dataesr/scientific-paragraphs-categorization huggingface dataset:
MA plot The MA plots were generated based on the DESeq2 (see above) results with the ggmaplot function (https://rpkgs. datanovia. com/ ggpubr/reference/ggmaplot. html) from the R package ggpubr (https://rpkgs. datanovia. com/ggpubr/). 107 Genes are indicated by dots, plotted by their log 2 fold change between RFe bat fibroblast and RFe pluripotent stem cells and the log 2 mean of normalized counts (ratio of means). Blue dots indicate genes with an adjusted p value of (or FDR) of <0. 05 and a fold change of 2 (log 2 fold change of 1), red dots indicate genes with an adjusted p value (or FDR) of <0. 05 and fold change of -2 (log 2 fold change of -1). Dotted lines are drawn at fold change of 2/-2 (log 2 fold change of 1/-1).
75 bp single-end sequencing reads (SE75) were generated by Illumina sequencing (using NextSeq 500) to a depth of at least 27 million reads (total of 54 million reads), with at least 2. 9 million covered CpGs. The reads were mapped to the GCA_004115265. 2 genome (Ensembl, annotation version 102) and the percentage of methylation at CpG sites across the genome was calculated. To visualize the methylation ratios aligned to the gnome with the UCSC genome browser, the methylation ratio files containing the methylation ratio for each chromosomal position were first converted to bed files, that were then used to generate bigwig files with the ''bedGraphToBigWig v4 tool'' (https://www. encodeproject. org/software/bedgraph tobigwig/). 109 Correlation scatter plots were generated to show the level of methylation at common CpG sites.
Principal component analysis (PCA) The DESeq2 output files of the RNA-seq analyses described above were subjected to a Variance Stabilizing Transformation (VST) using within-group-variability  122  to compare the RFe bat pluripotent stem cell transcriptional profile with that of other species. The first two principal components of this result were plotted using the ggscatter function (https://rpkgs. datanovia. com/ggpubr/ reference/ ggscatter. html) from the R package ggpubr (https://cran. r-project. org/web/packages/ggpubr/index. html),  107 and the weight of each gene's contribution to the principal components were extracted for PC1 and PC2. The datasets used in the PCA were: GSM4616525, GSM4616526, GSM4616527 (dog iPS), GSM4617887, GSM4617889, GSM4617890, GSM4617891, GSM46 17895, GSM4617900, GSM4617901 (marmoset iPS), GSM4616532 (human iPS), GSM4616535, GSM4616536 (pigiPS) from study GSE152493,  95  GSM1287734, GSM1287735, GSM1287745, GSM1287746 (mouse ESC), GSM1287736, GSM1287747, GSM128 7748 (mouse iPS), GSM1287749, GSM1287750 (mouse fibroblasts, MEF) from GSE53212,  96  and GSM4303994, GSM4303995 (human naı ¨ve ES), GSM4304018, GSM4304019 (human primed ES) from GSE144994.
Protein interaction network analysis The genes of the Corona virus disease related KEGG pathway were retrieved from the PathCards database (https://pathcards. genecards. org). The differential expression analysis was performed between RFe bat (this study) and mouse iPS cells (GSM1287736, GSM1287747 and GSM1287748 from Study GSE53212  95  using DESeq2. 105 The Corona virus disease-related genes were then illustrated with Cytoscape (Version 3. 8. 2)  111  using the STRING protein query with a 0. 8 confidence score cutoff. The nodes were colored based on the log 2 Fold-change with a negative (blue) fold change indicating down-regulation and a positive (red) fold change indicating upregulation in bat pluripotent stem cells. Bold borders indicate proteins that were present in the top 5% of PC1 in the PCA analysis described above.
The RFe cells were washed as before resuspended in 0. 5% BSA/PBS containing two drops/ml DyeCycle Violet to stain the nuclei. Imaging was conducted with the ImageStream MkII, at 60x magnification with the extended depth of field mode for probe resolution. Images were acquired using the INSPIRE 2. 0 software at the lowest flow speed. Fluorophores were excited by the 405 nm and 568 nm lasers at 60 mW and 100 mW, respectively. RFe cells in focus were gated via histogram of brightfield gradient R. M. S. values and an aspect ratio vs. area plot was used to select the population of single cells. 5000 individual images of focused single cells were taken. Gating was refined further post-acquisition via the IDEAS 6. 2 software suite by the same methods and plots, yielding n=1846 (BiPS). This software was used also for image processing, in which a set of custom masks defined by logical operators were used to denote vesicles and sensitively assess probes.
For vesicles, it was observed that they may be selected from other cell component by contrast (bright and dark) and also by aspect ratio, and therefore are defined here by ''Dilate(Range(Dilate(Range(System(Peak. (Threshold(M01, BF, 70), BF, Bright, 1), BF, 20), 0-5000, 0. 4-1), 1), 0-5000, 0. 4-1), 1) Or Range (AdaptiveErode(Level Set(M01, BF, Dim, 5), BF, 75), 0-5000, 0. 5-1). '' BF and BF2 represent each brightfield image taken of a single cell from each of the two cameras, M01 and M09 represent the corresponding channel masks for each channel and the remaining terms represent mask modifiers and their associated values in the IDEAS software. For resolving immunofluorescence, ''Peak(System(M05, Ch05, 3), Ch05, Bright, 1)'' where Ch05 represents the staining of interest and M05 represents the corresponding channel mask.
Next, overhang SMRTbell adapters were ligated onto each template and purified using 0. 6X AMPure PB beads to remove small fragments and excess reagents (Pacific Biosciences). The completed SMRTbell libraries were further treated with the SMRTbell Enzyme Clean Up Kit to remove unligated templates. The final libraries were then annealed to sequencing primer v4 and bound to sequencing polymerase 2. 0 before being sequenced on one SMRTcell 8M on the Sequel II system with a 24-hour movie each. After data collection, the raw sequencing subreads were imported to the SMRTLink analysis suite, version 10. 1 for processing. Intramolecular error correcting was performed using the circular consensus sequencing (CCS) algorithm to produce highly accurate (>Q10) CCS reads, each requiring a minimum of 3 polymerase passes.
Identification and illustration of viral sequences in the bat pluripotent stem cell transcriptome The existence of viruses in the Rhinolophus ferrumequinum transcriptome was explored by analysing the RNA-seq and Iso-seq data based on a metagenomic approach using Kraken2 v2. 1. 2  112 First, the adaptors in the RNA-seq data were removed with Trimgalore v0. 6. 7  114  and all replicates for corresponding datasets were joined in one file. The reference library ''RefSeq complete viral genomes / proteins'' was downloaded and a custom database was built to identify matches within the processed RNA-seq or Iso-seq. To eliminate false positive hits that could be due to matches with any cellular transcript such as oncogenes that are carried by some viruses, a second analysis was performed after eliminating all reads from the RNA-seq and Iso-seq datasets that matched any annotated Rhinolophus ferrumequinum transcript.
To do this, the Iso-Seq FLNC isoforms or RNA-seq trimmed fastq sequences were first mapped to the ''Rhinolophus ferrumequinum genomic rna exons RefSeq'' file ''GCF_004115265. 1_mRhiFer1_v1. p_rna_from_genomic. fna'' using gmap/gsnap. 113 The sequences with no mappings were then used to identify viral sequences using Kraken2 as before. In a first approximation, we mapped the sequencing reads against a virus database, using a metagenomic classification tool (Kraken2). The results revealed a taxonomically highly diverse ''zoo'' of assigned viruses belonging to several major viral families. We also classified viral sequences using RNA-seq data from BEFs (Table  S5B ) and from human ES cells (Table  S5C ) notably yielding some viral sequences albeit to a lesser degree (Figure  S11A ). This observation in BEFs was surprising as post-implantation tissues typically do not exhibit endogenous viral activity,  50  underscoring the notion that bat cells harbor pro-viral environments.
When the Kraken2 database was expanded to include bacteria, archaea, and the whole human genome, the yield was only 0. 65 percent, compared to 2. 53 percent when the viral database was probed (Figure  S11B ). Finally, we checked if some of the classified sequences were of murine origin and found that this was the case for several retroviruses, and for example, the sequences classified as Diatom colony associated ssRNA virus 1. The latter matched a genomic region on mouse chromosome chr9: 65,969,137-65,969,198 (GRCmm39/mm39). In addition to Kraken2, we also processed sequences through the Microsoft Premonition metagenomics pipeline (http://microsoft. com/premonition), which uses an alignment-based approach (cf Kraken2's k-mer based method) to identify matches, in addition to employing a larger reference database, factors which can increase sensitivity/reduce false negatives.
Mapping of RNA-seq reads to bat genomes and quantifying expression of ERVs To trim adapters and generate quality metrics of the fastq files, we used Trimmgalore v. 0. 6. 6 (https://github. com/FelixKrueger/Trim-Galore), a wrapper for Cutadapt (https://github. com/marcelm/cutadapt) and FastQC (https://www. bioinformatics. babraham. ac. uk/ projects/fastqc/). Then, reads were mapped to the genome of R. ferrumequinum and M. myotis (Bat1K assembly HLrhiFer5) using HISAT2 v. 2. 2  101  suppressing unpaired alignments for paired reads (-no-mixed), suppressing discordant alignments for paired reads (-no-discordant), and setting a function for the maximum number of ambiguous characters per read (-n-ceil L,0,0. 05). Output files were then filtered to remove any unmapped reads (-F 4), sorted and indexed using samtools.
102 Aligned reads were then assembled into transcripts using stringTie v2. 2. 1  115  in stranded mode (-rf). To generate a Ballgown readable expression output with normalized expression units of fragments per kilobase of transcript per million mapped fragments (FPKMs), we also used as input in strigTie the Bat1K annotation of known endogenous retroviruses (ERVs) for R. ferrumequinum and M. myotis (https://genome. senckenberg. de/). 25 Output counts were post-process and plotted with a custom R script.
De novo assembly of potential virus-derived RNA-seq The trimmed reads that were identified by Kraken2 v2. 1. 2 to map to viral sequences with a confidence score of 0 as described above were first grouped together based on their taxonomic ID assigned by Kraken and then classified as either mammalian or nonmammalian using the VIRION database. 123 The data were converted to FASTA format using the Seqtk v1. 3 program and the reads were assembled using the Trinity v2. 12 software. 116 To check and gather successful assemblies that had produced at least one contig, a custom BASH script was applied for both groups of mammalian and non-mammalian viruses.
Mapping transcripts to viral and mammalian databases To determine if the assembled transcripts represented an expressed viral sequence, all transcripts were mapped to a database of viral genomes using BLAST. 117, 118 The viral database consisted of genomes whose host species contained either 'human' or 'vertebrate' as specified in the NCBI database. Initially this list contained over 17,000 genomes. However, this was reduced to 3,922 genomes by taking only unique virus/strain names. An additional non-mammalian virus database was generated by combining all genomic sequences of viruses identified by Kraken2 and classified as non-mammalian via VIRION. Transcripts were also mapped to a combined database of RFe bat, human and mouse genomes to both confirm their presence in the bat and to exclude the possibility of false positives through contamination.
For each of these transcripts, expected values for both bat and viral genome BLAST results were combined into a single metric via the following formula: Log (bat-expected value+1 x virus-expected value+1). A threshold of less than 0. 3, representing a combined e-value of less than 1e -50 for both viral and bat hits, was used to rule out potential false positives. In addition, we used SQUID (http://eddylab. org/software. html) to shuffle the 63 (bottom-up) and 82 (top-down) sequences while preserving the dinucleotide distribution (parameter -d) to obtain a conservative threshold to distinguish bona fide viral homology from matches by random chance. Shuffled sequences were mapped to both the bat genome and viral genome databases, with the same BLAST threshold applied. All transcripts passing this threshold were extended by 5000 bp flanks within the bat genome and these regions were subsequently mapped to the viral database to confirm their presence in a viral genome.
S5  and S6  RNA-seq reads were first classified using Kraken2 (left). The classified reads were then either analyzed directly or separated by their homology to a mammalian or a non-mammalian virus using virion. In a 'bottom-up' approach (red boxes), the reads that were classified to belong to the same virus were assembled de novo and blasted against databases containing all viruses (AVDB), mammalian viruses (MVDB) or non-mammalian viruses (NMVDB). The identified sequences with viral hits were then further mapped to the R. ferrumequinum (RhiFer) genome (gVH) and in a final step, reads/assemblies that did map to the genome were extended by 5 kb on both sides and the sequences again blasted against the databases as before to extend the search for viral hits in flanking genomic regions (fgVH).
In a parallel 'top-down' approach (blue boxes), the Kraken2 reads were mapped directly to the R. ferrumequinum genome, micro-assemblies were generated based on the mapped reads, and blasted directly against the different databases as before or first extended by 5 kb on both sides. In an orthogonal approach, the reads were similarly assigned to viruses using the Microsoft Premonition metagenomics pipeline (right). First all reads were classified as aligning to a virus or as being unaligned, micro-assemblies were generated and mapped to viral genomes (red box). Consensus sequences were extracted and blasted against the R. ferrumequinum genome, extended by 5 kb and blasted against a database containing all viruses as before. In another 'top-down' approach (blue box), the Premonition classified reads were mapped to the R.
ferrumequinum genome first, and micro-assemblies generated that were blasted against the 'All virus' database either directly or after being extended by 5 kb on both sides. AVDB, all viruses database; MVDB, mammalian virus database; NMVDB, nonmammalian virus database; VH, viral hits; gVH, viral hits with homology to the bat genome; fgVH, viral hits using flanked genomic regions; RhiFer, Rhinolophus ferrumequinum; kb, kilobase pairs.
All high-throughput sequencing data have been deposited at GEO and are publicly available as of the date of publication. Accession numbers are listed in the key resources table. d This paper analyzes existing, publicly available data. These accession numbers for the datasets are listed in the key resources table. d This paper does not report any original code. d All software packages and their accessibility are described in the STAR Methods sections. d Any additional information required to reanalyze the data reported in this paper (including the BLAST results related to Figures S5-.
ACKNOWLEDGMENTS We thank  Prof. Eloy Revilla Ebd-CSIC 's director, the  EBD-CSIC's Bio-Ethical Committee , the  CABIMER , the  Consejerı ´a de Medio-Ambiente of the Junta de Andalucı ´a  and the  Subdireccion General de Acuerdos Sanitarios y Control en Frontera of the Spanish Ministry of Agricultura ,  Pesca y Alimentacion , for their support and help in obtaining the export permits in record time and many other people for making the shipment and delivery of the Rhinolophus samples from  Seville, Spain , to  New York, USA , under the  COVID-19 pandemic 's most arduous conditions possible. We thank the members of  Bretagne Vivante , local volunteers, and students from  University College Dublin  for their help in sample collection and the owners/local authorities for allowing access to the sites to collect Myotis samples in France.
G. M. H. is funded by a  University College Dublin  Ad Astra Fellowship. M. D. and T. P. Z. are supported by the  Huffington Foundation. T. P. Z. is supported by  NIH   GM129329  and  HD100518. A. G. S. is supported by  HR0011-19-2-0020 , awarded by  DARPA , and grant No. W81XWH-20-1-0270 , awarded by the  Department of Defense(DoD). This work was also partially supported by  NIAID  grant  U19AI135972  and by  CRIPT (Center for Research on Influenza Pathogenesis and Response) , a  NIAID-supported Center of Excellence for Influenza Research and Response (CEIRR , contract # 75N93019R00028 ) to A. G. S. and by grant  2021-244135(5384 ) from the  Open Philanthropy Project Fund  to A. G. S. and T. P. Z. , while J. J. and C. I. are supported by the  Spanish Ministerio de Ciencia e Innovacion  ( SAF2017-89355-P ).
0 Prolong Dimond antifade mounting medium Synthesis & Amplification Module NEBNext Single Cell/Low Input cDNA R&D Systems Abcam Sigma Aldrich R&D Systems Promega Becton Dickinson Qiagen Invitrogen PacBio Invitrogen New England Biolabs AF1979; RRID:AB_2157172 ab150404; RRID:AB_2868423 HPA023881; RID:AB_1857931 AF5726; RRID:AB_2202564 M7123 80204 BDB554714 100-938-900 R37606 P36965 E6421L anti-Cdx2 DyeCycle Violet stain SMRTbell Enzyme Clean Up Kit Invitrogen Invitrogen PacBio PA5-20891; RRID:AB_11155394 V35003 101-746-400 Donkey anti-chicken-Cy3 DNase RNeasy Mini Kit Millipore Qiagen Qiagen AP194C; RRID:AB_92679 79254 74104 Goat anti-chicken-AF488 Donkey anti-rabbit-AF647 Formaldehyde Sodium chloride solution, 5M Deposited data Goat anti-rabbit-AF488 Goat anti-mouse-AF488 Abberior Star 635P H3K4me3 H3K27me3 anti-mouse-HRP Bacterial and virus strains SARS-CoV-2, isolate USA-WA1/2020 Human Metapneumovirus MPV-GFP1 Chemicals, peptides, and recombinant proteins DPBS (Life Technologies, 14190144), DPBS 0.
This paper R&D Systems senckenberg. de/) This paper Gibco Fisher Scientific Fisher Scientific https://genome. Life Technologies senckenberg. de/) This paper ATCC ATCC Roche This paper WiCell Pierce ATCC Bio-Rad This paper Gibco Bio-Rad Bio-Rad This paper Charles River Bio-Rad Fisher Scientific This paper CytoTune 2. 0 A-11039; RRID:AB_2534096 F8775 S5150 A-31573; RRID:AB_2536183 A-10034; RRID:AB_2576217 A-11029; RRID:AB_2534088 ST635P; RRID:AB_2893232 39159; RRID:AB_2615077 39155; RRID:AB_2561020 W4021; RRID:AB_430834 NR-52281 M121 14190144 L0615-500 25300054 10569010 11995065 F4135 10500064 GCF_004115265. 1 AM9260G BEF 15630080 G8898 GCA_014108255. 1 RFe. iPS#1(BiPS1) I3021 P7626 GCA_004115265. 2 RFe. iPS2 (BiPS#2) 85850 N/A MMy. BUF 07180 MMy. iPS 314-BP-010 15040066 SF1004 N/A R700-07 CRL-1658 GEO: GSE221965 SCRC-1011 89900 GEO: GSE221965 WA09 45582400 CRL-1587 23252 GEO: GSE221965 A34181 4561044 1610772 GEO: GSE221965 250 161-3075 12010020 BP2471500 GEO: GSE221965 N/A MEM Non-essential amino GlutaMax Supplement Tween 20 Clarity Western ECL Substrate RFe_BiPS1-R3_RNA: R.
ferrumequinum iPS#1 RNA-seq replicate 3 ACCAGACAAGAGTTTAAGAGATATGTATC SeV-R: Gibco Gibco Bio-Rad Bio-Rad This paper CytoTune 2. 0 11140050 35050061 161-0781 170-5060 GEO: GSE221965 N/A Penicillin-Streptomycin solution Paraformaldehyde RFe_BiPS2-R1_RNA: R. ferrumequinum KOS-F: ATGCACCGCTACGACGTGAGCGC Gibco Electron Microscopy Sciences This paper CytoTune 2. 0 15140122 19200 GEO: GSE221965 N/A Gelatin Glutaraldehyde iPS#2 RNA-seq replicate 1 KOS-R: ACCTTGACAATCCTGATGTGG Millipore Electron Microscopy Sciences CytoTune 2. 0 ES006B 16220 N/A Antibiotic-Antimycotic (100X) Sodium Cacodylate Buffer RFe_BiPS2-R2_RNA: R. ferrumequinum Klf4-F TTCCTGCATGCCAGAGGAGCCC Gibco Electron Microscopy Sciences This paper CytoTune 2. 0 15240096 11652 GEO: GSE221965 N/A Collagenase type II Aqueous osmium tetroxide iPS#2 RNA-seq replicate 2 Klf4-R: AATGTATCGAAGGTGCTCAA Gibco Sigma-Aldrich CytoTune 2.
0 17101015 75633-2ML N/A Gentle Cell Dissociation Reagent 2% aqueous uranyl acetate RFe_BiPS2-R3_RNA: R. ferrumequinum cMyc-F: TAACTGACTAGCAGGCTTGTCG StemCell Technologies Electron Microscopy Sciences This paper CytoTune 2. 0 07174 22400-2 GEO: GSE221965 N/A DMEM/F-12 Ethanol iPS#2 RNA-seq replicate 3 cMyc-R: TCCACATACAGTCCTGGATGATGATG Gibco Electron Microscopy Sciences CytoTune 2. 0 11330057 15055 N/A Knockout serum replacement Epoxy resin EMbed 812 RFe_BiPS2-EB-R1_RNA: R. ferrumequinum GAPDH_F1_GHB: TGGTGAAGGTCGGAGTGAAC DMSO 2-mercaptoethanol FGF2 Lead citrate Minimum Essential Medium EB RNA-seq replicate 2 RFe_BiPS2-EB-R2_RNA: R. ferrumequinum Toluidine Blue EB RNA-seq replicate 1 GAPDH_R1_GHB: GAAGGGGTCATTGATGGCGA Gibco Electron Microscopy Sciences This paper This paper Sigma-Aldrich Fluka R&D Systems Electron Microscopy Sciences Gibco This paper Electron Microscopy Sciences This paper 14900 GEO: GSE221965 Z25-132 10828-028 63689 233-FB (Continued on next page) (Continued on next page) (Continued on next page) 11935046 22410 GEO: GSE221965 D8418-100ML 26074-15 Z25-133 (Continued on next page).
All high-throughput sequencing data have been deposited at GEO and are publicly available as of the date of publication. Accession numbers are listed in the key resources table. d This paper analyzes existing, publicly available data. These accession numbers for the datasets are listed in the key resources table. d This paper does not report any original code. d All software packages and their accessibility are described in the STAR Methods sections. d Any additional information required to reanalyze the data reported in this paper (including the BLAST results related to Figures S5- d.
In the absence of recombination, the number of transposable elements (TEs) increases due to less efficient selection, but the dynamics of such TE accumulations are not well characterized. Leveraging a dataset of 21 independent events of recombination cessation of different ages in mating-type chromosomes of Microbotryum fungi, we show that TEs rapidly accumulated in regions lacking recombination, but that TE content reached a plateau at ca. 50% of occupied base pairs by 1. 5 million years following recombination suppression. The same TE superfamilies have expanded in independently evolved non-recombining regions, in particular rolling-circle replication elements (Helitrons). Longterminal repeat (LTR) retrotransposons of the Copia and Ty3 superfamilies also expanded, through transposition bursts (distinguished from gene conversion based on LTR divergence), with both non-recombining regions and autosomes affected, suggesting that non-recombining regions constitute TE reservoirs.
Transposable elements in Microbotryum genomes We identified transposable elements (TEs) in the a 1 and a 2 haploid genomes deriving from a single diploid individual of each of 15 Microbotryum species and in a genome of the red yeast Rhodothorula babjavae, an outgroup with the ancestral condition of the PR and HD mating-type loci on separate chromosomes, using previously published high-quality genome assemblies  30, 31, 37, [64] [65] [66]. We detected TEs de novo, using the MicroTEp pipeline implementing LTRharvest and RepeatModeler 1. 0. 11, combining results from three other programs: RECON, RepeatScout and Tandem Repeats Finder. The TE detection was enriched by blasting the TE models in genomes. We performed TE annotation using the fungal Repbase database 23. 05 (see more details in Methods).