Assembly and analysis of 100 full MHC haplotypes from the Danish population

Jensen, James C.; Villesen, Palle; Friborg, Rune M.; Mailund, Thomas; Besenbacher, Søren; Schierup, Mikkel H.

doi:10.1101/gr.218891.116

Cited by 17 publications

(24 citation statements)

References 35 publications

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“…2). Our results matched expectation, with the highest levels of Tajima's D over the class I and II genes, and with more nucleotide diversity observed at class II genes compared to class I [40,41]. The majority of SNP and indel variation fell into the 0-0.1 minor allele frequency bins.…”

Section: Discussionsupporting

confidence: 87%

SweHLA: the high confidence HLA typing bio-resource drawn from 1000 Swedish genomes

et al. 2019

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There is a need to accurately call human leukocyte antigen (HLA) genes from existing short-read sequencing data, however there is no single solution that matches the gold standard of Sanger sequenced lab typing. Here we aimed to combine results from available software programs, minimizing the biases of applied algorithm and HLA reference. The result is a robust HLA population resource for the published 1000 Swedish genomes, and a framework for future HLA interrogation. HLA 2nd-field alleles were called using four imputation and inference methods for the classical eight genes (class I: HLA-A, HLA-B, HLA-C; class II: HLA-DPA1, HLA-DPB1, HLA-DQA1, HLA-DQB1, HLA-DRB1). A high confidence population set (SweHLA) was determined using an n−1 concordance rule for class I (four software) and class II (three software) alleles. Results were compared across populations and individual programs benchmarked to SweHLA. Per gene, 875 to 988 of the 1000 samples were genotyped in SweHLA; 920 samples had at least seven loci called. While a small fraction of reference alleles were common to all software (class I = 1.9% and class II = 4.1%), this did not affect the overall call rate. Gene-level concordance was high compared to European populations (>0.83%), with COX and PGF the dominant SweHLA haplotypes. We noted that 15/18 discordant alleles (delta allele frequency >2) were previously reported as disease-associated. These differences could in part explain across-study genetic replication failures, reinforcing the need to use multiple software solutions. SweHLA demonstrates a way to use existing NGS data to generate a population resource agnostic to individual HLA software biases.

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Section: Discussionsupporting

confidence: 87%

SweHLA: the high confidence HLA typing bio-resource drawn from 1000 Swedish genomes

et al. 2019

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“…While it was not the aim of this project to identify novel HLA alleles, we nonetheless examined the genetic diversity across the MHC for this population (Figure 2). Our results matched expectation, with the highest levels of Tajima’s D over the class I and II genes, and with more nucleotide diversity observed at class II genes compared to class I 40,41 . The majority of SNP and indel variation fell into the 0-0.1 minor allele frequency bins.…”

Section: Discussionsupporting

confidence: 89%

SweHLA: the high confidence HLA typing bio-resource drawn from 1 000 Swedish genomes

Nordin

Ameur

Gyllensten

et al. 2019

Preprint

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“…We predict HLA alleles from high-depth, high-coverage sequencing data from a cohort of 50 Danish trios (father, mother, and child) in the context of the Genome Denmark project [ 34 , 35 ]. The Genome Denmark project on these data has included, among other analysis, novel variation discovery [ 36 ] and therefore will not be covered in this publication. The Danish population is quite homogeneous and shows overall genomic resemblance to neighbouring countries [ 35 ].…”

Section: Introductionmentioning

confidence: 99%

Benchmarking the HLA typing performance of Polysolver and Optitype in 50 Danish parental trios

2018

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BackgroundThe adaptive immune response intrinsically depends on hypervariable human leukocyte antigen (HLA) genes. Concomitantly, correct HLA phenotyping is crucial for successful donor-patient matching in organ transplantation. The cost and technical limitations of current laboratory techniques, together with advances in next-generation sequencing (NGS) methodologies, have increased the need for precise computational typing methods.ResultsWe tested two widespread HLA typing methods using high quality full genome sequencing data from 150 individuals in 50 family trios from the Genome Denmark project. First, we computed descendant accuracies assessing the agreement in the inheritance of alleles from parents to offspring. Second, we compared the locus-specific homozygosity rates as well as the allele frequencies; and we compared those to the observed values in related populations. We provide guidelines for testing the accuracy of HLA typing methods by comparing family information, which is independent of the availability of curated alleles.ConclusionsAlthough current computational methods for HLA typing generally provide satisfactory results, our benchmark – using data with ultra-high sequencing depth – demonstrates the incompleteness of current reference databases, and highlights the importance of providing genomic databases addressing current sequencing standards, a problem yet to be resolved before benefiting fully from personalised medicine approaches HLA phenotyping is essential.

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Assembly and analysis of 100 full MHC haplotypes from the Danish population

Cited by 17 publications

References 35 publications

SweHLA: the high confidence HLA typing bio-resource drawn from 1000 Swedish genomes

SweHLA: the high confidence HLA typing bio-resource drawn from 1000 Swedish genomes

SweHLA: the high confidence HLA typing bio-resource drawn from 1 000 Swedish genomes

Benchmarking the HLA typing performance of Polysolver and Optitype in 50 Danish parental trios

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