dataesr/scientific-paragraphs-categorization huggingface dataset:
RNAseq mapping for differential expression was mapped with STAR v2. 7. 0  49  and reads were assigned with featureCounts v1. 6. 0  50. Differential expression results can be found in Supplementary Data 1, Supplementary Data 2 and Supplementary Data 3. Differential expression analysis. Differential expression results were generated using limma v3. 40. 6 51 and edgeR v3. 26. 8 52 R packages and tidyverse v1. 3. 0  53  was employed for various data rearrangements. Filtering was used to remove lowly expressed genes/proteins, and each dataset was filtered to remove genes/proteins for which the relative standard deviation was greater than 1 (RSD > 1) across replicates for a given condition and organism. Differential expression was defined by a significance cutoff of absolute log 2 FC > 1 and False Discovery Rate < 0.
Acknowledgements We are grateful to  Erik de Hulster  and  Fredrik Schubert  for technical support and training, as well as  Gang Li ,  Lucy Chao ,  Benjamín Sánchez , and colleagues in the CHASSY consortium for scientific discussions. This project has received funding from the  European Union 's  Horizon 2020 Framework Programme for Research and   Innovation-Grant  Agreement No. 720824. This work was also supported by the  Knut and Alice Wallenberg Foundation  and the  Novo Nordisk Foundation  (Grant no  NNF10CC1016517 ).
Data availability Data supporting the findings of this work are available within the paper and its Supplementary Information files. A reporting summary for this Article is available as a Supplementary Information file. All mapped transcript data and protein detection data generated in this work can be found at https://github. com/SysBioChalmers/OrthOmics. RNAseq datasets of data generated in this study can be found using SRA accession PRJNA531619 [https://www. ncbi. nlm. nih. gov/bioproject/PRJNA531619/]. Additional RNAseq data analyzed in Supplementary Fig. 6.
DNA Extraction, PCR, and Sequencing Analyses of 16S rRNA Gene Fragments DNA extraction from 0. 2-µm filters was carried out using a phenol/chloroform protocol detailed by  Bellaaj-Zouari et al. (2018). The quality and concentration of DNA extracts was measured using a Nanodrop spectrophotometer (Nano Drop 2000 Thermo). DNA samples were stored at -80 • C. Bacterial and archaeal 16S rRNA gene V4 variable regions were amplified by PCR using the Pro341F/Pro805R prokaryotic universal primer set  (Takahashi et al. , 2014) , with barcode on the forward primer, as previously described by  Dowd et al. (2008) , and were sequenced by the MiSeq Illumina (paired-end 2 × 300 bp) platform of the Molecular Research Laboratory (TX, United States). Raw amplicon sequencing data were processed using DADA2 version 1.
12. 1, a model-based approach for correcting amplicon sequencing errors  (Callahan et al. , 2016). After the inspection of quality read profiles, the data processing steps includes quality filtering, dereplication, denoising, merging, inference of ASVs (Amplicon Sequence Variants, i. e. , the true error-free sequences), and chimera removal. This process generates an error-corrected table of the abundances of ASVs in each sample. Because of low sequence number, one sample (S1S) was removed from the dataset for further analysis. The taxonomic assignment of ASVs were performed using the SILVA 16S rRNA gene reference (release 132) database  (Quast et al. , 2012). Finally, sub-sampling normalization, alpha and beta diversity were investigated by the Phyloseq and vegan R packages  (McMurdie and Holmes, 2013; Oksanen et al.
, 2016). Sequences from archaeal MGII ASVs were aligned using Muscle  (Edgar, 2004)  with related sequences from NCBI databases and sequences of Thaumarchaeota (MGI) which were used as outgroup. A phylogenetic tree was built with MEGA7  (Kumar et al. , 2016)  using the Maximum Likelihood method  (Tamura and Nei, 1993). Tree topology confidence was determined by bootstrap analysis on 1000 replicates  (Felsenstein, 1985). Raw sequence data are available in the Sequence Read Archive (SRA) of NCBI under BioProject PRJNA632896, BioSamples SAMN14927758-SAMN14927776.
The relationship between the dominant ASVs (selection of the top 40 ASVs, mean relative abundance >0. 5%) and environmental factors was carried out by Canonical correspondence analysis (CCA) with Vegan package. The bioenv function in the vegan R package selected the best combination of all environmental factors to explain the spatial patterns in the biological matrix. The CCA function used the ASV abundance matrix (transformed by log1p function) with the best combination of environmental factors. The envfit (permutation = 999) function fitted environmental factors onto the ordination for those with a p-value <0. 05.
Absence of large scale genome duplication in Anthoceros Whole genome duplications (WGD) have played an important role in shaping plant evolution and possibly underlie several adaptive radiations  20. A previous study, based on Ks divergence in transcriptomic datasets, suggested that hornworts may not have experienced any WGD event  19  , similar to M. polymorpha  7  and Selaginella moellendorffii  21. Our Ks plots on the annotated Anthoceros genes similarly show no sign of WGD (Supplementary Figure  7 ). To further corroborate this, we investigated patterns of intra-genomic synteny in the three hornwort genomes, as well as the published M. polymorpha and P. patens genomes for comparison. We found very little self-synteny in the hornwort genomes (Fig. 1b-d ), thus providing a strong evidence for the lack of WGD in Anthoceros.
Contamination removal While our cultures were grown in a putative axenic condition, low level of contamination cannot be completely ruled out. We therefore used blobtools  75  to identify scaffolds/contigs primarily consisting of contaminant sequences. The Hi-C library theoretically should sort DNA sequences originating from different organisms because cross-linking occurred within the nuclei. Therefore, we hypothesized that dropping scaffolds mainly with non-Streptophyte affiliation will effectively remove contaminants from our assembly. For A. agrestis Bonn, we used both the full uniprot and the NCBI nt database and blobtools to assign the taxonomic affiliation to each scaffold with an e-value of 10 -4. We found that some of the small scaffolds were classified as Ascomycota and Cyanobacteria; these scaffolds were then removed from the assembly.
RNA-seq dataset and analysis on developmental stages To study the expression pattern of transcription factor genes across developmental stages, we generated RNA-seq libraries for the following stages of the A. agrestis Bonn strain in two biological replicates: (1) spores after two weeks of germination, (2) four-week-old gametophytes, (3) two-month-old gametophytes, (4) sporophytes shorter than 5 mm, (5) sporophytes 5-10 mm, (6) sporophytes longer than 1 cm with brown or black tips. Plants were grown on agar plates containing BCD medium 61 at 22°C. RNA was extracted with the Spectrum Total RNA Plant Kit (Sigma-Aldrich) and stranded RNA-seq libraries were prepared using the TrueSeq Stranded mRNA Library Prep kit (Illumina). Libraries were sequenced at the FGCZ on a HiSeq4000 machine. We used trimmomatic  76  to quality filter and trim the raw reads.
Gene expression was estimated using Salmon  77  and differential expression done by DESeq2 (log2fold ≥ 2, false-discovery rate ≤ 0. 05, and normalized reads counts)  78. We also generated separate thallus RNA-seq data for the Oxford strain (for annotation purpose). The plants were cultured on solid BCD plates, and total RNA was extracted using RNeasy Plant Mini kit (QIAGEN). The library was prepared using the TrueSeq stranded mRNA Library Prep kit (Illumina) and sequenced on Hiseq1500.
RNA-seq dataset and analysis on CO 2 response For the CO 2 experiment, we grew hornworts in magenta boxes with vented lids in order to allow air circulation while maintaining sterility. A. agrestis Oxford strain was used in this experiment and kept on solid BCD medium. We subjected the plant cultures to one of the three CO 2 environments at 150 (low), 400 (ambient), and 800 (high) ppm in a CO 2 -controlled growth chamber for 10 days (12/12hr day/night cycle). Three biological replicates were done for each treatment. RNA was extracted by the Spectrum Total RNA Plant Kit (Sigma-Aldrich). The Illumina libraries were prepared by BGI, and sequenced on HiSeq4000. One of the low CO 2 samples failed to produce high quality library, and as a result the low CO 2 condition has only two replicates. RNA-seq data analysis was done following the same procedure as described above.
RNA-seq, transcript, and protein evidence We pooled A. agrestis Bonn, Oxford and A. punctatus RNA-seq reads together and mapped them onto each of the genome assemblies using HiSat2  80. We used all RNA-seq evidence available owing to the low nucleotide divergence among the three genomes. Transcriptomes were assembled for each species/strain separately. We used Portcullis 87 to filter out bad splice junctions, and Stringtie 81 to assemble the transcripts. We additionally used Trinity  88  to generate both de novo and genome-guided transcriptome assemblies. We combined Trinity transcripts using the PASA pipeline  89  and derived high-quality transcripts with Mikado  90. To obtain protein homology information, we retrieved the 19 proteomes (only primary transcripts; Supplementary Table  14 ) and aligned them to the genome assemblies using exonerate  91.
Generating consensus gene models We used EVM to derive consensus gene models best supported by the various evidence. We used all the previously generated gene predictions (gff files) and selected the best consensus gene models using protein (exonerate-mapped proteomes of species and the uniprot_sport plant dataset) and transcript evidence (Mikado and PASA assembled transcripts). We gave equal weights to each ab initio predictions, transcript evidence (weight 1), but increased the weight for Mikado loci (2) and PASA assembled transcripts (10). After deriving the consensus gene models, we used PASA and the PASA assembled transcripts to correct erroneous gene models, add UTRs, and predict alternative splice variants in two rounds.
Collinearity of the three hornwort genomes and collinearity across viridiplantae We used the D-GENIES dot-plot tool  96  with the default options to visually assess collinearity of the three genome assemblies. We also aligned the genomic sequences using the nucmer module of mummer  97  and assessed their differences using Assemblytics  98. To study the collinearity across all plants, we first created orthogroups with 19 species' proteomes using Orthofinder2  99. The dataset included representatives from each major groups of land plants (Supplementary Table  14 ), and species experienced different numbers of large-scale duplication events  100. Gff files and proteomes were retrieved from Phytozome v12  101. We used I-ADHore3 102 to detect highly degenerate collinear blocks among bryophytes and vascular plants requiring a minimum of 3, 4 and 5 anchor points within each collinear region ( gap_size=30, cluster_gap=35, q_value=0.
Phylogenetic reconstruction of KNOX, LEAFY, WOX, and YABBY For KNOX, AagrBONN. evm. model. Sc2ySwM. 368. 1986. 6 was used as a query to BLASTp search at NCBI on 13th Sept 2019. The search database was nr limited to records that include: A. thaliana , Oryza sativa (japonica cultivar-group), Phalaenopsis equestris , Amborella trichopoda , Ceratopteris richardii , Selaginella moellendorffii , M. polymorpha , P. patens , K. nitens , Ostreococcus tauri , C. reinhardtii. The search parameters were otherwise as default. The hit sequences were downloaded and combined with the Anthoceros KNOX sequences, then aligned with FFT-NS-2 in MAFFT v7. 427  108. The alignment was manually inspected in Mesquite v3. 6  109  and well conserved 149 sites of 51 sequences were included. Phylogenetic analysis based on Maximum Likelihood (ML) was conducted in MEGA X  110.
The best-fitting model was chosen as LG+G+I using the FindBestProteinModel function. A total of 100 bootstrap replicates were performed to evaluate branch support. "ML Heuristic Method" was set to "Subtree-Pruning-Regrafting -Extensive (SPR level 5)", and "No. of Discrete Gamma Categories" set to 5. For LEAFY, AagrOXF evm. model. utg000049l. 76. 4 was used as a query to BLASTp search at NCBI on 30th Aug 2019. The search database was nr limited to records that include: A. thaliana , O. sativa (japonica cultivar-group), P. equestris , A. trichopoda , P. radiata , P. armandii , P. abies , C. richardii , S. moellendorffii , M. polymorpha , and P. patens. The search parameters were otherwise as default. The hit sequences were downloaded and combined with the Anthoceros LEAFY sequence and AHJ90704.
1, AHJ90706. 1, AHJ90707. 1 from Sayou et al. 111  , then aligned with FFT-NS-2 in MAFFT v7. 427  108. The alignment was manually inspected and processed as described above to include 194 conserved sites of 20 sequences. Phylogenetic inference was done similarly as above but with LG selected as the best-fitting model. For WOX, WOX genes in Anthoceros genomes were searched using the corresponding A. thaliana , P. patens and M. polymorpha proteins. Based on comparison among the three genomes, three gene models with excess intron predictions were manually revised, and one model was added. AagrOXF_evm. model. utg000018l. 552. 1 was used as a query to BLASTp search at NCBI on 9 October 2019. The search database was nr limited to records that include: A. thaliana , O. sativa (japonica cultivar-group), P.
Bootstrap samples were generated with seqboot from PHYLIP package v3. 697  113  and RAxML was run for each of them. For YABBY , the 107 OTU dataset from Finet et al  114  was downloaded from treebase and combined with YABBY genes from Huperzia and Anthoceros. The sequences were aligned using einsi of MAFFT v7. 450  108. The aligned sequences were manually inspected with Mesquite and short sequences were removed and ambiguously aligned or gap containing sites were excluded. The best-fitting model was chosen as HIVB by ProteinModelSelection8. pl, and ML tree search followed what was described for WOX.
Phylogenetic reconstruction of stomata-related genes An Anthoceros ICE/SCRM homolog sequence AagrBONN_evm. model. Sc2ySwM_368. 1570. 1 was used as a query to BLASTp search at NCBI on 7 Oct 2019. The search database was nr limited to records that include: A. thaliana , O. sativa (japonica cultivar-group), P. equestris , A. trichopoda , S. moellendorffii , P. patens , M. polymorpha , C. braunii , K. nitens. The word size was set to 2 and max target sequences as 250. The search parameters were otherwise set as the default. The hit sequences (100)  were downloaded and combined with the Anthoceros ICE/SCRM sequences, then aligned with einsi --maxiterate 1000 in MAFFT v7. 429  108. The alignment was manually inspected with MacClade 4. 08 and well-conserved 123 sites were included to result in alignment of 66 sequences.
The sequence identical in the included region were treated as a single OTU during the phylogenetic analysis. The best-fitting model was chosen as JTTDCMUTF with ProteinModelSelection8. pl. The ML tree was inferred by RAxML with -f a -# 100 -m PROTGAMMAJTTDCMUTF and supplying -p and -x from random number generator. Bootstrap samples (1000 replicates) were generated with seqboot from PHYLIP package v3. 697  113  and RAxML 112 was run for each of them. For ERECTA and TMM, the sequences of AagrOXF_evm. model. utg000083l. 351. 1 and AagrOXF_evm. model. utg000012l. 100. 1 were respectively used as the query and processed as in ICE/SCRM. Phylogenetic analyses were performed same as ICE/SCRM case, but with LG selected as the best-fitting model. For EPF and EPF-like gene family, we used the matrix compiled by Takata et al  115  and added the Anthoceros and M.
Phylogenetic reconstruction of LCIB The orthogroup OG0009668 was identified as the LCIB gene family containing C. reinhardtii LCIB -E genes. Additional hornwort LCIB homologs were retrieved from the 1KP transcriptome database 5. To find other LCIB homologs, we ran BLASTp against the Phytozome database using both the Anthoceros and C. reinhardtii sequences as the query, and no hit could be obtained. Gene phylogeny was reconstructed based on the amino acid alignment done by MUSCLE  122. IQ-TREE v1. 6. 1  119  was used to obtain the ML tree as outlined above. F. -W. L. , P. S. , K. S. , T. N. coordinated the project, M. S. carried out chromosome work, F. -W. L. , P. S. , T. N. , D. H. , S. C. , G. K. -S. W. sequenced the genomes, F. -W. L. , P. S. assembled the genomes, P. S. , T. N. annotated the genomes, T.
Acknowledgements This project was supported by  National Science Foundation   DEB1831428  to F. -W. L. ,  Swiss National Science Foundation  (grants  160004  and  131726  ) to P. SZ. , the  Georges and Antoine Claraz Foundation (Switzerland)  to P. SZ. , The Forschungskredit and the  University Research Priority Program "Evolution in Action " of the  University of Zurich  to M. W and P. SZ. ,  IOS-1339156  and  EF-1550838  to M. S. B. ,  National Institute for Basic Biology (NIBB) Collaborative Research Program  ( 13-710 ) to T. N. ,  Japan Society for the Promotion of Science KAKENHI 26650143 ,  18K06367  to K. S. , Short  Term Postdoctoral Fellowship  ( PE14780 ) to E. F. ,  Bill & Melinda Gates Foundation  grant ( OPP11772165 ) to  P. -M. D. ,  Spanish Ministry of Science, Innovation and Universities  ( BFU2016-80621-P ) to J.
If symptoms suggestive of COVID-19 occur, discontinuation of treatment should be discussed. While some autoinflammatory diseases warrant continued administration of colchicine (for example, to prevent a gout attack), patients should be monitored for possible drug interactions. Furthermore, there may be an overlap in symptoms of COVID-19 or drug side effects. For example, diarrhea is commonly observed with COVID-19 but may also result from an overdose of colchicine. Of note, as of April 17, 2020, five studies testing the effects of colchicine on COVID-19 were available on ClinicalTrials. gov (NCT04350320, NCT04326790, NCT04328480, NCT04322565, NCT04322682).
Can JAK inhibitors (baricitinib and tofacitinib) be maintained or initiated? In the current context, there is no contraindication to the initiation or continuation of a Janus kinase inhibitor (JAKi). If signs suggestive of infection (coronavirus or other) occur, treatment should be discontinued. In addition, in vitro data are available that demonstrate antiviral activity of baricitinib  [19, 20]. Currently, no data exists on the risk or benefit to continue or stop a JAKi in patients with COVID-19. Only one openlabel pilot study on 12 patients suggests a potential benefit of baricitinib combined with lopinavir-ritonavir in COVID-19  [21]. Furthermore, on April 17, 2020, six studies testing the effects of JAKi on COVID-19 were available on ClinicalTrials. gov (baricitinib: NCT04340232, NCT04346147, NCT04320277, NCT04345289, NCT04321993; tofacitinib: NCT04332042; ruxolitinib: NCT04348071, NCT04334044, NCT04338958, NCT04337359, NCT04331665, NCT04348695).
Are anti-interleukin-6 receptor therapies beneficial to patients with severe COVID-19? The occurrence of acute respiratory distress patterns on day 8-10 of COVID-19 are associated with the so-called cytokine storm and other inflammatory responses that may resemble macrophage activation syndrome. One of the first open studies in China supported the potential efficacy of interleukin-6 (IL-6) blockade, notably by tocilizumab (TCZ)  [22]. In another study by Luo et al. [23] , there is less confidence in the use of TCZ since 3 of the 15 patients treated in open-label studies died. Results from recent studies are encouraging  [24, 25] , but data from randomized control trials are expected. As of April 17, 2020, there are 30 studies on ClinicalTrials. gov concerning the potential use of TCZ or other anti-IL6 therapies (sarilumab, siltuximab, sirukumab, and clazakizumab).
The Italian phase 2 study entitled TOCIVID-19 (NCT04317092) proposes 2 infusions of TCZ at 8 mg/kg 12 hours apart. The COVACTA (NCT04320615) study is a phase 3, randomized, doubleblind, placebo-controlled study. A phase 2 study in Denmark (NCT04320615) has planned to include 330 patients (a single infusion at 8 mg/kg). A phase 2 study in Denmark (NCT04322773) has planned to include 200 patients in 4 arms including one intravenous TCZ arm and one subcutaneous TCZ arm compared to sarilumab and control. The Swiss study CORON-ACT (NCT04335071) has planned to include 100 patients. Finally, the French study CORIMUNO plans to test different biological DMARDs (bDMARD), including tocilizumab (CORIMUNO-TOCI; NCT04331808). Sarilumab has been evaluated in at least 5 studies including the specific CORIMUNO-SARI arm (NCT04324073).
A large international phase 2 and phase 3 study (NCT04315298) has planned to include 400 patients (severe or critical forms of COVID-19) and will test the efficacy of sarilumab at a high and low intravenous dose. For siltuximab, there is one Italian retrospective study (NCT04322188) and one Spanish phase 2 study (NCT04329650) with open-label treatment of 100 patients who will receive one intravenous injection at 11 mg/kg. There is one study evaluating the efficacy of sirukumab in severe COVID-19 with acute respiratory distress. 3. 12. Can biological targeted treatments be maintained or initiated? It is advisable to maintain bDMARD if effective and well tolerated, while also practicing preventative measures in order to avoid the potential occurrence of an outbreak. If symptoms are suggestive of COVID-19 infection, bDMARD should be withheld, and corticosteroids if prescribed, should be maintained.
Initiation of a bDMARD should be decided on a case-by-case basis according to the inflammatory activity of the disease and the informed consent of the patient(s). Currently, there is no data in the medical literature to suggest additional risk or benefit to continuation or elimination of bDMARD in patients infected by SARS-CoV-2. Furthermore, on April 17, 2020, multiple studies testing the effects of anti-IL-1, anti-IL-6, anti-TNF and other bDMARD on COVID-19 were available on ClinicalTrials. gov (see question 17).
What are the main molecules currently being tested in clinical trials? As of April 12, 2020, the number of clinical trials listed on Clini-calTrials. gov for COVID-19 reached 689. Not surprisingly, the first studies initiated include the use of various antiviral molecules, most commonly remdesivir, but also ritonavir, darunavir, danoprevir, favipiravir, lopinavir, oseltamivir. There are currently more than twenty clinical studies using hydroxychloroquine, including controlled, double-blind, and placebo-controlled trials. A major phase 3 study in Germany (NCT04340544) has planned to include 2700 patients using a daily dose of 600 mg hydroxychloroquine for 7 days with a primary endpoint of clinical resolution of mild COVID-19 at D28 ± 2. Two other studies (NCT04344457 and NCT04334512) will compare hydroxychloroquine versus azithromycin.
Prevention strategy studies should also be highlighted. The French COVIDAXIS (NCT04328285) study is a large, randomized, double-blind, phase 3, controlled study conducted in 600 exposed healthcare professionals comparing hydroxychloroquine at a dose of 400 mg on D1 and D2, then 200 mg per day versus placebo. The duration of treatment is 2 months with a primary endpoint of the occurrence of a symptomatic or asymptomatic COVID-19. Other prevention studies are also scheduled including PATCH (NCT04329923), PHYDRA (NCT04318015), SHARP (NCT04342156) and EPICOS (NCT04334928). The Spanish study EmCOVID-HidroxiCLOROQUINA (NCT04330495) is a phase 4, randomized, double-blind, controlled study using hydroxychloroquine for chemoprophylaxis in patients with chronic inflammatory disease treated with biologics or JAK inhibitors (JAKi).