title: An experimental phylogeny to benchmark ancestral sequence reconstruction.
abstract: Ancestral sequence reconstruction (ASR) is a still-burgeoning method that has revealed many key mechanisms of molecular evolution. One criticism of the approach is an inability to validate its algorithms within a biological context as opposed to a computer simulation. Here we build an experimental phylogeny using the gene of a single red fluorescent protein to address this criticism. The evolved phylogeny consists of 19 operational taxonomic units (leaves) and 17 ancestral bifurcations (nodes) that display a wide variety of fluorescent phenotypes. The 19 leaves then serve as 'modern' sequences that we subject to ASR analyses using various algorithms and to benchmark against the known ancestral genotypes and ancestral phenotypes. We confirm computer simulations that show all algorithms infer ancient sequences with high accuracy, yet we also reveal wide variation in the phenotypes encoded by incorrectly inferred sequences. Specifically, Bayesian methods incorporating rate variation significantly outperform the maximum parsimony criterion in phenotypic accuracy. Subsampling of extant sequences had minor effect on the inference of ancestral sequences.
authors.affiliation: School of Biological Sciences, Georgia Institute of Technology, Atlanta, Georgia 30332, USA.
authors.forename: Ryan N
authors.initials: RN
authors.lastname: Randall
authors.affiliation: School of Biological Sciences, Georgia Institute of Technology, Atlanta, Georgia 30332, USA.
authors.forename: Caelan E
authors.initials: CE
authors.lastname: Radford
authors.affiliation: School of Biological Sciences, Georgia Institute of Technology, Atlanta, Georgia 30332, USA.
authors.forename: Kelsey A
authors.initials: KA
authors.lastname: Roof
authors.affiliation: School of Biological Sciences, Georgia Institute of Technology, Atlanta, Georgia 30332, USA.
authors.forename: Divya K
authors.initials: DK
authors.lastname: Natarajan
authors.affiliation: School of Biological Sciences, Georgia Institute of Technology, Atlanta, Georgia 30332, USA.|Institute for Bioengineering and Biosciences, Georgia Institute of Technology, Atlanta, Georgia 30332, USA.
authors.forename: Eric A
authors.initials: EA
authors.lastname: Gaucher
mesh_terms: D000465:Algorithms; D001483:Base Sequence; D001499:Bayes Theorem; D003198:Computer Simulation; D005821:Genetic Techniques; D008164:Luminescent Proteins / Q000235:genetics*; D010641:Phenotype; D010802:Phylogeny; D000097573:Red Fluorescent Protein
chemical_list: D008164:Luminescent Proteins; D000097573:Red Fluorescent Protein