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Nucleic Acids Res. 2015 Feb 27;43(4):2326-41. doi: 10.1093/nar/gkv057. Epub 2015 Feb 4.

Characterization of the mammalian miRNA turnover landscape.

Author information

1
Department of Genetics, Yale University School of Medicine, New Haven, CT 06510, USA Yale Stem Cell Center, Yale Cancer Center, New Haven, CT 06520, USA Graduate Program in Biological and Biomedical Sciences, Yale University, New Haven, CT 06510, USA.
2
Department of Genetics, Yale University School of Medicine, New Haven, CT 06510, USA Yale Stem Cell Center, Yale Cancer Center, New Haven, CT 06520, USA.
3
Yale Stem Cell Center, Yale Cancer Center, New Haven, CT 06520, USA Computational Biology and Bioinformatics Program, Yale University School of Medicine, New Haven, CT 06520, USA.
4
Yale Stem Cell Center, Yale Cancer Center, New Haven, CT 06520, USA.
5
Wadsworth Center, New York State Department of Health, Albany, NY 12208, USA.
6
Department of Genetics, Yale University School of Medicine, New Haven, CT 06510, USA Yale Stem Cell Center, Yale Cancer Center, New Haven, CT 06520, USA Yale Center for RNA Science and Medicine, New Haven, CT 06520, USA jun.lu@yale.edu.

Abstract

Steady state cellular microRNA (miRNA) levels represent the balance between miRNA biogenesis and turnover. The kinetics and sequence determinants of mammalian miRNA turnover during and after miRNA maturation are not fully understood. Through a large-scale study on mammalian miRNA turnover, we report the co-existence of multiple cellular miRNA pools with distinct turnover kinetics and biogenesis properties and reveal previously unrecognized sequence features for fast turnover miRNAs. We measured miRNA turnover rates in eight mammalian cell types with a combination of expression profiling and deep sequencing. While most miRNAs are stable, a subset of miRNAs, mostly miRNA*s, turnovers quickly, many of which display a two-step turnover kinetics. Moreover, different sequence isoforms of the same miRNA can possess vastly different turnover rates. Fast turnover miRNA isoforms are enriched for 5' nucleotide bias against Argonaute-(AGO)-loading, but also additional 3' and central sequence features. Modeling based on two fast turnover miRNA*s miR-222-5p and miR-125b-1-3p, we unexpectedly found that while both miRNA*s are associated with AGO, they strongly differ in HSP90 association and sensitivity to HSP90 inhibition. Our data characterize the landscape of genome-wide miRNA turnover in cultured mammalian cells and reveal differential HSP90 requirements for different miRNA*s. Our findings also implicate rules for designing stable small RNAs, such as siRNAs.

PMID:
25653157
PMCID:
PMC4344502
DOI:
10.1093/nar/gkv057
[Indexed for MEDLINE]
Free PMC Article
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