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Unifying model for molecular determinants of the preselection Vβ repertoire
Author(s) -
Suhasni Gopalakrishnan,
Kinjal Majumder,
Alexander V. Predeus,
Yue Huang,
Olivia I. Koues,
Jiyoti VermaGaur,
Salvatore Loguercio,
Andrew I. Su,
Ann J. Feeney,
Maxim N. Artyomov,
Eugene M. Oltz
Publication year - 2013
Publication title -
proceedings of the national academy of sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 5.011
H-Index - 771
eISSN - 1091-6490
pISSN - 0027-8424
DOI - 10.1073/pnas.1304048110
Subject(s) - chromatin , biology , genetics , repertoire , computational biology , gene , recombination , v(d)j recombination , recombination signal sequences , evolutionary biology , physics , recombination activating gene , acoustics
The primary antigen receptor repertoire is sculpted by the process of V(D)J recombination, which must strike a balance between diversification and favoring gene segments with specialized functions. The precise determinants of how often gene segments are chosen to complete variable region coding exons remain elusive. We quantified Vβ use in the preselection Tcrb repertoire and report relative contributions of 13 distinct features that may shape their recombination efficiencies, including transcription, chromatin environment, spatial proximity to their DβJβ targets, and predicted quality of recombination signal sequences (RSSs). We show that, in contrast to functional Vβ gene segments, all pseudo-Vβ segments are sequestered in transcriptionally silent chromatin, which effectively suppresses wasteful recombination. Importantly, computational analyses provide a unifying model, revealing a minimum set of five parameters that are predictive of Vβ use, dominated by chromatin modifications associated with transcription, but largely independent of precise spatial proximity to DβJβ clusters. This learned model-building strategy may be useful in predicting the relative contributions of epigenetic, spatial, and RSS features in shaping preselection V repertoires at other antigen receptor loci. Ultimately, such models may also predict how designed or naturally occurring alterations of these loci perturb the preselection use of variable gene segments.

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