Literature DB >> 26890679

Using single nuclei for RNA-seq to capture the transcriptome of postmortem neurons.

Suguna Rani Krishnaswami1, Rashel V Grindberg2, Mark Novotny1, Pratap Venepally3, Benjamin Lacar4, Kunal Bhutani1, Sara B Linker4, Son Pham4, Jennifer A Erwin4, Jeremy A Miller5, Rebecca Hodge5, James K McCarthy1, Martin Kelder4, Jamison McCorrison1, Brian D Aevermann1, Francisco Diez Fuertes1,6, Richard H Scheuermann1, Jun Lee7, Ed S Lein5, Nicholas Schork1, Michael J McConnell8, Fred H Gage4, Roger S Lasken1.   

Abstract

A protocol is described for sequencing the transcriptome of a cell nucleus. Nuclei are isolated from specimens and sorted by FACS, cDNA libraries are constructed and RNA-seq is performed, followed by data analysis. Some steps follow published methods (Smart-seq2 for cDNA synthesis and Nextera XT barcoded library preparation) and are not described in detail here. Previous single-cell approaches for RNA-seq from tissues include cell dissociation using protease treatment at 30 °C, which is known to alter the transcriptome. We isolate nuclei at 4 °C from tissue homogenates, which cause minimal damage. Nuclear transcriptomes can be obtained from postmortem human brain tissue stored at -80 °C, making brain archives accessible for RNA-seq from individual neurons. The method also allows investigation of biological features unique to nuclei, such as enrichment of certain transcripts and precursors of some noncoding RNAs. By following this procedure, it takes about 4 d to construct cDNA libraries that are ready for sequencing.

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Year:  2016        PMID: 26890679      PMCID: PMC4941947          DOI: 10.1038/nprot.2016.015

Source DB:  PubMed          Journal:  Nat Protoc        ISSN: 1750-2799            Impact factor:   13.491


  36 in total

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Journal:  Science       Date:  2005-03-24       Impact factor: 47.728

2.  Synthetic spike-in standards for RNA-seq experiments.

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3.  Unbiased classification of sensory neuron types by large-scale single-cell RNA sequencing.

Authors:  Dmitry Usoskin; Alessandro Furlan; Saiful Islam; Hind Abdo; Peter Lönnerberg; Daohua Lou; Jens Hjerling-Leffler; Jesper Haeggström; Olga Kharchenko; Peter V Kharchenko; Sten Linnarsson; Patrik Ernfors
Journal:  Nat Neurosci       Date:  2014-11-24       Impact factor: 24.884

4.  CEL-Seq: single-cell RNA-Seq by multiplexed linear amplification.

Authors:  Tamar Hashimshony; Florian Wagner; Noa Sher; Itai Yanai
Journal:  Cell Rep       Date:  2012-08-30       Impact factor: 9.423

5.  STAR: ultrafast universal RNA-seq aligner.

Authors:  Alexander Dobin; Carrie A Davis; Felix Schlesinger; Jorg Drenkow; Chris Zaleski; Sonali Jha; Philippe Batut; Mark Chaisson; Thomas R Gingeras
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6.  RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome.

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Authors:  Michal Rabani; Raktima Raychowdhury; Marko Jovanovic; Michael Rooney; Deborah J Stumpo; Andrea Pauli; Nir Hacohen; Alexander F Schier; Perry J Blackshear; Nir Friedman; Ido Amit; Aviv Regev
Journal:  Cell       Date:  2014-12-11       Impact factor: 41.582

8.  A method for isolating intact mitochondria and nuclei from the same homogenate, and the influence of mitochondrial destruction on the properties of cell nuclei.

Authors:  A L DOUNCE; R F WITTER; K J MONTY; S PATE; M A COTTONE
Journal:  J Biophys Biochem Cytol       Date:  1955-03

9.  Trimmomatic: a flexible trimmer for Illumina sequence data.

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10.  Nuclear RNA-seq of single neurons reveals molecular signatures of activation.

Authors:  Benjamin Lacar; Sara B Linker; Baptiste N Jaeger; Suguna R Krishnaswami; Jerika J Barron; Martijn J E Kelder; Sarah L Parylak; Apuã C M Paquola; Pratap Venepally; Mark Novotny; Carolyn O'Connor; Conor Fitzpatrick; Jennifer A Erwin; Jonathan Y Hsu; David Husband; Michael J McConnell; Roger Lasken; Fred H Gage
Journal:  Nat Commun       Date:  2016-04-19       Impact factor: 14.919

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  142 in total

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3.  In Vivo Chimeric Alzheimer's Disease Modeling of Apolipoprotein E4 Toxicity in Human Neurons.

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6.  Isolation of Adult Spinal Cord Nuclei for Massively Parallel Single-nucleus RNA Sequencing.

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7.  The State of the NIH BRAIN Initiative.

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Review 8.  Single-Cell RNA Sequencing: Unraveling the Brain One Cell at a Time.

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Review 9.  Design and application of single-cell RNA sequencing to study kidney immune cells in lupus nephritis.

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10.  Single sample sequencing (S3EQ) of epigenome and transcriptome in nucleus accumbens.

Authors:  S J Xu; E A Heller
Journal:  J Neurosci Methods       Date:  2018-07-18       Impact factor: 2.390

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