Combining tRNA sequencing methods to characterize plant tRNA expression and post-transcriptional modification. Issue 1 (2nd January 2021)

• Record Type: Journal Article
• Authors: Warren, Jessica M.; Salinas-Giegé, Thalia; Hummel, Guillaume; Coots, Nicole L.; Svendsen, Joshua M.; Brown, Kristen C.; Drouard, Laurence; Sloan, Daniel B.
• Is Part Of: RNA biology. Volume 18:Issue 1(2021)
• Page Start: 64
• Page End: 78
• Publication Date: 2021-01-02
• Subjects: tRNA-Seq -- AlkB -- YAMAT-Seq -- tRNA modification -- plant tRNAs; RNA -- Periodicals; Molecular biology -- Periodicals; Molecular biology; RNA; Periodicals; 572.8805
• DOI: 10.1080/15476286.2020.1792089
• Languages: English
• ISSNs: 1547-6286

Abstract

ABSTRACT: Differences in tRNA expression have been implicated in a remarkable number of biological processes. There is growing evidence that tRNA genes can play dramatically different roles depending on both expression and post-transcriptional modification, yet sequencing tRNAs to measure abundance and detect modifications remains challenging. Their secondary structure and extensive post-transcriptional modifications interfere with RNA-seq library preparation methods and have limited the utility of high-throughput sequencing technologies. Here, we combine two modifications to standard RNA-seq methods by treating with the demethylating enzyme AlkB and ligating with tRNA-specific adapters in order to sequence tRNAs from four species of flowering plants, a group that has been shown to have some of the most extensive rates of post-transcriptional tRNA modifications. This protocol has the advantage of detecting full-length tRNAs and sequence variants that can be used to infer many post-transcriptional modifications. We used the resulting data to produce a modification index of almost all unique reference tRNAs in Arabidopsis thaliana, which exhibited many anciently conserved similarities with humans but also positions that appear to be 'hot spots' for modifications in angiosperm tRNAs. We also found evidence based on northern blot analysis and droplet digital PCR that, even after demethylation treatment, tRNA-seq can produce highly biased estimates of absolute expression levels most likely due to biased reverse transcription. Nevertheless, the generation of full-length tRNA sequences with modification data is still promising for assessing differences in relative tRNA expression across treatments, tissues or subcellular fractions and help elucidate the functional roles of tRNA modifications.