Browse
Submit Data
Databases
API
Help

Dataset Information

19 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

MUNIn: A statistical framework for identifying long-range chromatin interactions from multiple samples.

ABSTRACT: Chromatin spatial organization (interactome) plays a critical role in genome function. Deep understanding of chromatin interactome can shed insights into transcriptional regulation mechanisms and human disease pathology. One essential task in the analysis of chromatin interactomic data is to identify long-range chromatin interactions. Existing approaches, such as HiCCUPS, FitHiC/FitHiC2, and FastHiC, are all designed for analyzing individual cell types or samples. None of them accounts for unbalanced sequencing depths and heterogeneity among multiple cell types or samples in a unified statistical framework. To fill in the gap, we have developed a novel statistical framework MUNIn (multiple-sample unifying long-range chromatin-interaction detector) for identifying long-range chromatin interactions from multiple samples. MUNIn adopts a hierarchical hidden Markov random field (H-HMRF) model, in which the status (peak or background) of each interacting chromatin loci pair depends not only on the status of loci pairs in its neighborhood region but also on the status of the same loci pair in other samples. To benchmark the performance of MUNIn, we performed comprehensive simulation studies and real data analysis and showed that MUNIn can achieve much lower false-positive rates for detecting sample-specific interactions (33.1%-36.2%), and much enhanced statistical power for detecting shared peaks (up to 74.3%), compared to uni-sample analysis. Our data demonstrated that MUNIn is a useful tool for the integrative analysis of interactomic data from multiple samples.

SUBMITTER: Liu W

PROVIDER: S-EPMC8415461 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Similar Datasets

ChIAMM: A Mixture Model for Statistical Analysis of Long-Range Chromatin Interactions From ChIA-PET Experiments.

Project description: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.

| S-EPMC7767989 | biostudies-literature

Nuclear position modulates long-range chromatin interactions.

Project description:The human genome is non-randomly organized within the cell nucleus. Spatial mapping of genome folding by biochemical methods and imaging has revealed extensive variation in locus interaction frequencies between cells in a population and between homologs within an individual cell. Commonly used mapping approaches typically examine either the relative position of genomic sites to each other or the position of individual loci relative to nuclear landmarks. Whether the frequency of specific chromatin-chromatin interactions is affected by where in the nuclear space a locus is located is unknown. Here, we have simultaneously mapped at the single cell level the interaction frequencies and radial position of more than a hundred locus pairs using high-throughput imaging to ask whether the location within the nucleus affects interaction frequency. We find strong enrichment of many interactions at specific radial positions. Position-dependency of interactions was cell-type specific, correlated with local chromatin type, and cell-type-specific enriched associations were marked by increased variability, sometimes without a significant decrease in mean spatial distance. These observations demonstrate that the folding of the chromatin fiber, which brings genomically distant loci into proximity, and the position of that chromatin fiber relative to nuclear landmarks, are closely linked.

| S-EPMC9581366 | biostudies-literature

Long-range chromatin interactions in pathogenic gene expression control.

Project description:A large number of distal cis-regulatory elements (cREs) have been annotated in the human genome, which plays a central role in orchestrating spatiotemporal gene expression. Since many cREs regulate non-adjacent genes, long-range cRE-promoter interactions are an important factor in the functional characterization of the engaged cREs. In this regard, recent studies have demonstrated that identification of long-range target genes can decipher the effect of genetic mutations residing within cREs on abnormal gene expression. In addition, investigation of altered long-range cREs-promoter interactions induced by chromosomal rearrangements has revealed their critical roles in pathogenic gene expression. In this review, we briefly discuss how the analysis of 3D chromatin structure can help us understand the functional impact of cREs harboring disease-associated genetic variants and how chromosomal rearrangements disrupting topologically associating domains can lead to pathogenic gene expression.

| S-EPMC7714423 | biostudies-literature

Analysis of long-range chromatin interactions using Chromosome Conformation Capture.

Project description:Chromosome Conformation Capture, or 3C, is a pioneering method for investigating the three-dimensional structure of chromatin. 3C is used to analyze long-range looping interactions between any pair of selected genomic loci. Most 3C studies focus on defined genomic regions of interest that can be up to several hundred Kb in size. The method has become widely adopted and has been modified to increase throughput to allow unbiased genome-wide analysis. These large-scale adaptations are presented in other articles in this issue of Methods. Here we describe the 3C procedure in detail, including the appropriate use of the technology, the experimental set-up, an optimized protocol and troubleshooting guide, and considerations for data analysis. The protocol described here contains previously unpublished improvements, which save time and reduce labor. We pay special attention to primer design, appropriate controls and data analysis. We include notes and discussion based on our extensive experience to help researchers understand the principles of 3C-based techniques and to avoid common pitfalls and mistakes. This paper represents a complete resource and detailed guide for anyone who desires to perform 3C.

| S-EPMC3874837 | biostudies-literature

Reconstructing the blood metabolome and genotype using long-range chromatin interactions.

Project description:Background-Maintenance of tight controls on circulating blood metabolites is crucial to normal, healthy tissue and organismal function. A number of single nucleotide polymorphisms (SNPs) have been associated with changes in the levels of blood metabolites. However, the impacts of the metabolite-associated SNPs are largely unknown because they fall within non-coding regions of the genome.Objective-We aimed to identify genes and tissues that are linked to changes in circulating blood metabolites by characterizing genome-wide spatial regulatory interactions involving blood metabolite-associated SNPs.Method-We systematically integrated chromatin interaction (Hi-C), expression quantitative trait loci (eQTL), gene ontology, drug interaction, and literature-supported connections to deconvolute the genetic regulatory influences of 145 blood metabolite-associated SNPs.Findings-We identified 577 genes that are regulated by 130 distal and proximal metabolite-associated SNPs across 48 different human tissues. The affected genes are enriched in categories that include metabolism, enzymes, plasma proteins, disease development, and potential drug targets. Our results suggest that regulatory interactions in other tissues contribute to the modulation of blood metabolites.Conclusions-The spatial SNP-gene-metabolite associations identified in this study expand on the list of genes and tissues that are influenced by metabolic-associated SNPs and improves our understanding of the molecular mechanisms underlying pathologic blood metabolite levels.

| S-EPMC7424797 | biostudies-literature

A statistical framework for differential pseudotime analysis with multiple single-cell RNA-seq samples.

Project description:Pseudotime analysis with single-cell RNA-sequencing (scRNA-seq) data has been widely used to study dynamic gene regulatory programs along continuous biological processes. While many computational methods have been developed to infer the pseudo-temporal trajectories of cells within a biological sample, methods that compare pseudo-temporal patterns with multiple samples (or replicates) across different experimental conditions are lacking. Lamian is a comprehensive and statistically-rigorous computational framework for differential multi-sample pseudotime analysis. It can be used to identify changes in a biological process associated with sample covariates, such as different biological conditions, and also to detect changes in gene expression, cell density, and topology of a pseudotemporal trajectory. Unlike existing methods that ignore sample variability, Lamian draws statistical inference after accounting for cross-sample variability and hence substantially reduces sample-specific false discoveries that are not generalizable to new samples. Using both simulations and real scRNA-seq data, including an analysis of differential immune response programs between COVID-19 patients with different disease severity levels, we demonstrate the advantages of Lamian in decoding cellular gene expression programs in continuous biological processes.

| S-EPMC8288148 | biostudies-literature

Histone H3 lysine 4 monomethylation modulates long-range chromatin interactions at enhancers.

Project description:Long-range chromatin interactions between enhancers and promoters are essential for transcription of many developmentally controlled genes in mammals and other metazoans. Currently, the exact mechanisms that connect distal enhancers to their specific target promoters remain to be fully elucidated. Here, we show that the enhancer-specific histone H3 lysine 4 monomethylation (H3K4me1) and the histone methyltransferases MLL3 and MLL4 (MLL3/4) play an active role in this process. We demonstrate that in differentiating mouse embryonic stem cells, MLL3/4-dependent deposition of H3K4me1 at enhancers correlates with increased levels of chromatin interactions, whereas loss of this histone modification leads to reduced levels of chromatin interactions and defects in gene activation during differentiation. H3K4me1 facilitates recruitment of the Cohesin complex, a known regulator of chromatin organization, to chromatin in vitro and in vivo, providing a potential mechanism for MLL3/4 to promote chromatin interactions between enhancers and promoters. Taken together, our results support a role for MLL3/4-dependent H3K4me1 in orchestrating long-range chromatin interactions at enhancers in mammalian cells.

| S-EPMC5799818 | biostudies-literature

Mapping of long-range chromatin interactions by proximity ligation-assisted ChIP-seq.

Project description: Not available

| S-EPMC5143423 | biostudies-literature

Dynamic long-range chromatin interactions control Myb proto-oncogene transcription during erythroid development.

Project description:The key haematopoietic regulator Myb is essential for coordinating proliferation and differentiation. ChIP-Sequencing and Chromosome Conformation Capture (3C)-Sequencing were used to characterize the structural and protein-binding dynamics of the Myb locus during erythroid differentiation. In proliferating cells expressing Myb, enhancers within the Myb-Hbs1l intergenic region were shown to form an active chromatin hub (ACH) containing the Myb promoter and first intron. This first intron was found to harbour the transition site from transcription initiation to elongation, which takes place around a conserved CTCF site. Upon erythroid differentiation, Myb expression is downregulated and the ACH destabilized. We propose a model for Myb activation by distal enhancers dynamically bound by KLF1 and the GATA1/TAL1/LDB1 complex, which primarily function as a transcription elongation element through chromatin looping.

| S-EPMC3280550 | biostudies-literature

A compendium of promoter-centered long-range chromatin interactions in the human genome.

Project description:A large number of putative cis-regulatory sequences have been annotated in the human genome, but the genes they control remain poorly defined. To bridge this gap, we generate maps of long-range chromatin interactions centered on 18,943 well-annotated promoters for protein-coding genes in 27 human cell/tissue types. We use this information to infer the target genes of 70,329 candidate regulatory elements and suggest potential regulatory function for 27,325 noncoding sequence variants associated with 2,117 physiological traits and diseases. Integrative analysis of these promoter-centered interactome maps reveals widespread enhancer-like promoters involved in gene regulation and common molecular pathways underlying distinct groups of human traits and diseases.

| S-EPMC6778519 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data