Profiling Chromatin Accessibility at Single-cell Resolution

Abstract

How distinct transcriptional programs are enacted to generate cellular heterogeneity and plasticity, and enable complex fate decisions are important open questions. One key regulator is the cell's epigenome state that drives distinct transcriptional programs by regulating chromatin accessibility. Genome-wide chromatin accessibility measurements can impart insights into regulatory sequences (in)accessible to DNA-binding proteins at a single-cell resolution. This review outlines molecular methods and bioinformatic tools for capturing cell-to-cell chromatin variation using single-cell assay for transposase-accessible chromatin using sequencing (scATAC-seq) in a scalable fashion. It also covers joint profiling of chromatin with transcriptome/proteome measurements, computational strategies to integrate multi-omic measurements, and predictive bioinformatic tools to infer chromatin accessibility from single-cell transcriptomic datasets. Methodological refinements that increase power for cell discovery through robust chromatin coverage and integrate measurements from multiple modalities will further expand our understanding of gene regulation during homeostasis and disease.

Keywords: Cis-regulatory elements; Epigenetics; Gene regulation; Single-cell ATAC-seq; Single-cell multi-omics.

Figure 1

ATAC-seq probes genome-wide chromatin accessibility using hyperactive Tn5 transposase A. Schematic illustrating hyperactive Tn5 being loaded with sequencing adapters by mixing equal amounts of two indexed oligos (s5 and s7) with Tn5 and incubating the mixture for approximately one hour. B. During Tn5 tagmentation (fragmentation and tagging), the transposase cleaves accessible DNA and attaches adaptor overhangs within intact nuclei. Since nuclei are not fragmented in this process, bulk Tn5 tagging can be performed in scATAC reactions prior to partitioning tagged nuclei. C. Tagmentation generates three different products: 1) sequence with s5 at both ends, 2) sequence with s7 at both ends, or ideally, 3) sequence with s5 and s7 at opposite ends (as shown in the diagram). Only the final product (containing different ends) is amplifiable. Final library is generated by appending additional identifiers such as cell/sample-specific barcodes using PCR. D. scATAC libraries are paired end sequenced and mapped to a reference genome. E. Peak-calling algorithms identify enriched (peak) regions which correspond to open chromatin states. ATAC-seq, assay for transposase-accessible chromatin using sequencing; scATAC, single-cell assay for transposase-accessible chromatin.

Figure 2

Schematic diagrams showing methods for transposition, barcoding, and library preparation for scATAC-seq A. In combinatorial indexing, nuclei are first tagged in bulk via barcoded Tn5 transposase in a 96 well plate. Then, cells are pooled, and 15 to 25 nuclei are randomly sorted into another 96 well plate where a second barcode is added during PCR. The probability for two cells to share the same combination of barcode is between 6%−11%. B. Micro-chamber capture utilizes a plate with thousands of non-adherent, barcode-containing microwells with a central and a serpentine microfluid flow path. The first cell entering a microwell gets trapped in the central path and blocks entry of subsequent cells, forcing them to take the serpentine path and be captured by a downstream chamber. The cell trapped in the central path is subsequently subjected to lysis, transposition, and downstream library construction within the chamber. C. Nanodispensers use non-contact dispensing to place a single cell (stained with live/dead Hoechst stain) into a nanowell containing preprinted barcodes. Only wells containing a dispensed cell (approximately one third of the 5184 nanowells) are transposed to generate sequencing libraries. D. In Drop-seq, transposed nuclei are compartmentalized into nanoliter-sized aqueous droplets containing unique barcodes that are carried in a continuous oil phase.

Figure 3

Customizations to scATAC-seq enables high-throughput CRISPR screening and T cell clonotyping A. Perturb-ATAC maps the impact of CRISPR perturbation on chromatin accessibility in single-cells. First, cells are transduced by sgRNA vectors containing a reporter sequence. FACS enriched cells are captured on microchambers (Figure 1C) and transposed with Tn5 enzyme. Following transposition, CRISPR sgRNAs are reversely transcribed using primers targeting the common 3′ end of sgRNA vectors. sgRNA and ATAC amplicons are amplified, pooled, sequenced, and analyzed for changes in TF features following genetic perturbations. B. T-ATAC-seq simultaneously profiles chromatin accessibility and TCRs in single T cells. Single CD4⁺ T cells are captured on microchambers (Figure 1C) where they are lysed, and their accessible chromatin transposed with Tn5 enzyme. TRα and TRβ transcripts (TRA and TRB) are reversely transcribed with primers targeting TRA and TRB, and ATAC amplicons are PCR amplified with well-specific barcodes, pooled, and sequenced. TF, transcription factor; sgRNA, single guide RNA; CRISPR, clustered regularly interspaced short palindromic repeats; FACS, fluorescence-activated cell sorting; Perturb-ATAC, perturbation-indexed scATAC-seq; T-ATAC-seq, transcript-indexed ATAC-seq; TCR, T cell receptor; TRA, T cell receptor alpha; TRB, T cell receptor beta; RT, reverse transcription; CDR3, complementarity-determining region 3.

Figure 4

Methods for single-cell multi-omics that integrate chromatin accessibility with proteomics and transcriptomics A. scCAT-seq separates the nucleus and the cytoplasm from single cells sorted in a 96-well plate. The cytoplasm is subjected to full-length transcript capture using Smart-seq2 and the nucleus to transposition, and both are marked by a barcode unique to each well. B. sci-CAR-seq profiling starts with nuclei distributed in a 96-well plate. First, nuclear RNA is indexed by reversely transcribing poly(A) mRNA with a poly(T) primer carrying a well-specific barcode and a UMI. Then, accessible chromatin is indexed with transposase carrying a well-specific barcode. All nuclei are pooled, and 15 to 25 are randomly sorted into another 96 well plate where a second barcode is added during indexed PCR for RNA-seq or for ATAC-seq. Amplicons from both libraries are pooled and sequenced. C. scPi-ATAC-seq starts with fixed and permeabilized cells that are subjected to antibody staining and bulk transposition. Cells are then sorted into a 96 well plate where fluorescence emitted by antibodies are quantified, proteins are reverse crosslinked, and barcodes are added by indexing PCR. scCAT-seq, single-cell chromatin accessibility and transcriptome sequencing; sci-CAR-seq, single-cell combinatorial indexing-based chromatin accessibility and mRNA; scPi-ATAC-seq, single-cell protein-indexed ATAC-seq; UMI, unique molecular identifier.

Figure 5

Predicting chromatin accessibility from single-cell transcriptomics A. Overview of the prediction approach. B. BIRD-predicted chromatin accessibility, experimental scATAC-seq data, and bulk ATAC-seq data for two cell types (GM12878 and H1) are compared in a sample genomic region. The scATAC-seq signals are sparse and discrete, while BIRD-predicted signals are more continuous and correlate better with the bulk ATAC-seq signals. BIRD, Big Data Regression for predicting DNase I hypersensitivity.