Can We Detect T Cell Receptors from Long-Read RNA-Seq Data?

Justyna Mika*, Serge M. Candéias, Christophe Badie, Joanna Polanska

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

T cells play an essential role in defense of the organism against pathogens and cancer. Efficient protection requires a vast repertoire of immune receptors, which is created by the V(D)J recombination process. There are multiple algorithms designed for the annotation of recombined T cell receptor (TR) sequences from traditional (short-read) RNA-Seq, however, none is adjusted for the long-read data. Here we intend to examine whether existing methods for TR sequences annotation using traditional RNA-Seq can be utilized for long-read sequencing data. ImReP, TRUST4, CATT and MiXCR algorithms were applied to data obtained by nanopore technology (PromethION). Adjustment of parameters was performed. The biggest number of CDR3 sequences was detected by the TRUST4 algorithm (20,599 unique TR sequences out of 73,904,478 total reads), representing 25% of the expected number of sequences. The distribution of annotated V and J genes was the same for MiXCR and TRUST4 algorithms and may be used to analyze the repertoire of V/J gene used in rearranged TR genes. Due to the high sequencing error rate of the analyzed sample (median read quality Q = 6.9), TR clonotype analysis is not suggested, and additional error correction steps are recommended for such analyses.

Original languageEnglish
Title of host publicationBioinformatics and Biomedical Engineering - 9th International Work-Conference, IWBBIO 2022, Proceedings
EditorsIgnacio Rojas, Olga Valenzuela, Fernando Rojas, Luis Javier Herrera, Francisco Ortuño
PublisherSpringer Science and Business Media Deutschland GmbH
Pages450-463
Number of pages14
ISBN (Print)9783031078019
DOIs
Publication statusPublished - 2022
Event9th International Work-Conference on Bioinformatics and Biomedical Engineering, IWBBIO 2022 - Gran Canaria, Spain
Duration: 27 Jun 202230 Jun 2022

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume13347 LNBI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference9th International Work-Conference on Bioinformatics and Biomedical Engineering, IWBBIO 2022
Country/TerritorySpain
CityGran Canaria
Period27/06/2230/06/22

Bibliographical note

Funding Information:
Acknowledgment. This work was funded by the European Social Fund grant POWR.03.02.00– 00-I029 and by the Silesian University of Technology grant for Support and Development of Research Potential.

Publisher Copyright:
© 2022, Springer Nature Switzerland AG.

Keywords

  • Long reads
  • Oxford Nanopore Sequencing
  • TCR detection

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