Computational Methods to Study Gene Regulation Using Genomic, Epigenomic and Chromosome Conformation Data

Transcriptional regulation in eukaryotes is the process in which different cells regulate the expression of genes. It is extremely complex and the adequate regulation of genes at precise times is what makes many cellular processes viable. Additionally, errors or disruptions in the transcriptional machinery can often compromise the livelihood of the cell or cause disease. In the past few years, novel genomic techniques have been developed to probe the regulatory mechanisms of genes. These techniques include next-generation sequencing, for example, to determine the exact location of DNA-bound regulatory proteins and sophisticated methylation arrays among others. Here we describe a set of computational methods that approach the process of gene regulation from three different research perspectives. Firstly, we explore the standard view of transcription factors binding directly to DNA to promote or repress the expression of genes. The understanding of transcription regulation is enhanced when considering how microRNAs regulate genes at a post-transcriptional phase. Secondly, we analyze how other epigenetic factors, such as DNA methylation, can affect gene expression. Thirdly, we delve into a more complex scenario within the nucleus of the cell where we consider gene regulation as the product, not only of epigenetics or acting transcription factors, but also of the three-dimensional conformation of chromosomes. The significance of our work is based on the fact that it provides an encompassing view of the complex nature of gene regulation. Because of constant advances in experimental genomics there is a need to develop new analysis methods to cope with the ever increasing volume of biological data that are generated. The deliverables from each of the research aims mentioned above will include, in addition to sound mathematical formulations of how to model the problems, a set of generic (executable) tools from which other researchers can benefit.