Quercus is a species-rich and ecologically diverse woody genus that dominates a wide range of forests and woodland communities of the Northern Hemisphere. Quercus thus offers a unique opportunity to investigate how adaptation to environmental changes has shaped the spatial genetic structure of closely related lineages. Furthermore, Quercus provides a deep insight into how tree species will respond to future climate change. This study investigated whether closely related Quercus lineages have similar spatial genetic structures and moreover, what roles have their geographic distribution, ecological tolerance, and historical environmental changes played in the similar or distinct genetic structures.Understanding the origin of genetic variation is the key to predict how species will respond to future climate change. The genus Quercus sections Cyclobalanopsis, Ilex, and Quercus) have different spatial genetic patterns and occupy different climatic niches. The lowest level and most homogeneous pattern of genetic diversity was found in section Cyclobalanopsis, which is restricted to warm and humid climates. The highest genetic diversity and strongest geographic genetic structure were found in section Ilex, which is due to their long-term isolation and strong local adaptation. The widespread section Quercus is distributed across the most heterogeneous range of environments; however, it exhibited moderate haplotype diversity. This is likely due to regional extinction during Quaternary climatic fluctuation in Europe and North America.Despite their close relationships, the three main oak lineages (Ilex and Quercus were significantly predicted by geographic and climate variations, while those of section Cyclobalanopsis were poorly predictable by geographic or climatic diversity. Apart from the different historical environmental changes experienced by different sections, variation of their ecological or climatic tolerances and physiological traits induced varying responses to similar environment changes, resulting in distinct spatial genetic patterns.Genetic variations of sections  Anthropogenic climate change has a marked impact on both species and ecosystems throughout the world , 2. ContQuercus, Fagaceae) in particular are an important group to understand the impacts of environmental change on population genetic diversity for organisms with different traits and distributions [Climate change may create particular problems for tree species. While, trees tend to be capable of high rates of local adaptation , their libutions , 20, 22.ibutions –26. Withibutions –30. Theyibutions . Moreoveibutions . As a coibutions , 34 thatibutions . Hence, Cyclobalanopsis and Ilex, which have an East and Southeast Asian and Eurasian (sub) tropical distribution, respectively; and section Quercus, which is widely distributed in the Northern Hemisphere [Cyclobalanopsis [Ilex, geomorphological and climate changes from the Neogene onward have been demonstrated to have shaped the genetic structure [Quercus have been particularly well studied [Oak plastome haplotypes have been widely sampled, particularly in three major clades: sections misphere . Recent lanopsis –38 indictructure –47. The  studied , 48, 49, studied , 50–53, Cyclobalanopsis, Ilex and Quercus) that span the geographic range of each. We aim to figure out the underlying mechanisms that influence the maternal genetic pattern of oaks to predict how future climatic changes will affect acorn migration and to provide new insights into the response of trees to future climate change, and to offer suggestions for the sustainable management of forest tree populations.This study addressed two interrelated sets of questions. First, do the closely related oak clades share a similar spatial genetic structure? If not, what induced the distinct genetic patterns of oak clades? Second, what roles have geographic distribution, ecological tolerance and historical environmental changes played in the genetic diversity of each clade? This study sampled plastome haplotypes of representative species from three oak clades , nucleotide diversity (0.917) and Fst (0.3220) among the three sections (Table Ilex had the highest genetic diversity as estimated using p-distance (0–0.0090), genetic distances and nucleotide diversity (0.985), however, it had a median Fst of 0.4624 , genetic distances and nucleotide diversity (0.934) were medium  negative and Fay and Wu’s H was negative in section Quercus. This is likely the result of population shrinkage during the glacial period.Tajima’s is Table , suggestCyclobalanopsis , bio3 , bio1 , and bio7 , in the order of variable contribution. For section Ilex, the top climatic factors with the highest contributions were bio7, bio3, bio1 and bio12. Furthermore, for section Quercus, they were bio1, bio12, bio3 and bio19 (precipitation of coldest quarter). Overall, annual mean temperature and annual precipitation were key climatic variables that restricted species distribution of the three oak sections.To identify which climatic variables restrict the geographic distribution of different sections, the contribution of climatic variables was ranked  analysis of section age Fig. b. In conure Fig. c. Similates Fig. c.Cyclobalanopsis and its two lineages were poorly predicted by either geographic or climatic diversity  but not by climate  and no correlation with climate  and climatic distances  were both strong predictors of genetic variation within section Quercus. Within geographic lineages, where plastomes were shared relatively freely, North American genetic distances were well predicted by geography  and climate , however, the Eurasian lineage showed no significant correlations  are shared by 69.6% of individuals. Therefore, incomplete lineage sorting is unlikely explain the large-scale sharing of haplotypes.Although section ligocene , 54, thery small . FurtherCyclobalanopsis could be a result of selective sweeps on the chloroplast. This is supported by the results of the conducted neutrality tests  indicate a recent selective sweep, as well as population expansion after a recent bottleneck [Cyclobalanopsis. The majority of individuals in this study  are genetically similar and dominated by few haplotypes, which is exactly as expected under purifying selection. The chloroplast genome can undergo trans-specific selective sweeps, as previously reported, e.g., in Salix [Begonia [Silene [Cyclobalanopsis [Alternatively, the high genetic similarity and large-scale haplotype sharing that was observed within section ts Table . Signifittleneck . Howeverttleneck . A negatttleneck , suggestin Salix , Begonia[Begonia  and Sile [Silene . Weak relanopsis –66, likelanopsis , 68, whiCyclobalanopsis could then have intensified the selection for attenuated plastome diversity. Diversification and range expansion of section Cyclobalanopsis from SW China-Indochina to East Asia were driven by a combination of climatic and orogenic factors, initiated by the extrusion of Indochina since the Oligocene [Cyclobalanopsis is relatively uniform in climate. Section Cyclobalanopsis is a dominant woody lineage of warm and humid Asian (sub) tropical evergreen broadleaved forests [Both the timing and geography in section ligocene –71 and aligocene  since thligocene , 73. The forests . Moreove forests , 75. TheCyclobalanopsis implicates selection as a driving force in its plastid evolution, section Ilex exhibits the hallmarks of geographic isolation. Its three lineages correspond to Sino-Japan, SW China and the Himalayas-Mediterranean. Moreover, geography explains a significant proportion of genetic diversity both among (r2 = 0.3603) and within (r2 = 0.0337–0.1563) these lineages  were inferred  and Quercus in only the plastome data, while nuclear data show clear monophyly of the sections [Quercus. This result seems most plausibly raised from long-term geographic isolation of the two groups of white oaks due to submersion of the North Atlantic land bridge and Bering land bridge since the late Neogene [The plastomes of the white oak derive from ancient and rapid diversification into four major plastome lineages in sections sections , 104. Mo Neogene . Climate Neogene  and Cent Neogene –109 sincHowever, the genetic variation of the Eurasian lineage does not correlate with geography or climate Table . The EurCyclobalanopsis is restricted to warm and humid subtropical Asia and has an almost continuous distribution within its range. While section Ilex has a wider climatic range, it is still unsuited to the dry and cold climate of central Asia, which shapes its disjunct distribution in East Asian-Himalayas and Mediterranean. White oaks, in contrast, have adapted to a wide spectrum of environments and have the widest geographic distribution, comprising the most diverse and productive  woody plant genus of North America [The disparate spatial genetic patterns of these oak clades appear to result from variance in their ecological / climatic tolerances, migration histories, the strength of climatic selection and physiological traits. Climatic tolerance is likely the easiest of these to characterize. Section  America . From th America , 111. WhIlex from East Asia share similar geographic distributions with section Cyclobalanopsis. Both sections originated during the late Eocene and experienced similar topological and climate changes in the Himalayas-East Asia [Ilex exhibits clear geographic differentiation, while section Cyclobalanopsis does not. As discussed above, this may be partially explained by selective sweeps, which affect the chloroplast genome of section Cyclobalanopsis and results rapid migration of selected haplotypes. However, varying adaptive traits, e.g. reproductive capacity and seed dispersal distance may account for their different spatial genetic structure. The geographic distribution of section Cyclobalanopsis is mostly concentrated in low to middle elevation montane areas with rugged topography [Ilex inhabit highly fragmented landscapes, e.g. sky-island such as subalpine areas or river gorges in mountains [Cyclobalanopsis and Ilex have different life-forms and tradeoffs between vegetative and reproductive growth. For example, most species of section Ilex are smaller trees and shrubs, and produce fewer seeds than species of section Cyclobalanopsis [Ilex than in section Cyclobalanopsis, and more influenced by both local adaptation and genetic drift, thus increasing their genetic spatial structure.In addition, adaptive traits can induce varying responses to similar environment changes. Several species of section ast Asia , 73. Howpography . Therefoountains , which dlanopsis , and havQuercus does not always match the pattern of nuclear genetic diversity. Section Cyclobalanopsis has high species richness [Cyclobalanopsis is very low and could not be predicted by climatic factors. While, the spatial phylogenetic structures of sections Ilex and Quercus were confirmed by nuclear DNA. Based on RADseq nuclear markers, the species of sections Ilex from Mediterranean-Himalaya formed a monophyletic clade, though species from Sino-Himalaya and Sino-Japan mixed together [r2 = 0.311, p < 0.002) [The plastome genetic diversity pattern of richness , 113, whtogether . Eurasiatogether , 114. Fu< 0.002) .Although nuclear genetic variation may show some similarity to plastome markers, they had very different evolution histories. The chloroplast is maternally inherited in oaks, and can only be transferred through seeds , while nCyclobalanopsis, Ilex, and Quercus, as manifest by their chloroplast diversity. The results highlight the importance of geological events and ecological adaptive capacity for the spatial genetic pattern of oak clades and provides detailed insights into the formation mechanism of their contemporary diversity. Further insights into the divergence history of this groups will originate from a combination of whole-chloroplast sequencing and nuclear genetic data of deeper population sampling. Finally, association mapping can be used to investigate the relationship between genetic polymorphisms and environment, which will help to identify the relative effects of the climatic, edaphic variation, and migration history on genetic variation in multiple clades.This study clarifies the individual diversification history of the sections Quercus section Cyclobalanopsis from China, Japan, Vietnam and Nepal as well as 121 individuals of 28 species of section Ilex from China, Himalayas, Azerbaijan, and Mediterranean. One individual of Lithocarpus henryi was used as outgroup to root the tree of genus Quercus. These data were obtained from our previous study [atpI-atpH, matK, psbA-trnH and ycf1. Eighty-nine individuals from 27 species of section Quercus from Eurasia and North America were included in this study. Among these, seven individuals of the six species were obtained from our previous study [cpDNA regions were aligned using Muscle [http://www.megasoftware.net/) and the extra end of long sequences were trimmed. An inversion of 60 bp found in the psbA-trnH region was replaced with its reverse complement . Relevant data on samples and sequences used in this study are included in the additional file . Genetic distances were calculated in GenAlEx 6.5 [D, Fu and Li’s D, Fu and Li’s F and Fay and Wu’s H) were conducted using DnaSP 5.10 [Haplotypes were extracted by using DnaSP 5.10 . GeneticA 7.0.21   to ensure effective sample size (ESS) exceeding 200. The first 15% of trees were discarded as burn-in. Phylogenetic trees were plotted on the world map using R package phytools [Bayesian trees were constructed using MrBayes 3.2.6 . The nucphytools .Cyclobalanopsis, Ilex and Quercus were obtained from our field collection database, Chinese Virtual Herbarium (http://www.cvh.ac.cn), Global Biodiversity Information Facility (https://www.gbif.org) and National Herbarium of the Netherlands . Additional geographic occurrence data were added from previous studies for section Cyclobalanopsis [Ilex [Quercus [Ilex and Quercus were uneven, which would have affect climate analysis. Therefore, the dense distribution records of sections Ilex and Quercus were filtered to ensure that the geographic records were even between main regions using the R packages raster [Ilex in west Europe retained only one occurrence record in each raster of 0.45 km × 0.45 km, but one record for each raster of 0.35 km × 0.35 km in SW China. The filtering resolution of section Quercus in Europe and North America retained one record in each raster of 0.04 km × 0.04 km. Records of each section were plotted on a map and the number of records were counted to ensure that the point densities were even between different regions.Georeferenced occurrence records were collected for each section from public specimen databases and the publications listed below and were augmented by our own collections. Data were initially cleaned by removing all records that were outside of published range records. Coordinates of these specimens were then used to extract 19 BIOCLIM variables from WorldClim 1.4: Current conditions (~ 1960–1990)  using thlanopsis –38, 130,is [Ilex , 47, 131[Quercus –134. Thes raster  and disms raster . The filMulticollinearity among 19 BIOCLIM variables was examined using a Pearson correlation matrix estimated in the R package psych . The subNonmetric multidimensional scaling (NMDS) was used on all 19 BIOCLIM variables to characterize the climatic niche for the three oak sections  and section Quercus (b).


Information on the distribution of genetic variation is essential to preserve olive germplasm from erosion and to recover alleles lost through selective breeding. In addition, knowledge on population structure and genotype–phenotype associations is crucial to support modern olive breeding programs that must respond to new environmental conditions imposed by climate change and novel biotic/abiotic stressors. To further our understanding of genetic variation in the olive, we performed genotype-by-sequencing on a panel of 94 Italian olive cultivars. A reference-based and a reference-independent SNP calling pipeline generated 22,088 and 8,088 high-quality SNPs, respectively. Both datasets were used to model population structure via parametric and non parametric clustering. Although the two pipelines yielded a 3-fold difference in the number of SNPs, both described wide genetic variability among our study panel and allowed individuals to be grouped based on fruit weight and the geographical area of cultivation. Multidimensional scaling analysis on identity-by-state allele-sharing values as well as inference of population mixtures from genome-wide allele frequency data corroborated the clustering pattern we observed. These findings allowed us to formulate hypotheses about geographical relationships of Italian olive cultivars and to confirm known and uncover novel cases of synonymy. Olea europaea L. subsp. europaea var. europaea) is believed to originate from the wild oleaster (Olea europaea L. subsp. europaea var. sylvestris) in the north Levant, a region corresponding to the modern Syrian-Turkish border4. It is still under debate whether independent domestication events have occurred in the Mediterranean basin or whether it represents a secondary olive diversification centre7.Cultivated olive tree 23.In addition to knowledge on genetic diversity, which is shaped by natural and human-derived processes, genotype-phenotype association is a key prerequisite to modern breeding programs. New challenges for olive breeding are related to (i) the increasing ecological impact of climate change and associated abiotic stresses and (ii) new or resurgent pests and diseases. Among the latter, the emergence of the bacterium 25. Different types of DNA markers, namely simple sequence repeats (SSRs)30, amplified fragment length polymorphism (AFLP)35 and single nucleotide polymorphisms (SNPs)38, have been till now used to dissect olive genetic variability.Morphological characterisation, traditionally used for the assessment of the genetic diversity across olive germplasm collections, has been recently paralleled by the use of molecular markers39.Compared to other types of DNA markers, SNPs have some advantageous features. They are common and found throughout the genome, stable (i.e. are less mutable), and readily assayed using high-throughput genotyping protocols and automated data analysis. Furthermore, adjacent SNPs in haplotype blocks that tend to be inherited together can be exploited in genetic dissection of complex traits42. In the last few years, GBS has been largely used in species with a reference genome to discover new SNP markers and to develop mapping populations45, to assess genome-wide diversity and linkage disequilibrium48, and to perform association mapping studies51.Recent progress in next-generation sequencing (NGS) has made SNP discovery cost-effective. Although SNP markers can be observed through various experimental protocols, at present, genotype-by-sequencing (GBS) is the most popular approach for SNP identification in plants54. Indeed, interesting studies have been successfully carried out in species lacking a reference genome such as switchgrass, oat, blackcurrant, hop, alfalfa and sugarcane59.Although GBS has been mostly applied to species with complete, near-complete or partial reference genomes, different SNP calling pipelines have been developed to apply GBS to species with limited genomic information52 have been performed in olive. These studies aimed at the construction of high-density genetic linkage maps as a resource for locating QTL (Quantitative trait loci) associated with agronomically important traits and for genome scaffolding61.To our knowledge, two studies based on GBS and on the reference-independent SNP calling pipeline Stacks62 and represents a diversity centre with more than 500 different cultivars grown across its territory63. This richness in biodiversity was well documented by Hatzopoulos, et al.64 and by Owen, et al.65, who described the wide genetic variability for a large number of bio-agronomic traits in Italian olive germplasm. We adopted two different SNP calling procedures: the first one is based on the TASSEL-GBS pipeline and on the partial O. europaea genome sequence released by Cruz, et al.66; the second relies on the reference-independent TASSEL Universal Network Enabled Analysis Kit (UNEAK) pipeline53. The extensive catalogue of SNPs we developed was used to (i) measure genetic variation and establish the relationships among all individuals across the population as independently assessed by a parametric (STRUCTURE67) and a non-parametric (AWclust68) population structure analysis software; (ii) resolve cases of synonymy in olive germplasm and (iii) formulate hypotheses about the geographical relationships and spread of olive cultivars on Italian territory.Herein, we describe the first genome-wide diversity study on a collection of 94 cultivars representative of Italian olive germplasm. Italy has the second-highest level of olive oil production in the WorldThe GBS analysis performed by Illumina sequencing generated ~247 M reads, on average 2.6 M reads per sample. GBS sequence tags were merged into a single master tag file including 1.4 M reads. Two SNP calling pipelines were run, namely TASSEL-UNEAK and TASSEL-GBS.loci was reduced to 8,088. In Fig. loci were heterozygous, whereas only 1.8% of missing data were observed  estimate was 0.134 between cluster C1u and C3u; 0.093 between cluster C1u and C2u and 0.104 between cluster C2u and C3u. The expected heterozygosity was 0.62, 0.84 and 0.72 within cluster C1u, C2u and C3u, respectively.STRUCTURE and Structure Harvester analyses indicated that the germplasm collection genotyped in this study could be divided into three clusters   and Iub (cultivars from Apulia).The dendrogram by AWclust displays two primary nodes and four clusters Fig. . Clusteru includes 28 cultivars and it is separated into two clades: IIua and IIub. Cultivars in clade IIua have drupes of medium weight (average of 2.84 g ± 0.86) and fall into distinct branches corresponding to different Italian regions. Clade IIub groups cultivars with small drupes (=1.65 g ± 0.28) typically cultivated in Calabria and in “Salento”, an area located in the South of Apulia region.Cluster IIu comprises 20 cultivars with the highest drupe weight (average  = 5.28 g ± 1.62), mainly cultivated in the two insular Italian regions. Finally, cluster IVu includes two clades for a total of 24 cultivars with drupes of medium weight (average of 3.44 g ± 0.99): IVua groups four varieties cultivated in Apulia , while IVub includes cultivars mainly cultivated in Sicily and Calabria.Cluster IIIThe one-way analysis of variance (ANOVA), that was used to determine whether there are any statistically significant differences between the means of drupe weight of cultivars in AWclust and STRUCTURE groups, confirms significant differences among the means  were transitions (Ti), with a Ti/Tv ratio of 1.82. The most and the least frequent substitutions were C→T (32.7%) and C→G (5.2%), respectively ; ~16.8% of SNPs were heterozygous and only 2.2% were the missing data , whereas a few loci were randomly selected in three different cultivars and were validated by PCR amplifications and Sanger sequencing. All the polymorphisms identified in silico were confirmed , we decided to divide the population under investigation into four sub-populations since this best fit with AWclust clustering. At qi ≥ 0.60, Giarraffa was the only accession included in the cluster C4r. Clusters C1r, C2r and C3r include 15, 12 and 2 varieties, respectively. Pair-wise fixation index (FST) estimated values were: 0.130 between cluster C2r and C1r, 0.184 between cluster C1r and C3r and 0.100 between cluster C2r and C3r.Structure Harvester indicated K = 6 as the optimal number of sub-populations for the germplasm collection, immediately followed by K = 4  cultivated in Apulia and Central Italy, respectively. Clusters IIIr (2.19 ± 0.81) and IVr (3.27 ± 0.90), comprising 24 and 26 cultivars, correspond to clusters IIu and IVu, respectively. Cluster Vr is clearly separated from the rest  allele-sharing values for all pair-wise comparisons using 22,088 unlinked SNPs. The frequency distribution of IBS estimates in Fig. Relationships among the 94 A multidimensional scaling (MDS) plot of genome-wide IBS pair-wise distances . TREEMIX was run on the dataset described above, with olive cultivars grouped into 4 arbitrary sub-populations  identified following population structure definition based on TASSEL-UNEAK SNP markers).The tree-based approach implemented in TREEMIXu and C4u (0.49) and C3u and C4u (0.28).Analysis of the TREEMIX log-likelihood values for 0 to 3 migrations revealed that the most predictive model (i.e. that had the highest log-likelihood) assumed the presence of 2 migration events  of 22,088 SNPs detected by TASSEL-GBS. Taking into account that these SNPs are located on more than 5,000 scaffolds that differ in size, LD decay was estimated considering only those SNP markers identified in the 30 longest scaffolds  and TASSEL-GBS (reference-based). Even if the current olive tree genome assembly is far from being chromosome-scaled 66 and despite the lack of a “gold standard” structural and functional annotation, we still used this reference genome for the de novo discovery of SNP markers via GBS. As expected, TASSEL-GBS outperformed TASSEL-UNEAK with respect to the number of high quality SNPs . The 3-fold difference in the number of SNPs could be influenced by the more stringent parameters used in absence of a reference genome53. Conversely, the mean depth of coverage, and the frequency of reference and effect  SNP alleles per cultivar were comparable between the pipelines  can be ascribed to (i) distance between DNA sequences that might have prevented read-to-genome-alignments especially when very stringent alignment parameters were used to minimize the number of multiple alignments; (ii) the incomplete nature of the reference genome; (iii) regions with lower quality sequences; (iv) presence of reads from organelle genomes.loci in individuals of the sample population, and a non-parametric distance-based hierarchical clustering, that it is based on a matrix of pair-wise allele sharing distances between all of the individuals in the dataset) to assess genetic diversity and establish relationships among individuals in the population under investigation. As previously discussed elsewhere, the two methods were found to corroborate each other remarkably well48.In this study we applied two complementary clustering methods  originate from a single ancestor node, which clearly separate them from the remaining cultivars with medium and low drupe weight. This finding suggests that the most important parameters which influenced clustering analysis are size and weight of the drupe. This assertion is consistent with results from previous studies, which indicates those as high heritability traits72.The first one affects olive cultivars with the highest drupe weight. They were assigned to distinct clusters with low overlap among their elements. However, when we examine the dendrogram developed on the basis of the SNPs identified by TASSEL-GBS, a significant clustering adjustment is observed. All olive cultivars with the highest drupe weight  including twenty-two varieties with comparable drupe weight (4–6 g.).This hypothesis is also supported by the second difference we observed in the clustering. This concerns the clusters to which Cerasuola and Grappolo, characterised by having a medium drupe weight, belong. Based on SNPs called by TASSEL-UNEAK, they unexpectedly grouped in cluster III74. In the dendrogram in Fig. u) that includes cultivars with medium drupe weight. Interestingly, the same sub-set is located into the cluster Ir , whose fruits are natural debittering on the tree during ripening Ir Fig. , where aAt first glance, STRUCTURE clustering may look less self-explaining than that made by AWclust. Going further in detail, population structure inferred by TASSEL-UNEAK SNP markers seems to be more profitable compared to that assessed by TASSEL-GBS, which includes a larger number of cultivars with a mosaic of allele frequencies (i.e. admixed ancestry).76 where diversification of cultivated olive tree mainly took place. Furthermore, we cannot ignore that the very high genetic variability in olive tree is especially due to its mating system. Olive tree is an allogamous wind-pollinated species to which self-incompatible cultivars belong77. This results in an increase of spontaneous crosses that give rise to olive genotypes with a spectrum of allele frequencies derived from ancestors78. Several studies have documented genetic admixture on a local or large scale in olive tree given the out-crossing nature of O. europaea18. Indeed, gene flow between wild and domesticate forms has been hypothesized to have shaped olive genetic diversity across the Mediterranean basin28.The fact that SNPs called by TASSEL-GBS and by TASSEL-UNEAK return several admixed genotypes reveals that Italian olive germplasm has accumulated high level of variability over the centuries. This is supported by the fact that Italy is located in the middle of the Mediterranean basin that is considered a hybrid area between the Eastern and Western zones79.Many studies based on a small number of SSR and AFLP markers have been carried out to identify synonyms and/or homonyms among Italian olive cultivars, although they do not unequivocally clarify the existing genetic relationships32, while others were uncovered here for the first time  it is possible to distinguish several cases of synonymy among the individuals that draws most of their genetic ancestry from different populations. For all these cases, varieties are cultivated in confined geographical areas and it is possible that original names were altered in accordance with local dialects. Interestingly, by fixing qi ≥ 0.97 we observed the following two cases of synonymies: (i) Cima di Mola, Bottoni di Gallo and Mignola (qi = 0.98); (ii) Ogliarola barese, Taggiasca and Frantoio (qi = 1). In both cases, synonymies are certainly not attributable to varieties cultivated in narrow geographical areas. It is well known that genetic improvement of olive is also characterised by vegetative propagation of the most valuable individuals80.Pair-wise clustering based on IBS as well as allele frequency estimates suggests the occurrence of several cases of synonymy. Many of them have been already described in previous studies based on morphological traits and molecular markers83.With this in mind, we can speculate that some individuals were vegetative propagated by cuttings or clonal propagation and were disseminated by human migrations across the Italian peninsula disregarding the cultivar name. It must however be stressed that cultivars genetically indistinguishable from others could be phenotypically different. This is not surprising since variations in light, altitude, soil composition and water availability could completely change the physiological and morphological aspect of the olive plantThe results we obtained by using SNPs called by TASSEL-GBS and TASSEL-UNEAK and applying two complementary methods for the estimation of genetic diversity indicated a clear and consistent subdivision of the cultivars under investigation into three main groups.r or Iua) and Central Italy (IIr or Iub) that may have evolved from a common ancestor population.This finding, together with data on patterns of population splits and mixtures, allowed us to formulate hypotheses about the geographical relationships, dissemination and diversification of olive cultivars in Italy. Given the above, we distinguished a sub-population that includes cultivars from Apulia  was observed. The MDS plot of genome-wide IBS pair-wise distances shows that members of the cluster Ir and IVr (i.e admixed genotypes) are scattered in the multidimensional space. On the basis of these further evidences we can state that C1u represents a relatively closed gene pool that exchanged genetic material through inter-breeding with other varieties cultivated in Italy.Fu population originated from local oleasters intermixed with feral forms and has spread to different Italian regions over time.This hypothesis is supported by Baldoni, et al.9, who investigated the genetic relationships among wild types and cultivars collected from three Italian regions: Umbria, Sicily and Sardinia.Most likely, the C1et al.84 reported that the modern Italian olive cultivars, localized in Central Italy, could derive from the hybridization between cv. Leccino and Dritta di Loreto with ancestral genotypes. Finally, Muzzalupo, et al.12 pointed out a high level of gene flow from the varieties cultivated in Central Italy and the others spread throughout the Italian territory.The authors concluded that Umbrian cultivars have mainly originated by selection from local oleasters. Interestingly, these cultivars are widely disseminated in the regions of north, central and southern Italy and this suggest their ancient origin. Albertini, r or IIIu) includes cultivars mainly from Sicily and Sardinia. We proved that these cultivars never exchanged genetic material with the remaining varieties under investigation. The close relationship between the pools of the two islands suggests that they did not originated from local oleasters but most likely have been introduced into these regions from the outside9. This hypothesis is supported by Las Casas, et al.79, who assessed the genetic diversity of olive cultivars from Sicily  and other countries of Mediterranean basin. The authors highlighted that Sicilian cultivars clearly separate from other Italian varieties but were grouped with cultivars from Spain and Marocco. Indeed, historical and cultural relationships between Catalan and Sardinian and Sicilian cultures are well known85 as well as trading contacts between Italian insular regions and Phoenicians.The second sub-population (Cluster Vr or IIu) could derive from a common ancestor from Magno-Greek origin, since all the cultivars in this sub-population are cultivated in Southern Italy, that was colonized by the Greeks in the eighth century BC86. In particular, two sub-clusters can be identified: cluster IIIra or IIua and IIIrb or IIub refer to the area of Ionic and Doric influence, respectively. Within the Doric group are cultivars from Salento (Cellina di Nardò) and Calabria (Sinopolese e Ottobratica). All are characterised by small drupes and monumental trees and are subjected to the same cropping system87.The third sub-population  and the Magno-Greek colonies1, I2, I3. I1 represents most of the Italiote cultivars with admixed ancestry; I2 consists of cultivars of Catalan origin and I3 includes most of the cultivars of Magno-Greek origin , while lines E2/E3 consist of varieties from the Western and Central Mediterranean. A further study based on SSR markers highlighted the existence of three genetic groups of olive cultivars in the Mediterranean basin 18. Q3 includes cultivars subjected to the first event of domestication occurred in North Levant (which corresponds to line E1), followed by a secondary independent event of domestication in central Mediterranean basin (Q2). Notably, Q2 (which corresponds to lines E2/E3) is a product of admixture between the set of Eastern domesticates (Q3) and Western oleasters. A close genetic relationship between cultivars in Southern Spain (Q1) and the feral forms from the Eastern was observed.According to Besnard The scenario just outlined for the population under investigation, although supported by different methods of analysis and by literature on the subject, may serve as working hypothesis for subsequent studies.38 as well as in other fruit crops90. The low extension of LD may be probably due to the self-incompatibility of several olive cultivars: the higher the level of heterozygosity is, then the lower the LD that is counterbalanced by the increasing number of recombination events.Herein, we evaluated the extent of LD decay and found that the rapid LD decay inferred by this study is consistent with previous estimates in oliveAlthough our work overlaps to some extent previous studies based on a limited number of AFLP, SSR and SNP markers, we provided much more precise indications on genetic similarity among the cultivars in the germplasm collection thanks to a large genome-wide SNP panel. Indeed, we were able to capture genetic variability at an unprecedented level of detail. This, in turn, allowed pairs of cultivars that look very similar to each other (cases of synonymy) to be identified based on identity-by-state (IBS) computation.In total agreement with previous studies, we corroborated the evidence that the geographical area of cultivation is a driving force for genetic clustering. The novelty that emerges when allele-frequency distribution histograms by STRUCTURE and dendrograms by AWclust are taken into account is that olive drupe weight plays a major role in structuring genetic diversity in olive.Finally, we believe that the genome-wide SNP panel we generated and released to the public will be valuable for future genome-wide association studies.Olea europaea L. var. sativa olive cultivars . Olive trees were spaced with a regular planting pattern of 4 × 6 m. Drupe weight (g) in Supplementary Table A panel of 94 91 with minor modifications as follow: after re-suspension in TE 0.1X, 2 volumes of CIA 24:1 were added to the mixture, then 2.5 volumes of 100% ethanol and 1/10 volume of sodium acetate 3 M pH 5.2 were added to force DNA precipitation. DNA quality and concentration were checked by agarose gel 0.8% and Qubit 3.0 fluorometer .Such germplasm is considered diverse on a regional scale since each region has gradually selected varieties adapted to environmental, agronomic, cultural and traditional features of the site. With this in mind, the 94 cultivars were selected so that they could represent the whole genetic diversity and phenotypic variability of the original collection. Genomic DNA was extracted from young leaves using the protocol described by Doyleet al.48 using the EcoT22I restriction enzyme. Two different pipelines were run for SNP calling: the reference-independent TASSEL-UNEAK pipeline53 and the reference-based TASSEL-GBS pipeline92. In the TASSEL-GBS pipeline, master tags (i.e. collapsed sequence tags from each sequence file) were aligned along the olive tree reference genome available at http://denovo.cnag.cat/genomes/olive/download/Oe6/Oe6.scaffolds.fa.gz66 using the Burrows-Wheeler Aligner tool (version 0.7.8-r455) with default settings.Genotyping-by-sequencing was performed as described by Taranto, 93;] with the following parameters: minimum allele frequency (MAF) ≥0.05, max-missing = 0.90, Hardy-Weinberg Equilibrium (hwe) = p ≤ 0.001 and min-mean depth = 5. Single nucleotide InDels were removed. VCFtools were also used to generate various statistics on the dataset under investigation and to add gene annotations to VCF files.Both pipelines produced a VCF file that was subjected to a filtering procedure using VCFtools [version 0.1.13loci were selected in three cultivars  for validation by PCR amplifications and Sanger sequencing  (see Supplementary Table locus was extracted and Oligo Explorer 1.2 (http://www.genelink.com/tools/gl-oe.asp) was employed to guide primer design (see Supplementary Table Ten SNP www.goldenhelix.com). LD decay across the genome was evaluated considering the SNPs of the 30 longest scaffolds (see Supplementary Table Linkage disequilibrium (LD) was calculated on the SNP dataset derived from the TASSEL-GBS pipeline using the SNP & Variation Suite software  ten independent runs were performed applying the admixture model, set a Markov chain Monte Carlo of 100,000 burn-in phases followed by 100,000 iterations. The optimal K value was estimated using Structure Harvester94. Cultivars having a membership coefficient (qi) ≥0.60 were clustered, while varieties with qi < 0.60 at each assigned K were considered as admixed. To determine the level of differentiation among sub-populations, we calculated the fixation index (FST) among all possible pair-wise combinations using SVS.As the STRUCTURE algorithm assumes independent 95. Pair-wise IBS allele-sharing estimates among olive tree samples were calculated using PLINK96 v1.90b5.2 and graphically represented by MDS plot. TREEMIX69 was used to infer patterns of population mixtures and to test the presence of gene flow among olive sub-populations. A variable number of migration events (M) ranging from 0 to 10 was tested and the value of M that had the highest log-likelihood was selected as the most predictive model.AWclust was also used to generate a matrix of pair-wise allele sharing distances (ADS) between all individuals in the dataset and to infer population structure. Gap statistic was employed to calculate the optimal number of groups (K) based on sample genetic relatednessThe MSTAT-C package (1983) was used to perform a one-way analysis of variance (ANOVA) in order to determine whether there are any statistically significant differences between the means of drupe weight of cultivars in AWclust and STRUCTURE groups.Supplementary tables, figures and filesSupplementary File S1Supplementary File S2


Many species occur across environmental gradients and it is expected that these species will exhibit some signals of adaptation as heterogeneous environments and localized gene flow may facilitate local adaptation. While riparian zones can cross climate gradients, many of which are being impacted by climate change, they also create microclimates for the vegetation, reducing environmental heterogeneity. Species with differing distributions in these environments provide an opportunity to investigate the importance of genetic connectivity in influencing signals of adaptation over relatively short geographical distance. Association analysis with genomic data was used to compare signals of selection to climate variables in two species that have differing distributions along a river traversing a climate gradient. Results demonstrate links between connectivity, standing genetic variation, and the development of signals of selection. In the restricted species, the combination of high gene flow in the middle and lower catchment and occurrence in a microclimate created along riverbanks likely mitigated the development of selection to most climatic variables. In contrast the more widely distributed species with low gene flow showed a stronger signal of selection. Together these results strengthen our knowledge of the drivers and scale of adaptation and reinforce the importance of connectivity across a landscape to maintain adaptive potential of plant species. Global climate change is predicted to lead to changes in local climate, particularly changes in temperature and precipitation . ClimateEcological resilience of ecosystems under a changing climate is likely to encompass both adaptation and plasticity in species . The patAcross environmental gradients, populations at the range edge currently adapted to warmer drier climates may harbor crucial genes for persistence under these conditions, and functional connectivity between these and central populations will be critical to allow for the migration of adapted genes as climate changes . HabitatCornus florida), also found adaptation to climate variables in a species with high gene flow. Similar studies over moderate distances have shown signals of both adaptation and plasticity in three eucalypt species with high gene flow that occupy semi-arid to arid environments in eastern and western Australia . T. T44]. TAstartea leptophylla and C. lanceolata are native to south-western Australia and occur within the Warren River catchment. Astartea leptophylla is a shrub that grows to 5 m tall while C. lanceolata is a tree or shrub that grows to 8 m tall [A. leptophylla dispersed via water and wind, and seed of C. lanceolata dispersed by gravity. Astartea leptophylla is restricted to the banks of rivers that are fast-flowing during the wet winter season [C. lanceolata is widespread, generally found in wet areas or along water courses but is not restricted to rivers. Astartea leptophylla has high gene flow and low genetic structure consistent with having a continuous distribution along the river bank [Callistachys lanceolata has high genetic structure and restricted gene flow, which is also consistent with its more patchy distribution and gravity dispersed seed [Astartea leptophylla is also impacted by habitat fragmentation at the north-eastern extent of its range within the catchment. As A. leptophylla is restricted to the major water flow systems, sampling for this species occurred along the main Warren River and its tributary the Tone River, where 12 sites were sampled . To reduce redundancy and minimize high correlations, the R package USDM 1.1-18 [C. lanceolata; this removed 22 variables, leaving nine variables for temperature (3), precipitation (3), moisture (2), and radiation (1). The values for variables for each site are listed in the A. leptophylla, although all variables for A. leptophylla were highly correlated. Environmental variable values for thirty-one bioclimatic variables for each population were retrieved from the Atlas of Living Australia , each run was 100,000, with a burnin of 50,000 and 30 pilot runs of 5000, this was repeated four times, and the mean of the four runs was taken to create the neutral covariance matrix. The auxiliary model was run using the neutral covariance matrix and the nine environmental variables. Each run was 100,000, with a burnin of 50,000 and 30 pilot runs of 5000, and this was repeated four times and the mean of the four runs was taken as the final results. Correlations with a Bayes factor of more than 20 were considered to have strong evidence for associations (as proposed in Kass and Raftery 1995) [ry 1995) , as the adegenet 2.1.1 [Poppr 2.8.1 [Hierfstat 0.04-22 [pophelper 2.2.9 [ST value were estimated using the R package hierfstat 0.04-22 [The data obtained in this study used newer sequencing methods that have been developed and refined since the earlier analysis of genetic structure in these species  and was et 2.1.1 , Poppr 2pr 2.8.1 , and Hie 0.04-22  packages 0.04-22  using ther 2.2.9  was used 0.04-22 .A. leptophylla and C. lanceolate, respectively. Further filtering to remove loci and samples with high proportions of missing data including loci with minor allele frequencies below 2%, resulted in a final SNP dataset for further analysis consisting of 11,769 SNPs for A. leptophylla and 5,331 SNPs for C. lanceolata. Outlier analysis in BayPass identified 357 directional and 366 balancing SNPs for A. leptophylla and 134 directional and 111 balancing SNPs for C. lanceolata. Removing these outlier SNPs from the full dataset resulted in neutral datasets with 10,581 and 4887 SNPs for A. leptophylla and C. lanceolate, respectively.The results from the DArT pipeline analysis resulted in 93,076 and 16,542 SNPs for A. leptophylla that had pairwise population FST values from 0.01 to 0.078, compared to values for C. lanceolata that ranged from 0.039 to 0.417. Populations of A. leptophylla in the upper catchment  showed higher differentiation, both among populations in the upper catchment and between these populations and those in the middle and lower catchment  from the remaining populations  than in the previous study but still showed high admixture among populations, particularly in populations in the lower and middle catchment  were with two environmental variables, radiation of the driest quarter, and moisture index of the coldest quarter, and only small numbers of correlations with other environmental variables , precipitation of the driest period (13), seasonality of precipitation (13), and mean temperature of the driest quarter (11), all variables related to water availability . This may indicate that climatic conditions at the extreme dry end of the range are a limiting factor in the distribution of the species, and therefore predicted climatic shifts will reduce suitable habitat for this species. While C. lanceolata occurs across a narrower annual rainfall range than A. leptophylla, it is not as restricted in its habitat niche, occurring in wet areas but not restricted to riverbanks. Greater isolation and less connectivity among populations is likely to limit the natural flow of genes adapted to the predicted drier and hotter climates. Thus, assisted gene migration/climate-adjusted provenancing [enancing ,11 wouldA. leptophylla, while those environmental variables with a strong selection pressure have formed signals of selection due to the isolation and reduced geneflow of sites in the upper catchment. In contrast, the less specific habitat requirement of C. lanceolata combined with low gene flow and higher standing genetic variation was consistent with conditions allowing development of selection to bioclimatic variables. While it is difficult to control environmental factors, our study on two species with differing levels of connectivity across the same climate gradient has provided the opportunity to test the interaction between genetic connectivity and signals of selection. These findings extend our current understanding on the factors that influence selection across climate gradients, confirming that gene flow influences with signatures of selection. These results also verify the need for management strategies that support genetic connectivity and, when needed, intervention to assist migration of genes to maximize the resilience of populations and species persistence in the face of changing climates.Differing gene flow, standing genetic variation, and habitat context in the two species studied here suggest patterns of signals of selection consistent with theoretical predictions of the effects of genetic connectivity on adaptation. The combination of riparian microclimate, higher levels of connectivity, and low standing genetic variation mitigated the development of selection in most environmental variables for


Aegilops tauschii and tetraploid wheat (Triticum turgidum) into common wheat (T. aestivum). The objective of this study was to evaluate 149 SHW lines and their 74 tetraploid parents for their genetic diversity, breeding values and inter-genomic interactions for resistance to Fusarium head blight (FHB). The genetic diversity analysis was performed based on the population structure established using 4,674 and 3,330 polymorphic SNP markers among the SHW lines and tetraploid parents, respectively. The results showed that all T. carthlicum and most T. dicoccum accessions formed different clusters and subpopulations, respectively, whereas all the T. durum, T. polonicum, T. turgidum, and T. turanicum accessions were clustered together, suggesting that T. durum was more closely related to T. polonicum, T. turgidum, and T. turanicum than to T. dicoccum. The genetic diversity of the SHW lines mainly reflected that of the tetraploid parents. The SHW lines and their tetraploid parents were evaluated for reactions to FHB in two greenhouse seasons and at two field nurseries for 2 years. As expected, most of the SHW lines were more resistant than their tetraploid parents in all environments. The FHB severities of the SHW lines varied greatly depending on the Ae. tauschii and tetraploid genotypes involved. Most of the SHW lines with a high level of FHB resistance were generally derived from the tetraploid accessions with a high level of FHB resistance. Among the 149 SHW lines, 140 were developed by using three Ae. tauschii accessions CIae 26, PI 268210, and RL 5286. These SHW lines showed FHB severities reduced by 21.7%, 17.3%, and 11.5%, respectively, with an average reduction of 18.3%, as compared to the tetraploid parents, suggesting that the D genome may play a major role in reducing disease severity in the SHW lines. Thirteen SHW lines consistently showed a high level of FHB resistance compared to the resistant check, Sumai 3, in each environment. These SHW lines will be useful for the development of FHB-resistant wheat germplasm and populations for discovery of novel FHB resistance genes.Synthetic hexaploid wheat (SHW) can serve as a bridge for the transfer of useful genes from  Triticum turgidum L. ssp. durum (Desf.) Husn., 2n = 4x = 28, AABB] and common wheat  in the humid and semi-humid wheat-growing areas of the world (Fusarium graminearum Schwabe [teleomorph Gibberella zeae (Schw.) Petch.] in North America, can lead to severe losses not only in grain yield but also in quality. Mycotoxins, the secondary metabolites of this pathogen, make the harvested grain unsuitable for consumption as food or feed (Fhb1), 5AS (Qfhs.ifa-5A), 5AL (Qfhb.rwg-5A.2), and 6BS (Fhb2) from common wheat ‘Sumai 3’ and PI 277012 (see reviewed by Fusarium head blight (FHB), also known as scab, is a destructive disease of durum wheat  and Ae. tauschii have been considered as invaluable genetic resources for wheat improvement  . Since the 1940s, over 1,500 SHW lines have been developed and a large number of the SHW lines have been identified to exhibit resistance to major wheat diseases  and insects (Hessian fly and greenbug) and tolerance to abiotic stresses  as well as novel grain yield and quality traits  parents were used in genetic diversity analysis and evaluation for resistance to FHB. These SHW lines were developed from crossing 10 Ae. tauschii accessions to 74 tetraploid wheat accessions belonging to durum wheat and five other tetraploid wheat subspecies . The accession or line numbers and sources of the tetraploid wheat and Ae. tauschii accessions are listed in Supplementary Table Ae. tauschii accessions, four  and six  were classified as subspecies strangulata and tauschii, respectively. Three  of the Ae. tauschii accessions were used as the parents of 140 (94%) SHW lines. Except for seven durum ‘Langdon’-derived SHW lines  developed by Dr. L. R. Joppa  with the 74 tetraploid wheat accessions.A total of 149 SHW lines and their tetraploid wheat  was applied to assess genetic diversity and was calculated for single loci ask is the total number of alleles detected for a given marker locus and iP is the frequency of the i-th allele in the set of genotypes investigated (p2+ q2) formula was used, where p and q denote the frequencies of the two alleles  in TASSEL4  and clusT. dicoccum PI 272572) was not evaluated because of the low germination rate. In the field and greenhouse evaluation experiments, common wheat varieties ‘Sumai 3’ and ‘Grandin’ were used as resistant and susceptible checks, respectively. In greenhouse experiments, a total of 224 genotypes  were evaluated in two seasons in winter 2015 and 2016, respectively, using a randomized complete block design (RCBD) with three replicates. Each genotype was planted in a plastic pot (16.2 × 18.4 cm) with four seeds for each genotype per replicate. Therefore, a total of 12 plants per genotype were evaluated for most of the lines in each greenhouse experiment. The greenhouse settings for photoperiod and temperature were 16 h and 22°C, respectively. The inoculum was prepared at a concentration of 50,000 spores mL-1 from three strains of pathogenic F. graminearum. For inoculation, 10 μL of inoculum was injected into a single central spikelet near the center of each spike at anthesis as described by Evaluation experiments were performed for evaluating Type II resistance (resistance to spread in the spike) in both greenhouse condition and field nurseries based on the well-established procedures for plant culture, inoculation, and disease scoring as described by F. graminearum strains, including 10 3ADON  producers and 10 15ADON  producers, collected from the field in North Dakota , until about 14 days after anthesis of most the genotypes. Ten spikes for each line were individually examined at 21 days post anthesis as the number of infected spikelets per spike using a visual scale: 0 = no spikelets infected, 100 = all spikelets infected based on the method of In the field experiments, the plant materials were planted in mist-irrigated nurseries using a RCBD with three replicates at two locations  in the summers of 2015 and 2016. Each genotype was planted in a hill plot with 15 seeds. Inoculum was prepared using the grain spawn inoculation method, in which autoclaved corn seeds were infected with a mixture of spores produced separately from 20 h Dakota . At the Plant height (PH) data were collected in the field experiments, and days to flowering (DTF) data were collected in the field and greenhouse experiments to determine the correlation of these traits with FHB disease severity. PH was measured from the ground surface to the top of the spike excluding the awns. DTF was calculated from January 1 in the greenhouse experiments, and in the field experiments it was calculated from July 1 in 2015 and from June 20 in 2016 when 50% of spikes in a hill were flowering.2 across environments = 1 - (MSG×E/MSG), where MSG×E was mean square genotype × environment; and MSG was mean square genotype.All the statistical analyses were performed separately using evaluation data from hexaploid entries (SHW lines and checks), the tetraploid wheat parents, and the two groups combined. Descriptive statistics were calculated using the software JMP Genomics 7 . A normality test for distribution of disease severity was performed using Shapiro-Wilk under the “Goodness of Fit” option using the same program. Bartlett’s test under the general linear model (GLM) procedure was used to test homogeneity of disease severity variances among the experiments using SAS program version 9.4 (SAS Institute). The reduction in FHB severity in the SHW lines was calculated as the difference in FHB severity between the SHW lines and their respective tetraploid parents. To determine the significance of the reduction, the least significant difference (LSD) value was used. Correlation coefficients between disease severity and PH or DTF were calculated using the PROC CORR procedure (SAS Institute). The same procedure was used to calculate the correlation coefficients between the disease severity of SHW lines and their tetraploid parents. To test homogeneity of PH and DTF data, Levene’s test was used under the GLM procedure (SAS Institute). Broad sense heritability was estimated across environments according to A total of 4,674 SNP markers that were polymorphic among the SHW lines were mapped based on the consensus map previously produced by T. dicoccum accession (PI 352548-1) and all 21 T. carthlicum accessions. Cluster 2 consisted of 50 individuals  may be an outlier, as it did not share similarity with any of the tetraploid lines  were grouped into the SHW cluster 2  were not evaluated in the field experiments in 2015 due to low germination rate. The Bartlett’s test for disease severity variances showed heterogeneity across the two greenhouse seasons and the 2 years of field experiment at two locations . However, the data from the field tests showed homogeneity between the two locations in each year , as well as between the two greenhouse experiments . Therefore, the disease severity data from the two greenhouse experiments (FHBGH) as well as from the field experiments within each year (FHB15 and FHB16) were combined. Thus, these three sets of FHB severity data were used in the subsequent statistical analyses. In addition, the overall mean of disease severity from all the experiments is presented in Supplementary Table The 149 SHW lines and their 73 tetraploid parents, together with the two hexaploid checks (Sumai 3 and Grandin), were evaluated for reactions to FHB in two greenhouse seasons and two field nurseries (Fargo and Prosper) in 2 years (Supplementary Table 2) values were 0.70, 0.85 and 0.64 among experiments in FHB15, FHB16 and FHBGH, respectively  Table . The susP = 0.05) from Sumai 3 in all three environments in which they were successfully evaluated. Among these SHW lines, eight (61.5%) were derived from the crosses involving Ae. tauschii CIae 26, suggesting that Ae. tauschii CIae 26 may carry FHB resistance QTL. Three resistant SHW lines SW91, SW92, and SW93 were derived from T. dicoccum CItr 14133-1 crossed with three Ae. tauschii accessions, indicating that CItr 14133-1 may carry FHB resistance QTL. In fact, CItr 14133-1 showed a high level of FHB resistance in the field conditions with 8.1% and 7.1% disease severities in FHB15 and FHB16, respectively. Similarly, two T. dicoccum accessions PI 191091 and T. dicoccum PI 272527 showed a high level of resistance comparable to Sumai 3 in all the environments. In particular, PI 272527 had the highest level of FHB resistance among all the tetraploid accessions and SHW lines evaluated in this study, with disease severities being 3.4%, 9.8%, and 8.5% in FHB15, FHB16, and FHBGH, respectively. The two SHW lines SW187 and SW188 derived from PI 272527 also had low disease severities.Several resistant genotypes were identified in the field as well as in the greenhouse. Among the 25 most FHB-resistant SHW lines listed in Table P < 0.1437, df = 3), therefore all the experiments were combined for further analyses. The tetraploid parents showed a wide variation in PH, ranging from 67.5 to 130.0 cm, whereas the SHW lines ranged from 73.8 to 108.9 cm , whereas the DTF data from field experiments were heterogeneous  and were analyzed separately in the further analyses. The plants started flowering early in 2016  due to the warm weather in May and June. However, the flowering period was longer in 2016  than in 2015, when the flowering started later  and took a shorter period (26 in Fargo and 24 days in Prosper) (Table The Levene’s test for PH showed homogeneity of error variances across the field experiments (cm Table . The DTFr) Table . Analyzir = -0.273 and -0.226, P < 0.001), indicating that the shorter plants had higher disease severities . Also, the plants that flowered later showed lower disease severity in the field experiments, except in the experiment at the Fargo location in 2016. The PH and DTF did not influence the FHB severity in the greenhouse experiments. Significant correlations were detected among DTF and FHB data collected in various environmental conditions (Supplementary Table The Pearson’s correlation coefficients between FHB severity and PH were significant in the field experiments (P < 0.05)  Table . The FHBP < 0.05) over their tetraploid wheat parents were 24 (16.6%), 108 (73.0%), and 98 (66.2%) in FHB15, FHB16, and FHBGH, respectively. On the contrary, there were only 14 (9.7%), 1 (0.7%), and 1 (0.7%) SHW lines having significant increases (P < 0.05) of FHB severities over their tetraploid parents in FHB15, FHB16, and FHBGH, respectively. Because most of these SHW lines were derived from FHB-susceptible tetraploid parents, the significantly higher FHB severities of these SHW lines were mainly caused by unusually low FHB severities of their tetraploid parents. For example, T. carthlicum PI 94751 had FHB severities 72.6% in FHB16 and 56.8% in FHBGH, however, it had FHB severity only 13.7% in FHB15. An FHB-susceptible genotype can occasionally exhibit a resistant reaction with low FHB severity, which might result from unfavorable environmental conditions for disease development or escape of inoculation. This phenomenon commonly occurs in the field FHB evaluation, especially in highly variable weather conditions.A comparison of FHB severities between individual SHW lines and their respective tetraploid parents showed that most SHW lines had lower FHB disease severities than their tetraploid wheat parents, especially under environments with high disease pressures  were grouped by their tetraploid subspecies and Ae. tauschii accessions (Table T. durum (27.6%), T. polonicum (55.5%), T. turgidum (45.2%), and T. turanicum (51.4%), whereas low levels of FHB severity reductions were observed in the SHW lines derived from T. dicoccum (16.0%) and T. carthlicum (11.0%). Similarly, different Ae. tauschii genotypes also affected the FHB severities of the SHW lines. Across the six tetraploid subspecies, the three Ae. tauschii accessions CIae 26, PI 268210, and RL 5286 resulted in 21.7%, 17.3%, and 11.5% of the FHB severity reduction in their SHW lines, respectively (Table T. turanicum accessions crossed with Ae. tauschii PI 268210 (69.0%) and CIae 26 (67.4%), and T. polonicum (66.7%) and T. durum (65.1%) accessions crossed with Ae. tauschii CIae 26 (data not shown). For all the SHW lines, there was an overall average of 18.3% FHB severity reduction compared with their tetraploid wheat parents  decreased their disease severities by 18.3%, suggesting that either the D genome or the increased ploidy level reduced the disease severity in the SHW lines. The data from our experiment provide some evidence to support the hypothesis  and TA 2377, were evaluated for FHB resistance by Ae. tauschii parents were not evaluated in our study, we cannot determine if the FHB severities of the SHW lines were associated with those of their Ae. tauschii parents. Therefore, further studies are needed to elucidate the relationships of FHB resistance between SHW lines and their Ae. tauschii parents by evaluating the SHW lines along with their Ae. tauschii parents.The evaluation data showed that the FHB severities of the SHW lines varied greatly with different ly Table . Becauser = 0.412, p < 0.001) and greenhouse  , whereas those SHW lines derived from the T. dicoccum and T. carthlicum had low levels of reductions in FHB severity   and greenhouse (FHBGH), respectively. However, only a 3.3% reduction was observed under low FHB pressure in the field nurseries in 2015 (FHB15), mostly because the low FHB severities in the field conditions in 2015 reduced the differences between the tetraploids and the SHW lines. This observation is in line with the fact that modern durum crop is more susceptible than bread wheat under the environments with high FHB pressures.In addition to T. turgidum, T. durum, T. carthlicum, T. paleocolchicum, T. turanicum, and T. polonicum using simple sequence repeat (SSR) markers and grouped T. durum, T. turgidum and T. polonicum into the same cluster in their experiment. T. dicoccum accessions from T. durum accessions by principal coordinate analyses. In our study, we found that accessions from T. durum, T. polonicum, T. turanicum, and T. turgidum formed a subpopulation, whereas all T. carthlicum and most T. dicoccum accessions formed two different clusters. Genetic diversity of the SHW lines in our study clearly reflected that of the tetraploid wheat parents. Therefore, these SHW lines represent a unique genetic resource by preserving the high level of genetic diversity from their tetraploid parents.T. dicoccum and 15 Ae. tauschii parental accessions using amplified fragment length polymorphism (AFLP) markers. They also found that the genetic diversity of the SHW lines was associated with the T. dicoccum parents rather than their Ae. tauschii parents. Ae. tauschii parents. Among the 10 Ae. tauschii accessions used in our study, four and six belong to the subspecies strangulata and tauschii, respectively. The fact that genetic diversity of the SHW lines was not related to the Ae. tauschii parents in our study is likely due to the paucity of molecular markers on the D genome because there are approximately ninefold less markers for the D genome than for the A and B genomes.Use of association mapping analysis to identify FHB resistance genes/QTL in both SHW and tetraploid populations was attempted. However, no associations of markers with significant effects on FHB resistance were detected in either the SHW population or the tetraploid genotypes. This is likely due to the low number of SHW lines used and/or the low frequency of resistance genes and alleles present in the populations. Nonetheless, the results from this study might provide guidance in selecting SHW lines for development of mapping populations to identify FHB resistance genes/QTL using linkage analysis. The SHW lines showing high levels of resistance in all environments, such as SW87, SW162, SW252, SW253, and SW261, might be suitable parents for future development of mapping populations for QTL analysis of FHB resistance.SX and SC initiated and planned this study. AS-H, SC, SX, QZ, SZ, TF, and EE conducted the FHB evaluations in field nurseries and greenhouse. AS-H and SC conducted marker analysis and association mapping. AS-H and SX analyzed the FHB data. SX and YJ conceived and planned the research on development of the SHW lines. QZ, SX, YJ, XC, and JF developed the SHW lines. AS-H, SX, and SC wrote the manuscript. All authors reviewed and edited the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


Euterpe edulis. We sampled and genotyped with microsatellite markers 544 juveniles of E. edulis in 17 fragments of Atlantic Forest in Brazil. In addition, we estimated the local logging rate and the forest cover and isolation at landscape scale. We found that the palm populations have not undergone any recent bottleneck events and that only logging intensification had affected the fixation index and the number of private alleles. Additionally, we did not detect any evidence of spatial genetic structure or genetic divergence associated with environmental disturbance variables at different scales. However, we identified distinct genetic clusters, which may indicate a reduction of gene flow between fragments that were previously a continuous habitat. Our results show that local disturbances, which act directly on population size reduction, such as logging, modified the genetic diversity more rapidly, whereas genetic structure is probably more influenced by large-scale modifications. In this way, to maximize the conservation efforts of economically exploited species, we recommend to increase the inspection to reduce the illegal exploitation, and reforestation of degraded areas, in order to increase the gene flow in Atlantic Forest fragments.Habitat loss and the illegal exploitation of natural resources are among the main drivers of species extinction around the world. These disturbances act at different scales, once changes in the landscape composition and configuration operate at large scales and exploitation of natural resources at local scales. Evidence suggests that both scales are capable of triggering genetic erosion in the remaining populations. However, most of the studies so far did not evaluate simultaneously the effects of these disturbances on genetic diversity and structure of plants. In this study, we used a multiple scale approach to empirically evaluate the impacts caused by local and landscape scale disturbances in the genetic diversity and structure of an endangered palm tree,  The conversion of natural environments into anthropogenic landscapes is one of the main causes of biodiversity loss worldwide . MountinIn human-modified landscapes, species of economic value are also locally vulnerable due to (i) the direct removal of individuals or (ii) the indirect exploitation of resources, such as seeds, impairing the regeneration capacity of these species . Acute dEuterpe edulis populations. This species is native to the Atlantic Rainforest . We avoided to sample in Montane and Restinga Forests, which resulted in a subdivision into two regions  From the map, we selected 58 possible forest fragments adopting as exclusion criteria highly demanding access areas, and indigenous lands. Then, we used previous studies in the region to select a subset of 17 forest fragments, at least 2 km apart, which spanned a large range of landscape-scale forest cover  and data collection. After finding stability in land use cover during this period, we performed all analyzes with forest cover calculations obtained by the high-resolution mapping.Euterpe edulis is a monoecious palm tree, with annual and predominantly crossed reproduction  based on the categories proposed by We randomly established three 50 × 10 forest-plots in each of the 17 forest fragments. Plots were located at least 50 m apart from each other and from the nearest edge. In each forest plot, we sampled all E. edulis individuals using 17 nuclear microsatellite markers developed for the species  and 7.8 µl of deionized formamide (Applied Biosystems). Later, we performed genotyping on the ABI 3500 Genetic Analyzer . The sizing of fragments was obtained with GeneMarker® software 2.2 .DNA extraction followed the CTAB protocol . We geno species . MultiplO and HE, respectively), allelic richness, and fixation index with a 95% confidence interval estimated by 999 bootstrap simulations. In addition, we used the GENALEX 6.5 program  and Apis mellifera that can reach distances of hundreds of meters of foraging   we used the multifit function  and geneWe performed GAM to capture linear and nonlinear relationships between variables. All possible additive combination of independent variables  and the genetic parameters were tested, totaling seven models. We tested for the concurvity among predictors i.e. the nonparametric counterpart of multicolinearity in linear regressions. We also included a null model containing only the intercept. Finally, we performed a model selection approach using the Akaike Information Criterion corrected for small sample sizes AICc;  for eachE. edulis was investigated through three distinct approaches: we used the DiveRsity package to calculate the Gst-statistics  to 33 (EE52), with a mean of 20.4 alleles for loci.Our results did not show evidence of genotypic linkage disequilibrium in any of the pairs of loci. In addition, we detected the presence of null alleles in all loci with frequency varying from 0.5 to 16%. The average of genetic parameters estimated with original or corrected data for null alleles lead to similar results (data not shown). However, we opted to show all results based on the corrected data for null alleles  and the proportion of alleles in the frequency intervals followed an L distribution format . All estimates of genetic differentiation given by this parameter were significantly different from zero (ST ranged from 0.022 to 0.19 (0.089 ± 0.032) and although genetic differentiation between populations was less pronounced than that presented by GST  (Grant N° 426828/2016-0) and Universidade Estadual de Santa Cruz (UESC) (Grant N° 00220.1100.1681) for financial support. We also thank for grants to LAS (Fapesb—Ph.D.), EC and FG (CNPq-PQ), and LRS (Capes-PNPD).The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


A. crassus, suggesting multiple introduction events from different source populations . Furthermore, a southern to northern clinal decrease in its genetic diversity is seen in Europe, suggesting that A. crassus was introduced in southern Europe and has since spread northwards [150].”“Population genetic studies have revealed multiple, distinct lineages of invasive Unfortunately, the original version of this article  containsA. crassus in North America versus Europe, suggesting introductions from different source populations . Furthermore, a northern to southern clinal decrease in its genetic diversity is seen in Europe, suggesting that A. crassus was introduced in northern Europe and has since spread southwards [150].”“Population genetic studies have revealed multiple, distinct lineages of invasive should readThe authors apologize for the inconvenience caused.


Nephrops norvegicus is still under research. For this reason the present study was focused on genetic variation of the species over a given continuous year period in a semi-enclosed gulf of the Aegean Sea.Comprehensively detailed information on population dynamics for benthic species is crucial since potential admixture of individuals could shift the genetic subdivision and age structure during a full breeding period. The apparent genetic impact of the potential recruitment strategy of Norway lobster Analyses revealed that the relative smaller size class in females and the apparent faster growth of males may represent a key-role differential strategy for the two sexes, whereas females tend to mature slower. Heterozygosity fitness correlations (HFCs) showed substantially significant associations suggesting that inbreeding depression for females and outbreeding depression for males are the proximate fitness mechanisms, respectively.Nephrops norvegicus uniformal genetic composition (background of high gene flow), could be attributed to potential population recolonization, due to a hypothesized passive larval movement from deeper waters, which may suggest that some offspring of local residents and potential male non-breeders from other regions admixture randomly. Nephrops norvegicus [N. norvegicus high population abundance site [Lobsters are a quite expensive, nevertheless, valuable type of tasty seafood as they are considered as a “delicatessen” around the world. Global landings of lobsters for 2013 exceeded 230,000 mt, of which approximately 60,000 mt corresponded to Norway lobster, nce site .Nephrops norvegicus is a marine benthic decapod crustacean (Family Nephropidae) with a wide geographical and bathymetric distribution (captured even at 400 m in northern Aegean Sea fishing grounds). It is considered as highly commercial important species resulting in a recent interest as a new candidate species for aquaculture [N. norvegicus [aculture , 5, 6. Aaculture , has beervegicus .N. norvegicus ecology and evolution was focused so far on classical ecological [N. norvegicus larval stage exceeds 50 days in plankton, before benthic settlement occurs. Juveniles appear to preferentially take up residence in vacated adult burrows, otherwise constructing their own burrows as an extension of the already existing ones [Knowledge of its population dynamic pattern  wilological , 11–13 aological , 14–17. ological ); such aological ). Since ing ones . Notwithing ones . Interesing ones . HoweverIt has been documented that during the protracted brooding periods and the periods of extended release of eggs, alteration of age and sex ratios in Norway lobster is possible . Thus, sN. norvegicus over a continuous year period. Also, the generation interval of the given year was calculated in order to assess the age overlap of the species in Pagasitikos gulf. For this reason microsatellite markers were used as a molecular genetic tool and proved to be a comprehensively informative approach in the study area. Morphometric data were combined with the allele frequencies of N. norvegicus at a temporal scale in order to assess the generation interval separately for the two sexes. Moreover, heterozygosity-fitness correlations were tested regarding levels of genetic diversity and carapace length variability.To test this hypothesis, the present study was focused on assessing genetic variation in Nephrops norvegicus was carried out during a given continuous year (2007) near the deepest area of Pagasitikos gulf  , and ddH2O, up to the final volume. For all reactions, cycling conditions were 94 °C for 30 s, 57 °C for 30 s, followed by 72 °C for 30 s. Microsatellites were amplified with fluorescently labeled forward primers and PCR products were run with the internal ladder Genescan-500 LIZ Size Standard  in an ABI3700 Automated Sequencer . Genotypic data were analyzed using the STRAND 2.3.0.48 software package [Six microsatellite loci, specific to Nephropidae family , 33, wer package .Table 1GIS index [All loci were tested for the presence of null alleles, or allelic dropout using the software MICROCHECKER v.2.2.3 . The sofIS index , number IS index .Species generation interval was assessed with the AgeStructure software  based onMean multilocus heterozygosity (MLH) and inbreeding measures  were performed using the software IRmacroN v.4.0, an EXCEL macro written in Visual Basic . Linear IS = 0.109, p < 0.05), while in male individuals this was not the case . The number of alleles ranged from 9 (Nnmic1-C12) to 24 (NnmicT-G2) with a mean value of MLH at 0.528 and 0.533 for female and male individuals, respectively. Summary statistics on genetic variability are presented in Table Factorial Correspondence Analysis (FCA) reveal a single population , which is considered rather informative . On the other hand, female individuals showed relatively low, but significantly positive association  with carapace length  did not differ significantly between male and female individuals Table . On the Nephrops norvegicus demonstrated a low but significant genetic heterogeneity [N. norvegicus populations, in order not only to test if the observed genetic pattern remains stable over time, but also in order to clarify the model of genetic and size classes structuring.This study represents one of the first attempts dealing with the ecological aspects of mixed gene pools in the marine environment, regarding different reproductive strategies with respect to sex. Male and female Norway lobsters, surprisingly, favored different evolutionary mechanisms suggesting that even relatively high migration movements (i.e. outbreeding), or high inbreeding could adapt robustly in terms of fitness. Previous genetic studies in ogeneity , 16 throogeneity . These fIn both sexes we observed significant but different HFC regression slopes according to carapace length. In males, the associations of different levels of heterozygosity with the fitness related trait were negative, suggesting that outbreeding depression is likely to be the substantial conservation scenario due to an apparent movement of lobsters. The latter suggests that, highly heterozygous male individuals grew less and suffered much greater loss of fitness. The mechanism that underlies this observed pattern may be local adaptation; offspring of genetically distant mates may be less adapted to the environment than their parents . In relaIS may suggest non-random mating, thus indicating high inbreeding within females. Given this pattern, the observed loss of allelic frequencies from the apparent local population, might imply some degree of adaptiveness to the local environment. The specific analyzed microsatellite loci were somewhat variable in all females and most of the individuals were homozygous at all these six loci. Such a documented absence of a fine-scale structure of the species to date [Despite this observed alteration in allele frequencies, little variation in levels of multilocus heterozygosity was recorded, suggesting high levels of inbreeding in female individuals. Interestingly, female individuals showed a rather low but also significant relationship between carapace length and overall heterozygosity measures, implying that inbreeding depression this time, is the primary mechanism for such an association. Indeed, high levels of F to date , 16, may to date .N. norvegicus populations may profound a temporal genetic variation in a local-scale level, demonstrating the presence of a non-inbreeding enhancement as a process of rare alleles transition. Although high inbreeding levels within temporal samples could affect the effective population size promoting low genetic differentiation among samples, the presence of non-breeders seems to have a greater local genetic impact than the dispersal of in-breeders. Nonetheless, the level of gene diversity was moderately high, implying either a degree of structuring, or an exchange of genes occurred in the past. Thus, taking into account the presently calculated mean generation interval of approximately 5.41 years for N. norvegicus, one could assume that at least one effective migrant each year might explain the recorded levels of pairwise genetic differentiation. It has been suggested [Moreover, significant levels of HFC differentiation among the two sexes could be explained by the actual migration of individuals favoring rather low relatedness within the population, suggesting a putative replacement by immigrants. To this extent, this study illustrates that the near-panmictic uggested  that a mThe differential status with regards to sex was also profound in size classes. Pairwise comparisons of the mean length-at-size class showed that female individuals were smaller compared to males. This may be due to the different reproductive behavior of the species in question, resulting to decreased catchability of female individuals . On the N. norvegicus, besides specificities on fishing, spawning and feeding grounds/banks [Sea water circulation pattern of the Aegean Sea depicts a far eastern movement of surface currents along Chalkidiki Peninsula (see ), followds/banks .N. norvegicus uniformal genetic composition (background of high gene flow), could be attributed to potential population recolonization, due to a hypothesized passive larval movement from deeper waters, which may suggest that some offspring of local residents and potential male non-breeders from other regions admixture randomly. Norway lobster has relatively high FIS values in the study area, suggesting that potential populations of the central Aegean Sea need to be identified and to apply conservation measures. Considering the above along with the apparent absence of physical barriers, individuals of the species in question within the study area may be favored to recruitment from an apparent nearby large population encountered in deeper waters as local fishermen claim.Conclusively, the northern/central Aegean Sea is subjected to a strong influence of more eutrophic waters compared to the southern Aegean, featuring higher zooplankton abundance. Richness of a number of benthic species was negatively correlated with depth, partly reflecting the intense research activities in shallower waters and the poor scientific knowledge of the deeper ones . In thatAdditional file 1: Table S1. Number of individuals per gender and month. Figure S1. Factorial Correspondence Analyses for all individuals. Result suggest a single population.