Clostridium perfringens epsilon toxin (Etx) is a pore forming toxin that causes enterotoxaemia in ruminants and may be a cause of multiple sclerosis in humans. To date, most in vitro studies of Etx have used the Madin-Darby canine kidney (MDCK) cell line. However, studies using Chinese hamster ovary (CHO) cells engineered to express the putative Etx receptor, myelin and lymphocyte protein (MAL), suggest that amino acids important for Etx activity differ between species. In this study, we investigated the role of amino acids Y42, Y43 and H162, previously identified as important in Etx activity towards MDCK cells, in Etx activity towards CHO-human MAL (CHO-hMAL) cells, human red blood cells (hRBCs) and synthetic bilayers using site-directed mutants of Etx. We show that in CHO-hMAL cells Y42 is critical for Etx binding and not Y43 as in MDCK cells, indicating that surface exposed tyrosine residues in the receptor binding domain of Etx impact efficiency of cell binding to MAL-expressing cells in a species-specific manner. We also show that Etx mutant H162A was unable to lyse CHO-hMAL cells, lysed hRBCs, whilst it was able to form pores in synthetic bilayers, providing evidence of the complexity of Etx pore formation in different lipid environments. Clostridium perfringens type B and D strains and plays a key role in enterotoxaemia, a severe disease of domestic ruminants that mainly affects sheep. More recently, a growing body of evidence has implicated Etx as a trigger for the development of multiple sclerosis (MS) in humans, a neurological disease of young adults [Epsilon toxin (Etx) is produced by g adults ,2,3,4.50) of Etx in mice after intravenous injection is 100 ng kg−1, equivalent to 7 mg in a 70 kg human, making Etx the third most potent bacterial toxin known [The 50% lethal dose , Etx is released from the bacterium as an inactive, water-soluble monomer, called protoxin (P-Etx). The P-Etx is then activated by proteolytic cleavage of the carboxy-terminal peptide (CTP) by digestive proteases of the host, such as trypsin, or by protease ,8. Both protease ,10,11. P in Ca2+ , which tIn the past few decades many cell lines have been tested for their sensitivity to Etx but only a few have been identified to be sensitive, such as kidney cell lines of dog, mouse and human origin , the mouMAL is an integral membrane protein constituent of lipid rafts with a molecular weight of approximately 17 kDa (VIP17) predicted to have four transmembrane domains and two extracellular loops. It is highly expressed in oligodendrocytes in the central nervous system, human T lymphocytes and kidney epithelial cells, cells that are targeted by Etx. MAL is also known to have four isoforms produced by alternative splicing ,26,27.Evidence to support MAL being a particularly attractive receptor candidate for Etx include: (1) MAL-knockout mice are resistant to Etx at doses at which wild type mice die rapidly ; 2) CHO CHO2,24,Alternative binding partners for Etx have also been proposed and include the extensively O-glycosylated hepatitis A virus cellular receptor 1 (HAVCR1) protein , caveoliAeromonas hydrophila [Clostridium perfringens enterotoxin (CPE) [Clostridium septicum α-toxin [Bacillus thuringiensis parasporin-2 [Eisenia fetida [Etx is a member of the aerolysin family of β-pore-forming toxins (aβ-PFTs) that are found in all kingdoms of life . Like Etdrophila , Clostriin (CPE) , and Clo α-toxin . Other bsporin-2  that kila fetida .Crystal structures of the monomeric forms of aβ-PFTs reveal that members of the aβ-PFTs share a similar domain arrangement : a recepThe high-resolution structure of P-Etx monomer was solved in 2004 (PDB ID: 1UYJ) . This reThrough site-directed mutagenesis studies we have previously identified tyrosine 43 (Y43) as a critical residue for Etx binding to MDCK cells . HoweverOur pore structure of Etx in MDCK cells provides an explanation to the phenotype of important mutants, such as the reduced binding of Etx mutant Y43A to MDCK cells ; tyrosinIn this study, we investigated the role of amino acids Y42, Y43 and H162, previously identified as important in Etx activity towards MDCK cells, in Etx activity towards CHO-hMAL cells, human red blood cells (hRBCs) and artificial lipid bilayers using site-directed mutants Etx-Y42A, Etx-Y43A and Etx-H162A, and a range of molecular, cell biology and biophysical approaches. We show that in CHO-hMAL cells Y42 is critical for Etx binding and not Y43 as in MDCK cells, indicating that surface exposed tyrosine residues in the RBD impact efficiency of Etx binding to MAL-expressing cells in a species-specific manner. We also show that Etx-H162A was unable to lyse CHO-hMAL cells but lysed hRBCs, whilst it was able to form pores in synthetic bilayers, providing substantial evidence of the complexity of Etx pore formation in different lipid environments. This will have implications in selecting a model system to assess the toxicity of Etx variants.In the first group of experiments we evaluated the three stages of Etx interaction  with the plasma membrane of CHO-hMAL cells using molecular and cell biology approaches. We have previously generated site-directed mutants of P-Etx containing mutations Y16A, Y20A, Y29A, Y30A, Y36A or Y196A  in H149A (H162A in this study) background to investigate the role of surface exposed tyrosine residues in the RBD in P-Etx binding to MDCK cells using On-Cell Western assay . In the To confirm that H162A mutation does not affect binding of P-Etx to CHO-hMAL cells, next we generated site-directed mutants P-Etx-Y42A, P-Etx-Y43A and P-Etx-H162A in wild type background. On-Cell Western assay shows that binding of P-Etx-H162A is similar to that of wild type P-Etx, and the binding pattern of P-Etx-Y42A and P-Etx-Y43A is similar to those of P-Etx-H162A-Y42A and P-Etx-H162A-Y43A . These dNext, we evaluated the effect of Y42A, Y43A or H162A mutation on oligomerisation of trypsin-activated P-Etx in CHO-hMAL cells at room temperature and 37 °C by performing Western blot analysis of SDS-resistant oligomers . Etx-H1650) relative to wild type Etx . Etx-H162A was unable to lyse CHO-hMAL cells despite its preserved binding  released into culture supernatants upon cell lysis as described in Methods . As show binding  and olig binding  activitiIn a second group of experiments we investigated Etx mode of action in hRBCs. First, we evaluated the effect of Etx-Y42A, Etx-Y43A and Etx-H162A on the haemolytic activity of Etx towards hRBCs at room temperature and 37 °C using toxin concentrations 1 µM and 10 µM. Etx-Y42A was non-haemolytic at 1 µM a,c, whilNext, we evaluated the effect of mutations Y42A, Y43A or H162A on Etx oligomerisation in hRBCs at room temperature and 37 °C by performing Western blot analysis of SDS-resistant oligomers . OligomeIn a separate group of experiments, we investigated the effect of Etx on hRBC morphology. As explained in Methods , haemoglFinally, to investigate if RBD mutations Y42A and Y43A or PFM mutation H162A affect a hydrophobic-mediated pore formation mechanism by Etx in 1,2-diphytanoyl-sn-glycerophosphatidylcholine (DPhPC) lipid bilayers we employed the technique of single channel electrophysiology on black lipid membranes. The pore conductance for each applied voltage was calculated as described in Methods  and therWe have previously provided key insights into the mechanisms by which Etx interfaces with the host cell membrane. Through site-directed mutagenesis studies we identified surface exposed tyrosine residue Y43 in the RBD of Etx as important for Etx binding to MDCK cells . HoweverOur cell binding studies revealed that in CHO-hMAL cells Y42 and not Y43, previously identified as important in Etx binding to MDCK cells, plays a critical role in Etx binding, suggesting that different tyrosine residues impact the efficiency of Etx binding to MAL-expressing cells in a species-specific manner. This exciting finding could explain the differences in potency and effect of Etx between species.We hypothesised that if binding of Etx-Y42A was significantly reduced to CHO-hMAL cells, which correlated with severely impaired oligomerisation and cytotoxic activities, and if Etx binding to CHO-hMAL cells is dependent on the presence of the hMAL receptor, then activity of Etx-Y42A towards hRBCs would be severely impaired, too. However, Etx-Y42A was haemolytic towards hRBCs and was able to form oligomers, indicating that Etx mode of action in hRBCs differs from that in CHO-hMAL cells.Haemolytic activity of Etx-Y42A increased with temperature at 10 µM that correlated with increased oligomer yield. The temperature increase appears to compensate the effect of the Y42A mutation; however, it does not repair it enough to match the activity of wild type toxin. This suggests that Y42A is defected in a way that the interaction with a receptor would be unstable, leading to transient binding and unbinding. Increased potency of Etx-Y42A at higher temperatures may suggest that more monomers are being bound to the membrane, resulting in increased receptor binding activity. Increased temperature could expose hydrophobic amino acids leading to enhanced hydrophobic binding efficiency, and/or expose receptor binding amino acids, which would enhance receptor binding. There is also a growing body of evidence for the importance of thermal shape fluctuations in regulating protein function such as dynamic contributions to allosteric regulation ,48. ThusHaemolytic activity of Etx-Y42A was also concentration dependent. Very little haemolysis was seen at 1 µM compared to 10 µM . This coThese results do not fully clarify whether Y42 is required for Etx binding to hRBCs but do provide evidence towards a complex interaction scenario where multiple binding mechanisms are used. It is possible that there is both hydrophobic-mediated and receptor-mediated interactions between Etx and the hRBC membrane. This hypothesis could explain the reduced haemolytic activity of Etx-Y42A relative to wild type toxin, where mutation of the Y42 amino acid prevents receptor-mediated but not hydrophobic-mediated binding, while Etx-wild type and Etx-Y43A may simultaneously employ both binding routes, and therefore have a more severe and rapid haemolytic affect. The Etx receptor identity on hRBCs remains controversial. A recent study suggested that MAL plays an important role in Etx-mediated haemolysis of hRBCs . Other sInterestingly, despite the preserved binding of Etx-Y43A to CHO-hMAL cells, Etx-Y43A showed reduced oligomer yield relative to wild type Etx that correlated with reduced cytotoxicity. In contrast, oligomerisation and haemolytic activities of Etx were not affected by the Y43A mutation in hRBCs.−19 J [−19 J [Our Etx pore structure assembled on MDCK cells has previously suggested that the reduced oligomer yield of Etx-H162A, which correlated with reduced cytotoxicity, may be due to reduced stability of the DBB fold, decreasing stability of formed oligomers and thus preventing efficient pore formation . However−19 J  is much J [−19 J , hence aThe partially hydrophobic H162 amino acid is thought to be in an equivalent position to leucine 277 (L277) in aerolysin , and EtxOur electrical measurements on Etx mutants in DPhPC lipid bilayers reveal that their ion conductance capabilities are unchanged within the error of our measurements. This demonstrates that RBD mutations Y42A or Y43A, or PFM mutation H162A do not affect Etx pore formation in DPhPC lipid bilayers, in contrast to the complex variations observed in cells. Cells have many other structures on their membranes, such as the glycocalyx that would inhibit access to a protein. With most Etx-susceptible cells, a receptor is likely needed to overcome any barriers to binding. In addition, the heterogeneity of lipid species in the outer (and inner) leaflets of plasma membranes could affect monomer diffusion times and therefore oligomerisation time scales.2+ influx which, in addition to the flux of K+ and Cl- through the Etx pore, induces haemolysis [The radial profiles and images of hRBCs incubated with wild type Etx show cells swelling and becoming more rounded, followed by a loss of haemoglobin, resulting in empty ghosts a. Etx poemolysis . P2 antaemolysis . Anotheremolysis . The resemolysis .In conclusion, our data provide substantial evidence of the complexity of Etx activity in different lipid environments and indicate that Etx toxicity in MDCK cells does not reflect Etx toxicity in human cells, which will have implications in assessing the toxicity of Etx vaccine candidates. Further research is needed to explore the role of thermal fluctuations in Etx pore formation.All chemicals were purchased from Sigma, UK, unless otherwise stated. The polyclonal antibody against Etx mutant Y30A-Y196A (Y43A-Y209A in this study) was raised in rabbits as described in . Protein−1 sodium bicarbonate supplemented with 0.05 mM nonessential amino acids and 10% foetal bovine serum Gold  at 37 °C in a humidified atmosphere of 95% air / 5% CO2. In between culturing, cells were routinely detached by incubation in trypsin/EDTA and split as appropriate .Chinese hamster ovary (CHO) stable cell line expressing green fluorescent protein (GFP)-tagged human MAL (CHO-hMAL) was constructed and cultured as described previously . In brieetxD, encoding epsilon protoxin (P-Etx) with the H162A mutation (P-Etx-H162A) was subcloned from plasmid pCl0 into the expression vector pET-26b(+)  using NcoI and XhoI restriction sites as described previously [The gene, eviously , which fMutations were introduced into the gene encoding P-Etx using the QuickChange Lightning Site-Directed Mutagenesis Kit  as described in . The preE. coli Rosetta 2 (DE3) cells  as described in [−1 carbenicillin and 34 μg mL−1 chloramphenicol and cultured at 37 °C for 3 h at 300 rpm and at 20 °C for a further 24 h at 300 rpm. Cells were harvested by centrifugation  and the cell pellet was lysed by 10 mL BugBuster™ Protein Extraction Reagent  containing rlysozyme™ (0.5 μL at 30 KU μL−1)  and Benzonase® Nuclease (10 μL at 25 U μL−1) . The cell suspension was incubated on a rotating mixer for 25 min at room temperature and centrifuged  to separate soluble and insoluble fractions. The supernatant was loaded onto His GraviTrap columns  and purification was carried out at 4 °C as described in [Recombinant P-Etx and its derivatives were expressed and purified in ribed in . In brieribed in . In briew/w) ratio and incubated at room temperature for 1 h. The reaction was stopped by adding trypsin inhibitor (0.66 mg per 1 mg trypsin) to the digest. Purified recombinant P-Etx and its derivatives were activated with trypsin, TPCK (L-(tosylamido-2-phenyl) ethyl chloromethyl ketone) treated from bovine pancreas as described in . In brieg for 10 min at 4 °C) between washes. Washed cells were resuspended in 50 mL DPBS (2.5 × 109 cells/mL) and stored on ice for 30 min. After centrifuging cells (1500g for 10 min), the supernatant was removed, and hemolysis was performed by resuspending cells in 1:15 PBS . Cells were incubated for 30 min on ice and ghosts were pelleted at 20,000g for 40 min. Ghosts were washed three times in 20 mOsm buffer as above and resuspended in DPBS.Human red blood cell ghosts were prepared as described previously ,55. In b4 cells/well in DMEM-F12 medium containing 10% foetal bovine serum (DMEM-F12/FBS) and plates were incubated overnight at 37 °C in a humidified atmosphere of 95% air / 5% CO2. The next day, cells were washed with DMEM-F12/FBS and incubated with purified recombinant P-Etx (5 µM) for 30 min at 37 °C in a humidified atmosphere of 95% air/5% CO2. For background control, cells were incubated with DPBS only. Unbound toxin was removed by washing cells three times with DMEM-F12/FBS. Cells were then fixed with 2% formaldehyde at room temperature for 15 min, washed with DPBS three times, and blocked for 1.5 h using Odyssey blocking buffer . Bound P-Etx was detected with rabbit anti-Etx polyclonal primary antibody raised against recombinant P-Etx with Y43A and Y209A mutations [® 800CW goat antirabbit IgG (H + L) secondary antibody  at 1:500 dilution. Fluorescence was detected using the Odyssey CLx infrared imaging system . Quantitative analyses were performed using the Image Studio ver 5.2 software. On-Cell Western assay was used to measure binding of recombinant P-Etx and its derivatives to CHO cells expressing human MAL as described previously . In brieutations  at 1:2006 cells per well), washed three times with DPBS to remove residual trypsin present in the cell culture medium, and incubated with 2 mL pre-warmed L15 medium containing trypsin-activated recombinant Etx-wild type, Etx-H162A, Etx-Y42A or Etx-Y43A  at room temperature or 37 °C for 1 h to allow binding and oligomerization. Cells were subsequently washed three times with DPBS to remove unbound Etx, lysed by three cycles of freezing and thawing in 100 μL ice cold DPBS supplemented with Halt™ Protease Inhibitor Cocktail (100×)  at a final concentration of 1× and harvested by scraping. The collected cells were transferred to a microcentrifuge tube and solubilized in DPBS containing 1% (w/v) DDM by incubation at 4 °C overnight with occasional shaking. After incubation, insoluble material was removed by centrifugation  and the concentration of solubilized protein was determined by BCA assay.Oligomerization assay was performed as described in , with mo® Turbo™ Transfer System (Bio-Rad). The membrane was blocked with PBS containing 0.1% Tween-20 and 5% skim milk and oligomeric complexes were detected with rabbit anti-Etx polyclonal primary antibody [® 800CW goat anti-rabbit IgG (H + L) secondary antibody  at 1:500 and 1:5000 dilutions, respectively. For loading control, the mouse monoclonal Na+/K+-ATPase α1 (C464.6): sc-21712 primary antibody  and the IRDye® 680RD goat  anti-mouse IgG (H + L) secondary antibody  were used at 1:200 and 1:5000 dilutions, respectively. Antibodies were diluted in PBS containing 0.1% Tween-20 and 3% skim milk. Immuno-reactive bands were detected using the Odyssey CLx infrared imaging system . Quantitative analyses were performed using the Image Studio ver 5.2 software and the Housekeeping Protein Normalization Protocol . Toxin complexes in solubilization buffer were analysed by SDS-PAGE and Western blot as described in . In brieantibody  and IRDy® 680RD goat  anti-mouse IgG (H + L) secondary antibody  were used at 1:2000 and 1:5000 dilutions, respectively.Human RBC ghosts  were incubated with trypsin-activated Etx variants  or buffer only at room temperature or 37 °C for 1 h. Following detergent solubilisation, toxin complexes (30 µg per lane) were separated by SDS-PAGE and oligomerization was assessed by immunoblotting with anti-Etx polyclonal antibody as described above. For loading control, the mouse monoclonal Flotillin 2 (FLOT2) antibody  and the IRDye4 cells per well), alongside negative (DPBS) and positive (0.9% (v/v) Triton X-100) controls. After incubation at 37 °C for 3 h, cell culture medium (50 µL) was transferred to an empty 96-well plate and reconstituted substrate mix (50 µL) was added to each well. The plate was incubated for 30 min at room temperature in the dark. Absorbance at 490 nm was measured using a Tecan Infinite 200 PRO Microplate Reader . Results were normalised to the signal from cells incubated with DPBS only (0% lysis) and cytotoxicity was expressed relative to cells treated with 0.9% (v/v) Triton X-100 (100% lysis). The toxin dose required to kill 50% of the cell monolayer (CT50) was determined by nonlinear regression analysis, fitting a variable slope log (dose) vs. response curve, constraining parameter F (response F percent) to a value of 50, CTF is the concentration of Etx that gives a response 50 percent of the way between Bottom and Top, which are plateaus in the units of the Y axis, HS is the hill slope and F is the percent response.The cytotoxic activity of trypsin-activated Etx and its derivatives toward CHO-hMAL cells was determined by measuring the amount of lactate dehydrogenase (LDH) released into culture supernatants upon cell lysis using the CytoTox 96 Nonradioactive Cytotoxicity Assay Kit  as described in . In brieWe used optical absorption measurements of individual cells to monitor the effect of Etx on hRBC morphology. Images of individual cells were captured in transmission mode using a 415 nm diode as a light source (where haemoglobin has a high absorption) on an Olympus IX50 inverted microscope  equipped with an Olympus UPlanSApo 60×/1.20 W objective, an AVT Stingray F-145B camera and Live Acquisition 2.2.0.8 software. In the first approximation, optical absorbance is linearly proportional to the cell thickness, which allows for the reconstruction of the cell shape from the measured optical absorbance across the image of the cell. Radially averaged absorbance profiles were calculated using a custom Python script as described in .Blood from healthy volunteers was taken using a finger prick lancet and added to a solution of BSA/PBS, to which Etx was gently mixed in. The final sample concentration was 10 µM Etx, 0.5% blood, and 0.1% BSA in PBS. As soon as Etx was added the sample was immediately injected into a microscope slide chamber. Images were taken with an AVT Stingray F-145B camera every two to five minutes using an inverted microscope , 60× water objective , and an ultraviolet (UV) light source at 415 nm (ThorLabs). The UV light was turned off between images to limit any radiative damage to the cells.To conduct the heated experiments, a stage top incubator with a slidable lid and glass plates were used  with a digital temperature controller unit . As only one microscope slide can fit inside the incubator, a slide with multiple wells (Ibidi 18 well µ-slide) was used. 30 µL of each sample mixture was transferred to individual wells on the slide. The slide was immediately placed inside the stage top incubator which had been pre-heated to 37 °C. At this point the temperature of the objective was set to 37 °C using an attached objective heater, to limit heat loss through contact with the objective.For all hemolysis experiments, five images from different areas of the slide were taken, per measurement, to reduce variation due to any uneven distribution of cells on the slide. The number of ghost cells were counted by eye and the number of viable cells were counted using a Python script. The percentage of ghost cells were calculated, averaged, and plotted against time to create the lysis curves.G, was calculated as I is the current and V the voltage.A 1,2-diphytanoyl-sn-glycero-3-phosphocholine (DPhPC) lipid bilayer was formed by opposing two lipid monolayers, as described previously , over a Data were analysed using the GraphPad Prism software v9 . Error bars are the standard error of the means (±S.E.M.) unless otherwise stated.


The clade 2.3.4.4b H5N8 avian influenza viruses (AIVs) have caused the loss of more than 33 million domestic poultry worldwide since January 2020. Novel H5N6 reassortants with hemagglutinin (HA) from clade 2.3.4.4b H5N8 AIVs are responsible for multiple human infections in China. Therefore, we conducted an epidemiological survey on waterfowl farms in Sichuan and Guangxi provinces and performed a comprehensive spatiotemporal analysis of H5N6 AIVs in China. At the nucleotide level, the H5N6 AIVs isolated in the present study exhibited high homology with the H5N6 AIVs that caused human infections. Demographic history indicates that clade 2.3.4.4b seemingly replaced clade 2.3.4.4h to become China’s predominant H5N6 AIV clade. Based on genomic diversity, we classified clade 2.3.4.4b H5N6 AIV into ten genotypes (2.3.4.4bG1–G10), of which the 2.3.4.4bG5 and G10 AIVs can cause human infections. Phylogeographic results suggest that Hong Kong and Jiangxi acted as important epicentres for clades 2.3.4.4b and 2.3.4.4h, respectively. Taken together, our study provides critical insight into the evolution and spread of H5N6 AIVs in China, which indicates that the novel 2.3.4.4b reassortants pose challenges for public health and poultry. Novel H5N6 reassortants were reported as one of the dominant AIV subtypes in China, especially in ducks, during 2014–2016 [The genetics and antigens of H5 AIVs, which circulate in wild birds and poultry globally, are diverse . To date014–2016 . The cla014–2016 . H5N8 AI014–2016 ,11. Curr014–2016 ,13. In thttps://www.gisaid.org; accessed on 15 May 2022). Sequences with (a) evidence of lab errors and (b) 100% similarity were discarded. Detailed information on all H5N6 AIVs analysed in this study can be found in Two H5N6 AIVs designated as A/duck/Sichuan/SS1/2021 and A/goose/Guangxi/GG1/2022 were isolated from lung samples of waterfowl farms in Sichuan and Guangxi. The whole genome was amplified using universal primers . All virSequence alignments were constructed for eight segments separately using the MAFFT version 7.149) program . Using M.149 proghttp://tree.bio.ed.ac.uk/software/figtree/; accessed on 15 June 2022).We used the TempEst (version 1.5.3) software to assess the temporal signals by performing root-to-tip regression analysis on viruses from clades 2.3.4.4b and 2.3.4.4h , which sWe used the Bayesian stochastic search variable selection (BSSVS) model with asymmetric substitution to infer the H5N6 AIV spread dynamics from 2017 to May 2022 in China . In ordeMolecular analysis revealed that all H5N6 AIVs in this study possess the same polybasic amino acid motif of -RRKR/GLF- in their HA cleavage site, which is a highly pathogenic avian influenza virus (HPAIV) characteristic . It is nWe found that clades 2.3.4.4c, 2.3.4.4e and 2.3.4.4g contained relatively few viruses . TherefoAdditional phylogenetic analyses of the internal genes of H5N6 AIVs revealed that the PB2, PB1, PA, NP, M and NS genes classified into five , five F, six Fi, four F, five F and fiveTo further reveal H5N6’s evolutionary characteristics, we conducted molecular clock phylogenic analysis and genotype characterisation . Based oUsing a phylogeographic approach, we then estimated the migration pathways of clade 2.3.4.4b and 2.3.4.4h. There were 22 and 35 statistically significant migrations in clades 2.3.4.4b and 2.3.4.4h, respectively . The lonIn summary, this spatiotemporal analysis revealed that clade 2.3.4.4b has seemingly become the predominant H5N6 AIV in China. These viruses are genetically diverse among waterfowl and frequently spread in southern China. Moreover, the novel 2.3.4.4bG5 and 2.3.4.4hG10 reassortants can cause human infection, thus, posing a serious threat to public health. Hence, systematic surveillance of the H5N6 AIVs is critical for early warning and preparation for the next potential pandemic.


Following the paths, these perceptional variables  showed considerable positive impacts on the uptake of genetic testing (standardized β (95% CIs): 0.25 , 0.28  and 0.12 , respectively). Pathways involving attitudinal and psychosocial factors showed much smaller or insignificant effects on the uptake of genetic testing. Our study brings several novel perspectives to the behavior model and may underpin certain issues regarding cancer risk genetic testing.Our study aimed to identify pathways from the source of information to the uptake of cancer genetic testing, with consideration of intermediate variables including perceptional, attitudinal and psychosocial factors. We used the Health Information National Trends Survey (2020 database) and constructed a structural equation model for pathway analysis (using SPSS version 24). Variables for socio-demographic, lifestyle and health information were also collected and used for confounding adjustment. A total of 2941 participants were analyzed  had undertaken genetic testing for cancer risk previously). Our pathway analysis found that only information from particular sources  had positive and significant effects on people’s perceptions of cancer regarding its prevention, detection and treatment (standardized β range, 0.15–0.31, all  According to the International Agency for Research on Cancer, cancer ranks as the second largest cause of premature mortality worldwide, and in 2020 alone it cost approximately 10 million lives ,4,5,6. EWhen introducing genetic testing into healthcare practice, the understanding of the relevant knowledge by the public, as well as psychosocial and attitudinal responses, are the driving forces for its adoption and uptake ,27,28. UPrevious research suggested information exposure to media coverage could shape the public’s perception on genetic testing . AdvertiPrevious studies investigated several individual associations or pathways regarding the relationship between intention and uptake of genetic testing with their predictor factors, such as attitude and perception, psychological characteristics, and information sources ,42,45,46We hypothesize that information from particular media coverage would affect people’s perception of genetic testing. Together with other attitudinal and psychosocial factors, this would influence the uptake of genetic testing for high-risk cancer assessment. In this paper, we aim to use structural equation modelling (SEM) to explore the pathways from media sources to perceptional variables, and subsequently from perceptional, attitudinal and psychosocial variables to the uptake of high-risk cancer genetic testing. We believe the findings from our research would address certain issues regarding the uptake of genetic testing for cancer risks.https://hints.cancer.gov/, accessed on 18 November 2022). The surveys target non-institutionalized adults aged 18 and above. They are intended as a comprehensive assessment of the access and use of health information, as well as the public’s attitudes about cancer in terms of the following aspects: risk perception, vital prevention, early detection, diagnosis, and treatment. We used data from the Health Information National Trends Survey , which was conducted between February and June 2020. The HINTS project is hosted by the National Cancer Institute (NCI), and has actively been collecting surveys from nationally representative samples in the USA since 2003 , was a result of the selection procedure illustrated in Variables  used in this study for the conceptual planning and pathway construction are described in The average proportion of missing data among studied variables was 4.7%. We employed the R package ‘rpart’ , a decision-tree based method, to impute those missing values on media exposure, perceptional variables, attitudinal variables, psychosocial factors, socio-demographics , and lifestyle .p-values. The 95% confidence intervals (95% CIs) for all parameters were calculated using the bootstrapping method. Standardized regression coefficients (β) were reported, obtained by using data after standardization. Data standardization was calculated by first subtracting the mean of a variable from its raw value and then dividing it by its standard deviation.We used Fisher’s Exact test to initially select the variables for media exposure and perception, which were significantly different between those who had undergone genetic testing and who had not. We also screened the socio-demographic variables and health indicators using a similar method and selected statistically significant variables for confounding adjustment. We then constructed SEM for pathway analysis. SEM is a multivariate statistical framework used to model complex relationships between directly and indirectly observed (latent) variables. The model-fitting was performed by IBM SPSS (version 24), which works with a combination of multiple single SEMs to implement pathway analysis. We used single headed arrows to build pathways from influential to affected variables. The conceptual pathways between the studied variables are exhibited in p-value of 0.05, two-tailed, was set as the threshold for statistical significance. Statistical analyses were conducted in R if not mentioned elsewhere.A More than half of the study participants were non-Hispanic white (68.5%) and female (59.7%). The median age was 58 years (interquartile range 42–68 years). A summary of collected variables in socio-demographics, lifestyle factors, and health information is provided in p < 0.01) and genetic counsellors  was positively associated with the uptake of genetic testing  and internet (49.1%) were listed as the top two sources of information, followed by papers (newspapers 15.2% and magazines 17.8%) and radio (16.4%) . Social  testing . As the With regards to the perceived importance of genetic information, the majority of participants approved of the importance for cancer prevention , detection (85.7%), and treatment (79.5%). Participants who had a higher perceived importance of genetic information for cancer prevention, detection, and treatment, were more likely to report an uptake of genetic testing than those who had a lower perceived importance .This study has reported the public’s perspectives on the genetic testing for cancer risks. One particular novelty is that we have integrated information sources into the behavioral model for predicting the uptake of cancer risk genetic testing. This study advocates for a better understanding of the factors associated with the uptake of cancer risk genetic testing using a pathway analysis, which may underpin certain issues on the topic and may encourage a better atmosphere for public participation in this healthcare practice.Information about cancer risk genetic testing from particular media types, as the original source of knowledge, was studied in our pathway analysis. This ‘media-perception-uptake’ pathway model should be considered as a meaningful contribution to the existing behavior models on genetic testing engagement, since our results show that only information expressed by certain sources have a positive impact. Healthcare providers and genetic counsellors were the only two sources of information that positively influenced individuals’ perceptions on cancer genetic testing in our analysis. However, the proportion of study participants receiving information about genetic testing from these two sources were small. In particular, only about 4% of participants received information from genetic counsellors . It is tDirect to consumer genetic testing (DCGT) has become an emerging service that allows individuals to have their genetic background examined without having to consult an expert . HoweverOur results also showed that television was the largest source of information for genetic testing 63%, . HoweverIn the framework of pathway analysis, our results suggest that the studied attitudinal variables  are not directly associated with the uptake of cancer risk genetic testing. Instead, some variables (including ‘everything causes cancer’ and ‘behavior change’) are found to be associated with psychosocial variables, although some psychosocial variables are also found to be associated with the uptake of testing. This observation is generally consistent with the findings of a previous study which also used the HINTS database (of 2017) . In a yoResults in our analysis suggest that some psychosocial variables  are significantly involved in our pathway model influencing the uptake of genetic testing. However, a previous study, which also used the HINTS database but in a different cycle (2017), concluded that psychosocial variables were not associated with uptake . In our This study has several limitations. It is a survey-based study, therefore information used for analysis is self-reported and the data is cross-sectional in nature. The HINTS 2020 is adapted to perform this pathway analysis, so the analysis is limited to the scale and concept of the variables collected in the survey. HINTS aims to collect nationally representative samples within the USA. However, its response rate is relatively low, therefore selection bias may exist. We constructed a behavior model to demonstrate the ‘media-perception-uptake’ pathway for the general population, but not all genetic testing services should be recommended for such people. Analysis for those recognized as potentially high-risk individuals from initial screening  is required.In conclusion, using the HINTS 2020 database, our study demonstrated the effective pathways regarding the factors associated with the uptake of cancer genetic testing, while estimating the size of these effects (direct or indirect) from certain media exposures, perceptional variables, attitudinal variables, and psychosocial variables on the testing uptake. We suggest that information about genetic testing from only professional sources  would positively influence individuals’ perceptions on cancer genetic testing. Our pathway model also suggests that the perceived importance of genetic information on preventing, detecting, and treating cancer is the direct and strongest predictor for the uptake of genetic testing. Our study brings several novel perspectives to the behavior model and may underpin certain issues regarding the genetic testing for cancer risks. To confirm the results, studies with larger scales or more representative populations must be conducted, preferably in other countries besides the USA.


Callinectes sapidus), we obtained 22 complete and 96 partial genomic sequences for CsRV1 strains from the US Atlantic coast, Gulf of Mexico, Caribbean Sea, and the Atlantic coast of South America. Phylogenetic analyses of CsRV1 genomes revealed that virus genotypes were divided into four major genogroups consistent with their host geographic origins. However, some CsRV1 sequences from the US mid-Atlantic shared high genetic similarity with the Gulf of Mexico genotypes, suggesting potential human-mediated movement of CsRV1 between the US mid-Atlantic and Gulf coasts. This study advances our understanding of how climate, coastal geography, host life history, and human activity drive patterns of genetic structure and diversity of viruses in marine animals and contributes to the capacity to infer broadscale host population connectivity in marine ecosystems from virus population genetic data.The movement of viruses in aquatic systems is rarely studied over large geographic scales. Oceanic currents, host migration, latitude-based variation in climate, and resulting changes in host life history are all potential drivers of virus connectivity, adaptation, and genetic structure. To expand our understanding of the genetic diversity of Callinectes sapidus reovirus 1 (CsRV1) across a broad spatial and host life history range of its blue crab host ( Diadema antillarum . Ea. Eahttp:Quality trimming and the removal of barcode sequences from raw reads were performed in CLC Genomics Workbench 9.5.2 . CsRV1 sequences were identified by assembling reads against the published CsRV1 reference genome   in CLC GEriocheir sinensis reovirus strain WX_2012 (SsRV WX_2012) [Best-fit models for nucleotide substitutions were determined with Bayesian Information Criterion (BIC) using ModelFinder implemented in IQ-Tree 1.5.5 . They weWX_2012)  as the oWX_2012) .Discriminant analysis of principal components (DAPC) was carried out in the adegenet 1.3–1 package for R studio (Jombart and Ahmed 2011), to infer the spatial genetic structure of CsRV1 and estimate membership probabilities of each viral sequence. For spatial genetic structure, the number of groups was pre-defined according to the geographic origins of CsRV1 samples: north Atlantic (N. Atl), mid-Atlantic (M. Atl), south Atlantic (S. Atl), GoM, CAR, and SAmer. The number of retained principal components (PCs) used for DAPC was selected by the a-score optimization method. The number of genetic clusters in the dataset (not grouping by sampling location) was also determined via K-means clustering in the ‘factoextra’ package , compariSequence alignments of both nucleotide and amino acid sequences were performed with MAFFT. Population diversity parameters, i.e., haplotype (H), haplotype diversity (Hd), nucleotide diversity (π), number of polymorphic sites (s), nucleotide differences (k), and average mutation rates (θ) were calculated using DnaSP v. 6.12.03 . The ratNeutrality indices of CsRV1 populations were evaluated using the statistical tests Tajima’s D , Fu and ST statistics implemented in Arlequin v. 3.5.2.2. The relationship between genetic distance (FST) and geographic distance was tested with a Mantel test with the package ade4 installed in R studio [Genetic subdivision of CsRV1 between sampling years, between regions, subregions, and locations, was assessed with the pairwise FR studio . GeograpIn total, 22 complete or near-complete genomes and 96 seg9 ORF sequences of CsRV1 were collected from 15 geographic locations along the US Atlantic coast (USAC), the Gulf of Mexico (GoM), the Caribbean (CAR), and South America (SAmer) between 2006 and 2021 . The conComparison of concatenated genomes translated into coding regions (6614 AA) B showed Comparison of seg9 nucleotide and amino acid sequences among CsRV1 strains also revealed higher sequence identities within populations than between geographic populations of USAC, GoM, CAR, and SAmer. CsRV1 strains collected from GoM and CAR had overall lower within-population sequence similarities compared to viral strains within USAC and SAmer populations .The ML phylogenetic trees were reconstructed using the data for 23 concatenated genome sequences A and 66 The ML phylogenetic tree constructed from 23 concatenated genome sequences of CsRV1 showed a similar tree topology to Group I of USAC genotypes and Group III of SAmer genotypes A. Still,ML phylogenetic trees based on amino acid translations of seg9, and the concatenated genome translations, showed the same tree topology as the nucleotide sequences did, revealing four groups. Group I consisted of genotypes from the USAC and genotypes from TX and LA. Group II included genotypes collected from the GoM (TX and FLK). Group III included genotypes from SAmer (BR and UR), and Group IV included genotypes that originated from the CAR .A ML phylogenetic tree was constructed for each genome segment. A comparison of the topology of the tree for each segment showed that positions of locations in Groups I and III were similar for seg3 and seg4, and seg7, seg8, and seg9, which was similar to the tree of the concatenated whole genome sequences . For segPopulation genetic parameters were calculated for all 12 segments. Based on the seg9 sequences, the nucleotide diversity was higher in the GoM and CAR  compared to the USAC and SAmer  . More syNeutrality tests on genomic segments of CsRV1 were estimated using three statistical methods  . Test vaST was calculated based on seg9 sequences. Pairwise comparisons between USAC and SAmer produced the largest estimates of genetic differentiation (FST = 0.69), which indicates little to no gene flow between the two continents  was much lower than between the GoM and CAR (=0.51) or the GoM and SAmer (=0.63), suggesting potential high CsRV1 gene flow between the GoM and USAC within the US, but very limited gene flow between the GoM and CAR or SAmer. CAR showed a similarly high genetic differentiation from both the USAC (FST = 0.66) and the SAmer (FST = 0.62).To test the genetic differentiation of CsRV1 among geographic regions, Fntinents . The FSTST (0.23), indicating more gene flow between the two regions. A larger FST was detected between S. Atl and other subregions, especially the N. Atl (FST = 0.57), indicating a distinct genetic composition of S. Atl CsRV1 compared to other subregions in the US. Incongruously, the GoM showed the lowest genetic differentiation (FST = 0.15) with M. Atl, but the highest genetic differentiation with S. Atl (FST = 0.35).Genetic differentiation was also investigated on a finer geographic scale between subregions within the US: N. Atl, M. Atl, S. Atl, and the GoM. Pairwise comparisons between the N. Atl and M. Atl showed lower FST estimates of 0.17, but the FST estimates between BR/UY and locations of the USAC were higher than 0.72 (ST with MD (0.34), suggesting a high gene flow between the two locations. TX showed lower FST estimates with the northern locations  within the subregions of N. Atl and M. Atl, but much higher FST with FL and LA (ST estimates between locations showed a significantly positive association between the genetic distance (FST) and the geographic distance (km) for all the sampling sites (p < 0.01), but not when considering the US sites only (p > 0.1)  . When thp < 0.01, the FST results based on seg1, seg8, and seg9 all allowed us to refute the null hypothesis of non-differentiation of CsRV1 between these geographic locations. AMOVA also suggested that there was no significant genetic differentiation of CsRV1 among populations within the US or within the SAmer populations. A higher percentage of variation was explained by the within-population components rather than among populations within each region.The AMOVA test on CsRV1 across the regions of the US (USAC & GoM), CAR, and SAmer revealed greater variance among populations than within the populations . With AMn = 6) as the pre-defined clusters. All the CAR and SAmer genotypes were placed into distinct groups, and the SAmer showed the largest distance relative to other groups. Within the US, the S. Atl genotypes (exclusively collected from FL) grouped far away from the N. Atl and M. Atl populations. The N. Atl, M. Atl, and GoM populations appeared to overlap substantially with each other. Consistently, the membership probabilities of each genotype show two unique groups of the CAR and SAmer genotypes  of PCA and five discriminant eigenvalues were retained for DAPC analyses with seg9 sequences based on the a-spline optimization results. K-means cluster analysis revealed that the most likely number of clusters (K) in the data was 4–5 based on a consensus of three metrics used to infer the most probable K . The scatter plot in enotypes B. US N. enotypes B.Understanding the connectivity of marine crustacean populations and how their pathogens spread over large ocean distances remain fundamental questions in marine ecology. RNA viruses are particularly valuable models for the study of these processes due to their potential for rapid evolution and high genetic variability . In thisST) among CsRV1 strains showed significant positive correlations with the geographic distance over the entire sampled range (7800 km). Population genetic analyses revealed high genetic differentiation (FST) between the USAC and SAmer, suggesting very limited gene flow for CsRV1 between the two continents which is a trend consistent with that of the host populations  confirmed the substantial genetic differentiation between CsRV1 from CAR and other geographic locations.The phylogenetic lineages of CsRV1 were consistent with their host origins at the hemispheric scale of its distributions. CsRV1 genotypes can be divided into four genogroups: (I) US Atlantic coast (USAC), (II) Gulf of Mexico (GoM), (III) Caribbean Sea (CAR), and (IV) South America (SAmer). Genetic differentiation . ,48. ST) s , suggesting high gene flow among CsRV1 populations located along a contiguous coastline. Genetic differentiation was also absent for CsRV1 between US north Atlantic and mid-Atlantic populations, and between Brazilian and Uruguayan populations. Ocean currents are the predominant factors enhancing larvae dispersal of blue crab, which consequently increases the population connectivity of crab hosts ,82,83,84Since vertical transmission has not been demonstrated for CsRV1, and the virus is unlikely to be carried and transported by blue crab larvae, the low genetic differentiation within these geographic regions suggests that the virus is carried by juvenile and adult blue crabs, which can travel tens of km along the near shore  and offST = 0.35), compared to the GoM and M. Atl (FST = 0.15), suggests that CsRV1 genotypes more likely moved directly between the GoM and M. Atl in a small number of individuals, rather than through the S.Atl. It is highly unlikely that CsRV1 genotypes moved from the GoM to the M. Atl region by coastal crab migration without leaving genetic evidence in the S. Atl. Similarly, it is difficult to explain these FST differences as a result of an incomplete lineage sorting from a past split.The presence of closely related virus genotypes in widely separate geographic regions may indicate high connectivity between them, or could be the result of an incomplete lineage sorting after an ancestral split. The shared CsRV1 genotypes present in both USAC and GoM populations suggest that the GoM or USAC could serve as a potential CsRV1 dispersion point from one region to the other. Pathogen spread can be driven by natural processes of host movement or by human-mediated transport . Long-diA plausible explanation for the similar CsRV1 genotypes is that they were received via the importation of infected blue crabs from other regions. The similarity of CsRV1 genotypes in the GoM and M. Atl is entirely consistent with the long-distance movement of CsRV1 mediated by interstate trucking of virus-infected crabs that are being seasonally traded between the M. Atl and GoM. Confidential communications with crab fishermen, soft crab producers, and seafood dealers in Maryland and Louisiana reveal that the scale of interstate transport is large yet un-measured. In both winter and summer months, blue crabs are shipped to the M. Atl regions because of the high consumer demand. Pre-molt blue crabs (a.k.a. peelers) also travel among states in the US as the ratio of peelers and soft-shell crab production capacity shifts between the regions. The stresses of long-distance transportation and the process of soft-shell crab production can concentrate virus-infected crabs. Moreover, it is common for soft crab producers and dealers to dispose of dead imported crabs in local estuaries. Therefore, human-mediated dispersal of CsRV1 during the transportation of blue crabs is a more parsimonious explanation for the high genetic similarity of CsRV1 between these two regions. Similar lessons have been learned from the global spread of OsHV-1 and OsHV-1 µ-var, which was linked to the human-mediated movement of Pacific oysters and insufficient biosecurity practices ,91.Host life history across a variable environmental range has the potential to affect pathogen genetic diversity and genetic structures . Blue crIn addition, behaviors unique to blue crabs in temperate regions, such as seasonal migrations for winter dormancy and mating activity, may increase contact between crabs from distant locations and therefore decrease the genetic differences of CsRV1 genotypes among locations. Previous work revealed that CsRV1 prevalence was significantly correlated with temperature and seasons . The lowAcropora palmata) and sponge (Ircinia campana) larvae in the Caribbean, limited by geographic distances among habitats [Besides the impact of latitude and host biology, geographic factors also likely contribute to the evolutionary dynamics of the CsRV1. Studies revealed the restricted population connectivity and short-distance dispersal of coral (habitats ,94. SimiAll segments of the CsRV1 genome appear to be under strong purifying selection, to different degrees. Observations of purifying selection in genomic segments have been reported for other reoviruses, such as the bluetongue virus . Tajima’The analysis of each individual segment in a multi-segmented genome can provide information on the evolutionary history of that specific segment. Genotypes of NC_ 2019#3 and FL_2019#2 grouped distinctly from other US Atlantic coast strains in the concatenated genome analysis primarily due to a relatively high number of nucleotide differences in seg3, seg5, seg8, and seg10, but the uniqueness of these genetic differences was not reflected in the analysis of other segments. Reassortment or recombination between divergent sequence variants can generate new viral genotypes and accelerate the evolution of segmented RNA viruses ,98. Due This study revealed patterns of genetic structure and genetic diversity of CsRV1 at a trans-hemispheric scale, through the lens of how evolutionary dynamics of CsRV1 may be influenced by interactions between the virus, the host life history, and latitude. Overall, this study sheds light on the factors controlling the spread and connectivity of viral pathogens in marine systems, examining the effect of geographic distance, possible oceanographic barriers and ocean currents, host migration and life history, and potential human-mediated movement of marine animals. Implicit in our study is the idea that for animals with complex life histories, there may not be perfect congruence between pathogen population genetic structure and that of its host. To fully address this question, a corresponding high-resolution study of blue crab genotypes in the same geographic range is being completed. The results show that analyzing virus genomes can inform research on host population connectivity and movement in the ocean with, potentially, higher resolution due to the higher mutation rate of the virus. However, attention must be paid to human-mediated processes, such as the anthropogenetic movement of viral genotypes via interstate transport of infected crabs, to accurately interpret findings. Our results highlight possible risks in moving live marine animals between populations and suggest that fishery resource management plans should include pathogen monitoring and biosecurity elements to limit the unintentional transport of pathogens.


Genetic differentiation among breeds accounted for 18% of the total genetic variability (AMOVA). Bayesian structure analysis (STRUCTURE) indicated that the four distinct genetic clusters obtained corresponded to the four breeds studied. The genetic Reynolds distances (Ɵw) showed a close relationship between PL and PLW breeds and the most distant for DUR and PUL pigs. The genetic differentiation values (FST) were lower between PL and PLW and higher between PUL and DUR. The principal coordinate analysis (PCoA) supported the classification of the populations into four clusters.Swine DNA profiling is highly important for animal identification and parentage verification and also increasingly important for meat traceability. This work aimed to analyze the genetic structure and genetic diversity in selected Polish pig breeds. The study used a set of 14 microsatellite (STR) markers recommended by ISAG for parentage verification in the native Puławska pig  and three commercial pig breeds: Polish Large White (PLW,  Maintaining high-quality meat production and the preservation of food safety are directly related to the biodiversity and individual and breed identification of animals. Swine DNA profiling is highly important for animal identification, parentage verification and, more recently, meat traceability ,2,3. Porhttps://www.polsus.pl/index.php/en/pig-breeding, accessed on 29 November 2022). The aims of this study were to assess the level of genetic diversity and determine the population structure of the native Puławska pig and three commercial pig breeds, PL, PLW and DUR, by using a set of 14 STRs. The 14 STRs are recommended for individual pig identification and parentage verification. No studies present the assessment of the polymorphisms of STR markers recommended for the identification of pigs in the Polish population. The study by Szmatola et al. [The National Breeding Program includes the following breeds: Puławska pig (PUL), Polish Large White (PLW), Polish Landrace (PL) and foreign breeds Duroc (DU), Hampshire and Pietrain. In Poland, these breeds are used for crossbreeding and fattening in pig production and are some of the most economically important (n = 85) and three selected commercial breeds: Polish Large White , Polish Landrace  and Duroc .Blood samples were collected from pigs undergoing routine parentage testing at NRIAP. A total of 338 pigs were studied, including Puławska pigs , following the manufacturer’s protocol. Extracted DNA was quantified using a NanoDrop 2000 spectrophotometer . In the analysis, we selected 14 loci from the recommended ISAG main panel of 15 markers for the identification of individuals and parentage testing in the pig: S0090, S0101, S0155, S0227, S0228, S0355, S0386, SW24, SW240, SW72, SW857, SW911, SW936 and SW951. The markers and used primer sequences are presented by Radko et al. ,21.® Thermal Cycler amplifier was used for the PCR reaction  with the following thermal profile: 5 min initial denaturation at 95 °C, followed by 28 cycles of denaturation at 95 °C for 30 s, annealing at 57 °C for 90 s, elongation of primers at 72 °C for 30 s and final elongation of primers at 60 °C for 30 min. The PCR products were analyzed using an ABI 3500xl capillary sequencer . The amplified DNA fragments were subjected to electrophoresis in 7% denaturing POP-7 polyacrylamide gel in the presence of a size standard of 500 LIZ (Thermo Fisher Scientific) and a reference sample with a known DNA profile for allele standardization. The results of the electrophoretic separation were analyzed using the GeneMapper® Software 4.0 .The one-multiplex reaction containing the 14 STR loci was amplified using the Type-It Microsatellite PCR Kit  reagents and fluorescently labeled primers. The reaction mixtures, with a final reagent volume of 12.5 μL, contained 50 ng DNA. The VeritiAnalysis of molecular variance and genetic differentiation.FST) across populations were performed using the GenAlEx ver. 6.51 software [Analysis of molecular variance (AMOVA) and pairwise estimates of genetic differentiation .Genetic distance was analyzed using pairwise estimates of genetic differentiation—FST and Reynolds distance—Ɵw . The indThe population relationships based on principal coordinate analysis (PCoA) were obtained using the GenAlEx ver. 6.51 software . The development of reliable molecular tools for genetically distinguishing between two breeds of species and identifying breed components in food products has become increasingly important due to the increasing demand for improved quality control. For the purpose of the identification of animals and products, microsatellites (STRs) are widely used as molecular markers. STR markers used in this context have to present high diversity. The genetic diversity of microsatellite loci is determined based on genetic parameters such as the PIC index and heterozygosity. These parameter values show the usefulness of markers for further research, including individual identification and genetic population diversity. Previous studies have shown that all 14 STR markers, recommended by ISAG for pig identification, were polymorphic in the sampled groups . Based oThe F-statistic is commonly chosen for studying population structures. It is frequently applied to decompose the genetic variance into within-individual, within-population and among-population components . The anaAMOVA is an important element of molecular analysis that allows the statistical inference of genetic variation among and within populations. In our study, the variance analysis (AMOVA) was performed using all 14 polymorphic STRs and revealed that variation among individuals was greater than the variation in the inter-population.p < 0.001), while the total variability was 82%. Details of AMOVA results are presented in The average genetic differentiation between the breeds was 18% . The pairwise FST values between breeds varied from 0.106 (between PL and PLW) to 0.283 (between PUL and DUR). Similarly, genetic distance was the greatest between PUL and DUR (Ɵw = 0.430) and the smallest between PL and PLW (Ɵw = 0.109)  . ST and the Reynolds distances among the breeds showed that the national PL and PLW breeds formed one cluster, while Duroc was relatively distant from the other breeds. This indicated that Poland’s pig breeds are separated by the largest genetic distance from the foreign Duroc breed. This reflects the fact that Duroc originated in the USA by the crossing of Red Guinea pigs and Iberian pigs with the Berkshire breed and was introduced to Poland relatively recently—in the 1970s. The pairwise FST and Ɵw values. This was further supported by the results of the principal coordinate analysis (PCoA). The obtained results of PCoA analysis show four pig clusters—Duroc (DUR), Puławska (PUL) and the Polish Landrace (PL) and Polish Large White (PLW) together (The close genetic relationship between the PL and PLW breeds was proven by STRUCTURE analysis with K = 3 , the paitogether . The PL Nowadays, single-nucleotide polymorphism markers are increasingly used for biodiversity studies and the identification and parentage control of livestock, including pigs ,34,35,36The present study analyzed the genetic differentiation of selected pig breeds, Polish Large White, Polish Landrace, Puławska pigs and Duroc, and the possibility of using DNA tests for pig breed prediction.The analysis of the genetic structure of the pig populations based on 14 STRs showed a clear division of the population into four groups, representing the four selected breeds for study. Our study demonstrates that a panel of microsatellite markers recommended by ISAG for the individual identification of pigs also may be useful for pig breed prediction and, in the future, for meat traceability. It is especially important for the population of native or local pigs, such as the Puławska breed, which can provide meat that is both high in quality and functional.The presented work can be the first step to developing a system to determine whether meat comes from a pig of the declared breed and whether the meat was produced consistently with the declaration on the packaging.


Aedes koreicus  is a recent invader on the European continent that was introduced to several new places since its first detection in 2008. Compared to other exotic Aedes mosquitoes with public health significance that invaded Europe during the last decades, this species’ biology, behavior, and dispersal patterns were poorly investigated to date.The mosquito Ae. koreicus from the European region. The complete genome of Ae. koreicus is 879 Mb. COI haplotype analyses identified five major groups  and revealed a large-scale dispersal pattern between European Ae. koreicus populations. Continuous admixture of populations from Belgium, Italy, and Hungary was highlighted, additionally, haplotype diversity and clustering indicate a separation of German sequences from other populations, pointing to an independent introduction of Ae. koreicus to Europe. Finally, a genetic expansion signal was identified, suggesting the species might be present in more locations than currently detected.To understand the species’ population relationships and dispersal patterns within Europe, a fragment of the cytochrome oxidase I (COI or COX1) gene was sequenced from 130 mosquitoes, collected from five countries where the species has been introduced and/or established. Oxford Nanopore and Illumina sequencing techniques were combined to generate the first complete nuclear and mitochondrial genomic sequences of Our results highlight the importance of genetic research of invasive mosquitoes to understand general dispersal patterns, reveal main dispersal routes and form the baseline of future mitigation actions. The first complete genomic sequence also provides a significant leap in the general understanding of this species, opening the possibility for future genome-related studies, such as the detection of ‘Single Nucleotide Polymorphism’ markers. Considering its public health importance, it is crucial to further investigate the species’ population genetic dynamic, including a larger sampling and additional genomic markers. Aedes have been introduced and have established during the last decades, generating a serious nuisance for people, representing a public health threat due to their potential vector competence for exotic and/or endemic pathogens [Aedes albopictus  and the Asian bush mosquito Aedes japonicus japonicus , little is known about another invader, Aedes koreicus . This Aedes Invasive Mosquitoes (AIM) has been proposed as an additional global invasive mosquito with good adaptation capability [Ae. albopictus, it can tolerate lower temperatures, with faster development and being able to become more abundant than the tiger mosquito during the colder months of the breeding season [Aedes koreicus is also better adapted to urban environments than the forest-dwelling species Ae. j. japonicus [Ae. koreicus might continue to expand across the continent.The introduction of alien species to new territories and biological invasions represent an increasing problem in our globalized world. The process has increased with modern trade and travel, which facilitates and intensifies the introduction of invasive alien species . Among oathogens  and a pog season . Aedes kaponicus . These cAedes koreicus was first detected out of its native area in Belgium in 2008, in an industrial area in Maasmechelen, province of Limburg, where it is established and overwintering [Ae. japonicus specimens collected in Slovenia confirmed the introduction of Ae. koreicus into the village of Lovrenc na Dravskem Polju, northeast Slovenia in 2013 [Ae. koreicus was found in Baranya county, southwest Hungary [Ae. koreicus was detected in Western Austria [intering . While tintering , where iintering –13. Furtintering , 15, andintering . Meanwhi in 2013 . The spe in 2013 , and a f in 2013 –21. At t Hungary , where a Hungary , but a f Hungary . Recentl Austria , on the  Austria , and in  Austria .Since information is restricted to countries where exotic mosquito surveillance activities are implemented, the above mentioned regions only depict our current knowledge of the species distribution . Beyond Ae. koreicus based on population genetic approaches. To do so, an approximately 1000 base pairs fragment of the cytochrome oxidase I (COI or COX1) gene was examined at a pan-European scale to reveal haplotype diversity and phylogeographic relatedness throughout the known European populations. We also provide the first complete mitochondrial and draft nuclear genome of the species Ae. koreicus by long-read sequencing (Oxford Nanopore) coupled with Illumina sequencing methods.In the present study, we analysed correlations between the European populations of Ae. koreicus within Europe, we analysed a total of 130 mosquito specimens, originating from nine geographically separated populations from five European countries  where the species is established, or was recently introduced and it is expected to become established soon. The mosquitoes were collected within the framework of local or national monitoring programs, from urban settlements, including parks, gardens, industrial areas, and cemeteries between 2008 and 2020. Eggs were sampled using oviposition traps, larvae originated from water bodies, and adults were collected either with Frommer Updraft Gravid  or BG-Sentinel traps  in combination with CO2 , 0.2 μl dNTP mix , 14.7 μl nuclease-free water, and used 2 μl of the DNA extract as a template. The PCR protocol included 5 cycles with the following parameters: 30 sec at 94°C, 30 sec at 45°C, and 1 min at 72°C, followed by 35 cycles of denaturation for 30 sec at 94°C, annealing for 1 min at 51°C, and 1 min of elongation at 72°C, ending with a final extension step at 72°C for 10 minutes. PCR products were purified using NEBMonarch PCR and DNA Clean-up Kit , following the manufacturer’s instructions. The sequencing was processed by Eurofins Genomics Custom DNA Sequencing service .Nucleic acid from homogenized mosquitoes was extracted individually, using the NucleoSpin DNA Insect Kit , following the manufacturer’s instructions. The mitochondrial COI region was amplified using the primer combination LCO1490 and UEA8 (targeting a ~1000 bp long fragment) , 30, andTo characterize the dispersal routes within Europe a discrete phylogeographic analysis was implemented using BEAST v1.10.4, under the HKY substitution model, with a strict molecular clock and constant population size parameters. Substitution model selection was performed using the IQ-TREE web server tool beforehand . To effeFor whole genome sequencing efforts, the DNA of a laboratory-reared female mosquito was used. The mosquito larva for laboratory rearing was collected in June 2019, Pécs, Hungary. Nucleic acid extraction was performed with the NucleoSpin DNA Insect Kit , following the manufacturer’s instructions. A final concentration of 75.8 ng/μl nucleic acid eluate was obtained and used as a template for the Nanopore library preparation. To this end, the genomic DNA was sheared using g-Tube  to reach 8 Kbp average fragment size. For the library preparation 1.6 μg sheared genomic DNA was used . The DNA was end-prepped with the NEBNext FFPE Repair and Ultra II End Prep Kit and purified using Agencourt AMPure XP . Then the adapter ligation was performed using NEBNext Quick T4 DNA Ligase. Finally, the adapted library was purified using Agencourt AMPure and the final concentration was determined using the Qubit 3.0 fluorometer. The library was mixed with ONT running buffer and loading beads, and primed on a FLO-MIN106 9.4.1 SpotON Flow Cell attached to the MinION device (running time: 96 hours). As a result of this sequencing protocol, we obtain the mitochondrial sequence data along with nuclear genomic sequence data.A final concentration of 75.8 ng/μl nucleic acid eluate from the same laboratory-reared female mosquito was used for the Illumina sequencing library preparation. The latter was prepared using NEBNext Ultra II FS DNA Library Prep Kit for Illumina . Briefly, 400 ng genomic DNA was fragmented, the end was prepped and the adapter was ligated. Then magnetic beads size selection was performed to select 250–300 bp insert size fragments. Finally, the library was amplified according to the manufacturer’s instructions. The quality of the library was checked on a 4200 TapeSation System using D1000 Screen Tape, the quantity was measured on a Qubit 3.0 fluorometer. Illumina sequencing was performed on a NextSeq550 instrument  with a 2x151 paired-end run configuration (Illumina PE). As a result of this sequencing protocol, we obtain the mitochondrial sequence data along with nuclear genomic sequence data.Obtained reads from both high-throughput sequencing techniques were used to create a draft genome assembly. Beforehand, reads were filtered as follow. Porechop  with defNanopore reads were assembled into contigs by Canu  with defAe. koreicus within Europe using genetic approaches. Although phylogenetic investigations of the invasive populations of Ae. albopictus [Ae. japonicus [Ae. koreicus only morphological characterizations are available from Belgium [Ae. koreicus mosquitoes that were collected in different countries in Europe (GenBank accessions: OK668709—OK668837 and JF430393 (S1 Table)). A total of 31 different haplotypes were identified from specimens collected in nine geographically isolated populations of five countries. This is reflecting high levels of genetic diversity between and within the examined regions. Among them, five haplotypes  are present in higher relative frequencies (i.e. relative to the sample set), while all the other identified haplotypes refer to single samples  . The cur in 2008 . It can Ae. albopictus in the north-eastern part of Italy in 1991, several local surveillance and control programs were implemented in the region. Non-colonized (i.e. tiger mosquito-free) areas were also monitored. However, Ae. koreicus was first detected in Italy in 2011 [On the other hand, since the discovery of the invasive Ae. koreicus population seems to have been established in a short period but is restricted to the city of Pécs [Ae. koreicus originating from mainland Korea [Ae. koreicus from Jeju-do Island have a fifth hind tarsomere with an incomplete pale basal band which is not the case for the specimens from the mainland [We revealed the presence of a diverse population in Hungary, which might be explained by common exchange events with the populations in other countries. Since this  of Pécs , the econd Korea . All othmainland . These pAe. koreicus [Ae. koreicus across Europe, as seen in the case of other invasive mosquitoes, e.g. transportation together with specific goods, or with human movements [Based on these results, we hypothesize a silent expansion of the species throughout Europe, with possibly more introduction events than currently identified. Although the routes or directions of the expansion is hard to predict, we pointed to a connectivity between Belgian, Italian and Hungarian populations, and a clear separation of the German population. Considering the yet unverified but hypothesized disease vector potential of koreicus –50, the koreicus . Meanwhiovements , 28.Ae. koreicus mitochondrial genome sequenced from a specimen collected from the Korean Peninsula (accession number: MT093832), the final product was annotated. The length of the generated mitogenome (deposited on GenBank with accession number: MZ460582) is 15,843 bp, due to a three basepair long insertion (AAT) at position 9,961. The nucleotide differences between the mitochondrial sequences isolated from specimens that originate from Korea (native range) and Europe  are indicated in Long-reads obtained with the Oxford Nanopore technology allowed for the construction of the complete mitochondrial and nuclear genomic information, subsequently verified with Illumina short-reads. As a result of combined sequencing methods we were able to retrieve a high-quality mitochondrial genome sequence. Based on the recently published Ae. koreicus genome assembly, with 2,380 (72.45%) and 68 (2.07%) being identified as complete and fragmented respectively . BUSCO analysis showed that 2,448 (74.52%) of 3,285 Diptera BUSCOs were detected in the final ectively . The mapAe. koreicus populations and we revealed multiple dispersal routes for this species. The most frequent geographic dispersal occures along the Belgium-Italy axis. Interestingly there are two different scenarios in Germany and other European countries, based on the population genetic patterns. At this point, we do not know the underlying factors behind the two different situations. To get a clearer picture, more studies are necessary. The first published complete genomic data opens the possibility to better understand the genetic features which may facilitate the successful establishment and survival of the species. Based on our results we suggest three key actions of future investigations for which we provide the baseline data. 1: Enforced and harmonized surveillance of this species with common IMS monitoring activities; 2: Re-analysis of previously collected Ae. japonicus specimens to reveal possible misidentification; 3: Perform large-scale and more detailed genetic analysis with more samples, using other genetic markers, such as Single Nucleotide Polymorphisms.Major introduction pathways of exotic mosquitoes and related pathogens are primarily passive and associated with human activities, as global trade and tourism. Since invasions are driven by multiple interacting factors across global, regional, and local scales, we need to investigate the phenomena from a more complex point of view to understand the mechanisms of IMS dispersal. Our study revealed a mixing of European S1 TableAedes koreicus specimens collected in five European countries between 2008 and 2020 were analyzed. All the sequences are available in GenBank with the referred accession numbers.A total of 130 COI sequences obtained from (PDF)Click here for additional data file.S2 TableThe completeness of the genome assembly was evaluated with the Benchmarking Universal Single-Copy Orthologs  software, using the Diptera lineage dataset. C: complete; S: single; D: duplicated; F: fragment; M: missing.(PDF)Click here for additional data file.S1 Appendix(PDF)Click here for additional data file.S2 Appendix“Freq” indicates the number of samples belong to the given haplotype, name of the “Sequences” refers to the GenBank Accession Numbers listed in the (PDF)Click here for additional data file.S3 Appendix(PDF)Click here for additional data file.


Puccinia striiformis f. sp. tritici (Pst), is a crucial disease for wheat worldwide and constantly threatens wheat production in southwestern and northwestern China, where the environment is a good fit for Pst oversummering and overwintering. However, the underlying genetic dynamics of spring epidemic Pst populations across large areas of continuous planting in the southwestern and northwestern regions are poorly understood. A total of 2,103 Pst isolates were sampled in the spring of 2019 from the two agroecosystems and grouped into three horizontal spatial scales  and two vertical spatial scales that consisted of elevational and geomorphic subpopulations. A total of 776 multilocus genotypes were identified, with the highest genetic diversity found in the northern and Sichuan populations, particularly in the Ningxia and Sichuan Basins, while the lowest genetic diversity was found in the Yunnan and Guizhou populations. Multivariate discriminant analysis of principal components (DAPC) and STRUCTURE (STRUCTURE 2.3.4) analyses revealed variation in the genotypic compositions of the molecular groups on horizontal and vertical dimensions from north to south or vice versa and from low to high or vice versa, respectively. The regional neighbor-joining tree revealed three large spatial structures consisting of the southwestern, the northwestern, and the Xinjiang regions, while the Tibetan population connected the southwestern and northwestern regions. The isolates of the Sichuan Basin were scattered over the four quartiles by principal coordinate analysis, which indicated frequent genotype interchange with others. Greater genetic differentiation was observed between the southwestern and northwestern regions. Linkage equilibrium (P ≥ 0.05) was detected on different spatial scales, suggesting that Pst populations are using sexual reproduction or mixed reproduction  in southwestern and northwestern China.Wheat stripe rust, caused by IMPORTANCE Understanding the epidemiology and population genetics of plant pathogens is crucial to formulate efficient predictions of disease outbreaks and achieve sustainable integrated disease management, especially for pathogens with migratory capability. Here, this study covers the genetic homogeneity and heterogeneity of different geographical Pst populations on broad to fine spatial scales from the key epidemic regions of the two agroecosystems in China, where wheat stripe rust occurs annually. We provide knowledge of the population genetics of Pst and reveal that, for instance, there is greater genetic diversity in northwestern China, there are close genetic relationships between Yunnan and Guizhou and between Gansu-Ningxia and Qinghai, and there are effects of altitude on genetic compositions, etc. All of these findings clarify the genetic relationships and expand the insights into the population dynamics and evolutionary mechanisms of Pst in southwestern and northwestern China, providing a theoretical basis for achieving sustainable control of wheat stripe rust in key epidemic regions. Puccinia striiformis f. sp. tritici (Pst), a causal pathogen of wheat stripe rust (WSR), is distributed globally  and southwestern (SW) areas at high altitudes, while overwintering occurs in SW and central regions where winter temperatures are higher  markers. The objectives of this study were to improve our understanding of (i) the genetic structure and spatial distribution among the various geographical subpopulations, (ii) the genetic diversity and differentiation within and among different spatial subpopulations, and (iii) the potential reproduction mode of Pst in SW and NW China.Nevertheless, there are still many questions to answer. For instance, in spring epidemics, what is the genetic connection and differentiation between the SW and NW patterns , 15, 16.Pst isolates (see Table S1), and the genotype accumulation curves showed that 97% (776 of 800) of the multilocus genotypes (MLGs) could be identified by 11 pairs of markers, indicating that 12 loci were sufficient for further genetic analysis in the present study . The numbers of alleles in the 12 SSR loci ranged from 1.400 (RJN8) to 4.700 (CPS34), with an average of 2.567 alleles per locus. The ranges of observed heterozygosity (oH), expected heterozygosity (eH), and polymorphism information content values across the 12 pairs of markers were from 0.048 to 0.404, 0.041 to 0.424, and 0.070 to 0.701, respectively.All 12 pairs of SSR markers were polymorphic among the Pst isolates from SW and NW China in spring 2019 (see Table S4). Provincial subpopulation abbreviations were as follows (see Table S2): CQ (Chongqing), SC (Sichuan), GZ (Guizhou), YN (Yunnan), XZ (Tibet), NX (Ningxia), GS (Gansu), QH (Qinghai), SX (Shaanxi), and XJ (Xinjiang). Regional subpopulation abbreviations were as follows: SB (Sichuan Basin), SN (northern Sichuan), SSW (southwestern Sichuan), SNW (northwestern Sichuan), GW (western Guizhou), YNE (northeastern Yunnan), YC , YSE (southeastern Yunnan), YW (western Yunnan), ZSE (southeastern Tibet), and SG (Shaanxi and Gansu). Abbreviations for the provincial subpopulations NX, QH, and XJ were the same as those used for the regional subpopulations. Due to fewer than three sampling villages or sites, the isolates from Xinjiang Province were excluded during the genetic diversity analysis at the provincial and regional levels (groups P and R) but included as a part of groups E and L, and the Shaanxi population was excluded at the provincial level but included as a part of groups R, E, and L. At the regional level (group R), the Pst isolates from Qianyang County of Central Shaanxi and Zhuanglang County of Longdong District in Gansu Province were grouped into one subpopulation, abbreviated as SG (Shaanxi and Gansu), based on the close genetic relationships in these regions according to Wang  of QH , SC , and NX  were relatively high; and the gene diversities  in Tibet , SC , CQ , and QH  were relatively high, where the total genetic diversity (genotypic and gene diversity) was lowest in GZ  and YN . The subpopulations of CQ, GZ, and XZ had 100% PL (percentage of polymorphic loci). At the regional level (group R)  , the gengroup R) , the gengroup R) , the gengroup R) , while tOn the horizontal spatial scale, the shared and dominant MLGs mainly occurred in the southwestern subpopulations despite the provincial and regional spatial levels, and the proportions were approximately 50%  and C. TAcross all four spatial groups, the genetic diversity declined from north to south and from high to low altitude, as well as the variation in genotypic structures. In general, the dominant and shared MLGs existed in the southwestern subpopulation, while the private MLGs existed in the northwestern subpopulation, and vertically, the subpopulations with extremely high altitudes possessed the purer, dominant MLGs. All the results indicate that genetic diversity is affected by geography.Pst isolates into different MGs was 2  with a nonparametric model and STRUCTURE 2.3.4 analysis with a Bayesian model displayed similar patterns of genetic structure in genotypic molecular groups (MGs) and revealed that the best number of putative clusters (K) to discriminate the 2,103 Gs was 2 . When K Gs was 2 . The disGs was 2 . When K Furthermore, to depict the horizontal and vertical genetic connectivity over a large area, pie charts were constructed from the different genotypic proportions in groups P, R, E, and L. Due to the similarity of the bar plots generated by the two different cluster methods, we only displayed the results of the nonparametric model . When K Based on Nei’s genetic distance, the 10 provincial subpopulations were classified into four clusters when the distance was 0.05 . The firPrincipal coordinate analysis (PCoA) showed that horizontal and vertical coordinates accounted for 22.92 and 15.35% of the total genetic variance, respectively. At the provincial level , the isoPst isolates among the four spatial groups revealed genetic differentiation between the SW and NW subpopulations (stG = 0.462), followed by that between the SX subpopulation and others, compared to the GZ subpopulation as the maximum (stG = 0.305), secondary compared to the YN subpopulation (stG = 0.23). There were certain degrees of differentiation between the other subpopulations of the northwestern and southwestern regions. For instance, the GS subpopulation compared to the GZ subpopulation (stG = 0.234), the QH subpopulation compared with the GZ subpopulation (stG = 0.226) and the QH subpopulation compared to the YN subpopulation (stG = 0.225), and the SX subpopulation compared to the XZ subpopulation (stG = 0.226). For the southwestern subpopulations, the genetic differentiations were negligible; only moderate genetic differentiation existed between the XZ subpopulation and others, except it was the lowest compared to the SC (stG = 0.049) and CQ (stG = 0.066) subpopulations and the highest compared to the XJ (stG = 0.285) and SX (stG = 0.226) subpopulations. All P values were significant (P = 0.001). In group R (stG = 0.372) between the XJ and GW subpopulations, followed by the XJ and YC subpopulations (stG = 0.352), which was the lowest compared to the SNW subpopulation (stG = 0.248). Among the southwestern subpopulations, genetic differentiation was almost negligible; the maximum was between the XZ and YSE subpopulations (stG = 0.139), and the minimum was between the YC and YNE subpopulations (stG = 0.012). All P values were significant (P < 0.01). In groups E and L  was between the subpopulations 2.8-3.0K and 1.0-1.2K, and the lowest values were between the subpopulations 1.2-1.4K and 0.2-0.4K and 0.4K-0.6K (stG = 0.012). Compared to group E, group L had lower genetic differentiations among subpopulations; the highest stG value was the HM subpopulation (compared to the plain subpopulation) (stG = 0.105), and greater genetic differentiations were detected only when the plain subpopulation was compared to the HM and EHM subpopulations .The pairwise comparisons of G-statistics based on the 2,103 2.8-3.0K . The higulations . HoweverP values among subpopulations in groups C, P, R, and E, other P values indicated significant variations (P < 0.01).Analysis of molecular variation (AMOVA) demonstrated the highest variation among isolates with 73.82, 74.18, 74.36, 72.91, and 83.74%  in groupThe results depicted the genetic separation in the subpopulations from the SW and NW regions from broad to fine spatial scales in both horizontal and vertical orientations, suggesting greater genetic variation between subpopulations. However, the isolates from the SC subpopulation, particularly northern and central, in addition to the central YN and Tibetan subpopulations, were mixed with other subpopulations, indicating the function of those subpopulations in gene interchanges such as bridges connecting the SW and NW regions.P ≥ 0.05, indicating linkage equilibrium and most likely sexual reproduction. In group P, the rbarD values ranged from 0.019 in the SC subpopulation to 0.209 in the SX subpopulation  to 0.264 (0.8-1.0K) . These results revealed the possibilities for sexual reproduction of Pst populations in the SW and NW regions but primarily asexual reproduction. It is important to note that the switch from the broad spatial scale to the fine spatial scale led to differences in the detection of reproduction modes; the highest sexual reproduction signals were detected in the county-wide subpopulation, followed by the provincial subpopulations and only one regional and elevational subpopulation. However, there was no sexual reproduction detected in group L.In group C, the rbarD values ranged from −0.125 in the SC-ML subpopulation to 0.596 in the SC-YY subpopulation (R (correction coefficient) and P (significance) were 0.149 and 0.01, 0.124 and 0.01, 0.141 and 0.01, 0.137 and 0.01, and 0.120 and 0.001, respectively, indicating that the genetic variation increased as the geographic distance increased. However, the five low R values indicated low genetic variation among the five spatial subpopulations.The Mantel test of the five spatial groups  showed a significant positive correlation between geographic distances and genetic distances. The corresponding values of Pst is a parasitic fungus with highly variable geographic subpopulations, thus leading to the need to increase monitoring of its population genetics  collected from a few provinces were characterized . Horizontal spatial scales were grouped by county (group C), with a total of 63 countywide subpopulations; by province (group P), with 10 subpopulations; and by region with geographical proximity and topography (group R), with 14 subpopulations. Vertical spatial scales were grouped by elevation (group E), an elevation of 200 m being used as the criterion for population classification in group E, with 16 subpopulations ranging from 0.0-0.2K to 3.0-3.2K, and by landform (group L); an elevation within 0 to 600 m was considered lowland, 601 to 1,400 m was considered plain, 1,401 to 2,000 m was considered highland, 2,001 to 2,600 m was considered HM (high mountain), and 2,601 to 3,200 m was considered EHM (extremely high mountain).The wheat leaves were kept in a desiccator at 4°C for 2 days. After drying, they were enfolded within absorbent paper. Some of the leaf samples with fresh urediniospores were used to propagate spores, and purification was carried out as previously described . UrediniPst from urediniospores was extracted with cetyltrimethylammonium bromide (CTAB) (–Genomic DNA of e (CTAB)  from infe (CTAB) . A NanoDe (CTAB) –60 were  (CTAB) – were folThe alleles were manually scored for each pair of SSR markers based on the size of the PCR products using GeneMarker V2.2 , and the isolates with identical alleles across all 12 pairs of SSR markers were assigned to the same multilocus genotypes (MLGs). Samples with any missing alleles were eliminated from the 2,702 samples, and 2,103 samples remained.To assess the number of selected loci that were sufficient for subsequent population genetic analysis, a genotype accumulation curve was employed. The genotype curve reached 100%, indicating that the number of loci selected was sufficient for the following analysis .aN , oH (the observed heterozygosity), and eH (the expected heterozygosity) calculated using GENALEX 6.501 software , the number of MLGs observed, the ratio of MLGs over N, and the number of expected MLGs (eMLGs) were determined as an approximation of the number of genotypes, which would be expected at the largest shared sample size based on rarefaction and the shared sample size (H), which measures MLG diversity (G) indicates genotypic richness ; private alleles (Ap), which represent the alleles unique to a single population; and polymorphic loci (PL), which indicate the diversity of loci. All the indices were conducted in the program GENALEX 6.501  was determined by the “Poppr” package in R program version 4.0.2 . Followiple size . The Shaiversity , was caliversity . Stoddarrichness . Lambda richness . Genotyprichness –72. GeneEX 6.501 , 63.The level of genetic homogeneity was determined by the structure of genotype compositions, and the 10 most repeated MLGs were defined as the dominant MLGs. Considering that the MLGs that occurred at least twice as frequently as the MLGs shared within or among subpopulations, the remaining MLGs were private MLGs that were unique to the subpopulation. We calculated the proportions of dominant, shared, and private MLGs in each spatial group in Excel and generated the corresponding histogram, as well as the number and frequency of the shared MLGs within and among subpopulations.http://taylor0.biology.ucla.edu/structureHarvester) and evaluated for the ΔK and the maximum value as the best K  in GENALEX 6.501 software to generate a stG value matrix that was visualized as a heatmap by using the ggplot package in the R program  was conducted by GENALEX 6.501 to visualize the genotypic interchange among all genotypes detected in the various spatial groups , 63, 81. program , 82. Aft program , 83.A] to lie between 0 [linkage equilibrium] and 1 [full disequilibrium]) calculated in the Poppr package of R program 4.0.2 based on the clone corrected data sets to indicate the reproduction mode . Meanwhile, the population recombined freely with sexual reproduction (P < 0.05) among loci and reproduced genotype by cloning, while the observed rbarD value was located outside the distribution of the randomized data set (Linkage disequilibrium was tested by the standard index of association (using rbarD to force the index of association [Iion mode . The nuloduction . An rbardata set .A Mantel test was conducted in GENALEX 6.501 with 1,000 permutations based on the corresponding clone-corrected data sets to assess the significance of the association between genetic distance and geographic distance. A pairwise, individual-by-individual genetic distance matrix was generated from binary data , and thePst genotypes generated by 12 SSR loci are documented in Table S5 in the supplemental material.The frequencies of all