dataesr/scientific-paragraphs-categorization huggingface dataset:
(g) smFISH staining for muscle (TAGLN), basal epithelia (KRT14), duct (ALDH1A3)and myoepithelium (FHOD3) cell type markers in human bronchus section. (h) H&E from bronchial section and Cell2location density values for mapping duct, mucous, serous, ciliated and myoepithelial cells onto the Visium ST section. (i) Linear mixed model analysis revealed 80 differentially expressed genes in ciliated cells between trachea and other locations (bronchi and parenchyma). Violin plots of normalised log-transformed expression separated by location in the single nuclei RNA-seq data for three representative genes upregulated in nasopharyngeal carcinoma gene set from GSEA database with LTSR>0. 9 consistently higher expressed in the trachea. (j) SARS-CoV-2 receptor and viral entry gene expression in airway epithelial cells, with expression levels of ACE-2 in the ciliated cells from snRNAseq data shown by location in a violin plot.
Acknowledgements We thank  Jana Eliasova  for the graphical illustrations. Chuan Xu  provided a script for TCR gene usage analysis. Cecilia Dominguez Conde supported with a script for TCR clonotype sharing analysis. Martin Prete 's and the  Cellgen  IT computational support has been central for the analysis. We are grateful to the organ donors, their families and the  Cambridge Biorepository for Translational Medicine  for the gift of human tissue. K. B. M. and S. A. T. are supported by  Wellcome  ( WT211276/Z/18/Z  and Sanger core grant  WT206194 ). E. M. is supported by  ESPOD fellowship of EMBL-EBI  and  Sanger Institute. The project has received funding from the  European Union 's  Horizon 2020 research and innovation programme  under grant agreement No  874656. This project has been made possible in part by grant  2019-202654  from the  Chan Zuckerberg Foundation.
1B, E ). We then demonstrated that knockdown of NRAS G12D in NRAS mutant dCMML MNC did not have an impact on ex vivo proliferation (Supplementary Fig. 3F ). Next, to better define clonal versus sublonal RAS pathway mutation thresholds, we assessed mutant NRAS and mutant oncogenic RAS pathway VAF data and correlated RAS VAF as a continuous measure of subclonality in relationship to clinical parameters. A receiver operating characteristic curve (ROC) analysis demonstrated that a NRAS VAF ≥ 0. 3 or an oncogenic RAS VAF of ≥0. 19 best correlated with a pCMML phenotype, in comparison to binary RAS mutation status (Fig. 3C-F ). Finally, we showed that the NRAS VAF threshold of ≥0. 3 correlated with lower platelet counts (Supplementary Fig. 3G ), while the RAS VAF threshold of ≥0. 19 correlated with lower platelet counts and higher PB blasts (Supplementary Fig.
To define the mechanism underlying the biological effects of RAS pathway mutations in CMML, transcriptome sequencing (RNA-seq) was performed. We attempted CD34 + selection from PB MNC prior to RNAseq, however, there was significant attrition in cell numbers resulting in sample inadequacy to carry out large scale experiments. A pilot verification study analyzed RNA-seq data from 5 CMML patients using unsorted PB MNC, 5 using CD14 + sorted PB cells (monocytes) and 5 using CD34 + selected PB progenitor cells (no overlap between groups). This demonstrated a linear correlation in pair-wise gene expression (Supplementary Fig. 4A ). Furthermore, comparing expression of housekeeping genes and select genes relevant to myeloid biology in CD34 + sorted and unsorted MNCs revealed no appreciable systematic differences between the two populations for these genes (Supplementary Fig.
Mutant RAS regulates PLK1 expression through the lysine methyltransferase KMT2A (MLL1). Interrogating molecular events involved in RAS-mediated increase in PLK1 expression, ChIP-seq was performed on BM MNC from 40 CMML patients [RAS pathway-mutated pCMML, n = 18; RAS pathway wild-type dCMML, n = 12) and healthy, age-matched controls (n = 10). From this data pool we selected 6 samples [3 RAS pathway mutant pCMML (#1 TET2/DNMT3A/NRAS, #2 ASXL1/CBL/ IDH2/SRSF2 and #3 ASXL1/TET2/EZH2/NRAS) and 3 RASpathway wild-type dCMML (#1 TET2/SRSF2, #2 IDH2/SRSF2/ RUNX1 and #3 TET2/SRSF2)] that had adequate number of reads and read depth and that met ENCODE criteria (https://www. encodeproject. org/chip-seq/histone/) for assessment of the three aforementioned histone marks. A peak was defined as either present (MACS2 FDR < 0.
Prior clonal architecture studies at the single cell  level have reported that in most adult onset hematological malignancies, including CMML, oncogenic RAS pathway mutations are usually secondary/subclonal events  6, 36. While that is true in dCMML, we show that in pCMML, RAS pathway mutations are often clonal and occur early in the disease course. A B D H I E G Log2 Fold change K M T 2 A K M T 2 B K M T 2 C K M T 2 D S T D 1 A S E T D 1 B M E N s i N T s i N R A S s i N T s i K R A S s i N T s i K M T 2 A s i N T s i K M T 2 A C o n t r o l N R A S G 1 2 D C o n t r o l K R A S G With the help of a large molecularly annotated database we show that clonal RAS pathway mutations (VAF ≥ 0. 19) were associated with high risk disease features and were associated with an inferior AML-FS (increased risk of LT).
By using ChIP-seq in CMML samples, we demonstrate that H3K27me3 occupancy and recruitment at the PLK1 promoter is not significantly different in RAS pathway-mutated pCMML relative to RAS pathway wildtype dCMML, regardless of ASXL1 mutational status (sequencespecific analysis restricted to PLK1). PLK1 (volasertib and onvansertib) inhibitors have completed clinical trials for patients with myeloid neoplasms (MDS and AML) with reasonable safety data, prompting us to establish the therapeutic efficacy of these agents in pCMML models  22, [42] [43] [44]. While a recent randomized phase III clinical trial testing the efficacy of volasertib with low-dose cytarabine (LDAC vs LDAC and placebo-NCT01721876) in AML patients ineligible for standard induction chemotherapy, did not meet its stated endpoints, this trial was not personalized to subsets of AML patients more likely to respond to therapy.
This included 48 patients with CMML whose paired MNC samples were collected in chronic phase and in LT to perform WES. A second cohort of 18 patients with CMML was used to perform WES on samples serially collected along disease progression. This cohort had been described previously  6. All patient samples were obtained either at diagnosis, or at first referral, which was usually within 3-6 months of diagnosis. Patients not meeting these criteria were not included in these cohorts. All patients were treatment naïve at the time of collection of their samples for sequencing. None of them were in a clinical trial at the time of sample collection. The disease stage is mentioned in the table under the World Health Organization-2016 diagnosis section. While 250 of the Mayo Clinic patients were eventually treated with hypomethylating agents, given the retrospective nature of this study and treatment at centers outside of Mayo Clinic, accurate response data and duration of treatment information is not available.
The same applies to the European cohorts. All patients in this data set that underwent allogeneic stem cell transplant (10%) were accurately accounted for and were censored in survival data calculations, as transplant is the only disease modifying treatment modality for CMML. The following statistical methods were used on the clinical data sets: Distribution of continuous variables was statistically compared using Mann-Whitney or Kruskal-Wallis tests, while nominal or categorical variables were compared using the Chi-Square or Fischer's exact test. Time to event analyses used the method of Kaplan-Meier for univariate comparisons using the log-rank test. Overall survival was calculated from the date of diagnosis to date of death or last follow-up, while AML-free survival was calculated from date of diagnosis to date of AML transformation or death.
All statistical calculations were carried out using JMP statistical software, version 16. 0, SAS Institute Inc. Cary, NC, 1989-2019. Whole exome sequencing. One microgram of genomic DNA was sheared with the Covaris S2 system (LGC Genomics). Exome capture and sequencing library preparation were performed using Agilent SureSelect Human All Exon V5 (Agilent Genomics, Santa Clara, CA), following standard protocols. The final libraries were indexed, pooled and paired-ends (2 × 100 bp) sequenced on Illumina HiSeq platforms (San Diego, CA). Germ-line DNA was obtained from CD3-positive cells for 5 patients of the CMML LT dataset and 17 patients with serial WES analyses  6. The mean coverage in the targeted regions was 100-fold. Sequencing data are deposited at the European Genome-Phenome Archive (EGA), hosted by the European Bioinformatics Institute (EBI).
Paired-end reads in the form of FASTQ files were aligned to the GRCh37 version of the human genome with BWA or Novalign to generate BAM files. Variant calling analysis was performed using Agilent SureCall software. Genomic variant information including evidence of and somatic status in cancer, significant protein domains, and known pathogenicity was further annotated using public databases: The Catalogue of Somatic Mutations in Cancer -COSMIC (https://cancer. sanger. ac. uk/cosmic), ClinVar (https://www. ncbi. nlm. nih. gov/clinvar) and UniProt (https://www. uniprot. org). Allele frequency in the normal population was calculated using the Exome Aggregation Consortium ExAC (http://exac. broadinstitute. org). Alternative alleles with <5 reads and/or a frequency <5% were excluded. All variants passing the sequencing quality-control filters and within a gene coding region, regardless of database population frequency, underwent characterization.
cnLOH was called based on the germline heterozygous SNPs VAFs in the tumor  45. Tumor evolution was visualized with ClonEvol (https://ieeexplore. ieee. org/document/6650525). WES data that support the findings in Fig. 2  have been deposited in EGA under ID EGAD00001007026. Targeted next-generation sequencing. Analysis of the Mayo cohort (#3) was done using a panel in which the regions of 36 genes was selected for custom target capture using Agilent SureSelect Target Enrichment Kit. Briefly, libraries derived from each DNA sample were prepared using NEB Ultra II (New England Biolabs, Ipswitch, MA) and individually bar coded by dual indexing. Sequencing was performed on a HiSeq 4000 (San Diego, CA) with 150-bp paired-end reads and consisted of 48 pooled libraries per lane. Median sequence read depth was ~400×.
Sequencing (2×250 bp reads) was performed on a MiSeq flow cell (Illumina, San Diego, CA) using the onboard cluster method. Sequencing reads were mapped to the GRCh37 version of reference genome with the Burrows-Wheeler Aligner (BWA) (PMID: 19451168) and then processed with the Genome Analysis Toolkit (GATK; version 4. 1. 2. 0) (PMID: 20644199) following best practices for exomes and specific indications for smaller targeted regions. Sequencing quality and target enrichment were verified with Picard tools metrics. Germinal DNA was obtained from CD3-positive cells for 5 patients from the CMML/sAML dataset and for 17 patients from CMML with serial WES analyses. Since CD3-positive cells are known to be contaminated with tumor cells (PMID: 26457647; PMID: 26908133) we performed MuTect2 in the 'tumor-only' mode.
For all identified mutations and indels Variant Allele Frequencies in the corresponding CD3 + DNA was retrieved from bam files. All the variants with p values from Fisher exact test below 10 -4 were considered as somatic. Regions of Somatic copy Number Alterations SCNA were screened manually. A panel of normal samples (PON) was constructed from 50 germline samples ad was used to reduce the rate of false positives. We filtered out all polymorphisms from ExAC database (http://exac. broadinstitute. org) with allelic frequency above 0. 001. Additionally, variants were considered putative drivers if reported in the COSMIC v89 database. Only stop-gain, frameshift indels, splice-site and probably damaging nonsynonymous mutations were considered to be putative drivers in tumor suppressor genes. SCNA analysis was performed with Facets statistical and computational analysis pipeline in 'tumor-normal' mode where possible, or in 'tumor only' mode.
cnLOH was called based on the germline heterozygous SNPs VAFs in the tumor (PMID: 27270079). All the variant processing was conducted in python with pandas library. Fisher exact test was used for contingency tables. Mann-Whitney test was used for two groups of continuous variables. Pearson-Spearman test was used for pairwise correlations of continuous variables. Log-rank test was used for survival analyses. Multivariate analysis was executed using logistic regression model, LASSO with selected features (Regression Shrinkage and Selection via the Lasso. Robert Tibshirani) and applied to measure enrichment / depletion between two subgroups. Tumor evolution was visualized with ClonEvol software (https://ieeexplore. ieee. org/document/6650525). Hematopoietic progenitor colony forming assay. PB and/or BM samples were first treated with ammonium chloride to deplete red blood cells, washed in RPMI, then plated at a final concentration of 5 × 10 4 -2 × 10 5 cells/mL into methylcellulose formulated with recombinant cytokines to support the optimal growth of erythroid progenitor cells (BFU-E and CFU-E), granulocyte-macrophage progenitor cells (CFU-GM, CFU-G and CFU-M), and multipotent granulocyte, erythroid, macrophage, and megakaryocyte progenitor cells (CFU-GEMM).
RNA-seq sequencing reads were processed through the MAPRSeq v2. 0. bionformatics workflow as described in Kalari et al. 48. Briefly reads were mapped using TopHat version 2. 06 against the reference GRCh37 without alternative haplotypes using the transcript models from UCSD (March 2012) available from Illumina iGenomes Project. Gene counts were calculated with featureCounts  49  , differential expression was performed using edgeR and clustering was performed using heatmap. 2  50. RNA samples were prepared and RNA quality was determined using an Agilent Bioanalyzer RNA Nanochip or Caliper RNA assay and arrayed into a 96-well plate. The paired-end sequencing libraries were prepared following BC Cancer Genome Sciences Centre's strandspecific, plate-based library construction protocol on a Microlab NIMBUS robot (Hamilton Robotics, USA).
Libraries were sequenced on an Illumina HiSeq2500 platform to a read depth of approximately 50 million reads per sample. Reads were aligned to the human genome (GRCh38/hg38) using the HISAT2 aligner  51. Read counts were generated using featureCounts with reference to Homo_sapiens. GRCh38. 90. gtf annotation file from Ensembl  49, 52. Patient's samples were grouped based on the previously identified histological classifications and differential expression analyses were performed using the R Bioconductor package DESeq2  53. Pathway data was derived from ConsensusPathDB  54. Heatmaps were derived using the R package pheatmap (pheatmap: CRAN. R-project. org/package=pheatmap) and principle component analyses were derived using the R package rgl (rgl: CRAN. R-project. org/package=rgl). RNA PCR.
11. 1 software with the following options: -gsize hs -d given. Regions of differential enrichment were derived using the R Bioconductor package DiffBind (citation: DiffBind: differential binding analysis of ChIP-Seq peak data. http:// bioconductor. org/packages/release/bioc/vignettes/DiffBind/inst/doc/DiffBind. pdf) and areas of were annotated using Homer  [58] [59] [60] [61] [62]. To identify differences in DNA binding, the Bioconductor package Diffbind v2. 16. 0 was used in R v4. 0. 3. Reads were counted in intervals using dba. count function and mapQCth = 1, minOverlap =3 parameters. Differential binding affinity analysis was performed using dba. analyze with method = DBA_DESEQ2, bCorPlot = F parameters. Differentially bound sites identified were then used to plot MA with dba. plotMA function.
Bigwig files, normalized for sequencing depths, have been generated with deeptools. Individual tracks for dysplastic and proliferative samples were visualized using UCSC repository. ChIP-seq data that support the findings in Fig. 5  have been deposited in GEO under series GSE156377. Chromatin immunoprecipitation-qPCR. ChIP was performed as described previously  60. Briefly, PB MNC from CMML patients (20 × 106) were crosslinked with 1% formaldehyde directly into the medium for 10 min at room temperature. The cells were then washed with PBS, collected by centrifugation at 800×g for 5 min at 4 °C, re-suspended in Cell Lysis Buffer (20 mM Tris [pH 8];15 mM PIPES; 85 mM KCl; 0. 5% NP-40), and incubated on ice for 15 min. Resulting pellets were then re-suspended in Nuclear Lysis Buffer (50 mM Tris [pH 8.
Complete blood counts were also analyzed on all PDX mice at endpoint (IDEXX Veterinary Diagnostics). Immunohistochemistry staining was performed at the Pathology Research Core (Mayo Clinic, Rochester, MN) using the Leica Bond RX stainer (Leica). Slides for CD3 stain were retrieved for 30 min using Epitope Retrieval 2 (EDTA; Leica) and incubated in block (Rodent Block M, Biocare) for 30 min. The CD3 primary antibody (Clone F7. 2. 38; Dako) was diluted to 1:150 in Bond Antibody Diluent (Leica). Slides for CD14 and CD163 stains were retrieved for 20 min using Epitope Retrieval 2 (EDTA; Leica) incubated in protein block (Rodent Block M, Biocare) for 30 min. The CD14 primary antibody (Rabbit Polyclonal -HPA001887; Sigma) was diluted to 1:300 in Bond Antibody Diluent (Leica). The CD163 primary antibody (Clone 10D6, Leica) was diluted to 1:400 Background Reducing Diluent (Dako).
Acknowledgements Current publication is supported in part by grants from the  "Gerstner Family Career Development Award", The "Center for Individualized Medicine-Mayo Clinic", and "The Henry J. Predolin Foundation for Research in Leukemia ,  Mayo Clinic, Rochester, MN, USA". This publication was also supported by  CTSA  Grant Number  KL2 TR000136  from the  National Center for Advancing Translational Science (NCATS). Its contents are solely the responsibility of the authors and do not necessarily represent the official views of the NIH. R. M. C. was supported by the 2020 Eagles 5th  District Cancer Telethon Cancer Research Fund Fellowship Award. M. E. F. Z. was supported by  CA136526. S. I. N. was supported by  Foundation   ARC 2017 ,  Foundation Gustave Roussy and Swiss Cancer League  (grant  KFC-3985-08-2016 ) grants.
Data availability We do not have patient consent to release raw NGS data. Any inquiries for accessing these data should be directed to Mrinal Patnaik (patnaik. mrinal@mayo. edu) and we will grant access to the de-identified datasets for research purposes. WES data that support the findings in Fig. 2  have been deposited in EGA under ID EGAD00001007026. RNA-seq data that support the findings in Figs. 4  and 5  have been deposited in GEO under series GSE156209. The ChIP-seq data that support the findings of this study have been deposited in GEO under series GSE156377. The UCSC session can be accessed through the genome browser [https://genome. ucsc. edu/s/mbinder/CMML_RAS_H3K4me1]. Source data are provided with this paper.
Results Individual Lucinid Hosts Can Harbor More Than One Symbiont Species Simultaneously. We sequenced, assembled, and binned metagenomes from 47 individual clams. This resulted in 63 MAGs (metagenome assembled genomes), 53 of which were considered high-quality with greater than 90% completeness and less than 10% contamination (18) (Dataset S1). All newly assembled MAGs from this study are available under GenBank accession numbers SAMN16825223 to SAMN16825285, including raw reads (SRA database project number PRJNA679177). All 63 MAGs were assigned to the genus Ca. Thiodiazotropha. Sixteen metagenomes yielded two distinct Ca. Thiodiazotropha MAGs in one gill. The majority of lucinids we investigated hosted a single symbiont species abundant enough for its genome to be assembled from gill metagenomes.
Of these, 15 Clathrolucina costata and 1 Loripes orbiculatus contained two distinct MAGs (Dataset S1). Using DESMAN, no more than two strains were detected within any MAG, indicating that there is also limited symbiont strain diversity in each host individual (Dataset S1). Symbionts Form Distinct Clades within the Gammaproteobacterial Family Sedimenticolaceae. We reconstructed the phylogenetic relationships of 63 Ca. Thiodiazotropha MAGs we generated to previously described lucinid symbionts and their closest freeliving relatives, Sedimenticola thiotaurini and Sedimenticola selenatireducens, using a concatenated amino acid alignment of 43 universally conserved marker genes, with Allochromatium vinosum as an outgroup [alignment on Figshare  (19) ]. The maximum likelihood phylogenetic reconstruction yielded 10 unique clades, each with an average nucleotide identity (ANI) above 95%, indicating that each clade likely corresponds to a distinct species, two of which have not been previously identified (Dataset S2).
1 ). The second species, Ca. T. sp. "RUGA," was found in a single Rugalucina munda metagenome. The Ca. T. sp. "RUGA" MAG shared an ANI of 94. 543% with all Ca. T. taylori MAGs, making it the closest identified relative to the Ca. T. taylori group. Reanalysis of L. orbiculatus metagenomes containing a previously described symbiont species, Ca. T. endoloripes, revealed that Ca. T. endoloripes is actually two distinct lineages with an ANI of 91. 938%, which indicates they are separate species (Dataset S2). We propose the names Ca. T. weberae and Ca. T. lotti for these two species after Dr. Miriam Weber and Christian Lott, who discovered the population of L. orbiculatus in Elba, Italy. Its symbionts Ca. T. weberae and Ca. T. lotti both share an ANI of roughly 89% with Ca. T. taylori and Ca. T.
sp. "RUGA," their next-closest relatives (Fig. 2 ). The lucinid symbionts from the genus Ca. Thiodiazotropha formed two major clades, one comprising the four above-mentioned species and another containing Ca. T. endolucinida and the Thiodiazotropha-like species associated with Ctena orbiculata from Florida, previously reported by Lim et al. (20)  (Fig. 2 ). Like Ca. T. taylori, Ca. T. endolucinida was also found in multiple host species (five species from subfamilies Lucininae, Codakiinae, and Leucosphaerinae) but its geographic distribution appears to be restricted to the Caribbean based on samples that are so far available (February 2021). Comparative Genomics of Lucinidae Symbionts. We compared the predicted functional capabilities of Ca. T. taylori, the most widespread symbiont in our dataset, to 1) its closest relatives (Ca.
T. weberae, Ca. T. lotti, and Ca. T. sp. "RUGA") and 2) the sympatric Ca. T. endolucinida, which can cooccur with Ca. T. taylori in the same host gill, to investigate whether functional potential reflects symbiont geography or phylogeny. All five symbiont species shared most core metabolic functions (Table  1 ). A maximum of 7. 2%, or 170 of the 2,361 protein families (Pfams) found in these genomes, were enriched in Ca. T. endolucinida, i. e. , they were significantly more frequent within this species group (P adj < 0. 05), while the closely related species Ca. T. taylori, weberae, and lotti had far fewer enriched Pfam functions, suggesting that phylogenetic relationships are to some extent reflected in genomic functional potential (details in SI Appendix, SI Results, Table  S3 , and Fig. S2  A and B and Dataset S5).