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Related Concept Videos

The Evidence for Evolution

The Evidence for Evolution

Genetic variations accumulating within populations over generations give rise to biological evolution. Evolutionary changes can result in the formation of novel varieties and entire new species. These changes are responsible for the diverse forms of life inhabiting the planet. The evidence for evolution suggests that all living organisms descended from common ancestors.

Convergent Evolution

Convergent Evolution

Evolution shapes the features of organisms over time, ensuring that they are suited for the environments in which they live. Sometimes, selection pressure leads to the rise of similar but unrelated adaptations in organisms with no recent common ancestors, a process known as convergent evolution.

Eukaryotic Evolution

Eukaryotic Evolution

The endosymbiont theory is the most widely accepted theory of eukaryotic evolution; however, its progression is still somewhat debated. According to the nucleus-first hypothesis, the ancestral prokaryote first evolved a membrane to enclose DNA and form the nucleus. Conversely, the mitochondria-first hypothesis suggests that the nucleus was formed after endosymbiosis of mitochondria.
Contrary to the endosymbiont theory, the eukaryote-first hypothesis proposes that the simpler prokaryotic and...

Synteny and Evolution

Synteny and Evolution

John H. Renwick first coined the term “synteny” in 1971, which refers to the genes present on the same chromosomes, even if they are not genetically linked. The species with common ancestry tend to show conserved syntenic regions. Therefore, the concept of synteny is nowadays used to describe the evolutionary relationship between species.
Around 80 million years ago, the human and mice lineages diverged from the common ancestor. During the course of evolution, the ancestral...

Genome Size and the Evolution of New Genes

Genome Size and the Evolution of New Genes

While every living organism has a genome of some kind (be it RNA, or DNA), there is considerable variation in the sizes of these blueprints. One major factor that impacts genome size is whether the organism is prokaryotic or eukaryotic. In prokaryotes, the genome contains little to no non-coding sequence, such that genes are tightly clustered in groups or operons sequentially along the chromosome. Conversely, the genes in eukaryotes are punctuated by long stretches of non-coding sequence.

Genome Size and the Evolution of New Genes

Genome Size and the Evolution of New Genes

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Related Experiment Video

Updated: Feb 15, 2026

Methylated DNA Immunoprecipitation

Methylated DNA Immunoprecipitation

Published on: January 2, 2009

Analyzing DNA Methylation Patterns During Tumor Evolution.

Heng Pan¹, Olivier Elemento²

¹Department of Physiology and Biophysics, Institute for Precision Medicine, Institute for Computational Biomedicine, Weill Cornell Medical College, 1305 York Avenue, New York, NY, 10021, USA.

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

|January 19, 2018

Summary

This summary is machine-generated.

This study presents a computational pipeline for analyzing DNA methylation patterns during tumor evolution. It enables detailed examination of epigenomic alterations, including intra-tumor heterogeneity, using bisulfite sequencing data.

Keywords:

DMRs DNA methylation ERRBS Intra-tumor methylation heterogeneity

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DNA Methylation: Bisulphite Modification and Analysis

DNA Methylation: Bisulphite Modification and Analysis

Published on: October 21, 2011

Methyl-binding DNA capture Sequencing for Patient Tissues

Methyl-binding DNA capture Sequencing for Patient Tissues

Published on: October 31, 2016

Related Experiment Videos

Last Updated: Feb 15, 2026

Methylated DNA Immunoprecipitation

Methylated DNA Immunoprecipitation

Published on: January 2, 2009

DNA Methylation: Bisulphite Modification and Analysis

DNA Methylation: Bisulphite Modification and Analysis

Published on: October 21, 2011

Methyl-binding DNA capture Sequencing for Patient Tissues

Methyl-binding DNA capture Sequencing for Patient Tissues

Published on: October 31, 2016

Area of Science:

Genomics
Epigenetics
Cancer Research

Background:

Epigenetic modifications are crucial in cell development and cancer.
Mutations in epigenetic regulators and altered epigenomic patterns are common in tumors.
DNA methylation is a key epigenetic mark, with aberrant patterns linked to gene expression and cancer.

Purpose of the Study:

To develop a comprehensive computational methodology for analyzing DNA methylation patterns.
To enable systematic analysis of epigenomic alterations during tumor evolution.
To investigate intra-tumor DNA methylation heterogeneity using bisulfite sequencing data.

Main Methods:

Utilizing open-source tools for data analysis.
Applying high-throughput bisulfite converted sequencing for base-pair resolution.
Developing a computational pipeline for whole-genome DNA methylation analysis.

Main Results:

A comprehensive computational methodology for DNA methylation analysis is described.
The pipeline facilitates the study of DNA methylation patterns during tumor evolution.
Intra-tumor DNA methylation heterogeneity can be analyzed.

Conclusions:

The developed methodology provides a robust framework for analyzing epigenomic alterations in cancer.
This approach aids in understanding the role of DNA methylation in tumor progression.
The open-source pipeline enhances accessibility for systematic epigenomic studies in cancer research.