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.     

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.     

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.     

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 on distributive lattices

We consider the directed evolution of a population after an intervention that has significantly altered the underlying fitness landscape. We model the space of genotypes as a distributive lattice; the fitness landscape is a real-valued function on that lattice. The risk of escape from intervention, i.e., the probability that the population develops an escape mutant before extinction, is encoded in the risk polynomial. Tools from algebraic combinatorics are applied to compute the risk polynomial in terms of the fitness landscape. In an application to the development of drug resistance in HIV, we study the risk of viral escape from treatment with the protease inhibitors ritonavir and indinavir.     

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 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.     

Evolution of migration in a metapopulation

In this paper a general deterministic discrete-time metapopulation model with a finite number of habitat patches is analysed within the framework of adaptive dynamics. We study a general model and prove analytically that (i) if the resident populations state is a fixed point, then the resident strategy with no migration is an evolutionarily stable strategy, (ii) a mutant population with no migration can invade any resident population in a fixed point state, (iii) in the uniform migration case the strategy not to migrate is attractive under small mutational steps so that selection favours low migration. Some of these results have been previously observed in simulations, but here they are proved analytically in a general case. If the resident population is in a two-cyclic orbit, then the situation is different. In the uniform migration case the invasion behaviour depends both on the type of the residents attractor and the survival probability during migration. If the survival probability during migration is low, then the system evolves towards low migration. If the survival probability is high enough, then evolutionary branching can happen and the system evolves to a situation with several coexisting types. In the case of out-of-phase attractor, evolutionary branching can happen with significantly lower survival probabilities than in the in-phase attractor case. Most results in the two-cyclic case are obtained by numerical simulations. Also, when migration is not uniform we observe in numerical simulations in the two-cyclic orbit case selection for low migration or evolutionary branching depending on the survival probability during migration.     

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.