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 Gürkan Yardımcı, Rosalie C. Sears, Frank J. Steemers, Andrew C. Adey

Research output: Contribution to journalArticlepeer-review

9 Scopus citations


Single-cell combinatorial indexing (sci) with transposase-based library construction increases the throughput of single-cell genomics assays but produces sparse coverage in terms of usable reads per cell. We develop symmetrical strand sci (‘s3’), a uracil-based adapter switching approach that improves the rate of conversion of source DNA into viable sequencing library fragments following tagmentation. We apply this chemistry to assay chromatin accessibility (s3-assay for transposase-accessible chromatin, s3-ATAC) in human cortical and mouse whole-brain tissues, with mouse datasets demonstrating a six- to 13-fold improvement in usable reads per cell compared with other available methods. Application of s3 to single-cell whole-genome sequencing (s3-WGS) and to whole-genome plus chromatin conformation (s3-GCC) yields 148- and 14.8-fold improvements, respectively, in usable reads per cell compared with sci-DNA-sequencing and sci-HiC. We show that s3-WGS and s3-GCC resolve subclonal genomic alterations in patient-derived pancreatic cancer cell lines. We expect that the s3 platform will be compatible with other transposase-based techniques, including sci-MET or CUT&Tag.

Original languageEnglish (US)
Pages (from-to)1574-1580
Number of pages7
JournalNature biotechnology
Issue number12
StatePublished - Dec 2021

ASJC Scopus subject areas

  • Biotechnology
  • Bioengineering
  • Applied Microbiology and Biotechnology
  • Molecular Medicine
  • Biomedical Engineering


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