HLA typing

HLA*LA

The HLA genes encode the molecules the immune system uses to tell self from non-self. They sit in the MHC on the short arm of chromosome 6 and form the most variable region of the human genome. Genome types the classical loci from sequence data.

Chromosome 6 HLA region · 6p21.1-21.3 telomere long arm (q) centromere short arm (p) telomere GENE MAP · HLA REGION Class II exogenous antigens DP DM DQ DR Class III complement, TNF Bf C4 C2 Hsp70 TNF Class I endogenous antigens B C E A G F short arm · 6p21 towards centromere →

Why this region matters so much

Across about 3.6 megabases lie more than 200 genes, many with immune function. The classical HLA genes are extremely polymorphic: for HLA-B several thousand alleles are known. This diversity is an evolutionary advantage against pathogens, but it makes typing technically demanding.

How Genome types

Genome uses HLA*LA. Instead of a linear reference it relies on a population reference graph that directly encodes known alleles of all classical MHC loci. Reads are projected onto this graph, which lets even strongly divergent alleles be assigned. The chr1/chr2 columns are HLA*LA output columns, not a phasing claim.

Clinical context

Individual HLA alleles are tightly linked to disease, for example HLA-DRB1*15:01 with multiple sclerosis, HLA-B*27 with ankylosing spondylitis, or HLA-B*57:01 with abacavir hypersensitivity. Genome presents the typing as technical evidence and does not replace qualified medical interpretation.

What Genome measures. For each classical locus (A, B, C, DRB1, DQB1, DPB1 and others) two alleles at up to four-digit resolution, each with a quality score and a status flag (unique, ambiguous, not typed).

Related topics

HLA and autoimmunityKIR genesKIR-HLA ligand contextPharmacogenetics

Sources

  1. 1Dilthey et al., 2019 HLA*LA — HLA typing from linearly projected graph alignments. Bioinformatics 35(21):4394–4396. doi.org/10.1093/bioinformatics/btz235
  2. 2Robinson et al., 2020 IPD-IMGT/HLA Database. Nucleic Acids Research 48:D948–D955. doi.org/10.1093/nar/gkz950
  3. 3Dendrou et al., 2018 HLA variation and disease. Nature Reviews Immunology 18:325–339. doi.org/10.1038/nri.2017.143
  4. 4Berlingerio et al., 2009 Mining Clinical, Immunological, and Genetic Data of Solid Organ Transplantation (Grafikvorlage). Biomedical Data and Applications, Springer, S. 211–236. doi.org/10.1007/978-3-642-02193-0_9