- Methodology article
- Open Access
miR-Q: a novel quantitative RT-PCR approach for the expression profiling of small RNA molecules such as miRNAs in a complex sample
© Sharbati-Tehrani et al; licensee BioMed Central Ltd. 2008
- Received: 20 August 2007
- Accepted: 10 April 2008
- Published: 10 April 2008
MicroRNAs (miRNAs) are small endogenous non-coding interfering RNA molecules regarded as major regulators in eukaryotic gene expression. Different methods are employed for miRNA expression profiling. For a better understanding of their role in essential biological processes, convenient methods for differential miRNA expression analysis are required.
Here, we present the miR-Q assay as a highly sensitive quantitative reverse transcription PCR (qRT-PCR) for expression analysis of small RNAs such as miRNA molecules. It shows a high dynamic range of 6 to 8 orders of magnitude comprising a sensitivity of up to 0.2 fM miRNA, which corresponds to single copies per cell. There is nearly no cross reaction among closely-related miRNA family members, which points to the high specificity of the assays. Using this approach, we quantified the expression of let-7b in different human cell lines as well as miR-145 and miR-21 expression in porcine intestinal samples.
miR-Q is a cost-effective and highly specific approach, which neither requires the use of fluorochromic probes, nor Locked Nucleic Acid (LNA)-modified oligonucleotides. Moreover, it provides a remarkable increase in specificity and simplified detection of small RNAs.
- miRNA Expression
- Reverse Transcription Reaction
- Ileal Sample
- miRNA Molecule
- miRNA Concentration
RNA interference (RNAi) is an evolutionarily-conserved process that modulates gene expression. Recently, miRNA molecules have been described as playing a major role among non-coding small interfering RNAs. MiRNAs represent an abundant and highly conserved family of endogenous single-stranded small RNA molecules of approximately 20–25 nucleotides in length. The high evolutionary conservation of miRNAs from distantly related species indicates their role in various crucial biological processes. Recent studies have demonstrated that miRNAs act as major regulators of developmental timing, cellular differentiation, apoptosis, and signalling pathways . In plants, RNAi has also been described as a phenomenon called post-transcriptional gene silencing . Within this context, miRNAs posses similar functions in plants such as organ development, signal transduction, and response to environmental stress .
Animal miRNAs derive from long endogenous primary transcripts with a local stem-loop structure, which is successively cleaved by cellular RNases to build the mature miRNA . One of the strands interacts with the RNA-induced silencing complex (RISC) and binds to a target site, which is located in the 3' UTR of the related mRNA. Most animal miRNAs bind to their targets with incomplete complementarity , while their regulatory impact is mainly based on the reduction of translation efficiency, rather than on enhanced mRNA degradation .
Due to the enormous regulative importance of miRNAs, research on miRNA expression analysis has recently increased. Although miRNAs represent a relatively abundant class of transcripts, their expression levels vary greatly among species and tissues . Various methods are employed for detection and differential expression analysis of miRNAs in biological samples. Initial miRNA expression studies were performed by means of Northern blot analysis . This method is well-established but is very laborious and highly limited, regarding sample throughputs. Recently, Microarrays have been used for genome-wide miRNA profiling based on different processing chemistries [8–10]. Microarrays provide a robust platform for fast screening and comparative expression analysis of miRNAs, but are limited, regarding accurate quantification of gene expression and need high quantities of RNA. Thus, less abundant miRNAs often escape detection by technologies such as cloning, Northern blot analysis and Microarray. A single-molecule method for quantification of miRNA expression was introduced by Neely et al. . Although this technique represents a modern alternative, it has a detection limit of 500 fM. Additionally, the method is utilised by a cost-intensive device, which may be unaffordable for many research groups.
A highly convenient and reliable method for differential gene expression analysis is considered to be qRT-PCR , which exhibits high sensitivity and target specificity. It is 1000-fold more sensitive than methods that are based on hybridisation  and can even detect a few target copies . However, the small size of miRNAs requires substantial modification of this method because ordinary PCR primers are usually the same size as the small RNA molecules being analysed. The first miRNA real-time PCR approach was based on detection and quantification of miRNA precursors [15, 16]. However, other studies have shown that the cellular steady-state level of miRNA precursors does not correspond to cellular concentrations of mature miRNAs [17, 18]. Chen and colleagues  have developed a quantitative stem-loop RT-PCR for detection of mature miRNAs that is based on TaqMan assays. Their assay displays high sensitivity and dynamic range and allows for discrimination between members of miRNA families such as let-7. This assay and a few others have recently become commercialised and are rather costly. Raymond et al.  have designed a SYBR Green real-time RT-PCR for detection of mature miRNA molecules using LNA-modified primers. Most of their developed assays are described as being sensitive to femtomolar concentrations. However, the performance and sensitivity of 70% of the analysed assays strictly depend on the use of LNA-modified primers, which increases the costs of this approach.
Due to the rising general interest in miRNA expression and their regulative impact on important biological processes, more sensitive and competitive alternatives applications are in demand. On this account, we have developed a new cost-effective, highly sensitive, and reliable qRT-PCR for quantification of small RNA molecules such as miRNAs. The method called miR-Q is based on primer extension, followed by a novel quantitative PCR (qPCR) approach that is carried out using three DNA-oligonucleotides. The assay exhibits high sensitivity, linearity, and discriminative power without the use of complex fluorochromic probes or LNA-modified oligonucleotides.
General assay design
The final detection and quantification of template miRNA molecules are performed by real-time acquisition of the SYBR Green fluorescence, utilising a calibration curve.
Assay validation, sensitivity, and dynamic range
Initial assays were performed with miRNA-specific oligonucleotides possessing an overlap of 6 bases with the RT6-miR-x, which was used for the initial primer extension reaction to convert and elongate the miRNA molecule in cDNA. Although PCR reactions were performed under stringent conditions, the application of oligonucleotides with 6 overlapping bases produced high background from 30 cycles onwards. Hereafter, we evaluated the use of short-miR-x-rev molecules, which featured basically no or, at most, 3 overlapping bases. The use of shortened miRNA-specific reverse oligonucleotides resulted in a higher sensitivity of all assays and a loss of background over 40 cycles.
Oligonucleotides used in this study. The assay-specific annealing temperatures are given in the bottom right column. Differing bases among members of the let-7 family are indicated in red. Binding sequences for universal primers are underlined and the miRNA specific sequences are indicated in bold.
Synthetic miRNA molecules and DNA-oligonucleotides for RT and qPCR
Sequence (5' to 3')
Tanopt of miR-Q assays [°C]
uga ggu agu agg uug uau agu u
uga ggu agu agg uug ugu ggu u
uga ggu agu agg uug uau ggu u
uag cag cac gua aau auu ggc g
uag cuu auc aga cug aug uug a
auc aca uug cca ggg auu acc
uuc aca gug gcu aag uuc cgc
uaa cac ugu cug gua aag aug g
guc cag uuu ucc cag gaa ucc cuu
uaa uac ugc cgg gua aug aug g
tgt cag gca acc gta ttc acc gtg agt ggt aac tat
tgt cag gca acc gta ttc acc gtg agt ggt aac cac
tgt cag gca acc gta ttc acc gtg agt ggt aac cat
tgt cag gca acc gta ttc acc gtg agt ggt cgc caa
tgt cag gca acc gta ttc acc gtg agt ggt tca aca
tgt cag gca acc gta ttc acc gtg agt gct ggt aat
tgt cag gca acc gta ttc acc gtg agt ggt gcg gaa
tgt cag gca acc gta ttc acc gtg agt ggt cca tct
tgt cag gca acc gta ttc acc gtg agt ggt aag gga
tgt cag gca acc gta ttc acc gtg agt ggt cca tca
cgt cag atg tcc gag tag agg ggg aac ggc gtg agg tag tag gtt gta ta
cgt cag atg tcc gag tag agg ggg aac ggc gtg agg tag tag gtt gtg tg
cgt cag atg tcc gag tag agg ggg aac ggc gtg agg tag tag gtt gta tg
cgt cag atg tcc gag tag agg ggg aac ggc gta gca gca cgt aaa ta
cgt cag atg tcc gag tag agg ggg aac ggc gta gct tat cag act ga
cgt cag atg tcc gag tag agg ggg aac ggc gat cac att gcc agg g
cgt cag atg tcc gag tag agg ggg aac ggc gtt cac agt ggc taa g
cgt cag atg tcc gag tag agg ggg aac ggc gta aca ctg tct ggt aaa g
cgt cag atg tcc gag tag agg ggg aac ggc ggt cca gtt ttc cca gga a
cgt cag atg tcc gag tag agg ggg aac ggc gta ata ctg ccg ggt aa
5S rRNA fw
gcc cga tct cgt ctg atc t
5S rRNA rev
agc cta cag cac ccg gta tt
tgt cag gca acc gta ttc acc
cgt cag atg tcc gag tag agg
Assay specificity and cross reaction between let-7 family members
Cross reaction of the miR-Q let-7 assays at different target concentrations. The percentage of cross reaction values was calculated between assay-specific and unspecific miRNA targets, while concentration of assay-specific molecules represented the full value.
2 nM let-7a
2 nM let-7b
2 nM let-7c
200 pM let-7a
200 pM let-7b
200 pM let-7c
20 pM let-7a
20 pM let-7b
20 pM let-7c
2 pM let-7a
2 pM let-7b
2 pM let-7c
200 fM let-7a
200 fM let-7b
200 fM let-7c
20 fM let-7a
20 fM let-7b
20 fM let-7c
2 fM let-7a
2 fM let-7b
2 fM let-7c
Comparison of the miR-Q approach with a commercial qRT-PCR detection kit
Expression of miR-145 and miR-21 in porcine intestinal samples
Expression of miR-145 and miR-21 in analysed samples was first evaluated by performing initial miRNA-Microarray experiments (data not shown). Subsequent miR-Q analysis demonstrated that both miR-145 and miR-21 were differentially expressed in the jejunal and ileal samples of all ten piglets (Figure 6). There was an obvious individual variance in expression of both miRNAs among the studied subjects. However, miR-145 expression levels in the two different intestinal loci showed similar tendencies. As shown in Figure 6A and 6B, animal f exhibited the highest miR-145 expression among the ten samples, both in jejunum and ileum. Interestingly, both intestinal loci of this animal featured the same miR-145:5S rRNA value, which was twice as high as the lowest expression ratios among the group.
Differential miR-21 expression was also observed among jejunal or ileal samples, respectively. However, there was no distinct concordance of miR-21 expression in the two intestinal loci compared with miR-145 expression. The highest miR-21:5S rRNA expression ratios within the ileal samples were about 2.5 times higher compared with the lowest values, while the highest expression value among the jejunal samples turned out to be 3.5 times higher (Figure 6C and 6D).
Expression values of miR-21 were enhanced in both the ileum and jejunum of all analysed animals compared with miR-145. In ileal samples, a 30-fold higher miR-21 expression value was measured compared with miR-145, while the average values in jejunum were enhanced 40-fold.
The expression of various protein coding genes, their role in development or disease, and their regulation become more and more deciphered. Recently, the small non-coding miRNAs have been highlighted as major modulators of eukaryotic gene expression. It is suggested that up to 30% of human genes may be under the control of miRNAs . MiRNAs are involved in essential developmental processes such as timing, embryogenesis, organogenesis, growth control, and programmed cell death; but they also play a role in human disease, in particular cancer . An increasing number of studies describe aberrant miRNA expression in cancerous tissue. For example, miR-21 was reported as being highly overexpressed in human glioblastoma tumour tissue  and in breast tumours, pointing to its function as an oncogene . Other miRNAs such as miR-143 or miR-145 are downregulated in colon carcinomas  or in human breast cancer . In many cases, detection of miRNAs and comparative miRNA expression analysis are performed using methods based on probe hybridisation, lacking any amplification step (Northern blot and Microarray). Despite these methods being well established, they are rather limited regarding sensitivity and accurate quantification. Otherwise, due to its high level of sensitivity, accuracy, and practical ease, qRT-PCR is accepted as being a powerful technique in comparative expression analysis in life sciences and medicine . In consideration of the aforementioned facts, quantification of miRNA expression by real-time PCR (e.g. as a diagnostic tool in cancer research) is the method of choice. However, few qRT-PCR approaches are adapted to small-sized miRNAs [18, 24] and are currently made available by companies. Our miR-Q approach represents a new, alternative method, which exhibits advanced discriminative power and sensitivity. It is based on primer extension, followed by amplification and quantification of the corresponding cDNA, based on the SYBR Green intercalating chemistry. To establish a novel PCR approach for RNA molecules (< 30 nt) such as miRNAs, three different oligonucleotides were simultaneously employed, one miRNA-specific molecule (short-miR-x-rev) for the detection of the corresponding cDNA and two universal primers for the exponential amplification of the product.
We established the described 10 miR-Q assays by randomly choosing miRNAs of interest. Since all of the validated assays proved to be highly sensitive and specific and because of the nature of the overhang sequences, we conclude that these sequence parts can be utilised for ubiquitous detection of small RNA molecule. The linearity and sensitivity of the proposed approach apparently correlates with the length of the detected miRNA molecule. According to miRBase sequence data , miR-145 has an extended length of 24 nt, displaying the longest molecule among the miRNAs in this study. Consequently, the most sensitive assay among the validated ten assays (linearity over 8 orders of magnitude) turned out to be the miR-145 assay, featuring an advanced sensitivity limit. Moreover, most of the analysed miRNA molecules with a length of 22 nt exhibited enhanced assay linearity, compared with shorter molecules. Currently, 475 human miRNAs are published in miRBase (Release 9.2). Based on these data, 67% of known human miRNAs are at least 22 nt in length. Accordingly, it can be suggested that the general detection limit of the miR-Q approach would be about 1 fM miRNA. This value may even be underestimated, since 27% of known human miRNAs are longer than 22 nt. Different tissues or cell types may contain diverse amounts of RNA. But according to our calculations, a general detection limit of 2 fM correlates with less than 5 measured copies of miRNA molecules per cell. Hence, the proposed approach offers a cost-effective alternative, exhibiting improved sensitivity and specificity compared with other existing methods without using fluorochromic hybridisation probes or LNA-modified oligonucleotides [18, 19]. Recently, qRT-PCR protocols for profiling of mature miRNAs have been introduced where the entire miRNA population contained in samples is reverse transcribed at the same time (Invitrogen or Qiagen). The application of specific RT primers, however, provides an increased specificity of the assays and reduces cross reaction between closely related miRNA molecules. The gain of higher sensitivity over existing assays is also underlined by comparison of our let-7b assay with a purchasable kit. While the mirVana™ qRT-PCR miRNA Detection Kit for let-7b provided lower detection limit, the miR-Q let-7b assay turned out to possess an enhanced dynamic range. Furthermore, the miR-Q assay turned out to be highly discriminative, exhibiting almost no cross reaction between related miRNA molecules, which differed by at least one base. As shown in the let-7a assay versus let-7b as a target, the optimisation of the approach's discriminative power can be achieved by positioning the terminal 3' nucleotide of short-miR-x-rev at one of the mismatched bases. Since in real human samples the RNA species are much richer, we performed side-by-side quantification of let-7b in different human cell lines using miR-Q and mirVana™ qRT-PCR and comparing the outcomes of the different assays. The miR-Q results such as the ratios between the spike-in controls and the non-spiked samples were verified using the commercial kit, pointing to the specificity of the miR-Q assay to detect mature miRNA molecules.
To minimise possible sample-to-sample variation due to imbalanced initial total RNA input, we chose 5S rRNA to normalise miRNA expression. Based on the small size of 5S rRNA (representing the small RNA fraction in total RNA samples) and its high conservation level among various species, it appears to be an appropriate gene for the normalisation of miRNAs. Vandesompele et al.  studied the normalisation of qRT-PCR data by geometric means. Depending on the selected genes, tissues, and samples, they reported average CV values ranging from 15% to 50%. Despite the fact that we only used the 5S rRNA expression values and not a geometric mean, our calculated CV values correlate well with their data for pooled tissues. Intestinal RNA samples used in this study also represent a complex starting material, since the total RNA was isolated from whole tissues.
miR-21 was reported as being overexpressed in various human cancerous tissues, including colon carcinoma [29, 30] and represents an antiapoptotic factor . While common miRNA dysregulation in cancer seems to result in a gain of expression , some miRNAs such as miR-145 are downregulated in colorectal carcinomas [26, 30]. Dysregulation of these miRNAs in human colorectal cancer points to their potential role in cell proliferation and differentiation in intestinal tissues. Variation in porcine miRNA expression among the ten examined piglets may therefore reflect the individual differences in the intestinal development of the animals. The measured miR-145 and miR-21 expression values in porcine intestinal samples should basically rely on detection of mature miRNA molecules. Within this context, Northern blot analysis and qRT-PCR studies have already shown that the cellular steady-state level of miRNA precursors is negligible, compared with the mature miRNA [17, 18].
Despite the existence of commercial miRNA qRT-PCR approaches, there is an increasing need for fast, reliable, and cost-effective assays, which are adaptable for any research group interested in miRNA detection. Our miR-Q approach provides a linearity of up to 8 orders of magnitude detecting as low as 0.2 fM miRNA molecules.
It offers an alternative method for scientists interested in detecting and quantifying miRNA expression in total RNA samples from different species and tissues.
Oligonucleotides and synthetic miRNA molecules
Ten known miRNA molecules were chosen, inter alia, according to preliminary miRNA-Microarray screening experiments using porcine intestinal samples. These miRNA sequences were chosen from the miRBase Sequence database Release 9.2  and oligonucleotides were designed for every assay (Table 1). Synthetic miRNA molecules were used for the validation of assays. All DNA- and RNA-oligonucleotides were synthesised by Metabion AG (Martinsried, Germany).
Total RNA isolation from samples
Human total RNA from the cervical carcinoma cell line HeLa (ATCC No.: CCL-2), the colon carcinoma cells HT-29 (ATCC No.: HTB-38), and the lung carcinoma cell line A549 (ATCC No.: CCL-185) as well as porcine total RNA from intestinal tissues were prepared using the mirVana miRNA Isolation Kit (Ambion, Darmstadt, Germany), according to the manufacturer's protocol. The porcine intestinal samples included the jejunum and ileum of ten 31-day-old piglets (EUROC × Pietrain).
In order to validate the new assays, bacterial total RNA was employed as an unspecific complex RNA background in reverse transcription (RT) reactions. RNA was isolated from Escherichia coli DH5á using the Invisorb Spin Cell RNA Mini Kit (Invitek, Berlin, Germany), according to the manufacturer's protocol.
The RNA quality and quantity of all samples were proven using the Agilent 2100 Bioanalyzer and the RNA Nano Chips (Agilent, Waldbronn, Germany).
The validation of every assay was performed by RT of certain amounts of the corresponding synthetic miRNA with 50 ng bacterial total RNA present, representing a complex RNA background. Furthermore, the human total RNA as well as the porcine intestinal total RNA were used for reverse transcription.
250 fmol of the miRNA-specific DNA-oligonucleotide (RT6-miR-x) with 5' overhang and the RevertAid™ M-MuLV Reverse Transcriptase (Fermentas GmbH, St. Leon-Roth, Germany) were employed to transcribe miRNA into cDNA. A mixture of 50 ng human or porcine total RNA or bacterial total RNA spiked with synthetic miRNA and RT6-miR-x was first prepared in a 4 μl volume. The mixture was incubated at 70°C for 5 min and chilled on ice. Then, the volume was brought up to 10 μl by adding the RT-Buffer, 1 mM dNTPs, 100 U Reverse Transcriptase and water. The reaction was incubated at 37°C for 5 min followed by 42°C for 60 min. The enzyme was inactivated by heating at 70°C for 10 min. The standard was prepared using 50 ng of bacterial total RNA spiked with different amounts of synthetic miRNA (10 nM – 1 fM in RT reaction) and was applied for validation and for preparation of qPCR calibration curves. 50 ng of non-spiked bacterial total RNA was used as negative control.
The optimal annealing temperature (Tanopt) for every miR-Q assay was first proven by performing a conventional PCR with an annealing temperature gradient ranging from 53 to 65°C. The reaction was performed with 4 nM short-miR-x-rev, 100 nM MP-fw, and 100 nM MP-rev using the Immolase DNA Polymerase (Bioline, Luckenwalde, Germany). The reaction was carried out according to the qPCR conditions (see below) in 25 μl final volume using 2 μl of cDNA, which was obtained from RT reaction with 10 pM of the particular synthetic miRNA. The product size ranged from 82 to 85 bp, depending on the miRNA being detected. After the Tanopt was determined, the cDNA was quantified using the Rotor-Gene 3000 real-time Detection System (Corbett Life Science, Sydney, Australia) as well as the StepOnePlus™ Real-Time PCR System (Applied Biosystems, Darmstadt, Germany). For this purpose, triplicate measurements of 2 μl cDNA were made in 10 μl final reaction volume. SYBR Green qPCR was performed using the SensiMix DNA Kit (Quantace Ltd., Berlin, Germany), 4 nM short-miR-x-rev, 100 nM MP-fw, and 100 nM MP-rev. The amplification was carried out via the first step at 95°C for 10 min, followed by 40 cycles with 15 s at 95°C, 10 s at the particular annealing temperature (Table 1), and 20 s at 72°C. The fluorescence signal was acquired at 72°C and the Ct values were converted into fM miRNA, using a miRNA-specific calibration curve. MiRNA amounts were determined by triplicate measurements for each sample, compared with a calibration curve established by reverse transcription of serially diluted amounts of the particular synthetic miRNA in the presence of 50 ng bacterial total RNA. The RT reaction of non-spiked bacterial total RNA samples and no template controls were used as negative controls.
5S ribosomal RNA normalisation
Sample-to-sample variation of miRNA expression in porcine intestinal samples was corrected by normalisation with 5S rRNA chosen as a housekeeping gene. Firstly, 50 ng of porcine total RNA was reverse-transcribed using the RevertAid™ M-MuLV Reverse Transcriptase (Fermentas GmbH), according to the manufacturer's protocol using random Hexamers. 5S rRNA molecules were quantitated by triplicate measurements of 2 μl cDNA in 10 μl final reaction volume. SYBR Green qPCR was performed using the SensiMix DNA Kit (Quantace Ltd.) and 0.2 μM of each primer 5S rRNA-fw and 5S rRNA-rev (table 1). Amplification was carried out via the first step at 95°C for 10 min, followed by 40 cycles with 15 s at 95°C, 10 s at 60°C and 20 s at 72°C, providing an amplicon of 114 bp. The fluorescence signal was acquired at 72°C and Ct values were converted into fg 5S rRNA per qPCR reaction using a calibration curve, which was established by serial dilutions of the corresponding PCR product. Normalisation was performed by calculating the miRNA:5S rRNA expression ratios.
We are grateful to Patrik Varadinek (Freie Universität Berlin), Dr. Christian Wunsch (ipal GmbH), Dr. Bettina Büttner (ipal GmbH), and Dr. Georg J. Hoppe (Forrester & Boehmert) for their active support in patent application (European Patent Application No. 07 006 897.8). We also would like to thank Dr. Astrid Lewin (Robert Koch-Institut, Berlin) and Dr. Joachim Mankertz (Charité, Campus Benjamin Franklin, Berlin) for providing the cell lines A549 and HT-29, respectively. Furthermore, we would like to thank Andrea Snelling for critical reading of the manuscript.
The study was funded by the "Forschungskommission" of the Freie Universität Berlin (Fonds 02235). Tissue Samples were donated by project DFG-Ei296/12-2.
- Kloosterman WP, Plasterk RH: The diverse functions of microRNAs in animal development and disease. Dev Cell 2006, 11: 441-450. 10.1016/j.devcel.2006.09.009View ArticlePubMedGoogle Scholar
- Hamilton AJ, Baulcombe DC: A species of small antisense RNA in posttranscriptional gene silencing in plants. Science 1999, 286: 950-952. 10.1126/science.286.5441.950View ArticlePubMedGoogle Scholar
- Zhang B, Wang Q, Pan X: MicroRNAs and their regulatory roles in animals and plants. J Cell Physiol 2007, 210: 279-289. 10.1002/jcp.20869View ArticlePubMedGoogle Scholar
- Kim VN, Nam JW: Genomics of microRNA. Trends Genet 2006, 22: 165-173. 10.1016/j.tig.2006.01.003View ArticlePubMedGoogle Scholar
- Jackson RJ, Standart N: How do microRNAs regulate gene expression? Sci STKE 2007, 2007: re1. 10.1126/stke.3672007re1View ArticlePubMedGoogle Scholar
- Kim J, Krichevsky A, Grad Y, Hayes GD, Kosik KS, Church GM, Ruvkun G: Identification of many microRNAs that copurify with polyribosomes in mammalian neurons. Proc Natl Acad Sci U S A 2004, 101: 360-365. 10.1073/pnas.2333854100PubMed CentralView ArticlePubMedGoogle Scholar
- Lee RC, Ambros V: An extensive class of small RNAs in Caenorhabditis elegans. Science 2001, 294: 862-864. 10.1126/science.1065329View ArticlePubMedGoogle Scholar
- Babak T, Zhang W, Morris Q, Blencowe BJ, Hughes TR: Probing microRNAs with microarrays: tissue specificity and functional inference. Rna 2004, 10: 1813-1819. 10.1261/rna.7119904PubMed CentralView ArticlePubMedGoogle Scholar
- Nelson PT, Baldwin DA, Scearce LM, Oberholtzer JC, Tobias JW, Mourelatos Z: Microarray-based, high-throughput gene expression profiling of microRNAs. Nat Methods 2004, 1: 155-161. 10.1038/nmeth717View ArticlePubMedGoogle Scholar
- Liang RQ, Li W, Li Y, Tan CY, Li JX, Jin YX, Ruan KC: An oligonucleotide microarray for microRNA expression analysis based on labeling RNA with quantum dot and nanogold probe. Nucleic Acids Res 2005, 33: e17. 10.1093/nar/gni019PubMed CentralView ArticlePubMedGoogle Scholar
- Neely LA, Patel S, Garver J, Gallo M, Hackett M, McLaughlin S, Nadel M, Harris J, Gullans S, Rooke J: A single-molecule method for the quantitation of microRNA gene expression. Nat Methods 2006, 3: 41-46. 10.1038/nmeth825View ArticlePubMedGoogle Scholar
- Wong ML, Medrano JF: Real-time PCR for mRNA quantitation. Biotechniques 2005, 39: 75-85.View ArticlePubMedGoogle Scholar
- Malinen E, Kassinen A, Rinttila T, Palva A: Comparison of real-time PCR with SYBR Green I or 5'-nuclease assays and dot-blot hybridization with rDNA-targeted oligonucleotide probes in quantification of selected faecal bacteria. Microbiology 2003, 149: 269-277. 10.1099/mic.0.25975-0View ArticlePubMedGoogle Scholar
- Palmer S, Wiegand AP, Maldarelli F, Bazmi H, Mican JM, Polis M, Dewar RL, Planta A, Liu S, Metcalf JA, Mellors JW, Coffin JM: New real-time reverse transcriptase-initiated PCR assay with single-copy sensitivity for human immunodeficiency virus type 1 RNA in plasma. J Clin Microbiol 2003, 41: 4531-4536. 10.1128/JCM.41.10.4531-4536.2003PubMed CentralView ArticlePubMedGoogle Scholar
- Schmittgen TD, Jiang J, Liu Q, Yang L: A high-throughput method to monitor the expression of microRNA precursors. Nucleic Acids Res 2004, 32: e43. 10.1093/nar/gnh040PubMed CentralView ArticlePubMedGoogle Scholar
- Jiang J, Lee EJ, Gusev Y, Schmittgen TD: Real-time expression profiling of microRNA precursors in human cancer cell lines. Nucleic Acids Res 2005, 33: 5394-5403. 10.1093/nar/gki863PubMed CentralView ArticlePubMedGoogle Scholar
- Lagos-Quintana M, Rauhut R, Yalcin A, Meyer J, Lendeckel W, Tuschl T: Identification of tissue-specific microRNAs from mouse. Curr Biol 2002, 12: 735-739. 10.1016/S0960-9822(02)00809-6View ArticlePubMedGoogle Scholar
- Raymond CK, Roberts BS, Garrett-Engele P, Lim LP, Johnson JM: Simple, quantitative primer-extension PCR assay for direct monitoring of microRNAs and short-interfering RNAs. Rna 2005, 11: 1737-1744. 10.1261/rna.2148705PubMed CentralView ArticlePubMedGoogle Scholar
- Chen C, Ridzon DA, Broomer AJ, Zhou Z, Lee DH, Nguyen JT, Barbisin M, Xu NL, Mahuvakar VR, Andersen MR, Lao KQ, Livak KJ, Guegler KJ: Real-time quantification of microRNAs by stem-loop RT-PCR. Nucleic Acids Res 2005, 33: e179. 10.1093/nar/gni178PubMed CentralView ArticlePubMedGoogle Scholar
- Griffiths-Jones S, Grocock RJ, van Dongen S, Bateman A, Enright AJ: miRBase: microRNA sequences, targets and gene nomenclature. Nucleic Acids Res 2006, 34: D140-4. 10.1093/nar/gkj112PubMed CentralView ArticlePubMedGoogle Scholar
- Vandesompele J, De Preter K, Pattyn F, Poppe B, Van Roy N, De Paepe A, Speleman F: Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes. Genome Biol 2002, 3: RESEARCH0034. 10.1186/gb-2002-3-7-research0034PubMed CentralView ArticlePubMedGoogle Scholar
- Lewis BP, Burge CB, Bartel DP: Conserved seed pairing, often flanked by adenosines, indicates that thousands of human genes are microRNA targets. Cell 2005, 120: 15-20. 10.1016/j.cell.2004.12.035View ArticlePubMedGoogle Scholar
- Alvarez-Garcia I, Miska EA: MicroRNA functions in animal development and human disease. Development 2005, 132: 4653-4662. 10.1242/dev.02073View ArticlePubMedGoogle Scholar
- Chan JA, Krichevsky AM, Kosik KS: MicroRNA-21 is an antiapoptotic factor in human glioblastoma cells. Cancer Res 2005, 65: 6029-6033. 10.1158/0008-5472.CAN-05-0137View ArticlePubMedGoogle Scholar
- Si ML, Zhu S, Wu H, Lu Z, Wu F, Mo YY: miR-21-mediated tumor growth. Oncogene 2007, 26: 2799-2803. 10.1038/sj.onc.1210083View ArticlePubMedGoogle Scholar
- Michael MZ, SM OC, van Holst Pellekaan NG, Young GP, James RJ: Reduced accumulation of specific microRNAs in colorectal neoplasia. Mol Cancer Res 2003, 1: 882-891.PubMedGoogle Scholar
- Iorio MV, Ferracin M, Liu CG, Veronese A, Spizzo R, Sabbioni S, Magri E, Pedriali M, Fabbri M, Campiglio M, Menard S, Palazzo JP, Rosenberg A, Musiani P, Volinia S, Nenci I, Calin GA, Querzoli P, Negrini M, Croce CM: MicroRNA gene expression deregulation in human breast cancer. Cancer Res 2005, 65: 7065-7070. 10.1158/0008-5472.CAN-05-1783View ArticlePubMedGoogle Scholar
- Mocellin S, Rossi CR, Pilati P, Nitti D, Marincola FM: Quantitative real-time PCR: a powerful ally in cancer research. Trends Mol Med 2003, 9: 189-195. 10.1016/S1471-4914(03)00047-9View ArticlePubMedGoogle Scholar
- Volinia S, Calin GA, Liu CG, Ambs S, Cimmino A, Petrocca F, Visone R, Iorio M, Roldo C, Ferracin M, Prueitt RL, Yanaihara N, Lanza G, Scarpa A, Vecchione A, Negrini M, Harris CC, Croce CM: A microRNA expression signature of human solid tumors defines cancer gene targets. Proc Natl Acad Sci U S A 2006, 103: 2257-2261. 10.1073/pnas.0510565103PubMed CentralView ArticlePubMedGoogle Scholar
- Bandres E, Cubedo E, Agirre X, Malumbres R, Zarate R, Ramirez N, Abajo A, Navarro A, Moreno I, Monzo M, Garcia-Foncillas J: Identification by Real-time PCR of 13 mature microRNAs differentially expressed in colorectal cancer and non-tumoral tissues. Mol Cancer 2006, 5: 29. 10.1186/1476-4598-5-29PubMed CentralView ArticlePubMedGoogle Scholar
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.