Dataset Information

Interpreting de novo Variation in Human Disease Using denovolyzeR.

ABSTRACT: Spontaneously arising (de novo) genetic variants are important in human disease, yet every individual carries many such variants, with a median of 1 de novo variant affecting the protein-coding portion of the genome. A recently described mutational model provides a powerful framework for the robust statistical evaluation of such coding variants, enabling the interpretation of de novo variation in human disease. Here we describe a new open-source software package, denovolyzeR, that implements this model and provides tools for the analysis of de novo coding sequence variants.

SUBMITTER: Ware JS

PROVIDER: S-EPMC4606471 | biostudies-literature | 2015 Oct

REPOSITORIES: biostudies-literature

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Interpreting de novo Variation in Human Disease Using denovolyzeR.

Ware James S JS Samocha Kaitlin E KE Homsy Jason J Daly Mark J MJ

Current protocols in human genetics 20151006

Spontaneously arising (de novo) genetic variants are important in human disease, yet every individual carries many such variants, with a median of 1 de novo variant affecting the protein-coding portion of the genome. A recently described mutational model provides a powerful framework for the robust statistical evaluation of such coding variants, enabling the interpretation of de novo variation in human disease. Here we describe a new open-source software package, denovolyzeR, that implements thi ...[more]

PMID: 26439716

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Project description: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.

Dataset Information

Interpreting de novo Variation in Human Disease Using denovolyzeR.

Publications

Interpreting de novo Variation in Human Disease Using denovolyzeR.

Similar Datasets

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