RNA editing is a molecular clock in unmodified human cells

Abstract

Despite major advances in spatial RNA sequencing, the ability to extract temporal information in RNA sequencing experiments is still limited. Here, we describe Transcriptome Timestamping (T2), a system which harnesses naturally occurring A-to-I editing of RNA transcripts in unmodified human cells to infer transcriptional history. T2 provides age estimates for individual RNA transcripts, and serves as an endogenous molecular recorder, differentiating between complex transcriptional programs. We show that T2 can identify transient and transitional transcriptional programs in primary differentiating monocytes that are not apparent from gene expression analysis alone, including a regulatory module in the monocyte-to-macrophage transition that, to our knowledge, has not yet been described in humans. Finally, we show that T2 can also be applied to single cell data, allowing us to identify transcriptional programs in heterogeneous populations, such as asynchronously dividing cells. T2 is a scalable approach to temporal transcriptomics that can be applied to track the activity of thousands of genes in unmodified, primary human cells and tissues, with no genetic engineering.