Literature DB >> 35524108

Single-Cell RNA Sequencing in Yeast Using the 10× Genomics Chromium Device.

Lieselotte Vermeersch1,2, Abbas Jariani1,2, Jana Helsen1,2,3, Benjamin M Heineike4,5,6, Kevin J Verstrepen7,8.   

Abstract

Single-cell RNA sequencing (scRNA-seq) is emerging as an essential technique for studying the physiology of individual cells in populations. Although well-established and optimized for mammalian cells, research of microorganisms has been faced with major technical challenges for using scRNA-seq, because of their rigid cell wall, smaller cell size and overall lower total RNA content per cell. Here, we describe an easy-to-implement adaptation of the protocol for the yeast Saccharomyces cerevisiae using the 10× Genomics platform, originally optimized for mammalian cells. Introducing Zymolyase, a cell wall-digesting enzyme, to one of the initial steps of single-cell droplet formation allows efficient in-droplet lysis of yeast cells, without affecting the droplet emulsion and further sample processing. In addition, we also describe the downstream data analysis, which combines established scRNA-seq analysis protocols with specific adaptations for yeast, and R-scripts for further secondary analysis of the data.
© 2022. The Author(s).

Entities:  

Keywords:  10× Genomics; Saccharomyces cerevisiae; Single-cell RNA sequencing; Single-cell omics; Transcriptomics; Yeast

Mesh:

Substances:

Year:  2022        PMID: 35524108     DOI: 10.1007/978-1-0716-2257-5_1

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


  15 in total

1.  Quantitative single-cell RNA-seq with unique molecular identifiers.

Authors:  Saiful Islam; Amit Zeisel; Simon Joost; Gioele La Manno; Pawel Zajac; Maria Kasper; Peter Lönnerberg; Sten Linnarsson
Journal:  Nat Methods       Date:  2013-12-22       Impact factor: 28.547

2.  Gene regulatory network reconstruction using single-cell RNA sequencing of barcoded genotypes in diverse environments.

Authors:  Christopher A Jackson; Dayanne M Castro; Richard Bonneau; David Gresham; Giuseppe-Antonio Saldi
Journal:  Elife       Date:  2020-01-27       Impact factor: 8.140

3.  Highly Parallel Genome-wide Expression Profiling of Individual Cells Using Nanoliter Droplets.

Authors:  Evan Z Macosko; Anindita Basu; Rahul Satija; James Nemesh; Karthik Shekhar; Melissa Goldman; Itay Tirosh; Allison R Bialas; Nolan Kamitaki; Emily M Martersteck; John J Trombetta; David A Weitz; Joshua R Sanes; Alex K Shalek; Aviv Regev; Steven A McCarroll
Journal:  Cell       Date:  2015-05-21       Impact factor: 41.582

4.  Evaluating measures of association for single-cell transcriptomics.

Authors:  Michael A Skinnider; Jordan W Squair; Leonard J Foster
Journal:  Nat Methods       Date:  2019-04-08       Impact factor: 28.547

5.  Single-cell RNA-sequencing reports growth-condition-specific global transcriptomes of individual bacteria.

Authors:  Fabian Imdahl; Ehsan Vafadarnejad; Christina Homberger; Antoine-Emmanuel Saliba; Jörg Vogel
Journal:  Nat Microbiol       Date:  2020-08-17       Impact factor: 17.745

6.  Comprehensive single-cell transcriptional profiling of a multicellular organism.

Authors:  Junyue Cao; Jonathan S Packer; Vijay Ramani; Darren A Cusanovich; Chau Huynh; Riza Daza; Xiaojie Qiu; Choli Lee; Scott N Furlan; Frank J Steemers; Andrew Adey; Robert H Waterston; Cole Trapnell; Jay Shendure
Journal:  Science       Date:  2017-08-18       Impact factor: 47.728

7.  Single-cell imaging and RNA sequencing reveal patterns of gene expression heterogeneity during fission yeast growth and adaptation.

Authors:  Malika Saint; François Bertaux; Wenhao Tang; Xi-Ming Sun; Laurence Game; Anna Köferle; Jürg Bähler; Vahid Shahrezaei; Samuel Marguerat
Journal:  Nat Microbiol       Date:  2019-02-04       Impact factor: 17.745

8.  Sensitive high-throughput single-cell RNA-seq reveals within-clonal transcript correlations in yeast populations.

Authors:  Mariona Nadal-Ribelles; Saiful Islam; Wu Wei; Pablo Latorre; Michelle Nguyen; Eulàlia de Nadal; Francesc Posas; Lars M Steinmetz
Journal:  Nat Microbiol       Date:  2019-02-04       Impact factor: 17.745

9.  High-Throughput Single-Cell Sequencing with Linear Amplification.

Authors:  Yi Yin; Yue Jiang; Kwan-Wood Gabriel Lam; Joel B Berletch; Christine M Disteche; William S Noble; Frank J Steemers; R Daniel Camerini-Otero; Andrew C Adey; Jay Shendure
Journal:  Mol Cell       Date:  2019-09-05       Impact factor: 17.970

10.  Single-cell RNA sequencing reveals intrinsic and extrinsic regulatory heterogeneity in yeast responding to stress.

Authors:  Audrey P Gasch; Feiqiao Brian Yu; James Hose; Leah E Escalante; Mike Place; Rhonda Bacher; Jad Kanbar; Doina Ciobanu; Laura Sandor; Igor V Grigoriev; Christina Kendziorski; Stephen R Quake; Megan N McClean
Journal:  PLoS Biol       Date:  2017-12-14       Impact factor: 8.029

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.