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PubMed1998

Coevolution of immunoglobulin heavy- and light-chain variable-region gene families.

The gene families encoding the immunoglobulin variable regions of heavy (VH) and light (VL) chains in vertebrates are composed of many genes. However, the gene number and the extent of diversity among VH and VL gene copies vary with species. To examine the causes of this variation and the evolutionary forces for these multigene families, we conducted a phylogenetic analysis of VH and VL genes from the species of amniotes. The results of our analysis showed that for each species, VH and VL genes have the same pattern of clustering in the trees, and, according to this clustering pattern, the species can be divided into two groups. In the first group of species (humans and mice), VH and VL genes were extensively intermingled with genes from other organisms; in the second group of species (chickens, rabbits, cattle, sheep, swine, and horses), the genes tended to form clusters within the same group of organisms. These results suggest that the VH and VL multigene families have evolved in the same fashion: they have undergone coordinated contraction and expansion of gene repertoires such that each group of organisms is characterized by a certain level of diversity of VH and VL genes. The extent of diversity among copies of VH and VL genes in each species is related to the mechanism of generation of antibody variety. In humans and mice, DNA rearrangement of immunoglobulin variable, diversity, and joining-segment genes is a main source of antibody diversity, whereas in chickens, rabbits, cattle, sheep, swine, and horses, somatic hypermutation and somatic gene conversion play important roles. The evolutionary pattern of VH and VL multigene families is consistent with the birth-and-death model of evolution, yet different levels of diversifying selection seem to operate in the VH and VL genes of these two groups of species.

Animals↗

PubMed2003

Are you my mother? Bayesian phylogenetic inference of recombination among putative parental strains.

Reconstructing evolutionary relationships using Bayesian inference has become increasingly popular due to the ability of Bayesian inference to handle complex models of evolution. In this review we concentrate on inference of recombination events between strains of viruses when these events are sporadic, ie rare relative to point mutations. Bayesian inference is especially attractive in the detection of recombination events because it allows for simultaneous inferences about the presence, number and location of crossover points and the identification of parental sequences. Current frequentist recombination identification falls into a sequential testing trap. The most likely parental sequences and crossover points are identified using the data and then the certainty of recombination is assessed conditional on this identification. After briefly outlining basic phylogenetic models, Bayesian inference and Markov chain Monte Carlo (MCMC) computation, we summarise three different approaches to recombination detection and discuss current challenges in applying Bayesian phylogenetic inference of recombination.

Algorithms↗

PubMed2006

Mutation accumulation in space and the maintenance of sexual reproduction.

The maintenance of sexual reproduction remains one of the major puzzles of evolutionary biology, since, all else being equal, an asexual mutant should have a twofold fitness advantage over the sexual wildtype. Most theories suggest that sex helps either to purge deleterious mutations, or to adapt to changing environments. Both mechanisms have their limitations if they act in isolation because they require either high genomic mutation rates or very virulent pathogens, and it is therefore often thought that they must act together to maintain sex. Typically, however, these theories have in common that they are not based on spatial processes. Here, we show that local dispersal and local competition can explain the maintenance of sexual reproduction as a means of purging deleterious mutations. Using a spatially explicit individual-based model, we find that even with reasonably low genomic mutation rates and large total population sizes, asexual clones cannot invade a sexual population. Our results demonstrate how spatial processes affect mutation accumulation such that it can fully erode the twofold benefit of asexuality faster than an asexual clone can take over a sexual population. Thus, the cost of sex is generally overestimated in models that ignore the effects of space on mutation accumulation.

Adaptation, Physiological↗

PubMed1992

Gene order comparisons for phylogenetic inference: evolution of the mitochondrial genome.

Detailed knowledge of gene maps or even complete nucleotide sequences for small genomes leads to the feasibility of evolutionary inference based on the macrostructure of entire genomes, rather than on the traditional comparison of homologous versions of a single gene in different organisms. The mathematical modeling of evolution at the genomic level, however, and the associated inferential apparatus are qualitatively different from the usual sequence comparison theory developed to study evolution at the level of individual gene sequences. We describe the construction of a database of 16 mitochondrial gene orders from fungi and other eukaryotes by using complete or nearly complete genomic sequences; propose a measure of gene order rearrangement based on the minimal set of chromosomal inversions, transpositions, insertions, and deletions necessary to convert the order in one genome to that of the other; report on algorithm design and the development of the DERANGE software for the calculation of this measure; and present the results of analyzing the mitochondrial data with the aid of this tool.

Biological Evolution↗

PubMed1989

The artificial worlds approach to emergent evolution.

Artificial worlds models of evolutionary systems are computer models that map the essential logical structure of ecological systems, defined as self-sustaining biological organizations. The artificial world comprises an artificial environment, with mass components, energy input, and physical states. It also comprises artificial organisms, including a genome, a phenome, and a (developmental) map that connects the genome to the phenome. Mass components are cycled and space is limited. The evolution process results, as in nature, from genetic variation combined with natural selection imposed by the finiteness of the environment. The selection criteria (fitness values) are not imposed, but rather emerge from the interactions of the organisms with each other and with the environment. The dynamics at the population level also emerges from these basic interactions. In this paper we describe the comparative properties of the EVOLVE family of artificial worlds models.

Artificial Intelligence↗

PubMed2004

Pleiotropic effect of disrupting a conserved sequence involved in a long-range compensatory interaction in the Drosophila Adh gene.

Recent advances in experimental analyses of the evolution of RNA secondary structures suggest a more complex scenario than that typically considered by Kimura's classical model of compensatory evolution. In this study, we examine one such case in more detail. Previous experimental analysis of long-range compensatory interactions between the two ends of Drosophila Adh mRNA failed to fit the classical model of compensatory evolution. To further investigate and verify long-range pairing in Drosophila Adh with respect to models of compensatory evolution and its potential functional role, we introduced site-directed mutations in the Drosophila melanogaster Adh gene. We explore two alternative hypotheses for why previous analysis of long-range compensatory interactions failed to fit the classical model. Specifically, we investigate whether the disruption of a conserved short-range pairing within Adh exon 2 has an effect on Adh expression or if there is a dual functional role of a conserved sequence in the 3'-UTR in both long-range pairing and the negative regulation of Adh expression. We find that a classical result was not observed due to the pleiotropic effect of changing a nucleotide involved in both long-range base pairing and the negative regulation of gene expression.

3' Untranslated Regions↗

PubMed1993

Stochastic dynamical aspects of neuronal activity.

A stochastic model of neuronal activity is proposed. Some stochastic differential equations based on jump processes are used to investigate the behavior of the membrane potential at a time scale small with respect to the neuronal states time evolution. A model for learning, implying short memory effects, is described.

Animals↗

PubMed1985

Soluble minerals in chemical evolution. I. Adsorption of 5'-AMP on CaSO4--a model system.

The adsorption of 5'-AMP onto solid CaSO4 2H2O was studied in a saturated suspension as a function of pH and electrolyte concentration. The adsorption is pH-dependent and is directly correlated with the charge on the 5'-AMP molecule which is determined by the state of protonation of the N-1 nitrogen of the purine ring and the phosphate oxygens. It is proposed that the binding occurs between the nucleotide and the salt is electrostatic in nature. The adsorption decreases with increasing ionic strength of the solution which means that in a fluctuating environment of wetting and drying cycles, a biomolecule similar to 5'-AMP could be expected to desorb during the drying phase. The results indicate that CaSO4 2H2O can serve as a concentrating surface for biomolecules. The significance of this is discussed with regard to the possible role of soluble minerals and their surfaces in a geochemical model consistent with the evolution of the Earth and the origin of life.

Adenosine Monophosphate↗

PubMed2003

Least and most powerful phylogenetic tests to elucidate the origin of the seed plants in the presence of conflicting signals under misspecified models.

Several tests of molecular phylogenies have been proposed over the last decades, but most of them lead to strikingly different P-values. I propose that such discrepancies are principally due to different forms of null hypotheses. To support this hypothesis, two new tests are described. Both consider the composite null hypothesis that all the topologies are equidistant from the true but unknown topology. This composite hypothesis can either be reduced to the simple hypothesis at the least favorable distribution (frequentist significance test [FST]) or to the maximum likelihood topology (frequentist hypothesis test [FHT]). In both cases, the reduced null hypothesis is tested against each topology included in the analysis. The tests proposed have an information-theoretic justification, and the distribution of their test statistic is estimated by a nonparametric bootstrap, adjusting P-values for multiple comparisons. I applied the new tests to the reanalysis of two chloroplast genes, psaA and psbB, and compared the results with those of previously described tests. As expected, the FST and the FHT behaved approximately like the Shimodaira-Hasegawa test and the bootstrap, respectively. Although the tests give overconfidence in a wrong tree when an overly simple nucleotide substitution model is assumed, more complex models incorporating heterogeneity among codon positions resolve some conflicts. To further investigate the influence of the null hypothesis, a power study was conducted. Simulations showed that FST and the Shimodaira-Hasegawa test are the least powerful and FHT is the most powerful across the parameter space. Although the size of all the tests is affected by misspecification, the two new tests appear more robust against misspecification of the model of evolution and consistently supported the hypothesis that the Gnetales are nested within gymnosperms.

Bayes Theorem↗

PubMed2005

Genetic correlations between basal and maximum metabolic rates in a wild rodent: consequences for evolution of endothermy.

According to the aerobic capacity model, endothermy in birds and mammals evolved as a correlated response to selection for an ability of sustained locomotor activity, rather than in a response to direct selection for thermoregulatory capabilities. A key assumption of the model is that aerobic capacity is functionally linked to basal metabolic rate (BMR). The assumption has been tested in several studies at the level of phenotypic variation among individuals or species, but none has provided a clear answer whether the traits are genetically correlated. Here we present results of a genetic analysis based on measurements of the basal and the maximum swim- and cold-induced oxygen consumption in about 1000 bank voles from six generations of a laboratory colony, reared from animals captured in the field. Narrow sense heritability (h2) was about 0.5 for body mass, about 0.4 for mass-independent basal and maximum metabolic rates, and about 0.3 for factorial aerobic scopes. Dominance genetic and common environmental (= maternal) effects were not significant. Additive genetic correlation between BMR and the swim-induced aerobic capacity was high and positive, whereas correlation resulting from specific-environmental effects was negative. However, BMR was not genetically correlated with the cold-induced aerobic capacity. The results are consistent with the aerobic capacity model of the evolution of endothermy in birds and mammals.

Analysis of Variance↗

PubMed2006

A nonlinear model with latent process for cognitive evolution using multivariate longitudinal data.

Cognition is not directly measurable. It is assessed using psychometric tests, which can be viewed as quantitative measures of cognition with error. The aim of this article is to propose a model to describe the evolution in continuous time of unobserved cognition in the elderly and assess the impact of covariates directly on it. The latent cognitive process is defined using a linear mixed model including a Brownian motion and time-dependent covariates. The observed psychometric tests are considered as the results of parameterized nonlinear transformations of the latent cognitive process at discrete occasions. Estimation of the parameters contained both in the transformations and in the linear mixed model is achieved by maximizing the observed likelihood and graphical methods are performed to assess the goodness of fit of the model. The method is applied to data from PAQUID, a French prospective cohort study of ageing.

Aged↗

PubMed2004

Stability and the evolvability of function in a model protein.

Functional proteins must fold with some minimal stability to a structure that can perform a biochemical task. Here we use a simple model to investigate the relationship between the stability requirement and the capacity of a protein to evolve the function of binding to a ligand. Although our model contains no built-in tradeoff between stability and function, proteins evolved function more efficiently when the stability requirement was relaxed. Proteins with both high stability and high function evolved more efficiently when the stability requirement was gradually increased than when there was constant selection for high stability. These results show that in our model, the evolution of function is enhanced by allowing proteins to explore sequences corresponding to marginally stable structures, and that it is easier to improve stability while maintaining high function than to improve function while maintaining high stability. Our model also demonstrates that even in the absence of a fundamental biophysical tradeoff between stability and function, the speed with which function can evolve is limited by the stability requirement imposed on the protein.

Biophysics↗

PubMed1999

Tile automation: a model for an architecture of a living system.

To understand an architecture of a living system, "Tile Automaton" is introduced as an abstract model of chemical reaction of molecules scattered over a space. The model consists of tiles of various shapes that stand for molecules. The chemical reaction, induced by the collisions of tiles, is represented by the change of the tile shapes. The rules for reaction are deterministic, and the evolution of the system strongly depends on mutual spatial relationship among tiles. The evolution often leads to self-organization of a "factory," a set of tiles that produces tiles continuously and keeps its structure. Several interesting phenomena, such as a deformation or a division of a factory, are also observed. It is proposed that the formation of the factory is due to the interference between different aspects of tiles - the shape and the motion. The concept of "entanglement" is introduced as a mechanism of living systems.

Biochemical Phenomena↗

PubMed2003

A hierarchical model of plumage: morphology, development, and evolution.

Plumage is a complex component of the avian phenotype. The plumage of an individual is composed of numerous hierarchically arranged developmental and morphological modules. We present a hierarchical model of plumage that provides an intellectual framework for understanding the development and evolution of feathers. Independence, covariation, and interaction among plumage modules create numerous opportunities for developmental and evolutionary diversification of feather complexity and function. The hierarchical relationships among plumage modules are characterized by both top-down and bottom-up effects in which properties of modules at one level of the hierarchy determine or influence the properties of modules at lower or higher levels of the hierarchy. Plumage metamodules are created by covariation or interaction among modules at different levels of the hierarchy.

Animals↗

PubMed2002

Spontaneous pattern formation and genetic invasion in locally mating and competing populations.

We present a theoretical model of evolution of spatially distributed populations in which organisms mate with and compete against each other only locally. We show using both analysis and numerical simulation that the typical dynamics of population density variation is a spontaneous formation of isolated groups due to competition for resources. The resulting spatial separation between groups strongly affects the process of genetic invasion by local reproductive mixing, and spatially inhomogeneous genetic distributions are possible in the final states. We then consider a specific version of this model in the presence of disruptive selection, favoring two fittest types against their genetic intermediates. This case can be simplified to a system that involves just two nonconserved order parameters: population density and type difference. Since the coexistence of two fittest types is unstable in this case, symmetry breaking and coarsening occur in type difference, implying eventual dominance by one type over another for finite populations. However, such coarsening patterns may be pinned by the spontaneously generated spatial separation between isolated groups. The long-term evolution of genetic composition is found to be sensitive to the ratio of the mating and competition ranges, and other parameters. Our model may provide a theoretical basis for consideration of various properties of spatially extended evolutionary processes, including spontaneous formation of subpopulations and lateral invasion of different types.

Journal Article↗

PubMed2004

Uses and abuses of mathematics in biology.

In the physical sciences, mathematical theory and experimental investigation have always marched together. Mathematics has been less intrusive in the life sciences, possibly because they have until recently been largely descriptive, lacking the invariance principles and fundamental natural constants of physics. Increasingly in recent decades, however, mathematics has become pervasive in biology, taking many different forms: statistics in experimental design; pattern seeking in bioinformatics; models in evolution, ecology, and epidemiology; and much else. I offer an opinionated overview of such uses--and abuses.

Allergy and Immunology↗

PubMed1995

Conditions for soft selection favoring the evolution of hybrid inviability.

Hybrid inviability per se is not generally considered adaptive; it is believed to evolve as a pleiotropic consequence of other genetic changes, either adaptive or neutral, between diverging populations. However, given the pre-existence of hybrid sterility, there are circumstances under which hybrid inviability may be directly selected. In this report, we model the evolution of hybrid inviability in the context of within-family density-dependent selection (soft selection). This paper shows that under certain conditions, an allele causing hybrid inviability can increase when rare, despite also decreasing viability in conspecifics. These conditions depend upon the strength of density effects within families and upon the frequency of matings with heterospecifics. It is found that, under the most favorable conditions (strong soft selection and frequent hybridization), the inviability allele can invade when its deleterious effect on the hybrid viability exceeds four times its deleterious effects on conspecific heterozygotes. The conditions for fixation of the allele are also investigated and the circumstances under which this process might operate in natural populations are discussed. The conclusion is that the most restrictive condition is that for this process to evolve, there must be little opportunity for postzygotic reproductive isolation to evolve.

Alleles↗

PubMed2004

Multidimensional vector space representation for convergent evolution and molecular phylogeny.

With growing amounts of genome data and constant improvement of models of molecular evolution, phylogenetic reconstruction became more reliable. However, our knowledge of the real process of molecular evolution is still limited. When enough large-sized data sets are analyzed, any subtle biases in statistical models can support incorrect topologies significantly because of the high signal-to-noise ratio. We propose a procedure to locate sequences in a multidimensional vector space (MVS), in which the geometry of the space is uniquely determined in such a way that the vectors of sequence evolution are orthogonal among different branches. In this paper, the MVS approach is developed to detect and remove biases in models of molecular evolution caused by unrecognized convergent evolution among lineages or unexpected patterns of substitutions. Biases in the estimated pairwise distances are identified as deviations (outliers) of sequence spatial vectors from the expected orthogonality. Modifications to the estimated distances are made by minimizing an index to quantify the deviations. In this way, it becomes possible to reconstruct the phylogenetic tree, taking account of possible biases in the model of molecular evolution. The efficacy of the modification procedure was verified by simulating evolution on various topologies with rate heterogeneity and convergent change. The phylogeny of placental mammals in previous analyses of large data sets has varied according to the genes being analyzed. Systematic deviations caused by convergent evolution were detected by our procedure in all representative data sets and were found to strongly affect the tree structure. However, the bias correction yielded a consistent topology among data sets. The existence of strong biases was validated by examining the sites of convergent evolution between the hedgehog and other species in mitochondrial data set. This convergent evolution explains why it has been difficult to determine the phylogenetic placement of the hedgehog in previous studies.

Animals↗