The use of non-functional clonotypes as a natural calibrator for quantitative bias correction in adaptive immune receptor repertoire profiling

  1. Anastasia O Smirnova
  2. Anna M Miroshnichenkova
  3. Yulia V Olshanskaya
  4. Michael A Maschan
  5. Yuri B Lebedev
  6. Dmitriy M Chudakov
  7. Ilgar Z Mamedov
  8. Alexander Komkov  Is a corresponding author
  1. Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Russian Federation
  2. Dmitry Rogachev National Medical and Research Center of Pediatric Hematology, Oncology and Immunology, Russian Federation

Abstract

High-throughput sequencing of adaptive immune receptor repertoires is a valuable tool for receiving insights in adaptive immunity studies. Several powerful TCR/BCR repertoire reconstruction and analysis methods have been developed in the past decade. However, detecting and correcting the discrepancy between real and experimentally observed lymphocyte clone frequencies is still challenging. Here we discovered a hallmark anomaly in the ratio between read count and clone count-based frequencies of non-functional clonotypes in multiplex PCR-based immune repertoires. Calculating this anomaly, we formulated a quantitative measure of V- and J-genes frequency bias driven by multiplex PCR during library preparation called Over Amplification Rate (OAR). Based on the OAR concept, we developed an original software for multiplex PCR-specific bias evaluation and correction named iROAR: Immune Repertoire Over Amplification Removal (https://github.com/smiranast/iROAR). The iROAR algorithm was successfully tested on previously published TCR repertoires obtained using both 5' RACE (Rapid Amplification of cDNA Ends)-based and multiplex PCR-based approaches and compared with a biological spike-in-based method for PCR bias evaluation. The developed approach can increase the accuracy and consistency of repertoires reconstructed by different methods making them more applicable for comparative analysis.

Data availability

Sequencing data have been deposited in SRA under accession code PRJNA825832. All other sequencing data analyzed during this study are previously published and fully available under links or access numbers included in the manuscript and supporting files.

The following data sets were generated
The following previously published data sets were used

Article and author information

Author details

  1. Anastasia O Smirnova

    Department of Genomics of Adaptive Immunity, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russian Federation
    Competing interests
    The authors declare that no competing interests exist.
  2. Anna M Miroshnichenkova

    Laboratory of Cytogenetics and Molecular Genetics, Dmitry Rogachev National Medical and Research Center of Pediatric Hematology, Oncology and Immunology, Moscow, Russian Federation
    Competing interests
    The authors declare that no competing interests exist.
  3. Yulia V Olshanskaya

    Laboratory of Cytogenetics and Molecular Genetics, Dmitry Rogachev National Medical and Research Center of Pediatric Hematology, Oncology and Immunology, Moscow, Russian Federation
    Competing interests
    The authors declare that no competing interests exist.
  4. Michael A Maschan

    Laboratory of Cytogenetics and Molecular Genetics, Dmitry Rogachev National Medical and Research Center of Pediatric Hematology, Oncology and Immunology, Moscow, Russian Federation
    Competing interests
    The authors declare that no competing interests exist.
  5. Yuri B Lebedev

    Department of Genomics of Adaptive Immunity, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russian Federation
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-4554-4733
  6. Dmitriy M Chudakov

    Department of Genomics of Adaptive Immunity, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russian Federation
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-0430-790X
  7. Ilgar Z Mamedov

    Department of Genomics of Adaptive Immunity, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russian Federation
    Competing interests
    The authors declare that no competing interests exist.
  8. Alexander Komkov

    Department of Genomics of Adaptive Immunity, Shemyakin-Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russian Federation
    For correspondence
    alexandrkomkov@yandex.ru
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-9113-698X

Funding

Russian Science Foundation (20-75-10091)

  • Alexander Komkov

Russian Foundation for Basic Research (20-015-00462)

  • Alexander Komkov

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Reviewing Editor

  1. Gabrielle T Belz, University of Queensland, Australia

Publication history

  1. Received: April 6, 2021
  2. Accepted: January 22, 2023
  3. Accepted Manuscript published: January 24, 2023 (version 1)
  4. Accepted Manuscript updated: January 26, 2023 (version 2)

Copyright

© 2023, Smirnova et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

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  1. Anastasia O Smirnova
  2. Anna M Miroshnichenkova
  3. Yulia V Olshanskaya
  4. Michael A Maschan
  5. Yuri B Lebedev
  6. Dmitriy M Chudakov
  7. Ilgar Z Mamedov
  8. Alexander Komkov
(2023)
The use of non-functional clonotypes as a natural calibrator for quantitative bias correction in adaptive immune receptor repertoire profiling
eLife 12:e69157.
https://doi.org/10.7554/eLife.69157

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