Physiological identification of human transcripts translationally regulated by a specific microRNA

Alternative splicing impacts microRNA regulation within coding regions

MicroRNAs (miRNAs) are small non-coding RNA molecules that bind to target sites in different gene regions and regulate post-transcriptional gene expression. Approximately 95% of human multi-exon genes can be spliced alternatively, which enables the production of functionally diverse transcripts and proteins from a single gene. Through alternative splicing, transcripts might lose the exon with the miRNA target site and become unresponsive to miRNA regulation. To check this hypothesis, we studied the role of miRNA target sites in both coding and non-coding regions using six cancer data sets from The Cancer Genome Atlas (TCGA) and Parkinson's disease data from PPMI. First, we predicted miRNA target sites on mRNAs from their sequence using TarPmiR. To check whether alternative splicing interferes with this regulation, we trained linear regression models to predict miRNA expression from transcript expression. Using nested models, we compared the predictive power of transcripts with miRNA target sites in the coding regions to that of transcripts without target sites. Models containing transcripts with target sites perform significantly better. We conclude that alternative splicing does interfere with miRNA regulation by skipping exons with miRNA target sites within the coding region.

Changes in circulating microRNA after recumbent isometric yoga practice by patients with myalgic encephalomyelitis/chronic fatigue syndrome: an explorative pilot study

Background

Yoga is a representative mind-body therapy. Our previous studies have demonstrated that isometric yoga (i.e. yoga programs that we developed so individuals can practice yoga poses with a self-adjustable isometric load) reduces the fatigue of patients with myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS); however, the underlying mechanisms remain unclear. Several studies have suggested that the micro-ribonucleic acid (miRNA) expression of ME/CFS patients is different from that of healthy subjects. However, it has not to date been determined if the practice of isometric yoga can affect miRNA expression. Therefore, we sought to investigate if isometric yoga is associated with changes in the expression levels of serum miRNA of patients with ME/CFS.

Methods

The study included nine patients with ME/CFS who failed to show satisfactory improvement after at least 6 months of treatment administered at our hospital. Patients practiced recumbent isometric yoga for 3 months; they met with a yoga instructor every 2 to 4 weeks and participated in daily in-home sessions. The effect of recumbent isometric yoga on fatigue was assessed by comparing pre- and post-intervention scores on the Japanese version of the 11-item Chalder fatigue scale (CFQ 11). Patient blood samples were drawn pre- and post-intervention, just prior to practicing recumbent isometric yoga with an instructor. The serum was used for miRNA array analysis with known human miRNAs.

Results

The average CFQ 11 score decreased significantly (from 25.3 ± 5.5 to 17.0 ± 5.8, p <  0.0001) after practicing recumbent isometric yoga for 3 months. The miRNA microarray analysis revealed that four miRNAs were significantly upregulated, and 42 were downregulated after the intervention period.

Conclusions

This explorative pilot study is the first to demonstrate changes in the serum levels of several miRNAs after regular practice of recumbent isometric yoga. These miRNAs might represent biomarkers for the fatigue-relieving effects of isometric yoga of patients with ME/CFS.

Trial registration

University Hospital Medical Information Network (UMIN CTR) 000023472. Registered Aug 4, 2016.

A rank-based algorithm of differential expression analysis for small cell line data with statistical control

To detect differentially expressed genes (DEGs) in small-scale cell line experiments, usually with only two or three technical replicates for each state, the commonly used statistical methods such as significance analysis of microarrays (SAM), limma and RankProd (RP) lack statistical power, while the fold change method lacks any statistical control. In this study, we demonstrated that the within-sample relative expression orderings (REOs) of gene pairs were highly stable among technical replicates of a cell line but often widely disrupted after certain treatments such like gene knockdown, gene transfection and drug treatment. Based on this finding, we customized the RankComp algorithm, previously designed for individualized differential expression analysis through REO comparison, to identify DEGs with certain statistical control for small-scale cell line data. In both simulated and real data, the new algorithm, named CellComp, exhibited high precision with much higher sensitivity than the original RankComp, SAM, limma and RP methods. Therefore, CellComp provides an efficient tool for analyzing small-scale cell line data.

Genome-Wide Analysis of MicroRNA-Regulated Transcripts

MicroRNAs (miRNAs) are small noncoding RNAs that regulate gene expression by either degrading transcripts or repressing translation . Over the past decade the significance of miRNAs has been unraveled by the characterization of their involvement in crucial cellular functions and the development of disease. However, continued progress in understanding the endogenous importance of miRNAs, as well as their potential uses as therapeutic tools, has been hindered by the difficulty of positively identifying miRNA targets. To face this challenge algorithmic approaches have primarily been utilized to date, but strictly mathematical models have thus far failed to produce a generally accurate, widely accepted methodology for accurate miRNA target determination. As such, several laboratory-based, comprehensive strategies for experimentally identifying all cellular miRNA regulations simultaneously have recently been developed. This chapter discusses the advantages and limitations of both classic and comprehensive strategies for miRNA target prediction .

Differential expression of microRNAs in the brains of mice subjected to increasing grade of mild traumatic brain injury

OBJECTIVE

To investigate the effect of heterogeneity in mTBI on miRNA expression in mouse brain and to identify molecular pathways targeted by the modulated miRNAs.

METHODS

A weight drop device was used to induce four increasing grades of mTBI. MiRNA expression was evaluated using TaqMan rodent miRNA arrays. Bioinformatics analysis was done using the DIANA miRPath tool and Ingenuity Pathway Analysis software. Histology of brain sections was evaluated using H&E staining.

RESULTS

No histologic lesions were observed in the brains of injured mice; however, significant modulation in miRNA expression profile was observed. Global miRNA profiling indicated a trend of decrease in the number of modulated miRNAs from 24 hours to day 7 post-injury, except for the most severe grade of mTBI. Canonical pathways like calcium signalling, synaptic pathways and axon guidance pathway were the major targets of the modulated miRNAs. Network correlation analyses indicated an interaction between the modulated miRNAs and putative protein biomarkers of TBI.

CONCLUSIONS

The data demonstrated that varying intensities of mTBI induced a differential miRNA expression profile in the brain post-injury. Pathways such as calcium and synaptic signalling were major targets of modulated miRNAs and may play a role in the pathophysiology of mTBI.

MicroRNA expression in hepatocellular carcinoma after the eradication of chronic hepatitis virus C infection using interferon therapy

AIM

Hepatocellular carcinoma (HCC) develops in up to 5% of patients after the successful treatment of chronic hepatitis C virus (HCV) infection using interferon therapy. The aim of this study was to characterize miRNA expression in liver tissues from patients who achieved a sustained viral response (SVR).

METHODS

Seventy-one patients with resected HCC were enrolled into the present study: 61 HCC from patients with continuously infected HCV (HCV-HCC) and 10 from patients who had achieved SVR (SVR-HCC). We also included non-tumor tissues (SVR-NT) from four patients with SVR-HCC, and liver tissue (SVR-CH) from four SVR patients without HCC. Total RNA was extracted from liver samples. The miRNA expression patterns were analyzed using microarrays. In addition, target gene expression was quantified after miRNA overexpression in HEK293 cells.

RESULTS

We could discriminate between SVR-HCC and HCV-HCC with 75.36% accuracy using the expression pattern of six specific miRNA. The expression levels of 37 miRNA were significantly lower in HCV-HCC than in SVR-HCC, whereas the expression of 25 miRNA was significantly higher in HCV-HCC than SVR-HCC (P < 1.0E-05). The expression of thrombospondin 1 was regulated in an opposing manner by miR-30a-3p in SVR-HCC and HCV-HCC. In non-tumor tissues, the expression pattern of seven miRNA could distinguish between SVR-CH and SVR-NT with 87.50% accuracy.

CONCLUSION

Comprehensive miRNA expression analyses could not only differentiate between SVR-HCC and HCV-HCC but also forecast hepatocarcinogenesis after achieving SVR.

MicroRNA profiling of the whitefly Bemisia tabaci Middle East-Aisa Minor I following the acquisition of Tomato yellow leaf curl China virus

Background

The begomoviruses are the largest and most economically important group of plant viruses exclusively vectored by whitefly (Bemisia tabaci) in a circulative, persistent manner. During this process, begomoviruses and whitefly vectors have developed close relationships and complex interactions. However, the molecular mechanisms underlying these interactions remain largely unknown, and the microRNA profiles for viruliferous and nonviruliferous whiteflies have not been studied.

Methods

Sequences of Argonaute 1(Ago1) and Dicer 1 (Dcr1) genes were cloned from B. tabaci MEAM1 cDNAs. Subsequently, deep sequencing of small RNA libraries from uninfected and Tomato yellow leaf curl China virus (TYLCCNV)-infected whiteflies was performed. The conserved and novel miRNAs were identified using the release of miRBase Version 19.0 and the prediction software miRDeep2, respectively. The sequencing results of selected deregulated and novel miRNAs were further confirmed using quantitative reverse transcription-PCR. Moreover, the previously published B. tabaci MEAM1 transcriptome database and the miRNA target prediction algorithm miRanda 3.1 were utilized to predict potential targets for miRNAs. Gene Ontology (GO) analysis was also used to classify the potential enriched functional groups of their putative targets.

Results

Ago1 and Dcr1orthologs with conserved domains were identified from B. tabaci MEAM1. BLASTn searches and sequence analysis identified 112 and 136 conserved miRNAs from nonviruliferous and viruliferous whitefly libraries respectively, and a comparison of the conserved miRNAs of viruliferous and nonviruliferous whiteflies revealed 15 up- and 9 down-regulated conserved miRNAs. 7 novel miRNA candidates with secondary pre-miRNA hairpin structures were also identified. Potential targets of conserved and novel miRNAs were predicted using GO analysis, for the targets of up- and down-regulated miRNAs, eight and nine GO terms were significantly enriched.

Conclusions

We identified Ago1 and Dcr1 orthologs from whiteflies, which indicated that miRNA-mediated silencing is present in whiteflies. Our comparative analysis of miRNAs from TYLCCNV viruliferous and nonviruliferous whiteflies revealed the relevance of deregulated miRNAs for the post-transcriptional gene regulation in these whiteflies. The potential targets of all expressed miRNAs were also predicted. These results will help to acquire a better understanding of the molecular mechanism underlying the complex interactions between begomoviruses and whiteflies.

Electronic supplementary material

The online version of this article (doi:10.1186/s12985-016-0469-7) contains supplementary material, which is available to authorized users.

microRNAs regulate cell-to-cell variability of endogenous target gene expression in developing mouse thymocytes

The development and homeostasis of multicellular organisms relies on gene regulation within individual constituent cells. Gene regulatory circuits that increase the robustness of gene expression frequently incorporate microRNAs as post-transcriptional regulators. Computational approaches, synthetic gene circuits and observations in model organisms predict that the co-regulation of microRNAs and their target mRNAs can reduce cell-to-cell variability in the expression of target genes. However, whether microRNAs directly regulate variability of endogenous gene expression remains to be tested in mammalian cells. Here we use quantitative flow cytometry to show that microRNAs impact on cell-to-cell variability of protein expression in developing mouse thymocytes. We find two distinct mechanisms that control variation in the activation-induced expression of the microRNA target CD69. First, the expression of miR-17 and miR-20a, two members of the miR-17-92 cluster, is co-regulated with the target mRNA Cd69 to form an activation-induced incoherent feed-forward loop. Another microRNA, miR-181a, acts at least in part upstream of the target mRNA Cd69 to modulate cellular responses to activation. The ability of microRNAs to render gene expression more uniform across mammalian cell populations may be important for normal development and for disease.

microRNAs are integral to many developmental processes and may 'canalise' development by reducing cell-to-cell variation in gene expression. This idea is supported by computational studies that have modeled the impact of microRNAs on the expression of their targets and the construction of artificial incoherent feedforward loops using synthetic biology tools. Here we show that this interesting principle of microRNA regulation actually occurs in a mammalian developmental system. We examine cell-to-cell variation of protein expression in developing mouse thymocytes by quantitative flow cytometry and find that the absence of microRNAs results in increased cell-to-cell variation in the expression of the microRNA target Cd69. Mechanistically, T cell receptor signaling induces both Cd69 and miR-17 and miR-20a, two microRNAs that target Cd69. Co-regulation of microRNAs and their target mRNA dampens the expression of Cd69 and forms an incoherent feedforward loop that reduces cell-to-cell variation on CD69 expression. In addition, miR-181, which also targets Cd69 and is a known modulator of T cell receptor signaling, also affects cell-to-cell variation of CD69 expression. The ability of microRNAs to control the uniformity of gene expression across mammalian cell populations may be important for normal development and for disease.

A summary for molecular regulations of miRNAs in breast cancer

BACKGROUND

Breast cancer is the most frequently diagnosed cancer and the leading cause of cancer-related death among women worldwide. MicroRNAs (miRNAs) are naturally-occurring, non-coding small RNA molecules that can modulate protein coding-genes, which makes it contributing to nearly all the physiological and pathological processes. Progression of breast cancer and resistance to endocrine therapies have been attributed to the possibility of hormone-responsive miRNAs involved in the regulation of certain signaling pathways.

METHODOLOGY

This review introduces better understanding of miRNAs to provide promising advances for treatment. miRNAs have multiple targets, and they were found to regulate different signaling pathways; consequently it is important to characterize their mechanisms of action and their cellular targets in order to introduce miRNAs as novel and promising therapies.

RESULTS

This review summarizes the molecular mechanisms of miRNAs in TGF-beta signaling, apoptosis, metastasis, cell cycle, ER-signaling, and drug resistance.

CONCLUSION

Finally, miRNAs will be introduced as promising molecules to be used in the fight against breast cancer and its developed drug resistance.

Genomic alterations as mediators of miRNA dysregulation in ovarian cancer

Ovarian cancer is the fifth most common cause of cancer death in women worldwide. Serous epithelial ovarian cancer (SEOC) is the most common and aggressive histological subtype. Widespread genomic alterations go hand-in-hand with aberrant DNA damage signaling and are a hallmark of high-grade SEOC. MicroRNAs (miRNAs) are a class of small noncoding RNA molecules that are nonrandomly distributed in the genome. They are frequently located in chromosomal regions susceptible to copy number variation (CNV) associated with malignancy that can influence their expression. Widespread changes in miRNA expression have been reported in multiple cancer types including ovarian cancer. This review examines CNV and single nucleotide polymorphisms, two common types of genomic alterations that occur in ovarian cancer, in the context of their influence on the expression of miRNA and the ability of miRNA to bind to and regulate their target genes. This includes genes encoding proteins involved in DNA repair and the maintenance of genomic stability. Improved understanding of mechanisms of miRNA dysregulation and the role of miRNA in ovarian cancer will provide further insight into the pathogenesis and treatment of this disease.

High-throughput sequencing of plasma microRNA in chronic fatigue syndrome/myalgic encephalomyelitis

Background

MicroRNAs (miRNAs) are known to regulate many biological processes and their dysregulation has been associated with a variety of diseases including Chronic Fatigue Syndrome/Myalgic Encephalomyelitis (CFS/ME). The recent discovery of stable and reproducible miRNA in plasma has raised the possibility that circulating miRNAs may serve as novel diagnostic markers. The objective of this study was to determine the role of plasma miRNA in CFS/ME.

Results

Using Illumina high-throughput sequencing we identified 19 miRNAs that were differentially expressed in the plasma of CFS/ME patients in comparison to non-fatigued controls. Following RT-qPCR analysis, we were able to confirm the significant up-regulation of three miRNAs (hsa-miR-127-3p, hsa-miR-142-5p and hsa-miR-143-3p) in the CFS/ME patients.

Conclusion

Our study is the first to identify circulating miRNAs from CFS/ME patients and also to confirm three differentially expressed circulating miRNAs in CFS/ME patients, providing a basis for further study to find useful CFS/ME biomarkers.

Unique microRNA-profiles in EGFR-mutated lung adenocarcinomas

The findings of mutations and the development of targeted therapies have improved lung cancer management. Still, the prognosis remains poor, and we need to know more about the genetic and epigenetic alterations in lung cancer. MicroRNAs are involved in crucial biological processes like carcinogenesis by regulating gene expression at the post-transcriptional level. In this project, we have studied the microRNA expression of lung adenocarcinomas and corresponding normal lung tissue and correlated the expression with clinical data and EGFR- and KRAS-mutational status. Agilent microarrays have been used, examining microRNA expression in 154 surgically resected lung adenocarcinomas and 20 corresponding normal lung tissue samples. Findings were confirmed by RT-qPCR in the same cohort and in an independent cohort of 103 lung cancer patients. EGFR and KRAS mutation analyses were also performed. 129 microRNAs were significantly differentially expressed in lung adenocarcinomas compared with normal lung tissue, and 17 microRNAs were differentially expressed between EGFR-mutated and EGFR wildtype tumors. We identified microRNAs associated with time to progression. We have identified several aberrantly expressed microRNAs that discriminate lung adenocarcinomas from normal lung tissue, and hence may be potential biomarkers for early detection. We have found microRNAs that are differentially expressed between EGFR-mutated and EGFR wildtype lung adenocarcinomas, suggesting that microRNAs can be used as molecular biomarkers in classification. We hypothesize that microRNA expression can be used as biomarkers for clinical course.

Fragile X Syndrome: from molecular pathology to therapy

Fragile X Syndrome (FXS) is the most common form of inherited intellectual disability due to the silencing of the FMR1 gene encoding FMRP (Fragile X Mental Retardation Protein), an RNA-binding protein involved in different steps of RNA metabolism. Of particular interest is the key role of FMRP in translational regulation. Since the first functional characterizations of FMRP, its role has been underlined by its association with actively translating polyribosomes. Furthermore, a plethora of mRNA targets of FMRP have been identified. In the absence of FMRP the deregulation of translation/transport/stability of these mRNAs has a cascade effect on many pathways, resulting into the final phenotype. We review here a set of targets of FMRP (mRNAs and proteins) that may have an impact on the FXS phenotype by deregulating some key cellular processes, such as translation, cytoskeleton remodeling and oxidative stress. The manipulation of these abnormal pathways by specific drugs may represent new therapeutic opportunities for FXS patients.

Identification of Dirofilaria immitis miRNA using illumina deep sequencing

The heartworm Dirofilaria immitis is the causative agent of cardiopulmonary dirofilariosis in dogs and cats, which also infects a wide range of wild mammals and humans. The complex life cycle of D. immitis with several developmental stages in its invertebrate mosquito vectors and its vertebrate hosts indicates the importance of miRNA in growth and development, and their ability to regulate infection of mammalian hosts. This study identified the miRNA profiles of D. immitis of zoonotic significance by deep sequencing. A total of 1063 conserved miRNA candidates, including 68 anti-sense miRNA (miRNA*) sequences, were predicted by computational methods and could be grouped into 808 miRNA families. A significant bias towards family members, family abundance and sequence nucleotides was observed. Thirteen novel miRNA candidates were predicted by alignment with the Brugia malayi genome. Eleven out of 13 predicted miRNA candidates were verified by using a PCR-based method. Target genes of the novel miRNA candidates were predicted by using the heartworm transcriptome dataset. To our knowledge, this is the first report of miRNA profiles in D. immitis, which will contribute to a better understanding of the complex biology of this zoonotic filarial nematode and the molecular regulation roles of miRNA involved. Our findings may also become a useful resource for small RNA studies in other filarial parasitic nematodes.

Sounds of silence: synonymous nucleotides as a key to biological regulation and complexity

Messenger RNA is a key component of an intricate regulatory network of its own. It accommodates numerous nucleotide signals that overlap protein coding sequences and are responsible for multiple levels of regulation and generation of biological complexity. A wealth of structural and regulatory information, which mRNA carries in addition to the encoded amino acid sequence, raises the question of how these signals and overlapping codes are delineated along non-synonymous and synonymous positions in protein coding regions, especially in eukaryotes. Silent or synonymous codon positions, which do not determine amino acid sequences of the encoded proteins, define mRNA secondary structure and stability and affect the rate of translation, folding and post-translational modifications of nascent polypeptides. The RNA level selection is acting on synonymous sites in both prokaryotes and eukaryotes and is more common than previously thought. Selection pressure on the coding gene regions follows three-nucleotide periodic pattern of nucleotide base-pairing in mRNA, which is imposed by the genetic code. Synonymous positions of the coding regions have a higher level of hybridization potential relative to non-synonymous positions, and are multifunctional in their regulatory and structural roles. Recent experimental evidence and analysis of mRNA structure and interspecies conservation suggest that there is an evolutionary tradeoff between selective pressure acting at the RNA and protein levels. Here we provide a comprehensive overview of the studies that define the role of silent positions in regulating RNA structure and processing that exert downstream effects on proteins and their functions.

Developing microRNA therapeutics: approaching the unique complexities

MicroRNAs are endogenous small non-coding RNAs that regulate gene expression by interfering with translation or stability of target transcripts. The importance of microRNAs for maintaining biological functions is illustrated by the fact that microRNAs are exploited in nature to regulate phenotypes, and by the diverse disease phenotypes that result when microRNAs are mutated or improperly expressed. Disease-associated microRNAs might therefore represent a new class of therapeutic targets. With the recent demonstration that inhibition of miR-122 reduces viral load in hepatitis C patients, microRNA modulators are no longer merely theoretical, but rather, have become strong candidate therapeutics. The complexity of microRNA biology offers a novel mechanism of action for therapeutic intervention but also poses unique challenges for the development of therapeutic modulators as drugs.

Synthetic incoherent feedforward circuits show adaptation to the amount of their genetic template

Natural and synthetic biological networks must function reliably in the face of fluctuating stoichiometry of their molecular components. These fluctuations are caused in part by changes in relative expression efficiency and the DNA template amount of the network-coding genes. Gene product levels could potentially be decoupled from these changes via built-in adaptation mechanisms, thereby boosting network reliability. Here, we show that a mechanism based on an incoherent feedforward motif enables adaptive gene expression in mammalian cells. We modeled, synthesized, and tested transcriptional and post-transcriptional incoherent loops and found that in all cases the gene product adapts to changes in DNA template abundance. We also observed that the post-transcriptional form results in superior adaptation behavior, higher absolute expression levels, and lower intrinsic fluctuations. Our results support a previously hypothesized endogenous role in gene dosage compensation for such motifs and suggest that their incorporation in synthetic networks will improve their robustness and reliability.

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/.

Systems Biology Reveals MicroRNA-Mediated Gene Regulation

MicroRNAs (miRNAs) are members of the small non-coding RNAs, which are principally known for their functions as post-transcriptional regulators of target genes. Regulation by miRNAs is triggered by the translational repression or degradation of their complementary target messenger RNAs (mRNAs). The growing number of reported miRNAs and the estimate that hundreds or thousands of genes are regulated by them suggest a magnificent gene regulatory network in which these molecules are embedded. Indeed, recent reports have suggested critical roles for miRNAs in various biological functions, such as cell differentiation, development, oncogenesis, and the immune responses, which are mediated by systems-wide changes in gene expression profiles. Therefore, it is essential to analyze this complex regulatory network at the transcriptome and proteome levels, which should be possible with approaches that include both high-throughput experiments and computational methodologies. Here, we introduce several systems-level approaches that have been applied to miRNA research, and discuss their potential to reveal miRNA-guided gene regulatory systems and their impacts on biological functions.

MicroRNAs 130a/b are regulated by BCR-ABL and downregulate expression of CCN3 in CML

Chronic Myeloid Leukaemia (CML) is a myeloproliferative disorder characterized by the expression of the oncoprotein, Bcr-Abl kinase. CCN3 normally functions as a negative growth regulator, but it is downregulated in CML, the mechanism of which is not known. MicroRNAs (miRNAs) are small non-coding RNAs, which negatively regulate protein translation by binding to the complimentary sequences of the 3' UTR of messenger RNAs. Deregulated miRNA expression has emerged as a hallmark of cancer. In CML, BCR-ABL upregulates oncogenic miRNAs and downregulates tumour suppressor miRNAs favouring leukaemic transformation. We report here that the downregulation of CCN3 in CML is mediated by BCR-ABL dependent miRNAs. Using the CML cell line K562, we profiled miRNAs, which are BCR-ABL dependent by transfecting K562 cells with anti-BCR-ABL siRNA. MiRNA expression levels were quantified using the Taqman Low Density miRNA array platform. From the miRNA target prediction databases we identified miRNAs that could potentially bind to CCN3 mRNA and reduce expression. Of these, miR-130a, miR-130b, miR-148a, miR-212 and miR-425-5p were significantly reduced on BCR-ABL knockdown, with both miR-130a and miR-130b decreasing the most within 24 h of siRNA treatment. Transfection of mature sequences of miR-130a and miR-130b individually into BCR-ABL negative HL60 cells resulted in a decrease of both CCN3 mRNA and protein. The reduction in CCN3 was greatest with overexpression of miR-130a whereas miR-130b overexpression resulted only in marginal repression of CCN3. This study shows that miRNAs modulate CCN3 expression. Deregulated miRNA expression initiated by BCR-ABL may be one mechanism of downregulating CCN3 whereby leukaemic cells evade negative growth regulation.

A simple Bayesian estimate of direct RNAi gene regulation events from differential gene expression profiles

BACKGROUND

Microarrays are commonly used to investigate both the therapeutic potential and functional effects of RNA interfering (RNAi) oligonucleotides such as microRNA (miRNA) and small interfering RNA (siRNA). However, the resulting datasets are often challenging to interpret as they include extensive information relating to both indirect transcription effects and off-target interference events.

METHOD

In an attempt to refine the utility of microarray expression data when evaluating the direct transcriptional affects of an RNAi agent we have developed SBSE (Simple Bayesian Seed Estimate). The key assumption implemented in SBSE is that both direct regulation of transcription by miRNA, and siRNA off-target interference, can be estimated using the differential distribution of an RNAi sequence (seed) motif in a ranked 3' untranslated region (3' UTR) sequence repository. SBSE uses common microarray summary statistics (i.e. fold change) and a simple Bayesian analysis to estimate how the RNAi agent dictated the observed differential expression profile. On completion a trace of the estimate and the location of the optimal partitioning of the dataset are plotted within a simple graphical representation of the 3'UTR landscape. The combined estimates define the differential distribution of the query motif within the dataset and by inference are used to quantify the magnitude of the direct RNAi transcription effect.

RESULTS

SBSE has been evaluated using five diverse human RNAi microarray focused investigations. In each instance SBSE unambiguously identified the most likely location of the direct RNAi effects for each of the differential gene expression profiles.

CONCLUSION

These analyses indicate that miRNA with conserved seed regions may share minimal biological activity and that SBSE can be used to differentiate siRNAs of similar efficacy but with different off-target signalling potential.

Integrated microRNA and mRNA expression profiling in a rat colon carcinogenesis model: effect of a chemo-protective diet

We have recently demonstrated that nutritional bioactives (fish oil and pectin) modulate microRNA molecular switches in the colon. Since integrated analysis of microRNA and mRNA expression at an early stage of colon cancer development is lacking, in this study, four computational approaches were utilized to test the hypothesis that microRNAs and their posttranscriptionally regulated mRNA targets, i.e., both total mRNAs and actively translated mRNA transcripts, are differentially modulated by carcinogen and diet treatment. Sprague-Dawley rats were fed diets containing corn oil ± fish oil with pectin ± cellulose and injected with azoxymethane or saline (control). Colonic mucosa was assayed at an early time of cancer progression, and global gene set enrichment analysis was used to obtain those microRNAs significantly enriched by the change in expression of their putative target genes. In addition, cumulative distribution function plots and functional network analyses were used to evaluate the impact of diet and carcinogen combination on mRNA levels induced via microRNA alterations. Finally, linear discriminant analysis was used to identify the best single-, two-, and three-microRNA combinations for classifying dietary effects and colon tumor development. We demonstrate that polysomal profiling is tightly related to microRNA changes when compared with total mRNA profiling. In addition, diet and carcinogen exposure modulated a number of microRNAs (miR-16, miR-19b, miR-21, miR26b, miR27b, miR-93, and miR-203) linked to canonical oncogenic signaling pathways. Complementary gene expression analyses showed that oncogenic PTK2B, PDE4B, and TCF4 were suppressed by the chemoprotective diet at both the mRNA and protein levels.

miRNA-34a is associated with docetaxel resistance in human breast cancer cells

Docetaxel is a chemotherapy drug to treat breast cancer, however as with many chemotherapeutic drugs resistance to docetaxel occurs in 50% of patients, and the underlying molecular mechanisms of drug resistance are not fully understood. Gene regulation through microRNAs (miRNA) has been shown to play an important role in cancer drug resistance. By directly targeting mRNA, miRNAs are able to inhibit genes that are necessary for signalling pathways or drug induced apoptosis rendering cells drug resistant. This study investigated the role of differential miRNA expression in two in vitro breast cancer cell line models (MCF-7, MDA-MB-231) of acquired docetaxel resistance. MiRNA microarray analysis identified 299 and 226 miRNAs altered in MCF-7 and MDA-MB-231 docetaxel-resistant cells, respectively. Docetaxel resistance was associated with increased expression of miR-34a and miR-141 and decreased expression of miR-7, miR-16, miR-30a, miR-125a-5p, miR-126. Computational target prediction revealed eight candidate genes targeted by these miRNAs. Quantitative PCR and western analysis confirmed decreased expression of two genes, BCL-2 and CCND1, in docetaxel-resistant cells, which are both targeted by miR-34a. Modulation of miR-34a expression was correlated with BCL-2 and cyclin D1 protein expression changes and a direct interaction of miR-34a with BCL-2 was shown by luciferase assay. Inhibition of miR-34a enhanced response to docetaxel in MCF-7 docetaxel-resistant cells, whereas overexpression of miR-34a conferred resistance in MCF-7 docetaxel-sensitive cells. This study is the first to show differences in miRNA expression, in particular, increased expression of miR-34a in an acquired model of docetaxel resistance in breast cancer. This serves as a mechanism of acquired docetaxel resistance in these cells, possibly through direct interactions with BCL-2 and CCND1, therefore presenting a potential therapeutic target for the treatment of docetaxel-resistant breast cancer.

Genome-wide approaches in the study of microRNA biology

MicroRNAs (miRNAs), a class of ∼21-23 nucleotide long non-coding RNAs (ncRNAs), have critical roles in diverse biological processes that encompass development, proliferation, apoptosis, stress response, and fat metabolism. miRNAs recognize their target mRNA transcripts by partial sequence complementarity and collectively have been estimated to regulate the majority of human genes. Consequently, misregulation of miRNAs or disruption of their target sites in genes has been implicated in a variety of human diseases ranging from cancer metastasis to neurological disorders. With the development and availability of genomic technologies and computational approaches, the field of miRNA biology has advanced tremendously over the last decade. Here we review the genome-wide approaches that have allowed for the discovery of new miRNAs, the characterization of their targets, and a systems-level view of their impact.

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.

Experimental identification of microRNA targets

microRNAs are small RNAs that regulate protein synthesis post-transcriptionally. Animal microRNAs recognize their targets by incomplete base pairing to sequence motifs most often present in the 3' untranslated region of their target mRNAs. This partial complementarity vastly expands the repertoire of potential targets and constitutes a problem for computational target prediction. Although computational analyses have shed light on important aspects of microRNA target recognition, several questions remain regarding how microRNAs can recognize and regulate their targets. Forward experimental approaches allow for an unbiased study of microRNA target recognition and may unveil novel, rare or uncommon target binding patterns. In this review we focus on animal microRNAs and the experimental approaches that have been described for identification of their targets.

Statistical use of argonaute expression and RISC assembly in microRNA target identification

MicroRNAs (miRNAs) posttranscriptionally regulate targeted messenger RNAs (mRNAs) by inducing cleavage or otherwise repressing their translation. We address the problem of detecting m/miRNA targeting relationships in homo sapiens from microarray data by developing statistical models that are motivated by the biological mechanisms used by miRNAs. The focus of our modeling is the construction, activity, and mediation of RNA-induced silencing complexes (RISCs) competent for targeted mRNA cleavage. We demonstrate that regression models accommodating RISC abundance and controlling for other mediating factors fit the expression profiles of known target pairs substantially better than models based on m/miRNA expressions alone, and lead to verifications of computational target pair predictions that are more sensitive than those based on marginal expression levels. Because our models are fully independent of exogenous results from sequence-based computational methods, they are appropriate for use as either a primary or secondary source of information regarding m/miRNA target pair relationships, especially in conjunction with high-throughput expression studies.

MicroRNAs are a family of small RNAs that play important roles in the development, physiological function and stress responses of a wide variety of organisms, and if abnormally expressed are associated with multiple types of cancer in humans. Rather than being translated into proteins, members of the family of microRNAs operate by preventing the translation of messenger RNAs to which they have some degree of sequence complementarity. Although sequence-based bioinformatics techniques have yielded large numbers of predicted messenger- and microRNA targeting relationships, verifying these as bona fide has proven practically difficult. We have developed a novel statistical approach based on the system biology of microRNAs in humans to detect such targeting relationships using high-throughput RNA expression data. Because our approach is not based on information from external target pair predictions, it can play a fully independent role in verifying such predictions as well as be used to obtain de novo target pair predictions. Using two separate data studies, we show that our approach is capable of both reproducing previously observed target pairs and verifying putative target pairs predicted from sequence data, at rates substantially better than marginal comparisons of messenger- and microRNA expression levels.

Evaluation of a new high-dimensional miRNA profiling platform

Background

MicroRNAs (miRNAs) are a class of approximately 22 nucleotide long, widely expressed RNA molecules that play important regulatory roles in eukaryotes. To investigate miRNA function, it is essential that methods to quantify their expression levels be available.

Methods

We evaluated a new miRNA profiling platform that utilizes Illumina's existing robust DASL chemistry as the basis for the assay. Using total RNA from five colon cancer patients and four cell lines, we evaluated the reproducibility of miRNA expression levels across replicates and with varying amounts of input RNA. The beta test version was comprised of 735 miRNA targets of Illumina's miRNA profiling application.

Results

Reproducibility between sample replicates within a plate was good (Spearman's correlation 0.91 to 0.98) as was the plate-to-plate reproducibility replicates run on different days (Spearman's correlation 0.84 to 0.98). To determine whether quality data could be obtained from a broad range of input RNA, data obtained from amounts ranging from 25 ng to 800 ng were compared to those obtained at 200 ng. No effect across the range of RNA input was observed.

Conclusion

These results indicate that very small amounts of starting material are sufficient to allow sensitive miRNA profiling using the Illumina miRNA high-dimensional platform. Nonlinear biases were observed between replicates, indicating the need for abundance-dependent normalization. Overall, the performance characteristics of the Illumina miRNA profiling system were excellent.

Abundant conserved microRNA target sites in the 5'-untranslated region and coding sequence

Recent studies have shown that miRNAs can target the promoter and CDS region. Thus, we predicted miRNA target sites in the 5'-UTR, CDS and 3'-UTR of Homo sapiens, Mus musculus and Drosophila melanogaster using miRanda and TargetScan. Target-site densities normalized with the average region length were higher in the 5'-UTR than 3'-UTR in all three organisms but were lower in the negative data set. Interestingly, the putative target sites were more conserved than non-target regions in both the 5'-UTR and 3'-UTR, implying that target sites in the 5'-UTR are subject to high selective pressure and might be functional. In Drosophila, 48 of 78 (61.5%) miRNAs showed high similarities with predicted siRNAs. Based on the results of previous experimental studies and a large-scale statistical analysis, we conclude that miRNA-mediated regulation is not limited to the 3'-UTR. However, the functionality of target sites in the 5'-UTR and CDS requires thorough investigation.

Characterization and comparative profiling of the small RNA transcriptomes in two phases of locust

High-throughput sequencing of the small RNA transcriptome of locust reveals differences in post-transcriptional regulation between solitary and swarming phases and provides insights into the evolution of insect small RNAs.

Background

All the reports on insect small RNAs come from holometabolous insects whose genome sequence data are available. Therefore, study of hemimetabolous insect small RNAs could provide more insights into evolution and function of small RNAs in insects. The locust is an important, economically harmful hemimetabolous insect. Its phase changes, as a phenotypic plasticity, result from differential gene expression potentially regulated at both the post-transcriptional level, mediated by small RNAs, and the transcriptional level.

Results

Here, using high-throughput sequencing, we characterize the small RNA transcriptome in the locust. We identified 50 conserved microRNA families by similarity searching against miRBase, and a maximum of 185 potential locust-specific microRNA family candidates were identified using our newly developed method independent of locust genome sequence. We also demonstrate conservation of microRNA*, and evolutionary analysis of locust microRNAs indicates that the generation of miRNAs in locusts is concentrated along three phylogenetic tree branches: bilaterians, coelomates, and insects. Our study identified thousands of endogenous small interfering RNAs, some of which were of transposon origin, and also detected many Piwi-interacting RNA-like small RNAs. Comparison of small RNA expression patterns of the two phases showed that longer small RNAs were expressed more abundantly in the solitary phase and that each category of small RNAs exhibited different expression profiles between the two phases.

Conclusions

The abundance of small RNAs in the locust might indicate a long evolutionary history of post-transcriptional gene expression regulation, and differential expression of small RNAs between the two phases might further disclose the molecular mechanism of phase changes.

Multiple approach to analyzing the role of microRNAs in apoptosis

MicroRNAs (miRNAs) are noncoding RNAs whose hallmarks are the very short sequences and the ability to repress the translation and/or transcription of target genes. miRNAs can have diverse functions, including regulation of cellular differentiation, proliferation, and embryogenesis. Over the past 5 years, an increasing number of studies have linked different miRNAs with programmed cell death or apoptosis. The principal aim of this chapter is to describe a method that (1) identifies miRNAs involved in apoptosis, using a validated array profiling approach, (2) assesses the direct involvement of candidate miRNAs in apoptosis, and (3) identifies the molecular mechanisms possibly involved in apoptotic response. To disclose the possible molecular targets of miRNAs, we propose the generation of a database created using a list of presumptive miRNA targets and the changes in the transcriptome after ectopic expression of the miRNAs. Our proposed method for doing this is suitable for both discovery of apoptotic pathways that regulate miRNAs and finding new miRNAs able to induce apoptosis.

miRecords: an integrated resource for microRNA-target interactions

MicroRNAs (miRNAs) are an important class of small noncoding RNAs capable of regulating other genes’ expression. Much progress has been made in computational target prediction of miRNAs in recent years. More than 10 miRNA target prediction programs have been established, yet, the prediction of animal miRNA targets remains a challenging task. We have developed miRecords, an integrated resource for animal miRNA–target interactions. The Validated Targets component of this resource hosts a large, high-quality manually curated database of experimentally validated miRNA–target interactions with systematic documentation of experimental support for each interaction. The current release of this database includes 1135 records of validated miRNA–target interactions between 301 miRNAs and 902 target genes in seven animal species. The Predicted Targets component of miRecords stores predicted miRNA targets produced by 11 established miRNA target prediction programs. miRecords is expected to serve as a useful resource not only for experimental miRNA researchers, but also for informatics scientists developing the next-generation miRNA target prediction programs. The miRecords is available at http://miRecords.umn.edu/miRecords.

Identification of suitable endogenous control genes for microRNA gene expression analysis in human breast cancer

The discovery of microRNAs (miRNAs) added an extra level of intricacy to the already complex system regulating gene expression. These single-stranded RNA molecules, 18–25 nucleotides in length, negatively regulate gene expression through translational inhibition or mRNA cleavage. The discovery that aberrant expression of specific miRNAs contributes to human disease has fueled much interest in profiling the expression of these molecules. Real-time quantitative PCR (RQ-PCR) is a sensitive and reproducible gene expression quantitation technique which is now being used to profile miRNA expression in cells and tissues. To correct for systematic variables such as amount of starting template, RNA quality and enzymatic efficiencies, RQ-PCR data is commonly normalised to an endogenous control (EC) gene, which ideally, is stably-expressed across the test sample set. A universal endogenous control suitable for every tissue type, treatment and disease stage has not been identified and is unlikely to exist, so, to avoid introducing further error in the quantification of expression data it is necessary that candidate ECs be validated in the samples of interest. While ECs have been validated for quantification of mRNA expression in various experimental settings, to date there is no report of the validation of miRNA ECs for expression profiling in breast tissue. In this study, the expression of five miRNA genes (let-7a, miR-10b, miR-16, miR-21 and miR-26b) and three small nucleolar RNA genes (RNU19, RNU48 and Z30) was examined across malignant, benign and normal breast tissues to determine the most appropriate normalisation strategy. This is the first study to identify reliable ECs for analysis of miRNA by RQ-PCR in human breast tissue.

Identifying the target mRNAs of microRNAs in colorectal cancer

MicroRNAs (miRNAs) play an important role in gene regulatory networks by inhibiting the expression of target mRNAs. There is a growing interest in identifying the relationship between miRNAs and their target mRNAs. Various experimental studies have been carried out to discover miRNAs involved in cancer and to identify their target genes. At the same time, a large volume of miRNA and mRNA expression profiles have become available owing to the development of high-throughput measurement technologies. So, there is now a pressing need to develop a computational method by which we can identify the target mRNAs of given miRNAs from such massive expression data sets. In this respect, we propose an effective linear model based identification method to unravel the relationship between miRNAs and their target mRNAs in colorectal cancer by using microarray expression profiles and sequence data.

Concise review: MicroRNA expression in multipotent mesenchymal stromal cells

Mesenchymal stem cells, or multipotent mesenchymal stromal cells (MSC), isolated from various adult tissue sources have the capacities to self-renew and to differentiate into multiple lineages. Both of these processes are tightly regulated by genetic and epigenetic mechanisms. Emerging evidence indicates that the class of single-stranded noncoding RNAs known as microRNAs also plays a critical role in this process. First described in nematodes and plants, microRNAs have been shown to modulate major regulatory mechanisms in eukaryotic cells involved in a broad array of cellular functions. Studies with various types of embryonic as well as adult stem cells indicate an intricate network of microRNAs regulating key transcription factors and other genes, which in turn determine cell fate. In addition, expression of unique microRNAs in specific cell types serves as a useful diagnostic marker to define a particular cell type. MicroRNAs are also found to be regulated by extracellular signaling pathways that are important for differentiation into specific tissues, suggesting that they play a role in specifying tissue identity. In this review, we describe the importance of microRNAs in stem cells, focusing on our current understanding of microRNAs in MSC and their derivatives.

Isolation of microRNA targets using biotinylated synthetic microRNAs

MicroRNAs are small regulatory RNAs found in multicellular organisms where they post-transcriptionally regulate gene expression. In animals, microRNAs bind mRNAs via incomplete base pairings making the identification of microRNA targets inherently difficult. Here, we present a detailed method for experimental identification of microRNA targets based on affinity purification of tagged microRNAs associated with their targets.

Isolation of microRNA targets by miRNP immunopurification

microRNAs (miRNAs) serve as post-transcriptional regulators of gene expression, by guiding effector complexes (miRNPs) to target RNAs. Although considerable progress has been made in computational methods to identify miRNA targets, only a relatively limited assessment of their ability to function in vivo has been reported. Here we describe an alternative approach to miRNA target identification based on a biochemical method for purifying miRNP complexes with associated miRNAs and bound mRNA targets. Microarray analysis revealed a high degree of enrichment for miRNA complementary sites in the 3'UTRs of the miRNP-associated mRNAs. mRNAs specifically associated with an individual miRNA were identified by comparing the miRNP-associated mRNAs from wild-type flies and mutant flies lacking miR-1, and their regulation by the miRNA was validated. This approach provides a means to identify functional miRNA targets based on their physical interaction in vivo.

MicroRNAs in search of a target

As the number of known microRNAs (miRNAs) increases, and their importance in physiology and disease becomes apparent, the identification of their regulatory targets is a requisite for a full characterization of their biological functions. Computational methods based on sequence homology and phylogenetic conservation have spearheaded this effort in the last 3 years, but they may not be sufficient. Experimental studies are now needed to extend and validate the computational predictions and further our understanding of target recognition by miRNAs.

Dysregulated metabotropic glutamate receptor-dependent translation of AMPA receptor and postsynaptic density-95 mRNAs at synapses in a mouse model of fragile X syndrome

Fragile X syndrome, a common form of inherited mental retardation, is caused by the loss of fragile X mental retardation protein (FMRP), an mRNA binding protein that is hypothesized to regulate local mRNA translation in dendrites downstream of gp1 metabotropic glutamate receptors (mGluRs). However, specific FMRP-associated mRNAs that localize to dendrites in vivo and show altered mGluR-dependent translation at synapses of Fmr1 knock-out mice are unknown so far. Using fluorescence in situ hybridization, we discovered that GluR1/2 and postsynaptic density-95 (PSD-95) mRNAs are localized to dendrites of cortical and hippocampal neurons in vivo. Quantitative analyses of their dendritic mRNA levels in cultured neurons and synaptoneurosomes did not detect differences between wild-type and Fmr1 knock-out (KO) mice. In contrast, PSD-95, GluR1/2, and calcium/calmodulin-dependent kinase IIalpha (CaMKIIalpha) mRNA levels in actively translating polyribosomes were dysregulated in synaptoneurosomes from Fmr1 knock-out mice in response to mGluR activation. [35S]methionine incorporation into newly synthesized proteins similarly revealed impaired stimulus-induced protein synthesis of CaMKIIalpha and PSD-95 in synaptoneurosomes from Fmr1 KO mice. Quantitative analysis of mRNA levels in FMRP-specific immunoprecipitations from synaptoneurosomes demonstrated the association of FMRP with CaMKIIalpha, PSD-95, and GluR1/2 mRNAs. These findings suggest a novel mechanism whereby FMRP regulates the local synthesis AMPA receptor (AMPAR) subunits, PSD-95, and CaMKIIalpha downstream of mGluR-activation. Dysregulation of local translation of AMPAR and associated factors at synapses may impair control of the molecular composition of the postsynaptic density and consequently alter synaptic transmission, causing impairments of neuronal plasticity observed in Fmr1 knock-out mice and fragile X syndrome.

MicroRNAs as Cancer Players: Potential Clinical and Biological Effects

MicroRNAs (miRNAs) are nonprotein-coding RNAs that function as posttranscriptional gene regulators. They can regulate their targets directly by mRNA cleavage or by repressing their translation, depending on the degree of complementariety between the miRNA and the target. Recent evidences have shown that miRNA control cell growth, apoptosis, and differentiation. Moreover, miRNA expression correlates with cancers and could have a crucial function in tumor progression. Bioinformatic data indicates that each miRNA can control hundreds of target genes, but identification of the accurate miRNA targets will be crucial to exploit the emerging knowledge of miRNA contribution to cancer process. While the miRNA field is still emerging, the benefit of our understanding of miRNA in cancer is potentially enormous, especially if we are able to apply this knowledge to provide new therapies for patients.

Improving the prediction of human microRNA target genes by using ensemble algorithm

MicroRNAs are a class of small endogenous noncoding RNAs which play important regulatory roles mainly by post-transcriptional depression. Finding miRNA target genes will help a lot to understand their biological functions. We developed an ensemble machine learning algorithm which helps to improve the prediction of miRNA targets. The performance was evaluated in the training set and in FMRP associated mRNAs. Moreover, using human mir-9 as a test case, our classification was validated in 9 of 15 transcripts tested. Finally, we applied our algorithm on the whole prediction data set provided by miRanda website. The results are available at http://www.biosino.org/~kanghu/mRTP/mRTP.html.

RNA Interference: A Tool for Querying Nervous System Function and an Emerging Therapy

RNA interference (RNAi), a mediator of gene silencing, has swiftly become one of the most exciting and applicable biological discoveries. There has been rapid progress in identifying RNAi pathway components and elucidating the mechanisms of microRNA (miRNA) biogenesis and gene suppression. As a result, RNAi technologies have been successfully employed in a variety of systems as biological tools, and studies are underway to test the therapeutic utility of RNAi. In the span of several years, significant advances in the delivery of inhibitory RNAs in the nervous system have been made. We have glimpses into how endogenous miRNAs interface with neuronal development and function; in addition, RNAi has shown therapeutic efficacy in several mouse models of human neurological conditions. In this review, we summarize the current state-of-the-art of RNAi and its utility to neuroscientists.

Glial cell-line derived neurotrophic factor and neurturin regulate the expressions of distinct miRNA precursors through the activation of GFRalpha2

Glial cell line-derived neurotrophic factor (GDNF) and neurturin (NTN) are structurally related neurotrophic factors that have both been shown to prevent the degeneration of dopaminergic neurons in vitro and in vivo. NTN and GDNF are thought to bind with different affinities to the GDNF family receptor alpha-2 (GFRalpha2), and can activate the same multi-component receptor system consisting of GFRalpha2, receptor tyrosine kinase Ret (RET) and NCAM. MicroRNAs (miRNAs) are a class of short, non-coding RNAs that regulate gene expression through translational repression or RNA degradation. miRNAs have diverse functions, including regulating differentiation, proliferation and apoptosis in several organisms. It is currently unknown whether GDNF and NTN regulate the expression of miRNAs through activation of the same multi-component receptor system. Using quantitative real-time PCR, we measured the expression of some miRNA precursors in human BE(2)-C cells that express GFRalpha2 but not GFRalpha1. GDNF and NTN differentially regulate the expression of distinct miRNA precursors through the activation of mitogen-activated protein kinase (extracellular signal-regulated kinase 1/2). This study showed that the expression of distinct miRNA precursors is differentially regulated by specific ligands through the activation of GFRalpha2.

Preliminary assessment of the impact of microRNA-mediated regulation on coding sequence evolution in mammals

Despite prior claims to the contrary, several lines of evidence suggest that selection acts on synonymous mutations in mammals. What might be the mechanisms for such selection? Here I attempt to quantify the constraints on the evolution of the coding sequence resulting from regulation of mRNA by microRNAs (miRNAs) that antisense-bind to the coding region of mRNAs. I employ a set of genes recently experimentally verified to be the target of a miRNA, all with putative antisense pairing domains within the coding sequence. Although very small ( approximately 22 nucleotides), 2 of 13 pairing domains show evidence of significantly slow sequence evolution. This, along with evidence that these genes are regulated by the miRNA under consideration, provides the first good candidate domains for intra-CDS pairing of a miRNA in mammals. When analyzed en masse, the putative pairing domains have a significantly reduced rate of synonymous evolution (approximately 35% lower than null). However, given the size and rarity of pairing domains within the coding sequence, the effects that such constraint has on estimates of the mutation rate are small enough to be ignored (probably less than 1% reduction). The pairing sites also have low Ka values and the selection on the synonymous sites is unlikely to lead to misleading reports of localized high Ka/Ks ratios.

Experimental approaches to identify non-coding RNAs

Cellular RNAs that do not function as messenger RNAs (mRNAs), transfer RNAs (tRNAs) or ribosomal RNAs (rRNAs) comprise a diverse class of molecules that are commonly referred to as non-protein-coding RNAs (ncRNAs). These molecules have been known for quite a while, but their importance was not fully appreciated until recent genome-wide searches discovered thousands of these molecules and their genes in a variety of model organisms. Some of these screens were based on biocomputational prediction of ncRNA candidates within entire genomes of model organisms. Alternatively, direct biochemical isolation of expressed ncRNAs from cells, tissues or entire organisms has been shown to be a powerful approach to identify ncRNAs both at the level of individual molecules and at a global scale. In this review, we will survey several such wet-lab strategies, i.e. direct sequencing of ncRNAs, shotgun cloning of small-sized ncRNAs (cDNA libraries), microarray analysis and genomic SELEX to identify novel ncRNAs, and discuss the advantages and limits of these approaches.