Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

SPARC enables genetic manipulation of precise proportions of cells

Nature Neuroscience volume 23, pages 1168–1175 (2020)Cite this article

Subjects

Abstract

Many experimental approaches rely on controlling gene expression in select subsets of cells within an individual animal. However, reproducibly targeting transgene expression to specific fractions of a genetically defined cell type is challenging. We developed Sparse Predictive Activity through Recombinase Competition (SPARC), a generalizable toolkit that can express any effector in precise proportions of post-mitotic cells in Drosophila. Using this approach, we demonstrate targeted expression of many effectors in several cell types and apply these tools to calcium imaging of individual neurons and optogenetic manipulation of sparse cell populations in vivo.

This is a preview of subscription content, access via your institution

Access options

Rent or buy this article

Prices vary by article type

from$1.95

to$39.95

Learn more

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Schematic description of the SPARC method.
Fig. 2: The SPARC toolkit enables predictable expression of effectors at three levels.
Fig. 3: SPARC2 labels precise proportions of neurons across a diverse set of cell types.
Fig. 4: SPARC2 stochastically labels different subsets of neurons in each animal.
Fig. 5: SPARC enables calcium imaging of single neurons.
Fig. 6: SPARC2 enables optogenetic stimulation of sparse cell populations.

Data availability

The data that support the findings of this study are available from the corresponding author upon reasonable request. Source data are provided with this paper.

Code availability

All analysis was carried out using custom-written MATLAB code: https://github.com/wienecke/SPARC. Visual stimuli were programmed with the OpenGL 1.0 API in Visual C#. All code is available on Github and will be made available upon reasonable request from the corresponding author. Source data are provided with this paper.

References

  1. Luo, L., Callaway, E. M. & Svoboda, K. Genetic dissection of neural circuits: a decade of progress. Neuron 98, 256–281 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Duffy, J. B. GAL4 system in Drosophila: a fly geneticist’s Swiss army knife. Genesis 34, 1–15 (2002).

    Article  CAS  PubMed  Google Scholar 

  3. Golic, K. G. & Lindquist, S. The FLP recombinase of yeast catalyzes site-specific recombination in the Drosophila genome. Cell 59, 499–509 (1989).

    Article  CAS  PubMed  Google Scholar 

  4. Sauer, B. & Henderson, N. Site-specific DNA recombination in mammalian cells by the Cre recombinase of bacteriophage P1. PNAS 85, 5166–5170 (1988).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Yeh, E., Gustafson, K. & Boulianne, G. L. Green fluorescent protein as a vital marker and reporter of gene expression in Drosophila. PNAS 92, 7036–7040 (1995).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Akerboom, J. et al. Optimization of a GCaMP calcium indicator for neural activity imaging. J. Neurosci. 32, 13819–13840 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Fenno, L., Yizhar, O. & Deisseroth, K. The development and application of optogenetics. Annu. Rev. Neurosci. 34, 389–412 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Atasoy, D., Aponte, Y., Su, H. H. & Sternson, S. M. A FLEX switch targets channelrhodopsin-2 to multiple cell types for imaging and long-range circuit mapping. J. Neurosci. 28, 7025–7030 (2008).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Lin, R. et al. Cell-type-specific and projection-specific brain-wide reconstruction of single neurons. Nat. Methods 15, 1033–1036 (2018).

  10. Feil, R. et al. Ligand-activated site-specific recombination in mice. Proc. Natl Acad. Sci. USA 93, 10887–10890 (1996).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Livet, J. et al. Transgenic strategies for combinatorial expression of fluorescent proteins in the nervous system. Nature 450, 56–62 (2007).

    Article  CAS  PubMed  Google Scholar 

  12. Zong, H., Espinosa, J. S., Su, H. H., Muzumdar, M. D. & Luo, L. Mosaic analysis with double markers in mice. Cell 121, 479–492 (2005).

    Article  CAS  PubMed  Google Scholar 

  13. Lee, T. & Luo, L. Mosaic analysis with a repressible cell marker for studies of gene function in neuronal morphogenesis. Neuron 22, 451–461 (1999).

    Article  CAS  PubMed  Google Scholar 

  14. Hadjieconomou, D. et al. Flybow: genetic multicolor cell labeling for neural circuit analysis in Drosophila melanogaster. Nat. Methods 8, 260–266 (2011).

    Article  CAS  PubMed  Google Scholar 

  15. Hampel, S. et al. Drosophila Brainbow: a recombinase-based fluorescence labeling technique to subdivide neural expression patterns. Nat. Methods 8, 253–259 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Sethi, S. & Wang, J. W. A versatile genetic tool for post-translational control of gene expression in Drosophila melanogaster. eLife 6, e04577 (2017).

    Article  Google Scholar 

  17. Gordon, M. D. & Scott, K. Motor control in a Drosophila taste circuit. Neuron 61, 373–384 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Bohm, R. A. et al. A genetic mosaic approach for neural circuit mapping in Drosophila. Proc. Natl Acad. Sci. USA 107, 16378–16383 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  19. Philipsborn, von et al. Neuronal control of Drosophila courtship song. Neuron 69, 509–522 (2011).

    Article  CAS  Google Scholar 

  20. Nern, A., Pfeiffer, B. D. & Rubin, G. M. Optimized tools for multicolor stochastic labeling reveal diverse stereotyped cell arrangements in the fly visual system. Proc. Natl Acad. Sci. USA 112, E2967–E2976 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Dionne, H., Hibbard, K. L., Cavallaro, A., Kao, J.-C. & Rubin, G. M. Genetic reagents for making split-GAL4 lines in Drosophila. Genetics 209, 31–35 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Jenett, A. et al. A GAL4-driver line resource for Drosophila neurobiology. Cell Rep. 2, 991–1001 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Thorpe, H. M. & Smith, M. C. In vitro site-specific integration of bacteriophage DNA catalyzed by a recombinase of the resolvase/invertase family. Proc. Natl Acad. Sci. USA 95, 5505–5510 (1998).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Groth, A. C., Olivares, E. C., Thyagarajan, B. & Calos, M. P. A phage integrase directs efficient site-specific integration in human cells. Proc. Natl Acad. Sci. USA 97, 5995–6000 (2000).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Hong, W. et al. Leucine-rich repeat transmembrane proteins instruct discrete dendrite targeting in an olfactory map. Nat. Neurosci. 12, 1542–1550 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Riabinina, O. et al. Improved and expanded Q-system reagents for genetic manipulations. Nat. Methods 12, 219–222 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Pinto-Teixeira, F. et al. Development of concurrent retinotopic maps in the fly motion detection circuit. Cell 173, 485–498 (2018).

  28. Pfeiffer, B. D. et al. Refinement of tools for targeted gene expression in Drosophila. Genetics 186, 735–755 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Lai, S.-L. & Lee, T. Genetic mosaic with dual binary transcriptional systems in Drosophila. Nat. Neurosci. 9, 703–709 (2006).

    Article  CAS  PubMed  Google Scholar 

  30. Perrotta, A. T. & Been, M. D. A pseudoknot-like structure required for efficient self-cleavage of hepatitis delta virus RNA. Nature 350, 434–436 (1991).

    Article  CAS  PubMed  Google Scholar 

  31. Wernet, M. F., Klovstad, M. & Clandinin, T. R. A Drosophila toolkit for the visualization and quantification of viral replication launched from transgenic genomes. PLoS ONE 9, e112092 (2014).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  32. Schnell, B. et al. Processing of horizontal optic flow in three visual interneurons of the Drosophila brain. J. Neurophysiol. 103, 1646–1657 (2010).

    Article  CAS  PubMed  Google Scholar 

  33. Sanes, J. R. & Zipursky, S. L. Design principles of insect and vertebrate visual systems. Neuron 66, 15–36 (2010).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Jefferis, G. S., Marin, E. C., Stocker, R. F. & Luo, L. Target neuron prespecification in the olfactory map of Drosophila. Nature 414, 204–208 (2001).

    Article  CAS  PubMed  Google Scholar 

  35. Wu, M. et al. Visual projection neurons in the Drosophila lobula link feature detection to distinct behavioral programs. eLife 5, e21022 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  36. Maisak, M. S. et al. A directional tuning map of Drosophila elementary motion detectors. Nature 500, 212–216 (2013).

    Article  CAS  PubMed  Google Scholar 

  37. Fisher, Y. E., Silies, M. & Clandinin, T. R. Orientation selectivity sharpens motion detection in Drosophila. Neuron 88, 390–402 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Leong, J. C. S., Esch, J. J., Poole, B., Ganguli, S. & Clandinin, T. R. Direction selectivity in Drosophila emerges from preferred-direction enhancement and null-direction suppression. J. Neurosci. 36, 8078–8092 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  39. Wienecke, C. F. R., Leong, J. C. S. & Clandinin, T. R. Linear summation underlies direction selectivity in Drosophila. Neuron 99, 680–688 (2018).

  40. Klapoetke, N. C. et al. Independent optical excitation of distinct neural populations. Nat. Methods 11, 338–346 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Seelig, J. D. & Jayaraman, V. Feature detection and orientation tuning in the Drosophila central complex. Nature 503, 262–266 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Omoto, J. J. et al. Neuronal constituents and putative interactions within the Drosophila ellipsoid body neuropil. Front. Neural Circuits 12, 103 (2018).

  43. Mosimann, C. et al. Site-directed zebrafish transgenesis into single landing sites with the phiC31 integrase system. Dev. Dyn. 242, 949–963 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Olivares, E. C. et al. Site-specific genomic integration produces therapeutic Factor IX levels in mice. Nat. Biotechnol. 20, 1124–1128 (2002).

    Article  CAS  PubMed  Google Scholar 

  45. Fischbach, P. K. F. & Dittrich, A. P. M. The optic lobe of Drosophila melanogaster. I. A Golgi analysis of wild-type structure. Cell Tissue Res. 258, 441–475 (1989).

    Article  Google Scholar 

  46. Gohl, D. M. et al. A versatile in vivo system for directed dissection of gene expression patterns. Nat. Methods 8, 231–237 (2011).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Gratz, S. J. et al. Highly specific and efficient CRISPR/Cas9-catalyzed homology-directed repair in Drosophila. Genetics 196, 961–971 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Silies, M. et al. Modular use of peripheral input channels tunes motion-detecting circuitry. Neuron 79, 111–127 (2013).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Housden, B. E. et al. Identification of potential drug targets for tuberous sclerosis complex by synthetic screens combining CRISPR-based knockouts with RNAi. Sci. Signal 8, rs9–rs9 (2015).

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  50. Wilson, R. I., Turner, G. C. & Laurent, G. Transformation of olfactory representations in the Drosophila antennal lobe. Science 303, 366–370 (2004).

    Article  CAS  PubMed  Google Scholar 

  51. Schindelin, J. et al. Fiji: an open-source platform for biological-image analysis. Nat. Methods 9, 676–682 (2012).

    Article  CAS  PubMed  Google Scholar 

  52. Leonhardt, A. et al. Asymmetry of Drosophila ON and OFF motion detectors enhances real-world velocity estimation. Nat. Neurosci. 19, 706–715 (2016).

    Article  CAS  PubMed  Google Scholar 

  53. Pnevmatikakis, E. A. et al. Simultaneous denoising, deconvolution, and demixing of calcium imaging data. Neuron 89, 285–299 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Fişek, M. & Wilson, R. I. Stereotyped connectivity and computations in higher-order olfactory neurons. Nat. Neurosci. 17, 280–288 (2014).

    Article  PubMed  CAS  Google Scholar 

  55. Gouwens, N. W. & Wilson, R. I. Signal propagation in Drosophila central neurons. J. Neurosci. 29, 6239–6249 (2009).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We thank members of the Clandinin, Wilson and Maimon labs for discussion of the project and manuscript. We thank A. Chakravorty for generating the SPARC-jGCaMP7f plasmids and S. Gratz, K. O’Connor-Giles (Brown University), C. Xie, L. Luo (Stanford University) and B. Pfeiffer and D. Anderson (CalTech) for providing template plasmids for molecular cloning. We also thank G. Rubin and H. Dionne (Janelia Farms) for sharing split-Gal4 stocks and N. Perrimon (Harvard University) for sharing Cas9 stocks. Additionally, stocks obtained from the Bloomington Drosophila Stock Center (National Institutes of Health (NIH) P40OD018537) were used in this study. The project was supported by the NIH (R01EY022638 and 5P30EY026877 to T.R.C. and 5U19NS104655 to T.R.C. and R.E.W). J.I.-B. is an Arnold O. Beckman Postdoctoral Fellow. H.H.Y. is a Howard Hughes Medical Institute (HHMI) fellow of the Jane Coffin Childs Memorial Fund for Medical Research. Y.E.F. is supported by a Hanna H. Grey Fellowship from the HHMI. C.F.R.W. is supported by a National Science Foundation Graduate Research Fellowship (DGE – 1656518). R.I.W. and G.M. are HHMI investigators.

Author information

Author notes

  1. Kristine C. Paik

    Present address: Department of Medicine, Weill Cornell Medical College, New York, NY, USA

  2. Irving E. Wang

    Present address: Freenome, South San Francisco, CA, USA

Authors and Affiliations

  1. Department of Neurobiology, Stanford University, Stanford, CA, USA

    Jesse Isaacman-Beck, Kristine C. Paik, Carl F. R. Wienecke, Irving E. Wang & Thomas R. Clandinin

  2. Department of Neurobiology and Howard Hughes Medical Institute, Harvard Medical School, Boston, MA, USA

    Helen H. Yang, Yvette E. Fisher & Rachel I. Wilson

  3. Laboratory of Integrative Brain Function and Howard Hughes Medical Institute, The Rockefeller University, New York, NY, USA

    Itzel G. Ishida & Gaby Maimon

Authors
  1. Jesse Isaacman-Beck
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Kristine C. Paik
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Carl F. R. Wienecke
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Helen H. Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Yvette E. Fisher
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Irving E. Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Itzel G. Ishida
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Gaby Maimon
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Rachel I. Wilson
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Thomas R. Clandinin
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

J.I.-B., H.H.Y., I.E.W. and T.R.C conceived the study. J.I.-B., C.F.R.W., H.H.Y. and Y.E.F. designed and performed the experiments under the supervision of T.R.C. and R.I.W. J.I.-B., K.C.P., H.H.Y., Y.E.F. and I.G.I. generated, maintained and/or validated transgenic fly stocks under the supervision of T.R.C, R.I.W. and G.M. J.I.-B., C.F.R.W., H.H.Y., Y.E.F. and K.C.P. analyzed the data. J.I.-B. and T.R.C. prepared the manuscript with contributions from C.F.R.W., H.H.Y. and Y.E.F.

Corresponding author

Correspondence to Thomas R. Clandinin.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Additional information

Peer review information Nature Neuroscience thanks Claude Desplan, Olena Riabinina and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Extended data

Extended Data Fig. 1 SPARC development cassettes.

a, b, Schematics of PhiC31-dependent UAS-inversion effector constructs. (a) control construct with canonical attP sites and (b) truncated 34bp_attP experimental construct. c, d”, 34bp_attP-Inversion-GCaMP6f expression (green, c, d) in Mi1 neurons (magenta, c’, d’) counterstained with anti-Bruchpilot (Brp; blue, overlay c”, d”). Fewer Mi1 neurons are labeled at day two post eclosion (c–c”) than at day six post eclosion (d–d”). e, Schematic of the LexA-OR-Flp expression construct. PhiC31 recombines one of two competing attP target sequences with one attB target sequence to enable either LexA or Flp expression. Reaction 1 leads to LexA expression. Reaction 2 leads to Flp expression. f–f”, Flp-enabled mCD8::GFP expression (green, f) or LexA-driven myr::tdTomato expression in Mi1 neurons (magenta, f’) counterstained with anti-Bruchpilot (Brp; blue, overlay f”). n = 10 optic lobes per genotype. Scale bar: 10 µm.

Extended Data Fig. 2 Plasmid maps and molecular cloning methods for SPARC and SPARC2 constructs.

a, Map of pHD-3xP3-DsRed-ΔattP (a CRISPR-HDR-donor precursor) showing multiple cloning sites for homology arm insertion (right). b, Map of pHD-3xP3-DsRed-ΔattP-CRISPR-donor (example includes homology arms targeting the attP40 region of the Drosophila genome). c, SPARC and SPARC2 cassettes are inserted into pHD-3xP3-DsRed-ΔattP-CRISPR-donor via unique KpnI, NdeI, or BsiWI restriction enzyme sites. SalI restriction enzyme sites in the SPARC2 module allow for one-step swapping of the effector and terminator to generate pHD-SPARC2 donor plasmids. Abbreviations: MCS – multiple cloning site; gRNA – guide RNA; HDVR – hepatitis delta virus ribozyme sequence.

Extended Data Fig. 3 SPARC-GCaMP6f expression in Kenyon cells.

a–d, Anterior view of the Drosophila central brain showing GCaMP6f expression (green) in Kenyon cells (magenta) counterstained with anti-Bruchpilot (Brp; blue). a, SPARC-D-GCaMP6f, no PhiC31. b, SPARC-D-GCaMP6f. c, SPARC-I-GCaMP6f. d, SPARC-S-GCaMP6f. e–h”, GCaMP6f expression (green, e–h) in Kenyon cell bodies (magenta, e’–h’) with overlay (e”–h”). e–e”, SPARC-D-GCaMP6f, no PhiC31. GCaMP6f is not detected in Kenyon Cells in the absence of PhiC31. f–f”, SPARC-D-GCaMP6f. g–g”, SPARC-I-GCaMP6f. h–h”, SPARC-S-GCaMP6f. Scale bars: 30 µm (a–d), 10 µm (e–h”). n > 10 brains per condition from three independent experiments.

Extended Data Fig. 4 SPARC and SPARC2 user guide.

a, Important notes regarding SPARC and SPARC2 use and stock maintenance. b, Example crossing schemes for SPARC or SPARC2 to allow expression of effectors.

Supplementary information

Supplementary Information

Supplementary Tables 5 and 7 and Supplementary Notes on fly genotypes (by figure) and origin of transgenes

Reporting Summary

Supplementary Table

Supplementary Tables 1–4 and 6 describe reagents from the Methods section.

Source data

Source Data Fig. 3

Original cell counts and complete statistical analyses

Rights and permissions

Reprints and Permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Isaacman-Beck, J., Paik, K.C., Wienecke, C.F.R. et al. SPARC enables genetic manipulation of precise proportions of cells. Nat Neurosci 23, 1168–1175 (2020). https://doi.org/10.1038/s41593-020-0668-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41593-020-0668-9

This article is cited by

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing