Sensitive spatial genome wide expression profiling at cellular resolution
biorxiv(2020)
摘要
The precise spatial localization of molecular signals within tissues richly informs the mechanisms of tissue formation and function. Previously, we developed Slide-seq, a technology which enables transcriptome-wide measurements with 10-micron spatial resolution. Here, we report new modifications to Slide-seq library generation, bead synthesis, and array indexing that markedly improve the mRNA capture sensitivity of the technology, approaching the efficiency of droplet-based single-cell RNAseq techniques. We demonstrate how this modified protocol, which we have termed Slide-seqV2, can be used effectively in biological contexts where high detection sensitivity is important. First, we deploy Slide-seqV2 to identify new dendritically localized mRNAs in the mouse hippocampus. Second, we integrate the spatial information of Slide-seq data with single-cell trajectory analysis tools to characterize the spatiotemporal development of the mouse neocortex. The combination of near-cellular resolution and high transcript detection will enable broad utility of Slide-seq across many experimental contexts.
更多查看译文
关键词
resolution,spatial
AI 理解论文
溯源树
样例
![](https://originalfileserver.aminer.cn/sys/aminer/pubs/mrt_preview.jpeg)
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要