Evolutionary Spectrum Research Articles

An expanding universe of mutational signatures and its rapid evolution in single-stranded RNA viruses.

The study of mutational processes in somatic genomes has gained recent momentum, uncovering a wide array of endogenous and exogenous factors associated with somatic changes. However, the overall landscape of mutational processes in germline mutations across the tree of life and associated evolutionary driving forces are rather unclear. In this study, we analyzed mutational processes in single-stranded RNA (ssRNA) viruses which are known to jump between different hosts with divergent exogenous environments. We found that mutational spectra in different ssRNA viruses differ significantly and are mainly associated with their genetic divergence. Surprisingly, host environments contribute much less significantly to the mutational spectrum, challenging the prevailing view that exogenous cellular environment is a major determinant of the mutational spectrum in viruses. To dissect the evolutionary forces shaping viral spectra, we selected two important scenarios, namely the inter-host evolution between different viral strains as well as the intra-host evolution. In both scenarios, we found mutational spectra change significantly through space and time, strongly correlating with levels of natural selection. Combining the mutations across all ssRNA viruses, we identified a suite of mutational signatures with varying degrees of similarity to somatic signatures in humans, indicating universal and divergent mutational processes across the tree of life. Taken together, we unraveled an unprecedented dynamic landscape of mutational processes in ssRNA viruses, pinpointing important evolutionary forces shaping fast evolution of mutational spectra in different species.

Evolutionary analysis of genes associated with the sense of balance in semi-aquatic mammals

BackgroundSemi-aquatic mammals represent a transitional phase in the evolutionary spectrum between terrestrial and aquatic mammals. The sense of balance is crucial for mammalian locomotion, and in semi-aquatic mammals, the structural foundation of this sense (the vestibular system) shows distinct morphological adaptations to both aquatic and terrestrial environments compared to their terrestrial counterparts. Despite this, the precise molecular mechanisms driving these adaptations remain elusive. Our study endeavors to unravel the genetic components associated with the sense of balance in semi-aquatic mammals and to examine the evolutionary trajectories of these genes, shed light on the molecular mechanisms underlying the adaptive evolution of balance perception in semi-aquatic mammals.ResultsWe selected 42 mammal species across 20 orders, 38 families, and 42 genera for analysis. We analyzed a comprehensive set of 116 genes related to the vestibular system's development or function. Our findings indicate that 27 of these genes likely experienced adaptive evolution in semi-aquatic mammals. Particularly, genes such as SLC26A2, SOX10, MYCN, and OTX1 are implicated in collectively orchestrating morphological adaptations in the semicircular canals to suit semi-aquatic environments. Additionally, genes associated with otolith development, including SLC26A2, OC90, and OTOP1, likely regulate otolith sensitivity across various locomotor modes. Moreover, genes linked to vestibular disorders, such as GJB2, GJB6, and USH1C, may provide a molecular foundation for averting vertigo amidst intricate locomotor scenarios in semi-aquatic mammals.ConclusionsOur research offers insights into the molecular mechanisms underlying the evolution of the sense of balance in semi-aquatic mammals, while also providing a new research direction for the adaptive evolution of mammals undergoing a secondary transition to an aquatic lifestyle.

Functional characterization of optic photoreception in Lymnaea stagnalis.

Optic photoreception is a critical function for animal survival. Across the evolutionary spectrum, diverse animal models have been used to investigate visual system function and potential mechanisms under physiological or pathophysiological states. However less is known on photoreceptive behaviors and retinal processing in invertebrates, especially molluscs. This study focuses on the freshwater pond snail, Lymnaea stagnalis (L. stagnalis), to explore its visual function and underlying mechanisms. Using anatomical and histological approaches we characterized the L. stagnalis eye structure and demonstrated structural connections and retinal rhodopsin-positive sensory cells potentially critical for phototransduction. To assess the snail phototactic responses, we developed a new neurobehavioral protocol and employed DeepLabCut to track and quantify animal locomotion. We demonstrated that L. stagnalis exhibits a positive locomotory response to intense focal light and has diverse photo-locomotory responses. Further, we conducted phylogenetic and protein structure analyses and demonstrated that L. stagnalis has a unique repertoire of both vertebrate and invertebrate phototransduction genes. Further characterization of a rhodopsin-like gene identified unique characteristics compared to other mollusks and vertebrates, suggesting different mechanisms of phototransduction. Taken together, our work establishes L. stagnalis as a model organism for studying optic photoreception, offering new insights into the evolution and diversity of visual function across animal species.

Comparison of the Distribution Patterns of Microsatellites Across the Genomes of Reptiles.

Microsatellites or simple sequence repeats (SSRs) are prevalent across various organisms' genomes. However, their distribution patterns and evolutionary dynamics in reptile genomes are rarely studied systematically. We herein conducted a comprehensive analysis of SSRs in the genomes of 36 reptile species. Our findings revealed that the total number of SSRs ranged from 1,840,965 to 7,664,452, accounting for 2.16%-8.19% of the genomes analyzed. The relative density ranged from 21,567.82 to 81,889.41 bp per megabase (Mbp). The abundance of different SSR categories followed the pattern of imperfect SSR (I-SSR) > perfect SSR (P-SSR) > compound SSR (C-SSR). A significant positive correlation was observed between the number of SSRs and genome size (p = 0.0034), whereas SSR frequency (p = 0.013) or density (p = 0.0099) showed a negative correlation with genome size. Furthermore, no correlation was found between SSR length and genome size. Mononucleotide repeats were the most common P-SSRs in crocodilians and turtles, whereas mononucleotides, trinucleotides, or tetranucleotides were the most common P-SSRs in snakes, lizards, and tuatara. P-SSRs of varying motif sizes showed nonrandom distribution across different genic regions, with AT-rich repeats being predominant. The genomic SSR content of the squamate lineage ranked the highest in abundance and variability, whereas crocodilians and turtles showed a slowly evolving and reduced microsatellite landscape. Gene ontology enrichment and Kyoto Encyclopedia of Genes and Genomes pathway analyses indicated that genes harboring P-SSRs in the coding DNA sequence regions were primarily involved in the regulation of transcription and translation processes. The SSR dataset generated in this study provides potential candidates for functional analysis and calls for broader-scale analyses across the evolutionary spectrum.

Spectral incremental dynamic methodology for nonlinear structural systems endowed with fractional derivative elements subjected to fully non-stationary stochastic excitation

A novel spectral incremental dynamic analysis methodology for analysing structural response in nonlinear systems with fractional derivative elements is presented, aligning with modern seismic design codes, like Eurocode 8. Drawing inspiration from the concept of fully non-stationary stochastic processes, the vector of the imposed seismic excitations is characterised by time and frequency evolving power spectra stochastically compatible with elastic response spectra of specified damping ratio and ground acceleration. The proposed method efficiently determines the nonlinear system time-dependent probability density functions for the non-stationary system response amplitude by employing potent nonlinear stochastic dynamics concepts, such as stochastic averaging and statistical linearisation. Unlike traditional incremental dynamic analysis curves found in the literature, the herein proposed method introduces a three-dimensional alternative counterpart, that of stochastic engineering demand parameter surfaces, providing with higher-order statistics of the system response. An additional noteworthy aspect involves the derivation of response evolutionary power spectra as function of spectral acceleration, offering a deeper insight into the underlying system dynamics. Besides its capabilities, the method maintains the coveted element of a particularly low associated computational cost, increasing its attractiveness and practicality among diverse applications of engineering interest. Numerical examples comprising the bilinear hysteretic model endowed with fractional derivative elements subject to an Eurocode 8 elastic design spectrum demonstrate the capabilities and reliability of the proposed methodology. Its accuracy is assessed by juxtaposing the derived results with germane Monte Carlo Simulation data.

Highly parallelized laboratory evolution of wine yeasts for enhanced metabolic phenotypes

Adaptive Laboratory Evolution (ALE) of microorganisms can improve the efficiency of sustainable industrial processes important to the global economy. However, stochasticity and genetic background effects often lead to suboptimal outcomes during laboratory evolution. Here we report an ALE platform to circumvent these shortcomings through parallelized clonal evolution at an unprecedented scale. Using this platform, we evolved 104 yeast populations in parallel from many strains for eight desired wine fermentation-related traits. Expansions of both ALE replicates and lineage numbers broadened the evolutionary search spectrum leading to improved wine yeasts unencumbered by unwanted side effects. At the genomic level, evolutionary gains in metabolic characteristics often coincided with distinct chromosome amplifications and the emergence of side-effect syndromes that were characteristic of each selection niche. Several high-performing ALE strains exhibited desired wine fermentation kinetics when tested in larger liquid cultures, supporting their suitability for application. More broadly, our high-throughput ALE platform opens opportunities for rapid optimization of microbes which otherwise could take many years to accomplish.

Survival probability surfaces of hysteretic fractional order structures exposed to non-stationary code-compliant stochastic seismic excitation

A novel first-passage probability stochastic incremental dynamics analysis (SIDA) methodology tailored for hysteretic fractional order structural systems under a fully non-stationary seismic excitation vector consistently designated with contemporary aseismic codes provisions (e.g., Eurocode 8) is developed. Specifically, the vector of the imposed seismic excitations is characterised by evolutionary power spectra that stochastically align with aseismic codes elastic response acceleration spectra, defined for specified modal damping ratios and scaled ground accelerations. Leveraging the concepts of stochastic averaging and statistical linearization, the approximative non-stationary response displacement joint probability density function (PDF) is derived, retaining the particularly coveted attribute of computational efficacy. Subsequently, the coupling with the survival probability model allows for the efficient determination of the response first-passage time probability density surfaces and the survival probability surfaces across various limit-state rules and scalable intensity measures. The first-passage time probability serves as a robust engineering demand parameter, effectively monitoring structural behaviour by considering both intensity and timing information, while inherently aligned with pertinent limit-state requirements. Notably, the associated low computational cost and the ability to handle a wide range of complex nonlinear/hysteretic structural behaviours, coupled with its compliance with modern aseismic codes, underscore its potential for applications in the fields of structural and earthquake engineering. A nonlinear system endowed with fractional derivative elements is used to exemplify the method’s reliability. The accuracy of the proposed method is validated in a Monte Carlo-based context, conducting nonlinear response time–history analyses with an extensive ensemble of accelerograms compatible with Eurocode 8 response acceleration spectra.

Nonstationary response statistics of structures with hysteretic damping to evolutionary stochastic excitation

The damping of a structure has often been modeled as linear hysteretic damping (LHD), so its corresponding equation of motion (EOM) is an integro-differential equation that involves the Hilbert transform of response displacement. As a result, the system is non-causal in nature, and it is challenging to compute its nonstationary response statistics under evolutionary stochastic excitation. This article develops an efficient solution method to obtain closed-form solutions for various nonstationary response statistics, including the evolutionary power spectrum (EPS), correlation function and mean square values. The novel solution method utilizes the concept of causalization time to introduce a “causalized” impulse response function (IRF), by which causal response statistics are computed based on a pole-residue approach. This approach requires obtaining a pole-residue form of the transfer function (TF) from the frequency response function (FRF) of the system, which is readily obtained from the EOM. Subsequently, the desired response statistics are obtained by shifting the causal response statistics back to the original time. To obtain the pole-residue form of the TF, two steps are necessary: (1) taking the inverse Fourier transform of the FRF of the oscillator to obtain a discrete IRF and (2) using the Prony-SS method to decompose this discrete IRF to obtain the pole residues associated with the TF. The correctness of the proposed method is numerically verified by Monte Carlo simulations through examples of hysteretic damping and mixed viscous-hysteretic damping oscillators that are subjected to white noise, modulated white noise and modulated Kanai–Tajimi model random excitations.

Nonstationary random vibration analysis of hysteretic systems with fractional derivatives by FFT-based frequency domain method

Nonstationary random vibration problems of nonlinear fractional systems are challenging and drawing increasing attention. This study presents an efficient numerical method for the random vibration analysis of large-scale nonlinear fractional systems subjected to fully nonstationary excitations. Firstly, the fast Fourier transform (FFT)-based frequency domain method originally proposed for the nonstationary random vibration analysis of linear integer-order systems is extended to linear fractional systems, in which the explicit expression of dynamic responses of fractional systems is derived based on the load superposition principle and Newmark method. Secondly, an equivalent linearization analysis framework is constructed to solve the nonstationary responses of hysteretic systems with fractional derivatives, in which the nonstationary response analyses of equivalent linear systems are accomplished by the FFT-based frequency domain method. The presented method can account for nonstationary excitations with arbitrary forms of evolutionary power spectrum, even of the non-separable one. Two numerical examples are used to confirm its superior performance in terms of accuracy and computational efficiency.

(Re)conceptualizing Sex and Gender in Physical Education Through Social Role Theory

ABSTRACT The line between gender and sex has become increasingly muddled in literature. Tensions surrounding this topic are ever-increasing and definitions of the two are rarely consistent. For improving conceptual clarity, we adopted the Social Role Theory to explore how these two terms differ and relate by laying out a cyclical framework of biological, sociological, and psychological components. Herein, we discuss the origins of the binary sex construct, anatomical brain/cognition differences, and sex/gender role implications for education and physical education. We confront the topic in a content area that continues to be masculine-oriented with the purpose to conceptualize sex/gender in physical education research through clarifying the evolutionary biosocial spectrum. Offering a reconceptualization of gender as a multidimensional construct could inspire further curricular reform for the content to be more inclusive of all participants, learnable by all students regardless of sex and gender, and beneficial both mentally and physically to all learners.

Dimension-Reduction Representation of Multivariate Mainshock-Aftershock Ground Motions Based on Measured Records

ABSTRACT This study proposes an integrated dimension-reduction representation strategy for simulating multivariate mainshock-aftershock stochastic ground motions based on measured motion records. The strategy includes a parameter identification method for modeling evolutionary power spectrum density (EPSD) of mainshock-aftershocks, a coherence function describing the spectrum correlation between mainshock and aftershock, and the EPSD function matrix establishment for mainshock-aftershock field combining with complex spatial coherence function. Furthermore, the dimension-reduction representation for simulating the ground motions considering the sequence and spatial variability simultaneously is presented with merely two elementary random variables. Numerical results effectively demonstrate the accuracy, efficiency, and engineering applicability of the proposed method.

Monitoring the Wear Trends in Wind Turbines by Tracking Fourier Vibration Spectra and Density Based Support Vector Machines

To make wind power more competitive, it is necessary to reduce turbine downtime and reduce costs associated with wind turbine operation and maintenance (O&M). Incorporating machine learning in the development of condition-based predictive maintenance methodologies for wind turbines can enhance their efficiency and reliability. This paper presents a monitoring method that utilizes Density Based Support Vector Machines (DBSVM) and the evolutionary Fourier spectra of vibrations. This method allows for the smart monitoring of the function evolution of the turbine. A complex optimal function (FO) for 5-degree order has been developed that will be the boundary function of the DBSVM to be timely determined from the Fourier spectrum through the magnitude–frequency and place of the failure occurring in the wind turbine drivetrains. The trend of the failure was constructed with the maximal values of the optimal frequency function for both yesthe cases of the upwind and downwind parts of the gearbox.

Non-stationary buffeting responses of a twin-box girder suspension bridge with various evolutionary spectra

The effects of evolutionary wind spectra with different modulation functions on the nonstationary buffeting responses of suspension bridges are uncertain. After considering the nonlinear buffeting force of a twin-box girder, the buffeting responses of a cross-sea suspension bridge under four nonstationary wind speed models with two uniform modulation and two nonuniform modulation functions were investigated in this paper. Through the evolutionary spectral theory, the nonstationary wind speed models at the bridge site with four typical modulation functions were generated and then validated from the autocorrelation and power spectrum density. The results show that the mean and root-mean-square error (RMSE) values of vertical and horizontal wind speeds by using nonuniform modulation functions (NMF1 and NMF2) were much larger than those by using uniform modulation functions (uMF1 and uMF2). Moreover, most of the peak and RMSE values for the torsional and lateral displacement under the NMF1 are the largest, while the RMSE values of the vertical displacement without the modulation function are the largest. With the increase of the circular frequency γ or decrease of the initial phase θ in the cosine function of time-varying mean wind speeds, the RMS values in three displacement responses of the bridge deck become larger.

Behavioral indicators of heterogeneous subjective experience in animals across the phylogenetic spectrum: Implications for comparative animal phenomenology

This behavioral study was undertaken to provide empirical evidence in favor of or opposed to the notion that animals across a wide breadth of the animal kingdom have subjective (personal) experience that varies with their lifestyles, ecological constraints, or phylogeny. Twelve species representing two invertebrate phyla and six vertebrate classes were observed unobtrusively in 15-min episodes, during which three modes of behavior (volitional, interactive, and egocentric) were quantified according to the frequency, variety, and dynamism of each mode. Volitional behavior was the most prevalent and dynamic mode for nearly all species, largely without regard to phylogenetic position. Interactive behavior likewise varied inconsistently across the entire evolutionary spectrum. Egocentric behavior was concentrated among the avian and mammalian species, but evidence of it were observed in the invertebrate species as well. Diagrams of the matrix constructed from the three qualitative modes and three quantitative attributes for each mode provide a metaphorical representation of the unique experiential profile of each species. To the extent that these behavioral measures correlate with the nature of the animal's subjective experience, they support the growing view that phenomenology is heterogeneous, multimodal, and non-linear in extent across the animal kingdom.

Failure Probability and Economic Loss Assessment of a High-Rise Frame Structure under Synthetic Multi-Dimensional Long-Period Ground Motions

Multiple research studies and seismic data analyses have shown that multi-directional long-period ground motion affects crucial and intricate large-scale structures like oil storage containers, long-span bridges, and high-rise buildings. Seismic damage data show a 3–55% chance of long-period ground motion. To clarify, the chance of occurrence is 3% in hard soil and 83% in soft soil. Due of the above characteristics, the aseismic engineering field requires a realistic stochastic model that accounts for long-period multi-directional ground motion. A weighted average seismic amplification coefficient selected NGA database multi-directional long-period ground motion recordings for this study. Due to the significant low-frequency component in the long-period ground motion, this research uses empirical mode decomposition (EMD) to efficiently decompose it into a composite structure with high- and low-frequency components. Given the above, further investigation is needed on the evolutionary power spectrum density (EPSD) functions of high- and low-frequency components. Analyzing the recorded data will reveal these functions and their corresponding parameters. Proper orthogonal decomposition (POD) is needed to simulate samples of high- and low-frequency components in different directions. These samples can be combined to illustrate multi-directional long-period ground motion. Representative samples exhibit the seismic characteristics of long-period multi-directional ground motion, as shown by numerical examples. This proves the method’s engineering accuracy and usefulness. Moreover, this study used incremental dynamic analysis (IDA) to apply seismic vulnerability theory. This study investigated whether long-period ground motions in both x and multi-directional directions could enhance the seismic response of a high-rise frame structure. By using this method, a comprehensive seismic economic loss rate curve was created, making economic loss assessment clearer. This study shows that multi-directional impacts should be included when studying seismic events and calculating structure economic damages.

Modeling and Prediction of Nonstationary Ground Motions as Time–Frequency Images

Proper modeling of nonstationary characteristics of ground motions is critical in estimating the seismic performance of structures. The importance of ground motion nonstationarity is being increasingly recognized in seismic design codes and provisions. This paper develops a new method for predicting seismic ground motions in the joint time–frequency domain based on recorded ground motions. We treat wavelet energy maps of acceleration records as images and extract essential patterns from them using principal component analysis. These patterns are then linked to the seismic source, path, and site variables using general regression neural network. The resulting model predicts an image representing the expected evolutionary power spectrum conditioned on the input variables. An example application is presented using records from the Next Generation Attenuation of Ground Motions Database of the Pacific Earthquake Engineering Center. As opposed to conventional ground motion prediction models, the proposed approach retains the time domain characteristics of ground motions. The results show that the proposed model can predict significant patterns in the seismic energy distribution, acceleration time series, and 5% damped elastic spectral accelerations.

Phylogeny and molecular evolution of the first local monkeypox virus cluster in Guangdong Province, China

The first local mpox outbreak in Guangdong Province, China occurred in June 2023. However, epidemiological data have failed to quickly identify the source and transmission of the outbreak. Here, phylogeny and molecular evolution of 10 monkeypox virus (MPXV) genome sequences from the Guangdong outbreak were characterized, revealing local silent transmissions that may have occurred in Guangdong whose mpox outbreaks suggested a molecular epidemiological correlation with Portugal and several regions of China during the same period. The lineage IIb C.1, which includes all 10 MPXV from Guangdong, shows consistent temporal continuity in both phylogenetic characteristics and unique molecular evolutionary mutation spectrum, reflected in the continuous increase of single nucleotide polymorphisms (SNPs) and shared mutations over time. Compared with the Japan MPXV, the Guangdong MPXV showed higher genomic nucleotide differences and separated 14 shared mutations from the B.1 lineage, comprising 6 non-synonymous mutations in genes linked to host regulation, virus infection, and virus life cycle. The unique mutation spectrum with temporal continuity in IIb C.1, related to apolipoprotein B mRNA-editing catalytic polypeptide-like 3, promotes rapid viral evolution and diversification. The findings contribute to understanding the ongoing mpox outbreak in China and offer insights for developing joint prevention and control strategies.

Exploring frequency-domain nonstationary of seismic ground motions using evolutionary power spectrum and Archimedean Copula functions

In this paper, the frequency-domain nonstationarity of seismic ground motions is investigated using Archimedean Copula functions. To measure the nonstationarity of the ground motions, a group of nonstationarity indexes is introduced based on the evolutionary power spectral density. The values of the proposed nonstationarity indexes of 1034 seismic ground motion records are calculated and their distributions are obtained. The Gumbel, Clayton, and Frank Copula functions among the nonstationarity indexes and intensity measures of the ground motions are estimated from the Kendall rank correlation coefficients. The best-fit Copula functions are determined by minimizing these three estimated Copula functions and the empirical Copula function. The correlation among the nonstationarity indexes and intensity measures from the Copula functions indicates that the average frequency and bandwidth of the seismic ground motion tend to decrease with time increasing, and the ground motion with long duration tends to have remarkable low-frequency components. It is suggested that the nonstationarity of the ground motions may increase the seismic risk of civil engineering structures and could not be ignored in the structural design.

A conservation planning strategy applied to the evolutionary history of the mantellid frogs of Madagascar

Phylogenetic diversity is an increasingly applied metric used to maximize the representation of evolutionary history in spatial conservation planning. When following this approach, researchers commonly overlook sites with a relatively higher proportion of recently diverged endemic species, also known as centers of neo-endemism. Here we aim to demonstrate how targeting the conservation of different facets of diversity (taxonomic diversity, phylogenetic diversity and centers of endemism) can provide more cost-effective solutions to the conservation of the all evolutionary spectrum of biodiversity. We do so by using the mantellid frogs of Madagascar as a case study. Our results confirm that areas with high concentrations of neo-endemism can be effectively identified as conservation planning priorities only if we specifically target them. Neglecting areas that are poor in phylogenetic diversity may therefore compromise the maintenance of diversification processes, particularly when lesser proportions of the landscape are protected. This approach can be of particular interest to island ecosystems, since they often harbor unique and restricted evolutionary radiations.

Rphylopic: An R package for fetching, transforming, and visualising PhyloPic silhouettes

Abstract Effective data visualisation is vital for data exploration, analysis and communication in research. In ecology and evolutionary biology, data are often associated with various taxonomic entities. Graphics of organisms associated with these taxa are valuable for framing results within a broader biological context. However, acquiring and using such resources can be challenging due to availability and licensing constraints. The PhyloPic database solves many of these issues by making organism silhouettes freely available. Tools that integrate this database with existing research workflows are needed to remove hurdles associated with data visualisation in the biological sciences. Here, we introduce rphylopic, an R package for fetching, transforming and visualising silhouettes of organisms from the PhyloPic database. In addition to making over 8000 organism silhouettes available within the R programming language, rphylopic empowers users to modify the appearance of these silhouettes for ultimate customisability when coding production–quality visualisations in both base R and ggplot2 workflows. In this work, we provide details about how the package can be installed, its implementation and potential use cases. For the latter, we showcase three examples across the ecology and evolutionary biology spectrum. Our hope is that rphylopic will make it easier for biologists to develop more accessible and engaging data visualisations by making external resources readily accessible, customisable and usable within R. In turn, by integrating into existing workflows, rphylopic helps to ensure that science is reproducible and accessible.