OGRDB: a reference database of inferred immune receptor genes

Author:

Lees William1ORCID,Busse Christian E2ORCID,Corcoran Martin3,Ohlin Mats4,Scheepers Cathrine56,Matsen Frederick A7,Yaari Gur8ORCID,Watson Corey T9,Collins Andrew10,Shepherd Adrian J1,

Affiliation:

1. Institute of Structural and Molecular Biology, Birkbeck College, University of London, London WC1E 7HX, UK

2. Division of B Cell Immunology, German Cancer Research Center, 69120 Heidelberg, Germany

3. Department of Microbiology, Tumor and Cell Biology, Karolinska Institute, Box 280, 171 77 Stockholm, Sweden

4. Department of Immunotechnology, Lund University, Medicon Village, S-223 81 Lund, Sweden

5. Center for HIV and STIs, National Institute for Communicable Diseases of the National Health Laboratory Service, Sandringam, Gauteng 2131, South Africa

6. Antibody Immunity Research Unit, School of Pathology, University of the Witwatersrand, Johannesburg 2050, South Africa

7. Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA 98109-1024, USA

8. Faculty of Engineering, Bar Ilan University, Ramat Gan 5290002, Israel

9. Department of Biochemistry and Molecular Genetics, University of Louisville School of Medicine, Louisville, KY 40202, USA

10. School of Biotechnology and Biomolecular Sciences, University of New South Wales, Sydney, New South Wales 2052, Australia

Abstract

Abstract High-throughput sequencing of the adaptive immune receptor repertoire (AIRR-seq) is providing unprecedented insights into the immune response to disease and into the development of immune disorders. The accurate interpretation of AIRR-seq data depends on the existence of comprehensive germline gene reference sets. Current sets are known to be incomplete and unrepresentative of the degree of polymorphism and diversity in human and animal populations. A key issue is the complexity of the genomic regions in which they lie, which, because of the presence of multiple repeats, insertions and deletions, have not proved tractable with short-read whole genome sequencing. Recently, tools and methods for inferring such gene sequences from AIRR-seq datasets have become available, and a community approach has been developed for the expert review and publication of such inferences. Here, we present OGRDB, the Open Germline Receptor Database (https://ogrdb.airr-community.org), a public resource for the submission, review and publication of previously unknown receptor germline sequences together with supporting evidence.

Funder

National Institutes of Health

Swedish Research Council

Publisher

Oxford University Press (OUP)

Subject

Genetics

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