MOSTA: Mouse Organogenesis Spatiotemporal Transcriptomic Atlas
Dataset ID: STDS0000058
351,014 Spots
28,879 Genes


Dataset information
We have only begun to scratch the surface in understanding mammalian development. An overwhelming caveat is the lack of topographical transcriptomic information to correlate signaling cues and cell-cell interactions within the hierarchy of cell fate decisions. Spatially resolved transcriptomic technologies are promising tools to fill this gap. However, the small field of view and imbalance between resolution and transcript capture of current methodologies precludes their systematic application to study relatively large and multilayered embryos. Here, we have combined DNA nanoball (DNB) patterned arrays and in situ RNA capture to create SpaTial Enhanced REsolution Omics-sequencing (Stereo-seq). This approach allows transcriptomic profiling of large histological sections with high resolution, sensitivity, and reproducibility. We have applied Stereo-seq to study the kinetics of transcriptional variation, the networks of transcription factor binding events and their relationship with morphogens across spatial domains of gene expression in a time course of mouse organogenesis. We have used this information to detect the emergence of tissue-specific cell identities such as early neuroblast populations in the late neural tube stage or the gradients of neuronal specification in the neocortex. Furthermore, we have mapped the expression of a panel of developmental disease-related loci to define the spatiotemporal windows of tissue vulnerability. Our panoramic atlas constitutes a essential resource to investigate longstanding questions concerning the molecular basis of normal and abnormal mammalian development.
Mus musculus(mm10)
Chen, Ao et al. “Spatiotemporal transcriptomic atlas of mouse organogenesis using DNA nanoball-patterned arrays.” Cell vol. 185,10 (2022): 1777-1792.e21. doi:10.1016/j.cell.2022.04.003
Submission date: 2021-10-22Update date: 2021-10-22
Sample number: 16Section number: 6

No results.

Project ID: CNP0001543
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