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Antigen receptor repertoire profiling from RNA-seq data

Nature Biotechnology volume 35, pages 908–911 (2017)Cite this article

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To the Editor:

Somatic recombination and accumulation of mutations in V-D-J segments result in vast heterogeneity of T-cell receptor (TCR) and immunoglobulin repertoires1,2. High-throughput profiling of immune receptors has become an important tool for studies of adaptive immunity and for the development of diagnostics, vaccines, and immunotherapies3,4,5,6,7. There are efficient molecular and software tools for the targeted sequencing of TCR and immunoglobulin repertoires6,8, including MiXCR, developed by our team9. However, sufficient amount and quality of tissue or extracted RNA or DNA are not always available for analysis.

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Figure 1: Sensitivity and specificity of extraction of TCR and immunoglobulin repertoires from tumor RNA-seq data.
Figure 2: Immune repertoire analysis in human melanoma and sorted mice T cells.

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Acknowledgements

Research supported by grant of the Ministry of Education and Science of the Russian Federation Number 14.W03.31.0005. Human melanoma SPX6730 and SPX8151 sample preparation supported by European Union's Horizon 2020 Research and Innovation Programme Number 633592 (to T.N. Schumacher). Foxp3yfpcre mice sample preparation supported by NIH/NCI Cancer Center Support Grant P30 CA008748 (to A.Y. Rudensky).

Author information

Author notes

  1. Dmitriy A Bolotin, Stanislav Poslavsky, Alexey N Davydov and Felix E Frenkel: These authors contributed equally to this work.

Authors and Affiliations

  1. MiLaboratory LLC, Skolkovo Innovation Center, Moscow, Russia

    Dmitriy A Bolotin, Stanislav Poslavsky & Mikhail Shugay

  2. Shemyakin and Ovchinnikov Institute of Bioorganic Chemistry, Moscow, Russia

    Dmitriy A Bolotin, Ekaterina V Putintseva, Anna S Obraztsova, Mikhail Shugay & Dmitriy M Chudakov

  3. Pirogov Russian National Research Medical University, Moscow, Russia

    Dmitriy A Bolotin, Stanislav Poslavsky, Mikhail Shugay & Dmitriy M Chudakov

  4. Central European Institute of Technology, Brno, Czech Republic

    Alexey N Davydov & Dmitriy M Chudakov

  5. BostonGene LLC, Lincoln, Massachusetts, USA

    Felix E Frenkel, Olga I Zolotareva & Ravshan I Ataullakhanov

  6. Division of Immunology, The Netherlands Cancer Institute, Amsterdam, The Netherlands

    Lorenzo Fanchi & Ton N Schumacher

  7. Howard Hughes Medical Institute and Immunology Program, Memorial Sloan-Kettering Cancer Center, New York, New York, USA

    Saskia Hemmers & Alexander Y Rudensky

  8. Centre for Genomic Regulation, The Barcelona Institute for Science and Technology, Barcelona, Spain

    Ekaterina V Putintseva

  9. Faculty of Bioengineering and Bioinformatics, Lomonosov Moscow State University, Moscow, Russia

    Anna S Obraztsova

  10. Nizhny Novgorod State Medical Academy, Nizhny Novgorod, Russia

    Mikhail Shugay & Dmitriy M Chudakov

  11. Center for Data-Intensive Biomedicine and Biotechnology, Skolkovo Institute of Science and Technology, Moscow, Russia

    Mikhail Shugay & Dmitriy M Chudakov

  12. Institute of Immunology FMBA, Moscow, Russia

    Ravshan I Ataullakhanov

  13. Faculties for Physics and Biology, Lomonosov Moscow State University, Moscow, Russia

    Ravshan I Ataullakhanov

  14. Ludwig Center at Memorial Sloan Kettering Cancer Center, Memorial Sloan Kettering Cancer Center, New York, New York, USA

    Alexander Y Rudensky

Authors
  1. Dmitriy A Bolotin
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  14. Dmitriy M Chudakov
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Corresponding author

Correspondence to Dmitriy M Chudakov.

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Competing interests

MiLaboratory LLC develops MiXCR software and has exclusive rights for its commercial distribution

Supplementary information

Supplementary Figures

Supplementary Figures 1–4, Supplementary Tables 1–3 and 5,Supplementary Notes 1–3 and Supplementary Methods (PDF 8248 kb)

Reporting Summary

Life sciences reporting summary (PDF 1295 kb)

Supplementary Table 4

Dominant and hypermutating intratumorally produced Ig clones (XLSX 27 kb)

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Bolotin, D., Poslavsky, S., Davydov, A. et al. Antigen receptor repertoire profiling from RNA-seq data. Nat Biotechnol 35, 908–911 (2017). https://doi.org/10.1038/nbt.3979

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