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Related Concept Videos

Histone Modification02:32

Histone Modification

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The histone proteins have a flexible N-terminal tail extending out from the nucleosome. These histone tails are often subjected to post-translational modifications such as acetylation, methylation, phosphorylation, and ubiquitination. Particular combinations of these modifications form “histone codes” that influence the chromatin folding and tissue-specific gene expression.
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The histone proteins in the nucleosomes are post-translationally modified (PTM) to increase or decrease access to DNA. The commonly observed PTMs are methylation, acetylation, phosphorylation, and ubiquitination of lysine amino acids in the histone H3 tail region. These histone modifications have specific meaning for the cell. Hence, they are called "histone code". The protein complex involved in histone modification is termed as "reader-writer" complex.
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In 1928, a German botanist Emil Heitz observed the moss nuclei with a DNA binding dye. He observed that while some chromatin regions decondense and spread out in the interphase nucleus, others do not. He termed them euchromatin and heterochromatin, respectively. He proposed that the heterochromatin regions reflect a functionally inactive state of the genome. It was later confirmed that heterochromatin is transcriptionally repressed, and euchromatin is transcriptionally active chromatin.
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Epigenetic mechanisms play an essential role in healthy development. Conversely, precisely regulated epigenetic mechanisms are disrupted in diseases like cancer.
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Epigenetic changes alter the physical structure of the DNA without changing the genetic sequence and often regulate whether genes are turned on or off. This regulation ensures that each cell produces only proteins necessary for its function. For example, proteins that promote bone growth are not produced in muscle cells. Epigenetic mechanisms play an essential role in healthy development. Conversely, precisely regulated epigenetic mechanisms are disrupted in diseases like cancer.
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An Integrated Platform for Genome-wide Mapping of Chromatin States Using High-throughput ChIP-sequencing in Tumor Tissues
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RoboCOP: Multivariate State Space Model Integrating Epigenomic Accessibility Data to Elucidate Genome-Wide Chromatin

Sneha Mitra1, Jianling Zhong2, David M MacAlpine2,3,4

  • 1Department of Computer Science, Duke University, Durham, NC 27708, USA.

Research in Computational Molecular Biology : ... Annual International Conference, RECOMB ... : Proceedings. RECOMB (Conference : 2005- )
|August 13, 2021
PubMed
Summary

Researchers developed RoboCOP, a novel computational model that integrates epigenomic data and DNA sequence to predict transcription factor (TF) and nucleosome binding sites across the genome. This method accurately identifies hundreds of protein occupancy patterns simultaneously.

Keywords:
Chromatin accessibilityHidden Markov modelMNase-seq

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Area of Science:

  • Molecular Biology
  • Genomics
  • Computational Biology

Background:

  • Chromatin structure, composed of DNA and proteins, regulates gene expression.
  • Understanding transcription factor (TF) and nucleosome binding is key to gene regulation.
  • Current methods for assaying chromatin occupancy are limited in scope or factor identification.

Purpose of the Study:

  • To present RoboCOP, a multivariate state space model for predicting genome-wide TF and nucleosome occupancy.
  • To integrate epigenomic accessibility data with nucleotide sequence information.
  • To enable simultaneous prediction of hundreds of protein binding factors.

Main Methods:

  • Developed RoboCOP, a multivariate state space model.
  • Integrated quantitative chromatin accessibility data (e.g., MNase-seq) with nucleotide sequence.
  • Applied the model to yeast (Saccharomyces cerevisiae) genome data.

Main Results:

  • RoboCOP computes genome-wide probabilistic scores for nucleosome and TF occupancy.
  • The model was applied to MNase-seq data to analyze nucleosomes and 150 TFs in yeast.
  • RoboCOP demonstrated higher accuracy in predicting TF binding compared to existing methods, using literature data.

Conclusions:

  • RoboCOP offers a powerful approach to deciphering the protein-binding landscape of chromatin.
  • The model can be applied to various epigenomic datasets and organisms.
  • Accurate prediction of TF and nucleosome occupancy advances the understanding of gene regulation.