Intracellular and intercellular gene regulatory networks inference from time-course individual RNA-Seq

Abstract

Motivation: Recent technical advances in bulk RNA-Seq have enabled time-course RNA-Seq of whole individual embryos to understand the underlying molecular mechanisms. Thus, we hypothesized that gene regulatory networks (GRNs) inferred from time-course individual RNA-Seq during embryonic development reveal intercellular regulatory relationships involved in signaling pathways. Results: Time-course bulk RNA-Seq of individual mouse embryos in early development, followed by pseudo-time analysis and GRN inference, demonstrated that GRN inference from RNA-Seq with pseudo-time can be applied for individual bulk RNA-Seq similar to scRNA-Seq. Validation using an experimental-source-based database showed that our approach could significantly infer GRN for all transcription factors in the database. Furthermore, the inferred ligand-related and receptor-related downstream genes were significantly overlapped. Overall, the inferred GRN include intracellular as well as intercellular regulatory relationships, which cannot be inferred from scRNA-Seq. Thus, inferring GRN from time-course bulk RNA-Seq is a novel approach for understanding the regulatory relationships underlying cellular events.