Abstract:Even if a species' phenotype does not change over evolutionary time, the underlying mechanism may change, as distinct molecular pathways can realize identical phenotypes. Here we use quantitative genetics and linear system theory to study how a gene network underlying a conserved phenotype evolves, as the genetic drift of small changes to these molecular pathways cause a population to explore the set of mechanisms with identical phenotypes. To do this, we model an organism's internal state as a linear system o… Show more
“…Previous authors have noted that Fisher's model predicts this pattern (Barton 2001; Fraïsse et al. 2016b; Schiffman and Ralph 2017), and here, we extend this insight to give formal conditions for Haldane's Rule. We will assume identical selection in both sexes, and that pure‐species individuals of both sexes have the same fitness.…”
Section: Results With Haploid Geneticsmentioning
confidence: 60%
“…For example, previous authors have shown that Fisher's model predicts Haldane's Rule: the tendency of sex‐specific breakdown to appear in the heterogametic sex (Haldane 1922; Turelli and Orr 2000; Barton 2001; Fraïsse et al. 2016b; Schiffman and Ralph 2017; see Fig. 1 C).…”
Natural selection plays a variety of roles in hybridization, speciation, and admixture. Most research has focused on two extreme cases: crosses between closely related inbred lines, where hybrids are fitter than their parents, or crosses between effectively isolated species, where hybrids suffer severe breakdown. But many natural populations must fall into intermediate regimes, with multiple types of gene interaction, and these are more difficult to study. Here, we develop a simple fitness landscape model, and show that it naturally interpolates between previous modeling approaches, which were designed for the extreme cases, and invoke either mildly deleterious recessives, or discrete hybrid incompatibilities. Our model yields several new predictions, which we test with genomic data from Mytilus mussels, and published data from plants (Zea, Populus, and Senecio) and animals (Mus, Teleogryllus, and Drosophila). The predictions are generally supported, and the model explains a number of surprising empirical patterns. Our approach enables novel and complementary uses of genome‐wide datasets, which do not depend on identifying outlier loci, or “speciation genes” with anomalous effects. Given its simplicity and flexibility, and its predictive successes with a wide range of data, the approach should be readily extendable to other outstanding questions in the study of hybridization.
“…Previous authors have noted that Fisher's model predicts this pattern (Barton 2001; Fraïsse et al. 2016b; Schiffman and Ralph 2017), and here, we extend this insight to give formal conditions for Haldane's Rule. We will assume identical selection in both sexes, and that pure‐species individuals of both sexes have the same fitness.…”
Section: Results With Haploid Geneticsmentioning
confidence: 60%
“…For example, previous authors have shown that Fisher's model predicts Haldane's Rule: the tendency of sex‐specific breakdown to appear in the heterogametic sex (Haldane 1922; Turelli and Orr 2000; Barton 2001; Fraïsse et al. 2016b; Schiffman and Ralph 2017; see Fig. 1 C).…”
Natural selection plays a variety of roles in hybridization, speciation, and admixture. Most research has focused on two extreme cases: crosses between closely related inbred lines, where hybrids are fitter than their parents, or crosses between effectively isolated species, where hybrids suffer severe breakdown. But many natural populations must fall into intermediate regimes, with multiple types of gene interaction, and these are more difficult to study. Here, we develop a simple fitness landscape model, and show that it naturally interpolates between previous modeling approaches, which were designed for the extreme cases, and invoke either mildly deleterious recessives, or discrete hybrid incompatibilities. Our model yields several new predictions, which we test with genomic data from Mytilus mussels, and published data from plants (Zea, Populus, and Senecio) and animals (Mus, Teleogryllus, and Drosophila). The predictions are generally supported, and the model explains a number of surprising empirical patterns. Our approach enables novel and complementary uses of genome‐wide datasets, which do not depend on identifying outlier loci, or “speciation genes” with anomalous effects. Given its simplicity and flexibility, and its predictive successes with a wide range of data, the approach should be readily extendable to other outstanding questions in the study of hybridization.
“…First, stabilizing selection might maintain the phenotype at a (more-or-less) stationary optimum, while still allowing for divergence at the genomic level, perhaps by nearly neutral evolution. This is sometimes called "system drift" (Barton 1989;Mani and Clarke 1990;Hartl and Taubes 1998;Rosas et al 2010;Schiffman and Ralph 2017), and it is illustrated in Figure 3c. Alternatively, divergence could involve adaptation to a moving optimum, but with a complex pattern of environmental change, e.g., with an optimum that oscillated back and forth; this is illustrated in Figure 3d.…”
Section: Hybrid Fitness and The Process Of Divergencementioning
confidence: 99%
“…So far, we have ignored an implausible prediction of Fisher's model. Equation 20, predicts that fully heterozygous hybrids will always be as fit as their parents, because, when p 12 = 1 and h = 1/2, the benefits of heterozygosity exactly cancel the costs of hybridity (Barton 2001;Fraïsse et al 2016;Schiffman and Ralph 2017).…”
Section: Phenotypic Dominancementioning
confidence: 99%
“…First, the model assumes that fitness is determined by a few quantitative traits, each with additive genetics. This assumption is less restrictive than it seems, because the "traits" need not be identified with standard quantitative traits (such as height or weight), but might emerge from a variety of more complex underlying phenotypic models (Martin 2014;Schiffman and Ralph 2017;Fraïsse and Welch 2019). Nevertheless, additivity leads to some questionable predictions, especially for the initial F1 cross (Fraïsse et al 2016).…”
We develop an analytical framework for predicting the fitness of hybrid genotypes, based on Fisher’s geometric model. We first show that all of the model parameters have a simple geometrical and biological interpretation. Hybrid fitness decomposes into intrinsic effects of hybridity and heterozygosity, and extrinsic measures of the (local) adaptedness of the parental lines; and all of these correspond to distances in a phenotypic space. We also show how these quantities change over the course of divergence, with convergence to a characteristic pattern of intrinsic isolation. Using individual-based simulations, we then show that the predictions apply to a wide range of population genetic regimes, and divergence conditions, including allopatry and parapatry, local adaptation and drift. We next connect our results to the quantitative genetics of line crosses in variable or patchy environments. This relates the geometrical distances to quantities that can be estimated from cross data, and provides a simple interpretation of the “composite effects” in the quantitative genetics partition. Finally, we develop extensions to the model, involving selectively-induced disequilibria, and variable phenotypic dominance. The geometry of fitness landscapes provides a unifying framework for understanding speciation, and wider patterns of hybrid fitness.
The evolution of diverse phenotypes both involves and is constrained by molecular interaction networks. When these networks influence patterns of expression, we refer to them as gene regulatory networks (GRNs). Here, we develop a model of GRN evolution analogous to work from quasi-species theory, which is itself essentially the mutation–selection balance model from classical population genetics extended to multiple loci. With this GRN model, we prove that—across a broad spectrum of selection pressures—the dynamics converge to a stationary distribution over GRNs. Next, we show from first principles how the frequency of GRNs at equilibrium is related to the topology of the genotype network, in particular, via a specific network centrality measure termed the eigenvector centrality. Finally, we determine the structural characteristics of GRNs that are favoured in response to a range of selective environments and mutational constraints. Our work connects GRN evolution to quasi-species theory—and thus to classical populations genetics—providing a mechanistic explanation for the observed distribution of GRNs evolving in response to various evolutionary forces, and shows how complex fitness landscapes can emerge from simple evolutionary rules.
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