dataesr/scientific-paragraphs-categorization huggingface dataset:
F I G U R E A7 Average proportions of genus Mycobacterium in the Actinobacteria hsp65 gene amplicon sequence libraries in different caves (Rouffignac, Lascaux, Mouflon, and Reille) and different locations within Lascaux Cave (Sas-1, Passage B, Passage IP, Apse, and Diaclase). F I G U R E A8 Average proportions of genus Nocardia in the Actinobacteria hsp65 gene amplicon sequence libraries in different caves (Rouffignac, Lascaux, Mouflon, and Reille) and different locations within Lascaux Cave (Sas-1, Passage B, Passage IP, Apse, and Diaclase). T A B L E A2 Genomes of Actinobacteria reference strains from the orders Streptomycetales and Corynebacteriales retrieved from the Integrated Microbial Genome and Microbiome database and used for in silico analyses: comparison of the hsp65 and 16S rRNA gene partial sequences.
Experimental design The study was performed on the model scleractinian coral Stylophora pistillata at the Centre Scientifique de Monaco between 2014 and 2017. Three experiments were carried out in this period, in which pH was measured in the mesoglea, calicoblastic epithelium and ECM of coral microcolonies. In the first experiment corals, were analyzed in seawater at pH 8 (shown in Figure  1 ). pH data from this experiment (mesoglea, calicoblastic epithelium and ECM) have not been published previously. In the second experiment (shown in Figure  2 ) seawater was acidified to pH 7. 8, 7. 4 and 7. 2 by bubbling with CO 2. In this experiment, pH values from the mesoglea have not been published previously, but pH in the calicoblastic epithelium and ECM in the same corals were reported previously in  Venn et al.
B A FIGURE 3 The influence of seawater dissolved inorganic carbon concentration  [DIC]  and in light and darkness on the pH gradient across the calcifying epithelium of S. pistillata. (A) pH (means ± SD) in the mesoglea (MESO), seawater surrounding the corals in the perfusion chamber (SW), the extracellular calcifying medium (ECM) and the calicoblastic epithelium (CE). ECM and CE values taken from  (Comeau et al. , 2017). A linear regression is drawn for each data set to display the trend. experimental treatment for 20 min in light or darkness, before being perfused with a seawater solution of 45µM cellimpermeable SNARF-1 for a 5 min loading period in light or darkness. Perfusion continued for a further 10 min in light or darkness during which repeated pH measurements were taken in the coral and the surrounding seawater.
pH calibration Calibration of the SNARF-1 ratio to pH in the mesoglea was carried out as follows. Coral microcolonies were perfused with buffered artificial seawater (ASW) containing SNARF-1 at pH 6. 5, 7. 0, 7. 5, 8. 0 and 8. 5 (National Bureau of Standards (NBS)) for a 10 min period. ASW was made up with 490mm NaCl, 10 mM CaCl 2 , 27mM MgCl 2 , 29 mM MgSO 4 , 2 mM NaHCO 3 and 10 mM KCl in dH 2 O (Benazet-Tambutté1996) and contained 25mM Tricine or PIPES. Confocal optical sections were taken in the mesoglea in both light and darkness at each pH level to obtain the fluorescence ratio of SNARF-1 from the two emission capture channels (see above). These data were plotted against pH and a calibration curve was produced (supplementary Figure  S1 ). The mesoglea SNARF-1 fluorescence signal was related to pH by the following equation: pH = pKA -log ½R -R B =R A X F A(l2) where (F) is fluorescence intensity measured at 640 nm (l2) and the subscripts A and B represent the limiting values at the acidic and basic end points of the titration respectively (i.
| FIGHT trial The FIGHT trial was sponsored by the National Heart, Lung, and Blood Institute (NHLBI). The study protocol was approved by the institutional review board and ethics committee at each participating centre. Access to the FIGHT database was provided through NHLBI/ BioLINCC (https://biolincc. nhlbi. nih. gov/studies/hfn_fight/) with ethical approval from the Centro Hospitalar Universitário São João / Faculdade de Medicina da Universidade do Porto (process number #432/21).
77, 95% CI 0. 65-0. 91) but not in the subgroup with baseline HF (HR 0. 92, 95% CI, 0. 74-1. 15), even though the interaction was not significant (interaction P = 0. 19). 30 In all these trials, HF subgroup included patients with HFrEF and patients with HF with preserved ejection fraction (HFpEF), which may explain the differences compared to the FIGHT trial. From the RCTs with GLP-1RAs in T2D, only the EXSCEL reported LVEF and, among participants with baseline HF and documented ejection fraction, only 22% had reduced ejection fraction. 28 rthermore, some trials of GLP-1RAs versus placebo in patients with with GLP-1RAs significantly reduced hospitalizations for HF. 35 Observational data also suggest that GLP-1RAs may decrease HF events in primary prevention. 36 The improvement of metabolic control and the prevention of coronary atherosclerotic disease with GLP-1RAs may explain the primary prevention of HF development in T2D.
Digestion took place at 75 °C for 2 h and then at 65 °C for 20 min for enzyme inactivation. The ligation reaction was completed in the same plate as the digestion, using T4 DNA ligase enzyme (New England Biolabs, Hitchin, UK) at 22 °C for 1 h. Then, the ligase was inactivated prior to pooling the samples by holding it at 65 °C for 20 min. For each library, ligated samples were pooled and PCRamplified in a single tube. Genome complexity was reduced using PCR primers with one selective base (A) as described by Sonah et al. [61]. Single-end sequencing was performed on a single lane of an Illumina HiSeq4000 at the Genoscope facilities (Paris, France). RAW sequencing data were cleaned with cutadapt  [62]  and demultiplexed with GBSX  [63]. SNP genotype calling was then performed with the VCF-Hunter 2.
1. 0 pipeline (https://github. com/SouthGreenPlatform/VcfHunter; accessed on 28 July 2021) as described in Baurens et al. [64] , using the Poncirus trifoliata v1. 3   [65]  and chloroplast  [66]  reference genomes. Positions with less than 10 reads were considered to be missing data. Polymorphic positions were filtered for diallelic SNPs and minor allele frequency greater than 0. 05. Clean demultiplexed sequencing data are available in the NCBI SRA (Sequence Read Archive), under accession number PRJNA648274 for Citrumello 4475 already published in Calvez et al. [67] , and PRJNA794128 for the 34 others genotypes newly sequenced in the present study.
Genetic Analysis Cytoplasmic genomes of parental lines and somatic hybrids were compared by neighbor-joining analysis on a dissimilarity matrix using DARwin software version 6. 0 (https://darwin. cirad. fr/; accessed on 28 July 2021). A factorial analysis on the dissimilarity matrix was performed for the nuclear genome with the same software. Both analyses were based on the Manhattan dissimilarity index: 𝐷 1 𝐾 |𝑥 𝑥 | where i and j are the two individuals, k is the locus, K is the total number of loci, and xik is the frequency of the alternative allele at locus k for the individual i. For the factorial analysis of the nuclear genome, polyploid plants were treated as the diploid ones by differentiating homozygous for reference or alternative alleles and heterozygous, but without taking into account the allelic doses at heterozygous sites.
For accession with known introgressed areas (particularly mandarins introgressed by fragments of the C. maxima genome and Chandler pummelo by a small C. reticulata fragment  [68, 69] ), we removed the data of the considered region/variety from the analysis, as described by Oueslati et al. [69]  and Ahmed et al. [70]. TraceAncestor software was then used to analyze the contribution of the three species all along the nuclear genome of the 35 accessions analyzed, following the method described by Ahmed et al. [70].
SNP Mining After genotype calling on the P. trifoliata reference genome and filtering for diallelic SNPs with less than 25% of missing data and minimum allele frequency of 0. 05, we obtained 109,406 SNPs. These were used to search for diagnostic SNPs from the three ancestral genomes involved in our material. An additional filtering for no missing data was performed for the analysis of genetic diversity organization by factorial analysis and delivered 46,826 SNPs.
| Sampling and genomic data production Needles from 25 mature, emergent individuals (i. e. , trees with crown reaching or above the canopy), located at least 20 m apart, were sampled in each stand. Methods M1 (in the Supporting Information) provide details on DNA isolation. DNA samples were submitted to sequence capture using a subset of the sequence capture probes designed for Pinus taeda by RapidGenomics (Table  T1.
| Diversity analyses Diversity was assessed by computing Nei's molecular diversity π  (Nei, 1987)  per contig, taking into account both variant and invariant sites in each contig, within each stand. Calculations were carried out in R with a custom script (Methods M2). Within-stand observed and expected heterozygosity and heterozygote excess/deficit were computed with the basic. Stats() function, and hierarchical F-statistics was computed using the pairwise. WCfst() function, both from the R package hierfstat  (De Meeûs & Goudet, 2007; Goudet, 2005) , which implements the hierarchical framework developed by  Yang (1998) , using all loci.
e. , the probability density distribution for Φ SC for a random locus) we randomly sampled 50,000 Φ SC values from all loci from all steps of the Markov chain produced by bamova (after discarding the burn-in), and computed the probability density distribution from this set of values. We then computed the position of the distribution's mode and proceeded with points (i) to (iii) described above. We considered loci with BF > 30 (corresponding to the middle of the "strong" evidence class in  Kass & Raftery, 1995)  as outliers. The second method used for the detection of F ST outliers is implemented in the R package pcadapt version 4. 3. 3 (Luu et al. , 2017). It ascertains population structure using principal component analysis (PCA) and computes associations between principal components (PCs) and locus variation for each SNP.
The rationale behind pcadapt is that loci under divergent selection present an atypical association with PCs. In this study, we used the first version of pcadapt (version 1. 0;  Duforet-Frebourg et al. , 2014). To run pcadapt, missing data were first imputed. Then, the number of PCs to be retained (K) was chosen by running a PCA with a large number of PCs (15 in our case). The best K was chosen based on the rate of decrease in the cumulative variance explained by each PC (i. e. , the scree plot). This choice was confirmed by plotting individuals on the first two PCs (i. e. , the score plot). After these preliminary steps, PCA was run setting the number of PCs to the optimal K value. Alleles with minor allele frequency (MAF) <5% were removed from the analysis. The communality statistic was used to detect outlier SNPs.
An FDR of 0. 05 was applied to avoid false positives, by using the R package qvalue  (Storey et al. , 2015). Overlap of lists of outliers obtained with the two methods was visualized using the R package upsetR version 1. 4. 0  (Conway et al. , 2017). The trends in allele frequencies at outlier SNPs were compared between same-species sites, to check whether they were consistent among sites; that is, we checked whether, when the frequency of an allele increased (or decreased) from one environmental level to the other between the two stands of a site, it also increased (or decreased) between the two same levels at the other site or sites; changes in the same direction are interpreted as suggestive of selection operating the same way at all sites. To estimate the Type I and Type II error rates in outlier detection, we used the quantinemo software  (Neuenschwander et al.
We used the results both to identify the numbers of probes having retrieved sequences in each species and to identify orthologous contigs in pairs of species. From the whole data set of the annotated genes, enrichment among the annotated outliers was performed using the R package TOPGO version 2. 36. 0  (Alexa & Rahnenfuhrer, 2019 ). The parentchild algorithm, which takes into account the hierarchical relationship between Gene Ontology (GO) terms, was used with a node size of 10. The result of the GO enrichment analysis was used for semantic clustering using revigo (http://revigo. irb. hr/) with default settings in order to identify nonredundant subsets of GO terms  (Supek et al. , 2011). The hierarchical data obtained were plotted using the CirGO package  (Kuznetsova et al. , 2019) , which allowed a better representation of the GO term categories and subcategories.
| Annotation Orthology among contigs of different species was tested by matching their sequences to P. taeda probe sequences by blast. In total, 4367 probes (out of 13,535) correctly matched at least one contig for A. alba, 5130 for C. atlantica, 6597 for P. halepensis and 5558 for P. pinaster (Table  T1 ). The fact that more probes retrieved sequences in pines than in nonpine species suggests that there is some identification bias, with probes from P. taeda more easily capturing DNA fragments from closely related pine species. In this view, probes that captured DNA fragments in nonpine species would correspond to more conserved genes, with the consequence that nonpine data would be enriched for conserved regions relative to pine data, thus introducing a bias. To test whether probes capturing fragments in nonpines corresponded to more conserved, and therefore less polymorphic, DNA fragments, we proceeded as follows.
3. 5 | AnnotationA blastx search was performed between the consensus sequences of each species and a protein database made from the P. taeda transcriptome version 1. 01 (https://piner efseq. facul ty. ucdav is. edu/), the NCBI plant ref_seq (release of June 2017) and the Uniprot/Swissprot (release of July 2017). Only the best hit was conserved for the annotation using interproscan version 5. 25 and the HAMAP, PFAM, PIRSF, PRINTS, PRODOM, PROSITEPATTEN, PROSITEPROFILE and TIGRFAM databases. Only the annotation with the highest e-value was reported. The blastx output was converted to gff format using the script blast_to_gff. py available at https://github. com/alvar almst edt/py_scrip ts/blob/maste r/blast_to_gff. py. The gff containing the open reading frame (ORF) and the delimitation of the coding DNA sequences (CDS) was used to identify the functional significance of.
Funding information Agence Nationale de la Recherche , Grant/ Award Number:  FLAG  project ( ANR-12-ADAP-0007-01 );  European Commission , Grant/Award Number:  TOPWOOD  project ( MSCA-RISE-2014-645654-TOPWOOD ) and grant agreement No. 676876  (GenTree);  Ministère de l'Écologie, du Développement Durable et de l'Énergie , Grant/Award Number:  GRAAL  project ( 10-MCGOT-GICC-8-CVS-139 ).
2. 3. 5 | AnnotationA blastx search was performed between the consensus sequences of each species and a protein database made from the P. taeda transcriptome version 1. 01 (https://piner efseq. facul ty. ucdav is. edu/), the NCBI plant ref_seq (release of June 2017) and the Uniprot/Swissprot (release of July 2017). Only the best hit was conserved for the annotation using interproscan version 5. 25 and the HAMAP, PFAM, PIRSF, PRINTS, PRODOM, PROSITEPATTEN, PROSITEPROFILE and TIGRFAM databases. Only the annotation with the highest e-value was reported. The blastx output was converted to gff format using the script blast_to_gff. py available at https://github. com/alvar almst edt/py_scrip ts/blob/maste r/blast_to_gff. py. The gff containing the open reading frame (ORF) and the delimitation of the coding DNA sequences (CDS) was used to identify the functional significance of.
Immunohistochemistry. Fetuses sections were rehydrated in PBS before antigene retrieval treatment in a pH6 citrate buffer solution at 95 °C for 15 min followed by 20 min cooling. They were permeabilized and blocked in PBS with 0. 5% triton X100 and 10% normal goat serum for 3 h at room temperature. Primary and secondary antibodies were diluted in the blocking solution and incubated on the sections at room temperature overnight and 1 h respectively. Immuno-stained sections were mounted under a coverslip with Mowiol fluorescent mounting medium before imaging. Images were taken on an Olympus BX63 upright fluormicroscope, or on a Yokogawa CSU X1 Spinning Disk coupled with a DMI6000B Leica inverted microscope and acquisitions were made with an ORCA-Flash4. 0 LT Hamamatsu camera or a CoolSnapHQ2 camera (Photometrics) respectively, with Metamorph 7 software.
Sections were further washed three times 5 min and mounted with mowiol solution and a glass coverslip. Images were collected with an Olympus BX63F microscope and a Hamamatsu ORCA-Flash 4. 0 camera. Images were analyzed with ImageJ program. The references of the antibodies used are listed in Table  S1. RNA extraction and quantification. RNA extractions from adult skeletal muscles were performed using TRIzol reagent (ThermoFischer) following the manufacturer's protocol. Muscles were lysed with Tissue lyser (Quiagen) in TRIzol solution. RNA was precipitated with isopropanol. cDNA synthesis was performed with Superscript III kit (Invitrogen) using 1 µg of RNA. RT-qPCR were performed using Light Cycler 480 (Roche) with the Light Cycler 480 SYBR Green I Master Kit (Roche) following the manufacturer's protocol with 40 cycles at 95 °C for 15 s, 60 °C for 15 s, and 72 °C for 15 s.
Libraries were then sequenced by pair with a HighOutput flowcel using an Illumina Nextseq 500. Single-nucleus ATAC-seq analysis. A minimum of 10 000 reads per nucleus were sequenced and analyzed with Cell Ranger Single Cell Software Suite 3. 0. 2 by 10X Genomics. Raw base call files from the Nextseq 500 were demultiplexed with the cellranger-atac mkfastq pipeline into library-specific FASTQ files. The FASTQ files for each library were then processed independently with the cellranger count pipeline. This pipeline used STAR21 to align reads to the Mus musculus genome. Once aligned, barcodes associated with these reads -cell identifiers and Unique Molecular Identifiers (UMIs), underwent filtering and correction. The subsequent visualizations, clustering and differential expression tests were performed in R (v 3.
4. 3) using Seurat36 (v3. 0. 2)  82  , Signac (v0. 2. 4) (https://github. com/timoast/signac) and Chromvar (v1. 1. 1)  83. Quality control on aligned and counted reads was performed keeping cells with peak_region_fragments >3000 reads and <100,000, pct reads in peaks >15, blacklist ratio <0. 025, nucleosome_signal <10 and TSS. enrichment >2. We get 6037 nuclei in total and we detected 132,966 peaks. The pseudo-bulk accessibility tracks of the fMyh locus were generated with the coverage plots function of Signac. The myonuclei expressing the different isoforms of Myh were classified according to the opening of the chromatin at the level of the promoters of the different genes of Myh. The number of nuclei used for this analysis was 64 for Myh7, 59 for Myh2, 249 for Myh1, and 495 for Myh4. Singlenucleus ATAC-seq tracks were visualized using IGV software version 2.
3. 70. ChIP-seq analysis. Fastq files of quadriceps femoris and soleus H3K27ac ChIPseq  25  were download from the GEO database (accession number GSE123879). Fastq files of quadriceps femoris Mll4 ChIP-seq  26  (accession number GSE137285) were download from the GEO database. Fastq files of CTCF ChIP-seq  84  (accession number GSE138994) were download from the GEO database. The reads were aligned to the mouse mm10 genome using bowtie2  85  and peaks were called by MACS2  86  using q value cutoff = 0. 05. ROSE algorithm  14  was applied to identify and rank the enhancers based on H3K27ac ChIP-seq signal, with a stitching distance of 12. 5 kb. Chip-seq tracks were visualized using IGV software version 2. 3. 70. Nuclei purification from adult skeletal muscle for 4C-seq. Nuclei purification from adult skeletal muscle has been performed as previously described  87  with some modifications.
The nuclear pellet was resuspended in 5 ml of hypotonic buffer and filtered with 70 µm and 40 µm cells strainers. The nuclei were pelleted with centrifugation at 1000×g for 10 min, snap frozen into liquid nitrogen and stored at -80 °C. 4C-seq. 4C-seq experiments have been performed as previously described  88  with some modifications. Purified crosslinked nuclei from 160 soleus and 80 quadriceps were pooled together to have 10 7 nuclei per condition. PCR primers were designed for each viewpoint according to the protocol. The first digestion was done with DpnII (New England Biolabs) and the second with NlaIII (New England Biolabs). For each viewpoint 800 ng of 4C template was amplified by PCR. The samples were sequenced on the Illumina NextSeq 500 platform, using 75 bp single end reads. The analysis of the data has been done using the HTSstation 4C-seq pipeline  89.
Hi-C data in mouse ES cells were obtained from the 3D Genome Browser website (http://promoter. bx. psu. edu/hi-c/view. php). ChIP-seq data against CTCF in mouse ES cells and DNase I hypersensitive site in adult fast skeletal muscle were obtained from the ENCODE database. The sequences of the oligonucleotides used for 4C-seq are listed in Table  S3. Mouse generation by CRISPR/Cas9. SgRNA and Cas9 purified protein were produced by the TACGENE platform. The SgRNA was designed with the Crispor program (http://crispor. tefor. net/)  92. SgRNA is produced by T7 Hiscribe transcription kit (New England Biolabs) and purified by EZNA microelute RNA clean up kit (Omega biotek). The DNA used for transcription was produced by overlapping PCR. For each cut sites, 3 different sgRNA were designed and tested in vitro by transfection in MEF cells.
Slides were then proceeded according to the manufacturer's protocol: ethanol dehydration, 10 min of H2O2 treatment and 30 min of protease IV treatment. After hybridization and revelation, the fibers were mounted under a glass coverslip with Prolong Gold Antifade Mountant (Thermofischer). Myofibers were imaged with a Leica DMI6000 confocal microscope composed by an Okogawa CSU-X1M1 disk and a CoolSnap HQ2 Photometrics camera. Images were analyzed with Fiji Cell counter program. Statistical analysis. The graphs represent mean values ±SEM. Significant differences between mean values were evaluated using two-way ANOVA for Fig. 2H , one-way ANOVA with multiple comparisons for Figs. 3D, 4E , and 5C-E, and Sup 8E and 9F-H and Student's t test for Figs. 1B and 2K with Graphpad 8. 4. 3 software. Immunostaining and FISH experiments were repeated 3 times independently with similar results.
Acknowledgements We thank  D. Duboule ,  S. Schiaffino ,  H. Amthor ,  M. Schuelke ,  E. Bloch-Gallego , and  F. Spitz  for helpful discussions. We thank  U. Schibler ,  S. Gautron , and  F. Britto  for helpful critical reading of the manuscript. We thank  T. Guilbert  and  F. Letourneur  at the  Cochin IMAG'IC  and GENOM'IC platform for helpful advice. We acknowledge the Highthroughput sequencing facility of the  I2BC (Gif-sur-Yvette, France)  for its sequencing and bioinformatics expertize. M. D. S was supported successively by a PhD fellowship from the  Association Française contre les Myopathies (AFM) , by a post doc fellowship from  EUR-Gene  and from the  Agence Nationale pour la Recherche (ANR MYOLINC). Financial support to this work was provided by the  AFM  (no. 16427 ,  21711 , and  23012 ), the  ANR  ( Myocodes -09-BLAN-0280-01  and  MYOLINC -16-CE14-0032-01 ), the  Institut National de la Santé et de la Recherche Médicale (INSERM) , and the  Centre National de la Recherche Scientifique (CNRS)  to P.
Data availability The authors declare that all data supporting the findings of this study are available within the article and its supplementary information files or from the corresponding author upon reasonable request. All 4C-seq data are available in the NCBI Gene Expression Omnibus (GEO) database under accession number "GSE168074". All snATAC-seq data are available in the NCBI Gene Expression Omnibus (GEO) database under accession number "GSE150065". Source data are provided with this paper.