Allele imputation for the Killer cell Immunoglobulin-like Receptor KIR3DL1/S1

Abstract

Highly polymorphic interactions of KIR3DL1 and KIR3DS1 with HLA class I ligands modulates the effector functions of natural killer (NK) cells and some T cells. This genetically determined diversity affects severity of infections, immune-mediated diseases, and some cancers, and impacts the course of cancer treatment, including transplantation. KIR3DL1 is an inhibitory receptor, and KIR3DS1 is an activating receptor encoded by the KIR3DL1/S1 gene that has more than 200 diverse and divergent alleles. Determination of KIR3DL1/S1 genotypes for medical application is hampered by complex sequence and structural variation that distinguishes individuals and populations, requiring targeted approaches to generate and analyze high-resolution allele data. To overcome these obstacles, we developed and optimized a model for imputing KIR3DL1/S1 alleles at high-resolution from whole-genome SNP data, and designed to represent a substantial component of human genetic diversity. We show that our Global model is effective at imputing KIR3DL1/S1 alleles with an accuracy ranging from 89% in Africans to 97% in East Asians, with mean specificity of 99.8% and sensitivity of 99% for named alleles >1% frequency. We used the established algorithm of the HIBAG program, in a modification named Pulling Out Natural killer cell Genomics (PONG). Because HIBAG was designed to impute HLA alleles also from whole-genome SNP data, PONG allows combinatorial diversity of KIR3DL1/S1 and HLA-A and B to be analyzed using complementary techniques on a single data source. The use of PONG thus negates the need for targeted sequencing data in very large-scale association studies where such methods might not be tractable. All code, imputation models, test data and documentation are available at https://github.com/NormanLabUCD/PONG.

Immunogenomics of Killer Cell Immunoglobulin-Like Receptor (KIR) and HLA Class I: Coevolution and Consequences for Human Health

“…[83][84][85] For much larger studies that are currently impractical to approach through DNA sequencing, imputation from whole-genome single-nucleotide polymorphism data provides an alternative to analyze KIR gene content, 86 or allele diversity. 87 As for HLA, the imputation methods are less accurate than direct sequencing, especially for some ethnicities or ancestry groups including Africans and South Asians. 87,88…”

“…87 As for HLA, the imputation methods are less accurate than direct sequencing, especially for some ethnicities or ancestry groups including Africans and South Asians. 87,88…”

“…170,171 A recent study revealed further independent contributions to psoriasis susceptibility from other receptor/ligand pairs and that ligand heterozygosity increases the risk. 172 We may predict that high-resolution analysis of KIR allotypes 83,85,87 will shed further light on these relationships. Indeed, the limited number of analyses to date have revealed, as for infection, that certain ligand and receptor combinations associate with severity rather than predisposition to disease.…”

“…Medical genetic and association studies have largely neglected non-European populations, [202][203][204] an exclusion that continues despite the knowledge that inclusion of multiple ancestries increases power of such studies. 205 For all these reasons, it is imperative that we can accurately characterize combinatorial diversity of KIR and HLA at high resolution and scale, 83,85,87 while encompassing all human diversity. With innovative new methods of evaluation such as KIR and HLA interaction scores 29,148,173 that evaluate the strength of binding and signal transduction as a proxy to infer NK cell function, it may be possible to shape the treatment or even prevent certain immune-mediated diseases based on knowledge of individual KIR and HLA compound genotypes.…”