Mean-field methods in evolutionary duplication-innovation-loss models for the genome-level repertoire of protein domains

TL;DR

This paper combines mean-field and simulation methods to analyze models of genome evolution, focusing on duplication, innovation, and loss of protein domain classes, to explain observed scaling behaviors across species.

Contribution

It introduces a unified approach to study genome-level protein domain repertoire models, highlighting the effects of element loss and class specificity on scaling behaviors.

Findings

Models reproduce observed genome domain scaling patterns

Loss of elements significantly impacts model outcomes

Class specificity influences the dynamics of domain repertoires

Abstract

We present a combined mean-field and simulation approach to different models describing the dynamics of classes formed by elements that can appear, disappear or copy themselves. These models, related to a paradigm duplication-innovation model known as Chinese Restaurant Process, are devised to reproduce the scaling behavior observed in the genome-wide repertoire of protein domains of all known species. In view of these data, we discuss the qualitative and quantitative differences of the alternative model formulations, focusing in particular on the roles of element loss and of the specificity of empirical domain classes.