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

• Published in: Nature protocols Vol. 11; no. 11; p. 2081
• Main Authors: Macaulay, Iain C, Teng, Mabel J, Haerty, Wilfried, Kumar, Parveen, Ponting, Chris P, Voet, Thierry
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group 01.11.2016
• Subjects: Automation; Bioinformatics; Cells; Data analysis; Deoxyribonucleic acid; DNA; Genetic diversity; Genetic variance; Genomes; Genomics; Laboratories; Methods; Protocol; Research parks; United Kingdom > UK
• ISSN: 1754-2189; 1750-2799
• DOI: 10.1038/nprot.2016.138

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.