Abstract
Single-cell and single-nucleus RNA sequencing (sc/snRNA-seq) technologies have enhanced the understanding of the molecular pathogenesis of neurodegenerative disorders, including Parkinson’s disease (PD). Nonetheless, their application in PD has been limited due mainly to the technical challenges resulting from the scarcity of postmortem brain tissue and low quality associated with RNA degradation. Despite such challenges, recent advances in animals and human in vitro models that recapitulate features of PD along with sequencing assays have fueled studies aiming to obtain an unbiased and global view of cellular composition and phenotype of PD at the single-cell resolution. Here, we reviewed recent sc/snRNA-seq efforts that have successfully characterized diverse cell-type populations and identified cell type-specific disease associations in PD. We also examined how these studies have employed computational and analytical tools to analyze and interpret the rich information derived from sc/snRNA-seq. Finally, we highlighted important limitations and emerging technologies for addressing key technical challenges currently limiting the integration of new findings into clinical practice.
Highlights
Parkinson’s disease (PD) is the second most common neurodegenerative disorder and affects over 1% of the population over the age of 60 [1]
PD is characterized by a loss of dopaminergic neurons (DaNs) in the substantia nigra pars compacta (SNpc), resulting in motor symptoms such as rigidity, postural instability, tremor at rest, and bradykinesia [4]
Rapid progress in the development of sc/snRNA-seq technologies along with analytical tools has greatly advanced the understanding of the molecular identity of neuronal and glial cell types in studies of PD
Summary
Parkinson’s disease (PD) is the second most common neurodegenerative disorder and affects over 1% of the population over the age of 60 [1]. $51.9 billion, including direct medical costs and indirect and non-medical costs, such as loss in wages and social productivity; the total economic burden is expected to increase to about. Single-cell and single-nucleus RNA sequencing (sc/snRNA-seq) technologies have become instrumental for assessing heterogeneous cell types and for reconstructing temporal and spatial dynamics of complex tissues [7,8,9]. With the advent of DNA barcode and combinatorial indexing strategy, up to millions of cells or nuclei can be sequenced from a single experiment, enabling ultra-high throughput sc/snRNA-seq of samples across different tissues and in the context of a wide range of diseases. While past efforts in deconvoluting the complex nature of neural circuits have been largely ineffective with bulk assays of the average composition of a brain tissue, single-cell sequencing technologies have the advantage of characterizing the cellular heterogeneity that governs the key aspect of neurobiology.
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