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Functional characterization of a heat shock factor regulated enhancer at coronary artery disease associated locus that controls CALCRL expression in endothelial cells

GSE222118 Homo sapiens (human) RNA-seq (gene expression) 14 samples Submitted 2024/05/22 Platform GPL21697
At a glance

RNA-seq (gene expression) · human · 14 samples

What it is
RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
Organism
Homo sapiens (human)
Samples
14 samples: 4 × TeloHAEC_CALCRL_siRNA_kockout vs 4 × TeloHAEC_CALCRL_scrambled_siRNA vs 3 × CRISPRCas9_TeloHAEC_CALCRL_ctrl vs 3 × CRISPRCas9_TeloHAEC_CALCRL_delGroups are read from the sample names, not from the paper. Check the list below.
Data you can get
A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.
Paper
Coronary Artery Disease Risk Variant Dampens the Expression of CALCRL by Reducing HSF Binding to Shear Stress Responsive Enhancer in Endothelial Cells In VitroArteriosclerosis, thrombosis, and vascular biology · 2024
Summary (written by the submitters)
We performed RNA-seq in TeloHAEC with samples where CALCRL was silenced using siRNA or enhancer-8 deleted using CRISPR-cas9 system to investigate the genes that are differentially expressed under CALCRL knockdown.
Published in
Coronary Artery Disease Risk Variant Dampens the Expression of CALCRL by Reducing HSF Binding to Shear Stress Responsive Enhancer in Endothelial Cells In Vitro
Selvarajan I, Kiema M, Huang RT et al. · Arteriosclerosis, thrombosis, and vascular biology 2024 · PMID 38602103 · doi:10.1161/ATVBAHA.123.318964
This dataset
Open GSE222118 in finder → Find more human RNA-seq datasets →
Download · which file do I need?

Direct links to NCBI and ENA, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.

1 · Just have a look

Processed table

The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.

Series matrix ↓
2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE222118_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓
3 · Start from the raw reads

Raw sequencing reads

The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.

Raw reads on ENA ↗

What the files usually look like: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.

Also filed as BioProject PRJNA918316 and SRA study SRP415703. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 38602103) ↗
Study design
4 × TeloHAEC_CALCRL_siRNA_kockout vs 4 × TeloHAEC_CALCRL_scrambled_siRNA vs 3 × CRISPRCas9_TeloHAEC_CALCRL_ctrl vs 3 × CRISPRCas9_TeloHAEC_CALCRL_del

Supports a between-group comparison across 14 samples.

How we read this: 4 replicated groups read from 14 sample titles; they account for 14 of them. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.

Samples in this study
Datasets on a similar topic

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