tetano
Editor, Senior Moderator
Mol Biol Evol. 2014 May 24. pii: msu173. [Epub ahead of print]
An experimentally determined evolutionary model dramatically improves phylogenetic fit.
Bloom JD.
Author information
Abstract
All modern approaches to molecular phylogenetics require a quantitative model for how genes evolve. Unfortunately, existing evolutionary models do not realistically represent the site-heterogeneous selection that governs actual sequence change. Attempts to remedy this problem have involved augmenting these models with a burgeoning number of free parameters. Here I demonstrate an alternative: experimental determination of a parameter-free evolutionary model via mutagenesis, functional selection, and deep sequencing. Using this strategy, I create an evolutionary model for influenza nucleoprotein that describes the gene phylogeny far better than existing models with dozens or even hundreds of free parameters. Emerging high-throughput experimental strategies such as the one employed here provide fundamentally new information that has the potential to transform the sensitivity of phylogenetic and genetic analyses.
? The Author(s) 2014. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.
PMID:
24859245
[PubMed - as supplied by publisher]
http://www.ncbi.nlm.nih.gov/pubmed/24859245
An experimentally determined evolutionary model dramatically improves phylogenetic fit.
Bloom JD.
Author information
Abstract
All modern approaches to molecular phylogenetics require a quantitative model for how genes evolve. Unfortunately, existing evolutionary models do not realistically represent the site-heterogeneous selection that governs actual sequence change. Attempts to remedy this problem have involved augmenting these models with a burgeoning number of free parameters. Here I demonstrate an alternative: experimental determination of a parameter-free evolutionary model via mutagenesis, functional selection, and deep sequencing. Using this strategy, I create an evolutionary model for influenza nucleoprotein that describes the gene phylogeny far better than existing models with dozens or even hundreds of free parameters. Emerging high-throughput experimental strategies such as the one employed here provide fundamentally new information that has the potential to transform the sensitivity of phylogenetic and genetic analyses.
? The Author(s) 2014. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.
PMID:
24859245
[PubMed - as supplied by publisher]
http://www.ncbi.nlm.nih.gov/pubmed/24859245