Skip to main content

Single-Cell RNA Sequencing of Glioblastoma Cells

  • Protocol
  • First Online:
Glioblastoma

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1741))

Abstract

Single-cell RNA sequencing (sc-RNASeq) is a recently developed technique used to evaluate the transcriptome of individual cells. As opposed to conventional RNASeq in which entire populations are sequenced in bulk, sc-RNASeq can be beneficial when trying to better understand gene expression patterns in markedly heterogeneous populations of cells or when trying to identify transcriptional signatures of rare cells that may be underrepresented when using conventional bulk RNASeq. In this method, we describe the generation and analysis of cDNA libraries from single patient-derived glioblastoma cells using the C1 Fluidigm system. The protocol details the use of the C1 integrated fluidics circuit (IFC) for capturing, imaging and lysing cells; performing reverse transcription; and generating cDNA libraries that are ready for sequencing and analysis.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Protocol
USD 49.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 89.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 119.00
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 119.00
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Tang F, Barbacioru C, Wang Y, Nordman E, Lee C, Xu N, Wang X, Bodeau J, Tuch BB, Siddiqui A, Lao K, Surani MA (2009) mRNA-Seq whole-transcriptome analysis of a single cell. Nat Methods 6(5):377–382. https://doi.org/10.1038/nmeth.1315

    Article  CAS  PubMed  Google Scholar 

  2. Brennecke P, Anders S, Kim JK, Kolodziejczyk AA, Zhang X, Proserpio V, Baying B, Benes V, Teichmann SA, Marioni JC, Heisler MG (2013) Accounting for technical noise in single-cell RNA-seq experiments. Nat Methods 10(11):1093–1095. https://doi.org/10.1038/nmeth.2645

    Article  CAS  PubMed  Google Scholar 

  3. Chiu IM, Barrett LB, Williams EK, Strochlic DE, Lee S, Weyer AD, Lou S, Bryman GS, Roberson DP, Ghasemlou N, Piccoli C, Ahat E, Wang V, Cobos EJ, Stucky CL, Ma Q, Liberles SD, Woolf CJ (2014) Transcriptional profiling at whole population and single cell levels reveals somatosensory neuron molecular diversity. eLife 3. https://doi.org/10.7554/eLife.04660

  4. Deng Q, Ramskold D, Reinius B, Sandberg R (2014) Single-cell RNA-seq reveals dynamic, random monoallelic gene expression in mammalian cells. Science (New York, NY) 343(6167):193–196. https://doi.org/10.1126/science.1245316

    Article  CAS  Google Scholar 

  5. Eckersley-Maslin MA, Thybert D, Bergmann JH, Marioni JC, Flicek P, Spector DL (2014) Random monoallelic gene expression increases upon embryonic stem cell differentiation. Dev Cell 28(4):351–365. https://doi.org/10.1016/j.devcel.2014.01.017

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Park J, Brureau A, Kernan K, Starks A, Gulati S, Ogunnaike B, Schwaber J, Vadigepalli R (2014) Inputs drive cell phenotype variability. Genome Res 24(6):930–941. https://doi.org/10.1101/gr.161802.113

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Piras V, Tomita M, Selvarajoo K (2014) Transcriptome-wide variability in single embryonic development cells. Sci Rep 4:7137. https://doi.org/10.1038/srep07137

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Poulin JF, Zou J, Drouin-Ouellet J, Kim KY, Cicchetti F, Awatramani RB (2014) Defining midbrain dopaminergic neuron diversity by single-cell gene expression profiling. Cell Rep 9(3):930–943. https://doi.org/10.1016/j.celrep.2014.10.008

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Qiu S, Luo S, Evgrafov O, Li R, Schroth GP, Levitt P, Knowles JA, Wang K (2012) Single-neuron RNA-Seq: technical feasibility and reproducibility. Front Genet 3:124. https://doi.org/10.3389/fgene.2012.00124

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Sul JY, Wu CW, Zeng F, Jochems J, Lee MT, Kim TK, Peritz T, Buckley P, Cappelleri DJ, Maronski M, Kim M, Kumar V, Meaney D, Kim J, Eberwine J (2009) Transcriptome transfer produces a predictable cellular phenotype. Proc Natl Acad Sci U S A 106(18):7624–7629. https://doi.org/10.1073/pnas.0902161106

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Dalerba P, Kalisky T, Sahoo D, Rajendran PS, Rothenberg ME, Leyrat AA, Sim S, Okamoto J, Johnston DM, Qian D, Zabala M, Bueno J, Neff NF, Wang J, Shelton AA, Visser B, Hisamori S, Shimono Y, van de Wetering M, Clevers H, Clarke MF, Quake SR (2011) Single-cell dissection of transcriptional heterogeneity in human colon tumors. Nat Biotechnol 29(12):1120–1127. https://doi.org/10.1038/nbt.2038

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Kalisky T, Blainey P, Quake SR (2011) Genomic analysis at the single-cell level. Annu Rev Genet 45:431–445. https://doi.org/10.1146/annurev-genet-102209-163607

    Article  CAS  PubMed  Google Scholar 

  13. Raj A, Peskin CS, Tranchina D, Vargas DY, Tyagi S (2006) Stochastic mRNA synthesis in mammalian cells. PLoS Biol 4(10):e309. https://doi.org/10.1371/journal.pbio.0040309

    Article  PubMed  PubMed Central  Google Scholar 

  14. Bengtsson M, Stahlberg A, Rorsman P, Kubista M (2005) Gene expression profiling in single cells from the pancreatic islets of Langerhans reveals lognormal distribution of mRNA levels. Genome Res 15(10):1388–1392. https://doi.org/10.1101/gr.3820805

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Tirosh I, Venteicher AS, Hebert C, Escalante LE, Patel AP, Yizhak K, Fisher JM, Rodman C, Mount C, Filbin MG, Neftel C, Desai N, Nyman J, Izar B, Luo CC, Francis JM, Patel AA, Onozato ML, Riggi N, Livak KJ, Gennert D, Satija R, Nahed BV, Curry WT, Martuza RL, Mylvaganam R, Iafrate AJ, Frosch MP, Golub TR, Rivera MN, Getz G, Rozenblatt-Rosen O, Cahill DP, Monje M, Bernstein BE, Louis DN, Regev A, Suva ML (2016) Single-cell RNA-seq supports a developmental hierarchy in human oligodendroglioma. Nature 539(7628):309–313. https://doi.org/10.1038/nature20123

    Article  PubMed  PubMed Central  Google Scholar 

  16. Venteicher AS, Tirosh I, Hebert C, Yizhak K, Neftel C, Filbin MG, Hovestadt V, Escalante LE, Shaw ML, Rodman C, Gillespie SM, Dionne D, Luo CC, Ravichandran H, Mylvaganam R, Mount C, Onozato ML, Nahed BV, Wakimoto H, Curry WT, Iafrate AJ, Rivera MN, Frosch MP, Golub TR, Brastianos PK, Getz G, Patel AP, Monje M, Cahill DP, Rozenblatt-Rosen O, Louis DN, Bernstein BE, Regev A, Suva ML (2017) Decoupling genetics, lineages, and microenvironment in IDH-mutant gliomas by single-cell RNA-seq. Science (New York, NY) 355(6332). https://doi.org/10.1126/science.aai8478

  17. Hashimshony T, Wagner F, Sher N, Yanai I (2012) CEL-Seq: single-cell RNA-Seq by multiplexed linear amplification. Cell Rep 2(3):666–673. https://doi.org/10.1016/j.celrep.2012.08.003

    Article  CAS  PubMed  Google Scholar 

  18. Hashimshony T, Senderovich N, Avital G, Klochendler A, de Leeuw Y, Anavy L, Gennert D, Li S, Livak KJ, Rozenblatt-Rosen O, Dor Y, Regev A, Yanai I (2016) CEL-Seq2: sensitive highly-multiplexed single-cell RNA-Seq. Genome Biol 17:77. https://doi.org/10.1186/s13059-016-0938-8

    Article  PubMed  PubMed Central  Google Scholar 

  19. Ziegenhain C, Vieth B, Parekh S, Reinius B, Guillaumet-Adkins A, Smets M, Leonhardt H, Heyn H, Hellmann I, Enard W (2017) Comparative analysis of single-cell RNA sequencing methods. Mol Cell 65(4):631–643.e634. https://doi.org/10.1016/j.molcel.2017.01.023

    Article  CAS  PubMed  Google Scholar 

  20. Zheng GX, Terry JM, Belgrader P, Ryvkin P, Bent ZW, Wilson R, Ziraldo SB, Wheeler TD, McDermott GP, Zhu J, Gregory MT, Shuga J, Montesclaros L, Underwood JG, Masquelier DA, Nishimura SY, Schnall-Levin M, Wyatt PW, Hindson CM, Bharadwaj R, Wong A, Ness KD, Beppu LW, Deeg HJ, McFarland C, Loeb KR, Valente WJ, Ericson NG, Stevens EA, Radich JP, Mikkelsen TS, Hindson BJ, Bielas JH (2017) Massively parallel digital transcriptional profiling of single cells. Nat Commun 8:14049. https://doi.org/10.1038/ncomms14049

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Satija R, Farrell JA, Gennert D, Schier AF, Regev A (2015) Spatial reconstruction of single-cell gene expression data. Nat Biotechnol 33(5):495–502. https://doi.org/10.1038/nbt.3192

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Deleyrolle LP, Harding A, Cato K, Siebzehnrubl FA, Rahman M, Azari H, Olson S, Gabrielli B, Osborne G, Vescovi A, Reynolds BA (2011) Evidence for label-retaining tumour-initiating cells in human glioblastoma. Brain 134(Pt 5):1331–1343. https://doi.org/10.1093/brain/awr081

    Article  PubMed  PubMed Central  Google Scholar 

  23. Li B, Ruotti V, Stewart RM, Thomson JA, Dewey CN (2010) RNA-Seq gene expression estimation with read mapping uncertainty. Bioinformatics 26(4):493–500. https://doi.org/10.1093/bioinformatics/btp692

    Article  PubMed  Google Scholar 

Download references

Acknowledgments

We would like to thank Fluidigm for sharing schematic images on using the C1 System, and Yutong Zhang from the NYU Langone Genome Technology Center for expert technical assistance.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Dimitris G. Placantonakis .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer Science+Business Media, LLC

About this protocol

Check for updates. Verify currency and authenticity via CrossMark

Cite this protocol

Sen, R., Dolgalev, I., Bayin, N.S., Heguy, A., Tsirigos, A., Placantonakis, D.G. (2018). Single-Cell RNA Sequencing of Glioblastoma Cells. In: Placantonakis, D. (eds) Glioblastoma. Methods in Molecular Biology, vol 1741. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-7659-1_12

Download citation

  • DOI: https://doi.org/10.1007/978-1-4939-7659-1_12

  • Published:

  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-7658-4

  • Online ISBN: 978-1-4939-7659-1

  • eBook Packages: Springer Protocols

Publish with us

Policies and ethics