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111 results for “genotype by environment”
Data for: The relative impact of parental and current environment on plant transcriptomes depends on type of stress and genotype
<p>Through developmental plasticity, an individual organism integrates influences from its immediate environment with those due to the environment of its parents. While both effects on phenotypes are well documented, their relative impact has been little studied in natural systems, especially at the level of gene expression. We examined this issue in four genotypes of the annual plant <em>Persicaria maculosa</em> by varying two key resources light and soil moisture in both generations. Transcriptomic analyses showed that the relative effects of parent and offspring environment on gene expression (i.e., the number of differentially expressed transcripts, DETs) varied both for the two types of resource stress and among genotypes. For light, immediate environment induced more DETs than parental environment for all genotypes (although the precise proportion of parental versus immediate DETs varied among genotypes). By contrast, the relative effect of soil moisture varied dramatically among genotypes, from 8-fold more DETs due to parental than immediate conditions to 10-fold fewer. These findings provide evidence at the transcriptome level that the relative impacts of parental and immediate environment on the developing organism may depend on the environmental factor and vary strongly among genotypes, providing potential for the interplay of these developmental influences to evolve.</p>
Static allometries of caste-associated traits vary with genotype but not environment in the clonal raider ant
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Phenotypic plasticity, heritability, and genotype-by-environment interactions in an insect dispersal polymorphism
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Data from: A temporally intensive survey of bacterial communities of Brassica napus genotypes grown in three environments
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Genotype-environment interaction and the maintenance of genetic variation: an empirical study of Lobelia inflata (Campanulaceae)
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Genotype-environment interaction reveals varied developmental responses to unpredictable host phenology in a tropical insect
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The potential for genotype-by-environment interactions to maintain genetic variation in a model legume–rhizobia mutualism
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Data from: Genotyping by sequencing and genome–environment associations in wild common bean predict widespread divergent adaptation to drought
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Data for: The relative impact of parental and current environment on plant transcriptomes depends on type of stress and genotype
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Combined genotype and phenotype analyses reveal patterns of genomic adaptation to local environments in the subtropical oak Quercus acutissima
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Unraveling the roles of genotype and environment in the expression of plant defense phenotypes
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Data from: Hybrid enrichment of adaptive variation revealed by genotype-environment associations in montane sedges
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Environment and genotype influence on Populus tremuloides condensed tannin composition
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Data from: Lack of genotype-by-environment interaction suggests limited potential for evolutionary changes in plasticity in the eastern oyster, Crassostrea virginica
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Data from: Genotype and social environment influence female-female interactions in a non-social insect
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Patterns of genotype-environment association in the eastern North American yellow birch (<em>Betula alleghaniensis</em> Britt.)
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Genotype-environment interactions shape leaf functional traits of cacao in agroforests
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Data from: Proteomic analysis of barley mapping population subjected to drought identifies proteins with genotype×environment interaction and pQTLs
Drought is one of the major abiotic stresses negatively influencing crop yield and is a serious issue in modern agriculture. To achieve further substantial crop improvements in terms of drought resistance it is necessary to incorporate scientific results into breeding strategies. However, most of the data on plant drought responses arises mostly from small-scale studies and, therefore, its use in breeding programs is very limited. Here, we present the results of the large-scale proteomic analysis performed on barley recombinant inbred lines (RILs) and their parental genotypes subjected to drought, applied shortly before tillering. The conducted proteomic analyses enabled us to monitor drought-induced proteome changes in leaf and root tissue, and to identify proteins that responded to drought in a genotype-specific manner, for instance Rubisco activase, luminal binding protein, phosphoglycerate mutase, glutathione S-transferase, heat shock proteins as well as enzymes involved in phenylpropanoid biosynthesis. We also demonstrated feasibility of incorporating proteomic data resulting from large-scale study into genetic linkage analysis, which constitutes a fundament in biotechnology-driven breeding strategies.
Data from: Field measurements of genotype by environment interaction for fitness caused by spontaneous mutations in Arabidopsis thaliana
As the ultimate source of genetic diversity, spontaneous mutation is critical to the evolutionary process. The fitness effects of spontaneous mutations are almost always studied under controlled laboratory conditions rather than under the evolutionarily relevant conditions of the field. Of particular interest is the conditionality of new mutations - i.e., is a new mutation harmful regardless of the environment in which it is found? In other words, what is the extent of genotype-environment interaction for spontaneous mutations? We studied the fitness effects of 25 generations of accumulated spontaneous mutations in Arabidopsis thaliana in two geographically widely separated field environments, in Michigan and Virginia. At both sites, mean total fitness of MA lines exceeded that of the ancestors, contrary to the expected decrease in the mean due to new mutations but in accord with prior work on these MA lines. We observed genotype-environment interactions in the fitness effects of new mutations, such that the effects of mutations in Michigan were a poor predictor of their effects in Virginia and vice versa. In particular, mutational variance for fitness was much larger in Virginia compared to Michigan. This strong genotype-environment interaction would increase the amount of genetic variation maintained by mutation-selection balance.
Data from: Cell wall composition and bioenergy potential of rice straw tissues are influenced by environment, tissue type, and genotype
Breeding has transformed wild plant species into modern crops, increasing the allocation of their photosynthetic assimilate into grain, fiber, and other products for human use. Despite progress in increasing the harvest index, much of the biomass of crop plants is not utilized. Potential uses for the large amounts of agricultural residues that accumulate are animal fodder or bioenergy, though these may not be economically viable without additional efforts such as targeted breeding or improved processing. We characterized leaf and stem tissue from a diverse set of rice genotypes (varieties) grown in two environments (greenhouse and field) and report bioenergy-related traits across these variables. Among the 16 traits measured, cellulose, hemicelluloses, lignin, ash, total glucose, and glucose yield changed across environments, irrespective of the genotypes. Stem and leaf tissue composition differed for most traits, consistent with their unique functional contributions and suggesting that they are under separate genetic control. Plant variety had the least influence on the measured traits. High glucose yield was associated with high total glucose and hemicelluloses, but low lignin and ash content. Bioenergy yield of greenhouse-grown biomass was higher than field-grown biomass, suggesting that greenhouse studies overestimate bioenergy potential. Nevertheless, glucose yield in the greenhouse predicts glucose yield in the field (ρ = 0.85, p < 0.01) and could be used to optimize greenhouse (GH) and field breeding trials. Overall, efforts to improve cell wall composition for bioenergy require consideration of production environment, tissue type, and variety.
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Allen Brain Atlas
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International Brain Laboratory public data
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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.