Pre-amplification in the context of high-throughput qPCR gene expression experiment
Tóm tắt
With the introduction of the first high-throughput qPCR instrument on the market it became possible to perform thousands of reactions in a single run compared to the previous hundreds. In the high-throughput reaction, only limited volumes of highly concentrated cDNA or DNA samples can be added. This necessity can be solved by pre-amplification, which became a part of the high-throughput experimental workflow. Here, we focused our attention on the limits of the specific target pre-amplification reaction and propose the optimal, general setup for gene expression experiment using BioMark instrument (Fluidigm). For evaluating different pre-amplification factors following conditions were combined: four human blood samples from healthy donors and five transcripts having high to low expression levels; each cDNA sample was pre-amplified at four cycles (15, 18, 21, and 24) and five concentrations (equivalent to 0.078 ng, 0.32 ng, 1.25 ng, 5 ng, and 20 ng of total RNA). Factors identified as critical for a success of cDNA pre-amplification were cycle of pre-amplification, total RNA concentration, and type of gene. The selected pre-amplification reactions were further tested for optimal Cq distribution in a BioMark Array. The following concentrations combined with pre-amplification cycles were optimal for good quality samples: 20 ng of total RNA with 15 cycles of pre-amplification, 20x and 40x diluted; and 5 ng and 20 ng of total RNA with 18 cycles of pre-amplification, both 20x and 40x diluted. We set up upper limits for the bulk gene expression experiment using gene expression Dynamic Array and provided an easy-to-obtain tool for measuring of pre-amplification success. We also showed that variability of the pre-amplification, introduced into the experimental workflow of reverse transcription-qPCR, is lower than variability caused by the reverse transcription step.
Tài liệu tham khảo
Spurgeon SL, Jones RC, Ramakrishnan R. High throughput gene expression measurement with real time PCR in a microfluidic dynamic array. PLoS One. 2008;3:e1662.
BioMark™ HD System. [http://www.fluidigm.com/biomark-hd-system.html]
Real-Time PCR Using OpenArray® Technology. [http://www.lifetechnologies.com/au/en/home/life-science/pcr/real-time-pcr/real-time-openarray.html?icid=fr-openarray-main%20http://www.lifetechnologies.com/au/en/home/life-science/pcr/real-time-pcr/real-time-openarray.html?icid=fr-openarray-main]
SmartChip Real-Time PCR System. [http://www.wafergen.com/products/smartchip-realtime-pcr-system]
Mengual L, Burset M, Marin-Aguilera M, Ribal MJ, Alcaraz A. Multiplex preamplification of specific cDNA targets prior to gene expression analysis by TaqMan Arrays. BMC Res notes. 2008;1:21.
Blow N. PCR’s next frontier. Nat Meth. 2007;4:869–75.
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;20:940–3.
Noutsias M, Rohde M, Block A, Klippert K, Lettau O, Blunert K, et al. Preamplification techniques for real-time RT-PCR analyses of endomyocardial biopsies. BMC Mol Biol. 2008;9:3.
Sindelka R, Sidova M, Svec D, Kubista M. Spatial expression profiles in the Xenopus laevis oocytes measured with qPCR tomography. Methods (San Diego, Calif). 2010;51:87–91.
Fluidigm. Real-Time PCR Analysis, Appendix B: Fast Gene Expression Analysis Using EvaGreen on the BioMark of BioMark HD System, part No. 68000088. [https://www.fluidigm.com/documents]
TaqMan PreAmp Master Mix Kit, Protocol. [http://tools.lifetechnologies.com/content/sfs/manuals/cms_039316.pdf]
Targeted Enrichment of Limited RNA Samples via Pre-Amplification Prior to Analysis in the WaferGen SmartChip Real-Time PCR System. [http://www.wafergen.com/wp-content/uploads/2013/01/TargetEnrchmnt_RNA_TNf.pdf]
OpenArray Plates for microRNA expression analysis. [http://tools.lifetechnologies.com/content/sfs/manuals/cms_092509.pdf]
Johnson G, Nour AA, Nolan T, Huggett J, Bustin S. Minimum information necessary for quantitative real-time PCR experiments. Methods Mol Biol (Clifton, NJ). 2014;1160:5–17.
Bustin SA, Benes V, Garson JA, Hellemans J, Huggett J, Kubista M, et al. The MIQE guidelines: minimum information for publication of quantitative real-time PCR experiments. Clin Chem. 2009;55:611–22.
Rusnakova V, Honsa P, Dzamba D, Stahlberg A, Kubista M, Anderova M. Heterogeneity of astrocytes: from development to injury - single cell gene expression. PLoS One. 2013;8:e69734.
Laurell H, Iacovoni JS, Abot A, Svec D, Maoret JJ, Arnal JF, et al. Correction of RT-qPCR data for genomic DNA-derived signals with ValidPrime. Nucleic Acids Res. 2012;40:e51.
Stahlberg A, Kubista M. The workflow of single-cell expression profiling using quantitative real-time PCR. Expert Rev Mol Diagn. 2014;14:323–31.
Fluidigm. Fluidigm Gene Expression Specific Target Amplification Quick Reference, part No. 68000133. [https://www.fluidigm.com/documents]
Fluidigm. BioMark Advanced Development Protocol Number 5: Single-Cell Gene Expression Protocol for the BioMark 48.48 Dynamic Array–Real-Time PCR, part No. 68000107. [https://www.fluidigm.com/documents]
Stahlberg A, Bengtsson M. Single-cell gene expression profiling using reverse transcription quantitative real-time PCR. Methods (San Diego, Calif). 2010;50:282–8.
Chen Y, Gelfond JA, McManus LM, Shireman PK. Reproducibility of quantitative RT-PCR array in miRNA expression profiling and comparison with microarray analysis. BMC Genomics. 2009;10:407.
Li J, Smyth P, Cahill S, Denning K, Flavin R, Aherne S, et al. Improved RNA quality and TaqMan Pre-amplification method (PreAmp) to enhance expression analysis from formalin fixed paraffin embedded (FFPE) materials. BMC Biotechnol. 2008;8:10.
Fox BC, Devonshire AS, Baradez MO, Marshall D, Foy CA. Comparison of reverse transcription-quantitative polymerase chain reaction methods and platforms for single cell gene expression analysis. Anal Biochem. 2012;427:178–86.
Bengtsson M, Hemberg M, Rorsman P, Stahlberg A. Quantification of mRNA in single cells and modelling of RT-qPCR induced noise. BMC Mol Biol. 2008;9:63.
Devonshire AS, Elaswarapu R, Foy CA. Applicability of RNA standards for evaluating RT-qPCR assays and platforms. BMC Genomics. 2011;12:118.
Jang JS, Kolbert C, Jen J. High throughput quantitative PCR using low-input samples for mRNA and MicroRNA gene expression analyses [abstract]. J Biomol Tech. 2013;24:S56.
Svec D, Rusnakova V, Korenkova V, Kubista M. Dye-Based High-Throughput qPCR in Microfluidic Platform BioMark™. In: Nolan T, Bustin SA, editors. PCR Technology: Current Innovations. 3rd ed. Boca Raton: CRC Press; 2013. p. 323–36.
Sorg D, Danowski K, Korenkova V, Rusnakova V, Kuffner R, Zimmer R, et al. Microfluidic high-throughput RT-qPCR measurements of the immune response of primary bovine mammary epithelial cells cultured from milk to mastitis pathogens. Animal. 2013;7:799–805.
Perkel JM. Microfluidics, macro-impacts. Biotechniques. 2012;52:131–4.
Morrison TB, Weis JJ, Wittwer CT. Quantification of low-copy transcripts by continuous SYBR Green I monitoring during amplification. Biotechniques. 1998;24:954–8. 960, 962.
Stahlberg A, Hakansson J, Xian X, Semb H, Kubista M. Properties of the reverse transcription reaction in mRNA quantification. Clin Chem. 2004;50:509–15.
Primer-BLAST. [http://www.ncbi.nlm.nih.gov/tools/primer-blast/index.cgi?LINK_LOC=BlastHome]
Jolliffe IT. Principal Component Analysis. 2nd ed. Springer-Verlag New York: Springer; 2002.
Kohonen Teuvo. Self-Organizing Maps. 3rd ed. Springer-Verlag Berlin Heidelberg: Springer; 2001.