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Methylated DNA Immunoprecipitation
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Analyzing DNA Methylation Patterns During Tumor Evolution
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 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.
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.
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