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Evolutionary Relationships through Genome Comparisons

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Genome comparison is one of the excellent ways to interpret the evolutionary relationships between organisms. The basic principle of genome comparison is that if two species share a common feature, it is likely encoded by the DNA sequence conserved between both species. The advent of genome sequencing technologies in the late 20th century enabled scientists to understand the concept of conservation of domains between species and helped them to deduce evolutionary relationships across diverse...

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Related Experiment Video

Updated: Jun 13, 2025

High-throughput Identification of Gene Regulatory Sequences Using Next-generation Sequencing of Circular Chromosome Conformation Capture 4C-seq

High-throughput Identification of Gene Regulatory Sequences Using Next-generation Sequencing of Circular Chromosome Conformation Capture 4C-seq

Published on: October 5, 2018

4D Genome Analysis Using PHi-C2.

Soya Shinkai¹, Shuichi Onami²

¹Laboratory for Developmental Dynamics, RIKEN Center for Biosystems Dynamics Research (BDR), Hyogo, Kobe, Japan. soya.shinkai@riken.jp.

Methods in Molecular Biology (Clifton, N.J.)

|September 16, 2024

Summary

This summary is machine-generated.

PHi-C2 software bridges the gap between static 3D genome structures and dynamic chromatin behavior. It transforms Hi-C data into polymer models for 4D genome analysis, revealing chromatin dynamics.

Keywords:

3D genome 4D genome Hi-C Polymer modeling

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Last Updated: Jun 13, 2025

High-throughput Identification of Gene Regulatory Sequences Using Next-generation Sequencing of Circular Chromosome Conformation Capture 4C-seq

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Generation of Genome-wide Chromatin Conformation Capture Libraries from Tightly Staged Early Drosophila Embryos

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Published on: October 3, 2018

Area of Science:

Genomics
Computational Biology
Biophysics

Background:

Hi-C techniques map genome 3D architecture but do not capture dynamic chromatin behavior.
Understanding chromatin dynamics is crucial for gene regulation and cellular function.

Purpose of the Study:

To introduce PHi-C2, a Python software tool for analyzing 4D genome dynamics.
To enable the transformation of Hi-C data into dynamic polymer models for advanced analysis.

Main Methods:

PHi-C2 utilizes an optimization algorithm to convert Hi-C contact data into polymer models.
The software facilitates the calculation of 3D genome conformations.
PHi-C2 enables dynamic simulations of chromatin behavior.

Main Results:

The software provides insights into chromatin dynamics through simulations.
Key dynamic properties such as mean-squared displacement and rheological properties can be calculated.
PHi-C2 allows for comprehensive 4D genome analysis.

Conclusions:

PHi-C2 enhances the analysis of Hi-C data by incorporating dynamic simulations.
The tool offers a novel approach to studying chromatin behavior in four dimensions.
PHi-C2 serves as a valuable resource for researchers investigating genome dynamics.