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NGS-Based High-Throughput Screen to Identify MicroRNAs Regulating Growth of B-Cell Lymphoma

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Lymphoma

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1956))

Abstract

MicroRNAs (miRNAs) play important roles in development, differentiation, and homeostasis by regulating protein translation. In B-cell lymphoma, many miRNAs have altered expression levels, and for a limited subset of them, experimental data supports their functional relevance in lymphoma pathogenesis. This chapter describes an unbiased next-generation sequencing (NGS)-based high-throughput screening approach to identify miRNAs that are involved in the control of cell growth. First, we provide a protocol for performing high-throughput screening for miRNA inhibition and overexpression. Second, we describe the procedure for next-generation sequencing library preparation. Third, we provide a workflow for data analysis.

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References

  1. Chendrimada TP, Gregory RI, Kumaraswamy E et al (2005) TRBP recruits the Dicer complex to Ago2 for microRNA processing and gene silencing. Nature 436:740–744

    Article  CAS  Google Scholar 

  2. Lewis BP, Burge CB, Bartel DP (2005) Conserved seed pairing, often flanked by adenosines, indicates that thousands of human genes are MicroRNA targets. Cell 120(1):15–20

    Article  CAS  Google Scholar 

  3. Vasilatou D, Papageorgiou S, Pappa V et al (2009) The role of microRNAs in normal and malignant hematopoiesis. Eur J Haematol 84(1):1–16

    Article  Google Scholar 

  4. Koralov SB, Muljo SA, Galler GR et al (2008) Dicer ablation affects antibody diversity and cell survival in the B lymphocyte lineage. Cell 132(5):860–874

    Article  CAS  Google Scholar 

  5. de Yébenes VG, Bartolomé-Izquierdo N, Ramiro AR (2013) Regulation of B-cell development and function by microRNAs. Immunol Rev 253(1):25–39

    Article  Google Scholar 

  6. Eis PS, Tam W, Sun L et al (2005) Accumulation of miR-155 and BIC RNA in human B cell lymphomas. Proc Natl Acad Sci U S A 102(10):3627–3632

    Article  CAS  Google Scholar 

  7. Kluiver J, Haralambieva E, de Jong D et al (2006) Lack of BIC and microRNA miR-155 expression in primary cases of Burkitt lymphoma. Genes Chromosom Cancer 45(2):147–153

    Article  CAS  Google Scholar 

  8. Costinean S, Zanesi N, Pekarsky Y et al (2006) Pre-B cell proliferation and lymphoblastic leukemia/high-grade lymphoma in Eμ-miR155 transgenic mice. Proc Natl Acad Sci U S A 103(18):7024–7029

    Article  CAS  Google Scholar 

  9. Ota A, Tagawa H, Karnan S et al (2004) Identification and characterization of a novel gene, C13orf25, as a target for 13q31-q32 amplification in malignant lymphoma. Cancer Res 64(9):3087–3095

    Article  CAS  Google Scholar 

  10. Robertus JL, Kluiver J, Weggemans C et al (2010) MiRNA profiling in B non-Hodgkin lymphoma: a MYC-related miRNA profile characterizes Burkitt lymphoma. Br J Haematol 149(6):896–899

    Article  CAS  Google Scholar 

  11. Scholtysik R, Kreuz M, Klapper W et al (2010) Detection of genomic aberrations in molecularly defined Burkitt’s lymphoma by array-based, high resolution, single nucleotide polymorphism analysis. Haematologica 95(12):2047–2055

    Article  CAS  Google Scholar 

  12. Xiao C, Srinivasan L, Calado DP et al (2008) Lymphoproliferative disease and autoimmunity in mice with increased miR-17-92 expression in lymphocytes. Nat Immunol 9:405–414

    Article  CAS  Google Scholar 

  13. He L, Thomson JM, Hemann MT et al (2005) A microRNA polycistron as a potential human oncogene. Nature 435:828–833

    Article  CAS  Google Scholar 

  14. Mu P, Han Y, Betel D et al (2009) Genetic dissection of the miR-17~92 cluster of microRNAs in Myc-induced B-cell lymphomas. Genes Dev 23(24):2806–2811

    Article  CAS  Google Scholar 

  15. Olive V, Bennett MJ, Walker JC et al (2009) miR-19 is a key oncogenic component of mir-17-92. Genes Dev 23(24):2839–2849

    Article  CAS  Google Scholar 

  16. Medina PP, Nolde M, Slack FJ (2010) OncomiR addiction in an in vivo model of microRNA-21-induced pre-B-cell lymphoma. Nature 467:86–90

    Article  CAS  Google Scholar 

  17. Calin GA, Dumitru CD, Shimizu M et al (2002) Frequent deletions and down-regulation of micro- RNA genes miR15 and miR16 at 13q14 in chronic lymphocytic leukemia. Proc Natl Acad Sci U S A 99(24):15524–15529

    Article  CAS  Google Scholar 

  18. Klein U, Lia M, Crespo M et al (2010) The DLEU2/miR-15a/16-1 cluster controls B cell proliferation and its deletion leads to chronic lymphocytic leukemia. Cancer Cell 17(1):28–40

    Article  CAS  Google Scholar 

  19. Shang W, Wang F, Fan G et al (2017) Key elements for designing and performing a CRISPR/Cas9-based genetic screen. J Genet Genomics 44(9):439–449

    Article  Google Scholar 

  20. Eulalio A, Mano M (2015) MicroRNA screening and the quest for biologically relevant targets. J Biomol Screen 20(8):1003–1017

    Article  CAS  Google Scholar 

  21. Voorhoeve PM, le Sage C, Schrier M et al (2006) A genetic screen implicates miRNA-372 and miRNA-373 as oncogenes in testicular germ cell tumors. Cell 124(6):1169–1181

    Article  CAS  Google Scholar 

  22. Choi Y, Yoon S, Byun Y et al (2015) MicroRNA library screening identifies growth-suppressive microRNAs that regulate genes involved in cell cycle progression and apoptosis. Exp Cell Res 339(2):320–332

    Article  CAS  Google Scholar 

  23. Maudet C, Mano M, Sunkavalli U et al (2014) Functional high-throughput screening identifies the miR-15 microRNA family as cellular restriction factors for Salmonella infection. Nat Commun 5:4718

    Article  CAS  Google Scholar 

  24. Morris VA, Cummings C, Meshinchi S et al (2014) Functional miRNA expression library screen identifies miRNAs that alter proliferation and differentiation in acute myeloid leukemia. Blood 124(21):3541–3541

    Google Scholar 

  25. Du L, Borkowski R, Zhao Z et al (2013) A high-throughput screen identifies miRNA inhibitors regulating lung cancer cell survival and response to paclitaxel. RNA Biol 10(11):1700–1713

    Article  CAS  Google Scholar 

  26. Mullokandov G, Baccarini A, Ruzo A et al (2012) High-throughput assessment of microRNA activity and function using microRNA sensor and decoy libraries. Nat Methods 9:840–846

    Article  CAS  Google Scholar 

  27. Nikolic I, Elsworth B, Dodson E et al (2017) Discovering cancer vulnerabilities using high-throughput micro-RNA screening. Nucleic Acids Res 45(22):12657–12670

    Article  CAS  Google Scholar 

  28. Chang H, Yi B, Ma R et al (2016) CRISPR/cas9, a novel genomic tool to knock down microRNA in vitro and in vivo. Sci Rep 6:22312

    Article  CAS  Google Scholar 

  29. Friedländer MR, Chen W, Adamidi C et al (2008) Discovering microRNAs from deep sequencing data using miRDeep. Nat Biotechnol 26:407–415

    Article  Google Scholar 

  30. Kluiver J, Slezak-Prochazka I, van den Berg A (2013) Studying microRNAs in lymphoma. Methods Mol Biol 971:265–276

    Article  CAS  Google Scholar 

  31. Yuan Y, Kluiver J, Koerts J et al (2017) miR-24-3p is overexpressed in Hodgkin lymphoma and protects Hodgkin and Reed-Sternberg cells from apoptosis. Am J Pathol 187(6):1343–1355

    Article  CAS  Google Scholar 

  32. Li H, Durbin R (2009) Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics 25(14):1754–1760

    Article  CAS  Google Scholar 

  33. Li H, Handsaker B, Wysoker A et al (2009) The sequence alignment/map format and SAMtools. Bioinformatics 25(16):2078–2079

    Article  Google Scholar 

  34. Tukey J (1977) Exploratory data analysis. Pearson, London, UK

    Google Scholar 

  35. Buschmann T, Bystrykh LV (2013) Levenshtein error-correcting barcodes for multiplexed DNA sequencing. BMC Bioinformatics 14(1):272

    Article  Google Scholar 

  36. Bystrykh LV (2012) Generalized DNA barcode design based on hamming codes. PLoS One 7(5):e36852

    Article  CAS  Google Scholar 

Download references

Acknowledgments

This work was supported by grants from the National Science Centre, Poland (grant no. 2016/23/D/NZ1/01611 to A.D.-K.), and the Pediatric Oncology Foundation Groningen, the Netherlands (SKOG 11-001 to J.K. and A.v.d.B.).

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Authors and Affiliations

  1. Department of Pathology and Medical Biology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands

    Joost Kluiver, Fubiao Niu, Ye Yuan, Anke van den Berg & Agnieszka Dzikiewicz-Krawczyk

  2. Department of Clinical Pharmacy, The Second Affiliated Hospital of Harbin Medical University, Harbin, China

    Ye Yuan

  3. Department of Genetics, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands

    Klaas Kok

  4. Institute of Human Genetics, Polish Academy of Sciences, Poznan, Poland

    Agnieszka Dzikiewicz-Krawczyk

Authors
  1. Joost Kluiver
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  2. Fubiao Niu
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  3. Ye Yuan
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  4. Klaas Kok
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  5. Anke van den Berg
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  6. Agnieszka Dzikiewicz-Krawczyk
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Corresponding authors

Correspondence to Joost Kluiver or Agnieszka Dzikiewicz-Krawczyk .

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Editors and Affiliations

  1. Institute of Cell Biology (Cancer Research), Medical School, University of Duisburg-Essen, Nordrhein-Westfalen, Essen, Germany

    Ralf Küppers

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Kluiver, J., Niu, F., Yuan, Y., Kok, K., van den Berg, A., Dzikiewicz-Krawczyk, A. (2019). NGS-Based High-Throughput Screen to Identify MicroRNAs Regulating Growth of B-Cell Lymphoma. In: Küppers, R. (eds) Lymphoma. Methods in Molecular Biology, vol 1956. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-9151-8_12

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  • DOI: https://doi.org/10.1007/978-1-4939-9151-8_12

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  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-9150-1

  • Online ISBN: 978-1-4939-9151-8

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