Literature DB >> 34766276

Combined Measurement of RNA and Protein Expression on a Single-Cell Level.

Valentina Russo1,2, Nadia Brasu1,2, Luigia Pace3,4.   

Abstract

Single-cell RNA sequencing (sc-RNAseq) has become a critical approach for the analysis of immune cell function and heterogeneity. So far, the immune cell isolation, based on surface marker expression predicted by the RNA expression profiles, is often limited by the poor correlation between transcript and protein expression patterns. To overcome these difficulties, novel single-cell multi-omic approaches based on the combined analysis of transcript and surface protein expression have been developed. One of the major benefits of these technologies is the possibility to use a high number of antibodies conjugated with oligonucleotide (AbOs) for the surface marker detection, thus overcoming the limit of using few surface markers as occurs in flow cytometry. Here we describe the BD Rhapsody single-cell analysis system protocol for 3' mRNA whole transcriptome analysis (WTA), combined with AbO- and Sample Tag library preparation.
© 2022. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.

Entities:  

Keywords:  AbOligos; AbSeq; BD Rhapsody; Cartridge; Sample Tag; Single-cell; Single-cell capture beads; WTA; Whole transcriptomics; scRNA-seq

Mesh:

Substances:

Year:  2022        PMID: 34766276     DOI: 10.1007/978-1-0716-1771-7_16

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


  9 in total

1.  Full-length RNA-seq from single cells using Smart-seq2.

Authors:  Simone Picelli; Omid R Faridani; Asa K Björklund; Gösta Winberg; Sven Sagasser; Rickard Sandberg
Journal:  Nat Protoc       Date:  2014-01-02       Impact factor: 13.491

2.  Expression profiling. Combinatorial labeling of single cells for gene expression cytometry.

Authors:  H Christina Fan; Glenn K Fu; Stephen P A Fodor
Journal:  Science       Date:  2015-02-06       Impact factor: 47.728

3.  Multiplexed quantification of proteins and transcripts in single cells.

Authors:  Vanessa M Peterson; Kelvin Xi Zhang; Namit Kumar; Jerelyn Wong; Lixia Li; Douglas C Wilson; Renee Moore; Terrill K McClanahan; Svetlana Sadekova; Joel A Klappenbach
Journal:  Nat Biotechnol       Date:  2017-08-30       Impact factor: 54.908

Review 4.  Mapping human cell phenotypes to genotypes with single-cell genomics.

Authors:  J Gray Camp; Randall Platt; Barbara Treutlein
Journal:  Science       Date:  2019-09-27       Impact factor: 47.728

5.  Single-cell RNA counting at allele and isoform resolution using Smart-seq3.

Authors:  Michael Hagemann-Jensen; Christoph Ziegenhain; Ping Chen; Daniel Ramsköld; Gert-Jan Hendriks; Anton J M Larsson; Omid R Faridani; Rickard Sandberg
Journal:  Nat Biotechnol       Date:  2020-05-04       Impact factor: 54.908

6.  Who cares about care in nursing education?

Authors:  J Stevens; M Crouch
Journal:  Int J Nurs Stud       Date:  1995-06       Impact factor: 5.837

7.  Simultaneous epitope and transcriptome measurement in single cells.

Authors:  Marlon Stoeckius; Christoph Hafemeister; William Stephenson; Brian Houck-Loomis; Pratip K Chattopadhyay; Harold Swerdlow; Rahul Satija; Peter Smibert
Journal:  Nat Methods       Date:  2017-07-31       Impact factor: 28.547

Review 8.  A Single-Cell Sequencing Guide for Immunologists.

Authors:  Peter See; Josephine Lum; Jinmiao Chen; Florent Ginhoux
Journal:  Front Immunol       Date:  2018-10-23       Impact factor: 7.561

9.  A Targeted Multi-omic Analysis Approach Measures Protein Expression and Low-Abundance Transcripts on the Single-Cell Level.

Authors:  Florian Mair; Jami R Erickson; Valentin Voillet; Yannick Simoni; Timothy Bi; Aaron J Tyznik; Jody Martin; Raphael Gottardo; Evan W Newell; Martin Prlic
Journal:  Cell Rep       Date:  2020-04-07       Impact factor: 9.423

  9 in total

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