Defining the Parameters for Sorting of RNA Cargo Into Extracellular Vesicles

Extracellular vesicles (EVs) are small particles that are released by cells and mediate cell-cell communication by transferring bioactive molecules such as RNA. RNA cargo of EVs, including coding and non-coding RNAs, can change the behaviour of recipient cells, affecting processes including gene expression, proliferation, and Fapoptosis. CircRNAs are stable and resistant to degradation and have been shown to be enriched in EVs. They play key roles in gene regulation and are also emerging as promising biomarkers for disease diagnosis due to their stability and disease-specific expression. Although microRNAs (miRNAs) are the most well studied RNA cargo of EVs, very little is known about the mechanisms of enrichment of circular RNAs (circRNAs) as well as long linear RNAs. Here, we take a comprehensive genome-wide approach to investigate the role of structuredness and shape along with GC%, size, exon count and coding potential, in the sorting and enrichment of circular and long linear RNAs into EVs. We developed a model using these parameters to predict the likelihood of EV packaging of RNA and it was validated by using single molecule RNA imaging of EV bound RNAs. Furthermore, we found that structuredness could explain the relative enrichment of circRNAs over their linear counterparts. These results were validated on existing public databases of circular and linear RNAs in EVs. By identifying and analysing these factors, we aim to better understand the complex mechanisms behind EV-mediated RNA transfer and its impact on cell communication in both health and disease. This mechanistic understanding of RNA enrichment in EVs is crucial for engineering EVs with selective RNA cargo.