A Probabilistic Model for Gene Family Evolution

• Activity Number: 594
• Type: Topic Contributed
• Date/Time: Wednesday, August 12, 2015 : 2:00 PM to 3:50 PM
• Sponsor: Biometrics Section
• Author(s): Liang Liu* and Jing Zhao and David Liberles and Ashley Teufel and Lili Yu
• Companies: University of Georgia and University of Georgia and Temple University and Temple University and Georgia Southern university
• Keywords: birth and death process ; gene duplication

Abstract

Gene duplication played a pivotal role in evolution (Ohta 1989). The widespread existence of gene families suggests that the newly arisen gene duplicates are the major contributors to evolutionary novelties (Lynch et al. 2001; Hurles 2004). The extra gene copies resulted from duplication provided raw genetic material that evolutionary forces can act on. Although a majority of duplicate genes may be silenced by degenerative mutations, some duplicated genes are able to evolve novel functions permanently preserved in the population (Lynch 2002). Accurately estimating the timing and mode of gene duplications along the evolutionary history of species can provide invaluable information about underlying mechanisms by which the genomes of organisms evolved and the genes with novel functions arose (Hahn et al. 2005). As genomic data become increasingly available, it is desirable to build a model based on a stochastic process that is a good approximation to the real biological process of gene duplication and loss. Such probabilistic model can both add biological realism to improve the fit of the model to the data as well as enable mechanistic inference that is currently not possible.