ArticleGenes2026
Limitations of Single Prediction Tools in miRNA Profiling of Grapevine Viral Coinfection.
Article in Genes, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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5 authors.
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Abstract
BACKGROUND/
objectivesGrapevine (
methodsTwo grapevine cultivars, Refošk ("Terrano") and Zeleni Sauvignon ("Sauvignon Vert"), were analyzed. Small RNA sequencing was performed on virus-free plants and plants coinfected with grapevine Pinot gris virus (GPGV), grapevine rupestris stem pitting-associated virus (GRSPaV), and grapevine rupestris vein feathering virus (GRVFV). Three miRNA prediction tools were used to identify miRNAs annotated in public databases. Differential expression analysis was performed separately for each tool and by using an integrated approach that combined all three datasets. The expression of selected miRNAs was further evaluated using stem-loop RT-qPCR.
resultsThe three prediction tools detected markedly different numbers of miRNAs, resulting in largely distinct sets of differentially expressed miRNAs and limited overlap between individual analyses. The integrated approach yielded a separate set of differentially expressed miRNAs, most of which overlapped with at least one individual dataset. Stem-loop RT-qPCR analysis supported the differential expression of several selected miRNAs.
conclusionsThis study provides new insight into miRNA expression in grapevine under mixed-virus infection and demonstrates that miRNA profiling outcomes are strongly influenced by the choice of bioinformatic prediction tool. Our results highlight the importance of integrated analytical strategies combined with experimental validation to obtain robust and biologically meaningful interpretations of miRNA expression in plants.
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