Inferring gene regulatory networks from single-cell data

With this paper, we want to examine the role of single-cell technologies in inferring gene regulatory networks. Single-cell-based techniques make use of single cells as their main source of information, working by singularly analyzing cells and producing a deeper knowledge about their characteristics. Our interest is focused on sequencing techniques applicable to single cells, such as scRNA-seq and scATAC-seq. As inferable by these sequencing techniques, the elements of interest in this paper are the transcriptome and the epigenome. These omics can be used to investigate the elements controlling gene regulation which consequently can be used to reconstruct GRNs. The relationships between genes and their regulation are fundamental aspects in the comprehension of a cell’s life and response to stimuli. Usually, the already existent GRNs are obtained by measuring these elements in bulk cell populations rather than on single cells. This allowed the discovery of many GRNs despite the limitations derived from cell population heterogeneity. For this reason, we took interest in investigating the use of single-cell techniques in the building of GRNs, to determine what could arise from a deeper discernment of cells’ characteristics, and consequently from a keen understanding of cell subdivision. In order to do so we analyzed three articles from the literature, examining the innovative methods developed by researchers and the derived results. Each article tackles this topic through a different methodology, using either one or both of the sequencing techniques we have seen. Also, gene perturbation was considered to better study specific elements’ role in GRN. So, compared to bulk cell populations, the use of single cells grants us an innovative point of view when reconstructing this type of system due to the greater level of detail obtained from cells. These details revealed new GRNs regulating several processes while identifying the elements which differentiate one state from another.