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Applications Of NMR In Biology01:25

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Related Experiment Video

Updated: Feb 11, 2026

Methylated DNA Immunoprecipitation
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Single-Cell DNA Methylation Profiling: Technologies and Biological Applications.

Ino D Karemaker1, Michiel Vermeulen1

  • 1Department of Molecular Biology, Faculty of Science, Radboud Institute for Molecular Life Sciences, Oncode Institute, Radboud University Nijmegen, Nijmegen, The Netherlands.

Trends in Biotechnology
|May 5, 2018
PubMed
Summary

Single-cell DNA methylation profiling advances gene expression understanding. New low-input methods enable studying epigenetic modifications in individual cells for biological and clinical insights.

Keywords:
DNA methylationepigeneticsgene expressionsingle-cell technologies

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Area of Science:

  • Epigenetics
  • Molecular Biology
  • Genomics

Background:

  • DNA methylation is a key epigenetic mechanism regulating gene expression, development, and disease.
  • Technological advancements now allow studying DNA methylation at the single-cell level.
  • Understanding DNA methylation heterogeneity is crucial for biological and clinical research.

Purpose of the Study:

  • To review methods for single-cell DNA methylation profiling.
  • To discuss the biological applications of these techniques.
  • To highlight how single-cell approaches advance the understanding of DNA methylation biology.

Main Methods:

  • Review of current single-cell DNA methylation profiling technologies.
  • Analysis of low-input methodologies.
  • Integration of single-cell DNA methylation data with other single-cell omics.

Main Results:

  • Development of innovative methods for single-cell DNA methylation analysis.
  • Enabling the study of epigenetic modifications in heterogeneous cell populations and rare cell types.
  • Facilitating clinical applications through low-input profiling.

Conclusions:

  • Single-cell DNA methylation profiling is a rapidly advancing field.
  • These methods provide unprecedented insights into gene regulation and cellular heterogeneity.
  • Future integration with other single-cell data will deepen our understanding of complex biological systems.