Pleiotropy, a feature or a bug? Toward co-ordinating plant growth, development, and environmental responses through engineering plant hormone signaling

The advent of gene editing technologies such as CRISPR has simplified co-ordinating trait development. However, identifying candidate genes remains a challenge due to complex gene networks and pathways. These networks exhibit pleiotropy, complicating the determination of specific gene and pathway functions. In this review, we explore how systems biology and single-cell sequencing technologies can aid in identifying candidate genes for co-ordinating specifics of plant growth and development within specific temporal and tissue contexts. Exploring sequence-function space of these candidate genes and pathway modules with synthetic biology allows us to test hypotheses and define genotype-phenotype relationships through reductionist approaches. Collectively, these techniques hold the potential to advance breeding and genetic engineering strategies while also addressing genetic diversity issues critical for adaptation and trait development.

Promoting scientific literacy in evolution through citizen science

Evolutionary understanding is central to biology. It is also an essential prerequisite to understanding and making informed decisions about societal issues such as climate change. Yet, evolution is generally poorly understood by civil society and many misconceptions exist. Citizen science, which has been increasing in popularity as a means to gather new data and promote scientific literacy, is one strategy through which people could learn about evolution. However, despite the potential for citizen science to promote evolution learning opportunities, very few projects implement them. In this paper, we make the case for incorporating evolution education into citizen science, define key learning goals, and suggest opportunities for designing and evaluating projects in order to promote scientific literacy in evolution.

Advantages of laboratory natural selection in the applied sciences

In the past three decades, laboratory natural selection has become a widely used technique in biological research. Most studies which have utilized this technique are in the realm of basic science, often testing hypotheses related to mechanisms of evolutionary change or ecological dynamics. While laboratory natural selection is currently utilized heavily in this setting, there is a significant gap with its usage in applied studies, especially when compared to the other selection experiment methodologies like artificial selection and directed evolution. This is despite avenues of research in the applied sciences which seem well suited to laboratory natural selection. In this review, we place laboratory natural selection in context with other selection experiments, identify the characteristics which make it well suited for particular kinds of applied research and briefly cover key examples of the usefulness of selection experiments within applied science. Finally, we identify three promising areas of inquiry for laboratory natural selection in the applied sciences: bioremediation technology, identifying mechanisms of drug resistance and optimizing biofuel production. Although laboratory natural selection is currently less utilized in applied science when compared to basic research, the method has immense promise in the field moving forward.

Evolution in the Anthropocene: Informing Governance and Policy

The Anthropocene biosphere constitutes an unprecedented phase in the evolution of life on Earth with one species, humans, exerting extensive control. The increasing intensity of anthropogenic forces in the twenty-first century has widespread implications for attempts to govern both human-dominated ecosystems and the last remaining wild ecosystems. Here, we review how evolutionary biology can inform governance and policies in the Anthropocene, focusing on five governance challenges that span biodiversity, environmental management, food and other biomass production, and human health. The five challenges are: ( a) evolutionary feedbacks, ( b) maintaining resilience, ( c) alleviating constraints, ( d) coevolutionary disruption, and ( e) biotechnology. Strategies for governing these dynamics will themselves have to be coevolutionary, as eco-evolutionary and social dynamics change in response to each other.

Celebrity Opinion Influences Public Acceptance of Human Evolution

The present research examined the influence of celebrity opinion upon individuals' acceptance of the theory of evolution. Priming stimuli were developed purveying pro-evolution, anti-evolution, or neutral opinion (Study 1). When paired with a male celebrity or expert source (Study 2), the male celebrity, but not the male expert, influenced undergraduates' acceptance of evolution. The influence of the male celebrity on acceptance of evolution was replicated in a community sample (Study 3). When paired with a female celebrity source, undergraduates' acceptance of evolution was similarly influenced (Study 4). Together, these findings extend our understanding of the reach of credible celebrity endorsers beyond consumer behavior to core individual beliefs, such as those surrounding the acceptance of human evolution.

Prescriptive Evolution to Conserve and Manage Biodiversity

We are witnessing a global, but unplanned, evolutionary experiment with the biodiversity of the planet. Anthropogenic disturbances such as habitat degradation and climate change result in evolutionary mismatch between the environments to which species are adapted and those in which they now exist. The impacts of unmanaged evolution are pervasive, but approaches to address them have received little attention. We review the evolutionary challenges of managing populations in the Anthropocene and introduce the concept of prescriptive evolution, which considers how evolutionary processes may be leveraged to proactively promote wise management. We advocate the planned management of evolutionary processes and explore the advantages of evolutionary interventions to preserve and sustain biodiversity. We show how an evolutionary perspective to conserving biodiversity is fundamental to effective management. Finally, we advocate building frameworks for decision-making, monitoring, and implementation at the boundary between management and evolutionary science to enhance conservation outcomes.

Applying evolutionary biology to address global challenges

Two categories of evolutionary challenges result from escalating human impacts on the planet. The first arises from cancers, pathogens, and pests that evolve too quickly and the second, from the inability of many valued species to adapt quickly enough. Applied evolutionary biology provides a suite of strategies to address these global challenges that threaten human health, food security, and biodiversity. This Review highlights both progress and gaps in genetic, developmental, and environmental manipulations across the life sciences that either target the rate and direction of evolution or reduce the mismatch between organisms and human-altered environments. Increased development and application of these underused tools will be vital in meeting current and future targets for sustainable development.

Experimental evolution of an oncolytic vesicular stomatitis virus with increased selectivity for p53-deficient cells

Experimental evolution has been used for various biotechnological applications including protein and microbial cell engineering, but less commonly in the field of oncolytic virotherapy. Here, we sought to adapt a rapidly evolving RNA virus to cells deficient for the tumor suppressor gene p53, a hallmark of cancer cells. To achieve this goal, we established four independent evolution lines of the vesicular stomatitis virus (VSV) in p53-knockout mouse embryonic fibroblasts (p53-/- MEFs) under conditions favoring the action of natural selection. We found that some evolved viruses showed increased fitness and cytotoxicity in p53-/- cells but not in isogenic p53+/+ cells, indicating gene-specific adaptation. However, full-length sequencing revealed no obvious or previously described genetic changes associated with oncolytic activity. Half-maximal effective dose (EC50) assays in mouse p53-positive colon cancer (CT26) and p53-deficient breast cancer (4T1) cells indicated that the evolved viruses were more effective against 4T1 cells than the parental virus or a reference oncolytic VSV (MΔ51), but showed no increased efficacy against CT26 cells. In vivo assays using 4T1 syngeneic tumor models showed that one of the evolved lines significantly delayed tumor growth compared to mice treated with the parental virus or untreated controls, and was able to induce transient tumor suppression. Our results show that RNA viruses can be specifically adapted typical cancer features such as p53 inactivation, and illustrate the usefulness of experimental evolution for oncolytic virotherapy.

Plant domestication and resistance to herbivory

Transformation of wild species into elite cultivars through "domestication" entails evolutionary responses in which plant populations adapt to selection. Domestication is a process characterized by the occurrence of key mutations in morphological, phenological, or utility genes, which leads to the increased adaptation and use of the plant; however, this process followed by modern plant breeding practices has presumably narrowed the genetic diversity in crop plants. The reduction of genetic diversity could result in "broad susceptibility" to newly emerging herbivores and pathogens, thereby threatening long-term crop retention. Different QTLs influencing herbivore resistance have also been identified, which overlap with other genes of small effect regulating resistance indicating the presence of pleiotropism or linkage between such genes. However, this reduction in genetic variability could be remunerated by introgression of novel traits from wild perhaps with antifeedant and antinutritional toxic components. Thus it is strongly believed that transgenic technologies may provide a radical and promising solution to combat herbivory as these avoid linkage drag and also the antifeedant angle. Here, important questions related to the temporal dynamics of resistance to herbivory and intricate genetic phenomenon with their impact on crop evolution are addressed and at times hypothesized for future validation.

Evolution-centered teaching of biology

University teaching remains an area of concern, and perhaps the most difficult discipline for both teaching and learning is evolution. The concepts that underpin evolution, although complex, have been shown to be fairly straightforward, yet students arrive at and leave university with serious misconceptions, misunderstandings related to language, and often a reluctance to learn the subject because of cultural or societal pressures. Because of the unifying power of the theory, however, it is necessary not only for biology students to have a thorough understanding of evolution, but also for them to learn it in their first year so that this knowledge can then be taken into further years of study. Rather than teaching evolution at the end of a degree program, embedding it as a semester-long first-year course will ensure that a far larger number of students are made aware of misconceptions that they have brought with them from high school. Teaching through traditional passive lectures makes learning difficult conceptual material more difficult, and needs to be replaced with more interactive lectures coupled with inquiry-based practicals and small group-learning sessions to increase student engagement and interest in the subject. A new approach in pedagogy, curriculum design, and academic staff professional development is essential, especially at this time, when enrollments across science courses in many countries around the world are in decline.

The double-edged sword: How evolution can make or break a live-attenuated virus vaccine

Even students who reject evolution are often willing to consider cases in which evolutionary biology contributes to, or undermines, biomedical interventions. Moreover the intersection of evolutionary biology and biomedicine is fascinating in its own right. This review offers an overview of the ways in which evolution has impacted the design and deployment of live-attenuated virus vaccines, with subsections that may be useful as lecture material or as the basis for case studies in classes at a variety of levels. Live- attenuated virus vaccines have been modified in ways that restrain their replication in a host, so that infection (vaccination) produces immunity but not disease. Applied evolution, in the form of serial passage in novel host cells, is a "classical" method to generate live-attenuated viruses. However many live-attenuated vaccines exhibit reversion to virulence through back-mutation of attenuating mutations, compensatory mutations elsewhere in the genome, recombination or reassortment, or changes in quasispecies diversity. Additionally the combination of multiple live-attenuated strains may result in competition or facilitation between individual vaccine viruses, resulting in undesirable increases in virulence or decreases in immunogenicity. Genetic engineering informed by evolutionary thinking has led to a number of novel approaches to generate live-attenuated virus vaccines that contain substantial safeguards against reversion to virulence and that ameliorate interference among multiple vaccine strains. Finally, vaccines have the potential to shape the evolution of their wild type counterparts in counter-productive ways; at the extreme vaccine-driven eradication of a virus may create an empty niche that promotes the emergence of new viral pathogens.

Dynamics of haplotype frequency change in a CD8+TL epitope of simian immunodeficiency virus

Deep pyrosequencing of a CD8+TL epitope from the Tat protein of simian immunodeficiency virus (SIV) from four infected rhesus macaques carrying the restricting MHC allele (Mamu-A*01) for that epitope, revealed that natural selection favoring escape mutations led to an increase in the frequency of haplotypes in the epitope region that differed from the inoculum. After 20 weeks of infection, a new sequence haplotype in the epitope region had increased to a frequency greater than 50% in each of the four monkeys (range 57.9-98.9%); but the predominant haplotype was not the same in all four monkeys. Thus, even under strong selection favoring escape from CD8+TL recognition, the random nature of mutation itself is the primary factor affecting which escape mutation is likely to become predominant within an individual host. The relationship between the frequency of the inoculum haplotype in the epitope region and time post-infection approximated a simple hyperbola. On this assumption, the expected ratio of the frequencies at the inoculum at two times t(1) and t(2), f(i)(t(2))/f(i)(t(1)), will be given by t(1)/t(2). Because standard phylogenetic methods for reconstructing ancestral sequences failed to predict the inoculum sequence correctly, we used this relationship to predict the inoculum sequence with 100% accuracy, given data on haplotype frequencies at different time periods.

Viral resistance evolution fully escapes a rationally designed lethal inhibitor

Viruses are notoriously capable of evolving resistance to drugs. However, if the endpoint of resistance evolution is only partial escape, a feasible strategy should be to stack drugs, so the combined effect of partial inhibition by several drugs results in net inhibition. Assessing the feasibility of this approach requires quantitative data on viral fitness before and after evolution of resistance to a drug, as done here with bacteriophage T7. An inhibitory gene expressed from a phage promoter aborts wild-type T7 infections. The effect is so severe that the phage population declines when exposed to the inhibitor but expands a billion-fold per hour in its absence. In prior work, T7 evolved modest resistance to this inhibitor, an expected result. Given the nature of the inhibitor, that it used the phage's own promoter to target the phage's destruction, we anticipated that resistance evolution would be limited as the phage may need to evolve a new regulatory system, with simultaneous changes in its RNA polymerase (RNAP) and many of its promoters to fully escape inhibition. We show here that further adaptation of the partially resistant phage led to complete resistance. Resistance evolution was due to three mutations in the RNAP gene and two other genes; unexpectedly, no changes were observed in promoters. Consideration of other mechanisms of T7 inhibition leaves hope that permanent inhibition of viral growth with drugs can in principle be achieved.

Rapid experimental evolution of pesticide resistance in C. elegans entails no costs and affects the mating system

Pesticide resistance is a major concern in natural populations and a model trait to study adaptation. Despite the importance of this trait, the dynamics of its evolution and of its ecological consequences remain largely unstudied. To fill this gap, we performed experimental evolution with replicated populations of Caenorhabditis elegans exposed to the pesticide Levamisole during 20 generations. Exposure to Levamisole resulted in decreased survival, fecundity and male frequency, which declined from 30% to zero. This was not due to differential susceptibility of males. Rather, the drug affected mobility, resulting in fewer encounters, probably leading to reduced outcrossing rates. Adaptation, i.e., increased survival and fecundity, occurred within 10 and 20 generations, respectively. Male frequency also increased by generation 20. Adaptation costs were undetected in the ancestral environment and in presence of Ivermectin, another widely-used pesticide with an opposite physiological effect. Our results demonstrate that pesticide resistance can evolve at an extremely rapid pace. Furthermore, we unravel the effects of behaviour on life-history traits and test the environmental dependence of adaptation costs. This study establishes experimental evolution as a powerful tool to tackle pesticide resistance, and paves the way to further investigations manipulating environmental and/or genetic factors underlying adaptation to pesticides.

Drug interactions modulate the potential for evolution of resistance

Antimicrobial treatments increasingly rely on multidrug combinations, in part because of the emergence and spread of antibiotic resistance. The continued effectiveness of combination treatments depends crucially on the frequency with which multidrug resistance arises. Yet, it is unknown how this propensity for resistance depends on cross-resistance and on epistatic interactions-ranging from synergy to antagonism-between the drugs. Here, we analyzed how interactions between pairs of drugs affect the spontaneous emergence of resistance in the medically important pathogen Staphylococcus aureus. Resistance is selected for within a window of drug concentrations high enough to inhibit wild-type growth but low enough for some resistant mutants to grow. Introducing an experimental method for high-throughput colony imaging, we counted resistant colonies arising across a two-dimensional matrix of drug concentrations for each of three drug pairs. Our data show that these different drug combinations have significantly different impacts on the size of the window of drug concentrations where resistance is selected for. We framed these results in a mathematical model in which the frequencies of resistance to single drugs, cross-resistance, and epistasis combine to determine the propensity for multidrug resistance. The theory suggests that drug pairs which interact synergistically, preferred for their immediate efficacy, may in fact favor the future evolution of resistance. This framework reveals the central role of drug epistasis in the evolution of resistance and points to new strategies for combating the emergence of drug-resistant bacteria.

The effect of natural selection on the performance of maximum parsimony

Background

Maximum parsimony is one of the most commonly used and extensively studied phylogeny reconstruction methods. While current evaluation methodologies such as computer simulations provide insight into how well maximum parsimony reconstructs phylogenies, they tell us little about how well maximum parsimony performs on taxa drawn from populations of organisms that evolved subject to natural selection in addition to the random factors of drift and mutation. It is clear that natural selection has a significant impact on Among Site Rate Variation (ASRV) and the rate of accepted substitutions; that is, accepted mutations do not occur with uniform probability along the genome and some substitutions are more likely to occur than other substitutions. However, little is know about how ASRV and non-uniform character substitutions impact the performance of reconstruction methods such as maximum parsimony. To gain insight into these issues, we study how well maximum parsimony performs with data generated by Avida, a digital life platform where populations of digital organisms evolve subject to natural selective pressures.

Results

We first identify conditions where natural selection does affect maximum parsimony's reconstruction accuracy. In general, as we increase the probability that a significant adaptation will occur in an intermediate ancestor, the performance of maximum parsimony improves. In fact, maximum parsimony can correctly reconstruct small 4 taxa trees on data that have received surprisingly many mutations if the intermediate ancestor has received a significant adaptation. We demonstrate that this improved performance of maximum parsimony is attributable more to ASRV than to non-uniform character substitutions.

Conclusion

Maximum parsimony, as well as most other phylogeny reconstruction methods, may perform significantly better on actual biological data than is currently suggested by computer simulation studies because of natural selection. This is largely due to specific sites becoming fixed in the genome that perform functions associated with an improved fitness.

Reconstruction of large phylogenetic trees: A parallel approach

Reconstruction of phylogenetic trees for very large datasets is a known example of a computationally hard problem. In this paper, we present a parallel computing model for the widely used Multiple Instruction Multiple Data (MIMD) architecture. Following the idea of divide-and-conquer, our model adapts the recursive-DCM3 decomposition method [Roshan, U., Moret, B.M.E., Williams, T.L., Warnow, T, 2004a. Performance of suptertree methods on various dataset decompositions. In: Binida-Emonds, O.R.P. (Eds.), Phylogenetic Supertrees: Combining Information to Reveal the Tree of Life, vol. 3 of Computational Biology, Kluwer Academics, pp. 301-328; Roshan, U., Moret, B.M.E., Williams, T.L., Warnow, T., 2004b. Rec-I-DCM3: A Fast Algorithmic Technique for reconstructing large phylogenetic trees, Proceedings of the IEEE Computational Systems Bioinformatics Conference (ICSB)] to divide datasets into smaller subproblems. It distributes computation load over multiple processors so that each processor constructs subtrees on each subproblem within a batch in parallel. It finally collects the resulting trees and merges them into a supertree. The proposed model is flexible as far as methods for dividing and merging datasets are concerned. We show that our method greatly reduces the computational time of the sequential version of the program. As a case study, our parallel approach only takes 22.1h on four processors to outperform the best score to date (Found at 123.7h by the Rec-I-DCM3 program [Roshan, U., Moret, B.M.E., Williams, T.L., Warnow, T, 2004a. Performance of suptertree methods on various dataset decompositions. In: Binida-Emonds, O.R.P. (Eds.), Phylogenetic Supertrees: Combining Information to Reveal the Tree of Life, vol. 3 of Computational Biology, Kluwer Academics, pp. 301-328; Roshan, U., Moret, B.M.E., Williams, T.L., Warnow, T., 2004b. Rec-I-DCM3: A Fast Algorithmic Technique for reconstructing large phylogenetic trees, Proceedings of the IEEE Computational Systems Bioinformatics Conference (ICSB)] on one dataset. Developed with the standard message-passing library, MPI, the program can be recompiled and run on any MIMD systems.

Perspective: Teaching evolution in higher education

In the past decade, the academic community has increased considerably its activity concerning the teaching and learning of evolution. Despite such beneficial activity, the state of public understanding of evolution is considered woefully lacking by most researchers and educators. This lack of understanding affects evolution/science literacy, research, and academia in general. Not only does the general public lack an understanding of evolution but so does a considerable proportion of college graduates. However, it is not just evolutionary concepts that students do not retain. In general, college students retain little of what they supposedly have learned. Worse yet, it is not just students who have avoided science and math who fail to retain fundamental science concepts. Students who have had extensive secondary-level and college courses in science have similar deficits. We examine these issues and explore what distinguishes effective pedagogy from ineffective pedagogy in higher education in general and evolution education in particular. The fundamental problem of students' prior conceptions is considered and why prior conceptions often underpin students' misunderstanding of the evolutionary concepts being taught. These conceptions can often be discovered and addressed. We also attend to concerns about coverage of course content and the influence of religious beliefs, and provide helpful strategies to improve college-level teaching of evolution.