Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1204466 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:We collected ovarian follicle fluids from 68 patients and assigned them to good group or bad group according to their oocyte quality. The exosomes were isolated and characterized. Exosomal microRNAs were extracted, the library was constructed and sequenced by Illumina hiseq platform. The exosomal microRNA expression was analyzed and profiled, the target genes were predicted, GO terms were enriched by GOSeq and KEGG pathway was analyzed using miranda.A total of 47 differential microRNAs was expressed significantly between good and bad group, of which 9 microRNAs were known microRNAs and 7 of them was upregulated in the bad group. In-silico analysis indicated that several of these exosomal microRNAs were involved in pathways implicated in oocyte quality.Our study suggests that exosomal microRNAs in ovarian follicle fluid are critical in maintaining the oocyte quality. Our study greatly improve our understanding of exosomal microRNAs in human ovarian follicular fluid, paving the way for further investigation on the microRNA functions in the ovarian microenvironment and the mechanism behind it.
2020-07-21 | GSE154740 | GEO
Project description:We constructed a small RNA cDNA library, using small RNA fraction with a length of 19-29 bases, and we performed deep sequencing of the cDNA library.
2013-03-02 | GSE27647 | GEO
Project description:In order to identify major regulatory events in the immediate phase of renal IRI associated with CCN2, we performed full transcriptome RNA-sequencing on a cDNA library constructed from RNA extracted from samples of kidney cortex.
2021-10-28 | GSE186316 | GEO
Project description:<p>RNA-Seq is an effective method to study the transcriptome, but specialized methods are required to identify 5' ends of transcripts. Several published strategies exist for this specific purpose, but their relative merits have not been systematically analyzed. Here, we directly compare the performance of six such methods - testing five with cellular RNA as well as a novel spike-in RNA assay that helps address interpretation challenges that arise from uncertainties in annotation or RNA processing. Using a single human RNA sample, we constructed and sequenced 18 libraries with these methods and one standard, control RNA-Seq library. We find that the CAGE method performed best for mRNA and that most of its unannotated peaks are supported by evidence from other genomic methods. We then applied CAGE to eight brain-related samples and revealed sample-specific transcription start site (TSS) usage as well as a transcriptome-wide shift in TSS usage between fetal and adult brain.</p>
| phs001463 | dbGaP