title: TT-seq-293T-TMPYP4-rep2

description: TT-seq  analysis with 293T TMPyP4 treatment

data_processing:
Library strategy: TT-seq
G4 ChIP-seq reads were aligned to the human genome (UCSC hg38) with Bowtie  version 1.1.2 (Langmead et al. 2009), allowing only uniquely mapping reads with up to three  mismatches within the 150 bp reads. The resulting reads were extended to 200 bp toward the interior  35of the sequenced fragments and normalized to the total reads using for alignment (reads per million,  r.p.m.). Peaks were called using MACS2 (model-based analysis of ChIP-Seq) version 2.1.2 (Zhang  et al. 2008) with default parameters and a q-value cutoff of 0.001. To perform the motif analysis, the  summits of the called G4 ChIP-seq peaks were extended to 50 bp to fetch the DNA sequences, and  MEME-ChIP (Bailey et al. 2009) was used.
ChIP-seq reads were aligned to the human genome (UCSC hg38) with Bowtie version 1.1.2, allowing only uniquely mapping reads with up to two mismatches within the 150 bp reads (Langmead et al. 2009). The resulting reads were extended to 200 bp toward the interior of the sequenced fragments and normalized to the total reads used for aligning (reads per million, r.p.m.).The aligned human BAM files were normalized to the total aligned reads and converted to bigwig files for visualization in the UCSC genome browser. Peaks were called using MACS2 (model-based analysis of ChIP-Seq) version 2.1.2 with default parameters (Zhang et al. 2008) and were annotated with ChIPseeker (Yu et al. 2015). Heatmap and metagene plots were made for the indicated windows around the transcription start site (TSS) using the average coverage (r.p.m.).
ChIP signals were normalized by the normalization factors as previous reported (Orlando et al. 2014).
CUT&Tag reads were aligned to the human genome (UCSC hg38) with Bowtie version1.1.2, allowing only uniquely mapping reads with up to three mismatches within the 150 bp reads.The aligned reads were normalized to total reads aligned (reads per million, r.p.m.). The track files were made with the bamCoverage command from deeptools 3.3.0 (Ramírez et al. 2014). Peaks were called using MACS (model-based analysis of ChIP-Seq) version 2.1.2 using default parameters and a q-value cutoff of 1E-5. The distribution of G4 peaks were annotated with ChIPpeakAnno. Heatmap  and metagene plots were made for the indicated windows around the transcription start site (TSS) using the average coverage (r.p.m.).
ATAC-seq reads were aligned to human genome hg38 and E. coli genome. Alignments were processed with Bowtie with command option of –m 1 –v2,  allowing only uniquely mapping reads with up to two mismatches within the 50 bp read. E. coli reads were used as spike-in controls for normalization of the ATAC-seq signals.
KAS-seq reads were aligned to the human genome (UCSC hg38) with Bowtie version 1.1.2, allowing only uniquely mapping reads with up to two mismatches within the 50 bp reads (Langmead et al. 2009). The resulting reads were normalized to the total reads used for alignment (reads per million, r.p.m.) and converted to bigwig files for visualization in the UCSC genome browser. Heatmap and metagene plots were made for the indicated windows around the transcription start site (TSS) using the average coverage (r.p.m.).
TT-seq reads were aligned to the human genome(UCSC hg38) and Drosophila dm6 genome, respectively. Alignments were processed with HISAT2,allowing only uniquely mapping reads with up to three mismatches within the 150 bp reads. The 42resulting reads were normalized to the total reads used for alignment (reads per million, r.p.m) for each strand. The read counts across each gene were counted with HT-seq with the union mode, and DESeq2 were used to perform the differentially gene expression analysis (Love et al. 2014). To estimate the fold changes based on the Drosophila spike-in RNA, size factors were calculated on the counts of the Drosophila genes and applied to the human gene counts prior to fold change estimation with DESeq2. The heatmap was generated by R package 3.4.3 with normalized counts from DESeq2.
qPRO-seq reads were aligned to the human hg38 genome. The resulting reads were normalized to the total reads used for alignment (reads per million, r.p.m.) and converted to bigwig files for visualization in the UCSC genome browser. Heatmap and metagene plots were made for the indicated windows using the average coverage (r.p.m.).
WGS reads were aligned to the human genome (UCSC hg38) using Bowtie2 version 2.2.6 with the following parameters: --local  --sensitive-local. The resulting reads were extended to 200 bp toward the interior 35 of the sequenced fragments and normalized to the total reads using for alignment (reads per million,r.p.m.).
Genome_build: Homo sapiens .hg38
Genome_build: Mus musculus.mm10
Genome_build: Escherichia coli K-12 substr. MG1655
Genome_build: Drosophila melanogaster.dm6
Supplementary_files_format_and_content: Library normalized bigWig files were provided for all samples


title: Hypoxia_input

status: Public on Jul 19 2021

type: SRA

city: BeiJing

first: Kai

last: Li

address: Yi He Yuan Street No.5

department: School of Life Science

country: China

institute: Peking University

description: RNA-seq

library_source: transcriptomic

data_processing:
Trim_galore (version0.6.6 http://www.bioinformatics.babraham.ac.uk/projects/trim_galore/) for quality control and adaptor trimming. The minimum quality threshold was set to 20, and the reads length is 25~60nt. The remaining reads were further processed by removing the first 10 nt random barcode in the 5’ end.
Processed reads were mapped to hg19 (UCSC refseq hg19).
The gene expression level was quantified as FPKM by Cufflinks.
Genome_build: hg19, UCSC Genome Browser
Supplementary_files_format_and_content: bigWig files, csv files

molecule: polyA RNA

organism: Homo sapiens

extract_protocol:
Total RNA was extracted from tissues using TRIzol reagent (Invitrogen,15596018), followed by DNase I (NEB, M0303L) treatment to remove DNA contamination.
Additional phenol-chloroform isolation and ethanol precipitation treatment was performed to remove enzyme contamination. Total RNA was fragmented into ~130-nucleotide-long fragments by magnesium RNA fragmentation buffer (NEB, E6150S). The fragmentation was stopped by adding RNA fragmentation stop solution followed by ethanol precipitation. 8ng of fragmented total RNA was used as input and remained RNA was used to do the m6A-seq. The libraries were sequenced on Illumina Hiseq X10 with paired-end 150 bp read length.

tag: cell line

tag: cell type

value: human embryonic kidney

tag: treatment


title: Hypoxia_FTO_m6AIP-rep2

description: In vitro demethylation treatment


title: TT-seq-293T-DMSO-rep2

city: Wuhan

first: Yin

last: Zhinang

state: Hubei

address: Donghu road 185

institute: Wuhan University

description: TT-seq  analysis with 293T

molecule: total RNA

growth_protocol: HEK293T, HeLa, U937 and SW1271 cells were obtained from ATCC and cultured at 37°C with 5% CO 2 . HEK293T and HeLa cells were maintained in DMEM (Life Technologies) supplemented with 10% fetal bovine serum (FBS; LONSERA). U937 and SW1271 cells were maintained in RPMI-1640 and DMEM-F12 medium (Life Technologies), respectively. MDA-231-LM2 (LM2) cells were cultured in DMEM supplemented with 10% FBS.Drosophila S2 cells were obtained from Invitrogen and maintained in Schneider's medium. Mouse embryonic fibroblasts (MEF) cells were maintained in DMEM with 10% FBS.

extract_protocol:
Total RNA was extracted using Trizol.
G4 ChIP-seq was performed according to a previously published protocol (Hansel-Hertsch et al.2018) with minor modifications. After fixation and chromatin shearing, 0.25% Triton X-100 was added to the chromatin and centrifuged at 20,000 g for 10 minutes to remove the insoluble debris.12.5 μl chromatin was immunoprecipitated with 800 ng BG4 antibodies and pre-blocked 5μl Anti-DYKDDDDK affinity beads (Smart-Lifesciences) sequentially. The beads were washed with 200 μl wash buffer (10 mM Tris-HCl at pH 7.4, 100 mM KCl, 0.1% Tween-20) at a 37°C rotating incubator (1,400 rpm) for 10 minutes. The captured DNA was eluted and reverse-crosslinked with 75 μl TE buffer and 1 μl 200 mg/mL proteinase K by incubation under rotation (1,400 rpm) for 1 hour at 37°C and then for 2 hours at 65°C. The DNA was further purified with phenol-chloroform extraction and ethanol precipitation. The G4 ChIP-seq libraries were prepared with the NEBNext ultra II DNA library prep kit for Illumina. The libraries were analyzed on an Agilent bioanalyzer and sequenced on a NovaSeq 6000.
Chromatin immunoprecipitation sequencing (ChIP-seq) was performed as previously described (Liang et al., 2015). Briefly, 1×107 cells were fixed with 1% paraformaldehyde in PBS for 10 minutes and then quenched with 0.125 M glycine for 5 minutes at room temperature. Fixed cells were sequentially lysed with 10 mL lysis buffer 1 (50 mM HEPES-KOH, pH 7.5, 140 mM NaCl, 1 mM EDTA, 10% glycerol, 0.5% NP-40, 0.25% Triton X-100, 1× protease inhibitors) and 10 mL lysis buffer 2 (10 mM Tris-HCl, pH 8.0, 200 mM NaCl, 1 mM EDTA, 0.5 mM EGTA, 1× protease inhibitors). The cells were then resuspended in 300 μl lysis buffer 3 (10 mM Tris-HCl, pH 8.0, 100 mM NaCl, 1 mM EDTA, 0.5 mM EGTA, 0.1% Na-Deoxycholate, 0.5% N-lauroylsarcosine, 1× protease inhibitors), and were sheared using the Diagenode Bruptor Plus with the high power mode for 25 cycles (sonication cycle: 30 seconds ON, 30 seconds OFF). After sonication, 1% Triton X-100 was added to the chromatin and centrifuged at 20,000 g for 10 minutes to remove the insoluble debris. The chromatin was immunoprecipitated with 10 μg individual antibodies and 15 μl pre-blocked Protein A/G beads (Smart-Lifesciences). The beads were washed three times with 1 mL lysis buffer 3, and three times with wash buffer (50 mM HEPES-KOH, pH 7.5, 300 mM LiCl, 1 mM EDTA, 1.0% NP-40, 0.7% Na-Deoxycholate). The immunoprecipitated DNA was eluted with 200 μl elution buffer (50 mM Tris-HCl, pH 8.0, 10 mM EDTA, 1.0% SDS, 200 μg/mL proteinase K) at 55°C overnight, and purified by phenol-chloroform extraction and ethanol precipitation. Library preparation was done using the NEBNext ultra II DNA library prep kit for Illumina, followed by sequencing on a NovaSeq 6000.
sonicated human chromatin was spiked-in with 10%-30% mouse chromatin toquantitatively normalize across experiments.
Cleavage Under Targets and Tagmentation (CUT&Tag) was performed as described before (Kaya-Okur et al. 2019; Wang et al. 2019) with some modifications. Briefly, half million cells were washed twice in 1.5 mL wash buffer (20 mM HEPES at pH 7.5, 150 mM KCl, 0.5 mM spermidine, 1× protease inhibitors) by gentle pipetting. 10 μL concanavalin A coated magnetic beads (Smart-Lifesciences) were activated, and added to these cells with a 10 minutes’ incubation at room temperature. The supernatant was removed and bead-bound cells were resuspended in 100 μL dig-wash buffer (20 mM HEPES at pH 7.5, 150 mM KCl, 0.5 mM spermidine, 1× protease inhibitors,0.05% digitonin, 0.01% NP-40) containing 2mM EDTA and a 1:10 dilution of the 0.1 mg/mL BG4 primary antibody. Primary antibody incubation was performed on a rotating platform overnight at 4°C and then the liquid was removed. The Anti-Flag M2 antibody (Sigma-Aldrich) was diluted to 1:100 in 100 μL of dig-wash buffer with 2 mM EDTA, and was incubated with the cells at room temperature for 30 minutes followed by removing the liquid. The rabbit anti-mouse IgG antibody was diluted 100 folds and incubated with the cells for another 1 hour and washed with dig-wash buffer three times. A 1:200 dilution of pA-Tn5 adapter complex (~0.2 μM) was prepared in dig-300 buffer (0.05% digitonin, 20 mM HEPES at pH 7.5, 300 mM KCl, 0.5 mM spermidine, 1× protease 36inhibitors, 0.01% NP-40). 100 μL pA-Tn5 adapter complex was added to the cells with gentle vertexing, and was incubated at room temperature for 1 hour. Cells were washed three times in 200 μL dig-300 buffer to remove unbound pA-Tn5 proteins. Next, bead-bound cells were resuspended in 40 μL tagmentation buffer (10 mM TAPS-NaOH at pH 8.5, 10 mM MgCl 2 , 7.5% DMF) and incubated at 37°C for 1 hour. To stop tagmentation reaction, 1.5 μL 0.5 M EDTA, 0.5 μL 10% SDS and 0.5 μL 20 mg/mL proteinase K were added and incubated at 55°C for 1 hour and then for 15 minutes at 75°C. The DNA was extracted with Sera-Mag carboxylate-modified magnetic beads (GE Healthcare) for library preparation.21 μL DNA was mixed with a universal i5 and a uniquely barcoded i7 primer, and amplified with NEB Q5 high-fidelity 2× master mix. The libraries were purified with 1.1× volume of Sera-Mag carboxylate-modified magnetic beads, and subjected to LabChip DNA analysis and Illumina sequencing.
ATAC-seq was performed as previously described (Corces et al. 2017). Briefly, 2.5×10 4 cells were washed with cold PBS and centrifuged at 600 g for 5 minutes. The cells were resuspended with 50μL cold lysis buffer (10 mM Tris-HCl at pH 7.5, 10 mM NaCl, 3 mM MgCl 2 , 0.1% NP-40, 0.1% Tween-20 and 0.02% digitonin) and incubated on ice for 3 minutes. The cells were furthered added with 200 μL cold resuspension buffer (10 mM Tris-HCl at pH 7.5, 10 mM NaCl and 3 mM MgCl 2 ) and centrifuged at 600 g for 5 minutes. The pellet was resuspended with 12.5 μL resuspension buffer. 10 μL 5× tagmentation buffer (50 mM TAPS-NaOH at pH 8.5 and 25 mM MgCl 2 ), 16.5 μL PBS, 0.5 μL 10% Tween-20, 0.5 μL 1% digitonin, 0.75 μL 37.5 μM pA-Tn5 transposome and 9.5 μLnuclease-free H2O were mixed with 12.5 μL cell suspension. The transposition reaction was performed at 37°C for 60 minutes with mixing at 1,000 rpm. The reaction was stopped by adding 1.5μL 0.5 M EDTA and 0.5 μL 10% SDS, and digested with 1 μL 20 mg/mL proteinase K (Roche) at 65°C for 6 hours. The DNA was further purified with 1× Sera-Mag carboxylate-modified magnetic beads and eluted with 20 μL H 2 O with 0.1% Tween-20. The purified transposed DNA was amplified with NEBNext high-fidelity 2× PCR master mix, Ad1_noMX primer and Ad2.indexing primers. The DNA libraries were size-selected with Sera-Mag carboxylate-modified magnetic beads and sequenced on the NovaSeq 6000 platform.
KAS-seq was performed as reported (Wu et al. 2020a) with minor modifications. Briefly, after drug treatment, HEK293T cells were labeled with 2.5 mM N 3 -kethoxal for 10 minutes. The cells were collected for genomic DNA purification. The extracted genomic DNA was biotinylated with DBCO-PEG 4 -biotin (Sigma-Aldrich) and sonicated with a Diagenode Bruptor Plus with a high power mode for 40 cycles (sonication cycle: 30 seconds ON, 30 seconds OFF). The fragmented N 3 -kethoxal- modified DNA was enriched with the Dynabeads Myone Streptavidin C1 beads (Thermo Fisher) and eluted with nuclease-free water at 95 ̊C for 15 minutes. The elutes were then repaired with the phi29 DNA polymerase (NEB) and random hexamers, and purified with the Sera-Mag carboxylate-modified magnetic beads. The libraries were prepared with the NEBNext ultra II DNA library prep kit. Indexed libraries were pooled and sequenced on an Illumina platform.
TT-seq was performed as described previously (Schwalb et al. 2016; Liang et al. 2018) with minor modifications. 1×10 7 cells were labeled with 400 μM 4-thiouridine (4sU, Sigma-Aldrich) in a CO 2 incubator at 37°C for 10 minutes and were quickly lysed with 4 mL Trizol (Invitrogen). RN

treatment_protocol: 4SU labeling was performed for TT-seq

tag: tissue

value: embryonic kidney

value: DMSO


title: Hypoxia_nonFTO_m7GIP-rep1

description: cap-m7G RNA immunoprecipitation


title: TMPyP4-ATAC-seq-TMPyP4

description: ATAC-seq  analysis with 293T TMPyP4 treatment

library_source: genomic

data_processing:
G4 ChIP-seq reads were aligned to the human genome (UCSC hg38) with Bowtie  version 1.1.2 (Langmead et al. 2009), allowing only uniquely mapping reads with up to three  mismatches within the 150 bp reads. The resulting reads were extended to 200 bp toward the interior  35of the sequenced fragments and normalized to the total reads using for alignment (reads per million,  r.p.m.). Peaks were called using MACS2 (model-based analysis of ChIP-Seq) version 2.1.2 (Zhang  et al. 2008) with default parameters and a q-value cutoff of 0.001. To perform the motif analysis, the  summits of the called G4 ChIP-seq peaks were extended to 50 bp to fetch the DNA sequences, and  MEME-ChIP (Bailey et al. 2009) was used.
ChIP-seq reads were aligned to the human genome (UCSC hg38) with Bowtie version 1.1.2, allowing only uniquely mapping reads with up to two mismatches within the 150 bp reads (Langmead et al. 2009). The resulting reads were extended to 200 bp toward the interior of the sequenced fragments and normalized to the total reads used for aligning (reads per million, r.p.m.).The aligned human BAM files were normalized to the total aligned reads and converted to bigwig files for visualization in the UCSC genome browser. Peaks were called using MACS2 (model-based analysis of ChIP-Seq) version 2.1.2 with default parameters (Zhang et al. 2008) and were annotated with ChIPseeker (Yu et al. 2015). Heatmap and metagene plots were made for the indicated windows around the transcription start site (TSS) using the average coverage (r.p.m.).
ChIP signals were normalized by the normalization factors as previous reported (Orlando et al. 2014).
CUT&Tag reads were aligned to the human genome (UCSC hg38) with Bowtie version1.1.2, allowing only uniquely mapping reads with up to three mismatches within the 150 bp reads.The aligned reads were normalized to total reads aligned (reads per million, r.p.m.). The track files were made with the bamCoverage command from deeptools 3.3.0 (Ramírez et al. 2014). Peaks were called using MACS (model-based analysis of ChIP-Seq) version 2.1.2 using default parameters and a q-value cutoff of 1E-5. The distribution of G4 peaks were annotated with ChIPpeakAnno. Heatmap  and metagene plots were made for the indicated windows around the transcription start site (TSS) using the average coverage (r.p.m.).
ATAC-seq reads were aligned to human genome hg38 and E. coli genome. Alignments were processed with Bowtie with command option of –m 1 –v2,  allowing only uniquely mapping reads with up to two mismatches within the 50 bp read. E. coli reads were used as spike-in controls for normalization of the ATAC-seq signals.
KAS-seq reads were aligned to the human genome (UCSC hg38) with Bowtie version 1.1.2, allowing only uniquely mapping reads with up to two mismatches within the 50 bp reads (Langmead et al. 2009). The resulting reads were normalized to the total reads used for alignment (reads per million, r.p.m.) and converted to bigwig files for visualization in the UCSC genome browser. Heatmap and metagene plots were made for the indicated windows around the transcription start site (TSS) using the average coverage (r.p.m.).
TT-seq reads were aligned to the human genome(UCSC hg38) and Drosophila dm6 genome, respectively. Alignments were processed with HISAT2,allowing only uniquely mapping reads with up to three mismatches within the 150 bp reads. The 42resulting reads were normalized to the total reads used for alignment (reads per million, r.p.m) for each strand. The read counts across each gene were counted with HT-seq with the union mode, and DESeq2 were used to perform the differentially gene expression analysis (Love et al. 2014). To estimate the fold changes based on the Drosophila spike-in RNA, size factors were calculated on the counts of the Drosophila genes and applied to the human gene counts prior to fold change estimation with DESeq2. The heatmap was generated by R package 3.4.3 with normalized counts from DESeq2.
qPRO-seq reads were aligned to the human hg38 genome. The resulting reads were normalized to the total reads used for alignment (reads per million, r.p.m.) and converted to bigwig files for visualization in the UCSC genome browser. Heatmap and metagene plots were made for the indicated windows using the average coverage (r.p.m.).
WGS reads were aligned to the human genome (UCSC hg38) using Bowtie2 version 2.2.6 with the following parameters: --local  --sensitive-local. The resulting reads were extended to 200 bp toward the interior 35 of the sequenced fragments and normalized to the total reads using for alignment (reads per million,r.p.m.).
Genome_build: Homo sapiens .hg38
Genome_build: Mus musculus.mm10
Genome_build: Escherichia coli K-12 substr. MG1655
Genome_build: Drosophila melanogaster.dm6
Supplementary_files_format_and_content: Library normalized bigWig files were provided for all samples

molecule: genomic DNA


title: TMPyP4-ATAC-seq-DMSO

description: ATAC-seq  analysis with 293T


title: TT-seq-293T-DMSO-rep1

description: TT-seq  analysis with 293T


title: Hypoxia_FTO_m6AIP-rep1

description: In vitro demethylation treatment


title: RING1AKO.RING1BAID_SUZ12_IAA_8h_rep3

city: Oxford

first: Paula

last: Dobrinić

address: South Parks Road

department: Department of Biochemistry

country: United Kingdom

institute: University of Oxford

description: RING1AKO_RING1BAID_SUZ12_AUX_8h_rep4_S14

data_processing:
Paired-end reads were aligned to the concatenated mouse (mm10) and spike-in (dm6 for native, hg19 for cross-linked cChIP-seq) genome sequences using Bowtie 2 (“–no-mixed” and “–no-discordant” options). Only uniquely mapped reads were kept for downstream analysis, after removal of PCR duplicates with Sambamba.
To internally calibrate cChIP-seq experiments, we spiked-in a fixed number of control cells (Drosophila SG4 cells for native cChIP-seq and human HEK293T cells for cross-linked cChIP-seq) to each experimental sample
For visualization of cChIP-seq sequencing data and annotation of genomic regions with read counts, uniquely mapped mouse reads were normalized using dm6 or hg19 spike-in as described previously (Furosva et al., 2019). Briefly, mouse reads were randomly subsampled based on the total number of spike-in (dm6 or hg19) reads in each sample. Additionally, to account for possible minor variations in spike-in cell mixing between cChIP-seq replicates, we corrected the subsampling factors by using the ratio of spike-in to mouse total read counts in the corresponding input samples. Prior to merging normalized replicates for visualization and analysis, read coverage across regions of interest (RING1B peaks for RING1B, SUZ12, H2AK119ub1 and H3K27me3, or TSS ± 2.5 kb for total Pol II, Ser5P-Pol II and H3K4me3, or gene bodies for Ser2P) was analyzed using multiBamSummary and plotCorrelation functions from deepTools , confirming a high correlation between replicates (Pearson's correlation coefficient > 0.9). Genome coverage tracks for cChIP-seq were generated using the pileup function from MACS2.
To identify genomic regions bound by PRC1 we performed peak calling using MACS2 (“BAMPE” and “–broad” options) on the RING1B cChIP-seq data with corresponding input samples for background normalization. A set of peaks identified in all biological replicates of untreated PRC1deg cells was used for further analysis, after filtering out several peaks identified following 4 hours of auxin treatment (i.e. following loss of RING1B) and manually removing sequencing artefacts. In total, 7240 stringent RING1B peaks were identified.
Genome_build: mm10
Supplementary_files_format_and_content: bigWig files representing genome coverage for merged replicates of spike-in normalised cChIP-seq.
Supplementary_files_format_and_content: bed file for a set of enrichment peaks for RING1B

organism:
Homo sapiens
Mus musculus

source_name: Mouse embryonic stem cells with human HEK293T cells spike-in, auxin-treated (8h IAA)

growth_protocol: Mouse ESCs were grown on gelatin-coated plates, in Dulbecco’s Modified Eagle Medium (DMEM, Life Technologies) supplemented with 15% fetal bovine serum (FBS, Labtech), 0.5 mM beta-mercaptoethanol (Life Technologies), 2 mM L-glutamine (Life Technologies), 1x penicillin-streptomycin (Life Technologies), 1x non-essential amino acids (Life Technologies) and 10 ng/mL leukemia inhibitory factor. Cells were cultured at 37°C with 5% CO2. For calibration of genomic experiments, we used either Drosophila S2 (SG4) cells, cultured at 25°C in Schneider’s Drosophila Medium (Life Technologies), supplemented with 10% heat-inactivated FBS and 1x penicillin-streptomycin, or human HEK293T cells, cultured at 37°C with 5% CO2, in DMEM supplemented with 10% FBS, 2 mM L-glutamine, 1x penicillin-streptomycin and 0.5 mM beta-mercaptoethanol.

extract_protocol:
For RING1B and SUZ12 cChIP-seq, 5x107 mouse ESCs were first crosslinked with 2 mM disuccinimidyl glutarate (DSG, Thermo Scientific) while rotating for 45 min at 25°C, and then with 1% formaldehyde (methanol-free, Thermo Scientific) for further 15 min. Reactions were quenched by addition of 125 mM glycine. Mouse ESCs were then mixed with 2x106 double-crosslinked HEK293T cells and incubated in lysis buffer (50 mM HEPES pH 7.9, 140 mM NaCl, 1 mM EDTA, 10% glycerol, 0.5% NP-40, 0.25% Triton X-100, 1x PIC) for 10 min at 4°C. The released nuclei were washed (10 mM Tris-HCl pH 8, 200 mM NaCl, 1 mM EDTA, 0.5 mM EGTA, 1x PIC) for 5 min at 4°C. Chromatin was then resuspended in 1 mL of sonication buffer (10 mM Tris-HCl pH 8, 100 mM NaCl, 1 mM EDTA, 0.5 mM EGTA, 0.1% sodium deoxycholate, 0.5% N-lauroylsarcosine, 1x PIC) and sonicated for 30 min using the BioRuptor Pico (Diagenode). Following sonication, Triton X-100 was added to a final concentration of 1%. The supernatant was collected after centrifugation at 20,000 g for 10 min at 4°C. For ChIP, chromatin was diluted 10-fold in ChIP dilution buffer (1% Triton X-100, 1 mM EDTA, 20 mM Tris-HCl pH 8, 150 mM NaCl, 1x PIC) and pre-cleared for 1 h with either protein A agarose beads (Repligen, for RING1B ChIP) or protein A magnetic Dynabeads (Invitrogen, for SUZ12 ChIP) blocked with 1 mg/mL bovine serum albumin (BSA) and 1 mg/mL yeast tRNA. For each ChIP reaction, 1 mL of diluted and pre-cleared chromatin was incubated overnight with the appropriate antibody, either anti-RING1B (CST, D22F2, 3 μl), or anti-SUZ12 (CST, D39F6, 3 μl). Antibody-bound chromatin was captured using blocked protein A beads (agarose for RING1B, magnetic Dynabeads for SUZ12) for at least 2 h at 4°C and collected by centrifugation/on a magnetic rack. ChIP washes were performed as described previously (Farcas et al. 2013). ChIP DNA was eluted in elution buffer (1% SDS, 0.1 M NaHCO3) and cross-linking was reversed overnight at 65°C with 200 mM NaCl and 2 μL RNase A (Sigma). A matched input sample (1/10 of original ChIP reaction) was treated identically. The following day, ChIP samples and inputs were incubated with Proteinase K (Sigma) for 1.5 h at 56°C and purified using ChIP DNA Clean and Concentrator Kit (Zymo Research). For Pol II cChIP-seq, 5x107 mouse ESCs were crosslinked in 1% formaldehyde for 10 min at 25°C and then quenched with 125 mM glycine. Mouse ECSs were mixed with 2x106 single-crosslinked HEK293T cells and incubated in FA-lysis buffer (50 mM HEPES pH 7.9, 150 mM NaCl, 2 mM EDTA, 0.5 mM EGTA, 0.5% NP-40, 0.1% sodium deoxycholate, 0.1% SDS, 10 mM NaF, 1 mM AEBSF, 1x PIC) for 10 min. Chromatin was sonicated for 30 min using the BioRuptor Pico, centrifuged at 20,000 g for 10 min at 4°C, and supernatant taken as chromatin. For ChIP, 300 ug of chromatin was diluted to 1 ml in FA-lysis buffer and pre-cleared for 1 h with protein A agarose beads blocked with 1 mg/mL BSA and 1 mg/mL yeast tRNA. For each ChIP reaction, diluted and pre-cleared chromatin was incubated overnight with the appropriate antibody, anti-Rbp1-NTD (CST, D8L4Y, 15 μl) to detect total Pol II, anti-Rbp1-CTD-Ser5P (CST, D9N5I, 12.5 μl), or anti-Rbp1-CTD-Ser2P (CST, E1Z3G, 12.5 μl). Antibody-bound chromatin was isolated using blocked protein A agarose beads for 3 h at 4°C. Washes were performed with FA-Lysis buffer, FA-Lysis buffer containing 500 mM NaCl, DOC buffer (250 mM LiCl, 0.5% NP-40, 0.5% sodium deoxycholate, 2 mM EDTA, 10 mM Tris–HCl pH 8), followed by two washes with TE buffer pH 8. ChIP DNA was eluted, de-crosslinked and purified as described above, along with the matched input samples. For H2AK119ub1, H3K27me3 and H3K4me3 cChIP-seq, 5x107 mouse ESCs were mixed with 2x107 Drosophila SG4 cells in PBS. The cells were pelleted and nuclei were released by resuspending in ice-cold lysis buffer (10 mM Tris-HCl pH 8, 10 mM NaCl, 3 mM MgCl2, 0.1% NP-40, 5 mM NEM). Nuclei were then washed, and resuspended in 1 mL of MNase digestion buffer (10 mM Tris-HCl pH 8, 10 mM NaCl, 3 mM MgCl2, 0.25 M sucrose, 3 mM CaCl2, 10 mM NEM, 1x PIC). Samples were digested with 150 units of MNase (Fermentas) for 5 min at 37°C, stopped by 4 mM EDTA. The supernatant (S1) was collected following centrifugation at 1500 g for 5 min at 4°C. The remaining pellet was incubated with 300 μl of nucleosome release buffer (10 mM Tris-HCl pH 7.5, 10 mM NaCl, 0.2 mM EDTA, 10 mM NEM, 1x PIC) at 4°C for 1 h, passed five times through a 27G needle, and spun at 1500 g for 5 min at 4°C. The second supernatant (S2) was collected and combined with corresponding S1 supernatant, and stored at -80°C until use. Digestion to predominantly mono-nucleosomal fragments was confirmed by agarose gel electrophoresies of purified DNA. Native chromatin was diluted 10-fold in native ChIP incubation buffer (70 mM NaCl, 10 mM Tris–HCl pH 7.5, 2 mM MgCl2, 2 mM EDTA, 0.1% TritonX-100, 10 mM NEM, 1x PIC). For each ChIP reaction, 1 ml of diluted nucleosomes was incubated overnight at 4°C with the appropriate antibody, anti-H2AK119ub1 (CST, D27C4, 5 μL), anti-H3K27me3 (in-house, 5 μL) or anti-H3K4me3 (in-house, 3 μL). Antibody-bound nucleosomes were captured by incubation for 1 h at 4°C with protein A agarose beads, pre-blocked overnight in native ChIP incubation buffer supplemented with 1 mg/ml BSA and 1 mg/ml yeast tRNA. The beads were then washed four times with native ChIP wash buffer (20 mM Tris–HCl pH 7.5, 2 mM EDTA, 125 mM NaCl, 0.1% TritonX-100) and once with TE buffer pH 8. Immunoprecipitated DNA was eluted using 100 μl of elution buffer (1% SDS, 0.1 M NaHCO3) and purified using ChIP DNA Clean and Concentrator Kit. DNA from a matched input sample (corresponding to 10% of the original ChIP reaction) purified in the same way.
cChIP-seq libraries for both ChIP and input samples were prepared using NEBNext Ultra DNA Library Prep Kit for Illumina (double-crosslinked and native ChIP-seq) or NEBNext Ultra II DNA Library Prep Kit for Illumina (Pol II ChIP-seq), following manufacturer’s guidelines. Samples were indexed using NEBNext Multiplex Oligos. The average size and concentration of all libraries was analysed using the 2100 Bioanalyzer High Sensitivity DNA Kit (Agilent) followed by qPCR using SensiMix SYBR (Bioline, UK) and KAPA Illumina DNA standards (Roche). Libraries were sequenced as 40 bp paired-end reads on the Illumina NextSeq 500.

treatment_protocol: To induce AID-RING1B degradation, water-dissolved auxin (indole-3-acetic acid (IAA), Sigma) was mixed with cell medium to the final concentration of 500 µM and added to PRC1deg cells at designated times before harvesting by trypsinisation. To induce dTAG-SUZ12 degradation, PRC2deg cells were treated with 100 nM dTAG-13 compound for 2 hours.

value: Mouse embryonic stem cells

tag: genotype/variation

value: E14 Rosa26::Tir1; Ring1A-/-; AID-Ring1B

tag: replicate

value: auxin (IAA)

tag: treatment duration

value: 8 hours

tag: spike-in reference organism

value: Homo sapiens

tag: spike-in cell line

tag: chip antibody

tag: antibody info.

value: Cell Signaling Technology (#D39F6 )


title: RING1AKO.RING1BAID_SUZ12_IAA_8h_rep2


title: TMPYP4-KAS-seq-TMPYP4-rep2

description: KAS-seq analysis with 293T TMPyP4 treatment

data_processing:
Library strategy: KAS-seq
G4 ChIP-seq reads were aligned to the human genome (UCSC hg38) with Bowtie  version 1.1.2 (Langmead et al. 2009), allowing only uniquely mapping reads with up to three  mismatches within the 150 bp reads. The resulting reads were extended to 200 bp toward the interior  35of the sequenced fragments and normalized to the total reads using for alignment (reads per million,  r.p.m.). Peaks were called using MACS2 (model-based analysis of ChIP-Seq) version 2.1.2 (Zhang  et al. 2008) with default parameters and a q-value cutoff of 0.001. To perform the motif analysis, the  summits of the called G4 ChIP-seq peaks were extended to 50 bp to fetch the DNA sequences, and  MEME-ChIP (Bailey et al. 2009) was used.
ChIP-seq reads were aligned to the human genome (UCSC hg38) with Bowtie version 1.1.2, allowing only uniquely mapping reads with up to two mismatches within the 150 bp reads (Langmead et al. 2009). The resulting reads were extended to 200 bp toward the interior of the sequenced fragments and normalized to the total reads used for aligning (reads per million, r.p.m.).The aligned human BAM files were normalized to the total aligned reads and converted to bigwig files for visualization in the UCSC genome browser. Peaks were called using MACS2 (model-based analysis of ChIP-Seq) version 2.1.2 with default parameters (Zhang et al. 2008) and were annotated with ChIPseeker (Yu et al. 2015). Heatmap and metagene plots were made for the indicated windows around the transcription start site (TSS) using the average coverage (r.p.m.).
ChIP signals were normalized by the normalization factors as previous reported (Orlando et al. 2014).
CUT&Tag reads were aligned to the human genome (UCSC hg38) with Bowtie version1.1.2, allowing only uniquely mapping reads with up to three mismatches within the 150 bp reads.The aligned reads were normalized to total reads aligned (reads per million, r.p.m.). The track files were made with the bamCoverage command from deeptools 3.3.0 (Ramírez et al. 2014). Peaks were called using MACS (model-based analysis of ChIP-Seq) version 2.1.2 using default parameters and a q-value cutoff of 1E-5. The distribution of G4 peaks were annotated with ChIPpeakAnno. Heatmap  and metagene plots were made for the indicated windows around the transcription start site (TSS) using the average coverage (r.p.m.).
ATAC-seq reads were aligned to human genome hg38 and E. coli genome. Alignments were processed with Bowtie with command option of –m 1 –v2,  allowing only uniquely mapping reads with up to two mismatches within the 50 bp read. E. coli reads were used as spike-in controls for normalization of the ATAC-seq signals.
KAS-seq reads were aligned to the human genome (UCSC hg38) with Bowtie version 1.1.2, allowing only uniquely mapping reads with up to two mismatches within the 50 bp reads (Langmead et al. 2009). The resulting reads were normalized to the total reads used for alignment (reads per million, r.p.m.) and converted to bigwig files for visualization in the UCSC genome browser. Heatmap and metagene plots were made for the indicated windows around the transcription start site (TSS) using the average coverage (r.p.m.).
TT-seq reads were aligned to the human genome(UCSC hg38) and Drosophila dm6 genome, respectively. Alignments were processed with HISAT2,allowing only uniquely mapping reads with up to three mismatches within the 150 bp reads. The 42resulting reads were normalized to the total reads used for alignment (reads per million, r.p.m) for each strand. The read counts across each gene were counted with HT-seq with the union mode, and DESeq2 were used to perform the differentially gene expression analysis (Love et al. 2014). To estimate the fold changes based on the Drosophila spike-in RNA, size factors were calculated on the counts of the Drosophila genes and applied to the human gene counts prior to fold change estimation with DESeq2. The heatmap was generated by R package 3.4.3 with normalized counts from DESeq2.
qPRO-seq reads were aligned to the human hg38 genome. The resulting reads were normalized to the total reads used for alignment (reads per million, r.p.m.) and converted to bigwig files for visualization in the UCSC genome browser. Heatmap and metagene plots were made for the indicated windows using the average coverage (r.p.m.).
WGS reads were aligned to the human genome (UCSC hg38) using Bowtie2 version 2.2.6 with the following parameters: --local  --sensitive-local. The resulting reads were extended to 200 bp toward the interior 35 of the sequenced fragments and normalized to the total reads using for alignment (reads per million,r.p.m.).
Genome_build: Homo sapiens .hg38
Genome_build: Mus musculus.mm10
Genome_build: Escherichia coli K-12 substr. MG1655
Genome_build: Drosophila melanogaster.dm6
Supplementary_files_format_and_content: Library normalized bigWig files were provided for all samples


title: TMPYP4-KAS-seq-TMPYP4-rep1


title: RING1AKO.RING1BAID_SUZ12_IAA_8h_rep1


title: TMPYP4-KAS-seq-DMSO-rep2

description: KAS-seq analysis with 293T


title: RING1AKO.RING1BAID_SUZ12_IAA_4h_rep2

source_name: Mouse embryonic stem cells with human HEK293T cells spike-in, auxin-treated (4h IAA)

value: 4 hours


title: Hypoxia_nonFTO_m6AIP-rep2

description: m6A RNA immunoprecipitation


title: RING1AKO.RING1BAID_SUZ12_IAA_4h_rep3

description: RING1AKO_RING1BAID_SUZ12_AUX_4h_rep4_S13


title: RING1AKO.RING1BAID_SUZ12_IAA_4h_rep1


title: TMPYP4-KAS-seq-DMSO-rep1

description: KAS-seq analysis with 293T


title: heat_shock_nonFTO_m7GIP-rep2

description: cap-m7G RNA immunoprecipitation


title: PDS-CUT-Tag-G4-PDS

description: CUT&Tag analysis with Flag-BG4 and PDS

data_processing:
Library strategy: CUT&Tag
G4 ChIP-seq reads were aligned to the human genome (UCSC hg38) with Bowtie  version 1.1.2 (Langmead et al. 2009), allowing only uniquely mapping reads with up to three  mismatches within the 150 bp reads. The resulting reads were extended to 200 bp toward the interior  35of the sequenced fragments and normalized to the total reads using for alignment (reads per million,  r.p.m.). Peaks were called using MACS2 (model-based analysis of ChIP-Seq) version 2.1.2 (Zhang  et al. 2008) with default parameters and a q-value cutoff of 0.001. To perform the motif analysis, the  summits of the called G4 ChIP-seq peaks were extended to 50 bp to fetch the DNA sequences, and  MEME-ChIP (Bailey et al. 2009) was used.
ChIP-seq reads were aligned to the human genome (UCSC hg38) with Bowtie version 1.1.2, allowing only uniquely mapping reads with up to two mismatches within the 150 bp reads (Langmead et al. 2009). The resulting reads were extended to 200 bp toward the interior of the sequenced fragments and normalized to the total reads used for aligning (reads per million, r.p.m.).The aligned human BAM files were normalized to the total aligned reads and converted to bigwig files for visualization in the UCSC genome browser. Peaks were called using MACS2 (model-based analysis of ChIP-Seq) version 2.1.2 with default parameters (Zhang et al. 2008) and were annotated with ChIPseeker (Yu et al. 2015). Heatmap and metagene plots were made for the indicated windows around the transcription start site (TSS) using the average coverage (r.p.m.).
ChIP signals were normalized by the normalization factors as previous reported (Orlando et al. 2014).
CUT&Tag reads were aligned to the human genome (UCSC hg38) with Bowtie version1.1.2, allowing only uniquely mapping reads with up to three mismatches within the 150 bp reads.The aligned reads were normalized to total reads aligned (reads per million, r.p.m.). The track files were made with the bamCoverage command from deeptools 3.3.0 (Ramírez et al. 2014). Peaks were called using MACS (model-based analysis of ChIP-Seq) version 2.1.2 using default parameters and a q-value cutoff of 1E-5. The distribution of G4 peaks were annotated with ChIPpeakAnno. Heatmap  and metagene plots were made for the indicated windows around the transcription start site (TSS) using the average coverage (r.p.m.).
ATAC-seq reads were aligned to human genome hg38 and E. coli genome. Alignments were processed with Bowtie with command option of –m 1 –v2,  allowing only uniquely mapping reads with up to two mismatches within the 50 bp read. E. coli reads were used as spike-in controls for normalization of the ATAC-seq signals.
KAS-seq reads were aligned to the human genome (UCSC hg38) with Bowtie version 1.1.2, allowing only uniquely mapping reads with up to two mismatches within the 50 bp reads (Langmead et al. 2009). The resulting reads were normalized to the total reads used for alignment (reads per million, r.p.m.) and converted to bigwig files for visualization in the UCSC genome browser. Heatmap and metagene plots were made for the indicated windows around the transcription start site (TSS) using the average coverage (r.p.m.).
TT-seq reads were aligned to the human genome(UCSC hg38) and Drosophila dm6 genome, respectively. Alignments were processed with HISAT2,allowing only uniquely mapping reads with up to three mismatches within the 150 bp reads. The 42resulting reads were normalized to the total reads used for alignment (reads per million, r.p.m) for each strand. The read counts across each gene were counted with HT-seq with the union mode, and DESeq2 were used to perform the differentially gene expression analysis (Love et al. 2014). To estimate the fold changes based on the Drosophila spike-in RNA, size factors were calculated on the counts of the Drosophila genes and applied to the human gene counts prior to fold change estimation with DESeq2. The heatmap was generated by R package 3.4.3 with normalized counts from DESeq2.
qPRO-seq reads were aligned to the human hg38 genome. The resulting reads were normalized to the total reads used for alignment (reads per million, r.p.m.) and converted to bigwig files for visualization in the UCSC genome browser. Heatmap and metagene plots were made for the indicated windows using the average coverage (r.p.m.).
WGS reads were aligned to the human genome (UCSC hg38) using Bowtie2 version 2.2.6 with the following parameters: --local  --sensitive-local. The resulting reads were extended to 200 bp toward the interior 35 of the sequenced fragments and normalized to the total reads using for alignment (reads per million,r.p.m.).
Genome_build: Homo sapiens .hg38
Genome_build: Mus musculus.mm10
Genome_build: Escherichia coli K-12 substr. MG1655
Genome_build: Drosophila melanogaster.dm6
Supplementary_files_format_and_content: Library normalized bigWig files were provided for all samples

value: PDS

tag: antibody


title: heat_shock_nonFTO_m7GIP-rep1

description: cap-m7G RNA immunoprecipitation


title: PDS-ChIP-Rx-Pol2-PDS

description: ChIP-seq analysis with RPB1 and PDS


title: heat_shock_nonFTO_m6AIP-rep2

description: m6A RNA immunoprecipitation


title: PDS-ChIP-Rx-Pol2-DMSO

description: ChIP-seq analysis with RPB1


title: RING1AKO.RING1BAID_SUZ12_IAA_2h_rep3

description: RING1AKO_RING1BAID_SUZ12_AUX_2h_rep4_S12

source_name: Mouse embryonic stem cells with human HEK293T cells spike-in, auxin-treated (2h IAA)

value: 2 hours


title: heat_shock_nonFTO_m6AIP-rep1

description: m6A RNA immunoprecipitation


title: PDS-ChIP-Rx-NELF-PDS

description: ChIP-seq analysis with NELF and PDS

value: NELF


title: TMPyP4-CUT-Tag-G4-TMPYP4-REP2

description: CUT&Tag analysis with Flag-BG4 and TMPyP4


title: TMPyP4-CUT-Tag-G4-TMPYP4-REP1


title: PDS-ChIP-Rx-NELF-DMSO

description: ChIP-seq analysis with NELF


title: heat_shock_FTO_m6AIP-rep2

description: In vitro demethylation treatment


title: TMPyP4-CUT-Tag-G4-DMSO-REP1

description: CUT&Tag analysis with Flag-BG4


title: TMPyP4-ChIP-Rx-RPB2-DMSO

description: ChIP-seq analysis with RPB2


title: TMPyP4-ChIP-Rx-RPB2-TMPyP4

description: ChIP-seq analysis with RPB2 and TMPyP4


title: PCIF1KO_nonFTO_m7GIP

description: m6A RNA immunoprecipitation


title: TT-seq-293T-TMPYP4-rep1


title: RING1AKO.RING1BAID_SUZ12_UNT_rep3

source_name: Mouse embryonic stem cells with human HEK293T cells spike-in, untreated control

value: 0 hours


title: RING1AKO.RING1BAID_SUZ12_IAA_2h_rep1


title: PCIF1KO_nonFTO_m6AIP

description: m6A RNA immunoprecipitation


title: RING1AKO.RING1BAID_SUZ12_IAA_2h_rep2


title: TMPyP4-CUT-Tag-G4-DMSO-REP2

description: CUT&Tag analysis with Flag-BG4


title: RING1AKO.RING1BAID_SUZ12_UNT_rep2


title: PDS-CUT-Tag-G4-DMSO

description: CUT&Tag analysis with Flag-BG4


title: TMPyP4-ChIP-Rx-RPB1-DMSO

description: ChIP-seq analysis with RPB1


title: RING1AKO.RING1BAID_SUZ12_UNT_rep1


title: TMPyP4-ChIP-Rx-RPB1-TMPyP4

description: ChIP-seq analysis with RPB1 and TMPyP4


title: TMPyP4-ChIP-Rx-NELF-TMPyP4

description: ChIP-seq analysis with NELF and TMPyP4


title: RING1AKO.RING1BAID_RING1B_IAA_4h_rep2

description: RING1AKO_RING1BAID_RING1B_AUX_4h_rep3_S25

value: Cell Signaling Technology (#D22F2 )


title: Flavopiridol-CUT-Tag-G4-FP

description: CUT&Tag analysis with Flag-BG4 and Flavopiridol

value: Flavopiridol


title: heat_shock_input

description: RNA-seq


title: PCIF1KO_input

description: RNA-seq

value: input


title: RING1AKO.RING1BAID_RING1B_IAA_4h_rep1

description: RING1AKO_RING1BAID_RING1B_AUX_4h_rep1_S21


title: Flavopiridol-CUT-Tag-G4-DMSO

description: CUT&Tag analysis with Flag-BG4


title: PCIF1KO_FTO_m6AIP

description: In vitro demethylation treatment

value: human embryonic kidney


title: Flavopiridol-ChIP-Rx-RPB1-FP

description: ChIP-seq analysis with RPB1 and Flavopiridol

value: embryonic kidney


title: heat_shock_FTO_m6AIP-rep1

description: In vitro demethylation treatment


title: Flavopiridol-ChIP-Rx-RPB1-DMSO

description: ChIP-seq analysis with RPB1

value: DMSO


title: SW1271-CUT-Tag-BG4

description: G4 CUT&Tag analysis with Flag-BG4 antibody

value: lung carcinoma


title: RING1AKO.RING1BAID_RING1B_IAA_2h_rep3

description: RING1AKO_RING1BAID_RING1B_AUX_2h_rep4_S28

value: Mouse embryonic stem cells

value: E14 Rosa26::Tir1; Ring1A-/-; AID-Ring1B


title: RING1AKO.RING1BAID_RING1B_IAA_4h_rep3

description: RING1AKO_RING1BAID_RING1B_AUX_4h_rep4_S29

value: auxin (IAA)


title: RING1AKO.RING1BAID_RING1B_IAA_2h_rep2

description: RING1AKO_RING1BAID_RING1B_AUX_2h_rep3_S24

value: Homo sapiens


title: LM2-CUT-Tag-BG4


title: HEK293T_input-rep1

description: RNA-seq


title: K562-CUT-Tag-BG4

value: Chronic Myelogenous Leukemia


title: HEK293T_input-rep2

description: RNA-seq


title: HeLa-CUT-Tag-BG4

source_name: HeLa

value: uterus adenocarcinoma


title: RING1AKO.RING1BAID_RING1B_UNT_rep3


title: HEK293T_nonFTO_m7GIP-rep2

description: cap-m7G RNA immunoprecipitation


title: HEK293T_nonFTO_m7GIP-rep1

description: cap-m7G RNA immunoprecipitation


title: IRI_K8

city: Chicago

first: Pinelopi

last: Kapitsinou

state: Il

address: 303 East Superior Street

department: Medicine/Nephrology

country: USA

institute: Northwestern University, Feinberg School of Medicine

data_processing:
Constructed sequencing libraries were subject to sequencing with Illumina NovaseqTM 6000 platform (paired-end, 150 bp). Prior to assembly, reads containing sequencing adaptors, reads containing sequencing primers, and sequences with q quality score lower than 20 were removed
The cleaned sequencing reads were aligned to reference genome [ftp://ftp.ensembl.org/pub/release-96/fasta/mus_musculus/dna/] using HISAT2 package. Multiple alignments were allowed for each read sequence (up to 20 by default), with a maximum of two mismatches allowed.
Aligned reads of individual samples were assembled using StringTie. Transcriptomes from all samples were then merged to reconstruct a comprehensive transcriptome using a proprietary Perl script of LC Sciences (Houston, Texas, U.S.A.). Following transcriptome reconstruction, FPKM reads were evaluated by StringTie, and differential expressed genes were evaluated by edgeR.
Supplementary_files_format_and_content: Matrix table with raw gene counts for every gene and every sample

organism: Mus musculus

source_name: kidney

extract_protocol:
Kidneys were removed, flash frozen on liquid nitrogen, and RNA was harvested using Trizol reagent. Poly(A) RNA sequencing library was prepared following Illumina’s TruSeq-stranded-mRNA sample preparation protocol
RNA libraries were prepared for sequencing using standard Illumina protocols

tag: strain

value: post IRI kidney

tag: age

value: 8 weeks

value: subjected to normoxia prior to IRI


title: IRI_K7


title: RING1AKO.RING1BAID_RING1B_UNT_rep2

value: 0 hours


title: IRI_K6


title: RING1AKO.RING1BAID_RING1B_IAA_2h_rep1

description: RING1AKO_RING1BAID_RING1B_AUX_2h_rep1_S20

value: 2 hours

value: Cell Signaling Technology (#D22F2 )


title: Histone-ChIP-seq-293T-POLII

description: ChIP-seq analysis with POLII

value: POLII


title: TMPyP4-ChIP-Rx-NELF-DMSO

description: ChIP-seq analysis with NELF

value: NELF


title: Histone-ChIP-seq-293T-H3K4me3-rep2

description: ChIP-seq analysis with H3K4me3

value: embryonic kidney


title: HEK293T_nonFTO_m6AIP-rep1

description: m6A RNA immunoprecipitation

value: human embryonic kidney


title: IRI_K5


title: Histone-ChIP-seq-293T-H3K4me3-rep1

description: ChIP-seq analysis with H3K4me3


title: RING1AKO.RING1BAID_RING1B_UNT_rep1


title: bz_IP_rep3

city: Indianapolis

first: Michael

middle: James

last: Holmes

state: IN

address: 635 Barnhill Drive

department: Pharmacology & Toxicology

institute: Indiana University School of Medicine

data_processing:
Library strategy: MeRIP-seq
remove adapters with trim galore! V0.6.3
in silico deplete rRNA and tRNA with bowtie2 v2.3.4.3
alignment with HISAT2 v2.1.0
gene counts with htseq-count v0.9.1
quantification of RNAseq data with DESEQ2 v2.11.40.6
peaks call from bams with MeTPeak (v1.1; PMID: 27307641) and MeTDiff (v1.1.0; PMID: 29610101)
Genome_build: TGME49_v45 (available at toxodb.org)
Supplementary_files_format_and_content: arrayed count table, tab delimited text file
Supplementary_files_format_and_content: peak text files

organism: Toxoplasma gondii

source_name: early bradyzoites

growth_protocol: parasites grown in confluent human foreskin fibroblasts

extract_protocol:
RNA extracted from purified parasites with Trizol. polyA enriched RNA was randomly fragmented (fraction stored for input) and incubated with m6A antibody for enrichment.
libraries prepared with KAPA Stranded RNAseq kit as per manufacturer

treatment_protocol: tachyzoites grown in DMEM + 1% FBS, 5% CO2; early bradyzoites grown in RPMI + 5% FBS, ambient CO2

value: alpha-m6A (Synaptic Systems, 202003)


title: HEK293T_FTO_m6AIP-rep1

description: In vitro demethylation treatment


title: Histone-ChIP-seq-293T-H3K4me2-rep2

description: ChIP-seq analysis with H3K4me2


title: HxIRI_K3

value: subjected to hypoxia prior to IRI


title: bz_IP_rep2


title: Histone-ChIP-seq-293T-H3K4me2-rep1

description: ChIP-seq analysis with H3K4me2


title: HEK293T_FTO_m6AIP-rep2

description: In vitro demethylation treatment


title: bz_IP_rep1


title: HxIRI_Ki2


title: HxIRI_Ki1


title: Histone-ChIP-seq-293T-H3K4me1-rep1

description: ChIP-seq analysis with H3K4me1


title: tz_IP_rep2

source_name: tachyzoites


title: Histone-ChIP-seq-293T-H3K27ac

description: ChIP-seq analysis with H3K27ac


title: tz_IP_rep1


title: wt-3 [RNA-seq]

city: La Jolla

first: Anjana

last: Rao

state: California

address: 9420 Athena Cir

department: Signaling and Gene Expression

institute: La Jolla Institute for Allergy and Immunology

description:
processed data file:
201903geneCts.exon.csv
201903geneFpkm.exon.csv
201903geneRpm.exon.csv

data_processing:
Bcl2fastq v2.20.0.442 was used to obtain fastq files from Illumina
FASTQ files were quality and adapter trimmed using Trim Galore (v0.4.2)
Reads were mapped to the UCSC mouse genome mm9 using Tophat2 (v2.1.1) with the following parameters “-p 8 –N2” and the UCSC mm9 KnownGenes gtf transcript file
BAM files from Tophat where sorted with Samtools (v1.7) and duplicates were marked with PICARD (v2.5.0; http://broadinstitute.github.io/picard).
Quantification of gene expression used exons defined by the ‘TxDb.Mmusculus.UCSC.mm9.knownGene’ transcript database (v3.2.2) and the summarizeOverlaps function in mode "IntersectionNotEmpty" from the GenomicAlignments package (v1.20.1) in R (v3.6.1).
Fragments per kilobase per million reads (FPKM) normalization was performed in R based on the number of mapped autosomal reads. Differentially expressed genes (DEGs) were determined using EdgeR (v3.26.6) where a maximum FDR of 0.05 and minimum fold-change of 2 were enforced to determine significance.
Genome_build: mm9
Supplementary_files_format_and_content: 201903geneCts.exon.csv.gz: Raw counts, each column represent a sample
Supplementary_files_format_and_content: 201903geneFpkm.exon.csv.gz: FPKM normalized counts, each column represent a sample
Supplementary_files_format_and_content: 201903geneRpm.exon.csv.gz: RPM normalized counts, each column represent a sample
Supplementary_files_format_and_content: 2019_Restimulation_FPKM.csv.gz: FPKM normalized counts, each column represent a sample
Supplementary_files_format_and_content: 2019_Restimulation_counts.csv.gz: Raw counts, each column represent a sample

extract_protocol:
Total RNAs were extracted using RNeasy plus mini or micro kit (Qiagen)
Truseq stranded mRNA kit (Illumina)

treatment_protocol: Cells were sorted directly from the mice; differentiated from CD4+ naïve T cells into Th0 cells or iTreg cells under the indicated conditions; or collected after anti-CD3/CD28 restimulation

tag: strain background

value: 3 weeks

value: Tet2fl/fl Tet3fl/fl Foxp3-eGFP

value: Spleen and lymph nodes

tag: sorting/differentiation strategy

value: CD4+eGFP+ Treg cells


title: wt-4 [RNA-seq]


title: Exosome KM control cell line rep2

city: Mainz

first: René

last: Ketting

address: Ackermannweg 4

country: Germany

institute: Institute of Molecular Biology

description: Cell line generated and described in Hernandez-Hernandez V, et al. Hum. Mol. Genet. 22(19):3858-68

data_processing:
The following steps were taken prior to read alignment: (1) adapter trimming with cutadapt v1.9 [REF: 10.14806/ej.17.1.200] (-a TGGAATTCTCGGGTGCCAAGG -O 5 -m 33 -M 45); (2) removal of reads with low-quality calls with fastq_quality_filter (-q 20 -p 100 -Q 33) from the FASTX-Toolkit v0.0.14; (3) removal of PCR duplicates making use of the unique molecule identifiers (UMIs) added during library preparation by collapsing reads with the same sequence (including UMIs), using a custom script; (4) Trimming of the UMI sequences (seqtk trimfq -b 4 -e 4); and finally (5) removal of reads shorter than 15 nucleotides (seqtk seq -L 15). FastQC was used to asses the quality of reads before and after processing.
Processed reads were aligned to the _Mus musculus_ genome assembly (gencode, release M10 / GRCm38) with bowtie v0.12.8
miRNA abundance was estimated with mirDeepMApper v2.0.0.8 (mapper.pl -e -p -h -m -i -j followed by miRDeep2.pl -t mouse -c -d -v). A table of miRNA read counts was prepared using the output of miRdeep2 (miRNA_expressed_all_samples), for those miRNAs with multiple entries only the maximal count was used to avoid redundant entries, and used for differential analysis with DESeq2.
Due to the large differences in miRNA absolute abundances between the cell fraction and the exosome, for comparisons between these two fractions DESeq2 library sizes were replaced with those calculated running DESeq using gene counts. Gene counts were obtained with htseq-count v0.9.0 (htseq-count -f bam -m intersection-nonempty -s reverse), and the annotation was from  Gencode (vM10.chr_patch_hapl_scaff.annotation.gtf).
Genome_build: gencode, release M10 / GRCm38
Supplementary_files_format_and_content: Tab separated matrix of raw read counts per miRNA. One row is a miRNA and each column a sample.

source_name: kidney medullary (KM) cell line

growth_protocol: cells were grown until confluency

extract_protocol:
cell culture supernatant were collected, small EVs were purified using differential centrifugation, small EV RNA was harvested with Total Exosome RNA & Portein Isolation Kit from Invitrogen
NGS library prep was performed with NEXTflex Small RNA-Seq Kit V3 following Step A to Step G of Bioo Scientific`s standard protocol (V16.06) using the NEXTFlex 3’ SR Adaptor and 5’ SR Adaptor (5’ rApp /NNNNTGGAATTCTCGGGTGCCAAGG/ 3ddC/ and 5' GUUCAGAGUUCUACAGUCCGACGAUCNNNN, respectively). Libraries for were prepared with a starting amount of 24,6ng and amplified in 15 PCR cycles. Amplified libraries were purified by running an 8% TBE gel and size-selected for 18 – 40nt.
Libraries were profiled in a High Sensitivity DNA on a 2100 Bioanalyzer (Agilent technologies) and quantified using the Qubit dsDNA HS Assay Kit, in a Qubit 2.0 Fluorometer (Life technologies).All samples were pooled in equimolar ratio together and sequenced on 1 NextSeq 500/550 Highoutput Flowcell, SR for 1x 75 cycles plus 7 cycles for the index read.

treatment_protocol: cells were incubated 24 hours without FBS prior extraction

value: kidney medullary (KM) cell line

tag: extract

value: Exosomal

tag: genotype

value: wild-type

value: serum starved


title: Exosome KM control cell line rep3


title: Rodent Lung CD45+ Immune Cells

city: Calgary

first: Jeff

last: Biernaskie

state: Alberta

address: 3330 Hospital Drive NW

department: Comparative Biology and Experimental Medicine

country: Canada

institute: University of Calgary

description: Recovered: 12,492 cells

data_processing:
Read alignment to the pre-built mm10 reference genome was performed using cellranger count (10X Genomics) (Zheng et al., 2017). The resulting gene-barcode matrix was imported into Seurat v.3 (Stuart et al., 2019) for quality control, dimensionality reduction, cell clustering, and differential expression analysis. Three Ms4a1/Cd20+ B cell clusters identified during first round of clustering were systematically subclustered at ten clustering resolutions (0-1 at 0.1 intervals). Optimal clustering resolution of 0.5, determined using clustree (v.0.4.2) (Zappia & Oshlack, 2018), generated 8 B cell subclusters. T1 B and T2 B states (each comprising two distinct subclusters) were identified by querying canonical state-specific markers Vpreb3, Egr1, and Cd24a for T1 and Fcer2a and Ighd for T2. B1 subcluster was identified by querying S100a6 and Itgb1. The remaining three subclusters were annotated by their highest expressed signature determined using the FindMarkers function in Seurat. To enable intuitive exploration of B cell profiles, a web portal interface (http://www.biernaskielab.ca/b_cell or http://www.biernaskielab.com/b_cell) was created using RShiny (v1.1.0), shinyLP (v.1.1.2), and shinythemes (v.1.1.2) packages.
Genome_build: mm10-1.2.0
Supplementary_files_format_and_content: Filtered gene - barcode matrix output from CellRanger

source_name: Rodent Lung

growth_protocol: All transgenic mice were housed singly. We received prior approval from the University of Calgary Animal Handling Committee, and mouse were treated in full accordance to guidelines set by the Canadian Council on Animal Care.

extract_protocol:
Cells were maintained at room temperature throughout our single cell sample preparation. Intact lungs were dissected from 6 mice (3 males, 3 females) and placed in FACS tube with 4 ml of 1X PBS. A gentleMACS™ Dissociator 2.01 was used to mechanically liberate lung cells and cell suspension was filtered through a 70-μm cell strainer. Cell strainer was rinsed with an additional 6 ml of 1X PBS to recover remaining cells. Tissue samples were centrifuged at 2000 rpm for 5 min and supernatant was discarded. To eliminate erythrocyte contamination in single cell suspension, 2 mL of red blood cell (RBC) lysis buffer was added for 3 min. RBC lysis buffer was diluted by adding 10 ml of PBS. The resulting cell suspension was centrifuged at 2000 rpm for 5 min and supernatant containing the medium plus enzyme was discarded. Cells were resuspended in 500 μL of PBS and 12.5 μL of Fc Block was added for 15 min to block Fc receptors before being exposed to anti-CD45-PeCy7 antibody. Following another round of centrifugation at 2000 rpm for 5 min, cell pellet was first stained with 7-AAD viability dye (5μL per 200 μL) for 7 minutes in dark and then with 1 μL of anti-CD45-PeCy7 in 200 μl of final volume for 20 min. Unbound antibodies were rinsed off by centrifuging cells at 2000 rpm for 5 min and discarding the supernatant. Cells were resuspended in 300μL of PBS + 2% BSA then filtered through a 100-μm cell strainer. 7AAD- CD45+ viable immune cells were sorted in PBS + 2% BSA. Percentage of CD45+ cells was determined by flow cytometry and varied between 92-97%. Following centrifugation at 2000 rpm for 10 min, 40,000 CD45+ single cells were resuspended in a 50 μl of PBS + 2% BSA + 1 μl of RNAse inhibitor solution. To isolate immune cells comprising healthy lung tissue, 40,000 single, viable CD45+ cells were barcoded using 10X Genomics ChromiumTM Single Cell 3′ Reagent Guidelines v3 Chemistry as per the manufacturer’s protocol. Quality control and cDNA quantification was performed using DNA Tape Station D1000. Sequencing was performed over two rounds on Illumina NovaSeq 125 Cycle S2 dual lane flow cell. We recovered 12,492 cells sequenced to 91,931 reads/cell (89% sequencing saturation) with an estimated doublet rate of ~8%. Read alignment to the pre-built mm10 reference genome was performed using cellranger count (10X Genomics) (Zheng et al., 2017).
Single-cell suspension of CD45+ immune cells were barcoded using 10X Genomics ChromiumTM Single Cell 3′ Reagent Guidelines v3 Chemistry as per the manufacturer’s protocol. Quality control and cDNA quantification was performed using Agilent High Sensitivity DNA Kit. Sequencing was performed over two rounds on Illumina NovaSeq 125 Cycle S2 dual lane flow cell. We recovered 12,492 cells sequenced to 91,931 reads/cell (89% sequencing saturation) with an estimated doublet rate of ~8%.

treatment_protocol: No treatment

value: Ly6Gcre:tdTomato mice

value: lung

tag: facs strategy

tag: library preparation

value: 10X Genomics Single Cell RNAseq v3


title: Exosome KM control cell line rep1

tag: tissue

tag: treatment


title: Balbc Adult mouse mammary gland

city: Chapel Hill

first: Charles

middle: M.

last: Perou

state: NC

address: 12-044 Lineberger Comprehensive Cancer Center CB# 7295

department: Professor of Genetics, and Pathology & Laboratory Medicine; Lineberger Comprehensive Cancer Center

institute: University of North Carolina at Chapel Hill

data_processing:
The Cell Ranger Single Cell Software Suite, version 3.1 was used for de-multiplexing, barcode ad UMI processing, and single-cell 3′ gene counting. Reads were mapped to the mm10 genome.
Specific details and instructions to run Cell Ranger v3.1 can be found at: https://support.10xgenomics.com/single-cell-gene-expression/software/release-notes/3-1
Genome_build: mm10
Supplementary_files_format_and_content: Cell Ranger output files: Barcode.tsv, Features.tsv and Matrix.mtx

source_name: Normal adult Mammary Gland

extract_protocol:
The Balbc mammary glands were placed in 10 ml of a digestion medium con-taining EpiCultTM-B Mouse Medium Kit (#05610, StemCell Technologies), Col-lagenase/Hyaluronidase (#07912, StemCell Technologies) and 1% penicillin streptomycin (Gibco). The mammary gland was digested overnight in a thermocycler maintained at 37 C with continuous rotation. RNA was isolated from the cell-lines and the mammary glands using the RNeasy Mini Kit (#74104, Qiagen) according to manufacturer protocol.
scRNA-Seq libraries were prepared following the Single Cell 30 Reagent Kits v3 User Guide (Manual Part # CG000183 Rev C) using the following Single Cell 30 Reagent Kits v3: ChromiumTMSingle Cell 3' Library & Gel Bead Kit v3, PN-120237, Chromium Single Cell B Chip Kit, 16 rxns PN-1000154 (America and Asia Pacific), and i7 Multiplex Kit PN-120262 (10X Genomics).
scRNA-Seq Libraries were run on an Illumina HiSeq 4000 as 2 150 paired-end reads.

value: 12 weeks old mouse mammary gland

value: Balbc / female


title: bz_input_rep3


title: HEK293T_nonFTO_m6AIP-rep2

description: m6A RNA immunoprecipitation

tag: cell line

tag: cell type


title: Exosome Bbs6 KO cell line rep3


title: Histone-ChIP-seq-293T-intput

description: ChIP-seq analysis with 293T

value: embryonic kidney


title: HxIRI_K4

value: post IRI kidney

value: 8 weeks


title: ATAC-293T

description: ATAC-seq  analysis chromatin accessibility


title: bz_input_rep2


title: wt-2 [RNA-seq]

tag: genotype/variation


title: CUT-Tag-IgG

description: G4 CUT&Tag analysis with IgG antibody

value: IgG


title: Exosome Bbs6 KO cell line rep2


title: bz_input_rep1


title: wt-1 [RNA-seq]

value: 3 weeks


title: Histone-ChIP-seq-293T-H3K4me1-rep2

description: ChIP-seq analysis with H3K4me1


title: tz_IP_rep3

value: alpha-m6A (Synaptic Systems, 202003)


title: Exosome Bbs6 KO cell line rep1


title: dko-4  [RNA-seq]

value: Tet2fl/fl Tet3fl/fl Foxp3-eGFP CD4-Cre

value: Spleen and lymph nodes


title: tz_input_rep3


title: G4-ChIP-IgG

description: ChIP-seq analysis with Flag-BG4 antibody


title: Exosome Bbs4 KO cell line rep3

value: kidney medullary (KM) cell line


title: dko-3 [RNA-seq]

value: CD4+eGFP+ Treg cells


title: G4-ChIP-rep2


title: tz_input_rep2


title: tz_input_rep1


title: Exosome Bbs4 KO cell line rep1

value: Exosomal


title: dko-1  [RNA-seq]


title: G4-ChIP-rep1


title: WT-miR171__1

status: Public on Jul 18 2021

city: Chuncheon

first: Taeyoung

last: Um

address: 1, Kangwondaehak-gil

country: South Korea

institute: kangwon national university

description: nontransgenic rice

data_processing:
Single-end seq were generated and raw seq reads were trimmed to removed adaptor seq, and those with a quality lower than Q20 were removed using the clc quality trim software (CLCBIO).
Duplicate paired short reads were removed using FastUniq.
All reads were assembled with the clc_ref_assmble 6 (version 4.06) program, using annotated gene and noncoding RNA seq from the rapdb (http://rapdb.dna.affrc.go.jp).
Genome_build: IRGSP-1.0
Supplementary_files_format_and_content: Excel files include FPKM values for each Sample

organism: Oryza sativa

source_name: nontransgenic control (wild type, WT)

growth_protocol: Rice was germinated on MS (Murashige and Skoog) media at 28C for 3 days, and transplanted into soil pots (15cm diameter x 14cm tall; 1 plants per pot) and grown in a greenhouse.

extract_protocol:
Total RNA was extracted from the leaves of 4-week-old OX plants, Ko mutants and WT rice using the RNeasy Plant Mini Kit (Qiagen, Hilden, Germany) according to the manufacturer’s instruction.
RNA libraries were prepared for sequencing using TruSeq Stranded mRNA Sample Preparation Guide (Part #  15031047 Rev. E)

value: leaves

tag: developmental stage

value: 4-week-old at young stage

value: nontransgenic control (wild type, WT)


title: WT-miR171__2

description: nontransgenic rice


title: Ko-miR171__1

description: CRISPR-Cas9 knock out mutant

source_name: Osa-mir171f K/O_2 (knockout mutant)

value: Osa-mir171f K/O_2 (knockout mutant)


title: OX-miR171__2

description: whole-body overexpression

source_name: Osa-MIR171f Ox_5 (overexpressing transgenic rice)


title: OX-miR171__1

description: whole-body overexpression

source_name: Osa-MIR171f Ox_3 (overexpressing transgenic rice)


title: CUT-Tag-BG4


title: LX2 HHT-1μM rep2

city: Shanghai

first: Chen

last: Yang

address: Xietu Road

institute: Shanghai Cancer Institute

data_processing:
Illumina Casava 1.8.2 software used for basecalling. The quality score encoding is in +Phred 33.
Raw sequencing reads were mapped to the human genome (GRCh38) using STAR (version 2.4.2g1).
Gene-level read counts were generated using featureCounts from the subRead package with default settings.
Genome_build: GRCh38
Supplementary_files_format_and_content: tab-delimited text files include FPKM values for each Sample ...

extract_protocol:
Total RNA was extracted and purified using the Trizol reagent (Invitrogen)
The library was prepared using TruSeq RNA sample prep kit according to the manufacturer’s protocol (Illumina).

treatment_protocol: We first treated LX-2 cells with vehicle or HHT (1μM and 5μM) for 6 hours. Then, RNA sequencing was conducted to quantify the mRNA expression level of vehicle-treated or HHT-treated LX-2 cells.  HHT-induced expression changes were obtained based on the resultant data.

value: Immortalized human hepatic stellate cell line

value: Homoharringtonine

value: Liver


title: LX2 HHT-5μM rep2


title: Ko-miR171__2

description: CRISPR-Cas9 knock out mutant

source_name: Osa-mir171f K/O_2_1 (knockout mutant)

value: Osa-mir171f K/O_2_1 (knockout mutant)


title: LX2 HHT-1μM rep1


title: LX2 HHT-5μM rep1


title: LX2 ctrl rep2

value: Control


title: LX2 ctrl rep1


title: Exosome Bbs4 KO cell line rep2

value: serum starved


title: dko-2 [RNA-seq]

value: 3 weeks


title: pretreatment AML_3035032-N

city: Houston

first: Hussein

middle: A.

last: Abbas

state: TX

address: 1400 Holcombe Blvd

department: Leukemia and Genomic Medicine

institute: MD Anderson Cancer Center

data_processing:
RNA-seq FASTQ files were processed through FastQC (v0.11.5)
STAR 2-pass alignment (v2.5.3) was performed with default parameters to generate RNA-seq BAM files
RNA-Seq gene expression raw read counts generated from HTSeq-count (v0.9.1)
Genome_build: hg19
Supplementary_files_format_and_content: Raw read counts for 81 samples

source_name: Bone marrow

extract_protocol:
Bone marrow aspirates were collected at time of AML diagnosis. RNA was isolated and purified from bone marrow mononuclear cells using Qiagen’s RNAEasy preparation kits.
The purified RNA was used to create cDNA libraries that were assayed using TruSeq (Illumina) RNAAccess. 40M 50 bp paired end reads were sequenced per sample using the illumina HiSeq sequencer. Note: the sequence model number was not provided to the submitter. GEO has listed HiSeq 4000 as a likely option.

value: pretreatment

tag: upin

value: bone marrow

tag: disease state

value: AML


title: pretreatment AML_3308122-N


title: Lipoma-derived adipocytes familial replicate2

city: Bronx

first: Kosaku

last: Shinoda

state: NY

address: 1301 Morris Park Ave

institute: Albert Einstein College of Medicine

data_processing:
Cell Ranger v3.1.0
kallisto_version: 0.46.1
Genome_build: GRCh38-2020
Supplementary_files_format_and_content: filtered featured bc matrix
Supplementary_files_format_and_content: abundance.tsv (kallisto)

source_name: mature adipocytes

extract_protocol:
Stromal Vascular Fraction (SVF) was isolated from lipomas using our published protocol. (Aune et al., 2013 PMID: 23568137)
10X genomics snRNA-seq library construction protocol

tag: replicate

value: replicate 2

tag: sample type

value: Lipoma-derived adipocytes familial


title: Lipoma-derived adipocytes familial replicate1

value: replicate 1


title: Sporadic lipoma

source_name: SVF from lipoma

value: Sporadic lipoma


title: Lipoma-derived adipocytes sporadic replicate2

value: Lipoma-derived adipocytes sporadic


title: Familial multiple lipomatosis

value: Familial multiple lipomatosis


title: Lipoma-derived adipocytes sporadic replicate1


title: Lipoma-derived adipocytes familial replicate3

value: replicate 3


title: pretreatment AML_3319790-N


title: pretreatment AML_3306954-N


title: pretreatment AML_3300732-N


title: pretreatment AML_3305912-N


title: pretreatment AML_3301782-N


title: pretreatment AML_3300166-N


title: pretreatment AML_3284706-N


title: pretreatment AML_3288192-N


title: pretreatment AML_3291336-N


title: pretreatment AML_3268498-N


title: pretreatment AML_3278622-N


title: pretreatment AML_3282000-N


title: pretreatment AML_3275492-N


title: pretreatment AML_3299802-N


title: pretreatment AML_3226562-N


title: pretreatment AML_3264658-N


title: pretreatment AML_3253308-N


title: Lipoma-derived adipocytes sporadic replicate3


title: pretreatment AML_3114948-N


title: pretreatment AML_3113814-N


title: pretreatment AML_3044292-N


title: pretreatment AML_3052308-N


title: pretreatment AML_3209016-N


title: pretreatment AML_3034582-N


title: pretreatment AML_3034804-N


title: pretreatment AML_3039422-N


title: pretreatment AML_3021382-N


title: pretreatment AML_3089062-N


title: pretreatment AML_3010468-N


title: pretreatment AML_2982210-N


title: pretreatment AML_2690050-N


title: pretreatment AML_2956294-N


title: pretreatment AML_3389988-N


title: pretreatment AML_2966936-N


title: pretreatment AML_3363000-N


title: pretreatment AML_2984296-N


title: pretreatment AML_3046888-N


title: pretreatment AML_3342412-N


title: pretreatment AML_2992234-N


title: pretreatment AML_3291110-N


title: pretreatment AML_3287842-N


title: pretreatment AML_3266562-N


title: pretreatment AML_3220256-N


title: pretreatment AML_3323254-N


title: pretreatment AML_3098760-N


title: pretreatment AML_3098754-N


title: pretreatment AML_3040788-N


title: pretreatment AML_3100570-N


title: pretreatment AML_3377824-N


title: pretreatment AML_3382770-N


title: pretreatment AML_3370202-N


title: pretreatment AML_3371080-N


title: pretreatment AML_3376904-N


title: pretreatment AML_2659168-N


title: pretreatment AML_2910438-N


title: pretreatment AML_3208794-N


title: pretreatment AML_3343544-N


title: pretreatment AML_3330336-N


title: pretreatment AML_3370058-N


title: pretreatment AML_3342986-N


title: pretreatment AML_3319246-N


title: pretreatment AML_3329434-N


title: pretreatment AML_3364008-N


title: pretreatment AML_3317526-N


title: pretreatment AML_3316808-N


title: pretreatment AML_3252956-N


title: pretreatment AML_3287312-N


title: pretreatment AML_3315886-N


title: pretreatment AML_3273170-N


title: pretreatment AML_3235738-N


title: pretreatment AML_3140004-N


title: pretreatment AML_3119184-N


title: pretreatment AML_3118298-N


title: pretreatment AML_3315356-N


title: wh_2

city: beijing

first: wei

last: li

address: No.5 Dongdansantiao street, Dongcheng district

institute: Peking Union Medical College

data_processing:
Illumina Casava 1.8 software used for basecalling.
Sequenced reads were trimmed for adaptor sequence, and masked for low-complexity or low-quality sequence, then mapped to mm8 whole genome using bowtie v0.12.2 with parameters -q -p 4 -e 100 -y -a -m 10 --best --strata
Reads Per Kilobase of exon per Megabase of library size (RPKM) were calculated using a protocol from Chepelev et al., Nucleic Acids Research, 2009. In short, exons from all isoforms of a gene were merged to create one meta-transcript. The number of reads falling in the exons of this meta-transcript were counted and normalized by the size of the meta-transcript and by the size of the library.
Genome_build: mm9
Supplementary_files_format_and_content: raw counts

source_name: Liver

extract_protocol: RNA libraries were prepared for sequencing using standard Illumina protocols

tag: strain

value: p53 wt

value: HFD

tag: age

value: 12 weeks


title: wh_3

value: Liver


title: pretreatment AML_3364888-N


title: pretreatment AML_3091926-N


title: pretreatment AML_3044356-N


title: kh_3

value: p53 ko


title: pretreatment AML_3347052-N


title: pretreatment AML_3103988-N


title: KO_rep3

city: shanghai

first: Qianwen

last: Hu

address: 重庆南路280号

institute: Shanghai Jiao Tong University School of Medicine

data_processing:
Using HISAT2 RNA-sequencing alignment software, the raw reads were aligned to the mouse reference genome (version mm10). The mapping rate was 96%, on average, across all the samples in the dataset.
The alignment files (bam files) were processed to generate read counts for every gene using HISAT and HTSeq.
The read counts were normalized using the R package DESeq2 and then were centered and scaled for each gene, generating z-scores. P values obtained from multiple tests were adjusted using the Benjamini-Hochberg correction.
Genome_build: mm10
Supplementary_files_format_and_content: excel file containing read count for each gene

source_name: active B cell

extract_protocol:
Transferred IgD- CD19+GL7+CD38+ NP-specific activated precursor cells were FACS-sorted from the host and  RNA was harvested using Trizol reagent.
RNA libraries were prepared for sequencing using standard Illumina protocols

treatment_protocol: B1-8hi Bach2+/+ ERT2cre or B1-8hi Bach2fl/fl ERT2cre mice were administrated with tamoxifen for 3 consecutive days. 7 days later, spleen naive B cells were isolated and adoptively transferred together with OT-II CD4+ T cells into the wild-type hosts . One day later, the recipients  were immunized with NP-OVA and sacrificed for analysis at day2.

value: spleen

value: active B cells

value: B1-8hi Bach2f/f ERT2cre

value: NP-OVA immunization


title: kh_1


title: KO_rep2


title: WT_rep3

value: B1-8hi Bach2+/+ ERT2cre


title: pretreatment AML_3003486-N

value: pretreatment

value: bone marrow

value: AML


title: kh_2


title: wn_1

value: normal


title: WT_rep2


title: WT_rep1


title: wn_2


title: kn_1


title: wh_1


title: kn_3


title: NMe_WT

city: New York

first: Laura

last: Belver

address: 1130 St Nicholas Ave

institute: Columbia University

data_processing:
BCL files were demultiplexed with 10x Cell Ranger's mkfastq command.
Analysis and alignment were performed using Cell Ranger's count command with Cell Ranger's reference mm10 version 1.2.0.
The version of Cell Ranger used in each step was 2.0.0.
Genome_build: mm10
Supplementary_files_format_and_content: Processed data files are tab-separated text files containing each the gene count matrix of the corresponding scRNA-seq experiment.

source_name: thymus

extract_protocol: Thymocyte suspensions (5000 cells per sample) were loaded on a 10× Chromium instrument (10× Genomics) and single-cell RNAseq libraries were prepared using Chromium Single Cell 3′ v2 Reagent Kit (10× Genomics CG00052). Sequencing was performed on an Illumina HiSeq platform (Illumina).

value: Thymocytes

value: thymus

value: wild type


title: P2_LowGlucose_Galactose

city: Melbourne

first: Shian

last: Su

state: Victoria

address: 1G Royal Parade

department: Molecular Medicine

country: Australia

institute: Walter and Eliza Hall Institute of Medical Research

data_processing:
Sequenced reads were mapped using the align function in the Rsubread package (Liao et al. Nucleic Acids Research, 2013) with default parameters.
Gene-level counts were obtained using the sc_gene_counting function from the scPipe package with the ENSEMBL v86 mouse annotation.
Size factors used in normalization were calculated using the computeSumFactors function from scran (Lun et al. F1000Res 2016)
Data were TMM normalized (Robinson and Oshlack, Genome Biology 2010) in the edgeR package (Robinson et al. Bioinformatics 2010) and transformed to log2 counts per million.
Generalized linear models were fitted to summarize the count values using the glmFit function from the edgeR package.
Genome_build: NCBI Build 38 patch 7
Supplementary_files_format_and_content: C5-P1-SC.csv (Counts matrix with samples along the columns and genes along the rows)
Supplementary_files_format_and_content: C5-P2-SC.csv (Counts matrix with samples along the columns and genes along the rows)

source_name: Muscle stem cell

growth_protocol: High Glucose, Low Glucose and Galactose cells were cultured for 96 hrs in DMEM supplemented with 1mM sodium pyruvate, 10% fetal bovine serum, 10% horse serum, 0.05% chick embryo extract, 2.5ng/ml bFGF, 1% penicillin/streptomycin and either 25mM or 5mM glucose or 10mM galactose

extract_protocol:
Muscle stem cells were isolated via FACS into 384-well plates.
Cell lysis and RNA library construction was performed in well using a modified CELseq2 protocol

tag: condition

value: mixed sample (non-demultiplexed) representing Low glucose and Galactose

tag: plate

tag: umi coordinate

value: Bases 1 to 6 in R1

tag: barcode coordinate

value: Bases 7 to 14 in R1


title: wn_3

tag: genotype

value: p53 wt

value: 12 weeks

value: Liver


title: HFD_DMSO

city: nanjing

first: feng

middle: ru

last: xu

address: jiangning

institute: nanjing medical university

data_processing: Differential expression analysis of two conditions/groups (twobiologicalreplicatespercondition) was performed using the DESeq2 R package(1.10.1). DESeq2 provide statistical routines for determining differential expression in digital gene expression data using a model based on the negative binomial distribution.There sulting P-values were adjusted using the Benjamini and Hochberg’s approach for controlling the false discovery rate.Genes with an adjusted P-value<0.05 found by DESeq2 were assigned as differentially expressed.

source_name: pancretic islets

growth_protocol: 4 month ND male mice and  HFD-feeding male mice were oral gavage DMSO,CGP 57380 for 1 month

extract_protocol:
Pancreatic islets were isolated, flash frozen on dry ice, and RNA was harvested using Trizol reagent. Illumina TruSeq RNA Sample Prep Kit was used with 1 ug of total RNA for the construction of sequencing libraries.
RNA libraries were prepared for sequencing using standard Illumina protocols

tag: tissue

value: pancreatic islets

value: HFD-feeding mice oral gavage DMSO


title: kn_2

value: p53 ko

tag: treatment


title: HFD_CGP

value: HFD-feeding mice oral gavage CGP 57380


title: P1_Quiescent_HighGlucose

value: mixed sample (non-demultiplexed) representing Quiescent and High glucose


title: KO_rep1

value: spleen

value: active B cells

value: B1-8hi Bach2f/f ERT2cre

value: NP-OVA immunization


title: ND

value: ND-feeding mice oral gavage DMSO


title: colorectal cancer_I [HH Vb 049_257015614598_2_3]

status: Public on Jul 17 2021

type: RNA

city: Heidelberg

first: Andrea

middle: S

last: Bauer

address: Im Neuenheimer Feld 580

department: Functional Genome Analysis

institute: DKFZ

description: miRNA expression

hyb_protocol: 1.5 ug of Cy3-labelled cRNA (specific activity >10.0 pmol Cy3/ug cRNA) was fragmented at 60°C for 30 minutes in a reaction volume of 250 ml containing 1x Agilent fragmentation buffer and 2x Agilent blocking agent following the manufacturers instructions. On completion of the fragmentation reaction, 250 ml of 2x Agilent hybridization buffer was added to the fragmentation mixture and hybridized to Agilent Whole Human Genome Oligo Microarrays (G4112A) for 17 hours at 65Â°C in a rotating Agilent hybridization oven.  After hybridization, microarrays were washed 1 minute at room temperature with GE Wash Buffer 1 (Agilent) and 1 minute with 37Â°C GE Wash buffer 2 (Agilent), then dried immediately by brief centrifugation.

scan_protocol: Slides were scanned immediately after washing on the Agilent DNA Microarray Scanner (G2505B) using one color scan setting for 1x44k array slides (Scan Area 61x21.6 mm, Scan resolution 10um, Dye channel is set to Green and Green PMT is set to 100%).

data_processing:
The scanned images were analyzed with Feature Extraction Software 9.1 (Agilent) using default parameters (protocol GE1-v1_91 and Grid: 012391_D_20060331) to obtain background subtracted and spatially detrended Processed Signal intensities.  Features flagged in Feature Extraction as Feature Non-uniform outliers were excluded.
The *qnorm.txt.geo.GPL21576.txt files contain normalized signal intensity.

source_name: colorectal cancer_I_whole blood

label_protocol: Cyanine-3 (Cy3) labeled cRNA was prepared from 0.5 ug RNA using the One-Color Low RNA Input Linear Amplification PLUS kit (Agilent) according to the manufacturer's instructions, followed by RNAeasy column purification (QIAGEN, Valencia, CA).  Dye incorporation and cRNA yield were checked with the NanoDrop ND-1000 Spectrophotometer.

extract_protocol: Total RNA including miRNA was isolated using the miRNeasy kit (Qiagen, Hilden, Germany) according to the manufacturer´s instruction. RNA was quantified using a NanoDrop-1000 spectrophotometer and quality was monitored with the Agilent 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA).

tag: class

value: colorectal cancer

tag: uicc stage

value: I

value: whole blood


title: colorectal cancer_IIA [HH Vb 034_257015614598_2_2]

description: miRNA expression

source_name: colorectal cancer_IIA_whole blood

value: IIA


title: NMe_GSmut

tag: cell type

value: Thymocytes

value: thymus

tag: genotype/variation

value: NMe GATA site 1 and 2 (GS1+2) homozygous mutant


title: colorectal cancer_I [HH Vb 091_257015614598_2_4]

description: miRNA expression


title: colorectal cancer_II [HH Vb 073_257015614598_2_1]

description: miRNA expression

source_name: colorectal cancer_II_whole blood

value: II


title: colorectal cancer_II [HH Vb 032_257015614598_1_4]

description: miRNA expression


title: colorectal cancer_I [HH Vb 089_257015614598_1_3]

description: miRNA expression


title: PLN-2

city: Taipei

first: I-Fang

last: Wang

address: Academia Rd.

department: Institute of Molecular Biology

country: Taiwan

institute: Academia Sinica

description: miRNA

hyb_protocol: Cy5-labelled enrichment miRNA was denatured at 95°C for 5 minutes in a reaction volume of 90 μl containing 1x miRNA hybridization buffer. On completion of the denature reaction, the mixture are hybridized to Phalanx Mouse & Rat miRNA OneArray for 16 hours at 37 °C in a rotating hybridization oven. After hybridization, microarrays were washed 5 minute at 37 °C with Wash Buffer 1 (Phalanx), 5 minute at 37 °C with Wash Buffer 2 (Phalanx) and 5 minute at room temperature with Wash Buffer 2 (Phalanx) and then rinsed with Wash Buffer 3 (Phalanx). Finally, the arrays were dried by centrifuge.

scan_protocol: Slides were scanned immediately after washing on the GenePix 4000B Microarray Scanner (Molecular Devices) using two color scan (Scan resolution 10um, Laser power setting is 100%).

data_processing: Flags are determined by GenePix software.

source_name: hippocampus

label_protocol: Cyanine-5 (Cy5) labeled total RNA was prepared from 2.5 ug RNA using the ULSTM microRNA Labeling kit (Kreatech, Netherlands) according to the manufacturer's instructions, followed by Nanosep 100K miRNA enrichment (Pall Corporation). Dye incorporation and RNA amount were checked with the NanoDrop ND-1000 Spectrophotometer.

extract_protocol: Total RNA extraction.

treatment_protocol: C57BL/6J mice underwent Morris water maze with good performances or poor performances & harvested hippocampus immediately after training.

value: WT

value: Hippocampus

value: Morris water maze

tag: performance

value: Poor


title: CD8-T_(-)_day25

city: Goyang-si

first: Chungyong

last: Han

state: Gyeonggi-do

address: 323 Ilsan-ro, Ilsandong-gu

institute: National Cancer Center

description: Gene expression data of endogeneous CD8+ T cells from B16F10-bearing mice treated with cyclophosphamide and Pmel-1.

hyb_protocol: Approximately 5.5 μg of labeled DNA target was hybridized to the Affymetrix GeneChip Array at 45°C for 16 hour.

scan_protocol: Hybridized arrays were washed and stained on a GeneChip Fluidics Station 450 and scanned on a GCS3000 Scanner (Affymetrix).

data_processing:
Array data export processing and analysis was performed using Affymetrix® GeneChip Command Console® Software (AGCC).
RMA by using Affymetrix Power Tools (affymetrix-power-tools.html).

label: biotin

source_name: CD8+ T cells, without anti-CD4 treatment, day 25

label_protocol: The sense cDNA was then fragmented and biotin-labeled with TdT (terminal deoxynucleotidyl transferase) using the GeneChip WT Terminal labeling kit.

growth_protocol: On day 0, six- to eight-week-old C57BL/6 female mice were intradermally inoculated with B16F10 (2E+05). On day 3, pre-conditioning lymphodepletion was induced via intraperitoneal injection of 300 mg/kg cyclophosphamide. On day 5, Pmel-1 cells (2E+06) were isolated from the splenocytes of Thy1.1 Pmel-1 transgenic mice (Thy1a/Cy Tg(TcraTcrb)8Rest/J; expressing transgenic TCR specific for gp10025–33 and congenic Thy1.1 antigen) and injected into tumor-bearing mice. Starting on day 5, recombinant human IL-2 (10,000 IU) was intraperitoneally injected daily for 3 days.

extract_protocol: On day 25, the lymph nodes and spleen were gently disrupted and filtered through a 40 μm nylon cell strainer to make single-cell suspensions. Cells were treated with RBC lysis buffer before use. After staining with anti-CD8 and anti-Thy1.1 fluorochrome-conjugated antibodies, Thy1.1-negative CD8-positive endogenous T cells were isolated by fluorescence-activated cell sorting. Total RNA was extracted from the isolated cells using Trizol reagent.

treatment_protocol: Starting from day 10, anti-CD4 treatment involved weekly intraperitoneal injections of 200 μg anti-mouse CD4 monoclonal antibody (clone: GK1.5) for 3 weeks.

tag: gender

value: Female

value: six- to eight-week-old

value: Inguinal lymph nodes and spleen

value: CD8+ T cells

value: control


title: HSCC_L2

city: chiba

first: sachi

last: oshima

state: chiba

address: 1-8-1 inohana chuo-ku

department: Grad. Sch. Med

country: Japan

institute: Chiba Univ

hyb_protocol: Agilent one-color Gene Expression Wash Pack (5188-5327 : Agilent) hyb/wash protocol

scan_protocol: Microarray slides were scanned in an Agilent Technologies G4900DA Microarray Scanner at 3 micron resolution.

data_processing: The scanned images were Images were quantified using Agilent Feature Extraction software version  12.1.1.1

source_name: Cervical lymph nodes

label_protocol: Agilent one-color Low Input Quick Amp Labeling Kit(5190-2305 :Agilent), protocol

growth_protocol: Normal cell culture medium DMEM.

extract_protocol: Total RNA was extracted using Trizol following the manufacturer's instructions.

value: Cervical lymph nodes


title: GLN-2

description: miRNA

value: Good


title: colorectal cancer_I [HH Vb 067_257015614598_1_2]

description: miRNA expression

value: colorectal cancer

value: I

value: whole blood


title: colorectal cancer_IIA [HH Vb 001_257015614598_1_1]

description: miRNA expression

value: IIA


title: CD8-T_aCD4_day25

description: Gene expression data of endogeneous CD8+ T cells from B16F10-bearing mice treated with cyclophosphamide, Pmel-1, and anti-CD4.

source_name: CD8+ T cells, with anti-CD4 treatment, day 25

value: anti-CD4 treatment


title: healthy [HH Vb 121_257015614597_2_2]

description: miRNA expression

source_name: healthy_whole blood

value: healthy


title: GLN-1

description: miRNA

value: WT


title: HSCC_N2

source_name: Hypopharyngeal

value: Normal hypopharyngeal tissues


title: healthy [HH Vb 122_257015614597_2_3]

description: miRNA expression


title: healthy [HH Vb 099_257015614597_1_4]

description: miRNA expression


title: healthy [HH Vb 133_257015614597_2_4]

description: miRNA expression


title: healthy [HH Vb 120_257015614597_2_1]

description: miRNA expression


title: HSCC_L1


title: HSCC_N3


title: HSCC_N1


title: healthy [HH Vb 005_257015614597_1_1]

description: miRNA expression


title: healthy [HH Vb 060_257015614597_1_2]

description: miRNA expression


title: colorectal cancer_IV [HH Vb 116_257015614594_2_3]

description: miRNA expression

source_name: colorectal cancer_IV_whole blood

value: IV


title: colorectal cancer_IV [HH Vb 126_257015614594_2_4]

description: miRNA expression


title: PLN-1

description: miRNA

value: Hippocampus

value: Morris water maze

value: Poor


title: HSCC_T1

value: HSCC tissues


title: HSCC_T2


title: HSCC_T3


title: colorectal cancer_IV [HH Vb 117_257015614594_1_3]

description: miRNA expression


title: healthy [HH Vb 070_257015614597_1_3]

description: miRNA expression


title: colorectal cancer_IV [HH Vb 140_257015614594_1_2]

description: miRNA expression


title: colorectal cancer_IV [HH Vb 036_257015614594_2_1]

description: miRNA expression


title: colorectal cancer_IV [HH Vb 041_257015614594_2_2]

description: miRNA expression


title: colorectal cancer_IV [HH Vb 118_257015614594_1_4]

description: miRNA expression


title: colorectal cancer_IV [HH Vb 135_257015614594_1_1]

description: miRNA expression


title: colorectal cancer_II [HH Vb 105_257015613960_2_4]

description: miRNA expression

value: II


title: intestinal polyps [HH Vb 103_257015613960_2_2]

description: miRNA expression

source_name: intestinal polyps_whole blood

value: intestinal polyps


title: intestinal polyps [HH Vb 104_257015613960_2_3]

description: miRNA expression


title: diverticulitis [HH Vb 097_257015613960_2_1]

description: miRNA expression

source_name: diverticulitis_whole blood

value: diverticulitis


title: colorectal cancer_IV [HH Vb 088_257015613960_1_1]

description: miRNA expression


title: colorectal cancer_III [HH Vb 092_257015613960_1_2]

description: miRNA expression

source_name: colorectal cancer_III_whole blood

value: III


title: colorectal cancer_III [HH Vb 094_257015613960_1_4]

description: miRNA expression

value: colorectal cancer


title: colorectal cancer_III [HH Vb 093_257015613960_1_3]

description: miRNA expression


title: healthy [HH Vb 086_257015613950_2_3]

description: miRNA expression


title: colorectal cancer_IV [HH Vb 075_257015613950_1_2]

description: miRNA expression


title: diverticulitis [HH Vb 082_257015613950_1_4]

description: miRNA expression


title: healthy [HH Vb 076_257015613950_1_3]

description: miRNA expression


title: healthy [HH Vb 083_257015613950_2_1]

description: miRNA expression


title: diverticulitis [HH Vb 151_257015613943_2_4]

description: miRNA expression


title: diverticulitis [HH Vb 084_257015613950_2_2]

description: miRNA expression


title: colorectal cancer_III [HH Vb 074_257015613950_1_1]

description: miRNA expression


title: GD 135_Control_5033_Male

city: College Station

first: Michael

middle: Carey

last: Satterfield

address: 2471 TAMUS

department: Animal Science

institute: Texas A&M University

data_processing:
Libraries were multiplexed and sequenced from both directions as 75 base pair paired-end reads on one lane on a NextSeq500 instrument
Raw sequences (FASTQ) were subjected to quality check by FastQC (http://www.bioinformatics.babraham.ac.uk/projects/fastqc/).
The program fqtrim (https://ccb.jhu.edu/software/fqtrim/) was used to remove adapters, perform quality trimming (phred score >30) by a sliding window scan (6 nucleotides) and select read length of 30 nucleotides or longer after trimming.
The reads obtained from the quality control step were mapped to the sheep reference genome (Oar_v3.1) by using Hisat2 aligner. The program FeatureCounts was used to quantify read counts by using the sequences alignment files of each sample.
Genes with evidence of expression (counts per million; rowSum >5) were used for model-based differential expression analysis using the edgeR robust method.
Genome_build: Oar_v3.1
Supplementary_files_format_and_content: CSV file with genes by row and samples by column, raw counts
Supplementary_files_format_and_content: Matrix file with normalized CPM from edgeR for all samples

organism: Ovis aries

source_name: Placentome

extract_protocol:
Total RNA was extracted using Trizol reagent, treated with DNAse I, and purified using an RNeasy Mini Kit.
RNA libraries were prepared for sequencing using standard Illumina protocols

treatment_protocol: Control animals were fed 100% of their NRC nutritional requirements from Day 35 to Day 135 of pregnancy. Nutrient restricted animals were fed 50% of their NRC nutritional requirements for the same time period.

value: Control

tag: day

tag: Sex

value: Male


title: GD 135_Control_5070_Female

value: Female


title: GD 135_Control_5067_Male


title: colorectal cancer_IV [HH Vb 128_257015613943_2_1]

description: miRNA expression

value: whole blood


title: intestinal polyps [HH Vb 134_257015613943_2_2]

description: miRNA expression


title: GD 135_Control_5136_Female


title: GD 135_Control_5114_Male


title: colorectal cancer_IV [HH Vb 127_257015613943_1_4]

description: miRNA expression


title: GD 135_Control_5218_Female


title: intestinal polyps [HH Vb 114_257015613943_1_3]

description: miRNA expression


title: GD 135_Control_5146_Male


title: GD 135_Control_5234_Male


title: intestinal polyps [HH Vb 106_257015613943_1_1]

description: miRNA expression


title: intestinal polyps [HH Vb 108_257015613943_1_2]

description: miRNA expression


title: healthy [HH Vb 087_257015613950_2_4]

description: miRNA expression

value: healthy


title: GD 135_High_5017_Female

value: High


title: GD 135_High_5022_Female


title: colorectal cancer_III [HH Vb 038_257015613790_2_3]

description: miRNA expression


title: GD 135_High_5058_Female


title: GD 135_High_5127_Male


title: colorectal cancer_III [HH Vb 028_257015613790_2_2]

description: miRNA expression


title: colorectal cancer_III [HH Vb 065_257015613790_1_4]

description: miRNA expression


title: GD 135_High_5210_Male


title: colorectal cancer_III [HH Vb 027_257015613790_2_1]

description: miRNA expression


title: GD 135_High_5247_Female


title: diverticulitis [HH Vb 147_257015613943_2_3]

description: miRNA expression


title: GD 135_Low_5001_Female

value: Low


title: GD 135_Low_5008_Female


title: GD 135_Low_5041_Male


title: GD 135_Low_5024_Male


title: GD 135_Low_5079_Male


title: colorectal cancer_III [HH Vb 003_257015613790_1_1]

description: miRNA expression


title: colorectal cancer_IV [HH Vb 071_257015613539_2_4]

description: miRNA expression

value: IV


title: colorectal cancer_III [HH Vb 054_257015613790_1_3]

description: miRNA expression


title: colorectal cancer_III [HH Vb 017_257015613790_1_2]

description: miRNA expression


title: healthy [HH Vb 064_257015613539_2_3]

description: miRNA expression


title: healthy [HH Vb 062_257015613539_2_1]

description: miRNA expression


title: GD 135_Low_5137_Male


title: healthy [HH Vb 063_257015613539_2_2]

description: miRNA expression


title: diverticulitis [HH Vb 058_257015613539_1_3]

description: miRNA expression


title: colorectal cancer_III [HH Vb 010_257015613790_2_4]

description: miRNA expression


title: GD 70_Control_5033_Male


title: intestinal polyps [HH Vb 059_257015613539_1_4]

description: miRNA expression


title: intestinal polyps [HH Vb 055_257015613539_1_1]

description: miRNA expression


title: GD 70_Control_5070_Female


title: GD 70_Control_5067_Male


title: GD 135_High_5173_Male


title: GD 70_Control_5114_Male


title: colorectal cancer_III [HH Vb 051_257015613538_2_2]

description: miRNA expression


title: GD 70_Control_5136_Female


title: colorectal cancer_II [HH Vb 052_257015613538_2_3]

description: miRNA expression


title: GD 70_Control_5146_Male


title: GD 135_Low_5057_Male


title: GD 70_Control_5218_Female


title: colorectal cancer_III [HH Vb 050_257015613538_2_1]

description: miRNA expression


title: GD 70_High_5017_Female


title: GD 70_Control_5234_Male


title: diverticulitis [HH Vb 048_257015613538_1_4]

description: miRNA expression


title: diverticulitis [HH Vb 042_257015613538_1_2]

description: miRNA expression


title: colorectal cancer_II [HH Vb 043_257015613538_1_3]

description: miRNA expression


title: GD 70_High_5022_Female


title: colorectal cancer_III [HH Vb 037_257015613538_1_1]

description: miRNA expression


title: GD 70_High_5127_Male


title: colorectal cancer_IIA [HH Vb 031_257015613537_2_4]

description: miRNA expression

value: IIA


title: GD 70_High_5058_Female


title: colorectal cancer_IV [HH Vb 025_257015613537_2_3]

description: miRNA expression


title: GD 70_High_5173_Male


title: colorectal cancer_I [HH Vb 024_257015613537_2_2]

description: miRNA expression

value: I