microRNA引物设计参考文献

Real-time quantification of microRNAs by stem–loop RT–PCR Caifu Chen*, Dana A. Ridzon, Adam J. Broomer, Zhaohui Zhou, Danny H. Lee, Julie T. Nguyen, Maura Barbisin, Nan Lan Xu, Vikram R. Mahuvakar, Mark R. Andersen, Kai Qin Lao, Kenneth J. Livak and Karl J. Guegler Applied Biosystems, 850 Lincoln Centre Drive, Foster City, CA 94404, USA Received May 24, 2005; Revised July 8, 2005; Accepted October 25, 2005 ABSTRACT 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 effici- ency and specificity. TaqMan miRNA assays are spe- cific for mature miRNAs and discriminate among related miRNAs that differ by as little as one nucleot- ide. 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 vari- ation 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. INTRODUCTION MicroRNAs (miRNAs) are naturally occurring, highly con- served families of transcripts (18–25 nt in length) that are processed from larger hairpin precursors (1,2). miRNAs are found in the genomes of animals (3–9) and plants (10–12). To date, there are �1000 unique transcripts, including 326 human miRNAs in the Sanger Center miRNA registry (13). miRNAs regulate gene expression by catalyzing the cleav- age of messenger RNA (mRNA) (14–19) or repressing mRNA translation (19–21). They are believed to be critical in cell development, differentiation and communication (2). Specific roles include the regulation of cell proliferation and metabol- ism (22), developmental timing (23,24), cell death (25), haematopoiesis (26), neuron development (27), human tumorigenesis (28) and DNA methylation and chromatin modification (29). Although miRNAs represent a relatively abundant class of transcripts, their expression levels vary greatly among species and tissues (30). Less abundant miRNAs routinely escape detection with technologies such as cloning, northern hybrid- ization (31) and microarray analysis (32,33). Here, we present a novel real-time quantification method for accurate and sens- itive detection of miRNAs and other small RNAs. This method expands the real-time PCR technology for detecting gene expression changes from macromolecules (e.g. mRNAs) to micro molecules (e.g. miRNAs). MATERIALS AND METHODS Targets, primers and probes (Supplementary Data) Seventeen miRNA genes were selected from the Sanger Center miRNA Registry at http://www.sanger.ac.uk/Software/ Rfam/mirna/index.shtml. All TaqMan miRNA assays are available through Applied Biosystems (P/N: 4365409). Stand- ard TaqMan� assays for pri-miRNA precursors, pri-let-7a-3 and pri-miR-26b and pre-miRNA precursor pre-miR-30a were designed using PrimerExpress� software (Applied Biosys- tems, Foster City, CA). All sequences are available in the section of the Supplementary Data. Synthetic miRNA oligo- nucleotides were purchased from Integrated DNA Technolo- gies (IDT, Coralville, IA). *To whom correspondence should be addressed. Tel: +1 650 638 5245; Fax: +1 650 638 6343; Email: chencx@appliedbiosystems.com � The Author 2005. Published by Oxford University Press. All rights reserved. The online version of this article has been published under an open access model. Users are entitled to use, reproduce, disseminate, or display the open access version of this article for non-commercial purposes provided that: the original authorship is properly and fully attributed; the Journal and Oxford University Press are attributed as the original place of publication with the correct citation details given; if an article is subsequently reproduced or disseminated not in its entirety but only in part or as a derivative work this must be clearly indicated. For commercial re-use, please contact journals.permissions@oxfordjournals.org Nucleic Acids Research, 2005, Vol. 33, No. 20 e179 doi:10.1093/nar/gni178 Tissue RNA samples, cells, cell lysates and total RNA preparation Mouse total RNA samples from brain, heart, liver, lung, thymus, ovary and embryo at day 10–12 were purchased from Ambion (P/N: 7810, 7812, 7814, 7816, 7818, 7824, 7826 and 7968). Ambion’s mouse total RNAs are derived from Swiss Webster mice. All RNA samples were normalized based on the TaqMan� Gene Expression Assays for human or mouse glyceraldehyde-3-phosphate dehydrogenase (GAPDH) endogenous controls (P/N: 4310884E and 4352339E, Applied Biosystems). Two cell lines, HepG2 and OP9, were cultured using Gibco MEM (P/N: 12492–021, Invitrogen, Carlsbad, CA) supplemented with 10% fetal bovine serum (FBS) (P/N: SH30070.01, HyClone, Logan, UT). Trypsinized cells were counted with a hemocytometer. Approximately 2.8 · 106 suspended cells were pelleted by centrifugation (Allegra 6, Beckman Coulter, Fullerton, CA) at 1500 r.p.m. for 5 min, washed with 1 ml Dulbecco’s phosphate-buffered saline (PBS) without MgCl2 and CaCl2 (P/N: 14190078, Invitrogen, Carls- bad, CA). The cell pellets were re-suspended in 140 ml PBS and processed with three different sample preparation meth- ods. With the first method, a 50 ml sample (106 cells) was mixed with an equal amount of Nucleic Acid Purification Lysis Solution (P/N: 4305895; Applied Biosystems) by pipet- ting up and down 10 times, and then spun briefly. The lysate was diluted 1/10 with 1 U/ml RNase inhibitor solution (P/N: N8080119; Applied Biosystems) before adding the solution to an RT reaction. In the second method, a 50 ml sample (106 cells) was used to purify total RNA using the mirVana� miRNA Isolation Kit (P/N: 1560, Ambion, Austin, TX) according to the manufacturer’s protocol. Purified total RNA was eluted in 100 ml of elution buffer. The third method involved diluting cells 1/2 with 1· PBS, heating at 95�C for 5 min, and immediately chilling on ice before aliquotting dir- ectly into RT reactions. miRNA detection using mirVana� miRNA detection kit Solution hybridization-based miRNA analysis was carried out using the mirVana� miRNA Detection Kit (Cat. #: 1552, Ambion) according to the manufacturer’s protocol. RNA probes were synthesized by IDT. The radioisotope labeled RNA fragments were detected and quantitated with a Cyclone Storage Phosphor System (PerkinElmer, Boston, MA). Reverse transcriptase reactions Reverse transcriptase reactions contained RNA samples including purified total RNA, cell lysate, or heat-treated cells, 50 nM stem–loop RT primer (P/N: 4365386 and 4365387, Applied Biosystems), 1· RT buffer (P/N: 4319981, Applied Biosystems), 0.25 mM each of dNTPs, 3.33 U/ml MultiScribe reverse transcriptase (P/N: 4319983, Applied Biosystems) and 0.25 U/ml RNase inhibitor (P/N: N8080119; Applied Biosystems). The 7.5 ml reactions were incubated in an Applied Biosystems 9700 Thermocycler in a 96- or 384-well plate for 30 min at 16�C, 30 min at 42�C, 5 min at 85�C and then held at 4�C. All Reverse transcriptase reac- tions, including no-template controls and RT minus controls, were run in duplicate. PCR Real-time PCR was performed using a standard TaqMan� PCR kit protocol on an Applied Biosystems 7900HT Sequence Detection System (P/N: 4329002, Applied Biosystems). The 10 ml PCR included 0.67 ml RT product, 1· TaqMan� Uni- versal PCR Master Mix (P/N: 4324018, Applied Biosystems), 0.2 mM TaqMan� probe, 1.5 mM forward primer and 0.7 mM reverse primer. The reactions were incubated in a 384-well plate at 95�C for 10 min, followed by 40 cycles of 95�C for 15 s and 60�C for 1 min. All reactions were run in triplicate. The threshold cycle (CT) is defined as the fractional cycle number at which the fluorescence passes the fixed threshold. TaqMan� CT values were converted into absolute copy numbers using a standard curve from synthetic lin-4 miRNA. The method for real-time quantification of pri-miRNA precursors, let-7a-3 and miR-26b, and pre-miRNA precursor miR-30a was described elsewhere (34). RESULTS We proposed a new real-time RT–PCR scheme for miRNA quantification (Figure 1). It included two steps: RT and real- time PCR. First, the stem–loop RT primer is hybridized to a miRNA molecule and then reverse transcribed with a Multi- Scribe reverse transcriptase. Next, the RT products are quan- tified using conventional TaqMan PCR. Figure 1. Schematic description of TaqMan miRNA assays, TaqMan-based real-time quantification of miRNAs includes two steps, stem–loop RT and real- time PCR. Stem–loop RT primers bind to at the 30 portion of miRNA molecules and are reverse transcribed with reverse transcriptase. Then, the RT product is quantified using conventional TaqMan PCR that includes miRNA-specific forward primer, reverse primer and a dye-labeled TaqMan probes. The purpose of tailed forward primer at 50 is to increase its melting temperature (Tm) depending on the sequence composition of miRNA molecules. e179 Nucleic Acids Research, 2005, Vol. 33, No. 20 PAGE 2 OF 9 Figure 2. Dynamic range and sensitivity of the TaqMan lin-4 miRNA assay. (A) Amplification plot of synthetic lin-4 miRNA over seven orders of magnitude. Synthetic RNA input ranged from 1.3 · 10�3 fM (equivalent to 7 copies per reaction) to 1.3 · 104 fM (7 · 107 copies per reaction) in PCR; (B) Standard curve of the lin-4 miRNA. PAGE 3 OF 9 Nucleic Acids Research, 2005, Vol. 33, No. 20 e179 The dynamic range and sensitivity of the miRNA quanti- fication scheme were first evaluated using a synthetic cel-lin-4 target. Synthetic RNA was quantified based on the A260 value and diluted over seven orders of magnitude. The cel-lin-4 TaqMan miRNA assay showed excellent linearity between the log of target input and CT value, demonstrating that the assay has a dynamic range of at least 7 logs and is capable of detecting as few as seven copies in the PCR reaction (Figure 2). Eight additional miRNA assays were also validated using mouse lung total RNA. The RNA input ranged from 0.025 to 250 ng (Figure 3). The CT values correlated to the RNA input (R2 > 0.994) over four orders of magnitude. A negative control assay, cel-miR-2, did not give a detectable signal, even in reactions with 250 ng mouse total RNA. The expression profile of five miRNAs was determined in seven different mouse tissues to create a miRNA expression map. The copy number per cell was calculated based on the input total RNA (assuming 15 pg/cell) and the standard curve of synthetic lin-4 target. Several interesting observations were made from this expression map. First, miRNAs are very abundant, averaging 2390 copies per cell in these tissues. The level of expression ranged from less than 10 to 32 090 copies per cell. Of the 12 miRNAs, miR-16 and miR-323 were the most and least abundant miRNAs, respectively, across all tissues. In addition, each tissue had a distinctive signature of miRNA expression. The overall level of miRNA expression was highest in mouse lung and lowest in embryos. Finally, the dynamic range of miRNA expression varied greatly from less than 5-fold (let-7a) to more than 2000-fold (miR-323) among these seven tissues (Table 1). To assess the need for RNA isolation, we added cell lysates directly to miRNA assays. The equivalent of 2.5–2500 cells were added directly to 7.5 ml RT reactions. When detected, the CT values correlated (R 2 > 0.998) to the number of cells in Figure 3. Correlation of total RNA input to the threshold of cycle (CT) values for eight miRNA assays. Mouse lung total RNA input ranged from 0.025 to 250 ng per RT reaction. A Caenorhabditis elegans miRNA (miR-2) was included as a negative control assay. Table 1. Expression profiles of five miRNAs across seven mouse tissues miRNA ID Copy number per cell cFold-change Brain Heart Liver Lung Thymus Ovary Embryo Average let-7a 2010 1420 700 2390 1420 3120 1050 1730 5 miR-16 10 240 13 520 3890 22 080 32 090 11 100 5210 14 020 6 miR-20 70 300 130 580 1990 420 620 590 28 miR-21 670 2540 4450 7970 3550 5310 390 3550 20 miR-22 290 1020 310 590 130 560 40 420 26 Average 2240 2040 1140 4430 3540 2600 750 2390 17 Mouse or human total RNA samples from brain, heart, liver, lung, thymus, ovary and embryo (at day 10–12) were purchased from Ambion. Copy number per cell is estimated based on standard curve of lin-4 synthetic miRNA. A total of 150 ng RNA (or equivalent to approximately 10 000 cells assuming 15 pg of total RNA per cell) was added to each RT reaction. RNA input was normalized based on TaqMan GAPDH endogenous control (P/N: 4352339E). e179 Nucleic Acids Research, 2005, Vol. 33, No. 20 PAGE 4 OF 9 the RT reactions over at least three orders of magnitude (Figure 4). The effect of non-specific genomic DNA on TaqMan miRNA assays was also tested for 12 assays. Results showed no difference in CT values in the presence or absence of 5 ng of human genomic DNA added to the RT reactions, suggesting that the assays are highly specific for RNA targets (data not shown). Based on this observation, we added heat-treated cells directly to miRNA quantification assays. Figure 5 illustrates the comparison of miRNA quantification using purified total Figure 4. Dynamic range of eight TaqMan miRNA assays using OP9 cell lysates. The number of cell input ranged from 3 to 2500 cells per RT. A Caenorhabditis elegans miRNA (miR-2) was used as a negative control. Figure 5. Comparison of heat-treated cells, cell lysate and total RNA for real-time quantitation of 10 miRNAs. The level of miRNA expression is measured in the threshold cycles (CT). Approximately 400 HepG2 cells were analyzed per PCR. PAGE 5 OF 9 Nucleic Acids Research, 2005, Vol. 33, No. 20 e179 RNA, cell lysates and heat-treated cells derived from an equal number of HepG2 cells. Adding heat-treated cells directly to the miRNA assays produced the lowest CT values, and good concordance was observed among all three different sample preparation methods. The reproducibility of TaqMan miRNA assays was examined by performing12 miRNA assays with 16 replicates performed by two independent operators (data not shown). The standard deviation of the CTs averaged 0.1, demonstrating the high precision of the assays. Solution hybridization-based miRNA northern analysis was used as an independent technology to compare with TaqMan miRNA assays (Figure 6). We observed that hybridization- based miRNA analyses were less reproducible and that con- cordance with TaqMan assays varied from target to target. There was a general concordance between the two methods (R2 ¼ 0.916) for miR-16 across five mouse tissue samples. However, correlations were relatively low for less abundant miRNAs, such as miR-30 (R2 ¼ 0.751). Hybridization methods can lack specificity for the mature miRNAs. We investigated the ability of the TaqMan miRNA assays to differentiate between the mature miRNAs and their longer precursors, using synthetic targets for pri-miRNA pre- cursors, pri-miR-26b and pri-let-7a and pre-miRNA precursor pre-miR-30a (Table 2). TaqMan assays designed to detect either precursors or mature miRNAs were tested with synthetic targets averaging 1.5 · 108 copies per RT reaction (1.3 · 107 copies per PCR). TaqMan miRNA analyses with only pri- miRNA precursor molecules produced CT values at least 11 cycles higher than analyses with mature miRNA ones. This result implies that if mature miRNA and precursor were at an equal concentration, the latter would contribute <0.05% background signal to the assay of mature target. For pre-miR-30a where the mature miRNA miR-30a-3p is located at the 30 end of the pre-miR-30a sequence, a difference Figure 6. Comparison of TaqMan miRNA miR-16 assay to solution-based northern hybridization analysis. Total RNAs from mouse kidney, liver, lung, spleen and testicle tissues were used. Table 2. Discrimination between mature miRNAs and their pri- or pre-miRNA precursors ID Synthetic miRNA (No. of copies) Synthetic precursor (No. of copies) Total RNA (ng) CT miRNA Precursor miR-26b 1.5 · 108 0 0 16.5 ND 0 1.5 · 108 0 27.4 18.7 0 0 7.5 21.9 28.7 0 0 0 ND ND let-7a 1.5 · 108 0 0 16.5 ND 0 1.5 · 108 0 29.5 19.4 0 0 7.5 19.9 34.7 0 0 0 ND ND miR-30a-3p 1.5 · 108 0 0 15.8 ND 0 1.5 · 108 0 24.2 17.2 0 0 7.5 25.4 30.3 0 0 0 ND ND miR-30a-5p 1.5 · 108 0 0 16.3 ND 0 1.5 · 108 0 29.1 18.9 0 0 7.5 22.1 30.3 0 0 0 39.6 ND Note: ND represents no detectable PCR products after 40 cycles. The copy number of synthetic miRNAs in RT was estimated based on the A260 values. Only 9% of RT product was added to PCR. Total RNA from human lung was used. Pre-miRNA precursors, pri-let-7a-3 and pri-miR-26b, and pre-miRNA precursor pre-miR-30a were examined. e179 Nucleic Acids Research, 2005, Vol. 33, No. 20 PAGE 6 OF 9 of 8.4 CT was observed. The results showed that TaqMan miRNA assays are specific to mature miRNAs. However, the assay specificity is better if the miRNA is located at the 50 strand of the pre-miRNA precursor. Experiments analyzing total RNA instead of synthetic targets indicated that the pre- cursors are at least two orders of magnitude less abundant than mature miRNAs, based on CT differences of 7 or more for miR-26b-1 and let-7a-2 precursors. Considered together, these results suggest that the TaqMan miRNA assays are highly specific for the mature miRNAs. The ability of the TaqMan miRNA assays to discriminate miRNAs that differ by as little as a single nucleotide was tested with the five synthetic miRNAs of let-7a, let-7b, let-7c, let-7d and let-7e (Figure 7). Each miRNA assay was examined against each miRNA. Relative detection efficiency was cal- culated from CT differences between perfectly matched and mismatched targets, assuming 100% efficiency for the perfect match. Very low levels of non-specific signal were observed, ranging from zero to 0.3% for miRNAs with 2–3 mismatched bases and only 0.1–3.7% for the miRNAs that differed by a single nucleotide. Most cross-reactions resulted from G–T mismatches during the RT reaction (let-7a assay versus let- 7c target etc.). Only the targeted miRNA was detected if more than three mismatched bases between any two miRNAs were present. We compared the discrimination ability of the TaqMan miRNA assays to that of solution-based hybridization analysis (Figure 8). In our hands, the hybridization method discrimin- ated well between let-7a and let-7b. However, poor or no discrimination was observed among let-7a, let-7c and let- 7d, which differ by 1–3 nt. We speculated that stem–loop primers might provide better RT efficiency and specificity than linear ones. Base stacking of the stem might enhance the thermal stability of the RNA–DNA heteroduplex. Furthermore, spatial constraint of the stem–loop would likely improve the assay specificity in comparison to conventional linear RT primers. We compared the sensitivity and specificity of the stem–loop and linear RT primers using synthetic miRNAs for let-7a (Figure 9). We observed several advantages for the stem–loop RT. First, in the presence of the synthetic let-7a target, the CT values between linear and stem– loop RT methods differed by 7, indicating that the efficiency of stem–loop RT was at least 100 times higher. Secondly, stem– loop RT discriminated better between miRNAs tha