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186 results for “Quantitative genetics”
Data from: The coevolution of male and female genitalia in a mammal: a quantitative genetic insight
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Data from: A mathematical framework for the quantitative analysis of genetic buffering
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The quantitative genetics of fitness in a wild seabird
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Data from: Quantitative genetic analysis of floral traits shows current limits but potential evolution in the wild
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Dissecting the genetic architecture of quantitative traits using genome-wide identity-by-descent sharing
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Quantitative genetics of developmental stability in flower traits of Solanum rostratum
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Results of quantitative genetic sensitivity analysis performed on reconstructed pedigrees based on large-scale genealogies
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Data from: The genetic regulation of avian migration timing: combining candidate genes and quantitative genetic approaches in a long-distance migrant
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Quantitative trait locus mapping reveals an independent genetic basis for joint divergence in leaf function, life-history, and floral traits between scarlet monkeyflower (Mimulus cardinalis) populations
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Data from: Quantitative genetics of the use of conspecific and heterospecific social cues for breeding site choice
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Data from: the quantitative genetic basis of variation in sexual versus non-sexual butterfly wing colouration: autosomal, Z-linked and maternal effects
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Data from: Can dominance genetic variance be ignored in evolutionary quantitative genetic analyses of wild populations?
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Efficient weighting methods for genomic best linear unbiased prediction (BLUP) adaption to the genetic architectures of quantitative traits
<p><a name="_Hlk19877414"></a>Genomic best linear unbiased prediction (GBLUP) assumes equal variance for all marker effects, which is suitable for traits that conform to the infinitesimal model. For traits controlled by major genes, Bayesian methods with shrinkage priors or genome-wide association study (GWAS) methods can be used to identify <a name="_Hlk24974556">causal variants</a> effectively. The information from Bayesian/GWAS methods can be used to construct the weighted genomic relationship matrix (<b>G</b>). However, it remains unclear which methods perform best for traits varying in genetic architecture. Therefore, we developed several methods to <a name="_Hlk23592218">optimize</a> the performance of weighted GBLUP and compare them with other available methods using simulated and real datasets. First, two types of methods (marker effects with local-shrinkage or normal prior) were used to obtain test statistics and estimates for each marker effect. Second, three weighted <b>G</b> matrices were constructed based on the marker information from the first step: (1) the genomic-feature weighted <b>G</b> (GFWG), (2) the estimated marker-variance weighted <b>G</b> (EVWG), and (3) the absolute value of estimated marker-effect weighted <b>G</b> (AEWG). Following the above process, six different weighted GBLUP methods (local-shrinkage/normal prior GF/EV/AE-WGBLUP) were proposed for genomic prediction. Analyses with both simulated and real data demonstrated that these options offer flexibility for optimizing the weighted GBLUP for traits with a broad spectrum of genetic architectures. The advantage of weighting methods over GBLUP in terms of accuracy were trait dependent, ranging from 14.8% to marginal for simulated traits and from 44% to marginal for real traits. Local-shrinkage prior EVWGBLUP is superior for traits mainly controlled by loci of large effect. Normal prior AEWGBLUP performs well for traits mainly controlled by loci of moderate effect. For traits controlled by some loci with large effects (<a name="_Hlk49869847">explain 25%~50% genetic variance</a>) and a range of loci with small effects, GFWGBLUP has advantages. In conclusion, the optimal weighted GBLUP method for genomic selection should take both the genetic architecture and number of QTLs of traits into consideration carefully.</p>
Quantitative genetics of phosphorus content in the freshwater herbivore, Daphnia pulicaria
<p>1. Phosphorus (P) is essential for growth of all organisms, and P content is correlated with growth in most taxa. Although P content was initially considered to be a trait fixed at the species level, there is growing evidence for considerable intraspecific variation. Selection on such variation can thus alter the rates at which P fluxes through food webs.</p> <p>2. Nevertheless, prior work describing the sources and extent of intraspecific variation in P content were not genetically explicit, confounded by unknown genetic background and evolutionary history. We constructed an F2 recombinant population of the dominant freshwater grazer, Daphnia pulicaria to mitigate such issues.</p> <p>3. F2 recombinants exhibited considerable variation in growth rate, P content (0.49% to 1.97%), P use efficiency (PUE; 51 to 208 mg biomass/mg P), and correlated traits such as hatching time of resting eggs, in common garden conditions.</p> <p>4. These results clearly demonstrate the scope of genetic recombination in generating variation in ecologically-relevant traits. The absence of environmental selection is a likely component driving such variation not observed in natural settings.</p> <p>5. Although phosphoglucose isomerase (PGI) genotype was significantly associated with variation in hatching time of resting eggs, contrary to prior work with less rigorous designs, allelic variation at the PGI locus did not explain variation in P content and PUE of Daphnia, indicating that such quantitative traits are under polygenic control.</p> <p>6. Together, these results suggest that although there is considerable genetic scope for variation in key ecologically-relevant traits, such as P content and efficiency of P use, these traits are likely under strong stabilizing selection, most likely due to selection on growth rate and size. Importantly, our observations suggest that anthropogenic alterations to P supply due to eutrophication could alter selection on these traits, thereby rapidly altering the role Daphnia plays in the P cycle of lakes.</p>
Data from: Quantitative genetics of a carotenoid-based color: heritability and persistent natal environmental effects in the great tit
The information content of signals, such as animal coloration, depends on the extent to which variation reflects underlying biological processes. Although animal coloration has received considerable attention, little work has addressed the quantitative genetics of colour variation in natural populations. We investigated the quantitative genetics of a carotenoid-based colour patch - the ventral plumage of mature great tits (Parus major) - in a wild population. Carotenoid-based colours are often suggested to reflect environmental variation in carotenoid availability, but numerous mechanisms could also lead to genetic variation in coloration. Analyses of individuals of known origin showed that while plumage chromaticity ('colour') was moderately heritable, there was no significant heritability to achromaticity ('brightness'). We detected multiple long-lasting effects of natal environment, with hatching date and brood size both negatively related to plumage chromaticity at maturity. Our reflectance measures contrasted in their spatiotemporal sensitivity, with plumage chromaticity exhibiting significant spatial variation while achromatic variation exhibited marked annual variation. Hence, colour variation in this species reflects both genetic and environmental influences on different scales. Our analyses demonstrate the context-dependence of components of colour variation and suggest that colour patches may convey multiple aspects of individual state.
Recent immigrants alter the quantitative genetic architecture of paternity in song sparrows
Quantifying additive genetic variances and cross-sex covariances in reproductive traits, and identifying processes that shape and maintain such (co)variances, is central to understanding the evolutionary dynamics of reproductive systems. Gene flow resulting from among-population dispersal could substantially alter additive genetic variances and covariances in key traits in recipient populations, thereby altering forms of sexual conflict, indirect selection and evolutionary responses. However, the degree to which genes imported by immigrants do in fact affect quantitative genetic architectures of key reproductive traits and outcomes is rarely explicitly quantified. We applied structured quantitative genetic analyses to multi-year pedigree, pairing and paternity data from free-living song sparrows (Melospiza melodia) to quantify the differences in mean breeding values for major sex-specific reproductive traits, specifically female extra-pair reproduction and male paternity loss, between recent immigrants and the previously existing population. We thereby quantify effects of natural immigration on the means, variances and cross-sex covariance in total additive genetic values for extra-pair paternity arising within the complex socially monogamous but genetically polygynandrous reproductive system. Recent immigrants had lower mean breeding values for male paternity loss, and somewhat lower values for female extra-pair reproduction, than the local recipient population, and would therefore increase the emerging degree of reproductive fidelity of social pairings. Furthermore, immigration increased the variances in total additive genetic values for these traits, but decreased the magnitudes of the negative cross-sex genetic covariation and correlation below those evident in the existing population. Immigration thereby increased the total additive genetic variance but could decrease the magnitude of indirect selection acting on sex-specific contributions to paternity outcomes. These results demonstrate that dispersal and resulting immigration and gene flow can substantially affect quantitative genetic architectures of complex local reproductive systems, implying that comprehensive theoretical and empirical efforts to understand mating system dynamics will need to incorporate spatial population processes.
Strong and weak cross-sex correlations govern the quantitative-genetic architecture of social group choice in Drosophila melanogaster
<p><span><span><span><span><span><span><span><span><span><span><span>When genotypes differ in niche-constructing traits, genotypes are expected to differ in which environments they experience, providing a novel causal relationship between genotypes, environments, and behavior. Such genetic variation in niche construction (or, more precisely, environment construction) is predicted to be especially important for social environments, yet the quantitative-genetic parameters governing such variation is still poorly understood. Here, we examine genetic variation and cross-sex genetic correlations for social environment-constructing behaviors. We focus on whether genetic variation in patch use—the tendency to spend time near food patches where conspecifics may be present—and group-size preference—the specific group size chosen when individuals are affiliating—is correlated or decoupled across sexes in the fruit fly, <i>Drosophila melanogaster</i>. Across three choice treatments, we find genotype and sex differences in how much time individuals spend near patches, and which group sizes they prefer. We find that the genetic basis of patch use is strongly coupled across sexes, whereas the genetic basis of group-size preference is completely <i>de</i>coupled across sexes. We discuss how these findings augment and complicate our understanding of the evolutionary genetics of social behaviors.</span></span></span></span></span></span></span></span></span></span></span></p>
Data from: Quantitative genetic divergence and standing genetic (co)variance in thermal reaction norms along latitude
Although the potential to adapt to warmer climate is constrained by genetic trade-offs, our understanding of how selection and mutation shape genetic (co)variances in thermal reaction norms is poor. Using 71 isofemale lines of the fly Sepsis punctum, originating from northern, central and southern European climates, we tested for divergence in juvenile development rate across latitude at five experimental temperatures. To investigate effects of evolutionary history in different climates on standing genetic variation in reaction norms, we further compared genetic (co)variances between regions. Flies were reared on either high or low food resources to explore the role of energy-acquisition in determining genetic trade-offs between different temperatures. Although the latter had only weak effects on the strength and sign of genetic correlations, genetic architecture differed significantly between climatic regions, implying that evolution of reaction norms proceeds via different trajectories at high versus low latitude in this system. Accordingly, regional genetic architecture was correlated to region-specific differentiation. Moreover, hot development temperatures were associated with low genetic variance and stronger genetic correlations compared to cooler temperatures. We discuss the evolutionary potential of thermal reaction norms in light of their underlying genetic architectures, evolutionary histories and the materialization of trade-offs in natural environments.
Data from: Is evolution predictable? quantitative genetics under complex genotype-phenotype maps
<p>A fundamental aim of post-genomic 21st century biology is to understand the genotype-phenotype map (GPM) or how specific genetic variation relates to specific phenotypic variation. Quantitative genetics approximates such maps using linear models, and has developed methods to predict the response to selection in a population. The other major field of research concerned with the GPM, developmental evolutionary biology or evo-devo, has found the GPM to be highly nonlinear and complex. Here we quantify how the predictions of quantitative genetics are affected by the complex, nonlinear maps found in developmental biology. We found that the disagreements between predicted and observed responses to selection are common, roughly in a third of generations, systematic and due to nonlinear nature of the genotype-phenotype map. They occur at all time scales, even from one generation to the next. Our results are a step towards integrating the fields studying the GPM.</p>
Data from: Sexual conflict and interacting phenotypes: a quantitative genetic analysis of fecundity and copula duration in Drosophila melanogaster
Many reproductive traits that have evolved under sexual conflict may be influenced by both sexes. Investigation of the genetic architecture of such traits can yield important insight into their evolution, but this entails that the heritable component of variation is estimated for males and females – as an interacting phenotype. We address the lack of research in this area through an investigation of egg production and copula duration in the fruit fly, Drosophila melanogaster. Despite egg production rate being determined by both sexes, which may cause sexual conflict, an assessment of this trait as an interacting phenotype is lacking. It is currently unclear whether copula duration is determined by males and/or females. We found significant female, but not male, genetic variance for egg production rate which may indicate reduced potential for ongoing sexually antagonistic coevolution. In contrast, copula duration was determined by significant genetic variance in both sexes. We also identified genetic variation in egg retention among virgin females. Although previously identified in wild populations, it is unclear why this should be present in a laboratory stock. This study provides a novel insight into the shared genetic architecture of reproductive traits that are the subject of sexual conflict.
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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
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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
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