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12 results for “Quantitative History”
Quantitative trait locus mapping reveals an independent genetic basis for joint divergence in leaf function, life-history, and floral traits between scarlet monkeyflower (Mimulus cardinalis) populations
<p><b>PREMISE </b></p> <p>Across taxa, vegetative and floral traits that vary along a fast-slow life-history axis are often correlated with leaf functional traits arrayed along the leaf economics spectrum, suggesting a constrained set of adaptive trait combinations. Such broad-scale convergence may arise from genetic constraints imposed by pleiotropy (or tight linkage) within species, or from natural selection alone. Understanding the genetic basis of trait syndromes and their components is key to distinguishing these alternatives and predicting evolution in novel environments.</p> <p><b>METHODS </b></p> <p>We used a line-cross approach and quantitative trait locus (QTL) mapping to characterize the genetic basis of twenty leaf functional/physiological, life history, and floral traits in hybrids between annualized and perennial populations of scarlet monkeyflower (<i>Mimulus cardinalis</i>).</p> <p><b>RESULTS </b></p> <p>We mapped both single and multi-trait QTLs for life history, leaf function and reproductive traits, but found no evidence of genetic co-ordination across categories. A major QTL for three leaf functional traits (thickness, photosynthetic rate, and stomatal resistance) suggests that a simple shift in leaf anatomy may be key to adaptation to seasonally dry habitats.</p> <p><b>CONCLUSIONS </b></p> <p>Our results suggest that the co-ordination of resource-acquisitive leaf physiological traits with a fast life history and more selfing mating system results from environmental selection rather than functional or genetic constraint. Independent assortment of distinct trait modules, as well as a simple genetic basis to leaf physiological traits associated with drought escape, may facilitate adaptation to changing climates. </p>
Quantitative trait locus mapping reveals an independent genetic basis for joint divergence in leaf function, life-history, and floral traits between scarlet monkeyflower (Mimulus cardinalis) populations
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Data from: Assessing the effects of quantitative host resistance on the life-history traits of sporulating parasites with growing lesions
Assessing life-history traits of parasites on resistant hosts is crucial in evolutionary ecology. In the particular case of sporulating pathogens with growing lesions, phenotyping is difficult because one needs to disentangle properly pathogen spread from sporulation. By considering Phytophthora infestans on potato, we use mathematical modelling to tackle this issue and refine the assessment pathogen response to quantitative host resistance. We elaborate a parsimonious leaf-scale model by convolving a lesion growth model and a sporulation function, after a latency period. This model is fitted to data obtained on two isolates inoculated on three cultivars with contrasted resistance level. Our results confirm a significant host-pathogen interaction on the various estimated traits, and a reduction of both pathogen spread and spore production, induced by host resistance. Most interestingly, we highlight that quantitative resistance also changes the sporulation function, whose mode is significantly time-lagged.This alteration of the infectious period distribution on resistant hosts may have strong impacts on the dynamics of parasite populations, and should be considered when assessing the durability of disease control tactics based on plant resistance management. This inter-disciplinary work also supports the relevance of mechanistic models for analysing phenotypic data of plant-pathogen interactions.
Assessing the Stability of Uterine Scar Tissue in Women With Previous History of Caesarean Section Using Multimodal Analyses of the Lower Uterine Segment Including Quantitative Sonography
ClinicalTrials.gov study NCT02827591. IPD Sharing: NO. Countries: 1. Publications: 2.
Data from: Genetic variation in HIF signaling underlies quantitative variation in physiological and life history traits within lowland butterfly populations
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Data from: Assessing the effects of quantitative host resistance on the life-history traits of sporulating parasites with growing lesions
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Data from: Quantitative genetics of immunity and life history under different photoperiods
Insects with complex life-cycles should optimize age and size at maturity during larval development. When inhabiting seasonal environments, organisms have limited reproductive periods and face fundamental decisions: individuals that reach maturity late in season have to either reproduce at a small size or increase their growth rates. Increasing growth rates is costly in insects due to higher juvenile mortality, decreased adult survival, or increased susceptibility to parasitism by bacteria and viruses via compromised immune function. Environmental changes such as seasonality can also alter the quantitative genetic architecture. Here we explore the quantitative genetics of life history and immunity traits under two experimentally induced seasonal environments in the cricket Gryllus bimaculatus. Seasonality affected the life history but not the immune phenotypes. Individuals under decreasing day length developed slower and grew to a bigger size. We found ample additive genetic variance and heritability for components of immunity (haemocyte densities, proPhenoloxidase activity, resistance against Serratia marcescens), and for the life history traits, age and size at maturity. Despite genetic covariance among traits, the structure of G was inconsistent with genetically based trade-off between life history and immune traits (e.g., a strong positive genetic correlation between growth rate and haemocyte density was estimated). However, conditional evolvabilities support the idea that genetic covariance structure limits the capacity of individual traits to evolve independently. We found no evidence for GxE interactions arising from the experimentally induced seasonality.
Data from: Quantitative genetics of immunity and life history under different photoperiods
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Data from: Spatially and temporally varying selection on intrapopulation quantitative trait loci for a life history trade-off in Mimulus guttatus
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A quantitative model for characterizing the evolutionary history of mammalian gene expression
GEO Series GSE106077. Monodelphis domestica; Dasypus novemcinctus; Canis lupus familiaris; Mustela putorius furo; Oryctolagus cuniculus. 33 samples. Type: Expression profiling by high throughput sequencing.
A Qualitative and Quantitative Analysis on the Living History of Survivors From Charcoal-burning Suicide
ClinicalTrials.gov study NCT02068534. IPD Sharing: Not stated. Countries: 1. Publications: 0.
The VIDYA Study-designed to Determine if Patients With a History of Basal Cell Carcinoma Are More Inclined to Return for Follow-up if Their Risk of a Subsequent Basal Cell Carcinoma is Quantitated.
ClinicalTrials.gov study NCT04093401. IPD Sharing: NO. Countries: 0. Publications: 0.
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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.