Digitala Vetenskapliga Arkivet

Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
SweHLA: the high confidence HLA typing bio-resource drawn from 1000 Swedish genomes
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology. Uppsala University, Science for Life Laboratory, SciLifeLab.ORCID iD: 0000-0002-8414-2190
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology. Uppsala University, Science for Life Laboratory, SciLifeLab.ORCID iD: 0000-0001-6085-6749
Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Medical Biochemistry and Microbiology. Uppsala University, Science for Life Laboratory, SciLifeLab. Broad Institute of MIT and Harvard, Cambridge, MA, USA.ORCID iD: 0000-0001-8338-0253
Uppsala University, Science for Life Laboratory, SciLifeLab. Uppsala University, Disciplinary Domain of Medicine and Pharmacy, Faculty of Medicine, Department of Immunology, Genetics and Pathology, Medicinsk genetik och genomik.ORCID iD: 0000-0002-6316-3355
Show others and affiliations
2020 (English)In: European Journal of Human Genetics, ISSN 1018-4813, E-ISSN 1476-5438, Vol. 28, no 5, p. 627-635Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
2020. Vol. 28, no 5, p. 627-635
National Category
Medical Genetics and Genomics Bioinformatics (Computational Biology) Genetics and Genomics
Research subject
Bioinformatics; Molecular Genetics; Medical Genetics
Identifiers
URN: urn:nbn:se:uu:diva-393313DOI: 10.1038/s41431-019-0559-2ISI: 000527343000012PubMedID: 31844174OAI: oai:DiVA.org:uu-393313DiVA, id: diva2:1352670
Funder
Knut and Alice Wallenberg Foundation, 2018.0101Swedish Research Council, 541-2013-8161
Note

Title in thesis list of papers: SweHLA: the high confidence HLA typing bio-resource drawn from 1,000 Swedish genomes

Available from: 2019-09-19 Created: 2019-09-19 Last updated: 2025-02-10Bibliographically approved
In thesis
1. Human leukocyte antigen in sickness and in health: Ankylosing spondylitis and HLA in Sweden
Open this publication in new window or tab >>Human leukocyte antigen in sickness and in health: Ankylosing spondylitis and HLA in Sweden
2019 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

The human leukocyte antigen (HLAplays a major role in keeping us healthy, but some of the HLA alleles can contribute to disease susceptibility. One example is HLA-B*27which confers increased susceptibility of ankylosing spondylitis and represents one of the strongest genetic associations found in any common human disease. Ankylosing spondylitis shows a strong sex ratio skew (2-3:1 male to female) and studies confirm the existence of sexual-dimorphism in the presentation of this disease. The genetic predisposition for this, however, has not previously been studied. 

A Swedish ankylosing spondylitis population was sequenced with a targeted array to investigate the existence of sex-specific associations. RUNX3 was revealed to be associated in males by a univariate test, while aggregate tests revealed the HLA gene MICB to be associated in females. Functional validation demonstrated that the risk variants in RUNX3 increase expression, and MICB changed the transcription factor binding sites. Interestingly, since the disease involves bone changes, both RUNX3 and one of the MICB variants had effect in the bone cell line, SaOS-2.

In order to help researchers obtain more controls for HLA analysis, an HLA allele bioresource (SweHLA) was generated from 1,000 Swedish genomes. The alleles were typed with three to four HLA typing software programs and results were combined by an n-1methodology. This produced high quality alleles where the bias from each software program was diminished.

The methodology from SweHLA was utilised to study HLA in ankylosing spondylitis. To investigate both sex-specific predisposition and HLA-B*27 independence, samples were subdivided into two populations (one population with mixed HLA-B*27 positive and negative samples and one with only HLA-B*27 positive samples) that in turn were grouped by sex. In the mixed population, several alleles were replicated from previous studies. This study also revealed three female-specific alleles, two of which were new and one that had previously been associated to the severity of radiological changes. The HLA-B*27 population revealed a previously unknown protective allele, HLA-A*24:02. Through deeper examination of the HLA-B*27 population, two amino acids in HLA-A, position 119 in the whole set and position 180 in the male set, were revealed to be protective.

This thesis brings new insight into the genetic predisposition for a sex-skewed disease, demonstrating how sexual-dimorphism can be reflected in the genetic predisposition, hopefully leading to more similar studies. It also highlights the importance of methodology and demonstrate the drastic biases that can be imparted by software programs.

Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2019. p. 69
Series
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Medicine, ISSN 1651-6206 ; 1599
Keywords
Disease genetics, Ankylosing spondylitis, HLA typing, Imputation, Inference, Sex-stratified, HLA-B*27 independent, Association tests, Functional validation
National Category
Bioinformatics (Computational Biology) Medical Genetics and Genomics Genetics and Genomics
Research subject
Bioinformatics; Molecular Genetics
Identifiers
urn:nbn:se:uu:diva-393317 (URN)978-91-513-0760-2 (ISBN)
Public defence
2019-11-14, Room B41, BMC, Husargatan 3, Uppsala, 13:15 (English)
Opponent
Supervisors
Available from: 2019-10-23 Created: 2019-09-24 Last updated: 2025-02-10

Open Access in DiVA

fulltext(1184 kB)440 downloads
File information
File name FULLTEXT01.pdfFile size 1184 kBChecksum SHA-512
d15dc7f3ba7b5f4b9fde7b1decec5a2fa5478812051847acbab5fea55cd40183831f0c11e806b251bbcb99abe0769db34004b00870ae07f4015723e988b4287b
Type fulltextMimetype application/pdf

Other links

Publisher's full textPubMed

Search in DiVA

By author/editor
Nordin, JessikaAmeur, AdamLindblad-Toh, KerstinGyllensten, UlfMeadows, Jennifer R. S.
By organisation
Department of Medical Biochemistry and MicrobiologyScience for Life Laboratory, SciLifeLabDepartment of Immunology, Genetics and PathologyMedicinsk genetik och genomik
In the same journal
European Journal of Human Genetics
Medical Genetics and GenomicsBioinformatics (Computational Biology)Genetics and Genomics

Search outside of DiVA

GoogleGoogle Scholar
Total: 441 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

doi
pubmed
urn-nbn

Altmetric score

doi
pubmed
urn-nbn
Total: 350 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf