|
| Status |
Public on Nov 04, 2022 |
| Title |
HemMC3 [CD146C] |
| Sample type |
SRA |
| |
|
| Source name |
primary hemangioma mural cells
|
| Organism |
Homo sapiens |
| Characteristics |
cell type: primary hemangioma mural cells
genotype: WT
treatment: culture in EGM2
time: 3 days
|
| Treatment protocol |
For transcriptional analysis, HemMCs were transferred to complete EGM2 for 3 days
|
| Growth protocol |
HemMCs were cultured in StemPro™ MSC serum-free medium (Thermo Fisher Scientific), and HemSCs were cultured in EGM-2 supplemented with Growth Medium 2 Supplement Mix (PromoCell) and 10% fetal bovine serum with 5% CO2 at 37℃.
|
| Extracted molecule |
total RNA |
| Extraction protocol |
Total RNA was isolated from HemMCs and HemSCs using TRIzol and the RNA Nano 6000 Assay Kit with the Bioanalyzer 2100 system, 1 ug of total RNA was used for the construction of sequencing libraries.
The clustering of the index-coded samples was performed on a cBot Cluster Generation System using TruSeq PE Cluster Kit v3-cBot-HS (Illumia) according to the manufacturer’s instructions.
After cluster generation, the library preparations were sequenced on an Illumina Novaseq platform and 150 bp paired-end reads were generated.
|
| |
|
| Library strategy |
RNA-Seq |
| Library source |
transcriptomic |
| Library selection |
cDNA |
| Instrument model |
Illumina NovaSeq 6000 |
| |
|
| Data processing |
Raw data (raw reads) of fastq format were firstly processed through in-house perl scripts. In this step, clean data (clean reads) were obtained by removing reads containing adapter, reads containing ploy-N and low quality reads from raw data. At the same time, Q20, Q30 and GC content the clean data were calculated. All the downstream analyses were based on the clean data with high quality.
Reference genome and gene model annotation files were downloaded from genome website directly. Index of the reference genome was built using Hisat2 v2.0.5 and paired-end clean reads were aligned to the reference genome using Hisat2 v2.0.5. We selected Hisat2 as the mapping tool for that Hisat2 can generate a database of splice junctions based on the gene model annotation file and thus a better mapping result than other non-splice mapping tools
featureCounts v1.5.0-p3 was used to count the reads numbers mapped to each gene. And then FPKM of each gene was calculated based on the length of the gene and reads count mapped to this gene. FPKM, expected number of Fragments Per Kilobase of transcript sequence per Millions base pairs sequenced, considers the effect of sequencing depth and gene length for the reads count at the same time, and is currently the most commonly used method for estimating gene expression levels.
Differential expression analysis of two conditions/groups (two biological replicates per condition) was performed using the DESeq2 R package (1.20.0). DESeq2 provide statistical routines for determining differential expression in digital gene expression data using a model based on the negative binomial distribution. The resulting P-values were adjusted using the Benjamini and Hochberg’s approach for controlling the false discovery rate . Genes with an adjusted P-value <0.05 found by DESeq2 were assigned as differentially expressed
|
| |
|
| Submission date |
Oct 30, 2022 |
| Last update date |
Nov 04, 2022 |
| Contact name |
Jialin Chen |
| E-mail(s) |
chenjl403@sjtu.edu.cn
|
| Organization name |
Shanghai Ninth People's Hospital
|
| Street address |
639 Zhizaoju Road, Huangpu District
|
| City |
Shanghai |
| ZIP/Postal code |
200001 |
| Country |
China |
| |
|
| Platform ID |
GPL24676 |
| Series (1) |
| GSE216867 |
CD146+ mural cells from infantile hemangioma |
|
| Relations |
| BioSample |
SAMN31525277 |
| SRA |
SRX18077907 |
