Allele imputation for the killer cell immunoglobulin-like receptor KIR3DL1/S1.
Journal
PLoS computational biology
ISSN: 1553-7358
Titre abrégé: PLoS Comput Biol
Pays: United States
ID NLM: 101238922
Informations de publication
Date de publication:
02 2022
02 2022
Historique:
received:
03
05
2021
accepted:
10
01
2022
revised:
04
03
2022
pubmed:
23
2
2022
medline:
13
4
2022
entrez:
22
2
2022
Statut:
epublish
Résumé
Highly polymorphic interaction 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 immunotherapies, 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, 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. We designed the model to represent a substantial component of human genetic diversity. Our Global imputation model is effective at genotyping KIR3DL1/S1 alleles with an accuracy ranging from 88% in Africans to 97% in East Asians, with mean specificity of 99% and sensitivity of 95% for 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 with 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.
Identifiants
pubmed: 35192601
doi: 10.1371/journal.pcbi.1009059
pii: PCOMPBIOL-D-21-00820
pmc: PMC8896733
doi:
Substances chimiques
HLA-B Antigens
0
KIR3DL1 protein, human
0
KIR3DS1 protein, human
0
Receptors, KIR
0
Receptors, KIR3DL1
0
Receptors, KIR3DS1
0
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
e1009059Subventions
Organisme : NIAID NIH HHS
ID : R01 AI158410
Pays : United States
Organisme : NIAID NIH HHS
ID : R01 AI151549
Pays : United States
Organisme : NIAID NIH HHS
ID : R56 AI151549
Pays : United States
Organisme : NHGRI NIH HHS
ID : R01 HG010297
Pays : United States
Organisme : NIAID NIH HHS
ID : R01 AI128775
Pays : United States
Déclaration de conflit d'intérêts
I have read the journal’s policy and the authors of this manuscript have the following competing interests: Dr. Stephen Leslie is a partner with Peptide Groove LLP. All other authors have no competing interests to declare.
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