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Sample GSM8356045

Query DataSets for GSM8356045

Status

Public on Feb 15, 2025

Title

Ngn3KONgn3CreNeurod1OE_E15.5_179

Sample type

SRA

Source name

fetal pancreas

Organism

Mus musculus

Characteristics

tissue: fetal pancreas
time: E15.5
genotype: Ngn3KONgn3CreNeurod1OEGFPH
dataset: dataset-5

Extracted molecule

polyA RNA

Extraction protocol

For Smart-seq2 scRNA-seq, single cells were manually picked from FACS-purified bulk cells using a mouth pipette. cDNA synthesis and amplification were performed following the protocol by Picelli et al. For Smart-seq3 scRNA-seq, single cells were directly sorted into 384-well plates containing lysis buffer. cDNA synthesis and amplification were carried out according to the Smart-seq3 protocol .For 10x Genomics scRNA-seq, the procedure was performed according to the manufacturer’s instructions using the Single Cell 3′ Reagent Kit v3.1. Sorted EpCAM+ pancreatic cells from wild-type (WT), conditional knockout (CKO), or overexpression (OE) embryos of different genders were pooled and processed as one sample. For NGN3-CKO samples, E14.5 EpCAM+ pancreatic cells were pooled per replicate: replicate 1 consisted of two WT male litters and one CKO female litter, and replicate 2 consisted of three WT male litters and three CKO female litters. For NGN3-OE samples, E14.5 EpCAM+ pancreatic cells were pooled from four WT female litters and four OE male litters, and E17.5 EpCAM+ pancreatic cells were pooled from two WT female litters and three OE male litters. For NeuroD1-CKO samples, E15.5 EpCAM+ pancreatic cells were pooled per replicate: replicate 1 consisted of one WT male litter and one CKO female litter, and replicate 2 consisted of two WT female litters and one CKO male litter. The gender of the embryos was determined by genotyping for Y-chromosome-associated gene Sry.
For Smart-seq2 scRNA-seq, libraries were prepared with 2 ng of cDNA using the TruePrep DNA Library Prep Kit (Vazyme, TD502), and sequenced on the Illumina HiSeq 4000 system, generating 150 bp paired-end reads. For Smart-seq3 scRNA-seq, libraries were constructed using the TruePrep DNA Library Prep Kit V2 for lllumina (Vazyme, TD501), and sequencing was conducted on the MGIseq-2000 platform, generating 100 bp paired-end reads. For 10x Genomics scRNA-seq, libraries were sequenced as 150-bp paired-end reads on an Illumina HiSeq 4000 system.
CUT&RUN was conducted following the published protocol with modifications in DNA purification and library construction steps. We used 30,000 cells per CUR&RUN assay with primary antibodies against FLAG (1:25, CST, 2368S), p300 (1;100, CST, 54062S), and NeuroD1 (1:100, Millpore, ABE991). DNA was purified using a spin column (VISTECH, DC2005) and processed for library construction with KAPA Hyper Prep Kit (KAPA biosystems, KK8502). Briefly, after end repair and adaptor ligation, the reaction was purified using VAHTS DNA Clean Beads (Vazyme, N411-03-AA) and subjected to PCR amplification with 2× KAPA HiFi HotStart ReadyMix (KAPA Biosystems, KM2602) and Illumina universal primers. The PCR program was: 98°C for 45 seconds, followed by 19 cycles of 98°C for 15 seconds, 60°C for 10 seconds, and 72°C for 1 minute, with a final extension at 72°C for 5 minutes. The final DNA was purified using 1× VAHTS DNA Clean Beads.
CUT&RUN libraries were subjected to 150 bp paired-end sequencing or 51 bp single-end sequencing on the Illumina NovaSeq 6000 or Illumina Hiseq 2500 platform.
Bulk-cell ATAC-seq was conducted following the published protocol with modifications in cell sorting and nuclei preparation. Specifically, 2,000 cells per ATAC-seq were directly sorted into 50 ul lysis buffer in a 200 ul tube for nuclei preparation. Libraries were constructed using the TruePrep DNA Library Prep Kit V2 for Illumina (Vazyme, TD502). PCR amplification was performed for 12 cycles under the following conditions: 72°C for 3 minutes, 98°C for 30 seconds, then 12 cycles of 98°C for 15 seconds, 60°C for 30 seconds, and 72°C for 3 minutes, followed by a final extension at 72°C for 5 minutes.
The final DNA was purified using 1× VAHTS DNA Clean Beads and sequenced as 150 bp paired-end reads on the Illumina NovaSeq 6000 platform.
For snATAC-seq, the procedure was performed according to the manufacturer’s instructions using the Chromium Next GEM Single Cell ATAC Library & Gel Bead Kit v1.1 (10x Genomics). For the Ngn3-CKO samples, E14.5 EpCAM+ pancreatic cells of WT and CKO embryos with different genders (two WT male litters and two CKO female litters) were pooled and loaded as one sample. To ensure experimental success and an adequate number of nuclei, extra pancreatic cells from WT embryos were included, with a ratio of to EpCAM+ cells of 1:4. For the NeuroD1-CKO samples, E15.5 EpCAM+ pancreatic cells of WT and CKO embryos with different genders (two WT female litters and three CKO male litters) were pooled and loaded as one sample.
Libraries were sequenced as 50-bp paired-end reads on an NovaSeq 6000 system.
snATAC-seq

Library strategy

RNA-Seq

Library source

transcriptomic single cell

Library selection

cDNA

Instrument model

Illumina HiSeq 4000

Description

Smartseq3 scRNA-seq
sm3_rc.cell.tsv
sm3_rc.gene.tsv
sm3_rc.mtx

Data processing

For CUT&RUN data, overrepresented sequences were identified using FastQC (v0.11.3), and then removed along with sequencing adaptors, primers, and other overrepresented sequences using Trimmomatic (v0.38). The remaining sequencing reads were aligned to the Mus musculus genome (mm10) using bowtie2 (v2.2.5) with default parameters. PCR duplicate reads were subsequently removed using samtools (v1.3.1), and only reads with a mapping quality score ≥30 were retained for downstream analysis. Peak calling was performed on individual samples using MACS2 (v2.2.6), retaining peaks with a P value less than 10-3. Reproducibility between two biological replicates was assessed using idr (v2.0.4.2). Different irreproducible discovery rate (IDR) thresholds were applied depending on the CUT&RUN targets. For CUT&RUN targeting NGN3 in Ngn3low cells, peaks with an IDR larger than 250 were retained for downstream analysis. For CUT&RUN targeting NGN3 in Ngn3high cells and NEUROD1, the threshold was set to 400. Genome regions overlapping with the ENCODE blacklist were filtered out from the final identified peaks. Tag intensities were calculated as Tags per ten million (TP10M) values and stored in bedGraph files using Homer (v4.7.2).
For bulk-cell ATAC-seq data, Overrepresented sequences were identified using FastQC (v0.11.3), and then removed along with sequencing adaptors, primers, and other overrepresented sequences using Trimmomatic (v0.38). The remaining sequencing reads were aligned to the Mus musculus genome (mm10) using bowtie2 (v2.2.5) with default parameters. PCR duplicate reads were subsequently removed using samtools (v1.3.1), and only reads with a mapping quality score ≥30 were retained for downstream analysis. Prior to peak calling, reads generated from biological replicates were combined. ATAC-seq peaks were then identified using MACS2 (v2.2.6), retaining peaks with a false discovery rate (FDR) less than 0.01. Genome regions overlapping with the ENCODE blacklist were excluded from further analysis. Tag intensities were calculated as TP10M values and stored in bedGraph files using Homer (v4.7.2).
For snATAC-seq, preprocessing was conducted using cellranger-atac (v1.2.0) with default parameters against the refdata-cellranger-atac-mm10-1.2.0 genome. Cells with detected UMI counts greater than 1,000 and reads in promoter regions (RIPR) between 15% and 45% were retained for downstream analysis. The mm10 genome was segmented into discrete 5 kb intervals, serving as bins for each cell. The tag intensities for each bin were calculated based on the frequency of sequence tags and imported into the R package Signac (v1.3.0) for downstream analysis.
For smart-seq2 snRNA-seq, sequencing reads were aligned to the mm10 mouse genome assembly using TopHat (v2.1.0). Gene-level quantification of mapped reads was performed with HTSeq (v0.6.6) using the parameters “-s no -a 30”. Cells exhibiting fewer than 0.2 million mapped reads or fewer than 4,000 detected genes were excluded from further analysis. Gene expression levels were quantified using TPM (transcripts per million).
For smart-seq3 snRNA-seq, Trimmomatic (v0.39) was utilized to remove primer and adaptor sequences from the reads. Subsequently, the trimmed forward reads (Read 1) were aligned to the mm10 mouse genome using HISAT2 (v2.1.0). The resulting aligned reads were annotated to gene features using featureCounts (v2.0.0), considering both the 5' and internal fragments. Cells were filtered out if they exhibited fewer than 4,000 detected genes. Gene expression levels were quantified using TPM.
For 10x Genomics scRNA-seq, preprocessing was conducted using Cell Ranger (v3.0.1) with default parameters aligned to the refdata-cellranger-mm10-1.2.0 reference genome. The “filtered_feature_bc_matrix” output from Cell Ranger was imported into the Seurat package (version 4.1.1) for downstream analysis in R. WT and CKO or OE cells within the same sample were initially distinguished based on TP10K (transcripts per 10 thousand) values of Uty, Eif2s3y, and Ddx3y for male cells, and the TP10K value of Xist for female cells. These values were log-transformed, with cells exhibiting male-related values greater than 0.2 and female-related values equal to 0 classified as male, while cells with female-related values greater than 1 and male-related values equal to 0 classified as female. The downstream analysis, including dimensional reduction, cell clustering, and differential expression analysis, was conducted using the standard Seurat pipeline.
Assembly: mm10
Supplementary files format and content: Sparce matrix, Bedgraph

Submission date

Jun 27, 2024

Last update date

Feb 15, 2025

Contact name

Cheng-ran Xu

Organization name

Peking University

Department

School of Basic Medical Sciences

Street address

NO.5 YIHEYUAN ROAD HAIDIAN DISTRICT, BEIJING, P.R.CHINA