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| Status |
Public on Apr 27, 2021 |
| Title |
MT2 snATAC-seq |
| Sample type |
SRA |
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| Source name |
C2C12
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| Organism |
Mus musculus |
| Characteristics |
cell type: myotube
cell line: C2C12
treatment protocol: Differentiation of C2C12, ENCODE (https://www.encodeproject.org/documents/b42974fd-1490-4d51-bdcf-7db97a3e8fe0/@@download/attachment/C2C12_Wold_protocol.pdf)
library prep protocol: snATAC-seq protocol; SureCell ATAC-seq Library Preparation Kit (Bio-Rad, cat. #17004620).
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| Treatment protocol |
To differentiate myoblasts to myotubes, cells at 90-100% confluency were rinsed with 1X PBS and myoblast growth media was replaced with 10 mL differentiation media: high-glucose DMEM with L-glutamine and without sodium pyruvate, supplemented with 2% donor horse serum, 100 units/mL penicillin, 100 ug/mL streptomycin, and freshly-added 1uM insulin. Differentiation media was replaced every 24 hours for 3 days. ENCODE protocol: https://www.encodeproject.org/documents/b42974fd-1490-4d51-bdcf-7db97a3e8fe0/@@download/attachment/C2C12_Wold_protocol.pdf
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| Growth protocol |
C2C12 cells (ATCC, CRL-1772) were cultured on 10 cm plates in 10 mL myoblast growth media: high-glucose DMEM with L-glutamine and without sodium pyruvate, supplemented with 20% fetal bovine serum, 100 units/mL penicillin, and 100 ug/mL streptomycin. Cells were maintained at 20-50% confluency at 37C with 5% CO2 and passaged at 1:3 or 1:4 every 2 to 3 days.
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| Extracted molecule |
genomic DNA |
| Extraction protocol |
Cells were rinsed with 1X PBS and incubated with 2 mL TrypLE-Express for 5 minutes at 37C, which was then neutralized with 8 mL myoblast growth media. Nuclei were prepared following Bio-Rad's SureCell WTA 3' Nuclei Isolation protocol (https://support.illumina.com/content/dam/illumina-support/documents/documentation/chemistry_documentation/surecell/surecell-wta3-nuclei-demonstrated-protocol-1000000044178-00.pdf). Myotubes were both filtered (3 samples) and not filtered (2 samples) through a 40uM strainer before nuclei isolation but data were very similar between the two different nuclei preps. Tagmented DNA was barcoded and amplified in nanodroplets, then extracted following Bio Rad's SureCell ATAC-seq library kit (cat. #17004620; protocol document: https://www.bio-rad.com/webroot/web/pdf/lsr/literature/10000106678.pdf).
Bio-Rad's SureCell ATAC-seq library kit (cat. #17004620; protocol document: https://www.bio-rad.com/webroot/web/pdf/lsr/literature/10000106678.pdf)
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| Library strategy |
ATAC-seq |
| Library source |
genomic |
| Library selection |
other |
| Instrument model |
Illumina NextSeq 500 |
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| Description |
Tn5 tagmented C2C12 myotube nuclei from myotubes filtered through a 40uM strainer were collected for snATAC-seq (technical rep 2). Library preparation was performed following manufacturer’s instructions for the SureCell ATAC-seq Library Preparation Kit (Bio-Rad, cat. #17004620, https://www.bio-rad.com/webroot/web/pdf/lsr/literature/10000106678.pdf) for the target output of 5,000 cells per well, one well per sample. Nuclei and barcoded beads are streamed together in the microfluidics device to produce nanodroplets where the first amplification reaction takes place. Droplets are then broken and barcoded, tagmented DNA is purified for sequencing.
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| Data processing |
Use Docker container to run FASTQC (https://www.bioinformatics.babraham.ac.uk/projects/fastqc/) and generate HTML report for each fastq file in input directory. docker run --rm -v $1:/data/ bioraddbg/atac-seq-fastqc:v1.0.0 -i /data/ -o /data/fastqc_results --name fastqc. (Protocol document: https://www.bio-rad.com/webroot/web/pdf/lsr/literature/Bulletin_7191.pdf)
Use Docker container to run BAP (https://github.com/caleblareau/bap) and debarcode fastq files. Barcodes are parsed from read 1 and appended to read name for valid barcodes only. docker run --rm -v $1:/data/ bioraddbg/atac-seq-debarcode-dbg:v1.0.0 -i /data/ -o /data/debarcoded_reads --name debarcode. (Protocol document: https://www.bio-rad.com/webroot/web/pdf/lsr/literature/Bulletin_7191.pdf)
Use Docker container to run BWA (http://bio-bwa.sourceforge.net) to align to mm10. docker run --rm -v $1:/data/ -v /path/to/mm10/bwa/:/genome/ bioraddbg/atac-seq-bwa:v1.0.0 -i /data/debarcoded_reads/ -o /data/alignments/ -r /genome/ --name align. (Protocol document: https://www.bio-rad.com/webroot/web/pdf/lsr/literature/Bulletin_7191.pdf)
Use Docker container to run QC on aligned file with Picard (https://broadinstitute.github.io/picard/) CollectAlignmentSummaryMetrics and writes a text file with alignment summary metrics. docker run --rm -v $1:/data/ -v /path/to/mm10/:/genome/ bioraddbg/atac-seq-alignment-qc:v1.0.0 -i /data/alignments/ -r /genome/mm10.fa -o /data/alignment_qc --name alignment_qc. (Protocol document: https://www.bio-rad.com/webroot/web/pdf/lsr/literature/Bulletin_7191.pdf)
Use Docker container to filter beads (barcodes) from cell-free nanodroplets, and identify beads that ended up in the same nanodroplet with a nucleus using Jaccard indexing. docker run --rm -v $1:/data/ bioraddbg/atac-seq-filter-beads:v1.0.0 -i /data/alignments/ -o /data/bead_filtration/ -r mm10 --name bead_filtration --cpus="10". (Protocol document: https://www.bio-rad.com/webroot/web/pdf/lsr/literature/Bulletin_7191.pdf)
Use Docker container to merge beads that ended up in the same nanodroplet with a nucleus using BAP (https://github.com/caleblareau/bap) . docker run --rm -v $1:/data/ bioraddbg/atac-seq-deconvolute:v1.0.0 -i /data/alignments/ -f /data/bead_filtration/ -r mm10 -o /data/deconvoluted_data --name deconv_${2}. (Protocol document: https://www.bio-rad.com/webroot/web/pdf/lsr/literature/Bulletin_7191.pdf)
Use Docker container to filter out cells with low read depth using a UMI- (unique molecular identifier) based "knee call". Outputs bam file and cell list included in this submission. docker run --rm -v $1:/data/ bioraddbg/atac-seq-cell-filter:v1.0.0 -i /data/deconvoluted_data/ -o /data/cells_filtered/ -r mm10 --name cell_filtration. (Protocol document: https://www.bio-rad.com/webroot/web/pdf/lsr/literature/Bulletin_7191.pdf)
Use Docker container to run MACS2 (https://github.com/taoliu/MACS). Outputs peaks included in this submission. docker run --rm -v $1:/data/ bioraddbg/atac-seq-macs2:v1.0.0 -i /data/deconvoluted_data/ -r mm10 -o /data/peaks --name peak_calling. (Protocol document: https://www.bio-rad.com/webroot/web/pdf/lsr/literature/Bulletin_7191.pdf)
Use Docker container to run QC on deconvoluted alignment data, generating a FRIP score, insert size metrics histogram, and TSS score. In v.1.0.1, docker tool is fixed to run chromVar and generate peaks-by-cells counts matrix; v. 1.0.0 crashed at this step, hence our custom code. docker run --rm -v $1:/data/ bioraddbg/atac-seq-qc:v1.0.0 -r mm10 -d /data/deconvoluted_data/ -p /data/peaks -o /data/atac_qc --name atac_qc. (Protocol document: https://www.bio-rad.com/webroot/web/pdf/lsr/literature/Bulletin_7191.pdf)
Use Docker container to generate an HTML and PDF report of all the outputs using MultiQC (https://multiqc.info). (Protocol document: https://www.bio-rad.com/webroot/web/pdf/lsr/literature/Bulletin_7191.pdf)
Merge peaks across all samples (https://github.com/fairliereese/lab_pipelines/tree/master/sc_atac_pipeline). For example, python merge_peaks.py -p peakfiles.csv --o merged_peaks
Use custom script to generate CSV file of peaks-by-cells matrix using merged peaks, cell list, and alignments (https://github.com/fairliereese/lab_pipelines/tree/master/sc_atac_pipeline). For example, python gen_count_matrix.py -p merged_peaks.bed -b MB1/MB1.bam -bc MB1/MB1.aboveKneeBarcodes.csv -e MB1 --o MB1/ --full_csv
Genome_build: mm10
Supplementary_files_format_and_content: Peak calls from MACS2.
Supplementary_files_format_and_content: CSV file of cell IDs passing UMI cutoff.
Supplementary_files_format_and_content: Peaks-by-cells matrix generated using custom code (https://github.com/fairliereese/lab_pipelines/tree/master/sc_atac_pipeline) and provided processed files: peaks, barcodes, and aligned reads.
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| Submission date |
Apr 27, 2021 |
| Last update date |
Apr 28, 2021 |
| Contact name |
Elisabeth Rebboah |
| E-mail(s) |
erebboah@uci.edu
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| Organization name |
University of California, Irvine
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| Department |
Developmental and Cell Biology
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| Lab |
Mortazavi Lab
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| Street address |
2300E Biological Sciences 3
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| City |
Irvine |
| State/province |
California |
| ZIP/Postal code |
92617 |
| Country |
USA |
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| Platform ID |
GPL19057 |
| Series (1) |
| GSE168776 |
Mapping and modeling the genomic basis of differential RNA isoform expression at single-cell resolution with LR-Split-seq |
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| Relations |
| BioSample |
SAMN18879537 |
| SRA |
SRX10687366 |
| Supplementary file |
Size |
Download |
File type/resource |
| GSM5267110_MT2.aboveKneeBarcodes.csv.gz |
51.8 Kb |
(ftp)(http) |
CSV |
| GSM5267110_MT2.aligned_peaks.narrowPeak.gz |
4.3 Mb |
(ftp)(http) |
NARROWPEAK |
| GSM5267110_MT2_full_counts.csv.gz |
67.3 Mb |
(ftp)(http) |
CSV |
SRA Run Selector |
| Raw data are available in SRA |
| Processed data provided as supplementary file |
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