Fiber-seq simultaneously profiles chromatin accessibility, DNA methylation, protein footprints, and genetic variation on single molecules at near—base-pair resolution, revealing how genetic and epigenetic features interact to regulate gene expression and provides a powerful new framework for dissecting immune cell function and disease mechanisms.
Abstract
Chromatin structure regulates gene expression, shaping immune cell responses and differentiation. Profiling accessibility, transcription factor binding, and DNA methylation is key to understanding immune regulation. Short-read sequencing (SRS) methods like ATAC-seq and ChIP-seq provide valuable insights but lack resolution and cannot capture multiple chromatin features together, limiting our ability to define their coordinated roles in immune function.
We optimized Fiber-seq, a multiomic long-read sequencing (LRS) method to simultaneously profile chromatin accessibility and endogenous methylation using LRS. Fiber-seq uses a non-specific DNA methyltransferase to label accessible DNA by creating N6-methyladenosine, a mark rarely found in eukaryotic genomes. This rapid enzymatic incubation also preserves endogenous DNA methylation so that both methylation marks can be detected by direct LRS.
We validated this new method using human lymphoblast cells (K562). Aggregate Fiber-seq accessibility profiles were highly concordant with published ATAC-seq datasets. We confirmed that 6mA-labeling preserved sequencing accuracy and detection of CpG methylation. We also found nucleosome and protein footprints could be inferred from Fiber-seq data. We have validated multiple transcription factor inferred footprints are highly concordant with published CUT&RUN or ChIP-seq datasets. Further, these footprints are captured at a per-molecule and near-base pair resolution, uncovering multiple binding events in close proximity, which is usually obscured by lower resolution SRS-based methods.
Fiber-seq simultaneously profiles chromatin accessibility, DNA methylation, protein footprints, and genetic variation on single molecules at near—base-pair resolution. This integrated view reveals how genetic and epigenetic features interact to regulate gene expression and provides a powerful new framework for dissecting immune cell function and disease mechanisms.
NIH R44 GM148145
Technological Innovations in Immunology (TECH)
Gene regulation emerges from coordinated interactions among DNA sequence, chromatin accessibility, DNA methylation, nucleosome positioning, and transcription factor occupancy. These features are typically measured using separate short-read assays, fragmenting regulatory information across experiments and obscuring how regulatory states co-occur along individual DNA molecules. This limits mechanistic interpretation of cis-regulatory architecture, particularly within repetitive or structurally complex genomic regions that are poorly resolved by short-read approaches. Fiber-seq is a long-read, single-assay multiomic method that preserves regulatory context across individual DNA molecules by integrating chromatin accessibility footprinting with native long-read sequencing. Accessible adenines are enzymatically methylated using the N6-adenine methyltransferase Hia5 and sequenced alongside endogenous 5mC using PacBio or Oxford Nanopore Technologies platforms. Each long read therefore links chromatin accessibility, DNA methylation, nucleosome positioning, and transcription factor occupancy across extended regulatory domains with haplotype resolution. Fiber-seq recapitulates accessibility patterns observed with conventional assays while revealing chromatin architectures that are collapsed in short-read data. Single-molecule profiles resolve heterogeneous protein occupancy across individual DNA molecules, enabling direct detection of nucleosome positioning, transcription factor binding, and polymerase II recruitment at active regulatory elements. By distinguishing protected from accessible motifs within motif-dense regions, Fiber-seq supports composite motif analysis and prioritization of candidate regulatory elements and transcription factors for functional validation. These capabilities could support mechanistic studies of therapeutic response by enabling direct observation of regulatory state transitions following pharmacologic perturbation. For example, Fiber-seq could resolve loss of occupancy following transcription factor degradation together with local rearrangement of neighboring protein occupancy within the same cis-regulatory domain and on the same DNA molecule. This integrated single-molecule view of regulatory remodeling may support identification of adaptive resistance mechanisms, compensatory regulatory programs, pharmacodynamic biomarkers, and candidate synthetic lethal interactions relevant to epigenetic drug development. NOTE: Generative AI was used to assist in drafting the abstract text; all authors reviewed and approved the final content.
Keith E. Maier, James T. Anderson, Connor P. Frasier, Allison R. Hickman, Sabrina R. Hunt, Zu-Wen Sun, Martis W. Cowles, Andrew Stergachis, Bryan J. Venters, Michael-Christopher Keogh. Single-molecule protein footprinting with Fiber-seq resolves coordinated chromatin states across regulatory domain [abstract]. In: Proceedings of AACR Drug Discovery and Development (AACR D3) Conference; 2026 Jul 21-24; Boston, MA. Philadelphia (PA): AACR; Clin Cancer Res 2026;32(14_Suppl):Abstract nr B011.
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Gene expression and chromatin accessibility provide complementary insights into the regulatory mechanisms that define cell states. Although methods for jointly profiling these modalities exist, plant applications remain limited because of complex workflows, inconsistent performance, and prohibitive costs. Here, we present easy-Multiome, a streamlined single-cell multiomic workflow that integrates a single in situ reverse transcription step into the standard droplet-based scATAC-seq protocol. Using easy-Multiome, we profiled more than 20,000 nuclei from maize seedlings generating paired gene expression and chromatin accessibility data, with approximately 90% of nuclei containing both high-quality RNA and chromatin accessibility profiles. The resulting transcriptome data resolved 16 clusters corresponding to nine major maize seedling cell types and enabled direct characterization of cell-type-specific chromatin accessibility from the same nuclei. Furthermore, easy-Multiome simultaneously captured cell-type-specific transcription factor expression and the accessibility of their cognate DNA-binding motifs, providing direct links between transcriptional programs and regulatory landscapes. Together, these results demonstrate that easy-Multiome enables robust and efficient joint profiling of plant gene expression and chromatin accessibility while requiring only minimal modifications to existing droplet-based scATAC-seq workflows.
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