dataesr/scientific-paragraphs-categorization huggingface dataset:
Spatio-temporal variability of Si mass and isotopic balance in the iron fertilized area By comparing the present dataset with the one collected during KEOPS-1 (summer 2005), the seasonality of the Si isotopic composition can be described, helping to refine the Si biogeochemical cycle in this area  (Fripiat et al. , 2011a; De Brauwere et al. , 2012). For this purpose, the short-term temporal evolution of the bloom initiation (two visits at A3) was examined by several visits in the meander that constituted a pseudo-Lagrangian time series (covering 27 days, Table  1 ). The silicon isotopic properties measured in the ML during the austral spring (KEOPS-2) were significantly lighter than those measured by  Fripiat et al. (2011a)  at the end of summer (Fig. 3 ) as expected from the seasonal progression of the preferential light Si isotope consumption (De la  Rocha et al.
Deep particulate Si fluxes BSi export flux collected in the sediment trap located above the plateau shows two summer maxima (> 2 mmol m -2 d -1 in early December 2011 and early January 2012) separated by a period of reduced flux (Fig. 6 ). In contrast, export during austral winter exhibited a long period of very low particle flux (< 0. 2 mmol m -2 d -1 , from March to September 2012). These seasonal variations are associated with the evolution of surface chlorophyll a concentrations with a delay of approximately 1 month, and were described in detail in  Rembauville et al. (2015). This sediment trap dataset allows us to investigate the variations of exported opal δ 30 Si and subsequently the mechanisms governing the seasonal variations of Si stocks and fluxes in the ML. Recent studies have suggested that the seasonal variations of the isotopic composition of exported BSi may reflect the evolution of δ 30 Si BSi in the ML  (Varela et al.
Data availability All original data from this paper are available in the Supplement section. Si isotope data are also available from the GEOTRACES International Data Assembly Centre http: //www. bodc. ac. uk/geotraces/. Moreover, all KEOPS-2 data are available from the French CYBER data centre: http: //keops2. obs-vlfr. fr/. The Supplement related to this article is available online at doi:10. 5194/bg-13-6049-2016-supplement. Acknowledgements. The authors would like to thank B. Quéguiner as the KEOPS-2 chief scientist, the captain, and the crew of the R/V Marion-Dufresne II for assistance on board; Mustapha Benrahmoune (LOCEAN, CNRS) and Irina Djouraev (LOCEAN, IRD) for their help in sample processing and Si and Al concentrations measurements; and Heather McNair for improvement of English.
Arbuscular mycorrhizal (AM) fungi are a diverse group of soil fungi (Glomeromycota) that form the most ancient mutualistic association termed AM symbiosis with a majority of land plants, improving their nutrition uptake and resistance to stresses. In contrast to their great ecological implications, the knowledge of the molecular biological mechanisms involved is still scant, partly due to the limited genomic resources available. Here, we describe the gene repertoire of a new AM fungus Gigaspora rosea (Diversisporales). Among the 86332 non-redundant virtual transcripts assembled, 15346 presented similarities with proteins in the Refseq database and 10175 were assigned with GO terms. KOG and Interpro domain annotations clearly showed an enrichment of genes involved in signal transduction in G.
, 2001; Pawlowska and Taylor, 2004; Hijri and Sanders, 2005; Pawlowska, 2005; Stukenbrock and Rosendahl, 2005; Bever et al. , 2008; Sanders and Croll, 2010; Boon et al. , 2015). Thanks to the advance in sequencing technology, the first transcriptome and genome of an AM fungus Rhizophagus irregularis DAOM197198 were released in recent years  (Tisserant et al. , 2012 (Tisserant et al. , , 2013;; Lin et al. , 2014). These genome-wide studies revealed far more information than ever before about the AM fungal gene repertoire and expression dynamics across its life cycle, such as the reduced number of genes involved in plant cell wall degradation, over-represented genes involved in signaling pathway and highly induced transporter and small secreted peptide genes during symbiosis. Moreover, these datasets also started to shed light on the key issues mentioned above.
In line with this, the transcriptome of Gigaspora margarita was assembled very recently  (Salvioli et al. , 2016). In order to strengthen the identification of shared and AM fungal lineage specific features, we surveyed the gene repertoire of Gigaspora rosea DAOM194757. mRNAs were isolated from several biological conditions (germinating spores, symbiotic tissues, extraradical hyphae) and sequenced using the Illumina strategy. The transcribed gene set of G. rosea was assembled from more than 230 M sequencing reads (over 24 Gbs). We then detailed the gene repertoire of G. rosea, with a focus on the gene categories that could be related to the specific biology of AM fungi. Finally, using the data retrieved from this gene set, a phylogeny based on a multiple-gene alignment was inferred to clarify the phylogenetic placement of Glomeromycota within the basal fungal lineages.
Preparation of Biological Materials To ensure a gene repertoire as complete as possible, biological materials were prepared in a manner to cover several typical fungal developmental stages: germinating spores with or without the addition of root exudates or GR24, a synthetic analog of strigolactones that were characterized as plant signals perceived by AM fungi  (Akiyama et al. , 2005; Besserer et al. , 2008) , extraradical mycelium and symbiotic root tissues (detailed information available at NCBI GEO portal, [GEO: GSE67906] and Supplementary Table  S1 ). In brief, spores and extraradical mycelium of G. rosea DAOM 194757 produced on root organ cultures were purchased from Agronutrition (Carbone, France). For the germinating spores treated with GR24, batches of 500 spores were incubated for pre-germination during 5 days in liquid mineral M medium  (Bécard and Fortin, 1988)  under 30 • C, 2% CO 2 with or without (control) GR24 at the final concentration of 10 -6 M during 2 days before sample collection.
Gigaspora rosea mRNA Sequencing and Assembly Gigaspora rosea RNA was extracted from the different biological conditions using RNeasy Plant Mini RNA Extraction Kit (Qiagen, Germany). Library construction and sequencing were performed on the GeT platform ( 1  Toulouse, France) according to the standard Illumina protocols. Totally, 31 libraries were constructed for all the samples mentioned above (see Supplementary Table  S1 ). Short pair-end sequencing reads generated from illumina platforms (2 × 101 bp from Hiseq2000 and 2 × 151 bp from Miseq1000) were trimmed based on the quality scores (limit: 0. 05), end ambiguity (maximum allowed number of ambiguities: 2) and adaptor sequences, using the commercial software CLC Genomic Workbench (v6. 0, Denmark). The reads less than 50 bp after trimming were discarded.
In addition, as the symbiotic materials contained RNAs from the host plant and other possible contaminants (fungi and other eukaryotic microorganisms), we developed a strategy to remove these non-G. rosea reads before assembly (Supplementary Figure  S1A ). The cleaned symbiotic reads displayed a GC% distribution highly similar to that of the non-symbiotic pure fungal reads (Supplementary Figure  S1B ), validating the efficiency of our procedure. We used these cleaned symbiotic reads and non-symbiotic fungal reads for the assembly process, also using the CLC software with default settings. In order to improve the quality of these assembled contigs, the option of mapping reads back onto the assembled contigs was run with default settings. See the online CLC protocol for more details on the reads trimming and assembly 2.
SNP and SSR Identification To detect the single nucleotide polymorphisms (SNPs) in the transcripts, the trimmed reads in pairs from all samples were firstly mapped onto all the transcripts (length fraction: 0. 9 and similarity: 0. 95). Based on the mapping, the procedure of qualitybased variants detection in CLC genomics workbench software was run using default quality settings and advanced significance settings of required variant count 3; sufficient variant count 5. Only SNPs with a frequency of not less than 0. 02, forward/reverse balance greater than 0. 05 and average base quality more than 20 were called. Whilst, the simple sequence repeats (SSRs) of 2-6 nucleotides and total length ≥20 bp, that is a minimum of 10 dimers, 7 trimmers, 5 tetramers, 4 pentamers or 4 hexamers, were identified using the SSR Locator tool  (Costa De Oliveira et al.
Functional Annotation Prior to the annotation process, the representativeness of G. rosea transcriptome assembly was both assessed by CEGMA and BUSCO methods  (Parra et al. , 2009; Simão et al. , 2015). A total of 248 core eukaryotic genes were searched against G. rosea assembly as described in  Tisserant et al. (2012). A total of 429 groups of eukaryotic BUSCO genes and 1438 groups of fungal BUSCO genes were searched against G. rosea assembly using the mode of trans with default settings. Annotations were derived by comparing the transcripts to the public Refseq protein database with the blastx algorithm (e-value cutoff at 1E -10 ). All protein ORFs (including the complete and incomplete ones) encoded by G. rosea were predicted by the OrfPredictor tool using default settings  (Min et al. , 2005).
The Gene ontology (GO) terms were assigned to each transcripts using InterProScan program  (Quevillon et al. , 2005). The annotation of Eukaryotic Orthologous Groups (KOG) and function classes was derived using webMGA tool  (Wu et al. , 2011). Potential InterPro domains harbored in each transcript were predicted based on InterProScan hits. G. rosea metabolic pathway prediction was achieved by the online KEGG Automatic Annotation Server (KAAS) using the single-directional best-hit information method and default bitscore threshold  (Moriya et al. , 2007). The following organisms  : uma, spo, tml, pcs, ang, ani, bfu, ncr, mgr, fgr, sce, yli, ecu, mgl, mpr, ppl, cne, ure, cpw, aor, afm, ssl, ago, kla, ppa, vpo, cgr, and dha  were selected as the reference datasets. Carbohydrate-active enzymes (CAzymes) in the predicted proteome were annotated by the dbCAN annotation server, with an e-value cutoff at 1E -10 (  Yin et al.
Membrane transporters were identified from the G. rosea gene repertoire by blastx searches against the Transporter Classification Database 5  with an e-value cut-off at 1E -20 , as described previously  (Wang et al. , 2015). The G. rosea transcripts coding for the meiosis required genes were obtained by tblastn against the whole gene repertoire using the inventory of 86 genes reported in the study of  Halary et al. (2011) , as the queries.
Gigaspora rosea DAOM 194757 Gene Repertoire Generation De novo assembly of 230 084 705 reads (208 454 640 nonsymbiotic pure fungal reads plus 21 630 065 cleaned symbiotic fungal reads, see Materials and Methods) produced 97463 contigs with an average length of 611 bp (N 50 : 839 bp, 33% of GC content, total length: 59. 5 Mb) and more than 90% of these reads could be mapped back to the assembly. Since symbiotic tissues were obtained from pot cultures, this original assembly still contained some non-G. rosea contaminant contigs. We compared the 97463 contigs with the NCBI nr/nt DNA database and removed 11131 sequences showing high similarity (blastn using a stringent e-value cut-off at 1E -50 , as used by  Tisserant et al. , 2012)  to those from organisms other than fungi: 7328 Eukaryots (most abundant Acanthamoeba castellanii, 449 NRVTs), 2819 bacteria (most abundant Bacteroides finegoldii, 613 NRVTs), 27 archaebacteria and 111 virus (most abundant Megavirus iba, 51 NRVT).
The remaining 86332 contigs constitute the first transcribed gene set of G. rosea (GiroV1, Girov1. fa available at the NCBI GEO portal [GEO: GSE67906]). The G. rosea gene repertoire GiroV1 is approximately 55. 5 Mb in size, with an average contig length of 643 bp (N 50 : 948 bp and 33% of GC content). CD-HIT clustering analysis indicated that G. rosea contigs and the predicted proteins are not redundant at the sequence level (identity threshold: 0. 95,  Li and Godzik, 2006) , although it cannot be excluded that redundancy can be masked by incomplete assembling (non-recovering contigs from the same full-length gene). In absence of size cut-off, the number of contigs in G. rosea is in the same range than the recent sequenced G. margarita  (Salvioli et al. , 2016). While considering the sequences longer (≥) than 350 bp, the NRVTs and gene repertoire of G.
has been accompanied to some extent by gene duplication and/or gene family expansion. The representativeness of the GiroV1 assembly was assessed in two ways. First, we found that among 428 G. rosea ESTs downloaded from the NCBI database, 307 can be blasted onto the GiroV1 contigs (e-value cut-off at 1E -50 as used by  Tisserant et al. , 2012). The 121 ESTs that do not match in GiroV1 are mainly short sequences. Secondly, 240 of the 248 Core Eukaryotic Genes (CEGs, e-value cut-off at 1E-5;  Parra et al. , 2009) , and 378 of the 429 BUSCO genes  (Simão et al. , 2015)  were found to be present in GiroV1, suggesting this assembly covers most of the genes of G. rosea (Supplementary Table  S2A ). This was further supported by the finding that most of the KEGG pathways identified in the genome of R.
Single Nucleotide Polymorphism (SNP) Analysis Suggests a Homokaryotic Organization of G. rosea Nuclei During their life cycle, AM fungi form multinucleate spores and no mono-nuclear stage was observed. These propagative structures are thought to be asexual spores where high genetic variations occur between co-existing nuclei  (Sanders and Croll, 2010). However, the first available genomic data did not support this interpretation  (Tisserant et al. , 2013; Lin et al. , 2014). To check it on G. rosea, we examined genetic diversity in the gene set of G. rosea through SNP analysis. The quality-based variant detection procedure in CLC software called a total of 57405 SNPs distributed in 9576 NRVTs (11. 1% of the total NRVTs), with an average of 1 SNP per kb. Few NRVTs are highly polymorphic: only 1499 of the 9576 NRVTs contained >10 SNP loci (Figure  1 ).
Global Annotation The homology search against the Refseq protein database resulted in only 15,346 annotated G. rosea NRVTs (17. 8% of the total 86,332 NRVTs) at e-value cut-off of 1E -10 (file Girov1_annotation. xlsx. gz available at GEO portal [GEO: GSE67906]). Using same threshold, 33. 7% of R. irregularis NRVT had a hit on GenBank nr  (Tisserant et al. , 2012). That such a small portion of G. rosea NRVTs could be annotated by the already known proteins in other organisms is not unexpected, since a large number of genes have been shown to be AM lineage specific  (Tisserant et al. , 2012 (Tisserant et al. , , 2013;; Lin et al. , 2014; Salvioli et al. , 2016)  and there are only limited AM fungal sequences in public databases. We observed that the number of matched NRVTs increased (22393, at the same e-value cut-off) when searching against the proteins of R.
Among the 86332 NRVTs, open reading frames (ORFs, complete or incomplete) were predicted for 83360 NRVTs by the OrfPredictor tool, and these proteins were classified into 25 KOG functional classes in which the class of signal transduction mechanisms was strikingly overrepresented (accounting for 36. 0% of total annotated proteins, Figure  2 ). Consistently, Interpro domains (for instance, IPR001245: serine-threonine/tyrosine-protein kinase catalytic domain and IPR000719: protein kinase, catalytic domain) involved in signaling were significantly enriched in G. rosea proteins (Supplementary Figure  S3 ). Noticeably, the significant enrichment of proteins involved in signaling is also the case in R. irregularis and G. margarita  (Tisserant et al. , 2013; Lin et al. , 2014; Salvioli et al. , 2016 ; Supplementary Table  S4 ), even of the ectomycorrhizal fungus Laccaria bicolor  (Martin et al.
Carbohydrate-Acting Enzymes (CAZymes) Annotation A reduced pool of carbohydrate-acting enzymes (CAZymes) involved in the degradation of plant cell wall polysaccharides has been reported in several obligate biotrophic pathogens and mutualists including ectomycorrhizal and AM fungi  (Martin et al. , 2008 (Martin et al. , , 2010;; Spanu et al. , 2010; Duplessis et al. , 2011; Tisserant et al. , 2012 Tisserant et al. , , 2013;; Kohler et al. , 2015; Salvioli et al. , 2016). Through dbCAN HMMER search, we found 293 G. rosea NRVTs that encode a total of 64 CAZyme families including 26 glycosyltransferases (GTs), 20 glycoside hydrolases (GHs), 6 carbohydrate esterases (CEs), 6 carbohydrate-binding modules (CBMs), and 6 auxiliary activities (AAs; Supplementary Table  S7 ). Consistent with the aforementioned lack of an invertase gene in G.
, 2013; Lin et al. , 2014). Function could be inferred for 141 G. rosea SPs through homology searches against Refseq, Swissprot and Fungal Secretome Knowledgebase (FunSecKB2) databases  (Meinken et al. , 2014). Interestingly, we observed that the secretome of G. rosea overlapped the most with that of the Mucoromycotina fungus Rhizopus delemar in the FunSecKB2 database (14 G. rosea SPs showing similarity with Rhizopus SPs, then five SPs with Melampsora larici-populina ones, see Supplementary Table  S8 ), thus hinting at a possible close relationship between them. GO analysis showed that the G. rosea SPs are involved in diverse biological processes such as proteolysis, protein maturation, carbohydrate metabolic process, and oxidation-reduction. CAZyme annotation suggests that the carbohydrate metabolic process related SPs could be involved in the degradation of bacterial cell wall peptidoglycan (like the lysozyme family GH25) and plant cell wall polysaccharides (like the α-galactosidase family GH27).
Transcription Factor Gene Annotation Transcription factors (TFs) orchestrate gene expression regulation of a cell and the repertoire of TFs determines the life and functionality of the cell  (Shelest, 2008). To better understand their regulatory mechanisms, it is essential to know the repertoire of TFs in a species. To annotate the TF genes of G. rosea, we screened all NRVTs for the 37 PFAM domains  (Todd et al. , 2014)  or 83 InterPro domains  (Park et al. , 2008) , which are typically harbored in fungal TFs, and obtained 559 potential TF genes (Supplementary Table  S10 ). Further homology searches against the Swissprot and Refseq protein databases confirmed that most are TFs or transcriptional regulator genes. Importantly, we identified a significant homolog (contig_342) in this TF repertoire of the only validated AM fungal TF gene GintSTE.
ACKNOWLEDGMENTS We are grateful to  Ms. Julie Viala ,  Agronutrition (Toulouse ) for producing large amounts of raw fungal material. We also thank  Pierre Marc Delaux  ( LRSV ) for the constructive discussions during the generation of this manuscript, and  Peter Winterton  and  Nizar Fawal  for the language corrections. LRSV is part of the  LabeX Tulip. NT was partially funded by the  Chinese Scholarship Council (CSC)  and the funder had no role in research design, data analysis, decision to publish, and preparation of the manuscript.
A Fourier Transform (FT) absorption spectrum of room temperature NH 3 in the region 7400 -8600 cm -1 is analysed using a variational line list and ground state energies determined using the MARVEL procedure. The spectrum was measured by Dr Catherine de Bergh in 1980 and is available from the Kitt Peak data center. The centers and intensities of 8468 ammonia lines were retrieved using a multiline fitting procedure. 2474 lines are assigned to 21 bands providing 1692 experimental energies in the range 7000 -9000 cm -1. The spectrum was assigned by the joint use of the BYTe variational line list and combination differences. The assignments and experimental energies presented in this work are the first for ammonia in the region 7400 -8600 cm -1 , considerably extending the range of known vibrational-excited states.
The recent study for NH 3 analysed 29,450 measured transitions and yielded 4961 accuratelydetermined energy levels. The critically reviewed and validated high resolution experiments employed by this study, cover the region 0. 7 -17,000 cm -1   with a large gap between 7000 -15,000 cm -1. In fact there is an overall lack of detailed and accurate information for NH 3 transitions in this region. The band model parameters of Irwin et al  [12]  cover the region 400 to 11000 cm -1 , but was intended for analysis at low spectral resolution so the measurements were obtained at a spectral resolution of only 0. 25 cm -1 and not assigned. The HITRAN database  [13] , a major source of experimental data, contains no information for NH 3 above 7000 cm -1. A number of variational line lists are available for NH 3  [14, 15, 16].
Construction of the line list The wavenumber scale was calibrated using water lines which are clearly apparent around 7500 and 8600 cm -1. The correction term fitted as a linear  function of the wavenumbers was found to be -0. 028 cm -1 at 8000 cm -1. It is worth noting that the shape of the water lines indicates that they involve a sharp contribution due to water molecules present as an impurity in the low pressure sample, and a broader contribution due to atmospheric water present in the spectrometer. The quality of the wavenumber calibration was checked in two ways: by comparison of ammonia line positions observed at the low energy range of the spectrum with positions provided in the HITRAN database below 7000 cm -1 and by comparison to the positions of ammonia lines identified in the high sensitivity CRDS spectrum of water  [25].
On the basis of spectral simulations, a correction curve was constructed for the line intensities; this curve was validated using lines near 7000 cm -1 with intensity provided in the HITRAN database and applied to all the intensities. The correction is on the order of 20 % for line intensities of 1 × 10 -22 cm/molecule. Figure  2  illustrates the quality of the final spectral reproduction achieved. After removal of some water lines located at the low and high energy borders of the 7400 -8640 cm -1 studied spectral region, the overall list presented in Fig. 3. For these lines, the transmission at the line center is of the order of only a few percent and biases related to the zero transmission or a not fully characterized apparatus function may be significant.
The Δβ value was calculated for all CpG sites in all sample pairs, and the data were loaded into the Jexpress software package  [19]. Rank product testing  [20]  was then performed to test whether the differential methylation between tumor tissue and matched normal mucosa was significant. The Δβ value was declared significant if the adjusted p-value, i. e. the FDR q-value, was less than 0. 05. Hierarchical clustering was performed using utilizing the J-express software package  [19]. The filtered dataset, consisting of the 200 most significant Δβ values, was imported into Pathway Express, part of the Onto-Tools software suite  [21, 22] , for KEGG (Kyoto Encyclopedia of Genes and Genomes) cellular signaling pathway analysis  [23]. Pathway Express calculates an Impact Factor (IF), which is used to rank the affected signaling pathways, based on the fold change, the number of the involved genes in the pathway, and the amount of perturbation of downstream genes  [24].