Extraction of nuclei from archived postmortem tissues for single-nucleus sequencing applications

Malosree Maitra, Corina Nagy, Anjali Chawla, Yu Chang Wang, Camila Nascimento, Matthew Suderman, Jean-François Théroux, Naguib Mechawar, Jiannis Ragoussis, Gustavo Turecki

Published: 2021-05-09 DOI: 10.1038/s41596-021-00514-4

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Single-cell and single-nucleus sequencing techniques are a burgeoning field with various biological, biomedical and clinical applications. Numerous high- and low-throughput methods have been developed for sequencing the RNA and DNA content of single cells
Introduction
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ACKNOWLEDGMENTS

Macosko, E. Z. et al. Highly parallel genome-wide expression profiling of individual cells using nanoliter droplets. Cell 161, 1202–1214 (2015).
Zilionis, R. et al. Single-cell barcoding and sequencing using droplet microfluidics. Nat. Protoc. 12, 44–73 (2017).
Zheng, G. X. Y. et al. Massively parallel digital transcriptional profiling of single cells. Nat. Commun. 8, 14049 (2017).
Haber, A. L. et al. A single-cell survey of the small intestinal epithelium. Nature 551, 333 (2017).
Wang, Y. et al. Pulmonary alveolar type I cell population consists of two distinct subtypes that differ in cell fate. Proc. Natl Acad. Sci. USA 115, 2407–2412 (2018).
Sathyamurthy, A. et al. Massively parallel single nucleus transcriptional profiling defines spinal cord neurons and their activity during behavior. Cell. Rep. 22, 2216–2225 (2018).
Hrvatin, S. et al. Single-cell analysis of experience-dependent transcriptomic states in the mouse visual cortex. Nat. Neurosci. 21, 120–129 (2018).
Hochgerner, H., Zeisel, A., Lönnerberg, P. & Linnarsson, S. Conserved properties of dentate gyrus neurogenesis across postnatal development revealed by single-cell RNA sequencing. Nat. Neurosci. 21, 290–299 (2018).
Lake, B. B. et al. Neuronal subtypes and diversity revealed by single-nucleus RNA sequencing of the human brain. Science 352, 1586–1590 (2016).
Habib, N. et al. Massively parallel single-nucleus RNA-seq with dronc-seq. Nat. Methods 14, 955 (2017).
Lake, B. B. et al. Integrative single-cell analysis of transcriptional and epigenetic states in the human adult brain. Nat. Biotechnol. 36, 70–80 (2018).
Sullivan, P. F., Neale, M. C. & Kendler, K. S. Genetic epidemiology of major depression: review and meta-analysis. Am. J. Psychiatry 157, 1552–1562 (2000).
Lacar, B. et al. Nuclear RNA-seq of single neurons reveals molecular signatures of activation. Nat. Commun. 7, 11022 (2016).
Van den Brink, S. C. et al. Single-cell sequencing reveals dissociation-induced gene expression in tissue subpopulations. Nat. Methods 14, 935 (2017).
Grindberg, R. V. et al. RNA-sequencing from single nuclei. Proc. Natl Acad. Sci. 110, 19802–19807 (2013).
Lake, B. B. et al. A comparative strategy for single-nucleus and single-cell transcriptomes confirms accuracy in predicted cell-type expression from nuclear RNA. Sci. Rep. 7, 6031 (2017).
Cutler, A. A., Jackson, J. B., Corbett, A. H. & Pavlath, G. K. Non-equivalence of nuclear import among nuclei in multinucleated skeletal muscle cells. J. Cell Sci. 131 (2018).
Berridge, B. R., Bolon, B. & Herman, E. Skeletal muscle system. in Fundamentals of Toxicologic Pathology 3rd edn (eds Wallig, M. A. et al.) Ch. 10, 195–212 (Academic Press, 2018).
Mathys, H. et al. Single-cell transcriptomic analysis of Alzheimer’s disease. Nature 570, 332–337 (2019).
Grubman, A. et al. A single-cell atlas of entorhinal cortex from individuals with Alzheimer’s disease reveals cell-type-specific gene expression regulation. Nat. Neurosci. 22, 2087–2097 (2019).
Jäkel, S. et al. Altered human oligodendrocyte heterogeneity in multiple sclerosis. Nature 566, 543–547 (2019).
Velmeshev, D. et al. Single-cell genomics identifies cell type–specific molecular changes in autism. Science 364, 685 (2019).
Krishnaswami, S. R. et al. Using single nuclei for RNA-seq to capture the transcriptome of postmortem neurons. Nat. Protoc. 11, 499–524 (2016).
Nagy, C. et al. Single-nucleus transcriptomics of the prefrontal cortex in major depressive disorder implicates oligodendrocyte precursor cells and excitatory neurons. Nat. Neurosci. 23, 771–781 (2020).
Jessa, S. et al. Stalled developmental programs at the root of pediatric brain tumors. Nat. Genet. 51, 1702–1713 (2019).
Reiner, B. C. et al. Single-nuclei transcriptomics of schizophrenia prefrontal cortex primarily implicates neuronal subtypes. Preprint at bioRxiv http://doi.org/10.1101/2020.07.29.227355 (2020).
Sorrells, S. F. et al. Immature excitatory neurons develop during adolescence in the human amygdala. Nat. Commun. 10, 2748 (2019).
Proudfoot, N. J., Furger, A. & Dye, M. J. Integrating mRNA processing with transcription. Cell 108, 501–512 (2002).
Amamoto, R. et al. Probe-Seq enables transcriptional profiling of specific cell types from heterogeneous tissue by RNA-based isolation. Elife 8, e51452 (2019).
Welch, J. D. et al. Single-cell multi-omic integration compares and contrasts features of brain cell identity. Cell 177, 1873–1887.e1817 (2019).
Skelly, D. A. et al. Single-cell transcriptional profiling reveals cellular diversity and intercommunication in the mouse heart. Cell. Rep. 22, 600–610 (2018).
Cusanovich, D. A. et al. The cis-regulatory dynamics of embryonic development at single-cell resolution. Nature 555, 538–542 (2018).
Thrupp, N. et al. Single-nucleus RNA-seq is not suitable for detection of microglial activation genes in humans. Cell. Rep. 32, 108189 (2020).
Stuart, T. et al. Comprehensive integration of single-cell data. Cell 177, 1888–1902.e1821 (2019).
Benaglia, T., Chauveau, D., Hunter, D. R. & Young, D. S. mixtools: an R package for analyzing mixture models. J. Stat. Softw. http://www.jstatsoft.org/index.php/jss/article/view/v032i06/v32i06.pdf (2009).
R Core Team. R: A language and environment for statistical computing. R Foundation for Statistical Computing (2017).
Yu, W., Uzun, Y., Zhu, Q., Chen, C. & Tan, K. Scatac-pro: a comprehensive workbench for single-cell chromatin accessibility sequencing data. Genome Biol. 21, 94 (2020).
Kriaucionis, S. & Heintz, N. The nuclear DNA base 5-hydroxymethylcytosine is present in Purkinje neurons and the brain. Science 324, 929–930 (2009).
McCarthy, D. J., Campbell, K. R., Lun, A. T. L. & Wills, Q. F. Scater: pre-processing, quality control, normalization and visualization of single-cell RNA-seq data in R. Bioinformatics 33, 1179–1186 (2017).
Kiselev, V. Y. et al. SC3: consensus clustering of single-cell RNA-seq data. Nat. Methods 14, 483–486 (2017).
Cao, J. et al. The single-cell transcriptional landscape of mammalian organogenesis. Nature 566, 496–502 (2019).
Butler, A., Hoffman, P., Smibert, P., Papalexi, E. & Satija, R. Integrating single-cell transcriptomic data across different conditions, technologies, and species. Nat. Biotechnol. 36, 411 (2018).
Darmanis, S. et al. A survey of human brain transcriptome diversity at the single cell level. Proc. Natl Acad. Sci. USA 112, 7285–7290 (2015).
Zhang, Y. et al. Model-based analysis of chip-seq (MACS). Genome Biol. 9, R137 (2008).
Lutz, P. E. et al. Association of a history of child abuse with impaired myelination in the anterior cingulate cortex: convergent epigenetic, transcriptional, and morphological evidence. Am. J. Psychiatry 174, 1185–1194 (2017).

Extraction of nuclei from archived postmortem tissues for single-nucleus sequencing applications

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