dataesr/scientific-paragraphs-categorization huggingface dataset:
The data are means 6 SD from one representative experiment, and significant differences were determined with an ANOVA with a posthoc Tukey's test, indicated by letters (P < 0. 05, n 5 24; Supplemental Data Set 3). (F) to (H) Quantification of the root length (F), lateral root number (G), and lateral root density (H) of the transgenic roots of control and overexpression plants as described in (E). Similar results were obtained in two independent experiments. The data are means 6 SD from one representative experiment, and significant differences were determined with a Kruskal-Wallis test (***, P < 0. 001, n 5 30; Supplemental Data Set 3). (I) Relative expression of the MtYUC2 transgene, as analyzed by RT-qPCR, showing that the expression level of MtYUC2 corresponds with the number of lateral roots observed in (E); OE1, OE2, and OE3 correspond to the representative roots OE1, OE2, and OE3 in (E).
Finally, we used liquid chromatography-mass spectrometry (MS) to quantify endogenous IAA concentrations in roots of R108 and cra2 with or without NO 3 2 (10 mM). These quantitative data showed that the free IAA content was reduced under low-nitrate conditions in R108 roots compared with that under high-nitrate conditions, but this effect was not observed in cra2 roots. In addition, cra2 roots had a significantly higher IAA content compared with R108 roots under low-nitrate conditions (Figure  4D ). These results collectively suggest that MtCEP1/MtCRA2 may control RSA by repressing MtYUC2 expression under low-N conditions, thereby reducing the auxin accumulation and response in root apical meristems.
05 and **, P < 0. 01; Supplemental Data Set 3). ns, nonsignificant. (C) Representative images of DR5:GUS staining of root tips (top) and emerging lateral roots (bottom) from two independent lines stably transformed with DR5:GUS in R108 or cra2-8. Germinated seedlings were grown in Fåhraeus medium containing 0. 25 or 10 mM KNO 3 for 10 d. Images were acquired with an Olympus microscope equipped with an interference device. Bars 5 100 mm. (D) Free IAA content in the roots of cra2T-4 and R108 grown with 0 or 10 mM KNO 3 for 7 d. The data are means 6 SD of three independent pools of roots, and significant differences were determined with an ANOVA with a posthoc Tukey's test, as indicated by letters (P < 0. 05; Supplemental Data Set 3). A quantitative phosphoproteomic approach was then comparatively applied for the roots and shoots of cra2 and R108.
The full-length MtEIN2-HA protein (146 kD) and C-terminal fragments of MtEIN2 (40 to 100 kD) are indicated. The Pro35S:MtEIN2-HA construct also contains a Pro35S:GUS fusion, and GUS was used as a loading control. (J) The quantification of the intensity of immunoblot bands, as analyzed using ImageJ software. The values show the percentages of the full-length MtEIN2 protein pool relative to the total of the MtEIN2 protein pool. The data are means 6 SD of three independent experiments based on three independent pools of roots, and significant differences were determined with an ANOVA with a posthoc Duncan's test, as indicated by letters (P < 0. 05; Supplemental Data Set 3). and no significant changes in ethylene levels were detected between cra2 and R108, prompting the suggestion that MtCEP1 peptides may repress ethylene signaling in an MtCRA2dependent manner to promote rhizobial infections and nodulation  (Mohd-Radzman et al.
RNA-Seq Analysis and RT-qPCR Total RNA was extracted with the TRIzol reagent (Invitrogen) from roots and shoots of cra2T-4 and R108 grown in Fåhraeus medium without N for 1 week and then inoculated with Sm1021 for 5 d. Three independent pools of tissue were prepared for all samples. RNA integrity was analyzed using 2% (v/v) agarose electrophoresis assays, and quantification was performed using a NanoDrop 2000 spectrophotometer. To generate a nondirectional Illumina RNA-seq library, 3 mg of total RNA was used, and sequences were generated using an Illumina HiSeq 2500 platform (raw data available from the China National GeneBank under accession number CNP0000354 with the link https://db. cngb. org/search/project/ CNP0000354/). Sequence reads were aligned to the M. truncatula reference genome (IMGA version 4.
0). The mapping rate of total reads in each sample was >83%. DEGs were filtered using the following criteria: fold change > 1. 5, P < 0. 01, and adjusted P < 0. 05. KOBAS (2. 0) was used to identify enriched DEGs in Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, and the 20 most significantly credible pathways were selected. RT-qPCR was used to confirm RNA-seq expression data for selected genes related to phytohormone biosynthesis and response as well as defense response genes. All primers used are listed in Supplemental Data Set 2. RNA was extracted with Trizol reagent (Invitrogen) from roots of cra2 and R108 treated with MtCEP1 peptides [synthesized with sequence AFQP(hyp)TTPGNSP(hyp)GVGH by GL Biochem] or inoculated with Sm1021 for 0, 1, 3, and 5 d. To test the expression of MtYUC2 in response to N starvation or MtCEP1, cra2 and R108 were grown in Fåhraeus medium supplemented with 10 mM KNO 3 for 10 d and then transferred to Fåhraeus medium without N or to Fåhraeus medium (10 mM KNO 3 ) supplemented with 1 mM MtCEP1 peptide for 2, 8, 12, and 24 h.
The accumulation time for MS-MS was 80 ms, and the CE setting principle was the same as for the IDA mode. Raw IDA data acquired from the TripleTOF 5600 were analyzed with the ProteinPilot software (version 5. 0, AB Sciex) with a Paragon algorithm search. Results were filtered with a 1% false discovery rate at both the protein and peptide levels, and the accuracy of the MS that we used was 0. 05 D for MS and 0. 1 D for MS-MS fragment ions. The result file was imported into the PeakView SWATH MicroApp (version 2. 0) software to generate a spectral library, with default parameters. The SWATH MicroApp was also used for peptide peak extraction from the SWATH data. Results were filtered with a q < 0. 01 threshold. MarkerView (version 1. 3) was used for data normalization and the quantification of relative peptide or protein peak extraction data.
About 100 mg of protein treated with or without CIAP was subjected to a separation via 10% (w/v) SDS-PAGE with 100 mM Phos-tag  (Boppard,. Mn 21 -Phos-tag SDS-PAGE preparation and immunoblotting were performed based on the protocol described in FU-JIFILM Wako Chemicals' Phos-tag guide book (https://labchem-wako. fujifilm. com/us/category/lifescience/proteomics/phostag/index. html). Proteins (10 mg) were assayed using another 10% (w/v) SDS-PAGE gel as a reference, and HA antibodies (Sigma-Aldrich, catalog no. H3 63, lot no. 066M4837V) or b-actin (CWBio, catalog no. CW0264) antibodies were used for the immunoblot analysis. The intensity of immunoblot bands was assayed with ImageJ software (https://imagej. nih. gov/ij/).
Statistical Analysis For root architecture and symbiotic nodulation phenotype assays, gene expression analysis, and the quantification of intensity of immunoblot bands, statistical analysis was performed as described in the figure legends. Significant differences were determined with paired two-tailed Student's t test using Excel 2016 or with ANOVA and Kruskal-Wallis nonparametric testing using IBM SPSS Statistics version 25 (Supplemental Data Set 3).
ACKNOWLEDGMENTS We thank  Peibin Qin  and  Yinghua Zhao  ( Shanghai AB Sciex Analytical Instrument Trading Co. ) for help with MS analyses,  Jijun Yan  and  Jinfang Chu  ( Institute of Genetics and Developmental Biology, Chinese Academy of Sciences ) for help with the IAA quantification,  Chuanen Zhou  ( School of Life Sciences, Shandong University ) for providing the DR5:GUS vector, and  Qijun Chen  ( College of Biological Science, China Agriculture University ) for providing the CRISPR/Cas9 system. This work was supported by the  National Natural Science Foundation of China  (grants  31772658  and  31571587 ), the project for Extramural Scientists of the  State Key Laboratory of Agrobiotechnology, China Agricultural University  (grant  2018SKLAB6-22 ), and the  China Postdoctoral Science Foundation  (grant  2019M660878 ).
However, in a conditional analysis, adjusting for heterozygosity at rs1799990, we found no substantive evidence of an independent association signal (Supplementary Figure  7  and 8 ); lead SNP rs12624635, P=0. 03 (heterozygous conditional model). The region of high LD surrounding rs3747957 in STX6 results in a large causal set, making identification of a single causal variant more complex (Figure  2b ). Subsequently, using eCAVIAR and GTEx  19  and other eQTL databases, we identified a strong correlation between sCJD risk and increased expression of STX6 mRNA in multiple brain regions, particularly in the caudate and putamen nuclei of the brain (Putamen STX6 rs3747957 P=2. 3 x 10 -13 , GTEx, Figure  3 ), key regions implicated in sCJD and the most frequently abnormal brain regions at diagnostic MRI brain imaging  20.
As the GWAS signal is associated with only two SNPs at GAL3ST1 (in strong LD with each other but low LD with all other surrounding variants) these SNPs predominantly define the causal set as expected, however, these are statistically indistinguishable from each other (Figure  2c ). One of these SNPs, rs2267161, is a non-synonymous variant of GAL3ST1 p. V29M. In GTEx, neither SNP correlates with expression of genes at the locus in brain tissues. Close to p. V29M resides p. V34M (rs55674628, allele frequency=0. 02; LD with rs2267161, r 2 =0. 01, D'=1. 00, discovery P=0. 18), these being the only common non-synonymous variants in European ancestries populations. These polymorphisms form three common haplotypes, rs2267161-C/rs55674628-C (CC), CT and TC with frequencies in the combined case-control dataset of 0.
This research study consists of an extended questionnaire, blood withdrawal from patients and relatives, and collection of data from the medical records. All patients and relatives participating in this study provided written informed consent to participate and to obtain information from their treating physicians. The patients included in this study were probable sCJD cases or definite sCJD cases based on the diagnostic criteria from the University of Edinburgh. 1  for sample sources and sizes. Control samples were chosen from genotype datasets available for biomedical research derived from countries that matched those providing case samples. In all but a single example, genotyping was done using Illumina arrays with substantial overlap with the Illumina Omniexpress array used to genotype cases.
LD matrix was calculated from sCJD GWAS data using PLINK --r2 function. CAVIAR was run with an undefined number of causal variants and causal set probability at 95%. eCAVIAR is an extension of the CAVIAR framework to estimate the posterior probability of the same variant being causal in both GWAS and eQTL datasets  55. The STX6 locus was defined as previously and SNPs were pruned with variant inflation factor of 5 to extract distinct signals. We obtained eQTL data for 48 tissues included in the GTEx portal (v7). eQTLs for these 46 pruned variants with nominal P≤10 -5 were defined as 'eGenes' and eCAVIAR performed for each in its target tissue. Resulting colocalisation posterior probability (CLPP) was ranked to identify target gene and tissue. Gene-based analysis (MAGMA / VEGAS2) By aggregating the effects of all SNPs of a GWAS in a gene, correcting for LD and testing the joint association of all markers in the gene with the phenotype, it is possible to extend the power of detection and detect multiple weaker associations within a gene, which otherwise would be missed.
PAINTOR In addition, we utilised PAINTOR, a Bayesian probabilistic framework, which integrates GWAS summary and LD data with functional genomic annotation data such as ENCODE and FANTOM, to calculate posterior probabilities and identify a set of likely causal variants at any given risk locus (Supplementary Table  6 ). We aimed to identify causal variants 100kB around the lead SNP rs11586493 in the STX6 locus, our prime candidate identified in the GWAS, including all available functional brain tissue annotations (n=587). Whole exome sequencing 249 sCJD exomes were captured with SureSelect and HaloPlex (Agilent) kits. Exomes were sequenced on the Illumina HiSeq2000 platform with 100 bp paired-end runs. Sequences were aligned to the human reference genome using Novoalign software. The Genome Analysis Toolkit (GATK) Unified Genotyper were used for SNP and indel calling then sequences were recalibrated with the GATK Variant Recalibrator and variants annotated with ANNOVAR.
Immunohistology We used rabbit polyclonal anti-syntaxin-6 (Atlas Antibodies, HPA038558) and PDIA4 (Atlas Antibodies) to immunostain cases of sporadic CJD from archives of the Division of Neuropathology, University College London Hospitals NHS Foundation Trust. Immunostaining was performed on control cases and sCJD cases. Controls (non-neurodegenerative disease deaths, processed similarly to sCJD) were obtained from the Division of Neuropathology. A proportion of the samples originated from frozen material, and these were fixed by immersion into formalin, formic acid treated and then processed into a Formalin Fixed Paraffin Embedded (FFPE) sample. On all cases, frontal cortex and cerebellum (including the dentate nucleus) were stained. Measurement of reference and GWAS significant gene expression level in cerebellum by reverse transcription quantitative PCR (RT-qPCR) RNA was extracted from 50-100 mg post-mortem cerebellum (10 sCJD cases and 10 neurologically normal controls) using the Zymo Direct-zol™ DNA/RNA Miniprep kit (Zymo Research, Irvine, US) according to the manufacturer's instructions followed by DNAse I digestion and concentration using RNA Clean & Concentrator-5 columns (Zymo Research, Irvine, US) according to manufacturer's instructions.
Acknowledgements We thank  Richard Newton  for support with images. This study makes use of data generated by the  Wellcome Trust Case-Control Consortium. A full list of the investigators who contributed to the generation of the data is available from www. wtccc. org. uk. Funding for the project was provided by the  Wellcome Trust and Medical Research Council. We would like to thank patients, their families and carers, UK neurologists and other referring physicians, co-workers at the  National Prion Clinic , our colleagues at the  National Creutzfeldt-Jakob Disease Research and Surveillance Unit, Edinburgh. We thank the Director of the  Papua New Guinea Institute of Medical Research ,  Professor Willie Pomat , and former Directors  Professors Peter Siba  and  John Reeder , the staff of the PNGIMR, especially the kuru project field team, and the communities of the kuru-affected region for their generous support.
of Central Nervous System Studies of the National Institutes of Health, Bethesda, USA for archiving and sharing old kuru samples. The kuru studies were initially funded by a Wellcome Trust Principal Research Fellowship in the Clinical Sciences to JC, and since 2001, and all other aspects of the work by the Medical Research Council. Several authors at UCL/UCLH receive funding from the Department of Health's NIHR Biomedical Research Centres funding scheme. Some of this work was supported by the Department of Health funded National Prion Monitoring Cohort study. SJC receives an NHMRC Practitioner Fellowship (ID# APP1105784). Tze How Mok is supported by a Fellowship award from Alzheimer's Society, UK (grant number 341 (AS-CTF-16b-007)) and CJD Support Network UK Research Support Grants. Funding for the collection of Polish samples for study was provided Medical University of Lodz.
The Italian national surveillance of Creutzfeldt-Jakob disease and related disorders is partially supported by the Ministero della Salute, Italy. The German National Reference Centre for TSE is funded by grants from the Robert-Koch-Institute. The Dutch National Prion Disease Registry is funded by the National Institute for Public Health and the Environment (RIVM), which is part from the Ministry for Health, Welfare and Sports, The Netherlands. PS-J was supported by Instituto de Salud Carlos III [Fondo de Investigación Sanitaria, PI16/01652] Accion Estrategica en Salud integrated in the Spanish National I+D+i Plan and financed by Instituto de Salud Carlos III (ISCIII) -Subdireccion General de Evaluacion and the Fondo Europeo de Desarrollo Regional (FEDER -"Una Manera de Hacer Europa"). We thank Inés Santiuste and the Valdecilla Biobank (PT17/0015/0019), integrated in the Spanish Biobank Network, for their support and collaboration in sample collection and management.
The study on Italian controls was supported by the Ministero dell'Istruzione, dell'Università e della Ricerca -MIUR project "Dipartimenti di Eccellenza 2018 -2022" (n° D15D18000410001) to the Department of Medical Sciences, University of Torino (G. M. ) and the AIRC -Associazione Italiana per la Ricerca sul Cancro (IG 2018 Id. 21390 to G. M. ). The Three-City Study was performed as part of a collaboration between the Institut National de la Santé et de la Recherche Médicale (Inserm), the Victor Segalen Bordeaux II University and Sanofi-Synthélabo. The Fondation pour la Recherche Médicale funded the preparation and initiation of the study. The 3C Study was also funded by the Caisse Nationale Maladie des Travailleurs Salariés, Direction Générale de la Santé, MGEN, Institut de la Longévité, Agence Française de Sécurité Sanitaire des Produits de Santé, the Aquitaine and Bourgogne Regional Councils, Agence Nationale de la Recherche, ANR supported the COGINUT and COVADIS projects.
Fondation de France and the joint French Ministry of Research/INSERM «Cohortes et collections de données biologiques» programme. Lille Génopôle received an unconditional grant from Eisai. The Three-city biological bank was developed and maintained by the laboratory for genomic analysis LAG-BRC -Institut Pasteur de Lille. This work was also funded by the Pasteur Institut de Lille, the Lille Métropole Communauté Urbaine, the Haut-de France council, the European Community (FEDER) and the French government's LABEX DISTALZ program (development of innovative strategies for a transdisciplinary approach to Alzheimer's disease). The French National Surveillance Network for Creutzfeldt-Jakob disease is supported by Santé Publique France. rs1799990 rs3747957 rs2267161 rs9065 rs6498552 Nearest gene PRNP STX6 GAL3ST1 PDIA4 BMERB1 Location (GRCh37) 20:4680251 1:180953853 22:30953295 7:148700849 16:15539901 Type of mutation Missense Synonymous Missense 3' UTR Intronic Exonic Exonic Exonic Exonic Risk allele A A C T T Minor allele G A T T T Number Cases 4110 4110 4110 4110 4110 of samples Controls 13569 13569 13569 13569 13569 s t a g e D i s c o v e r y MAF P-value Cases Controls 0.
The best-fitted nucleotide substitution model was evaluated in MEGA 7. 0. 26 based both on the corrected Akaike information criterion (AICc) and the maximized log likelihood (lnL). Maximum likelihood phylogeny was constructed in MEGA 7. 0. 26 [33]  using the Generalized Time Reversible substitution model (GTR) with a gamma distribution of rate variation among sites (shape parameter = 4) and acceptance of invariant sites (I). Branch support was assessed with 500 bootstrap replicates. X. populi CFBP 1817 T was chosen as an outgroup. All the sequences generated were deposited in the National Center for Biotechnology Information GenBank under accession numbers MK610462 to MK610526 for gapA, MK610527 to MK610591 for gyrB and MK610592 to MK610656 for rpoD. The full concatenated alignment is provided along with the supplementary material.
Genome sequencing, assembly, annotation and acquisition Genomic DNAs were extracted and purified from 25 ml 1/10 th TSB overnight cultures using the standard phenol-chloroform method  [55]   [73]  with a minimum contig size of 200 bp, then annotated with PROKKA v1. 14  [58]. Additionally, 46 genome assemblies representing the taxonomic diversity of Xanthomonas clade II as reported by Jacques et al. [28]  with the emended propositions of Constantin et al. [13]  were acquired from the NCBI Genbank database. Genome characteristics, GenBank accession numbers and quality statistics are listed in Table  S2.
Phylogenomic analysis Phylogenomic tree reconstruction was performed on all the genomes of type, pathotype and representative strains of Xanthomonas clade II using PHYLOPHLAN v1. 10  [59]. Type strain of Stenotrophomonas maltophilia CFBP 3035 T was selected as an outgroup. A core of ~350 single-copy full-length predicted proteins from the PhyloPhlan database were retrieved in the genomes with USEARCH v8. 0. 1623  [16] , then aligned and concatenated with MUSCLE v3. 8. 31  [17]. Finally, a phylogenomic tree was built with FASTTREE 2. 1. 10 SSE3  [44]  and robustness was locally assessed by the Shimodaira-Hasegawa test (SH) using 1,000 resamples. Additionally, a phylogeny was also constructed on all the available genomes of X. campestris pv. vitians type B, X. hortorum and X. cynarae with X.
2 µm filters, then added in the inoculation fluid only for PM03B microplates at a 1x final concentration. Fluids were then inoculated following the same procedure as for the GEN III microplates to obtain to transmittance values of 85 %. Plates were subsequently filled with 100 µL per well and incubated 5 days at 25°C in an OmniLog system. Raw data were imported in R and analyzed using the opm package  [70]. The maximum heights of the curves (parameter A) were discretized using empirical cutoffs of 75 and 125 omnilog arbitrary units for weak and positive reaction respectively. Some of the phenotypic features reported in Brown's first description of the pathogen responsible for bacterial leaf spot of lettuce  [7]  were also tested to check the authenticity of the pathotype strain. Gram staining were performed by staining with crystal violet for 1 min followed by Lugol for 1 min, then decolorized with 70 % ethanol for 20 s and finally stained with safranine for 1 min.
Pathogenicity assays All strains were tested for their pathogenicity on two lettuce cultivars (oakleaf cv. Kirinia and leaf lettuce cv. Météore), and 11 strains on tomato cv. Marmande. Strains able to induce a mean disease severity ≥ 2 on the 8 plants at the end of the three-week monitoring period were considered pathogenic, whereas strains were determined non-pathogenic when mean disease severity was < 2. When mean disease severity was ≥ 2, few variations of disease severity were observed between strains or cultivars using our five-point scale disease index (data not shown). All strains labelled as X. hortorum pv. vitians were able to induce typical BLSL symptoms on the two lettuce cultivars (Table  1 ), and therefore considered pathogenic on lettuce. Consistent with previous reports  [3, 53] , pathotype strain of X.
hortorum presents highly variable profiles of nitrogen sources utilization. The type strain is CFBP 5858 T = CFBP 4925 T = LMG 733 T = NCPPB 939 T = ICMP 453 T. The GenBank accession number for its genome assembly is GCA_002940005. 1 and its 16S rRNA gene accession number is NR_026386. The species has a G+C mole % value between 63. 3 to 63. 9 %. The species includes, so far, the following pathovars based on their phytopathogenic specialization: X. hortorum pv. hederae, X. hortorum pv. pelargonii, X. hortorum pv. carotae, X. hortorum pv. taraxaci, X. hortorum pv. cynarae, X. hortorum pv. gardneri and X. hortorum pv. vitians. The closest species described is X. populi (ex-Ridé 1958) van den Mooter and Swings 1990  [71]. According to the characteristics of X. populi described in the valid description, in  Ridé and Ridé 1992 [48]  and  Vauterin et al.