Ostreobium
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA962936 | ENA |
REPOSITORIES: ENA
Similar Datasets
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:Multiomics of faecal samples collected from individuals in families with multiple cases of type 1 diabetes mellitus (T1DM) over 3 or 4 months. Metagenomic and metatranscriptomic sequencing and metaproteomics were carried out, as well as whole human genome sequencing. Phenotypic data is available.
2017-10-19 | MSV000081630 | MassIVE
Project description:Multiomics of faecal samples collected from individuals in families with multiple cases of type 1 diabetes mellitus (T1DM) over 3 or 4 months. Metagenomic and metatranscriptomic sequencing and metaproteomics were carried out, as well as whole human genome sequencing. Phenotypic data is available.
2016-08-22 | PXD003791 | Pride
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:Detailed analyses of the clone-based genome assembly reveal that the recent duplication content of mouse (4.94%) is now comparable to that of human (5.5%), in contrast to previous estimates from the whole-genome shotgun sequence assembly. The architecture of mouse and human genomes differ dramatically; most mouse duplications are organized into discrete clusters of tandem duplications that are depleted for genes/transcripts and enriched for LINE1 and LTR retroposons. We assessed copy-number variation of the C57BL/6J duplicated regions within 15 mouse strains used for genetic association studies, sequencing, and the mouse phenome project. We determined that over 60% of these basepairs are polymorphic between the strains (on average 20 Mbp of copy-number variable DNA between different mouse strains). Our data suggest that different mouse strains show comparable, if not greater, copy-number polymorphism when compared to human; however, such variation is more locally restricted. We show large and complex patterns of inter-strain copy-number variation restricted to large gene families associated with spermatogenesis, pregnancy, viviparity, phermone signaling, and immune response. Keywords: comparative genomic hybridization
2008-05-10 | GSE11369 | 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
Project description:Phylogenetic position of the coral symbiont Ostreobium inferred from chloroplast genome data
| PRJNA362979 | ENA
Project description:SRNAs from field collected Coffea canephora leaves were profiled by Illumina sequencing and 63 unique microRNA genes belonging to 34 families were found.
2014-12-01 | GSE46617 | GEO