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High-content single-cell combinatorial indexing

View ORCID ProfileRyan M. Mulqueen, Dmitry Pokholok, Brendan L. O’Connell, View ORCID ProfileCasey A. Thornton, Fan Zhang, View ORCID ProfileBrian J. O’Roak, Jason Link, View ORCID ProfileGalip Gurkan Yardmici, Rosalie C. Sears, Frank J. Steemers, View ORCID ProfileAndrew C. Adey
doi: https://doi.org/10.1101/2021.01.11.425995
Ryan M. Mulqueen
1Oregon Health & Science University, Department of Molecular and Medical Genetics, Portland, OR
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Dmitry Pokholok
2ScaleBio, CA
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Brendan L. O’Connell
1Oregon Health & Science University, Department of Molecular and Medical Genetics, Portland, OR
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Casey A. Thornton
1Oregon Health & Science University, Department of Molecular and Medical Genetics, Portland, OR
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Fan Zhang
2ScaleBio, CA
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Brian J. O’Roak
1Oregon Health & Science University, Department of Molecular and Medical Genetics, Portland, OR
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Jason Link
3Oregon Health & Science University, Cancer Early Detection Advanced Research Center, Portland, OR
4Oregon Health & Science University, Knight Cancer Institute, Portland, OR
6Oregon Health & Science University, Brendan Colson Center for Pancreatic Care, Portland, OR
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Galip Gurkan Yardmici
3Oregon Health & Science University, Cancer Early Detection Advanced Research Center, Portland, OR
5Oregon Health & Science University, Department of Oncological Sciences, Portland, OR
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Rosalie C. Sears
1Oregon Health & Science University, Department of Molecular and Medical Genetics, Portland, OR
3Oregon Health & Science University, Cancer Early Detection Advanced Research Center, Portland, OR
4Oregon Health & Science University, Knight Cancer Institute, Portland, OR
5Oregon Health & Science University, Department of Oncological Sciences, Portland, OR
6Oregon Health & Science University, Brendan Colson Center for Pancreatic Care, Portland, OR
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Frank J. Steemers
2ScaleBio, CA
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Andrew C. Adey
1Oregon Health & Science University, Department of Molecular and Medical Genetics, Portland, OR
3Oregon Health & Science University, Cancer Early Detection Advanced Research Center, Portland, OR
5Oregon Health & Science University, Department of Oncological Sciences, Portland, OR
6Oregon Health & Science University, Brendan Colson Center for Pancreatic Care, Portland, OR
7Oregon Health & Science University, Knight Cardiovascular Institute, Portland, OR
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  • For correspondence: adey@ohsu.edu
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Abstract

Single-cell genomics assays have emerged as a dominant platform for interrogating complex biological systems. Methods to capture various properties at the single-cell level typically suffer a tradeoff between cell count and information content, which is defined by the number of unique and usable reads acquired per cell. We and others have described workflows that utilize single-cell combinatorial indexing (sci)1, leveraging transposase-based library construction2 to assess a variety of genomic properties in high throughput; however, these techniques often produce sparse coverage for the property of interest. Here, we describe a novel adaptor-switching strategy, ‘s3’, capable of producing one-to-two order-of-magnitude improvements in usable reads obtained per cell for chromatin accessibility (s3-ATAC), whole genome sequencing (s3-WGS), and whole genome plus chromatin conformation (s3-GCC), while retaining the same high-throughput capabilities of predecessor ‘sci’ technologies. We apply s3 to produce high-coverage single-cell ATAC-seq profiles of mouse brain and human cortex tissue; and whole genome and chromatin contact maps for two low-passage patient-derived cell lines from a primary pancreatic tumor.

Competing Interest Statement

D.P., F.Z., and F.J.S. are employees of ScaleBio. R.M.M., D.P., F.Z., F.J.S., and A.C.A. are authors on one or more patents that cover one or more components of the technologies described in this manuscript.

Copyright 
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 January 12, 2021.
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High-content single-cell combinatorial indexing
Ryan M. Mulqueen, Dmitry Pokholok, Brendan L. O’Connell, Casey A. Thornton, Fan Zhang, Brian J. O’Roak, Jason Link, Galip Gurkan Yardmici, Rosalie C. Sears, Frank J. Steemers, Andrew C. Adey
bioRxiv 2021.01.11.425995; doi: https://doi.org/10.1101/2021.01.11.425995
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High-content single-cell combinatorial indexing
Ryan M. Mulqueen, Dmitry Pokholok, Brendan L. O’Connell, Casey A. Thornton, Fan Zhang, Brian J. O’Roak, Jason Link, Galip Gurkan Yardmici, Rosalie C. Sears, Frank J. Steemers, Andrew C. Adey
bioRxiv 2021.01.11.425995; doi: https://doi.org/10.1101/2021.01.11.425995

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