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Results for “Conformational accessibility”

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At least 19 recordsLinked to original sources

PubMed2026

Integrated LiP-MS and quantitative proteomics reveal coordinated alterations in protein conformation and expression across tumor and peritumoral regions in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) exhibits substantial molecular heterogeneity, yet protein-level alterations beyond abundance remain insufficiently characterized. Here, we integrated limited proteolysis mass spectrometry (Lip-MS) with 4D label-free quantitative proteomics to investigate conformational accessibility and protein abundance across tumor, peritumoral-near, and peritumoral-far tissues from HCC patients. Differential LiP peptides identified by both DDA and DIA corresponded to 725, 674, and 33 differentially conformed proteins in the Tumor vs. Peritumor-far, Tumor vs. Peritumor-near, and Peritumor-near vs. Peritumor-far comparisons, respectively. Quantitative proteomics identified 405, 365, and 4 differentially expressed proteins in the corresponding comparisons. Integrated analysis identified 488 and 469 conformation-specific altered proteins (CSAPs), which showed altered conformational accessibility without significant abundance changes, and 237 and 205 conformation-expression coupled proteins (CECPs) in the two tumor-involved comparisons. LiP peptide and protein abundance changes were positively correlated, with Spearman coefficients of 0.69-0.72, and more than 99% of CECPs showed concordant directions. Among them, 169 region-conserved CECPs (rcCECPs) were predominantly associated with metabolic and redox-related pathways. Protein-protein interaction analysis identified 30 hub rcCECPs. ACLY, ALDH18A1, GMPS, and DHX9 showed increased representative LiP peptide signals and protein abundance, elevated transcript expression in HCC, and associations with poorer overall survival. Peptide mapping further localized their differential LiP signals to specific sequence regions and annotated domains. Collectively, these findings provide an integrated view of regional conformational accessibility and protein abundance alterations in HCC and identify candidate proteins for further structural and functional investigation.

Humans↗

PubMed2025

Dynamic changes in chromosome and nuclear architecture during maturation of normal and ALS C9orf72 motor neurons.

We have investigated changes in chromosome conformation, nuclear organization, and transcription during differentiation and maturation of control and mutant motor neurons harboring hexanucleotide expansions in the C9orf72 gene that cause amyotrophic lateral sclerosis (ALS). Using an in vitro reprogramming, differentiation and neural maturation protocol, we obtained highly purified populations of post-mitotic motor neurons for both normal and diseased cells. As expected, as fibroblasts are reprogrammed into iPSCs, and as iPSCs differentiate into motor neurons, chromatin accessibility, chromosome conformation, and nuclear organization change along with large-scale alterations in transcriptional profiles. We find that the transcriptome changes extensively during the first three weeks of post-mitotic neuronal maturation, with thousands of genes changing expression, but then is relatively stable for the next three weeks. In contrast, chromosome conformation and nuclear organization continue to change over the entire 6-week maturation period: chromosome territoriality increases, long-range interactions along chromosomes decrease, compartmentalization strength increases, and centromeres and telomeres increasingly cluster. In motor neurons derived from ALS patients such changes in chromosome conformation were much reduced. Chromatin accessibility changes also showed delayed maturation. The transcriptome in these cells matured relatively normally but with notable changes in expression of genes involved in lipid, sterol and mitochondrial function. We conclude that neural maturation is associated with large scale post-mitotic changes in gene expression, chromosome conformation and nuclear organization, and that these processes are defective in motor neurons derived from ALS patients carrying C9orf72 hexanucleotide repeat expansions.

Journal Article↗

PubMed2026

Refining sequence-to-expression modelling with chromatin accessibility.

MOTIVATION: Sequence-to-expression models typically do not consider chromatin accessibility, a major factor limiting gene regulation. We hypothesized that supplying accessibility as an input feature would allow a sequence-to-expression model to focus on important open regions of the genome. RESULTS: We found that the performance of such an augmented model was significantly better than that of sequence-only or accessibility-only models with similar architectures. Specifically, its ability to predict the expression of highly variable genes and gene expression in other cell types improved, and higher attribution scores in the input DNA sequences of the augmented model conformed to accessibility, enabling the learning of cell type-specific sequence patterns. Additionally, we show that fine-tuning a pre-trained sequence-only model with both sequence and accessibility can boost performance further and highlight the importance of sequencing depth in sequence-to-expression prediction. AVAILABILITY AND IMPLEMENTATION: Source code is available on GitHub at https://github.com/lapohosorsolya/accessible_seq2exp.

Chromatin↗

PubMed2025

AlphaFold2, SPINE-X, and Seder on Four Hard CASP Targets.

We analyzed four cases from the CASP15 experiment with low prediction accuracy and compared AlphaFold2, SPINE-X, and Seder on these cases. We find that overall, AlphaFold2 performs better than SPINE-X in predicting secondary structure (SS) and solvent accessible surface area (ASA). For some cases, SPINE-X better predicts sheet and coil regions. We also find that AlphaFold2 is better than Seder in selecting the best matching tertiary structure model for one case and is worse in another case. For two cases Alphafold2 and Seder selected the same models. From the cases presented here, it appears that AlphaFold2 predicts more compact structures than the native one. We find that while, as widely reported, AlphaFold2 significantly improved protein tertiary structure prediction, there are cases, such as the four presented here, for which the tertiary structure prediction could still be significantly enhanced. The source code, license, and documentation for SPINE-X and Seder are available from Research and Information Systems, LLC at http://mamiris.com .

Software↗

PubMed2026

Multidimensional Protein Corona Analysis Toward Predictive Nano-Bio Interface Design.

Nanoparticles entering biological fluids are rapidly coated by proteins and other biomolecules, converting their synthetic surfaces into biologically active nano-bio interfaces. These coronas regulate colloidal stability, immune recognition, cellular uptake, biodistribution, pharmacokinetics, cargo delivery, and toxicity. Yet a protein list obtained by mass spectrometry captures only part of this interface. Corona identity and function are also shaped by protein organization, binding stability, exchange dynamics, conformational changes, and molecular accessibility. Here, we discuss recent progress in protein corona isolation and analysis from a question-oriented analytical perspective, with emphasis on how centrifugation, magnetic recovery, affinity- or chemistry-enabled capture, chromatography, filtration, and field-flow fractionation (FFF) influence the fidelity, integrity, and comparability of recovered coronas. We then examine how proteomic profiling can be integrated with binding measurements, interfacial structural analysis and functional validation to distinguish descriptive corona signatures from biologically meaningful mechanisms. We further consider how biofluid composition, disease state, tissue interfaces and cellular environments remodel corona identity, presentation, and bioactivity. Finally, we argue that standardized reporting, computational modeling, and AI-enabled approaches are essential for converting protein corona datasets into reproducible and predictive knowledge that can guide the design of drug delivery systems and precision nanomedicines.

Protein Corona↗

PubMed2025

Defining three dimensional chromatin structures of pediatric and adolescent B cells using primary B cell and EBV-immortalized B cell reference genomes.

BACKGROUND/PURPOSE: Knowledge of the 3D genome is essential to elucidate genetic mechanisms driving autoimmune diseases. The 3D genome is distinct for each cell type, and it is uncertain whether cell lines faithfully recapitulate the 3D architecture of primary human cells or whether developmental aspects of the pediatric immune system require use of pediatric samples. We undertook a systematic analysis of B cells and B cell lines to compare 3D genomic features encompassing risk loci for juvenile idiopathic arthritis (JIA), systemic lupus (SLE), and type 1 diabetes (T1D). METHODS: We isolated B cells from four healthy individuals, ages 9-17. HiChIP was performed using a CTCF antibody, and CTCF peaks were called within each sample separately. Peaks observed in all four samples were identified. CTCF loops were called within the pediatric samples using three CTCF peak datasets: 1) self-called CTCF consensus peaks called within the pediatric samples, 2) ENCODE's publicly available GM12878 CTCF ChIP-seq peaks, and 3) ENCODE's primary B cell CTCF ChIP-seq peaks from two adult females. Differential looping was assessed within the pediatric samples and each of the three peak datasets. RESULTS: The number of consensus peaks called in the pediatric samples was similar to that identified in ENCODE's GM12878 and primary B cell datasets. We observed < 1% of loops that demonstrated significantly differential looping between peaks called within the pediatric samples themselves and when called using ENCODE GM12878 peaks. Significant looping differences were even fewer when comparing loops of the pediatric called peaks to those of the ENCODE primary B cell peaks. When querying loops found in juvenile idiopathic arthritis, type 1 diabetes, or systemic lupus erythematosus risk haplotypes, we observed significant differences in only 2.2%, 1.0%, and 1.3% loops, respectively, when comparing peaks called within the pediatric samples and ENCODE GM12878 dataset. The differences were even less apparent when comparing loops called with the pediatric vs ENCODE adult primary B cell peak datasets. CONCLUSION: The 3D chromatin architecture in B cells is similar across pediatric, adult, and EBV-transformed cell lines. This conservation of 3D structure includes regions encompassing autoimmune risk haplotypes. Thus, even for pediatric autoimmune diseases, publicly available adult B cell and cell line datasets may be sufficient for assessing effects exerted in the 3D genomic space.

Humans↗

PubMed2025

Hypermethylation at 45S rDNA promoter in cancers.

The ribosomal genes (rDNA genes) encode 47S rRNA which accounts for up to 80% of all cellular RNA. At any given time, no more than 50% of rDNA genes are actively transcribed, and the other half is silent by forming heterochromatin structures through DNA methylation. In cancer cells, upregulation of ribosome biogenesis has been recognized as a hallmark feature, thus, the reduced methylation of rDNA promoter has been thought to support conformational changes of chromatin accessibility and the subsequent increase in rDNA transcription. However, an increase in the heterochromatin state through rDNA hypermethylation can be a protective mechanism teetering on the brink of a threshold where cancer cells rarely successfully proliferate. Hence, clarifying hypo- or hypermethylation of rDNA will unravel its additional cellular functions, including organization of genome architecture and regulation of gene expression, in response to growth signaling, cellular stressors, and carcinogenesis. Using the bisulfite-based quantitative real-time methylation-specific PCR (qMSP) method after ensuring unbiased amplification and complete bisulfite conversion of the minuscule DNA amount of 1 ng, we established that the rDNA promoter was significantly hypermethylated in 107 breast, 65 lung, and 135 colon tumour tissue samples (46.81%, 51.02% and 96.60%, respectively) as compared with their corresponding adjacent normal samples (26.84%, 38.26% and 77.52%, respectively; p < 0.0001). An excessive DNA input of 1 μg resulted in double-stranded rDNA remaining unconverted even after bisulfite conversion, hence the dramatic drop in the single-stranded DNA that strictly required for bisulfite conversion, and leading to an underestimation of rDNA promoter methylation, in other words, a faulty hypomethylation status of the rDNA promoter. Our results are in line with the hypothesis that an increase in rDNA methylation is a natural pathway protecting rDNA repeats that are extremely sensitive to DNA damage in cancer cells.

DNA Methylation↗

PubMed2026

Dual solvent cavities and hydrogen-bond networks define the chromophore environment in a far-red/orange-sensing cyanobacteriochrome.

Cyanobacteriochromes (CBCRs) are bilin-binding photoreceptors that exhibit remarkable spectral diversity and mediate light-dependent signaling in cyanobacteria. Far-red/orange-sensing CBCRs (froCBCRs) have attracted interest because of their unusually red-shifted absorption properties, yet structural information for their illuminated states has been lacking. Here, we report the first high-resolution (1.8 Å) crystal structure of the orange-absorbing (Po) state of the froCBCR ToFrO from Tolypothrix sp. PCC 7910. The structure reveals a compact, cyclic bilin configuration and water-mediated hydrogen-bonding networks within two solvent-accessible cavities. Within the GAF domain, the D-ring remains nearly perpendicular to the planar A-to-C ring system through interactions involving a flexible loop region. Comparative analyses of cryogenic synchrotron and room-temperature X-ray free-electron laser (XFEL) structures, together with molecular dynamics (MD) simulations, revealed alternative Met636 conformations associated with dynamic water exchange through the solvent-accessible cavity. Site-directed mutagenesis of cavity-lining and water-interacting residues resulted in modest spectral shifts. By contrast, mutations of two Trp residues, participating in π-π stacking with the D-ring and likely imposing a steric constraint near the A-ring, resulted in substantial blue and red shifts in the dark and illuminated states, respectively. Together with the observed chromophore geometry, these findings indicate that the spectral properties of ToFrO are governed by chromophore conformation and its direct interaction with surrounding residues through hydrogen-bonding, electrostatic, and π-π interactions. These results further suggest that cavity-mediated solvent organization contributes to stabilizing the local structural environment surrounding the chromophore and adjacent protein backbone. Collectively, these findings elucidate the structural basis for photoconversion and spectral tuning in froCBCRs.

Cyanobacteria↗

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↗

PubMed2025

Free energy spectroscopy reveals the mechanistic landscape of chromatin compaction.

Eukaryotic genomic DNA is repeatedly wrapped into nucleosome spools: the basic building block of chromatin. This organization regulates the physical accessibility of the genome to gene transcription, replication, and repair regulatory factors. Chromatin compaction is controlled by multivalent weak interactions, resulting in a complicated conformational landscape that remains challenging to characterize. This work reports a method for characterizing chromatin compaction, Free Energy Spectroscopy (FES), which is based on DNA nanotechnology and transmission electron microscopy. This method experimentally determines the chromatin compaction free energy landscape in terms of end-to-end distance and nucleosome stacking interactions. By deconvolving the free energy landscapes of partially and fully compact tetranucleosomes, FES revealed three separate mechanisms by which linker histones reshape the compaction energetics to condense chromatin. This study establishes FES as a method with the potential to help answer a broad range of mechanistic questions about genome and epigenome function.

DNA nanotechnology↗

PubMed2025

The influence of 10n and 10n+5 linker lengths on chromatin fiber topologies explored by mesoscale modeling.

The structural organization of chromatin is intricately influenced by the length of linker DNA connecting nucleosomes. Some studies have suggested preferred linker lengths of 10n and 10n+5 base pairs (bp) (n = integer). Because these lengths dictate the rotational orientation of successive nucleosomes in the fiber axis, they can markedly affect chromatin fiber compaction and topology. Using a refined mesoscale chromatin model with 5-bp resolution, we investigate the influence of linker DNA periodicity, linker histone density, salt concentration, and starting fiber topology on chromatin architecture for regular fibers versus "life-like" fibers, the latter with irregular spacing between nucleosomes. Our results reveal that regular fibers with 10n linkers exhibit compact zigzag configurations, whereas 10n+5 linkers generate more open and flexible structures. However, these effects are pronounced only for short linker lengths, as longer linkers are more heterogeneous. Moreover, increased linker histone density further enhances compaction for long linker lengths, and lower salt concentration modifies chromatin topologies, diminishing periodicity-driven effects. In addition, any periodicity effect in tightly packed solenoid configurations is much less pronounced. All these trends for regular fibers are reduced in life-like fibers with irregularly spaced nucleosomes, despite having the same average spacing. Moreover, the trend details depend highly on specific features of the fiber architecture as designed in experiments and simulations. Overall, our study highlights how reported differences depend on modeling details and emphasizes the role of linker DNA length in regulating chromatin fiber architecture and its potential implications for genome accessibility and expression.

Chromatin↗

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

DescribePROT Database of Residue-Level Protein Structure and Function Annotations.

DescribePROT is a freely available online database of structural and functional descriptors of proteins at the amino acid level. It provides access to 13 diverse descriptors that include sequence conservation, putative secondary structure, solvent accessibility, intrinsic disorder, and signal peptides, and putative annotations of residues that interact with proteins, peptides and nucleic acids. These data can be used to elucidate protein functions, to support efforts to develop therapeutics, and to develop and evaluate future predictors of protein structure and function. DescribePROT includes 7.8 billion predictions for 1.4 million proteins from 83 complete proteomes of popular model organisms. This information can be downloaded at multiple levels of scope (entire database, specific organisms, and individual proteins) and can be interacted with using a graphical interface that simultaneously displays data on multiple descriptors. We describe the contents of this resource, provide directions on how to use its interface, and offer instructions on how to obtain and interact with the underlying data. Moreover, we briefly discuss plans for a future expansion of this database. DescribePROT is available at http://biomine.cs.vcu.edu/servers/DESCRIBEPROT/ .

Databases, Protein↗

PubMed2025

Structural and thermodynamic impact of oncogenic mutations on the nucleosome core particle.

The nucleosome core particle is essential for chromatin structure and function, serving as the fundamental unit of eukaryotic chromatin. Oncogenic mutations in core histones disrupt chromatin dynamics, altering DNA repair and transcription processes. Here, we investigate the molecular consequences of two mutations-H2BE76K and H4R92T-using 36 μs of all-atom molecular dynamics simulations and experimental biophysical assays. These mutations destabilize the H2B-H4 interface by disrupting critical salt bridges and hydrogen bonds, reducing binding free energy at this interface. Principal-component analysis reveals altered helix conformations and increased interhelical distances in mutant systems. Thermal stability assays and differential scanning calorimetry confirm that these mutations lower the dimer dissociation temperature and reduce enthalpy compared with the wild-type. Taken together, our results elucidate how these mutations compromise nucleosome stability and propose mechanisms through which they could modulate chromatin accessibility and gene dysregulation in cancer.

Nucleosomes↗

PubMed2026

One chromatin, many structures: From ensemble contact maps to single-cell 3D organization.

Understanding how chromatin folds in three dimensions remains challenging because most experimental assays capture low-dimensional projections of an underlying, highly heterogeneous polymer. Here, we present an ensemble-based interpretive framework built on the previously introduced Self-Returning Excluded Volume (SR-EV) model, a minimal generator of chromatin conformations using a nucleosome-indexed coarse-grained representation based on stochastic return rules and excluded-volume geometry. Despite its simplicity, SR-EV recapitulates key experimental signatures across scales: heterogeneous nanoscale packing domains resembling ChromEMT and ChromSTEM observations, sparse and highly variable single-configuration contact patterns analogous to single-cell chromosome conformation capture (Hi-C), and robust ensemble-level contact enrichment consistent with topologically associating domains (TADs). In this framework, Hi-C loop and TAD signatures are interpreted as ensemble-level statistical enrichments rather than invariant features of single-cell conformations. SR-EV is explicitly designed to generate large ensembles of complete three-dimensional chromatin configurations that can be projected consistently onto two-dimensional contact maps and one-dimensional genomic profiles. By introducing architectural-protein effects only through ensemble selection rather than explicit forces, SR-EV supports a separation between intrinsic polymer geometry and regulatory bias and suggests that TAD-like features can emerge as statistical enrichments rather than deterministic three-dimensional structures. Coordination number and probe-based accessibility computed directly from SR-EV provide a unified link between three-dimensional packing, two-dimensional contact maps, and one-dimensional genomic profiles. The main contribution of this work is to show, within a single coarse-grained framework, how these multimodal observables arise as linked projections of the same heterogeneous chromatin ensemble through averaging and conditional sampling. Together, these results establish SR-EV as a minimal and geometrically grounded mesoscale reference framework for interpreting how heterogeneous chromatin ensembles give rise to multimodal experimental observables while remaining consistent with the fact that chromatin organization is realized in individual cells.

Chromatin↗

PubMed2025

One thousand SARS-CoV-2 antibody structures reveal convergent binding and near-universal immune escape.

Understanding antibody recognition and adaptation to viral evolution is central to vaccine and therapeutic development. Over 1,100 SARS-CoV-2 antibody structures have been resolved, marking the largest structural biology effort for a single pathogen. We present a comprehensive analysis of this landmark dataset to investigate the principles of antibody recognition and immune escape. Human immunoglobulins and camelid single-chain antibodies dominate, collectively mapping 99% of the receptor-binding domain. Despite remarkable sequence and conformational diversity, antibodies exhibit convergence in their paratope structures, revealing evolutionary constraints in epitope selection. Analyses reveal near-universal immune escape of antibodies, including all clinical monoclonals, by advanced variants such as KP3.1.1. On average, over one-third of antibody epitope residues are mutated. These findings support pervasive immune escape, underscoring the need to effectively leverage multi-epitope-targeting strategies to achieve durable immunity. To support community accessibility, we developed an interactive web server for visualization and analysis of antibody-antigen complexes and mutational data.

SARS-CoV-2↗

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↗

PubMed2026

A network of steroid receptor transcription factors regulates ovarian chromatin remodeling in the transition to ovulation.

Steroid receptors are transcription factors activated by progesterone, androgen, and glucocorticoid that bind the same canonical DNA sequence to modulate genome function in response to steroid hormones. However, the mechanisms defining unique physiological roles of these conserved receptors within the same tissue context, including the ovary, remain elusive. Here, we describe the dynamic association between each steroid receptor cistrome in the mouse ovary responding to the hormonal switch from follicle development to ovulation and generate chromatin conformation maps to define steroid receptor roles in promoter-enhancer interactions and gene transcription. Ovulatory hormones trigger progesterone receptor (PGR) and glucocorticoid receptor (NR3C1 [also known as GR]) binding to novel chromatin sites, promoting transcriptional activation of genes that are required for ovulation, whereas AR-chromatin interactions and androgen receptor (AR)-associated genes are repressed. Integration of genomic and transcriptomic data illustrates two parallel modes of PGR-mediated gene activation. Unique cooperation between PGR and GR enables their recruitment to previously inaccessible promoters, increasing histone acetylation, chromatin accessibility, and transcription activation, with PGR being the indispensable component of this transcriptional complex. Alternatively, PGR tethered to enhancers interacting with preaccessible, AR/GR-bound promoters induces gene activation. Our findings illustrate the multifaceted steroid receptor interactions that translate progressive change in steroid environments to collectively reprogram granulosa cell genome function to switch from follicle development to ovulation.

Journal Article↗