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Sample GSM4223584 Query DataSets for GSM4223584
Status Public on Apr 22, 2020
Title OmniATAC-seq_MM165_BL
Sample type SRA
 
Source name Melanoma cell line
Organism Homo sapiens
Characteristics cell line: MM165
tissue type: Cutaneous melanoma
condition: Baseline
Treatment protocol For the knock-down data: SOX10, TFAP2A and the control knockdown was performed in MM001 using respectively a SMARTpool of four siRNAs against, respectively, SOX10 (SMARTpool: ON-TARGETplus SOX10 siRNA, number L017192-00-0005, Dharmacon), TFAP2A (SMARTpool: ON-TARGETplus TFAP2A siRNA, number L-006348-02-0005, Dharmacon) and a negative control pool (ON-TARGETplus non-targeting pool, number D-001810-10-05, Dharmacon) at a concentration of 20 nM for SOX10-KD, and 40 nM for TFAP2A-KD and the control using as medium Opti-MEM (Thermo Fisher Scientific) and omitting antibiotics. The cells were incubated for 72 h before processing.
Growth protocol Cells were cultured at 37°C with 5% CO2 and were maintained in Ham's F10 nutrient mix (Thermo Fisher Scientific) supplemented with 10% fetal bovine serum (FBS; Invitrogen) and 100 µg ml-1 penicillin/streptomycin (Thermo Fisher Scientific).
Mentioned per sample in the SAMPLE section.
Extracted molecule genomic DNA
Extraction protocol Cells were washed, trypsinised, spun down at 1000 RPM for 5 min, medium was removed and the cells were resuspended in 1 mL medium. Cells were counted and experiments were only continued when a viability of above 90% was observed. 50,000 cells were used per sample. OmniATAC-seq was performed as described previously in Corces et al., 2017; and ATAC-seq as described in Buenrostro et al., 2015.
Library prep was performed as described before in Corces et al., 2017 for OmniATAC-seq samplas; and as in Buenrostro et al., 2013 for ATAC-seq samples.
 
Library strategy ATAC-seq
Library source genomic
Library selection other
Instrument model Illumina NextSeq 500
 
Data processing Data processing of human melanoma baseline OmniATAC-seq samples: Paired-end reads were mapped to the human genome (hg19-Gencode v18) using bowtie2 (v2.2.6). Mapped reads were sorted using SAMtools (v1.8) and duplicates were removed using Picard MarkDuplicates (v1.134). Reads were filtered by removing chromosomal reads and filtering for Q>30 using SAMtools. Bam files of technical replicates of the same cell line were merged at this point using samtools merge. Peaks were called using MACS2 (v2.1.2) callpeak using the parameters -q 0.05, --nomodel, --call-summits, --shift -75 --keep-dup all and --extsize 150 per sample. Chromosomal peaks, blacklisted regions (ENCODE) and peaks overlapping with alternative chromosomes were removed. Summits were extended by 250bp up- and downstream using slopBed (bedtools; v2.28.0), providing human chromosome sizes. Peaks were normalised for the library size using a custom script and overlapping peaks were filtered using the peak score by keeping the peak with the highest score. For visualisation in IGV, normalised bigWigs were made by bamCoverage (Deeptools, v3.3.1), using as parameters --normalizeUsing None, -bl EncodeBlackListedRegions --effectiveGenomeSize 2913022398 and as scaling parameter (-scaleFactor) 1/(RIP/1E6), where the RIP stands for the number of reads in peaks.
Data processing of non-human (Omni)ATAC-seq samples, and of human SOX10 and TFAP2A knock-down OmniATAC-seq data: Adapter sequences were trimmed from the fastq files using fastq-mcf (as part of eautils; v1.05) and the read quality was checked using FastQC (v0.11.8). Reads were mapped using STAR (v2.5.1b) (for the zebrafish samples paired-end reads were mapped) to the genome which were downloaded from UCSC (http://hgdownload.cse.ucsc.edu/goldenPath/) (for human: hg19-Gencode v18; for dog: canFam3; for horse: equCab2; for pig: susScr11; for mouse: mm10; for zebrafish: danRer10) and by applying the parameters --alignIntronMax 1 and --aslignIntronMin 2. Mapped reads were filtered for quality using SAMtools (v1.2) view with parameter –q4, sorted with SAMtools sort and indexed using SAMtools index. Peaks were called using MACS2 (v2.1.2) callpeak using the parameters -q 0.05, --nomodel, --call-summits, --shift -75 --keep-dup all and with the genome size for the correct species in --g, and this for each sample per species separately. Summits were extended by 250bp up- and downstream using slopBed (bedtools; v2.28.0), providing the chromosome sizes for the specific species. Per sample, peaks were normalised for the library size using a custom script and overlapping peaks were filtered using the peak score (keeping the highest scoring peak). Normalised bedGraphs were produced by genomeCoverageBed (as part of bedtools; v2.28.0) using as scaling parameter (-scale) 1E6/(number of non-chromosomal mapping reads). BedGraphs were converted to bigWigs by the bedtools suit functions bedSort to sort the bedGraphs, followed by bedGraphToBigWig to create the bigWigs, which were used in IGV for visualisation.
Genome_build: For human: hg19-Gencode v18; for dog: canFam3; for horse: equCab2; for pig: susScr11; for mouse: mm10; for zebrafish: danRer10.
Supplementary_files_format_and_content: bigWig files represent the coverage of the ATAC-seq signal.
 
Submission date Dec 17, 2019
Last update date Apr 23, 2020
Contact name Stein Aerts
E-mail(s) stein.aerts@kuleuven.vib.be
Organization name KU Leuven
Street address O&N4 Herestraat 49 PO Box 602
City Leuven
ZIP/Postal code 3000
Country Belgium
 
Platform ID GPL18573
Series (1)
GSE142238 Cross-species analysis of melanoma enhancer logic using deep learning
Relations
BioSample SAMN13616478
SRA SRX7401786

Supplementary file Size Download File type/resource
GSM4223584_MM165_atac.norm.bw 89.8 Mb (ftp)(http) BW
SRA Run SelectorHelp
Raw data are available in SRA
Processed data provided as supplementary file

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