The meeting was initiated by Felix Breden, Jamie Scott, and Thomas Kepler to plan for a larger community meeting that would bring together a wide range of stakeholders interested in the use of HTS technologies to study BCR and TCR repertoires. Hundreds of studies are being published without common rules or standard procedures for the acquisition, storage, annotation, or sharing of the associated AIRR-seq data sets.Įfforts to organize the AIRR Community 12 formally began in September 2014 with a planning meeting held at the Interdisciplinary Research in the Mathematical and Computational Sciences Centre of Simon Fraser University (Burnaby, British Columbia, Canada). However, the ability to generate these data has outpaced the infrastructure available to manage it. With high-throughput technologies generating large, complex data sets, AIRR-seq has led to the development of a diverse set of sample-processing strategies 9 and bioinformatics data analysis tools 10, 11. Profiling of the AIRR with HTS (AIRR-seq) has since become an important part of basic and clinical immunology research, including vaccine design, therapeutic antibody discovery, minimal-residual disease detection, and monitoring of responses to therapy 4, 6– 8.
With the advent of high-throughput sequencing (HTS), it became possible to characterize the AIRR at unprecedented depth, with typical runs generating tens to hundreds of millions of receptor sequences 6. For decades, characterization of the AIRR relied on low-resolution approaches such as flow cytometry, spectratyping, and Sanger sequencing. The collection of BCRs and TCRs in an individual forms the adaptive immune receptor repertoire (AIRR), which is capable of recognizing a vast array of antigens, including pathogens, auto-antigens, allergens, toxins, and tumors 4, 5. These receptors are produced by somatic gene-segment rearrangement that generates unique antigen-specific variable regions 2, 3. B and T cells are the two pillars of the adaptive immune system, and both express antigen-specific receptors at their surface, namely, B cell receptors (BCRs) and T cell receptors (TCRs), respectively. Therefore, partial CDR3 sequences, such as those contained in the output of TRUST v2.1, may be valuable when seeking to gain insights into the frequency of shared specificities.Antigen specificity is a cardinal feature of adaptive immunity that underlies immune homeostasis and control of pathogenic attack in higher vertebrates 1. This is because structural studies indicate that only a small region in the complete CDR3 makes contact with the antigen peptide 5, 6, and the recent GLIPH (grouping of lymphocyte interactions by paratope hotspots) 5 method can cluster TCRs with likely shared specificity from enriched local motifs within many distinct CDR3 molecules. We also point out that partial CDR3 sequences of reasonable length (6–30 amino acids) and perfect match to a subregion of the respective CDR3 molecule are informative for modeling TCR binding specificity. However, we would note that single-chain CDR3 from bulk RNA-seq may also not be ideal to identify a unique clonotype because, for a strict definition of clonotype, generally both chains would be required. We recognize that partial CDR3 sequences or reads that extend beyond the accepted limits of CDR3 cannot be unambiguously counted as unique clonotypes. 1), which were considered “non-canonical unconfirmed” by Bolotin et al. The output of TRUST v2.1 contains reads with V or J gene motifs and partial CDR3 sequences ( Supplementary Fig.
TRUST uses TCR variable (V) and joining (J) gene motifs to search and annotate CDR3-containing reads and performs de novo assembly on the CDR3-overlapping reads.
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