Published in

American Association of Immunologists, The Journal of Immunology, 3(201), p. 950-956, 2018

DOI: 10.4049/jimmunol.1800203

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Detecting Rare AID-Induced Mutations in B-Lineage Oncogenes from High-Throughput Sequencing Data Using the Detection of Minor Variants by Error Correction Method

This paper is made freely available by the publisher.
This paper is made freely available by the publisher.

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Data provided by SHERPA/RoMEO

Abstract

Abstract In B-lineage cells, the cytidine deaminase AID not only generates somatic mutations to variable regions of Ig genes but also inflicts, at a lower frequency, mutations to several non-Ig genes named AID off-targets, which include proto-oncogenes. High-throughput sequencing should be in principle the method of choice to detect and document these rare nucleotide substitutions. So far, high-throughput sequencing–based methods are impaired by a global sequencing error rate that usually covers the real mutation rate of AID off-target genes in activated B cells. We demonstrate the validity of a per-base background subtraction method called detection of minor variants by error correction (DeMinEr), which uses deep sequencing data from mutated and nonmutated samples to correct the substitution frequency at each nucleotide position along the sequenced region. Our DeMinEr method identifies somatic mutations at a frequency down to 0.02% at any nucleotide position within two off-target genes: Cd83 and Bcl6. Biological models and control conditions such as AID- and UNG-deficient mice validate the specificity and the sensitivity of our method. The high resolution and robustness of DeMinEr enable us to document fine effects such as age-dependent accumulation of mutations in these oncogenes in the mouse.