Spatial perturb-seq: single-cell functional genomics within intact tissue architecture

Custom code is available at Github (https://github.com/kimberle9/spatialperturbseq) and archived on Zenodo⁵⁴ (https://doi.org/10.5281/zenodo.17959756). The repository is released under the MIT License, an Open Source Initiative–approved license. There are no restrictions on access or reuse. Analysis of the processed data in this study was done using open-source R packages Seurat (https://github.com/satijalab/seurat), BANKSY, powsimR (https://github.com/bvieth/powsimR), scCustomize (https://github.com/samuel-marsh/scCustomize), and open-source Python packages Stereopy (https://stereopy.readthedocs.io/en/latest/) and SAW.

1. Dixit, A. et al. Perturb-seq: dissecting molecular circuits with scalable single-cell RNA profiling of pooled genetic screens. Cell 167, 1853–1866.e17 (2016).

   Google Scholar 

2. Adamson, B. et al. A multiplexed single-cell CRISPR screening platform enables systematic dissection of the unfolded protein response. Cell 167, 1867–1882.e21 (2016).

   Google Scholar 

3. Santinha, A. J. et al. Transcriptional linkage analysis with in vivo AAV-Perturb-seq. Nature 622, 367–375 (2023).

   Google Scholar 

4. Zheng, X. et al. Massively parallel in vivo perturb-seq reveals cell-type-specific transcriptional networks in cortical development. Cell https://doi.org/10.1016/j.cell.2024.04.050 (2024).

5. Jin, X. et al. In vivo Perturb-Seq reveals neuronal and glial abnormalities associated with autism risk genes. Science (New York, N.Y.) 370, eaaz6063 (2020).

6. Dhainaut, M. et al. Spatial CRISPR genomics identifies regulators of the tumor microenvironment. Cell 185, 1223–1239.e20 (2022).

   Google Scholar 

7. Gu, J. et al. Mapping multimodal phenotypes to perturbations in cells and tissue with CRISPRmap. Nat. Biotechnol. https://doi.org/10.1038/s41587-024-02386-x (2024).

8. Kudo T. et al. Multiplexed, image-based pooled screens in primary cells and tissues with PerturbView. Nat. Biotechnol. https://doi.org/10.1038/s41587-024-02391-0 (2024)

9. Feldman, D. et al. Optical pooled screens in human cells. Cell 179, 787–799.e17 (2019).

   Google Scholar 

10. Wang, C., Lu, T., Emanuel, G., Babcock, H. P. & Zhuang, X. Imaging-based pooled CRISPR screening reveals regulators of lncRNA localization. Proc. Natl. Acad. Sci. USA 116, 10842–10851 (2019).

    Google Scholar 

11. Chen, A. et al. Spatiotemporal transcriptomic atlas of mouse organogenesis using DNA nanoball-patterned arrays. Cell 185, 1777–1792.e21 (2022).

    Google Scholar 

12. Marco Salas, S. et al. Optimizing xenium in situ data utility by quality assessment and best-practice analysis workflows. Nat. Methods 22, 813–823 (2025).

    Google Scholar 

13. Platt, R. J. et al. CRISPR-Cas9 knockin mice for genome editing and cancer modeling. Cell 159, 440–455 (2014).

    Google Scholar 

14. Montini, E. et al. The genotoxic potential of retroviral vectors is strongly modulated by vector design and integration site selection in a mouse model of HSC gene therapy. J. Clin. Invest. 119, 964–975 (2009).

    Google Scholar 

15. Hill, A. J. et al. On the design of CRISPR-based single-cell molecular screens. Nat. Methods 15, 271–274 (2018).

    Google Scholar 

16. Chan, K. Y. et al. Engineered AAVs for efficient noninvasive gene delivery to the central and peripheral nervous systems. Nat. Neurosci. 20, 1172–1179 (2017).

    Google Scholar 

17. Pandey, S. et al. Disease-associated oligodendrocyte responses across neurodegenerative diseases. Cell Rep. 40, 111189 (2022).

    Google Scholar 

18. Floriddia, E. M. et al. Distinct oligodendrocyte populations have spatial preference and different responses to spinal cord injury. Nat. Commun. 11, 5860 (2020).

    Google Scholar 

19. Wang, J. et al. Olig2 ablation in immature oligodendrocytes does not enhance CNS myelination and remyelination. J. Neurosci. 42, 8542–8555 (2022).

    Google Scholar 

20. Meireles, A. M. et al. The lysosomal transcription factor TFEB represses myelination downstream of the rag-ragulator complex. Dev. Cell 47, 319–330.e5 (2018).

    Google Scholar 

21. Jiang, L. et al. Systematic reconstruction of molecular pathway signatures using scalable single-cell perturbation screens. Nat. Cell Biol. 27, 505–517 (2025).

    Google Scholar 

22. Hu, P. et al. Dissecting cell-type composition and activity-dependent transcriptional state in mammalian brains by massively parallel single-nucleus RNA-seq. Mol. cell 68, 1006–1015.e7 (2017).

    Google Scholar 

23. Bannon, D. et al. DeepCell Kiosk: scaling deep learning-enabled cellular image analysis with Kubernetes. Nat. Methods 18, 43–45 (2021).

    Google Scholar 

24. Singhal, V. et al. BANKSY unifies cell typing and tissue domain segmentation for scalable spatial omics data analysis. Nat. Genet. 56, 431–441 (2024).

    Google Scholar 

25. Yang, S. et al. Pathogenicity and functional analysis of CFAP410 mutations causing cone-rod dystrophy with macular staphyloma. Front. Med. 10, 1216427 (2023).

    Google Scholar 

26. Tolosa, E., Vila, M., Klein, C. & Rascol, O. LRRK2 in Parkinson disease: challenges of clinical trials. Nat. Rev. Neurol. 16, 97–107 (2020).

    Google Scholar 

27. Usmani, A., Shavarebi, F. & Hiniker, A. The cell biology of LRRK2 in Parkinson’s disease. Mol. Cell. Biol. 41, e00660-20 (2021).

    Google Scholar 

28. Briz, V. et al. The non-coding RNA BC1 regulates experience-dependent structural plasticity and learning. Nat. Commun. 8, 293 (2017).

    Google Scholar 

29. Bu, M. et al. Inhibition of LRRK2 kinase activity rescues deficits in striatal dopamine physiology in VPS35 p.D620N knock-in mice. NPJ Parkinson’s. Dis. 9, 167 (2023).

    Google Scholar 

30. Jaudon, F. et al. The RhoGEF DOCK10 is essential for dendritic spine morphogenesis. Mol. Biol. Cell 26, 2112–2127 (2015).

    Google Scholar 

31. Morató, X. et al. The Parkinson’s disease-associated GPR37 receptor interacts with striatal adenosine A2A receptor controlling its cell surface expression and function in vivo. Sci. Rep. 7, 9452 (2017).

    Google Scholar 

32. Kuzniewska, B. et al. SRF is required for sprouting and maintenance of neuronal connections in the hippocampus. J. Neurosci. 36, 5699–5710 (2016).

    Google Scholar 

33. Ma’ayan Lab. (n.d.). SRF gene set—ENCODE Transcription Factor Targets. Harmonizome. Retrieved 2024 from https://maayanlab.cloud/Harmonizome/gene_set/SRF/ENCODE+Transcription+Factor+Targets

34. Ba, W. et al. ARHGAP12 functions as a developmental brake on excitatory synapse function. Cell Rep. 14, 1355–1368 (2016).

    Google Scholar 

35. Zeng, S. X., Dai, M. S., Keller, D. M. & Lu, H. SSRP1 functions as a co-activator of the transcriptional activator p63. EMBO J. 21, 5487–5497 (2002).

    Google Scholar 

36. Mitchell, A. C., Jiang, Y., Peter, C. & Akbarian, S. Transcriptional regulation of GAD1 GABA synthesis gene in the prefrontal cortex of subjects with schizophrenia. Schizophrenia Res. 167, 28–34 (2015).

    Google Scholar 

37. Dimitrov, D. et al. Comparison of methods and resources for cell-cell communication inference from single-cell RNA-Seq data. Nat. Commun. 13, 3224 (2022).

    Google Scholar 

38. Chen, K. et al. LRP1 is a neuronal receptor for α-synuclein uptake and spread. Mol. neurodegeneration 17, 57 (2022).

    Google Scholar 

39. Ludtmann, M. H. R. et al. LRRK2 deficiency induced mitochondrial Ca²⁺ efflux inhibition can be rescued by Na⁺/Ca²⁺/Li⁺ exchanger upregulation. Cell Death Dis. 10, 265 (2019).

    Google Scholar 

40. Binan, L. et al. Simultaneous CRISPR screening and spatial transcriptomics reveal intracellular, intercellular, and functional transcriptional circuits. Cell 188, 2141–2158.e18 (2025).

    Google Scholar 

41. Wroblewska, A. et al. Protein barcodes enable high-dimensional single-cell CRISPR screens. Cell 175, 1141–1155.e16 (2018).

    Google Scholar 

42. Baysoy, A. et al. Spatially resolved in vivo CRISPR screen sequencing via perturb-DBiT. bioRxiv https://doi.org/10.1101/2024.11.18.624106 (2024).

43. Saunders, R. A. et al. Perturb-Multimodal: A platform for pooled genetic screens with imaging and sequencing in intact mammalian tissue. Cell 188, 4790–4809.e22 (2025).

    Google Scholar 

44. Chen, K. H., Boettiger, A. N., Moffitt, J. R., Wang, S. & Zhuang, X. RNA imaging. Spatially resolved, highly multiplexed RNA profiling in single cells. Science (New York, N.Y.), 348, aaa6090 (2015).

45. He, S. et al. High-plex imaging of RNA and proteins at subcellular resolution in fixed tissue by spatial molecular imaging. Nat. Biotechnol. 40, 1794–1806 (2022).

    Google Scholar 

46. Bramlett, C. et al. Clonal tracking using embedded viral barcoding and high-throughput sequencing. Nat. Protoc. 15, 1436–1458 (2020).

    Google Scholar 

47. Kong, W. et al. CellTagging: combinatorial indexing to simultaneously map lineage and identity at single-cell resolution. Nat. Protoc. 15, 750–772 (2020).

    Google Scholar 

48. Jindal, K. et al. Single-cell lineage capture across genomic modalities with CellTag-multi reveals fate-specific gene regulatory changes. Nat. Biotechnol. 42, 946–959 (2024).

    Google Scholar 

49. Vieth, B., Ziegenhain, C., Parekh, S., Enard, W. & Hellmann, I. powsimR: power analysis for bulk and single cell RNA-seq experiments. Bioinformatics 33, 3486–3488 (2017).

    Google Scholar 

50. MacArthur, J. et al. The new NHGRI-EBI Catalog of published genome-wide association studies (GWAS Catalog). Nucleic Acids Res. 45, D896–D901 (2017).

    Google Scholar 

51. Chew, W. L. et al. A multifunctional AAV-CRISPR-Cas9 and its host response. Nat. Methods 13, 868–874 (2016).

    Google Scholar 

52. Goh, J. J. L. et al. Highly specific multiplexed RNA imaging in tissues with split-FISH. Nat. Methods 17, 689–693 (2020).

    Google Scholar 

53. Keng, C. T. et al. Multiplex viral tropism assay in complex cell populations with single-cell resolution. Gene Ther. 29, 555–565 (2022).

    Google Scholar 

54. Shen. K. spatialperturbseq (Version 1.0.0) [Computer Software]. Zenodo https://doi.org/10.5281/zenodo.17959756 (2025).

Download references

Authors and Affiliations

1. Genome Institute of Singapore (GIS), Agency for Science, Technology and Research (A*STAR), 60 Biopolis Street, Genome, Singapore, Republic of Singapore

   Kimberle Shen, Wan Yi Seow, Choong Tat Keng, Michelle Gek Liang Lim, Daryl Shern Lim, Ke Guo, Amine Meliani, Muhammad Irfan Bin Hajis, Bolun Wang, Shyam Prabhakar, Kok Hao Chen & Wei Leong Chew

2. Population and Global Health, Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Republic of Singapore

   Shyam Prabhakar

3. Cancer Science Institute of Singapore, National University of Singapore, Singapore, Republic of Singapore

   Shyam Prabhakar

4. Synthetic Biology Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Republic of Singapore

   Wei Leong Chew

Contributions

K.S., C.T.K. and W.L.C. conceived and conceptualized the technology framework. K.S., C.T.K., W.Y.S., K.H.C. and W.L.C. designed the experiments. K.S. did stereotaxic injections, tissue collection and processing. W.Y.S. performed the FISH experiments. M.G.L.L. processed slides for Xenium. S.P. provided intellectual contributions to Xenium experiments. D.L.S, C.T.K. and K.S. performed library cloning. D.L.S. and A.M. produced the AAVs. B.W. and C.T.K. prepared libraries for long-read sequencing of the 3xU6-sgRNA cassettes. M.I.B.H. and K.S. wrote the script for the generation of the barcodes. K.G. bred and maintained Cas9 mice. K.S. performed bioinformatics analysis. K.S., W.Y.S. and W.L.C. wrote the manuscript with contributions from the rest of the authors.

Corresponding author

Correspondence to Wei Leong Chew.

Competing interests

The authors (K.S., C.T.K., M.I.B.H., W.L.C., W.Y.S.) are listed as inventors on a patent application related to all of this work (Patent Cooperation Treaty Patent Application No. PCT/SG2025/050446). Applicant: A*STAR. The remaining authors declare no competing interests.

Peer review information

Nature Communications thanks Qi Liu and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. A peer review file is available.

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.

Reprints and permissions