The menu of features that define primary microRNAs and enable de novo design of microRNA genes
Transcriptomics Dataset
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General Information
AccessionGSE67937
TitleThe menu of features that define primary microRNAs and enable de novo design of microRNA genes
DescriptionMicroRNAs (miRNAs) are small regulatory RNAs processed from stem-loop regions of primary transcripts (pri-miRNAs), with the choice of stem-loops for initial processing largely determining what becomes a miRNA. To identify sequence and structural features influencing this choice, we determined cleavage efficiencies of >50,000 variants of three human pri-miRNAs, focusing on the regions intractable to previous high-throughput analyses. Our analyses revealed a mismatched motif in the basal stem region, a preference for maintaining or improving base-pairing throughout the remainder of the stem, and a narrow stem-length preference of 351 base pairs. Incorporating these features with previously identified features, including three primary-sequence motifs, yielded a unifying model defining mammalian pri-miRNAs, in which motifs help orient processing and increase efficiency, with the presence of more motifs compensating for structural defects. This model enables generation of artificial pri-miRNAs, designed de novo, without reference to any natural sequence, yet processed more efficiently than natural pri-miRNAs.
Landing Pagehttps://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE67937
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 GSE67937
Highly interactive web-based heatmap visualization of the top 500 most variable genes in t...
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