ArticleMolecular biology and evolution2014
An experimentally informed evolutionary model improves phylogenetic fit to divergent lactamase homologs.
Article in Molecular biology and evolution, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.
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30 citing papers in PubMed, 48 citations in OpenAlex.
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- Deep mutationally scanned (DMS) CHIKV E3/E2 virus library maps viral amino acid preferences and predicts viral escape mutants of neutralizing CHIKV antibodies.bioRxiv : the preprint server for biology · 2024Article
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- An Improved Codon Modeling Approach for Accurate Estimation of the Mutation Bias.Molecular biology and evolution · 2022Article
- Shifts in amino acid preferences as proteins evolve: A synthesis of experimental and theoretical work.Protein science : a publication of the Protein Society · 2021Review
- Relative Model Fit Does Not Predict Topological Accuracy in Single-Gene Protein Phylogenetics.Molecular biology and evolution · 2020Article
- Implications of localized charge for human influenza A H1N1 hemagglutinin evolution: Insights from deep mutational scans.PLoS computational biology · 2020Article
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- Inferring the shape of global epistasis.Proceedings of the National Academy of Sciences of the United States of America · 2018Article
- Modeling site-specific amino-acid preferences deepens phylogenetic estimates of viral sequence divergence.Virus evolution · 2018Article
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- Correlation of fitness landscapes from three orthologous TIM barrels originates from sequence and structure constraints.Nature communications · 2017Article
- Identification of positive selection in genes is greatly improved by using experimentally informed site-specific models.Biology direct · 2017Article
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- Detecting Adaptation in Protein-Coding Genes Using a Bayesian Site-Heterogeneous Mutation-Selection Codon Substitution Model.Molecular biology and evolution · 2017Article
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1 author at 1 institution in 1 country.
Funding
Abstract
Phylogenetic analyses of molecular data require a quantitative model for how sequences evolve. Traditionally, the details of the site-specific selection that governs sequence evolution are not known a priori, making it challenging to create evolutionary models that adequately capture the heterogeneity of selection at different sites. However, recent advances in high-throughput experiments have made it possible to quantify the effects of all single mutations on gene function. I have previously shown that such high-throughput experiments can be combined with knowledge of underlying mutation rates to create a parameter-free evolutionary model that describes the phylogeny of influenza nucleoprotein far better than commonly used existing models. Here, I extend this work by showing that published experimental data on TEM-1 beta-lactamase (Firnberg E, Labonte JW, Gray JJ, Ostermeier M. 2014. A comprehensive, high-resolution map of a gene's fitness landscape. Mol Biol Evol. 31:1581-1592) can be combined with a few mutation rate parameters to create an evolutionary model that describes beta-lactamase phylogenies much better than most common existing models. This experimentally informed evolutionary model is superior even for homologs that are substantially diverged (about 35% divergence at the protein level) from the TEM-1 parent that was the subject of the experimental study. These results suggest that experimental measurements can inform phylogenetic evolutionary models that are applicable to homologs that span a substantial range of sequence divergence.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.