RT Journal Article
SR Electronic
T1 A novel framework for characterizing genomic haplotype diversity in the human immunoglobulin heavy chain locus
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 2020.04.19.049270
DO 10.1101/2020.04.19.049270
A1 O. L. Rodriguez
A1 W. S. Gibson
A1 T. Parks
A1 M. Emery
A1 J. Powell
A1 M. Strahl
A1 G. Deikus
A1 K. Auckland
A1 E. E. Eichler
A1 W. A. Marasco
A1 R. Sebra
A1 A. J. Sharp
A1 M. L. Smith
A1 A. Bashir
A1 C. T. Watson
YR 2020
UL http://biorxiv.org/content/early/2020/05/07/2020.04.19.049270.abstract
AB 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 and B cell mediated processes. To date, methods for locus-wide genotyping of all IGH variant types do not exist. Here, we combine targeted long-read sequencing with a novel bioinformatics tool, IGenotyper, to fully characterize genetic variation within IGH 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, including 2 novel structural variants and 16 novel gene alleles. We show that 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 foundation for leveraging IG genomic data to study population-level variation in the antibody response.Competing Interest StatementE.E.E. is on the scientific advisory board (SAB) of DNAnexus, Inc.