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Human eIF2A has a minimal role in translation initiation and in uORFmediated translational control

GSE282509 Homo sapiens (human) RNA-seq (gene expression) 20 samples Submitted 2024/11/29 Platform GPL21697
At a glance

RNA-seq (gene expression) · human · 20 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
20 samples: 8 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.
Paper
Human eIF2A has a minimal role in translation initiation and in uORF-mediated translational control in HeLa cellseLife · 2025
Summary (written by the submitters)
We apply ribosome profiling here to assess the role of eIF2A in translation initiation. For this we test the change in translation efficiency between HeLa control and eIF2A-KO cells, however we do not find any transcript to depend on eIF2A. Since eIF2A is thought to take over the function of eIF2 when eIF2 is inhibited, we also test conditions where the integrated stress response is activated, thereby leading to eIF2 inactivation. In none of our assays, however, could we detect a role of eIF2A in translation initiation.
Published in
Human eIF2A has a minimal role in translation initiation and in uORF-mediated translational control in HeLa cells
Roiuk M, Neff M, Teleman AA · eLife 2025 · PMID 40600802 · doi:10.7554/eLife.105311
This dataset
Open GSE282509 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 GSE282509_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 PRJNA1189055 and SRA study SRP546775. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40600802) ↗
Study design
8 conditions, mostly in triplicate
Riboseq_HeLa_control_cells_dmso_replica ×3 Riboseq_HeLa_eIF2A-KO_dmso_replica ×3 Total_RNA_HeLa_control_cells_dmso_replica ×3 Total_RNA_HeLa_eIF2A-KO_dmso_replica ×3 Riboseq_HeLa_control_cells_TM_replica ×2 Riboseq_HeLa_eIF2A-KO_TM_replica ×2 Total_RNA_HeLa_control_cells_TM_replica ×2 Total_RNA_HeLa_eIF2A-KO_TM_replica ×2

Supports a between-group comparison across 20 samples.

How we read this: 8 replicated groups read from 20 sample titles; they account for 20 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
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