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| Status |
Public on Dec 20, 2023 |
| Title |
cKO_scATAC |
| Sample type |
SRA |
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| Source name |
Colon
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| Organism |
Mus musculus |
| Characteristics |
tissue: Colon
cell type: Treg
genotype: WT, Foxp3Cre x Rorc fl/fl, Foxp3Cre x Ikzf2 fl/fl, Foxp3Cre x Gata3 fl/fl, Foxp3Cre x cMaf fl/fl
strain: B6
Sex: pooled male and female
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| Extracted molecule |
genomic DNA |
| Extraction protocol |
For scATAC-seq, colonic lamina propria cells were sorted for Tregs (DAPI-CD19-CD8-CD11b-CD4+TRCRb+CD25hi) and activated Tconvs (DAPI-CD19-CD8-CD11b-CD4+TRCRb+CD25loCD44hi). Cells were hashtagged by condition at the time of staining as detailed below.
Nuclei isolation, transposition, GEM generation, and library construction targeting capture of 10000 cells were carried out as detailed in the Chromium Next GEM Single Cell ATAC manual (10x Genomics) with modifications to allow sample hashtagging (see below). Libraries were pooled and sequenced on an Illumina NovaSeq 6000 to a final median depth of approximately 20-30,000 paired-end reads per cell. Sequencing data were converted to fastq files, aligned to the mm10 reference genome, and quantified per cell using Cell Ranger ATAC software (10x Genomics, v1.2). To include multiple experimental conditions in the same scATAC run, we hashtagged cells using a modification of the ASAP-seq strategy (Mimitou et al., 2021) for low cell input primary cell samples. Before sorting, cells were hashtagged with mouse TotalSeqA DNA-barcoded hashtag antibodies at the same time as staining with fluorophore-conjugated antibodies (BioLegend). Cells were sorted into RPMI + 5% FCS in DNA Lo-Bind tubes (Eppendorf, cat # 022431021). After spinning down for 5 min at 500g in a refrigerated centrifuge at 4C, cells were resuspended in 100 μl chilled 0.1x Omni Lysis buffer (1x Omni Lysis buffer (10mM Tris-HCl, 10mM NaCl, 3 mM MgCl2, 0.1% Tween-20, 0.1% NP40 substitute/IGEPAL, 0.01% Digitonin, 1% BSA in nuclease free water) diluted 1:10 in Wash/Lysis Dilution Buffer (10mM Tris-HCl, 10mM NaCl, 3 mM MgCl2, 1% BSA in nuclease free water), gently mixed by pipetting, and incubated on ice for 6.5 min. Following lysis, 100 μl chilled wash buffer was added and gently mixed by pipetting. Cells were spun down for 5 min at 500g at 4C, all but 5 μl of supernatant was removed, and 45 μl of chilled 1x nuclei buffer (10x Genomics) was added without mixing. After one more centrifugation step at 500g, 4C for 5 min, supernatant was removed, and samples were resuspended in 7ul 1x nuclei buffer for cell counting and input into transposition, barcoding, and library preparation according to the Chromium Next GEM Single Cell ATAC manual (10x Genomics). Modifications to the original 10X protocol were made as described in the original ASAP-seq publication (Mimitou et al., 2021) and as detailed at https://citeseq.files.wordpress.com/2020/09/asap_protocol_20200908.pdf. Briefly, 0.5 μl of 1uM BOA bridge oligo was spiked into the barcoding reaction. During GEM incubation, an additional 5 min incubation at 40C was added to the beginning of the protocol. 43.5 instead of 40.5 μl of Elution Solution I was added during silane bead elution to recover 43 μl. 40 μl was used for SPRI clean up as indicated in the protocol, while 3 μl was set aside. During SPRI cleanup, the supernatant was saved. The bead bound fraction was processed as in the protocol, while for the supernatant fraction, 32 μl SPRI was added for 5 min. Beads were collected on a magnet, washed twice with 80% ethanol, and eluted in 42 μl EB. This 42 μl was combined with the 3 μl set aside from the previous step as input into the HTO indexing reaction. HTO Indexing PCR was run with partial P5 and indexed Rpxx primers (https://citeseq.files.wordpress.com/2020/09/asap_protocol_20200908.pdf) as: 95C 3 min, 12-14 cycles of (95C 20 sec, 60C 30 sec, 72C 20 sec), 72C 5 min. The PCR product was cleaned up with 1.6X SPRI purification for quantification and sequencing alongside ATAC libraries.
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| Library strategy |
ATAC-seq |
| Library source |
genomic single cell |
| Library selection |
other |
| Instrument model |
Illumina NovaSeq 6000 |
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| Data processing |
Sequencing data were converted to fastq files, aligned to the mm10 reference genome, and quantified per cell using Cell Ranger ATAC software (10x Genomics, v1.2).
Hashtag processing followed the original recommendations of the ASAP-seq paper (Mimitou et al, Nature Biotech, 2021), using asap_to_kite (https://github.com/caleblareau/asap_to_kite) to process FASTQs files for downstream quantification by the bustools and kite workflows {Melsted et al, Nature Biotech 2021; Booeshagi et al, bioRxiv, 2022}. We used the HTODemux() (Stoeckius et al, Genome Biology, 2018) function in the Seurat package (v4.0.2) (Hao et al, Cell, 2021) to remove doublets and call hashtag identities.
To enable comparisons across conditions and datasets, we used a common set of Treg-specific open chromatin regions, defined previously (Chowdhary et al., 2023) by supplementing pan-immunocyte OCRs from the ImmGen consortium(Yoshida et al., 2019) with additional peaks from Treg spleen and colon scATAC-seq data in (Chowdhary et al., 2023). To arrive at the final peak set, we also called peaks on the data generated in this study, using Archr v1.0.1(Granja et al., 2021) and MACS2 v2.2.7.1(Zhang et al., 2008) to call fixed-width peaks of 250bp within cell clusters. Any new OCRs not overlapping with the previous peak sets were added to the final merged peak set used for downstream analysis.
scATACseq data analysis was performed using Signac v1.4(Stuart et al., 2021). For quality control, only cells with at least 1x103 fragments per cell (depending on sequencing depth of experiment), greater than 25 percent reads in peaks, TSS enrichment score greater than 2, nucleosome signal less than 10, and ratio of blacklist-region reads less than 0.05 were retained for further analysis. Putative doublets identified by ArchR v1.0.1(Granja et al., 2021) and non-Treg, non-Tconv contaminant cells were also removed. We used the latent semantic indexing approach as previously described (Cusanovich et al., 2018; Stuart et al., 2019). Binarized count matrices were normalized using the term frequency-inverse document frequency (TF-IDF) transformation and reduced in dimensionality by singular value decomposition (SVD). As the first component was highly correlated with sequencing depth, SVD components 2-30 were used to generate a shared nearest neighbor (SNN) graph for clustering and as input into UMAP(McInnes et al., 2018) with cosine distance metric for visualization.
Assembly: mm10
Supplementary files format and content: .mtx ATAC counts matrices, peaks.txt files have OCR locations, barcodes.txt files have cell barcodes
Supplementary files format and content: fragments.tsv.gz files have raw ATAC fragments, fragments.tsv.gz.tbi files are index of fragments files
Supplementary files format and content: MetaData.txt files have relevant metadata, including cell population assignment, UMAP coordinates
Supplementary files format and content: Hashtag_Counts.txt files contain raw counts of ASAPseq hashtags by cell barcode for cells included in ATAC counts matrices
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| Submission date |
Aug 11, 2023 |
| Last update date |
Dec 20, 2023 |
| Contact name |
CBDM Lab |
| E-mail(s) |
cbdm@hms.harvard.edu
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| Phone |
617-432-7747
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| Organization name |
Harvard Medical School
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| Department |
Microbiology and Immunobiology
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| Lab |
CBDM
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| Street address |
77 Avenue Louis Pasteur
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| City |
Boston |
| State/province |
MA |
| ZIP/Postal code |
02215 |
| Country |
USA |
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| Platform ID |
GPL24247 |
| Series (1) |
| GSE240657 |
Homeostatic, repertoire and transcriptional relationships between colon T regulatory cell subsets |
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| Relations |
| BioSample |
SAMN36996184 |
| SRA |
SRX21337870 |
| Supplementary file |
Size |
Download |
File type/resource |
| GSM7707142_cko_scatac.mtx.gz |
12.3 Mb |
(ftp)(http) |
MTX |
| GSM7707142_cko_scatac_Hashtag_Counts.txt.gz |
5.7 Kb |
(ftp)(http) |
TXT |
| GSM7707142_cko_scatac_MetaData.txt.gz |
16.0 Kb |
(ftp)(http) |
TXT |
| GSM7707142_cko_scatac_barcodes.txt.gz |
3.2 Kb |
(ftp)(http) |
TXT |
| GSM7707142_cko_scatac_peaks.txt.gz |
1.6 Mb |
(ftp)(http) |
TXT |
| GSM7707142_fragments.tsv.gz |
2.1 Gb |
(ftp)(http) |
TSV |
| GSM7707142_fragments.tsv.gz.tbi.gz |
1008.6 Kb |
(ftp)(http) |
TBI |
SRA Run Selector |
| Raw data are available in SRA |
| Processed data provided as supplementary file |
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