Natural Selection Research Articles

A new perspective on tumor progression: Evolution via selection for function.

Tumorigenesis is commonly attributed to Darwinian processes involving natural selection among cells and groups of cells. However, progressing tumors are those that also achieve an appropriate group phenotypic composition (GPC). Yet, the selective processes acting on tumor GPCs are distinct from that associated with classical Darwinian evolution (i.e. natural selection based on differential reproductive success) as tumors are not genuine evolutionary individuals and do not exhibit heritable variation in fitness. This complex evolutionary scenario is analogous to the recently proposed concept of 'selection for function' invoked for the evolution of both living and non-living systems. Therefore, we argue that it is inaccurate to assert that Darwinian processes alone account for all the aspects characterizing tumorigenesis and cancer progression; rather, by producing the genetic and phenotypic diversity required for creating novel GPCs, these processes fuel the evolutionary success of tumors that is dependent on selection for function at the tumor level.

Impact of silvicultural practices on the genetic variations between sugar maple (Acer saccharum Marsh.) stands in the Northern Forest, U.S.A

Tree harvesting practices that enhance genetic diversity are essential for the long-term sustainability of our forests. Using eSSRs, which are markers within expressed genes and thus, potentially subjected to natural selection and reveal adaptive potential, this study examines the effects of selection (SE) and shelterwood (SW) management systems using unmanaged (UM) stands as reference on the genetic diversity of sugar maples in the Northern Forest, USA. Comparison between management types shows no difference between SE and SW, but compared to UM, both have lower allelic richness (AR) while only SE has lower expected heterozygosity (HE). Size class comparison shows that seedlings have higher AR and HE than poles and mature trees. Two-way interactions between management types, size classes, and study stands from each of the four states that comprise the Northern Forest region (Maine, New Hampshire, Vermont and New York) were also examined. Results show that seedlings in UM and SW have higher AR compared to all size classes in SE and poles and mature trees in SW, while only seedlings from SW have higher HE compared to poles and mature trees in SE and SW. Only in Maine was there a difference in AR between SW and SE stands per state. Seedlings in New Hampshire and Maine have higher HE, as well as seedlings and mature trees in New York compared to the poles in New Hampshire and mature trees in Maine. Overall, the results indicate genetic erosion in sugar maple stands in the Northern Forest region. This genetic impact may be due to several factors including the intensity of cutting associated with SE and SW systems and size of the canopy gaps created. Higher seedling genetic diversity in SW compared to SE may be due to their more open stand structure that facilitates gene flow and seedling recruitment. When using SE, longer cutting cycle paired with lower level of residual basal area is recommended. This approach allows for a more open stand structure that could facilitate pollen and seed exchanges from the stands, improving their genetic diversity. In both SE and SW systems, leaving high-quality growing stocks will enhance their genetic diversity and ensure their sustainability. This study increases our awareness of the potential genetic impacts of forest harvesting practices and guides the development of recommendations to alleviate genetic erosion in sugar maple stands.

How to Experimentally Determine the Influence of the Weak Nuclear Force in Promoting Molecular Chirality via Heavy–Metal Promoted Autocatalytic Synthesis of Amino Acids

AbstractThe potential impact of the parity non‐conserving (PNC) weak nuclear interaction on the chirality of a nascent chiral carbon center has previously been examined in the context of evolutionary models for enantiomeric selectivity in the formation of natural amino acids and nucleic acids. Since the PNC effect is the only inherently handed property in nature, it is an obvious candidate to consider in those cases where there is a natural selectivity for a specific enantiomer, including the molecular building blocks of the molecules of life. Over geological timeframes, the potential impact of the PNC weak nuclear force on chiral preference appears feasible. Key requirements included an autocatalytic reaction cycle and involvement of metal‐ion catalysts. While prior studies offer no feasible path to experimentally test the hypothesis; the Z5‐dependence of the PNC interaction does suggest that catalysis by heavy elements could yield observable chiral preferences within an experimentally accessible timeframe. Calculations of the magnitude of the effect are presented for select heavy‐elements and it is shown that chiral preference could be observed within a time span of weeks to months when such metals are used to promote amino acid synthesis via an autocatalytic Strecker reaction.

Research on Multi-Parameter Optimization of Conical Roller Line Processing Technology Based on Satisfaction Function

In the process of conical roller line processing, there will be problems such as low precision of processing parameters, long processing time, low utilization rate of machine tools, high rejection rate, and high processing cost, which will lead to low production efficiency. In order to solve this problem, it is necessary to iteratively optimize the size parameters, including inner diameter, ovality, and taper. By obtaining the optimal parameter combination, the size parameters in the production process are kept consistent, that is, the accuracy and performance of the workpiece during the processing are guaranteed so as to avoid the problem of quality difference, improve the production efficiency and reduce the processing cost. In view of the fact that there are often some constraints on the accuracy and efficiency in the machining process of tapered roller lines, how to optimize the parameters affecting the accuracy and the parameters affecting the efficiency to achieve balance between accuracy and efficiency in order to better meet the needs of customers for multi-objective optimization of the machining process has become the focus of research. Based on the existing research, this paper explores the multi-parameter optimization modeling and application in the machining process of tapered roller lines by constructing a satisfaction function, and then uses a genetic algorithm to iteratively search for the optimal solution by simulating natural selection and the genetic mechanism. Based on Python software v3.12, the production process of tapered roller bearings is simulated. The AHP analytic hierarchy process and CRITIC weight method are used to redistribute the parameter weights respectively. After eight iterations, it is concluded that the weight value assigned by the AHP analytic hierarchy process makes the satisfaction function value reach the best value of 0.99795 and tend to converge stably. The optimized parameter configuration significantly improves the machining accuracy and production efficiency of the tapered roller line. The optimal parameter combination is obtained: inner diameter: 9.9982 mm, ovality: 0.7 mm, taper: 0.5 degrees, production efficiency: 101.0.97 piece/h. In order to verify the optimization effect, the single value (X) and moving extreme difference (Rs) control charts in the measurement value control chart are used to analyze and verify the tolerance values of important parameters in the processing technology of the tapered roller line. The results show that the data points are all within the control limit, indicating that the processing process is in a statistical control state.

Genetic history and biological adaptive landscape of the Tujia people inferred from shared haplotypes and alleles

BackgroundHigh-quality genomic datasets from under-representative populations are essential for population genetic analysis and medical relevance. Although the Tujia are the most populous ethnic minority in southwestern China, previous genetic studies have been fragmented and only partially reveal their genetic diversity landscape. The understanding of their fine-scale genetic structure and potentially differentiated biological adaptive features remains nascent.ObjectivesThis study aims to explore the demographic history and genetic architecture related to the natural selection of the Tujia people, focusing on a meta-Tujia population from the central regions of the Yangtze River Basin.ResultsPopulation genetic analyses conducted on the meta-Tujia people indicate that they occupy an intermediate position in the East Asian North-South genetic cline. A close genetic affinity was identified between the Tujia people and neighboring Sinitic-speaking populations. Admixture models suggest that the Tujia can be modeled as a mixture of northern and southern ancestries. Estimates of f3/f4 statistics confirmed the presence of ancestral links to ancient Yellow River Basin millet farmers and the BaBanQinCen-related groups. Furthermore, population-specific natural selection signatures were explored, revealing highly differentiated functional variants between the Tujia and southern indigenous populations, including genes associated with hair morphology (e.g., EDAR) and skin pigmentation (e.g., SLC24A5). Additionally, both shared and unique selection signatures were identified among ethnically diverse but geographically adjacent populations, highlighting their extensive admixture and the biological adaptations introduced by this admixture.ConclusionsThe study unveils significant population movements and genetic admixture among the Tujia and other ethno-linguistically diverse East Asian groups, elucidating the differentiated adaptation processes across geographically diverse populations from the current genetic landscape.

Osmolyte-Induced Modulation of Hofmeister Series.

Natural selection has driven the convergence toward a selected set of osmolytes, endowing them with the necessary efficiency to manage stress arising from salt diversity. This study combines atomistic simulations and experiments to investigate how two osmolytes, glycine and betaine, individually modulate the Hofmeister ion ordering of alkali metal salts (LiCl, KCl, and CsCl) near a charged silica interface. Both osmolytes are found to prevent salt-induced aggregation of the charged entities, yet their mode and degree of relative modulation depend on their intricate interplay with specific salt cations. Betaine's ion-mediated surface interaction maintains Hofmeister ion ordering, whereas glycine alters the relative Hofmeister order of the cation by salt-specific ion desorption from the surface. Experimental validation through surface-enhanced Raman spectroscopy supports these findings, elucidating osmolyte-mediated alterations in interfacial water structures. These observations based on an inorganic interface are reciprocated in amyloid beta 40 dimerization dynamics, highlighting osmolytes' efficacy in mitigating salt-induced aggregation. A molecular analysis suggests that the differential modes of interaction, as found here for glycine and betaine, are prevalent across classes of zwitterionic osmolytes.

Optical fibre based artificial compound eyes for direct static imaging and ultrafast motion detection

Natural selection has driven arthropods to evolve fantastic natural compound eyes (NCEs) with a unique anatomical structure, providing a promising blueprint for artificial compound eyes (ACEs) to achieve static and dynamic perceptions in complex environments. Specifically, each NCE utilises an array of ommatidia, the imaging units, distributed on a curved surface to enable abundant merits. This has inspired the development of many ACEs using various microlens arrays, but the reported ACEs have limited performances in static imaging and motion detection. Particularly, it is challenging to mimic the apposition modality to effectively transmit light rays collected by many microlenses on a curved surface to a flat imaging sensor chip while preserving their spatial relationships without interference. In this study, we integrate 271 lensed polymer optical fibres into a dome-like structure to faithfully mimic the structure of NCE. Our ACE has several parameters comparable to the NCEs: 271 ommatidia versus 272 for bark beetles, and 180o field of view (FOV) versus 150–180o FOV for most arthropods. In addition, our ACE outperforms the typical NCEs by ~100 times in dynamic response: 31.3 kHz versus 205 Hz for Glossina morsitans. Compared with other reported ACEs, our ACE enables real-time, 180o panoramic direct imaging and depth estimation within its nearly infinite depth of field. Moreover, our ACE can respond to an angular motion up to 5.6×106 deg/s with the ability to identify translation and rotation, making it suitable for applications to capture high-speed objects, such as surveillance, unmanned aerial/ground vehicles, and virtual reality.

How Big Is Big? The Effective Population Size of Marine Bacteria.

Genome-reduced bacteria constitute most of the cells in surface-ocean bacterioplankton communities. Their extremely large census population sizes (N c) have been unfoundedly translated to huge effective population sizes (N e)-the size of an ideal population carrying as much neutral genetic diversity as the actual population. As N e scales inversely with the strength of genetic drift, constraining the magnitude of N e is key to evaluating whether natural selection can overcome the power of genetic drift to drive evolutionary events. Determining the N e of extant species requires measuring the genomic mutation rate, a challenging step for most genome-reduced bacterioplankton lineages. Results for genome-reduced Prochlorococcus and CHUG are surprising-their N e values are an order of magnitude lower than those of less abundant lineages carrying large genomes, such as Ruegeria and Vibrio. As bacterioplankton genome reduction commonly occurred in the distant past, appreciating their population genetic mechanisms requires constraining their ancient N e values by other methods.

Genomic Signatures of Domestication in a Fungus Obligately Farmed by Leafcutter Ants.

The naturally selected fungal crop (Leucoagaricus gongylophorus) farmed by leafcutter ants shows striking parallels with artificially selected plant crops domesticated by humans (e.g., polyploidy, engorged nutritional rewards, dependence on cultivation). To date, poorly resolved L. gongylophorus genome assemblies based on short-read sequencing have constrained hypotheses about how millions of years under cultivation by ants shaped the fungal crop genome and potentially drove domestication. We use PacBio HiFi sequencing of L. gongylophorus from the leafcutter ant Atta colombica to identify 18 putatively novel biosynthetic gene clusters that likely cemented life as a cultivar (e.g., plant fragment degradation, ant-farmer communication, antimicrobial defense). Comparative analyses with cultivated and free-living fungi showed genomic signatures of stepwise domestication transitions: 1) free-living to ant-cultivated: loss of genes conferring stress response and detoxification, 2) hyphal food to engorged nutritional rewards: expansions of genes governing cellular homeostasis, carbohydrate metabolism, and siderophore biosynthesis, and 3) detrital provisioning to freshly cut plant fragments: gene expansions promoting cell wall biosynthesis, fatty acid metabolism, and DNA repair. Comparisons across L. gongylophorus fungi farmed by three leafcutter ant species highlight genomic signatures of exclusively vertical clonal propagation and widespread transposable element activity. These results show how natural selection can shape domesticated cultivar genomes towards long-term ecological resilience of farming systems that have thrived across millennia.

Vital Characteristics Cellular Neural Network (VCeNN) for Melanoma Lesion Segmentation: A Biologically Inspired Deep Learning Approach.

Cutaneous melanoma is a highly lethal form of cancer. Developing a medical image segmentation model capable of accurately delineating melanoma lesions with high robustness and generalization presents a formidable challenge. This study draws inspiration from cellular functional characteristics and natural selection, proposing a novel medical segmentation model named the vital characteristics cellular neural network. This model incorporates vital characteristics observed in multicellular organisms, including memory, adaptation, apoptosis, and division. Memory module enables the network to rapidly adapt to input data during the early stages of training, accelerating model convergence. Adaptation module allows neurons to select the appropriate activation function based on varying environmental conditions. Apoptosis module reduces the risk of overfitting by pruning neurons with low activation values. Division module enhances the network's learning capacity by duplicating neurons with high activation values. Experimental evaluations demonstrate the efficacy of this model in enhancing the performance of neural networks for medical image segmentation. The proposed method achieves outstanding results across numerous publicly available datasets, indicating its potential to contribute significantly to the field of medical image analysis and facilitating accurate and efficient segmentation of medical imagery. The proposed method achieves outstanding results across numerous publicly available datasets, with an F1 score of 0.901, Intersection over Union of 0.841, and Dice coefficient of 0.913, indicating its potential to contribute significantly to the field of medical image analysis and facilitating accurate and efficient segmentation of medical imagery.

Intelligent Asset Allocation Portfolio Division and Recommendation

With the continuous development of financial markets, intelligent asset allocation has become a topic of great concern in the investment field. However, traditional asset allocation methods often face difficulties in grasping the relationship between diversity, risk and return, which limits its application in complex market environments. To solve this problem, this study introduces deep learning and knowledge graphs and proposes an intelligent asset allocation model. Our model makes full use of the advantages of the Knowledge Graph Embedding Model (KGE), LSTM, and Genetic Algorithm (GA) to build a multi-level and multi-dimensional asset allocation model. KGE helps capture the complex relationships between different assets, LSTM is used to learn key patterns of historical portfolio performance, and GA finds the optimal asset allocation combination by simulating natural selection and genetic mechanisms. Experimental findings indicate that our model has demonstrated substantial improvements across various performance metrics and outperforms conventional approaches.

Pervasive findings of directional selection realize the promise of ancient DNA to elucidate human adaptation.

We present a method for detecting evidence of natural selection in ancient DNA time-series data that leverages an opportunity not utilized in previous scans: testing for a consistent trend in allele frequency change over time. By applying this to 8433 West Eurasians who lived over the past 14000 years and 6510 contemporary people, we find an order of magnitude more genome-wide significant signals than previous studies: 347 independent loci with >99% probability of selection. Previous work showed that classic hard sweeps driving advantageous mutations to fixation have been rare over the broad span of human evolution, but in the last ten millennia, many hundreds of alleles have been affected by strong directional selection. Discoveries include an increase from ∼0% to ∼20% in 4000 years for the major risk factor for celiac disease at HLA-DQB1 ; a rise from ∼0% to ∼8% in 6000 years of blood type B; and fluctuating selection at the TYK2 tuberculosis risk allele rising from ∼2% to ∼9% from ∼5500 to ∼3000 years ago before dropping to ∼3%. We identify instances of coordinated selection on alleles affecting the same trait, with the polygenic score today predictive of body fat percentage decreasing by around a standard deviation over ten millennia, consistent with the "Thrifty Gene" hypothesis that a genetic predisposition to store energy during food scarcity became disadvantageous after farming. We also identify selection for combinations of alleles that are today associated with lighter skin color, lower risk for schizophrenia and bipolar disease, slower health decline, and increased measures related to cognitive performance (scores on intelligence tests, household income, and years of schooling). These traits are measured in modern industrialized societies, so what phenotypes were adaptive in the past is unclear. We estimate selection coefficients at 9.9 million variants, enabling study of how Darwinian forces couple to allelic effects and shape the genetic architecture of complex traits.

Flower position within plants influences reproductive success both directly and via phenology.

In plants, within-individual trait variation might result from mechanisms related to ontogenetic contingency, i.e., to the position of a particular structure within the plant, previous developmental events, and/or the developmental environment. Flower position within inflorescences as well as inflorescence position within plants can influence resource provisioning, phenology, biotic interactions, and reproductive success. Despite the potential implications of within-individual variation in plant reproductive phenotypes, its causes and effects on reproductive success are still little explored. We assessed how reproductive success, in terms of fruit and seed set, and seed predation of 5883 flowers in Lathyrus vernus were influenced by their position within and among racemes, to what extent relationships between flower position and reproductive success and seed predation were mediated by phenology, and if positional effects on reproductive success depended on the external environment. In three years, basal flowers and racemes opened earlier and had higher fruit set than distal. Basal flowers also experienced higher seed predation. Differences among racemes in fruit and seed set were largely related to phenology, while differences in fruit set, seed set, and seed predation within racemes were not. In one year, differences in fruit set among flowers at different positions depended on flowering duration. Our results highlight the important role of ontogenetic contingency for within-individual variation in phenology and reproductive success. As the spatial distribution of reproductive structures affects both within-plant trait distributions and fitness, it is a likely target for natural selection.

PSIV-14 Short-term heat stress affects the plasma metabolome of Florida Cracker sheep

Abstract Florida Cracker sheep is a heritage sheep breed and an endangered species that was developed under natural selection in Florida, US. The objective of this study was to evaluate the effect of short-term heat stress on the plasma metabolome of Florida Cracker ewes (2 yr). A total of fourteen ewes were allocated to heat stress (HT, n = 7) or cooling (CTL, n = 7) conditions for 6 wk during the summer season. Treatment groups were grouped in covered concrete floor pens with similar dimensions and characteristics and had access to shelter, feed, and freshwater ad libitum. The HT pen was exposed to regular ambient temperatures, and for the cooling pen, an evaporative cooling fan was used. Data for ambient temperature and relative humidity of HT and CTL pens were recorded every week to estimate the temperature humidity index (THI). Blood samples were collected from each experimental ewe 1 wk before the start of the experiment (baseline) and at wk 1, 2, 3, 4, 5, and 6 post-treatment. Plasma was extracted from the blood and processed for targeted metabolomics. Targeted metabolomics was performed using Nuclear Magnetic Resonance spectroscopy to quantify a total of 50 metabolites, including organic acids, amino acids, hexoses, lipids, and carnitines. Statistical analysis for biomarker and pathway enrichment was performed using Metaboanalyst 5.0. The THI values for the HT and THI groups ranged from 81.3 to 89.5 and from 73.5 to 75.6, respectively. A total of 19 differentially abundant metabolites were identified between HT and CTL. The pathway enrichment analysis showed upregulation of fatty acid and primary bile biosynthesis, and glutathione, porphyrin, glycine, serine, and threonine metabolism (P ≤ 0.05) in HT compared with CTL sheep. These metabolic pathways could have a role in the response of the ewes to short-term HT. Our findings highlight that short-term HT alters the plasma metabolome of Florida Cracker ewes. Understanding these changes can contribute to the development of effective management strategies to mitigate the detrimental impact of HT on sheep operations in the Southern US.

PSX-16 The effect of short-term heat stress on physiological, hematological, and immunological parameters of Florida Cracker Sheep

Abstract Florida Cracker sheep are a heritage sheep breed that was developed under natural selection in Florida, US. The objective of this study was to evaluate the effect of short-term heat stress on rectal temperature, respiration rate, hematological parameters, and IgA concentrations of Florida Cracker ewes (2 yr of age). A total of fourteen ewes were allocated to heat stress (HT, n = 7) or cooling (CTL, n = 7) conditions for 6 wk during the summer season. Treatment groups were grouped in covered concrete floor pens with similar dimensions and characteristics and had access to shelter, feed, and freshwater ad libitum. The HT pen was exposed to regular ambient temperatures, and for the cooling pen, an evaporative cooling fan was used. Data for ambient temperature and relative humidity of HT and CTL pens were recorded every week to estimate the temperature humidity index (THI). Blood samples were collected from each experimental ewe 1 wk before the start of the experiment (baseline) and at wk 1, wk 2, wk 3, wk 4, wk 5, and wk 6 post-treatment. Blood samples were analyzed using a hematology analyzer (Vetscan HM5, Zoetis). Plasma was extracted from the blood and was used to evaluate IgA concentrations with a commercial kit. For the statistical analysis of the physiological, hematological, and immunological parameters, a mixed model with repeated measures was used. Fixed effects included treatment (HT or CTL), wk (1 to 6), and the treatment by week interaction. Animal was fitted as a random effect and the baseline data was used as a covariate. The THI for the HT and CTL groups ranged from 81.3 to 89.5 and from 73.5 to 75.6, respectively. The HT group presented a significant (P < 0.05) increase in respiratory rate when compared with the CTL group. No significant changes were observed for rectal temperature and IgA concentrations in the experimental groups. However, for wk 3, a significant (P < 0.05) increase of neutrophils and a decrease in lymphocyte % was observed for the HT group. In conclusion, short-term heat stress increased respiratory rate and neutrophil % and decreased the lymphocyte % in Florida Cracker ewes. It is possible that heat stress could have a detrimental impact on immune mechanisms in Florida Cracker ewes. Further studies are required to investigate the effects of long-term heat stress.

Self-Reproduction and Evolution in Cellular Automata: 25 Years After Evoloops.

The year 2024 marks the 25th anniversary of the publication of evoloops, an evolutionary variant of Chris Langton's self-reproducing loops, which proved constructively that Darwinian evolution of self-reproducing organisms by variation and natural selection is possible within deterministic cellular automata. Over the last few decades, this line of Artificial Life research has since undergone several important developments. Although it experienced a relative dormancy of activity for a while, the recent rise of interest in open-ended evolution and the success of continuous cellular automata models have brought researchers' attention back to how to make spatiotemporal patterns self-reproduce and evolve within spatially distributed computational media. This article provides a review of the relevant literature on this topic over the past 25 years and highlights the major accomplishments made so far, the challenges being faced, and promising future research directions.

Body Mass Gain in Wild Brown Capuchins (Sapajus apella) in Relation to Fruit Production and Social Dominance.

In ecological contexts natural selection might favor individuals with a larger body mass to monopolize resources; however, there is wide variation in body mass within populations and potential factors. In this study, we evaluated whether fruit production limits body mass in one group of Sapajus apella, its effects on behavior, and whether there is a relationship between social status and body mass. We recorded activity patterns using focal follows (20 min), body mass (using a modified Ohaus scale), and community wide fruit production estimates (from 60 fruit traps). Body mass remained relatively stable during periods of food scarcity, but in periods of abundance most individuals gained weight, as indicated by their relative growth rates (RGR). Subordinate subadults showed the highest RGR, as expected by their age. In periods of high fruit production activities as traveling, grooming, and playing were more frequent than during fruit scarcity, suggesting energy maximization and potential energetic constraints. We found differences in behavior within the group, as the alpha male was observed feeding more frequently (and for longer periods of time), was more aggressive (e.g., feeding trees), and received more grooming than other individuals. In addition, the alpha male was 60% heavier than the group's average body mass. Our study supports the hypothesis that body weight gain is related to fruit abundance and that body size is associated with social dominance; however, large individuals (both males and females) seem to incur in high metabolic or reproductive costs, as they do not gain much weight as smaller individuals.

Genomic compliance with Chargaff’s second parity rule may have originated non-adaptively, but stem-loops now function adaptively

Of Chargaff’s four rules on DNA base quantity, his second parity rule (PR-2) is the most contentious. Various biometricians (e.g., Sueoka, Lobry) regarded PR-2 compliance as a non-adaptive feature of modern genomes that could be modeled through interrelations among mutation rates. However, PR-2 compliance with stem-loop potential was considered adaptively relevant by biochemists familiar with analyses of nucleic acid structure (e.g., of Crick) and of meiotic recombination (e.g., of Kleckner). Meanwhile, other biometricians had shown that PR-2 complementarity extended beyond individual bases (1-mers) to oligonucleotides (k-mers), possibly reflecting “advantageous DNA structure” (Nussinov). An “introns early” hypothesis (Reanney, Forsdyke) had suggested a primordial nucleic acid world with recombination-mediated error-correction requiring genome-wide stem-loop potential to have evolved prior to localized intrusions of protein-encoding potential (exons). Thus, a primordial genome was equivalent to one long intron. Indeed, when assessed as the base order-dependent component (correcting for local influences of GC%), modern genes, especially when evolving rapidly under positive Darwinian selection, display high intronic stem-loop potential. This suggests forced migration from neighboring exons by competing protein-encoding potential. PR-2 compliance may have first arisen non-adaptively. Primary prototypic structures were later strengthened by their adaptive contribution to recombination. Thus, contentious views may actually be in harmony.

Sexual dimorphism and functional allometry in scorpions: A comparative study from a neotropical species

Sexual dimorphism (SD), the divergence of secondary sexual traits between males and females within a species, can arise from diverse evolutionary forces, such as natural selection, mate choice, and intrasexual competition. Allometric scaling patterns of dimorphic traits are related to their functional roles and the different selective pressures that affect each sex. Generally, traits that threaten rivals involved in intrasexual competition tend to exhibit the highest allometric slopes. Conversely, non-sexual traits often display isometric scaling, while genitalia and traits in direct contact between the sexes during courtship and copulation typically show hypoallometry. A good approach to study patterns of SD and allometry is to complement interspecific studies with analyzes of case studies, where the functional aspect is known in detail. Here, we review the occurrence of SD and evaluation of allometry in the Order Scorpiones, allowing us to compare general trends in a broader comparative framework within the group. In addition, we examined SD and allometric slopes of multiple traits (including somatic traits used in sexual and non-sexual interactions, as well as genitalia) in adult individuals of the scorpion Timogenes elegans (Scorpiones, Bothriuridae). We found that at an interspecific level there was a variation in SD between species and morphological traits, with most traits showing a male-biased SD, except for the chelicerae, which were found to be wider in females. Regarding SD studies, we found relatively few reports of functional allometry showing differences in allometric patterns between species. The results in T. elegans follow some of the general patterns found in other scorpions. We found hypoallometry in genital traits and hyperallometry in the pedipalps of both sexes, with steeper allometric slopes observed for pedipalp height in males. These results suggest that genital traits are under stabilizing selective pressure, while pedipalps in both sexes may be under natural and sexual selective pressure. Understanding allometric patterns and their relationship to function in scorpions provides significant insights into the evolutionary pressures driving the divergence of morphological traits used in both sexual and non-sexual contexts.

Evolution of evolvability in rapidly adapting populations.

Mutations can alter the short-term fitness of an organism, as well as the rates and benefits of future mutations. While numerous examples of these evolvability modifiers have been observed in rapidly adapting microbial populations, existing theory struggles to predict when they will be favoured by natural selection. Here we develop a mathematical framework for predicting the fates of genetic variants that modify the rates and benefits of future mutations in linked genomic regions. We derive analytical expressions showing how the fixation probabilities of these variants depend on the size of the population and the diversity of competing mutations. We find that competition between linked mutations can dramatically enhance selection for modifiers that increase the benefits of future mutations, even when they impose a strong direct cost on fitness. However, we also find that modest direct benefits can be sufficient to drive evolutionary dead ends to fixation. Our results suggest that subtle differences in evolvability could play an important role in shaping the long-term success of genetic variants in rapidly evolving microbial populations.