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mTORC1 hyperactivation blocks pluripotent stem cells fate transitions through TFE3-NuRD association [RNA-Seq]

GSE274328 Mus musculus (mouse) RNA-seq (gene expression) 16 samples Submitted 2024/08/13 Platform GPL28330
At a glance

RNA-seq (gene expression) · mouse · 16 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
16 samples: 8 conditions, mostly in duplicateGroups 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)
As an evolutionarily conserved master regulator of metabolism, mechanistic target of rapamycin complex 1 (mTORC1) regulates cell states and fates in development, cancer and aging. mTORC1 activity regulation was critical for pluripotent stem cells maintenance and cell fate transitions. Inhibition of mTORC1 induces embryonic stem cells (ESCs) entry into a paused state which reversibly arrests self-renewal leaving pluripotency intact.
Read the full summary ↓
Hyperactivation of mTORC1 impedes both pluripotency re-establishment and exit of PSCs. As shown that mTORC1 mediates TFE3 nuclear translocation block pluripotency exit, whether similar mechanisms through transcription factor TFE3 are involved in these processes, and the detailed mechanism by which mTORC1-TFE3 regulates critical transcriptional processes for these transitions, remain unclear. In this study, we demonstrate that the nuclear translocation of TFE3, induced by hyperactivation of mTORC1, results in its binding to the nucleosome remodeling and deacetylation (NuRD) complex in both re-establishment and exit of pluripotency. This interaction inhibits the expression of various crucial genes during different fate transitions of PSCs. Our findings uncover a common and key role of TFE3-NuRD association as mediator of mTORC1 to block pluripotent cell fate transitions, with implications for various fields including physiological and pathological diseases.
This dataset
Open GSE274328 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 GSE274328_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 PRJNA1139377 and SRA study SRP522687. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
8 conditions, mostly in duplicate
OSKM iPSC,wildtype,Day5, ×2 OSKM iPSC,Tsc1 KO,Day5, ×2 OSKM iPSC,Tsc1 KO+shTfe3-1,Day5, ×2 OSKM iPSC,Tsc1 KO+shTfe3-2,Day5, ×2 OSKM iPSC,wildtype,Day10, ×2 OSKM iPSC,Tsc1 KO,Day10, ×2 OSKM iPSC,Tsc1 KO+shTfe3-1,Day10, ×2 OSKM iPSC,Tsc1 KO+shTfe3-2,Day10, ×2

Supports a between-group comparison across 16 samples.

How we read this: 8 replicated groups read from 16 sample titles; they account for 16 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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