Phedimus takesimensis (Ulleungdo flat-leaved stonecrop) is endemic to Ulleung and Dokdo Islands off the east coast of the Korean Peninsula. It was suggested that P. takesimensis originated via anagenetic speciation from the continental progenitor species P. kamtchaticus or P. aizoon. However, little is known of the phylogenetic relationships and population genetic structure among species of Phedimus in the Korean Peninsula and Ulleung/Dokdo Islands. We inferred the phylogenetic relationships among congeneric species in Korea based on nuclear ribosomal DNA internal transcribed spacer and chloroplast noncoding regions. We also sampled extensively for P. takesimensis on Ulleung Island and the continental species, P. kamtschaticus and P. aizoon, to assess the genetic consequences of anagenetic speciation. We found (1) the monophyly of P. takesimensis, (2) no apparent reduction in genetic diversity in anagenetically derived P. takesimensis compared to the continental progenitor species, (3) apparent population genetic structuring of P. takesimensis, and (4) two separate colonization events for the origin of the Dokdo Island population. This study contributes to our understanding of the genetic consequences of anagenetic speciation on Ulleung Island. Echium of the Canary Islands  from Mt. Seokrisan  could be recognized as infraspecific taxa of S. kamtschaticum  and S. ellacombianum [= P. ellacombianus] were clustered with S. takesimense, while S. aizoon [= P. aizoon] formed a distinct and separate cluster from the S. kamtschaticum group [P. kamtschaticus occurs widely in the Korean Peninsula and neighboring regions , P. ellacombianus is restricted to the southern part of the Korean Peninsula [P. aizoon is closely related to P. takesimensis genetically based on RAPDs (randomly amplified polymorphic DNAs) [P. takesimensis and its relationship to a continental progenitor was based on one noncoding chloroplast (cp) region (trnL-F) [P. takesimensis and two individuals of P. kamtschaticus), two chlorotypes were found; “type01” was found exclusively on Ulleung Island , while “type02” was found in 17 individuals from the Ulleung and Dokdo Islands. In addition, two individuals of P. kamtschaticus—as a continental progenitor—were similar to the chlorotype “type02” in that they had a 6-bp deletion but were distinguished by a single point mutation [Phedimus cultivar identification study, including several purported wild progenitor species, demonstrated unresolved species relationships within the genus [P. takesimensis was unresolved with P. middendorffianus and P. kamtschaticus based on nuclear ribosomal DNA (nrDNA) internal transcribed spacer (ITS) sequences, while one cp noncoding region (psbA-trnH) sequence suggested an unresolved relationship with P. aizoon, P. kamtschaticus, and P. middendorffianus. It seems likely that this lack of clear species relationships could be attributed to various factors, such as polyploidization, aneuploidization, interspecific gene flow, concerted evolution of nrDNA, incomplete lineage sorting of ancient polymorphisms, lack of sufficient cpDNA variation, and any combination of these. While precise species relationships within the genus remain to be determined, it is reasonable to consider that P. kamtschaticus is one of plausible continental progenitor species of P. takesimensis on Ulleung Island based on morphological characteristics.Considering the origin of endemic um group . While Peninsula . It was ic DNAs) . The fir(trnL-F) . Based omutation . Recentlhe genus . For exaP. takesimensis on Ulleung and Dokdo Islands and estimated their genetic variation and population structure based on five cpDNA noncoding regions. Then, we compared the genetic diversity and population genetic structure of P. takesimensis with two representative continental progenitor species (P. kamtschaticus and P. aizoon). Lastly, we took a phylogenetic approach to determine the phylogenetic position of P. takesimensis among the congeneric species occurring in Korea. Based on extensive sampling and the combination of population genetics and phylogenetic approaches, we hope to (1) estimate the level of genetic variation between insular endemic and purported continental progenitor species, (2) reveal the population genetic structure of P. takesimensis on Ulleung and Dokdo Islands, (3) determine the relationship between Ulleung and Dokdo Island populations of P. takesimensis, and (4) infer the relationship between insular derived endemic P. takesimensis and continental congeneric species.In this study, we sampled extensively Phedimus in Korea, we sampled nine accessions of P. aizoon, 10 accessions of P. kamtschaticus, 15 accessions of P. takesimensis, and two accessions of P. ellacombianus , Gyeonggi-do Province (two locations: Mt. Ungil and Mt. Munsu), Chungcheongnam-do Province (one location: Taean-gun), Gyeongsanbuk-do Province (one location: Pohang-si), Jeollanam-do Province , and Jeollabuk-do Province (two locations: Mt. Deogyu and Mt. Jiri). For P. latiovalifolius, which is endemic to Korea, we sampled a total of 10 accessions from Gangwon-do Province (Taebaek-si) and one accession from the same 15 populations sampled for the population genetic study for P. takesimensis  from Korea. Phedimus kamtschaticus occurs widely in East Asia, including eastern China, Russia, and Japan, but population-level sampling was not possible for those regions. The 10 populations from the Korean Peninsula represent the typical distribution range of P. kamtschaticus, which include the northeastern most population (YON), the southernmost population (MUD), and the westernmost population (AN), enabling us to assess their relationships to P. takesimensis , representing the northern region , eastern region , southern region , and southwestern/western region   . Voucherand TEA) .atpI-atpH, trnC(GCA)-ycf6, trnL-trnF, 3’rps16-5’trnK(UUU), and ndhJ-trnF(GAA)) [Taq polymerase, and 40.75 μl of ddH2O. The following PCR conditions were used for the chloroplast DNA regions: an initial denaturation of 95°C for 2 min, 35 cycles of 95°C denaturation for 1 min, 50–56°C annealing for 2 min, 72°C extension for 2 min, and a final extension at 72°C for 10 min. The following were the nrDNA ITS region reaction conditions: an initial denaturation of 94°C for 1 min, 35 cycles of 94°C denaturation for 1 min, 54°C annealing for 2 min, 72°C extension for 2 min, and a final extension at 72°C for 10 min. The PCR products were visualized using electrophoresis on a 1% agarose gel, purified using an Inclone Gel and PCR purification kit , and sequenced using Big Dye Terminator Cycle Sequencing reagents  at Geno Tech. Corp. . For the sequencing reactions, we used the same primers as those used for the PCR.Silica-gel dried leaves collected from the natural populations were used as DNA sources for the DNA extraction using DNeasy Plant mini kit  following the standard protocol. We screened 21 noncoding regions of chloroplast DNA and selected five variable noncoding regions ) . We alsonF(GAA)) ,41. PolyPhedimus in Korea, we conducted a separate phylogenetic analysis for the nrDNA ITS and four chloroplast noncoding regions . The maximum likelihood (ML) analysis was conducted using IQ-TREE v. 1.4.2. [All sequences were edited and assembled using Sequencher 4.2.2  and Geneious Pro v R.8 , and were deposited at GenBank with the accession numbers MK752203–MK752392. The sequences were aligned using Clustal X version 1.83 , with a . 1.4.2. , with 1,P. takesimensis and the purported continental progenitors P. kamtschaticus and P. aizoon in Korea, we concatenated four previously used chloroplast noncoding regions and one more highly variable region (rps16-trnK) to achieve more resolutions. We constructed a haplotype network using TCS version 1.21 [For the population level analysis of insular derived ion 1.21 . Gaps weion 1.21 . To deteion 1.21  with theion 1.21  was alsoion 1.21 .P. takesimensis, (c) the continental progenitor species P. aizoon, and (d) the continental progenitor species P. kamtschaticus. The significance levels of the AMOVA were evaluated using 1,023 permutations. A SAMOVA  using ARLEQUIN version 3.5 . The AMOariance; ) was useariance;  using Arariance;  and DnaSariance; . Unimodaariance; . Tajima’ance; [D  and Fu’s; [D [FS  were calFS [SSD; ) betweenSD; [RI; ) of the Phedimus was strongly supported as a monophyletic group (100%)  included P. takesimensis and the other (75% BS) included P. kamtschaticus, P. ellacombeanus, P. latiovalifolius, and P. aizoon. The latter lineage was not well resolved, but it showed that P. ellacombeanus is unresolved with P. kamtschaticus, while P. latiovalifolius (88% BS) and P. aizoon (79% BS) represent a separate distinct lineage. Two individuals of P. kamtschaticus (HAM1 and SAM1) were part of the P. aizoon clade (84%).The total aligned length of the nrDNA ITS was 697 sites. ML analysis based on the nrDNA ITS showed that p (100%) . It alsotrnL–trnF (1–758 sites), atpI–atpH , trnC–ycf6 , ndhJ–trnF , and indel codings . ML analysis based on cpDNA showed that Phedimus was monophyletic (100% BS)  of P. aizoon formed a monophyletic group (87% BS), while P. kamtschaticus was highly polyphyletic. Phedimus ellacombeanus was monophyletic (98%) and deeply embedded within one lineage of P. kamtschaticus (73%). The ML tree based on the combined ITS and cpDNA datasets (not shown) was nearly identical to the cpDNA tree.The total aligned sites of the four concatenated cpDNA noncoding regions and indel codings were 3,405 sites: 100% BS) . The UllP. aizoon and P. kamtschaticus) and insular derived P. takesimensis. The unrooted ML tree , while that of P. aizoon and P. kamtschaticus was 0.000617 ± 0.0005 and 0.00174 ± 0.000131, respectively. In the case of the pairwise distances among species, between P. takesimensis and P. aizoon it was 0.003231 ± 0.0006, between P. takesimensis and P. kamtschaticus it was 0.003477 ± 0.0006, and between P. aizoon and P. kamtschaticus it was 0.00391 ± 0.0006.We also assessed the relationships among three species, two purported continental progenitor species , ndhJ–trnF , rps16–trnK , trnL–trnF , trnC–ycf6 , and indel codings . We found a total of 44 haplotypes, 30 for P. takesimensis, seven for P. kamtschaticus, and seven for P. aizoon  to six (SUM)  . In addiix (SUM) . For the. aizoon .P. aizoon formed a ring-like network structure, and haplotype A7 was distantly related to the ring structure by three missing haplotypes , while the remaining haplotypes showed similar frequency levels  all samples from the three species, (b) P. takesimensis, (c) P. aizoon, and (d) P. kamtschaticus. When all samples from the three species were analyzed, 62% of the variation was found among the three taxa, followed by among populations (27.9%) and within populations (9.78%) , with 9.16% of the variation within populations. In contrast, 77% of the variation was found within populations and approximately 23% among populations in P. aizoon. In the case of the anagenetically derived insular P. takesimensis, around 70% of the variation was found among populations and 30% was found within populations.Although only two populations were sampled for  (9.78%) . In the P. takesimensis and P. kamtschaticus, had multimodal distributions, suggesting constant population sizes, multiple colonization, and/or sustained subdivision for a long period of time  as the optimal number of genetic groups (K) based on spatial locations and cpDNA haplotypes  on Ulleung Island and one (DON) on Dokdo Island  from the south-central part of Ulleung Island, while Group 4 included populations from the north facing  and east facing  part of the island. In the case of the three SAMOVA groups from the Korean Peninsula, Group 5 contained one central (UN), one northern (SAM), and three southern  populations of P. kamtschaticus, while Group 6 generally contained eastern (YON and HAM) and western  parts of the P. kamtschaticus populations. Group 7 exclusively contained two populations (HWA and TAE) of P. aizoon.Mismatch distributions showed that two species,  of time . In addi species . In the plotypes . The fireninsula . Group 1o Island . Group 2P. takesimensis on Ulleung and Dokdo Islands, despite its morphological variations within the islands and geographical proximity to continental source areas [P. takesimensis on the islands  and riaceae; ). Howevepiaceae; ), Hepatiulaceae; ), Acer ondaceae; ), A. takndaceae; ), Fagus agaceae; ), and Caulaceae; ). TherefP. takesimensis on the Ulleung and Dokdo Islands, the closest sister species on the continents and geographical source areas are yet to be determined. While the nuclear ITS phylogeny suggested a sister relationship of monophyletic P. takesimensis to the clade containing P. kamtschaticus, P. ellacombianus, P. latiovalifolius, and P. aizoon. . However, given that the monophyletic insular endemics were deeply embedded within the paraphyletic continental species relationships, it was possible to determine the continental source populations for certain taxa, e.g., the origin of Hepatica maxima from the eastern Korean Peninsula population of H. asiatica [Campanula takesimana from the southeastern Korean Peninsula population of C. punctata [Rubus takesimensis, it was shown that the northern mainland Korean Peninsula and southern Korean Peninsula/Japanese archipelago populations were responsible for its origin on Ulleung Island [Although we established the single origin of  aizoon. , the cpDlifolius . This unchaticus  and the chaticus . Althouggruences –35. The asiatica  and the punctata . In the g Island .P. kamtschaticus is one of most likely continental progenitor species of anagenetically derived endemic P. takesimensis on Ulleung Island. Therefore, this study also provided an opportunity to assess the genetic consequences of anagenetic speciation [P. takesimensis on the island. Although our sampling between the two species pairs was uneven, it seems there is no apparent reduction in genetic diversity in the insular derived P. takesimensis. For example, P. takesimensis showed much higher gene diversity (0.9346) and nucleotide diversity (0.003290) compared to P. kamtchaticus (gene diversity of 0.7699 and nucleotide diversity of 0.00197)  . In addiectively . These rsimensis , Acer tamotoanum ,66, and kesimana .P. takesimensis. When we compared these results to other endemics on Ulleung Island, we found 43% of the variation in Rubus takesimensis was within populations [Campanula takesimana [P. takesimensis showed apparent population genetic structure and differentiation after its divergence from the continental progenitor species. Given the fruit type of P. takesimensis are aggregates of follicles, with the fruit opening along an upward facing suture , and with small light-weighted seeds, it is highly conceivable that raindrops are responsible for splashing out and flushing away seeds over some distances [Sedum formosanum and S. subtile from the same family (Crassulaceae) in Japan and it was shown experimentally that the maximum seed dispersal distance of S. subtile was 63.7 ± 7.8 cm [P. takesimensis, which have apparent population genetic structure and differentiation.We also found that, based on the same molecular marker type of chloroplast DNA and the AMOVA results, a significant portion of the genetic variation existed between taxa (62%), suggesting genetic divergence among the three species . Furtherulations  and 48% kesimana . Therefoistances –73. ThisP. takesimensis on eastern Dokdo Island  most likely originated from two separate populations, one in southwestern Ulleung Island (GUA and NAM) and the other in southeastern Ulleung Island (JEO and DOD)  Islands, we demonstrated that Dokdo Island was the steppingstone island for its origin on Ulleung Island [In this study, we also demonstrated that the population of and DOD) . Dokdo Iand DOD) , it is hg Island .P. takesimensis on Ulleung Island is a strongly supported monophyletic group that is closely related to P. aizoon and P. kamtschaticus in the Korean Peninsula. We also found that P. takesimensis on Ulleung Island and P. aizoon on the peninsula harbor diverse haplotypes, while P. kamtschaticus shows highly monomorphic haplotypes. The overall genetic diversity parameters also suggested that insular derived P. takesimensis maintains a high genetic diversity compared to its continental progenitor species. Unlike other anagenetically originated endemics, P. takesimensis showed population genetic structuring and we suggest that limited seed-mediated gene flow via a splash rain dispersal mechanism is responsible for this genetic pattern. Lastly, we demonstrated that the Dokdo Island was colonized by two separate gene pools of P. takesimensis (southwestern and southeastern) from Ulleung Island.In conclusion, we provide the first convincing evidence, based on extensive sampling, that S1 Table(DOCX)Click here for additional data file.


Signal transducer and activator of transcription 3 (STAT3) is a transcription factor which can be activated by cytokines, growth factor receptors, and nonreceptor-like tyrosine kinase. An activated STAT3 translocates into the nucleus and combines with DNA to regulate the expression of target genes involved in cell proliferation, differentiation, apoptosis and metastasis. Recent studies have shown that STAT3 plays important roles in viral infection and pathogenesis. STAT3 exhibits a proviral function in several viral infections, including those of HBV, HCV, HSV-1, varicella zoster virus, human CMV and measles virus. However, in some circumstances, STAT3 has an antiviral function in other viral infections, such as enterovirus 71, severe acute respiratory syndrome coronavirus and human metapneumovirus. This review summarizes the roles of STAT3 in viral infection and pathogenesis, and briefly discusses the molecular mechanisms involved in these processes. Signal transducer and activator of transcription factors (STATs) are a family of transcription factors that regulate cell proliferation, differentiation, apoptosis, inflammation and oncogenesis . Seven Sreg, Th1 and Th17 ). Meanwhile, some herpesvirus infections are associated with STAT3.Bcl-2, Bcl-XL, IAP2, Pim-1, neurodegenerative gene GAP-43, and neurodevelopmental gene GFPAF, to maintain the latent state of HSV [HSV infection induces local skin or mucosa membrane lesions, these usually resolve within a few days to several weeks. After being triggered by stress or some stimulators, the virus retreats from neurons where it establishes latency, and is reactivated into the lytic infection. . The late of HSV . Anothere of HSV .et al. [in vivo upon HSV-1 infection. The STAT3-knockout mice were more susceptible to HSV-1 than the wild-type mice and failed to expand the CD8+ conventional DC population upon HSV-1 infection accompanied by the impaired NK and CD8+ T-cell activation. This report demonstrated that myeloid-specific STAT3 deletion causes defects in multiple aspects of the immune system in response to HSV-1. These findings suggested that STAT3 has a protective role at the early stage of systemic HSV-1 infection [To identify how STAT3 regulates the innate immune responses during the early phase of HSV-1 lytic infection, Hisa et al.  utilizednfection .in vitro and in human skin xenografts in SCID mice in vivo. STAT3 activation induces the antiapoptotic protein survivin and promotes VZV infection via increasing the survivin expression and inhibition of apoptosis [VZV causes varicella during primary infection and zoster upon reactivation. VZV triggers STAT3 phosphorylation in infected cells poptosis . Anotherpoptosis .HCMV causes an asymptomatic latent infection in healthy individuals. However, HCMV infection sometime leads to severe diseases involved in immune deficiency, especially in patients with AIDS and in immunocompromised solid organ and bone marrow allograft recipients. HCMV primarily utilizes unphosphorylated STAT3 to promote HCMV DNA replication . HCMV inet al. [EBV mainly invades B lymphocytes and exhibits an affinity to pharyngeal and glandular cells, which are closely correlated to Burkitt's lymphoma, Hodgkin's lymphoma, NK/T-cell lymphoma, post-transplant lymphoproliferative diseases and nasopharyngeal cancer (NPC). EBV LMP1 stimulated STAT3 signaling in a human NPC cell line. LMP1 can phosphorylate STAT3 at Tyr705 by activating JAK3 and phosphorylate STAT3 at Ser727 by activating ERK. STAT3-p705 is correlated with NPC stages III and IV; this observation suggests that STAT3 plays an important role in NPC invasion and metastasis . EBV LMPet al. , LMP1-CTet al. . Apart fet al. . In addiet al. .et al. [et al. [Constitutive STAT3 activation is reportedly correlated with advanced clinical staging in NPC . Lui et et al.  demonstr [et al.  found th [et al. . Meanwhi [et al. .EBV persists as a lifelong infection by maintaining the latent phase of its life cycle within B lymphocytes. Upon infecting primary B cells, EBV must initially drive cell proliferation to establish latency. The exposure of healthy subject-derived B cells to EBV early resulted in the activation of STAT3, and the activation is necessary for the subsequent survival and proliferation of EBV-infected cells past the S phase of the cell cycle. However, B cells derived from patients with autosomal dominant hyper-IgE syndrome (AD-HIES) are impaired in their susceptibility to EBV-driven growth transformation. Patients with AD-HIES harbor a dominant negative mutation in their STAT3 gene .et al. [The lytic activation of EBV is essential to the life cycle of the virus and to most EBV-related diseases. Antiviral agents that eliminate EBV-positive tumor cells induce the viral lytic cycle. In cell culture, HDAC inhibitors can induce EBV to enter the lytic cycle. However, only a fraction of cells enter the lytic cycle; the remainder of the population is refractory in this process. Daigle and his colleagues separated the lytic cells from refractory Burkitt lymphoma-derived HH514-16 cells after treatment with an HDAC inhibitor. They found that STAT3, Fos and IL-8 were upregulated in the refractory cell population, whereas IL-6 was upregulated in the lytic population. Examination of single cells revealed that high levels of STAT3 are strongly associated with the refractory state . The groet al.  further et al. [KSHV is the infectious cause of Kaposi's sarcoma, primary effusion lymphoma and multicentric Castleman's disease. STAT3 is activated in KSHV-infected endothelial cells by activating gp130 and JAK2. The activation persists for as long as the latent infection is maintained. The persistent activation of STAT3 may play a critical role in the viral pathogenesis of Kaposi's sarcoma, as well as primary effusion lymphoma . Muromotet al.  discoverRespiratory viruses mainly cause respiratory tract lesions and other organ lesions. Research has shown that IL-6 is an important factor regulating host susceptibility to respiratory tract infection. IL-6 plays an important role in host defense and the prevention of lung injury against pathogens. Given that IL-6 activates the JAK/STAT3 signaling cascade, STAT3 contributes to the pathogenic process of respiratory viruses.Influenza A virus (IAV) is a highly contagious single-stranded RNA virus that infects both the upper and lower respiratory tracts of humans and is considered a major worldwide public health problem. Although seasonal infections with the most common influenza virus strains  can be resolved typically, infection continues to cause a high rate of mortality . IAV H5NMumps virus infection causes parotitis, meningitis and orchitis. Mumps virus encodes a V protein that can assemble into an ubiquitin ligase complex that causes the polyubiquitylation and proteasome-mediated degradation of cellular STAT1 and STAT3 proteins, to modulate host innate and adaptive antiviral responses ,116. FurMeasles virus infection is characterized by the virus-induced immune suppression that increases the susceptibility to opportunistic infections. Similarly, the measles virus V protein also interferes with STAT3 activation and provides several general or tissue-specific replication advantages to the virus .SARS-CoV infection causes SARS, which may be mediated by the viral replication in target cells and immune responses. SARS-CoV infection can activate p38 MAPK, ERK1/2 and JNK pathways in Vero E6 cells, and the p38 MAPK pathway induces STAT3 dephosphorylation at Tyr705 to promote SARS-CoV replication .Human metapneumovirus (hMPV) infection can result in bronchiolitis or pneumonia and can exacerbate chronic obstructive pulmonary disease. hMPV can attenuate the IL-6-mediated JAK/STAT3 signaling cascade in lung epithelial cells. It also interrupts the IL-6-induced activation and nuclear translocation of STAT3 by inhibiting the phosphorylation of JAK2, and further regulates the STAT3 downstream genes for apoptosis, cell proliferation and differentiation . HoweverReproductive and respiratory syncytial virus (RSV) infection causes airway inflammation and exacerbates asthma. Respiratory syncytial virus can activate STAT3 via IL-6, and the activation is necessary for the viral early gene activation and successful infection of epithelial cells . PorcineCoxsackievirus B3 infection induces a severe inflammation during the acute phase of the resultant viral myocarditis. STAT3 signaling plays a protective function in Coxsackievirus B3-induced myocarditis . We alsoet al. [HIV infection induces AIDS. HIV-1 Nef mediates STAT3 activation in immature DCs . Percariet al.  found thet al. . HIV-1 get al. .Human T-cell leukemia virus type-1 (HTLV-1) predominantly infects T lymphocytes, causing two distinct diseases, adult T-cell leukemia/lymphoma and HTLV-1 associated myelopathy/tropical spastic paraparesis. HTLV Tax protein upregulates IL-6R and sIL-6R, which may contribute to the proliferation of HTLV-1-infected T cells through the activation of STAT3 and affect the malignant growth and transformation of T cells induced by HTLV-1 . IL-10-m+ T cell-mediated target destruction by activating STAT3 and NF-κB [In DCs, Dengue virus type 2 nonstructural 1 (NS1) protein interacts with STAT3β protein, which may influence the pathological changes observed in dengue fever, dengue hemorrhagic fever and dengue shock syndrome . Dengue nd NF-κB . Rabies nd NF-κB . Simian nd NF-κB . STAT3 ind NF-κB .STAT3 plays an important role in viral infection. It can be activated by virus-encoded proteins, such as HBx protein, HCV core protein, NS5A, EBV LMP1 and HIV Nef. However, STAT3 activation can also be inhibited by some viruses or viral proteins including IAV NS-1, hMPV and SARS-CoV . The dysFrom the literature collected in this review, it clearly shows that STAT3 plays an important role in the virus life cycle and in viral pathogenesis. However, the key viral and host factors that promote the activation or inhibition of STAT3 signaling after viral infection are largely unknown except several viruses listed in Further in depth studies are necessary to determine the mechanisms by which viruses exploit STAT3 for their life cycle. In the early and late stage of virus replication, when and how viruses activate STAT3 signaling by different viral proteins or genome? For examples, HBV activated STAT3 could be induced by HBx and HBsAg, and HCV activated STAT3 could be triggered by HCV core, NS4B, NS5B and HCV RNA . When anMoreover, STAT3 exerts the contradictory effects on the viral infection, antiviral to some virus and proviral to others. What is key factor to determine the switch between the proviral and antiviral function of STAT3? Further study is needed for the identification of the factors that drive STAT3 signaling to play antiviral or proviral role.Furthermore, in the viral pathogenesis, further studies are also needed for the identification of the mechanisms underlying host STAT3 function in an immune-protective or proinflammatory response. On this issue, many questions need to be resolved. For example, how viruses regulate STAT3 to respond to IFN? STAT3 negatively or positively regulates type 1 IFN response depending on the virus type involved? How viruses regulate STAT3 response to different cytokines, such as IL-6, IL-10 and IFNs, especially, when these cytokines induced by the virus in different tissues?Conclusively, a comprehensive analysis to dissect the role of STAT3 in viral infections in the future can provide valuable insights into the viral pathogenesis and development of novel antiviral therapies.As a STATs family member, STAT3 plays a central regulatory role in cell proliferation, differentiation, apoptosis and oncogenesis, and is also involved in the process of cellular immune responses and inflammation.STAT3 signaling is mainly activated by the IL-6 and IL-10 family cytokines and growth factor receptors. STAT3 phosphorylated at Tyr705 is required for dimerization to activate STAT3 signaling, which would be inhibited by suppressor of cytokine signaling, protein inhibitor of activated STAT and protein tyrosine phosphatase.STAT3 has a proviral function in several viral infections. However, in some circumstances, STAT3 has an antiviral activity in other viral infections. The activation or inhibition of STAT3 signaling is a virus-specific event.HBV infection activates STAT3 through HBx and hepatitis B surface antigen. HBx increases  reactive oxygen species, induces IL-6/STAT3/NANOG signaling, and regulates some miRNAs to promote the HBV-induced hepatocellular carcinoma. hepatitis B surface antigen activates the ERK/IL-6/STAT3 pathway to regulate monocyte toward myeloid-derived suppressor cells and T-cell activation.HCV NS4B, NS5B and HCV RNA activate STAT3 signaling through reactive oxygen species; HCV core activates STAT3 through the PI3K/Akt and IL-6 pathways. STAT3 activation contributes to HCV replication by inhibiting host antiviral immune responses and regulating the antiapoptosis and cancer-related genes that may promote the HCV-induced hepatocellular carcinoma.STAT3 plays a protective role in the early stage of HSV-1 infection. However, STAT3 activation contributes to maintain HSV-1 latency by inhibiting p300/CBP activity.EBV activates STAT3 signaling to inhibit lytic activation through PCBP2, and upregulates EGF receptor, JAK3 and STAT3 pathways for cancer cell proliferation, invasion and metastasis by LMP1, LMP2A and EBNA2.STAT3 increases HCMV replication and promotes HCMV-infected cell transformation. Varicella zoster virus activates STAT3 for its replication dependent on the increase of survivin, this occurrence also required for Kaposi's sarcoma herpesvirus-induced malignant transformation.Activation of STAT3 signaling shows antiviral activity against most of respiratory viruses, including influenza virus, measles virus, mumps virus, severe acute respiratory syndrome coronavirus, human metapneumovirus and porcine reproductive and respiratory syndrome virus, but reproductive and respiratory syndrome virus.STAT3 signaling responses to virus infection are complicated in a virus-specific manner and even in a stage-specific manner in the virus life cycle. It needs further investigation why STAT3 has been distinctively regulated by the different viruses. Specifically, to some viruses within a close branch in taxonomy.


Genetics has traditionally enabled the reliable diagnosis of patients with rare genetic disorders, thus empowering the key role of today’s clinical geneticists in providing healthcare. With the many novel technologies that have expanded the genetic toolkit, genetics is increasingly evolving beyond rare disease diagnostics. When placed in a transition context—like we do here—clinical genetics is likely to become a fully integral part of future healthcare and clinical genetic expertise will be required increasingly outside traditional clinical genetic settings. We explore transition effects on the thinking (culture), organizing (structure), and performing (practice) in clinical genetics, taking genetic healthcare in Estonia, Finland, and the Netherlands as examples. Despite clearly distinct healthcare histories, all three countries have initially implemented genetic healthcare in a rather similar fashion: as a diagnostic tool for predominantly rare congenital diseases, with clinical geneticists as the main providers. Dynamics at different levels, such as emerging technologies, biobanks and data infrastructure, and legislative frameworks, may require development of a new system attuned with the demands and (historic) context of specific countries. Here, we provide an overview of genetic service provisions in Estonia, Finland, and the Netherlands to consider the impact of historic and recent events on prospective developments in genetic healthcare. Clinical genetics is an established healthcare service dedicated to the study, treatment, and counseling of individuals with heritable diseases and disorders predisposition. New technologies and methodologies like next-generation sequencing (NGS) technologies, genome-wide association studies (GWAS), and the Clustered Regularly Interspaced Short Palindromic Repeats-associated nuclease 9 (CRISPR/Cas9) system are rapidly expanding the genomic toolkit and increasing the diagnostic power, risk assessment, and treatment options for many diseases, beyond rare disorders, and outside of the traditional boundaries of clinical genetics. While the focus is often on the potential of these technologies for solving persistent challenges for rare diseases—e.g., optimizing diagnosis and characterization—we aim here to explore how such emerging technologies affect the context in which clinical genetics operates.Healthcare systems are under increasing demands from a changing society and face rising costs, growing fragmentation, and staff reduction  healthcare services , the system-specific configuration (“regime”), and the emerging innovations (“niches”) that shape genetic healthcare , with the volume depending on the allocated budget for specific clinical service providers. Genetic services outside Estonia are also covered but on a case basis via a specific application process, if such services are not available in Estonia.The clinical genetics regime—e.g., newborn and prenatal screening—are free of charge, as is the national vaccination program for 12 recommended diseases and cancer screening programs. Neonatal screening covers neonatal hypothyreosis, and 20 treatable metabolic disorders and it is offered to all children since all children automatically have a health insurance  healthcare services for all inhabitants, as regulated by the Constitution  As for the genetic research regime. The registries are established and regulated by specific laws; no consent is required to add personal data to these registries, but access to the data is guarded by detailed processes for all stakeholders.A hallmark of Finish healthcare—as for other Nordic countries—is high-quality national health registries which provide a solid basis for the national public healthcare Many public health services are provided as national programs, largely directed towards health promotion and disease prevention  to Parliament and  governments. It is comprised of various autonomously evolving regimes   genetic causes for many rare congenital syndromes and the unravelling of novel disease mechanisms. These in turn have fueled the development of therapeutic strategies, and the launch of various large-scale population studies , structure (how we organize), and practice (what we do) (Table Developments in o) Table .Table 1Oniches) beyond the traditional boundaries of clinical genetics. For instance, the first attempts to use results from research on biobank samples in preventive healthcare have already been undertaken in Estonia, e.g.. return of copy number variants and actionable monogenic findings related to familial hypercholesterolemia and hereditary breast and ovarian cancer  has been to provide diagnoses for predominantly rare diseases. However, in both Estonia and Finland, genetic diagnostics have been considered part of the tool set of medical specialists other than clinical geneticists . This aspect of culture, namely the vision on the main application of genetics for diagnostics and perceived need to confine genetic services to the clinical genetic specialty, may affect attitudes towards adoption of emerging new technologies  available in-house. Dutch law prevents non-academic hospitals and private industry from conducting genetic services, while in Estonia and Finland, these roles are less confined. In Estonia and Finland, clinical genetic services offer genetic counseling and use both the hospitals’ as well as external (including foreign) laboratories for genetic testing, services increasingly also requested by non-genetic medical specialists. Besides the generally recognized medical profession of clinical geneticists in most countries in Europe, the three countries described here differ in their training and deployment of professionals specifically trained to conduct genetic counseling: genetic counselors. While Estonia and Finland lack specific training programs for this profession, Finland does have nurses trained in genetics. The Netherlands has several training programs and over 50 genetic counselors  in the Netherlands, with clinical genetics as an established department in each of the eight academic hospitals—thus boosting the demand for clinical genetic services from other medical specialists—would probably need the most increase in staff. A revolutionary change in the working traditions from comprehensive face-to-face counseling to, e.g., (online) tutorials supplemented, when needed, with short counseling sessions would radically decrease the need for more personnel. On the other hand, clinical geneticists or genetic counselors/nurses are increasingly needed as consultants and advisers outside the clinical genetic centers, as the use of genetic information expands in clinical practice and only patients with complex findings are referred to clinical geneticists. Still, clinical geneticists are the only specialty systematically engaging family members for cascade screening.In all three countries, there are indications of an increasing burden on clinical genetics staff and budget, predominantly as a result of increasing demand  has initiated reflections on the status, management, and use of genetic data across Europe. The effect of this European data uniformization effort has been different across countries. In Finland and Estonia, the traditional “broad consent model” in use when collecting biobank samples, or “no consent” relating to Finnish national healthcare registries, are being complemented by strict regulation of data access and the rights of donors/patients in specific national legislation, to be in line with GDPR Soini . Conversregime, such as pre-symptomatic (pharmacogenomics) testing and liquid biopsy screening in cancer patients for early diagnosis or personalized treatment.The absence of equivalents to the Dutch Specialist Medical Practice Act in Finland and Estonia (and in many other countries in Europe) more easily allows not only other specialists but also various local health centers, regional hospitals, and private clinics to offer genetic services. This potentially facilitates more efficient implementation of new genetic innovations outside the traditional clinical genetic While biobanks and healthcare data in Estonia and Finland are already largely centralized in national registries, the Netherlands is only recently trying to make fragmented genetic data findable, accessible, interoperable, and reusable (FAIR) Radboud .regimes, there seems to be general agreement on the essential components of clinical genetic care for patients in all three countries. For rare diseases, typically a primary or secondary care specialist refers the patient to genetic specialists, detailed phenotyping and clinical evaluation, pre- and post-test counseling, and possibly cascade screening  screening programs are implemented in the public health regimes of all three countries, while to a differing extent, pre-symptomatic screening for other hereditary disorders is implemented, piloted, or studied through the biobanks or other research infrastructures. While Estonia and Finland are inclined to do this at national level, the first broader applications of, e.g., pharmacogenetics or polygenic risk scores in the Netherlands is currently still restricted regionally to initiatives at medical centers.regimes or landscapes may change after a disruptive event. Perhaps, the public health crisis caused by the SARS-Cov2 pandemic and its potential implications on, e.g., public trust and views on solidarity and autonomy in addition to lessons from application of genomic sequencing technology in this context, could instigate disruption to cause transformation in healthcare. If true, this will likely also affect clinical genetic service provision.Development of truly transformative genetic services requires extensive exploration, preparation, implementation, and evaluation , which are generally long-term processes. The timely and careful planning of these processes are therefore of utmost importance to drive transitions that improve genetic healthcare effective tests will require evaluation of many different techniques, interventions, and outcomes. For many reasons outside the scope of this paper, this evaluation will be challenging  have and will significantly influence the genetics regime, including applications for rare diseases. Depending mainly on organizational characteristics and general acceptance of use of genetic data, most likely, there will be an increasing application of genetic analysis for healthy individuals which could be appropriate and feasible for prevention-based healthcare. Uptake of these applications is dependent on the existence of national biobank initiatives and legislative prerequisites, public perceptions of genetic data and its associated aspects of access, identity and uncertainty, and the future position of genetics in the healthcare system, and in society as a whole.regimes, as expected. In addition, new genetic tools and developments require retraining of existing genetic counselors, and possibly the creation of new medical professions specialized in various advanced medical genetic techniques.In terms of organization of clinical genetic services, genetic counselors/nurses are still deemed best equipped to address the increasing need for counseling, such as risk communication to non-symptomatic high-risk individuals or by facilitating cascade screening. However, the state of genetic counseling as a profession, or the necessary training in different countries across Europe, varies to a great degree, potentially already leading to suboptimal care in some regions , where—at least in the Netherlands—clinical geneticists took a central role in the development of counseling, training, and testing strategies  developments in the field. Of crucial importance will be data sharing and breaking down the silo mentality, not only within countries but also between nations.


Tunisia is considered a secondary center of diversification of durum wheat and has a large number of abandoned old local landraces. An accurate investigation and characterization of the morphological and genetic features of these landraces would allow their rehabilitation and utilization in wheat breeding programs. Here, we investigated a diverse collection of 304 local accessions of durum wheat collected from five regions and three climate stages of central and southern Tunisia.H′) of 0.80 was obtained, indicating high level of polymorphism among accessions. Based on these traits, 11 local landraces including Mahmoudi, Azizi, Jneh Khotifa, Mekki, Biskri, Taganrog, Biada, Badri, Richi, Roussia and Souri were identified. Spike length (H′ = 0.98), spike shape (H′ = 0.86), grain size (H′ = 0.94), grain shape (H′ = 0.87) and grain color (H′ = 0.86) were the most polymorphic morphological traits. The genetic diversity of these accessions was assessed using 10 simple sequence repeat (SSR) markers, with a polymorphic information content (PIC) of 0.69. Levels of genetic diversity were generally high . In addition, population structure analysis revealed 11 genetic groups, which were significantly correlated with the morphological characterization. Analysis of molecular variance (AMOVA) showed high genetic variation within regions (81%) and within genetic groups (41%), reflecting a considerable amount of admixture between landraces. The moderate (19%) and high (59%) levels of genetic variation detected among regions and among genetic groups, respectively, highlighted the selection practices of farmers. Furthermore, Mahmoudi accessions showed significant variation in spike density between central Tunisia (compact spikes) and southern Tunisia (loose spikes with open glume), may indicate an adaptation to high temperature in the south.Durum wheat accessions were morphologically characterized using 12 spike- and grain-related traits. A mean Shannon-Weaver index (Overall, this study demonstrates the genetic richness of local durum wheat germplasm for better in situ and ex situ conservation and for the subsequent use of these accessions in wheat breeding programs.The online version contains supplementary material available at 10.1186/s12863-021-00958-3. Triticum turgidum var. durum Desf.) is a tetraploid species  that originated and domesticated in the Fertile Crescent and spread within the Mediterranean region through different dispersal [Durum wheat  evaluate the genetic diversity and population structure of 304 Tunisian durum wheat accessions collected from central and southern Tunisia using SSR markers; (ii) study the phenotypic diversity of these accessions, based on the morphological characterization of spike- and grain-related traits; and (iii) analyze the relationship between genetic and phenotypic variation.H′) revealed a high morphological diversity among durum wheat accessions (H′ = 0.80) (Table H′ = 0.98), grain size , grain shape , grain color  and spike shape , while the least polymorphic trait was spike color .The Shannon-Weaver index (0) Table . The mosH′), which was relatively low for each landrace, ranging from 0.00 (Badri and Jneh Khotifa) to 0.23 (Richi), with an overall mean of 0.11  value was the highest for Xgwm413 (2.182) and the lowest for Xgpw2103 (0.781). The fixation index (Fis) was approximately equal to 1 for each locus, except Xgwm495 (Fis = − 0.373), for which a high PIC value was observed (0.659). Pairwise genetic differentiation (Fst) ranged from 0.201 (Xgwm495) to 0.688 (Xgpw7148).Ten SSR markers were used in this study to analyze the genetic diversity and population structure of Tunisian durum wheat accessions. These SSR markers were mapped onto eight different chromosomes and therefore were considered largely independent Table . The perWe analyzed the population structure on 188 MLGs. The maximum likelihood (LnP(K)) and delta K (ΔK) methods indicated that the most likely number of genetic groups (K) was 11 Fig. a, b. TheP = 0.01; Rxy = 0.435). However, a discrepancy between the genetic grouping and the morphological characterization was observed for Azizi, Souri and Roussia landraces; Azizi landraces were grouped by STRUCTURE into two different genetic groups G1 and G8, while Souri and Roussia landraces were grouped together into one genetic group (G6), despite their distinct morphological characteristics.Overall, each genetic group corresponded to a single landrace. The genetic groups G2, G3, G4, G5, G7, G9, G10 and G11 corresponded to Jneh Khotifa, Taganrog, Mekki, Richi, Badri, Beskri, Biada and Mahmoudi landraces, respectively. Moreover, a significant correlation was detected between the genetic distance matrix and morphological distance matrix  and G10 (Biada) (representing 14.6% of the admixed genotypes), followed by G1 (Azizi) and G9 (Beskri) (representing 9.7%). Mahmoudi (G11), Beskri (G9) and admixed genotypes were the most frequent , followed by Azizi (G1), Taganrog (G3), Mekki (G4), Badri (G7) and Biada (G10) (each accounting for approximately 8% of the entire collection). However, Jneh Khotifa (G2), Richi (G5), Roussia and Souri (G6) and Azizi (G8) were the least frequent, each accounting for 3% of the entire collection.Ne) ranged from 1.152 (G7) to 2.379 (G6). Genetic groups with the highest number of MLGs were G6 (100% of different MLGs), G8 (90%) and G3 (85.7%), while G7 and G11 had the lowest number of MLGs . The percentage of polymorphism (P) ranged from 40% (G7) to 100% (G6 and G8). Shannon’s information index (I) varied from 0.166 (G7) to 0.937 (G6), with an average value of 0.620 across all accessions. In addition, G6 and G8 showed the highest number of private alleles , while G2 and G7 contained no private alleles (PA = 0) (Table SFis ranged from 0.698 (G4) to 1.0 (G7), where observed heterozygosity (Ho) was 0.100 and null, respectively. Furthermore, analysis of variance (ANOVA) showed that 59% of the total genetic diversity was observed between distinct genetic groups, while 41% of the genetic diversity was explained by differences within each group  between C1 and C2 in terms of SS, SL, AL, GC, GSp, NS, AC and glume color (GlC) (Table He = 0.740) and phenotypic diversity (H′ = 0.77) than cluster C2   Table S. The valH′) of 12 spike and grain related traits was compared among five regions  and three different climate stages  (Table H′ = 0.74), followed by Medenine (H′ = 0.66). Sousse showed a null diversity index, indicating no phenotypic variability between accessions in this region; notably, Richi was the only landrace identified in this region. The most polymorphic characteristics by regions were SL (H′ = 0.69), GSp (H′ = 0.65), GC (H′ = 0.62) and NS (H′ = 0.61). Among all three climate stages, the high-arid climate (represented by Kairouan) showed the highest diversity index (H′ = 0.74), whereas the low semi-arid climate (represented by Mahdia and Sousse) showed the lowest diversity index (H′ = 0.59). The most polymorphic characters by climate stages were AL (H′ = 0.90), GSp (H′ = 0.82), GC (H′ = 0.79), and NS (H′ = 0.73).The Shannon-Weaver index  to 0.73 (Mahdia). Similarly, SL was the highest in Mahdia (0.99) and lowest in Gabes (0.49). Values of spike color (SC) and glume color (GC) indices were the highest in Medenine (0.53) and Kairouan (0.97), respectively, and lowest in Mahdia . Morphological traits were also variable from one climate stage to another. Values of SL and glume color were the highest in high-arid climate  and lowest in low semi-arid climate . By contrast, AC was the lowest in high-arid climate (0.12) and the highest in mid-arid climate (0.71). However, no variation was observed among regions for GC and among climates for GN.In addition, a dominant phenotypic class of some morphological traits was observed among regions (within more than 70% of accessions), except Sousse, which did not show any variation in morphological traits Table S. In GabeThe results of ANOVA showed that 19 and 10% of the total genetic diversity was observed among regions and among climate stages, respectively, while 81 and 90% of the genetic variability was explained by differences within regions and within climate stages, respectively Table .H′ = 1.296) and lowest in Sousse (H′ = 0.305). Moreover, the percentage of polymorphic loci (P) was 100% for all regions, except Sousse (50%). Moreover, the number of private alleles was also the highest in Gabes (PA = 17) and lowest in Sousse and Medenine (PA = 1). The value of Fis was greater than 0.800 in each region, except Sousse (Fis = 0.691). Interestingly, the DA number and heterozygosity index were the highest in Sousse. In fact, three diagnostic alleles  were registered in Sousse, whereas only one such allele was identified in Gabes.Genetic diversity among regions showed Ne ranging from 1.366 (Sousse) to 3.031 (Gabes) (Table I = 1.318) and the highest number of private alleles (PA = 19). By contrast, the high-arid climate stage showed the lowest number of effective alleles (Ne = 2.707), the lowest Shannon’s information index (I = 1.050) and the lowest number of private alleles (PA = 2). However, the value of Fis was similar (> 0.800) among all studied climate stages , the highest Shannon’s information index  between genetic and geographic distances among durum wheat accessions, suggesting that accessions growing in close geographical proximity were genetically related. Azizi and Mahmoudi landraces showed the most widespread geographical distribution in central and southern Tunisia, except Sousse, and all climate stages. However, Azizi was more frequent in Gabes (25 accessions out of 38), while Mahmoudi was mostly found in Medenine (13 accessions out of 22) and Mahdia (11 accessions out of 27)  Fig. . In addiP > 0.05), except for spike density (SD) which showed significant differences within Mahmoudi (P = 0.00). Mahmoudi accessions collected from central Tunisia had compact spikes (SD = 7), whereas those collected from southern Tunisia were characterized by loose spikes (SD = 5) . Similar level of polymorphism  was previously reported using 15 SSR markers in a Tunisian durum wheat collection composed of 7 modern cultivars and 27 old cultivars [He: 0.28–0.82; Na: 2–13) of Tunisian durum wheat germplasm, consisting of 41 traditional varieties and 13 cultivars, using 16 SSR markers. A higher level of polymorphism  was reported in a wider geographical collection of 172 durum wheat landraces (collected from 21 Mediterranean countries) and 20 modern cultivars genotyped by 44 SSR markers [He = 0.25) in 196 Tunisian durum wheat accessions; this was possibly due to (i) the use of bi-allelic DArTseq markers, which are less informative than the multi-allelic SSR markers, and (ii) to limited number of landraces (5). This variability between studies suggests that the ability to capture the maximum genetic diversity depends on the type of markers, number of landraces, their origin and geographical distribution.In the present study, we investigated the genetic diversity of 302 Tunisian durum wheat accessions using 10 SSR markers, which enabled maximal differentiation among MLGs, suggesting that these markers have a good resolution power. Overall, the studied collection was characterized by high genetic diversity  of 0.80. The morphological diversity observed in this study was higher than that described previously for 930 Tunisian durum wheat accessions (H′ = 0.53), collected from fewer sites in southern Tunisia, using 22 qualitative and 3 quantitative traits [H′ = 0.62) [H′ = 0.78) [H′ value of 0.71 using eight qualitative traits [H′ value of 0.52 and 0.66 using 15 qualitative and 17 quantitative traits, respectively [In this study, the level of phenotypic diversity detected on the basis of 12 morphological traits was consistent with that of genetic diversity, with a Shannon-Weaver index (e traits . Lower p = 0.62)  and 59 te traits , while Oectively .H′ = 0.98), GSz (H′ = 0.94), GSp (H′ = 0.87), GC (H′ = 0.86) and SS (H′ = 0.86) were the most polymorphic morphological traits. Previous studies on Tunisian durum wheat populations showed different results for polymorphic traits, based on UPOV and IPGRI. Belhadj et al. [H′ = 0.97) and spike color (H′ = 0.92), whereas Ayed et al. [H′ = 0.91), yield (H′ = 0.89), plant height (H′ = 0.87) and thousand kernel weight (H′ = 0.86) showed the highest diversity index values. Slim et al. [H′ = 1.18), spike glaucosity (H′ = 0.89), hairiness on the external surface (H′ = 0.88), awn color (H′ = 0.78) and awn length relative to spike length (H′ = 0.77). Ayed and Slim [H′ = 0.86), glume pubescence (H′ = 0.80) and glume color (H′ = 0.79) showed the highest diversity index values. These differences among studies were essentially related to landraces. Indeed, Ayed et al. [In this study, SL  and climate stages (Nm = 3.813). In fact, Mahmoudi (G11), Beskri (G9) and Azizi (G1 and G8), together accounted for 47% of the entire durum wheat collection, were distributed across different geographical locations. The widespread distribution of these landraces is explained by their earlier introduction (since 1893 or 1894) from Algeria and southern Europe, followed by their spread through local seed commercial trade and seed exchange between farmers. Thus, the exchange of seeds of different landraces between farmers from distant regions, followed by the introgression of these landraces into the pre-existing germplasm, could explain the level of high genetic variation observed within regions (81%) and climate stages (90%). Gabes and Mahdia showed the highest diversity indexes (including the number of MLGs), where 80 and 77% of the accessions, respectively had a unique MLG; and the highest number of private alleles (at a frequency < 0.4). In Gabes, 72% of the accessions belonged to cluster C1, whereas in Mahdia, 22 and 60% of the accessions belonged to clusters C1 and C2, respectively. This result suggests that a more diverse germplasm resource was available to farmers in Mahdia than to farmers in Gabes for breeding purposes. In fact, in Mahdia, 27 accessions were identified as belonging to five different landraces with a frequency less than 41%, whereas, 38 accessions were described in Gabes, with a predominance of the Azizi landrace (47%). Moreover, a high morphological diversity was observed among regions (H′ = 0.55) due to the presence of different phenotypic classes for all the studied phenotypic traits within regions. According to Chentoufi et al. [A high gene flow was observed between regions . We speculate that the loose spike, characterized by an open glume in southern Tunisian Mahmoudi accessions, could provide tolerance to high temperature by maintaining fertility, as shown in rice germplasm . The looMSN analysis grouped the accessions into two major clusters, C1 and C2. However, neither one of these clusters correlated with the geographical origin of landraces. Notably, both Mahmoudi and Biskri were introduced in Tunisia from Algeria, while Jneh Khotifa, Azizi, Mekki, Biada and Roussia were considered local landraces cultivated mainly in northern and central Tunisia. Although various origins have been reported for landraces Azizi and Mekki, no origin has been reported for Richi and Taganrog, which are very old, but non-local, landraces , 13. AccTunisian old durum wheat, characterized here by both high genetic and morphological diversity, represents an important and valuable genetic resource that should be included in breeding and well-established conservation programs. In this study, we showed that Tunisian old durum wheat is structured into landraces, revealing the effect of selection pressure directed by farmers for specific wheat types and agro-morphologies. Nevertheless, the morpho-geographical spike density trait, apparent specifically in Mahmoudi accessions, suggests that environmental selection also acted on Tunisian durum wheat. Thus, our results provide important data for improving the adaptation of wheat to extreme or fluctuating Mediterranean conditions. Further physiological and agronomic analyses are needed to ascertain whether the spike density trait could be exploited in durum wheat breeding programs for tolerance to heat and drought.A collection of 304 old durum wheat accessions provided by the National Gene Bank of Tunisia (BNG) were used in this study. Accessions were collected from five regions in three distinct climate stages: Sousse and Mahdia (low semi-arid climate) and Kairouan (high-arid climate) located in central Tunisia, and Gabes and Medenine (mid-arid climate) located in southern Tunisia. The Global Positioning System (GPS) coordinates of 163 out of 304 accessions were registered Table S. Seeds o− 1 and genotyped using 10 SSR markers (Table Shttps://www.eurofins.fr). Briefly, PCR was performed by preheating the DNA at 95 °C for 5 min, followed by 35 cycles of 95 °C for 30 s, 60 °C for 90 s and 72 °C for 30 s, with a final extension step of 60 °C for 30 min. PCR products were analyzed by electrophoresis on a 2% agarose gel, and fragments were separated according to their size on an ABI Prism Genetic Analyzer (Applied Biosystems). Data was checked again using the Peak scanner software (version 1.0) (https://www.thermofisher.com). Two accessions with missing data for all SSRs were excluded from the study.Five seeds collected from one spike of each accession were germinated and grown under controlled conditions  at Bioger research unit, INRAE, France. At the seedling stage , one leaf of each accession was sampled and placed in an extraction plate. The plates were placed at − 80 °C for 12 h before DNA extraction. DNA was extracted from the leaf samples of each of the 304 accessions using the DNeasy PowerPlant Pro HTP 96 Kit . DNA concentrations were quantified using a Nanodrop spectrophotometer (ND-1000) and stored at − 20 °C until needed for subsequent processing. The DNA of each accession was adjusted to a concentration of 15 ng·μlMorphological characterization was carried out using five spikes per accession . Accessions were evaluated using 12 quantitative and qualitative spike- and grain-related morphological traits. Spike evaluation was based on durum wheat descriptor standards of the IPGRI  and UPOVpegas’ package and ‘genotype_curve’ function in the R 3.3.2 [n− 1 loci (without replacement) and counting the number of MLGs observed.Based on the SSR data generated on 302 accessions, the number of MLGs were identified with using the GIMLET software (version 1.3.2) . To chec R 3.3.2 . This anfi is the frequency of the ith allele in the set of 302 genotypes. SSR markers with PIC ≥0.5 were considered informative.To assess the informativeness of SSR markers, the average PIC value of each marker was calculated by determining the frequency of alleles per locus using the following equation :\documeH′) was calculated for each trait using the Past software [H was estimated for the entire durum wheat collection, for accessions in different regions and climate stages and for each landrace. Each value of H was standardized by conversion to a relative phenotypic diversity index (H′) to express the values of H′ within the range of 0–1. The Shannon-Weaver index (H′) was calculated as follows:Hmax Ln (S), S = the number of phenotypic classes.Frequencies of different phenotypic classes were calculated for each of the 12 spike- and grain-related traits in the entire collection, by landraces Table S. Based osoftware . H was eTo investigate the morphological structure of the 304 accessions, PCA was performed based on 12 spike and grain related traits using R 3.3.2 . The poppoppr’ and ‘adegenet’ packages in R 3.3.2 [n is the number of individuals per phenotypic class; and Ci is the ith phenotypic class per morphological trait.To classify the 302 accessions according to their genetic relationship, MSN analysis was conducted based on Bruvo’s distance  using ‘p R 3.3.2 . FurtherTo determine significant differences between genetic clusters for each morphological trait, ANOVA of calculated means was carried out using R 3.3.2 .I, He, Ho, Fis, P, and DA  were calculated within each genetic group, region and climate stage using GenAlEx (version 6.501) [Values of Na, Ne, PA , n 6.501) . In addin 6.501)  for the n 6.501) . Correlan 6.501)  to invesMoreover, mean values of all 12 spike and grain related traits were estimated for Azizi and Mahmoudi accessions located in different climate stages of central and southern Tunisia. To test potential regional effects on morphological traits, ANOVA of mean values was conducted in R 3.3.2 .Additional file 1: Table S1. Frequencies of the different phenotypic classes calculated for each trait by landraces.Additional file 2: Table S2. Main morphological characteristics of 11 landraces identified across 304 Tunisian durum wheat accessions based on IPGRI (1985) [I (1985) , UPOV (1I (1985)  and DeghI (1985) .Additional file 3: Table S3. Shannon-Weaver index (H′) estimated on the 11 Tunisian durum wheat landraces.Additional file 4: Table S4. List of Single Sequence Repeat (SSR) markers with their chromosome allocation, forward and reverse primer sequences, size and dye used.Additional file 5: Figure S1. Genotype accumulation curve generated under R 3.3.2 [ R 3.3.2 , for theAdditional file 6: Table S5. Summary of Private Alleles.Additional file 7: Table S6. Pairwise Nei’s genetic distances between the durum wheat genetic groups based on 10 SSR markers.Additional file 8: Table S7. Shannon-Weaver index (H′) estimated for the genetic clusters C1 and C2 defined by MSN analysis.Additional file 9: Table S8. Diversity indexes of the genetic clusters C1 and C2 defined by MSN analysis.Additional file 10: Table S9. Frequencies of the different phenotypic classes calculated for each trait by regions and by climatic stages.Additional file 11: Table S10. Global Positioning System coordinates, number of durum wheat accessions and regions of the different collecting sites provided by The National Gene Bank.Additional file 12: Table S11. Descriptors used for estimating spike- and grain-based trait diversity in the durum wheat landraces.


DA genetic distance, multidimensional scaling analysis, and principal component analysis showed that the Guanzhong Han population has closer genetic affinities with Northern Han, Chengdu Han, and Xinjiang Hui groups from China based on allelic frequencies of 15 overlapped STR loci from Guanzhong Han and 13 reference groups. The present results indicated that Microreader™ 23sp ID kit included highly polymorphic loci, and it could be well used for individual identification, paternity testing, and population genetics in the Guanzhong Han population.The short tandem repeat (STR) loci are polymorphic markers in the combined DNA index system (CODIS) and non-CODIS STR loci. Due to the highly polymorphic characteristic of STR loci, they are popular and widely used in forensic DNA typing laboratories. In this study, 22 STR loci  and an Amelogenin locus were genotyped and analyzed in 590 unrelated individuals of the Guanzhong Han population. None of the 22 STR loci deviated from the Hardy–Weinberg equilibrium, and all the loci were in the linkage equilibrium state. We observed 247 alleles, and the corresponding allelic frequencies ranged from 0.0008 to 0.3695 in the Guanzhong Han population. The combined power of discrimination and the cumulative exclusion probability was 0.999 999 999 999 999 999 999 999 999 346 36 and 0.999 999 999 709 74, respectively. The results including Nei's  Short tandem repeats (STRs), as the molecular genetic marker of DNA length polymorphism, are widely spread in the human genome and often used to study population genetics, individual identification, and paternity testing by forensic researchers , 2. The The Han nationality is the largest of 56 ethnic groups in China, accounting for 91.59% of the national population , 10, 11.The Guanzhong region is located in the central part of Shaanxi province containing the five cities of Xi'an, Tongchuan, Baoji, Xianyang, and Weinan. It accounts for 55623 square kilometers with a permanent population of more than 23 million . Xi'an, According to the research purpose, the blood samples of 590 healthy volunteers in the Guanzhong region were collected and made into dried blood spot specimens. Before blood samples were collected, 264 male and 326 female volunteers who claimed that they were unrelated at least three generations understood and signed the informed consents. This project had been supported from the human and ethical committees of Xi'an Jiaotong University and Southern Medical University before it started.μl volume was performed by the GeneAmp® PCR 9700 Thermal Cycler . Then, PCR products labeled with fluorescent dyes were size-separated, detected using ABI PRISM® 3130xL Genetic Analyzer , and the results were analyzed by GeneMapper® ID-X 1.3 software . All the conditions and reagents in PCR and capillary electrophoresis were the same as previously reported [All samples were directly and simultaneously amplified with 22 STR loci and the Amelogenin gender locus using Microreader™ 23sp ID kit without the DNA extraction. Multiplex PCR with the 25 reported , 18.P values of Hardy–Weinberg equilibrium (HWE) tests as well. According to specification, ARLEQUIN software (version 3.5) [P values were calculated by ARLEQUIN software (version 3.5) using analysis of molecular variance (AMOVA) method, and the calculations of Nei's DA genetic distances [DA more intuitively by R statistical software (version 3.0.2). A Neighbor-Joining tree (NJ-tree) and a circular phylogenetic tree were constructed by MEGA version 3.697 [https://itol.embl.de/itol.cgi) based on the values of Nei's DA distances with the purpose of illustrating the genetic relationships among 14 different groups. In addition, an unrooted tree was plotted by PHYLIP software (version 3.69) on the basis of the allelic frequencies of 15 same STR loci. The multidimensional scaling analysis (MDS) diagram was plotted using an algorithm in PASW statistics software (version 18). In addition, the principal component analysis (PCA) diagram was constructed by MVSP software (version 3.1) based on allelic frequencies of 15 shared STR loci.Allelic frequencies and forensic parameters including probability of exclusion (PE), polymorphism information content (PIC), matching probability (MP), power of discrimination (PD), and observed heterozygosity (Ho) were calculated by modified PowerState spreadsheet (version 1.2). And it was used to analyze ion 3.5)  was usedion 3.5)  in this istances  were peron 3.697  and iTOLP values of 22 STR loci for the HWE tests in the Han population resided in the Guanzhong region were presented in Table P value with lower than the significance level of 0.05, while the others were higher than the significance level. P values of the LD tests were presented in Table P values of 25 pairs of 231 pairs in 22 STR loci were less than 0.05. The pairwise actual correlation coefficient (r2) values of 22 STR loci were less than 0.01, demonstrating that there were no strong relationships between pairwise loci  and linkage equilibrium (P ≤ 0.05/231) after using Bonferroni correction, indicating that these loci were independent of each other and could be performed in subsequent calculations using the multiplication rule.All the 22 STR loci were successfully genotyped in 590 unrelated samples. The i Figure . There wAllelic frequencies and forensic parameters of 22 STR loci were counted by Modified PowerState version 1.2 spreadsheet and shown in P values of the 15 same loci were calculated using AMOVA method and presented in DA values of the pairwise groups were shown in Table DA values from small to median to large. The Hainan Li and Changsha Hui showed the maximum Nei's DA value (0.1136), while Xinjiang Hui and Northern Han showed the minimum Nei's DA value (0.0029). As far as the Guanzhong Han population, it showed the longest genetic distance with the Changsha Hui group (DA = 0.0950), on the contrary, it presented the shortest genetic distance with the Northern Han population (DA = 0.0030).The locus-by-locus DA distances, and the circular phylogenetic tree presented in The genetic relationships among different groups were intuitively exhibited in trees. The NJ-tree which was shown in DA distances, which was presented in Next, in order to further explore the genetic relationships of 14 populations, we constructed a MDS plot based on the pairwise Nei's MVSP software was used to construct two PCA plots based on the allelic frequencies of 15 overlapped STR loci with the aim of demonstrating the genetic relationships among the 14 groups. The first, second, and third proportions of principal components accounted for a total of 47.484%. Different colors represented different populations in the two plots, and different shapes represented different populations or different regions; that is, the solid circle represented the Han population, the upward triangle represented the Tibetan group, the downward triangle represented the Hui group, the hollow circle represented the Li group, and the diamond represented the ethnic groups in the Xinjiang region. As shown in Due to the complexity of population backgrounds and geographical features in China, population genetic researches of different ethnic groups in China have attracted much attentions in recent years . Since aP values and r2 values of pairwise STRs in LD tests revealed that there was no LD in all pairwise loci at 22 STR loci.The 22 STR loci conformed to the HWE in the Guanzhong Han population and all pairwise STR loci did not deviated from linkage equilibrium, which could be used for subsequent population genetic analyses. In addition, it would not be considered as linkage if the physical distance between two STR loci is more than 10 Mb in the human genome , 37. TheA total of 247 alleles were found in the Guanzhong Han population. Among these 247 alleles, the minimum allelic frequency value was 0.0008, and the maximum allelic frequency was 0.3695. Generally speaking, a STR locus with PIC value greater than 0.5 indicates that it may provide high genetic information in the studied group. The Ho value of STR locus used in forensic genetic research should be more than 0.8 for forensic individual identification and paternity testing. In this study, the average PIC value was 0.7851, and the mean Ho value was 0.8088, which were similar to the values of other 13 reference groups based on 15 overlapped STR loci Figure . In addiDA distances showed that the closest genetic distance to the Guanzhong Han population was the Northern Han (DA = 0.0030) in this study, followed by the Southern Han (DA = 0.0040) and the Xinjiang Hui (DA = 0.0043). The three trees  were constructed using three different softwares, and all the results indicated that the genetic distances between the Han populations in different regions were relatively close. MDS represented the spatial distribution of clusters in different populations and reflected the genetic differentiation pattern among populations to a certain extent. The genetic relationships between populations could be analyzed directly through the spatial distances between different populations in the MDS diagram. In the PCA diagram, the relationships between discrete points formed in the two-dimensional space on basis of allelic frequencies of 15 STR loci in every population were sufficient to reflect the genetic differentiations among populations. The results of MDS and two PCA plots were the similar as those of the phylogenetic trees in this research.Allelic frequencies of the 15 STR loci were used to analyze the population differences between the Guanzhong Han and 13 reference groups published previously using AMOVA method in ARLEQUIN software, and the results showed that these loci with significant differences had population differentiation abilities between the Guanzhong Han population and the other 13 groups, which were suitable for the comparative study among populations [Previous research using HLA loci has explored the relationships between the Guanzhong Han population of Shaanxi province, Northern Han, and Southern Han populations and pointed out that these populations had closer genetic relationships . ObviousIn this research, 22 autosomal STR loci were used to successfully typed and collected genetic information from 590 Han individuals dwelling in the Guanzhong region. The CPD and CPE values showed that the 22 STR loci could be applied to forensic individual identification and paternity testing for the Guanzhong Han population in daily forensic DNA cases. The results of the phylogenetic analyses indicated that there were relatively close genetic relationships between the Guanzhong Han population and the other Han populations in different regions of China and Xinjiang Hui group. In order to further reveal ancestral components for the Guanzhong Han population, more genetic markers will be used for detection and analysis in the future.


One of the main goals of the plant breeding in the twenty-first century is the development of crop cultivars that can maintain current yields in unfavorable environments. Landraces that have been grown under varying local conditions include genetic diversity that will be essential to achieve this objective. The Center of Plant Genetic Resources of the Spanish Institute for Agriculture Research maintains a broad collection of wheat landraces. These accessions, which are locally adapted to diverse eco-climatic conditions, represent highly valuable materials for breeding. However, their efficient use requires an exhaustive genetic characterization. The overall aim of this study was to assess the diversity and population structure of a selected set of 380 Spanish landraces and 52 reference varieties of bread and durum wheat by high-throughput genotyping.durum, turgidum and dicoccon being identified. The population structure of bread wheat landraces was mainly biased by geographic origin.The DArTseq GBS approach generated 10 K SNPs and 40 K high-quality DArT markers, which were located against the currently available bread and durum wheat reference genomes. The markers with known locations were distributed across all chromosomes with relatively well-balanced genome-wide coverage. The genetic analysis showed that the Spanish wheat landraces were clustered in different groups, thus representing genetic pools providing a range of allelic variation. The subspecies had a major impact on the population structure of the durum wheat landraces, with three distinct clusters that corresponded to subsp. The results showed broader genetic diversity in the landraces compared to a reference set that included commercial varieties, and higher divergence between the landraces and the reference set in durum wheat than in bread wheat. The analyses revealed genomic regions whose patterns of variation were markedly different in the landraces and reference varieties, indicating loci that have been under selection during crop improvement, which could help to target breeding efforts. The results obtained from this work will provide a basis for future genome-wide association studies. Triticum aestivum L.; 2n = 6x = 42, 17Gb, AABBDD genomes). The remainder of the world’s wheat production includes about 35–40 million tons of durum wheat , which is cultivated mainly in the Mediterranean region (http://www.fao.org/faostat/en/).Wheat is a cereal that belongs to the Poaceae family. Wheat occupies a central place in human nutrition providing 20% of the daily protein and food calories of the human population. Currently cultivated wheat originated from natural hybridization events between different species . RoughlyAdvances in molecular biology and high-throughput genotyping technologies have significantly impacted the field of molecular plant breeding, leading to shift from a phenotype-based to a genotype-based selection . The intThe successful genomics-assisted breeding of any crop will be enhanced by a thorough understanding of the species’ genetic diversity. As is the case in other crops, genetic diversity of wheat has declined as a consequence of bottlenecks encountered during polyploidization and domestication , 8. ModeA large number of studies have been performed to estimate genetic diversity by employing different methodologies in diverse plant species , 12, inchttps://www.diversityarrays.com), where it has been extensively used [https://seedsofdiscovery.org/about/genotyping-platform/).The assessment of genome-wide diversity by GBS provides robust estimates of diversity and has been increasingly adopted as a fast, high-throughput cost-effective tool for whole-genome genetic diversity analysis in large germplasm sets . The DArely used , 22, 23.High-throughput genotyping also provides essential information for the design of high-power GWAS, which enable the identification of agriculturally important genes and facilitate their transfer from wild or local germplasm into modern cultivars through marker-assisted selection and marker-assisted breeding and/or genomic selection. For GWAS analysis, the optimum diverse panel must be genotyped with a set of molecular markers covering as much of the genome of the species as possible , but theThe Spanish wheat landraces conserved at the National Plant Genetic Resources Center (CRF-INIA) and maintained in the national collection were collected in the first half of the twentieth century. Several studies have shown the great variability of the Spanish durum wheat accessions compared to other germplasm collections –29. HoweThe aim of the present study was to characterize two collections of durum and bread wheat landraces from CRF-INIA by using the DArTseq-GBS approach. The specific objectives of the present investigation were: (1) to assess the genomic diversity of a set of durum wheat accessions comprising 191 Spanish landraces and 23 reference varieties, (2) to assess the genomic diversity of a set of bread wheat accessions comprising 189 Spanish landraces and 29 reference varieties, and (3) to compare the genetic diversity of landraces and modern cultivars in both wheat species.We characterized a set of 380 landraces and 52 reference varieties at genomic level . As shown in Table In tetraploid durum wheat (214 accessions), a total of 98,983 DArTseq markers and 51,751 SNP markers were obtained , a slightly higher number of markers, including 130,899 DArTseq markers and 58,660 SNPs, was generated  values for the DArT and SNP data was asymmetrical and skewed towards the lower values Fig. . In durudicoccon were grouped in Pop5, and all 37 of the subsp. turgidum accessions were clustered in Pop3. The landraces in both populations came mostly from the north of Spain , which was classified into Pop3, were distributed among five populations , containing between 10 and 80 accessions   value, a measure of population differentiation in collections with several populations, was 0.22. The FST values, which are related to genetic differentiation between populations, ranged from 0.743 (Pop2 vs Pop5) to 0.226 (Pop1 vs Pop6). Pop6 showed the least genetic differentiation from the rest of the populations, including those of subsp. turgidum (Pop3) and dicoccon (Pop5)  whereas subsp. turgidum showed lower values compared to either durum and dicoccon .Genetic diversity parameters were calculated for the fastSTRUCTURE populations based on the SNP data Table . The popturgidum and dicoccon , while durum showed higher diversity values across the genome  come from the North of Spain  based on the 9324 filtered SNP markers. The first two principal coordinates explained 21% of the total variation. Three discrete groups corresponding to the three subspecies could be clearly identified .Allelic variation was also studied for the HMW-GS (High Molecular Weight Glutenin Subunits) loci turgidum and dicoccon accessions to gain insight into the variability within subsp. durum  appeared to be located close to the Pop1 landraces in this case  was grouped together with the reference varieties. This accession, collected at the end of the 1990, is characterized by early-maturity and short plants [Pop1, Pop2, and Pop7 were the t plants , which sfastSTRUCTURE runs with 44,241 DArT markers divided the hexaploid wheat landrace accessions into four populations (K = 4). Compared to durum wheat landraces, a higher level of admixture was detected in the bread wheat populations, especially within Pop2, which was the largest population, containing 112 accessions . The FST values between populations ranged from 0.169 (Pop1 vs Pop2) to 0.573 (Pop3 vs Pop4). According to the FST values, Pop4 was the most differentiated population , which formed the most distant group, from the other three populations, which appeared to be distributed along PCo2 Fig. a. Some dVrn-A1 gene in relation to the bread wheat population structure. Three different alleles were identified in the collection: the winter-type allele vrn-A1 and two alleles that are generally related to a spring growth habit, Vrn-A1a and Vrn-A1b. The accessions from Pop4 were characterized by almost exclusively presenting the Vrn-A1b allele. The accessions presenting the other two alleles could be differentiated along the PCo2 axis, whose upper portion corresponded to spring-type landraces, whereas the reference varieties and winter-type landraces were included in the lower portion  were clustered on the right side of the PCoA and corresponded to most of the Pop4 samples. Again, an interesting tendency could be observed along the PCo2 axis: accessions with the Glu-B1e allele (HMW-GS 20x + 20y) appeared to be grouped in the upper portion, while the lower portion corresponded to accessions with Glu-B1u or Glu-B1al alleles (HMW-GS 7 + 8 or 7OE+ 8) .The representation of http://webx.inia.es/web_coleccionescrf/CaracterizacionCRFeng.asp), they may not be real landraces.The overlap between the landraces and reference varieties was more remarkable in bread wheat than in durum wheat. In fact, the reference varieties fully overlapped with the Pop2 accessions. Some of the landraces located closer to the reference varieties were collected in the 1990s , and according to their early flowering and lower height phenotypes  and Pop2 (durum), and the lowest differentiation from the durum landraces in Pop4 and Pop6 . In bread wheat, the reference varieties showed the highest and lowest differentiation from the landraces in Pop4 and Pop2, respectively .The divergence between the reference varieties and landraces varied among the different populations identified by fastSTRUCTURE. The durum wheat reference varieties showed the highest differentiation from the landraces in Pop5 (dicoccon and turgidum (4079 and 2119 respectively) and much higher than that found in subsp. durum (478 fixed markers). In the bread wheat reference accessions, the number of fixed SNP markers was 1771 (21%) clearly lower than the number obtained in durum wheat  was comparable to that found in subsp. Rht-D1, a key gene introduced in wheat cultivars during the 20th that is located on chromosome 4D, and Vrn-B1, located on 5B and related with growth habit.We also analyzed the Hs distribution across the genome in the landraces and reference varieties Fig. . We callwww.seedsofdiscovery.org; www.divsek.org). However, Spanish landraces, which are locally adapted to a wide diversity of eco-climatic conditions and mostly cultivated under rainfed low-input management systems, are absent or only represented by a small number of accessions in these studies. We decided to explore the genetic diversity of these valuable materials, by performing an analysis at the genomic level of 380 selected landraces representing the genetic variability of the wheat collection maintained at the Spanish Plant Genetic Resources Center, which is composed of more than 1600 accessions.Modern bread and durum wheat varieties have resulted from breeding programs that have mainly been focused on achieving high yields in conventional agricultural systems. The unpredictable effects on crop performance under future climate scenarios and the increasing concern for the environmental consequences of crop management practices, which are commonly based on excessive irrigation and fertilizer application, are reorienting breeders’ aims toward the development of new wheat cultivars that can maintain high yields under uncertain climatic conditions and in a more sustainable manner. For this purpose, genetic resources maintained in wheat genebanks, which have generally been underused, need to be thoroughly characterized so that the useful genetic variation that is present is transferred to modern elite gene pools. Several recent international initiatives are characterizing local wheat germplasm collections . Am. AmAe. tat  landraces belong to three main interfertile subspecies . The subsp. dicoccon, also known as emmer wheat, is a hulled wheat that is only grown in the North of Spain and represents the feral situation of this crop. Subsp. durum is the most widely cultivated and well adapted to the dry-summer conditions of the South. Subsp. turgidum, which is less common and grown in colder areas than durum, mostly consists of winter wheat [The Spanish durum wheat  carried Vrn-A1b, and 7 out of the 11 dicoccon landraces characterized for Vrn-A1 carried the winter vrn-A1 allele  in temperate cereals, and by affecting the vegetative to reproductive transition, these genes are involved in the ability of wheat plants to adapt to a wide range of environments . The evoterature , 49. Non studies , 51. Allarieties , 52, 53 arieties . In our escribed . The sprdicoccon and, to some extent, for turgidum landraces. The clustering of these two groups of accessions, each in a single population, may reflect similar environmental conditions in their respective geographic origins. The landraces of subsp. durum, which were structured into five distinct populations, showed higher variability and greater complexity, including different phylogenetic groups [Within our collection, a restricted geographic distribution exists for the Spanish landraces belonging to the less represented subspecies c groups . The idec groups , 54, 55.Triticum aestivum subsp. vulgare, and our bread wheat set was therefore composed exclusively of this subspecies. The population stratification of the bread wheat panel identified four groups of landraces with high divergence according to the obtained FST values. This clustering reflected the geographic origin of the accessions better than in the subsp. durum. The genetic differentiation estimated with Dest was lower in the bread landrace collection than in the whole durum wheat collection, in agreement with the lower level of stratification observed. Few studies have simultaneously addressed the variability of hexaploid and tetraploid wheat varieties but higher genetic diversity in durum than in bread wheat has been previously reported in landraces from other countries . Severaad wheat , 57.f allele at the Glu-B1 locus. The Glu-B1f allele presents a low frequency in worldwide collections but has been previously described as being characteristic of Iberian landraces, which is also the case for the Glu-B1e allele [Glu-B1e allele is related to poor rheological properties in bread wheat, but the f allele has been associated with good dough quality [One of the four groups detected (Pop4) was clearly more genetically distant. This group included landraces from western Spain, where there is a prevalence of acidic or neutral soils . Most ofe allele . The lat quality . The prevrn-A1 was the most common Vrn-A1 allele found in the T. aestivum reference cultivars (22 out of 29 varieties). However, the most frequent of these alleles within the bread wheat landraces was the Vrn-A1a allele, which was absent in the durum wheat. This Vrn-A1 allele, which results in complete insensitivity to vernalization, is recognized as the spring-habit allele with the greatest effect among all such alleles described [Vrn-A1 showed some relationship to population structure and a somewhat biased tendency along the second PCo axis . However, high relatedness to the reference varieties was detected for a reduced group of durum landraces. This group included ‘Caravaca’ (BGE002869), a Spanish landrace used by CIMMYT in the development of some modern cultivars . It can also be noted that other studies have reported a close relationship between Spanish and North African landraces [In diversity studies, wheat landraces usually cluster in a separate group from elite cultivars , 63, 65 andraces , 44 and http://www.wheatpedigree.net/). Some other varieties such as ‘Richela Blanca’, ‘Montnegre’ or ‘Ardito’, are related to old Italian material [In bread wheat, the situation was quite different, and the mixing between the landraces and reference varieties was much higher, especially for some accessions in Pop2 Fig. . It is lmaterial , 66, whiRht-D1, associated with dwarf phenotype, and Vrn-B1, associated with vernalization response, on bread wheat chromosomes 4D and 5B, respectively [Glu-1A locus. Coupling this analysis with future GWA studies will help to identify the traits underlying each of the fixed regions detected in this work.The overall genetic diversity of the reference cultivars was much lower than that of the landraces in both species Table  and 6. Gectively , 69. In The replacement of local landraces by high-yielding wheat varieties that began at the time of the Green Revolution has led to a loss of genetic variation in crop wheat varieties. This depletion has now encouraged the use of genetic resources in wheat breeding programs, but the genetic variability of these resources needs to be exhaustively characterized for their efficient use. The present study successfully used DArTseq technology for evaluating the diversity within and between two landrace collections of bread and durum wheat and for assessing the genetic relationships between each of these collections and a reference set of modern wheat cultivars. The study of genome-wide diversity provides a resource for the design of high-power GWAS experiments, which will help to achieve the overarching goal of improving wheat for cultivation in different environments, ecosystems and stress situations. The collections of Spanish landraces characterized in the present study were clearly clustered into different groups, representing different gene pools capable of providing different sources of genes for plant breeding. The investigated panel of genotypes showed an outstanding degree of diversity compared to the reference counterparts. It therefore clearly represents a strategic platform and a valuable genetic resource that must be further studied to ensure not only its efficient conservation and management but also its useful exploitation in breeding programs.durum, turgidum and dicoccon, respectively, while all the bread wheat landraces belonged to the subspecies vulgare. All these accessions were homozygous lines derived from genebank accessions provided by CRF-INIA. Additionally, the study included a set of 23 improved varieties of durum wheat and 29 improved varieties of bread wheat (hereafter referred to as reference varieties), which comprised the cultivars most widely grown in Spain during the last 50 years plus some varieties widely used in wheat research, such as tetraploid ‘Langdon’ and hexaploid ‘Chinese Spring’.The plant material analyzed in the present study comprised 432 selected accessions  was used to create a genome representation of the set of samples. PstI-RE site specific adapter was tagged with 96 different barcodes enabling multiplexing a 96-well microtiter plate with equimolar amounts of amplification products in order to run within a single lane on Illumina HiSeq2500 instrument . The successful amplified fragments were sequenced up to 77 bases, generating approximately 500,000 unique reads per sample. Thereafter the FASTQ files (full reads of 77 bp) were quality filtered using a Phred quality score of 30, which represent a 90% of base call accuracy for at least 50% of the bases. More stringent filtering was also performed on barcode sequences using a Phred quality score of 10, which represent 99.9% of base call accuracy for at least 75% of the bases. A proprietary analytical pipeline developed by DArT P/L was used to generate allele calls for SNP and DArT markers.Triticum aestivum genome IWGSC Refseq v1.0 [Triticum turgidum genome Svevo v1.0 [After this process the genotyping services provided two different sets of markers. The DArT markers were scored as binary data (0/1) indicating the presence or absence of a marker in each accession, and the SNP markers were scored as 0/1/2 indicating the presence of the reference allele in homozygosity, the alternative allele in homozygosity or a heterozygous genotype, respectively. The raw data are available upon request to the corresponding author. To locate the markers in the durum and bread wheat reference genomes, the markers sequences were subjected to BLAST searches against the currently available seq v1.0  for breaevo v1.0  for duruVrn-A1 gene, one of the most determinant loci involved in the transition from vegetative to reproductive growth [Vrn-A1 locus is sufficient to confer a spring growth habit [Vrn-A1a, Vrn-A1b and Vrn-A1c) were characterized by PCR according to [https://maswheat.ucdavis.edu/protocols/Vrn/index.htm.For comparison with the population structure based on GBS-DArTseq markers, we investigated the allelic variability of functional markers in the e growth , 75. It th habit . Three arding to , 52, 68 Glu-1 homoeoloci. These complex loci encode the HMW-GS, which are the major determinants of dough quality in wheat. For this purpose, endosperm proteins were extracted from single seeds and fractionated via sodium dodecyl sulfate polyacrylamide gel electrophoresis (12% polyacrylamide gels) according to Payne et al. [7Additionally, the panel of accessions was genotyped for  et al. 7. HMW-GS e et al. 7.Prior to any further analysis, the set of SNP and DART markers was filtered employing homemade R scripts , which aFor the SNP markers, prior to any filtering step we analyzed the presence of heterozygous genotypes. As we have previously described, genotyping was conducted on homozygous lines and thus we did not expect any heterozygous genotypes. When the genotypic values for a marker was only 0 and 2, we considered the heterozygous calling [The genetic substructure within the durum and bread wheat landrace collections was investigated using the fastSTRUCTURE algorithm  and the The genetic similarity based on the SNP data within the full sets of accessions (landraces plus reference varieties) was analyzed by principal coordinates analysis (PCoA) using the gl.pcoa function from the dartR R package   within populations, landraces and reference varieties was calculated based on the SNP dataset according to  with thefined by  with thifined by  with thefined by  using thFixed genomic regions in the reference varieties were identified by performing a scan of the Hs values along the different chromosomes. Hs was estimated as described previously . HoweverAdditional file 1. Excel file with the description of the accessions analyzed, passport data, population according to fastSTRUCTURE analysis, HMW-GS and VRN-A1 alleles. Sheet 1. Durum wheat. Sheet 2. Bread wheat. Sheet 3. Reference set.Additional file 2. File with the T. durum accession raw DArT genotyping results.Additional file 3. File with the T. durum accession raw SNP genotyping results.Additional file 4. File with the T. aestivum accession raw DArT genotyping results.Additional file 5. File with the T. aestivum accession raw SNP genotyping results.Additional file 6. Figure showing the genetic diversity (Hs) distribution across the A and B genomes in the different durum wheat populations identified with fastStructure.Additional file 7. Figure showing the genetic diversity (Hs) distribution across the A and B genomes in the different durum wheat subspecies.Additional file 8. Figure showing the genetic diversity (Hs) distribution across the A, B and D genomes in the different bread wheat populations identified with fastStructure.