Aneuploidy Can Be an Evolutionary Diversion on the Path to Adaptation.

Aneuploidy is common in eukaryotes, often leading to decreased fitness. However, evidence from fungi and human tumur cells suggests that specific aneuploidies can be beneficial under stressful conditions and facilitate adaptation. In a previous evolutionary experiment with yeast, populations evolving under heat stress became aneuploid, only to later revert to euploidy after beneficial mutations accumulated. It was therefore suggested that aneuploidy is a "stepping stone" on the path to adaptation. Here, we test this hypothesis. We use Bayesian inference to fit an evolutionary model with both aneuploidy and mutation to the experimental results. We then predict the genotype frequency dynamics during the experiment, demonstrating that most of the evolved euploid population likely did not descend from aneuploid cells, but rather from the euploid wild-type population. Our model shows how the beneficial mutation supply-the product of population size and beneficial mutation rate-determines the evolutionary dynamics: with low supply, much of the evolved population descends from aneuploid cells; but with high supply, beneficial mutations are generated fast enough to outcompete aneuploidy due to its inherent fitness cost. Our results suggest that despite its potential fitness benefits under stress, aneuploidy can be an evolutionary "diversion" rather than a "stepping stone": it can delay, rather than facilitate, the adaptation of the population, and cells that become aneuploid may leave less descendants compared to cells that remain diploid.

Limits to species' range: the tension between local and global adaptation.

We know that heritable variation is abundant, and that selection causes all but the smallest populations to rapidly shift beyond their original trait distribution. So then, what limits the range of a species? There are physical constraints and also population genetic limits to the effectiveness of selection, ultimately set by population size. Global adaptation, where the same genotype is favoured over the whole range, is most efficient when based on a multitude of weakly selected alleles and is effective even when local demes are small, provided that there is some gene flow. In contrast, local adaptation is sensitive to gene flow and may require alleles with substantial effect. How can populations combine the advantages of large effective size with the ability to specialise into local niches? To what extent does reproductive isolation help resolve this tension? I address these questions using eco-evolutionary models of polygenic adaptation, contrasting discrete demes with continuousspace.

Evolutionary emergence of alternative stable states in shallow lakes.

Ecosystems under stress may respond abruptly and irreversibly through tipping points. Although mechanisms leading to alternative stable states are much studied, little is known about how such ecosystems could have emerged in the first place. We investigate whether evolution by natural selection along resource gradients leads to bistability, using shallow lakes as an example. There, tipping points occur between two alternative states dominated by either submersed or floating macrophytes depending on nutrient loading. We model the evolution of macrophyte depth in the lake, identify the conditions under which the ancestor population diversifies and investigate whether alternative stable states dominated by different macrophyte phenotypes occur. We find that eco-evolutionary dynamics may lead to alternative stable states, but under restrictive conditions. Such dynamics require sufficient asymmetries in the acquisition of both light and nutrient. Our analysis suggests that competitive asymmetries along opposing resource gradients may allow bistability to emerge by natural selection.

Embeddability of centrosymmetric matrices capturing the double-helix structure in natural and synthetic DNA.

In this paper, we discuss the embedding problem for centrosymmetric matrices, which are higher order generalizations of the matrices occurring in strand symmetric models. These models capture the substitution symmetries arising from the double helix structure of the DNA. Deciding whether a transition matrix is embeddable or not enables us to know if the observed substitution probabilities are consistent with a homogeneous continuous time substitution model, such as the Kimura models, the Jukes-Cantor model or the general time-reversible model. On the other hand, the generalization to higher order matrices is motivated by the setting of synthetic biology, which works with different sizes of genetic alphabets.

Exclusive breastfeeding in African American women: A concept analysis.

AIM: To report an analysis of the concept of exclusive breastfeeding (EBF) in African American women. BACKGROUND: EBF is the gold standard for infant nutrition from birth until 6 months. The rate of EBF in United States is low-26%, with African American women having the lowest rates. The low rates of EBF in this population are strongly attributed to bias, racism and generational trauma. Therefore, clarifying the concept of EBF with respect to these factors is important for promoting EBF rates of this population. DESIGN: Concept analysis. DATA SOURCES: Search was conducted in four databases (CINAHL, PubMed, PsycINFO and Scopus) for articles published between 2001 and 2021. A total of 30 articles (20 quantitative, seven qualitative and three mixed methods) clarified the concept. Relevant literature emanated from diverse disciplines examining historical and present maternal and infant health. METHODS: Concept analysis using Rodger's evolutionary method. RESULTS: An operational definition of the concept of EBF in African American women was developed from the identified antecedents (modifiable and non-modifiable), defining attributes and consequences of the concept. Access to breastfeeding resources, maternal (prenatal intention to breastfeed, smoking status, attitude towards breastfeeding), infant (skin-to-skin care, successful latching and weight) and contextual factors (socioeconomic, occupational and cultural) predict EBF. The primary attributes of EBF were physiological, physical, psychological and relational. Consequences of EBF were positive health outcomes for, and increased bonding between, mother and infant. CONCLUSION: This concept analysis is the first identifying modifiable and non-modifiable antecedents of EBF. The analysis provides an operational definition for EBF in African American women which is useful to promote understanding of breastfeeding. This new concept examines the historic societal trauma associated with wet nursing and reframes breastfeeding as a positive maternal and infant health behaviour.

Contrast-FEL-A Test for Differences in Selective Pressures at Individual Sites among Clades and Sets of Branches.

A number of evolutionary hypotheses can be tested by comparing selective pressures among sets of branches in a phylogenetic tree. When the question of interest is to identify specific sites within genes that may be evolving differently, a common approach is to perform separate analyses on subsets of sequences and compare parameter estimates in a post hoc fashion. This approach is statistically suboptimal and not always applicable. Here, we develop a simple extension of a popular fixed effects likelihood method in the context of codon-based evolutionary phylogenetic maximum likelihood testing, Contrast-FEL. It is suitable for identifying individual alignment sites where any among the K≥2 sets of branches in a phylogenetic tree have detectably different ω ratios, indicative of different selective regimes. Using extensive simulations, we show that Contrast-FEL delivers good power, exceeding 90% for sufficiently large differences, while maintaining tight control over false positive rates, when the model is correctly specified. We conclude by applying Contrast-FEL to data from five previously published studies spanning a diverse range of organisms and focusing on different evolutionary questions.

An evolutionary perspective on stress responses, damage and repair.

Variation in stress responses has been investigated in relation to environmental factors, species ecology, life history and fitness. Moreover, mechanistic studies have unravelled molecular mechanisms of how acute and chronic stress responses cause physiological impacts ('damage'), and how this damage can be repaired. However, it is not yet understood how the fitness effects of damage and repair influence stress response evolution. Here we study the evolution of hormone levels as a function of stressor occurrence, damage and the efficiency of repair. We hypothesise that the evolution of stress responses depends on the fitness consequences of damage and the ability to repair that damage. To obtain some general insights, we model a simplified scenario in which an organism repeatedly encounters a stressor with a certain frequency and predictability (temporal autocorrelation). The organism can defend itself by mounting a stress response (elevated hormone level), but this causes damage that takes time to repair. We identify optimal strategies in this scenario and then investigate how those strategies respond to acute and chronic exposures to the stressor. We find that for higher repair rates, baseline and peak hormone levels are higher. This typically means that the organism experiences higher levels of damage, which it can afford because that damage is repaired more quickly, but for very high repair rates the damage does not build up. With increasing predictability of the stressor, stress responses are sustained for longer, because the animal expects the stressor to persist, and thus damage builds up. This can result in very high (and potentially fatal) levels of damage when organisms are exposed to chronic stressors to which they are not evolutionarily adapted. Overall, our results highlight that at least three factors need to be considered jointly to advance our understanding of how stress physiology has evolved: (i) temporal dynamics of stressor occurrence; (ii) relative mortality risk imposed by the stressor itself versus damage caused by the stress response; and (iii) the efficiency of repair mechanisms.

Predator-Prey Evolution from an Eco-evolutionary Trade-off Model: The Role of Trait Differentiation.

We develop a novel eco-evolutionary modelling framework and demonstrate its efficacy by simulating the evolution of trait distributions in predator and prey populations. The eco-evolutionary modelling framework assumes that population traits have beta distributions and defines canonical equations for the dynamics of each total population size, the population's average trait value, and a measure of the population's trait differentiation. The trait differentiation is included in the modelling framework as a phenotype analogue, Q, of Wright's fixation index [Formula: see text], which is inversely related to the sum of the beta distribution shape parameters. The canonical equations may be used as templates to describe the evolution of population trait distributions in many ecosystems that are subject to stabilising selection. The solutions of the "population model" are compared with those of a "phenotype model" that simulates the growth of each phenotype as it interacts with every other phenotype under the same trade-offs. The models assume no sources of new phenotypic variance, such as mutation or gene flow. We examine a predator-prey system in which each population trades off growth against mortality: the prey optimises devoting resources to growth or defence against predation; and the predator trades off increasing its attack rate against increased mortality. Computer solutions with stabilising selection reveal very close agreement between the phenotype and population model results, which both predict that evolution operates to stabilise an initially oscillatory system. The population model reduces the number of equations required to simulate the eco-evolutionary system by several orders of magnitude, without losing verisimilitude for the overarching population properties. The population model also allows insights into the properties of the system that are not available from the equivalent phenotype model.

The Shape of Phylogenies Under Phase-Type Distributed Times to Speciation and Extinction.

Phylogenetic trees describe relationships between extant species, but beyond that their shape and their relative branch lengths can provide information on broader evolutionary processes of speciation and extinction. However, currently many of the most widely used macro-evolutionary models make predictions about the shapes of phylogenetic trees that differ considerably from what is observed in empirical phylogenies. Here, we propose a flexible and biologically plausible macroevolutionary model for phylogenetic trees where times to speciation or extinction events are drawn from a Coxian phase-type (PH) distribution. First, we show that different choices of parameters in our model lead to a range of tree balances as measured by Aldous' [Formula: see text] statistic. In particular, we demonstrate that it is possible to find parameters that correspond well to empirical tree balance. Next, we provide a natural extension of the [Formula: see text] statistic to sets of trees. This extension produces less biased estimates of [Formula: see text] compared to using the median [Formula: see text] values from individual trees. Furthermore, we derive a likelihood expression for the probability of observing an edge-weighted tree under a model with speciation but no extinction. Finally, we illustrate the application of our model by performing both absolute and relative goodness-of-fit tests for two large empirical phylogenies (squamates and angiosperms) that compare models with Coxian PH distributed times to speciation with models that assume exponential or Weibull distributed waiting times. In our numerical analysis, we found that, in most cases, models assuming a Coxian PH distribution provided the best fit.

Synonymous Site-to-Site Substitution Rate Variation Dramatically Inflates False Positive Rates of Selection Analyses: Ignore at Your Own Peril.

Most molecular evolutionary studies of natural selection maintain the decades-old assumption that synonymous substitution rate variation (SRV) across sites within genes occurs at levels that are either nonexistent or negligible. However, numerous studies challenge this assumption from a biological perspective and show that SRV is comparable in magnitude to that of nonsynonymous substitution rate variation. We evaluated the impact of this assumption on methods for inferring selection at the molecular level by incorporating SRV into an existing method (BUSTED) for detecting signatures of episodic diversifying selection in genes. Using simulated data we found that failing to account for even moderate levels of SRV in selection testing is likely to produce intolerably high false positive rates. To evaluate the effect of the SRV assumption on actual inferences we compared results of tests with and without the assumption in an empirical analysis of over 13,000 Euteleostomi (bony vertebrate) gene alignments from the Selectome database. This exercise reveals that close to 50% of positive results (i.e., evidence for selection) in empirical analyses disappear when SRV is modeled as part of the statistical analysis and are thus candidates for being false positives. The results from this work add to a growing literature establishing that tests of selection are much more sensitive to certain model assumptions than previously believed.

A Bayesian Framework for Inferring the Influence of Sequence Context on Point Mutations.

The probability of point mutations is expected to be highly influenced by the flanking nucleotides that surround them, known as the sequence context. This phenomenon may be mainly attributed to the enzyme that modifies or mutates the genetic material, because most enzymes tend to have specific sequence contexts that dictate their activity. Here, we develop a statistical model that allows for the detection and evaluation of the effects of different sequence contexts on mutation rates from deep population sequencing data. This task is computationally challenging, as the complexity of the model increases exponentially as the context size increases. We established our novel Bayesian method based on sparse model selection methods, with the leading assumption that the number of actual sequence contexts that directly influence mutation rates is minuscule compared with the number of possible sequence contexts. We show that our method is highly accurate on simulated data using pentanucleotide contexts, even when accounting for noisy data. We next analyze empirical population sequencing data from polioviruses and HIV-1 and detect a significant enrichment in sequence contexts associated with deamination by the cellular deaminases ADAR 1/2 and APOBEC3G, respectively. In the current era, where next-generation sequencing data are highly abundant, our approach can be used on any population sequencing data to reveal context-dependent base alterations and may assist in the discovery of novel mutable sites or editing sites.

Increased risk of leukaemia in children with Down syndrome: a somatic evolutionary view.

Children show a higher incidence of leukaemia compared with young adolescents, yet their cells are less damaged because of their young age. Children with Down syndrome (DS) have an even higher risk of developing leukaemia during the first years of life. The presence of a constitutive trisomy of chromosome 21 (T21) in DS acts as a genetic driver for leukaemia development, however, additional oncogenic mutations are required. Therefore, T21 provides the opportunity to better understand leukaemogenesis in children. Here, we describe the increased risk of leukaemia in DS during childhood from a somatic evolutionary view. According to this idea, cancer is caused by a variation in inheritable phenotypes within cell populations that are subjected to selective forces within the tissue context. We propose a model in which the increased risk of leukaemia in DS children derives from higher rates of mutation accumulation, already present during fetal development, which is further enhanced by changes in selection dynamics within the fetal liver niche. This model could possibly be used to understand the rate-limiting steps of leukaemogenesis early in life.

Individual-based eco-evolutionary models for understanding adaptation in changing seas.

As climate change threatens species' persistence, predicting the potential for species to adapt to rapidly changing environments is imperative for the development of effective conservation strategies. Eco-evolutionary individual-based models (IBMs) can be useful tools for achieving this objective. We performed a literature review to identify studies that apply these tools in marine systems. Our survey suggested that this is an emerging area of research fuelled in part by developments in modelling frameworks that allow simulation of increasingly complex ecological, genetic and demographic processes. The studies we identified illustrate the promise of this approach and advance our understanding of the capacity for adaptation to outpace climate change. These studies also identify limitations of current models and opportunities for further development. We discuss three main topics that emerged across studies: (i) effects of genetic architecture and non-genetic responses on adaptive potential; (ii) capacity for gene flow to facilitate rapid adaptation; and (iii) impacts of multiple stressors on persistence. Finally, we demonstrate the approach using simple simulations and provide a framework for users to explore eco-evolutionary IBMs as tools for understanding adaptation in changing seas.

The eco-evolutionary modelling of populations and their traits using a measure of trait differentiation.

We develop new equations for the eco-evolutionary dynamics of populations and their traits. These equations resolve the change in the phenotypic differentiation within a population, which better estimates how the variance of the trait distribution changes. We note that traits may be bounded, assume they may be described by beta distributions with small variances, and develop a coupled ordinary differential equation system to describe the dynamics of the total population, the mean trait value, and a measure of phenotype differentiation. The variance of the trait in the population is calculated from its mean and the population's phenotype differentiation. We consider an example of two competing plant populations to demonstrate the efficacy of the new approach. Each population may trade-off its growth rate against its susceptibility to direct competition from the other population. We create two models of this system: a population model based on our new eco-evolutionary equations; and a phenotype model, in which the growth or demise of each fraction of each population with a defined phenotype is simulated as it interacts with a shared limiting resource and its competing phenotypes and populations. Comparison of four simulation scenarios reveals excellent agreement between the predicted quantities from both models: total populations, the average trait values, the trait variances, and the degree of phenotypic differentiation within each population. In each of the four scenarios simulated, three of which are initially subject to competitive exclusion in the absence of evolution, the populations adapt to coexist. One population maximises growth and dominates, while the other minimises competitive losses. These simulations suggest that our new eco-evolutionary equations may provide an excellent approximation to phenotype changes in populations.

Developing the Concept of Adverse Childhood Experiences: A Global Perspective.

BACKGROUND: The relationship between health and adverse childhood experiences (ACEs) has been a major topic in the field of healthcare. In recent years, the study ACEs and health has expanded internationally. PURPOSE: The purpose of this study was to further develop the concept of ACEs using a global perspective. METHOD: Rodgers' Evolutionary Model guided the study. PubMed, CINAHL, and PsychINFO databases were searched. A total of 39 publications were selected for review. FINDINGS: Development of the concept was achieved using a wide global lens. ACEs are influenced by diverse cultural, social, environmental, and economic factors that affect individuals' health worldwide. DISCUSSION: The developed ACEs concept described in this paper includes a global perspective, adding context to the existing definition, thus broadening its application, and expanding its usefulness in international research. A clear concept for ACEs is valuable to nurses who care for children, adolescents and young adults around the world, who have suffered from ACEs and seek health care.

Can an Investigation of a Single Gene be Effective in Differentiating Certain Features of the Bipolar Disorder Profile?

Bipolar disorder (BD) is amongst the most common heritable mental disorders, but the clarification of its genetic roots has proven to be very challenging. Many single nucleotide polymorphisms (SNPs) have been identified to be associated with BD. SNPs in the CACNA1C gene have emerged as the most significantly associated with the disease. The aim of the present study is to provide a concise description of SNP 1006737 variants identified by Real Time PCR and confirm sequencing analysis with the Sanger method in order to estimate the association with BD. The molecular method was tested on 47 Sardinian subjects of whom 23 were found to not be mutated, 1 was found to be a carrier of the homozygous A allele and 23 were found to be carriers of the heterozygous G allele. Moreover, the positive results of the preliminary application suggest that the development of the screener could be extended to the other 5 genetic variables identified as associated with BD.

Evolutionary model of protein secondary structure capable of revealing new biological relationships.

Ancestral sequence reconstruction has had recent success in decoding the origins and the determinants of complex protein functions. However, phylogenetic analyses of remote homologues must handle extreme amino acid sequence diversity resulting from extended periods of evolutionary change. We exploited the wealth of protein structures to develop an evolutionary model based on protein secondary structure. The approach follows the differences between discrete secondary structure states observed in modern proteins and those hypothesized in their immediate ancestors. We implemented maximum likelihood-based phylogenetic inference to reconstruct ancestral secondary structure. The predictive accuracy from the use of the evolutionary model surpasses that of comparative modeling and sequence-based prediction; the reconstruction extracts information not available from modern structures or the ancestral sequences alone. Based on a phylogenetic analysis of a sequence-diverse protein family, we showed that the model can highlight relationships that are evolutionarily rooted in structure and not evident in amino acid-based analysis.

Selection Shapes Synonymous Stop Codon Use in Mammals.

Phylogenetic models of the evolution of protein-coding sequences can provide insights into the selection pressures that have shaped them. In the application of these models synonymous nucleotide substitutions, which do not alter the encoded amino acid, are often assumed to have limited functional consequences and used as a proxy for the neutral rate of evolution. The ratio of nonsynonymous to synonymous substitution rates is then used to categorize the selective regime that applies to the protein (e.g., purifying selection, neutral evolution, diversifying selection). Here, we extend the Muse and Gaut model of codon evolution to explore the extent of purifying selection acting on substitutions between synonymous stop codons. Using a large collection of coding sequence alignments, we estimate that a high proportion (approximately 57%) of mammalian genes are affected by selection acting on stop codon preference. This proportion varies substantially by codon, with UGA stop codons far more likely to be conserved. Genes with evidence of selection acting on synonymous stop codons have distinctive characteristics, compared to unconserved genes with the same stop codon, including longer [Formula: see text] untranslated regions (UTRs) and shorter mRNA half-life. The coding regions of these genes are also much more likely to be under strong purifying selection pressure. Our results suggest that the preference for UGA stop codons found in many multicellular eukaryotes is selective rather than mutational in origin.

Trophic cascades alter eco-evolutionary dynamics and body size evolution.

Trait evolution in predator-prey systems can feed back to the dynamics of interacting species as well as cascade to impact the dynamics of indirectly linked species (eco-evolutionary trophic cascades; EETCs). A key mediator of trophic cascades is body mass, as it both strongly influences and evolves in response to predator-prey interactions. Here, we use Gillespie eco-evolutionary models to explore EETCs resulting from top predator loss and mediated by body mass evolution. Our four-trophic-level food chain model uses allometric scaling to link body mass to different functions (ecological pleiotropy) and is realistically parameterized from the FORAGE database to mimic the parameter space of a typical freshwater system. To track real-time changes in selective pressures, we also calculated fitness gradients for each trophic level. As predicted, top predator loss generated alternating shifts in abundance across trophic levels, and, depending on the nature and strength in changes to fitness gradients, also altered trajectories of body mass evolution. Although more distantly linked, changes in the abundance of top predators still affected the eco-evolutionary dynamics of the basal producers, in part because of their relatively short generation times. Overall, our results suggest that impacts on top predators can set off transient EETCs with the potential for widespread indirect impacts on food webs.

Alternative evolutionary outcomes following endosymbiont-mediated selection on male mating preference alleles.

In many arthropods, intracellular bacteria, such as those of the genus Wolbachia, may spread through host populations as a result of cytoplasmic incompatibility (CI). Here, there is sterility or reduced fertility in crosses between infected males and uninfected females. As the bacterium is maternally inherited, the reduced fertility of uninfected females increases the frequency of the infection. If the transmission fidelity of the bacterium is less than 100%, the bacterium cannot invade from a low frequency, but if its frequency exceeds a threshold, it increases to a high, stable, equilibrium frequency. We explore the expected evolutionary dynamics of mutant alleles that cause their male bearers to avoid mating with uninfected females. For alleles which create this avoidance behaviour conditional upon the male being infected, there is a wide zone of parameter space that allows the preference allele to drive Wolbachia from the population when it would otherwise stably persist. There is also a wide zone of parameter space that allows a joint stable equilibrium for the Wolbachia and a polymorphism for the preference allele. When the male's avoidance of uninfected females is unconditional, the preference allele's effect on Wolbachia frequency is reduced, but there is a narrow range of values for the transmission rate and CI fertility that allow an unconditional preference allele to drive Wolbachia from the population, in a process driven by positive linkage disequilibrium between Wolbachia and the preference allele. The possibility of the evolution of preference could hamper attempts to manipulate wild populations through Wolbachia introductions.