High-Resolution Characterization of KIR Genes in a Large North American Cohort Reveals Novel Details of Structural and Sequence Diversity

The KIR (killer-cell immunoglobulin-like receptor) region is characterized by structural variation and high sequence similarity among genes, imposing technical difficulties for analysis. We undertook the most comprehensive study to date of KIR genetic diversity in a large population sample, applying next-generation sequencing in 2,130 United States European-descendant individuals. Data were analyzed using our custom bioinformatics pipeline specifically designed to address technical obstacles in determining KIR genotypes. Precise gene copy number determination allowed us to identify a set of uncommon gene-content KIR haplotypes accounting for 5.2% of structural variation. In this cohort, KIR2DL4 is the framework gene that most varies in copy number (6.5% of all individuals). We identified phased high-resolution alleles in large multi-locus insertions and also likely founder haplotypes from which they were deleted. Additionally, we observed 250 alleles at 5-digit resolution, of which 90 have frequencies >= 1%. We found sequence patterns that were consistent with the presence of novel alleles in 398 (18.7%) individuals and contextualized multiple orphan dbSNPs within the KIR complex. We also identified a novel KIR2DL1 variant, Pro151Arg, and demonstrated by molecular dynamics that this substitution is predicted to affect interaction with HLA-C. No previous studies have fully explored the full range of structural and sequence variation of KIR as we present here. We demonstrate that pairing high-throughput sequencing with state-of-art computational tools in a large cohort permits exploration of all aspects of KIR variation including determination of population-level haplotype diversity, improving understanding of the KIR system, and providing an important reference for future studies.

Automated summary

The KIR region shows high genetic diversity and unusual gene-content haplotypes, with KIR2DL4 being the most variable gene in copy number. Utilizing high-throughput sequencing, we identified rare gene-content KIR haplotypes and high-frequency alleles, providing valuable insights into KIR variation in the population. This study expands the understanding of KIR complexity and sets a foundation for future research in this field.