Evidence That Mutation Is Universally Biased towards AT in Bacteria

Mutation is the engine that drives evolution and adaptation forward in that it generates the variation on which natural selection acts. Mutation is a random process that nevertheless occurs according to certain biases. Elucidating mutational biases and the way they vary across species and within genomes is crucial to understanding evolution and adaptation. Here we demonstrate that clonal pathogens that evolve under severely relaxed selection are uniquely suitable for studying mutational biases in bacteria. We estimate mutational patterns using sequence datasets from five such clonal pathogens belonging to four diverse bacterial clades that span most of the range of genomic nucleotide content. We demonstrate that across different types of sites and in all four clades mutation is consistently biased towards AT. This is true even in clades that have high genomic GC content. In all studied cases the mutational bias towards AT is primarily due to the high rate of C/G to T/A transitions. These results suggest that bacterial mutational biases are far less variable than previously thought. They further demonstrate that variation in nucleotide content cannot stem entirely from variation in mutational biases and that natural selection and/or a natural selection-like process such as biased gene conversion strongly affect nucleotide content

Nuclear brinkmanship: a study in non-linguistic communication

This article examines meaning making with nuclear bombs and military manoeuvres. The data is verbatim audio recordings from the White House during the Cuban Missile Crisis. The analysis uses concepts from impression management and dialogism. It is found that actions often speak louder than words and that even non-linguistic communication with nuclear weapons is often oriented to third-parties, in this case, world opinion. A novel process of 'staging the other' is identified, that is, when one side tries to create a situation which will force the other side to act in a way which will create a negative impression on world opinion. Staging the other is a subtle form of meaning making for it entails shaping how third parties will view a situation without those third parties being aware of the intentionality of the communication

Population Genomics on the Fly: Recent Advances in Drosophila

Drosophila melanogaster, a small dipteran of African origin, represents one of the best-studied model organisms. Early work in this system has uniquely shed light on the basic principles of genetics and resulted in a versatile collection of genetic tools that allow to uncover mechanistic links between genotype and phenotype. Moreover, given its worldwide distribution in diverse habitats and its moderate genome-size, Drosophila has proven very powerful for population genetics inference and was one of the first eukaryotes whose genome was fully sequenced. In this book chapter, we provide a brief historical overview of research in Drosophila and then focus on recent advances during the genomic era. After describing different types and sources of genomic data, we discuss mechanisms of neutral evolution including the demographic history of Drosophila and the effects of recombination and biased gene conversion. Then, we review recent advances in detecting genome-wide signals of selection, such as soft and hard selective sweeps. We further provide a brief introduction to background selection, selection of noncoding DNA and codon usage and focus on the role of structural variants, such as transposable elements and chromosomal inversions, during the adaptive process. Finally, we discuss how genomic data helps to dissect neutral and adaptive evolutionary mechanisms that shape genetic and phenotypic variation in natural populations along environmental gradients. In summary, this book chapter serves as a starting point to Drosophila population genomics and provides an introduction to the system and an overview to data sources, important population genetic concepts and recent advances in the field

Stochasticity versus determinism: consequences for realistic gene regulatory network modelling and evolution

Gene regulation is one important mechanism in producing observed phenotypes and heterogeneity. Consequently, the study of gene regulatory network (GRN) architecture, function and evolution now forms a major part of modern biology. However, it is impossible to experimentally observe the evolution of GRNs on the timescales on which living species evolve. In silico evolution provides an approach to studying the long-term evolution of GRNs, but many models have either considered network architecture from non-adaptive evolution, or evolution to non-biological objectives. Here, we address a number of important modelling and biological questions about the evolution of GRNs to the realistic goal of biomass production. Can different commonly used simulation paradigms, in particular deterministic and stochastic Boolean networks, with and without basal gene expression, be used to compare adaptive with non-adaptive evolution of GRNs? Are these paradigms together with this goal sufficient to generate a range of solutions? Will the interaction between a biological goal and evolutionary dynamics produce trade-offs between growth and mutational robustness? We show that stochastic basal gene expression forces shrinkage of genomes due to energetic constraints and is a prerequisite for some solutions. In systems that are able to evolve rates of basal expression, two optima, one with and one without basal expression, are observed. Simulation paradigms without basal expression generate bloated networks with non-functional elements. Further, a range of functional solutions was observed under identical conditions only in stochastic networks. Moreover, there are trade-offs between efficiency and yield, indicating an inherent intertwining of fitness and evolutionary dynamics

Bridging Archaeology and Genetics

With the development of the polymerase chain reaction (PCR) in the 1980s, the application of molecular methods to archaeological questions has seen a rapid expansion in the last three decades, addressing major research topics including human origins and migrations, domestication and chronology. The recent introduction of next-generation sequencing (NGS) has revolutionised the field, allowing for a larger amount of data to be generated quickly and at ever-decreasing costs. With such techniques now available, it is crucial for a clear and comprehensive dialogue to be established between archaeologists and geneticists. In the following paper, we first review the history of archaeogenetics before addressing some of the major misconceptions that remain commonly widespread across audiences. These include the misconception that genetics can reconstruct full phenotypes or that modern populations can be solely used to retrace a species? origin or domestication. After exploring the current potential of genetics applied to archaeology through successful case studies, we highlight practical considerations when undertaking archaeogenetic research including sample status and selecting adequate genetic markers and methods. Finally, we suggest ways of bridging the gap between both disciplines so as to allow better collaborations in the future.Fil: Lebrasseur, Ophélie. No especifíca;Fil: Ryan, Hannah. No especifíca;Fil: Abbona, Cinthia Carolina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mendoza. Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales. Provincia de Mendoza. Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales. Universidad Nacional de Cuyo. Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales; Argentin