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Related Concept Videos

Duplication of Chromatin Structure02:05

Duplication of Chromatin Structure

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The process of chromosome duplication during cell division requires genome-wide disruption and re-assembly of chromatin. The chromatin structure must be accurately inherited, reassembled, and maintained in the daughter cells to ensure lineage propagation.
The basic unit of the chromatin is the nucleosome, consisting of DNA wrapped around octameric histone proteins and short stretches of linker DNA separating individual nucleosomes. The histone proteins within the nucleosome have their...
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Heterochromatin

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The extent of chromatin compaction can be studied by staining chromatin using specific DNA binding dyes. Under the microscope, the dense-compacted regions that take up more dye are called heterochromatin. Heterochromatin is further classified into two forms – constitutive heterochromatin and facultative heterochromatin.
Constitutive heterochromatin: It is a highly compact region of chromatin that is mostly concentrated in the centromere and telomere. Unlike euchromatin, the amino acid at...
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Euchromatin01:01

Euchromatin

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The extent of chromatin compaction can be studied by staining chromatin using specific DNA binding dyes. Under the microscope, the dense-compacted regions take up more dye, appearing darker, while the less-compact areas take up less dye and appear lighter. Based on the compaction level, chromatins are classified into two primary forms – euchromatin and heterochromatin.
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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.
Acetylation
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Chromatin Packaging

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Each human somatic cell contains 6 billion base-pairs of DNA. Each base-pair is 0.34 nm long, which means that each diploid cell contains a staggering 2 meters of DNA. How is such a long DNA strand packed inside a nucleus measuring only 10 - 20 microns in diameter? 
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Chromatin Immunoprecipitation- ChIP02:36

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Chromatin immunoprecipitation, or ChIP, is an antibody-based technique used to identify sites on DNA that bind to transcription factors of interest or histone proteins. It also helps determine the type of histone modifications such as acetylation, phosphorylation, or methylation.
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Related Experiment Video

Updated: Aug 19, 2025

Hi-C: A Method to Study the Three-dimensional Architecture of Genomes.
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GILoop: Robust chromatin loop calling across multiple sequencing depths on Hi-C data.

Fuzhou Wang1, Tingxiao Gao2, Jiecong Lin3

  • 1Department of Computer Science, City University of Hong Kong, Kowloon Tong, Hong Kong SAR, China.

Iscience
|November 29, 2022
PubMed
Summary

GILoop, a novel dual-branch neural network, integrates graph and image views of Hi-C data to identify CTCF-mediated loops. This approach enhances loop calling accuracy and robustness, outperforming existing methods.

Keywords:
Computational bioinformaticsGenomic analysisNeural networks

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Area of Science:

  • Genomics
  • Computational Biology
  • Bioinformatics

Background:

  • Hi-C contact maps are commonly represented as graphs or images.
  • Current computational tools analyze Hi-C data using single data structures, overlooking synergistic potential.
  • Identifying CTCF-mediated loops is crucial for understanding genome organization.

Purpose of the Study:

  • To develop a novel computational framework, GILoop, for identifying genome-wide CTCF-mediated loops.
  • To leverage the complementary information from both graph and image representations of Hi-C data.
  • To improve the accuracy and robustness of loop calling compared to existing methods.

Main Methods:

  • Proposed GILoop, a dual-branch neural network architecture.
  • Trained GILoop on both graph and image representations of Hi-C data.
  • Evaluated GILoop's performance against state-of-the-art loop calling tools.

Main Results:

  • GILoop demonstrated superior performance in identifying CTCF-mediated loops.
  • The model showed increased robustness against low-quality Hi-C libraries.
  • Distinct preferences for matrix density were observed between graph-based and image-based models.
  • Transfer-learning studies confirmed GILoop's ability to model CTCF looping patterns across cell lines.

Conclusions:

  • Integrating graph and image views of Hi-C data offers significant advantages for loop identification.
  • GILoop provides a more accurate and robust method for detecting CTCF-mediated loops.
  • The study offers insights into Hi-C data interpretation and highlights the complementary nature of different data representations.