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Multiplexed droplet single-cell RNA-sequencing using natural genetic variation

Nature Biotechnology volume 36, pages 89–94 (2018)Cite this article

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An Author Correction to this article was published on 14 October 2020

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Abstract

Droplet single-cell RNA-sequencing (dscRNA-seq) has enabled rapid, massively parallel profiling of transcriptomes. However, assessing differential expression across multiple individuals has been hampered by inefficient sample processing and technical batch effects. Here we describe a computational tool, demuxlet, that harnesses natural genetic variation to determine the sample identity of each droplet containing a single cell (singlet) and detect droplets containing two cells (doublets). These capabilities enable multiplexed dscRNA-seq experiments in which cells from unrelated individuals are pooled and captured at higher throughput than in standard workflows. Using simulated data, we show that 50 single-nucleotide polymorphisms (SNPs) per cell are sufficient to assign 97% of singlets and identify 92% of doublets in pools of up to 64 individuals. Given genotyping data for each of eight pooled samples, demuxlet correctly recovers the sample identity of >99% of singlets and identifies doublets at rates consistent with previous estimates. We apply demuxlet to assess cell-type-specific changes in gene expression in 8 pooled lupus patient samples treated with interferon (IFN)-β and perform eQTL analysis on 23 pooled samples.

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Figure 1: Demuxlet: demultiplexing and doublet identification from single-cell data.
Figure 2: Performance of demuxlet.
Figure 3: Inter-individual variability in IFN-β response.
Figure 4: Genetic control over cell type proportion and gene expression (N = 23).

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  • 14 October 2020

    An amendment to this paper has been published and can be accessed via a link at the top of the paper.

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Acknowledgements

M.S. and C.J.Y. are supported by NIH R01AR071522 and R21AI133337. S.T. is supported by NIH F30DK115167. H.M.K. is supported by U01HL137182. N.Z. is supported by NIH K25HL121295, R03DE025665, and Department of Defense W81WH-16-2-0018.

Author information

Author notes

  1. Hyun Min Kang, Meena Subramaniam and Sasha Targ: These authors contributed equally to this work.

Authors and Affiliations

  1. Department of Biostatistics and Center for Statistical Genetics, University of Michigan School of Public Health, Ann Arbor, Michigan, USA

    Hyun Min Kang

  2. Biological and Medical Informatics Graduate Program, University of California, San Francisco, San Francisco, California, USA

    Meena Subramaniam, Sasha Targ & Rachel E Gate

  3. Institute for Human Genetics (IHG), University of California,, San Francisco, San Francisco, California, USA

    Meena Subramaniam, Sasha Targ, Lenka Maliskova, Eunice Wan, Simon Wong, Rachel E Gate, Noah Zaitlen, Lindsey A Criswell & Chun Jimmie Ye

  4. Institute for Computational Health Sciences, University of California,, San Francisco, San Francisco, California, USA

    Meena Subramaniam, Sasha Targ, Rachel E Gate & Chun Jimmie Ye

  5. Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, California, USA

    Meena Subramaniam, Sasha Targ, Rachel E Gate & Chun Jimmie Ye

  6. Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, California, USA

    Meena Subramaniam, Sasha Targ, Rachel E Gate & Chun Jimmie Ye

  7. Medical Scientist Training Program (MSTP), University of California, San Francisco, San Francisco, California, USA

    Sasha Targ & Elizabeth McCarthy

  8. Department of Microbiology and Immunology, University of California, San Francisco, San Francisco, California, USA

    Michelle Nguyen & Alexander Marson

  9. Diabetes Center, University of California, San Francisco, San Francisco, California, USA

    Michelle Nguyen & Alexander Marson

  10. Innovative Genomics Institute, University of California, Berkeley, Berkeley, California, USA

    Michelle Nguyen & Alexander Marson

  11. Department of Neurology, University of California, San Francisco, San Francisco, California, USA

    Lenka Maliskova

  12. Developmental and Stem Cell Biology Graduate Program, University of California, San Francisco, San Francisco, California, USA

    Lauren Byrnes

  13. Department of Medicine, University of California, San Francisco, San Francisco, California, USA

    Cristina M Lanata, Alexander Marson, Noah Zaitlen & Lindsey A Criswell

  14. Rosalind Russell/Ephraim P Engleman Rheumatology Research Center, University of California, San Francisco, San Francisco, California, USA

    Cristina M Lanata & Lindsey A Criswell

  15. Department of Statistics, University of British Columbia, Vancouver, British Columbia, Canada

    Sara Mostafavi

  16. UCSF Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, California, USA

    Alexander Marson

  17. Chan Zuckerberg Biohub, San Francisco, California, USA

    Alexander Marson

  18. Lung Biology Center, University of California, San Francisco, San Francisco, California, USA

    Noah Zaitlen

  19. Department of Orofacial Sciences, University of California, San Francisco, San Francisco, USA

    Lindsey A Criswell

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  1. Hyun Min Kang
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Contributions

H.M.K. and C.J.Y. conceived the project. M.S., S.T., L.M., R.G., L.B., E.W., S.W., and M.N. performed all experiments. H.M.K., M.S., S.T., E.M., S.M., and C.J.Y. analyzed the data. C.L. and L.A.C. provided the patient samples. N.Z. and A.M. provided helpful comments and discussion. H.M.K., M.S., S.T., and C.J.Y. wrote the manuscript.

Corresponding authors

Correspondence to Hyun Min Kang or Chun Jimmie Ye.

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Competing interests

A.M. is a founder of Spotlight Therapeutics and serves as an advisor to Juno Therapeutics and PACT Pharma; the Marson laboratory has received sponsored research support from Juno Therapeutics and Epinomics.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–21 (PDF 3273 kb)

Life Sciences Reporting Summary (PDF 130 kb)

Supplementary Table 1

Cell type specific differentially expressed genes (XLSX 680 kb)

Supplementary Table 2

Pathway enrichment for differentially expressed genes (XLSX 97 kb)

Supplementary Table 3

Cell type specific eQTLs (PDF 369 kb)

Supplementary Table 4

Base Call Probabilities (XLSX 2726 kb)

Supplementary Code

Implementation of demuxlet (ZIP 4903 kb)

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Kang, H., Subramaniam, M., Targ, S. et al. Multiplexed droplet single-cell RNA-sequencing using natural genetic variation. Nat Biotechnol 36, 89–94 (2018). https://doi.org/10.1038/nbt.4042

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