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Cited by 199

The DOI matches its Crossref record; 26 of the 26 references it cites were found in a registry or an index.

Nuclei multiplexing with barcoded antibodies for single-nucleus genomics

Gaublomme, Jellert T., Li, Bo, McCabe, Cristin, Knecht, Abigail, Yang, Yiming, Drokhlyansky, Eugene, Van Wittenberghe, Nicholas, Waldman, Julia, Dionne, Danielle, Nguyen, Lan, De Jager, Philip L., Yeung, Bertrand, Zhao, Xinfang, Habib, Naomi, Rozenblatt-Rosen, Orit, Regev, Aviv·2019·Nature Communications
DOI 10.1038/s41467-019-10756-2PMC PMC6606589

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Abstract

Single-nucleus RNA-seq (snRNA-seq) enables the interrogation of cellular states in complex tissues that are challenging to dissociate or are frozen, and opens the way to human genetics studies, clinical trials, and precise cell atlases of large organs. However, such applications are currently limited by batch effects, processing, and costs. Here, we present an approach for multiplexing snRNA-seq, using sample-barcoded antibodies to uniquely label nuclei from distinct samples. Comparing human brain cortex samples profiled with or without hashing antibodies, we demonstrate that nucleus hashing does not significantly alter recovered profiles. We develop DemuxEM, a computational tool that detects inter-sample multiplets and assigns singlets to their sample of origin, and validate its accuracy using sex-specific gene expression, species-mixing and natural genetic variation. Our approach will facilitate tissue atlases of isogenic model organisms or from multiple biopsies or longitudinal samples of one donor, and large-scale perturbation screens.

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Crossref · 10.1038/s41467-019-10756-2

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Figures

Fig. 1 Nuclei multiplexing using DNA-barcoded antibodies targeting the nuclear pore complex. a Experimental workflow. Nuclei are isolated from frozen tissues and stained with DNA-barcoded antibodies targeting the nuclear pore complex (MAb414, Biolegend). The DNA barcode encodes a unique sequence representing each tissue sample, enabling sequence-based identification of each nucleus after pooling and profiling the different samples. b–e Hashed and non-hashed samples of the human cortex from eight postmortem donors yield comparable results. b t-stochastic neighborhood embedding (tSNE) of single-nucleus profiles (dots) colored by cell type. c tSNE as in b colored by type of protocol. Non-hashed control sample (blue) and hashed sample (orange) show similar patterns. d Cell-type frequencies observed for hashed (orange) and non-hashed control (blue) samples. The adjusted mutual information (AMI) is shown at the top left. e Distributions of the number of expressed genes (y- axis, left) in each cell type (x-axis) in b, for nuclei from hashed (orange) and non-hashed control (blue) samples. f, g Hashed single nuclei from all donors are similarly represented across cell-type clusters. f tSNE as in b colored by donor. g Observed frequencies (y-axis) of each cell type (x-axis) per donor (color). The adjusted mutual information (AMI) is shown at the top left. Please follow the Supplementary Note in the Supplementary Information to reproduce this figure. Availability of source data is indicated in the Data Availability statement
Fig. 1 Nuclei multiplexing using DNA-barcoded antibodies targeting the nuclear pore complex. a Experimental workflow. Nuclei are isolated from frozen tissues and stained with DNA-barcoded antibodies targeting the nuclear pore complex (MAb414, Biolegend). The DNA barcode encodes a unique sequence representing each tissue sample, enabling sequence-based identification of each nucleus after pooling and profiling the different samples. b–e Hashed and non-hashed samples of the human cortex from eight postmortem donors yield comparable results. b t-stochastic neighborhood embedding (tSNE) of single-nucleus profiles (dots) colored by cell type. c tSNE as in b colored by type of protocol. Non-hashed control sample (blue) and hashed sample (orange) show similar patterns. d Cell-type frequencies observed for hashed (orange) and non-hashed control (blue) samples. The adjusted mutual information (AMI) is shown at the top left. e Distributions of the number of expressed genes (y- axis, left) in each cell type (x-axis) in b, for nuclei from hashed (orange) and non-hashed control (blue) samples. f, g Hashed single nuclei from all donors are similarly represented across cell-type clusters. f tSNE as in b colored by donor. g Observed frequencies (y-axis) of each cell type (x-axis) per donor (color). The adjusted mutual information (AMI) is shown at the top left. Please follow the Supplementary Note in the Supplementary Information to reproduce this figure. Availability of source data is indicated in the Data Availability statementCC BY · PubMed Central
Fig. 2 Sample assignment by DemuxEM allows overloading of hashed samples. a DemuxEM takes as input for each nucleus a count vector of hashtag UMIs (left) and estimates it as the sum of a background count vector (right, gray histograms) and a signal sample assignment count vector (right, color histograms). Schematic examples: singlet (top), multiplet (middle), and unassigned (bottom). b Validation by sex mixing in isogenic mice. Distribution of Xist expression (y-axis, log(TP100K + 1)) from eight (1–4 females, 5–8 males) cortex samples that were pooled. There is 94.8% agreement between DemuxEM-assigned sample identities of singlets and Xist expression. c, d Species mixing of the human and mouse cortex nuclei. c Species-mixing plot. Each nucleus (dot) is plotted by the number of RNA UMIs aligned to pre-mRNA mouse mm10 (x-axis) and human GRCh38 (y-axis) references (Methods), and colored by its DemuxEM-predicted identity for singlet human (red), singlet mouse (blue), or different multiplets (intra-species: green (mouse) and purple (human); inter-species: fuchsia). S24 singlets (chartreuse) and multiplets (any multiplet that includes a nucleus from sample S24, orange) are colored separately due to its large contribution to ambient hashtags. d Distribution of ambient hashtags matching the sample DNA barcode (x-axis) identified S24 as a disproportionate contributor. e, f Validation of hashtag-based assignment by natural genetic variation. Shown is the number of nuclei classified as singlet, multiplet or unassigned (rows, columns) by either natural genetic variation (columns) with Demuxlet7, or hashtag UMIs (rows), with (e) DemuxEM or (f) Seurat11. The agreement between Demuxlet and DemuxEM or Seurat is 96 and 92%, respectively. g–j Nucleus hashing enables overloading. g tSNE of combined singlets of eight hashed human cortex samples profiled at loading concentrations of 500, 1500, 3000, or 4500 nuclei/μl. Each nucleus (dot) is colored by its cell type. h Comparable distributions of the number of expressed genes (y-axis) in each cell type (x-axis) in g. i tSNE as in g, colored by loading concentration. j Comparable frequencies (y-axis) across cell types in g (x-axis). Please follow the Supplementary Note in the Supplementary Information to reproduce this figure. Availability of source data is indicated in the Data Availability statement
Fig. 2 Sample assignment by DemuxEM allows overloading of hashed samples. a DemuxEM takes as input for each nucleus a count vector of hashtag UMIs (left) and estimates it as the sum of a background count vector (right, gray histograms) and a signal sample assignment count vector (right, color histograms). Schematic examples: singlet (top), multiplet (middle), and unassigned (bottom). b Validation by sex mixing in isogenic mice. Distribution of Xist expression (y-axis, log(TP100K + 1)) from eight (1–4 females, 5–8 males) cortex samples that were pooled. There is 94.8% agreement between DemuxEM-assigned sample identities of singlets and Xist expression. c, d Species mixing of the human and mouse cortex nuclei. c Species-mixing plot. Each nucleus (dot) is plotted by the number of RNA UMIs aligned to pre-mRNA mouse mm10 (x-axis) and human GRCh38 (y-axis) references (Methods), and colored by its DemuxEM-predicted identity for singlet human (red), singlet mouse (blue), or different multiplets (intra-species: green (mouse) and purple (human); inter-species: fuchsia). S24 singlets (chartreuse) and multiplets (any multiplet that includes a nucleus from sample S24, orange) are colored separately due to its large contribution to ambient hashtags. d Distribution of ambient hashtags matching the sample DNA barcode (x-axis) identified S24 as a disproportionate contributor. e, f Validation of hashtag-based assignment by natural genetic variation. Shown is the number of nuclei classified as singlet, multiplet or unassigned (rows, columns) by either natural genetic variation (columns) with Demuxlet7, or hashtag UMIs (rows), with (e) DemuxEM or (f) Seurat11. The agreement between Demuxlet and DemuxEM or Seurat is 96 and 92%, respectively. g–j Nucleus hashing enables overloading. g tSNE of combined singlets of eight hashed human cortex samples profiled at loading concentrations of 500, 1500, 3000, or 4500 nuclei/μl. Each nucleus (dot) is colored by its cell type. h Comparable distributions of the number of expressed genes (y-axis) in each cell type (x-axis) in g. i tSNE as in g, colored by loading concentration. j Comparable frequencies (y-axis) across cell types in g (x-axis). Please follow the Supplementary Note in the Supplementary Information to reproduce this figure. Availability of source data is indicated in the Data Availability statementCC BY · PubMed Central

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Research works printed but not linked: 1

  1. Nagy, C. et al. Single-nucleus RNA sequencing shows convergent evidence from different cell types for altered synaptic plasticity in major depressive disorder. BioRxiv, https://doi.org/10.1101/384479 (2018). · DOI · Paper page

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Metadata

Authors
Gaublomme, J. T., Li, B., McCabe, C., Knecht, A., Yang, Y., Drokhlyansky, E., Van Wittenberghe, N., Waldman, J., Dionne, D., Nguyen, L., De Jager, P. L., Yeung, B., Zhao, X., Habib, N., Rozenblatt-Rosen, O., & Regev, A.
ORCID
Venue
Nature Communications
Publisher
Springer Science and Business Media LLC
Published
2019-07-02
Volume
10
Issue
1
ISSN
2041-1723
DOI
10.1038/s41467-019-10756-2
PMC
PMC6606589
Cited by
199
References
26
Language
en
Update notices
correction (2020-11-02)
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