Histoimmunogenetics Markup Language 1.0: Reporting next generation sequencing-based HLA and KIR genotyping

Area of Science:

• Immunogenomics
• Bioinformatics
• Computational Biology

Background:

• Accurate Human Leukocyte Antigen (HLA) and Killer Cell Immunoglobulin-like Receptor (KIR) genotyping is crucial for transplantation and disease research.
• Existing data exchange formats lack comprehensive support for next-generation sequencing (NGS) data and nuanced genotype representation.

Purpose of the Study:

• To present an enhanced electronic data exchange format for HLA and KIR genotyping.
• To ensure compatibility with next-generation sequencing (NGS) technologies and the Minimum Information for Reporting Immunogenomic NGS Genotyping (MIRING) guidelines.
• To accurately represent genotype ambiguity and integrate legacy genotyping methods.

Main Methods:

• Refinement of the Histoimmunogenetics Markup Language (HML) to incorporate new XML structures for NGS data and metadata.
• Integration of Genotype List Strings to precisely define allele and genotype ambiguity.
• Inclusion of support for legacy methods (e.g., Sequence Based Typing - SBT) and combined-method approaches.

Main Results:

• The enhanced HML format captures essential NGS data, including analysis-dependent and method-dependent components.
• Genotype ambiguity is fully represented using a hierarchical delimiter system.
• The format supports direct inclusion of consensus sequences and metadata, with external referencing for raw reads.

Conclusions:

• The refined HML provides a robust electronic format for HLA and KIR genotyping data exchange, specifically tailored for NGS.
• This format improves data completeness, accuracy, and the representation of complex genotypes.
• It facilitates standardized reporting and data sharing in immunogenomics research.