MCSeEd

MCSeEd enables comprehensive whole-genome methylation profiling across CG, CHG, CHH and N6-methyladenosine (6 mA) contexts using double-digest restriction-site-associated DNA (ddRAD) reduced-representation sequencing without requiring a reference genome.

Key Features:

• Methylation context profiling: Detects methylation in CG, CHG, CHH and N6-methyladenosine (6 mA) contexts.
• ddRAD reduced-representation: Employs double-digest restriction-site-associated DNA (ddRAD) to capture representative genomic fragments.
• Methylation-sensitive and -insensitive enzymes: Uses parallel digestion with combinations of methylation-sensitive and methylation-insensitive endonucleases to enrich fragments reflecting methylation status.
• Next-generation sequencing: Sequenced fragments are processed using next-generation sequencing technologies.
• Reference-free and reference-based analysis: Supports analyses with or without a reference genome.
• Differential methylation analysis: Includes a bioinformatic pipeline that performs differential methylation analysis.
• SNP calling and genetic variation detection: Performs single nucleotide polymorphism (SNP) calling and detects genetic variation across large sample sets, including hundreds of samples.

Scientific Applications:

• Reference-free methylome profiling: Whole-genome methylation profiling in species lacking a reference genome.
• Epigenetic studies: Comparative analysis of methylation patterns across CG, CHG, CHH and 6 mA contexts.
• Population genetics and variation mapping: Joint detection of genetic variation and methylation differences across populations and large sample cohorts.
• Large-scale comparative methylomics: Cost-effective reduced-representation sequencing for large-scale comparative methylation studies.

Methodology:

The computational pipeline performs differential methylation analysis and single nucleotide polymorphism (SNP) calling and supports reference-free and reference-based analyses.