ArticleNucleic acids research2012
Integration of Hi-C and ChIP-seq data reveals distinct types of chromatin linkages.
Article in Nucleic acids research, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 70 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
70 citing papers in PubMed, 116 citations in OpenAlex.
- Repeat expansions inbioRxiv : the preprint server for biology · 2026Article
- Generating three-dimensional genome structures with a variational quantum algorithm.Briefings in bioinformatics · 2025Article
- Integrated analysis of differential intra-chromosomal community interactions: A study of breast cancer.Artificial intelligence in medicine · 2025Article
- Modeling combinatorial regulation from single-cell multi-omics provides regulatory units underpinning cell type landscape using cRegulon.Genome biology · 2025Article
- In Silico Analysis of Post-COVID-19 Condition (PCC) Associated SNP rs9367106 Predicts the Molecular Basis of Abnormalities in the Lungs and Brain Functions.International journal of molecular sciences · 2025Article
- Advancing therapeutic target discovery in pulmonary diseases: evolution and application of space exploration technologies.Frontiers in cell and developmental biology · 2025Review
- Identification of drug responsive enhancers by predicting chromatin accessibility change from perturbed gene expression profiles.NPJ systems biology and applications · 2024Article
- HLA Genetics for the Human Diseases.Advances in experimental medicine and biology · 2024Review
- CHEX-seq detects single-cell genomic single-stranded DNA with catalytical potential.Nature communications · 2023Article
- The adapted Activity-By-Contact model for enhancer-gene assignment and its application to single-cell data.Bioinformatics (Oxford, England) · 2023Article
- A novel network pharmacology approach for leukaemia differentiation therapy using MogrifyOncogene · 2022Article
- HiC1Dmetrics: framework to extract various one-dimensional features from chromosome structure data.Briefings in bioinformatics · 2022Article
- Mapping nucleosome and chromatin architectures: A survey of computational methods.Computational and structural biotechnology journal · 2022Review
- New Approaches to Assess Mechanisms of Action of Selective Vitamin D Analogues.International journal of molecular sciences · 2021Review
- Chrom-Lasso: a lasso regression-based model to detect functional interactions using Hi-C data.Briefings in bioinformatics · 2021Article
- Inferring time series chromatin states for promoter-enhancer pairs based on Hi-C data.BMC genomics · 2021Article
- Ultrasound May Suppress Tumor Growth, Inhibit Inflammation, and Establish Tolerogenesis by Remodeling Innatome via Pathways of ROS, Immune Checkpoints, Cytokines, and Trained Immunity/Tolerance.Journal of immunology research · 2021Article
- Modeling and analysis of Hi-C data by HiSIF identifies characteristic promoter-distal loops.Genome medicine · 2020Article
- Epigenetic modifications of histones in cancer.Genome biology · 2019Review
- Landscape of Enhancer-Enhancer Cooperative Regulation during Human Cardiac Commitment.Molecular therapy. Nucleic acids · 2019Article
10 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors at 1 institution in 1 country.
Funding
Abstract
We have analyzed publicly available K562 Hi-C data, which enable genome-wide unbiased capturing of chromatin interactions, using a Mixture Poisson Regression Model and a power-law decay background to define a highly specific set of interacting genomic regions. We integrated multiple ENCODE Consortium resources with the Hi-C data, using DNase-seq data and ChIP-seq data for 45 transcription factors and 9 histone modifications. We classified 12 different sets (clusters) of interacting loci that can be distinguished by their chromatin modifications and which can be categorized into two types of chromatin linkages. The different clusters of loci display very different relationships with transcription factor-binding sites. As expected, many of the transcription factors show binding patterns specific to clusters composed of interacting loci that encompass promoters or enhancers. However, cluster 9, which is distinguished by marks of open chromatin but not by active enhancer or promoter marks, was not bound by most transcription factors but was highly enriched for three transcription factors (GATA1, GATA2 and c-Jun) and three chromatin modifiers (BRG1, INI1 and SIRT6). To investigate the impact of chromatin organization on gene regulation, we performed ribonucleicacid-seq analyses before and after knockdown of GATA1 or GATA2. We found that knockdown of the GATA factors not only alters the expression of genes having a nearby bound GATA but also affects expression of genes in interacting loci. Our work, in combination with previous studies linking regulation by GATA factors with c-Jun and BRG1, provides genome-wide evidence that Hi-C data identify sets of biologically relevant interacting loci.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.