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| Status |
Public on Jan 08, 2020 |
| Title |
HUVEC_H3K9_n3_DM [ChIP-seq] |
| Sample type |
SRA |
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| Source name |
H3K9me3 in differentiation medium
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| Organism |
Homo sapiens |
| Characteristics |
genotype/variation: Wild-type
cell type: human umbilical vein endothelial cells (HUVEC)
passages: P2
treatment: differentiation media (DM)
chip antibody: H3K9me7
chip antibody cat. #: C15410193 (Diagenode)
chip antibody lot nr.: K9A1671-001p
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| Treatment protocol |
4 x 10^5 HUVEC were seeded in a 60 mm cell culture dish, cells were cultivated either full medium (FM) or in differentiation media (DM). After 24 h of cultivation, cells were treated with 10 ng/ml TGF-β2 (#302-B2, R&D System). After additional 48 h of incubation, the treatment was repeated. 96h later, RNA was isolated.
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| Growth protocol |
Experiments were performed using human umbilical vein endothelial cells (HUVEC) purchased from Lonza. Cells were cultured in endothelial basal medium without phenol red (#C-22215, PromoCell), supplemented with hydrocortisone (#CC-4035C, Lonza), ascorbic acid (#CC-4116C, Lonza), bovine brain extract (BBE) (#CC-4092C, Lonza), epidermal growth factor (EGF) (#CC-4017, Lonza), 10% fetal bovine serum (FBS) (#CC-4101, Lonza) and GA-1000 (Gentamicin+Amphotericin-B, CC-4081C, Lonza) or for EndMT without EGF and BBE.
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| Extracted molecule |
genomic DNA |
| Extraction protocol |
Total RNA was isolated using Qiazol Lysis Reagent (#79306; Qiagen) and miRNeasy-kit (#217004; Qiagen) with additional DNase I (#79254; Qiagen) digestion according to the manufacturer’s protocol. 1 μg of RNA from each sample was reverse-transcribed using random hexamer primed single-strand cDNA (10 min at 25 °C, 15 min at 42 °C, 5 min at 99 °C) by MMLV Reverse Transcriptase (#N8080018; Life technologies) as previously described. (Boeckel et al., 2011). For qPCR, cDNA was amplified using Fast SYBR Green Mastermix (#4385612 Life Technologies) on a ViiA7- Realtime qPCR System (Life Technologies). Expression level of mRNAs were normalized to RPLP0 which served as a housekeeping gene using the 2‑ΔCt method.
900ng of total RNA was used as input for whole transcriptome RNA-seq library preparation (TruSeq® Stranded Total RNA, Illumina) following low throughput protocol. Sequencing was performed on Illumina Nextseq 500 (Illumina) using V2 chemistry and 75bp single-end setup.
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| Library strategy |
ChIP-Seq |
| Library source |
genomic |
| Library selection |
ChIP |
| Instrument model |
Illumina NextSeq 500 |
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| Description |
H3K9me3 in differentiation medium
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| Data processing |
Chip-Seq: The samples were sequenced on Illumina NextSeq hardware and assessed for quality using FastQC (Andrews S. 2010, FastQC: a quality control tool for high throughput sequence data. Available online at: http://www.bioinformatics.babraham.ac.uk/projects/fastqc) or used for qRT-PCR analysis with the primers described before. Reads were trimmed using fastx-trimmer (http://hannonlab.cshl.edu/fastx_toolkit/). Trimmed sequences were mapped to the GRCH38 version of the human genome with STAR 2.4.2a 4 using only unique alignments to exclude reads with unclear placing. PCR duplicates were removed using Picard 1.136 (Picard: A set of tools (in Java) for working with next generation sequencing data in the BAM format; http://broadinstitute.github.io/picard/) to avoid PCR artefacts leading to multiple copies of the same original fragment. Peaks were called using homer findPeaks version 4.0311 with parameter –region to combine close peaks. The minimum distance and size of peaks for H3K9me3 were set to -size 2000 and –minDist 10000
Data were filtered using the following specifications:
RNA:SEQ: Base calling and FASTQ were done with Illumina's HiSeq Control Software version 1.5.15.1 (RTA v1.13.18 and bclfastq v1.8.3). Sequenced reads were mapped to the mouse reference genome with TopHat version 2.0.5, and differentially expressed genes were assessed by use of Cuffdiff, a part of the Cufflinks version 2.1.1 package.
Cellular suspensions were loaded on a 10X Chromium Controller (10X Genomics) according to manufacturer’s protocol based on the 10X Genomics proprietary technology13. HUVEC study and murine scRNA-seq libraries were prepared using Chromium Single Cell 3′ v2 Reagent Kit and Chromium Single Cell 3′ v3 Reagent Kit, respectively (10X Genomics), according to manufacturer’s protocols. Briefly, the initial step consisted in performing an emulsion where individual cells were isolated into droplets together with gel beads coated with unique primers bearing 10X cell barcodes, UMI (unique molecular identifiers) and poly(dT) sequences. Reverse transcription reactions were engaged to generate barcoded full-length cDNA followed by the disruption of emulsions using the recovery agent and cDNA clean up with DynaBeads MyOne Silane Beads (Thermo Fisher Scientific). Bulk cDNA was amplified using a Biometra Thermocycler Professional Basic Gradient with 96-Well Sample Block (98°C for 3 minutes; cycled 14×: 98°C for 15 s, 67°C for 20 s, and 72°C for 1 minute; 72°C for 1 minute; held at 4°C). Amplified cDNA product was cleaned with the SPRIselect Reagent Kit (Beckman Coulter). Indexed sequencing libraries were constructed using the reagents from the Chromium Single Cell 3′ v2 and Chromium Single Cell 3′ v3 Reagent Kits as follows: fragmentation, end repair and A-tailing; size selection with SPRIselect; adaptor ligation; post-ligation cleanup with SPRIselect; sample index PCR and cleanup with SPRI select beads. Library quantification and quality assessment was performed using Bioanalyzer Agilent 2100 using a High Sensitivity DNA chip (Agilent Genomics). Indexed libraries were equimolarly pooled and sequenced using paired-end 26x98bp as sequencing mode by GenomeScan (Leiden, Netherlands). Single-cell RNA-seq outputs were processed using the Cell Ranger (10X Genomics) suite versions 2.1.1 (in vitro HUVEC samples) or 3.0.1 (in vivo 3d AMI samples). HUVEC in vitro data has been mapped to the GRCh38 (version 1.2.0) reference genome by using the “count” function. Subsequently, individual processed datasets have been merged with “aggregate”. Secondary analysis was conducted using the Seurat 2.3.4 package in R.14 We filtered the data for cells expressing at least 200 genes. Moreover, we aimed to avoid doublets by removing cells with high unique molecular identifier (UMI) counts (> 90000) and high number of genes (> 8000). We also accounted for possible dead cells and removed cells with high mitochondrial content (> 10 % of total UMI). The remaining matrix was log-normalized and scaled. After detecting variable genes, a principal component analysis (PCA) using 10 dimensions was applied. Clustering of the cells was then performed by Seurat’s FindCluster function with 0.6 resolution. We used t-distributed stochastic neighbor embedding (t-SNE) to visualize cell clusters.15 We applied a generic threshold of 2.5 to the scaled value of all candidate genes to separate high and low or no expressing cells. Accordingly, in vivo 3d AMI data we mapped against the mm10 (version 3.0.0) reference genome using Cell Ranger “count”. In Seurat 2.3.4 we applied similar filters for removing cells with high and low UMI counts but removed the upper 5 % and lower 1 % of all cells per individual sample. High mitochondrial content cells (>10 %) were removed similarly. We only kept genes that showed at least in 2 cells an UMI count of more than 1. We merged the data and counted cells expressing at least 1 UMI for Cdh5 and Pecam1 (ECs) as well as Cdh5, Pecam1 and two mesenchymal markers (EndMT cells) between the libraries.
Genome_build: GRCm38
Supplementary_files_format_and_content: Gene_expression.tsv was generatedby cuffdiff and assembled by cummerbund; ChIP-seq bed files
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| Submission date |
Jan 07, 2020 |
| Last update date |
Jan 08, 2020 |
| Contact name |
David John |
| E-mail(s) |
john@med.uni-frankfurt.de
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| Organization name |
Institute for Cardiovascular Regeneration
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| Street address |
Theodor-Stern-Kai 7
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| City |
Frankfurt |
| State/province |
Hessen |
| ZIP/Postal code |
60590 |
| Country |
Germany |
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| Platform ID |
GPL18573 |
| Series (2) |
| GSE143148 |
The histone demethylase JMJD2B regulates endothelial-to-mesenchymal transition [HTS] |
| GSE143151 |
The histone demethylase JMJD2B regulates endothelial-to-mesenchymal transition |
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| Relations |
| BioSample |
SAMN13746715 |
| SRA |
SRX7513711 |
| Supplementary file |
Size |
Download |
File type/resource |
| GSM4254158_H3K9_n3_DM.bed.gz |
48.2 Kb |
(ftp)(http) |
BED |
SRA Run Selector |
| Raw data are available in SRA |
| Processed data provided as supplementary file |
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