GEO series

Degron models: a toolbox for rapid in vivo depletion of essential proteins regulating mRNA metabolism

GSE309776 Mus musculus (mouse) RNA-seq (gene expression) 60 samples Submitted 2026/02/23 Platform GPL24973

At a glance

RNA-seq (gene expression) · mouse · 60 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: Mus musculus (mouse)
Samples: 60 samples: 21 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: Degron models: a toolbox for rapid in vivo depletion of essential proteins regulating mRNA metabolismCommunications biology · 2026

Summary (written by the submitters)

Due to their essentiality, studying proteins involved in fundamental processes in vivo is challenging. PROTAC-based systems offer time-controlled protein depletion, but their characterization in vivo remains limited. Here, with an efficient direct zygote editing protocol, we generated degron-tag models (dTAG/FKBP or BromoTag) for seven genes involved in therapeutic and endogenous mRNA metabolism (Cnot1, Pan2, Tent5a, Tent4b, Dcp2, Rnasel, Tsg101).

Read the full summary ↓

Degron tags occasionally caused phenotypes that were often mitigated by tag position or tagging system change. In cells, both approaches yielded rapid and sustained degradation. In mice, dTAG depletion was effective but varied by protein and administration route, whereas BromoTag showed no in vivo activity. We showcase the utility of these models through an analysis of CNOT1's roles in cell division, immunity, and poly(A) tail maintenance. We present a valuable toolbox for studying mRNA metabolism in mammalian models, while providing a benchmark for applying degron-tag models to study other biological processes.

Published in

Degron models: a toolbox for rapid in vivo depletion of essential proteins regulating mRNA metabolism

Antczak W, Szpila M, Sałas K et al. · Communications biology 2026 · PMID 41851445 · doi:10.1038/s42003-026-09828-z

This dataset

Open GSE309776 in finder → Find more mouse 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 GSE309776_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 PRJNA1363157 and SRA study SRP644318. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41851445) ↗

Study design

21 conditions, mostly in triplicate

liver, CNOT1, dTAG 2h, ×3 liver, CNOT1, dTAG 24h, ×3 liver, CNOT1, DMSO, ×3 liver, WT, dTAG 24h, ×3 BMDM, CNOT1, DMSO, ×3 BMDM, CNOT1, dTAG, ×3 BMDM, DCP2, DMSO, ×3 BMDM, DCP2, dTAG, ×3 +13 more

Supports a between-group comparison across 60 samples.

How we read this: 21 replicated groups read from 60 sample titles; they account for 60 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

GSM9278882 liver, CNOT1, dTAG 2h, 1 liver, CNOT1, dTAG 2h,
GSM9278883 liver, CNOT1, dTAG 2h, 2 liver, CNOT1, dTAG 2h,
GSM9278884 liver, CNOT1, dTAG 2h, 3 liver, CNOT1, dTAG 2h,
GSM9278885 liver, CNOT1, dTAG 24h, 1 liver, CNOT1, dTAG 24h,
GSM9278886 liver, CNOT1, dTAG 24h, 2 liver, CNOT1, dTAG 24h,
GSM9278887 liver, CNOT1, dTAG 24h, 3 liver, CNOT1, dTAG 24h,
GSM9278888 liver, CNOT1, DMSO, 1 liver, CNOT1, DMSO,
GSM9278889 liver, CNOT1, DMSO, 2 liver, CNOT1, DMSO,
GSM9278890 liver, CNOT1, DMSO, 3 liver, CNOT1, DMSO,
GSM9278891 liver, WT, dTAG 24h, 1 liver, WT, dTAG 24h,
GSM9278892 liver, WT, dTAG 24h, 2 liver, WT, dTAG 24h,
GSM9278893 liver, WT, dTAG 24h, 3 liver, WT, dTAG 24h,
GSM9278894 liver, WT, DRS, 1 liver, WT, DRS,
GSM9278895 liver, WT, DRS, 2 liver, WT, DRS,
GSM9278896 liver, CNOT1, DMSO, DRS, 1 liver, CNOT1, DMSO, DRS,
GSM9278897 liver, CNOT1, DMSO, DRS, 2 liver, CNOT1, DMSO, DRS,
GSM9278898 liver, CNOT1, dTAG, DRS, 1 liver, CNOT1, dTAG, DRS,
GSM9278899 liver, CNOT1, dTAG, DRS, 2 liver, CNOT1, dTAG, DRS,
GSM9278900 BMDM, CNOT1, DMSO, 1 BMDM, CNOT1, DMSO,
GSM9278901 BMDM, CNOT1, DMSO, 2 BMDM, CNOT1, DMSO,
GSM9278902 BMDM, CNOT1, DMSO, 3 BMDM, CNOT1, DMSO,
GSM9278903 BMDM, CNOT1, dTAG, 1 BMDM, CNOT1, dTAG,
GSM9278904 BMDM, CNOT1, dTAG, 2 BMDM, CNOT1, dTAG,
GSM9278905 BMDM, CNOT1, dTAG, 3 BMDM, CNOT1, dTAG,
GSM9278906 BMDM, DCP2, DMSO, 1 BMDM, DCP2, DMSO,
GSM9278907 BMDM, DCP2, DMSO, 2 BMDM, DCP2, DMSO,
GSM9278908 BMDM, DCP2, DMSO, 3 BMDM, DCP2, DMSO,
GSM9278909 BMDM, DCP2, dTAG, 1 BMDM, DCP2, dTAG,
GSM9278910 BMDM, DCP2, dTAG, 2 BMDM, DCP2, dTAG,
GSM9278911 BMDM, DCP2, dTAG, 3 BMDM, DCP2, dTAG,
GSM9278912 BMDM, PAN2, DMSO, 1 BMDM, PAN2, DMSO,
GSM9278913 BMDM, PAN2, DMSO, 2 BMDM, PAN2, DMSO,
GSM9278914 BMDM, PAN2, DMSO, 3 BMDM, PAN2, DMSO,
GSM9278915 BMDM, PAN2, dTAG, 1 BMDM, PAN2, dTAG,
GSM9278916 BMDM, PAN2, dTAG, 2 BMDM, PAN2, dTAG,
GSM9278917 BMDM, PAN2, dTAG, 3 BMDM, PAN2, dTAG,
GSM9278918 BMDM, RNASEL, DMSO, 1 BMDM, RNASEL, DMSO,
GSM9278919 BMDM, RNASEL, DMSO, 2 BMDM, RNASEL, DMSO,
GSM9278920 BMDM, RNASEL, DMSO, 3 BMDM, RNASEL, DMSO,
GSM9278921 BMDM, RNASEL, dTAG, 1 BMDM, RNASEL, dTAG,

+ 20 more — browse all 60 samples with per-sample file links →

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