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| Status |
Public on Mar 08, 2024 |
| Title |
ChIPseq_ZFP143_DMSO |
| Sample type |
SRA |
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| Source name |
E14TG2a
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| Organism |
Mus musculus |
| Characteristics |
cell line: E14TG2a
cell type: Embryonic Stem Cell
genotype: ZFP143-FKBP
treatment: DMSO
antibody: HA (ab9110, Abcam)
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| Treatment protocol |
For the knock-in of the FKBP sequence at the genes of interest, cells were transfected with the plasmids containing the gRNA sequence and the donor plasmid designed to include the FKBP-2xHA-P2A-GFP in between two homology arms for the gene of interest. To induce ZFP143 degradation, the cells were treated with 500 nM dTAG-V1 or DMSO as a control.
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| Growth protocol |
Mouse Embryonic Stem Cells E14Tg2A (129/Ola) cell lines were cultured on 0.1% gelatin-coated plates in serum-free DMEM/F12 (Gibco) and Neurobasal (Gibco) medium (1:1) supplemented with N-2 (Gibco), B-27 (Gibco), BSA (0.05%, Gibco), 10 × 4 U of Leukaemia Inhibitory Factor (LIF) (Millipore), MEK inhibitor PD0325901 (1 μM, Selleckchem), GSK3-β inhibitor CHIR99021 (3 μM, Cayman Chemical) and 1-Thioglycerol (1.5 × 10−4 M, Sigma-Aldrich). The cell lines were passaged every 2 days in daily culture.
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| Extracted molecule |
genomic DNA |
| Extraction protocol |
ChIP-seq: Chromatin was cross-linked using 1% FA final concentration. Chromatin was sheared on a Bioruptor Plus sonication instrument and immunoprecipitated by different antibodies. DNA was purified using the MiniElute PCR purification kit from Qiagen. TT-seq: Libraries for TTchem-seq were prepared following a published protocol (Gregersen et al., 2020). Cells were labelled with 2 mM of the uridine analog 4-thiouridine (4sU) for 10 min. Total RNA was isolated and fragmented. The 4sU-biotin labelled RNA was enriched using µMacs Streptavidin Kit (Miltenyi). Hi-C: Hi-C data were generated using as a previous published protocol (Rao et al., 2014) with minor modifications (Haarhuis et al., 2017). Cells were harvested and crosslinked using 2% formaldehyde. Crosslinked DNA was digested in nucleus using MboI (NEB), and biotinylated nucleotides were incorporated at the restriction overhangs and joined by blunt-end ligation. The ligated DNA was enriched in a streptavidin pull-down 4C-seq: 4C-seq was performed as previously described (Geeven et al., 2018; van de Werken et al., 2012) using a two-step PCR method for indexing described first in (Haarhuis et al., 2017). MboI (NEB) was used as the first restriction enzyme and Csp6I (NEB) as the second restriction enzyme. ATAC-seq: Cells were washed in cold PBS and subjected to lysis using a 2x lysis buffer. Subsequently, the cells were centrifuged, and the resulting pellet was treated with 2xTD buffer and 2 uL of transposon mix. RNA-seq: RNA was first isolated using standard RNA isolation procedure from Qiagen RNeasy Mini Kit (Qiagen), including a DNaseI treatment.
ChIP-seq: Libraries were prepared following the KAPA HTP Library Preparation Kit (Roche). TT-seq: Libraries were prepared using KAPA RNA HyperPrep and KAPA Dual-Indexed Adapter kits (Roche) using dual indexing adapters. Hi-C: Hi-C libraries were prepared using a standard end-repair and A-tailing method. 4C-seq: 4C-seq libraries were prepared using a two-step PCR method for indexing described first in (Haarhuis et al., 2017). ATAC-seq: PCR amplification was conducted using KAPA HiFi HotStart ReadyMix (Roche). Fragments ranging from 200 to 700 bp were purified utilising AMPure XP beads (Beckman Coulter). RNA-seq: Libraries were prepared following the TruSeq Stranded mRNA kit (Illumina) with TruSeq RNA Single Indexes set A (Illumina).
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| Library strategy |
ChIP-Seq |
| Library source |
genomic |
| Library selection |
ChIP |
| Instrument model |
NextSeq 550 |
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| Description |
ZFP143_peaks.bed
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| Data processing |
ChIP-seq: ZFP143 ChIP-seq reads were mapped to the mm10 mouse reference genome assembly using bwa mem. Calibrated CTCF ChIP-seq reads were mapped to the mm10 mouse and hg38 human reference genome assemblies using bwa mem. Uniquely mapped reads with MAPQ > 10 mapped in proper read pairs were selected using SAMtools. Duplicate reads were filtered out using the Picard “MarkDuplicates” function. Scaling factors for calibrated CTCF ChIP-seq normalisation were calculated as described previously (Greulich et al., 2021). The bigwig coverage tracks were generated using the “bamCoverage” and "bamCompare" functions from the deepTools. TT-seq: TT-seq reads were mapped to the mm10 mouse reference genome assembly using STAR with GENCODE vM25 gene annotation. Uniquely mapped reads with MAPQ > 10 were selected using SAMtools. Duplicate reads were filtered out using the Picard “MarkDuplicates” function. The reads were split by strand using SAMtools as described previously (Gregersen et al., 2020). Gene counts were obtained using the ”htseq-count” function from HTSeq. Bigwig coverage tracks were generated separately for forward and reverse strands using the "bamCoverage" function from deepTools. Hi-C: Hi-C reads were mapped to the mm10 mouse reference genome assembly using bwa mem with the Open2C distiller-nf pipeline. Mapped reads were parsed using pairtools with the “walks-policy” parameter set to “mask” and the “max_mismatch_bp” parameter set to 1. Read pairs were then binned into Hi-C contact matrices. Iterative correction of the matrices and removal of low coverage bins was performed using the "balance" function from cooler. 4C-seq: 4C-seq reads were processed as previously described (Haarhuis et al., 2017; van de Werken et al., 2012) using custom R scripts. The sequencing data were demultiplexed per viewpoint and mapped to the mm10 mouse reference genome assembly using the bwa aln and bwa samse. To generate the read counts per RE fragment, for each fragment we counted the number of mapped reads that have the same start or end coordinates as the fragment. To obtain 4C contact profiles, the counts were normalised to the total number of overlaps detected per million reads. ATAC-seq: ATAC-seq reads were mapped to the mm10 mouse reference genome assembly bwa mem. Uniquely mapped reads that were not mapped to mitochondrial DNA and had MAPQ > 10 were selected using SAMtools. Duplicate reads were filtered out using the Picard “MarkDuplicates” function. RNA-seq: RNA-seq reads were mapped to the mm10 mouse reference genome assembly using STAR with GENCODE vM25 gene annotation. Read counts per gene were obtained using the "quantMode" parameter in STAR.
Assembly: mm10
Supplementary files format and content: ChIP-seq: normalized signal tracks in bigWig format; peaks in BED format. TT-seq: normalized signal tracks in bigWig format; read counts per gene in TXT format. Hi-C: contact matrices in MCOOL and HIC formats. 4C-seq: viewpoint coordinates in TXT format; normalized coverage per fragment in TSV format. RNA-seq: read counts per gene in TXT format.
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| Submission date |
Mar 05, 2024 |
| Last update date |
Mar 08, 2024 |
| Contact name |
Mikhail Magnitov |
| Organization name |
The Netherlands Cancer Institute
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| Street address |
Plesmanlaan 121
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| City |
Amsterdam |
| ZIP/Postal code |
1066CX |
| Country |
Netherlands |
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| Platform ID |
GPL21626 |
| Series (1) |
| GSE260914 |
ZNF143 is a transcriptional regulator of nuclear-encoded mitochondrial genes that acts independently of looping and CTCF |
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| Relations |
| BioSample |
SAMN40268834 |
| SRA |
SRX23842007 |
| Supplementary file |
Size |
Download |
File type/resource |
| GSM8127953_ZFP143_DMSO.rpgc.bw |
80.4 Mb |
(ftp)(http) |
BW |
SRA Run Selector |
| Raw data are available in SRA |
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