tRF2Cancer: A web server to detect tRNA-derived small RNA fragments (tRFs) and their expression in multiple cancers

A comprehensive profile of circulating RNAs in human serum

Non-coding RNA (ncRNA) molecules have fundamental roles in cells and many are also stable in body fluids as extracellular RNAs. In this study, we used RNA sequencing (RNA-seq) to investigate the profile of small non-coding RNA (sncRNA) in human serum. We analyzed 10 billion Illumina reads from 477 serum samples, included in the Norwegian population-based Janus Serum Bank (JSB). We found that the core serum RNA repertoire includes 258 micro RNAs (miRNA), 441 piwi-interacting RNAs (piRNA), 411 transfer RNAs (tRNA), 24 small nucleolar RNAs (snoRNA), 125 small nuclear RNAs (snRNA) and 123 miscellaneous RNAs (misc-RNA). We also investigated biological and technical variation in expression, and the results suggest that many RNA molecules identified in serum contain signs of biological variation. They are therefore unlikely to be random degradation by-products. In addition, the presence of specific fragments of tRNA, snoRNA, Vault RNA and Y_RNA indicates protection from degradation. Our results suggest that many circulating RNAs in serum can be potential biomarkers.

The emerging complexity of the tRNA world: mammalian tRNAs beyond protein synthesis

The discovery of the genetic code and tRNAs as decoders of the code transformed life science. However, after establishing the role of tRNAs in protein synthesis, the field moved to other parts of the RNA world. Now, tRNA research is blooming again, with demonstration of the involvement of tRNAs in various other pathways beyond translation and in adapting translation to environmental cues. These roles are linked to the presence of tRNA sequence variants known as isoacceptors and isodecoders, various tRNA base modifications, the versatility of protein binding partners and tRNA fragmentation events, all of which collectively create an incalculable complexity. This complexity provides a vast repertoire of tRNA species that can serve various functions in cellular homeostasis and in adaptation of cellular functions to changing environments, and it likely arose from the fundamental role of RNAs in early evolution.

unitas: the universal tool for annotation of small RNAs

BACKGROUND

Next generation sequencing is a key technique in small RNA biology research that has led to the discovery of functionally different classes of small non-coding RNAs in the past years. However, reliable annotation of the extensive amounts of small non-coding RNA data produced by high-throughput sequencing is time-consuming and requires robust bioinformatics expertise. Moreover, existing tools have a number of shortcomings including a lack of sensitivity under certain conditions, limited number of supported species or detectable sub-classes of small RNAs.

RESULTS

Here we introduce unitas, an out-of-the-box ready software for complete annotation of small RNA sequence datasets, supporting the wide range of species for which non-coding RNA reference sequences are available in the Ensembl databases (currently more than 800). unitas combines high quality annotation and numerous analysis features in a user-friendly manner. A complete annotation can be started with one simple shell command, making unitas particularly useful for researchers not having access to a bioinformatics facility. Noteworthy, the algorithms implemented in unitas are on par or even outperform comparable existing tools for small RNA annotation that map to publicly available ncRNA databases.

CONCLUSIONS

unitas brings together annotation and analysis features that hitherto required the installation of numerous different bioinformatics tools which can pose a challenge for the non-expert user. With this, unitas overcomes the problem of read normalization. Moreover, the high quality of sequence annotation and analysis, paired with the ease of use, make unitas a valuable tool for researchers in all fields connected to small RNA biology.

Discovery and function of transfer RNA-derived fragments and their role in disease

Until recently, transfer RNAs (tRNAs) were thought to function in protein translation only. However, recent findings demonstrate that both pre- and mature tRNAs can undergo endonucleolytic cleavage by different ribonucleases originating different types of small non-coding RNAs, known as tRNA-derived fragments (tRFs). tRFs are classified according to their origin and are implicated in various cellular processes, namely apoptosis, protein synthesis control, and RNA interference. Although their functions are still poorly understood, their mechanisms of action vary according to the tRF sub-type. Several tRFs have been associated with cancer, neurodegenerative disorders, and viral infections and growing evidence shows that they may constitute novel molecular targets for modulating pathological processes. Here, we recapitulate the current knowledge of tRF biology, highlight the known functions and mechanisms of action of the different sub-classes of tRFs and discuss their implications in human disease. WIREs RNA 2017, 8:e1423. doi: 10.1002/wrna.1423 For further resources related to this article, please visit the WIREs website.

MINTmap: fast and exhaustive profiling of nuclear and mitochondrial tRNA fragments from short RNA-seq data

Transfer RNA fragments (tRFs) are an established class of constitutive regulatory molecules that arise from precursor and mature tRNAs. RNA deep sequencing (RNA-seq) has greatly facilitated the study of tRFs. However, the repeat nature of the tRNA templates and the idiosyncrasies of tRNA sequences necessitate the development and use of methodologies that differ markedly from those used to analyze RNA-seq data when studying microRNAs (miRNAs) or messenger RNAs (mRNAs). Here we present MINTmap (for MItochondrial and Nuclear TRF mapping), a method and a software package that was developed specifically for the quick, deterministic and exhaustive identification of tRFs in short RNA-seq datasets. In addition to identifying them, MINTmap is able to unambiguously calculate and report both raw and normalized abundances for the discovered tRFs. Furthermore, to ensure specificity, MINTmap identifies the subset of discovered tRFs that could be originating outside of tRNA space and flags them as candidate false positives. Our comparative analysis shows that MINTmap exhibits superior sensitivity and specificity to other available methods while also being exceptionally fast. The MINTmap codes are available through https://github.com/TJU-CMC-Org/MINTmap/ under an open source GNU GPL v3.0 license.

Computational Approaches to tRNA-Derived Small RNAs

tRNA-derived small RNAs (tDRs) are a group of small, non-coding RNAs derived from transfer RNAs (tRNAs). They can be classified as tRNA halves and tRNA-derived small RNA fragments (tRFs). Accumulating experimental evidence suggests their functional roles in cells and in various biological processes. Advances in next-generation sequencing (NGS) techniques allow a large amount of small RNA deep-sequencing data to be generated. To investigate tDRs from these data, software to identify tDRs and databases to retrieve or manage tDR data have been devised. In this review, we summarized the tools and databases for tDR identification and collection, with the aim of helping researchers choose the best tools for their analysis and inspiring the invention or improvement of tools in the field.