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Sample GSM7732616 Query DataSets for GSM7732616
Status Public on Sep 29, 2023
Title iPSC EC Diff Day 0 FOXO1 C&R
Sample type SRA
 
Source name BJFF.6
Organism Homo sapiens
Characteristics cell line: BJFF.6
cell type: iPSC
cut&run antibody: FOXO1 (#2880, Cell Signaling Technology)
Extracted molecule genomic DNA
Extraction protocol Nuclei were isolated by incubating cells in Nuclear Extraction Buffer (NEB) which consists of 20mM HEPES KOH pH7.9, 10mM KCl, 0.1% Triton X-100, 20% Glycerol, EDTA-free Protease Inhibitor (11836170001, Roche) and water for 10 minutes on ice. Aliquots of 250,000 nuclei were spun down then resuspended in nuclear extraction buffer and slowly frozen at -80°C in a Mr. Frosty freezing container (C1562, Sigma-Aldrich).
Libraries were prepared with the xGen ssDNA & Low-Input DNA Library Prep Kit (#10009859, IDT) and quantified using the Agilent 4150 TapeStation and Agilent Bioanalyzer before sequencing with NovaSeq6000 (Illumina).
 
Library strategy OTHER
Library source genomic
Library selection other
Instrument model Illumina NovaSeq 6000
 
Description iPSC EC Diff Day 0 FOXO1 C&R SRM ID 2572614
Data processing library strategy: CUT&RUN
Paired-end CUT&RUN-seq reads were aligned first to the E. coli reference genome using bowtie (version 1.2.2) in paired-end with parameters -k 1 –best and –un to retain unmapped reads. Because of nonbiological variability among samples, the numbers of E. coli reads were not used for cell-number-normalization hereafter. Retained non-E. coli reads were then mapped to the mouse reference genome (mm10) or human reference genome (hg38) using bowtie in paired-end mode with parameters -p 20 -k 2 -m 2 –best. A BAM file containing CUT&RUN-seq fragments was computationally created from each aligned read-pair using samtools sort -n, bedtools bamToBed -bedpe, a manual conversion from BEDPE to BED3, and bedtools bedToBam. For display, the reference genomes were binned into 50bp windows using bedtools makewindows, and coverage of those bins by fragments was calculated using bedtools intersect -c. Fragment coverage was normalized per million mapped fragments, converted to bedGraph using bedGraphToBigWig, converted to wiggle using bigWigToWig, converted to TDF using igvtools toTDF, and then visualized in the IGV(version 2.16.2.) browser in hg38 for human samples.
MACS1.4 was used to identify regions significantly enriched in CUT&RUN-seq reads. Prior to peak-calling, individual reads from each paired-end alignment were discarded if they overlapped the ENCODE-defined Problematic Regions list corresponding to the reference genome in use, and further filtered in mouse if they overlapped the region chr1:24611436-24616256, because of an observed genomically amplified region in all samples near the Col19a1 gene. Retained reads were used for peak-calling against each sample’s corresponding, identically processed, control IgG. In mouse, parameters –keep-dup=auto and –p 0.001 were used; in human, parameters –keep-dup=auto and -p 1e-9 were used. To compare TCP vs. MCP coverage at regions of interest, we collapsed peaks called separately in each sample (N=3 TCP and N=4 MCP in mouse) using bedtools merge. Bedtools closest -t first was used to annotate each peak with the name of the gene whose transcript has the nearest transcription start site from mm10_refGene.gtf downloaded from the UCSC Genome Browser. Individual read coverage in each of the seven samples was separately quantified using bedtools intersect -c. For comparative analyses (Fig.5c), read coverage in each sample was normalized to the millions of mapped reads (RPM), and the average RPMs from each condition were calculated. For statistical analysis (Fig. 5d) of differential coverage, raw reads from the three TCP samples and three representative MCP samples (MCP20_1, MCP20_2, and MCP_38) were used as input for DEseq2. Peaks were considered differentially covered if they had DEseq2 adjusted log2 fold-change >1 or <-1 and adjusted p value of 0.05.
We used ROSE (https://bitbucket.org/young_computation/rose) to separately identify super-enhancers from each sample of MCP, TCP, Day 15 Untransduced p53KO iPSC, and Day 15 Lenti-P3F transduced p53KO iPSC CUT&RUN-seq data targeting H3K27ac, as previously described. Each sample was separately processed with its corresponding IgG. For each sample, we used MACS1.4 to identify two sets of peaks from each read set filtered as above. In mouse, we used parameter sets –keep-dup=auto –p 0.001 and –keep-dup=all –p 0.001; in human, we used parameter sets –keep-dup=auto -p 1e-9 and –keep-dup=all -p 1e-9. These two peak sets from each sample were collapsed into a per-sample set of peaks using bedtools merge; these collapsed peaks were used as input for ROSE with parameters -s 12500 -t 1000.
Assembly: hg38
Supplementary files format and content: bigWig, bed (for Untransduced Day 15 and P3F Day 15 H3K27ac data)
 
Submission date Aug 24, 2023
Last update date Sep 29, 2023
Contact name Hongjian Jin
E-mail(s) hongjian.jin@STJUDE.ORG
Organization name St Jude Children's Research Hospital
Department Center for Applied Bioinformatics
Street address 262 Danny Thomas Place
City Memphis
State/province TN
ZIP/Postal code 38015
Country USA
 
Platform ID GPL24676
Series (2)
GSE218274 PAX3-FOXO1 expression in endothelial progenitors dictates myogenic reprogramming and rhabdomyosarcoma identity
GSE241644 PAX3-FOXO1 dictates myogenic reprogramming and rhabdomyosarcoma identity in endothelial progenitors [Cut&Run]
Relations
BioSample SAMN37144268
SRA SRX21479518

Supplementary file Size Download File type/resource
GSM7732616_ECD_d0_FOXO1.humanPE38.pebt.frag.w50.FPM.bw.tdf 122.6 Mb (ftp)(http) TDF
SRA Run SelectorHelp
Raw data are available in SRA
Processed data provided as supplementary file

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