Using local alignment to enhance single-cell bisulfite sequencing data efficiency.

Area of Science:

• Genomics
• Epigenetics
• Bioinformatics

Background:

• Single-cell bisulfite sequencing (scBS-seq) enables DNA methylation heterogeneity detection, particularly for limited biological samples.
• A critical challenge in scBS-seq is data deficiency, notably a low read mapping ratio.

Purpose of the Study:

• To comprehensively characterize single-cell bisulfite sequencing data and identify sources of alignment failures.
• To develop a computational tool for quality control, local alignment, and removal of problematic sequences in scBS-seq data.

Main Methods:

• Characterization of single-cell BS-seq data to identify chimerical molecules.
• Development of the scBS-map software for quality control, local alignment, chimerical molecule determination, and microhomology region (MR) removal.
• Analysis of DNA methylation variability within MR.

Main Results:

• Chimerical molecules, formed by recombination of proximal sequences at microhomology regions (MR) post-bisulfite conversion, are identified as the primary cause of alignment failures.
• DNA methylation exhibits high variability within MR, necessitating their removal for accurate estimation.
• scBS-map significantly increases uniquely mapped reads, genomic coverage, and the number of identified CpG sites.
• scBS-map facilitates the recovery of more functional genomic elements with precise DNA methylation estimation.

Conclusions:

• Chimerical molecules originating from MR are a major artifact in scBS-seq data.
• The scBS-map tool effectively addresses data deficiency issues in scBS-seq by performing quality control and removing problematic sequences.
• scBS-map enhances the accuracy and reliability of DNA methylation analysis at the single-cell level.