Transposition of native chromatin for fast and sensitive epigenomic profiling of open chromatin, DNA-binding proteins and nucleosome position

Abstract

We describe an assay for transposase-accessible chromatin using sequencing (ATAC-seq), based on direct in vitro transposition of sequencing adaptors into native chromatin, as a rapid and sensitive method for integrative epigenomic analysis. ATAC-seq captures open chromatin sites using a simple two-step protocol with 500-50,000 cells and reveals the interplay between genomic locations of open chromatin, DNA-binding proteins, individual nucleosomes and chromatin compaction at nucleotide resolution. We discovered classes of DNA-binding factors that strictly avoided, could tolerate or tended to overlap with nucleosomes. Using ATAC-seq maps of human CD4(+) T cells from a proband obtained on consecutive days, we demonstrated the feasibility of analyzing an individual's epigenome on a timescale compatible with clinical decision-making.

Figure 1. ATAC-seq is a sensitive, accurate probe of open chromatin state

(a) ATAC-seq reaction schematic. Transposase (green), loaded with sequencing adapters (red and blue), inserts only in regions of open chromatin (nucleosomes in grey) and generates sequencing library fragments that can be PCR amplified. (b) Approximate reported input material and sample preparation time requirements for genome-wide methods of open chromatin analysis. (c) A comparison of ATAC-seq to other open chromatin assays at a locus in GM12878 lymphoblastoid cells displaying high concordance. Lower ATAC-seq track was generated from 500 FACS-sorted cells.

Figure 2. ATAC-seq provides genome-wide information on chromatin compaction

(a) ATAC-seq fragment sizes generated from GM12878 nuclei (red) indicate chromatin-dependent periodicity with a spatial frequency consistent with nucleosomes, as well as a high frequency periodicity consistent with the pitch of the DNA helix for fragments less than 200 bp. (Inset) log-transformed histogram shows clear periodicity persists to 6 nucleosomes. (b) Normalized read enrichments for 7 classes of chromatin state previously defined.

Figure 3. ATAC-seq provides genome-wide information on nucleosome positioning in regulatory regions

(a) An example locus containing two transcription start sites (TSSs) showing nucleosome free read track, calculated nucleosome track (Methods), as well as DNase, MNase, and H3K27ac, H3K4me3, and H2A.Z tracks for comparison. (b) ATAC-seq (198 million paired reads) and MNase-seq (4 billion single-end reads from ref 23) nucleosome signal shown for all active TSSs (n=64,836), TSSs are sorted by CAGE expression. (c) TSSs are enriched for nucleosome free fragments, and show phased nucleosomes similar to those seen by MNase-seq at the −2, −1, +1, +2, +3 and +4 positions. (d) Relative fraction of nucleosome associated vs. nucleosome free (NFR) bases in TSS and distal sites (see Methods). (e) Hierarchical clustering of DNA binding factor position with respect to the nearest nucleosome dyad within accessible chromatin reveals distinct classes of DNA binding factors. Factors strongly associated with nucleosomes are enriched for chromatin remodelers.

Figure 4. ATAC-seq assays genome-wide factor occupancy

(a) CTCF footprints observed in ATAC-seq and DNase-seq data, at a specific locus on chr1. (b) Aggregate ATAC-seq footprint for CTCF (motif shown) generated over binding sites within the genome (c) CTCF predicted binding probability inferred from ATAC-seq data, position weight matrix (PWM) scores for the CTCF motif, and evolutionary conservation (PhyloP). Right-most column is the CTCF ChIP-seq data (ENCODE) for this GM12878 cell line, demonstrating high concordance with predicted binding probability.

Figure 5. ATAC-seq enables real-time personal epigenomics

(a) Work flow from standard blood draws. (b) Serial ATAC-seq data from proband T-cells over three days. (c) Example of application of ATAC-seq data (green track) to prioritize candidate TF drug targets. Among identified TF binding sites proximal to cytokine gene IL2 that can be targeted by FDA-approved drugs, only NFAT is engaged in proband T-cells. ATAC-seq footprint prediction is confirmed by alignment with published NFAT ChIP-seq data (blue track, data from ref ). (d) Cell type-specific regulatory network from proband T cells compared with GM12878 B-cell line. Each row or column is the footprint profile of a TF versus that of all other TFs in the same cell type. Color indicates relative similarity (yellow) or distinctiveness (blue) in T versus B cells. NFAT is one of the most highly differentially regulated TFs (red box) whereas canonical CTCF binding is essentially similar in T and B cells.