dataesr/scientific-paragraphs-categorization huggingface dataset:
00 and 0. 66 respectively). Bayesian phylogenetic analyses were carried out separately on the chloroplast and nuclear data sets using the program MrBayes 3. 2. 6  [29]. Each data set was treated as a single partition, analysed under the appropriate model of sequence evolution and the default parameters of two runs with four chains each, run for 10 000 000 generations with a sample tree taken every 10 000 generations. The convergence of the MCMC chains of the two runs was assessed by inspection of the trace plots of parameters using Tracer ver. 1. 6  [30]. The effective sample sizes (ESS) of all parameters were > 200, indicating that each parameter was sampled satisfactorily. The first 25% of sampled trees were discarded as burn-in, and the remainder summarized as a maximum clade credibility tree.
Incongruence tests Alignments with matching sampling for both chloroplast and nuclear markers were constructed for use in conducting an Incongruence Length Difference test (ILD)  [33]  and measures of internode certainty (IC)  [34]. The ILD test was conducted using PAUP, using 100 replicates based on heuristic searches with TBR branch swapping, each with 10 random addition replicates and Maxtrees set to 100. In order to further examine topological incongruence between the datasets, post burn-in samples of trees resulting from the Bayesian phylogenetic analysis of the chloroplast and ITS data were combined into a single majority rule consensus (MRC) tree with IC values for each node using RaxML  [35]. The IC metric (scaled between 0 and 1) represents the certainty for each internal branch, taking into account the frequency of the most prevalent conflicting bipartition in the population of trees used to make the consensus.
For example, if there are two conflicting bipartitions between the chloroplast and ITS derived topologies, each present at 100% frequency in the different datasets, then IC = 0, reflecting the complete incongruence between the genomes. A bipartition with 100% frequency in trees derived from the chloroplast dataset and 50% frequency in the ITS dataset, contradicted by 50% of the remaining trees in the ITS dataset would have an IC = 0. 18. Comparing all post burn-in trees allows us to further investigate the full range of topologies produced by the two separate analyses, rather than just comparing a separate consensus of each.
Molecular phylogenetics The ITS alignment consisted of 853 bp in length, with 299 of these being parsimony-informative. The chloroplast alignment consisted of 6764 bp in length, with 370 of these being parsimony informative. A majority of the species sampled in our Begonia sect. Baryandra phylogenies show some incongruence between their placements in the chloroplast and nuclear phylogenies ( showed some polymorphism towards the end of the reads, however good sequence data was obtained for all the alignment for these taxa with the exception of portions of the 5. 8S gene and the ITS2 spacer.
Incongruence tests The ILD test, as expected, showed significant incongruence between the chloroplast and ITS datasets (P = 0. 01). Only two clades of more than three taxa were present in the MRC tree Given the amount of incongruence between the phylogenies, assessing which species have a similar position in the two analyses is difficult. A large number of species show hard incongruence between our analyses, being in conflicting positions with support of PP >0. 95. We split these into two categories, depending on the spread of the differing positions in the two analyses. Firstly, there are species where the incongruence could potentially be due to lineage sorting, as the branch lengths are relatively short and only one node is involved.
gironellae are monophyletic in the nrDNA phylogeny, whilst appearing in two positions in the chloroplast phylogeny ( Petermannia and Baryandra respectively). The ITS sequence data from B. palawanensis places it outside the outgroups used for the analysis, and in a clade reflecting its morphology and taxonomy, with other members of Begonia sect. Petermannia from Borneo, the Philippines and New guinea (analysis not included here). The samples for these two species were taken from nearby localities near Salakot Falls, and it is probable that the population of B. palawanensis has captured the chloroplast from adjacent populations of B. tenuibracteata. Hence it seems that a large proportion of the 49 species we sampled from Palawan have acquired a foreign plastid at some point during their evolution.
Acknowledgments We thank the  Palawan Council for Sustainable Development ; the  Puerto Princesa Subterranean River National Park Protected Area Management Board ; the  Puerto Princesa City Council ; the  El Nido-Taytay Managed Resource Protected Area Management Board ; the  El Nido Municipal Council  and the  Department of Environment and Natural Resources  for granting access and research permits. We are indebted to  Prof. Elizabeth P. Gironella  of the  Palawan State University  who guided us in the 2014 field trip to Palawan. We thank the following people of  PSU  who helped us in the field:  Dr. Frances Muriel Tuquero , Director,  PSU Extension Office ;  Prof. William Martinez Herrera ,  Campus Director ,  PSU Brooke's Point, Palawan ;  Mr. Rejesam Nava  and  Family ,  Extension Staff  (detailed at  SIFMA  Project),  Culasian, Rizal, Palawan ;  Mr.
This study was supported in part by grants from  Ministry of Science and Technology, Taiwan  and  Academia Sinica  to  Ching-I Pen  g and  Kuo-Fang Chung  ( MOST 101-2621-B-001-003 ) as well as the University of the Philippines Enhanced Creative Work and  Research Grant  ( ECWRG-2015-2-035 ) to  Rosario R. Rubite. Mark Hughes  is grateful to the  Sibbald Trust  and  The Royal Society of Edinburgh Bilateral Programme  for funding research visits to  Academia Sinica. The  Royal Botanic Garden Edinburgh  is supported by the  Scottish Government's Rural and Environment Science and Analytical Services Division. During 2017 we are also grateful for the support of players of People's Postcode Lottery towards our scientific research.
1b ). Crystals (space group P6 4 ) of the core derived by trypsination diffracted to only 7 Å resolution probably because of the fragment heterogeneity. Better crystals (space group P3 1 21), diffracting to 3. 7 Å resolution, were obtained by co-expression of two defined fragments denoted as ARS2 147-270+408-763 in E. coli. The structure of ARS2 147-270+408-763 was solved using selenomethionine-labelled protein and the single-isomorphous replacement with anomalousscattering (SIRAS) method. The resultant map showed two molecules in the asymmetric unit and could be partially interpreted based on the known structure of the plant homologue SERRATE (PDB:3AX1 [10. 2210/pdb3AX1/pdb]). Based on the incomplete model, the N-terminal helix was truncated at position 171 with the aim of producing better crystals.
A database search reveals that only the homologue SERRATE from Arabidopsis 26 has a similar overall architecture to human ARS2 (Fig. 1c, d ). However, human ARS2 differs from plant SERRATE in being overall more elaborate with many of the equivalent helices being orientated differently, as is apparent when the structures are superposed via helices α1-3 (Fig. 1c, d ). The most significant difference is that SERRATE lacks the RRM domain that is present in metazoan ARS2 (Fig. 1d , Supplementary Fig. 3 ). Apart from this, the C-terminal leg is orientated quite differently with the foot rotated by ~90°(Fig. 1d, e ). In plant SERRATE, C500, C505, H518 and H523 ligate, a zinc ion that structurally stabilises the foot, and these residues are also conserved in S. pombe ARS2. However, in metazoans, C505 is replaced by a serine (S717 in human ARS2), and no zinc is found in the structure (Fig.
R448 from β2 makes a salt bridge with E258, as well as hydrogen bonds to the main-chain carbonyls of loop-C residues 634-635. The α-helical face of the RRM domain is solvent exposed with four hydrophobic residues (L439, L481, I484 and L486) identically positioned as in the RRM domain of the RBM7 subunit of the nuclear exosome targeting (NEXT) complex (L29, L70, I73, L75 and PDB:5LXY [https://doi. org/10. 2210/pdb5LXY/pdb]) (Fig. 2d ). Since RBM7 uses this surface for protein-protein interactions with a peptide from another NEXT component, ZCCHC8  19  , this observation suggests that ARS2 might also interact with partner proteins via the αhelical face of the RRM domain. = β = 90°α = β = 90°α = β = 90°c = 235. 66 Å γ = 120°γ = 120°γ = 120°α = β = γ = 90°W avelength (Å) 0. Metazoan-specific loops.
3  The RRM domain of ARS2 binds single-stranded RNA. FAM-labelled RNA and fluorescence polarisation measurements were used to determine the affinity of various RNAs to hARS2. See also Supplementary Fig. 5. a Recombinant ARS2 147-871 was titrated to FAM-labelled single-stranded (ss), partially double-stranded (pds) and double-stranded (ds) RNA and the polarisation measured for each concentration. b ARS2 147-871 , ARS2 147-270+408-763 and ARS2 147-270+494-763 were titrated to FAM-labelled ssRNA and the fluorescence polarisation measured. c Site-specific mutants of basic residues in the RRM domain, or mutants and deletion in the C-terminal foot of ARS2 147-871 , as indicated, were used to further localise the RNA-binding site. The K D was derived by fitting the data to a single-site binding model.
5a , Supplementary Dataset 1). Components of the RNA degradation machineries (NEXT (RBM7/ZCCHC8/hMTR4)), PAXT (PABPN1/ZFC3H1/hMTR4) and exosomal components (EXOSC4, EXOSC8, EXOSC9 and EXOSC10) were identified, in accordance with previous studies  3, 423, 30. Additionally, splicing factors (THRAP3, TRA2A/B and snRNP proteins), DDX helicases, 3′ end processing factors (CPSF1/2/3/3L/6/7) as well as hnRNP components, subunits of the TRanscription and EXport (TREX) complex (THOC1, 2, 3, 5 and 6), and ALY, hnRNPC and PHAX that are involved in the RNA export, were also identified. As expected, CBC components CBP80 (NCBP1) and CBP20 (NCBP2) were highly enriched, but also NCBP3 (previously C17orf85 or ELG), an mRNA-binding protein  31, 32  recently found to associate with CBP80 and to be important for mRNA export  27.
2 kV was applied. The temperature of the capillary was set at 300 °C. Full scan mass spectra (MS 1 ) with mass range 300-1700 m/z were acquired in profile mode in Fourier transform (FT) with a resolution of 30,000. The filling time was set at maximum of 500 ms with a limitation of 10 6 ions. The most intense ions (up to 15) from the MS 1 were selected for a fragment screen (MS 2 ) in the LTQ. A normalised collision energy of 40% was used, and the fragmentation was performed after accumulation of 3 × 10 4 ions or after filling time of 100 ms for each precursor ion. MS 2 data was acquired in centroid mode, only multiply charged (2 + , 3 + and 4 + ) precursor ions were selected. The dynamic exclusion list was restricted to 500 entries with maximum retention period of 30 s and relative mass window of 10 ppm.
Mass accuracy was improved using a lock mass correction of a background ion (m/z 445. 12003). For filtering the data and creating. mgf files MaxQuant (version 1. 0. 13. 13) was used. The files were used to search in MASCOT version 2. 2. 03 (Matrix Science) against the Homo sapiens Uniprot database with a list of common contaminants appended. The following parameters were set for the search: Carbamidomethyl (C) (fixed modification) and Oxidation (M) (variable modification), the MS 1 scan allowed a mass error tolerance of 20 ppm and for the MS 2 scan 0. 5 Da, and no enzyme was specified. Peptide ladders of increasing length, either starting or ending at the same residue, were used to determine the termini. Isothermal titration calorimetry. For isothermal titration calorimetry (ITC) experiments a MicroCal ITC200 system (Malvern) was used.
To exclude buffer differences, all proteins were dialysed against 20 mM HEPES, 120 mM, 2 mM TCEP pH 7. 8 overnight at 8 °C. Experiments were performed at 25 °C with a stirring speed of 800 rpm. At an interval of 120-180 s, 1. 5 µL of protein A was injected into the cell containing 205 µL of protein B. For the binding between NCBP3 and ARS2 as well as ITC experiments to determine the affinity to m 7 GTP, proteins were dialysed in buffer containing 250 mM NaCl. For the interaction between NCBP3 and ARS2, injections of 2. 5 µL were used. Data were analysed using the MicroCal ITC Origin software and the binding curves were fitted to a single-site binding equation. Fluorescence polarisation measurements. Fluorescence anisotropy binding assays were performed with 5′ FAM-labelled and non-labelled RNA obtained from IBA: 5′-FAM-AGUAGUAACAAGAGGGUA 3′; 5′-FAM-AGUAGUAACAA-GAGGGUA 3′; 5′-AGCAGAAGCAGAGGU 3′; 5′-AGUAGUAACAAGAGGG 3′.
Dynamic exclusion time of 30 s was used. The peptide match algorithm was set to 'preferred' and charge exclusion 'unassigned', charge states 1, 5-8 were excluded. MS 2 data was acquired in profile mode (https://doi. org/10. 1016/j. ymben. 2018. 03. 006). MS data analysis. Acquired data was processed by IsobarQuant  38  and Mascot (v2. 2. 07) and searched against a Uniprot Homo sapiens proteome database (UP000005640) containing common contaminants, reversed sequences and construct sequences. The data was searched with the following modifications: Carbamidomethyl (C) and TMT10 (K) (fixed modification), Acetyl (N-term), Oxidation (M) and TMT10 (N-term) (variable modifications). For MS 1 spectra a mass error tolerance of 10 ppm and for MS 2 spectra of 0. 02 Da was set. Trypsin was selected as protease with an allowance of maximum two missed cleavages and a minimum peptide length of seven amino acids.
At least two unique peptides were required for a protein identification. The false discovery rate on peptide and protein level was set to 0. 01. The raw output data of IsobarQuant was processed using the R programming language (ISBN 3-900051-07-0). Only proteins which were identified with at least two unique peptide matches were kept for downstream analysis. Subsequently, potential batch effects were removed using the LIMMA package  39  and data was normalised using the VSN package (variance stabilisation  40  ). In order to identify proteins that were significantly differentially expressed, LIMMA was used again. A protein was called a hit with a false discovery rate smaller than 1% and a fold change of at least 50%. Furthermore, hits were filtered and only called hits if they were enriched three-fold with a false discovery rate smaller than 1% comparing EGFF-ARS2 wild type against the EGFP and pcDNA3.
Acknowledgements We thank the staff of the  ESRF-EMBL Joint Structural Biology Group , in particular  Matthew Bowler , for access to and help on ESRF beamlines. We thank the  EMBL Grenoble Eukaryotic Expression Facility (EEF)  and high-throughput crystallisation facility (HTX), the  EMBL Heidelberg Proteomics Core Facility  and  Luca Signor  from the  Mass Spectrometry Platform at IBS. This work used the platforms of the Grenoble Instruct Center (ISBG:  UMS 3518 CNRS-CEA-UJF-EMBL ) within the  Grenoble Partnership for Structural Biology (PSB) , with support from  FRISBI  ( ANR-10-INSB-05-02 ) and  GRAL  ( ANR-10-LABX-49-01 ).
Data availability. Structure factors and co-ordinates have been deposited in the wwPDB with codes as follows: 6F7P: ARS2 147-270 +408-763 structure (P3 1 21 form), 6F7J: ARS2 171-270 +408-763 structure (P6 5 22 form), 6F8D: ARS2 171-270 +408-763 structure (P6 5 form), 6F7S: ARS2 147-270 +408-763 Δloop B structure (C222 1 form). The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD009035. Other data are available from the corresponding author upon reasonable request.
Trait values for the 72 benthic taxa were obtained from the expertise of the team members, by consulting other experts, and from literature review (See Supplementary Note 1). This study focused on global comparisons of traits across species and not on intraspecific variation. Trait values represent the most accurate average description of species-specific traits (e. g. size) without accounting for potential intraspecific variability  34. FEs were defined as groups of species sharing the same trait values  35   Functional diversity of benthic assemblages. We tested and quantified whether functional diversity was reduced along natural CO 2 gradients, and whether functional redundancy buffered expected losses caused by reductions in taxonomic diversity. In this study, we pooled the data at both sides (north and south) together to have a general pattern of the effects of acidification, thus resulting in three pH zones: ambient, low and extreme low pH.
Acknowledgements This research was supported by the  National Geographic Society  (Window to the  Future, Grant  No. 9771-15 ) and the  Total Foundation  ( High CO 2 Seas project , Grant No. BIO-2016-081-4 ). N. T. was supported by a  Maire Curie-Cofund  ( FP7-PEOPLE-Marie Curie Bandiera-Cofund , GA No. 600407 ) and by a  Marie Sklodowska-Curie Global Fellowship  under the European Union's  Horizon 2020 research and innovation programme  ( H2020-MSCA-IF-2015 , GA No. 702628 ). We thank  Capitan V. Rando  and  P. Sorvino  ( ANS Diving, Ischia ) for their field assistance. We also thank  E. Cebrian ,  S. de Caralt ,  X. Turon ,  M. J. Uriz ,  J. Vacelet  for their help with trait definitions and  J. Vidaurre  for assistance with Fig. 4. N. T. thanks  A. Smith  for helping with R code. We thank  R.
Background: Tunicates are the closest relatives of vertebrates and are widely used as models to study the evolutionary developmental biology of chordates. Their phylogeny, however, remains poorly understood, and to date, only the 18S rRNA nuclear gene and mitogenomes have been used to delineate the major groups of tunicates. To resolve their evolutionary relationships and provide a first estimate of their divergence times, we used a transcriptomic approach to build a phylogenomic dataset including all major tunicate lineages, consisting of 258 evolutionarily conserved orthologous genes from representative species. Results: Phylogenetic analyses using site-heterogeneous CAT mixture models of amino acid sequence evolution resulted in a strongly supported tree topology resolving the relationships among four major tunicate clades: (1) Appendicularia, (2) Thaliacea + Phlebobranchia + Aplousobranchia, (3) Molgulidae, and (4) Styelidae + Pyuridae.
Notably, the morphologically derived Thaliacea are confirmed as the sister group of the clade uniting Phlebobranchia + Aplousobranchia within which the precise position of the model ascidian genus Ciona remains uncertain. Relaxed molecular clock analyses accommodating the accelerated evolutionary rate of tunicates reveal ancient diversification (~450-350 million years ago) among the major groups and allow one to compare their evolutionary age with respect to the major vertebrate model lineages. Conclusions: Our study represents the most comprehensive phylogenomic dataset for the main tunicate lineages. It offers a reference phylogenetic framework and first tentative timescale for tunicates, allowing a direct comparison with vertebrate model species in comparative genomics and evolutionary developmental biology studies.
A phylogenetic and timing framework is notably critical for the identification and interpretation of both conserved and divergent developmental features of tunicates compared to model vertebrate species in the context of their fast rate of genomic evolution  [11]. Here, we use new transcriptomic data obtained through high-throughput sequencing technologies (Roche 454 and Illumina HiSeq) to build the first tunicate phylogenomic dataset including all major tunicate groups. This dataset consists of 258 orthologous nuclear genes for 63 taxa including representative deuterostome species and all major chordate lineages. Using phylogenetic analyses based on the best-fitting site-heterogeneous CAT mixture model of amino acid sequence evolution, we inferred well-resolved phylogenetic relationships for the major clades of tunicates.
Transcriptome data collection Live tunicate specimens were ordered from Gulf Specimen Marine Laboratories, Inc. (Panacea, FL, USA) and the Roscoff Biological Station (Roscoff, France) services and collected in Villefranche-sur-Mer (France) and Blanes (Spain). One single run of Roche 454 GS-FLX Titanium was conducted at GATC Biotech (Konstanz, Germany) on multiplexed total RNA libraries that were constructed for Clavelina lepadiformis, Cystodytes dellechiajei, Bostrichobranchus pilularis, Molgula manhattensis, Molgula occidentalis, Phallusia mammillata, Dendrodoa grossularia, Polyandrocarpa anguinea, and Styela plicata. Complementary RNA-seq data were acquired with paired-end 100-nt Illumina reads at Beijing Genome Institute (Shenzhen, China) for the thaliaceans Salpa fusiformis (mix of two blastozooids) and Doliolum nationalis (mix of 15 phorozooids), and with single-end 100-nt Illumina reads at GATC Biotech (Konstanz, Germany) for Clavelina lepadiformis and Cystodytes dellechiajei (mix of several individuals)  [36].
Previously obtained 454 transcriptomic data for Microcosmus squamiger  [16]  were also considered. De novo assemblies were conducted with Trinity  [37]  for 454 reads and ABySS  [38]  for Illumina reads using the programs' default parameters. For both kinds of libraries, we confirmed the sample taxonomic identifications by assembling the mitochondrial cytochrome c oxidase subunit 1 (CO1) and nuclear 18S rRNA barcoding genes and reconstructing maximum likelihood trees with available comparative data. Additional tunicate sequences were collected in public databases from various sequencing projects: Botryllus schlosseri, Halocynthia roretzi, and Diplosoma listerianum (expressed sequence tags (ESTs)), Molgula tectiformis (complementary DNAs), and Ciona robusta, Ciona savignyi, and Oikopleura dioica (genomes).
Phylogenomic dataset assembly We built upon a previous phylogenomic dataset  [39]  to select a curated set of 258 orthologous markers for deuterostomes. Alignments were complemented with sequences from the National Center for Biotechnology Information (NCBI) databases using a multiple best reciprocal hit approach implemented in the newly designed Forty-Two software  [40]. Because 454 DNA sequence reads are characterized by sequencing errors typically disrupting the reading frame when translated into amino acids, alignments were verified by eye using the program ED from the MUST package  [41]. Ambiguously aligned regions were excluded for each individual protein using Gblocks with medium default parameters  [42]  with a few subsequent manual refinements using NET from the MUST package to relax the fact that this automated approach is sometimes too conservative.
This manual refinement step restored only 418 amino acid sites (i. e. 0. 6% of the total alignment length). Potential environmental contaminations and cross-contaminations between our samples were also dealt with at the alignment stage by performing Basic Local Alignment Search Tool (BLAST) searches of each sequence against a taxon-rich reference database maintained for each curated gene alignment and were further sought by a visual examination of each individual gene phylogeny. The concatenation of the resulting 258 amino acid alignments was constructed with SCaFoS  [43]  by defining 63 deuterostomian operational taxonomic units (OTUs) representing all major lineages. The taxon sampling included 18 tunicates, 34 vertebrates, and one cephalochordate, with seven echinoderms, two hemichordates, and one xenoturbellid as more distant outgroups.