Analytical methods for studying the evolution of paralogs using duplicate gene datasets.

Abstract

Gene duplication is widely viewed as an important source of raw material for functional innovation in proteins because at least some duplicate copies will evolve new or slightly modified functions. The study of the molecular processes by which functional innovation occurs interests both evolutionary biologists and protein chemists, and the development of methods to investigate these processes has led to a productive meeting of disciplines and an availability of complementary approaches for exploring datasets. This has resulted in insights into past events, prediction of current function, and prediction of future change. The methods fall broadly into two categories: those that rely on detection of shifts in selective constraints and those that rely on detection of correlations between molecular changes and functional shifts. Strengths and limitations of the methods are evaluated here in the context of the question being addressed, the input required, and the specific metric that is evaluated in each test.