Differential Network Analysis Reveals Regulatory Patterns in Neural Stem Cell Fate Decision

Background: Neural stem cell (NSC) differentiation is one of many multi-stage lineage systems that require multiple cell fate decisions. Recent single-cell transcriptome datasets became available at individual differentiation, however, a systematic and integrative analysis of multiple datasets at multiple temporal points of NSC differentiation is lacking. Results Here we investigate five NSC differentiation paths by analyzing and comparing four different single-cell transcriptome datasets. By constructing gene regulatory networks for each cell type, we delineate their regulatory patterns via analyses of differential topology and network diffusion. Among the five NSC differentiation paths, we find 12 common differentially expressed genes, with one common three-gene regulatory pattern shared by all paths. The identified regulatory pattern, partly supported by previous experimental evidence, is found to be essential to all differentiation paths, however, plays a different role in each path when regulating other genes. Conclusions Together, our integrative analysis provides both common and specific regulatory mechanisms for each of the five NSC differentiation paths, and the approach can be applied to analyzing other complex multi-stage lineage systems.