The most well-studied RNA molecular structures, notably tRNA and rRNA, exist as a single dominant conformation. However, a growing number of small non-coding RNA sequences are known to function by switching between multiple stable configurations. It is expected that such multi modal structural motifs punctuate the ensemble of low-energy structures for an RNA viral genome like Chikungunya, regulating the viral lifecycle. Characterizing these small overlapping sets of stable base pairs, embedded in lengthy sequences with high structural diversity, is essential to understanding how critical structural signals encode the functionality of these important pathogens. This collaboration leverages complementary strengths of previous results --- mining competing signals from the structural ensemble (profiling) and next generation chemical footprinting (SHAPE-MaP) --- to tackle the challenge of multi modal motif discovery in a test set of three alphavirus genomes.
This first aim will be achieved by developing the necessary characterizations of profiling landscapes and of SHAPE-MaP signatures to identify target regions with multiple native conformations. These separate results will be validated in individual sequences by the combination of SHAPE-directed profiling, following experimental confirmation of the current prediction methodology.
The second aim will demonstrate evolutionary support for these new motifs, first across the three test sequences and then the entire alphaviral family, through a new application of computational algebraic topology. Persistent homology and simplicial complexes will be used to analyze evolution across the different scales at which biological information is encoded in RNA viral genomes, ranging from genomic sequence to vertebrate host. This will be followed by chemical probing confirmation for three additional alphavirus sequences. This project will extend the frontiers of RNA folding by integrating new mathematical models and analyses based on combinatorics and algebraic topology with recent advances in the biochemistry of chemical footprinting for the purposes of identifying significant motifs with multimodal structure in lengthy RNA viral genomes. The results of this study, a set of novel secondary structure motifs in alphavirus genomes which are ideal candidates for further investigation as important functional elements, will be a key resource for RNA virologists. Furthermore, the proposed theoretical and algorithmic developments are generally applicable to all RNA viruses, and hence of significant utility and interest to the scientific community.
This is a new cross-disciplinary collaboration between a mathematician and a biologist with convergent interests in RNA sequences with multiple native conformations. It is the first study to integrate theory, computation, and experiment to identify and validate multi-structured functional motifs across a viral genome family. Focusing on these positive-stranded RNA viruses is timely and appropriate given ongoing outbreaks including Chikungunya.
| Kutchko, Katrina M; Madden, Emily A; Morrison, Clayton et al. (2018) Structural divergence creates new functional features in alphavirus genomes. Nucleic Acids Res 46:3657-3670 |
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| Woods, Chanin T; Lackey, Lela; Williams, Benfeard et al. (2017) Comparative Visualization of the RNA Suboptimal Conformational Ensemble In Vivo. Biophys J 113:290-301 |
| Woods, Chanin Tolson; Laederach, Alain (2017) Classification of RNA structure change by 'gazing' at experimental data. Bioinformatics 33:1647-1655 |
