Literature DB >> 16873490

Mutation parameters from DNA sequence data using graph theoretic measures on lineage trees.

Reuma Magori-Cohen1, Yoram Louzoun, Steven H Kleinstein.   

Abstract

MOTIVATION: B cells responding to antigenic stimulation can fine-tune their binding properties through a process of affinity maturation composed of somatic hypermutation, affinity-selection and clonal expansion. The mutation rate of the B cell receptor DNA sequence, and the effect of these mutations on affinity and specificity, are of critical importance for understanding immune and autoimmune processes. Unbiased estimates of these properties are currently lacking due to the short time-scales involved and the small numbers of sequences available.
RESULTS: We have developed a bioinformatic method based on a maximum likelihood analysis of phylogenetic lineage trees to estimate the parameters of a B cell clonal expansion model, which includes somatic hypermutation with the possibility of lethal mutations. Lineage trees are created from clonally related B cell receptor DNA sequences. Important links between tree shapes and underlying model parameters are identified using mutual information. Parameters are estimated using a likelihood function based on the joint distribution of several tree shapes, without requiring a priori knowledge of the number of generations in the clone (which is not available for rapidly dividing populations in vivo). A systematic validation on synthetic trees produced by a mutating birth-death process simulation shows that our estimates are precise and robust to several underlying assumptions. These methods are applied to experimental data from autoimmune mice to demonstrate the existence of hypermutating B cells in an unexpected location in the spleen.

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Year:  2006        PMID: 16873490     DOI: 10.1093/bioinformatics/btl239

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


  2 in total

Review 1.  Getting started in computational immunology.

Authors:  Steven H Kleinstein
Journal:  PLoS Comput Biol       Date:  2008-08-29       Impact factor: 4.475

2.  Using Genotype Abundance to Improve Phylogenetic Inference.

Authors:  William S DeWitt; Luka Mesin; Gabriel D Victora; Vladimir N Minin; Frederick A Matsen
Journal:  Mol Biol Evol       Date:  2018-05-01       Impact factor: 16.240

  2 in total

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