Genome-wide profiling of histone modifications and transcription factor binding at single-cell resolution by DeChIC-seq

Unraveling genomic regulatory complexity by adding chromatin accessibility to the long-read sequencing toolkit 2247245

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.

Integrated single-cell profiling of RNA and DNA interactomes reveals targetable chromatin architectures in cancer

Abstract B011: Single-molecule protein footprinting with Fiber-seq resolves coordinated chromatin states across regulatory domain

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.

High Resolution Single-Cell Epigenetic Atlas of Immune Cell Types Reveals Gene Regulatory Circuits in Healthy Humans 2308992

Single-cell chromatin accessibility (scATAC-seq) profiles genome-wide regulatory elements that shape immune cell identity and function, but its interpretation is currently limited by low cell type resolution and small reference datasets. Existing datasets annotate fewer than 20 immune cell types and are too coarse to resolve heterogeneity and characterize cell type-specific gene regulatory programs and functions. Here, we present a large-scale scATAC-seq resource that substantially improves immune cell annotation and regulatory inference. By integrating matched-donor scRNA-seq and scATAC-seq data from human peripheral blood mononuclear cells (PBMCs) with trimodal TEA-seq (single-cell ATAC, RNA, and surface protein), we classified 36 immune cell types, including 4 myeloid, 6 B cell, 5 NK cell, 6 CD4 T cell, and 15 CD8 T cell subtypes. Cell frequencies from published scRNA-seq and new scATAC-seq labels were highly correlated (median ρ = 0.84). Labels were applied to our longitudinal multi-modal dataset of 206 samples spanning over 3 million PBMCs from 78 healthy human donors. We used these annotations to define baseline epigenetic states, age-associated differences, and epigenetic changes following influenza vaccination. Our analysis revealed extensive sets of differentially accessible tiles and enriched transcription factor motifs that define cell type-specific regulatory identities. Linking these chromatin regions and transcription factors to differentially expressed target genes enabled the construction of gene regulatory circuits associated with cell type, aging, and vaccination. Additionally, we trained a classification model for high resolution cell type labeling and doublet detection in new scATAC-seq datasets. Together, this multi-modal atlas and associated cell type-labeling model provide an unprecedented reference for immune cell gene regulatory circuits and a valuable resource for exploring the epigenome of human immune cells. n/a Computational and Systems Immunology (COMP)

G‑quadruplexes as regulatory platforms for human transcription factors: insights from ChIP-seq data

G-quadruplexes (G4s) are non-canonical DNA structures with important regulatory functions. While several transcription factors have been shown to interact with G4s, a comprehensive understanding of this interaction network remains elusive. Here, we integrated genome-wide predictions of highly stable G-quadruplex sequences with 32,817 ChIP-seq datasets from ChIP-Atlas to systematically map transcription factors and transcription-associated chromatin proteins linked to G4-rich regions in the human genome. Highly stable G4 motifs are non-randomly distributed, showing strong enrichment in gene-dense chromosomes, at promoters, regulatory regions, and repeat elements. Integration with transcription factor binding profiles revealed a broad spectrum of G4-associated proteins, including established interactors such as STAT3, TP53 and CTCF, and the transcription-associated chromatin regulator BRD4, as well as previously unrecognized candidates such as REST, NR3C1, FLI1, and HSF1. Unexpectedly, only a minority of transcription factors were consistently depleted from G4 regions. Our results indicate that G-quadruplex-prone sequences represent a common genomic feature associated with a number of human transcription factors and chromatin-associated regulatory proteins and support a model in which G4-rich regions act as selective regulatory scaffolds shaping transcription factor occupancy and gene regulation.

Mapping protein-DNA interactions across biological scales: principles, scalability and applications.

A comparative overview of major PDI technologies organized according to the biological scale at which they operate is provided, including sequence- and chromatin-based binding prediction, multi-omics integration, and regulatory network inference.