Methylation pipeline to accurately detect CpG methylation status.

e15120 Background: DNA methylation is a key epigenetic modification, and aberrant methylation patterns are strongly associated with carcinogenesis. Altered methylation can drive dysregulated gene expression programs involved in tumor development and progression, making methylation profiles valuable for cancer research. However, traditional methylation profiling approaches, such as whole-genome bisulfite sequencing and array-based methods, can be limited by cost, turnaround time, and DNA input requirements. Targeted next-generation sequencing (NGS) workflows provide flexible, rapid, and low-input alternatives for focused methylation analysis. Here, we describe an enhanced AmpliSeq-based primer design pipeline for targeted bisulfite sequencing to enable multiplexed methylation profiling of epigenetic regions of interest. Methods: The AmpliSeq methylation primer design pipeline was enhanced through full automation of the design workflow and expanded support for custom reference genomes from different organisms (or assembly versions). The pipeline was used to design custom Ion AmpliSeq methylation panels targeting cancer-related targets. Panels were designed and tested using human formalin-fixed, paraffin-embedded (FFPE) DNA or circulating cell-free DNA (cfDNA) with standard AmpliSeq protocols. Designs were also generated for non-human genomes, including viral vectors. Panel performance was evaluated using commercial fully methylated (~100%), fully unmethylated (~0%), and mixed (~50%) reference genomic DNA controls. Library preparation, templating, sequencing, and analysis were performed using standard workflows, with optimizations for the Genexus sequencing platform. Results: The enhanced pipeline enabled efficient panel design with high in silico coverage and consistent wet-lab performance. To date, more than 65 custom methylation panel designs have been generated, primarily targeting human cancer-related targets, with in silico coverage typically exceeding 90%. Data from internally evaluated panels, including the Ion AmpliSeq Methylation Panel for Cancer Research, and feedback from external testing demonstrated sufficient read depth and mapping efficiency, with high concordance of methylation measurements across technical replicates. Control samples confirmed robust performance across a broad dynamic range of methylation states. Conclusions: The improved automated primer design pipeline enables flexible, multiplexed targeted methylation panel design compatible with Ion AmpliSeq technology, supporting reproducible methylation analysis from low DNA input samples for research applications.