GEO series

Role of the STAR proteins in early mammalian development [RNA-seq]

GSE153800 Mus musculus (mouse) RNA-seq (gene expression) 27 samples Submitted 2024/08/01 Platform GPL17021

At a glance

RNA-seq (gene expression) · mouse · 27 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: 27 samples: 27 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.

Summary (written by the submitters)

RNA binding proteins (RBPs), are emerging as important master regulators of the biology of stem cells in both pluripotency and differentiation. The Signal transduction and activation of RNA (STAR) is family of proteins shown to be involved in mammalian development. We characterized the role of two members of the family, Sam68 and Quaking (QKI), in pluripotency and differentiation of mouse embryonic stem cells (mESCs) by making use of CRISPR-Cas9 generated knock-out (KO) cell lines along with RNA-sequencing, ribosome profiling and RNA crosslinking followed by immunoprecipitation (iCLIP2).

Read the full summary ↓

Our results indicate that both proteins are important in the regulation of mESCs cell cycle and self-renewal and are indispensable for proper cardiomyocyte differentiation by regulating expression, alternative splicing and translation of the cardiogenic factors GATA4. This work highlights the importance of the RBPs during the differentiation of mESCs.

This dataset

Open GSE153800 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 GSE153800_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 PRJNA644121 and SRA study SRP270009. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 42240622) ↗

Study design

27 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 27 sample titles: 27 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

GSM4654311 Sam68 KO, time 0, replicate 1 [RNA-seq]
GSM4654312 Sam68 KO, time 0, replicate 2 [RNA-seq]
GSM4654313 Sam68 KO, time 0, replicate 3 [RNA-seq]
GSM4654314 Sam68 KO, time 10, replicate 1 [RNA-seq]
GSM4654315 Sam68 KO, time 10, replicate 2 [RNA-seq]
GSM4654316 Sam68 KO, time 10, replicate 3 [RNA-seq]
GSM4654317 Sam68 KO, time 3, replicate 1 [RNA-seq]
GSM4654318 Sam68 KO, time 3, replicate 2 [RNA-seq]
GSM4654319 Sam68 KO, time 3, replicate 3 [RNA-seq]
GSM4654320 Quaking KO, time 0, replicate 1 [RNA-seq]
GSM4654321 Quaking KO, time 10, replicate 1 [RNA-seq]
GSM4654322 Quaking KO, time 3, replicate 1 [RNA-seq]
GSM4654323 Quaking KO, time 0, replicate 2 [RNA-seq]
GSM4654324 Quaking KO, time 10, replicate 2 [RNA-seq]
GSM4654325 Quaking KO, time 3, replicate 2 [RNA-seq]
GSM4654326 Quaking KO, time 0, replicate 3 [RNA-seq]
GSM4654327 Quaking KO, time 10, replicate 3 [RNA-seq]
GSM4654328 Quaking KO, time 3, replicate 3 [RNA-seq]
GSM4654329 Wild Type, time 0, replicate 1 [RNA-seq]
GSM4654330 Wild Type, time 10, replicate 1 [RNA-seq]
GSM4654331 Wild Type, time 3, replicate 1 [RNA-seq]
GSM4654332 Wild Type, time 0, replicate 2 [RNA-seq]
GSM4654333 Wild Type, time 10, replicate 2 [RNA-seq]
GSM4654334 Wild Type, time 3, replicate 2 [RNA-seq]
GSM4654335 Wild Type, time 0, replicate 3 [RNA-seq]
GSM4654336 Wild Type, time 10, replicate 3 [RNA-seq]
GSM4654337 Wild Type, time 3, replicate 3 [RNA-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.