dataesr/scientific-paragraphs-categorization huggingface dataset:
Taxonomy section Chloropicon roscoffensis Lopes dos Santos and Eikrem sp. nov. Diagnosis: With characters of genus. Additional characters; loroxanthin absent, combined nucleotide sequences of nuclear 18S rRNA (KF899840), rRNA ITS (MF077510) and plastid 16S rRNA (LN735295) are species specific. Holotype: Cells embedded in resin block deposited at the Natural History Museum, University of Oslo accession number O-A-10003. Figure  4H  shows a cell from the resin block. Culture deposited in the Roscoff Culture Collection as RCC1871. Type locality: RCC1871 was isolated from the English Channel off Roscoff (48° 45′ N, 3° 57′ W). Etymology: From the type locality. Chloropicon mariensis Eikrem, Lopes dos Santos sp. nov. Diagnosis: With characters of genus. Additional characters; combined nucleotide sequences of nuclear 18S rRNA (KF422632), rRNA ITS (MF077504) and plastid 16S rRNA (LN735516) are species specific.
Holotype: Cells embedded in resin block deposited at the Natural History Museum, University of Oslo, accession number O-A-10004. Figure  4F  shows cell from the resin block. Culture deposited in the Roscoff Culture Collection as RCC998. Type locality: RCC998 was isolated from water sampled at 100 m depth in the South Pacific Ocean (9° 04′ S, 136° 59′ W). Etymology: Named in recognition of Dominique Marie who isolated the culture and his efforts in picoplankton research. Chloropicon laureae Lopes dos Santos and Eikrem sp. nov. Diagnosis: With characters of genus. Additional characters; combined nucleotide sequences of nuclear 18S rRNA (KF422631), rRNA ITS (MF077480) and plastid 16S rRNA (LN735470) are species specific. Holotype: Cells embedded in resin block deposited at the Natural History Museum, University of Oslo, accession number O-A-10005.
Chloropicon Lopes dos Santos and Eikrem gen. nov. Diagnosis: With characters of order. Coccoid cells measure 2-4 µm. One green chloroplast, often crescent shaped with starch grain. Thylakoids occur singly and in stacks of three. Central nucleus, mitochondrion located between nucleus and chloroplast. Vacuoles (1-2) present at cell periphery may contain particles. Surface of cell wall smooth. Etymology: Named for its green color and small size. Type species: Chloropicon sieburthii Chloropicon sieburthii Lopes dos Santos and Eikrem sp. nov. Diagnosis: With characters of the genus. Additional characters; combined nucleotide sequences of the nuclear 18S rRNA (AY425302), rRNA ITS (MF077490) and plastid 16S rRNA (AY702147) are species specific. Holotype: Cells embedded in resin block deposited at the Natural History Museum, University of Oslo, accession number O-A-10001.
Acknowledgements We are thankful to  Dr. Ian Probert ,  Jahn Throndsen  and  Øjvind Moestrup  for a critical reading of the manuscript and providing invaluable help for the taxonomic treatment. We thank  Dr. Matthias Wolf  for advice on the use of 4SALE software,  Dr. Nathalie Simon  for helpful discussions on ITS2 secondary structures and the  Roscoff ABIMS  platform for access to bioinformatics resources. Financial support for this work was provided by the  European Union program MaCuMBA  ( FP7-KBBE-2012-6-311975 ) and  FONDECYT regular PiSCOSouth  ( 1171802 ). This work is a contribution of Microalgas Nocivas (IEO) and  Unidad Asociada al IIM (CSIC).
We produced a phylogenomic tree based on the set of orthologous genes to provide the evolutionary framework in which to conduct all analyses. Testing such hypotheses builds on the fact that recent parallel evolution to increased temperatures should produce a higher rate of replacements producing a signature of positive selection, as structural adaptation requires a large number of beneficial mutations all over the genome. On the contrary, if thermophily represents an ancestral trait in this worm family, present-day species that live under "hot" conditions should have evolved under more constrained conditions with slower rates of replacements. Both evolutionary scenarios were therefore also investigated by looking at signatures of selection using d N /d S ratio-based approaches. These ratios were determined in an original pipeline processing of high-throughput data that deals with both the lack of close well-annotated genomes and the recently highlighted limitation of codon models in the research of selection footprints.
Materials and Methods Animal Collection, mRNA Extraction, Sequencing, and Assembly Alvinella pompejana (Ap), Alvinella caudata (Ac), Paralvinella grasslei (Pg), and Paralvinella pandorae irlandei (Pp) were collected from hydrothermal vents on the EPR at a depth of 2,550 m during the Mescal oceanographic cruise in April/ May 2010. Specimens were collected using the submersible Nautile, and upon recovery on board, flash-frozen in liquid nitrogen. Paralvinella fijiensis was sampled from hydrothermal vent chimneys of the Lau back-arc basin (Tui'Malina, 1,980 m) during the Lau Basin 2009 USA expedition with the ROV Jason and the R/V Thompson and directly preserved in liquid nitrogen. Once back in the laboratory, total RNA extraction was performed with Trizol, and the isolated RNA were re-precipitated after PVPP treatment to eliminate polysaccharides.
An EST library for the thermophilic Paralvinella sulfincola  (Girguis and Lee 2006)  was acquired as part of an earlier Joint Genome Initiative project to P. R. Girguis and S. Hourdez. The dataset consists of 24,702 transcripts assembled using Newbler  (Margulies et al. 2005)  based on reads obtained by 454 Roche technology. The specimens were sampled on the Juan de Fuca Ridge during the JdFR 2008 oceanographic cruise in August/ September on board of the R/V Atlantis with the submersible Alvin. Transcriptomes for the remaining 5 species included in this study were assembled after Illumina sequencing, with 108bp paired end reads. For Paralvinella fijiensis, the sequencing effort was 1 full lane (160 million reads), and for the 4 other species, the sequencing effort was a quarter of a lane (40 million reads) per species on a HiSeq 2000 at Genome Quebec  (Metzker 2009).
Search for Orthologs A reciprocal best tblastx top hit search was performed between all possible transcriptomes pairs  (Tatusov et al. 1997; Savard et al. 2006 ) using a stringent e-value cutoff of 10 À20 and a "medium soft filtering" for low similarity regions  (Moreno-Hagelsieb and Latimer 2008). In this very conservative approach, any cluster of sequences with more than one copy per species was discarded from the dataset to avoid The Ancestry of Thermophily and Subsequent Adaptation to Cold GBE Genome Biol. Evol. 9(2):279-296. doi:10. 1093/gbe/evw298 Advance Access publication January 30, 2017 potential paralogy. Putative orthologous groups (POGs) were locally aligned on the corresponding complete transcript sequences using the BlastAlign algorithm (with a proportion of gaps per sequence <50%), which accounts for long indels in a conservative way  (Belshaw and Katzourakis 2005).
Additionally, because of the subsequent mutigene d N /d Sbased study, a script was developed to detect ORFs (with and without the initial methionine and a minimal coding sequence length of 50 a. a. ) to produce a series of loci alignments in the right coding frame without gaps in order to avoid false signal in case of misalignment in the areas flanking the indel (Gu and Li 1994 but see Fletcher and Yang 2010 and the discussion of the method in supplementary material S1, Supplementary Material online).
Base Composition The transcript composition (GC content at the two first positions, GC 12 , and GC content at the third position, GC 3 ) was first measured on the set of the 423 concatenated orthologs and, then on each gene separately to account for the intergenes variance. In the latter case, the standard error and the median value of each variable was calculated for each species. The purine load index (PLI) was also computed following the Forsdyke's (2011) formula. To evaluate whether the relative synonymous codon usage of each species vary between species and the thermal preference, we computed a standardized matrix of codon frequencies in all species from the concatenated set of coding sequences using the amino acid frequencies of the translated proteins. This matrix was then used as an input to perform a codon analysis to identify the preferred (Fop) codons following their relative contributions and coordinates on the two main axes of the correspondence analysis using the seqinR package, which controls for the amino acid composition of the proteome  (Charif and Lobry 2007).
Amino Acid Composition The relative amino acid composition of the proteome of each species was calculated based on the counts of residues found in the translated sequences of the orthologous transcripts from both the concatenated set of the 423 genes and each gene separately using an in-house Python script. Based on these counts, several thermophilic criteria previously described in the literature to discriminate between hyperthermophilic and mesophilic prokaryotes (de  Farias and Bonato 2003; Suhre and Claverie 2003; Zeldovich et al. 2007; Wang and Lercher 2010)  were calculated. According to  Jollivet et al. (2012)  and  Holder et al. (2013) , three thermophilic criteria that better characterize adaptation to hot temperatures in metazoans were more specifically tested: 1) the CvP (charged: DEKR vs polar: GHNPQST) bias criteria, 2) the EK/QH ratio, and 3) the IVYWREL criterion.
A matrix of amino acid counts at orthologous sites was produced based on the POGs alignments, in which rows represented species, and columns the amino acid frequencies. The factorial component analysis (FCA)  (Teil 1975 ) was conducted following a count normalization (transformation and scaling of the dataset) using the FactomineR package  (Heet al. 2008)  to explore how the amino acid composition (i. e. the overall variance) is partitioned between species. The amino acids that contribute the most in separating the "hot" versus "cold" species were then used to establish a new criterion.
Phylogenomic Reconstruction Previous phylogenetic analyses done with either ribosomal DNA  (Feral et al. 1994; Rousset et al. 2003)  or the mitochondrial Cox1 gene  (Vrijenhoek 2013 ) led to alternative scenarios about the monophyly or the polyphyly of the genus Paralvinella. Depending on the gene used, the dichotomy between the two morphologically distinct genera (i. e. Alvinella vs Paralvinella) is not fully supported (see supplementary fig. S1 , Supplementary Material online). Because of such a discrepancy, an unrooted phylogenomic tree of the six alvinellid species was reconstructed with RAxML-VI-HPC  (Stamatakis 2006)  and the GTR + Gamma nucleotide substitution model, in which the substitution rate variation among sites is modeled by the gamma distribution with four rate categories. Tree parameters and substitution models were optimized on the concatenated dataset of coding sequences from the aligned and filtered POGs using a codon partition model regardless of the substitution model used.
Reconstruction of the Residue Composition for Ancestral Nodes Ancestral states of the residue composition of alvinellid proteins were reconstructed over the whole set of concatenated genes from the amino acid frequency of the sequences inferred from the Bayesian reconstruction of ancestral nodes in the "aaml" package in PAML v4. 0 software  (Yang 2007)  using the classical Jones' matrix of amino acid substitutions and a P-value threshold of 0. 90 on amino acid replacements. To test whether the thermophilic trait of the worms is ancestral or recently derived in parallel in a few species, the new metazoan criterion (as designed from the result of the factorial correspondence analysis and the ecological a priori binomial tests) was computed from the frequency of residues of the reconstructed protein sequences at the four ancestral nodes of the alvinellid tree and on sequences of the present species.
Derived Mutation Rates in Recent Lineages Derived amino acid substitution rates in recent lineages (i. e. terminal branches) were also estimated from both the POGs dataset (concatenated and 423 individually). In this case, the derived substitution rate strictly refers to "private" substitutions, that is, that only occur in one lineage with all other lineages sharing the same alternative residue-a parsimonious ancestral state allowing us to orientate the mutation. The idea here is to solely target the relatively recent substitution events possibly prone to positive selection. This allows us to test whether thermophily is an ancestral or derived trait and alternative scenarios of parallel evolution in either chimney species (e. g. Ap, Ac, Ps, Pf) or "cold" species (Pp and Pg). To test whether the derived mutation rate can be higher in some species, the number of derived replacements was weighted by the overall divergence accumulated in terminal branches to account for the unequal time elapsed since the speciation between species.
This was achieved by the construction of an ultrametric tree corresponding to the ML tree previously obtained using the "mid-rooting position" approach implemented in Seaview 4. 0  (Gouy et al. 2010) , and the "ultrametrize" option of "Chronopl" from the Ape package in R  (Paradis et al. 2004 ). The null hypothesis of constant rate of accumulation of derived mutations was tested with a 2 statistics. We also tested whether the direction of substitution could lead to a specific enrichment in several classes of residues based on their electro-chemical properties. The selected classes were: Positively charged, negatively charged, polar, aliphatic, and aromatic plus the separate counts of un-categorizable residues cysteine, proline and glycine. We then computed the relative differences in amino acid classes/criteria observed between lineages (e.
Strength and Mode of Selection over Lineages The nonsynonymous/synonymous substitution ratio ! was also computed for each branch of the alvinellid phylogenomic tree using the free-ratio branch model (M1) implemented in the package CodeML of the PAML v4. 0 software  (Yang 2007). The small number of species used in the tree should reduce the risk of over-parametrization. Using the tree topology obtained with RaxML ((Ap,Ac),(Pp,(Pg,(Pf,Ps)))) as a reference, we compared this model with the one-ratio model (M 0 ) using a Likelihood Ratio Test (LRT) with a df of n-1 branches for either the concatenated set of sequences or each of 423 POGs independently. The ! values were estimated for each terminal branch and subsequently used to calculate an intergene median per branch and its standard error after filtering (see supplementary material S1, Supplementary Material online ).
Assembly and Gene Orthology The total number of assembled transcripts obtained from the Velvet/Oases procedure (with a kmer = 21) ranged from 20,018 in P. pandorae to 40,843 in P. grasslei, with the noticeable exception of P fijiensis (one Illumina lane), for which a maximum of 80,939 transcripts were successfully assembled (see supplementary table S1, Supplementary Material online for assembly statistics). Based on these sequence datasets, two sets of candidate orthologous loci were generated: One without missing species (423 POGs) and the other allowing one missing species for each POG (1340 POGs).
This new criterion corresponds to amino acids that also significantly differed between the two ecological groups on the basis of the sign test with ecological priors. Additionally, the arrangement of species on the first factorial axis was not the direct consequence of the GC genome-wide bias, as there is no correlation between the GC content and the coordinates of amino acid on the first FCA axis. Finally, cold-adapted species also displayed specific signatures of disordered residues using the Ising prediction software of  Lobanov and Galzitskaya (2011). Although not very conclusive, results showed that P. pandorae displays a greater proportion of disordered residues (about 42%) when compared with the other species (33-37%; see supplementary fig. S3 , Supplementary Material online).
Acknowledgments We are particularly grateful to the chief scientists that lead the oceanographic cruises Biospeedo 2004 ( D. Jollivet , doi: 10. 17600/4010050 ), JdFR 2008 Expedition  ( OCE06-23554 ,  P. R. Girguis ,  R. W. Lee ),  Lau Basin 2009 Expedition  ( C. R. Fisher ) and Mescal 2010 ( N. Le Bris  and  F. H. Lallier , doi: 10. 17600/12010020 )and to the  "Nautile", "Alvin" , and " Jason II " crews for their technical support and efforts during the expeditions for the animal collection. We thank the  Roscoff ABIMS platform of bioinformatics , and more particularly  S. Caron  for his help in the regular use of computing cluster facilities and to  M. Monsoor  for developing the pipeline suite (AdaptSearch) for the Galaxy environment. This research was supported by a joint research postdoc grant funded by both the  Institut Ecologie et Environnements (InEE) du CNRS  and the  Conseil General du Finiste  `re ( CG29 ) and by the  ANR  (project  05-BLAN-0407 ), the  Total Foundation and, the programme "Molecular and Cellular Biology " ( 01201353567 ) for O.
Analysis of sites of newly integrated DNA in cellular genomes is important to several fields, but methods for analyzing and visualizing these datasets are still under development. Here, we describe tools for data analysis and visualization that take as input integration site data from our INSPIIRED pipeline. Paired-end sequencing allows inference of the numbers of transduced cells as well as the distributions of integration sites in target genomes. We present interactive heatmaps that allow comparison of distributions of integration sites to genomic features and that support numerous user-defined statistical tests. To summarize integration site data from human gene therapy samples, we developed a reproducible report format that catalogs sample population structure, longitudinal dynamics, and integration frequency near cancer-associated genes.
These analyses allow users to carry out numerous custom statistical comparisons with annotations, random distributions, and other datasets by simply pointing and clicking. We also present a series of analytical tools for use with patient samples to characterize integration site population structure and possible adverse events. Results are packaged into reproducible reports (html or pdf file format), allowing for version tracking of the code, datasets used, and external datasets queried. Using these tools, we describe examples of tracking a subject from the first gene therapy trial to treat severe combined immunodeficiency-X1 (SCID-X1) deficiency. The data demonstrate durable reconstitution accompanied by a clonal expansion of cells harboring an integrated vector near the cancer-associated gene CCND2.
The INSPIIRED Pipeline The INSPIIRED pipeline is summarized in Figure  1. The first steps involve the generation of a sequence library and sequence data acquisition, genomic alignment, analysis of viral integration sites in repeated sequences, and quality controls (described in the accompanying paper  9  ). The intSiteCaller program takes FASTQ files as input. After sequence quality filtering, trimming of DNA sequences added during library construction, and sequence alignment, unique sites and integration sites in repeated sequences ("multihits") are saved in an intermediary binary format (RData file format). All sites from each run of the sequencing instrument are uploaded into a MySQL database (IntSiteDB) for storage and for use in downstream analysis using a utility script (intSiteUploader).
Alternatively, the INSPIIRED pipeline also supports use of a SQLite database, which is provided with the software. The IntSiteDB stores genomic locations of integration sites together with PCR break points and their counts, which is used for estimation of abundance. 34 All downstream analyses are carried out using genomic locations and sonic break points. The IntSiteDB schema is shown in Figure  S1. We use intSiteRetreiver, a key component of the INSPIIRED software package, to retrieve unique sites and multihits for chosen samples from the IntSiteDB for analysis. The database organization allows the combined analysis of multiple samples from different instrument runs. Integration sites are annotated with the hiAnnotator R software package (http://bioconductor. org/packages/release/bioc/html/hiAnnotator.
Analysis of the Relationship between Integration Site Locations and Genomic Annotation We use heatmaps to summarize the relationships between integration site distributions and genomic annotations (Figures  2, 3,  and 4 ). These maps were introduced in Berry et al. ,  35  which presents more background and examples of their uses. The heatmaps summarize information on integration site datasets in columns and different genomic features in rows. For each comparison, integration site distributions are compared with distributions of randomly selected sites in the human genome. 4, 35 Early integration site recovery methods involved use of cleavage by restriction enzymes, which are unevenly distributed in the human genome. 32, 33 For this reason, random controls were matched based on proximity to restriction enzyme cleavage sites.
35 The INSPIIRED pipeline uses random cleavage by sonication, so purely random control sites are generated in silico and used in the analysis described here. In the heatmaps, colored tiles indicate the intensity and direction of any departures from the distributions of random controls for each genomic feature in each integration site dataset. Three random sites are picked per integration site. The locations are then annotated using the hiAnnotator R package. The coincidence of genomic feature "J" with each integration site and random control site is measured. The nonparametric method of esti-mating receiver operating characteristic (ROC) curve areas and their covariance structure of DeLong et al. 45  is used. Each integration site is compared in a pairwise fashion with random control sites, and a number is assigned indicating the relative rank of the integration site: 1 if the measurement of J is higher at the integration site than at a random control site, 0 if the measurement of J is lower at the integration site than at a random control site, and 0.
5 if the measurement of J is equal for the two sites. All such values are calculated for a dataset of integration sites and averaged to obtain the overall ROC area for the feature measured (https://github. com/BushmanLab/hotROCs). This is equivalent to comparing the ranks of the sites with those of the controls. In older datasets with integration sites recovered by cleavage with restriction enzymes, matched random controls based on proximity to restriction enzyme cleavage sites were used. In that setting ROC curve areas were based on comparing each site only with its matched controls. 35  ROC area between 0 and 0. 5 indicates the genomic feature occurs less frequently at or near integration sites than at or near random sites in the genome and is therefore disfavored. An ROC area between 0.
5 and 1 indicates the genomic feature is enriched at integration sites. An ROC area of exactly 0. 5 indicates that integration sites in the dataset are neither enriched nor depleted with respect to the feature of interest. The ROC area is converted to a color tile according to the colorimetric scale shown at the bottom of the heatmap. 35 In Figure  2 , positive associations (enrichment compared with random) are shown as increasingly intense shades of blue, negative associations (depletion compared with random) as increasing intense shades of yellow, and no difference from random as black. Each tile represents a comparison of integration sites with the randomly sampled controls for one genomic feature (row) in one experimental dataset (column). Note that we do not present the magnitude of effect in terms of the original units of measurement.