Revisiting criteria for plant miRNA annotation in the era of big data

Abstract

MicroRNAs (miRNAs) are ~21 nucleotide-long regulatory RNAs that arise from endonucleolytic processing of hairpin precursors. Many function as essential post-transcriptional regulators of target mRNAs and long non-coding RNAs. Alongside miRNAs, plants also produce large numbers of short interfering RNAs (siRNAs), which are distinguished from miRNAs primarily by their biogenesis (typically processed from long double-stranded RNA instead of single-stranded hairpins) and functions (typically via roles in transcriptional regulation instead of post-transcriptional regulation). Next-generation DNA sequencing methods have yielded extensive datasets of plant small RNAs, resulting in many miRNA annotations, occasionally inaccurately curated. The sheer number of endogenous siRNAs compared to miRNAs has been a major factor in the erroneous annotation of siRNAs as miRNAs. Here, we provide updated criteria for the confident annotation of plant miRNAs, suitable for the era of \"big data\" from DNA sequencing. The updated criteria emphasize replication, the minimization of false positives, and they require next-generation sequencing of small RNAs. We argue that improved annotation systems are needed for miRNAs and all other classes of plant small RNAs. Finally, to illustrate the complexities of miRNA and siRNA annotation, we review the evolution and functions of miRNAs and siRNAs in plants.