Application of spatial transcriptomics across organoids for a high-resolution, spatial whole-transcriptome benchmarking dataset.

Stem cell-derived organoids hold promise to model tissue-specific diseases. To enable this, it is crucial to assess how transcriptional signatures, cellular organization, and composition of organoids compare to in vivo counterparts. However, spatial transcriptomics has been challenging to apply to organoids to elucidate regional molecular identity. This study presents the first systematic profiling of multiple stem cell-derived organoid models (brain, heart muscle, heart valve, kidney, lung, cartilage, and hematopoietic) with stereo-seq, a full transcriptome, spatial assay using on-chip in situ RNA capture. It describes assay optimization for characterization, use of multiple organoid samples on a single chip, assesses limitations in RNA capture efficiency compared to reference tissues. Furthermore, it introduces a bespoke analysis method that partitions samples into regions for characterization. These findings inform future works to characterize organoids using spatial transcriptomics, providing insights into optimizing RNA capture of multiple organoids across a chip and regional analysis.