GEO series

Microprotein-Encoding RNA Regulation in Cells Treated with Pro-inflammatory and Pro-Fibrotic Stimuli (RNA-Seq colon cell lines)

GSE269374 Homo sapiens (human) RNA-seq (gene expression) 54 samples Submitted 2024/10/23 Platform GPL24676

At a glance

RNA-seq (gene expression) · human · 54 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: 54 samples: 18 conditions, mostly in triplicateGroups 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.

Summary (written by the submitters)

Recent analysis of the human proteome via proteogenomics and ribosome profiling of the transcriptome revealed the existence of thousands of previously unannotated microprotein-coding small open reading frames (smORFs). Most functional microproteins were chosen for characterization because of their evolutionary conservation. However, one example of a non-conserved immunomodulatory microprotein in mice suggests that strict sequence conservation misses some intriguing microproteins.

Read the full summary ↓

Here, we examine the ability of gene regulation to identify human microproteins with potential roles in inflammation or fibrosis of the intestine. To do this, we collected ribosome profiling data of intestinal cell lines and peripheral blood mononuclear cells (PBMCs), and then used gene expression of microprotein-encoding transcripts to identify strongly regulated microproteins, including several examples of microproteins that are only conserved with primates. This approach reveals a number of new microproteins worthy of additional functional characterization, and provides a dataset that can be queried in different ways to find additional gut microproteins of interest.

This dataset

Open GSE269374 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 GSE269374_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 PRJNA1121291 and SRA study SRP512464. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

18 conditions, mostly in triplicate

HCEC-1CT Naive ×3 HCEC-1CT 100 ng/mL LPS ×3 HCEC-1CT 10 ng/mL IL-22 ×3 HCEC-1CT 10 ng/mL TNFa ×3 HCEC-1CT 10 ng/mL IFNg ×3 Caco-2 Naive ×3 Caco-2 100 ng/mL LPS ×3 Caco-2 10 ng/mL IL-22 ×3 +10 more

Supports a between-group comparison across 54 samples.

How we read this: 18 replicated groups read from 54 sample titles; they account for 54 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

GSM8314050 HCEC-1CT Naive 1 HCEC-1CT Naive
GSM8314051 HCEC-1CT Naive 2 HCEC-1CT Naive
GSM8314052 HCEC-1CT Naive 3 HCEC-1CT Naive
GSM8314053 HCEC-1CT 100 ng/mL LPS 1 HCEC-1CT 100 ng/mL LPS
GSM8314054 HCEC-1CT 100 ng/mL LPS 2 HCEC-1CT 100 ng/mL LPS
GSM8314055 HCEC-1CT 100 ng/mL LPS 3 HCEC-1CT 100 ng/mL LPS
GSM8314056 HCEC-1CT 10 ng/mL IL-22 1 HCEC-1CT 10 ng/mL IL-22
GSM8314057 HCEC-1CT 10 ng/mL IL-22 2 HCEC-1CT 10 ng/mL IL-22
GSM8314058 HCEC-1CT 10 ng/mL IL-22 3 HCEC-1CT 10 ng/mL IL-22
GSM8314059 HCEC-1CT 10 ng/mL TNFa 1 HCEC-1CT 10 ng/mL TNFa
GSM8314060 HCEC-1CT 10 ng/mL TNFa 2 HCEC-1CT 10 ng/mL TNFa
GSM8314061 HCEC-1CT 10 ng/mL TNFa 3 HCEC-1CT 10 ng/mL TNFa
GSM8314062 HCEC-1CT 10 ng/mL IFNg 1 HCEC-1CT 10 ng/mL IFNg
GSM8314063 HCEC-1CT 10 ng/mL IFNg 2 HCEC-1CT 10 ng/mL IFNg
GSM8314064 HCEC-1CT 10 ng/mL IFNg 3 HCEC-1CT 10 ng/mL IFNg
GSM8314065 Caco-2 Naive 1 Caco-2 Naive
GSM8314066 Caco-2 Naive 2 Caco-2 Naive
GSM8314067 Caco-2 Naive 3 Caco-2 Naive
GSM8314068 Caco-2 100 ng/mL LPS 1 Caco-2 100 ng/mL LPS
GSM8314069 Caco-2 100 ng/mL LPS 2 Caco-2 100 ng/mL LPS
GSM8314070 Caco-2 100 ng/mL LPS 3 Caco-2 100 ng/mL LPS
GSM8314071 Caco-2 10 ng/mL IL-22 1 Caco-2 10 ng/mL IL-22
GSM8314072 Caco-2 10 ng/mL IL-22 2 Caco-2 10 ng/mL IL-22
GSM8314073 Caco-2 10 ng/mL IL-22 3 Caco-2 10 ng/mL IL-22
GSM8314074 Caco-2 10 ng/mL TNFa 1 Caco-2 10 ng/mL TNFa
GSM8314075 Caco-2 10 ng/mL TNFa 2 Caco-2 10 ng/mL TNFa
GSM8314076 Caco-2 10 ng/mL TNFa 3 Caco-2 10 ng/mL TNFa
GSM8314077 Caco-2 10 ng/mL IFNg 1 Caco-2 10 ng/mL IFNg
GSM8314078 Caco-2 10 ng/mL IFNg 2 Caco-2 10 ng/mL IFNg
GSM8314079 Caco-2 10 ng/mL IFNg 3 Caco-2 10 ng/mL IFNg
GSM8314080 CCD-18Co Naive 1 CCD-18Co Naive
GSM8314081 CCD-18Co Naive 2 CCD-18Co Naive
GSM8314082 CCD-18Co Naive 3 CCD-18Co Naive
GSM8314083 CCD-18Co 10 ng/mL TNFa 1 CCD-18Co 10 ng/mL TNFa
GSM8314084 CCD-18Co 10 ng/mL TNFa 2 CCD-18Co 10 ng/mL TNFa
GSM8314085 CCD-18Co 10 ng/mL TNFa 3 CCD-18Co 10 ng/mL TNFa
GSM8314086 CCD-18Co 10 ng/mL IL-1b 1 CCD-18Co 10 ng/mL IL-1b
GSM8314087 CCD-18Co 10 ng/mL IL-1b 2 CCD-18Co 10 ng/mL IL-1b
GSM8314088 CCD-18Co 10 ng/mL IL-1b 3 CCD-18Co 10 ng/mL IL-1b
GSM8314089 CCD-18Co 10 ng/mL OSM 1 CCD-18Co 10 ng/mL OSM

+ 14 more — browse all 54 samples with per-sample file links →

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Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.