A single-nucleus transcriptomic atlas of the adult macaque ventral tegmental area

Library construction followed the manufacturer's protocol. Sequencing was performed on DNBSEQ-T1 instruments (BGI). For every library, the deposited sequencing output includes both cDNA-derived reads and oligonucleotide-derived reads, together with sequencing quality reports.

These read types were used jointly for barcode assignment and gene-expression quantification.  Primary data processingRead processing and count generation were performed using dnbc4tools (v2.1.3) with the Macaca fascicularis reference genome annotation file Macaca_fascicularis_5.0.91.2.2.gtf. Raw and filtered gene-barcode count matrices are provided for each library as Matrix files. In each matrix, rows represent genes, columns represent cell barcodes, and values represent unique molecular identifier (UMI) counts.

The raw matrices retain all barcodes reported by the upstream workflow, whereas the filtered matrices contain barcodes retained after the initial nucleus identification step implemented by dnbc4tools.  Integrated atlas and annotationsThe integrated atlas was generated using R-based single-cell analysis workflows. Ambient RNA contamination was corrected using SoupX, followed by quality-control filtering, doublet detection, dataset integration, dimensionality reduction, clustering, and Seurat-based annotation.

Integration was performed to mitigate technical and inter-animal batch effects. The final metadata include annotations for dopaminergic neurons (DA), non-dopaminergic neurons (Non DA Neuron), oligodendrocytes (Oligo), oligodendrocyte precursor cells (OPC), astrocytes (Astro), microglia (Micro), endothelial cells (Endothelial), and vascular and leptomeningeal cells (VLMC). The processed Seurat object contains cluster annotations, metadata, and both original and SoupX-corrected gene-expression matrices.  Data organization and reuseThe deposition is organized into raw sequencing data (Fq), gene-expression matrices (Matrix), SoupX-corrected matrices (SoupX), processed files (Supplementary data), and reproducible analysis materials (Macaque_VTA_snRNA_Script-main.zip, github.com/qwccccc/Macaque_VTA_snRNA_Script.git).

The processed files include the Seurat object ‘Macaque_VTA_dataset.rds’, DA/Neuron/Non-Neuron Seurat object, marker gene tables for DA, neuronal, and non-neuronal populations, differential expression results comparing the DA_6 cluster with other DA clusters, the ‘DA_6_top100_go_term’ results, and differential expression results comparing macaque and rat DA populations. The Seurat object contains processed expression data, nucleus and library metadata, dimensional reductions, clustering assignments, and curated annotations, and can be directly loaded and analyzed using the Seurat R package.

This dataset may facilitate cell-type annotation, marker identification, cross-species comparative analyses, and disease-related studies involving the VTA.