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Open AccessJournal ArticleDOI

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

TLDR
It is shown that the sensitivity of sequence-based repertoire profiling is limited by both sequencing depth and sequencing accuracy, and a new, directly measured, lower limit on individual T-cell repertoire size is established.
Abstract
Massively parallel sequencing is a useful approach for characterizing T-cell receptor diversity. However, immune receptors are extraordinarily difficult sequencing targets because any given receptor variant may be present in very low abundance and may differ legitimately by only a single nucleotide. We show that the sensitivity of sequence-based repertoire profiling is limited by both sequencing depth and sequencing accuracy. At two timepoints, 1 wk apart, we isolated bulk PBMC plus naive (CD45RA+/CD45RO-) and memory (CD45RA-/CD45RO+) T-cell subsets from a healthy donor. From T-cell receptor beta chain (TCRB) mRNA we constructed and sequenced multiple libraries to obtain a total of 1.7 billion paired sequence reads. The sequencing error rate was determined empirically and used to inform a high stringency data filtering procedure. The error filtered data yielded 1,061,522 distinct TCRB nucleotide sequences from this subject which establishes a new, directly measured, lower limit on individual T-cell repertoire size and provides a useful reference set of sequences for repertoire analysis. TCRB nucleotide sequences obtained from two additional donors were compared to those from the first donor and revealed limited sharing (up to 1.1%) of nucleotide sequences among donors, but substantially higher sharing (up to 14.2%) of inferred amino acid sequences. For each donor, shared amino acid sequences were encoded by a much larger diversity of nucleotide sequences than were unshared amino acid sequences. We also observed a highly statistically significant association between numbers of shared sequences and shared HLA class I alleles.

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Citations
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Journal ArticleDOI

Fluctuating fitness shapes the clone-size distribution of immune repertoires

TL;DR: Effective models of somatic evolution where cell fate depends on an effective fitness are proposed and fluctuations in the fitness acting specifically on clones are identified as the essential ingredient leading to the observed distributions.
Journal ArticleDOI

Diversity and divergence of the glioma-infiltrating T-cell receptor repertoire

TL;DR: A TCR signature strongly inversely correlated with the VJ-independent divergence between the peripheral and tissue-infiltrating repertoires of patients is discovered, and this signature is detectable in peripheral blood and could serve as a means of noninvasively monitoring immune response in patients.
Journal ArticleDOI

Studying the antibody repertoire after vaccination: practical applications.

TL;DR: Recent findings based on antibody repertoire sequencing are reviewed, and potential applications of these new technologies and of the analyses of the increasing volume of antibody sequence data in the context of vaccine development are discussed.
Journal ArticleDOI

New tools for classification and monitoring of autoimmune diseases

TL;DR: This Review provides an introduction to these powerful technologies that could promote the identification of actionable biomarkers, including mass cytometry, protein arrays, and immunoglobulin and T-cell receptor high-throughput sequencing.
References
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Journal ArticleDOI

Clustal W and Clustal X version 2.0

TL;DR: The Clustal W and ClUSTal X multiple sequence alignment programs have been completely rewritten in C++ to facilitate the further development of the alignment algorithms in the future and has allowed proper porting of the programs to the latest versions of Linux, Macintosh and Windows operating systems.
Journal ArticleDOI

Base-calling of automated sequencer traces using Phred. I. accuracy assessment

TL;DR: In this article, a base-calling program for automated sequencer traces, phred, with improved accuracy was proposed. But it was not shown to achieve a lower error rate than the ABI software, averaging 40%-50% fewer errors in the data sets examined independent of position in read, machine running conditions, or sequencing chemistry.
Journal ArticleDOI

Base-Calling of Automated Sequencer Traces Using Phred. II. Error Probabilities

TL;DR: The ability to estimate a probability of error for each base-call, as a function of certain parameters computed from the trace data, is developed and implemented in the base-calling program.
Journal ArticleDOI

T-cell antigen receptor genes and T-cell recognition.

TL;DR: This view of T-cell recognition has implications for how the receptors might be selected in the thymus and how they (and immunoglobulins) may have arisen during evolution.
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