A novel algorithm for the collective integration of single cell RNA-seq during embryogenesis

Abstract

Single cell RNA-seq (scRNA-seq) over specified time periods has been widely used to dissect the cell populations during mammalian embryogenesis. Integrating such scRNA-seq data from different developmental stages and from different laboratories is critical to comprehensively define and understand the molecular dynamics and systematically reconstruct the lineage trajectories. Here, we describe a novel algorithm to integrate heterogenous temporal scRNA-seq datasets and to preserve the global developmental trajectories. We applied this algorithm and approach to integrate 3,387 single cells from seven heterogenous temporal scRNA-seq datasets, and reconstructed the cell atlas of early mouse cardiovascular development from E6.5 to E9.5. Using this integrated atlas, we identified an Etv2 downstream target, Ebf1, as an important transcription factor for mouse endothelial development.