Poorly Expressed Alleles of Several Human Immunoglobulin Heavy Chain Variable Genes are Common in the Human Population.
Databases, Genetic
Gene Deletion
Gene Expression Profiling
Gene Rearrangement
Genes, Immunoglobulin Heavy Chain
Genetic Variation
Haplotypes
High-Throughput Nucleotide Sequencing
Humans
Immunoglobulin Class Switching
Immunoglobulin Heavy Chains
/ genetics
Immunoglobulin Variable Region
Somatic Hypermutation, Immunoglobulin
Transcriptome
adaptive immune receptor repertoire
allelic diversity
antibody heavy chain
germline gene
haplotype
immunoglobulin
inference
next generation sequencing
Journal
Frontiers in immunology
ISSN: 1664-3224
Titre abrégé: Front Immunol
Pays: Switzerland
ID NLM: 101560960
Informations de publication
Date de publication:
2020
2020
Historique:
received:
08
09
2020
accepted:
08
12
2020
entrez:
15
3
2021
pubmed:
16
3
2021
medline:
22
6
2021
Statut:
epublish
Résumé
Extensive diversity has been identified in the human heavy chain immunoglobulin locus, including allelic variation, gene duplication, and insertion/deletion events. Several genes have been suggested to be deleted in many haplotypes. Such findings have commonly been based on inference of the germline repertoire from data sets covering antibody heavy chain encoding transcripts. The inference process operates under conditions that may limit identification of genes transcribed at low levels. The presence of rare transcripts that would indicate the existence of poorly expressed alleles in haplotypes that otherwise appear to have deleted these genes has been assessed in the present study. Alleles IGHV1-2*05, IGHV1-3*02, IGHV4-4*01, and IGHV7-4-1*01 were all identified as being expressed from multiple haplotypes, but only at low levels, haplotypes that by inference often appeared not to express these genes at all. These genes are thus not as commonly deleted as previously thought. An assessment of the 5' untranslated region (up to and including the TATA-box), the signal peptide-encoding part of the gene, and the 3'-heptamer suggests that the alleles have no or minimal sequence difference in these regions in comparison to highly expressed alleles. This suggest that they may be able to participate in immunoglobulin gene rearrangement, transcription and translation. However, all four poorly expressed alleles harbor unusual sequence variants within their coding region that may compromise the functionality of the encoded products, thereby limiting their incorporation into the immunoglobulin repertoire. Transcripts based on IGHV7-4-1*01 that had undergone somatic hypermutation and class switch had mutated the codon that encoded the unusual residue in framework region 3 (cysteine 92; located far from the antigen binding site). This finding further supports the poor compatibility of this unusual residue in a fully functional protein product. Indications of a linkage disequilibrium were identified as IGHV1-2*05 and IGHV4-4*01 co-localized to the same haplotypes. Furthermore, transcripts of two of the poorly expressed alleles (IGHV1-3*02 and IGHV4-4*01) mostly do not encode in-frame, functional products, suggesting that these alleles might be essentially non-functional. It is proposed that the functionality status of immunoglobulin genes should also include assessment of their ability to encode functional protein products.
Identifiants
pubmed: 33717051
doi: 10.3389/fimmu.2020.603980
pmc: PMC7943739
doi:
Substances chimiques
Immunoglobulin Heavy Chains
0
Immunoglobulin Variable Region
0
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
603980Informations de copyright
Copyright © 2021 Ohlin.
Déclaration de conflit d'intérêts
MO is a member of the Adaptive Immune Receptor Repertoire (AIRR) Community’s Germline Database Working Group, and its Inferred Allele Review Committee. The Committee defines processes for approval of alleles of immunoglobulin gene alleles identified through computational inference, and that also approves inferences of such alleles.
Références
J Immunol. 2010 Jun 15;184(12):6986-92
pubmed: 20495067
Nucleic Acids Res. 2010 Jan;38(Database issue):D301-7
pubmed: 19900967
Front Immunol. 2016 Nov 04;7:457
pubmed: 27867380
J Immunol. 2017 May 1;198(9):3371-3373
pubmed: 28416712
Nucleic Acids Res. 2020 Jun 4;48(10):5499-5510
pubmed: 32365177
Mol Immunol. 2017 Jul;87:12-22
pubmed: 28388445
Methods Mol Biol. 2012;882:569-604
pubmed: 22665256
Bioinformatics. 2019 Nov 1;35(22):4840-4842
pubmed: 31173062
iScience. 2020 Mar 27;23(3):100883
pubmed: 32109676
Nucleic Acids Res. 2020 Jan 8;48(D1):D682-D688
pubmed: 31691826
Am J Hum Genet. 2013 Apr 4;92(4):530-46
pubmed: 23541343
Nucleic Acids Res. 2020 Jan 8;48(D1):D1051-D1056
pubmed: 31602484
Data Brief. 2017 Jun 27;13:620-640
pubmed: 28725665
Nat Commun. 2017 May 11;8:14946
pubmed: 28492228
Nucleic Acids Res. 2005 Jan 1;33(Database issue):D256-61
pubmed: 15608191
Proc Natl Acad Sci U S A. 2013 May 14;110(20):8146-51
pubmed: 23630267
Front Immunol. 2017 Nov 13;8:1433
pubmed: 29180996
Cold Spring Harb Protoc. 2011 Jun 01;2011(6):633-42
pubmed: 21632789
Eur J Immunol. 1998 Oct;28(10):3384-96
pubmed: 9808208
Front Immunol. 2019 Apr 05;10:660
pubmed: 31024532
Philos Trans R Soc Lond B Biol Sci. 2015 Sep 5;370(1676):
pubmed: 26194752
Immunol Cell Biol. 2008 Feb;86(2):111-5
pubmed: 18040280
Front Immunol. 2019 Mar 18;10:435
pubmed: 30936866
J Immunol. 2012 Feb 1;188(3):1333-40
pubmed: 22205028
Front Immunol. 2019 Feb 13;10:129
pubmed: 30814994
PLoS Comput Biol. 2019 Jul 22;15(7):e1007133
pubmed: 31329576
Nat Commun. 2016 Dec 20;7:13642
pubmed: 27995928
J Allergy Clin Immunol. 2017 Mar;139(3):1026-1030
pubmed: 27521279
Sci Rep. 2016 Feb 16;6:20842
pubmed: 26880249
Nat Commun. 2019 Feb 7;10(1):628
pubmed: 30733445
Protein Eng Des Sel. 2009 Mar;22(3):135-47
pubmed: 19188138
Proc Natl Acad Sci U S A. 2015 Feb 24;112(8):E862-70
pubmed: 25675496