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351 results for “functional genetics”
Data from: Spatial patterns of neutral and functional genetic variation reveal patterns of local adaptation in raccoon (Procyon lotor) populations exposed to raccoon rabies
Local adaptation is necessary for population survival and depends on the interplay between responses to selective forces and demographic processes that introduce or retain adaptive and maladaptive attributes. Host-parasite systems are dynamic, varying in space and time, where both host and parasites must adapt to their ever-changing environment in order to survive. We investigated patterns of local adaptation in raccoon populations with varying temporal exposure to the raccoon rabies virus (RRV). RRV infects approximately 85% of the population when epizootic and has been presumed to be completely lethal once contracted; however, disease challenge experiments and varying spatial patterns of RRV spread suggest some level of immunity may exist. We first assessed patterns of local adaptation in raccoon populations along the eastern seaboard of North America by contrasting spatial patterns of neutral (microsatellite loci) and functional, major histocompatibility complex (MHC) genetic diversity and structure. We explored variation of MHC allele frequencies in light of temporal population exposure to RRV (0-60 years) and specific RRV strains in infected raccoons. Our results revealed high levels of MHC variation (66 DRB exon 2 alleles) and pronounced genetic structure relative to neutral microsatellite loci, indicative of local adaptation. We found a positive association linking MHC genetic diversity and temporal RRV exposure, but no association with susceptibility and resistance to RRV strains. These results have implications for landscape epidemiology studies seeking to predict the spread of RRV and present an example of how population demographics influence the degree to which populations adapt to local selective pressures.
Data from: Optimizing the trade-off between spatial and genetic sampling efforts in patchy populations: towards a better assessment of functional connectivity using an individual-based sampling scheme
Genetic data are increasingly used in landscape ecology for the indirect assessment of functional connectivity, i.e. the permeability of landscape to movements of organisms. Among available tools, matrix correlation analyses (e.g. Mantel tests or mixed models) are commonly used to test for the relationship between pairwise genetic distances and movement costs incurred by dispersing individuals. When organisms are spatially clustered, a population-based sampling scheme (PSS) is usually performed, so that a large number of genotypes can be used to compute pairwise genetic distances on the basis of allelic frequencies. Because of financial constraints, this kind of sampling scheme implies a drastic reduction in the number of sampled aggregates, thereby reducing sampling coverage at the landscape level. We used matrix correlation analyses on simulated and empirical genetic datasets to investigate the efficiency of an individual-based sampling scheme (ISS) in detecting isolation-by-distance and isolation-by-barrier patterns. Provided that pseudo-replication issues are taken into account (e.g. through restricted permutations in Mantel tests), we showed that the use of inter-individual measures of genotypic dissimilarity may efficiently replace inter-population measures of genetic differentiation: the sampling of only three or four individuals per aggregate may be sufficient to efficiently detect specific genetic patterns in most situations. The ISS proved to be a promising methodological alternative to the more conventional PSS, offering much flexibility in the spatial design of sampling schemes and ensuring an optimal representativeness of landscape heterogeneity in data, with few aggregates left unsampled. Each strategy offering specific advantages, a combined use of both sampling schemes is discussed.
Is species richness mediated by functional and genetic divergence? A global analysis in birds
<p class="MsoNormal">Unravelling why species richness varies shows such dramatic spatial variation is an ongoing challenge. Common to many theories is that increasing species richness requires a compensatory trade-off on an axis of species' ecology. Spatial variation in species richness may also affect genetic diversity if large numbers of coexisting, related species result in smaller population sizes. Here, we test whether increasing species richness results in differential occupation of morphospace by the constituent species, or decreases species' genetic diversity. We test for two potential mechanisms of morphological accommodation: denser packing in ecomorphological space, and expansion of the space. We then test whether species differ in their nucleotide diversity depending on allopatry or sympatry with relatives, indicative of potential genetic consequences of coexistence that would reduce genetic diversity in sympatry. We ask these questions in a spatially explicit framework, using a global database of avian functional trait measurements in combination with >120,000 sequences downloaded from GenBank. We find that higher species richness within families is not systematically correlated with either packing in morphological space or overdispersion but, at the Class level, we find a general positive relationship between packing and species richness, but that packing is comparatively greater in tropical points relative to their species richness. We find limited evidence that geographical co-occurrence with closely related species or tropical distributions decreases nucleotide diversity of nuclear genes; however, this requires further analysis. Our results suggest that avian families can accumulate species regionally with minimal tradeoffs or cost, implying that external biotic factors do not limit species richness.</p>
Identification of genetic loci and functional analysis of candidate gene, OsCycB1;5 associated with seed callus induction in rice (Oryza sativa L.)
Open the record for dataset details and reuse information.
How long is 3 kilometres for a butterfly? Ecological constraints and functional traits explain high mitochondrial genetic diversity between Sicily and the Italian Peninsula
<p>1. Populations inhabiting Mediterranean islands often show contrasting genetic lineages, even on islands that were connected to the mainland during glacial maxima. This pattern is generated by forces acting in historical and contemporary times. Understanding these phenomena requires comparative studies relating genetic structure, functional traits and dispersal constraints.</p> <p>2. Using as a model the butterfly species living across the Messina strait separating Sicily from the Italian Peninsula (3 km wide), we aimed to unravel the mechanisms limiting the dispersal of matrilines across a narrow sea strait and producing genetic differentiation. </p> <p>3. We analysed the mitochondrial COI gene of 84 butterfly species out of 90 documented in Sicily and compared them with populations from the neighbouring southern Italian Peninsula (1398 sequences) and from the entire Palearctic region (8093 sequences). For each species, we regressed 13 functional traits and two ecological constraints to dispersal (winds experienced at the strait and climatic suitability) against genetic differentiation between Sicily and Italian Peninsula to understand the factors limiting dispersal.</p> <p>4. More than a third of the species showed different haplogroups across the strait and most of them also represented endemic haplogroups for this island. One fifth of Sicilian populations (and 32.3% of endemic lineages) had their closest relatives in distant areas, instead of the neighbouring Italian Peninsula, which suggests high relictuality. Haplotype diversity was significantly explained by length of the flight period, an intrinsic phenology trait, while genetic differentiation was explained by both intrinsic traits (wingspan and degree of generalism) and contemporary local constraints (winds experienced at the strait and climatic suitability).</p> <p>5. A relatively narrow sea strait can produce considerable differentiation among butterfly matrilines and this phenomenon showed a largely deterministic fingerprint. Because of unfavourable winds, populations of the less dispersive Sicilian butterflies tended to differentiate into endemic variants or to maintain relict populations. Understanding these phenomena required the integration of DNA sequences, species traits and physical constraints for a large taxon at continental scale. Future studies may reveal if the patterns here shown for mitochondrial DNA are also reflected in the nuclear genome or, alternatively, are the product of limited female dispersal.</p>
Data from: Replicated landscape genetic and network analyses reveal wide variation in functional connectivity for American pikas
Landscape connectivity is essential for maintaining viable populations, particularly for species restricted to fragmented habitats or naturally arrayed in metapopulations and facing rapid climate change. The importance of assessing both structural connectivity (the physical distribution of favorable habitat patches) and functional connectivity (how species move among habitat patches) for managing such species is well understood. However, the degree to which functional connectivity for a species varies among landscapes, and the resulting implications for conservation, have rarely been assessed. We used a landscape genetics approach to evaluate resistance to gene flow and, thus, to determine how landscape and climate-related variables influence gene flow for American pikas (Ochotona princeps) in eight federally managed sites in the western United States. We used those empirically-derived, individual-based landscape resistance models in conjunction with predictive occupancy models to generate patch-based network models describing functional landscape connectivity. Metareplication across landscapes enabled identification of limiting factors for dispersal that would not otherwise have been apparent. Despite the cool microclimates characteristic of pika habitat, south-facing aspects consistently represented higher resistance to movement, supporting the previous hypothesis that exposure to relatively high temperatures may limit dispersal in American pikas. We found that other barriers to dispersal included areas with a high degree of topographic relief, such as cliffs and ravines, as well as streams and distances greater than one to four kilometers depending on the site. Using the empirically-derived network models of habitat patch connectivity, we identified habitat patches that were likely disproportionately important for maintaining functional connectivity, areas in which habitat appeared fragmented, and locations that could be targeted for management actions to improve functional connectivity. We concluded that climate change, besides influencing patch occupancy as predicted by other studies, may alter landscape resistance for pikas, thereby influencing functional connectivity through multiple pathways simultaneously. Spatial autocorrelation among genotypes varied across study sites and was largest where habitat was most dispersed, suggesting that dispersal distances increased with habitat fragmentation, up to a point. This study demonstrates how landscape features linked to climate can affect functional connectivity for species with naturally fragmented distributions, and reinforces the importance of replicating studies across landscapes.
Data from: Standing genetic diversity and selection at functional gene loci are associated with differential invasion success in two non-native fish species
Invasive species are expected to experience a unique combination of high genetic drift due to demographic factors while also experiencing strong selective pressures. The paradigm that reduced genetic diversity should limit the evolutionary potential of invasive species and thus their potential for range expansion has received little empirical support, possibly due to the choice of genetic markers. Our goal was to test for effects of genetic drift and selection at functional genetic markers as they relate to the invasion success of two paired invasive goby species, one widespread (successful) and one with limited range expansion (less successful). We genotyped fish using two marker types: single nucleotide polymorphisms (SNPs) in known-function, protein-coding genes and microsatellites to contrast the effects of neutral genetic processes. We identified reduced allelic variation in the invaded range for the less-successful tubenose goby. SNPs putatively under selection were responsible for the observed differences in population structure between marker types for round goby (successful) but not tubenose goby (less successful). A higher proportion of functional loci experienced divergent selection for round goby, suggesting increased evolutionary potential in invaded ranges may be associated with round goby's greater invasion success. Genes involved in thermal tolerance were divergent for round goby populations but not tubenose goby, consistent with the hypothesis that invasion success for fish in temperate regions is influenced by capacity for thermal tolerance. Our results highlight the need to incorporate functional genetic markers in studies to better assess evolutionary potential for the improved conservation and management of species.
Challenges of ELA-based Function Evolution using Genetic Programming - Reproducability files
<p>This repository contains the data and code for the paper "Challenges of ELA-based Function Evolution using Genetic<br> Programming"</p> <p> </p> <p>This repository consists of separated folders, which contain the following data:</p> <p>## Code:</p> <p>This is the main code used to run the GP functions. The main executable is 'main_gp.py', which executes a single run of the GP system (based on the passed-in argument, which is an index from 0-71 in our experiments).</p> <p>The data for the BBOB functions are generated using the 'preliminary' folder and the 'get_ela_preliminary.py' file.</p> <p> </p> <p>## Data_GP:</p> <p>This contains the full logs from each GP run, separated by target function and dimension.</p> <p> </p> <p>## data_random_func:</p> <p>This contains the same kind of data but for the Random Function Generator.</p> <p> </p> <p>## Reproducibility:</p> <p>This contains all code used to analyse and visualize the resulting data. The notebook is structured in the same way as the paper, separated by figure.</p>
Source data for "Genetically encoding multiple functionalities into extracellular vesicles for the targeted delivery of biologics to T cells"
<p>Source Data include all reported experimental data and plasmid maps for all plasmids generated in the associated publication, "Genetically encoding multiple functionalities into extracellular vesicles for the targeted delivery of biologics to T cells," which is in press at Nature Biomedical Engineering.</p>
The Genetics of Adipose Tissue Function and Its Link to Type 2 Diabetes and Heart Disease
ClinicalTrials.gov study NCT04040595. IPD Sharing: NO. Countries: 1. Publications: 9.
Genetic Risk for Attention Deficit Hyperactivity Disorder Expressed in Brain Functioning
ClinicalTrials.gov study NCT00143832. IPD Sharing: Not stated. Countries: 1. Publications: 2.
Precise Stratification of Genetic Risk of Ovarian Function Impairment
ClinicalTrials.gov study NCT05665010. IPD Sharing: UNDECIDED. Countries: 1. Publications: 1.
Genetic and Functional Analysis of Craniometaphyseal Dysplasia (CMD)
ClinicalTrials.gov study NCT01630460. IPD Sharing: Not stated. Countries: 1. Publications: 11.
Monocentric Registry to Investigate the Role of Platelet Function, Platelet Genetics, Proteomics and Metabonomics in Heart Disease
ClinicalTrials.gov study NCT01417884. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Bone Marrow Cell Engraftment of the Uterus and Genetic Studies of Reproductive Functioning
ClinicalTrials.gov study NCT01468935. IPD Sharing: Not stated. Countries: 1. Publications: 3.
Genetic and Functional Analysis of Aplasia Cutis Congenital (ACC)
ClinicalTrials.gov study NCT01630421. IPD Sharing: Not stated. Countries: 1. Publications: 1.
Genetic Expression in Schizophrenics Treated With SSRI Augmentation: Relationship to Clinical and Cognitive Function
ClinicalTrials.gov study NCT00645580. IPD Sharing: Not stated. Countries: 1. Publications: 28.
Effect of Functional Genetic Polymorphisms on Brain Morphology and Function
ClinicalTrials.gov study NCT01035723. IPD Sharing: Not stated. Countries: 1. Publications: 3.
Clinical, Functional, Immunological and Genetic Factors on the Severity of the Course of Coronavirus Infection
ClinicalTrials.gov study NCT04987853. IPD Sharing: YES. Countries: 1. Publications: 17.
Ioflupane I123 (DaTSCAN) and Positron Emission Tomography-computed Tomography Fludeoxyglucose (PET-CT FDG) to Assess Brain Function of Parkinson Patients With Different Genetic Characteristics
ClinicalTrials.gov study NCT01089283. IPD Sharing: Not stated. Countries: 1. Publications: 13.
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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.