TDRmapper: challenges and solutions to mapping, naming, and quantifying tRNA-derived RNAs from human small RNA-sequencing data. Issue 1 (December 2015)

• Record Type: Journal Article
• Authors: Selitsky, Sara; Sethupathy, Praveen
• Is Part Of: BMC bioinformatics. Volume 16:Issue 1(2015)
• Page Start: 1
• Page End: 13
• Publication Date: 2015-12
• Subjects: tRNA -- tDR -- Sequencing -- RNA modifications -- Bioinformatics; Bioinformatics -- Periodicals; Computational biology -- Periodicals; 570.285
• DOI: 10.1186/s12859-015-0800-0
• Languages: English
• ISSNs: 1471-2105

Abstract

Abstract Background Small RNA-sequencing has revealed the diversity and high abundance of small RNAs derived from tRNAs, referred to as tRNA-derived RNAs. However, at present, there is no standardized nomenclature and there are no methods for accurate annotation and quantification of these small RNAs. tRNA-derived RNAs have unique features that limit the utility of conventional alignment tools and quantification methods. Results We describe here the challenges of mapping, naming, and quantifying tRNA-derived RNAs and present a novel method that addresses them, calledtDRmapper . We then usetDRmapper to perform a comparative analysis of tRNA-derived RNA profiles across different human cell types and diseases. We found that (1) tRNA-derived RNA profiles can differ dramatically across different cell types and disease states, (2) that positions and types of chemical modifications of tRNA-derived RNAs vary by cell type and disease, and (3) that entirely different tRNA-derived RNA species can be produced from the same parental tRNA depending on the cell type. Conclusion tDRmapper not only provides a standardized nomenclature and quantification scheme, but also includes graphical visualization that facilitates the discovery of novel tRNA and tRNA-derived RNA biology.