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RNA sequencing, or RNA-Seq, is a high-throughput sequencing technology used to study the transcriptome of a cell. Transcriptomics helps to interpret the functional elements of a genome and identify the molecular constituents of an organism. Additionally, it also helps in understanding the development of an organism and the occurrence of diseases. 
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Related Experiment Video

Updated: Dec 31, 2025

Genome-wide Surveillance of Transcription Errors in Eukaryotic Organisms
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Recording transcriptional histories using Record-seq.

Tanmay Tanna1, Florian Schmidt1, Mariia Y Cherepkova1

  • 1Department of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland.

Nature Protocols
|January 12, 2020
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Summary
This summary is machine-generated.

Record-seq technology captures a cell's transcriptional history by recording RNA using CRISPR. This method overcomes limitations of destructive, single-time-point analyses, enabling comprehensive transcriptome studies.

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Area of Science:

  • Molecular Biology
  • Genomics
  • Biotechnology

Background:

  • Current experimental methods for studying cell transcriptional history are destructive, providing only a snapshot in time.
  • Elucidating the dynamic transcriptional changes within a cell over time remains a significant challenge in biological research.

Purpose of the Study:

  • To introduce and detail the Record-seq workflow for non-destructive transcriptional history recording.
  • To describe the SENECA method for recovering and analyzing recorded transcriptomes.
  • To provide a comprehensive guide for experimental design and data analysis using Record-seq.

Main Methods:

  • Record-seq utilizes CRISPR spacer acquisition from RNA to create a permanent record of cellular transcription.
  • The SENECA method selectively amplifies CRISPR arrays containing the recorded transcriptome information.
  • Deep sequencing and alignment of CRISPR spacers to the host genome enable transcript quantification.

Main Results:

  • Record-seq allows for the reconstruction of transcriptional history without cell destruction.
  • The workflow enables accurate transcript quantification and associated downstream analyses.
  • Data acquisition and analysis can be completed within 1-2 weeks, offering a rapid experimental turnaround.

Conclusions:

  • Record-seq provides a powerful new tool for studying cellular transcriptional dynamics over time.
  • This technology overcomes the limitations of existing methods, offering a non-destructive approach to transcriptome analysis.
  • The described workflow facilitates efficient experimental design and data interpretation for researchers.