title: E14 mESC Si8L4

city: Santa Barbara

first: Alex

last: Chialastri

address: 2002 BioEngineering Bldg, CNTR for Bioengineering

institute: University of California Santa Barbara

data_processing:
Library strategy: scDyad&T-seq
Illumina bcl2fastq2 v 2.20 software used for basecalling
A custom Perl script was used to demultiplex genomic based read barcodes from RNA based read barcodes. This code is available on request. RNA enriched samples were processed for RNA transcripts, while unenriched samples were used to identify site specific 5mC as well as the status of CpG dyads as fully or hemi-methylated.
For genomic site specific 5mC detection (for absolute 5mC (or 5hmC) level calling), exact duplicates were removed using Clumpify from BBTools. A custom Perl script was use to extract the single cell barcode and UMI from each read. Then read 1 and 2 were trimmed using TrimGalore in paired end mode. The 5’ end of read 1 was clipped by 20 bases and the 3’ end of read 2 was hard clipped 34 bases after detection of the PCR amplification sequence CCACATCACCCAAACC to remove potential bias from enzymatic digestion and to avoid recounting CpG dyad detections utilized in the maintenance measurement. The 5’ end of read 2 was clipped by 9 bases to remove potential bias from the linear amplification 9-mer. The 3’ end of read 1 was also hard clipped 9 bases after detection of the Illumina adapter was performed. Each read was mapped individually using Bismark v0.21.0 in conjunction with Bowtie2 v2.3.5 to MM10 or hg19 for mouse or human samples, respectively. Using Bismark, both resulting sam files were deduplicated further using UMI, cell barcode and mapping location. The bismark_methylation_extractor tool was then used to extract detected cytosines. After which custom Perl code was used to connect detected cytosines to their respective cell. CpG detection files from the same DNA strand for read 1 and read 2 were then combined and any duplicate detections where the same cytosine was read in both read 1 and read 2 were removed using the UMI. Custom codes for analyzing Dyad-seq data and the accompanying documentation is provided with this work.
For genomic CpG Dyad specific calling (for 5mCpG (or 5hmC) maintenance calling), Read 1 was trimmed to 86 bases. Then exact duplicates were removed using Clumpify from BBTools. A custom Perl script was use to extract the single cell barcode and UMI from each read. Then read 1 was trimmed using the default settings of TrimGalore. Read 1 was mapped using Bismark v0.21.0 in conjunction with Bowtie2 v2.3.5 to MM10 or hg19 for mouse or human samples, respectively. Using Bismark, both resulting sam files were deduplicated further using UMI, cell barcode and mapping location. For library preparation using MspJI, a custom Perl script was used to identify 5mC positions in the genome as detected by MspJI and interrogate the methylation status of the opposing cytosine in a CpG or CpHpG dyad context from the nucleobase conversion. For library preparation using AbaSI, a custom Perl script was used to identify 5hmC positions in the genome as detected by AbaSI and interrogate the methylation status of the opposing cytosine in a CpG dyad context from the nucleobase conversion.
For bulk RNA based reads, read 2 sequences were trimmed to 50 bases and mapped in the sense direction to the refseq MM10 transcriptome build supplemented with ERCC mRNA spike-in sequences using bwa v0.7.15 with parameters aln -q 0 -n 0.04 -k 2 -l 200 -t 6 -B 12. Any read mapping to multiple loci were distributed uniformly across those loci. Gene isoforms were consolidated into a gene count, and the UMI was used to deduplicate reads from each gene for each individual cell. The number of observations was converted into transcript counts based on binomial statistics as described previously by Grün et al.. Genes that were not detected in at least one cell were discarded from any downstream analysis.
For single cell RNA based reads, Read 2 was trimmed using the default settings of TrimGalore. After trimming, STARsolo (STAR aligner version 2.7.8a) was used to map the reads to MM10 using the gene annotation file from Ensembl . The reads were again mapped to MM10 using the transposable elements annotation file described in TEtranscripts. Transcripts with the same UMI were deduplicated, transcripts detected from genes or transposable elements were analyzed together and any that were not detected in at least one cell were removed from any downstream analysis.
Required code to go from raw FASTQ files to processed data can be found on github at https://github.com/alexchialastri/scDyad-T-seq
Genome_build: MM10 and hg19
Supplementary_files_format_and_content: 5mCpG Dyad maintenance detection files [noted in the naming of the file as *_CGMaintained.txt (for loci detected as maintained {e.g. fully methylated dyads for M-M-Dyad-seq}) and *_CGNonMaintained.txt (for loci detected as not maintained  {e.g. hemi-methylated dyads for M-M-Dyad-seq})] list detected methylated or unmethylated CpG maintenance sites. Column 1 is the cell number (in bulk this is the sample replicate indicator), column 2 is the chromosome (with chr23 indicating the X chromosome, chr24 indicating the Y chromosome, and chr25 indicating a mitocondrial based detection), column 3 is the genomic loci, column 4 is the UMI detected and column 4 is the strand of the detected mark.
Supplementary_files_format_and_content: Absolute 5mCpG detection files [noted in the naming of the file as *_BS-CpG_All.txt or *BS-CpG_All_BothStrands_Unique.txt] list detected methylated or unmethylated CpG sites. Column 1 is the cell number (in bulk this is the sample replicate indicator), column 2 is the chromosome (with chr23 indicating the X chromosome, chr24 indicating the Y chromosome, and chr25 indicating a mitocondrial based detection), column 3 is the genomic loci, column 4 is the the strand of the detected mark, column 5 is the UMI detected and column 6 indicates if the cytosine was methylated (Z) or unmethylated (z) .
Supplementary_files_format_and_content: For Bulk samples RNA-seq gene count files (noted in the naming of the file as *-READ_COUNTS_c.txt.gz) is a matrix with the columns indicating  sample (replicate) number, and each row indicating the number of counts detected for a given gene.
Supplementary_files_format_and_content: Single cell transcript counts contain 6 files. 3 refer to the detection of unique transcripts related to genes (*_Genes_matrix.mtx.gz, *_Genes_features.tsv.gz, and *_Genes_barcodes.tsv.gz) and 3 refer to the detection of unique transcripts related to transposable elements (*_TE_matrix.mtx.gz, *_TE_features.tsv.gz, and *_TE_barcodes.tsv.gz). These set of 3 files are in the standard 10x sparse data matrix format (Market Exchange Format). The *_barcodes.tsv.gz file gives the list of cell barcodes used in the experiment. Note: these are in alphabetical order and not ordered by cell number, see supplementary file ('SingleCell_barcodesOrdered.csv') on main page for which barcodes refer to what cell number. The *_features.tsv.gz file gives the list of gene or transposable elements names. The *_matrix.mtx.gz gives the location and value of non zero elements in gene or transposable elements detection matrix, with column 1 refering to the feature, column 2 to the cell number, and column 3 to the number of transcripts detected.

source_name: E14 mESC

growth_protocol: All cells were maintained in incubators at 37°C and 5% CO2. Mouse embryonic stem cell line ES-E14TG2a (E14) were grown on gelatin (Millipore Sigma, ES-006-B) coated tissue culture plates with media containing high glucose DMEM (Gibco, 10569044), 1% non-essential amino acid (Gibco, 11140050), 1% Glutamax (Gibco, 35050061), 1x Penicillin-Streptomycin (Gibco, 15140122), and 15% stem cell qualified serum (Millipore Sigma, ES-009-B). The media was frozen in aliquots and used thereafter for a maximum of 2 weeks after thawing while storing it at 4°C. Once thawed, 1 µL of beta-mercaptoethanol (Gibco, 21985023), and 1 µL of LIF (Gibco, A35933) were added for every 1 mL of thawed media. Cells were washed with 1x DPBS (Gibco, 14190250) and the media was exchanged daily. Cells were routinely passaged 1:6 once they reached 75% confluency using 0.25% trypsin-EDTA (Gibco, 25200056). E14 cells grown under these conditions also describe the SL experimental group. For FACS sorting, a single-cell suspension was made using 0.25% trypsin-EDTA. The trypsin was then inactivated using serum containing medium. Afterwards, the cells were washed with 1x DPBS before being passed through a cell strainer and sorted for single cells into 384-well plates.  K562 cells were grown in RPMI (Gibco, 61870036) with 10% serum (Gibco, 10437028) and 1x Penicillin-Streptomycin. When the culture reached a density of approximately 1 million cells per mL, they were split and resuspended at a density of 200,000 cells per mL. Cells were washed and FACS sorted as described for E14 cells.

extract_protocol:
Bulk genomic DNA was extracted using the DNeasy kit (Qiagen, 69504) according to the manufacturer’s recommendations. Bulk total RNA was extracted using TRIzol reagent (Invitrogen, 15596018) according to the manufacturer’s recommendations. For single cell experiments, whole cell lysate was used by soring cells via FACs directly into lysis buffer.
4 µL of Vapor-Lock (QIAGEN, 981611) was manually dispensed into each well of a 384-well plate using a 12-channel pipette. All downstream dispensing into 384-well plates were performed using the Nanodrop II liquid handling robot (BioNex Solutions). To each well, 100 nL of uniquely barcoded reverse transcription primers (7.5 ng/µL) containing 6 nucleotide UMI was added. The reverse transcription primers used here were previously described in Grun et al. with the exception that a UMI length of 6 was used45. Next, 100 nL of lysis buffer (0.175% IGEPAL CA-630, 1.75 mM dNTPs (NEB, N0447S), 1:1,250,000 ERCC RNA spike-in mix (Ambion, 4456740), and 0.19 U RNase inhibitor (Clontech, 2313A)) was added to each well. Single cells were sorted into individual wells of a 384-well plate using FACS and stored at -80°C. To begin processing, plates were heated to 65°C for 3 minutes and returned to ice. Next, 150 nL of reverse transcription mix (0.7 U RNAseOUT (Invitrogen, 10777-019), 2.33x first strand buffer, 23.33 mM DTT, and 3.5 U Superscript II (Invitrogen, 18064-071)) was added to each well and the plates were incubated at 42°C for 75 minutes, 4°C for 5 minutes, and 70°C for 10 minutes. Thereafter, 1.5 µL of second strand synthesis mix (1.23x second strand buffer (Invitrogen, 10812-014), 0.25 mM dNTPs (NEB, N0447S), 0.14 U E. coli DNA Ligase (Invitrogen, 18052-019), 0.56 U E. coli DNA Polymerase I (Invitrogen, 18010-025), 0.03 U RNase H (Invitrogen, 18021-071)) was added to each well and the plates were incubated at 16°C for 2 hours. Following this step, 650 nL of protease mix (6 µg protease (Qiagen, 19155), 3.85x NEBuffer 4 (NEB, B7004S)) was added to each well, and the plates were heated to 50°C for 15 hours, 75°C for 20 minutes, and 80°C for 5 minutes. Next, 500 nL of glucosylation mix (1 U T4-BGT (NEB, M0357L), 6x UDP-glucose, 1x NEBuffer 4) was added to each well and the plates were incubated at 37°C for 16 hours. Thereafter, 500 nL of protease mix (2 µg protease, 1x NEBuffer 4) was added to each well, and the plates were incubated at 50°C for 3 hours, 75°C for 20 minutes, and 80°C for 5 minutes. Next, 500 nL of MspJI endonuclease mix (1x NEBuffer 4, 8x enzyme activator solution, 0.1 U MspJI (NEB, R0661L)) was added to each well and the plates were incubated at 37°C for 4.5 hours, and then heated to 65°C for 25 minutes. To each well, 280 nL of uniquely barcoded 250 nM unphosphorylated double-stranded Dyad-seq adapters were added. Next, 720 nL of ligation mix (1.39x T4 ligase reaction buffer, 5.56 mM ATP (NEB, P0756L), 140 U T4 DNA ligase (NEB, M0202M)) was added to each well, and the plates were incubated at 16°C for 16 hours. After ligation, uniquely barcoded reaction wells were pooled using a multichannel pipette, and the oil phase was discarded. The aqueous phase was incubated for 30 minutes with 1x AMPure XP beads (Beckman Coulter, A63881), and then subjected to standard bead cleanup with the DNA eluted in 30 µL of water. After vacuum concentrating the elute to 6.4 µL, in vitro transcription (IVT) was performed as previously described in the scAba-seq and scMspJI-seq protocols1,8. RNA enrichment from the IVT product was performed as described previously with the following modifications. The entire IVT product was used for enrichment, 4 µL of 1µM biotinylated polyA primer (5’- AAAAAAAAAAAAAAAAAAAAAAAA/3BioTEG/ -3’), and 8 µL of Dynabeads MyOne Streptavidin C1 beads (Invitrogen, 65001) were used and resuspended in 24 µL of 2x B&W solution after establishing RNase-free conditions. In addition, the supernatant was saved for additional processing.
The supernatant from the RNA enrichment process contains unamplified barcoded scDyad-seq DNA molecules. A 1x AMPure XP bead cleanup was performed by incubating the samples with beads for 30 minutes and eluting in 40 µL of water. Samples were then concentrated to 28 µL and nucleobase conversion was performed as described above for bulk M-M-Dyad-seq. Samples were then subjected to four rounds of linear amplification. The first round was the same as described for bulk Dyad-seq. In subsequent rounds, samples were first heated to 95°C for 45 seconds before being quenched on ice. Once cold, 5 µL of amplification mix was added (1x NEBuffer 2.1 (NEB, B7202S), 2 mM dNTPs (NEB, N0447L), 2 uM Linear amplification 9-mer, and 10 U of high concentration Klenow DNA polymerase (3’-5’ Exo-) (fisher scientific, 50-305-912)). Samples were then quickly vortexed, centrifuged and the same thermocycler conditions were used as in the first round of linear amplification. After 4 rounds of linear amplification, sequencing libraries were prepared the same way as described for bulk Dyad-seq. Finally, 150 bp paired-end Illumina sequencing was performed on a HiSeq platform. Sequencing metrics and associated metadata for each cell can be found in Supplementary File 1.

treatment_protocol:
Decitabine treatment: E14 mouse embryonic stem cells were cultured as described above. Upon passage of the E14 cells, SL media was supplemented with 0.05 µM of Decitabine. After 24 hours, cells were harvested using 0.25% trypsin-EDTA. The trypsin was then inactivated using serum containing medium. The cells were washed with 1x DPBS and then resuspended in 200 µL of DPBS. Genomic DNA was extracted using the DNeasy kit (Qiagen, 69504) according to the manufacturer’s recommendations.
K562 cells were cultured as described above. Upon passage, the media was supplemented with 0.6 µM of Decitabine or DMSO vehicle control. After 24 hours the cells were washed and single-cell FACS sorting was performed as described above.
Transition from serum to 2i and other media conditions: E14 mouse embryonic stem cells were cultured in SL conditions as described above. Upon passage, cells were resuspended in the following media depending on the condition studied. Commercial 2i media containing LIF (Millipore, SF016-200) was used for BL, G, 2i, and M experiments. For 2i, all components were used according to the manufacturer's recommendations. For G and M conditions, only the GSK3B inhibitor or MEK1/2 inhibitor was added, respectively. For the BL condition, no inhibitors were added. For the No condition, commercial 2i media without LIF (Millipore, SF002-100) was used with no inhibitors added. After 24 hours, the cells were washed with 1x DPBS and the media was exchanged. 48 hours after the initial media switch, the cells were collected using 0.25% trypsin-EDTA, quenched using serum containing media, washed in 1x DPBS and finally resuspended in 1x DPBS. The sample was then split in half for genomic DNA and total RNA extraction.
In single-cell serum to 2i experiments, the same process was followed with cells being isolated into a reaction well of a 384 well plate using FACS after 3, 6, or 10 days in 2i. Cells grown in 2i were split 1:6 every other day.

value: E14 mESC

tag: conditions

tag: strategy

value: scDyad&T-seq


title: E14 mESC Si8L2

status: Public on Aug 07 2023

type: SRA

state: CA

country: USA

library_source: genomic

molecule: other

organism: Mus musculus

tag: cell type


title: E14 mESC Si8L3


title: snRNA-seq of 6hpf S. purpuratus embryos

city: PITTSBURGH

first: Hinman

last: Veronica

state: PA

address: 587 S Negley Ave, Apt 17

department: Biological Sciences

institute: Carnegie Mellon University

description: 10X Genomics

library_source: transcriptomic single cell

data_processing:
Cell Ranger V4.0.0 (Zheng et al., 2017) was used to create  aligned to a pre- mRNA indexes for P. miniatagenome V3.0 (GenBank assembly accession: GCA_015706575.1) andS. purpuratusgenome V5.0 (GenBank assembly accession: GCA_000002235.4). The pre-mRNA indices were constructed using gene annotation files modified by an in-house script to remove intron annotations. Read were aligned using the cellranger count command. The raw, unfiltered count files are presented in this GEO entry. In the P. miniata entries, note that when applicable, the gene names are consistant with the names of their 1:1 othologs in S. purpuratus, as is consistant with the gene page naming system of echinobase.org
A Standard Seurat processing pipeline (V4.2.0 ) was used to prepare the final .RDS atlases provided in this entry.
Assembly: P miniatagenome V3.0 (GenBank assembly accession: GCA_015706575.1); S. purpuratusgenome V5.0 (GenBank assembly accession: GCA_000002235.4)
Supplementary files format and content: annotated and processed S. purpuratus developmental atlas in .RDS format

molecule: total RNA

organism: Strongylocentrotus purpuratus

source_name: whole embryo nuclar extract

extract_protocol:
Nuclear isolation protocol adapted from Omni-ATAC-seq protocol (Corces et al., 2017). Full protocol in Meyer et al 2021, biorxiv
Single nuclei libraries were created using the Chromium Next GEM Single Cell 3’ Reagent Kit v3.1 RevD (10X Genomics) and the Chromium X instrument (10X Genomics) using manufacturer protocols

tag: tissue

value: whole embryo nuclear extract

tag: developmental stage


title: CM-PC-1h-2

city: Jinju

first: Seon-In

last: Yeom

address: 501, Jinjou-daero

country: South Korea

institute: Gyeongsang National University

library_source: transcriptomic

data_processing:
A quality control application for high throughput sequence data using FastQC Version 0.11.8
Removes adapter sequences from DNA high-throughput sequencing data using Cutadapt  Version 1.15
A toolkit for the quality control (QC) of next generation sequencing (NGS) data using Trimmomatic Version 0.38
Alignment program for mapping next-generation sequencing reads to Capsicum annuum genome using Hisat2 Version 2-2.1.0
Calculated manually based on the method in the following paper. (Lee, J., Jang, H., Kang, W. H., & Yeom, S. I. (2023). Transcriptome analysis of pepper-phytophthora infestans interaction based on a pipeline of a simplified and effective RNA-seq analysis (PoRAS).)
Assembly: Capsicum annuum v1.6
Supplementary files format and content: tab-delimited text files include the values of FPKM/RPKM for each sample

molecule: polyA RNA

organism: Capsicum annuum

source_name: Leaves

extract_protocol:
Three biological replicates at each time point per condition were collected. The leaf samples were flash-frozen in liquid nitrogen and stored at ˗80°C until RNA isolation. Total RNA was extracted from pepper leaf samples (100 mg) using the Trizol reagent. Five micrograms of each RNA sample were used for construction of sequencing libraries.
RNA libraries were prepared for sequencing using strand-specfic RNA-seq Illumina protocols

value: Leaves

tag: genotype

value: WT

tag: treatment

tag: timepoint


title: E14 mESC Si8L1


title: IL-6 1 ng/ml, 1 H, biol rep 1

city: Pittsburgh

first: Rachel

middle: A.

last: Gottschalk

state: Pennsylvania

address: 200 Lothrop St., W1047 BST

department: Immunology

institute: University of Pittsburgh

data_processing:
Rsubread was used for the file alignment and read counting
DESeq2 was used for normalization
Assembly: mm10
Supplementary files format and content: STAT_final_DESeq2_normalizedCounts.csv

source_name: primary macrophages

growth_protocol: Cells were cultured for six days in DMEM with 10% fetal bovine serum (FBS), penicillin (100 U/ml), streptomycin (100 U/ml), 2 mM l-glutamine, and 20 mM Hepes supplemented with recombinant mouse M-CSF (60 ng/ml) at 37C.

extract_protocol:
RNA was extracted with the Direct-zol RNA MicroPrep Kit (Zymo Research).
RNA libraries for RNA-seq were prepared using Illumina Stranded mRNA Prep protocol.
Final libraries were sequenced on the NextSeq2000 (Illumina)

treatment_protocol: On day 7, BMDM were stimulated with the appropriate dose of IL-6 or IL-10 at the specified time and lysed with TRIzol Reagent (Ambion) for RNA isolation.

tag: strain

tag: Sex

value: Female

tag: age

value: 8-12 weeks

value: BMDM

value: primary macrophages

value: IL-6 1 ng/ml

tag: time

value: 1 H


title: CM-PC-1h-1


title: sample.sas2

city: West Lafayette

first: Kyle

middle: A

last: Cottrell

state: IN

address: 201 S University Street

department: Medicine

institute: Purdue University

data_processing:
Basecalls and demultiplexing were performed with Illumina’s bcl2fastq software with a maximum of one mismatch in the indexing read.
RNA-seq reads were then aligned to the Ensembl release 101 primary assembly with STAR version 2.7.9a1.
Gene counts were derived from the number of uniquely aligned unambiguous reads by Subread:featureCount version 2.0.32.
Gene counts, including transposable elements, were determined using the TEcount function from Tetranscripts using a GTF containing transposable elements from RepeatMasker, GRCh38_Ensembl_rmsk_TE.gtf, Jin Y., Tam O.H., Paniagua E. and Hammell M. (2015). TEtranscripts: A package for including transposable elements in differential expression analysis of RNA-seq datasets. Bioinformatics 31: 3593-3599. Pubmed ID: 26206304
Assembly: GRCh38.101
Supplementary files format and content: gene level count data, Tab-separated values
Supplementary files format and content: gene level count data including transposable elements from repeatmasker, Tab-separated values

organism: Homo sapiens

source_name: SK-BR-3, shADAR1 + shSCR

growth_protocol: All cell lines were cultured in Dulbecco’s modified Eagle’s medium (DMEM) (Hyclone) with 10% fetal bovine serum (Invitrogen), 2 mM glutamine (Hyclone), 0.1 mM nonessential amino acids (Hyclone), and 1 mM sodium pyruvate (Hyclone).

extract_protocol:
RNA was isolated using the NucleoSpin RNA, Mini kit for RNA purification from Macherey-Nagel per manufacturers instructions
Total RNA integrity was determined using Agilent Bioanalyzer or 4200 Tapestation. Library preparation was performed with 500ng to 1ug of total RNA. Ribosomal RNA was removed by an RNase-H method using RiboErase kits (Kapa Biosystems). mRNA was then fragmented in reverse transcriptase buffer and heating to 94 degrees for 8 minutes. mRNA was reverse transcribed to yield cDNA using SuperScript III RT enzyme (Life Technologies, per manufacturer's instructions) and random hexamers. A second strand reaction was performed to yield ds-cDNA. cDNA was blunt ended, had an A base added to the 3' ends, and then had Illumina sequencing adapters ligated to the ends. Ligated fragments were then amplified for 12-15 cycles using primers incorporating unique dual index tags. Fragments were sequenced on an Illumina NovaSeq-6000 using paired end reads extending 150 bases.

treatment_protocol: Cells were transduced with lentivirus for 16 hours in the presence of 10 µg/mL protamine sulfate. The cells were selected with puromycin at 2 µg/mL and 150 μg/mL hygromycin (Invitrogen). Transductions were done sequentially, shSCR or shADAR1, followed by shSCR or shDHX9

value: cell line, breast cancer

tag: cell line

value: ADAR1 knockdown

value: transduced with shRNA for ADAR1 and a scramble control


title: E14 mESC Si7L4

value: Cells 1-48:2iD10; Cells 49:96:Serum+LIF


title: CM-PC-TDW-1D-3


title: WSU-AML_IgG_rep2

city: Seattle

first: Research

middle: Scientific

last: Computing

state: WASHINGTON

address: 818 Stewart Street

department: Research Scientific Computing

institute: Seattle Children's Research Institute

data_processing:
Sequencing reads were mapped to the human hg38 genome build using Bowtie2.
Regions of enrichment (peaks) were identified using SEACRv1.4 in stringent mode and IgG control normalization.
CBFA2T3-GLIS2 (C/G) peaks were identified by intersection of the high confidence peaks from CBFA2T3 and GLIS2 from C/G transduced cord blood samples using Bedtools intersect.
Motif enrichment and peak annotations were completed using Homerversion 4.11 with hg38 promoter sets.
Assembly: GRCh38
Supplementary files format and content: bigWig
Supplementary files format and content: bed, peak calls from SEACR
Library strategy: Cut & Run

molecule: genomic DNA

source_name: Blood

growth_protocol: Cells were grown as described in PMID: 36136600, 500K cells were used for all CUT&RUN samples

extract_protocol:
Fresh CB samples were processed with red blood cell lysis buffer, enriched for CD34+ cells using CliniMACS CD34 MicroBeads (Miltenyi Biotec, 130-017-501), and frozen down for the future use. On the day of sort, CD34+ cells from multiple pooled CB samples (8 units each) were thawed and stained with the following antibodies: CD45RA-APC-Cyanine7, CD38-PECy7 (Invitrogen), CD34-PerCP, CD90-BV421, EPCR-BV786, Lineage cocktail (CD3, 14, 16,19,20,56)-FITC (BD Biosciences) and DAPI (to exclude dead cells)
Cut&Run data were generated from human umbilical cord blood samples transduced with CBFA2T3-GLIS2 or GFP control

treatment_protocol: The M07e cell line was seeded at 1x106 cells/ml and cultured in RPMI (Gibco) +10%FBS +1X Glutamax (Gibco) + 10ng/ml IL-3 (STEMCELL Technologies). The WSU-AML cell line was also seeded at 1x106 cells/ml, cultured in RPMI (Gibco) +10%FBS +1X Glutamax (Gibco). Both cell lines were treated with FHD-186 or BRM-014 for 48 hours. FHD-286 was added at 1nM, 10 nM, and 100 nM. BRM-014 was added at 10 nM, 100 nM, and 1000 nM. A DMSO control group was included with each drug treatment. For the CUT&RUN experiments, the M07e line was treated with 100 nM FHD-286 for 24 hours, while the WSU-AML line was treated with 10 nM FHD-286 for 24 hours.

value: Blood

value: WSU-AML

value: leukemia

tag: antibody

value: IgG


title: E14 mESC Si7L3

value: E14 mESC

value: scDyad&T-seq


title: sample.sas1


title: WSU-AML_IgG_rep1


title: CM-PC-TDW-1D-2

value: Leaves

value: WT


title: E14 mESC Si7L2


title: WSU-AML_Brg1_rep2


title: sample.ssd1

source_name: SK-BR-3, shSCR + shDHX9

value: DHX9 knockdown

value: transduced with shRNA for DHX9 and a scramble control


title: M07e_IgG_rep2


title: CM-PC-1h-3


title: M07e_IgG_rep1


title: WSU-AML_Brg1_rep1


title: CM-PC-TDW-1D-1


title: sample.mss2

source_name: MCF-7, shSCR + shSCR

value: control knockdown

value: transduced with scramble control shRNA


title: M07e_Brg1_rep2


title: CM-PC-TDW-12h-1


title: CM-PC-TDW-12h-3


title: E14 mESC Si7L1


title: E14 mESC SL_RNA-seq

data_processing:
Illumina bcl2fastq2 v 2.20 software used for basecalling
A custom Perl script was used to demultiplex genomic based read barcodes from RNA based read barcodes. This code is available on request. RNA enriched samples were processed for RNA transcripts, while unenriched samples were used to identify site specific 5mC as well as the status of CpG dyads as fully or hemi-methylated.
For genomic site specific 5mC detection (for absolute 5mC (or 5hmC) level calling), exact duplicates were removed using Clumpify from BBTools. A custom Perl script was use to extract the single cell barcode and UMI from each read. Then read 1 and 2 were trimmed using TrimGalore in paired end mode. The 5’ end of read 1 was clipped by 20 bases and the 3’ end of read 2 was hard clipped 34 bases after detection of the PCR amplification sequence CCACATCACCCAAACC to remove potential bias from enzymatic digestion and to avoid recounting CpG dyad detections utilized in the maintenance measurement. The 5’ end of read 2 was clipped by 9 bases to remove potential bias from the linear amplification 9-mer. The 3’ end of read 1 was also hard clipped 9 bases after detection of the Illumina adapter was performed. Each read was mapped individually using Bismark v0.21.0 in conjunction with Bowtie2 v2.3.5 to MM10 or hg19 for mouse or human samples, respectively. Using Bismark, both resulting sam files were deduplicated further using UMI, cell barcode and mapping location. The bismark_methylation_extractor tool was then used to extract detected cytosines. After which custom Perl code was used to connect detected cytosines to their respective cell. CpG detection files from the same DNA strand for read 1 and read 2 were then combined and any duplicate detections where the same cytosine was read in both read 1 and read 2 were removed using the UMI. Custom codes for analyzing Dyad-seq data and the accompanying documentation is provided with this work.
For genomic CpG Dyad specific calling (for 5mCpG (or 5hmC) maintenance calling), Read 1 was trimmed to 86 bases. Then exact duplicates were removed using Clumpify from BBTools. A custom Perl script was use to extract the single cell barcode and UMI from each read. Then read 1 was trimmed using the default settings of TrimGalore. Read 1 was mapped using Bismark v0.21.0 in conjunction with Bowtie2 v2.3.5 to MM10 or hg19 for mouse or human samples, respectively. Using Bismark, both resulting sam files were deduplicated further using UMI, cell barcode and mapping location. For library preparation using MspJI, a custom Perl script was used to identify 5mC positions in the genome as detected by MspJI and interrogate the methylation status of the opposing cytosine in a CpG or CpHpG dyad context from the nucleobase conversion. For library preparation using AbaSI, a custom Perl script was used to identify 5hmC positions in the genome as detected by AbaSI and interrogate the methylation status of the opposing cytosine in a CpG dyad context from the nucleobase conversion.
For bulk RNA based reads, read 2 sequences were trimmed to 50 bases and mapped in the sense direction to the refseq MM10 transcriptome build supplemented with ERCC mRNA spike-in sequences using bwa v0.7.15 with parameters aln -q 0 -n 0.04 -k 2 -l 200 -t 6 -B 12. Any read mapping to multiple loci were distributed uniformly across those loci. Gene isoforms were consolidated into a gene count, and the UMI was used to deduplicate reads from each gene for each individual cell. The number of observations was converted into transcript counts based on binomial statistics as described previously by Grün et al.. Genes that were not detected in at least one cell were discarded from any downstream analysis.
For single cell RNA based reads, Read 2 was trimmed using the default settings of TrimGalore. After trimming, STARsolo (STAR aligner version 2.7.8a) was used to map the reads to MM10 using the gene annotation file from Ensembl . The reads were again mapped to MM10 using the transposable elements annotation file described in TEtranscripts. Transcripts with the same UMI were deduplicated, transcripts detected from genes or transposable elements were analyzed together and any that were not detected in at least one cell were removed from any downstream analysis.
Required code to go from raw FASTQ files to processed data can be found on github at https://github.com/alexchialastri/scDyad-T-seq
Genome_build: MM10 and hg19
Supplementary_files_format_and_content: 5mCpG Dyad maintenance detection files [noted in the naming of the file as *_CGMaintained.txt (for loci detected as maintained {e.g. fully methylated dyads for M-M-Dyad-seq}) and *_CGNonMaintained.txt (for loci detected as not maintained  {e.g. hemi-methylated dyads for M-M-Dyad-seq})] list detected methylated or unmethylated CpG maintenance sites. Column 1 is the cell number (in bulk this is the sample replicate indicator), column 2 is the chromosome (with chr23 indicating the X chromosome, chr24 indicating the Y chromosome, and chr25 indicating a mitocondrial based detection), column 3 is the genomic loci, column 4 is the UMI detected and column 4 is the strand of the detected mark.
Supplementary_files_format_and_content: Absolute 5mCpG detection files [noted in the naming of the file as *_BS-CpG_All.txt or *BS-CpG_All_BothStrands_Unique.txt] list detected methylated or unmethylated CpG sites. Column 1 is the cell number (in bulk this is the sample replicate indicator), column 2 is the chromosome (with chr23 indicating the X chromosome, chr24 indicating the Y chromosome, and chr25 indicating a mitocondrial based detection), column 3 is the genomic loci, column 4 is the the strand of the detected mark, column 5 is the UMI detected and column 6 indicates if the cytosine was methylated (Z) or unmethylated (z) .
Supplementary_files_format_and_content: For Bulk samples RNA-seq gene count files (noted in the naming of the file as *-READ_COUNTS_c.txt.gz) is a matrix with the columns indicating  sample (replicate) number, and each row indicating the number of counts detected for a given gene.
Supplementary_files_format_and_content: Single cell transcript counts contain 6 files. 3 refer to the detection of unique transcripts related to genes (*_Genes_matrix.mtx.gz, *_Genes_features.tsv.gz, and *_Genes_barcodes.tsv.gz) and 3 refer to the detection of unique transcripts related to transposable elements (*_TE_matrix.mtx.gz, *_TE_features.tsv.gz, and *_TE_barcodes.tsv.gz). These set of 3 files are in the standard 10x sparse data matrix format (Market Exchange Format). The *_barcodes.tsv.gz file gives the list of cell barcodes used in the experiment. Note: these are in alphabetical order and not ordered by cell number, see supplementary file ('SingleCell_barcodesOrdered.csv') on main page for which barcodes refer to what cell number. The *_features.tsv.gz file gives the list of gene or transposable elements names. The *_matrix.mtx.gz gives the location and value of non zero elements in gene or transposable elements detection matrix, with column 1 refering to the feature, column 2 to the cell number, and column 3 to the number of transcripts detected.

extract_protocol:
Bulk genomic DNA was extracted using the DNeasy kit (Qiagen, 69504) according to the manufacturer’s recommendations. Bulk total RNA was extracted using TRIzol reagent (Invitrogen, 15596018) according to the manufacturer’s recommendations. For single cell experiments, whole cell lysate was used by soring cells via FACs directly into lysis buffer.
Bulk RNA-seq was prepared using a scaled up CEL-seq2 protocol.

value: Grown in Serum + LIF media

value: bulk RNA-seq


title: E14 mESC SL_H-M-Dyad-seq

data_processing:
Library strategy: H-M-Dyad-seq
Illumina bcl2fastq2 v 2.20 software used for basecalling
A custom Perl script was used to demultiplex genomic based read barcodes from RNA based read barcodes. This code is available on request. RNA enriched samples were processed for RNA transcripts, while unenriched samples were used to identify site specific 5mC as well as the status of CpG dyads as fully or hemi-methylated.
For genomic site specific 5mC detection (for absolute 5mC (or 5hmC) level calling), exact duplicates were removed using Clumpify from BBTools. A custom Perl script was use to extract the single cell barcode and UMI from each read. Then read 1 and 2 were trimmed using TrimGalore in paired end mode. The 5’ end of read 1 was clipped by 20 bases and the 3’ end of read 2 was hard clipped 34 bases after detection of the PCR amplification sequence CCACATCACCCAAACC to remove potential bias from enzymatic digestion and to avoid recounting CpG dyad detections utilized in the maintenance measurement. The 5’ end of read 2 was clipped by 9 bases to remove potential bias from the linear amplification 9-mer. The 3’ end of read 1 was also hard clipped 9 bases after detection of the Illumina adapter was performed. Each read was mapped individually using Bismark v0.21.0 in conjunction with Bowtie2 v2.3.5 to MM10 or hg19 for mouse or human samples, respectively. Using Bismark, both resulting sam files were deduplicated further using UMI, cell barcode and mapping location. The bismark_methylation_extractor tool was then used to extract detected cytosines. After which custom Perl code was used to connect detected cytosines to their respective cell. CpG detection files from the same DNA strand for read 1 and read 2 were then combined and any duplicate detections where the same cytosine was read in both read 1 and read 2 were removed using the UMI. Custom codes for analyzing Dyad-seq data and the accompanying documentation is provided with this work.
For genomic CpG Dyad specific calling (for 5mCpG (or 5hmC) maintenance calling), Read 1 was trimmed to 86 bases. Then exact duplicates were removed using Clumpify from BBTools. A custom Perl script was use to extract the single cell barcode and UMI from each read. Then read 1 was trimmed using the default settings of TrimGalore. Read 1 was mapped using Bismark v0.21.0 in conjunction with Bowtie2 v2.3.5 to MM10 or hg19 for mouse or human samples, respectively. Using Bismark, both resulting sam files were deduplicated further using UMI, cell barcode and mapping location. For library preparation using MspJI, a custom Perl script was used to identify 5mC positions in the genome as detected by MspJI and interrogate the methylation status of the opposing cytosine in a CpG or CpHpG dyad context from the nucleobase conversion. For library preparation using AbaSI, a custom Perl script was used to identify 5hmC positions in the genome as detected by AbaSI and interrogate the methylation status of the opposing cytosine in a CpG dyad context from the nucleobase conversion.
For bulk RNA based reads, read 2 sequences were trimmed to 50 bases and mapped in the sense direction to the refseq MM10 transcriptome build supplemented with ERCC mRNA spike-in sequences using bwa v0.7.15 with parameters aln -q 0 -n 0.04 -k 2 -l 200 -t 6 -B 12. Any read mapping to multiple loci were distributed uniformly across those loci. Gene isoforms were consolidated into a gene count, and the UMI was used to deduplicate reads from each gene for each individual cell. The number of observations was converted into transcript counts based on binomial statistics as described previously by Grün et al.. Genes that were not detected in at least one cell were discarded from any downstream analysis.
For single cell RNA based reads, Read 2 was trimmed using the default settings of TrimGalore. After trimming, STARsolo (STAR aligner version 2.7.8a) was used to map the reads to MM10 using the gene annotation file from Ensembl . The reads were again mapped to MM10 using the transposable elements annotation file described in TEtranscripts. Transcripts with the same UMI were deduplicated, transcripts detected from genes or transposable elements were analyzed together and any that were not detected in at least one cell were removed from any downstream analysis.
Required code to go from raw FASTQ files to processed data can be found on github at https://github.com/alexchialastri/scDyad-T-seq
Genome_build: MM10 and hg19
Supplementary_files_format_and_content: 5mCpG Dyad maintenance detection files [noted in the naming of the file as *_CGMaintained.txt (for loci detected as maintained {e.g. fully methylated dyads for M-M-Dyad-seq}) and *_CGNonMaintained.txt (for loci detected as not maintained  {e.g. hemi-methylated dyads for M-M-Dyad-seq})] list detected methylated or unmethylated CpG maintenance sites. Column 1 is the cell number (in bulk this is the sample replicate indicator), column 2 is the chromosome (with chr23 indicating the X chromosome, chr24 indicating the Y chromosome, and chr25 indicating a mitocondrial based detection), column 3 is the genomic loci, column 4 is the UMI detected and column 4 is the strand of the detected mark.
Supplementary_files_format_and_content: Absolute 5mCpG detection files [noted in the naming of the file as *_BS-CpG_All.txt or *BS-CpG_All_BothStrands_Unique.txt] list detected methylated or unmethylated CpG sites. Column 1 is the cell number (in bulk this is the sample replicate indicator), column 2 is the chromosome (with chr23 indicating the X chromosome, chr24 indicating the Y chromosome, and chr25 indicating a mitocondrial based detection), column 3 is the genomic loci, column 4 is the the strand of the detected mark, column 5 is the UMI detected and column 6 indicates if the cytosine was methylated (Z) or unmethylated (z) .
Supplementary_files_format_and_content: For Bulk samples RNA-seq gene count files (noted in the naming of the file as *-READ_COUNTS_c.txt.gz) is a matrix with the columns indicating  sample (replicate) number, and each row indicating the number of counts detected for a given gene.
Supplementary_files_format_and_content: Single cell transcript counts contain 6 files. 3 refer to the detection of unique transcripts related to genes (*_Genes_matrix.mtx.gz, *_Genes_features.tsv.gz, and *_Genes_barcodes.tsv.gz) and 3 refer to the detection of unique transcripts related to transposable elements (*_TE_matrix.mtx.gz, *_TE_features.tsv.gz, and *_TE_barcodes.tsv.gz). These set of 3 files are in the standard 10x sparse data matrix format (Market Exchange Format). The *_barcodes.tsv.gz file gives the list of cell barcodes used in the experiment. Note: these are in alphabetical order and not ordered by cell number, see supplementary file ('SingleCell_barcodesOrdered.csv') on main page for which barcodes refer to what cell number. The *_features.tsv.gz file gives the list of gene or transposable elements names. The *_matrix.mtx.gz gives the location and value of non zero elements in gene or transposable elements detection matrix, with column 1 refering to the feature, column 2 to the cell number, and column 3 to the number of transcripts detected.

extract_protocol:
Bulk genomic DNA was extracted using the DNeasy kit (Qiagen, 69504) according to the manufacturer’s recommendations. Bulk total RNA was extracted using TRIzol reagent (Invitrogen, 15596018) according to the manufacturer’s recommendations. For single cell experiments, whole cell lysate was used by soring cells via FACs directly into lysis buffer.
For all bulk Dyad-seq experiments, 100 ng of purified genomic DNA was resuspended in 20 µL of glucosylation mix (1x CutSmart buffer (NEB, B7204S), 2.5x UDP-glucose, 10 U T4-BGT (NEB, M0357L)) and the samples were incubated at 37°C for 16 hours. Afterwards, 10 µL of protease mix (100 µg protease (Qiagen, 19155), 1x CutSmart buffer) was added to each sample, and the samples were heated to 50°C for 5 hours, 75°C for 20 minutes, and 80°C for 5 minutes. After this, processing of the samples differed based on the version of Dyad-seq used.
For M-M-Dyad-seq and M-H-Dyad-seq, 10 µL of MspJI digestion mix (2 U MspJI, 1x enzyme activator solution, 1x CutSmart buffer) was added to each sample and the samples were heated to 37°C for 5 hours, and 65°C for 20 minutes. Next, 1 µL of barcoded 1 µM double-stranded adapter was added. Then 9 µL of ligation mix (1.11x T4 ligase reaction buffer, 4.44 mM ATP (NEB, P0756L), 2000 U T4 DNA ligase (NEB, M0202M)) was added to each sample, and the samples were incubated at 16°C for 16 hours.
For H-M-Dyad-seq and H-H-Dyad-seq, 10 µL of AbaSI digestion mix (10 U AbaSI (NEB, R0665S), 1x CutSmart buffer) was added to each sample and the samples were incubated at 25°C for 2 hours, and then heated to 65°C for 20 minutes. Next, 1 µL of barcoded 1 µM double-stranded adapter was added. Then 9 µL of ligation mix (1.11x T4 ligase reaction buffer, 4.44 mM ATP (NEB, P0756L), 2000 U T4 DNA ligase (NEB, M0202M)) was added to each sample, and the samples were incubated at 16°C for 16 hours.
After ligation, up to three barcoded libraries of the same type were pooled and all Dyad-seq versions were subjected to a 1x AMPure XP bead cleanup (Beckman Coulter, A63881), and eluted in 40 µL of water.
M-M-Dyad-seq and H-M-Dyad-seq samples were then concentrated to a volume of 28 µL and subjected to nucleobase conversion using the NEBNext enzymatic methyl-seq conversion module (NEB, E7125S) according to the manufacturer’s recommendations except for performing the final elution step in 40 µL of water. For M-H-Dyad-seq and H-H-Dyad-seq samples, nucleobase conversion was performed using the NEBNext enzymatic methyl-seq conversion module similar to what has been described previously11. Briefly, samples were first concentrated to a volume of 17 µL. Then 4 µL of formamide (Sigma-Aldrich, F9037-100ML) was added and the samples were heated to 85°C for 10 minutes before being quenched on ice. APOBEC nucleobase conversion was performed as described by the manufacturer except for two minor changes. Samples were incubated at 37°C for 16 hours, and the final elution step was performed using 40 µL of water.
To all Dyad-seq versions, the nucleobase converted samples were subjected to one round of linear amplification. To do this, 9 µL of amplification mix was added (5.56x NEBuffer 2.1 (NEB, B7202S), 2.22 mM dNTPs (NEB, N0447L), and 2.22 uM Linear amplification 9-mer: 5’- GCCTTGGCACCCGAGAATTCCANNNNNNNNN -3’) and the samples were heated to 95°C for 45 seconds before being quenched on ice. Once cold, 100 U of high concentration Klenow DNA polymerase (3’-5’ Exo-) (fisher scientific, 50-305-912) was added. Then samples were quickly vortexed, centrifuged and then incubated at 4°C for 5 minutes, followed by an increase of 1°C every 15 seconds at a ramp rate of 0.1°C per second till the samples reach 37°C which was then held for an additional 1.5 hours. Afterwards a 1.1x AMPure XP bead cleanup was performed, and the samplers were eluted in 40 µL of water before being concentrated down to 10 µL. The entire sample was then used in a linear PCR reaction by adding 15 µL of PCR mix (1.67x high-fidelity PCR mix (NEB, M0541L) and 0.67 µM Extended RPI primer: 5’- AATGATACGGCGACCACCGAGATCTACACGTTCAGAGTTCTACAGTCCGACGATCGGTGTAGTGGGTTTGG-3’) and performing PCR as follows: Initial denaturing at 98°C for 30 seconds, followed by 16 cycles of 98°C for 10 seconds, 59°C for 30 seconds, and 72°C for 30 seconds, and a final extension step at 72°C for 1 minute. Next, 5 µL of the linear PCR product was amplified further in a standard Illumina library PCR reaction, incorporating a uniquely indexed i7 primer. The remaining linear PCR product was stored at -20°C. To the final sequencing library, two 0.825x AMPure XP bead cleanups were performed with a final elution volume of 15 µL in water. The libraries were then quantified on an Agilent Bioanalyzer and Qubit fluorometer. Finally, libraries were subjected to paired-end 150 bp Illumina sequencing on a HiSeq platform.

value: bulk H-M-Dyad-seq


title: sample.sad1

source_name: SK-BR-3, shADAR1 + shDHX9

value: cell line, breast cancer

value: ADAR1 and DHX9 knockdown

value: transduced with shRNAs for ADAR1 and DHX9


title: M07e_Brg1_rep1

value: Blood


title: sample.mss1


title: CM-PC-TDW-6h-3


title: WSU-AML DMSO_K27me3_rep2

value: WSU-AML

value: leukemia


title: E14 mESC No_RNA-seq

value: E14 mESC

value: 48 Hour in Basal media


title: sample.mas2

source_name: MCF-7, shADAR1 + shSCR

value: ADAR1 knockdown

value: transduced with shRNA for ADAR1 and a scramble control


title: sample.msd1

source_name: MCF-7, shSCR + shDHX9

value: DHX9 knockdown


title: E14 mESC SL_H-H-Dyad-seq

data_processing:
Library strategy: H-H-Dyad-seq
Illumina bcl2fastq2 v 2.20 software used for basecalling
A custom Perl script was used to demultiplex genomic based read barcodes from RNA based read barcodes. This code is available on request. RNA enriched samples were processed for RNA transcripts, while unenriched samples were used to identify site specific 5mC as well as the status of CpG dyads as fully or hemi-methylated.
For genomic site specific 5mC detection (for absolute 5mC (or 5hmC) level calling), exact duplicates were removed using Clumpify from BBTools. A custom Perl script was use to extract the single cell barcode and UMI from each read. Then read 1 and 2 were trimmed using TrimGalore in paired end mode. The 5’ end of read 1 was clipped by 20 bases and the 3’ end of read 2 was hard clipped 34 bases after detection of the PCR amplification sequence CCACATCACCCAAACC to remove potential bias from enzymatic digestion and to avoid recounting CpG dyad detections utilized in the maintenance measurement. The 5’ end of read 2 was clipped by 9 bases to remove potential bias from the linear amplification 9-mer. The 3’ end of read 1 was also hard clipped 9 bases after detection of the Illumina adapter was performed. Each read was mapped individually using Bismark v0.21.0 in conjunction with Bowtie2 v2.3.5 to MM10 or hg19 for mouse or human samples, respectively. Using Bismark, both resulting sam files were deduplicated further using UMI, cell barcode and mapping location. The bismark_methylation_extractor tool was then used to extract detected cytosines. After which custom Perl code was used to connect detected cytosines to their respective cell. CpG detection files from the same DNA strand for read 1 and read 2 were then combined and any duplicate detections where the same cytosine was read in both read 1 and read 2 were removed using the UMI. Custom codes for analyzing Dyad-seq data and the accompanying documentation is provided with this work.
For genomic CpG Dyad specific calling (for 5mCpG (or 5hmC) maintenance calling), Read 1 was trimmed to 86 bases. Then exact duplicates were removed using Clumpify from BBTools. A custom Perl script was use to extract the single cell barcode and UMI from each read. Then read 1 was trimmed using the default settings of TrimGalore. Read 1 was mapped using Bismark v0.21.0 in conjunction with Bowtie2 v2.3.5 to MM10 or hg19 for mouse or human samples, respectively. Using Bismark, both resulting sam files were deduplicated further using UMI, cell barcode and mapping location. For library preparation using MspJI, a custom Perl script was used to identify 5mC positions in the genome as detected by MspJI and interrogate the methylation status of the opposing cytosine in a CpG or CpHpG dyad context from the nucleobase conversion. For library preparation using AbaSI, a custom Perl script was used to identify 5hmC positions in the genome as detected by AbaSI and interrogate the methylation status of the opposing cytosine in a CpG dyad context from the nucleobase conversion.
For bulk RNA based reads, read 2 sequences were trimmed to 50 bases and mapped in the sense direction to the refseq MM10 transcriptome build supplemented with ERCC mRNA spike-in sequences using bwa v0.7.15 with parameters aln -q 0 -n 0.04 -k 2 -l 200 -t 6 -B 12. Any read mapping to multiple loci were distributed uniformly across those loci. Gene isoforms were consolidated into a gene count, and the UMI was used to deduplicate reads from each gene for each individual cell. The number of observations was converted into transcript counts based on binomial statistics as described previously by Grün et al.. Genes that were not detected in at least one cell were discarded from any downstream analysis.
For single cell RNA based reads, Read 2 was trimmed using the default settings of TrimGalore. After trimming, STARsolo (STAR aligner version 2.7.8a) was used to map the reads to MM10 using the gene annotation file from Ensembl . The reads were again mapped to MM10 using the transposable elements annotation file described in TEtranscripts. Transcripts with the same UMI were deduplicated, transcripts detected from genes or transposable elements were analyzed together and any that were not detected in at least one cell were removed from any downstream analysis.
Required code to go from raw FASTQ files to processed data can be found on github at https://github.com/alexchialastri/scDyad-T-seq
Genome_build: MM10 and hg19
Supplementary_files_format_and_content: 5mCpG Dyad maintenance detection files [noted in the naming of the file as *_CGMaintained.txt (for loci detected as maintained {e.g. fully methylated dyads for M-M-Dyad-seq}) and *_CGNonMaintained.txt (for loci detected as not maintained  {e.g. hemi-methylated dyads for M-M-Dyad-seq})] list detected methylated or unmethylated CpG maintenance sites. Column 1 is the cell number (in bulk this is the sample replicate indicator), column 2 is the chromosome (with chr23 indicating the X chromosome, chr24 indicating the Y chromosome, and chr25 indicating a mitocondrial based detection), column 3 is the genomic loci, column 4 is the UMI detected and column 4 is the strand of the detected mark.
Supplementary_files_format_and_content: Absolute 5mCpG detection files [noted in the naming of the file as *_BS-CpG_All.txt or *BS-CpG_All_BothStrands_Unique.txt] list detected methylated or unmethylated CpG sites. Column 1 is the cell number (in bulk this is the sample replicate indicator), column 2 is the chromosome (with chr23 indicating the X chromosome, chr24 indicating the Y chromosome, and chr25 indicating a mitocondrial based detection), column 3 is the genomic loci, column 4 is the the strand of the detected mark, column 5 is the UMI detected and column 6 indicates if the cytosine was methylated (Z) or unmethylated (z) .
Supplementary_files_format_and_content: For Bulk samples RNA-seq gene count files (noted in the naming of the file as *-READ_COUNTS_c.txt.gz) is a matrix with the columns indicating  sample (replicate) number, and each row indicating the number of counts detected for a given gene.
Supplementary_files_format_and_content: Single cell transcript counts contain 6 files. 3 refer to the detection of unique transcripts related to genes (*_Genes_matrix.mtx.gz, *_Genes_features.tsv.gz, and *_Genes_barcodes.tsv.gz) and 3 refer to the detection of unique transcripts related to transposable elements (*_TE_matrix.mtx.gz, *_TE_features.tsv.gz, and *_TE_barcodes.tsv.gz). These set of 3 files are in the standard 10x sparse data matrix format (Market Exchange Format). The *_barcodes.tsv.gz file gives the list of cell barcodes used in the experiment. Note: these are in alphabetical order and not ordered by cell number, see supplementary file ('SingleCell_barcodesOrdered.csv') on main page for which barcodes refer to what cell number. The *_features.tsv.gz file gives the list of gene or transposable elements names. The *_matrix.mtx.gz gives the location and value of non zero elements in gene or transposable elements detection matrix, with column 1 refering to the feature, column 2 to the cell number, and column 3 to the number of transcripts detected.

value: bulk H-H-Dyad-seq


title: CM-PC-TDW-6h-1

value: Leaves

value: WT


title: sample.msd2

value: transduced with shRNA for DHX9 and a scramble control


title: sample.sad2


title: CM-PC-TDW-6h-2


title: E14 mESC SL_M-H-Dyad-seq

data_processing:
Library strategy: M-H-Dyad-seq
Illumina bcl2fastq2 v 2.20 software used for basecalling
A custom Perl script was used to demultiplex genomic based read barcodes from RNA based read barcodes. This code is available on request. RNA enriched samples were processed for RNA transcripts, while unenriched samples were used to identify site specific 5mC as well as the status of CpG dyads as fully or hemi-methylated.
For genomic site specific 5mC detection (for absolute 5mC (or 5hmC) level calling), exact duplicates were removed using Clumpify from BBTools. A custom Perl script was use to extract the single cell barcode and UMI from each read. Then read 1 and 2 were trimmed using TrimGalore in paired end mode. The 5’ end of read 1 was clipped by 20 bases and the 3’ end of read 2 was hard clipped 34 bases after detection of the PCR amplification sequence CCACATCACCCAAACC to remove potential bias from enzymatic digestion and to avoid recounting CpG dyad detections utilized in the maintenance measurement. The 5’ end of read 2 was clipped by 9 bases to remove potential bias from the linear amplification 9-mer. The 3’ end of read 1 was also hard clipped 9 bases after detection of the Illumina adapter was performed. Each read was mapped individually using Bismark v0.21.0 in conjunction with Bowtie2 v2.3.5 to MM10 or hg19 for mouse or human samples, respectively. Using Bismark, both resulting sam files were deduplicated further using UMI, cell barcode and mapping location. The bismark_methylation_extractor tool was then used to extract detected cytosines. After which custom Perl code was used to connect detected cytosines to their respective cell. CpG detection files from the same DNA strand for read 1 and read 2 were then combined and any duplicate detections where the same cytosine was read in both read 1 and read 2 were removed using the UMI. Custom codes for analyzing Dyad-seq data and the accompanying documentation is provided with this work.
For genomic CpG Dyad specific calling (for 5mCpG (or 5hmC) maintenance calling), Read 1 was trimmed to 86 bases. Then exact duplicates were removed using Clumpify from BBTools. A custom Perl script was use to extract the single cell barcode and UMI from each read. Then read 1 was trimmed using the default settings of TrimGalore. Read 1 was mapped using Bismark v0.21.0 in conjunction with Bowtie2 v2.3.5 to MM10 or hg19 for mouse or human samples, respectively. Using Bismark, both resulting sam files were deduplicated further using UMI, cell barcode and mapping location. For library preparation using MspJI, a custom Perl script was used to identify 5mC positions in the genome as detected by MspJI and interrogate the methylation status of the opposing cytosine in a CpG or CpHpG dyad context from the nucleobase conversion. For library preparation using AbaSI, a custom Perl script was used to identify 5hmC positions in the genome as detected by AbaSI and interrogate the methylation status of the opposing cytosine in a CpG dyad context from the nucleobase conversion.
For bulk RNA based reads, read 2 sequences were trimmed to 50 bases and mapped in the sense direction to the refseq MM10 transcriptome build supplemented with ERCC mRNA spike-in sequences using bwa v0.7.15 with parameters aln -q 0 -n 0.04 -k 2 -l 200 -t 6 -B 12. Any read mapping to multiple loci were distributed uniformly across those loci. Gene isoforms were consolidated into a gene count, and the UMI was used to deduplicate reads from each gene for each individual cell. The number of observations was converted into transcript counts based on binomial statistics as described previously by Grün et al.. Genes that were not detected in at least one cell were discarded from any downstream analysis.
For single cell RNA based reads, Read 2 was trimmed using the default settings of TrimGalore. After trimming, STARsolo (STAR aligner version 2.7.8a) was used to map the reads to MM10 using the gene annotation file from Ensembl . The reads were again mapped to MM10 using the transposable elements annotation file described in TEtranscripts. Transcripts with the same UMI were deduplicated, transcripts detected from genes or transposable elements were analyzed together and any that were not detected in at least one cell were removed from any downstream analysis.
Required code to go from raw FASTQ files to processed data can be found on github at https://github.com/alexchialastri/scDyad-T-seq
Genome_build: MM10 and hg19
Supplementary_files_format_and_content: 5mCpG Dyad maintenance detection files [noted in the naming of the file as *_CGMaintained.txt (for loci detected as maintained {e.g. fully methylated dyads for M-M-Dyad-seq}) and *_CGNonMaintained.txt (for loci detected as not maintained  {e.g. hemi-methylated dyads for M-M-Dyad-seq})] list detected methylated or unmethylated CpG maintenance sites. Column 1 is the cell number (in bulk this is the sample replicate indicator), column 2 is the chromosome (with chr23 indicating the X chromosome, chr24 indicating the Y chromosome, and chr25 indicating a mitocondrial based detection), column 3 is the genomic loci, column 4 is the UMI detected and column 4 is the strand of the detected mark.
Supplementary_files_format_and_content: Absolute 5mCpG detection files [noted in the naming of the file as *_BS-CpG_All.txt or *BS-CpG_All_BothStrands_Unique.txt] list detected methylated or unmethylated CpG sites. Column 1 is the cell number (in bulk this is the sample replicate indicator), column 2 is the chromosome (with chr23 indicating the X chromosome, chr24 indicating the Y chromosome, and chr25 indicating a mitocondrial based detection), column 3 is the genomic loci, column 4 is the the strand of the detected mark, column 5 is the UMI detected and column 6 indicates if the cytosine was methylated (Z) or unmethylated (z) .
Supplementary_files_format_and_content: For Bulk samples RNA-seq gene count files (noted in the naming of the file as *-READ_COUNTS_c.txt.gz) is a matrix with the columns indicating  sample (replicate) number, and each row indicating the number of counts detected for a given gene.
Supplementary_files_format_and_content: Single cell transcript counts contain 6 files. 3 refer to the detection of unique transcripts related to genes (*_Genes_matrix.mtx.gz, *_Genes_features.tsv.gz, and *_Genes_barcodes.tsv.gz) and 3 refer to the detection of unique transcripts related to transposable elements (*_TE_matrix.mtx.gz, *_TE_features.tsv.gz, and *_TE_barcodes.tsv.gz). These set of 3 files are in the standard 10x sparse data matrix format (Market Exchange Format). The *_barcodes.tsv.gz file gives the list of cell barcodes used in the experiment. Note: these are in alphabetical order and not ordered by cell number, see supplementary file ('SingleCell_barcodesOrdered.csv') on main page for which barcodes refer to what cell number. The *_features.tsv.gz file gives the list of gene or transposable elements names. The *_matrix.mtx.gz gives the location and value of non zero elements in gene or transposable elements detection matrix, with column 1 refering to the feature, column 2 to the cell number, and column 3 to the number of transcripts detected.

value: Grown in Serum + LIF media

value: bulk M-H-Dyad-seq


title: WSU-AML DMSO_k27me3_rep1


title: sample.mas1

value: cell line, breast cancer


title: CM-PC-TDW-4h-3


title: E14 mESC No_M-H-Dyad-seq


title: E14 mESC SL_M-M-Dyad-seq

data_processing:
Library strategy: M-M-Dyad-seq
Illumina bcl2fastq2 v 2.20 software used for basecalling
A custom Perl script was used to demultiplex genomic based read barcodes from RNA based read barcodes. This code is available on request. RNA enriched samples were processed for RNA transcripts, while unenriched samples were used to identify site specific 5mC as well as the status of CpG dyads as fully or hemi-methylated.
For genomic site specific 5mC detection (for absolute 5mC (or 5hmC) level calling), exact duplicates were removed using Clumpify from BBTools. A custom Perl script was use to extract the single cell barcode and UMI from each read. Then read 1 and 2 were trimmed using TrimGalore in paired end mode. The 5’ end of read 1 was clipped by 20 bases and the 3’ end of read 2 was hard clipped 34 bases after detection of the PCR amplification sequence CCACATCACCCAAACC to remove potential bias from enzymatic digestion and to avoid recounting CpG dyad detections utilized in the maintenance measurement. The 5’ end of read 2 was clipped by 9 bases to remove potential bias from the linear amplification 9-mer. The 3’ end of read 1 was also hard clipped 9 bases after detection of the Illumina adapter was performed. Each read was mapped individually using Bismark v0.21.0 in conjunction with Bowtie2 v2.3.5 to MM10 or hg19 for mouse or human samples, respectively. Using Bismark, both resulting sam files were deduplicated further using UMI, cell barcode and mapping location. The bismark_methylation_extractor tool was then used to extract detected cytosines. After which custom Perl code was used to connect detected cytosines to their respective cell. CpG detection files from the same DNA strand for read 1 and read 2 were then combined and any duplicate detections where the same cytosine was read in both read 1 and read 2 were removed using the UMI. Custom codes for analyzing Dyad-seq data and the accompanying documentation is provided with this work.
For genomic CpG Dyad specific calling (for 5mCpG (or 5hmC) maintenance calling), Read 1 was trimmed to 86 bases. Then exact duplicates were removed using Clumpify from BBTools. A custom Perl script was use to extract the single cell barcode and UMI from each read. Then read 1 was trimmed using the default settings of TrimGalore. Read 1 was mapped using Bismark v0.21.0 in conjunction with Bowtie2 v2.3.5 to MM10 or hg19 for mouse or human samples, respectively. Using Bismark, both resulting sam files were deduplicated further using UMI, cell barcode and mapping location. For library preparation using MspJI, a custom Perl script was used to identify 5mC positions in the genome as detected by MspJI and interrogate the methylation status of the opposing cytosine in a CpG or CpHpG dyad context from the nucleobase conversion. For library preparation using AbaSI, a custom Perl script was used to identify 5hmC positions in the genome as detected by AbaSI and interrogate the methylation status of the opposing cytosine in a CpG dyad context from the nucleobase conversion.
For bulk RNA based reads, read 2 sequences were trimmed to 50 bases and mapped in the sense direction to the refseq MM10 transcriptome build supplemented with ERCC mRNA spike-in sequences using bwa v0.7.15 with parameters aln -q 0 -n 0.04 -k 2 -l 200 -t 6 -B 12. Any read mapping to multiple loci were distributed uniformly across those loci. Gene isoforms were consolidated into a gene count, and the UMI was used to deduplicate reads from each gene for each individual cell. The number of observations was converted into transcript counts based on binomial statistics as described previously by Grün et al.. Genes that were not detected in at least one cell were discarded from any downstream analysis.
For single cell RNA based reads, Read 2 was trimmed using the default settings of TrimGalore. After trimming, STARsolo (STAR aligner version 2.7.8a) was used to map the reads to MM10 using the gene annotation file from Ensembl . The reads were again mapped to MM10 using the transposable elements annotation file described in TEtranscripts. Transcripts with the same UMI were deduplicated, transcripts detected from genes or transposable elements were analyzed together and any that were not detected in at least one cell were removed from any downstream analysis.
Required code to go from raw FASTQ files to processed data can be found on github at https://github.com/alexchialastri/scDyad-T-seq
Genome_build: MM10 and hg19
Supplementary_files_format_and_content: 5mCpG Dyad maintenance detection files [noted in the naming of the file as *_CGMaintained.txt (for loci detected as maintained {e.g. fully methylated dyads for M-M-Dyad-seq}) and *_CGNonMaintained.txt (for loci detected as not maintained  {e.g. hemi-methylated dyads for M-M-Dyad-seq})] list detected methylated or unmethylated CpG maintenance sites. Column 1 is the cell number (in bulk this is the sample replicate indicator), column 2 is the chromosome (with chr23 indicating the X chromosome, chr24 indicating the Y chromosome, and chr25 indicating a mitocondrial based detection), column 3 is the genomic loci, column 4 is the UMI detected and column 4 is the strand of the detected mark.
Supplementary_files_format_and_content: Absolute 5mCpG detection files [noted in the naming of the file as *_BS-CpG_All.txt or *BS-CpG_All_BothStrands_Unique.txt] list detected methylated or unmethylated CpG sites. Column 1 is the cell number (in bulk this is the sample replicate indicator), column 2 is the chromosome (with chr23 indicating the X chromosome, chr24 indicating the Y chromosome, and chr25 indicating a mitocondrial based detection), column 3 is the genomic loci, column 4 is the the strand of the detected mark, column 5 is the UMI detected and column 6 indicates if the cytosine was methylated (Z) or unmethylated (z) .
Supplementary_files_format_and_content: For Bulk samples RNA-seq gene count files (noted in the naming of the file as *-READ_COUNTS_c.txt.gz) is a matrix with the columns indicating  sample (replicate) number, and each row indicating the number of counts detected for a given gene.
Supplementary_files_format_and_content: Single cell transcript counts contain 6 files. 3 refer to the detection of unique transcripts related to genes (*_Genes_matrix.mtx.gz, *_Genes_features.tsv.gz, and *_Genes_barcodes.tsv.gz) and 3 refer to the detection of unique transcripts related to transposable elements (*_TE_matrix.mtx.gz, *_TE_features.tsv.gz, and *_TE_barcodes.tsv.gz). These set of 3 files are in the standard 10x sparse data matrix format (Market Exchange Format). The *_barcodes.tsv.gz file gives the list of cell barcodes used in the experiment. Note: these are in alphabetical order and not ordered by cell number, see supplementary file ('SingleCell_barcodesOrdered.csv') on main page for which barcodes refer to what cell number. The *_features.tsv.gz file gives the list of gene or transposable elements names. The *_matrix.mtx.gz gives the location and value of non zero elements in gene or transposable elements detection matrix, with column 1 refering to the feature, column 2 to the cell number, and column 3 to the number of transcripts detected.

value: bulk M-M-Dyad-seq


title: WSU-AML DMSO_K4me3_rep2


title: E14 mESC No_H-M-Dyad-seq

value: bulk H-M-Dyad-seq


title: WSU-AML DMSO_K4me3_rep1

value: Blood


title: CM-PC-TDW-4h-2


title: sample.mad1

source_name: MCF-7, shADAR1 + shDHX9

value: ADAR1 and DHX9 knockdown

value: transduced with shRNAs for ADAR1 and DHX9


title: CM-PC-TDW-2h-3


title: CM-PC-TDW-4h-1


title: E14 mESC No_H-H-Dyad-seq

value: E14 mESC


title: M07e DMSO_K27me3

value: leukemia


title: TBX3-3xHA_ChIP_Replicate_1

city: Oxford

first: Pakavarin

last: Louphrasitthiphol

address: Old Road Campus Research Building (off Roosevelt Drive)

department: Nuffield Department of Clinical Medicine

country: United Kingdom

institute: Ludwig Institute for Cancer Research

data_processing:
Basecalling, demultiplexing were carried out by the Wellcome Trust Genomic Service, Oxford
Quality of the raw sequencing data was evaluated using FastQC (v.0.11.7)
Adapter contamination removed using CutAdapt (v.2.8) and ampped to the human reference genome (hg38) with Bowtie2 (v.2.3.5)
To create ChIP-seq coverage plots, the locations of the mapped ChIP-seq reads were extended to 150 bp to represent sequenced fragments, renormalized (to reads per million, rpm) and reformatted in the bigWig file format.
Peak calling was performed using MACS2 (v.2.1.2) with a  0.01 q-value threshold. Bowtie2-generated SAM files were compressed to BAM files, indexed using SAMtools (v.1.9), sequentially converted to bigWig files using USCStools (v.373).
Assembly: hg38
Supplementary files format and content: bigWig, narrowPeak (except for Input sample)

source_name: 501mel (RRID:CVCL_4633)

growth_protocol: RPMI-1640, 10% fetal bovine serum,1x penicillin/streptomycin, 37C at 10% CO2.

extract_protocol:
Cells were cross-linked for 10 min by adding formaldehyde (Sigma F8775) to a final concentration of 0.8%, and then quenched for 10 min by adding glycine to a final concentration of 200 mM.  Cells were then washed, scraped, and collected into a 50-mL falcon tube (Corning 430828), and centrifuged at 1500g for 10 min. Cell pellet was lysed in 1 mL of ChIP lysis buffer (50 mM Tris-HCl at pH 8.0, 10 mM EDTA, 10 mM sodium butyrate, 1% SDS, 4× PIC [Roche 05056489001]) and passed through a 100-μm cell strainer before being sonicated for 15 min in a Covaris S220 (peak incident = 145 W, duty factor = 5%, cycle/burst = 200) until 200- to 400-bp fragments were obtained (assessed by 1% agarose gel). The sonicated chromatin was cleared by centrifugation at 13,000g for 10 min and the supernatant was diluted eightfold in ChIP dilution buffer (16.7 mM Tris at pH 8.0, 167 mM NaCl, 1.2 mM EDTA, 1% Triton X-100, 0.01% SDS) before 12 μg of anti-HA antibody (Roche 11666606001) was added, and chromatin was rotated in a 50-mL falcon tube overnight. In parallel, 60 μL of Dynabeads protein G (Invitrogen, 10004D) was washed, resuspended in ChIP dilution buffer, and blocked in 0.5 mg/mL BSA overnight at 4°C. Immunoprecipitation was carried out using blocked Dynabeads for 1 h at 4°C. The beads were washed three times each in low-salt wash buffer (20 mM Tris-HCl at pH 8.0, 150 mM NaCl, 2 mM EDTA, 1% Triton X-100, 0.1% SDS), high-salt wash buffer (20 mM Tris-HCl at pH 8.0, 500 mM NaCl, 2 mM EDTA, 1% Triton X-100, 0.1% SDS), and LiCl wash buffer (10 mM Tris-HCl at pH 8.0, 250 mM LiCl, 1 mM EDTA, 1% sodium deoxycholate, 1% NP-40) with beads transferred to a new DNA LoBind tube (Eppendorf Z666548) with each wash. The beads were eluted in 200 µL of elution buffer (100 mM NaHCO3, 1% SDS). Reversal of cross-linking of chromatin-immunoprecipitated DNA was done overnight at 55°C with addition of NaCl (final concentration 300 mM), 20 µg of RNase A, and 20 µg of Proteinase. Chromatin-immunoprecipitated DNA was recovered using a QIAquick PCR purification kit (Qiagen 28106).
Samples library were prepped and subjected to 150-bp paired-end sequencing using a NovaSeq6000 (Illumina) at the Wellcome Trust Genomic Service, Oxford.

value: 501mel (RRID:CVCL_4633)

value: Melanoma

tag: chip antibody


title: TBX3-3xHA_ChIP_Replicate_2


title: M07e DMSO_K4me3_rep2


title: E14 mESC No_M-M-Dyad-seq

value: 48 Hour in Basal media


title: E14 mESC M_RNA-seq

value: 48 Hour in Basal media + MEKi

value: bulk RNA-seq


title: CM-PC-TDW-2h-1

value: Leaves

value: WT


title: CM-PC-TDW-2h-2


title: M07e DMSO_K4me3_rep1


title: Input_replicate_1

value: Input


title: hESC, vitamin C

city: London

first: Miguel

middle: R

last: Branco

address: 4 Newark Street

institute: Blizard Institute

description:
VC43.vitC
hESC_vitC-43

data_processing:
Adaptors and low-quality base calls were trimmed using Trim Galore with default parameters.
Trimmed reads were mapped using HiSat2 with --no-softclip and --no-unal. Reads with MAPQ<2 were removed.
Raw read counts for each gene were extracted using Seqmonk's RNA-seq quantitation pipeline.
Gene expression values for each sample were generated using the variance-stabilizing transformation in DESeq2.
Transposable element subfamily counts were generated using SQuIRE
Assembly: mm10, hg38
Supplementary files format and content: Matrix containing normalised (variance-stabilizing transformation) gene expression values
Supplementary files format and content: SQuIRE output containing raw and normalised counts for transposable element subfamilies

growth_protocol: Mouse ESCs were grown in 2i medium comprising 50% DMEM/F-12 and 50% neurobasal media, supplemented with N2, B27, beta-mercaptoethanol, 0.1 mM non-essential amino acids, 2 mM GlutaMAX, 1 mM sodium pyruvate, 1000 U/mL ESGRO LIF, 1 µM PD-035901 and 3 µM CHIR-99021. Human ESCs were maintained in conventional medium (KSR/FGF) comprised of DMEM/F-12 with 20% KSR and 10 ng/ml bFGF, supplemented with 2mM l-glutamine, 100 μM 2-mercaptoethanol, 1% MEM non-essential amino acids, and 50 mg/ml Penicillin-Streptomycin.

extract_protocol:
RNA was extracted with Quick-DNA/RNA Miniprep Kit (Zymo Research) and DNAse treated with the TURBO DNA-free Kit (Ambion)
Total RNA samples were processed with the NEBNext rRNA Depletion Kit or mRNA Isolation Kit. Libraries were generated with the NEBNext Ultra II Directional RNA Library Prep Kit for Illumina.

treatment_protocol: Cells were treated with 100 µg/ml of vitamin C for 24 hours, and compared to untreated controls.

value: Embryonic stem cells

value: Vitamin C


title: E14 mESC M_M-H-Dyad-seq

value: bulk M-H-Dyad-seq


title: CM-PC-TDW-1h-3


title: hESC, control

description:
VC43.ctrl
hESC_ctrl-43

value: Control


title: E14 mESC M_H-M-Dyad-seq

value: bulk H-M-Dyad-seq


title: sample.mad2

value: cell line, breast cancer

value: ADAR1 and DHX9 knockdown


title: S3_D2_10PM

first: Shuchang

last: Liu

address: 203 Lothrop Street

data_processing:
Low-quality reads and adapter sequences were trimmed out from the raw sequencing data by tool Trimmomatic.
Surviving reads were then aligned to human reference genome hg38 by STAR aligner. Gene counts were quantified by STAR --quantMode GeneCounts function.
Assembly: hg38
Supplementary files format and content: Tab file for gene counts

extract_protocol:
Blood samples were then collected every two hours for 48 hours (total 24 samples). Blood was then immediately processed in the Center for Human Integrative Physiology. Blood was centrifuged (1900 RCF x 10 min) and the buffy coats were collected and immediately snap frozen in liquid nitrogen for storage at -80C.
Illumina prep kit

value: Blood

tag: gender

value: Male

tag: subject

value: 38 hr


title: CM-PC-TDW-1h-2


title: E14 mESC M_H-H-Dyad-seq

value: E14 mESC

tag: conditions

value: bulk H-H-Dyad-seq


title: S3_D2_8PM

value: 36 hr


title: Input_replicate_2

value: 501mel (RRID:CVCL_4633)

value: Melanoma


title: HeLa_polyA_ModSeq_GS_PRUNE1_Mn

city: New Haven

first: Rafael

middle: de Cesaris

last: Araujo Tavares

state: Connecticut

address: 260 Whitney Ave

department: Chemistry

institute: Yale University

data_processing:
ShapeMapper2 (Busan et al.2018)
Mg libraries = untreated samples; Mn libraries = modified samples; use ‘--output-counted-mutations’ flag to output counted mutations
Assembly: MALAT1 (NR_002819.4); PRUNE1 (NM_021222.3)
Supplementary files format and content: profile.txt files = csv containing calculated mutation rates for each nucleotide position in the reference sequence; mutation_counts.txt files = csv containing mutation rate compositions for each nucleotide position in the reference sequence

source_name: HeLa cell line

growth_protocol: Human cell lines were grown in DMEM supplemented with 10% fetal bovine serum and 1X antimycotic-antibiotic at 37 deg C

extract_protocol:
Trizol
cDNA was prepared from polyA-enriched RNA from each source using gene specific primers, along with MarathonRT enzyme in the presence of either Mg or Mn as enzymatic cofactors; gene-specific PCR was done to get targeted amplicons from each cDNA sample (target 1 = MALAT1 lncRNA, target 2 = PRUNE1 mRNA); library preparation was carried out from resulting dsDNA amplicons using the Nextera XT DNA kit

value: cervical cancer

value: HeLa


title: CM-PC-TDW-1h-1

value: Leaves

value: WT


title: E14 mESC M_M-M-Dyad-seq

value: 48 Hour in Basal media + MEKi

tag: strategy

value: bulk M-M-Dyad-seq


title: S3_D2_6PM

value: 34 hr


title: E14 mESC 2i_RNA-seq

tag: cell type

value: 48 Hour in 2i media

value: bulk RNA-seq


title: HeLa_polyA_ModSeq_GS_PRUNE1_Mg

tag: tissue


title: CM-0h-2


title: CM-0h-3


title: S3_D2_4PM

value: Blood

value: 32 hr


title: E14 mESC 2i_M-H-Dyad-seq

value: bulk M-H-Dyad-seq


title: Huh7.5_polyA_ModSeq_GS_PRUNE1_Mn

source_name: Huh7.5 cell line

value: hepatocellular carcinoma


title: CM-0h-1


title: HeLa_polyA_ModSeq_GS_MALAT1_Mn


title: S3_D2_2PM

value: Male

value: 30 hr


title: S3_D2_12PM

value: 28 hr


title: CM_pi_5D-3


title: E14 mESC 2i_H-M-Dyad-seq

value: E14 mESC

value: bulk H-M-Dyad-seq


title: E14 mESC 2i_H-H-Dyad-seq

value: bulk H-H-Dyad-seq


title: CM_pi_5D-2

value: Leaves


title: S3_D2_10AM

value: 26 hr


title: Huh7.5_polyA_ModSeq_GS_MALAT1_Mn


title: S3_D2_8AM

value: 24 hr


title: HeLa_polyA_ModSeq_GS_MALAT1_Mg

value: cervical cancer

value: HeLa


title: E14 mESC G_RNA-seq

value: 48 Hour in Basal media + GSKi


title: CM_pi_5D-1

value: WT


title: Huh7.5_polyA_ModSeq_GS_MALAT1_Mg


title: S3_D2_6AM

value: Blood

value: 46 hr


title: E14 mESC G_M-H-Dyad-seq

value: bulk M-H-Dyad-seq


title: CM_pi_3.5D-3


title: CM_pi_3.5D-2


title: E14 mESC G_H-M-Dyad-seq


title: E14 mESC 2i_M-M-Dyad-seq

value: 48 Hour in 2i media

value: bulk M-M-Dyad-seq


title: S3_D2_2AM

value: Male

value: 42 hr


title: E14 mESC G_H-H-Dyad-seq

value: E14 mESC


title: CM_pi_3.5D-1


title: CM_pi_2D-3


title: Huh7.5_polyA_ModSeq_GS_PRUNE1_Mg

value: hepatocellular carcinoma


title: S3_D2_12AM

value: 40 hr


title: S3_D1_10PM

value: 14 hr


title: CM_pi_2D-2

value: Leaves


title: Seedling, H2AX segregating wild type seedlings (in Col-0)

city: Kannapolis

first: Tzung-Fu

last: Hsieh

state: NC

address: Tzung-Fu Hsieh, 600 Laureate Way

department: Plant and Microbial Biology

institute: North Carolina State University

data_processing:
We used Perl scripts to convert all the Cs in the ‘forward’ reads to Ts, and all the Gs in the ‘reverse’ reads to As. The converted reads were then aligned to the equivalently converted TAIR reference genome, allowing up to two mismatches per read.
We use Perl scripts to recover the original sequence of each mapped read and, for each C (on either strand), count the number of times it was sequenced as a C or a T.
We used a Perl script to calculate fractional methylation (#C/(#C+#T)) within a 50 bp window for each sequence context (CG, CHG, CHH).
Assembly: TAIR8
Supplementary files format and content: whole genome 50bp window gff file
Supplementary files format and content: allele-specific 50bp window gff file

organism: Arabidopsis thaliana

source_name: Seedling

growth_protocol: Long day condition (16 hours light, 8 hours dark) at 23 °C

extract_protocol:
Eight to ten days after pollination (DAP) developing F1 seeds (linear to bending cotyledon stage) were immersed in dissection solution (filter-sterilized 0.3 M sorbitol and 5 mM pH 5.7 MES) on sticky tape and dissected by hand under a stereo-microscope using fine forceps (Fine Science Tools, Inox Dumont #5) and insect mounting pins. The seed coat was discarded, and debris removed by washing collected embryos or endosperm five to six times with dissection solution under the microscope. Genomic DNA was isolated using CTAB method.
Bisulfite sequencing libraries for Illumina sequencing were constructed as in (Ibarra et al 2012) with minor modifications. In brief, about 50 ng of genomic DNA was fragmented by sonication, end repaired and ligated to custom-synthesized methylated adapters (Eurofins MWG Operon) according to the manufacturer’s instructions for gDNA library construction (Illumina).  Adaptor-ligated libraries were subjected to two successive treatments of sodium bisulfite conversion using the EpiTect Bisulfite kit (Qiagen) as outlined in the manufacturer’s instructions. The bisulfite-converted library was split between two 50 ul reactions and PCR amplified using the following conditions: 2.5 U of ExTaq DNA polymerase (Takara Bio), 5 μl of 10X ExTaq reaction buffer, 25 μM dNTPs, 1 μl Primer 1.1 and 1 μl multiplexed indexing primer.  PCR reactions were carried out as follows: 95ºC for 3 minutes, then 14-16 cycles of 95 ºC 30 s, 65 ºC 30 s and 72 ºC 60 s. Enriched libraries were purified twice with AMPure beads (Beckman Coulter) prior to quantification with the Qubit fluorometer (Thermo Scientific) and quality assessment using the DNA Bioanalyzer high sensitivity DNA assay (Agilent).  Sequencing on either the Illumina HiSeq 2000/2500 or HiSeq 4000 platforms was performed at the Vincent J. Coates Genomic Sequencing Laboratory at UC Berkeley.

treatment_protocol: For crossed libraries, crosses were performed between h2ax double mutant and wild type Ler. Crosses between Col-0 and Ler were used as the control.

value: Seedling

value: Segregating WT seedling Col-0

value: bisulfite conversion


title: E14 mESC G_M-M-Dyad-seq

value: 48 Hour in Basal media + GSKi


title: Endosperm, hta5/hta5;HTA3/hta3 x Ler

source_name: Endosperm

value: Endosperm

value: hta5/hta5;HTA3/hta3 x Ler


title: S3_D1_8PM

value: Blood

value: 12 hr


title: Embryo, HTA5/hta5;hta3/hta3 x Ler

source_name: Embryo

value: Embryo

value: HTA5/hta5;hta3/hta3 x Ler


title: CM_pi_2D-1

value: WT


title: E14 mESC D_M_H_AllReps

source_name: E14 mESC

value: 24 Hour in Serum + LIF + 0.05 µM of Decitabine

value: bulk M-H-Dyad-seq


title: E14 mESC D_H_H_AllReps

value: E14 mESC

value: bulk H-H-Dyad-seq


title: CM_pi_1D-3

source_name: Leaves


title: S3_D1_6PM

value: Male

value: 10 hr


title: S3_D2_4AM

value: 44 hr


title: Seedling, h2ax double mutant seedlings (in Col-0)

value: Seedling

value: h2ax double mutant seedlings Col-0


title: E14 mESC D_M-M-Dyad-seq

value: bulk M-M-Dyad-seq


title: Endosperm, h2ax homo X Ler

value: Endosperm

value: h2ax homo X Ler

value: bisulfite conversion


title: S3_D1_4PM

value: Blood

value: 8 hr


title: Endosperm, Segregating WT X Ler

value: Col-0 X Ler


title: CM_pi_1D-2

value: Leaves

value: WT


title: S3_D1_2PM

value: 6 hr


title: E14 mESC BL_RNA-seq

value: E14 mESC

value: 48 Hour in Basal media + LIF

value: bulk RNA-seq


title: Embryo, h2ax homo X Ler

value: Embryo


title: E14 mESC BL_M-H-Dyad-seq

value: bulk M-H-Dyad-seq


title: CM_pi_1D-1


title: S3_D1_12PM

value: Male

value: 4 hr


title: E14 mESC BL_H-M-Dyad-seq

value: bulk H-M-Dyad-seq


title: CM_pi_12h-3


title: Endosperm, HTA5/hta5;hta3/hta3 x Ler

value: Endosperm

value: HTA5/hta5;hta3/hta3 x Ler


title: CM_pi_12h-2


title: Embryo, h2ax double mutant (selfed)

value: h2ax double mutant

value: bisulfite conversion


title: S3_D1_10AM

value: Blood

value: 2 hr


title: E14 mESC BL_H-H-Dyad-seq

value: bulk H-H-Dyad-seq


title: S3_D1_8AM

value: 0 hr


title: CM_pi_12h-1

value: Leaves

value: WT


title: S3_D1_6AM

value: 22 hr


title: Endosperm, h2ax double mutant (selfed)


title: S3_D1_4AM

value: 20 hr


title: CM_pi_6h-3


title: Endosperm, Segregating WT (i.e. is a sister plant to the mutant) - selfed

value: Segregating WT Col-0


title: E14 mESC BL_M-M-Dyad-seq

value: E14 mESC

value: 48 Hour in Basal media + LIF

value: bulk M-M-Dyad-seq


title: H-5

city: Changchun

first: Mindan

last: Sun

address: Street Xinmin 1

country: China

institute: the First Hospital of Jilin University

data_processing:
Index of the reference genome was built using Hisat2 v2.0.5
Paired-end clean reads were aligned to the reference genome using Hisat2 v2.0.5
The mapped reads of each sample were assembled by StringTie (v1.3.3b) (Mihaela Pertea.et al. 2015) in a reference-based approach
FeatureCounts v1.5.0-p3 was used to count the reads numbers mapped to each gene.
FPKM of each gene was calculated based on the length of the gene and reads count mapped to this gene.
Assembly: rn6
Supplementary files format and content: excel file includes raw counts for each sample
Supplementary files format and content: excel file includes FPKM values for each sample

organism: Rattus norvegicus

source_name: kidney

extract_protocol:
RNA was harvested using TRIzol, 0.2ug of total RNA was used for constuction of sequencing libraries.
RNA libraries for RNA-seq were prepared using NEBNextUltraRNALibraryPrepKitforIllumina(NEB,USA,Catalog#:E7530L)

value: kidney

value: Wistar

value: endotracheal drip 6.0 mg/kg/week SiNPs


title: H-4


title: H-3


title: IonXpress_020-D-28_72hr_con

city: Columbus

first: Maciej

last: Pietrzak

state: OH

address: 1800 Cannon Drive, 340C Lincoln Tower

department: Department of Biomedical Informatics College of Medicine

institute: Ohio State University

data_processing:
Torrent Suite Software v 5.2 was used for basecalling, alignment, and mapping validated reads to HG19 transcriptome and AmpliSeq specific bed files.
TMAP: The Torrent Mapping Alignment Program for Ion Torrent Data provides a fast and accurate aligner through the integration of a novel alignment algorithm and three popular algorithms:BWA-short(Li and Durbin, 2009),BWA-long(Li and Durbin, 2010), SSAHA(Ning et al, 2001)
BaseCaller steps include: Remove low-quality reads. From the signal values, create the sequence of bases. Estimate the base quality value for each base. Assign each read to a barcode. Trim the barcode sequence away. Trim extra bases at the 5' end. Filter out reads that are too short.  Filter out reads that do not have the correct library key. Trim the P1 adapter (at the 3' end). Perform quality trimming.
The Torrent Suite software generates counts per transcript as well as normalized reads per million (RPM)
Additional processing using EdgeR and Qiagen Integrated Pathway Analysis (IPA)
Genome_build: Hg19
Supplementary_files_format_and_content: Super-maximal Exact Matching (Li 2012)

source_name: Human alveolar macrophages

growth_protocol: Alveolar macropahges (AMs) were adhered in either a 24-well plate (1.5x105 cells/well) or 96-well plate (5x104 cells/well) in RPMI containing 10% human AB serum and Penicillin G (10,000 U/ml) for 2h. Then, medium was replaced and incubations continued until 24 and 72h to collect culture supernatants and TRIzol-lysed cells to repeat protein and RNA analysis, respectively

extract_protocol:
Cells were lysed in Trizol. Ethanol was added to the Trizol lysate and the mix was applied to Directzol columns (Zymo Research). Colums were washed and RNA eluted per manufacturer instructions.
The AmpliSeq human transcriptome gene expression kit was used to prepare libraries covering 20,803 human transcripts, including coding and non-coding RNA. cDNA was synthesized from 10 ng of total RNA. Targeted amplification, digestion, adapter ligation and cleanup was per protocol. Libraries were quantified withqPCR.

treatment_protocol: Adhered AMs after 2h were infected with luminescence-producing M.tb strain (M.tb-Lux) and the cellular uptake, adaptation, and intracellular growth of M.tb were assessed as relative luminescence units (RLUs) at 2, 24, 48, and 72h using a multiwell plate reader Glomax. For technical reasons, AM uptake and growth assays from donors 1-16 were incubated in 24 well plates, while AMs from donors 17-28 were incubated in 96 well plates.

tag: time point

tag: sample group

value: Control

value: Human alveolar macrophages


title: CM_pi_6h-2

tag: genotype

tag: treatment


title: IonXpress_019-D-28_72hr_Mtb

value: Mtb-infected cells


title: S3_D1_2AM

source_name: Blood

value: Blood

value: Male

value: 18 hr


title: S3_D1_12AM

value: 16 hr


title: Embryo, Segregating WT X Ler

value: Embryo

value: Col-0 X Ler

value: bisulfite conversion


title: CM_pi_6h-1

value: Leaves

value: WT

tag: timepoint


title: CM-TDW_5D-3


title: H-2

tag: strain


title: H-1


title: CM-TDW_5D-2


title: S2_D2_10PM

value: 38 hr


title: IonXpress_018-D-28_24hr_con


title: Embryo, Segregating WT (i.e. is a sister plant to the mutant) - selfed

value: Segregating WT Col-0


title: S2_D2_8PM

value: 36 hr


title: IonXpress_017-D-28_24hr_Mtb


title: NC-5

value: kidney

value: Wistar

value: administered 0.9percent NaCl


title: CM-TDW_5D-1


title: IonXpress_016-D-28_2hr_con

value: Control

value: Human alveolar macrophages


title: S2_D2_6PM

value: Blood

value: 34 hr


title: NC-4


title: CM-TDW_3_5D-3


title: IonXpress_015-D-28_2hr_Mtb

value: Mtb-infected cells


title: NC-3


title: S2_D2_4PM

value: Male

value: 32 hr


title: CM-TDW_3_5D-2


title: NC-2


title: IonXpress_014-D-27_72hr_con


title: CM-TDW_3_5D-1


title: S2_D2_2PM

value: 30 hr


title: NC-1


title: IonXpress_012-D-27_24hr_con


title: IonXpress_013-D-27_72hr_Mtb


title: S2_D2_10AM

value: 26 hr


title: CM-TDW_2D-2

value: Leaves


title: IonXpress_011-D-27_24hr_Mtb


title: S2_D2_8AM

value: 24 hr


title: S2_D2_12PM

value: 28 hr


title: CM-TDW_1D-3

value: WT


title: EDC-MMSCs + LY-364947 biol rep 2

city: Chicago

first: Qiwei

last: Yang

state: IL

address: 5821 S Drexel Ave

department: Obstetrics and Gynecology

institute: The University of Chicago

data_processing:
Base calling was performed using the Illumina NovaSeq 6000 platform
Adapters were trimmed using Trim Galore! (0.6.7)
Trimmed sequences were aligned to the reference genome and projected to the transcriptome using STAR (4.0.2)
Raw gene counts were quantified using Salmon (1.5.2)
Assembly: Rnor_6.0, mapped to Ensembl version 102 transcriptome
Supplementary files format and content: matrix of raw counts with genes in rows and samples in columns

source_name: Rat myometrial stem cells (MMSCs) isolated from Eker rat treated with Diethylstilbestrol (an EDCs)

growth_protocol: Isolated VEH- and EDC-MMSCs were plated in coated flasks (Attachment factor #S006100, Thermo Fisher Scientific, Waltham, MA) and cultured separately in Smooth Muscle Growth Medium-2 BulletKit (complete SmGm media) (CC-3182, Lonza, Walkersville, MD) under hypoxic conditions (37°C, 5% CO2, 2% O2).

extract_protocol:
Total cellular RNA was isolated from frozen MMSCs pellets using TRIzol Reagent (#15596026, Invitrogen, Waltham, MA, USA) following manufacturer instructions.
RNA quality and quantity were assessed using the Agilent bio-analyzer. Strand-specific RNA-SEQ libraries were prepared using a TruSEQ mRNA-SEQ library protocol (Illumina provided). Library quality and quantity were assessed using the Agilent bio-analyzer, and libraries were sequenced using an Illumina NovaSEQ6000 (Illumina provided reagents and protocols).

treatment_protocol: Once VEH- or EDC-MMSCs reached 80% confluence, they were treated with human recombinant TGF-β1 (10 ng/ml, 7754-BH, R&D Systems,) for 48 h or with TGF-β Receptor I inhibitor (2µM, LY-364947, L6293, Sigma, St. Louis, MO, USA) for 24 h, respectively. The vehicle used to dissolve TGF-β1 was 4 mM HCl (SA49, Thermo Fisher Scientific, Waltham, MA, USA) containing 0.1% bovine serum albumin (BSA, A3294, Sigma, St. Louis, MO, USA). Mature human TGF-β1 shares 99% amino acid identity with rat TGF-β1, and it demonstrated cross-species activity [35]. Dimethyl sulfoxide (DMSO, 472301, Sigma, St. Louis, MO, USA) was used as a VEH to dissolve the TGF-β Receptor I inhibitor (final concentration <0.1%). VEH- and EDC-treated MMSCs were washed with PBS, trypsinized, and centrifuged at 500 × g for 5 min. The supernatant was discarded, and the pellets were snap-frozen and stored at -80°C for RNA isolation.

value: MMSCs

value: Eker (Tsc2/wt)

tag: in vivo treatment

value: Diethylstilbestrol (an EDCs)

tag: in vitro treatment

value: TGFβ Receptor I INHIBITOR treatment (LY-364947):2 uM - serum-free media (SmBm) (Sigma cat#L6293)


title: EDC-MMSCs + LY-364947 biol rep 1

tag: time


title: S2_D2_4AM

value: 44 hr


title: CM-TDW_1D-2

data_processing:
A quality control application for high throughput sequence data using FastQC Version 0.11.8
Removes adapter sequences from DNA high-throughput sequencing data using Cutadapt  Version 1.15
A toolkit for the quality control (QC) of next generation sequencing (NGS) data using Trimmomatic Version 0.38
Alignment program for mapping next-generation sequencing reads to Capsicum annuum genome using Hisat2 Version 2-2.1.0
Calculated manually based on the method in the following paper. (Lee, J., Jang, H., Kang, W. H., & Yeom, S. I. (2023). Transcriptome analysis of pepper-phytophthora infestans interaction based on a pipeline of a simplified and effective RNA-seq analysis (PoRAS).)
Assembly: Capsicum annuum v1.6
Supplementary files format and content: tab-delimited text files include the values of FPKM/RPKM for each sample


title: EDC-MMSCs + veh biol rep 3

value: veh:DMSO <0.1% - serum-free media (SmBm)


title: IonXpress_009-D-27_2hr_Mtb

value: Human alveolar macrophages


title: IonXpress_010-D-27_2hr_con

value: Control


title: S2_D2_6AM

value: Blood

value: 46 hr


title: EDC-MMSCs + veh biol rep 2


title: S2_D2_2AM

value: Male

value: 42 hr


title: CM-TDW_1D-1


title: S2_D2_12AM

value: 40 hr


title: CM-TDW_2D-3

value: Leaves


title: IonXpress_008-D-24_2hr_con


title: EDC-MMSCs + LY-364947 biol rep 3


title: CM-TDW_12h-3


title: IonXpress_007-D-24_2hr_Mtb

value: Mtb-infected cells


title: EDC-MMSCs + veh biol rep 1


title: S2_D1_10PM

value: 14 hr


title: CM-TDW_2D-1

value: WT


title: VEH-MMSCs + TGFβ1 biol rep 3

source_name: Rat myometrial stem cells (MMSCs) isolated from Eker rat treated with vehicle (sesame oil)

value: MMSCs

value: vehicle (sesame oil)

value: TGFβ1 treatment:10 ng/ml - serum-free media (SmBm) (TGFb R&D system cat#7754-BH)


title: CM-TDW_12h-2


title: IonXpress_006-D-23_72hr_con


title: S2_D1_8PM

value: 12 hr


title: IonXpress_009-D-24_24hr_Mtb


title: VEH-MMSCs + TGFβ1 biol rep 2

value: Eker (Tsc2/wt)


title: CM-TDW_12h-1


title: IonXpress_005-D-23_72hr_Mtb


title: VEH-MMSCs + TGFβ1 biol rep 1


title: CM-TDW_6h-3


title: S2_D1_6PM

value: 10 hr


title: S2_D1_4PM

value: 8 hr


title: VEH-MMSCs + veh biol rep 3

value: veh: 4mM HCl 0.1 BSA- serum-free media (SmBm)


title: IonXpress_004-D-23_24hr_con

value: Control

value: Human alveolar macrophages


title: IonXpress_003-D-23_24hr_Mtb


title: CM-TDW_6h-2


title: VEH-MMSCs + veh biol rep 2


title: S2_D1_2PM

value: Blood

value: Male

value: 6 hr


title: CM-TDW_6h-1

value: Leaves


title: IonXpress_024-D-26_72hr_con


title: IonXpress_023-D-26_72hr_Mtb

value: Mtb-infected cells


title: VEH-MMSCs + veh biol rep 1


title: S2_D1_12PM

value: 4 hr


title: CM_pi_0-2

value: WT


title: S2_D1_10AM

value: 2 hr


title: CM_pi_0-3


title: IonXpress_022-D-26_24hr_con


title: S2_D1_8AM

value: 0 hr


title: DES-MMSC RRBS

address: 909 S. Wolcott Ave

department: Surgery

institute: University of Illinois at Chicago

data_processing:
Data was trimmed using trimGalore
Data was mapped on rn6 using bismark
DNA methylation ratio was evaluated using Bismark
Genome_build: rn6
Supplementary_files_format_and_content: Bedgraph file format containing DNA methylation ratios at individual CpG sites

source_name: myometrial stem cells from myometrium of  5 month Eker Rats exposed to DES

growth_protocol: Eker rat MMSCs were grown in cell culture plates coated with attachment factor protein. Cells were grown in regular SMBM medium. The cells were maintained at 370C in an incubator in a humidified atmosphere at 2% hypoxia.

extract_protocol: Genomic DNA was isolated using  the Puregene core kit (Qiagen) and futher purified using nucleic acid purification column (Qiagen).

treatment_protocol: DES-MMSC and VEH-MMSC were prepared  from 5 month adult Eker rats myometrium PND 10-12  exposed to DES or VEH respectively. FACS was conducted to isolate MMSCs using Stro-1/CD44 antibodies

value: Myometrial stem cells

value: DES


title: IonXpress_021-D-26_24hr_Mtb


title: VEH-MMSC RRBS

source_name: myometrial stem cells from myometrium of  5 month Eker Rats exposed to VEH

value: VEH


title: S2_D1_6AM

value: 22 hr


title: CM_pi_0-1