September 22, 2019  |  

Human and rhesus macaque KIR haplotypes defined by their transcriptomes.

The killer-cell Ig-like receptors (KIRs) play a central role in the immune recognition in infection, pregnancy, and transplantation through their interactions with MHC class I molecules. KIR genes display abundant copy number variation as well as high levels of polymorphism. As a result, it is challenging to characterize this structurally dynamic region. KIR haplotypes have been analyzed in different species using conventional characterization methods, such as Sanger sequencing and Roche/454 pyrosequencing. However, these methods are time-consuming and often failed to define complete haplotypes, or do not reach allele-level resolution. In addition, most analyses were performed on genomic DNA, and thus were lacking substantial information about transcription and its corresponding modifications. In this paper, we present a single-molecule real-time sequencing approach, using Pacific Biosciences Sequel platform to characterize the KIR transcriptomes in human and rhesus macaque (Macaca mulatta) families. This high-resolution approach allowed the identification of novel Mamu-KIR alleles, the extension of reported allele sequences, and the determination of human and macaque KIR haplotypes. In addition, multiple recombinant KIR genes were discovered, all located on contracted haplotypes, which were likely the result of chromosomal rearrangements. The relatively high number of contracted haplotypes discovered might be indicative of selection on small KIR repertoires and/or novel fusion gene products. This next-generation method provides an improved high-resolution characterization of the KIR cluster in humans and macaques, which eventually may aid in a better understanding and interpretation of KIR allele-associated diseases, as well as the immune response in transplantation and reproduction. Copyright © 2018 by The American Association of Immunologists, Inc.


September 22, 2019  |  

Report from the Killer-cell Immunoglobulin-like Receptors (KIR) component of the 17th International HLA and Immunogenetics Workshop.

The goals of the KIR component of the 17th International HLA and Immunogenetics Workshop (IHIW) were to encourage and educate researchers to begin analyzing KIR at allelic resolution, and to survey the nature and extent of KIR allelic diversity across human populations. To represent worldwide diversity, we analyzed 1269 individuals from ten populations, focusing on the most polymorphic KIR genes, which express receptors having three immunoglobulin (Ig)-like domains (KIR3DL1/S1, KIR3DL2 and KIR3DL3). We identified 13 novel alleles of KIR3DL1/S1, 13 of KIR3DL2 and 18 of KIR3DL3. Previously identified alleles, corresponding to 33 alleles of KIR3DL1/S1, 38 of KIR3DL2, and 43 of KIR3DL3, represented over 90% of the observed allele frequencies for these genes. In total we observed 37 KIR3DL1/S1 allotypes, 40 for KIR3DL2 and 44 for KIR3DL3. As KIR allotype diversity can affect NK cell function, this demonstrates potential for high functional diversity worldwide. Allelic variation further diversifies KIR haplotypes. We determined KIR3DL3?~?KIR3DL1/S1?~?KIR3DL2 haplotypes from five of the studied populations, and observed multiple population-specific haplotypes in each. This included 234 distinct haplotypes in European Americans, 191 in Ugandans, 35 in Papuans, 95 in Egyptians and 86 in Spanish populations. For another 35 populations, encompassing 642,105 individuals we focused on KIR3DL2 and identified another 375 novel alleles, with approximately half of them observed in more than one individual. The KIR allelic level data gathered from this project represents the most comprehensive summary of global KIR allelic diversity to date, and continued analysis will improve understanding of KIR allelic polymorphism in global populations. Further, the wealth of new data gathered in the course of this workshop component highlights the value of collaborative, community-based efforts in immunogenetics research, exemplified by the IHIW.Copyright © 2018. Published by Elsevier Inc.


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