Real-time quantification of microRNAs by stem-loop RT-PCR

A novel microRNA (miRNA) quantification method has been developed using stem-loop RT followed by TaqMan PCR analysis. Stem-loop RT primers are better than conventional ones in terms of RT efficiency and specificity. TaqMan miRNA assays are specific for mature miRNAs and discriminate among related miRNAs that differ by as little as one nucleotide. Furthermore, they are not affected by genomic DNA contamination. Precise quantification is achieved routinely with as little as 25 pg of total RNA for most miRNAs. In fact, the high sensitivity, specificity and precision of this method allows for direct analysis of a single cell without nucleic acid purification. Like standard TaqMan gene expression assays, TaqMan miRNA assays exhibit a dynamic range of seven orders of magnitude. Quantification of five miRNAs in seven mouse tissues showed variation from less than 10 to more than 30,000 copies per cell. This method enables fast, accurate and sensitive miRNA expression profiling and can identify and monitor potential biomarkers specific to tissues or diseases. Stem-loop RT-PCR can be used for the quantification of other small RNA molecules such as short interfering RNAs (siRNAs). Furthermore, the concept of stem-loop RT primer design could be applied in small RNA cloning and multiplex assays for better specificity and efficiency.     

Quantification of Mature MicroRNAs Using Pincer Probes and Real-Time PCR Amplification

The robust and reliable detection of small microRNAs (miRNAs) is important to understand the functional significance of miRNAs. Several methods can be used to quantify miRNAs. Selectively quantifying mature miRNAs among miRNA precursors, pri-miRNAs, and other miRNA-like sequences is challenging because of the short length of miRNAs. In this study, we developed a two-step miRNA quantification system based on pincer probe capture and real-time PCR amplification. The performance of the method was tested using synthetic mature miRNAs and clinical RNA samples. Results showed that the method demonstrated dynamic range of seven orders of magnitude and sensitivity of detection of hundreds of copies of miRNA molecules. The use of pincer probes allowed excellent discrimination of mature miRNAs from their precursors with five Cq (quantification cycle) values difference. The developed method also showed good discrimination of highly homologous family members with cross reaction less than 5%. The pincer probe-based approach is a potential alternative to currently used methods for mature miRNA quantification.     

Real-time quantification of microRNAs by stem–loop RT–PCR

A novel microRNA (miRNA) quantification method has been developed using stem–loop RT followed by TaqMan PCR analysis. Stem–loop RT primers are better than conventional ones in terms of RT efficiency and specificity. TaqMan miRNA assays are specific for mature miRNAs and discriminate among related miRNAs that differ by as little as one nucleotide. Furthermore, they are not affected by genomic DNA contamination. Precise quantification is achieved routinely with as little as 25 pg of total RNA for most miRNAs. In fact, the high sensitivity, specificity and precision of this method allows for direct analysis of a single cell without nucleic acid purification. Like standard TaqMan gene expression assays, TaqMan miRNA assays exhibit a dynamic range of seven orders of magnitude. Quantification of five miRNAs in seven mouse tissues showed variation from less than 10 to more than 30000 copies per cell. This method enables fast, accurate and sensitive miRNA expression profiling and can identify and monitor potential biomarkers specific to tissues or diseases. Stem–loop RT–PCR can be used for the quantification of other small RNA molecules such as short interfering RNAs (siRNAs). Furthermore, the concept of stem–loop RT primer design could be applied in small RNA cloning and multiplex assays for better specificity and efficiency.     

220-plex microRNA expression profile of a single cell

Here we describe a protocol for the detection of the microRNA (miRNA) expression profile of a single cell by stem-looped real-time PCR, which is specific to mature miRNAs. A single cell is first lysed by heat treatment without further purification. Then, 220 known miRNAs are reverse transcribed into corresponding cDNAs by stem-looped primers. This is followed by an initial PCR step to amplify the cDNAs and generate enough material to permit separate multiplex detection. The diluted initial PCR product is used as a template to check individual miRNA expression by real-time PCR. This sensitive technique permits miRNA expression profiling from a single cell, and allows analysis of a few cells from early embryos as well as individual cells (such as stem cells). It can also be used when only nanogram amounts of rare samples are available. The protocol can be completed in 7 d.     

Cerebrospinal Fluid MicroRNA Profiling Using Quantitative Real Time PCR

MicroRNAs (miRNAs) constitute a potent layer of gene regulation by guiding RISC to target sites located on mRNAs and, consequently, by modulating their translational repression. Changes in miRNA expression have been shown to be involved in the development of all major complex diseases. Furthermore, recent findings showed that miRNAs can be secreted to the extracellular environment and enter the bloodstream and other body fluids where they can circulate with high stability. The function of such circulating miRNAs remains largely elusive, but systematic high throughput approaches, such as miRNA profiling arrays, have lead to the identification of miRNA signatures in several pathological conditions, including neurodegenerative disorders and several types of cancers. In this context, the identification of miRNA expression profile in the cerebrospinal fluid, as reported in our recent study, makes miRNAs attractive candidates for biomarker analysis.There are several tools available for profiling microRNAs, such as microarrays, quantitative real-time PCR (qPCR), and deep sequencing. Here, we describe a sensitive method to profile microRNAs in cerebrospinal fluids by quantitative real-time PCR. We used the Exiqon microRNA ready-to-use PCR human panels I and II V2.R, which allows detection of 742 unique human microRNAs. We performed the arrays in triplicate runs and we processed and analyzed data using the GenEx Professional 5 software.Using this protocol, we have successfully profiled microRNAs in various types of cell lines and primary cells, CSF, plasma, and formalin-fixed paraffin-embedded tissues.     

Systematic evaluation of microRNA processing patterns in tissues, cell lines, and tumors

Very little is known regarding regulation of microRNA (miRNA) biogenesis in normal tissues, tumors, and cell lines. Here, we profiled the expression of 225 precursor and mature miRNAs using real-time PCR and compared the expression levels to determine the processing patterns. RNA from 22 different human tissues, 37 human cancer cell lines, and 16 pancreas and liver tissues/tumors was profiled. The relationship between precursor and mature miRNA expression fell into the following four categories: (1) a direct correlation exists between the precursor and mature miRNA expression in all cells/tissues studied; (2) direct correlation of the precursor and mature miRNA exists, yet the expression is restricted to specific cell lines or tissues; (3) there is detectable expression of mature miRNA in certain cells and tissues while the precursor is expressed in all or most cells/tissues; or (4) both precursor and mature miRNA are not expressed. Pearson correlation between the precursor and mature miRNA expression was closer to one for the tissues but was closer to zero for the cell lines, suggesting that processing of precursor miRNAs is reduced in cancer cell lines. By using Northern blotting, we show that many of these miRNAs (e.g., miR-31, miR-105 and miR-128a) are processed to the precursor, but in situ hybridization analysis demonstrates that these miRNA precursors are retained in the nucleus. We provide a database of the levels of precursor and mature miRNA in a variety of cell types. Our data demonstrate that a large number of miRNAs are transcribed but are not processed to the mature miRNA.     

New miRNA labeling method for bead-based quantification

Background  

microRNAs (miRNAs) are small single-stranded non-coding RNAs that act as crucial regulators of gene expression. Different methods have been developed for miRNA expression profiling in order to better understand gene regulation in normal and pathological conditions. miRNAs expression values obtained from large scale methodologies such as microarrays still need a validation step with alternative technologies.     

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.     

Expression profiles of precursor and mature microRNAs under dehydration and high salinity shock in Populus euphratica

MicroRNAs (miRNAs) are small non-coding RNAs that play vital roles in plant abiotic stress responses via cleavage or translational inhibition of their target mRNAs. Populus euphratica is a typical stress-resistant sessile organism that grows in desert areas. Here, we identified sequences of 12 miRNA precursors from 11 families and 13 mature miRNAs from 12 families by PCR amplification in P. euphratica. To detect expression differences in mature miRNAs and their precursors under dehydration and high salinity shock in P. euphratica, we examined 14 miRNA precursors from 13 miRNA families and 17 mature miRNAs from 17 miRNA families using the SYBR Green RT–PCR assay. This is the first report of expression profiles for both precursor and mature miRNAs in P. euphratica. By profiling both the mature miRNAs and the precursors under abiotic stress shock, it was possible to identify miRNA whose processing is regulated during stress shock environments. A majority of the genes predicted to be targets for plant miRNAs are involved in development, stress resistance and metabolic processes. We have cloned and experimentally identified in vivo five of the predicted target genes and quantified the five target mRNAs from the same RNA sample simultaneously. Based on this study, we propose some regulatory pathways that illustrate the important role that miRNAs play in response to abiotic stress shock in P. euphratica.     

SNPs in human miRNA genes affect biogenesis and function

MicroRNAs (miRNAs) are 21–25-nucleotide-long, noncoding RNAs that are involved in translational regulation. Most miRNAs derive from a two-step sequential processing: the generation of pre-miRNA from pri-miRNA by the Drosha/DGCR8 complex in the nucleus, and the generation of mature miRNAs from pre-miRNAs by the Dicer/TRBP complex in the cytoplasm. Sequence variation around the processing sites, and sequence variations in the mature miRNA, especially the seed sequence, may have profound affects on miRNA biogenesis and function. In the context of analyzing the roles of miRNAs in Schizophrenia and Autism, we defined at least 24 human X-linked miRNA variants. Functional assays were developed and performed on these variants. In this study we investigate the affects of single nucleotide polymorphisms (SNPs) on the generation of mature miRNAs and their function, and report that naturally occurring SNPs can impair or enhance miRNA processing as well as alter the sites of processing. Since miRNAs are small functional units, single base changes in both the precursor elements as well as the mature miRNA sequence may drive the evolution of new microRNAs by altering their biological function. Finally, the miRNAs examined in this study are X-linked, suggesting that the mutant alleles could be determinants in the etiology of diseases.     

人源microRNA分子表达库的构建

microRNA(miRNA)是一类长度为22nt左右的单链非编码小RNA分子,通过与靶mRNA分子结合而沉默其表达.目前,虽然在多种生物中发现了大量的miRNA,但对它们的功能还知之甚少.为了深入研究miRNA的功能,构建了一个包括170多种人源miRNA表达载体的miRNA分子表达库,并对部分表达载体采用RNA印迹及双荧光素酶分析技术进行验证.实验证明:这些miRNA表达载体在HEK-293细胞内可以高水平表达miRNA前体和成熟的miRNA,并且能抑制含有相应靶位点的报告基因的表达.这些结果表明:该miRNA表达库可以表达功能miRNA,并可用于miRNA功能的筛选和研究.     

A comprehensive study of multiple mapping and feature selection for correction strategy in the analysis of small RNAs from SOLiD sequencing

High-throughput sequencing is a powerful tool for discovering and profiling microRNAs (miRNAs) to gain further insights into their biogenesis and function. Due to shorter size, short RNAs from deep sequencing dataset are prone to map to multiple loci with an equal number of mismatches, especially among multicopy miRNA precursors and homologous miRNA genes. Systematic analysis of SOLiD sequencing dataset showed that 37.94% short RNAs could simultaneously map to more than one miRNA precursor, and more short RNAs were found to have multiple genomic loci. Improper selection from candidate loci might lose some mapping information, influence miRNA expression profile or even mislead to identify novel miRNAs. A comprehensive study indicated several potential features for correction strategy: location and distribution of mismatches, quality values, expression profiles of multiple isomiRs (miRNA variants), miRNA* and moRs (miRNA-offset-RNAs) at candidate locus and in its flank sequence. Further studies should develop an approach to correct the widespread phenomenon of multiple mapping based on these features, and improve accuracy of profiling and discovering miRNAs.     

Rapid microRNA (miRNA) detection and classification via surface-enhanced Raman spectroscopy (SERS)

microRNAs (miRNA) are recognized as regulators of gene expression during development and cell differentiation as well as biomarkers of disease. Development of rapid and sensitive miRNA profiling methods is essential for evaluating the pattern of miRNA expression that varies across normal and diseased states. The ability to identify miRNA expression patterns is limited to cumbersome assays that often lack sensitivity and specificity to distinguish between different miRNA families and members. We evaluated a surface-enhanced Raman scattering (SERS) platform for detection and classification of miRNAs. The strength of the SERS-based sensor is its sensitivity to detect extremely low levels of analyte and specificity to provide the molecular fingerprint of the analyte. We show that the SERS spectra of related and unrelated miRNAs can be detected in near-real time, that detection is sequence dependent, and that SERS spectra can be used to classify miRNA patterns with high accuracy.