariation for Pseudotsuga menziesii and Populus tremuloides; however, these values were not significant after Bonferroni correction  between number of the tree species per plot (N) and spν2, and gν2, at the putative adaptive AFLP 210 was significantly positive for Populus tremuloides before Bonferroni correction . However, the relationships between N and mean,2ν, g,2ν at AFLP locus 209 and vgf at the AFLP loci 209 and 210 were moderate  and statistically non-significant  for Populus tremuloides.Finally, the covariation (δ) value for the fourteen sampled plots of Picea chihuahuana tree community was 0.583, with a P(Z≥δ) value lower than 0.000001.The differentiation  was positively and significantly only related to genetic variant ‘2’ (vrf) and genetic diversity  at two putatively adaptive AFLPs in Populus tremuloides in the Picea chihuahuana tree community under study  explained the positive relationship between tree species diversity and mean (multilocus) genetic diversity per AFLP locus because population size has been positively related to mean genetic diversity Populus tremuloides trees were more frequent in locations of higher tree species diversity. The highest tree species diversity and tree density were found in the most humid and coldest climate on the Sierra Madre Occidental in Durango Populus tremuloides in forests of Durango N was positively correlated with genetic diversity by differential selection (at the putatively adaptive AFLP 210). Thus, we can only speculate as to why the genetic structure at the putative adaptive AFLP 209 and 210 of Populus tremuloides was strongly correlated with species diversity in the tree community under study. This may have been due to the dioecious nature, mating system The number of δ) among the fourteen sampled locations under study in the Picea chihuahuana tree community also indicate a strong effect of non-randomly acting diversifying forces  on species diversity The relationship between the two levels of diversity was positive for detected putatively adaptive AFLP Table 4.The positive but non-significant relationships between tree species diversity and the mean genetic diversity per AFLP locus  found in three tree species under study Table 5 The present findings indicate the existence of correlations between genetic and species diversity as the two most important levels of biodiversity Picea chihuahuana tree community Thus, the present results may contribute to a better understanding of the concurrence of evolutionary and ecological processes for determining community structure and dynamics Data S1Raw data used in this work.(XLSX)Click here for additional data file.


Ethylparaben and ethyl vanillate inhibited 17β-HSD2 with IC50 values of 4.6 ± 0.8 and 1.3 ± 0.3 µM, respectively. Additionally, parabens size-dependently inhibited 17β-HSD1, whereby hexyl- and heptylparaben were most active with IC50 values of 2.6 ± 0.6 and 1.8 ± 0.3 µM. Low micromolar concentrations of hexyl- and heptylparaben decreased 17β-HSD1 activity, and ethylparaben and ethyl vanillate decreased 17β-HSD2 activity. However, regarding the very rapid metabolism of these compounds to the inactive p-hydroxybenzoic acid by esterases, it needs to be determined under which conditions low micromolar concentrations of these parabens or their mixtures can occur in target cells to effectively disturb estrogen effects in vivo.Parabens are effective preservatives widely used in cosmetic products and processed food, with high human exposure. Recent evidence suggests that parabens exert estrogenic effects. This work investigated the potential interference of parabens with the estrogen-activating enzyme 17β-hydroxysteroid dehydrogenase (17β-HSD) 1 and the estrogen-inactivating 17β-HSD2. A ligand-based 17β-HSD2 pharmacophore model was applied to screen a cosmetic chemicals database, followed by in vitro testing of selected paraben compounds for inhibition of 17β-HSD1 and 17β-HSD2 activities. All tested parabens and paraben-like compounds, except their common metabolite  The preservative effects of parabens are at least in part due to disturbances of membrane transport and mitochondrial function in microorganisms ,,18], whip-hydroxybenzoic acid, and four paraben-like compounds, such as the virtual hit ethyl vanillate, were analyzed in vitro  and heptylparaben (4.9 ± 1.0 µM), indicating that parabens are able to penetrate cell membranes and inhibit the enzyme  -estrone and 500 μM NADPH. Whereas, the 17β-HSD2 activity was performed in the presence of 200 nM estrone, including 50 nCi of -estradiol and 500 μM NAD+.Lysate activity assays were performed as previously described. Briefly, HEK-293 cells (ATCC) were transiently transfected with expression constructs for human 17β-HSD1 or 17β-HSD2 using the calcium phosphate precipitation method. Lysates of HEK-293 cells expressing 17β-HSD1 or 17β-HSD2 were incubated at 37 °C for 10 min in TS2 buffer . Both activity essays were stopped by adding a 1:1 ratio of 2 mM unlabeled estrone and estradiol in methanol. Radiolabeled steroids were obtained from Perkin-Elmer  whereas normal steroids and cofactors were purchased from Sigma-Aldrich. Estrogens were separated by thin layer chromatography and samples were analyzed using scintillation counting. All data were collected from at least three independent measurements.To determine 17β-HSD1 activity in COV434 cells, cells were seeded  into 96-well plates and incubated for 90 min with 200 nM estrone, including 50 nCi of [2,4,6,7-Molecular docking studies were performed using GOLD  . The prop-hydroxybenzoic acid, interfered with the activity of 17β-HSD2 at a concentration of 20 µM. The most potent compounds had IC50 values in the low micromolar range and these parabens showed additive inhibitory effects. The potential estrogenic effects reported in this study were observed at lower concentrations than those activating the ER or inhibiting SULTs as previously reported [The present study identified several parabens inhibiting 17β-HSD1 and 17β-HSD2. Parabens can exert estrogenic effects by inhibiting 17β-HSD2. Inhibition of 17β-HSD2 prevents local inactivation of the active estrogen E2. All tested parabens and paraben-like structures, except the main metabolite reported ,24,25,26


Coffea canephora is commercially identified as “Conilon” when produced in Brazil, or “Robusta” when produced elsewhere in the world. It represents approximately 40 % of coffee production worldwide. While the genetic diversity of wild C. canephora has been well studied in the past, only few studies have addressed the genetic diversity of currently cultivated varieties around the globe. Vietnam is the largest Robusta producer in the world, while Mexico is the only Latin American country, besides Brazil, that has a significant Robusta production. Knowledge of the genetic origin of Robusta cultivated varieties in countries as important as Vietnam and Mexico is therefore of high interest.The coffee species C. canephora composed of known accessions and accessions cultivated in Vietnam and Mexico, 4,021 polymorphic SNPs were identified. We used a multivariate analysis using SNP data from reference accessions in order to confirm and further fine-tune the genetic diversity of C. canephora. Also, by interpolating the data obtained for the varieties from Vietnam and Mexico, we determined that they are closely related to each other, and identified that their genetic origin is the Robusta Congo – Uganda group.Through the use of Sequencing-based diversity array technology-DArTseq method-on a collection of C. canephora, and contributed to the understanding of the genetic background of varieties from very important coffee producers. Given the common genetic origin of the Robusta varieties cultivated in Vietnam, Mexico and Uganda, and the similar characteristics of climatic areas and relatively high altitude where they are grown, we can state that the Vietnamese and the Mexican Robusta have the same genetic potential to produce good cup quality.The genetic characterization based on SNP markers of the varieties grown throughout the world, increased our knowledge on the genetic diversity of The online version of this article (doi:10.1186/s12870-016-0933-y) contains supplementary material, which is available to authorized users. Coffea canephora is named either “Conilon” when produced in Brazil, or “Robusta” when produced elsewhere in the world. In 2014, Canephora (hence Conilon and Robusta) coffee represented around 40 % of coffee production worldwide, while the remaining part corresponded to (http://www.ico.org/).Canephora coffee produced by the coffee species C. canephora is a rubiaceous plant originated from the sub-equatorial plains of Africa. It belongs to the Coffea genus, which comprises 124 species, originating from Africa, Madagascar, the Mascarene Islands, Asia and Oceania [C. canephora and Coffea species are lowland, generally allogamous and diploids (2n = 2x = 22), with the notable exception of the highland, self-fertilizing allotetraploid (2n = 4x = 44) C. arabica [C. canephora plants are naturally distributed within intertropical Africa, stretching from Guinea to Uganda and from Central African Republic to Angola. Natural populations are composed of few individuals, subjected to gene flows from neighboring populations up to a few kilometers away [ers away , 4.C. canephora has been analyzed using isozyme markers [C. canephora, which will be explained in detail in the plant materials section.Based on former genetic studies –7, five  markers , 9, micr markers –12 and R markers . While tC. arabica was cultivated early (since the XIVth century) in Ethiopia and Yemen, C. canephora cultivation dates back to the end of the XIXth century, based on the use of local landraces populations. C. canephora was introduced to the main current producers of Robusta coffee by colonists during the 19th century [C. canephora trees were derived from common sources reported to belong to the Congo basin [C. canephora have focused on wild accessions from Africa and several Brazilian cultivated varieties [C. canephora producer (http://faostat3.fao.org), yet the genetic origin of the coffee plants grown by more than 400 000 cultivators in over 600 000 ha, within relatively high altitudes for Robusta coffee (>600 m.a.s.l), remains unknown. From 2012 to 2015, Vietnam produced 23 to 27 million 60 kg-bags of coffee, while Brazil produced 43 to 51 million of Arabica and Robusta taken together. In Latin America, apart from Brazil, only Mexico has a significant C. canephora production, producing 3.5 to 4.3 million (http://www.ico.org/). The qualities of the beans from Mexico and Vietnam have limited their marketability. Notably, Vietnamese beans are typically used in cheap soluble Western coffee. As a consequence of climate change, C. arabica growing will be affected in hotter lower (600–800 m.a.s.l.) production zones [C. canephora could thus represent a good alternative for millions of small coffee farmers. In the near future, Mexican C. canephora varieties will probably become the sources of varieties for Central America, where C. canephora cultivation is rapidly expanding due to its resistance to several diseases. Knowing the genetic origin of the accessions cultivated in Vietnam and Mexico is therefore of the greatest interest.Whereas  century . Until rgo basin , 16. Whiarieties , nothingon zones . C. caneC. canephora genetic diversity has been analyzed using a limited number of isozyme, SSR and RFLP markers, representing only a restricted fraction of the C. canephora genome. In contrast to classical molecular markers, SNPs (Single nucleotide polymorphisms) are the most abundant markers, particularly in the non-coding regions of the genome [C. canephora genome, representing 64 % of the 710 Mb genome [As mentioned before, e genome . New seqe genome , GBS  to test the performance of DArTseq method-derived markers in coffee: repeatability, error rates and genome wide representation of the markers; (ii) to assess consistency of C. canephora genetic diversity structures as compared to previous studies with ancient markers; and (iii) to identify the genetic origin of the coffee plants cultivated in Vietnam and Mexico, and to discuss possible consequences for coffee quality and breeding. By evaluating DArTseq-derived SNP markers from a set of well-known and unknown C. canephora accessions, it was possible to confirm and further fine-tune the genetic diversity of C. canephora, and to identify the genetic origin of accessions cultivated in two climate change susceptible zones, Vietnam and Mexico.For this new extended study of the genetic diversity of  DArTseq , a technC. canephora: (i) “Guinean” Group , it is the genetic group originating from the Ivory Coast-Guinea area in West Africa; (ii) “Nana” group , stands for the coffee originating from the fringes of South-East Cameroon, South-West Central Africa and Northern Congo; (iii) “Conilon” group  represented by the Luki, Niaouli and Kouilou domesticated populations, originating from the south of Gabon; (iv) “Robusta Congo-Central Africa” group , constituted by the wild coffees from the north of the Congo central basin and the south of Central Africa; and (v) “Robusta Congo-Uganda” group  corresponding to the wild populations or cultivated varieties native to Uganda and the Congo basin.Since each previous independent study has given different names to the genetic groups found, in this paper we have therefore chosen the use of the following nomenclature for the five previously referenced genetic groups of C. canephora was analyzed in this study, from which 81 were used to analyze the diversity structure present in C. canephora. Known accessions, provided by the IRD (Institut de recherche pour le développement), were used as biological and technical replicates, to structure C. canephora diversity; while lyophilized leaves of plants cultivated in Mexico and Vietnam were supplied by AMSA (Agroindustrias unidas de México). Details on the accessions are given in Table C. canephora accessions are coded using the following rules: The first letter depicts their agronomical interest: wild (W) or cultivated (C). The following two letters represent their country of origin: Central African Republic (Ca), Congo (Cg), Ivory Coast (Ci), Cameroon (Cm), Uganda (Ug), Mexico (Mx), and Vietnam (Vn). The remaining numbers correspond to the plant number. Full siblings are named with “_” followed by the corresponding number. Biological replicates are named with “-” followed by the corresponding number. Accessions with technical replicates are marked as “-a” or “-b”.A collection of 105 individuals from 87 accessions of http://www.adnid.fr/index-2-4A.html). Technical replicates from two independent DNA extractions were used for some accessions and several accessions were represented by more than one tree, as biological replicates , and mean expected heterozygosity (He) were calculated with the “adegenet” 2.0.2 package [ST) was calculated with the “fstat” function of the “hierfstat” 0.04–22 pakage [C. canephora collection was analyzed using a Discriminant Analysis of Principal Components (DAPC) multivariate analysis implemented in “adegenet” [ST under an island model of migration, implemented in LOSITAN [ST value was then recalculated, and with it, outlier SNPs were identified after 100,000 simulations, as the ones outside the 1 to 99 % confidence interval, with a false discovery rate smaller than 0.05.All the genetic statistical analyses were carried using R, version 3.2.3 . The pol package . The Fix2 pakage . The per2 pakage . Diversidegenet” , as follmentclass2pt{minimdegenet” , 32 were LOSITAN , in ordeFinally, individuals of unknown groups were projected onto the discriminant functions found with DAPC, using the “predict” function from the package., using 100 iterations.To illustrate the genetic relationships between individuals, unrooted NJ trees were constructed with the package “poppr” 2.1.0 , based oC. canephora pseudo-molecules [C. canephora genes (available at http://coffee-genome.org), using the Bowtie2 algorithm [C. canephora pseudo-molecules and genes. Graphical representations of the hits were drawn with the “Circos” program [The sequences obtained by the DArTseq method, containing the filtered SNPs markers, were mapped against olecules  and predlgorithm  with the program .C. canephora, we obtained 10,806 DArTseq-derived SNP markers. The average missing data and MAF percentages were 16.3 % and 12.8 %, respectively. After removing markers with more than 10 % of missing data and MAF below 1 %, 4,021 polymorphic SNPs remained for the analysis, with an average missing data of 3.1 %, a MAF percentage of 12.6 %, and an average PIC of 0.159 for the whole sample panel. The mean Ho and mean He calculated for the 4,021 markers were 0.124 and 0.162, respectively, estimated based on a panel of depurated biological and technical replicates (81 unique accessions) in order to avoid any bias on the measure.After sequencing 105 individuals from C. canephora genome . Taken together, these results suggest that the overall error rate in allele calls for the DArTseq method in C. canephora would be near 4 %.Technical and biological replicates allowed us to assess the reliability of the DArTseq method in coffee. Genotyping error rates in technical and biological replicates for the 2,616 SNPs with no missing data within the entire panel of replicates were 4.0 % (s = 1.0) and 4.3 % (s = 0.8), respectively Additional file The observed and expected heterozygosities calculated with 4,021 SNPs for the 34 analyzed accessions were 0.1405 and 0.1933, respectively , which explained 25.4 %, 10.3 %, 9.5 % and 7.0 % of the variance, respectively, were retained for the discriminant analysis with the DAPC function. Genetic diversity, as revealed by the DArTseq-derived SNP markers, confirms the genetic diversity previously revealed by RFLPs and SSRs, as five genetic clusters were identified Fig. . A detaiC. canephora, the identity and genome location of the SNPs discriminating the five groups were determined, taking advantage of the recently available C. canephora genome [C. canephora genome; while 15, 17, 5 and 2 mapped more than once, and 54, 99, 12, and 2 fell into an annotated gene. Their putative functions and gene ontologies show a large range of putative functions  produce beans from two very different genetic origins.In contrast with the on group , here weoworkers  showed tC. canephora trees are grown at relatively high altitudes (>600 m.a.s.l.), as compared to the usual 0–400 m.a.s.l range [In Vietnam as well as in Mexico and Uganda, cultivated In the long term, climate changes-particularly, global warming-will affect not only the three biggest producing countries , but also several producing countries like Mexico. Is the “Conilon” genetic group present in Brazil more adapted to climate change than the “Robusta Congo-Uganda group” present in Asia or Mexico? This issue needs to be addressed by researchers to predict supply scenarios for the industry and growers. We strongly recommend comparing the performance of Robusta to Conilon cultivars under abiotic stresses. We also suggest comparing those origins with hybrids produced between genetics groups.http://www.ico.org/) for Arabica should be undertaken urgently for C. canephora, in order to cope with future challenges brought about by the evolving climate conditions.In the majority of Robusta-producing countries, the current genetic diversity available for breeding programs is very low . The intC. canephora, and contributed to the understanding of the genetic background of varieties from very important coffee producers. Also, the discriminant SNP markers identified in our work represent a valuable tool that could be used by breeders to discriminate between C. canephora genetic groups in Robusta germplasm.In the present study, we established that markers obtained from NGS approaches are easily exploitable in coffee, with an error rate similar to what has been observed for other crops. The genetic characterization based on SNP markers of the varieties grown throughout the world increased our knowledge on the genetic diversity of The quality of Mexico and Vietnamese coffee are traded at a price lower than Uganda. Given the similar characteristics of climatic areas and relatively high altitude where Robusta is grown in the three countries, and given the common genetic origin of the varieties cultivated, we can state that the Vietnamese and Mexican Robusta accessions have the genetic potential to increase the quality of Robusta they produce.


Sagmariasus verreauxi.One of the major impediments to spiny lobster aquaculture is the high cost of hatchery production due to the long and complex larval cycle and poor survival during the many moult stages, especially at metamorphosis. We examined if the key trait of larval survival can be improved through selection by determining if genetic variance exists for this trait. Specifically, we report, for the first time, genetic parameters (heritability and correlations) for early survival rates recorded at five larval phases; early-phyllosoma stages , mid-phyllosoma stages , late-phyllosoma stages , metamorphosis (S4) and puerulus stage (S5) in hatchery-reared spiny lobster The data were collected from a total of 235,060 larvae produced from 18 sires and 30 dams over nine years (2006 to 2014). Parentage of the offspring and full-sib families was verified using ten microsatellite markers. Analysis of variance components showed that the estimates of heritability for all the five phases of larval survival obtained from linear mixed model were generally similar to those obtained from threshold logistic generalised models (0.03–0.47 vs. 0.01–0.50). The heritability estimates for survival traits recorded in the early larval phases (S1 and S2) were higher than those estimated in later phases . The existence of the additive genetic component in larval survival traits indicate that they could be improved through selection. Both phenotypic and genetic correlations among the five survival measures studied were moderate to high and positive. The genetic associations between successive rearing periods were stronger than those that are further apart.Our estimates of heritability and genetic correlations reported here in a spiny lobster species indicate that improvement in the early survival especially during metamorphosis can be achieved through genetic selection in this highly economic value species.The online version of this article (10.1186/s12863-018-0621-z) contains supplementary material, which is available to authorized users. Sagmariasus verreauxi, at the University of Tasmania has opened new opportunities to promote commercial aquaculture and also undertake genetic improvement of the species [Penaeus monodon [Liptopenaeus vannamei [Fenneropenaeus merguiensis [Macrobrachium rosenbergii [Spiny lobsters are one of the world’s most valuable seafood commodities, however, closed life cycle commercial aquaculture has not been possible due to difficulties in culturing larvae during the long and complicated development phases . Larval  species , 4. As a species , 6. To o monodon , Liptopevannamei , Fenneroguiensis , 10 and enbergii , 12. Theenbergii , 14.Oncorhynchus mykiss, tilapia Oreochromis niloticus and white leg shrimp L. vannamei [Sagmariasus verreauxi moult through 17 phyllosoma instars which takes from 6 and 8 months in hatchery production before they metamorphose to puerulus; a 21 days period, before moulting to juvenile [Homarus americanus [In addition to growth characteristics, survival especially during metamorphosis, is another trait of commercial importance because it determines yield/or productivity and thereby affects profit and economic return of hatchery operators, growers and production sectors. Survival rate during grow-out is heritable in freshwater fishes –17, as ivannamei , 19. Lowjuvenile , 21. Reljuvenile . In addijuvenile . To our ericanus  based onS. verreauxi. The study was conducted using data from over nine successive years of hatchery production from 2006 to 2014.To gain new knowledge in quantitative genetic characteristics for this emerging aquaculture species, we computed genetic parameter estimates (heritability and correlations) for measures of five larval survival phases, including metamorphosis, of S. verreauxi were collected from the wild as early instar juveniles off the East coast of Tasmania and held until reproductively active. They were kept in 4000 l fibreglass tanks under ambient photoperiod and water temperature (11 °C–19 °C), 33–35 ‰ salinity, pH approximately 8.1, and 90–100% oxygen saturation at IMAS [Mytilus galloprovincialis) and commercial shrimp pellet twice a week.Data were collected at the Institute of Marine and Antarctic Studies (IMAS) in Hobart, Tasmania, Australia. Foundation stocks of S. verreauxi prior to breeding were 2.5 and 3.5 kg, respectively. A general description of breeding, larval rearing and growout is reported in earlier studies [− 1, reduced to 7.5 l− 1 during mid-stage and 1 l− 1 during the late phyllosoma stages. Parentage of the offspring and full-sib families was verified using newly developed DNA markers (section 2.3 below). During phyllosoma rearing, larvae were fed with juvenile brine shrimp (Artemia sp.), blue mussel gonad and/or a ‘commercial in confidence’ manufactured diet. Individual final instar phyllosoma (instar 17) were transferred from mass culture tanks and were held in isolation for metamorphosis before pueruli were transferred to mass holding tanks until they moulted to the juvenile phase.The average body weight of female and male S. verreauxi were determined at five larval rearing phases, early-phyllosoma stages , mid-phyllosoma stages , late-phyllosoma stages , metamorphosis  and puerulus stage . Phyllosoma survival measures were determined at routine density reductions at the mid- and late-phyllosoma stages and during isolation of final instar phyllosoma before metamorphosis. Early and mid-phyllosoma survival was determined by volumetric counts of larval numbers whereby five subsamples of larvae were counted and the average used to determine the total number of animals being cultured. Late stage phyllosoma were counted individually when removed from mass rearing vessels for metamorphosis. Metamorphosis survival was defined as survival from final phyllosoma instar (instar 17) to 2 days’ post metamorphosis. For each family cohort a minimum of three culture vessels were monitored for survival and the mean survival between the vessels indicated cohort survival.The survival data for hatchery reared Body weight of all individually tagged female broodstock was recorded using a digital scale following the annual moult cycle and before egg extrusion. The survival data at the five time points (S1 to S5) during the larval rearing was treated as binary characteristics and analysed using both linear and threshold mixed models (section 2.5).S. verreauxi individuals [PIC)  and threshold logistic generalised mixed models (TLGM) in ASReml 3.0 . For theyijklmn is the observation for survival traits studied of the individual nth; μ is the overall mean; F and Y are the fixed effects of live feeds and spawning years, respectively. FWk is linear co-variable of average family weight of females before spawning; al is the additive genetic effect of individual lobsters; cm is the common full-sib effect; and eijklmn is the random residual effect associated with individual ijklmn.where σ12 was the estimated additive genetic or phenotypic covariance between the two traits, and Heritability for survival traits were estimated from a single trait model as p is the survival probability of individual lobster recorded at five different nursing periods and x is a linear predictor. The class variable effects were the same as described in Eq. 1. The random effects included both the additive genetic effect of individual lobster and common full-sib effects (Model 2).As survival traits were recorded as binary characters , the threshold logistic generalised mixed models (TLGM) were also used because they may have better explained genetic variation in survival characters. The threshold logistic generalised model (Model 2) assumed that the data followed a binomial distribution with a logit link functions Under model 2, the heritability was calculated ash2 on the observed scale (0/1) were transformed to the liability scales (logit and probit) using the formula of Robertson and Lerner [p is a proportion of a given survival rate in the data, and z is the height of the ordinate of normal distribution corresponding to a truncation point applied to p proportion of survival. Significance of the heritability estimates was tested using z-score against a large random normal distribution [For binomial observations, estimates of d Lerner  as folloribution .A total of 235,060 individual larvae were analysed from offspring of 18 sires and 30 dams recorded over a nine-year period from 2006 to 2014 (Table S. verreauxi during the five stages of rearing show significant variation (P < 0.05) among full-sib families or breeding pairs recorded over the nine-year period . Taking survival from hatching to instars 1–6 (S1) as an example, the difference among the families that had the highest and lowest survival was 69.4%  for S4 and highest (about 74.8%) for S2 (P < 0.01).The mean survival rates of the whole population averaged over nine years is given in Table P < 0.05) in S3, S4 and S5 among the three cohorts  that were used repeatedly in years 2009–2014 were similar during the early phase of rearing (S1 and S2). However, there were significant differences (P > 0.05).General linear model was also used to test the effect of supplementary feeds  on survival. Supplementing live feeds with formulated diet did not have significant effects on survival rates (P < 0.001). Within a spawning year (season), the survival rates at different rearing stages also differed statistically (P < 0.05). A linear regression showed an annual improvement in metamorphosis survival by about 2.86% (R2 = 0.07).On the other hand, survival rates (S1 – S5) differed statistically between spawning seasons (or spawning years). Yearly survival rates for S1, S2 and S3 showed an increasing trend over the nine years of the study  for the five measures of early survival in S. verreauxi were estimated using two different statistical models: i) Linear General Mixed Model , ii) Threshold Logistic Generalised Linear Mixed Model .Heritability . The heritability for S5 were not different from zero, due to the limited number of families available during this rearing phase.The heritability obtained from model 1 (LMM) for the survival traits before metamorphosis  were moderate (Table 2 estimates from model 2 were low to moderate (ranging from 0.01 to 0.50). Across the models, the estimates of heritability for survival at five different time points during the early phases of rearing were significant (p < 0.05), indicating that there are additive genetic variations in these characters to be improved via selection.Due to binary characteristics of survival measures, the heritability’s were also estimated from the model 2. The h2) accounted for 3 to 18% of total variance for survival traits. The c2 estimates were generally similar between the two statistical models.The common full-sib effects (cg) correlations among the five measures of early survival were moderate to high and all positive  performed better in culture both within and between years. This was particularly true for mean survival at metamorphosis. Successfully culturing phyllosoma through metamorphosis has been a major bottleneck in production of all spiny lobster species [S. verreauxi seed.Our study reports, for the first time, a set of genetic parameters (heritability and correlations) for a spiny lobster species,  species . Our res species , there a2) on survival traits during the early phase of rearing in crustacean species. The c2 estimates in our study ranged from 3 to 18%.To date, only a few studies have reported heritabilities for early rearing survival for farmed aquaculture species and these mainly involved salmonids , 31 and O. mykiss and Nile tilapia O. niloticus, suggesting that the survival rates at different rearing periods may be under alternative genetic control and that they should be treated as genetically different traits in selective breeding programs. However, further studies are needed to have a better understanding about genetic architecture of age-specific survival trait across life stages in lobster species.Our results also show strong genetic associations among the five measures of larval survival. Of practical significance is the close to perfect (unity) genetic correlations between S2  and S4 , suggesting that selection for larval survival post instar7 can improve the number of larvae during metamorphosis (S4). The increased survival rate during this period is crucial to commercial hatcheries to enhance revenue and return. However, selection for increased early survival (S1 or S2) may not capture all genetic expressions in subsequent rearing periods, as indicated by the genetic correlation estimates that were significantly different from one, such as between S2 and Puerulus survival. In a selection program for rainbow trout over 10 generations, Vehviläinen et al.  also repP > 0.05). Studies in fish and other species of spiny lobsters [Despite the significant heritability in all the statistical models used, the estimates decreased as the larvae developed. This is as expected because the larval survivals during the early phases of growth development are strongly influenced by intrinsic environmental factors, e.g. Thoa et al. . A numbelobsters  also suglobsters . Taken clobsters .S. verreauxi, breeding a larger number of families using new broodstocks should be made to frequently update heritability and genetic correlations for survival traits especially those from hatching to settlement. Furthermore, upgrading the hatchery capacity should be conducted to increase availability of spawning and rearing tanks to accommodate a larger number of families per year . This would enable larval rearing of families in replicate tanks to minimise possible environmental differences in survival rates among families and the family (or genotype) by environment effects [Although basic information about quantitative genetic inheritance is reported for survival traits in spiny lobsters, the design of this study had been adjusted to fit biology of the species as well as the availability of facilities and resources at our station. Genetic parameters obtained here are likely somewhat biased due to possible confounding of environmental and genetic effects. Hence, when production cycle is fully controlled for  effects , 41, as  effects . A routiS. verreauxi assisted our understanding of the genetic architecture of quantitative traits of commercial importance. This information will aid in the design of future breeding program for lobster species. Our estimates of heritability and genetic correlations among five measures of larval survival indicated that it is possible to improve hatchery production of this species, especially during the key bottle-neck around metamorphosis, and that selection for increased survival in the early phase can improve survival rates in subsequent rearing periods. Successful captive breeding of S. verreauxi and improving seed quality through genetic selection are likely to help facilitate commercial production of this sector.The new set of genetic parameters obtained for Additional file 1:Table S1. Characterization of microsatellite loci (DOCX 16 kb)Additional file 2:Figure S1. Variation in survival rates among families (DOCX 33 kb)Additional file 3:Figure S2. Variation in survival rates among breeding cohorts (DOCX 32 kb)


Nymania capensis (Meliaceae) across the deeply incised landscapes of the subescarpment coastal lowlands of South Africa; a region that is home to three biodiversity hotspots .This study investigates orbitally-forced range dynamics at a regional scale by exploring the evolutionary history of A range of methods are used including: multilocus phylogeography (chloroplast and high- and low-copy nuclear DNA), molecular dating and species distribution modelling (SDM).N. capensis suggest fragmentation into refugia that correspond to the current phylogeographic populations.The results support an ‘evolutionarily distinct catchment’ hypothesis where: (1) different catchments contain genetically distinct lineages, (2) limited genetic structuring was detected within basins whilst high structuring was detected between basins, and (3) within primary catchment populations display a high degree of genealogical lineage sorting. In addition, the results support a glacial refugia hypothesis as: (a) the timing of chloroplast lineage diversification is restricted to the Pleistocene in a landscape that has been relatively unchanged since the late Pliocene, and (b) the projected LGM distribution of suitable climate for This study highlights the interaction of topography and subtle Pleistocene climate variations as drivers limiting both seed and pollen flow along these lowlands. This lends support to the region’s large-scale conservation planning efforts, which used catchments as foundational units for conservation as these are likely to be evolutionarily significant units. Here I explore the role of ORD on a regional scale, specifically in terms of the interaction between glacial–inter-glacial climate changes and topography  on a tree species, Nymania capensis (Meliaceae), across a section of the subescarpment coastal plains in South Africa.Climate changes driven by variations in the Earth’s orbit, i.e., Milankovitch oscillations, have influenced the distribution of species and clades across the globe. Nymania capensis is associated with the subtropical thicket vegetation in South Africa, locally termed the Albany Subtropical Thicket. This region forms the western part of the Maputaland-Pondoland-Albany biodiversity hotspot Different catchments should contain genetically distinct lineages, (2)There should be limited genetic structuring within catchments and a high degree of genetic structuring among basins, and (3)If watersheds have been long term barriers to gene flow, then isolated catchment populations should contain evidence of genealogical sorting.Southern Africa did not experience glaciation during the Pleistocene climate cycles . Nonethe (4)β-clades that have persisted for longer than 100 kyr The species’ distribution should experience contraction and fragmentation that is consistent with phylogeographic patterns.Nymania capensis and Pappea capensis have previously been shown to be isolated to primary catchments . However, the Gouritz catchment has additional topographic complexity as two parallel mountain ranges associated with the Cape Fold Belt run across it, creating an intermontane basin known as the Little Karoo. An inselberg, the Rooiberg Mountain, splits this intermontane basin along a west-east orientation  it is a common component of the Albany Thicket, (ii) for its ease of location and identification in the landscape, and (iii) human activities, such as livestock farming, do not appear to have affected its local distribution in the landscape .This species occurs across a wide range of environmental conditions and is split into two disjunct distributions, one in the southern semi-arid region  of the Albany Subtropical Thicket and the other in the northern arid region  of South Africa, which is a mosaic of Subtropical Thicket and Nama-Karoo vegetation. Preliminary morphological  and genetic data (two samples used in this study) suggest that the northern distribution that extends from the Nama-Karoo into Namibia and the southern distribution, which is restricted to the Albany Thicket, are different species. The northern and southern distributions of N. capensis from the northern distribution stored in the Bolus Herbarium were used to generate outgroup accessions (Bolus Herbarium voucher numbers BOL48535 and BOL60966).Sampling consisted of one individual from each of 78 localities across the thicket. Sampling permits were obtained from the Eastern Cape Parks and Tourism Agency and CapeNature (0028-AAA008-00015). The sampling strategy was focussed on maximising the number of sites sampled in order to explore the broad scale regional patterns rather than intra-population differences. This scattered sampling strategy is also not affected by local and rapid coalescence events  and thusThree DNA sequence markers were analysed: chloroplast DNA and nuclear DNA from high and low copy regions. Chloroplast DNA accessions of the trnQ-5′–rps16 and atpI–atpH regions from  are treaDetails of sequence alignment and, in the case of nuclear DNA, the detection of intra-individual site polymorphisms (2ISPs) are given in N. capensis samples, I found a high degree of congruence between direct-PCR and cloned samples with a low false detection rate; two other studies show similar findings . Where 2ISPs comprised an indel and a base or bases (observed in the ITS dataset), then these were given a unique code for inclusion into subsequent analyses as no IUPAC nucleotide code exists for this combination.p-distances  and NeighbourNet (NN) networks in TCS version 1.21  and Spliistances  were use library  in R3.0. library . Consens library  and RAxM library  were use library .Bayesian software such as MrBayes  or BEASTgsi, gsi statistic is a standardised measure of the extent to which predefined groups in a gene tree exhibit exclusive ancestry ; the gsi statistic ranges from 0  to 1 . Further details are provided in The level of genealogical divergence was assessed using the genealogical sorting index gsi, . The gsip-distances, whereas ITS and ncpGS genetic distances were calculated using polymorphism p-distances . The ITS and ncpGS datasets comprised 666 bp and 1,089 bp, respectively. Sequence characteristics for each dataset are summarised in Two individuals situated in the Gamtoos had chloroplast haplotypes and ITS genotypes associated with the Sundays catchment lineage, however these were very close (≤5 km) to the watershed suggesting incorrect watershed delineation or recent migration rather than incomplete lineage sorting. Thus, these samples were grouped with the Sundays basin samples for all analyses.BOL48535; Under the evolutionarily discrete catchment (EDC) hypothesis, different catchments should contain genetically distinct lineages (Prediction 1). The catchment association was strong with chloroplast haplotypes, with all but one haplotype restricted to one of the primary or secondary catchments . A stronSamples AJP0537 and AJP0810  and significant but high MTR values  were observed. There were significant and high MTR values between the Olifants and Gamtoos basins across all DNA regions. Significant MTR values between the Groot and Olifants and the Gamtoos and Sundays were only observed in the cpDNA and ITS; however, the MTR values were low for the former pair of basins and high for the latter pair.Isolation by distance using the Mantel Test (MT) was used to determine if there was genetic structuring within and between catchments (Prediction 2). In general, non-significant MTtchments  across tgsi results do suggest a high level of lineage sorting (>0.600) in the western Gouritz basin for both datasets, and in the Gamtoos and Sundays for cpDNA . Although monophyletic lineages were detected with moderate to high support (60%–98%) in the chloroplast bootstrap phylogenies, only samples from the Gamtoos catchment displayed catchment-based monophyly . In contor cpDNA .Beast analysis was used to date the diversification of chloroplast lineages in order to determine whether the Pleistocene climate cycles have also played a role in population isolation in catchments (Prediction 4). The timing of all of the thicket lineages fall firmly within the Pleistocene whether a ‘fast’ or ‘slow’ rate of chloroplast mutation is used  hypothesis and the glacial multiple refugia (GMR) hypothesis. The former hypothesis was generated from a phytosociological study of thicket  and the fast turnover in generations is likely to have greatly increased the substitution rate . It is thus highly unlikely that its substitution rate would coincide with that of an annual herb, leading to the conclusion that lineage diversification fell within the Pleistocene. The slower substitution rate also falls within the generally accepted range of 1.0 to 3.0 × 10−9 colonised their modern range, a process that is apparently accompanied by secondary contact and introgression . The findings validate and further highlight the importance of including catchments in conservation planning as discrete and evolutionarily significant units important for maintaining genetic resources.In conclusion, the results from these phylogeographic analyses and ensemble niche modelling suggest that the genetic structuring of 10.7717/peerj.2965/supp-1Supplemental Information 1Appendices S1, S2 and S3.Click here for additional data file.10.7717/peerj.2965/supp-2Supplemental Information 2See the Readme for file descriptions. This zip file includes all DNA alignments.Click here for additional data file.


Triticum urartu (T. urartu) is the progenitor of bread wheat, and understanding its genetic diversity and genome function will provide considerable reference for dissecting genomic information of common wheat.Wild diploid wheat, T. urartu accessions collected from different geographic regions. This collection had 19.37 alleles per SSR locus and its polymorphic information content (PIC) value was 0.76, and the PIC and Nei’s gene diversity (GD) of high-molecular-weight glutenin subunits (HMW-GSs) were 0.86 and 0.88, respectively. UPGMA clustering analysis indicated that the 238 T. urartu accessions could be classified into two subpopulations, of which Cluster I contained accessions from Eastern Mediterranean coast and those from Mesopotamia and Transcaucasia belonged to Cluster II. The wide range of genetic diversity along with the manageable number of accessions makes it one of the best collections for mining valuable genes based on marker-trait association. Significant associations were observed between simple sequence repeats (SSR) or HMW-GSs and six morphological traits: heading date (HD), plant height (PH), spike length (SPL), spikelet number per spike (SPLN), tiller angle (TA) and grain length (GL).In this study, we investigated the morphological and genetic diversity and population structure of 238 T. urartu, and subsequently for their conservation and future utilization, which may be useful for genetic improvement of the cultivated hexaploid wheat.Our data demonstrated that SSRs and HMW-GSs were useful markers for identification of beneficial genes controlling important traits in The online version of this article (doi:10.1186/s12870-017-1058-7) contains supplementary material, which is available to authorized users. Triticum aestivum L.) is one of the most important crops in the world, providing about 20% of the calories consumed globally . To meet the world’s growing demand for food, it is urgent to develop high yielding varieties with good end-product making quality [T. urartu , the A-genome donor of cultivated tetraploid  and hexaploid wheat  [T. urartu as the reference sub-genome of common wheat, which will obviously provide considerable valuable information for the improvement of the latter.Bread wheat  , it is mT. urartu possesses the A genome in common with bread wheat, its genetic diversity has not been well investigated as Einkorn wheat (T. monococcum), another diploid progenitor [T. urartu harbors rich allelic diversity for numerous important traits, including agronomic characteristics, grain quality and biotic stress tolerance [T. urartu has been investigated using various markers such as isozyme, restriction fragment length polymorphism (RFLP), amplified fragment length polymorphism (AFLP), and random amplified polymorphic DNA (RAPD) markers [Although ogenitor . Nowadayogenitor , 8, and olerance –11. Gene markers –16. SuchMost agronomic traits in common wheat, such as yield and its components, dough quality and resistant characters, are controlled by multiple genes and influenced substantially by the environment, which hinders the dissection of their genetic basis . ClassicT. urartu accessions collected from the Fertile Crescent region and to identify marker loci associated with important agronomic and grain traits. Our results would provide further insights into the utility of association mapping for marker-assisted selection and its potential application in bread wheat breeding.The objectives of this study were to investigate the genetic diversity, population structure and relationships among a collection of 238 T. urartu accessions, which covered most of the original areas, were subjected to SSR and high-molecular-weight glutenin subunits (HMW-GS) analysis with SDS-PAGE. This panel was obtained from the Institute of Genetics and Developmental Biology, Chinese Academy of Sciences , the National Small Grain collection (USDA-ARS) and the International Center for Agricultural Research in the Dry Areas (ICARDA). Among these accessions, 84 were originated from Lebanon, 80 from Turkey, 37 from Syria, 12 from Armenia, 11 from Jordan, 11 from Iran, and three from Iraq , that of Henan Agricultural University, Zhengzhou  and that of Dezhou Academy of Agricultural Sciences, Dezhou  in two consecutive years (2013-2014 and 2014-2015 cropping seasons). These environments were designated as E1 , E2 , E3 , E4 , E5 , and E6 , respectively.The collected Each field trial was managed in a completely randomized block design with two replications. All the plants were grown in a single 2-m row with 40 cm between rows and 20 cm between individuals. Nine traits were evaluated and analyzed, including heading date (HD), plant height (PH), spike length (SPL), spikelet number per spike (SPLN), tiller angle (TA), grain length (GL), grain width (GW), grain length/width ratio (GLW) and thousand-grain weight (TGW). The HD was counted as days from sowing to heading, and the date of heading was subsequently recorded when half of the spikes emerged from the flag leaf in each accession. The TA was measured between the last developed tillers and the ground level with a protractor at the maximum tillering stage, while the other agronomic traits were determined on the primary tiller. After the harvest, a minimum of 200 grains from each sample was photographed on a flat-bed scanner and the images were obtained as the aerial view of the ventral side of the grains. The GL, GW and GLW were calculated using the grain analyzer software , and the TGW was measured by the average of two 1000 kernel-weights.https://wheat.pw.usda.gov/cgi-bin/graingenes/browse.cgi?class=marker). The nested-PCR amplifications were performed using fluorescent dye labeling system according to Schuelke [2O . PCR was performed as follows: initial denaturing at 95 °C for 4 min, 15 cycles of 94 °C for 30 s, 60 °C for 45 s, and 72 °C for 45 s, followed by 25 cycles of 95 °C for 30s, 52 °C for 45 s, 72 °C for 45 s, and a final extension at 72 °C for 10 min. All reactions were conducted using a thermal cycler, Veriti 96 .Genomic DNA was isolated from young leaf tissue of two-week-old seedlings  using the cetyl trimethyl ammonium bromide (CTAB) method . DNA conSchuelke . In briexlDNA Analyzer with GeneScan-500 LIZ size standard . SSR polymorphism was analyzed by GeneMapper software version 4.0  according to the manufacturer’s instructions.Amplified PCR products were pooled and then purified with 3.0 M sodium acetate and 70% ethanol before adding HiDi-formamide. Fluorescently labeled DNA fragments were separated by capillary electrophoresis in an ABI 3730w/v) separating and 3% (w/v) stacking gels. Electrophoresis was conducted at a constant current of 18 mA at room temperature for about 8 h, and then the SDS-PAGE gels were stained overnight with Coomassie Brilliant Blue G-250 in a solution containing 20% (v/v) methanol and 10% (v/v) acetic acid. De-staining was carried out with tap water and then the gels were subjected to image capturing on a high-resolution scanner (GE ImageScanner III). The identification of HMW-GSs and alleles were based on the methodology described by [In each accession, the HMW-GS proteins were extracted from three seeds according to previous procedure , and SDSribed by .Shannon’s information index (I), Nei’s Gene diversity (GD) and Polymorphism information content (PIC). The accuracy of these genotyping data was also manually checked for the scoring errors and null alleles using the Micro-Checker software [T. urartu accessions were conducted based on the Jaccard’s coefficient similarity matrix obtained from the proportion of shared SSR fragments and HMW-GS bands, then a dendrogram was drawn with NTSYSpc 2.11 program [For 62 SSR polymorphic loci, the genetic parameters of variability were estimated via the POPGENE1.32 software , includisoftware . All the program  using UPK value (number of subpopulations) ranging from 1 to 15, adopting the admixture model and correlated allele frequencies, with a burn-in period of 50,000 and the number of replications at 100,000. The normal logarithm of the probability was calculated against each K value, and the optimal number of subpopulations was determined using the ΔK approach described by Evanno et al. [T. urartu individuals could be assigned to the putative subpopulations according to their average membership coefficient, which was calibrated using CLUMPP [The model-based (Bayesian) STRUCTURE version 2.3.1 was applied to identify clusters of genetically similar individuals on the basis of their genotypes . The proo et al. . Then eag CLUMPP , 43. A nT. urartu accessions. Population differentiation was assessed by calculating pairwise Fst values and Nei’s genetic distances for different regional population pairs. The threshold for statistical significance was determined by running 10,000 permutations. Principal coordinate analysis (PCoA) was also carried out based on binary genetic distance. The generated eigenvalues and accumulated percentage of the variation were applied to plot the scatter diagram of these representative accessions, with the first two principal coordinates which accounted for the highest variation. All the calculations mentioned above were implemented in the GenAlex 6.5 software [Analysis of molecular variance (AMOVA) was performed to estimate the genetic variance within and among inferred populations in software .T. urartu mapping panel was included as fixed effects, while association was estimated by simultaneous accounting of multiple levels of population structure (Q matrix) and relative kinship among the individuals (K matrix) in MLM. The significant threshold for associations between loci and traits was set at P < 0.01. The Bonferroni correction of multiple testing was performed based on the q value using false discovery rate . For all associated markers, the average phenotypic effects of different alleles were estimated using the method proposed by Breseghello and Sorrells [The markers with minor allele frequency less than 5% were removed in order to reduce false positive associations. The pairwise kinship (K matrix) among samples was generated from the program SPAGeDi . LinkageSorrells .h2), were calculated  with 12.23 cm standard deviation in E1, and TGW ranged from 4.29 to 18.87 g with 2.96 g standard deviation in E5. The phenotypic data for HD, PH, SPL, SPLN, GL, GW, GLW and TGW followed the normal distribution, suggesting that these traits were controlled by multiple loci. The broad-sense heritability (h2) of all the traits was relatively high, ranging from 68.91% for TA (E2) to 94.05% for SPLN (E4), which confirmed that most of the phenotypic variance was genetically determined. Moreover, significant correlations coefficients among different environments were also detected, implying the less genotype x environment interactions of these traits  analysis revealed that several traits were correlated , followed by TGW versus GL , indicating that grain weight was largely influenced by grain size in T. urartu. In addition, significant positive correlations of HD with PH, SPL and SPLN were observed in all environments, suggesting that late-heading varieties were prone to have a high statue and large spike with many spikelets. On the other hand, HD was also negatively correlated with GL and GLW, demonstrating that a T. urartu accession with late heading date almost followed with small grain length and low grain length/width ratio. Notably, TA had a significant positive correlation with PH and SPLN, which reflected the tendency for prostrate type to have a high plant and a large number of spikelets.The correlation coefficient  distributed on seven chromosomes  to 42 (Xgwm136) were amplified, with an average of 19.37 alleles per locus (Ao). 881 rare alleles (73.36%) were detected with the frequency lower than 5%, but none was fixed with the frequency more than 90%, resulting in an average expected allele (Ae) of 7.29. This suggested that the higher genetic variations of alleles were present in T. urartu accessions. Consequently, the major allele frequencies varied from 0.13 (Xcfd15) to 0.86 (Xbarc206), with the overall mean of 0.32.To evaluate the genetic diversity of the Nei’s gene diversity (GD) for 62 loci demonstrated that Xcfa2134 preserved the highest GD (GD = 0.94) and Xbarc206 did the lowest (GD = 0.25), with the mean value of 0.80. Hardy–Weinberg equilibrium testing of these markers indicated that T. urartu population is not mating randomly, probably owing to the self-pollination in diploid wheat  and expected heterozygosity (He) ranged between 0.04-0.72 and 0.24-0.85, respectively. As a result, a total of 1357 genotypes were deduced with an average of 21.89 per SSR marker. According to the polymorphic information content (PIC), 53 SSR loci (85.48%) were highly informative (PIC >0.5), eight (12.90%) were reasonably informative (0.5 > PIC >0.25) and only one (1.61%) was slightly informative (PIC <0.25). Calculation of the T. urartu accessions possessed high polymorphic information, covering most original areas. In order to explore and compare the variability inherent in genetic diversity, variability parameters were calculated in eight sample subsets (Table P < 0.01), resulting in a general decrease in GD from 0.76 to 0.64. Likewise, the Shannon’s information indices (I) were counted as 1.97 versus 1.48  were observed as well in Turkish (1.73) and Armenian (0.68) accessions, respectively.With respect to the geographic regions analyzed separately, the subpopulation of accessions collected from Turkey exhibited the highest diversity, followed by that from Northern Syria, Southwestern Syria, Lebanon, Iran, Jordan, Armenia and Iraq, due to their differences in number of alleles and genetic diversity Table . GD in eT. urartu accessions is formed by two distinct electrophoretic moving zones, including one major 1Ax subunit zone with slower mobility and one major 1Ay subunit zone with faster mobility , and only one (0.42%) was found silenced for the 1Ax subunit. All the 1Ax subunits in T. urartu showed faster electrophoretic mobility than the subunit 1Ax1 detected in bread wheat Xiaoyan 54 (XY), and four 1Ax subunits in 46 accessions displayed slower electrophoretic mobility than the 1Ax2* present in bread wheat Cheyenne (CNN) .The pattern of HMW-GSs from most of the ity Fig. . Among tcessions 8.99%, anA total of eleven 1Ax and eight 1Ay subunits were detected, resulting in 18 HMW-GS genotypes (U1-U18) Table . U1, U6 T. urartu accessions into two clusters: Cluster I mainly distributed in the east of Mediterranean coastal regions, including Lebanon, Jordan and southwestern Syria, and Cluster II tended to occur in the Mesopotamia and Transcaucasia regions, including Turkey, Iraq, Iran, Armenia and northern Syria. The genetic distance in the dendrogram revealed that Cluster II exhibited more diversity than Cluster I, which was consistent with its extensive geographic distribution. In Cluster I, Lebanese accessions (84) gathered tightly and were further distinguished from the other accessions, thus this cluster split into two major subclasses. Cluster II was also divided into two subclasses, one of which contained all the Iraqi and Iranian accessions (14), most of Turkish and northern Syrian accessions (84), and one Armenian accession, whereas the other one contained eight Turkish accessions, six northern Syrian accessions and eleven Armenian accessions. Typically, the sequenced accession, PI428198 (G1812) [r = 0.92, P < 0.001), indicating a good fit between the dendrogram and its original similarity matrix. The range of similarity coefficients (0.03-0.97) showed abundant genetic variation in this collection, which is supported by the high means observed for the number of alleles per locus and the PIC values.The information about genetic variation determined from SSR data combining with the SDS-PAGE analysis of HMW-GS was employed to estimate similarity matrix value. Based on Jaccard’s coefficient, an UPGMA dendrogram was constructed to reveal the genetic relationships Fig. . The phy (G1812)  grouped Principal coordinates analysis (PCoA) was also performed in order to assess the individual differences Fig. . The firT. urartu, the model-based Bayesian cluster analysis was tested using the software program STRUCTURE  from two to fifteen, with five independent runs for each K value. The CLUMPP alignment of independent solutions showed the high posterior probability in assignment of accessions among runs. At K = 2, we detected a division between 112 eastern Mediterranean coastal accessions (Cluster I) and 126 Mesopotamia-Transcaucasia accessions (Cluster II). At K = 3, Cluster II split into 61 Turkish accessions and the remainders, while 58 Lebanese accessions were segregated from the rest of Cluster I when K = 4. With increasing K, minor subpopulations from different geographic regions such as Jordan, Iran, Iraq and Armenia could be separated gradually. The optimum number of subpopulations (K) was identified based on lnP (D) value and the delta K (ΔK) method suggested K = 2 as the best fitting one in our study . The pairwise Fst value, interpreted as standardized population distances between two populations, ranged from 0.0658 (between Turkish and northern Syrian populations) to 0.4419 (between Jordanian and Armenian populations). The Nei’s genetic distance data consisted with the Fst estimates, in which Turkish population showed the smallest genetic distance with northern Syrian population (0.0289), whereas the greatest genetic distance was observed between Jordanian and Armenian populations (0.7947) , followed by variation among geographic regions (18.93%), variation within individuals (12.87%) and variation among the large two Clusters (8.16%). The overall T. urartu collection, with 257 possible linked (in the same linkage groups) and 1696 unlinked locus pairs (from different linkage groups), respectively. Among these linked locus pairs, the pairwise r2 values varied from 0.00 to 0.25 with a median of 0.04, and only nine (3.50%) marker pairs were at significant LD level (r2 > 0.1 and P < 0.001), which suggested seldom LD among the analyzed loci.The SSR and HWM-GS data were subjected to evaluate the linkage disequilibrium (LD) on a whole genome level. Across all the 63 loci, 1953 locus pairs were detected in the entire K = 2) inferred from STRUCTURE defined the ancestry coefficient of individuals in the population and the K-matrix was subjected to correct for their genetic relatedness. Besides, the averages of the phenotypic variations calculated by the two models for association mapping were 15.89% (Q) and 22.74% (Q + K), indicating that the MLM could explain more genetic variation than GLM. Henceforth, our attention will focus on associations incorporating both Q-matrix and K-matrix since they were more conservative and accurate.The association analysis between markers and phenotypic data was carried out using GLM and MLM models in the software TASSEL. Among the 63 × 9 marker-trait comparisons, 67 significant associations (11.82%) were identified using GLM approach with Q-matrix. However, the MLM analysis reduced to 10 significant associations (1.76%) once considering K-matrix as co-variate. The Q-matrix  in T. urartu accessions  in five environments, and could explain 15.99 to 20.33% and 23.55 to 28.23% of the phenotypic variation, respectively.Considering the MLM statistics, significant marker-trait associations for six traits were identified with six SSRs and protein marker HMW-GSs , whereas the U14 pattern with the prostrate type (21 accessions). Regarding GL, the significant associations were attributed to the 224-bp allele at Xcfa2219-1A and the 205-bp allele at Xgwm293-5A being specific to genotypes with large kernel length.We further investigated the relationships between the genotype and haplotype with the phenotypic traits analyzed Fig. . For HD,T. urartu harbors rich allelic diversity for numerous important traits, including agronomic characteristics, dough quality and biotic stress tolerance [Nowadays, the genetic variability of wheat cultivars is decreasing as a consequence of the genetic erosion of cultivated hexaploid wheat. As a wild diploid progenitor of hexaploid wheat, olerance –11. ThusT. urartu using SSR markers developed in common wheat. A total of 1201 alleles were identified from the 62 SSR loci in the 238 accessions, with an average of 19.37 alleles per locus, which is much higher than that observed in an earlier study (19.37 vs. 8.00) of 23 T. urartu accessions using 25 SSRs [T. urartu has also been reported with RFLP and RAPD markers [T. urartu using SSR markers, probably because of a relatively large number of accessions collected in a wider geographic region. Moreover, compared to other wheat species, T. urartu possesses higher level of genetic diversity than the A genome of tetraploid and hexaploid wheat [In recent years, SSRs markers have been proven to be an efficient tool for molecular and genetic studies in wheat –49. Many 25 SSRs . In addi markers . This isid wheat , 53.T. urartu accessions were found to express the 1Ay subunit, which was consistent with previous reports [HMW-GSs are the major seed storage proteins that determine dough viscoelastic properties and bread-making quality , 55, whi reports , 59, 60.T. urartu possessed high genetic variation, which make them suitable for mining valuable genes based on association mapping.The genetic diversity observed in this study is well reflected by the variation in multiple biological traits. For example, PH showed a broad variation with an average of 112.43 cm ranging from 86.10 cm to 149.10 cm. All these data demonstrated that the collection of T. urartu species are endemic to the major geographic regions of the Fertile Crescent [T. urartu accessions were grouped together. Specially, populations originated from Armenian, Nusaybin east of Turkey and Malikiyah of northern Syria exhibited high frequencies for the rare alleles such as 127-bp at Xgwm614-2A and 214-bp at Xcfa2193-3A, which separated the populations from other regions. The restricted distribution of these alleles indicated that variation at the associated loci possibly has some adaptive significance, which was supported by previous report [Crescent , 62. In Crescent . The levCrescent . The othCrescent . The IraCrescent , thus, tT. urartu collection used in this study. The result separated these accessions into Eastern Mediterranean coastal and Mesopotamia-Transcaucasia populations, generally in agreement with the phylogenetic tree and PCoA analysis. However, the loss of genetic diversity and decrease of population size were detected from Cluster II to Cluster I, since bottleneck and genetic drift may generate in the duration of natural selections. Given the subdivision, accessions from Turkey and northern Syria exhibited higher diversity than others, which had also been reported previously [T. urartu populations in these regions.In order to avoid distortion of the relationships among members and the spurious association mapping between phenotype and genotype, we examined population structure of the representative eviously , 51, andT. urartu  mapping population [Xbarc138-4A for SPLN was associated with yellow rust in ITMI-mapping population [T. urartu and hexaploid wheat, and T. urartu could be explored in underlying gene characterization through mapping based cloning for its relative simple genome [T. urartu to hexaploid wheat.Agronomic traits such as PH, HD, SPL and TA play important roles in wheat life cycle and environment adaptability, which are closely associated with the yield potential , 65. Graon wheat . Xgwm328on wheat , 73. As on wheat . Xgwm293pulation . Moreovepulation . The datT. urartu and T. aestivum indicates the great potential for discovery and utilization of wild diploid relatives in wheat breeding. The associations determined in this study would be very useful for marker-assisted selection (MAS) in wheat breeding programs, although more effort is needed to validate these associations in other populations. Along with the progress and wide applications of comparative genomics approaches, further work to elucidate the genetic basis of complex traits will be accelerated.Except the phenotypic traits mentioned above, the A genome of wheat is also known to contain QTLs or genes affecting other agronomic traits, heat and drought tolerance, pathogen resistance and so on –79. The T. urartu accessions were analyzed through SSR and HMW-GS markers and their associations with phenotypes were detected. Six markers, associated with HD, PH, SPL, SPLN, TA and GL were determined, which should be beneficial to effectively exploit new genetic variations of the wild diploid T. urartu in yield and quality improvement of common wheat using MAS programs. Our results also provide further insights into conservation and future utilization of wild wheat resources.Genetic diversity and population structure of 238 Additional file 1: Table S1.T. urartu accessions used in the present. Table S2. List of SSR primers used for genetic diversity and association analysis. Table S3. Correlations coefficients for the investigated traits of 238 T. urartu accessions in six environments. Table S4. Details of phenotypic performances and ANOVA analysis of differences between the Eastern Mediterranean coastal and Mesopotamia-Transcaucasia groups. Table S5. Correlation coefficients between the investigated traits in 238 T. urartu accessions in six environments. Table S6. Summary of Hardy-Weinberg equilibrium testing for SSR markers used in this study. (DOCX 75 kb)Additional file 2: Figure S1.K value) for 238 T. urartu accessions by the method of Delta K . The peak represents the appropriate number of subpopulations. (TIFF 311 kb)Optimization of the number of subpopulations (