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42 results for “population genetics model”
Data to accompany the publication "Combined biophysical and genetic modelling approaches reveal complementary information about population connectivity of New Zealand green-lipped mussels"
<p>Data to accompany the publication "Combined biophysical and genetic modelling approaches reveal complementary information about population connectivity of New Zealand green-lipped mussels". </p> <p>migrationmatrix14.txt contains the particle tracking matrix, with the total number of particles that migrated from row i to column j (out of a total of 2217864 particles released per population).</p> <p>mussel_microsat_Genepop.txt contains the microsatellite data for each population in Genepop format.</p>
Figure 6. One chromosome from the population and the five chromosomes existing in the evaluation partition.-Genetic Algorithms Principles Towards Hidden Markov Model
<p>For example comparing the<br> chromosome given in Figure 6 with the first chromosome in the evaluation partition, the<br> difference between the relation Med-Med and Med-High as a pair is 0.0 and the difference<br> between the relation High-High and High-Med as a pair is 0.1. Similarly the difference between<br> the relation Med-Cold and Med-Hot as a pair is 0.1 and the difference between the relation<br> High-Cold and High-Hot as a pair is 0.2. We sum all these differences to get the value of<br> compare(i,j), the sum value is 0+0.1+0.1+0.2 = 0.4. Using the same approach we compute the<br> compare function with the other four chromosomes and we get values 0.4, 0.5,0.4 and 0.6. Now<br> we sum the five values 0.4 + 0.4 + 0.5+ 0.4 +0.6 = 2.3. The fitness value is then 1/ 2.3 = 0.434.<br> The highest is the fitness value, the better is the performance of the chromosome.</p>
Whole genome demographic models indicate divergent effective population size histories shape contemporary genetic diversity gradients in a montane bumble bee
<p>Understanding historical range shifts and population size variation provides important context for interpreting contemporary genetic diversity. Methods to predict changes in species distributions and model changes in effective population size (N<sub>e</sub>) using whole genomes make it feasible to examine how temporal dynamics influence diversity across populations. We investigate N<sub>e</sub> variation and climate-associated range shifts to examine the origins of a previously observed latitudinal heterozygosity gradient in the bumble bee <em>Bombus</em> <em>vancouverensis</em> Cresson (Hymenoptera: Apidae: <em>Bombus</em> Latreille) in western North America. We analyze whole genomes from a latitude-elevation cline using sequentially Markovian coalescent models of N<sub>e</sub> through time to test whether relatively low diversity in southern high-elevation populations is a result of long-term differences in N<sub>e</sub>. We use Maxent models of the species range over the last 130,000 years to evaluate range shifts and stability. N<sub>e</sub> fluctuates with climate across populations, but more genetically diverse northern populations have maintained greater Ne over the late Pleistocene and experienced larger expansions with climatically favorable time periods. Northern populations also experienced larger bottlenecks during the last glacial period which matched the loss of range area near these sites, however, bottlenecks were not sufficient to erode diversity maintained during periods of large N<sub>e</sub>. A genome sampled from an island population indicated a severe postglacial bottleneck, indicating that large recent post-glacial declines are detectable if they have occurred. Genetic diversity was not related to niche stability or glacial-period bottleneck size. Instead, spatial expansions and increased connectivity during favorable climates likely maintain diversity in the north while restriction to high elevations maintains relatively low diversity despite greater stability in southern regions. Results suggest genetic diversity gradients reflect long-term differences in N<sub>e</sub> dynamics and also emphasize the unique effects of isolation on insular habitats for bumble bees. Patterns are discussed in the context of conservation under climate change.</p>
Whole genome demographic models indicate divergent effective population size histories shape contemporary genetic diversity gradients in a montane bumble bee
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Dataset for METAPOPGEN 2.0: a multi-locus genetic simulator to model populations of large size
<p>Multi-locus genetic processes in subdivided populations can be complex and difficult to interpret using theoretical population genetics models. Genetic simulators offer a valid alternative to study multi-locus genetic processes in arbitrarily complex scenarios. However, the use of forward-in-time simulators in realistic scenarios involving high numbers of individuals distributed in multiple local populations is limited by computation time and memory requirements. These limitations increase with the number of simulated individuals. We developed a genetic simulator, <span>MetaPopGen</span> 2.0, to model multi-locus population genetic processes in subdivided populations of arbitrarily large size. It allows for spatial and temporal variation in demographic parameters, age structure, adult and propagule dispersal, variable mutation rates and selection on survival and fecundity. We developed <span>MetaPopGen</span> 2.0 in the R environment to facilitate its use by non-modeler ecologists and evolutionary biologists. We illustrate the capabilities of <span>MetaPopGen</span> 2.0 for studying adaptation to water salinity in the striped red mullet <i>Mullus surmuletus</i>.</p>
Data for: Coevolution fails to maintain genetic variation in a host-parasite model with constant finite population size
<p>Coevolutionary negative frequency-dependent selection has been hypothesized to maintain genetic variation in host and parasites. <br> Despite the extensive literature pertaining to host-parasite coevolution, the dynamics of genetic variation has not been examined in a matching-alleles model (MAM) with a finite population size relative to the expectation under neutral genetic drift alone. The dynamics of the MA coevolution in an infinite population, in fact, suggests that genetic variation in these coevolving populations behaves neutrally. By comparing host heterozygosity to the expectation in a single-species model of neutral genetic drift we find that while this is also largely true in finite populations two additional phenomena arise. First, reciprocal natural selection acting on stochastic perturbations in host and pathogen allele frequencies results in a slight increase or decrease in genetic variation depending on the parameter conditions. Second, following the fixation of an allele in the parasite, selection in the MAM becomes directional, which then rapidly erodes genetic variation in the host. Hence, rather than maintain it, we find that, on average, matching-alleles coevolution depletes genetic variation.</p>
Data from: Phylogeography, population genetics, and distribution modeling reveal vulnerability of Scirpus longii (Cyperaceae) and the Atlantic Coastal Plain Flora to climate change.
A proactive approach to conservation must be predictive, anticipating how habitats will change and which species are likely to decline or prosper. We use composite species distribution modeling to identify suitable habitats for 18 members of the North American Atlantic Coastal Plain Flora (ACPF) since the Last Glacial Maximum and project these into the future. We then use Scirpus longii (Cyperaceae), a globally imperiled ACPF sedge with many of the characteristics of extinction vulnerability, as a case study. We integrate phylogeographic and population genetic analyses and species distribution modeling to develop a broad view of its current condition and prognosis for conservation. We use genotyping-by-sequencing to characterize the genomes of 142 S. longii individuals from twenty populations distributed throughout its range (New Jersey to Nova Scotia). We measure the distribution of genetic diversity in the species and reconstruct its phylogeographic history using SNAPP and RASE. Extant populations of S. longii originated from a single refugium south of the Laurentide ice sheet around 25 thousand years ago. The genetic diversity of S. longii is exceedingly low, populations exhibit little genetic structure, and the species is slightly inbred. Projected climate scenarios indicate that nearly half of extant populations of S. longii will be exposed to unsuitable climate by 2070. Similar changes in suitable habitat will occur for many other northern ACPF species – centers of diversity will shift northward and Nova Scotia may become the last refuges for those species not extinguished.
Code for the population genetic models of the evolution of preference strength
<p>Sexual selection has a rich history of mathematical models that consider why preferences favor one trait phenotype over another (for population genetic models) or what specific trait value is preferred (for quantitative genetic models). Less common is exploration of the evolution of choosiness or preference strength: that is, by how much a trait is preferred. We examine both population and quantitative genetic models of the evolution of preferences, specifically developing "baseline models" of the evolution of preference strength during the Fisher process. Using a population genetic approach based on the classic model of Kirkpatrick (1982), we find selection for stronger and stronger preferences when trait variation is maintained by mutation. However, this force is quite weak and likely to be swamped by drift in moderately-sized populations. In a quantitative genetic model based on Lande (1981), unimodal preferences will generally not evolve to be increasingly strong without bounds when male traits are under stabilizing viability selection, but evolve to extreme values when viability selection is directional. Our results highlight that different shapes of fitness and preference functions lead to qualitatively different trajectories for preference strength evolution ranging from no evolution to extreme evolution of preference strength.</p>
Data from: Phylogeography, population genetics, and distribution modeling reveal vulnerability of Scirpus longii (Cyperaceae) and the Atlantic Coastal Plain Flora to climate change.
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Code for the population genetic models of the evolution of preference strength
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Dataset for METAPOPGEN 2.0: a multi-locus genetic simulator to model populations of large size
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Data for: Coevolution fails to maintain genetic variation in a host-parasite model with constant finite population size
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Data from: Integrating genetic analysis of mixed populations with a spatially-explicit population dynamics model
Inferring the dynamics of populations in time and space is a central challenge in ecology. Intra-specific structure (for example genetically distinct sub-populations or meta-populations) may require methods that can jointly infer the dynamics of multiple populations. This is of particular importance for harvested species, for which management must balance utilization of productive populations with protection of weak ones. Here we present a novel method for simultaneous learning about the spatio-temporal dynamics of multiple populations that combines genetic data with prior information about abundance and movement in an integrated population modelling approach. We apply the Bayesian genetic mixed stock analysis to 17 wild and 10 hatchery-reared Baltic salmon (S. salar) stocks, quantifying uncertainty in stock composition in time and space, and in population dynamics parameters such as migration timing and speed. Our results indicate that the commonly used "equal prior probabilities" assumption may not be appropriate for all mixed stock analyses. Incorporation of prior information about stock abundance and movement resulted in more precise and plausible estimates of mixture compositions in time and space. Inclusion of a population dynamics model also allowed robust interpolation of expected catch composition at areas and times with no genetic observations. The genetic data were informative about stock-specific movement patterns, updating priors for migration path, timing and speed. The model we present here forms the basis for optimizing the spatial and temporal allocation of harvest to support the management of mixed populations of migratory species.
Data from: Population genetics of Setaria viridis, a new model system
An extensive survey of the standing genetic variation in natural populations is among the priority steps in developing a species into a model system. In recent years, green foxtail (Setaria viridis), along with its domesticated form foxtail millet (S. italica), has rapidly become a promising new model system for C4 grasses and bioenergy crops, due to its rapid life cycle, large amount of seed production, and small diploid genome, among other characters. However, remarkably little is known about the genetic diversity in natural populations of this species. In this study, we survey the genetic diversity of a world-wide sample of more than 200 S. viridis accessions, using the genotyping by sequencing technique. Two distinct genetic groups in S. viridis and a third group resembling S. italica were identified, with considerable admixture among the three groups. We find the genetic variation of North American S. viridis correlates with both geography and climate, and is representative of the total genetic diversity in this species. This pattern may reflect several introduction/dispersal events of S. viridis into North America. We also modeled demographic history and show signal of recent population decline in one subgroup. Finally we show linkage disequilibrium decay is rapid (less then 45 kb) in our total sample and slow in genetic subgroups. These results together provide an in-depth understanding of the pattern of genetic diversity of this new model species on a broad geographic scale. They also provide key guidelines for on-going and future work including germplasm preservation, local adaptation, crossing designs and genome-wide association studies.
Data from: Heterogeneity in genetic diversity among non-coding loci fails to fit neutral coalescent models of population history
Inferring aspects of the population histories of species using coalescent analyses of non-coding nuclear DNA has grown in popularity. These inferences, such as divergence, gene flow, and changes in population size, assume that genetic data reflect simple population histories and neutral evolutionary processes. However, violating model assumptions can result in a poor fit between empirical data and the models. We sampled 22 nuclear intron sequences from at least 19 different chromosomes (a genomic transect) to test for deviations from selective neutrality in the gadwall (Anas strepera), a Holarctic duck. Nucleotide diversity among these loci varied by nearly two orders of magnitude (from 0.0004 to 0.029), and this heterogeneity could not be explained by differences in substitution rates. Using two different coalescent methods to infer models of population history and then simulating neutral genetic diversity under these models, we found that the among-locus heterogeneity in nucleotide diversity was significantly higher than expected for these simple models. Defining more complex models of population history demonstrated that a pre-divergence bottleneck was also unlikely to explain this heterogeneity. However, both selection and interspecific hybridization could account for the heterogeneity observed among loci. Regardless of the cause of the deviation, our results illustrate that violating key assumptions of coalescent models can mislead inferences of population history.
Data from: A test of the central-marginal hypothesis using population genetics and ecological niche modelling in an endemic salamander (Ambystoma barbouri)
The central-marginal hypothesis (CMH) predicts that population size, genetic diversity, and genetic connectivity are highest at the core and decrease near the edges of species' geographic distributions. We provide a test of the CMH using three replicated core-to-edge transects that encompass nearly the entire geographic range of the endemic streamside salamander (Ambystoma barbouri). We confirmed that the mapped core of the distribution was the most suitable habitat using ecological niche modelling (ENM) and via genetic estimates of effective population sizes. As predicted by the CMH, we found statistical support for decreased genetic diversity, effective population size, and genetic connectivity from core to edge in western and northern transects, yet not along a southern transect. Based on our niche model, habitat suitability is lower towards the southern range edge, presumably leading to conflicting core-to-edge genetic patterns. These results suggest that multiple processes may influence a species' distribution based on the heterogeneity of habitat across a species' range and that replicated sampling may be needed to accurately test the CMH. Our work also emphasizes the importance of identifying the geographic range core with methods other than using the Euclidean center on a map, which may help to explain discrepancies among other empirical tests of the CMH. Assessing core to edge population genetic patterns across an entire species' range accompanied with ENM can inform our general understanding of the mechanisms leading to species' geographic range limits.
Data from: Population genetic data of a model symbiotic cnidarian system reveal remarkable symbiotic specificity and vectored introductions across ocean basins
The Aiptasia-Symbiodinium symbiosis is a promising model for experimental studies of cnidarian-dinoflagellate associations, yet relatively little is known regarding the genetic diversity of either symbiotic partner. To address this we collected Aiptasia from 17 localities throughout the world and examined the genetic diversity of both anemones and their endosymbionts. Based on newly-developed SCAR markers, Aiptasia consisted of two genetically-distinct populations, one Aiptasia lineage from Florida and a second network of Aiptasia genotypes found at other localities. These populations did not conform to the distributions of described Aiptasia species, suggesting that taxonomic re-evaluation is needed in light of molecular genetics. Associations with Symbiodinium further demonstrated the distinctions among Aiptasia populations. According to 18S-RFLP, ITS2-DGGE, and microsatellite flanker region sequencing, Florida anemones engaged in diverse symbioses predominantly with members of Symbiodinium Clades A and B, but also C, whereas anemones from elsewhere harboured only S. minutum within Clade B. Symbiodinium minutum apparently does not form a stable symbiosis with other hosts, which implies a highly-specific symbiosis. Fine-scale differences among S. minutum populations were quantified using six microsatellite loci. Populations of S. minutum had low genotypic diversity and high clonality (R=0.14). Furthermore, minimal population structure was observed among regions and ocean basins, due to allele and genotype sharing. The lack of genetic structure and low genotypic diversity suggest recent vectoring of Aiptasia and S. minutum across localities. This first ever molecular-genetic study of a globally-distributed cnidarian and its Symbiodinium assemblages reveals host-symbiont specificity and widely-distributed populations in an important model system.
Fig. 8 in Taxonomic revision of the southern hemisphere pygmy forget-me-not group (Myosotis; Boraginaceae) based on morphological, population genetic and climate-edaphic niche modelling data
Fig. 8. Myosotis antarctica subsp. traillii photographs and distribution map. (a) Habit. (b, d) Rosette leaf tips: (b) adaxial and (d) abaxial sides. (c) Flower. (e) Nutlets. (f) Map of georeferenced herbarium specimens observed by J. M. Prebble (35). Whie scale bars: 2 mm; black scale bars: 1 mm. Photo credits: a, e by J. M. Prebble (a: WELT SP100487, Tiwai Point, Southland, South Island; e: WELT SP104518, cultivated ex Mason Bay, Stewart Island). b, c © Te Papa by H. M. Meudt (b: WELT SP090544, Manihi Rd, Taranaki, North Island; c: WELT SP090629, Hukanui, Gisborne, North Island; d: WELT SP090631, Waipuna, Gisborne, North Island).
Fig. 2 in Taxonomic revision of the southern hemisphere pygmy forget-me-not group (Myosotis; Boraginaceae) based on morphological, population genetic and climate-edaphic niche modelling data
Fig. 2. Maps of MaxEnt niche models for pygmy Myosotis in New Zealand and southern South America. (a) Myosotis glauca (light blue circles). (b) M. pygmaea (green circles). (c, h) M. "Volcanic Plateau" (grey triangles). (d) M. brevis (yellow cir-cles). (e) M. drucei (dark blue circles; excluding individuals identified as M. "Volcanic Plateau"). (f) M. drucei (dark blue circles) + M. pygmaea (green circles) + M. "Volcanic Plateau" (grey triangles) (g) M. antarctica (pink circles; Chilean locations), note scale is the same as for maps of New Zealand. a–f use models based on the nine-layer model (see Table 1), whereas g and h are based on the sevenlayer model.
Fig. 5 in Taxonomic revision of the southern hemisphere pygmy forget-me-not group (Myosotis; Boraginaceae) based on morphological, population genetic and climate-edaphic niche modelling data
Fig. 5. Myosotis glauca photographs and distribution map. (a) Habit. (b) Rosette leaves, adaxial and abaxial sides. (c) Calyces, left to right most to least mature. (d) Nutlets. (e) Map of georeferenced herbarium specimens observed by J. M. Prebble (16). White scale bars: 2 mm; black scale bar: 1 mm. Photo credits: all by J. M. Prebble (WELT SP093285, Nevis Valley, Otago).
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Allen Brain Atlas
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Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
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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.