RNA pre-amplification enables large-scale RT-qPCR gene-expression studies on limiting sample amounts
- Joëlle Vermeulen†1,
- Stefaan Derveaux†1,
- Steve Lefever1,
- Els De Smet1,
- Katleen De Preter1,
- Nurten Yigit1,
- Anne De Paepe1,
- Filip Pattyn1,
- Frank Speleman1 and
- Jo Vandesompele1, 2Email author
© Vandesompele et al; licensee BioMed Central Ltd. 2009
Received: 11 August 2009
Accepted: 25 November 2009
Published: 25 November 2009
The quantitative polymerase chain reaction (qPCR) is a widely utilized method for gene-expression analysis. However, insufficient material often compromises large-scale gene-expression studies. The aim of this study is to evaluate an RNA pre-amplification method to produce micrograms of cDNA as input for qPCR.
The linear isothermal Ribo-SPIA pre-amplification method (WT-Ovation; NuGEN) was first evaluated by measuring the expression of 20 genes in RNA samples from six neuroblastoma cell lines and of 194 genes in two commercially available reference RNA samples before and after pre-amplification, and subsequently applied on a large panel of 738 RNA samples extracted from neuroblastoma tumours. All RNA samples were evaluated for RNA integrity and purity. Starting from 5 to 50 nanograms of total RNA the sample pre-amplification method was applied, generating approximately 5 microgams of cDNA, sufficient to measure more than 1000 target genes. The results obtained from this study show a constant yield of pre-amplified cDNA independent of the amount of input RNA; preservation of differential gene-expression after pre-amplification without introduction of substantial bias; no co-amplification of contaminating genomic DNA; no necessity to purify the pre-amplified material; and finally the importance of good RNA quality to enable pre-amplification.
Application of this unbiased and easy to use sample pre-amplification technology offers great advantage to generate sufficient material for diagnostic and prognostic work-up and enables large-scale qPCR gene-expression studies using limited amounts of sample material.
Amongst the various methods available to measure gene-expression, the reverse transcription quantitative polymerase chain reaction (RT-qPCR) is the most rapid, sensitive, and reproducible method [1–5]. However, it often remains challenging to obtain from clinical samples the amounts of mRNA required to perform a gene-expression analysis, especially for large-scale studies.
Therefore, it seems that a method capable of pre-amplifying nanogram quantities of RNA is essential, to ensure that sufficient material is available for high-throughput gene-expression profiling. Various pre-amplification methods have been proposed including as well PCR-based [6, 7] as linear isothermal [8–10] pre-amplification strategies. Each method has proven to be effective in generating microgram quantities of cDNA from minute amounts of input RNA. While various studies have evaluated these methods for microarray-based procedures [11–17], only limited information is available for qPCR applications.
This paper extensively evaluates the linear isothermal Ribo-SPIA pre-amplification method for qPCR [10, 18]. The method was first evaluated in RNA samples from neuroblastoma cell lines and commercially available reference RNA, and subsequently applied on a large panel of RNA samples extracted from neuroblastoma tumours, to be used in a prognostic multigene-expression signature study .
Materials and methods
Total RNA was extracted from 6 neuroblastoma cell lines and 738 fresh frozen neuroblastoma tumour biopsies according to three methods in collaborating laboratories. Two commercial RNA samples were mixed (Universal Human Reference RNA (UHRR) from Stratagene and Human Brain Reference RNA (HBRR) from Ambion) to generate the four MAQC (MicroArray Quality Control) reference samples .
In order to assess the RNA purity and integrity, we performed a SPUD assay for the detection of enzymatic inhibitors  and a capillary gel electrophoresis analysis (Experion; Bio-Rad) to establish an RNA quality index (RQI).
RNA pre-amplification and cDNA synthesis
In parallel the same RNA extracted from the neuroblastoma cell lines and the MAQC samples were used for conventional cDNA synthesis using the iScript cDNA Synthesis Kit according to the manufacturer's instructions (Bio-Rad).
High-throughput real-time quantitative PCR based gene-expression
See [Additional file 3] for more details on this section.
Pre-amplification yield as a function of RNA input
Pre-amplification method does not pre-amplify DNA
In order to determine if residual DNA in the RNA extract is co-amplified and consequently might confound the results, we pre-amplified pure human genomic DNA (HGDNA) and two RNA samples from neuroblastoma cell lines verified for absence of DNA and subsequently spiked with 1% and 10% HGDNA (2 ng DNA per 20 ng RNA input for pre-amplification) (Roche). We next performed qPCR with a DNA-specific primer pair (NEUROD1; RTPrimerDB ID 8113 ) and used HGDNA as positive control. No signal for NEUROD1 could be observed in the pre-amplified cell lines spiked with DNA as resulting DNA concentration after a 200× dilution of the pre-amplified product is lower than 0.5 pg/μl, which is below the detection level for qPCR. Moreover, the Cq-value of NEUROD1 was equal in the HGDNA that had undergone the above described pre-amplification procedure and in the HGDNA used as positive control. These results indicate that DNA is not co-amplified (data not shown).
No need for purification of the pre-amplified products
Expression values of 6 reference genes using qPCR in purified versus non-purified pre-amplified samples
mean Cq NP1 (n = 2)
mean Cq P1 (n = 2)
mean Cq NP2 (n = 2)
mean Cq P2 (n = 2)
mean Cq NP3 (n = 2)
mean Cq P3 (n = 2)
mean Cq NP4 (n = 2)
mean Cq P4 (n = 2)
mean Cq NP5 (n = 2)
mean Cq P5 (n = 2)
mean Cq NP6 (n = 2)
mean Cq P6 (n = 2)
6.31 (95% CI: 4.89 - 8.14)
In a last step of the evaluation of the necessity of pre-amplification clean-up, we measured the expression of ten reference genes in ten samples before and after pre-amplification. Comparison of the cumulative distribution plots of the ddCq-values obtained on purified and non-purified pre-amplified product showed that the plots almost completely overlap, providing further evidence that purification is not required [Additional file 7, Figure S4].
Pre-amplification as a function of RNA quality
An import limitation of gene-expression analysis in the current diagnostic workflow is the fact that often minimal amounts of biomaterial are procured. As such, in many cases only a few nanograms of total RNA are available. In order to measure a large number of genes on this limited material and to maximize the number of samples through collaborative studies, a robust sample pre-amplification method is required. In this study we evaluated the linear isothermal Ribo-SPIA pre-amplification method for qPCR-based gene-expression analysis in cancer cell lines and commercially available reference samples, optimized the pre-amplification workflow, and used the method in a large clinical sample set.
First, we could clearly demonstrate that differential expression is preserved after pre-amplification and that no substantial bias is introduced. The fold-changes between pre-amplified samples were compared to those observed between non-amplified samples in the largest set to date (194 genes, 4 samples, 1164 data points), revealing an accurate preservation of relative transcriptome composition despite the pre-amplification process. This is in accordance with previously reported findings on smaller datasets using qPCR [10, 26]. However, careful interpretation of the results is warranted in case of very small fold changes in gene-expression between samples. We further noticed that the observed bias (high ddCq) is mainly due to a lower pre-amplification efficiency for the region targeted with qPCR. Assays with a large difference in Cq-value before and after pre-amplification may thus need redesign. Further studies are required to investigate the potential relationship between various factors (including target localisation in the transcript) and the observed bias; if conclusive, guidelines might be developed for design of better qPCR assays to be used in pre-amplified products to further reduce the bias. Important to note is that the comparison of gene-expression of non-amplified samples with pre-amplified samples is not possible, which means that all samples analysed in the same expression study need pre-amplification. Moreover, since a sequence-specific pre-amplification bias has been recognized this technique is not suitable for splice-variant quantification or any other study that aims at the comparison of expression levels of two genes.
We also assessed the need of DNase treatment before and of purification after pre-amplification. The results obtained show that neither of these procedures is required. This is an important finding, especially in large-scale gene-expression studies, as both techniques are time-consuming and add a substantial cost to the experiments. Furthermore, DNase treatment may lead to a loss of material and of mRNA integrity due to the exposure of the RNA samples to a high temperature during heat inactivation required for many commercial DNases.
Monitoring RNA quality and using intact RNA is of critical importance to obtain reliable gene-expression data and to ensure reproducibility of the results [27, 28]. In this study we assessed the RNA quality of 738 tumour samples before pre-amplification and evaluated the pre-amplification success by measuring the expression of two low abundant reference genes (SDHA and HPRT1). As expected, pre-amplification of highly degraded samples turned out to be unsuccessful. In addition, there was a negative correlation between the Cq-values of the reference genes and the RQI. A possible explanation for the imperfect negative correlation is the use of random primers in the RNA pre-amplification process, resulting in successful pre-amplification of partially compromised RNA samples.
As the tumour sample size is often very limited, the applied RNA pre-amplification procedure offers the possibility to perform large multicenter studies. This enabled us to establish and validate a robust prognostic multigene-expression signature in the largest neuroblastoma study cohort till now . Moreover, the generated cDNA library is available for future qPCR-based gene-expression studies.
An additional advantage of the evaluated pre-amplification method is its potential usefulness to generate a sufficient nucleic acids concentration for use in ultra high-throughput qPCR systems. These systems operate with very low volumes and have the potential disadvantage of compromised detection sensitivity as only limited volumes of nucleic acids can be added. As the concentration of the pre-amplified material is very high, this technique may offer a solution and should be evaluated in future studies.
In conclusion, the results obtained from this study indicate that differential gene-expression is preserved after sample pre-amplification using the linear isothermal Ribo-SPIA pre-amplification method, that DNA is not co-amplified, that a pre-amplification clean-up step is not required, and that the pre-amplification product is free of enzymatic inhibitors. Application of this unbiased and straightforward pre-amplification technology offers a great advantage in terms of accessibility of material for diagnostic and prognostic work-up and enables large-scale qPCR gene-expression studies.
List of abbreviations
difference in quantification cycle or delta-Cq (measure for differential gene-expression)
difference in dCq or delta-delta-Cq (see additional file 3 for an example)
Human Brain Reference RNA
human genomic deoxyribonucleic acid
MicroArray Quality Control
MYCN single copy
RNA quality index (determined by microfluidic capillary electrophoresis as a measure for RNA integrity)
reverse transcription quantitative polymerase chain reaction
Universal Human Reference RNA.
We thank Liesbeth Vercruysse, Justine Nuytens and Fanny De Vloed for their excellent technical assistance.
We acknowledge Lars Vahlkamp and Bas Hulshof from NuGEN for their support and Roderick Jensen for providing gene symbols of genes common to all MAQC gene-expression platforms.
We are indebted to all members of the International Society of Paediatric Oncology, European Neuroblastoma Group (SIOPEN), the Children's Oncology Group (COG) and the Gesellschaft fuer Paediatrische Onkologie und Haematologie (GPOH) for providing tumour samples.
This work was supported by the Belgian Foundation Against Cancer, found of public interest [grant number SCIE2006-25]; the Children Cancer Fund Ghent; the Fondation Fournier Majoie pour l'Innovation; the Belgian Society of Paediatric Haematology and Oncology, the Belgian Kid's Fund (JVM); the Fondation pour la recherche Nuovo-Soldati (JVM); the Institute for the Promotion of Innovation by Science and Technology in Flanders (SDR); the Fund for Scientific Research Flanders (KDR and [grant number G.0198.08]); the Ghent University Research Fund (BOF; SLF, FPT, and JVS); the European Community under the FP6 [project: STREP: EET-pipeline; number: 037260]; the Methusalem program [BOF08/01 M01108]; and the Belgian program of Interuniversity Poles of Attraction, initiated by the Belgian State, Prime Minister's Office, Science Policy Programming.
- Weis JH, Tan SS, Martin BK, Wittwer CT: Detection of rare mRNAs via quantitative RT-PCR. Trends Genet. 1992, 8 (8): 263-264. 10.1016/0168-9525(92)90242-V.View ArticlePubMedGoogle Scholar
- Bustin SA: Absolute quantification of mRNA using real-time reverse transcription polymerase chain reaction assays. J Mol Endocrinol. 2000, 25 (2): 169-193. 10.1677/jme.0.0250169.View ArticlePubMedGoogle Scholar
- Ginzinger DG: Gene quantification using real-time quantitative PCR: an emerging technology hits the mainstream. Exp Hematol. 2002, 30 (6): 503-512. 10.1016/S0301-472X(02)00806-8.View ArticlePubMedGoogle Scholar
- Bustin SA: Real-time quantitative PCR - opportunities and pitfalls. Eur Pharm Rev. 2008, 4: 18-23.Google Scholar
- Murphy J, Bustin SA: Reliability of real-time reverse-transcription PCR in clinical diagnostics: gold standard or substandard?. Expert Rev Mol Diagn. 2009, 9 (2): 187-197. 10.1586/14737184.108.40.206.View ArticlePubMedGoogle Scholar
- Iscove NN, Barbara M, Gu M, Gibson M, Modi C, Winegarden N: Representation is faithfully preserved in global cDNA amplified exponentially from sub-picogram quantities of mRNA. Nat Biotechnol. 2002, 20 (9): 940-943. 10.1038/nbt729.View ArticlePubMedGoogle Scholar
- Seth D, Gorrell MD, McGuinness PH, Leo MA, Lieber CS, McCaughan GW, Haber PS: SMART amplification maintains representation of relative gene expression: quantitative validation by real time PCR and application to studies of alcoholic liver disease in primates. J Biochem Biophys Methods. 2003, 55 (1): 53-66. 10.1016/S0165-022X(02)00177-X.View ArticlePubMedGoogle Scholar
- Van Gelder RN, von Zastrow ME, Yool A, Dement WC, Barchas JD, Eberwine JH: Amplified RNA synthesized from limited quantities of heterogeneous cDNA. Proc Natl Acad Sci USA. 1990, 87 (5): 1663-1667. 10.1073/pnas.87.5.1663.PubMed CentralView ArticlePubMedGoogle Scholar
- Eberwine J, Yeh H, Miyashiro K, Cao Y, Nair S, Finnell R, Zettel M, Coleman P: Analysis of gene expression in single live neurons. Proc Natl Acad Sci USA. 1992, 89 (7): 3010-3014. 10.1073/pnas.89.7.3010.PubMed CentralView ArticlePubMedGoogle Scholar
- Dafforn A, Chen P, Deng G, Herrler M, Iglehart D, Koritala S, Lato S, Pillarisetty S, Purohit R, Wang M, et al: Linear mRNA amplification from as little as 5 ng total RNA for global gene expression analysis. Biotechniques. 2004, 37 (5): 854-857.PubMedGoogle Scholar
- Saghizadeh M, Brown DJ, Tajbakhsh J, Chen Z, Kenney MC, Farber DB, Nelson SF: Evaluation of techniques using amplified nucleic acid probes for gene expression profiling. Biomol Eng. 2003, 20 (3): 97-106. 10.1016/S1389-0344(03)00006-6.View ArticlePubMedGoogle Scholar
- Puskas LG, Zvara A, Hackler L, Van Hummelen P: RNA amplification results in reproducible microarray data with slight ratio bias. Biotechniques. 2002, 32 (6): 1330-1334.PubMedGoogle Scholar
- Hu L, Wang J, Baggerly K, Wang H, Fuller GN, Hamilton SR, Coombes KR, Zhang W: Obtaining reliable information from minute amounts of RNA using cDNA microarrays. BMC Genomics. 2002, 3 (1): 16-10.1186/1471-2164-3-16.PubMed CentralView ArticlePubMedGoogle Scholar
- Zhao H, Hastie T, Whitfield ML, Borresen-Dale AL, Jeffrey SS: Optimization and evaluation of T7 based RNA linear amplification protocols for cDNA microarray analysis. BMC Genomics. 2002, 3 (1): 31-10.1186/1471-2164-3-31.PubMed CentralView ArticlePubMedGoogle Scholar
- Klur S, Toy K, Williams MP, Certa U: Evaluation of procedures for amplification of small-size samples for hybridization on microarrays. Genomics. 2004, 83 (3): 508-517. 10.1016/j.ygeno.2003.09.005.View ArticlePubMedGoogle Scholar
- Stirewalt DL, Pogosova-Agadjanyan EL, Khalid N, Hare DR, Ladne PA, Sala-Torra O, Zhao LP, Radich JP: Single-stranded linear amplification protocol results in reproducible and reliable microarray data from nanogram amounts of starting RNA. Genomics. 2004, 83 (2): 321-331. 10.1016/j.ygeno.2003.08.008.View ArticlePubMedGoogle Scholar
- Kenzelmann M, Klaren R, Hergenhahn M, Bonrouhi M, Grone HJ, Schmid W, Schutz G: High-accuracy amplification of nanogram total RNA amounts for gene profiling. Genomics. 2004, 83 (4): 550-558. 10.1016/j.ygeno.2003.09.026.View ArticlePubMedGoogle Scholar
- Kurn N, Chen P, Heath JD, Kopf-Sill A, Stephens KM, Wang S: Novel isothermal, linear nucleic acid amplification systems for highly multiplexed applications. Clin Chem. 2005, 51 (10): 1973-1981. 10.1373/clinchem.2005.053694.View ArticlePubMedGoogle Scholar
- Vermeulen J, De Preter K, Naranjo A, Vercruysse L, Van Roy N, Hellemans J, Swerts K, Bravo S, Scaruffi P, Tonini GP, et al: Predicting outcomes for children with neuroblastoma using a multigene-expression signature: a retrospective SIOPEN/COG/GPOH study. Lancet Oncol. 2009, 10 (7): 663-671. 10.1016/S1470-2045(09)70154-8.PubMed CentralView ArticlePubMedGoogle Scholar
- Shi L, Reid LH, Jones WD, Shippy R, Warrington JA, Baker SC, Collins PJ, de Longueville F, Kawasaki ES, Lee KY, et al: The MicroArray Quality Control (MAQC) project shows inter- and intraplatform reproducibility of gene expression measurements. Nat Biotechnol. 2006, 24 (9): 1151-1161. 10.1038/nbt1239.View ArticlePubMedGoogle Scholar
- Nolan T, Hands RE, Ogunkolade W, Bustin SA: SPUD: a quantitative PCR assay for the detection of inhibitors in nucleic acid preparations. Anal Biochem. 2006, 351 (2): 308-310. 10.1016/j.ab.2006.01.051.View ArticlePubMedGoogle Scholar
- Lefever S, Vandesompele J, Speleman F, Pattyn F: RTPrimerDB: the portal for real-time PCR primers and probes. Nucleic Acids Res. 2009, D942-945. 10.1093/nar/gkn777. 37 Database
- The MYCNot database. [http://medgen.ugent.be/MYCNot]
- Zhao S, Fernald RD: Comprehensive algorithm for quantitative real-time polymerase chain reaction. J Comput Biol. 2005, 12 (8): 1047-1064. 10.1089/cmb.2005.12.1047.PubMed CentralView ArticlePubMedGoogle Scholar
- Ruijter JM, Ramakers C, Hoogaars WM, Karlen Y, Bakker O, Hoff van den MJ, Moorman AF: Amplification efficiency: linking baseline and bias in the analysis of quantitative PCR data. Nucleic Acids Res. 2009, 37 (6): e45-10.1093/nar/gkp045.PubMed CentralView ArticlePubMedGoogle Scholar
- Goff LA, Bowers J, Schwalm J, Howerton K, Getts RC, Hart RP: Evaluation of sense-strand mRNA amplification by comparative quantitative PCR. BMC Genomics. 2004, 5 (1): 76-10.1186/1471-2164-5-76.PubMed CentralView ArticlePubMedGoogle Scholar
- Fleige S, Pfaffl MW: RNA integrity and the effect on the real-time qRT-PCR performance. Mol Aspects Med. 2006, 27 (2-3): 126-139. 10.1016/j.mam.2005.12.003.View ArticlePubMedGoogle Scholar
- Perez-Novo CA, Claeys C, Speleman F, Van Cauwenberge P, Bachert C, Vandesompele J: Impact of RNA quality on reference gene expression stability. Biotechniques. 2005, 39 (1): 52-54. 10.2144/05391BM05. 56View ArticlePubMedGoogle Scholar