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1.  Evolution of Networks for Body Plan Patterning; Interplay of Modularity, Robustness and Evolvability 
PLoS Computational Biology  2011;7(10):e1002208.
A major goal of evolutionary developmental biology (evo-devo) is to understand how multicellular body plans of increasing complexity have evolved, and how the corresponding developmental programs are genetically encoded. It has been repeatedly argued that key to the evolution of increased body plan complexity is the modularity of the underlying developmental gene regulatory networks (GRNs). This modularity is considered essential for network robustness and evolvability. In our opinion, these ideas, appealing as they may sound, have not been sufficiently tested. Here we use computer simulations to study the evolution of GRNs' underlying body plan patterning. We select for body plan segmentation and differentiation, as these are considered to be major innovations in metazoan evolution. To allow modular networks to evolve, we independently select for segmentation and differentiation. We study both the occurrence and relation of robustness, evolvability and modularity of evolved networks. Interestingly, we observed two distinct evolutionary strategies to evolve a segmented, differentiated body plan. In the first strategy, first segments and then differentiation domains evolve (SF strategy). In the second scenario segments and domains evolve simultaneously (SS strategy). We demonstrate that under indirect selection for robustness the SF strategy becomes dominant. In addition, as a byproduct of this larger robustness, the SF strategy is also more evolvable. Finally, using a combined functional and architectural approach, we determine network modularity. We find that while SS networks generate segments and domains in an integrated manner, SF networks use largely independent modules to produce segments and domains. Surprisingly, we find that widely used, purely architectural methods for determining network modularity completely fail to establish this higher modularity of SF networks. Finally, we observe that, as a free side effect of evolving segmentation and differentiation in combination, we obtained in-silico developmental mechanisms resembling mechanisms used in vertebrate development.
Author Summary
An important question in evolutionary developmental biology is how the complex organisms we see around us have evolved, and how this complexity is encoded in their DNA. An often heard statement is that the gene regulatory networks underlying developmental processes are modular; that is, different functions are carried out by largely independent network parts. It is argued that this network modularity allows both for robust functioning and evolutionary tinkering, and that selection thus produces modular networks. Here we use a simulation model for the evolution of animal body plan patterning to investigate these ideas. To allow for the evolution of modular networks we independently select for both body plan segmentation and differentiation. We find two distinct evolutionary trajectories, one in which segments evolve before domains, and one in which segments and domains evolve simultaneously. In addition, the two evolved network types also differ in terms of developmental dynamics. We show that indirect selection for robustness favors the segments first type networks. Furthermore, as a free side effect, these more robust networks are also more evolvable. Finally, we take into account both functional and architectural aspects to determine the modularity of the network types. We show that segments simultaneous networks generate segments and domains in a integrated manner, whereas segments first networks use largely independent modules to generate segments and domains. Finally, although mimicking natural developmental mechanisms was not part of our model design, the segments first developmental mechanisms resembles vertebrate axial patterning mechanisms. This resemblance arises for free, simply from considering segmentation and differentiation in combination.
PMCID: PMC3188509  PMID: 21998573
2.  A Perspective on Micro-Evo-Devo: Progress and Potential 
Genetics  2013;195(3):625-634.
The term “micro-evo-devo” refers to the combined study of the genetic and developmental bases of natural variation in populations and the evolutionary forces that have shaped this variation. It thus represents a synthesis of the fields of evolutionary developmental biology and population genetics. As has been pointed out by several others, this synthesis can provide insights into the evolution of organismal form and function that have not been possible within these individual disciplines separately. Despite a number of important successes in micro-evo-devo, however, it appears that evo devo and population genetics remain largely separate spheres of research, limiting their ability to address evolutionary questions. This also risks pushing contemporary evo devo to the fringes of evolutionary biology because it does not describe the causative molecular changes underlying evolution or the evolutionary forces involved. Here we reemphasize the theoretical and practical importance of micro-evo-devo as a strategy for understanding phenotypic evolution, review the key recent insights that it has provided, and present a perspective on both the potential and the remaining challenges of this exciting interdisciplinary field.
PMCID: PMC3813853  PMID: 24190920
3.  Mutational robustness can facilitate adaptation 
Nature  2010;463(7279):353-355.
Robustness seems to be the opposite of evolvability. If phenotypes are robust against mutation, we might expect that a population will have difficulty adapting to an environmental change, as several studies have suggested1–4. However, other studies contend that robust organisms are more adaptable5–8. A quantitative understanding of the relationship between robustness and evolvability will help resolve these conflicting reports and will clarify outstanding problems in molecular and experimental evolution, evo-devo, and protein engineering. Using a general population-genetic model, we demonstrate here that mutational robustness can either impede or facilitate adaptation, depending on the population size, the mutation rate, and the structure of the fitness landscape. In particular, neutral diversity in a robust population can accelerate adaptation provided the number of phenotypes accessible to an individual by mutation is smaller than the total number of phenotypes in the fitness landscape. These results provide a quantitative resolution to a significant ambiguity in evolutionary theory.
PMCID: PMC3071712  PMID: 20090752
4.  The EvoDevoCI: A Concept Inventory for Gauging Students’ Understanding of Evolutionary Developmental Biology 
CBE Life Sciences Education  2013;12(4):665-675.
The authors present the development and validation of the EvoDevoCI, a concept inventory for evolutionary developmental biology. This CI measures student understanding of six core evolutionary developmental biology (evo-devo) concepts using four scenarios and 11 multiple-choice items, all inspired by authentic scientific examples. Distracters were designed to represent the common conceptual difficulties students have with each evo-devo concept.
The American Association for the Advancement of Science 2011 report Vision and Change in Undergraduate Biology Education encourages the teaching of developmental biology as an important part of teaching evolution. Recently, however, we found that biology majors often lack the developmental knowledge needed to understand evolutionary developmental biology, or “evo-devo.” To assist in efforts to improve evo-devo instruction among undergraduate biology majors, we designed a concept inventory (CI) for evolutionary developmental biology, the EvoDevoCI. The CI measures student understanding of six core evo-devo concepts using four scenarios and 11 multiple-choice items, all inspired by authentic scientific examples. Distracters were designed to represent the common conceptual difficulties students have with each evo-devo concept. The tool was validated by experts and administered at four institutions to 1191 students during preliminary (n = 652) and final (n = 539) field trials. We used student responses to evaluate the readability, difficulty, discriminability, validity, and reliability of the EvoDevoCI, which included items ranging in difficulty from 0.22–0.55 and in discriminability from 0.19–0.38. Such measures suggest the EvoDevoCI is an effective tool for assessing student understanding of evo-devo concepts and the prevalence of associated common conceptual difficulties among both novice and advanced undergraduate biology majors.
PMCID: PMC3846517  PMID: 24297293
5.  Getting to Evo-Devo: Concepts and Challenges for Students Learning Evolutionary Developmental Biology 
CBE Life Sciences Education  2013;12(3):494-508.
In this study we used surveys of evo-devo experts to identify the core concepts of evo-devo and outline an underlying conceptual framework. We also use interviews and surveys of conceptual difficulties with these concepts.
To examine how well biology majors have achieved the necessary foundation in evolution, numerous studies have examined how students learn natural selection. However, no studies to date have examined how students learn developmental aspects of evolution (evo-devo). Although evo-devo plays an increasing role in undergraduate biology curricula, we find that instruction often addresses development cursorily, with most of the treatment embedded within instruction on evolution. Based on results of surveys and interviews with students, we suggest that teaching core concepts (CCs) within a framework that integrates supporting concepts (SCs) from both evolutionary and developmental biology can improve evo-devo instruction. We articulate CCs, SCs, and foundational concepts (FCs) that provide an integrative framework to help students master evo-devo concepts and to help educators address specific conceptual difficulties their students have with evo-devo. We then identify the difficulties that undergraduates have with these concepts. Most of these difficulties are of two types: those that are ubiquitous among students in all areas of biology and those that stem from an inadequate understanding of FCs from developmental, cell, and molecular biology.
PMCID: PMC3763016  PMID: 24006397
6.  Network Hubs Buffer Environmental Variation in Saccharomyces cerevisiae 
PLoS Biology  2008;6(11):e264.
Regulatory and developmental systems produce phenotypes that are robust to environmental and genetic variation. A gene product that normally contributes to this robustness is termed a phenotypic capacitor. When a phenotypic capacitor fails, for example when challenged by a harsh environment or mutation, the system becomes less robust and thus produces greater phenotypic variation. A functional phenotypic capacitor provides a mechanism by which hidden polymorphism can accumulate, whereas its failure provides a mechanism by which evolutionary change might be promoted. The primary example to date of a phenotypic capacitor is Hsp90, a molecular chaperone that targets a large set of signal transduction proteins. In both Drosophila and Arabidopsis, compromised Hsp90 function results in pleiotropic phenotypic effects dependent on the underlying genotype. For some traits, Hsp90 also appears to buffer stochastic variation, yet the relationship between environmental and genetic buffering remains an important unresolved question. We previously used simulations of knockout mutations in transcriptional networks to predict that many gene products would act as phenotypic capacitors. To test this prediction, we use high-throughput morphological phenotyping of individual yeast cells from single-gene deletion strains to identify gene products that buffer environmental variation in Saccharomyces cerevisiae. We find more than 300 gene products that, when absent, increase morphological variation. Overrepresented among these capacitors are gene products that control chromosome organization and DNA integrity, RNA elongation, protein modification, cell cycle, and response to stimuli such as stress. Capacitors have a high number of synthetic-lethal interactions but knockouts of these genes do not tend to cause severe decreases in growth rate. Each capacitor can be classified based on whether or not it is encoded by a gene with a paralog in the genome. Capacitors with a duplicate are highly connected in the protein–protein interaction network and show considerable divergence in expression from their paralogs. In contrast, capacitors encoded by singleton genes are part of highly interconnected protein clusters whose other members also tend to affect phenotypic variability or fitness. These results suggest that buffering and release of variation is a widespread phenomenon that is caused by incomplete functional redundancy at multiple levels in the genetic architecture.
Author Summary
Most species maintain abundant genetic variation and experience a wide range of environmental conditions, yet phenotypic differences between individuals are usually small. This phenomenon, known as phenotypic robustness, presents an apparent contradiction: if biological systems are so resistant to variation, how do they diverge and adapt through evolutionary time? Here, we address this question by investigating the molecular mechanisms that underlie phenotypic robustness and how these mechanisms can be broken to produce phenotypic heterogeneity. We identify genes that contribute to phenotypic robustness in yeast by analyzing the variance of morphological phenotypes in a comprehensive collection of single-gene knockout strains. We find that ∼5% of yeast genes break phenotypic robustness when knocked out. The products of these genes tend to be involved in critical cellular processes, including maintaining DNA stability, processing RNA, modifying proteins, and responding to stressful environments. These genes tend to interact genetically with a large number of other genes, and their products tend to interact physically with a large number of other gene products. Our results suggest that loss of phenotypic robustness might be a common phenomenon during evolution that occurs when cellular networks are disrupted.
A genome-wide screen inSaccharomyces cerevisiae identifies over 300 gene products that buffer environmental variation--dubbed phenotypic capacitors--and function as hubs in protein-protein and synthetic-lethal interaction networks.
PMCID: PMC2577700  PMID: 18986213
7.  Evolution of Evolvability in Gene Regulatory Networks 
PLoS Computational Biology  2008;4(7):e1000112.
Gene regulatory networks are perhaps the most important organizational level in the cell where signals from the cell state and the outside environment are integrated in terms of activation and inhibition of genes. For the last decade, the study of such networks has been fueled by large-scale experiments and renewed attention from the theoretical field. Different models have been proposed to, for instance, investigate expression dynamics, explain the network topology we observe in bacteria and yeast, and for the analysis of evolvability and robustness of such networks. Yet how these gene regulatory networks evolve and become evolvable remains an open question.
An individual-oriented evolutionary model is used to shed light on this matter. Each individual has a genome from which its gene regulatory network is derived. Mutations, such as gene duplications and deletions, alter the genome, while the resulting network determines the gene expression pattern and hence fitness. With this protocol we let a population of individuals evolve under Darwinian selection in an environment that changes through time.
Our work demonstrates that long-term evolution of complex gene regulatory networks in a changing environment can lead to a striking increase in the efficiency of generating beneficial mutations. We show that the population evolves towards genotype-phenotype mappings that allow for an orchestrated network-wide change in the gene expression pattern, requiring only a few specific gene indels. The genes involved are hubs of the networks, or directly influencing the hubs. Moreover, throughout the evolutionary trajectory the networks maintain their mutational robustness. In other words, evolution in an alternating environment leads to a network that is sensitive to a small class of beneficial mutations, while the majority of mutations remain neutral: an example of evolution of evolvability.
Author Summary
A cell receives signals both from its internal and external environment and responds by changing the expression of genes. In this manner the cell adjusts to heat, osmotic pressures and other circumstances during its lifetime. Over long timescales, the network of interacting genes and its regulatory actions also undergo evolutionary adaptation. Yet how do such networks evolve and become adapted?
In this paper we describe the study of a simple model of gene regulatory networks, focusing solely on evolutionary adaptation. We let a population of individuals evolve, while the external environment changes through time. To ensure evolution is the only source of adaptation, we do not provide the individuals with a sensor to the environment. We show that the interplay between the long-term process of evolution and short-term gene regulation dynamics leads to a striking increase in the efficiency of creating well-adapted offspring. Beneficial mutations become more frequent, nevertheless robustness to the majority of mutations is maintained. Thus we demonstrate a clear example of the evolution of evolvability.
PMCID: PMC2432032  PMID: 18617989
8.  A quantitative atlas of Even-skipped and Hunchback expression in Clogmia albipunctata (Diptera: Psychodidae) blastoderm embryos 
EvoDevo  2014;5:1.
Comparative studies of developmental processes are one of the main approaches to evolutionary developmental biology (evo-devo). Over recent years, there has been a shift of focus from the comparative study of particular regulatory genes to the level of whole gene networks. Reverse-engineering methods can be used to computationally reconstitute and analyze the function and dynamics of such networks. These methods require quantitative spatio-temporal expression data for model fitting. Obtaining such data in non-model organisms remains a major technical challenge, impeding the wider application of data-driven mathematical modeling to evo-devo.
We have raised antibodies against four segmentation gene products in the moth midge Clogmia albipunctata, a non-drosophilid dipteran species. We have used these antibodies to create a quantitative atlas of protein expression patterns for the gap gene hunchback (hb), and the pair-rule gene even-skipped (eve). Our data reveal differences in the dynamics of Hb boundary positioning and Eve stripe formation between C. albipunctata and Drosophila melanogaster. Despite these differences, the overall relative spatial arrangement of Hb and Eve domains is remarkably conserved between these two distantly related dipteran species.
We provide a proof of principle that it is possible to acquire quantitative gene expression data at high accuracy and spatio-temporal resolution in non-model organisms. Our quantitative data extend earlier qualitative studies of segmentation gene expression in C. albipunctata, and provide a starting point for comparative reverse-engineering studies of the evolutionary and developmental dynamics of the segmentation gene system.
PMCID: PMC3897886  PMID: 24393251
Clogmia albipunctata; Non-drosophilid diptera; Non-model organism; Pattern formation; Comparative network analysis; Segmentation gene network; Hunchback; Even-skipped; Image bioinformatics; Quantitative expression data
9.  EvoRSR: an integrated system for exploring evolution of RNA structural robustness 
BMC Bioinformatics  2009;10:249.
Robustness, maintaining a constant phenotype despite perturbations, is a fundamental property of biological systems that is incorporated at various levels of biological complexity. Although robustness has been frequently observed in nature, its evolutionary origin remains unknown. Current hypotheses suggest that robustness originated as a direct consequence of natural selection, as an intrinsic property of adaptations, or as a congruent correlate of environment robustness. To elucidate the evolutionary origins of robustness, a convenient computational package is strongly needed.
In this study, we developed the open-source integrated system EvoRSR (Evolution of RNA Structural Robustness) to explore the evolution of robustness based on biologically important landscapes induced by RNA folding. EvoRSR is object-oriented, modular, and freely available at under the GNU/GPL license. We present an overview of EvoRSR package and illustrate its features with the miRNA gene cel-mir-357.
EvoRSR is a novel and flexible package for exploring the evolution of robustness. Accordingly, EvoRSR can be used for future studies to investigate the evolution and origin of robustness and to address other common questions about robustness. While the current EvoRSR environment is a versatile analysis framework, future versions can include features to enhance evolutionary studies of robustness.
PMCID: PMC2731758  PMID: 19674478
10.  Allocating structure to function: the strong links between neuroplasticity and natural selection 
A central question in brain evolution is how species-typical behaviors, and the neural function-structure mappings supporting them, can be acquired and inherited. Advocates of brain modularity, in its different incarnations across scientific subfields, argue that natural selection must target domain-dedicated, separately modifiable neural subsystems, resulting in genetically-specified functional modules. In such modular systems, specification of neuron number and functional connectivity are necessarily linked. Mounting evidence, however, from allometric, developmental, comparative, systems-physiological, neuroimaging and neurological studies suggests that brain elements are used and reused in multiple functional systems. This variable allocation can be seen in short-term neuromodulation, in neuroplasticity over the lifespan and in response to damage. We argue that the same processes are evident in brain evolution. Natural selection must preserve behavioral functions that may co-locate in variable amounts with other functions. In genetics, the uses and problems of pleiotropy, the re-use of genes in multiple networks have been much discussed, but this issue has been sidestepped in neural systems by the invocation of modules. Here we highlight the interaction between evolutionary and developmental mechanisms to produce distributed and overlapping functional architectures in the brain. These adaptive mechanisms must be robust to perturbations that might disrupt critical information processing and action selection, but must also recognize useful new sources of information arising from internal genetic or environmental variability, when those appear. These contrasting properties of “robustness” and “evolvability” have been discussed for the basic organization of body plan and fundamental cell physiology. Here we extend them to the evolution and development, “evo-devo,” of brain structure.
PMCID: PMC3882658  PMID: 24431995
cortex; modularity; evo-devo; visual system; neural re-use
11.  500,000 fish phenotypes: The new informatics landscape for evolutionary and developmental biology of the vertebrate skeleton 
The rich phenotypic diversity that characterizes the vertebrate skeleton results from evolutionary changes in regulation of genes that drive development. Although relatively little is known about the genes that underlie the skeletal variation among fish species, significant knowledge of genetics and development is available for zebrafish. Because developmental processes are highly conserved, this knowledge can be leveraged for understanding the evolution of skeletal diversity. We developed the Phenoscape Knowledgebase (KB; to yield testable hypotheses of candidate genes involved in skeletal evolution. We developed a community anatomy ontology for fishes and ontology-based methods to represent complex free-text character descriptions of species in a computable format. With these tools, we populated the KB with comparative morphological data from the literature on over 2,500 teleost fishes (mainly Ostariophysi) resulting in over 500,000 taxon phenotype annotations. The KB integrates these data with similarly structured phenotype data from zebrafish genes ( Using ontology-based reasoning, candidate genes can be inferred for the phenotypes that vary across taxa, thereby uniting genetic and phenotypic data to formulate evo-devo hypotheses. The morphological data in the KB can be browsed, sorted, and aggregated in ways that provide unprecedented possibilities for data mining and discovery.
PMCID: PMC3377363  PMID: 22736877
12.  Flower color as a model system for studies of plant evo-devo 
Even though pigmentation traits have had substantial impacts on the field of animal evolutionary developmental biology, they have played only relatively minor roles in plant evo-devo. This is surprising given the often direct connection between flower color and fitness variation mediated through the effects of pollinators. At the same time, ecological and evolutionary genetic studies have utilized the molecular resources available for the anthocyanin pathway to generate several examples of the molecular basis of putatively adaptive transitions in flower color. Despite this opportunity to synthesize experimental approaches in ecology, evolution, and developmental biology, the investigation of many fundamental questions in evo-devo using this powerful model is only at its earliest stages. For example, a long-standing question is whether predictable genetic changes accompany the repeated evolution of a trait. Due to the conserved nature of the biochemical and regulatory control of anthocyanin biosynthesis, it has become possible to determine whether, and under what circumstances, different types of mutations responsible for flower color variation are preferentially targeted by natural selection. In addition, because plants use anthocyanin and related compounds in vegetative tissue for other important physiological functions, the identification of naturally occurring transitions from unpigmented to pigmented flowers provides the opportunity to examine the mechanisms by which regulatory networks are co-opted into new developmental domains. Here, we review what is known about the ecological and molecular basis of anthocyanic flower color transitions in natural systems, focusing on the evolutionary and developmental features involved. In doing so, we provide suggestions for future work on this trait and suggest that there is still much to be learned from the evolutionary development of flower color transitions in nature.
PMCID: PMC3748380  PMID: 23970892
anthocyanin; flower color; R2R3-MYB; predictability; co-option; pleiotropy
13.  Conservation and co-option in developmental programmes: the importance of homology relationships 
Frontiers in Zoology  2005;2:15.
One of the surprising insights gained from research in evolutionary developmental biology (evo-devo) is that increasing diversity in body plans and morphology in organisms across animal phyla are not reflected in similarly dramatic changes at the level of gene composition of their genomes. For instance, simplicity at the tissue level of organization often contrasts with a high degree of genetic complexity. Also intriguing is the observation that the coding regions of several genes of invertebrates show high sequence similarity to those in humans. This lack of change (conservation) indicates that evolutionary novelties may arise more frequently through combinatorial processes, such as changes in gene regulation and the recruitment of novel genes into existing regulatory gene networks (co-option), and less often through adaptive evolutionary processes in the coding portions of a gene. As a consequence, it is of great interest to examine whether the widespread conservation of the genetic machinery implies the same developmental function in a last common ancestor, or whether homologous genes acquired new developmental roles in structures of independent phylogenetic origin. To distinguish between these two possibilities one must refer to current concepts of phylogeny reconstruction and carefully investigate homology relationships. Particularly problematic in terms of homology decisions is the use of gene expression patterns of a given structure. In the future, research on more organisms other than the typical model systems will be required since these can provide insights that are not easily obtained from comparisons among only a few distantly related model species.
PMCID: PMC1282587  PMID: 16216118
14.  Functional genetics for all: engineered nucleases, CRISPR and the gene editing revolution 
EvoDevo  2014;5:43.
Developmental biology, as all experimental science, is empowered by technological advances. The availability of genetic tools in some species - designated as model organisms - has driven their use as major platforms for understanding development, physiology and behavior. Extending these tools to a wider range of species determines whether (and how) we can experimentally approach developmental diversity and evolution. During the last two decades, comparative developmental biology (evo-devo) was marked by the introduction of gene knockdown and deep sequencing technologies that are applicable to a wide range of species. These approaches allowed us to test the developmental role of specific genes in diverse species, to study biological processes that are not accessible in established models and, in some cases, to conduct genome-wide screens that overcome the limitations of the candidate gene approach. The recent discovery of CRISPR/Cas as a means of precise alterations into the genome promises to revolutionize developmental genetics. In this review we describe the development of gene editing tools, from zinc-finger nucleases to TALENs and CRISPR, and examine their application in gene targeting, their limitations and the opportunities they present for evo-devo. We outline their use in gene knock-out and knock-in approaches, and in manipulating gene functions by directing molecular effectors to specific sites in the genome. The ease-of-use and efficiency of CRISPR in diverse species provide an opportunity to close the technology gap that exists between established model organisms and emerging genetically-tractable species.
PMCID: PMC4332929
Comparative developmental biology; Model organisms; Gene targeting; Homologous recombination; Gene-editing nucleases; CRISPR
15.  The evolutionary-developmental analysis of plant microRNAs 
MicroRNAs (miRNAs) control many important aspects of plant development, suggesting these molecules may also have played key roles in the evolution of developmental processes in plants. However, evolutionary-developmental (evo-devo) studies of miRNAs have been held back by technical difficulties in gene identification. To help solve this problem, we have developed a two-step procedure for the efficient identification of miRNA genes in any plant species. As a test case, we have studied the evolution of the MIR164 family in the angiosperms. We have identified novel MIR164 genes in three species occupying key phylogenetic positions and used these, together with published sequence data, to partially reconstruct the evolution of the MIR164 family since the last common ancestor of the extant flowering plants. We use our evolutionary reconstruction to discuss potential roles for MIR164 genes in the evolution of leaf shape and carpel closure in the angiosperms. The techniques we describe may be applied to any miRNA family and should thus enable plant evo-devo to begin to investigate the contributions miRNAs have made to the evolution of plant development.
PMCID: PMC2838268  PMID: 20047873
microRNA; miR164; angiosperm; flower; carpel; leaf dissection
16.  Neofunctionalization in Vertebrates: The Example of Retinoic Acid Receptors 
PLoS Genetics  2006;2(7):e102.
Understanding the role of gene duplications in establishing vertebrate innovations is one of the main challenges of Evo-Devo (evolution of development) studies. Data on evolutionary changes in gene expression (i.e., evolution of transcription factor-cis-regulatory elements relationships) tell only part of the story; protein function, best studied by biochemical and functional assays, can also change. In this study, we have investigated how gene duplication has affected both the expression and the ligand-binding specificity of retinoic acid receptors (RARs), which play a major role in chordate embryonic development. Mammals have three paralogous RAR genes—RARα, β, and γ—which resulted from genome duplications at the origin of vertebrates. By using pharmacological ligands selective for specific paralogues, we have studied the ligand-binding capacities of RARs from diverse chordates species. We have found that RARβ-like binding selectivity is a synapomorphy of all chordate RARs, including a reconstructed synthetic RAR representing the receptor present in the ancestor of chordates. Moreover, comparison of expression patterns of the cephalochordate amphioxus and the vertebrates suggests that, of all the RARs, RARβ expression has remained most similar to that of the ancestral RAR. On the basis of these results together, we suggest that while RARβ kept the ancestral RAR role, RARα and RARγ diverged both in ligand-binding capacity and in expression patterns. We thus suggest that neofunctionalization occurred at both the expression and the functional levels to shape RAR roles during development in vertebrates.
In eukaryotic organisms, each gene is a stretch of DNA composed of control regions that bind transcription factors and coding regions that transcribe the mRNA that is later translated into proteins. At the molecular level, changes in control regions can affect the time and place at which a protein is synthesized, whereas changes in the coding region can alter the protein's function. Retinoic acid receptors (RARs) are chordate-specific transcription factors which, upon binding the natural morphogen retinoic acid, bind to and activate transcription from target genes. Here, the authors show how the ligand specificity of RARs has changed during vertebrate evolution in parallel with changes in expression. Through functional characterization of the RARs from several vertebrates, the chordate amphioxus, and the reconstructed ancestral RAR sequence, the authors show that of the three vertebrate RARs, RARβ has retained the ancestral characteristics in terms of both function and expression, while RARα and γ have evolved by acquiring new functions, both new binding specificity and new expression patterns. Thus both types of evolution have been important in the diversification of vertebrate RARs.
PMCID: PMC1500811  PMID: 16839186
17.  The Hourglass and the Early Conservation Models—Co-Existing Patterns of Developmental Constraints in Vertebrates 
PLoS Genetics  2013;9(4):e1003476.
Developmental constraints have been postulated to limit the space of feasible phenotypes and thus shape animal evolution. These constraints have been suggested to be the strongest during either early or mid-embryogenesis, which corresponds to the early conservation model or the hourglass model, respectively. Conflicting results have been reported, but in recent studies of animal transcriptomes the hourglass model has been favored. Studies usually report descriptive statistics calculated for all genes over all developmental time points. This introduces dependencies between the sets of compared genes and may lead to biased results. Here we overcome this problem using an alternative modular analysis. We used the Iterative Signature Algorithm to identify distinct modules of genes co-expressed specifically in consecutive stages of zebrafish development. We then performed a detailed comparison of several gene properties between modules, allowing for a less biased and more powerful analysis. Notably, our analysis corroborated the hourglass pattern at the regulatory level, with sequences of regulatory regions being most conserved for genes expressed in mid-development but not at the level of gene sequence, age, or expression, in contrast to some previous studies. The early conservation model was supported with gene duplication and birth that were the most rare for genes expressed in early development. Finally, for all gene properties, we observed the least conservation for genes expressed in late development or adult, consistent with both models. Overall, with the modular approach, we showed that different levels of molecular evolution follow different patterns of developmental constraints. Thus both models are valid, but with respect to different genomic features.
Author Summary
During development, vertebrate embryos pass through a “phylotypic” stage, during which their morphology is most similar between different species. This gave rise to the hourglass model, which predicts the highest developmental constraints during mid-embryogenesis. In the last decade, a large effort has been made to uncover the relation between developmental constraints and the evolution of genome. Several studies reported gene characteristics that change according to the hourglass model, e.g. sequence conservation, age, or expression. Here, we first show that some of the previous conclusions do not hold out under detailed analysis of the data. Then, we discuss the disadvantages of the standard evo-devo approach, i.e. comparing descriptive statistics of all genes across development. Results of such analysis are biased by genes expressed constantly during development (housekeeping genes). To overcome this limitation, we use a modularization approach, which reduces the complexity of the data and assures independency between the sets of genes which are compared. We identified distinct sets of genes (modules) with time-specific expression in zebrafish development and analyzed their conservation of sequence, gene expression, and regulatory elements, as well as their age and orthology relationships. Interestingly, we found different patterns of developmental constraints for different gene properties. Only conserved regulatory regions follow an hourglass pattern.
PMCID: PMC3636041  PMID: 23637639
18.  Role of Pleiotropy in the Evolution of a Cryptic Developmental Variation in Caenorhabditis elegans 
PLoS Biology  2012;10(1):e1001230.
Using vulval phenotypes in Caenorhabditis elegans, the authors show that cryptic genetic variation can evolve through selection for pleiotropic effects that alter fitness, and identify a cryptic variant that has conferred enhanced fitness on domesticated worms under laboratory conditions.
Robust biological systems are expected to accumulate cryptic genetic variation that does not affect the system output in standard conditions yet may play an evolutionary role once phenotypically expressed under a strong perturbation. Genetic variation that is cryptic relative to a robust trait may accumulate neutrally as it does not change the phenotype, yet it could also evolve under selection if it affects traits related to fitness in addition to its cryptic effect. Cryptic variation affecting the vulval intercellular signaling network was previously uncovered among wild isolates of Caenorhabditis elegans. Using a quantitative genetic approach, we identify a non-synonymous polymorphism of the previously uncharacterized nath-10 gene that affects the vulval phenotype when the system is sensitized with different mutations, but not in wild-type strains. nath-10 is an essential protein acetyltransferase gene and the homolog of human NAT10. The nath-10 polymorphism also presents non-cryptic effects on life history traits. The nath-10 allele carried by the N2 reference strain leads to a subtle increase in the egg laying rate and in the total number of sperm, a trait affecting the trade-off between fertility and minimal generation time in hermaphrodite individuals. We show that this allele appeared during early laboratory culture of N2, which allowed us to test whether it may have evolved under selection in this novel environment. The derived allele indeed strongly outcompetes the ancestral allele in laboratory conditions. In conclusion, we identified the molecular nature of a cryptic genetic variation and characterized its evolutionary history. These results show that cryptic genetic variation does not necessarily accumulate neutrally at the whole-organism level, but may evolve through selection for pleiotropic effects that alter fitness. In addition, cultivation in the laboratory has led to adaptive evolution of the reference strain N2 to the laboratory environment, which may modify other phenotypes of interest.
Author Summary
Robustness is a property of biological systems that ensures the production of reproducible phenotypes in spite of underlying environmental, stochastic, and genetic variability. A consequence of robustness is that potentially functional genetic variation is free to accumulate in natural populations because it is buffered at the phenotypic level. Even if this so-called “cryptic” genetic variation has no obvious effects under standard conditions, it may become phenotypically expressed upon major genetic or environmental perturbations. Here we used the model organism Caenorhabditis elegans to identify genetic variations involved in the cryptic evolution of vulval cell fate induction between wild strains. We found that a mutation in the essential nath-10 gene not only contributes to cryptic genetic variation in the vulval system, but also affects key life history traits that are expected to be under a strong selective pressure (brood size, age at sexual maturity, sperm number and rate of progeny production). Indeed, an allele of nath-10 that emerged during the laboratory domestication of C. elegans about 50 years ago confers a strong competitive advantage over the ancestral allele under laboratory conditions. A genetic variation that is cryptic for a robust trait can therefore affect more sensitive phenotypes and thus evolve under selection.
PMCID: PMC3250502  PMID: 22235190
19.  Niche adaptation by expansion and reprogramming of general transcription factors 
Experimental analysis of TFB family proteins in a halophilic archaeon reveals complex environment-dependent fitness contributions. Gene conversion events among these proteins can generate novel niche adaptation capabilities, a process that may have contributed to archaeal adaptation to extreme environments.
Evolution of archaeal lineages correlate with duplication events in the TFB family.Each TFB is required for adaptation to multiple environments.The relative fitness contributions of TFBs change with environmental context.Changes in the regulation of duplicated TFBs can generate new adaptation capabilities.
The evolutionary success of an organism depends on its ability to continually adapt to changes in the patterns of constant, periodic, and transient challenges within its environment. This process of ‘niche adaptation' requires reprogramming of the organism's environmental response networks by reorganizing interactions among diverse parts including environmental sensors, signal transducers, and transcriptional and post-transcriptional regulators. Gene duplications have been discovered to be one of the principal strategies in this process, especially for reprogramming of gene regulatory networks (GRNs). Whereas eukaryotes require dozens of factors for recruitment of RNA polymerase, archaea require just two general transcription factors (GTFs) that are orthologous to eukaryotic TFIIB (TFB in archaea) and TATA-binding protein (TBP) (Bell et al, 1998). Both of these GTFs have expanded extensively in nearly 50% of all archaea whose genomes have been fully sequenced. The phylogenetic analysis presented in this study reveal lineage-specific expansions of TFBs, suggesting that they might encode functionally specialized gene regulatory programs for the unique environments to which these organisms have adapted. This hypothesis is particularly appealing when we consider that the greatest expansion is observed within the group of halophilic archaea whose habitats are associated with routine and dynamic changes in a number of environmental factors including light, temperature, oxygen, salinity, and ionic composition (Rodriguez-Valera, 1993; Litchfield, 1998).
We have previously demonstrated that variations in the expanded set of TFBs (a through e) in Halobacterium salinarum NRC-1 manifests at the level of physical interactions within and across the two families, their DNA-binding specificity, their differential regulation in varying environments, and, ultimately, on the large-scale segregation of transcription of all genes into overlapping yet distinct sets of functionally related groups (Facciotti et al, 2007). We have extended findings from this earlier study with a systematic survey of the fitness consequences of perturbing the TFB network of H. salinarum NRC-1 across 17 environments. Notably, each TFB conferred fitness in two or more environmental conditions tested, and the relative fitness contributions (see Table I) of the five TFBs varied significantly by environment. From an evolutionary perspective, the relationships among these fitness landscapes reveal that two classes of TFBs (c/g- and f-type) appear to have played an important role in the evolution of halophilic archaea by overseeing regulation of core physiological capabilities in these organisms. TFBs of the other clades (b/d and a/e) seem to have emerged much more recently through gene duplications or horizontal gene transfers (HGTs) and are being utilized for adaptation to specialized environmental conditions.
We also investigated higher-order functional interactions and relationships among the duplicated TFBs by performing competition experiments and by mapping genetic interactions in different environments. This demonstrated that depending on environmental context, the TFBs have strikingly different functional hierarchies and genetic interactions with one another. This is remarkable as it makes each TFB essential albeit at different times in a dynamically changing environment.
In order to understand the process by which such gene family expansions shape architecture and functioning of a GRN, we performed integrated analysis of phylogeny, physical interactions, regulation, and fitness landscapes of the seven TFBs in H. salinarum NRC-1. This revealed that evolution of both their protein-coding sequence and their promoter has been instrumental in the encoding of environment-specific regulatory programs. Importantly, the convergent and divergent evolution of regulation and binding properties of TFBs suggested that, aside from HGT and random mutations, a third plausible (and perhaps most interesting) mechanism for acquiring a novel TFB variant is through gene conversion. To test this hypothesis, we synthesized a novel TFBx by transferring TFBa/e clade-specific residues to a TFBd backbone, transformed this variant under the control of either the TFBd or the TFBe promoter (PtfbD or PtfbE) into three different host genetic backgrounds (Δura3 (parent), ΔtfbD, and ΔtfbE), and analyzed fitness and gene expression patterns during growth at 25 and 37°C. This showed that gene conversion events spanning the coding sequence and the promoter, environmental context, and genetic background of the host are all extremely influential in the functional integration of a TFB into the GRN. Importantly, this analysis suggested that altering the regulation of an existing set of expanded TFBs might be an efficient mechanism to reprogram the GRN to rapidly generate novel niche adaptation capability. We have confirmed this experimentally by increasing fitness merely by moving tfbE to PtfbD control, and by generating a completely novel phenotype (biofilm-like appearance) by overexpression of tfbE.
Altogether this study clearly demonstrates that archaea can rapidly generate novel niche adaptation programs by simply altering regulation of duplicated TFBs. This is significant because expansions in the TFB family is widespread in archaea, a class of organisms that not only represent 20% of biomass on earth but are also known to have colonized some of the most extreme environments (DeLong and Pace, 2001). This strategy for niche adaptation is further expanded through interactions of the multiple TFBs with members of other expanded TF families such as TBPs (Facciotti et al, 2007) and sequence-specific regulators (e.g. Lrp family (Peeters and Charlier, 2010)). This is analogous to combinatorial solutions for other complex biological problems such as recognition of pathogens by Toll-like receptors (Roach et al, 2005), generation of antibody diversity by V(D)J recombination (Early et al, 1980), and recognition and processing of odors (Malnic et al, 1999).
Numerous lineage-specific expansions of the transcription factor B (TFB) family in archaea suggests an important role for expanded TFBs in encoding environment-specific gene regulatory programs. Given the characteristics of hypersaline lakes, the unusually large numbers of TFBs in halophilic archaea further suggests that they might be especially important in rapid adaptation to the challenges of a dynamically changing environment. Motivated by these observations, we have investigated the implications of TFB expansions by correlating sequence variations, regulation, and physical interactions of all seven TFBs in Halobacterium salinarum NRC-1 to their fitness landscapes, functional hierarchies, and genetic interactions across 2488 experiments covering combinatorial variations in salt, pH, temperature, and Cu stress. This systems analysis has revealed an elegant scheme in which completely novel fitness landscapes are generated by gene conversion events that introduce subtle changes to the regulation or physical interactions of duplicated TFBs. Based on these insights, we have introduced a synthetically redesigned TFB and altered the regulation of existing TFBs to illustrate how archaea can rapidly generate novel phenotypes by simply reprogramming their TFB regulatory network.
PMCID: PMC3261711  PMID: 22108796
evolution by gene family expansion; fitness; niche adaptation; reprogramming of gene regulatory network; transcription factor B
20.  Effects of Ploidy and Recombination on Evolution of Robustness in a Model of the Segment Polarity Network 
PLoS Computational Biology  2009;5(2):e1000296.
Many genetic networks are astonishingly robust to quantitative variation, allowing these networks to continue functioning in the face of mutation and environmental perturbation. However, the evolution of such robustness remains poorly understood for real genetic networks. Here we explore whether and how ploidy and recombination affect the evolution of robustness in a detailed computational model of the segment polarity network. We introduce a novel computational method that predicts the quantitative values of biochemical parameters from bit sequences representing genotype, allowing our model to bridge genotype to phenotype. Using this, we simulate 2,000 generations of evolution in a population of individuals under stabilizing and truncation selection, selecting for individuals that could sharpen the initial pattern of engrailed and wingless expression. Robustness was measured by simulating a mutation in the network and measuring the effect on the engrailed and wingless patterns; higher robustness corresponded to insensitivity of this pattern to perturbation. We compared robustness in diploid and haploid populations, with either asexual or sexual reproduction. In all cases, robustness increased, and the greatest increase was in diploid sexual populations; diploidy and sex synergized to evolve greater robustness than either acting alone. Diploidy conferred increased robustness by allowing most deleterious mutations to be rescued by a working allele. Sex (recombination) conferred a robustness advantage through “survival of the compatible”: those alleles that can work with a wide variety of genetically diverse partners persist, and this selects for robust alleles.
Author Summary
Most so-called “higher organisms” are diploid (have two copies of each gene) and reproduce sexually. Diploidy may be advantageous if one functional copy can mask the effects of a mutation in the other copy; however, it is a liability if most mutations are dominant. Sex can increase genetic diversity and the rate of evolution by creating new combinations of alleles that might function better together but can also disrupt working combinations. Given these trade-offs, why are sex and diploidy so common, and why do they occur so often together? We hypothesize that sex and diploidy allow gene networks to evolve to function more robustly in the face of genetic and environmental variation. This robustness would be advantageous because organisms are exposed to constantly changing environments and all genes undergo mutation. To test this hypothesis, we simulated evolution in a model of the segment polarity network, a well-studied group of genes essential for proper development in many organisms. We compared the robustness of haploid and diploid populations that reproduced either sexually or asexually. Sexually reproducing diploid populations evolved the greatest robustness, suggesting an explanation for the selective advantage of diploid sexual reproduction.
PMCID: PMC2637435  PMID: 19247428
21.  Predictability of Evolutionary Trajectories in Fitness Landscapes 
PLoS Computational Biology  2011;7(12):e1002302.
Experimental studies on enzyme evolution show that only a small fraction of all possible mutation trajectories are accessible to evolution. However, these experiments deal with individual enzymes and explore a tiny part of the fitness landscape. We report an exhaustive analysis of fitness landscapes constructed with an off-lattice model of protein folding where fitness is equated with robustness to misfolding. This model mimics the essential features of the interactions between amino acids, is consistent with the key paradigms of protein folding and reproduces the universal distribution of evolutionary rates among orthologous proteins. We introduce mean path divergence as a quantitative measure of the degree to which the starting and ending points determine the path of evolution in fitness landscapes. Global measures of landscape roughness are good predictors of path divergence in all studied landscapes: the mean path divergence is greater in smooth landscapes than in rough ones. The model-derived and experimental landscapes are significantly smoother than random landscapes and resemble additive landscapes perturbed with moderate amounts of noise; thus, these landscapes are substantially robust to mutation. The model landscapes show a deficit of suboptimal peaks even compared with noisy additive landscapes with similar overall roughness. We suggest that smoothness and the substantial deficit of peaks in the fitness landscapes of protein evolution are fundamental consequences of the physics of protein folding.
Author Summary
Is evolution deterministic, hence predictable, or stochastic, that is unpredictable? What would happen if one could “replay the tape of evolution”: will the outcomes of evolution be completely different or is evolution so constrained that history will be repeated? Arguably, these questions are among the most intriguing and most difficult in evolutionary biology. In other words, the predictability of evolution depends on the fraction of the trajectories on fitness landscapes that are accessible for evolutionary exploration. Because direct experimental investigation of fitness landscapes is technically challenging, the available studies only explore a minuscule portion of the landscape for individual enzymes. We therefore sought to investigate the topography of fitness landscapes within the framework of a previously developed model of protein folding and evolution where fitness is equated with robustness to misfolding. We show that model-derived and experimental landscapes are significantly smoother than random landscapes and resemble moderately perturbed additive landscapes; thus, these landscapes are substantially robust to mutation. The model landscapes show a deficit of suboptimal peaks even compared with noisy additive landscapes with similar overall roughness. Thus, the smoothness and substantial deficit of peaks in fitness landscapes of protein evolution could be fundamental consequences of the physics of protein folding.
PMCID: PMC3240586  PMID: 22194675
22.  The Generation of Variation and The Developmental Basis for Evolutionary Novelty 
Organisms exhibit an incredible diversity of form, a fact that makes the evolution of novelty seemingly self-evident. However, despite the “obvious” case for novelty, defining this concept in evolutionary terms is highly problematic, so much so that some have suggested discarding it altogether. Approaches to this problem tend to take either an adaptation or development-based perspective, but we argue here that an exclusive focus on either of these misses the original intent of the novelty concept and undermines its practical utility. We instead propose that for a feature to be novel it must have evolved both by a transition between adaptive peaks on the fitness landscape and that this transition must have overcome a previous developmental constraint. This definition focuses novelty on the explanation of apparently difficult or low probability evolutionary transitions and highlights how the integration of developmental and functional considerations is necessary to evolutionary explanation. It further reinforces that novelty is a central concern not just of evolutionary developmental biology (i.e., “evo-devo”) but of evolutionary biology more generally. We explore this definition of novelty in light of four examples that range from the obvious to subtle.
PMCID: PMC3648206  PMID: 22649039
Evolutionary novelty; development and evolution; developmental constraint; integration; generation of variation; adaptive landscape
23.  Synonymous Genes Explore Different Evolutionary Landscapes 
PLoS Genetics  2008;4(11):e1000256.
The evolutionary potential of a gene is constrained not only by the amino acid sequence of its product, but by its DNA sequence as well. The topology of the genetic code is such that half of the amino acids exhibit synonymous codons that can reach different subsets of amino acids from each other through single mutation. Thus, synonymous DNA sequences should access different regions of the protein sequence space through a limited number of mutations, and this may deeply influence the evolution of natural proteins. Here, we demonstrate that this feature can be of value for manipulating protein evolvability. We designed an algorithm that, starting from an input gene, constructs a synonymous sequence that systematically includes the codons with the most different evolutionary perspectives; i.e., codons that maximize accessibility to amino acids previously unreachable from the template by point mutation. A synonymous version of a bacterial antibiotic resistance gene was computed and synthesized. When concurrently submitted to identical directed evolution protocols, both the wild type and the recoded sequence led to the isolation of specific, advantageous phenotypic variants. Simulations based on a mutation isolated only from the synthetic gene libraries were conducted to assess the impact of sub-functional selective constraints, such as codon usage, on natural adaptation. Our data demonstrate that rational design of synonymous synthetic genes stands as an affordable improvement to any directed evolution protocol. We show that using two synonymous DNA sequences improves the overall yield of the procedure by increasing the diversity of mutants generated. These results provide conclusive evidence that synonymous coding sequences do experience different areas of the corresponding protein adaptive landscape, and that a sequence's codon usage effectively constrains the evolution of the encoded protein.
Author Summary
Evolutionary processes largely rely on the production of diversity. Genetic robustness, by allowing the accumulation of neutral diversity within a population, has been associated with increase in evolutionary potential (evolvability). In this work, we propose to use a well-known source of robustness, the redundancy of the genetic code, to alter the evolvability of any protein. The topology of the code allows synonymous codons to sample different mutational neighborhoods. Using this property, we developed an algorithm to design synonymous sequences with maximally divergent evolutionary potentials relative to the input sequences. At the population level, each of these sequences expands the scope of the evolutionary landscape that can be explored by the encoded protein, and ultimately increase the odds of uncovering adaptive mutants. We applied this principle to evolve new antibiotic resistance phenotype variants. Fundamentally, our results provide an example of how neutral diversity may favor evolvability. Moreover, in light of the rapid development in nucleic acid synthesis, the use of rationally designed synonymous genes offers a profitable enhancement to any directed evolution procedure.
PMCID: PMC2575237  PMID: 19008944
24.  Robustness Can Evolve Gradually in Complex Regulatory Gene Networks with Varying Topology 
PLoS Computational Biology  2007;3(2):e15.
The topology of cellular circuits (the who-interacts-with-whom) is key to understand their robustness to both mutations and noise. The reason is that many biochemical parameters driving circuit behavior vary extensively and are thus not fine-tuned. Existing work in this area asks to what extent the function of any one given circuit is robust. But is high robustness truly remarkable, or would it be expected for many circuits of similar topology? And how can high robustness come about through gradual Darwinian evolution that changes circuit topology gradually, one interaction at a time? We here ask these questions for a model of transcriptional regulation networks, in which we explore millions of different network topologies. Robustness to mutations and noise are correlated in these networks. They show a skewed distribution, with a very small number of networks being vastly more robust than the rest. All networks that attain a given gene expression state can be organized into a graph whose nodes are networks that differ in their topology. Remarkably, this graph is connected and can be easily traversed by gradual changes of network topologies. Thus, robustness is an evolvable property. This connectedness and evolvability of robust networks may be a general organizational principle of biological networks. In addition, it exists also for RNA and protein structures, and may thus be a general organizational principle of all biological systems.
Author Summary
Living things are astonishingly complex, yet unlike houses of cards they are also highly robust. That is, they have persisted for billions of years, despite being exposed to an endless stream of environmental stressors and random mutations. Is this robustness an evolvable property? Do different biological systems vary in their robustness? Has natural selection shaped this robustness? These questions are very difficult to answer experimentally for most systems, be they proteins or large gene networks. Here we address these questions with a model of the transcription regulation networks that regulate both cellular functions and embryonic development in many organisms. We examine millions of such networks that differ in the topology or architecture of their regulatory interactions, that is, in the “who interacts with whom” of a network. We find that radically different network architectures can show the same gene expression pattern. The networks' robustness to both mutations and gene expression noise shows a broad distribution: some network architectures are highly robust, whereas others are quite fragile. Importantly, the entire space of network architectures can be traversed through small changes of individual regulatory interactions, without changing a network's gene expression pattern. This means that high robustness in gene expression can evolve through gradual and neutral evolution in the space of network architectures. Our results show that the robustness of transcriptional regulation networks is an evolvable trait that natural selection can change like any other trait.
PMCID: PMC1794322  PMID: 17274682
25.  Isolation-by-Distance and Outbreeding Depression Are Sufficient to Drive Parapatric Speciation in the Absence of Environmental Influences 
PLoS Computational Biology  2008;4(7):e1000126.
A commonly held view in evolutionary biology is that speciation (the emergence of genetically distinct and reproductively incompatible subpopulations) is driven by external environmental constraints, such as localized barriers to dispersal or habitat-based variation in selection pressures. We have developed a spatially explicit model of a biological population to study the emergence of spatial and temporal patterns of genetic diversity in the absence of predetermined subpopulation boundaries. We propose a 2-D cellular automata model showing that an initially homogeneous population might spontaneously subdivide into reproductively incompatible species through sheer isolation-by-distance when the viability of offspring decreases as the genomes of parental gametes become increasingly different. This simple implementation of the Dobzhansky-Muller model provides the basis for assessing the process and completion of speciation, which is deemed to occur when there is complete postzygotic isolation between two subpopulations. The model shows an inherent tendency toward spatial self-organization, as has been the case with other spatially explicit models of evolution. A well-mixed version of the model exhibits a relatively stable and unimodal distribution of genetic differences as has been shown with previous models. A much more interesting pattern of temporal waves, however, emerges when the dispersal of individuals is limited to short distances. Each wave represents a subset of comparisons between members of emergent subpopulations diverging from one another, and a subset of these divergences proceeds to the point of speciation. The long-term persistence of diverging subpopulations is the essence of speciation in biological populations, so the rhythmic diversity waves that we have observed suggest an inherent disposition for a population experiencing isolation-by-distance to generate new species.
Author Summary
A commonly held view in evolutionary biology is that new species form in response to environmental factors, such as habitat differences or barriers to individual movements that sever a population. We have developed a computer model, called EvoSpace, that illustrates how new species can emerge when a species range becomes very large compared with the dispersal distances of its individuals. This situation has been called isolation-by-distance because remote parts of the range can take different evolutionary paths even though there is no particular place where we would expect different populations to separate. When the extent of genetic difference between individuals is coupled with decreasing offspring viability (e.g., resulting from developmental problems), EvoSpace predicts that sharp spatial boundaries can emerge in arbitrary locations, separating subpopulations that occasionally persist long enough to become reproductively incompatible species. The model shows an inherent tendency toward spatial self-organization, in contrast with the traditional view of environmentally forced origins of new species. We think that isolation-by-distance is a common aspect of the evolutionary process and that spatial self-organization of gene pools may often facilitate the evolution of new species.
PMCID: PMC2440541  PMID: 18654617

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