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T cell receptor beta germline variability is revealed by inference from repertoire data

BACKGROUND: T and B cell receptor (TCR, BCR) repertoires constitute the foundation of adaptive immunity. Adaptive immune receptor repertoire sequencing (AIRR-seq) is a common approach to study immune system dynamics. Understanding the genetic factors influencing the composition and dynamics of these...

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Autores principales: Omer, Aviv, Peres, Ayelet, Rodriguez, Oscar L, Watson, Corey T, Lees, William, Polak, Pazit, Collins, Andrew M, Yaari, Gur
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8740489/
https://www.ncbi.nlm.nih.gov/pubmed/34991709
http://dx.doi.org/10.1186/s13073-021-01008-4
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author Omer, Aviv
Peres, Ayelet
Rodriguez, Oscar L
Watson, Corey T
Lees, William
Polak, Pazit
Collins, Andrew M
Yaari, Gur
author_facet Omer, Aviv
Peres, Ayelet
Rodriguez, Oscar L
Watson, Corey T
Lees, William
Polak, Pazit
Collins, Andrew M
Yaari, Gur
author_sort Omer, Aviv
collection PubMed
description BACKGROUND: T and B cell receptor (TCR, BCR) repertoires constitute the foundation of adaptive immunity. Adaptive immune receptor repertoire sequencing (AIRR-seq) is a common approach to study immune system dynamics. Understanding the genetic factors influencing the composition and dynamics of these repertoires is of major scientific and clinical importance. The chromosomal loci encoding for the variable regions of TCRs and BCRs are challenging to decipher due to repetitive elements and undocumented structural variants. METHODS: To confront this challenge, AIRR-seq-based methods have recently been developed for B cells, enabling genotype and haplotype inference and discovery of undocumented alleles. However, this approach relies on complete coverage of the receptors’ variable regions, whereas most T cell studies sequence a small fraction of that region. Here, we adapted a B cell pipeline for undocumented alleles, genotype, and haplotype inference for full and partial AIRR-seq TCR data sets. The pipeline also deals with gene assignment ambiguities, which is especially important in the analysis of data sets of partial sequences. RESULTS: From the full and partial AIRR-seq TCR data sets, we identified 39 undocumented polymorphisms in T cell receptor Beta V (TRBV) and 31 undocumented 5 (′) UTR sequences. A subset of these inferences was also observed using independent genomic approaches. We found that a single nucleotide polymorphism differentiating between the two documented T cell receptor Beta D2 (TRBD2) alleles is strongly associated with dramatic changes in the expressed repertoire. CONCLUSIONS: We reveal a rich picture of germline variability and demonstrate how a single nucleotide polymorphism dramatically affects the composition of the whole repertoire. Our findings provide a basis for annotation of TCR repertoires for future basic and clinical studies. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at (10.1186/s13073-021-01008-4).
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spelling pubmed-87404892022-01-07 T cell receptor beta germline variability is revealed by inference from repertoire data Omer, Aviv Peres, Ayelet Rodriguez, Oscar L Watson, Corey T Lees, William Polak, Pazit Collins, Andrew M Yaari, Gur Genome Med Research BACKGROUND: T and B cell receptor (TCR, BCR) repertoires constitute the foundation of adaptive immunity. Adaptive immune receptor repertoire sequencing (AIRR-seq) is a common approach to study immune system dynamics. Understanding the genetic factors influencing the composition and dynamics of these repertoires is of major scientific and clinical importance. The chromosomal loci encoding for the variable regions of TCRs and BCRs are challenging to decipher due to repetitive elements and undocumented structural variants. METHODS: To confront this challenge, AIRR-seq-based methods have recently been developed for B cells, enabling genotype and haplotype inference and discovery of undocumented alleles. However, this approach relies on complete coverage of the receptors’ variable regions, whereas most T cell studies sequence a small fraction of that region. Here, we adapted a B cell pipeline for undocumented alleles, genotype, and haplotype inference for full and partial AIRR-seq TCR data sets. The pipeline also deals with gene assignment ambiguities, which is especially important in the analysis of data sets of partial sequences. RESULTS: From the full and partial AIRR-seq TCR data sets, we identified 39 undocumented polymorphisms in T cell receptor Beta V (TRBV) and 31 undocumented 5 (′) UTR sequences. A subset of these inferences was also observed using independent genomic approaches. We found that a single nucleotide polymorphism differentiating between the two documented T cell receptor Beta D2 (TRBD2) alleles is strongly associated with dramatic changes in the expressed repertoire. CONCLUSIONS: We reveal a rich picture of germline variability and demonstrate how a single nucleotide polymorphism dramatically affects the composition of the whole repertoire. Our findings provide a basis for annotation of TCR repertoires for future basic and clinical studies. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at (10.1186/s13073-021-01008-4). BioMed Central 2022-01-07 /pmc/articles/PMC8740489/ /pubmed/34991709 http://dx.doi.org/10.1186/s13073-021-01008-4 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Omer, Aviv
Peres, Ayelet
Rodriguez, Oscar L
Watson, Corey T
Lees, William
Polak, Pazit
Collins, Andrew M
Yaari, Gur
T cell receptor beta germline variability is revealed by inference from repertoire data
title T cell receptor beta germline variability is revealed by inference from repertoire data
title_full T cell receptor beta germline variability is revealed by inference from repertoire data
title_fullStr T cell receptor beta germline variability is revealed by inference from repertoire data
title_full_unstemmed T cell receptor beta germline variability is revealed by inference from repertoire data
title_short T cell receptor beta germline variability is revealed by inference from repertoire data
title_sort t cell receptor beta germline variability is revealed by inference from repertoire data
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8740489/
https://www.ncbi.nlm.nih.gov/pubmed/34991709
http://dx.doi.org/10.1186/s13073-021-01008-4
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