An Update on RNA Virus Discovery: Current Challenges and Future Perspectives

Abstract

The relentless emergence of RNA viruses poses a perpetual threat to global public health, necessitating continuous efforts in surveillance, discovery, and understanding of these pathogens. This review provides a comprehensive update on recent advancements in RNA virus discovery, highlighting breakthroughs in technology and methodologies that have significantly enhanced our ability to identify novel viruses across diverse host organisms. We explore the expanding landscape of viral diversity, emphasizing the discovery of previously unknown viral families and the role of zoonotic transmissions in shaping the viral ecosystem. Additionally, we discuss the potential implications of RNA virus discovery on disease emergence and pandemic preparedness. Despite remarkable progress, current challenges in sample collection, data interpretation, and the characterization of newly identified viruses persist. Our ability to anticipate and respond to emerging respiratory threats relies on virus discovery as a cornerstone for understanding RNA virus evolution. We address these challenges and propose future directions for research, emphasizing the integration of multi-omic approaches, advanced computational tools, and international collaboration to overcome barriers in the field. This comprehensive overview aims to guide researchers, policymakers, and public health professionals in navigating the intricate landscape of RNA virus discovery, fostering a proactive and collaborative approach to anticipate and mitigate emerging viral threats.

Keywords: RNA virus discovery; SARS-CoV-2 variants; emerging respiratory viruses; metagenomics; pandemic preparedness; viral evolution; virus surveillance; zoonotic spillover.

Figure 1

A schematic representation outlining the key stages in the contemporary workflow for RNA virus discovery. The process begins with diverse sampling from clinical, environmental, vector, or wildlife sources to capture a broad range of viral reservoirs, followed by RNA extraction and library preparation, which includes RNA fragmentation, adapter ligation, and quality control to ensure high-quality input for sequencing and post processing (e.g., FastQC, Trimmomatic). In the sequencing and assembly phase, raw reads generated from high-throughput platforms are processed, for instance, using k-mer–based approaches (e.g., SPAdes, MEGAHIT) to reconstruct viral genomes. The resulting viral contigs then enter the bioinformatics analysis pipeline, where viral sequences are annotated, quantified, and compared against reference databases using tools such as BLAST, Diamond, Kraken, LucaProt or Serratus to identify known viral elements and potential novelties. Phylogenetic placement (e.g., IQ-TREE, RAxML) enables preliminary classification into known, unclassified, or novel viral groups. Virus characterization incorporates functional and structural annotation through domain prediction (e.g., RdRp, helicase, capsid), protein structure modeling (e.g., using AlphaFold or HHpred), and receptor-binding inference to understand viral biology and potential pathogenicity. This multi-step workflow illustrates the integration of field sampling, molecular biology, high-throughput sequencing, and computational tools required to advance RNA virus discovery in the post-genomic era.