Profiling Transcriptional Heterogeneity with Seq-Well S3: A Low-Cost, Portable, High-Fidelity Platform for Massively Parallel Single-Cell RNA-Seq

Riley S Drake; Martin Arreola Villanueva; Mike Vilme; Daniela D Russo; Andrew Navia; J Christopher Love; Alex K Shalek

doi:10.1007/978-1-0716-2756-3_3

Profiling Transcriptional Heterogeneity with Seq-Well S³: A Low-Cost, Portable, High-Fidelity Platform for Massively Parallel Single-Cell RNA-Seq

Methods Mol Biol. 2023:2584:57-104. doi: 10.1007/978-1-0716-2756-3_3.

Authors

Riley S Drake^#^{1

2

3

4

5}, Martin Arreola Villanueva^#^{6

7

8

9

10

11}, Mike Vilme^{1

2

3

4

5}, Daniela D Russo^{1

2

3

4

5}, Andrew Navia^{1

2

3

4

5}, J Christopher Love^#^{12

13

14

15}, Alex K Shalek^#^{16

17

18

19}

Affiliations

¹ Institute for Medical Engineering and Science (IMES), Massachusetts Institute of Technology, Cambridge, MA, USA.
² Department of Chemistry, Massachusetts Institute of Technology, Cambridge, MA, USA.
³ Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA.
⁴ The Ragon Institute of Massachusetts General Hospital, Massachusetts Institute of Technology and Harvard University, Cambridge, MA, USA.
⁵ Broad Institute of MIT and Harvard, Cambridge, MA, USA.
⁶ Institute for Medical Engineering and Science (IMES), Massachusetts Institute of Technology, Cambridge, MA, USA. mav@mit.edu.
⁷ Department of Chemistry, Massachusetts Institute of Technology, Cambridge, MA, USA. mav@mit.edu.
⁸ Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA. mav@mit.edu.
⁹ The Ragon Institute of Massachusetts General Hospital, Massachusetts Institute of Technology and Harvard University, Cambridge, MA, USA. mav@mit.edu.
¹⁰ Broad Institute of MIT and Harvard, Cambridge, MA, USA. mav@mit.edu.
¹¹ Department of Biology, Massachusetts Institute of Technology, Cambridge, MA, USA. mav@mit.edu.
¹² Koch Institute for Integrative Cancer Research, Massachusetts Institute of Technology, Cambridge, MA, USA. clove@mit.edu.
¹³ The Ragon Institute of Massachusetts General Hospital, Massachusetts Institute of Technology and Harvard University, Cambridge, MA, USA. clove@mit.edu.
¹⁴ Broad Institute of MIT and Harvard, Cambridge, MA, USA. clove@mit.edu.
¹⁵ Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA. clove@mit.edu.
¹⁶ Institute for Medical Engineering and Science (IMES), Massachusetts Institute of Technology, Cambridge, MA, USA. shalek@mit.edu.
¹⁷ Department of Chemistry, Massachusetts Institute of Technology, Cambridge, MA, USA. shalek@mit.edu.
¹⁸ The Ragon Institute of Massachusetts General Hospital, Massachusetts Institute of Technology and Harvard University, Cambridge, MA, USA. shalek@mit.edu.
¹⁹ Broad Institute of MIT and Harvard, Cambridge, MA, USA. shalek@mit.edu.

^# Contributed equally.

PMID: 36495445
DOI: 10.1007/978-1-0716-2756-3_3

Abstract

Seq-Well is a high-throughput, picowell-based single-cell RNA-seq technology that can be used to simultaneously profile the transcriptomes of thousands of cells (Gierahn et al. Nat Methods 14(4):395-398, 2017). Relative to its reverse-emulsion-droplet-based counterparts, Seq-Well addresses key cost, portability, and scalability limitations. Recently, we introduced an improved molecular biology for Seq-Well to enhance the information content that can be captured from individual cells using the platform. This update, which we call Seq-Well S³ (S³: Second-Strand Synthesis), incorporates a second-strand-synthesis step after reverse transcription to boost the detection of cellular transcripts normally missed when running the original Seq-Well protocol (Hughes et al. Immunity 53(4):878-894.e7, 2020). This chapter provides details and tips on how to perform Seq-Well S³, along with general pointers on how to subsequently analyze the resultant single-cell RNA-seq data.

Keywords: Picowells; RNA-Seq; Seq-Well; Single-cell RNA sequencing; Single-cell genomics; Systems biology; Transcriptomics; scRNA-seq.

Publication types

Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't

MeSH terms

Gene Expression Profiling / methods
High-Throughput Nucleotide Sequencing / methods
Reverse Transcription
Sequence Analysis, RNA / methods
Single-Cell Analysis* / methods
Single-Cell Gene Expression Analysis*
Transcriptome

Abstract

Publication types

MeSH terms

Grants and funding