A Novel Framework for Characterizing Genomic Haplotype Diversity in the Human Immunoglobulin Heavy Chain Locus
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...
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Format: | Article |
Language: | English |
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Frontiers Media S.A.
2020-09-01
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Series: | Frontiers in Immunology |
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Online Access: | https://www.frontiersin.org/article/10.3389/fimmu.2020.02136/full |
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doaj-898d5da7ab434af3b8fb0d021effc906 |
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record_format |
Article |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Oscar L. Rodriguez William S. Gibson Tom Parks Matthew Emery James Powell Maya Strahl Gintaras Deikus Kathryn Auckland Evan E. Eichler Evan E. Eichler Wayne A. Marasco Robert Sebra Robert Sebra Andrew J. Sharp Melissa L. Smith Melissa L. Smith Melissa L. Smith Ali Bashir Corey T. Watson |
spellingShingle |
Oscar L. Rodriguez William S. Gibson Tom Parks Matthew Emery James Powell Maya Strahl Gintaras Deikus Kathryn Auckland Evan E. Eichler Evan E. Eichler Wayne A. Marasco Robert Sebra Robert Sebra Andrew J. Sharp Melissa L. Smith Melissa L. Smith Melissa L. Smith Ali Bashir Corey T. Watson A Novel Framework for Characterizing Genomic Haplotype Diversity in the Human Immunoglobulin Heavy Chain Locus Frontiers in Immunology immunoglobulin heavy chain locus single nucleotide variation structural variation antibody B cell receptor long-read sequencing |
author_facet |
Oscar L. Rodriguez William S. Gibson Tom Parks Matthew Emery James Powell Maya Strahl Gintaras Deikus Kathryn Auckland Evan E. Eichler Evan E. Eichler Wayne A. Marasco Robert Sebra Robert Sebra Andrew J. Sharp Melissa L. Smith Melissa L. Smith Melissa L. Smith Ali Bashir Corey T. Watson |
author_sort |
Oscar L. Rodriguez |
title |
A Novel Framework for Characterizing Genomic Haplotype Diversity in the Human Immunoglobulin Heavy Chain Locus |
title_short |
A Novel Framework for Characterizing Genomic Haplotype Diversity in the Human Immunoglobulin Heavy Chain Locus |
title_full |
A Novel Framework for Characterizing Genomic Haplotype Diversity in the Human Immunoglobulin Heavy Chain Locus |
title_fullStr |
A Novel Framework for Characterizing Genomic Haplotype Diversity in the Human Immunoglobulin Heavy Chain Locus |
title_full_unstemmed |
A Novel Framework for Characterizing Genomic Haplotype Diversity in the Human Immunoglobulin Heavy Chain Locus |
title_sort |
novel framework for characterizing genomic haplotype diversity in the human immunoglobulin heavy chain locus |
publisher |
Frontiers Media S.A. |
series |
Frontiers in Immunology |
issn |
1664-3224 |
publishDate |
2020-09-01 |
description |
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. |
topic |
immunoglobulin heavy chain locus single nucleotide variation structural variation antibody B cell receptor long-read sequencing |
url |
https://www.frontiersin.org/article/10.3389/fimmu.2020.02136/full |
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doaj-898d5da7ab434af3b8fb0d021effc9062020-11-25T01:28:59ZengFrontiers Media S.A.Frontiers in Immunology1664-32242020-09-011110.3389/fimmu.2020.02136571270A Novel Framework for Characterizing Genomic Haplotype Diversity in the Human Immunoglobulin Heavy Chain LocusOscar L. Rodriguez0William S. Gibson1Tom Parks2Matthew Emery3James Powell4Maya Strahl5Gintaras Deikus6Kathryn Auckland7Evan E. Eichler8Evan E. Eichler9Wayne A. Marasco10Robert Sebra11Robert Sebra12Andrew J. Sharp13Melissa L. Smith14Melissa L. Smith15Melissa L. Smith16Ali Bashir17Corey T. Watson18Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, United StatesDepartment of Biochemistry and Molecular Genetics, University of Louisville School of Medicine, Louisville, KY, United StatesWellcome Centre for Human Genetics, University of Oxford, Oxford, United KingdomDepartment of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, United StatesDepartment of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, United StatesDepartment of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, United StatesDepartment of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, United StatesWellcome Centre for Human Genetics, University of Oxford, Oxford, United KingdomDepartment of Genome Sciences, University of Washington School of Medicine, Seattle, WA, United StatesHoward Hughes Medical Institute, University of Washington, Seattle, WA, United StatesDepartment of Cancer Immunology and AIDS, Dana-Farber Cancer Institute, Department of Medicine, Harvard Medical School, Boston, MA, United StatesDepartment of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, United StatesIcahn Institute of Data Science and Genomic Technology, New York, NY, United StatesDepartment of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, United StatesDepartment of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, United StatesDepartment of Biochemistry and Molecular Genetics, University of Louisville School of Medicine, Louisville, KY, United StatesIcahn Institute of Data Science and Genomic Technology, New York, NY, United StatesDepartment of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, United StatesDepartment of Biochemistry and Molecular Genetics, University of Louisville School of Medicine, Louisville, KY, United StatesAn 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.https://www.frontiersin.org/article/10.3389/fimmu.2020.02136/fullimmunoglobulin heavy chain locussingle nucleotide variationstructural variationantibodyB cell receptorlong-read sequencing |