An optimized protocol for microarray validation by quantitative PCR using amplified amino allyl labeled RNA

Springer Science and Business Media LLC - Tập 11 - Trang 1-13 - 2010
Céline Jeanty1, Dan Longrois2, Paul-Michel Mertes3, Daniel R Wagner1,4, Yvan Devaux1
1Laboratory of Cardiovascular Research, Centre de Recherche Public-Santé, Luxembourg, France
2Department of Anesthesia and Intensive Care, Hopital Bichat-Claude-Bernard, Université Paris-VII, France
3Department of Anesthesia and Intensive Care, Centre Hospitalier et Universitaire de Nancy, Nancy, France
4Division of Cardiology, Centre Hospitalier, Luxembourg, France

Tóm tắt

Validation of microarrays data by quantitative real-time PCR (qPCR) is often limited by the low amount of available RNA. This raised the possibility to perform validation experiments on the amplified amino allyl labeled RNA (AA-aRNA) leftover from microarrays. To test this possibility, we used an ongoing study of our laboratory aiming at identifying new biomarkers of graft rejection by the transcriptomic analysis of blood cells from brain-dead organ donors. qPCR for ACTB performed on AA-aRNA from 15 donors provided Cq values 8 cycles higher than when original RNA was used (P < 0.001), suggesting a strong inhibition of qPCR performed on AA-aRNA. When expression levels of 5 other genes were measured in AA-aRNA generated from a universal reference RNA, qPCR sensitivity and efficiency were decreased. This prevented the quantification of one low-abundant gene, which was readily quantified in un-amplified and un-labeled RNA. To overcome this limitation, we modified the reverse transcription (RT) protocol that generates cDNA from AA-aRNA as follows: addition of a denaturation step and 2-min incubation at room temperature to improve random primers annealing, a transcription initiation step to improve RT, and a final treatment with RNase H to degrade remaining RNA. Tested on universal reference AA-aRNA, these modifications provided a gain of 3.4 Cq (average from 5 genes, P < 0.001) and an increase of qPCR efficiency (from -1.96 to -2.88; P = 0.02). They also allowed for the detection of a low-abundant gene that was previously undetectable. Tested on AA-aRNA from 15 brain-dead organ donors, RT optimization provided a gain of 2.7 cycles (average from 7 genes, P = 0.004). Finally, qPCR results significantly correlated with microarrays. We present here an optimized RT protocol for validation of microarrays by qPCR from AA-aRNA. This is particularly valuable in experiments where limited amount of RNA is available.

Tài liệu tham khảo

Valk PJ, Verhaak RG, Beijen MA, Erpelinck CA, Barjesteh van Waalwijk van Doorn-Khosrovani S, Boer JM, Beverloo HB, Moorhouse MJ, van der Spek PJ, Lowenberg B, Delwel R: Prognostically useful gene-expression profiles in acute myeloid leukemia. N Engl J Med. 2004, 350: 1617-1628. 10.1056/NEJMoa040465.

Bullinger L, Dohner K, Bair E, Frohling S, Schlenk RF, Tibshirani R, Dohner H, Pollack JR: Use of gene-expression profiling to identify prognostic subclasses in adult acute myeloid leukemia. N Engl J Med. 2004, 350: 1605-1616. 10.1056/NEJMoa031046.

Moore DF, Li H, Jeffries N, Wright V, Cooper RA, Elkahloun A, Gelderman MP, Zudaire E, Blevins G, Yu H, Goldin E, Baird AE: Using peripheral blood mononuclear cells to determine a gene expression profile of acute ischemic stroke: a pilot investigation. Circulation. 2005, 111: 212-221. 10.1161/01.CIR.0000152105.79665.C6.

Wingrove JA, Daniels SE, Sehnert AJ, Tingley W, M E, Rosenberger S, Buellesfeld L, Grube E, Newby LK, Ginsburg GS, Kraus WE: Correlation of Peripheral-Blood Gene Expression With the Extent of Coronary Artery Stenosis. Circ Cardiovasc Genet. 2008, 1: 31-38. 10.1161/CIRCGENETICS.108.782730.

Feezor RJ, Baker HV, Mindrinos M, Hayden D, Tannahill CL, Brownstein BH, Fay A, MacMillan S, Laramie J, Xiao W, Moldawer LL, Cobb JP, Laudanski K, Miller-Graziano CL, Maier RV, Schoenfeld D, Davis RW, Tompkins RG: Whole blood and leukocyte RNA isolation for gene expression analyses. Physiol Genomics. 2004, 19: 247-254. 10.1152/physiolgenomics.00020.2004.

Rainen L, Oelmueller U, Jurgensen S, Wyrich R, Ballas C, Schram J, Herdman C, Bankaitis-Davis D, Nicholls N, Trollinger D, Tryon V: Stabilization of mRNA expression in whole blood samples. Clin Chem. 2002, 48: 1883-1890.

Kagedal B, Lindqvist M, Farneback M, Lenner L, Peterson C: Failure of the PAXgene Blood RNA System to maintain mRNA stability in whole blood. Clin Chem Lab Med. 2005, 43: 1190-1192. 10.1515/CCLM.2005.206.

Livesey FJ: Strategies for microarray analysis of limiting amounts of RNA. Brief Funct Genomic Proteomic. 2003, 2: 31-36. 10.1093/bfgp/2.1.31.

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: 1663-1667. 10.1073/pnas.87.5.1663.

Croner RS, Lausen B, Schellerer V, Zeittraeger I, Wein A, Schildberg C, Papadopoulos T, Dimmler A, Hahn EG, Hohenberger W, Brueckl WM: Comparability of microarray data between amplified and non amplified RNA in colorectal carcinoma. J Biomed Biotechnol. 2009, 2009: 837170-

Duftner N, Larkins-Ford J, Legendre M, Hofmann HA: Efficacy of RNA amplification is dependent on sequence characteristics: implications for gene expression profiling using a cDNA microarray. Genomics. 2008, 91: 108-117. 10.1016/j.ygeno.2007.09.004.

Degrelle SA, Hennequet-Antier C, Chiapello H, Piot-Kaminski K, Piumi F, Robin S, Renard JP, Hue I: Amplification biases: possible differences among deviating gene expressions. BMC Genomics. 2008, 9: 46-10.1186/1471-2164-9-46.

Kerkhoven RM, Sie D, Nieuwland M, Heimerikx M, De Ronde J, Brugman W, Velds A: The T7-primer is a source of experimental bias and introduces variability between microarray platforms. PLoS One. 2008, 3: e1980-10.1371/journal.pone.0001980.

Waddell SJ, Laing K, Senner C, Butcher PD: Microarray analysis of defined Mycobacterium tuberculosis populations using RNA amplification strategies. BMC Genomics. 2008, 9: 94-10.1186/1471-2164-9-94.

Rajeevan MS, Vernon SD, Taysavang N, Unger ER: Validation of array-based gene expression profiles by real-time (kinetic) RT-PCR. J Mol Diagn. 2001, 3: 26-31.

Land WG: The role of postischemic reperfusion injury and other nonantigen-dependent inflammatory pathways in transplantation. Transplantation. 2005, 79: 505-514. 10.1097/01.TP.0000153160.82975.86.

Jurata LW, Bukhman YV, Charles V, Capriglione F, Bullard J, Lemire AL, Mohammed A, Pham Q, Laeng P, Brockman JA, Altar CA: Comparison of microarray-based mRNA profiling technologies for identification of psychiatric disease and drug signatures. J Neurosci Methods. 2004, 138: 173-188. 10.1016/j.jneumeth.2004.04.002.

Reinders ME, Rabelink TJ, Briscoe DM: Angiogenesis and endothelial cell repair in renal disease and allograft rejection. J Am Soc Nephrol. 2006, 17: 932-942. 10.1681/ASN.2005121250.

Polumuri SK, Ruknudin A, Schulze DH: RNase H and its effects on PCR. Biotechniques. 2002, 32: 1224-1225.

Kitabayashi M, Esaka M: Improvement of reverse transcription PCR by RNase H. Biosci Biotechnol Biochem. 2003, 67: 2474-2476. 10.1271/bbb.67.2474.

Gerszten RE, Wang TJ: The search for new cardiovascular biomarkers. Nature. 2008, 451: 949-952. 10.1038/nature06802.

Dallas PB, Gottardo NG, Firth MJ, Beesley AH, Hoffmann K, Terry PA, Freitas JR, Boag JM, Cummings AJ, Kees UR: Gene expression levels assessed by oligonucleotide microarray analysis and quantitative real-time RT-PCR -- how well do they correlate?. BMC Genomics. 2005, 6: 59-10.1186/1471-2164-6-59.

Morey JS, Ryan JC, Van Dolah FM: Microarray validation: factors influencing correlation between oligonucleotide microarrays and real-time PCR. Biol Proced Online. 2006, 8: 175-193. 10.1251/bpo126.

Azuaje F, Devaux Y, Wagner DR: Identification of potential targets in biological signalling systems through network perturbation analysis. Biosystems. 2010, 100 (1): 55-64. 10.1016/j.biosystems.2010.01.002.

Azuaje F, Devaux Y, Wagner D: Computational biology for cardiovascular biomarker discovery. Brief Bioinform. 2009, 10: 367-377. 10.1093/bib/bbp008.

Cohen S, Tuppin P, Pessione F, Jacob F, Claquin J: Aspects historiques, réglementaires et épidémiologiques de la mort encéphalique, Prise en charge des sujets en état de mort encéphalique dans l'optique du prélèvement d'organes et de tissus. Edited by: Boulard G, Guiot P, Pottecher T, Tenaillon A. 2005, Elsevier SAS, 35-50.

Le Brigand K, Russell R, Moreilhon C, Rouillard JM, Jost B, Amiot F, Magnone V, Bole-Feysot C, Rostagno P, Virolle V, Defamie V, Dessen P, Williams G, Lyons P, Rios G, Mari B, Gulari E, Kastner P, Gidrol X, Freeman TC, Barbry P: An open-access long oligonucleotide microarray resource for analysis of the human and mouse transcriptomes. Nucleic Acids Res. 2006, 34: e87-10.1093/nar/gkl485.

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