Populations within a species may experience genetic adaptation to local environmental conditions while individuals may tolerate variation in environmental conditions due to phenotypic plasticity. European eels reproduce in the Sargasso Sea but spend most of their adult life in highly diverse environmental conditions from northern Europe to North Africa. An unresolved question is whether this species constitutes a single panmictic population or if locally adapted subpopulations occur. Here we conclude, based on whole-genome sequencing, that there is a complete absence of genetic differentiation among eels from different parts of Europe and North Africa. Thus, we postulate that European eels must respond to the extremely diverse ecological conditions they inhabit during the postlarval stages by phenotypic plasticity. Proc. Natl. Acad. Sci. U.S.A. 102 (suppl. 1), 6543–6549 (2005)]. European eels have a complex life cycle, including transitions between life stages across ecological conditions in the Sargasso Sea, where spawning occurs, and those in brackish and freshwater bodies from northern Europe to northern Africa. Whether continental eel populations consist of locally adapted and genetically distinct populations or comprise a single panmictic population has received conflicting support. Here we use whole-genome sequencing and show that European eels belong to one panmictic population. A complete lack of geographical genetic differentiation is demonstrated. We postulate that this is possible because the most critical life stages—spawning and embryonic development—take place under near-identical conditions in the Sargasso Sea. We further show that within-generation selection, which has recently been proposed as a mechanism for genetic adaptation in eels, can only marginally change allele frequencies between cohorts of eels from different geographic regions. Our results strongly indicate plasticity as the predominant mechanism for how eels respond to diverse environmental conditions during postlarval stages, ultimately solving a long-standing question for a classically enigmatic species.The relative role of genetic adaptation and phenotypic plasticity is of fundamental importance in evolutionary ecology [M. J. West-Eberhard,  How species adapt to the diverse environmental conditions that they experience through their life is fundamental to understanding evolutionary processes. Species that occur across extreme environmental gradients must respond to a diverse range of conditions. This can be accomplished by individual-level phenotypic plasticity, meaning that individuals adjust their physiology to the prevailing environmental conditions , and by Anguilla anguilla) provides a fascinating example. Adult eels are mostly found in freshwater bodies and brackish coastal areas from North Africa in the south to the North Cape in the north (well above the polar circle), from the Azores in the west to the Black Sea in the east. The spawning grounds long remained a mystery, but 100 y ago larvae were discovered in the Sargasso Sea, ∼7,000 km away from the mainland (Anguilla rostrata), estimated to have split from a common ancestor around 3.75 million y ago  from diverse ecological conditions, and a single panmictic population could not be excluded . We also include a sample of American eel (n = 49) as an outgroup. Our study scales considerably over existing genomics research on the European eel, both in number of individuals and number of loci sequenced . A few individuals from the English, Irish, and French samples have a small, but detectable, contribution of American genomic composition (maximum 3%), which could indicate ongoing gene flow at a low rate, consistent with the sporadic occurrence of F1 hybrids reported elsewhere . This signal covers the first three exons of LOC118232784 (myelin-associated glycoprotein-like) and includes one missense mutation . In this specific region, shared polymorphisms are segregating in both European and American eels and the “mid-Atlantic” samples are more similar to the Canadian sample than to other European samples . This suggests some ongoing gene flow, as discussed above, or a balanced polymorphism. This SNP-based approach could have missed population-specific small insertions and deletions or structural variants, but it is unlikely that population differentiation is caused exclusively by such variants and that these variants do not show linkage disequilibrium to SNPs in the near vicinity.In order to evaluate if genetic differentiation is restricted to a small number of single-nucleotide polymorphisms (SNPs) or haplotypes, we scanned the genome for regions associated with location or environmental conditions using per-SNP delta allele frequency contrasts, based on SNPs with at least 5% minor allele frequency across the entire sample set. First, we compared European and American eels and demonstrated that this approach reveals genome-wide high divergence, as expected, with hundreds of thousands of fixed differences all over the genome A. In shaSI Appendix, Fig. S3). We explored if this pattern could be consistent with a sex chromosome , but anSI Appendix, Fig. S4). Comparing the estimated allele counts for each individual shows that this pattern is consistent across the region for the vast majority of samples but then quickly deteriorates in either direction .The signal on chromosome 15 is strong enough to affect the PCA for the entire chromosome B, althouirection D, a pattlotype 1 E. This iP = 0.96 ), and the per-population frequencies do not covary with any obvious environmental gradient. Given the comparatively high frequency of the younger version, it is unlikely to be a neutral polymorphism. Furthermore, the frequency of haplotype 2 is close to 100% in the American eel sample  and the locus displays a drastic loss of diversity , a feature not found in European samples . Thus, it is likely that this haplotype has undergone a selective sweep in the American eel, and introgressed into European eels. Based on the absence of genetic differentiation among geographic regions sampled in this study, we predict that the variant is possibly associated with selection at the egg or larval stages, related to the large range of spawning areas within the Sargasso Sea. The annotated genes within the putative inversion are discussed in SI Appendix, Text.The frequency of haplotype 2 has no significant association with any subpopulation . A 5% allele frequency shift at 100 loci would still be small compared with genetic differentiation, for instance in the Atlantic herring, where ecological adaptation to the brackish Baltic Sea involves strong allele frequency shifts at hundreds of loci, many approaching fixation for different alleles . The aim was to get a good representation across Europe and North Africa including an outgroup sample from Canada (American eel). The majority of samples (8 out of 11) constituted glass eels of unknown sex.The samples used in this study were selected from the sample collection previously used by Dannewitz et al.  combinedDNA was extracted using Qiagen Blood & Tissue 96 Kits. DNA was quantified using the Qubit and Tecan plate reader, and diluted to 10 ng/μL for library preparation. We created custom Tn5-based libraries  for indihttp://www.htslib.org/) and finally processed with MarkDuplicates from PicardTools v1.92 (https://broadinstitute.github.io/picard/).The Illumina short reads were mapped to the primary fAngAng1 assembly (GCA_013347855.1), which was produced as part of the Vertebrate Genomes Project . MappingSI Appendix, Table S1). For all runs, we used the following parameters: “-uniqueOnly 1 -remove_bads 1 -only_proper_pairs 0 -trim 0 -GL 2.” Depending on the analysis, we used the “–doMajorMinor 4 –minMaf 0.05 or 0.1” combination to generate lists of positions with minor allele frequency (MAF) >5 or >10%, respectively, for all 19 chromosomes. These were then supplied as the “-sites” arguments for PCA, genotype likelihood, and population-wise allele frequency calculations, while diversity and Tajima’s D calculation used all observed positions.We used ANGSD v0.933  to estimk = 2 and k = 3 and visual inspection of the results clearly excluded population structure within the run with k = 3 . Furthermore, we calculated individual admixture proportions using PCAngsd v0.985  due to excessively low sequencing coverage after inspecting coverage estimates produced using the software Indexcov (We ran NGSadmix using a downsampled list of 2 million sites (using the MAF > 0.1 filter) and supplying the -SNP_pval 1e-6 to ANGSD to include only high-confidence variants. We ran NGSadmix with both d v0.985  which emIndexcov  and eel The frequencies for each component of the contrast were calculated using ANGSD  “–doMajoA. rostrata) removed. The test statistic follows a χ2 distribution with 1 degree of freedom and per-SNP probabilities were calculated using the pchisq function  for the first principal component in R (v3.6.1)  . The cov(v3.6.1) .A. rostrata samples using the angsd -getfasta 2 command to polarize A. anguilla alleles. We next calculated sample allele frequencies per sampling locality using the following command:$ANGSD_PATH/angsd -bam ${POPULATION}_bamlist.txt -doSaf 1 -anc american_ell.fasta -GL 2 -P 8 -out $POPULATION -doCounts 1 -setMinDepth 15 -setMaxDepth 1000 -setMinDepthInd 0.25 -minMapQ 1 -minQ 20 -remove_bads 1 -uniqueOnly 1 -dumpCounts 2 -doMajorMinor 5 -doMaf 2We calculated thetas using allele frequencies calculated from a callset that was not filtered for MAF cutoffs. Any MAF cutoff will bias site frequency spectrum-based diversity estimates. We first generated a consensus fasta file of Our filters were selected to remove extreme outliers in sequencing depth and to remove spurious alignments and low-quality sites. We next used the ANGSD realSFS command to generate the unfolded site frequency spectrum, which was used as a prior for calculating diversity statistics with the saf2theta command . PairwisSupplementary File


Fhb1 QTL were identified, with an emmer wheat haplotype contributing to disease susceptibility. The large number of QTL identified here can provide a rich resource to improve FHB resistance in commercially grown durum wheat. Among the 31 QTL most were associated with plant height and/or flower time. QTL 1A.1, 1A.2, 3B.2, 5A.1, 6A.1, 7A.3 were associated with FHB resistance and not associated or only weakly associated with flowering time nor plant height. These QTL have features that would make them good targets for FHB resistance breeding.Durum wheat is an economically important crop for Canadian farmers. Fusarium head blight (FHB) is one of the most destructive diseases that threatens durum production in Canada. FHB reduces yield and end-use quality and most commonly contaminates the grain with the fungal mycotoxin deoxynivalenol, also known as DON. Serious outbreaks of FHB can occur in durum wheat in Canada, and combining genetic resistance with fungicide application is a cost effective approach to control this disease. However, there is limited variation for genetic resistance to FHB in elite Canadian durum cultivars. To explore and identify useful genetic FHB resistance variation for the improvement of Canadian durum wheat, we assembled an association mapping (AM) panel of diverse durum germplasms and performed genome wide association analysis (GWAS). Thirty-one quantitative trait loci (QTL) across all 14 chromosomes were significantly associated with FHB resistance. On 3BS, a stable QTL with a larger effect for resistance was located close to the centromere of 3BS. Three haplotypes of  Fusarium graminearum Schwabe [teleomorph: Gibberella zeae (Schwein.) Petch] (Fusarium head blight (FHB), also known as scab and mainly caused by ) Petch] , is a de) Petch] . Moreove) Petch] . Canada ) Petch] . Since t) Petch] . In 2016) Petch] . It is tCurrently, the combination of agronomic and chemical control along with genetic resistance is the most effective means to manage FHB . GeneticDevelopmental traits including flower time, plant height, spike morphology, and anther extrusion/or retention are often reported for their relationship with FHB resistance . Plant hFhb1 on chromosome arm 3BS (Qfhs.ifa-5A on 5AS (Fhb5)  type I – resistance to initial infection measured by the incidence of disease in the presence of natural or augmented artificial inoculum ; (2) type II – resistance to fungal spread measured by the severity of disease; and (3) type III – resistance to the accumulation of the toxin deoxynivalenol (DON) in infected spikes . Till no arm 3BS , Qfhs.ifS (Fhb5)  and Fhb22 on 6BS  have bee2 on 6BS . Fhb1 isance QTL . It is cance QTL . Fhb1 isulations . Fhb1 wate genes  with conT. carthlicum  are a promising way to detect FHB resistance QTL present in diverse genetic sources. Only a few GWAS have been conducted on FHB resistance, including winter wheat , elite CTriticum turgidum L. ssp. Durum (Desf.) Husn.) lines were selected to constitute a durum association mapping (AM) panel targeted to improve FHB resistance in durum wheat. This panel was primarily composed of durum from Canada, including elite Canadian cultivars, advanced breeding lines, recently developed germplasm from Canadian breeding programs and from research projects  and a 15-acetyl-deoxynivalenol  isolate, after which colonized kernels were air dried. In Morden, approximately 2–3 weeks prior to heading, the corn spawn inoculum was spread at 8 g per single meter row with two applications at weekly intervals. Plots were irrigated three times per week using Cadman Irrigation travelers with Briggs booms. At Brandon, the corn spawn inoculum was applied between the rows at a rate of 40 g/m 6 weeks after planting, with a second application performed at the same rate 2 weeks after the first. Plots were irrigated three times per week with a mist irrigation system to create favorable conditions for F. graminearum infection. In Indian Head, FHB was achieved solely by natural disease infection. FHB incidence  and severity  were estimated with visual assessment. FHB index (IND) was calculated with the formula: (INC × SEV)/100. Plant height (HT) and days to anthesis (DTA) were also recorded for Morden plots.Lines of the durum AM panel were evaluated for FHB infection in Morden and Brandon, MB, Canada in 2015 to 2017 with artificial inoculation and Indian Head, SK, Canada in 2015 and 2016 with natural infection. At both Morden and Brandon, FHB nurseries, corn spawn inoculum of TM PicoGreen® dsDNA Assay Kit  and diluted to 50 ng/μL for SNP array genotyping. Genotyping of DNA was performed with the Illumina iSelect 90K SNP array . DNA was quantified with a Quant-iTNP array  accordinNP array  for the Piy = μ + Gi + Ey + (GiXEy) + Eiy, where, Piy are the values of the tested phenotypic trait, μ is the population mean, Gi is the effect of genotypes, Ey is the effect of environments , Eiy is the residual, where i is the genotype, y is the year. The restricted maximum likelihood (REML) method within lme4 (H2) was estimated with the equation Statistical analysis was performed with R 3.4.2  with thehin lme4  was usedorrplot” .r2) for all 5933 anchored SNP markers implemented in Tassel v.5.5.0  were square-root transformed into a normal distribution. The baseline  r2 value, a value that suggested LD was likely caused by genetic linkage, was determined by taking the 95% percentile of this distribution (r2 versus genetic distance (cM) was fitted using a non-linear model described by Linkage disequilibrium (LD) was estimated by correlation coefficient analysis and used the squared correlation coefficients ( v.5.5.0 . The r2 ribution . The scar2) ≤ 0.2 were used for population structure analysis. STRUCTURE analysis was performed with a 50000 burn-in length and 100000 Markov chain Monte Carlo (MCMC) iterations from K = 2 to K = 12 . Fifteen independent STRUCTURE runs were conducted for each specialized K. The optimal cluster (K) was determined by the ΔK method  was performed with R package Genome Association and Prediction Integrated Tools (GAPIT)  .p < 0.05, marker-wise) in at least four of the tested environments for FHB resistance or two for plant height and flower time, and with at least one environment with a highly significant response (p < 0.001). Significant SNPs on the same linkage group were grouped into a QTL region if markers were linked with LD > 0.2.Association mapping was performed on the durum association panel using the phenotypic data collected from the multiple nurseries in multiple years, including HT, DTA, INC, SEV and IND. Association mapping was performed using 5933 mapped SNPs that had a MAF > 0.05 using both Tassel v5.5.50  and GAPIT. dicoccoides introgression lines. The baseline critical threshold r2 value of LD was identified as 0.2, corresponding to a genetic distance around 3.0 cM from the whole genome analysis  and NJ-phylogenetic tree analysis were all used to determine clustering of lines within the durum AM panel, and two subpopulations were consistently indicated, as shown by different colors in analysis .P < 0.001, Mean values (across years) of FHB INC, SEV, IND, DTA and HT of lines from the durum AM panel at Brandon, Morden, and Indian Head, were summarized in p-value) is shown for each environment and trait tested whenever the p-value is less than p = 0.05. As shown in With GWAS analysis, 31 genomic regions were significantly associated with FHB resistance traits , 5. The 1B.1, was found between 544 and 580 Mb on 1B . By adopting strategies to stratify experimental genotypes into groups by both days to anthesis and plant height, it may be possible to recombine earlier to flower and shorter plants with reduced FHB symptoms. The correlation will not be broken but it can be shifted so that earlier maturing and shorter genotypes can be recombined with reduced FHB symptoms. Using this strategy, the negative relationship between plant height and FHB traits has been shifted by recombining semi-dwarf stature with a moderate level of resistance in hexaploid wheat cultivars such as Carberry . Recently, 3B.1 identified in this durum AM panel study. The 3B.3 QTL was one of the most stable QTL identified, with a larger effect on FHB resistance than other QTL in this AM panel. Notably, the resistant 3BSc haplotypes were identified in the durum wheat lines that also had Fhb1 introgressed from Sumai 3 by 3B.3 corresponds to the 3BSc region QTL previously reported as important to FHB resistance, particularly in Canadian elite germplasm, where 3BSc conferred a larger effect than Fhb1  gene that promotes flowering was found physically mapped around 528.1 Mb of 1A in CS Ref 1.0 (1A.3. The major QTL 1B.1 located to the region coinciding with a QTL of FHB resistance from the European winter wheat Arina (FLOWERING LOCUS T3-B1 (TaFT3-B1) that promotes flowering time, was physically identified at position 581 Mb of 1B  and VRNB1 (at 613.0 Mb). 5A.1 and 5B.2 both conferred a stable effect for INC and IND, and while 5B.2 also had a large effect of on DTA, 5A.1 had no effect on DTA and only a minor effect on HT in one environment. 5A.1, also finding no DTA or HT QTL in this region. 5A.1 and 5B.2 in common wheat that controlled anther extrusion, heading time and FHB resistance. There is potential that these vernalization genes are responsible for the FHB resistance coming from these regions, and that the VRNA1 gene has just a minor effect on flowering time in durum wheat. The resistance haplotype of 5A.1 was found in Canadian durum cultivars including Brigade  population. HB, RD, RK, RC, and YR contributed to the durum germplasm development in the AM population. YR, RK, HC, and SB contributed to seed increase of this AM population and the design of field trials. MH, AB, and SK conducted field trials and disease evaluation at FHB nurseries located in Morden and Brandon, Manitoba. YR, SB, RK, RC, and HC performed field trials and disease evaluation at FHB nursery in Indian Head, Saskatchewan. KB and BP contributed to the 90K SNP genotyping and marker identification. KB, WZ, and YR analyzed the data and interpreted results. KB, WZ, RR, and YR contributed to data validation. WZ, KB, and YR wrote the original draft. KB, RK, WZ, YR, RD, HB, HC, and PF reviewed and edited the manuscript. YR was the principal investigator and supervised the project. All authors contributed to the article and approved the submitted version.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.


Echinococcus multilocularis is an endemic parasite of red foxes in several European countries. This parasite has been present for decades in central Europe i.e. Switzerland, Eastern France, Southern Germany and Austria, which constitute the core endemic area of Europe. In the Scandinavian countries Sweden and Denmark, several recent findings were made in foxes. To better understand the dynamics and geographic spread of E. multilocularis in Europe, genetic studies have been undertaken using the DNA microsatellite marker EmsB. In Europe, the parasite spread in hitherto non-endemic areas was suspected to take place after founder events, in which the core endemic area presents a wider genetic diversity in comparison to newly endemic areas. However, identical parasite profiles can be shared between them, highlighting the parasite spreading in a mainland-island system. In this study, Swedish (27 adult worms from seven red foxes) and Danish (38 adult worms from nine red foxes) isolates were examined using fragment size analyses of the tandemly repeated microsatellite EmsB in order to compare the genetic profiles of the Scandinavian worms with a reference collection of European worm isolates from seven countries. Six EmsB profiles were detected in the Scandinavian panel. Three profiles were described in Denmark and four in Sweden. Only one of these profiles was detected in both countries. All profiles identified in the present study have previously been found in other European countries, suggesting an epidemiological link. Due to the relatively low number of Scandinavian E. multilocularis isolates analysed so far, firm conclusions cannot be made regarding the true genetic diversity. Nevertheless, the low genetic variation detected in Sweden and Denmark in this study is similar to the values obtained from peripheral areas of the main European endemic focus, which were more recently colonized by E. multilocularis; and continuous surveillance of this parasite is warranted to provide further insight into its epidemiology in Scandinavia. •E. multilocularis is described.EmsB diversity of 65 Danish and Swedish isolates of •Six different EmsB profiles were found, all previously identified in Europe.•This reflects a possible link between Scandinavia and other European countries.•Only one of the six different EmsB profiles was shared between Sweden and Denmark. The majority of the foxes included in the surveillance were hunted from all over the country by the Danish Nature Agency or by voluntary hunters  from which material for subtyping was available, were included in the present study.The foxes from Denmark included in the present study were collected during the period September 2012 to January 2014 as part of the Danish surveillance program. The program, which was initiated in September 2011, had included 1040 red foxes  (E. multilocularis positive foxes from Sweden (n = 7) identified until October 2013 were included in this study.After the first positive red fox was identified in Sweden in February 2011, hunted foxes were collected in two studies. During 2011, 2985 foxes were submitted for creening  and frome (SSCT) . Morphole (SSCT) . All E. From each positive fox, five to seven worms were selected for genotyping. However, seven foxes had less than five worms and therefore all worms i.e. 1–4 were genotyped from these animals .Table 1D2.2The worms were stored in 70% (v/v) ethanol until molecular analysis. In all but five worms, individual DNA extraction was done using the High Pure PCR Template Preparation kit®  and purified DNA was eluted in 200 μl of the provided elution buffer. DNA extracts were stored at −20 °C prior to PCR analysis. DNA of five Swedish isolates from three foxes, SE5D (two of seven worms), SE6S (two of seven worms) and SE2VG (one worm) , was extA fluorescent PCR assay was carried out on DNA from each worm . Briefly2.3Fragment size analysis was performed by capillary electrophoresis of PCR products performed on an automaton sequencer machine . The size (base pair) and height (fluorescence intensity) of each peak of the EmsB electrophoregrams were obtained with the use of GeneMapper 4.1® . To normalize fluorescence intensity, each fluorescence peak value was divided by the sum of all fluorescence values obtained for all peaks of a given sample , global electrophoregram aspects (number and distribution of peaks), and genetic distance from other existing E. multilocularis EmsB profiles from the same geographical region. Samples that could not be technically validated based on these criteria were excluded from the genetic analyses.Genotyping by EmsB was based on a microsatellite with 40 copies on the same chromosome  and deteP-values. A dendrogram was built based on results from the hierarchical clustering analysis using the package “pvclust” available under the R Project (v 3.0.0) (E. granulosus sensu stricto (G1) were used as an outgroup in the present dendrogram.In order to describe the genetic relationship among the worms, the samples were grouped into different EmsB profiles, defined by performing hierarchical clustering analysis using the Euclidean distance and the unweighted-pair group method with average linkages (UPGMA method) . The stav 3.0.0) . The worv 3.0.0) . Two E. E. multilocularis isolates, each EmsB profile identified was compared with a reference collection of profiles previously obtained by n = 13), North America (n = 14) and the archipelago of Svalbard, Norway (n = 27). The comparison was done by evaluating the genetic distance of one sample from each profile obtained in this study with all the samples from the collection using the R statistical software (https://ewet-db.univ-fcomte.fr)  . Samples3A total of 74 worms from 17 foxes were genotyped. Of these, 65 worms from 16 foxes were successfully genotyped: 38 worms from nine Danish foxes and 27 worms from seven Swedish foxes . Two worn = 26) from all foxes (n = 7) sampled in the Højer area (H) had identical profiles (P4). In the Grindsted area (G), two different profiles were found: P1 and P5 (n = 15) from all foxes (n = 4) sampled in the county of Västra Götaland (VG) had the same profile (P6). In the county of Södermanland (S), the profiles P1 and P2 were found in nine worms from two foxes, and one of these foxes harbored worms with both profiles. In the county of Dalarna (D), profile P2 and P3 were detected in one and two worms respectively, recovered from the same fox. The profiles P1, P2 and P3 are closely related, and all of these profiles correspond to G07 from the “ref collection”  was common between Denmark and Sweden (six worms from a Danish fox and seven worms from two Swedish foxes). In Denmark, two additional profiles were identified. All worms  were obtained from the historical core areas Switzerland, Jura Swabe (Southern Germany), Northern Austria and Eastern France  and one in Sweden , only a single EmsB profile was detected although worms from seven and four foxes, respectively, were analysed. Without prior knowledge of the expected speed of subtype divergence after introduction, the time of introduction of the described profiles cannot be estimated. Furthermore, as dogs travel frequently between Denmark, Sweden and other European countries, subtype diversity does not only depend on subtype divergence. In isolated areas where parasites have limited or no connection with other infected areas the parasite population is expected to be uniform if the area is environmentally homogenous and the host population is not stratified. Yet, this does not explain the low diversity observed in the present areas as they seem to have no obvious natural borders preventing the parasites as well as their hosts from contact with surrounding areas, in contrast to e.g. the autochthonous focus of rn Italy . It is pE. multilocularis profiles. The distance between Utoft, where the foxes were shot and the nearest endemic area in Northern Germany is around 90 km, which is within the known migration distance of red foxes  were sampled. In Södermanland and Dalarna, the mixed infections were found in dual-infected foxes harbouring worms with different EmsB profiles. This was not the case in Grindsted, Denmark were the different EmsB profiles originated from two mono-infected foxes. Both of these foxes were shot in the same location (Utoft). The fact that different profiles were detected in foxes sharing the same home range suggests that the parasites were introduced separately by animals of diverse origin and/or infected with different ed foxes . Howeveristances . Alternaistances . It shouistances  were foxOnly one infected fox was found in Dalarna, whereas several positive samples were detected in the other infected areas in Sweden. Yet, the possibility that the infected fox in Dalarna could have migrated from another infected area is unlikely as young males are the primary driver of migration, whereas adult females (as in this case) are more likely to remain local . The divE. multilocularis was recently introduced to Sweden and Denmark. Nevertheless, the actual time of introduction cannot be estimated as a molecular clock cannot be deduced from EmsB analysis due to its complex multilocus nature and the general absence of E. multilocularis fossil DNA. Based on the epidemiological surveillance data of E. multilocularis in both countries with recent first detections and low prevalence levels in foxes the low genetic variation found in our study was expected. Only one of the six profiles identified in the present study was found in both Denmark and Sweden. This suggests that the presence of E. multilocularis in these countries cannot be explained solely by transmission of the parasite from one country to the other, even if a potential connection cannot be excluded. If recent introduction has occurred, the most likely sources of infection would be migrating wildlife, for example foxes, or infected domestic animals, for example dogs travelling from, or having visited, high endemic areas. In Denmark, dog travel from other European countries is relatively unrestricted (E. multilocularis (E. multilocularis has been known since 1999 (E. multilocularis via infected dogs is therefore considered to have increased (In the present study, all the six profiles identified have previously been found in other European countries , suggeststricted , and foxocularis  with thence 1999 . Howeverncreased .5E. multilocularis isolated from seven Swedish and nine Danish foxes, which may indicate recent introduction of the parasite to these countries. The description of the genetic diversity of E. multilocularis via EmsB profiles performed in the present study is expected to be useful for comparisons with future samples in order to increase our understanding of the epidemiologic situation in Scandinavia and the general expansion of E. multilocularis in Europe.In this study, few genetic profiles were identified in


Molecular and biochemical markers are used to analyze the intraspecific genetic diversity of crops.Prolamin-codingloci are highly effective for assessing this indicator. On the basis of the Laboratory of VarietalSeed Identification of the State Agrarian University of the Northern Trans-Urals, 18 varieties of common oatincluded in the State Register of Selection Achievements in the Tyumen Region from the 1930s to 2019 werestudiedby electrophoresis in 2018–2019. The aim of the work was to study the dynamics of the genetic diversityof oat varietiesat avenin-coding loci. For the analysis, 100 grains of each variety were used. Electrophoresis wascarried out in vertical plates of 13.2 % polyacrylamide gel at a constant voltageof 500 V for 4.0–4.5 h. It was foundthat 44.4 % of the varieties are heterogeneous, each consisting of two biotypes. For three loci, 20 alleles wereidentified, 10 of which were detected for the first time. The allele frequency of avenin-coding loci varied withtime. In the process of variety exchange, alleles that are characteristic of varieties of non-Russian origin were replacedby alleles present in domestic varieties and then in the varieties developed by local breeding institutions.The following alleles had the highest frequency in Tyumen varieties: Avn A4 (50.0 %), A2 (25.0 %), Avn B4 (50.0 %),Bnew6 (37.5 %), Avn C1 (37.5 %), C2 and C5 (25.0 %). These alleles are of great value as markers of agronomicallyand adaptively important characters for the region in question. The amount of genetic diversity of oats variedwith time from 0.33 in 1929–1950 to up to 0.75 in 2019. The high value of genetic diversity in modern breedingvarieties of the Scientific Research Institute of Agriculture of the Northern Trans-Urals and an increase in thisindicator over the past 20 years are associated with the use of genetically heterogeneous source material in thebreeding process. This allowed obtaining varieties with high adaptive potentials in the natural climatic conditionsof the region. Common oat (Avena sativa L.) is a valuable agriculturalcrop used both for food and animal feed .An important factor in increasing the production of oat isthe creation of new intensive type varieties characterizedby high productivity and environmental sustainability. In the Tyumen region, breedingwork with this culture is very active. From the first half ofthe twentieth century to the present, 18 varieties of springoat have been included in the State Register of SelectionAchievements in the region. In 1993, the first variety oflocal breeding, Megion, was regionalized. The proportionof varieties created by the Scientific Research Institute ofAgriculture of the Northern Trans-Urals in the region’scrops has since been constantly increasing. Nowadays,only varieties of local breeding are included in the StateRegister of Selection Achievements in the region.However, active breeding can lead to a decrease in thegenetic diversity of the species. This is due to the frequentinvolvement of the same genotypes in the breeding processto enhance specific agronomic characters. A decreasein genetic diversity negatively affects the resistance ofpopulations to diseases and the populations’ ability toadapt to changing environmental and climatic conditions.A variety of molecular and biochemical markers areused to analyze intraspecific genetic diversity . Prolamin-coding loci are very effectivefor assessing this indicator . Prolamins of oat (avenins) are inherited asblocks and are controlled by three independent loci: Avn A,Avn B and Avn C, located in three homeologous chromosomesof group A . Dueto the high level of avenin polymorphism, almost everyoat variety, biotype, or line is characterized by a uniquecomponent composition of storage proteins . This allows analyzingthe individual allele frequency of avenin-coding loci, thedynamics of changes in their occurrence in time and space,and also assessing the genetic transformations that occurunder the influence of prolonged artificial selection.The aim of the work is to study the dynamics of geneticdiversity at avenin-coding loci in common oat varietiesincluded in the State Register of Selection Achievementsin the Tyumen region from the 1930s to the present forassessing the effectiveness of selection work carried outin the region.The studies were carried out in the Laboratory of VarietalSeed Identification of the Agrobiotechnological Centerof the Northern Trans-Urals State Agrarian University in2018–2019. Eighteen varieties of common oat included inthe State Register of Selection Achievements in the TyumenRegion since 1929 were studied (Table 1).Plant material was provided from the collection of theFederal Research Center N.I. Vavilov All-Russian Instituteof Plant Genetic Resources and the institution-originatorof varieties, the Scientific Research Institute of Agricultureof the Northern Trans-Urals, a Branch of the Tyumen ScientificCenter of Siberian Branch of the Russian Academyof Sciences.For laboratory analysis, 100 grains of each variety selectedby random sampling were used. For one-dimensionalelectrophoresis of avenins, a published technique  with modifications was used. Proteins wereextracted from individual crushed grains by adding 90 μlof 70 % ethanol. The obtained extract was centrifuged, and300 μl of methylene green dye was added to it. Protein extract(22 μl) was added to the polyacrylamide gel. Gel composition:13.17 g of acrylamide, 0.66 g of N,Nʹ-methylenebis-acrylamide, 7.17 g of urea, 2.0 mg of iron sulfate (III),80.0 mg of ascorbic acid, and 0.26 g of aluminum lactate.All reagents were dissolved in 100 ml aluminum-lactatebuffer (pH 3.1). Acrylamide polymerization was initiatedby adding 25 μl of 15 % hydrogen peroxide to 75 ml of a gel solution. Electrophoresis was carried out in verticalelectrophoretic chambers with dimensions of the formedplates of 17.8 × 17.8 × 0.15 cm  for4.0–4.5 h at a constant voltage of 500 V. To fix and stainthe gel, a 10 % solution of trichloroacetic acid with the additionof 0.05 % Coomassie brilliant blue R-250 in ethanolwas used. Identification of allelic variants of componentblocks controlled by avenin-coding loci was carried out onthe basis of a catalog developed by V.A. Portyanko et al.(1987). Astor common oat (Avn A2 B4 C2) were used as astandard. In case the detected block was not in the catalog,it was marked with a “new” mark.In order to assess the dynamics of the change in thegenetic diversity of oat varieties over time, all the studiedsamples were grouped. One group included varieties cultivatedin the same ten-year period. The gene diversity atthe locus (H) was calculated for each group of varietiesseparately according to the following formula:i is the population frequency of the i-th allele; k isthe number of locus alleles; n is the sample size .To calculate the average gene diversity (H), the number of alleles per locus was averaged over all loci. The calculationswere performed using the Arlequin Ver 3.5.2.2 program.where pAs a result of the studies, it was found that 8 (44.4 %) of the18 analyzed varieties were heterogeneous in the compositionof avenin. Seger, Golden Rain, Omhafer, Severyanin,Narymskij 943, Tayozhnik, Megion and Otrada varietiesconsisted of two biotypes. These varieties are characterizedby the presence of several alleles at one or more avenincodingloci. In the genetic formula, such states of loci wererecorded with the “+” sign (Table 2). In subsequent calculations,each biotype was considered by us as a separatesample. A total of 26 samples were examined.An analysis of the electrophoretic spectra of avenin allowedus to describe the genetic formulas for each of thestudied varieties. Altogether, 8 alleles were detected for theAvn A locus; 7, for the Avn B locus; and 5, for the Avn Clocus. It should be noted that some of the combinationsof avenin components that we found were absent in thecatalog of genetic nomenclature. To identify new blocks of components, it is necessary to conduct a hybridologicalanalysis and assess the nature of the inheritance of avenincomponents. However, we highlighted the alleged blocksof components, each of which was assigned a numberfollowing the blocks previously described in the catalog.A “new” mark was added before the number of each of theproposed blocks.To assess genetic diversity at different time intervals,we calculated the allele frequency of avenin-coding loci(Table 3).Different alleles predominate in different groups of varieties.For the Avn A locus, only alleles 2 and new9 werefound before 1950. However, the frequency of their occurrencebegan to decrease with the appearance of domesticvarieties and then varieties of local breeding in the crops of the region . Alleles 1, 5 and new12 were characteristicof varieties cultivated from 1960 to 2010, and areno longer found today. Allele 4 (50.0 %) is currently themost widespread; allele 2 accounts for 25.0 %; new11 andnew12, for 12.5 % each.For the Avn B locus of modern oat varieties, alleles 4(50.0 %) and new6 (37.5 %) predominate; new7 is foundwith a frequency of 12.5 %. Alleles 1, new8, new9 andnew10, which are characteristic of varieties of foreign anddomestic breeding, but not found by us among the varietiesof local breeding, are completely eliminated.A similar situation is observed for the Avn C locus: allelenew8, which occurred with a frequency of 66.7 % in1929–1950, is currently replaced by alleles 1 (37.5 %),5 (25.0 %) and 3 (12.5 %). It is necessary to pay attentionto allele 2, the presence of which in varieties has beennoted at all periods of cultivation ever since 1929. Thisallele frequency ranged from 25.0 to 62.5 %. Nowadays,this allele is presented in 25.0 % of the varieties. The samefeature was noted for allele 2 of the Avn A locus.The value of genetic diversity, calculated on the basisof data on the allele frequency, also changed over time.This indicator was minimal before 1950 (0.38), whenonly three varieties of oat were cultivated in the region:Seger, Golden Rain and Omhafer. Subsequently, with theadvent of new varieties in the region’s crops, the valueof genetic diversity increased, reaching its maximum inthe period from 1970 to 1980 (0.78). During this periodof time, an active variety exchange was carried out in theregion – Seger, Udarnik 883 and Nidar were removed fromregionalization, and they were replaced by Skorospelyj,Narymskij 943, Tayozhnik and Astor varieties bearing newalleles of avenin-coding loci. The period 1970–1980 was characterized by the largest variety of allelic variants invarieties – 15 alleles were found at three Avn loci (Table 3).Subsequently, in the process of replacing foreign varietieswith domestic ones, the indicator of genetic diversity decreasedto 0.70 by 2010. A decrease in diversity was causedby the exclusion from regionalization of a large numberof varieties bearing alleles not found in varieties of localbreeding. However, to date, there has been an increase inaverage gene diversity to 0.75.As a result of our analysis using multiple alleles of avenincodingloci, we described the genetic formulas for 18 va-rieties of common oat included in the State Register ofSelection Achievements in the Tyumen region. It wasestablished that the heterogeneity of varieties is 44.4 %.The presence of several biotypes increases the adaptivepotential of the variety , which is extremely important in thenatural climatic conditions of the Tyumen region, which isa risky farming zone.In some varieties, identical prolamin spectra were found.Thus, the first and second biotypes of Golden Rain areidentical to Seger (I biotype) (2.1.new8) and Nidar (2.1.2),respectively. The second biotype of Seger coincided withthe second biotype of Omhafer (new9.1.new8). The firstand second biotypes of Severyanin coincide with Udarnik(new11.new9.3) and Skorospelyj (new12.new10.3). Thesame types of spectra are characteristic of the second biotypeof Narymskij 943 as well as Astor and Novosibirskij88 (2.4.2); the spectra of Perona and Talisman (4.4.2) coincide.As a result of the analysis, it was found that only 10(38.5 %) of the 26 studied genotypes are variety-specific.This is a fairly low rate.The identity of alleles of prolamin-coding loci in varietiesis associated with the involvement of the same genotypesin breeding programs . Forexample, Seger and Golden Rain were bred from thesame oat variety Milton (=Propsteier), and Omhafer, too,originated from it. The old oat variety Milton appearedin northern Germany and was widespread in northernEurope . Apparently, this varietypossessed outstanding economic characteristics, which ledto its frequent inclusion in the breeding process. This wasreflected in the matching set of alleles of avenin-codingloci in its descendants. The presence of varieties with thesame genetic formulas of prolamins reduces the efficiencyof using the method of electrophoresis for their differentiation.A number of authors in their studies concluded thatthe use of avenin-coding loci as the only marker systemfor distinguishing a large number of oat varieties is insufficient,since the allelic diversity of oat prolamin loci is characterized as low compared to wheat, barley and rye. In such cases, there is a need for an additionaluse of other marker systems . However,it should be noted that the modern varieties of oat createdby the Scientific Research Institute of Agriculture of theNorthern Trans-Urals have an individual allelic compositionof avenin-encoding loci, which makes it possible todifferentiate their genotypes with high accuracy.An analysis of the frequencies of alleles of avenin-codingloci for all three loci allowed us to note the relationshipbetween the frequency of alleles and a set of cultivatedvarieties, especially their origin. In the process of varietyexchange, the alleles characteristic of varieties of foreignbreeding were gradually replaced by alleles present indomestic varieties, and then in the varieties developed oflocal breeding istitutions. A similar replacement of oneallele with another during breeding work was noted bymany researchers in the study of prolamin-coding loci ofwheat and barley . On a large number of examples,the adaptive nature of prolamin polymorphism has beenproved. Their connection with adaptive gene complexesallows, based on the spectra of storage proteins, identifyinggenotypes that are most adapted to specific climatic conditions.A.Yu. Novoselskaya-Dragovich and the co-workers(2013) noted that genetic differences between varieties ofdifferent geographical origin are determined by naturalselection. In this case, the reason for the rather rapid replacementof the “old” alleles with “new” ones is directedprocesses associated with new directions in breeding andthe involvement of genetically different source material. Our data on theallele frequency of avenin-coding loci are in good agreementwith this statement.With the beginning of breeding work on oat in theTyumen region, varieties appeared that possess a set ofagronomically and adaptively significant characters for thisregion. This led to an increase in the frequency of certainalleles of avenin-coding loci, which can be consideredmarkers of such genotypes or characters. At the same time,it caused a decrease in the frequency or even completedisappearance of alleles characteristic of foreign varieties.A2 and C2 alleles found in all groups of varieties, pro-bably,mark highly competitive gene associations that givetheir carriers important advantages in the natural climaticconditions of the region.Monitoring changes in the genetic diversity of varietiesover time allows judging the presence or absence of geneticerosion. In the works devoted to the assessment ofgenetic diversity in varieties of other crops, its values were0.62–0.76 for soft wheat varieties created in Serbia andItaly , 0.5–0.6 in soft wheat varieties of Ukrainian selection ,and 0.42–0.64 in groups of durum wheat varieties originatingfrom different countries of the world . At the same time, a decrease in the value of thisindicator in modern varieties is noted .The high values of genetic diversity identified as aresult of our work and an increase in this indicator since2000 indicate the absence of genetic erosion. It should benoted that, at different periods of time, the contribution ofindividual avenin-coding loci to the average gene diversityin varieties of oat in the region was not the same. In theperiod from 1970 to 2010, the Avn A and Avn B loci playedan important role in the formation of genetic diversity. Butcurrently, the maximum genetic diversity is observed at theAvn C locus. In our opinion, this suggests that the allelesof this locus may be important as markers of adaptivelysignificant characters.The allele frequency of avenin-coding loci in varieties ofcommon oat included in the State Register of SelectionAchievements in the Tyumen region from 1929 to 2019changed over time. The alleles characteristic of the varietiesof foreign selection were replaced by “new” ones,specific to the varieties of local selection: Avn A4 (50.0 %),A2 (25.0 %), Avn B4 (50.0 %), Bnew6 (37.5 %), Avn C1(37.5 %), C2 and C5 (25.0 %). These alleles are of greatvalue as markers of agronomically and adaptively significantcharacters for the region in question.Modern regionalized varieties of oat are characterizedby high genetic diversity (0.75), which is associated withthe use of heterogeneous source material in the breedingprocess. This allows obtaining varieties with high adaptivepotentials in the climatic conditions of Western Siberia.The high importance of genetic diversity in modernbreeding varieties of the Scientific Research Institute ofAgriculture of the Northern Trans-Urals and an increase inthis indicator over the past 20 years indicate competentlyorganized and effective breeding work with this crop inthe Tyumen region.The authors declare no conflict of interest.Afanasenko O.S., Novozhilov K.V. Problems of rational use of geneticresources of plant resistance to diseases. EkologicheskayaGenetika = Ecological Genetics. 2009;7(2):38-43. (in Russian)Barsila S.R. The fodder oat (Avena sativa) mixed legume foragefarming: Nutritional and ecological benefits. J. Agric. Nat. Resour.2018;1(1):206-222. DOI 10.3126/janr.v1i1.22236.Che Y.H., Li L.H. Genetic diversity of prolamines in Agropyronmongolicum Keng indigenous to northern China. Genet. Resour.Crop. Evol. 2007;54(5):1145-1151. 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Current state of the geneticpolymorphism in spring barley (Hordeum vulgare L.) fromRussia assessed by the alleles of hordein-coding loci. Russ. J.Genet. 2016;52(6):565-577. DOI 10.1134/S1022795416060077.Lyubimova A.V., Eremin D.I. Peculiarities of the avenin componentcomposition in oats cultivated in Western Siberia. Trudypo Prikladnoy Botanike, Genetike i Selektsii = Proceedings onApplied Botany, Genetics, and Breeding. 2018a;179(2):85-95.DOI 10.30901/ 2227-8834-2018-2-85-95. (in Russian)Lyubimova A., Eremin D. Variety check as an element of precisionfarming in the modern agriculture. In: International Scientificand Practical Conference “AgroSMART – Smart Solutionsfor Agriculture” (AgroSMART 2018). 2018b. Vol. 151. DOI10.2991/agrosmart-18.2018.91.Melnikova N.V., Kudryavtsev A.M., Mitrofanova O.P., LiapunovaO.A. Global diversity of durum wheat Triticum durum Desf.for alleles of gliadin-coding loci. Russ. J. Genet. 2010;46(1):43-49. DOI 10.1134/S1022795410010072.Metakovsky E.V. The value of gliadin biotypes in commercial cultivarsof wheat. In: Proc. 4th Int. Workshop on Gluten Proteins.Winnipeg, 1990.Montilla-Bascón G., Sánchez-Martín J., Rispail N., Rubiales D.,Mur L., Langdon T., Griffiths I., Howarth C., Prats E. Geneticdiversity and population structure among oat cultivars and landraces.Plant Mol. Biol. Rep. 2013;31(1305):1305-1314. DOI10.1007/s11105-013-0598-8.Nei M. Molecular Evolutionary Genetics. New York: ColumbiaUniversity Press, 1987.Novoselskaya-Dragovich A.Yu., Fisenko A.V., Imasheva A.G.,Pukhalskiy V.A. Comparative analysis of the genetic diversitydynamics at gliadin loci in the winter common wheat Triticumaestivum L. cultivars developed in Serbia and Italy over 40 yearsof scientific breeding. Russ. J. Genet. 2007;43(11):1236-1242.DOI 10.1134/S1022795407110051.Novoselskaya-Dragovich A.Y., Fisenko A.V., Puhal’skii V.A. Geneticdifferentiation of common wheat cultivars using multiplealleles of gliadin-coding loci. Russ. J. Genet. 2013;49(5):487-496. DOI 10.1134/S1022795413020087.Portyanko V.A., Pomortsev A.A., Kalashnik N.A., Bogachkov V.I.,Sozinov A.A. The genetic control of avenins and the principlesof classification. Genetika = Genetics (Moscow). 1987;23(5):845-853. (in Russian)Portyanko V.A., Sharopova N.R., Sozinov A.A. Characterization ofEuropean oat germ plasm: allelic variation at complex aveninloci detected by acid polyacrylamide gel electrophoresis. Euphytica.1998;102:15-27. DOI 10.1023/A:1018399919953.Scheben A., Batley J., Edwards D. Genotyping-by-sequencing approachesto characterize crop genomes: choosing the right toolfor the right application. Plant Biotechnol. J. 2017;15(2):149-161. DOI 10.1111/pbi.12645.Shavrukov Y. Comparison of SNP and CAPS markers applicationin genetic research in wheat and barley. BMC Plant Biol.2016;16:11. DOI 10.1186/s12870-015-0689-9.Souza E., Sorrels M. Inheritance and distribution of variation atfour avenin loci in North American oat germplasm. 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Grapes contain high concentrations of secondary metabolites and antioxidants that have been linked to a reduction of several chronic diseases. Here, we report results of a UK retail survey, which investigated the effect of the production region (Mediterranean vs. South Africa), grape type (white vs. red vs. black) and variety, and production system  on antioxidant activity and concentrations of phenolic compounds in table grapes. Black grapes had ~180% total antioxidant activity (TAA), ~60% higher total phenolic content (TPC) and ~40 times higher anthocyanin concentrations (TAC) than white grapes, while red grapes had intermediate levels of TAA, TPC and TAC. The effects of season and production system and differences between varieties of the same grape type were substantially smaller. Grapes imported from Mediterranean countries in summer had a 14% higher TPC and ~20% higher TAA than grapes imported from South Africa in winter, and organic grapes had a 16% higher TPC and 22% higher TAA, but ~30% lower TAC than conventional grapes. Significant differences in TPC, TAA and/or TAC between organic and conventional grapes could only be detected for specific grape types, varieties and/or sampling years. Grapes are one of the most popular fruit species globally and are used as table grapes and for processing into grape juice, wine and a range of other alcoholic drinks . FAO  statistiGrapes have high concentrations of plant metabolites with antioxidant activity including polyphenols, such as flavonoids, tannins, resveratrol and anthocyanins ,4,5. TheTEAC) levels in (a) organic white grapes of the variety Albana, (b) organic red grapes of the variety Lambrusco, but (c) conventional red grapes of the variety Sangiovese, while production system had no significant effect on TAATEAC in white grapes of the variety Pignoletto.The demand for organic table grapes has rapidly increased mainly due to consumer perceptions that organic foods have higher sensory and nutritional quality ,12,13. AApart from variety choice and environmental conditions , a range of specific agronomic factors  factors are known to affect total phenolic, anthocyanin and/or antioxidant activity levels in gapes, and may therefore explain the variability of results of these comparative  studies.The contrasting effects of grape exposure to high temperatures (>35 °C) and solar irradiation were studied in a groundbreaking study by Tarara et al. . Total aThe type of fertilizer, input levels, and the ratio  of mineral fertilizers applied to grapes are shown to affect phenolic and/or antioxidant levels in grapes ,26,27. PStudies by Peterlunger et al.  with MerA study in Spain with Tempranillo and Grenache grapes reported that mechanical thinning led to a higher Brix and increased concentrations of berry phenolics, but not anthocyanins and the study also found strong treatment x year interactions for berry phenolics .3) to increase fruit yield was reported to decrease total phenolic, flavonoid and antioxidant activity in ‘Muscat’ grape berry skin and flesh, although levels in leaf, stem and tendril tissue increased [The use of gibberellic acid  July and October (when grapes imported from Mediterranean countries) and (b) January and April (when grapes are imported from South Africa and other countries in the Southern hemisphere).Preliminary supermarket surveys had shown that the varieties available as organic and conventional tables grapes differed substantially in both the winter and summer periods and variety-matched samples of organic and conventional grapes are rarely available. It was therefore not possible to quantify to what extent the contrasting variety of profiles of organic and conventional grapes contributed to/confounded the composition differences detected between organic and conventional grapes. However, to identify the potential impact of variety choice we carried out supplementary statistical analyses using data obtained for varieties available both as organic and conventional grapes only.It should also be pointed out that, although retail surveys can provide an accurate estimate of composition differences between (a) organic and conventional and (b) white, red and black grapes experienced by consumers, they do not allow these differences to be linked to contrasting (a) pedoclimatic conditions in grape-producing regions, (b) agronomic practices  and (c) supply chain-related parameters . This is primarily because the information on pedoclimatic, agronomic and supply chain-related parameters cannot be obtained from the supermarkets where grapes were collected.The table grape retail survey was conducted within two seasons (winter and summer) and during two years (2015 and 2016). During each season grapes were collected at regular weekly intervals in stores of three different UK supermarkets that sold both organic and conventional table grapes within the Newcastle upon Tyne (NE) UK postcode area. Table grapes collected during the winter season were all imported from South Africa while those collected during the summer season were imported from Egypt, Morocco, Greece, Italy and Spain. Depending on the season and sampling date, different color  grape varieties were available in the shops. The varieties available as organic and conventional table grapes also differed on most sampling dates. White and red color grape varieties were available from both organic and conventional production in both seasons (winter and summer), whereas black colored grape varieties were only available during the summer season.In each of the three supermarkets, all organic table grape varieties available on sampling days were purchased, together with either (a) conventional table grapes of the same variety (when available) with the same sell-by date (+/− 1 day), or (b) conventional table grapes of a different variety (if the same variety was not available), but the same color type and sell-by date (+/− 1 day).We collected up to three paired samples  per grape type  on an individual sampling date (3 supermarkets × 2 production systems × 3 grape types = 18 samples). However, on many sampling dates, matching samples for some grape types were only available in one or two of the supermarkets, and black organic grapes were mainly available in the summer season when grapes were imported from the Mediterranean. A list of varieties available in the UK as both organic and conventional products in the UK during the summer and winter seasons is shown in All 485 fresh grape samples (each sample being 1.5 or 2 bunch(es) of grapes in a plastic container) were transferred to Newcastle University within an hour of purchase and stored at −20 °C until sample preparation. After defrosting for 2 h at room temperature and under a dim light, about 40–50 whole grape berries (approximately 250–350 g) were randomly selected from each sample (1.5 or 2 bunch(es) of grapes/box), cut in half in order to allow removal of seeds and then crushed/homogenized (skin and pulp) for 30–120 s in a homogenizer (multipurpose food blender) to prepare grape juice. Following homogenizing, 5 aliquots of juice (for each sample) were labeled  and stored at −80 °C until use in different biochemical assays/analyses. Dry matter (DM)  and sugaFolin-Ciocalteau phenol reagent, gallic acid, potassium persulfate and radical scavenging assay reagents: 6-hydroxy-2, 5, 7, 8-tetramethylchroman-2-carboxylic acid (Trolox), 2,2-diphenyl-1-picrylhydrazyl (DPPH), 2, 2′-azinobis-(3-ethylbenzothiazoline)-6-sulfonic acid (ABTS) were purchased from Sigma-Aldrich . Sodium carbonate, methanol, hydrochloric acid (12 N), sodium chloride, sodium dihydrogen phosphate, sodium hydrogen phosphate, potassium chloride, sodium acetate, formic acid, acetonitrile and methanol (for HPLC grade) were supplied by Fisher Scientific.Secondary metabolites were extracted according to Tassoni, et al. . In brieTotal phenolic content was determined by the Folin-Ciocalteau (FC) colorimetric assay method . An extrTotal antioxidant activity was determined by the 2,2-diphenyl-1-picrylhydrazyl (DPPH)  and 2, 2Anthocyanins were extracted from the grape sample using the methods described by Tassoni, et al.  and ChioIndividual anthocyanins in grape samples were detected and their concentrations were quantified according to Kammerer, et al.  with sliAnalyses and separation of individual anthocyanin components were performed using a Phenomenex, Synergiᵀᴹ 4 μm Hydro-RP 80Å  column, fitted with a C18 guard column  at a temperature of 25 °C. The HPLC system  was equipped with LabSolution software, a DGU-20A3R degasser, 2 LC-20AD pump, a SIL-20AC HT autosampler, a SPD- M20A diode array detector and a CTO- 20AC column oven. The detector was set to an acquisition range of 190–700 nm.Water/formic acid/acetonitrile (A) (87:10:3) and water/formic acid/acetonitrile (B) (40:10:50) were used as a mobile phase with a flow rate of 0.8 mL/min. The gradient programme for the mobile phases (A:B) was at 0.02 min (10:90), 5 min (10:90), 15 min (25:75), 20 min (31:69), 25 min (40:60), 35 min (50:50), 45 min (100:0), 50 min (10:90) and 55 min (10:90). The injection volume was 50 μL for all samples and quantification was performed at 520 nm.O-glucoside in the range of 50 to 0.05 µg/mL. LC-MS analysis was performed separately by Newcastle University Protein and Proteome Analysis (NUPPA) laboratory team to confirm the identity of the peaks based on m/z identified by HPLC analysis.Identification of individual anthocyanins was based on peak relative retention times and elution order of chromatograms obtained by Kammerer, et al. . IndividPrinciple component analyses (PCA) were carried out for both secondary metabolite, antioxidant activity and sugar content data obtained for individual samples using the ‘prcomp’ function in R and visualized by using the ‘autoplot’ function of the ggplot2 package in R . PCA-resANOVA derived from Linear mixed-effects (lme) models  was usedFor secondary metabolites and antioxidant activity, PCA identified a clear separation between results obtained for different grape types  a, but noThe two main factorial ANOVA, therefore, focused on identifying the main effects of grape type and potential interactions between grape type, and year, production region and production system. ANOVA 1 was based on all data from matching organic and conventional white and red grape samples and included (a) year, (b) production system , (c) season (winter vs. summer) and (d) grape type (white vs. red) as factors. ANOVA 2 was based on all data from matching organic and conventional white, red and black samples collected in the summer season.The hierarchical nature of the experimental design was designated in the random error structures of the model as: replicate (brand)/year/production system/season (ANOVA 1); and replicate (brand)/year/production system (ANOVA 2).Separate PCA with data obtained for white , red Fi and blacHowever, due to the differences in the range of varieties available (1) in summer and winter and (2) from organic and conventional production systems , varietyp < 0.05) interactions between factors, general linear hypothesis tests (Tukey contrasts) were performed using the ‘glht’ function of the ‘multcomp’ package in R [In order to further investigate the significant  and summer (when grapes were imported from Mediterranean countries) in two consecutive years (2015 and 2016). All experimental factors significantly affected the grape composition and ANOVA also detected a wide range of significant interaction between factors . The effSince only red and white grapes were available in UK supermarkets from both (a) organic and conventional production and (b) production regions (South Africa in winter and Mediterranean in summer) main effects of production region and interactions of production region with year, grape type and/or production systems could only be assessed for red and white varieties .For white and red grapes from both production regions and black grapes from the Mediterranean samples were collected in two successive years (2015 and 2016) and the year was included in the ANOVA to estimate effects of production year (and associated differences in climatic conditions during the grape growing season) on grape composition.TEAC), were significantly higher  in samples from the Mediterranean. The production region had no significant main effect on anthocyanin concentrations  while white grapes from the two regions had similar levels of TPC and TAADPPH  TAATEAC in both white and red grapes in 2015, but only white grapes in 2016 with levels higher in Mediterranean grapes in 2015, but South African white grapes in 2016  TAA in 2016 .Significant 3-way and 4-way interactions with the production system  were also detected in the 4-factor ANOVA for a range of composition parameters  and are Black grapes from organic production were not available during the winter grape season (when grapes are imported from South African) main effects of all three grape types  and interactions with year and production systems could therefore only be assessed for grapes produced in Mediterranean countries during the summer grape season .Three-factor  ANOVA detected significant main effects of grape type for all composition parameters assessed when data obtained from samples of three grape types  produced in the Mediterranean were analyzed .DPPH and TAATEAC were highest in black, intermediate in red and lowest in white grapes, but only the difference between black and white grapes was significant for all three parameters  and SC (juice) were significantly higher in red than in both white and black grapes, which had similar concentrations. The TPC, TAArameters . The larrameters .TEAC (higher in 2015 than 2016) and TAC (higher in 2016 than 2015) and a range of significant 2-way interactions between (a) year and grape type (TEAC in red grapes only (higher in 2016) and (b) TAC in black grapes only (higher in 2016). . . In 2015k grapes .Interactions between grape type, and production systems and/or year identified in the 3-factor ANOVA  are descSince white grapes were found to have very low anthocyanin concentrations , anthocyO-glucoside, penunidin 3-O-gluciside, malvidin 3-O-glucoside, peonidin 3-O-p-coumaroylglucoside and malvidin 3-O-p-coumaroylglucoside were significantly and substantially (between 8 and 31 times) higher in black than red grapes. In contrast, concentrations of cyanindin 3-O-glucoside and peonidin 3-O-glucocside were not significantly different in red and black grapes .Significant 2-way interactions between grape type and year were detected for delphinidin 3-Three-way Interactions between production system, year and grape type identified by 3-factor ANOVA  are descTEAC were slightly, but significantly higher  in organic grapes, while the TAC was 44% lower in organic grapes  TAC  were detected for (a) the sugar content in both pulp and juice, (b) TAA (c) TAC . When th samples .Significant 4-way interactions between production system, year, production region and grape types (red vs. white) were only detected for TAC . When thTEAC only  . When th in 2015 .DPPH of white grape produced in South Africa in 2015 (DPPH and TAATEAC of red grapes produced in the Mediterranean and South Africa in 2015 (DPPH and TAATEAC and TAC in black grapes produced in the Mediterranean in 2015 (Significant main effects of variety were detected for the (a) dry matter and sugar content, TPC and TAA in 2015 , (b) sug in 2015  and (c)  in 2015 . However in 2015 .Significant interactions between the production system and variety choice were also detected for a range of composition parameters in white, red and black grapes collected in 2015 –S4. FurtThe range of grape varieties available in UK supermarkets during the winter (from South African production) and summer (from the Mediterranean) different considerably and for most varieties it was not possible to obtain samples from both organic and conventional production in both seasons. The season could therefore not be included as a factor in the Three-factor ANOVA of data for the red varieties “Crimson” and “Flame” identified significant main effects of production region for all composition parameters. Specifically, grapes from the Mediterranean had a higher TPC, TAA and TAC content, while grapes from South Africa had a higher dry matter and sugar content .DPPH and TAATEAC were significantly higher in “Flame” than “Crimson” grapes produced in the Mediterranean, but higher in “Crimson” than “Flame” grapes produced in South Africa  TACh Africa . Furtherh Africa .The data available allowed anthocyanin profiles to be compared in samples from (a) the red varieties Crimson and Flame from Mediterranean countries collected in 2015 , (b) theO-glucoside, cyanindin 3-O-glucoside and petunidin 3-O-glucoside concentrations compared to the variety Crimson, while no significant main effect of variety could be detected for the other four anthocyanins assessed  higher delphinidin 3-assessed . Howeverassessed . When thparators .O-glucoside and peonidin 3-O-glucoside, but significantly higher peonidin 3-O-p-coumaroyl glucoside and malvidin 3-O-p-coumaroyl glucoside concentrations than conventional Allison grapes , grape type (white vs. red vs. black) and production systems  on the nutritional composition of table grape products available to consumers in UK supermarkets. Retail surveys are the most accurate approach to assess differences in composition/quality between different food products at the point of purchase by consumers .However, one of the main limitations of retail surveys is that information on the exact production protocols and pedo-climatic conditions on the farms supplying supermarkets is usually not available . In the study reported here it was, therefore, possible to identify effects of specific agronomic/management protocols , environmental drivers and post-harvest conditions  on the grape composition parameters assessed in this study. Results are therefore discussed in the context of existing published information on the effects of pedoclimatic, agronomic and supply chain-related parameters on phenolic and anthocyanin concentrations, and antioxidant activity in table grapes.Effects of contrasting climatic conditions between years on grape quality are well documented ,26,27,28Winter season grapes produced in the southern hemisphere spend longer (15–40 days) in transport than summer season grapes (2–5 days) produced in the Mediterranean . They maDifferences in the (a) postharvest treatment  protocols  and (b) Both PCA and ANOVA clearly identified grape type as the main explanatory variable/driver for differences in nutritionally desirable total phenolic and anthocyanin concentrations and antioxidant activity in grapes. In contrast year, production season and production system explained less of the variation in the nutritional composition of table grapes at the point of retail.Our findings that (a) total phenolic and anthocyanin concentrations and antioxidant activity were highest in black, intermediate in red and lowest in white red grapes and (b) magnitude of difference in anthocyanin concentrations (five-times higher in black than red and more than seven times higher in red than white grapes) is consistent with the results of previous studies ,55,56.The profile of grape varieties produced is known to differ between countries/regions ,46 and rTEAC in organic and higher TAC in conventional table grapes) in this study.Supplementary analysis of composition differences between varieties of the same grape type identified in this study suggests that differences in the profile of varieties available as organic and conventional table grapes may also have contributed to overall effects of production systems detected  crop composition data which reported 20% higher antioxidant activity in organic crops . HoweverTEAC in organic than conventional white and red grapes was also reported in a recent farm survey-based study in Crete, which compared the effect of organic and conventional production system on the nutritional composition of traditional local grape varieties (2 white and 1 red) used as table grapes and for wine-making [Overall higher (~15%) TAAe-making .However, this study also demonstrated that the effect of the production system differs between varieties for a range of composition parameters assessed see  above. FTEAC and TAADPPH in red grapes, while da Silva Haas, et al. [DPPH is higher in organic than conventional red Lambrusco grapes, but higher in conventional white Albana and red Sangioves grapes, while no effect of production system was found in white Pignoletto grapes.This study also suggests that the effect of the production system can be confounded by both (a) production year or season (and associated pedo-climatic and supply chain differences) and (b) grape type and/or variety. The confounding effects of year/season (and associated pedoclimatic differences) and grape type/varieties identified in this study, may also explain the contrasting results of previous studies that compared antioxidant activity and/or concentrations in grapes from organic and conventional grapes. For example, in two studies carried out in Brazil, Toaldo, et al.  reported, et al.  found no, et al. ,23 reporThese interactions should be considered in the design of future retail and farm surveys, and experimental studies.There is increasing epidemiological evidence that the antioxidant/(poly)phenol compounds in food crops have protective effects against a range of chronic diseases ,60,61,62However, this study has identified changes in the grape type and to a lesser extent variety choice as the most important strategy to increase dietary intakes of phenolic compounds and the antioxidant activity associated with them. Specifically, the study suggests that switching from white to red and especially black grape consumption will increase TPC, TAA and TAC intakes  at the same level of consumption, as reported previously ,19,22,23The relatively small differences in TPC and TAA levels between grapes from the two production regions are unlikely to be nutritionallyrelevant. However, results suggest that targeted changes to variety choice and/or supply chain-related parameters may allow TPC and TAA levels and associated potential health benefits to be further increased in grapes imported from South Africa. However, this would require further studies to identify the parameters responsible for composition differences between seasons, which may include (a) variety choice, (b) primary production and harvest protocols, (c) pedo-climatic conditions and/or (d) postharvest treatments, storage and transport conditions.This study does not allow the potential overall nutritional/health impact of switching to organic grape consumption to be assessed. This is mainly, because organic and conventional crops were previously shown to not only differ in antioxidant activity and phenolic content (which were assessed in this study), but also concentrations of other nutritionally-relevant compounds  ,17,63 wh


Coronavirus disease 2019 is a recent strong challenge for the world. In this paper, an epidemiology model is investigated as a model for the development of COVID-19. The propagation of COVID-19 through various sub-groups of society is studied. Some critical parameters, such as the background of mortality without considering the disease state and the speed of moving people from infected to resistance, affect the conditions of society. In this paper, early warning indicators are used to predict the bifurcation points in the system. In the interaction of various sub-groups of society, each sub-group can have various parameters. Six cases of the sub-groups interactions are studied. By coupling these sub-groups, various dynamics of the whole society are investigated. Recently, many countries are dealing with coronavirus disease 2019 (COVID-19). COVID-19 is a dangerous disease with many death cases in many countries . The stuPredicting bifurcation points of the dynamical disease are important , 19. ManThe study of networks of systems can help to understand the collective behavior of systems. Complex networks have a great impact on human life . They haS, E, I, R are the number of susceptible, exposes, infected, and resistant people. Parameters In this paper, the SEIR model is used as a model for the development of COVID-19. It is a compartmental model of infectious disease and its epidemic outbreak . It contCOVID-19 –15. The To study the dynamical properties of the model, various bifurcations are investigated. Part (a) of Fig. The speed of moving people from infected to resistance is another parameter that is investigated in the following. Figure f is their functions. The nodes are connected by coupling matrix C, and In this section, the connections of five cities are considered to show the effect of intercity traffic restrictions. To reach this goal, System (1) is considered as the model of development of COVID-19 in each city. Then, the five cities are connected in a Watts–Strogatz network , 37. TheNow, various cases are studied. The initial values of variables are set constant as Table In the first case, we consider that no people can travel from one city to another one (In the second case, the cities are considered to have some connections to each other (In the third case, the cities are considered to have more significant connections to each other (In the fourth case, the cities are considered to have some connections to each other (To have a more realistic viewpoint, the parameters of cities are considered to be different. In the next two cases, parameters for each city are considered as, In the fifth case, the cities with various parameters are considered to have some connections to each other (In the sixth case, the cities with various parameters are considered to have more connections to each other (So, in cities with the same parameters, increasing the coupling strength causes the dynamics of five cities to become the same by passing enough time. However, in cities with various parameters, reaching the same dynamics needs a much bigger coupling strength. Also, decreasing parameter In this paper, the SEIR model was used as the model for the development of COVID-19 outbreak. In the first step of this study, various bifurcations of the model by changing some critical parameters such as the background of mortality without considering the disease state and the speed of moving people from infected to resistance were discussed. Then, autocorrelation was used to predict bifurcation points of the model. To visualize the collective behavior of COVID-19 by the effect of traveling between various cities, a network consisting of five cities was studied. The effect of various parameters and the coupling strength between cities was discussed. Watts–Strogatz network was used to simulate the connection of five cities. In the interaction of various cities, each city can have various parameters. By coupling these cities, various dynamics of the whole society were investigated. Six cases were defined to study various cases of cities interactions. The results showed that in cities with the same parameters, by increasing the coupling strength from zero, the dynamics of five cities become the same by passing enough time. However, in cities with various parameters, the same dynamics cannot be reached very quickly, and it needs a much bigger coupling strength. Also, the results showed that decreasing the parameter