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Time-resolved function of cell polarity kinases PRKCZ and PRKCI in CNS myelination [bulk_oligo]

GSE263979 Mus musculus (mouse) RNA-seq (gene expression) 11 samples Submitted 2024/04/21 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 11 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
11 samples: 11 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)
The atypical Protein Kinase C (aPKC) is a critical component of the PAR polarity complex, as well as of cell polarity in general. There are two paralogs of aPKC in the mammalian genome. Their expression pattern and functional role in oligodendrocyte lineage differentiation and development remains heretofore uncharacterized. Here we show that both paralogs of aPKC – PRKCI, the primary transcript of Prkci and PKMz, an alternate transcript of Prkcz – are expressed during oligodendrocyte differentiation, yet are functionally non-redundant.
Read the full summary ↓
Asymmetric cell division and early specification of the oligodendrocyte fate stage required both paralogs. By contrast, the stage of oligodendrocyte maturation involving membrane polarization and myelination of axons continued to require PKMz, but no longer needed PRKCI. Taken together, our results indicate to a two-stage role of aPKCs and cell polarity in oligodendrocyte differentiation and development.
This dataset
Open GSE263979 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 GSE263979_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 PRJNA1100495 and SRA study SRP501832. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
11 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 11 sample titles: 11 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
Datasets on a similar topic

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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.