HMCan: A method for detecting chromatin modifications in cancer samples using ChIP-seq data
Bajic, Vladimir B.
KAUST DepartmentComputational Bioscience Research Center (CBRC)
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Computer Science Program
Applied Mathematics and Computational Science Program
Permanent link to this recordhttp://hdl.handle.net/10754/325440
MetadataShow full item record
AbstractMotivation: Cancer cells are often characterized by epigenetic changes, which include aberrant histone modifications. In particular, local or regional epigenetic silencing is a common mechanism in cancer for silencing expression of tumor suppressor genes. Though several tools have been created to enable detection of histone marks in ChIP-seq data from normal samples, it is unclear whether these tools can be efficiently applied to ChIP-seq data generated from cancer samples. Indeed, cancer genomes are often characterized by frequent copy number alterations: gains and losses of large regions of chromosomal material. Copy number alterations may create a substantial statistical bias in the evaluation of histone mark signal enrichment and result in underdetection of the signal in the regions of loss and overdetection of the signal in the regions of gain. Results: We present HMCan (Histone modifications in cancer), a tool specially designed to analyze histone modification ChIP-seq data produced from cancer genomes. HMCan corrects for the GC-content and copy number bias and then applies Hidden Markov Models to detect the signal from the corrected data. On simulated data, HMCan outperformed several commonly used tools developed to analyze histone modification data produced from genomes without copy number alterations. HMCan also showed superior results on a ChIP-seq dataset generated for the repressive histone mark H3K27me3 in a bladder cancer cell line. HMCan predictions matched well with experimental data (qPCR validated regions) and included, for example, the previously detected H3K27me3 mark in the promoter of the DLEC1 gene, missed by other tools we tested. The Author 2013. Published by Oxford University Press. All rights reserved.
CitationAshoor H, Herault A, Kamoun A, Radvanyi F, Bajic VB, et al. (2013) HMCan: a method for detecting chromatin modifications in cancer samples using ChIP-seq data. Bioinformatics 29: 2979-2986. doi:10.1093/bioinformatics/btt524.
PublisherOxford University Press (OUP)
PubMed Central IDPMC3834794
The following license files are associated with this item:
Except where otherwise noted, this item's license is described as This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
- HMCan-diff: a method to detect changes in histone modifications in cells with different genetic characteristics.
- Authors: Ashoor H, Louis-Brennetot C, Janoueix-Lerosey I, Bajic VB, Boeva V
- Issue date: 2017 May 5
- histoneHMM: Differential analysis of histone modifications with broad genomic footprints.
- Authors: Heinig M, Colomé-Tatché M, Taudt A, Rintisch C, Schafer S, Pravenec M, Hubner N, Vingron M, Johannes F
- Issue date: 2015 Feb 22
- Genome-wide localization of protein-DNA binding and histone modification by a Bayesian change-point method with ChIP-seq data.
- Authors: Xing H, Mo Y, Liao W, Zhang MQ
- Issue date: 2012
- Identifying dispersed epigenomic domains from ChIP-Seq data.
- Authors: Song Q, Smith AD
- Issue date: 2011 Mar 15
- Analysis of histone modifications at human ribosomal DNA in liver cancer cell.
- Authors: Yu F, Shen X, Fan L, Yu Z
- Issue date: 2015 Dec 11
Showing items related by title, author, creator and subject.
Large-scale Comparative Study of Hi-C-based Chromatin 3D Structure Modeling MethodsWang, Cheng (2018-05-17) [Thesis]
Advisor: Gao, Xin
Committee members: Hoehndorf, Robert; Fischle, WolfgangChromatin is a complex polymer molecule in eukaryotic cells, primarily consisting of DNA and histones. Many works have shown that the 3D folding of chromatin structure plays an important role in DNA expression. The recently proposed Chro- mosome Conformation Capture technologies, especially the Hi-C assays, provide us an opportunity to study how the 3D structures of the chromatin are organized. Based on the data from Hi-C experiments, many chromatin 3D structure modeling methods have been proposed. However, there is limited ground truth to validate these methods and no robust chromatin structure alignment algorithms to evaluate the performance of these methods. In our work, we first made a thorough literature review of 25 publicly available population Hi-C-based chromatin 3D structure modeling methods. Furthermore, to evaluate and to compare the performance of these methods, we proposed a novel data simulation method, which combined the population Hi-C data and single-cell Hi-C data without ad hoc parameters. Also, we designed a global and a local alignment algorithms to measure the similarity between the templates and the chromatin struc- tures predicted by different modeling methods. Finally, the results from large-scale comparative tests indicated that our alignment algorithms significantly outperform the algorithms in literature.
Live cell CRISPR-imaging in plants reveals dynamic telomere movementsDreissig, Steven; Schiml, Simon; Schindele, Patrick; Weiss, Oda; Rutten, Twan; Schubert, Veit; Gladilin, Evgeny; Mette, Michael F.; Puchta, Holger; Houben, Andreas (The Plant Journal, Wiley, 2017-05-16) [Article]Elucidating the spatio-temporal organization of the genome inside the nucleus is imperative to understand the regulation of genes and non-coding sequences during development and environmental changes. Emerging techniques of chromatin imaging promise to bridge the long-standing gap between sequencing studies which reveal genomic information and imaging studies that provide spatial and temporal information of defined genomic regions. Here, we demonstrate such an imaging technique based on two orthologues of the bacterial CRISPR-Cas9 system. By fusing eGFP/mRuby2 to the catalytically inactive version of Streptococcus pyogenes and Staphylococcus aureus Cas9, we show robust visualization of telomere repeats in live leaf cells of Nicotiana benthamiana. By tracking the dynamics of telomeres visualized by CRISPR-dCas9, we reveal dynamic telomere movements of up to 2 μm within 30 minutes during interphase. Furthermore, we show that CRISPR-dCas9 can be combined with fluorescence-labelled proteins to visualize DNA-protein interactions in vivo. By simultaneously using two dCas9 orthologues, we pave the way for imaging of multiple genomic loci in live plants cells. CRISPR-imaging bears the potential to significantly improve our understanding of the dynamics of chromosomes in live plant cells.
Post-Translational Modification, Phase Separation, and Robust Gene TranscriptionSingh, Hari R.; Ostwal, Yogesh B. (Trends in Genetics, Elsevier BV, 2018-11-23) [Article]A few recent reports reveal fundamental new insights into the intricate regulatory mechanisms that govern RNA polymerase II (Pol II)-mediated gene transcription. Whereas a histidine-rich domain (HRD) triggers phase separation, promoting transcription elongation, a phosphatase switch promotes transcription termination. A paradigm that might govern the underlying mechanisms leading to robust gene transcription is now starting to emerge.