GEO series

Systematic discovery of potential regulators of transcriptional variability reveals NAP1L1 as a transcriptional stabilizer in mouse ESCs

GSE306521 Mus musculus (mouse) Single-cell RNA-seq 26 samples Submitted 2026/08/06 Platform GPL30172

At a glance

Single-cell RNA-seq · mouse · 26 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: Mus musculus (mouse)
Samples: 26 samples: 9 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.

Summary (written by the submitters)

Embryonic stem cells (ESCs) maintain their capacity to generate all different cell types of the developing embryo. When grown in serum, ESCs display transcriptional heterogeneity of several key pluripotency-related genes (e.g. Nanog). This transcriptional variability was suggested to support ESC pluripotency by enabling them to differentiate along different lineages simultaneously.

Read the full summary ↓

We hypothesized that expression heterogeneity is a regulated process, mediated by transcriptional (de)stabilizers. To test this systematically, and to identify potential ESC regulators of transcriptional variability, we compared single-cell RNA-seq (scRNA-seq) with ChIP-seq datasets to identify variable and stable genes in ESCs. One of the potential ‘stabilizer’ proteins we identified is Nucleosome Assembly Protein 1-Like 1 (NAP1L1), a member of the NAP1 family. NAP1L1 participates in many cellular functions, including nucleosome maintenance, chromatin remodeling, cell division, and transcription. To test its potential ‘stabilizer’ function, we recruited NAP1L1 to the Nanog promoter via fusion with dCAS9. Immunofluorescence (IF) and single-molecule fluorescence in situ hybridization (smFISH) analyses of Nanog expression revealed that NAP1L1 directly stabilizes both RNA and protein expression levels. To further explore NAP1L1’s function genome-wide, we generated Nap1l1-knock-out (KO) ESCs. scRNA-seq experiments comparing Nap1l1-KO and WT ESCs, revealed increased gene expression variability in Nap1l1-KO cells. To reveal the potential mechanism by which NAP1L1 exerts its stabilizing activity we identified NAP1L1-interacting partners by co-IP followed by Mass-Spectrometry experiments, revealing DPPA3 as a key interacting partner. Taken together, we provide a systematic discovery platform for regulators of transcriptional variability and identify NAP1L1 as a transcriptional stabilizer in ESCs.

This dataset

Open GSE306521 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 GSE306521_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 PRJNA1311037 and SRA study SRP612715. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

9 conditions, mostly in triplicate

WT-0D ×3 WT-2D ×3 WT-4D ×3 alpha-KO-0D ×3 alpha-KO-2D ×3 alpha-KO-4D ×3 full-KO-2D ×3 full-KO-4D ×3 +1 more

Supports a between-group comparison across 26 samples.

How we read this: 9 replicated groups read from 26 sample titles; they account for 26 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

GSM9202652 WT-0D-1 WT-0D
GSM9202653 WT-2D-1 WT-2D
GSM9202654 WT-4D-1 WT-4D
GSM9202655 WT-0D-2 WT-0D
GSM9202656 WT-2D-2 WT-2D
GSM9202657 WT-4D-2 WT-4D
GSM9202658 WT-0D-3 WT-0D
GSM9202659 WT-2D-3 WT-2D
GSM9202660 WT-4D-3 WT-4D
GSM9202661 alpha-KO-0D-1 alpha-KO-0D
GSM9202662 alpha-KO-2D-1 alpha-KO-2D
GSM9202663 alpha-KO-4D-1 alpha-KO-4D
GSM9202664 alpha-KO-0D-2 alpha-KO-0D
GSM9202665 alpha-KO-2D-2 alpha-KO-2D
GSM9202666 alpha-KO-4D-2 alpha-KO-4D
GSM9202667 alpha-KO-0D-3 alpha-KO-0D
GSM9202668 alpha-KO-2D-3 alpha-KO-2D
GSM9202669 alpha-KO-4D-3 alpha-KO-4D
GSM9202670 full-KO-0D-1 full-KO-0D
GSM9202671 full-KO-2D-1 full-KO-2D
GSM9202672 full-KO-4D-1 full-KO-4D
GSM9202673 full-KO-0D-2 full-KO-0D
GSM9202674 full-KO-2D-2 full-KO-2D
GSM9202675 full-KO-4D-2 full-KO-4D
GSM9202676 full-KO-2D-3 full-KO-2D
GSM9202677 full-KO-4D-3 full-KO-4D

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