Andrew M Ritchie1, Tristan L Stark1, David A Liberles2. 1. Department of Biology, Temple University, 1900 North 12th Street, Philadelphia, PA, USA. 2. Department of Biology, Temple University, 1900 North 12th Street, Philadelphia, PA, USA. daliberles@temple.edu.
Abstract
BACKGROUND: Recovering the historical patterns of selection acting on a protein coding sequence is a major goal of evolutionary biology. Mutation-selection models address this problem by explicitly modelling fixation rates as a function of site-specific amino acid fitness values.However, they are restricted in their utility for investigating directional evolution because they require prior knowledge of the locations of fitness changes in the lineages of a phylogeny. RESULTS: We apply a modified mutation-selection methodology that relaxes assumptions of equlibrium and time-reversibility. Our implementation allows us to identify branches where adaptive or compensatory shifts in the fitness landscape have taken place, signalled by a change in amino acid fitness profiles. Through simulation and analysis of an empirical data set of [Formula: see text]-lactamase genes, we test our ability to recover the position of adaptive events within the tree and successfully reconstruct initial codon frequencies and fitness profile parameters generated under the non-stationary model. CONCLUSION: We demonstrate successful detection of selective shifts and identification of the affected branch on partitions of 300 codons or more. We successfully reconstruct fitness parameters and initial codon frequencies in simulated data and demonstrate that failing to account for non-equilibrium evolution can increase the error in fitness profile estimation. We also demonstrate reconstruction of plausible shifts in amino acid fitnesses in the bacterial [Formula: see text]-lactamase family and discuss some caveats for interpretation.
BACKGROUND: Recovering the historical patterns of selection acting on a protein coding sequence is a major goal of evolutionary biology. Mutation-selection models address this problem by explicitly modelling fixation rates as a function of site-specific amino acid fitness values.However, they are restricted in their utility for investigating directional evolution because they require prior knowledge of the locations of fitness changes in the lineages of a phylogeny. RESULTS: We apply a modified mutation-selection methodology that relaxes assumptions of equlibrium and time-reversibility. Our implementation allows us to identify branches where adaptive or compensatory shifts in the fitness landscape have taken place, signalled by a change in amino acid fitness profiles. Through simulation and analysis of an empirical data set of [Formula: see text]-lactamase genes, we test our ability to recover the position of adaptive events within the tree and successfully reconstruct initial codon frequencies and fitness profile parameters generated under the non-stationary model. CONCLUSION: We demonstrate successful detection of selective shifts and identification of the affected branch on partitions of 300 codons or more. We successfully reconstruct fitness parameters and initial codon frequencies in simulated data and demonstrate that failing to account for non-equilibrium evolution can increase the error in fitness profile estimation. We also demonstrate reconstruction of plausible shifts in amino acid fitnesses in the bacterial [Formula: see text]-lactamase family and discuss some caveats for interpretation.
Authors: Valeria A Risso; Jose A Gavira; Diego F Mejia-Carmona; Eric A Gaucher; Jose M Sanchez-Ruiz Journal: J Am Chem Soc Date: 2013-02-14 Impact factor: 15.419
Authors: Sangeet Lamichhaney; Jonas Berglund; Markus Sällman Almén; Khurram Maqbool; Manfred Grabherr; Alvaro Martinez-Barrio; Marta Promerová; Carl-Johan Rubin; Chao Wang; Neda Zamani; B Rosemary Grant; Peter R Grant; Matthew T Webster; Leif Andersson Journal: Nature Date: 2015-02-11 Impact factor: 49.962