ArticleScientific reports2023
P-TarPmiR accurately predicts plant-specific miRNA targets.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- Suppression of microRNAs targeting key MEP pathway genes affects plastid terpenoid content and photosynthesis under variable light conditions.Molecular biology reports · 2026Article
- miRNA Target Prediction: An Overview of the Past and Current Tools.Methods in molecular biology (Clifton, N.J.) · 2026Review
- Long Non-Coding RNAs in the Cold-Stress Response of Horticultural Plants: Molecular Mechanisms and Potential Applications.International journal of molecular sciences · 2025Review
- The Role of MicroRNA-Based Strategies in Optimizing Plant Biomass Composition for Bio-Based Packaging Materials.Plants (Basel, Switzerland) · 2025Review
- MicroRNAs in plant-parasitic nematodes: what are they and why should we care?Journal of nematology · 2025Review
- Mechanism of action and potential therapeutic targets of TGF-β-related signaling pathway and its downstream miRNA expression in pulmonary arterial hypertension.Frontiers in pharmacology · 2025Review
- Prediction of miRNA Targets in Plants.Methods in molecular biology (Clifton, N.J.) · 2025Article
- Catalase (CAT) Gene Family in Oil Palm (International journal of molecular sciences · 2024Article
- Comparative analysis of SPL transcription factors from streptophyte algae and embryophytes reveals evolutionary trajectories of SPL family in streptophytes.Scientific reports · 2024Article
- Species-specific microRNA discovery and target prediction in the soybean cyst nematode.Scientific reports · 2023Article
- Characterization of microRNAs in the cyst nematodeRNA biology · 2023Article
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
microRNAs (miRNAs) are small non-coding ribonucleic acids that post-transcriptionally regulate gene expression through the targeting of messenger RNA (mRNAs). Most miRNA target predictors have focused on animal species and prediction performance drops substantially when applied to plant species. Several rule-based miRNA target predictors have been developed in plant species, but they often fail to discover new miRNA targets with non-canonical miRNA-mRNA binding. Here, the recently published TarDB database of plant miRNA-mRNA data is leveraged to retrain the TarPmiR miRNA target predictor for application on plant species. Rigorous experiment design across four plant test species demonstrates that animal-trained predictors fail to sustain performance on plant species, and that the use of plant-specific training data improves accuracy depending on the quantity of plant training data used. Surprisingly, our results indicate that the complete exclusion of animal training data leads to the most accurate plant-specific miRNA target predictor indicating that animal-based data may detract from miRNA target prediction in plants. Our final plant-specific miRNA prediction method, dubbed P-TarPmiR, is freely available for use at http://ptarpmir.cu-bic.ca . The final P-TarPmiR method is used to predict targets for all miRNA within the soybean genome. Those ranked predictions, together with GO term enrichment, are shared with the research community.
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