dataesr/scientific-paragraphs-categorization huggingface dataset:
Acknowledgment The authors thank the patients and their families whose ongoing help and participation in this research made this study possible. Thanks to  Leen Thielemans  for insightful advice on study design and critical reading of the manuscript; to  Beiyu Lin  and  Sundos Al-Husayni  for assistance with data collection and recording; to  Caroline Dorrepaal ,  Stéphanie Hoffman , and  Khazal Paradis  for critical advice on experimental design, data analysis, and interpretation; and to  Jill Madden  and  Stéphane van Rooijen  for critical reading of the manuscript.
Study Funding Data collection and collation, and analysis and reporting were supported by  Dynacure. Participant ascertainment, enrollment, and data collection were supported by grant  MDA602235  from the  Muscular Dystrophy Association, USA , and generous support from the  Anderson Family Foundation  to A. H. B. DNM2 mutation analysis utilized the resources of the  Boston Children's Hospital IDDRC Molecular Genetics Core Laboratory  funded by  NIH   P50HD105351  from the  National Institute of Child Health and Human Development of the NIH. Role  of the funder/sponsor: Dynacure staff participated in study conception and design, data analysis and reporting, review and approval of the manuscript, and the decision to submit for publication. All other funders had no role in the design or conduct of the study.
An F 2 mapping population (Avocet 2B × Avocet S; n = 345) segregating for a single dominant stripe rust resistance gene (R:S = 254:91, χ 2 = 0. 348, P = 0. 554) was genotyped with the QYr. sgi-2B. 1 flanking markers 1 Xbarc55 and Xwmc344 to identify recombinants. Identified recombinants were genotyped with additional Kompetitive Allele Specific PCR (KASP) markers derived from polymorphic iSelect and Axiom 35K SNPs between Avocet S and Avocet 2B (Extended Data Fig. 6  and Supplementary Table  7 )  35. The following Yr27-carrying lines were obtained from the University of the Free State (UFS) and the Agricultural Research Council -Small Grain in South Africa (SA): Selkirk (UFS31b), Kubsa (SA9399), Kauz (SA6643), Opata 85 (SA8997) and Avocet Yr27 (Yr27/6*AvS; UFS31a). HiFi library preparation and sequencing.
DNA was labeled using the DLS protocol (Bionano Genomics). Labeled molecules were produced using the Saphyr System (Saphyr Chip G1. 2). Data processing was performed using the Bionano Solve v. 3. 6 software (https://bionanogenomics. com/support/software-downloads). Omni-C library preparation and sequencing. The Omni-C library was prepared using the Dovetail Omni-C Kit according to the manufacturer's protocol. In brief, chromatin was fixed in place in the nucleus. Fixed chromatin was digested with DNase I and then extracted. Chromatin ends were repaired and ligated to a biotinylated bridge adapter, before proximity ligation of adapter containing ends. After proximity ligation, crosslinks were reversed and the DNA was purified from proteins. Purified DNA was treated to remove biotin that was not internal to ligated fragments.
In brief, 300 ng of total RNA from each of the six developmental stages was used as input for complementary DNA synthesis. Each sample was first barcoded and then subjected to cDNA amplification using 12 cycles. Purified cDNAs were pooled in equal molarity and then subjected to library preparation using the SMRTbell Express Template Prep Kit 2. 0 (Pacific Biosciences, 100-938-900) following the Iso-Seq protocol previously referenced. The library was prepared for sequencing by annealing primer v4 with the Sequel II Binding Kit 2. 1 and the Internal Control Kit 1. 0 (Pacific Biosciences, 101-843-000). One SMRT Cell 8M (Pacific Biosciences, 101-389-001) was sequenced on the PacBio Sequel II system using the Sequencing Kit 2. 0 (Pacific Biosciences, 101-820-200). The IsoSeq pipeline (v. 3; https://github.
com/PacificBiosciences/IsoSeq) was used for CCS generation, demultiplexing and clustering of the six datasets. Genome assembly and validation. The PacBio HiFi reads were assembled using hifiasm  12  (v. 0. 11) with default parameters. Hybrid scaffolding incorporating the PacBio contigs and the optical map was performed using the hybridScaffold pipeline (Bionano Solve 3. 6) with default parameters. For the pseudomolecule construction, the Omni-C reads were incorporated using Juicer tools  38 (v. 1. 6 ) and 3D-DNA  39 (v. 180114). In brief, the preprocessing of the Omni-C reads was performed with juicer. sh (parameter: -s none). The 'merged_nodups. txt' output file corresponding to the Hi-C contacts with duplicates removed was subsequently used with run-asm-pipeline. sh (parameter: -r 0) as input to produce the '.
hic' and '. assembly' files. These files were uploaded into Juicebox  40 (v. 1. 11. 08) to visualize the Hi-C map and for manual curation. As a final step, the script run-asm-pipeline-post-review. sh (default parameters) was used to save the final Hi-C contact map and to output the final Kariega assembly (21 pseudomolecules and 1 unanchored pseudochromosome). To validate the genome assembly, we remapped the optical map onto the pseudomolecule using the hybridScaffold pipeline (Bionano Solve 3. 6), and the final pseudomolecules were compared with the recent bread wheat assemblies of Chinese Spring (IWGSC RefSeq v. 2. 1)  41  and the assemblies of the 10+ Wheat Genomes Project 7 using MashMap 42 (v. 2. 0; parameter: -s 300000-pi 98).
Gene model prediction. Gene model prediction was performed following the method described by Mascher et al. 5  with minor modifications, combining transcriptomics data, protein homology and ab initio prediction. First, the RNA-Seq data from the six developmental stages were mapped to the reference assembly using STAR  43  (v. 2. 7. 0f; parameter:-outFilterMismatchNoverReadLmax 0. 02) and assembled into transcripts with StringTie 44 (v. 2. 1. 4; parameter:-rf -m 150 -f 0. 3 -t). Iso-Seq data were mapped using minimap2  45  (v. 2. 17-r941; parameter: -ax splice -uf -secondary=no -C5), and the redundant isoforms were further collapsed into transcript loci using cDNA_Cupcake (http://github. com/Magdoll/cDNA_ Cupcake; parameter:-dun-merge-5-shorter). The RNA-Seq and Iso-Seq transcripts were merged using StringTie (parameters:-merge -m 150) into a pool of candidate transcripts, and TransDecoder (v.
5. 5. 0; https://github. com/TransDecoder/ TransDecoder) was used to find potential open reading frames and to predict protein sequences within the candidate transcript set. For the protein homology evidences, we used the translated proteins from the projected gene annotation of the 10+ Wheat Genomes Project 7 , the IWGSC RefSeq v. 2. 1  41  and the Triticeae protein sequences downloaded from the UniProt database (2021_03). All of the proteins were mapped against the Kariega assembly using GenomeThreader  46  (v. 1. 7. 1; parameters: -startcodon -finalstopcodon -species rice -gcmincoverage 70 -prseedlength 7 -prhdist 4 -gff3out). Then, we produced ab initio gene predictions using AUGUSTUS  47  (v. 3. 4. 0), GeneMark  48 (v. 4. 38)  and Fgenesh (v. 8. 0. 0; http:// www. softberry. com). In brief, AUGUSTUS gene prediction was performed using a model specifically trained according to Hoff and Stanke  49  and a hints file generated using the previously mentioned Iso-Seq and RNA-Seq predictions.
GeneMark was used with the option -ET and the intron coordinates calculated with the perl script star_to_gff. pl provided in the GeneMark package. For the Fgenesh prediction, the Kariega pseudomolecules were repeat masked using a de novo repeat library constructed with the Extensive de novo TE Annotator (EDTA) pipeline  50  and the TREP database  51 (v. 19). Fgenesh annotation was performed with the specific Triticum aestivum matrix for the gene prediction. We used EVidenceModeler 52 (v. 1. 1. 1) to join all of the gene evidences from transcriptomics, protein alignments and ab initio predictions with weights adjusted according to the input source (Fgenesh, 2; AUGUSTUS, 1; GeneMark, 1; protein homology, 5; transcriptomics, 12). Finally, we performed two rounds of isoform and UTR prediction using the Program to Assemble Spliced Alignments (PASA) pipeline  53  with default parameters.
Gene models were classified as high-confidence or low-confidence genes according to criteria used by the International Wheat Genome Sequencing Consortium  13  and by Mascher et al. 5. In brief, protein-encoding gene models were considered complete when start and stop codons were present. A comparison with PTREP  51  , UniPoa (Poaceae database of annotated proteins from the UniProt database (2021_03)) and UniViri (Viridiplantae database) was performed using DIAMOND  54  (v. 2. 0. 9; parameters: -e 1e-10-query-cover 80-subject-cover 80). Gene candidates were further classified using the following criteria: a high-confidence gene model is complete with a hit in the UniViri database and/or in UniPoa and not PTREP; a low-confidence gene model is incomplete and has a hit in the UniViri or UniPoa database but not in PTREP, or the protein sequence is complete with no hit in UniViri, UniPoa or PTREP.
VIGS. To develop the VIGS probes, the predicted QYr. sgi-2B. 1 coding sequence was searched against the Kariega whole transcriptome (RNA-Seq and Iso-Seq) database using siRNA-Finder (si-Fi) software  59. Based on the RNA interference (RNAi) design plot, three regions (Si1 (197 bp) in the 5′ UTR, Si2 (200 bp), and Si3 (198 bp) in the coding sequence) were selected for VIGS. The selected probes were verified for specificity using a BLAST search against the Kariega genome assembly (<80% sequence identity for hits other than Yr27). The target sequences were cloned into the pBS-BSMV-γ (BSMV, barley stripe mosaic virus) vector in an antisense direction  60, 61. Viral RNAs of BSMV-GFP and BSMV-GUS were used as controls, along with the BSMV-Si1, BSMV-Si2 and BSMV-Si3 constructs to infect the plants.
RNA extraction was done using the Maxwell RSC Plant RNA kit and the Maxwell RSC48 instrument (Promega). One microgram of RNA was used for the first-strand cDNA synthesis using a High-Capacity cDNA Reverse Transcription Kit following the user guidelines (Applied Biosystems, 4368814). cDNA was further diluted 20-fold, and 4 μl of diluted cDNA were used for qPCR (quantitative real-time PCR). qPCR was performed using the 2BNLR5F17/R11 primers (Supplementary Table  7 ). A 20 μl qPCR was set up and run on the ABI QuantStudio 6 Flex Real-Time PCR machine using PowerUp SYBR Green Master Mix (Applied Biosystems, AS25741). The 2 -ΔΔCt method was used to normalize transcript values relative to endogenous controls Ta. 6863 (ref. 62 ). Haplotype analysis, Shannon entropy and homology modeling. Yr27 protein versions were retrieved from the National Center for Biotechnology Information (NCBI) using a protein BLAST search (Supplementary Table  8 ) and aligned using MUSCLE in Geneious Prime 2019.
Haplotypes were classified based on amino acid variations (Extended Data Fig. 5a ). To identify residues overlapping functional motifs, the Motif Alignment Search Tool (MAST v. 5. 3. 3)  63 was used to predict the predefined NLR motifs  64  and LRRpredictor was used to predict canonical LXXLXLXX repeats  65. Shannon entropy values were calculated using the Entropy-one tool in the HIV sequence database (https://www. hiv. lanl. gov/content/ sequence/ENTROPY/entropy_one. html). The raw output values were plotted using GraphPad Prism v. 9. 2. 0. The Yr27 amino acid sequence was submitted to the Protein Homology/analogY Recognition Engine v. 2. 0 (Phyre2) for homology modeling to predict the three-dimensional structure  66. The resulting top two Yr27 models comprise residues D87 to L1060 (90%) aligned to RPP1 with 18% identity and 100% confidence, and residues P43 to I977 (87%) aligned to ZAR1 with 22% identity and 100% confidence.
The coordinates of RPP1-CJID-ATR1 and ZAR1-RKS1-PBL2 cryo-electron microscopy (cryo-EM) structures were retrieved from the Protein Data Bank (PDB) (7CRC 27 and 6J5T  67  ) for further analysis. Based on the structure analysis, graphical illustrations were created in UCSF ChimeraX v. 1. 3dev2021 software 68 using RPP1-CJID-ATR1 as reference. Reporting Summary. Further information on research design is available in the Nature Research Reporting Summary linked to this article.
Acknowledgements We are grateful to  L. Zhou  and  V. Venkataraman  for technical assistance, and the  King Abdullah University of Science and Technology (KAUST) Bioscience Core Lab  for sequencing support. We thank  H. Šimková  from the  Institute of Experimental Botany, Czech Republic , for technical advice. This publication is based on work supported by the  South African Winter Cereal Trust  (Grant  WCT/W/2020/04 ) and the  KAUST Office of Sponsored Research (OSR)  under award no. OSR-CRG2018-3768.
Data availability Data supporting the findings of this work are available within the paper and its Supplementary Information. The raw sequencing data used for de novo whole-genome assembly, CCS reads, raw bionano map, Omni-C reads, Kariega genome assembly, RNA-Seq data and Iso-Seq data for the annotation are available on the European Bioinformatics Institute (EBI) European Nucleotide Archive (ENA) under study number PRJEB45541. The Yr27 coding sequence and genomic sequences have been deposited in the ENA under accession numbers OU248057 and OU248342, respectively. The whole-genome assembly and annotations of gene models, repeats and NLRs are available on the DRYAD database (https://doi. org/10. 5061/dryad. nk98sf7td).
2c ). Altogether, these data demonstrate that upon 5-FU treatment, ribosomes containing fluorinated rRNA are fully assembled and exported to the cytoplasm, revealing that presence of 5-FUrd is tolerated by the quality control systems of the cell. Next, we investigated whether fluorinated ribosomes could be found within tumors in vivo. First, we analyzed rRNA from HCT116 xenografts established in nude mice. 5-FU treatment efficacy was evidenced by a decrease in tumor growth (Supplementary Fig. 3d ). 5-FUrd was detected in mature rRNA purified from tumor cells collected after the last treatment at levels close to those observed in cultured cells (Fig. 2d ). We extended this observation to xenografts similarly established with HT29 and SW480 cell lines (Fig. 2e, f ). Thus, 5-FU incorporation into ribosomes can be replicated in a common xenografted animal model.
The Fig. 2  5-FU is incorporated in ribosomes of cell lines and tumours. a Schematic representation of 5-FUrd incorporation into ribosomes determined using liquid chromatography-mass spectrometry-high-resolution mass spectrometry (LC-HRMS). b, HCT116 cells were treated for 24 h with 5 to 100 µM 5-FU and 5-FUrd incorporation was determined as in a. Data are expressed as mean + /-s. d. of independent experiments (n = 3). c, Indicated cell lines were treated for 24 h with 10 µM of 5-FU and incorporation of 5-FUrd into rRNA was determined as in a. Data are expressed as mean + /-s. d. of independent experiments (n = 3). d-f, d, HCT116, e, HT29 or f, SW480 cells were xenografted into nude mice, and mice were treated with 50 mg/kg of 5-FU twice a week (5-FU) or with PBS (Control). Incorporation of 5-FUrd into rRNA was determined as in a, from gel-purified rRNA.
Data are values for individual animals (noted M1 to M3) (n = 1). g, rRNA were purified from total RNA extracted from colorectal cancer samples. Incorporation of 5-FUrd into rRNA was determined as in a. Pt = sample from 5-FU treated patient, CT Pt = sample from patient not treated with 5-FU. n = 1 for each sample. Source data are provided as a Source Data file. finding that fluorine appears to modify the functioning of rRNA is not unexpected since chemical modifications of rRNA including 2′-O-methylation and pseudouridylation were shown (i) to contribute to translational regulation and efficiency  [13] [14] [15] 38  , and (ii) to establish molecular interactions that cannot be provided by non-modified ones  7, 9. Th  effect we observe on translation initiation suggests that 5-FUrd incorporation is enriched at or close to regions of the ribosome that are critical for the interaction of the ribosome with mRNAs or translation factors, or in the functional domains of the ribosome, such as the A, P and E sites.
Methods Cell lines, cell culture, and 5-FU treatment. Cells were maintained in Dulbecco Minimum Essential Medium-GlutaMax (Invitrogen) supplemented with 10% foetal bovine serum (FBS) at 37 °C with 5% CO 2. The following cell lines were obtained from ATCC: HCT116 (ATCC CCL-247), MDA-MB-231 (ATCC HTB-26), BT20 (ATCC HTB-19), HT29 (ATCC HTB-38), SW480 (ATCC CCL-228) Panc1 (ATCC CRL-1469) and MiaPaCa (ATCC CRL-1420). The following cell lines were obtained from the authors: ISRECO1 (Cajot, J. F. , et al. Cancer Res. (1997) 57, 2593-2597). The following cell lines were authenticated by 21 PCRsingle-locus-technology (Eurofins, Ebersberg, Germany): HCT116, HT29, MDA-MB-231, MiaPaCa, Panc1. ISRECO1 cell line was not authenticated by PCR-singlelocus-technology as this cell line genetic pattern is not described in databases.
Incorporation of 5-FUrd was measured by LC-HRMS. Data are expressed as mean + /-s. d of independent experiments (n = 3). b Schematic representation of the hybrid in vitro translation assay used in c and d. c and d Ribosomes were purified from HCT116 cells treated with 10 µM 5-FU for 24 h or 48 h, and their translational activity was evaluated using the hybrid in vitro translation assay. Translation efficacy was evaluated on luciferase reporter mRNA containing the 5'-untranslated region (5'-UTR) of the indicated gene. CDS = coding sequence. Values are units of Renilla luciferase activity normalized against the untreated (NT) condition. c, Evaluation on capped mRNA containing the 5'UTR of actin, GAPDH, IGF-1R and c-Myc genes. d Evaluation on uncapped mRNA containing the IRES element from the cricket paralysis virus (CrPV) and the encephalomyocarditis virus (EMCV).
Data are expressed as mean + /-s. d. of independent experiments (n = 3). e IRES activity of IGF-1R 5'UTR and deletions was evaluated by transfection of a bicistronic reporter vector represented on top of the figure. IRES activity is monitored as the ratio of firefly luciferase (Fluc) activity over Renilla luciferase (Rluc) activity. HCT116 cells were transfected for 24 h and then treated for 24 h with either 10 µM or 50 µM 5-FU. Data are expressed as mean + /-s. d. of independent experiments (n = 4). f Translation initiation activity of IGF-1R 5'UTR and deletions and of GAPDH 5'UTR was evaluated by co-transfection of a reporter vector represented on top of the figure with a renilla reporter vector for normalization. Translation activity is monitored as the ratio of firefly luciferase (Fluc) activity over Renilla luciferase (Rluc) activity.
HCT116 cells were transfected for 24 h and then treated for 24 h with either 10 µM or 50 µM 5-FU. Data are expressed as mean + /-s. d. of independent experiments (n = 4). Results of unpaired two-tailed t test are indicated as nonsignificant (ns) p < 0. 05 (*), p < 0. 01 (**), p < 0. 001 (***), and p < 0. 0001 (****). Source data are provided as a Source Data file. proteins were subjected to SDS-PAGE, and blotted onto poly-vinylidene difluoride (PVDF) membranes (Immobilon-P, Millipore). Membranes were blocked in Trisbuffered saline solution containing 0. 05% Tween 20 and 5% nonfat milk and incubated with primary antibodies: mouse monoclonal antibodies against GAPDH [6C5] (AM4300, Invitrogen) and rabbit monoclonal antibodies against IGF-1R (#9750, Cell Signalling) and actin (ab179467, Abcam) and anti-Histone H3 (ab1791, Abcam) diluted at 1:2000.
Adjustments for multiple comparisons were made using Benjamini and Hochberg correction method. P values for individual mRNA are available in Supplementary Data 2. The data show all analyzed mRNAs. mRNAs whose polysomal level either increased (red) or decreased (blue) by more than twofold between untreated and 5-FU treated cells are colored (p. adj < 0. 05). The threshold +/-1 log2(FC) is indicated by vertical lines. The number of significantly altered mRNAs is indicated on top of the graphs. c Same datasets as in (a) and (b). Venn diagrams showing the comparison of translationally upregulated and downregulated mRNAs in 10 µM and 50 µM 5-FU treated cells. d Gene ontology analysis of all translationally altered mRNAs upon treatment with 50 µM 5-FU. The data show enriched GO terms for biological processes category (GO-Term-BP) and KEGG pathways.
Analysis was carried out on a liquid chromatography coupled with a highresolution mass spectrometer (Q-Exactive Plus Orbitrap -Thermo Scientific). Data acquisition was performed alternatively in negative and positive modes with the full scan mode (FS) at a resolution of 70,000 or 140,000 and with the parallel reaction monitoring mode (PRM) at a resolution of 17,500. Chromatographic separation of nucleosides was achieved on a Hypercarb® column ((2. 1 mm×100 mm; 5 µm) (ThermoScientific)). The level of 5-FU per ribosome was calculated as the ratio of measured [5-FUrd].
7. 7  58  , on the Homo sapiens reference genome, version GRCh38. dna. -primary_assembly release v100, and annotated with GRCh38. 100 gtf Ensembl annotation file. Quantification of mapped reads was performed using HTSeq-count v0. 13. 5  59  , using the following parameters: strand = reverse, mode = intersectionnonempty, typesearch = exon, id_attributes = gene_id, additional attributes = gene_name, and ignoring chimeric reads. Statistical differential analyses were performed between the control and each 5-FU conditions (10 or 50 μM) using the Wald test from DESeq2 R package  60. For each dataset, the read counts were filtered with a minimum of 1 count per million per biological sample after size factors estimation (method RLE for Relative Log Expression normalisation), and then dispersion was estimated (using DESeq2).
P value adjustment that corrects for multiple tests to lower the risk of false discovery was performed with the method of Benjamini and Hochberg  61. Genes with corrected p values below 0. 05 were kept. Gene identifications were performed with biomaRt R package  62. Functional annotations were performed with gProfileR 63 using a g:SCS threshold < at 0. 80, and Ensembl release v103. Go terms were then clustered using CateGOrizer  64  according to the Goslim2 classification in multiple mode, which is well suited for the general-purpose analyses. Gene ontology classification of mRNA of Survival genes was performed using the "functional annotation clustering" tool of the Database for Annotation, Visualization and Integrated Discovery (DAVID) version 6. 8, using default parameters  65. Immunofluorescence analysis.
Coverslips were mounted using the Fluoromount G mounting medium (EMS). Images were acquired on a Zeiss LSM 780 confocal microscope using a 63X Plan Apochromat immersion objective (NA 1. 4), as a Z-stack (voxel size: 0. 0634 × 0. 0634 × 0. 3155 µm). Final images were prepared by maximum intensity projection to display all nucleoli, using Zeiss ZEN Black software. As indicated, level images of actinomycin D treated cells was adjusted to correct for NCL dispersion. Images were cropped using ImageJ (https://imagej. net)  66. [ 32 P] pulse-chase labelling. Labelling of newly synthesised RNAs was performed as described previously  21. Briefly, cells were grown in DMEM containing 10% FBS, and 5-FU containing medium for 24 h or 48 h or actinomycin D at 50 ng/mL for 3 h. Phosphate deprivation was performed by incubating cells for 1 h with phosphate-free DMEM (Invitrogen) containing 10% dialysed FBS.