Small RNA Sequencing across Diverse Biofluids Identifies Optimal Methods for exRNA Isolation.

Poor reproducibility within and across studies arising from lack of knowledge regarding the performance of extracellular RNA (exRNA) isolation methods has hindered progress in the exRNA field. A systematic comparison of 10 exRNA isolation methods across 5 biofluids revealed marked differences in the complexity and reproducibility of the resulting small RNA-seq profiles. The relative efficiency with which each method accessed different exRNA carrier subclasses was determined by estimating the proportions of extracellular vesicle (EV)-, ribonucleoprotein (RNP)-, and high-density lipoprotein (HDL)-specific miRNA signatures in each profile. An interactive web-based application (miRDaR) was developed to help investigators select the optimal exRNA isolation method for their studies. miRDar provides comparative statistics for all expressed miRNAs or a selected subset of miRNAs in the desired biofluid for each exRNA isolation method and returns a ranked list of exRNA isolation methods prioritized by complexity, expression level, and reproducibility. These results will improve reproducibility and stimulate further progress in exRNA biomarker development.

Coding-independent regulation of the tumor suppressor PTEN by competing endogenous mRNAs.

Here, we demonstrate that protein-coding RNA transcripts can crosstalk by competing for common microRNAs, with microRNA response elements as the foundation of this interaction. We have termed such RNA transcripts as competing endogenous RNAs (ceRNAs). We tested this hypothesis in the context of PTEN, a key tumor suppressor whose abundance determines critical outcomes in tumorigenesis. By a combined computational and experimental approach, we identified and validated endogenous protein-coding transcripts that regulate PTEN, antagonize PI3K/AKT signaling, and possess growth- and tumor-suppressive properties. Notably, we also show that these genes display concordant expression patterns with PTEN and copy number loss in cancers. Our study presents a road map for the prediction and validation of ceRNA activity and networks and thus imparts a trans-regulatory function to protein-coding mRNAs.

MINRbase: a comprehensive database of nuclear- and mitochondrial-ribosomal-RNA-derived fragments (rRFs).

We describe the Mitochondrial and Nuclear rRNA fragment database (MINRbase), a knowledge repository aimed at facilitating the study of ribosomal RNA-derived fragments (rRFs). MINRbase provides interactive access to the profiles of 130 238 expressed rRFs arising from the four human nuclear rRNAs (18S, 5.8S, 28S, 5S), two mitochondrial rRNAs (12S, 16S) or four spacers of 45S pre-rRNA. We compiled these profiles by analyzing 11 632 datasets, including the GEUVADIS and The Cancer Genome Atlas (TCGA) repositories. MINRbase offers a user-friendly interface that lets researchers issue complex queries based on one or more criteria, such as parental rRNA identity, nucleotide sequence, rRF minimum abundance and metadata keywords (e.g. tissue type, disease). A 'summary' page for each rRF provides a granular breakdown of its expression by tissue type, disease, sex, ancestry and other variables; it also allows users to create publication-ready plots at the click of a button. MINRbase has already allowed us to generate support for three novel observations: the internal spacers of 45S are prolific producers of abundant rRFs; many abundant rRFs straddle the known boundaries of rRNAs; rRF production is regimented and depends on 'personal attributes' (sex, ancestry) and 'context' (tissue type, tissue state, disease). MINRbase is available at https://cm.jefferson.edu/MINRbase/.

The subcellular distribution of miRNA isoforms, tRNA-derived fragments, and rRNA-derived fragments depends on nucleotide sequence and cell type.

BACKGROUND: MicroRNA isoforms (isomiRs), tRNA-derived fragments (tRFs), and rRNA-derived fragments (rRFs) represent most of the small non-coding RNAs (sncRNAs) found in cells. Members of these three classes modulate messenger RNA (mRNA) and protein abundance and are dysregulated in diseases. Experimental studies to date have assumed that the subcellular distribution of these molecules is well-understood, independent of cell type, and the same for all isoforms of a sncRNA. RESULTS: We tested these assumptions by investigating the subcellular distribution of isomiRs, tRFs, and rRFs in biological replicates from three cell lines from the same tissue and same-sex donors that model the same cancer subtype. In each cell line, we profiled the isomiRs, tRFs, and rRFs in the nucleus, cytoplasm, whole mitochondrion (MT), mitoplast (MP), and whole cell. Using a rigorous mathematical model we developed, we accounted for cross-fraction contamination and technical errors and adjusted the measured abundances accordingly. Analyses of the adjusted abundances show that isomiRs, tRFs, and rRFs exhibit complex patterns of subcellular distributions. These patterns depend on each sncRNA's exact sequence and the cell type. Even in the same cell line, isoforms of the same sncRNA whose sequences differ by a few nucleotides (nts) can have different subcellular distributions. CONCLUSIONS: SncRNAs with similar sequences have different subcellular distributions within and across cell lines, suggesting that each isoform could have a different function. Future computational and experimental studies of isomiRs, tRFs, and rRFs will need to distinguish among each molecule's various isoforms and account for differences in each isoform's subcellular distribution in the cell line at hand. While the findings add to a growing body of evidence that isomiRs, tRFs, rRFs, tRNAs, and rRNAs follow complex intracellular trafficking rules, further investigation is needed to exclude alternative explanations for the observed subcellular distribution of sncRNAs.

MicroRNA-139 Expression Is Dispensable for the Generation of Influenza-Specific CD8+ T Cell Responses.

MicroRNAs (miRNAs/miRs) are small, endogenous noncoding RNAs that are important post-transcriptional regulators with clear roles in the development of the immune system and immune responses. Using miRNA microarray profiling, we characterized the expression profile of naive and in vivo generated murine effector antiviral CD8+ T cells. We observed that out of 362 measurable mature miRNAs, 120 were differentially expressed by at least 2-fold in influenza-specific effector CD8+ CTLs compared with naive CD8+ T cells. One miRNA found to be highly downregulated on both strands in effector CTLs was miR-139. Because previous studies have indicated a role for miR-139-mediated regulation of CTL effector responses, we hypothesized that deletion of miR-139 would enhance antiviral CTL responses during influenza virus infection. We generated miR-139-/- mice or overexpressed miR-139 in T cells to assess the functional contribution of miR-139 expression in CD8+ T cell responses. Our study demonstrates that the development of naive T cells and generation or differentiation of effector or memory CD8+ T cell responses to influenza virus infection are not impacted by miR-139 deficiency or overexpression; yet, miR-139-/- CD8+ T cells are outcompeted by wild-type CD8+ T cells in a competition setting and demonstrate reduced responses to Listeria monocytogenes Using an in vitro model of T cell exhaustion, we confirmed that miR-139 expression similarly does not impact the development of T cell exhaustion. We conclude that despite significant downregulation of miR-139 following in vivo and in vitro activation, miR-139 expression is dispensable for influenza-specific CTL responses.

Reproducibility efforts as a teaching tool: A pilot study.

The "replication crisis" is a methodological problem in which many scientific research findings have been difficult or impossible to replicate. Because the reproducibility of empirical results is an essential aspect of the scientific method, such failures endanger the credibility of theories based on them and possibly significant portions of scientific knowledge. An instance of the replication crisis, analytic replication, pertains to reproducing published results through computational reanalysis of the authors' original data. However, direct replications are costly, time-consuming, and unrewarded in today's publishing standards. We propose that bioinformatics and computational biology students replicate recent discoveries as part of their curriculum. Considering the above, we performed a pilot study in one of the graduate-level courses we developed and taught at our University. The course is entitled Intro to R Programming and is meant for students in our Master's and PhD programs who have little to no programming skills. As the course emphasized real-world data analysis, we thought it would be an appropriate setting to carry out this study. The primary objective was to expose the students to real biological data analysis problems. These include locating and downloading the needed datasets, understanding any underlying conventions and annotations, understanding the analytical methods, and regenerating multiple graphs from their assigned article. The secondary goal was to determine whether the assigned articles contained sufficient information for a graduate-level student to replicate its figures. Overall, the students successfully reproduced 39% of the figures. The main obstacles were the need for more advanced programming skills and the incomplete documentation of the applied methods. Students were engaged, enthusiastic, and focused throughout the semester. We believe that this teaching approach will allow students to make fundamental scientific contributions under appropriate supervision. It will teach them about the scientific process, the importance of reporting standards, and the importance of openness.

IsoMiRmap: fast, deterministic and exhaustive mining of isomiRs from short RNA-seq datasets.

MOTIVATION: MicroRNA (miRNA) precursor arms give rise to multiple isoforms simultaneously called 'isomiRs.' IsomiRs from the same arm typically differ by a few nucleotides at either their 5' or 3' termini or both. In humans, the identities and abundances of isomiRs depend on a person's sex and genetic ancestry as well as on tissue type, tissue state and disease type/subtype. Moreover, nearly half of the time the most abundant isomiR differs from the miRNA sequence found in public databases. Accurate mining of isomiRs from deep sequencing data is thus important. RESULTS: We developed isoMiRmap, a fast, standalone, user-friendly mining tool that identifies and quantifies all isomiRs by directly processing short RNA-seq datasets. IsoMiRmap is a portable 'plug-and-play' tool, requires minimal setup, has modest computing and storage requirements, and can process an RNA-seq dataset with 50 million reads in just a few minutes on an average laptop. IsoMiRmap deterministically and exhaustively reports all isomiRs in a given deep sequencing dataset and quantifies them accurately (no double-counting). IsoMiRmap comprehensively reports all miRNA precursor locations from which an isomiR may be transcribed, tags as 'ambiguous' isomiRs whose sequences exist both inside and outside of the space of known miRNA sequences and reports the public identifiers of common single-nucleotide polymorphisms and documented somatic mutations that may be present in an isomiR. IsoMiRmap also identifies isomiRs with 3' non-templated post-transcriptional additions. Compared to similar tools, isoMiRmap is the fastest, reports more bona fide isomiRs, and provides the most comprehensive information related to an isomiR's transcriptional origin. AVAILABILITY AND IMPLEMENTATION: The codes for isoMiRmap are freely available at https://cm.jefferson.edu/isoMiRmap/ and https://github.com/TJU-CMC-Org/isoMiRmap/. IsomiR profiles for the datasets of the 1000 Genomes Project, spanning five population groups, and The Cancer Genome Atlas (TCGA), spanning 33 cancer studies, are also available at https://cm.jefferson.edu/isoMiRmap/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

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.

The transcriptional trajectories of pluripotency and differentiation comprise genes with antithetical architecture and repetitive-element content.

BACKGROUND: Extensive molecular differences exist between proliferative and differentiated cells. Here, we conduct a meta-analysis of publicly available transcriptomic datasets from preimplantation and differentiation stages examining the architectural properties and content of genes whose abundance changes significantly across developmental time points. RESULTS: Analysis of preimplantation embryos from human and mouse showed that short genes whose introns are enriched in Alu (human) and B (mouse) elements, respectively, have higher abundance in the blastocyst compared to the zygote. These highly expressed genes encode ribosomal proteins or metabolic enzymes. On the other hand, long genes whose introns are depleted in repetitive elements have lower abundance in the blastocyst and include genes from signaling pathways. Additionally, the sequences of the genes that are differentially expressed between the blastocyst and the zygote contain distinct collections of pyknon motifs that differ between up- and down-regulated genes. Further examination of the genes that participate in the stem cell-specific protein interaction network shows that their introns are short and enriched in Alu (human) and B (mouse) elements. As organogenesis progresses, in both human and mouse, we find that the primarily short and repeat-rich expressed genes make way for primarily longer, repeat-poor genes. With that in mind, we used a machine learning-based approach to identify gene signatures able to classify human adult tissues: we find that the most discriminatory genes comprising these signatures have long introns that are repeat-poor and include transcription factors and signaling-cascade genes. The introns of widely expressed genes across human tissues, on the other hand, are short and repeat-rich, and coincide with those with the highest expression at the blastocyst stage. CONCLUSIONS: Protein-coding genes that are characteristic of each trajectory, i.e., proliferation/pluripotency or differentiation, exhibit antithetical biases in their intronic and exonic lengths and in their repetitive-element content. While the respective human and mouse gene signatures are functionally and evolutionarily conserved, their introns and exons are enriched or depleted in organism-specific repetitive elements. We posit that these organism-specific repetitive sequences found in exons and introns are used to effect the corresponding genes' regulation.

Megakaryocyte-specific knockout of the Mir-99b/let7e/125a cluster lowers platelet count without altering platelet function.

The purpose of this research was to assess the effects of a microRNA (miRNA) cluster on platelet production. Human chromosome 19q13.41 harbors an evolutionarily conserved cluster of three miRNA genes (MIR99B, MIRLET7E, MIR125A) within 727 base-pairs. We now report that levels of miR-99b-5p, miR-let7e-5p and miR-125a-5p are strongly correlated in human platelets, and all are positively associated with platelet count, but not white blood count or hemoglobin level. Although the cluster regulates hematopoietic stem cell proliferation, the function of this genomic locus in megakaryocyte (MK) differentiation and platelet production is unknown. Furthermore, studies of individual miRNAs do not represent broader effects in the context of a cluster. To address this possibility, MK/platelet lineage-specific Mir-99b/let7e/125a knockout mice were generated. Compared to wild type littermates, cluster knockout mice had significantly lower platelet counts and reduced MK proplatelet formation, but no differences in MK numbers, ploidy, maturation or ultra-structural morphology, and no differences in platelet function. Compared to wild type littermates, knockout mice showed similar survival after pulmonary embolism. The major conclusions are that the effect of the Mir-99b/let7e/125a cluster is confined to a late stage of thrombopoiesis, and this effect on platelet number is uncoupled from platelet function.

Unification of miRNA and isomiR research: the mirGFF3 format and the mirtop API.

MOTIVATION: MicroRNAs (miRNAs) are small RNA molecules (∼22 nucleotide long) involved in post-transcriptional gene regulation. Advances in high-throughput sequencing technologies led to the discovery of isomiRs, which are miRNA sequence variants. While many miRNA-seq analysis tools exist, the diversity of output formats hinders accurate comparisons between tools and precludes data sharing and the development of common downstream analysis methods. RESULTS: To overcome this situation, we present here a community-based project, miRNA Transcriptomic Open Project (miRTOP) working towards the optimization of miRNA analyses. The aim of miRTOP is to promote the development of downstream isomiR analysis tools that are compatible with existing detection and quantification tools. Based on the existing GFF3 format, we first created a new standard format, mirGFF3, for the output of miRNA/isomiR detection and quantification results from small RNA-seq data. Additionally, we developed a command line Python tool, mirtop, to create and manage the mirGFF3 format. Currently, mirtop can convert into mirGFF3 the outputs of commonly used pipelines, such as seqbuster, isomiR-SEA, sRNAbench, Prost! as well as BAM files. Some tools have also incorporated the mirGFF3 format directly into their code, such as, miRge2.0, IsoMIRmap and OptimiR. Its open architecture enables any tool or pipeline to output or convert results into mirGFF3. Collectively, this isomiR categorization system, along with the accompanying mirGFF3 and mirtop API, provide a comprehensive solution for the standardization of miRNA and isomiR annotation, enabling data sharing, reporting, comparative analyses and benchmarking, while promoting the development of common miRNA methods focusing on downstream steps of miRNA detection, annotation and quantification. AVAILABILITY AND IMPLEMENTATION: https://github.com/miRTop/mirGFF3/ and https://github.com/miRTop/mirtop. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Ribosomal RNA fragmentation into short RNAs (rRFs) is modulated in a sex- and population of origin-specific manner.

BACKGROUND: The advent of next generation sequencing (NGS) has allowed the discovery of short and long non-coding RNAs (ncRNAs) in an unbiased manner using reverse genetics approaches, enabling the discovery of multiple categories of ncRNAs and characterization of the way their expression is regulated. We previously showed that the identities and abundances of microRNA isoforms (isomiRs) and transfer RNA-derived fragments (tRFs) are tightly regulated, and that they depend on a person's sex and population origin, as well as on tissue type, tissue state, and disease type. Here, we characterize the regulation and distribution of fragments derived from ribosomal RNAs (rRNAs). rRNAs form a group that includes four (5S, 5.8S, 18S, 28S) rRNAs encoded by the human nuclear genome and two (12S, 16S) by the mitochondrial genome. rRNAs constitute the most abundant RNA type in eukaryotic cells. RESULTS: We analyzed rRNA-derived fragments (rRFs) across 434 transcriptomic datasets obtained from lymphoblastoid cell lines (LCLs) derived from healthy participants of the 1000 Genomes Project. The 434 datasets represent five human populations and both sexes. We examined each of the six rRNAs and their respective rRFs, and did so separately for each population and sex. Our analysis shows that all six rRNAs produce rRFs with unique identities, normalized abundances, and lengths. The rRFs arise from the 5'-end (5'-rRFs), the interior (i-rRFs), and the 3'-end (3'-rRFs) or straddle the 5' or 3' terminus of the parental rRNA (x-rRFs). Notably, a large number of rRFs are produced in a population-specific or sex-specific manner. Preliminary evidence suggests that rRF production is also tissue-dependent. Of note, we find that rRF production is not affected by the identity of the processing laboratory or the library preparation kit. CONCLUSIONS: Our findings suggest that rRFs are produced in a regimented manner by currently unknown processes that are influenced by both ubiquitous as well as population-specific and sex-specific factors. The properties of rRFs mirror the previously reported properties of isomiRs and tRFs and have implications for the study of homeostasis and disease.

Therapeutic potential of FLANC, a novel primate-specific long non-coding RNA in colorectal cancer.

OBJECTIVE: To investigate the function of a novel primate-specific long non-coding RNA (lncRNA), named FLANC, based on its genomic location (co-localised with a pyknon motif), and to characterise its potential as a biomarker and therapeutic target. DESIGN: FLANC expression was analysed in 349 tumours from four cohorts and correlated to clinical data. In a series of multiple in vitro and in vivo models and molecular analyses, we characterised the fundamental biological roles of this lncRNA. We further explored the therapeutic potential of targeting FLANC in a mouse model of colorectal cancer (CRC) metastases. RESULTS: FLANC, a primate-specific lncRNA feebly expressed in normal colon cells, was significantly upregulated in cancer cells compared with normal colon samples in two independent cohorts. High levels of FLANC were associated with poor survival in two additional independent CRC patient cohorts. Both in vitro and in vivo experiments demonstrated that the modulation of FLANC expression influenced cellular growth, apoptosis, migration, angiogenesis and metastases formation ability of CRC cells. In vivo pharmacological targeting of FLANC by administration of 1,2-dioleoyl-sn-glycero-3-phosphatidylcholine nanoparticles loaded with a specific small interfering RNA, induced significant decrease in metastases, without evident tissue toxicity or pro-inflammatory effects. Mechanistically, FLANC upregulated and prolonged the half-life of phosphorylated STAT3, inducing the overexpression of VEGFA, a key regulator of angiogenesis. CONCLUSIONS: Based on our findings, we discovered, FLANC as a novel primate-specific lncRNA that is highly upregulated in CRC cells and regulates metastases formation. Targeting primate-specific transcripts such as FLANC may represent a novel and low toxic therapeutic strategy for the treatment of patients.

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/.

Integrative Multi-omic Analysis of Human Platelet eQTLs Reveals Alternative Start Site in Mitofusin 2.

Platelets play a central role in ischemic cardiovascular events. Cardiovascular disease (CVD) is a major cause of death worldwide. Numerous genome-wide association studies (GWASs) have identified loci associated with CVD risk. However, our understanding of how these variants contribute to disease is limited. Using data from the platelet RNA and expression 1 (PRAX1) study, we analyzed cis expression quantitative trait loci (eQTLs) in platelets from 154 normal human subjects. We confirmed these results in silico by performing allele-specific expression (ASE) analysis, which demonstrated that the allelic directionality of eQTLs and ASE patterns correlate significantly. Comparison of platelet eQTLs with data from the Genotype-Tissue Expression (GTEx) project revealed that a number of platelet eQTLs are platelet specific and that platelet eQTL peaks localize to the gene body at a higher rate than eQTLs from other tissues. Upon integration with data from previously published GWASs, we found that the trait-associated variant rs1474868 coincides with the eQTL peak for mitofusin 2 (MFN2). Additional experimental and computational analyses revealed that this eQTL is linked to an unannotated alternate MFN2 start site preferentially expressed in platelets. Integration of phenotype data from the PRAX1 study showed that MFN2 expression levels were significantly associated with platelet count. This study links the variant rs1474868 to a platelet-specific regulatory role for MFN2 and demonstrates the utility of integrating multi-omic data with eQTL analysis in disease-relevant tissues for interpreting GWAS results.

Exploration of CCA-added RNAs revealed the expression of mitochondrial non-coding RNAs regulated by CCA-adding enzyme.

Post-transcriptional non-template additions of nucleotides to 3'-ends of RNAs play important roles in the stability and function of RNA molecules. Although tRNA nucleotidyltransferase (CCA-adding enzyme) is known to add CCA trinucleotides to 3'-ends of tRNAs, whether other RNA species can be endogenous substrates of CCA-adding enzyme has not been widely explored yet. Herein, we used YAMAT-seq to identify non-tRNA substrates of CCA-adding enzyme. YAMAT-seq captures RNA species that form secondary structures with 4-nt protruding 3'-ends of the sequence 5'-NCCA-3', which is the hallmark structure of RNAs that are generated by CCA-adding enzyme. By executing YAMAT-seq for human breast cancer cells and mining the sequence data, we identified novel candidate substrates of CCA-adding enzyme. These included fourteen 'CCA-RNAs' that only contain CCA as non-genomic sequences, and eleven 'NCCA-RNAs' that contain CCA and other nucleotides as non-genomic sequences. All newly-identified (N)CCA-RNAs were derived from the mitochondrial genome and were localized in mitochondria. Knockdown of CCA-adding enzyme severely reduced the expression levels of (N)CCA-RNAs, suggesting that the CCA-adding enzyme-catalyzed CCA additions stabilize the expression of (N)CCA-RNAs. Furthermore, expression levels of (N)CCA-RNAs were severely reduced by various cellular treatments, including UV irradiation, amino acid starvation, inhibition of mitochondrial respiratory complexes, and inhibition of the cell cycle. These results revealed a novel CCA-mediated regulatory pathway for the expression of mitochondrial non-coding RNAs.

The biogenesis pathway of tRNA-derived piRNAs in Bombyx germ cells.

Transfer RNAs (tRNAs) function in translational machinery and further serves as a source of short non-coding RNAs (ncRNAs). tRNA-derived ncRNAs show differential expression profiles and play roles in many biological processes beyond translation. Molecular mechanisms that shape and regulate their expression profiles are largely unknown. Here, we report the mechanism of biogenesis for tRNA-derived Piwi-interacting RNAs (td-piRNAs) expressed in Bombyx BmN4 cells. In the cells, two cytoplasmic tRNA species, tRNAAspGUC and tRNAHisGUG, served as major sources for td-piRNAs, which were derived from the 5'-part of the respective tRNAs. cP-RNA-seq identified the two tRNAs as major substrates for the 5'-tRNA halves as well, suggesting a previously uncharacterized link between 5'-tRNA halves and td-piRNAs. An increase in levels of the 5'-tRNA halves, induced by BmNSun2 knockdown, enhanced the td-piRNA expression levels without quantitative change in mature tRNAs, indicating that 5'-tRNA halves, not mature tRNAs, are the direct precursors for td-piRNAs. For the generation of tRNAHisGUG-derived piRNAs, BmThg1l-mediated nucleotide addition to -1 position of tRNAHisGUG was required, revealing an important function of BmThg1l in piRNA biogenesis. Our study advances the understanding of biogenesis mechanisms and the genesis of specific expression profiles for tRNA-derived ncRNAs.

YAMAT-seq: an efficient method for high-throughput sequencing of mature transfer RNAs.

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.

Knowledge about the presence or absence of miRNA isoforms (isomiRs) can successfully discriminate amongst 32 TCGA cancer types.

Isoforms of human miRNAs (isomiRs) are constitutively expressed with tissue- and disease-subtype-dependencies. We studied 10 271 tumor datasets from The Cancer Genome Atlas (TCGA) to evaluate whether isomiRs can distinguish amongst 32 TCGA cancers. Unlike previous approaches, we built a classifier that relied solely on 'binarized' isomiR profiles: each isomiR is simply labeled as 'present' or 'absent'. The resulting classifier successfully labeled tumor datasets with an average sensitivity of 90% and a false discovery rate (FDR) of 3%, surpassing the performance of expression-based classification. The classifier maintained its power even after a 15× reduction in the number of isomiRs that were used for training. Notably, the classifier could correctly predict the cancer type in non-TCGA datasets from diverse platforms. Our analysis revealed that the most discriminatory isomiRs happen to also be differentially expressed between normal tissue and cancer. Even so, we find that these highly discriminating isomiRs have not been attracting the most research attention in the literature. Given their ability to successfully classify datasets from 32 cancers, isomiRs and our resulting 'Pan-cancer Atlas' of isomiR expression could serve as a suitable framework to explore novel cancer biomarkers.

Threshold-seq: a tool for determining the threshold in short RNA-seq datasets.

SUMMARY: We present 'Threshold-seq,' a new approach for determining thresholds in deep-sequencing datasets of short RNA transcripts. Threshold-seq addresses the critical question of how many reads need to support a short RNA molecule in a given dataset before it can be considered different from 'background.' The proposed scheme is easy to implement and incorporate into existing pipelines. AVAILABILITY AND IMPLEMENTATION: Source code of Threshold-seq is freely available as an R package at: http://cm.jefferson.edu/threshold-seq/. CONTACT: isidore.rigoutsos@jefferson.edu. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.