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Benchmarking of T cell receptor repertoire profiling methods reveals large systematic biases
P. Barennes, V. Quiniou, M. Shugay, ES. Egorov, AN. Davydov, DM. Chudakov, I. Uddin, M. Ismail, T. Oakes, B. Chain, A. Eugster, K. Kashofer, PP. Rainer, S. Darko, A. Ransier, DC. Douek, D. Klatzmann, E. Mariotti-Ferrandiz
Language English Country United States
Document type Journal Article, Research Support, N.I.H., Intramural, Research Support, Non-U.S. Gov't
Grant support
Department of Health - United Kingdom
NLK
ProQuest Central
from 2000-01-01 to 1 year ago
Health & Medicine (ProQuest)
from 2000-01-01 to 1 year ago
- MeSH
- Adult MeSH
- Jurkat Cells MeSH
- Middle Aged MeSH
- Humans MeSH
- Computer Simulation MeSH
- Receptors, Antigen, T-Cell, alpha-beta genetics MeSH
- Receptors, Antigen, T-Cell genetics MeSH
- Reproducibility of Results MeSH
- High-Throughput Nucleotide Sequencing methods MeSH
- Bias MeSH
- Check Tag
- Adult MeSH
- Middle Aged MeSH
- Humans MeSH
- Male MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
- Research Support, N.I.H., Intramural MeSH
Monitoring the T cell receptor (TCR) repertoire in health and disease can provide key insights into adaptive immune responses, but the accuracy of current TCR sequencing (TCRseq) methods is unclear. In this study, we systematically compared the results of nine commercial and academic TCRseq methods, including six rapid amplification of complementary DNA ends (RACE)-polymerase chain reaction (PCR) and three multiplex-PCR approaches, when applied to the same T cell sample. We found marked differences in accuracy and intra- and inter-method reproducibility for T cell receptor α (TRA) and T cell receptor β (TRB) TCR chains. Most methods showed a lower ability to capture TRA than TRB diversity. Low RNA input generated non-representative repertoires. Results from the 5' RACE-PCR methods were consistent among themselves but differed from the RNA-based multiplex-PCR results. Using an in silico meta-repertoire generated from 108 replicates, we found that one genomic DNA-based method and two non-unique molecular identifier (UMI) RNA-based methods were more sensitive than UMI methods in detecting rare clonotypes, despite the better clonotype quantification accuracy of the latter.
Adaptive Immunity Group Central European Institute of Technology Brno Czechia
AP HP Hôpital Pitié Salpêtrière Biotherapy Paris France
Center of Life Sciences Skoltech Moscow Russia
Diagnostic and Research Institute of Pathology Medical University of Graz Graz Austria
Division of Cardiology Medical University of Graz Graz Austria
Division of Infection and Immunity University College London London UK
Sorbonne Université INSERM Immunology Immunopathology Immunotherapy Paris France
References provided by Crossref.org
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