GEO series

CRISPR-Cas9 Screening Reveals Microproteins Regulating Adipocyte Proliferation and Lipid Metabolism [RNA-seq]

GSE297349 Mus musculus (mouse) RNA-seq (gene expression) 18 samples Submitted 2025/08/27 Platform GPL24247

At a glance

RNA-seq (gene expression) · mouse · 18 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: 18 samples: 18 samples, each with a distinct title — no replicated groupsGroups 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: CRISPR-Cas9 screening reveals microproteins regulating adipocyte proliferation and lipid metabolismProceedings of the National Academy of Sciences of the United States of America · 2025

Summary (written by the submitters)

Small open reading frames (smORFs) encode microproteins that play crucial roles in various biological processes, yet their functions in adipocyte biology remain largely unexplored. In a previous study, we identified thousands of smORFs in white and brown adipocytes derived from the stromal vascular fraction (SVF) of mice using ribosome profiling (Ribo-Seq).

Read the full summary ↓

Here, we expand on this work by identifying additional smORFs related to adipocytes using the in vitro 3T3-L1 preadipocyte model. To systematically investigate the functional relevance of these smORFs, we designed a custom CRISPR/Cas9 guide RNA (sgRNA) library and screened for smORFs influencing adipocyte proliferation and differentiation. Through a dropout screen and fluorescence-assisted cell sorting (FACS) of lipid droplets, we identified dozens of smORFs that regulate either cell proliferation or lipid accumulation. Among these, we validated a novel microprotein as a key regulator of adipocyte differentiation. These findings highlight the potential of CRISPR/Cas9-based screening to uncover functional smORFs and provide a framework for further exploration of microproteins in adipocyte biology and metabolic regulation.

Published in

CRISPR-Cas9 screening reveals microproteins regulating adipocyte proliferation and lipid metabolism

Pai VJ, Shan H, Donaldson CJ et al. · Proceedings of the National Academy of Sciences of the United States of America 2025 · PMID 40773238 · doi:10.1073/pnas.2506534122

This dataset

Open GSE297349 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 GSE297349_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 PRJNA1263618 and SRA study SRP585736. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40773238) ↗

Study design

18 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 18 sample titles: 18 distinct titles with little repetition. 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

GSM8989047 3T3-L1 undifferentiated, biol rep 1, total RNA seq
GSM8989048 3T3-L1 undifferentiated, biol rep 1, mRNA seq
GSM8989049 3T3-L1 undifferentiated, biol rep 2, total RNA seq
GSM8989050 3T3-L1 undifferentiated, biol rep 2, mRNA seq
GSM8989051 3T3-L1 undifferentiated, biol rep 3, total RNA seq
GSM8989052 3T3-L1 undifferentiated, biol rep 3, mRNA seq
GSM8989053 3T3-L1 differentiated day 3, biol rep 1, total RNA seq
GSM8989054 3T3-L1 differentiated day 3, biol rep 1, mRNA seq
GSM8989055 3T3-L1 differentiated day 3, biol rep 2, total RNA seq
GSM8989056 3T3-L1 differentiated day 3, biol rep 2, mRNA seq
GSM8989057 3T3-L1 differentiated day 3, biol rep 3, total RNA seq
GSM8989058 3T3-L1 differentiated day 3, biol rep 3, mRNA seq
GSM8989059 3T3-L1 differentiated day 7, biol rep 1, total RNA seq
GSM8989060 3T3-L1 differentiated day 7, biol rep 1, mRNA seq
GSM8989061 3T3-L1 differentiated day 7, biol rep 2, total RNA seq
GSM8989062 3T3-L1 differentiated day 7, biol rep 2, mRNA seq
GSM8989063 3T3-L1 differentiated day 7, biol rep 3, total RNA seq
GSM8989064 3T3-L1 differentiated day 7, biol rep 3, mRNA seq

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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.