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May 9th, 2025
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Stem Cell Medicine Theme, Murdoch Childrens Research Institute, Parkville, VIC, Australia; The Novo Nordisk Foundation Center for Stem Cell Medicine, reNEW Melb
bioinformatics
biorxiv

Application of spatial transcriptomics across organoids: a high-resolution spatial whole-transcriptome benchmarking dataset

Nucera, M. R. R.Open in Google Scholar•Charitakis, N.Open in Google Scholar•Leung, R.Open in Google Scholar•Leichter, A.Open in Google Scholar•Tuano, N.Open in Google Scholar•Walkiewicz, M.Open in Google Scholar•Sawant, V.Open in Google Scholar•Rowley, L.Open in Google Scholar•Scurr, M.Open in Google Scholar•Er, P.Open in Google Scholaret al.

Stem cell-derived organoid models hold great promise to model tissue-specific disease. To enable this, it is crucial to determine how their composition compares to endogenous organs. However, technologies such as spatial transcriptomics (STs) that can inform on regional molecular identity have been challenging to apply to organoids. Here we present the first systematic profiling of multiple organoids (brain, heart muscle,heart valve, kidney, lung, cartilage, and blood) using Stereo-seq. We describe the optimisation of ST with multiple organoids on a single chip. We reveal differences in data capture efficiency compared to reference tissues hindering traditional downstream analyses. To overcome such challenges, we developed a bespoke regional analysis method to enable detection of transcriptional changes. Together, these developments form a platform to inform future work to investigate organoids using ST, both in terms of optimising data capture of multiple organoids across a chip and novel methods for regional analysis of organoids.

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