GEO series

Nuclei isolation from frozen heart tissues through an easy-to-operating, prompt, and inexpensive method for single-nucleus Multiome-seq

GSE281085 Mus musculus (mouse) Single-nucleus RNA-seq 18 samples Submitted 2025/01/01 Platform GPL24247

At a glance

Single-nucleus RNA-seq · mouse · 18 samples

What it is: Single-nucleus RNA-seqGene activity measured in individual nuclei (used when whole cells are hard to isolate, for example from frozen tissue).
Organism: Mus musculus (mouse)
Samples: 18 samples: 18 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.
Paper: A simple approach of nuclei isolation for single nucleus multiome sequencingJournal of molecular and cellular cardiology · 2025

Summary (written by the submitters)

Existing protocols are difficult to obtain high-quality sequencing data for isolating nuclei from long-term cryopreserved frozen tissues, especially such as hearts that contain rich fibrous connective tissue for single-nucleus multiome sequencing (snMultiome-seq, including snRNA-seq and snATAC-seq for the same nucleus). Here, we optimize some current methods for isolating nuclei from frozen tissues and describe an easy-to-operating, prompt, and inexpensive method for obtaining high-quality single-nucleus sequencing data, which is named as Douncer-Filter-Gradient-Centrifugation (DFGC).

Read the full summary ↓

This protocol takes about 1.5h to complete, including mincing (1min), douncing (3min), filtering (20min) and density gradient centrifugating (40min), depending on how many samples are done at the same time, and does not require special reagents and instruments, so it is versatile and economical for most laboratories. We selected two commonly used isolating nuclei methods, microBeads- and FACS-, as controls and all analysis processes are carried out in accordance with unified standardization, including nucleus morphology, library construction, library quality inspection, data parameters, clustering, cell-type identification, and gene expression distribution. This protocol provides a step-by-step guide to nuclei isolating from frozen heart tissues to generate high-quality single nucleus gene expression and chromatin transposase accessibility sequencing data for the same nucleus.

Published in

A simple approach of nuclei isolation for single nucleus multiome sequencing

Wang Y, Ren D, Kang R et al. · Journal of molecular and cellular cardiology 2025 · PMID 40849079 · doi:10.1016/j.yjmcc.2025.08.009

This dataset

Open GSE281085 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 GSE281085_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 PRJNA1182253 and SRA study SRP543267. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40849079) ↗

Study design

18 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 18 sample titles: 18 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

GSM8610658 Beads_1_RNA,snMultiome
GSM8610659 Beads_2_RNA,snMultiome
GSM8610660 Beads_3_RNA,snMultiome
GSM8610661 Beads_1_ATAC,snMultiome
GSM8610662 Beads_2_ATAC,snMultiome
GSM8610663 Beads_3_ATAC,snMultiome
GSM8610664 FACS_1_RNA,snMultiome
GSM8610665 FACS_2_RNA,snMultiome
GSM8610666 FACS_3_RNA,snMultiome
GSM8610667 FACS_1_ATAC,snMultiome
GSM8610668 FACS_2_ATAC,snMultiome
GSM8610669 FACS_3_ATAC,snMultiome
GSM8610670 DFGC_1_RNA,snMultiome
GSM8610671 DFGC_2_RNA,snMultiome
GSM8610672 DFGC_3_RNA,snMultiome
GSM8610673 DFGC_1_ATAC,snMultiome
GSM8610674 DFGC_2_ATAC,snMultiome
GSM8610675 DFGC_3_ATAC,snMultiome

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