Expanded virome analysis of metatranscriptomes from grapevine downy mildew lesions reveals novel viral segments, novel viruses and viroid-like RNAs.

Grapevine downy mildew, caused by the obligate biotrophic oomycete Plasmopara viticola, represents a major constraint to viticulture worldwide. Previous metatranscriptomic analyses revealed an unexpectedly rich viral diversity associated with downy mildew leaf lesions and in this study we re-analyzed the same RNA-seq libraries to complete viral genomes and identify additional RNA infectious elements. Using homology-based searches, RNA structural motif detection, coverage-based segment association and targeted experimental validation, we reconstructed the presumed complete genomes of multiple viruses belonging to the Splipalmiviridae, the proposed 'Orfanplasmoviridae' and 'Viviviridae' families. Specifically, we completed the genomes of seven known and three novel splipalmiviruses, five known and two novel orfanplasmoviruses, and four viviviruses, substantially expanding their genomic characterization. We further identified six novel ambiviruses, designated "downy mildew lesion-associated ambivirus 1-6" (DmlaAV1-6), which have a circular genome encoding two open reading frames on opposite polarities, including a putative RNA-dependent RNA polymerase. One DmlaAV contains paired delta-like ribozymes for which the self-cleavage activity was demonstrated in vitro, providing the first biochemical evidence of functional delta-like ribozymes in ambiviruses. In addition, a 767-nt circular RNA element lacking coding capacity and homology to known sequences was identified. This RNA adopts a quasi-rod-like structure, contains twister ribozymes in both polarity strands and lacks a DNA counterpart, supporting its classification as an infectious viroid-like RNA. Overall, this work refines and extends the virome associated with grapevine downy mildew leaf lesions, highlighting the remarkable diversity of RNA infectious agents inhabiting this ecological niche and underscoring the value of re-analyzing existing transcriptomic datasets.