Literature DB >> 25965262

Hi-C Chromatin Interaction Networks Predict Co-expression in the Mouse Cortex.

Sepideh Babaei1, Ahmed Mahfouz2, Marc Hulsman3, Boudewijn P F Lelieveldt4, Jeroen de Ridder1, Marcel Reinders1.   

Abstract

The three dimensional conformation of the genome in the cell nucleus influences important biological processes such as gene expression regulation. Recent studies have shown a strong correlation between chromatin interactions and gene co-expression. However, predicting gene co-expression from frequent long-range chromatin interactions remains challenging. We address this by characterizing the topology of the cortical chromatin interaction network using scale-aware topological measures. We demonstrate that based on these characterizations it is possible to accurately predict spatial co-expression between genes in the mouse cortex. Consistent with previous findings, we find that the chromatin interaction profile of a gene-pair is a good predictor of their spatial co-expression. However, the accuracy of the prediction can be substantially improved when chromatin interactions are described using scale-aware topological measures of the multi-resolution chromatin interaction network. We conclude that, for co-expression prediction, it is necessary to take into account different levels of chromatin interactions ranging from direct interaction between genes (i.e. small-scale) to chromatin compartment interactions (i.e. large-scale).

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Year:  2015        PMID: 25965262      PMCID: PMC4429121          DOI: 10.1371/journal.pcbi.1004221

Source DB:  PubMed          Journal:  PLoS Comput Biol        ISSN: 1553-734X            Impact factor:   4.475


  40 in total

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Journal:  Nature       Date:  2012-09-06       Impact factor: 49.962

6.  Integration of Hi-C and ChIP-seq data reveals distinct types of chromatin linkages.

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9.  A high-resolution map of the three-dimensional chromatin interactome in human cells.

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10.  Large-scale functional organization of long-range chromatin interaction networks.

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  14 in total

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2.  Big data challenges in genome informatics.

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3.  Integrating epigenomic data and 3D genomic structure with a new measure of chromatin assortativity.

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4.  The Genome Conformation As an Integrator of Multi-Omic Data: The Example of Damage Spreading in Cancer.

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5.  ChiCMaxima: a robust and simple pipeline for detection and visualization of chromatin looping in Capture Hi-C.

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6.  A subset of topologically associating domains fold into mesoscale core-periphery networks.

Authors:  Harvey Huang; Sunnia T Chen; Katelyn R Titus; Daniel J Emerson; Danielle S Bassett; Jennifer E Phillips-Cremins
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7.  Reorganization of 3D genome structure may contribute to gene regulatory evolution in primates.

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8.  QuIN: A Web Server for Querying and Visualizing Chromatin Interaction Networks.

Authors:  Asa Thibodeau; Eladio J Márquez; Oscar Luo; Yijun Ruan; Francesca Menghi; Dong-Guk Shin; Michael L Stitzel; Paola Vera-Licona; Duygu Ucar
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9.  Analysis of the relationship between coexpression domains and chromatin 3D organization.

Authors:  María E Soler-Oliva; José A Guerrero-Martínez; Valentina Bachetti; José C Reyes
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10.  Galaxy HiCExplorer: a web server for reproducible Hi-C data analysis, quality control and visualization.

Authors:  Joachim Wolff; Vivek Bhardwaj; Stephan Nothjunge; Gautier Richard; Gina Renschler; Ralf Gilsbach; Thomas Manke; Rolf Backofen; Fidel Ramírez; Björn A Grüning
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