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| Status |
Public on Nov 28, 2022 |
| Title |
DP-Rag1ko-CBEko-TEAp-3C-HTGTS-rep3 |
| Sample type |
SRA |
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| Source name |
Thymocytes
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| Organism |
Mus musculus |
| Characteristics |
strain: C57BL/6
tissue: Thymus
cell type: DP thymocytes
genotype: CBE-/-Rag1-/-
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| Growth protocol |
All experiments involving mice were performed using protocols approved by Southern Medical University Animal Studies Committee. Mice were on a C57Bl/6 genetic background . Animals were housed and bred in a specific pathogen-free animal facility.
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| Extracted molecule |
genomic DNA |
| Extraction protocol |
For 3C-HTGTS, mouse thymus and liver were removed, cells were filtered through nylon mech.10 million cells were cross-linked with 1% formaldehyde. Cell were lysed and digest with 200U MboI overnight at 37°C. The sample was ligated with T4 DNA ligase overnight at 16°C. Crosslinks were reversed by Proteinase K and RNase A prior to DNA extraction with 1:1 phenol-chloroform and precipitation with ethanol. The 10ug 3C DNA was sonicated to 300-500bp and was linearly amplified with a biotinylated primer. The biotin-labeled single-stranded DNA products were enriched with streptavidin C1 beads, and followed by 3’ ends ligation with the bridge adaptor. The adaptor-ligated products were amplified via nested PCR using a nested primer and an adaptor-complementary primer. And a final PCR for another 5-10 cycles with P5 and P7 was performed. After purification of the PCR products, the final libraries were sequenced on an Illumina NovaSeq 6000 platform to obtain 150 bp or 250 bp paired-end reads.
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| Library strategy |
OTHER |
| Library source |
genomic |
| Library selection |
other |
| Instrument model |
Illumina NovaSeq 6000 |
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| Data processing |
Illumina Casava1.7 software used for basecalling.
Pair-wise chromatin interactions for 3C-HTGTS data processing. Paired-end Illumina sequencing fastq data were filtered by removing adapters and low-quality reads with using fastp (v0.20.0). Trimmed reads again were extracted from the sequence file after quality control with Cutadapt (v1.18). Paired-end reads containing nested primer or adapter primer were merged manually using restriction enzyme recognition sequences into single reads with Pear (v0.9.6), then the first digested fragment behind the bait was obtained through spliting the single reads into fragments according to restriction enzyme recognition sequences. The remaining single-end reads were aligned to the enzyme-digested mm10 reference genome with Bowtie2 (v2.4.5, parameter: -p 8 --sensitive), and mouse genome sequence (mm10) was retrieved from the UCSC and we extracted concordantly exactly alignments using SAMtools (v1.9). Self-ligation reads and off-targeted reads were filtered after mapping. For visualization, we converted the final bam files into bedGraph file using Bedtools (v2.29.2). The signal peak bedGraph file was obtained by post-comparison filtering, signal statistics, and standardization. We normalized bedGraph file using CPM (Counts Per Million in cis) normalization method, and visualized on IGV genome browser. Differential pair-wise interactions were identified by the R package R.4Cker (v1.0.0, k=30) with the function nearBaitAnalysis called to define domains of interaction with the bait and DESeq2 (v1.34.0, p < 0.05). Finally, we organized the results report and visualized it with the Bioconductor package ggplot2 (v3.3.6). The analysis of the correlation for experimental repetition used the R package corrplot(v.0.92).
Pair-wise chromatin interactions for 4C data processing. Paired-end reads were obtained through quality filtering and adapters trimming using fastp (v0.20.0). Notablely, 4C reads which contain a secondary restriction enzyme were removed crosslinks after digesting with the primary restriction enzyme MboI and ligating, so more additional fragments from secondary restriction enzyme digestion and ligation should be discarded necessarily. The first digested fragment for the primary restriction enzyme MboI behind the bait was only extracted and mapped to the enzyme-digested mm10 reference genome by Bowtie2 (v2.4.5, parameter: -p 8 --sensitive) in the form of single-end reads, and we extracted concordantly exactly alignments using SAMtools (v1.9). We again filtered the self-ligation reads and off-targeted reads, etc.. For visualization, we converted the final bam files into bedGraph file using Bedtools (v2.29.2). Reads numbers were counted and normalized by CPM (Counts Per Million in cis) normalization method per sample, and then visualized on IGV genome browser. The analysis of the correlation for experimental repetition used the R package corrplot (v.0.92).
Three-way chromatin interactions for 3C-HTGTS data processing. As the 3C-HTGTS analysis of pair-wise chromatin interactions, Paired-end Illumina sequencing reads were filtered by removing adapters and low-quality reads with using fastp (v0.20.0). Trimmed reads again were extracted from the sequence file after quality control with Cutadapt (v1.18). Paired-end reads containing Nested primer or Adapter primer were merged manually using restriction enzyme recognition sequences into single reads with Pear (v0.9.6), then multiple digested fragments for the restriction enzyme MboI behind the bait were splited and individually aligned to the enzyme-digested mm10 reference genome by Bowtie2 (v2.4.5, parameter: -p 8 --sensitive) in the form of single-end reads, and we extracted concordantly exactly alignments using SAMtools (v1.9). We converted the final bam files into bed file using Bedtools (v2.29.2). The self-ligation fragments and off-targeted fragments were filtered after mapping. Subsequently, we put all the digested fragments retrieved from the same read according to the unique ID of each read on one line, then removed the continuous fragments. In order to create contact matrices, we directly extracted the first two digested fragments except for the fragment where bait was located, or a variety of combinations of three fragments were obtained by arranging all fragments from the same read. Raw contact matrices were generated at 3-kb, 5-kb, 10-kb resolutions. For raw contact matrices correction, these interaction counts were normalized for a total of 1,000,000 interactions at the same resolutions. Similar to a Hi-C matrix, coverage was represented in a 2-dimensional matrix where each point represented the number of interactions found between two bins meaning a specific resolution. Visualization of three-way contact matrices was done with the R package GENOVA (v1.0.0) then differential analysis and visualization of local interactions from three-way interactions were obtained using the Bioconductor package DESeq2 (v1.34.0, p < 0.001). Loops seen on IGV genome browser were called using fixed-size bin resolutions from 3-kb to 10-kb. Briefly, interaction loops (contact frequencies >= 20) were identified through using raw contact frequencies. The distribution for the frequencies of unique reads containing the pair-wise and multi-way chromatin interactions was counted after aligning and filtering, and visualized with the Bioconductor package ggplot2 (v3.3.6).
Three-way chromatin interactions for 4C data processing. As the 4C analysis of pair-wise chromatin interactions, adapters of the paired-end reads were trimmed with fastp (v0.20.0). We only retained reads that were separated by sites associated with the first restriction enzyme MboI. In other words, only fragments with two or more primary restriction enzyme sites were considered for identification of multi-way interactions. Multiple digested fragments for the primary restriction enzyme MboI behind the bait were splited and individually aligned to the enzyme-digested mm10 reference genome by Bowtie2 (v2.4.5, parameter: -p 8 --sensitive) in the form of single-end reads, and we extracted concordantly exactly alignments using SAMtools (v1.9). We converted the final bam files into bed file using Bedtools (v2.29.2). We filtered the self-ligation fragments and off-targeted fragments after mapping. Subsequently, we put all the digested fragments retrieved from the same read according to the unique ID of each read on one line, then removed the continuous fragments. In order to create contact matrices, we directly extracted the first two digested fragments except for the fragment where bait was located, or a variety of combinations of three fragments were obtained by arranging all fragments from the same read. Raw contact matrices were generated at 3-kb, 5-kb, 10-kb resolutions. For raw contact matrices correction, these interaction counts were normalized for a total of 1,000,000 interactions at the same resolutions. Also similar to a Hi-C matrix, coverage was represented in a 2-dimensional matrix where each point represented the number of interactions found between two bins meaning a specific resolution. Heatmap of three-way contact matrices was done with the R package GENOVA (v1.0.0) and the distribution for the frequencies of unique reads containing the pair-wise and multi-way chromatin interactions was counted after aligning and filtering, and visualized with the Bioconductor package ggplot2 (v3.3.6).
Assembly: mm10
Supplementary files format and content: bedGraph files were generated using Bedtools (v2.29.2) with normalized values for each sample. we used the custom script to get bedpe files for interaction loops identified by using raw contact frequencies. The custom utility was used to convert the raw contact frequencies into sparse .matrix format, and these interaction counts were normalized for a total of 1,000,000 interactions at the same resolutions.
Library strategy: 3C-HTGTS
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| Submission date |
Oct 06, 2022 |
| Last update date |
Nov 30, 2022 |
| Contact name |
Hao bingtao |
| E-mail(s) |
haobingtao@gmail.com
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| Phone |
18578669173
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| Organization name |
Southern Medical University
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| Street address |
ShataiNan Road, Baiyun District, Guangzhou, Guangdong Province
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| City |
Guangzhou |
| ZIP/Postal code |
haobingtao@gmail.com |
| Country |
China |
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| Platform ID |
GPL24247 |
| Series (1) |
| GSE214918 |
Three-way contact analysis characterizes the higher-order organization of the Tcra locus |
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| Relations |
| BioSample |
SAMN31182921 |
| SRA |
SRX17813387 |
| Supplementary file |
Size |
Download |
File type/resource |
| GSM6617939_DP-Rag1ko-CBEko-TEAp-3C-HTGTS-rep3.bedGraph.gz |
33.8 Mb |
(ftp)(http) |
BEDGRAPH |
| GSM6617939_DP-Rag1ko-CBEko-TEAp-3C-HTGTS-rep3_2D_percell.matrix.gz |
1.3 Mb |
(ftp)(http) |
MATRIX |
| GSM6617939_DP-Rag1ko-CBEko-TEAp-3C-HTGTS-rep3_2D_percell_5000_norm.matrix.gz |
30.8 Kb |
(ftp)(http) |
MATRIX |
| GSM6617939_DP-Rag1ko-CBEko-TEAp-3C-HTGTS-rep3_2D_percell_5000_raw.matrix.gz |
14.6 Kb |
(ftp)(http) |
MATRIX |
| GSM6617939_DP-Rag1ko-CBEko-TEAp-3C-HTGTS-rep3_cisCPM.bedGraph.gz |
1.6 Mb |
(ftp)(http) |
BEDGRAPH |
SRA Run Selector |
| Raw data are available in SRA |
| Processed data provided as supplementary file |
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