dataesr/scientific-paragraphs-categorization huggingface dataset:
ACKNOWLEDGEMENTS The authors thank  M. Duffy  and  S. Schelhaas  for proof reading and  C. Bätza ,  S. Bouma ,  F. Breuer ,  W. Gottschlich ,  C. Gräf ,  I. Hoppe ,  M. Kattenbeck ,  S. Köster ,  C. Möllmann ,  R. Priebe , and  D. Reinhard  for their excellent technical support. The research leading to these results has received funding from the  Interdisciplinary Centre for Clinical Research (IZKF) ;  Münster; Germany  (project  SchwJ3/001/11  and  Core Unit PIX)  and the  European Union 's  Seventh Framework Programme  ( FP7/2007-2013)  under grant agreement n°  278850  ( INMiND ). The authors declared no conflict of interest.
Statistical analyses. All values are expressed as the mean ± S. E. M. Non-parametric tests were used: Mann-Whitney test to compare two groups and Kruskal-Wallis test followed by Dunn's adjusted multiple comparisons to compare more than two groups were performed using GraphPad Prism version 6. 0 for Windows (GraphPad Software, San Diego, CA, USA). A value of P < 0. 05 was considered statistically significant.
Acknowledgements The authors thank  Nathalie Ialy-Rado  from  Core Animal Facilities  and  Isabelle Pingenot  from the  Department of Gastroenterology and Nutritional Support at Beaujon Hospital  for their technical supports. They thank also  Robert Ducroc  and  Henri Duboc  for helpful criticisms and suggestions. This research was supported by the  Institut National de la Santé et de la Recherche Médicale (INSERM) ,  Assistance Publique des Hôpitaux de Paris (APHP) , a  BIOCODEX grant  to FJ and a LACTALIS grant through the  Société Francophone de Nutrition Clinique et Métabolisme  to LG. LG and JBC received Ph. D. fellowships from the  French Ministry of Education and Research ; LB received grants from  Fonds d'Etudes et de Recherche du Corps Médical (FERCM)  and from  DHU  UNITY; LRP received a grant from  Fondation pour la Recherche Médicale.
solve algorithm. [22] All non-H atoms were refined anisotropically, with the exception of highly disordered groups. H atoms were refined isotropically using a riding model. All structures were refined by full-matrix least squares against F 2 of all data using the programs SHELXL  [20]  and OLEX2. refine. [23] The program DIAMOND was used for graphical representation. [24] General color code: carbon (white), sulfur (yellow), oxygen (red), phosphorus (purple), rhodium (dark green), nitrogen (blue). Crystal data and experimental details are listed in Table  S1 ; full structural information has been deposited with the Cambridge Structural Database, CCDC 1419146 to 1419156. General photophysical measurements: UV-visible absorption spectra were obtained on an Agilent 1100 Series Diode Array spectrophotometer using standard 1 cm path length quartz cells.
Data were collected to 10 000 counts in the peak channel and were fitted over >1 000 channels. The instrument response function (IRF) was measured using a scattering sample (LUDOX) and setting the emission monochromator at the wavelength of the excitation beam. The resulting intensity decay is a convolution of the luminescence decay with the IRF, and iterative reconvolution of the IRF with one or two decay function(s) and non-linear least squares analysis was used to analyze the convoluted data. A bi-exponential decay fit was chosen only when the fit was significantly better than with a single function. The quality of all decay fits was judged to be satisfactory, based on the calculated values of the reduce χ 2 and Durbin-Watson parameters and visual inspection of the weighted residuals.
Acknowledgements We thank the  DFG  for support. A. S. thanks the DAAD and the  EU (Marie-Curie   FP7 ), M. -H. T. thanks the  FQRNT Quebec, Canada  and R. M. E. and A. L. thank the  Alexander von Humboldt Foundation  for postdoctoral fellowships. M. G. T thanks  Universiti Malaysia Sarawak, Malaysia , for a Ph. D. scholarship. Part of this work was conducted within the scope of the  CNRS Associated European Laboratory "Molecular Materials and Catalysis (MMC )" involving the  Department of Chemistry of Durham University  and the  Institut des Sciences Chimiques de Rennes of the University of Rennes 1 , and within the  Collaborative Research Network "Solar Technologies go Hybrid " of the  Bavarian State Ministry of Science, Research , and the Arts.
To this aim, we performed transcriptome analyses and developed the PhyloFish database to provide (i) de novo assembled gene repertoires in 23 different ray-finned fish species including two holosteans (i. e. a group that diverged from teleosts before TGD) and 21 teleosts (including six salmonids), and (ii) gene expression levels in ten different tissues and organs (and embryos for many) in the same species. This resource was generated using a common deep RNA sequencing protocol to obtain the most exhaustive gene repertoire possible in each species that allows between-species comparisons to study the evolution of gene expression in different lineages. The PhyloFish database described here can be accessed and searched using RNAbrowse, a simple and efficient solution to give access to RNA-seq de novo assembled transcripts.
In line with that lack of an evolutionary based dataset of teleost genomes, our knowledge of expressed gene repertoires remains also extremely limited and skewed towards specific branches within the teleost tree of life. Significant resources exist in some lineages (e. g. percomorphs) while they are scarce in other lineages (e. g. osteoglossomorphs). The lack of data generated using similar (or at least comparable) methodologies across several species that make comparative analysis possible is a hurdle for understanding. For reasons listed above, it is currently difficult to compare gene expression among teleost species due to (i) the lack of an exhaustive gene repertoire in all but a few species and (ii) the lack of expression data collected using comparable methodologies across the same tissues and stages in different species.
The PhyloFish database was designed to address both questions and provides a comprehensive gene repertoire from de novo assembled RNA-seq data in a large number of species chosen to entirely span the ray-finned fish tree of life with special attention for TGD and SaGD WGD events. The PhyloFish database also provides consistent gene expression data in the same tissues and organs in the different species to allow between-species comparisons. The PhyloFish database is therefore a unique and essential resource to study the evolution of gene expression in the different ray-finned fish lineages that will be extremely useful in many biological fields such as 'evo-devo' , ecology, toxicology, aquaculture, and physiology.
Species selection and tissue collection Fish used in this study were reared and handled in strict accordance with French and European policies and guidelines of the INRA LPGP Institutional Animal Care and Use Committee (# 25 M10), which approved this study. Species included in the PhyloFish database (Fig. 1 , Table  1 ) were chosen not only for their evolutionary position in the tree of life  [2, 22]  but also, when possible, for their ecological and economical relevance. A total of 23 species were included in the database to span two different whole genome duplication events found in teleost fish. Different species were therefore selected before the TGD (Holosteans, N = 2 species), after the TGD and before the SaGD (TGD teleosts, N = 15 species), and after SaGD (SaGD teleost, N = 6 species).
In addition, two species (Pike (Esox lucius) and Eastern mudminnow (Umbra pygmaea)) were selected among Esociformes as this group serves as the most closely related outgroup to study evolution after the SaGD. After SaGD, six species were selected among Salmoniformes, providing a unique opportunity to explore the evolution of gene expression and function after a comparatively recent animal genome duplication event. For each species included in the database we constructed separate libraries from the following tissues or organs to allow analysis of tissue specific expression patterns: brain, liver, gills, heart, muscle, liver, kidney, bones, intestine, ovary, and testis. The gill library for blackghost knifefish (Apteronotus albifrons) is lacking due to limiting RNA quality libraries for embryos or larvae were made for gar (Lepisosteus oculatus), European eel (Anguilla anguilla), Aliss shad (Alosa alosa), zebrafish (Danio rerio), panga (Pangasius hypophthalmus), Northern pike (Esox lucius), grayling (Thymallus thymallus), Atlantic cod (Gadus morhua), medaka (Orysias latipes), Eurasian perch (Perca fluviatilis), brook trout  For each species, the common name (according to fishbase.
org), the species name, phylogenetic group, the number of de novo assembled contigs generated, and position related to successive whole genome duplication (WGD) are shown. VGD2 (vertebrate 2 nd round of WGD), TGD (teleost-specific WGD), SaGD (salmonid specific WGD) (Salvelinus fontinalis), Mexican tetra (Astyanax mexicanus, both cave and surface populations), and European whitefish (Coregonus lavaretus). For all species, tissues were sampled from the same female individual and testis from a male individual, when possible. For rainbow trout, existing RNA-seq data previously used in the rainbow trout genome sequencing project were used  [13]. In this study, tissues had been sampled from a gynogenetic female and the testis is missing. In some species and depending on the tissues, RNA samples from different individuals were pooled to obtain sufficient amounts of RNA for sequencing.
RNA-seq Sequencing libraries were prepared using a TruSeq RNA sample preparation kit, according to manufacturer instructions (Illumina, San Diego, CA). Poly-A-containing mRNA was isolated from total RNA using poly-T oligoattached magnetic beads, and chemically fragmented. First-strand cDNA was generated using SuperScript II reverse transcriptase and random primers. Following the second strand cDNA synthesis and adaptor ligation, cDNA fragments were amplified by PCR. Products were loaded onto an Illumina HiSeq2000 instrument and subjected to multiplexed paired-end (2 × 100 bp) sequencing. The processing of fluorescent images into sequences, base-calling and quality value calculations were performed using the Illumina data processing pipeline.
de novo transcriptome assembly For each library, raw sequence data in fastq format were quality checked, stored in the ng6 database [http:// www. biomedcentral. com/1471-2164/13/462], and filtered to remove unknown nucleotides. The longest subsequences without Ns exceeding half of the total read length were retained. Velvet and Oases performed transcriptome de novo assembly  [23]. We first constructed nine independent assemblies for each library using different k-mers (k-mers for velveth: 25,31,37,43,49,55,61,65,69; parameters for velvetg: -read_trkg yes -min_contig_lgth 100 -cov_cutoff 4; parameters for oases: -cov_cutoff 4). Raw transcripts. fa files were filtered to retain only one transcript per locus based on the highest fold coverage using a Python script developed by a bioinformatic team at the Brown University (https://sites.
google. com/a/brown. edu/ bioinformatics-in-biomed/velvet-and-oases-transcriptome). Antisense chimeras accidentally produced during the assembly step were removed using a homemade script. Independent assemblies were pooled and duplicate/similar transcripts built by close k-mers were removed by a cd-hitest  [24]  step (parameters: -M 0 -d 0 -c 0. 98) and merged by a TGICL  [25]  step (parameters: -l 60 -p 96 -s 100000). After this assembly process, all input reads were mapped back to the set of transcripts using BWA  [26]  and the size of the longest open reading frames (ORFs) for each transcript was computed using the getorf EMBOSS tool  [27]. Finally, transcripts were filtered using mapping rate and ORF length criteria. Transcripts with ORFs shorter than 200 nt and with fewer than two mapped reads per million of overall mapped reads were discarded.
Transcriptome coverage and quality control The de novo assembly procedure was trained and optimized using zebrafish, for which a genome-based high quality transcriptome is available. Our de novo assembly procedure yielded 48,158 contigs in zebrafish. This number is consistent with the 25,642 coding gene and 57,369 gene transcripts predicted from the latest Ensembl genome assembly (GRCz10, 2014). The number of Phylo-Fish contigs for zebrafish is lower that the total number of Ensembl zebrafish transcripts. This difference can be explained, at least in part, by the biological material used here (10 tissues, each being sampled at a single biological stage) that does not cover all possible biological conditions. The number of transcript contigs scaled with the number of WGD events, from holeosteans (two) to most teleosts (three) to salmonids (four) (Table  1 ).
While the lowest number of contigs (<41,500, N = 2) was found in holosteans, it ranged between 42,200 and 60,200 in TGD teleosts (N = 15) and between 67,000 and 78,400 in SaGD species (N = 6). These figures track with the number of genes resulting from the different WGD events found in the analyzed species. In rainbow trout, a SaGD species, it has been shown that 48 % of the duplicated genes originating from SaGD were retained in two copies  [13]. The mean number of contigs in the 15 TGD but non-SaGD species present in the PhyloFish database was 48,900, while it was 72,000 for the six SaGD salmonid species, on average. We have therefore generated 47 % more contigs in SaGD species in comparison to TGD species, in agreement with the percent of duplicated gene retention after WGD in salmonids (i.
Database features The PhyloFish database is made available (http://phylofish. sigenae. org/index. html) through the internet using RNAbrowse, which provides a simple and efficient access to RNA-Seq de novo assembled transcripts  [28]. RNAbrowse offers many features that will help users analyze and extract biologically meaningful information from the PhyloFish data. The PhyloFish web browser offers several different possible modes of analysis. For each species, which can be selected in the front page by a simple click on the species name, an overview is provided that includes a set of graphics showing general statistics, containing for example the contig length histogram. The browser also includes detailed information about the different sequenced libraries and provides access to tools such as Venn diagrams and digital differential display.
A blast query form is available to align a known sequence on all contigs. The query must be provided using a fasta or multi fasta format. The search can also be done using a name or description through the biomart form. Users can then add retrieved contigs to the favorite table. For each contig, the sequence can be extracted to perform a multiple alignment to check if different splice forms have been assembled. All possible open reading frames can be visualized and annotations can be graphically displayed using jbrowse  [29]. It is also possible to graphically visualize expression levels along the contigs in the different libraries. Expression data in the various libraries can be exported to generate expression profiles for the different tissues/organs. To our knowledge, the PhyloFish database is the only database that allows (i) the identification of contigs in such a large diversity of fish species, including many species with no or limited transcriptomic resources, and (ii) the generation of tissue expression patterns from 23 different species (including two holosteans) in which the same tissues were sampled by consistent methodologies and for which the RNA-seq procedure is similar (i.
Case study To illustrate the utility of the PhyloFish database to solve problems of gene evolutionary history, we used it to decipher the evolutionary history of stra8 (Stimulated by retinoic acid gene 8), and subsequently characterize its expression in holosteans and teleosts. The stra8 gene encodes a retinoic acid-responsive protein that is involved in the regulation of meiotic initiation during spermatogenesis and oogenesis  [30]. This gene was first hypothesized to be lost either in the ray-finned fish lineage or in the teleost lineage  [31]. This assumption was mainly based on its absence from the zebrafish genome and other teleost reference genomes available at that time (i. e. stickleback, Tetraodon, fugu, medaka). The loss of stra8 in teleosts was however recently challenged by the discovery of an apparent stra8 ortholog (AGM53488.
1) in Southern catfish (Silurus meridionalis)  [32]. We revisited stra8 gene evolution using the PhyloFish database as a main resource. Using the Stra8 protein sequence from Southern catfish  [32] , we queried PhyloFish databases and retrieved fourteen sequences with a significant Stra8 hit in thirteen teleosts and one holostean species (species in bold type in Fig. 2a ). These fourteen sequences were used in a phylogenetic analysis combined with the Southern catfish Stra8 protein sequence used as bait in our analysis and three additional teleost Stra8 sequences available in public databases (Esox lucius, Astyanax mexicanus, and Anguilla japonica). Phylogenetic analysis revealed that all these PhyloFish sequences are true orthologs of the tetrapods and the southern catfish stra8 gene (Fig.
2a ) and that only a single stra8 paralog was retained after the TGD whole genome duplication. No stra8 sequence was found in the Phylo-Fish database for zebrafish, cod, medaka, and European perch, thus corroborating previous reports based on zebrafish and Acanthomorpha genome analysis  [31]. No stra8 homolog was detected in public databases in any Cypriniform species (e. g. , carps) even after an extensive search of GenBank nucleotide collection (nr/nt), Expressed Sequence Tags (ESTs), Transcriptome Shotgun Assembly (TSA), and NCBI genomes. This surprising finding strongly suggests that stra8 was lost in Acanthomorpha (Fig. 2b ), and independently lost in the Cypriniform lineage. In addition, using the PhyloFish database, we explored the tissue expression of stra8 genes, showing that stra8 is mainly gonadal with a predominant expression in the testis (Fig.
3 ), as previously shown in the Southern catfish  [32]  and in mammals  [33]. In addition to the stra8 case study presented above that highlights a very specific case of evolution after duplication (i. e. , loss of one copy of a duplicated pair of paralogs and lineage-specific losses of the second copy) we also investigated a more classical case of gene evolution. We thus characterized the evolutionary history of mcam (melanoma cell adhesion molecule) (also known as cd146). This gene encodes a protein with known roles in cell adhesion and in cohesion of the endothelial monolayer at intercellular junctions in vascular tissue  [34, 35]. Using a combination of sequences originating from sequences available in GenBank and from the PhyloFish database, we reconstructed the evolutionary history of the mcam gene (Fig.
4 ). This gene was retained as two paralogous copies after the TGD with an additional complete retention of duplicated paralogs in the salmonid lineage after the SaGD. This gene follows a complete 1 (Tetrapods and Holostei) to 2 (Teleosts) to 4 (Salmonids) duplication rule with a total retention of paralogs after two round of whole genome duplication leading to four copies in salmonids. PhyloFish data were also used to characterize the evolution of the expression of prrx1 and prrx2 genes, two VGD ohnologs, in teleosts compared to the spotted Gar. We concluded that for prrx, the spotted gar genome and gar gene expression patterns mimic mammals better than teleosts do, and that there is significant diversity among teleost lineages with respect to the loss and retention of prrx TGD ohnologs  [36].
Finally, the Phylo-Fish database was recently used by the Spotted Gar Genome Consortium to thoroughly analyze the evolution of gene expression after TGD using spotted gar, zebrafish, and medaka  [37]. Fig. 2  Stra8 proposed gene evolution in teleosts following the TGD WGD. Maximum-likelihood phylogeny of Stra8 (a) was performed using the PhyML software  [38]  implemented in the Phylogeny. fr web platform  [39]  using default "a la carte" parameters and a bootstrapping procedure (N = 100 bootstraps). The resulting tree was exported and edited in Evolview  [40]. Input sequences were retrieved using a tblastn search of the PhyloFish database using as bait the Southern catfish Stra8 protein (AGM53488. 1). PhyloFish Stra8 coding sequences (in bold on the tree) were submitted to GenBank with the following accession numbers: Lepisosteus oculatus (KU161162), Osteoglossum bicirhosum (KU161164), Anguilla anguilla (KU161163), Alosa alosa (KU161165), Astyanax mexicanus (KU161166), Apteronotus albifrons (KU161167), Oncorhynchus mykiss (KU161168), Salvelinus fontinalis (KU161169), Coregonus lavaretus (KU161172), Coregonus clupeaformis (KU161171), Salmo trutta (KU161170), Thymallus thymallus (KU161173), Umbra pygmae (KU161174) and Plecoglossus altivelis (KU161175).
This dataset was complemented with two additional teleost public sequences of Stra8 in Esox lucius (XP_012986862) and Astyanax mexicanus (XP_007229918. 1) and a Stra8 sequence deduced from the Anguilla japonica genome (scaffold 6093). The tree was rooted with tetrapod sequences using the Homo sapiens STRA8 (AAP47163. 1) and Alligator mississippiensis Stra8 (XP_006261218. 1). b Schematic representation of the deduced evolution of stra8 based on PhyloFish sequences. This analysis suggests that stra8 was completely lost in Acanthomorpha, but also specifically and independently lost in the Cypriniformes lineage. The tree is based on  [2].
Conclusions The PhyloFish database is a unique resource providing comprehensive expressed gene repertoires collected and processed using the same protocol for 23 ray-finned fish species. This resource is currently the only database offering the possibility to analyze gene expression after genome duplication in teleost fish, including salmonids, in such a comprehensive and comparative way. The Phy-loFish database has already proved its utility and will be of further interest in many biological fields such as 'evodevo' , ecology, toxicology, aquaculture, and physiology. In the future, the PhyloFish database can be expanded to incorporate data from other fish species to broaden its scope and explore gene evolution in many different teleost lineages. Fig. 3  Tissue expression profiles of stra8 reveal expression predominantly in testes in most PhyloFish species.
Relative expression of stra8 was calculated as the percentage of the maximum rpkm (number of reads per kilobase per million reads) value per species. ND: no data (tissue not sequenced in that species) (black ghost knifefish), SRP045099 (European eel), SRP045100 (butterfly fish), SRP045101 (brown trout), SRP045102 (arowana), SRP045103 (aliss shad), SRP045138 (eastern mudminnow), SRP045139 (rainbow trout), SRP 045140 (panga), SRP045141 (northern pike), SRP045142 (grayling), SRP045143 (European whitefish), SRP045144   [38]  implemented in the Phylogeny. fr web platform  [39]  using default "a la carte" parameters and a bootstrapping procedure (N = 100 bootstraps). The resulting tree was exported and edited in Evolview  [40]. Input sequences were retrieved using a tblastn search of the PhyloFish database using as bait the zebrafish Mcam protein (XP_005157627.
(blastx -e 1e-5 -F T -v 20 -b 20) as well as several nucleic acid databases, including Unigene Danio rerio version 126, Oryzias latipes 130 and Ensembl 71 transcripts of Danio rerio, Oryzias latipes, Takifugu rubripes and Tetraodon nigroviridis and RefSeq_RNAs (June 2013).