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1. Epistasis Creates Invariant Sites and Modulates the Rate of Molecular Evolution

   https://doi.org/10.1093/molbev/msac106  

   Patel, Ravi; Carnevale, Vincenzo; Kumar, Sudhir (May 2022, Molecular Biology and Evolution)

   Ozkan, Banu (Ed.)

   Abstract Invariant sites are a common feature of amino acid sequence evolution. The presence of invariant sites is frequently attributed to the need to preserve function through site-specific conservation of amino acid residues. Amino acid substitution models without a provision for invariant sites often fit the data significantly worse than those that allow for an excess of invariant sites beyond those predicted by models that only incorporate rate variation among sites (e.g., a Gamma distribution). An alternative is epistasis between sites to preserve residue interactions that can create invariant sites. Through computer-simulated sequence evolution, we evaluated the relative effects of site-specific preferences and site-site couplings in the generation of invariant sites and the modulation of the rate of molecular evolution. In an analysis of ten major families of protein domains with diverse sequence and functional properties, we find that the negative selection imposed by epistasis creates many more invariant sites than site-specific residue preferences alone. Further, epistasis plays an increasingly larger role in creating invariant sites over longer evolutionary periods. Epistasis also dictates rates of domain evolution over time by exerting significant additional purifying selection to preserve site couplings. These patterns illuminate the mechanistic role of epistasis in the processes underlying observed site invariance and evolutionary rates. 

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2. The effectiveness of selection in a species affects the direction of amino acid frequency evolution

   https://doi.org/10.1101/2023.02.01.526552  

   McShea, Hanon; Wheeler, Andrew L; Goodman, Peter; Weibel, Catherine; Wehbi, Sawsan; James, Jennifer E; Huttley, Gavin; Masel, Joanna (February 2023, bioRxiv)

   Nearly neutral theory predicts that species with higher effective population size (N_e) are better at purging slightly deleterious mutations. We compare evolution in high N_e vs. low-N_e vertebrates to reveal subtle selective preferences among amino acids. We take three complementary approaches. First, we fit non-stationary substitution models using maximum likelihood, comparing the high-N_e clade of rodents and lagomorphs to its low-N_e sister clade of primates and colugos. Second, we compared evolutionary outcomes across a wider range of vertebrates, via correlations between amino acid frequencies and N_e. Third, we dissected which amino acids substitutions occurred in human, chimpanzee, mouse, and rat, as scored by parsimony – this also enabled comparison to a historical paper. All methods agree on amino acid preference under more effective selection. Preferred amino acids are less costly to synthesize and use GC-rich codons, which are hard to maintain under AT-biased mutation. These factors explain 85% of the variance in amino acid preferences. Parsimony-induced bias in the historical study produces an apparent reduction in structural disorder, perhaps driven by slightly deleterious substitutions in rapidly evolving regions. Within highly exchangeable pairs of amino acids, arginine is strongly preferred over lysine, aspartate over glutamate, and valine over isoleucine, consistent with more effective selection preferring a marginally larger free energy of folding. Two of these preferences (K→R and I→V), but not a third (E→D) match differences between thermophiles and mesophilic relatives. These results reveal the biophysical consequences of mutation-selection-drift balance, and demonstrate the utility of nearly neutral theory for understanding protein evolution. 

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3. Mutation pressure, drift, and the pace of molecular coevolution

   https://doi.org/10.1073/pnas.2306741120  

   Lynch, Michael (July 2023, Proceedings of the National Academy of Sciences)

   Most aspects of the molecular biology of cells involve tightly coordinated intermolecular interactions requiring specific recognition at the nucleotide and/or amino acid levels. This has led to long-standing interest in the degree to which constraints on interacting molecules result in conserved vs. accelerated rates of sequence evolution, with arguments commonly being made that molecular coevolution can proceed at rates exceeding the neutral expectation. Here, a fairly general model is introduced to evaluate the degree to which the rate of evolution at functionally interacting sites is influenced by effective population sizes ( N e ), mutation rates, strength of selection, and the magnitude of recombination between sites. This theory is of particular relevance to matters associated with interactions between organelle- and nuclear-encoded proteins, as the two genomic environments often exhibit dramatic differences in the power of mutation and drift. Although genes within low N e environments can drive the rate of evolution of partner genes experiencing higher N e , rates exceeding the neutral expectation require that the former also have an elevated mutation rate. Testable predictions, some counterintuitive, are presented on how patterns of coevolutionary rates should depend on the relative intensities of drift, selection, and mutation. 

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4. Energy landscape reshaped by strain-specific mutations underlies epistasis in NS1 evolution of influenza A virus

   https://doi.org/10.1038/s41467-022-33554-9  

   Kim, Iktae; Dubrow, Alyssa; Zuniga, Bryan; Zhao, Baoyu; Sherer, Noah; Bastiray, Abhishek; Li, Pingwei; Cho, Jae-Hyun (December 2022, Nature Communications)

   Abstract Elucidating how individual mutations affect the protein energy landscape is crucial for understanding how proteins evolve. However, predicting mutational effects remains challenging because of epistasis—the nonadditive interactions between mutations. Here, we investigate the biophysical mechanism of strain-specific epistasis in the nonstructural protein 1 (NS1) of influenza A viruses (IAVs). We integrate structural, kinetic, thermodynamic, and conformational dynamics analyses of four NS1s of influenza strains that emerged between 1918 and 2004. Although functionally near-neutral, strain-specific NS1 mutations exhibit long-range epistatic interactions with residues at the p85β-binding interface. We reveal that strain-specific mutations reshaped the NS1 energy landscape during evolution. Using NMR spin dynamics, we find that the strain-specific mutations altered the conformational dynamics of the hidden network of tightly packed residues, underlying the evolution of long-range epistasis. This work shows how near-neutral mutations silently alter the biophysical energy landscapes, resulting in diverse background effects during molecular evolution. 

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5. Inferring the number and position of changes in selective regime in a non-equilibrium mutation-selection framework

   https://doi.org/10.1186/s12862-021-01770-4  

   Ritchie, Andrew M.; Stark, Tristan L.; Liberles, David A. (March 2021, BMC Ecology and Evolution)

   Abstract BackgroundRecovering the historical patterns of selection acting on a protein coding sequence is a major goal of evolutionary biology. Mutation-selection models address this problem by explicitly modelling fixation rates as a function of site-specific amino acid fitness values.However, they are restricted in their utility for investigating directional evolution because they require prior knowledge of the locations of fitness changes in the lineages of a phylogeny. ResultsWe apply a modified mutation-selection methodology that relaxes assumptions of equlibrium and time-reversibility. Our implementation allows us to identify branches where adaptive or compensatory shifts in the fitness landscape have taken place, signalled by a change in amino acid fitness profiles. Through simulation and analysis of an empirical data set of$$\beta $$ $\beta$-lactamase genes, we test our ability to recover the position of adaptive events within the tree and successfully reconstruct initial codon frequencies and fitness profile parameters generated under the non-stationary model. ConclusionWe demonstrate successful detection of selective shifts and identification of the affected branch on partitions of 300 codons or more. We successfully reconstruct fitness parameters and initial codon frequencies in simulated data and demonstrate that failing to account for non-equilibrium evolution can increase the error in fitness profile estimation. We also demonstrate reconstruction of plausible shifts in amino acid fitnesses in the bacterial$$\beta $$ $\beta$-lactamase family and discuss some caveats for interpretation. 

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