dataesr/scientific-paragraphs-categorization huggingface dataset:
Statistical analysis The whole experiment was carried out three times for statistical accuracy. All analyses and measurements in this work were conducted in triplicate. The statistical differences (p < 0. 05) were examined using SPSS 19 software (IBM SPSS statistics, Version 19, USA) following descriptive tests including the student's t-test, the one-way ANOVA, and the Tukey post-hoc test with a confidence level of 95%.
LC/MS of camel and bovine whey proteins before and after drying The protein denaturation extent of acidic and sweet camel or bovine whey during drying was studied using LC-MS. The chromatograms profiles of unprocessed whey and reconstituted whey powders are shown in Supplementary data. By comparing these profiles, a slight and significant thermal denaturation was observed during the drying step. The proteins concentrations before and after reconstitution as well as their denaturation extent are presented in Table  2. Analysis of the LC-MS profiles of SBWP and RSBWP (Supplementary data, Fig. S1 ) indicated that the bovine milk serum albumin protein (BSA) was co-eluted with α-lactalbumin (Peak 1, Table  2 ). These proteins were identified by comparing their molecular weight (results of mass spectroscopy) with the existing data in Uniprot database (http:// www.
(A) Genome-wide RNA-seq analysis was performed using T47D cells to identify genes dependent on PRMT1 for R5020-regulated expression. Left panel: Hypothetical results of gene expression profiles for a given gene, illustrating how specific pairwise comparisons were performed between datasets for individual samples. Numbered bars represent hypothetical mRNA levels from RNA-seq data for cells expressing the indicated siRNAs (PRMT1 or CT) and treated for 6 h with ethanol (Eth) or R5020 (10 nM). Colored numbers represent pairwise comparisons performed to determine sets of genes for which mRNA levels were significantly different between the samples. For instance, comparison 1 = set of R5020-regulated genes (fold change R2, adjusted p < 0. 01); comparison 4 = set of PRMT1-dependent genes (fold change >1.
Figure5. PRMT1 Is Required for Progesterone-Dependent Expression of a Subset of PR Target Genes (A) Genome-wide RNA-seq analysis was performed using T47D cells to identify genes dependent on PRMT1 for R5020-regulated expression. Left panel: Hypothetical results of gene expression profiles for a given gene, illustrating how specific pairwise comparisons were performed between datasets for individual samples. Numbered bars represent hypothetical mRNA levels from RNA-seq data for cells expressing the indicated siRNAs (PRMT1 or CT) and treated for 6 h with ethanol (Eth) or R5020 (10 nM). Colored numbers represent pairwise comparisons performed to determine sets of genes for which mRNA levels were significantly different between the samples. For instance, comparison 1 = set of R5020-regulated genes (fold change R2, adjusted p < 0.
Left panel: The bar plots indicate the cellular migration rate, with a direct comparison between control and PRMT1-depleted cells. Right panel: Images of cells 24 h after the scratch wound. The blue line corresponds to the initial area of the wound. White arrows indicate cell migration areas. Both (B) and (C) graphs show the mean G SD of one experiment representative of three. The p value was determined using the Student's t test: * indicates p % 0. 05, **p % 0. 01, and ***p % 0. 001. (D) Kaplan-Meier estimates relapse-free survival in patients, in GEO, EGA, TCGA datasets, with low (black) or high (red) PR expression, as indicated using KM-plotter in a cohort of 1,764 breast tumors (a), or stratified in 2 groups following low-PRMT1 (b) or high-PRMT1 expression (c).
ACKNOWLEDGMENTS We thank  Helene Joly  for starting the project and  Julien Jacquemetton ,  Farida Nasri ,  Maeva Ruel , and  Aurore Souef  for helpful technical assistance. We are grateful to  Dr. Loredana D'Amato ,  Dr. Samuele Gherardi , and  Dr. Romain Teinturier  for their valuable advice and discussions. We also thank  Prof. Pierre Chambon  for kindly providing the pSG5PR-B and MMTV-Luc plasmids,  Dr. Catherine Teyssier  for the PRMT1 constructs, and  Dr. Stephane Ansieau  for the plasmid pPRUpu. We are also grateful to  Benjamin Gillet  and  Sandrine Hughes  for performing the RNA sequencing at the IGFL platform in Lyon. A special thanks to  Brigitte Manship  and  Clement Chapat  for reading the manuscript. This study was partially supported by the  ''Ligue Nationale Contre le Cancer ,'' the '' Association pour la Recherche sur le Cancer ,'' and the association '' Odyssea Chambery.
Most are epilithic or endolithic, and some are true endoliths with the capacity to dig and grow into calcium carbonates or sequestrate Ca-carbonates in their baeocytes  (Garcia-Pichel et al. , 2010; Benzerara et al. , 2014; Guida and Garcia-Pichel, 2016)  leading to marine and terrestrial carbonate erosion and deleterious effects on coral reef and bivalve ecology. Hyella is a euendolithic baeocytous genus characterized by cells surrounded by a firm sheath, and the thalli often form branching pseudofilaments that can grow on calcium carbonate substrates  (Al-Thukair and Golubic, 1991; Al-Thukair, 2011; Brito et al. , 2017). To date, thirteen genomes representing five baeocyte-forming genera have been reported (NCBI and IMG/JGI databases) but none from Hyella is available so far. Beyond evolution and classification of the organisms, the growing interest in genomics of cyanobacteria is driven by the discovery of new drugs  (Kleigrewe et al.
Horizontal Gene Transfer The high number of putative orthologs shared between H. patelloides and the other baeocyte-forming strains studied (Table  1 ) suggests horizontal gene transfer (HGT). To evaluate this transfer, the Ks values for a set of orthologs identified in all strains ("All"; Supplementary Table  S2 ) were compared against the set of orthologs found in H. patelloides and another strain only ("Pair"; Supplementary Table  S6 ). The dataset for "All" is the 1209 concatenated gene alignments with an average of 261835. 7 synonymous sites, while the datasets for the Ks distributions under the label   8366. 7, 14767, 30910. 2, 4798. 08, and 1581. 6 , synonymous sites, respectively). If the pattern was created by HGT, the Ks value estimated for a "Pair" will be lower than the Ks estimated for "All.
PCC 7319. In addition, we addressed if the HGT events could be mainly related to plasmid transfer. Among the studied strains, only Stanieria spp. have their genomes assigned in chromosome and plasmids (Stanieria cyanosphaera PCC 7437: Chr -5. 04 Mb and 5 plasmids -0. 50 Mb (9. 1%); Stanieria sp. NIES-3757: Chr -5. 32 Mb and 1 plasmid -0. 14 Mb (2. 6%). Therefore, plasmid sequences in the H. patelloides genome, as well as in the other strains studied, were predicted using PlasFlow (default parameters, threshold = 0. 7) (Supplementary Table  S9 ). For both Stanieria strains, the fraction (base pairs) predicted to be located in plasmids is in line with the values reported in the databases. However, this is only true if the category "unclassified" is assumed to be "chromosome. " Therefore, for the remaining genomes, the same assumption was followed.
Natural Product Biosynthetic Gene Clusters and Hydrocarbons Production A total of 21 biosynthetic gene clusters (BGCs) involved in the production of natural products were identified in the H. patelloides genome. Interestingly, H. patelloides and Pleurocapsa sp. PCC 7319, both isolated from a marine organism shell (intertidal zone), harbor the highest number of predicted BGCs (21 and 23, respectively) (Supplementary Table  S1 ). The H. patelloides BGCs include three polyketide synthase (PKS), four non-ribosomal peptide synthetase (NRPS), five hybrid PKS/NRPS, six RiPPs, and three terpenes. Remarkably, most of these BGCs displayed low similarity with the ones available in the antiSMASH database (Supplementary Table  S12 ). However, two of H. patelloides BGCs have similarities with the ones identified in other cyanobacterial strains.
patelloides was further investigated, revealing that this cyanobacterial strain produces hydrocarbons with C 15 chain length, such as 1-pentadecene (C 15:1 , 1) and 2-pentadecene (C 15:1 , 2) (Figure  8A ). Furthermore, the investigation of the fatty acid substrates for the OLS pathway showed that this strain synthesizes C 14 , C 16 , and C 18 fatty acids, being C 16 the most abundant. In total, the amount of fatty acid in H. patelloides exceeds 4% of the Dry Cell Weight (DCW) (Figure  8B ). S13. As stated above, the majority of the H. patelloides BGCs displayed low similarity with the databases. Thus, in order to evaluate if they could be strain-specific BGCs we run them through the BiG-SCAPE software  (Navarro-Muñoz et al. , 2020). In this analysis, the 104 predicted BGCs from H. patelloides and the baeocyte-forming strains (Supplementary Table  S1 ), as well as the ones from the Minimum Information about a Biosynthetic Gene cluster (MIBiG) repository  (Kautsar et al.
Genome Sequencing and Assembly Genomic DNA was extracted using the phenol/chloroform method described previously  (Tamagnini et al. , 1997) , with the exception that the first aqueous phase was run through a Phase Lock Gel TM tube (5 Prime, Hilden, Germany) prior to chloroform extraction and DNA precipitation. Genomic DNA was sequenced at the Genomics Core Facility at the i3S institute (GENCORE), Porto. Libraries of 200 and 600-base-pair-reads were sequenced using an Ion Torrent S5 TM XL Sequencer (Thermo Fisher Scientific). As the unicyanobacterial culture of Hyella was not axenic, its genomic data set was treated as a metagenome, and further binned to obtain cyanobacterialspecific contigs. The reads were initially assembled using the SPAdes v3. 11. 1  (Bankevich et al. , 2012)  and the ion-torrent specific option, the built-in read correction tool, and K-mer sizes 21, 33, 55, and 77.
Contigs shorter than 1 kb were discarded resulting in a final set of 4818 contigs. A local BLASTn search using the 16S rRNA gene sequence of an uncultured marine cyanobacterium (JX477009) was performed and evidence for a minimum of nine different organisms was obtained. Besides the 16S rRNA gene sequence for H. patelloides, eight different bacteria were identified. Subject sequences were retrieved and a BLASTn analysis against the nt database at NCBI was carried out, revealing that the contaminants were from the Proteobacteria and Cytophaga-Flavobacterium-Bacteroides (CFB) groups. Thus, a local BLASTx was performed against a database containing the predicted proteomes of cyanobacteria (340 proteomes), proteobacteria (41109 proteomes) and CFB (1599 proteomes), and the first 20 hits were retrieved.
Genes identified in H. patelloides and another strain only, are listed in Supplementary Table  S6. The corresponding Fasta file showing the alignment of the concatenated sequences can be found in Supplementary Files S2-S7. The files have been used for the divergence analyses. The number of non-synonymous changes per nonsynonymous position (Ka) and the number of synonymous changes per synonymous position (Ks) values have been estimated using the DnaSP software  (Rozas et al. , 2017). The non-parametric Mann-Whitney test was used in order to determine whether the two samples could have been obtained from the same Ks distribution. Tajima's relative rate tests were performed using the Mega 7 software  (Kumar et al. , 2016).
Natural Product Biosynthetic Gene Clusters Analysis Natural product biosynthetic gene clusters (BGCs) of H. patelloides were identified using the genome mining software antiSMASH v5. 0  (Blin et al. , 2019). Subsequently, the identified BGCs were analyzed and compared against available cyanobacterial genomes using the MicroScope platform  (Vallenet et al. , 2019). BiG-SCAPE (Biosynthetic Gene Similarity Clustering and Prospecting Engine) software v1. 0. 0 3   (Navarro-Muñoz et al. , 2020)  was used to perform the biosynthetic gene cluster networking analyses. The dataset (input) included the 104 predicted BGCs (using antiSMASH v5. 0) from H. patelloides and the baeocyte-forming strains studied here. The MIBiG parameter was set to include the MIBiG repository v1. 4  (Kautsar et al. , 2020).
ACKNOWLEDGMENTS We would like to thank the  LABGeM (CEA/Genoscope  and  CNRS UMR 8030 ) and the  France Génomique National  infrastructure (funded as part of  Investissement d'avenir program  managed by  Agence Nationale de la Recherche , contract  ANR-10-INBS-09 ) for the support within the MicroScope annotation platform. We acknowledge  Dr. Jorge Navarro Muñoz  and  Dr. Marnix Medema  for their helpful advice with BiG-SCAPE.
FUNDING This work was funded by the  National Funds  through  FCT -Fundação para a Ciência e a Tecnologia, I. P. , under the project  UIDB/04293/2020 , and by the project  NORTE-01-0145-FEDER-000012 ,  Structured Programme on Bioengineering Therapies for Infectious Diseases and Tissue Regeneration , supported by  Norte Portugal Regional Operational Programme  ( NORTE 2020 ), under the  PORTUGAL 2020 Partnership Agreement , through the  European Regional Development Fund (ERDF). This work was also funded by the  FCT  grant  SFRH/BPD/115571/2016  (ÂB) and by the  FCT  Projects  UIDB/04423/2020  and  UIDP/04423/2020. This work was also supported by the  National Natural Science Foundation of China  (Grant  31570068 ). The authors acknowledged the support and the use of resources of  EMBRC-ERIC , specifically of the  Portuguese infrastructure node of the European Marine Biological Resource Centre  ( EMBRC-PT) CIIMAR -PINFRA/22121/2016 -ALG-01-0145-FEDER-022121 , financed by the  European Regional Development Fund (ERDF)  through  COMPETE2020 -Operational Programme for Competitiveness and Internationalization (POCI)  and national funds through  FCT/MCTES.
Methods Sample preparation. Sample #1 is a highly stoichiometric magnetite Fe 3(1-δ) O 4 with 3δ = 0. 0000 originally provided by Prof. J. Honig that has been used in previously studies  8, 9, 21. Samples #2 and #3 were synthesised through a modified route from Honig  17. Small microcrystals of Fe   22  was adjusted by reannealing the crystals in a vertical furnace with a fixed CO 2 /H 2 buffer gas flow, to control the oxygen partial pressure according to the thermodynamic equilibrium of magnetite  17  and reference tables derived from the JANAF database  23. Magnetisation. Magnetic measurements were recorded with a Quantum Design SQUID magnetometer after zero-field cooling in fields of 100 Oe (samples #1 and #2) or 500 Oe (sample #3) during warming. Microcrystals were fixed in Eicosane within the gelatine capsule.
Hole-doping levels x = 0. 0116 and 0. 0228 of samples #2 and #3, respectively, were estimated from their measured Verwey transition temperatures using the T V -x doping correlation plot in ref. 17. X-ray diffraction. Microcrystal X-ray diffraction data were collected on the diffractometer ID11 at ESRF (France). The wavelengths were all close to λ = 0. 16 Å. The microcrystals (40-60 μm) were suspended in paratone oil in a litholoop. Cooling in a magnetic field from ambient temperature to 80-90 K (as described in ref. 6  ) was used to align the magnetic easy axis of the crystal with the field, thus helping to create a unique monoclinic c-axis below the Verwey transition. Temperature was controlled with a nitrogen cryostream. Data sets were recorded at 90 K (samples #1 and #2) or 80 K (sample #3), with varying omega-step sizes, exposure times, beam fluxes and at different phi settings, for high redundancy and to observe both low angle fundamental diffraction peaks and high-angle weak superstructure reflections.
Data reduction and integration for sample #2 were performed using the same procedure as for #1 in ref. 8  , via Bruker SMART and SAINT software  24. For crystal #3, data were indexed and integrated using CrysalisPro 25 using an increased integration box (×2), and a filter for reflections above 50,000 counts to ensure detector linearity. Integrated results for each collection run were then processed using Sadabs  26  , applying a spherical absorption correction. The data were finally merged for refinement using Xprep  27  to a maximum resolution of 0. 28 Å. Structure refinements were carried out using SHELXL software  28  and took both monoclinic and orthorhombic twin domains into account (excluding inversion twinning). Samples #2 and #3 were found to show substantial monoclinic twinning. All 168 of the variable atomic coordinates were refined independently, subject to the origin constraints of space group Cc.
High-resolution powder diffraction patterns for sample #3 were recorded at the ID22 beamline of ESRF from 55 to 325 K using a helium cryostat with λ = 0. 354224 Å. Rietveld refinements were performed using Fullprof software  29  , and the monoclinic unit-cell parameters at 80 K were used as the values for the singlecrystal refinement. Distortion modes. Local distortion mode parameters are used to quantify the magnitude and changes of local distortions of the low-temperature magnetite structure with doping. Distortions of FeO 6 octahedra have been previously described by local modes Q in the O h point group  8. The radial expansion (breathing) mode Q rad is calculated from Eq. (1). Q rad ¼ X i d i À hdi ffiffi ffi 6 p ð1Þ where d i are the six Fe-O distances in the octahedron and <d> is the global average octahedral Fe-O distance.
Analysis of differentially-expressed genes To explore the responses of BAT93 and JaloEEP558 to strain CFBP6546R, transcriptomes of inoculated leaves were produced. In other Xanthomonas-plant pathosystems such as tomato  [54] , rice  [55]  or sweet orange  [56, 57] , bacterial effectors impacted plant transcriptomes around 24 to 48 h after leaf infiltration. Here, we performed RNA-Seq analyses on inoculated leaves 48 h after infiltration. Illumina sequencing led to a total of 139. 4 and 138. 2 million raw reads for BAT93 and JaloEEP558 respectively, with an average of 23. 2 million raw reads per sample for BAT93 and 23. 0 million raw reads per sample for JaloEEP558 (Table  1 ). After stringent quality check, data cleaning and mapping, we obtained an average of 20. 2 million mapped reads on genes per sample (87% of raw reads) for BAT93 and 20.
DEGs belonging to "signaling" were mostly upregulated in the core transcriptome, while specific transcriptomes comprised both upregulated and downregulated genes. This suggests that common signaling pathways were induced in both genotypes, while other were specifically up-or downregulated in one genotype or another. GO analysis done using up-and downregulated genes separately highlighted different GO terms than when using the whole dataset of DEGs (Table  S5 ). It pointed out an upregulation of RNA metabolism and gene expression, as well as in nitrogen compound metabolic process in JaloEEP558, while the later was downregulated in BAT93.
Genes with high log 2 FC difference Interestingly, 201 DEGs had a large difference of expression (|Δlog 2 FC| > 5) between BAT93 and JaloEEP558 (Table  S8 ). Among those genes, 148 (74%) were more expressed in JaloEEP558 than in BAT93. This proportion was higher than what was observed for the whole dataset (52%), and this difference was even higher when focusing on the top 50 genes with the largest |Δlog 2 FC|, among which 46 had a higher log 2 FC in JaloEEP558 than in BAT93 (Table  S3 ). This indicates that the greatest differences observed between the two genotypes were due to genes strongly induced in JaloEEP558 and/or strongly repressed in BAT93. Of these 148 genes, the Heat Shock Protein (HSP) family was the most represented with 13 members, four of which belonged to the top 10 genes more expressed in JaloEEP558 than in BAT93.
Plant materials, bacterial strains and growing conditions The original seeds from common bean cultivars BAT93 (Mesoamerican) and JaloEEP558 (Andean) were obtained from the Center for Tropical Agriculture (CIAT, Colombia) and are available under accession numbers G51294 and G9603, respectively (http://genebank. ciat. cgiar. org/genebank/main. do). Common bean cultivars were seeded in plastic pots (7 × 7 × 8 cm) containing prewetted soil. Plants were grown in a growth chamber at 23 °C/20 °C (day/night) with 80% relative humidity and a photoperiod of 16 h. Plants were watered every 2 days with water for the first 10 days, then with a nutrient solution of N-P-K  (15-10-30). The day before inoculation, relative humidity and temperature were increased at 95% and 28 °C/25 °C (day/night) to provide adequate conditions for infection.
Bean whole genome sequencing, assembly and annotation Genomic DNA was extracted from young leaves and buds using the Nucleospin Plant II kit (Macherey-Nagel, Hoerdt, France). Paired libraries were prepared using the Illumina TruSeq Nano DNA Library prep kit, then sequenced at 2 × 150 bp on an Illumina HiSeq3000. Reads were trimmed to the first undefined base and assembled using SOAPdenovo software with k-mer size of 81 bp and max read length of 100 bp. Assembled contigs were gap filled and spurious assemblies were removed using redundancy search (97% identity, maximum overhang 50 bp). Scaffolds of minimum 1000 bp with at least 500 bp defined were retained. Annotation of the whole genome assembly was performed using EuGene-EP pipeline  [135]  using our BAT93 or JaloEEP558 RNA-Seq assemblies and four different protein databases as training sets for structural annotation: TAIR10, Swiss-Prot, UniProt plant subset and predicted proteins from the soybean (Glycine max) reference genome  [136].
Gene completeness was assessed using BUSCO version 1. 22 and the plantae dataset  [137]. Gene functions presented here were determined by BLASTp (e-value ≤1 × 10 -6 ) on the P. vulgaris v2. 1 reference genome from genotype G19833  [18]. Homologs between BAT93 and JaloEEP558 were searched for by reciprocal BLASTp (e-value ≤1 × 10 -6 ) of all predicted genes, and keeping only genes having the same best hit after both reciprocal BLASTp searches and the same best hit after BLASTp on the P. vulgaris reference genome. The four QRLs to CBB described in a BAT93 x JaloEEP558 progeny  [50]  were delimited by using the sequence of restriction fragment length polymorphism (RFLP) markers flanking these QRLs (Table  S11 ), available at the PhaseolusGenes database (http://phaseolusgenes. bioinformatics. ucdavis.
RNA-Seq experiments have been performed on an Illumina HiSeq3000 using a paired-end read length of 2 × 150 pb with the Illumina HiSeq3000 sequencing kits. Total reads were mapped on the annotated genome sequences of BAT93 or JaloEEP558 and counted using the glint software (http://lipm-bioinfo. toulouse. inra. fr/download/ glint). Only best-scores were taken into account, with a minimal hit length of 40 bp, a maximum of 5 mismatches and no gap allowed. Ambiguous matches with the same best score were removed. Principal component analysis and a Pearson correlation matrix were performed with R, using the number of reads per genes within each sample.
genome. jp/ kegg/mapper. html). Lists of DEGs associated with the cell wall or the metabolism of lipids were extracted using corresponding MapMan Bin codes. Transcription factors (TFs), kinase genes and RLKs used in this study were retrieved from the iTAK database (http://itak. feilab. net) [142]. The complete set of common bean NLRs was retrieved according to Richard et al. 2017a  [143].
Acknowledgements The authors thank  Céline Rousseau  from the PHENOTIC platform for her help in the analysis of chlorophyll fluorescence and  Muriel Bahut  from the  ANAN  platform for her help in performing RT-qPCR assays. The authors also thank the  French Network on Xanthomonads (FNX)  (https://www. reseau-xantho. org/) for recurrent scientific exchange within the framework of the  ANR CROpTAL  project and particularly  Lionel Gagnevin  for critical reading of the manuscript. Bacterial strain preservation and supply is ensured by the  CIRM-CFBP (Beaucouzé, INRA , France; https://www6. inrae. fr/cirm_eng/CFBP-Plant-Associated-Bacteria).