利用 Slide-seqV2 实现近细胞分辨率的超高灵敏空间转录组学
Highly sensitive spatial transcriptomics at near-cellular resolution with Slide-seqV2.
机构信息
Broad Institute of Harvard and MIT, Cambridge, MA, USA.
Graduate School of Arts and Sciences, Harvard University, Cambridge, MA, USA.
出版信息
Nat Biotechnol. 2021 Mar;39(3):313-319. doi: 10.1038/s41587-020-0739-1. Epub 2020 Dec 7.
Measurement of the location of molecules in tissues is essential for understanding tissue formation and function. Previously, we developed Slide-seq, a technology that enables transcriptome-wide detection of RNAs with a spatial resolution of 10 μm. Here we report Slide-seqV2, which combines improvements in library generation, bead synthesis and array indexing to reach an RNA capture efficiency 50% that of single-cell RNA-seq data (10-fold greater than Slide-seq), approaching the detection efficiency of droplet-based single-cell RNA-seq techniques. First, we leverage the detection efficiency of Slide-seqV2 to identify dendritically localized mRNAs in neurons of the mouse hippocampus. Second, we integrate the spatial information of Slide-seqV2 data with single-cell trajectory analysis tools to characterize the spatiotemporal development of the mouse neocortex, identifying underlying genetic programs that were poorly sampled with Slide-seq. The combination of near-cellular resolution and high transcript detection efficiency makes Slide-seqV2 useful across many experimental contexts.
测量组织中分子的位置对于理解组织形成和功能至关重要。此前，我们开发了 Slide-seq，这是一种能够以 10 μm 的空间分辨率检测转录组范围内 RNA 的技术。在这里，我们报告了 Slide-seqV2，它结合了文库生成、珠子合成和阵列索引方面的改进，达到了约 50%的 RNA 捕获效率，与单细胞 RNA-seq 数据相当（比 Slide-seq 高 10 倍），接近基于液滴的单细胞 RNA-seq 技术的检测效率。首先，我们利用 Slide-seqV2 的检测效率来鉴定小鼠海马体神经元中树突定位的 mRNAs。其次，我们将 Slide-seqV2 数据的空间信息与单细胞轨迹分析工具相结合，以描述小鼠新皮层的时空发育，确定了使用 Slide-seq 难以采样的潜在遗传程序。接近细胞分辨率和高转录检测效率的结合使得 Slide-seqV2 在许多实验环境中都非常有用。
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