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Ultrasensitive allele inference from immune repertoire sequencing data with MiXCR

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MIKELOV Artem NEFEDIEV George TASHKEEV Alexander RODRIGUEZ Oscar L DIEGO Aguilar Ortmans SKATOVA Valeriia IZRAELSON Mark DAVYDOV Alexey N POSLAVSKY Stanislav RAHMOUNI Souad WATSON Corey T CHUDAKOV Dmitriy BOYD Scott D BOLOTIN Dmitry

Rok publikování 2024
Druh Článek v odborném periodiku
Časopis / Zdroj Genome research
Fakulta / Pracoviště MU

Středoevropský technologický institut

Citace
www https://genome.cshlp.org/content/34/12/2293
Doi https://doi.org/10.1101/gr.278775.123
Klíčová slova TOOLKIT
Popis Allelic variability in the adaptive immune receptor loci, which harbor the gene segments that encode B cell and T cell receptors (BCR/TCR), is of critical importance for immune responses to pathogens and vaccines. Adaptive immune receptor repertoire sequencing (AIRR-seq) has become widespread in immunology research making it the most readily available source of information about allelic diversity in immunoglobulin (IG) and T cell receptor (TR) loci. Here, we present a novel algorithm for extrasensitive and specific variable (V) and joining (J) gene allele inference, allowing the reconstruction of individual high-quality gene segment libraries. The approach can be applied for inferring allelic variants from peripheral blood lymphocyte BCR and TCR repertoire sequencing data, including hypermutated isotype-switched BCR sequences, thus allowing high-throughput novel allele discovery from a wide variety of existing data sets. The developed algorithm is a part of the MiXCR software. We demonstrate the accuracy of this approach using AIRR-seq paired with long-read genomic sequencing data, comparing it to a widely used algorithm, TIgGER. We applied the algorithm to a large set of IG heavy chain (IGH) AIRR-seq data from 450 donors of ancestrally diverse population groups, and to the largest reported full-length TCR alpha and beta chain (TRA and TRB) AIRR-seq data set, representing 134 individuals. This allowed us to assess the genetic diversity within the IGH, TRA, and TRB loci in different populations and to establish a database of alleles of V and J genes inferred from AIRR-seq data and their population frequencies with free public access through VDJ.online database.

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