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Extensive promoter-centered chromatin interactions provide a topological basis for transcription regulation.

ABSTRACT: Higher-order chromosomal organization for transcription regulation is poorly understood in eukaryotes. Using genome-wide Chromatin Interaction Analysis with Paired-End-Tag sequencing (ChIA-PET), we mapped long-range chromatin interactions associated with RNA polymerase II in human cells and uncovered widespread promoter-centered intragenic, extragenic, and intergenic interactions. These interactions further aggregated into higher-order clusters, wherein proximal and distal genes were engaged through promoter-promoter interactions. Most genes with promoter-promoter interactions were active and transcribed cooperatively, and some interacting promoters could influence each other implying combinatorial complexity of transcriptional controls. Comparative analyses of different cell lines showed that cell-specific chromatin interactions could provide structural frameworks for cell-specific transcription, and suggested significant enrichment of enhancer-promoter interactions for cell-specific functions. Furthermore, genetically-identified disease-associated noncoding elements were found to be spatially engaged with corresponding genes through long-range interactions. Overall, our study provides insights into transcription regulation by three-dimensional chromatin interactions for both housekeeping and cell-specific genes in human cells.

SUBMITTER: Li G

PROVIDER: S-EPMC3339270 | biostudies-literature | 2012 Jan

REPOSITORIES: biostudies-literature

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Extensive promoter-centered chromatin interactions provide a topological basis for transcription regulation.

Li Guoliang G Ruan Xiaoan X Auerbach Raymond K RK Sandhu Kuljeet Singh KS Zheng Meizhen M Wang Ping P Poh Huay Mei HM Goh Yufen Y Lim Joanne J Zhang Jingyao J Sim Hui Shan HS Peh Su Qin SQ Mulawadi Fabianus Hendriyan FH Ong Chin Thing CT Orlov Yuriy L YL Hong Shuzhen S Zhang Zhizhuo Z Landt Steve S Raha Debasish D Euskirchen Ghia G Wei Chia-Lin CL Ge Weihong W Wang Huaien H Davis Carrie C Fisher-Aylor Katherine I KI Mortazavi Ali A Gerstein Mark M Gingeras Thomas T Wold Barbara B Sun Yi Y Fullwood Melissa J MJ Cheung Edwin E Liu Edison E Sung Wing-Kin WK Snyder Michael M Ruan Yijun Y

Cell 20120101 1-2

Higher-order chromosomal organization for transcription regulation is poorly understood in eukaryotes. Using genome-wide Chromatin Interaction Analysis with Paired-End-Tag sequencing (ChIA-PET), we mapped long-range chromatin interactions associated with RNA polymerase II in human cells and uncovered widespread promoter-centered intragenic, extragenic, and intergenic interactions. These interactions further aggregated into higher-order clusters, wherein proximal and distal genes were engaged thr ...[more]

PMID: 22265404

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Project description:Higher-order chromosomal organization for transcription regulation is poorly understood in eukaryotes. Using genome-wide Chromatin Interaction Analysis with Paired-End-Tag sequencing (ChIA-PET), we mapped long-range chromatin interactions associated with RNA polymerase II in human cells and uncovered widespread promoter-centered intragenic, extragenic, and intergenic interactions. These interactions further aggregated into higher-order clusters, wherein proximal and distal genes were engaged through promoter-promoter interactions. Most genes with promoter-promoter interactions were active and transcribed cooperatively, and some interacting promoters could influence each other implying combinatorial complexity of transcriptional controls. Comparative analyses of different cell lines showed that cell-specific chromatin interactions could provide structural frameworks for cell-specific transcription, and suggested significant enrichment of enhancer-promoter interactions for cell-specific functions. Furthermore, genetically-identified disease-associated noncoding elements were found to be spatially engaged with corresponding genes through long-range interactions. Overall, our study provides insights into transcription regulation by three-dimensional chromatin interactions for both housekeeping and cell-specific genes in human cells. RNA polymerase II (RNAPII) bound chromatin interactions were extracted with Chromatin Interaction Analysis with Paired-End Tag (ChIA-PET) sequencing, in order to study the transcription regulations with RNAPII-associated long-range chromatin interactions. Five cell lines, namely MCF7 (ATCC# HTB-22), K562 (ATCC# CCL-243), HCT116 (ATCC# CCL-247), HeLa (ATCC# CCL-2.2), and NB4 (Roussel and Lanotte, 2001) (provided by Dr. Sherman Weissman, Yale University), were grown under standard culture conditions and harvested at log phase. Harvested cells were cross-linked using 1% formaldehyde followed by neutralization with 0.2M glycine. Chromatin was isolated and subjected to ChIA-PET protocol as described in Fullwood et al (Fullwood et al: An oestrogen-receptor-alpha-bound human chromatin interactome. Nature 2009, 462(7269):58-64). The ChIA-PET sequence reads were processed and analyzed using ChIA-PET Tool (Li et al: ChIA-PET tool for comprehensive chromatin interaction analysis with paired-end tag sequencing. Genome Biol 2010, 11(2):R22).

Project description:MotivationPromoter-centered chromatin interactions, which include promoter-enhancer (PE) and promoter-promoter (PP) interactions, are important to decipher gene regulation and disease mechanisms. The development of next-generation sequencing technologies such as promoter capture Hi-C (pcHi-C) leads to the discovery of promoter-centered chromatin interactions. However, pcHi-C experiments are expensive and thus may be unavailable for tissues/cell types of interest. In addition, these experiments may be underpowered due to insufficient sequencing depth or various artifacts, which results in a limited finding of interactions. Most existing computational methods for predicting chromatin interactions are based on in situ Hi-C and can detect chromatin interactions across the entire genome. However, they may not be optimal for predicting promoter-centered chromatin interactions.ResultsWe develop a supervised multi-modal deep learning model, which utilizes a comprehensive set of features such as genomic sequence, epigenetic signal, anchor distance, evolutionary features and DNA structural features to predict tissue/cell type-specific PE and PP interactions. We further extend the deep learning model in a multi-task learning and a transfer learning framework and demonstrate that the proposed approach outperforms state-of-the-art deep learning methods. Moreover, the proposed approach can achieve comparable prediction performance using predefined biologically relevant tissues/cell types compared to using all tissues/cell types in the pretraining especially for predicting PE interactions. The prediction performance can be further improved by using computationally inferred biologically relevant tissues/cell types in the pretraining, which are defined based on the common genes in the proximity of two anchors in the chromatin interactions.Availability and implementationhttps://github.com/lichen-lab/DeepPHiC.Supplementary informationSupplementary data are available at Bioinformatics online.

Dataset Information

Extensive promoter-centered chromatin interactions provide a topological basis for transcription regulation.

Publications

Extensive promoter-centered chromatin interactions provide a topological basis for transcription regulation.

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