Developmental Bias and Evolution: A Regulatory Network Perspective

Abstract

Phenotypic variation is generated by the processes of development, with some variants arising more readily than others-a phenomenon known as "developmental bias." Developmental bias and natural selection have often been portrayed as alternative explanations, but this is a false dichotomy: developmental bias can evolve through natural selection, and bias and selection jointly influence phenotypic evolution. Here, we briefly review the evidence for developmental bias and illustrate how it is studied empirically. We describe recent theory on regulatory networks that explains why the influence of genetic and environmental perturbation on phenotypes is typically not uniform, and may even be biased toward adaptive phenotypic variation. We show how bias produced by developmental processes constitutes an evolving property able to impose direction on adaptive evolution and influence patterns of taxonomic and phenotypic diversity. Taking these considerations together, we argue that it is not sufficient to accommodate developmental bias into evolutionary theory merely as a constraint on evolutionary adaptation. The influence of natural selection in shaping developmental bias, and conversely, the influence of developmental bias in shaping subsequent opportunities for adaptation, requires mechanistic models of development to be expanded and incorporated into evolutionary theory. A regulatory network perspective on phenotypic evolution thus helps to integrate the generation of phenotypic variation with natural selection, leaving evolutionary biology better placed to explain how organisms adapt and diversify.

Keywords: constraint; development; developmental bias; evolvability; facilitated variation; gene regulatory network.

Figure 1

Compelling examples of developmental bias and its evolutionary effect in animals. (A) By combining experiments in vivo and in vitro, comparative analyses, and mathematical modeling, researchers have shown that the evolutionary diversity in tooth morphology among mammals is shaped by the mechanism by which teeth develop. Pictured is the skull of a crabeater seal, Lobodon carcinophaga. (B) The oral and pharyngeal jaws of cichlid fishes are putative examples of how a bias caused by plasticity, itself possibly favored by selection, can feed back to facilitate adaptive divergence and convergence in independently evolving lineages. (C) In Drosophila, the phenotypic divergence between species in wing shape is aligned with the phenotypic bias associated with random mutation, one explanation for which is that developmental bias coevolves with phenotypic divergence. (D) Artificial selection on the size and color of Mycalesine butterfly eye spots demonstrates the effects of bias misaligned or aligned with the direction of selection. Photo credits: (A) Panther Media GmbH, Alamy Stock Photo; (B) Kevin Parsons; (C) Martin Hauser Phycus, CC-BY-3.0-DE; (D) Saenko et al., BMC Biology 2010 8:111, CC-BY-2.0.

Figure 2

Developmental bias can both constrain and facilitate adaptive evolution. (A–D) Adaptive landscapes with a ridge and a positive slope toward the top-right corner. The shading represents the distribution of evolutionarily relevant phenotypic variation introduced into the population (e.g., by mutation), with darker regions representing higher frequencies of variants. (A) The default assumption in evolutionary theory is typically that the distribution of evolutionarily relevant phenotypic variation introduced into the population is unbiased. (B) Developmental bias will constrain adaptive evolution if it limits variability in the direction of selection. (C) Developmental bias will accelerate adaptive evolution if it biases variability in dimensions aligned with the direction of selection. (D) Recent theory and empirical research described in this paper further suggests that developmental bias can itself evolve both to orient with the adaptive landscape and to increase phenotypic variability in the direction favored by past natural selection (dashed arrow represents changes in phenotypic distribution over time as the population evolves).

Figure 3

Regulatory networks, their topology, dynamics, and connectivity via mutation. (A) A regulatory network with nodes (e.g., genes) connected by regulatory interactions can be considered a genotype. Mutation to the genotype is represented by a modification in the network topology, for example, by adding or removing regulatory interactions or by modifying the interactions from suppression to activation. Pointed arrows represent activation, while those ending in perpendicular lines show suppression. (B) A regulatory network has a phase space, here represented by the concentrations of molecules encoded by the two genes. The flow of the phase space (gray arrows) describes what trajectory (black arrow) from the starting point (red circles) the system will take as it reaches equilibrium (“basin of attraction”; black circles). Which of potentially several equilibrium states is reached can depend on external conditions, such as the concentration of the activating substance (red arrow and red circles). (C) Connecting regulatory networks (A) to other regulatory networks that differ in only one regulatory change results in large “network-of-networks” or genotype networks. Real genotype networks are very large so two dimensions can only represent a small part of all possible genotypes and how they are connected by mutation. In this hypothetical example, each node represents a single regulatory network, with the color indicating its phenotype. Edges connect regulatory networks that are related by a single modification of their topologies, as represented in A. The properties of these genotype networks determine how likely it is that an alternative phenotype can be reached through mutation. The three shaded areas represent, from left to right, (i) a boundary region between two distinct phenotypes where some genotypes can produce both phenotypes; (ii) a region of genotype space where mutations (i.e., changes in topology) are phenotypically neutral; and (iii) a region where a change in topology can produce several distinct phenotypes that are not accessible from other parts of the network. (D) The regulatory network of this node in the genotype network. ‘A and B are based on representations in Jaeger and Crombach (2012) and Jaeger and Monk (2012) and C is based on representations in Wagner (2011).