Spatially tunable multiomic sequencing using light-driven combinatorial barcoding of molecules in tissues.

Overview

1. Cancer Research UK Cambridge Institute, University of Cambridge, Li Ka Shing Centre, Robinson Way, Cambridge CB2 0RE, United Kingdom
2. Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge CB2 1EW, United Kingdom

Abstract

Mapping the molecular identities and functions of cells within their spatial context is key to understanding the complex interplay within and between tissue neighborhoods. A wide range of methods have recently enabled spatial profiling of cellular anatomical contexts, some offering single-cell resolution. These use different barcoding schemes to encode either the location or the identity of target molecules. However, all these technologies face a trade-off between spatial resolution, depth of profiling, and scalability. Here, we present Barcoding by Activated Linkage of Indexes (BALI), a method that uses light to write combinatorial spatial molecular barcodes directly onto target molecules in situ, enabling multiomic profiling by next generation sequencing. A unique feature of BALI is that the user can define the number, size, shape, and resolution of the spatial locations to be interrogated, with the potential to profile millions of distinct regions with subcellular precision. As a proof of concept, we used BALI to capture the transcriptome, chromatin accessibility, or both simultaneously, from distinct areas of the mouse brain in single tissue sections, demonstrating strong concordance with publicly available datasets. We also developed an integrated instrument that automates combinatorial barcode writing on tissue sections, enabling high-throughput profiling. BALI therefore combines high spatial resolution, high throughput, compatibility with standard histological pipelines, and workflow accessibility to enable tunable spatial multi-omic profiling.

Reproduced under the paper's license (CC BY), from the paper cited above.

Code

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Data

Datasets cited

• geo:GSE260699, at NCBI GEO; found in “Data, Materials, and Software Availability”

Data, Materials, and Software Availability

All the sequencing data are available through GEO (accession no. GSE260699 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE260699)) (62). Raw images and non sequencing data are available from the authors upon request. The scripts used for analysis and data processing are available from the authors upon request. Similarly, the LightScribe software is available from the authors upon request.

Reproduced under the paper's license (CC BY), from the paper cited above.

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Version 1, 28 September 2026: the first record

Recorded: type, language, journal, volume, issue, pages, dates, 15 authors, 3 keywords, 9 MeSH terms, 5 funders, 58 references.

Cite

This paper

Battistoni, G., Torres-Garcia, S., Sia, C. Y., Corriero, S., Boquetale, C., Williams, E., Cregeen, A., Wasilewska, K., Alini, M., Hemmer, N., IMAXT Cancer Grand Challenge Consortium, Balasubramanian, S., Nicholson, B. C., Hannon, G. J., & Bressan, D. (2026). Spatially tunable multiomic sequencing using light-driven combinatorial barcoding of molecules in tissues. Proceedings of the National Academy of Sciences of the United States of America, 123(21), e2527896123. https://doi.org/10.1073/pnas.2527896123

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