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Making Invisible RNA Visible: Discriminative Sequencing Methods for RNA Molecules with Specific Terminal Formations.

Megumi ShigematsuYohei Kirino
Published in: Biomolecules (2022)
Next generation sequencing of RNA molecules (RNA-seq) has become a common tool to characterize the expression profiles of RNAs and their regulations in normal physiological processes and diseases. Although increasingly accumulating RNA-seq data are widely available through publicly accessible sites, most of the data for short non-coding RNAs (sncRNAs) have been obtained for microRNA (miRNA) analyses by standard RNA-seq, which only capture the sncRNAs with 5'-phosphate (5'-P) and 3'-hydroxyl (3'-OH) ends. The sncRNAs with other terminal formations such as those with a 5'-hydroxyl end (5'-OH), a 3'-phosphate (3'-P) end, or a 2',3'-cyclic phosphate end (2',3'-cP) cannot be efficiently amplified and sequenced by standard RNA-seq. Due to the invisibility in standard RNA-seq data, these non-miRNA-sncRNAs have been a hidden component in the transcriptome. However, as the functional significances of these sncRNAs have become increasingly apparent, specific RNA-seq methods compatible with various terminal formations of sncRNAs have been developed and started shedding light on the previously unrecognized sncRNAs that lack 5'-P/3'-OH ends. In this review, we summarize the expanding world of sncRNAs with various terminal formations and the strategic approaches of specific RNA-seq methods to distinctively characterize their expression profiles.
Keyphrases
  • rna seq
  • single cell
  • electronic health record
  • big data
  • magnetic resonance imaging
  • magnetic resonance
  • machine learning
  • diffusion weighted imaging