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A Novel Framework for Characterizing Genomic Haplotype Diversity in the Human Immunoglobulin Heavy Chain Locus. | LitMetric

AI Article Synopsis

  • The study addresses the incomplete understanding of genetic variation in the immunoglobulin heavy chain locus (IGH), which limits knowledge about antibody-related processes due to its complexity and previous inadequate sequencing methods.
  • By using targeted long-read sequencing combined with a bioinformatics tool called IGenotyper, researchers successfully analyzed eight human samples, revealing high-quality data that identified new structural variants and alleles.
  • This improved framework not only enhances the accuracy of genetic data but also provides a vital resource for exploring the role of IGH variation in immunity, disease risk, and responses to vaccinations and treatments.

Article Abstract

An incomplete ascertainment of genetic variation within the highly polymorphic immunoglobulin heavy chain locus (IGH) has hindered our ability to define genetic factors that influence antibody-mediated processes. Due to locus complexity, standard high-throughput approaches have failed to accurately and comprehensively capture IGH polymorphism. As a result, the locus has only been fully characterized two times, severely limiting our knowledge of human IGH diversity. Here, we combine targeted long-read sequencing with a novel bioinformatics tool, IGenotyper, to fully characterize IGH variation in a haplotype-specific manner. We apply this approach to eight human samples, including a haploid cell line and two mother-father-child trios, and demonstrate the ability to generate high-quality assemblies (>98% complete and >99% accurate), genotypes, and gene annotations, identifying 2 novel structural variants and 15 novel IGH alleles. We show multiplexing allows for scaling of the approach without impacting data quality, and that our genotype call sets are more accurate than short-read (>35% increase in true positives and >97% decrease in false-positives) and array/imputation-based datasets. This framework establishes a desperately needed foundation for leveraging IG genomic data to study population-level variation in antibody-mediated immunity, critical for bettering our understanding of disease risk, and responses to vaccines and therapeutics.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7539625PMC
http://dx.doi.org/10.3389/fimmu.2020.02136DOI Listing

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