Genome-wide quantification of microRNA processing efficiency from RNA-seq data
Transcriptomics Dataset
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General Information
AccessionGSE56862
TitleGenome-wide quantification of microRNA processing efficiency from RNA-seq data
DescriptionMicroprocessor is responsible for conversion of pri-miRNA transcripts into pre-miRNA hairpins in miRNA biogenesis. The in vivo properties of this process remain enigmatic. Here, we present the first study of in vivo transcriptome-wide pri-miRNA processing using next-generation sequencing of chromatin-associated pri-miRNAs. We identify a distinctive Microprocessor signature in the transcriptome profile, from which efficiency of the endogenous processing event can be accurately quantified. This analysis reveals differential susceptibility to Microprocessor cleavage as a key regulatory step in miRNA biogenesis. Processing is highly variable among pri-miRNAs and a better predictor of miRNA abundance than primary transcription itself. Processing is also largely stable across three cell lines, suggesting a major contribution of sequence determinants. Based on differential processing efficiencies we define functionality for short sequence features adjacent to the pre-miRNA hairpin. In conclusion, we identify Microprocessor as the main hub for diversified miRNA output and suggest a role for uncoupling miRNA biogenesis from host gene expression.
Landing Pagehttps://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE56862
RepositoryGene Expression Omnibus
Tools used to analyze the dataset

Dataset Accession

ARCHS4
Published September 2017
ARCHS4 provides access to gene counts from HiSeq 2000 and HiSeq 2500 platforms for human and mouse experiments from GEO ...
4645
Clustergrammer
Published October 2017
Web-based tool for visualizing and analyzing high-dimensional data as interactive and shareable heatmaps
4645
Canned Analyses generated with the dataset

Dataset Accession
Tool Name

Interactive heatmap visualization of RNA-seq dataset GSE56862
Highly interactive web-based heatmap visualization of the top 500 most variable genes in t...
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