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Results for “Micro Capture-C”

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4 recordsLinked to original sources
PubMed2026

Regulation of immune signal integration and memory by inflammation-induced chromosome conformation.

Three-dimensional (3D) genome conformation is central to gene expression regulation, yet our understanding of its contribution to rapid transcriptional responses, signal integration, and memory in immune cells is limited. Here, we study the molecular regulation of the inflammatory response in primary macrophages using integrated transcriptomic, epigenomic, and chromosome conformation data, including base pair-resolution Micro Capture-C. We demonstrate that interleukin-4 (IL-4) primes the inflammatory response in macrophages by stably rewiring 3D genome conformation, juxtaposing endotoxin-, interferon-gamma-, and dexamethasone-responsive enhancers to their cognate gene promoters. CRISPR-based perturbations of enhancer-promoter contacts or CCCTC-binding factor (CTCF) boundary elements show that IL-4-driven conformation changes are required for enhanced and synergistic endotoxin-induced transcriptional responses, as well as transcriptional memory following stimulus removal. Moreover, transcriptional memory mediated by changes in chromosome conformation can occur in the absence of changes in chromatin accessibility or histone modifications. Collectively, these findings demonstrate that rapid and memory transcriptional responses to immunological stimuli are encoded in the 3D genome.

Animals↗
PubMed2026

MYB activity drives emergent enhancer activation and enhancer-promoter interactions in acute lymphoblastic leukemia.

Aberrant enhancer usage is a defining feature of oncogenic transcriptional reprogramming. Therapeutic strategies that disrupt enhancer-driven gene regulation may offer new treatment avenues. MYB is a key hematopoietic transcription factor that is frequently dysregulated in a broad range of cancers and plays a critical role in sustaining malignant cell states, including in aggressive leukemia subtypes such as KMT2A-rearranged leukemias. The molecular mechanisms by which it maintains oncogenic transcription remain incompletely understood. Here, we investigate the role of MYB in directing pathological enhancer activity to drive oncogene expression in leukemia. Using high-resolution Micro Capture-C, we show that upon MYB degradation, highly defined enhancer-promoter interactions at MYB binding sites are lost, correlating with the significant downregulation of target gene expression. When anchored to a gene desert region, the Myb transactivation domain (MybTA) is sufficient and necessary for the nucleation of an enhancer-like region. Critically, long-range chromatin interactions are established up to 400 kb away from where MybTA is anchored. This results in the activation of transcription from distal cryptic elements, which is reduced or abolished in the presence of point mutations that disrupt its interaction with the coactivators P300/CBP. All these results indicate that MYB activity alone is sufficient to generate an enhancer, inducing transcription through precise enhancer-promoter cross talk, and identify the MYB-P300/CBP axis as a therapeutically actionable vulnerability in enhancer-driven malignancies.

Promoter Regions, Genetic↗
PubMed2026

How advances in chromosome conformation capture (3C) methods are reshaping our understanding of gene regulation in hematopoiesis.

The three-dimensional organization of the DNA within the nucleus plays a key role in regulating gene expression. Over the past two decades, advances in chromosome conformation capture (3C) technologies, in tandem with other methods, have shown that the genome forms a complex structure at multiple scales. Early studies identified large-scale structures such as chromosome territories, compartments and topologically associating domains (TADs). As the resolution of 3C techniques has improved, it has become possible to identify contacts between regulatory elements in detail and more recently, it has become possible to define intricate structures within cis-regulatory elements. In this chapter, we review the development of 3C-based methodologies and discuss the strengths and limitations of the different approaches. We examine how these technologies have refined our understanding of genome organization and gene regulation. Recent high-resolution studies reveal that chromatin architecture extends beyond classical domain structures to include nanoscale organization. Integration of 3C data with super-resolution imaging and molecular dynamics simulations supports a model in which genome folding is governed by the biophysical properties of chromatin.

Animals↗
PubMed2026

HiCPotts: An R/Bioconductor package to identify significant interactions in chromosome conformation capture data and model sources of bias.

MOTIVATION: Chromosome Conformation Capture methods, including Hi-C, micro-C or Capture-C, are used to map chromatin interactions genome-wide. Most of the existing computational methods do not account for sources of bias (such as DNA accessibility, GC content or TE content) in the data. RESULTS: We previously developed ZipHiC, a Bayesian method based on the hidden Markov random field (HMRF) model and the Approximate Bayesian Computation (ABC), that uses zero-inflated Poisson distribution to model the noise, signal and false signal of the data and showed that this approach was able to detect bias from DNA accessibility, GC content and TE content in both Hi-C and micro-C data. Here, we present HiCPotts, another Bayesian method based on the HMRF model and the ABC that uses a zero-inflated Negative Binomial distribution instead to model the noise and signal of the data. We systematically show that HiCPotts reduces false positives and increases recovery of true interactions compared to ZipHiC, but also compared to other methods such as FastHiC, Juicer and HiCExplorer. Most importantly, we provide an R/Bioconductor package that allows modelling the noise, signal and false signal using various distributions such as the zero-inflated Negative Binomial (ZINB) and the zero-inflated Poisson distribution (ZIP). AVAILABILITY AND IMPLEMENTATION: https://bioconductor.org/packages/HiCPotts/. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Approximate Bayesian Computation↗