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ALPHLARD: a Bayesian method for analyzing HLA genes from whole genome sequence data.

Shuto Hayashi1, Rui Yamaguchi1, Shinichi Mizuno2

  • 1Human Genome Center, The Institute of Medical Science, The University of Tokyo, 4-6-1 Shirokanedai, Minato-ku, Tokyo, 108-8639, Japan.

BMC Genomics
|November 3, 2018
PubMed
Summary

Accurate human leukocyte antigen (HLA) genotyping from low-coverage whole genome sequence (WGS) data is now possible with ALPHLARD. This new Bayesian model also identifies unknown HLA types and detects somatic mutations.

Keywords:
Bayesian hierarchical modelCancer immunogenomicsHLA genotypingMarkov chain Monte CarloNext generation sequencingWhole exome sequencingWhole genome sequencing

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Area of Science:

  • Genomics
  • Immunogenetics
  • Bioinformatics

Background:

  • Accurate human leukocyte antigen (HLA) genotyping is crucial for various applications.
  • Existing methods struggle with low-depth whole genome sequence (WGS) data.
  • There's a need for methods to identify novel HLA types beyond current databases.

Purpose of the Study:

  • To develop a robust method for accurate HLA genotyping from WGS data.
  • To enable the identification of unknown HLA types.
  • To detect germline and somatic mutations within HLA genes.

Main Methods:

  • Developed ALPHLARD, a Bayesian model for HLA read collection and genotyping.
  • Applied ALPHLARD to 253 whole exome sequence (WES) and 25 WGS datasets.
  • Validated genotyping accuracy against Sanger-based typing (SBT) and amplicon sequencing.

Main Results:

  • ALPHLARD achieved 98.8% accuracy for WES and 98.5% for WGS data at 2nd field resolution.
  • The model successfully identified HLA types for key HLA genes (A, B, C, DPA1, DPB1, DQA1, DQB1, DRB1).
  • Detected rare germline variants, three somatic point mutations, and one loss of heterozygosity event in HLA genes from WGS data.

Conclusions:

  • ALPHLARD demonstrates high performance for HLA genotyping, even with low-coverage data.
  • The method can identify novel HLA sequences and somatic mutations within HLA genes.
  • ALPHLARD has the potential to expand HLA reference databases and reveal the immunological impact of HLA mutations.