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Codon-dependent regulation of mRNA translation and stability by ZC3H7A and ZC3H7B RNA-binding proteins

GSE325326 Homo sapiens (human) RNA-seq (gene expression) 24 samples Submitted 2026/05/13 Platform GPL34284
At a glance

RNA-seq (gene expression) · human · 24 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
24 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.
Summary (written by the submitters)
The reduced translation elongation rate caused by the presence of non-optimal codons can negatively impact mRNA stability through translation-dependent decay. A key aspect of this process is the coupling of sensing the mRNA codon usage with the regulation of translation efficiency and stability. We found that two paralog RNA-binding proteins; ZC3H7A and ZC3H7B; which have only emerged in Chordates, preferentially bind to and reduce the stability and translation of mRNAs enriched in the non-optimal codons with A/U at their wobble sites (A/U3 codons).
Read the full summary ↓
ZC3H7A/B engage with ribosomes that lack elongation factors and induce mRNA degradation or block translation initiation through their interactions with the CCR4-NOT and the GIGYF2/4EHP translation repressor complex, respectively. Depletion of ZC3H7A and ZC3H7B or 4EHP impairs the repression of non-optimal A/U3-rich mRNAs. This study provides insights into a unique mechanism in higher eukaryotes that couples codon usage with the regulation of translation efficiency and mRNA stability.
This dataset
Open GSE325326 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 GSE325326_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 PRJNA1439640 and SRA study SRP685022. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
8 conditions, mostly in triplicate
Flag/HA-control-SLAM-Seq-0h ×3 Flag/HA-ZC3H7B-OE-SLAM-Seq-2h ×3 Flag/HA-control-SLAM-Seq-4h ×3 Flag/HA-ZC3H7B-OE-SLAM-Seq-4h ×3 Flag/HA-control-SLAM-Seq-6h ×3 Flag/HA-ZC3H7B-OE-SLAM-Seq-6h ×3 Flag/HA-ZC3H7B-OE-SLAM-Seq-0h ×3 Flag/HA-control-SLAM-Seq-2h ×3

Supports a between-group comparison across 24 samples.

How we read this: 8 replicated groups read from 24 sample titles; they account for 24 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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