dataesr/scientific-paragraphs-categorization huggingface dataset:
Available data Paramecia, like other ciliates, harbour structurally and functionally distinct nuclei in their unique cytoplasm. A diploid germline micronucleus (MIC) undergoes meiosis and transmits the genetic information to the next sexual generation. A polyploid (800n in P. tetraurelia) somatic macronucleus (MAC), streamlined for gene expression through programmed DNA elimination, develops at each sexual generation and determines the phenotype. At D600 Nucleic Acids Research, 2020, Vol. 48, Database issue the time of the most recent ParameciumDB update (4), only the somatic genome of the P. tetraurelia model was available  (1). The MAC genomes of P. caudatum, P. sexaurelia and P. biaurelia were published in 2014 (9,10) followed by many more genomes for aurelia species, the P. bursaria and P.
All IESs can be visualized in the genome browser which links to IES pages with additional information. Intragenic IESs also appear on Gene pages. In the future, germline genomes from more species, their IESs and other germline-limited elements such as transposable elements will be included in ParameciumDB. An exponentially growing number of genomic datasets from mechanistic studies of P. tetraurelia biological processes are integrated into ParameciumDB. In addition to RNA-Seq developmental time-course data (13), a majority of the functional datasets currently available consist of DNA-Seq data generated by re-sequencing the somatic genome that developed after depletion of factors involved in the genome rearrangements. This can lead to retention of some or all IESs at the next sexual generation.
Technology components behind ParameciumDB Table  2  presents the tools and software components used by ParameciumDB. Like the previous versions of Parame-ciumDB, the current release takes advantage of tools developed by the GMOD project consortium. All genomic and post-genomic data are loaded into a Chado-PosgreSQL database  (25)  and also into a Bio::DB::SeqFeature::Store-MySQL database  (26)  for use by the genome browsers. To build the web interface, Perl-Template-toolkit technology was used for server-side dynamic web content generation. The client-side possibilities provided by Ajax-JavaScript  the BWA (31) mapper to check a sequence for possible offtarget matches.
Gene pages, the heart of the web interface All pages of ParameciumDB have a header with hyperlinks leading to the main sections of the website (cf. Figure  2 ). Beyond the classic link to the Home page, the Tools link reveals a dropdown menu with the available tools (see Table  2 ). The Download link is used to retrieve all the genomic data and annotations contained in ParameciumDB, as well as a daily SQL dump of the database. 2 , the Overview section includes important properties of the gene and its protein: name, synonyms, cross references, gene and protein sizes, species to which it belongs, genomic location and electronically inferred functional annotation. Below, a JBrowse inset shows a graphical representation of the gene. The genomic, coding and protein sequences are accessible in the Sequence section.
Thanks to the Action button, the user can easily initiate a homology search using BLAST, at ParameciumDB or at NCBI. The Transcription Unit section can provide additional information about transcript structure (introns, exons, 5 UTR, 3 UTR, TSS, polyA site)  (13). Any publications related to the gene are mentioned in the References section. Curation of the literature related to Paramecium biology is performed every month using PubMed, linking genes and bibliographic references. The Protein Domains section groups the results of domain predictions on protein sequences (pre-calculated results of HMMscan on the PfamA library, dynamic analysis using the NCBI Conserved Domain Database, prediction of signal peptides or transmembrane helices). Orthology between proteins of multiple Paramecium species is one of the novelties of this version of Parame-ciumDB.
FUTURE OF PARAMECIUMDB We hope that the inclusion of more and more Paramecium genomes will make ParameciumDB as useful to evolutionary biologists and population geneticists as it has been to cell and molecular biologists over the past decade. Beyond the goal of maintaining the database with a very small staff and little specific funding--which is only possible thanks to many wonderful open source software projects and to large well-funded generalist databases hosted by e. g. SBI, NCBI, EMBL-EBI--we hope to integrate more and more somatic and germline genomes and their annotations. We also plan to interface, integrate or develop better tools to facilitate comparison of genes, proteins and chromosomes. ParameciumDB can also provide added-value through expert human curation, as highlighted here for Paramecium mitochondrial genomes.
ACKNOWLEDGEMENTS We thank the  French National Sequencing Center (Genoscope CEA ) and the  France Génomique Paramecium Sequencing Project  coordinated by  Sandra Duharcourt  for help with the mitochondrial genomes for P. sonneborni, P. primaurelia and P. pentaurelia. We are grateful to  Michael Lynch ,  Tom Doak  and  Jean-Francois Go  ût for sharing Paramecium genomes. We thank  France Koll  for finding bugs and making numerous suggestions to improve ParameciumDB. The  Informatics and Scientific Calculation Service  of the I2BC has consistently supported ParameciumDB by providing infrastructure, help with purchase and configuration of servers and advice on deployment. We continue to benefit enormously from the  GMOD  project software and support. FUNDING ParameciumDB is supported by intramural funding from the  CNRS ;  Agence Nationale de la Recherche  [ ANR-14-CE10-0005-04  ' PIGGYPACK ',  ANR-18-CE12-0005-01  'LaMarque'].
Data storage (26) Interface Template toolkit v2. 24 Web content system http://www. templatetoolkit. org Web design Jquery (v2. 1. 4), Bootstrap (v3. 3. 5), font-awesome (v4. 5. 0) Javascript and CSS libraries https://jquery. com, https://getbootstrap. com, https://fontawesome. com/ DATA AVAILABILITY https://paramecium. i2bc. paris-saclay. fr.
To achieve this goal, we used LC coupled to high resolution mass spectrometry (HRMS) to draw a large-scale metabolic profile of the different compartments studied. Public databases were used to annotate the metabolic features found, and manual curation revealed 11 major classes of compounds in the matrices. The tissue localization of micropollutants and plant metabolites in poplar leaves was investigated by MSI, using the advantage of a control plant to search the discriminative metabolites that are mostly found in polluted poplar leaves, either micropollutants or plant metabolites. The hormonal profile of the trees was also investigated to search for a plant response to chronic exposure to low doses of micropollutants.
LC-Q-TOF-HRMS analysis Water, sludge and plant extracts were analyzed using liquid chromatography (LC) coupled to high resolution mass spectrometry (HRMS) on a DioneX Utlimate 3000 (Thermo) coupled to a Q-TOF Impact II (Bruker) using the TargetScreener method developed by Burker (Bremen, Germany). This method was already used by  Bergé et al. , (2018) , it allows the targeted identification of drugs and pesticides, but the data can also be investigated for untargeted analysis. Solvent A was composed of H2O:MeOH (90:10), 0. 01% formic acid and 314 mg. L -1 ammonium formate. Solvent B was composed of MeOH, 0. 01% formic acid, and 314 mg. L -1 ammonium formate. Samples were separated on a C18 column (Acclaim TM RSLC 120 C18, 2. 2 µm 120 A 2. 1x100 mm, Dionex bonded silica products) operated at 30°C for a total run time of 20 minutes.
LC-Q-TOF-HRMS data processing Raw formula annotations and tentative identifications in water, sludge and plant extracts were performed using Metaboscape 3. 0 (Bruker) and TASQ 1. 4 (Bruker) software, already used by  Olmo-García et al. , (2018)  and  Bergé et al. , (2018)  respectively. In TASQ, a database of 2204 drugs and pesticides was used to annotate ions in a targeted way based on the retention time, m/z value, mSigma and qualifier ions. In Metaboscape, all adduct forms were grouped to form a "bucket", representing one single metabolite feature used for annotations. An intensity threshold of 10 000 was applied for the extraction of metabolite features, which corresponds to a cutoff above 10 times the noise level in our experimental conditions, as already described in the literature  (Gago-Ferrero et al.
MSI analysis MALDI imaging acquisition was performed on a SolariX XR 7T spectrometer (Bruker) in MS positive ion mode using a mass range of 50-1000Da, with a transient size of 2M. On-line calibration was performed using the matrix peaks as reference masses. The laser power was set to 18% with a small focus, 50 shots and a frequency of 1000Hz. The raster width was set to 50 µm. Teaching of the points and definition of the regions of interest were performed using flexImaging 5. 0 (Bruker). Data acquisition was performed using ftmsControl 2. 2. 0 (Bruker).
MSI data processing Data obtained from MALDI imaging analysis were treated using SCiLS Lab2016b software as already shown in  Halade et al. , (2018). Total ion count normalization was applied before each statistical analysis. The segmentation pipeline was used to check for differences between control and polluted leaves, and then discriminative values were searched for using the software tool. The m/z intervals obtained were annotated using the Metaspace online platform (http://metaspace2020. eu)with the HMDB, CHEBI and SwissLipids databases. Metaboscape software (Bruker) was used to complete these annotations using the same analyte lists as described above, with a criterion of mass deviation (∆m/z) under 3 ppm. As described for LC-Q-TOF HRMS data processing,metabolite features annotated with only a raw formula were considered annotated, while metabolite features annotated with a raw formula and a name were considered tentatively identified.
Statistical analysis Statistical analysis of the MALDI imaging data was performed with SCiLS Lab 2016b software using the statistical tools provided to perform a spatial segmentation, a principal component analysis (PCA) and to search for discriminative values. The spatial segmentation analysis is a pipeline that performs successive steps: find peaks, peak alignment to maxima, spatial denoising, bisecting k-means. The bisecting k-means step is a clustering method that allows the iterative division of a set of spectra into two maximally different sets of spectra, permitting the segmentation of imaging datasets to visually identify differential regions according to their spectral patterns. This tool is explained in SCiLS Lab application note #6 available on the SCiLS Lab website (https://scils.
General overview of water, sludge and plant contents Three compartments of the environment were investigated using a nontargeted approach to gain an overview of the diversity of micropollutants that can be found at the exit of a water treatment facility. Water, sludge and black poplar leaves were sampled and extracted to analyze their contents using LC coupled to high HRMS. The results (Fig. 1 ) revealed that part of the compounds detected in the different samples were common to the three compartments of the environment. Conversely, some compounds were exclusively specific to only one compartment or two compartments (Fig. 1, A ). Tentative identifications (Level 3 of the Schymanski classification  (Schymanski et al. , 2014) ) were obtained by comparison with the public databases listed in section 2.
The metabolites of 67 common drugs were predicted using Metabolite Predict 2. 0 (Bruker), and used as an analyte list to search for drug metabolites in the samples. Commercial standards of 3-ethoxypropylamine, adenine, lyso PC 16:0, pheophorbide A, Dsalicin and piperidine were successfully used to confirm the tentative identifications obtained from MSI experiments by comparison of the retention time and MS/MS profiles (when available) of the commercial standards and the ions found in the plant extract (Level 1 of the Schymanski classification). Schymanski classification (Schymanski et al. , 2014) was used to assess the level of identification obtained, and is a reference cited in the literature (for example, Bergé et al. , (2018)). Metabolite features annotated with only a raw formula were considered annotated (level 4 of the Schymanski Tentative identifications were performed using analyte lists created from the toxic exposome database (http://www.
PS, plurilocular sporangium (asexual reproduction). Gametes of the oro mutant (lower panel) are unable to initiate the sporophyte program and develop parthenogenetically to produce partheno-gametophytes. The mutation is recessive so a cross with a wild type gametophyte produces a heterozygous diploid sporophyte with a wild type phenotype. (B) Young gamete-derived parthenotes of wild type and oro strains. Arrowheads indicate round, thick-walled cells typical of the sporophyte for the wild type and long, wavy cells typical of the gametophyte for the oro mutant. Scale bars: 20 mm. (C) Representation of the interval on chromosome 14 between the closest recombining markers to the ORO locus (M_133_107 and M_133) showing the position of the single mutation within the mapped interval. DOI: https://doi.
This indicated either a dominant effect of the sam mutations in the fertile sporophyte or abortion of the sporangia due to arrested development of the two (haploid) meiotic daughter cells that carried the mutant sam allele. Note that no meiotic defects were observed in heterozygous sporophytes carrying the oro mutation. Ectocarpus sporophytes produce a diffusible factor that induces gametophyte initial cells or protoplasts of mature gametophyte cells to switch to the sporophyte developmental program  (Arun et al. , 2013). The oro mutant is not susceptible to this diffusible factor (oro protoplasts regenerate as gametophytes in sporophyte-conditioned medium) indicating that ORO is required for the diffusible factor to direct deployment of the sporophyte developmental pathway  (Arun et al. , 2013).
Ec-27_006660 was therefore given the gene name SAMSARA (SAM). ORO and SAM transcripts were most abundant in gametes (Figure  3A ), consistent with a role in initiating sporophyte development following gamete fusion. Interestingly, transcripts of both ORO and SAM were detected in both male and female gametes indicating that gametes of both sexes carry both ORO and SAM proteins. This situation therefore appears to differ from that observed in Chlamydomonas where GSP1 and GSM1 are expressed uniquely in the plus and minus gametes, respectively  (Lee et al. , 2008). Whilst we cannot rule out the possibility that post-transcriptional regulatory processes result in ORO and SAM exhibiting sex-specific patterns of gamete expression, genetic evidence also supports a bi-sexual pattern of expression, at least for ORO, because complementation was observed when both male and female strains carrying the oro mutation were crossed with wild type strains (Supplementary file 1).
The latter were significantly enriched in the sporophyte-biased gene set (c2 test p=0. 001). Both the sporophyte-biased and the gametophyte-biased datasets were enriched in genes that were predicted to encode secreted proteins (Fisher's Exact Test p=2. 02e À8 and p=4. 14e À6 , respectively; Supplementary file 3). Analysis of GO terms associated with the secreted proteins indicated a similar pattern of enrichment to that observed for the complete set of generation-biased genes (terms associated with signalling, cell wall and membrane transport; Supplementary file 4). Figure  3C  illustrates the relative abundances of manually-assigned functional categories represented in the generation-biased genes predicted to encode secreted proteins. The lists of differentially expressed genes identified by the above analysis were used to select 200 genes that showed strong differential expression between the sporophyte and gametophyte generations.
The ORO and SAM proteins interact in vitro HD TFs that act as life cycle regulators or mating type determinants often form heterodimeric complexes  (Banham, 1995; Horst et al. , 2016; Hull et al. , 2005; Ka ¨mper et al. , 1995; Lee et al. , 2008). The ORO and SAM proteins were also shown to be capable of forming a stable heterodimer representations of the relative abundances (log2 gene number) of manually assigned functional categories in the set of genes that were differential regulated between the sporophyte and gametophyte generations (upper panel) and in the subset of those genes that encode secreted proteins (lower panel). Asterisks indicate functional categories that were significantly over-or under-represented in the two datasets. (D-E) Significantly overrepresented GO terms (D) and KEGG pathways (E) associated with generation-biased genes.
(F) Expression patterns of the 200 most strongly generation-biased genes. oro, oro mutant; sam, sam mutant; imm, immediate upright mutant; GA: gametophyte; SP: sporophyte. DOI: https://doi. org/10. 7554/eLife. 43101. 006 The following figure supplement is available for figure  3 : using an in vitro pull-down approach (Figure  4 ). Deletion analysis indicated that the interaction between the two proteins was mediated by their homeodomains. Evolutionary origins and domain structure of the ORO and SAM genes Analysis of sequence databases indicated that all brown algae possess three HD TFs, all of the TALE class, including orthologues of ORO and SAM (Figure  5A , Supplementary file 6). Comparison of brown algal ORO and SAM orthologues identified conserved domains both upstream and downstream of the HDs in both ORO and SAM (Figure  5B, C ).
Only one non-brown-algal protein, from the raphidophyte Heterosigma akashiwo, possessed similarity to these domains, allowing it to be classed tentatively as an ORO orthologue (gene identifier 231575mod; Figure  5A, C , Supplementary file 6). The transcriptome of this strain also included a truncated TALE HD TF transcript similar to SAM but more complete sequence data will be required to confirm orthology with SAM (gene identifier 296151; Figure  5A , Supplementary file 6). This analysis allowed the origin of ORO to be traced back to the common ancestor with the raphidophytes (about 360 Mya;  Brown and Sorhannus, 2010)  but the rate of divergence of the non-HD regions of ORO and SAM precluded the detection of more distantly related orthologues. An additional search based on looking for TALE HD TF genes with intron positions corresponding to those of ORO and SAM did not detect any further orthologues (Figure  5 -figure supplement 1).
Heterodimerisation appears to be a conserved feature of brown algal and green lineage TALE HD TFs (Figure  4  and  Lee et al. , 2008)  despite the lack of domain conservation. However, in Ectocarpus heterodimerisation involves the ORO and SAM HDs whereas in Chlamydomonas, it is the KNOX1 and KNOX2 domains of Gsm1 that interact with the C-terminal region of Gsp1 (which includes the HD, Ala and DE domains). In Chlamydomonas, the Gsp1 and Gsm1 proteins are carried specifically by plus and minus gametes, respectively, so that dimerisation of the two proteins allows the organism to detect syngamy and therefore the transition from a haploid to a diploid state. Based on transcript detection (Figure  3A ) and genetic analysis (Supplementary file 1), ORO and SAM do not appear to exhibit sex-specific patterns of expression in gametes.
Moreover, modified regulation of these TALE HD TFs may have had advantages in terms of life cycle flexibility. For example, in Ectocarpus, it would not be possible to deploy the sporophyte program in parthenogenetic gametes if gamete fusion was strictly required to create an ORO-SAM heterodimer. Interestingly, diploid sporophytes heterozygous for sam mutations exhibited abortive development of unilocular sporangia at a stage corresponding to the meiotic division of the mother cell. At first sight it might seem surprising that a gene should play an important role both directly following the haploid to diploid transition (initiation of sporophyte development) and at the opposite end of the life cycle, during the diploid to haploid transition (meiosis). However, these phenotypes make more sense when viewed from an evolutionary perspective, if the ORO SAM system originally evolved as a global regulator of diploid phase processes.
Key resources table Reconstruction and sequence correction of the ORO and SAM loci The sequence of the 34. 5 kbp mapped interval containing the ORO gene (chromosome 27, 5463270-5497776) in the wild type Ectocarpus reference strain Ec32 included one short region of uncertain sequence 1026 bp downstream of the end of the ORO open reading frame. The sequence of this region was completed by PCR amplification and Sanger sequencing and confirmed by mapping Illumina read data to the corrected region. The corrected ORO gene region has been submitted to Genbank under the accession number KU746822. Comparison of the reference genome (strain Ec32) supercontig that contains the SAM gene (sctg_251) with homologous supercontigs from several independently assembled draft genome sequences corresponding to closely related Ectocarpus sp.
Reactions were run in 10 ml containing 5 ng cDNA, 500 nM of each oligo and 1x LightCycler 480 DNA SYBR Green I mix (Roche). The sequences of the oligonucleotides used are listed in Supplementary file 8. Pre-amplification was performed at 95 ˚C for 5 min, followed by the amplification reaction consisting of 45 cycles of 95 ˚C for 10 s, 60 ˚C for 30 s and 72 ˚C for 15 s with recording of the fluorescent signal after each cycle. Amplification specificity and efficiency were checked using a melting curve and a genomic DNA dilution series, respectively, and efficiency was always between 90% and 110%. Data were analysed using the LightCycler 480 software (release 1. 5. 0). A pair of primers that amplified a fragment which spanned intron 2 of the SAM gene was used to verify that there was no contaminating DNA (Supplementary file 1-table supplement 8).
Raw reads were quality trimmed with Trimmomatic (leading and trailing bases with quality below three and the first 12 bases were removed, minimum read length 50 bp)  (Bolger et al. , 2014). High score reads were aligned to the Ectocarpus reference genome  (Cock et al. , 2010; available at Orcae; Sterck et al. , 2012)  using Tophat2 with the Bowtie2 aligner  (Kim et al. , 2013). The mapped sequencing data was then processed with HTSeq  (Anders et al. , 2014)  to obtain counts for sequencing reads mapped to exons. Expression values were represented as TPM and TPM >1 was applied as a filter to remove noise. Differential expression was detected using the DESeq2 package (Bioconductor; Love et al. , 2014) using an adjusted p-value cut-off of 0. 05 and a minimal fold-change of two. Genes that were differentially expressed in the gametophyte-and sporophyte generations were identified using duplicate RNA-seq datasets for whole gametophytes (GBP-5 and GBP-6, Supplementary file 9) and whole sporophytes (GBP-7 and GBP-8, Supplementary file 9) that had been grown in parallel under identical culture conditions.
Heatmaps were generated using the Heatplus package for R  (Ploner, 2015)  and colour schemes selected from the ColorBrewer project (http://colorbrewer. org). The entire set of 16,724 protein-coding genes in the Ectocarpus Ec32 genome were manually assigned to one of 22 functional categories (Supplementary file 10) and this information was used to determine whether sets of differentially expressed genes were enriched in particular functional categories compared to the entire nuclear genome (c 2 test). Blast2GO  (Conesa and Go ¨tz, 2008)  was used to detect enrichment of GO-terms associated with the genes that were consistently up-or downregulated in pairwise comparisons of the wild type gametophyte, the sam mutant and the oro mutant with the wild type sporophyte. Significance was determined using a Fisher exact test with an FDR corrected p-value cutoff of 0.