Ex situ31P and 119Sn SSNMR analyses reveal that while both Sn4P3 and SnP3 exhibit phase separation of elemental P andthe formation of KSnP-type environments  during potassiation, only Sn4P3 produces metallic Sn as a byproduct. In bothanode materials, K reacts with elemental P to form K-rich compoundscontaining isolated P sites that resemble K3P but K doesnot alloy with Sn during potassiation of Sn4P3. During charge, K is only fully removed from the K3P-typestructures, suggesting that the formation of ternary regions in theanode and phase separation contribute to capacity loss upon reactionof K with tin phosphides.K-ion batteries (KIBs) have the potential to offer acheaper alternativeto Li-ion batteries (LIBs) using widely abundant materials. Conversion/alloyinganodes have high theoretical capacities in KIBs, but it is believedthat electrode damage from volume expansion and phase segregationby the accommodation of large K-ions leads to capacity loss duringelectrochemical cycling. To date, the exact phase transformationsthat occur during potassiation and depotassiation of conversion/alloyinganodes are relatively unexplored. In this work, we synthesize twodistinct compositions of tin phosphides, Sn However, KIBs arestill a nascent technology compared to LIBs, requiring new avenuesof electrode and electrolyte materials design.7 K-ion conversion electrodes thatcan accommodate the large volume changes associated with K insertion/removalwhile simultaneously delivering practical energy densities are beingactively developed. Phosphorus- and phosphide-based compounds displayhigh theoretical specific capacity for KIBs,12 making these materials attractive to study as potentialanodes. In particular, binary metal phosphides provide a route tomitigate the large volume expansion observed upon conversion reactionswith phosphorus (up to 600% for the formation of K3P) byproducing ternary intermediates and/or displacement and subsequentconversion reactions during potassiation of the parent phase.18Conversion- and alloying-type anodes offerhigh capacities in alkalimetal batteries, such as commercially successful Si anodes in Li-ionbatteries (LIBs). Due to the greater abundance of K compared to Li, K-ion batteries(KIBs) have the potential to lower the cost of grid-scale electrochemicalstorage4P3, SnP, Sn3P4, and SnP3200) offering a rich phase space to study the mechanisms underpinningpotassiation/depotassiation in high-capacity (>600 mAh g–1) anodes. Yet, many of the intermediates generated upon K reactionwith tin phosphides are highly disordered and separate into multiplephases, making structural assignment challenging. For example, Guoand co-workers used operando X-ray diffraction (XRD)to examine the potassiation behavior in Sn4P3, proposing a mechanism by which the Sn4P3 phase-separatesinto metallic Sn and amorphous P upon discharge to ∼0.21 Vvs K+/K, allowing the formation of K3P11.20 After further discharge to potentialsbelow 0.17 V vs K+/K, K3P11 reactswith additional K to form K3P and metallic Sn alloys withK to form KSn. However, each of these assignments relied on a singular,low-intensity reflection in the XRD pattern (12.71° (for KSn),12.14° (for K3P11), and 14.27° (forK3P)). Li and co-workers also report segregation of Sn4P3 and Sn, followed by conversion and alloyingreactions that form K3P, KSn, and K4Sn23, although these assignments rely on minor, low-intensity XRD reflectionsor lattice spacing measurements from high-resolution transmissionelectron microscopy (HRTEM) of the crystalline components.21 In another study, Park and co-workers reportedon the final discharge products formed at the end of potassiationof SnP3 using ex situ XRD, HRTEM, andX-ray photoelectron spectroscopy (XPS).22 The authors proposed a reaction pathway that included phase separationof Sn particles from bulk SnP3 and a conversion reactionbetween the remaining P and K to form K3P. The Sn followeda two-step alloying reaction to first form K4Sn23 and then KSn. Yet only one reflection could be observed for eachintermediate in the diffraction data, indicating that heterogeneityand disorder in the anode complicate structural analyses.Of the binary compounds, tin phosphides are readily synthesizedin a variety of different stoichiometries spectroscopy and density functional theory (DFT) calculations of stabilityand simulated NMR spectra for a large set of hypothetical structuresto elucidate the amorphous and short-range crystalline structure inproducts that form during potassiation/depotassiation of SnP3 and Sn4P3. Assignments of crystalline structuresare supported via ex situ XRD at different statesof discharge/charge of KIBs assembled with both anode materials. Bothexperiment and theory suggest that SnP3 and Sn4P3 exhibit distinct potassiation mechanisms. K insertioninto Sn4P3 and SnP3 generates localenvironments resembling K-Sn-P ternary phases that are predicted tobe stable based on DFT calculations. Displacement of metallic Sn isobserved in the case of Sn4P3, but no Sn phaseseparates upon potassiation of SnP3. Unambiguous assignmentof metallic Sn during K insertion is achieved by monitoring the metallicKnight shift in 119Sn NMR . When metallic Sn is present, little to no K–Sn alloyingis observed.Experimentaland computational tools that can identify and parseamorphous, multicomponent species with high chemical resolution arerequired to understand and control complex potassiation behavior inbinary anodes. In this study, we use a combination of 6, > 99.5%), propylene carbonate ,dimethylcarbonate , hexanes ,Sn(> 99%), and sodium carboxymethyl cellulose (CMC) were purchasedfromSigma-Aldrich. Red phosphorous powder (98.9%) was purchased from AlfaAesar. Carbon Super P was purchased from MTI Corporation. Prior touse, KPF6 salt was dried in vacuo overnightat 100 °C before bringing into an Ar-filled glovebox . All other materialswere used as received.Potassium metal , potassium hexafluorophosphate  and 1 h (Sn4P3). Product purity was confirmedwith XRD and SSNMR.SnPxPy:carbon Super P:CMC binder. First, the SnxPy and carbon SuperP were mixed in a stainless-steel ball mill under Ar for 30 min. Ina mortar and pestle, water was added dropwise (∼10 drops per100 mg of dry mixture) to CMC binder until a slurry was formed. TheSnxPy andcarbon mixture was then added and mixed to make a uniform slurry.The slurry was cast onto a Cu current collector  using a 150 μm doctor blade and dried at 100 °C undervacuum overnight. The dried film was punched into 12.7 mm diameterdisks to use in cell assembly. Typical mass loadings of active material(SnxPy) peranode were 5–15 mg cm–2. To assemble theopposing K electrodes, K metal was first treated by rinsing thoroughlyin hexanes, then removing the external oxide layer with a razor blade.Small pieces of potassium were then placed in a bag coated with hexanesand rolled into thin sheets (∼0.25 mm thick) using a cylindricalweight. The K sheet was then removed from the bag and, after waitingfor the hexanes to evaporate, stamped into 12.7 mm diameter disks.These electrodes were used for all electrochemical testing and NMRcharacterization.Electrode films were createdby mixing an 8:1:1 mass ratio of Sn3 and K/Sn4P3 half-cells with 15 mm diameter glass microfiber separators(purchased from GE Life Sciences) soaked with 0.8 M KPF6 in PC. Galvanostatic cycling experiments were performed at C/200and C/100 for SnP3 and Sn4P3, respectively. C-rates were calculated from the theoreticalcapacities of SnP3 and Sn4P3 forthe formation of K3P and KSn . Cells were discharged to 0.05 V and charged to 2.00V vs K+/K.2032-type coin cell casingswere used to assemble K/SnPxPy electrode was removed from the coin cell and submergedin DMC for 30 s before drying at room temperature under vacuum for30 min. Extraction was performed in an Ar-filled glovebox within,at most, 4 h after cells completed cycling. To collect data for thepristine electrodes, SnxPy electrodes were assembled into coin cells, thenimmediately removed, washed, and dried as described.3 and Sn4P3 powders were removed from the Cu current collector and placeddirectly on a zero-background Si plate in the glovebox and sealedwith Kapton polyimide film (Chemplex) in an air-free sample holderfor data collection. To conduct ex situ measurements,individual SnxPy electrodes (including the Cu current collector) were placed on azero-background Si plate and sealed in the same manner. Referencepowder diffraction patterns for SnP3 and Sn4P3 are from the Inorganic Crystal Structure Database . Rietveld refinement was performedusing the TOPAS Academic software package (version 7.12). The crystallitesizes were estimated by a Voigt-convolution approach according toBalzar et al., assuming a lognormal size distribution.25XRD patterns were collected on aPANalytical XPERT3 powder diffractometer with Cu Kα radiation.To confirm synthesis, pristine SnPxPy electrodes at various states of charge were washedand dried as described above. The SnxPy active material was then scraped from the Cucurrent collector, ground in a mortar and pestle, and packed in a1.6 mm o.d. ZrO2 rotor in an Ar-filled glovebox. 1D 31P NMR experiments were referenced to the 31P shift of solid ammoniumdihydrogen phosphate at 0.8 ppm. The recycle delay for 31P NMR experiments was optimized on the pure phase binary compounds. 119Sn NMR was collected using a rotor-synchronized Hahn echo pulse sequence. 119Sn NMR was collected attwo separate offset frequencies: one corresponding to metallic Snat 6894 ppm with 46,080 scans and 0.5 s recycle delay, and a secondcorresponding to diamagnetic Sn compounds and alloys at −153ppm with 512 scans and 60 s recycle delay, unless otherwise noted. 119Sn NMR shifts were externally referenced to SnO2 at −604.3 ppm.SSNMR experimentswere performed at room temperature on a Bruker Avance NEO 600 MHzspectrometer equipped with a 1.6 mm HFXY magic-angle spinning (MAS)Phoenix NMR probehead. Snab initio random structure searching (AIRSS), evolutionaryalgorithms, and structural prototyping,27 yielding awealth of predicted stable and metastable phases that could form duringelectrochemical cycling. Gauge Including Projector Augmented Waves(GIPAW) calculations were performed with CASTEP (v20)29 to predict the 31P chemical shifts for these stable andlow-lying metastable phases of K–Sn–P reported in previouswork.The ternaryK–Sn–P composition space has been recently exploredusing various crystal structure prediction techniques, namely, 30 Vanderbilt ultrasoft pseudopotentials,31 and a plane-wave cutoff energy of 650 eV. TheBrillouin zone was consistently sampled with Monkhorst–Packgrids of maximum spacing of 2π × 0.02 Å–1.32 All structures were relaxed untilthe forces on each ion fell below 0.01 eV/Å–1 prior to performing the chemical shielding calculations; any structuresexhibiting metallicity at the PBE level of theory were excluded fromthe subsequent GIPAW calculations due to the difficulty of reliablysimulating chemical shielding of paramagnetic systems.33 The computed chemical shielding tensors werereferenced against reported experimental 31P shifts forblack P, LiP5, Li3P, NaP, and Na3P to provide chemical shift tensors , showing good agreement .35 All of thedescribed calculations and analyses were performed at high throughputwith the open-source Python library matador.26The GIPAW-NMR calculations employed the PBE functional,3 and Sn4P3 were synthesizedby ball-milling stoichiometric amounts of Sn and P. The structuralintegrity of SnP3 and Sn4P3 afterball-milling with conductive carbon for electrode fabrication wasconfirmed by XRD . Nano-sized active materials areconsistent with previously reported syntheses for use in KIBs.36 Particles in this size range are expected to improve transport throughthe active material and may be less prone to fracture and pulverizationduring electrochemical cycling compared to micron-sized particles.37SnPd by XRD 1. Rietve3) and 235 mAh g–1 (for Sn4P3). The lower discharge capacity compared to thetheoretical capacity is consistent with either deviation from thepredicted potassiation pathway and/or sluggish kinetics that preventK insertion in the active material. The shape of the voltage profileobserved upon the charge of SnP3 is similar to the dischargecurve, albeit at lower capacity, suggesting that potassiation maybe only partially reversible and/or that side reactions occur on thefirst discharge. In contrast, the voltage profile for K removal fromSn4P3 is substantially more sloped, indicatingthat different phase transformations may occur during depotassiation.Voltage profiles for later cycles retain these features .The experimental galvanostatic discharge/chargeplot 2 showst38 in this work, the local environments from low-lyingtrial structures are used to provide insight into the short-rangestructural motifs formed during cycling and probed with SSNMR andXRD (vide infra).To understand the possible phase transformationstaking place duringpotassiation/depotassiation of the tin phosphide anodes, we firstturn to DFT. DFT calculations describe the thermodynamic stabilityof several phases in the relevant composition space, many of whichare not currently reported in crystal structure databases, computationalor otherwise (indicated with an asterisk (*) in the following lists).The full predicted phase space is elaborated elsewhere;2P2, KSn3P3, KSnP, K5SnP3, and K8SnP4 are all stablephases that may be formed during potassiation or depotassiation ofeither Sn4P3 or SnP3 anodes . For the K–P edge,each of KP15, KP7*, K3P11, K3P7*, K2P3, KP, andK5P4* are predicted to be stable. Most notably,calculations performed with the PBE functional also indicate thattwo possible charging endpoints, K4P3 and K3P, are both only metastable at finite temperatures; however,they both lie very close to the convex hull .Applying instead the rSCAN functional,40 K3P is found to be thermodynamically stable, yet lies almost preciselyon the existing tie-line between K5P4 and K,indicating that this phase may not form unless cycled to very lowvoltages (0.01 V vs K+/K). Similar calculations for theK–Sn phase space indicate that there are three stable K–Snphases, namely, K3Sn17 (which destabilizes theknown K4Sn23 phase), K4Sn9, and KSn.No crystal structures for ternary K–Sn–Pcompoundsexist in current databases. Our DFT calculations predict that KSnWe note that while DFT-predicted thermodynamic stabilityis usefulfor screening individual trial structures, the formation of a givenphase during electrochemical cycling is highly dependent on kinetics.Ex situ31P and 119Sn SSNMRwere collected at multiple states of charge to directly measure thelocal structural environments present in tin phosphide anodes duringpotassiation/depotassiation  resonance centeredat −20 ppm. Since R3̅m-SnP3 only contains one independent P site, the combination of broad andsharp lines for pristine SnP3 likely arises from smallparticle sizes (∼9 nm) observed in XRD after prolonged ballmilling during synthesis (8 h) and/or amorphous SnP3 compounds.For nano-sized materials, atoms in the particle core often displaya sharp resonance consistent with the bulk crystalline material, whereasthe surface sites exhibit inhomogeneous broadening.43 In the pristinestate, 119Sn SSNMR does not show a resonance for SnP3 (T1) relaxation times, in combination with inhomogeneous linebroadening, making detection prohibitively long44 .ssiation 3 and 4. ation  appears with a small shoulder at11 ppm .The resonance at 11 ppm is consistent with elemental black P,45 whereas the peak at 2.6 ppm agrees with the 31P shift predicted for the on-hull P63mc-KSnP ternaryphase discovered with DFT . Likewise, a broad 119Sn resonance at −66 ppm (fwhm ∼240 ppm) appears atthe same voltage, supporting the formation of new Sn environmentsthat may resemble KSnP-type sites. .The lack of new Bragg reflections in XRD  indicates that crystalline KSnP does not form, but ratherthat K reaction with SnP3 results in local environmentssimilar to those found in the ternary KSnP phase (where P is coordinatedto three Sn and three K atoms and exhibits C3v symmetry).After discharge of SnP+/K 45 and Li3P (δiso = −275 ppm).50 Examination of the chemical shift anisotropy (CSA) associated withthe 31P resonance at −244.5 ppm shows that thereis very little anisotropy at this site, consistent with the formationof isolated P atoms, likely surrounded by K, similar to those expectedfor K3P . These data indicate that phase separation of elemental Penables a conversion reaction between P and K that produces K3P-like structures. Since there are no additional reflectionsobserved in XRD at the end of discharge , we suspect that these K3P-like environmentsdo not exhibit long-range order. Further, we do not observe metallicSn at any state of charge , indicating that only reactions of Kwith P and SnxPy lead to the observed capacity.In the fully discharged state at 0.06 V vs KEx situ31P and 119Sn NMRof the intermediates formed during potassiation of Sn4P3 are shown in 31P SSNMR of the pristine sample  in R3̅m-Sn4P3.49 Minor resonances in 31Pand 119Sn NMR spectra are attributed to residual P (at∼15 ppm) and Sn (center of mass at ∼6870 ppm) from synthesis.Upon discharge to the middle of the voltage plateau at 0.18 V vs K+/K . At full dischargeto 0.06 V vs K+/K .52 We would expect similar 119Sn NMR spectrum changes ifK–Sn alloying were taking place.e sample 4b, black3 to 1.77 V vsK+/K  increases, consistent withK removal. At 2.00 V vs K+/K , likely due tochanges in the stoichiometry of KxSnyPz, some of whichmay regenerate SnP3-like sites. Partial reformation ofSnP3 is also consistent with observations from XRD thatshow increased intensity for SnP3 reflections upon chargingrelative to the fully discharged electrode .Upon charge of SnP4P3 to 1.50 V vs K+/K . DFT simulationspredict several KxSnyPz phases with 31P chemical shifts in this range, indicating that both Sn4P3 and SnP3 anodes generate highly disorderedKxSnyPz coordination environments, although these sitesmay overlap with inhomogeneous broadening observed for SnP3 particles. The chemical shift of metallic Sn in 119SnNMR remains constant  andK to produce the C3v symmetry about the P atom observedin KSnP. This mechanism resembles that proposed by Nazar and co-workersfor Li insertion in MnP4, where reduction is facilitatedby P–P bond breakage rather than redox chemistry associatedwith the metal center.16 In both tin phosphides,residual KSnP-like sites are present at full charge. This suggestskinetic or transport limitations on K removal and presents a mechanismof capacity fade by which K is locked in the tin phosphide structure.We note that this degradation is in addition to electrode crackingobserved in scanning electron microscopy (SEM) of both tin phosphideanodes .The combination of SSNMR and DFT providesunique insight into thepotassiation/depotassiation behavior of tin phosphide anodes. First,we assign a new ternary KSnP-type environment that forms upon dischargeof the battery. The formation of KSnP-like coordination environmentsin both Sn4P3, and not in SnP3 as previously suggested.22 Whilethis phase-separated Sn can, in principle, provide capacity in termsof K–Sn alloying , no evidence for the electrochemical reaction between K and Snis seen in 119Sn NMR nor XRD. The lack of capacity frommetallic Sn is consistent with a loss of electrical contact upon phaseseparation.58 Metallic Sn is never reincorporatedin the anode, which is consistent with displacement reactions observedin LIB systems producing electrically isolated metal particles uponconversion and displacement reactions . Thus, most of the observedcapacity in both Sn4P3 and SnP3 isdue to the formation of disordered sites resembling K3Pand likely explains the rapid capacity loss in these systems. Effortsto enable alloying anodes in KIBs must consider this phase separationand find a way to tether the components to the electrode during potassiation/depotassiation.The second majorfinding of this work is that metallic Sn is onlygenerated in the case of Sn4P3 and SnP3) and metallic Sn (in the case of Sn4P3), onlyP-containing compounds react reversibly with K. Local structures resemblingKSnP persist after charge, suggesting transport and/or kinetic limitationsfor removing K from within the layered tin phosphides (regardlessof starting stoichiometry). In the case of Sn4P3, the formation of electrically isolated Sn prevents total recoveryof the pristine material and does not appear to add reversible capacityvia alloying. The irreversible phase separation and structural rearrangementsinherent to tin phosphides motivate new approaches to enabling P orbinary phosphides as a high-capacity KIB anode material. We suspectthat tin phosphides in KIBs may benefit from the approaches takenfor Si–C anodes in LIBs,63 where nanoparticles of the high-capacityanode material  are embedded in a graphitic matrix toaccommodate volume expansion.The combination of SSNMR and DFT enabledthe detection and assignmentof short-range and amorphous intermediates previously invisible indiffraction analyses of tin phosphide anodes for KIBs. While the intentionof binary phosphide anodes, such as tin phosphides, is to enable highcapacity and mitigate volume expansion, we find that upon phase separationof elemental P (in both Sn


Sinularia leptoclados, while alkaloidal terpenes and N-acyl amino acids were proposed in both Sarcophyton roseum and Sarcophyton acutum.Soft corals are recognized as an abundant source of diverse secondary metabolites with unique chemical features and physiologic capabilities. However, the discovery of these metabolites is usually hindered by the traditional protocol which requires a large quantity of living tissue for isolation and spectroscopic investigations. In order to overcome this problem, untargeted metabolomics protocols have been developed. The latter have been applied here to study the chemodiversity of common Egyptian soft coral species, using only minute amounts of coral biomass. Spectral similarity networks, based on high-resolution tandem mass spectrometry data, were employed to explore and highlight the metabolic biodiversity of nine Egyptian soft coral species. Species-specific metabolites were highlighted for future prioritization of soft coral species for MS-guided chemical investigation. Overall, 79 metabolites were tentatively assigned, encompassing diterpenes, sesquiterpenes, and sterols. Simultaneously, the methodology assisted in shedding light on newly-overlooked chemical diversity with potential undescribed scaffolds. For instance, glycosylated fatty acids, nitrogenated aromatic compounds, and polyketides were proposed in  Egypt, with its exclusive geographical location spanning over 3000 km of coastal area, offers numerous distinguishable habitats with abundant biodiversity. The Red Sea is one of the most biodiverse areas, harboring multitudes of corals and sponges . Among cSoft corals represent an outstanding natural resource harboring diverse classes of natural products with a broad spectrum of biological properties . In addiSinularia and Lobophytum, and are enriched in Sarcophyton species +, C20H26O4) and another feature was hypothesized to be sarcoehrenbergilid C +, C20H30O5). Within the same cluster, gyrosanolide A  was proposed as a uniquely morphed cembrane-derived scaffold formerly described in Sinularia gyrosa +, C20H28O5), previously reported to occur in the soft corals Sarcophyton infundibuliforma +, C21H32O6) and durumolide Q +, C21H32O5).Similarly, an additional group of cembrane diterpenes sharing the same distribution pattern among the species b were uniodiol A   was proposed as a metabolite of Sarcophyton roseum, and found to be associated with a further set of descendant ions possessing mass differences of +24 and +26 Da. The latter tentative derivatives of 65, which are larger in size, have not been previously described and represent possibly new congeners , was annotated. The associated features were proposed to identify possibly new congeners with variable structural modifications such as dehydration, hydration, hydroxylation, or hydroperoxylation, as implied from the edge connections of −18 Da, +18 Da, +16 Da, or +17 Da, respectively. The terpenes d, and amCladiella pachyclados appeared to produce numerous isomers of dihydroxydeepoxysarcophytoxide +, C20H32O3)  e.Lastly, a number of cembrane diterpenes were extracted as either a cluster of two nodes or as singletons as shown in Cladiella pachyclados and Lobophytum pauciflorum. In line with former investigations +, C20H34O5) identified in Cladiella pachyclados  with two additional isomeric forms including the structurally related sclerophytin E +, C22H36O5)  b. Lobophytum pauciflorum as a prolific source of eunicellin diterpenes , connected with an edge of 28 Da to litophynol A acetate isomers +, C26H40O6), as reflected through their comparative elemental composition (+C2H4). Similarly, cluster 4d was proposed to demonstrate several isomeric forms of pachycladin B +, C26H42O7), and cladieunicellin N +, C24H38O7), while klysimplexin E +, C24H38O7), and klysimplexin C +, C26H42O7) constituted cluster 4e. Interestingly, the MN unequivocally delineated terpenes c–e. Clusgorgin B  , and its characterized peroxy derivative +, C26H38O6), which was originally reported from the soft coral Litophyton viscudium , and numerous isomers of cladieunicellin K +, C24H38O6), respectively. The third putatively defined set of eunicellin-derived features included litophynin G +, C24H36O4), briarellin P +, C25H40O7), simplexin P +, C26H42O7), and australin G +, C24H38O5).In a similar fashion, and foremost in ked down g,h,i. Thcellin K  , klymollin S +, C22H34O5), and sclerophytin C +, C22H36O6)  j.Litophyton mollis, and sporadically in samples of the genus Sinularia  in addition to numerous isomers  was deciphered as a self-looped node, and was also found to exist in Sinularia gardineri, and Sinularia leptoclados.As illustrated from the FBMN, sesquiterpenes with various carbon skeletons were mostly proposed from the extract of terpenes a. Such i isomers a, while 21, m/z 203.1789 [M + H]+, C15H22), previously characterized as (+)-trans-calamenene from Nephthea erecta  grouped with an unknown pair of dehydrogenated derivatives, and isomers of capillosanane M +, C15H22O2), while, both capillosanane D +, C15H20O2), occurring exclusively in Lobophytum pauciflorum, and capillosanane F +, C15H22O2), appeared as scattered single nodes  and the aromatic cuteazul +, C15H18) , and oxoeudesmendiol +, C15H24O3)  d. In add8 and 10   e, was su5- (or Δ0-) cholestane nucleus embedded with a C8−C10 side chain +, C29H46O5), previously characterized from Sinularia candidula, nephalsterol B +, C28H46O3), isomers of hydroxyergostadiene-one +, C28H44O2), sarcrasterol +, C28H48O4), erectasteroid D +, C29H46O4), and hydroxystigmastatrienone +, C29H44O2)  . The clu75, m/z 429.3359 [M + H]+, C28H44O3) were proposed to cluster separately  .Sarcophyton and Sinularia; and by the number of the autozooids to differentiate between Sarcophyton species [The collected soft coral samples were identified based on morphology, colony color, shape, interior, and sclerites, using established identification keys ,81,82,83 species ,82, wherAll chemicals for chemical analysis were obtained from Sigma-Aldrich .The frozen soft coral specimens (100 g each) were chopped into small pieces and extracted with ethyl acetate (1 L) at room temperature, five times until exhaustion, with respective yields listed in ®, Bremen, Germany) coupled with an Ultimate 3000 HPLC . A UPLC-method was applied as described in [®, Düren, Germany), and the range for MS acquisition was 50–1800 Daltons (Da). A capillary voltage of 4500 V, nebulizer gas pressure (nitrogen) of 2 (1.6) bar, ion source temperature of 200 °C, dry gas flow of 9 L/min, and spectral rates of 3 Hz for MS1 and 10 Hz for MS2, were used. For acquiring MS/MS fragmentation, the 10 most intense ions per MS1 were selected for subsequent CID, with stepped CID energy applied. The employed parameters for tandem MS were applied as previously detailed [The HRMS/MS analysis was carried out on a MaXis 4G instrument . Metaboscape 3.0  was utilized for feature detection, grouping, and alignment, employing the T-ReX 3D  algorithm [5 and a retention time range from 0.5 to 40 min with a restricted mass range m/z from 190 to 1800. The produced MGF file and the feature quantification table (CSV file) were used in the feature-based molecular networking (FBMN) following the online workflow in GNPS platform (http://gnps.ucsd.edu (accessed on 1 August 2022)) [via the GNPS platform, are detailed in Raw data inspection was performed using Compass Data Analysis 4.4 ) . The parhttps://cytoscape.org/, accessed on 15 February 2021) was used for the network visualization. Sirius + CSI:FingerID 4.0.1 was used for the manual putative structures identification [m/z tolerance set to 20 ppm connected to online Pubchem and verified through the MarineLit database .Cytoscape version 3.7.1.60 (fication , assiste


Gammaherpesviridae, encodes the Bcl-2 homolog BHRF1, a potent inhibitor of Bcl-2-mediated apoptosis. BHRF1 acts by directly targeting Bid and Puma, two proapoptotic proteins of the Bcl-2 family. Here, we determined the crystal structures of BHRF1 bound to peptides spanning the Bcl-2 binding motifs  of Bid and Puma. BHRF1 engages BH3 peptides using the canonical ligand-binding groove of its Bcl-2 fold and maintains a salt bridge between an Arg residue with a conserved Asp residue in the BH3 motif mimicking the canonical ionic interaction seen in host Bcl-2:BH3 motif complexes. Furthermore, both Bid and Puma utilize a fifth binding pocket in the canonical ligand binding groove of BHRF1 to provide an additional hydrophobic interaction distinct from the interactions previously seen with Bak and Bim. These findings provide a structural basis for EBV-mediated suppression of host cell apoptosis and reveal the flexibility of virus encoded Bcl-2 proteins in mimicking key interactions from the endogenous host signaling pathways.Apoptosis is a powerful defense mechanism used by multicellular organisms to counteract viral infection. In response to premature host cell suicide, viruses have evolved numerous countermeasures to ensure cell viability to optimize their replication by encoding proteins homologous in structure and function to cellular pro-survival Bcl-2 proteins. Epstein–Barr virus (EBV), a member of the  Gammaherpesviridae genus and is the causative agent of infectious mononucleosis (glandular fever) in humans and implicated in lymphoproliferative disorders, gastric, and nasopharyngeal cancer  as asL (17.ID 2M04) a. The foID 2M04) c. FurtheL 17.%, Bcl-w BHRF1 and D146Puma. These salt bridges were supplemented by additional hydrogen bonds between the carboxyl group of E89BHRF1 and the NδH side-chain group of R135Puma, and between the G99BHRF1 main-chain amide group and the side-chain carboxyl and amide group of N149Puma  to neutralize their activity but not with Bcl-B ..L. AlthoL and KSHV KsBcl2 have conserved BH1 NWGR motifs and show comparatively high affinities for both Bid and Puma ,51L comp and V79 e. The biPuma BH3 f differsPuma BH3 g and tanPuma BH3 h. BindinPuma BH3 a 20]. T. TL compPuma BH3 c,d. CollPuma BH3 a. An altH3 (Puma , as well(Puma [L , Bcl-2 [(Puma [L , ORFV125(Puma [L , and SPP(Puma [L . Collect(Puma [L . Clearly(Puma [L  and grou(Puma [L , as well(Puma [L .Apoptosis induction by viral infection has been shown to be dependent on Puma for apoptosis via Bax/Bak activation ; viral i


Petal blotch is a unique ornamental trait in angiosperm families, and blotch in rose petal is rare and has great esthetic value. However, the cause of the formation of petal blotch in rose is still unclear. The influence of key enzyme genes and regulatory genes in the pigment synthesis pathways needs to be explored and clarified.O-diglucoside (Cy3G5G) contributed to the blotch pigmentation of ‘Sunset Babylon Eyes’, and the amounts of Cy3G5G varied at different developmental stages. Only flavonols but no flavone were found in blotch and non-blotch parts. As a consequence, kaempferol and its derivatives as well as quercetin and its derivatives may act as background colors during flower developmental stages. Despite of the differences in composition, the total content of carotenoids in blotch and non-blotch parts were similar, and carotenoids may just make the petals show a brighter color. Transcriptomic data, quantitative real-time PCR and promoter sequence analyses indicated that RC7G0058400 (F3’H), RC6G0470600 (DFR) and RC7G0212200 (ANS) may be the key enzyme genes for the early formation and color deepening of blotch at later stages. As for two transcription factor, RC7G0019000 (MYB) and RC1G0363600 (WRKY) may bind to the promoters of critical enzyme genes, or RC1G0363600 (WRKY) may bind to the promoter of RC7G0019000 (MYB) to activate the anthocyanin accumulation in blotch parts of ‘Sunset Babylon Eyes’.In this study, the rose cultivar ‘Sunset Babylon Eyes’ with rose-red to dark red blotch at the base of petal was selected as the experimental material. The HPLC-DAD and UPLC-TQ-MS analyses indicated that only cyanidin 3,5-Our findings provide a theoretical basis for the understanding of the chemical and molecular mechanism for the formation of petal blotch in rose.The online version contains supplementary material available at 10.1186/s12870-023-04057-6. Cistus purpureus), Paeoniaceae , Onagraceae , Violaceae  and Compositae  [Petal color patterning, such as flower spots and stripes, is one of the most significantly biological and ornamental characteristics for plants and has great significance in plant evolutionary biology –4. As onruentus) –9. Althoruentus) , 10, 11.ruentus) .Flavonoids include flavones, flavonols, anthocyanins and other compounds. Flavonoids are synthesized by a branched pathway that yields both colorless compounds (e.g. flavonols) and colored pigments (e.g. anthocyanins) . As majoPigment  pathways and genes have been extensively characterized in model and non-model plants , 18–21. Arabidopsis thaliana, Petunia hybrida and Rosa hybrida [Medicago truncatula [Arabidopsis thaliana [Regulation of flavonoid pathways is mostly coordinated by a transcription factor complex consisting of R2R3 MYB transcription factors (TFs), basic helix–loop–helix (bHLH) TFs and WD40 proteins (MBW complex), which activates transcription biosynthetic genes in many plants, such as  hybrida , 24–26. uncatula . Besidesuncatula . NAC trauncatula . DOF trathaliana .Rosa contains approximately 200 species and over 40,000 cultivars [R. persica stands out from all wild roses by the chestnut red blotch at the base of each yellow petal [Roses are among the most commonly cultivated ornamental plants worldwide and have gained the title of the world’s favorite flower . The genultivars . R. persow petal , 34. Sinow petal . Hulthemow petal –41. Yellow petal , 43. Admow petal –46. NeveIn this study, the hybrid hulthemia cultivar ‘Sunset Babylon Eyes’ was used to explore the pigmentation regulatory network of blotch and non-blotch parts during the development of rose flowers. We reported the metabolic profiling of flavonoids and carotenoids, as well as gene expression dynamics for the blotch and non-blotch petals of five different coloring stages using integrated analysis of the metabolome and transcriptome. With this extensive analysis of multiple approaches in hybrid hulthemia cultivar ‘Sunset Babylon Eyes’, we reveal changes in the key pigments and related biosynthesis genes that are associated with petal blotch formation.We collected materials at five stages depending on the progress of anthesis and development of blotch , 47, 48.L*, a* and b* of CIEL*a*b* color system of petals were measured. Significant differences were observed in color parameters among the blotch and non-blotch parts at different stages  was found in the blotch parts from S2 to S5  was not detected at S1 and S2, but the compound began to accumulate at S3. Among the flavonol glycosides, f7, which was characterized as kaempferol 3 -O--glucuronide or kaempferol 7 -O--glucuronide, was the predominant component in the blotch parts at S1, S2 and S3, but no longer accumulated at S5. However, f8 (kaempferol 7 -O-glucoside) and f10 (kaempferol 3 -O-α-D-rhamnoside) were the predominant flavonols in non-blotch parts at S3, S4 and S5 -glucuronide or kaempferol 7-O--glucuronide) was the key compound for petals to show yellow. From S3 to S5, f8 (kaempferol 7 -O-glucoside) played a major role in coloration.Eleven flavonol glycosides and no flavone glycosides were identified  at S5 was the lowest, followed by that at S1. TF in the non-blotch parts were always higher than that in the blotch parts, peaking at S3 in the non-blotch part Fig. c. The coE)-Lutein (c7) and  -β-Carotene (c12). It is worthwhile mentioning that the content of c7 was always higher than that of c12. At S4 and S5, the content of c7 decreased and the distribution of each component was relatively average except c12. The total content of carotenoids (TC) at S1 were slightly higher than that at S2 and S3. The categories and the total content of carotenoids began to surge from S4, reaching the maximum at S5. At S4 and S5, blotch parts differed from non-blotch parts in carotenoid compositions (Supplementary Table SL*)  | > 1 and We analyzed the GO and KEGG pathways to determine the biological functions of DEGs. 16,367 41.26%) and 13,695 (34.52%) genes were annotated to GO and KEGG databases. The GO annotation system consisted of three major branches: biological process, molecular function, and cellular component. Phosphotransferase activity, cinnamyl−alcohol dehydrogenase activity, xyloglucosyl transferase activity, sequence−specific DNA binding, secondary active sulfate transmembrane transporter, and isoleucine−tRNA ligase activity were the most significant enrichment GO terms under the molecular function category among six comparisons, respectively. Meanwhile, under the biological process category, DNA packaging, defense response, xyloglucan metabolic process, auxin metabolic process, sulfate transport, and response to biotic stimulus were the most significant enrichment GO terms among six comparisons, respectively  and downstream genes   and RC1G0494500 (CHI), both had the highest expression level at S1 and expressed higher in blotch parts from S2 to S3. RC2G0136900 (F3H) has the highest expression level at S5, except that the expression level in the blotch part at S2 was higher, from S3 to S5, its expression in the non-blotch parts was lower than or equal to that in the blotch parts.To investigate the pathways of pigment synthesis in the blotch and non-blotch parts of petals, we analyzed the genes involved in anthocyanin and flavonol biosynthesis pathways in ys Table  were fouc.) Fig. . As the FLS and UF3GT were key enzyme genes for the biosynthesis and modification of flavonol compounds, thus genes which expressed higher in the non-blotch parts from S1 to S3 were got more attention. Among them, the expression level of RC0G0031100 (FLS) was the highest in the non-blotch part at S2. In addition, RC5G0593900 , whose expression level was higher in blotch parts from S1 to S3, could also be the key gene for the modification of flavonol compounds. As the downstream genes of anthocyanin synthesis pathway, the majority of F3’H, DFR, and ANS genes expressed higher in the blotch parts from S2 to S4.CHS and CHI were consistent with the formation and accumulation of anthocyanin and flavonol. F3’H, DFR and ANS were related to the accumulation of Cy3G5G and the formation of the dark-red blotch, whereas FLS and A3GT were involved in the accumulation of flavonol compounds in non-blotch parts.In summary, DOF, 9 MYB,8 NAC,7 bHLH, 6 WD40, 6 WRKY, 3 TCP and 1 AP2.Some transcription factor (TF) families including MYB, bHLH, AP2, DOF, NAC, TCP, WD40 and WRKY play important roles in color formation via anthocyanins biosynthesis by regulating the expression of key enzyme genes. We therefore analyzed the expression pattern of 592 genes belonging to these TF families in blotch and non-blotch parts (Table RC5G0279600 (TCP) and RC2G0471400 (WD40) had the highest expression level at S1 and the expression level in all the blotch parts were lower than or equal to those in the non-blotch parts. The color change of blotch and non-blotch parts of ‘Sunset Babylon Eyes’ may be related to the decrease of the expression of these two regulatory genes. RC7G0019000 (MYB) was an up-regulated gene in blotch parts and expressed highest at S4. However, as up-regulated genes in blotch parts, RC1G0363600 (WRKY), RC2G0406300 (AP2), RC5G0166100 (WRKY), RC1G0093800 (NAC), RC2G0093100 (MYB), RC0G0030000 (DOF), and RC0G0179800 (NAC) expressed at the highest level in the blotch part at S2. Seven bHLH expressed the highest at S1 or in the non-blotch parts, and thus they may not be the key transcription factors with direct effect on the blotch pigmentation.Among them, RC5G0279600 (TCP) and RC2G0471400 (WD40) may be negative regulatory genes for blotch formation. RC7G0019000 (MYB), RC1G0363600 (WRKY), RC2G0406300 (AP2), RC5G0166100 (WRKY), RC1G0093800 (NAC), RC2G0093100 (MYB), RC0G0030000 (DOF), and RC0G0179800 (NAC) may be positive regulatory genes for blotch formation.Collectively, RC1G0025000 (CHS), RC1G0494500 (CHI), RC2G0136900 (F3H) may be involved in the initiation of ‘Sunset Babylon Eyes’ blotch, and RC7G0563900 (ANS) may be related to the deepening of ‘Sunset Babylon Eyes’ blotch in the later stages, but the relative expression level of these four enzyme genes was not much different from those of the non-blotch parts. Two enzyme genes, RC0G0031100 (FLS) and RC5G0593900 (A3GT), significantly highly expressed in the non-blotch parts at S2 and S3, respectively; hence they may be involved in the synthesis of flavonol glycosides in the non-blotch parts. Three enzyme genes, RC7G0058400 (F3’H), RC6G0470600 (DFR) and RC7G0212200 (ANS), all significantly highly expressed in the blotch parts at S2 and S4, which were supposed to be the key enzyme genes for the early pigmentation and color deepening of blotch in the later stages  significantly highly expressed in the blotch part at S2, but also highly expressed in the non-blotch part at S3. RC2G0406300 (AP2) significantly highly expressed in the blotch part at S2, however, at S4, its relative expression level of the blotch part was lower than that of the non-blotch part. These two regulatory genes may be involved in the regulation of the early pigmentation in blotch parts, or also be related to the regulation of the late pigmentation in non-blotch parts at the same time. The relative expression levels of six regulatory genes, including RC7G0019000 (MYB), RC1G0363600 (WRKY), RC5G0166100 (WRKY), RC0G0179800 (NAC), RC1G0093800 (NAC), and RC0G0030000 (DOF), were always higher of the blotch parts than that of the non-blotch parts from S2 to S4. It is noteworthy that while RC7G0058400 (F3’H), RC6G0470600 (DFR) and RC7G0212200 (ANS) significantly highly expressed at S2 and S4 in the blotch parts, there were corresponding trends of the relative expression levels of RC7G0019000 (MYB) and RC1G0363600 (WRKY). Hence, RC7G0019000 (MYB) and RC1G0363600 (WRKY) may be the key regulatory genes for the early pigmentation and color deepening of blotch in the later stages. In contrast, the relative expression level of the rest two genes, RC5G0279600 (TCP) and RC2G0471400 (WD40), in blotch parts were lower than those in non-blotch parts from S2 to S4. In that case, these two genes may negatively regulate the pigmentation of blotch . All three enzyme genes’ promoters had the cis-acting regulatory element of MYB recognition site (MRS), MYB binding site (MBS) or MYB recognition element (MRE) , RC6G0470600 (DFR) and RC7G0212200 (ANS) were all likely to be regulated by MYB transcription factor. Meanwhile, the promoter sequences of RC7G0058400 (F3’H), RC6G0470600 (DFR) and RC7G0019000 (MYB) all had the cis-acting regulatory element of W box or WRKY recognition element (WRE), so all of them might be regulated by the transcription factor of WRKY  non-blotch parts, or exactly the opposite , 50–59. O-diglucoside (Cy3G5G) was found in the petal’s blotch. As for Paeonia suffruticosa [Viola × wittrockiana Gams [Clarkia gracilis [Rosa [Paeonia suffruticosa cultivar ‘High Noon’ which had both of flavones and flavonols in petals [Rosa ‘Sunset Babylon Eyes’ could directly start from the research on flavonol biosynthesis pathway. Thirdly, a variety of different carotenoids played an assisted role in the coloration of petals by adding orange or yellow hue as in other plants’ flowers [Mimulus [Firstly, the anthocyanin composition of its petal was quite simple. Only one anthocyanin: cyanidin 3,5-ruticosa , Viola ×ana Gams . and Clais [Rosa . Comparen petals  , RC6G0467567 (DFR), and RC7G0212200 (ANS) which all expressed significantly highly may be the most significant enzyme genes that directly facilitate the pigmentation of blotch. species , 61, 63 MYB, especially R2R3-MYB participated in almost all the blotch formation mechanism in different species by activating, enhancing or inhibiting [MdWRKY11 could promote the expression of F3H, FLS, DFR, ANS and UFGT, thereby increasing the accumulation of flavonoids and anthocyanin in apple calli [PyWRKY26 and PybHLH3 could co-target the promoter of PyMYB114, which activated the expression of PyDFR, PyANS, and PyUFGT, and therefore resulted in anthocyanin accumulation in red-skinned pear [StWRKY13 could not only enhance the role of StAN2 (belongs to MYB family) in promoting anthocyanin biosynthesis in tobacco, but also interact with the promoters of StCHS, StF3H, StDFR and StANS genes, thereby enhancing their activation of anthocyanin formation in coloured potato tubers [MYB belongs to a common transcription factor family that regulates anthocyanin synthesis. hibiting , 66–68  and WRKY (RC1G0360567) significantly highly expressed in blotch parts at S2 and S4, and their relative expression level trends matched that of RC7G0055400 (F3’H), RC6G0467567 (DFR) and RC7G0212200 (ANS). The cis-acting regulatory elements analysis of promoter sequences indicated that MYB (RC7G0019000) and WRKY (RC1G0360567) may bind to the promoters of critical enzyme genes or WRKY (RC1G0360567) may bind to the promoter of MYB (RC7G0019000) to activate the anthocyanin accumulation in rose blotch.In ‘Sunset Babylon Eyes’, WRKY (RC1G0363600) or MYB (RC7G0019000).12 genes may be positive regulatory genes of WRKY (RC1G0363600) or MYB (RC7G0019000) while 10 genes may be negative regulators  by absorbing excess light in angiosperms , 73. ThePaMADS2, PaMADS4 and PaMADS7 inhibited fruit ripening and decreased the anthocyanin content in sweet cherry [ScAG and ScAGL11) negatively regulated anthocyanin biosynthesis in cineraria ray florets, and their differential expression influenced the bicolour pattern appearance [Camellia japonica whereas GATA became a negative regulator of anthocyanin synthesis during Lycoris radiata petal development stages [Hibiscus syriacus, IAA (auxin-responsive protein IAA) could bind with ARFs to remove their repressive action on anthocyanin biosynthesis genes, while JAZ degradation caused the transcriptional activation of MBW complex and thereby resulting in color flower [MdHY5 promoted anthocyanin accumulation by regulating expression of the MdMYB10 and downstream anthocyanin biosynthesis genes in apple [JAGGED (JAG) could regulate cell differentiation and flower morphological development in Arabidopsis thaliana. Overexpression of MdZAT5 (a C2H2-type zinc finger gene) promoted anthocyanin accumulation in apple calli and Arabidopsis thaliana [LhGST was positively correlated with anthocyanin accumulation in lilies [Genes involved in developmental program, environmental cues, or plant hormones have a positive or negative effect on anthocyanin accumulation in different species , 74. Silpearance . One GATt stages , 76. Gent stages . Stress-t stages . Exogenot stages –81. Exogt stages . Far-redt stages , 80. A vt stages , 81. In r flower –85. The in apple . The C2Hthaliana , 84. LhGO-diglucoside) in different regions of petals contributed to the blotch formation. In addition, 11 flavonol glycosides were responsible for the yellow background color while 12 carotenoids brighten the petal color. In an analysis of the anthocyanin biosynthesis pathway, 9 structural genes  and 10 TFs  were identified. Analysis of cis-acting regulatory elements of promoter sequences suggested that MYB (RC7G0019000) and WRKY (RC1G0363600) may bind to the promoters of RC7G0058400 (F3’H), RC6G0470600 (DFR) or RC7G0212200 (ANS). Also WRKY (RC1G0363600) may bind to the promoter of MYB (RC7G0019000) to activate anthocyanin accumulation in rose blotch  under the condition that the indoor light was sufficient but not dazzling, and the light source could be kept stable for a long time. For each sample, three petals were detected and each petal was measured five times. The values of software .O-diglucoside and quercetin 3-O-galactoside were y = 22,887x-96.484 (R2 = 0.9987) and y = 46,796x + 10.026 (R2 = 0.9996), respectively. The following analysis of mass spectrometry was performed on Waters I-Class UPLC/Xevo TQ MS . Identification of flavonols and anthocyanins were based on standards and a previous study [The extraction and flavonoid analysis were carried out as described by a previous study , with mius study .n-hexane and 1 mL NaCl solution  were added. Next, the upper organic phase was collected and the bottom layer was re-extracted with 1 mL of n-hexane: diethyl ether (volume ratio = 3:1) until the sample turned colorless. The combined extracts were evaporated to dryness in a nitrogen blower and saponified with 1 mL of 6% KOH methanolsolution. Then the mixture was extracted with 1 mL of NaCl solution  and 1 mL of n-hexane: ether  until the sample appeared colorless. The extracted supernatants were concentrated to dryness with Concentrator plus vacuum centrifugal concentrator . The saponified carotenoid dry powder was reconstituted with methanol-methyl tert-butyl Base ether  prior to HPLC analysis. To avoid carotenoid degradation, 0.1% BHT (w/v) was added to the solvent extracts. HPLC analysis was performed on Agilent 1260 Infinity II HPLC-DAD . The flow rate, injection volume and column oven temperature was 1 mL/min, 100 uL and 25 °C, respectively. The detection wavelength of carotenoids was 450 nm. Carotenoids were quantitatively analyzed by external standard method. Calibration equations for 13/13’Z-Neoxanthin was y = 288,930x-614.38 (R2 = 0.9999).The extraction and HPLC analysis of carotenoids were performed as described by a previous study , with miThe following analysis of mass spectrometry was performed on Waters I-Class UPLC/Xevo TQ MS . Identification of carotenoids was based on standards and a previous study .The total RNA was extracted with the Invitrogen TRIzol . The quality and integrity of RNA were assessed with a 1% agarose gel, NanoDrop 2000  and Agilent 2100 Bioanalyzer . The construction of the libraries and RNA-Seq were carried out on an Illumina Novaseq™ 6000 platform  by HT Health Biotechnology Corporation .R. chinesis (https://pubmed.ncbi.nlm.nih.gov/29713014/) by HISAT2 software (version: hisat2–2.0.4) and then the mapped reads were assembled using StringTie (version: stringtie-1.3.4d.Linux_x86_64) with default parameters. Subsequently, all transcriptomes were merged to reconstruct a comprehensive transcriptome using gffcompare software (version: gffcompare-0.9.8.Linux_x86_64). The expression of mRNA was calculated by FPKM (Fragments Per kb Per Million Reads) method. The differentially expressed genes (DEG) were selected with thresholds of fold change > 2 or fold change < 0.5, p value< 0.05 by DESeq2 tool, and then used for the GO and KEGG [After removing low-quality reads, undetermined reads and reads containing prime/ adaptor, raw data were filtered as clean data for the following analyses. Clean reads were mapped to the genome of Gene expression analysis was conducted by qRT-PCR as described by Gu et al. . The prihttp://bioinformatics.psb.ugent.be/webtools/plantcare/html/) to predict the possible cis-acting regulatory elements.Promoter sequences of the obtained key genes were analyzed using Plant-CARE online software , MassLynx  and Origin 9.0 . All assays were performed in triplicate. Relative expression level of candidate genes by qRT-PCR were compared by analysis of variance (ANOVA).Additional file 1: Supplementary Fig. S1. HPLC chromatograms of flavonoid detected at 525 nm and 350 nm. Supplementary Fig. S2. Difference analysis of gene expression between blotch and non-blotch parts. Supplementary Fig. S3. Veen analysis of gene expression between blotch and non-blotch parts. Supplementary Fig. S4. GO classification of differentially expressed genes. Supplementary Fig. S5. KEGG enrichment of differentially expressed genes. Supplementary Fig. S6. Promoter sequences and key cis-acting regulatory elements of genes most likely to influence the blotch pigmentation in rose. Supplementary Fig. S7. DEGs associated with developmental program, environmental cues, or plant hormones. Supplementary Table S1. Contents of pigments. Supplementary Table S2. Identification of carotenoids. Supplementary Table S3. RNA sequencing data and corresponding quality control. Supplementary Table S4. Different blotch formation in different species. Supplementary Table S5. Other DEGs identified in anthocyanin biosynthesis-related pathways. Supplementary Table S6. Primers required for candidate unigenes qRT-PCR expression.


At present, there are still no specific therapeutic drugs and appropriate vaccines for Dengue. Therefore, it is important to explore distinct clinical diagnostic indicators.In this study, we combined differentially expressed genes (DEGs) analysis, weighted co-expression network analysis (WGCNA) and Receiver Operator Characteristic Curve (ROC) to screen a stable and robust biomarker with diagnosis value for Dengue patients. CIBERSORT was used to evaluate immune landscape of Dengue patients. Gene Ontology (GO) enrichment, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis and Gene set enrichment analysis (GSEA) were applied to explore potential functions of hub genes.CD38 and Plasma cells have excellent Area Under the Curve (AUC) in distinguishing clinical stages for Dengue patients, and activated memory CD4+ T cells and Monocytes have good AUC for this function. ZNF595 has acceptable AUC in discriminating dengue hemorrhagic fever (DHF) from dengue fever (DF) in whole acute stages. Analyzing any serotype, we can obtain consistent results. Negative inhibition of viral replication based on GO, KEGG and GSEA analysis results, up-regulated autophagy genes and the impairing immune system are potential reasons resulting in DHF.CD38, Plasma cells, activated memory CD4+ T cells and Monocytes can be used to distinguish clinical stages for dengue patients, and ZNF595 can be used to discriminate DHF from DF, regardless of serotypes.The online version contains supplementary material available at 10.1186/s12985-022-01853-8. Vaccn health –12, but n health –17. Asymn health , 18 and Autophagy, a catabolic process that degrades damaged or abnormal intracellular components to recover nutrients, is essential for maintaining cell and body homeostasis , 20, andTranscriptomics researches are beneficial to assist researchers in better understanding disease causes  and locahttp://www.ncbi.nlm.nih.gov/geo). We followed these reference points: 1. datasets analyzed whole blood samples of different stages from Dengue patients including DF and DHF, and normal samples; 2. Datasets should include at least 20 dengue patients. Based on these criteria, we obtained GSE43777 dataset analyzing Two chip types (affymetrix HG-U133 plus 2 in GLP570 platform and HG-Focus in GLP201 platform) [Gene expression datasets of Dengue patients were selected from a public database named the Gene Expression Omnibus databases  , GSE2840latform)  and GSE5In GSE43777, more than 200 samples (one sample for each stage) were collected from 51 DF and 13 DHF subjects in Maracay, Venezuela, and demographics and clinical, immunological and hematological characteristics of participants were preciously summarized . In GSE2Regarding gene expression levels in C or EA stages as baselines, these patients were divided into 3 groups, C vs EA, C vs LA and EA vs LA, as precious studies . The Prihttp://sangerbox.com/Tool) based on a R package “Limma” was applied to analyze DEGs among three phases  and between DHF and DF for Dengue patients. A R package “clusterProfiler” in R version 4.1.0 and a gene set enrichment analysis (GSEA) software (4.1.0) [A website ( (4.1.0)  were useWe obtained a total of 4843 genes in the C vs EA group, 4472 genes in the C vs the LA group and 4463 genes in the EA vs LA group by a “WGCNA” package. We converted the adjacency matrix into the topological overlap matrix (TOM) when the power of β were equal to 5, 4 and 12. According to a height cutoff of 0.25, we merged similar modules and the module displaying the highest conformity with the development disease of Dengue was used to intersect with DEGs to identify more stable DEGs.https://cibersortx.stanford.edu/index.php) which can be used to input gene expression data and then obtain a fraction estimate of 22 immune cell types in whole blood samples [we estimated fractions of immune cells in whole blood samples by the “CIBERSORT” website  and R. Studio (version 1.9.0) were used to analyze data and visualize results. We applied the t-test, Mann–Whitney U test and the chi-square test to identify differences between two groups. Correlation analyses were showed according to the Pearson and Spearman theories. Figure P value < 0.05. Likewise, in the EA stage we obtained 30 DEGs (16 up-regulated genes and 14 down-regulated genes)  shows three stage samples can be distinguished  are mainly enriched in defense response to viruses and type I interferon Fig. K; DNA reCCL2) by intersecting DEGs between DHF and DH samples from GSE43777 analyzed on GLP570 platform with 222 autophagy-related genes downloaded from Human Autophagy Database (HADb) which provides a complete and an up-to-date list of human genes and proteins involved directly or indirectly in autophagy. The boxplot diagram  in Fig. KEGG analysis results reveal that pathogen infection and NOD − like receptor signaling pathway are obvious enrichment pathways for 147 DEGs (between the C and the EA stages) Fig. P; Cell rUsing the GSE43777 dataset analyzed on GLP201 platform, we performed a “WGCNA” package to obtain key modules associated with procession features of Dengue. We select 5, 4 and 12  and the C group  in Fig. P = 5e−20) and the blue module, and between the C group  and the blue module in Fig. The association of module eigengene (ME) values and clinical stages is applied to assess the module-stage feature correlation. WGCNA results show 14, 12 and 8 modules, respectively Fig. G–I. Comphttp://www.ehbio.com/test/venn/#/) [CD38 and CDKN1C are shared by the three phases  for each serotype and log|FC|> 1 or log|FC| is extremely closed to 1 . While the expression of CDKN1C is firstly down-regulated and subsequently up-regulated from the day 0 to the C stage (***P < 0.001) . We select CD38 and CDKN1C for follow-up analyses.To filter reliable and strong hub genes (shared genes) accurately, Venn diagrams were used to visualize hub genes between DEGs and key modules by a website (venn/#/) . The resses Fig. D. When c01) Fig. G. The GSays Fig. E and CDKays Fig. F. CorrelCD38 and CDKN1C express differently in three stages , GSE43777 datasets analyzed on the GPL570 platform  and GSE28405  as a training dataset, a verifying dataset and a testing dataset, respectively. When analyzing single serotype, we regard GSE43777 datasets analyzed on the GPL201 platform , GSE43777 datasets analyzed on the GPL570 platform  as a training dataset and verifying dataset, respectively.Because ges Fig. A–B, we sCD38 has 0.960, 0.976, and 0.829 of AUC in three comparing groups  respectively and CDKN1C has 0.852, 0.868 and 0.955 of AUC in three comparing groups  respectively , CDKN1C . Figure CD38 , CDKN1C . The analytical results above show that CD38 can distinguish admirably different phases for Dengue patients and has a higher distinguishable value than CDKN1C. Although we consider serotypes (serotype I–IV), results are similar among three comparison groups  . Therefore, CD38 shows the high value in distinguishing stages for Dengue patients. We selected CD38 as a biomarker for staging diagnosis of Dengue.In addition, as Fig. CD38 and CDKN1C between DH and DHF samples    and DHF (n = 11) samples from GSE43777 dataset on GLP570 platform in the EA stage with 58 DEGs between DF (n = 25) and DHF n = 26) samples in the LA stage, we identify 6 shared DEGs  increase significantly compared to the LA and C phases. Compared the LA phase with the EA phase and the C phase, fractions of Plasma cells and activated memory CD4+ T cells (P < 0.05) increase clearly  are more obvious in the C phase  increase in DHF samples , which imply immune response are damaged in DHF samples. In the EA stage, the immune response of DF patients is similar to that of DHF patients . In individual serotype, we can still draw this conclusion  expressed differently and increased significantly in DHF, all of which suggested DENV regulated autophagy to lead to DHF. results  and distIn addition, we analyzed systematically immune differences among three stages and between DHF and DF in the acute stage, and correlation between immune cells and genes. Immune analysis results showed fractions of monocytes, activated mast cells, M1 macrophages and neutrophils referred to innate immune response increased obviously in the EA stage compared with the C stage; significant increments can be observed in fractions of plasma cells and activated memory CD4+ T cells comparing the LA stage with the C stage; increasing fractions of plasma cells, CD8+ T cells, activated memory CD4+ T cells, follicular helper T cells, regulatory T cells (Tregs) and gamma delta T cells can be discovered in the LA stage compared with the EA stage. Above results were suitable for any serotype, suggesting different serotypes did not have obvious immune differences. Increasing immune response eliminated DENV which avoided Dengue symptoms  and immuInterestingly, KEGG enrichment showed DEGs  were enriched in Coronavirus disease —COVID-19, Influenza A, Hepatitis C and Measles pathways, implying Coronavirus , AlphainGene expression profiles from public databases (GEO) have been applied to explore Dengue biomarkers by researchers. Several studies have used multiple genes to distinguish Dengue patients from healthy samples , 40, DHFCompared with previous studies –41, our There is still a shortcoming of this study, because the study only uses public datasets to analyze, verify and test, without clinical verification and test. Our research has provided help in distinguishing the stage and severity of Dengue infection and understanding pathogenic mechanism of different serotypes, and will help analyze mechanisms of DHF and benefit to clinical treatment in the future.CD38 and fractions of Plasma cells, activated memory CD4+ T cells and Monocytes, we can discriminate admirably three clinical stages for Dengue patients (results are suitable for any serotype); ZNF595 can better distinguish dengue hemorrhagic fever (DHF) from Dengue fever (DF). Up-regulated autophagy-related genes contribute to understand mechanisms of DHF.In conclusion, based on expression levels of Additional file 1. Figure S1. (A–C) PCA shows that different stages can be distinguished. Weighted co-expression network analysis (WGCNA). (D–F) Showing the cutoff height. (G–I) Sample clustering. (J) Shared gene (CCL2) in the LA stage between DEGs (between Dengue Hemorrhagic Fever (DHF) and Dengue Fever (DF)) and 232 autophagy-related genes, and (K) its expression levels. Similar expression levels of CD38 and CDKN1C between DH and DHF (L) and among different serotypes (M). S1, serotype I; S2, serotype II; S3, serotype III; S4, serotype IV. .Additional file 2. Figure S2. Analyzing staging diagnosis value of CD38 and CDKN1C for four serotypes among three comparison groups by Area Under the Curve (AUC) in the training set (GSE43777 dataset of GLP201 platform), respectively. (A) C vs EA in serotype I; (B) C vs LA in serotype I; (C) EA vs LA in serotype I; (D) C vs EA in serotype II; (E) C vs LA in serotype II; (F) EA vs LA in serotype II; (G) C vs EA in serotype III; (H) C vs LA in serotype III; (I) EA vs LA in serotype III; (J) C vs EA in serotype IV; (K) C vs LA in serotype IV; (L) EA vs LA in serotype IV. .Additional file 3. Figure S3. Analyzing staging diagnosis value of CD38 and CDKN1C for four serotypes among three comparison groups by Area Under the Curve (AUC) in the test set (GSE43777 dataset of GLP570 platform), respectively. (A) C vs EA in serotype I; (B) C vs LA in serotype I; (C) EA vs LA in serotype I; (D) C vs EA in serotype II; (E) C vs LA in serotype II; (F) EA vs LA in serotype II; (G) C vs EA in serotype III; (H) C vs LA in serotype III; (I) EA vs LA in serotype III; (J) C vs EA in serotype IV; (K) C vs LA in serotype IV; (L) EA vs LA in serotype IV. .Additional file 4. Figure S4. Violin diagrams and heatmaps display immune differences of immune cells in different comparing groups. (A) C vs EA stages in the serotype I. (B) C vs LA stages in the serotype I. (C) EA vs LA stages in the serotype I. (D) Immune difference heatmap of the serotype I in three stages. (E) C vs EA stages in the serotype II. (F) C vs LA stages in the serotype II. (G) EA vs LA stages in the serotype II. (H) Immune difference heatmap of the serotype II in three stages. (I) C vs EA stages in the serotype III. (J) C vs LA stages in the serotype III. (K) EA vs LA stages in the serotype III. (L) Immune difference heatmap of the serotype III in three stages. (M) C vs EA stages in the serotype IV. (N) C vs LA stages in the serotype IV. (O) EA vs LA stages in the serotype IV. (P) Immune difference heatmap of the serotype IV in three stages. .Additional file 5. Figure S5.  Correlation between CD38 and 22 types of immune cells ). (A) In serotype I; (B) in serotype II; (C) in serotype III; (D) in serotype IV. .Additional file 6. Figure S6. Analyzing staging diagnosis value of immune cells for Dengue by Area Under the Curve (AUC) in each serotype. (A) C vs EA stages in the serotype I. (B) C vs LA stages in the serotype I. (C) EA vs LA stages in the serotype I. (D) C vs EA stages in the serotype II. (E) C vs LA stages in the serotype II. (F) EA vs LA stages in the serotype II. (G) C vs EA stages in the serotype III. (H) C vs LA stages in the serotype III. (I) EA vs LA stages in the serotype III. (J) C vs EA stages in the serotype IV. (K) C vs LA stages in the serotype IV. (L) EA vs LA stages in the serotype IV. .Additional file 7. Table S1. Differentially expressed genes (DEGs) in the C vs EA group. .Additional file 8. Table S2. Differentially expressed genes (DEGs) in the C vs LA group. .Additional file 9. Table S3. Differentially expressed genes (DEGs) in the EA vs LA group. .Additional file 10. Table S4. Differentially expressed genes (DEGs) from comparing Dengue Hemorrhagic Fever (DHF) with Dengue Fever (DF) in EA group. .Additional file 11. Table S5. Differentially expressed genes (DEGs) from comparing Dengue Hemorrhagic Fever (DHF) with Dengue Fever (DF) in LA group. .Additional file 12. Table S6. Differentially expressed fold of genes in individual serotype for three comparison groups. .


We elucidated the functional significance and molecular mechanisms of DUSP5P1 lncRNA  in gastric carcinogenesis. We demonstrated that gastric cancer (GC) patients with high DUSP5P1 expression had shortened survival in two independent cohorts. DUSP5P1 promoted GC cell migration and invasion in vitro and metastasis in vivo. Mechanistically, DUSP5P1 activated ARHGAP5 transcription by directly binding to the promoter of ARHGAP5 with a binding motif of TATGTG. RNA-seq revealed that ARHGAP5 activated focal adhesion and MAPK signaling pathways to promote GC metastasis. DUSP5P1 also dysregulated platinum drug resistance pathway. Consistently, DUSP5P1 overexpression in GC cells antagonized cytotoxic effect of Oxaliplatin, and shDUSP5P1 plus Oxaliplatin exerted synergistic effect on inhibiting GC metastasis in vitro and in vivo. DUSP5P1 depletion also suppressed the growth of platinum drug-resistant PDO models. In conclusion, DUSP5P1 promoted GC metastasis by directly modulating ARHGAP5 expression to activate focal adhesion and MAPK pathways, serves as therapeutic target for platinum drug resistant GC, and is an independent prognostic factor in GC. Gastric cancer (GC) is the third leading cause of cancer-related mortality globally , 2. The Long noncoding RNAs (lncRNAs) are emerging as a central player in controlling diverse cellular mechanisms. Aberrant expression of lncRNA may have repercussions for cell proliferation, tumor progression, invasion and metastasis , 5. lncRWe reported that C8orf76 promotes GC tumorigenesis through directly binding to the promoter of lncRNA dual-specificity phosphatase 5 pseudogene 1 (DUSP5P1) to activate MAPK signaling . High exTwo independent cohorts of patients with histologically confirmed GC were included in the study. Cohort I included 112 paired GC tumor tissues and adjacent non-tumor tissues from Prince of Wales Hospital at the Chinese University of Hong Kong, Hong Kong, and Cohort II included 106 paired GC tumor tissues and adjacent non-tumor tissues from Peking University Cancer Hospital, Beijing, China. The detailed patient information is shown in Table Eight GC cell lines , normal gastric epithelial cell line GES1 and normal liver cell line LO2 were used in this study. AGS, NCI-N87, and LO2 were obtained from ATCC . BGC823, MGC803, SGC7901, and GES1 were obtained from Cell Research Institute . MKN74 and MKN45 were obtained from JCRB . HGC27 was obtained from RIKEN BRC Cell Bank . All cell lines have been obtained since 2014 and grown fewer than 20 passages. Cell authentication was confirmed by short tandem repeat profiling. Cells were cultured in Dulbecco’s modified Eagle’s medium  supplemented with 10% fetal bovine serum (Gibco BRL). Routine Mycoplasma testing was performed by PCR.6 cells) stably transfected with DUSP5P1 expression vector or its control vector, MKN45 cells (2 × 107 cells) stably transfected with DUSP5P1 sh-negative control (shNC) or shDUSP5P1 were injected into the tail vein (n = 10 per group) or abdominal cavity (n = 5 per group) of 6-week-old male Balb/c nude mice, respectively. Four weeks after injection, the mice were sacrificed and examined. The lungs or the celiac implantation tumor including the intestinal tract were dissected and paraffin-embedded. The sections were stained with hematoxylin and eosin (H&E). Metastatic tumors in the lungs or the celiac implantation tumor were counted in a blinded manner.To assess the effect of DUSP5P1 on tumor metastasis, BGC823 cells (1 × 107 cells) stably transfected with DUSP5P1 shNC or shDUSP5P1 were injected into the spleen of 6-week-old male Balb/c nude mice (n = 5 per group). Four weeks after injection, the mice were sacrificed and examined. Livers were dissected and paraffin embedded, and the sections were stained with haematoxylin and eosin (H&E). Metastatic tumors in the livers were counted in a blinded manner. All animal experimental procedures were approved by the Animal Ethics Committee of the Chinese University of Hong Kong.To establish the liver metastasis mouse model, MKN45 cells  using TMA and cell slides according to the protocol provided by the manufacturer. Probe sequences are listed in Table TM RNA Interactome Kits  [7 cells were prepared, crosslinked with 1% glutaraldehyde PBS, unreacted glutaraldehyde was quenched with glycine, and then lysed with lysis buffer. Sonication was used to break genomic DNA into small DNA fragments. Odd or even probes were added and used to hybridization DNA fragments corresponding to the gene regions for ChIRP reactions. Input was used as a control. The sequence of odd or even probes is listed in Table https://pypi.python.org/pypi/MACS/1.4.2) as compared with input. The lncRNA-binding motifs were identified using MEME software (http://meme-suite.org/).ChIRP assays were performed using Magna ChIRPo., USA) . BrieflyPDO models were established as previously described . BrieflyP value < 0.05 was taken as statistical significance, and all tests were two-tailed.The results were expressed as mean ± SD. Statistical analysis was performed using the Statistical Package for the Social Sciences (SPSS) (standard V.16.0) . Crude relative risks (RRs) of death associated with DUSP5P1 expression and other predictor variables were estimated by univariate Cox proportional hazards regression model. Multivariate Cox model was constructed to estimate the adjusted RR for DUSP5P1 expression. Kaplan–Meier analysis was used to compare the survival distributions of two groups with log-rank test. Mann–Whitney U test or Student’s t test was performed to compare the variables of two groups. Other details and additional experimental procedures are provided in Supporting Materials and Methods.P < 0.01, Fig. P < 0.05, Fig. n = 112, Cohort II: n = 106). The optimal cutoff value of DUSP5P1 expression was determined by ROC curve analysis     (Table P = 0.0154)    than those with low or silenced DUSP5P1 expression in Cohort I (18) Fig.  and Coho6) Table . Multiva2) Table . Moreove01) Fig.  and in C82) Fig. .P = 0.0005; PFS: P = 0.0017)  . Consistently, Kaplan-Meier survival analysis demonstrated that high DUSP5P1 expression predicted shortened OS and PFS for GC patients (OS: 17) Fig. , especia91) Fig. . High DUDUSP5P1 was highly expressed in 5 out of 8 GC cell lines , but was silenced in the normal gastric epithelial cell line GES1 Fig. . EctopicP < 0.05)   of the mice bearing BGC823-DUSP5P1 produced lung metastases, while only 40% (4/10) of the mice in BGC823-control vector cells exhibited lung metastases (5) Figs. , S2. Mor05) Fig. . We furt05) Fig. , S3.To confirm the effect of DUSP5P1 on metastasis, we evaluated the metastatic capacity of MKN45 cells with or without DUSP5P1 knockdown in three experimental metastasis models using tail vein (lung), abdominal (peritoneum) or intrasplenic (liver) injection, respectively. At the end of experiment, fewer tumor nodules were observed on the lung Figs. , S4 and To understand the molecular mechanisms of DUSP5P1 in promotion of GC metastasis, global gene transcriptional profiling was analyzed by RNA-sequencing in DUSP5P1-ectopic expressing MGC803 cells and their control counterparts. Our result showed that ectopic expression of DUSP5P1 significantly dysregulated twelve signaling pathways including focal adhesion, MAPK signaling, pathway in cancer, FOXO signaling, Cell adhesion molecules, tight junction, p53 signaling, platinum drug resistance, Ras signaling, AMPK signaling, mTOR signaling and Hippo signaling pathways. Among them, focal adhesion and MAPK signaling were the most enriched pathways Fig. . The majWe next analyzed the cellular localization of DUSP5P1 by RNA FISH after nuclear and cytoplasmic fractionation. Twenty-six probes of DUSP5P1 were designed for RNA FISH Table . RT-PCR P < 0.001, Fig. P < 0.05, Fig. Ectopic expression of DUSP5P1 significantly upregulated transcription and increased the expression of ARHGAP5 in BGC823, MGC803, and GES1 cells Fig. . MoreoveGiven that focal adhesion promotes MAPK pathway, the effect of ARHGAP5 on MAPK pathway was investigated by SRE luciferase reporter assay. ARHGAP5 depletion reduced MAPK activities in both AGS and MKN74 cells Fig. . The effPrevious reports indicated that focal adhesion molecules, MAPK signaling pathway and specific lncRNA in tumor cells induced resistance to chemotherapy , 14. OurThe synergistic effect of the combination of DUSP5P1 depletion and Oxaliplatin on cell migration was then investigated. MKN74, MGC803 and AGS cells with stable knockdown of DUSP5P1 were treated with Oxaliplatin at 25 μmol for 36 h. Combined Oxaliplatin treatment and shDUSP5P1 showed a synergistic effect on suppressing the cell migration as compared with DUSP5P1 depletion alone Fig. . To confIn this study, we found that DUSP5P1 is highly expressed in GC tumor tissues. High expression of DUSP5P1 is associated with poor prognosis of GC patients independent of their clinical pathological features, especially for early stage GC patients, implying that DUSP5P1 is an independent prognostic factor of GC patients.A series of bio-functional experiments revealed that DUSP5P1 significantly promoted cell migration/invasion abilities in vitro, and lung, liver, and peritoneal metastasis of GC cells in nude mice in vivo; whilst depletion of DUSP5P1 by shRNA in MKN45 cells inhibited lung and liver metastasis in vivo. These results collectively confirmed the pro-metastatic effect of DUSP5P1 in GC. Concomitantly with the promotion of metastases, we demonstrated that DUSP5P1 facilitated EMT transition through the upregulation of mesenchymal critical regulators   and downThe molecular mechanisms by which DUSP5P1 exerts its pro-tumorigenesis and pro-metastases functions in GC were then investigated. We demonstrated that DUSP5P1 caused significant dysregulation of signaling pathways, in particular, focal adhesion and MAPK signaling, which are the key regulating pathways of cancer progression and metastasis , 17. We As DUSP5P1 was localized primarily to the nucleus, we hypothesized that DUSP5P1 may regulate transcription in GC. We performed integrated ChIRP-sequencing  and RNA-Emerging reports indicate that lncRNAs predict responsiveness to chemotherapy and may function as potential drug targets . We therIn conclusion, our study reported for the first time that lncRNA DUSP5P1 is a novel tumor metastasis-promoting factor in GC. The molecular mechanisms of DUSP5P1 as a tumor-promoting factor involved direct induction of the tumor promoting factor ARHGAP5, resulting in the activation of focal adhesion and MAPK signaling pathways Fig. . DUSP5P1Supplemental material and methodsSupplemental figuresSupplemental tables


R) genes, such as LepR1, against Leptosphaeria maculans, the causal agent of blackleg in canola (Brassica napus), could help manage the disease in the field and increase crop yield. Here we present a genome wide association study (GWAS) in B. napus to identify LepR1 candidate genes. Disease phenotyping of 104 B. napus genotypes revealed 30 resistant and 74 susceptible lines. Whole genome re-sequencing of these cultivars yielded over 3 million high quality single nucleotide polymorphisms (SNPs). GWAS in mixed linear model (MLM) revealed a total of 2,166 significant SNPs associated with LepR1 resistance. Of these SNPs, 2108 (97%) were found on chromosome A02 of B. napus cv. Darmor bzh v9 with a delineated LepR1_mlm1 QTL at 15.11-26.08 Mb. In LepR1_mlm1, there are 30 resistance gene analogs (RGAs) (13 nucleotide-binding site-leucine rich repeats (NLRs), 12 receptor-like kinases (RLKs), and 5 transmembrane-coiled-coil (TM-CCs)). Sequence analysis of alleles in resistant and susceptible lines was undertaken to identify candidate genes. This research provides insights into blackleg resistance in B. napus and assists identification of the functional LepR1 blackleg resistance gene.Utilising resistance ( Brassica napus L.  is one of the most important crops for edible oil, food and industrial purposes  gene and an avirulence (Avr) gene  gene . These Rlt stage . On the lt stage . Both tyR gene in the genome, genetic mapping of genotypic variants is frequently undertaken. Two of the most common approaches for genetic mapping are association mapping, or genome wide association studies (GWAS), and biparental linkage mapping. GWAS is an alternative approach to traditional mapping of biparental populations and has been widely used in B. napus  encoding a receptor-like protein (RLP), while Rlm4, Rlm7 and Rlm9 are also allelic variants of an RGA encoding wall-associated kinases (WAKs) -leucine rich repeats (LRR)  . Other bts (LRR) . One of B. napus . This stL. maculans isolates were used to genotype B. napus genotypes for the presence or absence of resistance gene LepR1. All isolates and their genotypes (-5) of each L. maculans isolate were dropped onto cotyledons of wounded ten-day-old seedlings grown in the glasshouse at 22°C. Disease symptoms were scored at 14 days post-inoculation on a 0-9 scale, as previously described  were used in this study  according to the manufacturer’s instructions. Total DNA was quantified using a Qubit 3.0 Fluorometer and the Qubit dsDNA BR Assay kit , while DNA quality was assessed using the LabChip GX Touch 24 . WGRS of the cultivars was carried out using an Illumina NovaSeq™ 6000 Sequencing System by GeneWiz , which generated approximately ~6 Gb of 150 bp paired-end sequencing data per cultivar.A total of 104 Australian is study Table S2From the WGRS data, raw FASTQ files were trimmed of adapter sequences and low quality bases using Trimmomatic v0.39  with a mB. napus genome cv. Darmor bzh v9 (https://github.com/samtools/bcftools). Duplicate reads were removed using samtools markdup. SNPs for each individual were called using bcftools v.1.10  plot in mixed linear model (MLM) with PCA  + Kinship matrix for family relatedness estimates (K) , were co markers . The phe markers . Figure  markers .LepR1 introgressed lines and structural variants, derived from the results of L. maculans containing AvrLep1 screened at the cotyledon stage  were visualised in Geneious R10  nearest to the LepR1 QTL identified in this study. The marker development was done in two stages. First, markers flanking each candidate were designed using the Primer3 function in Geneious R10   (The WGRS data of 104 ty SNPs) Table S3markers) .LepR1 resistance were identified across 10 chromosomes  at the 1.58 E-08 cut-off value, implemented with Bonferroni correction and FDR , however only 9 of them contained RGAs S6 and wLepR1 blackleg resistance were found in chromosome A02 in B. napus cv. Darmor bzh v9 (LepR1_mlm1) was 11.07 Mb in length (15.11-26.18 Mb)  of the total significant SNPs associated with r bzh v9 Table S3LepR1 introgression line (cv. Topas), mapped in genome cv. Darmor bzh v4.1 , LepR1_TLepR1, LepR1_SV, and LepR1_meta contained 1915 genes (46 RGAs), 344 genes (8 RGAs), and 1434 genes (20 RGAs), respectively  were also within the intervals of the LepR1_TLepR1 and LepR1_SV , with 17 having SNPs in the CDS region (CDS-SNPs)  (LepR1 candidate gene were 12 in BnaA02g25110D3 (RLK), 11 in BnaA02g31910D3 (RLK), BnaA02g33310D3 (RLK) and BnaA02g34160D3 (TM-CC), 10 in BnaA02g33320D3 (NLR) and 8 in BnaA02g26040D3 (RLK) (Eighteen (60%) out of the 30 RGAs underlying n total) Table 2.LepR1 candidates  had at least 4 SNPs in their CDS regions between resistant and susceptible lines  of Darmor bzh genomes (v4.1 or v8.1). For instance, Darmor bzh v9 has a total size of 1,043.4 Mb compared to the 850.3 Mb of Darmor bzh v4.1  .LepR1_meta was based on adult plant survival rate and average internal infection of the stem at maturity stage paired with imputed SNPs, a methodology that would identify quantitative instead of qualitative blackleg resistance in B. napus  kinase 9 (BnMPK9), BnaCnng11720D or C05p48150.1_BnaDar on C05 (R gene Rlm1 on A07 and pathogen effector AvrLm1 (Suppresor of BAK1-interacting receptor like kinase 1 (SOBIR1) genes on A03 and C03 (BnaA03g14760D and BnaC03g17800D) are also required for the blackleg resistance of the alleles LepR3 and Rlm2 (BnaA10g20720D) of A10 to effectors AvrLm1 and AvrLm2, respectively (The few significant SNP associations on C01 and C02 (having RGAs in the QTL) could possibly be due the incorrect mapping of DNA sequences containing notable SNPs that occurred during the genome assembly process in B. napus . Another and C02 , indicat thought . Functior on C05 , is an er AvrLm1 . Furtherectively .LepR1 gene. The CDS-SNPs of these RGAs could alter amino acids (aa) of the predicted proteins explaining the difference between susceptible and resistant phenotypes. Among the SNP types, a nonsense SNP leads to a premature stoppage of the amino acids, potentially changing the gene expression among cultivars with different genotypes. Although this study did not examine gene expression between cultivars with different LepR1 phenotypes, previous studies have shown that RLKs and NLRs were significantly expressed in LepR1 resistant cultivars  genes RPM1 against Pseudomonas syringae  can be found below: NCBI accession PRJNA885991.B. napus materials including DNA extraction. AV provided the phenotype data. AS-E, NS and RA provided bioinformatics support by calling SNPs on the reference B. napus cv. Darmor-bzh v9 genome and statistical codes. AC designed the primers/markers and prepared the materials for sequencing analysis. JB supervised, reviewed, and suggested revisions to the paper. All authors contributed to the article and approved the submitted version.AC and JB conceptualized the paper. AC wrote the original draft along with formal analyses. WT, PB, DE, and AV helped improve the paper by suggesting additional ideas and by thorough revision/editing. AC and NS planted the