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Heterochromatin

Heterochromatin

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...

Chromatin Immunoprecipitation- ChIP

Chromatin Immunoprecipitation- ChIP

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.
Types of ChIP
ChIP can be divided into two types - X-ChIP and N-ChIP. X-ChIP involves in vivo cross-linking of histones and regulatory proteins to DNA, fragmenting the DNA by sonication, and isolating the protein-DNA...

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Related Experiment Video

Updated: Nov 28, 2025

Mapping Genome-wide Accessible Chromatin in Primary Human T Lymphocytes by ATAC-Seq

Mapping Genome-wide Accessible Chromatin in Primary Human T Lymphocytes by ATAC-Seq

Published on: November 13, 2017

Systematic clustering algorithm for chromatin accessibility data and its application to hematopoietic cells.

Azusa Tanaka^1,2, Yasuhiro Ishitsuka^3,4, Hiroki Ohta^3,5

¹Department of Human Genetics, Graduate School of Medicine, The University of Tokyo, Tokyo, Japan.

Plos Computational Biology

|November 30, 2020

Summary

This summary is machine-generated.

High-throughput sequencing generates vast data. A new clustering algorithm reduces this data by treating genomes as binary strings, enabling effective cell type classification and a deeper understanding of leukemia.

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Last Updated: Nov 28, 2025

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Author Spotlight: An Integrated Workflow to Study the Promoter-Centric Spatio-Temporal Genome Architecture in Scarce Cell Populations

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An Integrated Platform for Genome-wide Mapping of Chromatin States Using High-throughput ChIP-sequencing in Tumor Tissues

An Integrated Platform for Genome-wide Mapping of Chromatin States Using High-throughput ChIP-sequencing in Tumor Tissues

Published on: April 5, 2018

Area of Science:

Genomics
Bioinformatics
Computational Biology

Background:

High-throughput sequencing technologies generate massive datasets, necessitating efficient data reduction strategies for comprehensive analysis.
Analyzing genome-wide open chromatin data is crucial for understanding cellular function and disease pathogenesis.

Purpose of the Study:

To introduce a novel data reduction method and clustering algorithm for genome-wide open chromatin data.
To enable quantitative evaluation of differences between hematopoietic cell samples.
To facilitate cell type classification for improved leukemia pathogenesis research.

Main Methods:

A new data reduction technique representing the genome as binary strings (1s and 0s) based on peak sets.
Calculation of Hamming distances between these genomic strings.
Development of a clustering algorithm utilizing an optimized set of peaks.

Main Results:

The proposed algorithm effectively reduces large-scale genomic data.
Quantitative differences between hematopoietic cell samples were successfully evaluated.
Accurate classification of cell types was achieved using the clustering algorithm.

Conclusions:

The developed clustering algorithm and data reduction method offer a powerful approach for analyzing high-throughput sequencing data.
This method has the potential to advance our understanding of cell type heterogeneity and leukemia pathogenesis.