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bioRxiv · 10.64898/2026.08.30.748061

Kintsugi maps nucleus-poor RNA compartments in subcellular spatial transcriptomics

Yang, C.·Zhang, X.·Chen, J.
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Abstract

Subcellular spatial transcriptomics captures where RNA is in tissue, but a single location holds too few molecules of any one gene to estimate composition alone. Every current method fixes in advance where to borrow -- a smoothing scale, a cell outline or a factor model -- and the fixed choice shapes what is visible. Kintsugi removes the fixed choice and lets held-out molecules decide, gene by gene, how much to borrow from spatial neighbours and from other genes at the same location. On a lung section measured by both Xenium and Visium HD, the data-chosen allocation placed an epithelial programme where the Xenium molecules were, ahead of smoothing, cell segmentation and a factor model; the result replicated across tissues and against protein. Across a 45-core pulmonary fibrosis cohort, separating composition from captured amount shows that a fibroblastic focus is not a place with more RNA but a place with different RNA: 2.8-fold higher in activated-fibroblast composition while segmented nuclear density is at most 1.08-fold higher.

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Yang, C., Zhang, X., Chen, J.. 2026-09-03. Kintsugi maps nucleus-poor RNA compartments in subcellular spatial transcriptomics. https://doi.org/10.64898/2026.08.30.748061

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