Identification of a set of endogenous reference genes for miRNA expression studies in Parkinson's disease blood samples

BMC Research Notes

Volumn 7, Issue 1, 2014, Pages

  Serafin, Alice ^a   Foco, Luisa ^a   Blankenburg, Hagen ^a   Picard, Anne ^a   Zanigni, Stefano ^a   Zanon, Alessandra ^a   Pramstaller, Peter P ^a,c,d   Hicks, Andrew A ^a   Schwienbacher, Christine ^a,b  

^a University of Lubeck   (Italy)

^b Institute of the University of Löbeck   (Germany)

^c General Central Hospital   (Italy)

^d University of Löbeck   (Germany)

Author keywords

Comparative delta Ct; geNorm algorithm; Normfinder algorithm; qRT PCR; snoRNA; snRNA

Indexed keywords

GENETIC MARKER; MICRORNA;

ALGORITHM; BLOOD; CALIBRATION; CASE CONTROL STUDY; COMPARATIVE STUDY; DNA MICROARRAY; EVALUATION STUDY; GENE EXPRESSION PROFILING; GENETIC DATABASE; GENETIC MARKER; GENETICS; HUMAN; PARKINSON DISEASE; PREDICTIVE VALUE; PROCEDURES; REAL TIME POLYMERASE CHAIN REACTION; REPRODUCIBILITY; STANDARD; STANDARDS;

ALGORITHMS; CALIBRATION; CASE-CONTROL STUDIES; DATABASES, GENETIC; GENE EXPRESSION PROFILING; GENETIC MARKERS; HUMANS; MICRORNAS; OLIGONUCLEOTIDE ARRAY SEQUENCE ANALYSIS; PARKINSON DISEASE; PREDICTIVE VALUE OF TESTS; REAL-TIME POLYMERASE CHAIN REACTION; REFERENCE STANDARDS; REPRODUCIBILITY OF RESULTS;

EID: 84932135606     PISSN: None     EISSN: 17560500     Source Type: Journal    
DOI: 10.1186/1756-0500-7-715     Document Type: Article

References (36)

1. Saini HK, Griffiths-Jones S, Enright AJ: Genomic analysis of human microRNA transcripts. Proc Natl Acad Sci U S A 2007, 104(45):17719-17724.
2. Bartel DP: MicroRNAs: genomics, biogenesis, mechanism, and function. Cell 2004, 116(2):281-297.
3. Heyer MP, Pani AK, Smeyne RJ, Kenny PJ, Feng G: Normal midbrain dopaminergic neuron development and function in miR-133b mutant mice. J Neurosci 2012, 32(32):10887-10894.
4. Bras J, Singleton A, Cookson MR, Hardy J: Emerging pathways in genetic Parkinson's disease: Potential role of ceramide metabolism in Lewy body disease. FEBS J 2008, 275(23):5767-5773.
5. Shtilbans A, Henchcliffe C: Biomarkers in Parkinson's disease: An update. Curr Opin Neurol 2012, 25(4):460-465.
6. Liew CC, Ma J, Tang HC, Zheng R, Dempsey AA: The peripheral blood transcriptome dynamically reflects system wide biology: A potential diagnostic tool. J Lab Clin Med 2006, 147(3):126-132.
7. Margis R, Margis R, Rieder CR: Identification of blood microRNAs associated to Parkinsonis disease. J Biotechnol 2011, 152(3):96-101.
8. Martins M, Rosa A, Guedes LC, Fonseca BV, Gotovac K, Violante S, Mestre T, Coelho M, Rosa MM, Martin ER, Vance JM, Outeiro TF, Wang L, Borovecki F, Ferreira JJ, Oliveira SA: Convergence of miRNA expression profiling, alpha-synuclein interacton and GWAS in Parkinson's disease. PLoS One 2011, 6(10):e25443.
9. Kang K, Peng X, Luo J, Gou D: Identification of circulating miRNA biomarkers based on global quantitative real-Time PCR profiling. J Anim Sci Biotechnol 2012, 3(1):1-9.
10. D'haene B, Mestdagh P, Hellemans J, Vandesompele J: miRNA expression profiling: from reference genes to global mean normalization. Methods Mol Biol 2012, 822:261-272.
11. Hellemans J, Vandesompele J: qPCR data analysis-unlocking the secret to successful results. In PCR Troubleshooting and Optimization: The Essential Guide. Edited by Suzanne K, Nick O. Poole (UK): MO BIO Laboratories. Caister Academic Press; 2011:1-13.
12. Wotschofsky Z, Meyer HA, Jung M, Fendler A, Wagner I, Stephan C, Busch J, Erbersdobler A, Disch AC, Mollenkopf HJ, Jung K: Reference genes for the relative quantification of microRNAs in renal cell carcinomas and their metastases. Anal Biochem 2011, 417(2):233-241.
13. Sanders I, Holdenrieder S, Walgenbach-Brunagel G, von Ruecker A, Kristiansen G, Muller SC, Ellinger J: Evaluation of reference genes for the analysis of serum miRNA in patients with prostate cancer, bladder cancer and renal cell carcinoma. Int J Urol 2012, 19(11):1017-1025.
14. 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(7):1-12.
15. Peltier HJ, Latham GJ: Normalization of microRNA expression levels in quantitative RT-PCR assays: identification of suitable reference RNA targets in normal and cancerous human solid tissues. RNA 2008, 14(5):844-852.
16. Latham G: Normalization of MicroRNA Quantitative RT-PCR Data in Reduced Scale Experimental Designs. In MicroRNAs and the Immune System: Methods and Protocols, Methods in Molecular Biology. Volume 667. Edited by Monticelli S, Springer Science+Business Media. New York: Humana Press; 2010:19-31.
17. Gee HE, Buffa FM, Camps C, Ramachandran A, Leek R, Taylor M, Patil M, Sheldon H, Betts G, Homer J, West C, Ragoussis J, Harris AL: The small-nucleolar RNAs commonly used for microRNA normalisation correlate with tumour pathology and prognosis. Br J Cancer 2011, 104(7):1168-1177.
18. Khoo SK, Petillo D, Kang UJ, Resau JH, Berryhill B, Linder J, Forsgren L, Neuman LA, Tan AC: Plasma-Based Circulating MicroRNA Biomarkers for Parkinson's Disease. J Parkinson's Dis 2012, 2:321-331.
19. Cardo LF, Coto E, de Mena L, Ribacoba R, Moris G, Menendez M, Alvarez V: Profile of microRNAs in the plasma of Parkinson's disease patients and healthy controls. J Neurol 2013, 260(5):1420-1422.
20. Silver N, Best S, Jiang J, Thein SL: Selection of housekeeping genes for gene expression studies in human reticulocytes using real-Time PCR. BMC Mol Biol 2006, 7:33.
21. Andersen CL, Jensen JL, Orntoft TF: Normalization of real-Time quantitative reverse transcription-PCR data: A model-based variance estimation approach to identify genes suited for normalization, applied to bladder and colon cancer data sets. Cancer Res 2004, 64(15):5245-5250.
22. Gelb DJ, Oliver E, Gilman S: Diagnostic criteria for Parkinson disease. Arch Neurol 1999, 56(1):33-39.
23. Tukey JW: Exploratory Data Analysis. Boston: Anonymous Addison-Wesley Publishing Company, Reading, MA; 1977.
24. StataCorp: Stata Statistical Software: Release 12. College Station, TX: StataCorp LP; 2011.
25. Dheda K, Huggett JF, Bustin SA, Johnson MA, Rook G, Zumla A: Validation of housekeeping genes for normalizing RNA expression in real-Time PCR. Biotechniques 2004, 37(1):112.-4, 116, 118-9.
26. Valente V, Teixeira SA, Neder L, Okamoto OK, Oba-Shinjo SM, Marie SK, Scrideli CA, Paco-Larson ML, Carlotti CG Jr: Selection of suitable housekeeping genes for expression analysis in glioblastoma using quantitative RT-PCR. BMC Mol Biol 2009, 10:17-2199. 10-17.
27. Benn CL, Fox H, Bates GP: Optimisation of region-specific reference gene selection and relative gene expression analysis methods for pre-clinical trials of Huntington's disease. Mol Neurodegener 2008, 3:1-17.
28. Glare EM, Divjak M, Bailey MJ, Walters EH: beta-Actin and GAPDH housekeeping gene expression in asthmatic airways is variable and not suitable for normalising mRNA levels. Thorax 2002, 57(9):765-770.
29. Sikand K, Singh J, Ebron JS, Shukla GC: Housekeeping gene selection advisory: glyceraldehyde-3-phosphate dehydrogenase (GAPDH) and beta-Actin are targets of miR-644a. PLoS One 2012, 7(10):e47510.
30. Moncini S, Salvi A, Zuccotti P, Viero G, Quattrone A, Barlati S, De Petro G, Venturin M, Riva P: The role of miR-103 and miR-107 in regulation of CDK5R1 expression and in cellular migration. PLoS One 2011, 6(5):e20038.
31. Smith PD, Crocker SJ, Jackson-Lewis V, Jordan-Sciutto KL, Hayley S, Mount MP, O'Hare MJ, Callaghan S, Slack RS, Przedborski S, Anisman H, Park DS: Cyclin-dependent kinase 5 is a mediator of dopaminergic neuron loss in a mouse model of Parkinson's disease. Proc Natl Acad Sci U S A 2003, 100(23):13650-13655.
32. Wang WX, Rajeev BW, Stromberg AJ, Ren N, Tang G, Huang Q, Rigoutsos I, Nelson PT: The expression of microRNA miR-107 decreases early in Alzheimer's disease and may accelerate disease progression through regulation of beta-site amyloid precursor protein-cleaving enzyme 1. J Neurosci 2008, 28(5):1213-1223.
33. Trajkovski M, Hausser J, Soutschek J, Bhat B, Akin A, Zavolan M, Heim MH, Stoffel M: MicroRNAs 103 and 107 regulate insulin sensitivity. Nature 2011, 474(7353):649-653.
34. Herrera BM, Lockstone HE, Taylor JM, Ria M, Barrett A, Collins S, Kaisaki P, Argoud K, Fernandez C, Travers ME, Grew JP, Randall JC, Gloyn AL, Gauguier D, McCarthy MI, Lindgren CM: Global microRNA expression profiles in insulin target tissues in a spontaneous rat model of type 2 diabetes. Diabetologia 2010, 53(6):1099-1109.
35. Noren Hooten N, Abdelmohsen K, Gorospe M, Ejiogu N, Zonderman AB, Evans MK: microRNA expression patterns reveal differential expression of target genes with age. PLoS One 2010, 5(5):e10724.
36. Lim QE, Zhou L, Ho YK, Wan G, Too HP: snoU6 and 5S RNAs are not reliable miRNA reference genes in neuronal differentiation. Neuroscience 2011, 199:32-43.