Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1307061 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Florida’s coral reefs are currently experiencing a multi-year disease-related mortality event, that has resulted in massive die-offs in multiple coral species. Approximately 21 species of coral, including both Endangered Species Act-listed and the primary reef-building species, have displayed tissue loss lesions which often result in whole colony mortality [Stony Coral Tissue Loss Disease (SCTLD)]. Determining the causative agent(s) of coral disease relies on a multidisciplinary approach since the causation may be a combination of abiotic, microbial or viral agents. Metaproteomics was used to survey changes in the molecular landscape in the coral holobiont with the goal of providing useful information not only in diagnosis, but for prediction and prognosis. Specifically, in the case of SCTLD, defining molecular changes in the coral holobiont will help define disease progression and aid in identifying the causative agent by clearly defining traits of disease progression shared across affected species. Using samples from nine coral species (46 samples total; those appearing healthy, n = 23, and diseased, n = 23), analysis of the coral and its associated microbiome were performed using bottom-up proteomics. Ongoing analysis (including improving coral holobiont genome-based search space) will demonstrate the utility of this approach and help define improved future experiments.
2021-05-21 | PXD026192 | Pride
Project description:Female genital tract (FGT) diseases such as bacterial vaginosis (BV) and sexually transmitted infections are prevalent in South Africa, with young women being at an increased risk. Since imbalances in the FGT microbiome are associated with FGT diseases, it is vital to investigate the factors that influence FGT health. The mycobiome plays an important role in regulating mucosal health, especially when the bacterial component is disturbed. However, we have a limited understanding of the FGT mycobiome since many studies have focused on bacterial communities and have neglected low abundance taxonomic groups, such as fungi. To reduce this knowledge deficit, we present the first large-scale metaproteomic study to define the taxonomic composition and potential functional processes of the FGT mycobiome in South African reproductive-age women. We examined FGT fungal communities present in 123 women by collecting lateral vaginal wall swabs for liquid chromatography-tandem mass spectrometry.
2025-03-28 | PXD046053 | Pride
Project description:Coral microbiome isolates characterization
| PRJNA637498 | ENA
Project description:Coral microbiome isolates characterization
| PRJNA637595 | ENA
Project description:Coral microbiome isolates characterization
| PRJNA637594 | ENA
Project description:The surprising observation that virtually the entire human genome is transcribed means we know very little about the function of many emerging classes of RNAs, except their astounding diversity. Traditional RNA function prediction methods rely on sequence or alignment information, which are limited in their ability to classify classes of non-coding RNAs (ncRNAs). To address this, we developed CoRAL, a machine learning-based approach for classification of RNA molecules. CoRAL uses biologically interpretable features including fragment length, cleavage specificity, and antisense transcription to distinguish between different ncRNA classes. We evaluated CoRAL using genome-wide small RNA sequencing (smRNA-seq) datasets from two human tissue types (brain and skin [GSE31037]), and were able to classify six different types of RNA transcripts with 79~80% accuracy in cross-validation experiments, and with 71~73% accuracy when CoRAL uses one tissue type for training and the other as validation. Analysis by CoRAL revealed that long intergenic ncRNAs, small cytoplasmic RNAs, and small nuclear RNAs show more tissue specificity, while microRNAs, small nucleolar, and transposon-derived RNAs are highly discernible and consistent across the two tissue types. The ability to consistently annotate loci across tissue types demonstrates the potential of CoRAL to characterize ncRNAs using smRNA-seq data in less characterized organisms.
2013-07-07 | GSE43335 | GEO
Project description:Branching coral species like the Caribbean Acroporids are long lived and reproduce asexually via breakage of branches. Fragmentation is the dominant mode of local population maintenance for these corals across much of their range. Thus, large genets with many member ramets (colonies) are common. Each of the ramets experiences different microenvironments, especially with respect to light and water flow. Here, we investigate whether colonies that are members of the same genet have different epigenomes because of differences in their microenvironments. The Florida Keys experienced a large- scale coral bleaching event in 2014-2015 caused by high water temperatures. During the event, ramets of the same coral genet bleached differently. Previous work had shown that this was unlikely to be due to their eukaryotic algal symbionts (Symbiodinium ‘fitti’) because each genet of this coral species typically harbors a single strain of S. ‘fitti’. Characterization of the microbiome via 16S tag sequencing did not provide evidence for a central role of microbiome variation in determining bleaching response. Instead, epigenetic changes were significantly correlated with the host’s genetic background, the position of the sampled polyps within the colonies (e.g. tip versus base of colony), and differences in the colonies’ condition during the bleaching event. We conclude that microenvironmental differences in growing conditions led to long-term changes in the way the ramets methylated their genomes and thus to a differential bleaching response.
2019-12-05 | GSE124246 | GEO
Project description:Branching coral species like the Caribbean Acroporids are long lived and reproduce asexually via breakage of branches. Fragmentation is the dominant mode of local population maintenance for these corals across much of their range. Thus, large genets with many member ramets (colonies) are common. Each of the ramets experiences different microenvironments, especially with respect to light and water flow. Here, we investigate whether colonies that are members of the same genet have different epigenomes because of differences in their microenvironments. The Florida Keys experienced a large- scale coral bleaching event in 2014-2015 caused by high water temperatures. During the event, ramets of the same coral genet bleached differently. Previous work had shown that this was unlikely to be due to their eukaryotic algal symbionts (Symbiodinium ‘fitti’) because each genet of this coral species typically harbors a single strain of S. ‘fitti’. Characterization of the microbiome via 16S tag sequencing did not provide evidence for a central role of microbiome variation in determining bleaching response. Instead, epigenetic changes were significantly correlated with the host’s genetic background, the position of the sampled polyps within the colonies (e.g. tip versus base of colony), and differences in the colonies’ condition during the bleaching event. We conclude that microenvironmental differences in growing conditions led to long-term changes in the way the ramets methylated their genomes and thus to a differential bleaching response.
2020-12-18 | GSE124256 | GEO
Project description:Purpose: There is a dearth of knowledge regarding the molecular pathology of growth anomaly in corals. We investigated the gene expression profile of Montipora capitata metatranscriptomes from healthy and diseased (growth anomaly) coral colonies to elucidate differentially expressed genes. Methods: mRNA profiles of coral tissue (including symbionts) were generated from three different tissue states: healthy, affected and unaffected. Healthy tissue was collected from coral colonies not affected by growth anomaly. Affected tissue was collected from coral growth anomaly lesions. Unaffected tissue was collected from coral colonies affected by growth anomaly.
2017-06-20 | GSE97888 | GEO