Mosaic deletion patterns of the human antibody heavy chain gene locus shown by Bayesian haplotyping

Moriah Gidoni, Omri Snir, Ayelet Peres, Pazit Polak, Ida Lindeman, Ivana Mikocziova, Vikas Kumar Sarna, Knut E. A. Lundin, Christopher Clouser, Francois Vigneault, Andrew M. Collins, Ludvig M. Sollid and Gur Yaari ()
Additional contact information
Moriah Gidoni: Bar Ilan University
Omri Snir: University of Oslo and Oslo University Hospital
Ayelet Peres: Bar Ilan University
Pazit Polak: Bar Ilan University
Ida Lindeman: University of Oslo and Oslo University Hospital
Ivana Mikocziova: University of Oslo and Oslo University Hospital
Vikas Kumar Sarna: University of Oslo and Oslo University Hospital
Knut E. A. Lundin: University of Oslo and Oslo University Hospital
Christopher Clouser: AbVitro, Inc
Francois Vigneault: AbVitro, Inc
Andrew M. Collins: University of NSW, Kensington
Ludvig M. Sollid: University of Oslo and Oslo University Hospital
Gur Yaari: Bar Ilan University

Nature Communications, 2019, vol. 10, issue 1, 1-14

Abstract: 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.

Date: 2019
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.nature.com/articles/s41467-019-08489-3 Abstract (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:nat:natcom:v:10:y:2019:i:1:d:10.1038_s41467-019-08489-3

Ordering information: This journal article can be ordered from
https://www.nature.com/ncomms/

DOI: 10.1038/s41467-019-08489-3

Access Statistics for this article

Nature Communications is currently edited by Nathalie Le Bot, Enda Bergin and Fiona Gillespie

More articles in Nature Communications from Nature
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().