Accurate Profiling and Quantification of tRNA Fragments from RNA-Seq Data: A Vade Mecum for MINTmap.

Publication/Presentation Date

1-1-2018

Abstract

There is an increasing interest within the scientific community in identifying tRNA-derived fragments (tRFs) and elucidating the roles they play in the cell. Such endeavors can be greatly facilitated by mining the numerous datasets from many cellular contexts that exist publicly. However, the standard mapping tools cannot be used for the purpose. Several factors complicate this endeavor including: the presence of multiple identical or nearly identical isodecoders at various genomic locations; the presence of identical sequence segments that are shared by isodecoders of the same or even different anticodons; the existence of numerous partial tRNA sequences across the genome; the existence of hundreds of "lookalike" sequences that resemble true tRNAs; and others. This is generating a need for specialized tools that can mine deep sequencing data to identify and quantify tRFs. We discuss the various complicating factors and their ramifications, and how to use and run MINTmap, a tool that addresses these considerations.

Volume

1680

First Page

237

Last Page

255

ISSN

1940-6029

Disciplines

Business Administration, Management, and Operations | Health and Medical Administration | Management Sciences and Quantitative Methods

PubMedID

29030853

Department(s)

Administration and Leadership

Document Type

Article

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