YAMAT-seq: an efficient method for high-throughput sequencing of mature transfer RNAs.
Publication/Presentation Date
5-19-2017
Abstract
Besides translation, transfer RNAs (tRNAs) play many non-canonical roles in various biological pathways and exhibit highly variable expression profiles. To unravel the emerging complexities of tRNA biology and molecular mechanisms underlying them, an efficient tRNA sequencing method is required. However, the rigid structure of tRNA has been presenting a challenge to the development of such methods. We report the development of Y-shaped Adapter-ligated MAture TRNA sequencing (YAMAT-seq), an efficient and convenient method for high-throughput sequencing of mature tRNAs. YAMAT-seq circumvents the issue of inefficient adapter ligation, a characteristic of conventional RNA sequencing methods for mature tRNAs, by employing the efficient and specific ligation of Y-shaped adapter to mature tRNAs using T4 RNA Ligase 2. Subsequent cDNA amplification and next-generation sequencing successfully yield numerous mature tRNA sequences. YAMAT-seq has high specificity for mature tRNAs and high sensitivity to detect most isoacceptors from minute amount of total RNA. Moreover, YAMAT-seq shows quantitative capability to estimate expression levels of mature tRNAs, and has high reproducibility and broad applicability for various cell lines. YAMAT-seq thus provides high-throughput technique for identifying tRNA profiles and their regulations in various transcriptomes, which could play important regulatory roles in translation and other biological processes.
Volume
45
Issue
9
First Page
70
Last Page
70
ISSN
1362-4962
Published In/Presented At
Shigematsu, M., Honda, S., Loher, P., Telonis, A. G., Rigoutsos, I., & Kirino, Y. (2017). YAMAT-seq: an efficient method for high-throughput sequencing of mature transfer RNAs. Nucleic acids research, 45(9), e70. https://doi.org/10.1093/nar/gkx005
Disciplines
Business Administration, Management, and Operations | Health and Medical Administration | Management Sciences and Quantitative Methods
PubMedID
28108659
Department(s)
Administration and Leadership
Document Type
Article