 microRNA (miRNA) & quantitative real-time RT-PCR (1) microRNA (miRNA) & quantitative real-time RT-PCR (2) microRNA (miRNA) & quantitative real-time RT-PCR (3) microRNA (miRNA) & quantitative real-time RT-PCR (4) microRNA (miRNA) & quantitative real-time RT-PCR (5) microRNA Reviews
microRNA
REVIEWS
Richard
J. Jackson & Nancy Standart
Sci STKE. 2007(367): re1
Department of Biochemistry, University of Cambridge, 80 Tennis Court Road, Cambridge CB2 1GA, UK Several thousand human
genes, amounting to aboutone-third of the whole genome, are potential
targetsfor regulation by the several hundred microRNAs(miRNAs) encoded
in the genome. The regulationoccurs posttranscriptionally and involves
the ~21-nucleotide miRNAinteracting with a target site in themRNAthat
generally has imperfect complementarityto the miRNA. The target sites
are almost invariablyin the 3′-untranslated region of the messenger
RNA(mRNA), often in multiple copies. Metazoan miRNAswere previously
thought to down-regulate proteinexpression by inhibiting target
mRNAtranslation atsome stage after the translation initiation step,
with-out much effect on mRNAabundance. However,recent studies have
questioned these suppositions.With some targets, an increase in the
rate of mRNAdegradation by the normal decay pathway con-tributes to the
decrease in protein expression.miRNAs can also inhibit translation
initiation, specif-ically the function of the cap-binding initiation
factor,eIF4E. Repressed target mRNAs as well as miRNAsthemselves
accumulate in cytoplasmic foci knownas P-bodies, where many enzymes
involved in mRNAdegradation are concentrated. However, P-bodiesmay also
serve as repositories for the temporary andreversible storage of
untranslated mRNA, and reduc-ing the expression (knockdown) of several
distinctP-body protein components can alleviate miRNA-mediated
repression of gene expression.
MicroRNA: past and present Yang Wang, Heidi M. Stricker, Deming Gou, Lin Liu Department of Physiological Sciences, Oklahoma State University, Stillwater, OK, 74078 Frontiers in Bioscience 12, 2316-2329, January 1, 2007 MicroRNAs (miRNAs) are
~22 nucleotide (nt) non-coding RNAs that participate in gene
regulation. MiRNAs confer their regulation at a
post-transcriptional level, where they either cleave or repress
translation of mRNAs. Over 3000 identified mature miRNAs exist in
species ranging from plants to humans, suggesting that they are ancient
players in gene regulation. A relatively small number of miRNAs
have been experimentally tested for their function. Of those
tested, functions including cell differentiation, proliferation,
apoptosis, anti-viral defense and cancer have been proposed.
Improved software programs are now able to predict the targets of
miRNAs in a more efficient manner, thus facilitating the elucidation of
miRNA function. Furthermore, methods such as real-time PCR and
microarray have been enhanced for studying miRNA expression.
Using these tools, scientists are able to discover novel functions for
miRNAs. It is possible that miRNAs will be revealed as having a
role in virtually every aspect of gene regulation. This review
guides readers through the biogenesis of miRNAs, their mechanism of
action on their target mRNAs, the functional outcomes of their action
on mRNAs and the current techniques to investigate these processes.
microRNAs
in vertebrate physiology and human disease
Over the past five years, the importance of a diverse
class of 18-24 nucleotide RNA molecules, known as microRNAs (miRNAs)
has increasingly been recognized. These highly conserved RNAs regulate
the stability and translational efficiency of complementary target
messenger RNAs. The human genome is now predicted to encode nearly
1,000 miRNAs that likely regulate at least one third of all human
transcripts. Despite rapid progress in miRNA discovery, the physiologic
functions of only a small number have been definitively established. In
this review, we discuss the principles of miRNA function that have
emerged from the studies performed thus far in vertebrates. We also
discuss known and potential roles for miRNAs in human disease states
and discuss the influence of human genetic variation on miRNA-mediated
regulation.Chang TC, Mendell JT. The McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, 21205, USA. Annu Rev Genomics Hum Genet. 2007;8: 215-239. Illuminating
the silence: understanding the structure and function of small RNAs
Tariq M. Rana NATURE REVIEWS | MOLECULAR CELL BIOLOGY VOLUME 8 | JANUARY 2007 | 23 Boyd SD. Department of Pathology, Stanford University School of Medicine, Stanford, CA 94305-2297, USA. Lab Invest. 2008 Jun;88(6): 569-578 MicroRNAs are a class of
recently discovered small RNA molecules that regulate other
genes in the human genome. Studies in human cells and model organisms
have begun to reveal the mechanisms of microRNA
activity, and the wide range of normal physiological
functions they influence. Their alteration in pathologic statesfrom
cancer to cardiovascular disease is also increasingly clear. A review
of current evidence for the role of these molecules in
human health and disease will be helpful to
pathologists and medical researchers as the fascinating story of these
small regulators continues to unfold.
The regulation of genes andgenomes by small RNAsVictor Ambros & Xuemei Chen Development 134, 1635-1641(2007) A recent Keystone
Symposium on ‘MicroRNAs and siRNAs:Biological Functions and Mechanisms’
was organized by DavidBartel and Shiv Grewal (and was held in
conjunction with ‘RNAifor Target Validation and as a Therapeutic’,
organized byStephen Friend and John Maraganore). The ‘MicroRNAs
andsiRNAs’ meeting brought together scientists working on
diversebiological aspects of small regulatory RNAs, includingmicroRNAs,
small interfering RNAs (siRNAs) and Piwi-interactingRNAs (piRNAs and
rasiRNAs). Among the themes discussed werethe diversity of small
regulatory RNAs and their developmentalfunctions, their biogenesis, the
identification of their regulatorytargets, their mechanisms of action,
and their roles in theelaboration of multicellular complexity.
MicroRNAs
in Gene Regulation: When the Smallest Governs It All
Encoded by the genome of most eukaryotes examined so far,
microRNAs (miRNAs) are small ~21-nucleotide (nt) noncoding RNAs
(ncRNAs) derived from a biosynthetic cascade involving sequential
processing steps executed by the ribonucleases (RNases) III Drosha and
Dicer. Following their recent identification, miRNAs have rapidly taken
the center stage as key regulators of gene expression. In this review,
we will summarize our current knowledge of the miRNA biosynthetic
pathway and its protein components, as well as the processes it
regulates via miRNAs, which are known to exert a variety of biological
functions in eukaryotes. Although the relative importance of miRNAs
remains to be fully appreciated, deregulated protein expression
resulting from either dysfunctional miRNA biogenesis or abnormal
miRNA-based gene regulation may represent a key etiologic factor in
several, as yet unidentified, diseases. Hence is our need to better
understand the complexity of the basic mechanisms underlying miRNA
biogenesis and function.Ouellet DL, Perron MP, Gobeil LA, Plante P, Provost P. J Biomed Biotechnol. 2006;2006(4): 69616. Clustering
and conservation patterns of human microRNAs
Altuvia Y, Landgraf P, Lithwick G, Elefant N, Pfeffer S, Aravin A, Brownstein MJ, Tuschl T, Margalit H. Department of Molecular Genetics and Biotechnology, Faculty of Medicine, The Hebrew University PO Box 12272, Jerusalem 91120, Israel. Nucleic Acids Res. 2005 May 12;33(8): 2697-2706 microRNA normalisation in real-time qRT-PCR Data normalisation in microRNA experiments using qRT-PCR is a new challenge in gene quantification analysis. The reliability of any relative RT-PCR experiment can be improved by including an invariant endogenous control (reference gene) in the assay to correct for sample to sample variations in the qRT-PCR efficiency and errors in sample quantification. A biologically meaningful reporting of target mRNA copy numbers requires accurate and relevant normalisation to some standard and is strongly recommended in microRNA qRT-PCR. => But the
quality of normalized quantitative expression data cannot be better
than the quality of the normalizer itself. Any variation in the normalizer will obscure real changes and produce artifactual changes. Real-time RT-PCR-specific errors in the quantification of microRNA transcripts are easily compounded with any variation in the amount of starting material between the samples, e.g. caused by sample-to-sample variation and cDNA sample loading variation. This is especially relevant when the samples have been obtained from different individuals, different tissues and different time courses, and will result in the misinterpretation of the derived expression profile of the target genes. => Therefore, normalisation of target gene expression levels must be performed to compensate intra- and inter-kinetic RT-PCR variations (sample-to-sample & run-to-run variations). Data normalisation can be carried out against an endogenous unregulated reference gene transcript or against total cellular DNA or RNA content (molecules/g total DNA/RNA and concentrations/g total DNA/RNA). Normalisation according the total cellular RNA content is increasingly used, but little is known about the total RNA content of cells or even about the microRNA or mRNA concentrations. The content per cell or per gram tissue may vary in different tissues in vivo, in cell culture (in vitro), between individuals and under different experimental conditions. Nevertheless, it has been shown that normalisation to total cellular RNA is the least unreliable method. It requires an accurate quantification of the isolated total RNA or mRNA or microRNA fraction by optical density at 260 nm, Lab-on-Chip capillary electrophoresis instruments, or Ribogreen RNA Quantification Kit. To normalize the absolute amount according to a single reference gene (or better a set of multiple stable reference genes), further sets of kinetic PCR reactions has to be performed for the invariant endogenous control(s) on all experimental samples and the relative abundance values are calculated for internal control as well as for the target gene. For each target gene sample, the relative abundance value obtained is divided by the value derived from the control sequence in the corresponding target gene. The normalized values for different biological samples can then directly be compared. The workflow:
Molecular Cancer 2006, 5:29 E Bandrés*1, E Cubedo1, X Agirre2, R Malumbres1, R Zárate1, N Ramirez1, A Abajo1, A Navarro3, I Moreno4, M Monzó3 and J García-Foncillas1 MicroRNAs (miRNAs)
are short non-coding RNA molecules playing regulatory roles by
repressing translation or
cleaving RNA transcripts. Although the number of verified human miRNA
is still expanding, only few
have been functionally described. However, emerging evidences suggest
the potential
involvement of altered regulation of miRNA in pathogenesis of cancers
and these genes are thought to
function as both tumours suppressor and oncogenes. In our study, we
examined by Real-Time PCR the expression of 156 mature miRNA in
colorectal cancer. The analysis
by several bioinformatics algorithms of colorectal tumours and adjacent
nonneoplastic tissues from patients
and colorectal cancer cell lines allowed identifying a group of 13 miRNA whose
expression is significantly altered in this tumor. The most
significantly deregulated miRNA being miR-31,
miR-96, miR-133b, miR-135b, miR-145, and miR-183. In addition, the expression level of
miR-31 was correlated with the stage of CRC tumor. Our results suggest
that miRNA expression profile could have relevance to the biological
and clinical
behavior of colorectal neoplasia.
Proper normalization is a critical but often an
underappreciated aspect of quantitative gene expression
analysis. This study describes the identification and
characterization of appropriate reference RNA targets for the
normalization of microRNA (miRNA) quantitative RT-PCR
data. miRNA microarray data from dozens of normal and
disease human tissues revealed ubiquitous and stably expressed normalization
candidates for evaluation by qRT-PCR. miR-191 and miR-103, among others,
were found to be highly consistent in their expression across 13 normal
tissues and five pair of distinct tumor/normal
adjacent tissues. These miRNAs were statistically
superior to the most commonly used reference RNAs used in miRNA
qRT-PCR experiments, such as 5S rRNA, U6 snRNA, or total RNA. The most stable
normalizers were also highly conserved across flash-frozen and formalin-fixed
paraffin-embedded lung cancer tumor/NAT sample sets, resulting in the
confirmation of one well-documented oncomir (let-7a), as well as the identification
of novel oncomirs. These findings constitute the first report describing
the rigorous normalization of miRNA qRT-PCR data and have important implications
for proper experimental design and accurate data interpretation.
Identification of suitable endogenous control genes for microRNA gene expression analysis in human breast cancer. Davoren PA, McNeill RE, Lowery AJ, Kerin MJ, Miller N. Department of Surgery, National University of Ireland, Galway, Ireland. BMC Mol Biol. 2008 9: 76. 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.
High-throughput stem-loop RT-qPCR miRNA expression profiling using minute amounts of input RNA. Mestdagh P, Feys T, Bernard N, Guenther S, Chen C, Speleman F, Vandesompele J. Center for Medical Genetics, Ghent University Hospital, Ghent, Belgium. Nucleic Acids Res. 2008 Dec;36(21): e143 MicroRNAs (miRNAs) are
an emerging class of small non-coding RNAs implicated in a wide
variety of cellular processes. Research in this field is accelerating,
and the growing number of miRNAs emphasizes the need
for high-throughput and sensitive detection methods.
Here we present the successful evaluation of the Megaplex
reverse transcription format of the stem-loop primer-based real-time quantitative
polymerase chain reaction (RT-qPCR) approach to quantify miRNA expression.
The Megaplex reaction provides simultaneous reverse transcription of 450
mature miRNAs, ensuring high-throughput detection. Further, the
introduction of a complementary DNA pre-amplification
step significantly reduces the amount of input RNA
needed, even down to single-cell level. To evaluate possible pre-amplification
bias, we compared the expression of 384 miRNAs in three different
cancer cell lines with Megaplex RT, with or without an additional pre-amplification
step. The normalized Cq values of all three sample pairs showed a
good correlation with maintenance of differential miRNA expression
between the cell lines. Moreover, pre-amplification
using 10 ng of input RNA enabled the detection of
miRNAs that were undetectable when using Megaplex alone with 400 ng of
input RNA. The high specificity of RT-qPCR together with a superior sensitivity
makes this approach the method of choice for high-throughput miRNA expression
profiling.
Facile
means for quantifying microRNA expression by real-time PCR.
Shi R, Chiang VL. Biotechniques. 2005 39(4): 519-525. North Carolina State University, Raleigh, NC 27695-7247, USA.  MicroRNAs (miRNAs) are 20-24 nucleotide RNAs that are predicted to play regulatory roles in animals and plants. Here we report a simple and sensitive real-time PCR method for quantifying the expression of plant miRNAs. Total RNA, including miRNAs, was polyadenylated and reverse-transcribed with a poly(T) adapter into cDNAs for real-time PCR using the miRNA-specific forward primer and the sequence complementary to the poly(T) adapter as the reverse primer. Several Arabidopsis miRNA sequences were tested using SYBR Green reagent, demonstrating that this method, using as little as 100 pg total RNA, could readily discriminate the expression of miRNAs having asfew as one nucleotide sequence difference. This method also revealed miRNA tissue-specific expression patterns that cannot be resolved by Northern blot analysis and may therefore be widely useful for characterizing miRNA expression in plants as well as in animals. A
single-molecule method for the quantitation of microRNA gene expression.
Neely LA, Patel S, Garver J, Gallo M, Hackett M, McLaughlin S, Nadel M, Harris J, Gullans S, Rooke J. Nat Methods. 2006 (1): 41-46 US Genomics, 12 Gill Street, Suite 4700, Woburn, Massachusetts 01801, USA MicroRNAs (miRNA) are short endogenous noncoding RNA molecules that regulate fundamental cellular processes such as cell differentiation, cell proliferation and apoptosis through modulation of gene expression. Critical to understanding the role of miRNAs in this regulation is a method to rapidly and accurately quantitate miRNA gene expression. Existing methods lack sensitivity, specificity and typically require upfront enrichment, ligation and/or amplification steps. The Direct miRNA assay hybridizes two spectrally distinguishable fluorescent locked nucleic acid (LNA)-DNA oligonucleotide probes to the miRNA of interest, and then tagged molecules are directly counted on a single-molecule detection instrument. In this study, we show the assay is sensitive to femtomolar concentrations of miRNA (500 fM), has a three-log linear dynamic range and is capable of distinguishing among miRNA family members. Using this technology, we quantified expression of 45 human miRNAs within 16 different tissues, yielding a quantitative differential expression profile that correlates and expands upon published results. Endogenous Controls for Real-Time Quantitation of miRNA Using TaqMan® MicroRNA Assays. Applied Biosystems - Application Note MicroRNAs
(miRNAs) are small noncoding RNAs whose function has been implicated in
a wide range of fundamental cellular processes including cell
proliferation, cell differentiation, and cell death. Quantitation of
miRNA gene expression levels has become an essential step in
understanding these mechanisms, and has shown great promise in
identifying effective biomarkers correlative with human disease1,2.
Applied Biosystems has developed an extensive set of TaqMan®
MicroRNA Assays, novel stem-loop RT and real-time PCR assays, for the
quantitation of mature miRNA expression3. TaqMan® Assays are the
ideal choice for these applications because of their unsurpassed
sensitivity, specificity, and wide dynamic range. Additionally, far
less input material is required compared to microarrays and other
alternative technologies. When performing these experiments,variation
in the amount of starting material, sample collection, RNA preparation
and quality, and reverse transcription (RT) efficiency can contribute
to quantification errors. Normalization to endogenous control genes is
currently the most accurate method to correct for potential RNA input
or RT efficiency biases. Careful selection of an appropriate control or
set of controls is extremely important as significant variation has
been observed between samples, even for the most commonly used
housekeeping genes, including ACTB (ß-Actin) and GAPDH4. An ideal
endogenous control generally demonstrates gene expression that is
relatively constant and highly abundant across tissues and cell types.
However, one must still validate the chosen endogenous control or set
of controls for the target cell, tissue, or treatment5, as no single
control can serveas a universal endogenous control for
all experimental conditions. When considering endogenous controls
suitable for use with TaqMan MicroRNA Assays, it is important that they
share similar properties, such as RNA stability and size, and are
amenable to the miRNA assay design. A number of reports indicate that
other classes of small non-coding RNAs (ncRNAs) are expressed both
abundantly and stably, making them good endogenous control candidates.
We have performed a systematic study of a set of human ncRNA species
ranging in size from 45 to 200 nucleotides, including transfer RNA
(tRNA), small nuclear RNA (snRNA) and small nucleolar RNA (snoRNA) 6
across a relatively wide variety of tissues and cell lines to determine
their suitability as endogenous controls when quantitating miRNA
expression levels using real-time PCR methods.
microRNA normalisation of microRNA arrays Quality
assessment and data analysis for microRNA expression arrays.
MicroRNAs are small (approximately 22 nt) RNAs that
regulate gene expression and play important roles in both normal and
disease physiology. The use of microarrays for global characterization
of microRNA expression is becoming increasingly popular and has the
potential to be a widely used and valuable research tool. However,
microarray profiling of microRNA expression raises a number of data
analytic challenges that must be addressed in order to obtain reliable
results. We introduce here a universal reference microRNA reagent set
as well as a series of nonhuman spiked-in synthetic microRNA controls,
and demonstrate their use for quality control and between-array
normalization of microRNA expression data. We also introduce diagnostic
plots designed to assess and compare various normalization methods. We
anticipate that the reagents and analytic approach presented here will
be useful for improving the reliability of microRNA microarray
experiments.Sarkar D, Parkin R, Wyman S, Bendoraite A, Sather C, Delrow J, Godwin AK, Drescher C, Huber W, Gentleman R, Tewari M. Fred Hutchinson Cancer Research Center, 1100 Fairview Ave N, Seattle, WA 98109, USA. Nucleic Acids Res. 2009 Feb;37(2):e17 A
comparison of normalization techniques for microRNA microarray data.
Rao Y, Lee Y, Jarjoura D, Ruppert AS, Liu CG, Hsu JC, Hagan JP. The Ohio State University, USA. Stat Appl Genet Mol Biol. 2008;7(1): Article 22 Normalization of
expression levels applied to microarray data can help in reducing
measurement error. Different methods, including cyclic loess, quantile
normalization and median or mean normalization, have been utilized to
normalize microarray data. Although there is considerable literature
regarding normalization techniques for mRNA microarray data, there are
no publications comparing normalization techniques for microRNA (miRNA)
microarray data, which are subject to similar sources of measurement
error. In this paper, we compare the performance of cyclic loess,
quantile normalization, median normalization and no
normalization for a single-color microRNA microarray dataset. We show
that the quantile normalization method works best in reducing
differences in miRNA expression values for replicate tissue samples. By
showing that the total mean squared error are lowest across almost all
36 investigated tissue samples, we are assured that the bias correction
provided by quantile normalization is not outweighed by additional
error variance that can arise from a more complex normalization method.
Furthermore, we show that quantile normalization does not achieve these
results by compression of scale.
A
sensitive array for microRNA expression profiling (miChip) based on
locked nucleic acids (LNA).
MicroRNAs represent a class of short (approximately 22
nt), noncoding regulatory RNAs involved in development,
differentiation, and metabolism. We describe a novel
microarray platform for genome-wide profiling of mature miRNAs (miChip)
using locked nucleic acid (LNA)-modified capture
probes. The biophysical properties of LNA were
exploited to design probe sets for uniform, high-affinity hybridizations
yielding highly accurate signals able to discriminate between single
nucleotide differences and, hence, between closely related miRNA family
members. The superior detection sensitivity
eliminates the need for RNA size selection and/or
amplification. MiChip will greatly simplify miRNA expression profiling
of biological and clinical samples.
Castoldi M, Schmidt S, Benes V, Noerholm M, Kulozik AE, Hentze MW, Muckenthaler MU. Department of Pediatric Oncology, Hematology and Immunology, University of Heidelberg, Germany. RNA. 2006 12(5): 913-920 miChip:
an array-based method for microRNA expression profiling using locked
nucleic acid capture probes.
Mirco Castoldi, Sabine Schmidt, Vladimir Benes, Matthias W Hentze & Martina U Muckenthaler Nature Protocols 3, - 321 - 329 (2008) MicroRNAs (miRNAs)
represent a class of short (22 nt) noncoding RNAs that control gene
expression post-transcriptionally. Microarray technology is frequently
applied to monitor miRNA expression levels but is challenged by (i) the
short length of miRNAs that offers little sequence for appending
detection molecules; (ii) low copy number of some miRNA; and (iii) a
wide range of predicted melting temperatures (Tm) versus their DNA
complementary sequences. We recently developed a microarray platform
for genome-wide profiling of miRNAs (miChip) by applying locked nucleic
acid (LNA)-modified capture probes. Here, we provide detailed protocols
for the generation of the miChip microarray platform, the preparation
and fluorescent labeling of small RNA containing total RNA, its
hybridization to the immobilized LNA-modified capture probes and the
post-hybridization handling of the microarray. Starting from the intact
tissue sample, the entire protocol takes approx3 d to yield highly
accurate and sensitive data about miRNA expression levels.
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