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 Steinmetz
Affiliations
Mariona Nadal-Ribelles
Department of Genetics, Stanford University, School of Medicine, California, USAStanford Genome Technology Center, Stanford University, California, USA, Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, Barcelona, Spain, Departament de Ciències Experimentals i de la Salut, Cell Signaling Research Group, Universitat Pompeu Fabra (UPF), Barcelona, Spain
Saiful Islam
Department of Genetics, Stanford University, School of Medicine, California, USAStanford Genome Technology Center, Stanford University, California, USA
Wu Wei
Department of Genetics, Stanford University, School of Medicine, California, USAStanford Genome Technology Center, Stanford University, California, USA, 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
Pablo Latorre
Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, Barcelona, SpainDepartament de Ciències Experimentals i de la Salut, Cell Signaling Research Group, Universitat Pompeu Fabra (UPF), Barcelona, Spain
Michelle Nguyen
Department of Genetics and Stanford Genome Center, School of Medicine, California, USAStanford Genome Technology Center, Stanford University, California, USA
Eulàlia de Nadal
Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, Barcelona, SpainDepartament de Ciències Experimentals i de la Salut, Cell Signaling Research Group, Universitat Pompeu Fabra (UPF), Barcelona, Spain
Francesc Posas
Institute for Research in Biomedicine (IRB Barcelona), The Barcelona Institute of Science and Technology, Barcelona, SpainDepartament de Ciències Experimentals i de la Salut, Cell Signaling Research Group, Universitat Pompeu Fabra (UPF), Barcelona, Spain
Lars Steinmetz
Department of Genetics, Stanford University, School of Medicine, California, USAStanford Genome Technology Center, Stanford University, California, USA, European Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany
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.
