瑞典卡罗林斯卡学院Rickard Sandberg课题组取得一项新突破。他们使用Smart-seq3在等位基因和同种型分辨率水平对单细胞RNA进行计数。这一研究成果于2020年5月4日在线发表在国际学术期刊《自然-生物技术》上。

研究人员开发了Smart-seq3，它结合全长转录组覆盖和5'独特分子识别RNA计数策略，该策略可实现对每个细胞数千个RNA分子进行计算机模拟重建。在计数和重建的分子中，有60％可以直接分配给等位基因来源；而30-50％可以分配给特定的同种型。

研究人员发现在小鼠不同品系和人细胞类型中，同种型的使用存在很大差异。与Smart-seq2相比，Smart-seq3大大提高了灵敏度，通常每个细胞检测数千个转录本。研究人员预计Smart-seq3能够对组织和生物体中的细胞类型和状态进行大规模表征。

据了解，对单个细胞进行大规模RNA测序可以揭示跨细胞类型和状态的基因、同种型和等位基因表达模式。但是，目前短读单细胞RNA测序方法在等位基因和同种型分辨率水平对RNA计数的能力有限，而长读测序技术则缺乏跨细胞大规模应用所需的深度。

附：英文原文

Title: Single-cell RNA counting at allele and isoform resolution using Smart-seq3

Author: Michael Hagemann-Jensen, Christoph Ziegenhain, Ping Chen, Daniel Ramskld, Gert-Jan Hendriks, Anton J. M. Larsson, Omid R. Faridani, Rickard Sandberg

Issue&Volume: 2020-05-04

Abstract: Large-scale sequencing of RNA from individual cells can reveal patterns of gene, isoform and allelic expression across cell types and states1. However, current short-read single-cell RNA-sequencing methods have limited ability to count RNAs at allele and isoform resolution, and long-read sequencing techniques lack the depth required for large-scale applications across cells2,3. Here we introduce Smart-seq3, which combines full-length transcriptome coverage with a 5′ unique molecular identifier RNA counting strategy that enables in silico reconstruction of thousands of RNA molecules per cell. Of the counted and reconstructed molecules, 60% could be directly assigned to allelic origin and 30–50% to specific isoforms, and we identified substantial differences in isoform usage in different mouse strains and human cell types. Smart-seq3 greatly increased sensitivity compared to Smart-seq2, typically detecting thousands more transcripts per cell. We expect that Smart-seq3 will enable large-scale characterization of cell types and states across tissues and organisms.

DOI: 10.1038/s41587-020-0497-0

Source: https://www.nature.com/articles/s41587-020-0497-0