Literature DB >> 33659534

Single-cell qPCR Assay with Massively Parallel Microfluidic System.

Marta Prieto-Vila1,2, Takahiro Ochiya1,2, Yusuke Yamamoto2.   

Abstract

The single-cell transcriptome is the set of messenger RNA molecules expressed in one cell. It is extremely variable and changes according to external, physical and biochemical conditions. Due to sensitivity shortages, most of genetic studies use bulk samples, providing only the average gene expression. Single-cell technologies have provided a powerful approach to a more detailed understanding of the heterogenic populations and minority cells. However, since it is still a quite novel technique, standardized protocol has to be established. Single-cell qPCR, although partly limited by the number of genes, is relatively simple to analyze. Therefore, its use is accessible without the necessity to recourse to complex bioinformatics analyses. The main steps for single-cell qPCR, as illustrated in this protocol, are composed by single-cell isolation, cell lysate, cDNA reverse-transcription synthesis, amplification for cDNA library generation, and finally, quantitative polymerase chain reaction.
Copyright © 2020 The Authors; exclusive licensee Bio-protocol LLC.

Entities:  

Keywords:  Cell heterogeneity; Microfluidic system; Single-cell; Single-cell qPCR; Transcriptomics; mRNA

Year:  2020        PMID: 33659534      PMCID: PMC7842821          DOI: 10.21769/BioProtoc.3563

Source DB:  PubMed          Journal:  Bio Protoc        ISSN: 2331-8325


  10 in total

1.  Comparative Analysis of Single-Cell RNA Sequencing Methods.

Authors:  Christoph Ziegenhain; Beate Vieth; Swati Parekh; Björn Reinius; Amy Guillaumet-Adkins; Martha Smets; Heinrich Leonhardt; Holger Heyn; Ines Hellmann; Wolfgang Enard
Journal:  Mol Cell       Date:  2017-02-16       Impact factor: 17.970

2.  Landscape of Infiltrating T Cells in Liver Cancer Revealed by Single-Cell Sequencing.

Authors:  Chunhong Zheng; Liangtao Zheng; Jae-Kwang Yoo; Huahu Guo; Yuanyuan Zhang; Xinyi Guo; Boxi Kang; Ruozhen Hu; Julie Y Huang; Qiming Zhang; Zhouzerui Liu; Minghui Dong; Xueda Hu; Wenjun Ouyang; Jirun Peng; Zemin Zhang
Journal:  Cell       Date:  2017-06-15       Impact factor: 41.582

3.  Single-cell sequencing reveals dissociation-induced gene expression in tissue subpopulations.

Authors:  Susanne C van den Brink; Fanny Sage; Ábel Vértesy; Bastiaan Spanjaard; Josi Peterson-Maduro; Chloé S Baron; Catherine Robin; Alexander van Oudenaarden
Journal:  Nat Methods       Date:  2017-09-29       Impact factor: 28.547

Review 4.  The trajectory of microbial single-cell sequencing.

Authors:  Tanja Woyke; Devin F R Doud; Frederik Schulz
Journal:  Nat Methods       Date:  2017-10-31       Impact factor: 28.547

5.  The Drosophila embryo at single-cell transcriptome resolution.

Authors:  Nikos Karaiskos; Philipp Wahle; Jonathan Alles; Anastasiya Boltengagen; Salah Ayoub; Claudia Kipar; Christine Kocks; Nikolaus Rajewsky; Robert P Zinzen
Journal:  Science       Date:  2017-08-31       Impact factor: 47.728

6.  Single-Cell Analysis Reveals a Preexisting Drug-Resistant Subpopulation in the Luminal Breast Cancer Subtype.

Authors:  Marta Prieto-Vila; Wataru Usuba; Ryou-U Takahashi; Iwao Shimomura; Hideo Sasaki; Takahiro Ochiya; Yusuke Yamamoto
Journal:  Cancer Res       Date:  2019-07-09       Impact factor: 12.701

Review 7.  Exploring viral infection using single-cell sequencing.

Authors:  Sylvie Rato; Monica Golumbeanu; Amalio Telenti; Angela Ciuffi
Journal:  Virus Res       Date:  2016-11-02       Impact factor: 3.303

Review 8.  Single-cell sequencing in stem cell biology.

Authors:  Lu Wen; Fuchou Tang
Journal:  Genome Biol       Date:  2016-04-15       Impact factor: 13.583

9.  Methods for qPCR gene expression profiling applied to 1440 lymphoblastoid single cells.

Authors:  Kenneth J Livak; Quin F Wills; Alex J Tipping; Krishnalekha Datta; Rowena Mittal; Andrew J Goldson; Darren W Sexton; Chris C Holmes
Journal:  Methods       Date:  2012-10-16       Impact factor: 3.608

10.  Transcriptomic Dissection of Hepatocyte Heterogeneity: Linking Ploidy, Zonation, and Stem/Progenitor Cell Characteristics.

Authors:  Takeshi Katsuda; Kazunori Hosaka; Juntaro Matsuzaki; Wataru Usuba; Marta Prieto-Vila; Tomoko Yamaguchi; Atsunori Tsuchiya; Shuji Terai; Takahiro Ochiya
Journal:  Cell Mol Gastroenterol Hepatol       Date:  2019-09-05
  10 in total

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