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Temporally resolved transcriptional recording in E. coli DNA using a Retro-Cascorder


Biological signals occur over time in living cells. Yet most current approaches to interrogate biology, particularly gene expression, use destructive techniques that quantify signals only at a single point in time. A recent technological advance, termed the Retro-Cascorder, overcomes this limitation by molecularly logging a record of gene expression events in a temporally organized genomic ledger. The Retro-Cascorder works by converting a transcriptional event into a DNA barcode using a retron reverse transcriptase and then storing that event in a unidirectionally expanding clustered regularly interspaced short palindromic repeats (CRISPR) array via acquisition by CRISPR–Cas integrases. This CRISPR array-based ledger of gene expression can be retrieved at a later point in time by sequencing. Here we describe an implementation of the Retro-Cascorder in which the relative timing of transcriptional events from multiple promoters of interest is recorded chronologically in Escherichia coli populations over multiple days. We detail the molecular components required for this technology, provide a step-by-step guide to generate the recording and retrieve the data by Illumina sequencing, and give instructions for how to use custom software to infer the relative transcriptional timing from the sequencing data. The example recording is generated in 2 d, preparation of sequencing libraries and sequencing can be accomplished in 2–3 d, and analysis of data takes up to several hours. This protocol can be implemented by someone familiar with basic bacterial culture, molecular biology and bioinformatics. Analysis can be minimally run on a personal computer.

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Fig. 1: Plots summarizing the effect of the number of simulated informative arrays on ordering score accuracy.
Fig. 2: Retro-Cascorder experimental and computational workflow.
Fig. 3: Simulated ordering score results from different transcriptional programs.
Fig. 4: Illustrative ordering analysis of a recording experiment.

Data availability

Sequencing data associated with this study are available in the NCBI SRA (PRJNA838025).

Code availability

The latest version of the analysis code can be accessed through our lab GitHub ( The release at time of manuscript publishing is available at


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This work was supported by funding from the National Science Foundation (2137692), the NIH/NIGMS (1DP2GM140917-01) and the Pew Biomedical Scholars Program. S.L.S. is a Chan Zuckerberg Biohub investigator and acknowledges additional funding support from the L.K. Whittier Foundation. S.K.L. was supported by an NSF Graduate Research Fellowship (2034836). S.C.L. was supported by a Berkeley Fellowship for Graduate Study.

Author information

Authors and Affiliations



S.K.L. and S.C.L. wrote the protocol, with S.K.L. focusing on the experimental components and S.C.L. focusing on the computational components. The protocol was revised on the basis of input from A.G.-D., S.B.-K. and S.L.S. Additional simulation data was generated and analyzed by S.K.L. and S.C.L. using the Spacer-Seq code adapted into a JupyterLab notebook written by S.C.L. Figures were contributed by S.K.L., S.C.L. and A.G.D.

Corresponding author

Correspondence to Seth L. Shipman.

Ethics declarations

Competing interests

S.L.S. is a named inventor on a patent application assigned to Harvard College, ‘Method of recording multiplexed biological information into a CRISPR array using a retron’ (US20200115706A1). The remaining authors declare no competing interests.

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Peer review information

Nature Protocols thanks Michelle Chan and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Related links

Key reference using this protocol

Bhattarai-Kline, S. et al. Nature 608, 217–225 (2022):

Supplementary information

Supplementary Information

Supplementary Method and Supplementary Fig. 1.

Reporting Summary

Supplementary Table 1

Indexing primer sequences for multiplexing samples during library preparation.

Supplementary Table 2

KAPA Library Quantification Data Analysis Template as described for the KAPA Library Quantification Kit. Worksheet provides a readme page, an analysis page for data input, and a summary page for data output.

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Lear, S.K., Lopez, S.C., González-Delgado, A. et al. Temporally resolved transcriptional recording in E. coli DNA using a Retro-Cascorder. Nat Protoc (2023).

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