Gene Regulatory Network Reconstruction Using Single-Cell RNA-Sequencing

Abstract

Gene regulatory networks (GRNs) describe the relationship between transcription factors and their target genes, offering a platform to discover new pathways for complex diseases such as neurodegenerative diseases. These methods are usually based on gene expression experiments from transcriptomics studies. In recent years, at the molecular biology level, the emerging single-cell RNA-sequencing (scRNAseq) technology has revolutionized the way complex diseases are studied. This technology offers gene expressions for each cell separately, offering molecular information at a tremendous scale and resolution. In this chapter, the state-of-the-art GRN methods that are based on scRNAseq data are described, analyzed, and compared. These algorithms were applied to Alzheimer's Disease (AD), showing that current GRN methods have displayed an essential contribution; however, as the scRNAseq data increases, the need for novel GRN tools able to cope with the challenges of various complex diseases such as AD arises.