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Spatially tuneable multi-omics sequencing using light-driven combinatorial barcoding of molecules in tissues / Multiomic

GSE260694 Mus musculus Genome binding/occupancy profiling by high throughput sequencing; Expression profiling by high throughput sequencing 6 samples Submitted 2026/06/03 Platform GPL24247
Summary
Mapping the molecular identities and functions of cells alongside their spatial tissue context is key to understanding the complex interplay within and between their tissue neighbourhoods. A wide range of methods enable spatial profiling of regions, some down to the level of individual cells, in their anatomical context, via different barcoding schemes that 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 multi-omics profiling by next generation sequencing. A unique feature of BALI is that the user can define the number, size, and shape of the spatial locations to be interrogated, with the potential to profile millions of distinct regions down to subcellular scale. As a proof of concept, we used BALI to capture the transcriptome, chromatin accessibility, or both, from distinct areas of the mouse brain in single tissue sections, demonstrating strong concordance with publicly available datasets. BALI therefore combines high spatial resolution, high throughput, histological adaptability, and workflow accessibility to enable powerful spatial multi-omics profiling.
Published in
Spatially tunable multiomic sequencing using light-driven combinatorial barcoding of molecules in tissues
Battistoni G, Torres-Garcia S, Sia CY et al. · Proceedings of the National Academy of Sciences of the United States of America 2026 · PMID 42150070 · doi:10.1073/pnas.2527896123
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Direct links to NCBI, no account and no request form: the whole study as GSE260694_RAW.tar, processed values as the series matrix, the supplementary file directory, and per-sample supplementary files for any of the 6 samples. Raw sequencing reads are also available from ENA.

Also filed as BioProject PRJNA1082720. Searching any of these in the dataset finder brings you back here.

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