Empirical fitness landscapes reveal accessible evolutionary paths

By F. J. Poelwijk, D. J. Kiviet, Daniel M. Weinreich, S. Tans. 2007

554 citations recorded by the source corpus.

Subfields: Genetics, Molecular Biology, Sociology and Political Science

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Citations in the corpus

Coevolutionary Landscape Inference and the Context-Dependence of Mutations in Beta-Lactamase TEM-1 (2015, background): “…in evolutionary and medical biology: It has a key role in our understanding of mutational pathways accessible in the course of evolution [2–4], it can lead to the identification of genetic determinants of complex diseases based on rare variants [5], and it can guide towards the understanding…”
Inferring fitness landscapes by regression produces biased estimates of epistasis (2014, background): “We also investigated two other measures of epistasis: the number of local maxima in the fitness landscape (7, 8, 48, 70, 71) and the prevalence of sign epistasis between pairs of mutations (18, 41, 71, 72).”
How Protein Stability and New Functions Trade Off (2008, background): “proteins [1–6], but also in engineering, designing, and evolving,”
Predicting evolution (2017, background): “In the adaptive evolution of anti biotic resistance 66–69 , repeatability has been observed for some large-effect sequence changes, but more broadly for molecular resistance phenotypes 39,66–72 .”
The Speed of Evolution in Large Asexual Populations (2009, background): “The few exam ples available so far indicate that real fitness landscapes lie between these two e xtremes [48,55], which implies that the structure of the type space cannot be ignore d.”
Natural Selection Fails to Optimize Mutation Rates for Long-Term Adaptation on Rugged Fitness Landscapes (2008, background): “A growing body of experiments with viruses, bacteria, yeast, and higher eukaryotes shows that epistatic interactions are widespread and vary in their sign and intensity, implying that natural fitness landscapes are also often rugged [35,36,38].”
Do hormonal control systems produce evolutionary inertia? (2008, background): “New interactions within modules can evolve even if there are some seemingly awkward intermediate stages on the way to the new adaptive peak (Bridgham et al. 2006; Poelwijk et al. 2007).”
Germination, Postgermination Adaptation, and Species Ecological Ranges (2010, background): “…favoring early germination (Benard & Toft 2007, Castro 2006, Donohue 2002, Jones et al. 1997, Seiwa 1998, Shimono & Kudo 2003, Stanton 1985) intermediate germination time (Donohue et al. 2005, Fernandez-Quintanilla et al. 1986), and late germination (Purrington & Schmitt 1998, Weekley et al. 2007).”
Experimental interrogation of the path dependence and stochasticity of protein evolution using phage-assisted continuous evolution (2013, unknown): “These results indicate that the ability to benefit from F646L has already been lost by 96 h from all populations other than SP6 population 3, and therefore represents an example of “sign epistasis” (17), because F646L results in either increased or decreased activity, depending on genetic context.”
Adaptation in protein fitness landscapes is facilitated by indirect paths (2016, background): “As expected, the number of selectively inaccessible direct paths, i.e. paths that involve fitness declines, was found to be positively correlated with the ruggedness induced by pairwise epistasis (Figure 1 -figure supplement 6, Pearson correlation = 0.66, p=1.0 Â 10 À4 ) (Poelwijk et al., 2007) .”
Epistasis Among Adaptive Mutations in Deer Mouse Hemoglobin (2013, unknown): “1324 Nonadditive interactions between mutations (epistasis) can exert a strong influence on the rate and direction of evolutionary change (1, 2).”
Constraints on the evolution of azole resistance in plant pathogenic fungi (2013, background): “graminicola populations under selection by azoles is an elegant demonstration of these epistatic effects, where the phenotypic consequences of individual mutations are dependent on the genetic background in which they occur (Poelwijk et al., 2007).”