Genesis of the alpha beta T-cell receptor

The T-cell (TCR) repertoire relies on the diversity of receptors composed of two chains, called $\alpha$ and $\beta$, to recognize pathogens. Using results of high throughput sequencing and computational chain-pairing experiments of human TCR repertoires, we quantitively characterize the $\alpha\beta$ generation process. We estimate the probabilities of a rescue recombination of the $\beta$ chain on the second chromosome upon failure or success on the first chromosome. Unlike $\beta$ chains, $\alpha$ chains recombine simultaneously on both chromosomes, resulting in correlated statistics of the two genes which we predict using a mechanistic model. We find that $\sim 28 \%$ of cells express both $\alpha$ chains. We report that clones sharing the same $\beta$ chain but different $\alpha$ chains are overrepresented, suggesting that they respond to common immune challenges. Altogether, our statistical analysis gives a complete quantitative mechanistic picture that results in the observed correlations in the generative process. We learn that the probability to generate any TCR$\alpha\beta$ is lower than $10^{-12}$ and estimate the generation diversity and sharing properties of the $\alpha\beta$ TCR repertoire

Inferring processes underlying B-cell repertoire diversity

We quantify the VDJ recombination and somatic hypermutation processes in human B-cells using probabilistic inference methods on high-throughput DNA sequence repertoires of human B-cell receptor heavy chains. Our analysis captures the statistical properties of the naive repertoire, first after its initial generation via VDJ recombination and then after selection for functionality. We also infer statistical properties of the somatic hypermutation machinery (exclusive of subsequent effects of selection). Our main results are the following: the B-cell repertoire is substantially more diverse than T-cell repertoires, due to longer junctional insertions; sequences that pass initial selection are distinguished by having a higher probability of being generated in a VDJ recombination event; somatic hypermutations have a non-uniform distribution along the V gene that is well explained by an independent site model for the sequence context around the hypermutation site.Comment: acknowledgement adde

Approches probabilistes du répertoire immunitaire adaptatif : une approche guidée par les données

An individual’s adaptive immune system needs to face repeated challenges of a constantly evolving environment with a virtually infinite number of threats. To achieve this task, the adaptive immune system relies on large diversity of B-cells and T-cells, each carrying a unique receptor specific to a small number of pathogens. These receptors are initially randomly built through the process of V(D)J recombination. This initial generated diversity is then narrowed down by a step of functional selection based on the receptors' folding properties and their ability to recognize self antigens. Upon recognition of a pathogen the B-cell will divide and its offsprings will undergo several rounds of successive somatic hypermutations and selection in an evolutionary process called affinity maturation. This work presents principled probabilistic approaches to infer the probability distribution underlying the recombination and somatic hypermutation processes from high throughput sequencing data using IGoR - a flexible software developed throughout the course of this PhD. IGoR has been developed as a versatile research tool and can encode a variety of models of different biological complexity to allow researchers in the field to characterize evermore precisely immune receptor repertoires. To motivate this data-driven approach we demonstrate that IGoR outperforms existing tools in accuracy and estimate the sample sizes needed for reliable repertoire characterization. Finally, using obtained model predictions, we show potential applications of these methods by demonstrating that homozygous twins share T-cells through cord blood, that the public core of the T cell repertoire is formed in the pre-natal period and finally estimate naive T cell clone lifetimes in human.Le système immunitaire de chaque individu doit faire face à des agressions répétées d'un environnement en constante évolution, constituant ainsi un nombre de menaces virtuellement infini. Afin de mener ce rôle à bien, le système immunitaire adaptatif s'appuie sur une énorme diversité de lymphocytes T et B. Chacune de ces cellules exhibe à sa surface un récepteur unique, créé aléatoirement via le processus de recombinaison V(D)J, et spécifique à un petit nombre de pathogènes seulement. La diversité initiale générée lors de ce processus de recombinaison est ensuite réduite par une étape de sélection fonctionnelle basée sur les propriétés de repliement du récepteur ainsi que ses capacités à interagir avec des protéines du soi. Pour les cellules B, cette diversité peut être à nouveau étendue après rencontre d'un pathogène lors du processus de maturation d'affinité durant lequel le récepteur subit des cycles successifs d'hypermutation et sélection. Ces travaux présentent des approches probabilistes visant à inférer les distributions de probabilités sous-tendant les processus de recombinaison et d'hypermutation à partir de données de séquençage haut débit. Ces approches ont donné naissance à IGoR, un logiciel polyvalent dont les performances dépassent celles des outils existants. En utilisant les modèles obtenus comme base, je présenterai comment ces derniers peuvent être utilisés afin d'étudier le vieillissement et évolution du répertoire immunitaire, la présence d'emprunte parentale lors de la recombinaison V(D)J ou encore pour démontrer que les jumeaux échangent des lymphocytes au cours de la vie fœtale

High-throughput immune repertoire analysis with IGoR

B and T cell receptor diversity can be studied by high-throughput immune receptor sequencing. Here, the authors develop a software tool, IGoR, that calculates the likelihoods of potential V(D)J recombination and somatic hypermutation scenarios from raw immune sequence reads

Particle approximation for first order stochastic partial differential equations

SIGLEAvailable at INIST (FR), Document Supply Service, under shelf-number : 14802 E, issue : a.1991 n.1502 / INIST-CNRS - Institut de l'Information Scientifique et TechniqueFRFranc

TCR nucleotide sequences shared between twins are statistically different from sequences shared between unrelated individuals.

<p>Distribution of log₁₀ <i>P</i>_gen, with <i>P</i>_gen the probability that a sequence is generated by the VJ recombination process, for shared out-of-frame TCR alpha clonotypes between one individual and the other five. While the distribution of shared sequences between unrelated individuals (red curves) is well explained by coincidental convergent recombination as predicted by our stochastic model (blue), sequences shared between two twins (green) have an excess of low probability sequences: 31 sequences with log₁₀ <i>P</i>_gen < −10. For comparison the distribution of <i>P</i>_gen in regular (not necessarily shared) sequences is shown in black.</p