RNA velocity of single cells,Nature

当前位置： X-MOL 学术 › Nature › 论文详情

Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)

RNA velocity of single cells
Nature ( IF 50.5 ) Pub Date : 2018-08-01 , DOI: 10.1038/s41586-018-0414-6
Gioele La Manno _{1,

2} , Ruslan Soldatov ₃ , Amit Zeisel _{1,

2} , Emelie Braun _{1,

2} , Hannah Hochgerner _{1,

2} , Viktor Petukhov _{3,

4} , Katja Lidschreiber ₅ , Maria E Kastriti ₆ , Peter Lönnerberg _{1,

2} , Alessandro Furlan ₁ , Jean Fan ₃ , Lars E Borm _{1,

2} , Zehua Liu ₃ , David van Bruggen ₁ , Jimin Guo ₃ , Xiaoling He ₇ , Roger Barker ₇ , Erik Sundström ₈ , Gonçalo Castelo-Branco ₁ , Patrick Cramer _{5,

9} , Igor Adameyko ₆ , Sten Linnarsson _{1,

2} , Peter V Kharchenko _{3,

10}

Affiliation

Laboratory of Molecular Neurobiology, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden.
Science for Life Laboratory, Solna, Sweden.
Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA.
Department of Applied Mathematics, Peter The Great St. Petersburg Polytechnic University, St, Petersburg, Russia.
Department of Biosciences and Nutrition, Karolinska Institutet, Stockholm, Sweden.
Department of Physiology and Pharmacology, Karolinska Institutet, Stockholm, Sweden.
John van Geest Centre for Brain Repair, Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK.
Division of Neurodegeneration, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Stockholm, Sweden.
Max Planck Institute for Biophysical Chemistry, Department of Molecular Biology, Göttingen, Germany.
Harvard Stem Cell Institute, Cambridge, MA, USA.

RNA abundance is a powerful indicator of the state of individual cells. Single-cell RNA sequencing can reveal RNA abundance with high quantitative accuracy, sensitivity and throughput1. However, this approach captures only a static snapshot at a point in time, posing a challenge for the analysis of time-resolved phenomena such as embryogenesis or tissue regeneration. Here we show that RNA velocity—the time derivative of the gene expression state—can be directly estimated by distinguishing between unspliced and spliced mRNAs in common single-cell RNA sequencing protocols. RNA velocity is a high-dimensional vector that predicts the future state of individual cells on a timescale of hours. We validate its accuracy in the neural crest lineage, demonstrate its use on multiple published datasets and technical platforms, reveal the branching lineage tree of the developing mouse hippocampus, and examine the kinetics of transcription in human embryonic brain. We expect RNA velocity to greatly aid the analysis of developmental lineages and cellular dynamics, particularly in humans.RNA velocity, estimated in single cells by comparison of spliced and unspliced mRNA, is a good indicator of transcriptome dynamics and will provide a useful tool for analysis of developmental lineage.

中文翻译：

单细胞RNA速度

RNA 丰度是单个细胞状态的有力指标。单细胞 RNA 测序可以以高定量精度、灵敏度和通量揭示 RNA 丰度1。然而，这种方法仅捕获某个时间点的静态快照，这对分析胚胎发生或组织再生等时间分辨现象提出了挑战。在这里，我们表明，RNA 速度（基因表达状态的时间导数）可以通过区分常见单细胞 RNA 测序方案中未剪接和剪接的 mRNA 来直接估计。 RNA 速度是一种高维向量，可以预测单个细胞在数小时的时间尺度上的未来状态。我们验证了其在神经嵴谱系中的准确性，展示了其在多个已发表的数据集和技术平台上的用途，揭示了发育中的小鼠海马体的分支谱系树，并检查了人类胚胎大脑中的转录动力学。我们期望 RNA 速度能够极大地帮助分析发育谱系和细胞动力学，特别是在人类中。RNA 速度是通过比较剪接和未剪接 mRNA 在单细胞中估计的，是转录组动力学的良好指标，并将为分析提供有用的工具的发育谱系。

更新日期：2018-08-01

点击分享查看原文

点击收藏

公开下载

阅读更多本刊新发论文本刊介绍/投稿指南