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Highly Efficient, Massively-Parallel Single-Cell RNA-Seq Reveals Cellular States and Molecular Features of Human Skin Pathology

Travis K Hughes, Marc H Wadsworth II, Todd M Gierahn, Tran Do, David Weiss, Priscilla R. Andrade, Feiyang Ma, Bruno J. de Andrade Silva, Shuai Shao, Lam C Tsoi, Jose Ordovas-Montanes, Johann E Gudjonsson, Robert L Modlin, J Christopher Love, Alex K Shalek
doi: https://doi.org/10.1101/689273
Travis K Hughes
1Institute for Medical Engineering & Science (IMES) and Department of Chemistry, MIT, Cambridge, Massachusetts, USA
2Department of Immunology, Harvard Medical School, Boston, MA 02115, USA
3Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
4Ragon Institute of MGH, MIT and Harvard, Cambridge, Massachusetts, USA
5Koch Institute for Integrative Cancer Research, MIT, Cambridge, Massachusetts, USA
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Marc H Wadsworth II
1Institute for Medical Engineering & Science (IMES) and Department of Chemistry, MIT, Cambridge, Massachusetts, USA
3Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
4Ragon Institute of MGH, MIT and Harvard, Cambridge, Massachusetts, USA
5Koch Institute for Integrative Cancer Research, MIT, Cambridge, Massachusetts, USA
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Todd M Gierahn
5Koch Institute for Integrative Cancer Research, MIT, Cambridge, Massachusetts, USA
6Department of Chemical Engineering, MIT, Cambridge, Massachusetts, USA
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Tran Do
7Division of Dermatology and Department of Microbiology, Immunology and Molecular Biology, David Geffen School of Medicine at UCLA, Los Angeles, California, USA
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David Weiss
7Division of Dermatology and Department of Microbiology, Immunology and Molecular Biology, David Geffen School of Medicine at UCLA, Los Angeles, California, USA
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Priscilla R. Andrade
7Division of Dermatology and Department of Microbiology, Immunology and Molecular Biology, David Geffen School of Medicine at UCLA, Los Angeles, California, USA
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Feiyang Ma
7Division of Dermatology and Department of Microbiology, Immunology and Molecular Biology, David Geffen School of Medicine at UCLA, Los Angeles, California, USA
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Bruno J. de Andrade Silva
7Division of Dermatology and Department of Microbiology, Immunology and Molecular Biology, David Geffen School of Medicine at UCLA, Los Angeles, California, USA
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Shuai Shao
8Department of Dermatology, University of Michigan, Ann Arbor, Michigan, USA
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Lam C Tsoi
8Department of Dermatology, University of Michigan, Ann Arbor, Michigan, USA
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Jose Ordovas-Montanes
1Institute for Medical Engineering & Science (IMES) and Department of Chemistry, MIT, Cambridge, Massachusetts, USA
3Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
4Ragon Institute of MGH, MIT and Harvard, Cambridge, Massachusetts, USA
5Koch Institute for Integrative Cancer Research, MIT, Cambridge, Massachusetts, USA
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Johann E Gudjonsson
8Department of Dermatology, University of Michigan, Ann Arbor, Michigan, USA
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Robert L Modlin
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J Christopher Love
3Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
4Ragon Institute of MGH, MIT and Harvard, Cambridge, Massachusetts, USA
5Koch Institute for Integrative Cancer Research, MIT, Cambridge, Massachusetts, USA
6Department of Chemical Engineering, MIT, Cambridge, Massachusetts, USA
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  • For correspondence: shalek@mit.edu clove@mit.edu
Alex K Shalek
1Institute for Medical Engineering & Science (IMES) and Department of Chemistry, MIT, Cambridge, Massachusetts, USA
2Department of Immunology, Harvard Medical School, Boston, MA 02115, USA
3Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA
4Ragon Institute of MGH, MIT and Harvard, Cambridge, Massachusetts, USA
5Koch Institute for Integrative Cancer Research, MIT, Cambridge, Massachusetts, USA
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  • For correspondence: shalek@mit.edu clove@mit.edu
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SUMMARY

The development of high-throughput single-cell RNA-sequencing (scRNA-Seq) methodologies has empowered the characterization of complex biological samples by dramatically increasing the number of constituent cells that can be examined concurrently. Nevertheless, these approaches typically recover substantially less information per-cell as compared to lower-throughput microtiter plate-based strategies. To uncover critical phenotypic differences among cells and effectively link scRNA-Seq observations to legacy datasets, reliable detection of phenotype-defining transcripts – such as transcription factors, affinity receptors, and signaling molecules – by these methods is essential. Here, we describe a substantially improved massively-parallel scRNA-Seq protocol we term Seq-Well S^3 (“Second-Strand Synthesis”) that increases the efficiency of transcript capture and gene detection by up to 10- and 5-fold, respectively, relative to previous iterations, surpassing best-in-class commercial analogs. We first characterized the performance of Seq-Well S^3 in cell lines and PBMCs, and then examined five different inflammatory skin diseases, illustrative of distinct types of inflammation, to explore the breadth of potential immune and parenchymal cell states. Our work presents an essential methodological advance as well as a valuable resource for studying the cellular and molecular features that inform human skin inflammation.

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The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted July 02, 2019.
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Highly Efficient, Massively-Parallel Single-Cell RNA-Seq Reveals Cellular States and Molecular Features of Human Skin Pathology
Travis K Hughes, Marc H Wadsworth II, Todd M Gierahn, Tran Do, David Weiss, Priscilla R. Andrade, Feiyang Ma, Bruno J. de Andrade Silva, Shuai Shao, Lam C Tsoi, Jose Ordovas-Montanes, Johann E Gudjonsson, Robert L Modlin, J Christopher Love, Alex K Shalek
bioRxiv 689273; doi: https://doi.org/10.1101/689273
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Highly Efficient, Massively-Parallel Single-Cell RNA-Seq Reveals Cellular States and Molecular Features of Human Skin Pathology
Travis K Hughes, Marc H Wadsworth II, Todd M Gierahn, Tran Do, David Weiss, Priscilla R. Andrade, Feiyang Ma, Bruno J. de Andrade Silva, Shuai Shao, Lam C Tsoi, Jose Ordovas-Montanes, Johann E Gudjonsson, Robert L Modlin, J Christopher Love, Alex K Shalek
bioRxiv 689273; doi: https://doi.org/10.1101/689273

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