Regulatory complexity in gene expression - Rennie, Sarah (The University of Edinburgh, 2017)
The regulation of gene expression is the driver of cellular differentiation in multicellular organisms; the result is a diverse range of cell types each with their own unique profile of expression. Within these cell types the transcriptional product of a gene is up or down regulated in response to intrinsic and extrinsic stimuli according to its own regulatory programme encoded within the cell. The complexity of this regulatory programme depends on the requirements of the gene to change expression states in different cell lineages or temporally in response to a range of conditions. In the case of many housekeeping genes integral to the survival of the cell, this programme is simple - switch on the gene and leave it on, whereas often the required level and precision of regulatory control is much more involved and lends to subtle changes in expression. This raises many questions of precisely where and how that regulatory information is encoded and whether different biological systems encode it in the same way. This project attempts to answer these questions through the development of novel approaches in quantifying the output of this regulatory programme according to the state changes as observed from the expression profile of a given gene. Measures of complexity in gene expression are calculated over a wide range of cell types and conditions collected using CAGE, which provides a quantitative estimate of gene expression that precisely defines the promoter utilised to initiate that expression. As expected, housekeeping genes were found to be amongst the least complex, as a result of their uniform expression profiles, as well as those genes highly restricted in their expression. The genes most complex in their expression output were those associated with the presence of H3K27me3 repressive marks; genes poised for activation in a specific set of cell types, as well as those enriched in DNAse I hypersensitive sites in their upstream region but not necessarily conserved in that region. Evidence also suggests that different promoters associated with a gene contribute in different ways to its resultant regulatory complexity, suggesting that certain promoters may be more crucial in driving the regulation of some genes. This allows for the targeting of such promoters in the analysis of certain diseases implicated by changes in regulatory regions. Indeed, genes known to be associated with diseases such as leukaemia and Alzheimer’s are found to be highly complex in their expression.
Keywords: gene expression; complexity