Single-nucleus RNA velocity reveals synaptic and cell-cycle dysregulations missed by gene expression in neuropathologic Alzheimer disease
Adewale, Q.; Khan, A. F.; Bennett, D. A.; Iturria-Medina, Y.
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BackgroundTypical differential single-nucleus gene expression (snRNA-seq) analyses in Alzheimers disease (AD) provide fixed snapshots of cellular alterations, making the accurate detection of temporal cell dynamics challenging. MethodsTo characterize the dynamic genetic and cellular differences in AD neuropathology, we apply the novel concept of RNA velocity to the study of single-nucleus RNA from the cortex of 60 subjects with varied levels of AD pathology. RNA velocity captures the rate of change of gene expression by comparing intronic and exonic sequence counts. We performed differential analyses to find the significant genes driving both cell-specific RNA velocity and expression differences in AD, extensively compared these two transcriptomic metrics, and clarified their associations with multiple neuropathologic traits. The results were cross-validated in an independent dataset. ResultsComparison of AD pathology-associated RNA velocity with parallel gene expression differences reveals sets of genes and molecular pathways that underlie the dynamic and static regimes of cell type-specific dysregulations underlying the disease. Differential RNA velocity and its linked progressive neuropathology point to significant dysregulations in synaptic organization and cell development across cell types. In addition, there are accelerated cell changes in AD subjects compared to controls, suggesting that the precocious depletion of precursor cell pools might be associated with neurodegeneration. Finally, we find active molecular drivers of the spatiotemporal alterations in neuropathological AD and discuss implications towards gene- and cell-centric therapeutic strategies. ConclusionsIn sum, our results support that the consideration of other less-studied molecular processes (RNA velocity) offers substantial complementary information to the typical analysis of RNA abundance alone.
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