Strategies for profiling microRNA expression

MicroRNAs (miRNAs) are a class of small RNAs ( approximately 22-nt) that play an important role in the control of different cell processes by negative regulation of protein-coding genes. In the last several years, a number of miRNA profiling strategies have been used to document the miRNA expression changes during physiological and pathological processes. Aberrant expression of miRNAs has been linked to developmental defects, cancer, neurological disorders, and heart diseases. Over 540 human miRNAs have been validated to date; however, computer models suggest there may be thousands more. As bench work continue to verify in silico predictions, miRNA profiling will remain a prominent tool for identification of differential expression miRNAs in normal cellular courses and human disorders. This review focuses on current strategies for miRNA expression profiling and discusses their sensitivity and specificity, as well as advantage and disadvantage.     

Focus on RNA isolation: obtaining RNA for microRNA (miRNA) expression profiling analyses of neural tissue

MicroRNAs (miRNAs) are present in all known plant and animal tissues and appear to be somewhat concentrated in the mammalian nervous system. Many different miRNA expression profiling platforms have been described. However, relatively little research has been published to establish the importance of 'upstream' variables in RNA isolation for neural miRNA expression profiling. We tested whether apparent changes in miRNA expression profiles may be associated with tissue processing, RNA isolation techniques, or different cell types in the sample. RNA isolation was performed on a single brain sample using eight different RNA isolation methods, and results were correlated using a conventional miRNA microarray and then cross-referenced to Northern blots. Differing results were seen between samples obtained using different RNA isolation techniques and between microarray and Northern blot results. Another complication of miRNA microarrays is tissue-level heterogeneity of cellular composition. To investigate this phenomenon, miRNA expression profiles were determined and compared between highly-purified primary cerebral cortical cell preparations of rat primary E15-E18 neurons versus rat primary E15-E18 astrocytes. Finally, to assess the importance of dissecting human brain gray matter from subjacent white matter in cerebral cortical studies, miRNA expression profiles were compared between gray matter and immediately contiguous white matter. The results suggest that for microarray studies, cellular composition is important, and dissecting white matter from gray matter improves the specificity of the results. Based on these data, recommendations for miRNA expression profiling in neural tissues, and considerations worthy of further study, are discussed.     

miRExpress: Analyzing high-throughput sequencing data for profiling microRNA expression

Background  

MicroRNAs (miRNAs), small non-coding RNAs of 19 to 25 nt, play important roles in gene regulation in both animals and plants. In the last few years, the oligonucleotide microarray is one high-throughput and robust method for detecting miRNA expression. However, the approach is restricted to detecting the expression of known miRNAs. Second-generation sequencing is an inexpensive and high-throughput sequencing method. This new method is a promising tool with high sensitivity and specificity and can be used to measure the abundance of small-RNA sequences in a sample. Hence, the expression profiling of miRNAs can involve use of sequencing rather than an oligonucleotide array. Additionally, this method can be adopted to discover novel miRNAs.     

An oligonucleotide microarray for microRNA expression analysis based on labeling RNA with quantum dot and nanogold probe

MicroRNAs (miRNAs) play important regulatory roles in animals and plants by targeting mRNAs for cleavage or translational repression. They have diverse expression patterns and might regulate various developmental and physiological processes. Profiling miRNA expression is very helpful for studying biological functions of miRNAs. We report a novel miRNA profiling microarray, in which miRNAs were directly labeled at the 3′ terminus with biotin and hybridized with complementary oligo-DNA probes immobilized on glass slides, and subsequently detected by measuring fluorescence of quantum dots labeled with streptavidin bound to miRNAs through streptavidin–biotin interaction. The detection limit of this microarray for miRNA was ~0.4 fmol, and the detection dynamic range spanned about 2 orders of magnitude. We made a model microarray to profile 11 miRNAs from leaf and root of rice (Oryza sativa L. ssp. indica) seedlings. The analysis results of the miRNAs had a good reproducibility and were consistent with the northern blot result. To avoid using high-cost detection equipment, colorimetric detection, a method based on nanogold probe coupled with silver enhancement, was also successfully introduced into miRNA profiling microarray detection.     

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.     

Highly sensitive and specific microRNA expression profiling using BeadArray technology

We have developed a highly sensitive, specific and reproducible method for microRNA (miRNA) expression profiling, using the 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. Currently, assay probes are designed to simultaneously analyse 735 well-annotated human miRNAs. Using this method, highly reproducible miRNA expression profiles were generated with 100–200 ng total RNA input. Furthermore, very similar expression profiles were obtained with total RNA and enriched small RNA species (R² ≥ 0.97). The method has a 3.5–4 log (10⁵–10⁹ 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 (R² = 0.85–0.90) and direct sequencing (R = 0.87–0.89). This method, in conjunction with the 96-sample array matrix should prove useful for high-throughput expression profiling of miRNAs in large numbers of tissue samples.     

Developmental microRNA expression profiling of murine embryonic orofacial tissue

BACKGROUND: Orofacial development is a multifaceted process involving precise, spatio‐temporal expression of a panoply of genes. MicroRNAs (miRNAs), the largest family of noncoding RNAs involved in gene silencing, represent critical regulators of cell and tissue differentiation. MicroRNA gene expression profiling is an effective means of acquiring novel and valuable information regarding the expression and regulation of genes, under the control of miRNA, involved in mammalian orofacial development. METHODS: To identify differentially expressed miRNAs during mammalian orofacial ontogenesis, miRNA expression profiles from gestation day (GD) ‐12, ‐13 and ‐14 murine orofacial tissue were compared utilizing miRXplore microarrays from Miltenyi Biotech. Quantitative real‐time PCR was utilized for validation of gene expression changes. Cluster analysis of the microarray data was conducted with the clValid R package and the UPGMA clustering method. Functional relationships between selected miRNAs were investigated using Ingenuity Pathway Analysis. RESULTS: Expression of over 26% of the 588 murine miRNA genes examined was detected in murine orofacial tissues from GD‐12–GD‐14. Among these expressed genes, several clusters were seen to be developmentally regulated. Differential expression of miRNAs within such clusters wereshown to target genes encoding proteins involved in cell proliferation, cell adhesion, differentiation, apoptosis and epithelial‐mesenchymal transformation, all processes critical for normal orofacial development. CONCLUSIONS: Using miRNA microarray technology, unique gene expression signatures of hundreds of miRNAs in embryonic orofacial tissue were defined. Gene targeting and functional analysis revealed that the expression of numerous protein‐encoding genes, crucial to normal orofacial ontogeny, may be regulated by specific miRNAs. Birth Defects Research (Part A), 2010. © 2010 Wiley‐Liss, Inc.     

Systematic identification of microRNA functions by combining target prediction and expression profiling

Target predictions and validations are major obstacles facing microRNA (miRNA) researchers. Animal miRNA target prediction is challenging because of limited miRNA sequence complementarity to the targets. In addition, only a small number of predicted targets have been experimentally validated and the miRNA mechanism is poorly understood. Here we present a novel algorithm for animal miRNA target prediction. The algorithm combines relevant parameters for miRNA target recognition and heuristically assigns different weights to these parameters according to their relative importance. A score calculation scheme is introduced to reflect the strength of each parameter. We also performed microarray time course experiments to identify downregulated genes due to miRNA overexpression. The computational target prediction is combined with the miRNA transfection experiment to systematically identify the gene targets of human miR-124. miR-124 overexpression led to a significant downregulation of many cell cycle related genes. This may be the result of direct suppression of a few cell growth inhibitors at the early stage of miRNA overexpression, and these targeted genes were continuously suppressed over a long period of time. Our high-throughput approach can be generalized to globally identify the targets and functions of other miRNAs.     

Identification of reference microRNAs and suitability of archived hemopoietic samples for robust microRNA expression profiling

In many cancers, including neuroblastoma, microRNA (miRNA) expression profiling of peripheral blood (PB) and bone marrow (BM) may increase understanding of the metastatic process and lead to the identification of clinically informative biomarkers. The quality of miRNAs in PB and BM samples archived in PAXgene? blood RNA tubes from large-scale clinical studies and the identity of reference miRNAs for standard reporting of data are to date unknown. In this study, we evaluated the reliability of expression profiling of 377 miRNAs using quantitative polymerase chain reaction (qPCR) in PB and BM samples (n = 90) stored at ?80 °C for up to 5 years in PAXgene? blood RNA tubes. There was no correlation with storage time and variation of expression for any single miRNA (r < 0.50). The profile of miRNAs isolated as small RNAs or co-isolated with small/large RNAs was highly correlated (r = 0.96). The mean expression of all miRNAs and the geNorm program identified miR-26a, miR-28-5p, and miR-24 as the most stable reference miRNAs. This study describes detailed methodologies for reliable miRNA isolation and profiling of PB and BM, including reference miRNAs for qPCR normalization, and demonstrates the suitability of clinical samples archived at ?80 °C into PAXgene? blood RNA tubes for miRNA expression studies.     

Real-time expression profiling of microRNA precursors in human cancer cell lines

Our previous study described a real-time PCR method to quantify microRNA (miRNA) precursors using SYBR green detection [T. D. Schmittgen, J. Jiang, Q. Liu and L. Yang (2004) Nucleic Acids Res., 32, e43]. The present study adapted the assay to a 384-well format and expanded it to include primers to 222 human miRNA precursors. TaqMan minor groove binder probes were used to discriminate nearly identical members of the let-7 family of miRNA isoforms. The miRNA precursor expression was profiled in 32 human cell lines from lung, breast, colorectal, hematologic, prostate, pancreatic, and head and neck cancers. Some miRNA precursors were expressed at similar levels in many of the cell lines, while others were differentially expressed. Clustering analysis of the miRNA precursor expression data revealed that most of the cell lines clustered into their respective tissues from which each cell line was ostensibly derived. miRNA precursor expression by PCR paralleled the mature miRNA expression by northern blotting for most of the conditions studied. Our study provides PCR primer sequences to all of the known human miRNA precursors as of December 2004 and provides a database of the miRNA precursor expression in many commonly used human cancer cell lines.     

Gene Expression Commons: an open platform for absolute gene expression profiling

Gene expression profiling using microarrays has been limited to comparisons of gene expression between small numbers of samples within individual experiments. However, the unknown and variable sensitivities of each probeset have rendered the absolute expression of any given gene nearly impossible to estimate. We have overcome this limitation by using a very large number (>10,000) of varied microarray data as a common reference, so that statistical attributes of each probeset, such as the dynamic range and threshold between low and high expression, can be reliably discovered through meta-analysis. This strategy is implemented in a web-based platform named "Gene Expression Commons" (https://gexc.stanford.edu/) which contains data of 39 distinct highly purified mouse hematopoietic stem/progenitor/differentiated cell populations covering almost the entire hematopoietic system. Since the Gene Expression Commons is designed as an open platform, investigators can explore the expression level of any gene, search by expression patterns of interest, submit their own microarray data, and design their own working models representing biological relationship among samples.     

An optimized system for expression and purification of secreted bacterial proteins

In this report, we describe an optimized system for the efficient overexpression, purification, and refolding of secreted bacterial proteins. Candidate secreted proteins were produced recombinantly in Escherichia coli as Tobacco Etch Virus protease-cleavable hexahistidine-c-myc eptiope fusion proteins. Without regard to their initial solubility, recombinant fusion proteins were extracted from whole cells with guanidium chloride, purified under denaturing conditions by immobilized metal affinity chromatography, and refolded by rapid dilution into a solution containing only Tris buffer and sodium chloride. Following concentration on the same resin under native conditions, each protein was eluted for further purification and/or characterization. Preliminary studies on a test set of 12 secreted proteins ranging in size from 13 to 130 kDa yielded between 10 and 50 mg of fusion protein per liter of induced culture at greater than 90% purity, as judged by Coomassie-stained SDS-PAGE. Of the nine proteins further purified, analytical gel filtration chromatography indicated that each was a monomer in solution and circular dichroism spectroscopy revealed that each had adopted a well-defined secondary structure. While there are many potential applications for this system, the results presented here suggest that it will be particularly useful for investigators employing structural approaches to understand protein function, as attested to by the crystal structures of three proteins purified using this methodology (B.V. Geisbrecht, B.Y. Hamaoka, B. Perman, A. Zemla, D.J. Leahy, J. Biol. Chem. 280 (2005) 17243-17250).