Factor In Evolution Research Articles

Natural genetic variation as a tool for discovery in Caenorhabditis nematodes.

Over the last 20 years, studies of Caenorhabditis elegans natural diversity have demonstrated the power of quantitative genetic approaches to reveal the evolutionary, ecological, and genetic factors that shape traits. These studies complement the use of the laboratory-adapted strain N2 and enable additional discoveries not possible using only one genetic background. In this chapter, we describe how to perform quantitative genetic studies in Caenorhabditis, with an emphasis on C. elegans. These approaches use correlations between genotype and phenotype across populations of genetically diverse individuals to discover the genetic causes of phenotypic variation. We present methods that use linkage, near-isogenic lines, association, and bulk-segregant mapping, and we describe the advantages and disadvantages of each approach. The power of C. elegans quantitative genetic mapping is best shown in the ability to connect phenotypic differences to specific genes and variants. We will present methods to narrow genomic regions to candidate genes and then tests to identify the gene or variant involved in a quantitative trait. The same features that make C. elegans a preeminent experimental model animal contribute to its exceptional value as a tool to understand natural phenotypic variation.

Determinants of diversity and composition of the tapeworm fauna of blue sharks, Prionace glauca: a geographical and host-specificity analysis.

Blue sharks, Prionace glauca, are cosmopolitan, extremely vagile sharks and the species among elasmobranchs for which most surveys containing tapeworm community data are available worldwide. In this study we report on the tapeworm fauna of three samples of blue sharks (n = 37) from two new regions (one sample from Galicia, north-east Atlantic, and two from Valencia, western Mediterranean), and compared it with previous studies, assessing the relative role of the ecological and evolutionary factors in structuring local tapeworm assemblages. Nine cestode taxa were identified, of which four included adult specimens, that is, Platybothrium auriculatum, Prosobothrium armigerum, Anthobothrium caseyi and Molicola horridus. The abundance of these species, and Brillouin's diversity index, differed significantly among samples without a clear geographical signal. A comparison with six previous surveys revealed that tapeworm assemblages were composed of the same 'core' taxa, with mean species richness typically ranging from two to four species. Global records of adult tapeworms in blue sharks included: 15 taxa identified at species level, of which only eight (generalist trypanorhynchs) were shared with other sympatric host species; five mostly with other carcharhinids; and three with large lamnid sharks sharing the blue sharks' habitat. The composition of tapeworm communities of blue sharks is thus highly constrained by strong host specificity, with composition and abundance varying across localities depending on idiosyncratic environmental conditions.

Evolutionary Algorithm Based Z-Source DC-DC Boost Converter for Charging EV Battery

In this paper, efficient charging of electric vehicle battery from a considered renewable solar photovoltaic source with the help of a modified Z source with efficient boosting topology. Adapting this Z-source converter to act as a voltage gainer with a boosting function allows a solar Photovoltaic (PV) input voltage of 25VDC (Volts Direct Current) to be increased to a designed output voltage of 75VDC at a low duty ratio, resulting in minimal switching loss. The closed-loop steady-state and transient parameters at the output were analyzed and compared using modern evolutionary algorithms. The power range upheld throughout the circuit is around (300–350) W. The battery is assumed to have an impedance model of Resistor-Capacitor (RC) load with a serial range of 12 V and 7 Ah. The proposed converter achieves higher conversion efficiency by the Maximum Power Pont Tracking (MPPT) and NSGA-II/MNSGA-II (non-dominated sorting genetic algorithm) based controller algorithm for tuning the optimal design value and is validated in a MATLAB Simulink platform. In this work, we analyze closed-loop systems under the mentioned power range. The MPPT with an algorithm-based controller tends to trigger the switch in the closed-loop system to get the optimized output. The Maximum Power Point (MPP) technique implemented is an incremental conductance method for extracting solar PV power and improving load performance. Consequently, the proposed evolutionary optimization algorithm steady-state ripple factor response of the proposed MNSGA-II has a lower output side, thus achieving around 98% of the controller implementation efficiency.

Relationship between body weight and elevation in Leadbeater’s possum (

The body size of mammals is influenced by several evolutionary, morphological, physiological and ecological factors. Studies of body size can provide insight into the processes underlying observed variation in patterns of mammal morphology. We sought to determine if body weight in Leadbeater’s possum (Gymnobelideus leadbeateri) is related to environmental variables and/or sex. Using linear regression modelling, we quantified the influence on body weight of broadscale geographic variables such as latitude and elevation, site-level indicators of forest productivity (forest type, slope, aspect and topographic wetness) and an individual-level variable (sex). We found that body weight was significantly associated with elevation and sex, with individuals being heavier at higher elevations and males (on average) being heavier than females. Monitoring body weight changes over time within particular forest types will be valuable, given the variations in temperature and resource productivity throughout the range of Leadbeater’s possum that are likely to arise from climate change.

Genetic Analysis of Plant Pathogens Natural Populations.

Population genetics allow to address fundamental questions about the biology of plant pathogens. By testing specific hypotheses, population genetics provide insights into the population genetic variability of pathogens across different geographical areas, time, and associated plant hosts, as well as on the structure and differentiation of populations, and on the possibility that a population is introduced and from where it has originated. In this chapter, basic concepts of population genetics are introduced, as well as the five evolutionary factors affecting populations, that is, mutations, recombination, variation in population size, gene flow, and natural selection. A step-by-step workflow, from sampling to data analysis, on how to perform a genetic analysis of natural populations of plant pathogens is discussed. Increased knowledge of the population biology of pathogens is pivotal to improve management strategies of diseases in agricultural and forest ecosystems.

Resistance to change: A case study on framing and policy change of a controversial nature area

Nature policies can be a major source of long-term debates, in which actors involved define problems differently and are unable to formulate (co-constructed) solutions. Especially issues about the well-being of animals raise heated debate among stakeholders. Though debates over nature policies often span longer periods, they are most likely dealt with on the short term. Policy makers will attempt to solve acute issues, which requires minimal political effort. However, these short-term solutions do not necessarily solve the issue as a whole. This paper analyzes conflicting frames about nature in the Dutch Oostervaardersplassen, and presents an analysis of how the different issues are debated, and framed, over a period of 23 years. Gaining in-depth insight into these frames shows linkages between media attention to issues and policy change. This research shows how diverse and unstable the debate has been over 23 years, by using Punctuated Equilibrium Theory to understand the policy process, and by analyzing the evolution of frames in the media with an Evolutionary Factor Analysis. With the combination of both Punctuated Equilibrium Theory and the Evolutionary Factor Analysis, we can relate issue framing to policy change. This shows that policy is adapted, following rising attention. However, at first the attempts for adaptation by policy makers will be minor, as stability is favored over change, until a certain threshold whereafter policy is changed radically. The article will provide more insight for stakeholders, scientists, and policy makers into the complexity of these kinds of wicked problems.

Sexual segregation of shell resource use by hermit crabs: Ecological and evolutionary factors

Sexual segregation of shell resource use by hermit crabs: Ecological and evolutionary factors

Role of Aryl Hydrocarbon Receptor Activation in Inflammatory Chronic Skin Diseases.

Aryl Hydrocarbon Receptor (AhR) is an evolutionary transcription factor which acts as a crucial sensor of different exogenous and endogenous molecules Recent data indicate that AhR is implicated in several physiological processes such as cell physiology, host defense, proliferation and differentiation of immune cells, and detoxification. Moreover, AhR involvement has been reported in the development and maintenance of several pathological conditions. In recent years, an increasing number of studies have accumulated highlighting the regulatory role of AhR in the physiology of the skin. However, there is evidence of both beneficial and harmful effects of AHR signaling. At present, most of the evidence concerns inflammatory skin diseases, in particular atopic dermatitis, psoriasis, acne, and hidradenitis suppurativa. This review exam-ines the role of AhR in skin homeostasis and the therapeutic implication of its pharmacological modulation in these cutaneous inflammatory diseases.

Working Memory for Spatial Sequences: Developmental and Evolutionary Factors in Encoding Ordinal and Relational Structures.

Sequence learning is a ubiquitous facet of human and animal cognition. Here, using a common sequence reproduction task, we investigated whether and how the ordinal and relational structures linking consecutive elements are acquired by human adults, children, and macaque monkeys. While children and monkeys exhibited significantly lower precision than adults for spatial location and temporal order information, only monkeys appeared to exceedingly focus on the first item. Most importantly, only humans, regardless of age, spontaneously extracted the spatial relations between consecutive items and used a chunking strategy to compress sequences in working memory. Monkeys did not detect such relational structures, even after extensive training. Monkey behavior was captured by a conjunctive coding model, whereas a chunk-based conjunctive model explained more variance in humans. These age- and species-related differences are indicative of developmental and evolutionary mechanisms of sequence encoding and may provide novel insights into the uniquely human cognitive capacities.SIGNIFICANCE STATEMENT Sequence learning, the ability to encode the order of discrete elements and their relationships presented within a sequence, is a ubiquitous facet of cognition among humans and animals. By exploring sequence-processing abilities at different human developmental stages and in nonhuman primates, we found that only humans, regardless of age, spontaneously extracted the spatial relations between consecutive items and used an internal language to compress sequences in working memory. The findings provided insights into understanding the origins of sequence capabilities in humans and how they evolve through development to identify the unique aspects of human cognitive capacity, which includes the comprehension, learning, and production of sequences, and perhaps, above all, language processing.

Necrotizing pneumonia due to Streptococcus pneumoniae in children during the period of non-systematic use of PCV13 in Catalonia, Spain

BackgroundSome studies have observed an increased incidence of necrotizing pneumonia (NP) in recent years. This might be related to the emergence of non-vaccine S. pneumoniae serotypes after PCV7 introduction although it is suggested that evolutionary factors may have modified the virulence and the interactions of pneumococci. The aim of this study was to clinically and microbiologically define NP in the population served by the three major paediatric hospitals in Barcelona (Catalonia, Spain). MethodsA prospective observational study was conducted in patients <18 years hospitalized due to invasive pneumococcal disease (January 2012–June 2016). Data of confirmed cases of pneumococcal NP (diagnosed by culture or DNA detection and serotyped) were collected. PCV13 was not systematically administered in Catalonia during the study period, but was available in the private market so the vaccination coverage in children increased from 48.2% to 74.5%. Results35 cases of NP were identified. 77.1% of cases were associated with empyema. In the first 4 years, a trend to a decrease in NP incidence was observed (p=0.021), especially in children <5 years (p=0.006). Serotype 3 was responsible for 48.6% of NP cases. Five patients with NP due to serotype 3 were fully vaccinated for their age with PCV13. ConclusionsSerotype 3 has a preeminent role in pneumococcal NP and was associated with all PCV13 vaccination failures. Although in our series the incidence does not seem to be increasing, evolution of pneumococcal NP rates should be monitored after inclusion of PCV13 in the systematic calendar.

Species boundaries in the messy middle-A genome-scale validation of species delimitation in a recently diverged lineage of coastal fog desert lichen fungi.

Species delimitation among closely related species is challenging because traditional phenotype‐based approaches, for example, using morphology, ecological, or chemical characteristics, may not coincide with natural groupings. With the advent of high‐throughput sequencing, it has become increasingly cost‐effective to acquire genome‐scale data which can resolve previously ambiguous species boundaries. As the availability of genome‐scale data has increased, numerous species delimitation analyses, such as BPP and SNAPP+Bayes factor delimitation (BFD*), have been developed to delimit species boundaries. However, even empirical molecular species delimitation approaches can be biased by confounding evolutionary factors, for example, hybridization/introgression and incomplete lineage sorting, and computational limitations. Here, we investigate species boundaries and the potential for micro‐endemism in a lineage of lichen‐forming fungi, Niebla Rundel & Bowler, in the family Ramalinaceae by analyzing single‐locus and genome‐scale data consisting of (a) single‐locus species delimitation analysis using ASAP, (b) maximum likelihood‐based phylogenetic tree inference, (c) genome‐scale species delimitation models, e.g., BPP and SNAPP+BFD, and (d) species validation using the genealogical divergence index (gdi). We specifically use these methods to cross‐validate results between genome‐scale and single‐locus datasets, differently sampled subsets of genomic data and to control for population‐level genetic divergence. Our species delimitation models tend to support more speciose groupings that were inconsistent with traditional taxonomy, supporting a hypothesis of micro‐endemism, which may include morphologically cryptic species. However, the models did not converge on robust, consistent species delimitations. While the results of our analysis are somewhat ambiguous in terms of species boundaries, they provide a valuable perspective on how to use these empirical species delimitation methods in a nonmodel system. This study thus highlights the challenges inherent in delimiting species, particularly in groups such as Niebla, with complex, relatively recent phylogeographic histories.

Methodology for isolation study as a factor of the evolutionary process for the university course «Theory of Evolution»

The development of the synthetic theory of evolution, which arose on the basis of the synthesis of Darwinism, genetics and ecology, was accompanied by the discovery of evolutionary factors that were unknown in the 19thcentury. The discovery of isolation made it possible to describe the mechanism of conservation of populations, species, as well as the process of speciation. The educational literature on the theory of evolution provides definitions of isolation, a classification of isolation forms, and the role of isolation in the evolutionary process. The study of isolation as a factor in evolution requires a development of a methodology for isolating mechanisms study. The achievement of this goal is associated with the choice of a variant of isolation definition as a factor of evolution. Methodologically successful is the definition of isolation, which describes the role of this factor at the initial stages of microevolution and leads to the emergence of new species and the preservation of their isolation. When formulating the definition of isolation, it is advisable to use terms such as population, species, gene flow and divergence. The isolating mechanisms are manifested in several forms, which necessitate their classification. The classification of E.Mayr (1974) makes it possible to describe the sequence, relationship and role in the evolution of the main forms of isolation when conducting classes. From the point of view of teaching methods, laboratory work is recommended when considering such forms of isolation as seasonal, biotopic and ethological forms. The implementation of the proposed methodology for isolation study as a factor in the evolutionary process while doing the university course Theory of Evolution makes it possible to increase the effectiveness of the assimilation of educational material by students.

A Hybrid Preaching Optimization Algorithm Based on Kapur Entropy for Multilevel Thresholding Color Image Segmentation.

Multilevel thresholding segmentation of color images plays an important role in many fields. The pivotal procedure of this technique is determining the specific threshold of the images. In this paper, a hybrid preaching optimization algorithm (HPOA) for color image segmentation is proposed. Firstly, the evolutionary state strategy is adopted to evaluate the evolutionary factors in each iteration. With the introduction of the evolutionary state, the proposed algorithm has more balanced exploration-exploitation compared with the original POA. Secondly, in order to prevent premature convergence, a randomly occurring time-delay is introduced into HPOA in a distributed manner. The expression of the time-delay is inspired by particle swarm optimization and reflects the history of previous personal optimum and global optimum. To better verify the effectiveness of the proposed method, eight well-known benchmark functions are employed to evaluate HPOA. In the interim, seven state-of-the-art algorithms are utilized to compare with HPOA in the terms of accuracy, convergence, and statistical analysis. On this basis, an excellent multilevel thresholding image segmentation method is proposed in this paper. Finally, to further illustrate the potential, experiments are respectively conducted on three different groups of Berkeley images. The quality of a segmented image is evaluated by an array of metrics including feature similarity index (FSIM), peak signal-to-noise ratio (PSNR), structural similarity index (SSIM), and Kapur entropy values. The experimental results reveal that the proposed method significantly outperforms other algorithms and has remarkable and promising performance for multilevel thresholding color image segmentation.

Modeling Community Evolution Characteristics of Dynamic Networks with Evolutionary Bayesian Nonnegative Matrix Factorization

In most cases, the block structures and evolution characteristics always coexist in dynamic networks. This leads to inaccurate results of temporal community structure analysis with a two-step strategy. Fortunately, a few approaches take the evolution characteristics into account for modeling temporal community structures. But the number of communities cannot be determined automatically. Therefore, a model, Evolutionary Bayesian Nonnegative Matrix Factorization (EvoBNMF), is proposed in this paper. It focuses on modeling the temporal community structures with evolution characteristics. More specifically, the evolution behavior, which is introduced into EvoBNMF, can quantify the transfer intensity of communities between adjacent snapshots for modeling the evolution characteristics. Innovatively, the most appropriate number of communities can be determined autonomously by shrinking the corresponding evolution behaviors. Experimental results show that our approach has superior performance on temporal community detection with the virtue of autonomous determination of the number of communities.

A theoretical composite model for population sex-specific shell size dynamics in Strombidae (Gastropoda, Neostromboidae)

ABSTRACT Modelling sexual dimorphism has important implications for understanding the evolution of size relationships among and within organisms. We present a composite model for the regulation and evolution of sex-specific inter-population shell size in a family of herbivorous marine molluscs, the Strombidae. In particular, this model postulates that gene flow acts as a size regulator that limits inter-population divergence by not allowing the mean size of each sex to deviate significantly between disparate populations. The mean shell size of individuals within populations is affected by the ecological setting in which the animal is growing. The model considers niche divergence as inconsequential in the regulation of sexual dimorphism, whereas environmental regulation for the mean size of a population is considered a significant driving factor. Sexual competition, where males may dislodge other males during copulation, is also considered a non-significant driver of male body size because of the open mating system. In such a system, smaller males can simply mate before larger males have matured. Selection for earlier mating in males so as to maximise lifetime fecundity favours male maturation at small body sizes. Conversely, greater fecundity at larger body size in females argues for larger females. The postulated composite model presented here fills a knowledge gap by graphically illustrating the factors affecting inter-and intra-specific variation. These differences include the modelling of mean inter-population shell size, as well as the regulation of intra-population sex size ratios. The components of this new model can be applied to a wider range of sexually dimorphic organisms to explain the evolutionary factors involved in regulating the observed sexual dimorphism.

Contribution of historical herbarium small RNAs to the reconstruction of a cassava mosaic geminivirus evolutionary history

Emerging viral diseases of plants are recognised as a growing threat to global food security. However, little is known about the evolutionary processes and ecological factors underlying the emergence and success of viruses that have caused past epidemics. With technological advances in the field of ancient genomics, it is now possible to sequence historical genomes to provide a better understanding of viral plant disease emergence and pathogen evolutionary history. In this context, herbarium specimens represent a valuable source of dated and preserved material. We report here the first historical genome of a crop pathogen DNA virus, a 90-year-old African cassava mosaic virus (ACMV), reconstructed from small RNA sequences bearing hallmarks of small interfering RNAs. Relative to tip-calibrated dating inferences using only modern data, those performed with the historical genome yielded both molecular evolution rate estimates that were significantly lower, and lineage divergence times that were significantly older. Crucially, divergence times estimated without the historical genome appeared in discordance with both historical disease reports and the existence of the historical genome itself. In conclusion, our study reports an updated time-frame for the history and evolution of ACMV and illustrates how the study of crop viral diseases could benefit from natural history collections.

Evolutionary Social Poisson Factorizationfor Temporal Recommendation

Preference-based recommendation systems analyze user-item interactions to reveal latent factors that explain our latent preferences for items and form personalized recommendations based on the behavior of others with similar tastes. Most of the works in the recommendation systems literature have been developed under the assumption that user preference is a static pattern, although user preferences and item attributes may be changed through time. To achieve this goal, we develop an Evolutionary Social Poisson Factorization (EPF_Social) model, a new Bayesian factorization model that can effectively model the smoothly drifting latent factors using Conjugate Gamma–Markov chains. Otherwise, EPF_Social can obtain the impact of friends on social network for user’ latent preferences. We studied our models with two large real-world datasets, and demonstrated that our model gives better predictive performance than state-of-the-art static factorization models.

Exploring the link between star and planet formation with Ariel

The goal of the Ariel space mission is to observe a large and diversified population of transiting planets around a range of host star types to collect information on their atmospheric composition. The planetary bulk and atmospheric compositions bear the marks of the way the planets formed: Ariel’s observations will therefore provide an unprecedented wealth of data to advance our understanding of planet formation in our Galaxy. A number of environmental and evolutionary factors, however, can affect the final atmospheric composition. Here we provide a concise overview of which factors and effects of the star and planet formation processes can shape the atmospheric compositions that will be observed by Ariel, and highlight how Ariel’s characteristics make this mission optimally suited to address this very complex problem.

Clinically Relevant Influenza Virus Evolution Reconstituted in a Human Lung Airway-on-a-Chip.

ABSTRACTHuman-to-human transmission of viruses, such as influenza viruses and coronaviruses, can promote virus evolution and the emergence of new strains with increased potential for creating pandemics. Clinical studies analyzing how a particular type of virus progressively evolves new traits, such as resistance to antiviral therapies, as a result of passing between different human hosts are difficult to carry out because of the complexity, scale, and cost of the challenge. Here, we demonstrate that spontaneous evolution of influenza A virus through both mutation and gene reassortment can be reconstituted in vitro by sequentially passaging infected mucus droplets between multiple human lung airway-on-a-chip microfluidic culture devices (airway chips). Modeling human-to-human transmission of influenza virus infection on chips in the continued presence of the antiviral drugs amantadine or oseltamivir led to the spontaneous emergence of clinically prevalent resistance mutations, and strains that were resistant to both drugs were identified when they were administered in combination. In contrast, we found that nafamostat, an inhibitor targeting host serine proteases, did not induce viral resistance. This human preclinical model may be useful for studying viral evolution in vitro and identifying potential influenza virus variants before they appear in human populations, thereby enabling preemptive design of new and more effective vaccines and therapeutics.IMPORTANCE The rapid evolution of viruses, such as influenza viruses and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is challenging the use and development of antivirals and vaccines. Studies of within-host viral evolution can contribute to our understanding of the evolutionary and epidemiological factors that shape viral global evolution as well as development of better antivirals and vaccines. However, little is known about how viral evolution of resistance to antivirals occurs clinically due to the lack of preclinical models that can faithfully model influenza infection in humans. Our study shows that influenza viral evolution through mutation or gene reassortment can be recapitulated in a human lung airway-on-a-chip (airway chip) microfluidic culture device that can faithfully recapitulate the influenza infection in vitro. This approach is useful for studying within-host viral evolution, evaluating viral drug resistance, and identifying potential influenza virus variants before they appear in human populations, thereby enabling the preemptive design of new and more effective vaccines and therapeutics.

Susceptibility to Neurodegenerative Disorders: Insights from Paleogenomic Data

abstract: Ancient human genome data accumulated in recent years can be employed to establish the spatiotemporal trajectories of genetic variants associated with human diseases. Such knowledge might illuminate if and how past adaptations impact contemporary human health and medicine. Scarcely any studies have yet attempted to evaluate genetic susceptibility to neurodegenerative disorders in ancient human communities. Using publicly available ancient human genome-wide data, this study evaluated the molecular predisposition to neurodegenerative disorders in ancient human communities. Ancient genome-wide data was screened for the presence of variants unequivocally associated with neuro-degenerative disorders in modern populations, identifying two rare variants in the LRRK2 gene associated with Mendelian Parkinson’s disease, a pathogenic variant in the CRH gene associated with an uncommon form of epilepsy, and a rare variant in the TREM2 gene that is a possible risk modifier associated with Alzheimer’s disease. Their historical and geographic prevalence was also assessed, indicating differing spatiotemporal frequency dynamics for these clinically significant variants. Neurodegenerative disorders often have poorly understood pathogenesis that might be elucidated by studying the interaction of past genetic variability with ecological and evolutionary factors such as adverse environmental conditions, specific selective pressures, periods of population isolation, and admixture processes. Data on molecular predisposition to neurodegenerative disorders in ancient genomes is instructive to modern medical diagnostic and therapeutic practices.