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344 results for “genetic testing”
Data from: Testing the link between population genetic differentiation and clade diversification in Costa Rican orchids
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Data from: Genetic basis of adult migration timing in anadromous steelhead discovered through multivariate association testing
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Data for: Global frequency analyses of canine progressive rod-cone degeneration–progressive retinal atrophy and collie eye anomaly using commercial genetic testing data
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Genetic testing limits the spread of inherited kidney disease while avoiding inbreeding in domestic cats
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Data from: Integrative testing of how environments from the past to the present shape genetic structure across landscapes
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Data from: Testing for beneficial reversal of dominance during salinity shifts in the invasive copepod Eurytemora affinis, and implications for the maintenance of genetic variation
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Data from: Testing the species–genetic diversity correlation in the Aegean archipelago: towards a haplotype-based macroecology?
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Data from: Climate structures genetic variation across a species' elevation range: a test of range limits hypotheses
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Data from: A test of the central-marginal hypothesis using population genetics and ecological niche modelling in an endemic salamander (Ambystoma barbouri)
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Data from: Does population size affect genetic diversity? A test with sympatric lizard species
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Data from: Comparative tests of the species-genetic diversity correlation at neutral and non-neutral loci in four species of stream insect
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Data from: What caused over a century of decline in general intelligence? Testing predictions from the genetic selection and neurotoxin hypotheses
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Data from: Does human-induced hybridization have long-term genetic effects? Empirical testing with domesticated, wild and hybridized fish populations
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Data from: Genetic patterns across an invasion's history: a test of change versus stasis for the Eurasian round goby in North America
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Data from: Comparison of population-genetic structuring in congeneric kelp- versus rock-associated snails: a test of a dispersal-by-rafting hypothesis
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Data from: Demographic and population-genetic tests provide mixed support for the abundant center hypothesis in the endemic plant Leavenworthia stylosa
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Data and Code for Publication "Testing the Utility of Dental Morphological Trait Combinations for Inferring Human Neutral Genetic Variation"
<p>Data and code for publication: H. Rathmann, H. Reyes-Centeno, Testing the utility of dental morphological trait combinations for inferring human neutral genetic variation. <em>Proc. Natl. Acad. Sci. U.S.A.</em> 117, 10769-10777 (2020). DOI: 10.1073/pnas.1914330117</p> <p>The repository contains:</p> <ul> <li>“R-code.txt”: R code for an exhaustive search algorithm testing the utility of dental morphological traits and trait combinations for inferring human neutral genetic variation.</li> <li>“dental trait frequencies.csv”: Data set with 27 dental morphological trait frequencies for 20 modern human populations worldwide used for analysis. Data from G. R. Scott, C. G. Turner, G. C. Townsend, M. Martinón-Torres, <em>The Anthropology of Modern Human Teeth</em> (Cambridge University Press, 2018). DOI: 10.1017/ 9781316795859</li> <li>“microsatellite loci mean sizes.csv”: Data set with 645 microsatellite mean allele sizes for 20 modern human populations worldwide used for analysis. Data from T. J. Pemberton, M. DeGiorgio, N. A. Rosenberg, Population structure in a comprehensive genomic data set on human microsatellite variation. <em>G3: Genes Genom. Genet.</em> 3, 891–907 (2013). DOI: 10.1534/g3.113.005728</li> <li>“utility estimates for 134217727 trait combinations.txt”: A large table with utility estimates for 27 dental morphological traits and all 134,217,700 possible trait combinations.</li> </ul> <p>Abbreviations for the 20 population names (rows) in “dental trait frequencies.csv” and “microsatellite loci mean sizes.csv” as follows:</p> <ul> <li>AUS = Australia</li> <li>CAS = Central Asia</li> <li>EAF = Eastern Africa</li> <li>EAS = East Asia</li> <li>EEU = Eastern Europe</li> <li>IND = India</li> <li>MAM = Mesoamerica</li> <li>MEL = Melanesia</li> <li>MIC = Micronesia</li> <li>NAF = North Africa</li> <li>NAM = North America</li> <li>NESI = Northeast Siberia</li> <li>NGU = New Guinea</li> <li>NWAM = Na-Dene</li> <li>POL = Polynesia</li> <li>SAM = South America</li> <li>SAN = San</li> <li>SEAS = Southeast Asia</li> <li>WEU = Western Europe</li> <li>WSAF = Sub-Saharan Africa</li> </ul> <p>Abbreviations for the 27 dental morphological trait names (columns) in “dental trait frequencies.csv” as follows:</p> <ul> <li>T1 = Winging (UI1)</li> <li>T2 = Shoveling (UI1)</li> <li>T3 = Double-Shoveling (UI1)</li> <li>T4 = Interruption Grooves (UI2)</li> <li>T5 = Tuberculum Dentale (UI2)</li> <li>T6 = Mesial Ridge (UC)</li> <li>T7 = Distal Accessory Ridge (UC)</li> <li>T8 = Hypocone (UM2)</li> <li>T9 = Carabelli Trait (UM1)</li> <li>T10 = Cusp 5 (UM1)</li> <li>T11 = Enamel Extensions (UM1)</li> <li>T12 = Peg-Reduced-Missing (UM3)</li> <li>T13 = Lingual Cusp Number (LP2)</li> <li>T14 = Groove Pattern (LM2)</li> <li>T15 = Cusp 6 (LM1)</li> <li>T16 = Cusp Number (LM2)</li> <li>T17 = Deflecting Wrinkle (LM1)</li> <li>T18 = Distal Trigonid Crest (LM1)</li> <li>T19 = Protostylid (LM1)</li> <li>T20 = Cusp 7 (LM1)</li> <li>T21 = Odontomes (UP-LP)</li> <li>T22 = Root Number (UP1)</li> <li>T23 = Root Number (UM2)</li> <li>T24 = Root Number (LC)</li> <li>T25 = Tomes’ Root (LP1)</li> <li>T26 = Root Number (LM1)</li> <li>T27 = Root Number (LM2)</li> </ul> <p>Abbreviations for the 645 microsatellite allele locus names (columns) in “microsatellite loci mean sizes.csv” as in T. J. Pemberton, M. DeGiorgio, N. A. Rosenberg, Population structure in a comprehensive genomic data set on human microsatellite variation. <em>G3: Genes Genom. Genet.</em> 3, 891–907 (2013). DOI: 10.1534/g3.113.005728</p>
Supplementary material 8 from: Zizka VMA, Weiss M, Leese F (2020) Can metabarcoding resolve intraspecific genetic diversity changes to environmental stressors? A test case using river macrozoobenthos. Metabarcoding and Metagenomics 4: e51925. https://doi.org/10.3897/mbmg.4.51925
Table S1. Number of macroinvertebrate individuals per sample and season
Data from: Genetics of adaptation: experimental test of a biotic mechanism driving divergence in traits and genes
The genes underlying adaptations are becoming known, yet the causes of selection on genes -- a key step in the study of the genetics of adaptation -- remains uncertain. We address this issue experimentally in a threespine stickleback species pair showing exaggerated divergence in bony defensive armor in association with competition-driven character displacement. We used semi-natural ponds to test the role of a native predator in causing divergent evolution of armor and two known underlying genes. Predator presence/absence altered selection on dorsal spines and allele frequencies at the Msx2a gene across a generation. Evolutionary trajectories of alleles at a second gene, Pitx1, and the pelvic spine trait it controls, were more variable. Our experiment demonstrates how manipulation of putative selective agents help to identify causes of evolutionary divergence at key genes, rule out phenotypic plasticity as a sole determinant of phenotypic differences, and eliminate reliance on fitness surrogates. Divergence of predation regimes in sympatric stickleback is associated with coevolution in response to resource competition, implying a cascade of biotic interactions driving species divergence. We suggest that as divergence proceeds, an increasing number of biotic interactions generate divergent selection, causing more evolution in turn. In this way, biotic adaptation perpetuates species divergence through time during adaptive radiation in an expanding number of traits and genes.
Data from: Testing mechanisms of Bergmann's rule: phenotypic but no genetic change in body size in three passerine bird populations
Bergmann's rule predicts a decrease in body size with increasing temperature and has much empirical support. Surprisingly, we know very little about whether 'Bergmann size clines' are due to a genetic response or is a consequence of phenotypic plasticity. Here we use data on body size (mass and tarsus length) from three long-term (1979-2008) study populations of great tits (Parus major), in which there has been a temperature increase, to examine mechanisms behind Bergmann's rule. We show that adult body mass decreased over the study period in all populations and that tarsus length increased in one population. Both body mass and tarsus length were heritable and under weak positive directional selection, predicting an increase, rather than decrease, in body mass. There was no support for micro-evolutionary change and thus the observed declines in body mass were a result of phenotypic plasticity. Interestingly, this plasticity was not in direct response to temperature changes but seemed to be due to changes in prey dynamics. Our results caution against interpreting recent phenotypic body size declines as an adaptive evolutionary response to temperature changes and highlight the importance of considering alternative environmental factors when testing size clines.
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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.