MicroRNAs (miRNAs) are small (20-24 nucleotides) non-coding ribo-regulatory molecules with significant roles in regulating target mRNA and long non-coding RNAs at transcriptional and post-transcriptional levels. Rapid advancement in the small RNA sequencing methods with integration of degradome sequencing has accelerated the understanding of miRNA-mediated regulatory hubs in plants and yielded extensive annotation of miRNAs and corresponding targets. However, it is becoming clear that large numbers of such annotations are questionable. Therefore, it is imperative to adopt reliable and strict bioinformatics pipelines for miRNA identification. Furthermore, sensitive methods are needed for validation and functional characterization of miRNA and its target(s). In this chapter, we have provided a comprehensive and streamlined methodology for miRNA identification and its functional validation in plants. This includes a combination of various in silico and experimental methodologies. To identify miRNA compendium from large-scale Next-Generation Sequencing (NGS) small RNA datasets, the miR-PREFeR (miRNA PREdiction From small RNA-Seq data) bioinformatics tool has been described. Also, a homology-based search protocol for finding members of a specific miRNA family has been discussed. The chapter also includes techniques to ascertain miRNA:target pair specificity using in silico target prediction from degradome NGS libraries using CleaveLand pipeline, miRNA:target validation by in planta transient assays, 5' RLM-RACE and expression analysis as well as functional techniques like miRNA overexpression, short tandem target mimic and resistant target approaches. The proposed strategy offers a reliable and sensitive way for miRNA:target identification and validation. Additionally, we strongly promulgate the use of multiple methodologies to validate a miRNA as well as its target.

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http://dx.doi.org/10.1007/978-1-0716-1875-2_17DOI Listing

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