Kecai yaks are an important genetic resource in Gansu Province, China. These yaks, produced through the crossbreeding of Gannan yaks and wild yaks, exhibit excellent production performance and high fecundity. Despite these beneficial characteristics, the genetic characteristics, population structure, and other properties of Kecai yaks have not been effectively characterized to date. Accordingly, this study was developed to explore the genetic diversity and population structure of Kecai yaks through whole-genome resequencing. These analyses ultimately revealed the status of Kecai yaks as an independent group within the overall Chinese yak population.Kecai yaks are regarded as an important genetic resource in China owing to their high fecundity and flavorful meat. However, the genetic characteristics of Kecai yaks have not been effectively characterized to date, and the relationship between Kecai yaks and other yak breeds remains to be fully characterized. In this paper, the resequencing of the Kecai yak genome is performed leading to the identification of 11,491,383 high-quality single nucleotide polymorphisms (SNPs). Through principal component, phylogenetic, and population genetic structure analyses based on these SNPs, Kecai yaks were confirmed to represent an independent population of yaks within China. In this study, marker and functional enrichment analysis of genes related to positive selection in Kecai yak was carried out, and the results show that such selection in Kecai yaks is associated with the adaptation to alpine environments and the deposition of muscle fat. Overall, these results offer a theoretical foundation for the future utilization of Kecai yak genetic resources. Bos grunniens) are a long-haired livestock species native to the Qinghai–Tibet Plateau and surrounding regions, living at an average altitude of over 3000 m. These yaks are uniquely adapted to high-altitude conditions such that they exhibit robust cardiopulmonary functionality, strong muscles, and good feeding performance [Bos mutus) populations, and have accordingly experienced a series of population bottlenecks, artificial selection events, and continuous bidirectional gene flow [Yaks . Blood samples for this study were obtained from the jugular vein of live yaks following surface disinfection with topical alcohol. Iodophor was applied to the site of venipuncture after blood collection was complete to prevent infection.For this study, 45 adult yaks of similar age, health status, and size were analyzed. A total of 9 Kecai yaks , 7 Gannan yaks , 10 Jiulong yaks , 10 Tianzhu white yaks , and 9 Jinchuan yaks  were included. DNA was extracted from individual blood samples with an EasyPure Blood Genomic DNA Kit . DNA purity and concentrations were measured with a Nanodrop 2000 spectrophotometer  based on OD260/280 values. The integrity of samples with an OD260/280 of 1.6–1.8 and a concentration of 50–1000 ng/µL were separated via 1% agarose gel electrophoresis (AGE) to ensure sample quality. Those samples that exhibited a single distinct AGE band were diluted to 50 ng/µL and stored at −80 °C. For sequencing analyses, these samples were fragmented into 350–500 bp segments with Covaris after which a TruSeq DNA LT Sample Prep kit was used for library construction. Briefly, DNA fragments were subjected to end repair, polyadenylation, the addition of sequencing connectors, purification, PCR amplification, and other necessary steps, with the final libraries then being used for 150 bp paired-end sequencing with the HiSeq X Ten platform . Wild yak genomic data were obtained from breeding genome data generated by the European Nucleotide Archive (EMBL-EBI) (Accession number: PRJNA285834), while Kecai yak sequencing data were uploaded to the Sequence Read Archive (SRA) (Accession number: PRJNA842787). The data were compared to genomic data from other local yak populations.Raw reads from Kecai yaks were filtered to remove low-quality reads, base duplications, and other forms of artificial bias. Library sequencing and data analyses were partially conducted by Shanghai OE Biomedical Technology Co. Raw reads were initially obtained in the fastq format following high-throughput sequencing, after which pre-processing was performed using fastp v 0.20.0   through https://broadinstitute.github.io/picard/) (accessed on 15 January 2022). To enable statistical analyses, the results were then compared with Qualimap [Reference genome alignment of the filtered reads was performed using BWA v 0.7.12 , using tSNP and InDel detection were performed using the Haplotypecaller module in GATK v.3.8.1  based onGATK was similarly used to analyze InDels in these data with the following screening criteria: QD < 2.0 || MQ < 40.0 || FS > 200.0 || SOR > 3.0 || MQRankSum < −12.5 || ReadPosRankSum < −8.0.The SnpEff program was used to annotate InDels and SNPs based on the reference genome . Annotathttp://evolution.genetics.washington.edu/phylip.html) (accessed on 15 January 2022). Feature vectors were computed with EIGENSOFT [To facilitate a genome-wide analysis of phylogenetic relationships, PLINK  was usedIGENSOFT , which wIGENSOFT , and opt2θπ ratio and Fst values were calculated using VCFtools [2θπ ratio values and the top 5% of Fst values were identified as selected regions of the genome, and the target genes were subject to functional enrichment analyses using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) functional annotation tools. The numbers of genes associated with these GO terms and KEGG pathways were counted, after which a hypergeometric distribution test was used to compute the significance of gene enrichment therein.Selected regions of the genome were identified by using the θπ ratio and Fst values for screening purposes , as thisVCFtools , with a In these resequencing analyses, an average of 209,142,764 raw reads were obtained per Kecai yak sample, with 208,238,267 valid reads (≥99%) being retained following the filtering of unqualified data. Overall, 95.23% of reads with a quality value ≥20 bases (sequencing error rate < 0.01), with a GC content of 43.14%, with good sequencing quality. After filtering, over 98.75% of these reads were successfully aligned to the reference genome .The genomes of 13 wild yaks and 45 domestic yaks from the Gansu and Sichuan provinces were analyzed. After filtering, 11,491,383 valid high-quality SNPs were retained for subsequent annotation and analysis. Resequencing was achieved at an average 6.7× depth with 99.07% average genome coverage. Intergenic regions accounted for the majority (64.77%) of these data , while iFollowing the filtering of InDel data for all yak populations, 1,404,453 InDel loci were obtained and associated genes were annotated. Of these InDels, 63.35% of the indels are located in the intergenic region, 33.13% in the intron region, and only 0.30% in the exon region b. Among To explore the genetic population structure of Kecai yaks and their relationship with other yak populations, genome-wide polymorphism analyses were performed for both domesticated and wild yaks. Phylogenetic trees developed based upon these genome-wide resequencing data indicated that each group of yaks clustered separately, with Kecai yaks being located immediately between wild and Gannan yaks, with some Kecai yaks being genetically similar to wild yaks but wholly separate from Gannan yaks, consistent with their identity as a separate group e. In a pThe genetic differentiation index (Fst) is frequently used in population genetics studies as a means of gauging the degree of genetic differentiation between two populations. When comparing the Xueduo and Kecai yak populations, the average Fst value was 0.00523, whereas it rose to 0.01998 when comparing Gannan and Kecai yaks. Xueduo yaks are primarily distributed throughout the Henan County located in Huangnan Prefecture, Qinghai Province, in the eastern region of the Qinghai–Tibet Plateau. Ganna yaks are primarily distributed in the Gannan Tibetan Autonomous Prefecture regions of Gansu Province. Greater differentiation was evident between Gannan and Kecai yaks relative to that observed between Xueduo and Kecai yaks. Higher levels of nucleotide diversity correspond to a higher degree of genetic variation within a given population. In these resequencing analyses, nucleotide diversity was 0.00121 in Gannan yaks, 0.00117 in Jiulong yaks, 0.00132 in Kecai yaks, and 0.00127 in Xueduo yak, suggesting that Kecai yaks exhibit the highest levels of nucleotide diversity among analyzed yak populations.The θπ ratio and Fst values were next used to screen the areas of the genome under selection using defined thresholds ; values above these thresholds indicate positive selection and can be divided into groups with unique characteristics. When comparing Gannan and Kecai yak samples, the selection area under positive selection was found to be greater than that under negative selection b.ACOX1 related to fat deposition was found.Genome-wide variations in the Gannan and Kecai yak populations were next analyzed, with the results being used for GO enrichment analyses of the 1882 identified genes . These gYaks are an invaluable genetic resource in the Qinghai–Tibet Plateau and surrounding high-altitude regions. Several reports estimate that yaks were initially domesticated from wild yak populations approximately 7300 years ago ,26. GannA phylogenetic tree was constructed by SNP, and it was found that wild yak and domestic yak were mainly divided into two different branches. Because Kecai yak is the offspring of a branch of Gannan yak crossed with wild yak, some Kecai yak are genetically close to wild yak. The genetic similarities between wild and Kecai yak populations are likely attributable to the fact that Kecai yaks were genetically distinguishable from wild and Gannan yak populations. When analyzing yak population structures at k = 2, these yaks were clustered into wild and domesticated yak samples in line with prior research ,27. WhenGenome-wide analyses revealed that over 50% of the selected regions of the Kecai and Gannan yak genomes were under positive selection, while further supporting the classification of Kecai yaks as a distinct yak subgroup. GO analyses of genes annotated in these selected regions revealed their enrichment in biological processes and molecular functions related to transfer between glycolipid membranes, including glycolipid transfer protein (GLTP) involved in ceramide transport, membrane interlipid transfer, intermembrane lipid transfer activity, ceramide 1-phosphate binding, and ceramide 1-phosphate transporter activities. GLTP is a soluble 23.8 kDa protein that can accelerate selective intermembrane glycolipid transfer ,29,30. GKEGG enrichment analyses indicated that genes in selected regions of the genome were most strongly enriched in the Staphylococcus aureus infection, estrogen signaling, and glycosaminoglycan biosynthesis–chondroitin sulfate/pidan sulfate pathways. Amino acids are essential taste-active compounds that play a central role in establishing the flavor of meat. The unsaturated fatty acid biosynthesis, linolenic acid metabolism, arachidonic acid metabolism, and linoleic acid metabolism pathways detected in this study are involved in muscle fat development, and ACOX1 is an acyl-CoA oxidate associated with fatty acid oxidative decomposition. ACOX1 is a highly conserved and unique enzyme that is highly expressed in the liver, with lower levels of expression being evident in the kidney, brain, and adipose tissue consistent with its importance in the context of fat metabolism ,38. ManyIn summary, a whole-genome resequencing strategy was used in this paper to explore the genetic diversity and population structure of Kecai yaks. The SNP markers used for these analyses revealed that Kecai yaks are genetically distinguishable from wild and Gannan yak populations. These Kecai yaks also exhibited evidence of the functional enrichment of positively selected genes relative to Ganna yaks, suggesting that these genes may play a role in the meat quality of these animals and their adaptation to alpine environments. The comprehensive analysis showed that the Kecai yak has unique genetic characteristics. This study provides a theoretical basis for the protection and utilization of Kecai yak resources.


Lolium multiflorum Lam., commonly known as Italian ryegrass, is a forage grass mostly valued for its high palatability and digestibility, along with its high productivity. However, Italian ryegrass has an outbreeding nature and therefore has high genetic heterogeneity within each variety. Consequently, the exclusive use of morphological descriptors in the existing varietal identification and registration process based on the Distinctness, Uniformity, and Stability (DUS) test results in an inadequately precise assessment. The primary objective of this work was to effectively test whether the uniformity observed at the phenological level within each population of Italian ryegrass was confirmed at the genetic level through an SSR marker analysis. In this research, using 12 polymorphic SSR loci, we analyzed 672 samples belonging to 14 different Italian ryegrass commercial varieties to determine the pairwise genetic similarity (GS), verified the distribution of genetic diversity within and among varieties, and investigated the population structure. Although the fourteen commercial varieties did not show elevated genetic differentiation, with only 13% of the total variation attributable to among-cultivar genetic variation, when analyzed as a core, each variety constitutes a genetic cluster on its own, resulting in distinct characteristics from the others, except for two varieties. In this way, by combining a genetic tool with the traditional morphological approach, we were able to limit biases linked to the environmental effect of field trials, assessing the real source of diversity among varieties and concretely answering the key requisites of the Plant Variety Protection (PVP) system. Lolium multiflorum Lam., commonly known as Italian ryegrass, is one of the most important groups of grasses largely used as forage crops due to its high productivity and high nutritional value as livestock feed, especially in terms of fiber palatability and digestibility [L. multiflorum can be used as a soil stabilizer during the winter to provide ground cover against soil erosion and depletion. Moreover, despite its lower persistence and stress tolerance in comparison with Lolium perenne, Italian ryegrass is more productive and can provide faster ground cover due to its timely emergence and seedling vigor.tibility ,2. Over L. multiflorum Lam. var. westerwoldicum Wittm. (Westerwolds ryegrass) can be distinguished by their complete flowering in the year of sowing from the biennial forms of L. multiflorum Lam. ssp. italicum (A. Br.) Volkarts, which generally produce very few seed heads in the sowing year, complete the cycle the following year after cold and short-day conditions, and remain leafy during the entire season.Both annual and biennial varieties are available on the market, and to prevent any misunderstanding, it is fundamental to clarify that they both belong to this species: the truly annual forms of Although Italian ryegrass is naturally diploid, tetraploid forms have been developed by chromosome doubling to achieve higher biomass production and better nutritional characteristics. The increase in an organism’s cellular ploidy caused by genome replication without mitosis, as occurred in Italian ryegrass using colchicine , has beThe most common method used to produce Italian ryegrass varieties is based on a recurrent selection strategy, consisting of repeated cycles of intercrossing among selected superior individuals. Almost 700 varieties of Italian ryegrass were reported in the 2022 edition of the OECD (Organization for Economic Co-operation and Development) list of varieties eligible for seed certification . This hiWithout a more precise and standardizable characterization, it is impossible to clearly differentiate one variety of Italian ryegrass from another and guarantee real compliance with the DUS requirements in the current Plant Variety Protection (PVP) system.L. multiflorum accessions has been reported by few studies using sequence-related amplified polymorphisms (SRAPs) [In this scenario, molecular tools would be useful in implementing the traditional DUS test, as proposed by Gilliland et al. , to avoi (SRAPs) , randoml (SRAPs) , and SSR (SRAPs) .In this study, we used 12 polymorphic SSR loci to genotype 14 Italian ryegrass commercial varieties, each composed of 48 individuals . In the downstream analysis, we determined the genetic similarity (GS), verified the distribution of genetic diversity within and among varieties, and investigated the population structure. The main aim was to concretely test whether the uniformity observed at the phenological level within each population of Italian ryegrass was confirmed at the genetic level through an SSR marker analysis. Thus, in this way, we limited biases linked to the environmental effect of field trials. Thus, we were able to evaluate the real source of diversity among varieties and obtained a concrete answer to the fundamental requisites of the PVP system.In this study, 14 commercial varieties of Italian ryegrass, differing in ploidy level (diploid or tetraploid) and vegetative habit  , were pr® 96 Plant Kit (Qiagen) following the manufacturer’s protocol. The quantity and quality of the gDNA were checked using a NanoDrop spectrophotometer  in terms of concentration and 260/280 and 260/280 ratios. Extracted gDNA was stored at −20 °C until further PCR amplification.Genomic DNA (gDNA) was extracted from young freeze-dried leaves finely ground with a TissueLyser II mill  using a DNeasyFor genotyping analysis, an initial batch of 28 primer pairs was chosen from Hirata  and Guan® Multiplex PCR Master Mix, 10% GC Enhancer , 0.25 μM of each tailed primer, 0.75 μM of each tailed reverse primer, 0.5 μM of each fluorescent labeled primer (Applied Biosystems), 20–30 ng of gDNA, and sterile water to volume. Touchdown PCRs were completed for all three multiplexes in 96-well plates under the following conditions: initial denaturation of 5 min at 95 °C, followed by 6 cycles at 95 °C for 30 s, extension at 65 °C for 45 s, which decreased by 1 °C with each cycle, and at 72 °C for 45 s, then 34 cycles at 95 °C for 30 s, at 59 °C for 45 s, and at 72 °C for 45 s. The reaction finished with a final extension step of 30 min at 60 °C. Finally, the quality of the amplicons was verified by electrophoresis run on a 2% agarose/1 TAE gel containing 1× SYBR Safe DNA Gel Stain (Life Technologies).The multiplex PCR mixtures had a total reaction volume of 20 µL resulting from 1 × PlatinumThe PCR products were dried at 65 °C and investigated with capillary electrophoresis using an ABI 3730 DNA analyzer, adopting the GeneScan 500 Liz as the molecular weight internal standard. Thus, chromatograms were screened to define amplicon size at each locus using Peak Scanner software 2.0 (Applied Biosystems).Two distinct datasets for marker statistics and analyses were constructed, setting different thresholds of missing data: a dataset admitting samples with missing data of two SSR loci at most, and a second dataset composed of samples with missing data of five SSR loci at most. The strictest dataset (576 samples) was uploaded to the NTSYS software package v.2.21c  and usedThe genetic relationship analysis was performed according to the maximum-likelihood method (ML) implemented in IQ-Tree v1.6.12 software. This approach enabled us to associate phylogenetic and combinatorial optimization techniques into a fast and effective tree search algorithm with the implementation of the ultrafast bootstrap approximation approach . The SSRa), number of effective alleles (Ne), and observed (Ho) and expected (He) heterozygosity within subpopulations assuming Hardy–Weinberg equilibrium according to Nei. These parameters were also calculated for each Italian ryegrass variety.On the other hand, the second most comprehensive dataset, including 644 samples, was used both for the SSR statistics and the population structure analysis. GenoDive v3.0 software  was usedST) and gene flow (Nm) were calculated for each marker locus. FST measures the amount of genetic variance that can be explained by population structure based on Wright’s F-statistics [m = {(1/FST) − 1}/4. An FST value of 0 indicates no differentiation between the subpopulations, while a value of 1 indicates complete differentiation [IT and FIS) were computed to measure the deficiency  or excess  of heterozygotes for each assessed microsatellite. Similarly, inbreeding coefficients were calculated at the multilocus level to estimate the genetic effect of total population subdivision as a proportional reduction in overall heterozygosity due to variation in SSR allele frequencies among different subpopulations. Finally, marker allele frequencies for each locus were also determined.F-statistics were computed, and the fixation index  values  was constructed for all possible pairwise comparisons between the fourteen varieties.Considering each variety separately, Wright’s inbreeding coefficient GIn addition, the population structure of the 644 samples was assessed using the clustering algorithm of STRUCTURE v2.2 software. Since no a priori knowledge of the origin of the populations under study was available, the admixture model was chosen. We ran the Markov chain Monte Carlo (MCMC) model with 100,000 iterations and a burn-in of 20,000 samples under the assumption that the allele frequencies in the populations were correlated. Ten iterations were conducted for each value of the number of populations (K), with K ranging from 1 to 20. The obtained results were analyzed using the STRUCTURE HARVESTER web software to calculate the best value of K according to Evanno et al. , and thea) of 19.9, ranging from 10 (02_01B) to 48 (02_10B). Moreover, the effective number of alleles (Ne) per locus varied from 1.7 (02_01B) to 5.2 (02_10B), as reported in a) and 3.5 (Ne), ranging from 4.4 in variety I to 9.3 in variety N and from 2.5 (variety A) to 4.6 (variety D), respectively  for single marker locus and population accessions were computed. The mean observed heterozygosity Ho equal to 0.498 ranged from 0.384 to 0.671 among the 12 loci; similarly, He ranged from 0.42 (02_01B) to 0.827 (02_10B) among loci, with a mean value of 0.649. The inbreeding coefficient (FIS) had an average value of 0.302 for microsatellite loci, derived from all positive values, except −0.024 of the 16_03D marker. Finally, FIT and FST were both positive and, on average, equal to 0.385 and 0.125, respectively, while the gene flow (Nm) was equal to 1.753. The calculated Nm values were >1 in all assayed marker loci (except for 02_02C and 12_05E), ranging from 0.871 to 3.987 over all accessions , hence supporting the little genetic differentiation between the fourteen varieties in the analysis.Descriptive statistics for Nei’s genetic diversity (H-statistics) and Wright’s inbreeding coefficients  over all the plant accessions scored a mean value significantly higher than the observed heterozygosity. As a consequence, Wright’s inbreeding coefficient GIS scored positive values, revealing a marked deficiency of heterozygotes across more than half of the varieties , although negative values of GIS were estimated for varieties F, I, M, and P, suggesting an excess of heterozygous individuals within these varieties.Considering each variety separately, the mean HST values indicate some genetic differentiation between populations  was detected between the M and N varieties, which showed that these varieties had the lowest genetic differentiation and differences. Conversely, the highest GST value (0.236) was presented between the A and L varieties, which had the highest genetic differentiation and differences.Pairwise Gulations . Levels IS showed all positive values, ranging from 0.142 to 0.62 , since at the multilocus level, the inbreeding coefficient G to 0.62 .Genetic variability within and between varieties was investigated primarily by calculating genetic similarity (GS) for all possible pairwise comparisons among the 576 samples (the strictest dataset) using the entire set of marker alleles scored at all genomic loci. In particular, a pairwise genetic similarity matrix was calculated using a simple matching coefficient. Rohlf’s genetic similarity ranged from 78% to 99% among all individuals analyzed. When calculated within each variety, GS varied on average from 88.5% (±2.03) within the N variety to 92.6% (±1.99) within the G variety . In the In addition, an analysis of molecular variance (AMOVA) was conducted to better understand the distribution of genetic differentiation among and within varieties of Italian ryegrass. Findings from AMOVA revealed that 87%  of the total genetic variation was contributed by differences within varieties, which was notably and significantly higher than that among varieties, since only 13% of the total genetic variation was due to differences among varieties.Clustering analyses were performed to identify PCoA centroids based on the genetic similarity estimates and to draw the maximum likelihood (ML) dendrogram. Generally, the ML dendrogram revealed a slightly structured distribution of Italian ryegrass accessions . In mostPrincipal coordinates analysis graphically represented the spatial distribution of the samples . To obtaFor the biennial varieties, even though most of the accessions were nearly plotted in the central part of the four main quadrants, individuals belonging to the L variety were grouped together and well separated from the other samples. The first two principal components were able to explain 60.3% of the total genetic variation found within the population of the biannual varieties. In particular, the first component, which explained 33.9% of the total diversity, discriminated samples of the L and G varieties from the C and D varieties. On the other hand, with the second component, explaining 26.4% of the total diversity, accessions of the L variety could be distinguished from the G samples and part of the individuals belonging to the M and N varieties. In addition, as shown in the dendrogram, C could not be distinguished from D and partially from E.Based on the marker alleles at all SSR loci, the genetic structure of the Italian ryegrass core collection (644 samples) was analyzed using STRUCTURE v. 2.2 software  and StruStarting from the graphical representation of K = 2, each sample is plotted as a vertical histogram divided into K = 2 (and then for K = 13) with colored segments representing the estimated membership in each hypothesized ancestral genotype. The first clustering of the considered genotypes revealed that 518 of the 644 samples showed a strong ancestral association (>90%). Individuals’ membership with the first identified cluster was observed to be higher than 80% in almost all of the analyzed accessions. Particularly, populations A, B, C, D, O, and P had 94%, 91%, 98%, 89%, 92%, and 79% of samples with membership to the first cluster higher than the considered threshold, respectively. On average, all of these varieties presented a membership higher than 90% (except for P with 84%) with the main cluster. On the other hand, populations E, F, G, H, I, and L had 80%, 100%, 100%, 87%, 93%, and 98% of the samples with membership with the second cluster higher than 80%, respectively. Additionally, in this case, the average membership with the second cluster of all these varieties was higher than 90%, with the exception of the E variety with 87%. In contrast, most of the admixed genotypes  were from the M and N varieties, with 62% and 67% of the samples, respectively. Specifically, these two populations showed complementary average membership to the two hypothesized ancestral genotypes: the M variety had 63% and 37% membership to Cluster 1 and Cluster 2, while the N variety had 40% and 60%, respectively. More generally, other populations had a very low percentage of admixed samples with this clustering, ranging from 24% and 20% for the E and P varieties to the total absence of admixed genotypes in the F and G populations.The second largest ΔK revealed an additional level of population structure and allowed the clustering of all investigated genotypes into thirteen additional subgroups. Interestingly, the ancestral population size K = 13 corresponded to the number of varieties used in this study, combining the M and N varieties into a unique admixed group. On average, all individuals of the same variety showed a membership higher than 50% to a specific cluster, which was different for each variety (exceptions were observed for varieties M and N). In addition, membership mean values higher than 80% were reached in the B (82.4%-Cluster 12), C (84.6%-Cluster 4), F (84%-Cluster 7), G (83.9%-Cluster 11), I (87.5%-Cluster 1), and L varieties (80.5%-Cluster 13) by the majority of their individuals. The only cluster shared by two different varieties (M and N) was Cluster 3, with an average membership equal to 50.8% and 68.8%, respectively. Moreover, considering those samples with a membership to the major cluster lower than 80% as admixed, the percentage of admixed samples within the same population ranged from 64% (the M variety) to 13% (the I variety). In particular, the highest proportions of admixed samples were shown within the H (58%), D (57%), N (56%), and O varieties (52%). In contrast, the I, C, and F populations had only 13%, 25%, and 25% admixed samples, respectively.Morphological characteristics have been used for descriptive purposes and are traditionally used to distinguish plant varieties. However, these methods are questionable because of the strong effect of the environment on morphological traits. In addition, this approach is inefficient because of the time and cost involved . MoreoveL. multiflorum Lam. is a crucial step toward a more trusted variety identification and stronger protection for breeder rights.In this study, 14 commercial varieties of Italian ryegrass were tested with 12 SSR loci, analyzing a total of 672 samples to assess their intrapopulation and interpopulation genetic variation and differentiation and the structure of the population as a whole, and in turn to evaluate them in the PVP context. Detecting genetic variability by means of marker allele composition, allele proportion, and multilocus genotypes in different accessions of L. multiflorum Lam. varieties. Moreover, in perennial ryegrass cultivars, the total within-cultivar component of genetic variation was 85% [As a general rule, the outcrossing breeding system of self-incompatible species, along with the annual life cycle, may have a central role in affecting the conservation of genetic diversity in Italian ryegrass. Indeed, for species with outcrossing mating systems, within-variety variation is usually high because pollen can be widely spread between varieties, resulting in a low degree of differentiation attributable to among-varieties variation . In this was 85% . In tetr was 85% .IS = 0.302, on average), a reduced fixation index , and a high gene flow  between overall accessions confirm that most allele diversity and genotype variation are found within populations and that genetic differentiation among varieties is low. Such a low genetic differentiation can be attributable to a high gene flow among populations because of pollen dispersal among too close multiplication fields of different varieties. In addition, along the variety selection and commercialization process other possible causes could be related to variability of heading time and consequent preferential pairing, climate/location effect during seed batch multiplication, or any possible admixture events during storage and bagging processes. Interestingly, the heterozygosity deficiency seen in our results, with a consequent robust deviation from Hardy–Weinberg equilibrium, is not only a common observation in commercial varieties due to the human-induced bottleneck and artificial selection, but also attests to the low variability in these accessions.The simultaneous occurrence of a marked inbreeding rate , and again, the intra-variety genetic similarity value of the N population was practically the same as that among the M and N populations . In other words, we can assume that the populations with the highest within variability (M and N), according also to STRUCTURE results, can be considered the most closely related. According to all these results, we can therefore say that the M and N varieties are not distinguishable from each other. In contrast, ML clustering analysis clearly suggested that the A accession has a gene pool clearly distinct from the other accessions, hence clustering apart from the core of varieties. Furthermore, in the pairwise comparisons with other varieties, the genetic similarity values of the L population were the lowest, confirming the resulting values in the pairwise STF comparisons.The STRUCTURE analysis suggested moderate structuration of populations and the existence of admixed ancestry based on two or thirteen distinct gene pools. It should be noted that the subdivision in two genetically distinguishable subgroups does not reflect either the two different ploidy levels or the two vegetative habitus. However, the resulting information from the STRUCTURE analysis partially confirmed the outcomes from the maximum likelihood dendrogram. In particular, the I, L, and G varieties could have the same hypothesized ancestral genotype according to STRUCTURE analysis and formed a monophyletic group in the ML cladogram with significant UFB support (91). Moreover, samples belonging to the M and N varieties appear to be closely related to each other. In fact, when K = 13 in the STRUCTURE analysis, M and N samples were the only ones to share the same ancestral gene pool , and in the ML dendrogram, they were always mixed and clustered together. Additionally, in the pairwise In conclusion, if it is true that these fourteen commercial varieties of Italian ryegrass did not show high degrees of genetic differentiation, it is also true that, when analyzed as a core, each variety described a genetic cluster on its own, resulting in distinguishability from the others. The only evident exception was represented by the M and N varieties. Given their biennial tetraploid nature, a common recent origin from a shared ancestor could be assumed, as reported also by the population structure analysis. Interestingly, from what was reported in the varietal sheets, these two cultivars are morphologically similar, showing a similar growth habit and comparable heading time and inflorescence length, although the M variety should have longer stems and bigger leaves than the N variety.The registration of a new variety in the Italian National Register of Varieties still does not take genetic information into account, and the features used to distinguish the candidate variety are genealogical, phenotypic, and other agronomic traits . Molecul


Existing empirical work has analysed the impacts of COVID‐19 on mortality, fertility and international migration. Less is known about the ways in which the COVID‐19 pandemic has influenced the patterns of internal migration. Anecdotal reports of mass migration from large cities to less populated areas have emerged, but lack of data has prevented empirically assessing this hypothesis. Drawing on geographically granular administrative population register data, we aim to analyse the extent of change in the patterns of internal migration across the urban hierarchy in Spain during 2020. Our results show a decline of 2.5% in the number of internal migration moves, particularly during the early stages of the pandemic, returning to pre‐pandemic levels in late 2020. Results also reveal unusually large net migration losses in core cities and net migration gains in rural areas. Net migration losses in cities and gains in rural areas particularly accumulated following the elimination of the strict lockdown measures in June. Yet, these net losses and gains trended to pre‐pandemic levels in late 2020, and movements between cities, and between cities and suburbs, continued to dominate the internal migration system. Thus, while the COVID‐19 pandemic exerted notable changes in the geographic balance of internal migration flows, these changes appear to have been temporary and did not significantly alter the existing structures of the national migration system. This is similar to the low migration intensities observed in other countries in Southern and Eastern Europe, including Italy, Greece, Poland, Romania, Russia and Czech Republic  to identify their key destinations along the urban hierarchy and extent of variations across cities in 2020. Third, we analysed the spatial patterns of internal migration at the municipal geographical scale to identify key changes across the internal migration system and the extent of these variations in less populated areas. Finally, we explored monthly changes in the levels of internal migration flows during 2020 to determine the durability of the internal migration patterns observed during the COVID‐19 pandemic.3.1We had access to a unique and large administrative data set recording all individual reported changes in place of residence in Spain. We drew on data from official microdata collected by the (EVR) of the Instituto Nacional de Estadística (INE) from 2016 to 2020 for 8131 municipalities. An open access version of this data set is available to researchers, but it does not include information for municipalities with less than 10,000 inhabitants, which equate to 90.7% of all Spanish municipalities. The data set we used includes data for all municipalities. During the lockdown, mainly in the early stages, EVR registrations were affected by underreporting, but the effect of this influence is unclear. On the one hand, closure of some in‐person EVR registration offices may have resulted in under‐reporting, with EVR capturing a lower number of changes in residential locations than those occurring. On the other hand, telematic services were rapidly deployed across the country, enabling digital registration. Additionally, selective local and regional mobility restrictions on nonessential activities were implemented during the last 4 months of 2020 where COVID‐19 cases increased, mostly in cities . This source only includes urban areas, therefore core cities and their suburbs are listed, but not towns and rural areas. It used several variables to classify municipalities as urban areas, such as administrative criteria, population density, size, trends and structure, urban morphology, housing market, transport infrastructures or labour market characteristics. Core cities represent central municipalities of urban areas and are classified based on administrative criteria, including most Spanish capital cities. We classified municipalities which are not considered as urban areas into towns or rural areas if they are larger or smaller than 10,000 inhabitants, respectively. Table Stage 2. We analysed variations in internal migration patterns across core cities. Focusing on a selection of five core cities , we examined changes in out‐, in‐ and net‐migration rates from these cities to their suburbs (according to the MITMA), other urban areas (core cities and suburbs), towns and rural areas. We chose these cities because they represent key population agglomerations in the Spanish settlement system with populations of over 300k, recorded large overall increases in net migration losses during the COVID‐19 pandemic in 2020 (higher than 50% compared to 2016–2019) and provide a diverse overview of changes in local regional internal migration systems. For our analysis, we used city‐specific out‐migration rates (ORs), in‐migration rates (IRs) and net‐migration rates (NRs):iO is the number of migrants moving out of the origin area i; Ii is the number of migrants moving to the destination area i; and Pi is the middle population.Stage 3. We analysed the spatial patterns of internal migration using municipality‐specific ORs, IRs and NRs to identify the location of key internal migration winners and losers during COVID‐19 in 2020 and quantify the demographic impact of out‐migration flows from these cities to less populous areas.Stage 4. We analysed monthly changes in the level of internal migration to assess the continuity of internal migration patterns during COVID‐19 and shed light into future patterns. To establish the extent of changes in internal migration patterns during COVID‐19, we compared monthly internal migration counts in 2020 to those recorded in prepandemic years between 2016 and 2019. This comparison captures monthly seasonal variations in internal migration patterns and enables determining the extent to which observed variations deviate from the long‐term trajectory in internal migration intensity. We also analysed these trends across the urban hierarchy, to assess the extent of variation in the volume of internal migration during COVID‐19 across core cities, suburbs, towns and rural areas.44.1Taken together, the number of moves decreased from 1.56 million to 1.52 million (2.5%) between the prepandemic 2016–2019 average and 2020. Although there was not a significant difference in the total number of movements, Figure During the pandemic in 2020, a pattern of population deconcentration emerged reflecting net migration losses in high‐density areas and net migration gains in more sparsely populous locations. Core cities recorded a rise in out‐migration by 6.0% (515k–546k) in 2020, and a drop in in‐migration by 15.4% (494k to 418k). These changes resulted in a population loss due to internal migration of 127k in 2020, representing an increase in annual population loss in core cities. Annual prepandemic net‐migration during the 2016–19 period averaged −20k. By contrast, rural areas recorded a decrease in out‐migration by 12.6% (296k–258k), which was met by a rise in in‐migration by 20.5% (288k–347k), leading to an overall positive net‐migration balance of 88k in 2020. In rural areas, this represents a reversal of prepandemic population losses due to internal migration, and a trend of rising counterurbanisation. Yet, movement between core cities and suburbs continued to dominate the internal migration system in 2020.4.2We next analyse out‐, in‐ and net‐, migration outcomes for a selection of five core cities. Figure Although rising declines in net migration rates are observed for population exchanges with all types of areas for our sample of cities, the largest drops consistently occurred for migration interactions with rural municipalities, reflecting an acceleration in counter‐urbanisation, especially in Madrid and Barcelona. Figure 4.3We then explored the spatial patterns of internal migration at the municipal level to understand the general structure of internal migration flows. Figure 4.4As indicated in Section These changes conceal distinctive temporal patterns across core cities, suburbs, towns and rural areas. While all areas recorded a notable drop in in‐migration and out‐migration during March–May, variations in the intensity and recovery of these outcomes during June and November resulted in distinctive net migration balances Figure . Core ci5During the early phases of the COVID‐19 pandemic, anecdotal evidence of an urban exodus emerged. This hypothesis suggests that the concentration of COVID‐19 in cities, teleworking, lockdowns in poor housing conditions and the shutdown of urban vibrancy led to large migration outflows from cities to less populated areas Davies, . Our resWe provided evidence revealing that the largest Spanish cities experienced the highest increase in migration outflows and declines in migration inflows, especially Madrid and Barcelona, as it has been also observed in Stockholm in Sweden  to capture internal migration movements. As indicated in Section The author declares no conflict of interest.Supplementary information.Click here for additional data file.


The Healthy Cities project supports municipal policymakers in the struggle to safeguard the health of urban citizens around the world (and in other limited geographies such as islands). Although Healthy Cities has been implemented in thousands of settings, no synthesis of implementation experiences have been conducted. In this article, we develop a scoping review protocol that can be applied to collect evidence on process evaluations of Healthy Cities.To develop a scoping review protocol that could identify experiences evaluating the Healthy Cities project, we followed the PRISMA guidelines for Scoping Reviews (PRISMA-ScR). We applied these guidelines in consultation with a research librarian to design a search of the peer-reviewed literature, specifically Ovid Medline, Ovid Embase, Web of Science Core Collection, and Scopus databases, and a grey literature search.In addition to the aim of collecting evidence on Healthy Cities process evaluation experiences, the broader goal is to spark discussions and inform future evaluations of Healthy Cities. This work can also inform other evaluations of initiatives seeking to raise socio-political change, such as those focused on enhancing intersectoral and multisectoral action. From the initial eleven European cities selected for the project in 1986, this quickly grew to 650 cities in 1993 , to overGiven that Healthy Cities entails various theoretical elements, including: “proximal and distal determinants of health, proximal and distal interventions for health, and ‘known impact’”; this complicates evaluation 8, pp. i23]. O’Neill and Simard . O’Neill. For insWe are interested understanding approaches taken to evaluate the approach itself across various settings . We are not interested in evaluating the relationship between the Healthy City projects on individual-level outcomes associated with behaviour change or similar . In other words, we are interested in assessing impacts  rather than outcomes. An impact is “a result or change that has come about as the result of complex interactions between a range of factors, including Healthy City designation, but potentially much wider  and is driven by priorities determined by the Healthy Cities value system” (11); whereas an outcome is “is a result or change that can be directly attributed to such an activity or intervention within a Healthy City […] Or more succinctly: outcome evaluation assesses the result in terms of achievement of objectives set” (11). Because ‘The’ Healthy City does not exist, as each city operates within its own unique context , we are In addition to this primary aim, we are also interested in understanding if consideration is afforded to the context in which the city operates, such as cities of the global south, and if so, how this consideration is built into evaluation. This is supported by the aforementioned evaluation from Chittagong, which determined that Healthy Cities projects established in developing countries are fundamentally different than those in industrialized nations, calling for both the need to adapt projects and conduct comparative analysis of Healthy Cities projects in developing countries .While Healthy Cities seems to have an inherent tension between research and practice , evaluatTo design a scoping review protocol that could identify experiences evaluating the Healthy Cities project, we drew on the work of Arksey and O’Malley , wherebyThis study protocol can be applied to synthesize evidence on how evaluations of Healthy Cities  have been conducted through drawing on both peer-reviewed and grey literature. Thus, asking: how has the Healthy Cities project or approach been evaluated?Considering that “the real success of any Healthy City project is when it ceases to be a project, because the system it set up to ensure that health issues are given priority, to involve all stakeholders and to ensure that all sectors recognize that their role in healthy cities becomes part of the structure of local governance” , pp. 27,As such, the inclusion criteria eligibility is as follows: (i) must discuss the healthy cities project/approach , (ii) describe an evaluation undertaken or report results of an evaluation of the approach itself applied within a city, cities, community, etc., and (iii) available in English due to resource constraints.References are excluded if they are either (i) not evaluating the Healthy City approach itself, (ii) evaluating health outcome indicators  rather than an evaluation of the approach itself—and cases where the Healthy City approach was evaluated using various indicators that may include health outcomes will be included, (iii) evaluating a program that is not a Healthy City project, despite seeking to improve health , (iv) commentary, reflection, or interview discussing evaluation issues , or (v) the full text is not available.The search strategy was developed with an academic librarian possessing relevant expertise of appropriate databases and comprehensive search strategies for knowledge synthesis projects. The strategy was designed to cast a wide net, searching a multitude of databases and grey literature from the WHO, namely the: Ovid MEDLINE, Ovid EMBASE, Web of Science Core Collection, Scopus, and WHO Institutional Repository for Information Sharing (IRIS) databases. These numerous databases will be searched to minimize any potential gaps, as the Ovid databases are focused on biomedicine, whereas the Web of Science Core Collection and Scopus draw from a range of disciplines, thus ensuring articles that may be missed through searching biomedical databases will be retrieved in interdisciplinary databases, and vice versa. In addition, through searching the WHO’s IRIS, grey literature hits, specifically WHO texts, will be included that would not be retrieved through these four aforementioned databases. The search strategy will include relevant keywords such as healthy city/healthy cities, healthy municipality/municipalities, healthy community/communities, healthy island(s), evaluation, assessment, effectiveness, efficacy, and indicator(s), and the subject heading of program evaluation. No publication date limit will be applied, but results will be filtered so that only English language results are included. The databases to be searched and associated search strategies are provided in Covidence software  will be Studies marked for inclusion will be further assessed through ‘citation chaining’ . This entails both reviewing sources cited in the included references and checking resources that cite these included studies to determine if there are any potentially missed references that meet the inclusion criteria. This will be undertaken with Web of Science automatically when this stage is reached.Data extracted from the full texts will be charted across: title, author(s), journal or book title, location of evaluation, method of evaluation , who conducted the evaluation, indicators assessed/what was evaluated, rationale for the evaluation, and consideration for city context. These dimensions were informed by the work of O’Neill and Simard  and de LThe PRISMA diagram will be used to illustrate the review process and delineate stages where studies were eliminated with the associated reason. The charted data will be narratively synthesized, drawing on the dimensions to thematically group findings in the discussion of the manuscript. We hypothesize being able to point to both commonalities and differences across evaluations and raise important considerations for those undertaking an evaluation of a Healthy Cities project.Given the resource constraints faced in undertaking this study, as only literature available in English will be assessed, we understand that this is a limitation to this work. Similarly, despite undertaking a systematic approach to reviewing grey literature, given the vast amount of grey literature available, it is possible there may be missed sources. However, in seeking to overcome this difficulty, we intend to publish the findings of the completed review to make the findings more easily accessible for researchers and policymakers.Given that the Healthy Cities approach has been implemented in thousands of settings but faces the problem of limited synthesized evaluations, we believe it is crucial to gain a better grasp of the landscape in which this inconsistency operates. Our pursuit of assessing the nature of process evaluations in the Healthy Cities projects is supported by other scholars, such as those who have emphasized the importance of evaluation for examining efforts and justifying investments made . Given tS1 Checklist(DOCX)Click here for additional data file.


Traditional fermented foods, which are well-known microbial resources, are also bright national cultural inheritances. Recently, traditional fermented foods have received great attention due to their potential probiotic properties. Based on shotgun metagenomic sequencing data, we analyzed the microbial diversity, taxonomic composition, metabolic pathways, and the potential benefits and risks of fermented foods through a meta-analysis including 179 selected samples, as well as our own sequencing data collected from Hainan Province, China. As expected, raw materials, regions (differentiated by climatic zones), and substrates were the main driving forces for the microbial diversity and taxonomic composition of traditional fermented foods. Interestingly, a higher content of beneficial bacteria but a low biomass of opportunistic pathogens and antibiotic resistance genes were observed in the fermented dairy products, indicating that fermented dairy products are the most beneficial and reliable fermented foods. In contrast, despite the high microbial diversity found in the fermented soy products, their consumption risk was still high due to the enrichment of opportunistic pathogens and transferable antibiotic resistance genes. Overall, we provided the most comprehensive assessment of the microbiome of fermented food to date and generated a new view of its potential benefits and risks related to human health. Fermentation is one of the oldest and most economical methods for food storage and processing in the world. It has been widely used to improve food safety, shelf life, and sensory and nutritional properties . The IntTraditional fermented foods usually depend on natural wild colony fermentation as the main production mode. In fermentation, a variety of microorganisms from raw materials and the environment are usually introduced. This process can involve the use of nutrients in the raw materials to change the texture and edible quality of the food through metabolic pathways and produce a unique fermentation fragrance . The micNext-generation sequencing technology has completely changed microbial research, including that regarding the microbial community in food, by enabling high-throughput gene analysis of mixed microbial communities . MetagenHere, based on the shotgun metagenome approach, we explored the microbiome of different traditional fermented foods at the species level; revealed the microbial diversity, taxonomic composition, and metabolic pathways of different fermented foods; and comprehensively analyzed the potential benefits and safety risks of the different fermented foods to human health. We hope to provide a scientific basis for consumers to know more about fermented food and provide direction for the development of the traditional fermented food industry.A detailed flowchart of the sample collection process is shown in ® DNA Mini Kit  according to the instruction manual. After detection for integrity and purity, the shotgun metagenome sequencing was carried out by an Illumina HiSeq 2500 instrument . The whole metagenome library preparation and sequencing process used services from Beijing Novogene Technology Co., Ltd.Samples were stored at –20°C until DNA extraction. After homogeneously mixing 10 g of the fermented food sample with 90 mL of sterile NaCl solution , total DNA was extracted from the diluent of the mixture by a QIAampp-value < 0.05 was considered to be significantly different.MetaPhlan 2 software was used to annotate and classify metagenomic species, and HumanN 2 was used to annotate metagenomic metabolic pathways. By comparing the microbial sequences with the CARD database, the abundance of microbial antibiotic resistance genes (ARGs) was obtained . StatistThe metadata of the samples are listed in p < 0.05) in the microbial α diversity of fermented foods with different raw materials (p < 0.05)  based on Bray–Curtis distance was used to compare β diversity. The results showed that there were significant differences  . In addi < 0.05) , and β d < 0.05) .p < 0.05) and mean relative abundance greater than 0.05%   in different substrate fermented foods by calculating the Spearman rank correlation coefficient. Network diagrams with correlation coefficients r greater than 0.4 between core microbes and metabolic pathways of various basal fermented foods are shown in  < 0.05) . The resLeuconostoc mesenteroides widely existed in other kinds of fermented foods, except fermented soy products. Lactococcus lactis was the beneficial bacterium in fermented bean products, and its number accounted for more than 70% of the beneficial microbes in this kind of fermented food. The main opportunistic pathogen in fermented dairy products was Bacillus amyloliquefaciens, and Streptococcus infantarius was the most important opportunistic pathogen in fermented foods with marine protein. In addition, microbes in fermented soy products had the most types of resistance genes  are an important class of probiotics in the human body, with immunomodulatory, anti-inflammatory, antioxidative, and antiproliferative functions  can be found below: MX: investigation, project administration, formal analysis, writing—original draft, and data curation. SS, ZZ, SJ, and JZ: project administration, conceptualization, and writing—review and editing. YX and XH: funding acquisition, conceptualization, validation, project administration, and writing—review and editing. All authors contributed to the article and approved the submitted version.


Paranoia describes unfounded interpersonal threat beliefs. Secure attachment imagery attenuates paranoia, but limited research examines mechanisms of change and no studies examine how secure imagery may be implemented most effectively in clinical practice. In this study, we tested: (a) the causal impact of secure, anxious, and avoidant attachment imagery on paranoia and anxiety, (b) whether emotion regulation strategies mediate these relationships, and (c) whether secure imagery buffers against social stress.We utilized a longitudinal, experimental design.N = 265) completed measures of paranoia, anxiety, and emotion regulation strategies. Participants were randomly allocated to secure, anxious, or avoidant conditions and repeated an imagery prime for four days prior to a social stress task.A general population sample with high non‐clinical paranoia  hyperactivating strategies mediated the association between attachment anxiety and paranoia, and (b) suppression mediated the association between attachment avoidance and paranoia.Secure attachment imagery reduces state paranoia and anxiety and could be incorporated into psychotherapies to attenuate clinical paranoia. Measurement of state emotion regulation was problematic. Attachment imagery does not buffer stress; further research is required to test whether secure imagery facilitates recovery from stress. Attachment style is likely to account for trait paranoia via attachment‐congruent emotion regulation strategies. Research is now needed to determine if these strategies can be targeted to alleviate paranoia in clinical populations. In clinical practice, secure attachment imagery may be effective in reducing state paranoia and distress.Attachment styles influence the way that people typically regulate emotion which, in turn, impacts paranoia. Emotion regulation may therefore be an important therapeutic target to attenuate paranoia and associated distress.after stress.Secure attachment imagery does not buffer the impact of stress. This result requires replication in clinical groups, and future research should test whether secure imagery facilitates recovery Secure attachment imagery priming reduces paranoia in non‐clinical  distress regulation strategies due to inconsistent or rejecting attachment figures. Attachment anxious adults tend to Several studies evidence hyperactivating and deactivating strategies in people with psychosis  working models and observing whether this influences subsequent cognitions and emotions  and extend previous research by examining: (a) whether the impact of attachment imagery on paranoia is mediated by hyperactivating (rumination and catastrophization), deactivating (suppression and distractionWe sought to extend the emerging evidence base for secure attachment imagery as a therapeutic technique to attenuate paranoia. We examine the https://osf.io/j8ckrThe study was pre‐registered (23.03.21): ≥53  on the Paranoia Scale were eligible . Many were from Portugal (26%), Poland (23%), UK (10.2%), and Italy (9.1%). Most identified as White/British/Caucasian (67.9%).We recruited adults from the general population with high levels of non‐clinical paranoia.p = .05 with three groups and measurements, and one covariate, 251 participants are required. For mediation, Kline  from 1  to 5 (extremely applicable to me).The Paranoia Scale  to 10 (very much). Internal consistency was good at Time 1a (α = 0.83), 1b (α = 0.88), and 4 (α = 0.83).The Adapted Paranoia Checklist (APC) measures state paranoia  from 1  to 4 . We used a 6‐item version (STAI‐6) of the state subscale , 1b (α = 0.92), and 4 (α = 0.85). Participants rated the frequency of state items from 1  to 4 (very much).The State and Trait Anxiety Inventory (STAI) measures trait and state anxiety  and attachment avoidance (α = 0.81) (6 items each). Participants rated items from 1 (disagree strongly) to 7 (agree strongly).The Experiences in Close Relationships Inventory‐Short‐Form , catastrophization (α = 0.78), self‐blaming (α = 0.60), other‐blaming (α = 0.76), reappraisal (α = 0.67), putting into perspective (α = 0.64), acceptance (α = 0.74), positive refocusing (α = 0.72), and refocusing on planning (α = 0.73). In the absence of validated state suppression/distraction scales, and given that the CERQ does not measure suppression, we developed items to measure state and trait suppression  and distraction (“I try to distract myself” and “I try to turn my attention away” [α = 0.82]).almost never) to 5 .The Cognitive Emotion Regulation Questionnaire (CERQ)‐Brief  measures e α = 0.6, acceptastate rumination (α = 0.79), catastrophization (α = 0.91), reappraisal (α = 0.79), and putting into perspective (α = 0.68). State suppression (α = 0.65) and distraction (α = 0.86) were measured using the items above. Participants reported how they were reacting right now, and rated items from 1  to 5 (completely).We also used the CERQ‐brief to measure We used scripts to manipulate attachment imagery  to 10 (very much), percentage of time that the image was held in mind (0–100%), and felt security  they felt from 1  to 6 (very much).On Day 1, participants rated image‐vividness from 1  to 4 (very much).Cyberball  scored higher on attachment anxiety  and avoidance  than those who did not have high paranoia (N = 561): attachment anxiety ; avoidance .Between‐group differences on demographic and trait measures are reported in Tables F[2262] = 123.81, p < .001, η2 = 0.49). All groups reported comparable levels of image‐vividness . Participants, across all conditions, were able to hold the imagery in mind for 80% of the time, on average; however, between‐group differences emerged  – the avoidant group held the image in mind for less time than the secure group  and negative affect  post‐Cyberball and, as predicted, reported more negative than positive affect post‐Cyberball  on most variables.Mixed‐model Analyses of Covariance (ANCOVA) were conducted on state paranoia and anxiety with one between‐subjects factor , one within‐subjects factor , 1b (post‐imagery), and 4 , and one covariate  (Hypotheses 1 and 4). Simple effects tests with multiple comparisons and paired Descriptive statistics for the state measures are reported in Table As predicted, the three conditions did not differ in paranoia and anxiety at Time 1a (pre‐imagery), but differed at Time 1b (post‐imagery). At Time 1b, relative to the secure imagery condition, the anxious and avoidant imagery conditions reported higher paranoia and anxiety, as hypothesized Table . ContrarFrom Time 1a to 1b (pre‐ to post‐imagery), paranoia and anxiety decreased in the secure imagery condition and increased in the anxious and avoidant imagery conditions, as hypothesized Table . In the There was no main effect of percentage image held in mind nor a percentage×time interaction for both paranoia and anxiety.One‐way ANOVAs were used to test Hypotheses 2a, 3a, and 4a. Counter to expectations, there were no between‐imagery group differences on any of the state ER strategies , and avoidant relative to secure imagery (D2) . Relative specific indirect effectsabps; Hayes, Dummy coding was used to produce two variables: anxious relative to secure imagery (α = 0.84) and deactivating (α = 0.81) variables, respectively. Putting into perspective was not correlated with reappraisal, deactivating ER, or paranoia, and therefore was dropped from mediation analyses. There were no correlations between reappraisal and anxiety, so we did not examine reappraisal in the anxiety model.Rumination and catastrophization, and suppression and distraction, were positively correlated Table  and thusD1, but there was a direct effect of D2, on state paranoia . The same model was tested to compare anxious and avoidant imagery . Previous research shows that trait hyperactivating ER strategies mediate the association between global attachment anxiety and trait paranoia . Attachment avoidance was correlated with trait suppression but not distraction, and distraction was not associated with trait paranoia or anxiety  than post‐imagery (Time 1b), suggesting that secure imagery failed to buffer the impact of the stressor. While it is possible that the repeated imagery was less effective at Time 4 due to practice effects, a recent systematic review suggests that repeated attachment primes tend to have a cumulative effect  Cyberball increased state paranoia and anxiety in the secure imagery group with large effects and maintained high paranoia and anxiety levels in the insecure imagery groups, (b) no indirect effects emerged when only those who were highly distressed following Cyberball were included in analyses, and (c) previous research consistently shows that Cyberball effectively increases paranoia  imagery on paranoia or anxiety, and deactivating ER did not mediate the impact of avoidant (vs. secure) imagery on paranoia and anxiety. These results are likely to be due to problems with the measurement of ER described previously.The results also showed that relative to the secure imagery group, the anxious imagery group used less deactivating ER and therefore had higher paranoia. A possible explanation is that some deactivating ER items could be interpreted in positive ways . Additionally, it may be that distraction and suppression are adaptive in the context of Cyberball; for example, while avoidance is maladaptive for solvable problems, it is arguably optimal for unsolvable problems  may be a useful addition to CBT to support clinical (symptom‐reduction) and recovery  outcomes, which are currently modest (Jones et al., The results also suggest that secure imagery does not buffer stress. Future research should test whether secure imagery facilitates recovery after stress – if so, psychotherapies might support people to use secure imagery when distressed or after discussing difficult topics such as trauma or adversity (which are common in clinical populations with psychosis [Varese et al., Monica Sood: Conceptualization; Data curation; Formal analysis; Funding acquisition; investigation; methodology; Project administration; visualization; Writing–original draft; Writing–review&editing. Katherine B. Carnelley: Conceptualization; methodology; supervision; Writing–review&editing. Katherine Newman‐Taylor: Conceptualization; methodology; supervision; Writing–review&editing.None.Open Science FrameworkThis article has a preregistered research design available at Table S1Table S2Table S3Click here for additional data file.


Plant genetic resources (PGRs) are the total hereditary material, which includes all the alleles of various genes, present in a crop species and its wild relatives. They are a major resource that humans depend on to increase farming resilience and profit. Hence, the demand for genetic resources will increase as the world population increases. There is a need to conserve and maintain the genetic diversity of these valuable resources for sustainable food security. Due to environmental changes and genetic erosion, some valuable genetic resources have already become extinct. The landraces, wild relatives, wild species, genetic stock, advanced breeding material, and modern varieties are some of the important plant genetic resources. These diverse resources have contributed to maintaining sustainable biodiversity. New crop varieties with desirable traits have been developed using these resources. Novel genes/alleles linked to the trait of interest are transferred into the commercially cultivated varieties using biotechnological tools. Diversity should be maintained as a genetic resource for the sustainable development of new crop varieties. Additionally, advances in biotechnological tools, such as next-generation sequencing, molecular markers, in vitro culture technology, cryopreservation, and gene banks, help in the precise characterization and conservation of rare and endangered species. Genomic tools help in the identification of quantitative trait loci (QTLs) and novel genes in plants that can be transferred through marker-assisted selection and marker-assisted backcrossing breeding approaches. This article focuses on the recent development in maintaining the diversity of genetic resources, their conservation, and their sustainable utilization to secure global food security. Genetic diversity is the amount of genetic variability present among individuals of a variety or a population within a species. It is the product of the recombination of genetic material (DNA) during the inheritance process, mutations, gene flow, and genetic drift , and it In general, plant genetic resources (PGRs) are the total hereditary material, which includes all the alleles of various genes, present in a crop species, including horticulture and medicinal plants, and their wild relatives. They can also be defined as any type of reproductive or vegetative propagating material of the plant species. PGRs include newly developed varieties, cultivated crop varieties, landraces, modern cultivars, obsolete cultivars, breeding stocks, wild forms, weedy forms, wild species of cultivated crops, and genetic stocks, including current breeders’ lines, elite lines, and mutants. These are the building blocks for the genetic improvement of agricultural and industrial crops . Most ofMaintaining diversity in PGRs is vital for the development and genetic improvement of crop varieties. Presently, the plant species extinction rate is skyrocketing, and life on Earth is facing a sixth mass extinction event caused by climate change and anthropogenic activities, which may lead to ecological collapse . The LeiToday, the conservation and sustainable use of PGRs is a priority of the global community to solve issues surrounding food security and other problems arising from increased population growth. In the future, these resources will completely vanish if proper and stringent PGR conservation practices and policies are not implemented . This chGenetic diversity is the genetic base for crop improvement . Diverse1 and advanced generations are developed by crossing two or more diverse parents. The offspring developed from two genetically diverse parents possess genetic variations because of recombination during meiosis. Hence, genetically dissimilar offspring from parents are produced. However, this is the genetic material of individuals underlying the variability within, as well as between, species [Genetic diversity in plant species depends on the heritable variation present within and between populations. It occurs due to genetic variation in the nucleotide sequence of DNA, chromosome mutations, and recombination during sexual reproduction . In the  species . General species . Before  species . For theGenetic diversity changes over time owing to several factors. The main factors responsible for changes in genetic diversity are mutation, selection, genetic drift, and gene flow. Over time, natural and artificial selections play a substantial role in the choosing of superior genotypes, which significantly affects the gene and genotypic frequencies of the population . As per Mutations are sudden heritable changes that occur due to aberrations in the nucleotide sequence of DNA. A mutation is the source of genetic variation impacting the phenotype in crop species. Genetic diversity caused by mutations can have neutral, positive, and negative impacts on various characteristics of a plant species. Genetic variations caused by mutations in DNA are the principal cause of changes in the allele frequencies in a population besides selection and genetic drift. From the beginning, natural or spontaneous mutations have played a significant role in creating the genetic variation that has led to food security . MutatioNatural and artificial selections act on the phenotypic characteristics of the plant species. The phenotypic expression of the plant species depends upon the heritable and non-heritable components in which the genotype–environment interaction also plays a significant role. The selection of superior genotypes depends on the availability of genetic variation present in the plant species. Artificial selection is effective only when sufficient genetic variation is present in the population. The genetic improvement of a genotype depends on the magnitude of genetic variability present in the population, as well as the nature of the association between different components. For example, the level of association of yield traits with other characteristics of the plant species enables the selection of various traits at a time . Plant bMigration is the movement of alleles from one species to another or from one population to another. It occurs through the movement of pollen and seed dispersal and planting material such as rhizomes, suckers, and other vegetative propagating materials. The rate of migration is affected by reproduction cycles and the dispersion of seeds and pollens. Migration can also occur through the moving or shifting of the germplasm from one area to another, which results in the mixing of two or more alleles through pollen and seeds .Genetic drift is a mechanism in which the gene and allele frequencies of a population change due to sampling errors over generations. The sampling error changes the allele frequencies by chance, which ultimately changes the genetic diversity over generations. Every pollen grain has a different combination of alleles and can be carried by insects, wind, humans, or other means for hybridization with compatible flowers, largely determined by chance. Thus, in every reproduction cycle, the genetic diversity in crop species is lost at every generation through these chance events .Over the past century, it has been observed that the genetic diversity in wild populations is declining globally ,37. GeneThe main reason for genetic erosion and vulnerability is the cultivation of genetically uniform cultivars with a narrow genetic base. Indigenous or traditional crop varieties have a broad genetic base, and these cultivars can tolerate various biotic and abiotic stresses . TraditiThe widespread cultivation of a single crop variety over a large area causes genetic vulnerability. These varieties may perform well for a short period but may become susceptible to several diseases and pests. Vertical resistance occurs due to the presence of oligogenic or monogenic resistance, and horizontal resistance occurs due to the presence of polygenes. Sometimes the vertical resistance present in the modern cultivar may show resistance against a disease, but will become susceptible if the pathogen evolves. In vertical resistance, the race of the pathogen or the insect pest biotype interacts with the host and overcomes the monogenic resistance present in the modern cultivar, and the variety becomes susceptible to a particular pathogen or biotype.Helminthosporium maydis). The southern corn leaf blight disease colonized and spread widely, and the whole maize crop was wiped out. If the TMS, a source of male sterility, had been tested and screened properly before use in hybrid breeding programs, or if the monoculture of TMS hybrids had been avoided, the spread of this epidemic could have been countered [Sometimes, new high-yielding plant species are introduced and used in a breeding program without proper screening for disease and insect pest resistance, which may result in an unpredicted epidemic of diseases. An example of this is the unplanned introduction of the Texas male sterile (TMS) genotype of maize for the development of hybrid maize genotypes in the USA in 1970. Newly developed maize hybrids had all the desirable characteristics and resistance to most of the common maize diseases. The TMS hybrids were widely cultivated in the USA, covering more than 90% of the maize area. However, these hybrids were susceptible to fungal strains and southern corn leaf blight  came into force in 2004. ITPGRFA works in harmony with the CBD for sustainable agriculture and food security. The objective of the treaty is the conservation and sustainable use of plant genetic resources for food and agriculture and the fair and equitable sharing of the benefits arising from their use. The conservation and sustainable use of PGRFA are essential to achieving sustainable agriculture and food security, for present and future generations, and are indispensable for crop genetic improvement in adapting to unpredictable environmental changes and human needs.The Nagoya Protocol, which came into force in 2014, aims to access genetic resources and encourage the fair and equitable sharing of benefits arising from their utilization. The Nagoya Protocol helps in ensuring benefit-sharing, creates incentives to conserve and sustainably use genetic resources, and therefore, enhances the contribution of biodiversity to development and human well-being.The Svalbard Global Seed Vault situated in Norway safeguards duplicate seed varieties from almost every country in the world. The Seed Vault is owned and run by the Ministry of Agriculture and Food on behalf of the Kingdom of Norway and is established as a service to the world community. The Global Crop Diversity Trust provides support for the ongoing operations of the Seed Vault, as well as funding for the preparation and shipment of seeds from developing countries to the facility. The Nordic Genetic Resource Center (NordGen) operates the facility and maintains a public online database of samples stored in the seed vault. It provides insurance against both incremental and catastrophic loss of crop diversity held in traditional genebanks around the world. The Seed Vault offers long-term protection for one of the most important natural resources on Earth. The main purpose is to backup genebank collections to secure the foundation of our future food supply.The Cartagena Protocol on Biosafety’s goal is to provide safety in the handling of genetic resources, particularly genetically modified organisms. It is an international agreement that aims to ensure the safe handling, transport, and use of living-modified organisms (LMOs) resulting from modern biotechnology that may have adverse effects on biological diversity, while also taking into account risks to human health.The ever-increasing demand resulting from the explosive growth rate of the human population worldwide, and global warming, have forced world communities to think about the sustainable use of PGRs. The conservation of PGRs, including landraces, obsolete varieties, breeding material, wild species, and their wild relatives, is of utmost importance to secure future food security . The vanIn in situ conservation, genetic resources are conserved in their natural habitat, and the species are maintained in their original place. The plant species are conserved where they are found and are maintained in their original location . In in sEx situ conservation is the conservation of different genetic resources outside their natural habitat. It involves the conservation of seed gene banks, plant tissue culture, cryopreservation, greenhouses, etc. It is the process of conserving endangered and overexploited genetic resources outside their natural habitat, which otherwise may experience habitat destruction and degradation, and every PGR may go extinct. Therefore, ex situ conservation is an alternate method of conserving valuable genetic resources . In thisGenerally, the conservation of collected seeds is carried out in two ways: base collection and active collection. Base collection is the collection and maintenance of seed samples for long-term conservation. In this case, the seed samples are stored for the maximum time of seed viability at −18 to −20 °C . In the Plant biotechnology tools provide new opportunities for the conservation of genetic resources using various in vitro culture techniques. Various biotechnological tools, such as cell and tissue culture and other micropropagation techniques, have greatly contributed to the storage and transportation of PGRs . Cell anIn vitro gene banks are where PGRs are stored in an artificial nutrient medium. This is an alternative method to conserving the vegetative propagated plant genetic material ,60. The The successful production and propagation of genetically stable plants from cultures are prerequisites for in vitro conservation. Shoots are used for slow-growth storage to avoid somaclonal variations. This slow-growth storage is optimal for the medium-term conservation of PGRs ,62,63. IThe cryopreservation technique involves the storage of biological plant tissue for conservation at ultra-low temperatures (−196 °C), mostly using liquid nitrogen. In cryopreservation, the plant species can be stored for a long period as all the activities, such as cellular metabolism and cell division in recalcitrant seeds and vegetatively propagated plant material, stop. In this approach, no sub-culturing is required, and the chances of somaclonal variations are also reduced ,66. The Advances in molecular biology have made the conservation of endangered and rare species complementary. Genetic resource conservation through DNA is a cost-effective form of conserving PGRs. In biodiversity, many species are difficult to conserve and are at the stage of extinction. DNA storage may be one of the best alternatives to conserve the genetic diversity of these resources, which could possess novel genes/alleles that could aid in future food security. In a gene bank, genomic fragments consisting of individual genes or entire genotypes are conserved in a gene library or a library of DNA samples. Genetic information can be stored in the form of DNA, RNA, and cDNA. These libraries are the primary source of important germplasm for future scientific research worldwide. DNA conservation is an alternative method of conserving PGRs, where the genetic materials are difficult to conserve or threatened because of wild populations or climate change . The genDigitized molecular data are vital to numerous aspects of scientific research and genetic resource use. Substantial advances in DNA sequencing over the last decades hold great potential to enhance food security and the sustainable use of global biodiversity, benefiting the world’s poorest people. Digital Sequence Information (DSI) plays a crucial role in catalyzing research applications that can contribute to international societal and biodiversity conservation targets. There are concerns over access to genetic resources and the absence of benefit sharing by provider countries. Open access to DSI might exacerbate this, which is leading to increasing policy interventions and restricted access to genetic resources and DSI. However, benefit sharing related to DSI is difficult to identify and hindered by the lack of clear international governance and legislation, which, in turn, has led to a reluctance to make DSI publicly and freely available.Before modern cultivated crop varieties, landraces had more genetic diversity. Modern varieties are developed for specific traits, such as high yield, disease resistance, insect pest resistance, stress tolerance, and the improvement of nutritional characteristics. The plant breeders select diverse parents from PGRs in crossing programs to develop new crop varieties . New croWith the advent of modern biotechnological techniques, the efficiency of plant breeders has significantly increased in the development and improvement of crop varieties. Next-generation sequencing (NGS), high-throughput sequencing (HTS), and high-throughput phenotypic (HTP) techniques enable more efficient use of PGRs. Among the various available techniques, DNA-based techniques are more reliable and widely used in crop improvement programs. Unlike other markers, molecular markers are not influenced by the environmental changes and developmental stages of plants . MoleculWith the advances in high-throughput sequencing techniques, SNP markers are preferred for use in crop improvement programs. Various QTLs have been identified by developing a biparental population using PGR populations ,95,96. BBiotechnological tools have been efficiently used for the improvement of susceptible crop varieties. However, for the sustainable utilization of genetic resources, advanced techniques, such as NGS, HPG, and HTP, should be used to develop new crop varieties to ensure food security in the near future.To meet the ever-increasing demand for food production, crop diversification, climate-resilient farming, etc., PGRs should be used for sustainability for future food security. However, the efficient use of PGRs can help to meet these needs, and one of the major challenges in the PGR community is to improve access to PGR collections by increasing the amount of information available about collections, through conservation, by participating in pre-breeding activities, etc. A great challenge in the PGR community is the increased demand for PGRs in the wider farming and breeding community. Maintaining genetic diversity, the conservation of PGRs, and sustainable utilization should be the priority of national and international communities. The proper monitoring of genetic erosion and genetic diversity vulnerability is crucial to protecting rare and endangered plant species. As no single technique of conservation is perfect, there is a need to practice in situ and ex situ conservation complementarily. Technical as well as financial support should be provided to farmers and local people for the proper conservation of plant genetic resources. For the management and sustainable use of PGRs, the capacities of local communities, indigenous people, farmers, breeders, extension workers, and other stakeholders, including entrepreneurs and small-scale enterprises, should be strengthened. The proper evaluation, characterization, and documentation of endemic plant species and their exact habitats should be prioritized. More frameworks and policies should be implemented for the sustainable conservation of landraces and their wild relatives. Biotechnological tools should be used for the characterization of plant genetic resources, conservation, and their utilization in breeding programs. Allele/gene mining for important traits in wild species and wild relatives of crops should be given more importance. The effective utilization of plant genetic resources would contribute to solving constraints that limit crop productivity. High-throughput genotypic and phenotypic techniques should be used for the sustainable utilization of genetic resources for future food security.


Luzula sect. Luzula. Several morphologically very similar species with different karyotypes have evolved, but their evolutionary origins and relationships are unknown. In this study, we used a combination of relative genome size and karyotype estimations as well amplified fragment length polymorphism (AFLP) fingerprinting to investigate the relationships among predominately (sub)alpine Luzula alpina, L. exspectata, L multiflora and L. sudetica in the Eastern Alps, including also some samples of L. campestris and L. taurica as outgroup. Our study revealed common co-occurrence of two or three different ploidies  at the same localities, and thus also common co-occurrence of different species, of which L. sudetica was morphologically, ecologically and genetically most divergent. Whereas agmatoploid L. exspectata likely originated only once from the Balkan L. taurica, and hexaploid L. multiflora once from tetraploid L. multiflora, the AFLP data suggest multiple origins of tetraploid L. multiflora, from which partly agmatoploid individuals of L. alpina likely originated recurrently by partial fragmentation of the chromosomes. In contrast to common recurrent formation of polyploids in flowering plants, populations of agmatoploids resulting by fission of complete chromosome sets appear to have single origins, whereas partial agmatoploids are formed recurrently. Whether this is a general pattern in Luzula sect. Luzula, and whether segregation of ecological niches supports the frequent co-occurrence of closely related cytotypes in mixed populations, remains the subject of ongoing research.Polyploidisation, agmatoploidy and symploidy have driven the diversification of  Polyploidy is one of the most important evolutionary pathways in flowering plants and has significantly contributed to their diversification and radiation ,2,3,4. MContrary to true polyploidy, where the genome size is expected to increase proportionally to the increase in ploidy level , theLuzula sect. Luzula (Juncaceae). The fission of chromosomes led to three karyotypes characterized by differently sized chromosomes, namely full-size chromosomes (AL-type), half-size chromosomes (BL-type) and quarter-size chromosomes (CL-type). Due to partial agmatoploidy or hybridization, combinations between these basic karyotypes are also possible [Luzula sect. Luzula is represented by eight taxa, whose distribution in the Eastern Alps has recently been revised based on an extensive herbarium revision combined with genome size and karyotype estimation [L. alpina (karyotype 12 AL + 24 BL), L. exspectata (24 BL), L. multiflora  and L. sudetica, (48 CL) [Both true polyploidy as well as agmatoploidy and symploidy have driven the diversification of possible ,20,27. Itimation . However (48 CL) ,29.L. sudetica that is divergent both morphologically, having small seeds with very short caruncles and relatively small flower parts with dark tepals and capsules, and ecologically, growing in moist meadows and bogs in the montane and alpine zones [L. exspectata  as well as the hexaploid populations of L. multiflora from tetraploid L. alpina and L. multiflora, only karyological investigations can reliably distinguish the last two taxa [Luzula alpina and L. sudetica prefer siliceous substrate but can also be found on limestone on locally acidic or, in the case of L. sudetica, wet soils. On the other hand, L. exspectata predominantly grows on limestone, but can occasionally be found on siliceous bedrock, and L. multiflora thrives on both substrates. All four species appear to be widespread in the Eastern Alps, with L. alpina and L. sudetica being most common in the Central Alps and L. exspectata in the Southern Alps [L. exspectata in the Northern Alps [With the exception of ne zones ,30, the ne zones ,29,30,31two taxa . In addiern Alps . A few rern Alps  were basern Alps .L. sect. Luzula are available to date. In a phylogenetic study of Luzula based on plastid trnL–F and internal transcribed spacer (ITS) sequences [L. sect. Luzula remained unresolved. It is well known that in flowering plants, polyploids can be formed recurrently within single species [L. exspectata and L. sudetica monophyletic. Bačič et al. [L. exspectata (24 BL) might have originated via chromosome fission from L. taurica (V. I. Krecz) Novikov, a species with 12 AL chromosomes, distributed between the Balkan Peninsula and the Caucasus [L. sudetica (48 CL) could have originated from L. exspectata [L. multiflora (24 AL) could be of autopolyploid origin, whereas the lowland hexaploid populations (36 AL) are probably of allopolyploid origin. Likewise, L. alpina (12 AL + 24 BL) could be of allopolyploid origin [L. exspectata (24 BL) and L. taurica (12 AL) acting as putative parents [L. multiflora, we hypothesized that L. alpina could be a partial agmatoploid, which originated by the fission of half of the chromosomes of L. multiflora.Little is known about the origin of and the phylogenetic relationships among the four species, as no phylogenetic studies providing sufficient resolution among the species of equences , relatio species , but notč et al.  hypothesCaucasus ,31. In tspectata . Kirschnspectata  suggested origin , with L. parents ,28,29. ALuzula sect. Luzula based on a comprehensive geographic sampling of almost 440 individuals across the Eastern Alps. We applied ploidy level estimation via flow cytometric measurements of relative genome size (RGS) to discriminate among diploid L. exspectata and L. sudetica, tetraploid L. alpina and L. multiflora, and hexaploid L. multiflora. In addition, we estimated the chromosome number of several individuals in order to discriminate between tetraploid L. alpina and L. multiflora and to establish the karyotype of the diploids from the Northern Alps. Finally, we used amplified fragment length polymorphisms (AFLP) to explore the relationships among the four species. Specifically, we investigated whether polyploid and agmatoploid populations have single or multiple origins.Taking into account the unclear evolutionary history, the aim of the present study was to shed light on the relationships among the four alpine species of L. taurica  and 24 BL of L. exspectata , as well as two tetraploid karyotypes, i.e., 24 AL of L. multiflora  and 12 AL + 24 BL of L. alpina , whereas individuals from all other localities, including four individuals from locality 1 and five from locality 2 had higher RGS ranging from 0.52 to 0.54. RGS values of the karyotyped individuals of L. alpina and L. multiflora were scattered across the entire higher range of tetraploid RGS variation, indicating no divergence in RGS between the two species. Among the hexaploids, two individuals had slightly lower RGS (0.74 and 0.77), whereas all others had their RGS ranging from 0.78 to 0.82. One individual from locality 2 had an RGS of 0.66, intermediate between the tetraploids and hexaploids, suggesting that it may be pentaploid. Besides this odd-ploidy cytotype, at the same locality, eleven individuals were tetraploid, four were hexaploid and two were diploid.RGS was discretely distributed . DiploidL. exspectata and/or L. sudetica were intermingled with tetraploid individuals of L. alpina/L. multiflora at a small spatial scale; occasionally, single hexaploid individuals of L. multiflora were growing at the same localities  scattered across them. Finally, all hexaploid individuals formed a separate cluster positioned within the tetraploids. The PCoA revealed similar results, with diploids and hexaploids being most divergent  and L. sudetica (2n = 48 CL) both have a single origin. This may suggest that fission of chromosomes leading to different agmatoploid karyotypes is not a common process. In the absence of comparable large-scale studies including multiple populations in both Luzula as well as other genera with incidence of agmatoploidy [Contrary to the commonly recurrent formation of polyploids , our restoploidy ,24,28,33L. sudetica is not just morphologically and ecologically [L. sudetica originated once via chromosome fission from L. exspectata (2n = 24 BL), and shared splits between these two taxa are in support of this hypothesis. However, the sampling of additional species with the 24 BL karyotype such as L. divulgatiformis Bačič & Jogan would be needed to further test this hypothesis. Likewise, the origin of L. exspectata from the Balkan L. taurica (2n = 12 AL) via chromosome fission suggested by Bačič et al. [L. campestris (2n = 12 AL) appeared more distant. Finally, L. pallescens, the third diploid with 12 AL karyotype that could have acted as a parent of L. exspectata, was not included in our study; further studies are therefore needed to finally resolve the origin of L. exspectata. Both karyotype  Schleich. [Senecio carniolicus Willd. group [Contrary to the diploid species and the hexaploid populations of clusters , suggestigata L. ,35, Lotuchleich.  and—mored. group .L. campestris in the NeighbourNet , that we did not include in our study, but since the latter species does not occur in the Eastern Alps, this hypothesis appears less plausible.The position of hbourNet  close tothe Alps , it appeirschner  suggesteL. alpina, Kirschner [L. exspectata (24 BL) and L. taurica (12 AL) could be its putative parents. However, genetic data in the present study do not support this hypothesis, as karyotyped individuals of L. alpina were scattered among karyotyped individuals of L. multiflora within different AFLP clusters . We also included two individuals of L. campestris (L.) DC. from two localities and eight individuals of L. taurica from a single locality (both 2n = 12 AL) as outgroups  of 4′,6-diamidino-2-phenylindole (DAPI)-stained nuclei was used to estimate the RGS following the procedure described by Suda and Trávníček . The RGS pg DNA; ) as a re pg DNA;  was usedL. exspectata, 29/11 of L. sudetica, 174/27 of tetraploid L. alpina/L. multiflora , 32/10 of the hexaploid L. multiflora, as well as two individuals from two populations of L. campestris and eight individuals from one population of L. taurica as outgroup  in the size range from 100 to 500 bp using the default peak detection method. Automated binning and scoring of the AFLP fragments were performed using RawGeno 2.0-2  with theSplitsTree4 v.12.3  was used