Recording transcriptional histories using Record-seq

• Published in: Nature protocols Vol. 15; no. 2; pp. 513 - 539
• Main Authors: Tanna, Tanmay, Schmidt, Florian, Cherepkova, Mariia Y., Okoniewski, Michal, Platt, Randall J.
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 01.02.2020; Nature Publishing Group
• Subjects: 631/1647/2017; 631/1647/48; 631/1647/514/1949; 631/337/2019; 631/337/4041/3196; Amplification; Analytical Chemistry; Arrays; Biological Techniques; Biomedical and Life Sciences; Clustered Regularly Interspaced Short Palindromic Repeats - genetics; Computational Biology/Bioinformatics; CRISPR; Data analysis; Design of experiments; Escherichia coli - genetics; Experimental design; Gene sequencing; Genetic transcription; Genomes; History; Life Sciences; Microarrays; Organic Chemistry; Protocol; Recording; Ribonucleic acid; RNA; Sequence Analysis, DNA - methods; Technology application; Transcription; Transcription, Genetic; Workflow; Switzerland
• ISSN: 1754-2189; 1750-2799
• DOI: 10.1038/s41596-019-0253-4

It is difficult to elucidate the transcriptional history of a cell using current experimental approaches, as they are destructive in nature and therefore describe only a moment in time. To overcome these limitations, we recently established Record-seq, a technology that enables transcriptional recording by CRISPR spacer acquisition from RNA. The recorded transcriptomes are recovered by SENECA, a method that selectively amplifies expanded CRISPR arrays, followed by deep sequencing. The resulting CRISPR spacers are aligned to the host genome, thereby enabling transcript quantification and associated analyses. Here, we describe the experimental procedures of the Record-seq workflow as well as subsequent data analysis. Beginning with the experimental design, Record-seq data can be obtained and analyzed within 1–2 weeks. Record-seq is a technology that enables transcriptional recording by CRISPR spacer acquisition from RNA. Transcriptomes are recovered using SENECA, a method that selectively amplifies expanded CRISPR arrays, followed by deep sequencing.