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Seq-Well: A Sample-Efficient, Portable Picowell Platform for Massively Parallel Single-Cell RNA Sequencing

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Single Cell Methods

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1979))

Abstract

Seq-Well is a low-cost picowell platform that can be used to simultaneously profile the transcriptomes of thousands of cells from diverse, low input clinical samples. In Seq-Well, uniquely barcoded mRNA capture beads and cells are co-confined in picowells that are sealed using a semipermeable membrane, enabling efficient cell lysis and mRNA capture. The beads are subsequently removed and processed in parallel for sequencing, with each transcript’s cell of origin determined via the unique barcodes. Due to its simplicity and portability, Seq-Well can be performed almost anywhere.

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References

  1. Kolodziejczyk AA, Lönnberg T (2018) Global and targeted approaches to single-cell transcriptome characterization. Brief Funct Genomics 17:209–219. https://doi.org/10.1093/bfgp/elx025

    Article  CAS  PubMed  Google Scholar 

  2. Svensson V, Vento-Tormo R, Teichmann SA (2018) Exponential scaling of single-cell RNA-seq in the past decade. Nat Protoc 13:599–604. https://doi.org/10.1038/nprot.2017.149

    Article  CAS  PubMed  Google Scholar 

  3. Kolodziejczyk AA, Kim JK, Svensson V et al (2015) The technology and biology of single-cell RNA sequencing. Mol Cell 58:610–620. https://doi.org/10.1016/j.molcel.2015.04.005

    Article  CAS  PubMed  Google Scholar 

  4. Ziegenhain C, Vieth B, Parekh S et al (2017) Comparative analysis of single-cell RNA sequencing methods. Mol Cell 65:631–643.e4. https://doi.org/10.1016/j.molcel.2017.01.023

    Article  CAS  PubMed  Google Scholar 

  5. Tang F, Barbacioru C, Wang Y et al (2009) mRNA-Seq whole-transcriptome analysis of a single cell. Nat Methods 6:377–382. https://doi.org/10.1038/nmeth.1315

    Article  CAS  PubMed  Google Scholar 

  6. Macaulay IC, Svensson V, Labalette C et al (2016) Single-cell RNA-sequencing reveals a continuous spectrum of differentiation in hematopoietic cells. Cell Rep 14:966–977. https://doi.org/10.1016/j.celrep.2015.12.082

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Shalek AK, Satija R, Adiconis X et al (2013) Single-cell transcriptomics reveals bimodality in expression and splicing in immune cells. Nature 498:236–240. https://doi.org/10.1038/nature12172

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Klein AM, Mazutis L, Akartuna I et al (2015) Droplet barcoding for single-cell transcriptomics applied to embryonic stem cells. Cell 161:1187–1201. https://doi.org/10.1016/j.cell.2015.04.044

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Macosko EZ, Basu A, Satija R et al (2015) Highly parallel genome-wide expression profiling of individual cells using nanoliter droplets. Cell 161:1202–1214. https://doi.org/10.1016/j.cell.2015.05.002

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Zheng GXY, Terry JM, Belgrader P et al (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 

  11. Gierahn TM, Ii MHW, Hughes TK et al (2017) Seq-Well: portable, low-cost RNA sequencing of single cells at high throughput. Nat Methods 14:395–398. https://doi.org/10.1038/nmeth.4179

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Bose S, Wan Z, Carr A et al (2015) Scalable microfluidics for single-cell RNA printing and sequencing. Genome Biol 16:120. https://doi.org/10.1186/s13059-015-0684-3

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Kivioja T, Vähärautio A, Karlsson K et al (2012) Counting absolute numbers of molecules using unique molecular identifiers. Nat Methods 9:72–74. https://doi.org/10.1038/nmeth.1778

    Article  CAS  Google Scholar 

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Acknowledgments

R.G. was supported by the Intramural Research Program of the Division of Intramural Research Z01AI000947, NIAID, NIH; the UCLA-Caltech MSTP, and the NIGMS T32 GM008042. A.K.S. was supported by the Searle Scholars Program, the Beckman Young Investigator Program, the Pew-Stewart Scholars, a Sloan Fellowship in Chemistry, NIH grants 1DP2OD020839, 2U19AI089992, 1U54CA217377, P01AI039671, 5U24AI118672, 2RM1HG006193, 1R33CA202820, 2R01HL095791, 1R01AI138546, 1R01HL126554, 1R01DA046277, 2R01HL095791, and Bill and Melinda Gates Foundation grants OPP1139972, OPP1137006, and OPP1116944. J.C.L. was supported by NIH grants DP3DK09768101, P01AI045757, R21AI106025, and R56AI104274, the W.M. Keck Foundation, Camille Dreyfus Teacher-Scholar program, and the US Army Research Office through the Institute for Soldier Nanotechnologies, under contract number W911NF-13-D-0001. This work was also supported in part by the Koch Institute Support (core) NIH Grant P30-CA14051 from the National Cancer Institute.

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Aicher, T.P. et al. (2019). Seq-Well: A Sample-Efficient, Portable Picowell Platform for Massively Parallel Single-Cell RNA Sequencing. In: Proserpio, V. (eds) Single Cell Methods. Methods in Molecular Biology, vol 1979. Humana, New York, NY. https://doi.org/10.1007/978-1-4939-9240-9_8

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  • DOI: https://doi.org/10.1007/978-1-4939-9240-9_8

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  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-4939-9239-3

  • Online ISBN: 978-1-4939-9240-9

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