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Updated: Jan 14, 2026

A Complete Pipeline for Isolating and Sequencing MicroRNAs, and Analyzing Them Using Open Source Tools
Published on: August 21, 2019
Knowing is not enough; we must apply: the case for rigorous microRNA annotation standards
Michael Hackenberg1,2, Panagiotis Kalogeropoulos3, Kevin J Peterson4
1Bioinformatics Laboratory, Biotechnology Institute & Biomedical Research Centre (CIBM), Avenida del Conocimiento 19, Granada 18100, Spain.
None:
MicroRNAs are by far the most extensively studied and best-characterized class of small RNAs. This depth of knowledge may partly explain the persistent eagerness in the field to classify new sequences as microRNAs-since labeling a molecule as such often implies immediate functional insight and biological relevance. However, this enthusiasm has led to the publication and deposition of thousands of spurious microRNA entries in public repositories, increasing the risk of misinterpretation-particularly when these sequences are linked to human disease. To address this, we present a concise, four-part checklist for evaluating putative microRNAs, based on structural, genomic, functional, and expression-related criteria. Applying it to "Mir-690" and nine other examples, which are not listed in the curated microRNA database MirGeneDB, but highly cited, we find no support for their classification as microRNAs. They fail to meet core microRNA annotation criteria, lack structural features, conservation of targets, and reproducible or microRNA-typical expression evidence. Our findings underscore the need for heightened scrutiny and standardized validation in microRNA research. The checklist we provide offers a practical tool for authors, editors, reviewers, and readers to critically assess microRNA claims-particularly when such sequences are proposed as biomarkers or therapeutic targets in translational studies.
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