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Biology and Bias in Cell Type-Specific RNAseq of Nucleus Accumbens Medium Spiny Neurons
Subcellular RNAseq promises to dissect transcriptional dynamics but is not well characterized. Furthermore, FACS may introduce bias but has not been benchmarked genome-wide. Finally, D1 and D2 dopamine receptor-expressing medium spiny neurons (MSNs) of the nucleus accumbens (NAc) are fundamental to...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6554355/ https://www.ncbi.nlm.nih.gov/pubmed/31171808 http://dx.doi.org/10.1038/s41598-019-44798-9 |
Sumario: | Subcellular RNAseq promises to dissect transcriptional dynamics but is not well characterized. Furthermore, FACS may introduce bias but has not been benchmarked genome-wide. Finally, D1 and D2 dopamine receptor-expressing medium spiny neurons (MSNs) of the nucleus accumbens (NAc) are fundamental to neuropsychiatric traits but have only a short list of canonical surface markers. We address these gaps by systematically comparing nuclear-FACS, whole cell-FACS, and RiboTag affinity purification from D1- and D2-MSNs. Using differential expression, variance partitioning, and co-expression, we identify the following trade-offs for each method. RiboTag-seq best distinguishes D1- and D2-MSNs but has the lowest transcriptome coverage. Nuclear-FACS-seq generates the most differentially expressed genes and overlaps significantly with neuropsychiatric genetic risk loci, but un-annotated genes hamper interpretation. Whole cell-FACS is more similar to nuclear-FACS than RiboTag, but captures aspects of both. Using pan-method approaches, we discover that transcriptional regulation is predominant in D1-MSNs, while D2-MSNs tend towards cytosolic regulation. We are also the first to find evidence for moderate sexual dimorphism in these cell types at baseline. As these results are from 49 mice (n(male) = 39, n(female) = 10), they represent generalizable ground-truths. Together, these results guide RNAseq methods selection, define MSN transcriptomes, highlight neuronal sex differences, and provide a baseline for D1- and D2-MSNs. |
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