Graph clustering as a method to investigate riboswitch variation

Abstract

Non-coding RNA (ncRNA) perform vital functions in cells, but the impact of diversity across structure and function of homologous motifs has yet to be fully investigated. One reason for this is that the standard phylogenetic analysis used to address these questions in proteins cannot easily be applied to ncRNA due to their inherent characteristics. Compared to proteins, ncRNA have shorter sequence lengths, lower sequence conservation, and secondary structures that need to be incorporated into the analysis. This has necessitated an effort to develop methodology for investigating the evolutionary and functional relationship between sets of ncRNA. In this pursuit, I studied closely related riboswitches. Riboswitches are structured ncRNA found in bacterial mRNA that regulate gene expressions using their two major components: the aptamer and the expression platform. The aptamer of a riboswitch is able to bind a specific small molecule (ligand), and the bound/unbound state of the aptamer influences conformational changes in the expressions platform that can lead to increased or decreased downstream gene expression. Utilizing sequence and structural similarity metrics combined with graph clustering and de novo community detection algorithms I have determined a methodology for investigating the functional and evolutionary relationship between closely related riboswitches, and other ncRNA by extension, that are found across a range of diverse phyla.