Yeast as a model organism for studying the evolution of non-standard genetic codes.

During the last 30 years, a number of alterations to the standard genetic code have been uncovered both in prokaryotes and eukaryotic nuclear and mitochondrial genomes. But, the study of the evolutionary pathways and molecular mechanisms of codon identity redefinition has been largely ignored due to the assumption that non-standard genetic codes can only evolve through neutral evolutionary mechanisms and that they have no functional significance. The recent discovery of a genetic code change in the genus Candida that evolved through an ambiguous messenger RNA decoding mechanism is bringing that naive assumption to an abrupt end by showing, in a rather dramatic way, that genetic code changes have profound physiological and evolutionary consequences for the species that redefine codon identity. In this paper, the recent data on the evolution of the Candida genetic code are reviewed and an experimental framework based on forced evolution, molecular genetics and comparative and functional genomics methodologies is put forward for the study of non-standard genetic codes and genetic code ambiguity in general. Additionally, the importance of using Saccharomyces cerevisiae as a model organism for elucidating the evolutionary pathway of the Candida and other genetic code changes is emphasised.     

Community genetics in the time of next-generation molecular technologies

Understanding the interactions of co-occurring species within and across trophic levels provides key information needed for understanding the ecological and evolutionary processes that underlie biological diversity. As genetics has only recently been integrated into the study of community-level interactions, the time is right for a critical evaluation of potential new, gene-based approaches to studying communities. Next-generation molecular techniques, used in parallel with field-based observations and manipulative experiments across spatio-temporal gradients, are key to expanding our understanding of community-level processes. Here, we introduce a variety of ‘-omics’ tools, with recent studies of plant–insect herbivores and of ectomycorrhizal systems providing detailed examples of how next-generation approaches can revolutionize our understanding of interspecific interactions. We suggest ways that novel technologies may convert community genetics from a field that relies on correlative inference to one that reveals causal mechanisms of genetic co-variation and adaptations within communities.     

A domain model for eukaryotic DNA organization: a molecular basis for cell differentiation and chromosome evolution

A model for eukaryotic chromatin organization is presented in which the basic structural and functional unit is the DNA domain. This simple model predicts that both chromosome replication and cell type-specific control of gene expression depend on a combination of stable and dynamic DNA-nuclear matrix interactions. The model suggests that in eukaryotes, DNA regulatory processes are controlled mainly by the intranuclear compartmentalization of the specific DNA sequences, and that control of gene expression involves multiple steps of specific DNA-nuclear matrix interactions. Predictions of the model are tested using available biochemical, molecular and cell biological data. In addition, the domain model is discussed as a simple molecular mechanism to explain cell differentiation in multi-cellular organisms and to explain the evolution of eukaryotic genomes consisting mainly of repetitive sequences and "junk" DNA.     

Degeneracy and genetic assimilation in RNA evolution

Background

The neutral theory of Motoo Kimura stipulates that evolution is mostly driven by neutral mutations. However adaptive pressure eventually leads to changes in phenotype that involve non-neutral mutations. The relation between neutrality and adaptation has been studied in the context of RNA before and here we further study transitional mutations in the context of degenerate (plastic) RNA sequences and genetic assimilation. We propose quasineutral mutations, i.e. mutations which preserve an element of the phenotype set, as minimal mutations and study their properties. We also propose a general probabilistic interpretation of genetic assimilation and specialize it to the Boltzmann ensemble of RNA sequences.

Results

We show that degenerate sequences i.e. sequences with more than one structure at the MFE level have the highest evolvability among all sequences and are central to evolutionary innovation. Degenerate sequences also tend to cluster together in the sequence space. The selective pressure in an evolutionary simulation causes the population to move towards regions with more degenerate sequences, i.e. regions at the intersection of different neutral networks, and this causes the number of such sequences to increase well beyond the average percentage of degenerate sequences in the sequence space. We also observe that evolution by quasineutral mutations tends to conserve the number of base pairs in structures and thereby maintains structural integrity even in the presence of pressure to the contrary.

Conclusions

We conclude that degenerate RNA sequences play a major role in evolutionary adaptation.

     

Biochemical and genetic properties of oligomeric structures: a general approach

The oligomers constituted by association of different subunits can exist under multiple forms. In the case of the genetically variable proteins, such a multiplicity leads to numerous questions (i) on the enumerations: what is the number of active forms when a given subunit can make the oligomer inactive, or when the subunits are encoded by s alleles; (ii) on the subunit effects on biochemical properties: how to estimate these effects, are they equal, are there interactions between subunits, etc. Theoretical methods for the study of such oligomeric structures are developed, which mainly rely on linear model techniques. Peculiar properties examined are Vmax and Km, but also the quantities of the various oligomers, which depend on their association law. This approach is extended to the oligomers composed of different sets of subunits, as are for example some enzymes. These aspects are discussed from numerous bibliographic examples, with special reference to molecular interactions (protein complementation or molecular heterosis). Otherwise the genetic application of this theoretical approach is presented: it is possible to consider a genotype as an oligomer of alleles, and thus to study their effects and their interactions, in the one-locus case as well as in the several-loci case. The relevance of this generalization is discussed in connection with two other concepts, the "sequence space" used in molecular evolution and the regression of the genotypic values on the number of alleles used in quantitative genetics.     

Systems genetics in “-omics” era: current and future development

The systems genetics is an emerging discipline that integrates high-throughput expression profiling technology and systems biology approaches for revealing the molecular mechanism of complex traits, and will improve our understanding of gene functions in the biochemical pathway and genetic interactions between biological molecules. With the rapid advances of microarray analysis technologies, bioinformatics is extensively used in the studies of gene functions, SNP–SNP genetic interactions, LD block–block interactions, miRNA–mRNA interactions, DNA–protein interactions, protein–protein interactions, and functional mapping for LD blocks. Based on bioinformatics panel, which can integrate “-omics” datasets to extract systems knowledge and useful information for explaining the molecular mechanism of complex traits, systems genetics is all about to enhance our understanding of biological processes. Systems biology has provided systems level recognition of various biological phenomena, and constructed the scientific background for the development of systems genetics. In addition, the next-generation sequencing technology and post-genome wide association studies empower the discovery of new gene and rare variants. The integration of different strategies will help to propose novel hypothesis and perfect the theoretical framework of systems genetics, which will make contribution to the future development of systems genetics, and open up a whole new area of genetics.     

The neutral theory of molecular evolution: a review of recent evidence

In sharp contrast to the Darwinian theory of evolution by natural selection, the neutral theory claims that the overwhelming majority of evolutionary changes at the molecular level are caused by random fixation (due to random sampling drift in finite populations) of selectively neutral (i.e., selectively equivalent) mutants under continued inputs of mutations. The theory also asserts that most of the genetic variability within species at the molecular level (such as protein and DNA polymorphism) are selectively neutral or very nearly neutral and that they are maintained in the species by the balance between mutational input and random extinction. The neutral theory is based on simple assumptions, enabling us to develop mathematical theories based on population genetics to treat molecular evolution and variation in quantitative terms. The theory can be tested against actual observations. Neo-Darwinians continue to criticize the neutral theory, but evidence for it has accumulated over the last two decades. The recent outpouring of DNA sequence data has greatly strengthened the theory. In this paper, I review some recent observations that strongly support the neutral theory. They include such topics as pseudoglobin genes of the mouse, alpha A-crystallin genes of the blind mole rat, genes of influenza A virus and nuclear vs. mitochondrial genes of fruit flies. I also discuss such topics as the evolution of deviant coding systems in Mycoplasma, the origin of life and the unified understanding of molecular and phenotypic evolution. I conclude that since the origin of life on Earth, neutral evolutionary changes have predominated over Darwinian evolutionary changes, at least in number.     

Compensatory vs. pseudocompensatory evolution in molecular and developmental interactions

The evolution of molecules, developmental circuits, and new species are all characterized by the accumulation of incompatibilities between ancestors and descendants. When specific interactions between components are necessary at any of these levels, this requires compensatory coevolution. Theoretical treatments of compensatory evolution that only consider the endpoints predict that it should be rare because intermediate states are deleterious. However, empirical data suggest that compensatory evolution is common at all levels of molecular interaction. A general solution to this paradox is provided by plausible neutral or nearly neutral intermediates that possess informational redundancy. These intermediates provide an evolutionary path between coadapted allelic combinations. Although they allow incompatible end points to evolve, at no point was a deleterious mutation ever in need of compensation. As a result, what appears to be compensatory evolution may often actually be “pseudocompensatory.” Both theoretical and empirical studies indicate that pseudocompensation can speed the evolution of intergenic incompatibility, especially when driven by adaptation. However, under strong stabilizing selection the rate of pseudocompensatory evolution is still significant. Important examples of this process at work discussed here include the evolution of rRNA secondary structures, intra- and inter-protein interactions, and developmental genetic pathways. Future empirical work in this area should focus on comparing the details of intra- and intergenic interactions in closely related organisms.     

How genomic and developmental dynamics affect evolutionary processes

Evolutionary genetics is concerned with natural selection and neutral drift, to the virtual exclusion of almost everything else. In its current focus on DNA variation, it reduces phenotypes to symbols. Varying phenotypes, however, are the units of evolution, and, if we want a comprehensive theory of evolution, we need to consider both the internal and external evolutionary forces that shape the development of phenotypes. Genetic systems are redundant, modular and subject to a variety of genomic mechanisms of "turnover" (transposition, gene conversion, unequal crossingover, slippage and so on). As such the construction and spread of novel combinations of modules by turnover, in particular within gene promoters, contributes significantly to the evolution of phenotypes. Furthermore, redundancy, turnover and modularity lead to ever more complex networks of genetic interactions and ever more functions for a given module. The significant interaction between genomic turnover and natural selection leads to a molecular coevolution between interacting modules and hence facilitates the establishment of biological novelties.     

Mathematical and computational approaches can complement experimental studies of host–pathogen interactions

In addition to traditional and novel experimental approaches to study host–pathogen interactions, mathematical and computer modelling have recently been applied to address open questions in this area. These modelling tools not only offer an additional avenue for exploring disease dynamics at multiple biological scales, but also complement and extend knowledge gained via experimental tools. In this review, we outline four examples where modelling has complemented current experimental techniques in a way that can or has already pushed our knowledge of host–pathogen dynamics forward. Two of the modelling approaches presented go hand in hand with articles in this issue exploring fluorescence resonance energy transfer and two-photon intravital microscopy. Two others explore virtual or ' in silico ' deletion and depletion as well as a new method to understand and guide studies in genetic epidemiology. In each of these examples, the complementary nature of modelling and experiment is discussed. We further note that multi-scale modelling may allow us to integrate information across length (molecular, cellular, tissue, organism, population) and time (e.g. seconds to lifetimes). In sum, when combined, these compatible approaches offer new opportunities for understanding host–pathogen interactions.     

Degeneracy: A design principle for achieving robustness and evolvability

Robustness, the insensitivity of some of a biological system's functionalities to a set of distinct conditions, is intimately linked to fitness. Recent studies suggest that it may also play a vital role in enabling the evolution of species. Increasing robustness, so is proposed, can lead to the emergence of evolvability if evolution proceeds over a neutral network that extends far throughout the fitness landscape. Here, we show that the design principles used to achieve robustness dramatically influence whether robustness leads to evolvability. In simulation experiments, we find that purely redundant systems have remarkably low evolvability while degenerate, i.e. partially redundant, systems tend to be orders of magnitude more evolvable. Surprisingly, the magnitude of observed variation in evolvability can neither be explained by differences in the size nor the topology of the neutral networks. This suggests that degeneracy, a ubiquitous characteristic in biological systems, may be an important enabler of natural evolution. More generally, our study provides valuable new clues about the origin of innovations in complex adaptive systems.     

植物分子群体遗传学研究动态

分子群体遗传学是当代进化生物学研究的支柱学科, 也是遗传育种和关于遗传关联作图和连锁分析的基础理论学科。分子群体遗传学是在经典群体遗传的基础上发展起来的, 它利用大分子主要是DNA序列的变异式样来研究群体的遗传结构及引起群体遗传变化的因素与群体遗传结构的关系, 从而使得遗传学家能够从数量上精确地推知群体的进化演变, 不仅克服了经典的群体遗传学通常只能研究群体遗传结构短期变化的局限性, 而且可检验以往关于长期进化或遗传系统稳定性推论的可靠程度。同时, 对群体中分子序列变异式样的研究也使人们开始重新审视达尔文的以“自然选择”为核心的进化学说。到目前为止, 分子群体遗传学已经取得长足的发展, 阐明了许多重要的科学问题, 如一些重要农作物的DNA多态性式样、连锁不平衡水平及其影响因素、种群的变迁历史、基因进化的遗传学动力等, 更为重要的是, 在分子群体遗传学基础上建立起来的新兴的学科如分子系统地理学等也得到了迅速的发展。文中综述了植物分子群体遗传研究的内容及最新成果。     

Biopolymers and evolution

Biopolymers are usually studied being extracted from the whole system of a cell or of an organism. Some important features are lost during such a procedure. It is necessary to take into account the behavior of proteins and nucleic acids in metabolic networks and to investigate their evolution. The substitutions of amino-acids metabolic networks residues are biologically possible in the polypeptides and proteins if they do not influence their spatial structure and function. The correlations of the primary structure with these properties are degenerate. The protein can be treated as "an edited statistical copolymer" (Ptitsyn). In the process of "edition" an important role is played by the ions of transient metals. Nucleic acids possess similar properties. It can be shown that the deleterious mutations of proteins can be compensated by the changes of their amount, spatial and temporal characteristics of the synthesis. Not only the structure of the protein is important but also the exact answers of the questions: how much, when and where? The contemporary theory of evolution unites phylogeny and onthogeny. The directionality of evolution is determined both by natural selection and by the already existing structure of an organism. Hence many characters are not adaptive. This is valid also for the molecular level of the structure. Thus three independent groups of facts and suggestions are presented, which confirm the neutral theory of evolution (Kimura) and elucidate its physical meaning. The molecular evolution does not coincide with the biological evolution.     

Rapid evolution of yeast centromeres in the absence of drive

To find the most rapidly evolving regions in the yeast genome we compared most of chromosome III from three closely related lineages of the wild yeast Saccharomyces paradoxus. Unexpectedly, the centromere appears to be the fastest-evolving part of the chromosome, evolving even faster than DNA sequences unlikely to be under selective constraint (i.e., synonymous sites after correcting for codon usage bias and remnant transposable elements). Centromeres on other chromosomes also show an elevated rate of nucleotide substitution. Rapid centromere evolution has also been reported for some plants and animals and has been attributed to selection for inclusion in the egg or the ovule at female meiosis. But Saccharomyces yeasts have symmetrical meioses with all four products surviving, thus providing no opportunity for meiotic drive. In addition, yeast centromeres show the high levels of polymorphism expected under a neutral model of molecular evolution. We suggest that yeast centromeres suffer an elevated rate of mutation relative to other chromosomal regions and they change through a process of "centromere drift," not drive.     

Novel integrative genomics strategies to identify genes for complex traits

Forward genetics is a common approach to dissecting complex traits like common human diseases. The ultimate aim of this approach was the identification of genes that are causal for disease or other phenotypes of interest. However, the forward genetics approach is by definition restricted to the identification of genes that have incurred mutations over the course of evolution or that incurred mutations as a result of chemical mutagenesis, and that as a result lead to disease or to variations in other phenotypes of interest. Genes that harbour no such mutations, but that play key roles in parts of the biological network that lead to disease, are systematically missed by this class of approaches. Recently, a class of novel integrative genomics approaches has been devised to elucidate the complexity of common human diseases by intersecting genotypic, molecular profiling, and clinical data in segregating populations. These novel approaches take a more holistic view of biological systems and leverage the vast network of gene–gene interactions, in combination with DNA variation data, to establish causal relationships among molecular profiling traits and Fbetween molecular profiling and disease (or other classic phenotypes). A number of novel genes for disease phenotypes have been identified as a result of these approaches, highlighting the utility of integrating orthogonal sources of data to get at the underlying causes of disease.     

The effect of demographic population factors and individual biological parameters on the rate of the neutral molecular evolution

The dependence of the rate of neutral molecular evolution on both biological parameters and demographic population factors has been investigated. Real genetic data and an individual-based model of the population dynamics were used for the study. The first part of the study deals with tracing the neutral molecular evolution occurring in the model concurrently with adaptive speciation. The second part concerns the effect of individual biological parameters and demographic population factors of members of the Order Testudines (Turtles) on the relative rate of evolution of the mitochondrial CytB gene. It has been shown that demographic population factors and individual biological parameters affect the rate of the neutral molecular evolution.