Ontology highlight
ABSTRACT:
PROVIDER: PRJNA649523 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:QuantSeq-Rev method to generate highly strand-specific next-generation sequencing (NGS) libraries enabling transcript quantification and identification of the 3'end of polyadenylated RNAs
2019-02-25 | E-MTAB-5090 | biostudies-arrayexpress
Project description:QuantSeq-Rev method to generate highly strand-specific next-generation sequencing (NGS) libraries enabling transcript quantification and identification of the 3'end of polyadenylated RNAs
2019-02-25 | E-MTAB-5091 | biostudies-arrayexpress
Project description:Intramolecular ligation method (iLIME) for pre-miRNA quantification and sequencing
| PRJNA769430 | ENA
Project description:RNA-sequencing is a powerful tool for exploring expression profiles of microbial species that does not require the production of a custom genechip. We used microarrays to compare our quantitative RNA-sequencing method to the standard expression quantification methods
2011-03-30 | GSE25535 | GEO
Project description:Hairpin-containing pre-miRNAs are precursors of microRNAs (miRNAs) that play important roles in cellular processes and various human diseases. Pre-miRNAs are produced from longer primary transcripts (pri-miRNAs). The falsity in cellular expression and sequences of pre-miRNAs might cause cellular defects or human diseases. However, the current pre-miRNA quantification methods by qPCR cannot discriminate between pre-miRNAs and their parental pri-miRNAs. In addition, the ligation of the sequencing adapter to 5’-end of pre-miRNAs is inefficient, therefore, pre-miRNA sequencing is highly impractical. Here, we developed a method, called the intramolecular ligation method (iLIME) for pre-miRNA quantification and sequencing. This method utilized T4 RNA ligase 1 to convert hairpin-pre-miRNAs into circularized RNAs that do not naturally exist in cells. The resulting circuliarized RNAs allow us to design unique primers to quantify pre-miRNAs by qPCR specicially, and thus this qPCR can distinguish pre-miRNA from pri-miRNAs. In addition, the iLIME also allows us to sequence pre-miRNAs using next-generation sequencing. The iLIME method offers a simple and effective way to quantify and sequence pre-miRNAs. This will be useful in investigating pre-miRNAs for addressing research questions for medical applications. The iLIME can be potentially extended to other hairpin-containing RNAs, such as tRNAs and snRNAs.
2021-10-11 | GSE185524 | GEO
Project description:Accurate quantification of all microRNAs (miRNA) is important for understanding miRNA biology and for development of new biomarkers and therapeutic targets. We have developed a new method of preparation of small RNA sequencing libraries (RealSeq®-AC) that ligates miRNAs with a single combo adapter and then circularizes the ligation products. When compared to other methods, RealSeq®-AC provided greatly reduced sequencing bias and allowed the identification of the largest variety of miRNAs in biological samples.
2018-07-01 | GSE107304 | GEO
Project description:In mammals brain evolution, specifically that of the cerebellum, is a focus of evolutionary change. Here we functionally characterize the phylogenetically-restricted novel gene, piggyBac transposable element. The ChiP-exonuclease assay protocol was performed as in Serandour's method. The libraries were quantified by using the KAPA library quantification kit for Illumina sequencing platforms (KAPA Biosystems, KK4824) and sequenced on HiSeq following the manufacturer’s protocol.
2022-09-23 | GSE213758 | GEO
Project description:The use of alternative polyadenylation sites is common and affects the post-transcriptional fate of mRNA, including its stability, localization, and translation. Here we present a method for genome-wide and strand-specific mapping of poly(A) sites and quantification of RNA levels at unprecedented efficiency by using an on-cluster dark T-fill procedure on the Illumina sequencing platform. Our method outperforms former protocols in quality and throughput, and reveals new insights into polyadenylation in Saccharomyces cerevisiae. Experimental benchmark of five different protocols (3tfill, bpmI, internal, rnaseq and yoon) for genome-wide identification of polyadenylation sites in Saccharomyces cerevisiae and transcript quantification. RNA was extracted from WT cells grown in glucose (ypd) or galactose (ypgal) as carbon source. The same RNA was used for 3 independent library constructions (technical replicates, rep).
2013-01-10 | E-GEOD-40110 | biostudies-arrayexpress
Project description:MiRNA-mediated regulation depends on the stoichiometry between miRNAs and their mRNA targets. To decipher dynamic function of this complex layer, it is critical to characterize individual miRNA species within a specific cellular context. Small RNA cloning followed by deep sequencing is uniquely positioned as a genome-wide profiling method to quantify miRNA expression with potentially unlimited dynamic range and provide single-nucleotide resolution for precise miRNA classification and de novo discovery. However, significant biases introduced by RNA ligation steps in the current RNA cloning protocol often lead to inaccurate miRNA quantification by >1000-fold deviation. As a result, it has greatly hindered the broad application of this method. Here we report a highly efficient RNA cloning method that achieves over 90% efficiency for both 5’ and 3’ ligations with diverse small RNA substrates. When applied to a pool of either equimolar or differentially mixed synthetic miRNAs, the deviation of the cloning frequency for each miRNA is minimized to less than 2-fold of the anticipated value. By using samples obtained from multiple tissues and cells, we further demonstrate the accurate quantification of miRNA expression over a dynamic range of four orders of magnitude. Our results also reveal that most cistronic miRNAs are expressed at similar levels and, in each cell population, miRNAs repress their cognate targets in a dosage dependent manner. Collectively, our high-efficiency RNA cloning method combining with deep sequencing establishes a cost-effective approach for accurate genome-wide miRNA profiling.
2013-09-18 | GSE47858 | GEO
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2020-01-28 | GSE138318 | GEO