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15,277 results for “GENETICS”
Data accompanying Polyphenisms and polymorphisms: genetic variation in plasticity and color variation within and among bluefin killifish populations
<p>The presence of stable color polymorphisms within populations begs the question of how genetic variation is maintained. Consistent variation among populations in coloration, especially when correlated with environmental variation, raises questions about whether environmental conditions affect either the fulcrum of those balanced polymorphisms, the plastic expression of coloration, or both. Color patterns in male bluefin killifish provoke both types of questions. Red and yellow morphs are common in all populations. Blue males are more common in tannin-stained swamps relative to clear springs. Here we combined crosses with a manipulation of light to explore how genetic variation and phenotypic plasticity shape these patterns. We found that the variation in coloration is attributable mainly to two axes of variation: (1) a red-yellow axis with yellow being dominant to red, and (2) a blue axis that can override red-yellow and is controlled by genetics, phenotypic plasticity, and genetic variation for phenotypic plasticity. The variation among populations in plasticity suggests it is adaptive in some populations but not others. The variation among sires in plasticity within the swamp population suggests balancing selection may be acting not only on the red-yellow polymorphism but also on plasticity for blue coloration.</p>
Data and Software for "Complex Dynamics in a Synchronized Cell-Free Genetic Clock"
<p>Contains raw data, analysis scripts, simulation scripts, device operation software for the publication: "Complex Dynamics in a Synchronized Cell-Free Genetic Clock".</p>
Fig. 7 in Genetic And Morphological Variability And Differentiation Of Freshwater Mussels (Bivavia, Unionidae, Anodontinae) In Ukraine
Fig. 7. Micrographs of the outer edge of the inhalant siphon in mussels: 1 — A. cygnea (r. Derevychka); 2 — A. anatina (Lyutsymer lake); 3 — P. complanata (r. Uzh); 4 — S. woodiana (r. Danube). Рис. 7. Микрофотографии наружного края вводных сифонов у беззубок: 1 — A. cygnea (р. Деревичка); 2 — A. anatina (оз. Люцимер); 3 — P. complanata (р. Уж); 4 — S. woodiana (р. Дунай.
Fig. 5 in Genetic And Morphological Variability And Differentiation Of Freshwater Mussels (Bivavia, Unionidae, Anodontinae) In Ukraine
Fig. 5. The distribution of mussels from four species in the space of canonical variables made by conchological characters. N o t e. Еxtrapolation of specimens distribution on probability level is p <0.05. Рис. 5. Распределение особей четырёх видов беззубок в пространстве канонических переменных, построенных по конхиологическим признакам. П р и м е ч а н и е. Экстраполяция распределения особей проведена на уровне вероятности p <0,05.
Fig. 2 in Genetic And Morphological Variability And Differentiation Of Freshwater Mussels (Bivavia, Unionidae, Anodontinae) In Ukraine
Fig. 2. UPGMA phenogram of genetic distances (Nei, 1972) between mussel species and populations. N o t e. Aa — A. anatina, Ac — A. cygnea, Pc — P. complanata, Sw — S. woodiana. Riwer systems: 1 — Danube, 2 — r. Tysa, 3 — Upper Dniester, 4 — Lower Dniester, 5 — r. Ingul, 6 — r. Western Bug, 7 — r. Prypyat, 8 — Upper Dnipro, 9 — r. Ros, 10 — r. Psel, 11 — r. Siversky Donets, 12 — r. Salgyr.
Fig. 1 in Genetic And Morphological Variability And Differentiation Of Freshwater Mussels (Bivavia, Unionidae, Anodontinae) In Ukraine
Fig. 1. Main places of material collection: 1 — r. Danube, 2 — r. Tysa, 3 — Upper Dniester, 4 — Lower Dniester, 5 — r. Ingul, 6 — r. Western Bug, 7 — r. Prypyat, 8 — Upper Dnipro, 9 — r. Ros, 10 — r. Psel, 11 — r. Siversky Donets, 12 — r. Salgyr.
Fig. 4 in Genetic And Morphological Variability And Differentiation Of Freshwater Mussels (Bivavia, Unionidae, Anodontinae) In Ukraine
Fig. 4. UPGMA phenogram of genetic distances (Tamura et al., 2004, 2011) between specimens of four Anodontinae species made by homologous sequences of two homologous loci (COI and 16S). Рис. 4. UPGMA фенограмма генетических дистанций (Tamura et al., 2004, 2011), построенная по гомологичным последовательностям двух локусов (COI и 16S) между отдельными особями четырёх видов Anоdontinae.
Fig. 3 in Genetic And Morphological Variability And Differentiation Of Freshwater Mussels (Bivavia, Unionidae, Anodontinae) In Ukraine
Fig. 3. Geographic variation of Mdh-1 locus in P. complanata populations in Ukraine (Mdh-1110 — filled with black, Mdh-1120 — filled with grey).
Fig. 6 in Genetic And Morphological Variability And Differentiation Of Freshwater Mussels (Bivavia, Unionidae, Anodontinae) In Ukraine
Fig. 6. The umbonal structure of the shell in molluscs from subfamily Anodontinae: 1 — A. cygnea; 2 — A. anatina; 3 — P. complanata; 4 — S. woodiana. Рис. 6. Структура вершины раковины моллюсков подсемейства Anodontinae: 1 — A. cygnea; 2 — A. anatina; 3 — P. complanata; 4 — S. woodiana.
Рис. 3. Географическая изменчивость локуса Mdh-1 в популяциях P. complanata в пределах Украины (Mdh-1110 — заполнение чёрным цветом, Mdh-1120 — серым). in Genetic And Morphological Variability And Differentiation Of Freshwater Mussels (Bivavia, Unionidae, Anodontinae) In Ukraine
Рис. 3. Географическая изменчивость локуса Mdh-1 в популяциях P. complanata в пределах Украины (Mdh-1110 — заполнение чёрным цветом, Mdh-1120 — серым).
Рис. 2. UPGMA — фенограма генетических дистанций (Nei, 1972) между видами и популяциями двустворчатых моллюсков. П р и м е ч а н и е. Aa — A. anatina, Ac — A. cygnea, Pc — P. complanata, Sw — S. woodiana. Речные системы: 1 — Дунай, 2 — р. Тиса, 3 — Верхний Днестр, 4 — Нижний Днестр, 5 — р. Ингул, 6 — р. Западный Буг, 7 — р. Припять, 8 — р. Верхний Днепр, 9 — р. Рось, 10 — р. Псёл, 11 — р. Северский Донец, 12 — р. Салгир. in Genetic And Morphological Variability And Differentiation Of Freshwater Mussels (Bivavia, Unionidae, Anodontinae) In Ukraine
Рис. 2. UPGMA — фенограма генетических дистанций (Nei, 1972) между видами и популяциями двустворчатых моллюсков. П р и м е ч а н и е. Aa — A. anatina, Ac — A. cygnea, Pc — P. complanata, Sw — S. woodiana. Речные системы: 1 — Дунай, 2 — р. Тиса, 3 — Верхний Днестр, 4 — Нижний Днестр, 5 — р. Ингул, 6 — р. Западный Буг, 7 — р. Припять, 8 — р. Верхний Днепр, 9 — р. Рось, 10 — р. Псёл, 11 — р. Северский Донец, 12 — р. Салгир.
Habitat-linked genetic variation supports microgeographic adaptive divergence in an island-endemic bird species
<p>We present evidence for and investigate potential mechanisms driving habitat-linked genetic divergence within a bird species endemic to a single 250 km<sup>2</sup> island. The island scrub-jay (<em>Aphelocoma insularis</em>) exhibits microgeographic divergence in bill morphology across pine-oak ecotones on Santa Cruz Island, California (USA) similar to adaptive differences described in mainland congeners over much larger geographic scales. To test whether individuals exhibit genetic differentiation related to habitat type and divergence in bill length, we genotyped over 3,000 single nucleotide polymorphisms (SNPs) in 123 adult island scrub-jay males from across Santa Cruz Island using restriction site-associated DNA sequencing (RADseq). Neutral landscape genomic analyses revealed that genome-wide genetic differentiation was primarily related to geographic distance and differences in habitat composition. We also found 168 putatively adaptive loci associated with habitat type using multivariate redundancy analysis (RDA) while controlling for spatial effects. Finally, two genome-wide association analyses revealed a polygenic basis to variation in bill length with multiple loci detected in or near genes known to affect bill morphology in other birds. Our findings support the hypothesis that divergent selection at microgeographic scales can cause adaptive divergence in the presence of ongoing gene flow.</p>
Fig. 2 in Genetic Diversity And Place In The General Phylogeographic Structure Of Capercaillie,Tetrao Urogallus (Galliformes, Phasianidae), From Belarus
Fig. 2. Reconstruction of the phylogeny of the capercaillie according to the polymorphism of the control region of mtDNA. Red dots — sequences from Belarus (this study).
Fig. 3 in Genetic Diversity And Place In The General Phylogeographic Structure Of Capercaillie,Tetrao Urogallus (Galliformes, Phasianidae), From Belarus
Fig. 3. Network of capercaillie haplotypes according to the mtDNA control region. Balkans — the Balkan Peninsula, E_Europe — Eastern Europe, N_Europe — Northern Europe, W_Russia — Western Russia (up to Ural Mountains), W_Europe — Western Europe, NW_Russia — Northwest Russia, C_Europe — Central Europe.
Fig. 1 in Genetic Diversity And Place In The General Phylogeographic Structure Of Capercaillie,Tetrao Urogallus (Galliformes, Phasianidae), From Belarus
Fig. 1. Distribution of samples of the capercaillie. Black circles are samples obtained independently, black squares are mtDNA sequences (control region) downloaded from the GenBank database (see Appendix, table 1).
Fig. 1 in Winter Diet Of The Common Genet, Genetta Genetta (Carnivora, Viverridae), And The African Golden Wolf, Canis Anthus (Carnivora, Canidae), In Altitudinal Locality Of The Edough Forest (Northeastern Algeria)
Fig. 1. Geographical situation of the study locality. (with indication of the three transects: 1, 2 and 3). Source: https://journals.openedition.org/physio-geo/docannexe/image/4217/img-1.jpg. Modified by Boukheroufa (present work).
Fig. 3 in Genetic Divergence Of The Species Of The Yellow Wagtails Group (Passeriformes, Motacillidae) In European Territory Of Russia
Fig. 3. Phylogenetic dendrogram of the species of the genus Motacilla built after alignment of sequences of the cytochrome oxidase I gene using JalView software (full version).
A genome-wide test for paternal indirect genetic effects on lifespan in Drosophila melanogaster
<p>Exposing sires to various environmental manipulations has demonstrated that paternal effects can be non-trivial also in species where male investment in offspring is almost exclusively limited to sperm. Whether paternal effects also have a genetic component (i.e. paternal indirect genetic effects - PIGEs) in such species is however largely unknown, primarily because of methodological difficulties separating indirect from direct effects of genes. PIGEs may nevertheless be important, since they have the capacity to contribute to evolutionary change. Here we use Drosophila genetics to construct a breeding design that allows testing nearly complete haploid genomes (>99%) for PIGEs. Using this technique, we estimate the variance in male lifespan due to PIGEs among four populations and compare this to the total paternal genetic variance (the sum of paternal indirect and direct genetic effects). Our results indicate that a substantial part of the total paternal genetic variance results from PIGEs. A screen of 38 haploid genomes, randomly sampled from a single population, suggests that PIGEs also influence variation in lifespan within populations. Collectively, our results demonstrate that PIGEs may constitute an underappreciated source of phenotypic variation.</p>
VCF data for genetic polyploid phasing
<p>Used data for evaluation in pending Recomb 2022 submission "Genetic Polyploid Phasing using Marker Signals from Low-Depth Progeny Samples". Data was used in and partly created by the scripts from here: https://github.com/AlBi-HHU/genetic-phasing-scripts</p>
Gene expression plasticity, genetic variation and fatty acid remodelling in divergent populations of a tropical bivalve species: lipid profiles
<p><span>Ocean warming challenges marine organisms' resilience, especially for species experiencing temperatures close to their upper thermal limits. A potential increase in thermal tolerance might significantly reduce the risk of population decline, which is intrinsically linked to variability in local habitat temperatures.</span></p> <p><span>Our goal was to assess the plastic and genetic potential of response to elevated temperatures in a tropical bivalve model, <em>Pinctada margaritifera</em>. We benefit from two ecotypes for which local environmental conditions are characterized by either large diurnal variations in the tide-pools (Marquesas archipelago) or lower mean temperature with stable to moderate seasonal variations (Gambier archipelago).</span><br><br><span>We explored the physiological basis of individual responses to elevated temperature<em>, </em>genetic divergence as well as plasticity and acclimation by combining lipidomic and transcriptomic approaches.</span><br><br><span>We show that <em>P. margaritifera</em> has certain capacities to adjust to long-term elevated temperatures that was thus far largely underestimated. Genetic variation across populations overlaps with gene expression and involves the mitochondrial respiration machinery, a central physiological process that contributes to species thermal sensitivity and their distribution ranges.</span><br><br><span>Our results present evidence for acclimation potential in <em>P. margaritifera</em> and urge for longer term studies to assess populations resilience in face of climate change.</span></p>
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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.