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Results for “Micro-C”

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7 recordsLinked to original sources

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↗

PubMed2025

Genome topology analysis and transcriptomics of human osteoclasts reveals enhancer-promoter interactions at loci for bone traits and diseases.

Genome-wide association studies (GWAS) relevant to osteoporosis have identified hundreds of loci; however, understanding how these variants influence the phenotype is complicated because most reside in non-coding DNA sequence that serves as transcriptional enhancers and repressors. To advance knowledge on these regulatory elements in osteoclasts (OCs), we performed Micro-C analysis, which informs on the genome topology of these cells and integrated the results with transcriptome and GWAS data to further define loci linked to BMD. Using blood cells isolated from 4 healthy participants aged 31-61 yr, we cultured OC in vitro and generated a Micro-C chromatin conformation capture dataset. We characterized chromatin loops (CLs) in OC from among more than 69 million chromatin interactions identified in the genome. Of the CL identified in OC, >16 000 were unique compared to precursor cells. When sentinel single nucleotide polymorphisms from osteoporosis and bone-related GWAS and those in linkage disequilibrium at r 2 > 0.6 were mapped to CL for OC, 12 588 of these variants were observed within chromatin contact regions. Notable in differential gene ontology enrichment analyses of the topology data for OC and precursors were pathways regulating pluripotency of stem cells, Wnt signaling, nucleotide-binding oligomerization domain (NOD)-like receptor signaling and chemokine signaling. These data, in combination with other 3D genome architecture and epigenetic data (eg, histone modifications and chromatin accessibility), will be useful in modeling to predict genome-wide, which enhancers regulate which genes in OC. This data will therefore also be informative for resolving GWAS hits. In conclusion, we have generated a high-resolution genome topology dataset for human OC and have used this to identify CLs relevant to studies of the genetics of osteoporosis. This data will serve as a powerful resource to inform future functional studies of OC biology.

BMD↗

PubMed2025

3D chromatin structures precede genome activation in Drosophila embryogenesis.

3D chromatin structure is critical for the regulation of gene expression during development. Here we used Micro-C assays at 100-bp resolution to map genome organization in Drosophila melanogaster throughout the first half of embryogenesis. These high-resolution contact maps reveal fine-scale features such as loops and boundaries delineating topologically associating domains. Notably, we observe that 3D chromatin structures form prior to zygotic genome activation and persist during successive mitotic cycles. Integrative analysis with 149 public chromatin immunoprecipitation sequencing (ChIP-seq) datasets identifies four classes of chromatin structuring elements, including a distinct group enriched for GAGA-associated factor (GAF) and Zelda binding, associated with developmental-gene regulation. These elements are mitotically retained and exhibit sequence and structure similarity between D. melanogaster and D. virilis. We propose that 3D chromatin organization in the pre-cellular embryo facilitates deployment of developmentally regulated genes during Drosophila embryogenesis.

Animals↗

PubMed2025

MIA-Jet: Multi-scale Identification Algorithm of Chromatin Jets.

The mammalian genome is organized into large-scale chromosome territories, compartments, domains, and at the smallest scale, chromatin loops and stripes. The newest element is a chromatin jet, a diffused line perpendicular to the main diagonal in the Hi-C contact map, which was reported in quiescent mammalian lymphocytes supporting a two-sided symmetric cohesin loop extrusion model. A similar structure is observed in Repli-HiC data, where relatively thin and straight chromatin fountains indicate coupling of DNA replication forks. However, the precise biological implications of these jet-like structures are unknown due to the limitations in computational methods. We developed MIA-Jet, a multi-scale ridge detection algorithm that can accurately detect jets of variable lengths, widths, and angles. When tested on Hi-C, Repli-HiC, ChIA-PET, ChIA-Drop, and Micro-C data in mouse, human, roundworm, and zebrafish cells, MIA-Jet outperformed existing methods. In human cells, jets were enriched in cohesin loading sites and early replication initiation zones. Applying MIA-Jet to Hi-C data generated from protein-degraded cells revealed that jets are dependent on cohesin but not YY1, and jet signals are strengthened after depleting WAPL. We envision MIA-Jet to be broadly applicable to any 3D genome mapping data, thereby providing new insights into the functional roles of chromatin jets.

3D genome mapping↗

PubMed2025

Genome reorganisation and expansion shape 3D genome architecture and define a distinct regulatory landscape in coleoid cephalopods.

How genomic changes translate into organismal novelties is often confounded by the multi-layered nature of genome architecture and the long evolutionary timescales over which molecular changes accumulate. Coleoid cephalopods (squid, cuttlefish, and octopus) provide a unique system to study these processes due to a large-scale chromosomal rearrangement in the coleoid ancestor that resulted in highly modified karyotypes, followed by lineage-specific fusions, translocations, and repeat expansions. How these events have shaped gene regulatory patterns underlying the evolution of coleoid innovations, including their large and elaborately structured nervous systems, novel organs, and complex behaviours, remains poorly understood. To address this, we integrate Micro-C, RNA-seq, and ATAC-seq across multiple coleoid species, developmental stages, and tissues. We find that while topological compartments are broadly conserved, hundreds of chromatin loops are species- and context-specific, with distinct regulation signatures and dynamic expression profiles. CRISPR-Cas9 knockout of a putative regulatory sequence within a conserved region demonstrates the role of loops in neural development and the prevalence of long-range, inter-compartmental interactions. We propose that differential evolutionary constraints across the coleoid 3D genome allow macroevolutionary processes to shape genome topology in distinct ways, facilitating the emergence of novel regulatory entanglements and ultimately contributing to the evolution and maintenance of complex traits in coleoids.

Journal Article↗

PubMed2025

esBAF and INO80C fine-tune subcompartments and differentially regulate enhancer-promoter interactions.

The genome is compacted in the nucleus through a hierarchical chromatin organization, ranging from chromosome territories to compartments, topologically associating domains (TADs), and individual nucleosomes. Nucleosome remodeling complexes hydrolyze ATP to translocate DNA and thereby mobilize histone proteins. While nucleosome remodeling complexes have been extensively studied for their roles in regulating nucleosome positioning and accessibility, their contributions to higher-order chromatin architecture remain less well understood. Here, we investigate the roles of two key nucleosome remodelers, esBAF and INO80C, in shaping 3D genome organization in mouse embryonic stem cells. Using Hi-C, we find that loss of either remodeler has minimal effects on global compartment or TAD structures. In contrast, subcompartment organization is notably altered, suggesting that esBAF and INO80C contribute to finer-scale chromatin topology. To overcome the limited resolution of Hi-C for detecting regulatory loops, we employed promoter capture Micro-C (PCMC), which revealed that the loss of esBAF or INO80C alters a subset of promoter anchored looping interactions. Although these changes occur at distinct genomic loci for each remodeler, the affected sites are commonly enriched for bivalent chromatin regions bound by OCT4, SOX2, and NANOG (OSN), as well as BRG1 and INO80 themselves. Together, our findings reveal that esBAF and INO80C selectively influence subcompartment identity and enhancer-promoter communication at key regulatory loci, highlighting a previously underappreciated role for nucleosome remodelers in higher-order chromatin organization.

chromatin↗

PubMed1976

[The demonstration of HL-A antigens on thrombocytes under various conditions].

Platelets of healthy test persons were gained according to the method of Aster (avital cells) and according to the procedure of BUBE and GMURZYNSKI (vital cells). Because of their tendency towards aggregation vital cells do bind any HL-A antibodies and whereas avital cells will fix antibodies and complement depending on the height of the titre. Thrombocytes stored in the own serum will respond less to the micro-C'-fixation test at + 4 degrees C as well as--196 degrees C, whereas storage in NaN3/NaCl and under the conditions of the own serum will reveal no differences up to--196 degrees C in each case.

Blood Platelets↗