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An ultra high-throughput method for single-cell joint analysis of open chromatin and transcriptome

Nature Structural & Molecular Biology volume 26, pages 1063–1070 (2019)Cite this article

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Abstract

Simultaneous profiling of transcriptome and chromatin accessibility within single cells is a powerful approach to dissect gene regulatory programs in complex tissues. However, current tools are limited by modest throughput. We now describe an ultra high-throughput method, Paired-seq, for parallel analysis of transcriptome and accessible chromatin in millions of single cells. We demonstrate the utility of Paired-seq for analyzing the dynamic and cell-type-specific gene regulatory programs in complex tissues by applying it to mouse adult cerebral cortex and fetal forebrain. The joint profiles of a large number of single cells allowed us to deconvolute the transcriptome and open chromatin landscapes in the major cell types within these brain tissues, infer putative target genes of candidate enhancers, and reconstruct the trajectory of cellular lineages within the developing forebrain.

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Fig. 1: Paired-seq enables simultaneous profiling of accessible chromatin and gene expression in millions of single cells.
Fig. 2: Paired-seq identified major cell types in the mouse cerebral cortex.
Fig. 3: Paired-seq links candidate CREs to their putative target genes.
Fig. 4: Analysis of cellular trajectory in the developing mouse forebrain.

Code Availability

MAPS is freely available at https://github.com/ijuric/MAPS. Custom scripts used in this study can be downloaded from https://github.com/cxzhu/paired-seq.

Data Availability

The sequencing data obtained in this study have been deposited to the NCBI Gene Expression Omnibus (GEO) (http://www.ncbi.nlm.nih.gov/geo/) under accession number GSE130399. Source data for Figs. 1e–g, 2b,e,f, 3a,b and 4b–d are available with the paper online. External data sets used in this study are available from GEO: ENCODE DNase-seq (GSE37074), PolyA-RNA-seq (GSE39524) of mouse NIH/3T3 cells, sci-CAR mixed cells datasets (GSE117089), SPLiT-seq (GSE110823), sci-RNA-seq (GSE98561), Drop-seq (GSE63269), sci-ATAC-seq (GSE67446), and dscATAC-seq (GSE123581); or from the 10X genomics website, 10X scRNA-seq (https://www.10xgenomics.com, 1k_hgmm_v3_nextgem dataset). All other data are available upon reasonable request.

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Acknowledgements

We thank B. Li for bioinformatic support and S. Kuan for sequencing. We thank the QB3 MacroLab for purifying the Tn5 enzyme. We thank D. U. Gorkin (UC San Diego) for sharing the frozen archived mouse fetal brain tissues. We thank S. Preissl, R. Fang, X. Hou, J. Song, Y. Li, Y. Zhang, and Y. Qiu for discussion. This study was funded by grants 1U19 MH114831, U54 HG006997 and the Ludwig Institute for Cancer Research (to B.R.).

Author information

Authors and Affiliations

  1. Ludwig Institute for Cancer Research, La Jolla, CA, USA

    Chenxu Zhu, Miao Yu, Hui Huang, Rong Hu & Bing Ren

  2. Biomedical Sciences Graduate Program, University of California San Diego, La Jolla, CA, USA

    Hui Huang

  3. Department of Quantitative Health Sciences, Lerner Research Institute, Cleveland Clinic Foundation, Cleveland, OH, USA

    Ivan Juric, Armen Abnousi & Ming Hu

  4. Computational Neurobiology Laboratory, The Salk Institute for Biological Studies, La Jolla, CA, USA

    Jacinta Lucero & M. Margarita Behrens

  5. Center for Epigenomics, Department of Cellular and Molecular Medicine, Institute of Genomic Medicine, Moores Cancer Center, University of California San Diego, School of Medicine, La Jolla, CA, USA

    Bing Ren

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Contributions

B.R. and C.Z. conceived and designed the study and wrote the manuscript. C.Z. performed the Paired-seq experiments and data analysis. M.Y. and R.H. performed PLAC-seq experiments. H.H. prepared the nuclei. I.J., A.A., and M.H. performed PLAC-seq data analysis. J.L. and M.M.B. harvested adult mouse cerebral cortex tissues. All authors discussed results and edited the manuscript.

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Correspondence to Bing Ren.

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Extended data

Extended Data Fig. 1 Quality control for Paired-seq libraries.

a, Sequence of Paired-seq products illustrating the structure of DNA barcode combinations. b, Paired-seq DNA profiles are enriched around the TSSs, whereas (e) RNA profiles are enriched at the TTSs in NIH/3T3 cells. As comparison, DNA and RNA profiles from sci-CAR are also plotted. c, Proportions of DNA and RNA reads in both libraries are shown, n = 3 independent experiments. d,e, Scatter plots showing the correlation of reads from two replicates of Paired-seq (d) DNA profiles or (e) RNA profiles. f,g, Box plots showing (f) the fraction of reads around TSS (-1000 to + 500 bp) and (g) the faction of reads inside known peaks (GSE:49847) of Paired-seq DNA profiles from HEK293T, HepG2 and NIH/3T3 cells. sci-CAR40 datasets (GSE117089) from the same cell types were also used for comparison. h,i, Scatter plot showing the proportion of human and mouse reads in each cell in Paired-seq (h) DNA and (i) RNA profiles. j, Scatter plot showing the proportions of both DNA and RNA reads mapped to genomes in the same single cells. Cells with more than 80% reads mapped to human and mouse genome were colored in red and blue, respectively. k,l, UMAP visualization of HepG2 and HEK293T cells based on (k) DNA and (l) RNA reads. Cells were colored by density-based clustering from each profile and cell identities. The clustering results were also projected to each other. In box plots, center lines indicate the median, box limits indicate the first and third quartiles, and whiskers indicate 1.5× IQR. The sample sizes are provided in the Source Data with this paper online.

Source data

Extended Data Fig. 2 Integrative analysis of Paired-seq DNA and RNA profiles from mouse adult cerebral cortex.

a, UMAP visualization of co-clustering of nuclei from two replicates. b, Comparison of DNA-based, RNA-based, and integrated clustering results. Cells were colored based on unsupervised clustering from integrated clustering and colored the same as Fig. 2b. c, Promoter accessibility and gene expression of several marker genes in the nine major groups. Relative promoter accessibilities and gene expressions are indicated in the size and the color of circles. d, Expression levels of genes of all clusters are plotted in a box plot for each quantile of promoter accessibility. e, For each cell cluster, expression levels of genes are plotted in a box plot for each quantile of promoter accessibility. In box plots center lines indicate the median, box limits indicate the first and third quartiles, and whiskers indicate 1.5× IQR.

Source data

Extended Data Fig. 3 Co-clustering of Paired-seq datasets from mouse E12.5, E16.5 forebrain, and adult cerebral cortex.

a, UMAP visualization of Paired-seq data from two replicates of both mouse E12.5 and E16.5 forebrains showing clustering of cells based on cell types, not replicates. b, UMAP visualization of Paired-seq data of mouse E12.5 and E16.5 forebrains and adult cerebral cortex showing clustering of cells based on cell type, not batches. c, Aggregate chromatin accessibility (blue) and gene expression (green) profiles for each cell clusters at several marker gene loci.

Source data

Extended Data Fig. 4 Paired-seq facilitates the linking of candidate CREs to putative target genes in mouse fetal forebrains.

a, Bar charts show the numbers of gene−CRE links identified in mouse E12.5 and E16.5 forebrain and adult cerebral cortex data sets. b,c, Bar charts show the fractions of gene−CRE pairs (b) identified by Paired-seq and supported by PLAC-seq or (c) identified by PLAC-seq and supported by Paired-seq. P value, two-sided Fisher’s exact test. d−o, Number of identified CREs linked to each gene, number of identified genes linked to each CRE, number of CREs between CREs and their linked genes, and number of genes between CREs and their linked genes in (d−g) E12.5, (h−k) E16.5 forebrain and (l−o) adult cerebral cortex.

Source data

Extended Data Fig. 5 Dynamics of gene−CRE pairing during mouse brain development.

a,b, Box plots showing the number of linked CREs for genes of each group of (a) E12.5 to E16.5 and (b) E16.5 to adult. P value, two-sided Kolmogorov–Smirnov test test. Genes were classified according the number of linked candidate CREs: genes with a gain of CREs (log2(fold-change) > 3), genes with unchanged number of linked CREs (−1 < log2(fold-change) < 1) and genes with a loss of linked CREs (log2(fold-change) < -3). c, DAVID GO analysis of genes with more than ten linked CREs. d, Top 20 TF genes with the highest number of linked CREs. e, The predicted gene−CRE pair for Dlx1 gene in the dIn2 cluster. The common links shared by two stages of development are shown in gray, and the stage-specific links were shown in light and dark violet red. In the close-up view, the positions of stage-specific CREs ae indicated by a red dashed box. In box plots. center lines indicate the median, box limits indicate the first and third quartiles and whiskers indicate 1.5× interquartile range IQR.

Source data

Extended Data Fig. 6 Analysis of cellular trajectory of developing mouse forebrain.

a−c, Diffusion map showing the single-cell trajectories of neurogenesis toward (a) GABAergic neurons, (b) glutamatergic neurons, and (c) astrogenesis. d, The combined diffusion map corresponding to Fig. 4a is also shown. The cells were colored by stages and clusters, respectively. e, Heat map shows the ordering of the chromVAR TF motif enrichments across astrogenesis. The relative expression and promoter accessibility of corresponding TF genes are also shown. f, Line plots showing the relative enrichment of TF motifs, gene expression, and promoter accessibility for STAT3, NFKB1, and SP1 according to the diffusion pseudotime for astrogenesis. The estimated time-of-gain and time-of-loss of TF motifs are indicated by red and green rectangles below. g, Pie charts showing the fraction of TFs with the TF gene promoters became accessible before (TF gene first), synchronized with, or after (Motif first) the TF motifs became accessible, for neurogenesis towards GABAergic neurons, glutamatergic neurons and astrogenesis.

Source data

Supplementary information

Reporting Summary

Supplementary Table 1

Paired-seq primer sequences

Supplementary Table 2

Paired-seq barcode oligo sequences

Supplementary Table 3

Summary of sequenced nuclei

Supplementary Table 4

Identified gene−CRE pairs in mouse fetal forebrains

Supplementary Table 5

Identified gene−CRE pairs in adult cerebral cortex

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Zhu, C., Yu, M., Huang, H. et al. An ultra high-throughput method for single-cell joint analysis of open chromatin and transcriptome. Nat Struct Mol Biol 26, 1063–1070 (2019). https://doi.org/10.1038/s41594-019-0323-x

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