TRFTars: predicting the targets of tRNA-derived fragments

Qiong Xiao,Yu Fu,Peng Gao,Xuanzhang Huang,Zhenning Wang,Yongxi Song,Xiaowan Chen,Xinger Lv,Quan Chen

doi:10.1186/s12967-021-02731-7

Abstract

BackgroundtRNA-derived fragments (tRFs) are 14–40-nucleotide-long, small non-coding RNAs derived from specific tRNA cleavage events with key regulatory functions in many biological processes. Many studies have shown that tRFs are associated with Argonaute (AGO) complexes and inhibit gene expression in the same manner as miRNAs. However, there are currently no tools for accurately predicting tRF target genes.MethodsWe used tRF-mRNA pairs identified by crosslinking, ligation, and sequencing of hybrids (CLASH) and covalent ligation of endogenous AGO-bound RNAs (CLEAR)-CLIP to assess features that may participate in tRF targeting, including the sequence context of each site and tRF-mRNA interactions. We applied genetic algorithm (GA) to select key features and support vector machine (SVM) to construct tRF prediction models.ResultsWe first identified features that globally influenced tRF targeting. Among these features, the most significant were the minimum free folding energy (MFE), position 8 match, number of bases paired in the tRF-mRNA duplex, and length of the tRF, which were consistent with previous findings. Our constructed model yielded an area under the receiver operating characteristic (ROC) curve (AUC) = 0.980 (0.977–0.983) in the training process and an AUC = 0.847 (0.83–0.861) in the test process. The model was applied to all the sites with perfect Watson–Crick complementarity to the seed in the 3′ untranslated region (3′-UTR) of the human genome. Seven of nine target/nontarget genes of tRFs confirmed by reporter assay were predicted. We also validated the predictions via quantitative real-time PCR (qRT-PCR). Thirteen potential target genes from the top of the predictions were significantly down-regulated at the mRNA levels by overexpression of the tRFs (tRF-3001a, tRF-3003a or tRF-3009a).ConclusionsPredictions can be obtained online, tRFTars, freely available at http://trftars.cmuzhenninglab.org:3838/tar/, which is the first tool to predict targets of tRFs in humans with a user-friendly interface.

Highlights

TRNA-derived fragments are 14–40-nucleotide-long, small non-coding RNAs derived from specific tRNA cleavage events with key regulatory functions in many biological processes
Identification of tRNA-derived fragments (tRFs) targets from CLASH data Based on CLASH data from HEK293 cells and covalent ligation of endogenous AGO-bound RNAs (CLEAR)-CLIP data from Huh-7.5 cells, we obtained 547 tRF-mRNA pairs (532 from CLASH and 15 from CLEAR-CLIP) involving 28 tRFs (20 tRF-3 s and eight tRF-5 s) in CLASH and 15 tRFs in CLEAR-CLIP
Sequence features of the transcripts When focusing on the whole-sequence features to assess their impacts on the efficacies of sites, we found that the positive group had a significantly lower global GC content than the background in the 3′ untranslated region (3′-UTR) (P = 5.40E−06), but this trend was not as significant as that detected in local comparisons near seed matches

Summary

Introduction

TRNA-derived fragments (tRFs) are 14–40-nucleotide-long, small non-coding RNAs derived from specific tRNA cleavage events with key regulatory functions in many biological processes. TRNA-derived fragments (tRFs) are small non-coding RNAs derived from tRNAs with lengths of 14–40 nucleotides (nts). They have been identified at high abundances in many species [1,2,3] and can be divided into five categories: (i) tRF-5 s, from the 5′ ends of mature tRNAs; (ii) tRF-3 s, from the 3′ ends of mature tRNAs with 3′-CCA termini; (iii) i-tRFs, from the internal cleavage of mature tRNAs; (iv) tRF-1 s (3′U tRFs), from the 3′ trailing sequences of pre-tRNAs with poly-U residues; and (v). Seed pairing is commonly thought to function in gene expression regulation [17, 18], studies on specific factors that affect tRF targeting are limited

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