The frailty of adaptive hypotheses for the origins of organismal complexity

Low exchangeability of selenocysteine, the 21st amino acid, in vertebrate proteins

Selenocysteine (Sec), the 21st amino acid, is incorporated into proteins through the recoding of a termination codon, an inefficient translational process mediated by a complex molecular machinery. Sec is a rare amino acid in extant proteins, chemically similar to cysteine (Cys), found in homologous position to Cys of nonselenoprotein families. Selenoproteins account for the dependence of vertebrates on environmental selenium (Se) and have an important role in several Se-deficiency diseases. Selenoproteins are poorly characterized enzymes and reports on the functional exchangeability of Sec with Cys are limited and controversial. Whether the unique role of Sec in some selenoenzymes illustrates the broader contribution of Se to protein function is unknown (Gromer S, Johansson L, Bauer H, Arscott LD, Rauch S, Ballou DP, Williams CH Jr, Schirmer RH, Arnér ES. 2003. Active sites of thioredoxin reductases: why selenoproteins? Proc Natl Acad Sci USA. 100:12618-12623). Here, we address this question from an evolutionary perspective by the simultaneous identification of the patterns of divergence in almost half a billion years of vertebrate evolution and diversity within the human lineage for the full complement of enzymatic Sec residues in these proteomes. We complete this analysis with data for the homologous Cys residues in the same genomes. Our results indicate concerted purifying selection across Sec and Cys sites in all selenoproteomes, consistent with a unique role of Sec in protein function, low exchangeability, and an unknown degree of functional divergence with Cys homologs. The distinct biochemical properties of Sec, rather than the geographical distribution of Se, global O(2) levels or Sec metabolic cost, appear to play a major role in driving adaptive changes in vertebrate selenoproteomes. A better understanding of the selenoproteomes and neutral evolutionary patterns in other taxa will be necessary to fully assess the generality of this conclusion.

Trade-offs between efficiency and robustness in bacterial metabolic networks are associated with niche breadth

The relation between structure and function in biologic networks is a central point of systems biology research. Key functional features--notably, efficiency and robustness--are linked to the topologic structure of a network, and there appears to be a degree of trade-off between these features, i.e., simulation studies indicate that more efficient networks tend to be less robust. Here, we investigate this issue in metabolic networks from 105 lineages of bacteria having a wide range of ecologies. We take quantitative measurements on each network and integrate this network data with ecologic data using a phylogenetic comparative model. In this setting, we find that biologic conclusions obtained with classical phylogenetic comparative methods are sensitive to correlations between model covariates and phylogenetic branch length. To avoid this problem, we propose a revised statistical framework--hierarchical mixed-effect regression--to accommodate phylogenetic nonindependence. Using this approach, we show that the cartography of metabolic networks does indeed reflect a trade-off between efficiency and robustness. Furthermore, ecologic characteristics related to niche breadth are strong predictors of network shape. Given the broad variation in niche breadth seen among species, we predict that there is no universally optimal balance between efficiency and robustness in bacterial metabolic networks and, thus, no universally optimal network structure. These results highlight the biologic relevance of variation in network structure and the potential role of niche breadth in shaping metabolic strategies of efficiency and robustness.

Dynamics of hybrid incompatibility in gene networks in a constant environment

After an ancestral population splits into two allopatric populations, different mutations may fix in each. When pairs of mutations are brought together in a hybrid offspring, epistasis may cause reduced fitness. Such pairs are known as Bateson-Dobzhansky-Muller (BDM) incompatibilities. A well-known model of BDM incompatibility due to Orr suggests that the fitness load on hybrids should initially accelerate, and continue to increase as the number of potentially incompatible substitutions increases (the "snowball effect"). In the gene networks model, which violates a key assumption of Orr's model (independence of fixation probabilities), the snowball effect often does not occur. Instead, we describe three possible dynamics in a constant environment: (1) Stabilizing selection can constrain two allopatric populations to remain near-perfectly compatible. (2) Despite constancy of environment, punctuated evolution may obtain; populations may experience rare adaptations asynchronously, permitting incompatibility. (3) Despite stabilizing selection, developmental system drift may permit genetic change, allowing two populations to drift in and out of compatibility. We reinterpret Orr's model in terms of genetic distance. We extend Orr's model to the finite loci case, which can limit incompatibility. Finally, we suggest that neutral evolution of gene regulation in nature, to the point of speciation, is a distinct possibility.

Evolution of the Caenorhabditis elegans genome

A fundamental problem in genome biology is to elucidate the evolutionary forces responsible for generating nonrandom patterns of genome organization. As the first metazoan to benefit from full-genome sequencing, Caenorhabditis elegans has been at the forefront of research in this area. Studies of genomic patterns, and their evolutionary underpinnings, continue to be augmented by the recent push to obtain additional full-genome sequences of related Caenorhabditis taxa. In the near future, we expect to see major advances with the onset of whole-genome resequencing of multiple wild individuals of the same species. In this review, we synthesize many of the important insights to date in our understanding of genome organization and function that derive from the evolutionary principles made explicit by theoretical population genetics and molecular evolution and highlight fertile areas for future research on unanswered questions in C. elegans genome evolution. We call attention to the need for C. elegans researchers to generate and critically assess nonadaptive hypotheses for genomic and developmental patterns, in addition to adaptive scenarios. We also emphasize the potential importance of evolution in the gonochoristic (female and male) ancestors of the androdioecious (hermaphrodite and male) C. elegans as the source for many of its genomic and developmental patterns.

Towards a postmodern synthesis of evolutionary biology

In 2009, we are celebrating the 200th anniversary of Charles Darwin and the 150th jubilee of his masterpiece, the Origin of Species. Darwin developed the first coherent and compelling narrative of biological evolution and thus founded evolutionary biology-and modern biology in general, remembering the famous dictum of Dobzhansky. It is, however, counter-productive, and ultimately, a disservice to Darwin's legacy, to define modern evolutionary biology as neo-Darwinism. The current picture of evolution, informed, in particular, by results of comparative genomics and systems biology, is by far more complex than that presented in the Origin of Species, so that Darwinian principles, including natural selection, are incorporated into the evolving new synthesis as important but certainly not all-embracing tenets. This expansion of evolutionary biology does not denigrate Darwin in the least but rather emphasizes the fertility of his ideas.

A framework for evolutionary systems biology

BACKGROUND

Many difficult problems in evolutionary genomics are related to mutations that have weak effects on fitness, as the consequences of mutations with large effects are often simple to predict. Current systems biology has accumulated much data on mutations with large effects and can predict the properties of knockout mutants in some systems. However experimental methods are too insensitive to observe small effects.

RESULTS

Here I propose a novel framework that brings together evolutionary theory and current systems biology approaches in order to quantify small effects of mutations and their epistatic interactions in silico. Central to this approach is the definition of fitness correlates that can be computed in some current systems biology models employing the rigorous algorithms that are at the core of much work in computational systems biology. The framework exploits synergies between the realism of such models and the need to understand real systems in evolutionary theory. This framework can address many longstanding topics in evolutionary biology by defining various 'levels' of the adaptive landscape. Addressed topics include the distribution of mutational effects on fitness, as well as the nature of advantageous mutations, epistasis and robustness. Combining corresponding parameter estimates with population genetics models raises the possibility of testing evolutionary hypotheses at a new level of realism.

CONCLUSION

EvoSysBio is expected to lead to a more detailed understanding of the fundamental principles of life by combining knowledge about well-known biological systems from several disciplines. This will benefit both evolutionary theory and current systems biology. Understanding robustness by analysing distributions of mutational effects and epistasis is pivotal for drug design, cancer research, responsible genetic engineering in synthetic biology and many other practical applications.

Darwinian evolution in the light of genomics

Comparative genomics and systems biology offer unprecedented opportunities for testing central tenets of evolutionary biology formulated by Darwin in the Origin of Species in 1859 and expanded in the Modern Synthesis 100 years later. Evolutionary-genomic studies show that natural selection is only one of the forces that shape genome evolution and is not quantitatively dominant, whereas non-adaptive processes are much more prominent than previously suspected. Major contributions of horizontal gene transfer and diverse selfish genetic elements to genome evolution undermine the Tree of Life concept. An adequate depiction of evolution requires the more complex concept of a network or ‘forest’ of life. There is no consistent tendency of evolution towards increased genomic complexity, and when complexity increases, this appears to be a non-adaptive consequence of evolution under weak purifying selection rather than an adaptation. Several universals of genome evolution were discovered including the invariant distributions of evolutionary rates among orthologous genes from diverse genomes and of paralogous gene family sizes, and the negative correlation between gene expression level and sequence evolution rate. Simple, non-adaptive models of evolution explain some of these universals, suggesting that a new synthesis of evolutionary biology might become feasible in a not so remote future.

Plasticity and errors of a robust developmental system in different environments

Many developmental processes generate invariant phenotypes in a wide range of ecological conditions. Such robustness to environmental variation is a fundamental biological property, yet its extent, limits, and adaptive significance have rarely been assessed empirically. Here we tested how environmental variation affects vulval formation in Caenorhabditis nematodes. In different environments, a correct vulval pattern develops with high precision, but rare deviant patterns reveal the system's limits and how its mechanisms respond to environmental challenges. Key features of the apparent robustness are functional redundancy among vulval precursor cells and tolerance to quantitative variation in Ras, Notch, and Wnt pathway activities. The observed environmental responses and precision of vulval patterning vary within and between Caenorhabditis species. These results highlight the complex response of developmental systems to the environment and illustrate how a robust and invariant phenotype may result through cellular and molecular processes that are highly plastic--across environments and evolution.

Harnessing genomics for evolutionary insights

Next-generation DNA sequencing technologies can generate unprecedented amounts of genomic data, even for non-model organisms. Here we describe how these new technologies have facilitated recent key advances in ecology and evolutionary biology, and highlight several outstanding ecological and evolutionary questions that are distinctly suited to the innovations they provide. Importantly, using these technologies to their full potential requires careful experimental design and critical consideration of several caveats associated with them. Although several significant challenges remain to be resolved before the integration of next-generation sequencing technologies into single-investigator research programs, we argue that they will soon transform ecology and evolution by fundamentally changing the ranges and types of questions that can be addressed.

Evolution of genome architecture

Charles Darwin believed that all traits of organisms have been honed to near perfection by natural selection. The empirical basis underlying Darwin's conclusions consisted of numerous observations made by him and other naturalists on the exquisite adaptations of animals and plants to their natural habitats and on the impressive results of artificial selection. Darwin fully appreciated the importance of heredity but was unaware of the nature and, in fact, the very existence of genomes. A century and a half after the publication of the "Origin", we have the opportunity to draw conclusions from the comparisons of hundreds of genome sequences from all walks of life. These comparisons suggest that the dominant mode of genome evolution is quite different from that of the phenotypic evolution. The genomes of vertebrates, those purported paragons of biological perfection, turned out to be veritable junkyards of selfish genetic elements where only a small fraction of the genetic material is dedicated to encoding biologically relevant information. In sharp contrast, genomes of microbes and viruses are incomparably more compact, with most of the genetic material assigned to distinct biological functions. However, even in these genomes, the specific genome organization (gene order) is poorly conserved. The results of comparative genomics lead to the conclusion that the genome architecture is not a straightforward result of continuous adaptation but rather is determined by the balance between the selection pressure, that is itself dependent on the effective population size and mutation rate, the level of recombination, and the activity of selfish elements. Although genes and, in many cases, multigene regions of genomes possess elaborate architectures that ensure regulation of expression, these arrangements are evolutionarily volatile and typically change substantially even on short evolutionary scales when gene sequences diverge minimally. Thus, the observed genome architectures are, mostly, products of neutral processes or epiphenomena of more general selective processes, such as selection for genome streamlining in successful lineages with large populations. Selection for specific gene arrangements (elements of genome architecture) seems only to modulate the results of these processes.

Systems biology spins off a new model for the study of canalization

The tools of systems biology make possible the study of phenotypic robustness at the molecular level. A recent investigation by Ansel et al. shows that alleles with different capabilities to buffer noise in gene expression - variation in protein abundance among genetically identical cells - segregate in populations of budding yeasts. These findings show that there is raw material for robust gene expression to evolve by natural selection, enabling the study of canalization of gene networks as it evolves in nature.

Turning a hobby into a job: how duplicated genes find new functions

Gene duplication provides raw material for functional innovation. Recent advances have shed light on two fundamental questions regarding gene duplication: which genes tend to undergo duplication? And how does natural selection subsequently act on them? Genomic data suggest that different gene classes tend to be retained after single-gene and whole-genome duplications. We also know that functional differences between duplicate genes can originate in several different ways, including mutations that directly impart new functions, subdivision of ancestral functions and selection for changes in gene dosage. Interestingly, in many cases the 'new' function of one copy is a secondary property that was always present, but that has been co-opted to a primary role after the duplication.

The evolutionary dynamics of evolvability in a gene network model

Evolvability, the ability of populations to adapt, has recently emerged as a major unifying concept in biology. Although the study of evolvability offers new insights into many important biological questions, the conceptual bases of evolvability, and the mechanisms of its evolution, remain controversial. We used simulated evolution of a model of gene network dynamics to test the contentious hypothesis that natural selection can favour high evolvability, in particular in sexual populations. Our results conclusively demonstrate that fluctuating natural selection can increase the capacity of model gene networks to adapt to new environments. Detailed studies of the evolutionary dynamics of these networks establish a broad range of validity for this result and quantify the evolutionary forces responsible for changes in evolvability. Analysis of the genotype-phenotype map of these networks also reveals mechanisms connecting evolvability, genetic architecture and robustness. Our results suggest that the evolution of evolvability can have a pervasive influence on many aspects of organisms.

A critical view of metabolic network adaptations

There has been considerable recent interest in deciphering the adaptive properties underlying the structure and function of metabolic networks. Various features of metabolic networks such as the global topology, distribution of fluxes, and mutational robustness, have been proposed to have adaptive significance and hence reflect design principles. However, whether evolutionary processes alternative to direct selection on the trait under investigation also play a role is often ignored and the selection pressures maintaining a given metabolic trait often remain speculative. Some systems-level traits might simply arise as by-products of selection on other traits or even through random genetic drift. Here, we ask which systems-level aspects of metabolism are likely to have adaptive utility and which could be better explained as by-products of other evolutionary forces. We conclude that the global topological characteristics of metabolic networks and their mutational robustness are unlikely to be directly shaped by natural selection. Conversely, models of optimal design revealed that various aspects of individual pathways and the behavior of the whole network show signs of adaptations, even though the exact selective forces often remain elusive. Comparative and experimental approaches, which so far have been relatively rarely employed, could help to distinguish between alternative adaptive scenarios.

Copying and evolution of neuronal topology

We propose a mechanism for copying of neuronal networks that is of considerable interest for neuroscience for it suggests a neuronal basis for causal inference, function copying, and natural selection within the human brain. To date, no model of neuronal topology copying exists. We present three increasingly sophisticated mechanisms to demonstrate how topographic map formation coupled with Spike-Time Dependent Plasticity (STDP) can copy neuronal topology motifs. Fidelity is improved by error correction and activity-reverberation limitation. The high-fidelity topology-copying operator is used to evolve neuronal topologies. Possible roles for neuronal natural selection are discussed.

The evolution of cell types in animals: emerging principles from molecular studies

Cell types are fundamental units of multicellular life but their evolution is obscure. How did the first cell types emerge and become distinct in animal evolution? What were the sets of cell types that existed at important evolutionary nodes that represent eumetazoan or bilaterian ancestors? How did these ancient cell types diversify further during the evolution of organ systems in the descending evolutionary lines? The recent advent of cell type molecular fingerprinting has yielded initial insights into the evolutionary interrelationships of cell types between remote animal phyla and has allowed us to define some first principles of cell type diversification in animal evolution.

Epistasis--the essential role of gene interactions in the structure and evolution of genetic systems

Epistasis, or interactions between genes, has long been recognized as fundamentally important to understanding the structure and function of genetic pathways and the evolutionary dynamics of complex genetic systems. With the advent of high-throughput functional genomics and the emergence of systems approaches to biology, as well as a new-found ability to pursue the genetic basis of evolution down to specific molecular changes, there is a renewed appreciation both for the importance of studying gene interactions and for addressing these questions in a unified, quantitative manner.

A diversity of uncharacterized reverse transcriptases in bacteria

Retroelements are usually considered to be eukaryotic elements because of the large number and variety in eukaryotic genomes. By comparison, reverse transcriptases (RTs) are rare in bacteria, with only three characterized classes: retrons, group II introns and diversity-generating retroelements (DGRs). Here, we present the results of a bioinformatic survey that aims to define the landscape of RTs across eubacterial, archaeal and phage genomes. We identify and categorize 1021 RTs, of which the majority are group II introns (73%). Surprisingly, a plethora of novel RTs are found that do not belong to characterized classes. The RTs have 11 domain architectures and are classified into 20 groupings based on sequence similarity, phylogenetic analyses and open reading frame domain structures. Interestingly, group II introns are the only bacterial RTs to exhibit clear evidence for independent mobility, while five other groups have putative functions in defense against phage infection or promotion of phage infection. These examples suggest that additional beneficial functions will be discovered among uncharacterized RTs. The study lays the groundwork for experimental characterization of these highly diverse sequences and has implications for the evolution of retroelements.

From protein interactions to functional annotation: graph alignment in Herpes

Background

Sequence alignment is a prolific basis of functional annotation, but remains a challenging problem in the 'twilight zone' of high sequence divergence or short gene length. Here we demonstrate how information on gene interactions can help to resolve ambiguous sequence alignments. We compare two distant Herpes viruses by constructing a graph alignment, which is based jointly on the similarity of their protein interaction networks and on sequence similarity. This hybrid method provides functional associations between proteins of the two organisms that cannot be obtained from sequence or interaction data alone.

Results

We find proteins where interaction similarity and sequence similarity are individually weak, but together provide significant evidence of orthology. There are also proteins with high interaction similarity but without any detectable sequence similarity, providing evidence of functional association beyond sequence homology. The functional predictions derived from our alignment are consistent with genomic position and gene expression data.

Conclusion

Our approach shows that evolutionary conservation is a powerful filter to make protein interaction data informative about functional similarities between the interacting proteins, and it establishes graph alignment as a powerful tool for the comparative analysis of data from highly diverged species.

Introduction. Extent, processes and evolutionary impact of interspecific hybridization in animals

Since the time of Charles Darwin, studies of interspecific hybridization have been a major focus for evolutionary biologists. Although this phenomenon has often been viewed as problematic in the fields of ecology, taxonomy and systematics, it has become a primary source of data for studies on speciation and adaptation. Effects from genetic/evolutionary processes, such as recombination and natural selection, usually develop over extended periods of time; however, they are accelerated in cases of hybridization. Interspecific hybrids exhibit novel genomes that are exposed to natural selection, thus providing a key to unravel the ultimate causes of adaptation and speciation. Here we provide firstly a historic perspective of hybridization research, secondly a novel attempt to assess the extent of hybridization among animals and thirdly an overview of the reviews and case studies presented in this theme issue.

Genomics of bacteria and archaea: the emerging dynamic view of the prokaryotic world

The first bacterial genome was sequenced in 1995, and the first archaeal genome in 1996. Soon after these breakthroughs, an exponential rate of genome sequencing was established, with a doubling time of approximately 20 months for bacteria and approximately 34 months for archaea. Comparative analysis of the hundreds of sequenced bacterial and dozens of archaeal genomes leads to several generalizations on the principles of genome organization and evolution. A crucial finding that enables functional characterization of the sequenced genomes and evolutionary reconstruction is that the majority of archaeal and bacterial genes have conserved orthologs in other, often, distant organisms. However, comparative genomics also shows that horizontal gene transfer (HGT) is a dominant force of prokaryotic evolution, along with the loss of genetic material resulting in genome contraction. A crucial component of the prokaryotic world is the mobilome, the enormous collection of viruses, plasmids and other selfish elements, which are in constant exchange with more stable chromosomes and serve as HGT vehicles. Thus, the prokaryotic genome space is a tightly connected, although compartmentalized, network, a novel notion that undermines the ‘Tree of Life’ model of evolution and requires a new conceptual framework and tools for the study of prokaryotic evolution.

Nested genes and increasing organizational complexity of metazoan genomes

The most common form of protein-coding gene overlap in eukaryotes is a simple nested structure, whereby one gene is embedded in an intron of another. Analysis of nested protein-coding genes in vertebrates, fruit flies and nematodes revealed substantially higher rates of evolutionary gains than losses. The accumulation of nested gene structures could not be attributed to any obvious functional relationships between the genes involved and represents an increase of the organizational complexity of animal genomes via a neutral process.

The evolution of combinatorial gene regulation in fungi

It is widely suspected that gene regulatory networks are highly plastic. The rapid turnover of transcription factor binding sites has been predicted on theoretical grounds and has been experimentally demonstrated in closely related species. We combined experimental approaches with comparative genomics to focus on the role of combinatorial control in the evolution of a large transcriptional circuit in the fungal lineage. Our study centers on Mcm1, a transcriptional regulator that, in combination with five cofactors, binds roughly 4% of the genes in Saccharomyces cerevisiae and regulates processes ranging from the cell-cycle to mating. In Kluyveromyces lactis and Candida albicans, two other hemiascomycetes, we find that the Mcm1 combinatorial circuits are substantially different. This massive rewiring of the Mcm1 circuitry has involved both substantial gain and loss of targets in ancient combinatorial circuits as well as the formation of new combinatorial interactions. We have dissected the gains and losses on the global level into subsets of functionally and temporally related changes. One particularly dramatic change is the acquisition of Mcm1 binding sites in close proximity to Rap1 binding sites at 70 ribosomal protein genes in the K. lactis lineage. Another intriguing and very recent gain occurs in the C. albicans lineage, where Mcm1 is found to bind in combination with the regulator Wor1 at many genes that function in processes associated with adaptation to the human host, including the white-opaque epigenetic switch. The large turnover of Mcm1 binding sites and the evolution of new Mcm1–cofactor interactions illuminate in sharp detail the rapid evolution of combinatorial transcription networks.

In explaining the diversity of organisms on Earth, it is increasingly evident that evolutionary changes in when and where genes are expressed provide a crucial source of variation. By using genome-wide transcription factor localization experiments in S. cerevisiae, K. lactis, and C. albicans, combined with comparative genomics across many more yeast species, we examined how a large combinatorial transcription circuit evolves over the course of hundreds of millions of years. Combinatorial regulation is pervasive in eukaryotic organisms and is thought to allow for increased specificity and integration of multiple signals in the control of gene expression. Our studies focused on one prolific combinatorial regulator, Mcm1, which, in combination with five cofactors, binds and regulates genes functioning in a diverse range of cellular processes in S. cerevisiae. We found evidence of massive network rewiring, including high rates of gain and loss of Mcm1 binding sites and the formation of new Mcm1–cofactor combinations and the breaking of old ones. We propose that the multiple protein–protein and protein–DNA interactions that specify transcription in combinatorial circuits allow for a richness of compensatory mutations and thereby provide ample opportunity for both adaptive and neutral evolution.

Experimental approaches combined with comparative genomics show how a large combinatorial transcription circuit has rewired over evolutionary time scales.

Tilting at quixotic trait loci (QTL): an evolutionary perspective on genetic causation

Recent years have seen great advances in generating and analyzing data to identify the genetic architecture of biological traits. Human disease has understandably received intense research focus, and the genes responsible for most Mendelian diseases have successfully been identified. However, the same advances have shown a consistent if less satisfying pattern, in which complex traits are affected by variation in large numbers of genes, most of which have individually minor or statistically elusive effects, leaving the bulk of genetic etiology unaccounted for. This pattern applies to diverse and unrelated traits, not just disease, in basically all species, and is consistent with evolutionary expectations, raising challenging questions about the best way to approach and understand biological complexity.

Evolutionary origins of invasive populations

What factors shape the evolution of invasive populations? Recent theoretical and empirical studies suggest that an evolutionary history of disturbance might be an important factor. This perspective presents hypotheses regarding the impact of disturbance on the evolution of invasive populations, based on a synthesis of the existing literature. Disturbance might select for life-history traits that are favorable for colonizing novel habitats, such as rapid population growth and persistence. Theoretical results suggest that disturbance in the form of fluctuating environments might select for organismal flexibility, or alternatively, the evolution of evolvability. Rapidly fluctuating environments might favor organismal flexibility, such as broad tolerance or plasticity. Alternatively, longer fluctuations or environmental stress might lead to the evolution of evolvability by acting on features of the mutation matrix. Once genetic variance is generated via mutations, temporally fluctuating selection across generations might promote the accumulation and maintenance of genetic variation. Deeper insights into how disturbance in native habitats affects evolutionary and physiological responses of populations would give us greater capacity to predict the populations that are most likely to tolerate or adapt to novel environments during habitat invasions. Moreover, we would gain fundamental insights into the evolutionary origins of invasive populations.

Evolution of complexity in RNA-like replicator systems

BACKGROUND

The evolution of complexity is among the most important questions in biology. The evolution of complexity is often observed as the increase of genetic information or that of the organizational complexity of a system. It is well recognized that the formation of biological organization--be it of molecules or ecosystems--is ultimately instructed by the genetic information, whereas it is also true that the genetic information is functional only in the context of the organization. Therefore, to obtain a more complete picture of the evolution of complexity, we must study the evolution of both information and organization.

RESULTS

Here we investigate the evolution of complexity in a simulated RNA-like replicator system. The simplicity of the system allows us to explicitly model the genotype-phenotype-interaction mapping of individual replicators, whereby we avoid preconceiving the functionality of genotypes (information) or the ecological organization of replicators in the model. In particular, the model assumes that interactions among replicators--to replicate or to be replicated--depend on their secondary structures and base-pair matching. The results showed that a population of replicators, originally consisting of one genotype, evolves to form a complex ecosystem of up to four species. During this diversification, the species evolve through acquiring unique genotypes with distinct ecological functionality. The analysis of this diversification reveals that parasitic replicators, which have been thought to destabilize the replicator's diversity, actually promote the evolution of diversity through generating a novel "niche" for catalytic replicators. This also makes the current replicator system extremely stable upon the evolution of parasites. The results also show that the stability of the system crucially depends on the spatial pattern formation of replicators. Finally, the evolutionary dynamics is shown to significantly depend on the mutation rate.

CONCLUSION

The interdependence of information and organization can play an important role for the evolution of complexity. Namely, the emergent ecosystem supplies a context in which a novel phenotype gains functionality. Realizing such a phenotype, novel genotypes can evolve, which, in turn, results in the evolution of more complex ecological organization. Hence, the evolutionary feedback between information and organization, and thereby the evolution of complexity.

Recognizing student misconceptions through Ed's Tools and the Biology Concept Inventory

Recognizing student misconceptions is critical for effective teaching. Tools that reveal student thinking indicate that misunderstanding randomness interferes with learning of molecular dynamics and evolutionary processes.

Understanding randomness and its impact on student learning: lessons learned from building the Biology Concept Inventory (BCI)

While researching student assumptions for the development of the Biology Concept Inventory (BCI; http://bioliteracy.net), we found that a wide class of student difficulties in molecular and evolutionary biology appears to be based on deep-seated, and often unaddressed, misconceptions about random processes. Data were based on more than 500 open-ended (primarily) college student responses, submitted online and analyzed through our Ed's Tools system, together with 28 thematic and think-aloud interviews with students, and the responses of students in introductory and advanced courses to questions on the BCI. Students believe that random processes are inefficient, whereas biological systems are very efficient. They are therefore quick to propose their own rational explanations for various processes, from diffusion to evolution. These rational explanations almost always make recourse to a driver, e.g., natural selection in evolution or concentration gradients in molecular biology, with the process taking place only when the driver is present, and ceasing when the driver is absent. For example, most students believe that diffusion only takes place when there is a concentration gradient, and that the mutational processes that change organisms occur only in response to natural selection pressures. An understanding that random processes take place all the time and can give rise to complex and often counterintuitive behaviors is almost totally absent. Even students who have had advanced or college physics, and can discuss diffusion correctly in that context, cannot make the transfer to biological processes, and passing through multiple conventional biology courses appears to have little effect on their underlying beliefs.

The evolution of genetic networks by non-adaptive processes

Although numerous investigators assume that the global features of genetic networks are moulded by natural selection, there has been no formal demonstration of the adaptive origin of any genetic network. This Analysis shows that many of the qualitative features of known transcriptional networks can arise readily through the non-adaptive processes of genetic drift, mutation and recombination, raising questions about whether natural selection is necessary or even sufficient for the origin of many aspects of gene-network topologies. The widespread reliance on computational procedures that are devoid of population-genetic details to generate hypotheses for the evolution of network configurations seems to be unjustified.