Studying BDNF/TrkB Signaling: High-Throughput Microfluidic Gene Expression Analysis from Rare or Limited Samples of Adult and Aged Central Neurons

  • Arup R. Nath
  • Roy Drissen
  • Fei Guo
  • Claus Nerlov
  • Liliana MinichielloEmail author
Part of the Neuromethods book series (NM, volume 143)


High-throughput next generation sequencing technologies are an invaluable tool to gain insight into the transcriptional states of large cohorts of cells. Such data can help to shed light on the organization of tissues and pathways under normal and pathological conditions. In our case, we are using the above technology to decipher how the enkephalinergic medium spiny neurons (MSNs) of the striatum adapt to aging in the presence or absence of BDNF/TrkB signaling. However, sequencing data must be validated, ideally with an alternative method that interrogates the transcriptional state of cells, and is able to detect gene expression in rare single cells or bulk cells with high sensitivity. Thus, we have optimized a protocol for high-throughput microfluidic analysis [Fluidigm Dynamic Array Integrated Microfluidic Circuit (IFC)] to validate RNA sequencing data from a limited number of adult and aged sorted neurons. Here is a detailed description of this protocol.


Bulk cell Fluidigm Gene expression Heatmap High-throughput Microfluidic Quantitative RNA sequencing RT-PCR TaqMan Validation 



We would like to thank members of the Minichiello and the Nerlov laboratories for the support they provided. A.R.N. was supported by a Clarendon Scholarship. F.G. was supported by a China Scholarship Council (CSC). This work was supported by a BBSRC grant (BB/L021382/1) to L.M.


  1. 1.
    Poulin JF, Tasic B, Hjerling-Leffler J, Trimarchi JM, Awatramani R (2016) Disentangling neural cell diversity using single-cell transcriptomics. Nat Neurosci 19:1131–1141. CrossRefPubMedGoogle Scholar
  2. 2.
    Besusso D, Geibel M, Kramer D, Schneider T, Pendolino V, Picconi B, Calabresi P, Bannerman DM, Minichiello L (2013) BDNF-TrkB signaling in striatopallidal neurons controls inhibition of locomotor behavior. Nat Commun 4:2031. CrossRefPubMedPubMedCentralGoogle Scholar
  3. 3.
    Heid CA, Stevens J, Livak KJ, Williams PM (1996) Real time quantitative PCR. Genome Res 6:986–994CrossRefGoogle Scholar
  4. 4.
    Osman F, Leutenegger C, Golino D, Rowhani A (2007) Real-time RT-PCR (TaqMan) assays for the detection of Grapevine Leafroll associated viruses 1-5 and 9. J Virol Methods 141:22–29. CrossRefPubMedGoogle Scholar
  5. 5.
    Holland PM, Abramson RD, Watson R, Gelfand DH (1991) Detection of specific polymerase chain reaction product by utilizing the 5′----3′ exonuclease activity of Thermus aquaticus DNA polymerase. Proc Natl Acad Sci U S A 88:7276–7280CrossRefGoogle Scholar
  6. 6.
    Livak KJ, Schmittgen TD (2001) Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method. Methods 25:402–408. CrossRefPubMedGoogle Scholar
  7. 7.
    Drissen R, Buza-Vidas N, Woll P, Thongjuea S, Gambardella A, Giustacchini A, Mancini E, Zriwil A, Lutteropp M, Grover A, Mead A, Sitnicka E, Jacobsen SE, Nerlov C (2016) Distinct myeloid progenitor-differentiation pathways identified through single-cell RNA sequencing. Nat Immunol 17:666–676. CrossRefPubMedPubMedCentralGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2017

Authors and Affiliations

  • Arup R. Nath
    • 1
  • Roy Drissen
    • 2
  • Fei Guo
    • 1
  • Claus Nerlov
    • 2
  • Liliana Minichiello
    • 1
    Email author
  1. 1.Department of PharmacologyUniversity of OxfordOxfordUK
  2. 2.MRC Molecular Haematology Unit, Weatherall Institute of Molecular MedicineUniversity of OxfordOxfordUK

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