Single-nucleus and single-cell transcriptomes compared in matched cortical cell types
| Autor: | Jeremy A. Miller, Soraya I. Shehata, Thuc Nghi Nguyen, Matthew Kroll, Nick Dee, Sheana Parry, Rebecca D. Hodge, Kimberly A. Smith, Brian D. Aevermann, Ed Lein, Christine Rimorin, Darren Bertagnolli, Amy Bernard, Michael Tieu, Bosiljka Tasic, Eliza Barkan, Jeff Goldy, Emma Garren, Tamara Casper, Richard H. Scheuermann, Hongkui Zeng, Nicholas J. Schork, Trygve E. Bakken, Roger S. Lasken, Kanan Lathia, John W. Phillips, Lucas T. Graybuck, Zizhen Yao |
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| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: |
0301 basic medicine
Cell genetic processes Gene Expression Biochemistry Transcriptome Database and Informatics Methods Mice Single-cell analysis Animal Cells Gene expression Visual Cortex Neurons Multidisciplinary Mammalian Genomics Messenger RNA Genomics Cell biology Nucleic acids medicine.anatomical_structure Medicine Cellular Types Single-Cell Analysis Transcriptome Analysis Sequence Analysis Research Article Cell type Sequence analysis Bioinformatics Science Biology Research and Analysis Methods Genome Complexity 03 medical and health sciences medicine Genetics Animals natural sciences Cell Lineage Molecular Biology Techniques Molecular Biology Cell Nucleus Sequence Analysis RNA Gene Expression Profiling Intron Biology and Life Sciences Computational Biology Marker Genes Cell Biology Genome Analysis Introns 030104 developmental biology Animal Genomics Cellular Neuroscience RNA Nucleus Sequence Alignment Neuroscience |
| Zdroj: | PLoS ONE PLoS ONE, Vol 13, Iss 12, p e0209648 (2018) |
| ISSN: | 1932-6203 |
| Popis: | Transcriptomic profiling of complex tissues by single-nucleus RNA-sequencing (snRNA-seq) affords some advantages over single-cell RNA-sequencing (scRNA-seq). snRNA-seq provides less biased cellular coverage, does not appear to suffer cell isolation-based transcriptional artifacts, and can be applied to archived frozen specimens. We used well-matched snRNA-seq and scRNA-seq datasets from mouse visual cortex to compare cell type detection. Although more transcripts are detected in individual whole cells (~11,000 genes) than nuclei (~7,000 genes), we demonstrate that closely related neuronal cell types can be similarly discriminated with both methods if intronic sequences are included in snRNA-seq analysis. We estimate that the nuclear proportion of total cellular mRNA varies from 20% to over 50% for large and small pyramidal neurons, respectively. Together, these results illustrate the high information content of nuclear RNA for characterization of cellular diversity in brain tissues. |
| Databáze: | OpenAIRE |
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