JaPseCliv
Ontology highlight
ABSTRACT:
PROVIDER: PRJEB97659 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:Pseudodiploria clivosa (knobby brain coral), genomic and transcriptomic data
| PRJEB97658 | ENA
Project description:Microbiota of the scleractinian brain coral Pseudodiploria strigosa. Raw sequence reads
| PRJNA610838 | 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: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. Four samples were sequenced, each one coming from frozen brain tissue (frontal cortex) of a deceased female human patient with no remarkable pathology.
2013-07-07 | E-GEOD-43335 | biostudies-arrayexpress
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
Project description:Background Coral reefs belong to the most ecologically and economically important ecosystems on our planet. Yet, they are under steady decline worldwide due to rising sea surface temperatures, disease, and pollution. Understanding the molecular impact of these stressors on different coral species is imperative in order to predict how coral populations will respond to this continued disturbance. The use of molecular tools such as microarrays has provided deep insight into the molecular stress response of corals. Here, we have performed comparative genomic hybridizations (CGH) with different coral species to an Acropora palmata microarray platform containing 13,546 cDNA clones in order to identify potentially rapidly evolving genes and to determine the suitability of existing microarray platforms for use in gene expression studies (via heterologous hybridization). Results Our results showed that the current microarray platform for A. palmata is able to provide biological relevant information for a wide variety of coral species covering both the complex clade as well the robust clade. Analysis of the fraction of highly diverged genes showed a significantly higher amount of genes without annotation corroborating previous findings that point towards a higher rate of divergence for taxonomically restricted genes. Among the genes with annotation, we found many mitochondrial genes to be highly diverged in M. faveolata when compared to A. palmata, while the majority of nuclear encoded genes maintained an average divergence rate. Conclusions The use of present microarray platforms for transcriptional analyses in different coral species will greatly enhance the understanding of the molecular basis of stress and health and highlight evolutionary differences between scleractinian coral species. On a genomic basis, we show that cDNA arrays can be used to identify patterns of divergence. Mitochondrion-encoded genes seem to have diverged faster than nuclear encoded genes in robust corals. Accordingly, this needs to be taken into account when using mitochondrial markers for scleractinian phylogenies.
2012-11-22 | GSE37279 | GEO
Project description:Coral reefs are based on the symbiotic relationship between corals and photosynthetic dinoflagellates of the genus Symbiodinium. We followed gene expression of coral larvae of Acropora palmata and Montastraea faveolata after exposure to Symbiodinium strains that differed in their ability to establish symbioses. We show that the coral host transcriptome remains almost unchanged during infection by competent symbionts, but is massively altered by symbionts that fail to establish symbioses. Our data suggest that successful coral-algal symbioses depend mainly on the symbionts' ability to enter the host in a stealth manner rather than a more active response from the coral host.
2009-04-01 | GSE14923 | GEO
Project description:A mutualistic relationship between reef-building corals and endosymbiotic algae (Symbiodinium spp.) forms the basis for the existence of coral reefs. Genotyping tools for Symbiodinium spp. have added a new level of complexity to studies concerning cnidarian growth, nutrient acquisition, and stress. For example, the response of the coral holobiont to thermal stress is connected to the host-Symbiodinium genotypic combination, as different partnerships can have different bleaching susceptibilities. If, and to what extent, differences in algal symbiont clade contents can exert effects on the coral host transcriptome is currently unknown. In this study, we monitored algal physiological parameters and profiled the coral host transcriptional responses in acclimated, thermally stressed, and recovered coral fragments using a custom cDNA gene expression microarray. Combining these analyses with results from algal and host genotyping revealed a striking symbiont effect on both the acclimated coral host transcriptome and the magnitude of the thermal stress response. This is the first study that links coral host transcriptomic patterns to the clade content of their algal symbiont community. Our data provide a critical step to elucidating the molecular basis of the apparent variability seen among different coral-algal partnerships.
2009-05-31 | GSE15253 | GEO