MINTmap: fast and exhaustive profiling of nuclear and mitochondrial tRNA fragments from short RNA-seq data.
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ABSTRACT:
SUBMITTER: Loher P
PROVIDER: S-EPMC5318995 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:MotivationMicroRNA (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.ResultsWe 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 implementationThe 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 informationSupplementary data are available at Bioinformatics online.
| S-EPMC8317110 | biostudies-literature
Project description:MotivationIt has been known that mature transfer RNAs (tRNAs) that are encoded in the nuclear genome give rise to short molecules, collectively known as tRNA fragments or tRFs. Recently, we reported that, in healthy individuals and in patients, tRFs are constitutive, arise from mitochondrial as well as from nuclear tRNAs, and have composition and abundances that depend on a person's sex, population origin and race as well as on tissue, disease and disease subtype. Our findings as well as similar work by other groups highlight the importance of tRFs and presage an increase in the community's interest in elucidating the roles of tRFs in health and disease.ResultsWe created MINTbase, a web-based framework that serves the dual-purpose of being a content repository for tRFs and a tool for the interactive exploration of these newly discovered molecules. A key feature of MINTbase is that it deterministically and exhaustively enumerates all possible genomic locations where a sequence fragment can be found and indicates which fragments are exclusive to tRNA space, and thus can be considered as tRFs: this is a very important consideration given that the genomes of higher organisms are riddled with partial tRNA sequences and with tRNA-lookalikes whose aberrant transcripts can be mistaken for tRFs. MINTbase is extremely flexible and integrates and presents tRF information from multiple yet interconnected vantage points ('vistas'). Vistas permit the user to interactively personalize the information that is returned and the manner in which it is displayed. MINTbase can report comparative information on how a tRF is distributed across all anticodon/amino acid combinations, provides alignments between a tRNA and multiple tRFs with which the user can interact, provides details on published studies that reported a tRF as expressed, etc. Importantly, we designed MINTbase to contain all possible tRFs that could ever be produced by mature tRNAs: this allows us to report on their genomic distributions, anticodon/amino acid properties, alignments, etc. while giving users the ability to at-will investigate candidate tRF molecules before embarking on focused experimental explorations. Lastly, we also introduce a new labeling scheme that is tRF-sequence-based and allows users to associate a tRF with a universally unique label ('tRF-license plate') that is independent of a genome assembly and does not require any brokering mechanism.Availability and implementationMINTbase is freely accessible at http://cm.jefferson.edu/MINTbase/. Dataset submissions to MINTbase can be initiated at http://cm.jefferson.edu/MINTsubmit/Contactisidore.rigoutsos@jefferson.eduSupplementary informationSupplementary data are available at Bioinformatics online.
| S-EPMC4978933 | biostudies-literature
Project description:High-throughput RNA sequencing has accelerated discovery of the complex regulatory roles of small RNAs, but RNAs containing modified nucleosides may escape detection when those modifications interfere with reverse transcription during RNA-seq library preparation. Here we describe AlkB-facilitated RNA methylation sequencing (ARM-seq), which uses pretreatment with Escherichia coli AlkB to demethylate N(1)-methyladenosine (m(1)A), N(3)-methylcytidine (m(3)C) and N(1)-methylguanosine (m(1)G), all commonly found in tRNAs. Comparative methylation analysis using ARM-seq provides the first detailed, transcriptome-scale map of these modifications and reveals an abundance of previously undetected, methylated small RNAs derived from tRNAs. ARM-seq demonstrates that tRNA fragments accurately recapitulate the m(1)A modification state for well-characterized yeast tRNAs and generates new predictions for a large number of human tRNAs, including tRNA precursors and mitochondrial tRNAs. Thus, ARM-seq provides broad utility for identifying previously overlooked methyl-modified RNAs, can efficiently monitor methylation state and may reveal new roles for tRNA fragments as biomarkers or signaling molecules.
| S-EPMC4553111 | biostudies-literature
Project description: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/.
| S-EPMC10767805 | biostudies-literature
Project description:Profiling T cell receptor (TCR) repertoire via short read transcriptome sequencing (RNA-Seq) has a unique advantage of probing simultaneously TCRs and the genome-wide RNA expression of other genes. However, compared to targeted amplicon approaches, the shorter read length is more prone to mapping error. In addition, only a small percentage of the genome-wide reads may cover the TCR loci and thus the repertoire could be significantly under-sampled. Although this approach has been applied in a few studies, the utility of transcriptome sequencing in probing TCR repertoires has not been evaluated extensively. Here we present a systematic assessment of RNA-Seq in TCR profiling. We evaluate the power of both Fluidigm C1 full-length single cell RNA-Seq and bulk RNA-Seq in characterizing the repertoires of different diversities under either naïve conditions or after immunogenic challenges. Standard read length and sequencing coverage were employed so that the evaluation was conducted in accord with the current RNA-Seq practices. Despite high sequencing depth in bulk RNA-Seq, we encountered difficulty quantifying TCRs with low transcript abundance (<1%). Nevertheless, top enriched TCRs with an abundance of 1-3% or higher can be faithfully detected and quantified. When top TCR sequences are of interest and transcriptome sequencing is available, it is worthwhile to conduct a TCR profiling using the RNA-Seq data.
| S-EPMC6237323 | biostudies-literature
Project description:Mutations in mitochondrial (mt) genes coding for mt-tRNAs are responsible for a range of syndromes, for which no effective treatment is available. We recently showed that the carboxy-terminal domain (Cterm) of human mt-leucyl tRNA synthetase rescues the pathologic phenotype associated either with the m.3243A>G mutation in mt-tRNA(Leu(UUR)) or with mutations in the mt-tRNA(Ile), both of which are aminoacylated by Class I mt-aminoacyl-tRNA synthetases (mt-aaRSs). Here we show, by using the human transmitochondrial cybrid model, that the Cterm is also able to improve the phenotype caused by the m.8344A>G mutation in mt-tRNA(Lys), aminoacylated by a Class II aaRS. Importantly, we demonstrate that the same rescuing ability is retained by two Cterm-derived short peptides, ?30_31 and ?32_33, which are effective towards both the m.8344A>G and the m.3243A>G mutations. Furthermore, we provide in vitro evidence that these peptides bind with high affinity wild-type and mutant human mt-tRNA(Leu(UUR)) and mt-tRNA(Lys), and stabilize mutant mt-tRNA(Leu(UUR)). In conclusion, we demonstrate that small Cterm-derived peptides can be effective tools to rescue cellular defects caused by mutations in a wide range of mt-tRNAs.
| S-EPMC4754043 | biostudies-literature
Project description:Background: Cell free DNA (cfDNA) in plasma has received increasing attention and has been studied in a broad range of clinical conditions implicating inflammation, cancer, and aging. However, few studies have focused on mitochondrial DNA (mtDNA) in the cell free form. This study characterized the size distribution and sequence characteristics of plasma cell free mtDNA (cf mtDNA) in humans.Methods and Results: We optimized DNA isolation and next-generation sequencing library preparation protocols to better retain short DNA fragments from plasma, and applied these optimized methods to plasma samples from patients with sepsis. After massive parallel sequencing, we verified that our methods can retain substantially shorter DNA fragments than the standard isolation method, resulting in an average of 11.5 fold increase in short DNA fragments yield (DNA < 100bp). We report that cf mtDNA in plasma is highly enriched in short-size cfDNA (30 ~ 60 bp), which is much shorter than the value previously reported (~140 bp). Motivated by this unique size distribution, we size-selected short cfDNA fragments from the sequencing library, which further increased the mtDNA recovery rate by an average of 10.4 fold. Using this approach we detected mixtures of different mtDNA sequences, termed heteroplasmy, in plasma from 3 patients. In one patient who previously received bone marrow transplantation, different minor allele frequencies were observed between plasma and white blood cells (WBC) at heteroplasmic mtDNA sites, consistent with mixed-tissue origin for plasma DNA.Conclusion: mtDNA in plasma exists as very short fragments that exhibit mtDNA heteroplasmy distribution differences from that found in a single organ/tissue. This study is the first report of genome wide identification of mtDNA heteroplasmy in human plasma. Our optimized method can be used to investigate the potential utility of cf mtDNA fragments and heteroplasmy as biomarkers in various diseases.
2016-05-07 | GSE81178 | GEO
Project description:Cell free DNA (cfDNA) has received increasing attention and has been studied in a broad range of clinical conditions. However, few studies have focused on mitochondrial DNA (mtDNA) in the cell free form. We optimized DNA isolation and sequencing library preparation protocols to better retain short DNA fragments from plasma, and applied these optimized methods to plasma samples from patients with sepsis. Our methods can retain substantially shorter DNA, resulting in an average of 11.5 fold increase in short DNA fragments yield (DNA <100bp). We report that cf-mtDNA in plasma is highly enriched in short-size cfDNA (30~60 bp). Motivated by this unique size distribution, we size-selected short cfDNA, which further increased the mtDNA recovery rate by an average of 10.4 fold. We then detected mtDNA heteroplasmy in plasma from 3 patients. In one patient who previously received bone marrow transplantation, different minor allele frequencies were observed between plasma and leukocytes at heteroplasmic sites, consistent with mixed-tissue origin for cfDNA. For the other two patients, the heteroplasmy pattern is also different between plasma and leukocyte. Our study shed new lights into the architecture of the cfDNA, and mtDNA heteroplasmy identified in plasma provides new potential for biomarker discovery.
| S-EPMC5095883 | biostudies-literature
Project description:We are interested in identifying and characterizing loci of the human genome that harbor sequences resembling known mitochondrial and nuclear tRNAs. To this end, we used the known nuclear and mitochondrial tRNA genes (the "tRNA-Reference" set) to search for "tRNA-lookalikes" and found many such loci at different levels of sequence conservation. We find that the large majority of these tRNA-lookalikes resemble mitochondrial tRNAs and exhibit a skewed over-representation in favor of some mitochondrial anticodons. Our analysis shows that the tRNA-lookalikes have infiltrated specific chromosomes and are preferentially located in close proximity to known nuclear tRNAs (z-score ≤ -2.54, P-value ≤ 0.00394). Examination of the transcriptional potential of these tRNA-lookalike loci using public transcript annotations revealed that more than 20% of the lookalikes are transcribed as part of either known protein-coding pre-mRNAs, known lncRNAs, or known non-protein-coding RNAs, while public RNA-seq data perfectly agreed with the endpoints of tRNA-lookalikes. Interestingly, we found that tRNA-lookalikes are significantly depleted in known genetic variations associated with human health and disease whereas the known tRNAs are enriched in such variations. Lastly, a manual comparative analysis of the cloverleaf structure of several of the transcribed tRNA-lookalikes revealed no disruptive mutations suggesting the possibility that these loci give rise to functioning tRNA molecules.
| S-EPMC4189335 | biostudies-literature
Project description:We introduce a k-mer-based computational protocol, DE-kupl, for capturing local RNA variation in a set of RNA-seq libraries, independently of a reference genome or transcriptome. DE-kupl extracts all k-mers with differential abundance directly from the raw data files. This enables the retrieval of virtually all variation present in an RNA-seq data set. This variation is subsequently assigned to biological events or entities such as differential long non-coding RNAs, splice and polyadenylation variants, introns, repeats, editing or mutation events, and exogenous RNA. Applying DE-kupl to human RNA-seq data sets identified multiple types of novel events, reproducibly across independent RNA-seq experiments.
| S-EPMC5747171 | biostudies-literature