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Sample GSM7776347 Query DataSets for GSM7776347
Status Public on Sep 14, 2023
Title HL-1-SMC3-KD-rep1
Sample type SRA
 
Source name Muscle
Organism Mus musculus
Characteristics cell line: Cardiac muscle cells HL-1
tissue: Atrial tissue
genotype: SMC3-KD
Growth protocol All mouse procedures were approved and monitored by the Research Ethics Committee of the School of Basic Medical Sciences, Fudan University, China. Mice were on a C57Bl/6 genetic background . Animals were housed and bred in a specific pathogen-free animal facility.
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. For SnRNA-seq, the E12.5 mouse embryos were microdissected in PBS solution using a Leica M205C microscope, and the heart tissues were extracted. The whole heart samples from different embryos, including six Smc3fl/fl, seven Smc3fl/+; Nkx2.5-Cre, and seven Smc3fl/fl; Nkx2.5-Cre, subjected to mechanical trituration, were made into the cell suspension. Cell counts and viability were determined for the resulting suspension, and the cell concentration was adjusted to the ideal 300-600 cells / μL. The prepared single-cell suspension was combined with a mixture of gel beads containing barcode information and enzymes and then encapsulated by oil droplets to form Gel Bead-In-EMulsions (GEMs). After the reverse transcription reaction, the GEMs were fragmented to complete the amplification of nuclear cDNA, and the quality-checked amplification products were constructed as sequencing libraries. Briefly, the cDNA was broken into fragments of 200-300 bp, end-repaired, ligated into the P7 Adapter, and finally amplified by PCR for introduction into the indexes of samples.
 
Library strategy RNA-Seq
Library source genomic
Library selection cDNA
Instrument model Illumina NovaSeq 6000
 
Description Smc3-All.ReadsCount.xls
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).
For snRNA-seq data analysis, the cleaned data were generated by Cell Ranger (v3.0.2) (https://github.com/10XGenomics/cellranger) and filtered for the low-quality reads. The data were aligned to mouse mm10 reference genome. 10× Genomics‐derived data were collected. The downstream analysis using the Seurat (v4.0.5) (https://satijalab.org/seurat) program screened out Cells with gene numbers greater than 200, and mitochondrial gene ratios less than 25% and 2000 genes with highly variable expression in 3 or more cells. Principal component analysis was then runned using significantly variable genes, and Uniform Manifold Approximation and Projection (UMAP) was performed to visualize data. Cells were represented in a two-dimensional UMAP plane, and clusters were identified and annotated according to the previously published cardiac cell markers. The significance of differential expression was calculated using the bimod test. Functional enrichment of differentially expressed genes was then processed by Gene Ontology (GO) (http://www.geneontology.org/) analysis. The pseudotime trajectory was determined with the Monocle2 package with the default settings. Specifically, the DDRTree method was used for dimension reduction with max_components set at 2, and the cells were ordered using the orderCells function.
Bulk RNA-sequencing (RNA-seq) of mouse embryo hearts and HL-1 cells was carried on by the LC-Bio Technology, Hangzhou, China. The detailed operations were as follows: total RNA was isolated and purified using TRIzol reagent (Invitrogen, CA, USA). The RNA samples which passed quality control were fragmented into small pieces at 94℃ for 5-7min and reverse-transcribed to create the cDNA. The average insert size for the final cDNA library was 300±50 bp. The FASTQ data of sequencing reads were trimmed using paired-end sequencing. Consecutively, the trimmed reads were mapped to the mouse genome reference (mm10) by HISAT2 software (https://ccb.jhu.edu/software/hisat2). The mRNA expression abundance was analyzed using StringTie software and represented by FPKM. The differentially expressed mRNAs were selected with FC >1.5 and a parametric F-test comparing nested linear models (p value < 0.05) by the R package edgeR (https://bioconductor.org/packages/release/bioc/html/edgeR.html). Gene set enrichment analysis was run on all expressed genes which were ranked by log2FC value. Functional enrichment of differentially expressed genes was then processed by GO (http://www.geneontology.org/) analysis.
For ChIP-seq, ChIP products were end repaired, dA-tailing and linker ligation were performed, and barcoding and Illumina adapter addition were performed by PCR amplification. Libraries were purified using QiaQuick PCR purification reagents (Qiagen, Hilden, Germany) and size selected by 0.7×and 0.2×Ampure XP beads (Beckman, California, USA).
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.
 
Submission date Sep 12, 2023
Last update date Sep 14, 2023
Contact name bowen zhang
E-mail(s) 20111010022@fudan.edu.cn
Phone 13399288269
Organization name Fudan university
Street address dongan road
City shanghai
State/province shanghai
ZIP/Postal code 200032
Country China
 
Platform ID GPL24247
Series (1)
GSE242974 The role of SMC3 in heart development by regulating super-enhancer associated genes
Relations
BioSample SAMN37361512
SRA SRX21758616

Supplementary data files not provided
SRA Run SelectorHelp
Raw data are available in SRA

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