Long-read ChIA-PET for base-pair-resolution mapping of haplotype-specific chromatin interactions.

BackgroundLong-range chromatin interactions play an important role in transcription regulation. Chromatin Interaction Analysis with Paired-End-Tag sequencing (ChIA-PET) is an emerging technology that has unique advantages in chromatin interaction analysis, and thus provides insight into the study of transcription regulation.ResultsThis article introduces the experimental protocol and data analysis process of ChIA-PET, as well as discusses some applications using this technology. It also unveils the direction of future studies based on this technology.ConclusionsOverall we show that ChIA-PET is the cornerstone to explore the three-dimensional (3D) chromatin structure, and certainly will lead the forthcoming wave of 3D genomics studies.

High-throughput chromosome conformation capture (3C) technologies, such as Hi-C, have made it possible to survey 3D genome structure. However, obtaining 3D profiles at kilobase resolution at low cost remains a major challenge. Therefore, we herein present an algorithm for precise identification of chromatin interaction sites at kilobase resolution from MNase-seq data, termed chromatin interaction site detector (CISD), and a CISD-based chromatin loop predictor (CISD_loop) that predicts chromatin–chromatin interactions (CCIs) from low-resolution Hi-C data. We show that the predictions of CISD and CISD_loop overlap closely with chromatin interaction analysis by paired-end tag sequencing (ChIA-PET) anchors and loops, respectively. The validity of CISD/CISD_loop was further supported by a 3C assay at about 5 kb resolution. Finally, we demonstrate that only modest amounts of MNase-seq and Hi-C data are sufficient to achieve ultrahigh resolution CCI maps. Our results suggest that CCIs may result in characteristic nucleosomes arrangement patterns flanking the interaction sites, and our algorithms may facilitate precise and systematic investigations of CCIs on a larger scale than hitherto have been possible.

Chromatin interaction analysis by paired-end tag sequencing (ChIA-PET) is an important experimental method for detecting specific protein-mediated chromatin loops genome-wide at high resolution. Here, we proposed a new statistical approach with a mixture model, chromatin interaction analysis using mixture model (ChIAMM), to detect significant chromatin interactions from ChIA-PET data. The statistical model is cast into a Bayesian framework to consider more systematic biases: the genomic distance, local enrichment, mappability, and GC content. Using different ChIA-PET datasets, we evaluated the performance of ChIAMM and compared it with the existing methods, including ChIA-PET Tool, ChiaSig, Mango, ChIA-PET2, and ChIAPoP. The result showed that the new approach performed better than most top existing methods in detecting significant chromatin interactions in ChIA-PET experiments.

Genome-wide association studies have identified 1q22 as a susceptibility locus for cerebral small vessel diseases, including non-lobar intracerebral hemorrhage (ICH) and lacunar stroke. In the present study, we performed targeted high-depth sequencing of 1q22 in ICH cases and controls to further characterize this locus and prioritize potential causal mechanisms, which remain unknown. A total of 95,000 base pairs spanning 1q22, including SEMA4A, SLC25A44, and PMF1/PMF1-BGLAP were sequenced in 1,055 spontaneous ICH cases (534 lobar and 521 non-lobar) and 1,078 controls. Firth regression and Rare Variant Influential Filtering Tool analysis were used to analyze common and rare variants, respectively. Chromatin interaction analyses were performed using Hi-C, chromatin immunoprecipitation followed by sequencing, and chromatin interaction analysis with paired-end tag databases. Multivariable Mendelian randomization assessed whether alterations in gene-specific expression relative to regionally co-expressed genes at 1q22 could be causally related to ICH risk. Common and rare variant analyses prioritized variants in SEMA4A 5'-UTR and PMF1 intronic regions, overlapping with active promoter and enhancer regions based on ENCODE annotation. Hi-C data analysis determined that 1q22 is spatially organized in a single chromatin loop, and that the genes therein belong to the same topologically associating domain. Chromatin immunoprecipitation followed by sequencing and chromatin interaction analysis with paired-end tag data analysis highlighted the presence of long-range interactions between the SEMA4A-promoter and PMF1-enhancer regions prioritized by association testing. Multivariable Mendelian randomization analyses demonstrated that PMF1 overexpression could be causally related to non-lobar ICH risk. Altered promoter-enhancer interactions leading to PMF1 overexpression, potentially dysregulating polyamine catabolism, could explain demonstrated associations with non-lobar ICH risk at 1q22, offering a potential new target for prevention of ICH and cerebral small vessel disease. ANN NEUROL 2024;95:325-337.

Free energy-based model of CTCF-mediated chromatin looping in the human genome.

Methods for comparative ChIA-PET and Hi-C data analysis.

Long-range chromatin interactions are important for transcriptional regulation of genes, many of which are related to complex agronomics traits. However, the pattern of three-dimensional chromatin interactions remains unclear in plants. Here we report the generation of chromatin interaction analysis by paired-end tag sequencing (ChIA-PET) data and the construction of extensive H3K4me3- and H3K27ac-centered chromatin interaction maps in maize. Results show that the interacting patterns between proximal and distal regulatory regions of genes are highly complex and dynamic. Genes with chromatin interactions have higher expression levels than those without interactions. Genes with proximal-proximal interactions prefer to be transcriptionally coordinated. Tissue-specific proximal–distal interactions are associated with tissue-specific expression of genes. Interactions between proximal and distal regulatory regions further interweave into organized network communities that are enriched in specific biological functions. The high-resolution chromatin interaction maps will help to understand the transcription regulation of genes associated with complex agronomic traits of maize.

Histone modifications have previously been leveraged to map the locations of candidate enhancer and promoters in one dimensional genomic space. Chepelev et al. report the first Chromatin Interaction Analysis with Paired-End Tag (ChIA-PET) sequencing of a specific histone modification to systematically map long-range physical interactions among enhancer and promoters, yielding insights into the nature of these interactions.

BackgroundThe impact of signal-dependent transcription factors, such as glucocorticoid receptor and nuclear factor kappa-b, on the three-dimensional organization of chromatin remains a topic of discussion. The possible scenarios range from remodeling of higher order chromatin architecture by activated transcription factors to recruitment of activated transcription factors to pre-established long-range interactions.ResultsUsing circular chromosome conformation capture coupled with next generation sequencing and high-resolution chromatin interaction analysis by paired-end tag sequencing of P300, we observed agonist-induced changes in long-range chromatin interactions, and uncovered interconnected enhancer–enhancer hubs spanning up to one megabase. The vast majority of activated glucocorticoid receptor and nuclear factor kappa-b appeared to join pre-existing P300 enhancer hubs without affecting the chromatin conformation. In contrast, binding of the activated transcription factors to loci with their consensus response elements led to the increased formation of an active epigenetic state of enhancers and a significant increase in long-range interactions within pre-existing enhancer networks. De novo enhancers or ligand-responsive enhancer hubs preferentially interacted with ligand-induced genes.ConclusionsWe demonstrate that, at a subset of genomic loci, ligand-mediated induction leads to active enhancer formation and an increase in long-range interactions, facilitating efficient regulation of target genes. Therefore, our data suggest an active role of signal-dependent transcription factors in chromatin and long-range interaction remodeling.Electronic supplementary materialThe online version of this article (doi:10.1186/s13059-015-0832-9) contains supplementary material, which is available to authorized users.

In this study, we identified a key enhancer RNA (eRNA) region in breast cancer (BRCA) by applying an integrated analysis method. Reported eRNA region and genes affected by them were selected as presumed target pairs. Kaplan–Meier (KM) survival and correlation analyses were performed to screen valuable eRNA region. Based on the KM value and its correlation with the paired target genes, we carefully selected ELOVL2-AS1 as a potential key eRNA region in BRCA. Subsequently, we analyzed the expression of ELOVL2-AS1 and ELOVL2 in four BRCA subtypes and in different BRCA cell lines. The expression of ELOVL2-AS1 and ELOVL2 in triple negative breast cancer (TNBC) was significantly lower than those in Luminal A. After that, we analyzed the function of genes that are positively correlated with ELOVL2-AS1. We found that the co-expression gene mainly related to cilia and cilia characteristics of TNBC is significantly weaker than that of Luminal A. Considering the stronger invasion and metastasis of TNBC (compared with Luminal A) and the close relationship between decreased cilia and metastasis, we overexpressed ELOVL2-AS1 in TNBC and observed its effect on cell migration. The results show that it can inhibit the migration of TNBC. Finally, we analyzed the assay for transposase-accessible chromatin sequencing data, chromatin interaction analysis with paired-end tag sequencing data, and chromatin immunoprecipitation sequencing data and identified the chromatin interaction between ELOVL2-AS1 and ELOVL2, suggesting a direct regulatory interaction.

CTCF-Mediated Human 3D Genome Architecture Reveals Chromatin Topology for Transcription

Chromatin loops connect regulatory elements to their target genes. They serve as bridges between transcriptional regulation and phenotypic variation in mammals. However, spatial organization of regulatory elements and its impact on gene expression in plants remain unclear. Here, we characterize epigenetic features of active promoter proximal regions and candidate distal regulatory elements to construct high-resolution chromatin interaction maps for maize via long-read chromatin interaction analysis by paired-end tag sequencing (ChIA-PET). The maps indicate that chromatin loops are formed between regulatory elements, and that gene pairs between promoter proximal regions tend to be co-expressed. The maps also demonstrated the topological basis of quantitative trait loci which influence gene expression and phenotype. Many promoter proximal regions are involved in chromatin loops with distal regulatory elements, which regulate important agronomic traits. Collectively, these maps provide a high-resolution view of 3D maize genome architecture, and its role in gene expression and phenotypic variation.

One of the major findings in systems biomedicine is that both pathogenesis of diseases and drug mode of action have a module basis. However, the transcription factors (TFs) regulating the modules remain largely unknown. In this study, by using biclustering approach FABIA (factor analysis for bicluster acquisition), we generate 49 modules for gene expression profiles on 1309 agent treatments. These modules are of biological relevance in terms of functional enrichment, drug-drug interactions and 3D proximity in chromatins. By using the information of drug targets (some of which are TFs) and biological regulation, the links between 28 modules and 12 specific TFs, such as estrogen receptors (ERs), nuclear factor-like 2 and peroxisome proliferator-activated receptor gamma, can be established. Some of the links are supported by 3D transcriptional regulation data [derived from ChIA-PET (chromatin interaction analysis using paired-end tags) experiments] and drug mode of action as well. The relationships between modules and TFs provide new clues to interpreting biological regulation mechanisms, in particular, the lipid metabolism regulation by ERα. In addition, the links between natural products (e.g. polyphenols) and their associated modules and TFs are helpful to elucidate their polypharmacological effects in terms of activating specific TFs, such as ERs, nuclear factor-like 2 and peroxisome proliferator-activated receptor gamma.

The mammalian circadian clock relies on the transcription factor CLOCK:BMAL1 to coordinate the rhythmic expression of thousands of genes. Consistent with the various biological functions under clock control, rhythmic gene expression is tissue-specific despite an identical clockwork mechanism in every cell. Here we show that BMAL1 DNA binding is largely tissue-specific, likely because of differences in chromatin accessibility between tissues and cobinding of tissue-specific transcription factors. Our results also indicate that BMAL1 ability to drive tissue-specific rhythmic transcription is associated with not only the activity of BMAL1-bound enhancers but also the activity of neighboring enhancers. Characterization of physical interactions between BMAL1 enhancers and other cis-regulatory regions by RNA polymerase II chromatin interaction analysis by paired-end tag (ChIA-PET) reveals that rhythmic BMAL1 target gene expression correlates with rhythmic chromatin interactions. These data thus support that much of BMAL1 target gene transcription depends on BMAL1 capacity to rhythmically regulate a network of enhancers.

Three-dimensional (3D) genomics is an emerging discipline that studies the three-dimensional structure of chromatin and the three-dimensional and functions of genomes. It mainly studies the three-dimensional conformation and functional regulation of intranuclear genomes, such as DNA replication, DNA recombination, genome folding, gene expression regulation, transcription factor regulation mechanism, and the maintenance of three-dimensional conformation of genomes. Self-chromosomal conformation capture (3C) technology has been developed, and 3D genomics and related fields have developed rapidly. In addition, chromatin interaction analysis techniques developed by 3C technologies, such as paired-end tag sequencing (ChIA-PET) and whole-genome chromosome conformation capture (Hi-C), enable scientists to further study the relationship between chromatin conformation and gene regulation in different species. Thus, the spatial conformation of plant, animal, and microbial genomes, transcriptional regulation mechanisms, interaction patterns of chromosomes, and the formation mechanism of spatiotemporal specificity of genomes are revealed. With the help of new experimental technologies, the identification of key genes and signal pathways related to life activities and diseases is sustaining the rapid development of life science, agriculture, and medicine. In this paper, the concept and development of 3D genomics and its application in agricultural science, life science, and medicine are introduced, which provides a theoretical basis for the study of biological life processes.