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Preparation of plant tissue to enable Spatial Transcriptomics profiling using barcoded microarrays

Abstract

Elucidation of the complex processes involved in plant growth requires analysis of the spatial gene expression patterns in all affected tissues. This protocol extension is an adaptation of a protocol that describes how to use barcoded oligo-dT microarrays to evaluate spatial global gene expression profiles in mammalian tissue to enable it to be applied to plant material. Here, we explain the required adjustments for preparing and treating plant tissue sections on the array surface, specifically in regard to how to permeabilize and remove the tissue. Once the tissue has been removed, the cDNA–mRNA hybrid that is left on the slide is processed in the same way as cDNA obtained during experiments on mammalian tissue; thus the later stages of the protocol are not included here, and readers should follow the accompanying protocol for those. We have previously used our protocol to generate high-quality sequencing libraries for Arabidopsis thaliana inflorescence, Populus tremula developing and dormant leaf buds, and Picea abies female cones. However, we anticipate that the protocol can be adapted to other tissue types and species. The entire protocol for preparing samples and processing libraries can be completed in 3–4 d.

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Fig. 1: Complete workflow for tissue-optimization experiments and generation of Spatial Transcriptomics sequencing libraries.
Fig. 2: Barcoded oligo-dT microarray resolution.
Fig. 3: Successful and unsuccessful tissue removal.
Fig. 4: Analysis of secondary metabolites.
Fig. 5: cDNA footprint.

References

  1. 1.

    Emmert-buck, M. R. et al. Laser capture microdissection. Science 274, 998–1001 (1996).

    CAS  Article  PubMed  Google Scholar 

  2. 2.

    Blokhina, O. et al. Laser capture microdissection protocol for xylem tissues of woody plants. Front. Plant Sci. 7, 1–14 (2017).

    Article  Google Scholar 

  3. 3.

    Birnbaum, K. et al. A gene expression map of the Arabidopsis root. Science 302, 1956–1960 (2003).

    CAS  Article  PubMed  Google Scholar 

  4. 4.

    Carter, A. D., Bonyadi, R. & Gifford, M. L. The use of fluorescence-activated cell sorting in studying plant development and environmental responses. Int. J. Dev. Biol. 57, 545–552 (2013).

    CAS  Article  PubMed  Google Scholar 

  5. 5.

    Deal, R. B. & Henikoff, S. A simple method for gene expression and chromatin profiling of individual cell types within a tissue. Dev. Cell 18, 1030–1040 (2010).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  6. 6.

    Moreno-romero, J., Santos-gonzález, J., Hennig, L. & Köhler, C. Applying the INTACT method to purify endosperm nuclei and to generate parental-specific epigenome profiles. Nat. Protoc. 12, 238–254 (2017).

    CAS  Article  PubMed  Google Scholar 

  7. 7.

    Femino, A. M., Fay, F. S., Fogarty, K. & Singer, R. H. Visualization of single RNA transcripts in situ. Science 280, 585–590 (1998).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  8. 8.

    Lyubimova, A. et al. Single-molecule mRNA detection and counting in mammalian tissue. Nat. Protoc. 8, 1743–1758 (2013).

    Article  PubMed  Google Scholar 

  9. 9.

    Chen, K. H., Boettiger, A. N., Moffitt, J. R., Wang, S. & Zhuang, X. Spatially resolved, highly multiplexed RNA profiling in single cells. Science 348, aaa6090-1–aaa6090-14 (2015).

    Google Scholar 

  10. 10.

    Moffitt, J. R. et al. High-throughput single-cell gene-expression profiling with multiplexed error-robust fluorescence in situ hybridization. Proc. Natl. Acad. Sci. USA 113, 11046–11051 (2016).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  11. 11.

    Lubeck, E., Coskun, A. F., Zhiyentayev, T., Ahmad, M. & Cai, L. Single-cell in situ RNA profiling by sequential hybridization. Nat. Methods 11, 360–361 (2014).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  12. 12.

    Shah, S., Lubeck, E., Zhou, W. & Cai, L. In situ transcription profiling of single cells reveals spatial organization of cells in the mouse hippocampus. Neuron 92, 342–357 (2016).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  13. 13.

    Eng, C.-H. L., Shah, S., Thomassie, J. & Cai, L. Profiling the transcriptome with RNA SPOTs. Nat. Methods 14, 1153–1155 (2017).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  14. 14.

    Choi, H. M. T., Beck, V. A. & Pierce, N. A. Next-generation in situ hybridization chain reaction: higher gain, lower cost, greater durability. ACS Nano 8, 4284–4294 (2014).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  15. 15.

    Shah, S. et al. Single-molecule RNA detection at depth by hybridization chain reaction and tissue hydrogel embedding and clearing. Development 143, 2862–2867 (2016).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  16. 16.

    Ke, R. et al. In situ sequencing for RNA analysis in preserved tissue and cells. Nat. Methods 10, 857–860 (2013).

    CAS  Article  Google Scholar 

  17. 17.

    Lee, J. H. et al. Highly multiplexed subcellular RNA sequencing in situ. Science 343, 1360–1363 (2014).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  18. 18.

    Ståhl, P. L. et al. Visualization and analysis of gene expression in tissue sections by spatial transcriptomics. Science 353, 78–82 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  19. 19.

    Duncan, S., Olsson, T. S. G., Hartley, M., Dean, C. & Rosa, S. A method for detecting single mRNA molecules in Arabidopsis thaliana. Plant Methods 12, 1–10 (2016).

    Article  Google Scholar 

  20. 20.

    Giacomello, S. et al. Spatially resolved transcriptome profiling in model plant species. Nat. Plants 17061, 1–11 (2017).

    Google Scholar 

  21. 21.

    Lieben, L. Spatial transcriptomics in plants. Nat. Rev. Genet. 18, 394 (2017).

  22. 22.

    Salmén, F. et al. Barcoded solid-phase RNA capture for Spatial Transcriptomics profiling in mammalian tissue sections. Nat. Protoc. https://doi.org/10.1038/s41596-018-0045-2 (2018).

  23. 23.

    Birnbaum, K. et al. Cell type-specific expression profiling in plants via cell sorting of protoplasts from fluorescent reporter lines. Nat. Methods 2, 615–619 (2005).

    CAS  Article  PubMed  Google Scholar 

  24. 24.

    Deal, R. B. & Henikoff, S. The INTACT method for cell type-specific gene expression and chromatin profiling in Arabidopsis thaliana. Nat. Protoc. 19, 56–68 (2010).

    Google Scholar 

  25. 25.

    Brady, S. M. et al. A high-resolution root spatiotemporal map reveals dominant expression patterns. Science 302, 801–806 (2007).

    Article  Google Scholar 

  26. 26.

    Satija, R., Farrell, J. A., Gennert, D., Schier, A. F. & Regev, A. A spatial reconstruction of single-cell gene expression data. Nat. Biotechnol. 33, 495–502 (2015).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  27. 27.

    Karaiskos, N. et al. The Drosophila embryo at single-cell transcriptome resolution. Science 3235, 1–14 (2017).

    Google Scholar 

  28. 28.

    Keegstra, K. Plant cell walls. Plant Physiol. 154, 483–486 (2010).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  29. 29.

    Sarkar, P., Bosneaga, E. & Auer, M. Plant cell walls throughout evolution: towards a molecular understanding of their design principles. J. Exp. Bot. 60, 3615–3635 (2009).

    CAS  Article  PubMed  Google Scholar 

  30. 30.

    Burton, R. A. & Fincher, G. B. (1,3;1,4)-β-D-glucans in cell walls of the poaceae, lower plants, and fungi: a tale of two linkages. Mol. Plant 2, 873–882 (2009).

    CAS  Article  PubMed  Google Scholar 

  31. 31.

    Popper, Z. A. & Fry, S. C. Primary cell wall composition of bryophytes and charophytes. Ann. Bot. 91, 1–12 (2003).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  32. 32.

    Bourgaud, F., Gravot, A., Milesi, S. & Gontier, E. Production of plant secondary metabolites: a historical perspective. Plant Sci. 161, 839–851 (2001).

    CAS  Article  Google Scholar 

  33. 33.

    Koonjul, P. K., Brandt, W. F., Farrant, J. M. & Lindsey, G. G. Inclusion of polyvinylpyrrolidone in the polymerase chain reaction reverses the inhibitory effects of polyphenolic contamination of RNA. Nucleic Acids Res. 27, 915–916 (1999).

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  34. 34.

    Yadav, R. K., Tavakkoli, M., Xie, M., Girke, T. & Reddy, G. V. A high-resolution gene expression map of the Arabidopsis shoot meristem stem cell niche. Development 141, 2735–2744 (2014).

    CAS  Article  PubMed  Google Scholar 

  35. 35.

    Islam, S. et al. Quantitative single-cell RNA-seq with unique molecular identifiers. Nat. Methods 11, 163–166 (2014).

    CAS  Article  PubMed  Google Scholar 

  36. 36.

    Navarro, J. F., Sjöstrand, J., Salmén, F., Lundeberg, J. & Ståhl, P. L. ST Pipeline: an automated pipeline for spatial mapping of unique transcripts. Bioinformatics 33, 2591–2593 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

This work was supported by the Knut and Alice Wallenberg Foundation and the Swedish Research Council.

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Authors

Contributions

S.G. and J.L. designed the research. S.G. developed the protocol and wrote the manuscript.

Corresponding authors

Correspondence to Stefania Giacomello or Joakim Lundeberg.

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Competing interests

J.L. is the founder of a company that holds IP rights to the presented technology. S.G. declares no competing interests.

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Key reference using this protocol

Giacomello, S. et al. Nat. Plants 3, 17061 (2017): https://doi.org/10.1038/nplants.2017.61

This protocol is an extension to: Nat. Protoc. https://doi.org/10.1038/s41596-018-0045-2

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Giacomello, S., Lundeberg, J. Preparation of plant tissue to enable Spatial Transcriptomics profiling using barcoded microarrays. Nat Protoc 13, 2425–2446 (2018). https://doi.org/10.1038/s41596-018-0046-1

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