Letter | Published:

Synthetic recording and in situ readout of lineage information in single cells

Nature volume 541, pages 107111 (05 January 2017) | Download Citation


Reconstructing the lineage relationships and dynamic event histories of individual cells within their native spatial context is a long-standing challenge in biology. Many biological processes of interest occur in optically opaque or physically inaccessible contexts, necessitating approaches other than direct imaging. Here we describe a synthetic system that enables cells to record lineage information and event histories in the genome in a format that can be subsequently read out of single cells in situ. This system, termed memory by engineered mutagenesis with optical in situ readout (MEMOIR), is based on a set of barcoded recording elements termed scratchpads. The state of a given scratchpad can be irreversibly altered by CRISPR/Cas9-based targeted mutagenesis, and later read out in single cells through multiplexed single-molecule RNA fluorescence hybridization (smFISH). Using MEMOIR as a proof of principle, we engineered mouse embryonic stem cells to contain multiple scratchpads and other recording components. In these cells, scratchpads were altered in a progressive and stochastic fashion as the cells proliferated. Analysis of the final states of scratchpads in single cells in situ enabled reconstruction of lineage information from cell colonies. Combining analysis of endogenous gene expression with lineage reconstruction in the same cells further allowed inference of the dynamic rates at which embryonic stem cells switch between two gene expression states. Finally, using simulations, we show how parallel MEMOIR systems operating in the same cell could enable recording and readout of dynamic cellular event histories. MEMOIR thus provides a versatile platform for information recording and in situ, single-cell readout across diverse biological systems.

Access optionsAccess options

Rent or Buy article

Get time limited or full article access on ReadCube.


All prices are NET prices.


  1. 1.

    , , , & Genomic variability within an organism exposes its cell lineage tree. PLOS Comput. Biol. 1, e50 (2005)

  2. 2.

    & Phylogenetic fate mapping. Proc. Natl Acad. Sci. USA 103, 5448–5453 (2006)

  3. 3.

    et al. Genome sequencing of normal cells reveals developmental lineages and mutational processes. Nature 513, 422–425 (2014)

  4. 4.

    et al. Reconstruction of cell lineage trees in mice. PLoS One 3, e1939 (2008)

  5. 5.

    et al. Somatic mutation in single human neurons tracks developmental and transcriptional history. Science 350, 94–98 (2015)

  6. 6.

    et al. Cell lineage analysis in human brain using endogenous retroelements. Neuron 85, 49–59 (2015)

  7. 7.

    et al. Multiplex genome engineering using CRISPR/Cas systems. Science 339, 819–823 (2013)

  8. 8.

    et al. RNA-guided human genome engineering via Cas9. Science 339, 823–826 (2013)

  9. 9.

    et al. A programmable dual-RNA-guided DNA endonuclease in adaptive bacterial immunity. Science 337, 816–821 (2012)

  10. 10.

    , , , & Single-cell in situ RNA profiling by sequential hybridization. Nat. Methods 11, 360–361 (2014)

  11. 11.

    , , & In situ transcription profiling of single cells reveals spatial organization of cells in the mouse hippocampus. Neuron 92, 342–357 (2016)

  12. 12.

    , , , & Real-time observation of transcription initiation and elongation on an endogenous yeast gene. Science 332, 475–478 (2011)

  13. 13.

    et al. Efficient transposition of the piggyBac (PB) transposon in mammalian cells and mice. Cell 122, 473–483 (2005)

  14. 14.

    , , , & A rapid, reversible, and tunable method to regulate protein function in living cells using synthetic small molecules. Cell 126, 995–1004 (2006)

  15. 15.

    et al. XTcf-3 transcription factor mediates beta-catenin-induced axis formation in Xenopus embryos. Cell 86, 391–399 (1996)

  16. 16.

    , , , & Imaging individual mRNA molecules using multiple singly labeled probes. Nat. Methods 5, 877–879 (2008)

  17. 17.

    & Single-cell systems biology by super-resolution imaging and combinatorial labeling. Nat. Methods 9, 743–748 (2012)

  18. 18.

    et al. Comparing algorithms that reconstruct cell lineage trees utilizing information on microsatellite mutations. PLOS Comput. Biol. 9, e1003297 (2013)

  19. 19.

    & A statistical method for evaluating systematic relationships. Univ. Kans. Sci. Bull. 28, 1409–1438 (1958)

  20. 20.

    et al. Whole-organism lineage tracing by combinatorial and cumulative genome editing. Science 353, aaf7907 (2016)

  21. 21.

    et al. Estrogen-related receptor beta interacts with Oct4 to positively regulate Nanog gene expression. Mol. Cell. Biol. 28, 5986–5995 (2008)

  22. 22.

    et al. Deconstructing transcriptional heterogeneity in pluripotent stem cells. Nature 516, 56–61 (2014)

  23. 23.

    et al. Dynamic heterogeneity and DNA methylation in embryonic stem cells. Mol. Cell 55, 319–331 (2014)

  24. 24.

    et al. Inferring cell-state transition dynamics from lineage trees and endpoint single-cell measurements. Cell Syst. 3, 419–433 (2016)

  25. 25.

    , & Inferring epigenetic dynamics from kin correlations. Proc. Natl Acad. Sci. USA 112, E2281–E2289 (2015)

  26. 26.

    , & Rewritable digital data storage in live cells via engineered control of recombination directionality. Proc. Natl Acad. Sci. USA 109, 8884–8889 (2012)

  27. 27.

    , & Continuous genetic recording with self-targeting CRISPR-Cas in human cells. Science 353, aag0511 (2016)

  28. 28.

    , , & Molecular recordings by directed CRISPR spacer acquisition. Science 353, aaf1175 (2016)

  29. 29.

    , , & A population-based temporal logic gate for timing and recording chemical events. Mol. Syst. Biol. 12, 869 (2016)

  30. 30.

    & Genomically encoded analog memory with precise in vivo DNA writing in living cell populations. Science 346, 1256272 (2014)

  31. 31.

    & Self-processing of ribozyme-flanked RNAs into guide RNAs in vitro and in vivo for CRISPR-mediated genome editing. J. Integr. Plant Biol. 56, 343–349 (2014)

  32. 32.

    , , , & Multiplexed and programmable regulation of gene networks with an integrated RNA and CRISPR/Cas toolkit in human cells. Mol. Cell 54, 698–710 (2014)

  33. 33.

    et al. Cre-lox-regulated conditional RNA interference from transgenes. Proc. Natl Acad. Sci. USA 101, 10380–10385 (2004)

  34. 34.

    & The neighbor-joining method: a new method for reconstructing phylogenetic trees. Mol. Biol. Evol. 4, 406–425 (1987)

  35. 35.

    & A method for deducing branching sequences in phylogeny. Evolution 19, 311–326 (1965)

  36. 36.

    , & A 5′ element of the chicken beta-globin domain serves as an insulator in human erythroid cells and protects against position effect in Drosophila. Cell 74, 505–514 (1993)

  37. 37.

    et al. Database for mRNA half-life of 19 977 genes obtained by DNA microarray analysis of pluripotent and differentiating mouse embryonic stem cells. DNA Res. 16, 45–58 (2009)

  38. 38.

    , , , & Conserved principles of mammalian transcriptional regulation revealed by RNA half-life. Nucleic Acids Res. 37, e115 (2009)

  39. 39.

    et al. Genome-wide analysis of long noncoding RNA stability. Genome Res. 22, 885–898 (2012)

  40. 40.

    & Comparison of phylogenetic trees. Math. Biosci. 53, 131–147 (1981)

  41. 41.

    et al. Ncoa3 functions as an essential Esrrb coactivator to sustain embryonic stem cell self-renewal and reprogramming. Genes Dev. 26, 2286–2298 (2012)

  42. 42.

    , , , & Dax1 associates with Esrrb and regulates its function in embryonic stem cells. Mol. Cell. Biol. 33, 2056–2066 (2013)

Download references


We thank M. Budd and H. Li for helpful suggestions. We thank R. Kishony, and members of the Elowitz and Cai laboratories for discussions and comments on the manuscript. This research was supported by the Allen Distinguished Investigator Program, through The Paul G. Allen Frontiers Group, NIH R01HD075605 and K99GM118910 (to S.H.), the Gordon and Betty Moore Foundation Grant GBMF2809 to the Caltech Programmable Molecular Technology Initiative, and the Beckman Institute pilot program.

Author information

Author notes

    • Kirsten L. Frieda
    • , James M. Linton
    •  & Sahand Hormoz

    These authors contributed equally to this work.

    • Michael B. Elowitz
    •  & Long Cai

    These authors jointly supervised this work.


  1. Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, California 91125, USA

    • Kirsten L. Frieda
    • , James M. Linton
    • , Sahand Hormoz
    • , Ke-Huan K. Chow
    • , Zakary S. Singer
    • , Mark W. Budde
    •  & Michael B. Elowitz
  2. Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, California 91125, USA

    • Joonhyuk Choi
    •  & Long Cai
  3. Howard Hughes Medical Institute, California Institute of Technology, Pasadena, California 91125, USA

    • Michael B. Elowitz


  1. Search for Kirsten L. Frieda in:

  2. Search for James M. Linton in:

  3. Search for Sahand Hormoz in:

  4. Search for Joonhyuk Choi in:

  5. Search for Ke-Huan K. Chow in:

  6. Search for Zakary S. Singer in:

  7. Search for Mark W. Budde in:

  8. Search for Michael B. Elowitz in:

  9. Search for Long Cai in:


K.L.F. and J.M.L. performed the experiments with assistance from S.H., J.C., K.K.C. and Z.S.S.; K.L.F. and S.H. analysed the data; S.H. performed the simulations; M.B.E. and L.C. supervised the project. All authors wrote the manuscript.

Competing interests

The biotechnology associated with MEMOIR is the subject of a patent application (14/650,133). The authors declare no other competing financial interests.

Corresponding authors

Correspondence to Michael B. Elowitz or Long Cai.

Reviewer Information

Nature thanks A. Raj and the other anonymous reviewer(s) for their contribution to the peer review of this work.

Extended data

Supplementary information

PDF files

  1. 1.

    Supplementary Information

    This file contains Supplementary Methods, describing the distance matrix computation, noise source analysis, sparsely sampled tree simulations, and switching rates inference. It also contains Supplementary Figure 1, the uncropped gels.

Excel files

  1. 1.

    Supplementary Table 1

    A table of sequences for 28 scratchpad barcodes.

  2. 2.

    Supplementary Table 2

    A table of oligo sequences for probes used in smFISH and targeting either the PP7 array or one of 28 scratchpad barcodes.

About this article

Publication history






Further reading


By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.