Spatial transcriptomics and in silico random pooling identify novel markers of vulnerable and resistant dopamine neurons

Defining transcriptional profiles of substantia nigra pars compacta (SNc) and ventral tegmental area (VTA) dopamine neurons (DNs) is critical to understand their differential vulnerability in Parkinson disease. Reported transcriptional profiles for these DN subpopulations display extensive variability. To resolve this issue we analyze single isolated SNc and VTA DNs from 18 human post mortem brains using LCM-seq, providing the largest transcriptome dataset of adult DNs. Using a unique iterative random pooling algorithm, with high utility to resolve differences across any two subpopulations, we reveal 33 robust DN subtype-specific markers. We define that eight subjects is the minimal cohort size required to identify these stably differentially expressed genes, explaining inconsistent results from smaller cohorts. Finally, we identify three genes, ZCCHC12, CDH13 and SERPINE2, that alone can classify SNc or VTA DNs across species. The markers identified will be vital for future studies aiming to induce DN resilience or model disease.