Scalable spatial transcriptomics through computational array reconstruction

Chenlei Hu; Mehdi Borji; Giovanni J Marrero; Vipin Kumar; Jackson A Weir; Sachin V Kammula; Evan Z Macosko; Fei Chen

doi:10.1038/s41587-025-02612-0

Scalable spatial transcriptomics through computational array reconstruction

Nat Biotechnol. 2025 Apr 3. doi: 10.1038/s41587-025-02612-0. Online ahead of print.

Authors

Chenlei Hu^{1

2}, Mehdi Borji¹, Giovanni J Marrero¹, Vipin Kumar¹, Jackson A Weir^{1

3}, Sachin V Kammula¹, Evan Z Macosko^{1

4}, Fei Chen^{5

6}

Affiliations

¹ Broad Institute of Harvard and MIT, Cambridge, MA, USA.
² Department of Molecular and Cellular Biology, Harvard University, Cambridge, MA, USA.
³ Biological and Biomedical Sciences Program, Harvard University, Cambridge, MA, USA.
⁴ Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA.
⁵ Broad Institute of Harvard and MIT, Cambridge, MA, USA. chenf@broadinstitute.org.
⁶ Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA, USA. chenf@broadinstitute.org.

PMID: 40181168
DOI: 10.1038/s41587-025-02612-0

Abstract

Spatial transcriptomics enables gene expression mapping within tissues but is often limited by imaging constraints. We present an imaging-free approach that reconstructs spatial barcode locations using molecular diffusion and dimensionality reduction. Validated against ground truth imaging, our method achieves high fidelity and scales to centimeter-sized tissues. This approach enhances spatial transcriptomics' accessibility and throughput, enabling large-scale studies without specialized imaging equipment.

Abstract

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