dataesr/scientific-paragraphs-categorization huggingface dataset:
Differential scanning fluorimetry. Differential scanning fluorimetry (DSF) was performed with SYPRO Orange dye (Catalog #S-6650; Life Technologies) to determine the thermal stability by monitoring the protein unfolding of the purified Fc domains. For each sample, 15 μL of Fc domains varying from 0. 08 to 20 μM were mixed with 5 μL of dye, diluted from 5000× to 20× for use. Each experiment included a control without proteins containing 100 mM HEPES buffer at pH 7. The DSF assays were performed on an Applied Biosystems ViiA 7 Real-Time PCR System using a temperature gradient from 25 to 99 °C at a temperature ramp rate of 0. 03 °C/s. The fluorescence emissions and melting temperature measurements were analyzed using ViiA 7 Software from Life Technologies. AC-SINS. Goat anti-human Fc fragment specific (Jackson ImmunoResearch, 109-005-008) was buffer exchanged into 20 mM potassium acetate (pH 4.
For SPR analysis, IgG1 antibody variants were immobilized on CM5 chip surface at a density of ~500 response units (RU) via an amine coupling. hFcRn:hβ2 m dimer (Novus Biologicals) was injected at serially diluted concentrations (1000-40 nM) in PBS, pH 5. 8, at a flow rate of 30 μL/min. To examine the interaction of hFcRn and antibody variants at physiological pH 7. 4, hFcRn:hβ2m dimer (Novus Biologicals) was immobilized on the BIACore Chip at three different densities, 500 RU, 2000 RU, and 4000 RU via amine coupling  11. Serially diluted antibodies (800-50 nM) were injected in PBS, pH 7. 4, at a flow rate of 30 μL/min. Dissociation constants (K D s) were determined by fitting the corresponding binding isotherms for steadystate data or by fitting the kinetics for association and dissociation employing a 1:1 Langmuir mass transfer model.
Anti-kappa light chain antibody-HRP (Abcam) was used to detect the human antibody (dilution 1:5,000). Absorbance at 450 nm was measured after development with TMB substrate (Pierce Biotechnology, Rockford, IL) according to the manufacturer's directions. Standard curves were generated for each antibody variant diluted into 1:100 pre-bleed mouse serum. The linear portions of standard curves generated in Prism (GraphPad Software) were then used to quantify human IgG in the serum samples. Pharmacokinetic parameters were analyzed with a two-compartment elimination model. AUC inf (area under the curve to infinity) was calculated using the log-linear trapezoidal method  20. Terminal half-life (T 1/2 ) was calculated using two-phase clearance models. Log-linear regression of the concentration data including at least the last six sampling time-points with measurable concentrations.
Acknowledgements We thank  Y. Tanno  for assistance with protein expression and  M. Tichit  with immunohistochemistry assay. This work was supported by the  Clayton Foundation , by the  European Research Council (ERC) - Seventh Framework Program  ( ERC-2013-CoG 616050  to P. B. ), by the  Institut Pasteur  and the  Institut National de la Santé et de la Recherche Médicale  (INSERM). P. M. T was supported by the  National Institutes of Health  ( R01GM104130 ),  National Science Foundation  ( CBET 1804313 ) and the Albert M. Mattocks Chair. A. J. M. was supported by  NIH   DP5-OD019815. C. M. G was supported partly by a stipend from the  Pasteur-Paris University (PPU)   International PhD program  and by the  Institut Carnot Pasteur Maladies Infectieuses. D. S. benefited from a stipend (Poste d'accueil) provided by  AP-HP, Paris, France  and by the  Institut Pasteur, Paris, France.
NATURE COMMUNICATIONS | https://doi. org/10. 1038/s41467-019-13108-2 https://doi. org/10. 5281/zenodo. 3474026). Test conditions were identified throughout to ensure model accuracy. Computational modeling. All analysis was implemented in R and Stan, and can be found at [https://github. com/meyer-lab/FcRn-trafficking], release 1. 0 ARTICLE NATURE COMMUNICATIONS | (2019)10:5031 | https://doi. org/10. 1038/s41467-019-13108-2| www. nature. com/naturecommunications(.
Genetic studies The entire coding region of CD59 gene (transcript variant CD59-211 ENST00000642928. 1) was amplified by polymerase chain reaction (PCR) and Sanger sequenced on an ABI 3100 automatic sequencer (Applied Biosystems, Foster City, CA, USA). Resulting electropherograms were visually analyzed using Sequencher software (Gene Codes Corp. Ann Arbor, MI, USA). Primer pair sequences and PCR conditions are available under request. In silico evaluation of potential deleterious effects of CD59 genetic variants was performed with the CADD-score (http://cadd. gs. washington. edu/), Mutation Taster (http:// www. mutationtaster. org/), SIFT (http://sift. jcvi. org/), and Human Splicing Finder tool (http:// www. umd. be/HSF3/index. html).
Results A total of 35 patients (57% male, mean age at inclusion 61 years old) were included in the study. Direct sequencing of all coding exons of CD59 was performed. Only one variant was detected in one patient (Fig 1 ), a heterozygous guanine to alanine substitution (c. 18G>A) which resulted in the synonymous change rs111771149 (p. Gly6Gly). According to the genome aggregation database (http://gnomad. broadinstitute. org/) this is a rare variant with an allele frequency of 0. 003 in ExAC database and 0. 001899 in gnomAD database in non-Finnish Europeans. In silico analysis of possible damaging consequences did not reveal any potential deleterious effect related to this genetic variant. The previously reported pathogenic p. Cys58Tyr mutation was not present in our patient cohort.
This project was supported by  Fondo de Investigaciones Sanitarias (FIS) ,  Instituto de Salud Carlos III, Spain  and  FEDER  under grant  FIS16/ 00627 , and a personal grant to LQ  SLT006/17/ 00131  of the  Pla Estratègic de Recerca i Innovacio én Salut (PERIS)   2016-2020  of the  Departament de Salut of the Generalitat de Catalunya , pricipal investigator LQ. Competing interests: LQ has provided expert testimony for Grifols,  Genzyme  and  CSL Behring , received speaking honoraria from  Biogen Spain and Roche  and received research funds from  Grifols  ( Spin Award ) and LFB. This does not alter the authors' adherence to PLOS ONE policies on sharing data and materials.
Data Analysis Images were viewed and analyzed with MetaMorph 6. The theoretical resolvable limit of our microscope setup is R = 0. 61 λ/NA = 0. 61 × 510 nm/1. 45 ≈ 0. 22 µm, or approximately the width of 4 pixels. In practice, the width of the fluorescence signal of the linear MT structure varied between 5-8 pixels. We defined a width of 6 pixels (for interphase MTs) and 10 pixels (for the mitotic spindle) as the scan width for measuring MT intensity along its long axis. Briefly, each 3D stack was projected by the summation of all planes onto a final image containing all MTs of the cell. All MT intensities are background corrected by subtracting the cellular background intensities prior to analysis. For the spindle, intensity line scans were performed on the entire lengths of the MT structures.
Results and Discussion Genome assembly and annotation. We used a whole genome shotgun approach with Illumina technology (Hiseq2500) to sequence the genome of one male and one female at 58. 6 and 59. 8x coverage, respectively (Fig. S1 ). The DNA was extracted from fin tissues, and the libraries were produced using the Truseq DNA Nano sample preparation kit. The DISCOVAR (version 52488) assembly resulted in 52,688 scaffolds with size ranging from 138 bp to 2,146 kb for the female (average size 13 kb, N50 315 kb); for male, 60,055 scaffolds with size ranging from 192 bp to 3,323 kb (average size 12 kb, N50 285 kb). The total size of the male assembly is 666 Mb and of the female 664 Mb compared to the estimated 790 Mb from cytometric C-value measurements  17. Based on the Benchmarking Universal Single-Copy Orthologs (BUSCO) method from the vertebrate database  18  , the completeness of the male assembly is estimated to being 96.
None of the 30 sex-associated RAD-tags matched only to female-specific scaffolds (Table  S15 ). The identification of male-specific RAD-tags but no female-specific tags is compatible with an XY chromosomal sex-determination system with a reasonable molecular differentiation of the sex chromosomes. Arapaima, however, lacks heteromorphic sex chromosomes detected cytologically  33. Male-specific scaffolds lacked any annotated protein coding genes previously known to be related to sex determination or gonad development (Table  S16 ). Comparing those genes to the "potential male-specific gene" from Vialle et al. 4  , we found amdhd1 (probable imidazolonepropionase) and cd48 (CD48 antigen) to be contained in both datasets. It is interesting to note that these scaffolds are considerably different from the rest of the genome with respect to TE content (Fig.
RAD-tag sequencing and analysis of sex-specific tags. Genomic DNA was extracted from 90% ethanol-preserved fin clips using a classical phenol/chloroform protocol. The arapaima RAD-tag library was built according to standard protocols  37  , using Sbf1 as a single restriction enzyme, and sequenced on a single lane of Hiseq2500 using the v4 SR100nt mode. The resulting read file was then demultiplexed using the process_radtags. pl script of STACKS software version 1. 44  38  with default settings. Demultiplexed reads were analyzed with the denovo_map. pl STACKS script with the following settings: m = 3 (more than 3 reads are needed to build a stack of sequences), M = 0 (zero mismatch allowed when building stacks in one sample), N = 0 (zero mismatch allowed when merging stacks in the catalog),-gapped not set (gapped assembly disabled), H not set (calling haplotypes from secondary reads disabled),-max_locus_stacks = 1 (ustacks max locus per stack set to 1), and-keep_high_ cov set (ustacks lumberjack step deactivated).
Zero values for the M and N setting produce stacks of reads with no polymorphism, each resulting stacks of reads containing single allele reads or non polymorphic stacks of reads. Repeat annotation and TE analysis. The genome assembly was inspected by RepeatModeler (http:// www. repeatmasker. org/RepeatModeler, version 1. 0. 4) to generate a library of known and model a de-novo repeats (Fig. S1 ). This library, together with our in-house fish-specific repeat library, was incorporated by RepeatMasker (http://www. repeatmasker. org/RMDownload. html, version open-4. 0. 7) to annotate and mask repeat elements from the genome assembly. For TE insertion repeats, we also used RepeatLandscape (https://github. com/caballero/RepeatLandscape) to calculate Kimura distance as a measure of age, and to display a relative age profile.
Genome annotation. Genome annotation was done by combining gene evidence from homology annotation, de novo annotation and transcripts (Fig. S1 ). For homology evidence we downloaded 354,871 protein sequences from Ensembl species (Ensembl release 87) H. sapiens (human), D. rerio (zebrafish), L. chalumnae (coelacanth), P. marinus (sea lamprey), T. rubripes (torafugu), T. nigroviridis (spotted green pufferfish), G. aculeatus (three-spined stickleback), O. latipes (Japanese medaka), C. milii (elephant shark)  39  , and from S. formosus (Asian bonytongue)  9  , the closest known relative to arapaima. These sequences were then aligned to the repeat-masked genome sequence using exonerate2. 2. 0 (http://www. ebi. ac. uk/about/vertebrate-genomics/software/exonerate) and Genewise2-2-0  40  , respectively, to predict potential gene structures.
To improve the efficiency of Genewise, we also used genBlastA1. 0. 1  41  to roughly locate each protein on the genome sequence before Genewise was implemented. For gene evidence from de novo annotation, AUGUSTUS3. 2. 3  42  was used to predict genes on the repeat-masked genome sequence with 'zebrafish' as the parameter for -species flag. In parallel, we also used GeneMark-ES  43  in unsupervised training model (-ES) for the de novo prediction. For the gene evidence from transcripts, we collected RNA-seq reads from eyes, gills, spleen, lung, ovary, liver, heart, muscle and secretory field from one female and testis and secretory field from one male, and assembled the transcripts with and without the reference genome independently. Tophat and cufflinks 2. 1. 1  44  were used for the with-reference assembly.
We also used BUSCO  18  based on the vertebrata odb9 database to access the annotation completeness. To assign gene symbols, we compared those gene sequences to the UniProt database (www. uniprot. org/e) using BLAST with a criterion e-value of 1E-5 (blastp2. 2. 28+  50  ), and took the symbol of the best hit. Orthology inference. To form a protein pool, we unified 338,336 protein sequences from 12 species L. oculatus (spotted gar), O. latipes (Japanese medaka), X. maculatus (southern platyfish), O. niloticus (Nile tilapia), G. aculeatus (three-spined stickleback), T. rubripes (torafugu), G. morhua (Atlantic cod), D. rerio (zebrafish), L. chalumnae (coelacanth) (Ensembl release 87), A. anguilla (European eel) (http://www. zfgenomics. com/sub/eel), S. formosus (Asian bonytongue) and arapaima (our annotation).
The MCMC process was run for 1,500,000 steps and sampled every 150 steps. Expansion and contraction of gene families. Gene family expansion and contraction was analyzed with the program CAFE 3. 0  59  , in a maximum likelihood framework, using as input the gene group (family) size result from Hcluster_sg and the phylogenic tree from phylogenetic analysis. We instructed the program to search for the maximum likelihood value of birth and death rate (λ) following parameters "-p 0. 01 -r 10000". This means using 10,000 Monte Carlo random samplings to determine the probability of a gene family with the observed sizes and its birth and death rate, and then only of gene family with probabilities less than 0. 01 to report the birth and death rate (λ). Before inputting to the CAFE program, gene families with no homology in the SWISS-PROT database or with multiple functional annotations were removed.
To assign them into groups (α-λ), we blasted them to a database containing the sequences of 1,593 functional ORs and 59 Non-ORs  50. After discarding results with more than 40% identical matches, we assigned each query to the group with the best hit. dN/dS analysis. The dN/dS analysis was performed mainly with the CodeML program from the PAML package  57. First, for the 12,929 one-to-one orthologs between arapaima and Asian arowana, pairwise dN/dS values were calculated and those with dN/dS > 1 were kept as positively selected gene candidates. Second, for the 5,882 one-to-one orthologs among arapaima, Asian arowana and European eel, the arapaima-European eel and Asian arowana-European eel pairwise dN/dS values were calculated, respectively. We then ranked those orthologs according to value |log 2 (ω 1 /ω 2 )| (ω 1 refers to arapaima-European eel pairwise dN/dS value and ω 2 refers to Asian arowana-European eel pairwise dN/dS value, and kept the top 5% that they are showed significant difference between arapaima and Asian arowana lineages in dN/dS value.
Identification of proteins with arapaima-unique residues. Sequences were aligned and gap-removed for 6052 homologs (orthologs and paralogs) retrieved from all 12 fish species. Alignments were analyzed by an in-house Perl script to identify and score the unique arapaima amino acid residues. The unique residue score was measured according to the variance of flanking residues across species: in which p stands for the location of the unique arapaima amino acid residues in the alignment; S(p), the score; V i , the number of different residues in No. i position of the alignment; l the alignment length, thus lower flanking residue variance leading to a higher score for unique residues. Finally, the score for the sequence was determined as a synthesis of its unique residue scores normalized to protein length: = ∑ S S(p)/l, in which ∑ S(p) stands for the score sum of the unique residues it harbors; l, the alignment length.
GO enrichment analysis. Enrichment of GO terms for the genes that were selected in dN/dS analysis and identification of proteins with arapaima-unique residues was determined using the TopGO package from Bioconductor (http://www. bioconductor. org), which employs Fisher's exact test and 2 × 2 contingency tables to check for significant over-representation of GO terms in one set compared with another set. GO categories with p < 0. 05 were considered significantly enriched. Whole arapaima gene were used as background. Sex-specific sequences. To extract sex-specific scaffolds, at first, the male and female genomes were aligned one versus the other using blat (male versus female and vice versa). Then blat hits were filtered and hits having a match length greater than 100 bp, a mismatch rate (match length divided by mismatch length) lower than 3% and coverage (match length divided by query length) greater than 10% were retained.
Differential gene expression. Genes were aligned to the arapaima transcripts using Bowtie2 65 with default settings. Differentially expressed genes were detected using the Bioconductor package DESeq2 66. A gene was considered to be expressed, if at least ten reads were detected. A gene was considered to be differentially expressed for the comparison ovary vs. testis, if a gene was expressed with read counts >500 in one gonad and unexpressed in the other. For the comparison male vs. female secretory organ a gene was required to have an expression value of at least 500 in male or female and a log2FC > 4. These highly stringent criteria were chosen to account for the fact that there were no replicates. For functional enrichment analysis the web tool DAVID (https://david. ncifcrf. gov/) has been used with human as reference.
Acknowledgements This project was supported by funds from the  "Agence nationale de la recherché" (France)  and the  Deutsche Forschungsgemeinschaft (ANR/DGF ,  PhyloSex  project  2014-216 ) and the  IGB seed funding project AraAqua. This publication was funded by the  German Research Foundation (DFG)  and the  University of Wuerzburg  in the funding  programme Open Access Publishing. Du Kang  was supported by the  State Scholarship Fund from China Scholarship Council. Marcos Oliveira  and  Rafael Nóbrega  were supported by  São Paulo Research Foundation -FAPESP  (project number  2014/25313-4 ,  2014/07620-7  and  2015/15631-1 ) and  SPRINT/BAYLAT  ( 2014/50602-0 ).
Examination of stomatal pore was performed on a Zeiss Axioskop microscope equipped with Nomarski optics, AxioCam MRc5, and the Zeiss AxioVision software (Freeware 'Carl Zeiss AxioVision Rel. 4. 9. 1. 0' available in Zeiss Homepage http://www. zeiss. com/, Carl Zeiss Microscopy GmbH, 07745 Jena, Germany). In order to quantify the pore opening area in μm 2 , the outline tool of the AxioVision Software was used.
Statistical analysis Statistical analysis was performed using the STATGRAPHICS Centurion XVI software (http://www. statgraphics. com; StatPoint Technologies, Warrenton, VA). Shapiro-Wilk (W) test was used to verify the normality of the data sets. One-way Analysis of Variance (ANOVA) and Multivariate Analysis of Variance (MANOVA) were done to determine significant differences between groups of samples, and levels of significance were described by asterisks: P ≤ 0. turgor on a representative plant of the assay using the non-invasive magnetic leaf patch clamp pressure probes  (Zimmermann et al. , 2008). Patch-pressure (P p ) is inversely correlated with leaf turgor pressure and positively correlated with leaf water potential and plant transpiration  (Zimmermann et al. , 2008; Zimmermann et al.
ACKNOWLEDGEMENTS This work was supported by the  Spanish Ministry of Economy and Competitiveness-FEDER  grant  AGL2015-71386-R  and by the  Spanish National Research Council  Projects  CSIC-201540E108  and  CSIC-201740E084. Help, expertise and technical assistance of  F. J. Durán ,  C. Rivero  and  P. Benítez-Pulido  are gratefully acknowledged.
Developmental delay and intellectual disability (DD and ID) are heterogeneous phenotypes that arise in many rare monogenic disorders. Because of this rarity, developing cohorts with enough individuals to robustly identify disease-associated genes is challenging. Socialmedia platforms that facilitate data sharing among sequencing labs can help to address this challenge. Through one such tool, GeneMatcher, we identified nine DD-and/or ID-affected probands with a rare, heterozygous variant in the gene encoding the serine/ threonine-protein kinase BRSK2. All probands have a speech delay, and most present with intellectual disability, motor delay, behavioral issues, and autism. Six of the nine variants are predicted to result in loss of function, and computational modeling predicts that the remaining three missense variants are damaging to BRSK2 structure and function.
All nine variants are absent from large variant databases, and BRSK2 is, in general, relatively intolerant to protein-altering variation among humans. In all six probands for whom parents were available, the mutations were found to have arisen de novo. Five of these de novo variants were from cohorts with at least 400 sequenced probands; collectively, the cohorts span 3,429 probands, and the observed rate of de novo variation in these cohorts is significantly higher than the estimated background-mutation rate (p ¼ 2. 46 3 10 À6 ). We also find that exome sequencing provides lower coverage and appears less sensitive to rare variation in BRSK2 than does genome sequencing; this fact most likely reduces BRSK2's visibility in many clinical and research sequencing efforts. Altogether, our results implicate damaging variation in BRSK2 as a source of neurodevelopmental disease.
GeneMatcher is a database developed as part of the MatchMaker Exchange and has been shown to facilitate rare-disease-gene discovery. 10 Information about five additional affected probands who were found by research or diagnostic sequencing (Table  1 ) and who had variants likely to be deleterious in BRSK2 was independently submitted to GeneMatcher. Informed consent to publish de-identified data was obtained from all affected individuals and/or families (see Supplemental Material and Methods). Altogether, the affected probands ranged in age from 3 years and 9 months old to 19 years old and had a mean age of just under 8 years (Table  2 ). All probands described here display ID except for one. All probands present with developmental delays, including speech delay (9/9) and motor delay (7/9).
The remaining three variants were missense. All nine variants are absent from gnomAD  9  and the Bravo TOPMed database. Although gnomAD does contain variant data aggregated from several disease cohorts, there has been an effort to remove any variants found in individuals with severe pediatric disease. 9 All variants were computationally predicted to be deleterious and had Combined Annotation Dependent Depletion (CADD) scores 11 ranging from 24. 8 to 38; these scores indicate that they rank among the most highly deleterious variants possible in the human genome reference assembly, similar to most variants previously reported to cause Mendelian diseases. 11 he canonical protein encoded by the BRSK2 locus (GenBank: NP_001243556. 1, UniProt: Q8IWQ3, 736 aa) contains several domains, including a protein kinase domain (aa 19-270), a ubiquitin-associated domain (UBA; aa 297-339), a proline-rich domain (aa 424-468), and a kinase-associated domain (KA1; aa 530-653) that contains a KEN box (a degradation signal, aa 603-605) (Figure  1B ).