dataesr/scientific-paragraphs-categorization huggingface dataset:
, 2017). To generate the fungal species phylogenetic tree, single copy gene families were identified by orthoMCL  (Li et al. , 2003)  from the 32 fungi analyzed using all-vs-all BLASTp with a cut-off E-value of 1E-5 and an inflation value of 1. 5. Sequences from individual gene families were aligned using MAFFT and trimmed using trimAl  (Katoh et al. , 2002; Capella-Gutiérrez et al. , 2009)  as described above. Then, trimmed alignments from the 501 single copy gene families identified were concatenated resulting in a dataset of 227,412 sites. The concatenated alignment was used for RAxML analysis which was carried out as described above. Rhizophagus irregularis was set as the root using FigTree v1. 4. 2  (Rambaut, Andrew)  in the best estimated tree, which was then converted to an ultrametric chronogram using r8s version 1.
Prediction of SRN homologs in 22 Colletotrichum species Using amino acid sequences of C. orbiculare SRN1, SRN2, SRN3. 1, SRN3. 2, and SRN4 as queries, genomes of 22 Colletotrichum species were searched by Exonerate version 2. 2 software. Proteins lacking signal peptides predicted by SignalP 4. 1 software  (Petersen et al. , 2011)  were removed. The sequences were aligned using Molecular Evolutionary Genetics Analysis (Mega) Version 7. 0  (Kumar et al. , 2016). The phylogenetic tree of the SRN homologs was then drawn using the same software.
Among them, we found that one of the C. orbiculare effector candidates induced cell death (Fig. 1b ) when expressed transiently in N. benthamiana. The gene that induced cell death (Locus tag: Cob_v010174) was named SECRETED RIBONUCLEASE 1 (SRN1), due to the presence of the ribonuclease domain (Pfam database: PF00545, NCBI's conserved domain database: cd00606) and the signal peptide sequence (Fig. 1c ). The C. orbiculare genome is predicted to encode three other SRN1-like genes and we therefore termed them as SRN2, SRN3 and SRN4 (Supporting Information Fig. S1a , Table  S6 ). By cloning the coding sequences from the cDNA of C. orbiculare we found that each gene transcript had a single isoform except for SRN3, which had two different isoforms (denoted as SRN3. 1 and SRN3. 2) (Fig. 1c ). Divergence dates were estimated based on a maximum likelihood tree constructed from 501 single copy genes in all the analyzed fungi using the program r8s.
sativus cotyledons. Next, we examined the chitin-triggered ROS bursts in C. sativus cotyledons expressing either SRN1-HA, SRN2-HA, SRN3. 1-HA, SRN3. 2-HA, or SRN4-HA (Fig. 4a ). Remarkably, SRN1-HA and SRN2-HA significantly enhanced chitin-triggered ROS bursts compared to GFP controls. On the other hand, SRN3. 1-HA, SRN3. 2-HA, and SRN4-HA did not, despite the detectable proteins accumulated (Fig. 4b ). These data indicated that SRN1 and SRN2 leads to immune responses in host plants.
The H130 ribonuclease catalytic residue of SRN2 was mutated in SRN2 H130A -HA. Both H75 and H130 ribonuclease catalytic residues of SRN2 were mutated in SRN2 H75A/H130A -HA. The predicted signal peptide of SRN2 was deleted in SRN2 ΔSP -HA. Experiments were performed as described in (a). Data represent mean ±SE (n=3). (f) Expression of wild-type and mutated series of SRN2 (SRN2-HA, SRN2 H130A -HA, SRN2 H75A/H130A -HA, and SRN2 ΔSP -HA) was confirmed by immunoblot analysis. The estimated molecular weight of each protein is as follows; SRN2-HA, SRN2 H130A -HA, and SRN2 H75A/H130A -HA: 22. 9 kDa, SRN2 ΔSP -HA: 21. 2 kDa. ** indicates p < 0. 01 (t-test) (a, c, e). Anti-HA antibody was used to detect HA-tagged proteins (b, d, f). Coomassie-stained RBCL proteins were used as loading controls (b, d, f).
7e ), suggesting the ribonuclease catalytic residues or activity are monitored by host to drive the immunity. We also assessed the relative fungal biomass levels, which was probed by C. orbiculare transcripts (especially ribosome protein L5), during infection on C. sativus leaves. Consistent with the invasion ratios, srn1 srn2 double mutants showed significantly increased fungal biomass (Fig. 7c ). Collectively, our data indicates that SRN1 and SRN2 in C. sativus enhance defense responses of the host plant to this fungi.
Acknowledgements We thank  Drs. Satoko Nonaka  and  Hiroshi Ezura  for providing the pBBRgabT plasmid,  Drs. Mikiko Sodeoka  and  Kosuke Dodo  for sharing equipment, and  Dr. Yasuhiro Kadota  for critical reading of the manuscript. This work was supported by  Cooperative Research Grant  of the  Plant Transgenic Design Initiative  (PTraD) by  Gene Research Center ,  Tsukuba-Plant Innovation Research Center (University of Tsukuba) ,  RIKEN   Special Postdoctoral Researcher Program  (NK),  JSPS   KAKENHI JP18K14440  and  JP20K15500  (NK),  JP19K15846  (PG),  JP17J02983  (AT),  JP21H05032  (YT),  JP17H06172  (KS),  JP19H02959  (SI),  JST ACT- X Grant number  JPMJAX20  (NK), The  Program for Promotion of Basic and Applied Researches for Innovations in Bio-oriented Industry  (BRAIN;  10103721 ) (KS),  Council for Science, Technology and Innovation (CSTI) (KS) , and  Cross-ministerial Strategic Innovation Promotion Program  (SIP) (YN, YT, and  KS ) " Technologies for creating next-generation agriculture, forestry and fisheries ".
(d) Cell death phenotypes of SRN1, SRN2, SRN3. 1, SRN3. 2, and SRN4 expressed as in (b). (e) PF00545 ribonuclease domain-containing proteins are highly conserved in fungi. Numbers of PF00545 ribonuclease domain-containing proteins in different fungi. Divergence dates were estimated based on a maximum likelihood tree constructed from 501 single copy genes in all the analyzed fungi using the program r8s.
Full-length amino acid SRN homologs (Supporting Information Table S7). because SRN1 encodes the domain. Genes encoding PF00545 domains were conserved in bacteria and fungi, especially in Ascomycota, but not in plants and animals (Pfam 34. 0) (Mistry et al. , 2021)   (Fig. 1e , 2), suggesting that PF00545 is the microorganisms specific domain. In fungi, all 26 Pezizomycotina species tested were predicted to encode proteins with the PF00545 domain. However, most species belonging to the Glomeromycota and Basidiomycota did not have the PF00545 domain, except for Ustilago maydis, a causal agent of corn smut. sequences of C. orbiculare SRN1, SRN2, SRN3. 1, SRN3. 2, and SRN4 were used to query the whole genome sequences of the 22 species. All species tested had at least two.
Acknowledgments This is the Insight contribution number  143  and IPGP contribution number XXX. We acknowledge  NASA ,  CNES , their partner agencies and Institutions (UKSA,  SSO ,  DLR ,  JPL ,  IPGP-CNRS, ETHZ, IC, MPS-MPG ) and the flight operations team at  JPL ,  SIS-MOC, MSDS, IRIS-DMC  and  PDS  for providing SEED SEIS data. French authors are manuscript submitted to JGR: Planets.
Matrix-Assisted Laser Desorption/Ionization-Time-of-Flight-Mass Spectrometry (MALDI-TOF-MS) Matrix-assisted laser desorption/ionization-time-of-flight-mass spectrometry (MALDI-TOF-MS) analysis was performed using the AutoflexSpeed TM (Bruker, Berlin, Germany) mass spectrometer running the Flexcontrol 3. 4 software (Bruker). The mass spectrometer was calibrated according to the recommendations of the manufacturer. Mass spectra were acquired in the negative linear-ion mode using the automatic negative linear method of the manufacturer across a massto-charge (m/z) ratio of 100-2,000 atomic mass unit. The mass spectra correspond to mass signals summed from 2,000 laser shots in 100 shot steps performed randomly on different areas of the spot. Ulvan was solubilized at 10 mg. ml -1 in ultrapure (MQ) water, while 2,5-dihydroxybenzoic acid (DHB), used as the MALDI matrix, was dissolved at 10 mg.
Four categories of germlings were recorded: non-germinated spore (NGS), germinated spore with a short germ tube (GS-SGT), germinated spore with a well-developed germ tube (GS-DGT), and germinated spore with branched hyphae (GS-BH). Pictures were taken with a digital camera (DXM1200C, Nikon) using image capture software (Nis-Elements BR, Nikon). To measure the colonization of the substomatal cavities, 4-cm third-leaf segments were collected at 21 dai and then bleached in a mixture of absolute ethanol and acetic acid (3:1; v/v) overnight. The cleared leaves were rehydrated in distilled water for 4 h and then fixed in lactoglycerol (lactic acid: glycerol: water; 1:1:1; v/v/v) for 20 min. The fungal structures were stained by immersing the leaf segments in 0. 1% Trypan blue (Sigma-Aldrich, Saint Quentin Fallavier, France) dissolved in lactophenol-ethanol (1:2; v/v) at 50 • C for 20 min.
Parameters were set at 300 • C for the ion transfer capillary temperature and 2,500 V for the needle voltages. Nebulization with nitrogen sheath gas and auxiliary gas was maintained at 60 and 15 arbitrary units, respectively. The spectra were acquired within the massto-charge ratio (m/z) ranging from 100 to 1,000 atomic mass unit, using a resolution of 50,000 at m/z 200 atomic mass unit. The system was calibrated internally using dibutyl-phthalate as the lock mass at m/z 279. 1591, giving a mass accuracy lower than 1 ppm. The instruments were controlled using the Xcalibur software (Thermo Fisher Scientific). Metabolites were sought based on the calculated m/z of the corresponding pseudo-molecular ion [M + H] + from a list of metabolites of interest using a suspect screening approach  (Krauss et al.
, 2010; Flamini et al. , 2013). The previous wheat metabolome characterizations were used for a detailed analysis of the metabolites of interest in specific chemical families such as benzoxazinoids  (de Bruijn et al. , 2016) , flavonoids  (Wojakowska et al. , 2013) , and hydroxycinnamic acid amides  (Li et al. , 2018). Putative metabolite identifications were proposed based on expertized analysis of the corresponding mass spectra and comparison with published literature. Further information was retrieved from the Kyoto Encyclopedia of Genes and Genomes (KEGG 1 ) and PubChem 2  databases. Relative quantification of the selected metabolites was performed using the Xcalibur software. For some metabolites, identity was confirmed with the corresponding standard provided by Sigma-Aldrich (France).
Experimental Design and Statistical Analyses The in vitro microscopic assays were conducted in a completely randomized design with five replications, each composed of one Petri dish. All experiments performed in planta in the greenhouse, including protection efficacy, cytological, gene expression, and metabolomic analyses, were carried out in a factorial completely randomized design with two factors: treatment (water or ulvan) and inoculation (Z. tritici or mockinoculated plants). Three replications (pots), each composed of three plants, were used for each condition. After verification of the variance homogeneity of the data sets, data were subjected to ANOVA. Comparisons between data obtained for disease severity, pycnidium density, and all assessed in planta cytological events, as well as for in vitro spore germination and mycelial growth assays, were carried out with Student's t-test at a significance level of P ≤ 0.
05. Heatmaps were performed using the package ComplexHeatmap  (Gu et al. , 2016)  after Log2 transformation data. Principal component analysis (PCA) was constructed in the package vegan  (Oksanen et al. , 2019). The statistical analyses were performed using the software R version 3. 5. 1 (R Core Team, 2018). All experiments were repeated three times and the values presented in this study are the average of the three experiments.
ACKNOWLEDGMENTS MB is grateful to the  Brazilian agency Coordination for the Improvement of Higher Education Personnel (CAPES)  for the doctoral scholarship. MS is a research member of the  National Council and Technological Development (CNPq). We are also grateful to the REALCAT platform funded by a  French governmental grant  administered by the  French National Research Agency (ANR)  as part of the frame of the " Investments for the Future" program  ( ANR-11-EQPX-0037 ).
Despite growing evidence that diverse forests play an important role in ecosystem functioning, ensuring the provision of different ecosystem services, whether such diversity improves their response to drought events remains unclear. In this study, we use a large tree-ring database from thirty case studies across nine European countries and eleven species, covering from Mediterranean to hemiboreal forests, to test if the growth response to site specific drought events that occurred between 1975 and 2015 varied between mixed and monospecific stands. In particular, we quantify how stands resist those specific drought events and recover after them, thus analyzing their resilience. For each drought event and forest stand we calculated resistance, recovery, resilience and relative resilience and we related the variation in these indices between monospecific and mixed stands with type of admixture, tree species identity, site aridity gradient, stand basal area and stand age.
2016). Vulnerability to water stress for a given species may also depend on stand basal area  (Forrester et al. 2016) , stand density  (Bottero et al. 2017 ) and stand age  (Sohn et al. 2016). These are important issues to consider when conducting studies across large geographical scales, where local site characteristics, climate conditions, forest management, forest type, tree species assemblages (and their related functional traits) are likely to interact, making the identification of species mixture effects more complex  (Grossiord, 2019; Bello et al. , 2019). In this study, we used tree ring data from thirty case studies covering from Mediterranean to hemiboreal forests and eleven tree species to test whether the response of mixed stands to drought events differed to that of monospecific stands.
Experimental sites This study was performed using data from 30 case studies spread over 9 countries that represent different European forest stands, including both natural forests and plantations. Stands were located along a gradient from hemiboreal to Mediterranean forests, spanning from central Spain to northern Latvia (Table  A1 , Fig. 1 ). Altogether, the case studies cover the main admixtures found across Europe, including conifer and conifer (Pinus-Juniperus; Pinus-Pinus; Pinus-Picea; Picea-Abies; Larix-Pinus; Larix-Picea), conifer and broadleaved (Pinus-Quercus; Pinus-Fagus; Picea-Fagus; Larix-Quercus, Larix-Alnus, Larix-Tilia) and broadleaved and broadleaved (oak-beech). We considered many important tree species for the bioeconomy of European forests such as Fagus sylvatica, Quercus pyrenaica, Quercus petraea, Quercus robur, Quercus pubescens, Pinus sylvestris, Pinus pinaster, Pinus pinea, Pinus nigra, Picea abies, Abies alba and Larix decidua, with most tree species occurring in several case studies.
Data collection and dendrochronological analyses Two perpendicular increment cores at breast height were taken per tree. The total number of trees cored was 3,298 trees (Table  A2 ). Annual ring widths were measured from each increment core using standardised dendrochronological techniques  (Speer 2010). At the end of the growing season, when cores were taken, different dendrometric variables were measured on each plot, both at tree (diameter at breast height of all trees in each plot) and stand level (mean diameter, mean height, basal area and tree density). To analyze the effect of drought on tree growth we calculated the tree basal area increment (BAI, cm 2 ), using mean annual ring width of both increment cores: BAI = π/4 ( d 2 t -d 2 t-1 ) (1) where d t and d t-1 are the tree diameter at breast height at the end (d t ) and the beginning (d t-1 ) of a given annual ring increment corresponding to rings formed in year t and year t-1, respectively.
To eliminate the biological growth trends and to produce stationary and residual tree ring width chronologies  (Fritts et al. , 1990)  we used a detrending procedure and an autocorrelation removal with the Friedman supersmoother spline  (Friedman, 1984)  and autocorrelation modeling. Through this procedure we obtained chronologies of dimensionless indices (CDI), preserving a common variance with interannual time scales. To assess the reliability of the chronologies, we calculated descriptive statistics using "dplR" R package  (Bunn 2010)  for each species and plot, including Rbar (mean interseries correlation) and EPS (expressed population signal of detrended BAI series) (Table  A2 ). Rbar has been used to measure the strength of the common growth signal within each chronology  (Wigley et al 1984) , while EPS is used to measure the reliability of chronologies  (Lindholm et al.
Climate data We used climate data on a monthly basis (precipitation, mean, maximum and minimum temperature) for each case study. Climate data were obtained from meteorological stations nearby each case study site. When data were not available, they were obtained from the CGMS database (AGRI4CAST, http://mars. jrc. ec. europa. eu/mars). Monthly data were used to calculate mean annual temperature (T, • C) and annual precipitation (P, mm) from 1975 to 2015 (see Figure  A1  for the relationship between mean annual temperature and total annual precipitation). For characterizing the climatic water supply for each case study, we used the annual De Martonne aridity index (DMI, mm • C -1 ) (Eq. (  2 )) and De Martonne aridity index for the summer months (June, July and August) (DMI summer , mm • C -1 ) (Eq.
We used the pointerRES R package (Van der  Maaten-Theunissen et al. , 2015)  that uses the normalization in a moving window, relating tree growth in a year to the average growth of a fixed number of preceding years. In our study, we used a window width of four years. Years were considered as pointer when at least 60% of the de-trended BAI series of at least one of the two species in the monospecific plots of each study site showed an episode that indicated a growth decrease of 75% compared to the mean value. Lastly, in order to confirm that these periods of growth reduction corresponded to drought conditions rather than to other biotic (e. g. pests and diseases) or abiotic (e. g. frosts) factors, we chose years that were both drought years and pointer years. Site specific drought events were then used to evaluate the relationship between the reduction in tree growth and drought in monospecific and mixed stands.
(  8 ) to the whole database. Y ijkl = μ + SCM jk + CS k + D kl + ε ijkl (8) where Y refers to the response variable (Rc, Rt, Rs or RRs); SCM represents the fixed effect for stand composition (Mixed or Monospecific); CS and D are random effects of case study and drought event, respectively, D being nested into the case study. Finally, μ is the intercept of the model and ε ijkl represents the independent and identically distributed residual error. Subscripts i, j, k and l refers to the i th tree within the j th plot of the k th case study, for the l th drought event. Hypotheses II: The benefits of mixture to cope with drought events cannot be generalized to the three types of admixtures found  (conifer-conifer, conifer-broadleaved and broadleaved-broadleaved)  To check whether the effect of stand composition (mixed vs monospecific) on tree growth response to drought events were dependent on the three types of admixtures found (TM, Table  A3 ), we fitted Eq.
Influence of stand composition (monospecific vs mixed stands) on tree growth response to specific drought events When considering the whole database with 30 case studies (Hypothesis I) we observed that overall mixed stands showed greater resistance (P-value = 0. 0564), resilience (P-value < 0. 0001) and relative resilience (P-value = 0. 0283) compared to monospecific stands, while no significant differences were detected for recovery (Fig. 2 ). Interestingly, monospecific stands showed a slight growth decline after the drought event (Rs = 99%), while growth slightly increased in mixed stands after the drought event (Rs = 102%). Despite these general trends, we detected a large variability among case studies, even for those case studies that share the same species composition and have similar climates (Figure  A3 ).
Discussion In line with a number of recent studies (e. g. Pretzsch et al. 2013; Metz et al. 2016; Jucker et al. 2016; Steckel et al. , 2020) , our results using a large database from thirty case studies covering a wide climatic gradient and including eleven common tree species in Europe indicated, on average, a positive effect of mixing on tree growth response to drought, especially on resilience and relative resilience and to a lesser extent on resistance. However, we found a large species-specific variability in growth response to drought in monospecific and mixed stands, being mediated by the type of admixture and more particularly the association of conifers and broadleaves. Moreover, the general positive effect of mixing on resilience to drought was influenced by stand age and basal area, while relative resilience was influenced by stand age.
Acknowledgements The study was supported by the  ERA-Net   SUMFOREST  project  RE-FORM  "Mixed species forest management. Lowering risk, increasing resilience" ( PCIN2017-026 ) and  Marie Sklodowska Curie Actions-RISE ,  CARE4C. Special thanks to  Nuria Simón  and  Guillermo Madrigal  for their assistance building up the common database. All coauthors thank their national funding institutions for supporting the establishment, measure and analysis of core data in the studied plots. Research at the Polish case studies was additionally supported by the  Ministry of Science and Higher Education of the Republic of Poland  (No  W117/H2020/ 2018 ).
Popular GPU implementations of these projection and backprojection operators are also often unmatched as it is the case in the ASTRA software package  [56]. State-of-the-art matched projection/backprojection pairs rely on advanced interpolation schemes that are difficult to parallelize on GPU  [16, 43, 44]. Using an unmatched pair to reduce the computational costs however endangers the convergence of the reconstruction algorithm. It is an open problem to know whether errors will accumulate over iterations  [1, 60]  and lead to suboptimal reconstruction compared to having a matched pair. The literature remains scarce on the influence of such mathematical approximation on the convergence of PGA. When the objective function is a least-squares term without any regularization, PGA is reduced to a simple gradient algorithm.
Note that, in both experiments, the noise variance σ 2 is kept small to emphasize that sub-sampling is the main issue (as it is the case in interventional C-arm CBCT imaging) while still avoiding to commit an 'inverse crime' simulation. All the simulations were performed with the ASTRA Toolbox  [56]  implemented on Matlab, which allows the explicit computation of matrices H and K. In both experiments, matrix H was computed using ASTRA line-length ray driven projector  [62] , while K was generated using the pixel-driven backprojector  [58]. Note that the latter corresponds to the default choice in the GPU implementation for backprojection in ASTRA. All iterative reconstructions are initialized with x 0 equal to the null vector of R N. The regularization parameters were tuned empirically with a grid search so as to reach a satisfying reconstructed image quality.
Building a reference image dataset capturing ovule primordium development at cellular resolution To generate a reference image dataset describing ovule primordium development in 3D and with cellular resolution, we imaged primordia at consecutive stages in intact carpels by confocal microscopy. Carpels were cleared and stained for cell boundaries using a modified PS-PI staining  (Truernit et al. , 2008)  and mounted using a procedure preserving their 3D integrity (Mendocilla Sato and Baroux, 2017; Figure  1A ). We selected high signal-to-noise ratio images and segmented them based on cell boundary signals using Imaris (Bitplane, Switzerland) as described previously (Mendocilla Sato and Baroux, 2017; Figure  1B ). We manually curated 92 ovules representing seven consecutive developmental stages (7-21 ovules per stage, Figure  1B , Table  1 , Figure 1-source data 1) and classified them according to an extended nomenclature (explained in Materials and methods).