Search bioRxivSearch

Biology subjects

Marcou, Q.

Publications and source records attributed to Marcou, Q..

2 recordsLinked to original sources

Genesis of the αβ T-cell receptor

The T-cell (TCR) repertoire relies on the diversity of receptors composed of two chains, called and {beta}, to recognize pathogens. Using results of high throughput sequencing and computational chain-pairing experiments of human TCR repertoires, we quantitively characterize the {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, chains recombine simultaneously on both chromosomes, resulting in correlated statistics of the two genes which we predict using a mechanistic model. We find that[~] 28% of cells express both chains. 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{beta} is lower than 10-12 and estimate the generation diversity and sharing properties of the {beta} TCR repertoire.

immunology

IGoR: A Tool For High-Throughput Immune Repertoire Analysis

High throughput immune repertoire sequencing is promising to lead to new statistical diagnostic tools for medicine and biology. Successful implementations of these methods require a correct characterization, analysis and interpretation of these datasets. We present IGoR - a new comprehensive tool that takes B or T-cell receptors sequence reads and quantitatively characterizes the statistics of receptor generation from both cDNA and gDNA. It probabilistically annotates sequences and its modular structure can investigate models of increasing biological complexity for different organisms. For B-cells IGoR returns the hypermutation statistics, which we use to reveal co-localization of hypermutations along the sequence. We demonstrate that IGoR outperforms existing tools in accuracy and estimate the sample sizes needed for reliable repertoire characterization.

immunology