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/.

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.

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.

The Short and the Long of it: Timing of Mortality for Older Adults in a State Trauma System.

BACKGROUND: The impact of injury extends beyond the hospital stay, but trauma center performance metrics typically focus on in-hospital mortality. We compared risk adjusted rates of in-hospital and long-term mortality among Pennsylvania trauma centers. We hypothesized that centers with low rates of in-hospital mortality would also have low rates of long-term mortality. METHODS: We identified injured patients (age ≥ 65) admitted to Pennsylvania trauma centers in 2013 and 2014 using the Pennsylvania Trauma Outcomes Study, a robust, state-wide trauma registry. We matched trauma registry records to Medicare claims from the y 2013 to 2015. Matching variables included admission date and patient demographics including date of birth, zip, sex, and race and/or ethnicity. Outcomes examined were inpatient, 30-day, and 1-y mortality. Multivariable logistic regression models including presenting physiology, comorbidities, injury characteristics, and demographics were developed to calculate expected mortality rates for each trauma center at each time point. Trauma center performance was assessed using observed-to-expected ratios and ranking for in-hospital, 30-day, and 1-y mortality. RESULTS: Of the 15,451 patients treated at 28 centers, 8.1% died before discharge or were discharged to hospice. Another 3.4% died within 30 d, and another 14.7% died within 1 y of injury. Of patients who survived hospitalization but died within 30 d, 92.5% were injured due to fall, and 75.0% sustained head injuries. Survival at 1 y was higher in patients discharged home (88.4%), compared to those discharged to a skilled nursing facility or long-term acute care hospital (72.7% and 52.6%, respectively). Three centers were identified as outliers (two low and one high) for in-hospital mortality, none of which were outliers when the horizon was stretched to 30 d from injury. At 30 d, two different low and two different high outliers were found. CONCLUSION: Nearly one-in-three injured older adults who die within 30 d of injury dies after hospital discharge. Hospital rankings for in-hospital mortality correlate poorly with long-term outcomes. These findings underscore the importance of looking beyond survival to discharge for quality improvement and benchmarking.

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.

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/.

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.

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.

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.

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.

Sex hormone-dependent tRNA halves enhance cell proliferation in breast and prostate cancers.

Sex hormones and their receptors play critical roles in the development and progression of the breast and prostate cancers. Here we report that a novel type of transfer RNA (tRNA)-derived small RNA, termed Sex HOrmone-dependent TRNA-derived RNAs (SHOT-RNAs), are specifically and abundantly expressed in estrogen receptor (ER)-positive breast cancer and androgen receptor (AR)-positive prostate cancer cell lines. SHOT-RNAs are not abundantly present in ER(-) breast cancer, AR(-) prostate cancer, or other examined cancer cell lines from other tissues. ER-dependent accumulation of SHOT-RNAs is not limited to a cell culture system, but it also occurs in luminal-type breast cancer patient tissues. SHOT-RNAs are produced from aminoacylated mature tRNAs by angiogenin-mediated anticodon cleavage, which is promoted by sex hormones and their receptors. Resultant 5'- and 3'-SHOT-RNAs, corresponding to 5'- and 3'-tRNA halves, bear a cyclic phosphate (cP) and an amino acid at the 3'-end, respectively. By devising a "cP-RNA-seq" method that is able to exclusively amplify and sequence cP-containing RNAs, we identified the complete repertoire of 5'-SHOT-RNAs. Furthermore, 5'-SHOT-RNA, but not 3'-SHOT-RNA, has significant functional involvement in cell proliferation. These results have unveiled a novel tRNA-engaged pathway in tumorigenesis of hormone-dependent cancers and implicate SHOT-RNAs as potential candidates for biomarkers and therapeutic targets.

Analysis of 13 cell types reveals evidence for the expression of numerous novel primate- and tissue-specific microRNAs.

Two decades after the discovery of the first animal microRNA (miRNA), the number of miRNAs in animal genomes remains a vexing question. Here, we report findings from analyzing 1,323 short RNA sequencing samples (RNA-seq) from 13 different human tissue types. Using stringent thresholding criteria, we identified 3,707 statistically significant novel mature miRNAs at a false discovery rate of ≤ 0.05 arising from 3,494 novel precursors; 91.5% of these novel miRNAs were identified independently in 10 or more of the processed samples. Analysis of these novel miRNAs revealed tissue-specific dependencies and a commensurate low Jaccard similarity index in intertissue comparisons. Of these novel miRNAs, 1,657 (45%) were identified in 43 datasets that were generated by cross-linking followed by Argonaute immunoprecipitation and sequencing (Ago CLIP-seq) and represented 3 of the 13 tissues, indicating that these miRNAs are active in the RNA interference pathway. Moreover, experimental investigation through stem-loop PCR of a random collection of newly discovered miRNAs in 12 cell lines representing 5 tissues confirmed their presence and tissue dependence. Among the newly identified miRNAs are many novel miRNA clusters, new members of known miRNA clusters, previously unreported products from uncharacterized arms of miRNA precursors, and previously unrecognized paralogues of functionally important miRNA families (e.g., miR-15/107). Examination of the sequence conservation across vertebrate and invertebrate organisms showed 56.7% of the newly discovered miRNAs to be human-specific whereas the majority (94.4%) are primate lineage-specific. Our findings suggest that the repertoire of human miRNAs is far more extensive than currently represented by public repositories and that there is a significant number of lineage- and/or tissue-specific miRNAs that are uncharacterized.

MINTbase: a framework for the interactive exploration of mitochondrial and nuclear tRNA fragments.

MOTIVATION: It 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. RESULTS: We 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 IMPLEMENTATION: MINTbase is freely accessible at http://cm.jefferson.edu/MINTbase/. Dataset submissions to MINTbase can be initiated at http://cm.jefferson.edu/MINTsubmit/ CONTACT: isidore.rigoutsos@jefferson.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Beyond the one-locus-one-miRNA paradigm: microRNA isoforms enable deeper insights into breast cancer heterogeneity.

Here we describe our study of miRNA isoforms (isomiRs) in breast cancer (BRCA) and normal breast data sets from the Cancer Genome Atlas (TCGA) repository. We report that the full isomiR profiles, from both known and novel human-specific miRNA loci, are particularly rich in information and can distinguish tumor from normal tissue much better than the archetype miRNAs. IsomiR expression is also dependent on the patient's race, exemplified by miR-183-5p, several isomiRs of which are upregulated in triple negative BRCA in white but not black women. Additionally, we find that an isomiR's 5' endpoint and length, but not the genomic origin, are key determinants of the regulation of its expression. Overexpression of distinct miR-183-5p isomiRs in MDA-MB-231 cells followed by microarray analysis revealed that each isomiR has a distinct impact on the cellular transcriptome. Parallel integrative analysis of mRNA expression from BRCA data sets of the TCGA repository demonstrated that isomiRs can distinguish between the luminal A and luminal B subtypes and explain in more depth the molecular differences between them than the archetype molecules. In conclusion, our findings provide evidence that post-transcriptional studies of BRCA will benefit from transcending the one-locus-one-miRNA paradigm and taking into account all isoforms from each miRNA locus as well as the patient's race.

Consequential considerations when mapping tRNA fragments.

We examine several of the choices that went into the design of tDRmapper, a recently reported tool for identifying transfer RNA (tRNA) fragments in deep sequencing data, evaluate them in the context of currently available knowledge, and discuss their potential impact on the output that the tool generates.

The microRNAs within the DLK1-DIO3 genomic region: involvement in disease pathogenesis.

The mammalian genome is transcribed in a developmentally regulated manner, generating RNA strands ranging from long to short non-coding RNA (ncRNAs). NcRNAs generated by intergenic sequences and protein-coding loci, represent up to 98 % of the human transcriptome. Non-coding transcripts comprise short ncRNAs such as microRNAs, piwi-interacting RNAs, small nucleolar RNAs and long intergenic RNAs, most of which exercise a strictly controlled negative regulation of expression of protein-coding genes. In humans, the DLK1-DIO3 genomic region, located on human chromosome 14 (14q32) contains the paternally expressed imprinted genes DLK1, RTL1, and DIO3 and the maternally expressed imprinted genes MEG3 (Gtl2), MEG8 (RIAN), and antisense RTL1 (asRTL1). This region hosts, in addition to two long intergenic RNAs, the MEG3 and MEG8, one of the largest microRNA clusters in the genome, with 53 miRNAs in the forward strand and one (mir-1247) in the reverse strand. Many of these miRNAs are differentially expressed in several pathologic processes and various cancers. A better understanding of the pathophysiologic importance of the DLK1-DIO3 domain-containing microRNA cluster may contribute to innovative therapeutic strategies in a range of diseases. Here we present an in-depth review of this vital genomic region, and examine the role the microRNAs of this region may play in controlling tissue homeostasis and in the pathogenesis of some human diseases, mostly cancer, when aberrantly expressed. The potential clinical implications of this data are also discussed.

The complex transcriptional landscape of the anucleate human platelet.

BACKGROUND: Human blood platelets are essential to maintaining normal hemostasis, and platelet dysfunction often causes bleeding or thrombosis. Estimates of genome-wide platelet RNA expression using microarrays have provided insights to the platelet transcriptome but were limited by the number of known transcripts. The goal of this effort was to deep-sequence RNA from leukocyte-depleted platelets to capture the complex profile of all expressed transcripts. RESULTS: From each of four healthy individuals we generated long RNA (≥40 nucleotides) profiles from total and ribosomal-RNA depleted RNA preparations, as well as short RNA (<40 nucleotides) profiles. Analysis of ~1 billion reads revealed that coding and non-coding platelet transcripts span a very wide dynamic range (≥16 PCR cycles beyond ß-actin), a result we validated through qRT-PCR on many dozens of platelet messenger RNAs. Surprisingly, ribosomal-RNA depletion significantly and adversely affected estimates of the relative abundance of transcripts. Of the known protein-coding loci, ~9,500 are present in human platelets. We observed a strong correlation between mRNAs identified by RNA-seq and microarray for well-expressed mRNAs, but RNASeq identified many more transcripts of lower abundance and permitted discovery of novel transcripts. CONCLUSIONS: Our analyses revealed diverse classes of non-coding RNAs, including: pervasive antisense transcripts to protein-coding loci; numerous, previously unreported and abundant microRNAs; retrotransposons; and thousands of novel un-annotated long and short intronic transcripts, an intriguing finding considering the anucleate nature of platelets. The data are available through a local mirror of the UCSC genome browser and can be accessed at: http://cm.jefferson.edu/platelets_2012/.

Interactive exploration of RNA22 microRNA target predictions.

MicroRNA (miRNA) target prediction is an important problem. Given an miRNA sequence the task is to determine the identity of the messenger RNAs targeted by it, the locations within them where the interactions happen and the specifics of the formed heteroduplexes. Here, we describe a web-based application, RNA22-GUI, which we have designed and implemented for the interactive exploration and in-context visualization of predictions by RNA22, one of the popular miRNA target prediction algorithms. Central to our design has been the requirement to provide informative and comprehensive visualization that is integrated with interactive search capabilities and permits one to selectively isolate and focus on relevant information that is distilled on-the-fly from a large repository of pre-compiled predictions. RNA22-GUI is currently available for Homo sapiens, Mus musculus, Drosophila melanogaster and Caenorhabditis elegans.