A1 Refereed original research article in a scientific journal
Mosaic deletion patterns of the human antibody heavy chain gene locus shown by Bayesian haplotyping
Authors: Gidoni M, Snir O, Peres A, Polak P, Lindeman I, Mikocziova I, Sarna VK, Lundin KEA, Clouser C, Vigneault F, Collins AM, Sollid LM, Yaari G
Publisher: NATURE PUBLISHING GROUP
Publication year: 2019
Journal: Nature Communications
Journal name in source: NATURE COMMUNICATIONS
Journal acronym: NAT COMMUN
Article number: ARTN 628
Volume: 10
Number of pages: 14
ISSN: 2041-1723
DOI: https://doi.org/10.1038/s41467-019-08489-3
Web address : https://www.nature.com/articles/s41467-019-08489-3
Abstract
Analysis of antibody repertoires by high-throughput sequencing is of major importance in understanding adaptive immune responses. Our knowledge of variations in the genomic loci encoding immunoglobulin genes is incomplete, resulting in conflicting VDJ gene assignments and biased genotype and haplotype inference. Haplotypes can be inferred using IGHJ6 heterozygosity, observed in one third of the people. Here, we propose a robust novel method for determining VDJ haplotypes by adapting a Bayesian framework. Our method extends haplotype inference to IGHD- and IGHV-based analysis, enabling inference of deletions and copy number variations in the entire population. To test this method, we generated a multi-individual data set of naive B-cell repertoires, and found allele usage bias, as well as a mosaic, tiled pattern of deleted IGHD and IGHV genes. The inferred haplotypes may have clinical implications for genetic disease predispositions. Our findings expand the knowledge that can be extracted from antibody repertoire sequencing data.
Analysis of antibody repertoires by high-throughput sequencing is of major importance in understanding adaptive immune responses. Our knowledge of variations in the genomic loci encoding immunoglobulin genes is incomplete, resulting in conflicting VDJ gene assignments and biased genotype and haplotype inference. Haplotypes can be inferred using IGHJ6 heterozygosity, observed in one third of the people. Here, we propose a robust novel method for determining VDJ haplotypes by adapting a Bayesian framework. Our method extends haplotype inference to IGHD- and IGHV-based analysis, enabling inference of deletions and copy number variations in the entire population. To test this method, we generated a multi-individual data set of naive B-cell repertoires, and found allele usage bias, as well as a mosaic, tiled pattern of deleted IGHD and IGHV genes. The inferred haplotypes may have clinical implications for genetic disease predispositions. Our findings expand the knowledge that can be extracted from antibody repertoire sequencing data.
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