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Sample GSM4340689 Query DataSets for GSM4340689
Status Public on Aug 13, 2020
Title CEBPb ChIP-seq Msc Experiment #1
Sample type SRA
 
Source name BM-hMSC-TERT4
Organism Homo sapiens
Characteristics cell type: Stem cell
Stage: Day 0
antibody: CEBPb (Santa Cruz, sc-150)
Treatment protocol Two days post confluency (day 0), cells were induced to undergo adipocyte differentiation by exposing them to a adipogenic differentiation cocktail (DMEM supplemented with 10% fetal calf serum, 10ug/mL insulin, 1µM rosiglitazone, 100 mM dexamethasone, and 500 µM isobutylmethylxanthine). Medium was replaced on days 2, 4, 7 and 9.
Growth protocol Telomerase-immortalized human mesenchymal stromal cells of bone marrow (BM-hMSC-TERT4) were grown under standard cell culture conditions in α-MEM supplemented with 10 % fetal calf serum (FCS) and 1 % penicillin/streptomycin (P/S).
Extracted molecule genomic DNA
Extraction protocol Chromatin was prepared from 150 mm culture dishes by in 1% formaldehyde in PBS (10 minutes, RT). Cross-linking was stopped by adding glycine to a final concentration of 0.125 M (10 minutes, RT). The cells were washed twice in ice-cold PBS, and harvested in ice-cold lysis buffer (0.1% SDS, 1% Triton X-100, 0.15 M NaCl, 1 mM EDTA, 20 mM Tris pH=8) and sonicated at high setting in a Bioruptor-Twin (Diagenode) at a volume of 1.5 ml in 15-mL tubes for 40 cycles of 30 seconds on and 30 seconds off. The chromatin IPs were performed as described in (Nielsen R, et al. 2014. Methods in Enzymology 537: 261-279).
ChIP-seq libraries were constructed from 10 to 20 ng of genomic DNA according to the manufacturer's instructions (Illumina) as described in (Nielsen R, et al. 2014. Methods in Enzymology 537: 261-279).
 
Library strategy ChIP-Seq
Library source genomic
Library selection ChIP
Instrument model Illumina HiSeq 1500
 
Description ChIP_CEBPb_Msc.counts.txt.gz
Data processing Base calling for all sequencing runs was performed using bcl2fastq (v2.20.0.422).
ChIP-seq: Reads were aligned using STAR (v2.3.1, --outSJfilterIntronMaxVsReadN 0 --outFilterMatchNmin 25 --outFilterMismatchNmax 2 --alignIntronMax 1). Duplicated reads/fragments were removed using Picard (v2.5.0). Reads/fragments were counted using HOMER (v4.10.3) in DNase I hypersensitive regions identified in a previous study (Rauch et al., 2019)
scATAC-seq: Reads (R1 and R2) were trimmed using TrimGalore (v. 0.6.0) and aligned aligned using STAR (v2.3.1, --outSJfilterIntronMaxVsReadN 0 --outFilterMatchNmin 25 --outFilterMismatchNmax 2 --alignIntronMax 1). Only short fragments (< 140bp) were kept , the short fragments were deduplicated using Picard (v2.5.0) and peaks were detected using MACS2 (v. 2.1.2). The cell barcodes (Index1) were quality filtered using FASTX toolkit (v. 0.0.13, -q 30 -p 80). The quality filtered barcodes were matched to the barcode white list (10X Genomics) and only barcodes with more than 10000 reads were kept. The raw aligned reads were split into cell-specific files using the filtered barcodes and individually deduplicated. Count matrices were generated by counting fragments for each cell using featureCounts (v.2.0.0) in peak detected regions. Cells and peaks were quality filtered and co-accessible peaks were identified using Cicero.
CUT&RUN: Reads trimmed with cutadpt and aligned using STAR (v2.3.1, --outSJfilterIntronMaxVsReadN 0 --outFilterMatchNmin 25 --outFilterMismatchNmax 2 --alignIntronMax 1).
RNA-seq: Reads were aligned using STAR (v2.3.1). Reads were counted using iRNA-seq (v1.0).
HiC: Reads were aligned and quality controlled using Hicup (v0.6.1). TADs were identified using HiTAD from TADlib (v0.3.1).
ECHiC: Reads were aligned and quality controlled using Hicup (v0.6.1). Interactions between virtual restriction fragments were detected using Chicago (v1.6.0) using custom weights calculated from high confidence interactions in the data.
Genome_build: hg19
Supplementary_files_format_and_content: ChIP-seq: Tab-delimited txt files containing normalized tag counts for each replicate in DNase I hypersensitive regions identified in a previous study (Rauch et al., 2019). For each replicate, read depth normalized bedGraph files are also supplied for filtered and deduplicated alignments.
Supplementary_files_format_and_content: scATAC-seq: Tab-deliminted txt file containing the peak co-accessibility (estimated with Cicero).
Supplementary_files_format_and_content: CUT&RUN: Tab-delimited txt files containing raw tag counts for each replicate in DNase I hypersensitive regions identified in a previous study (Rauch et al., 2019). For each replicate, read depth normalized bedGraph files are also supplied.
Supplementary_files_format_and_content: RNA-seq: Tab-delimited txt file containing raw tag counts for each replicate for all RefSeq genes . For each replicate, read depth normalized bedGraph files are also supplied.
Supplementary_files_format_and_content: Hi-C: The BED file contains all detected TADs and subTADs (identified using HiTAD).
Supplementary_files_format_and_content: ECHi-C: All interactions identified (using Chicago), as well as counts in all samples and annotation is also supplied in a tab-delimited txt file.
 
Submission date Feb 26, 2020
Last update date Aug 14, 2020
Contact name Susanne Mandrup
E-mail(s) s.mandrup@bmb.sdu.dk
Phone +45 6550 2340
Organization name University of Southern Denmark
Department Department of Biochemistry and Molecular Biologi
Street address Campusvej 55
City Odense M
State/province Fyn
ZIP/Postal code 5230
Country Denmark
 
Platform ID GPL18460
Series (1)
GSE140782 Highly connected enhancer communities control lineage-determining genes in human mesenchymal stem cells
Relations
BioSample SAMN14214189
SRA SRX7807100

Supplementary file Size Download File type/resource
GSM4340689_ChIP_CEBPb_Msc_E1_SM785.bedGraph.gz 121.6 Mb (ftp)(http) BEDGRAPH
SRA Run SelectorHelp
Raw data are available in SRA
Processed data provided as supplementary file
Processed data are available on Series record

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