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
- The pig (Sus scrofa) is both an economically important livestock species and a valuable biomedical model . Its genome bears regulatory features shaped by domestication and selection that are often poorly captured by genomic language models (gLMs) trained on human or model organism data. To address these challenges, we developed Porcine MutBERT, a suite of lightweight gLMs with 86 million parameters that employs a probabilistic masking strategy targeting evolutionarily informative single-nucleotide polymorphisms. This design captures population-specific variation while reducing computational cost. We further propose PorcineBench, a benchmark that evaluates gLM performance across porcine functional genomics tasks, including chromatin accessibility (ATAC-seq), CTCF binding, and histone modifications (H3K27ac, H3K4me1, and H3K27me3). Results show that Porcine MutBERT family achieves highly competitive performance on PorcineBench relative to substantially larger models, while providing an explicitly porcine-adapted alternative for downstream functional genomics in pigs. These findings underscore the advantages of species-adapted, efficient architectures in agricultural genomics and demonstrate that compact gLMs can expand accessibility and impact in resource-constrained settings. The code and data are available at https://github.com/ai4nucleome/pigmutbert. - Source: PubMed
Long WeicaiZhou RongWei WenkangZhang XiaoaiWu ShanshanLi KuiZhang YanlinWang Zishuai - Nonunion of fractures is a major challenge in orthopedics and traumatology, especially with increasing high-energy injuries. Adipose-derived mesenchymal stem cells (ASCs) are a readily accessible source with strong osteogenic potential. This study compared the bone regenerative efficacy of undifferentiated ASCs versus their osteogenically pre-differentiated derivatives in a critical-size femoral nonunion model. - Source: PubMed
Publication date: 2026/06/18
Maslennikov SerhiiIsachenko MariiaDanukalo MaksymHancheva OlgaGolovakha MaksymKolesnyk Yurii - Protein-mediated chromatin interactions are fundamental to gene regulation. However, experimental approaches such as Chromatin Interaction Analysis by Paired-End Tag sequencing are limited by data scarcity and high cost, while existing computational models are constrained by limited resolution and challenges in effectively integrating heterogeneous genomic data. To address these issues, we propose GraphChIAr, a regression-based deep learning framework that estimates chromatin interaction strength by augmenting Hi-C contact maps with various ChIP-seq profiles and genomic sequence information. A key advantage of GraphChIAr is its super-resolution capability, enabling accurate estimations of chromatin interactions from conventional resolutions down to ultra-high near-nucleosome resolution (e.g. 200 bp). By introducing genomic shift distance in GraphChIAr, we enabled it to predict remote interactions between distant genomic loci at a genome-wide scale. Cross-referencing results demonstrate high predictive accuracy for key mediating proteins such as CTCF, highlighting the benefits of integrating complementary genomic features. Together, GraphChIAr provides an effective computational tool to augment experimental data and advance the study of 3D genome organization. The source code of GraphChIAr is available at (https://github.com/don194/GraphChIAr). - Source: PubMed
Dong HaoRao Guo-ZhengWang Hao-YuWu Xin-RanXian TongWang Bo-QiangDu Pu-Feng - Cleavage under target and tagmentation (CUT&Tag) is a widely used method for profiling chromatin occupancy; however, its reproducibility is impacted by a lack of standardization in experimental and analytical procedures. This study identifies four key parameters critical for optimizing CUT&Tag performance. First, optimal cell number requirements are target and species specific: H3K27me3 detection requires ≥10K cells in both mouse and rat cells, whereas CTCF mapping needs 50K cells in mouse embryonic stem cells and 100K in rat C6 cells, reflecting potential differences in protein abundance and antibody affinity. Second, the peak-calling methodology is crucial; default model-based analysis of chromatin immunoprecipitation followed by sequencing (MACS2) scaling causes a paradoxical decrease in peak numbers with decreasing IgG control size, a limitation resolved by the "scale-to-large" option. Third, duplicate removal strategies differentially affect peak callers, with MACS2 performing best using biological reads and sparse enrichment analysis for CUT&RUN (SEACR) relying on technical duplicates for accurate calling. Finally, mild crosslinking with 0.2 mM ethylene glycol bis (succinimidyl succinate) (EGS) for 5 min enhances CTCF detection and reduces variability. Together, these optimizations establish practical guidelines for reliable CUT&Tag experimental design and analysis. - Source: PubMed
Publication date: 2026/06/12
Murray Josiah DRay AtrayeeKasomva KhanmiSteen EricaStelloh CaryPulakanti KirthiDoerfler Phillip ADe Sarkar NavonilQiu QiongziLiu YongGeurts Aron MCowley Allen WMeyer Alison ELiang MingyuRao Sridhar - Adeno-Associated Viruses (AAVs) are powerful platforms for delivering therapeutic transgenes via recombinant AAV (rAAV) vectors. However, a limited understanding of the regulation of AAV gene expression has narrowed the ability to efficiently express therapeutic transgenes from rAAV vectors. Since rAAVs retain only the wtAAV inverted terminal repeats (ITR), we hypothesized that regulatory elements outside the ITR that govern wild-type AAV (wtAAV) gene expression can be used to modify rAAV genomes to enhance vector performance. Through in silico analysis, biochemical pulldowns, and high-throughput sequencing, we have identified that the host architectural protein CCCTC-binding Factor (CTCF) associates with the wtAAV type 2 (wtAAV2) genome but is absent from rAAV vectors. Global knockdown and site-specific deletion revealed that the CTCF binding element (CBE) on the wtAAV2 genome, located upstream of the viral P5 promoter, regulates expression of the viral genes. We have re-engineered new rAAV vectors expressing a GFP reporter transgene to contain the wtAAV2-CBE upstream of the vector promoter. Our results show that CTCF binding dramatically increased rAAV transduction efficiency and GFP expression by up to four-fold across multiple cell types. This enhancement was independent of the AAV capsid serotype used for packaging rAAV vectors. CUT&RUN analysis revealed that this CBE was necessary and sufficient to regulate the chromatin landscape of wtAAV2 and rAAV2. Finally, we observed that CTCF-mediated chromatin remodeling of rAAV2 led to increased production of nascent RNA transcripts from the vector genome. Based on our findings, we propose that CTCF supports wtAAV2/rAAV gene expression by shaping the local chromatin landscape. - Source: PubMed
Publication date: 2026/06/03
Larsen Clairine I SAbrahams Rhiannon RGuertler ReaWilion Elliott MErata EdaSykes Zachary HStoica LoreleiThirumoorthy GopishankarSinha DivyaRai RichaHofer Elizabeth KHart EleanorGamm David MFuller Matthew SMajumder Kinjal