ArticlePLoS genetics2016
Strong Selection Significantly Increases Epistatic Interactions in the Long-Term Evolution of a Protein.
Article in PLoS genetics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed, 32 citations in OpenAlex.
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- Full-Length Envelope Analyzer (FLEA): A tool for longitudinal analysis of viral amplicons.PLoS computational biology · 2018Article
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- Highly expressed genes evolve under strong epistasis from a proteome-wide scan in E. coli.Scientific reports · 2017Article
- Inference of Epistatic Effects Leading to Entrenchment and Drug Resistance in HIV-1 Protease.Molecular biology and evolution · 2017Article
- Potts Hamiltonian models of protein co-variation, free energy landscapes, and evolutionary fitness.Current opinion in structural biology · 2017Review
- Shared Information between Residues Is Sufficient to Detect Pairwise Epistasis in a Protein.PLoS genetics · 2016Article
- Epistasis and Entropy.PLoS genetics · 2016Article
- What is information?†.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2016Article
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Authors and funding
2 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Epistatic interactions between residues determine a protein's adaptability and shape its evolutionary trajectory. When a protein experiences a changed environment, it is under strong selection to find a peak in the new fitness landscape. It has been shown that strong selection increases epistatic interactions as well as the ruggedness of the fitness landscape, but little is known about how the epistatic interactions change under selection in the long-term evolution of a protein. Here we analyze the evolution of epistasis in the protease of the human immunodeficiency virus type 1 (HIV-1) using protease sequences collected for almost a decade from both treated and untreated patients, to understand how epistasis changes and how those changes impact the long-term evolvability of a protein. We use an information-theoretic proxy for epistasis that quantifies the co-variation between sites, and show that positive information is a necessary (but not sufficient) condition that detects epistasis in most cases. We analyze the "fossils" of the evolutionary trajectories of the protein contained in the sequence data, and show that epistasis continues to enrich under strong selection, but not for proteins whose environment is unchanged. The increase in epistasis compensates for the information loss due to sequence variability brought about by treatment, and facilitates adaptation in the increasingly rugged fitness landscape of treatment. While epistasis is thought to enhance evolvability via valley-crossing early-on in adaptation, it can hinder adaptation later when the landscape has turned rugged. However, we find no evidence that the HIV-1 protease has reached its potential for evolution after 9 years of adapting to a drug environment that itself is constantly changing. We suggest that the mechanism of encoding new information into pairwise interactions is central to protein evolution not just in HIV-1 protease, but for any protein adapting to a changing environment.
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