tDRmapper: challenges and solutions to mapping, naming, and quantifying tRNA-derived RNAs from human small RNA-sequencing data

The role of tRNA-Derived small RNAs (tsRNAs) in pancreatic cancer and acute pancreatitis

tRNA-derived small RNAs (tsRNAs), encompassing tRNA fragments (tRFs) and tRNA-derived stress-induced RNAs (tiRNAs), represent a category of non-coding small RNAs (sncRNAs) that are increasingly recognized for their diverse biological functions. These functions include gene silencing, ribosome biogenesis, retrotransposition, and epigenetics. tsRNAs have been identified as key players in the progression of various tumors, yet their specific roles in pancreatic cancer (PC) and acute pancreatitis (AP) remain largely unexplored. Pancreatic cancer, particularly pancreatic ductal adenocarcinoma, is notorious for its high mortality rate and extremely low patient survival rate, primarily due to challenges in early diagnosis. Similarly, acute pancreatitis is a complex and significant disease. This article reviews the roles of 18 tsRNAs in PC and AP, focusing on their mechanisms of action and potential clinical applications in these two diseases. These tsRNAs influence the progression of pancreatic cancer and acute pancreatitis by modulating various pathways, including ZBP1/NLRP3, Hippo, PI3K/AKT, glycolysis/gluconeogenesis, and Wnt signaling. Notably, the dysregulation of tsRNAs is closely linked to critical clinical factors in pancreatic cancer and acute pancreatitis, such as lymph node metastasis, tumor-node-metastasis (TNM) stage, overall survival (OS), and disease-free survival (DFS). This article not only elucidates the mechanisms by which tsRNAs affect pancreatic cancer and acute pancreatitis but also explores their potential as biomarkers and therapeutic targets for pancreatic cancer. The insights provided here offer valuable references for future research, highlighting the importance of tsRNAs in the diagnosis and treatment of these challenging diseases.

tRNA modifications and tRNA-derived small RNAs: new insights of tRNA in human disease

tRNAs are codon decoders that convert the transcriptome into the proteome. The field of tRNA research is excited by the increasing discovery of specific tRNA modifications that are installed at specific, evolutionarily conserved positions by a set of specialized tRNA-modifying enzymes and the biogenesis of tRNA-derived regulatory fragments (tsRNAs) which exhibit copious activities through multiple mechanisms. Dysregulation of tRNA modification usually has pathological consequences, a phenomenon referred to as "tRNA modopathy". Current evidence suggests that certain tRNA-modifying enzymes and tsRNAs may serve as promising diagnostic biomarkers and therapeutic targets, particularly for chemoresistant cancers. In this review, we discuss the latest discoveries that elucidate the molecular mechanisms underlying the functions of clinically relevant tRNA modifications and tsRNAs, with a focus on malignancies. We also discuss the therapeutic potential of tRNA/tsRNA-based therapies, aiming to provide insights for the development of innovative therapeutic strategies. Further efforts to unravel the complexities inherent in tRNA biology hold the promise of yielding better biomarkers for the diagnosis and prognosis of diseases, thereby advancing the development of precision medicine for health improvement.

Exploring the role of tRNA-derived small RNAs (tsRNAs) in disease: implications for HIF-1 pathway modulation

The tRNA-derived small RNAs (tsRNAs) can be categorized into two main groups: tRNA-derived fragments (tRFs) and tRNA-derived stress-induced RNAs (tiRNAs). Each group possesses specific molecular sizes, nucleotide compositions, and distinct physiological functions. Notably, hypoxia-inducible factor-1 (HIF-1), a transcriptional activator dependent on oxygen, comprises one HIF-1β subunit and one HIF-α subunit (HIF-1α/HIF-2α/HIF-3α). The activation of HIF-1 plays a crucial role in gene transcription, influencing key aspects of cancer biology such as angiogenesis, cell survival, glucose metabolism, and invasion. The involvement of HIF-1α activation has been demonstrated in numerous human diseases, particularly cancer, making HIF-1 an attractive target for potential disease treatments. Through a series of experiments, researchers have identified two tiRNAs that interact with the HIF-1 pathway, impacting disease development: 5'tiRNA-His-GTG in colorectal cancer (CRC) and tiRNA-Val in diabetic retinopathy (DR). Specifically, 5'tiRNA-His-GTG promotes CRC development by targeting LATS2, while tiRNA-Val inhibits Sirt1, leading to HIF-1α accumulation and promoting DR development. Clinical data have further indicated that certain tsRNAs' expression levels are associated with the prognosis and pathological features of CRC patients. In CRC tumor tissues, the expression level of 5'tiRNA-His-GTG is significantly higher compared to normal tissues, and it shows a positive correlation with tumor size. Additionally, KEGG analysis has revealed multiple tRFs involved in regulating the HIF-1 pathway, including tRF-Val-AAC-016 in diabetic foot ulcers (DFU) and tRF-1001 in pathological ocular angiogenesis. This comprehensive article reviews the biological functions and mechanisms of tsRNAs related to the HIF-1 pathway in diseases, providing a promising direction for subsequent translational medicine research.

tRNA-derived small RNAs in human cancers: roles, mechanisms, and clinical application

Transfer RNA (tRNA)-derived small RNAs (tsRNAs) are a new type of non-coding RNAs (ncRNAs) produced by the specific cleavage of precursor or mature tRNAs. tsRNAs are involved in various basic biological processes such as epigenetic, transcriptional, post-transcriptional, and translation regulation, thereby affecting the occurrence and development of various human diseases, including cancers. Recent studies have shown that tsRNAs play an important role in tumorigenesis by regulating biological behaviors such as malignant proliferation, invasion and metastasis, angiogenesis, immune response, tumor resistance, and tumor metabolism reprogramming. These may be new potential targets for tumor treatment. Furthermore, tsRNAs can exist abundantly and stably in various bodily fluids (e.g., blood, serum, and urine) in the form of free or encapsulated extracellular vesicles, thereby affecting intercellular communication in the tumor microenvironment (TME). Meanwhile, their abnormal expression is closely related to the clinicopathological features of tumor patients, such as tumor staging, lymph node metastasis, and poor prognosis of tumor patients; thus, tsRNAs can be served as a novel type of liquid biopsy biomarker. This review summarizes the discovery, production, and expression of tsRNAs and analyzes their molecular mechanisms in tumor development and potential applications in tumor therapy, which may provide new strategies for early diagnosis and targeted therapy of tumors.

Quantitative and qualitative detection of tRNAs, tRNA halves and tRFs in human cancer samples: Molecular grounds for biomarker development and clinical perspectives

Transfer RNAs (tRNAs) are small non-coding RNAs playing a central role during protein synthesis. Besides translation, growing evidence suggests that in many contexts, precursor or mature tRNAs can also be processed into smaller fragments playing many non-canonical regulatory roles in different biological pathways with oncogenic relevance. Depending on the source, these molecules can be classified as tRNA halves (also known as tiRNAs) or tRNA-derived fragments (tRFs), and furtherly divided into 5'-tRNA and 3'-tRNA halves, or tRF-1, tRF-2, tRF-3, tRF-5, and i-tRF, respectively. Unlike DNA and mRNA, high-throughput sequencing of tRNAs is challenging, because of technical limitations of currently developed sequencing methods. In recent years, different sequencing approaches have been proposed allowing the quantification and identification of an increasing number of tRNA fragments with critical functions in distinct physiological and pathophysiological processes. In the present review, we discussed pros and cons of recent advances in different sequencing methods, also introducing the expanding repertoire of bioinformatics tool and resources specifically focused on tRNA research and discussing current issues in the study of these small RNA molecules. Furthermore, we discussed the potential value of tRNA fragments as diagnostic and prognostic biomarkers for different types of cancers.

In Silico Identification of tRNA Fragments, Novel Candidates for Cancer Biomarkers, and Therapeutic Targets

The identification of a wide variety of RNA molecules using high-throughput sequencing techniques in the transcriptome pool of living organisms has revealed hidden regulatory insights in the cell. The class of non-coding RNA fragments produced from transfer RNA, or tRFs, is one such example. They are heterogeneously sized molecules with lengths ranging between 15 and 50 nt. They have a history of being dysregulated in human malignancies and other illnesses. The detection of these molecules has been made easier by a variety of bioinformatics techniques. The various types of tRFs and how they relate to cancer are covered in this chapter. It also provides a summary of the biological significance of tRFs reported in human cancer. Additionally, it emphasizes the utilities of databases and computational tools that have been created by different research teams for the investigation of tRFs. This will further aid the exploration and analysis of tRFs in cancer research and will support future advancement and a better comprehension of these molecules.

tRF-21-LNK8KEP1B as a potential novel diagnostic biomarker for enthesitis-related arthritis

OBJECTIVE

tRNA-derived fragments (tRFs) play crucial roles in the progression of various diseases, and widely distribute in human tissues, including blood and urine. The diagnosis of enthesitis-related arthritis (ERA) is based on the observation of clinical manifestations. Therefore, we aimed to investigate whether serum tRFs can be used as diagnostic markers for ERA.

METHODS

Serum was collected from children admitted to the Children's Hospital Affiliated with Nanjing Medical University between February 2022 to October 2022. The expression profiles of tRFs in the serum of ERA patients (n = 5) and healthy controls (HCs; n = 5) were investigated using small RNA high-throughput sequencing. The level and diagnostic value of tRF-21-LNK8KEP1B were evaluated by real-time quantitative PCR in serum samples from 30 ERA patients and 31 HCs. The specificity and sensitivity of tRFs were determined using receiver operating characteristic analyses. Bioinformatics analysis was performed to explore and identify the potential biological pathways induced by tRFs.

RESULTS

Ninety-eight upregulated and 63 downregulated tRFs were identified in the serum. We selected tRF-21-LNK8KEP1B as a candidate marker using KEGG pathway enrichment and PCR validation. tRF-21-LNK8KEP1B was substantially increased in the serum of ERA patients compared with that in HCs. The area under the curve (AUC) for tRF-21-LNK8KEP1B in the ERA group was 0.7849.

CONCLUSIONS

Collectively, we demonstrated the promising role of serum tRF-21-LNK8KEP1B -levels as a diagnostic biomarker for ERA.

Transfer RNA-derived small RNAs (tsRNAs) in gastric cancer

Transfer RNA-derived small RNAs (tsRNAs) are newly discovered noncoding RNAs (ncRNAs). According to the specific cleavage of nucleases at different sites of tRNAs, the produced tsRNAs are divided into tRNA-derived stress-inducible RNAs (tiRNAs) and tRNA-derived fragments (tRFs). tRFs and tiRNAs have essential biological functions, such as mRNA stability regulation, translation regulation and epigenetic regulation, and play significant roles in the occurrence and development of various tumors. Although the roles of tsRNAs in some tumors have been intensively studied, their roles in gastric cancer are still rarely reported. In this review, we focus on recent advances in the generation and classification of tsRNAs, their biological functions, and their roles in gastric cancer. Sixteen articles investigating dysregulated tsRNAs in gastric cancer are summarized. The roles of 17 tsRNAs are summarized, of which 9 were upregulated and 8 were downregulated compared with controls. Aberrant regulation of tsRNAs was closely related to the main clinicopathological factors of gastric cancer, such as lymph node metastasis, Tumor-Node-Metastasis (TNM) stage, tumor size, and vascular invasion. tsRNAs participate in the progression of gastric cancer by regulating the PTEN/PI3K/AKT, MAPK, Wnt, and p53 signaling pathways. The available literature suggests the potential of using tsRNAs as clinical biomarkers for gastric cancer diagnosis and prognosis and as therapeutic targets for gastric cancer treatment.

Identification of tRNA-derived RNAs in adipose tissue from overweight type 2 diabetes mellitus patients and their potential biological functions

Background

Type 2 diabetes mellitus (T2DM)causes a huge public health burden worldwide, especially for those who are overweight or obese, the pain is often greater. And search for effective targets in overweight T2DM could help improve patient quality of life and prognosis. tRNA-derived RNAs (tsRNAs) are multifunctional regulators that are currently receiving much attention, but there is still a lack of knowledge about tsRNAs in overweight T2DM.

Methods

T2DM patients with BMI ≥ 25 (Overweight group) and BMI< 25 (Control group) were subjected to tsRNA sequencing; differentially expressed tsRNAs in the two groups were analyzed and their expression was verified using qRT-PCR. The biological function of downstream target genes was also evaluated by enrichment analysis.

Results

qRT-PCR evaluation identified a tsRNA with up-regulated expression (tRF-1-28-Glu-TTC-3-M2) and a tsRNA with down-regulated expression (tRF-1-31-His-GTG-1), both of which may be involved in metabolic and energy-related processes.

Conclusion

Dysregulation of tsRNA expression in overweight patients with T2DM suggests a potential role for tsRNA in the development of T2DM.

Elucidation of transfer RNAs as stress regulating agents and the experimental strategies to conceive the functional role of tRNA-derived fragments in plants

In plants, the transfer RNAs (tRNAs) exhibit their profound influence in orchestrating diverse physiological activities like cell growth, development, and response to several surrounding stimuli. The tRNAs, which were known to restrict their function solely in deciphering the codons, are now emerging as frontline defenders in stress biology. The plants that are constantly confronted with a huge panoply of stresses rely on tRNA-mediated stress regulation by altering the tRNA abundance, curbing the transport of tRNAs, fragmenting the mature tRNAs during stress. Among them, the studies on the generation of transfer RNA-derived fragments (tRFs) and their biological implication in stress response have attained huge interest. In plants, the tRFs hold stable expression patterns and regulate biological functions under diverse environmental conditions. In this review, we discuss the fate of plant tRNAs upon stress and thereafter how the tRFs are metamorphosed into sharp ammunition to wrestle with stress. We also address the various methods developed to date for uncovering the role of tRFs and their function in plants.

Transfer RNA-derived small RNAs (tsRNAs) sequencing revealed a differential expression landscape of tsRNAs between glioblastoma and low-grade glioma

BACKGROUND

Glioblastomas (GBMs) are the most lethal brain cancer with a median survival rate of fewer than 15 months. Both clinical and biological features of GBMs are largely different from those of low-grade gliomas (LGs), but the reasons for this intratumoral heterogeneity are not entirely clear. Transfer RNA (tRNA)-derived small RNAs (tsRNAs) were derived from tRNA precursors and mature tRNA, referring to the specific cleavage of tRNAs by dicer and angiogenin (ANG) in particular cells or tissues or under certain conditions such as stress and hypoxia. With the characteristics of wide expression and high stability, tsRNAs could be used as favorable biomarkers for diagnosis, treatment, and prognosis prediction of the tumor, viral infection, neurological as well as other systemic diseases. In this study, we have compared the differential expressed tsRNAs between GBMs and LGs, so as to investigate the possible pathogenic molecules and provide references for discovering novel nucleic acid drugs in future studies.

METHODS

Fresh tumor tissues of patients that were diagnosed as GBMs (4 cases) and LGs (5 cases) at the First Affiliated Hospital of Wenzhou Medical University from 2019.05 to 2021.01 were collected. The tsRNAs' levels were analyzed and compared through high-throughput sequencing, candidate tsRNAs were chosen according to the expression level, and the expression of the candidate tsRNAs was validated through qPCR. Finally, the potential targets were imputed using the Miranda and TargetScan databases, and possible biological functions of the differentially expressed (DE) tsRNAs' targets were enriched based on GO and KEGG databases.

RESULTS

A total of 4 GBMs and 5 LGs patients were enrolled in the current study. High-throughput sequencing showed that 186 tsRNAs were expressed in two groups, over them, 43 tsRNAs were unique to GBMs, and 24 tsRNAs were unique to LGs. A total of 9 tsRNAs were selected as candidate tsRNAs according to the tsRNA expression level, among which 6 tsRNAs were highly expressed in GBMs and 3 tsRNAs were low expressed in GBMs. qPCR verification further demonstrated that 5 tsRNAs were significantly up-regulated and 1 tsRNA was significantly down-regulated in GBMs: tRF-1-32-chrM.Lys-TTT (p=0.00118), tiRNA-1-33-Gly-GCC-1 (p=0.00203), tiRNA-1-33-Gly-CCC-1 (p=0.00460), tRF-1-31-His-GTG-1 (p=0.00819), tiRNA-1-33-Gly-GCC-2-M3 (p=0.01032), and tiRNA-1-34-Lys-CTT-1-M2 (p=0.03569). Enrichment analysis of the qPCR verified DE tsRNAs showed that the 5 up-regulated tsRNAs seemed to be associated with axon guidance, pluripotent stem cells regulation, nucleotide excision repair, Hippo signaling pathway, and cancer-related pathways, while the down-regulated tsRNA (tRF-1-32-chrM.Lys-TTT) was associated with oocyte meiosis and renin secretion.

CONCLUSION

The tsRNAs were differentially expressed in tumor tissues between GBMs and LGs, especially tRF-1-32-chrM.Lys-TTT, tiRNA-1-33-Gly-GCC-1, tiRNA-1-33-Gly-CCC-1, tRF-1-31-His-GTG-1, tiRNA-1-33-Gly-GCC-2-M3, and tiRNA-1-34-Lys-CTT-1-M2. These tsRNAs seemed to be associated with nucleotide excision repair, Hippo signaling, and cancer-related pathways. This may be the main reason for the differences in clinical characteristics between GBMs and LGs, which may provide a certain theoretical basis for further functional research and development of related nucleic acid drugs.

CONCLUSION

The tsRNAs were differentially expressed in tumor tissues between GBMs and LGs, especially tRF-1-32-chrM.Lys-TTT, tiRNA-1-33-Gly-GCC-1, tiRNA-1-33-Gly-CCC-1, tRF-1-31-His-GTG-1, tiRNA-1-33-Gly-GCC-2-M3, and tiRNA-1-34-Lys-CTT-1-M2. These tsRNAs seemed to be associated with nucleotide excision repair, Hippo signaling, and cancer-related pathways. This may be the main reason for the differences in clinical characteristics between GBMs and LGs, which may provide a certain theoretical basis for further functional research and development of related nucleic acid drugs.

mtR_find: A Parallel Processing Tool to Identify and Annotate RNAs Derived from the Mitochondrial Genome

RNAs originating from mitochondrial genomes are abundant in transcriptomic datasets produced by high-throughput sequencing technologies, primarily in short-read outputs. Specific features of mitochondrial small RNAs (mt-sRNAs), such as non-templated additions, presence of length variants, sequence variants, and other modifications, necessitate the need for the development of an appropriate tool for their effective identification and annotation. We have developed mtR_find, a tool to detect and annotate mitochondrial RNAs, including mt-sRNAs and mitochondria-derived long non-coding RNAs (mt-lncRNA). mtR_find uses a novel method to compute the count of RNA sequences from adapter-trimmed reads. When analyzing the published datasets with mtR_find, we identified mt-sRNAs significantly associated with the health conditions, such as hepatocellular carcinoma and obesity, and we discovered novel mt-sRNAs. Furthermore, we identified mt-lncRNAs in early development in mice. These examples show the immediate impact of miR_find in extracting a novel biological information from the existing sequencing datasets. For benchmarking, the tool has been tested on a simulated dataset and the results were concordant. For accurate annotation of mitochondria-derived RNA, particularly mt-sRNA, we developed an appropriate nomenclature. mtR_find encompasses the mt-ncRNA transcriptomes in unpreceded resolution and simplicity, allowing re-analysis of the existing transcriptomic databases and the use of mt-ncRNAs as diagnostic or prognostic markers in the field of medicine.

tncRNA Toolkit: A pipeline for convenient identification of RNA (tRNA)-derived non-coding RNAs

Insights into the eukaryotic gene regulation networks have improved due to the advent of diverse classes of non-coding RNAs. The transfer RNA (tRNA)-derived non-coding RNAs or tncRNAs is a novel class of non-coding RNAs, shown to regulate gene expression at transcription and translation levels. Here, we present a pipeline 'tncRNA Toolkit' for accurately identifying tncRNAs using small RNA sequencing (sRNA-seq) data. Previously, we identified tncRNA in six major angiosperms by utilizing our pipeline and highlighted the significant points regarding their generation and functions. The 'tncRNA Toolkit' is available at the URL: http://www.nipgr.ac.in/tncRNA. The scripts are written in bash and Python3 programming languages. The program can be efficiently run as a standalone command-line tool and installed in any Linux-based Operating System (OS). The user can run this program by providing the input of sRNA-seq data and genome file.The various features of the 'tncRNA Toolkit' are as follows:•Major tncRNA classes identified by this tool include tRF-5, tRF-3, tRF-1, 5'tRH, 3'tRH, and leader tRF. Also, it categorizes miscellaneous tncRNAs as other tRF.•It provides the following information for each identified tncRNA viz. tncRNA class, raw and normalized read count (RPM), read length, progenitor tRNA information (amino acid, anticodon, locus, strand), tncRNA sequence, and tRNA modification sites.•We hope to facilitate quick and reliable tncRNA identification, which will boost the exploration of this novel class of non-coding RNAs and their relevance in the living world, including plants.

Identification of tRNA-derived small RNAs and their potential roles in porcine skeletal muscle with intrauterine growth restriction

Intrauterine growth restriction (IUGR) in humans often manifests as poor growth and delayed intellectual development, whereas in domestic animals it results in increased mortality. As a novel epigenetic regulatory molecule, tRNA-derived small RNAs (tsRNAs) have been reported to be involved in many biological processes. In this study, pigs (35d) were used as a model to characterize tsRNAs by sequencing in normal and IUGR porcine skeletal muscle. A total of 586 tsRNAs were identified, of which 103 were specifically expressed in normal-size pigs and 38 were specifically expressed in IUGR pigs. The tsRNAs formed by splicing before the 5' end anti codon of mature tRNA (tRF-5c) accounted for over 90% of tsRNAs, which were significantly enriched in IUGR pigs than in normal-size pigs. Enriched pathways of differentially expressed tsRNAs target genes mainly included metabolic pathways, Rap1 signaling pathway, endocytosis, mTOR signaling pathway, and AMPK signaling pathway. Regulatory network analysis of target genes revealed that IGF1 was one of the most important molecules of regulatory nodes in IUGR and normal porcine skeletal muscle. In addition, IGF1 was found to be one of the target genes of tRF-Glu-TTC-047, which is a highly expressed tsRNA in IUGR pigs. The findings described herein uncover the role of tsRNAs in IUGR porcine skeletal muscle development, thus providing insights into the prevention and treatment of IUGR in mammals.

Transfer RNA-derived small RNAs (tsRNAs): Versatile regulators in cancer

tRNA-derived small RNAs (tsRNAs) represent a novel class of regulatory small non-coding RNAs (sncRNAs), produced by the specific cleavage of transfer RNAs (tRNAs). In recent years, pilot studies one after the other have uncovered the critical roles of tsRNAs in various fundamental biological processes as well as in the development of human diseases including cancer. Based on the newly updated hallmarks of cancer, we provide a comprehensive review regarding the dysregulation, functional implications and complicated molecular mechanisms of tsRNAs in cancer. In addition, the potential technical challenges and future prospects in the fields of tsRNA research are discussed in this review.

tRNA derived small RNAs—Small players with big roles

In the past 2 decades, small non-coding RNAs derived from tRNA (tsRNAs or tRNA derived fragments; tRFs) have emerged as new powerful players in the field of small RNA mediated regulation of gene expression, translation, and epigenetic control. tRFs have been identified from evolutionarily divergent organisms from Archaea, the higher plants, to humans. Recent studies have confirmed their roles in cancers and other metabolic disorders in humans and experimental models. They have been implicated in biotic and abiotic stress responses in plants as well. In this review, we summarize the current knowledge on tRFs including types of tRFs, their biogenesis, and mechanisms of action. The review also highlights recent studies involving differential expression profiling of tRFs and elucidation of specific functions of individual tRFs from various species. We also discuss potential considerations while designing experiments involving tRFs identification and characterization and list the available bioinformatics tools for this purpose.

Expression profiles of exosomal tRNA-derived fragments and their biological functions in lipomas

There is evidence that exosomes derived from the lipoma tissue (Exo-LT) have a stronger capacity to promote the proliferation and migration of adipose-derived stem cells (ADSCs) than those from the adipose tissue (Exo-AT). But the Exo-LT do not have a significant effect on the adipogenic differentiation of the ADSCs. Recently, certain exosomal tRNA-derived fragments (tRFs) have been shown to play a crucial role in the pathogenesis of certain tumors. Therefore, it is necessary to identify the differently expressed tRFs in Exo-LT to further elucidate their molecular functions in lipomas. High-throughput sequencing was performed to examine the tRFs and mRNAs from the all samples belonging to the Exo-LT and Exo-AT groups. Target prediction and bioinformatics analysis were performed to explore their downstream mRNAs and biological functions. In total, 456 differently expressed tRFs and tiRNAs were identified in the Exo-LT group, 12 of which were up-regulated and 12 were down-regulated, respectively. Notably, tRF-1001 was most obviously down-regulated and tRF-3004a was most obviously up-regulated in the Exo-LT group. Moreover, among the target genes of tRF-1001 and tRF-3004a, both JAG2 and VSIG4 were significantly down-regulated in the Exo-LT group, while WNT5A, COL1A1, and PPARGC1A were highly expressed in both the Exo-LT and Exo-AT groups. The significant down-regulation of JAG2 and VSIG4 in the Exo-LT group could be due to the fact that Exo-LT had a stronger capacity to promote the proliferation and migration of ADSCs compared to the Exo-AT. The high expression of WNT5A, COL1A1, and PPARGC1A in both the Exo-LT and Exo-AT groups could be due to the similar ability of Exo-LT and Exo-AT to promote the adipogenic differentiation of ADSCs.

Extracellular vesicles-associated tRNA-derived fragments (tRFs): biogenesis, biological functions, and their role as potential biomarkers in human diseases

Traditionally, transfer RNAs (tRNAs) specifically decoded messenger RNA (mRNA) and participated in protein translation. tRNA-derived fragments (tRFs), also known as tRNA-derived small RNAs (tsRNAs), are generated by the specific cleavage of pre- and mature tRNAs and are a class of newly defined functional small non-coding RNAs (sncRNAs). Following the different cleavage positions of precursor or mature tRNA, tRFs are classified into seven types, 5′-tRNA half, 3′-tRNA half, tRF-1, 5′U-tRF, 3′-tRF, 5′-tRF, and i-tRF. It has been demonstrated that tRFs have a diverse range of biological functions in cellular processes, which include inhibiting protein translation, modulating stress response, regulating gene expression, and involvement in cell cycles and epigenetic inheritance. Emerging evidences have indicated that tRFs in extracellular vesicles (EVs) seem to act as regulatory molecules in various cellular processes and play essential roles in cell-to-cell communication. Furthermore, the dysregulation of EV-associated tRFs has been associated with the occurrence and progression of a variety of cancers and they can serve as novel potential biomarkers for cancer diagnosis. In this review, the biogenesis and classification of tRFs are summarized, and the biological functions of EV-associated tRFs and their roles as potential biomarkers in human diseases are discussed.

Transfer RNA-derived non-coding RNAs (tncRNAs): Hidden regulation of plants' transcriptional regulatory circuits

The emergence of distinct classes of non-coding RNAs has led to better insights into the eukaryotic gene regulatory networks. Amongst them, the existence of transfer RNA (tRNA)-derived non-coding RNAs (tncRNAs) demands exploration in the plant kingdom. We have designed a methodology to uncover the entire perspective of tncRNAome in plants. Using this pipeline, we have identified diverse tncRNAs with a size ranging from 14 to 50 nucleotides (nt) by utilizing 2448 small RNA-seq samples from six angiosperms, and studied their various features, including length, codon-usage, cleavage pattern, and modified tRNA nucleosides. Codon-dependent generation of tncRNAs suggests that the tRNA cleavage is highly specific rather than random tRNA degradation. The nucleotide composition analysis of tncRNA cleavage positions indicates that they are generated through precise endoribonucleolytic cleavage machinery. Certain nucleoside modifications detected on tncRNAs were found to be conserved across the plants, and hence may influence tRNA cleavage, as well as tncRNA functions. Pathway enrichment analysis revealed that common tncRNA targets are majorly enriched during metabolic and developmental processes. Further distinct tissue-specific tncRNA clusters highlight their role in plant development. Significant number of tncRNAs differentially expressed under abiotic and biotic stresses highlights their potential role in stress resistance. In summary, this study has developed a platform that will help in the understanding of tncRNAs and their involvement in growth, development, and response to various stresses. The workflow, software package, and results are freely available at http://nipgr.ac.in/tncRNA.

Plant transfer RNA-derived fragments: Biogenesis and functions

Processing of mature transfer RNAs (tRNAs) produces complex populations of tRNA-derived fragments (tRFs). Emerging evidence shows that tRFs have important functions in bacteria, animals, and plants. Here, we review recent advances in understanding plant tRFs, focusing on their biological and cellular functions, such as regulating stress responses, mediating plant-pathogen interactions, and modulating post-transcriptional gene silencing and translation. We also review sequencing strategies and bioinformatics resources for studying tRFs in plants. Finally, we discuss future directions for plant tRF research, which will expand our knowledge of plant non-coding RNAs.

tRNA-derived fragments as New Hallmarks of Aging and Age-related Diseases

tRNA-derived fragments (tRFs), which are non-coding RNAs produced via tRNA cleavage with lengths of 14 to 50 nucleotides, originate from precursor tRNAs or mature tRNAs and exist in a wide range of organisms. tRFs are produced not by random fracture of tRNAs but by specific mechanisms. Considerable evidence shows that tRFs are detectable in model organisms of different ages and are associated with age-related diseases in humans, such as cancer and neurodegenerative diseases. In this literature review, the origin and classification of tRFs and the regulatory mechanisms of tRFs in aging and age-related diseases are summarized. We also describe the available tRF databases and research techniques and lay a foundation for the exploration of tRFs as biomarkers for the diagnosis and treatment of aging and age-related diseases.

tsRNAsearch: A pipeline for the identification of tRNA and ncRNA fragments from small RNA-sequencing data

MOTIVATION

tRNAs were originally considered uni-functional RNA molecules involved in the delivery of amino acids to growing peptide chains on the ribosome. More recently, the liberation of tRNA fragments from tRNAs via specific enzyme cleavage has been characterized. Detection of tRNA fragments in sequencing data is difficult due to tRNA sequence redundancy and the short length of both tRNAs and their fragments.

RESULTS

Here we introduce tsRNAsearch, a Nextflow pipeline for the identification of differentially abundant tRNA fragments and other non-coding RNAs from small RNA-sequencing data. tsRNAsearch is intended for use when comparing two groups of datasets, such as control and treatment groups. tsRNAsearch comparatively searches for tRNAs and ncRNAs with irregular read distribution profiles (a proxy for RNA cleavage) using a combined score made up of four novel methods and a differential expression analysis, and reports the top ranked results in simple PDF and TEXT files. In this study, we used publicly available small RNA-seq data to replicate the identification of tsRNAs from chronic hepatitis-infected liver tissue data. In addition, we applied tsRNAsearch to pancreatic ductal adenocarcinoma (PDAC) and matched healthy pancreatic tissue small RNA-sequencing data. Our results support the identification of miR135b from the original study as a potential biomarker of PDAC and identify other potentially stronger miRNA biomarkers of PDAC.

AVAILABILITY

https://github.com/GiantSpaceRobot/tsRNAsearch.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

tRFTars: predicting the targets of tRNA-derived fragments

Background

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. 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.

Methods

We 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.

Results

We 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).

Conclusions

Predictions 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.

Circulating tRNA-derived small RNAs (tsRNAs) signature for the diagnosis and prognosis of breast cancer

Liquid biopsy is noninvasive and convenient to detect cancer-derived materials in blood or other body fluids. The aim of this study was to identify tRNA-derived small RNAs (tsRNAs) in plasma that could distinguish patients with breast cancer (BC) from healthy controls. Basing on high-throughput sequencing, 15 significantly upregulated tsRNAs were selected and assessed in cell supernatants and cell lines. 6 tsRNAs were identified and verified in a large cohort of 120 patients with BC and 112 healthy controls. tRF-Arg-CCT-017, tRF-Gly-CCC-001, and tiRNA-Phe-GAA-003 could serve as novel diagnostic biomarkers. Meanwhile, tRF-Arg-CCT-017 and tiRNA-Phe-GAA-003 could also act as prognostic biomarkers. Target genes of these tsRNAs were related to the development of cancers. These results suggested that specific tsRNAs in plasma might serve as diagnostic and prognostic biomarkers of BC.

Global profile of tRNA-derived small RNAs in gastric cancer patient plasma and identification of tRF-33-P4R8YP9LON4VDP as a new tumor suppressor

Transfer RNA (tRNA)-derived small RNAs (tsRNAs) have been found to play important roles in the occurrence and development of cancers. However, the tsRNA profile in gastric cancer is unknown. In this study, we aimed to identify the global tsRNA profile in plasma from gastric cancer patients and elucidate the role of tRF-33-P4R8YP9LON4VDP in gastric cancer. Differentially expressed tsRNAs in the plasma of gastric cancer patients and healthy controls were investigated using RNA sequencing. The expression levels of tRF-33-P4R8YP9LON4VDP in the plasma of gastric cancer patients, healthy controls and gastric cancer cell lines were first detected by quantitative reverse transcription-polymerase chain reaction. The effects of tRF-33-P4R8YP9LON4VDP overexpression or downregulation in gastric cancer cells on proliferation, migration, apoptosis, and cell cycle were analyzed using the Cell Counting Kit-8, scratch assay, Transwell assay, and flow cytometry, respectively. There were 21 upregulated and 46 downregulated tsRNAs found in plasma from gastric cancer patients. The significantly upregulated tsRNAs included tRF-18-S3M83004, tRF-31-PNR8YP9LON4VD, tRF-19-3L7L73JD, tRF-33-P4R8YP9LON4VDP, tRF-31-PER8YP9LON4VD, tRF-18-MBQ4NKDJ, and tRF-31-PIR8YP9LON4VD. The significantly downregulated tsRNAs included tRF-41-YDLBRY73W0K5KKOVD, tRF-18-07QSNHD2, tRF-28-86J8WPMN1E0J, tRF-29-86V8WPMN1EJ3, tRF-31-6978WPRLXN4VE, tRF-30-MIF91SS2P46I, tRF-26-MI7O3B1NR8E, tRF-30-RRJ89O9NF5W8, tRF-26-XIP2801MK8E, and tRF-35-V0J8O9YEKPRS93, In vitro studies showed that tRF-33-P4R8YP9LON4VDP inhibited proliferation of gastric cancer cells. In conclusion, tsRNAs such as tRF-33-P4R8YP9LON4VDP could serve as a novel diagnostic biomarker and target for gastric cancer therapeutics.

Computational methods for annotation of plant regulatory non-coding RNAs using RNA-seq

Plant transcriptome encompasses numerous endogenous, regulatory non-coding RNAs (ncRNAs) that play a major biological role in regulating key physiological mechanisms. While studies have shown that ncRNAs are extremely diverse and ubiquitous, the functions of the vast majority of ncRNAs are still unknown. With ever-increasing ncRNAs under study, it is essential to identify, categorize and annotate these ncRNAs on a genome-wide scale. The use of high-throughput RNA sequencing (RNA-seq) technologies provides a broader picture of the non-coding component of transcriptome, enabling the comprehensive identification and annotation of all major ncRNAs across samples. However, the detection of known and emerging class of ncRNAs from RNA-seq data demands complex computational methods owing to their unique as well as similar characteristics. Here, we discuss major plant endogenous, regulatory ncRNAs in an RNA sample followed by computational strategies applied to discover each class of ncRNAs using RNA-seq. We also provide a collection of relevant software packages and databases to present a comprehensive bioinformatics toolbox for plant ncRNA researchers. We assume that the discussions in this review will provide a rationale for the discovery of all major categories of plant ncRNAs.

Hijacking tRNAs From Translation: Regulatory Functions of tRNAs in Mammalian Cell Physiology

Transfer tRNAs (tRNAs) are small non-coding RNAs that are highly conserved in all kingdoms of life. Originally discovered as the molecules that deliver amino acids to the growing polypeptide chain during protein synthesis, tRNAs have been believed for a long time to play exclusive role in translation. However, recent studies have identified key roles for tRNAs and tRNA-derived small RNAs in multiple other processes, including regulation of transcription and translation, posttranslational modifications, stress response, and disease. These emerging roles suggest that tRNAs may be central players in the complex machinery of biological regulatory pathways. Here we overview these non-canonical roles of tRNA in normal physiology and disease, focusing largely on eukaryotic and mammalian systems.

On the expanding roles of tRNA fragments in modulating cell behavior

The fragments that derive from transfer RNAs (tRNAs) are an emerging category of regulatory RNAs. Known as tRFs, these fragments were reported for the first time only a decade ago, making them a relatively recent addition to the ever-expanding pantheon of non-coding RNAs. tRFs are short, 16-35 nucleotides (nts) in length, and produced through cleavage of mature and precursor tRNAs at various positions. Both cleavage positions and relative tRF abundance depend strongly on context, including the tissue type, tissue state, and disease, as well as the sex, population of origin, and race/ethnicity of an individual. These dependencies increase the urgency to understand the regulatory roles of tRFs. Such efforts are gaining momentum, and comprise experimental and computational approaches. System-level studies across many tissues and thousands of samples have produced strong evidence that tRFs have important and multi-faceted roles. Here, we review the relevant literature on tRF biology in higher organisms, single cell eukaryotes, and prokaryotes.

tRNA Fragments Populations Analysis in Mutants Affecting tRNAs Processing and tRNA Methylation

tRNA fragments (tRFs) are a class of small non-coding RNAs (sncRNAs) derived from tRNAs. tRFs are highly abundant in many cell types including stem cells and cancer cells, and are found in all domains of life. Beyond translation control, tRFs have several functions ranging from transposon silencing to cell proliferation control. However, the analysis of tRFs presents specific challenges and their biogenesis is not well understood. They are very heterogeneous and highly modified by numerous post-transcriptional modifications. Here we describe a bioinformatic pipeline (tRFs-Galaxy) to study tRFs populations and shed light onto tRNA fragments biogenesis in Drosophila melanogaster. Indeed, we used small RNAs Illumina sequencing datasets extracted from wild type and mutant ovaries affecting two different highly conserved steps of tRNA biogenesis: 5'pre-tRNA processing (RNase-P subunit Rpp30) and tRNA 2'-O-methylation (dTrm7_34 and dTrm7_32). Using our pipeline, we show how defects in tRNA biogenesis affect nuclear and mitochondrial tRFs populations and other small non-coding RNAs biogenesis, such as small nucleolar RNAs (snoRNAs). This tRF analysis workflow will advance the current understanding of tRFs biogenesis, which is crucial to better comprehend tRFs roles and their implication in human pathology.

tRNA-Derived Small RNAs: Novel Epigenetic Regulators

Simple Summary

Cells must synthesize new proteins to maintain its life and tRNA (transfer RNA) is an essential component of the translation process. tRNA-derived small RNA (tsRNA) is a relatively uncharacterized small RNA, derived from enzymatic cleavage of the tRNAs. Accumulating evidences suggest that tsRNA is an abundant, highly modified, dynamically regulated small-RNA and interacts with other types of RNAs or proteins. Moreover, it is abnormally expressed in multiple human diseases including systemic lupus, neurological disorder, metabolic disorder and cancer, implying its diverse function in the initiation or progression of such diseases. In this review, we summarize the classification of tsRNA and its role focused on the epigenetic regulation. Further, we discuss the limitation of current knowledge about the tsRNA and its potential applications.

Abstract

An epigenetic change is a heritable genetic alteration that does not involve any nucleotide changes. While the methylation of specific DNA regions such as CpG islands or histone modifications, including acetylation or methylation, have been investigated in detail, the role of small RNAs in epigenetic regulation is largely unknown. Among the many types of small RNAs, tRNA-derived small RNAs (tsRNAs) represent a class of noncoding small RNAs with multiple roles in diverse physiological processes, including neovascularization, sperm maturation, immune modulation, and stress response. Regarding these roles, several pioneering studies have revealed that dysregulated tsRNAs are associated with human diseases, such as systemic lupus, neurological disorder, metabolic disorder, and cancer. Moreover, recent findings suggest that tsRNAs regulate the expression of critical genes linked with these diseases by a variety of mechanisms, including epigenetic regulation. In this review, we will describe different classes of tsRNAs based on their biogenesis and will focus on their role in epigenetic regulation.

Transcriptome-Wide Analysis of Interplay between mRNA Stability, Translation and Small RNAs in Response to Neuronal Membrane Depolarization

Experience-dependent changes to neural circuitry are shaped by spatially-restricted activity-dependent mRNA translation. Although the complexity of mRNA translation in neuronal cells is widely appreciated, translational profiles associated with neuronal excitation remain largely uncharacterized, and the associated regulatory mechanisms are poorly understood. Here, we employed ribosome profiling, mRNA sequencing and small RNA sequencing to profile transcriptome-wide changes in mRNA translation after whole cell depolarization of differentiated neuroblast cultures, and investigate the contribution of sequence-specific regulatory mechanisms. Immediately after depolarization, a functional partition between transcriptional and translational responses was uncovered, in which many mRNAs were subjected to significant changes in abundance or ribosomal occupancy, but not both. After an extended (2 h) post-stimulus rest phase, however, these changes became synchronized, suggesting that there are different layers of post-transcriptional regulation which are temporally separated but become coordinated over time. Globally, changes in mRNA abundance and translation were found to be associated with a number of intrinsic mRNA features, including mRNA length, GC% and secondary structures; however, the effect of these factors differed between both post-depolarization time-points. Furthermore, small RNA sequencing revealed that miRNAs and tRNA-derived small RNA fragments were subjected to peak changes in expression immediately after stimulation, during which these molecules were predominantly associated with fluctuations in mRNA abundance, consistent with known regulatory mechanisms. These data suggest that excitation-associated neuronal translation is subjected to extensive temporal coordination, with substantial contributions from a number of sequence-dependent regulatory mechanisms.

Mycobacterium tuberculosis Infection Drives Mitochondria-Biased Dysregulation of Host Transfer RNA-Derived Fragments

BACKGROUND

Mycobacterium tuberculosis (Mtb), the bacterium that causes tuberculosis, causes 10 million infections and 1.5 million deaths per year worldwide. The success of Mtb as a human pathogen is directly related to its ability to suppress host responses, which are critical for clearing intracellular pathogens. Emerging evidence suggests that key response pathways may be regulated by a novel class of small noncoding RNA, called transfer RNA (tRNA)-derived fragments (tRFs). tRFs can complex with Argonaute proteins to target and degrade messenger RNA targets, similarly to micro RNAs, but have thus far been overlooked in the context of bacterial infections.

METHODS

We generated a novel miRge2.0-based tRF-analysis tool, tRFcluster, and used it to analyze independently generated and publicly available RNA-sequencing datasets to assess tRF dysregulation in host cells following infection with Mtb and other intracellular bacterial pathogens.

RESULTS

We found that Mtb and Listeria monocytogenes drive dramatic tRF dysregulation, whereas other bacterial pathogens do not. Interestingly, Mtb infection uniquely increased the expression of mitochondria-derived tRFs rather than genomic-derived tRFs, suggesting an association with mitochondrial damage in Mtb infection.

CONCLUSIONS

tRFs are dysregulated in some, but not all, bacterial infections. Biased dysregulation of mitochondria-derived tRFs in Mtb infection suggests a link between mitochondrial distress and tRF production.

Action mechanisms and research methods of tRNA-derived small RNAs

tRNA-derived small RNAs (tsRNAs), including tRNA-derived fragments (tRFs) and tRNA halves (tiRNAs), are small regulatory RNAs processed from mature tRNAs or precursor tRNAs. tRFs and tiRNAs play biological roles through a variety of mechanisms by interacting with proteins or mRNA, inhibiting translation, and regulating gene expression, the cell cycle, and chromatin and epigenetic modifications. The establishment and application of research technologies are important in understanding the biological roles of tRFs and tiRNAs. To study the molecular mechanisms of tRFs and tiRNAs, researchers have used a variety of bioinformatics and molecular biology methods, such as microarray analysis, real-time quantitative reverse transcription-polymerase chain reaction (qRT-PCR); Northern blotting; RNA sequencing (RNA-seq); cross-linking, ligation and sequencing of hybrids (CLASH); and photoactivatable-ribonucleoside-enhanced cross-linking and immunoprecipitation (PAR-CLIP). This paper summarizes the classification, action mechanisms, and roles of tRFs and tiRNAs in human diseases and the related signal transduction pathways, targeted therapies, databases, and research methods associated with them.

OncotRF: an online resource for exploration of tRNA-derived fragments in human cancers

Transfer RNA-derived fragments (tRFs) are a new class of small non-coding RNAs whose biological roles in cancers are not well understood. Emerging evidence suggests that tRFs are involved in gene regulation at multiple levels. In this study, we constructed an integrative database, OncotRF (http://bioinformatics.zju.edu.cn/OncotRF), for in silico exploration of tRF functions, and identification of diagnostic and prognostic biomarkers in cancers. The database contains an analysis pipeline for tRF identification and characterization, analysis results of 11,211 small RNA sequencing samples and 8,776 RNA sequencing samples, and clinicopathologic annotation data from The Cancer Genome Atlas (TCGA). The results include: tRF identification and quantification across 33 cancers, abnormally expressed tRFs and genes, tRF-gene correlations, tRF-gene networks, survival analyses, and tRF-related functional enrichment analyses. Users are also able to identify differentially expressed tRFs, predict their functions, and assess the relevance of the tRF expression levels to the clinical outcome according to user-defined groups. Additionally, an online Kaplan-Meier plotter is available in OncotRF for plotting survival curves according to user-defined groups. OncotRF will be a valuable online database and functional annotation tool for researchers studying the roles, functions, and mechanisms of tRFs in human cancers.

Pervasive Small RNAs in Cardiometabolic Research: Great Potential Accompanied by Biological and Technical Barriers

Advances in small RNA sequencing have revealed the enormous diversity of small noncoding RNA (sRNA) classes in mammalian cells. At this point, most investigators in diabetes are aware of the success of microRNA (miRNA) research and appreciate the importance of posttranscriptional gene regulation in glycemic control. Nevertheless, miRNAs are just one of multiple classes of sRNAs and likely represent only a minor fraction of sRNA sequences in a given cell. Despite the widespread appreciation of sRNAs, very little research into non-miRNA sRNA function has been completed, likely due to some major barriers that present unique challenges for study. To emphasize the importance of sRNA research in cardiometabolic diseases, we highlight the success of miRNAs and competitive endogenous RNAs in cholesterol and glucose metabolism. Moreover, we argue that sequencing studies have demonstrated that miRNAs are just the tip of the iceberg for sRNAs. We are likely standing at the precipice of immense discovery for novel sRNA-mediated gene regulation in cardiometabolic diseases. To realize this potential, we must first address critical barriers with an open mind and refrain from viewing non-miRNA sRNA function through the lens of miRNAs, as they likely have their own set of distinct regulatory factors and functional mechanisms.

Role of tRNA-derived fragments in cancer: novel diagnostic and therapeutic targets tRFs in cancer

Recent studies have revealed that tRNAs are not always the terminal molecules and small RNA fragments can be mapped to precursor tRNA sequences or mature tRNA sequences. tRNA-derived fragments (tRFs) are a novel class of small RNAs in miRNA-size found in a diverse range of organisms and can be the source of small regulatory RNAs, a previously unanticipated concept. tRFs have a diverse range of effects on cells involving in cell differentiation and homeostasis. They play a critical role in pathological processes, particularly in cancer, and therefore can modulate complicated regulatory networks. Recent studies on the role of tRFs in tumorigenesis suggest that they are promising targets for diagnosis and therapeutics. Improvement in experimental and computational approaches permit a greater understanding of the regulatory networks and will have a significant impact on both basic and clinical research.

Small noncoding RNA discovery and profiling with sRNAtools based on high-throughput sequencing

Small noncoding RNAs (sRNA/sncRNAs) are generated from different genomic loci and play important roles in biological processes, such as cell proliferation and the regulation of gene expression. Next-generation sequencing (NGS) has provided an unprecedented opportunity to discover and quantify diverse kinds of sncRNA, such as tRFs (tRNA-derived small RNA fragments), phasiRNAs (phased, secondary, small-interfering RNAs), Piwi-interacting RNA (piRNAs) and plant-specific 24-nt short interfering RNAs (siRNAs). However, currently available web-based tools do not provide approaches to comprehensively analyze all of these diverse sncRNAs. This study presents a novel integrated platform, sRNAtools (https://bioinformatics.caf.ac.cn/sRNAtools), that can be used in conjunction with high-throughput sequencing to identify and functionally annotate sncRNAs, including profiling microRNAss, piRNAs, tRNAs, small nuclear RNAs, small nucleolar RNAs and rRNAs and discovering isomiRs, tRFs, phasiRNAs and plant-specific 24-nt siRNAs for up to 21 model organisms. Different modules, including single case, batch case, group case and target case, are developed to provide users with flexible ways of studying sncRNA. In addition, sRNAtools supports different ways of uploading small RNA sequencing data in a very interactive queue system, while local versions based on the program package/Docker/virtureBox are also available. We believe that sRNAtools will greatly benefit the scientific community as an integrated tool for studying sncRNAs.

Dysregulation of different classes of tRNA fragments in chronic lymphocytic leukemia

Chronic lymphocytic leukemia (CLL) is the most common human leukemia, and dysregulation of tRNA-derived short noncoding RNA (tsRNA) (tRF-1) expression is an accompanying event in the development of this disease. tsRNAs are fragments originating from the 3' end of tRNA precursors and do not contain mature tRNA sequences. In contrast to tsRNAs, mature tRFs (tRF-3s, tRF-5s, and internal tRFs) are produced from mature tRNA sequences and are redundant fragments. We investigated tsRNA expression in CLL and determined tsRNA signatures in indolent CLL and aggressive CLL vs. normal B cells. We noticed that both ts-43 and ts-44 are derived from distinct genes of pre-tRNA^His, and are down-regulated in CLL 3- to 5-fold vs. normal B cells. Thus, we investigated expression levels of tRF-5 fragments from tRNA^His in CLL samples and healthy controls, and determined that such fragments are down-regulated by 5-fold in CLLs vs. normal controls. Given these results, we investigated the expression of all mature tRFs in CLLs vs. normal controls. We found a drastic dysregulation of the expression of mature tRFs in CLL. In aggressive CLL, for the top 15 up-regulated fragments, linear fold change varied from 2,053- to 622-fold. For the top 15 down-regulated fragments in CLL, linear fold change varied from 314- to 52-fold. In addition, 964 mature tRFs were up-regulated at least 2-fold in CLL, while 701 fragments were down-regulated at least 2-fold. Similar results were obtained for indolent CLL. Our results suggest that mature tRFs may have oncogenic and/or tumor suppressor function in CLL.

DEUS: an R package for accurate small RNA profiling based on differential expression of unique sequences

Summary

Despite their fundamental role in various biological processes, the analysis of small RNA sequencing data remains a challenging task. Major obstacles arise when short RNA sequences map to multiple locations in the genome, align to regions that are not annotated or underwent post-transcriptional changes which hamper accurate mapping. In order to tackle these issues, we present a novel profiling strategy that circumvents the need for read mapping to a reference genome by utilizing the actual read sequences to determine expression intensities. After differential expression analysis of individual sequence counts, significant sequences are annotated against user defined feature databases and clustered by sequence similarity. This strategy enables a more comprehensive and concise representation of small RNA populations without any data loss or data distortion.

Availability and implementation

Code and documentation of our R package at http://ibis.helmholtz-muenchen.de/deus/.

Supplementary information

Supplementary data are available at Bioinformatics online.

Differential expression of human tRNA genes drives the abundance of tRNA-derived fragments

The human genome encodes hundreds of transfer RNA (tRNA) genes but their individual contribution to the tRNA pool is not fully understood. Deep sequencing of tRNA transcripts (tRNA-Seq) can estimate tRNA abundance at single gene resolution, but tRNA structures and posttranscriptional modifications impair these analyses. Here we present a bioinformatics strategy to investigate differential tRNA gene expression and use it to compare tRNA-Seq datasets from cultured human cells and human brain. We find that sequencing caveats affect quantitation of only a subset of human tRNA genes. Unexpectedly, we detect several cases where the differences in tRNA expression among samples do not involve variations at the level of isoacceptor tRNA sets (tRNAs charged with the same amino acid but using different anticodons), but rather among tRNA genes within the same isodecoder set (tRNAs having the same anticodon sequence). Because isodecoder tRNAs are functionally equal in terms of genetic translation, their differential expression may be related to noncanonical tRNA functions. We show that several instances of differential tRNA gene expression result in changes in the abundance of tRNA-derived fragments (tRFs) but not of mature tRNAs. Examples of differentially expressed tRFs include PIWI-associated RNAs, tRFs present in tissue samples but not in cells cultured in vitro, and somatic tissue-specific tRFs. Our data support that differential expression of tRNA genes regulate noncanonical tRNA functions performed by tRFs.

Novel molecules lncRNAs, tRFs and circRNAs deciphered from next-generation sequencing/RNA sequencing: computational databases and tools

Powerful next-generation sequencing (NGS) technologies, more specifically RNA sequencing (RNA-seq), have been pivotal toward the detection and analysis and hypotheses generation of novel biomolecules, long noncoding RNAs (lncRNAs), tRNA-derived fragments (tRFs) and circular RNAs (circRNAs). Experimental validation of the occurrence of these biomolecules inside the cell has been reported. Their differential expression and functionally important role in several cancers types as well as other diseases such as Alzheimer's and cardiovascular diseases have garnered interest toward further studies in this research arena. In this review, starting from a brief relevant introduction to NGS and RNA-seq and the expression and role of lncRNAs, tRFs and circRNAs in cancer, we have comprehensively analyzed the current landscape of databases developed and computational software used for analyses and visualization for this emerging and highly interesting field of these novel biomolecules. Our review will help the end users and research investigators gain information on the existing databases and tools as well as an understanding of the specific features which these offer. This will be useful for the researchers in their proper usage thereby guiding them toward novel hypotheses generation and saving time and costs involved in extensive experimental processes in these three different novel functional RNAs.

tRNA-Derived Small RNAs: Biogenesis, Modification, Function and Potential Impact on Human Disease Development

Transfer RNAs (tRNAs) are abundant small non-coding RNAs that are crucially important for decoding genetic information. Besides fulfilling canonical roles as adaptor molecules during protein synthesis, tRNAs are also the source of a heterogeneous class of small RNAs, tRNA-derived small RNAs (tsRNAs). Occurrence and the relatively high abundance of tsRNAs has been noted in many high-throughput sequencing data sets, leading to largely correlative assumptions about their potential as biologically active entities. tRNAs are also the most modified RNAs in any cell type. Mutations in tRNA biogenesis factors including tRNA modification enzymes correlate with a variety of human disease syndromes. However, whether it is the lack of tRNAs or the activity of functionally relevant tsRNAs that are causative for human disease development remains to be elucidated. Here, we review the current knowledge in regard to tsRNAs biogenesis, including the impact of RNA modifications on tRNA stability and discuss the existing experimental evidence in support for the seemingly large functional spectrum being proposed for tsRNAs. We also argue that improved methodology allowing exact quantification and specific manipulation of tsRNAs will be necessary before developing these small RNAs into diagnostic biomarkers and when aiming to harness them for therapeutic purposes.

PtRFdb: a database for plant transfer RNA-derived fragments

Transfer RNA-derived fragments (tRFs) represent a novel class of small RNAs (sRNAs) generated through endonucleolytic cleavage of both mature and precursor transfer RNAs (tRNAs). These 14–28 nt length tRFs that have been extensively studied in animal kingdom are to be explored in plants. In this study, we introduce a database of plant tRFs named PtRFdb (www.nipgr.res.in/PtRFdb), for the scientific community. We analyzed a total of 1344 sRNA sequencing datasets of 10 different plant species and identified a total of 5607 unique tRFs (758 tRF-1, 2269 tRF-3 and 2580 tRF-5), represented by 487 765 entries. In PtRFdb, detailed and comprehensive information is available for each tRF entry. Apart from the core information consisting of the tRF type, anticodon, source organism, tissue, sequence and the genomic location; additional information like PubMed identifier (PMID), Sample accession number (GSM), sequence length and frequency relevant to the tRFs may be of high utility to the user. Two different types of search modules (Basic Search and Advanced Search), sequence similarity search (by BLAST) and Browse option with data download facility for each search is provided in this database. We believe that PtRFdb is a unique database of its kind and it will be beneficial in the validation and further characterization of plant tRFs.

Database URL: http://www.nipgr.res.in/PtRFdb/

Bioinformatic analysis of endogenous and exogenous small RNAs on lipoproteins

To comprehensively study extracellular small RNAs (sRNA) by sequencing (sRNA-seq), we developed a novel pipeline to overcome current limitations in analysis entitled, "Tools for Integrative Genome analysis of Extracellular sRNAs (TIGER)". To demonstrate the power of this tool, sRNA-seq was performed on mouse lipoproteins, bile, urine and livers. A key advance for the TIGER pipeline is the ability to analyse both host and non-host sRNAs at genomic, parent RNA and individual fragment levels. TIGER was able to identify approximately 60% of sRNAs on lipoproteins and >85% of sRNAs in liver, bile and urine, a significant advance compared to existing software. Moreover, TIGER facilitated the comparison of lipoprotein sRNA signatures to disparate sample types at each level using hierarchical clustering, correlations, beta-dispersions, principal coordinate analysis and permutational multivariate analysis of variance. TIGER analysis was also used to quantify distinct features of exRNAs, including 5' miRNA variants, 3' miRNA non-templated additions and parent RNA positional coverage. Results suggest that the majority of sRNAs on lipoproteins are non-host sRNAs derived from bacterial sources in the microbiome and environment, specifically rRNA-derived sRNAs from Proteobacteria. Collectively, TIGER facilitated novel discoveries of lipoprotein and biofluid sRNAs and has tremendous applicability for the field of extracellular RNA.

tRNA fragments (tRFs) guide Ago to regulate gene expression post-transcriptionally in a Dicer-independent manner

tRNA related RNA fragments (tRFs), also known as tRNA-derived RNAs (tdRNAs), are abundant small RNAs reported to be associated with Argonaute proteins, yet their function is unclear. We show that endogenous 18 nucleotide tRFs derived from the 3' ends of tRNAs (tRF-3) post-transcriptionally repress genes in HEK293T cells in culture. tRF-3 levels increase upon parental tRNA overexpression. This represses target genes with a sequence complementary to the tRF-3 in the 3' UTR. The tRF-3-mediated repression is Dicer-independent, Argonaute-dependent, and the targets are recognized by sequence complementarity. Furthermore, tRF-3:target mRNA pairs in the RNA induced silencing complex associate with GW182 proteins, known to repress translation and promote the degradation of target mRNAs. RNA-seq demonstrates that endogenous target genes are specifically decreased upon tRF-3 induction. Therefore, Dicer-independent tRF-3s, generated upon tRNA overexpression, repress genes post-transcriptionally through an Argonaute-GW182 containing RISC via sequence matches with target mRNAs.

SPORTS1.0: A Tool for Annotating and Profiling Non-coding RNAs Optimized for rRNA- and tRNA-derived Small RNAs

High-throughput RNA-seq has revolutionized the process of small RNA (sRNA) discovery, leading to a rapid expansion of sRNA categories. In addition to the previously well-characterized sRNAs such as microRNAs (miRNAs), piwi-interacting RNAs (piRNAs), and small nucleolar RNA (snoRNAs), recent emerging studies have spotlighted on tRNA-derived sRNAs (tsRNAs) and rRNA-derived sRNAs (rsRNAs) as new categories of sRNAs that bear versatile functions. Since existing software and pipelines for sRNA annotation are mostly focused on analyzing miRNAs or piRNAs, here we developed the sRNA annotation pipelineoptimized for rRNA- and tRNA-derived sRNAs (SPORTS1.0). SPORTS1.0 is optimized for analyzing tsRNAs and rsRNAs from sRNA-seq data, in addition to its capacity to annotate canonical sRNAs such as miRNAs and piRNAs. Moreover, SPORTS1.0 can predict potential RNA modification sites based on nucleotide mismatches within sRNAs. SPORTS1.0 is precompiled to annotate sRNAs for a wide range of 68 species across bacteria, yeast, plant, and animal kingdoms, while additional species for analyses could be readily expanded upon end users' input. For demonstration, by analyzing sRNA datasets using SPORTS1.0, we reveal that distinct signatures are present in tsRNAs and rsRNAs from different mouse cell types. We also find that compared to other sRNA species, tsRNAs bear the highest mismatch rate, which is consistent with their highly modified nature. SPORTS1.0 is an open-source software and can be publically accessed at https://github.com/junchaoshi/sports1.0.

Heavy Chronic Intermittent Ethanol Exposure Alters Small Noncoding RNAs in Mouse Sperm and Epididymosomes

While the risks of maternal alcohol abuse during pregnancy are well-established, several preclinical studies suggest that chronic preconception alcohol consumption by either parent may also have significance consequences for offspring health and development. Notably, since isogenic male mice used in these studies are not involved in gestation or rearing of offspring, the cross-generational effects of paternal alcohol exposure suggest a germline-based epigenetic mechanism. Many recent studies have demonstrated that the effects of paternal environmental exposures such as stress or malnutrition can be transmitted to the next generation via alterations to small noncoding RNAs in sperm. Therefore, we used high throughput sequencing to examine the effect of preconception ethanol on small noncoding RNAs in sperm. We found that chronic intermittent ethanol exposure altered several small noncoding RNAs from three of the major small RNA classes in sperm, tRNA-derived small RNA (tDR), mitochondrial small RNA, and microRNA. Six of the ethanol-responsive small noncoding RNAs were evaluated with RT-qPCR on a separate cohort of mice and five of the six were confirmed to be altered by chronic ethanol exposure, supporting the validity of the sequencing results. In addition to altered sperm RNA abundance, chronic ethanol exposure affected post-transcriptional modifications to sperm small noncoding RNAs, increasing two nucleoside modifications previously identified in mitochondrial tRNA. Furthermore, we found that chronic ethanol reduced epididymal expression of a tRNA methyltransferase, Nsun2, known to directly regulate tDR biogenesis. Finally, ethanol-responsive sperm tDR are similarly altered in extracellular vesicles of the epididymis (i.e., epididymosomes), supporting the hypothesis that alterations to sperm tDR emerge in the epididymis and that epididymosomes are the primary source of small noncoding RNAs in sperm. These results add chronic ethanol to the growing list of paternal exposures that can affect small noncoding RNA abundance and nucleoside modifications in sperm. As small noncoding RNAs in sperm have been shown to causally induce heritable phenotypes in offspring, additional research is warranted to understand the potential effects of ethanol-responsive sperm small noncoding RNAs on offspring health and development.

MINTbase v2.0: a comprehensive database for tRNA-derived fragments that includes nuclear and mitochondrial fragments from all The Cancer Genome Atlas projects

MINTbase is a repository that comprises nuclear and mitochondrial tRNA-derived fragments ('tRFs') found in multiple human tissues. The original version of MINTbase comprised tRFs obtained from 768 transcriptomic datasets. We used our deterministic and exhaustive tRF mining pipeline to process all of The Cancer Genome Atlas datasets (TCGA). We identified 23 413 tRFs with abundance of ≥ 1.0 reads-per-million (RPM). To facilitate further studies of tRFs by the community, we just released version 2.0 of MINTbase that contains information about 26 531 distinct human tRFs from 11 719 human datasets as of October 2017. Key new elements include: the ability to filter tRFs on-the-fly by minimum abundance thresholding; the ability to filter tRFs by tissue keywords; easy access to information about a tRF's maximum abundance and the datasets that contain it; the ability to generate relative abundance plots for tRFs across cancer types and convert them into embeddable figures; MODOMICS information about modifications of the parental tRNA, etc. Version 2.0 of MINTbase contains 15x more datasets and nearly 4x more distinct tRFs than the original version, yet continues to offer fast, interactive access to its contents. Version 2.0 is available freely at http://cm.jefferson.edu/MINTbase/.