Literature DB >> 33603748

Correlations in Somatic Hypermutation Between Sites in IGHV Genes Can Be Explained by Interactions Between AID and/or Polη Hotspots.

Artem Krantsevich1, Catherine Tang1, Thomas MacCarthy1,2.   

Abstract

The somatic hypermutation (SHM) of Immunoglobulin (Ig) genes is a key process during antibody affinity maturation in B cells. The mutagenic enzyme activation induced deaminase (AID) is required for SHM and has a preference for WRC hotspots in DNA. Error-prone repair mechanisms acting downstream of AID introduce further mutations, including DNA polymerase eta (Polη), part of the non-canonical mismatch repair pathway (ncMMR), which preferentially generates mutations at WA hotspots. Previously proposed mechanistic models lead to a variety of predictions concerning interactions between hotspots, for example, how mutations in one hotspot will affect another hotspot. Using a large, high-quality, Ig repertoire sequencing dataset, we evaluated pairwise correlations between mutations site-by-site using an unbiased measure similar to mutual information which we termed "mutational association" (MA). Interactions are dominated by relatively strong correlations between nearby sites (short-range MAs), which can be almost entirely explained by interactions between overlapping hotspots for AID and/or Polη. We also found relatively weak dependencies between almost all sites throughout each gene (longer-range MAs), although these arise mostly as a statistical consequence of high pairwise mutation frequencies. The dominant short-range interactions are also highest within the most highly mutating IGHV sub-regions, such as the complementarity determining regions (CDRs), where there is a high hotspot density. Our results suggest that the hotspot preferences for AID and Polη have themselves evolved to allow for greater interactions between AID and/or Polη induced mutations.
Copyright © 2021 Krantsevich, Tang and MacCarthy.

Entities:  

Keywords:  B cell receptor; activation-induced deaminase; computational immunology; immunoglobulin heavy chain; overlapping hotspots; somatic hypermutation

Mesh:

Substances:

Year:  2021        PMID: 33603748      PMCID: PMC7884765          DOI: 10.3389/fimmu.2020.618409

Source DB:  PubMed          Journal:  Front Immunol        ISSN: 1664-3224            Impact factor:   7.561


  41 in total

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Journal:  Nat Immunol       Date:  2001-06       Impact factor: 25.606

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Journal:  Cell Cycle       Date:  2009-10-29       Impact factor: 4.534

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Journal:  Cell       Date:  2000-09-01       Impact factor: 41.582

5.  Overlapping hotspots in CDRs are critical sites for V region diversification.

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Journal:  Proc Natl Acad Sci U S A       Date:  2015-02-02       Impact factor: 11.205

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Journal:  Nat Immunol       Date:  2002-07-29       Impact factor: 25.606

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Journal:  Nature       Date:  2003-06-18       Impact factor: 49.962

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Journal:  J Biol Chem       Date:  2013-08-26       Impact factor: 5.157

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Journal:  J Exp Med       Date:  2005-04-11       Impact factor: 14.307

10.  Sequence-Intrinsic Mechanisms that Target AID Mutational Outcomes on Antibody Genes.

Authors:  Leng-Siew Yeap; Joyce K Hwang; Zhou Du; Robin M Meyers; Fei-Long Meng; Agnė Jakubauskaitė; Mengyuan Liu; Vinidhra Mani; Donna Neuberg; Thomas B Kepler; Jing H Wang; Frederick W Alt
Journal:  Cell       Date:  2015-11-12       Impact factor: 41.582

View more
  1 in total

1.  Deep learning model of somatic hypermutation reveals importance of sequence context beyond hotspot targeting.

Authors:  Catherine Tang; Artem Krantsevich; Thomas MacCarthy
Journal:  iScience       Date:  2021-12-20
  1 in total

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