Systematic comparison of microarray profiling, real-time PCR, and next-generation sequencing technologies for measuring differential microRNA expression

Epigenetic biomarkers in skin cancer

Epigenetic aberrations have been associated with cutaneous melanoma tumorigenesis and progression including dysregulated DNA gene promoter region methylation, histone modification, and microRNA. Several of these major epigenetic aberrations have been developed into biomarkers. Epigenetic biomarkers can be detected in tissue and in blood as circulating DNA in melanoma patients. There is strong evidence that biomarkers in cutaneous melanoma will have an important role as companions to therapeutics and overall patient management. Important progress has been made in epigenetic melanoma biomarker development and verification of clinical utility, and this review discusses some of the key current developments and existing challenges.

Expression profiling of human immune cell subsets identifies miRNA-mRNA regulatory relationships correlated with cell type specific expression

Blood consists of different cell populations with distinct functions and correspondingly, distinct gene expression profiles. In this study, global miRNA expression profiling was performed across a panel of nine human immune cell subsets (neutrophils, eosinophils, monocytes, B cells, NK cells, CD4 T cells, CD8 T cells, mDCs and pDCs) to identify cell-type specific miRNAs. mRNA expression profiling was performed on the same samples to determine if miRNAs specific to certain cell types down-regulated expression levels of their target genes. Six cell-type specific miRNAs (miR-143; neutrophil specific, miR-125; T cells and neutrophil specific, miR-500; monocyte and pDC specific, miR-150; lymphoid cell specific, miR-652 and miR-223; both myeloid cell specific) were negatively correlated with expression of their predicted target genes. These results were further validated using an independent cohort where similar immune cell subsets were isolated and profiled for both miRNA and mRNA expression. miRNAs which negatively correlated with target gene expression in both cohorts were identified as candidates for miRNA/mRNA regulatory pairs and were used to construct a cell-type specific regulatory network. miRNA/mRNA pairs formed two distinct clusters in the network corresponding to myeloid (nine miRNAs) and lymphoid lineages (two miRNAs). Several myeloid specific miRNAs targeted common genes including ABL2, EIF4A2, EPC1 and INO80D; these common targets were enriched for genes involved in the regulation of gene expression (p<9.0E-7). Those miRNA might therefore have significant further effect on gene expression by repressing the expression of genes involved in transcriptional regulation. The miRNA and mRNA expression profiles reported in this study form a comprehensive transcriptome database of various human blood cells and serve as a valuable resource for elucidating the role of miRNA mediated regulation in the establishment of immune cell identity.

Relationships of PBMC microRNA expression, plasma viral load, and CD4+ T-cell count in HIV-1-infected elite suppressors and viremic patients

Background

HIV-1-infected elite controllers or suppressors (ES) maintain undetectable viral loads (< 50 copies/mL) without antiretroviral therapy. The mechanisms of suppression are incompletely understood. Modulation of HIV-1 replication by miRNAs has been reported, but the role of small RNAs in ES is unknown. Using samples from a well-characterized ES cohort, untreated viremic patients, and uninfected controls, we explored the PBMC miRNA profile and probed the relationships of miRNA expression, CD4+ T-cell counts, and viral load.

Results

miRNA profiles, obtained using multiple acquisition, data processing, and analysis methods, distinguished ES and uninfected controls from viremic HIV-1-infected patients. For several miRNAs, however, ES and viremic patients shared similar expression patterns. Differentially expressed miRNAs included those with reported roles in HIV-1 latency (miR-29 family members, miRs -125b and -150). Others, such as miR-31 and miR-31*, had no previously reported connection with HIV-1 infection but were found here to differ significantly with uncontrolled HIV-1 replication. Correlations of miRNA expression with CD4+ T-cell count and viral load were found, and we observed that ES with low CD4+ T-cell counts had miRNA profiles more closely related to viremic patients than controls. However, expression patterns indicate that miRNA variability cannot be explained solely by CD4+ T-cell variation.

Conclusions

The intimate involvement of miRNAs in disease processes is underscored by connections of miRNA expression with the HIV disease clinical parameters of CD4 count and plasma viral load. However, miRNA profile changes are not explained completely by these variables. Significant declines of miRs-125b and -150, among others, in both ES and viremic patients indicate the persistence of host miRNA responses or ongoing effects of infection despite viral suppression by ES. We found no negative correlations with viral load in viremic patients, not even those that have been reported to silence HIV-1 in vitro, suggesting that the effects of these miRNAs are exerted in a focused, cell-type-specific manner. Finally, the observation that some ES with low CD4 counts were consistently related to viremic patients suggests that miRNAs may serve as biomarkers for risk of disease progression even in the presence of viral suppression.

Advances in microRNA experimental approaches to study physiological regulation of gene products implicated in CNS disorders

The central nervous system (CNS) is a remarkably complex organ system, requiring an equally complex network of molecular pathways controlling the multitude of diverse, cellular activities. Gene expression is a critical node at which regulatory control of molecular networks is implemented. As such, elucidating the various mechanisms employed in the physiological regulation of gene expression in the CNS is important both for establishing a reference for comparison to the diseased state and for expanding the set of validated drug targets available for disease intervention. MicroRNAs (miRNAs) are an abundant class of small RNA that mediates potent inhibitory effects on global gene expression. Recent advances have been made in methods employed to study the contribution of these miRNAs to gene expression. Here we review these latest advances and present a methodological workflow from the perspective of an investigator studying the physiological regulation of a gene of interest. We discuss methods for identifying putative miRNA target sites in a transcript of interest, strategies for validating predicted target sites, assays for detecting miRNA expression, and approaches for disrupting endogenous miRNA function. We consider both advantages and limitations, highlighting certain caveats that inform the suitability of a given method for a specific application. Through careful implementation of the appropriate methodologies discussed herein, we are optimistic that important discoveries related to miRNA participation in CNS physiology and dysfunction are on the horizon.

The emerging important role of microRNAs in the pathogenesis, diagnosis and treatment of human cancers

MicroRNAs are small non-protein-coding RNAs which repress gene expression, through base pair matching with messenger RNA (mRNA). A single microRNA is capable of regulating hundreds of mRNA sequences. Only a small fraction of the over 1000 discovered microRNAs have currently known functions; many are crucial in the regulation of genetic signalling, including cellular processes such as cellular differentiation, growth, proliferation and death. Dysfunction in microRNA signalling is present in all cancers studied thus far, leading to overactive oncogenic and underactive tumour suppressor gene signalling. Current research is actively pursuing the potential to use microRNAs as diagnostic tools and novel therapies in a variety of diseases. This review summarises normal and abnormal maturation and function of microRNAs and their role in the pathogenesis of various human tumours and highlights how microRNAs may be used as diagnostic and treatment tools in human cancers in the future.

Introduction to miRNA profiling technologies and cross-platform comparison

MicroRNA analysis has been widely adopted for basic and applied science. The tools and technologies available for quantifying and analysing miRNAs are still maturing. Here, we give an introductory overview of the main tools and the challenges in their use. We also discuss the importance of basic experimental design, sample handling and analysis methods as the impact of these can be as profound as the choice of miRNA analysis platform. Whether the reader is interested in a gene-by-gene or genome-wide approach choosing the platform to use is not trivial. Careful thought given before starting an experiment will make the execution much easier.

miRNA expression profiling using Illumina Universal BeadChips

We have developed a highly sensitive, specific, and reproducible method for microRNA (miRNA) expression profiling, using BeadArray technology. This method incorporates an enzyme-assisted specificity step, a solid-phase primer extension to distinguish between members of miRNA families. In addition, a universal PCR is used to amplify all targets prior to array hybridization. Using this method, highly reproducible miRNA expression profiles were generated with 100-200 ng total RNA input. The method has a 3.5-4 log (10(5)-10(9) molecules) dynamic range and is able to detect 1.2- to 1.3-fold differences between samples. Expression profiles generated by this method are highly comparable to those obtained with RT-PCR (R (2) = 0.85-0.90) and direct sequencing (R = 0.87-0.89). This method should prove useful for high-throughput expression profiling of miRNAs in large numbers of tissue samples.

Agilent microRNA microarray profiling system

MicroRNA (miRNA) profiling is of great interest because of the significant roles these short noncoding RNA molecules play in cellular regulation. Signature profiles, usually involving several miRNAs, have also been associated with dysfunctional cellular regulation such as in cancer. Profiling miRNAs can be done using the Agilent Technologies miRNA profiling system, which is a sensitive and accurate miRNA microarray assay. The assay is based on a highly efficient labeling method linked to a novel probe design strategy. The labeling method uses a simple, single-vial approach where 100 ng of nonfractionated total RNA is directly labeled by ligation of a Cy3 labeled pCp molecule to the 3' end of the RNA. The labeled cytosine interacts with the guanidine at the 5' end of the probe which adds stability to the hybridization complex. In addition, the probes have been designed to provide both sequence and size discrimination, generally resulting in highly specific detection of closely related mature miRNAs. The labeling and probe design strategies allow for a precise and accurate measurement that spans a linear dynamic range of greater than four orders of magnitude from at least 0.2 amol to 2 fmol of miRNA and a detection limit of less than 0.1 amol. The assay works over a wide range of sample types including FFPE samples. Agilent's microarray technology is a flexible design platform allowing quick array design iterations and incorporation of the latest miRBase content.

A microRNA guide for clinicians and basic scientists: background and experimental techniques

MicroRNAs (miRNAs) are short non-coding RNA molecules that are approximately 22 nucleotides in length. In the last 10 years, miRNA research and discovery has advanced at a rapid rate. This review provides a brief overview of the discovery and biology of miRNAs, and summarises some of the experimental techniques used for isolation, detection, target prediction, and regulation of miRNAs. We also outline experimental workflows for investigators new to the field, and discuss the diagnostic and therapeutic application of miRNAs.

A comprehensive survey of maternal plasma miRNAs expression profiles using high-throughput sequencing

OBJECTIVE

Recently, microRNAs (miRNAs) had been shown as potential important regulators in pregnancy. Circulating miRNAs are considered as potentially useful non-invasive biomarkers for the diagnosis of pregnancy-related disease and congenital disorders, but maternal peripheral blood miRNAs expression profile in pregnancy remains less investigated. We thus set out to investigate maternal plasma miRNAs expression profile using genome-wide sequencing.

METHODS

Maternal plasma miRNA expression profiles of different pregnancy stages were detected by SOLiD sequencing. We observed the expression level of the most abundant miRNAs in maternal plasma during pregnancy process. We examined functional relationships of targets of pregnancy-relative miRNAs by enrichment analyzing of signaling pathways.

RESULTS

147 miRNAs were sequenced from maternal plasma in this study, among them, 90 types of miRNAs were found in all of the samples, while 136 miRNAs in the first trimester gestation, 108 in second trimester gestation, and 99 miRNAs in the third trimester gestation, respectively. The varieties and the expression level of maternal plasma miRNAs were changing during pregnancy. The expression level of miRNA cluster members was changing with the same trend during pregnancy. The function and functional relationship analysis of target genes of pregnancy-relative miRNAs showed that genetic disorder, immunological disease, cell signaling, cancer, and cell cycle were the enriched pathways.

CONCLUSIONS

Maternal plasma miRNA expression profiles are dynamically changing during pregnancy. The results of function analysis suggested that miRNAs may play an important role in regulating pregnancy process, which can help us understand the refine regulation mechanism in pregnancy. Moreover, the results of this present study may be the basis for a further study to find useful prenatal diagnosis biomarkers.

Characterization of the stress associated microRNAs in Glycine max by deep sequencing

BACKGROUND

Plants involved in highly complex and well-coordinated systems have evolved a considerable degree of developmental plasticity, thus minimizing the damage caused by stress. MicroRNAs (miRNAs) have recently emerged as key regulators in gene regulation, developmental processes and stress tolerance in plants.

RESULTS

In this study, soybean miRNAs associated with stress responses (drought, salinity, and alkalinity) have been identified and analyzed in combination with deep sequencing technology and in-depth bioinformatics analysis. One hundred and thirty three conserved miRNAs representing 95 miRNA families were expressed in soybeans under three treatments. In addition, 71, 50, and 45 miRNAs are either uniquely or differently expressed under drought, salinity, and alkalinity, respectively, suggesting that many miRNAs are inducible and are differentially expressed in response to certain stress.

CONCLUSION

Our study has important implications for further identification of gene regulation under abiotic stresses and significantly contributes a complete profile of miRNAs in Glycine max.

Influence of RNA labeling on expression profiling of microRNAs

Although a number of technical parameters are now being examined to optimize microRNA profiling experiments, it is unknown whether reagent or component changes to the labeling step affect starting RNA requirements or microarray performance. Human brain/lung samples were each labeled in duplicate, at 1.0, 0.5, 0.2, and 0.1 μg of total RNA, by means of two kits that use the same labeling procedure but differ in the reagent composition used to label microRNAs. Statistical measures of reliability and validity were used to evaluate microarray data. Cross-platform confirmation was accomplished using TaqMan microRNA assays. Synthetic microRNA spike-in experiments were also performed to establish the microarray signal dynamic range using the ligation-modified kit. Technical replicate correlations of signal intensity values were high using both kits, but improved with the ligation-modified assay. The drop in detection call sensitivity and miRNA gene list correlations, when using reduced amounts of standard-labeled RNA, was considerably improved with the ligation-modified kit. Microarray signal dynamic range was found to be linear across three orders of magnitude from 4.88 to 5000 attomoles. Thus, optimization of the microRNA labeling reagent can result in at least a 10-fold decrease in microarray total RNA requirements with little compromise to data quality. Clinical investigations bottlenecked by the amount of starting material may use a ligation mix modification strategy to reduce total RNA requirements.

snoU6 and 5S RNAs are not reliable miRNA reference genes in neuronal differentiation

Accurate profiling of microRNAs (miRNAs) is an essential step for understanding the functional significance of these small RNAs in both physiological and pathological processes. Quantitative real-time PCR (qPCR) has gained acceptance as a robust and reliable transcriptomic method to profile subtle changes in miRNA levels and requires reference genes for accurate normalization of gene expression. 5S and snoU6 RNAs are commonly used as reference genes in microRNA quantification. It is currently unknown if these small RNAs are stably expressed during neuronal differentiation. Panels of miRNAs have been suggested as alternative reference genes to 5S and snoU6 in various physiological contexts. To test the hypothesis that miRNAs may serve as stable references during neuronal differentiation, the expressions of eight miRNAs, 5S and snoU6 RNAs in five differentiating neuronal cell types were analyzed using qPCR. The stabilities of the expressions were evaluated using two complementary statistical approaches (geNorm and Normfinder). Expressions of 5S and snoU6 RNAs were stable under some but not all conditions of neuronal differentiation and thus are not suitable reference genes. In contrast, a combination of three miRNAs (miR-103, miR-106b and miR-26b) allowed accurate expression normalization across different models of neuronal differentiation.

Label-free high-throughput microRNA expression profiling from total RNA

MicroRNAs (miRNAs) are key biological regulators and promising disease markers whose detection technologies hold great potentials in advancing fundamental research and medical diagnostics. Currently, miRNAs in biological samples have to be labeled before being applied to most high-throughput assays. Although effective, these labeling-based approaches are usually labor-intensive, time-consuming and liable to bias. Besides, the cross-hybridization of co-existing miRNA precursors (pre-miRNAs) is not adequately addressed in most assays that use total RNA as input. Here, we present a hybridization-triggered fluorescence strategy for label-free, microarray-based high-throughput miRNA expression profiling. The total RNA is directly applied to the microarray with a short fluorophore-linked oligonucleotide Universal Tag which can be selectively captured by the target-bound probes via base-stacking effects. This Stacking-Hybridized Universal Tag (SHUT) assay has been successfully used to analyze as little as 100 ng total RNA from human tissues, and found to be highly specific to homogenous miRNAs. Superb discrimination toward single-base mismatch at the 5′ or 3′ end has been demonstrated. Importantly, the pre-miRNAs generated negligible signals, validating the direct use of total RNA.

miRNA regulation of cytotoxic effects in mouse Sertoli cells exposed to nonylphenol

BACKGROUND

It is known that some environmental chemicals affect the human endocrine system. The harmful effects of endocrine disrupting chemical (EDC) nonylphenol (NP) have been studied since the 1980s. It is known that NP adversely affects physiological functions by mimicking the natural hormone 17 beta-estradiol. In the present study, we analyzed the expression of miRNAs and their target genes in mouse Sertoli TM4 cells to better understand the regulatory roles of miRNAs on Sertoli cells after NP exposure.

METHODS

Mouse TM4 Sertoli cells were treated with NP for 3 or 24 h, and global gene and miRNA expression were analyzed using Agilent mouse whole genome and mouse miRNA v13 arrays.

RESULTS

We identified genes that were > 2-fold differentially expressed in NP-treated cells and control cells (P < 0.05) and analyzed their functions through Gene Ontology analysis. We also identified miRNAs that were differentially expressed in NP-treated and control cells. Of the 186 miRNAs the expression of which differed between NP-treated and control cells, 59 and 147 miRNAs exhibited 1.3-fold increased or decreased expression at 3 and 24 h, respectively. Network analysis of deregulated miRNAs suggested that Ppara may regulate the expression of certain miRNAs, including miR-378, miR-125a-3p miR-20a, miR-203, and miR-101a, after exposure to NP. Additionally, comprehensive analysis of predicted target genes for miRNAs showed that the expression of genes with roles in cell proliferation, the cell cycle, and cell death were regulated by miRNA in NP-treated TM4 cells. Levels of expression of the miRNAs miR-135a* and miR-199a-5p were validated by qRT-PCR. Finally, miR-135a* target gene analysis suggests that the generation of reactive oxygen species (ROS) following exposure to NP exposure may be mediated by miR-135a* through regulation of the Wnt/beta-catenin signaling pathway.

CONCLUSIONS

Collectively, these data help to determine NP's actions on mouse TM4 Sertoli cells and increase our understanding of the molecular mechanisms underlying the adverse effects of xenoestrogens on the reproductive system.

Current approaches to micro-RNA analysis and target gene prediction

It is becoming increasingly evident that micro-RNAs (miRNA) play a significant role in regulating the cellular machinery. These ∼22-nt non-coding RNAs function as negative regulators of gene expression. Since their discovery, considerable information has been obtained on miRNA biology and the mechanism of their action. Guidelines have been established for miRNA nomenclature and databases have been built to house all miRNA from many species. A number of methodologies are available for miRNA analysis. There is a lot of interest in developing bioinformatics approaches to predict miRNA target genes. This article will bring together the information on our current knowledge of miRNA biology, the approaches for miRNA analysis, and computational strategies to gain insight in miRNA functional roles.

Identification and remediation of biases in the activity of RNA ligases in small-RNA deep sequencing

Deep sequencing of small RNAs (sRNA-seq) is now the gold standard for small RNA profiling and discovery. Biases in sRNA-seq have been reported, but their etiology remains unidentified. Through a comprehensive series of sRNA-seq experiments, we establish that the predominant cause of the bias is the RNA ligases. We further demonstrate that RNA ligases have strong sequence-specific biases which distort the small RNA profiles considerably. We have devised a pooled adapter strategy to overcome this bias, and validated the method through data derived from microarray and qPCR. In light of our findings, published small RNA profiles, as well as barcoding strategies using adapter-end modifications, may need to be revisited. Importantly, by providing a wide spectrum of substrate for the ligase, the pooled-adapter strategy developed here provides a means to overcome issues of bias, and generate more accurate small RNA profiles.

Evaluation of two commercial global miRNA expression profiling platforms for detection of less abundant miRNAs

Background

microRNAs (miRNA) are short, endogenous transcripts that negatively regulate the expression of specific mRNA targets. miRNAs are found both in tissues and body fluids such as plasma. A major perspective for the use of miRNAs in the clinical setting is as diagnostic plasma markers for neoplasia. While miRNAs are abundant in tissues, they are often scarce in plasma. For quantification of miRNA in plasma it is therefore of importance to use a platform with high sensitivity and linear performance in the low concentration range. This motivated us to evaluate the performance of three commonly used commercial miRNA quantification platforms: GeneChip miRNA 2.0 Array, miRCURY Ready-to-Use PCR, Human panel I+II V1.M, and TaqMan Human MicroRNA Array v3.0.

Results

Using synthetic miRNA samples and plasma RNA samples spiked with different ratios of 174 synthetic miRNAs we assessed the performance characteristics reproducibility, recovery, specificity, sensitivity and linearity. It was found that while the qRT-PCR based platforms were sufficiently sensitive to reproducibly detect miRNAs at the abundance levels found in human plasma, the array based platform was not. At high miRNA levels both qRT-PCR based platforms performed well in terms of specificity, reproducibility and recovery. At low miRNA levels, as in plasma, the miRCURY platform showed better sensitivity and linearity than the TaqMan platform.

Conclusion

For profiling clinical samples with low miRNA abundance, such as plasma samples, the miRCURY platform with its better sensitivity and linearity would probably be superior.

Next-generation sequencing applied to molecular diagnostics

Next-generation sequencing technologies have begun to revolutionize the field of cancer genetics through rapid and accurate assessment of a patient's DNA makeup with minimal cost. These technologies have already led to the realization of the inter- and intra-tumor genetic heterogeneity and the identification of novel mutations and chimeric genes, however, several challenges lie ahead. Given the low number of recurrent somatic genetic aberrations in common types of cancer, the identification of 'driver' genetic aberrations has proven challenging. Furthermore, implementation of next-generation sequencing and/or some of its derivatives into routine practice as diagnostic tests will require in-depth understanding of the pitfalls of these technologies and a great degree of bioinformatic expertise. This article focuses on the contribution of next-generation sequencing technologies to diagnosis and cancer prognostication and prediction.

SEAS: a system for SEED-based pathway enrichment analysis

Pathway enrichment analysis represents a key technique for analyzing high-throughput omic data, and it can help to link individual genes or proteins found to be differentially expressed under specific conditions to well-understood biological pathways. We present here a computational tool, SEAS, for pathway enrichment analysis over a given set of genes in a specified organism against the pathways (or subsystems) in the SEED database, a popular pathway database for bacteria. SEAS maps a given set of genes of a bacterium to pathway genes covered by SEED through gene ID and/or orthology mapping, and then calculates the statistical significance of the enrichment of each relevant SEED pathway by the mapped genes. Our evaluation of SEAS indicates that the program provides highly reliable pathway mapping results and identifies more organism-specific pathways than similar existing programs. SEAS is publicly released under the GPL license agreement and freely available at http://csbl.bmb.uga.edu/~xizeng/research/seas/.

Diagnostic and prognostic signatures from the small non-coding RNA transcriptome in prostate cancer

Prostate cancer (PCa) is the most frequent male malignancy and the second most common cause of cancer-related death in Western countries. Current clinical and pathological methods are limited in the prediction of postoperative outcome. It is becoming increasingly evident that small non-coding RNA (ncRNA) species are associated with the development and progression of this malignancy. To assess the diversity and abundance of small ncRNAs in PCa, we analyzed the composition of the entire small transcriptome by Illumina/Solexa deep sequencing. We further analyzed the microRNA (miRNA) expression signatures of 102 fresh-frozen patient samples during PCa progression by miRNA microarrays. Both platforms were cross-validated by quantitative reverse transcriptase-PCR. Besides the altered expression of several miRNAs, our deep sequencing analyses revealed strong differential expression of small nucleolar RNAs (snoRNAs) and transfer RNAs (tRNAs). From microarray analysis, we derived a miRNA diagnostic classifier that accurately distinguishes normal from cancer samples. Furthermore, we were able to construct a PCa prognostic predictor that independently forecasts postoperative outcome. Importantly, the majority of miRNAs included in the predictor also exhibit high sequence counts and concordant differential expression in Illumina PCa samples, supported by quantitative reverse transcriptase-PCR. Our findings provide miRNA expression signatures that may serve as an accurate tool for the diagnosis and prognosis of PCa.

Molecular markers and mechanisms of stroke: RNA studies of blood in animals and humans

Whole genome expression microarrays can be used to study gene expression in blood, which comes in part from leukocytes, immature platelets, and red blood cells. Since these cells are important in the pathogenesis of stroke, RNA provides an index of these cellular responses to stroke. Our studies in rats have shown specific gene expression changes 24  hours after ischemic stroke, hemorrhage, status epilepticus, hypoxia, hypoglycemia, global ischemia, and following brief focal ischemia that simulated transient ischemic attacks in humans. Human studies show gene expression changes following ischemic stroke. These gene profiles predict a second cohort with >90% sensitivity and specificity. Gene profiles for ischemic stroke caused by large-vessel atherosclerosis and cardioembolism have been described that predict a second cohort with >85% sensitivity and specificity. Atherosclerotic genes were associated with clotting, platelets, and monocytes, and cardioembolic genes were associated with inflammation, infection, and neutrophils. These gene profiles predicted the cause of stroke in 58% of cryptogenic patients. These studies will provide diagnostic, prognostic, and therapeutic markers, and will advance our understanding of stroke in humans. New techniques to measure all coding and noncoding RNAs along with alternatively spliced transcripts will markedly advance molecular studies of human stroke.

MicroRNA expression profiling reveals miRNA families regulating specific biological pathways in mouse frontal cortex and hippocampus

MicroRNAs (miRNAs) are small regulatory molecules that cause post-transcriptional gene silencing. Although some miRNAs are known to have region-specific expression patterns in the adult brain, the functional consequences of the region-specificity to the gene regulatory networks of the brain nuclei are not clear. Therefore, we studied miRNA expression patterns by miRNA-Seq and microarrays in two brain regions, frontal cortex (FCx) and hippocampus (HP), which have separate biological functions. We identified 354 miRNAs from FCx and 408 from HP using miRNA-Seq, and 245 from FCx and 238 from HP with microarrays. Several miRNA families and clusters were differentially expressed between FCx and HP, including the miR-8 family, miR-182|miR-96|miR-183 cluster, and miR-212|miR-312 cluster overexpressed in FCx and miR-34 family overexpressed in HP. To visualize the clusters, we developed support for viewing genomic alignments of miRNA-Seq reads in the Chipster genome browser. We carried out pathway analysis of the predicted target genes of differentially expressed miRNA families and clusters to assess their putative biological functions. Interestingly, several miRNAs from the same family/cluster were predicted to regulate specific biological pathways. We have developed a miRNA-Seq approach with a bioinformatic analysis workflow that is suitable for studying miRNA expression patterns from specific brain nuclei. FCx and HP were shown to have distinct miRNA expression patterns which were reflected in the predicted gene regulatory pathways. This methodology can be applied for the identification of brain region-specific and phenotype-specific miRNA-mRNA-regulatory networks from the adult and developing rodent brain.

Regulation of cellular miRNA expression by human papillomaviruses

High-risk HPV infection leads to aberrant expression of cellular oncogenic and tumor suppressive miRNAs. A large number of these miRNA genes are downstream targets of the transcription factors c-Myc, p53, and E2F and their expression can therefore be modulated by oncogenic HPV E6 and E7. Cervical cancer represents a unique tumor model for understanding how viral E6 and E7 oncoproteins deregulate the expression of the miR-15/16 cluster, miR-17-92 family, miR-21, miR-23b, miR-34a, and miR-106b/93/25 cluster via the E6-p53 and E7-pRb pathways. Moreover, miRNAs may influence the expression of papillomavirus genes in a differentiation-dependent manner by targeting viral RNA transcripts. Cellular miRNAs affecting HPV DNA replication are of great interest and will be a future focus. We are entering an era focusing on miRNA and noncoding RNA, and the studies on HPV and host miRNA interactions will continue shedding more light on our understanding of the HPV life cycle and the mechanistic underpinnings of HPV-induced oncogenesis. This article is part of a Special Issue entitled: "MicroRNAs in viral gene regulation".

Effect of life history on microRNA expression during C. elegans development

Animals have evolved mechanisms to ensure the robustness of developmental outcomes to changing environments. MicroRNA expression may contribute to developmental robustness because microRNAs are key post-transcriptional regulators of developmental gene expression and can affect the expression of multiple target genes. Caenorhabditis elegans provides an excellent model to study developmental responses to environmental conditions. In favorable environments, C. elegans larvae develop rapidly and continuously through four larval stages. In contrast, in unfavorable conditions, larval development may be interrupted at either of two diapause stages: The L1 diapause occurs when embryos hatch in the absence of food, and the dauer diapause occurs after the second larval stage in response to environmental stimuli encountered during the first two larval stages. Dauer larvae are stress resistant and long lived, permitting survival in harsh conditions. When environmental conditions improve, dauer larvae re-enter development, and progress through two post-dauer larval stages to adulthood. Strikingly, all of these life history options (whether continuous or interrupted) involve an identical pattern and sequence of cell division and cell fates. To identify microRNAs with potential functions in buffering development in the context of C. elegans life history options, we used multiplex real-time PCR to assess the expression of 107 microRNAs throughout development in both continuous and interrupted life histories. We identified 17 microRNAs whose developmental profile of expression is affected by dauer life history and/or L1 diapause, compared to continuous development. Hence these microRNAs could function to regulate gene expression programs appropriate for different life history options in the developing worm.

Role of microRNAs in cardiovascular disease: therapeutic challenges and potentials

MicroRNAs (miRNAs, miRs) are short approximately 22-nucleotide noncoding RNAs that bind to messenger RNA transcripts and in doing so modulate cognate gene expression. In eukaryotes, miRNAs act primarily by causing translational repression although they may also act to destabilize RNA transcripts. During the past few years, a number of studies have demonstrated that miR expression changes as a result of cardiac hypertrophy or heart failure. Additionally, cell-based and transgenic mouse studies have demonstrated that individual miRs can affect a number of aspects of cardiac biology including developmental processes, stem cell differentiation, progression of hypertrophy and failure, ion channel function, as well as angiogenesis, rates of apoptosis, and fibroblast proliferation. In this review, we will summarize several of the miRs known to change in expression in association with heart failure and outline details of what is known about their putative targets. In addition, we will review several aspects of regulation of miR expression that have not been addressed in a cardiovascular context. Finally, as is common to all new and rapidly moving fields, we will highlight some of the gaps and inconsistencies related to miR expression and cardiac phenotypes, particularly those associated with heart failure.

A wholly defined Agilent microarray spike-in dataset

MOTIVATION

Spike-in datasets provide a valuable resource for assessing and comparing among competing microarray analysis strategies. Our previous wholly defined spike-in datasets, the Golden and Platinum Spikes, have provided insights for the analysis of Affymetrix GeneChips. However, a similar dataset, in which all cRNA identities and relative levels are known prospectively, has not been available for two-color platforms.

RESULTS

We have generated a wholly defined spike-in dataset for Agilent microarrays consisting of 12 arrays with more than 2000 differentially expressed, and approximately 3600 background, cRNAs. The composition of this 'Ag Spike' dataset is identical to that of our previous Platinum Spike dataset and therefore allows direct cross-platform comparison. We demonstrate here the utility of the Ag Spike dataset for evaluating different analysis methods designed for two-color arrays. Comparison between the Ag Spike and Platinum Spike studies shows high agreement between results obtained using the Affymetrix and Agilent platforms.

AVAILABILITY

The Ag Spike raw data can be accessed at http://www.ccr.buffalo.edu/halfon/spike/index.html and through NCBI's Gene Expression Omnibus (GEO; accession GSE24866).

The small-nucleolar RNAs commonly used for microRNA normalisation correlate with tumour pathology and prognosis

BACKGROUND

To investigate small-nucleolar RNAs (snoRNAs) as reference genes when measuring miRNA expression in tumour samples, given emerging evidence for their role in cancer.

METHODS

Four snoRNAs, commonly used for normalisation, RNU44, RNU48, RNU43 and RNU6B, and miRNA known to be associated with pathological factors, were measured by real-time polymerase chain reaction in two patient series: 219 breast cancer and 46 head and neck squamous cell carcinoma (HNSCC). SnoRNA and miRNA were then correlated with clinicopathological features and prognosis.

RESULTS

Small-nucleolar RNA expression was as variable as miRNA expression (miR-21, miR-210, miR-10b). Normalising miRNA PCR expression data to these recommended snoRNAs introduced bias in associations between miRNA and pathology or outcome. Low snoRNA expression correlated with markers of aggressive pathology. Low levels of RNU44 were associated with a poor prognosis. RNU44 is an intronic gene in a cluster of highly conserved snoRNAs in the growth arrest specific 5 (GAS5) transcript, which is normally upregulated to arrest cell growth under stress. Low-tumour GAS5 expression was associated with a poor prognosis. RNU48 and RNU43 were also identified as intronic snoRNAs within genes that are dysregulated in cancer.

CONCLUSION

Small-nucleolar RNAs are important in cancer prognosis, and their use as reference genes can introduce bias when determining miRNA expression.

Investigation of the microRNAs in safflower seed, leaf, and petal by high-throughput sequencing

Safflower (Carthamus tinctorius L.) is one of the most important crop plants that has been utilized for production of oleosins. miRNAs (microRNAs) are a class of small and non-coding RNAs that negatively regulate gene expression at post-transcriptional level thus playing a role in plant growth, development, and stress response. In this study, high-throughput Illumina sequencing technology has been used to comprehensively investigate the small RNA transcriptomes of safflower seed, flower, and leaf. It is found that there are at least 236 known miRNAs expressed in safflower, of which 100 miRNAs with relatively high expression abundance exhibited evolutionary conservation across multiple plants. Comparison of their expression abundance among different tissues shows that a total of 116, 133, and 128 miRNAs are significantly differentially expressed with higher abundance or lower abundance between safflower seed/leaf, seed/petal, and leaf/petal. The majority of the most significant differences in miRNA abundance between tissues are tissue-specific miRNAs. In addition, 13 putative novel miRNAs have been identified in safflower. The small RNA transcriptomes obtained in this study provide a basis for further investigation of the physiological roles of identified miRNAs in safflower.

Systematic evaluation of three microRNA profiling platforms: microarray, beads array, and quantitative real-time PCR array

Background

A number of gene-profiling methodologies have been applied to microRNA research. The diversity of the platforms and analytical methods makes the comparison and integration of cross-platform microRNA profiling data challenging. In this study, we systematically analyze three representative microRNA profiling platforms: Locked Nucleic Acid (LNA) microarray, beads array, and TaqMan quantitative real-time PCR Low Density Array (TLDA).

Methodology/Principal Findings

The microRNA profiles of 40 human osteosarcoma xenograft samples were generated by LNA array, beads array, and TLDA. Results show that each of the three platforms perform similarly regarding intra-platform reproducibility or reproducibility of data within one platform while LNA array and TLDA had the best inter-platform reproducibility or reproducibility of data across platforms. The endogenous controls/probes contained in each platform have been observed for their stability under different treatments/environments; those included in TLDA have the best performance with minimal coefficients of variation. Importantly, we identify that the proper selection of normalization methods is critical for improving the inter-platform reproducibility, which is evidenced by the application of two non-linear normalization methods (loess and quantile) that substantially elevated the sensitivity and specificity of the statistical data assessment.

Conclusions

Each platform is relatively stable in terms of its own microRNA profiling intra-reproducibility; however, the inter-platform reproducibility among different platforms is low. More microRNA specific normalization methods are in demand for cross-platform microRNA microarray data integration and comparison, which will improve the reproducibility and consistency between platforms.

miR-ID: a novel, circularization-based platform for detection of microRNAs

MicroRNAs (miRNAs) are important regulators of gene expression and have great potential as biomarkers, prognostic indicators, and therapeutic targets. Determining the expression patterns of these molecules is essential for elucidating their biogenesis, regulation, relation to disease, and response to therapy. Although PCR-based assays are commonly used for expression profiling of miRNAs, the small size, sequence heterogeneity, and (in some cases) end modifications of miRNAs constrain the performance of existing PCR methods. Here we introduce miR-ID, a novel method that avoids these constraints while providing superior sensitivity and sequence specificity at a lower cost. It also has the unique ability to differentiate unmodified small RNAs from those carrying 2'-OMe groups at their 3'-ends while detecting both forms. miR-ID is comprised of the following steps: (1) circularization of the miRNA by a ligase; (2) reverse transcription of the circularized miRNA (RTC), producing tandem repeats of a DNA sequence complementary to the miRNA; and (3) qPCR amplification of segments of this multimeric cDNA using 5'-overlapping primers and a nonspecific dye such as SYBR Green. No chemically modified probes (e.g., TaqMan) or primers (e.g., LNA) are required. The circular RNA and multimeric cDNA templates provide unmatched flexibility in the positioning of primers, which may include straddling the boundaries between these repetitive miRNA sequences. miR-ID is based on new findings that are themselves of general interest, including reverse transcription of small RNA circles and the use of 5'-overlapping primers for detection of repetitive sequences by qPCR.

Bacteria-responsive microRNAs regulate plant innate immunity by modulating plant hormone networks

MicroRNAs (miRNAs) are key regulators of gene expression in development and stress responses in most eukaryotes. We globally profiled plant miRNAs in response to infection of bacterial pathogen Pseudomonas syringae pv. tomato (Pst). We sequenced 13 small-RNA libraries constructed from Arabidopsis at 6 and 14 h post infection of non-pathogenic, virulent and avirulent strains of Pst. We identified 15, 27 and 20 miRNA families being differentially expressed upon Pst DC3000 hrcC, Pst DC3000 EV and Pst DC3000 avrRpt2 infections, respectively. In particular, a group of bacteria-regulated miRNAs targets protein-coding genes that are involved in plant hormone biosynthesis and signaling pathways, including those in auxin, abscisic acid, and jasmonic acid pathways. Our results suggest important roles of miRNAs in plant defense signaling by regulating and fine-tuning multiple plant hormone pathways. In addition, we compared the results from sequencing-based profiling of a small set of miRNAs with the results from small RNA Northern blot and that from miRNA quantitative RT-PCR. Our results showed that although the deep-sequencing profiling results are highly reproducible across technical and biological replicates, the results from deep sequencing may not always be consistent with the results from Northern blot or miRNA quantitative RT-PCR. We discussed the procedural differences between these techniques that may cause the inconsistency.

Circulating microRNAs: Association with disease and potential use as biomarkers

The control of gene expression by microRNAs influences many cellular processes and has been implicated in the control of many (patho)physiological states. Recently, microRNAs have been detected in serum and plasma, and circulating microRNA profiles have now been associated with a range of different tumour types, diseases such as stroke and heart disease, as well as altered physiological states such as pregnancy. Here we review the disease-specific profiles of circulating microRNAs, and the methodologies used for their detection and quantification. We also discuss possible functions of circulating microRNAs and their potential as non-invasive biomarkers.

Outsourcing of experimental work

With the development of new technologies for simultaneous analysis of many genes, transcripts, or proteins (the "omics" revolution), it has become common to outsource parts of the experimental work. In order to maintain the integrity of the research projects, it is important that the interphase between the researcher and the service is further developed. This involves robust protocols for sample preparation, an informed choice of analytical tool, development of standards for individual technologies, and transparent data analysis. This chapter introduces some of the problems related to analysis of RNA samples in the "omics" context and gives a few hints and key references related to sample preparation for the non-specialist.

A distributed system for fast alignment of next-generation sequencing data

We developed a scalable distributed computing system using the Berkeley Open Interface for Network Computing (BOINC) to align next-generation sequencing (NGS) data quickly and accurately. NGS technology is emerging as a promising platform for gene expression analysis due to its high sensitivity compared to traditional genomic microarray technology. However, despite the benefits, NGS datasets can be prohibitively large, requiring significant computing resources to obtain sequence alignment results. Moreover, as the data and alignment algorithms become more prevalent, it will become necessary to examine the effect of the multitude of alignment parameters on various NGS systems. We validate the distributed software system by (1) computing simple timing results to show the speed-up gained by using multiple computers, (2) optimizing alignment parameters using simulated NGS data, and (3) computing NGS expression levels for a single biological sample using optimal parameters and comparing these expression levels to that of a microarray sample. Results indicate that the distributed alignment system achieves approximately a linear speed-up and correctly distributes sequence data to and gathers alignment results from multiple compute clients.

The discovery approaches and detection methods of microRNAs

MicroRNAs (miRNAs) are small, highly conserved, non-coding RNAs that regulate gene expression of target mRNAs through cleavage or translational inhibition. Computer-based approaches for miRNA gene identification are being considered as indispensable in miRNAs research. Similarly, experimental approaches for detection of miRNAs are crucial to the testing and validating of computational algorithms. The detection of miRNAs in tissues or cells can supply valuable information for investigating the biological function of these molecules. Selective and highly sensitive detection methods will pave the way for extended understanding of miRNA function within organisms. In this review, we summarize the various computational methods for identification of miRNAs as well as the methodologies that have been developed to detection miRNAs.

Differential expression of cellular microRNAs in HPV-11 transfected cells. An analysis by three different array platforms and qRT-PCR

Human papillomavirus type 11 (HPV-11) infects the genital and the respiratory tract leading to condylomas and respiratory papillomatosis. HPV infections are restricted to epithelial tissue and the progression through the virus lifecycle is tightly coordinated to the differentiation of the host cell. The changes of cellular microRNAs by HPV-11 gene expression were investigated in a cell culture model of HaCaT cells transfected with HPV-11, with the goal of understanding which cellular processes were affected by the virus. Human microRNA profiling was conducted on three different array platform systems and because very few microRNAs (miR-663, -638, -149* and -92b*) were consistently found in all three array data sets we performed extensive statistical analyses of the array data and the qRT-PCR validation. We assume that the most reliable differentially expressed microRNAs are the ones identified by more than one array platform. We also show that TaqMan® qRT-PCR validation is of limited use for less abundant microRNAs.

MicroRNA profiling: separating signal from noise

Various platforms for measuring microRNAs can provide different answers.

Entrapment neuropathy results in different microRNA expression patterns from denervation injury in rats

Background

To compare the microRNA (miRNA) expression profiles in neurons and innervated muscles after sciatic nerve entrapment using a non-constrictive silastic tube, subsequent surgical decompression, and denervation injury.

Methods

The experimental L4-L6 spinal segments, dorsal root ganglia (DRGs), and soleus muscles from each experimental group (sham control, denervation, entrapment, and decompression) were analyzed using an Agilent rat miRNA array to detect dysregulated miRNAs. In addition, muscle-specific miRNAs (miR-1, -133a, and -206) and selectively upregulated miRNAs were subsequently quantified using real-time reverse transcription-polymerase chain reaction (real-time RT-PCR).

Results

In the soleus muscles, 37 of the 47 miRNAs (13.4% of the 350 unique miRNAs tested) that were significantly downregulated after 6 months of entrapment neuropathy were also among the 40 miRNAs (11.4% of the 350 unique miRNAs tested) that were downregulated after 3 months of decompression. No miRNA was upregulated in both groups. In contrast, only 3 miRNAs were upregulated and 3 miRNAs were downregulated in the denervated muscle after 6 months. In the DRGs, 6 miRNAs in the entrapment group (miR-9, miR-320, miR-324-3p, miR-672, miR-466b, and miR-144) and 3 miRNAs in the decompression group (miR-9, miR-320, and miR-324-3p) were significantly downregulated. No miRNA was upregulated in both groups. We detected 1 downregulated miRNA (miR-144) and 1 upregulated miRNA (miR-21) after sciatic nerve denervation. We were able to separate the muscle or DRG samples into denervation or entrapment neuropathy by performing unsupervised hierarchal clustering analysis. Regarding the muscle-specific miRNAs, real-time RT-PCR analysis revealed an ~50% decrease in miR-1 and miR-133a expression levels at 3 and 6 months after entrapment, whereas miR-1 and miR-133a levels were unchanged and were decreased after decompression at 1 and 3 months. In contrast, there were no statistical differences in the expression of miR-206 during nerve entrapment and after decompression. The expression of muscle-specific miRNAs in entrapment neuropathy is different from our previous observations in sciatic nerve denervation injury.

Conclusions

This study revealed the different involvement of miRNAs in neurons and innervated muscles after entrapment neuropathy and denervation injury, and implied that epigenetic regulation is different in these two conditions.

The miR-15/107 group of microRNA genes: evolutionary biology, cellular functions, and roles in human diseases

The miR-15/107 group of microRNA (miRNA) gene is increasingly appreciated to serve key functions in humans. These miRNAs regulate gene expression involved in cell division, metabolism, stress response, and angiogenesis in vertebrate species. The miR-15/107 group has also been implicated in human cancers, cardiovascular disease and neurodegenerative disease, including Alzheimer's disease. Here we provide an overview of the following: (1) the evolution of miR-15/107 group member genes; (2) the expression levels of miRNAs in mammalian tissues; (3) evidence for overlapping gene-regulatory functions by different miRNAs; (4) the normal biochemical pathways regulated by miR-15/107 group miRNAs; and (5) the roles played by these miRNAs in human diseases. Membership in this group is defined based on sequence similarity near the mature miRNAs' 5' end: all include the sequence AGCAGC. Phylogeny of this group of miRNAs is incomplete; thus, a definitive taxonomic classification (e.g., designation as a "superfamily") is currently not possible. While all vertebrates studied to date express miR-15a, miR-15b, miR-16, miR-103, and miR-107, mammals alone are known to express miR-195, miR-424, miR-497, miR-503, and miR-646. Multiple different miRNAs in the miR-15/107 group are expressed at moderate to high levels in human tissues. We present data on the expression of all known miR-15/107 group members in human cerebral cortical gray matter and white matter using new miRNA profiling microarrays. There is extensive overlap in the mRNAs targeted by miR-15/107 group members. We show new data from cultured H4 cancer cells that demonstrate similarities in mRNAs targeted by miR-16 and miR-103 and also support the importance of the mature miRNAs' 5' seed region in mRNA target recognition. In conclusion, the miR-15/107 group of miRNA genes is a fascinating topic of study for evolutionary biologists, miRNA biochemists, and clinically oriented translational researchers alike.