High-throughput sequencing of the transcriptome and chromatin accessibility in the same cell

Abstract

Single-cell RNA sequencing can reveal the transcriptional state of cells, yet provides little insight into the upstream regulatory landscape associated with open or accessible chromatin regions. Joint profiling of accessible chromatin and RNA within the same cells would permit direct matching of transcriptional regulation to its outputs. Here, we describe droplet-based single-nucleus chromatin accessibility and mRNA expression sequencing (SNARE-seq), a method that can link a cell's transcriptome with its accessible chromatin for sequencing at scale. Specifically, accessible sites are captured by Tn5 transposase in permeabilized nuclei to permit, within many droplets in parallel, DNA barcode tagging together with the mRNA molecules from the same cells. To demonstrate the utility of SNARE-seq, we generated joint profiles of 5,081 and 10,309 cells from neonatal and adult mouse cerebral cortices. We reconstructed the transcriptome and epigenetic landscapes of major and rate cell types, uncovered lineage-specific accessible sites especially for low-abundance cells, and connected the dynamics of promoter accessibility with transcription level during neurogenesis.RNA sequencing of single cells or nuclei reveals their transcription state, whereas chromatin accessibility sequencing uncovers the associated regulatory landscape. Current strategies 1,2 , which involve profiling these modalities separately followed by computational integration, may not fully recapitulate the true biological state. Joint profiling of two layers of -omics information within the same cells would enable a direct matching of transcriptional regulation to its output, allowing for more accurate reconstruction of the molecular processes underlying a cell's physiology.

Unsupervised manifold alignment for single-cell multi-omics data

“…This data set contains gene expression and chromatin accessibility measurements which, when projected to 2D using PCA, exhibit qualitatively similar clusterings into three groups (Figure 2a-b). This is roughly similar to [11], where further pre-processing and t-SNE plots of the data result in four clusters representing BJ, GM12878, H1, and K562 cell mixtures. MMD-MA analysis of this data set, using a 5D latent space followed by projection to 2D via PCA, suggests that the algorithm succeeds in overlaying the two distributions (Figure 2c).…”

“…Single-nucleus chromatin accessibility and mRNA expression sequencing (SNAREseq) [11] is a recently described, droplet-based method that can link a cell's transcriptome with its accessible chromatin for sequencing at scale. Because this method can measure both gene expression and chromatin accessibility information from the same cell, we use the SNARE-seq dataset to validate MMD-MA by evaluating the algorithm's ability to correctly pair each expression profile with the correct chromatin accessibility profile.…”

Chromatin potential identified by shared single cell profiling of RNA and chromatin

“…Emerging single cell "multi-omic" technologies offer a direct means to determine the coordination between layers of gene regulation, including the epigenome and gene expression. Prior studies have sought to correlate gene expression with regulatory element accessibility (Cao et al, 2018;Chen et al, 2019;Zhu et al, 2019).…”

Single nucleus multi-omics links human cortical cell regulatory genome diversity to disease risk variants

“…The continuous development of multi-omic profiling techniques such as scNMT-seq (Clark et al, 2018) and snmC2T-seq, and several methods for joint RNA and chromatin accessibility profiling sci-CAR (Cao et al, 2018) , SNARE-seq (Chen et al, 2019) and Paired-seq (Zhu et al, 2019) provide the opportunity to classify cell types with multiple molecular signatures. Our study provided a computational framework to cross-validate clustering-based cell-type classifications using multi-modal data.…”