dataesr/scientific-paragraphs-categorization huggingface dataset:
The expected cross-section limits are computed assuming the absence of WVγ production. The last column shows the theory prediction for the SM signal cross-section computed with the VBFNLO program and corrected to particle level. The ν j jγ cross-section corresponds to the average cross-section per lepton flavour in the semileptonic analysis and all events of the eν j jγ and µν j jγ final states are employed for the determination of this limit. using the CL s formalism at 95% CL. The results are given in Table  6  together with limits expected in absence of WVγ production. In addition, the theory prediction for the SM signal cross-section computed with the VBFNLO program and corrected to particle level is reported. The cross-section uncertainties are evaluated as described in Section 7. 1 and range up to 22%.
Sequence processing Raw reads were trimmed for quality and aligned to the Petunia axillaris v4 reference transcripts from solgenomics (https://solgenomics. net) using the suite CLC Genomics Workbench v9. For mapping, the minimum length fraction was 0. 9, the minimum similarity fraction 0. 9 and the maximum number of hits for a read was set to 10. The unique and total mapped number of reads for each transcript was determined, and then normalized to RPKM (Reads Per Kilobase of exon model per Million mapped reads). Intact pairs were counted as two, broken pairs as one. Fold change values were calculated by proportion-based test statistics  [41]  with a False Discovery Rate (FDR) correction for multiple testing  [66]. Genes were considered differentially expressed if the induction ratio was either 2-fold induced or repressed (-2 ≤ or ≥2) with an FDR-corrected p-value of p < 0.
Potential bias could arise from a range of factors including preferential amplification  (Taberlet et al. , 2012) , inconsistent taxonomic resolution of the sequenced barcodes  (Pawlowski et al. , 2012)  and insufficient coverage of the barcode reference database  (Pawlowski et al. , 2014b). Here we take advantage of the possibility to unambiguously ascribe sequences of foraminifera to benthic and planktonic lineages. By analyzing the planktonic portion of foraminiferal metabarcodes from deep-sea sediments, we provide evidence that the structure and diversity of surface ocean communities is preserved in eDNA molecules and that the preservation is not limited to specific depositional environments. We focus our analysis on the foraminifera because of access to highly resolving short barcodes  (Pawlowski and Lecroq, 2010)  and the availability of a taxonomically wellresolved barcode database for the planktonic taxa  (Morard et al.
, 2015). This database allows the unambiguous separation of the benthic, autochthonous component of the dataset from its planktonic, allochthonous component. Foraminifera are single-cell eukaryotes (protists) belonging to the phylum Rhizaria  (Adl et al. , 2012). Most foraminifera lineages occupy benthic ecological niches. Their ∼ 5000 morphospecies inhabit the bottom of shallow coastal environments to deep abyssal plains. In contrast, the planktonic lineages only include 50 morphospecies, living mostly in the photic part of the water column. They are found from tropical to polar water masses and spend their entire life cycle in the plankton  (Hemleben et al. , 1989). After their death, planktonic foraminifera sink to the bottom of the ocean, where they are found in the calcareous ooze, ranging from ∼ 1 to 4.
With the recent development of the Planktonic Foraminifera Ribosomal Ref- erence Database (PFR 2 ;  Morard et al. , 2015) , the environmental sequences belonging to planktonic foraminifera in the eDNA libraries generated by  Lecroq et al. (2011)  can now be, for the first time, thoroughly analyzed and assigned to the morphological and cryptic species levels The extensive knowledge on the distribution and abundance of planktonic foraminiferal shells in surface sediments  (Kucera et al. , 2005)  enabled the eDNA data to be directly compared with data derived from classical taxonomy. We thus assess to what extent the eDNA originating from plankton is representative of the source community, which is an essential prerequisite for interpretation of the eDNA archive in the sediment.
Material and methods The 31 surface sediment samples analyzed were taken at water depths ranging from 1745 to 5338 m and cover sediment types from calcareous ooze in the Caribbean Sea to fine clastic sediments in the Arctic Ocean (Fig. 1a , Supplement 1). All analyses are based on the Illumina Solexa GAII datasets generated by  Lecroq et al. (2011)  and registered at the NCBI's Short Read Archive under BioProject number PRJEB2682. The original sequencing data include 78 613 888 reads covering the 36 positions starting at 3' of the "GACAG" motif delimitating the foraminifera-specific hypervariable region 37f region  (Pawlowski and Lecroq, 2010). We used the unique sequences obtained for each library in  Lecroq et al. (2011)  after the strict dereplication step and the removal of singletons associated with only one read occurrence in a library.
filosa previously obtained by using classical Sanger technology, thus showing the absence of cross contamination  (Lecroq et al. , 2011). We compared the retained reads to the PFR 2 database  (Morard et al. , 2015) , which represents a compilation of 3322 curated partial SSU rDNA sequences of planktonic foraminifera groups associated with a six-rank taxonomy. The ranks reflect taxonomic units and are organized into a hierarchal framework, with the basal ranks being the coarsest units and the terminal ranks corresponding the finest taxonomic levels. The first three basal ranks correspond to the level of assignation comparable to that achievable using morphological data and are thus analogous to fossil data. The three terminal levels correspond to the molecular taxonomy accessible using molecular data only.
The PFR 2 taxonomic framework derives from single-cell genetic studies where the molecular taxonomy (definition of genetic types) was based on phylogenetic inferences and/or automatic delimitation methods. The delimited cluster of sequences were then compared to ecological and biogeographical data to validate their status as genuine biological species (see  Morard et al. , 2015, and references herein). Of the 3322 sequences available in PFR 2 , 2418 sequences covered the fragment of the region 37f. These sequences were downloaded from the PFR 2 database (http://pfr2. sb-roscoff. fr/) and trimmed to the 36-nt fragment corresponding to the environmental sequences, which resulted in a total of 463 unique homologous reference sequences (Supplement 2). Initially, we evaluated the taxonomic resolution of the 36 nt barcoding region and found that it was variable enough to discriminate the genetic types (equivalent to cryptic species) within morphological species of almost all planktonic foraminifera taxa referenced in PFR 2.
We observed a lack of genetic resolution (different taxonomic entities yielding identical barcodes) for only two species pairs belonging to Globorotalia (tumida and ungulata) and Globigerinella (calida and siphonifera) and three pairs of genetic types among Globorotalia truncatulinoides (type III and IV), Pulleniatina obliquiloculata (types I and II) and Globigerinita glutinata (types III and IV). We then individually aligned the 4466 to 27 578 unique sequences obtained for each of the 31 samples against the 461 reference sequences using the Needleman-Wunsch global sequence alignment algorithm  (Needleman and Wunsch, 1970)  to separate the portion of the dataset belonging to the planktonic foraminifera (allochthonous origin) from the portion belonging to the benthic foraminifera (autochthonous origin).
Pairwise genetic distances were calculated as the number of differences (counting successive indels and terminal gaps as one difference), and an iterative clustering of the unique environmental sequences with the reference sequences was performed, allowing 1, 2, 3, 5 and 10 differences as thresholds for the average linkage algorithm. We then extracted all environmental sequences found within each cluster containing a planktonic reference sequence in an iterative manner by screening from the most stringent (1 difference threshold) to the most permissive (10 differences threshold) clusters. As a post hoc verification, we compared these sequences with the extensive benthic foraminifera sequence database used in  Pawlowski et al. (2014a)  together with the sequences of the Protist Ribosomal Reference Database (PR 2 , version based on release 203 of Genbank;  Guillou et al.
17  (Hammer et al. , 2001)  to estimate to what degree the full taxonomic spectrum of each sample was recovered by eDNA (Fig. 2 ). Genuine sequences of planktonic foraminifera representing species not yet registered in the reference database may have been omitted. We therefore structured our analyses to account for the detection of possibly unknown genetic types. To this end, we used the phylogenetic signal contained in the 36 bp reads to build a taxonomic framework within each morphospecies. In contrast to strict annotation approaches using arbitrary similarity thresholds, a phylogenetic approach can identify novel genetic type, not represented in the reference comparative database. The retained e-ribotypes were automatically aligned using MAFFT v. 7  (Katoh and Standley, 2013) , with reference sequences of the complete 37f region.
These assignments were used to prepare three datasets with different degrees of taxonomic resolution (at the level of e-ribotype, genetic types and morphological species). The occurrences of the defined genetic types in the samples are shown in Fig. 3. The three boxes show the same rarefaction curves at three different scales highlighted by grey rectangles. For each magnification, the curves which are out of range are drawn in dashed lines to ease the reading of the figure. The difference in number of reads recovered between libraries was normalized using the cumulative sum scaling method  (Paulson et al. , 2013)  available on the metagenome-Seq Bioconductor package  (Paulson et al. , 2016)  in R (R Development Core Team, 2014). The cumulative sum scaling corrects the biases induced by differential sequencing depths and uses a zero-inflated Gaussian distribution mixture model that accounts for technical zero value resulting from undersampling.
The taxonomic richness and structure of the normalized datasets for each taxonomic resolution level were analyzed using non-metric distribution scaling (NMDS) as implemented in PAST v2. 17  (Hammer et al. , 2001) , associated with one-way PERMANOVA to test for significance of distribution difference between groups (Table  1 ). We used the Dice distance to consider only the presence/absence data and the Bray-Curtis distance to compare absolute and relative abundances of reads among the samples (Fig. 4 ). To compare the similarity structure and diversity in the samples based on the eDNA reads with census counts of microfossils, we used the MARGO database. The census count represent the relative abundance of species observed in a fossil assemblage based on the count of typically 300-500 specimens  (Kucera et al.
Results After quality filtering and collapsing of identical reads into single sequences, the comparison of the entire dataset with reference databases (Supplement 2) allowed for ascribing with certainty 1373 unique sequence patterns representing 488 291 reads to planktonic foraminifera (Supplement 1, 3). Because we required reads to be present in a minimum of two samples or to show a minimal abundance of 10 in the entire dataset, the retained dataset was reduced to 697 unique sequences of planktonic foraminifera (e-ribotypes), which represent a total of 486 435 reads (∼ 0. 63 % of the total dataset, Supplement 1). Diversity was then assessed using a phylogenetic approach and the 697 e-ribotypes were found to represent 37 genotypes (Fig. 3 , Supplement 4). Of these, 675 eribotypes (representing ∼ 99 % of the planktonic reads) were attributed to 24 genotypes already detected in plankton and assigned to 17 morphological species (Supplement 3, 4).
2b, c ), despite having a lower number of reads than the samples from Japan, implying lower diversity. 1 0 1 0 0 0 1 0 0 0 0 0 C. n it id a I C. n it id a U 1 G. v iv a n s I G. v iv a n s U 1 G. v iv a n s U 2 G. v iv a n s U 3 G. v With respect to the composition of the reads, we observed that e-ribotypes attributed to the microperforate species Globigerinita glutinata dominated the dataset (∼ 77 % of the reads) and were particularly abundant in subtropical communities (Fig. 3 ). E-ribotypes of common subtropical species Orbulina universa, Globorotalia menardii, Globorotalia hirsuta, Hastigerina pelagica Neogloboquadrina dutertrei, Globigerina falconensis, Globigerinella siphonifera, Pulleniatina obliquiloculata, Galitellia vivans and Candeina nitida were found in subtropical samples, whereas e-ribotypes assigned to the species Globigerinita uvula and Neogloboquadrina pachyderma appeared to dominate subpolar and polar samples.
, 1999). The latitudinal diversity gradient is present at all three taxonomic levels but is most pronounced at the e-ribotype level (Fig. 5b ). Finally, since census counts of planktonic foraminifera morphospecies in surface sediments are available from the same regions as those analyzed for eDNA (Fig. 1a ), we assessed whether the e-ribotype abundances reflect the same community turnover pattern as that indicated by fossil assemblages (Fig. 6 ). To this end, we compared pairwise distances between eDNA MOTU assemblages with pairwise distances between fossil assemblages. This comparison reveals that eDNA and morphospecies community turnover rates are significantly correlated (Fig. 6 ), with highest similarity among samples from the same region and lowest The grey areas represent the distribution of the Shannon index calculated on the census count of planktonic foraminifera in core top samples from the MARGO database  (Kucera et al.
We also show that the eDNA composition consistently reflects the composition of the pelagic planktonic communities from which it was  derived (Figs. 5, 6). The high reproducibility of read diversity (Dice index) and relative abundance (Bray-Curtis index) within a single region (Fig. 4 ) suggests that the taphonomic processes governing the transfer and preservation of extracellular DNA from surface to bottom ocean are similar at the regional scale and do not differentially impact DNA from species within different ecological groups. Although the number of planktonic foraminifera reads recovered differed by 3 orders of magnitude between the Caribbean (62 to 212 reads per samples, representing ∼ 0. 003 to 0. 03 % of the dataset) and Japan (3620 to 124 355 reads per sample, representing 0. 8 to 9.
4 % of the dataset), the information recovered was sufficient to reveal the structure of foraminifera communities across the whole range of environments investigated (Figs. 3 4 5 6 ). However, since the taxonomic richness in eDNA data increased with sequencing efforts (Fig. 2 ), the recovery of the full taxonomic diversity requires a certain minimum sequencing effort. From the analyzed dataset, it is not possible to explain the large variation in the numbers of reads ascribed to planktonic foraminifera among regions (Fig. 2 ). This could represent DNA differential preservation conditions or an imbalance between flux from the surface, allochthonous community and the abundance of DNA from the benthic, autochthonous community. The latter is a likely explanation because the analyzed eDNA material was amplified by PCR primers anwww.
biogeosciences. net/14/2741/2017/ Biogeosciences, 14, 2741-2754, 2017 dataset. Hence, such mutations in the conserved regions of the gene where the primers anneal may be responsible for detection failures. Another preferential PCR amplification could also explain the strong skew dataset towards microperforate species sequences, which represent 55 to 99 % of the reads (Fig. 3 ), but only 0 to 30 % of the morphological assemblages  (Kucera et al. , 2005). The microperforate clade appears to have significantly lower rDNA substitution rates  (Aurahs et al. , 2009 ) and here we observe no mismatch between the primer and the reference sequences within this clade. Alternatively, the higher abundance of reads assigned to microperforate taxa could represent a genuine pattern, questioning the representativeness of census counts of fossil foraminifera, which ignore specimens smaller than 150 µm  (Kucera et al.
, 2005). Microperforate species tend to be small and are disproportionately abundant in the size fraction smaller than 150 µm  (Brummer et al. , 1986). This is significant because the eDNA archive comprises information on all planktonic foraminifera irrespective of size and is thus potentially a more comprehensive recorder of species proportions in the plankton. Overall, our results indicate PCR/primer bias as the important limitation of planktonic foraminiferal community surveys based on metabarcoding. Alleviating these biases will allow detection of the full taxonomic spectrum, provided that sufficient sequencing effort is achieved, as recently discussed for fungi  (Adams et al. , 2013a, b). To our knowledge, the dataset we re-analyzed represents the largest sequencing data for a given taxonomic group.
Yet, it seems to indicate that the main ecological pattern can be extracted even from metabarcodes found at relatively modest frequencies  (< 1000 reads, Figs. 3, 4: Caribbean samples). This conclusion underlines the importance of comprehensive reference datasets and barcoding efforts to facilitate the development of specific and effective probing techniques to recover the signal of individual key groups  (Pawlowski et al. , 2012). Metabarcoding surveys of marine sediments offer a powerful alternative to study marine plankton ecology and biogeography. Plankton eDNA diversity observed in seafloor sediments represents a continuous flux of biomass, averaged over seasons and throughout the entire water column. Unlike plankton sampling, seafloor deposits are not affected by the seasonality, reproductive cycle or habitat depth of the plankton at the time of sampling.
Conclusions Assuming that eDNA deposited on the seafloor is also preserved through time, marine sediments should contain a remarkable ancient DNA (aDNA) archive of the history of the complete plankton communities. There is growing evidence that eDNA is preserved in marine sediments old enough to cover the previous ice age  (Lejzerowicz et al. , 2013). Until now, the interpretation of aDNA datasets from marine sediments suffered from insufficient sequencing depth  (Coolen et al. , 2009)  or insufficient coverage of the reference database  (Pawlowski et al. , 2014a). As a result, to what degree the observed aDNA patterns reflect genuine past ecological shifts and community structure remained contentious. Indeed, an investigation of a lake environment showed that only 71 % of the eDNA diversity identified in the water column was preserved in the sediments  (Capo et al.
Figure5. Macroecological pattern of spatial diversity known as the latitudinal gradient of diversity. (a) The grey areas represent the distribution of the Shannon index calculated on the census count of planktonic foraminifera in core top samples from the MARGO database (Kucera et al. , 2005)  against latitude. The dark-grey area represents the 1st-3rd quartiles (50 % confidence interval), light-grey area the 5th-95th percentile (90 % confidence interval), and the black line the median. The same similarity measure has been calculated at each location for the eDNA samples based on the relative abundances with the three levels of taxonomic resolution. (b) Relationships between mean Shannon index calculated at regional levels (symbols as in Fig. 1) for census count and eDNA assemblages; vertical and horizontal lines indicate the standard deviation.
Patients and samples Melanoma samples were obtained from the bank of biological resources of Ambroise Paré Hospital in Boulogne-Billancourt. The research was performed in compliance with the ethical principles of the Helsinki Declaration (1964) and with the French ethics laws. Patients were informed and approved the use of their samples for research purpose. Tumor samples collection was declared to the French Ministry of Research  (DC 2009-933). Melan-Cohort study was approved by CPP IDF 8 Ethics committee (030209) and registered with https://www. clinicaltrials. gov/ct2/search (NCT00839410). Clinical and survival data were collected from clinical records of the Dermatology Department of Ambroise Paré Hospital. The frequency of NRAS Q61 mutations was evaluated in a consecutive series of melanomas received for diagnosis from March 2013 until May 2015.
Microsatellite analysis Eight microsatellite markers were selected from the NCBI dbSNP short genetic variations database and analyzed by AFLP. Their positions are showed in Fig. 1 , and the primers used in Table  1. No highly heterozygous microsatellite was identified within NRAS gene; thus the genetic status of this gene was evaluated on the basis of two microsatellites closed to NRAS locus (rs3220698 and rs3220987). PCR reactions were performed with fluorescent-labeled forward primers and the amplified PCR products were analyzed by capillary array electrophoresis on the ABI PRISM 3100 sequencer (Applied Biosystems, Foster City, USA) and GeneScan software (Applied Biosystems). Detection of loss of heterozygosity was performed as detailed in Loss of Heterozygosity Analysis Getting Started Guide.
NRAS mutation frequency and allele quantification The frequencies of BRAF V600 and NRAS Q61 mutations were evaluated in 267 FFPE melanoma patients of the series (flow chart in Additional file 2: Figure  S2 ) diagnosed between March 2013 and May 2015. NRAS   We then compared our results with database of the Cancer Genome Atlas (TCGA) analyzed on the CBio-Portal platform. Among the 85 NRAS mutated cases that were available only 50. 6% (43/85) had a heterozygous status of NRAS mutation, while 34. 1% (29/85) was High non-HET and 15. 3% (13/85) was Low non-HET (Additional file 3: Figure  S3 ). F TTCAAGGCTGCAGTGAGCTA rs3219599 R AGTGGAAGCTAGACACACATTAAGA s3219653 F CCAGAGAGACAGAACTGAACAAA s3219653 R CAAATTTTGGACCTGCCATG rs3219587 F GGGCAAATGGAGGAAAGAGA rs3219587 R TAAAAATACCCCCACCCCACT rs3220698 F TTAAAAAACGTACTGCCACATTCA rs3220698 R GGCAGAAACCAGGAAATGTAGTA rs3220987 F GGCTTTTAGCTATGATTTGAGA rs3220987 R GACTCAGGAAATAAACAAGGC rs3220389 F CGCTGCTCACTCCTCCTCTGA rs3220389 R AGTGCTGCTCTCAGTGAACTC rs3219612 F AGCACACAATATACTCTCTCAGA rs3219612 R ACCTGGGCAAAAGAGTAAGACC rs3219703 F AACGAAGGTGTACTGGGACTGGT rs3219703 R ACAGGGATGTGAGGGATTTTTTC.
Discussion In this study, we reported the prevalence of NRAS Q61 mutation and, for the first time, the variations of NRAS mutant alleles (M%NRAS), in a large series of human melanoma samples. We have demonstrated that M%NRAS SMM superficial spreading melanoma NA data not available SD standard deviation M/F male/female was highly heterogeneous; indeed, only 61% of NRAS mutated melanomas were heterozygous, while 30% of cases had a significantly increased M%NRAS (≥60%). Our results were confirmed by analysis of the cases of the TCGA database. NRAS pyrosequencing assays used in this study were developed to identify all hot-spot mutations in the codon 61 of NRAS gene. The specificity of these assays for different mutations was confirmed by Sanger sequencing. Additionally, the genotyping accuracy of 40 NRAS mutated melanomas, 27 of which were p.