S-Adenosylmethionine Treatment Diminishes the Proliferation of Castration-Resistant Prostate Cancer Cells by Modulating the Expression of miRNAs

AdoMet (S-adenosylmethionine) inhibits cancer cell proliferation and migration via epigenetic alterations. This study aimed to investigate whether AdoMet may cause alterations in microRNA (miRNA) expression profiles that are important for the initiation and progression of prostate cancer. PC-3 cells were treated with AdoMet before miRNA sequencing. A total of 17 differentially expressed miRNAs were detected. Target gene prediction was performed by means of databases. Results were aligned to transcriptomic data. The bioinformatic analysis revealed upregulation of anticancerogenic genes, downregulation of cancerogenic-related processes and pathways. Knocking down hsa-miR-192-5p in PC-3 cells resulted in downregulation of cancer cell proliferation, thus confirming these results.

The Tumor-Associated Calcium Signal Transducer 2 (TACSTD2) oncogene is upregulated in pre-cystic epithelial cells revealing a new target for polycystic kidney disease

Polycystic kidney disease (PKD) is an important cause of end stage renal disease, but treatment options are limited. While later stages of the disease have been extensively studied, mechanisms driving the initial conversion of renal tubules into cysts are not understood. To identify factors that promote the initiation of cysts we deleted polycystin-2 ( Pkd2 ) in mice and surveyed transcriptional changes before and immediately after cysts developed. We identified 74 genes which we term cyst initiation candidates (CICs). To identify conserved changes with relevance to human disease we compared these murine CICs to single cell transcriptomic data derived from patients with PKD and from healthy controls. Tumor-associated calcium signal transducer 2 ( Tacstd2 ) stood out as an epithelial-expressed gene whose levels were elevated prior to cystic transformation and further increased with disease progression. Human tissue biopsies and organoids show that TACSTD2 protein is low in normal kidney cells but is elevated in cyst lining cells. While TACSTD2 has not been studied in PKD, it has been studied in cancer where it is highly expressed in solid tumors while showing minimal expression in normal tissue. This property is being exploited by antibody drug conjugates that target TACSTD2 for the delivery of cytotoxic drugs. Our finding that Tacstd2 is highly expressed in cysts, but not normal tissue, suggests that it should be explored as a candidate for drug development in PKD. More immediately, our work suggests that PKD patients undergoing TACSTD2 treatment for cancer should be monitored for kidney effects.

One Sentence Summary

The oncogene, tumor-associated calcium signal transducer 2 (Tacstd2) mRNA increased in abundance shortly after Pkd2 loss and may be a driver of cyst initiation in polycystic kidney disease.

Circulating microRNAs predict recurrence and death following venous thromboembolism

BACKGROUND

Recurrent events frequently occur after venous thromboembolism (VTE) and remain difficult to predict based on established genetic, clinical, and proteomic contributors. The role of circulating microRNAs (miRNAs) has yet to be explored in detail.

OBJECTIVES

To identify circulating miRNAs predictive of recurrent VTE or death, and to interpret their mechanistic involvement.

METHODS

Data from 181 participants of a cohort study of acute VTE and 302 individuals with a history of VTE from a population-based cohort were investigated. Next-generation sequencing was performed on EDTA plasma samples to detect circulating miRNAs. The endpoint of interest was recurrent VTE or death. Penalized regression was applied to identify an outcome-relevant miRNA signature, and results were validated in the population-based cohort. The involvement of miRNAs in coregulatory networks was assessed using principal component analysis, and the associated clinical and molecular phenotypes were investigated. Mechanistic insights were obtained from target gene and pathway enrichment analyses.

RESULTS

A total of 1950 miRNAs were detected across cohorts after postprocessing. In the discovery cohort, 50 miRNAs were associated with recurrent VTE or death (cross-validated C-index, 0.65). A weighted miRNA score predicted outcome over an 8-year follow-up period (HRSD, 2.39; 95% CI, 1.98-2.88; P < .0001). The independent validation cohort validated 20 miRNAs (ORSD for score, 3.47; 95% CI, 2.37-5.07; P < .0001; cross-validated-area under the curve, 0.61). Principal component analysis revealed 5 miRNA networks with distinct relationships to clinical phenotype and outcome. Mapping of target genes indicated regulation via transcription factors and kinases involved in signaling pathways associated with fibrinolysis.

CONCLUSION

Circulating miRNAs predicted the risk of recurrence or death after VTE over several years, both in the acute and chronic phases.

Modulation of microRNA processing by 5-lipoxygenase

The miRNA biogenesis is tightly regulated to avoid dysfunction and consequent disease development. Here, we describe modulation of miRNA processing as a novel noncanonical function of the 5-lipoxygenase (5-LO) enzyme in monocytic cells. In differentiated Mono Mac 6 (MM6) cells, we found an in situ interaction of 5-LO with Dicer, a key enzyme in miRNA biogenesis. RNA sequencing of small noncoding RNAs revealed a functional impact, knockout of 5-LO altered the expression profile of several miRNAs. Effects of 5-LO could be observed at two levels. qPCR analyses thus indicated that (a) 5-LO promotes the transcription of the evolutionarily conserved miR-99b/let-7e/miR-125a cluster and (b) the 5-LO-Dicer interaction downregulates the processing of pre-let-7e, resulting in an increase in miR-125a and miR-99b levels by 5-LO without concomitant changes in let-7e levels in differentiated MM6 cells. Our observations suggest that 5-LO regulates the miRNA profile by modulating the Dicer-mediated processing of distinct pre-miRNAs. 5-LO inhibits the formation of let-7e which is a well-known inducer of cell differentiation, but promotes the generation of miR-99b and miR-125a known to induce cell proliferation and the maintenance of leukemic stem cell functions.

Principles and innovative technologies for decrypting noncoding RNAs: from discovery and functional prediction to clinical application

Noncoding RNAs (ncRNAs) are a large segment of the transcriptome that do not have apparent protein-coding roles, but they have been verified to play important roles in diverse biological processes, including disease pathogenesis. With the development of innovative technologies, an increasing number of novel ncRNAs have been uncovered; information about their prominent tissue-specific expression patterns, various interaction networks, and subcellular locations will undoubtedly enhance our understanding of their potential functions. Here, we summarized the principles and innovative methods for identifications of novel ncRNAs that have potential functional roles in cancer biology. Moreover, this review also provides alternative ncRNA databases based on high-throughput sequencing or experimental validation, and it briefly describes the current strategy for the clinical translation of cancer-associated ncRNAs to be used in diagnosis.

Epigenetics in non-classical monocytes support their pro-inflammatory gene expression

Non-classical human monocytes are characterized by high-level expression of cytokines like TNF, but the mechanisms involved are elusive. We have identified miRNAs and CpG-methylation sites that are unique to non-classical monocytes, defined via CD14 and CD16 expression levels. For down-regulated miRNAs that are linked to up-regulated mRNAs the dominant gene ontology term was intracellular signal transduction. This included down-regulated miRNA-20a-5p and miRNA-106b-5p, which both are linked to increased mRNA for the TRIM8 signaling molecule. Methylation analysis revealed 16 hypo-methylated CpG sites upstream of 14 differentially increased mRNAs including 2 sites upstream of TRIM8. Consistent with a positive role in signal transduction, high TRIM8 levels went along with high basal TNF mRNA levels in non-classical monocytes. Since cytokine expression levels in monocytes strongly increase after stimulation with toll-like-receptor ligands, we have analyzed non-classical monocytes (defined via slan expression) after stimulation with lipopolysaccharide (LPS). LPS-stimulated cells continued to have low miRNA-20a and miRNA-106b and high TRIM8 mRNA levels and they showed a 10-fold increase in TNF mRNA. These data suggest that decreased miRNAs and CpG hypo-methylation is linked to enhanced expression of TRIM8 and that this can contribute to the increased TNF levels in non-classical human monocytes.

Computational tools for plant small RNA detection and categorization

Small RNAs (sRNAs) are important short-length molecules with regulatory functions essential for plant development and plasticity. High-throughput sequencing of total sRNA populations has revealed that the largest share of sRNA remains uncategorized. To better understand the role of sRNA-mediated cellular regulation, it is necessary to create accurate and comprehensive catalogues of sRNA and their sequence features, a task that currently relies on nontrivial bioinformatic approaches. Although a large number of computational tools have been developed to predict features of sRNA sequences, these tools are mostly dedicated to microRNAs and none integrates the functionalities necessary to describe units from all sRNA pathways thus far discovered in plants. Here, we review the different classes of sRNA found in plants and describe available bioinformatics tools that can help in their detection and categorization.

Response Assessment With Molecular Characterization of Circulating Tumor Cells and Plasma MicroRNA Profiling in Patients With Locally Advanced Breast Cancer During Neoadjuvant Chemotherapy

BACKGROUND

Cells detaching from the primary tumor site are metastasis initiator cells, and the detection of CTC, known as liquid biopsy, is an important test of biomarkers of cancer progression. We investigated the molecular characterization of circulating tumor cells (CTCs), profiled the plasma microRNA (miR) content, and analyzed the relationship with the clinical outcomes by sampling the peripheral blood from patients with locally advanced breast cancer before and after neoadjuvant chemotherapy.

PATIENTS AND METHODS

Markers of breast cancer, epithelial-mesenchymal transition (EMT), drug resistance, and stem cells were used for CTC isolation and characterization. Plasma miR profiles were obtained from selected patients with CTC positivity determined using next-generation sequencing.

RESULTS

The proportion of CTC, EMT, and stem cell marker positivity was 16.7%, 8.3%, and 25% before and 18.2%, 15.2%, and 9.1% after treatment, respectively. A significant correlation was found between the pretreatment CTCs and ALDH1 positivity (P = .0245). These CTCs with stemness properties were observed in most hormone receptor-positive, human epidermal growth factor receptor 2-negative cases and were also present with a high incidence in cases of early metastasis. miR-146b-5p and miR-199a-5p, which are involved in metastasis, invasion, and EMT, were accompanied by CTC positivity, and miR-4646-3p was associated with the development of early metastasis.

CONCLUSIONS

Molecular characterization of CTCs and miR profiling of serial samples from patients with locally advanced breast cancer during neoadjuvant chemotherapy appears to be a very useful in predicting cure and clinical course and might be a key to developing new targeted therapies.

Non-Invasive Approach for Evaluation of Pulmonary Hypertension Using Extracellular Vesicle-Associated Small Non-Coding RNA

Extracellular vesicles are released by numerous cell types of the human body under physiological but also under pathophysiological conditions. They are important for cell–cell communication and carry specific signatures of peptides and RNAs. In this study, we aimed to determine whether extracellular vesicles isolated from patients with pulmonary hypertension show a disease specific signature of small non-coding RNAs and thus have the potential to serve as diagnostic and prognostic biomarkers. Extracellular vesicles were isolated from the serum of 23 patients with chronic thromboembolic pulmonary hypertension (CTEPH) and 23 controls using two individual methods: a column-based method or by precipitation. Extracellular vesicle- associated RNAs were analyzed by next-generation sequencing applying molecular barcoding, and differentially expressed small non-coding RNAs were validated by quantitative real-time polymerase chain reaction (qRT-PCR). We identified 18 microRNAs and 21 P-element induced wimpy testis (PIWI)-interacting RNAs (piRNAs) or piRNA clusters that were differentially expressed in CTEPH patients compared with controls. Bioinformatic analysis predicted a contribution of these piRNAs to the progression of cardiac and vascular remodeling. Expression levels of DQ593039 correlated with clinically meaningful parameters such as mean pulmonary arterial pressure, pulmonary vascular resistance, right ventricular systolic pressure, and levels of N-terminal pro-brain natriuretic peptide. Thus, we identified the extracellular vesicle- derived piRNA, DQ593039, as a potential biomarker for pulmonary hypertension and right heart disease.

Computational Resources for Prediction and Analysis of Functional miRNA and Their Targetome

microRNAs are evolutionarily conserved, endogenously produced, noncoding RNAs (ncRNAs) of approximately 19-24 nucleotides (nts) in length known to exhibit gene silencing of complementary target sequence. Their deregulated expression is reported in various disease conditions and thus has therapeutic implications. In the last decade, various computational resources are published in this field. In this chapter, we have reviewed bioinformatics resources, i.e., miRNA-centered databases, algorithms, and tools to predict miRNA targets. First section has enlisted more than 75 databases, which mainly covers information regarding miRNA registries, targets, disease associations, differential expression, interactions with other noncoding RNAs, and all-in-one resources. In the algorithms section, we have compiled about 140 algorithms from eight subcategories, viz. for the prediction of precursor (pre-) and mature miRNAs. These algorithms are developed on various sequence, structure, and thermodynamic based features incorporated into different machine learning techniques (MLTs). In addition, computational identification of miRNAs from high-throughput next generation sequencing (NGS) data and their variants, viz. isomiRs, differential expression, miR-SNPs, and functional annotation, are discussed. Prediction and analysis of miRNAs and their associated targets are also evaluated under miR-targets section providing knowledge regarding novel miRNA targets and complex host-pathogen interactions. In conclusion, we have provided comprehensive review of in silico resources published in miRNA research to help scientific community be updated and choose the appropriate tool according to their needs.

Identifying Exosome-Derived MicroRNAs as Candidate Biomarkers of Frailty

Frailty is a geriatric syndrome associated with progressive physical decline and significantly increases risk for falls, disability, hospitalizations, and death. However, much remains unknown regarding the biological mechanisms that contribute to aging and frailty, and to date, there are no clinically used prognostic or diagnostic molecular biomarkers. The present study profiled exosome-derived microRNAs isolated from the plasma of young, robust older, and frail older individuals and identified eight miRNAs that are uniquely enriched in frailty: miR-10a-3p, miR-92a-3p, miR-185-3p, miR-194-5p, miR-326, miR-532-5p, miR-576-5p, and miR-760. Furthermore, since exosomes can deliver miRNAs to alter cellular activity and behavior, these miRNAs may also provide insights into the biological mechanisms underlying frailty; KEGG analysis of their target genes revealed multiple pathways implicated in aging and age-related processes. Although further validation and research studies are warranted, our study identified eight novel candidate biomarkers of frailty that may help to elucidate the multifactorial pathogenesis of frailty.

MALAT1 regulates the transcriptional and translational levels of proto-oncogene RUNX2 in colorectal cancer metastasis

Ectopic expression of lncRNA-MALAT1 has been discovered in recurrent colorectal cancer (CRC) and metastatic sites in postsurgical patients, however, its biological mechanism remained unelucidated. Our study first revealed the novel roles of MALAT1 in promoting CRC metastasis through two mechanisms: first, MALAT1 binds miR-15 family members, to “de-inhibit” their effect on LRP6 expression, enhances β-catenin signaling, leading to elevated transcriptional levels of downstream target genes RUNX2. Second, MALAT1 binds SFPQ, and dissociates SFPQ/PTBP2 dimer to release free PTBP2, which elevates translational levels of RUNX2, through interacting with IRES domain in the 5′UTR of the corresponding RUNX2 mRNAs. Moreover, increased RUNX2 expression levels were detected in recurrent CRC tumors, which were closely associated with TMN stages, metastasis, as well as CRC patients’ survival. Our study demonstrated that MALAT1 and RUNX2 may serve as two biomarkers for predicting the recurrence and metastasis of CRC patients.

TEsmall Identifies Small RNAs Associated With Targeted Inhibitor Resistance in Melanoma

MicroRNAs (miRNAs) are small 21–22 nt RNAs that act to regulate the expression of mRNA target genes through direct binding to mRNA targets. While miRNAs typically dominate small RNA (sRNA) transcriptomes, many other classes are present including tRNAs, snoRNAs, snRNAs, Y-RNAs, piRNAs, and siRNAs. Interactions between processing machinery and targeting networks of these various sRNA classes remains unclear, largely because these sRNAs are typically analyzed separately. Here, we present TEsmall, a tool that allows for the simultaneous processing and analysis of sRNAs from each annotated class in a single integrated workflow. The pipeline begins with raw fastq reads and proceeds all the way to producing count tables formatted for differential expression analysis. Several interactive charts are also produced to look at overall distributions in length and annotation classes. We next applied the TEsmall pipeline to sRNA libraries generated from melanoma cells responding to targeted inhibitors of the MAPK pathway. Targeted oncogene inhibitors have emerged as way to tailor cancer therapies to the particular mutations present in a given tumor. While these targeted strategies are typically effective for short intervals, the emergence of resistance is extremely common, limiting the effectiveness of single-agent therapeutics and driving the need for a better understanding of resistance mechanisms. Using TEsmall, we identified several microRNAs and other sRNA classes that are enriched in inhibitor resistant melanoma cells in multiple melanoma cell lines and may be able to serve as markers of resistant populations more generally.

Plasma small ncRNA pair panels as novel biomarkers for early-stage lung adenocarcinoma screening

Background

Lung cancer is a major cause of cancer-related mortality worldwide, and around two-thirds of patients have metastasis at diagnosis. Thus, detecting lung cancer at an early stage could reduce mortality. Aberrant levels of circulating small non-coding RNAs (small ncRNAs) are potential diagnostic or prognostic markers for lung cancer. We aimed to identify plasma small ncRNA pairs that could be used for early screening and detection of lung adenocarcinoma (LAC).

Results

A panel of seven small ncRNA pair ratios could differentiate patients with LAC or benign lung disease from high-risk controls with an area under the curve (AUC) of 100.0%, a sensitivity of 100.0% and a specificity of 100.0% at the training stage (which included 50 patients with early-stage LAC, 35 patients with benign diseases and 29 high-risk controls) and an AUC of 90.2%, a sensitivity of 91.5% and a specificity of 80.4% at the validation stage (which included 44 patients with early-stage LAC, 32 patients with benign diseases and 51 high-risk controls). The same panel could distinguish LAC from high-risk controls with an AUC of 100.0%, a sensitivity of 100.0% and a specificity of 100.0% at the training stage and an AUC of 89.5%, a sensitivity of 85.4% and a specificity of 83.3% at the validation stage. Another panel of five small ncRNA pair ratios (different from the first) was able to differentiate LAC from benign disease with an AUC of 82.0%, a sensitivity of 81.1% and a specificity of 78.1% in the training cohort and an AUC of 74.2%, a sensitivity of 70.4% and a specificity of 72.7% in the validation cohort.

Conclusions

Several small ncRNA pair ratios were identified as markers capable of discerning patients with LAC from those with benign lesions or high-risk control individuals.

Electronic supplementary material

The online version of this article (10.1186/s12864-018-4862-z) 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.

A comprehensive review of web-based resources of non-coding RNAs for plant science research

Non-coding RNAs (ncRNAs) are transcribed from genome but not translated into proteins. Many ncRNAs are key regulators of plants growth and development, metabolism and stress tolerance. In order to make the web-based ncRNA resources for plant science research be more easily accessible and understandable, we made a comprehensive review for 83 web-based resources of three types, including genome databases containing ncRNA data, microRNA (miRNA) databases and long non-coding RNA (lncRNA) databases. To facilitate effective usage of these resources, we also suggested some preferred resources of miRNAs and lncRNAs for performing meaningful analysis.

miR-MaGiC improves quantification accuracy for small RNA-seq

Objective

Many tools have been developed to profile microRNA (miRNA) expression from small RNA-seq data. These tools must contend with several issues: the small size of miRNAs, the small number of unique miRNAs, the fact that similar miRNAs can be transcribed from multiple loci, and the presence of miRNA isoforms known as isomiRs. Methods failing to address these issues can return misleading information. We propose a novel quantification method designed to address these concerns.

Results

We present miR-MaGiC, a novel miRNA quantification method, implemented as a cross-platform tool in Java. miR-MaGiC performs stringent mapping to a core region of each miRNA and defines a meaningful set of target miRNA sequences by collapsing the miRNA space to “functional groups”. We hypothesize that these two features, mapping stringency and collapsing, provide more optimal quantification to a more meaningful unit (i.e., miRNA family). We test miR-MaGiC and several published methods on 210 small RNA-seq libraries, evaluating each method’s ability to accurately reflect global miRNA expression profiles. We define accuracy as total counts close to the total number of input reads originating from miRNAs. We find that miR-MaGiC, which incorporates both stringency and collapsing, provides the most accurate counts.

Electronic supplementary material

The online version of this article (10.1186/s13104-018-3418-2) contains supplementary material, which is available to authorized users.

miRDis: a Web tool for endogenous and exogenous microRNA discovery based on deep-sequencing data analysis

Small RNA sequencing is the most widely used tool for microRNA (miRNA) discovery, and shows great potential for the efficient study of miRNA cross-species transport, i.e., by detecting the presence of exogenous miRNA sequences in the host species. Because of the increased appreciation of dietary miRNAs and their far-reaching implication in human health, research interests are currently growing with regard to exogenous miRNAs bioavailability, mechanisms of cross-species transport and miRNA function in cellular biological processes. In this article, we present microRNA Discovery (miRDis), a new small RNA sequencing data analysis pipeline for both endogenous and exogenous miRNA detection. Specifically, we developed and deployed a Web service that supports the annotation and expression profiling data of known host miRNAs and the detection of novel miRNAs, other noncoding RNAs, and the exogenous miRNAs from dietary species. As a proof-of-concept, we analyzed a set of human plasma sequencing data from a milk-feeding study where 225 human miRNAs were detected in the plasma samples and 44 show elevated expression after milk intake. By examining the bovine-specific sequences, data indicate that three bovine miRNAs (bta-miR-378, -181* and -150) are present in human plasma possibly because of the dietary uptake. Further evaluation based on different sets of public data demonstrates that miRDis outperforms other state-of-the-art tools in both detection and quantification of miRNA from either animal or plant sources. The miRDis Web server is available at: http://sbbi.unl.edu/miRDis/index.php.

Classification of miRNA-related sequence variations

miRNA regulome is whole set of regulatory elements that regulate miRNA expression or are under control of miRNAs. Its understanding is vital for comprehension of miRNA functions. Classification of miRNA-related genetic variability is challenging because miRNA interact with different genomic elements and are studied at different omics levels. In the present study, miRNA-associated genetic variability is presented at three levels: miRNA genes and their upstream regulation, miRNA silencing machinery and miRNA targets. Several types of miRNA-associated genetic variations are known, including short and structural polymorphisms and epimutations. Differential expression can also affect miRNA regulome function. Classification of miRNA-associated genetic variability presents a baseline for complementing sequence variant nomenclature, planning of experiments, protocols for multi-omics data integration and development of biomarkers.

Oasis 2: improved online analysis of small RNA-seq data

Background

Small RNA molecules play important roles in many biological processes and their dysregulation or dysfunction can cause disease. The current method of choice for genome-wide sRNA expression profiling is deep sequencing.

Results

Here we present Oasis 2, which is a new main release of the Oasis web application for the detection, differential expression, and classification of small RNAs in deep sequencing data. Compared to its predecessor Oasis, Oasis 2 features a novel and speed-optimized sRNA detection module that supports the identification of small RNAs in any organism with higher accuracy. Next to the improved detection of small RNAs in a target organism, the software now also recognizes potential cross-species miRNAs and viral and bacterial sRNAs in infected samples. In addition, novel miRNAs can now be queried and visualized interactively, providing essential information for over 700 high-quality miRNA predictions across 14 organisms. Robust biomarker signatures can now be obtained using the novel enhanced classification module.

Conclusions

Oasis 2 enables biologists and medical researchers to rapidly analyze and query small RNA deep sequencing data with improved precision, recall, and speed, in an interactive and user-friendly environment.

Availability and Implementation

Oasis 2 is implemented in Java, J2EE, mysql, Python, R, PHP and JavaScript. It is freely available at https://oasis.dzne.de

Electronic supplementary material

The online version of this article (10.1186/s12859-018-2047-z) contains supplementary material, which is available to authorized users.

Post-transcriptional gene silencing mediated by microRNAs is controlled by nucleoplasmic Sfpq

There is a growing body of evidence about the presence and the activity of the miRISC in the nucleus of mammalian cells. Here, we show by quantitative proteomic analysis that Ago2 interacts with the nucleoplasmic protein Sfpq in an RNA-dependent fashion. By a combination of HITS-CLIP and transcriptomic analyses, we demonstrate that Sfpq directly controls the miRNA targeting of a subset of binding sites by local binding. Sfpq modulates miRNA targeting in both nucleoplasm and cytoplasm, indicating a nucleoplasmic commitment of Sfpq-target mRNAs that globally influences miRNA modes of action. Mechanistically, Sfpq binds to a sizeable set of long 3′UTRs forming aggregates to optimize miRNA positioning/recruitment at selected binding sites, including let-7a binding to Lin28A 3′UTR. Our results extend the miRNA-mediated post-transcriptional gene silencing into the nucleoplasm and indicate that an Sfpq-dependent strategy for controlling miRNA activity takes place in cells, contributing to the complexity of miRNA-dependent gene expression control.

MicroRNAs have been best characterized for their functions in the cytoplasm; however, there is growing evidence of a nuclear localized role. Here, the authors identify Sfpq as an Ago2-interacting protein that modulates miRNA activity in both the nucleus and cytoplasm.

From benchmarking HITS-CLIP peak detection programs to a new method for identification of miRNA-binding sites from Ago2-CLIP data

Experimental evidence indicates that about 60% of miRNA-binding activity does not follow the canonical rule about the seed matching between miRNA and target mRNAs, but rather a non-canonical miRNA targeting activity outside the seed or with a seed-like motifs. Here, we propose a new unbiased method to identify canonical and non-canonical miRNA-binding sites from peaks identified by Ago2 Cross-Linked ImmunoPrecipitation associated to high-throughput sequencing (CLIP-seq). Since the quality of peaks is of pivotal importance for the final output of the proposed method, we provide a comprehensive benchmarking of four peak detection programs, namely CIMS, PIPE-CLIP, Piranha and Pyicoclip, on four publicly available Ago2-HITS-CLIP datasets and one unpublished in-house Ago2-dataset in stem cells. We measured the sensitivity, the specificity and the position accuracy toward miRNA binding sites identification, and the agreement with TargetScan. Secondly, we developed a new pipeline, called miRBShunter, to identify canonical and non-canonical miRNA-binding sites based on de novo motif identification from Ago2 peaks and prediction of miRNA::RNA heteroduplexes. miRBShunter was tested and experimentally validated on the in-house Ago2-dataset and on an Ago2-PAR-CLIP dataset in human stem cells. Overall, we provide guidelines to choose a suitable peak detection program and a new method for miRNA-target identification.

Profiling of cellular microRNA responses during the early stages of KSHV infection

Kaposi's sarcoma-associated herpesvirus (KSHV) causes a variety of cancers, including Kaposi's sarcoma (KS), primary effusion lymphoma (PEL), and multicentric Castleman disease (MCD). Host cellular microRNAs (miRNAs) play important post-transcriptional regulatory roles in gene expression and can greatly influence virus-host cell interactions. This study investigated cellular miRNA expression profiles operating in response to early stages of KSHV infection of human Burkitt lymphoma B cells (BJAB). We employed deep sequencing to analyze miRNA expression in KSHV-infected BJAB cells 15 min post infection (PI) and compared this to uninfected BJAB cells. A total of 32 known miRNAs and 28 novel miRNA candidates were differentially expressed in KSHV-infected compared to uninfected BJAB cells. Interestingly, miRNA expression profiles during the early stages of viral infection yielded comparable results when UV-inactivated KSHV was used. The deep sequencing results were further confirmed by performing real-time reverse transcription PCR. The target genes predicted to be regulated by both the known and novel miRNAs are mainly involved in assisting virus entry, inducing critical cell signaling, initiating transcription of immediate early genes, promoting latent infection, and modulating the host immune response. For the first time, we provide insight into the host cellular miRNA expression profiles in response to early stages of KSHV infection of human B cells. Furthermore, this study offers a valuable basis for further investigation on the roles of cellular miRNAs in the KSHV entry process.

Comprehensive processing of high-throughput small RNA sequencing data including quality checking, normalization, and differential expression analysis using the UEA sRNA Workbench

Recently, high-throughput sequencing (HTS) has revealed compelling details about the small RNA (sRNA) population in eukaryotes. These 20 to 25 nt noncoding RNAs can influence gene expression by acting as guides for the sequence-specific regulatory mechanism known as RNA silencing. The increase in sequencing depth and number of samples per project enables a better understanding of the role sRNAs play by facilitating the study of expression patterns. However, the intricacy of the biological hypotheses coupled with a lack of appropriate tools often leads to inadequate mining of the available data and thus, an incomplete description of the biological mechanisms involved. To enable a comprehensive study of differential expression in sRNA data sets, we present a new interactive pipeline that guides researchers through the various stages of data preprocessing and analysis. This includes various tools, some of which we specifically developed for sRNA analysis, for quality checking and normalization of sRNA samples as well as tools for the detection of differentially expressed sRNAs and identification of the resulting expression patterns. The pipeline is available within the UEA sRNA Workbench, a user-friendly software package for the processing of sRNA data sets. We demonstrate the use of the pipeline on a H. sapiens data set; additional examples on a B. terrestris data set and on an A. thaliana data set are described in the Supplemental Information A comparison with existing approaches is also included, which exemplifies some of the issues that need to be addressed for sRNA analysis and how the new pipeline may be used to do this.

Reprint of: MicroRNA profiling of human intermediate monocytes

Among the three human monocyte subsets, intermediate CD14++CD16+ monocytes have been characterized as particularly proinflammatory cells in experimental studies and as potential biomarkers of cardiovascular risk in clinical cohorts. To further substantiate the distinct role of intermediate monocytes within human monocyte heterogeneity, we assessed subset-specific expression of miRNAs as central epigenetic regulators of gene expression. We hypothesized that intermediate monocytes have a distinct miRNA profile compared to classical and non-classical monocytes. By using small RNA-seq we analyzed 662 miRNAs in the three monocyte subsets. We identified 38 miRNAs that are differentially expressed in intermediate monocytes compared to both classical and non-classical monocytes with a p value of <10^-10, of which two miRNAs - miR-6087 (upregulated) and miR-150-5p (downregulated) - differed in their expression more than ten-fold. Pathway analysis of the 38 differentially expressed miRNAs linked intermediate monocytes to distinct biological processes such as gene regulation, cell differentiation, toll-like receptor signaling as well as antigen processing and presentation. Moreover, differentially expressed miRNAs were connected to those genes that we previously identified as markers of intermediate monocytes. In aggregation, we provide first genome-wide miRNA data in the context of monocyte heterogeneity, which substantiate the concept of monocyte trichotomy in human immunity. The identification of miRNAs that are specific for intermediate monocytes may allow to develop strategies, which particularly target this cell population while sparing the other two subsets.

Regulatory crosstalk between microRNAs and hormone signalling cascades controls the variation on seed dormancy phenotype at Arabidopsis thaliana seed set

We employed an Illumina sequencing approach to identify candidate microRNA cohorts that may greatly contribute to seed dormancy modulation and to construct a microRNA-gene regulatory network in hormone signalling cascades. MicroRNAs (miRNAs) are important signalling molecules and regulate many developmental programs of plants. Some miRNAs have been integrated into gene regulatory networks (GRNs) and coordinate developmental plasticity, but few study systematically investigated how phenotypical variations are regulated through differential expression of miRNA tags in GRNs during seed set. Using 'top-down' analyses (i.e., identify miRNAs associated with known phenotypical variations), we chose two Arabidopsis ecotypes (Cvi-0 and Col-0) with contrasting seed dormancy and sequenced miRNA reads in the first ten phases at seed set. We computationally predicted target genes of miRNAs and implemented statistical analyses for normalized relative expression of top abundant miRNA cohorts between the two ecotypes. We especially focused on miRNA cohorts targeting mRNAs encoding transcription factors in hormone signalling cascades. We report, with high confidence hits, that a cohort of 14 miRNAs (miR-156b, -159b, -160, -161*, -319a, -390a, -396, -773a, -779, -842, -852, -859, -1886*, and a novel sequence in miR8172 family) may greatly contribute to seed dormancy modulation, of which seven are involved in hormone signalling cascades. Moreover, their expression patterns indicated that 5 ± 1 days after flowering (at embryogenesis-to-maturation transition) is a critical phase at seed set. This study reinforces the notion that miRNAs that regulate seed dormancy modulation and provides a novel paradigm of studying the correlation between genotypes (miRNAs) and phenotypes.

Nutrition, microRNAs, and Human Health

MicroRNAs (miRs) hybridize with complementary sequences in mRNA and silence genes by destabilizing mRNA or preventing translation of mRNA. Over 60% of human protein-coding genes are regulated by miRs, and 1881 high-confidence miRs are encoded in the human genome. Evidence suggests that miRs not only are synthesized endogenously, but also might be obtained from dietary sources, and that food compounds alter the expression of endogenous miR genes. The main food matrices for studies of biological activity of dietary miRs include plant foods and cow milk. Encapsulation of miRs in exosomes and exosome-like particles confers protection against RNA degradation and creates a pathway for intestinal and vascular endothelial transport by endocytosis, as well as delivery to peripheral tissues. Evidence suggests that the amount of miRs absorbed from nutritionally relevant quantities of foods is sufficient to elicit biological effects, and that endogenous synthesis of miRs is insufficient to compensate for dietary miR depletion and rescue wild-type phenotypes. In addition, nutrition alters the expression of endogenous miR genes, thereby compounding the effects of nutrition-miR interactions in gene regulation and disease diagnosis in liquid biopsies. For example, food components and dietary preferences may modulate serum miR profiles that may influence biological processes. The complex crosstalk between nutrition, miRs, and gene targets poses a challenge to gene network analysis and studies of human disease. Novel pipelines and databases have been developed recently, including a dietary miR database for archiving reported miRs in 15 dietary resources. miRs derived from diet and endogenous synthesis have been implicated in physiologic and pathologic conditions, including those linked with nutrition and metabolism. In fact, several miRs are actively regulated in response to overnutrition and tissue inflammation, and are involved in facilitating the development of chronic inflammation by modulating tissue-infiltrated immune cell function.

Integrating Epigenomics into the Understanding of Biomedical Insight

Epigenetics is one of the most rapidly expanding fields in biomedical research, and the popularity of the high-throughput next-generation sequencing (NGS) highlights the accelerating speed of epigenomics discovery over the past decade. Epigenetics studies the heritable phenotypes resulting from chromatin changes but without alteration on DNA sequence. Epigenetic factors and their interactive network regulate almost all of the fundamental biological procedures, and incorrect epigenetic information may lead to complex diseases. A comprehensive understanding of epigenetic mechanisms, their interactions, and alterations in health and diseases genome widely has become a priority in biological research. Bioinformatics is expected to make a remarkable contribution for this purpose, especially in processing and interpreting the large-scale NGS datasets. In this review, we introduce the epigenetics pioneering achievements in health status and complex diseases; next, we give a systematic review of the epigenomics data generation, summarize public resources and integrative analysis approaches, and finally outline the challenges and future directions in computational epigenomics.

MicroRNA profiling of human intermediate monocytes

Among the three human monocyte subsets, intermediate CD14++CD16+ monocytes have been characterized as particularly proinflammatory cells in experimental studies and as potential biomarkers of cardiovascular risk in clinical cohorts. To further substantiate the distinct role of intermediate monocytes within human monocyte heterogeneity, we assessed subset-specific expression of miRNAs as central epigenetic regulators of gene expression. We hypothesized that intermediate monocytes have a distinct miRNA profile compared to classical and non-classical monocytes. By using small RNA-seq we analyzed 662 miRNAs in the three monocyte subsets. We identified 38 miRNAs that are differentially expressed in intermediate monocytes compared to both classical and non-classical monocytes with a p value of <10^-10, of which two miRNAs - miR-6087 (upregulated) and miR-150-5p (downregulated) - differed in their expression more than ten-fold. Pathway analysis of the 38 differentially expressed miRNAs linked intermediate monocytes to distinct biological processes such as gene regulation, cell differentiation, toll-like receptor signaling as well as antigen processing and presentation. Moreover, differentially expressed miRNAs were connected to those genes that we previously identified as markers of intermediate monocytes. In aggregation, we provide first genome-wide miRNA data in the context of monocyte heterogeneity, which substantiate the concept of monocyte trichotomy in human immunity. The identification of miRNAs that are specific for intermediate monocytes may allow to develop strategies, which particularly target this cell population while sparing the other two subsets.

Gld2-catalyzed 3' monoadenylation of miRNAs in the hippocampus has no detectable effect on their stability or on animal behavior

Gld2, a noncanonical cytoplasmic poly(A) polymerase, interacts with the RNA binding protein CPEB1 to mediate polyadenylation-induced translation in dendrites of cultured hippocampal neurons. Depletion of Gld2 from the hippocampus leads to a deficit in long-term potentiation evoked by theta burst stimulation. At least in mouse liver and human primary fibroblasts, Gld2 also 3' monoadenylates and thereby stabilizes specific miRNAs, which enhance mRNA translational silencing and eventual destruction. These results suggest that Gld2 would be likely to monoadenylate and stabilize miRNAs in the hippocampus, which would produce measurable changes in animal behavior. We now report that using Gld2 knockout mice, there are detectable alterations in specific miRNA monoadenylation in the hippocampus when compared to wild type, but that these modifications produce no detectable effect on miRNA stability. Moreover, we surprisingly find no overt change in animal behavior when comparing Gld2 knockout to wild-type mice. These data indicate that miRNA monoadenylation-mediated stability is cell type-specific and that monoadenylation has no measurable effect on higher cognitive function.

Noncoding RNA: Current Deep Sequencing Data Analysis Approaches and Challenges

One of the most significant biological discoveries of the last decade is represented by the reality that the vast majority of the transcribed genomic output comprises diverse classes of noncoding RNAs (ncRNAs) that may play key roles and/or be affected by many biochemical cellular processes (i.e., RNA editing), with implications in human health and disease. With 90% of the human genome being transcribed and novel classes of ncRNA emerging (tRNA-derived small RNAs and circular RNAs among others), the great majority of the human transcriptome suggests that many important ncRNA functions/processes are yet to be discovered. An approach to filling such vast void of knowledge has been recently provided by the increasing application of next-generation sequencing (NGS), offering the unprecedented opportunity to obtain a more accurate profiling with higher resolution, increased throughput, sequencing depth, and low experimental complexity, concurrently posing an increasing challenge in terms of efficiency, accuracy, and usability of data analysis software. This review provides an overview of ncRNAs, NGS technology, and the most recent/popular computational approaches and the challenges they attempt to solve, which are essential to a more sensitive and comprehensive ncRNA annotation capable of furthering our understanding of this still vastly uncharted genomic territory.

Wnt-signalling pathways and microRNAs network in carcinogenesis: experimental and bioinformatics approaches

Over the past few years, microRNAs (miRNAs) have not only emerged as integral regulators of gene expression at the post-transcriptional level but also respond to signalling molecules to affect cell function(s). miRNAs crosstalk with a variety of the key cellular signalling networks such as Wnt, transforming growth factor-β and Notch, control stem cell activity in maintaining tissue homeostasis, while if dysregulated contributes to the initiation and progression of cancer. Herein, we overview the molecular mechanism(s) underlying the crosstalk between Wnt-signalling components (canonical and non-canonical) and miRNAs, as well as changes in the miRNA/Wnt-signalling components observed in the different forms of cancer. Furthermore, the fundamental understanding of miRNA-mediated regulation of Wnt-signalling pathway and vice versa has been significantly improved by high-throughput genomics and bioinformatics technologies. Whilst, these approaches have identified a number of specific miRNA(s) that function as oncogenes or tumour suppressors, additional analyses will be necessary to fully unravel the links among conserved cellular signalling pathways and miRNAs and their potential associated components in cancer, thereby creating therapeutic avenues against tumours. Hence, we also discuss the current challenges associated with Wnt-signalling/miRNAs complex and the analysis using the biomedical experimental and bioinformatics approaches.

Transcriptomic Analyses of Adipocyte Differentiation From Human Mesenchymal Stromal-Cells (MSC)

Adipogenesis is a physiological process required for fat-tissue development, mainly involved in regulating the organism energetic-state. Abnormal distribution-changes and dysfunctions in such tissue are associated to different pathologies. Adipocytes are generated from progenitor cells, via a complex differentiating process not yet well understood. Therefore, we investigated differential mRNA and miRNA expression patterns of human mesenchymal stromal-cells (MSC) induced and not induced to differentiate into adipocytes by next (second)-generation sequencing. A total of 2,866 differentially expressed genes (101 encoding miRNA) were identified, with 705 (46 encoding miRNA) being upregulated in adipogenesis. They were related to different pathways, including PPARG, lipid, carbohydrate and energy metabolism, redox, membrane-organelle biosynthesis, and endocrine system. Downregulated genes were related to extracellular matrix and cell migration, proliferation, and differentiation. Analyses of mRNA-miRNA interaction showed that repressed miRNA-encoding genes can act downregulating PPARG-related genes; mostly the PPARG activator (PPARGC1A). Induced miRNA-encoding genes regulate downregulated genes related to TGFB1. These results shed new light to understand adipose-tissue differentiation and physiology, increasing our knowledge about pathologies like obesity, type-2 diabetes and osteoporosis. J. Cell. Physiol. 232: 771-784, 2017. © 2016 Wiley Periodicals, Inc.

PmiRExAt: plant miRNA expression atlas database and web applications

High-throughput small RNA (sRNA) sequencing technology enables an entirely new perspective for plant microRNA (miRNA) research and has immense potential to unravel regulatory networks. Novel insights gained through data mining in publically available rich resource of sRNA data will help in designing biotechnology-based approaches for crop improvement to enhance plant yield and nutritional value. Bioinformatics resources enabling meta-analysis of miRNA expression across multiple plant species are still evolving. Here, we report PmiRExAt, a new online database resource that caters plant miRNA expression atlas. The web-based repository comprises of miRNA expression profile and query tool for 1859 wheat, 2330 rice and 283 maize miRNA. The database interface offers open and easy access to miRNA expression profile and helps in identifying tissue preferential, differential and constitutively expressing miRNAs. A feature enabling expression study of conserved miRNA across multiple species is also implemented. Custom expression analysis feature enables expression analysis of novel miRNA in total 117 datasets. New sRNA dataset can also be uploaded for analysing miRNA expression profiles for 73 plant species. PmiRExAt application program interface, a simple object access protocol web service allows other programmers to remotely invoke the methods written for doing programmatic search operations on PmiRExAt database.Database URL:http://pmirexat.nabi.res.in.

Impact of individual intravenous iron preparations on the differentiation of monocytes towards macrophages and dendritic cells

Background

Treatment of iron deficiency with intravenous (i.v.) iron is a first-line strategy to improve anaemia of chronic kidney disease. Previous in vitro experiments demonstrated that different i.v. iron preparations inhibit differentiation of haematopoietic stem cells to monocytes, but their effect on monocyte differentiation to macrophages and mature dendritic cells (mDCs) has not been assessed. We investigated substance-specific effects of iron sucrose (IS), sodium ferric gluconate (SFG), ferric carboxymaltose (FCM) and iron isomaltoside 1000 (IIM) on monocytic differentiation to M1/M2 macrophages and mDCs.

Methods

Via flow cytometry and microRNA (miRNA) expression analysis, we morphologically and functionally characterized monocyte differentiation to M1/M2 macrophages and mDCs after monocyte stimulation with IS, SFG, FCM and IIM (0.133, 0.266 and 0.533 mg/mL, respectively). To assess potential clinical implications, we compared monocytic phagocytosis capacity in dialysis patients who received either 500 mg IS or IIM.

Results

Phenotypically, IS and SFG dysregulated the expression of macrophage (e.g. CD40, CD163) and mDC (e.g. CD1c, CD141) surface markers. Functionally, IS and SFG impaired macrophage phagocytosis capacity. Phenotypic and functional alterations were less pronounced with FCM, and virtually absent with IIM. In miRNA expression analysis of mDCs, IS dysregulated miRNAs such as miR-146b-5p and miR-155-5p, which are linked to Toll-like receptor and mitogen-activated protein kinase signalling pathways. In vivo, IS reduced monocytic phagocytosis capacity within 1 h after infusion, while IIM did not.

Conclusions

This study demonstrates that less stable i.v. iron preparations specifically affect monocyte differentiation towards macrophages and mDCs.

miRge - A Multiplexed Method of Processing Small RNA-Seq Data to Determine MicroRNA Entropy

Small RNA RNA-seq for microRNAs (miRNAs) is a rapidly developing field where opportunities still exist to create better bioinformatics tools to process these large datasets and generate new, useful analyses. We built miRge to be a fast, smart small RNA-seq solution to process samples in a highly multiplexed fashion. miRge employs a Bayesian alignment approach, whereby reads are sequentially aligned against customized mature miRNA, hairpin miRNA, noncoding RNA and mRNA sequence libraries. miRNAs are summarized at the level of raw reads in addition to reads per million (RPM). Reads for all other RNA species (tRNA, rRNA, snoRNA, mRNA) are provided, which is useful for identifying potential contaminants and optimizing small RNA purification strategies. miRge was designed to optimally identify miRNA isomiRs and employs an entropy based statistical measurement to identify differential production of isomiRs. This allowed us to identify decreasing entropy in isomiRs as stem cells mature into retinal pigment epithelial cells. Conversely, we show that pancreatic tumor miRNAs have similar entropy to matched normal pancreatic tissues. In a head-to-head comparison with other miRNA analysis tools (miRExpress 2.0, sRNAbench, omiRAs, miRDeep2, Chimira, UEA small RNA Workbench), miRge was faster (4 to 32-fold) and was among the top-two methods in maximally aligning miRNAs reads per sample. Moreover, miRge has no inherent limits to its multiplexing. miRge was capable of simultaneously analyzing 100 small RNA-Seq samples in 52 minutes, providing an integrated analysis of miRNA expression across all samples. As miRge was designed for analysis of single as well as multiple samples, miRge is an ideal tool for high and low-throughput users. miRge is freely available at http://atlas.pathology.jhu.edu/baras/miRge.html.

mirPRo-a novel standalone program for differential expression and variation analysis of miRNAs

Being involved in many important biological processes, miRNAs can regulate gene expression by targeting mRNAs to facilitate their degradation or translational inhibition. Many miRNA sequencing studies reveal that miRNA variations such as isomiRs and “arm switching” are biologically relevant. However, existing standalone tools usually do not provide comprehensive, detailed information on miRNA variations. To deepen our understanding of miRNA variability, we developed a new standalone tool called “mirPRo” to quantify known miRNAs and predict novel miRNAs. Compared with the most widely used standalone program, miRDeep2, mirPRo offers several new functions including read cataloging based on genome annotation, optional seed region check, miRNA family expression quantification, isomiR identification and categorization, and “arm switching” detection. Our comparative data analyses using three datasets from mouse, human and chicken demonstrate that mirPRo is more accurate than miRDeep2 by avoiding over-counting of sequence reads and by implementing different approaches in adapter trimming, mapping and quantification. mirPRo is an open-source standalone program (https://sourceforge.net/projects/mirpro/).

Identification of novel small ncRNAs in pollen of tomato

BACKGROUND

The unprecedented role of sncRNAs in the regulation of pollen biogenesis on both transcriptional and epigenetic levels has been experimentally proven. However, little is known about their global regulation, especially under stress conditions. We used tomato pollen in order to identify pollen stage-specific sncRNAs and their target mRNAs. We further deployed elevated temperatures to discern stress responsive sncRNAs. For this purpose high throughput sncRNA-sequencing as well as Massive Analysis of cDNA Ends (MACE) were performed for three-replicated sncRNAs libraries derived from tomato tetrad, post-meiotic, and mature pollen under control and heat stress conditions.

RESULTS

Using the omiRas analysis pipeline we identified known and predicted novel miRNAs as well as sncRNAs from other classes, responsive or not to heat. Differential expression analysis revealed that post-meiotic and mature pollen react most strongly by regulation of the expression of coding and non-coding genomic regions in response to heat. To gain insight to the function of these miRNAs, we predicted targets and annotated them to Gene Ontology terms. This approach revealed that most of them belong to protein binding, transcription, and Serine/Threonine kinase activity GO categories. Beside miRNAs, we observed differential expression of both tRNAs and snoRNAs in tetrad, post-meiotic, and mature pollen when comparing normal and heat stress conditions.

CONCLUSIONS

Thus, we describe a global spectrum of sncRNAs expressed in pollen as well as unveiled those which are regulated at specific time-points during pollen biogenesis. We integrated the small RNAs into the regulatory network of tomato heat stress response in pollen.

Principles of miRNA-mRNA interactions: beyond sequence complementarity

MicroRNAs (miRNAs) are small non-coding RNAs that post-transcriptionally regulate gene expression by altering the translation efficiency and/or stability of targeted mRNAs. In vertebrates, more than 50% of all protein-coding RNAs are assumed to be subject to miRNA-mediated control, but current high-throughput methods that reliably measure miRNA-mRNA interactions either require prior knowledge of target mRNAs or elaborate preparation procedures. Consequently, experimentally validated interactions are relatively rare. Furthermore, in silico prediction based on sequence complementarity of miRNAs and their corresponding target sites suffers from extremely high false positive rates. Apparently, sequence complementarity alone is often insufficient to reflect the complex post-transcriptional regulation of mRNAs by miRNAs, which is especially true for animals. Therefore, combined analysis of small non-coding and protein-coding RNAs is indispensable to better understand and predict the complex dynamics of miRNA-regulated gene expression. Single-nucleotide polymorphisms (SNPs) and alternative polyadenylation (APA) can affect miRNA binding of a given transcript from different individuals and tissues, and especially APA is currently emerging as a major factor that contributes to variations in miRNA-mRNA interplay in animals. In this review, we focus on the influence of APA and SNPs on miRNA-mediated gene regulation and discuss the computational approaches that take these mechanisms into account.

miFRame: analysis and visualization of miRNA sequencing data in neurological disorders

Background

While in the past decades nucleic acid analysis has been predominantly carried out using quantitative low- and high-throughput approaches such as qRT-PCR and microarray technology, next-generation sequencing (NGS) with its single base resolution is now frequently applied in DNA and RNA testing. Especially for small non-coding RNAs such as microRNAs there is a need for analysis and visualization tools that facilitate interpretation of the results also for clinicians.

Methods

We developed miFRame, which supports the analysis of human small RNA NGS data. Our tool carries out different data analyses for known as well as predicted novel mature microRNAs from known precursors and presents the results in a well interpretable manner. Analyses include among others expression analysis of precursors and mature miRNAs, detection of novel precursors and detection of potential iso-microRNAs. Aggregation of results from different users moreover allows for evaluation whether remarkable results, such as novel mature miRNAs, are indeed specific for the respective experimental set-up or are frequently detected across a broad range of experiments.

Results

We demonstrate the capabilities of miFRame, which is freely available at http://www.ccb.uni-saarland.de/miframe on two studies, circulating biomarker screening for Multiple Sclerosis (cohort includes clinically isolated syndrome, relapse remitting MS, matched controls) as well as Alzheimer Disease (cohort includes Alzheimer Disease, Mild Cognitive Impairment, matched controls). Here, our tool allowed for an improved biomarker discovery by identifying likely false positive marker candidates.

Electronic supplementary material

The online version of this article (doi:10.1186/s12967-015-0594-x) contains supplementary material, which is available to authorized users.

Next-generation sequencing reveals novel differentially regulated mRNAs, lncRNAs, miRNAs, sdRNAs and a piRNA in pancreatic cancer

Background

Previous studies identified microRNAs (miRNAs) and messenger RNAs with significantly different expression between normal pancreas and pancreatic cancer (PDAC) tissues. Due to technological limitations of microarrays and real-time PCR systems these studies focused on a fixed set of targets. Expression of other RNA classes such as long intergenic non-coding RNAs or sno-derived RNAs has rarely been examined in pancreatic cancer. Here, we analysed the coding and non-coding transcriptome of six PDAC and five control tissues using next-generation sequencing.

Results

Besides the confirmation of several deregulated mRNAs and miRNAs, miRNAs without previous implication in PDAC were detected: miR-802, miR-2114 or miR-561. SnoRNA-derived RNAs (e.g. sno-HBII-296B) and piR-017061, a piwi-interacting RNA, were found to be differentially expressed between PDAC and control tissues. In silico target analysis of miR-802 revealed potential binding sites in the 3′ UTR of TCF4, encoding a transcription factor that controls Wnt signalling genes. Overexpression of miR-802 in MiaPaCa pancreatic cancer cells reduced TCF4 protein levels. Using Massive Analysis of cDNA Ends (MACE) we identified differential expression of 43 lincRNAs, long intergenic non-coding RNAs, e.g. LINC00261 and LINC00152 as well as several natural antisense transcripts like HNF1A-AS1 and AFAP1-AS1. Differential expression was confirmed by qPCR on the mRNA/miRNA/lincRNA level and by immunohistochemistry on the protein level.

Conclusions

Here, we report a novel lncRNA, sncRNA and mRNA signature of PDAC. In silico prediction of ncRNA targets allowed for assigning potential functions to differentially regulated RNAs.

Electronic supplementary material

The online version of this article (doi:10.1186/s12943-015-0358-5) contains supplementary material, which is available to authorized users.

MicroRNA-Seq Data Analysis Pipeline to Identify Blood Biomarkers for Alzheimer's Disease from Public Data

BACKGROUND

Alzheimer’s disease (AD) is the most common cause of dementia with no curative therapy currently available. Establishment of sensitive and non-invasive biomarkers that promote an early diagnosis of AD is crucial for the effective administration of disease-modifying drugs. MicroRNAs (miRNAs) mediate posttranscriptional repression of numerous target genes. Aberrant regulation of miRNA expression is implicated in AD pathogenesis, and circulating miRNAs serve as potential biomarkers for AD. However, data analysis of numerous AD-specific miRNAs derived from small RNA-sequencing (RNA-Seq) is most often laborious.

METHODS

To identify circulating miRNA biomarkers for AD, we reanalyzed a publicly available small RNA-Seq dataset, composed of blood samples derived from 48 AD patients and 22 normal control (NC) subjects, by a simple web-based miRNA data analysis pipeline that combines omiRas and DIANA miRPath.

RESULTS

By using omiRas, we identified 27 miRNAs expressed differentially between both groups, including upregulation in AD of miR-26b-3p, miR-28–3p, miR-30c-5p, miR-30d-5p, miR-148b-5p, miR-151a-3p, miR-186–5p, miR-425–5p, miR-550a-5p, miR-1468, miR-4781–3p, miR-5001–3p, and miR-6513–3p and downregulation in AD of let-7a-5p, let-7e-5p, let-7f-5p, let-7g-5p, miR-15a-5p, miR-17–3p, miR-29b-3p, miR-98–5p, miR-144–5p, miR-148a-3p, miR-502–3p, miR-660–5p, miR-1294, and miR-3200–3p. DIANA miRPath indicated that miRNA-regulated pathways potentially downregulated in AD are linked with neuronal synaptic functions, while those upregulated in AD are implicated in cell survival and cellular communication.

CONCLUSIONS

The simple web-based miRNA data analysis pipeline helps us to effortlessly identify candidates for miRNA biomarkers and pathways of AD from the complex small RNA-Seq data.

In silico analysis of regulatory networks underlines the role of miR-10b-5p and its target BDNF in huntington's disease

Non-coding RNAs (ncRNAs) play various roles during central nervous system development. MicroRNAs (miRNAs) are a class of ncRNAs that exert their function together with argonaute proteins by post-transcriptional gene silencing of messenger RNAs (mRNAs). Several studies provide evidence for alterations in miRNA expression in patients with neurodegenerative diseases. Among these is huntington's disease (HD), a dominantly inherited fatal disorder characterized by deregulation of neuronal-specific mRNAs as well as miRNAs. Recently, next-generation sequencing (NGS) miRNA profiles from human HD and neurologically normal control brain tissues were reported. Five consistently upregulated miRNAs affect the expression of genes involved in neuronal differentiation, neurite outgrowth, cell death and survival. We re-analyzed the NGS data publicly available in array express and detected nineteen additional differentially expressed miRNAs. Subsequently, we connected these miRNAs to genes implicated in HD development and network analysis pointed to miRNA-mediated downregulation of twenty-two genes with roles in the pathogenesis as well as treatment of the disease. In silico prediction and reporter systems prove that levels of BDNF, a central node in the miRNA-mRNA regulatory network, can be post-transcriptionally controlled by upregulated miR-10b-5p and miR-30a-5p. Reduced BDNF expression is associated with neuronal dysfunction and death in HD. Moreover, the 3'UTR of CREB1 harbors a predicted binding site for these two miRNAs. CREB1 is similarly downregulated in HD and overexpression decreased susceptibility to 3-nitropropionic-induced toxicity in a cell model. In contradiction to these observations, it is presumed that miR-10b-5p upregulation in HD exerts a neuroprotective role in response to the mutation in the huntingtin gene. Therefore, the function of miR-10b-5p and especially its effect on BDNF expression in HD requires further academic research.

microRNAs: role in leukemia and their computational perspective

MicroRNAs (miRNAs) belong to the family of noncoding RNAs (ncRNAs) and had gained importance due to its role in complex biochemical pathways. Changes in the expression of protein coding genes are the major cause of leukemia. Role of miRNAs as tumor suppressors has provided a new insight in the field of leukemia research. Particularly, the miRNAs mediated gene regulation involves the modulation of multiple mRNAs and cooperative action of different miRNAs to regulate a particular gene expression. This highly complex array of regulatory pathway network indicates the great possibility in analyzing and identifying novel findings. Owing to the conventional, slow experimental identification process of miRNAs and their targets, the last decade has witnessed the development of a large amount of computational approaches to deal with the complex interrelations present within biological systems. This article describes the various roles played by miRNAs in regulating leukemia and the role of computational approaches in exploring new possibilities.

APADB: a database for alternative polyadenylation and microRNA regulation events

Alternative polyadenylation (APA) is a widespread mechanism that contributes to the sophisticated dynamics of gene regulation. Approximately 50% of all protein-coding human genes harbor multiple polyadenylation (PA) sites; their selective and combinatorial use gives rise to transcript variants with differing length of their 3′ untranslated region (3′UTR). Shortened variants escape UTR-mediated regulation by microRNAs (miRNAs), especially in cancer, where global 3′UTR shortening accelerates disease progression, dedifferentiation and proliferation. Here we present APADB, a database of vertebrate PA sites determined by 3′ end sequencing, using massive analysis of complementary DNA ends. APADB provides (A)PA sites for coding and non-coding transcripts of human, mouse and chicken genes. For human and mouse, several tissue types, including different cancer specimens, are available. APADB records the loss of predicted miRNA binding sites and visualizes next-generation sequencing reads that support each PA site in a genome browser. The database tables can either be browsed according to organism and tissue or alternatively searched for a gene of interest. APADB is the largest database of APA in human, chicken and mouse. The stored information provides experimental evidence for thousands of PA sites and APA events. APADB combines 3′ end sequencing data with prediction algorithms of miRNA binding sites, allowing to further improve prediction algorithms. Current databases lack correct information about 3′UTR lengths, especially for chicken, and APADB provides necessary information to close this gap.

Database URL:http://tools.genxpro.net/apadb/

MAGI: a Node.js web service for fast microRNA-Seq analysis in a GPU infrastructure

Summary: MAGI is a web service for fast MicroRNA-Seq data analysis in a graphics processing unit (GPU) infrastructure. Using just a browser, users have access to results as web reports in just a few hours—>600% end-to-end performance improvement over state of the art. MAGI’s salient features are (i) transfer of large input files in native FASTA with Qualities (FASTQ) format through drag-and-drop operations, (ii) rapid prediction of microRNA target genes leveraging parallel computing with GPU devices, (iii) all-in-one analytics with novel feature extraction, statistical test for differential expression and diagnostic plot generation for quality control and (iv) interactive visualization and exploration of results in web reports that are readily available for publication.

Availability and implementation: MAGI relies on the Node.js JavaScript framework, along with NVIDIA CUDA C, PHP: Hypertext Preprocessor (PHP), Perl and R. It is freely available at http://magi.ucsd.edu.

Contact:j5kim@ucsd.edu

Supplementary information:Supplementary data are available at Bioinformatics online.

CAP-miRSeq: a comprehensive analysis pipeline for microRNA sequencing data

Background

miRNAs play a key role in normal physiology and various diseases. miRNA profiling through next generation sequencing (miRNA-seq) has become the main platform for biological research and biomarker discovery. However, analyzing miRNA sequencing data is challenging as it needs significant amount of computational resources and bioinformatics expertise. Several web based analytical tools have been developed but they are limited to processing one or a pair of samples at time and are not suitable for a large scale study. Lack of flexibility and reliability of these web applications are also common issues.

Results

We developed a Comprehensive Analysis Pipeline for microRNA Sequencing data (CAP-miRSeq) that integrates read pre-processing, alignment, mature/precursor/novel miRNA detection and quantification, data visualization, variant detection in miRNA coding region, and more flexible differential expression analysis between experimental conditions. According to computational infrastructure, users can install the package locally or deploy it in Amazon Cloud to run samples sequentially or in parallel for a large number of samples for speedy analyses. In either case, summary and expression reports for all samples are generated for easier quality assessment and downstream analyses. Using well characterized data, we demonstrated the pipeline’s superior performances, flexibility, and practical use in research and biomarker discovery.

Conclusions

CAP-miRSeq is a powerful and flexible tool for users to process and analyze miRNA-seq data scalable from a few to hundreds of samples. The results are presented in the convenient way for investigators or analysts to conduct further investigation and discovery.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-423) contains supplementary material, which is available to authorized users.

Exploring the miRNA-mRNA regulatory network in clear cell renal cell carcinomas by next-generation sequencing expression profiles

Altered microRNA (miRNA) expression is a hallmark of many cancer types. The combined analysis of miRNA and messenger RNA (mRNA) expression profiles is crucial to identifying links between deregulated miRNAs and oncogenic pathways. Therefore, we investigated the small non-coding (snc) transcriptomes of nine clear cell renal cell carcinomas (ccRCCs) and adjacent normal tissues for alterations in miRNA expression using a publicly available small RNA-Sequencing (sRNA-Seq) raw-dataset. We constructed a network of deregulated miRNAs and a set of differentially expressed genes publicly available from an independent study to in silico determine miRNAs that contribute to clear cell renal cell carcinogenesis. From a total of 1,672 sncRNAs, 61 were differentially expressed across all ccRCC tissue samples. Several with known implications in ccRCC development, like the upregulated miR-21-5p, miR-142-5p, as well as the downregulated miR-106a-5p, miR-135a-5p, or miR-206. Additionally, novel promising candidates like miR-3065, which i.a. targets NRP2 and FLT1, were detected in this study. Interaction network analysis revealed pivotal roles for miR-106a-5p, whose loss might contribute to the upregulation of 49 target mRNAs, miR-135a-5p (32 targets), miR-206 (28 targets), miR-363-3p (22 targets), and miR-216b (13 targets). Among these targets are the angiogenesis, metastasis, and motility promoting oncogenes c-MET, VEGFA, NRP2, and FLT1, the latter two coding for VEGFA receptors.