A combined computational-experimental approach predicts human microRNA targets

Post-transcriptional control of circadian rhythms

Circadian rhythms exist in most living organisms. The general molecular mechanisms that are used to generate 24-hour rhythms are conserved among organisms, although the details vary. These core clocks consist of multiple regulatory feedback loops, and must be coordinated and orchestrated appropriately for the fine-tuning of the 24-hour period. Many levels of regulation are important for the proper functioning of the circadian clock, including transcriptional, post-transcriptional and post-translational mechanisms. In recent years, new information about post-transcriptional regulation in the circadian system has been discovered. Such regulation has been shown to alter the phase and amplitude of rhythmic mRNA and protein expression in many organisms. Therefore, this Commentary will provide an overview of current knowledge of post-transcriptional regulation of the clock genes and clock-controlled genes in dinoflagellates, plants, fungi and animals. This article will also highlight how circadian gene expression is modulated by post-transcriptional mechanisms and how this is crucial for robust circadian rhythmicity.

miRTar: an integrated system for identifying miRNA-target interactions in human

Background

MicroRNAs (miRNAs) are small non-coding RNA molecules that are ~22-nt-long sequences capable of suppressing protein synthesis. Previous research has suggested that miRNAs regulate 30% or more of the human protein-coding genes. The aim of this work is to consider various analyzing scenarios in the identification of miRNA-target interactions, as well as to provide an integrated system that will aid in facilitating investigation on the influence of miRNA targets by alternative splicing and the biological function of miRNAs in biological pathways.

Results

This work presents an integrated system, miRTar, which adopts various analyzing scenarios to identify putative miRNA target sites of the gene transcripts and elucidates the biological functions of miRNAs toward their targets in biological pathways. The system has three major features. First, the prediction system is able to consider various analyzing scenarios (1 miRNA:1 gene, 1:N, N:1, N:M, all miRNAs:N genes, and N miRNAs: genes involved in a pathway) to easily identify the regulatory relationships between interesting miRNAs and their targets, in 3'UTR, 5'UTR and coding regions. Second, miRTar can analyze and highlight a group of miRNA-regulated genes that participate in particular KEGG pathways to elucidate the biological roles of miRNAs in biological pathways. Third, miRTar can provide further information for elucidating the miRNA regulation, i.e., miRNA-target interactions, affected by alternative splicing.

Conclusions

In this work, we developed an integrated resource, miRTar, to enable biologists to easily identify the biological functions and regulatory relationships between a group of known/putative miRNAs and protein coding genes. miRTar is now available at http://miRTar.mbc.nctu.edu.tw/.

MicroRNA: Biogenesis, Function and Role in Cancer

MicroRNAs are small, highly conserved non-coding RNA molecules involved in the regulation of gene expression. MicroRNAs are transcribed by RNA polymerases II and III, generating precursors that undergo a series of cleavage events to form mature microRNA. The conventional biogenesis pathway consists of two cleavage events, one nuclear and one cytoplasmic. However, alternative biogenesis pathways exist that differ in the number of cleavage events and enzymes responsible. How microRNA precursors are sorted to the different pathways is unclear but appears to be determined by the site of origin of the microRNA, its sequence and thermodynamic stability. The regulatory functions of microRNAs are accomplished through the RNA-induced silencing complex (RISC). MicroRNA assembles into RISC, activating the complex to target messenger RNA (mRNA) specified by the microRNA. Various RISC assembly models have been proposed and research continues to explore the mechanism(s) of RISC loading and activation. The degree and nature of the complementarity between the microRNA and target determine the gene silencing mechanism, slicer-dependent mRNA degradation or slicer-independent translation inhibition. Recent evidence indicates that P-bodies are essential for microRNA-mediated gene silencing and that RISC assembly and silencing occurs primarily within P-bodies. The P-body model outlines microRNA sorting and shuttling between specialized P-body compartments that house enzymes required for slicer –dependent and –independent silencing, addressing the reversibility of these silencing mechanisms. Detailed knowledge of the microRNA pathways is essential for understanding their physiological role and the implications associated with dysfunction and dysregulation.

MicroRNA Gene Networks in Oncogenesis

MicroRNAs are small non-coding RNAs that regulate gene expression at the transcriptional or posttranscriptional level. They are involved in cellular development, differentiation, proliferation and apoptosis and play a significant role in cancer. Examination of tumor-specific microRNA expression profiles has revealed widespread deregulation of these molecules in diverse cancers. Several studies have shown that microRNAs function either as tumor suppressor genes or oncogenes, whose loss or overexpression respectively has diagnostic and prognostic significance. It seems that microRNAs act as major regulators of gene expression. In this review, we discuss microRNAs’ role in cancer and how microRNAs exert their functions through regulation of their gene targets. Bioinformatic analysis of putative miRNA binding sites has indicated several novel potential gene targets involved in apoptosis, angiogenesis and metastatic mechanisms. Matching computational prediction analysis together with microarray data seems the best method for microRNA gene target identification. MicroRNAs together with transcription factors generate a complex combinatorial code regulating gene expression. Thus, manipulation of microRNA-transcription factor gene networks may be provides a novel approach for developing cancer therapies.

Survey of Computational Algorithms for MicroRNA Target Prediction

MicroRNAs (miRNAs) are 19 to 25 nucleotides non-coding RNAs known to possess important post-transcriptional regulatory functions. Identifying targeting genes that miRNAs regulate are important for understanding their specific biological functions. Usually, miRNAs down-regulate target genes through binding to the complementary sites in the 3' untranslated region (UTR) of the targets. In part, due to the large number of miRNAs and potential targets, an experimental based prediction design would be extremely laborious and economically unfavorable. However, since the bindings of the animal miRNAs are not a perfect one-to-one match with the complementary sites of their targets, it is difficult to predict targets of animal miRNAs by accessing their alignment to the 3' UTRs of potential targets. Consequently, sophisticated computational approaches for miRNA target prediction are being considered as essential methods in miRNA research.

We surveyed most of the current computational miRNA target prediction algorithms in this paper. Particularly, we provided a mathematical definition and formulated the problem of target prediction under the framework of statistical classification. Moreover, we summarized the features of miRNA-target pairs in target prediction approaches and discussed these approaches according to two categories, which are the rule-based and the data-driven approaches. The rule-based approach derives the classifier mainly on biological prior knowledge and important observations from biological experiments, whereas the data driven approach builds statistic models using the training data and makes predictions based on the models. Finally, we tested a few different algorithms on a set of experimentally validated true miRNA-target pairs [1] and a set of false miRNA-target pairs, derived from miRNA overexpression experiment [2]. Receiver Operating Characteristic (ROC) curves were drawn to show the performances of these algorithms.

Specific sequence determinants of miR-15/107 microRNA gene group targets

MicroRNAs (miRNAs) target mRNAs in human cells via complex mechanisms that are still incompletely understood. Using anti-Argonaute (anti-AGO) antibody co-immunoprecipitation, followed by microarray analyses and downstream bioinformatics, 'RIP-Chip' experiments enable direct analyses of miRNA targets. RIP-Chip studies (and parallel assessments of total input mRNA) were performed in cultured H4 cells after transfection with miRNAs corresponding to the miR-15/107 gene group (miR-103, miR-107, miR-16 and miR-195), and five control miRNAs. Three biological replicates were run for each condition with a total of 54 separate human Affymetrix Human Gene 1.0 ST array replicates. Computational analyses queried for determinants of miRNA:mRNA binding. The analyses support four major findings: (i) RIP-Chip studies correlated with total input mRNA profiling provides more comprehensive information than using either RIP-Chip or total mRNA profiling alone after miRNA transfections; (ii) new data confirm that miR-107 paralogs target coding sequence (CDS) of mRNA; (iii) biochemical and computational studies indicate that the 3' portion of miRNAs plays a role in guiding miR-103/7 to the CDS of targets; and (iv) there are major sequence-specific targeting differences between miRNAs in terms of CDS versus 3'-untranslated region targeting, and stable AGO association versus mRNA knockdown. Future studies should take this important miRNA-to-miRNA variability into account.

MicroRNA expression aberration as potential peripheral blood biomarkers for schizophrenia

Since brain tissue is not readily accessible, a new focus in search of biomarkers for schizophrenia is blood-based expression profiling of non-protein coding genes such as microRNAs (miRNAs), which regulate gene expression by inhibiting the translation of messenger RNAs. This study aimed to identify potential miRNA signature for schizophrenia by comparing genome-wide miRNA expression profiles in patients with schizophrenia vs. healthy controls. A genome-wide miRNA expression profiling was performed using a Taqman array of 365 human miRNAs in the mononuclear leukocytes of a learning set of 30 cases and 30 controls. The discriminating performance of potential biomarkers was validated in an independent testing set of 60 cases and 30 controls. The expression levels of the miRNA signature were then evaluated for their correlation with the patients' clinical symptoms, neurocognitive performances, and neurophysiological functions. A seven-miRNA signature (hsa-miR-34a, miR-449a, miR-564, miR-432, miR-548d, miR-572 and miR-652) was derived from a supervised classification with internal cross-validation, with an area under the curve (AUC) of receiver operating characteristics of 93%. The putative signature was then validated in the testing set, with an AUC of 85%. Among these miRNAs, miR-34a was differentially expressed between cases and controls in both the learning (P = 0.005) and the testing set (P = 0.002). These miRNAs were differentially correlated with patients' negative symptoms, neurocognitive performance scores, and event-related potentials. The results indicated that the mononuclear leukocyte-based miRNA profiling is a feasible way to identify biomarkers for schizophrenia, and the seven-miRNA signature warrants further investigation.

Practical Aspects of microRNA Target Prediction

microRNAs (miRNAs) are endogenous non-coding RNAs that control gene expression at the posttranscriptional level. These small regulatory molecules play a key role in the majority of biological processes and their expression is also tightly regulated. Both the deregulation of genes controlled by miRNAs and the altered miRNA expression have been linked to many disorders, including cancer, cardiovascular, metabolic and neurodegenerative diseases. Therefore, it is of particular interest to reliably predict potential miRNA targets which might be involved in these diseases. However, interactions between miRNAs and their targets are complex and very often there are numerous putative miRNA recognition sites in mRNAs. Many miRNA targets have been computationally predicted but only a limited number of these were experimentally validated. Although a variety of miRNA target prediction algorithms are available, results of their application are often inconsistent. Hence, finding a functional miRNA target is still a challenging task. In this review, currently available and frequently used computational tools for miRNA target prediction, i.e., PicTar, TargetScan, DIANA-microT, miRanda, rna22 and PITA are outlined and various practical aspects of miRNA target analysis are extensively discussed. Moreover, the performance of three algorithms (PicTar, TargetScan and DIANA-microT) is both demonstrated and evaluated by performing an in-depth analysis of miRNA interactions with mRNAs derived from genes triggering hereditary neurological disorders known as trinucleotide repeat expansion diseases (TREDs), such as Huntington’s disease (HD), a number of spinocerebellar ataxias (SCAs), and myotonic dystrophy type 1 (DM1).

C-T variant in a miRNA target site of BCL2 is associated with increased risk of human papilloma virus related cervical cancer--an in silico approach

MicroRNAs control gene expression at the posttranscriptional level by base-pairing to the 3'-UTR of their target mRNAs, thus leading to mRNA degradation of protein fabrication. We hypothesize, SNPs within miRNAs and their targets could be of significance to an individual's risk of developing cancer. We analyzed in silico SNP information on cervical cancer associated aberrant alleles and further investigated this in a case-control study by examining eleven SNPs from different genes. It was observed that a C to T polymorphism in putative miRNA target site of BCL2 was significantly conspicuous for the aberrant SNP allele in cancer tissues as compared to controls. This study provides evidence that SNPs in miRNA-binding sites may play an important role in increasing risk of cancer. The results also paves way for future studies to validate these results in other well-characterized populations as well as to explore the biological significance of these particular SNPs.

MicroRNA-373, a new regulator of protein phosphatase 6, functions as an oncogene in hepatocellular carcinoma

MicroRNAs are a class of small noncoding RNAs that function as key regulators of gene expression at the post-transcriptional level. Recently, microRNA-373 (miR-373) has been found to function as an oncogene in testicular germ cell tumors. In our study, we found that miR-373 is upregulated in human hepatocellular carcinoma (HCC) tissues as compared with adjacent normal tissues, and promotes the proliferation of the HCC cell lines HepG2 and QGY-7703 by regulating the transition between G(1)-phase and S-phase. The gene encoding the protein phosphatase 6 catalytic subunit (PPP6C ), a negative cell cycle regulator, was identified as a direct target gene of miR-373 by use of a fluorescent reporter assay. The mRNA and protein levels of PPP6C were both inversely correlated with the miR-373 expression level. Overexpression of PPP6C abolished the regulation of cell cycle and cell growth exercised by miR-373 in HepG2 cells. These results indicate that miR-373 plays an important role in the pathogenesis of HCC, and may be a new biomarker in HCC. Our results demonstrate that miR-373 can regulate cell cycle progression by targeting PPP6C transcripts and promotes the growth activity of HCC cells in vitro. The downregulation of PPP6C by miR-373 may explain why the expression of miR-373 can promote HCC cell proliferation.

DIANA-microT Web server upgrade supports Fly and Worm miRNA target prediction and bibliographic miRNA to disease association

microRNAs (miRNAs) are small endogenous RNA molecules that are implicated in many biological processes through post-transcriptional regulation of gene expression. The DIANA-microT Web server provides a user-friendly interface for comprehensive computational analysis of miRNA targets in human and mouse. The server has now been extended to support predictions for two widely studied species: Drosophila melanogaster and Caenorhabditis elegans. In the updated version, the Web server enables the association of miRNAs to diseases through bibliographic analysis and provides insights for the potential involvement of miRNAs in biological processes. The nomenclature used to describe mature miRNAs along different miRBase versions has been extensively analyzed, and the naming history of each miRNA has been extracted. This enables the identification of miRNA publications regardless of possible nomenclature changes. User interaction has been further refined allowing users to save results that they wish to analyze further. A connection to the UCSC genome browser is now provided, enabling users to easily preview predicted binding sites in comparison to a wide array of genomic tracks, such as single nucleotide polymorphisms. The Web server is publicly accessible in www.microrna.gr/microT-v4.

MicroRNA-200a inhibits CD133/1+ ovarian cancer stem cells migration and invasion by targeting E-cadherin repressor ZEB2

OBJECTIVES

MicroRNA-200a (miR-200a) has been reported to be a prognostic marker and to play an important role in ovarian cancer progression. The aim of the study was to elucidate the mechanism of miR-200a involved in migration and invasion in CD133/1+ ovarian cancer stem cells (OCSCs).

METHODS

The expression of miR-200a between CD133/1+ and CD133/1- cells was performed using real-time PCR, and wound healing assay and matrigel invasion assay were used to detect migration and invasion of CD133/1+ cells, respectively, target gene regulated by miR-200a was detected using Dual Luciferase Reporter system, The expression levels of target gene were confirmed using real-time PCR and western blot.

RESULTS

miR-200a was downregulated in CD133/1+ cells compared with CD133/1- cells, and overexpression of miR-200a significantly reduced CD133/1+ cells migration and invasion compare with negative control (NC) (p<0.05). The 3'-UTR of ZEB2 mRNA, a transcriptional repressor of E-cadherin, was found to be regulated directly by miR-200a. In addition, when miR-200a was overexpressed in CD133/1+ cells, the mRNA and protein levels of ZEB2 were both suppressed, which resulted in an increase in the E-cadherin expression level, suggesting that ZEB2 was a functionally important target of miR-200a in CD133/1+ cells.

CONCLUSIONS

Our results suggest that loss of expression of miR-200a may play a critical role in the repression of E-cadherin by ZEB2, thereby enhancing migration and invasion in CD133/1+ cells.

miR-365, a novel negative regulator of interleukin-6 gene expression, is cooperatively regulated by Sp1 and NF-kappaB

Interleukin-6 (IL-6) is a pleiotropic cytokine that plays a central role in host defense. IL-6 expression can be regulated at both a transcriptional and a post-transcriptional level. We used a combination of bioinformatics and experimental techniques to demonstrate that the miR-365 is a direct negative regulator of IL-6. Overexpression of miR-365 mimics decreased activity of a luciferase reporter containing the IL-6 3'-UTR and led to repression of IL-6 protein. In contrast, ectopic expression of a miR-365 inhibitor elevated IL-6 expression. The negative regulation of miR-365 was strictly dependent on a microRNA binding element in the 3'-UTR of IL-6 mRNA. Deletion mutant analysis of the miR-365 promoter showed that two transcription factors, Sp1 and NF-κB, are essential for the transcriptional regulation of miR-365. We also demonstrate that the MAPK/ERK pathway contributes to the regulation of miR-365. Furthermore, miR-365 exhibited a greater negative regulatory effect on IL-6 than hsa-let-7a, a previously identified microRNA negatively regulating IL-6. Taken together, our results show that miR-365 is a novel negative regulator of IL-6.

MicroRNAs in Drosophila development

Micro-ribonucleic acids (miRNAs) are small (21-24 nucleotide), endogenously expressed, noncoding RNAs that have emerged as important posttranscriptional regulators of gene expression. MiRNAs have been identified and cloned from diverse eukaryotic organisms where they have been shown to control important physiological and developmental processes such as apoptosis, cell division, and differentiation. A high level of conservation of some miRNAs across phyla further emphasizes their importance as posttranscriptional regulators. Research in a variety of model systems has been instrumental in dissecting the biological functions of miRNAs. In this chapter, we discuss the current literature on the role of miRNAs as developmental regulators in Drosophila.

Molecular strategies to design an escape-proof antiviral therapy

Two antiviral approaches against the human immunodeficiency virus type 1 (HIV-1) were presented at the Antivirals Congress in Amsterdam. The common theme among these two separate therapeutic research lines is the wish to develop a durable therapy that prevents viral escape. We will present a brief overview of these two research lines and focus on our efforts to design an escape-proof anti-HIV therapy. The first topic concerns the class of HIV-1 fusion inhibitors, including the prototype T20 peptide and the improved versions T1249 and T2635, which were all developed by Trimeris-Roche. The selection of T20-resistant HIV-1 strains is a fairly easy evolutionary process that requires a single amino acid substitution in the peptide binding site of the viral envelope glycoprotein (Env) target. The selection of T1249-resistant HIV-1 strains was shown to require a more dramatic amino acid substitution in the viral Env protein, in particular the introduction of charged amino acid residues that cause resistance by charge-repulsion of the antiviral peptide. The third generation peptide T2635 remains active against all these HIV-1 escape variants because the charged residues within this peptide are "masked" by an introduced intra-helical salt bridge. This charge masking concept could facilitate the future design of escape-proof antiviral peptides. The second topic concerns the mechanism of RNA interference (RNAi) that we are currently employing to develop an antiviral gene therapy. One can make human T cells resistant to HIV-1 infection by a stable RNAi-inducing gene transfer, but the virus escapes under therapeutic pressure of a single inhibitor. Several options for a combinatorial RNAi attack to prevent viral escape will be discussed. The simultaneous use of multiple RNAi inhibitors turns out to be the most effective and durable strategy.

Differential expression of microRNAs in tumors from chronically inflamed or genetic (APC(Min/+)) models of colon cancer

Background

Chronic inflammation associated with ulcerative colitis predisposes individuals to increased colon cancer risk. The aim of these studies was to identify microRNAs that are aberrantly regulated during inflammation and may participate in transformation of colonic epithelial cells in the inflammatory setting.

Methodology/Principal Findings

We have use quantitative PCR arrays to compare microRNA (miRNA) expression in tumors and control colonic epithelial cells isolated from distal colons of chronically inflamed mice and APC^Min/+ mice. Rank order statistics was utilized to identify differentially regulated miRNAs in tumors that arose due to chronic inflammation and/or to germline APC mutation. Eight high priority miRNAs were identified: miR-215, miR-137, miR-708, miR-31, and miR-135b were differentially expressed in APC tumors and miR-215, miR-133a, miR-467d, miR-218, miR-708, miR-31, and miR-135b in colitis-associated tumors. Four of these (miR-215, miR-708, miR-31, and miR-135b) were common to both tumors types, and dysregulation of these miRNAs was confirmed in an independent sample set. Target prediction and pathway analysis suggests that these microRNAs, in the aggregate, regulate signaling pathways related to MAPK, PI3K, WNT, and TGF-β, all of which are known to be involved in transformation.

Conclusions/Significance

We conclude that these four miRNAs are dysregulated at some very early stage in transformation of colonic epithelial cells. This response is not dependent on the mechanism of initiation of transformation (inflammation versus germline mutation), suggesting that the miRNAs that we have identified are likely to regulate critical signaling pathways that are central to early events in transformation of colonic epithelial cells.

Messenger RNA and microRNA profiling during early mouse EB formation

Embryonic stem (ES) cells can be induced to differentiate into embryoid bodies (EBs) in a synchronised manner when plated at a fixed density in hanging drops. This differentiation procedure mimics post-implantation development in mouse embryos and also serves as the starting point of protocols used in differentiation of stem cells into various lineages. Currently, little is known about the potential influence of microRNAs (miRNAs) on mRNA expression patterns during EB formation. We have measured mRNA and miRNA expression in developing EBs plated in hanging drops until day 3, when discrete structural changes occur involving their differentiation into three germ layers. We observe significant alterations in mRNA and miRNA expression profiles during this early developmental time frame, in particular of genes involved in germ layer formation, stem cell pluripotency and nervous system development. Computational target prediction using Pictar, TargetScan and miRBase Targets reveals an enrichment of binding sites corresponding to differentially and highly expressed miRNAs in stem cell pluripotency genes and a neuroectodermal marker, Nes. We also find that members of let-7 family are significantly down-regulated at day 3 and the corresponding up-regulated genes are enriched in let-7 seed sequences. These results depict how miRNA expression changes may affect the expression of mRNAs involved in EB formation on a genome-wide scale. Understanding the regulatory effects of miRNAs during EB formation may enable more efficient derivation of different cell types in culture.

Two-tiered approach identifies a network of cancer and liver disease-related genes regulated by miR-122

MicroRNAs function as important regulators of gene expression and are commonly linked to development, differentiation, and diseases such as cancer. To better understand their roles in various biological processes, identification of genes targeted by microRNAs is necessary. Although prediction tools have significantly helped with this task, experimental approaches are ultimately required for extensive target search and validation. We employed two independent yet complementary high throughput approaches to map a large set of mRNAs regulated by miR-122, a liver-specific microRNA implicated in regulation of fatty acid and cholesterol metabolism, hepatitis C infection, and hepatocellular carcinoma. The combination of luciferase reporter-based screening and shotgun proteomics resulted in the identification of 260 proteins significantly down-regulated in response to miR-122 in at least one method, 113 of which contain predicted miR-122 target sites. These proteins are enriched for functions associated with the cell cycle, differentiation, proliferation, and apoptosis. Among these miR-122-sensitive proteins, we identified a large group with strong connections to liver metabolism, diseases, and hepatocellular carcinoma. Additional analyses, including examination of consensus binding motifs for both miR-122 and target sequences, provide further insight into miR-122 function.

Post-transcriptional regulation of ULBP1 ligand for the activating immunoreceptor NKG2D involves 3' untranslated region

The stress-inducible ULBP1 cell surface ligand for the activating immunoreceptor NKG2D allows recognition and lysis of tumor cells by natural killer (NK) and T cells. Understanding of mechanisms regulating ULBP1 expression is limited, but it is important for exploiting NKG2D-dependent antitumor responses. We studied the role of 3' untranslated region (3' UTR) in post-transcriptional regulation of ULBP1 expression in Jurkat and HeLa cells. Analysis of 2.4 kb-long 3' UTR revealed the presence of four AU-rich elements (ARE) and more then 200 putative microRNA binding sites. Stable or transient delivery of luciferase reporter constructs containing ULBP1-3' UTR sequences resulted in a strong reduction of luciferase activity to 7-22% with the full-length 3' UTR or 19%-62% with its fragments, indicating a contribution of 3' UTR to regulation of ULBP1 gene. Mutations introduced to ARE motifs significantly diminished luciferase activity, suggesting mRNA stabilizing effect of ARE. Among ULBP1-specific candidate microRNAs, we found miR-140-5p/-409-3p/-433-3p/-650 expressed in HeLa and Jurkat cells, and the microRNA involvement was supported by luciferase reporter assays with constructs carrying seed sequence mutations. However, microRNA overexpression or partial silencing of the microRNA processing enzyme Drosha did not equivocally clarify the role of microRNAs in regulation of ULBP1. Altogether these results provide evidence for a novel 3' UTR-mediated mechanism of regulation of ULBP1 at the post-transcriptional level.

MicroRNAs in skeletal muscle: their role and regulation in development, disease and function

Maintaining skeletal muscle function throughout the lifespan is a prerequisite for good health and independent living. For skeletal muscle to consistently function at optimal levels, the efficient activation of processes that regulate muscle development, growth, regeneration and metabolism is required. Numerous conditions including neuromuscular disorders, physical inactivity, chronic disease and ageing are associated with perturbations in skeletal muscle function. A loss or reduction in skeletal muscle function often leads to increased morbidity and mortality either directly, or indirectly, via the development of secondary diseases such as diabetes, obesity, cardiovascular and respiratory disease. Identifying mechanisms which influence the processes regulating skeletal muscle function is a key priority. The discovery of microRNAs (miRNAs) provides a new avenue that will extend our knowledge of factors controlling skeletal muscle function. miRNAs may also improve our understanding and application of current therapeutic approaches as well as enable the identification of new therapeutic strategies and targets aimed at maintaining and/or improving skeletal muscle health. This review brings together the latest developments in skeletal muscle miRNA biology and focuses on their role and regulation under physiological and patho-physiological conditions with an emphasis on: myogenesis, hypertrophy, atrophy and regeneration; exercise and nutrition; muscle disease, ageing, diabetes and obesity.

Circuitry of mRNA regulation

Some of the classical paradigms of gene regulation have been challenged by global-scale analysis of eukaryotic transcriptional and post-transcriptional gene regulation (PTGR), made possible by the development of genomics and proteomics tools. Post-transcriptional events in particular are increasingly being recognized as important sources of gene regulation. The hundreds of regulatory RNA-binding proteins that exist in eukaryotes may regulate dozens to hundreds of functionally related RNA targets. Likewise, the expression of considerable fractions of many eukaryotic genomes is affected by hundreds of non-coding RNAs, e.g., microRNAs. These findings suggest an enormous regulatory potential for PTGR that may affect virtually every message in a cell. All gene regulatory systems are composed of simple network circuits that coordinate the transfer of regulatory signals to a target gene/message.

MicroRNA-21 targets tumor suppressor genes ANP32A and SMARCA4

MicroRNA-21 (miR-21) is a key regulator of oncogenic processes. It is significantly elevated in the majority of human tumors and functionally linked to cellular proliferation, survival and migration. In this study, we used two experimental-based strategies to search for novel miR-21 targets. On the one hand, we performed a proteomic approach using two-dimensional differential gel electrophoresis (2D-DIGE) to identify proteins suppressed upon enhanced miR-21 expression in LNCaP human prostate carcinoma cells. The tumor suppressor acidic nuclear phosphoprotein 32 family, member A (ANP32A) (alias pp32 or LANP) emerged as the most strongly downregulated protein. On the other hand, we applied a mathematical approach to select correlated gene sets that are negatively correlated with primary-miR-21 (pri-miR-21) expression in published transcriptome data from 114 B-cell lymphoma cases. Among these candidates, we found tumor suppressor SMARCA4 (alias BRG1) together with the already validated miR-21 target, PDCD4. ANP32A and SMARCA4, which are both involved in chromatin remodeling processes, were confirmed as direct miR-21 targets by immunoblot analysis and reporter gene assays. Furthermore, knock down of ANP32A mimicked the effect of enforced miR-21 expression by enhancing LNCaP cell viability, whereas overexpression of ANP32A in the presence of high miR-21 levels abrogated the miR-21-mediated effect. In A172 glioblastoma cells, enhanced ANP32A expression compensated for the effects of anti-miR-21 treatment on cell viability and apoptosis. In addition, miR-21 expression clearly increased the invasiveness of LNCaP cells, an effect also seen in part upon downregulation of ANP32A. In conclusion, these results suggest that downregulation of ANP32A contributes to the oncogenic function of miR-21.

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.

Virus-encoded microRNAs

MicroRNAs (miRNAs) are the subject of enormous interest. They are small non-coding RNAs that play a regulatory role in numerous and diverse cellular processes such as immune function, apoptosis and tumorigenesis. Several virus families have been shown to encode miRNAs, and an appreciation for their roles in the viral infectious cycle continues to grow. Despite the identification of numerous (>225) viral miRNAs, an in depth functional understanding of most virus-encoded miRNAs is lacking. Here we focus on a few viral miRNAs with well-defined functions. We use these examples to extrapolate general themes of viral miRNA activities including autoregulation of viral gene expression, avoidance of host defenses, and a likely important role in maintaining latent and persistent infections. We hypothesize that although the molecular mechanisms and machinery are similar, the majority of viral miRNAs may utilize a target strategy that differs from host miRNAs. That is, many viral miRNAs may have evolved to regulate viral-encoded transcripts or networks of host genes that are unique to viral miRNAs. Included in this latter category is a likely abundant class of viral miRNAs that may regulate only one or a few principal host genes. Key steps forward for the field are discussed, including the need for additional functional studies that utilize surgical viral miRNA mutants combined with relevant models of infection.

The guideline of the design and validation of MiRNA mimics

The miRNA mimic technology (miR-Mimic) is an innovative approach for gene silencing. This approach is to generate nonnatural double-stranded miRNA-like RNA fragments. Such an RNA fragment is designed to have its 5'-end bearing a partially complementary motif to the selected sequence in the 3'UTR unique to the target gene. Once introduced into cells, this RNA fragment, mimicking an endogenous miRNA, can bind specifically to its target gene and produce posttranscriptional repression, more specifically translational inhibition, of the gene. Unlike endogenous miRNAs, miR-Mimics act in a gene-specific fashion. The miR-Mimic approach belongs to the "miRNA-targeting" and "miRNA-gain-of-function" strategy and is primarily used as an exogenous tool to study gene function by targeting mRNA through miRNA-like actions in mammalian cells. The technology was developed by my research group (Department of Medicine, Montreal Heart Institute, University of Montreal) in 2007 (Xiao, et al. J Cell Physiol 212:285-292, 2007; Xiao et al. Nat Cell Biol, in review).

Bioinformatics for RNomics

Rapid improvements in high-throughput experimental technologies make it nowadays possible to study the expression, as well as changes in expression, of whole transcriptomes under different environmental conditions in a detailed view. We describe current approaches to identify genome-wide functional RNA transcripts (experimentally as well as computationally), and focus on computational methods that may be utilized to disclose their function. While genome databases offer a wealth of information about known and putative functions for protein-coding genes, functional information for novel non-coding RNA genes is almost nonexistent. This is mainly explained by the lack of established software tools to efficiently reveal the function and evolutionary origin of non-coding RNA genes. Here, we describe in detail computational approaches one may follow to annotate and classify an RNA transcript.

Impact of microRNA in normal and pathological respiratory epithelia

Extensive sequencing efforts, combined with ad hoc bioinformatics developments, have now led to the identification of 1222 distinct miRNAs in human (derived from 1368 distinct genomic loci) and of many miRNAs in other multicellular organisms. The present chapter is aimed at describing a general experimental strategy to identify specific miRNA expression profiles and to highlight the functional networks operating between them and their mRNA targets, including several miRNAs deregulated in cystic fibrosis and during differentiation of airway epithelial cells.

Toward a durable treatment of HIV-1 infection using RNA interference

RNA interference (RNAi) is a cellular mechanism that mediates sequence-specific gene silencing at the posttranscriptional level. RNAi can be used as an antiviral approach against human pathogens. An attractive target for RNAi therapeutics is the human immunodeficiency virus type 1 (HIV-1), and the first clinical trial using a lentiviral gene therapy was initiated in early 2008. In this chapter, we focus on some basic principles of such an RNAi-based gene therapy against HIV-1. This includes the subjects of target site selection within the viral RNA genome, the phenomenon of viral escape, and therapeutic strategies to prevent viral escape. The latter antiescape strategies include diverse combinatorial RNAi approaches that are all directed against the HIV-1 RNA genome. As an alternative strategy, we also discuss the possibilities and restrictions of targeting cellular cofactors that are essential for virus replication, but less important for cell physiology.

Prediction of the biological effect of polymorphisms within microRNA binding sites

MicroRNAs (miRNAs) are negative gene regulators acting at the 3'UTR level, modulating the translation of cancer-related genes. Single-nucleotide polymorphisms (SNPs) within the 3'UTRs could impact the miRNA-dependent gene regulation either by weakening or by reinforcing the binding sites. Thus, the alteration of the normal regulation of a given gene could affect the individual's risk of cancer. Therefore, it is helpful to develop a tool enabling the researchers to predict which of the many SNPs could really impact the regulation of a target gene. At present, there are several available databases and algorithms able to predict potential binding sites in the 3'UTR of genes. However, each algorithm gives different predictions and none of them gives, for each polymorphism, a direct measurement of the biological impact. We propose an approach allowing the assignment to each polymorphism a ranking of its biological impact. The method is based on a simple elaboration of predictions from preexisting well-established algorithms. As an example, we show the application of this approach to 140 genes candidate for colorectal cancer (CRC). These genes were identified following a genome-wide sequencing of 20,857 transcripts from 18,191 genes in 11 CRC specimens and were found somatically mutated and thought to be crucial for the development of cancer.

Advances in understanding the roles of microRNA in hepatitis virus infection

Hepatitis B virus (HBV) and hepatitis C virus (HCV) can cause viral hepatitis. HBV or HCV infection is the major risk factor for cirrhosis and hepatocellular carcinoma (HCC). MicroRNAs (miRNAs) can regulate post-transcriptional gene expression and participate in the control of diverse biological processes. Recent studies have identified the important roles of miRNAs in multiple aspects of hepatitis viruses, including replication, gene expression and pathogensis. MiRNA-based drugs may shed light on the treatment of hepatitis virus infection. In this review, we discuss the latest advances in the research of miRNAs involved in hepatitis virus infection.

A study of miRNAs targets prediction and experimental validation

microRNAs (miRNAs) are 20-24 nucleotide (nt) RNAs that regulate eukaryotic gene expression post-transcriptionally by the degradation or translational inhibition of their target messenger RNAs (mRNAs). To identify miRNA target genes will help a lot by understanding their biological functions. Sophisticated computational approaches for miRNA target prediction, and effective biological techniques for validating these targets now play a central role in elucidating their functions. Owing to the imperfect complementarity of animal miRNAs with their targets, it is difficult to judge the accuracy of the prediction. Complexity of regulation by miRNA-mediated targets at protein and mRNAs levels has made it more challenging to identify the targets. To date, only a few miRNAs targets are confirmed. In this article, we review the methods of miRNA target prediction and the experimental validation for their corresponding mRNA targets in animals.

A BAYESIAN GRAPHICAL MODELING APPROACH TO MICRORNA REGULATORY NETWORK INFERENCE

It has been estimated that about 30% of the genes in the human genome are regulated by microRNAs (miRNAs). These are short RNA sequences that can down-regulate the levels of mRNAs or proteins in animals and plants. Genes regulated by miRNAs are called targets. Typically, methods for target prediction are based solely on sequence data and on the structure information. In this paper we propose a Bayesian graphical modeling approach that infers the miRNA regulatory network by integrating expression levels of miRNAs with their potential mRNA targets and, via the prior probability model, with their sequence/structure information. We use a directed graphical model with a particular structure adapted to our data based on biological considerations. We then achieve network inference using stochastic search methods for variable selection that allow us to explore the huge model space via MCMC. A time-dependent coefficients model is also implemented. We consider experimental data from a study on a very well-known developmental toxicant causing neural tube defects, hyperthermia. Some of the pairs of target gene and miRNA we identify seem very plausible and warrant future investigation. Our proposed method is general and can be easily applied to other types of network inference by integrating multiple data sources.

A Bayesian approach for identifying miRNA targets by combining sequence prediction and gene expression profiling

Background

MicroRNAs (miRNAs) are single-stranded non-coding RNAs shown to plays important regulatory roles in a wide range of biological processes and diseases. The functions and regulatory mechanisms of most of miRNAs are still poorly understood in part because of the difficulty in identifying the miRNA regulatory targets. To this end, computational methods have evolved as important tools for genome-wide target screening. Although considerable work in the past few years has produced many target prediction algorithms, most of them are solely based on sequence, and the accuracy is still poor. In contrast, gene expression profiling from miRNA transfection experiments can provide additional information about miRNA targets. However, most of existing research assumes down-regulated mRNAs as targets. Given the fact that the primary function of miRNA is protein inhibition, this assumption is neither sufficient nor necessary.

Results

A novel Bayesian approach is proposed in this paper that integrates sequence level prediction with expression profiling of miRNA transfection. This approach does not restrict the target to be down-expressed and thus improve the performance of existing target prediction algorithm. The proposed algorithm was tested on simulated data, proteomics data, and IP pull-down data and shown to achieve better performance than existing approaches for target prediction. All the related materials including source code are available at http://compgenomics.utsa.edu/expmicro.html.

Conclusions

The proposed Bayesian algorithm integrates properly the sequence paring data and mRNA expression profiles for miRNA target prediction. This algorithm is shown to have better prediction performance than existing algorithms.

Targets for human encoded microRNAs in HBV genes

MicroRNAs (miRNAs) are increasingly being shown to play vital roles in development, apoptosis, and oncogenesis by interfering with gene expression at the post-transcriptional level. miRNAs, in principle, can contribute to the repertoire of host-pathogen interactions during infection by the Hepatitis B virus (HBV). Using a consensus-scoring approach, high-scoring miRNA-target pairs were selected, which were identified by four well-established target-prediction softwares. The miRNAs miR-7, miR196b, miR433, and miR511 target the polymerase or S gene of HBV, miR205 targets the X gene, and miR345 targets the preC gene. The minimum free-energy values for the bound complexes were the lowest, and the rules so far observed for miRNA-target pairing, namely, (1) pairing at a continuous stretch of 6-7 bases toward the 5'-end of the miRNA and (2) incomplete complementarity with the target sequence, were found to be valid. The target regions were highly conserved across the various clades of HBV. miRNA expression profiles from previously reported Solexa-sequencing based experiments showed that the four human miRNAs are expressed in the liver. This is the first report of human miRNAs that can target crucial HBV genes.

Involvement of microRNAs in physiological and pathological processes in the lung

To date, at least 900 different microRNA (miRNA) genes have been discovered in the human genome. These short, single-stranded RNA molecules originate from larger precursor molecules that fold to produce hairpin structures, which are subsequently processed by ribonucleases Drosha/Pasha and Dicer to form mature miRNAs. MiRNAs play role in the posttranscriptional regulation of about one third of human genes, mainly via degradation of target mRNAs. Whereas the target mRNAs are often involved in the regulation of diverse physiological processes ranging from developmental timing to apoptosis, miRNAs have a strong potential to regulate fundamental biological processes also in the lung compartment. However, the knowledge of the role of miRNAs in physiological and pathological conditions in the lung is still limited. This review, therefore, summarizes current knowledge of the mechanism, function of miRNAs and their contribution to lung development and homeostasis. Besides the involvement of miRNAs in pulmonary physiological conditions, there is evidence that abnormal miRNA expression may lead to pathological processes and development of various pulmonary diseases. Next, the review describes current state-of-art on the miRNA expression profiles in smoking-related diseases including lung cancerogenesis, in immune system mediated pulmonary diseases and fibrotic processes in the lung. From the current research it is evident that miRNAs may play role in the posttranscriptional regulation of key genes in human pulmonary diseases. Further studies are, therefore, necessary to explore miRNA expression profiles and their association with target mRNAs in human pulmonary diseases.

Sizing up the future of microRNA analysis

In less than 20 years, our appreciation for micro-RNA molecules (miRNAs) has grown from an original, curious observation in worms to their current status as incredibly important global regulators of gene expression that play key roles in many transformative biological processes. As our understanding of these small, non-coding transcripts continues to evolve, new approaches for their analysis are emerging. In this critical review we describe recent improvements to classical methods of detection as well as innovative new technologies that are poised to help shape the future landscape of miRNA analysis.

microRNA: a master regulator of cellular processes for bioengineering systems

microRNAs (miRNAs) are small RNAs 18 to 24 nucleotides in length that serve the pivotal function of regulating gene expression. Instead of being translated into proteins, the mature single-stranded miRNA binds to messenger RNAs (mRNAs) to interfere with the translational process. It is estimated that whereas only 1% of the genomic transcripts in mammalian cells encode miRNA, nearly one-third of the encoded genes are regulated by miRNA. Various bioinformatics databases, tools, and algorithms have been developed to predict the sequences of miRNAs and their target genes. In combination with the in silico approaches in systems biology, experimental studies on miRNA provide a new bioengineering approach for understanding the mechanism of fine-tuning gene regulation. This review aims to provide state-of-the-art information on this important mechanism of gene regulation for researchers working in biomedical engineering and related fields. Particular emphases are placed on summarizing the current tools and strategies for miRNA study from a bioengineering perspective and the possible applications of miRNAs (such as antagomirs and miRNA sponges) in biomedical engineering research.

Ranking of microRNA target prediction scores by Pareto front analysis

Over the past ten years, a variety of microRNA target prediction methods has been developed, and many of the methods are constantly improved and adapted to recent insights into miRNA-mRNA interactions. In a typical scenario, different methods return different rankings of putative targets, even if the ranking is reduced to selected mRNAs that are related to a specific disease or cell type. For the experimental validation it is then difficult to decide in which order to process the predicted miRNA-mRNA bindings, since each validation is a laborious task and therefore only a limited number of mRNAs can be analysed. We propose a new ranking scheme that combines ranked predictions from several methods and - unlike standard thresholding methods - utilises the concept of Pareto fronts as defined in multi-objective optimisation. In the present study, we attempt a proof of concept by applying the new ranking scheme to hsa-miR-21, hsa-miR-125b, and hsa-miR-373 and prediction scores supplied by PITA and RNAhybrid. The scores are interpreted as a two-objective optimisation problem, and the elements of the Pareto front are ranked by the STarMir score with a subsequent re-calculation of the Pareto front after removal of the top-ranked mRNA from the basic set of prediction scores. The method is evaluated on validated targets of the three miRNA, and the ranking is compared to scores from DIANA-microT and TargetScan. We observed that the new ranking method performs well and consistent, and the first validated targets are elements of Pareto fronts at a relatively early stage of the recurrent procedure, which encourages further research towards a higher-dimensional analysis of Pareto fronts.

Improving performance of mammalian microRNA target prediction

Background

MicroRNAs (miRNAs) are single-stranded non-coding RNAs known to regulate a wide range of cellular processes by silencing the gene expression at the protein and/or mRNA levels. Computational prediction of miRNA targets is essential for elucidating the detailed functions of miRNA. However, the prediction specificity and sensitivity of the existing algorithms are still poor to generate meaningful, workable hypotheses for subsequent experimental testing. Constructing a richer and more reliable training data set and developing an algorithm that properly exploits this data set would be the key to improve the performance current prediction algorithms.

Results

A comprehensive training data set is constructed for mammalian miRNAs with its positive targets obtained from the most up-to-date miRNA target depository called miRecords and its negative targets derived from 20 microarray data. A new algorithm SVMicrO is developed, which assumes a 2-stage structure including a site support vector machine (SVM) followed by a UTR-SVM. SVMicrO makes prediction based on 21 optimal site features and 18 optimal UTR features, selected by training from a comprehensive collection of 113 site and 30 UTR features. Comprehensive evaluation of SVMicrO performance has been carried out on the training data, proteomics data, and immunoprecipitation (IP) pull-down data. Comparisons with some popular algorithms demonstrate consistent improvements in prediction specificity, sensitivity and precision in all tested cases. All the related materials including source code and genome-wide prediction of human targets are available at http://compgenomics.utsa.edu/svmicro.html.

Conclusions

A 2-stage SVM based new miRNA target prediction algorithm called SVMicrO is developed. SVMicrO is shown to be able to achieve robust performance. It holds the promise to achieve continuing improvement whenever better training data that contain additional verified or high confidence positive targets and properly selected negative targets are available.

Got target? Computational methods for microRNA target prediction and their extension

MicroRNAs (miRNAs) are a class of small RNAs of 19-23 nucleotides that regulate gene expression through target mRNA degradation or translational gene silencing. The miRNAs are reported to be involved in many biological processes, and the discovery of miRNAs has been provided great impacts on computational biology as well as traditional biology. Most miRNA-associated computational methods comprise the prediction of miRNA genes and their targets, and increasing numbers of computational algorithms and web-based resources are being developed to fulfill the need of scientists performing miRNA research. Here we summarize the rules to predict miRNA targets and introduce some computational algorithms that have been developed for miRNA target prediction and the application of the methods. In addition, the issue of target gene validation in an experimental way will be discussed.

MicroRNA hsa-miR-135b regulates mineralization in osteogenic differentiation of human unrestricted somatic stem cells

Unrestricted somatic stem cells (USSCs) have been recently identified in human umbilical cord blood and have been shown to differentiate into lineages representing all 3 germ layers. To characterize microRNAs that may regulate osteogenic differentiation of USSCs, we carried out expression analysis for 157 microRNAs using quantitative RT-PCR before and after osteogenic induction (t = 0.5, 24, 72, 168, 216 h). Three microRNAs, hsa-miR-135b, hsa-miR-224, and hsa-miR-31, were consistently down-regulated during osteogenesis of USSC line 1. Hsa-miR-135b was shown to be the most profoundly down-regulated in osteogenesis of USSC line 1 and further confirmed to be down-regulated in the osteogenic differentiation of 2 additional USSC lines. Function of hsa-miR-135b in osteogenesis of USSCs was examined by retroviral overexpression, which resulted in an evident decreased mineralization, indicating that hsa-miR-135b down-regulation is functionally important for full osteogenic differentiation of USSCs. MicroRNAs have been shown to regulate negatively expression of their target gene(s). To identify putative targets of hsa-miR-135b, we performed cDNA microarray expression analysis. We selected in total 10 transcripts that were down-regulated (>or=2-fold) in response to hsa-miR-135b overexpression at day 7 and day 9 of osteogenic differentiation. The function of most of these targets in human osteogenesis is unknown and requires further investigation. Markedly, quantitative RT-PCR data showed decreased expression of osteogenic markers IBSP and Osterix, both known to be involved in bone mineralization, in osteogenesis of USSCs that overexpress hsa-miR-135b. This finding suggests that hsa-miR-135b may control osteoblastic differentiation of USSCs by regulating expression of bone-related genes.

Expression of microRNAs and their target mRNAs in human stem cell-derived cardiomyocyte clusters and in heart tissue

Recent studies have shown that microRNAs (miRNAs) act as posttranscriptional regulators and that they play important roles during heart development and in cardiac function. Thus, they may provide new means of altering stem cell fate and differentiation processes. However, information about the correlation between global miRNA and mRNA expression in cardiomyocyte clusters (CMCs) derived from human embryonic stem cells (hESC) and in fetal and adult heart tissue is lacking. In the present study the global miRNA and mRNA expression in hESC-derived CMCs and in fetal and adult heart tissue was investigated in parallel using microarrays. Target genes for the differentially expressed miRNAs were predicted using computational methods, and the concordance in miRNA expression and mRNA levels of potential target genes was determined across the experimental samples. The biology of the predicted target genes was further explored regarding their molecular functions and involvement in known regulatory pathways. A clear correlation between the global miRNA expression and corresponding target mRNA expression was observed. Using three different sources of cardiac tissue-like samples, we defined the similarities between in vitro hESC-derived CMCs and their in vivo counterparts. The results are in line with previously reported observations that miRNAs repress mRNA expression and additionally identify a number of novel miRNAs with potential important roles in human cardiac tissue. The concordant miRNA expression pattern observed among all the cardiac tissue-like samples analyzed here provide a starting point for future ambitious studies aiming towards assessment of the functional roles of specific miRNAs during cardiomyocyte differentiation.

Cooperative and individualistic functions of the microRNAs in the miR-23a~27a~24-2 cluster and its implication in human diseases

The small RNA molecules of about 19-22 nucleotides in length, aptly called microRNAs, perform the task of gene regulation in the cell. Interestingly, till the early nineties very little was known about them but eventually, the microRNAs have become forefront in the area of research. The huge number of microRNAs plus each one of them targeting a vast number of related as well as unrelated genes makes them very interesting molecules to study. To add to the mystery of miRNAs is the fact that the same miRNA can have antagonizing role in two different cell types i.e. in one cell type; the miRNA promotes proliferation whereas in another cell type the same miRNA inhibits proliferation. Another remarkable aspect of the microRNAs is that many of them exist in clusters. In humans alone, out of 721 microRNAs known, 247 of them occur in 64 clusters at an inter-miRNA distance of less than 5000bp. The reason for this clustering of miRNAs is not fully understood but since the miRNA clusters are evolutionary conserved, their significance cannot be ruled out. The objective of this review is to summarize the recent progress on the functional characterization of miR-23a~27a~24-2 cluster in humans in relation to various health and diseased conditions and to highlight the cooperative effects of the miRNAs of this cluster.

Clinical applications of miRNAs in cardiac remodeling and heart failure

MicroRNAs (miRNAs or miRs) are short, highly conserved noncoding RNAs that regulate gene expression at the post-transcriptional level by inhibiting translation or promoting the degradation of target mRNA. Even though the field of miRNA biology is relatively young, growing lines of evidence suggest that miRNAs play a key role pathogenesis of heart failure through their ability to regulate genes that govern the process of adaptive and maladaptive cardiac remodeling. Herein, we review the biology of miRNAs in relation to their role in modulating various aspects of the cardiac remodeling process, as well as discuss the potential applications of miRNA biology to the field of heart failure.

A model-based strategy to investigate the role of microRNA regulation in cancer signalling networks

In this paper we present and discuss a model-based approach to link miRNA translational control with cell signalling networks. MicroRNAs are small regulatory RNAs that are able to regulate the activity and the stability of specific messenger RNA and have been implicated in tumour progression due to their ability to translationally regulate critical oncogenes and tumour suppressors. In our approach, data on protein-protein interactions and miRNA regulation, obtained from bioinformatics databases, are integrated with quantitative experimental data using mathematical modelling. Predictive computational simulations and qualitative (bifurcation) analyses of those mathematical models are employed to further support the investigation of such multifactorial networks in the context of cancer progression. We illustrate our approach with the C-Myc/E2F signalling network, involved in the progression of several tumour subtypes, including colorectal cancer.

Flanking region sequence information to refine microRNA target predictions

The non-coding elements of a genome, with many of them considered as junk earlier, have now started gaining long due respectability, with microRNAs as the best current example. MicroRNAs bind preferentially to the 3' untranslated regions 9UTRs) of the target genes and negatively regulate their expression most of the time. Several microRNA: target prediction softwares have been developed based upon various assumptions and the majority of them consider the free energy of binding of a target to its microRNA and seed conservation. However, the average concordance between the predictions made by these softwares is limited and compounded by a large number of false-positive results. In this study, we describe a methodology developed by us to refine microRNA: target prediction by target prediction softwares through observations made from a comprehensive study. We incorporated the information obtained from dinucleotide content variation patterns recorded for flanking regions around the target sites using support vector machines (SVMs) trained over two different major sources of experimental data, besides other sources. We assessed the performance of our methodology with rigorous tests over four different dataset models and also compared it with a recently published refinement tool, MirTif. Our methodology attained a higher average accuracy of 0.88, average sensitivity and specificity of 0.81 and 0.94, respectively, and areas under the curves (AUCs) for all the four models scored above 0.9, suggesting better performance by our methodology and a possible role of flanking regions in microRNA targeting control. We used our methodology over genes of three different pathways--toll-like receptor (TLR), apoptosis and insulin--to finally predict the most probable targets. We also investigated their possible regulatory associations, and identified a hsa-miR-23a regulatory module.

The impact of miR-34a on protein output in hepatocellular carcinoma HepG2 cells

MicroRNAs are small non-coding RNA molecules that play essential roles in biological processes ranging from cell cycle to cell migration and invasion. Accumulating evidence suggests that miR-34a, as a key mediator of p53 tumor suppression, is aberrantly expressed in human cancers. In the present study, we aimed to explore the precise biological role of miR-34a and the global protein changes in HCC cell line HepG2 cells transiently transfected with miR-34a. Transfection of miR-34a into HepG2 cells caused suppression of cell proliferation, inhibition of cell migration and invasion. It also induced an accumulation of HepG2 cells in G1 phase. Among 116 protein spots with differential expression separated by 2-DE method, 34 proteins were successfully identified by MALDI-TOF/TOF analysis. Of these, 15 downregulated proteins may be downstream targets of miR-34a. Bioinformatics analysis produced a protein-protein interaction network, which revealed that the p53 signaling pathway and cell cycle pathway were two major hubs containing most of the proteins regulated by miR-34a. Cytoskeletal proteins such as LMNA, GFAP, MACF1, ALDH2, and LOC100129335 are potential targets of miR-34a. In conclusion, abrogation of miR-34a function could cause downstream molecules to switch on or off, leading to HCC development.