GENE REGULATORY NETWORK ANALYSIS IN STEM CELL DIFFERENTIATION USING INTEGRATIVE OMICS APPROACHES

Abstract

Stem cell differentiation is a highly controlled biological phenomenon that is mediated by elaborate system of gene regulatory networks (GRNs). It requires multi-layered regulatory patterns that cannot be adequately captured using conventional single-omics. Indeed, in the given research, an integrative omics model was created to examine GRNs in stem cell differentiation as a synthesis of transcriptomic (RNA-seq) and epigenomic (DNA methylation) data, accessible on the Gene Expression Omnibus (GEO) database. DESEQ2 was used to analyse differences in gene expression between the undifferentiated cells and the differentiated cells to discover the genes significantly regulated by the analysis. This was followed by weighted analysis of gene co-expression network (WGCNA), to create coherent clusters of genes and identify important regulatory clusters linked to the differentiation. The hub genes were discovered using network topology measures, such as intramodular connectedness and centrality of the degree. The results of functional enrichment analysis done through Gene Ontology (GO) and Kyoto Encyclopaedia of Genes and Genomes (KEGG), indicate that the identified modules are closely connected with signalling pathways, transcriptional regulation, and cellular differentiation processes. The integrative analysis revealed important regulatory genes and network interrelationships that can be potential biomarkers or targets of therapy. On the whole, this paper has shown that the multi-omics integration with network-based modelling is a powerful concept that can be used to understand the molecular pathways that regulate stem cell differentiation.