Method to completely characterize the highly polymorphic KIR genomic region

Stanford researcher Paul Norman has developed an integrated capture/next-gen sequencing/ bioinformatics method to completely characterize the structure and sequence of the highly polymorphic killer cell immunoglobulin-like receptor (KIR) genes to aid in donor matching for clinical transplantations. KIRs are a family of proteins expressed by natural killer (NK) cells that, upon binding with HLA class I molecules, allow NK cells to discriminate healthy cells from infected or diseased cells. The genomic region containing KIR is unusually diverse, both in the number of genes and their alleles. The region is structurally complex and highly polymorphic. In addition, the genomic region is also strongly associated with a wide spectrum of diseases. It would be beneficial to understand KIR diversity, but methods to do so are limited by the complexity of the region.

Stanford is making available for licensing the copyrighted list of 4,000 oligonucleotide probes that cover the KIR genes and can be used to enrich KIR regions to prepare DNA libraries for next-gen sequencing. The bioinformatics pipeline that automatically analyzes KIR specific reads is open-source and will be made freely available – it attributes sequencing reads to specific KIR genes, determines copy number by read depth, and calls high-resolution genotypes for each of the KIR genes. This technology will facilitate donor matching for bone marrow transplants and allow determination of a complete description of KIR in the human population and its influence on physiology, disease, and immunotherapy.

Stage of research
The method was validated using DNA from well-characterized cell lines, by comparison with established methods of KIR genotyping and by determining KIR genotypes from the 1000 Genomes Project sequence data.