REVIEW: Optimality models in the age of experimental evolution and genomics

Optimality models have been used to predict evolution of many properties of organisms. They typically neglect genetic details, whether by necessity or design. This omission is a common source of criticism, and although this limitation of optimality is widely acknowledged, it has mostly been defended rather than evaluated for its impact. Experimental adaptation of model organisms provides a new arena for testing optimality models and for simultaneously integrating genetics. First, an experimental context with a well‐researched organism allows dissection of the evolutionary process to identify causes of model failure – whether the model is wrong about genetics or selection. Second, optimality models provide a meaningful context for the process and mechanics of evolution, and thus may be used to elicit realistic genetic bases of adaptation – an especially useful augmentation to well‐researched genetic systems. A few studies of microbes have begun to pioneer this new direction. Incompatibility between the assumed and actual genetics has been demonstrated to be the cause of model failure in some cases. More interestingly, evolution at the phenotypic level has sometimes matched prediction even though the adaptive mutations defy mechanisms established by decades of classic genetic studies. Integration of experimental evolutionary tests with genetics heralds a new wave for optimality models and their extensions that does not merely emphasize the forces driving evolution.     

The genetics of chutes and ladders: a community genetics approach to tritrophic interactions

Community genetics research has firmly established that intraspecific genetic variation in single populations can have large extended ecological consequences for populations and entire communities of organisms. Here, we sought to understand the bottom‐up effects of plant genetic variation on herbivore preference and performance, and the top–down control of predators on herbivores and their joint effects on plant fitness and evolution. Following three ecological genetics field experiments we detected heritable variation in plant traits that influenced both the preference and performance of a specialist weevil on Oenothera biennis. However, the weevil's preference and performance were not genetically correlated among O. biennis plant genotypes. Although predators and parasitoids were abundant, predators had no detectable effect on weevil performance because high egg and larval mortality was caused by non‐predatory factors such as intraspecific competition. Finally, neither the specialist weevil nor predators influenced plant fitness. Our results suggest that the focal tritrophic community studied here is primarily shaped by the bottom–up effects of plant genetic variation on herbivores, while top–down effects have no clear impacts on O. biennis fitness or evolution. We suggest that future studies should incorporate plant intraspecific genetic variation as a fundamental part of tritrophic interactions including their eco‐evolutionary dynamics.     

MODELING PHENOTYPIC PLASTICITY IN GROWTH TRAJECTORIES: A STATISTICAL FRAMEWORK

Phenotypic plasticity, that is multiple phenotypes produced by a single genotype in response to environmental change, has been thought to play an important role in evolution and speciation. Historically, knowledge about phenotypic plasticity has resulted from the analysis of static traits measured at a single time point. New insight into the adaptive nature of plasticity can be gained by an understanding of how organisms alter their developmental processes in a range of environments. Recent advances in statistical modeling of functional data and developmental genetics allow us to construct a dynamic framework of plastic response in developmental form and pattern. Under this framework, development, genetics, and evolution can be synthesized through statistical bridges to better address how evolution results from phenotypic variation in the process of development via genetic alterations.     

Population genetics and sociobiology: conflicting views of evolution

This article explores the tension between the population genetics and sociobiological approaches to the study of evolution. Whereas population geneticists, like Stanford's Marc Feldman, insist that the genetic complexities of organisms cannot be overlooked, sociobiologists (many of whom now prefer to call themselves "behavioral ecologists") rely on optimization models that are based on the simplest possible genetics.These optimization approaches have their roots in the classical result known as the fundamental theorem of natural selection, formulated by R. A. Fisher in 1930. From the start there was great uncertainty over the proper interpretation of Fisher's theorem, which became confused with Sewall Wright's immensely influential adaptive landscape concept. In the 1960s, a new generation of mathematical biologists proved that Fisher's theorem did not hold when fitness depended on more than one locus. Similar reasoning was used to attack W. D. Hamilton's inclusive fitness theory. A new theory, known as the theory of long-term evolution, attempts to reconcile the rigorous population genetics approach with the long-standing sociobiological view that natural selection acts to increase the fitness of organisms.     

What can microbial genetics teach sociobiology?

Progress in our understanding of sociobiology has occurred with little knowledge of the genetic mechanisms that underlie social traits. However, several recent studies have described microbial genes that affect social traits, thereby bringing genetics to sociobiology. A key finding is that simple genetic changes can have marked social consequences, and mutations that affect cheating and recognition behaviors have been discovered. The study of these mutants confirms a central theoretical prediction of social evolution: that genetic relatedness promotes cooperation. Microbial genetics also provides an important new perspective: that the genome-to-phenome mapping of social organisms might be organized to constrain the evolution of social cheaters. This constraint can occur both through pleiotropic genes that link cheating to a personal cost and through the existence of phoenix genes, which rescue cooperative systems from selfish and destructive strategies. These new insights show the power of studying microorganisms to improve our understanding of the evolution of cooperation.     

Facilitated variation: how evolution learns from past environments to generalize to new environments

One of the striking features of evolution is the appearance of novel structures in organisms. Recently, Kirschner and Gerhart have integrated discoveries in evolution, genetics, and developmental biology to form a theory of facilitated variation (FV). The key observation is that organisms are designed such that random genetic changes are channeled in phenotypic directions that are potentially useful. An open question is how FV spontaneously emerges during evolution. Here, we address this by means of computer simulations of two well-studied model systems, logic circuits and RNA secondary structure. We find that evolution of FV is enhanced in environments that change from time to time in a systematic way: the varying environments are made of the same set of subgoals but in different combinations. We find that organisms that evolve under such varying goals not only remember their history but also generalize to future environments, exhibiting high adaptability to novel goals. Rapid adaptation is seen to goals composed of the same subgoals in novel combinations, and to goals where one of the subgoals was never seen in the history of the organism. The mechanisms for such enhanced generation of novelty (generalization) are analyzed, as is the way that organisms store information in their genomes about their past environments. Elements of facilitated variation theory, such as weak regulatory linkage, modularity, and reduced pleiotropy of mutations, evolve spontaneously under these conditions. Thus, environments that change in a systematic, modular fashion seem to promote facilitated variation and allow evolution to generalize to novel conditions.     

The evolution of sex-biased genes and sex-biased gene expression

Differences between males and females in the optimal phenotype that is favoured by selection can be resolved by the evolution of differential gene expression in the two sexes. Microarray experiments have shown that such sex-biased gene expression is widespread across organisms and genomes. Sex-biased genes show unusually rapid sequence evolution, are often labile in their pattern of expression, and are non-randomly distributed in the genome. Here we discuss the characteristics and expression of sex-biased genes, and the selective forces that shape this previously unappreciated source of phenotypic diversity. Sex-biased gene expression has implications beyond just evolutionary biology, including for medical genetics.     

Perspective: reverse evolution

For some time, the reversibility of evolution was primarily discussed in terms of comparative patterns. Only recently has this problem been studied using experimental evolution over shorter evolutionary time frames. This has raised questions of definition, experimental procedure, and the hypotheses being tested. Experimental evolution has provided evidence for multiple population genetic mechanisms in reverse evolution, including pleiotropy and mutation accumulation. It has also pointed to genetic factors that might prevent reverse evolution, such as a lack of genetic variability, epistasis, and differential genotype-by-environment interactions. The main focus of this perspective is on laboratory studies and their relevance to the genetics of reverse evolution. We discuss reverse evolution experiments with Drosophila, bacterial, and viral populations. Field studies of the reverse evolution of melanism in the peppered moth are also reviewed.     

Detection of mitochondrial insertions in the nucleus (NuMts) of Pleistocene and modern muskoxen

Background  

Nuclear insertions of mitochondrial sequences (NuMts) have been identified in a wide variety of organisms. Trafficking of genetic material from the mitochondria to the nucleus has occurred frequently during mammalian evolution and can lead to the production of a large pool of sequences with varying degrees of homology to organellar mitochondrial DNA (mtDNA) sequences. This presents both opportunities and challenges for forensics, population genetics, evolutionary genetics, conservation biology and the study of DNA from ancient samples. Here we present a case in which difficulties in ascertaining the organellar mtDNA sequence from modern samples hindered their comparison to ancient DNA sequences.     

Developmental system drift and flexibility in evolutionary trajectories

SUMMARY The comparative analysis of homologous characters is a staple of evolutionary developmental biology and often involves extrapolating from experimental data in model organisms to infer developmental events in non-model organisms. In order to determine the general importance of data obtained in model organisms, it is critical to know how often and to what degree similar phenotypes expressed in different taxa are formed by divergent developmental processes. Both comparative studies of distantly related species and genetic analysis of closely related species indicate that many characters known to be homologous between taxa have diverged in their morphogenetic or gene regulatory underpinnings. This process, which we call "developmental system drift" (DSD), is apparently ubiquitous and has significant implications for the flexibility of developmental evolution of both conserved and evolving characters. Current data on the population genetics and molecular mechanisms of DSD illustrate how the details of developmental processes are constantly changing within evolutionary lineages, indicating that developmental systems may possess a great deal of plasticity in their responses to natural selection.     

An introduction to genetic quality in the context of sexual selection

This special issue of Genetica brings together empirical researchers and theoreticians to present the latest on the evolutionary ecology of genetic quality in the context of sexual selection. The work comes from different fields of study including behavioral ecology, quantitative genetics and molecular genetics on a diversity of organisms using different approaches from comparative studies, mathematical modeling, field studies and laboratory experiments. The papers presented in this special issue primarily focus on genetic quality in relation to (1) sources of genetic variation, (2) polyandry, (3) new theoretical developments and (4) comprehensive reviews.     

N. I. Vavilov's law of genetic homology in modern genetics

The paper considers the place in modern genetics and the significance of the main N.I. Vavilov's generalization--his law of homologous series in variation. Recent analysis of amino acid sequences of gene products (proteins) and especially of nucleotide sequences of genes shows the high degree of molecular homology between genes of closely related species and the retention of the homology through the course of evolution. The study of homologous genes disposition in chromosomes shows conservation of the similar orders of genes in many organisms, especially in mammals. Thus, the law of genetic homology has been confirmed by modern genetic researchers. It is a foundation-stone of comparative genetics--new and rapid developing branch of genetics which involves studies on similarity and differences in heredity and variation in organisms of different taxa.     

On the evolution of multigene families

Multigene families are classified into three groups: small families as exemplified by hemoglobin genes of mammals; middlesize multigene families, by genes of mammalian histocompatibility antigens; and large multigene families, by variable region genes of immunoglobulins. Facts and theories on these evolving multigene families are reviewed, with special reference to the population genetics of their concerted evolution. It is shown that multigene families are evolving under continued occurrence of unequal (but homologous) crossing-over and gene conversion, and that mechanisms for maintaining genetic variability are totally different from the conventional models of population genetics. Thus, in view of widespread occurrence of multigene families in genomes of higher organisms, the evolutionary theory based mainly on change of gene frequency at each locus would appear to need considerable revision.     

Mapping quantitative trait Loci interactions from the maternal and offspring genomes

The expression of most developmental or behavioral traits involves complex interactions between quantitative trait loci (QTL) from the maternal and offspring genomes. The maternal-offspring interactions play a pivotal role in shaping the direction and rate of evolution in terms of their substantial contribution to quantitative genetic (co)variation. To study the genetics and evolution of maternal-offspring interactions, a unifying statistical framework that embraces both the direct and indirect genetic effects of maternal and offspring QTL on any complex trait is developed. This model is derived for a simple backcross design within the maximum-likelihood context, implemented with the EM algorithm. Results from extensive simulations suggest that this model can provide reasonable estimation of additive and dominant effects of the QTL at different generations and their interaction effects derived from the maternal and offspring genomes. Although our model is framed to characterize the actions and interactions of maternal and offspring QTL affecting offspring traits, the idea can be readily extended to decipher the genetic machinery of maternal traits, such as maternal care. Our model provides a powerful means for studying the evolutionary significance of indirect genetic effects in any sexually reproductive organisms.     

Mutational Dynamics of Microsatellites

Microsatellites are a ubiquitous class of simple repetitive DNA sequences, which are widespread in both eukaryotic and prokaryotic genomes. The use of microsatellites as polymorphic DNA markers has considerably increased both in the number of studies and in the number of organisms, primarily for genetic mapping, studying genomic instability in cancer, population genetics, forensics, conservation biology, molecular anthropology and in the studies of human evolutionary history. Although simple sequence repeats have been extensively used in studies encompassing varied areas of genetics, the mutation dynamics of these genome regions is still not well understood. The present review focuses on the mutational dynamics of microsatellite DNA with special reference to mutational mechanisms and their role in microsatellite evolution.     

Admixture as the basis for genetic mapping

Genetic mapping in natural populations is increasing rapidly in feasibility and accessibility. As with many areas in genetics, advances in molecular techniques and statistics are drastically altering how we can investigate inheritance in wild organisms. For ecology and evolution, this is particularly significant and promising, because many of the organisms of interest are not amenable to conventional genetic approaches. Admixture mapping falls within a family of statistical approaches that use natural recombination and linkage disequilibrium between genetic markers and phenotypes as the basis for mapping. Our aim in this review is to provide a snapshot of previous and ongoing research, existing methods and challenges, the nature of questions that can be investigated and prospects for the future of admixture mapping.     

Genetic and Genomic Toolbox of the Chordate Ciona intestinalis

The experimental malleability and unique phylogenetic position of the sea squirt Ciona intestinalis as part of the sister group to the vertebrates have helped establish these marine chordates as model organisms for the study of developmental genetics and evolution. Here we summarize the tools, techniques, and resources available to the Ciona geneticist, citing examples of studies that employed such strategies in the elucidation of gene function in Ciona. Genetic screens, germline transgenesis, electroporation of plasmid DNA, and microinjection of morpholinos are all routinely employed, and in the near future we expect these to be complemented by targeted mutagenesis, homologous recombination, and RNAi. The genomic resources available will continue to support the design and interpretation of genetic experiments and allow for increasingly sophisticated approaches on a high-throughput, whole-genome scale.     

Early 20th-century research at the interfaces of genetics, development, and evolution: reflections on progress and dead ends

Three early 20th-century attempts at unifying separate areas of biology, in particular development, genetics, physiology, and evolution, are compared in regard to their success and fruitfulness for further research: Jacques Loeb's reductionist project of unifying approaches by physico-chemical explanations; Richard Goldschmidt's anti-reductionist attempts to unify by integration; and Sewall Wright's combination of reductionist research and vision of hierarchical genetic systems. Loeb's program, demanding that all aspects of biology, including evolution, be studied by the methods of the experimental sciences, proved highly successful and indispensible for higher level investigations, even though evolutionary change and properties of biological systems up to now cannot be fully explained on the molecular level alone. Goldschmidt has been appraised as pioneer of physiological and developmental genetics and of a new evolutionary synthesis which transcended neo-Darwinism. However, this study concludes that his anti-reductionist attempts to integrate genetics, development and evolution have to be regarded as failures or dead ends. His grand speculations were based on the one hand on concepts and experimental systems that were too vague in order to stimulate further research, and on the other on experiments which in their core parts turned out not to be reproducible. In contrast, Sewall Wright, apart from being one of the architects of the neo-Darwinian synthesis of the 1930s, opened up new paths of testable quantitative developmental genetic investigations. He placed his research within a framework of logical reasoning, which resulted in the farsighted speculation that examinations of biological systems should be related to the regulation of hierarchical genetic subsystems, possibly providing a mechanism for development and evolution. I argue that his suggestion of basing the study of systems on clearly defined properties of the components has proved superior to Goldschmidt's approach of studying systems as a whole, and that attempts to integrate different fields at a too early stage may prove futile or worse.     

Dynamics of Horizontal Gene Transfer and the Ecological Risk Assessment of Genetically Engineered Organisms

The extensive published discussion of potential ecological impacts of introduced genetic sequences and genetically engineered organisms has lacked a quantified delineation of the critical questions for the estimation of risk. Ultimately, the ecological risk assessment of introduced gene sequences is the application of evolution, population genetics, and ecology to risk estimation and decision making. This paper provides a framework for the estimation of risk due to introduced sequences in bacteria, and the principles should also hold for many diploid species. Horizontal genetic exchange poses new challenges for ecological risk assessment. Plasmid transfer can occur without any impacts, although the sequence can become ubiquitous in the population. Conversely, the introduction of a plasmid can change the dynamics of the host population, potentially altering the population minimum and maximum characteristics of its dynamics. Because of genetic exchange, new genetic information is unlikely to be constrained among one type of prokaryote. An example of the use of the model is given using genetic exchange data from a series of published soil microcosm experiments. The model demonstrates the increase in plasmid frequency when using experimentally derived conjugation frequencies. Application of these results to ongoing discussion of the risks of genetically engineered organisms is presented. Particular attention is paid to the transfer of genetic material and the resultant changes in host population dynamics.     

Mainstreaming Caenorhabditis elegans in experimental evolution

Experimental evolution provides a powerful manipulative tool for probing evolutionary process and mechanism. As this approach to hypothesis testing has taken purchase in biology, so too has the number of experimental systems that use it, each with its own unique strengths and weaknesses. The depth of biological knowledge about Caenorhabditis nematodes, combined with their laboratory tractability, positions them well for exploiting experimental evolution in animal systems to understand deep questions in evolution and ecology, as well as in molecular genetics and systems biology. To date, Caenorhabditis elegans and related species have proved themselves in experimental evolution studies of the process of mutation, host–pathogen coevolution, mating system evolution and life-history theory. Yet these organisms are not broadly recognized for their utility for evolution experiments and remain underexploited. Here, we outline this experimental evolution work undertaken so far in Caenorhabditis, detail simple methodological tricks that can be exploited and identify research areas that are ripe for future discovery.