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1,155 results for “loci”
FIGURE 12 in A broadly sampled 3-loci plastid phylogeny of Atraphaxis (Polygoneae, Polygonoideae, Polygonaceae) reveals new taxa: II. Atraphaxis selengensis spec. nov., and A. davurica Jaub. & Spach from Russian Transbaikalia
FIGURE 12. Distributional map for Atraphaxis species from Russian Transbaikalia:
Stronger population differentiation at infection-sensing than infection-clearing innate immune loci in songbirds: different selective regimes for different defenses
<p><span><span><span><span><span><span><span><span><span><span><span>Parasite-mediated selection is widespread at loci involved in immune defence, but different defences may experience different selective regimes. For defences involved in clearing infections, purifying selection favouring a single most efficacious allele likely predominates. However, for defences involved in sensing and recognizing infections, evolutionary arms races may make positive selection particularly important. This could manifest primarily within populations (e.g., balancing selection maintaining variation) or among them (e.g., spatially varying selection enhancing population differences in allele frequencies). We genotyped three toll-like receptors (TLR; involved in sensing infections) and three avian beta-defensins (involved in clearing infections) in 96 song sparrows (<i>Melospiza melodia</i>) from three breeding populations that differ in disease resistance. Variation-based indicators of selection (proportion of variable sites, proportion of nonsynonymous SNPs, proportion of sites bearing signatures of positive or purifying selection, rare allele frequencies) did not differ appreciably between the two locus types. However, differentiation was generally higher at infection-sensing than infection-clearing loci. Allele frequencies differed markedly at TLR3, driven by a variant predicted to alter protein function. Geographically structured variants at infection-sensing loci may reflect local adaptation to spatially heterogeneous parasite communities. Selective regimes experienced by infection-sensing versus infection-clearing loci may differ primarily due to parasite-mediated population differentiation.</span></span></span></span></span></span></span></span></span></span></span></p>
High resolution imaging as a tool for identifying quantitative trait loci that regulate photomorphogenesis in Arabidopsis thaliana
<p>A primary component of seedling establishment is the photomorphogenic response as seedlings emerge from the soil. This process is characterized by a reduced growth rate in the hypocotyl, increased root growth, opening of the apical hook, and expansion of the cotyledons as photosynthetic organs. While fundamental to plant success, the photomorphogenic response can be highly variable. Additionally, studies of <i>Arabidopsis thaliana</i> are made difficult by subtle differences in growth rate between individuals. High-resolution imaging and computational processing have emerged as useful tools for quantification of such phenotypes. This study sought to: 1) develop an imaging methodology which could capture changes in growth rate as seedlings transition from darkness to blue light in real time, and 2) apply this methodology to single-QTL analysis using the Cvi x L<i>er</i> RIL mapping population. Significant differences in the photomorphogenic response were observed between the parent lines and analysis of 158 RILs revealed a wide range of growth rate phenotypes. QTL analysis detected significant loci associated with dark growth rate on chromosome 5 and significant loci associated with light growth rate on chromosome 2. Candidate genes associated with these loci, such as the previously characterized <i>ER</i> locus, highlight the application of this approach for QTL analysis. Genetic analysis of Landsberg lines without the <i>erecta </i>mutation also supports a role for ER in modulating the photomorphogenic response, consistent with previous QTL analyses of this population. Strengths and limitations of this methodology are presented, as well as means of improvement.</p>
FIGURE 2 in Hundreds of nuclear and plastid loci yield novel insights into orchid relationships.
FIGURE 2. Species-coalescence tree of the orchid family inferred from 292 maximum likelihood (ML) gene trees. Pie diagrams at nodes represent quartet support values, with q1 (deep blue portion) representing the proportion of gene tree quartets that support the main (depicted) branch, q2 (blue portion) representing the proportion of quartets supporting the first alternative branch, and q3 (gray portion) representing the proportion of quartets supporting the second alternative branch (an explanation of how the quartet values are computed is available at https://github.com/smira rab/ASTRAL/blob/master/astral-tutorial.md). (Inset): ML tree derived from a supermatrix of 292 low copy nuclear genes. Terminal names with alternative positions to those obtained by the species-tree coalescence analysis are highlighted in bold and red. Adetailed version of the tree is presented in Appendix S4.
Double digest RADseq loci using standard Illumina indexes improve deep and shallow phylogenetic resolution of Lophodermium, a widespread fungal endophyte of pine needles
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Data from: Canonical correlations reveal adaptive loci and phenotypic responses to climate in perennial ryegrass
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Data from: Evolution of sex determination loci in Atlantic salmon
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Data from: Molecular evolution of shattering loci in U.S. weedy rice
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Data from: Molecular evidence that the genes for dioecism and monoecism in Spinacia oleracea L. are located at different loci in a chromosomal region
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Data from: A universal mechanism generating clusters of differentiated loci during divergence-with-migration
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Microsatellite genotype data from seven loci for a phylogeographic/population genetic study of the South African endemic freshwater crab Potamonautes lividus sampled from eight localities in the KwaZulu-Natal and Eastern Cape provinces in South Africa
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Data from: Introgression study reveals two quantitative trait loci involved in interspecific variation in memory retention among Nasonia wasp species
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Data from: Paths to selection on life history loci in different natural environments across the native range of Arabidopsis thaliana
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Data from: Selection on outlier loci and their association with adaptive phenotypes in Littorina saxatilis contact zones
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Data from: Genetic loci inherited from hens lacking maternal behaviour both inhibit and paradoxically promote this behaviour
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Data from: Genetic mapping of novel loci affecting canine blood phenotypes
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Data from: New Zealand tree and giant wētā (Orthoptera) transcriptomics reveal divergent selection patterns in metabolic loci
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Data from: Selective breeding and selection mapping using a novel wild-derived heterogeneous stock mice revealed two closely-linked loci for tameness
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Data from: The MC1R and ASIP coat color loci may impact behavior in the horse
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Data from: Loci contributing to boric acid toxicity in two reference populations of Drosophila melanogaster
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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.