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Single cell sequencing and retrograde barcode tracing reveal human DA neuron identities based on projection patterns in stem cell-derived grafts

GSE233885 Homo sapiens (human) Single-cell RNA-seq 21 samples Submitted 2024/11/03 Platform GPL24676
At a glance

Single-cell RNA-seq · human · 21 samples

What it is
Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism
Homo sapiens (human)
Samples
21 samples: 21 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
TARGET-seq: Linking single-cell transcriptomics of human dopaminergic neurons with their target specificityProceedings of the National Academy of Sciences of the United States of America · 2024
Summary (written by the submitters)
Groundbreaking research in the last decade has definitively established human pluripotent stem cells (hPSCs) as a powerful source for the unlimited generation of dopamine (DA) neurons used in cell-based therapy in Parkinson’s disease (PD). However, DA neurons constitute a heterogeneous group of cells with different molecular identities and, consequently, different functions and innervation targets.
Read the full summary ↓
Moreover, the inaccessibility of the human brain has so far hindered our understanding of the highly complex human DA system and, therefore, the design of DA neuron subtype-specific differentiation protocols for more effective cell replacement therapies. Currently, DA neurons – located in human ventral midbrain – can only be reliably distinguished based on their projection patterns. Here, we used hPSCs to derive and then transplant DA neurons into a rat model of PD. After one year of transplantation, we performed single nucleus RNA sequencing (snRNAseq) of ~80,000 human nuclei to transcriptionally define cell type composition and obtained a comprehensive map of DA neuron molecular identities. Exploiting the fact that transplanted DA neurons innervated and integrated within the host circuitry, we then combined snRNAseq with axonal retrograde AAV barcoding to trace the projection patterns of molecularly distinct human DA neuron subtypes in the grafts. We thus defined human DA neuron transcriptional profiles based on their target-specific outgrowth in the host brain. The resulting datasets provide an unprecedented resource both for elucidating the molecular basis of human DA neuron diversity as well as for developing more targeted cell-based therapies, with major implications for outcomes of PD patients.
Published in
TARGET-seq: Linking single-cell transcriptomics of human dopaminergic neurons with their target specificity
Fiorenzano A, Storm P, Sozzi E et al. · Proceedings of the National Academy of Sciences of the United States of America 2024 · PMID 39541349 · doi:10.1073/pnas.2410331121
This dataset
Open GSE233885 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 GSE233885_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 PRJNA978512. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39541349) ↗
Study design
21 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 21 sample titles: 21 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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