dataesr/scientific-paragraphs-categorization huggingface dataset:
Genetic analysis Genomic DNA was extracted from peripheral blood leukocytes using the FlexiGene DNA kit (Qiagen) following the manufacturer's protocol. DNA purity and quantity were assessed with Nanodrop spectrophotometer (Thermo Scientific). The two exons and intronic HOXA1 regions were sequenced bidirectionally to search for sequence variations. Primers were designed according to HOXA1 genomic reference sequence NM_005522. PCR products were sequenced using BigDye Terminator Cycle Sequencing kit (Applied Biosystems) and run-on automatic sequencer ABI 3130XL (Applied Biosystems). Patient sequences were aligned to the HOXA1 reference sequence using Seqscape software V5. 2 (Applied Biosystems) and validated using Sequencher V5. 4. 6 (Gene Codes Corporation). Variant pathogenicity was estimated using UMD-Predictor (http:// umd-predictor.
Detection of variants in the Histidine stretch in controls The FranceGenRef panel comprises 856 individuals from France. Whole-genome sequencing BAM files were mapped according to the Broad Institute's Best Practices. We then used a custom java tool to genotype the interval. This tool scans the BAM files in the interval and builds the DNA sequences from the CIGAR string of each read. Each DNA sequence is then reverse complemented and translated to get the amino-acid sequence. The code for this tool is available at: https://github. com/lindenb/ScanHoxa1/ (https://doi. org/10. 5281/ zenodo. 7625919).
Whole exome sequencing Genomic DNA was extracted by standard techniques. Exome sequencing was performed using the Twist Comprehensive exome (37 Mb) kit according to the manufacturer's protocol (Twist Bioscience). Pairedend 75-bp reads from the DNA libraries were sequenced using Illumina NextSeq 500 platform (Illumina). Raw fastQ files were aligned to the hg19 reference human genome (University of California Santa Cruz, UCSC) using the Maximum Exact Matches algorithm in Burrows-Wheeler Aligner (BWA) software. Alignment quality was evaluated using Qualimap 2. 2. 2. Variant calling and annotation were performed using GATK and ANNOVAR best practices, respectively. Variant annotation and exome analysis were performed with VarAFT software, version 2. 17 (http:// varaft. eu).
Generation of Hoxa1 knock-in mice line by CRISPR-Cas9 Cloning-free CRISPR-Cas9 system  70  was used to modify the polyhistidine tract in the mouse Hoxa1 gene by homologous direct repair mechanism. CRISPRdirect software (http://crispr. dbcls. jp/) was used for designing the guide RNA  71. We used 2-part guide RNA (crRNA + tracrRNA) to target the mouse Hoxa1 gene. crRNA corresponding to the target sequence (20 nucleotides) with a tail (16 nucleotides) and a tracrRNA (67 nucleotides) containing the hairpin recognized by Cas9 nuclease with an extremity complementary to the crRNA tail. Single-strand oligonucleotide containing an inserted histidine codon (CAT) was ordered as Ultramer DNA (Hoxa1 His ) and used as DNA donor template for homologous direct repair mechanism. Sequences of guide RNA and single-strand DNA oligonucleotide are shown below.
HEK293T cells were lysed with IPLS buffer (20 mM TrisHCl pH 7. 5, 120 mM NaCl, 0. 5 mM EDTA, 0. 5% NP40, 10% glycerol) supplemented with Complete™ protease inhibitor (cat: 11873580001, Roche) for 20 min under agitation on ice. Cell lysates were centrifuged 5 min at 16,000 g at 4 °C. 50 μl of each lysate was mixed to Laemmli 6×, boiled 5 min at 95 °C and run on a 10% SDS-PAGE. Western blotting was used to visualize FLAG-tagged and β-ACTIN proteins with anti-Flag (1:1,000; clone F2; cat: F1804; Sigma-Aldrich), secondary anti-mouse-IgGκ BP-HRP (1:1,000; cat: sc-516102; Santacruz), and Anti-β-Actin-Peroxidase antibody (1:5,000; clone AC-15; cat: A3854; Sigma-Aldrich). ImageJ software was used to estimate protein abundance.
Acknowledgements The authors thank  Pr. Pierre Chambon  for his authorization to use the Hoxa1 neo mouse strain. We thank  N. Eudes  for her technical help during HOXA1 sequencing. We are grateful to the  GBiM MMG Platform  and particularly to  Nicolas Lenfant  to his help in the analysis of the RNA-seq data. We thank all staff members of  MMG animal core facility  for their help in the breeding. A. F. and C. J. acknowledge the Montpellier MRI and IPAM facilities, members of the  France-BioImaging  national infrastructure supported by the  French National Research Agency  ( ANR-10-INBS-04 ,  «Investments  for the future». The FranceGenRef Consortium was supported by LABEX GENMED funded as part of " Investissement d'avenir" program  managed by  Agence Nationale pour la Recherche  (grant number  ANR-10-LABX-0013 ).
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 request. The raw data for the transcriptomic data have been deposited in the Gene Expression Omnibus database from NCBI under accession code: GSE224217. The source data underlying Figs. 2a-f, 3g, h, n, 5c, f, i, l, S3 and S8 are provided as a Source Data file. Source data are provided with this paper.
Set 1: salmonid genes induced by poly I:C belonging to a core conserved ISG set We previously identified 95 human ISGs (in 77 paralogy groups) sharing ortholog(s) with zebrafish ISGs  [27] , representing a core ISG set present in the last common ancestor of teleosts and tetrapods (LCATT) that lived ~450 Mya. This gene set comprised most of the key signalling components of the type I IFN system  [27]. Rainbow trout and Atlantic salmon (co-)orthologous genes could be found for all these core ISGs (except for gimap and pmaip): in total, 325 genes in trout and 348 genes in Atlantic salmon (Table  S4 ). Of all these salmonid genes, 303 and rainbow trout genes (in vitro and in vivo, respectively), and 305 and Atlantic salmon genes (in vitro and in vivo, respectively) were expressed in our datasets.
While these genes lacked a human ortholog, six had orthologs in other tetrapods in the Ensembl database, indicating that a subset of Set 3 genes were present in Fig. 5. Genes involved in the antiviral response of zebrafish, rainbow trout or Atlantic salmon, but lacking a human ortholog. Venn diagrams showing the intersect between zebrafish, trout and salmon lists of poly I:C induced genes with no ortholog in human and no ortholog in chicken. (A) overlap between zebrafish type I IFN induced genes, zebrafish Ensembl orthologs of rainbow trout poly I:C induced genes and zebrafish Ensembl orthologs of Atlantic salmon poly I:C induced genes. (B) Maximum likelihood tree of protein sequences of gig2 family members from zebrafish (red), rainbow trout (blue) and Atlantic salmon (green). All gig2 zebrafish paralogs were included in the analysis; those induced by IFNφ1 in Levraud et al.
Sample processing and sequencing For in vivo, head kidney tissue was homogenised with ceramic beads in a FastPrep-24 5 G tissuelyser in 1 ml of Trizol, while in vitro cells were already frozen in TRIzol (see above). Following homogenisation, total RNA was extracted from both in vivo and in vitro studies following the manufacturer instructions for a standard TRIzol total RNA extraction. Concentration and purity of the RNA was estimated using a Nanodrop 2000C Spectrophotometer, alongside further confirmation on an Agilent Bioanalyser 2100 (Agilent) to generate RNA integrity (RIN) values. Libraries were sequenced using the Illumina NovaSeq 6000 platform to generate around 30 million paired end 150 bp reads per sample. Raw reads were deposited in the European nucleotide archive (EBI) and are accessible in the FAANG data coordination centre under accession numbers (PRJEB50076 and PRJEB49984) for Atlantic salmon and rainbow trout, respectively.
Annotation of Ensembl rapid release genomes of Atlantic salmon and rainbow trout Annotation of gene models predicted in the latest Atlantic salmon (GCA_905237065. 2; [45] ) and rainbow trout (GCA_013265735. 3; [17] ) genome assemblies downloaded from the Ensembl rapid release portal (prior to release of Ensembl 106, which provided full annotations for the same gene models) was performed using a blast-based approach to generate a list of best matching hits against various databases. Proteomes from each species were retrieved and filtered to retain only the longest isoform for each gene. Each filtered protein sequence was subjected to blastp using Diamond v2. 0. 9. 147  [11]  against the Atlantic salmon and rainbow trout proteomes downloaded from previously released genome assembly versions, available on Ensembl release 104 (GCA_000233375.
Phylogenetic analyses Global phylogenetic relationships between paralogs and gene family members were analysed based on (  [27]  and references therein), and phylogenetic relationships (gene trees) available on Ensembl. For conserved ISGs, phylogenetic trees extracted from Ensembl (release 106, April 2022) were also verified using synteny-based corrected data produced by SCORPiOs  [37]. SCORPiOs reconciles species trees and sequence-based gene trees while accounting for the local syntenic landscape of paralogs stemming from WGD events. Finally, compatibility with the current annotation of rainbow trout and Atlantic salmon genomes in Ensembl release 108 was checked. Additional phylogenetic reconstruction was performed for targeted gene families (gig2, fintrim, btr, trim25). For each gene, the protein sequence of the longest isoform was used in the analysis.
Acknowledgements This work was funded by the  European Union 's  Horizon research and innovation program  under grant agreement No ( AQUAFAANG ), by  ANR  ( ANR-21-CE35-0019 , LipofishVac), by the  Eranet ICRAD-Nucnanofish  ( ANR_13001498  and  BBSRC_ICRAD BB/ V019902/1 ), by the  BBSRC   Institutional strategic programme award  ( BBS/E/D/20002174 ) and by institutional grants from  INRAE. We thank  Drs Hugues Roest Crollius ,  Camille Berthelot ,  Alexandra Louis  and  Elise Parey  for sharing synteny-based corrected data produced by SCORPiOs, and  Louis du Pasquier  for insightful discussions.
12 to 2. 5 mm  (Waters et al. , 2006; Livesey et al. , 2008). According to  Millán et al. (2022)  who used level 2 version 4 MLS data following the HTHH eruption, similar but spurious features are seen in many of the MLS retrieved species because of interference from SO 2 absorption lines  (Millán et al. , 2022). However, the quality of ozone and temperature measurements are not affected by the aerosol plume  (Millán et al. , 2022). Here, ozone concentration profiles with respect to geometric altitude were constructed with MLS level 2 version 5 ozone volume mixing ratio, temperature and geopotential profiles  (Livesey et al. , 2022). To fit with the lidar time series, this procedure was repeated for both ascending and descending nodes on each measuring day from January 2013 to December 2021.
This procedure was extended to January 2022 in order to include MLS ozone profiles recorded before and after the HTHH eruption. To calculate Stratospheric Column Ozone (SCO) data from MLS over the Indian Ocean, all available ozone concentration profiles within a 5-degree radius were averaged. In most of the stratosphere, specifically between 1 hPa and 68 hPa, ozone volume mixing ratio profiles have accuracy and precision that are both lower than 10 %  (Livesey et al. , 2022). In accordance with the recommendations made in the MLS data quality and description document, all quality flags (quality, convergence, status and precision) were used on the raw profiles, and data lying outside the recommended range (261 to 0. 001 hPa, or approximately 11 to 90 km) were not used  (Livesey et al. , 2022).
OMI data can be accessed using NASA's data portal (https://disc. gsfc. nasa. gov/, last accessed on 23 August 2023). Assimilation products have the ability to estimate atmospheric parameters with high temporal and spatial resolutions by combining observational information from multiple sources and propagating it forward in time using fundamental laws of motion. Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2), created by NASA's Global Modeling and Assimilation Office (GMAO), is such an assimilation dataset which analyses numerous atmospheric parameters from 1980 to the present  (Koster et al. , 2016; Wargan et al. , 2017). Since the launch of the Aura satellite in 2004, ozone profiles https://doi. org/10. 5194/egusphere-2023-2645 Preprint. Discussion started: 22 November 2023 c Author(s) 2023.
Aerosol measurements In addition to the DIAL system, the Reunion atmospheric observatory is equipped with several other active remote sensing systems, including a Rayleigh-Mie lidar for aerosol profile measurements  (Baron et al. , 2023). In this study we used aerosol extinction profiles together with the corresponding sAOD at 532 nm as derived from the Rayleigh-Mie lidar measurements at the Reunion observatory. The data used in this study are publicly accessible via this webpage: https://geosur. osureunion. fr/geonetwork/srv/eng/catalog. search#/metadata/f2c35798-47b7-433c-8927-46cf7babca83. The L2 ready-to-use data set in netCDF format are available through this link: https://doi. org/10. 5281/zenodo. 7790283 (last accessed on 14 September 2023). Aerosol optical properties can also be retrieved using sun-photometers.
These remote sensing sun-tracking radiometers perform regular and frequent measurements of the direct solar spectral irradiance, typically at wavelengths between 340 nm and 1640 nm. By comparing the ground solar irradiance to the estimated top of the atmosphere irradiance, they can determine the total Aerosol Optical Depth (AOD), a quantity that describes the opacity of the atmosphere to radiation. Therefore, a sunphotometer gives a measure of aerosol abundance in the atmospheric column above the study site. In the present study, we used AOD data from a Cimel sun-photometer located in Saint-Denis campus (20 km northeast of the observatory at 80 m asl), which has been operating since December 2003 in the framework of the AERONET (AErosol RObotic NETwork) program. We used version 3 level 2. 0 AERONET data for the period from December 2003 to January 2022.
With the goal to study the spatial extension of the plume, we used OMPS-LP aerosol extinction profiles at 745 nm. According to  Taha et al. (2021) , extinction coefficients at 745 nm have relative accuracy and precision of 10 % and 15 %, respectively  (Taha et al. , 2021). OMPS data were downloaded from the following link: https://ozoneaq. gsfc. nasa. gov/ (last accessed on 23 August 2023).
According to  Hoskins et al. (1985) , the EPV on isentropic surfaces behaves as a dynamical tracer when diabatic effects are absent  (Hoskins et al. , 1985). Many authors have demonstrated its utility in studying isentropic transport in the stratosphere  (Holton et al. , 1995; Bencherif et al. , 2003; Semane et al. , 2006; Bencherif et al. , 2011). EPV maps on the 600 K isentropic level were downloaded from ECMWF's data archive (MARS) using a CDS API key. EPV maps over the study area were analysed further using the DYnamical Barrier Localization (DYBAL) algorithm, which allows the localization of the subtropical barrier. The DYBAL code is a numerical tool developed at the Laboratoire de l'Atmosphère et des Cyclones (LACy, France) to detect dynamical barriers and mixing in the subtropical stratosphere  (Portafaix et al.
As a result, the profile comparison is based on the following formula:  Relative bias (z) = 100 × O 3 DIAL (z) -O 3 c (z) O 3 DIAL (z) , (1) where O 3 DIAL (z) represents the stratospheric DIAL ozone value at altitude z and O 3 c (z) represents the comparison ozone value (from MLS, MERRA-2 or M2-SCREAM) at the same altitude. Other statistical quantities were also determined, namely the number of profiles (N), the p-value, the coefficient of correlation (r), the linear regression (in the form y = ax) and the relative Root-Mean-Square Dispersion (RMSD) (see Appendix A). These statistical quantities were used to assess the differences and similarities between different ozone data in different layers. 3 Results.
MLS, MERRA-2 and ERA5 ozone profiles Comparisons of MLS and MERRA-2 profiles to DIAL observations yield similar statistical quantities and similar mean relative bias profiles. This similarity is expected as MERRA-2 incorporates MLS data into its assimilation process. Overall, the best agreements are found in the 20-40 km altitude range, with higher and increasing deviations below 20 km and above 40 km (see Table  1 ). In the altitude range from 20 km to 40 km, MLS and MERRA-2 relative bias and error yield -1. 22 ± 0. 31 % and 0. 09 ± 0. 30 %, respectively. Above 40 km, MLS (MERRA-2) results show 3. 73 ± 2. 22 % (11. 87 ± 1. 94 %). Conversely, below 20 km, one has -0. 06 ± 1. 95 % (4. 28 ± 1. 81 %). On both mean relative bias profiles, there is a negative bias that appears at ∼20 km of altitude, with -11.
73 ± 1. 60 % at 16. 70 km. ERA5, on the other hand, shows accentuated differences with the DIAL profiles, with -18. 85 ± 2. 22 % between 15 and 20 km, 0. 79 ± 0. 31 % between 20 and 40 km and 15. 54 ± 2. 02 % between 40 and 47. 5 km. Note that the relative bias of ERA5 is greater than that of MERRA-2, particularly in the troposphere and in the upper stratosphere. Correlation coefficients (r = 0. 994 for lidar-MLS and r = 0. 993 for lidar-MERRA-2) indicate a very high correlation between the lidar and both datasets, and linear regressions (y = 1. 013 x for lidar-MLS and y = 1. 024 x for lidar-MERRA-2) show that satellite and assimilation profiles tend to slightly over-estimate ozone concentrations, irrespective of the altitude. Finally, a low relative dispersion (RMSD = 7. 542 % and RMSD = 8.
Discussion The HTHH eruption on 15 January 2022 injected enormous amounts of H 2 O, aerosols, and a significant quantity of SO 2 into the tropical stratosphere. As previously mentioned in Sect. 3, the presence of SO 2 within the volcanic plume had significant impacts on OMI observations, leading to biases in total ozone measurements. This is particularly the case on 17 January (see Fig. 5 ), but anomalies as severe as -42. 13 DU (-16. 40 %) can still be found on 19 January and -29. 32 DU (-11. 11 %) on 22 January. Employing a filtering method on 308 nm residuals within OMI TCO level 2 data removes most, if not all, of the volcanic induced errors (not shown). Applying this filter on 17 January data eliminates almost entirely the ozone anomaly. The application of this filter in the following days continued to remove parts of the anomaly until 22 January.
Therefore, level 3 OMI TCO data may certainly be affected by errors induced by the volcanic aerosol plume. Additionally, because it incorporates OMI data into its assimilation process, MERRA-2 ozone fields are also expected to be influenced by OMI measurements. Since MLS did not record any anomalies on 17 January, the initial anomaly observed by MERRA-2 on that day is primarily derived from anomalous OMI data. Therefore, the ozone anomalies described in the previous section with MERRA-2 and OMI results might not have been as severe as depicted here, but their spatial localization should be accurate. Furthermore, because MERRA-2 lacked concurrent MLS profiles, the vertical structure of this anomaly was not accurately represented. Consequently, the algorithm distributed the TCO increment vertically based on the background error estimate  (Wargan et al.
, 2017). In MERRA-2, these background error standard deviations are linked to the background ozone mixing ratio, leading to the majority of the anomaly being placed around the ozone maximum in the stratosphere. However, as subsequent days unfolded, the vertical placement of the anomaly gradually evolved and became more realistic, owing to the gradual acquisition of MLS observations, which provided additional insights into its structure. This could explain why MLS and MERRA-2 data do not converge prior to 18 January in Fig. 6. The cause of the ozone anomaly can stem from multiple causes and may result from a combination of various factors. First, the low ozone levels reported in this article are likely influenced by the injection of tropospheric ozone-poor air into the stratosphere. Considering the short chemical lifetime of ozone at the altitudes where we observed ozone anomalies (∼22-28 km or 40-15 hPa), it is expected that ozone levels would have rebounded from this initial impact before reaching the western part of the Indian Ocean.
8 to 29. 7 km. The dynamics of the stratosphere responsible for the volcanic plume's advection over the Indian Ocean were studied using ERA5 EPV maps. The HYSPLIT simulation highlighted the presence of the summer's westward stratospheric flow. ERA5 EPV maps indicated that the region situated between Australia and Reunion showed no PVU discontinuity at the 600 K isentropic level during the passage of the volcanic plume. Thus, due to isentropic transport and the summer's westward stratospheric flow, the volcanic plume traveled westward and reached the Indian Ocean and Reunion within days, confirming the results of previous studies. The ozone anomaly associated with the volcanic plume was investigated using OMI, MLS, MERRA-2 and M2-SCREAM ozone data, taking advantage of the fine temporal and spatial resolution of assimilation datasets.
Acknowledgements. The authors acknowledge the  French South-African PROTEA program  and the  CNRS-NRF IRP ARSAIO   (Atmospheric Research   in Southern Africa and Indian Ocean ) project for supporting research activities, as well as the  Conseil Régional de la Réunion  for the Ph. D. scholarship of  Tristan Millet. The authors thank  NASA  for facilitating easy access and providing documentation for OMPS, MLS, OMI, MERRA-2 and M2-SCREAM data. The authors extend their thank to  ECMWF  for providing access to ERA5 data and the  NOAA-ARL  for supplying the HYSPLIT transport and dispersion model. The authors are appreciative of the  PIs  for providing data and their respective https://doi. org/10. 5194/egusphere-2023-2645 Preprint. Discussion started: 22 November 2023 c Author(s) 2023. CC BY 4.
Data availability. Reunion aerosol lidar and used in this steady are accessible from https://doi. org/10. 5281/zenodo. 7790283 (last accessed on 14 September 2023). Reunion ozone lidar measurements are available through the NDACC page (https://ndacc. larc. nasa. gov/, last accessed on 23 August 2023). OMI, MLS and MERRA-2 data can be downloaded using NASA's data portal (https://disc. gsfc. nasa. gov/, last accessed on 23 August 2023). M2-SCREAM data can be accessed using this specific link: https://disc. gsfc. nasa. gov/datasets?keywords= M2-SCREAM&page=1 (last accessed on 23 August 2023). ERA5 reanalyses can be obtained from ECMWF's Climate Data Store (https: //cds. climate. copernicus. eu/#!/home, last accessed on 23 August 2023). AERONET Version 3 Level 2 data are available through this link: https://aeronet.
Prior to obtaining results relative to ozone measurements and stratospheric dynamics, we conducted a statistical analysis to determine the most accurate dataset for describing ozone levels in the study region during unperturbed condition. Thus, we compared MLS, MERRA-2 and ERA5 ozone concentration profiles obtained over Reunion to the Reunion stratospheric DIAL ozone concentration profiles from January 2013 to December 2021. Results are presented in Fig. 4 where the continuous line and the shaded area represent the mean relative bias and the standard error, respectively. This standard error represents standard https://doi. org/10. 5194/egusphere-2023-2645 Preprint. Discussion started: 22 November 2023 c Author(s) 2023. CC BY 4. 0 License. deviation divided by the square root of the number of individual comparisons (which varies as a function of altitude).
Statistical parameters were used to for comparisons between lidar and satellite or assimilation data. Here we chose to use the correlation coefficient (r) and the Root-Mean-Square Dispersion (RMSD) to assess the differences and agreements between datasets in different layers of the atmosphere. They are based on the following equations: https://doi. org/10. 5194/egusphere-2023-2645 Preprint. Discussion started: 22 November 2023 c Author(s) 2023. CC BY 4. 0 License.