Developmental Plasticity and Evolution. In: Mary Jane West-Eberhard, Editor, Oxford University Press (2003) Pp. xi+794. Price $50.00 paper.

Phenotypic plasticity (the ability of a single genotype to produce multiple phenotypes in response to variation in the environment) is commonplace. Yet its evolutionary significance remains controversial, especially in regard to whether and how it impacts diversification and speciation. Here, we review recent theory on how plasticity promotes: (i) the origin of novel phenotypes, (ii) divergence among populations and species, (iii) the formation of new species and (iv) adaptive radiation. We also discuss the latest empirical support for each of these evolutionary pathways to diversification and identify potentially profitable areas for future research. Generally, phenotypic plasticity can play a largely underappreciated role in driving diversification and speciation.

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Phenotypic plasticity's impacts on diversification and speciation

骨髄異形成症候群のgenome-wide analysis

ECOLOGY/EVOLUTION: Phenotypic Plasticity

Zebrafish (Danio rerio) are rapidly gaining popularity in translational neuroscience and behavioral research. Physiological similarity to mammals, ease of genetic manipulations, sensitivity to pharmacological and genetic factors, robust behavior, low cost, and potential for high-throughput screening contribute to the growing utility of zebrafish models in this field. Understanding zebrafish behavioral phenotypes provides important insights into neural pathways, physiological biomarkers, and genetic underpinnings of normal and pathological brain function. Novel zebrafish paradigms continue to appear with an encouraging pace, thus necessitating a consistent terminology and improved understanding of the behavioral repertoire. What can zebrafish 'do', and how does their altered brain function translate into behavioral actions? To help address these questions, we have developed a detailed catalog of zebrafish behaviors (Zebrafish Behavior Catalog, ZBC) that covers both larval and adult models. Representing a beginning of creating a more comprehensive ethogram of zebrafish behavior, this effort will improve interpretation of published findings, foster cross-species behavioral modeling, and encourage new groups to apply zebrafish neurobehavioral paradigms in their research. In addition, this glossary creates a framework for developing a zebrafish neurobehavioral ontology, ultimately to become part of a unified animal neurobehavioral ontology, which collectively will contribute to better integration of biological data within and across species.

/pdf/towards-a-comprehensive-catalog-of-zebrafish-behavior-1-0-3r83946qdn.pdf

Towards a Comprehensive Catalog of Zebrafish Behavior 1.0 and Beyond

Analyses of gene expression data sets for multiple individuals and species promise to shed light on the mode of evolution of gene expression. However, complementary complexities challenge this goal. Characterization of the genetic variation underlying gene expression can easily be compromised by lack of environmental control. Conversely, the breadth of conclusions from studies of environmental effects has been limited by the use of single strains. Controlled studies have hinted at extensive gene×environment interaction. Thus, both genetics and environment are key components in models of the evolution of gene expression. We review the literature on the evolution of gene expression in terms of genetics (G), environmental response (E) and G×E interactions to make this conceptual point.

/pdf/evolving-gene-expression-from-g-to-e-to-g-e-4xbk9m3i6t.pdf

Evolving gene expression: from G to E to G × E

Distinguishing kin from non-kin profoundly impacts the evolution of social behaviour. Individuals able to assess the genetic relatedness of conspecifics can preferentially allocate resources towards related individuals and avoid inbreeding. We have addressed the question of how animals acquire the ability to recognize kin by studying the development of olfactory kin preference in zebrafish (Danio rerio). Previously, we showed that zebrafish use an olfactory template to recognize even unfamiliar kin through phenotype matching. Here, we show for the first time that this phenotype matching is based on a learned olfactory imprinting process in which exposure to kin individuals on day 6 post fertilization (pf) is necessary and sufficient for imprinting. Larvae that were exposed to kin before or after but not on day 6 pf did not recognize kin. Larvae isolated from all contact with conspecifics did not imprint on their own chemical cues; therefore, we see no evidence for kin recognition through self-matching in this species. Surprisingly, exposure to non-kin odour during the sensitive phase of development did not result in imprinting on the odour cues of unrelated individuals, suggesting a genetic predisposition to kin odour. Urine-born peptides expressed by genes of the immune system (MHC) are important messengers carrying information about ‘self’ and ‘other’. We suggest that phenotype matching is acquired through a time-sensitive learning process that, in zebrafish, includes a genetic predisposition potentially involving MHC genes expressed in the olfactory receptor neurons.

/pdf/kin-recognition-in-zebrafish-a-24-hour-window-for-olfactory-1hz2c4vmuo.pdf

Kin recognition in zebrafish: a 24-hour window for olfactory imprinting

Early acquisition of mate preferences or mate-preference learning is associated with signal diversity and speciation in a wide variety of animal species. However, the diversity of mechanisms of mate-preference learning across taxa remains poorly understood. Using the butterfly Bicyclus anynana we uncover a mechanism that can lead to directional sexual selection via mate-preference learning: a bias in learning enhanced ornamentation, which is independent of preexisting mating biases. Naive females mated preferentially with wild-type males over males with enhanced wing ornamentation, but females briefly exposed to enhanced males mated significantly more often with enhanced males. In contrast, females exposed to males with reduced wing ornamentation did not learn to prefer drab males. Thus, we observe both a learned change of a preexisting mating bias, and a bias in ability to learn enhanced male ornaments over reduced ornaments. Our findings demonstrate that females are able to change their preferences in response to a single social event, and suggest a role for biased learning in the evolution of visual sexual ornamentation.

https://www.pnas.org/content/pnas/109/27/10948.full.pdf

Biased learning affects mate choice in a butterfly

Divergence in gene regulation is hypothesized to underlie much of phenotypic evolution, but the role of natural selection in shaping the molecular phenotype of gene expression continues to be debated. To resolve the mode of gene expression, evolution requires accessible theoretical predictions for the effect of selection over long timescales. Evolutionary quantitative genetic models of phenotypic evolution can provide such predictions, yet those predictions depend on the underlying hypotheses about the distributions of mutational and selective effects that are notoriously difficult to disentangle. Here, we draw on diverse genomic data sets including expression profiles of natural genetic variation and mutation accumulation lines, empirical estimates of genomic mutation rates, and inferences of genetic architecture to differentiate contrasting hypotheses for the roles of stabilizing selection and mutation in shaping natural expression variation. Our analysis suggests that gene expression evolves in a domain of phenotype space well fit by the House-of-Cards (HC) model. Although the strength of selection inferred is sensitive to the number of loci controlling gene expression, the model is not. The consistency of these results across evolutionary time from budding yeast through fruit fly implies that this model is general and that mutational effects on gene expression are relatively large. Empirical estimates of the genetic architecture of gene expression traits imply that selection provides modest constraints on gene expression levels for most genes, but that the potential for regulatory evolution is high. Our prediction using data from laboratory environments should encourage the collection of additional data sets allowing for more nuanced parameterizations of HC models for gene expression.

Gene Expression Evolves under a House-of-Cards Model of Stabilizing Selection

Gene expression noise is an evolvable property of biological systems that describes differences in expression among genetically identical cells in the same environment. Prior work has shown that expression noise is heritable and can be shaped by selection, but the impact of variation in expression noise on organismal fitness has proven difficult to measure. Here, we quantify the fitness effects of altering expression noise for the TDH3 gene in Saccharomyces cerevisiae. We show that increases in expression noise can be deleterious or beneficial depending on the difference between the average expression level of a genotype and the expression level maximizing fitness. We also show that a simple model relating single-cell expression levels to population growth produces patterns consistent with our empirical data. We use this model to explore a broad range of average expression levels and expression noise, providing additional insight into the fitness effects of variation in expression noise.

Andrea Hodgins-Davis

Papers

Evolving gene expression: from G to E to G × E

Kin recognition in zebrafish: a 24-hour window for olfactory imprinting

Biased learning affects mate choice in a butterfly

Gene Expression Evolves under a House-of-Cards Model of Stabilizing Selection

Fitness effects of altering gene expression noise in Saccharomyces cerevisiae.