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3,339 results for “heterogeneities”
Data from: Ecological specialization in populations adapted to constant versus heterogeneous environments
Populations vary in their degree of ecological specialization. An intuitive, but often untested, hypothesis is that populations evolving under greater environmental heterogeneity will evolve to be less specialized. How important is environmental heterogeneity in explaining among-population variation in specialization? We assessed juvenile viability of 20 Drosophila melanogaster populations evolving under one of four regimes: (i) a salt-enriched environment, (ii) a cadmium-enriched environment, (iii) a temporally varying environment, and (iv) a spatially varying environment. Juvenile viability was tested in both the original selective environments and a set of novel environments. In both the original and novel environments, populations from the constant cadmium regime had the lowest average viability and the highest variance in viability across environments but populations from the other three regimes were similar. Our results suggest that variation in specialization among these populations is most simply explained as a pleiotropic by-product of adaptation to specific environments rather than resulting from a history of exposure to environmental heterogeneity.
Data from: Modeling site heterogeneity with posterior mean site frequency profiles accelerates accurate phylogenomic estimation
Proteins have distinct structural and functional constraints at different sites that lead to site-specific preferences for particular amino acid residues as the sequences evolve. Heterogeneity in the amino acid substitution process between sites is not modeled by commonly used empirical amino acid exchange matrices. Such model misspecification can lead to artefacts in phylogenetic estimation such as long-branch attraction. Although sophisticated site-heterogeneous mixture models have been developed to address this problem in both Bayesian and maximum likelihood (ML) frameworks, their formidable computational time and memory usage severely limits their use in large phylogenomic analyses. Here we propose a posterior mean site frequency (PMSF) method as a rapid and efficient approximation to full empirical profile mixture models for ML analysis. The PMSF approach assigns a conditional mean amino acid frequency profile to each site calculated based on a mixture model fitted to the data using a preliminary guide tree. These PMSF profiles can then be used for in-depth tree-searching in place of the full mixture model. Compared with widely used empirical mixture models with k classes, our implementation of PMSF in IQ-TREE (http://www.iqtree.org) speeds up the computation by approximately k /1.5-fold and requires a small fraction of the RAM. Furthermore, this speedup allows, for the first time, full nonparametric bootstrap analyses to be conducted under complex site-heterogeneous models on large concatenated data matrices. Our simulations and empirical data analyses demonstrate that PMSF can effectively ameliorate long-branch attraction artefacts. In some empirical and simulation settings PMSF provided more accurate estimates of phylogenies than the mixture models from which they derive.
Data from: Heterogeneous and efficient transesterification of Jatropha curcas L. seed oil to produce biodiesel catalyzed by nano-sized SO42-/TiO2
Developing high-efficiency hetero-catalysts for transesterification reaction is of great importance in the production of biodiesel from Jatropha curcas L. seed oil (JO). Here, we synthesized a series of sulfated TiO2 by treating with varying H2SO4 concentration (xSO42-/TiO2) and TiO2 catalysts and applied to the transesterification of JO. Furthermore, these heterostructures were characterized by many characterization methods including XRD, FT–IR, N2–adsorption, SEM, TEM, TG, py-IR and NH3-TPD, and their catalytic performance were investigated under various operating conditions. The results reveal that both the Brønsted and Lewis acid sites are presented in the xSO42-/TiO2 catalysts, while only Lewis-type sites are observed in the TiO2 catalyst. And the acid intensity, surface area and mesoporous volume of catalysts are improved obviously after treating with sulfuric acid of TiO2. Then the xSO42-/TiO2 catalysts exhibit much higher catalytic activity than TiO2 catalyst, which is attributed to the larger surface area and mesoporous volume and stronger acidity. Furthermore, the reusability behavior of 1.5SO42-/TiO2 catalyst in transesterification of JO was also studied.
Data from: Should I change or should I go? phenotypic plasticity and matching habitat choice in the adaptation to environmental heterogeneity
It can be challenging for organisms to achieve a good match between their phenotypic characteristics and environmental requirements that vary in space and time. The evolution of adaptive phenotypes can result from genetic differentiation at the population level. Individuals, however, could also change their phenotype (adaptive plasticity) or select an environment because it matches with their phenotype (matching habitat choice). It is poorly known under which conditions these different solutions to environmental heterogeneity evolve and whether they operate together. Using an individual-based simulation model, we assessed which solutions evolved depending on degree of temporal variation, costs of multiple underlying traits, and order of dispersal and development. Population genetic divergence was superseded by plasticity or matching habitat choice as temporal variation increased. Plasticity and matching habitat choice were limited by their trait costs, even when this involved only a part of the underlying traits. Independent of the order of dispersal and development, plasticity evolved more commonly than matching habitat choice, in part because the match a phenotype can achieve by matching habitat choice is limited by the types of environments available. Our results explain the apparent relative rarity of matching habitat choice in nature. At the same time, our results can be used to look for matching habitat choice in those biological systems where the conditions for other solutions seem unfavorable.
Data from: Genome-wide association analysis for blood lipid traits measured in three pig populations revealed a substantial level of genetic heterogeneity
Serum lipids are associated with myocardial infarction and cardiovascular disease in humans. Here we dissected the genetic architecture of blood lipid traits by applying genome-wide association studies (GWAS) in 1,256 pigs from Laiwu, Erhualian and Duroc × (Landrace × Yorkshire) populations, and a meta-analysis of GWAS in more than 2,400 pigs from five diverse populations. A total of 22 genomic loci surpassing the suggestive significance level were detected on 11 pig chromosomes (SSC) for six blood lipid traits. Meta-analysis of GWAS identified 5 novel loci associated with blood lipid traits. Comparison of GWAS loci across the tested populations revealed a substantial level of genetic heterogeneity for porcine blood lipid levels. We further evaluated the causality of nine polymorphisms nearby or within the APOB gene on SSC3 for serum LDL-C and TC levels. Of the 9 polymorphisms, an indel showed the most significant association with LDL-C and TC in Laiwu pigs. But the significant association was not identified in the White Duroc × Erhualian F2 resource population, in which the QTL for LDL-C and TC was also detected on SSC3. This indicates that population-specific signals may exist for the SSC3 QTL. Further investigations are warranted to validate this assumption.
Data from: A spatial theory for characterizing predator–multiprey interactions in heterogeneous landscapes
Trophic interactions in multiprey systems can be largely determined by prey distributions. Yet, classic predator–prey models assume spatially homogeneous interactions between predators and prey. We developed a spatially informed theory that predicts how habitat heterogeneity alters the landscape-scale distribution of mortality risk of prey from predation, and hence the nature of predator interactions in multiprey systems. The theoretical model is a spatially explicit, multiprey functional response in which species-specific advection–diffusion models account for the response of individual prey to habitat edges. The model demonstrates that distinct responses of alternative prey species can alter the consequences of conspecific aggregation, from increasing safety to increasing predation risk. Observations of threatened boreal caribou, moose and grey wolf interacting over 378 181 km2 of human-managed boreal forest support this principle. This empirically supported theory demonstrates how distinct responses of apparent competitors to landscape heterogeneity, including to human disturbances, can reverse density dependence in fitness correlates.
Data from: Multilevel and quasi-Monte Carlo methods for uncertainty quantification in particle travel times through random heterogeneous porous media
In this study, we apply four Monte Carlo simulation methods, namely, Monte Carlo, quasi-Monte Carlo, multilevel Monte Carlo and multilevel quasi-Monte Carlo to the problem of uncertainty quantification in the estimation of the average travel time during the transport of particles through random heterogeneous porous media. We apply the four methodologies to a model problem where the only input parameter, the hydraulic conductivity, is modelled as a log-Gaussian random field by using direct Karhunen–Loéve decompositions. The random terms in such expansions represent the coefficients in the equations. Numerical calculations demonstrating the effectiveness of each of the methods are presented. A comparison of the computational cost incurred by each of the methods for three different tolerances is provided. The accuracy of the approaches is quantified via the mean square error.
Data from: Roles of pathogens on replacement of tree seedlings in heterogeneous light environments in a temperate forest: a reciprocal seed sowing experiment
1. In forest communities, the Janzen–Connell (J-C) hypothesis proposes that species diversity is maintained by non-competitive distance- and/or density-dependent seedling mortality caused by host-specific natural enemies. However, the effects of pathogen associations from nearby conspecifics vs. heterospecifics remain unknown in spatially heterogeneous light environments. 2. Seeds of hardwood species Cornus controversa (Cornus) and Prunus grayana (Prunus) were sown beneath 6–7 Cornus and Prunus adults in both the forest understory (FU) and in gaps (Gap) created by felling all woody vegetation near the focal adults. Seedling growth, mortality, killing agents (e.g. pathogens that cause damping-off and leaf diseases), and root infection by arbuscular mycorrhizal fungi (AMF) were investigated. 3. We found strong habitat effects on the expression of soil fungi beneath both tree species. Seedling mortality caused by soil-borne damping-off pathogens was greater in FU than in Gap, and AMF infection, which enhanced relative seedling growth rate, was greater in Gap than in FU. Seedling mortality caused by damping-off pathogens did not differ between Cornus and Prunus seedlings beneath the adults of conspecific or heterospecific adults in both FU and Gap, suggesting little distance-dependence or host preference in the fungus. 4. Beneath the adults of Cornus and Prunus, the most prevalent leaf diseases were zonate leaf blight and angular leaf spot caused by the airborne pathogenic fungi Haradamyces foliicola and Phaeoisariopsis pruni-grayanae, respectively. Although these pathogens attacked the seedlings of both species, conspecific seedlings (i.e. home) showed more severe leaf damage, earlier leaf shedding and/or less defensive behaviour (cell wall defence) relative to heterospecific seedlings (i.e. away), suggesting negative distance-dependent attack (i.e. host preference) for these leaf diseases. As a result, greater seedling mortality was observed for conspecific seedlings under both FU and Gap treatments. 5. Synthesis. In the temperate forest, the J-C hypothesis is largely mediated through the strong negative influence of airborne leaf diseases rather than through soil-borne damping-off pathogens. We found that airborne diseases demonstrated distance-dependent host preferences, which led to greater conspecific seedling damage regardless of environmental light conditions.
Data from: Effect of detection heterogeneity in occupancy-detection models: an experimental test of time-to-first-detection methods
Imperfect detection can bias estimates of site occupancy in ecological surveys but can be corrected by estimating detection probability. Time-to-first-detection (TTD) occupancy models have been proposed as a cost-effective survey method that allows detection probability to be estimated from single site visits. Nevertheless, few studies have validated the performance of occupancy-detection models by creating a situation where occupancy is known, and model outputs can be compared with the truth. We tested the performance of TTD occupancy models in the face of detection heterogeneity using an experiment based on standard survey methods to monitor koala (Phascolarctos cinereus) populations in Australia. Known numbers of koala faecal pellets were placed under trees, and observers, uninformed as to which trees had pellets under them, carried out a TTD survey. We fitted five TTD occupancy models to the survey data, each making different assumptions about detectability, to evaluate how well each estimated the true occupancy status. Relative to the truth, all five models produced strongly biased estimates, overestimating detection probability and underestimating the number of occupied trees. Despite this, goodness-of-fit tests indicated that some models fitted the data well, with no evidence of model misfit. Hence, TTD occupancy models that appear to perform well with respect to the available data may be performing poorly. The reason for poor model performance was unaccounted for heterogeneity in detection probability, which is known to bias occupancy-detection models. This poses a problem because unaccounted for heterogeneity could not be detected using goodness-of-fit tests and was only revealed because we knew the experimentally determined outcome. A challenge for occupancy-detection models is to find ways to identify and mitigate the impacts of unobserved heterogeneity, which could unknowingly bias many models.
Genetic homogeneity in the face of morphological heterogeneity in the harbor porpoise from the Black Sea and adjacent waters (Phocoena phocoena relicta)
<p>Absence of genetic differentiation is usually taken as an evidence of panmixia, but can also reflect other situations including even nearly complete demographic independence among large-sized populations. Deciphering which situation applies has major practical implications (e.g., in conservation biology). The endangered harbor porpoises in the Black Sea illustrates well this point. While morphological heterogeneity suggested that population differentiation may exist between individuals from the Black and Azov seas, no genetic study provided conclusive evidence or covered the entire subspecies range. Here, we assessed the genetic structure at ten microsatellite loci and a 3,904 base-pairs mitochondrial fragment in 144 porpoises across the subspecies range (i.e., Aegean, Marmara, Black, and Azov seas). Analyses of the genetic structure including <i>F<sub>ST</sub></i>, Bayesian clustering, and multivariate analyses revealed a nearly complete genetic homogeneity. Power analyses rejected the possibility of underpowered analyses (power to detect <i>F<sub>ST</sub></i>≥0.008 at microsatellite loci). Simulations under various demographic models, evaluating the evolution of <i>F<sub>ST</sub></i>, showed that a time-lag effect between demographic and genetic subdivision is also unlikely. With a realistic effective population size of 1000 individuals, the expected "<i>grey zone"</i> would be at most 20 generations under moderate levels of gene flow (≤10 migrants per generation). After excluding alternative hypotheses, panmixia remains the most likely hypothesis explaining the genetic homogeneity in the Black Sea porpoises. Morphological heterogeneity may thus reflect other processes than population subdivision (e.g., plasticity, selection). This study illustrates how combining empirical and theoretical approaches can contribute to understanding patterns of weak population structure in highly mobile marine species.</p>
Data from: A branch-heterogeneous model of protein evolution for efficient inference of ancestral sequences
Most models of nucleotide or amino acid substitution used in phylogenetic studies assume that the evolutionary process has been homogeneous across lineages and that composition of nucleotides or amino acids has remained the same throughout the tree. These oversimplified assumptions are refuted by the observation that compositional variability characterizes extant biological sequences. Branch-heterogeneous models of protein evolution that account for compositional variability have been developed, but are not yet in common use because of the large number of parameters required, leading to high computational costs and potential overparameterization. Here, we present a new branch-nonhomogeneous and nonstationary model of protein evolution that captures more accurately the high complexity of sequence evolution. This model, henceforth called Correspondence and likelihood analysis (COaLA), makes use of a correspondence analysis to reduce the number of parameters to be optimized through maximum likelihood, focusing on most of the compositional variation observed in the data. The model was thoroughly tested on both simulated and biological data sets to show its high performance in terms of data fitting and CPU time. COaLA efficiently estimates ancestral amino acid frequencies and sequences, making it relevant for studies aiming at reconstructing and resurrecting ancestral amino acid sequences. Finally, we applied COaLA on a concatenate of universal amino acid sequences to confirm previous results obtained with a nonhomogeneous Bayesian model regarding the early pattern of adaptation to optimal growth temperature, supporting the mesophilic nature of the Last Universal Common Ancestor.
Data from: Resource heterogeneity, soil fertility, and species diversity: effects of clonal species on plant communities
Spatial heterogeneity in soil resources is widely thought to promote plant species coexistence, and this mechanism figures prominently in resource-ratio models of competition. However, most experimental studies have found that nutrient enhancements depress diversity regardless of whether nutrients are uniformly or heterogeneously applied. This mismatch between theory and empirical pattern is potentially due to an interaction between plant size and the scale of resource heterogeneity. Clonal plants that spread vegetatively via rhizomes or stolons can grow large and may integrate across resource patches, thus reducing the positive effect of small-scale resource heterogeneity on plant species richness. Many rhizomatous clonal species respond strongly to increased soil fertility, and they have been hypothesized to drive the descending arm of the hump-shaped productivity-diversity relationship in grasslands. We tested whether clonals reduce species richness in a grassland community by manipulating nutrient heterogeneity, soil fertility, and the presence of rhizomatous clonal species in a 6-year field experiment. We found strong and consistent negative effects of clonals on species richness. These effects were greatest at high fertility and when soil resources were applied at a scale at which rhizomatous clonals could integrate across resource patches. Thus, we find support for the hypothesis that plant size and resource heterogeneity interact to determine species diversity.
Data from: Spatiotemporal heterogeneity in prey abundance and vulnerability shapes the foraging tactics of an omnivore
1. Prey abundance and prey vulnerability vary across space and time, but we know little about how they mediate predator-prey interactions and predator foraging tactics. To evaluate the interplay between prey abundance, prey vulnerability, and predator space use, we examined patterns of black bear (Ursus americanus) predation of caribou (Rangifer tarandus) neonates in Newfoundland, Canada using data from 317 collared individuals (9 bears, 34 adult female caribou, 274 caribou calves). 2. During the caribou calving season, we predicted that landscape features would influence calf vulnerability to bear predation, and that bears would actively hunt calves by selecting areas associated with increased calf vulnerability. Further, we hypothesized that bears would dynamically adjust their foraging tactics in response to spatiotemporal changes in calf abundance and vulnerability (collectively, calf availability). Accordingly, we expected bears to actively hunt calves when they were most abundant and vulnerable, but switch to foraging on other resources as calf availability declined. 3. As predicted, landscape heterogeneity influenced risk of mortality, and bears displayed the strongest selection for areas where they were most likely to kill calves, which suggested they were actively hunting caribou. Initially, the per-capita rate at which bears killed calves followed a type-I functional response, but as the calving season progressed and calf vulnerability declined, kill rates dissociated from calf abundance. In support of our hypothesis, bears adjusted their foraging tactics when they were less efficient at catching calves, highlighting the influence that predation phenology may have on predator space use. Contrary to our expectations, however, bears appeared to continue to hunt caribou as calf availability declined, but switched from a tactic of selecting areas of increased calf vulnerability to a tactic that maximized encounter rates with calves. 4. Our results reveal that generalist predators can dynamically adjust their foraging tactics over short time scales in response to changing prey abundance and vulnerability. Further, they demonstrate the utility of integrating temporal dynamics of prey availability into investigations of predator-prey interactions, and move towards a mechanistic understanding of the dynamic foraging tactics of a large omnivore.
Data from: The impact of rate heterogeneity on inference of phylogenetic models of trait evolution
Rates of trait evolution are known to vary across phylogenies; however, standard evolutionary models assume a homogeneous process of trait change. These simple methods are widely applied in small-scale phylogenetic studies, whereas models of rate heterogeneity are not, so the prevalence and patterns of potential rate variation in groups up to hundreds of species remain unclear. The extent to which trait evolution is modelled accurately on a given phylogeny is also largely unknown because studies typically lack absolute model fit tests. We investigated these issues by applying both rate-static and variable-rates methods on (i) body mass data for 88 avian clades of 10–318 species, and (ii) data simulated under a range of rate-heterogeneity scenarios. Our results show that rate heterogeneity is present across small-scaled avian clades, and consequently applying only standard single-process models prompts inaccurate inferences about the generating evolutionary process. Specifically, these approaches underestimate rate variation, and systematically mislabel temporal trends in trait evolution. Conversely, variable-rates approaches have superior relative fit (they are the best model) and absolute fit (they describe the data well). We show that rate changes such as single internal branch variations, rate decreases and early bursts are hard to detect, even by variable-rates models. We also use recently developed absolute adequacy tests to highlight misleading conclusions based on relative fit alone (e.g. a consistent preference for constrained evolution when isolated terminal branch rate increases are present). This work highlights the potential for robust inferences about trait evolution when fitting flexible models in conjunction with tests for absolute model fit.
Data from: Plant community evenness responds to spatial plant-soil feedback heterogeneity primarily through the diversity of soil conditioning
1.Plant-soil feedback (PSF) has been identified as a key driver of local plant diversity and evenness in competitive communities. However, while it has been shown that spatial PSF heterogeneity can alter plant performance and competitive interactions, there is no proof of principle that spatial PSF heterogeneity enhances community diversity. 2.Using a grassland model system we separated two aspects of spatial heterogeneity: the number of species conditioning the soil and spatial distribution of the PSFs. 3.Our data show that PSFs promoted a higher plant evenness when the soil was conditioned by multiple species (mixed-conditioned), then when the soil was conditioned by a single species (mono-conditioned). On mono-conditioned soils, heterospecifics typically outperformed the focal species. In addition, there was a trend for increasing community evenness from uniform, via fine-grained to coarse-grained mixed-conditioned soils, but this was not significant. 4.On mixed-conditioned soils, performance of all competing species was intermediate to the best and the worst mono-conditioned soils, leading to higher community evenness. 5.Our data demonstrate that PSFs play a role in promoting plant evenness. Across mono-conditioned soils, PSF led to altered competitive hierarchies. However, on soils conditioned by multiple species, competitive ability among species was more similar and this led to higher plant evenness. The spatial distribution of the heterogeneity, on the other hand, did not significantly affect plant evenness. Our data therefore show that community evenness was more strongly related to the number of plant species that conditioned the soil than the spatial distribution of the PSF heterogeneity. Future studies need to investigate the importance of PSFs in the field across plant life-stages and multiple generations.
Data from: Do genetic structure and landscape heterogeneity impact color morph frequency in a polymorphic salamander?
Landscape heterogeneity plays an important role in population structure and divergence, particularly for species with limited vagility. Here, we used a landscape genetic approach to identify how landscape and environmental variables affect genetic structure and color morph frequency in a polymorphic salamander. The Eastern Red-backed Salamander, Plethodon cinereus, is widely distributed in northeastern North America and contains two common color morphs, striped and unstriped, that are divergent in ecology, behavior, and physiology. To quantify population structure, rates of gene flow, and genetic drift, we amplified 10 microsatellite loci from 648 individuals across 28 sampling localities. This study was conducted in northern Ohio, where populations of P. cinereus exhibit an unusually wide range of morph frequency variation. To test whether genetic distance was more correlated with morph frequency, elevation, canopy cover, waterways, ecological niche, or geographic distance, we used resistance distance and least cost path analyses. We then examined whether landscape and environmental variables, genetic distance, or geographic distance were correlated with variation in morph frequency. Tests for population structure revealed three genetic clusters across our sampling range, with one cluster monomorphic for the striped morph. Rates of gene flow and genetic drift were low to moderate across sites. Genetic distance was most correlated with ecological niche, elevation, and a combination of landscape and environmental variables. In contrast, morph frequency variation was correlated with waterways and geographic distance. Thus, our results suggest that selection is also an important evolutionary force across our sites, and a balance between gene flow, genetic drift, and selection interact to maintain the two color morphs.
Data from: Linking resource availability and heterogeneity to understorey species diversity through succession in boreal forest of Canada
Understorey vegetation hosts the majority of species diversity and contributes greatly to ecosystem functioning in natural systems. Although patterns of understorey abundance, species diversity and composition associated with forest stand development are well researched, mechanisms driving these patterns remain largely speculative. We sampled fire origin stands of varying stand ages and overstorey compositions on mesic sites of the boreal forest of Canada and used structural equation modeling (SEM) to link time since fire (stand age), light availability and heterogeneity, substrate heterogeneity and soil nitrogen to understorey vegetation cover and species diversity. The most parsimonious model for total understorey cover showed a positive direct effect of stand age (r = 0.43) and an indirect effect via mean light level (0.18) and shrub cover (-0.11), with a positive total effect (0.50); the percent broadleaf canopy had a direct negative effect (-0.22) and an indirect effect via shrub cover (-0.11). The model for total understorey species richness showed an indirect effect of stand age via mean light (0.24), light heterogeneity (0.10), and substrate heterogeneity (0.07), with a positive total effect (0.52); percent broadleaf canopy had an indirect effect via light heterogeneity (0.09), and substrate heterogeneity (-0.10). Soil nitrogen did not significantly influence either understorey cover or species richness. The models for vascular plants followed similar trends to those for total understorey cover and species richness; however, there was an opposite indirect effect of light heterogeneity for both cover and species richness of non-vascular plants. Shrub cover had positive direct and negative direct and indirect effects on both vascular and non-vascular cover and species richness. Our findings indicate that understorey cover and species diversity are driven by time since disturbance, light availability as influenced by overstorey and shrub layers, but with important additional effects mediated by light and substrate heterogeneity. Non-vascular understorey vegetation is more strongly determined by time since disturbance than vascular vegetation, and negatively affected by broadleaf tree abundance. The overall results highlight the importance of colonization, light availability and heterogeneity, substrate specialization and growth dynamics in determining successional patterns of boreal forest understorey vegetation.
Data from: Aβ42 fibril formation from predominantly oligomeric samples suggests a link between oligomer heterogeneity and fibril polymorphism
Aβ oligomers play a central role in the pathogenesis of Alzheimer's disease. Oligomers of different sizes, morphology, and structures have been reported in both in vivo and in vitro studies, but there is a general lack of understanding about where to place these oligomers in the overall process of Aβ aggregation and fibrillization. Here we show that Aβ42 spontaneously forms oligomers with a wide range of sizes in the same sample. These Aβ42 samples contain predominantly oligomers, and they quickly form fibrils upon incubation at 37°C. When fractionated using ultrafiltration filters, the samples enriched with smaller oligomers form fibrils at a faster rate than the samples enriched with larger oligomers, with both a shorter lag time and faster fibril growth rate. This observation is independent of Aβ42 batches and HFIP treatment. Furthermore, the fibrils formed by the samples enriched with larger oligomers are more readily solubilized by EGCG, a main catechin component of green tea. These results suggest that the fibrils formed by larger oligomers may adopt a different structure from fibrils formed by smaller oligomers, pointing to a link between oligomer heterogeneity and fibril polymorphism.
Data from: Selective breeding and selection mapping using a novel wild-derived heterogeneous stock mice revealed two closely-linked loci for tameness
Tameness is a major behavioral factor for domestication, and can be divided into two potential components: motivation to approach humans (active tameness) and reluctance to avoid humans (passive tameness). We identified genetic loci for active tameness through selective breeding, selection mapping, and association analysis. In previous work using laboratory and wild mouse strains, we found that laboratory strains were predominantly selected for passive tameness but not active tameness during their domestication. To identify genetic regions associated with active tameness, we applied selective breeding over 9 generations for contacting, a behavioural parameter strongly associated with active tameness. The prerequisite for successful selective breeding is high genetic variation in the target population, so we established and used a novel resource, wild-derived heterogeneous stock (WHS) mice from eight wild strains. The mice had genetic variations not present in other outbred mouse populations. Selective breeding of the WHS mice increased the contacting level through the generations. Selection mapping was applied to the selected population using a simulation based on a non-selection model and inferred haplotype data derived from single-nucleotide polymorphisms. We found a genomic signature for selection on chromosome 11 containing two closely linked loci.
Data from: Bayesian inference of selection in a heterogeneous environment from genetic time-series data
Evolutionary geneticists have sought to characterize the causes and molecular targets of selection in natural populations for many years. Although this research program has been somewhat successful, most statistical methods employed were designed to detect consistent, weak to moderate selection. In contrast, phenotypic studies in nature show that selection varies in time and that individual bouts of selection can be strong. Measurements of the genomic consequences of such fluctuating selection could help test and refine hypotheses concerning the causes of ecological specialization and the maintenance of genetic variation in populations. Herein, I proposed a Bayesian non-homogenous hidden Markov model to estimate effective population sizes and quantify variable selection in heterogeneous environments from genetic time-series data. The model is described and then evaluated using a series of simulated data, including cases where selection occurs on a trait with a simple or polygenic molecular basis. The proposed method accurately distinguished neutral loci from non-neutral loci under strong selection, but not from those under weak selection. Selection coefficients were accurately estimated when selection was constant or when the fitness values of genotypes varied linearly with the environment, but these estimates were less accurate when fitness was polygenic or the relationship between the environment and the fitness of genotypes was non-linear. Past studies of temporal evolutionary dynamics in lab populations have been remarkably successful. The proposed method makes similar analyses of genetic time-series data from natural populations more feasible, and thereby could help answer fun damental questions about the causes and consequences of evolution in the wild.
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.