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Hum Mol Genet. 2014 Aug 15;23(16):4443-51. doi: 10.1093/hmg/ddu149. Epub 2014 Apr 3.

Predicting HLA alleles from high-resolution SNP data in three Southeast Asian populations.

Author information

  • 1Saw Swee Hock School of Public Health.
  • 2Division of Rheumatology, Immunology, and Allergy, Division of Genetics, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA, Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA.
  • 3Department of Medical Microbiology, University of Manitoba, 730 William Avenue, Winnipeg, Manitoba R3E 0Z2, Canada, National Microbiology Laboratory, Winnipeg, Manitoba, Canada.
  • 4Life Sciences Institute.
  • 5Department of Pharmacology, National University of Singapore, Singapore 117597, Singapore.
  • 6Cancer Science Institute of Singapore, National University of Singapore, Singapore 117599, Singapore.
  • 7Department of Biochemistry, National University of Singapore, Singapore 117596, Singapore, Department of Biological Sciences, National University of Singapore, Singapore 117543, Singapore.
  • 8Division of Rheumatology, Immunology, and Allergy, Division of Genetics, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA, Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA, Centre for Human Genetic Research, Massachusetts General Hospital, Boston, MA 02114-2790, USA.
  • 9Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA, Centre for Human Genetic Research, Massachusetts General Hospital, Boston, MA 02114-2790, USA.
  • 10Saw Swee Hock School of Public Health, Life Sciences Institute, Department of Statistics and Applied Probability, National University of Singapore, Singapore, Singapore, NUS Graduate School for Integrative Science and Engineering, National University of Singapore, Singapore 117456, Singapore and Agency for Science, Technology and Research, Genome Institute of Singapore, Singapore 138672, Singapore statyy@nus.edu.sg.

Abstract

The major histocompatibility complex (MHC) containing the classical human leukocyte antigen (HLA) Class I and Class II genes is among the most polymorphic and diverse regions in the human genome. Despite the clinical importance of identifying the HLA types, very few databases jointly characterize densely genotyped single nucleotide polymorphisms (SNPs) and HLA alleles in the same samples. To date, the HapMap presents the only public resource that provides a SNP reference panel for predicting HLA alleles, constructed with four collections of individuals of north-western European, northern Han Chinese, cosmopolitan Japanese and Yoruba Nigerian ancestry. Owing to complex patterns of linkage disequilibrium in this region, it is unclear whether the HapMap reference panels can be appropriately utilized for other populations. Here, we describe a public resource for the Singapore Genome Variation Project with: (i) dense genotyping across ∼ 9000 SNPs in the MHC; (ii) four-digit HLA typing for eight Class I and Class II loci, in 96 southern Han Chinese, 89 Southeast Asian Malays and 83 Tamil Indians. This resource provides population estimates of the frequencies of HLA alleles at these eight loci in the three population groups, particularly for HLA-DPA1 and HLA-DPB1 that were not assayed in HapMap. Comparing between population-specific reference panels and a cosmopolitan panel created from all four HapMap populations, we demonstrate that more accurate imputation is obtained with population-specific panels than with the cosmopolitan panel, especially for the Malays and Indians but even when imputing between northern and southern Han Chinese. As with SNP imputation, common HLA alleles were imputed with greater accuracy than low-frequency variants.

© The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

PMID:
24698974
[PubMed - in process]
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