GEO series

MAPK14 Governs Mammalian Müller glia Fate Determination between Gliosis and Reprogramming

GSE316279 Homo sapiens (human) Single-cell RNA-seq 12 samples Submitted 2026/01/18 Platform GPL29480

At a glance

Single-cell RNA-seq · human · 12 samples

What it is: Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism: Homo sapiens (human)
Samples: 12 samples: 12 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)

Irreversible loss of retinal neurons is the leading cause of blindness. Harnessing the latent stem cell potential of mammalian Müller glia offers a promising strategy for endogenous retinal regeneration. Shifting the Müller glia response from gliosis to regeneration after retinal injury is a critical step in promoting the orderly entry of Müller glia into a regenerative program. However, the molecular switch governing this divergent fate decision remains elusive. Here, through RNA-seq and scRNA-seq, we confirm the upstream determinant of Müller glia fate after retinal injury.

This dataset

Open GSE316279 in finder → Find more human 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 GSE316279_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1402154 and SRA study SRP661780. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

12 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 12 sample titles: 12 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

GSM9448788 MIO-M1 cells, siControl for siMapk14_1, Day 3
GSM9448789 MIO-M1 cells, siControl for siMapk14_2, Day 3
GSM9448790 MIO-M1 cells, siControl for siMapk14_3, Day 3
GSM9448791 MIO-M1 cells, siMapk14_1, Day 3
GSM9448792 MIO-M1 cells, siMapk14_2, Day 3
GSM9448793 MIO-M1 cells, siMapk14_3, Day 3
GSM9448794 MIO-M1 cells, siControl for siMapk8+9_1, Day 3
GSM9448795 MIO-M1 cells, siControl for siMapk8+9_2, Day 3
GSM9448796 MIO-M1 cells, siControl for siMapk8+9_3, Day 3
GSM9448797 MIO-M1 cells, siMapk8+9_1, Day 3
GSM9448798 MIO-M1 cells, siMapk8+9_2, Day 3
GSM9448799 MIO-M1 cells, siMapk8+9_3, Day 3

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