Ontology highlight
ABSTRACT:
PROVIDER: PRJNA380807 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR5429530_1.fastq.gz | Fastqsanger.gz | |||
| SRR5429530_2.fastq.gz | Fastqsanger.gz | |||
| SRR5429540_1.fastq.gz | Fastqsanger.gz | |||
| SRR5429540_2.fastq.gz | Fastqsanger.gz | |||
| SRR5429531_1.fastq.gz | Fastqsanger.gz |
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Project description:Corals in nearshore marine environments are increasingly exposed to reduced water quality, which is the major local threat to coral reefs in Hawaii. Corals surviving in such conditions may have adapted to withstand sedimentation, pollutants, and other environmental stressors. Lobe coral (Porites lobata) populations from Maunalua Bay, Hawaii showed clear genetic differentiation along with distinct cellular protein expressions between the 'polluted, high-stress' nearshore site and the 'low-stress' offshore site. To understand the driving force of the observed genetic partitioning, reciprocal transplant and common-garden experiments were conducted using the nearshore and offshore colonies of P. lobata from Maunalua Bay to assess phenotypic differences between the two coral populations. Stress-related physiological and molecular responses were compared between the two populations. Proteomic responses highlighted the inherent differences in the cellular metabolic state and activities between the two populations under the same environmental conditions; nearshore corals did not significantly alter their proteome between the sites, while offshore corals responded to the nearshore transplantation with increased abundances of proteins associated with detoxification, antioxidant, and various metabolic processes. The response differences across multiple phenotypes suggest that the observed genetic partitioning was likely due to local adaptation.
2021-04-20 | PXD021407 | Pride
Project description:In light of global reef decline new methods to accurately, cheaply, and quickly evaluate coral metabolic states are needed to assess reef health. Metabolomic profiling can describe the response of individuals to disturbance (i.e., shifts in environmental conditions) across biological models and is a powerful approach for characterizing and comparing coral metabolism. For the first time, we assess the utility of a proton-nuclear magnetic resonance spectroscopy (1H-NMR)-based metabolomics approach in characterizing coral metabolite profiles by 1) investigating technical, intra-, and inter-sample variation, 2) evaluating the ability to recover targeted metabolite spikes, and 3) assessing the potential for this method to differentiate among coral species. Our results indicate 1H-NMR profiling of Porites compressa corals is highly reproducible and exhibits low levels of variability within and among colonies. The spiking experiments validate the sensitivity of our methods and showcase the capacity of orthogonal partial least squares discriminate analysis (OPLS-DA) to distinguish between profiles spiked with varying metabolite concentrations (0 mM, 0.1 mM, and 10 mM). Finally, 1H-NMR metabolomics coupled with OPLS-DA, revealed species-specific patterns in metabolite profiles among four reef-building corals (Pocillopora damicornis, Porites lobata, Montipora aequituberculata, and Seriatopora hystrix). Collectively, these data indicate that 1H-NMR metabolomic techniques can profile reef-building coral metabolomes and have the potential to provide an integrated picture of the coral phenotype in response to environmental change.
2014-11-20 | MTBLS116 | MetaboLights
Project description:Bacterial Community Porites lobata coral mucus
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Project description:Raw metabolomic Mass spectrometry data from thermal stress experiment on 3 corals from the Great Barrier Reef, Acropora hyacinthus , Porites lobata and Stylophora pistillata.
2024-05-22 | MSV000094832 | MassIVE
Project description:Coral growth anomalies (GAs) are tumor-like protrusions that are detrimental to coral health, impacting both the coral skeleton and soft tissues. These lesions are increasingly found throughout the tropics and are commonly associated with high human population density, yet little is known about the molecular pathology of the disease. Here, we investigate the metabolic impacts of GAs through 1H NMR metabolomics in Porites compressa tissues from a site of high disease prevalence (Coconut Island, Hawaii). We annotated 18 metabolites through complementary 1H and 1H–13C heteronuclear single quantum correlation (HSQC) data that increase confidence in pathway analyses and may bolster future efforts in coral metabolite annotation. Mass of extracted metabolites was elevated in both GA and unaffected (normal tissue from a diseased colony) compared to reference (normal tissue from GA-free colony) samples, potentially indicating elevated metabolic activity in GA-afflicted colonies. Relatively high variation in metabolomic profiles among corals of the same treatment confounded data interpretation, however, analyses of paired GA and unaffected samples identified 73 features that differed between these respective metabolome types. These features were largely annotated as unknowns, but 1-methylnicotinamide and trigonelline were found to be elevated in GA samples, while betaine, glycine and histamine were lower in GA samples. Pathway analyses suggest decreased choline oxidation in GA samples, making this a pathway of interest for future targeted studies. Collectively, our results provide unique insights into GA pathophysiology by showing these lesions alter both the absolute and relative metabolism of affected colonies and by identifying features (metabolites and unknowns) and metabolic pathways of interest in GA pathophysiology going forward.
2021-06-15 | MTBLS2424 | MetaboLights
Project description:Background: Array comparative genomic hybridization (aCGH) is commonly used to screen different types of genetic variation in humans and model species. Here, we performed aCGH using an oligonucleotide gene-expression array for a non-model species, the intertidal snail Littorina saxatilis. First, we tested what types of genetic variation can be detected by this method using direct re-sequencing and comparison to the Littorina genome draft. Secondly, we performed a genome-wide comparison of four closely related Littorina species: L. fabalis, L. compressa, L. arcana and L. saxatilis and of populations of L. saxatilis found in Spain, Britain and Sweden. Finally, we tested whether we could identify genetic variation underlying M-bM-^@M-^\CrabM-bM-^@M-^] and M-bM-^@M-^\WaveM-bM-^@M-^] ecotypes of L. saxatilis. Results: We could reliably detect copy number variations, deletions and high sequence divergence (i.e. above 3%), but not single nucleotide polymorphisms. The overall hybridization pattern and number of significantly diverged genes were in close agreement with earlier phylogenetic reconstructions based on single genes. The trichotomy of L. arcana, L. compressa and L. saxatilis could not be resolved and we argue that these divergence events have occurred recently and very close in time. We found evidence for high levels of segmental duplication in the Littorina genome (10% of the transcripts represented on the array and up to 23% of the analyzed genomic fragments); duplicated genes and regions were mostly the same in all analyzed species. Finally, this method discriminated geographically distant populations of L. saxatilis, but we did not detect any significant genome divergence associated with ecotypes of L. saxatilis. Conclusions: The present study provides new information on the sensitivity and the potential use of oligonucleotide arrays for genotyping of non-model organisms. Applying this method to Littorina species yields insights into genome evolution following the recent species radiation and supports earlier single-gene based phylogenies. Genetic differentiation of L. saxatilis ecotypes was not detected in this study, despite pronounced innate phenotypic differences. The reason may be that these differences are due to single-nucleotide polymorphisms. Genomic DNA samples of L. fabalis, L. compressa, L. arcana and 3 geographic populations x 2 ecotypes of L. saxatilis (n=4 per group) have been hybridized to a transcriptomic oligoarray.
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