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58 results for “Thermotolerance”
Coral thermotolerance retained following year-long exposure to a novel environment
<p>Description of datasets:</p> <h4>HTSeqCounts</h4> <p>Raw HTSeq count data used for downstream RNA sequencing analyses and visualisations including Principal Component Analysis and Differential Gene Expression analysis of the four habitat groups (mangrove to reef, reef to reef, wild mangrove and wild reef).</p> <h4>GO enriched gene results:</h4> <p>GO enriched genes summarised by broad categories of GO Slims for <em>Pocillopora acuta</em> corals originating from a mangrove system vs colonies from an adjacent reef site, translocated to a reef environment for one year. Samples for gene expression were collected during an acute heat stress assay to assess differentially enriched genes between mangrove and reef corals under 36 ºC. Enriched GO terms were grouped into broader functional categories using the “goSlim” function in the GSEABase R package with GOslim generic obo as the reference database to allow for a summary of key functions enriched in groups under heat stress. See manuscript methods for further detail on differential gene expression analysis.</p> <h4>2022-2023 mangrove/reef temperature and pH</h4> <p>Temperature and pH data measured in the Low Isles mangrove lagoon and reef habitat using HOBO MX2510 loggers deployed from February 2022 - February 2023. </p> <h4>Methylated DNA data</h4> <p>Percent DNA methylation relative to total DNA of mangrove to reef, reef to reef and wild mangrove groups under acute temperature stress during the February 2023 CBASS experiment.</p> <h4>Analysis code.zip</h4> <p>A copy of all R code used in the data analysis of this project</p> <p> </p>
Free‐living and symbiotic lifestyles of a thermotolerant coral endosymbiont display profoundly distinct transcriptomes under both stable and heat stress conditions
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Multiple sequence alignments: Detection and isolation of a new member of Burkholderiaceae‑related endofungal bacteria from Saksenaea boninensis sp. nov., a new thermotolerant fungus in Mucorales
<p><strong>Methods:</strong></p><p>Nucleotide sequences were aligned independently for each region using MAFFT v7.212 (Katoh and Standley, 2013). The obtained alignment blocks were subject to Gblocks 0.91b (Castresana, 2000) to remove poorly aligned positions with the relaxed selection setting described in Talavera & Castresana (2007) using the following parameters (-t = d -b2 = 9 -b3 = 10 -b4 = 5 -b5 = h). After automatically removing gaps, the alignment blocks were viewed using MEGA 6.06 software (Tamura et al., 2013) and poorly aligned positions at either end of the alignments were removed manually. Pairwise distances of the nucleotide sequences (ITS2, ITS1-5.8S-ITS2, LSU, and tef1) of the ex-type strains of seven <i>Saksenaea</i> spp. and the representative isolate <i>S. boninensis</i> Sak4 were calculated by MEGA 6.06 software (Tamura et al. 2013). Multiple sequence alignment of 16S rRNA gene of the family <i>Burkholderiaceae</i> was prepared for the phylogeny of a bacterial endosymbiont. Multiple sequence alignments of ITS, LSU, and tef1 genes of <i>Saksenaea</i> spp. (Mucorales) were separately prepared for the phylogeny of a fungal host. Concatenated dataset of these genes were also prepared. All nucleotide sequences were retrieved from GenBank (See "Sequence_ID.csv" and taxon names of each alignment). </p><p> </p><p><strong>Description of files:</strong></p><p><strong>A. Phylogeny of the family </strong><i><strong>Burkholderiaceae</strong></i><strong> (Bacterial endosymbiont):</strong></p><p>1. Burkholderiaceae_16S_RAW.fasta</p><p>Non-aligned dataset of 16S rRNA gene of the family <i>Burkholderiaceae</i>.</p><p> </p><p>2. Burkholderiaceae_16S_aligned.fasta</p><p>Aligned dataset of 16S rRNA gene of the family <i>Burkholderiaceae</i>.</p><p> </p><p><strong>B. Phylogenies of </strong><i><strong>Saksenaea</strong></i><strong> spp. (Fungal host):</strong></p><p>1. Sequence_ID_v2.csv</p><p>Taxon names, accession numbers, and sequence ID for the concatenated multiple sequence alignment are listed.</p><p> </p><p>2. Saksenaea_ITS_RAW_v2.fasta</p><p>Non-aligned dataset of ITS1-5.8S-ITS2 region of <i>Saksenaea</i> spp. </p><p> </p><p>3. Saksenaea_ITS_aligned_v2.fasta</p><p>Aligned dataset of ITS1-5.8S-ITS2 region of <i>Saksenaea</i> spp. Only used for ITS1-5.8S-ITS2 phylogeny.</p><p> </p><p>4. Saksenaea_LSU_RAW_v2.fasta</p><p>Non-aligned dataset of LSU gene region of <i>Saksenaea</i> spp. </p><p> </p><p>5. Saksenaea_LSU_aligned_v2.fasta</p><p>Aligned dataset of LSU gene region of <i>Saksenaea</i> spp. Only used for LSU phylogeny.</p><p> </p><p>6. Saksenaea_tef1_RAW_v2.fasta</p><p>Non-aligned dataset of tef1 gene region of <i>Saksenaea</i> spp. </p><p> </p><p>7. Saksenaea_tef1_aligned_v2.fasta</p><p>Aligned dataset of tef1 gene region of <i>Saksenaea</i> spp. Only used for tef1 phylogeny.</p><p> </p><p><strong><Concatenated dataset 1 (ITS2, LSU, tef1)></strong></p><p>8. Saksenaea_ITS2_for_concatenated_RAW_v2.fasta</p><p>Non-aligned dataset of ITS2 region of <i>Saksenaea</i> spp. used for preparation of a concatenated dataset 1.</p><p> </p><p>9. Saksenaea_ITS2_for_concatenated_aligned_v2.fasta</p><p>Aligned dataset of ITS2 region of <i>Saksenaea</i> spp. used for preparation of a concatenated dataset 1.</p><p> </p><p>10. Saksenaea_LSU_for_concatenated_RAW_v2.fasta</p><p>Non-aligned dataset of LSU gene region of <i>Saksenaea</i> spp. used for preparation of concatenated datasets 1 and 2.</p><p> </p><p>11. Saksenaea_LSU_for_concatenated_aligned_v2.fasta</p><p>Aligned dataset of LSU gene region of <i>Saksenaea</i> spp. used for preparation of concatenated datasets 1 and 2.</p><p> </p><p>12. Saksenaea_tef1_for_concatenated_RAW_v2.fasta</p><p>Non-aligned dataset of tef1 gene region of <i>Saksenaea</i> spp. used for preparation of concatenated datasets 1 and 2.</p><p> </p><p>13. Saksenaea_tef1_for_concatenated_aligned_v2.fasta</p><p>Aligned dataset of tef1 gene region of <i>Saksenaea</i> spp. used for preparation of concatenated datasets 1 and 2.</p><p> </p><p>14. Saksenaea_ITS2_LSU_tef1_concatenated_dataset1.fasta</p><p>Concatenated dataset of three multiple sequence alignments (9, 11, and 13). This concatenated dataset was used for the main phylogeny of <i>Saksenaea</i> spp.</p><p> </p><p><strong><Concatenated dataset 2 (ITS1-5.8S-ITS2, LSU, tef1)></strong></p><p>15. Saksenaea_ITS_for_concatenated_RAW_v2.fasta</p><p>Non-aligned dataset of ITS1-5.8S-ITS2 region of <i>Saksenaea</i> spp. used for preparation of a concatenated dataset 2.</p><p> </p><p>16. Saksenaea_ITS_for_concatenated_aligned_v2.fasta</p><p>Aligned dataset of ITS1-5.8S-ITS2 region of <i>Saksenaea</i> spp. used for preparation of a concatenated dataset 2.</p><p>Blank sequences were inserted for five isolates of <i>Saksenaea longicolla</i> after the alignment.</p><p> </p><p>17.Saksenaea_ITS_LSU_tef1_concatenated_dataset2.fasta</p><p>Concatenated dataset of three multiple sequence alignments (15, 11, and 13). This concatenated dataset was used for the main phylogeny of <i>Saksenaea</i> spp.</p><p> </p><p><strong>C. Pairwise distances of the ex-type strains of </strong><i><strong>Saksenaea</strong></i><strong> spp.</strong></p><p>1. Saksenaea_ITS_type_RAW.fasta</p><p>Non-aligned dataset of ITS1-5.8S-ITS2 region of the ex-type strains of <i>Saksenaea</i> spp.</p><p> </p><p>2. Saksenaea_ITS2_type_aligned.fasta</p><p>Aligned dataset of ITS2 region of the ex-type strains of <i>Saksenaea</i> spp.</p><p> </p><p>3.Saksenaea_ITS_type_aligned.fasta</p><p>Aligned dataset of ITS1-5.8S-ITS2 region of the ex-type strains of <i>Saksenaea</i> spp. without <i>Saksenaea longicolla</i>.</p><p> </p><p>4. Saksenaea_LSU_type_RAW.fasta</p><p>Non-aligned dataset of LSU gene region of the ex-type strains of <i>Saksenaea </i>spp.</p><p> </p><p>5. Saksenaea_LSU_type_aligned.fasta</p><p>Aligned dataset of LSU gene region of the ex-type strains of <i>Saksenaea</i> spp.</p><p> </p><p>6. Saksenaea_tef1_type_RAW.fasta</p><p>Non-aligned dataset of tef1 gene region of the ex-type strains of <i>Saksenaea</i> spp.</p><p> </p><p>7. Saksenaea_tef1_type_aligned.fasta</p><p>Aligned dataset of tef1 gene region of the ex-type strains of <i>Saksenaea</i> spp.</p>
Data from: Consequences of gene editing of PRLR on thermotolerance, growth, and male reproduction in cattle
<p>Global warming is a major challenge to the sustainable and humane production of food because of the increased risk of livestock to heat stress. Here, the example of the prolactin receptor (<em>PRLR</em>) gene is used to demonstrate how gene editing can increase the resistance of cattle to heat stress by the introduction of mutations conferring thermotolerance. Several cattle populations in South and Central America possess natural mutations in <em>PRLR</em> that result in affected animals having short hair and being thermotolerant. CRISPR/Cas9 technology was used to introduce variants of <em>PRLR</em> in two thermosensitive breeds of cattle – Angus and Jersey. Gene-edited animals exhibited superior ability to regulate vaginal temperature (heifers) and rectal temperature (bulls) compared to animals that were not gene-edited. Moreover, gene-edited animals exhibited superior growth characteristics. There was no evidence for deleterious effects of the mutation on carcass characteristics or male reproductive function. These results indicate the potential for reducing heat stress in relevant environments to enhance cattle productivity. <strong><br></strong></p>
Dataset for "On Developing an ML-Based Approach for the Automatic Characterization of Behavioral Phenotypes for Dairy Cows Relevant to Thermotolerance"
<p>This dataset consists of 3,421 videos filmed at T & K Dairy in Snyder, TX, over a 24-hour period on March 12-13, 2023. These videos were then used to train, validate, and evaluate a computer vision algorithm that is capable of automatically identifying cows using their coat patterns.</p>
Data from: Consequences of gene editing of PRLR on thermotolerance, growth, and male reproduction in cattle
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Data and code from: Assessing the effect of experimental evolution under combined thermal-nutritional stress on larval thermotolerance and thermal plasticity in Drosophila melanogaster
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Data from: Heat shock factor ZmHsf17 positively regulates phosphatidic acid phosphohydrolase ZmPAH1 and enhances maize thermotolerance
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Data from: Symbiodinium thermophilum sp. nov., a thermotolerant symbiotic alga prevalent in corals of the world's hottest sea, the Persian/Arabian Gulf
Coral reefs are in rapid decline on a global scale due to human activities and a changing climate. Shallow water reefs depend on the obligatory symbiosis between the habitat forming coral host and its algal symbiont from the genus Symbiodinium (zooxanthellae). This association is highly sensitive to thermal perturbations and temperatures as little as 1°C above the average summer maxima can cause the breakdown of this symbiosis, termed coral bleaching. Predicting the capacity of corals to survive the expected increase in seawater temperatures depends strongly on our understanding of the thermal tolerance of the symbiotic algae. Here we use molecular phylogenetic analysis of four genetic markers to describe Symbiodinium thermophilum, sp. nov. from the Persian/Arabian Gulf, a thermally tolerant coral symbiont. Phylogenetic inference using the non-coding region of the chloroplast psbA gene resolves S. thermophilum as a monophyletic lineage with large genetic distances from any other ITS2 C3 type found outside the Gulf. Through the characterisation of Symbiodinium associations of 6 species (5 genera) of Gulf corals, we demonstrate that S. thermophilum is the prevalent symbiont all year round in the world's hottest sea, the southern Persian/Arabian Gulf.
Data from: Response diversity in Mediterranean coralligenous assemblages facing climate change: Insights from a multispecific thermotolerance experiment
Climate change threatens coastal benthic communities on a global scale. However, the potential effects of ongoing warming on mesophotic temperate reefs at the community level remain poorly understood. Investigating how different members of these communities will respond to the future expected environmental conditions is, therefore, key to anticipating their future trajectories and developing specific management and conservation strategies. Here, we examined the responses of some of the main components of the highly diverse Mediterranean coralligenous assemblages to thermal stress. We performed thermotolerance experiments with different temperature treatments (from 26 to 29°C) with 10 species from different phyla (three anthozoans, six sponges and one ascidian) and different structural roles. Overall, we observed species‐specific contrasting responses to warming regardless of phyla or growth form. Moreover, the responses ranged from highly resistant species to sensitive species and were mostly in agreement with previous field observations from mass mortality events (MMEs) linked to Mediterranean marine heat waves. Our results unravel the diversity of responses to warming in coralligenous outcrops and suggest the presence of potential winners and losers in the face of climate change. Finally, this study highlights the importance of accounting for species‐specific vulnerabilities and response diversity when forecasting the future trajectories of temperate benthic communities in a warming ocean.
Data from: Evidence for a host role in thermotolerance divergence between populations of the mustard hill coral (Porites astreoides) from different reef environments
Studying the mechanisms that enable coral populations to inhabit spatially varying thermal environments can help evaluate how they will respond in time to the effects of global climate change and elucidate the evolutionary forces that enable or constrain adaptation. Inshore reefs in the Florida Keys experience higher temperatures than offshore reefs for prolonged periods during the summer. We conducted a common garden experiment with heat stress as our selective agent to test for local thermal adaptation in corals from inshore and offshore reefs. We show that inshore corals are more tolerant of a 6-week temperature stress than offshore corals. Compared with inshore corals, offshore corals in the 31 °C treatment showed significantly elevated bleaching levels concomitant with a tendency towards reduced growth. In addition, dinoflagellate symbionts (Symbiodinium sp.) of offshore corals exhibited reduced photosynthetic efficiency. We did not detect differences in the frequencies of major (>5%) haplotypes comprising Symbiodinium communities hosted by inshore and offshore corals, nor did we observe frequency shifts ('shuffling') in response to thermal stress. Instead, coral host populations showed significant genetic divergence between inshore and offshore reefs, suggesting that in Porites astreoides, the coral host might play a prominent role in holobiont thermotolerance. Our results demonstrate that coral populations inhabiting reefs <10-km apart can exhibit substantial differences in their physiological response to thermal stress, which could impact their population dynamics under climate change.
Selection and characterization of Beauveria bassiana isolates highly thermotolerant and toxic against Aphis gossypii (Hemiptera: Aphididae)
<p>these raw data are supporting the results of the paper entiled "<strong>Selection and characterization of <em>Beauveria bassiana </em>isolates highly thermotolerant and toxic against <em>Aphis gossypii</em> (Hemiptera: Aphididae)"</strong></p>
Data from: Response diversity in Mediterranean coralligenous assemblages facing climate change: Insights from a multispecific thermotolerance experiment
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Data from: Symbiodinium thermophilum sp. nov., a thermotolerant symbiotic alga prevalent in corals of the world’s hottest sea, the Persian/Arabian Gulf
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Data from: Evidence for a host role in thermotolerance divergence between populations of the mustard hill coral (Porites astreoides) from different reef environments
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Data from: Intraspecific and interspecific variation in thermotolerance and photoacclimation in Symbiodinium dinoflagellates
Light and temperature are major drivers in the ecology and biogeography of symbiotic dinoflagellates living in corals and other cnidarians. We examined variations in physiology among 11 strains comprising five species of clade A Symbiodinium. We grew cultures at 26°C (control) and 32°C (high temperature) over a duration of 18 days while measuring growth and photochemical efficiency (Fv/Fm). Responses to thermal stress ranged from susceptible to tolerant across species and strains. Most strains exhibited a decrease in cell densities and Fv/Fm when grown at 32°C. Tolerance to high temperature (T32) was calculated for all strains, ranging from 0 (unable to survive at high temperature) to 1 (able survive at high temperature). There was substantial variation in thermotolerance across species and among strains. One strain had a T32 close to 1, indicating that growth was not reduced at 32°C for only this one strain. To evaluate the combined effect of temperature and light on physiological stress, we selected three strains with different levels of thermotolerance (tolerant, intermediate and susceptible) and grew them under five different light intensities (65, 80, 100, 240 and 443 µmol quanta m−2 s−1) at 26 and 32°C. High irradiance exacerbated the effect of high temperature, particularly in strains from thermally sensitive species. This work further supports the recognition that broad physiological differences exist not only among species within Symbiodinium clades, but also among strains within species demonstrating that thermotolerance varies widely between species and among strains within species.
Data from: Intraspecific and interspecific variation in thermotolerance and photoacclimation in Symbiodinium dinoflagellates
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Data from: Hsp70 protein levels and thermotolerance in Drosophila subobscura: a reassessment of the thermal co-adaptation hypothesis
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Transcriptomic response of tall fescue to heat stress and improved thermotolerance by melatonin and 24-epibrassinolide
GEO Series GSE101699. Lolium arundinaceum. 6 samples. Type: Expression profiling by high throughput sequencing.
An Ancient COI1-independent Function for Reactive Electrophilic Oxylipins in Thermotolerance [array]
GEO Series GSE141429. Arabidopsis thaliana. 3 samples. Type: Expression profiling by array.
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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.