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Asset Tag: Single-cell RNA-Seq

April 21, 2020  |  

Combined Genome and Transcriptome (G&T) Sequencing of Single Cells.

The simultaneous examination of a single cell’s genome and transcriptome presents scientists with a powerful tool to study genetic variability and its effect on gene expression. In this chapter, we describe the library generation method for combined genome and transcriptome sequencing (G&T-seq) originally described by Macaulay et al. (Nat Protoc 11(11):2081-2103, 2016; Nat Methods 12(6):519-522, 2015). This includes some alterations we made to improve robustness of this process for both the novice user and laboratories that want to deploy this method at scale. Using this method, genomic DNA and full-length mRNA from single cells are separated, amplified, and converted into Illumina sequencer-compatible sequencing libraries.

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April 21, 2020  |  

The tech for the next decade: promises and challenges in genome biology.

The 19th Annual Advances in Genome Biology and Technology (AGBT) meeting came back to Marco Island, Florida, and was held in the renovated venue from 27 February to 2 March 2019. The meeting showed a variety of new technology, both in wet lab and in bioinformatics. This year’s themes included single-cell technology and applications, spatially resolved gene expression measurements, new sequencing platforms, genome assembly and variation, and long and linked reads.

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September 22, 2019  |  

Separation and parallel sequencing of the genomes and transcriptomes of single cells using G&T-seq.

Parallel sequencing of a single cell’s genome and transcriptome provides a powerful tool for dissecting genetic variation and its relationship with gene expression. Here we present a detailed protocol for G&T-seq, a method for separation and parallel sequencing of genomic DNA and full-length polyA(+) mRNA from single cells. We provide step-by-step instructions for the isolation and lysis of single cells; the physical separation of polyA(+) mRNA from genomic DNA using a modified oligo-dT bead capture and the respective whole-transcriptome and whole-genome amplifications; and library preparation and sequence analyses of these amplification products. The method allows the detection of thousands of transcripts in parallel with the genetic variants captured by the DNA-seq data from the same single cell. G&T-seq differs from other currently available methods for parallel DNA and RNA sequencing from single cells, as it involves physical separation of the DNA and RNA and does not require bespoke microfluidics platforms. The process can be implemented manually or through automation. When performed manually, paired genome and transcriptome sequencing libraries from eight single cells can be produced in ~3 d by researchers experienced in molecular laboratory work. For users with experience in the programming and operation of liquid-handling robots, paired DNA and RNA libraries from 96 single cells can be produced in the same time frame. Sequence analysis and integration of single-cell G&T-seq DNA and RNA data requires a high level of bioinformatics expertise and familiarity with a wide range of informatics tools.

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September 22, 2019  |  

G&T-seq: parallel sequencing of single-cell genomes and transcriptomes.

The simultaneous sequencing of a single cell’s genome and transcriptome offers a powerful means to dissect genetic variation and its effect on gene expression. Here we describe G&T-seq, a method for separating and sequencing genomic DNA and full-length mRNA from single cells. By applying G&T-seq to over 220 single cells from mice and humans, we discovered cellular properties that could not be inferred from DNA or RNA sequencing alone.

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September 22, 2019  |  

Defining cell identity with single cell omics.

Cells are a fundamental unit of life, and the ability to study the phenotypes and behaviors of individual cells is crucial to understanding the workings of complex biological systems. Cell phenotypes (epigenomic, transcriptomic, proteomic, and metabolomic) exhibit dramatic heterogeneity between and within the different cell types and states underlying cellular functional diversity. Cell genotypes can also display heterogeneity throughout an organism, in the form of somatic genetic variation-most notably in the emergence and evolution of tumors. Recent technical advances in single-cell isolation and the development of omics approaches sensitive enough to reveal these aspects of cell identity have enabled a revolution in the study of multicellular systems. In this review, we discuss the technologies available to resolve the genomes, epigenomes, transcriptomes, proteomes, and metabolomes of single cells from a wide variety of living systems.© 2018 The Authors. Proteomics Published by WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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September 22, 2019  |  

Single-cell mRNA isoform diversity in the mouse brain.

Alternative mRNA isoform usage is an important source of protein diversity in mammalian cells. This phenomenon has been extensively studied in bulk tissues, however, it remains unclear how this diversity is reflected in single cells.Here we use long-read sequencing technology combined with unique molecular identifiers (UMIs) to reveal patterns of alternative full-length isoform expression in single cells from the mouse brain. We found a surprising amount of isoform diversity, even after applying a conservative definition of what constitutes an isoform. Genes tend to have one or a few isoforms highly expressed and a larger number of isoforms expressed at a low level. However, for many genes, nearly every sequenced mRNA molecule was unique, and many events affected coding regions suggesting previously unknown protein diversity in single cells. Exon junctions in coding regions were less prone to splicing errors than those in non-coding regions, indicating purifying selection on splice donor and acceptor efficiency.Our findings indicate that mRNA isoform diversity is an important source of biological variability also in single cells.

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September 22, 2019  |  

Single-cell isoform RNA sequencing characterizes isoforms in thousands of cerebellar cells.

Full-length RNA sequencing (RNA-Seq) has been applied to bulk tissue, cell lines and sorted cells to characterize transcriptomes, but applying this technology to single cells has proven to be difficult, with less than ten single-cell transcriptomes having been analyzed thus far. Although single splicing events have been described for =200 single cells with statistical confidence, full-length mRNA analyses for hundreds of cells have not been reported. Single-cell short-read 3′ sequencing enables the identification of cellular subtypes, but full-length mRNA isoforms for these cell types cannot be profiled. We developed a method that starts with bulk tissue and identifies single-cell types and their full-length RNA isoforms without fluorescence-activated cell sorting. Using single-cell isoform RNA-Seq (ScISOr-Seq), we identified RNA isoforms in neurons, astrocytes, microglia, and cell subtypes such as Purkinje and Granule cells, and cell-type-specific combination patterns of distant splice sites. We used ScISOr-Seq to improve genome annotation in mouse Gencode version 10 by determining the cell-type-specific expression of 18,173 known and 16,872 novel isoforms.

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September 22, 2019  |  

Single-cell multiomics: multiple measurements from single cells.

Single-cell sequencing provides information that is not confounded by genotypic or phenotypic heterogeneity of bulk samples. Sequencing of one molecular type (RNA, methylated DNA or open chromatin) in a single cell, furthermore, provides insights into the cell’s phenotype and links to its genotype. Nevertheless, only by taking measurements of these phenotypes and genotypes from the same single cells can such inferences be made unambiguously. In this review, we survey the first experimental approaches that assay, in parallel, multiple molecular types from the same single cell, before considering the challenges and opportunities afforded by these and future technologies. Copyright © 2016. Published by Elsevier Ltd.

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September 22, 2019  |  

Single-cell RNAseq for the study of isoforms-how is that possible?

Single-cell RNAseq and alternative splicing studies have recently become two of the most prominent applications of RNAseq. However, the combination of both is still challenging, and few research efforts have been dedicated to the intersection between them. Cell-level insight on isoform expression is required to fully understand the biology of alternative splicing, but it is still an open question to what extent isoform expression analysis at the single-cell level is actually feasible. Here, we establish a set of four conditions that are required for a successful single-cell-level isoform study and evaluate how these conditions are met by these technologies in published research.

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