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215 results for “environmental adaptation”

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zenodo52/100

Resources from: Disparate patterns of genetic divergence in three widespread corals across a pan-pacific environmental gradient highlights species-specific adaptation trajectories

<p>The following files are contained in this repository:</p> <p><br> README.Hume_et_al_2022.zenodov4.txt - This document.</p> <p>scripts.Hume_et_al_2022.zenodov4.pdf - Contains the scripts, or locations of the scripts, used to conduct the data analyses detailed in the associated manuscript.</p> <p>acknowledgements_local_authorities.Hume_et_al_2022.zenodov1.pdf - Acknowledgements of local authorities for the collection of samples used in the associated study.</p> <p>TaraPacific_SST_timeseries_mean_productsV2mai2021.Hume_et_al_2022.zenodov1.csv - The historical temperature data set used for the RDA, Mantel tests and gradient Forest analysis.</p> <p>Pocillopora_meandrina_v3_11Islands.raw.Hume_et_al_2022.zenodov2.vcf.genozip - The Pocillopora SNPs referred to as &#39;raw&#39; in the Methods of the associated manuscript. Compressed using genozip (https://genozip.readthedocs.io/index.html).</p> <p>Pocillopora_meandrina_v3_11Islands.raw.Hume_et_al_2022.zenodov2.vcf.genozip.md5 - md5 of the the Pocillopora raw SNPs.</p> <p>Pocillopora_meandrina_v3_11Islands_maf05_minQ30_biallelic_nomiss.linked.Hume_et_al_2022.zenodov2.vcf.gz - The Pocillopora SNPs referred to as &#39;linked&#39; in the Methods of the associated manuscript.</p> <p>Pocillopora_meandrina_v3_11Islands_maf05_minQ30_biallelic_nomiss.linked.Hume_et_al_2022.zenodov2.vcf.gz.md5 - md5 of the the Pocillopora linked SNPs.</p> <p>Pocillopora_meandrina_v3_11Islands_maf05_minQ30_biallelic_nomiss_LD02.unlinked.Hume_et_al_2022.zenodov2.vcf.gz - The Pocillopora SNPs referred to as &#39;unlinked&#39; in the Methods of the associated manuscript.</p> <p>Pocillopora_meandrina_v3_11Islands_maf05_minQ30_biallelic_nomiss_LD02.unlinked.Hume_et_al_2022.zenodov2.vcf.gz.md5 - md5 of the the Pocillopora unlinked SNPs.</p> <p>Porites_lobata_v3_11Islands.raw.Hume_et_al_2022.zenodov2.vcf.genozip - The Pocillopora SNPs referred to as &#39;raw&#39; in the Methods of the associated manuscript. Compressed using genozip (https://genozip.readthedocs.io/index.html).</p> <p>Porites_lobata_v3_11Islands.raw.Hume_et_al_2022.zenodov2.vcf.genozip.md5 - md5 of the the Pocillopora raw SNPs.</p> <p>Porites_lobata_v3_11Islands_maf05_minQ30_biallelic_nomiss.linked.Hume_et_al_2022.zenodov2.vcf.gz - The Pocillopora SNPs referred to as &#39;linked&#39; in the Methods of the associated manuscript.</p> <p>Porites_lobata_v3_11Islands_maf05_minQ30_biallelic_nomiss.linked.Hume_et_al_2022.zenodov2.vcf.gz.md5 - md5 of the the Pocillopora linked SNPs.</p> <p>Porites_lobata_v3_11Islands_maf05_minQ30_biallelic_nomiss_LD02.unlinked.Hume_et_al_2022.zenodov2.vcf.gz - The Pocillopora SNPs referred to as &#39;unlinked&#39; in the Methods of the associated manuscript.</p> <p>Porites_lobata_v3_11Islands_maf05_minQ30_biallelic_nomiss_LD02.unlinked.Hume_et_al_2022.zenodov2.vcf.gz.md5 - md5 of the the Pocillopora unlinked SNPs.</p> <p>PANAMA2021.raw.Hume_et_al_2022.zenodov2.vcf.gz - The Millepora SNPs referred to as &#39;raw&#39; in the Methods of the associated manuscript.</p> <p>PANAMA2021.raw.Hume_et_al_2022.zenodov2.vcf.gz.md5 - md5 of the the Millepora raw SNPs.</p> <p>Millepora_REF_orthologue_genes.Hume_et_al_2022.zenodov2.csv - The Millepora gene list referred to as &#39;target genes&#39; in the Methods of the associated manuscript.</p> <p>Mil_transcriptom.Hume_et_al_2022.zenodov2.fa.gz - The Millepora de novo assembled transcriptome.</p> <p>Mil_transcriptom.Hume_et_al_2022.zenodov2.fa.gz.md5 - md5 of the Millepora de novo assembled transcriptome.</p> <p>&nbsp;</p> <p>mtORF Phylogeny</p> <p>TP-Johnston_mtORF-Pocillo.fa = all sequences</p> <p>TP-Johnston_mtORF-Pocillo.mafft.fa = mafft alignment</p> <p>TP-Johnston_mtORF-Pocillo.mafft.ML.nwk = ML tree newick</p> <p>&nbsp;</p> <p>Hellberg genotype network Porites</p> <p>TP-Hellberg_MM32-Porites.nex = all aligned sequences for this locus with indels encoded</p> <p>TP-Hellberg_MM100-Porites.nex = all aligned sequences for this locus with indels encoded</p> <p>TP-Hellberg_ATPaseB.nex = all aligned sequences for this locus with indels encoded,</p> <p>TP-Hellberg_POFAD.nex = POFAD multilocus genotypic distance,</p> <p>TP-Hellberg_Splitstree.nex= Multilocus genotype network in nexus format</p> <p><br> Gradient Forest Analysis</p> <p>Poc_abund.csv - Pocillopora SSH Occurrences per Site er Island</p> <p>Por_abund.csv - Porites SSH Occurrences per Site er Island</p> <p>mean_depth_por.csv - per site per island mean depth among Porites colonies</p> <p>mean_depth_poc.csv - per site per island mean depth among Pocillopora colonies</p>

opencc-by-4.0Oct 2022View details →
zenodo40/100

Code and Data for: "Signs of local adaptation and phenotypic plastic response to elevation shifted between environmental backgrounds in Snapdragon plants"

<p>Code and data for manuscript: &quot;Signs of local adaptation and phenotypic plastic response to elevation shifted between environmental backgrounds in Snapdragon plants&quot;</p>

opencc-by-4.0Nov 2020View details →
zenodo40/100

Data From: Powerful detection of polygenic selection and environmental adaptation in US beef cattle

<p>GEMMA output containing summary statistics for generation proxy selection mapping (GPSM) and environmental GWAS (envGWAS) selection analyses from&nbsp;<br> Rowan et al. &quot;Powerful detection of polygenic selection and environmental adaptation in US beef cattle&quot; 2021<br> https://doi.org/10.1101/2020.03.11.988121&nbsp; &nbsp;&nbsp;</p> <p>File names identify the analysis run, for example<br> &quot;Gelbvieh_envgwas_desert_summary_stats.txt.gz&quot;<br> Is the Gelbvieh dataset analyzed using the Desert ecoregion as the dependent variable&nbsp;<br> in a univariate envGWAS model.&nbsp;</p> <p>Files are formated according to GEMMA output.</p>

opencc-by-4.0Jan 2021View details →
dryad40/100

Data from: Local adaptation (mostly) remains local: reassessing environmental associations of climate-related candidate SNPs in Arabidopsis halleri

<p>Numerous landscape genomic studies have identified single-nucleotide polymorphisms (SNPs) and genes potentially involved in local adaptation. Rarely, it has been explicitly evaluated whether these environmental associations also hold true beyond the populations studied. We tested whether putatively adaptive SNPs in <em>Arabidopsis</em> <em>halleri</em> (Brassicaceae), characterized in a previous study investigating local adaptation to a highly heterogeneous environment, show the same environmental associations in an independent, geographically enlarged set of 18 populations. We analysed new SNP data of 444 plants with the same methodology (partial Mantel tests, PMTs) as in the original study and additionally with a latent factor mixed model (LFMM) approach. Of the 74 candidate SNPs, 41% (PMTs) and 51% (LFMM) were associated with environmental factors in the independent data set. However, only 5% (PMTs) and 15% (LFMM) of the associations showed the same environment–allele relationships as in the original study. In total, we found 11 genes (31%) containing the same association in the original and independent data set. These can be considered prime candidate genes for environmental adaptation at a broader geographical scale. Our results suggest that selection pressures in highly heterogeneous alpine environments vary locally and signatures of selection are likely to be population-specific. Thus, genotype-by-environment interactions underlying adaptation are more heterogeneous and complex than is often assumed, which might represent a problem when testing for adaptation at specific loci.</p>

opencc-zeroDec 2015View details →
dryad40/100

Environmental effects on genetic variance are likely to constrain adaptation in novel environments

<p>Adaptive plasticity allows populations to cope with environmental variation but is expected to fail as conditions become unfamiliar. In novel conditions, populations may instead rely on rapid adaptation to increase fitness and avoid extinction. Adaptation should be fastest when both plasticity and selection occur in directions of the multivariate phenotype that contain abundant genetic variation. However, tests of this prediction from field experiments are rare. Here, we quantify how additive genetic variance in a multivariate phenotype changes across an elevational gradient, and test whether plasticity and selection align with genetic variation. We do so using two closely related, but ecologically distinct, sister species of Sicilian daisy (Senecio, Asteraceae) adapted to high and low elevations on Mount Etna. Using a paternal half-sibling breeding design, we generated and then reciprocally planted c.19,000 seeds of both species, across an elevational gradient spanning each species' native elevation, and then quantified mortality and five leaf traits of emergent seedlings. We found that genetic variance in leaf traits changed more across elevations than between species. The high-elevation species at novel lower elevations showed changes in the distribution of genetic variance among the leaf traits, which reduced the amount of genetic variance in the directions of selection and the native phenotype. By contrast, the low-elevation species mainly showed changes in the amount of genetic variance at the novel high elevation, and genetic variance was concentrated in the direction of the native phenotype. For both species, leaf trait plasticity across elevations was in a direction of the multivariate phenotype that contained a moderate amount of genetic variance. Together, these data suggest that where plasticity is adaptive, selection on genetic variance for an initially plastic response could promote adaptation. However, large environmental effects on genetic variance are likely to reduce adaptive potential in novel environments.</p>

opencc-zeroDec 2023View details →
zenodo40/100

F I G U R E 4 in Environmental correlates of adaptive diversification in postglacial freshwater fishes

F I G U R E 4 Visual representation of trends in ecomorph number based on phosphorus concentration (μg L 1). Data from Landry et al. (2007) and Siwertsson et al. (2010). Graph plotted in R using the ggplot2 package (Wickham, 2016).

opencc-by-4.0Dec 2023View details →
zenodo40/100

F I G U R E 1 in Environmental correlates of adaptive diversification in postglacial freshwater fishes

F I G U R E 1 Conceptual diagram of the different components examined in this paper and how they may relate to origins and maintenance of sympatric divergent ecomorphs. Created with BioRender.com.

opencc-by-4.0Dec 2023View details →
zenodo40/100

F I G U R E 5 in Environmental correlates of adaptive diversification in postglacial freshwater fishes

F I G U R E 5 Visual representation of trends in ecomorph number based on the number of fish species present in a lake, other than the diversifying species pairs/groups. Data from Siwertsson et al. (2010), Vamosi (2003), and Öhlund et al. (2020). Graph plotted in R using the ggplot2 package (Wickham, 2016).

opencc-by-4.0Dec 2023View details →
zenodo40/100

F I G U R E 3 in Environmental correlates of adaptive diversification in postglacial freshwater fishes

F I G U R E 3 Visual representation of trends in ecomorph number based on bathymetric traits. (a) Lake surface area (km2). Data from Bolnick and Lau (2008), Gordeeva et al. (2015), Lucek et al. (2016), Öhlund et al. (2020), Siwertsson et al. (2010), and Vamosi (2003). (b) Lake maximum depth (m). Data from Gordeeva et al. (2015), Landry et al. (2007), Öhlund et al. (2020), and Siwertsson et al. (2010). Box plots indicate median and interquartile range. Note that the y-axes in graphs consist of untransformed data but are plotted on logarithmic scales due to the large range in reported values for these variables. Graphs plotted in R using the ggplot2 package (Wickham, 2016).

opencc-by-4.0Dec 2023View details →
zenodo40/100

Supplementary Data - Using landscape genomics to infer genomic regions involved in environmental adaptation of soybean genebank accessions

<p><strong>File: 50K_GenotypesEU_raw_UHOH_SoySNP50K.csv.tgz </strong></p> <p>Genotyping data of SoySNP50k SNP array of 170 European soybean varieties.</p> <p>The array includes 51.955 SNP markers.</p> <p>Genotypes of each variety are in columns and each row is a SNP marker. Naming of markers follows the annotation of the soybean genome.</p> <p><strong>File: EUvarieties_infos.csv </strong></p> <p>Description of European varieties</p> <p>Contains variety name, country of origin, EU region and maturity group assignment.</p> <p>&nbsp;</p> <p><strong>File: Supplementary_Data_Haupt_Schmid.xlsx</strong></p> <p>Additional data derived from data analysis. Description of data contained within file (Worksheet &quot;Summary&quot;)</p> <p>&nbsp;</p>

opencc-by-4.0Feb 2022View details →
dryad40/100

Adaptation to environmental temperature in divergent clades of the nematode Pristionchus pacificus

<p><span>Because of ongoing climate change, populations of organisms are being subjected to stressful temperatures more often. This is especially problematic for ectothermic organisms, which are likely to be more sensitive to changes in temperature. Therefore, we need to know if ectotherms have adapted to environmental temperature and, if so, what are the evolutionary mechanisms behind such adaptation. Here, we use the nematode <em>Pristionchus pacificus</em> as a case study to investigate thermal adaptation on the Indian Ocean island of La Réunion, which experiences a range of temperatures from coast to summit. We study the evolution of high temperature tolerance by constructing a phylogenetic tree of strains collected from many different thermal niches. We show that populations of <em>P. pacificus</em> at low altitudes have higher fertility at warmer temperatures. Most likely, this phenotype has arisen recently and at least twice independently, consistent with parallel evolution. We also studied low temperature tolerance and showed that populations from high altitudes have increased their fertility at cooler temperatures. </span><span>Together, these data indicate that <em>P. pacificus</em> strains on La Réunion are subject to divergent selection, adapting to hot and cold niches at the coast and summit of the volcano.</span><span> </span><span>Precisely defining these thermal niches provides essential information for models that predict the impact of future climate change on these populations.</span></p>

opencc-zeroApr 2022View details →
dryad40/100

Data from: Periodic environmental disturbance drives repeated ecomorphological diversification in an adaptive radiation of Antarctic fishes

<p><span>The ecological theory of adaptive radiation has profoundly shaped our conceptualization of the rules that govern diversification. However, while many radiations follow classic early burst patterns of diversification as they fill ecological space, the longer-term fates of these radiations depend on many factors, such as climatic stability. In systems with periodic disturbances, species-rich clades can contain nested adaptive radiations of subclades with their own distinct diversification histories, and how adaptive radiation theory applies in these cases is less clear. Here, we investigated patterns of ecological and phenotypic diversification within two iterative adaptive radiations of cryonotothenioid fishes in Antarctica's Southern Ocean: crocodile icefishes and notoperches. For both clades, we observe evidence of repeated diversification into disparate regions of trait space between closely related taxa and into overlapping regions of trait space between distantly related taxa. We additionally find little evidence that patterns of ecological divergence are correlated with evolution of morphological disparity, suggesting that these axes of divergence may not be tightly linked. Finally, we reveal evidence of repeated convergence in sympatry that suggests niche complementarity. These findings reflect the dynamic history of Antarctic marine habitats, and may guide hypotheses of diversification dynamics in environments characterized by periodic disturbance.</span></p>

opencc-zeroMay 2022View details →
zenodo40/100

Fig. 3 in Adaptations, life-history traits and ecological mechanisms of parasites to survive extremes and environmental unpredictability in the face of climate change

Fig. 3. Flow chart outlining factors that can influence the response of parasites to climate change.

opencc-by-4.0Aug 2020View details →
dryad40/100

Anticipatory plasticity: frog embryos respond to environmental cues by producing an adaptive phenotype at hatching

<p>Developmental plasticity can occur at any life stage, but a context in which it might be crucial is when individuals that produce specific phenotypes early in development gain a competitive advantage at a later life stage. Here we asked if pre-hatching (embryonic) exposure to a nutrient-rich resource can impact hatchling morphology in tadpoles of Mexican spadefoot toads, <em>Spea multiplicata</em>. Induction of a distinctive carnivore morph can occur when a tadpole eats live fairy shrimp. We investigated whether cues from fairy shrimp, detected as embryos, determine hatchling morphology in a manner allowing individuals to take advantage of this nutritious resource. We found that hatchlings with embryonic exposure to shrimp were larger and had larger jaw muscles––traits that increase their ability to compete for shrimp. Thus, embryos can assess and respond to environmental cues by producing preemptive resource-use phenotypes. Such anticipatory plasticity may be an important but understudied form of developmental plasticity.</p>

opencc-zeroFeb 2023View details →
zenodo40/100

Upper thermal tolerance of grassland vipers (Vipera spp.): environmental drivers and local adaptation

<p>The thermal tolerance of ectotherms is a critical factor that influences their distribution, physiology, behaviour, and ultimately survival. Understanding the factors that shape thermal tolerance in these organisms is therefore of great importance for predicting their responses to forecasted climate warming. Here, we investigated the voluntary thermal maximum (VTmax) of nine grassland viper taxa and explored the factors that influence this trait. The small size of these vipers and the open landscape they inhabit renders them particularly vulnerable to overheating and dehydration. We found that the VTmax of grassland vipers is influenced by environmental temperature, precipitation, shortwave flux, and individual body size, rather than by phylogenetic relatedness. Vipers living in colder environments exhibited a higher upper thermal tolerance, contradicting the hypothesis that environmental temperature is positively related to VTmax. Our findings emphasise the importance of considering local to regional adaptation and environmental conditions when studying thermal physiology and the evolution of thermal tolerance in ectotherms.</p>

opencc-by-4.0Mar 2023View details →
zenodo40/100

Code Appendix: Do Seed Dispersal Strategies Reflect Adaptation to Environmental Variability? Functional Ecology, 2023

<p>This code appendix contains all of the R code and data for the manuscript:<br> <br> Van Den Elzen, C. L., N. Sigman, and N. C. Emery. 2023. Do Seed Dispersal Strategies Reflect Adaptation to Environmental Variability?. Functional Ecology (Manuscript ID:&nbsp;FE-2022-00850).<br> <br> Abstract:&nbsp;</p> <p>1. Dispersal is one of the primary mechanisms by which organisms adapt to spatial and temporal variation in the environment. Theory predicts that increasing spatiotemporal variation drives selection for offspring dispersal away from their natal habitat and one another. However, due to inherent difficulties in measuring dispersal in plant systems, there are few empirical tests of the extent to which this hypothesis can explain variation in seed dispersal strategies.</p> <p>2. In this study, we characterized and compared the dispersal patterns of three closely related plant species that segregate across gradients in spatiotemporal variation in seasonal wetlands.</p> <p>3. We tracked individual seeds as they dispersed in their natural habitats to measure seed dispersal distance (the distance traveled from the maternal plant) and inter-seed spread (distances between dispersed seeds), and to identify the plant traits causing within-species variation in seed dispersal. We also evaluated the seed traits causing within-species variation in seed flight distance and terminal velocity in a wind tunnel&nbsp;and a drop tube, respectively.</p> <p>4. We found that average seed dispersal distance was lowest in the species that occupies the most spatiotemporally variable habitat, contradicting our predictions; however, inter-seed spread was lowest in the species from the least variable habitat, which&nbsp;aligned with our expectations.</p> <p>5. The maternal plant and seed traits explaining intraspecific variation in seed dispersal varied among species as well as the method used to measure dispersal potential. Two traits had non-intuitive effects on dispersal, including pappus size, which reduced seed flight distance in two of the focal taxa.</p> <p>6. Overall, our results indicate that the differences we detected in seed dispersal among three closely related plant taxa can be only partially explained by current patterns of environmental variability in their respective habitats, and that the traits driving within species variation in seed dispersal can evolve rapidly and change with the environmental context in which they are measured.</p>

opencc-by-3.0-usMar 2023View details →
dryad40/100

Data from: An adaptive biomolecular condensation response is conserved across environmentally divergent species

<p>Cells must sense and respond to sudden maladaptive environmental changes—stresses—to survive and thrive. Across eukaryotes, stresses such as heat shock trigger conserved responses: growth arrest, a specific transcriptional response, and biomolecular condensation of protein and mRNA into structures known as stress granules under severe stress. The composition, formation mechanism, adaptive significance, and even evolutionary conservation of these condensed structures remain enigmatic. Here we provide an unprecedented view into stress-triggered condensation, its evolutionary conservation and tuning, and its integration into other well-studied aspects of the stress response. Using three morphologically near-identical budding yeast species adapted to different thermal environments and diverged by up to 100 million years, we show that proteome-scale biomolecular condensation is tuned to species-specific thermal niches, closely tracking corresponding growth and transcriptional responses. In each species, poly(A)-binding protein—a core marker of stress granules—condenses in isolation at species-specific temperatures, with conserved molecular features and conformational changes modulating condensation. From the ecological to the molecular scale, our results reveal previously unappreciated levels of evolutionary selection in the eukaryotic stress response, while establishing a rich, tractable system for further inquiry.</p>

opencc-zeroAug 2023View details →
dryad40/100

Adaptation to environmental temperature in divergent clades of the nematode Pristionchus pacificus

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publicApr 2022View details →
dryad40/100

Data from: Periodic environmental disturbance drives repeated ecomorphological diversification in an adaptive radiation of Antarctic fishes

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publicMay 2022View details →
dryad40/100

Data from: Local adaptation (mostly) remains local: reassessing environmental associations of climate-related candidate SNPs in Arabidopsis halleri

Open the record for dataset details and reuse information.

publicAug 2016View details →

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