@ARTICLE{10.3389/fimmu.2020.02136, AUTHOR={Rodriguez, Oscar L. and Gibson, William S. and Parks, Tom and Emery, Matthew and Powell, James and Strahl, Maya and Deikus, Gintaras and Auckland, Kathryn and Eichler, Evan E. and Marasco, Wayne A. and Sebra, Robert and Sharp, Andrew J. and Smith, Melissa L. and Bashir, Ali and Watson, Corey T.}, TITLE={A Novel Framework for Characterizing Genomic Haplotype Diversity in the Human Immunoglobulin Heavy Chain Locus}, JOURNAL={Frontiers in Immunology}, VOLUME={11}, YEAR={2020}, URL={https://www.frontiersin.org/articles/10.3389/fimmu.2020.02136}, DOI={10.3389/fimmu.2020.02136}, ISSN={1664-3224}, 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.} }