Laboratory of Lymphocyte Biology, The Rockefeller University, New York, New York 10065, USA.
School of Mathematics and Statistics, University of Glasgow, Glasgow G12 8QW, UK.
Nat Commun. 2016 Jul 15;7:12145. doi: 10.1038/ncomms12145.
RNA editing is a mutational mechanism that specifically alters the nucleotide content in transcribed RNA. However, editing rates vary widely, and could result from equivalent editing amongst individual cells, or represent an average of variable editing within a population. Here we present a hierarchical Bayesian model that quantifies the variance of editing rates at specific sites using RNA-seq data from both single cells, and a cognate bulk sample to distinguish between these two possibilities. The model predicts high variance for specific edited sites in murine macrophages and dendritic cells, findings that we validated experimentally by using targeted amplification of specific editable transcripts from single cells. The model also predicts changes in variance in editing rates for specific sites in dendritic cells during the course of LPS stimulation. Our data demonstrate substantial variance in editing signatures amongst single cells, supporting the notion that RNA editing generates diversity within cellular populations.
RNA 编辑是一种突变机制，可特异性改变转录 RNA 中的核苷酸含量。然而，编辑率差异很大，可能是由于个体细胞中相同的编辑，或者代表群体内可变编辑的平均值。在这里，我们提出了一个层次贝叶斯模型，该模型使用来自单细胞和同源批量样本的 RNA-seq 数据来量化特定位点编辑率的方差，以区分这两种可能性。该模型预测了在小鼠巨噬细胞和树突状细胞中特定编辑位点的高方差，我们通过从单细胞中靶向扩增特定可编辑转录本的实验验证了这一发现。该模型还预测了在 LPS 刺激过程中树突状细胞中特定位点编辑率方差的变化。我们的数据表明，单细胞中的编辑特征存在大量差异，这支持了 RNA 编辑在细胞群体中产生多样性的观点。
