Models for gene duplication when dosage balance works as a transition state to subsequent neo- or sub-functionalization. Issue 1 (December 2016)

• Record Type: Journal Article
• Authors: Teufel, Ashley; Liu, Liang; Liberles, David
• Is Part Of: BMC evolutionary biology. Volume 16:Issue 1(2016)
• Page Start: 1
• Page End: 8
• Publication Date: 2016-12
• Subjects: Duplicate gene retention -- Protein complex -- Functional change -- Probabilistic model -- Birth-death process; Evolution (Biology) -- Periodicals; 576.805
• DOI: 10.1186/s12862-016-0616-1
• Languages: English
• ISSNs: 1471-2148

Abstract

Abstract Background Dosage balance has been described as an important process for the retention of duplicate genes after whole genome duplication events. However, dosage balance is only a temporary mechanism for duplicate gene retention, as it ceases to function following the stochastic loss of interacting partners, as dosage balance itself is lost with this event. With the prolonged period of retention, on the other hand, there is the potential for the accumulation of substitutions which upon release from dosage balance constraints, can lead to either subsequent neo-functionalization or sub-functionalization. Mechanistic models developed to date for duplicate gene retention treat these processes independently, but do not describe dosage balance as a transition state to eventual functional change. Results Here a model for these processes (dosage plus neofunctionalization and dosage plus subfunctionalization) has been built within an existing framework. Because of the computational complexity of these models, a simpler modeling framework that captures the same information is also proposed. This model is integrated into a phylogenetic birth-death model, expanding the range of available models. Conclusions Including further levels of biological reality in methods for gene tree/species tree reconciliation should not only increase the accuracy of estimates of the timing and evolutionary history of genes but can also offer insight into how genes and genomes evolve. These new models add to the tool box for characterizing mechanisms of duplicate gene retention probabilistically.