<xhtml:span xmlns:xhtml="http://www.w3.org/1999/xhtml" xml:lang="en">RNA Plasmids:&#160; The Bioinformatic Elucidation of a Novel Biomolecule Class of Environmental Genetic Element </xhtml:span>

Recent advances in nucleic acid sequencing technologies have identified new classes of molecules that allow organisms to share information. One such example is obelisks, a class of circular RNA present in cells without being encoded by host DNA. A defining feature of obelisks is that they contain a homolog of the Oblin-1 gene. Recently, additional types of RNA molecules that resemble obelisks without the inclusion of an Oblin-1 gene homolog have been reported. As such, we propose that obelisks represent a larger group of molecules we define as RNA plasmids that contain an obelisk-like structure, open reading frame(s), and behaviour more akin to plasmids. However, there is the possibility that these molecules are in fact artifacts of either library preparation or computational analyses. To provide evidence that RNA plasmids are not artifacts and bona fide nucleic acid structures within sequence datasets, we have engineered a novel bioinformatics pipeline capable of identifying novel RNA plasmids in existing metatranscriptomic short-read archive datasets. Unlike existing pipelines that search for obelisks using homology to the hypothetical obelisk protein Oblin-1, our pipeline utilizes a homology-agnostic approach, allowing identification of non-obelisk RNA plasmids. We provide evidence that these elements are circular and demonstrate their novelty by performing alignment against the entire NCBI database. We then provide support that these are not technical artifacts by analyzing how environmental variables, namely exposure to different human disease states and environmental conditions, affect their abundance. We analyze the composition of select RNA plasmids to better understand their biological relevance and how they may interact with both their host and the environment. The identification of RNA plasmids in multiple environmental datasets highlights the potential importance of this novel class of biomolecules in situ and significantly enhances our understanding of non-chromosomal genetic elements. ​