Evolution Of Population Research Articles

Binary black hole mergers from Population III star clusters

Binary black holes (BBHs) that are born from the evolution of Population III (Pop. III) stars are one of the main high-redshift targets for next-generation ground-based gravitational-wave (GW) detectors. Their predicted initial mass function and lack of metals make them the ideal progenitors of black holes above the upper edge of the pair-instability mass gap, that is, with a mass higher than ~134 (241) M⊙ for stars that become (or do not become) chemically homogeneous during their evolution. We investigate the effects of cluster dynamics on the mass function of BBHs that are born from Pop. III stars by considering the main uncertainties on the mass function of Pop. III stars, the orbital properties of the binary systems, the star cluster mass, and the disruption time. In our dynamical models, at least ~5% and up to 100% BBH mergers in Pop. III star clusters have a primary mass m1 above the upper edge of the pair-instability mass gap. In contrast, only ≲3% isolated BBH mergers have a primary mass above the gap, unless their progenitors evolved as chemically homogeneous stars. The lack of systems with a primary and/or secondary mass inside the gap defines a zone of avoidance with sharp boundaries in the plane of the primary mass-mass ratio. Finally, we estimate the merger rate density of BBHs. In the most optimistic case, we find a maximum of ℛ ~ 200 Gpc-3 yr-1 at ɀ ~ 15 for BBHs that formed via dynamical capture. For comparison, the merger rate density of isolated Pop. III BBHs is ℛ ≤ 10 Gpc−3 yr−1 for the same model of Pop. III star formation history.

Population Size in Evolutionary Biology Is More Than the Effective Size.

In population genetics idealized Wright-Fisher (WF) populations are generally considered equivalent to real populations with regard to the major evolutionary processes that influence genotype and allele frequencies. As a result we often model the response of populations by focusing on the effective size N e . The Diversity Partitioning Theorem (DPT) shows that you cannot model the behavior of a system solely on the basis of a diversity (accounting for unevenness among items) without taking richness into account. I show that the census population size (the number of adults, N c ) is equivalent to a richness, and that the effective size N e is equivalent to a true diversity. It follows logically from the DPT that we require both N e and N c to understand how drift, selection, mutation, and gene flow interact to shape the course of evolution of populations. Here I review evidence that both N c and N e affect evolutionary trajectories of populations for neutral and adaptive processes. This also influences how we should consider evolutionary potential and genetic criteria for conservation of populations. The effective size of a population is of huge importance in evolutionary biology, but it should not be the sole focus when population size is concerned. Applied evolutionary studies need to integrate N c in the equation more consistently when modeling the response to selection, mutation, migration, and drift.

Effects of group size and noise on cooperation in population evolution of dynamic groups

Effects of group size and noise on cooperation in population evolution of dynamic groups

Evolutionary origin and population diversity of a cryptic hybrid pathogen

Cryptic fungal pathogens pose disease management challenges due to their morphological resemblance to known pathogens. Here, we investigated the genomes and phenotypes of 53 globally distributed isolates of Aspergillus section Nidulantes fungi and found 30 clinical isolates—including four isolated from COVID-19 patients—were A. latus, a cryptic pathogen that originated via allodiploid hybridization. Notably, all A. latus isolates were misidentified. A. latus hybrids likely originated via a single hybridization event during the Miocene and harbor substantial genetic diversity. Transcriptome profiling of a clinical isolate revealed that both parental subgenomes are actively expressed and respond to environmental stimuli. Characterizing infection-relevant traits—such as drug resistance and growth under oxidative stress—revealed distinct phenotypic profiles among A. latus hybrids compared to parental and closely related species. Moreover, we identified four features that could aid A. latus taxonomic identification. Together, these findings deepen our understanding of the origin of cryptic pathogens.

Genomic analysis of hypoxia-tolerant population of the Chinese mitten crab (Eriocheir sinensis)

Hypoxic stress, triggered by a multitude of factors, has inflicted significant economic repercussions on the aquaculture of Eriocheir sinensis. In this research, we sequenced a collective of 60 samples from both hypoxia-sensitive and hypoxia-resistant groups utilizing streamlined genome sequencing techniques. Subsequently, we delved into population evolution, scrutinized the selective sweep within these populations, and performed a genome-wide association study (GWAS) focused on the hypoxia tolerance traits within the population, all through the lens of SNPs molecular markers. This comprehensive analysis aimed to uncover the SNPs and pinpoint the pertinent candidate genes that influence the hypoxia tolerance capabilities of E. sinensis. The selective sweep analysis revealed that genes harboring potential genetic variations within the two populations were predominantly enriched in areas such as signaling molecules and interactions, energy metabolism, glycolipid metabolism, and immune response. In the genome-wide association study focusing on hypoxia tolerance traits, we identified four SNPs significantly associated with hypoxia resistance. Furthermore, one potential candidate gene, Dscam2, which is believed to influence hypoxia tolerance, was discovered within a 50 kb vicinity of these SNPs. These identified SNPs can serve as molecular markers for screening hypoxia tolerance, offering valuable insights for the genetic improvement of E. sinensis.

Tertiary Care Center Trends in Colonic Stent Placement over the Past Decade.

Colonic endoluminal stent placement is a commonly utilized and effective endoscopic approach for the management of malignant large bowel obstruction and is an emerging approach for the management of some benign etiologies of large bowel obstruction. However, recent studies evaluating the evolution of clinical scenarios and patient populations for which stenting is performed in real-world practice are lacking. We assessed colonic stent utilization patterns in a tertiary care academic medical center over the past 10 years. We analyzed the demographics and patient and procedure characteristics of the initial (first half of study period) and latter (second half of the study period) procedures to assess trends over time using standard descriptive statistics. Our analysis was notable due to its provision of some novel insights. The frequency of colonic stent placement procedures increased significantly over time by comparison of the procedure volume for the initial 5-year interval (22 colonic stent procedures) relative to the latter 5-year interval (49 colonic stent procedures) (p = 0.03). The median age of patients who underwent colonic stent placement was significantly lower in the latter 5 years, compared with the initial 5 years of the study period (mean of 81.41 vs. 58.73 years, respectively, p < 0.001). The increased diversity of indications for colonic stent placement was also noted over time. Our data highlight the evolution of colonic stent placement in tertiary care practice over time and are notable for some interesting trends, including the increased utilization of colonic stent placement over time, the broadening of indications for colonic stent placement to include benign indications, and lower patient age at the time of colonic stent placement over time. These findings will help inform the clinical practice of colonic stent placement and provide a foundation to guide future research on the topic.

Limited population structure but signals of recent selection in introduced African Fig Fly (Zaprionus indianus) in North America.

Invasive species have devastating consequences for human health, food security, and the environment. Many invasive species adapt to new ecological niches following invasion, but little is known about the early steps of adaptation. Here we examine population genomics of a recently introduced drosophilid in North America, the African Fig Fly, Zaprionus indianus. This species is likely intolerant of subfreezing temperatures and recolonizes temperate environments yearly. We generated a new chromosome-level genome assembly for Z. indianus. Using resequencing of over 200 North American individuals collected over four years in temperate Virginia, plus a single collection from subtropical Florida, we tested for signatures of recolonization, population structure, and adaptation within invasive populations. We show founding populations are sometimes small and contain close genetic relatives, yet temporal population structure and differentiation of populations is mostly absent across recurrent recolonization events. Although we find limited signals of genome-wide spatial or temporal population structure, we identify haplotypes on the X chromosome that are repeatedly differentiated between Virginia and Florida populations. These haplotypes show signatures of natural selection and are not found in African populations. We also find evidence for several large structural polymorphisms segregating within North America populations and show X chromosome evolution in invasive populations is strikingly different from the autosomes. These results show that despite limited population structure, populations may rapidly evolve genetic differences early in an invasion. Further uncovering how these genomic regions influence invasive potential and success in new environments will advance our understanding of how organisms evolve in changing environments.

Reconstructing tumor clonal heterogeneity and evolutionary relationships based on tumor DNA sequencing data.

The heterogeneity of tumor clones drives the selection and evolution of distinct tumor cell populations, resulting in an intricate and dynamic tumor evolution process. While tumor bulk DNA sequencing helps elucidate intratumor heterogeneity, challenges such as the misidentification of mutation multiplicity due to copy number variations and uncertainties in the reconstruction process hinder the accurate inference of tumor evolution. In this study, we introduce a novel approach, REconstructing Tumor Clonal Heterogeneity and Evolutionary Relationships (RETCHER), which characterizes more realistic cancer cell fractions by accurately identifying mutation multiplicity while considering uncertainty during the reconstruction process and the credibility and reasonableness of subclone clustering. This method comprehensively and accurately infers multiple forms of tumor clonal heterogeneity and phylogenetic relationships. RETCHER outperforms existing methods on simulated data and infers clearer subclone structures and evolutionary relationships in real multisample sequencing data from five tumor types. By precisely analysing the complex clonal heterogeneity within tumors, RETCHER provides a new approach to tumor evolution research and offers scientific evidence for developing precise and personalized treatment strategies. This approach is expected to play a significant role in tumor evolution research, clinical diagnosis, and treatment. RETCHER is available for free at https://github.com/zlsys3/RETCHER.

Growth rate as a link between microbial diversity and soil biogeochemistry.

Measuring the growth rate of a microorganism is a simple yet profound way to quantify its effect on the world. The absolute growth rate of a microbial population reflects rates of resource assimilation, biomass production and element transformation-some of the many ways in which organisms affect Earth's ecosystems and climate. Microbial fitness in the environment depends on the ability to reproduce quickly when conditions are favourable and adopt a survival physiology when conditions worsen, which cells coordinate by adjusting their relative growth rate. At the population level, relative growth rate is a sensitive metric of fitness, linking survival and reproduction to the ecology and evolution of populations. Techniques combining omics and stable isotope probing enable sensitive measurements of the growth rates of microbial assemblages and individual taxa in soil. Microbial ecologists can explore how the growth rates of taxa with known traits and evolutionary histories respond to changes in resource availability, environmental conditions and interactions with other organisms. We anticipate that quantitative and scalable data on the growth rates of soil microorganisms, coupled with measurements of biogeochemical fluxes, will allow scientists to test and refine ecological theory and advance process-based models of carbon flux, nutrient uptake and ecosystem productivity. Measurements of in situ microbial growth rates provide insights into the ecology of populations and can be used to quantitatively link microbial diversity to soil biogeochemistry.

The imprint of the first stars on the faint end of the white dwarf luminosity function

ABSTRACT Population III stars are characterized by extremely low metallicities as they are thought to be formed from a pristine gas in the early Universe. Although the existence of Population III stars is widely accepted, the lack of direct observational evidence hampers the study of the nature of the putative stars. In this article, we explore the possibilities of constraining the nature of the oldest stars by using the luminosity function of their remnants – white dwarfs. We study the formation and evolution of white dwarf populations by following star formation in a Milky Way-like galaxy using the semi-analytic model a-sloth. We derive the white dwarf luminosity function by applying a linear initial-final mass relation and Mestel’s cooling model. The obtained luminosity function is generally in agreement with available observations and theoretical predictions – with an exponential increase to a maximum of $M_{\mathrm{abs}} = 16$ and a sudden drop for $M_{\mathrm{abs}} \gt 16$. We explore the uncertainties of our model and compare them to the observational estimates. We adopt two different models of the initial mass function of Population III stars to show that the faint end of the luminosity function imprints the signature of Population III remnants. If the feature is detected in future observations, it would provide a clue to Population III stars and would also be an indirect evidence of low- to intermediate-mass Population III stars. We discuss the challenges and prospects for detecting the signatures.

Effects of periodic bottlenecks on the dynamics of adaptive evolution in microbial populations.

Population bottlenecks can impact the rate of adaptation in evolving populations. On the one hand, each bottleneck reduces the genetic variation that fuels adaptation. On the other hand, each founder that survives a bottleneck can undergo more generations and leave more descendants in a resource-limited environment, which allows surviving beneficial mutations to spread more quickly. A theoretical model predicted that the rate of fitness gains should be maximized using ~8-fold dilutions. Here we investigate the impact of repeated bottlenecks on the dynamics of adaptation using numerical simulations and experimental populations of Escherichia coli. Our simulations confirm the model's prediction when populations evolve in a regime where beneficial mutations are rare and waiting times between successful mutations are long. However, more extreme dilutions maximize fitness gains in simulations when beneficial mutations are common and clonal interference prevents most of them from fixing. To examine these predictions, we propagated 48 E. coli populations with 2-, 8-, 100-, and 1000-fold dilutions for 150 days. Adaptation began earlier and fitness gains were greater with 100- and 1000-fold dilutions than with 8-fold dilutions, consistent with the simulations when beneficial mutations are common. However, the selection pressures in the 2-fold treatment were qualitatively different from the other treatments, violating a critical assumption of the model and simulations. Thus, varying the dilution factor during periodic bottlenecks can have multiple effects on the dynamics of adaptation caused by differential losses of diversity, different numbers of generations, and altered selection.

True unicorns and false positives: Simulated probabilities of dark massive companions to bright stars

Abstract Many compact objects (black holes and neutron stars) exist in binaries. These binaries are normally discovered through their interactions, either from accretion as an X-ray binary or collisions as a gravitational wave source. However, the majority of compact objects in binaries should be non-interacting. Recently proposed discoveries have used radial velocities of a bright star (main sequence or evolved) that are indicative of a massive but dark companion, which is inferred to be a compact object. Unfortunately, this burgeoning new field has been hindered by false positives, including the “Unicorn” (V723 Mon) which was initially believed to be a red giant/black hole binary before being refuted. In this work, we investigate the evolution of stellar binary populations over time, using the binary evolution code COSMIC to simulate binary populations and determine the probability of a candidate object being either a “true Unicorn” (actual compact objects in binaries) or a false positive. We find that main sequence stars have a higher true Unicorn probability than red giants or naked helium stars (an exposed core of an evolved star), particularly if the companion is more massive and is ≥3 times less luminous than the MS star. We also find that a top-heavy initial mass function raises the true Unicorn probability further, that super-solar metallicity reduces the probability, and that most true Unicorns are found at periods ≤100 days. Finally, we find that a significant fraction of true Unicorns do not evolve into x-ray binaries during the age of the universe.

Independent repeated mutations within the alphaviruses Ross River virus and Barmah Forest virus indicates convergent evolution and past positive selection in ancestral populations despite ongoing purifying selection.

Ross River virus (RRV) and Barmah Forest virus (BFV) are arthritogenic arthropod-borne viruses (arboviruses) that exhibit generalist host associations and share distributions in Australia and Papua New Guinea (PNG). Using stochastic mapping and discrete-trait phylogenetic analyses, we profiled the independent evolution of RRV and BFV signature mutations. Analysis of 186 RRV and 88 BFV genomes demonstrated their viral evolution trajectories have involved repeated selection of mutations, particularly in the nonstructural protein 1 (nsP1) and envelope 3 (E3) genes suggesting convergent evolution. Convergent mutations in the nsP1 genes of RRV (residues 248 and 441) and BFV (residues 297 and 447) may be involved with catalytic enzyme mechanisms and host membrane interactions during viral RNA replication and capping. Convergent E3 mutations (RRV site 59 and BFV site 57) may be associated with enzymatic furin activity and cleavage of E3 from protein precursors assisting viral maturation and infectivity. Given their requirement to replicate in disparate insect and vertebrate hosts, convergent evolution in RRV and BFV may represent a dynamic link between their requirement to selectively 'fine-tune' intracellular host interactions and viral replicative enzymatic processes. Despite evidence of evolutionary convergence, selection pressure analyses did not reveal any RRV or BFV amino acid sites under strong positive selection and only weak positive selection for nonstructural protein sites. These findings may indicate that their alphavirus ancestors were subject to positive selection events which predisposed ongoing pervasive convergent evolution, and this largely supports continued purifying selection in RRV and BFV populations during their replication in mosquito and vertebrate hosts.

Characteristics of Phenotypic Variation of Malus Pollen at Infrageneric Scale.

Pollen carries extensive genetic information, which may provide clues regarding the kinship of Malus, whose genetic relationships are complex. In this study, the phenotypic variation of pollen from 107 Malus taxa was investigated using combined methods of intraspecific/interspecific uniformity testing, cluster analysis, and Pearson correlation analysis. The family aggregation distributions in Malus sections, species, and cultivars were analyzed to infer their pedigree relationships. The results showed that (1) compared with pollen size and morphology, aberrant pollen rate and ornamentation were highly interspecifically differentiated, but ornamentation was also intraspecifically unstable, especially perforation densities (c.v.¯ > 15%). (2) The pollen alteration direction from the original to the evolutionary population of Malus was large to small, with elliptic to rectangular morphologies, large and compact to small and sparse ridges, and low to high perforation densities. However, there was no significant change in pollen size. (3) The 107 studied taxa were divided into four groups. Malus species were relatively clustered in the same section, while homologous cultivars showed evidence of family aggregation distribution characteristics (92.60% of cultivars were clustered with their parents). (4) M. baccata and M. pumilar var. neidzwetzkyana were high-frequency parents, participating in 38.7% and 20.7% of cross-breeding, respectively. Overall, this study provides a reference for identifying Malus' pedigree relationship.

Evolutionary dynamics of the successful expansion of pandemic Vibrio parahaemolyticus ST3 in Latin America

The underlying evolutionary mechanisms driving global expansions of pathogen strains are poorly understood. Vibrio parahaemolyticus is one of only two marine pathogens where variants have emerged in distinct climates globally. The success of a Vibrio parahaemolyticus clone (VpST3) in Latin America- the first spread identified outside its endemic region of tropical Asia- provided an invaluable opportunity to investigate mechanisms of VpST3 expansion into a distinct marine climate. A global collection of VpST3 isolates and novel Latin American isolates were used for evolutionary population genomics, pangenome analysis and combined with oceanic climate data. We found a VpST3 population (LatAm-VpST3) introduced in Latin America well before the emergence of this clone in India, previously considered the onset of the VpST3 epidemic. LatAm-VpST3 underwent successful adaptation to local conditions over its evolutionary divergence from Asian VpST3 isolates, to become dominant in Latin America. Selection signatures were found in genes providing resilience to the distinct marine climate. Core genome mutations and accessory gene presences that promoted survival over long dispersals or increased environmental fitness were associated with environmental conditions. These results provide novel insights into the global expansion of this successful V. parahaemolyticus clone into regions with different climate scenarios.

Modeling Polymer Microencapsulation Processes Using CFD and Population Balance Models

Computational fluid dynamics (CFD) modeling has emerged as a valuable tool for investigating complex processes like microencapsulation. This paper aims to validate the ability of CFD simulations to predict particle size distribution in a polymer microencapsulation process. The CFD modeling approach employed a Eulerian multiphase framework, incorporating a discrete population balance model to track the evolution of the droplet population. A realizable k-ε turbulence model and a multiple reference frame strategy were utilized to capture the system’s flow dynamics. The results reveal that while the CFD simulations align well with experimental data at higher agitation speeds (&gt;10,000 rpm), discrepancies arise at lower speeds (&lt;7500 rpm), indicating a challenge in accurately capturing turbulent viscous regimes. Despite these challenges, the CFD model demonstrates robust predictive capabilities for droplet formation and distribution in microencapsulation processes, validated by error margins within the acceptable limits. The validated model can be used as a reliable tool to guide experimental efforts and optimize process parameters, contributing to an enhanced understanding and control of microencapsulation processes.

The assembly and comparative analysis of the first complete mitogenome of Lindera aggregata.

Lindera aggregata, a member belongs to the genus Lindera of Lauraceae family. Its roots and leaves have been used as traditional Chinese medicine or functional food for thousands of years. However, its mitochondrial genome has not been explored. Our aim is to sequence and assemble the mitogenome of L. aggregata to elucidate the genetic mechanism and evolutionary pathway. The results had shown that the mitogenome was extremely complex and had a unique multi-branched conformation with total size of 912,473 bp. Comprehensive analysis of protein coding genes of 7 related species showed that there were 40 common genes in their mitogenome. Interestingly, positive selection had become an important factor in the evolution of ccmB, ccmFC, rps10, rps11 and rps7 genes. Furthermore, our data highlighted the repeated trend of homologous fragment migrations between chloroplast and mitochondrial organelles, and 38 homologous fragments were identified. Phylogenetic analysis identified a tree that was basically consistent with the phylogeny of Laurales species described in the APG IV system. To sum up, this study will be helpful to the study of population genetics and evolution of Lindera species.

Drivers of diversification in fungal pathogen populations.

To manage and treat chronic fungal diseases effectively, we require an improved understanding of their complexity. There is an increasing appreciation that chronic infection populations are often heterogeneous due to diversification and drift, even within a single microbial species. Genetically diverse populations can contribute to persistence and resistance to treatment by maintaining cells with different phenotypes capable of thriving in these dynamic environments. In chronic infections, fungal pathogens undergo prolonged challenges that can drive trait selection to convergent adapted states through restricted access to critical nutrients, assault by immune effectors, competition with other species, and antifungal drugs. This review first highlights the various genetic and epigenetic mechanisms that promote diversity in pathogenic fungal populations and provide an additional barrier to assessing the actual heterogeneity of fungal infections. We then review existing studies of evolution and genetic heterogeneity in fungal populations from lung infections associated with the genetic disease cystic fibrosis. We conclude with a discussion of open research questions that, once answered, may aid in diagnosing and treating chronic fungal infections.

Expulsion of runaway electrons using ECRH in the TCV tokamak

Abstract Runaway electrons (REs) are a concern for tokamak fusion reactors from discharge startup to termination. A sudden localized loss of a multi-megaampere RE beam can inflict severe damage to the first wall. Should a disruption occur, the existence of a RE seed may play a significant role in the formation of a RE beam and the magnitude of its current. The application of central electron cyclotron resonance heating (ECRH) in the Tokamak à Configuration Variable (TCV) reduces an existing RE seed population by up to three orders of magnitude within only a few hundred milliseconds. Applying ECRH before a disruption can also prevent the formation of a post-disruption RE beam in TCV where it would otherwise be expected. The RE expulsion rate and consequent RE current reduction are found to increase with applied ECRH power. Whereas central ECRH is effective in expelling REs, off-axis ECRH has a comparatively limited effect. A simple 0-D model for the evolution of the RE population is presented that explains the effective ECRH-induced RE expulsion results from the combined effects of increased electron temperature and enhanced RE transport.

Advances on the Global Human Settlement Layer by joint assessment of Earth Observation and population survey data

ABSTRACT The Global Human Settlement Layer (GHSL) project fosters an enhanced, public understanding of the human presence on Earth. A decade after its inception in the Digital Earth 2020 vision, GHSL is an established project of the European Commission’s Joint Research Centre and an integral part of the Copernicus Emergency Management Service. The 2023 GHSL edition, a result of rigorous research on Earth Observation data and population censuses, contributes significantly to understanding worldwide human settlements. It introduces new elements like 10-m-resolution, sub-pixel estimation of built-up surfaces, global building height and volume estimates, and a classification of residential and non-residential areas, improving population density grids. This paper evaluates the key components of the GHSL, including the Symbolic Machine Learning approach, using novel reference data. These data enable a comparative assessment of GHSL model predictions on the evolution of built-up surface, building heights, and resident population. Empirical evidence suggests that GHSL estimates are the most accurate in the public domain today, e.g. achieving an IoU of 0.98 for the water class, 0.92 for the built-up class, and 0.8 for the non-residential class at 10 m resolution. At 100 m resolution, we find that the MAE of built-up surface estimates corresponds to 6% of the grid cell area, the MAE for the building height estimates is 2.27 m, and we find a total allocation accuracy of 83% for resident population. This paper consolidates the theoretical foundation of the GHSL and highlights its innovative features for transparent Artificial Intelligence, facilitating international decision-making processes.