An integrated cell barcoding and computational analysis pipeline for scalable analysis of differentiation at single-cell resolution

Abstract: This study develops a versatile cell multiplexing and data analysis platform to accelerate knowledge gain into mechanisms of cell differentiation. We engineer a cell barcoding system in human cells enabling multiplexed single-cell RNA sequencing for high throughput perturbation of customisable and versatile experimental conditions. This is coupled with a new computational analysis pipeline that overcomes the limitations of existing algorithms by using an unsupervised, genome-wide, orthogonal biological reference point to reveal the cell diversity and regulatory networks of any input scRNA-seq data set. We implement this pipeline by engineering transcribed barcodes into induced pluripotent stem cells and multiplex 62 independent experimental conditions comprising eight differentiation time points and nine developmental signalling perturbations with duplicates. We identify and deconstruct the temporal, signalling, and gene regulatory basis of multilineage iPSC differentiation into ectoderm, mesoderm, and endoderm cell types. This study provides a cellular and computational pipeline to study cell differentiation applicable to diverse fields of developmental biology, drug discovery, and disease modelling.