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Updated: Jun 4, 2025

Targeted DNA Methylation Analysis by Next-generation Sequencing
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Atlas-scale single-cell DNA methylation profiling with sciMETv3.

Ruth V Nichols1, Lauren E Rylaarsdam1, Brendan L O'Connell2

  • 1Department of Molecular & Medical Genetics, Oregon Health & Science University, Portland, OR, USA.

Cell Genomics
|December 25, 2024
PubMed
Summary
This summary is machine-generated.

sciMETv3 is a new single-cell DNA methylation method that dramatically increases throughput, enabling large-scale atlases. This technique integrates with capture methods and enzymatic conversion for enhanced data and introduces sciMET+ATAC for combined epigenomic analysis.

Keywords:
DNA methylationepigeneticsneurosciencesingle cell

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Area of Science:

  • Epigenetics and Genomics
  • Single-cell Biology
  • Computational Biology

Background:

  • Current single-cell DNA methylation assays face limitations in cell throughput, hindering the creation of large-scale datasets.
  • Existing methods often require significant automation, time, and resources, posing a barrier to comprehensive epigenomic studies.

Purpose of the Study:

  • To introduce sciMETv3, a novel combinatorial indexing-based technique for high-throughput single-cell DNA methylation analysis.
  • To demonstrate the scalability and efficiency of sciMETv3 for generating atlas-scale single-cell epigenomic libraries.
  • To present sciMET+ATAC, a method for simultaneously profiling DNA methylation and chromatin accessibility at single-cell resolution.

Main Methods:

  • Development and application of sciMETv3, a combinatorial indexing technique for single-cell DNA methylation profiling.
  • Integration of capture techniques to enrich for regulatory regions, reducing sequencing burden.
  • Utilization of enzymatic conversion to enhance library diversity and data quality.
  • Development of sciMET+ATAC for simultaneous measurement of DNA methylation and chromatin accessibility.

Main Results:

  • Successfully generated a single-cell DNA methylation library from over 140,000 cells from human middle frontal gyrus across four multiplexed individuals.
  • Demonstrated compatibility of sciMETv3 with both Illumina and Ultima sequencing platforms.
  • Showcased the ability to combine DNA methylation with chromatin accessibility profiling using sciMET+ATAC.

Conclusions:

  • sciMETv3 significantly advances high-throughput single-cell DNA methylation analysis, enabling the creation of large-scale epigenomic atlases.
  • The integration of capture techniques and enzymatic conversion optimizes library preparation and sequencing efficiency.
  • sciMET+ATAC provides a powerful tool for dissecting the interplay between DNA methylation and chromatin accessibility in single cells.