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MicroRNAs and Reference Gene Methodology

  • Petra MatouškováEmail author
Reference work entry

Abstract

microRNAs (miRNAs), short noncoding RNAs, are posttranscriptional negative regulators, with extracellular circulating miRNAs considered promising biomarkers of various diseases. The relative quantification of miRNA transcripts requires an endogenous reference gene for data normalization, which is the critical step in this process. In the present chapter, the means of normalization and methods for the selection of suitable reference gene(s) are discussed, with a key finding being how common reference genes such as RNU6 and miR-16 can cause bias in data interpretation if used without proper validation.

Keywords

microRNA qPCR Reference gene Normalization RNU6 miR-16 Circulating miRNA geNorm BestKeeper NormFinder miRBase Absolute quantification Relative quantification MIQE guidelines 

List of Abbreviations

18S

Ribosomal RNA 18S

5S

Ribosomal RNA 5S

ACT

Actin

Cq

Quantitation cycle

FFPE

Formalin-fixed paraffin-embedded

GAPDH

Glyceraldehyde 3-phosphate dehydrogenase

LNA

Locked nucleic acid

MIQE

Minimum information for publication of quantitative real-time PCR experiments

miRNA

microRNA

qPCR

Quantitative real-time polymerase chain reaction

References

  1. Ambros V, Bartel B, Bartel DP, Burge CB, Carrington JC, Chen XM, Dreyfuss G, Eddy SR, Griffiths-Jones S, Marshall M, Matzke M, Ruvkun G, Tuschl T (2003) A uniform system for microRNA annotation. RNA 9:277–279.  https://doi.org/10.1261/rna.2183803CrossRefPubMedPubMedCentralGoogle Scholar
  2. Andersen CL, Jensen JL, Ørntoft TF (2004) 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 64:5245–5250.  https://doi.org/10.1158/0008-5472.CAN-04-0496CrossRefPubMedGoogle Scholar
  3. Ansari MH, Irani S, Edalat H, Amin R, Roushandeh AM (2016) Deregulation of miR-93 and miR-143 in human esophageal cancer. Tumor Biol 37:3097–3103.  https://doi.org/10.1007/s13277-015-3987-9CrossRefGoogle Scholar
  4. Barry SE, Chan B, Ellis M, Yang YR, Plit ML, Guan GY, Wang XL, Britton WJ, Saunders BM (2015) Identification of miR-93 as a suitable miR for normalizing miRNA in plasma of tuberculosis patients. J Cell Mol Med 19:1606–1613.  https://doi.org/10.1111/jcmm.12535CrossRefPubMedPubMedCentralGoogle Scholar
  5. Bartel DP (2004) MicroRNAs: genomics, biogenesis, mechanism, and function. Cell 116:281–297.  https://doi.org/10.1016/s0092-8674(04)00045-5CrossRefPubMedPubMedCentralGoogle Scholar
  6. Benz F, Roderburg C, Cardenas DV, Vucur M, Gautheron J, Koch A, Zimmermann H, Janssen J, Nieuwenhuijsen L, Luedde M, Frey N, Tacke F, Trautwein C, Luedde T (2013) U6 is unsuitable for normalization of serum miRNA levels in patients with sepsis or liver fibrosis. Exp Mol Med 45.  https://doi.org/10.1038/emm.2013.81
  7. Bustin SA, Benes V, Garson JA, Hellemans J, Huggett J, Kubista M, Mueller R, Nolan T, Pfaffl MW, Shipley GL, Vandesompele J, Wittwer CT (2009) The MIQE guidelines: minimum information for publication of quantitative real-time PCR experiments. Clin Chem 55:611–622.  https://doi.org/10.1373/clinchem.2008.112797CrossRefPubMedGoogle Scholar
  8. Chakraborty C, Das S (2016) Profiling cell-free and circulating miRNA: a clinical diagnostic tool for different cancers. Tumour Biol 37:5705–5714.  https://doi.org/10.1007/s13277-016-4907-3CrossRefPubMedGoogle Scholar
  9. Chen CF, Ridzon DA, Broomer AJ, Zhou ZH, Lee DH, Nguyen JT, Barbisin M, Xu NL, Mahuvakar VR, Andersen MR, Lao KQ, Livak KJ, Guegler KJ (2005) Real-time quantification of microRNAs by stem-loop RT-PCR. Nucleic Acids Res 33.  https://doi.org/10.1093/nar/gni178
  10. Cheng XH, Ku CH, Siow RCM (2013) Regulation of the Nrf2 antioxidant pathway by microRNAs: new players in micromanaging redox homeostasis. Free Radic Biol Med 64:4–11.  https://doi.org/10.1016/j.freeradbiomed.2013.07.025CrossRefPubMedGoogle Scholar
  11. Cheng L, Doecke JD, Sharples RA, Villemagne VL, Fowler CJ, Rembach A, Martins RN, Rowe CC, Macaulay SL, Masters CL, Hill AF, Australian Imaging B, Lifestyle Research G (2015) Prognostic serum miRNA biomarkers associated with Alzheimer’s disease shows concordance with neuropsychological and neuroimaging assessment. Mol Psychiatry 20:1188–1196.  https://doi.org/10.1038/mp.2014.127CrossRefPubMedGoogle Scholar
  12. Cloutier F, Marrero A, O’connell C, Morin P (2015) MicroRNAs as potential circulating biomarkers for amyotrophic lateral sclerosis. J Mol Neurosci 56:102–112.  https://doi.org/10.1007/s12031-014-0471-8CrossRefPubMedGoogle Scholar
  13. D’angelo B, Benedetti E, Cimini A, Giordano A (2016) MicroRNAs: a puzzling tool in cancer diagnostics and therapy. Anticancer Res 36:5571–5575.  https://doi.org/10.21873/anticanres.11142CrossRefPubMedGoogle Scholar
  14. Das MK, Andreassen R, Haugen TB, Furu K (2016) Identification of endogenous controls for use in miRNA quantification in human cancer cell lines. Cancer Genomics Proteomics 13:63–68PubMedGoogle Scholar
  15. De Spiegelaere W, Dern-Wieloch J, Weigel R, Schumacher V, Schorle H, Nettersheim D, Bergmann M, Brehm R, Kliesch S, Vandekerckhove L, Fink C (2015) Reference gene validation for RT-qPCR, a note on different available software packages. PLoS One 10.  https://doi.org/10.1371/journal.pone.0122515
  16. Dheda K, Huggett JF, Chang JS, Kim LU, Bustin SA, Johnson MA, Rook GAW, Zumla A (2005) The implications of using an inappropriate reference gene for real-time reverse transcription PCR data normalization. Anal Biochem 344:141–143.  https://doi.org/10.1016/j.ab.2005.05.022CrossRefPubMedGoogle Scholar
  17. Dugas DV, Bartel B (2004) MicroRNA regulation of gene expression in plants. Curr Opin Plant Biol 7:512–520.  https://doi.org/10.1016/j.pbi.2004.07.011CrossRefPubMedGoogle Scholar
  18. Esquela-Kerscher A, Slack FJ (2006) Oncomirs – microRNAs with a role in cancer. Nat Rev Cancer 6:259–269.  https://doi.org/10.1038/nrc1840CrossRefPubMedGoogle Scholar
  19. Fierro-Fernandez M, Miguel V, Lamas S (2016) Role of redoximiRs in fibrogenesis. Redox Biol 7:58–67.  https://doi.org/10.1016/j.redox.2015.11.006CrossRefPubMedGoogle Scholar
  20. Garcia-Segura L, Perez-Andrade M, Miranda-Rios J (2013) The emerging role of microRNAs in the regulation of gene expression by nutrients. J Nutrigenet Nutrigenomics 6:16–31.  https://doi.org/10.1159/000345826CrossRefPubMedGoogle Scholar
  21. Griffiths-Jones S, Grocock RJ, Van Dongen S, Bateman A, Enright AJ (2006) miRBase: microRNA sequences, targets and gene nomenclature. Nucleic Acids Res 34:D140–D144.  https://doi.org/10.1093/nar/gkj112CrossRefPubMedGoogle Scholar
  22. Guduric-Fuchs J, O’connor A, Camp B, O’neill CL, Medina RJ, Simpson DA (2012) Selective extracellular vesicle-mediated export of an overlapping set of microRNAs from multiple cell types. BMC Genomics 13.  https://doi.org/10.1186/1471-2164-13-357
  23. Hellemans J, Mortier G, De Paepe A, Speleman F, Vandesompele J (2007) qBase relative quantification framework and software for management and automated analysis of real-time quantitative PCR data. Genome Biol 8:1–14CrossRefGoogle Scholar
  24. Hindson BJ, Ness KD, Masquelier DA, Belgrader P, Heredia NJ, Makarewicz AJ, Bright IJ, Lucero MY, Hiddessen AL, Legler TC, Kitano TK, Hodel MR, Petersen JF, Wyatt PW, Steenblock ER, Shah PH, Bousse LJ, Troup CB, Mellen JC, Wittmann DK, Erndt NG, Cauley TH, Koehler RT, So AP, Dube S, Rose KA, Montesclaros L, Wang SL, Stumbo DP, Hodges SP, Romine S, Milanovich FP, White HE, Regan JF, Karlin-Neumann GA, Hindson CM, Saxonov S, Colston BW (2011) High-throughput droplet digital PCR system for absolute quantitation of DNA copy number. Anal Chem 83:8604–8610.  https://doi.org/10.1021/ac202028gCrossRefPubMedPubMedCentralGoogle Scholar
  25. Hrustincova A, Votavova H, Merkerova MD (2015) Circulating microRNAs: methodological aspects in detection of these biomarkers. Folia Biol 61:203–218Google Scholar
  26. Lamba V, Ghodke-Puranik Y, Guan W, Lamba JK (2014) Identification of suitable reference genes for hepatic microRNA quantitation. BMC Res Notes 7:129.  https://doi.org/10.1186/1756-0500-7-129CrossRefPubMedPubMedCentralGoogle Scholar
  27. Lardizabal MN, Nocito AL, Daniele SM, Ornella LA, Palatnik JF, Veggi LM (2012) Reference genes for real-time PCR quantification of microRNAs and messenger RNAs in rat models of hepatotoxicity. PLoS One 7.  https://doi.org/10.1371/journal.pone.0036323
  28. Lee RC, Ambros V (2001) An extensive class of small RNAs in Caenorhabditis elegans. Science 294:862–864.  https://doi.org/10.1126/science.1065329CrossRefPubMedGoogle Scholar
  29. Li Y, Xiang GM, Liu LL, Liu C, Liu F, Jiang DN, Pu XY (2015a) Assessment of endogenous reference gene suitability for serum exosomal microRNA expression analysis in liver carcinoma resection studies. Mol Med Rep 12:4683–4691.  https://doi.org/10.3892/mmr.2015.3919CrossRefPubMedGoogle Scholar
  30. Li Y, Zhang L, Liu F, Xiang G, Jiang D, Pu X (2015b) Identification of endogenous controls for analyzing serum exosomal miRNA in patients with hepatitis B or hepatocellular carcinoma. Dis Markers 2015:893594.  https://doi.org/10.1155/2015/893594CrossRefPubMedPubMedCentralGoogle Scholar
  31. Liang Y, Ridzon D, Wong L, Chen C (2007) Characterization of microRNA expression profiles in normal human tissues. BMC Genomics 8:166.  https://doi.org/10.1186/1471-2164-8-166CrossRefPubMedPubMedCentralGoogle Scholar
  32. Lim QE, Zhou L, Ho YK, Wan G, Too HP (2011) snoU6 and 5S RNAs are not reliable miRNA reference genes in neuronal differentiation. Neuroscience 199:32–43.  https://doi.org/10.1016/j.neuroscience.2011.10.024CrossRefPubMedGoogle Scholar
  33. Liu XL, Zhang L, Cheng K, Wang X, Ren GP, Xie P (2014) Identification of suitable plasma-based reference genes for miRNAome analysis of major depressive disorder. J Affect Disord 163:133–139.  https://doi.org/10.1016/j.jad.2013.12.035CrossRefPubMedGoogle Scholar
  34. Lou G, Ma N, Xu Y, Jiang L, Yang J, Wang C, Jiao Y, Gao X (2015) Differential distribution of U6 (RNU6-1) expression in human carcinoma tissues demonstrates the requirement for caution in the internal control gene selection for microRNA quantification. Int J Mol Med 36:1400–1408.  https://doi.org/10.3892/ijmm.2015.2338CrossRefPubMedGoogle Scholar
  35. Ludwig N, Leidinger P, Becker K, Backes C, Fehlmann T, Pallasch C, Rheinheimer S, Meder B, Stahler C, Meese E, Keller A (2016) Distribution of miRNA expression across human tissues. Nucleic Acids Res 44:3865–3877.  https://doi.org/10.1093/nar/gkw116CrossRefPubMedPubMedCentralGoogle Scholar
  36. Mccarthy JJ (2008) MicroRNA-206: the skeletal muscle-specific myomiR. Biochim Biophys Acta 1779:682–691.  https://doi.org/10.1016/j.bbagrm.2008.03.001CrossRefPubMedPubMedCentralGoogle Scholar
  37. Mestdagh P, Van Vlierberghe P, De Weer A, Muth D, Westermann F, Speleman F, Vandesompele J (2009) A novel and universal method for microRNA RT-qPCR data normalization. Genome Biol 10.  https://doi.org/10.1186/gb-2009-10-6-r64
  38. Mitchell PS, Parkin RK, Kroh EM, Fritz BR, Wyman SK, Pogosova-Agadjanyan EL, Peterson A, Noteboom J, O’briant KC, Allen A, Lin DW, Urban N, Drescher CW, Knudsen BS, Stirewalt DL, Gentleman R, Vessella RL, Nelson PS, Martin DB, Tewari M (2008) Circulating microRNAs as stable blood-based markers for cancer detection. Proc Natl Acad Sci USA 105:10513–10518.  https://doi.org/10.1073/pnas.0804549105CrossRefPubMedGoogle Scholar
  39. Occhipinti G, Giulietti M, Principato G, Piva F (2016) The choice of endogenous controls in exosomal microRNA assessments from biofluids. Tumor Biol 37:11657–11665.  https://doi.org/10.1007/s13277-016-5164-1CrossRefGoogle Scholar
  40. Peltier HJ, Latham GJ (2008) Normalization of microRNA expression levels in quantitative RT-PCR assays: identification of suitable reference RNA targets in normal and cancerous human solid tissues. RNA 14:844–852.  https://doi.org/10.1261/rna.939908CrossRefPubMedPubMedCentralGoogle Scholar
  41. Pfaffl MW, Tichopad A, Prgomet C, Neuvians TP (2004) Determination of stable housekeeping genes, differentially regulated target genes and sample integrity: BestKeeper – excel-based tool using pair-wise correlations. Biotechnol Lett 26:509–515.  https://doi.org/10.1023/b:bile.0000019559.84305.47CrossRefPubMedGoogle Scholar
  42. Raymond CK, Roberts BS, Garrett-Engele P, Lim LP, Johnson JM (2005) Simple, quantitative primer-extension PCR assay for direct monitoring of microRNAs and short-interfering RNAs. RNA 11:1737–1744.  https://doi.org/10.1261/rna.2148705CrossRefPubMedPubMedCentralGoogle Scholar
  43. Rinnerthaler G, Hackl H, Gampenrieder SP, Hamacher F, Hufnagl C, Hauser-Kronberger C, Zehentmayr F, Fastner G, Sedlmayer F, Mlineritsch B, Greil R (2016) miR-16-5p is a stably-expressed housekeeping microRNA in breast cancer tissues from primary tumors and from metastatic sites. Int J Mol Sci 17:156.  https://doi.org/10.3390/ijms17020156CrossRefPubMedCentralGoogle Scholar
  44. Rome S (2015) Use of miRNAs in biofluids as biomarkers in dietary and lifestyle intervention studies. Genes Nutr 10:483.  https://doi.org/10.1007/s12263-015-0483-1CrossRefPubMedGoogle Scholar
  45. Sarkar D, Parkin R, Wyman S, Bendoraite A, Sather C, Delrow J, Godwin AK, Drescher C, Huber W, Gentleman R, Tewari M (2009) Quality assessment and data analysis for microRNA expression arrays. Nucleic Acids Res 37:e17.  https://doi.org/10.1093/nar/gkn932CrossRefPubMedGoogle Scholar
  46. Schaefer A, Jung M, Miller K, Lein M, Kristiansen G, Erbersdobler A, Jung K (2010) Suitable reference genes for relative quantification of miRNA expression in prostate cancer. Exp Mol Med 42:749–758.  https://doi.org/10.3858/emm.2010.42.11.07CrossRefPubMedPubMedCentralGoogle Scholar
  47. Schwarzenbach H, Da Silva AM, Calin G, Pantel K (2015) Data normalization strategies for microRNA quantification. Clin Chem 61:1333–1342.  https://doi.org/10.1373/clinchem.2015.239459CrossRefPubMedPubMedCentralGoogle Scholar
  48. Shen Y, Tian F, Chen Z, Li R, Ge Q, Lu Z (2015) Amplification-based method for microRNA detection. Biosens Bioelectron 71:322–331.  https://doi.org/10.1016/j.bios.2015.04.057CrossRefPubMedGoogle Scholar
  49. Silver N, Best S, Jiang J, Thein SL (2006) Selection of housekeeping genes for gene expression studies in human reticulocytes using real-time PCR. BMC Mol Biol 7.  https://doi.org/10.1186/1471-2199-7-33
  50. Song J, Bai Z, Han W, Zhang J, Meng H, Bi J, Ma X, Han S, Zhang Z (2012) Identification of suitable reference genes for qPCR analysis of serum microRNA in gastric cancer patients. Dig Dis Sci 57:897–904.  https://doi.org/10.1007/s10620-011-1981-7CrossRefPubMedGoogle Scholar
  51. Song H, Zhang X, Shi C, Wang S, Wu A, Wei C (2016) Selection and verification of candidate reference genes for mature microRNA expression by quantitative RT-PCR in the tea plant (Camellia sinensis). Genes (Basel) 7:25.  https://doi.org/10.3390/genes7060025CrossRefGoogle Scholar
  52. Takada S, Mano H (2007) Profiling of microRNA expression by mRAP. Nat Protoc 2:3136–3145.  https://doi.org/10.1038/nprot.2007.457CrossRefPubMedGoogle Scholar
  53. Tan YW, Ge GH, Pan TL, Wen DF, Gan JH (2015) Serum MiRNA panel as potential biomarkers for chronic hepatitis B with persistently normal alanine aminotransferase. Clin Chim Acta 451:232–239.  https://doi.org/10.1016/j.cca.2015.10.002CrossRefPubMedGoogle Scholar
  54. Tarallo S, Pardini B, Mancuso G, Rosa F, Di Gaetano C, Rosina F, Vineis P, Naccarati A (2014) MicroRNA expression in relation to different dietary habits: a comparison in stool and plasma samples. Mutagenesis 29:385–391.  https://doi.org/10.1093/mutage/geu028CrossRefPubMedGoogle Scholar
  55. Tian CO, Li ZF, Yang ZG, Huang QH, Liu JM, Hong B (2016) Plasma microRNA-16 is a biomarker for diagnosis, stratification, and prognosis of hyperacute cerebral infarction. PLoS One 11.  https://doi.org/10.1371/journal.pone.0166688
  56. Turchinovich A, Weiz L, Langheinz A, Burwinkel B (2011) Characterization of extracellular circulating microRNA. Nucleic Acids Res 39:7223–7233.  https://doi.org/10.1093/nar/gkr254CrossRefPubMedPubMedCentralGoogle Scholar
  57. Van Peer G, Lefever S, Anckaert J, Beckers A, Rihani A, Van Goethem A, Volders PJ, Zeka F, Ongenaert M, Mestdagh P, Vandesompele J (2014) miRBase tracker: keeping track of microRNA annotation changes. Database (Oxford) 2014.  https://doi.org/10.1093/database/bau080
  58. Vandesompele J, De Preter K, Pattyn F, Poppe B, Van Roy N, De Paepe A, Speleman F (2002) Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes. Genome Biol 3.  https://doi.org/10.1186/gb-2002-3-7-research0034
  59. Vecchione A, Croce CM (2010) Apoptomirs: small molecules have gained the license to kill. Endocr Relat Cancer 17:F37–F50.  https://doi.org/10.1677/erc-09-0163CrossRefPubMedGoogle Scholar
  60. Vogelstein B, Kinzler KW (1999) Digital PCR. Proc Natl Acad Sci USA 96:9236–9241.  https://doi.org/10.1073/pnas.96.16.9236CrossRefPubMedGoogle Scholar
  61. Wang ZYB (2010) MicroRNAs expression detection methods. Springer, BerlinCrossRefGoogle Scholar
  62. Wang JY, Mao RC, Zhang YM, Zhang YJ, Liu HY, Qin YL, Lu MJ, Zhang JM (2015a) Serum microRNA-124 is a novel biomarker for liver necroinflammation in patients with chronic hepatitis B virus infection. J Viral Hepat 22:128–136.  https://doi.org/10.1111/jvh.12284CrossRefPubMedGoogle Scholar
  63. Wang LS, Liu YM, Du LT, Li J, Jiang XM, Zheng GX, Qu AL, Wang HY, Wang LL, Zhang X, Liu H, Pan HW, Yang YM, Wang CX (2015b) Identification and validation of reference genes for the detection of serum microRNAs by reverse transcription-quantitative polymerase chain reaction in patients with bladder cancer. Mol Med Rep 12:615–622.  https://doi.org/10.3892/mmr.2015.3428CrossRefPubMedGoogle Scholar
  64. Weber JA, Baxter DH, Zhang S, Huang DY, Huang KH, Lee MJ, Galas DJ, Wang K (2010) The microRNA spectrum in 12 body fluids. Clin Chem 56:1733–1741.  https://doi.org/10.1373/clinchem.2010.147405CrossRefPubMedPubMedCentralGoogle Scholar
  65. Witwer KW (2012) XenomiRs and miRNA homeostasis in health and disease evidence that diet and dietary miRNAs directly and indirectly influence circulating miRNA profiles. RNA Biol 9:1147–1154.  https://doi.org/10.4161/rna.21619CrossRefPubMedPubMedCentralGoogle Scholar
  66. Witwer KW, Halushka MK (2016) Toward the promise of microRNAs – enhancing reproducibility and rigor in microRNA research. RNA Biol 13:1103–1116.  https://doi.org/10.1080/15476286.2016.1236172CrossRefPubMedPubMedCentralGoogle Scholar
  67. Witwer KW, Mcalexander MA, Queen SE, Adams RJ (2013) Real-time quantitative PCR and droplet digital PCR for plant miRNAs in mammalian blood provide little evidence for general uptake of dietary miRNAs limited evidence for general uptake of dietary plant xenomiRs. RNA Biol 10:1080–1086CrossRefGoogle Scholar
  68. Wylie D, Shelton J, Choudhary A, Adai AT (2011) A novel mean-centering method for normalizing microRNA expression from high-throughput RT-qPCR data. BMC Res Notes 4:555.  https://doi.org/10.1186/1756-0500-4-555CrossRefPubMedPubMedCentralGoogle Scholar
  69. Xiang MQ, Zeng Y, Yang RR, Xu HF, Chen Z, Zhong J, Xie HL, Xu YH, Zeng X (2014) U6 is not a suitable endogenous control for the quantification of circulating microRNAs. Biochem Biophys Res Commun 454:210–214.  https://doi.org/10.1016/j.bbrc.2014.10.064CrossRefPubMedGoogle Scholar
  70. Xie F, Xiao P, Chen D, Xu L, Zhang B (2012) miRDeepFinder: a miRNA analysis tool for deep sequencing of plant small RNAs. Plant Mol Biol.  https://doi.org/10.1007/s11103-012-9885-2

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© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Department of Biochemical SciencesCharles University, Faculty of PharmacyHradec KrálovéCzech Republic

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