Evolution of model proteins on a foldability landscape

We model the evolution of simple lattice proteins as a random walk in a fitness landscape, where the fitness represents the ability of the protein to fold. At higher selective pressure, the evolutionary trajectories are confined to neutral networks where the native structure is conserved and the dynamics are non self-averaging and nonexponential. The optimizability of the corresponding native structure has a strong effect on the size of these neutral networks and thus on the nature of the evolutionary process. Proteins 29:461–466, 1997. © 1997 Wiley-Liss, Inc.     

Sketch for a Theory of Evolution Based on Coding

At the heart of evolutionary theory lays the notion of replication. Unfortunately, this notion is far less exact than the weight of its importance. In this paper, it is argued that replication always involves coding. Furthermore, when a theory of evolution is built on replication based on coding, a unifying and coherent picture arises that sheds new light on some of the controversies and open questions in contemporary biology, such as what are the roles of phylogeny and ontogeny in evolution, and how to characterize and explain the increase of biological complexity.     

Accelerated Adaptive Evolution on a Newly Formed X Chromosome

Sex chromosomes originated from ordinary autosomes, and their evolution is characterized by continuous gene loss from the ancestral Y chromosome. Here, we document a new feature of sex chromosome evolution: bursts of adaptive fixations on a newly formed X chromosome. Taking advantage of the recently formed neo-X chromosome of Drosophila miranda, we compare patterns of DNA sequence variation at genes located on the neo-X to genes on the ancestral X chromosome. This contrast allows us to draw inferences of selection on a newly formed X chromosome relative to background levels of adaptation in the genome while controlling for demographic effects. Chromosome-wide synonymous diversity on the neo-X is reduced 2-fold relative to the ancestral X, as expected under recent and recurrent directional selection. Several statistical tests employing various features of the data consistently identify 10%–15% of neo-X genes as targets of recent adaptive evolution but only 1%–3% of genes on the ancestral X. In addition, both the rate of adaptation and the fitness effects of adaptive substitutions are estimated to be roughly an order of magnitude higher for neo-X genes relative to genes on the ancestral X. Thus, newly formed X chromosomes are not passive players in the evolutionary process of sex chromosome differentiation, but respond adaptively to both their sex-biased transmission and to Y chromosome degeneration, possibly through demasculinization of their gene content and the evolution of dosage compensation.     

Evolution in a Changing Environment

We propose a simple model for genetic adaptation to a changing environment, describing a fitness landscape characterized by two maxima. One is associated with “specialist” individuals that are adapted to the environment; this maximum moves over time as the environment changes. The other maximum is static, and represents “generalist” individuals not affected by environmental changes. The rest of the landscape is occupied by “maladapted” individuals. Our analysis considers the evolution of these three subpopulations. Our main result is that, in presence of a sufficiently stable environmental feature, as in the case of an unchanging aspect of a physical habitat, specialists can dominate the population. By contrast, rapidly changing environmental features, such as language or cultural habits, are a moving target for the genes; here, generalists dominate, because the best evolutionary strategy is to adopt neutral alleles not specialized for any specific environment. The model we propose is based on simple assumptions about evolutionary dynamics and describes all possible scenarios in a non-trivial phase diagram. The approach provides a general framework to address such fundamental issues as the Baldwin effect, the biological basis for language, or the ecological consequences of a rapid climate change.     

Evolution of a species' range

Gene flow from the center of a species' range can stymie adaptation at the periphery and prevent the range from expanding outward. We study this process using simple models that track both demography and the evolution of a quantitative trait in a population that is continuously distributed in space. Stabilizing selection acts on the trait and favors an optimum phenotype that changes linearly across the habitat. One of three outcomes is possible: the species will become extinct, expand to fill all of the available habitat, or be confined to a limited range in which it is sufficiently adapted to allow population growth. When the environment changes rapidly in space, increased migration inhibits local adaptation and so decreases the species' total population size. Gene flow can cause enough maladaptation that the peripheral half of a species' range acts as a demographic sink. The trait's genetic variance has little effect on species persistence or the size of the range when gene flow is sufficiently strong to keep population densities far below the carrying capacity throughout the range, but it can increase the range width and population size of an abundant species. Under some conditions, a small parameter change can dramatically shift the balance between gene flow and local adaptation, allowing a species with a limited range to suddenly expand to fill all the available habitat.     

Textbooks as a Possible Influence on Unscientific Ideas about Evolution

While school textbooks are assumed to be written for and used by students, it is widely acknowledged that they also serve a vital support function for teachers, particularly in times of curriculum change. A basic assumption is that biology textbooks are scientifically accurate. Furthermore, because of the negative impact of ‘misconceptions’ on learning, it is desirable that textbooks point out common misconceptions and why they are scientifically unacceptable. This paper reports on a study of life sciences textbooks as a potential influence on misconceptions about evolution by natural selection. Textbooks for Grades 10 to 12, from two different publishers, were investigated using content analysis to establish, first, the nature and extent of scientifically incorrect statements about evolution; second, latent problems with wording which might lead to unscientific ideas; and third, whether the books identified and addressed common misconceptions. Unscientific statements were found in all six books, but latent problems associated with the way explanations were expressed were also considered to pose a significant threat to learning. While particularly important for textbook authors and publishers, these findings are also of value to teachers. Although this study was conducted in South Africa, the findings provide useful insights for a wider audience of biology education stakeholders.     

Evolution and stability of the G-matrix on a landscape with a moving optimum

In quantitative genetics, the genetic architecture of traits, described in terms of variances and covariances, plays a major role in determining the trajectory of evolutionary change. Hence, the genetic variance-covariance matrix (G-matrix) is a critical component of modern quantitative genetics theory. Considerable debate has surrounded the issue of G-matrix constancy because unstable G-matrices provide major difficulties for evolutionary inference. Empirical studies and analytical theory have not resolved the debate. Here we present the results of stochastic models of G-matrix evolution in a population responding to an adaptive landscape with an optimum that moves at a constant rate. This study builds on the previous results of stochastic simulations of G-matrix stability under stabilizing selection arising from a stationary optimum. The addition of a moving optimum leads to several important new insights. First, evolution along genetic lines of least resistance increases stability of the orientation of the G-matrix relative to stabilizing selection alone. Evolution across genetic lines of least resistance decreases G-matrix stability. Second, evolution in response to a continuously changing optimum can produce persistent maladaptation for a correlated trait, even if its optimum does not change. Third, the retrospective analysis of selection performs very well when the mean G-matrix (G) is known with certainty, indicating that covariance between G and the directional selection gradient beta is usually small enough in magnitude that it introduces only a small bias in estimates of the net selection gradient. Our results also show, however, that the contemporary G-matrix only serves as a rough guide to G. The most promising approach for the estimation of G is probably through comparative phylogenetic analysis. Overall, our results show that directional selection actually can increase stability of the G-matrix and that retrospective analysis of selection is inherently feasible. One major remaining challenge is to gain a sufficient understanding of the G-matrix to allow the confident estimation of G.     

Bayesian Inference of the Evolution of a Phenotype Distribution on a Phylogenetic Tree

The distribution of a phenotype on a phylogenetic tree is often a quantity of interest. Many phenotypes have imperfect heritability, so that a measurement of the phenotype for an individual can be thought of as a single realization from the phenotype distribution of that individual. If all individuals in a phylogeny had the same phenotype distribution, measured phenotypes would be randomly distributed on the tree leaves. This is, however, often not the case, implying that the phenotype distribution evolves over time. Here we propose a new model based on this principle of evolving phenotype distribution on the branches of a phylogeny, which is different from ancestral state reconstruction where the phenotype itself is assumed to evolve. We develop an efficient Bayesian inference method to estimate the parameters of our model and to test the evidence for changes in the phenotype distribution. We use multiple simulated data sets to show that our algorithm has good sensitivity and specificity properties. Since our method identifies branches on the tree on which the phenotype distribution has changed, it is able to break down a tree into components for which this distribution is unique and constant. We present two applications of our method, one investigating the association between HIV genetic variation and human leukocyte antigen and the other studying host range distribution in a lineage of Salmonella enterica, and we discuss many other potential applications.     

Evolution of a Molluscan Cardioregulatory Neuropeptide

SYNOPSIS. The cardioexcitatory neuropeptide FMRFamide was firstidentified from a clam, but has now been demonstrated in severalother molluscs. It is probably present throughout the molluscanphylum though co-existing with related peptides in some species.For example, I report here the finding of the peptide phenylalanyl-leucyl-arginyl-phenylalanineamide (FLRFamide) in the mesogastropod Pomacea paludosa whereit accounts for 10–20% of the total FMRFamide-like activity.This peptide may be a minor component of the FMRFamide-likeactivity in other species as well. The pulmonate snails haveseveral, closely-related, heptapeptide analogs of FLRFamidethat are unique to them, such as pyroglutamyl-aspartyl-prolyl-phenylalanyl-leucyl-arginyl-phenylalanineamide (pQDPFLRFamide) which was isolated from Helix aspersa.Two additional pulmonate heptapeptides that have been isolatedprobably differ from pQDPFLRFamide only in their N-terminalamino acid residues. The heptapeptides account for most of theFMRFamidelike activity in the species in which they occur. Though the tetrapeptides FMRFamide and FLRFamide have virtuallyidentical activities on various molluscan tissues, the heptapeptideshave activity that is distinct from the tetrapeptides on somepulmonate muscles. 1 have attempted to explain the evolutionof this diversity of peptide structure and function found inthe modern pulmonates by postulating a gene duplication in thegastropod line leading to them.     

Exceptional Convergent Evolution in a Virus

Replicate lineages of the bacteriophage X 174 adapted to growth at high temperature on either of two hosts exhibited high rates of identical, independent substitutions. Typically, a dozen or more substitutions accumulated in the 5.4-kilobase genome during propagation. Across the entire data set of nine lineages, 119 independent substitutions occurred at 68 nucleotide sites. Over half of these substitutions, accounting for one third of the sites, were identical with substitutions in other lineages. Some convergent substitutions were specific to the host used for phage propagation, but others occurred across both hosts. Continued adaptation of an evolved phage at high temperature, but on the other host, led to additional changes that included reversions of previous substitutions. Phylogenetic reconstruction using the complete genome sequence not only failed to recover the correct evolutionary history because of these convergent changes, but the true history was rejected as being a significantly inferior fit to the data. Replicate lineages subjected to similar environmental challenges showed similar rates of substitution and similar rates of fitness improvement across corresponding times of adaptation. Substitution rates and fitness improvements were higher during the initial period of adaptation than during a later period, except when the host was changed.     

Evolution of a student model-building program

We describe the design and development of a highly interactive model-building program to assist students from a diverse range of academic backgrounds to understand the baroreceptor reflex. Our approach is to have students work in small groups to construct their own simple model of such a control system. This model then provides the basis for a structural framework for students to add further complexity without losing overall perspective and allows exploration of deeper issues. Our program is suitable for many disciplines and student backgrounds and provides a visual representation of a difficult concept, providing a basis to ground further knowledge. Audit trail data have been analyzed to identify and resolve areas of student difficulty, and extensive surveys and observations on students' use of the program over three years in several courses have been used to test and improve its effectiveness.     

Evolution in a flat fitness landscape

A simple model of a population of asexually reproducing individuals, evolving in a flat fitness landscape, is defined. It is shown that the model is equivalent to a dynamical system with stochastic dynamics, the Annealed Random Map Model. Thus, it is possible to solve exactly for the genealogy statistics and for the genetic variability of the population. Fluctuations of quantities, like the average relatedness and the variability, which also take place in the limit of an infinitely large population, are computed.