Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1101115 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR28710856.fastq.gz | Fastqsanger.gz | |||
| SRR28710857.fastq.gz | Fastqsanger.gz | |||
| SRR28710858.fastq.gz | Fastqsanger.gz | |||
| SRR28710859.fastq.gz | Fastqsanger.gz | |||
| SRR28710860.fastq.gz | Fastqsanger.gz |
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Project description:Publication Abstract: As climate changes, sea surface temperature anomalies that negatively impact coral reef organisms continue to increase in frequency and intensity. Yet, despite widespread coral mortality, genetic diversity remains high even in those coral species listed as threatened. While this is good news in many ways it presents a challenge for the development of biomarkers that can identify resilient or vulnerable genotypes. Taking advantage of three coral restoration nurseries in Florida that serve as long-term common garden experiments, we exposed over thirty genetically distinct Acropora cervicornis colonies to hot and cold temperature shocks seasonally and measured pooled gene expression responses using RNAseq. Targeting a subset of twenty genes, we designed a high-throughput qPCR array to quantify expression in all individuals separately under each treatment with the goal of identifying predictive and/or diagnostic thermal stress biomarkers. We observed extensive transcriptional variation in the population, suggesting abundant raw material is available for adaptation via natural selection. However, this high variation made it difficult to correlate gene expression changes with colony performance metrics such as growth, mortality, and bleaching susceptibility. Nevertheless, we identified several promising diagnostic biomarkers for acute thermal stress that may improve coral restoration and climate change mitigation efforts in the future.
2017-12-21 | GSE108338 | 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.
2013-07-07 | GSE43335 | GEO
Project description:Naval training exercises involving live ordnance can introduce munitions constituents (MCs) such as 1,3,5-trinitro-1,3,5 triazine (RDX) into the marine environment posing a potential environmental hazard to reef organisms, including corals. We developed a bioinformatic infrastructure and high-density microarray for a coral consortium and assessed the effects of RDX bioaccumulation on gene expression related to coral and endosymbiont health in the reef building coral (Acropora formosa). High-throughput sequencing and assembly of the transcriptomes for A. formosa and all eukaryotic endosymbionts yielded 189,616 unique sequences and 25,003 significant functional matches to protein-coding genes. Functional annotation and metabolic pathway associations were also developed. The bioinformatics base was transitioned to custom 15,000 probe microarrays that were used to assess RDX effects on gene expression in the A. formosa coral consortium. Coral fragments were exposed to RDX (0.5, 1, 2, 4, and 8 mg/L) for 5d in a controlled laboratory experiment. RDX readily accumulated into coral tissues; however, bioconcentration was minimal (bioconcentration factor = 1.09-1.50). RDX caused no significant changes in zooxanthellae tissue densities, however a significant (p<0.05) 40% increase in mucocytes was observed in the 8 mg/L exposure indicating a mucosal protective response to RDX exposure. Investigation of T-RFLP profiles indicated significant differences in bacterial community composition inhabiting the coral surface microlayer of Acropora sp. between control and RDX-exposed coral as among exposure concentrations. Differential expression of transcripts increased with increasing RDX concentration where 126, 195 and 272 transcripts were differentially expressed in the 0.5, 2.0 and 8 mg/L RDX treatments, respectively. The commonality in differentially expressed transcripts (DET) among exposure concentrations ranged from 9.9 to 29.0% where the lowest commonality was observed between the most disparate RDX exposure concentrations. Increasing RDX concentrations caused an increasing proportion of the number of transcripts differentially expressed in symbionts relative to corals. Further, a trend toward decreased transcript expression in symbionts in response to increasing RDX concentration was observed where 20.0% of differentially expressed transcripts had decreased expression at the 0.5 mg/L concentration, whereas 80.4% had decreased expression at the 8 mg/L concentration. Investigation of KEGG orthology for DET indicated potential impacts of RDX on a variety of molecular pathways, predominantly in endosymbionts compared to the coral host. Prominent effects of RDX exposure on pathways included enrichment of DET involved in carbohydrate metabolism, amino acid metabolism, energy metabolism, lipid metabolism, metabolism of cofactors and vitamins, environmental information processing and cellular processes. Fragments of the living branched coral Acropora formosa were obtained from Oceans, Reefs and Aquaria (http://www.orafarm.com). Ten gallon aquaria were used to expose 5 coral fragments to control or RDX exposure conditions (0.49, 0.93, 1.77, 3.67 and 7.18 mg/L, measured concentrations). The microarray hybridization experiment included 3 biological replicates for the 0.5, 2, and 8 mg/L RDX conditions and 4 biological replicates for the control.
2014-03-26 | E-GEOD-27624 | biostudies-arrayexpress
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
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