• An Intersection of Computational Biology and Functional Genomics to identify Transcriptional Gene Enhancers and Their Role in Cancer

      Aslam Khattak, Naureen; Gonser, Rusty Allen (Indiana State University, 2022)
      Despite the critical role of gene regulation in cell development and differentiation, the major challenge remains to identify the cis-regulatory modules (CRMs). Mainly, these CRMs include enhancers, promoters and insulators that governs the spatiotemporal gene regulation. The gene regulatory networks are highly dependent on their CRMs and mostly consist of DNA motifs and epigenetic landmarks. The recent advancements in high-throughput sequencing techniques and comparative genomics analysis accelerate the discovery of enhancers, however the major obstacles are to identify the genome-wide location of these CRMs, their dynamic nature of interactions, and cis/trans location which could be hundred to thousands base pairs away from the target gene location. The goal of this literature review is to provide an insight into the CRMs specifically enhancers, how they modulate gene expression, mutations that converts normal cell into a disease-state such as cancer. Also, this embedded review article is focused on the use of computational strategies coupled with the biochemical assays to predict functional gene enhancers. The computational strategies such as window clustering, probabilistic modeling, phylogenetic footprinting and discriminative modeling are briefly discussed to scan and locate the putative gene enhancers. Besides theses, biochemical techniques such as ChIP-seq, DNA footprinting, and deletion mapping are briefly reviewed in Drosophila to predict functional gene enhancers and dissecting gene regulatory networks. In addition, this review article may help bench scientists to incorporate bioinformatics tools with biochemical techniques to scan, locate and verify gene enhancer regions within a cell. With best of our knowledge, this is a first-time effort to combine insilico, in vitro and in vivo techniques to explore the connections between CRMs and gene regulation.