| Literature DB >> 33654857 |
Mariona Nadal-Ribelles1,2,3,4, Saiful Islam1,2, Wu Wei1,2,5, Pablo Latorre3,4, Michelle Nguyen1,2, Eulàlia de Nadal3,4, Francesc Posas3,4, Lars M Steinmetz1,2,6.
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.Entities:
Keywords: Noncoding RNA; Single-cell RNA-seq; Transcript isoforms; Transcriptomics; Yeast
Year: 2019 PMID: 33654857 PMCID: PMC7854150 DOI: 10.21769/BioProtoc.3359
Source DB: PubMed Journal: Bio Protoc ISSN: 2331-8325