An experimental phylogeny to benchmark ancestral sequence reconstruction

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 p...

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Bibliographic Details
Published in:Nature communications Vol. 7; no. 1; pp. 12847 - 6
Main Authors: Randall, Ryan N., Radford, Caelan E., Roof, Kelsey A., Natarajan, Divya K., Gaucher, Eric A.
Format: Journal Article
Language:English
Published: London Nature Publishing Group UK 15.09.2016
Nature Publishing Group
Nature Portfolio
Subjects:
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Accuracy
Algorithms
Amino acids
Base Sequence
Bayes Theorem
Bioengineering
Computer Simulation
Genetic Techniques
Genotypes
Humanities and Social Sciences
Leaves
Luminescent Proteins - genetics
multidisciplinary
Mutagenesis
Phenotype
Phylogeny
Proteins
Red Fluorescent Protein
Science
Science (multidisciplinary)
Taxonomy
Atlanta Georgia
United States > US
Georgia
ISSN:2041-1723, 2041-1723
Online Access:Get full text
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Summary: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. Methods for ancestral sequence reconstruction are currently tested with computer simulations, since true biological phylogenies are unknown. Here, Randall et al. build an experimental phylogeny to benchmark the performance of alternate ancestral sequence reconstruction algorithms in inferring ancestral genotypes and phenotypes.
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ISSN:2041-1723
2041-1723
DOI:10.1038/ncomms12847