A Multiplexed Barcodelet Single-Cell RNA-Seq Approach Elucidates Combinatorial Signaling Pathways that Drive ESC Differentiation

Abstract

Empirical optimization of stem cell differentiation protocols is time consuming, is laborintensive, and typically does not comprehensively interrogate all relevant signaling pathways. Here we describe barcodelet single-cell RNA sequencing (barRNA-seq), which enables systematic exploration of cellular perturbations by tagging individual cells with RNA "barcodelets" to identify them on the basis of the treatments they receive. We apply barRNA-seq to simultaneously manipulate up to seven developmental pathways and study effects on embryonic stem cell (ESC) germ layer specification and mesodermal specification, uncovering combinatorial effects of signaling pathway activation on gene expression. We further develop a data-driven framework for identifying combinatorial signaling perturbations that drive cells toward specific fates, including several annotated in an existing scRNA-seq gastrulation atlas, and use this approach to guide ESC differentiation into a notochord-like population. We expect that barRNA-seq will have broad utility for investigating and understanding how cooperative signaling pathways drive cell fate acquisition.

Keywords: computational modeling; directed differentiation; embryonic development; embryonic stem cell; single cell RNA-seq.