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