A data-adaptive methods in detecting exogenous methyltransferase accessible chromatin in human genome using nanopore...

Area of Science:

• Genomics
• Epigenetics
• Molecular Biology

Background:

• Identifying chromatin accessibility is crucial for understanding eukaryotic genome regulation.
• Nanopore sequencing with methyltransferases offers single-molecule, long-range chromatin accessibility detection.
• Existing methods face challenges with endogenous methylation, non-specific methylation, and base-calling errors.

Purpose of the Study:

• To develop a computational method for accurate chromatin accessibility identification.
• To address limitations of current sequencing-based approaches in complex genomes.
• To improve the detection of open chromatin regions, including those in repetitive elements.

Main Methods:

• Systematic evaluation of factors affecting methyltransferase and nanopore sequencing accuracy.
• Development of a model-based computational method named MAGNIFIER.
• Incorporation of control data and a data-adaptive comparison strategy.
• Integration with long-read RNA sequencing data.

Main Results:

• MAGNIFIER significantly improves the accuracy of open chromatin identification.
• The method effectively mitigates the impact of endogenous methylation, non-specific methylation, and base-calling errors.
• MAGNIFIER successfully detects chromatin accessibility in repetitive genomic regions, often missed by next-generation sequencing (NGS) methods.
• Association between accessible Alu elements and non-classic gene isoforms was revealed using long-read RNA-seq.

Conclusions:

• MAGNIFIER provides a robust and accurate computational solution for chromatin accessibility profiling.
• The method enhances the application of nanopore sequencing for complex genome analysis.
• MAGNIFIER facilitates the discovery of regulatory elements in previously inaccessible genomic regions.