Slide-seqV2可實現近細胞水平的高靈敏空間轉錄組學測序
作者：
小柯機器人發布時間：2020/12/9 13:16:42
哈佛大學和麻省理工學院Fei Chen和Evan Z. Macosko研究組合作的最新研究，介紹了可在近細胞解析度水平完成高靈敏空間轉錄組學的測序工具Slide-seqV2。這一研究成果於2020年12月7日發表在《自然-生物技術》上。
之前，該研究組開發了Slide-seq技術，該技術可實現全轉錄組範圍內RNA的檢測，其空間解析度為10μm。
在本研究中，研究人員研發了Slide-seqV2，它結合和改進了文庫生成、磁珠合成和陣列索引方面的功能，使RNA捕獲效率可達到單細胞RNA-seq的50％（比Slide-seq提高了約10倍），接近於液滴單細胞RNA-seq技術的檢測效率。
首先，研究人員利用Slide-seqV2檢測和識別了小鼠海馬神經元中樹狀定位的mRNA。其次，研究人員將Slide-seqV2數據的空間信息與單細胞軌跡分析工具整合在一起，以表徵小鼠新皮層的時空發育，從而可以鑑定出因Slide-seq採樣不足而遺漏的潛在遺傳程序。近細胞水平解析度和高轉錄本檢測效率的結合使Slide-seqV2在許多實驗中都大有可為。
研究人員介紹，測量組織中的分子位置對於了解組織形成和功能至關重要。
附：英文原文
Title: Highly sensitive spatial transcriptomics at near-cellular resolution with Slide-seqV2
Author: Robert R. Stickels, Evan Murray, Pawan Kumar, Jilong Li, Jamie L. Marshall, Daniela J. Di Bella, Paola Arlotta, Evan Z. Macosko, Fei Chen
Issue&Volume: 2020-12-07
Abstract: 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 10μm. 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.
DOI: 10.1038/s41587-020-0739-1
Source: https://www.nature.com/articles/s41587-020-0739-1