Yeast Single-cell RNA-seq, Cell by Cell and Step by Step

Mariona Nadal-Ribelles; Saiful Islam; Wu Wei; Pablo Latorre; Michelle Nguyen; Eulàlia de Nadal; Francesc Posas; Lars M Steinmetz

doi:10.21769/BioProtoc.3359

Yeast Single-cell RNA-seq, Cell by Cell and Step by Step

Bio Protoc. 2019 Sep 5;9(17):e3359. doi: 10.21769/BioProtoc.3359.

Authors

Mariona Nadal-Ribelles^{1

2

3

4}, Saiful Islam^{1

2}, Wu Wei^{1

2

5}, Pablo Latorre^{3

4}, Michelle Nguyen^{1

2}, Eulàlia de Nadal^{3

4}, Francesc Posas^{3

4}, Lars M Steinmetz^{1

2

6}

Affiliations

¹ Department of Genetics, Stanford University, School of Medicine, California, USA.
² Stanford Genome Technology Center, Stanford University, California, USA.
³ Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, Barcelona, Spain.
⁴ Departament de Ciències Experimentals i de la Salut, Cell Signaling Research Group, Universitat Pompeu Fabra (UPF), Barcelona, Spain.
⁵ CAS Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Shanghai Institutes for Biological Sciences, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai, China.
⁶ European Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany.

Abstract

Single-cell RNA-seq (scRNA-seq) has become an established method for uncovering the intrinsic complexity within populations. Even within seemingly homogenous populations of isogenic yeast cells, there is a high degree of heterogeneity that originates from a compact and pervasively transcribed genome. Research with microorganisms such as yeast represents a major challenge for single-cell transcriptomics, due to their small size, rigid cell wall, and low RNA content per cell. Because of these technical challenges, yeast-specific scRNA-seq methodologies have recently started to appear, each one of them relying on different cell-isolation and library-preparation methods. Consequently, each approach harbors unique strengths and weaknesses that need to be considered. We have recently developed a yeast single-cell RNA-seq protocol (yscRNA-seq), which is inexpensive, high-throughput and easy-to-implement, tailored to the unique needs of yeast. yscRNA-seq provides a unique platform that combines single-cell phenotyping via index sorting with the incorporation of unique molecule identifiers on transcripts that allows to digitally count the number of molecules in a strand- and isoform-specific manner. Here, we provide a detailed, step-by-step description of the experimental and computational steps of yscRNA-seq protocol. This protocol will ease the implementation of yscRNA-seq in other laboratories and provide guidelines for the development of novel technologies.

Keywords: Noncoding RNA; Single-cell RNA-seq; Transcript isoforms; Transcriptomics; Yeast.