Quantitative profiling of intrinsic dCas9-DNA recognition reveals key determinants of guide RNA performance

Evaluating high-fidelity CRISPR-Cas nucleases in nucleosomal contexts using a quantitative framework

It is demonstrated that local nucleosome sequence and structure profoundly influence Cas nuclease accessibility and specificity, with HIFIv1 emerging as the top-performing nuclease for nucleosomal targets, while evoSpCas9 excelled in exposed contexts.

CRISPR RNA-independent activation of Cas12a

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

Mapping protein-DNA interactions (PDIs) is essential for understanding transcriptional regulation and chromatin organization. Experimental approaches now range from in vitro assays that characterize intrinsic DNA-binding specificity to chromatin-based methods that capture protein occupancy in native genomes, as well as single-cell and single-molecule technologies that reveal regulatory heterogeneity across cells and individual chromatin fibers. These methods differ in resolution, sensitivity, input requirements, and their ability to preserve chromatin context, giving each approach distinct strengths and limitations. Here, we provide a comparative overview of major PDI technologies organized according to the biological scale at which they operate. We discuss their underlying principles, quantitative features, throughput, and key considerations for experimental design and method selection. We also review computational approaches for PDI analysis, including sequence- and chromatin-based binding prediction, multi-omics integration, and regulatory network inference. In addition, we discuss current challenges, such as platform-specific biases, sparse signals in single-cell datasets, and the lack of standardized benchmarking, and highlight future directions for improving PDI mapping and interpretation.

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)

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

Programmable Allosteric DNAzyme Coupled with CRISPR/Cas12a System for Multiplexed and Sensitive Detection of Extracellular Vesicle Derived MicroRNAs