Abstract
AbstractPhylogenetic models of gene family evolution based on birth-death processes (BDPs) vide an awkward fit to comparative genomic data sets. A central assumption of these models is the constant per-gene loss rate in any particular family. Because of the possibility of partial functional redundancy among gene family members, gene loss dynamics are however likely to be dependent on the number of genes in a family, and different variations of commonly employed BDP models indeed suggest this is the case. We propose a simple two-type branching process model to better approximate the stochastic evolution of gene families by gene duplication and loss and perform Bayesian statistical inference of model parameters in a phylogenetic context. We evaluate the statistical methods using simulated data sets and apply the model to gene family data for Drosophila, yeasts and primates, providing new quantitative insights in the long-term maintenance of duplicated genes.
Publisher
Cold Spring Harbor Laboratory
Cited by
3 articles.
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