Killer cell immunoglobulin-like receptor (KIR) gene content variation in the HGDP-CEPH populations

The killer cell immunoglobulin-like receptor (KIR) gene cluster on chromosome 19 encodes cell surface glycoproteins that bind class I human leukocyte antigen (HLA) molecules as well as some other ligands. Through regulation of natural killer (NK) cell activity KIRs participate in tumour surveillance and clearing viral infections. KIR gene gene copy number variation associates with the outcome of transplantations and susceptibility to immune-mediated diseases. Inferring KIR gene content from genetic variant data is therefore desirable for immunogenetic analysis, particularly in the context of growing biobank genome data collections that rely on genotyping by microarray. Here we describe a stand-alone and freely available gene content imputation for 12 KIR genes. The models were trained using 807 Finnish biobank samples genotyped for 5900 KIR-region SNPs and analysed for KIR gene content with targeted sequencing. Cross-validation results demonstrate a high mean overall accuracy of 98.5% (95% CI [97.0–99.2]%) which compares favourably with previous methods including short-read sequencing based approaches.

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KIR gene content imputation from single-nucleotide polymorphisms in the Finnish population

10.1101/2021.05.26.445789 ◽

2021 ◽

Author(s):

Jarmo Ritari ◽

Kati Hyvarinen ◽

Jukka Partanen ◽

Satu Koskela

Keyword(s):

Viral Infections ◽

Nk Cell ◽

Killer Cell ◽

Cell Activity ◽

Gene Copy Number ◽

Human Leukocyte ◽

Gene Content ◽

Gene Copy ◽

Nucleotide Polymorphisms ◽

Kir Gene

The killer cell immunoglobulin-like receptor (KIR) gene cluster on chromosome 19 encodes cell surface glycoproteins that bind class I human leukocyte antigen (HLA) molecules as well as some other ligands. Through regulation of natural killer (NK) cell activity KIRs participate in tumour surveillance and clearing viral infections. KIR gene gene copy number variation associates with the outcome of transplantations and susceptibility to immune-mediated diseases. Inferring KIR gene content from genetic variant data is therefore desirable for immunogenetic analysis, particularly in the context of growing biobank genome data collections that rely on genotyping by microarray. Here we describe a stand-alone and freely available gene content imputation for 12 KIR genes. The models were trained using 818 Finnish biobank samples genotyped for 5774 KIR-region SNPs and analysed for KIR gene content with targeted sequencing. Cross-validation results demonstrate a high mean overall accuracy of 99.2% (95% CI: 97.8-99.7%) which compares favourably with previous methods including short-read sequencing based approaches.

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Cost-effective and fast KIR gene-content genotyping by multiplex melting curve analysis

HLA ◽

10.1111/tan.13430 ◽

2018 ◽

Vol 92 (6) ◽

pp. 384-391

Author(s):

Leonardo M. Amorim ◽

Tiago H. S. Santos ◽

Jill A. Hollenbach ◽

Paul J. Norman ◽

Wesley M. Marin ◽

...

Keyword(s):

Melting Curve ◽

Cost Effective ◽

Curve Analysis ◽

Gene Content ◽

Melting Curve Analysis ◽

Kir Gene

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Extensive gene content variation in the Brachypodium distachyon pan-genome correlates with population structure

Nature Communications ◽

10.1038/s41467-017-02292-8 ◽

2017 ◽

Vol 8 (1) ◽

Cited By ~ 102

Author(s):

Sean P. Gordon ◽

Bruno Contreras-Moreira ◽

Daniel P. Woods ◽

David L. Des Marais ◽

Diane Burgess ◽

...

Keyword(s):

Population Structure ◽

Brachypodium Distachyon ◽

Gene Content ◽

Pan Genome ◽

Content Variation

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Analysis of KIR3DP1 Polymorphism Provides Relevant Information on Centromeric KIR Gene Content

The Journal of Immunology ◽

10.4049/jimmunol.1800564 ◽

2018 ◽

Vol 201 (5) ◽

pp. 1460-1467 ◽

Cited By ~ 3

Author(s):

Maria Bono ◽

Daniela Pende ◽

Alice Bertaina ◽

Alessandro Moretta ◽

Mariella Della Chiesa ◽

...

Keyword(s):

Relevant Information ◽

Gene Content ◽

Kir Gene

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Characterisation of B killer cell immunoglobulin-like receptor genes and telomeric and centromeric motifs in hematopoietic stem cell transplantation donors in Vojvodina, Serbia

Genetika ◽

10.2298/gensr1701345a ◽

2017 ◽

Vol 49 (1) ◽

pp. 345-354

Author(s):

Dusica Ademovic-Sazdanic ◽

Svetlana Vojvodic ◽

S. Popovic ◽

N. Konstantinidis

Keyword(s):

Relapse Prevention ◽

Hematological Malignancies ◽

Killer Cell ◽

Simple Algorithm ◽

Hematopoietic Stem ◽

Graft Versus Host ◽

Kir Genes ◽

Graft Versus Leukemia ◽

Kir Gene ◽

Kir Genotypes

The outcome of HSCT is strongly in?uenced by the genetic similarity or identity in the HLA genes that affects the incidence of graft-versus-host disease (GvHD). Successful allogeneic HSCT, however, depends also on T-cell mediated graft-versus-leukemia (GvL) effect, in which donor-derived T cells and natural killer (NK) cells kill these malignant cells in the patient, therefore playing a crucial role in relapse prevention. The aim of this study was to make the predictive analysis of the structure and distribution of B KIR alleles and centromeric and telomeric KIR genotypes in HSCT donors in Vojvodina with regard to their contribution to protection from relapse. A total of 124 first-degree relatives of patients with hematological malignancies were examined for the presence or absence of 15 KIR genes by using of PCR-SSO technique with Luminex xMap technology. The percentage of individuals carrying each KIR gene, centromeric and telomeric KIR haplotypes and genotypes was determined by direct counting. Sixty two percent of the HSCT donors in Vojvodina carry A KIR haplotype, while nearly 38% carry B KIR haplotype. The distribution of B KIR genes showed that among 124 studied HSCT donors, 31(25%) do not carry none of the KIR genes belonging to B group, 71.77% of donors have two or more B KIR genes, 61.29% of them carry KIR 2DL2 and 2DS2 or more B KIR genes. The analysis of centromeric and telomeric KIR genotypes, showed that Cen-A1/Tel-A1 genotype had a highest frequency of 51.47% and Cen-B2/Tel-B1 the lowest frequency of 1.30%. The usage of donor KIR B gene content and centromeric and telomeric KIR gene structure could be used in development of a simple algorithm to identify donors who will provide the most protection against the relapse in related HSC transplants.

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