← BioTransfer GEO Dataset Finder
GEO series

RNA-seq analysis to examine the effect of the Ube2e1 and Ube2e1 knockdown on gene expression profile in 3T3-L1 pre-adipocyte cells

GSE268800 Mus musculus (mouse) RNA-seq (gene expression) 18 samples Submitted 2025/01/09 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: 6 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
Noncoding variation near UBE2E2 orchestrates cardiometabolic pathophenotypes through polygenic effectorsJCI insight · 2024
Summary (written by the submitters)
UBE2E2 and UBE2E1 are both members of the same family of E2 conjugating enzymes raising the question of whether they are functionally redundant, particularly given that genetic targeting of both genes inhibited adipogenesis, in vitro. To explore this question, we sought to test for molecular redundancy using transcriptomics analyses. We performed comparative transcriptomics analyses of 3T3-L1 cells in which we targeted either Ube2e2 or Ube2e1.
Published in
Noncoding variation near UBE2E2 orchestrates cardiometabolic pathophenotypes through polygenic effectors
Zhang Y, David NL, Pesaresi T et al. · JCI insight 2024 · PMID 39656538 · doi:10.1172/jci.insight.184140
This dataset
Open GSE268800 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 GSE268800_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 PRJNA1118760 and SRA study SRP511070. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39656538) ↗
Study design
6 conditions, mostly in triplicate
3T3-L1 cells, Scramble, Control, ×3 3T3-L1 cells, Scramble, adipogenic induction … ×3 3T3-L1 cells, shUbe2e1, Control, ×3 3T3-L1 cells, shUbe2e1, adipogenic induction … ×3 3T3-L1 cells, shUbe2e2, Control, ×3 3T3-L1 cells, shUbe2e2, adipogenic induction … ×3

Supports a between-group comparison across 18 samples.

How we read this: 6 replicated groups read from 18 sample titles; they account for 18 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

Search all mouse RNA-seq datasets in GEO →

Share this dataset

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.