A pattern-based method for the identification of MicroRNA binding sites and their corresponding heteroduplexes

MicroRNA-deficient Schwann cells display congenital hypomyelination

MicroRNAs, by modulating gene expression, have been implicated as regulators of various cellular and physiological processes, including differentiation, proliferation, and cancer. Here, we study the role of microRNAs in Schwann cell (SC) differentiation by conditional removal of the microRNA processing enzyme Dicer1. We reveal that both male and female mice lacking Dicer1 in SC (Dicer1 conditional knock-outs) display a severe neurological phenotype resembling congenital hypomyelination. Ultrastructural analyses show that many SC lacking Dicer1 are stalled in differentiation at the promyelinating state and fail to myelinate axons. Gene expression analyses reveal a failure to extinguish genes characteristic of the undifferentiated state such as Sox2, Jun, and Ccnd1. Sox2 and Jun are well characterized negative regulators of SC differentiation. Consistent with Sox2/Jun maintenance, Egr2, a master regulator of the myelinating program, is drastically downregulated and likely accounts for the myelination defect. We posit a model wherein microRNAs are critical for downregulation of antecedent programs of gene expression. In SC differentiation, this is particularly relevant in the key developmental transition from a promyelinating to myelinating SC.

TargetSpy: a supervised machine learning approach for microRNA target prediction

Background

Virtually all currently available microRNA target site prediction algorithms require the presence of a (conserved) seed match to the 5' end of the microRNA. Recently however, it has been shown that this requirement might be too stringent, leading to a substantial number of missed target sites.

Results

We developed TargetSpy, a novel computational approach for predicting target sites regardless of the presence of a seed match. It is based on machine learning and automatic feature selection using a wide spectrum of compositional, structural, and base pairing features covering current biological knowledge. Our model does not rely on evolutionary conservation, which allows the detection of species-specific interactions and makes TargetSpy suitable for analyzing unconserved genomic sequences.

In order to allow for an unbiased comparison of TargetSpy to other methods, we classified all algorithms into three groups: I) no seed match requirement, II) seed match requirement, and III) conserved seed match requirement. TargetSpy predictions for classes II and III are generated by appropriate postfiltering. On a human dataset revealing fold-change in protein production for five selected microRNAs our method shows superior performance in all classes. In Drosophila melanogaster not only our class II and III predictions are on par with other algorithms, but notably the class I (no-seed) predictions are just marginally less accurate. We estimate that TargetSpy predicts between 26 and 112 functional target sites without a seed match per microRNA that are missed by all other currently available algorithms.

Conclusion

Only a few algorithms can predict target sites without demanding a seed match and TargetSpy demonstrates a substantial improvement in prediction accuracy in that class. Furthermore, when conservation and the presence of a seed match are required, the performance is comparable with state-of-the-art algorithms. TargetSpy was trained on mouse and performs well in human and drosophila, suggesting that it may be applicable to a broad range of species. Moreover, we have demonstrated that the application of machine learning techniques in combination with upcoming deep sequencing data results in a powerful microRNA target site prediction tool http://www.targetspy.org.

MicroRNA networks in mouse lung organogenesis

BACKGROUND

MicroRNAs (miRNAs) are known to be important regulators of both organ development and tumorigenesis. MiRNA networks and their regulation of messenger RNA (mRNA) translation and protein expression in specific biological processes are poorly understood.

METHODS

We explored the dynamic regulation of miRNAs in mouse lung organogenesis. Comprehensive miRNA and mRNA profiling was performed encompassing all recognized stages of lung development beginning at embryonic day 12 and continuing to adulthood. We analyzed the expression patterns of dynamically regulated miRNAs and mRNAs using a number of statistical and computational approaches, and in an integrated manner with protein levels from an existing mass-spectrometry derived protein database for lung development.

RESULTS

In total, 117 statistically significant miRNAs were dynamically regulated during mouse lung organogenesis and clustered into distinct temporal expression patterns. 11,220 mRNA probes were also shown to be dynamically regulated and clustered into distinct temporal expression patterns, with 3 major patterns accounting for 75% of all probes. 3,067 direct miRNA-mRNA correlation pairs were identified involving 37 miRNAs. Two defined correlation patterns were observed upon integration with protein data: 1) increased levels of specific miRNAs directly correlating with downregulation of predicted mRNA targets; and 2) increased levels of specific miRNAs directly correlating with downregulation of translated target proteins without detectable changes in mRNA levels. Of 1345 proteins analyzed, 55% appeared to be regulated in this manner with a direct correlation between miRNA and protein level, but without detectable change in mRNA levels.

CONCLUSION

Systematic analysis of microRNA, mRNA, and protein levels over the time course of lung organogenesis demonstrates dynamic regulation and reveals 2 distinct patterns of miRNA-mRNA interaction. The translation of target proteins affected by miRNAs independent of changes in mRNA level appears to be a prominent mechanism of developmental regulation in lung organogenesis.

MicroRNA-21 and microRNA-148a contribute to DNA hypomethylation in lupus CD4+ T cells by directly and indirectly targeting DNA methyltransferase 1

Systemic lupus erythematosus is a complex autoimmune disease caused by genetic and epigenetic alterations. DNA methylation abnormalities play an important role in systemic lupus erythematosus disease processes. MicroRNAs (miRNAs) have been implicated as fine-tuning regulators controlling diverse biological processes at the level of posttranscriptional repression. Dysregulation of miRNAs has been described in various disease states, including human lupus. Whereas previous studies have shown miRNAs can regulate DNA methylation by targeting the DNA methylation machinery, the role of miRNAs in aberrant CD4+ T cell DNA hypomethylation of lupus is unclear. In this study, by using high-throughput microRNA profiling, we identified that two miRNAs (miR-21 and miR-148a) overexpressed in CD4+ T cells from both patients with lupus and lupus-prone MRL/lpr mice, which promote cell hypomethylation by repressing DNA methyltransferase 1 (DNMT1) expression. This in turn leads to the overexpression of autoimmune-associated methylation-sensitive genes, such as CD70 and LFA-1, via promoter demethylation. Further experiments revealed that miR-21 indirectly downregulated DNMT1 expression by targeting an important autoimmune gene, RASGRP1, which mediated the Ras-MAPK pathway upstream of DNMT1; miR-148a directly downregulated DNMT1 expression by targeting the protein coding region of its transcript. Additionally, inhibition of miR-21 and miR-148a expression in CD4+ T cells from patients with lupus could increase DNMT1 expression and attenuate DNA hypomethylation. Together, our data demonstrated a critical functional link between miRNAs and the aberrant DNA hypomethylation in lupus CD4+ T cells and could help to develop new therapeutic approaches.

Individual microRNAs (miRNAs) display distinct mRNA targeting "rules"

MicroRNAs (miRNAs) guide Argonaute (AGO)-containing microribonucleoprotein (miRNP) complexes to target mRNAs.It has been assumed that miRNAs behave similarly to each other with regard to mRNA target recognition. The usual assumptions, which are based on prior studies, are that miRNAs target preferentially sequences in the 3'UTR of mRNAs,guided by the 5' "seed" portion of the miRNAs. Here we isolated AGO- and miRNA-containing miRNPs from human H4 tumor cells by co-immunoprecipitation (co-IP) with anti-AGO antibody. Cells were transfected with miR-107, miR-124,miR-128, miR-320, or a negative control miRNA. Co-IPed RNAs were subjected to downstream high-density Affymetrix Human Gene 1.0 ST microarray analyses using an assay we validated previously-a "RIP-Chip" experimental design. RIP-Chip data provided a list of mRNAs recruited into the AGO-miRNP in correlation to each miRNA. These experimentally identified miRNA targets were analyzed for complementary six nucleotide "seed" sequences within the transfected miRNAs. We found that miR-124 targets tended to have sequences in the 3'UTR that would be recognized by the 5' seed of miR-124, as described in previous studies. By contrast, miR-107 targets tended to have 'seed' sequences in the mRNA open reading frame, but not the 3' UTR. Further, mRNA targets of miR-128 and miR-320 are less enriched for 6-mer seed sequences in comparison to miR-107 and miR-124. In sum, our data support the importance of the 5' seed in determining binding characteristics for some miRNAs; however, the "binding rules" are complex, and individual miRNAs can have distinct sequence determinants that lead to mRNA targeting.

Computational methods for the identification of microRNA targets

MicroRNAs are pivotal regulators of development and cellular homeostasis. They act as post-transcriptional regulators, which control the stability and translation efficiency of their target mRNAs. The prediction of microRNA targets and detection of microRNA-mRNA regulatory modules (MRMs) are crucial components for understanding of microRNA functions. Numerous computational methods for microRNA target prediction have been developed. Computationally-predicted targets have been recently used in the integrative analysis of microRNA and mRNA expression analysis to identify microRNA targets and MRMs. In this article we review these recent developments in the integrative analysis methods. We also discuss the remaining challenges and our insights on future directions.

MicroRNA: A matter of life or death

Progressive cell loss due to apoptosis is a pathological hallmark implicated in a wide spectrum of degenerative diseases such as heart disease, atherosclerotic arteries and hypertensive vessels, Alzheimer's disease and other neurodegenerative disorders. Tremendous efforts have been made to improve our understanding of the molecular mechanisms and signaling pathways involved in apoptosistic cell death. Once ignored completely or overlooked as cellular detritus, microRNAs (miRNAs) that were discovered only a decade ago, have recently taken many by surprise. The importance of miRNAs has steadily gained appreciation and miRNA biology has exploded into a massive swell of interest with enormous range and potential in almost every biological discipline because of their widespread expression and diverse functions in both animals and humans. It has been established that miRNAs are critical regulators of apoptosis of various cell types. These small molecules act by repressing the expression of either the proapoptotic or antiapoptotic genes to produce antiapoptotic or proapoptotic effects. Appealing evidence has been accumulating for the involvement of miRNAs in human diseases associated with apoptotic cell death and the potential of miRNAs as novel therapeutic targets for the treatment of the diseases. This editorial aims to convey this message and to boost up the research interest by providing a timely, comprehensive overview on regulation of apoptosis by miRNAs and a synopsis on the pathophysiologic implications of this novel regulatory network based on the currently available data in the literature. It begins with a brief introduction to apoptosis and miRNAs, followed by the description of the fundamental aspects of miRNA biogenesis and action, and the role of miRNAs in regulating apoptosis of cancer cells and cardiovascular cells. Speculations on the development of miRNAs as potential therapeutic targets are also presented. Remarks are also provided to point out the unanswered questions and to outline the new directions for the future research of the field.

The code within the code: microRNAs target coding regions

The coding sequence of a protein must contain the information required for the canonical amino acid sequence. However, the redundancy of the genetic code creates potential for embedding other types of information within coding regions as well. In a genome-wide computational screen for functional motifs within coding regions based on evolutionary conservation, highly conserved motifs included some expected motifs, some novel motifs and coding region target sites for known microRNAs, which are generally presumed to target 3' untranslated regions (UTRs) (www.SiteSifter.org). We report here an analysis of published proteomics experiments that further support a functional role for coding region microRNA binding sites, though the effects are weaker than for sites in the 3' UTR. We also demonstrate a positional bias with greater conservation for sites at the end of the coding region, and the beginning and end of the 3' UTR. An increased effectiveness of microRNA binding sites at the 3' end of transcripts could reflect proximity to the poly(A) tail or interactions with the 5' terminal 7mGpppN "cap", which is physically adjacent to this region once the message is circularized. The effectiveness of 3' UTR sites could reflect a cooperative role for RNA binding proteins. Finally, increased microRNA conservation near the stop codon suggests to us the possible involvement of proteins that execute nonsense-mediated decay, since this process is activated by tagging of termination codons with factors that induce transcript degradation.

Computational methodologies for studying non-coding RNAs relevant to central nervous system function and dysfunction

Non-coding RNAs (ncRNAs) are a large and diverse group of transcripts that span the eukaryotic genome, of which less than 2% encodes proteins. Several distinct families of ncRNAs have been described and implicated in many aspects of central nervous system (CNS) function including translation, RNA metabolism, gene regulation, and development. The need to distinguish ncRNAs from sequence data, as well as potentially uncovering novel ncRNA families, has ignited the development of customized computational approaches and bioinformatic resources to handle these tasks. In this review, we provide an overview of the numerous procedures developed to predict ncRNAs based on their primary sequence and predicted secondary structure. These methodologies are broadly grouped into genome scanning algorithms, mixed approaches, and machine learning algorithms. Regulatory ncRNAs, particularly microRNAs (miRNAs), are a major focus of current research efforts and this review will therefore center on the prediction of miRNAs and the putative gene targets they act upon. With the advent of ultra high-throughput sequencing technologies 'deep sequencing' has emerged as the cutting-edge method for ncRNA identification and we will also touch on some computational resources that play a key role in analysis of this type of data.

Intronic microRNAs support their host genes by mediating synergistic and antagonistic regulatory effects

BACKGROUND

MicroRNA-mediated control of gene expression via translational inhibition has substantial impact on cellular regulatory mechanisms. About 37% of mammalian microRNAs appear to be located within introns of protein coding genes, linking their expression to the promoter-driven regulation of the host gene. In our study we investigate this linkage towards a relationship beyond transcriptional co-regulation.

RESULTS

Using measures based on both annotation and experimental data, we show that intronic microRNAs tend to support their host genes by regulation of target gene expression with significantly correlated expression patterns. We used expression data of three differentiating cell types and compared gene expression profiles of host and target genes. Many microRNA target genes show expression patterns significantly correlated with the expressions of the microRNA host genes. By calculating functional similarities between host and predicted microRNA target genes based on GO annotations, we confirm that many microRNAs link host and target gene activity in an either synergistic or antagonistic manner.

CONCLUSIONS

These two regulatory effects may result from fine tuning of target gene expression functionally related to the host or knock-down of remaining opponent target gene expression. This finding allows to extend the common practice of mapping large scale gene expression data to protein associated genes with functionality of co-expressed intronic microRNAs.

Gain of miR-151 on chromosome 8q24.3 facilitates tumour cell migration and spreading through downregulating RhoGDIA

Recurrent chromosomal aberrations are often observed in hepatocellular carcinoma (HCC), but little is known about the functional non-coding sequences, particularly microRNAs (miRNAs), at the chromosomal breakpoints in HCC. Here we show that 22 miRNAs are often amplified or deleted in HCC. MicroRNA-151 (miR-151), a frequently amplified miRNA on 8q24.3, is correlated with intrahepatic metastasis of HCC. We further show that miR-151, which is often expressed together with its host gene FAK, encoding focal adhesion kinase, significantly increases HCC cell migration and invasion in vitro and in vivo, mainly through miR-151-5p, but not through miR-151-3p. Moreover, miR-151 exerts this function by directly targeting RhoGDIA, a putative metastasis suppressor in HCC, thus leading to the activation of Rac1, Cdc42 and Rho GTPases. In addition, miR-151 can function synergistically with FAK to enhance HCC cell motility and spreading. Thus, our findings indicate that chromosome gain of miR-151 is a crucial stimulus for tumour invasion and metastasis of HCC.

Single-nucleotide polymorphisms inside microRNA target sites influence tumor susceptibility

Single-nucleotide polymorphisms (SNP) associated with polygenetic disorders, such as breast cancer (BC), can create, destroy, or modify microRNA (miRNA) binding sites; however, the extent to which SNPs interfere with miRNA gene regulation and affect cancer susceptibility remains largely unknown. We hypothesize that disruption of miRNA target binding by SNPs is a widespread mechanism relevant to cancer susceptibility. To test this, we analyzed SNPs known to be associated with BC risk, in silico and in vitro, for their ability to modify miRNA binding sites and miRNA gene regulation and referred to these as target SNPs. We identified rs1982073-TGFB1 and rs1799782-XRCC1 as target SNPs, whose alleles could modulate gene expression by differential interaction with miR-187 and miR-138, respectively. Genome-wide bioinformatics analysis predicted approximately 64% of transcribed SNPs as target SNPs that can modify (increase/decrease) the binding energy of putative miRNA::mRNA duplexes by >90%. To assess whether target SNPs are implicated in BC susceptibility, we conducted a case-control population study and observed that germline occurrence of rs799917-BRCA1 and rs334348-TGFR1 significantly varies among populations with different risks of developing BC. Luciferase activity of target SNPs, allelic variants, and protein levels in cancer cell lines with different genotypes showed differential regulation of target genes following overexpression of the two interacting miRNAs (miR-638 and miR-628-5p). Therefore, we propose that transcribed target SNPs alter miRNA gene regulation and, consequently, protein expression, contributing to the likelihood of cancer susceptibility, by a novel mechanism of subtle gene regulation.

Dysregulation of kallikrein-related peptidases in renal cell carcinoma: potential targets of miRNAs

Renal cell carcinoma (RCC) accounts for 3% of all adult malignancies and currently no diagnostic marker exists. Kallikrein-related peptidases (KLKs) have been implicated in numerous cancers including ovarian, prostate, and breast carcinoma. KLKs 5, 6, 10, and 11 have decreased expression in RCC when compared to normal kidney tissue. Our bioinformatic analysis indicated that theKLK 1,6, and7genes have decreased expression in RCC. We experimentally verified these results and found that decreased expression ofKLKs 1and3were significantly associated with the clear cell RCC subtype (p<0.001). An analysis of miRNAs differentially expressed in RCC showed that 61 of the 117 miRNAs that were reported to be dysregulated in RCC were predicted to target KLKs. We experimentally validated two targets using two independent approaches. Transfection of miR-224 into HEK-293 cells resulted in decreased KLK1 protein levels. A luciferase assay demonstrated that hsa-let-7f can target KLK10 in the RCC cell line ACHN. Our results, showing differential expression of KLKs in RCC, suggest that KLKs could be novel diagnostic markers for RCC and that their dysregulation could be under miRNA control. The observation that KLKs could represent targets for miRNAs suggests a post-transcriptional regulatory mechanism with possible future therapeutic applications.

Interpretation and applicability of microRNA data to the context of Alzheimer's and age-related diseases

Generated by the ribonuclease III Dicer, microRNAs (miRNAs) are predicted to regulate up to 90% of the genes in humans, suggesting that they may control every cellular processes in all cells and tissues of the human body! Likely to play a central role in health and disease, a dysfunctional miRNA-based regulation of gene expression may represent the main etiologic factor underlying age-related diseases affecting major organs, such as the brain. Here, we discuss some of the limitations associated to the interpretation and applicability of miRNA data, based on our recent study on the etiology of Alzheimer's disease (AD). Using transiently transfected murine neuronal N2a cells in culture, in parallel to a mouse model of AD, we were able to demonstrate a role for two miRNAs (miR-298 and miR-328) in the regulation of ß-amyloid (Aß) precursor protein (APP)-converting enzyme (BACE) messenger RNA (mRNA) translation, thereby providing key insights into the molecular basis underlying BACE deregulation in AD. However, whether miRNA data can be extrapolated and transposed to the human context of age-related diseases, such as AD, not only requires caution, but also warrants several considerations.

Three dysregulated miRNAs control kallikrein 10 expression and cell proliferation in ovarian cancer

BACKGROUND

Kallikrein-related peptidases (KLKs) are a family of serine proteases that have been shown to be dysregulated in several malignancies including ovarian cancer. The control of kallikrein genes and their physiological function in cancer is not well understood. We hypothesized that microRNAs (miRNAs) represent a novel mechanism for post-transcriptional control of KLK expression in cancer.

METHODS

We first analysed miRNA expression in ovarian cancer in silico. A total of 98 miRNAs were reported to have altered expression in ovarian cancer. Three of these miRNAs were predicted to target KLK10. We experimentally verified the predicted miR-KLK10 interaction using two independent techniques, a luciferase assay with a construct containing the KLK10 3' untranslated region (UTR), pMIR-KLK10, and measuring KLK10 protein levels after transfection with miRNA.

RESULTS

When we co-transfected cells with pMIR-KLK10 and either let-7f, miR-224, or mR-516a, we saw decreased luciferase signal, suggesting that these miRNAs can target KLK10. We then examined the effect of these three miRNAs on KLK10 protein expression and cell growth. Transfection of all miRNAs, let-7f, miR-224, and miR-516a led to a decrease in protein expression and cellular growth. This effect was shown to be dose dependent. The KLK10 protein levels were partially restored by co-transfecting let-7f and its inhibitor. In addition, there was a slight decrease in KLK10 mRNA expression after transfection with let-7f.

CONCLUSION

Our results confirm that KLKs can be targeted by more than one miRNA. Increased expression of certain miRNAs in ovarian cancer can lead to decreased KLK protein expression and subsequently have a negative effect on cell proliferation. This dose-dependent effect suggests that a 'tweaking' or 'fine-tuning' mechanism exists in which the expression of one KLK can be controlled by multiple miRNAs. These data together suggest that miRNA may be used as potential therapeutic options and further studies are required.

A dictionary on microRNAs and their putative target pathways

While in the last decade mRNA expression profiling was among the most popular research areas, over the past years the study of non-coding RNAs, especially microRNAs (miRNAs), has gained increasing interest. For almost 900 known human miRNAs hundreds of pretended targets are known. However, there is only limited knowledge about putative systemic effects of changes in the expression of miRNAs and their regulatory influence. We determined for each known miRNA the biochemical pathways in the KEGG and TRANSPATH database and the Gene Ontology categories that are enriched with respect to its target genes. We refer to these pathways and categories as target pathways of the corresponding miRNA. Investigating target pathways of miRNAs we found a strong relation to disease-related regulatory pathways, including mitogen-activated protein kinase (MAPK) signaling cascade, Transforming growth factor (TGF)-beta signaling pathway or the p53 network. Performing a sophisticated analysis of differentially expressed genes of 13 cancer data sets extracted from gene expression omnibus (GEO) showed that targets of specific miRNAs were significantly deregulated in these sets. The respective miRNA target analysis is also a novel part of our gene set analysis pipeline GeneTrail. Our study represents a comprehensive theoretical analysis of the relationship between miRNAs and their predicted target pathways. Our target pathways analysis provides a ‘miRNA-target pathway’ dictionary, which enables researchers to identify target pathways of differentially regulated miRNAs.

Discovery of novel microRNAs in female reproductive tract using next generation sequencing

MicroRNAs (miRNAs) are small non-coding RNAs that mediate post-transcriptional gene silencing. Over 700 human miRNAs have currently been identified, many of which are mutated or de-regulated in diseases. Here we report the identification of novel miRNAs through deep sequencing the small RNAome (<30 nt) of over 100 tissues or cell lines derived from human female reproductive organs in both normal and disease states. These specimens include ovarian epithelium and ovarian cancer, endometrium and endometriomas, and uterine myometrium and uterine smooth muscle tumors. Sequence reads not aligning with known miRNAs were each mapped to the genome to extract flanking sequences. These extended sequence regions were folded in silico to identify RNA hairpins. Sequences demonstrating the ability to form a stem loop structure with low minimum free energy (<-25 kcal) and predicted Drosha and Dicer cut sites yielding a mature miRNA sequence matching the actual sequence were considered putative novel miRNAs. Additional confidence was achieved when putative novel hairpins assembled a collection of sequences highly similar to the putative mature miRNA but with heterogeneous 3'-ends. A confirmed novel miRNA fulfilled these criteria and had its "star" sequence in our collection. We found 7 distinct confirmed novel miRNAs, and 51 additional novel miRNAs that represented highly confident predictions but without detectable star sequences. Our novel miRNAs were detectable in multiple samples, but expressed at low levels and not specific to any one tissue or cell type. To date, this study represents the largest set of samples analyzed together to identify novel miRNAs.

Insights into the regulation of a common variant of HMGA2 associated with human height during embryonic development

Early genetic studies in the mouse and chicken identified the HMGA oncogene as a candidate that regulates body height. Subsequent genome-wide SNP studies revealed a significant association of rs1042725 genotypes CT and CC in the 3' UTR of HMGA2 with human height. Together, these studies indicated that HMGA2 expression levels during prenatal development might be a critical factor that contributes to the height phenotype. In the present study, we sought to gain insight into the regulation of HMGA2 during human embryonic development and provide evidence that the rs1042725 genotype is unlikely to affect HMGA2 levels in pluripotent human embryonic stem cells (hESCs). This implies that hESCs in the inner cell mass of blastocysts are most likely not involved in determining the human height phenotype associated with this SNP. By applying a computational approach and cell-based reporter assays, we then identified miR-196b as a candidate microRNA that could contribute to SNP-specific expression of HMGA2 during human prenatal development. We briefly discuss this result in the context of other known functions for miR-196b during vertebrate development.

MicroRNAs--targeting and target prediction

MicroRNAs (miRNAs) are a class of small noncoding RNAs that can regulate many genes by base pairing to sites in mRNAs. The functionality of miRNAs overlaps that of short interfering RNAs (siRNAs), and many features of miRNA targeting have been revealed experimentally by studying miRNA-mimicking siRNAs. This review outlines the features associated with animal miRNA targeting and describes currently available prediction tools.

MicroRNAs in cardiac remodeling and disease

MicroRNAs (miRNAs) are a large sub-group of small non-coding RNAs, which have been demonstrated to post-transcriptionally regulate the expression of protein-coding genes in a wide-range biological process. miRNAs have been shown to be essential for normal heart development and cardiac function. Recent data suggest that miRNAs are involved in the etiology of cardiac disease and the remodeling of hearts, including cardiac hypertrophy, myocardial infarction, and cardiac arrhythmias. In this review, we focus on the recent progress in the understanding of the function of miRNAs in cardiac remodeling and disease. We will also discuss the diagnostic and therapeutic potential of miRNAs in heart disease.

MicroRNA-370 controls the expression of microRNA-122 and Cpt1alpha and affects lipid metabolism

We previously observed that treatment of mice with a dominant negative form of cJun (dn-cJun) increased the expression of genes involved in lipid metabolism and modulated the expression of nine microRNAs (miR). To investigate the potential effect of these miRs on the expression of the genes of lipid metabolism, we performed studies in cultured HepG2 cells. Transfection of HepG2 cells with sense or antisense miR-370 or miR-122 upregulated and downregulated, respectively, the transcription factor sterol-regulatory element binding protein 1c (SREBP-1c) and the enzymes diacylglycerol acyltransferase-2 (DGAT2), fatty acid synthase (FAS), and acyl-CoA carboxylase 1 (ACC1) that regulate fatty acid and triglyceride biosynthesis. The other seven miRs identified by the miR array screening did not affect the expression of lipogenic genes. miR-370 upregulated the expression of miR-122. Furthermore, the effect of miR-370 on the expression of the lipogenic genes was abolished by antisense miR-122. miR-370 targets the 3' untranslated region (UTR) of Cpt1alpha, and it downregulated the expression of the carnitine palmitoyl transferase 1alpha (Cpt1alpha) gene as well as the rate of beta oxidation. Our data suggest that miR-370 acting via miR-122 may have a causative role in the accumulation of hepatic triglycerides by modulating initially the expression of SREBP-1c, DGAT2, and Cpt1alpha and, subsequently, the expression of other genes that affect lipid metabolism.

A microRNA expression signature for cervical cancer prognosis

Invasive cervical cancer is a leading cause of cancer death in women worldwide, resulting in about 300,000 deaths each year. The clinical outcomes of cervical cancer vary significantly and are difficult to predict. Thus, a method to reliably predict disease outcome would be important for individualized therapy by identifying patients with high risk of treatment failures before therapy. In this study, we have identified a microRNA (miRNA)-based signature for the prediction of cervical cancer survival. miRNAs are a newly identified family of small noncoding RNAs that are extensively involved in human cancers. Using an established PCR-based miRNA assay to analyze 102 cervical cancer samples, we identified miR-200a and miR-9 as two miRNAs that could predict patient survival. A logistic regression model was developed based on these two miRNAs and the prognostic value of the model was subsequently validated with independent cervical cancers. Furthermore, functional studies were done to characterize the effect of miRNAs in cervical cancer cells. Our results suggest that both miR-200a and miR-9 could play important regulatory roles in cervical cancer control. In particular, miR-200a is likely to affect the metastatic potential of cervical cancer cells by coordinate suppression of multiple genes controlling cell motility.

Non-codingRNA sequence variations in human chronic lymphocytic leukemia and colorectal cancer

Cancer is a genetic disease in which the interplay between alterations in protein-coding genes and non-coding RNAs (ncRNAs) plays a fundamental role. In recent years, the full coding component of the human genome was sequenced in various cancers, whereas such attempts related to ncRNAs are still fragmentary. We screened genomic DNAs for sequence variations in 148 microRNAs (miRNAs) and ultraconserved regions (UCRs) loci in patients with chronic lymphocytic leukemia (CLL) or colorectal cancer (CRC) by Sanger technique and further tried to elucidate the functional consequences of some of these variations. We found sequence variations in miRNAs in both sporadic and familial CLL cases, mutations of UCRs in CLLs and CRCs and, in certain instances, detected functional effects of these variations. Furthermore, by integrating our data with previously published data on miRNA sequence variations, we have created a catalog of DNA sequence variations in miRNAs/ultraconserved genes in human cancers. These findings argue that ncRNAs are targeted by both germ line and somatic mutations as well as by single-nucleotide polymorphisms with functional significance for human tumorigenesis. Sequence variations in ncRNA loci are frequent and some have functional and biological significance. Such information can be exploited to further investigate on a genome-wide scale the frequency of genetic variations in ncRNAs and their functional meaning, as well as for the development of new diagnostic and prognostic markers for leukemias and carcinomas.

Anti-Argonaute RIP-Chip shows that miRNA transfections alter global patterns of mRNA recruitment to microribonucleoprotein complexes

MicroRNAs (miRNAs) play key roles in gene expression regulation by guiding Argonaute (AGO)-containing microribonucleoprotein (miRNP) effector complexes to target polynucleotides. There are still uncertainties about how miRNAs interact with mRNAs. Here we employed a biochemical approach to isolate AGO-containing miRNPs from human H4 tumor cells by co-immunoprecipitation (co-IP) with a previously described anti-AGO antibody. Co-immunoprecipitated (co-IPed) RNAs were subjected to downstream Affymetrix Human Gene 1.0 ST microarray analysis. During rigorous validation, the "RIP-Chip" assay identified target mRNAs specifically associated with AGO complexes. RIP-Chip was performed after transfecting brain-enriched miRNAs (miR-107, miR-124, miR-128, and miR-320) and nonphysiologic control miRNA to identify miRNA targets. As expected, the miRNA transfections altered the mRNA content of the miRNPs. Specific mRNA species recruited to miRNPs after miRNA transfections were moderately in agreement with computational target predictions. In addition to recruiting mRNA targets into miRNPs, miR-107 and to a lesser extent miR-128, but not miR-124 or miR-320, caused apparent exclusion of some mRNAs that are normally associated with miRNPs. MiR-107 and miR-128 transfections also result in decreased AGO mRNA and protein levels. However, AGO mRNAs were not recruited to miRNPs after either miR-107 or miR-128 transfection, confirming that miRNAs may alter gene expression without stable association between particular mRNAs and miRNPs. In summary, RIP-Chip assays constitute an optimized, validated, direct, and high-throughput biochemical assay that provides data about specific miRNA:mRNA interactions, as well as global patterns of regulation by miRNAs.

Hepatitis C virus proteins modulate microRNA expression and chemosensitivity in malignant hepatocytes

PURPOSE

Hepatocellular cancer (HCC) is highly resistant to chemotherapy and is associated with poor prognosis. Chronic hepatitis C virus (HCV) infection is a major cause of HCC. However, the effect of viral proteins in mediating chemosensitivity in tumor cells is unknown. We postulated that HCV viral proteins could modulate therapeutic responses by altering host cell microRNA (miRNA) expression.

EXPERIMENTAL DESIGN

HepG2 malignant hepatocytes were stably transfected with full-length HCV genome (Hep-394) or an empty vector (Hep-SWX). MiRNA profiling was done by using a custom microarray, and the expression of selected miRNAs was validated by real-time PCR. Protein expression was assessed by Western blotting, whereas caspase activation was assessed by a luminometric assay.

RESULTS

The IC(50) to sorafenib was lower in Hep-394 compared with Hep-SWX control cells. Alterations in miRNA expression occurred with 10 miRNAs downregulated >2-fold and 23 miRNAs upregulated >2-fold in Hep-394 cells compared with controls. Of these, miR-193b was overexpressed by 5-fold in Hep-394 cells. miR-193b was predicted to target Mcl-1, an antiapoptotic protein that can modulate the response to sorafenib. The expression of Mcl-1 was decreased, and basal caspase-3/7 activity and poly ADP ribose polymerase cleavage were increased in Hep-394 cells compared with controls. Moreover, transfection with precursors to miR-193b decreased both Mcl-1 expression and the IC(50) to sorafenib.

CONCLUSIONS

Cellular expression of full-length HCV increases sensitivity to sorafenib by the miRNA-dependent modulation of Mcl-1 and apoptosis. Modulation of miRNA responses may be a useful strategy to enhance response to chemotherapy in HCC.

microRNA expression profile and identification of miR-29 as a prognostic marker and pathogenetic factor by targeting CDK6 in mantle cell lymphoma

Mantle cell lymphoma (MCL) is one of the most aggressive B-cell lymphomas. Although several protein-coding genes are altered, expression signature and importance of microRNA (miRNA) have not been well documented in this malignancy. Here, we performed miRNA expression profile in 30 patients with MCL using a platform containing 515 human miRNAs. Eighteen miRNAs were down-regulated and 21 were up-regulated in MCL compared with normal B lymphocytes. The most frequently altered miRNAs are decrease of miR-29a/b/c, miR-142-3p/5p, and miR-150 and increase of miR-124a and miR-155. Notably, expression levels of miR-29 family are associated with prognosis. The patients with significant down-regulated miR-29 had short survival compared with those who express relatively high levels of miR-29. The prognostic value of miR-29 is comparable with the Mantle Cell Lymphoma International Prognostic Index. Furthermore, we demonstrate miR-29 inhibition of CDK6 protein and mRNA levels by direct binding to 3'-untranslated region. Inverse correlation between miR-29 and CDK6 was observed in MCL. Because cyclin D1 overexpression is a primary event and exerts its function through activation of CDK4/CDK6, our results in primary MCL cells indicate that down-regulation of miR-29 could cooperate with cyclin D1 in MCL pathogenesis. Thus, our findings provide not only miRNA expression signature but also a novel prognostic marker and pathogenetic factor for this malignancy.

MTar: a computational microRNA target prediction architecture for human transcriptome

BACKGROUND

MicroRNAs (miRNAs) play an essential task in gene regulatory networks by inhibiting the expression of target mRNAs. As their mRNA targets are genes involved in important cell functions, there is a growing interest in identifying the relationship between miRNAs and their target mRNAs. So, there is now a imperative need to develop a computational method by which we can identify the target mRNAs of existing miRNAs. Here, we proposed an efficient machine learning model to unravel the relationship between miRNAs and their target mRNAs.

RESULTS

We present a novel computational architecture MTar for miRNA target prediction which reports 94.5% sensitivity and 90.5% specificity. We identified 16 positional, thermodynamic and structural parameters from the wet lab proven miRNA:mRNA pairs and MTar makes use of these parameters for miRNA target identification. It incorporates an Artificial Neural Network (ANN) verifier which is trained by wet lab proven microRNA targets. A number of hitherto unknown targets of many miRNA families were located using MTar. The method identifies all three potential miRNA targets (5' seed-only, 5' dominant, and 3' canonical) whereas the existing solutions focus on 5' complementarities alone.

CONCLUSION

MTar, an ANN based architecture for identifying functional regulatory miRNA-mRNA interaction using predicted miRNA targets. The area of target prediction has received a new momentum with the function of a thermodynamic model incorporating target accessibility. This model incorporates sixteen structural, thermodynamic and positional features of residues in miRNA: mRNA pairs were employed to select target candidates. So our novel machine learning architecture, MTar is found to be more comprehensive than the existing methods in predicting miRNA targets, especially human transcritome.

Computational methods to identify miRNA targets

MicroRNAs (miRNAs) are short RNA molecules that regulate the post-transcriptional expression of their target genes. This regulation may take the form of stable translational or degradation of the target transcript, although the mechanisms governing the outcome of miRNA-mediated regulation remain largely unknown. While it is becoming clear that miRNAs are core components of gene regulatory networks, elucidating precise roles for each miRNA within these networks will require an accurate means of identifying target genes and assessing the impact of miRNAs on individual targets. Numerous computational methods for predicting targets are currently available. These methods vary widely in their emphasis, accuracy, and ease of use for researchers. This review will focus on a comparison of the available computational methods in animals, with an emphasis on approaches that are informed by experimental analysis of microRNA:target complexes.

Comprehensive discovery of endogenous Argonaute binding sites in Caenorhabditis elegans

MicroRNAs (miRNAs) regulate gene expression by guiding Argonaute proteins to specific target mRNA sequences. Identification of bona fide miRNA target sites in animals is challenging because of uncertainties regarding the base-pairing requirements between miRNA and target as well as the location of functional binding sites within mRNAs. Here we present the results of a comprehensive strategy aimed at isolating endogenous mRNA target sequences bound by the Argonaute protein ALG-1 in C. elegans. Using cross-linking and ALG-1 immunoprecipitation coupled with high-throughput sequencing (CLIP-seq), we identified extensive ALG-1 interactions with specific 3' untranslated region (UTR) and coding exon sequences and discovered features that distinguish miRNA complex binding sites in 3' UTRs from those in other genic regions. Furthermore, our analyses revealed a striking enrichment of Argonaute binding sites in genes important for miRNA function, suggesting an autoregulatory role that may confer robustness to the miRNA pathway.

A combined immunoprecipitation, mass spectrometric and nucleic acid sequencing approach to determine microRNA-mediated post-transcriptional gene regulatory networks

While initiation of transcription has attracted the most attention in the field of gene regulation, it has become clear that additional stages in the gene expression cascade including post-transcriptional events are under equally exquisite control. The seminal discovery that short RNAs (microRNA, small interfering RNA, Piwi-interacting RNA), play important roles in repressing gene expression has spurred a rush of new interest in post-transcriptional gene silencing mechanisms. The development of affinity tags and high-resolution tandem mass spectrometry (MS/MS) has greatly simplified the analysis of proteins that regulate gene expression. Further, the use of DNA microarrays and 'second generation' nucleic acid sequencing ('deep sequencing') technologies has facilitated the identification of their regulatory targets. These technological advancements mark a significant step towards a comprehensive understanding of gene regulatory networks. The purpose of this review is to highlight several recent reports that illustrate the value of affinity-purification (immunoprecipitation) followed by mass spectrometric protein analysis and nucleic acid analysis by deep sequencing (AP-MS/Seq) to examine mRNA after it has been transcribed. The ability to identify the direct nucleic acid targets of post-transcriptional gene regulatory machines is a critical first step towards understanding the contribution of post-transcriptional pathways on gene expression.

microRNAs in diseases: from candidate to modifier genes

Until recently, the search for genetic factors predisposing or causing Mendelian diseases focused almost exclusively on protein coding sequences. As essential components of the regulatory system of gene expression, microRNAs (miRNAs) hold great promises into elucidating a number of inherited diseases. The herein review focuses on the genetic variations, whether copy number variation (CNV) or single nucleotide polymorphism (SNP), alternatively at the levels of the miRNA gene itself and of its target genes. We consider miRNA as the candidate gene, or the regulator of a disease-causing gene, or the modifier gene. The best paradigms of the field are presented in both monogenic diseases and complex traits. The computational tools, which are essential into identifying miRNAs and characterizing miRNA targets, are overviewed.

Current knowledge of MicroRNAs and noncoding RNAs in virus-infected cells

Within the past few years, microRNAs (miRNAs) and other noncoding RNAs (ncRNAs) have emerged as elements with critically high importance in posttranscriptional control of cellular and, more recently, viral processes. Endogenously produced by a component of the miRNA-guided RNA silencing machinery known as Dicer, miRNAs are known to control messenger RNA (mRNA) translation through recognition of specific binding sites usually located in their 3' untranslated region. Recent evidences indicate that the host miRNA pathway may represent an adapted antiviral defense mechanism that can act either by direct miRNA-mediated modulation of viral gene expression or through recognition and inactivation of structured viral RNA species by the protein components of the RNA silencing machinery such as Dicer. This latter process, however, is a double-edge sword, as it may yield viral miRNAs exerting gene regulatory properties on both host and viral mRNAs. Our knowledge of the interaction between viruses and host RNA silencing machineries, and how this influences the course of infection, is becoming increasingly complex. This chapter aims to summarize our current knowledge about viral miRNAs/ncRNAs and their targets, as well as cellular miRNAs that are modulated by viruses upon infection.

Sequence and structure analysis of noncoding RNAs

Noncoding RNAs (ncRNAs) are increasingly recognized as important functional molecules in the cell. Here we give a short overview of fundamental computational techniques to analyze ncRNAs that can help us better understand their function. Topics covered include prediction of secondary structure from the primary sequence, prediction of consensus structures for homologous sequences, search for homologous sequences in databases using sequence and structure comparisons, annotation of tRNAs, rRNAs, snoRNAs, and microRNAs, de novo prediction of novel ncRNAs, and prediction of RNA/RNA interactions including miRNA target prediction.

Computational prediction of microRNA targets

One critical step in miRNA functional studies is to identify the gene targets that are directly regulated by miRNAs. In this chapter, we describe a computational algorithm and an online database, miRDB, for miRNA target prediction. In miRDB, flexible Web search interface has been developed for the retrieval of target prediction results generated by the newly developed computational algorithm. In addition, a wiki editing interface has been established to allow anyone with Internet access to make contributions on miRNA functional annotation. All data stored in miRDB are freely accessible at http://www.mirdb.org.

MicroRNAs: a novel class of potential therapeutic targets for cardiovascular diseases

Currently, cardiovascular diseases remain one of the leading causes of morbidity and mortality in the world, indicating the need for innovative therapies and diagnosis for heart disease. MicroRNAs (miRNAs) have recently emerged as one of the central players in regulating gene expression. Numerous studies have documented the implications of miRNAs in nearly every pathological process of the cardiovascular system, including cardiac arrhythmia, cardiac hypertrophy, heart failure, cardiac fibrosis, cardiac ischemia and vascular atherosclerosis. More surprisingly, forced expression or suppression of a single miRNA is enough to cause or alleviate the pathological alteration, underscoring the therapeutic potential of miRNAs in cardiovascular diseases. In this review we summarize the key miRNAs that can solely modulate the cardiovascular pathological process and discuss the mechanisms by which they exert their function and the perspective of these miRNAs as novel therapeutic targets and/or diagnostic markers. In addition, current approaches for manipulating the action of miRNAs will be introduced.

miR-19 is a key oncogenic component of mir-17-92

Recent studies have revealed the importance of multiple microRNAs (miRNAs) in promoting tumorigenesis, among which mir-17-92/Oncomir-1 exhibits potent oncogenic activity. Genomic amplification and elevated expression of mir-17-92 occur in several human B-cell lymphomas, and enforced mir-17-92 expression in mice cooperates with c-myc to promote the formation of B-cell lymphomas. Unlike classic protein-coding oncogenes, mir-17-92 has an unconventional gene structure, where one primary transcript yields six individual miRNAs. Here, we functionally dissected the individual components of mir-17-92 by assaying their tumorigenic potential in vivo. Using the Emu-myc model of mouse B-cell lymphoma, we identified miR-19 as the key oncogenic component of mir-17-92, both necessary and sufficient for promoting c-myc-induced lymphomagenesis by repressing apoptosis. The oncogenic activity of miR-19 is at least in part due to its repression of the tumor suppressor Pten. Consistently, miR-19 activates the Akt-mTOR (mammalian target of rapamycin) pathway, thereby functionally antagonizing Pten to promote cell survival. Our findings reveal the essential role of miR-19 in mediating the oncogenic activity of mir-17-92, and implicate the functional diversity of mir-17-92 components as the molecular basis for its pleiotropic effects during tumorigenesis.

Progress in miRNA target prediction and identification

Recently, the identification of miRNA targets has received much attention. The strategies to determine miRNA targets include bioinformatic prediction and experimental assays. The bioinformatic prediction methods are mainly based on the confirmed rules of interaction between miRNAs and their targets, and are carried out by programs, such as miRanda, TargetScan, TargetScanS, RNAhybrid, DIANA-microT, PicTar, RNA22 and FindTar, which follow well-known principles. The experimental assays to find miRNA targets employ immunoprecipitation of AGO proteins to identify interacting mRNAs, or the analysis of mRNA or protein levels to identify genes which can be regulated by miRNAs. The improvement of current bioinformatic and experimental assays and the development of novel assays will enable greater efficiency in the identification of miRNA targets and thus facilitate miRNA research. This paper describes progress in the prediction and identification of miRNA targets.

In silico method for systematic analysis of feature importance in microRNA-mRNA interactions

Background

MicroRNA (miRNA), which is short non-coding RNA, plays a pivotal role in the regulation of many biological processes and affects the stability and/or translation of mRNA. Recently, machine learning algorithms were developed to predict potential miRNA targets. Most of these methods are robust but are not sensitive to redundant or irrelevant features. Despite their good performance, the relative importance of each feature is still unclear. With increasing experimental data becoming available, research interest has shifted from higher prediction performance to uncovering the mechanism of microRNA-mRNA interactions.

Results

Systematic analysis of sequence, structural and positional features was carried out for two different data sets. The dominant functional features were distinguished from uninformative features in single and hybrid feature sets. Models were developed using only statistically significant sequence, structural and positional features, resulting in area under the receiver operating curves (AUC) values of 0.919, 0.927 and 0.969 for one data set and of 0.926, 0.874 and 0.954 for another data set, respectively. Hybrid models were developed by combining various features and achieved AUC of 0.978 and 0.970 for two different data sets. Functional miRNA information is well reflected in these features, which are expected to be valuable in understanding the mechanism of microRNA-mRNA interactions and in designing experiments.

Conclusions

Differing from previous approaches, this study focused on systematic analysis of all types of features. Statistically significant features were identified and used to construct models that yield similar accuracy to previous studies in a shorter computation time.

Computational approaches for microRNA studies: a review

MicroRNAs (miRNAs) are one class of tiny, endogenous RNAs that can regulate messenger RNA (mRNA) expression by targeting homologous sequences in mRNAs. Their aberrant expressions have been observed in many cancers and several miRNAs have been convincingly shown to play important roles in carcinogenesis. Since the discovery of this small regulator, computational methods have been indispensable tools in miRNA gene finding and functional studies. In this review we first briefly outline the biological findings of miRNA genes, such as genomic feature, biogenesis, gene structure, and functional mechanism. We then discuss in detail the three main aspects of miRNA computational studies: miRNA gene finding, miRNA target prediction, and regulation of miRNA genes. Finally, we provide perspectives on some emerging issues, including combinatorial regulation by miRNAs and functional binding sites beyond the 3'-untranslated region (3'UTR) of target mRNAs. Available online resources for miRNA computational studies are also provided.

Insight into microRNA regulation by analyzing the characteristics of their targets in humans

Background

microRNAs (miRNAs) are believed to regulate their targets through posttranscriptional gene regulation and have the potential to silence gene expression via multiple mechanisms. Despite previous advances on miRNA regulation of gene expression, little has been investigated from a genome scale.

Results

To gain new insight into miRNA regulation in humans, we used large scale data and carried out a series of studies to compare various features of miRNA target genes to that of non-miRNA target genes. We observed significant differences between miRNA and non-miRNA target genes for a number of characteristics, including higher and broader mRNA expression, faster mRNA decay rate, longer protein half-life, and longer gene structures. Based on these features and by analyzing their relationships we found that miRNA target genes, other than having miRNA repression, were most likely under more complex regulation than non-miRNA target genes, which was evidenced by their higher and broader gene expression but longer gene structures. Our results of higher and broader gene expression but fast mRNA decay rates also provide evidence that miRNA dampening of the output of preexisting transcripts facilitates a more rapid and robust transition to new expression programs. This could be achieved by enhancing mRNA degradation through an additive effect from multiple miRNA targeting.

Conclusion

Genome-scale analysis on the nature of miRNA target genes has revealed a general mechanism for miRNA regulation of human gene expression. The results of this study also indicate that miRNA target genes, other than having miRNA repression, are under more complex gene regulation than non-miRNA target genes. These findings provide novel insight into miRNA regulation of human gene expression.

Haplotype distribution and evolutionary pattern of miR-17 and miR-124 families based on population analysis

Background

MicroRNAs (miRNAs) are small, endogenously expressed non-coding RNAs that regulate mRNAs post-transcriptionally. Previous studies have explored miRNA evolutionary trend, but evolutionary history and pattern in the miRNA world are still not fully clear. In the paper, we intended to analyze miRNA haplotype distribution and evolutionary network by analyzing miRNA sequences of miR-17 and miR-124 families across animal species as special populations.

Principal Findings

31 haplotypes were detected in miR-17 family while only 9 haplotypes were defined in miR-124 family. The complex miR-17 family was mainly distributed in vertebrates, but miR-124 was shared by more animal species from Caenorhabditis to Homo and had a wide distribution spectrum. Some haplotypes of the two miRNA families appeared discontinuous distributions across animals. Compared with a simple phylogenetic network in miR-124 family, miR-17 family indicated a complex network with some median vectors that might be lost ancestral or potential miRNA haplotypes. By analyzing different miRNAs across 12 animal species, we found these small RNAs showed different haplotype diversities, haplotype distributions and phylogenetic networks.

Conclusions

Different miRNAs had quite different haplotype distributions and evolutionary patterns. Discontinuous distributions of miRNAs and median vectors in phylogenetic networks implied more members in the miRNA world. miRNA may be an excellent phylogenetic marker to discover its evolutionary history and pattern across the animal kingdom.

mimiRNA: a microRNA expression profiler and classification resource designed to identify functional correlations between microRNAs and their targets

MOTIVATION

microRNAs (miRNAs) are short non-coding RNAs that regulate gene expression by inhibiting target mRNA genes. Their tissue- and disease-specific expression patterns have immense therapeutic and diagnostic potential. To understand these patterns, a reliable compilation of miRNA and mRNA expression data is required to compare multiple tissue types. Moreover, with the appropriate statistical tools, such a resource could be interrogated to discover functionally related miRNA-mRNA pairs.

RESULTS

We have developed mimiRNA, an online resource that integrates expression data from 1483 samples and permits visualization of the expression of 635 human miRNAs across 188 different tissues or cell types. mimiRNA incorporates a novel sample classification algorithm, ExParser, that groups identical miRNA or mRNA experiments from separate sources. This enables mimiRNA to provide reliable expression profiles and to discover functional relations between miRNAs and mRNAs such as miRNA targets. Additionally, mimiRNA incorporates a decision tree algorithm to discover distinguishing miRNA features between two tissue or cell types. We validate the efficacy of our resource on independent experimental data and through biologically relevant analyses.

AVAILABILITY

http://mimirna.centenary.org.au.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

A novel microRNA targeting HDAC5 regulates osteoblast differentiation in mice and contributes to primary osteoporosis in humans

MicroRNAs (miRNAs) interfere with translation of specific target mRNAs and are thought to thereby regulate many cellular processes. Recent studies have suggested that miRNAs might play a role in osteoblast differentiation and bone formation. Here, we identify a new miRNA (miR-2861) in primary mouse osteoblasts that promotes osteoblast differentiation by repressing histone deacetylase 5 (HDAC5) expression at the post-transcriptional level. miR-2861 was found to be transcribed in ST2 stromal cells during bone morphogenetic protein 2-induced (BMP2-induced) osteogenesis, and overexpression of miR-2861 enhanced BMP2-induced osteoblastogenesis, whereas inhibition of miR-2861 expression attenuated it. HDAC5, an enhancer of runt-related transcription factor 2 (Runx2) degradation, was confirmed to be a target of miR-2861. In vivo silencing of miR-2861 in mice reduced Runx2 protein expression, inhibited bone formation, and decreased bone mass. Importantly, miR-2861 was found to be conserved in humans, and a homozygous mutation in pre-miR-2861 that blocked expression of miR-2861 was shown to cause primary osteoporosis in 2 related adolescents. Consistent with the mouse data, HDAC5 levels were increased and Runx2 levels decreased in bone samples from the 2 affected individuals. Thus, our studies show that miR-2861 plays an important physiological role in osteoblast differentiation and contributes to osteoporosis via its effect on osteoblasts.

MicroRNAs and epigenetic regulation in the mammalian inner ear: implications for deafness

Sensorineural hearing loss is the most common sensory disorder in humans and derives, in most cases, from inner-ear defects or degeneration of the cochlear sensory neuroepithelial hair cells. Genetic factors make a significant contribution to hearing impairment. While mutations in 51 genes have been associated with hereditary sensorineural nonsyndromic hearing loss (NSHL) in humans, the responsible mutations in many other chromosomal loci linked with NSHL have not been identified yet. Recently, mutations in a noncoding microRNA (miRNA) gene, MIR96, which is expressed specifically in the inner-ear hair cells, were linked with progressive hearing loss in humans and mice. Furthermore, additional miRNAs were found to have essential roles in the development and survival of inner-ear hair cells. Epigenetic mechanisms, in particular, DNA methylation and histone modifications, have also been implicated in human deafness, suggesting that several layers of noncoding genes that have never been studied systematically in the inner-ear sensory epithelia are required for normal hearing. This review aims to summarize the current knowledge about the roles of miRNAs and epigenetic regulatory mechanisms in the development, survival, and function of the inner ear, specifically in the sensory epithelia, tectorial membrane, and innervation, and their contribution to hearing.

MicroRNA 125a and its regulation of the p53 tumor suppressor gene

MicroRNA (miRNA) are a class of non-coding RNA that suppress gene expression by degradation or translational inhibition of target RNA. Several miRNA have been shown to target oncogenes and recently miRNA-125b was shown to translationally and transcriptionally inhibit the p53 gene. Here, we show that an additional isomer of miRNA-125 (miRNA-125a) translationally arrests mRNA of the p53 tumor suppressor gene. The basis of this activity is the high degree of sequence homology between the seed sequence of miR-125a and the 3'-UTR of p53. Our findings add miRNA-125a to the growing list of miRNA with oncogenic targets.