Ask about this productRelated genes to: CTCF antibody
- Gene:
- CTCF NIH gene
- Name:
- CCCTC-binding factor
- Previous symbol:
- -
- Synonyms:
- -
- Chromosome:
- 16q22.1
- Locus Type:
- gene with protein product
- Date approved:
- 2000-10-20
- Date modifiied:
- 2016-02-12
Related products to: CTCF antibody
Related articles to: CTCF antibody
- Sequence-based deep learning has advanced genome interpretation, yet most models remain task-specific and rely on retraining, limiting scalability across biological contexts. Here we present SUCCEED, a supervised multi-task DNA foundation model pretrained on 6,389 ENCODE functional genomics tracks to learn transferable regulatory representations. By integrating convolutional layers with a Transformer architecture, SUCCEED captures both local sequence motifs and long-range regulatory dependencies, achieving performance comparable to or exceeding Enformer across benchmark tasks. Through transfer learning, it predicts cell-type-specific epigenomic profiles, denoises sparse chromatin accessibility signals, and predicts three-dimensional chromatin contacts without CTCF input across data scales and cell types. Across diverse genomics tasks, SUCCEED performs comparably to supervised foundation models such as Sei and outperforms self-supervised models trained solely on DNA sequence. Overall, SUCCEED is a transferable and scalable foundation model that provides a unified framework for genome-scale regulatory modeling in complex biological contexts. - Source: PubMed
Publication date: 2026/05/14
Sun CanzhuangHe ZhijieZhang ShifeiXu KangSun YuWang YuyangHu PengzhenBo XiaochenLiao MingzhiLi HaoChen Hebing - Quantitative interpretation of ChIP-seq data is instrumental to derive insight into chromatin and transcription factor biology. Here we developed ChIP-FRiP, an end-to-end pipeline enabling systematic comparison of pairwise protein positioning, and applied it to the study of cohesin. In mammalian interphase, loop extruding cohesin complexes are positioned by CTCF barriers to generate locus-specific 3D genome folding patterns. Many aspects of our understanding of cohesin loop extrusion come from interpreting the amount of cohesin ChIP-seq signal at CTCF barriers, which has been reported to change variably after perturbing cohesin co-factors, such as NIPBL, PDS5A/B, and WAPL. Using ChIP-FRiP to homogeneously process 140 cohesin ChIP-seq datasets from 13 publicly available studies, we observed substantial variation attributable to technical effects, obscuring biological interpretability. To better understand how technical considerations, such as antibody specificity, influence apparent cohesin binding patterns, we integrated technical aspects of ChIP-seq into biophysical simulations of loop extrusion. Leveraging a simple biochemical model for background ChIP-seq signal, we derived a strategy to estimate and correct for the background using paired spike-in ChIP-seq data from wild-type and depletion conditions. Our results establish a framework for reliable comparative analysis, demonstrating that accurate background correction is requisite for interpreting the roles of cohesin cofactors in cohesin positioning. - Source: PubMed
Publication date: 2026/02/27
Xiao YaoAnderson Erika CRahmaninejad HadiNora ElphègeFudenberg Geoffrey - In this study, we systematically analyzed the dynamic changes in chromatin accessibility and the transcriptional responses in the spleen of largemouth bass () following infection with iridovirus (LMBV) using the assay for transposase-accessible chromatin with sequencing (ATAC-seq) and transcriptome sequencing (RNA-seq). Based on post-infection survival status, largemouth bass were classified into a resistant group (SR) and a susceptible group (SS). A total of 11,317 differentially accessible regions were identified between the two groups, among which the chromatin accessibility of core promoter regions was entirely increased in the SR group, suggesting that chromatin remodeling in these regions may directly participate in the transcriptional regulation of immune-related genes. Functional enrichment analysis revealed that genes associated with differentially accessible regions were significantly enriched in immune-related pathways such as autophagy, apoptosis, Toll-like receptor signaling, and NOD-like receptor signaling. Motif analysis further identified that transcription factors significantly enriched in the SR group included CTCF and heterodimers composed of multiple members of the ETS and FOX transcription factor families. Through integrative analysis, seven transcription factors (CTCF, Spi1, ETV2::FOXI1, FOXJ2::ELF1, FOXO1::ELK1, SPIC, and FOXO1::ELF1) were found to be significantly enriched in core promoter regions. To further screen for differentially expressed genes directly regulated by chromatin accessibility changes, an overlapping analysis was performed between 629 predicted target genes and 2656 differentially expressed genes (DEGs), resulting in the identification of 71 candidate genes. Among these, three immune-related genes (, , and ) belonging to the ETS and FOX families were identified. This study reveals the dynamic chromatin accessibility landscape of largemouth bass in response to LMBV infection and demonstrates that increased chromatin accessibility in core promoter regions is closely associated with the resistant phenotype. Heterodimers of ETS and FOX family transcription factors may participate in antiviral immune responses by regulating the expression of key immune genes such as , , and , providing potential epigenetic molecular markers for disease resistance breeding in fish. - Source: PubMed
Publication date: 2026/05/05
Sun HuiHua JixiangTao YifanLu SiqiWang WenDong YalunZhang LinbingHe JixiangHe JieQiang Jun - Standard Micro-C protocols typically require millions of cells, limiting their application to rare cell populations. Here, we present an optimized low-input Micro-C workflow that requires only 100 000 cells. By downsampling both our low-input dataset and a control dataset from 5 million cells to 120 million raw read pairs, we demonstrate that all key architectural features-Compartments, Topologically associating domains (TADs), and Chromatin loops-are reliably detected from as few as 100 000 cells. The low-input protocol achieved a high cis interaction ratio (96.1%) and low PCR duplication rate (3.0%), indicating high library complexity and low background noise. Applying this method to investigate acute CTCF (CCCTC-binding factor) degradation, we observed the loss of loops and TAD boundaries in CTCF-degraded samples, consistent with previous reports. Our optimized protocol enables nucleosome-resolution 3D genome mapping for sample-limited studies. - Source: PubMed
Publication date: 2026/04/15
Shan FengnianPei ChongrenXia SijianLing Fei - The three-dimensional (3D) organization of the genome is strongly influenced by interactions between chromatin and lamin proteins at the nuclear envelope. Here, we investigate the role of lamina-associated domains (LADs) in shaping genome architecture using coarse-grained polymer models of mouse embryonic fibroblasts and embryonic stem cells. By integrating genome-wide LAD maps from DamID assays, we simulate chromatin conformations with and without LAD attachment. Incorporating LAD-lamina interactions reproduces the experimentally observed radial chromatin distribution and reveals that LADs induce extensive long-range (70-120 Mbp) chromatin contacts beyond typical loops and topologically associating domains (TADs). We describe these contacts in terms of two limiting geometric scenarios: LAD crowding, in which peripheral tethering increases the proximity of nearby non-LAD regions to LADs, and LAD anchoring, in which lamina-bound LADs constrain neighboring chromatin positions. LAD-induced interactions were especially prominent in chromatin regions lacking architectural proteins such as CTCF, and were associated with lower gene density and reduced transcriptional activity. Together, these results suggest that LAD-lamina tethering reshapes long-range chromatin contact probabilities through boundary-driven effects and is associated with gene-poor, less transcriptionally active chromatin regions. - Source: PubMed
Publication date: 2026/05/08
Delafrouz PouryaFarooq HammadDu LinMa AoLiang Jie