Stargazer: a software tool for calling star alleles from next-generation sequencing data using CYP2D6 as a model

Area of Science:

• Pharmacogenomics
• Bioinformatics
• Genetics

Background:

• CYP2D6 genotyping is crucial for precision drug therapy due to its role in metabolizing ~25% of drugs and significant inter-individual activity variations.
• The highly polymorphic nature of CYP2D6, with over 100 defined haplotypes (star alleles), including gene conversions with CYP2D7, presents challenges for accurate genotype analysis.

Purpose of the Study:

• To introduce Stargazer, a novel bioinformatics tool designed for accurate CYP2D6 star allele calling from next-generation sequencing (NGS) data.
• To extend Stargazer's utility to other pharmacogenes.

Main Methods:

• Stargazer identifies CYP2D6 star alleles by detecting single nucleotide variants, insertion-deletion variants, and structural variations.
• Structural variations like gene deletions, duplications, and conversions are detected by calculating paralog-specific copy numbers from read depths.

Main Results:

• Stargazer was applied to NGS data from 32 ethnically diverse HapMap trios, showing 99.0% concordance with established genotyping methods.
• Analysis revealed structural variations in 28.1% of samples, including CYP2D6/CYP2D7 hybrid genes.

Conclusions:

• Accurate pharmacogene genotyping using NGS and Stargazer facilitates the implementation of precision drug therapy.
• Stargazer provides a robust method for analyzing complex CYP2D6 variations, improving the foundation for personalized medicine.