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Technical and biological sources of noise confound multiplexed enhancer AAV screening [dataset4]

GSE312361 Mus musculus (mouse) Single-cell RNA-seq 47 samples Submitted 2026/02/23 Platform GPL24247
At a glance

Single-cell RNA-seq · mouse · 47 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
47 samples: 43 distinct titles, 4 of them repeatedGroups 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
Technical and biological sources of noise confound multiplexed enhancer AAV screeningNature communications · 2026
Summary (written by the submitters)
Cis-acting regulatory enhancer elements are valuable tools for gaining cell type-specific genetic access. Leveraging large chromatin accessibility atlases, putative enhancer sequences can be identified and deployed in adeno-associated virus (AAV) delivery platforms. However, a significant bottleneck in enhancer AAV discovery is charting their detailed expression patterns in vivo, a process that currently requires gold-standard one-by-one testing.
Read the full summary ↓
Here we perform barcoded multiplexed screening of enhancer AAVs at cell type resolution using single cell RNA sequencing and taxonomy mapping. We executed a proof-of-concept study using small pools of well-validated enhancer-AAVs expressing in a variety of neuronal and non-neuronal cell types across the mouse brain. Unexpectedly, we encountered substantial technical and biological noise including chimeric packaging products, necessitating development of novel techniques to accurately deconvolve enhancer expression patterns. These results underscore the need for improved methods to mitigate noise and highlight the complexity of enhancer AAV biology in vivo.
Published in
Technical and biological sources of noise confound multiplexed enhancer AAV screening
Hunker AC, Mich JK, Taskin N et al. · Nature communications 2026 · PMID 42049725 · doi:10.1038/s41467-026-72147-8
This dataset
Open GSE312361 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 GSE312361_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 PRJNA1373163 and SRA study SRP651846. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 42049725) ↗
Study design
43 distinct titles, 4 of them repeated
Nuclei_AiP13244_SYFP2pos_CTX_GEX_L ×2 Nuclei_AiP13247_SYFP2pos_CTX_GEX_L ×2 WholeCells_20plex-multiscQers_SYFP2pos_ALM_GE… ×2 WholeCells_20plex-multiscQers_SYFP2pos_STR_GE… ×2

How we read this: Read from 47 sample titles: 43 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

+ 7 more — browse all 47 samples with per-sample file links →

Datasets on a similar topic

Search all mouse RNA-seq datasets in GEO →

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