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UPF1 ATPase autoinhibition and activation modulate RNA binding kinetics and NMD efficiency 1

GSE246483 Homo sapiens (human) RNA-seq (gene expression) 48 samples Submitted 2024/05/29 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 48 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
48 samples: 16 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
UPF1 ATPase autoinhibition and activation modulate RNA binding kinetics and NMD efficiencyNucleic acids research · 2024
Summary (written by the submitters)
The RNA helicase UPF1 interacts with mRNAs, mRNA decay machinery, and the terminating ribosome to promote nonsense-mediated mRNA decay (NMD). Structural and biochemical data have revealed that UPF1 exists in an enzymatically autoinhibited “closed” state. Upon binding the NMD protein UPF2, UPF1 undergoes an extensive conformational change into a more enzymatically active “open” state, which exhibits enhanced ATPase and helicase activity.
Read the full summary ↓
However, mechanically deficient UPF1 mutants can support efficient NMD, bringing into question the roles of UPF1 enzymatic autoinhibition and activation in NMD. Here, we identify two additional important features of the activated open state: slower nucleic acid binding kinetics and enhanced ATP-stimulated nucleic acid dissociation kinetics. Computational modeling based on empirical measurements of UPF1, UPF2, and RNA interaction kinetics predicts that the majority of UPF1-RNA binding and dissociation events in cells occur independently of UPF2 binding. We find that UPF1 mutants with either reduced or accelerated dissociation from RNA have NMD defects, whereas UPF1 mutants that are more dependent on UPF2 for catalytic activity remain active on well-established NMD targets. These findings support a model in which the kinetics of UPF1-mRNA interactions are important determinants of cellular NMD efficiency.
Published in
UPF1 ATPase autoinhibition and activation modulate RNA binding kinetics and NMD efficiency
Chapman JH, Youle AM, Grimme AL et al. · Nucleic acids research 2024 · PMID 38412299 · doi:10.1093/nar/gkae136
This dataset
Open GSE246483 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 GSE246483_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 PRJNA1033188 and SRA study SRP468959. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 38412299) ↗
Study design
16 conditions, mostly in triplicate
Flp-In 293 T-REx, CLIP-UPF1 A546H, siNT, ×3 Flp-In 293 T-REx, CLIP-UPF1 A546H, siUPF1, ×3 Flp-In 293 T-REx, CLIP, siNT, ×3 Flp-In 293 T-REx, CLIP, siUPF1, ×3 Flp-In 293 T-REx, CLIP-UPF1 DE636AA, siNT, ×3 Flp-In 293 T-REx, CLIP-UPF1 DE636AA, siUPF1, ×3 Flp-In 293 T-REx, CLIP-UPF1 E797R, siNT, ×3 Flp-In 293 T-REx, CLIP-UPF1 E797R, siUPF1, ×3 +8 more

Supports a between-group comparison across 48 samples.

How we read this: 16 replicated groups read from 48 sample titles; they account for 48 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

+ 8 more — browse all 48 samples with per-sample file links →

Datasets on a similar topic

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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.