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20 results for “Evolutionary limit”
Limited sex differences in plastic responses suggest evolutionary conservatism of thermal reaction norms: A meta-analysis in insects
<p>Temperature has a profound effect on the growth and development of ectothermic animals. However, the extent to which ecologically-driven selection pressures can adjust thermal plastic responses in growth schedules is not well understood. Comparing temperature-induced plastic responses between sexes provides a promising but underexploited approach to evaluating the evolvability of thermal reaction norms: males and females share largely the same genes and immature environments but typically experience different ecological selection pressures. We proceed from the idea that substantial sex differences in plastic responses could be interpreted as resulting from sex-specific life-history optimization, whereas similarity among the sexes should rather be seen as evidence of an essential role of physiological constraints. In this study, we performed a meta-analysis of sex-specific thermal responses in insect development times, using data on 161 species with comprehensive phylogenetic and ecological coverage. As a reference for judging the magnitude of sex-specificity in thermal plasticity, we compared the magnitude of sex differences in plastic responses to temperature with those in response to diet. We show that sex-specific responses of development times to temperature variation are broadly similar. We also found no strong evidence for sex-specificity in thermal responses to depend on the magnitude or direction of sex differences in development time. Sex differences in temperature-induced plastic responses were systematically less pronounced than sex differences in responses induced by variations in larval diet. Our results point to the existence of substantial constraints on the evolvability of thermal reaction norms in insects as the most likely explanation. If confirmed, the low evolvability of thermal response is an essential aspect to consider in predicting evolutionary responses to climate warming.</p>
Data from: The limit to evolutionary rescue depends on ploidy in yeast exposed to nystatin
<h4>Data package about haploid vs diploid adaptation to nystatin in yeast</h4> <div>This package contains files and scripts related to the publication "The limit to evolutionary rescue depends on ploidy in yeast exposed to nystatin". Raw data and analyses are included.</div>
Limited sex differences in plastic responses suggest evolutionary conservatism of thermal reaction norms: A meta-analysis in insects
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A decision-making framework to maximize the evolutionary potential of populations: Genetic and genomic insights from the common midwife toad (Alytes obstetricans) at its range limits
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Data from: Evolutionary constraints in host shifts: limited adaptation of <em>Plutella xylostella</em> to cardenolide-defended <em>Erysimum cheiranthoides</em>
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Data from: Deforestation limits evolutionary rescue under climate change in Amazonian lizards
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Data from: Lack of genotype-by-environment interaction suggests limited potential for evolutionary changes in plasticity in the eastern oyster, Crassostrea virginica
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Discussions of the not-so-fit: how ableism limits diverse thought and investigative potential in evolutionary biology
<p>Evolutionary biology and many of its foundational concepts are grounded in a history of ableism and eugenics. The field has not made a concerted effort to divest our concepts and investigative tools from this fraught history and as a result, an ableist investigative lens has persisted into present-day evolutionary research, limiting the scope of research and harming the ability to communicate and synthesize knowledge about evolutionary processes. This failure to divest from our eugenicist and ableist history has harmed progress in evolutionary biology and allowed principles from evolutionary biology to continue to be weaponized against marginalized communities in the modern-day. To rectify this problem, scholars in evolutionary research must come to terms with how the history of the field has influenced their investigations and work to establish a new framework for defining and investigating concepts, such as selection and fitness.</p>
Data for: Evolutionary history limits species' ability to match color sensitivity to available habitat light
<p>The spectrum of light that an animal sees – from ultraviolet to far red light – is governed by the number and wavelength sensitivity of a family of retinal proteins called opsins. It has been hypothesized that the spectrum of light available in an environment influences the range of colors that a species has evolved to see. However, invertebrates and vertebrates use phylogenetically distinct opsins in their retinae, and it remains unclear whether these distinct opsins influence what animals see, or how they adapt to their light environments. Systematically utilizing published visual sensitivity data from across animal phyla, we found that terrestrial animals are more sensitive to shorter and longer wavelengths of light than aquatic animals, and that invertebrates are more sensitive to shorter wavelengths of light than vertebrates. Controlling for phylogeny removes the effects of habitat and lineage on visual sensitivity. Closed and open habitat terrestrial species have similar spectral sensitivities when comparing across the Metazoa, and deep water animals are more sensitive to shorter wavelengths of light than shallow water animals. Our results suggest that animals do adapt to their light environment, however the invertebrate-vertebrate evolutionary divergence has limited the degree to which animals can perform visual tuning.</p>
Data for: Evolutionary history limits species' ability to match color sensitivity to available habitat light
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Data from: Evolutionary processes, dispersal limitation and climatic history shape current diversity patterns of European dragonflies
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Discussions of the not-so-fit: how ableism limits diverse thought and investigative potential in evolutionary biology
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Data from: High mutation rates limit evolutionary adaptation in Escherichia coli
Mutation is fundamental to evolution, because it generates the genetic variation on which selection can act. In nature, genetic changes often increase the mutation rate in systems that range from viruses and bacteria to human tumors. Such an increase promotes the accumulation of frequent deleterious or neutral alleles, but it can also increase the chances that a population acquires rare beneficial alleles. Here, we study how up to 100-fold increases in Escherichia coli's genomic mutation rate affect adaptive evolution. To do so, we evolved multiple replicate populations of asexual E. coli strains engineered to have four different mutation rates for 3000 generations in the laboratory. We measured the ability of evolved populations to grow in their original environment and in more than 90 novel chemical environments. In addition, we subjected the populations to whole genome population sequencing. Although populations with higher mutation rates accumulated greater genetic diversity, this diversity conveyed benefits only for modestly increased mutation rates, where populations adapted faster and also thrived better than their ancestors in some novel environments. In contrast, some populations at the highest mutation rates showed reduced adaptation during evolution, and failed to thrive in all of the 90 alternative environments. In addition, they experienced a dramatic decrease in mutation rate. Our work demonstrates that the mutation rate changes the global balance between deleterious and beneficial mutational effects on fitness. In contrast to most theoretical models, our experiments suggest that this tipping point already occurs at the modest mutation rates that are found in the wild.
Data from: Sign epistasis limits evolutionary trade-offs at the confluence of single- and multi-carbon metabolism in Methylobacterium extorquens AM1
Adaptation of one set of traits is often accompanied by attenuation of traits important in other selective environments, leading to fitness trade-offs. The mechanisms that either promote or prevent the emergence of trade-offs remain largely unknown, and are difficult to discern in most systems. Here, we investigate the basis of trade-offs that emerged during experimental evolution of Methylobacterium extorquens AM1 to distinct growth substrates. After 1500 generations of adaptation to a multi-carbon substrate, succinate (S), many lineages had lost the ability to use one-carbon compounds such as methanol (M), generating a mixture of M+ and M− evolved phenotypes. We show that trade-offs in M− strains consistently arise via antagonistic pleiotropy through recurrent selection for loss-of-function mutations to ftfL (formate-tetrahydrofolate ligase), which improved growth on S while simultaneously eliminating growth on M. But if loss of FtfL was beneficial, why were M trade-offs not found in all populations? We discovered that eliminating FtfL was not universally beneficial on S, as it was neutral or even deleterious in certain evolved lineages that remained M+. This suggests that sign epistasis with earlier arising mutations prevented the emergence of mutations that drove trade-offs through antagonistic pleiotropy, limiting the evolution of metabolic specialists in some populations.
Data from: High evolutionary constraints limited adaptive responses to past climate changes in toad skulls
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Data from: High mutation rates limit evolutionary adaptation in Escherichia coli
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Data from: Sign epistasis limits evolutionary trade-offs at the confluence of single- and multi-carbon metabolism in Methylobacterium extorquens AM1
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The Repertoire and Dynamics of Evolutionary Adaptations to Controlled Nutrient-Limited Environments in Yeast
GEO Series GSE13435. Saccharomyces cerevisiae. 190 samples. Type: Expression profiling by array; Genome variation profiling by array.
Genetic interaction network has a very limited impact on the evolutionary trajectories in continuous culture-grown populations of yeast
GEO Series GSE167397. Saccharomyces cerevisiae. 17 samples. Type: Expression profiling by array.
Structurally Complex Osteosarcoma Genomes Exhibit Limited Heterogeneity within Individual Tumors and across Evolutionary Time
A key characteristic of osteosarcoma is extensive and complex genomic rearrangements. However, published models explaining how these genomic rearrangements occur disagree about if these rearrangements occur early in tumor progression and then are stable afterwards, or if there is ongoing genomic instability. Previous studies have employed bulk sequencing technologies to characterize genomic alterations. A limitation of this approach is that it averages all changes within the bulk sample, essentially masking intra-sample heterogeneity and making evaluation of ongoing genomic instability difficult. To overcome this limitation and compliment previous work, we utilized single-cell whole genome sequencing to quantify somatic copy number alterations (SCNA). By interrogating individual cells within a sample, we were able to examine intra-sample heterogeneity. We found that the SCNA patterns between cells within a single sample were remarkably consistent, which supports the concept that the genomes of osteosarcoma tumors are relatively stable after early genome fragmentation events.
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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.