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At least 37 records · Page 2

Vicennial metagenomic time series unveils evolutionary dynamics of giant viruses in a freshwater ecosystem

Giant viruses play crucial ecological roles in aquatic ecosystems, yet their evolutionary dynamics in response to environmental changes, particularly in freshwater environments, are not well understood. We analyzed a 20-year time series (2000-2019) of 471 co-assembled metagenomes from Lake Mendota (USA) to reconstruct 1512 giant virus metagenome-assembled genomes, providing insights into viral genome evolution. Viruses in the order Imitervirales dominate the virome, remaining consistent across seasons and years. Our findings reveal gene duplication (23% of genes) and horizontal gene transfer (29% of genes) as key drivers of genomic innovation. A co-occurrence network analysis indicates increased virus-host interactions following the introduction of an invasive predatory zooplankton in 2009, highlighting potential hosts in Bigyra, Perkinsea, and Euglenozoa. While single nucleotide polymorphism analysis shows predominantly purifying selection in viral genes, there is a significant increase in positively selected genes post-invasion, particularly those related to infection. Comparative evolutionary analyses reveal that giant viruses exhibit genome-wide substitution rates similar to co-occurring bacteria but significantly slower than smaller dsDNA phages, suggesting both stability and adaptability. Our study demonstrates that freshwater giant viruses employ various evolutionary strategies to respond to environmental change. These results underscore their significant yet often underappreciated role in freshwater ecosystem dynamics.

Vasquez, Yumary M

A compendium of human gene functions derived from evolutionary modelling

A comprehensive, computable representation of the functional repertoire of all macromolecules encoded within the human genome is a foundational resource for biology and biomedical research. The Gene Ontology Consortium has been working towards this goal by generating a structured body of information about gene functions, which now includes experimental findings reported in more than 175,000 publications for human genes and genes in experimentally tractable model organisms 1,2 . Here, we describe the results of a large, international effort to integrate all of these findings to create a representation of human gene functions that is as complete and accurate as possible. Specifically, we apply an expert-curated, explicit evolutionary modelling approach to all human protein-coding genes. This approach integrates available experimental information across families of related genes into models that reconstruct the gain and loss of functional characteristics over evolutionary time. The models and the resulting set of 68,667 integrated gene functions cover approximately 82% of human protein-coding genes. The functional repertoire reveals a marked preponderance of molecular regulatory functions, and the models provide insights into the evolutionary origins of human gene functions. We show that our set of descriptions of functions can improve the widely used genomic technique of Gene Ontology enrichment analysis. The experimental evidence for each functional characteristic is recorded, thereby enabling the scientific community to help review and improve the resource, which we have made publicly available.

59 BASIC BIOLOGICAL SCIENCES

Specialization Restricts the Evolutionary Paths Available to Yeast Sugar Transporters

Functional innovation at the protein level is a key source of evolutionary novelties. The constraints on functional innovations are likely to be highly specific in different proteins, which are shaped by their unique histories and the extent of global epistasis that arises from their structures and biochemistries. These contextual nuances in the sequence–function relationship have implications both for a basic understanding of the evolutionary process and for engineering proteins with desirable properties. Here, we have investigated the molecular basis of novel function in a model member of an ancient, conserved, and biotechnologically relevant protein family. These Major Facilitator Superfamily sugar porters are a functionally diverse group of proteins that are thought to be highly plastic and evolvable. By dissecting a recent evolutionary innovation in an α-glucoside transporter from the yeast Saccharomyces eubayanus, we show that the ability to transport a novel substrate requires high-order interactions between many protein regions and numerous specific residues proximal to the transport channel. To reconcile the functional diversity of this family with the constrained evolution of this model protein, we generated new, state-of-the-art genome annotations for 332 Saccharomycotina yeast species spanning ~400 My of evolution. By integrating phylogenetic and phenotypic analyses across these species, we show that the model yeast α-glucoside transporters likely evolved from a multifunctional ancestor and became subfunctionalized. The accumulation of additive and epistatic substitutions likely entrenched this subfunction, which made the simultaneous acquisition of multiple interacting substitutions the only reasonably accessible path to novelty.

59 BASIC BIOLOGICAL SCIENCES

Pangenomes suggest ecological-evolutionary responses to experimental soil warming

ABSTRACT Below-ground carbon transformations that contribute to healthy soils represent a natural climate change mitigation, but newly acquired traits adaptive to climate stress may alter microbial feedback mechanisms. To better define microbial evolutionary responses to long-term climate warming, we study microorganisms from an ongoing in situ soil warming experiment where, for over three decades, temperate forest soils are continuously heated at 5°C above ambient. We hypothesize that across generations of chronic warming, genomic signatures within diverse bacterial lineages reflect adaptations related to growth and carbon utilization. From our bacterial culture collection isolated from experimental heated and control plots, we sequenced genomes representing dominant taxa sensitive to warming, including lineages of Actinobacteria, Alphaproteobacteria, and Betaproteobacteria. We investigated genomic attributes and functional gene content to identify signatures of adaptation. Comparative pangenomics revealed accessory gene clusters related to central metabolism, competition, and carbon substrate degradation, with few functional annotations explicitly associated with long-term warming. Trends in functional gene patterns suggest genomes from heated plots were relatively enriched in central carbohydrate and nitrogen metabolism pathways, while genomes from control plots were relatively enriched in amino acid and fatty acid metabolism pathways. We observed that genomes from heated plots had less codon bias, suggesting potential adaptive traits related to growth or growth efficiency. Codon usage bias varied for organisms with similar 16S rrn operon copy number, suggesting that these organisms experience different selective pressures on growth efficiency. Our work suggests the emergence of lineage-specific trends as well as common ecological-evolutionary microbial responses to climate change. IMPORTANCE Anthropogenic climate change threatens soil ecosystem health in part by altering below-ground carbon cycling carried out by microbes. Microbial evolutionary responses are often overshadowed by community-level ecological responses, but adaptive responses represent potential changes in traits and functional potential that may alter ecosystem function. We predict that microbes are adapting to climate change stressors like soil warming. To test this, we analyzed the genomes of bacteria from a soil warming experiment where soil plots have been experimentally heated 5°C above ambient for over 30 years. While genomic attributes were unchanged by long-term warming, we observed trends in functional gene content related to carbon and nitrogen usage and genomic indicators of growth efficiency. These responses may represent new parameters in how soil ecosystems feedback to the climate system.

Choudoir, Mallory J. (ORCID:0000000291175150)

Evolutionary history of arbuscular mycorrhizal fungi and genomic signatures of obligate symbiosis

The colonization of land and the diversification of terrestrial plants is intimately linked to the evolutionary history of their symbiotic fungal partners. Extant representatives of these fungal lineages include mutualistic plant symbionts, the arbuscular mycorrhizal (AM) fungi in Glomeromycota and fine root endophytes in Endogonales (Mucoromycota), as well as fungi with saprotrophic, pathogenic and endophytic lifestyles. These fungal groups separate into three monophyletic lineages but their evolutionary relationships remain enigmatic confounding ancestral reconstructions. Their taxonomic ranks are currently fluid. In this study, we recognize these three monophyletic linages as phyla, and use a balanced taxon sampling and broad taxonomic representation for phylogenomic analysis that rejects a hard polytomy and resolves Glomeromycota as sister to a clade composed of Mucoromycota and Mortierellomycota. Low copy numbers of genes associated with plant cell wall degradation could not be assigned to the transition to a plant symbiotic lifestyle but appears to be an ancestral phylogenetic signal. Both plant symbiotic lineages, Glomeromycota and Endogonales, lack numerous thiamine metabolism genes but the lack of fatty acid synthesis genes is specific to AM fungi. Many genes previously thought to be missing specifically in Glomeromycota are either missing in all analyzed phyla, or in some cases, are actually present in some of the analyzed AM fungal lineages, e.g. the high affinity phosphorus transporter Pho89. Based on a broad taxon sampling of fungal genomes we present a well-supported phylogeny for AM fungi and their sister lineages. We show that among these lineages, two independent evolutionary transitions to mutualistic plant symbiosis happened in a genomic background profoundly different from that known from the emergence of ectomycorrhizal fungi in Dikarya. These results call for further reevaluation of genomic signatures associated with plant symbiosis.

59 BASIC BIOLOGICAL SCIENCES

Evolutionary problems of Cepheids and other giants investigated with new radiative opacities

Comparison of evolutionary tracks, pulsation constants, and linearized pulsational-stability coefficients for stellar models applicable to the problems of classical Cepheids, whose structures were calculated using the Cox-Stewart (1965) opacities and a recently computed set of opacities. The latter are based on the hot 'Thomas-Fermi' statistical model of the atom for all elements heavier than hydrogen and helium; they contain larger helium and metals contributions, but a smaller hydrogen contribution than the former ones for the same chemical composition. The difference in metals contribution affects mainly the location and shape of the evolutionary tracks on the H-R diagram, while the difference in hydrogen and helium contributions has its greatest effect on the pulsational properties of the Cepheid models. From the comparison of evolutionary tracks it is concluded that: (1) the theoretical M/L relation for evolved giants is changed very little by using the second set of opacities; (2) Q-values for the fundamental mode of radial pulsation in Cepheid envelope models increase if the second set is used, but the classical mass discrepancy remains; and (3) the second set leads to pulsational-instability.

Carson, T. R.

Evolutionary models of interstellar chemistry

The goal of evolutionary models of interstellar chemistry is to understand how interstellar clouds came to be the way they are, how they will change with time, and to place them in an evolutionary sequence with other celestial objects such as stars. An improved Mark II version of an earlier model of chemistry in dynamically evolving clouds is presented. The Mark II model suggests that the conventional elemental C/O ratio less than one can explain the observed abundances of CI and the nondetection of O2 in dense clouds. Coupled chemical-dynamical models seem to have the potential to generate many observable discriminators of the evolutionary tracks. This is exciting, because, in general, purely dynamical models do not yield enough verifiable discriminators of the predicted tracks.

Prasad, Sheo S.

Evolutionary period changes in the rapidly oscillating Ap stars

Preliminary computations of the asymptotic p-mode frequency spacings, and their time derivatives, are presented for a grid of evolutionary models of the rapidly oscillating Ap ('roAp') stars. It is shown how the frequency spacings depend on stellar mass, metallicity, and evolutionary stage. The frequency spacings observed in two of the roAp stars indicate that they either are main-sequence objects or have evolved off of the main sequence, depending on how the pulsation spectrum is interpreted. A way to remove this ambiguity is suggested: secular evolutionary changes in the pulsation frequencies may be measurable if the roAp stars have evolved off of the main sequence. In principle, this determination may be made for the roAp star HR 1217 with existing data.

Heller, Clayton H.

Evolutionary tree reconstruction

It is described how Minimum Description Length (MDL) can be applied to the problem of DNA and protein evolutionary tree reconstruction. If there is a set of mutations that transform a common ancestor into a set of the known sequences, and this description is shorter than the information to encode the known sequences directly, then strong evidence for an evolutionary relationship has been found. A heuristic algorithm is described that searches for the simplest tree (smallest MDL) that finds close to optimal trees on the test data. Various ways of extending the MDL theory to more complex evolutionary relationships are discussed.

Cheeseman, Peter

Scheduling Earth Observing Fleets Using Evolutionary Algorithms: Problem Description and Approach

We describe work in progress concerning multi-instrument, multi-satellite scheduling. Most, although not all, Earth observing instruments currently in orbit are unique. In the relatively near future, however, we expect to see fleets of Earth observing spacecraft, many carrying nearly identical instruments. This presents a substantially new scheduling challenge. Inspired by successful commercial applications of evolutionary algorithms in scheduling domains, this paper presents work in progress regarding the use of evolutionary algorithms to solve a set of Earth observing related model problems. Both the model problems and the software are described. Since the larger problems will require substantial computation and evolutionary algorithms are embarrassingly parallel, we discuss our parallelization techniques using dedicated and cycle-scavenged workstations.

Globus, Al

Evolutionary Design and Simulation of a Tube Crawling Inspection Robot

The Space Robotics Assembly Team Simulation (SpaceRATS) is an expansive concept that will hopefully lead to a space flight demonstration of a robotic team cooperatively assembling a system from its constitutive parts. A primary objective of the SpaceRATS project is to develop a generalized evolutionary design approach for multiple classes of robots. The portion of the overall SpaceRats program associated with the evolutionary design and simulation of an inspection robot's morphology is the subject of this paper. The vast majority of this effort has concentrated on the use and modification of Darwin2K, a robotic design and simulation software package, to analyze the design of a tube crawling robot. This robot is designed for carrying out inspection duties in relatively inaccessible locations within a liquid rocket engine similar to the SSME. A preliminary design of the tube crawler robot was completed, and the mechanical dynamics of the system were simulated. An evolutionary approach to optimizing a few parameters of the system was utilized, resulting in a more optimum design.

Craft, Michael

Aerodynamic Shape Optimization Using Evolutionary Algorithms

A method for aerodynamic shape optimization based on an evolutionary algorithm approach is presented and demonstrated. Results are presented for a number of model problems to access the effect of algorithm parameters on convergence efficiency and reliability. A transonic viscous airfoil optimization problem, both single and two-objective variations, is used as the basis for a preliminary comparison with an adjoint-gradient optimizer. The evolutionary algorithm is coupled with a transonic full potential flow solver and is used to optimize the inviscid flow about transonic wings including multi-objective and multi-discipline solutions that lead to the generation of pareto fronts. The results indicate that the evolutionary algorithm approach is easy to implement, flexible in application and extremely reliable.

Holst, Terry L.

A Genetic Representation for Evolutionary Fault Recovery in Virtex FPGAs

Most evolutionary approaches to fault recovery in FPGAs focus on evolving alternative logic configurations as opposed to evolving the intra-cell routing. Since the majority of transistors in a typical FPGA are dedicated to interconnect, nearly 80% according to one estimate, evolutionary fault-recovery systems should benefit hy accommodating routing. In this paper, we propose an evolutionary fault-recovery system employing a genetic representation that takes into account both logic and routing configurations. Experiments were run using a software model of the Xilinx Virtex FPGA. We report that using four Virtex combinational logic blocks, we were able to evolve a 100% accurate quadrature decoder finite state machine in the presence of a stuck-at-zero fault.

Lohn, Jason

Aerodynamic Shape Optimization using an Evolutionary Algorithm

A method for aerodynamic shape optimization based on an evolutionary algorithm approach is presented and demonstrated. Results are presented for a number of model problems to access the effect of algorithm parameters on convergence efficiency and reliability. A transonic viscous airfoil optimization problem-both single and two-objective variations is used as the basis for a preliminary comparison with an adjoint-gradient optimizer. The evolutionary algorithm is coupled with a transonic full potential flow solver and is used to optimize the inviscid flow about transonic wings including multi-objective and multi-discipline solutions that lead to the generation of pareto fronts. The results indicate that the evolutionary algorithm approach is easy to implement, flexible in application and extremely reliable.

Hoist, Terry L.

Automated Hardware Design via Evolutionary Search

The goal of this research is to investigate the application of evolutionary search to the process of automated engineering design. Evolutionary search techniques involve the simulation of Darwinian mechanisms by computer algorithms. In recent years, such techniques have attracted much attention because they are able to tackle a wide variety of difficult problems and frequently produce acceptable solutions. The results obtained are usually functional, often surprising, and typically "messy" because the algorithms are told to concentrate on the overriding objective and not elegance or simplicity. advantages. First, faster design cycles translate into time and, hence, cost savings. Second, automated design techniques can be made to scale well and hence better deal with increasing amounts of design complexity. Third, design quality can increase because design properties can be specified a priori. For example, size and weight specifications of a device, smaller and lighter than the best known design, might be optimized by the automated design technique. The domain of electronic circuit design is an advantageous platform in which to study automated design techniques because it is a rich design space that is well understood, permitting human-created designs to be compared to machine- generated designs. developed for circuit design was to automatically produce high-level integrated electronic circuit designs whose properties permit physical implementation in silicon. This process entailed designing an effective evolutionary algorithm and solving a difficult multiobjective optimization problem. FY 99 saw many accomplishments in this effort.

Lohn, Jason D.

Bell-Curve Based Evolutionary Optimization Algorithm

The paper presents an optimization algorithm that falls in the category of genetic, or evolutionary algorithms. While the bit exchange is the basis of most of the Genetic Algorithms (GA) in research and applications in America, some alternatives, also in the category of evolutionary algorithms, but use a direct, geometrical approach have gained popularity in Europe and Asia. The Bell-Curve Based Evolutionary Algorithm (BCB) is in this alternative category and is distinguished by the use of a combination of n-dimensional geometry and the normal distribution, the bell-curve, in the generation of the offspring. The tool for creating a child is a geometrical construct comprising a line connecting two parents and a weighted point on that line. The point that defines the child deviates from the weighted point in two directions: parallel and orthogonal to the connecting line, the deviation in each direction obeying a probabilistic distribution. Tests showed satisfactory performance of BCB. The principal advantage of BCB is its controllability via the normal distribution parameters and the geometrical construct variables.

Sobieszczanski-Sobieski, J.

Taking evolutionary circuit design from experimentation to implementation: some useful techniques and a silicon demonstration

Current techniques in evolutionary synthesis of analogue and digital circuits designed at transistor level have focused on achieving the desired functional response, without paying sufficient attention to issues needed for a practical implementation of the resulting solution. No silicon fabrication of circuits with topologies designed by evolution has been done before, leaving open questions on the feasibility of the evolutionary circuit design approach, as well as on how high-performance, robust, or portable such designs could be when implemented in hardware. It is argued that moving from evolutionary 'design-for experimentation' to 'design-for-implementation' requires, beyond inclusion in the fitness function of measures indicative of circuit evaluation factors such as power consumption and robustness to temperature variations, the addition of certain evaluation techniques that are not common in conventional design. Several such techniques that were found to be useful in evolving designs for implementation are presented; some are general, and some are particular to the problem domain of transistor-level logic design, used here as a target application. The example used here is a multifunction NAND/NOR logic gate circuit, for which evolution obtained a creative circuit topology more compact than what has been achieved by multiplexing a NAND and a NOR gate. The circuit was fabricated in a 0.5 mum CMOS technology and silicon tests showed good correspondence with the simulations.

digital circuits designs

Development of X-TOOLSS: Preliminary Design of Space Systems Using Evolutionary Computation

Evolutionary computational (EC) techniques such as genetic algorithms (GA) have been identified as promising methods to explore the design space of mechanical and electrical systems at the earliest stages of design. In this paper the authors summarize their research in the use of evolutionary computation to develop preliminary designs for various space systems. An evolutionary computational solver developed over the course of the research, X-TOOLSS (Exploration Toolset for the Optimization of Launch and Space Systems) is discussed. With the success of early, low-fidelity example problems, an outline of work involving more computationally complex models is discussed.

Schnell, Andrew R.