dataesr/scientific-paragraphs-categorization huggingface dataset:
Additional observations of the sample microstructure were carried out under a Scanning Electron Microscope (SEM-JEOL JSM 6510LV), using secondary electron imaging (SEM-SEI) mode, while ImageJ free software was used to analyse the SEM images and evaluate both grain and precipitate area and size. In addition, Energy Dispersive X-ray (EDX-PGT PRIMS2000) spectroscopy coupled with the SEM device allowed elementary chemical mapping of the Mg, Nd and Zr elements to be performed. Quantitative elemental chemical analyses were also carried out (volume of the analysed area: some mm 3 ) using an Electron Probe Micro-Analyser (EPMA e CAMECA SX50). Ten measurements were made over the whole sample surface. Analysis of the pickling solutions used was performed by Inductively Coupled Plasma (ICP) mass spectrometry using a spectrophotometer (Thermofischer Scientific ICP-AES, IRIS) at the Service Central d'Analyses (Villeurbanne) to evaluate Mg, Nd, Gd, Zr, Zn releases resulting from the alloy etching.
Acknowledgements The present work was carried out as a part of the  CAR-AIBE  project. The  FDA  and the OSEO are gratefully acknowledged for the financial support they provided for this project. The authors are grateful for partnership from  Liebherr, Turbomeca, Eurocopter, Mecaprotec ,  Fonderie Messier  and the  Institut Carnot CIRIMAT. The authors would like especially to thank  Philippe de Parseval  from the LMTG for the EPAM measurements.
Leptosphaeria maculans 'brassicae' is a damaging fungal pathogen of canola (Brassica napus), causing lesions on cotyledons and leaves, and cankers on the lower stem. A related species, L. biglobosa 'canadensis', colonises cotyledons but causes few stem cankers. We describe the complement of genes encoding carbohydrate-active enzymes (CAZys) and peptidases of these fungi, as well as of four related plant pathogens. We also report dual-organism RNA-seq transcriptomes of these two Leptosphaeria species and B. napus during disease. During the first seven days of infection L. biglobosa 'canadensis', a necrotroph, expressed more cell wall degrading genes than L. maculans 'brassicae', a hemi-biotroph. L. maculans 'brassicae' expressed many genes in the Carbohydrate Binding Module class of CAZy, particularly CBM50 genes, with potential roles in the evasion of basal innate immunity in the host plant.
In vitro derived RNA was sequenced with 100 bp paired-end reads in order to aid gene annotation, and in planta derived RNA was sequenced with 100 bp single-end reads. A total of 15. 5 Gbp sequence was generated from the in vitro libraries of the two fungi (7. 75 Gbp per sample), and 72 Gbp sequence was generated from 12 in planta libraries (6 Gbp per sample) (Table  S1  in file S2). Reads were trimmed to a minimum phred quality score of 20 using Nesoni sequence software  [26] , orphaned members of pairs were retained, adaptor sequences were removed, and reads shorter than 20 bp were rejected. Trimmed reads were aligned to a reference genome sequence with Tophat v1. 4. 1 splice-junction mapper  [26]. Reference genomes were Lmb isolate v23. 1. 3 [2] , Lbc isolate J154  (Grandaubert et al. , submitted) , and a Brassica exon array curated unigene set representing 135,201 gene models from B.
napus, B. rapa and B. oleracea  [27]. Aligned reads were quantified using Cufflinks v1. 0. 3 transcript assembly and quantification software and denoted as average expression levels (FPKMfragments per kilobase of exon per million mapped reads)  [28]. Cufflinks was run with bias correction to reduce variance due to sequence positional bias during Illumina sequencing. Gene expression FPKM values are listed in the relevant supplementary tables. All of the aligned RNA-seq reads have been deposited at the NCBI Sequence Read Archive (SRA), accessible under bioproject accession PRJNA230885 or sequence read archive SRP035525. SRA files may be read using the NCBI SRA toolkit (http://www. ncbi. nlm. nih. gov/sra). Quantitative RT-PCR experiments were carried out to determine levels of expression of genes containing CBM50 (LysM) domains.
Annotation of genes and domains Genes encoding CAZys were identified in six dothideomycetes (Lmb, Lbc, A. brassicicola, S. nodorum, P. tritici-repentis and Z. tritici) using www. cazy. org [29]  and the dbCAN v3. 0 HMM-based CAZy annotation server (http://csbl. bmb. uga. edu/dbCAN/) [30]. The major CAZy classes are Polysaccharide Lyases (PL), Glycosyl Transferases (GT), Glycosyl Hydrolases (GH), Carbohydrate Esterases (CE), Carbohydrate Binding Modules (CBM) and Auxiliary Activities (AA). Secretion signal peptides were predicted using the SignalP 4. 0 algorithm  [31]. Pfam domains (Pfam A and B) were identified using profile hidden Markov models with HMMER3. 0  [32]  and Pfam_scan. pl software; the e value cut off was set to 1e-5  [33]. LysM-containing genes (with CBM50 domain) were examined in more detail.
Predicted gene models and aligned RNA-seq reads were viewed with the IGV browser  [34] , predicted intron splice sites were verified and translation start sites were checked for congruence with observed RNA-seq transcript boundaries. They were initially identified by comparison to the Pfam database  [33] , and then aligned to ECP6, the well characterised LysM-containing protein from Cladosporium fulvum  [35]. Other Leptosphaeria proteins with LysM motifs were identified and characterised as described in supporting information (Figure  S1  in file S1). Peptidase domains were identified by BlastP  [36]  comparison of predicted protein sequences to the MEROPS 'peptidase database pepunit. lib dataset' of database of peptidase and inhibitor units (http://merops. sanger. ac. uk)  [37].
Analysis of expression of fungal and B. napus genes The 100 most highly up regulated genes of Lmb and Lbc at 7 and 14 dpi, compared to in vitro growth, were identified from the RNA-seq data (Table  S  3-6 in file S2). Averages of quantilenormalised log10-transformed FPKM values were calculated for each dataset for direct comparison of CAZy gene expression between Lmb and Lbc. Genes containing a CBM, GH, PL or AA domain and predicted to be secreted were analysed further. The sum of the expression values of each CAZy gene across the three treatments (in vitro, 7 and 14 dpi) was determined and the top 100 genes were identified. Quantile-normalisation was applied so that expression values of genes of both fungi could be directly compared and log10-transformed FPKM values were graphed. For each treatment, a heat map based on expression values was generated.
B. napus defence genes, 9-cis-epoxycarotenoid dioxygenase 3 (NCED), 1-amino-cyclopropane-1-carboxylate synthase 2(ACS2),   [38]  were identified (Table  1 ). Their RNA-seq expression was analysed at 7 and 14 dpi in inoculated and uninoculated cotyledons. Additionally, expression of Brassica genes involved in metabolic pathways was compared at 7 dpi by either Lmb or Lbc, and then analysed using MapMan, software that processes large gene expression datasets into metabolic pathways or other processes  [39]. A Wilcoxon rank sum test with Bonferroni correction for multiple tests was used within MapMan to identify 20 functional categories of B. napus genes that were significantly regulated in response to infection by Lmb or Lbc.
General features of fungal and plant transcriptomes RNA-seq was used to define the transcriptomes of both pathogens and host during infection. A total of 87. 5 Gbp of raw sequence was generated across all libraries (Table  S1  in file S2). In spite of the differences in disease symptoms at 7 dpi, the percentage of Lmb and Lbc reads aligned to the Lmb and Lbc reference genomes was similar (5 and 6% of the total), while 61 and 44% of reads aligned to the reference genomes at 14 dpi (Figure  2 ). These data reflect that by 14 dpi the plant tissue is heavily colonised by both fungi. As expected, very few reads (less than 1%) from the mock-infected plant libraries aligned to the Leptosphaeria reference genomes. These libraries represent highly complex large datasets and Principal Component Analysis was carried out to compare the overall features of the transcriptomes, particularly gene identity and expression level.
Distribution of CAZy domains and their expression In view of the dominance of CAZys in the 20 most highly expressed genes of Lbc after seven days in planta, CAZy domains were sought in genome sequences of Lbc, Lmb, and also in four other Dothideomycetes for comparison. The repertoire of domains derived from the dbCAN database and its HMM-based sequence similarity search was consistent with CAZy classifications carried out previously on Dothideomycetes (Table  S7  in file S2)  [18, 42] , and the www. cazy. org annotation for Lmb isolate v23. 1. 3. In general, the numbers of carbohydrate-binding module (CBM), glycosyl hydrolase (GH), glycosyl transferase (GT), and polysaccharide lyase (PL) domains were in agreement with previous studies (Table  6 ). CAZys are divided into sub classes, generally based on substrate specificity or ligand; some of these are described later.
Two CAZy classes in Lmb were identified more frequently using our analyses; CE domains (109 vs 34) and AA (78 vs 27). The difference in numbers of CE domains was probably because 27 CE1 and 42 CE10 domains had been previously excluded from the CAZy expert curated dataset on the basis that they were likely to act upon non-carbohydrate substrates  [43]. AA domains are a newly formed CAZy classification for ligninolytic or lytic polysaccharide monooxygenases. Our automated approach may have included closely related monooxygenases that do not degrade lignin or polysaccharides. Most of the CAZy containing-genes had only one CAZy domain, but several had multiple CBM domains, particularly of the subclass CBM50 (see later and Figure  S1  in file S1). Five of the six dothideomycetes had between 580 and 700 CAZy domains, but Z.
maculans 'brassicae' (Lmb) or L. biglobosa 'canadensis' (Lbc). RNA-seq gene expression values for a B. napus unigene set  [27]  were used to calculate a ratio of expression values (log2) for B. napus genes after infection by Lmb or Lbc. Ratios were plotted on major metabolic pathways with Mapman software  [39]. A yellow square indicates a B. napus gene that is expressed more highly during Lmb infection, while a blue square indicates a B. napus gene with higher expression during Lbc infection. An expression ratio close to zero is shown with a white square and indicates equivalent expression during infection by either pathogen. Only genes with expression values greater than 10 FPKM were included. Abbreviations: LDH, lactate dehydrogenase; ADH, Alcohol dehydrogenases, TCA, tricarboxylic acid cycle; raff, raffinose; Treh, trehalose; PSI, photosystem one; PSII, photosystem two; ABA, abscisic acid; ET, Ethylene; SA, salicylic acid; JA, jasmonic acid.
The increased level of expression of B. napus genes involved in ethylene, jasmonic acid and salicylic acid signalling during Lbc infections prompted further examination of biochemical pathways during infection. A ratio of expression values of B. napus genes at 7 days after infection with Lmb compared to Lbc was calculated and analysed by MapMan software to identify pathways coordinately responding to early infection of the cotyledon (Figure  6 , Table  9 ). The major difference in host response to infection by the two fungi was in genes with photosynthesis-associated activities. L. biglobosa 'canadensis' infection resulted in massive down-regulation of genes involved in photosynthesis (e. g. PSI, PSII), electron transport, photorespiration and chlorophyll (tetrapyrrole) biosynthesis compared to that in Lmb.
A cohort of genes associated with secondary metabolism in B. napus was also plotted using Mapman on the same dataset (Figure  S3  in file S1). Isoflavone reductase genes associated with isoflavonoid biosynthesis, were more highly expressed during Lbc infection, while genes associated with carotenoid metabolism (phytoene dehydrogenase, zeta-carotene desaturase, lycopene cyclases and violaxanthin de-epoxidase) were expressed more highly during Lmb infection. These observations are in agreement with the increased necrosis observed during Lbc infection at the early stages of infection. As well as increased expression of secondary metabolism genes during Lbc infection, peroxidase, nitrilase, and cytochrome P450 genes were consistently upregulated by B. napus at 7 dpi (Figure  S3  in file S1). Twenty four general peroxidases were upregulated suggesting a strong oxidative burst was deployed during infection by Lbc.
In contrast, L. biglobosa 'canadensis' expresses a high number of cell wall degrading CAZy genes during the first seven days of infection, consistent with extensive necrosis and a high degree of activation of host defence signalling pathways. Figure  S3 , Response of B. napus secondary metabolism and large enzyme families to infection by L. maculans 'brassicae' or L. biglobosa 'canadensis. 'RNA-seq gene expression values for a B. napus unigene set  [27]  were used to calculate a ratio of expression values (log2) for B. napus genes seven days after infection by Lmb or Lbc. Ratios were plotted on secondary metabolism gene groups using MapMan software on maps for 'Secondary metabolism', and 'Large enzyme families' maps  [39]. A yellow square indicates a B. napus gene that is expressed more highly during Lmb infection, while a blue square indicates a B.
The following sources of funding supported this work:  Grains Research and Development Corporation  for funding RL  AW BC BH , the  Australian Research Council  for funding AC, the  Victoria Life Sciences Computation Initiative (VLSCI)  for computational resources via grant  RAS990  for RL, the  University of Melbourne  for an  Early Career Researcher award  to RL, and the  French agency Agence Nationale de la Recherche , contract  ANR-09-GENM-028  (' FungIsochores ') for funding JG and  TR. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
RRES unigenes are listed from the Brassica exon array [27], to which RNA-seq reads were aligned. Corresponding GenBank accession numbers are given for each gene. The response of each gene (with the exception of PDF1. 2) to its corresponding signalling pathway was confirmed by Sasek et al [50]. doi:10. 1371/journal. pone. 0103098. t001 Figure 1. Symptoms on cotyledons of B. napus cv. Westar infected with L. maculans 'brassicae' or L. biglobosa 'canadensis'. B. napus cv. Westar cotyledons were wounded and inoculated with Lmb or Lbc spores and disease allowed to progress for 17 days post inoculation (dpi). Cotyledons were harvested and photographed at 3, 5, 7, 10, 14, and 17 dpi to track lesion development by the two pathogens. doi:10. 1371/journal. pone. 0103098. g001Figure 2. Percentages of plant and fungal transcripts in B.
doi:10. 1371/journal. pone. 0103098. t002 Pfam expect score 4. 2E-08 9. 0E-57 3. 9E-08 2. 1E-33 5. 7E-23 6. 4E-57 4. 1E-43 8. 0E-140 Pfam description and accession Pfam-B_14615 [PB014615] Cytochrome P450 [PF00067. 17] LysM domain [PF01476. 15] Pfam-B_2613 [PB002613] Transferase family [PF02458. 10] Cytochrome P450 [PF00067. 17] Cytochrome P450 [PF00067. 17] Pfam-B_8517 [PB008517] Log2 (7dpi FPKM/in vitro FPKM) 16. 9 15. 3 13. 7 13. 7 13. 1 13. 0 12. 5 12. 5 12. 4 12. 3 12. 3 11. 7 11. 5 11. 5 11. 5 11. 4 11. 2 11. 1 11. 0 10. 9 in vitro (FPKM) 0. 1 0. 1 0. 1 0. 1 0. 3 0. 1 0. 5 0. 1 0. 3 0. 1 0. 1 0. 8 0. 1 1. 8 0. 1 0. 1 0. 7 0. 1 0. 6 0. 2 in planta (FPKM) 14dpi 1163. 5 728. 9 30. 2 38. 6 70. 8 42. 8 207. 0 24. 7 59. 3 3. 4 3. 9 105. 4 19. 0 1356. 8 6. 2 2. 1 96. 0 2. 1 6. 9 34. 8 7dpi in planta (FPKM) 12645.
12] Pectate_lyase [PF03211. 8] Trypsin [PF00089. 21] Pfam-B_14072 [PB014072] Cellulase (glycosyl hydrolase family 5) [PF00150. 13] Putative amidotransferase (DUF4066) [PF13278. 1] Glycosyl hydrolases family 43 [PF04616. 9] Sugar (and other) transporter [PF00083. 19] Log2 (7dpi FPKM/in vitro FPKM) 17. 0 16. 2 13. 5 13. 2 13. 2 12. 8 12. 6 10. 4 10. 3 10. 3 10. 2 10. 2 10. 1 10. 0 9. 9 9. 9 9. 9 9. 7 9. 5 9. 4 in vitro (FPKM) 0. 01 0. 01 0. 1 0. 1 0. 04 0. 1 0. 05 0. 5 4. 7 1. 2 6. 0 3. 2 0. 4 0. 9 1. 4 13. 1 0. 7 0. 4 1. 9 0. 9 7dpi in planta 14dpi in planta Gene name Gene name (FPKM) (FPKM) Lb_j154_P000524 886. 3 18. 0 Lb_j154_P003557 515. 7 63. 8 Lb_j154_P001652 1083. 8 151. 2 Lb_j154_P009247 1012. 1 146. 1 Lb_j154_P006347 341. 8 76. 1 Lb_j154_P002168 878. 3 9. 0 Lb_j154_P001276 317. 1 24.
20] Alcohol dehydrogenase GroES-like domain [PF08240. 7] Log2 (14dpi FPKM/in vitro FPKM) 14. 0 13. 2 11. 3 11. 0 10. 6 10. 4 10. 4 10. 4 10. 2 9. 4 9. 4 9. 3 9. 2 9. 2 9. 1 9. 0 9. 0 9. 0 9. 0 8. 9 in vitro (FPKM) 0. 01 0. 01 0. 01 0. 04 0. 1 0. 1 4. 7 0. 01 0. 01 0. 01 13. 1 0. 01 8. 5 2. 8 0. 1 0. 01 0. 2 0. 05 6. 1 3. 5 7dpi in planta 14dpi in planta Gene ID Gene name (FPKM) (FPKM) Lb_j154_P003075 156. 1 116. 5 Lb_j154_P003557 515. 7 63. 8 Lb_j154_P000524 886. 3 18. 0 Lb_j154_P006347 341. 8 76. 1 Lb_j154_P001652 1083. 8 151. 2 Lb_j154_P009247 1012. 1 146. 1 Lb_j154_P010735 5991. 3 6460. 7 Lb_j154_P001707 63. 1 9. 2 Lb_j154_P006327 113. 6 8. 5 Lb_j154_P008556 1. 4 4. 9 Lb_j154_P000527 12641. 8 8785. 2 Lb_j154_P000350 32. 9 4. 3 Lb_j154_P006232 3710. 7 5194. 8 Lb_j154_P005193 1399. 2 1588.
For example, the Erg11Δ/ERG11 strain represents a "hit" as it had the largest FD in the fluconazole HIP profile and passed significance and specificity thresholds  (10). Fluconazole inhibits the protein Erg11, thus demonstrating the ability of HIP to identify targets in vivo (Fig. 1A ). Fluconazole HOP identified mechanisms that buffer the ergosterol pathway, including the requirement for iron (Fig. 1A ). Gene Ontology (GO) enrichments are provided for each profile (fig. S2 )  (10). Additional relationships among genes, profiles, pathways, and compounds can be explored with the interactive online HIPHOP chemogenomic database http://chemogenomics. pharmacy. ubc. ca/HIPHOP/ (10). In total, HIP identified 317 compounds that specifically perturb the function of 121 essential genes. To distinguish these compounds from drugs or credentialed chemical probes, we refer to them as "chemical-genetic probes," and to their interacting gene partners as "HIP hits"  (10).
Acknowledgments Supported by the  National Human Genome Research Institute  ( RO1 003317-07 ) (C. N. , G. G. , and  R. W. D. ) ;  Canadian Cancer Society Research Institute  (# 020380 ) (C. N. and G. G. );  Canadian Institute for Health Research  ( MOP-81340 ) (G. G. ),  MOP-79368  (G. W. B. ), and  MOP-700724  (W. S. T. );  Canadian Research Chair  (G. G. );  Charles H. Best Institute  (A. Y. L. );  Belgian National Fund for Scientific Research  and the  Interuniversity Poles of Attraction Program  (M. B. );  French National Research Agency  (J. C. );  Marie Curie Fellowship  (I. M. W. );  Leukemia and Lymphoma Society  (A. D. S. );  Robert A. Welch Foundation  (V. A. B. ); and  NIH  grants ( GM103504 ) (G. D. B. ) and GM44530 (V. A. B. ).
Because many of our species had never been subjected to large-scale sequencing, 2 gigabases (Gb) of data per sample was sufficient to increase the number of plant genes by approximately 100-fold in comparison to the totality of the public databases. The 1KP project began as a public-private partnership, with 75% of the funding provided by the Government of Alberta and 25% by Musea Ventures. Significant in-kind contributions were provided by BGI-Shenzhen in the form of reduced sequencing costs and by the NSF-funded iPlant collaborative  [1]  in the form of computational informatics support. Many plant scientists from around the world were involved in the collection of live tissue samples and in the extraction of RNA. Additional computing resources were provided by Compute Canada and by the China National GeneBank.
Review Access to raw and processed data Our initial phylogenomics effort used sequences from multiple sources. They include transcriptomes from 1KP representing 85 species, transcriptomes from other sources representing 7 species, and genomes representing an additional 11 species. A summary of these data sources is given in Table  1. We submitted all of the unassembled reads from the 1KP transcriptomes to the Short Reads Archive (SRA) under project accession PRJEB4921 "1000 Plant (1KP) Transcriptome: The Pilot Study. " Note that, with the exception of Eschscholzia californica, we sequenced only one sample per species. To make it easier for others to reproduce our phylogenomics analyses, we are releasing our intermediate computations, not just the final results. Everything is hosted at the iPlant Data Store, a high performance, large capacity, distributed storage system.
We only knew that, just as there was value in sequencing every gene in a genome, despite not knowing a priori what many of the genes might do, there would be value in sequencing across an ancient and ecologically dominant clade, even when many of the species have no obvious economic or scientific value that would justify a genome sequencing effort. Transcriptomes were a less expensive way to explore plant diversity, and demonstrate value beyond the obvious species. Meta-assembly refers to a transcriptome assembled from more than one sequenced sample. Some of these were a combination of 1KP and other data; some were entirely non-1KP. Accession numbers (SRA or otherwise) are given for all of the transcriptomes that we used. In some instances, users will find many directories with similar names, as indicated in this table by hash (#) marks.
Acknowledgments The 1000 Plants ( 1KP ) initiative, led by GKW, is funded by the  Alberta Ministry of Innovation and Advanced Education, Alberta Innovates Technology Futures (AITF) ,  Innovates Centre of Research Excellence (iCORE) ,  Musea Ventures, BGI-Shenzhen and China National GeneBank  (CNGB). We thank the many people responsible for sample collection on  1KP  and the staff at  BGI-Shenzhen  for doing our sequencing. Phylogenomic analyses were supported by the  US National Science Foundation  through the iPlant collaborative. CANDO was funded by an  NIH   Director's Pioneer Award   1DP1OD006779-01.
Recent improvements in satellite altimetry data correction terms are encouraging studies of the remote sensed sea level anomalies (SLA) progressively closer to the coast and over shallow continental shelves. In this paper we describe and discuss the SLA trend and variability at seasonal and interannual time scales in the southeastern South American continental shelf influenced by the Río de la Plata estuary and the Patos Lagoon fresh waters. The spatio-temporal coverage of the gridded altimetry SLA data allows identify several variability patterns and the associated physical processes. On seasonal time scales, the combination of the solar radiation and wind forcing cycles accounts for up to 98% of the variability. Seasonal variability of the wind is responsible for a difference of up to 16 cm between the southern (Argentinean) Río de la Plata estuary coast and the Uruguayan and southern Brazilian coasts.
On interannual time scales, positive/negative SLA anomalies are coherent with El Niño/La Niña events. Finally, a significant positive trend of up to 5 mm yr À 1 is found in all the study area except in the region around the Patos Lagoon (Brazil) and part of the Río de la Plata. Besides the local relevance of the results, this study indicates that satellite altimetry data are accurate enough to unveil SLA spatio-temporal patterns close to the coast and over continental shelves in the mentioned time scales.