SNP‐HLA Reference Consortium (SHLARC): HLA and SNP data sharing for promoting MHC‐centric analyses in genomics

Vince, Nicolas; Douillard, Venceslas; Geffard, Estelle; Meyer, Diogo; Castelli, Erick C.; Mack, Steven J.; Limou, Sophie; Gourraud, Pierre‐Antoine

doi:10.1002/gepi.22334

Cited by 18 publications

(27 citation statements)

References 30 publications

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“…The greatest progress in this direction has been made for inference of HLA alleles [42][43][44][45] and to a lesser extent KIR alleles [46] based on large databases of known gene sequences. More recent approaches have used targeted long-read sequencing to characterize immunoglobulin variation [15].…”

Section: Plos Computational Biologymentioning

confidence: 99%

Using de novo assembly to identify structural variation of eight complex immune system gene regions

et al. 2021

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Driven by the necessity to survive environmental pathogens, the human immune system has evolved exceptional diversity and plasticity, to which several factors contribute including inheritable structural polymorphism of the underlying genes. Characterizing this variation is challenging due to the complexity of these loci, which contain extensive regions of paralogy, segmental duplication and high copy-number repeats, but recent progress in long-read sequencing and optical mapping techniques suggests this problem may now be tractable. Here we assess this by using long-read sequencing platforms from PacBio and Oxford Nanopore, supplemented with short-read sequencing and Bionano optical mapping, to sequence DNA extracted from CD14+ monocytes and peripheral blood mononuclear cells from a single European individual identified as HV31. We use this data to build a de novo assembly of eight genomic regions encoding four key components of the immune system, namely the human leukocyte antigen, immunoglobulins, T cell receptors, and killer-cell immunoglobulin-like receptors. Validation of our assembly using k-mer based and alignment approaches suggests that it has high accuracy, with estimated base-level error rates below 1 in 10 kb, although we identify a small number of remaining structural errors. We use the assembly to identify heterozygous and homozygous structural variation in comparison to GRCh38. Despite analyzing only a single individual, we find multiple large structural variants affecting core genes at all three immunoglobulin regions and at two of the three T cell receptor regions. Several of these variants are not accurately callable using current algorithms, implying that further methodological improvements are needed. Our results demonstrate that assessing haplotype variation in these regions is possible given sufficiently accurate long-read and associated data. Continued reductions in the cost of these technologies will enable application of these methods to larger samples and provide a broader catalogue of germline structural variation at these loci, an important step toward making these regions accessible to large-scale genetic association studies.

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Section: Plos Computational Biologymentioning

confidence: 99%

Using de novo assembly to identify structural variation of eight complex immune system gene regions

et al. 2021

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“…To effect worldwide improvement in HLA imputation efforts, we led the creation of an international consortium, the SNP-HLA Reference Consortium (SHLARC), whose aim is to gather data to represent the extreme diversity of HLA alleles, fostering accurate imputation ( Vince et al, 2020b ). We further advocate for improvements to current HLA imputation tools and for the development of a platform promoting easy access to HLA imputation for immunogeneticists.…”

Section: Inferring and Imputing Hla Alleles: From Complex Read-mapping To The Study Of Linkage Disequilibriummentioning

confidence: 99%

Approaching Genetics Through the MHC Lens: Tools and Methods for HLA Research

et al. 2021

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The current SARS-CoV-2 pandemic era launched an immediate and broad response of the research community with studies both about the virus and host genetics. Research in genetics investigated HLA association with COVID-19 based on in silico, population, and individual data. However, they were conducted with variable scale and success; convincing results were mostly obtained with broader whole-genome association studies. Here, we propose a technical review of HLA analysis, including basic HLA knowledge as well as available tools and advice. We notably describe recent algorithms to infer and call HLA genotypes from GWAS SNPs and NGS data, respectively, which opens the possibility to investigate HLA from large datasets without a specific initial focus on this region. We thus hope this overview will empower geneticists who were unfamiliar with HLA to run MHC-focused analyses following the footsteps of the Covid-19|HLA & Immunogenetics Consortium.

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“…Resolving this will likely require the creation of reference haplotype variation datasets linked to genome function. The greatest progress in this direction has been made for inference of HLA alleles [39–41] and to a lesser extent KIR alleles [42] based on large databases of known gene sequences. More recent approaches have used targeted long-read sequencing to characterize immunoglobulin variation [15].…”

Section: Discussionmentioning

confidence: 99%

Usingde novoassembly to identify structural variation of complex immune system gene regions

Zhang

Roberts

Flores

et al. 2021

Preprint

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Driven by the necessity to survive environmental pathogens, the human immune system has evolved exceptional diversity and plasticity, to which several factors contribute including inheritable structural polymorphism of the underlying genes. Characterizing this variation is challenging due to the complexity of these loci, which contain extensive regions of paralogy, segmental duplication and high copy-number repeats, but recent progress in long-read sequencing and optical mapping techniques suggests this problem may now be tractable. Here we assess this by using long-read sequencing platforms from PacBio and Oxford Nanopore, supplemented with short-read sequencing and Bionano optical mapping, to sequence DNA extracted from CD14+ monocytes and peripheral blood mononuclear cells from a single European individual identified as HV31. We use this data to build a de novo assembly of eight genomic regions encoding four key components of the immune system, namely the human leukocyte antigen, immunoglobulins, T cell receptors, and killer-cell immunoglobulin-like receptors. Validation of our assembly using k-mer based and alignment approaches suggests that it has high accuracy, with estimated base-level error rates below 1 in 10 kb, although we identify a small number of remaining structural errors. We use the assembly to identify heterozygous and homozygous structural variation in comparison to GRCh38. Despite analyzing only a single individual, we find multiple large structural variants affecting core genes at all three immunoglobulin regions and at two of the three T cell receptor regions. Several of these variants are not accurately callable using current algorithms, implying that further methodological improvements are needed. Our results demonstrate that assessing haplotype variation in these regions is possible given sufficiently accurate long-read and associated data; application of these methods to larger samples would provide a broader catalogue of germline structural variation at these loci, an important step toward making these regions accessible to large-scale genetic association studies.

show abstract

SNP‐HLA Reference Consortium (SHLARC): HLA and SNP data sharing for promoting MHC‐centric analyses in genomics

Cited by 18 publications

References 30 publications

Using de novo assembly to identify structural variation of eight complex immune system gene regions

Using de novo assembly to identify structural variation of eight complex immune system gene regions

Approaching Genetics Through the MHC Lens: Tools and Methods for HLA Research

Usingde novoassembly to identify structural variation of complex immune system gene regions

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