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1. Y RNA and Y RNA-derived ysRNA associations with viral pathogens

   https://doi.org/10.3389/frnar.2025.1679653  

   Olliff, Nathaniel S; Mabien, Alexandria A; Cole, Grayson M; Borchert, Glen M (September 2025, Frontiers in RNA Research)

   Y RNAs are a poorly-studied class of small non-coding RNAs (sncRNAs) which have previously been implicated in the pathogenesis of different human diseases, including cardiac and autoimmune conditions, as well as certain cancers. In recent years, however, multiple studies have reported correlations between Y RNA expressions and disease outcomes in viral infections (e.g., IAV, HIV, HPV, and SARS-CoV-2) as well as potential mechanistic roles that Y RNAs may play in host anti-viral defense. These studies suggest that Y RNAs may be associated with upregulation of viral defense proteins as well as altered cell-cell communication during viral infections. In this review, current literature detailing Y RNA effects on human viral infection will be summarized and future directions in the study of these relationships discussed. 

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2. Switchable RNA motifs for dynamic transcriptional control of RNA condensates

   https://doi.org/10.1093/nar/gkaf497  

   Tang, Anli A.; Gobry, Martin Vincent; Li, Shiyi; Andersen, Ebbe Sloth; Franco, Elisa (June 2025, Nucleic Acids Research)

   Abstract RNA-driven phase separation is emerging as a promising approach for engineering biomolecular condensates with diverse functionalities. Condensates form thanks to weak yet specific RNA–RNA interactions established by design via complementary sequence domains. Here, we demonstrate how RNA condensates formed by star-shaped RNA motifs, or nanostars, can be dynamically controlled when the motifs include additional linear or branch-loop domains that facilitate access of regulatory RNA molecules to the nanostar interaction domains. We show that condensates dissolve in the presence of RNA “invaders” that occlude selected nanostar bonds and reduce the valency of the nanostars, preventing phase separation. We further demonstrate that the introduction of “anti-invader” strands, complementary to the invaders, makes it possible to restore condensate formation. An important aspect of our experiments is that we demonstrate these behaviors in one-pot reactions, where RNA nanostars, invaders, and anti-invaders are simultaneously transcribed in vitro using short DNA templates. Our results lay the groundwork for engineering RNA-based assemblies with tunable, reversible condensation, providing a promising toolkit for synthetic biology applications requiring responsive, self-organizing biomolecular materials. 

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3. RNA-clique: a method for computing genetic distances from RNA-seq data

   https://doi.org/10.1186/s12859-024-05811-9  

   Tapia, Andrew_C; Jaromczyk, Jerzy_W; Moore, Neil; Schardl, Christopher_L (June 2024, BMC Bioinformatics)

   Abstract BackgroundAlthough RNA-seq data are traditionally used for quantifying gene expression levels, the same data could be useful in an integrated approach to compute genetic distances as well. Challenges to using mRNA sequences for computing genetic distances include the relatively high conservation of coding sequences and the presence of paralogous and, in some species, homeologous genes. ResultsWe developed a new computational method, RNA-clique, for calculating genetic distances using assembled RNA-seq data and assessed the efficacy of the method using biological and simulated data. The method employs reciprocal BLASTn followed by graph-based filtering to ensure that only orthologous genes are compared. Each vertex in the graph constructed for filtering represents a gene in a specific sample under comparison, and an edge connects a pair of vertices if the genes they represent are best matches for each other in their respective samples. The distance computation is a function of the BLAST alignment statistics and the constructed graph and incorporates only those genes that are present in some complete connected component of this graph. As a biological testbed we used RNA-seq data of tall fescue (Lolium arundinaceum), an allohexaploid plant ($$2n = 14\text { Gb}$$ $2n=14\text{Gb}$), and bluehead wrasse (Thalassoma bifasciatum), a teleost fish. RNA-clique reliably distinguished individual tall fescue plants by genotype and distinguished bluehead wrasse RNA-seq samples by individual. In tests with simulated RNA-seq data, the ground truth phylogeny was accurately recovered from the computed distances. Moreover, tests of the algorithm parameters indicated that, even with stringent filtering for orthologs, sufficient sequence data were retained for the distance computations. Although comparisons with an alternative method revealed that RNA-clique has relatively high time and memory requirements, the comparisons also showed that RNA-clique’s results were at least as reliable as the alternative’s for tall fescue data and were much more reliable for the bluehead wrasse data. ConclusionResults of this work indicate that RNA-clique works well as a way of deriving genetic distances from RNA-seq data, thus providing a methodological integration of functional and genetic diversity studies. 

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4. Improved modeling of RNA-binding protein motifs in an interpretable neural model of RNA splicing

   https://doi.org/10.1186/s13059-023-03162-x  

   Gupta, Kavi; Yang, Chenxi; McCue, Kayla; Bastani, Osbert; Sharp, Phillip A.; Burge, Christopher B.; Solar-Lezama, Armando (January 2024, Genome Biology)

   Abstract Sequence-specific RNA-binding proteins (RBPs) play central roles in splicing decisions. Here, we describe a modular splicing architecture that leverages in vitro-derived RNA affinity models for 79 human RBPs and the annotated human genome to produce improved models of RBP binding and activity. Binding and activity are modeled by separate Motif and Aggregator components that can be mixed and matched, enforcing sparsity to improve interpretability. Training a new Adjusted Motif (AM) architecture on the splicing task not only yields better splicing predictions but also improves prediction of RBP-binding sites in vivo and of splicing activity, assessed using independent data. 

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5. The Naturally Occurring m1A RNA Modification Can Be Efficiently Incorporated into RNA by SARS-CoV-2 RdRp

   https://doi.org/10.21203/rs.3.rs-3615885/v1  

   Apostle, Alexander; Arneson, Reed; Yuan, Yinan; Fang, Shiyue (November 2023, Research Square)

   Abstract When it is in the template RNA, the naturally occurring m¹A epitranscriptomic RNA modification was recently reported to be able to stop the RNA polymerization reaction catalyzed by the RNA dependent RNA polymerase (RdRp) of SARS-CoV-2. In this report, we report that m¹A via its triphosphate form (m¹ATP) can be incorporated into RNA by the same RdRp. These two findings point a new direction for antiviral drug development based on m¹A for combatting COVID-19. More broadly, it is possible that the large pool of epigenetic RNA as well as DNA modifications could serve as a treasury for drug discovery aimed at combating various infectious and other diseases. 

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