Integrative nascent RNA methods to reveal cell-type specific transcription programs in peripheral blood and its derivative cells

Abstract Nascent RNA sequencing is a powerful method to measure transcription with high resolution, sensitivity, and directional information. We present an integrated package of nascent RNA-seq methods composed of ultrafast Precision Run On (uPRO) combined with deep learning and hierarchical co-expression network analysis to discover enhancers, promoters, and transcription factor networks that define cell-type specific transcription programs. We generated nascent transcription profiles using one-day uPRO in human blood-derived cell lines and raw whole blood of ~ 1 ml. Transcription sites at enhancers and genes were conserved in positions but varied in expression levels across cell types. Transcription factors such as TCF-3 and OCT1 were pivotally associated with enhancer-gene networks. Intriguingly, transcription factors related to cell stress and inflammation are associated with inter-individual variation of leukocyte transcription in whole blood. Our integration of experimental and computational nascent RNA methods will provide an efficient strategy to identify specific transcriptional programs with minimal sample requirements.