Sequencing-based Spatial Transcriptomics with scRNA-seq Sensitivity
Liao, R.; Fu, D.; Xu, Z.; Liang, H.; Zhou, X.; Chen, Y.; Liu, X.; Cheng, J.; Guo, R.; Li, C.; Xia, H.; Li, G.; Feng, D.; Chen, W.; Chen, Y.; Chen, L.; Huang, Z.; Zhou, Y.; Chen, Q.; Chen, D.; Xuan, S.; Zhang, C.; Lu, Y.; Wang, H.; Feng, T.; Bao, Y.; Zhao, L.; Liu, E.; Wang, G.
Show abstract
The advent of spatial transcriptomics has dramatically expanded our ability to study the vast network of cell-cell interactions at the molecular level in tissue. Among current methods, sequencing-based approaches have great potential in discovering because of its unbiased capture. In the last couple of years, the spatial resolution for the capture addresses has been significantly improved from 100 m to <1 m, well below the size of a mammalian cell. However, the capture efficiency has always been a pain point, [~]one order of magnitude lower than that of single cell RNA sequencing (scRNA-seq). The low capture efficiency limits the depth and breadth of its applications in the study of complex biological systems and diseases. Here, we introduce Salus Spatial transcriptomic system (Salus-STS), which provides [~]1 m capture resolution and a capture efficiency [~]1 order of magnitude higher than other current methods. Analysis with sub-cellular resolution becomes practical for sequencing-based spatial transcriptomics.
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