Advertisement

pp 1-38 | Cite as

Advanced Assays in Epigenetics

  • Carmela Dell’Aversana
  • Federica Sarno
  • Mariarosaria Conte
  • Cristina Giorgio
  • Lucia AltucciEmail author
Chapter
Part of the Topics in Medicinal Chemistry book series

Abstract

Epigenetic mechanisms orchestrate the finely tuned regulation of genetic material and play a pivotal role in defining cellular functions and phenotypes. A growing set of tools supports analysis of the epigenome. This chapter will provide an overview of the principle methods of studying complex epigenetic machinery, focusing on recent advancements of tools and techniques in the field of epigenetics. It will also address the advantages, limitations and perspectives of each approach. Increasingly, the high sensitivity, specificity, accuracy, precision and reproducibility of cutting-edge technologies in epigenetics are allowing the identification of new key targets and molecular mechanisms in healthy and pathological states and are becoming methods of choice for clinical investigations.

Keywords

Epigenetics Genome Histone modification Methylation miRNA 

Abbreviations

5caC

5-Carboxylcytosine

5fC

5-Formylcytosine

5hmC

5-Hydroxymethylcytosine

5mC

5-Methylcytosine

AlphaScreen

Amplified Luminescent Proximity Homogeneous Assay Screen

BRET

Bioluminescence resonance energy transfer

BS-seq

Bisulfite sequencing

CAB-seq

Chemical modification-assisted bisulfite sequencing

CE-SSCP

Capillary electrophoresis single-strand conformation polymorphism

CETSA

Cellular thermal shift assay

ChIP

Chromatin immunoprecipitation

ChroP

Chromatin proteomics

ddPCR

Droplet digital PCR

EDC

1-Ethyl-3(3-dimethylaminoproyl)-carbodiimide hydrochloride

EnIGMA

Enzyme-assisted identification of genome modification assay

ePL

Enhanced ProLabel

ES

Embryonic stem

EWAS

Epigenome-wide association studies

EXPAR

Exponential amplification reaction

fCAB-seq

5-Formylcytosine chemical modification-assisted bisulfite sequencing

FISH

Fluorescent in situ hybridization

FLIM

Fluorescence lifetime microscopy

FRET

Förster resonance energy transfer

G4

G-quadruplex

HATs

Histone acetyltransferases

HMTs

Histone methyltransferases

HTDR

High-throughput dose-response

HTS

High-throughput screening

HT-seq

High-throughput sequencing

ISH

In situ hybridization

ITC

Isothermal titration colorimetry

LC-MS

Liquid chromatography-mass spectrometry

LNA

Locked nucleic acid

miRNA

microRNA

miR-TRAP

miRNA trapping

MPS

Massive parallel sequencing

MS

Mass spectrometry

MST

Microscale thermophoresis

NGS

Next-generation sequencing

Nluc

NanoLuc luciferase

PAR-CLIP

Photoactivatable ribonucleoside-enhanced cross-linking and immunoprecipitation

QD

Quantum dot

RBPs

RNA binding proteins

RIME

Rapid immunoprecipitation mass spectrometry of endogenous protein

Rluc

Renilla luciferase

RRBS

Reduced representation bisulfite sequencing

scBS-seq

Single-cell bisulfite sequencing

scM&T-seq

Single-cell genome-wide methylome and transcriptome sequencing

scRRBS

Single-cell reduced representation bisulfite sequencing

snmC-seq

Single-nucleus methylcytosine sequencing

SNPs

Single-nucleotide polymorphisms

SPR

Surface plasmon resonance

TAB-seq

Tet-assisted bisulfite sequencing

TCL

Targeted chromatin ligation

Tm

Melting temperature

TR-FRET

Time-resolved fluorescent energy transfer

UV

Ultraviolet

YFP

Yellow fluorescent protein

Notes

Compliance with Ethical Standards

Funding: The authors acknowledge AIRC17217; PON_0101227; VALERE: Vanvitelli per la Ricerca; Regione Campania lotta alle patologie oncologiche: iCURE (CUP B21C17000030007); and Regione Campania FASE2: IDEAL (CUP B53D18000080007). We thank C. Fisher for linguistic editing.

Conflict of Interest: The authors declare no competing interests.

Ethical Statement: This article does not contain any studies with human participants or animals performed by any of the authors.

References

  1. 1.
    Bernstein BE, Meissner A, Lander ES (2007) The mammalian epigenome. Cell 128(4):669–681.  https://doi.org/10.1016/j.cell.2007.01.033CrossRefGoogle Scholar
  2. 2.
    Baylin SB, Jones PA (2011) A decade of exploring the cancer epigenome – biological and translational implications. Nat Rev Cancer 11(10):726–734.  https://doi.org/10.1038/nrc3130CrossRefGoogle Scholar
  3. 3.
    Cheuk IW, Shin VY, Kwong A (2017) Detection of methylated circulating DNA as noninvasive biomarkers for breast cancer diagnosis. J Breast Cancer 20(1):12–19.  https://doi.org/10.4048/jbc.2017.20.1.12CrossRefGoogle Scholar
  4. 4.
    Ho SM, Johnson A, Tarapore P, Janakiram V, Zhang X, Leung YK (2012) Environmental epigenetics and its implication on disease risk and health outcomes. ILAR J 53(3–4):289–305.  https://doi.org/10.1093/ilar.53.3-4.289CrossRefGoogle Scholar
  5. 5.
    Thomas ML, Marcato P (2018) Epigenetic modifications as biomarkers of tumor development, therapy response, and recurrence across the cancer care continuum. Cancers (Basel) 10(4).  https://doi.org/10.3390/cancers10040101Google Scholar
  6. 6.
    Vardabasso C, Gaspar-Maia A, Hasson D, Punzeler S, Valle-Garcia D, Straub T, Keilhauer EC, Strub T, Dong J, Panda T, Chung CY, Yao JL, Singh R, Segura MF, Fontanals-Cirera B, Verma A, Mann M, Hernando E, Hake SB, Bernstein E (2015) Histone variant H2A.Z.2 mediates proliferation and drug sensitivity of malignant melanoma. Mol Cell 59(1):75–88.  https://doi.org/10.1016/j.molcel.2015.05.009CrossRefGoogle Scholar
  7. 7.
    Jia M, Jansen L, Walter V, Tagscherer K, Roth W, Herpel E, Kloor M, Blaker H, Chang-Claude J, Brenner H, Hoffmeister M (2016) No association of CpG island methylator phenotype and colorectal cancer survival: population-based study. Br J Cancer 115(11):1359–1366.  https://doi.org/10.1038/bjc.2016.361CrossRefGoogle Scholar
  8. 8.
    Ullman EF, Kirakossian H, Singh S, Wu ZP, Irvin BR, Pease JS, Switchenko AC, Irvine JD, Dafforn A, Skold CN et al (1994) Luminescent oxygen channeling immunoassay: measurement of particle binding kinetics by chemiluminescence. Proc Natl Acad Sci U S A 91(12):5426–5430Google Scholar
  9. 9.
    Yasgar A, Jadhav A, Simeonov A, Coussens NP (2016) AlphaScreen-based assays: ultra-high-throughput screening for small-molecule inhibitors of challenging enzymes and protein-protein interactions. Methods Mol Biol 1439:77–98.  https://doi.org/10.1007/978-1-4939-3673-1_5CrossRefGoogle Scholar
  10. 10.
    Wigle TJ, Herold JM, Senisterra GA, Vedadi M, Kireev DB, Arrowsmith CH, Frye SV, Janzen WP (2010) Screening for inhibitors of low-affinity epigenetic peptide-protein interactions: an AlphaScreen-based assay for antagonists of methyl-lysine binding proteins. J Biomol Screen 15(1):62–71.  https://doi.org/10.1177/1087057109352902CrossRefGoogle Scholar
  11. 11.
    Prabhu L, Chen L, Wei H, Demir O, Safa A, Zeng L, Amaro RE, O’Neil BH, Zhang ZY, Lu T (2017) Development of an AlphaLISA high throughput technique to screen for small molecule inhibitors targeting protein arginine methyltransferases. Mol Biosyst 13(12):2509–2520.  https://doi.org/10.1039/c7mb00391aCrossRefGoogle Scholar
  12. 12.
    Scarano S, Scuffi C, Mascini M, Minunni M (2011) Surface plasmon resonance imaging-based sensing for anti-bovine immunoglobulins detection in human milk and serum. Anal Chim Acta 707(1–2):178–183.  https://doi.org/10.1016/j.aca.2011.09.012CrossRefGoogle Scholar
  13. 13.
    Kim D, Lee IS, Jung JH, Yang SI (1999) Psammaplin A, a natural bromotyrosine derivative from a sponge, possesses the antibacterial activity against methicillin-resistant Staphylococcus aureus and the DNA gyrase-inhibitory activity. Arch Pharm Res 22(1):25–29Google Scholar
  14. 14.
    Duff MR Jr, Grubbs J, Howell EE (2011) Isothermal titration calorimetry for measuring macromolecule-ligand affinity. J Vis Exp (55).  https://doi.org/10.3791/2796
  15. 15.
    Holdgate G (2009) Isothermal titration calorimetry and differential scanning calorimetry. Methods Mol Biol 572:101–133.  https://doi.org/10.1007/978-1-60761-244-5_7CrossRefGoogle Scholar
  16. 16.
    Jerabek-Willemsen M, Wienken CJ, Braun D, Baaske P, Duhr S (2011) Molecular interaction studies using microscale thermophoresis. Assay Drug Dev Technol 9(4):342–353.  https://doi.org/10.1089/adt.2011.0380CrossRefGoogle Scholar
  17. 17.
    Zillner K, Jerabek-Willemsen M, Duhr S, Braun D, Langst G, Baaske P (2012) Microscale thermophoresis as a sensitive method to quantify protein: nucleic acid interactions in solution. Methods Mol Biol 815:241–252.  https://doi.org/10.1007/978-1-61779-424-7_18CrossRefGoogle Scholar
  18. 18.
    Alpatov R, Lesch BJ, Nakamoto-Kinoshita M, Blanco A, Chen S, Stutzer A, Armache KJ, Simon MD, Xu C, Ali M, Murn J, Prisic S, Kutateladze TG, Vakoc CR, Min J, Kingston RE, Fischle W, Warren ST, Page DC, Shi Y (2014) A chromatin-dependent role of the fragile X mental retardation protein FMRP in the DNA damage response. Cell 157(4):869–881.  https://doi.org/10.1016/j.cell.2014.03.040CrossRefGoogle Scholar
  19. 19.
    Josling GA, Petter M, Oehring SC, Gupta AP, Dietz O, Wilson DW, Schubert T, Langst G, Gilson PR, Crabb BS, Moes S, Jenoe P, Lim SW, Brown GV, Bozdech Z, Voss TS, Duffy MF (2015) A plasmodium falciparum bromodomain protein regulates invasion gene expression. Cell Host Microbe 17(6):741–751.  https://doi.org/10.1016/j.chom.2015.05.009CrossRefGoogle Scholar
  20. 20.
    Raha D, Hong M, Snyder M (2010) ChIP-seq: a method for global identification of regulatory elements in the genome. Curr Protoc Mol Biol Chapter 21:Unit 21 19 21-14.  https://doi.org/10.1002/0471142727.mb2119s91Google Scholar
  21. 21.
    Wang CI, Alekseyenko AA, LeRoy G, Elia AE, Gorchakov AA, Britton LM, Elledge SJ, Kharchenko PV, Garcia BA, Kuroda MI (2013) Chromatin proteins captured by ChIP-mass spectrometry are linked to dosage compensation in Drosophila. Nat Struct Mol Biol 20(2):202–209.  https://doi.org/10.1038/nsmb.2477CrossRefGoogle Scholar
  22. 22.
    Mohammed H, Taylor C, Brown GD, Papachristou EK, Carroll JS, D'Santos CS (2016) Rapid immunoprecipitation mass spectrometry of endogenous proteins (RIME) for analysis of chromatin complexes. Nat Protoc 11(2):316–326.  https://doi.org/10.1038/nprot.2016.020CrossRefGoogle Scholar
  23. 23.
    Cao Z, Lu C (2016) A microfluidic device with integrated sonication and immunoprecipitation for sensitive epigenetic assays. Anal Chem 88(3):1965–1972.  https://doi.org/10.1021/acs.analchem.5b04707CrossRefGoogle Scholar
  24. 24.
    Jafari R, Almqvist H, Axelsson H, Ignatushchenko M, Lundback T, Nordlund P, Martinez Molina D (2014) The cellular thermal shift assay for evaluating drug target interactions in cells. Nat Protoc 9(9):2100–2122.  https://doi.org/10.1038/nprot.2014.138CrossRefGoogle Scholar
  25. 25.
    Becher I, Werner T, Doce C, Zaal EA, Togel I, Khan CA, Rueger A, Muelbaier M, Salzer E, Berkers CR, Fitzpatrick PF, Bantscheff M, Savitski MM (2016) Thermal profiling reveals phenylalanine hydroxylase as an off-target of panobinostat. Nat Chem Biol 12(11):908–910.  https://doi.org/10.1038/nchembio.2185CrossRefGoogle Scholar
  26. 26.
    McNulty DE, Bonnette WG, Qi H, Wang L, Ho TF, Waszkiewicz A, Kallal LA, Nagarajan RP, Stern M, Quinn AM, Creasy CL, Su DS, Graves AP, Annan RS, Sweitzer SM, Holbert MA (2018) A high-throughput dose-response cellular thermal shift assay for rapid screening of drug target engagement in living cells, exemplified using SMYD3 and IDO1. SLAS Discov 23(1):34–46.  https://doi.org/10.1177/2472555217732014CrossRefGoogle Scholar
  27. 27.
    Song Y, Madahar V, Liao J (2011) Development of FRET assay into quantitative and high-throughput screening technology platforms for protein-protein interactions. Ann Biomed Eng 39(4):1224–1234.  https://doi.org/10.1007/s10439-010-0225-xCrossRefGoogle Scholar
  28. 28.
    Alibhai D, Kelly DJ, Warren S, Kumar S, Margineau A, Serwa RA, Thinon E, Alexandrov Y, Murray EJ, Stuhmeier F, Tate EW, Neil MA, Dunsby C, French PM (2013) Automated fluorescence lifetime imaging plate reader and its application to Forster resonant energy transfer readout of Gag protein aggregation. J Biophotonics 6(5):398–408.  https://doi.org/10.1002/jbio.201200185CrossRefGoogle Scholar
  29. 29.
    Wade M, Mendez J, Coussens NP, Arkin MR, Glicksman MA (2004) Inhibition of protein-protein interactions: cell-based assays. In: Sittampalam GS, Coussens NP, Brimacombe K et al (eds) Assay guidance manual. Eli Lilly & Company and the National Center for Advancing Translational Sciences, BethesdaGoogle Scholar
  30. 30.
    Bacart J, Corbel C, Jockers R, Bach S, Couturier C (2008) The BRET technology and its application to screening assays. Biotechnol J 3(3):311–324.  https://doi.org/10.1002/biot.200700222CrossRefGoogle Scholar
  31. 31.
    Machleidt T, Woodroofe CC, Schwinn MK, Mendez J, Robers MB, Zimmerman K, Otto P, Daniels DL, Kirkland TA, Wood KV (2015) NanoBRET – a novel BRET platform for the analysis of protein-protein interactions. ACS Chem Biol 10(8):1797–1804.  https://doi.org/10.1021/acschembio.5b00143CrossRefGoogle Scholar
  32. 32.
    Hu F, Martin H, Martinez A, Everitt J, Erkanli A, Lee WT, Dewhirst M, Ramanujam N (2017) Distinct angiogenic changes during carcinogenesis defined by novel label-free dark-field imaging in a hamster cheek pouch model. Cancer Res 77(24):7109–7119.  https://doi.org/10.1158/0008-5472.CAN-17-1058CrossRefGoogle Scholar
  33. 33.
    Tollefsbol TO (2011) Advances in epigenetic technology. Methods Mol Biol 791:1–10.  https://doi.org/10.1007/978-1-61779-316-5_1CrossRefGoogle Scholar
  34. 34.
    Weinhold B (2006) Epigenetics: the science of change. Environ Health Perspect 114(3):A160–A167Google Scholar
  35. 35.
    Gasperskaja E, Kucinskas V (2017) The most common technologies and tools for functional genome analysis. Acta Med Litu 24(1):1–11.  https://doi.org/10.6001/actamedica.v24i1.3457CrossRefGoogle Scholar
  36. 36.
    Schwartzman O, Tanay A (2015) Single-cell epigenomics: techniques and emerging applications. Nat Rev Genet 16(12):716–726.  https://doi.org/10.1038/nrg3980CrossRefGoogle Scholar
  37. 37.
    Milne TA, Zhao K, Hess JL (2009) Chromatin immunoprecipitation (ChIP) for analysis of histone modifications and chromatin-associated proteins. Methods Mol Biol 538:409–423.  https://doi.org/10.1007/978-1-59745-418-6_21CrossRefGoogle Scholar
  38. 38.
    Zarnegar MA, Reinitz F, Newman AM, Clarke MF (2017) Targeted chromatin ligation, a robust epigenetic profiling technique for small cell numbers. Nucleic Acids Res 45(17):e153.  https://doi.org/10.1093/nar/gkx648CrossRefGoogle Scholar
  39. 39.
    Teste B, Champ J, Londono-Vallejo A, Descroix S, Malaquin L, Viovy JL, Draskovic I, Mottet G (2017) Chromatin immunoprecipitation in microfluidic droplets: towards fast and cheap analyses. Lab Chip 17(3):530–537.  https://doi.org/10.1039/c6lc01535bCrossRefGoogle Scholar
  40. 40.
    Rotem A, Ram O, Shoresh N, Sperling RA, Goren A, Weitz DA, Bernstein BE (2015) Single-cell ChIP-seq reveals cell subpopulations defined by chromatin state. Nat Biotechnol 33(11):1165–1172.  https://doi.org/10.1038/nbt.3383CrossRefGoogle Scholar
  41. 41.
    Hansel-Hertsch R, Spiegel J, Marsico G, Tannahill D, Balasubramanian S (2018) Genome-wide mapping of endogenous G-quadruplex DNA structures by chromatin immunoprecipitation and high-throughput sequencing. Nat Protoc 13(3):551–564.  https://doi.org/10.1038/nprot.2017.150CrossRefGoogle Scholar
  42. 42.
    Gaasterland T, Oprea M (2001) Whole-genome analysis: annotations and updates. Curr Opin Struct Biol 11(3):377–381Google Scholar
  43. 43.
    Behjati S, Tarpey PS (2013) What is next generation sequencing? Arch Dis Child Educ Pract Ed 98(6):236–238.  https://doi.org/10.1136/archdischild-2013-304340CrossRefGoogle Scholar
  44. 44.
    Almouzni G, Cedar H (2016) Maintenance of epigenetic information. Cold Spring Harb Perspect Biol 8(5).  https://doi.org/10.1101/cshperspect.a019372Google Scholar
  45. 45.
    Moore LD, Le T, Fan G (2013) DNA methylation and its basic function. Neuropsychopharmacology 38(1):23–38.  https://doi.org/10.1038/npp.2012.112CrossRefGoogle Scholar
  46. 46.
    Li E, Zhang Y (2014) DNA methylation in mammals. Cold Spring Harb Perspect Biol 6(5):a019133.  https://doi.org/10.1101/cshperspect.a019133CrossRefGoogle Scholar
  47. 47.
    Tucker T, Marra M, Friedman JM (2009) Massively parallel sequencing: the next big thing in genetic medicine. Am J Hum Genet 85(2):142–154.  https://doi.org/10.1016/j.ajhg.2009.06.022CrossRefGoogle Scholar
  48. 48.
    Li Q, Hermanson PJ, Springer NM (2018) Detection of DNA methylation by whole-genome bisulfite sequencing. Methods Mol Biol 1676:185–196.  https://doi.org/10.1007/978-1-4939-7315-6_11CrossRefGoogle Scholar
  49. 49.
    Lu X, Han D, Zhao BS, Song CX, Zhang LS, Dore LC, He C (2015) Base-resolution maps of 5-formylcytosine and 5-carboxylcytosine reveal genome-wide DNA demethylation dynamics. Cell Res 25(3):386–389.  https://doi.org/10.1038/cr.2015.5CrossRefGoogle Scholar
  50. 50.
    Yu M, Han D, Hon GC, He C (2018) Tet-assisted bisulfite sequencing (TAB-seq). Methods Mol Biol 1708:645–663.  https://doi.org/10.1007/978-1-4939-7481-8_33CrossRefGoogle Scholar
  51. 51.
    Kawasaki Y, Kuroda Y, Suetake I, Tajima S, Ishino F, Kohda T (2017) A novel method for the simultaneous identification of methylcytosine and hydroxymethylcytosine at a single base resolution. Nucleic Acids Res 45(4):e24.  https://doi.org/10.1093/nar/gkw994CrossRefGoogle Scholar
  52. 52.
    Lu X, Song CX, Szulwach K, Wang Z, Weidenbacher P, Jin P, He C (2013) Chemical modification-assisted bisulfite sequencing (CAB-seq) for 5-carboxylcytosine detection in DNA. J Am Chem Soc 135(25):9315–9317.  https://doi.org/10.1021/ja4044856CrossRefGoogle Scholar
  53. 53.
    Song CX, Szulwach KE, Dai Q, Fu Y, Mao SQ, Lin L, Street C, Li Y, Poidevin M, Wu H, Gao J, Liu P, Li L, Xu GL, Jin P, He C (2013) Genome-wide profiling of 5-formylcytosine reveals its roles in epigenetic priming. Cell 153(3):678–691.  https://doi.org/10.1016/j.cell.2013.04.001CrossRefGoogle Scholar
  54. 54.
    Guo H, Zhu P, Guo F, Li X, Wu X, Fan X, Wen L, Tang F (2015) Profiling DNA methylome landscapes of mammalian cells with single-cell reduced-representation bisulfite sequencing. Nat Protoc 10(5):645–659.  https://doi.org/10.1038/nprot.2015.039CrossRefGoogle Scholar
  55. 55.
    Smallwood SA, Lee HJ, Angermueller C, Krueger F, Saadeh H, Peat J, Andrews SR, Stegle O, Reik W, Kelsey G (2014) Single-cell genome-wide bisulfite sequencing for assessing epigenetic heterogeneity. Nat Methods 11(8):817–820.  https://doi.org/10.1038/nmeth.3035CrossRefGoogle Scholar
  56. 56.
    Clark SJ, Smallwood SA, Lee HJ, Krueger F, Reik W, Kelsey G (2017) Genome-wide base-resolution mapping of DNA methylation in single cells using single-cell bisulfite sequencing (scBS-seq). Nat Protoc 12(3):534–547.  https://doi.org/10.1038/nprot.2016.187CrossRefGoogle Scholar
  57. 57.
    Luo C, Keown CL, Kurihara L, Zhou J, He Y, Li J, Castanon R, Lucero J, Nery JR, Sandoval JP, Bui B, Sejnowski TJ, Harkins TT, Mukamel EA, Behrens MM, Ecker JR (2017) Single-cell methylomes identify neuronal subtypes and regulatory elements in mammalian cortex. Science 357(6351):600–604.  https://doi.org/10.1126/science.aan3351CrossRefGoogle Scholar
  58. 58.
    Angermueller C, Clark SJ, Lee HJ, Macaulay IC, Teng MJ, Hu TX, Krueger F, Smallwood S, Ponting CP, Voet T, Kelsey G, Stegle O, Reik W (2016) Parallel single-cell sequencing links transcriptional and epigenetic heterogeneity. Nat Methods 13(3):229–232.  https://doi.org/10.1038/nmeth.3728CrossRefGoogle Scholar
  59. 59.
    Han J, Zhang Z, Wang K (2018) 3C and 3C-based techniques: the powerful tools for spatial genome organization deciphering. Mol Cytogenet 11:21.  https://doi.org/10.1186/s13039-018-0368-2CrossRefGoogle Scholar
  60. 60.
    Li G, Cai L, Chang H, Hong P, Zhou Q, Kulakova EV, Kolchanov NA, Ruan Y (2014) Chromatin interaction analysis with paired-end tag (ChIA-PET) sequencing technology and application. BMC Genomics 15(Suppl 12):S11.  https://doi.org/10.1186/1471-2164-15-S12-S11CrossRefGoogle Scholar
  61. 61.
    Mumbach MR, Rubin AJ, Flynn RA, Dai C, Khavari PA, Greenleaf WJ, Chang HY (2016) HiChIP: efficient and sensitive analysis of protein-directed genome architecture. Nat Methods 13(11):919–922.  https://doi.org/10.1038/nmeth.3999CrossRefGoogle Scholar
  62. 62.
    Chen C, Ridzon DA, Broomer AJ, Zhou Z, 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(20):e179.  https://doi.org/10.1093/nar/gni178CrossRefGoogle Scholar
  63. 63.
    Varkonyi-Gasic E, Wu R, Wood M, Walton EF, Hellens RP (2007) Protocol: a highly sensitive RT-PCR method for detection and quantification of microRNAs. Plant Methods 3:12.  https://doi.org/10.1186/1746-4811-3-12CrossRefGoogle Scholar
  64. 64.
    Jacobsen N, Andreasen D, Mouritzen P (2011) Profiling microRNAs by real-time PCR. Methods Mol Biol 732:39–54.  https://doi.org/10.1007/978-1-61779-083-6_4CrossRefGoogle Scholar
  65. 65.
    Campomenosi P, Gini E, Noonan DM, Poli A, D'Antona P, Rotolo N, Dominioni L, Imperatori A (2016) A comparison between quantitative PCR and droplet digital PCR technologies for circulating microRNA quantification in human lung cancer. BMC Biotechnol 16(1):60.  https://doi.org/10.1186/s12896-016-0292-7CrossRefGoogle Scholar
  66. 66.
    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 S, 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(22):8604–8610.  https://doi.org/10.1021/ac202028gCrossRefGoogle Scholar
  67. 67.
    Song Y, Kilburn D, Song JH, Cheng Y, Saeui CT, Cheung DG, Croce CM, Yarema KJ, Meltzer SJ, Liu KJ, Wang TH (2017) Determination of absolute expression profiles using multiplexed miRNA analysis. PLoS One 12(7):e0180988.  https://doi.org/10.1371/journal.pone.0180988CrossRefGoogle Scholar
  68. 68.
    Androvic P, Valihrach L, Elling J, Sjoback R, Kubista M (2017) Two-tailed RT-qPCR: a novel method for highly accurate miRNA quantification. Nucleic Acids Res 45(15):e144.  https://doi.org/10.1093/nar/gkx588CrossRefGoogle Scholar
  69. 69.
    Moody L, He H, Pan YX, Chen H (2017) Methods and novel technology for microRNA quantification in colorectal cancer screening. Clin Epigenetics 9:119.  https://doi.org/10.1186/s13148-017-0420-9CrossRefGoogle Scholar
  70. 70.
    Sun Z, Evans J, Bhagwate A, Middha S, Bockol M, Yan H, Kocher JP (2014) CAP-miRSeq: a comprehensive analysis pipeline for microRNA sequencing data. BMC Genomics 15:423.  https://doi.org/10.1186/1471-2164-15-423CrossRefGoogle Scholar
  71. 71.
    Wu J, Liu Q, Wang X, Zheng J, Wang T, You M, Sheng Sun Z, Shi Q (2013) mirTools 2.0 for non-coding RNA discovery, profiling, and functional annotation based on high-throughput sequencing. RNA Biol 10(7):1087–1092.  https://doi.org/10.4161/rna.25193CrossRefGoogle Scholar
  72. 72.
    Rueda A, Barturen G, Lebron R, Gomez-Martin C, Alganza A, Oliver JL, Hackenberg M (2015) sRNAtoolbox: an integrated collection of small RNA research tools. Nucleic Acids Res 43(W1):W467–W473.  https://doi.org/10.1093/nar/gkv555CrossRefGoogle Scholar
  73. 73.
    Andres-Leon E, Nunez-Torres R, Rojas AM (2016) miARma-seq: a comprehensive tool for miRNA, mRNA and circRNA analysis. Sci Rep 6:25749.  https://doi.org/10.1038/srep25749CrossRefGoogle Scholar
  74. 74.
    Garcia-Gimenez JL, Rubio-Belmar PA, Peiro-Chova L, Hervas D, Gonzalez-Rodriguez D, Ibanez-Cabellos JS, Bas-Hermida P, Mena-Molla S, Garcia-Lopez EM, Pallardo FV, Bas T (2018) Circulating miRNAs as diagnostic biomarkers for adolescent idiopathic scoliosis. Sci Rep 8(1):2646.  https://doi.org/10.1038/s41598-018-21146-xCrossRefGoogle Scholar
  75. 75.
    Gustafson D, Tyryshkin K, Renwick N (2016) microRNA-guided diagnostics in clinical samples. Best Pract Res Clin Endocrinol Metab 30(5):563–575.  https://doi.org/10.1016/j.beem.2016.07.002CrossRefGoogle Scholar
  76. 76.
    Rodriguez M, Bajo-Santos C, Hessvik NP, Lorenz S, Fromm B, Berge V, Sandvig K, Line A, Llorente A (2017) Identification of non-invasive miRNAs biomarkers for prostate cancer by deep sequencing analysis of urinary exosomes. Mol Cancer 16(1):156.  https://doi.org/10.1186/s12943-017-0726-4CrossRefGoogle Scholar
  77. 77.
    Buschmann D, Kirchner B, Hermann S, Marte M, Wurmser C, Brandes F, Kotschote S, Bonin M, Steinlein OK, Pfaffl MW, Schelling G, Reithmair M (2018) Evaluation of serum extracellular vesicle isolation methods for profiling miRNAs by next-generation sequencing. J Extracell Vesicles 7(1):1481321.  https://doi.org/10.1080/20013078.2018.1481321CrossRefGoogle Scholar
  78. 78.
    Van Ness J, Van Ness LK, Galas DJ (2003) Isothermal reactions for the amplification of oligonucleotides. Proc Natl Acad Sci U S A 100(8):4504–4509.  https://doi.org/10.1073/pnas.0730811100CrossRefGoogle Scholar
  79. 79.
    Zhang Y, Zhang CY (2012) Sensitive detection of microRNA with isothermal amplification and a single-quantum-dot-based nanosensor. Anal Chem 84(1):224–231.  https://doi.org/10.1021/ac202405qCrossRefGoogle Scholar
  80. 80.
    Liu H, Tian T, Zhang Y, Ding L, Yu J, Yan M (2017) Sensitive and rapid detection of microRNAs using hairpin probes-mediated exponential isothermal amplification. Biosens Bioelectron 89(Pt 2):710–714.  https://doi.org/10.1016/j.bios.2016.10.099CrossRefGoogle Scholar
  81. 81.
    Na J, Shin GW, Son HG, Lee SV, Jung GY (2017) Multiplex quantitative analysis of microRNA expression via exponential isothermal amplification and conformation-sensitive DNA separation. Sci Rep 7(1):11396.  https://doi.org/10.1038/s41598-017-11895-6CrossRefGoogle Scholar
  82. 82.
    Urbanek MO, Nawrocka AU, Krzyzosiak WJ (2015) Small RNA detection by in situ hybridization methods. Int J Mol Sci 16(6):13259–13286.  https://doi.org/10.3390/ijms160613259CrossRefGoogle Scholar
  83. 83.
    Thomas M, Lieberman J, Lal A (2010) Desperately seeking microRNA targets. Nat Struct Mol Biol 17(10):1169–1174.  https://doi.org/10.1038/nsmb.1921CrossRefGoogle Scholar
  84. 84.
    Elmen J, Lindow M, Silahtaroglu A, Bak M, Christensen M, Lind-Thomsen A, Hedtjarn M, Hansen JB, Hansen HF, Straarup EM, McCullagh K, Kearney P, Kauppinen S (2008) Antagonism of microRNA-122 in mice by systemically administered LNA-antimiR leads to up-regulation of a large set of predicted target mRNAs in the liver. Nucleic Acids Res 36(4):1153–1162.  https://doi.org/10.1093/nar/gkm1113CrossRefGoogle Scholar
  85. 85.
    Krutzfeldt J, Rajewsky N, Braich R, Rajeev KG, Tuschl T, Manoharan M, Stoffel M (2005) Silencing of microRNAs in vivo with ‘antagomirs’. Nature 438(7068):685–689.  https://doi.org/10.1038/nature04303CrossRefGoogle Scholar
  86. 86.
    Ebert MS, Sharp PA (2010) MicroRNA sponges: progress and possibilities. RNA 16(11):2043–2050.  https://doi.org/10.1261/rna.2414110CrossRefGoogle Scholar
  87. 87.
    Kuhn DE, Martin MM, Feldman DS, Terry AV Jr, Nuovo GJ, Elton TS (2008) Experimental validation of miRNA targets. Methods 44(1):47–54.  https://doi.org/10.1016/j.ymeth.2007.09.005CrossRefGoogle Scholar
  88. 88.
    Beitzinger M, Peters L, Zhu JY, Kremmer E, Meister G (2007) Identification of human microRNA targets from isolated argonaute protein complexes. RNA Biol 4(2):76–84Google Scholar
  89. 89.
    Licatalosi DD, Mele A, Fak JJ, Ule J, Kayikci M, Chi SW, Clark TA, Schweitzer AC, Blume JE, Wang X, Darnell JC, Darnell RB (2008) HITS-CLIP yields genome-wide insights into brain alternative RNA processing. Nature 456(7221):464–469.  https://doi.org/10.1038/nature07488CrossRefGoogle Scholar
  90. 90.
    Hafner M, Landthaler M, Burger L, Khorshid M, Hausser J, Berninger P, Rothballer A, Ascano M Jr, Jungkamp AC, Munschauer M, Ulrich A, Wardle GS, Dewell S, Zavolan M, Tuschl T (2010) Transcriptome-wide identification of RNA-binding protein and microRNA target sites by PAR-CLIP. Cell 141(1):129–141.  https://doi.org/10.1016/j.cell.2010.03.009CrossRefGoogle Scholar
  91. 91.
    Danan C, Manickavel S, Hafner M (2016) PAR-CLIP: a method for transcriptome-wide identification of RNA binding protein interaction sites. Methods Mol Biol 1358:153–173.  https://doi.org/10.1007/978-1-4939-3067-8_10CrossRefGoogle Scholar
  92. 92.
    Ule J, Jensen KB, Ruggiu M, Mele A, Ule A, Darnell RB (2003) CLIP identifies Nova-regulated RNA networks in the brain. Science 302(5648):1212–1215.  https://doi.org/10.1126/science.1090095CrossRefGoogle Scholar
  93. 93.
    Favre A, Moreno G, Blondel MO, Kliber J, Vinzens F, Salet C (1986) 4-Thiouridine photosensitized RNA-protein crosslinking in mammalian cells. Biochem Biophys Res Commun 141(2):847–854Google Scholar
  94. 94.
    Bezerra R, Favre A (1990) In vivo incorporation of the intrinsic photolabel 4-thiouridine into Escherichia coli RNAs. Biochem Biophys Res Commun 166(1):29–37Google Scholar
  95. 95.
    Kishore S, Jaskiewicz L, Burger L, Hausser J, Khorshid M, Zavolan M (2011) A quantitative analysis of CLIP methods for identifying binding sites of RNA-binding proteins. Nat Methods 8(7):559–564.  https://doi.org/10.1038/nmeth.1608CrossRefGoogle Scholar
  96. 96.
    Baigude H, Ahsanullah LZ, Zhou Y, Rana TM (2012) miR-TRAP: a benchtop chemical biology strategy to identify microRNA targets. Angew Chem Int Ed Engl 51(24):5880–5883.  https://doi.org/10.1002/anie.201201512CrossRefGoogle Scholar
  97. 97.
    Cambronne XA, Shen R, Auer PL, Goodman RH (2012) Capturing microRNA targets using an RNA-induced silencing complex (RISC)-trap approach. Proc Natl Acad Sci U S A 109(50):20473–20478.  https://doi.org/10.1073/pnas.1218887109CrossRefGoogle Scholar

Copyright information

© Springer Nature Switzerland AG  2019

Authors and Affiliations

  • Carmela Dell’Aversana
    • 1
  • Federica Sarno
    • 1
  • Mariarosaria Conte
    • 2
  • Cristina Giorgio
    • 1
  • Lucia Altucci
    • 1
    Email author
  1. 1.Department of Precision MedicineUniversity of Campania “Luigi Vanvitelli”NapoliItaly
  2. 2.IRCCS, SDNNaplesItaly

Personalised recommendations