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Molecular Diagnosis & Therapy

, Volume 21, Issue 3, pp 259–268 | Cite as

The Importance of Standardization on Analyzing Circulating RNA

  • Inyoul Lee
  • David Baxter
  • Min Young Lee
  • Kelsey Scherler
  • Kai WangEmail author
Review Article

Abstract

Circulating RNAs, especially microRNAs (miRNAs), have recently emerged as non-invasive disease biomarkers. Despite enthusiasm and numerous reports on disease-associated circulating miRNAs, currently there is no circulating miRNA-based diagnostic in use. In addition, there are many contradictory reports on the concentration changes of specific miRNA in circulation. Here we review the impact of various technical and non-technical factors related to circulating miRNA measurement and elucidate the importance of having a general guideline for sample preparation and concentration measurement in studying circulating RNA.

Keywords

Sample Collection Time Extracellular miRNAs miRNA Concentration Biofluid Sample qPCR Platform 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgements

Authors would like to thank Taek-kyun Kim, Xiaogang Wu and Vikas Ghai for helpful discussion, and Deborah Min for editing the manuscript.

Compliance with Ethical Standards

Conflict of interest statement

The authors (Kai Wang, Inyoul Lee, David Baxter, Min Young Lee, and Kelsey Scherler) declare that they have no competing interests.

Funding

This work is supported by grant from NIH (U01HL126496-02) and research contracts from DOD (W911NF-10-2-0111) and DTRA (HDTRA1-13-C-0055).

References

  1. 1.
    Mandel P, Metais P. Comptes rendus séances société. C R Seances Soc Biol Fil. 1948;142(3–4):241–3.PubMedGoogle Scholar
  2. 2.
    Kopreski MS, et al. Detection of tumor messenger RNA in the serum of patients with malignant melanoma. Clin Cancer Res. 1999;5(8):1961–5.PubMedGoogle Scholar
  3. 3.
    Miura N, et al. Clinical usefulness of serum telomerase reverse transcriptase (hTERT) mRNA and epidermal growth factor receptor (EGFR) mRNA as a novel tumor marker for lung cancer. Cancer Sci. 2006;97(12):1366–73.PubMedCrossRefGoogle Scholar
  4. 4.
    Barzon L, et al. Evaluation of circulating thyroid-specific transcripts as markers of thyroid cancer relapse. Int J Cancer. 2004;110(6):914–20.PubMedCrossRefGoogle Scholar
  5. 5.
    Mitchell PS, et al. Circulating microRNAs as stable blood-based markers for cancer detection. Proc Natl Acad Sci. 2008;105(30):10513–8.PubMedPubMedCentralCrossRefGoogle Scholar
  6. 6.
    Wang K, et al. Circulating microRNAs, potential biomarkers for drug-induced liver injury. Proc Natl Acad Sci. 2009;106(11):4402–7.PubMedPubMedCentralCrossRefGoogle Scholar
  7. 7.
    Etheridge A, et al. Extracellular microRNA: a new source of biomarkers. Mutat Res. 2011;717(1–2):85–90.PubMedPubMedCentralCrossRefGoogle Scholar
  8. 8.
    Chevillet JR, et al. Issues and prospects of microRNA-based biomarkers in blood and other body fluids. Molecules. 2014;19(5):6080–105.PubMedCrossRefGoogle Scholar
  9. 9.
    Lim LP, et al. Vertebrate microRNA genes. Science. 2003;299(5612):1540.PubMedCrossRefGoogle Scholar
  10. 10.
    Lau NC, et al. An abundant class of tiny RNAs with probable regulatory roles in Caenorhabditis elegans. Science. 2001;294(5543):858–62.PubMedCrossRefGoogle Scholar
  11. 11.
    Ambros V, et al. A uniform system for microRNA annotation. RNA. 2003;9(3):277–9.PubMedPubMedCentralCrossRefGoogle Scholar
  12. 12.
    He L, Hannon GJ. MicroRNAs: small RNAs with a big role in gene regulation. Nat Rev Genet. 2004;5(7):522–31.PubMedCrossRefGoogle Scholar
  13. 13.
    Eulalio A, Huntzinger E, Izaurralde E. Getting to the root of miRNA-mediated gene silencing. Cell. 2008;132(1):9–14.PubMedCrossRefGoogle Scholar
  14. 14.
    Bushati N, Cohen SM. microRNA functions. Annu Rev Cell Dev Biol. 2007;23:175–205.PubMedCrossRefGoogle Scholar
  15. 15.
    Kong YW, et al. The mechanism of micro-RNA-mediated translation repression is determined by the promoter of the target gene. Proc Natl Acad Sci. 2008;105(26):8866–71.PubMedPubMedCentralCrossRefGoogle Scholar
  16. 16.
    Ruike Y, et al. Global correlation analysis for micro-RNA and mRNA expression profiles in human cell lines. J Hum Genet. 2008;53(6):515–23.PubMedCrossRefGoogle Scholar
  17. 17.
    Lee I, et al. New class of microRNA targets containing simultaneous 5′-UTR and 3′-UTR interaction sites. Genome Res. 2009;19(7):1175–83.PubMedPubMedCentralCrossRefGoogle Scholar
  18. 18.
    Bartel DP. MicroRNAs: target recognition and regulatory functions. Cell. 2009;136(2):215–33.PubMedPubMedCentralCrossRefGoogle Scholar
  19. 19.
    Fabian MR, Sonenberg N, Filipowicz W. Regulation of mRNA translation and stability by microRNAs. Annu Rev Biochem. 2010;79:351–79.PubMedCrossRefGoogle Scholar
  20. 20.
    Griffiths-Jones S, et al. miRBase: microRNA sequences, targets and gene nomenclature. Nucleic Acids Res. 2006;34(Database issue):D140–4.Google Scholar
  21. 21.
    Smalheiser NR. Exosomal transfer of proteins and RNAs at synapses in the nervous system. Biology direct. 2007;2:35.PubMedPubMedCentralCrossRefGoogle Scholar
  22. 22.
    Valadi H, et al. Exosome-mediated transfer of mRNAs and microRNAs is a novel mechanism of genetic exchange between cells. Nat Cell Biol. 2007;9(6):654–9.PubMedCrossRefGoogle Scholar
  23. 23.
    Vickers KC, et al. MicroRNAs are transported in plasma and delivered to recipient cells by high-density lipoproteins. Nat Cell Biol. 2011;13(4):423–33.PubMedPubMedCentralCrossRefGoogle Scholar
  24. 24.
    Michell DL, Vickers KC. Lipoprotein carriers of microRNAs. Biochimica et biophysica acta. 2016;1861:2069–74.PubMedCrossRefGoogle Scholar
  25. 25.
    Wagner J, et al. Characterization of levels and cellular transfer of circulating lipoprotein-bound microRNAs. Arterioscler Thromb Vasc Biol. 2013;33(6):1392–400.PubMedCrossRefGoogle Scholar
  26. 26.
    Wang K, et al. Export of microRNAs and microRNA-protective protein by mammalian cells. Nucleic Acids Res. 2010;38(20):7248–59.PubMedPubMedCentralCrossRefGoogle Scholar
  27. 27.
    Arroyo JD, et al. Argonaute2 complexes carry a population of circulating microRNAs independent of vesicles in human plasma. Proc Natl Acad Sci. 2011;108(12):5003–8.PubMedPubMedCentralCrossRefGoogle Scholar
  28. 28.
    Turchinovich A, Burwinkel B. Distinct AGO1 and AGO2 associated miRNA profiles in human cells and blood plasma. RNA Biol. 2012;9(8):1066–75.PubMedPubMedCentralCrossRefGoogle Scholar
  29. 29.
    Thery C, Zitvogel L, Amigorena S. Exosomes: composition, biogenesis and function. Nat Rev Immunol. 2002;2(8):569–79.PubMedGoogle Scholar
  30. 30.
    Pan BT, Johnstone RM. Fate of the transferrin receptor during maturation of sheep reticulocytes in vitro: selective externalization of the receptor. Cell. 1983;33(3):967–78.PubMedCrossRefGoogle Scholar
  31. 31.
    Andaloussi SEL, et al. Extracellular vesicles: biology and emerging therapeutic opportunities. Nat Rev Drug Discov. 2013;12(5):347–57.Google Scholar
  32. 32.
    Borges FT, Reis LA, Schor N. Extracellular vesicles: structure, function, and potential clinical uses in renal diseases. Braz J Med Biol Res = Revista brasileira de pesquisas medicas e biologicas/Sociedade Brasileira de Biofisica … [et al.]. 2013;46(10):824–30.Google Scholar
  33. 33.
    Raposo G, Stoorvogel W. Extracellular vesicles: exosomes, microvesicles, and friends. J Cell Biol. 2013;200(4):373–83.PubMedPubMedCentralCrossRefGoogle Scholar
  34. 34.
    Gyorgy B, et al. Membrane vesicles, current state-of-the-art: emerging role of extracellular vesicles. Cell Mol Life Sci. 2011;68(16):2667–88.PubMedPubMedCentralCrossRefGoogle Scholar
  35. 35.
    Denzer K, et al. Exosome: from internal vesicle of the multivesicular body to intercellular signaling device. J Cell Sci. 2000;113(Pt 19):3365–74.PubMedGoogle Scholar
  36. 36.
    Taylor RC, Cullen SP, Martin SJ. Apoptosis: controlled demolition at the cellular level. Nat Rev Mol Cell Biol. 2008;9(3):231–41.PubMedCrossRefGoogle Scholar
  37. 37.
    Mathivanan S, Ji H, Simpson RJ. Exosomes: extracellular organelles important in intercellular communication. J Proteom. 2010;73(10):1907–20.CrossRefGoogle Scholar
  38. 38.
    Eichelser C, et al. Increased serum levels of circulating exosomal microRNA-373 in receptor-negative breast cancer patients. Oncotarget. 2014;5(20):9650–63.PubMedPubMedCentralCrossRefGoogle Scholar
  39. 39.
    Braicu C, et al. Exosomes as divine messengers: are they the Hermes of modern molecular oncology? Cell Death Differ. 2015;22(1):34–45.PubMedCrossRefGoogle Scholar
  40. 40.
    Kanada M, et al. Differential fates of biomolecules delivered to target cells via extracellular vesicles. Proc Natl Acad Sci. 2015;112(12):E1433–42.PubMedPubMedCentralGoogle Scholar
  41. 41.
    Yoon YJ, Kim OY, Gho YS. Extracellular vesicles as emerging intercellular communicasomes. BMB reports. 2014;47(10):531–9.PubMedPubMedCentralCrossRefGoogle Scholar
  42. 42.
    Salaspuro M. Use of enzymes for the diagnosis of alcohol-related organ damage. Enzyme. 1987;37(1–2):87–107.PubMedGoogle Scholar
  43. 43.
    Borlak J, Chougule A, Singh PK. How useful are clinical liver function tests in in vitro human hepatotoxicity assays? Toxicol In Vitro. 2014;28(5):784–95.PubMedCrossRefGoogle Scholar
  44. 44.
    Gowda S, et al. A review on laboratory liver function tests. Pan Afr Med J. 2009;3:17.PubMedPubMedCentralGoogle Scholar
  45. 45.
    James O, et al. Liver damage after paracetamol overdose. Comparison of liver-function tests, fasting serum bile acids, and liver histology. Lancet. 1975;2(7935):579–81.PubMedCrossRefGoogle Scholar
  46. 46.
    Crawford ED, DeAntoni EP. PSA as a screening test for prostate cancer. Urol Clin N Am. 1993;20(4):637–46.Google Scholar
  47. 47.
    Catalona WJ, et al. Detection of organ-confined prostate cancer is increased through prostate-specific antigen-based screening. JAMA. 1993;270(8):948–54.PubMedCrossRefGoogle Scholar
  48. 48.
    Bagcchi S. PSA testing beneficial for prostate cancer. Lancet Oncol. 2014;15(10):e424.PubMedCrossRefGoogle Scholar
  49. 49.
    Katus HA, et al. Diagnostic efficiency of troponin T measurements in acute myocardial infarction. Circulation. 1991;83(3):902–12.PubMedCrossRefGoogle Scholar
  50. 50.
    Antman EM, et al. Cardiac-specific troponin I levels to predict the risk of mortality in patients with acute coronary syndromes. N Engl J Med. 1996;335(18):1342–9.PubMedCrossRefGoogle Scholar
  51. 51.
    Brase JC, et al. Circulating miRNAs are correlated with tumor progression in prostate cancer. Int J Cancer. 2011;128(3):608–16.PubMedCrossRefGoogle Scholar
  52. 52.
    Westermann AM, et al. Serum microRNAs as biomarkers in patients undergoing prostate biopsy: results from a prospective multi-center study. Anticancer Res. 2014;34(2):665–9.PubMedGoogle Scholar
  53. 53.
    Laterza OF, et al. Plasma MicroRNAs as sensitive and specific biomarkers of tissue injury. Clin Chem. 2009;55(11):1977–83.PubMedCrossRefGoogle Scholar
  54. 54.
    Starkey Lewis PJ, et al. Circulating microRNAs as potential markers of human drug-induced liver injury. Hepatology. 2011;54(5):1767–76.PubMedCrossRefGoogle Scholar
  55. 55.
    Hu Z, et al. Quantitative liver-specific protein fingerprint in blood: a signature for hepatotoxicity. Theranostics. 2014;4(2):215–28.PubMedPubMedCentralCrossRefGoogle Scholar
  56. 56.
    Fichtlscherer S, et al. Circulating microRNAs in patients with coronary artery disease. Circ Res. 2010;107(5):677–84.PubMedCrossRefGoogle Scholar
  57. 57.
    Adachi T, et al. Plasma microRNA 499 as a biomarker of acute myocardial infarction. Clin Chem. 2010;56(7):1183–5.PubMedCrossRefGoogle Scholar
  58. 58.
    Li C, et al. Serum microRNAs profile from genome-wide serves as a fingerprint for diagnosis of acute myocardial infarction and angina pectoris. BMC Med Genomics. 2013;6:16.PubMedPubMedCentralCrossRefGoogle Scholar
  59. 59.
    Wang GK, et al. Circulating microRNA: a novel potential biomarker for early diagnosis of acute myocardial infarction in humans. Eur Heart J. 2010;31(6):659–66.PubMedCrossRefGoogle Scholar
  60. 60.
    Shi R, Chiang VL. Facile means for quantifying microRNA expression by real-time PCR. Biotechniques. 2005;39(4):519–25.PubMedCrossRefGoogle Scholar
  61. 61.
    Chen C, et al. Real-time quantification of microRNAs by stem-loop RT-PCR. Nucleic Acids Res. 2005;33(20):e179.PubMedPubMedCentralCrossRefGoogle Scholar
  62. 62.
    Schmittgen TD, et al. Real-time PCR quantification of precursor and mature microRNA. Methods. 2008;44(1):31–8.PubMedPubMedCentralCrossRefGoogle Scholar
  63. 63.
    Sato F, et al. Intra-platform repeatability and inter-platform comparability of microRNA microarray technology. PLoS One. 2009;4(5):e5540.PubMedPubMedCentralCrossRefGoogle Scholar
  64. 64.
    Git A, et al. Systematic comparison of microarray profiling, real-time PCR, and next-generation sequencing technologies for measuring differential microRNA expression. RNA. 2010;16(5):991–1006.PubMedPubMedCentralCrossRefGoogle Scholar
  65. 65.
    Hafner M, et al. RNA-ligase-dependent biases in miRNA representation in deep-sequenced small RNA cDNA libraries. RNA. 2011;17(9):1697–712.PubMedPubMedCentralCrossRefGoogle Scholar
  66. 66.
    Fuchs RT, et al. Bias in ligation-based small RNA sequencing library construction is determined by adaptor and RNA structure. PLoS One. 2015;10(5):e0126049.PubMedPubMedCentralCrossRefGoogle Scholar
  67. 67.
    Wang K, et al. Comparing the MicroRNA spectrum between serum and plasma. PLoS One. 2012;7(7):e41561.PubMedPubMedCentralCrossRefGoogle Scholar
  68. 68.
    McDonald JS, et al. Analysis of circulating microRNA: preanalytical and analytical challenges. Clin Chem. 2011;57(6):833–40.PubMedCrossRefGoogle Scholar
  69. 69.
    Kirschner MB, et al. Haemolysis during sample preparation alters microRNA content of plasma. PLoS One. 2011;6(9):e24145.PubMedPubMedCentralCrossRefGoogle Scholar
  70. 70.
    Kirschner MB, et al. The impact of hemolysis on cell-free microRNA biomarkers. Front Genet. 2013;4:94.PubMedPubMedCentralGoogle Scholar
  71. 71.
    Pritchard CC, Cheng HH, Tewari M. MicroRNA profiling: approaches and considerations. Nat Rev Genet. 2012;13(5):358–69.PubMedPubMedCentralCrossRefGoogle Scholar
  72. 72.
    Cheng HH, et al. Plasma processing conditions substantially influence circulating microRNA biomarker levels. PLoS One. 2013;8(6):e64795.PubMedPubMedCentralCrossRefGoogle Scholar
  73. 73.
    Duttagupta R, et al. Impact of cellular miRNAs on circulating miRNA biomarker signatures. PLoS One. 2011;6(6):e20769.PubMedPubMedCentralCrossRefGoogle Scholar
  74. 74.
    Wang YT, et al. Circulating microRNAs have a sex-specific association with metabolic syndrome. J Biomed Sci. 2013;20:72.PubMedPubMedCentralCrossRefGoogle Scholar
  75. 75.
    Rekker K, et al. Circulating microRNA Profile throughout the menstrual cycle. PLoS One. 2013;8(11):e81166.PubMedPubMedCentralCrossRefGoogle Scholar
  76. 76.
    Ioannidis J, Donadeu FX. Circulating microRNA profiles during the bovine oestrous cycle. PLoS One. 2016;11(6):e0158160.PubMedPubMedCentralCrossRefGoogle Scholar
  77. 77.
    Cho S, et al. Circulating microRNAs as potential biomarkers for endometriosis. Fertil Steril. 2015;103(5):1252–60 e1.Google Scholar
  78. 78.
    Cosar E, et al. Serum microRNAs as diagnostic markers of endometriosis: a comprehensive array-based analysis. Fertil Steril. 2016;106(2):402–9.PubMedCrossRefGoogle Scholar
  79. 79.
    Miura K, et al. Circulating chromosome 19 miRNA cluster microRNAs in pregnant women with severe pre-eclampsia. J Obstet Gynaecol Res. 2015;41(10):1526–32.PubMedCrossRefGoogle Scholar
  80. 80.
    Ioannidis J, Donadeu FX. Circulating miRNA signatures of early pregnancy in cattle. BMC Genom. 2016;17:184.CrossRefGoogle Scholar
  81. 81.
    Gu Y, et al. Differential miRNA expression profiles between the first and third trimester human placentas. Am J Physiol Endocrinol Metab. 2013;304(8):E836–43.PubMedPubMedCentralCrossRefGoogle Scholar
  82. 82.
    Danielson KM, et al. Diurnal variations of circulating extracellular vesicles measured by nano flow cytometry. PLoS One. 2016;11(1):e0144678.PubMedPubMedCentralCrossRefGoogle Scholar
  83. 83.
    Shende VR, et al. Expression and rhythmic modulation of circulating microRNAs targeting the clock gene Bmal1 in mice. PLoS One. 2011;6(7):e22586.PubMedPubMedCentralCrossRefGoogle Scholar
  84. 84.
    Heegaard NH, et al. Diurnal variations of human circulating cell-free micro-RNA. PLoS One. 2016;11(8):e0160577.PubMedPubMedCentralCrossRefGoogle Scholar
  85. 85.
    Wang K, et al. The complex exogenous RNA spectra in human plasma: an interface with human gut biota? PLoS One. 2012;7(12):e51009.PubMedPubMedCentralCrossRefGoogle Scholar
  86. 86.
    Witwer KW. Contamination or artifacts may explain reports of plant miRNAs in humans. J Nutr Biochem. 2015;26(12):1685.PubMedCrossRefGoogle Scholar
  87. 87.
    Witwer KW, et al. 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. 2013;10(7):1080–6.PubMedPubMedCentralCrossRefGoogle Scholar
  88. 88.
    Witwer KW, Hirschi KD. Transfer and functional consequences of dietary microRNAs in vertebrates: concepts in search of corroboration: negative results challenge the hypothesis that dietary xenomiRs cross the gut and regulate genes in ingesting vertebrates, but important questions persist. BioEssays. 2014;36(4):394–406.PubMedPubMedCentralCrossRefGoogle Scholar
  89. 89.
    MacLellan SA, et al. Pre-profiling factors influencing serum microRNA levels. BMC Clin Pathol. 2014;14:27.PubMedPubMedCentralCrossRefGoogle Scholar
  90. 90.
    Gomes CP, et al. Circulating miR-1, miR-133a, and miR-206 levels are increased after a half-marathon run. Biomarkers. 2014;19(7):585–9.PubMedCrossRefGoogle Scholar
  91. 91.
    Nielsen S, et al. The miRNA plasma signature in response to acute aerobic exercise and endurance training. PLoS One. 2014;9(2):e87308.PubMedPubMedCentralCrossRefGoogle Scholar
  92. 92.
    Uhlemann M, et al. Circulating microRNA-126 increases after different forms of endurance exercise in healthy adults. Eur J Prev Cardiol. 2014;21(4):484–91.PubMedCrossRefGoogle Scholar
  93. 93.
    Baggish AL, et al. Dynamic regulation of circulating microRNA during acute exhaustive exercise and sustained aerobic exercise training. J Physiol. 2011;589(Pt 16):3983–94.PubMedPubMedCentralCrossRefGoogle Scholar
  94. 94.
    Willems M, et al. Plasma collected from heparinized blood is not suitable for HCV-RNA detection by conventional RT-PCR assay. J Virol Methods. 1993;42(1):127–30.PubMedCrossRefGoogle Scholar
  95. 95.
    Ding M, et al. An optimized sensitive method for quantitation of DNA/RNA viruses in heparinized and cryopreserved plasma. J Virol Methods. 2011;176(1–2):1–8.PubMedPubMedCentralCrossRefGoogle Scholar
  96. 96.
    Moldovan L, et al. Analyzing the circulating microRNAs in exosomes/extracellular vesicles from serum or plasma by qRT-PCR. Methods Mol Biol. 2013;1024:129–45.PubMedPubMedCentralCrossRefGoogle Scholar
  97. 97.
    Li X, Mauro M, Williams Z. Comparison of plasma extracellular RNA isolation kits reveals kit-dependent biases. Biotechniques. 2015;59(1):13–7.PubMedCrossRefGoogle Scholar
  98. 98.
    Tanriverdi K, et al. Comparison of RNA isolation and associated methods for extracellular RNA detection by high-throughput quantitative polymerase chain reaction. Anal Biochem. 2016;501:66–74.PubMedCrossRefGoogle Scholar
  99. 99.
    Farr RJ, et al. A comparative analysis of high-throughput platforms for validation of a circulating microRNA signature in diabetic retinopathy. Sci Rep. 2015;5:10375.PubMedPubMedCentralCrossRefGoogle Scholar
  100. 100.
    Kim S, et al. Deep learning of support vector machines with class probability output networks. Neural Netw. 2015;64:19–28.PubMedCrossRefGoogle Scholar
  101. 101.
    Chen Y, et al. Reproducibility of quantitative RT-PCR array in miRNA expression profiling and comparison with microarray analysis. BMC Genom. 2009;10:407.CrossRefGoogle Scholar
  102. 102.
    Backes C, et al. Bias in high-throughput analysis of miRNAs and implications for biomarker studies. Anal Chem. 2016;88(4):2088–95.PubMedCrossRefGoogle Scholar
  103. 103.
    Mestdagh P, et al. Evaluation of quantitative miRNA expression platforms in the microRNA quality control (miRQC) study. Nat Methods. 2014;11(8):809–15.PubMedCrossRefGoogle Scholar
  104. 104.
    Tan GW, Khoo AS, Tan LP. Evaluation of extraction kits and RT-qPCR systems adapted to high-throughput platform for circulating miRNAs. Sci Rep. 2015;5:9430.PubMedPubMedCentralCrossRefGoogle Scholar
  105. 105.
    Pradervand S, et al. Concordance among digital gene expression, microarrays, and qPCR when measuring differential expression of microRNAs. Biotechniques. 2010;48(3):219–22.PubMedCrossRefGoogle Scholar
  106. 106.
    Mou G, et al. Evaluation of three RT-qPCR-based miRNA detection methods using seven rice miRNAs. Biosci Biotechnol Biochem. 2013;77(6):1349–53.PubMedCrossRefGoogle Scholar
  107. 107.
    Baran-Gale J, et al. Addressing bias in small RNA library preparation for sequencing: a new protocol recovers MicroRNAs that evade capture by current methods. Front Genet. 2015;6:352.PubMedPubMedCentralCrossRefGoogle Scholar
  108. 108.
    Huang X, et al. Characterization of human plasma-derived exosomal RNAs by deep sequencing. BMC Genom. 2013;14:319.CrossRefGoogle Scholar
  109. 109.
    Sorefan K, et al. Reducing ligation bias of small RNAs in libraries for next generation sequencing. Silence. 2012;3(1):4.PubMedPubMedCentralCrossRefGoogle Scholar
  110. 110.
    Tam S, Tsao MS, McPherson JD. Optimization of miRNA-seq data preprocessing. Brief Bioinform. 2015;16(6):950–63.PubMedPubMedCentralCrossRefGoogle Scholar
  111. 111.
    Bullard JH, et al. Evaluation of statistical methods for normalization and differential expression in mRNA-Seq experiments. BMC Bioinform. 2010;11:94.CrossRefGoogle Scholar
  112. 112.
    Robinson MD, Oshlack A. A scaling normalization method for differential expression analysis of RNA-seq data. Genome Biol. 2010;11(3):R25.PubMedPubMedCentralCrossRefGoogle Scholar
  113. 113.
    Anders S, Huber W. Differential expression analysis for sequence count data. Genome Biol. 2010;11(10):R106.PubMedPubMedCentralCrossRefGoogle Scholar
  114. 114.
    Bolstad BM, et al. A comparison of normalization methods for high density oligonucleotide array data based on variance and bias. Bioinformatics. 2003;19(2):185–93.PubMedCrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Inyoul Lee
    • 1
  • David Baxter
    • 1
  • Min Young Lee
    • 1
  • Kelsey Scherler
    • 1
  • Kai Wang
    • 1
    Email author
  1. 1.Institute for Systems BiologySeattleUSA

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