DASHR: database of small human noncoding RNAs

tRFUniverse: A comprehensive resource for the interactive analyses of tRNA-derived ncRNAs in human cancer

tRNA-derived ncRNAs are a heterogeneous class of non-coding RNAs recently proposed to be active regulators of gene expression and be involved in many diseases, including cancer. Consequently, several online resources on tRNA-derived ncRNAs have been released. Although interesting, such resources present only basic features and do not adequately exploit the wealth of knowledge available about tRNA-derived ncRNAs. Therefore, we introduce tRFUniverse, a novel online resource for the analysis of tRNA-derived ncRNAs in human cancer. tRFUniverse presents an extensive collection of classes of tRNA-derived ncRNAs analyzed across all the TCGA and TARGET tumor cohorts, NCI-60 cell lines, and biological fluids. Moreover, public AGO CLASH/CLIP-Seq data were analyzed to identify the molecular interactions between tRNA-derived ncRNAs and other transcripts. Importantly, tRFUniverse combines in a single resource a comprehensive set of features that we believe may be helpful to investigate the involvement of tRNA-derived ncRNAs in cancer biology.

The urinary RNA atlas of patients with chronic kidney disease

Chronic kidney disease (CKD) represents a significant global health burden. Currently employed CKD biomarkers are influenced by various factors and lack accuracy in reflecting early-stage renal fibrosis severity. Consequently, there is an urgent need for the identification of early, noninvasive CKD biomarkers. Urine, easily collectible and kidney-derived, has demonstrated potential as a diagnostic source for various kidney diseases by leveraging its RNA content. To address this, we obtained RNA-seq data pertaining to urinary RNAs from both CKD patients and healthy controls via the Gene Expression Omnibus database (GEO). The DEseq2 software was utilized to identify differentially expressed RNAs (DE-RNAs). To evaluate the overall accuracy of these DE-RNAs in urine, we performed Receiver Operating Characteristic analysis (ROC). Selected urinary RNAs were subsequently validated using reverse-transcription quantitative real-time Polymerase Chain Reaction (qRT-PCR) in conjunction with ROC analysis. Computational and experimental analyses revealed significant increases in miR-542-5p, miR-33b-5p, miR-190a-3p, miR-507, and CSAG4 within the urine of CKD patients, exhibiting high AUC values. In conclusion, our findings suggest that urinary RNAs hold promise as diagnostic biomarkers for CKD.

Detection of a 7SL RNA-derived small non-coding RNA using Molecular Beacons in vitro and in cells

Small non-coding RNAs (sncRNA) are involved in many steps of the gene expression cascade and regulate processing and expression of mRNAs by the formation of ribonucleoprotein complexes (RNP) such as the RNA-induced silencing complex (RISC). By analyzing small RNA Seq data sets, we identified a sncRNA annotated as piR-hsa-1254, which is likely derived from the 3'-end of 7SL RNA2 (RN7SL2), herein referred to as snc7SL RNA. The 7SL RNA is an abundant long non-coding RNA polymerase III transcript and serves as structural component of the cytoplasmic signal recognition particle (SRP). To evaluate a potential functional role of snc7SL RNA, we aimed to define its cellular localization by live cell imaging. Therefore, a Molecular Beacon (MB)-based method was established to compare the subcellular localization of snc7SL RNA with its precursor 7SL RNA. We designed and characterized several MBs in vitro and tested those by live cell fluorescence microscopy. Using a multiplex approach, we show that 7SL RNA localizes mainly to the endoplasmic reticulum (ER), as expected for the SRP, whereas snc7SL RNA predominately localizes to the nucleus. This finding suggests a fundamentally different function of 7SL RNA and its derivate snc7SL RNA.

Evidence for Existence of Multiple Functional Human Small RNAs Derived from Transcripts of Protein-Coding Genes

The human genome encodes a multitude of different noncoding transcripts that have been traditionally separated on the basis of their lengths into long (>200 nt) or small (<200 nt) noncoding RNAs. The functions, mechanisms of action, and biological relevance of the vast majority of both long and short noncoding transcripts remain unknown. However, according to the functional understanding of the known classes of long and small noncoding RNAs (sncRNAs) that have been shown to play crucial roles in multiple biological processes, it is generally assumed that many unannotated long and small transcripts participate in important cellular functions as well. Nevertheless, direct evidence of functionality is lacking for most noncoding transcripts, especially for sncRNAs that are often dismissed as stable degradation products of longer RNAs. Here, we developed a high-throughput assay to test the functionality of sncRNAs by overexpressing them in human cells. Surprisingly, we found that a significant fraction (>40%) of unannotated sncRNAs appear to have biological relevance. Furthermore, contrary to the expectation, the potentially functional transcripts are not highly abundant and can be derived from protein-coding mRNAs. These results strongly suggest that the small noncoding transcriptome can harbor multiple functional transcripts that warrant future studies.

Diverse monogenic subforms of human spermatogenic failure

Non-obstructive azoospermia (NOA) is the most severe form of male infertility and typically incurable. Defining the genetic basis of NOA has proven challenging, and the most advanced classification of NOA subforms is not based on genetics, but simple description of testis histology. In this study, we exome-sequenced over 1000 clinically diagnosed NOA cases and identified a plausible recessive Mendelian cause in 20%. We find further support for 21 genes in a 2-stage burden test with 2072 cases and 11,587 fertile controls. The disrupted genes are primarily on the autosomes, enriched for undescribed human "knockouts", and, for the most part, have yet to be linked to a Mendelian trait. Integration with single-cell RNA sequencing data shows that azoospermia genes can be grouped into molecular subforms with synchronized expression patterns, and analogs of these subforms exist in mice. This analysis framework identifies groups of genes with known roles in spermatogenesis but also reveals unrecognized subforms, such as a set of genes expressed across mitotic divisions of differentiating spermatogonia. Our findings highlight NOA as an understudied Mendelian disorder and provide a conceptual structure for organizing the complex genetics of male infertility, which may provide a rational basis for disease classification.

EVAtool: an optimized reads assignment tool for small ncRNA quantification and its application in extracellular vesicle datasets

Extracellular vesicles (EVs) carrying various small non-coding RNAs (sncRNAs) play a vital roles in cell communication and diseases. Correct quantification of multiple sncRNA biotypes simultaneously in EVs is a challenge due to the short reads (<30 bp) could be mapped to multiple sncRNA types. To address this question, we developed an optimized reads assignment algorithm (ORAA) to dynamically map multi-mapping reads to the sncRNA type with a higher proportion. We integrated ORAA with reads processing steps into EVAtool Python-package (http://bioinfo.life.hust.edu.cn/EVAtool) to quantify sncRNAs, especially for sncRNA-seq from EV samples. EVAtool allows users to specify interested sncRNA types in advanced mode or use default seven sncRNAs (microRNA, small nucleolar RNA, PIWI-interacting RNAs, small nuclear RNA, ribosomal RNA, transfer RNA and Y RNA). To prove the utilities of EVAtool, we quantified the sncRNA expression profiles for 200 samples from cognitive decline and multiple sclerosis. We found that more than 20% of short reads on average were mapped to multiple sncRNA biotypes in multiple sclerosis. In cognitive decline, the proportion of Y RNA is significantly higher than other sncRNA types. EVAtool is a flexible and extensible tool that would benefit to mine potential biomarkers and functional molecules in EVs.

CRISPRs in the human genome are differentially expressed between malignant and normal adjacent to tumor tissue

Clustered Regularly Interspaced Short Palindromic Repeats (CRISPRs) have been identified in bacteria, archaea and mitochondria of plants, but not in eukaryotes. Here, we report the discovery of 12,572 putative CRISPRs randomly distributed across the human chromosomes, which we termed hCRISPRs. By using available transcriptome datasets, we demonstrate that hCRISPRs are distinctively expressed as small non-coding RNAs (sncRNAs) in cell lines and human tissues. Moreover, expression patterns thereof enabled us to distinguish normal from malignant tissues. In prostate cancer, we confirmed the differential hCRISPR expression between normal adjacent and malignant primary prostate tissue by RT-qPCR and demonstrate that the SHERLOCK and DETECTR dipstick tools are suitable to detect these sncRNAs. We anticipate that the discovery of CRISPRs in the human genome can be further exploited for diagnostic purposes in cancer and other medical conditions, which certainly will lead to the development of point-of-care tests based on the differential expression of the hCRISPRs.

CRISPR elements in the human genome are expressed in both healthy tissues and tumors but with distinct patterns, representing a potential biomarker for cancer.

FILER: a framework for harmonizing and querying large-scale functional genomics knowledge

Querying massive functional genomic and annotation data collections, linking and summarizing the query results across data sources/data types are important steps in high-throughput genomic and genetic analytical workflows. However, these steps are made difficult by the heterogeneity and breadth of data sources, experimental assays, biological conditions/tissues/cell types and file formats. FILER (FunctIonaL gEnomics Repository) is a framework for querying large-scale genomics knowledge with a large, curated integrated catalog of harmonized functional genomic and annotation data coupled with a scalable genomic search and querying interface. FILER uniquely provides: (i) streamlined access to >50 000 harmonized, annotated genomic datasets across >20 integrated data sources, >1100 tissues/cell types and >20 experimental assays; (ii) a scalable genomic querying interface; and (iii) ability to analyze and annotate user's experimental data. This rich resource spans >17 billion GRCh37/hg19 and GRCh38/hg38 genomic records. Our benchmark querying 7 × 109 hg19 FILER records shows FILER is highly scalable, with a sub-linear 32-fold increase in querying time when increasing the number of queries 1000-fold from 1000 to 1 000 000 intervals. Together, these features facilitate reproducible research and streamline integrating/querying large-scale genomic data within analyses/workflows. FILER can be deployed on cloud or local servers (https://bitbucket.org/wanglab-upenn/FILER) for integration with custom pipelines and is freely available (https://lisanwanglab.org/FILER).

Dysregulation of Human Somatic piRNA Expression in Parkinson's Disease Subtypes and Stages

Piwi interacting RNAs (piRNAs) are small non-coding single-stranded RNA species 20–31 nucleotides in size generated from distinct loci. In germline tissues, piRNAs are amplified via a “ping-pong cycle” to produce secondary piRNAs, which act in transposon silencing. In contrast, the role of somatic-derived piRNAs remains obscure. Here, we investigated the identity and distribution of piRNAs in human somatic tissues to determine their function and potential role in Parkinson’s disease (PD). Human datasets were curated from the Gene Expression Omnibus (GEO) database and a workflow was developed to identify piRNAs, which revealed 902 somatic piRNAs of which 527 were expressed in the brain. These were mainly derived from chromosomes 1, 11, and 19 compared to the germline tissues, which were from 15 and 19. Approximately 20% of somatic piRNAs mapped to transposon 3′ untranslated regions (UTRs), but a large proportion were sensed to the transcript in contrast to germline piRNAs. Gene set enrichment analysis suggested that somatic piRNAs function in neurodegenerative disease. piRNAs undergo dysregulation in different PD subtypes (PD and Parkinson’s disease dementia (PDD)) and stages (premotor and motor). piR-has-92056, piR-hsa-150797, piR-hsa-347751, piR-hsa-1909905, piR-hsa-2476630, and piR-hsa-2834636 from blood small extracellular vesicles were identified as novel biomarkers for PD diagnosis using a sparse partial least square discriminant analysis (sPLS-DA) (accuracy: 92%, AUC = 0.89). This study highlights a role for piRNAs in PD and provides tools for novel biomarker development.

MGcount: a total RNA-seq quantification tool to address multi-mapping and multi-overlapping alignments ambiguity in non-coding transcripts

BACKGROUND

Total-RNA sequencing (total-RNA-seq) allows the simultaneous study of both the coding and the non-coding transcriptome. Yet, computational pipelines have traditionally focused on particular biotypes, making assumptions that are not fullfilled by total-RNA-seq datasets. Transcripts from distinct RNA biotypes vary in length, biogenesis, and function, can overlap in a genomic region, and may be present in the genome with a high copy number. Consequently, reads from total-RNA-seq libraries may cause ambiguous genomic alignments, demanding for flexible quantification approaches.

RESULTS

Here we present Multi-Graph count (MGcount), a total-RNA-seq quantification tool combining two strategies for handling ambiguous alignments. First, MGcount assigns reads hierarchically to small-RNA and long-RNA features to account for length disparity when transcripts overlap in the same genomic position. Next, MGcount aggregates RNA products with similar sequences where reads systematically multi-map using a graph-based approach. MGcount outputs a transcriptomic count matrix compatible with RNA-sequencing downstream analysis pipelines, with both bulk and single-cell resolution, and the graphs that model repeated transcript structures for different biotypes. The software can be used as a python module or as a single-file executable program.

CONCLUSIONS

MGcount is a flexible total-RNA-seq quantification tool that successfully integrates reads that align to multiple genomic locations or that overlap with multiple gene features. Its approach is suitable for the simultaneous estimation of protein-coding, long non-coding and small non-coding transcript concentration, in both precursor and processed forms. Both source code and compiled software are available at https://github.com/hitaandrea/MGcount .

Using bioinformatics approaches to identify survival-related oncomiRs as potential targets of miRNA-based treatments for lung adenocarcinoma

Lung cancer is a major cause of cancer-associated deaths worldwide, and lung adenocarcinoma (LUAD) is the most common lung cancer subtype. Micro RNAs (miRNAs) regulate the pattern of gene expression in multiple cancer types and have been explored as potential drug development targets. To develop an oncomiR-based panel, we identified miRNA candidates that show differential expression patterns and are relevant to the worse 5-year overall survival outcomes in LUAD patient samples. We further evaluated various combinations of miRNA candidates for association with 5-year overall survival and identified a four-miRNA panel: miR-9-5p, miR-1246, miR-31-3p, and miR-3136-5p. The combination of these four miRNAs outperformed any single miRNA for predicting 5-year overall survival (hazard ratio [HR]: 3.47, log-rank p-value = 0.000271). Experiments were performed on lung cancer cell lines and animal models to validate the effects of these miRNAs. The results showed that singly transfected antagomiRs largely inhibited cell growth, migration, and invasion, and the combination of all four antagomiRs considerably reduced cell numbers, which is twice as effective as any single miRNA-targeted transfected. The in vivo studies revealed that antagomiR-mediated knockdown of all four miRNAs significantly reduced tumor growth and metastatic ability of lung cancer cells compared to the negative control group. The success of these in vivo and in vitro experiments suggested that these four identified oncomiRs may have therapeutic potential.

Deciphering the tRNA-derived small RNAs: origin, development, and future

Transfer RNA (tRNA)-derived small RNAs (tsRNAs), a novel category of small noncoding RNAs, are enzymatically cleaved from tRNAs. Previous reports have shed some light on the roles of tsRNAs in the development of human diseases. However, our knowledge about tsRNAs is still relatively lacking. In this paper, we review the biogenesis, classification, subcellular localization as well as action mechanism of tsRNAs, and discuss the association between chemical modifications of tRNAs and the production and functions of tsRNAs. Furthermore, using immunity, metabolism, and malignancy as examples, we summarize the molecular mechanisms of tsRNAs in diseases and evaluate the potential of tsRNAs as new biomarkers and therapeutic targets. At the same time, we compile and introduce several resource databases that are currently publicly available for analyzing tsRNAs. Finally, we discuss the challenges associated with research in this field and future directions.

PIWI interacting RNAs perspectives: a new avenues in future cancer investigations

As a currently identified small non-coding RNAs (ncRNAs) category, the PIWI-interacting RNAs (piRNAs) are crucial mediators of cell biology. The human genome comprises over 30.000 piRNA genes. Although considered a new field in cancer research, the piRNA pathway is shown by the existing evidence as an active pathway in a variety of different types of cancers with critical impacts on main aspects of cancer progression. Among the regulatory molecules that contribute to maintaining the dynamics of cancer cells, the P-element Induced WImpy testis (PIWI) proteins and piRNAs, as new players, have not been broadly studied so far. Therefore, the identification of cancer-related piRNAs and the assessment of target genes of piRNAs may lead to better cancer prevention and therapy strategies. This review articleaimed to highlight the role and function of piRNAs based on existing data. Understanding the role of piRNA in cancer may provide perspectives on their applications as particular biomarker signature in diagnosis in early stage, prognosis and therapeutic strategies.

Non-coding RNAs in Regulating Tumor Angiogenesis

Non-coding RNAs (ncRNAs) are RNAs that do not encode proteins, but perform biological functions in various physiological and pathological processes, including cancer formation, inflammation, and neurological diseases. Tumor blood vessels are a key target for cancer management. A number of factors regulate the angiogenesis of malignant tumors. NcRNAs participate in the regulation of tumor angiogenesis. Abnormal expression of ncRNAs act as tumor suppressors or oncogenes to affect the development of tumors. In this review we summarized the biological functions of ncRNAs, and discussed its regulatory mechanisms in tumor angiogenesis. This article will provide new insights for the research of ncRNAs in tumor angiogenesis.

Systematic Identification and Functional Validation of New snoRNAs in Human Muscle Progenitors

Small non-coding RNAs (sncRNAs) represent an important class of regulatory RNAs involved in the regulation of transcription, RNA splicing or translation. Among these sncRNAs, small nucleolar RNAs (snoRNAs) mostly originate from intron splicing in humans and are central to posttranscriptional regulation of gene expression. However, the characterization of the complete repertoire of sncRNAs in a given cellular context and the functional annotation of the human transcriptome are far from complete. Here, we report the large-scale identification of sncRNAs in the size range of 50 to 200 nucleotides without a priori on their biogenesis, structure and genomic origin in the context of normal human muscle cells. We provided a complete set of experimental validation of novel candidate snoRNAs by evaluating the prerequisites for their biogenesis and functionality, leading to their validation as genuine snoRNAs. Interestingly, we also found intergenic snoRNAs, which we showed are in fact integrated into candidate introns of unannotated transcripts or degraded by the Nonsense Mediated Decay pathway. Hence, intergenic snoRNAs represent a new type of landmark for the identification of new transcripts that have gone undetected because of low abundance or degradation after the release of the snoRNA.

piRNAs as Modulators of Disease Pathogenesis

Advances in understanding disease pathogenesis correlates to modifications in gene expression within different tissues and organ systems. In depth knowledge about the dysregulation of gene expression profiles is fundamental to fully uncover mechanisms in disease development and changes in host homeostasis. The body of knowledge surrounding mammalian regulatory elements, specifically regulators of chromatin structure, transcriptional and translational activation, has considerably surged within the past decade. A set of key regulators whose function still needs to be fully elucidated are small non-coding RNAs (sncRNAs). Due to their broad range of unfolding functions in the regulation of gene expression during transcription and translation, sncRNAs are becoming vital to many cellular processes. Within the past decade, a novel class of sncRNAs called PIWI-interacting RNAs (piRNAs) have been implicated in various diseases, and understanding their complete function is of vital importance. Historically, piRNAs have been shown to be indispensable in germline integrity and stem cell development. Accumulating research evidence continue to reveal the many arms of piRNA function. Although piRNA function and biogenesis has been extensively studied in Drosophila, it is thought that they play similar roles in vertebrate species, including humans. Compounding evidence suggests that piRNAs encompass a wider functional range than small interfering RNAs (siRNAs) and microRNAs (miRNAs), which have been studied more in terms of cellular homeostasis and disease. This review aims to summarize contemporary knowledge regarding biogenesis, and homeostatic function of piRNAs and their emerging roles in the development of pathologies related to cardiomyopathies, cancer, and infectious diseases.

Multiple information carried by RNAs: total eclipse or a light at the end of the tunnel?

The findings that an RNA is not necessarily either coding or non-coding, or that a precursor RNA can produce different types of mature RNAs, whether coding or non-coding, long or short, have challenged the dichotomous view of the RNA world almost 15 years ago. Since then, and despite an increasing number of studies, the diversity of information that can be conveyed by RNAs is rarely searched for, and when it is known, it remains largely overlooked in further functional studies. Here, we provide an update with prominent examples of multiple functions that are carried by the same RNA or are produced by the same precursor RNA, to emphasize their biological relevance in most living organisms. An important consequence is that the overall function of their locus of origin results from the balance between various RNA species with distinct functions and fates. The consideration of the molecular basis of this multiplicity of information is obviously crucial for downstream functional studies when the targeted functional molecule is often not the one that is believed.

Non-Coding RNA Databases in Cardiovascular Research

Cardiovascular diseases (CVDs) are of multifactorial origin and can be attributed to several genetic and environmental components. CVDs are the leading cause of mortality worldwide and they primarily damage the heart and the vascular system. Non-coding RNA (ncRNA) refers to functional RNA molecules, which have been transcribed into DNA but do not further get translated into proteins. Recent transcriptomic studies have identified the presence of thousands of ncRNA molecules across species. In humans, less than 2% of the total genome represents the protein-coding genes. While the role of many ncRNAs is yet to be ascertained, some long non-coding RNAs (lncRNAs) and microRNAs (miRNAs) have been associated with disease progression, serving as useful diagnostic and prognostic biomarkers. A plethora of data repositories specialized in ncRNAs have been developed over the years using publicly available high-throughput data from next-generation sequencing and other approaches, that cover various facets of ncRNA research like basic and functional annotation, expressional profile, structural and molecular changes, and interaction with other biomolecules. Here, we provide a compendium of the current ncRNA databases relevant to cardiovascular research.

Versatile interactions and bioinformatics analysis of noncoding RNAs

Advances in RNA sequencing technologies and computational methodologies have provided a huge impetus to noncoding RNA (ncRNA) study. Once regarded as inconsequential results of transcriptional promiscuity, ncRNAs were later found to exert great roles in various aspects of biological functions. They are emerging as key players in gene regulatory networks by interacting with other biomolecules (DNA, RNA or protein). Here, we provide an overview of ncRNA repertoire and highlight recent discoveries of their versatile interactions. To better investigate the ncRNA-mediated regulation, it is necessary to make full use of innovative sequencing techniques and computational tools. We further describe a comprehensive workflow for in silico ncRNA analysis, providing up-to-date platforms, databases and tools dedicated to ncRNA identification and functional annotation.

Circulating Small Noncoding RNA Biomarkers of Response to Triple Disease-modifying Antirheumatic Drug Therapy in White Women With Early Rheumatoid Arthritis

OBJECTIVE

To identify small noncoding RNA (sncRNA) serum biomarkers that predict response to triple disease-modifying antirheumatic drug (DMARD) therapy in patients with early rheumatoid arthritis (RA).

METHODS

Early RA patients entered into a treat-to-target management algorithm, with triple DMARD therapy (methotrexate, sulfasalazine, hydroxychloroquine). Patients were assessed following 6 months of therapy and classified as European League Against Rheumatism responders or nonresponders. RNA was isolated from 42 archived serum samples, collected prior to commencement of triple DMARD therapy. Small RNA sequencing was performed and the reads mapped to annotations in a database of human sncRNA. Differential expression analysis was performed, comparing responders (n = 24) and nonresponders (n = 18).

RESULTS

Pretreatment levels of 4 sncRNA were significantly increased in nonresponders: chr1. tRNA131-GlyCCC (4.1-fold, adjusted P = 0.01), chr2.tRNA13-AlaCGC (2.2-fold, adjusted P = 0.02), U2-L166 (6.6-fold, adjusted P = 0.02), and piR-35982 (2.4-fold, adjusted P = 0.03). 5S-L612 was the only sncRNA significantly increased in responders (3.3-fold; adjusted P = 0.01). Reads for chr1. tRNA131-GlyCCC and chr2.tRNA13-AlaCGC mapped to the 5' end of each tRNA gene and were truncated at the anticodon loop, consistent with these sncRNA having roles as 5' translation interfering tRNA halves (tiRNA).

CONCLUSION

Pretreatment levels of specific serum sncRNA might facilitate identification of patients more likely to respond to triple DMARD therapy.

HiPR: High-throughput probabilistic RNA structure inference

Recent high-throughput structure-sensitive genome-wide sequencing-based assays have enabled large-scale studies of RNA structure, and robust transcriptome-wide computational prediction of individual RNA structures across RNA classes from these assays has potential to further improve the prediction accuracy. Here, we describe HiPR, a novel method for RNA structure prediction at single-nucleotide resolution that combines high-throughput structure probing data (DMS-seq, DMS-MaPseq) with a novel probabilistic folding algorithm. On validation data spanning a variety of RNA classes, HiPR often increases accuracy for predicting RNA structures, giving researchers new tools to study RNA structure.

The Biogenesis and Functions of piRNAs in Human Diseases

Piwi-interacting RNAs (piRNAs) are a novel type of small noncoding RNAs, which are 26-30 nt in length and bind to Piwi proteins. These short RNAs were originally discovered in germline cells and are considered as key regulators for germline maintenance. A growing body of evidence has now extended our views into piRNA biological significance showing that they can also regulate gene expression in somatic cells through transposon silencing, epigenetic programming, DNA rearrangements, mRNA turnover, and translational control. Mounting studies have revealed that the dysregulation of piRNAs may cause epigenetic changes and contribute to diverse diseases. This review illustrates piRNA biogenesis, mechanisms behind piRNA-mediated gene regulation, and changes of piRNAs in different diseases, especially in cancers.

PIWI-interacting RNAs are differentially expressed during cardiac differentiation of human pluripotent stem cells

PIWI-interacting RNAs (piRNAs) are a class of non-coding RNAs initially thought to be restricted exclusively to germline cells. In recent years, accumulating evidence has demonstrated that piRNAs are actually expressed in pluripotent, neural, cardiac and even cancer cells. However, controversy remains around the existence and function of somatic piRNAs. Using small RNA-seq samples from H9 pluripotent cells differentiated to mesoderm progenitors and cardiomyocytes we identified the expression of 447 piRNA transcripts, of which 241 were detected in pluripotency, 218 in mesoderm and 171 in cardiac cells. The majority of them originated from the sense strand of protein coding and lncRNAs genes in all stages of differentiation, though no evidences of amplification loop (ping-pong) were found. Genes hosting piRNA transcripts in cardiac samples were related to critical biological processes in the heart, like contraction and cardiac muscle development. Our results indicate that these piRNAs might have a role in fine-tuning the expression of genes involved in differentiation of pluripotent cells to cardiomyocytes.

MicroRNA 27a Is a Key Modulator of Cholesterol Biosynthesis

Hypercholesterolemia is a strong predictor of cardiovascular diseases. The 3-hydroxy-3-methylglutaryl coenzyme A reductase gene (Hmgcr) coding for the rate-limiting enzyme in the cholesterol biosynthesis pathway is a crucial regulator of plasma cholesterol levels. However, the posttranscriptional regulation of Hmgcr remains poorly understood. The main objective of this study was to explore the role of microRNAs (miRNAs) in the regulation of Hmgcr expression. Systematic in silico predictions and experimental analyses reveal that miRNA 27a (miR-27a) specifically interacts with the Hmgcr 3' untranslated region in murine and human hepatocytes. Moreover, our data show that Hmgcr expression is inversely correlated with miR-27a levels in various cultured cell lines and in human and rodent tissues. Actinomycin D chase assays and relevant experiments demonstrate that miR-27a regulates Hmgcr by translational attenuation followed by mRNA degradation. Early growth response 1 (Egr1) regulates miR-27a expression under basal and cholesterol-modulated conditions. miR-27a augmentation via tail vein injection of miR-27a mimic in high-cholesterol-diet-fed Apoe ^-/- mice shows downregulation of hepatic Hmgcr and plasma cholesterol levels. Pathway and gene expression analyses show that miR-27a also targets several other genes (apart from Hmgcr) in the cholesterol biosynthesis pathway. Taken together, miR-27a emerges as a key regulator of cholesterol biosynthesis and has therapeutic potential for the clinical management of hypercholesterolemia.

RNA-Seq profiling of deregulated miRs in CLL and their impact on clinical outcome

Abnormal expression patterns of regulatory small non-coding RNA (sncRNA) molecules such as microRNAs (miRs), piwi-interacting RNAs (piRNAs), and small nucleolar RNAs (snoRNAs) play an important role in the development and progression of cancer. Identification of clinically relevant sncRNA signatures could, therefore, be of tremendous translational value. In the present study, genome-wide small RNA sequencing identified a unique pattern of differential regulation of eight miRs in Chronic Lymphocytic Leukemia (CLL). Among these, three were up-regulated (miR-1295a, miR-155, miR-4524a) and five were down-regulated (miR-30a, miR-423, miR-486*, let-7e, and miR-744) in CLL. Altered expression of all these eight differentially expressed miRs (DEMs) was validated by RQ-PCR. Besides, seven novel sequences identified to have elevated expression levels in CLL turned out to be transfer RNA (tRNA)/piRNAs (piRNA-30799, piRNA-36225)/snoRNA (SNORD43) related. Multivariate analysis showed that miR-4524a (HR: 1.916, 95% CI: 1.080–3.4, p value: 0.026) and miR-744 (HR: 0.415, 95% CI: 0.224–0.769, p value: 0.005) were significantly associated with risk and time to first treatment. Further investigations could help establish the scope of integration of these DEM markers into risk stratification designs and prognostication approaches for CLL.

SEAweb: the small RNA Expression Atlas web application

We present the Small RNA Expression Atlas (SEAweb), a web application that allows for the interactive querying, visualization and analysis of known and novel small RNAs across 10 organisms. It contains sRNA and pathogen expression information for over 4200 published samples with standardized search terms and ontologies. In addition, SEAweb allows for the interactive visualization and re-analysis of 879 differential expression and 514 classification comparisons. SEAweb's user model enables sRNA researchers to compare and re-analyze user-specific and published datasets, highlighting common and distinct sRNA expression patterns. We provide evidence for SEAweb's fidelity by (i) generating a set of 591 tissue specific miRNAs across 29 tissues, (ii) finding known and novel bacterial and viral infections across diseases and (iii) determining a Parkinson's disease-specific blood biomarker signature using novel data. We believe that SEAweb's simple semantic search interface, the flexible interactive reports and the user model with rich analysis capabilities will enable researchers to better understand the potential function and diagnostic value of sRNAs or pathogens across tissues, diseases and organisms.

DASHR 2.0: integrated database of human small non-coding RNA genes and mature products

Motivation

Small non-coding RNAs (sncRNAs, <100 nts) are highly abundant RNAs that regulate diverse and often tissue-specific cellular processes by associating with transcription factor complexes or binding to mRNAs. While thousands of sncRNA genes exist in the human genome, no single resource provides searchable, unified annotation, expression and processing information for full sncRNA transcripts and mature RNA products derived from these larger RNAs.

Results

Our goal is to establish a complete catalog of annotation, expression, processing, conservation, tissue-specificity and other biological features for all human sncRNA genes and mature products derived from all major RNA classes. DASHR (Database of small human non-coding RNAs) v2.0 database is the first that integrates human sncRNA gene and mature products profiles obtained from multiple RNA-seq protocols. Altogether, 185 tissues/cell types and sncRNA annotations and >800 curated experiments from ENCODE and GEO/SRA across multiple RNA-seq protocols for both GRCh38/hg38 and GRCh37/hg19 assemblies are integrated in DASHR. Moreover, DASHR is the first to contain both known and novel, previously un-annotated sncRNA loci identified by unsupervised segmentation (13 times more loci with 1 678 800 total). Additionally, DASHR v2.0 adds >3 200 000 annotations for non-small RNA genes and other genomic features (long-noncoding RNAs, mRNAs, promoters, repeats). Furthermore, DASHR v2.0 introduces an enhanced user interface, interactive experiment-by-locus table view, sncRNA locus sorting and filtering by biological features. All annotation and expression information directly downloadable and accessible as UCSC genome browser tracks.

Availability and implementation

DASHR v2.0 is freely available at https://lisanwanglab.org/DASHRv2.

Supplementary information

Supplementary data are available at Bioinformatics online.

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.

Altered Fecal Small RNA Profiles in Colorectal Cancer Reflect Gut Microbiome Composition in Stool Samples

The characteristics of microbial small RNA transcription are largely unknown, while it is of primary importance for a better identification of molecules with functional activities in the gut niche under both healthy and disease conditions. By performing combined analyses of metagenomic and small RNA sequencing (sRNA-Seq) data, we characterized both the human and microbial small RNA contents of stool samples from healthy individuals and from patients with colorectal carcinoma or adenoma. With the integrative analyses of metagenomic and sRNA-Seq data, we identified a human and microbial small RNA signature which can be used to improve diagnosis of the disease. Our analysis of human and gut microbiome small RNA expression is relevant to generation of the first hypotheses about the potential molecular interactions occurring in the gut of CRC patients, and it can be the basis for further mechanistic studies and clinical tests.

Dysbiotic configurations of the human gut microbiota have been linked to colorectal cancer (CRC). Human small noncoding RNAs are also implicated in CRC, and recent findings suggest that their release in the gut lumen contributes to shape the gut microbiota. Bacterial small RNAs (bsRNAs) may also play a role in carcinogenesis, but their role has been less extensively explored. Here, we performed small RNA and shotgun sequencing on 80 stool specimens from patients with CRC or with adenomas and from healthy subjects collected in a cross-sectional study to evaluate their combined use as a predictive tool for disease detection. We observed considerable overlap and a correlation between metagenomic and bsRNA quantitative taxonomic profiles obtained from the two approaches. We identified a combined predictive signature composed of 32 features from human and microbial small RNAs and DNA-based microbiome able to accurately classify CRC samples separately from healthy and adenoma samples (area under the curve [AUC] = 0.87). In the present study, we report evidence that host-microbiome dysbiosis in CRC can also be observed by examination of altered small RNA stool profiles. Integrated analyses of the microbiome and small RNAs in the human stool may provide insights for designing more-accurate tools for diagnostic purposes.

IMPORTANCE The characteristics of microbial small RNA transcription are largely unknown, while it is of primary importance for a better identification of molecules with functional activities in the gut niche under both healthy and disease conditions. By performing combined analyses of metagenomic and small RNA sequencing (sRNA-Seq) data, we characterized both the human and microbial small RNA contents of stool samples from healthy individuals and from patients with colorectal carcinoma or adenoma. With the integrative analyses of metagenomic and sRNA-Seq data, we identified a human and microbial small RNA signature which can be used to improve diagnosis of the disease. Our analysis of human and gut microbiome small RNA expression is relevant to generation of the first hypotheses about the potential molecular interactions occurring in the gut of CRC patients, and it can be the basis for further mechanistic studies and clinical tests.

SPAR: small RNA-seq portal for analysis of sequencing experiments

The introduction of new high-throughput small RNA sequencing protocols that generate large-scale genomics datasets along with increasing evidence of the significant regulatory roles of small non-coding RNAs (sncRNAs) have highlighted the urgent need for tools to analyze and interpret large amounts of small RNA sequencing data. However, it remains challenging to systematically and comprehensively discover and characterize sncRNA genes and specifically-processed sncRNA products from these datasets. To fill this gap, we present Small RNA-seq Portal for Analysis of sequencing expeRiments (SPAR), a user-friendly web server for interactive processing, analysis, annotation and visualization of small RNA sequencing data. SPAR supports sequencing data generated from various experimental protocols, including smRNA-seq, short total RNA sequencing, microRNA-seq, and single-cell small RNA-seq. Additionally, SPAR includes publicly available reference sncRNA datasets from our DASHR database and from ENCODE across 185 human tissues and cell types to produce highly informative small RNA annotations across all major small RNA types and other features such as co-localization with various genomic features, precursor transcript cleavage patterns, and conservation. SPAR allows the user to compare the input experiment against reference ENCODE/DASHR datasets. SPAR currently supports analyses of human (hg19, hg38) and mouse (mm10) sequencing data. SPAR is freely available at https://www.lisanwanglab.org/SPAR.

m6AVar: a database of functional variants involved in m6A modification

Identifying disease-causing variants among a large number of single nucleotide variants (SNVs) is still a major challenge. Recently, N⁶-methyladenosine (m⁶A) has become a research hotspot because of its critical roles in many fundamental biological processes and a variety of diseases. Therefore, it is important to evaluate the effect of variants on m⁶A modification, in order to gain a better understanding of them. Here, we report m6AVar (http://m6avar.renlab.org), a comprehensive database of m⁶A-associated variants that potentially influence m⁶A modification, which will help to interpret variants by m⁶A function. The m⁶A-associated variants were derived from three different m⁶A sources including miCLIP/PA-m⁶A-seq experiments (high confidence), MeRIP-Seq experiments (medium confidence) and transcriptome-wide predictions (low confidence). Currently, m6AVar contains 16 132 high, 71 321 medium and 326 915 low confidence level m⁶A-associated variants. We also integrated the RBP-binding regions, miRNA-targets and splicing sites associated with variants to help users investigate the effect of m⁶A-associated variants on post-transcriptional regulation. Because it integrates the data from genome-wide association studies (GWAS) and ClinVar, m6AVar is also a useful resource for investigating the relationship between the m⁶A-associated variants and disease. Overall, m6AVar will serve as a useful resource for annotating variants and identifying disease-causing variants.

Identification, Prediction and Data Analysis of Noncoding RNAs: A Review

BACKGROUND

Noncoding RNAs (ncRNAs) which play an important role in various cellular processes are important in medicine as well as in drug design strategies. Different studies have shown that ncRNAs are dis-regulated in cancer cells and play an important role in human tumorigenesis. Therefore, it is important to identify and predict such molecules by experimental and computational methods, respectively. However, to avoid expensive experimental methods, computational algorithms have been developed for accurately and fast prediction of ncRNAs.

OBJECTIVE

The aim of this review was to introduce the experimental and computational methods to identify and predict ncRNAs structure. Also, we explained the ncRNA's roles in cellular processes and drugs design, briefly.

METHOD

In this survey, we will introduce ncRNAs and their roles in biological and medicinal processes. Then, some important laboratory techniques will be studied to identify ncRNAs. Finally, the state-of-the-art models and algorithms will be introduced along with important tools and databases.

RESULTS

The results showed that the integration of experimental and computational approaches improves to identify ncRNAs. Moreover, the high accurate databases, algorithms and tools were compared to predict the ncRNAs.

CONCLUSION

ncRNAs prediction is an exciting research field, but there are different difficulties. It requires accurate and reliable algorithms and tools. Also, it should be mentioned that computational costs of such algorithm including running time and usage memory are very important. Finally, some suggestions were presented to improve computational methods of ncRNAs gene and structural prediction.

The full recovery of mice (Mus Musculus C57BL/6 strain) from virus-induced sarcoma after treatment with a complex of DDMC delivery system and sncRNAs

Background

Virus-induced cellular genetic modifications result in the development of many human cancers.

Methods

In our experiments, we used the RVP3 cell line, which produce primary mouse virus-induced sarcoma in 100% of cases. Inbreed 4-week-old female C57BL/6 mice were injected subcutaneously in the interscapular region with RVP3 cells. Three groups of mice were used. For treatment, one and/or two intravenous injections of a complex of small non-coding RNAs (sncRNAs) a-miR-155, piR-30074, and miR-125b with a 2-diethylaminoethyl-dextran methyl methacrylate copolymer (DDMC) delivery system were used. The first group consisted of untreated animals (control). The second group was treated with one injection of complex DDMC/sncRNAs (1st group). The third group was treated with two injections of complex DDMC/sncRNAs (2nd group). The tumors were removed aseptically, freed of necrotic material, and used with spleen and lungs for subsequent RT-PCR and immunofluorescence experiments, or stained with Leishman-Romanowski dye.

Results

As a result, the mice fully recovered from virus-induced sarcoma after two treatments with a complex including the DDMC vector and a-miR-155, piR-30074, and miR-125b. In vitro studies showed genetic and morphological transformations of murine cancer cells after the injections.

Conclusions

Treatment of virus-induced sarcoma of mice with a-miR-155, piR-30074, and miR-125b as active component of anti-cancer complex and DDMC vector as delivery system due to epigenetic-regulated transformation of cancer cells into cells with non-cancerous physiology and morphology and full recovery of disease.

Profiling of epididymal small non-protein-coding RNAs

BACKGROUND

Our understanding of epididymal physiology and function has been transformed over the three decades in which the International Meeting Series on the Epididymis has been hosted. This transformation has occurred along many fronts, but among the most significant advances has been the unexpected discovery of the diversity of small non-protein-coding RNAs (sRNAs) expressed in the epididymal epithelium and differentially accumulated in the luminal population of spermatozoa.

OBJECTIVES

Here we survey recent literature pertaining to profiling the sRNA landscape of the mammalian epididymis with the goal of demonstrating the contribution that these key regulatory elements, and their associated pathways, make to epididymal physiology and sperm maturation.

RESULTS AND DISCUSSION

High throughput sequencing strategies have fueled an unprecedented advance in our understanding of RNA biology. In the last decade, such high throughput profiling tools have been increasingly applied to study the mammalian epididymis, presaging the discovery of diverse classes of sRNA expressed along the length of the tract. Among the best studied sRNA classes are the microRNAs (miRNA), a sRNA species shown to act in concert with endocrine signals to fine-tune the segmental patterning of epididymal gene expression. In addition to performing this homeostatic role, epithelial cell-derived sRNAs also selectively accumulate into the epididymosomes and spermatozoa that occupy the duct lumen. This exciting discovery alludes to a novel form of intracellular communication that contributes to the establishment of the sperm epigenome and its modification under conditions of paternal stress.

CONCLUSION

Compelling literature has identified sRNAs as a crucial regulatory tier that allows the epididymis to fulfill its combined roles of sperm transport, maturation, and storage. Continued research in this emerging field will contribute to our growing understanding of the etiology of male factor infertility and potentially allow for the future design of rational therapeutic options for these individuals.

The cellular landscape of mid-size noncoding RNA

Noncoding RNA plays an important role in all aspects of the cellular life cycle, from the very basic process of protein synthesis to specialized roles in cell development and differentiation. However, many noncoding RNAs remain uncharacterized and the function of most of them remains unknown. Mid-size noncoding RNAs (mncRNAs), which range in length from 50 to 400 nucleotides, have diverse regulatory functions but share many fundamental characteristics. Most mncRNAs are produced from independent promoters although others are produced from the introns of other genes. Many are found in multiple copies in genomes. mncRNAs are highly structured and carry many posttranscriptional modifications. Both of these facets dictate their RNA-binding protein partners and ultimately their function. mncRNAs have already been implicated in translation, catalysis, as guides for RNA modification, as spliceosome components and regulatory RNA. However, recent studies are adding new mncRNA functions including regulation of gene expression and alternative splicing. In this review, we describe the different classes, characteristics and emerging functions of mncRNAs and their relative expression patterns. Finally, we provide a portrait of the challenges facing their detection and annotation in databases. This article is categorized under: Regulatory RNAs/RNAi/Riboswitches > Regulatory RNAs RNA Structure and Dynamics > RNA Structure, Dynamics, and Chemistry RNA Structure and Dynamics > Influence of RNA Structure in Biological Systems RNA Evolution and Genomics > RNA and Ribonucleoprotein Evolution.

Noncoding RNAs Databases: Current Status and Trends

One of the most important resources for researchers of noncoding RNAs is the information available in public databases spread over the internet. However, the effective exploration of this data can represent a daunting task, given the large amount of databases available and the variety of stored data. This chapter describes a classification of databases based on information source, type of RNA, source organisms, data formats, and the mechanisms for information retrieval, detailing the relevance of each of these classifications and its usability by researchers. This classification is used to update a 2012 review, indexing now more than 229 public databases. This review will include an assessment of the new trends for ncRNA research based on the information that is being offered by the databases. Additionally, we will expand the previous analysis focusing on the usability and application of these databases in pathogen and disease research. Finally, this chapter will analyze how currently available database schemas can help the development of new and improved web resources.

Inferring the Molecular Mechanisms of Noncoding Alzheimer's Disease-Associated Genetic Variants

Most of the loci identified by genome-wide association studies (GWAS) for late-onset Alzheimer's disease (LOAD) are in strong linkage disequilibrium (LD) with nearby variants all of which could be the actual functional variants, often in non-protein-coding regions and implicating underlying gene regulatory mechanisms. We set out to characterize the causal variants, regulatory mechanisms, tissue contexts, and target genes underlying these associations. We applied our INFERNO algorithm to the top 19 non-APOE loci from the IGAP GWAS study. INFERNO annotated all LD-expanded variants at each locus with tissue-specific regulatory activity. Bayesian co-localization analysis of summary statistics and eQTL data was performed to identify tissue-specific target genes. INFERNO identified enhancer dysregulation in all 19 tag regions analyzed, significant enrichments of enhancer overlaps in the immune-related blood category, and co-localized eQTL signals overlapping enhancers from the matching tissue class in ten regions (ABCA7, BIN1, CASS4, CD2AP, CD33, CELF1, CLU, EPHA1, FERMT2, ZCWPW1). In several cases, we identified dysregulation of long noncoding RNA (lncRNA) transcripts and applied the lncRNA target identification algorithm from INFERNO to characterize their downstream biological effects. We also validated the allele-specific effects of several variants on enhancer function using luciferase expression assays. By integrating functional genomics with GWAS signals, our analysis yielded insights into the regulatory mechanisms, tissue contexts, genes, and biological processes affected by noncoding genetic variation associated with LOAD risk.

Identification of tRNA-derived ncRNAs in TCGA and NCI-60 panel cell lines and development of the public database tRFexplorer

Next-generation sequencing is increasing our understanding and knowledge of non-coding RNAs (ncRNAs), elucidating their roles in molecular mechanisms and processes such as cell growth and development. Within such a class, tRNA-derived ncRNAs have been recently associated with gene expression regulation in cancer progression. In this paper, we characterize, for the first time, tRNA-derived ncRNAs in NCI-60. Furthermore, we assess their expression profile in The Cancer Genome Atlas (TCGA). Our comprehensive analysis allowed us to report 322 distinct tRNA-derived ncRNAs in NCI-60, categorized in tRNA-derived fragments (11 tRF-5s, 55 tRF-3s), tRNA-derived small RNAs (107 tsRNAs) and tRNA 5' leader RNAs (149 sequences identified). In TCGA, we were able to identify 232 distinct tRNA-derived ncRNAs categorized in 53 tRF-5s, 58 tRF-3s, 63 tsRNAs and 58 5' leader RNAs. This latter group represents an additional evidence of tRNA-derived ncRNAs originating from the 5' leader region of precursor tRNA. We developed a public database, tRFexplorer, which provides users with the expression profile of each tRNA-derived ncRNAs in every cell line in NCI-60 as well as for each TCGA tumor type. Moreover, the system allows us to perform differential expression analyses of such fragments in TCGA, as well as correlation analyses of tRNA-derived ncRNAs expression in TCGA and NCI-60 with gene and miRNA expression in TCGA samples, in association with all omics and compound activities data available on CellMiner. Hence, the tool provides an important opportunity to investigate their potential biological roles in absence of any direct experimental evidence. Database URL: https://trfexplorer.cloud/.

Competing endogenous RNA (ceRNA) cross talk and language in ceRNA regulatory networks: A new look at hallmarks of breast cancer

Breast cancer (BC) is the most frequently occurring malignancy in women worldwide. Despite the substantial advancement in understanding the molecular mechanisms and management of BC, it remains the leading cause of cancer death in women. One of the main reasons for this obstacle is that we have not been able to find the Achilles heel for the BC as a highly heterogeneous disease. Accumulating evidence has revealed that noncoding RNAs (ncRNAs), play key roles in the development of BC; however, the involving of complex regulatory interactions between the different varieties of ncRNAs in the development of this cancer has been poorly understood. In the recent years, the newly discovered mechanism in the RNA world is "competing endogenous RNA (ceRNA)" which proposes regulatory dialogues between different RNAs, including long ncRNAs (lncRNAs), microRNAs (miRNAs), transcribed pseudogenes, and circular RNAs (circRNAs). In the latest BC research, various studies have revealed that dysregulation of several ceRNA networks (ceRNETs) between these ncRNAs has fundamental roles in establishing the hallmarks of BC development. And it is thought that such a discovery could open a new window for a better understanding of the hidden aspects of breast tumors. Besides, it probably can provide new biomarkers and potential efficient therapeutic targets for BC. This review will discuss the existing body of knowledge regarding the key functions of ceRNETs and then highlights the emerging roles of some recently discovered ceRNETs in several hallmarks of BC. Moreover, we propose for the first time the "ceRnome" as a new term in the present article for RNA research.

Non-coding RNAome of RPE cells under oxidative stress suggests unknown regulative aspects of Retinitis pigmentosa etiopathogenesis

The discovery of thousands of non-coding RNAs has revolutionized molecular biology, being implicated in several biological processes and diseases. To clarify oxidative stress role on Retinitis pigmentosa, a very heterogeneous and inherited ocular disorder group characterized by progressive retinal degeneration, we realized a comparative transcriptome analysis of human retinal pigment epithelium cells, comparing two groups, one treated with oxLDL and one untreated, in four time points (1 h, 2 h, 4 h, 6 h). Data analysis foresaw a complex pipeline, starting from CLC Genomics Workbench, STAR and TopHat2/TopHat-Fusion alignment comparisons, followed by transcriptomes assembly and expression quantification. We then filtered out non-coding RNAs and continued the computational analysis roadmap with specific tools and databases for long non-coding RNAs (FEELnc), circular RNAs (CIRCexplorer, UROBORUS, CIRI, KNIFE, CircInteractome) and piwi-interacting RNAs (piRNABank, piRNA Cluster, piRBase, PILFER). Finally, all detected non-coding RNAs underwent pathway analysis by Cytoscape software. Eight-hundred and fifty-four non-coding RNAs, between long non-coding RNAs and PIWI-interacting, were differentially expressed throughout all considered time points, in treated and untreated samples. These non-coding RNAs target host genes involved in several biochemical pathways are related to compromised response to oxidative stress, visual functions, synaptic impairment of retinal neurotransmission, impairment of the interphotoreceptor matrix and blood – retina barrier, all leading to retinal cell death. These data suggest that non-coding RNAs could play a relevant role in Retinitis pigmentosa etiopathogenesis.

Mini viral RNAs act as innate immune agonists during influenza virus infection

The molecular processes that determine the outcome of influenza virus infection in humans are multifactorial and involve a complex interplay between host, viral and bacterial factors1. However, it is generally accepted that a strong innate immune dysregulation known as 'cytokine storm' contributes to the pathology of infections with the 1918 H1N1 pandemic or the highly pathogenic avian influenza viruses of the H5N1 subtype2-4. The RNA sensor retinoic acid-inducible gene I (RIG-I) plays an important role in sensing viral infection and initiating a signalling cascade that leads to interferon expression5. Here, we show that short aberrant RNAs (mini viral RNAs (mvRNAs)), produced by the viral RNA polymerase during the replication of the viral RNA genome, bind to and activate RIG-I and lead to the expression of interferon-β. We find that erroneous polymerase activity, dysregulation of viral RNA replication or the presence of avian-specific amino acids underlie mvRNA generation and cytokine expression in mammalian cells. By deep sequencing RNA samples from the lungs of ferrets infected with influenza viruses, we show that mvRNAs are generated during infection in vivo. We propose that mvRNAs act as the main agonists of RIG-I during influenza virus infection.

Arena-Idb: a platform to build human non-coding RNA interaction networks

BACKGROUND

High throughput technologies have provided the scientific community an unprecedented opportunity for large-scale analysis of genomes. Non-coding RNAs (ncRNAs), for a long time believed to be non-functional, are emerging as one of the most important and large family of gene regulators and key elements for genome maintenance. Functional studies have been able to assign to ncRNAs a wide spectrum of functions in primary biological processes, and for this reason they are assuming a growing importance as a potential new family of cancer therapeutic targets. Nevertheless, the number of functionally characterized ncRNAs is still too poor if compared to the number of new discovered ncRNAs. Thus platforms able to merge information from available resources addressing data integration issues are necessary and still insufficient to elucidate ncRNAs biological roles.

RESULTS

In this paper, we describe a platform called Arena-Idb for the retrieval of comprehensive and non-redundant annotated ncRNAs interactions. Arena-Idb provides a framework for network reconstruction of ncRNA heterogeneous interactions (i.e., with other type of molecules) and relationships with human diseases which guide the integration of data, extracted from different sources, via mapping of entities and minimization of ambiguity.

CONCLUSIONS

Arena-Idb provides a schema and a visualization system to integrate ncRNA interactions that assists in discovering ncRNA functions through the extraction of heterogeneous interaction networks. The Arena-Idb is available at http://arenaidb.ba.itb.cnr.it.

Epigenetic changes in status epilepticus

Epigenetics refers broadly to processes that influence medium- to long-term expression of genes through changes to the readability and accessibility of the genome to transcription. The mediators include DNA methylation, posttranslational modification of histone proteins, and noncoding RNAs. The present review focuses on recent findings showing epigenetic processes influence susceptibility to and severity of status epilepticus, while status epilepticus in turn drives changes to epigenetic marks that affect the gene expression landscape underlying epileptogenesis. Experimental status epilepticus triggers select, spatiotemporal hypo- and hypermethylation changes throughout the genome. Experimental manipulations that alter DNA methylation after status epilepticus are associated with amelioration of cognitive and hyperexcitability phenotypes. Prolonged seizures also modify chromatin compaction via acetylation and other changes to histones and their expression. Finally, short noncoding RNAs called microRNAs target networks of genes through posttranscriptional and other mechanisms and their modulation can alter status epilepticus as well as serve as potential molecular biomarkers. Long noncoding RNAs have also been targeted to influence expression of genes affecting electrophysiological functions of neurons. In summary, epigenetic processes can modulate status epilepticus, and status epilepticus imposes changes on the epigenome, which together provide novel insight into pathomechanisms, therapy, and biomarkers for status epilepticus.

Non-coding RNA in cystic fibrosis

Non-coding RNAs (ncRNAs) are an abundant class of RNAs that include small ncRNAs, long non-coding RNAs (lncRNA) and pseudogenes. The human ncRNA atlas includes thousands of these specialised RNA molecules that are further subcategorised based on their size or function. Two of the more well-known and widely studied ncRNA species are microRNAs (miRNAs) and lncRNAs. These are regulatory RNAs and their altered expression has been implicated in the pathogenesis of a variety of human diseases. Failure to express a functional cystic fibrosis (CF) transmembrane receptor (CFTR) chloride ion channel in epithelial cells underpins CF. Secondary to the CFTR defect, it is known that other pathways can be altered and these may contribute to the pathophysiology of CF lung disease in particular. For example, quantitative alterations in expression of some ncRNAs are associated with CF. In recent years, there has been a series of published studies exploring ncRNA expression and function in CF. The majority have focussed principally on miRNAs, with just a handful of reports to date on lncRNAs. The present study reviews what is currently known about ncRNA expression and function in CF, and discusses the possibility of applying this knowledge to the clinical management of CF in the near future.

Distribution of ncRNAs expression across hypothalamic-pituitary-gonadal axis in Capra hircus

Background

Molecular regulation of the hypothalamic-pituitary-gonadal (HPG) axis plays an essential role in the fine tuning of seasonal estrus in Capra hircus. Noncoding RNAs (ncRNAs) are emerging as key regulators in sexual development and mammalian reproduction. In order to identify ncRNAs and to assess their expression patterns, along the HPG axis, we sequenced ncRNA libraries from hypothalamus, pituitary and ovary of three goats.

Results

Among the medium length noncoding RNAs (mncRNAs) identified, small nucleolar RNAs (snoRNAs) and transfer RNAs (tRNAs) were found to be more abundant in ovary and hypothalamus, respectively. The observed GC content was representative for different classes of ncRNAs, allowing the identification of a tRNA-derived RNA fragments (tRFs) subclass, which had a peak distribution around 32–38% GC content in the hypothalamus. Differences observed among organs confirmed the specificity of microRNA (miRNA) profiles for each organ system.

Conclusions

Data on ncRNAs in organs constituting the HPG axis will contribute to understanding their role in the physiological regulation of reproduction in goats.

Electronic supplementary material

The online version of this article (10.1186/s12864-018-4767-x) contains supplementary material, which is available to authorized users.

A compilation of Web-based research tools for miRNA analysis

Since the discovery of microRNAs (miRNAs), a class of noncoding RNAs that regulate the gene expression posttranscriptionally in sequence-specific manner, there has been a release of number of tools useful for both basic and advanced applications. This is because of the significance of miRNAs in many pathophysiological conditions including cancer. Numerous bioinformatics tools that have been developed for miRNA analysis have their utility for detection, expression, function, target prediction and many other related features. This review provides a comprehensive assessment of web-based tools for the miRNA analysis that does not require prior knowledge of any computing languages.

m6ASNP: a tool for annotating genetic variants by m6A function

Background

Large-scale genome sequencing projects have identified many genetic variants for diverse diseases. A major goal of these projects is to characterize these genetic variants to provide insight into their function and roles in diseases. N6-methyladenosine (m6A) is one of the most abundant RNA modifications in eukaryotes. Recent studies have revealed that aberrant m6A modifications are involved in many diseases.

Findings

In this study, we present a user-friendly web server called "m6ASNP" that is dedicated to the identification of genetic variants that target m6A modification sites. A random forest model was implemented in m6ASNP to predict whether the methylation status of an m6A site is altered by the variants that surround the site. In m6ASNP, genetic variants in a standard variant call format (VCF) are accepted as the input data, and the output includes an interactive table that contains the genetic variants annotated by m6A function. In addition, statistical diagrams and a genome browser are provided to visualize the characteristics and to annotate the genetic variants.

Conclusions

We believe that m6ASNP is a very convenient tool that can be used to boost further functional studies investigating genetic variants. The web server "m6ASNP" is implemented in JAVA and PHP and is freely available at [60].

Characterization of mouse serum exosomal small RNA content: The origins and their roles in modulating inflammatory response

In the last decade, although studies on exosomal microRNAs (miRNAs) derived from serum and other body fluids have increased dramatically; the contents and biological significance of serum exosomes under normal conditions remain unclear. In the present study, we profiled the small RNA content of mouse serum exosomes (mSEs) using small RNAseq and found that fragments of transfer RNAs (tRNAs) and miRNAs were the two predominant exosomal RNA species, accounting for approximately 60% and 10% of mapped reads, respectively. Moreover, 466 known and 5 novel miRNAs were identified from two independent experiments, among which the five most abundant miRNAs (miR-486a-5p, miR-22-3p, miR-16-5p, miR-10b-5p and miR-27b-3p) accounted for approximately 60% of all the aligned miRNA sequences. As inferred from the identities of the well known cell- or tissue-specific miRNAs, mSEs were primarily released by RBCs, liver and intestinal cells. Bioinformatics analysis revealed over half of the top 20 miRNAs by abundance were involved in inflammatory responses and further in vitro experiments demonstrated that mSEs potently primed macrophages towards the M2 phenotype. To the best of our knowledge, this is the first study to profile small RNAs from mSEs. In addition to providing a reference for future biomarker studies and extrapolating their origins, our data also suggest the roles of mSEs in maintaining internal homeostasis under normal conditions.

miRmine: a database of human miRNA expression profiles

Motivation

MicroRNAs (miRNAs) are small non-coding RNAs that are involved in post-transcriptional regulation of gene expression. In this high-throughput sequencing era, a tremendous amount of RNA-seq data is accumulating, and full utilization of publicly available miRNA data is an important challenge. These data are useful to determine expression values for each miRNA, but quantification pipelines are in a primitive stage and still evolving; there are many factors that affect expression values significantly.

Results

We used 304 high-quality microRNA sequencing (miRNA-seq) datasets from NCBI-SRA and calculated expression profiles for different tissues and cell-lines. In each miRNA-seq dataset, we found an average of more than 500 miRNAs with higher than 5x coverage, and we explored the top five highly expressed miRNAs in each tissue and cell-line. This user-friendly miRmine database has options to retrieve expression profiles of single or multiple miRNAs for a specific tissue or cell-line, either normal or with disease information. Results can be displayed in multiple interactive, graphical and downloadable formats.

Availability and Implementation

http://guanlab.ccmb.med.umich.edu/mirmine.

Contact

bharatpa@umich.edu.

Supplementary information

Supplementary data are available at Bioinformatics online.