Poster abstracts
Poster number 80 submitted by Kobie Kirven
SPARCS: A Modular, Containerized, and Scalable Pipeline for Genome-Wide RiboSNitch Prediction
Kobie J. Kirven (Graduate Program in Bioinformatics and Genomics, Center for RNA Molecular Biology, Pennsylvania State University, University Park, Pennsylvania, USA .), Gabriela R. Hohenwarter (Department of Chemistry, Pennsylvania State University, University Park, Pennsylvania, USA.), Philip C. Bevilacqua (Department of Chemistry, Center for RNA Molecular Biology, Pennsylvania State University, University Park, Pennsylvania, USA.), Sarah M. Assmann (Department of Biology, Center for RNA Molecular Biology, Pennsylvania State University, University Park, Pennsylvania, USA.)
Abstract:
Rather than adopting a single structure, many RNAs populate ensembles of structures. Some single-nucleotide polymorphisms (SNPs), known as riboSNitches, alter the free-energy landscape of an RNA, affecting its ensemble of secondary structures. While several computational tools are available for predicting whether a SNP is a riboSNitch, they are generally developed to analyze RNAs one at a time and are not optimized for genome-wide analysis. To fill this gap, we developed SPARCS, a modular, containerized, and automated pipeline for genome-wide riboSNitch prediction. SPARCS is built using the Snakemake framework, allowing for automatic dependency handling and the ability to be run locally or scaled on a high-performance cluster. We used SPARCS to analyze publicly available population variant datasets from Ensembl for several organisms. We find synonymous mutations and SNPs at the third codon position are consistently depleted in predicted riboSNitches whereas missense mutations are enriched in riboSNitches. Additionally, we observe a significant increase in riboSNitches immediately downstream of the start codon, consistent across all organisms included in our analysis. SPARCS is freely available at https://github.com/The-Bevilacqua-Lab/SPARCS.
Keywords: RiboSNitch, Pipeline, Snakemake