Multiple transcription factor binding sites predict AID targeting in non-Ig genes

Aberrant targeting of the enzyme activation-induced cytidine deaminase (AID) results in the accumulation of somatic mutations in ≈ 25% of expressed genes in germinal center B cells. Observations in Ung(-/-) Msh2(-/-) mice suggest that many other genes efficiently repair AID-induced lesions, so that...

Full description

Saved in:
Bibliographic Details
Published in:The Journal of immunology (1950) 2013-04, Vol.190 (8), p.3878-3888
Main Authors: Duke, Jamie L, Liu, Man, Yaari, Gur, Khalil, Ashraf M, Tomayko, Mary M, Shlomchik, Mark J, Schatz, David G, Kleinstein, Steven H
Format: Article
Language:English
Subjects:
Animals
B-Lymphocyte Subsets - immunology
B-Lymphocyte Subsets - metabolism
Binding Sites - genetics
Binding Sites - immunology
Cytidine Deaminase - genetics
Cytidine Deaminase - metabolism
E-Box Elements - genetics
Genes, Immunoglobulin
Mice
Mice, Inbred BALB C
Mice, Knockout
Mice, Transgenic
Predictive Value of Tests
Somatic Hypermutation, Immunoglobulin
Transcription Factors - genetics
Transcription Factors - metabolism
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Aberrant targeting of the enzyme activation-induced cytidine deaminase (AID) results in the accumulation of somatic mutations in ≈ 25% of expressed genes in germinal center B cells. Observations in Ung(-/-) Msh2(-/-) mice suggest that many other genes efficiently repair AID-induced lesions, so that up to 45% of genes may actually be targeted by AID. It is important to understand the mechanisms that recruit AID to certain genes, because this mistargeting represents an important risk for genome instability. We hypothesize that several mechanisms combine to target AID to each locus. To resolve which mechanisms affect AID targeting, we analyzed 7.3 Mb of sequence data, along with the regulatory context, from 83 genes in Ung(-/-) Msh2(-/-) mice to identify common properties of AID targets. This analysis identifies three transcription factor binding sites (E-box motifs, along with YY1 and C/EBP-β binding sites) that may work together to recruit AID. Based on previous knowledge and these newly discovered features, a classification tree model was built to predict genome-wide AID targeting. Using this predictive model, we were able to identify a set of 101 high-interest genes that are likely targets of AID.
ISSN:0022-1767
1550-6606
DOI:10.4049/jimmunol.1202547