MicroRNA is a set of small RNA molecules mediating gene expression at post-transcriptional/translational levels. Most of well-established high throughput discovery platforms, such as microarray, real time quantitative PCR, and sequencing, have been adapted to study microRNA in various human diseases. The total number of microRNAs in humans is approximately 1,800, which challenges some analytical methodologies requiring a large number of entries. Unlike messenger RNA, the majority of microRNA (60%) maintains relatively low abundance in the cells. When analyzed using microarray, the signals of these low-expressed microRNAs are influenced by other non-specific signals including the background noise. It is crucial to distinguish the true microRNA signals from measurement errors in microRNA array data analysis. In this study, we propose a novel measurement error model-based normalization method and differentially-expressed microRNA detection method for microRNA profiling data acquired from locked nucleic acids (LNA) microRNA array. Compared with some existing methods, the proposed method significantly improves the detection among low-expressed microRNAs when assessed by quantitative real-time PCR assay.
Second-generation sequencing is a powerful method for identifying and quantifying small-RNA components of cells. However, little attention has been paid to the effects of the choice of sequencing platform and library preparation protocol on the results obtained. We present a thorough comparison of small-RNA sequencing libraries generated from the same embryonic stem cell lines, using different sequencing platforms, which represent the three major second-generation sequencing technologies, and protocols. We have analysed and compared the expression of microRNAs, as well as populations of small RNAs derived from repetitive elements. Despite the fact that different libraries display a good correlation between sequencing platforms, qualitative and quantitative variations in the results were found, depending on the protocol used. Thus, when comparing libraries from different biological samples, it is strongly recommended to use the same sequencing platform and protocol in order to ensure the biological relevance of the comparisons.
Over the last decade, DNA microarray technology has provided a great contribution to the life sciences. The MicroArray Quality Control (MAQC) project demonstrated the way to analyze the expression microarray. Recently, microarray technology has been utilized to analyze a comprehensive microRNA expression profiling. Currently, several platforms of microRNA microarray chips are commercially available. Thus, we compared repeatability and comparability of five different microRNA microarray platforms (Agilent, Ambion, Exiqon, Invitrogen and Toray) using 309 microRNAs probes, and the Taqman microRNA system using 142 microRNA probes. This study demonstrated that microRNA microarray has high intra-platform repeatability and comparability to quantitative RT-PCR of microRNA. Among the five platforms, Agilent and Toray array showed relatively better performances than the others. However, the current lineup of commercially available microRNA microarray systems fails to show good inter-platform concordance, probably because of lack of an adequate normalization method and severe divergence in stringency of detection call criteria between different platforms. This study provided the basic information about the performance and the problems specific to the current microRNA microarray systems.
MicroRNAs play a role in regulating diverse biological processes and have considerable utility as molecular markers for diagnosis and monitoring of human disease. Several technologies are available commercially for measuring microRNA expression. However, cross-platform comparisons do not necessarily correlate well, making it difficult to determine which platform most closely represents the true microRNA expression level in a tissue. To address this issue, we have analyzed RNA derived from cell lines, as well as fresh frozen and formalin-fixed paraffin embedded tissues, using Affymetrix, Agilent, and Illumina microRNA arrays, NanoString counting, and Illumina Next Generation Sequencing. We compared the performance within- and between the different platforms, and then verified these results with those of quantitative PCR data. Our results demonstrate that the within-platform reproducibility for each method is consistently high and although the gene expression profiles from each platform show unique traits, comparison of genes that were commonly detectable showed that detection of microRNA transcripts was similar across multiple platforms.
microRNAs represent the best described class of small RNAs (21-23nt) and have been shown to function as post-transcriptional regulators of gene expression. The high relative stability of microRNA in common clinical source materials and the ability of microRNA expression profiles to accurately classify discrete tissue types and specific disease states have positioned microRNA quantification as a promising new biomarker for a wide range of diagnostic applications
We have developed a genome-wide LNA™-based microRNA qPCR platform with unparalleled sensitivity and robustness even in biofluids where microRNA levels are extremely low. Only a single cDNA synthesis reaction is required to conduct full miRNome profiling thereby facilitating high-throughput profiling in important clinical sources without the need for pre-amplification. Thousands of biofluid samples have been profiled including blood derived plasma/serum and urine to accurately determine normal reference ranges for circulating microRNAs. Procedures have been developed to control pre-analytical variables such as hemolysis in serum/plasma samples. In addition, a data QC system has been implemented to secure technical excellence and reveal any unwanted bias in the dataset.
We are currently screening for and validating microRNAs as biomarkers for stage II colorectal cancer (CRC). microRNA profiling has been performed on plasma samples from a clinical trial conducted in 7 different hospitals. We show that hemolysis in this sample set correlates with hospital ID, and with the utilization of specific blood sample collection vials. Using a microRNA-based hemolysis signature, we eliminated hemolyzed samples and demonstrated that this step leads to a major improvement of CRC detection (ROC AUC increase from 0.67 to 0.80). We conclude that pre-analytical variables such as hemolysis can be a source of bias in samples of different origin, and that sample and data QC procedures can overcome this challenge and lead to improved miRNA biomarker performance.
MicroRNAs fine-tune the activity of hundreds of protein-coding genes. The identification of tissue-specific microRNAs and their promoters has been constrained by the limited sensitivity of prior microRNA quantification methods. Here, we determine the entire microRNAome of three endoderm-derived tissues, liver, jejunum and pancreas, using ultra-high throughput sequencing. Although many microRNA genes are expressed at comparable levels, 162 microRNAs exhibited striking tissue-specificity. After mapping the putative promoters for these microRNA genes using H3K4me3 histone occupancy, we analyzed the regulatory modules of 63 microRNAs differentially expressed between liver and jejunum or pancreas. We determined that the same transcriptional regulatory mechanisms govern tissue-specific gene expression of both mRNA and microRNA encoding genes in mammals.
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.
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.
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.
Over the past year, the MARG has focused on 3 biotechnology research and education areas: 1) completion and analysis of aperformance study of multiple DNA microarray and deep-sequencing platforms for microRNA profiling; 2) development of synthetic microRNA standards for validating methods and platforms for microRNA profilingassays in core and research laboratories; and 3) expanding MARG focus to include other genomic profiling platforms.We will present an overview on current MARG activities and new initiatives including the launch of a new webforum for genomic profiling technology and assays. The results of the microRNA profiling study on 5 DNA array platforms and 2 next-generation sequencers will be presented and discussed. Finally, we will summarize our progress in developing a set of synthetic microRNA standards that can be used by core laboratories to test methods and validate platforms for microRNA profiling.These standards will be made available to ABRF member labs after testing in MARG laboratories is complete.
Urothelial carcinoma of the bladder (UCC) is a common disease that arises by at least two different molecular pathways. The biology of UCC is incompletely understood, making the management of this disease difficult. Recent evidence implicates a regulatory role for microRNA in cancer. We hypothesized that altered microRNA expression contributes to UCC carcinogenesis. To test this hypothesis we examined the expression of 322 microRNAs and their processing machinery in 78 normal and malignant urothelial samples using realtime rtPCR. Genes targeted by differentially expressed microRNA were investigated using realtime quantification and microRNA knock-down. We also examined the role of aberrant DNA hypermethylation in microRNA down-regulation. We found that altered microRNA expression is common in UCC and occurs early in tumorogenesis. In normal urothelium from patients with UCC 11% of microRNA’s had altered expression when compared to disease-free controls. This was associated with upregulation of Dicer, Drosha and Exportin 5. In UCC, microRNA alterations occur in a tumor phenotype-specific manner and can predict disease progression. High-grade UCC were characterized by microRNA upregulation, including microRNA-21 that suppresses p53 function. In low-grade UCC there was down-regulation of many microRNA molecules. In particular, loss of microRNAs-99a/100 leads to upregulation of FGFR3 prior to its mutation. Promoter hypermethylation is partly responsible for microRNA down-regulation. In conclusion, distinct microRNA alterations characterize UCC and target genes in a pathway-specific manner. These data reveal new insights into the disease biology and have implications regarding tumor diagnosis, prognosis and therapy.
MicroRNAs are positive and negative regulators of eukaryotic gene expression that modulate transcript abundance by specific binding to sequence motifs located prevalently in the 3' untranslated regions of target messenger RNAs (mRNA). Interferon-alpha-2a (IFNα) induces a large set of protein coding genes mediating antiproliferative and antiviral responses. Here we use a global microarray-based microRNA detection platform to identify genes that are induced by IFNα in hepatoma- or melanoma-derived human tumor cell lines. Despite the enormous differences in expression levels between these models, we were able to identify microRNAs that are upregulated by IFNα in both lines suggesting the possibility that interferon-regulated microRNAs are involved in the transcriptional repression of mRNA relevant to cytokine responses.
MicroRNAs; Oligonucleotide Array Sequence Analysis; Interferons; Melanoma; Hepatoma; Reverse Transcriptase Polymerase Chain Reaction; Suppressor of Cytokine Signaling Proteins
MicroRNA profiling represents an important first-step in deducting individual RNA-based regulatory function in a cell, tissue, or at a specific developmental stage. Currently there are several different platforms to choose from in order to make the initial miRNA profiles. In this study we investigate recently developed digital microRNA high-throughput technologies. Four different platforms were compared including next generation SOLiD ligation sequencing and Illumina HiSeq sequencing, hybridization-based NanoString nCounter, and miRCURY locked nucleic acid RT-qPCR. For all four technologies, full microRNA profiles were generated from human cell lines that represent noninvasive and invasive tumorigenic breast cancer. This study reports the correlation between platforms, as well as a more extensive analysis of the accuracy and sensitivity of data generated when using different platforms and important consideration when verifying results by the use of additional technologies. We found all the platforms to be highly capable for microRNA analysis. Furthermore, the two NGS platforms and RT-qPCR all have equally high sensitivity, and the fold change accuracy is independent of individual miRNA concentration for NGS and RT-qPCR. Based on these findings we propose new guidelines and considerations when performing microRNA profiling.
EBV and KSHV are both gamma-herpesviruses which express multiple viral microRNAs. Various methods have been used to investigate the functions of these microRNAs, largely through identification of microRNA target genes. Surprisingly, these related viruses do not share significant sequence homology in their microRNAs. A number of reports have described functions of EBV and KSHV microRNA targets, however only three experimentally validated target genes have been shown to be targeted by microRNAs from both viruses. More sensitive methods to identify microRNA targets have predicted approximately 60% of host targets could be shared by EBV and KSHV microRNAs, but by targeting different sequences in the host targets. In this review, we explore the similarities of microRNA functions and targets of these related viruses.
EBV; KSHV; HHV4; HHV8; miRNAs; microRNAs
Vesicular stomatitis virus (VSV) has long been regarded as a promising recombinant vaccine platform and oncolytic agent but has not yet been tested in humans because it causes encephalomyelitis in rodents and primates. Recent studies have shown that specific tropisms of several viruses could be eliminated by engineering microRNA target sequences into their genomes, thereby inhibiting spread in tissues expressing cognate microRNAs. We therefore sought to determine whether microRNA targets could be engineered into VSV to ameliorate its neuropathogenicity. Using a panel of recombinant VSVs incorporating microRNA target sequences corresponding to neuron-specific or control microRNAs (in forward and reverse orientations), we tested viral replication kinetics in cell lines treated with microRNA mimics, neurotoxicity after direct intracerebral inoculation in mice, and antitumor efficacy. Compared to picornaviruses and adenoviruses, the engineered VSVs were relatively resistant to microRNA-mediated inhibition, but neurotoxicity could nevertheless be ameliorated significantly using this approach, without compromise to antitumor efficacy. Neurotoxicity was most profoundly reduced in a virus carrying four tandem copies of a neuronal mir125 target sequence inserted in the 3′-untranslated region of the viral polymerase (L) gene.
Although analysis of microRNAs (miRNAs) by DNA microarrays is gaining in popularity, these new technologies have not been adequately validated. We examined within and between platform reproducibility of four miRNA array technologies alongside TaqMan PCR arrays.
Two distinct pools of reference materials were selected in order to maximize differences in miRNA content. Filtering for miRNA that yielded signal above background revealed 54 miRNA probes (matched by sequence) across all platforms. Using this probeset as well as all probes that were present on an individual platform, within-platform analyses revealed Spearman correlations of >0.9 for most platforms. Comparing between platforms, rank analysis of the log ratios of the two reference pools also revealed high correlation (range 0.663-0.949). Spearman rank correlation and concordance correlation coefficients for miRNA arrays against TaqMan qRT-PCR arrays were similar for all of the technologies. Platform performances were similar to those of previous cross-platform exercises on mRNA and miRNA microarray technologies.
These data indicate that miRNA microarray platforms generated highly reproducible data and can be recommended for the study of changes in miRNA expression.
Playing a central role in the maintenance of hemostasis as well as in thrombotic disorders, platelets contain a relatively diverse messenger RNA (mRNA) transcriptome as well as functional mRNA-regulatory microRNAs, suggesting that platelet mRNAs may be regulated by microRNAs. Here, we elucidated the complete repertoire and features of human platelet microRNAs by high-throughput sequencing. More than 492 different mature microRNAs were detected in human platelets, whereas the list of known human microRNAs was expanded further by the discovery of 40 novel microRNA sequences. As in nucleated cells, platelet microRNAs bear signs of post-transcriptional modifications, mainly terminal adenylation and uridylation. In vitro enzymatic assays demonstrated the ability of human platelets to uridylate microRNAs, which correlated with the presence of the uridyltransferase enzyme TUT4. We also detected numerous microRNA isoforms (isomiRs) resulting from imprecise Drosha and/or Dicer processing, in some cases more frequently than the reference microRNA sequence, including 5′ shifted isomiRs with redirected mRNA targeting abilities. This study unveils the existence of a relatively diverse and complex microRNA repertoire in human platelets, and represents a mandatory step towards elucidating the intraplatelet and extraplatelet role, function and importance of platelet microRNAs.
MicroRNAs are small, highly conserved non-coding RNA molecules involved in the regulation of gene expression. MicroRNAs are transcribed by RNA polymerases II and III, generating precursors that undergo a series of cleavage events to form mature microRNA. The conventional biogenesis pathway consists of two cleavage events, one nuclear and one cytoplasmic. However, alternative biogenesis pathways exist that differ in the number of cleavage events and enzymes responsible. How microRNA precursors are sorted to the different pathways is unclear but appears to be determined by the site of origin of the microRNA, its sequence and thermodynamic stability. The regulatory functions of microRNAs are accomplished through the RNA-induced silencing complex (RISC). MicroRNA assembles into RISC, activating the complex to target messenger RNA (mRNA) specified by the microRNA. Various RISC assembly models have been proposed and research continues to explore the mechanism(s) of RISC loading and activation. The degree and nature of the complementarity between the microRNA and target determine the gene silencing mechanism, slicer-dependent mRNA degradation or slicer-independent translation inhibition. Recent evidence indicates that P-bodies are essential for microRNA-mediated gene silencing and that RISC assembly and silencing occurs primarily within P-bodies. The P-body model outlines microRNA sorting and shuttling between specialized P-body compartments that house enzymes required for slicer –dependent and –independent silencing, addressing the reversibility of these silencing mechanisms. Detailed knowledge of the microRNA pathways is essential for understanding their physiological role and the implications associated with dysfunction and dysregulation.
MicroRNA; RNA interference (RNAi); Post-transcriptional gene regulation; Cancer.
MicroRNAs expression is deregulated in acute myeloid leukemia, but the corresponding functional microRNA-controlled pathways are poorly understood. Integration of mRNA and microRNA expression profiling may allow the identification of functional links between the whole transcriptome and microRNome that are involved in myeloid leukemogenesis.
Therefore, here we integrated microRNA and mRNA expression profiles obtained from 48 newly diagnosed acute myeloid leukemia patients by using two different microarray platforms and performed correlation, gene ontology and network analysis. Experimental validation was also performed in acute myeloid leukemia cell lines using microRNA mimics oligonucleotides and functional assays.
Our analysis identified a strong positive correlation of HOX related genes with miR-10 and miR-20a. Furthermore, we observed a negative correlation between miR-181a and -181b, -155 and -146 expression with that of genes involved in immunity and inflammation (e.g. IRF7 and TLR4) and a positive correlation between miR-23a, miR-26a, miR-128a and miR-145 expression with that of pro-apoptotic genes (e.g., BIM and PTEN). These correlations were confirmed by gene ontology analyses, which evidenced the enrichment of members of the homeobox, immunity and inflammation and apoptosis biologic process, respectively. Furthermore, we validated experimentally the association of miR-145, miR-26a and miR-128a with apoptosis in acute myeloid leukemia.
Our results indicate that by integrating the transcriptome and microRNome in acute myeloid leukemia cells is possible to identify previously unidentified putative functional microRNA-mRNA interactions in acute myeloid leukemia.
microRNA; networks; AML; microarrays
MicroRNAs are important regulators of gene expression at the post-transcriptional level and play an important role in many biological processes. Due to the important biological role it is of great interest to quantitatively determine their expression level in different biological settings.
We describe a PCR method for quantification of microRNAs based on a single reverse transcription reaction for all microRNAs combined with real-time PCR with two, microRNA-specific DNA primers. Primer annealing temperatures were optimized by adding a DNA tail to the primers and could be designed with a success rate of 94%. The method was able to quantify synthetic templates over eight orders of magnitude and readily discriminated between microRNAs with single nucleotide differences. Importantly, PCR with DNA primers yielded significantly higher amplification efficiencies of biological samples than a similar method based on locked nucleic acids-spiked primers, which is in agreement with the observation that locked nucleic acid interferes with efficient amplification of short templates. The higher amplification efficiency of DNA primers translates into higher sensitivity and precision in microRNA quantification.
MiR-specific quantitative RT-PCR with DNA primers is a highly specific, sensitive and accurate method for microRNA quantification.
microRNAs have been shown to be involved in different human cancers. We therefore have performed expression profiles on a panel of pediatric tumors to identify cancer-specific microRNAs. We also investigated if microRNAs are co-regulated with their host gene.
We performed parallel microRNAs and mRNA expression profiling on 57 tumor xenografts and cell lines representing 10 different pediatric solid tumors using microarrays. For those microRNAs that map to their host mRNA, we calculated correlations between them.
We found that the majority of cancer types clustered together based on their global microRNA expression profiles by unsupervised hierarchical clustering. Fourteen microRNAs were significantly differentially expressed between rhabdomyosarcoma and neuroblastoma, and 8 of them were validated in independent patient tumor samples. Exploration of the expression of microRNAs in relationship with their host genes demonstrated that the expression for 43 (63%) of 68 microRNAs located inside known coding genes were significantly correlated with that of their host genes. Among these 43 microRNAs, 5 out of 7 microRNAs in the OncomiR-1 cluster correlated significantly with their host gene MIRHG1 (P<0.01). In addition, high expression of MIRHG1 was significantly associated with high stage and MYCN-amplification in neuroblastoma tumors; and the expression level of MIRHG1 could predict the outcome of neuroblastoma patients independently from the current neuroblastoma risk-stratification in two independent patient cohorts.
Pediatric cancers express cancer-specific microRNAs. The high expression of the OncomiR-1 host gene MIRHG1 correlates with poor outcome for patients with neuroblastoma, indicating important oncogenic functions of this microRNA cluster in neuroblastoma biology.
microRNA; gene expression profiling; microarray; pediatric cancer; neuroblastoma; cancer classification; OncomiR-1; MIRHG1; prognosis
The use of new, deep sequencing technologies has greatly accelerated microRNA discovery. We have applied this approach to the identification of chicken microRNAs and to the comparison of microRNAs in chicken embryo fibroblasts (CEF) infected with Marek's disease virus (MDV) to those present in uninfected CEF.
We obtained 125,463 high quality reads that showed an exact match to the chicken genome. The majority of the reads corresponded to previously annotated chicken microRNAs; however, the sequences of many potential novel microsRNAs were obtained. A comparison of the reads obtained in MDV-infected and uninfected CEF indicates that infection does not significantly perturb the expression profile of microRNAs. Frequently sequenced microRNAs include miR-221/222, which are thought to play a role in growth and proliferation. A number of microRNAs (e.g., let-7, miR-199a-1, 26a) are expressed at lower levels in MDV-induced tumors, highlighting the potential importance of this class of molecules in tumorigenesis.
Deep sequencing technology is highly suited for small RNA discovery. This approach is independent of comparative sequence analysis, which has been the primary method used to identify chicken microRNAs. Our results have confirmed the expression of many microRNAs identified by sequence similarity and identified a pool of candidate novel microRNAs.
MicroRNAs (small ~22 nucleotide long non-coding endogenous RNAs) have recently attracted immense attention as critical regulators of gene expression in multi-cellular eukaryotes, especially in humans. Recent studies have proved that viruses also express microRNAs, which are thought to contribute to the intricate mechanisms of host-pathogen interactions. Computational predictions have greatly accelerated the discovery of microRNAs. However, most of these widely used tools are dependent on structural features and sequence conservation which limits their use in discovering novel virus expressed microRNAs and non-conserved eukaryotic microRNAs. In this work an efficient prediction method is developed based on the hypothesis that sequence and structure features which discriminate between host microRNA precursor hairpins and pseudo microRNAs are shared by viral microRNA as they depend on host machinery for the processing of microRNA precursors. The proposed method has been found to be more efficient than recently reported ab-initio methods for predicting viral microRNAs and microRNAs expressed by mammals.
MicroRNAs can promote translation of specific mRNAs in quiescent (G0) mammalian cells and immature Xenopus laevis oocytes. We report that microRNA-mediated upregulation of target mRNAs in oocytes is dependent on nuclear entry of the microRNA; cytoplasmically-injected microRNA repress target mRNAs. Components of the activation microRNP, AGO, FXR1 (FXR1-iso-a) and miR16 are present in the nucleus and cytoplasm. Importantly, microRNA target mRNAs for upregulation, Myt1, TNFα and a reporter bearing the TNFα AU-rich, microRNA target sequence, are associated with AGO in immature oocyte nuclei and AGO2 in G0 human nuclei, respectively. mRNAs that are repressed or lack target sites are not associated with nuclear AGO. Crosslinking-coupled immunopurification revealed greater association of AGO2 with FXR1 in the nucleus compared to cytoplasm. Consistently, overexpression of FXR1-iso-a rescues activation of cytoplasmically-injected RNAs and in low density, proliferating cells. These data indicate the importance of a compartmentalized AGO2-FXR1-iso-a complex for selective recruitment for microRNA-mediated upregulation.
MicroRNAs (miRNAs) are ~22 nucleotide non-coding RNA molecules that usually function as endogenous repressors of target genes. Many biological processes depend on faithful miRNA expression and miRNA profiling has revealed dysregulation of many miRNAs in neurological, and cardiovascular diseases, and in cancer. Despite this finding, most studies have focused on the function of single miRNAs or miRNA clusters. To better address physiologically relevant collaborative miRNA interactions, we developed a simple and flexible platform which expresses several miRNAs that have different genomic locations from a single transcript using endogenous pre-miRNA sequences. As a proof of principle we cloned the miR-34 tumor suppressor family and showed that the miR-34a/34b/34c vector expresses each miRNA at similar levels to individual miRNA containing vectors. Moreover, the miR-34a/34b/34c vector suppressed cell growth more than the individual miRNA vectors. We expect that this platform will be invaluable as a tool to study the complex and synergistic interactions of aberrantly expressed miRNAs in human diseases and may have applications for use in gene therapy.
Archived formalin-fixed paraffin-embedded (FFPE) specimens represent excellent resources for biomarker discovery, but it has been a major challenge to study gene expression in these samples due to mRNA degradation and modification during fixation and processing. MicroRNAs (miRNAs) regulate gene expression at post-transcriptional level and are considered as important regulators of cancer progression. Next generation sequencing technologies such as SOLiD™ provide an ideal method for measuring the abundance of miRNA molecules in different cancer stages and provide insightful information on tumorigenesis. However, currently there is no good method to systematically study miRNA expression in FFPE samples on next generation sequencing platforms. We have designed and developed a ligation-based miRNA detection method to capture small RNA sequences in FFPE samples and convert them into templates suitable for sequencing on the SOLiD™ System. Total RNA was isolated from matched lung adenocarcinoma FFPE and snap frozen tissues using an Ambion RecoverAll™ kit. A PureLink™ miRNA Isolation kit was used to enrich the small RNA fraction in these total RNA samples. Library preparation using a SOLiD™ Total RNA-Seq kit with modified protocol was performed on the enriched RNA followed by sequencing on SOLiD™ system. Our results show that small RNA extracted from FFPE samples was successfully converted to small RNA libraries. Very similar mapping statistics were obtained from matched FFPE and fresh-frozen samples after SOLiD™ sequencing. A good correlation of miRNA expression pattern was also observed. This suggests that miRNA molecules are less affected by sample degradation and RNA-protein crosslink. This study provides a foundation for miRNA expression analysis on SOLiD™ system using FFPE samples in cancer and other diseases.
There is great demand for flexible biomolecule analysis platforms that can precisely quantify very low levels of multiple targets directly in complex biological samples. Herein we demonstrate multiplexed quantification of microRNAs (miRNAs) on encoded hydrogel microparticles with sub-femtomolar sensitivity and single-molecule reporting resolution. Rolling circle amplification (RCA) of a universal adapter sequence that is ligated to all miRNA targets captured on gel-embedded probes provides the ability to label each target with multiple fluorescent reporters and eliminates the possibility of amplification bias. The high degree of sensitivity achieved by the RCA scheme and the resistance to fouling afforded by the use of gel particles are leveraged to directly detect miRNA in small quantities of unprocessed human serum samples without the need for RNA extraction or target-amplification steps. This versatility has powerful implications for the development of rapid, non-invasive diagnostic assays.