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Cannon, G. H.

Publications and source records attributed to Cannon, G. H..

2 recordsLinked to original sources

Variation in neuronal activity state, axonal projection target, and position principally define the transcriptional identity of individual neocortical projection neurons.

Single-cell RNA sequencing technologies have generated the first catalogs of transcriptionally defined neuronal subtypes of the brain. However, the biologically informative cellular processes that contribute to neuronal subtype specification and transcriptional heterogeneity remain unclear. By comparing the gene expression profiles of single layer 6 corticothalamic neurons in somatosensory cortex, we show that transcriptional subtypes primarily reflect axonal projection pattern, laminar position within the cortex, and neuronal activity state. Pseudotemporal ordering of 1023 cellular responses to manipulation of sensory input demonstrates that changes in expression of activity-induced genes both reinforced cell-type identity and contributed to increased transcriptional heterogeneity within each cell type. This is due to cell-type specific biases in the choice of transcriptional states following manipulation of neuronal activity. These results reveal that axonal projection pattern, laminar position, and activity state define significant axes of variation that contribute both to the transcriptional identity of individual neurons and to the transcriptional heterogeneity within each neuronal subtype.

neuroscience

Temporal and spatial variation among single dopaminergic neuron transcriptomes informs cellular phenotype diversity and Parkinson’s Disease gene prioritization

Parkinsons disease (PD) is caused by the collapse of substantia nigra (SN) dopaminergic (DA) neurons of the midbrain (MB), while other DA populations remain relatively intact. Common variation influencing susceptibility to sporadic PD has been primarily identified through genome wide association studies (GWAS). However, like many other common genetic diseases, the genes impacted by common PD-associated variation remain to be elucidated. Here, we used single-cell RNA-seq to characterize DA neuron populations in the mouse brain at embryonic and early postnatal timepoints. These data allow for the unbiased identification of DA neuron subpopulations, including a novel postnatal neuroblast population and SN DA neurons. Comparison of SN DA neurons with other DA neurons populations in the brain reveals a unique transcriptional profile, novel marker genes, and specific gene regulatory networks. By integrating these cell population specific data with published GWAS, we develop a scoring system for prioritizing candidate genes in PD-associated loci. With this, we prioritize candidate genes in all 32 GWAS intervals implicated in sporadic PD risk, the first such systematically generated list. From this we confirm that the prioritized candidate gene CPLX1 disrupts the nigrostriatal pathway when knocked out in mice. Ultimately, this systematic rationale leads to the identification of biologically pertinent candidates and testable hypotheses for sporadic PD that will inform a new era of PD genetic research.

genetics