Expanding the Orchidaceae virome through analysis of public-domain sequencing data

ABSTRACT Orchidaceae is one of the largest plant families and includes species of major ornamental, economic, and ecological importance. Despite this diversity, the viruses associated with orchids remain poorly characterized. The growing availability of high-throughput sequencing data offers new opportunities to explore plant virus diversity across broad taxonomic scales. Here, we conducted a large-scale meta-analysis of orchid-associated viruses by reanalyzing 2,789 publicly available RNA-seq data sets representing 41 genera across 18 subtribes and five subfamilies. We identified sequences corresponding to 163 viruses, including 13 new associations with orchids. Notably, 117 sequences likely represent putative novel species, including tentative new genera within the families Benyviridae , Betaflexiviridae , Phenuiviridae , and Tymoviridae . This analysis also reveals patterns of virus co-occurrence within the orchid virome and uncovers links between viral taxa and orchid life forms. Overall, these findings greatly broaden the known diversity of orchid-associated viruses and offer a comprehensive global framework for understanding their composition, ecological interactions, and potential scope. IMPORTANCE Orchids are among the most diverse plant families, yet little is known about the viruses associated with them. Plant viruses pose significant risks to agriculture and may also threaten orchid conservation, particularly when infected plant material is moved through trade or cultivation. A comprehensive understanding of the orchid virome is therefore essential for improving virus detection, managing diseases, and producing virus-free planting material. In this study, we used large-scale analysis of publicly available RNA-seq data to identify viral sequences associated with orchid-derived transcriptomic data sets and to characterize the diversity of orchid-associated viruses. Our results substantially expand the catalog of viruses associated with Orchidaceae, revealing numerous previously undescribed viruses and candidate virus-orchid associations. By providing a global perspective on the Orchidaceae virome, this work highlights the power of data mining approaches for virus discovery and establishes a foundation for future studies on plant virus ecology, evolution, and surveillance.