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497 results for “stickleback”
Data from: The ecology of an adaptive radiation of three-spined stickleback from North Uist, Scotland
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Data from: Genetic divergence of a sympatric lake-resident–anadromous three-spined stickleback Gasterosteus aculeatus species pair
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Data from: Comparative analysis of Japanese three-spined stickleback clades reveals the Pacific Ocean lineage has adapted to freshwater environments while the Japan Sea has not
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Data from: An experimental test of the effect of predation upon behaviour and trait correlations in threespine stickleback
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Data from: Bringing habitat information into statistical tests of local adaptation in quantitative traits: a case study of nine-spined sticklebacks
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Data from: Genetic and morphometric divergence in threespine stickleback in the Chignik catchment, Alaska
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Data from: Carry-over effects of early thermal conditions on somatic and germline oxidative damages are mediated by compensatory growth in sticklebacks
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Data from: Geographic variation in age structure and longevity in the nine-spined stickleback (Pungitius pungitius)
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Data from: Cline coupling and uncoupling in a stickleback hybrid zone
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Data from: Accumulation of deleterious mutations on the neo-Y chromosome of Japan sea stickleback (Gasterosteus nipponicus)
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Data from: Male choice in the stream-anadromous stickleback complex
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Data from: Sex-specific phenotypes and metabolism-related gene expression in juvenile sticklebacks
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Genomic data from: Are you ready for the heat? Phenotypic plasticity vs adaptation of heat tolerance in three-spined stickleback
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Sexually mediated phenotypic variation within and between sexes as a continuum structured by ecology: The mosaic nature of skeletal variation across body regions in Threespine stickleback (Gasterosteus aculeatus L.)
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Sex differences in laterality are associated with reproduction in three-spine stickleback
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Data from: Adaptation via pleiotropy and linkage: association mapping reveals a complex genetic architecture within the stickleback Eda locus
Genomic mapping of the loci associated with phenotypic evolution has revealed genomic "hotspots", or regions of the genome that control multiple phenotypic traits. This clustering of loci has important implications for the speed and maintenance of adaptation and could be due to pleiotropic effects of a single mutation or tight genetic linkage of multiple causative mutations affecting different traits. The threespine stickleback (<i>Gasterosteus aculeatus</i>) is a powerful model for the study of adaptive evolution because the marine ecotype has repeatedly adapted to freshwater environments across the northern hemisphere in the last 12,000 years. Freshwater ecotypes have repeatedly fixed a 16 kilobase haplotype on chromosome IV that contains Ectodysplasin (<i>Eda</i>), a gene known to affect multiple traits, including defensive armor plates, lateral line sensory hair cells, and schooling behavior. Many additional traits have previously been mapped to a larger region of chromosome IV that encompasses the <i>Eda</i> freshwater haplotype. To identify which of these traits specifically map to this adaptive haplotype, we made crosses of rare marine fish heterozygous for the freshwater haplotype in an otherwise marine genetic background. Further, we performed fine-scale association mapping in a fully interbreeding, polymorphic population of freshwater stickleback to disentangle the effects of pleiotropy and linkage on the phenotypes affected by this haplotype. Although we find evidence that linked mutations have small effects on a few phenotypes, a small 1.4 kb region within the first intron of <i>Eda</i> has large effects on three phenotypic traits: lateral plate count, and both the number and patterning of the posterior lateral line neuromasts. Thus, the <i>Eda</i> haplotype is a hotspot of adaptation in stickleback due to both a small, pleiotropic region affecting multiple traits as well as multiple linked mutations affecting additional traits.
Data from: Non-consumptive effects of predation: does perceived risk strengthen the genetic integration of behaviour and morphology in stickleback?
<p>Predators can shape genetic correlations in prey by altering prey perception of risk. We manipulated perceived risk to test whether such non-consumptive effects tightened behavioural trait correlations in wild-caught stickleback from high- compared to low-risk environments due to genetic variation in plasticity. We expected tighter genetic correlations within perceived risk treatments than across them, and tighter genetic correlations in high-risk than in low-risk treatments. We identified genetic variation in plasticity, with genetic correlations between boldness, sociality and antipredator morphology, as expected, being tighter within treatments than across them, for both of two populations. By contrast, genetic correlations did not tighten with exposure to risk. Tighter phenotypic correlations in wild stickleback may thus arise because predators induce correlational selection on environmental components of these traits, or because predators tighten residual correlations by causing environmental heterogeneity that is controlled in the laboratory. Our study places phenotypic integration firmly into an ecological context.</p>
Genetic population structure constrains local adaptation in sticklebacks
<p class="MsoBodyText"><span><span><span><span><span><span><span><span><span><span><span>Repeated and independent adaptation to specific environmental conditions from standing genetic variation is common. However, if genetic variation is limited, the evolution of similar locally adapted traits may be restricted to genetically different and potentially less optimal solutions or prevented from happening altogether. Using a quantitative trait locus (QTL) mapping approach, we identified the genomic regions responsible for the repeated pelvic reduction (PR) in three crosses between nine-spined stickleback populations expressing full and reduced pelvic structures. In one cross, PR mapped to linkage group 7 (LG7) containing the gene<i> Pitx1</i>, known to control pelvic reduction also in the three-spined stickleback. In the two other crosses, PR was polygenic and attributed to ten novel QTL, of which 90% were unique to specific crosses. When screening the genomes from 27 different populations for deletions in the <i>Pitx1</i> regulatory element, these were only found in the population in which PR mapped to LG7, even though the morphological data indicated large effect QTL for PR in several other populations as well. Consistent with the available theory and simulations parameterised on empirical data, we hypothesise that the observed variability in genetic architecture of PR is due to heterogeneity in the spatial distribution of standing genetic variation caused by >2x stronger population structuring among freshwater populations and >10x stronger genetic isolation by distance in the sea in nine-spined sticklebacks as compared to three-spined sticklebacks.</span></span></span></span></span></span></span></span></span></span></span></p>
Resource diversity promotes among-individual diet variation, but not genomic diversity, in lake stickleback
Many generalist species consist of specialized individuals that use different resources. This within-population niche variation can stabilize population and community dynamics. Consequently, ecologists wish to identify environmental settings that promote such variation. Theory predicts that environments with greater resource diversity favor ecological diversity (via disruptive selection or plasticity). Alternatively, niche variation might be a side-effect of neutral genomic diversity in larger populations. We tested these alternatives in a metapopulation of threespine stickleback. Stickleback consume benthic and limnetic invertebrates, focusing on the former in small lakes, the latter in large lakes. Intermediate-sized lakes support generalist stickleback populations using an even mixture of the two prey types, due to greater among-individual variation in diet and morphology. In contrast, genomic diversity increases with lake size. Thus, phenotypic diversity and neutral genetic polymorphism are decoupled: trophic diversity being greatest in intermediate-sized lakes with high resource diversity, whereas neutral genetic diversity is greatest in the largest lakes.
What evolutionary processes maintain MHCIIβ diversity within and among populations of stickleback?
<p>Major Histocompatibility Complex (MHC) genes encode for proteins that recognize foreign protein antigens to initiate T-cell mediated adaptive immune responses. They are often the most polymorphic genes in vertebrate genomes. How evolution maintains this diversity is still an unsettled issue. Three main hypotheses seek to explain the maintenance of MHC diversity by invoking pathogen-mediated selection: heterozygote advantage, frequency-dependent selection, and fluctuating selection across landscapes or through time. Here, we use a large-scale field parasite survey in a stickleback metapopulation to test predictions derived from each of these hypotheses. We identify over a thousand MHCIIβ variants (alleles spanning paralogous genes) and find that many of them covary positively or negatively with parasite load, suggesting that these genes contribute to resistance or susceptibility. However, despite our large sample-size, we find no evidence for the widely-cited stabilizing selection on MHC heterozygosity, in which individuals with an intermediate number of MHC variants have the lowest parasite burden. Nor do we observe a rare-variant advantage, or widespread fluctuating selection across populations. In contrast, we find that MHC diversity is best predicted by neutral genome-wide heterozygosity and between-population genomic divergence, suggesting neutral processes are important in shaping the pattern of metapopulation MHC diversity. Thus, although MHCIIβ is highly diverse and relevant to the type and intensity of macroparasite infection in these populations of stickleback, the main models of MHC evolution still provide little explanatory power in this system.</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)
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