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

Abstract
Data availability
Article and author information
Metrics

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

1. Smirnova A
2. et al
(2022) TRA repertoire
SRA PRJNA825832.

https://www.ncbi.nlm.nih.gov/sra/?term=PRJNA825832

The following previously published data sets were used

1. Warren et al
(2011) Exhaustive T-cell repertoire sequencing of human peripheral blood samples reveals signatures of antigen selection and a directly measured repertoire size of at least 1 million clonotypes
NCBI SRA, SRA020989.

https://www.ncbi.nlm.nih.gov/sra/?term=SRA020989
1. Zvyagin et al
(2014) Homo sapiens T-cell repertoire - MZ twins
NCBI BioProject, PRJNA214848.

https://www.ncbi.nlm.nih.gov/bioproject/?term=PRJNA214848
1. Rosati et al
(2020) TCR repertoire in IBD twins
NCBI BioProject, PRJEB27352.

https://www.ncbi.nlm.nih.gov/bioproject/?term=PRJEB27352
1. Greef et al
(2020) TCR repertoire sequencing of T cell subsets from healthy individuals
NCBI BioProject, PRJNA390125.

https://www.ncbi.nlm.nih.gov/bioproject/?term=PRJNA390125
1. Pogorelyy et al
(2018) Precise tracking of vaccine-responding T-cell clones reveals convergent and personalized response in identical twins
NCBI BioProject, PRJNA493983.

https://www.ncbi.nlm.nih.gov/bioproject/?term=PRJNA493983
1. Turchaninova et al
(2016) Protocol for full length profiling of IG repertoires
NCBI BioProject, PRJNA297771.

https://www.ncbi.nlm.nih.gov/bioproject/?term=PRJNA297771
1. Minervina et al
(2020) Comprehensive analysis of antiviral adaptive immunity formation and reactivation down to single cell level
NCBI BioProject, PRJNA577794.

https://www.ncbi.nlm.nih.gov/bioproject/?term=PRJNA577794
1. Simon et al
(2018) Sequencing the Peripheral Blood B and T cell Repertoire - Quantifying robustness and limitations
NCBI BioProject,PRJNA494572.

https://www.ncbi.nlm.nih.gov/bioproject/?term=PRJNA494572
1. Pan et al
(2019) Identification of drug-specific public TCR driving severe cutaneous adverse reactions
NCBI BioProject, PRJNA550004.

https://www.ncbi.nlm.nih.gov/bioproject/?term=PRJNA550004
1. Ma et al
(2018) T cell receptor repertoire sequencing with MIDCIRS
NCBI BioProject, PRJNA427746.

https://www.ncbi.nlm.nih.gov/bioproject/?term=PRJNA427746
1. Truong et al
(2019) TCR diversity and clonality of human CD4+ memory T cells
NCBI BioProject, PRJEB31283.

https://www.ncbi.nlm.nih.gov/bioproject/?term=PRJEB31283
1. Simnica et al
(2019) Immunoaging
NCBI BioProject, PRJEB33490.

https://www.ncbi.nlm.nih.gov/bioproject/?term=PRJEB33490
1. Weinberger et al
(2015) Immune repertoire profiling reveals that clonally expanded B and T cells infiltrating diseased human kidneys can also be tracked in the blood
https://zenodo.org.

https://zenodo.org/record/27483#.XpCuQ1MzZQI
1. Tanno et al
(2019) Paired TCR alpha:TCR beta sequencing at the single-cell level
NCBI BioProject, PRJNA593622.

https://www.ncbi.nlm.nih.gov/bioproject/?term=PRJNA593622
1. Liu et al
(2016) TRB and IGH are captured from peripheral blood using Multiplex PCR and 5'RACE
NCBI BioProject, PRJNA309577.

https://www.ncbi.nlm.nih.gov/bioproject/?term=PRJNA309577
1. Barennes et al
(2020) Benchmarking of T cell receptor repertoire profiling methods reveals large systematic biases
NCBI BioProject, PRJNA548335.

https://www.ncbi.nlm.nih.gov/bioproject/?term=PRJNA548335
1. 10X Genomics
(2022) Single Cell Immune Profiling
10X Genomics.

https://www.10xgenomics.com/resources/datasets/

Article and author information

Author details

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.
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.
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.
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.
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.

"This ORCID iD identifies the author of this article:" 0000-0003-4554-4733
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.

"This ORCID iD identifies the author of this article:" 0000-0003-0430-790X
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.
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.

"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.

Copyright

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.