Joint analysis of miRNA and mRNA expression data

Expanding the immune-related targetome of miR-155-5p by integrating time-resolved RNA patterns into miRNA target prediction

The lack of a sufficient number of validated miRNA targets severely hampers the understanding of their biological function. Even for the well-studied miR-155-5p, there are only 239 experimentally validated targets out of 42,554 predicted targets. For a more complete assessment of the immune-related miR-155 targetome, we used an inverse correlation of time-resolved mRNA profiles and miR-155-5p expression of early CD4+ T cell activation to predict immune-related target genes. Using a high-throughput miRNA interaction reporter (HiTmIR) assay we examined 90 target genes and confirmed 80 genes as direct targets of miR-155-5p. Our study increases the current number of verified miR-155-5p targets approximately threefold and exemplifies a method for verifying miRNA targetomes as a prerequisite for the analysis of miRNA-regulated cellular networks.

Human Peripheral Blood Leukocyte Transcriptome-Based Aging Clock Reveals Acceleration of Aging by Bacterial or Viral Infections

The aging of the population is a global concern. In the post-coronavirus disease 2019 (COVID-19) pandemic era, there are no effective methods to identify aging acceleration due to infection. In this study, we conducted whole-transcriptome sequencing on peripheral blood samples from 35 healthy individuals (22-88 years old). By analyzing the changes in mRNA, lncRNA, and miRNA expression, we investigated the characteristics of transcriptome alterations during the aging process. ceRNA networks were constructed, and 10 genes (CD248, PHGDH, SFXN2, MXRA8, NOG, TTC24, PHYKPL, CACHD1, BPGM, and TWF1) were identified as potential aging markers and used to construct an aging clock. Moreover, our aging clock categorized individuals into slow-, average-, and quick-aging groups, highlighting a link between accelerated aging and infection-related clinical parameters. Pseudotime analysis further revealed 2 distinct aging trajectories, corroborating the variations in the aging rate identified by the aging clock. Furthermore, we validated the results using the OEP001041 data set (277 healthy individuals aged 17-75), and data sets comprising patients with infectious diseases (n = 1 558). Our study revealed that infection accelerates aging via increased inflammation and oxidative stress in infectious disease patients. Besides, the aging clock exhibited alterations after infection, highlighting its potential for assessing the aging rate after patient recovery. In conclusion, our study introduces a novel aging clock to assess the aging rate in healthy individuals and those with infections, revealing a strong link between accelerated aging and infections through inflammation and oxidative stress. These findings offer valuable insights into aging mechanisms and potential strategies for healthy aging.

LINC00342 regulates the PI3K-AKT signaling pathway via the miR-149-5p/FGF11 axis and affects the progression of oral cancer

BACKGROUND

A large number of long non-coding RNAs (lncRNAs) have been implicated in the progression of oral cancer (OC). This study aimed to investigate the role of a novel lncRNA, LINC00342, in OC and elucidate its molecular mechanism.

METHODS

Differential expression of lncRNA/miRNA/mRNA was analyzed using the Gene Expression Omnibus database and validated with RT-qPCR. Additionally, the expression levels of these molecules in OC cells and their effects on cell viability and cell cycle were assessed using the Cell Counting Kit-8 and flow cytometry. RNA bindings was analyzed by dual luciferase, and Western blot was used to detect the activation of relevant pathways.

RESULTS

This study showed that, in contrast to miR-149-5p, the expression of LINC00342 and fibroblast growth factor 11 (FGF11) were upregulated in OC cells (LINC00342: 10.00 ± 1.06 (FaDu) and 3.55 ± 0.25 (CAL-27) vs 1.00 ± 0.07 (HOECs), P < 0.05; FGF11: 7.31 ± 0.33 (FaDu) and 3.43 ± 0.08 (CAL-27) vs 1.00 ± 0.10 (HOECs), P < 0.05). Dual-luciferase assays confirmed that LINC00342 bind to miR-149-5p in a direct targeting manner. Furthermore, inhibition of LINC00342 expression resulted in decreased proliferation rate (FaDu: 136.22 ± 22.10% vs 59.36 ± 8.98% (control), P < 0.05; CAL-27: 131.40 ± 11.58% vs 49.83 ± 11.19 (control), P < 0.05) and migration ability of OC cells, cell cycle arrest in G1 phase, and inhibition of PI3K-AKT signaling. Inhibition of miR-149-5p or overexpression of FGF11 reversed the effects of si-LINC00342.

CONCLUSIONS

LINC00342 promotes PI3K-AKT signaling by activating FGF11 through adsorption of miR-149-5p, thereby regulating the progression of OC.

microRNA Isolation, Expression Profiling, and Target Identification for Neuroprotection in Alzheimer's Disease

Millions of people throughout the world are affected by neurodegenerative disorders like Alzheimer's disease (AD), making them a major public health concern. To create successful medicines, early diagnosis and illness monitoring are required. Emerging as possible diagnostic and treatment tools for neurodegenerative illnesses are biomarkers such as microRNAs (miRNAs). In the realm of neuroscience, miRNAs have been discovered to function as essential regulators of gene expression, with roles spanning development, differentiation, and illness. Several neurodegenerative diseases, including AD, have been linked to miRNA dysregulation. As high-throughput methods have been developed for monitoring miRNA expression and identifying miRNA targets, miRNAs have become a prime candidate for use in diagnostics and therapy. The techniques for isolating miRNAs and the most up-to-date computational methods for finding miRNA target transcripts are both described in this chapter. This chapter will be a helpful reference for anyone investigating the role of miRNAs in AD and related neurodegenerative illnesses.

Joint and Individual Component Regression

Multi-group data, which include the same set of variables on separate groups of samples, are commonly seen in practice. Such data structure consists of data from multiple groups and can be challenging to analyze due to data heterogeneity. We propose a novel Joint and Individual Component Regression (JICO) model to analyze multi-group data. Our proposed model decomposes the response into shared and group-specific components, which are driven by low-rank approximations of joint and individual structures from the predictors respectively. The joint structure has the same regression coefficients across multiple groups, whereas individual structures have group-specific regression coefficients. We formulate this framework under the representation of latent components and propose an iterative algorithm to solve for the joint and individual scores. We utilize the Continuum Regression (CR) to estimate the latent scores, which provides a unified framework that covers the Ordinary Least Squares (OLS), the Partial Least Squares (PLS), and the Principal Component Regression (PCR) as its special cases. We show that JICO attains a good balance between global and group-specific models and remains flexible due to the usage of CR. We conduct simulation studies and analysis of an Alzheimer's disease dataset to further demonstrate the effectiveness of JICO. R package of JICO is available online at https://CRAN.R-project.org/package=JICO.

Therapeutic Hypothermia Inhibits Hypoxia-Induced Cardiomyocyte Apoptosis Via the MiR-483-3p/Cdk9 Axis

Background Therapeutic hypothermia has a beneficial effect on cardiac function after acute myocardial infarction, but the exact mechanism is still unclear. Recent research has suggested that microRNAs participate in acute myocardial infarction to regulate cardiomyocyte survival. This study aimed to explore the ability of hypothermia-regulated microRNA-483-3p (miR-483-3p) to inhibit hypoxia-induced myocardial infarction. Methods and Results Primary cardiomyocytes were cultured under hypoxia at 32 °C to mimic therapeutic hypothermia, and the differentially expressed microRNAs were determined by RNA sequencing. Therapeutic hypothermia recovered hypoxia-induced increases in apoptosis, decreases in ATP levels, and decreases in miR-483-3p expression. Overexpression of miR-483-3p exhibited effects similar to those of therapeutic hypothermia on hypoxia in the treatment of cardiomyocytes to associate with maintaining the mitochondrial membrane potential, and cyclin-dependent kinase 9 (Cdk9) was identified as a target gene with downregulated expression by miR-483-3p. Knockdown of Cdk9 also promoted cardiac survival, ATP production, and mitochondrial membrane potential stability under hypoxia. In vivo, the expression of miR-483-3p and Cdk9 was tested in the cardiac tissue of the mice with acute myocardial infarction, and the expression of miR-483-3p decreased and Cdk9 increased in the region of myocardial infarction. However, miR-483-3p was overexpressed with lentivirus, which suppressed apoptosis, infarct size (miR-483-3p, 22.00±4.04% versus negative control, 28.57±5.44%, P<0.05), and Cdk9 expression to improve cardiac contractility. Conclusions MiR-483-3p antagonizes hypoxia, leading to cardiomyocyte injury by targeting Cdk9, which is a new mechanism of therapeutic hypothermia.

A novel approach for a joint analysis of isomiR and mRNA expression data reveals features of isomiR targeting in breast cancer

A widely used procedure for selecting significant miRNA-mRNA or isomiR-mRNA pairs out of predicted interactions involves calculating the correlation between expression levels of miRNAs/isomiRs and mRNAs in a series of samples. In this manuscript, we aimed to assess the validity of this procedure by comparing isomiR-mRNA correlation profiles in sets of sequence-based predicted target mRNAs and non-target mRNAs (negative controls). Target prediction was carried out using RNA22 and TargetScan algorithms. Spearman's correlation analysis was conducted using miRNA and mRNA sequencing data of The Cancer Genome Atlas Breast Invasive Carcinoma (TCGA-BRCA) project. Luminal A, luminal B, basal-like breast cancer subtypes, and adjacent normal tissue samples were analyzed separately. Using the sets of putative targets and non-targets, we introduced adjusted isomiR targeting activity (ITA)-the number of negatively correlated potential isomiR targets adjusted by the background (estimated using non-target mRNAs). We found that for most isomiRs a significant negative correlation between isomiR-mRNA expression levels appeared more often in a set of predicted targets compared to the non-targets. This trend was detected for both classical seed region binding types (8mer, 7mer-m8, 7mer-A1, 6mer) predicted by TargetScan and the non-classical ones (G:U wobbles and up to one mismatch or unpaired nucleotide within seed sequence) predicted by RNA22. Adjusted ITA distributions were similar for target sites located in 3'-UTRs and coding mRNA sequences, while 5'-UTRs had much lower scores. Finally, we observed strong cancer subtype-specific patterns of isomiR activity, highlighting the differences between breast cancer molecular subtypes and normal tissues. Surprisingly, our target prediction- and correlation-based estimates of isomiR activities were practically non-correlated with the average isomiR expression levels neither in cancerous nor in normal samples.

E2F1 regulates miR-215-5p to aggravate paraquat-induced pulmonary fibrosis via repressing BMPR2 expression

Background

Pulmonary fibrosis is considered to be an irreversible lung injury, which can be caused by paraquat (PQ) poisoning. MiRNAs have been demonstrated crucial roles in pulmonary fibrosis caused by numerous approaches including PQ induction. The purpose of this study was to investigate the role and the underlying mechanism of miR-215 in PQ-induced pulmonary fibrosis.

Methods

The cell and animal models of pulmonary fibrosis were established through PQ intervention. Cell viability was performed to test by MTT assay. Immunofluorescence assay was used to detect COL1A1 expression and its location. The relationships among E2F1, miR-215-5p, and BMPR2 were validated by dual luciferase reporter gene assay, chromatin immunoprecipitation and RNA-binding protein immunoprecipitation. Lung morphology was evaluated by hematoxylin and eosin staining.

Results

MiR-215-5p was upregulated in PQ-induced pulmonary fibrosis in vitro and in vivo. MiR-215-5p silencing relieved PQ-induced pulmonary fibrosis progression by enhancing cell viability and reducing the expression of fibrosis-related markers (COL1A1, COL3A1, and α-SMA). Mechanistically, miR-215-5p directly targeted BMRP2. BMPR2 knockdown abolished the suppressive effects of miR-215-5p knockdown on PQ-induced pulmonary fibrosis. In addition, E2F1 interacted with miR-215-5p promoter and positively regulated miR-215-5p expression. E2F1 downregulation reduced miR-215-5p level and promoted BMPR2 level via regulating TGF-β/Smad3 pathway, and then suppressed PQ-induced pulmonary fibrosis, whereas these effects were compromised by miR-215-5p sufficiency.

Conclusion

MiR-215-5p was activated by E2F1 to repress BMPR2 expression and activate TGF-β/Smad3 pathway, which aggravated PQ-induced pulmonary fibrosis progression. Targeting the E2F1/miR-215-5p/BMPR2 axis might be a new approach to alleviate PQ-induced pulmonary fibrosis.

MIO: MicroRNA target analysis system for Immuno-Oncology

Summary

MicroRNAs have been shown to be able to modulate the tumor microenvironment and the immune response and hence could be interesting biomarkers and therapeutic targets in immuno-oncology; however, dedicated analysis tools are missing. Here, we present a user-friendly web platform MIO and a Python toolkit miopy integrating various methods for visualization and analysis of provided or custom bulk microRNA and gene expression data. We include regularized regression and survival analysis and provide information of 40 microRNA target prediction tools as well as a collection of curated immune related gene and microRNA signatures and processed TCGA data including estimations of infiltrated immune cells and the immunophenoscore. The integration of several machine learning methods enables the selection of prognostic and predictive microRNAs and gene interaction network biomarkers.

Availability and implementation

https://mio.icbi.at, https://github.com/icbi-lab/mio and https://github.com/icbi-lab/miopy.

Supplementary information

Supplementary data are available at Bioinformatics online.

The pleiotropic roles of circular and long noncoding RNAs in cutaneous melanoma

Cutaneous melanoma (CM) is a very aggressive disease, often characterized by unresponsiveness to conventional therapies and high mortality rates worldwide. The identification of the activating BRAFV600 mutations in approximately 50% of CM patients has recently fueled the development of novel small-molecule inhibitors that specifically target BRAFV600 -mutant CM. In addition, a major progress in CM treatment has been made by monoclonal antibodies that regulate the immune checkpoint inhibitors. However, although target-based therapies and immunotherapeutic strategies have yielded promising results, CM treatment remains a major challenge. In the last decade, accumulating evidence points to the aberrant expression of different types of noncoding RNAs (ncRNAs) in CM. While studies on microRNAs have grown exponentially leading to significant insights on CM biology, the role of circular RNAs (circRNAs) and long noncoding RNAs (lncRNAs) in this tumor is less understood, and much remains to be discovered. Here, we summarize and critically review the available evidence on the molecular functions of circRNAs and lncRNAs in BRAFV600 -mutant CM and CM immunogenicity, providing recent updates on their functional role in targeted therapy and immunotherapy resistance. In addition, we also include an evaluation of several algorithms and databases for prediction and validation of circRNA and lncRNA functional interactions.

Simultaneous learning of individual microRNA-gene interactions and regulatory comodules

BACKGROUND

MicroRNAs (miRNAs) function in post-transcriptional regulation of gene expression by binding to target messenger RNAs (mRNAs). Because of the key part that miRNAs play, understanding the correct regulatory role of miRNAs in diverse patho-physiological conditions is of great interest. Although it is known that miRNAs act combinatorially to regulate genes, precise identification of miRNA-gene interactions and their specific functional roles in regulatory comodules remains a challenge. We developed THEIA, an effective method for simultaneously predicting miRNA-gene interactions and regulatory comodules, which group functionally related miRNAs and genes via non-negative matrix factorization (NMF).

RESULTS

We apply THEIA to RNA sequencing data from breast invasive carcinoma samples and demonstrate its effectiveness in discovering biologically significant regulatory comodules that are significantly enriched in spatial miRNA clusters, biological pathways, and various cancers.

CONCLUSIONS

THEIA is a theoretically rigorous optimization algorithm that simultaneously predicts the strength and direction (i.e., up-regulation or down-regulation) of the effect of modules of miRNAs on a gene. We posit that if THEIA is capable of recovering known clusters of genes and miRNA, then the clusters found by our method not previously identified by literature are also likely to have biological significance. We believe that these novel regulatory comodules found by our method will be a springboard for further research into the specific functional roles of these new functional ensembles of miRNAs and genes,especially those related to diseases like breast cancer.

Altered microRNA and target gene expression related to Tetralogy of Fallot

MicroRNAs (miRNAs) play an important role in guiding development and maintaining function of the human heart. Dysregulation of miRNAs has been linked to various congenital heart diseases including Tetralogy of Fallot (TOF), which represents the most common cyanotic heart malformation in humans. Several studies have identified dysregulated miRNAs in right ventricular (RV) tissues of TOF patients. In this study, we profiled genome-wide the whole transcriptome and analyzed the relationship of miRNAs and mRNAs of RV tissues of a homogeneous group of 22 non-syndromic TOF patients. Observed profiles were compared to profiles obtained from right and left ventricular tissue of normal hearts. To reduce the commonly observed large list of predicted target genes of dysregulated miRNAs, we applied a stringent target prediction pipeline integrating probabilities for miRNA-mRNA interaction. The final list of disease-related miRNA-mRNA pairs comprises novel as well as known miRNAs including miR-1 and miR-133, which are essential to cardiac development and function by regulating KCNJ2, FBN2, SLC38A3 and TNNI1. Overall, our study provides additional insights into post-transcriptional gene regulation of malformed hearts of TOF patients.

Biclustering analysis of transcriptome big data identifies condition-specific microRNA targets

We present a novel approach to identify human microRNA (miRNA) regulatory modules (mRNA targets and relevant cell conditions) by biclustering a large collection of mRNA fold-change data for sequence-specific targets. Bicluster targets were assessed using validated messenger RNA (mRNA) targets and exhibited on an average 17.0% (median 19.4%) improved gain in certainty (sensitivity + specificity). The net gain was further increased up to 32.0% (median 33.4%) by incorporating functional networks of targets. We analyzed cancer-specific biclusters and found that the PI3K/Akt signaling pathway is strongly enriched with targets of a few miRNAs in breast cancer and diffuse large B-cell lymphoma. Indeed, five independent prognostic miRNAs were identified, and repression of bicluster targets and pathway activity by miR-29 was experimentally validated. In total, 29 898 biclusters for 459 human miRNAs were collected in the BiMIR database where biclusters are searchable for miRNAs, tissues, diseases, keywords and target genes.

MiR-190a potentially ameliorates postoperative cognitive dysfunction by regulating Tiam1

BACKGROUND

Postoperative cognitive dysfunction (POCD) affects a large number of post-surgery patients, especially for the elderly. However, the etiology of this neurocognitive disorder is largely unknown. Even if several studies have reported a small number of miRNAs as the essential modulatory factors in POCD, these findings are still rather limited. The aim of current study was to screen the POCD-related miRNAs in the hippocampus tissues and investigate the target genes of differentially expressed miRNAs and their biological functions underlying POCD pathophysiology.

METHODS

The miRNA microarray was used to find the abnormal expression of miRNAs in the hippocampus tissues from the POCD model mice to normal mice (Discovery cohort, 3 vs 3). The nominal significant results were validated in an independent sample of hippocampus tissues of 10 mice based on same miRNA microarray (Replication cohort, 5 vs 5). Expression level of the most significantly abnormal miRNA was further validated by real-time quantitative polymerase chain reaction (PCR). To determine the expression pattern among miRNAs and genes and detect the interactions, we conducted a weighted gene co-expression network analysis (WGCNA) in the miRNAs and genes expression data from hippocampus tissue of wild type mice (n = 24). The target genes of miRNAs were predicted using the miRWalk3.0 software. Furthermore, we used the ClueGO software to decipher the pathways network and reveal the biological functions of target genes of miRNAs.

RESULTS

We found that nine miRNAs showed significant associations with POCD in both datasets. Among these miRNAs, mmu-miR-190a-3p was the most significant one. By performing WGCNA analysis, we found 25 co-expression modules, of which mmu-miR-190a-3p was significantly anti-correlated with red module. Moreover, in the red module, 314 genes were significantly enriched in four pathways such as axon guidance and calcium signaling pathway, which are well-documented to be associated with psychiatric disorders and brain development. Also, 169 of the 314 genes were highly correlated with mmu-miR-190a-3p, and four genes (Sphkap, Arhgef25, Tiam1, and Ntrk3) had putative binding sites at 3'-UTR of mmu-miR-190a-3p. Based on protein-protein network analysis, we detected that Tiam1 was a central gene regulated by the mmu-miR-190a-3p.

CONCLUSIONS

Taken together, we conclude that mmu-miR-190a-3p is involved in the etiology of POCD and may serve as a novel predictive indicator for POCD.

Large-scale inference of competing endogenous RNA networks with sparse partial correlation

MOTIVATION

MicroRNAs (miRNAs) are important non-coding post-transcriptional regulators that are involved in many biological processes and human diseases. Individual miRNAs may regulate hundreds of genes, giving rise to a complex gene regulatory network in which transcripts carrying miRNA binding sites act as competing endogenous RNAs (ceRNAs). Several methods for the analysis of ceRNA interactions exist, but these do often not adjust for statistical confounders or address the problem that more than one miRNA interacts with a target transcript.

RESULTS

We present SPONGE, a method for the fast construction of ceRNA networks. SPONGE uses 'multiple sensitivity correlation', a newly defined measure for which we can estimate a distribution under a null hypothesis. SPONGE can accurately quantify the contribution of multiple miRNAs to a ceRNA interaction with a probabilistic model that addresses previously neglected confounding factors and allows fast P-value calculation, thus outperforming existing approaches. We applied SPONGE to paired miRNA and gene expression data from The Cancer Genome Atlas for studying global effects of miRNA-mediated cross-talk. Our results highlight already established and novel protein-coding and non-coding ceRNAs which could serve as biomarkers in cancer.

AVAILABILITY AND IMPLEMENTATION

SPONGE is available as an R/Bioconductor package (doi: 10.18129/B9.bioc.SPONGE).

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

microRNA-16-5p promotes 3T3-L1 adipocyte differentiation through regulating EPT1

Adipogenesis is an organized process of cellular differentiation by which pre-adipocytes differentiate towards mature adipocytes. miR-16-5p has been reported to be involved in cell proliferation, apoptosis, differentiation and angiogenesis. However little is known about miR-16-5p functional role in 3T3-L1 adipocyte differentiation. In this study, we found that miRNA-16-5p was significantly upregulated during 3T3-L1 preadipocytes differentiation towards mature adipocytes. Over-expression of miRNA-16-5p promoted mature adipocytes specific genes expression and fat droplet accumulation in vitro and in vivo. Meanwhile we have identified EPT1 as the target gene of miRNA-16-5p. Taken together, our data provided evidence to support that miRNA-16-5p promotes adipocyte differentiation by suppressing EPT1.

Prediction and Characterization of miRNA/Target Pairs in Non-Model Plants Using RNA-seq

Plant microRNAs (miRNAs) are ∼20- to 24-nucleotide small RNAs that post-transcriptionally regulate gene expression of mRNA targets. Here, we present a workflow to characterize the miRNA transcriptome of a non-model plant, focusing on miRNAs and targets that are differentially expressed under one experimental treatment. We cover RNA-seq experimental design to create paired small RNA and mRNA libraries and perform quality control of raw data, de novo mRNA transcriptome assembly and annotation, miRNA prediction, differential expression, target identification, and functional enrichment analysis. Additionally, we include validation of differential expression and miRNA-induced target cleavage using qRT-PCR and modified RNA ligase-mediated 5' rapid amplification of cDNA ends, respectively. Our procedure relies on freely available software and web resources. It is intended for users that lack programming skills but can navigate a command-line interface. To enable an understanding of formatting requirements and anticipated results, we provide sample RNA-seq data and key input/output files for each stage. © 2019 The Authors. This is an open access article under the terms of the Creative Commons Attribution-NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.

Identifying miRNA-mRNA regulatory relationships in breast cancer with invariant causal prediction

BACKGROUND

microRNAs (miRNAs) regulate gene expression at the post-transcriptional level and they play an important role in various biological processes in the human body. Therefore, identifying their regulation mechanisms is essential for the diagnostics and therapeutics for a wide range of diseases. There have been a large number of researches which use gene expression profiles to resolve this problem. However, the current methods have their own limitations. Some of them only identify the correlation of miRNA and mRNA expression levels instead of the causal or regulatory relationships while others infer the causality but with a high computational complexity. To overcome these issues, in this study, we propose a method to identify miRNA-mRNA regulatory relationships in breast cancer using the invariant causal prediction. The key idea of invariant causal prediction is that the cause miRNAs of their target mRNAs are the ones which have persistent causal relationships with the target mRNAs across different environments.

RESULTS

In this research, we aim to find miRNA targets which are consistent across different breast cancer subtypes. Thus, first of all, we apply the Pam50 method to categorize BRCA samples into different "environment" groups based on different cancer subtypes. Then we use the invariant causal prediction method to find miRNA-mRNA regulatory relationships across subtypes. We validate the results with the miRNA-transfected experimental data and the results show that our method outperforms the state-of-the-art methods. In addition, we also integrate this new method with the Pearson correlation analysis method and Lasso in an ensemble method to take the advantages of these methods. We then validate the results of the ensemble method with the experimentally confirmed data and the ensemble method shows the best performance, even comparing to the proposed causal method.

CONCLUSIONS

This research found miRNA targets which are consistent across different breast cancer subtypes. Further functional enrichment analysis shows that miRNAs involved in the regulatory relationships predicated by the proposed methods tend to synergistically regulate target genes, indicating the usefulness of these methods, and the identified miRNA targets could be used in the design of wet-lab experiments to discover the causes of breast cancer.

TACCO, a Database Connecting Transcriptome Alterations, Pathway Alterations and Clinical Outcomes in Cancers

Because of innumerable cancer sequencing projects, abundant transcriptome expression profiles together with survival data are available from the same patients. Although some expression signatures for prognosis or pathologic staging have been identified from these data, systematically discovering such kind of expression signatures remains a challenge. To address this, we developed TACCO (Transcriptome Alterations in CanCer Omnibus), a database for identifying differentially expressed genes and altered pathways in cancer. TACCO also reveals miRNA cooperative regulations and supports construction of models for prognosis. The resulting signatures have great potential for patient stratification and treatment decision-making in future clinical applications. TACCO is freely available at http://tacco.life.nctu.edu.tw/.

The miR-15a/16 gene cluster in human cancer: A systematic review

MicroRNAs (miRNAs) are an important class of endogenous small noncoding single-stranded RNAs that suppress the expression of their target genes through messenger RNA (mRNA) degradation to inhibit transcription and translation. MiRNAs play a crucial regulatory role in many biological processes including proliferation, metabolism, and cellular malignancy. miR-15a/16 is an important tumor suppressor gene cluster with a variety of factors that regulate its transcriptional activity. It has been discovered that a relative reduction of miR-15a/16 expression in various cancers is closely related to the occurrence and progression of tumors. miR-15a/16 takes part in a wide array of biological processes including tumor cell proliferation, apoptosis, invasion, and chemoresistance by binding to the 3'-untranslated region of its target gene's mRNA. In this review, we will examine the complex regulatory network of miR-15a/16 gene expression and its biological functions in human cancers to further elucidate the molecular mechanisms of its antitumor effects.

Revealing post-transcriptional microRNA-mRNA regulations in Alzheimer's disease through ensemble graphs

BACKGROUND

In silico investigations on the integration of multiple datasets are in need of higher statistical power methods to unveil secondary findings that were hidden from the initial analyses. We present here a novel method for the network analysis of messenger RNA post-translational regulation by microRNA molecules. The method integrates expression data and sequence binding predictions through a set of sound machine learning techniques, forwarding all results to an ensemble graph of regulations.

RESULTS

Bayesian network classifiers are induced based on a pool of ensemble graphs with ascending order of complexity. Individual goodness-of-fit and classification performances are evaluated for each learned model. As a testbed, four Alzheimer's disease datasets are integrated using the new approach, achieving top values of 0.9794 ± 0.01 for the area under the receiver operating characteristic curve and 0.9439 ± 0.0234 for the prediction accuracy.

CONCLUSIONS

Post-transcriptional regulations found by the optimal network classifier concur with previous literature findings. Furthermore, additional network structures suggest previously unreported regulations in the state of the art of Alzheimer's research. The quantitative performance as well as sound biological findings provide confidence in the ensemble approach and encourage similar integrative analyses for other conditions.

Highly focused transcriptional response of Anopheles coluzzii to O'nyong nyong arbovirus during the primary midgut infection

Background

Anopheles mosquitoes are efficient vectors of human malaria, but it is unknown why they do not transmit viruses as well as Aedes and Culex mosquitoes. The only arbovirus known to be consistently transmitted by Anopheles mosquitoes is O’nyong nyong virus (ONNV, genus Alphavirus, family Togaviridae). The interaction of Anopheles mosquitoes with RNA viruses has been relatively unexamined.

Results

We transcriptionally profiled the African malaria vector, Anopheles coluzzii, infected with ONNV. Mosquitoes were fed on an infectious bloodmeal and were analyzed by Illumina RNAseq at 3 days post-bloodmeal during the primary virus infection of the midgut epithelium, before systemic dissemination. Virus infection triggers transcriptional regulation of just 30 host candidate genes. Most of the regulated candidate genes are novel, without known function. Of the known genes, a significant cluster includes candidates with predicted involvement in carbohydrate metabolism. Two candidate genes encoding leucine-rich repeat immune (LRIM) factors point to possible involvement of immune protein complexes in the mosquito antiviral response. The primary ONNV infection by bloodmeal shares little transcriptional response in common with ONNV infection by intrathoracic injection, nor with midgut infection by the malaria parasites, Plasmodium falciparum or P. berghei. Profiling of A. coluzzii microRNA (miRNA) identified 118 known miRNAs and 182 potential novel miRNA candidates, with just one miRNA regulated by ONNV infection. This miRNA was not regulated by other previously reported treatments, and may be virus specific. Coexpression analysis of miRNA abundance and messenger RNA expression revealed discrete clusters of genes regulated by Imd and JAK/STAT, immune signaling pathways that are protective against ONNV in the primary infection.

Conclusions

ONNV infection of the A. coluzzii midgut triggers a remarkably limited gene regulation program of mostly novel candidate genes, which likely includes host genes deployed for antiviral defense, as well as genes manipulated by the virus to facilitate infection. Functional dissection of the ONNV-response candidate genes is expected to generate novel insight into the mechanisms of virus-vector interaction.

Electronic supplementary material

The online version of this article (10.1186/s12864-018-4918-0) contains supplementary material, which is available to authorized users.

Analysis of Purines and Pyrimidines distribution over miRNAs of Human, Gorilla, Chimpanzee, Mouse and Rat

Meaningful words in English need vowels to break up the sounds that consonants make. The Nature has encoded her messages in RNA molecules using only four alphabets A, U, C and G in which the nine member double-ring bases (adenine (A) and Guanine (G)) are purines, while the six member single-ring bases (cytosine (C) and uracil (U)) are pyrimidines. Four bases A, U, C and G of RNA sequences are divided into three kinds of classifications according to their chemical properties. One of the three classifications, the purine-pyrimidine class is important. In understanding the distribution (organization) of purines and pyrimidines over some of the non-coding RNAs, all miRNAs of the three species (human, gorilla and chimpanzee) of Hominidae family and two species (mouse and rat) from of Muridae family are considered. The distribution of purines and pyrimidines over miRNA shows deviation from randomness. Based on the quantitative metrics (fractal dimension, Hurst exponent, Hamming distance, distance pattern of purine-pyrimidine, density distribution of purine-pyrimidine and Shannon entropy) five different clusters have been made for the five species. We have observed some couple of results including the closeness of different clusters among the five species.

Integration of the Pokeweed miRNA and mRNA Transcriptomes Reveals Targeting of Jasmonic Acid-Responsive Genes

The American pokeweed plant, Phytolacca americana, displays broad-spectrum resistance to plant viruses and is a heavy metal hyperaccumulator. However, little is known about the regulation of biotic and abiotic stress responses in this non-model plant. To investigate the control of miRNAs in gene expression, we sequenced the small RNA transcriptome of pokeweed treated with jasmonic acid (JA), a hormone that mediates pathogen defense and stress tolerance. We predicted 145 miRNAs responsive to JA, most of which were unique to pokeweed. These miRNAs were low in abundance and condition-specific, with discrete expression change. Integration of paired mRNA-Seq expression data enabled us to identify correlated, novel JA-responsive targets that mediate hormone biosynthesis, signal transduction, and pathogen defense. The expression of approximately half the pairs was positively correlated, an uncommon finding that we functionally validated by mRNA cleavage. Importantly, we report that a pokeweed-specific miRNA targets the transcript of OPR3, novel evidence that a miRNA regulates a JA biosynthesis enzyme. This first large-scale small RNA study of a Phytolaccaceae family member shows that miRNA-mediated control is a significant component of the JA response, associated with widespread changes in expression of genes required for stress adaptation.

MiR-145 improves macrophage-mediated inflammation through targeting Arf6

PURPOSE

To explore the relationship between miR-145 and ADP ribosylation factor 6 (Arf6) in regulating macrophage-mediated inflammation.

METHODS

THP-1 cells were induced by 160 nM of phorbol 12^-myristate 13-acetate (PMA) for 48 h to differentiate to macrophages and then were treated with LPS (100 ng/ml) for 8 h to simulate chronic metabolic inflammation in vitro. Dual-luciferase reporter assay was performed. MiR-145 siRNA and LV-ARF6-RNAi were used to up or down regulate miR-145 and Arf6 expression in THP-1 cells, respectively. Omental adipose tissue from patients in surgical ward were collected to detect the expression of miR-145, Arf6 and production of proinflammatory cytokines. Patients were divided into three groups according to their body mass index and history of diabetes.

RESULTS

Dual-luciferase reporter assays showed the direct down-regulation of Arf6 by miR-145. Forty-eight-hour-transfection of miR-145 inhibitor resulted in significant increase of Arf6, IL-1beta, TNF-alpha and IL-6 as well as phosphorylation of p65 in NF-kappaB pathway in THP-1 cells, which, inversely, were reversed by overexpressing miR-145. In addition, down-regulation of Arf6 in macrophages reduced expression and secretion of cytokines. Expression of miR-145 was found to be attenuated in the omental adipose tissue of obese patients and diabetics with greater Arf6 expression, confirming the role of miR-145 in regulating macrophage-mediated inflammation targeting Arf6.

CONCLUSIONS

By means of reducing the expression of Arf6 and subsequent signal transduction via NF-kappaB, miR-145 plays a role in inhibiting the secretion of inflammatory factors and then improving the inflammatory status. MiR-145 might be one of the candidates for anti-inflammatory treatment for metabolic diseases.

Inferring MicroRNA Targets Based on Restricted Boltzmann Machines

Predicting the miRNA-target interactions (MTIs) is a critical task for elucidating mechanistic roles of miRNAs in pathophysiology. However, most existing techniques have a higher false positive because the precise miRNA target mechanisms are poorly known. Considering that ensemble methods can take advantage of the complementary knowledge in different methods, we propose an alternative optimization framework, Inferring MiRNA Targets based on Restricted Boltzmann Machines (IMTRBM), to enhance the accuracy of previous prediction results. First, the proposed method directly constructs a weighted MTI network though the results predicted by individual methods and each miRNA target pair is weighted based on the frequency appearing in these results. Second, we transform the miRNA-target prediction problem into a complete bipartite graph model, named restricted Boltzmann machine, and utilize a practical learning procedure to train our model and make predictions. Our results show that the algorithm outperforms individual miRNA-target prediction approach in the number of validated miRNA targets at cutoffs of top list. Moreover, our framework can tolerate the decrease and increase of predicted MTIs and even discover new miRNA targets, which have been a challenge to predict for any individual methods. Finally, for the miRNAs that are not appearing in IMTRBM, we design a new method to supplement IMTRBM based on the intuition that similar miRNAs have similar functions, which also achieves a comparable result. The source code of IMTRBM is available at https://github.com/liuying201705/IMTRBM.

MicroRNA Networks in Breast Cancer Cells

A variety of molecular techniques can be used in order to unravel the molecular composition of cells. In particular, the microarray technology has been used to identify novel biomarkers that may be useful in the diagnosis, prognosis, or treatment of cancer. The microarray technology is ideal for biomarker discovery as it allows for the screening of a large number of molecules at once. In this review, we focus on microRNAs (miRNAs) which are key molecules in cells and regulate gene expression post-transcriptionally. miRNAs are small, single-stranded RNA molecules that bind to complementary mRNAs. Binding of miRNAs to mRNAs leads either to degradation, or translational inhibition of the target mRNA. Roughly one third of all the mRNAs are postulated to be regulated by miRNAs. miRNAs are known to be deregulated in different types of cancer, including breast cancer, and it has been demonstrated that deregulation of several miRNAs can be used as biological markers in cancer. miRNA expression can for example discriminate between normal, benign and malignant breast tissue, and between different breast cancer subtypes.In the post-genomic era, an important task of molecular biology is to understand gene regulation in the context of biological networks. Because miRNAs have such a pronounced role in cells, it is pivotal to understand the mechanisms that underlie their control, and to identify how miRNAs influence cancer development and progression.

Integrated regulatory network reveals novel candidate regulators in the development of negative energy balance in cattle

Negative energy balance (NEB) is an altered metabolic state in modern high-yielding dairy cows. This metabolic state occurs in the early postpartum period when energy demands for milk production and maintenance exceed that of energy intake. Negative energy balance or poor adaptation to this metabolic state has important effects on the liver and can lead to metabolic disorders and reduced fertility. The roles of regulatory factors, including transcription factors (TFs) and micro RNAs (miRNAs) have often been separately studied for evaluating of NEB. However, adaptive response to NEB is controlled by complex gene networks and still not fully understood. In this study, we aimed to discover the integrated gene regulatory networks involved in NEB development in liver tissue. We downloaded data sets including mRNA and miRNA expression profiles related to three and four cows with severe and moderate NEB, respectively. Our method integrated two independent types of information: module inference network by TFs, miRNAs and mRNA expression profiles (RNA-seq data) and computational target predictions. In total, 176 modules were predicted by using gene expression data and 64 miRNAs and 63 TFs were assigned to these modules. By using our integrated computational approach, we identified 13 TF-module and 19 miRNA-module interactions. Most of these modules were associated with liver metabolic processes as well as immune and stress responses, which might play crucial roles in NEB development. Literature survey results also showed that several regulators and gene targets have already been characterized as important factors in liver metabolic processes. These results provided novel insights into regulatory mechanisms at the TF and miRNA levels during NEB. In addition, the method described in this study seems to be applicable to construct integrated regulatory networks for different diseases or disorders.

A causal mediation model of ischemia reperfusion injury in the retina

The goal of this study is to develop a model that explains the relationship between microRNAs, transcription factors, and their co-target genes. This relationship was previously reported in gene regulatory loops associated with 24 hour (24h) and 7 day (7d) time periods following ischemia-reperfusion injury in a rat's retina. Using a model system of retinal ischemia-reperfusion injury, we propose that microRNAs first influence transcription factors, which in turn act as mediators to influence transcription of genes via triadic regulatory loops. Analysis of the relative contributions of direct and indirect regulatory influences on genes revealed that a substantial fraction of the regulatory loops (69% for 24 hours and 77% for 7 days) could be explained by causal mediation. Over 40% of the mediated loops in both time points were regulated by transcription factors only, while about 20% of the loops were regulated entirely by microRNAs. The remaining fractions of the mediated regulatory loops were cooperatively mediated by both microRNAs and transcription factors. The results from these analyses were supported by the patterns of expression of the genes, transcription factors, and microRNAs involved in the mediated loops in both post-ischemic time points. Additionally, network motif detection for the mediated loops showed a handful of time specific motifs related to ischemia-reperfusion injury in a rat's retina. In summary, the effects of microRNAs on genes are mediated, in large part, via transcription factors.

Global miRNA expression analysis identifies novel key regulators of plasma cell differentiation and malignant plasma cell

MicroRNAs (miRNAs) are small noncoding RNAs that attenuate expression of their mRNA targets. Here, we developed a new method and an R package, to easily infer candidate miRNA–mRNA target interactions that could be functional during a given biological process. Using this method, we described, for the first time, a comprehensive integrated analysis of miRNAs and mRNAs during human normal plasma cell differentiation (PCD). Our results reveal 63 miRNAs with significant temporal changes in their expression during normal PCD. We derived a high-confidence network of 295 target relationships comprising 47 miRNAs and 141 targets. These relationships include new examples of miRNAs that appear to coordinately regulate multiple members of critical pathways associated with PCD. Consistent with this, we have experimentally validated a role for the miRNA-30b/c/d-mediated regulation of key PCD factors (IRF4, PRDM1, ELL2 and ARID3A). Furthermore, we found that 24 PCD stage-specific miRNAs are aberrantly overexpressed in multiple myeloma (MM) tumor plasma cells compared to their normal counterpart, suggesting that MM cells frequently acquired expression changes in miRNAs already undergoing dynamic expression modulation during normal PCD. Altogether, our analysis identifies candidate novel key miRNAs regulating networks of significance for normal PCD and malignant plasma cell biology.

Polymorphisms in Non-coding RNA Genes and Their Targets Sites as Risk Factors of Sporadic Colorectal Cancer

Colorectal cancer (CRC) is a complex disease that develops as a consequence of both genetic and environmental risk factors in interplay with epigenetic mechanisms, such as microRNAs (miRNAs). CRC cases are predominantly sporadic in which the disease develops with no apparent hereditary syndrome. The last decade has seen the progress of genome-wide association studies (GWAS) that allowed the discovery of several genetic regions and variants associated with weak effects on sporadic CRC. Collectively these variants may enable a more accurate prediction of an individual's risk to the disease and its prognosis. However, the number of variants contributing to CRC is still not fully explored.SNPs in genes encoding the miRNA sequence or in 3'UTR regions of the corresponding binding sites may affect miRNA transcription, miRNA processing, and/or the fidelity of the miRNA-mRNA interaction. These variants could plausibly impact miRNA expression and target mRNA translation into proteins critical for cellular integrity, differentiation, and proliferation.In the present chapter, we describe the different aspects of variations related to miRNAs and other non-coding RNAs (ncRNAs) and evidence from studies investigating these candidate genetic alterations in support to their role in CRC development and progression.

Independent prognostic miRNAs for bladder urothelial carcinoma

Bladder cancer is the most common malignant tumor of the urinary system, and it is also an important cause of death by cancer globally. Increasing number of studies have shown that miRNAs can be used as prognostic markers for cancers. This study made use of the data available in the Cancer Genome Atlas in order to statistically analyze reported expression levels of miRNAs in samples from bladder urothelial carcinoma patients. Clinical features from a total of 399 patients and the expression data for 1,581 kinds of miRNA were included in the study. Single factor Cox regression analysis was used to identify miRNAs related to survival times for the patients. Then, through multifactors Cox regression we sorted out the independent prognostic miRNAs for the carcinoma. According to our results, 19 miRNAs were closely related to the survival times of patients with bladder urothelial carcinoma, and 3 miRNAs including hsa-mir-518b (p=0.02), hsa-mir-192 (p=0.04) and hsa-mir-7705 (p=0.04) should be useful as independent prognostic factors in patients. In addition, the survival time of those expressing high levels of hsa-mir-7705 and hsa-mir-192 was less than the survival time of those with low expression levels. However, there were no obvious differences in the survival times between high and low expressors of hsa-mir-518b. According to our results, hsa-mir-7705, hsa-mir-192 and hsa-mir-518b can be applied as independent prognostic markers for bladder urothelial carcinoma.

Gene-microRNA network module analysis for ovarian cancer

Background

MicroRNAs (miRNAs) are involved in many biological processes by regulating post-transcriptional gene expression. The alterations of the regulatory pathways can cause different diseases including cancer. Although many works have been done to study the gene-miRNA regulatory network, the intertwined relationship is far from being fully understood. The objective of this study is to integrate both gene expression data and miRNA data so as to explore the complex relationships among them.

Methods

By integrating the networks consisting of gene coexpression, miRNA coexpression, gene-miRNA coexpression, and the known gene-miRNA interactions, we aim to find the most connected network modules so as to study their functions and properties. In this paper, we proposed an optimization model for identification of the modules in the integrated networks. This model tries to find both the modules in the gene-gene and miRNA-miRNA coexpression networks and the densely connected gene-miRNA subneworks. An approximation computational method was developed to solve the optimization problem.

Results

We applied the method to 556 human ovarian cancer samples with both gene expression data and miRNA expression data. The identified modules are significantly enriched by miRNA clusters, GO-BPs, and KEGG pathways. We compared our method with some existing methods and showed the better performance of our method. We also showed that the miRNAs and genes in our identified modules are associated with cancers, especially ovarian cancer.

Conclusions

This study provides strong support that the subnetworks consisting of genes and miRNAs with close interactions contribute the cancers. The proposed computational method can be applied to other studies that are related to different types of networks.

Electronic supplementary material

The online version of this article (doi:10.1186/s12918-016-0357-1) contains supplementary material, which is available to authorized users.

miRNAs in multiple myeloma--a survival relevant complex regulator of gene expression

Purpose

microRNAs regulate gene-expression in biological and pathophysiological processes, including multiple myeloma. Here we address i) What are the number and magnitude of changes in miRNA-expression between normal plasma cells and myeloma- or MGUS-samples, and the latter two? ii) What is the biological relevance and how does miRNA-expression impact on gene-expression? iii) Is there a prognostic significance, and what is its background?

Experimental design

Ninety-two purified myeloma-, MGUS-, normal plasma cell- and myeloma cell line-samples were investigated using miChip-arrays interrogating 559 human miRNAs. Impact on gene-expression was assessed by Affymetrix DNA-microarrays in two cohorts of myeloma patients (n = 677); chromosomal aberrations were assessed by iFISH, survival for 592 patients undergoing up-front high-dose chemotherapy.

Results

Compared to normal plasma cells, 67/559 miRNAs (12%) with fold changes of 4.6 to −3.1 are differentially expressed in myeloma-, 20 (3.6%) in MGUS-samples, and three (0.5%) between MGUS and myeloma. Expression of miRNAs is associated with proliferation, chromosomal aberrations, tumor mass, and gene expression-based risk-scores. This holds true for target-gene signatures of regulated mRNAs. miRNA-expression confers prognostic significance for event-free and overall survival, as do respective target-gene signatures.

Conclusions

The myeloma-miRNome confers a pattern of small changes of individual miRNAs impacting on gene-expression, biological functions, and survival.

Platelets miRNA as a Prediction Marker of Thrombotic Episodes

The blood platelets are crucial for the coagulation physiology to maintain haemostatic balance and are involved in various pathologies such as atherosclerosis and thrombosis. The studies of recent years have shown that anucleated platelets are able to succeed protein synthesis. Additionally, mRNA translation in blood platelets is regulated by miRNA molecules. Recent works postulate the possibility of using miRNAs as biomarkers of atherosclerosis and ischemic episodes. This review article describes clinical studies that presented blood platelets miRNAs expression profile changes in different thrombotic states, which suggest use of these molecules as predictive biomarkers.

Inhibition of fat cell differentiation in 3T3-L1 pre-adipocytes by all-trans retinoic acid: Integrative analysis of transcriptomic and phenotypic data

The process of adipogenesis is controlled in a highly orchestrated manner, including transcriptional and post-transcriptional events. In developing 3T3-L1 pre-adipocytes, this program can be interrupted by all-trans retinoic acid (ATRA). To examine this inhibiting impact by ATRA, we generated large-scale transcriptomic data on the microRNA and mRNA level. Non-coding RNAs such as microRNAs represent a field in RNA turnover, which is very important for understanding the regulation of mRNA gene expression. High throughput mRNA and microRNA expression profiling was performed using mRNA hybridisation microarray technology and multiplexed expression assay for microRNA quantification. After quantitative measurements we merged expression data sets, integrated the results and analysed the molecular regulation of in vitro adipogenesis. For this purpose, we applied local enrichment analysis on the integrative microRNA-mRNA network determined by a linear regression approach. This approach includes the target predictions of TargetScan Mouse 5.2 and 23 pre-selected, significantly regulated microRNAs as well as Affymetrix microarray mRNA data. We found that the cellular lipid metabolism is negatively affected by ATRA. Furthermore, we were able to show that microRNA 27a and/or microRNA 96 are important regulators of gap junction signalling, the rearrangement of the actin cytoskeleton as well as the citric acid cycle, which represent the most affected pathways with regard to inhibitory effects of ATRA in 3T3-L1 preadipocytes. In conclusion, the experimental workflow and the integrative microRNA–mRNA data analysis shown in this study represent a possibility for illustrating interactions in highly orchestrated biological processes. Further the applied global microRNA–mRNA interaction network may also be used for the pre-selection of potential new biomarkers with regard to obesity or for the identification of new pharmaceutical targets.

Prioritizing cancer-related microRNAs by integrating microRNA and mRNA datasets

MicroRNAs (miRNAs) are small non-coding RNAs regulating the expression of target genes, and they are involved in cancer initiation and progression. Even though many cancer-related miRNAs were identified, their functional impact may vary, depending on their effects on the regulation of other miRNAs and genes. In this study, we propose a novel method for the prioritization of candidate cancer-related miRNAs that may affect the expression of other miRNAs and genes across the entire biological network. For this, we propose three important features: the average expression of a miRNA in multiple cancer samples, the average of the absolute correlation values between the expression of a miRNA and expression of all genes, and the number of predicted miRNA target genes. These three features were integrated using order statistics. By applying the proposed approach to four cancer types, glioblastoma, ovarian cancer, prostate cancer, and breast cancer, we prioritized candidate cancer-related miRNAs and determined their functional roles in cancer-related pathways. The proposed approach can be used to identify miRNAs that play crucial roles in driving cancer development, and the elucidation of novel potential therapeutic targets for cancer treatment.

Discovering MicroRNA-Regulatory Modules in Multi-Dimensional Cancer Genomic Data: A Survey of Computational Methods

MicroRNAs (miRs) are small single-stranded noncoding RNA that function in RNA silencing and post-transcriptional regulation of gene expression. An increasing number of studies have shown that miRs play an important role in tumorigenesis, and understanding the regulatory mechanism of miRs in this gene regulatory network will help elucidate the complex biological processes at play during malignancy. Despite advances, determination of miR–target interactions (MTIs) and identification of functional modules composed of miRs and their specific targets remain a challenge. A large amount of data generated by high-throughput methods from various sources are available to investigate MTIs. The development of data-driven tools to harness these multi-dimensional data has resulted in significant progress over the past decade. In parallel, large-scale cancer genomic projects are allowing new insights into the commonalities and disparities of miR–target regulation across cancers. In the first half of this review, we explore methods for identification of pairwise MTIs, and in the second half, we explore computational tools for discovery of miR-regulatory modules in a cancer-specific and pan-cancer context. We highlight strengths and limitations of each of these tools as a practical guide for the computational biologists.

A Meta-Path-Based Prediction Method for Human miRNA-Target Association

MicroRNAs (miRNAs) are short noncoding RNAs that play important roles in regulating gene expressing, and the perturbed miRNAs are often associated with development and tumorigenesis as they have effects on their target mRNA. Predicting potential miRNA-target associations from multiple types of genomic data is a considerable problem in the bioinformatics research. However, most of the existing methods did not fully use the experimentally validated miRNA-mRNA interactions. Here, we developed RMLM and RMLMSe to predict the relationship between miRNAs and their targets. RMLM and RMLMSe are global approaches as they can reconstruct the missing associations for all the miRNA-target simultaneously and RMLMSe demonstrates that the integration of sequence information can improve the performance of RMLM. In RMLM, we use RM measure to evaluate different relatedness between miRNA and its target based on different meta-paths; logistic regression and MLE method are employed to estimate the weight of different meta-paths. In RMLMSe, sequence information is utilized to improve the performance of RMLM. Here, we carry on fivefold cross validation and pathway enrichment analysis to prove the performance of our methods. The fivefold experiments show that our methods have higher AUC scores compared with other methods and the integration of sequence information can improve the performance of miRNA-target association prediction.

Discovering miRNA Regulatory Networks in Holt-Oram Syndrome Using a Zebrafish Model

MicroRNAs (miRNAs) are small non-coding RNAs that play an important role in the post-transcriptional regulation of gene expression. miRNAs are involved in the regulation of many biological processes such as differentiation, apoptosis, and cell proliferation. miRNAs are expressed in embryonic, postnatal, and adult hearts, and they have a key role in the regulation of gene expression during cardiovascular development and disease. Aberrant expression of miRNAs is associated with abnormal cardiac cell differentiation and dysfunction. Tbx5 is a member of the T-box gene family, which acts as transcription factor involved in the vertebrate heart development. Alteration of Tbx5 level affects the expression of hundreds of genes. Haploinsufficiency and gene duplication of Tbx5 are at the basis of the cardiac abnormalities associated with Holt–Oram syndrome (HOS). Recent data indicate that miRNAs might be an important part of the regulatory circuit through which Tbx5 controls heart development. Using high-throughput technologies, we characterized genome-widely the miRNA and mRNA expression profiles in WT- and Tbx5-depleted zebrafish embryos at two crucial developmental time points, 24 and 48 h post fertilization (hpf). We found that several miRNAs, which are potential effectors of Tbx5, are differentially expressed; some of them are already known to be involved in cardiac development and functions, such as miR-30, miR-34, miR-190, and miR-21. We performed an integrated analysis of miRNA expression data with gene expression profiles to refine computational target prediction approaches by means of the inversely correlation of miRNA–mRNA expressions, and we highlighted targets, which have roles in cardiac contractility, cardiomyocyte proliferation/apoptosis, and morphogenesis, crucial functions regulated by Tbx5. This approach allowed to discover complex regulatory circuits involving novel miRNAs and protein coding genes not considered before in the HOS such as miR-34a and miR-30 and their targets.

Statistical Methods in Integrative Genomics

Statistical methods in integrative genomics aim to answer important biology questions by jointly analyzing multiple types of genomic data (vertical integration) or aggregating the same type of data across multiple studies (horizontal integration). In this article, we introduce different types of genomic data and data resources, and then review statistical methods of integrative genomics, with emphasis on the motivation and rationale of these methods. We conclude with some summary points and future research directions.

SePIA: RNA and small RNA sequence processing, integration, and analysis

Background

Large-scale sequencing experiments are complex and require a wide spectrum of computational tools to extract and interpret relevant biological information. This is especially true in projects where individual processing and integrated analysis of both small RNA and complementary RNA data is needed. Such studies would benefit from a computational workflow that is easy to implement and standardizes the processing and analysis of both sequenced data types.

Results

We developed SePIA (Sequence Processing, Integration, and Analysis), a comprehensive small RNA and RNA workflow. It provides ready execution for over 20 commonly known RNA-seq tools on top of an established workflow engine and provides dynamic pipeline architecture to manage, individually analyze, and integrate both small RNA and RNA data. Implementation with Docker makes SePIA portable and easy to run. We demonstrate the workflow’s extensive utility with two case studies involving three breast cancer datasets. SePIA is straightforward to configure and organizes results into a perusable HTML report. Furthermore, the underlying pipeline engine supports computational resource management for optimal performance.

Conclusion

SePIA is an open-source workflow introducing standardized processing and analysis of RNA and small RNA data. SePIA’s modular design enables robust customization to a given experiment while maintaining overall workflow structure. It is available at http://anduril.org/sepia.

Electronic supplementary material

The online version of this article (doi:10.1186/s13040-016-0099-z) contains supplementary material, which is available to authorized users.

Integrated analysis of miRNA and mRNA expression profiles in tilapia gonads at an early stage of sex differentiation

Background

MicroRNAs (miRNAs) represent a second regulatory network that has important effects on gene expression and protein translation during biological process. However, the possible role of miRNAs in the early stages of fish sex differentiation is not well understood. In this study, we carried an integrated analysis of miRNA and mRNA expression profiles to explore their possibly regulatory patterns at the critical stage of sex differentiation in tilapia.

Results

We identified 279 pre-miRNA genes in tilapia genome, which were highly conserved in other fish species. Based on small RNA library sequencing, we identified 635 mature miRNAs in tilapia gonads, in which 62 and 49 miRNAs showed higher expression in XX and XY gonads, respectively. The predicted targets of these sex-biased miRNAs (e.g., miR-9, miR-21, miR-30a, miR-96, miR-200b, miR-212 and miR-7977) included genes encoding key enzymes in steroidogenic pathways (Cyp11a1, Hsd3b, Cyp19a1a, Hsd11b) and key molecules involved in vertebrate sex differentiation (Foxl2, Amh, Star1, Sf1, Dmrt1, and Gsdf). These genes also showed sex-biased expression in tilapia gonads at 5 dah. Some miRNAs (e.g., miR-96 and miR-737) targeted multiple genes involved in steroid synthesis, suggesting a complex miRNA regulatory network during early sex differentiation in this fish.

Conclusions

The sequence and expression patterns of most miRNAs in tilapia are conserved in fishes, indicating the basic functions of vertebrate miRNAs might share a common evolutionary origin. This comprehensive analysis of miRNA and mRNA at the early stage of molecular sex differentiation in tilapia XX and XY gonads lead to the discovery of differentially expressed miRNAs and their putative targets, which will facilitate studies of the regulatory network of molecular sex determination and differentiation in fishes.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-016-2636-z) contains supplementary material, which is available to authorized users.

Cell-type-specific miR-431 dysregulation in a motor neuron model of spinal muscular atrophy

Spinal muscular atrophy (SMA) is an autosomal-recessive pediatric neurodegenerative disease characterized by selective loss of spinal motor neurons. It is caused by mutation in the survival of motor neuron 1, SMN1, gene and leads to loss of function of the full-length SMN protein. microRNAs (miRNAs) are small RNAs that are involved in post-transcriptional regulation of gene expression. Prior studies have implicated miRNAs in the pathogenesis of motor neuron disease. We hypothesized that motor neuron-specific miRNA expression changes are involved in their selective vulnerability in SMA. Therefore, we sought to determine the effect of SMN loss on miRNAs and their target mRNAs in spinal motor neurons. We used microarray and RNAseq to profile both miRNA and mRNA expression in primary spinal motor neuron cultures after acute SMN knockdown. By integrating the miRNA:mRNA profiles, a number of dysregulated miRNAs were identified with enrichment in differentially expressed putative mRNA targets. miR-431 expression was highly increased, and a number of its putative mRNA targets were significantly downregulated in motor neurons after SMN loss. Further, we found that miR-431 regulates motor neuron neurite length by targeting several molecules previously identified to play a role in motor neuron axon outgrowth, including chondrolectin. Together, our findings indicate that cell-type-specific dysregulation of miR-431 plays a role in the SMA motor neuron phenotype.

De novo assembly of the blunt snout bream (Megalobrama amblycephala) gill transcriptome to identify ammonia exposure associated microRNAs and their targets

De novo transcriptome sequencing is a robust method for microRNA (miRNA) target gene prediction, especially for organisms without reference genomes. Following exposure of Megalobrama amblycephala to ammonia (0.1 or 20 mg L⁻¹ ), two cDNA libraries were constructed from the fish gills and sequenced using Illumina HiSeq 2000. Over 90 million reads were generated and de novo assembled into 46, 615 unigenes, which were then extensively annotated by comparing to different protein databases, followed by biochemical pathway prediction. The expression of 2666 unigenes significantly differed; 1961 were up-regulated, while 975 were down-regulated. Among these, 250 unigenes were identified as the targets for 10 conserved and 4 putative novel miRNA families by miRNA target computational prediction. We examined expression of ssa-miRNA-21 and its target genes by real-time quantitative PCR and found agreement with the sequencing data. This study demonstrates the feasibility of identifying miRNA targets by transcriptome analysis. The transcriptome assembly data represent a substantial increase in the genomic resources available for Megalobrama amblycephala and will be useful for gene expression profile analysis and miRNA functional annotation.

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Several differentially expressed genes and miRNA were identified.

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Target prediction indicated that a number of miRNAs involved in immunity.

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The study provides an understanding of molecular mechanisms of ammonia-induced toxicology in fish.

Ammonia-induced miRNA expression changes in cultured rat astrocytes

Hepatic encephalopathy is a neuropsychiatric syndrome evolving from cerebral osmotic disturbances and oxidative/nitrosative stress. Ammonia, the main toxin of hepatic encephalopathy, triggers astrocyte senescence in an oxidative stress-dependent way. As miRNAs are critically involved in cell cycle regulation and their expression may be regulated by oxidative stress, we analysed, whether astrocyte senescence is a consequence of ammonia-induced miRNA expression changes. Using a combined miRNA and gene microarray approach, 43 miRNA species which were downregulated and 142 genes which were upregulated by NH₄Cl (5 mmol/l, 48 h) in cultured rat astrocytes were found. Ammonia-induced miRNA and gene expression changes were validated by qPCR and 43 potential miRNA target genes, including HO-1, were identified by matching upregulated mRNA species with predicted targets of miRNA species downregulated by ammonia. Inhibition of HO-1 targeting miRNAs which were downregulated by NH₄Cl strongly upregulated HO-1 mRNA and protein levels and inhibited astrocyte proliferation in a HO-1-dependent way. Preventing ammonia-induced upregulation of HO-1 by taurine (5 mmol/l) as well as blocking HO-1 activity by tin-protoporphyrine IX fully prevented ammonia-induced proliferation inhibition and senescence. The data suggest that ammonia induces astrocyte senescence through NADPH oxidase-dependent downregulation of HO-1 targeting miRNAs and concomitant upregulation of HO-1 at both mRNA and protein level.