MicroRNAs (miRNAs) are small RNAs (∼22 nucleotides long) that post-transcriptionally regulate the expression of thousands of genes in a broad range of organisms.
miRNA expression profiling is useful for identifying miRNAs that are important in the regulation of a range of processes, including organismal development, tissue differentiation and disease pathology.
miRNAs show promise as biomarkers for various diseases.
miRNAs are more stable than mRNAs in many specimen types and are more readily measured than proteins. However, sample type, processing and RNA extraction methods can have a substantial impact on the results of miRNA profiling, and therefore quality and quantity assessment is recommended.
Biogenesis of miRNAs occurs through multiple steps and includes the intermediate primary miRNA and precursor miRNA forms, as well as post-transcriptional nucleotide additions and deletions, leading to 'isomiRs'. Choice of platform and analysis in miRNA profiling should include consideration of the need to distinguish between different forms of miRNAs.
Three main approaches are currently well established for miRNA profiling: quantitative reverse transcription PCR (qRT-PCR), hybridization-based methods (for example, DNA microarrays) and high-throughput sequencing (that is, RNA sequencing). The optimal choice of platform depends on the specific experimental goals.
Analysis of miRNA-profiling data typically includes data processing, data quality assessment, data normalization and calculation of differential expression. The optimal approach to data analysis depends on the platform selected and the nature of the experiment.
MicroRNAs (miRNAs) are small RNAs that post-transcriptionally regulate the expression of thousands of genes in a broad range of organisms in both normal physiological contexts and in disease contexts. miRNA expression profiling is gaining popularity because miRNAs, as key regulators in gene expression networks, can influence many biological processes and also show promise as biomarkers for disease. Technological advances have spawned a multitude of platforms for miRNA profiling, and an understanding of the strengths and pitfalls of different approaches can aid in their effective use. Here, we review the major considerations for carrying out and interpreting results of miRNA-profiling studies.
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We thank J. Tait for helpful comments on the manuscript. We acknowledge the many authors whose work could not be cited owing to space constraints. M.T. acknowledges generous support from a Damon Runyon-Rachleff Innovation Award, a Stand Up To Cancer Innovative Research Grant (Innovative Research Grant SU2C-AACR-IRG1109), a Prostate Cancer Foundation Creativity Award and funding from the US National Institutes of Health (R01DK085714; P50 CA83636; 5 P30 CA015704; P50 CA97186) and Department of Defense (PC074012; OC080159).
Muneesh Tewari is a named inventor on patent applications relating to circulating microRNA. He has served on the scientific advisory boards of Wafergen, Inc. and Combimatrix, Inc. within the last three years and has had a past research collaboration with scientists at Nanostring, Inc. Neither Colin C. Pritchard nor Heather H. Cheng declares any competing financial interests.
- Primary miRNA
(pri-miRNA). The initial transcription product of microRNA (miRNA) genes. Pri-miRNAs are generally >100 nucleotides long (frequently a few kilobases long) and may contain one or more miRNA stem–loops that are processed by the miRNA biogenesis machinery.
- Precursor miRNA
(pre-miRNA). A hairpin precursor of microRNA (miRNA) that is formed by the cleavage of the primary miRNA transcript by the Drosha–DGCR8 protein complex. Precursor miRNAs are typically ∼70–100 nucleotides long.
A comprehensive database of microRNA sequences and nomenclature from plant and animal species.
- Pre-analytic variables
Variables that occur before sample assay. For example, the time elapsed between when a blood sample is drawn from the patient and when it is processed by the laboratory is a pre-analytic variable.
(AGO). These proteins are the central components of RNA-silencing mechanisms. They provide the platform for target–mRNA recognition by short guide RNA strands (for example, miRNAs) and, in the case of AGO2 (in humans), the catalytic activity for mRNA cleavage.
- Seed region
The six or seven nucleotides between the nucleotides positions 2–7 or 2–8 of the microRNA (miRNA) 5′ end that determine, in large measure, miRNA target selection by virtue of sequence complementarity to the miRNA seed region.
- Laser capture microdissection
(LCM). A method for capturing specific cells of interest from heterogeneous tissue samples. Cells for capture are chosen by the operator using a microscope and are cut out from the tissue using a laser. The isolated cells can be used for various analyses, including miRNA profiling.
- Splinted ligation
A method of labelling in which ligation of an oligonucleotide to the 3′ end of a microRNA is facilitated by a 'bridge' oligonucleotide that hybridizes to both the 3′ end of the miRNA and the 5 end of the oligonucleotide to be ligated.
- Microfluidic cards
Typically, disposable cards in which fluid pressure is used to move input samples and reagents through microfabricated channels into specific locations (akin to 'wells') with high precision, permitting highly parallel and low-sample-volume, real-time PCR.
- Locked nucleic acids
(LNAs). A class of RNA analogues in which the 2′ oxygen and the 4′ carbon positions in the ribose ring are connected or 'locked' to create increased thermal stability relative to DNA or RNA when they are complexed with complementary DNA or RNA.
- Next-generation sequencing
(NGS). Any of several technologies that sequence large numbers of DNA fragments in parallel, producing millions or billions of short reads in a single run of an automated sequencer.
- PIWI-interacting RNAs
(piRNAs). Small (23–32 nt) RNAs that are associated with PIWI clade proteins of the Argonaute family. They ensure genome stability in the germline of flies, mice and zebrafish by silencing transposable and repetitive elements.
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Pritchard, C., Cheng, H. & Tewari, M. MicroRNA profiling: approaches and considerations. Nat Rev Genet 13, 358–369 (2012). https://doi.org/10.1038/nrg3198
Identification of microRNAs associated with human fragile X syndrome using next-generation sequencing
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