Unusually effective microRNA targeting within repeat-rich coding regions of mammalian mRNAs
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Schnall-Levin-2011-Unusually effective microRNA.pdf
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Author(s)
Schnall-Levin, Michael
Rissland, Olivia S.
Johnston, Wendy K.
Perrimon, Norbert
Bartel, David
Berger Leighton, Bonnie
Date Issued
June 2011
Journal
Genome Research
Publisher
Cold Spring Harbor Laboratory Press
Citation
Schnall-Levin, M. et al. “Unusually Effective microRNA Targeting Within Repeat-rich Coding Regions of Mammalian mRNAs.” Genome Research 21.9 (2011): 1395–1403. Copyright © 2011 by Cold Spring Harbor Laboratory Press
Version
Final published version
Abstract
MicroRNAs (miRNAs) regulate numerous biological processes by base-pairing with target messenger RNAs (mRNAs), primarily through sites in 3′ untranslated regions (UTRs), to direct the repression of these targets. Although miRNAs have sometimes been observed to target genes through sites in open reading frames (ORFs), large-scale studies have shown such targeting to be generally less effective than 3′ UTR targeting. Here, we show that several miRNAs each target significant groups of genes through multiple sites within their coding regions. This ORF targeting, which mediates both predictable and effective repression, arises from highly repeated sequences containing miRNA target sites. We show that such sequence repeats largely arise through evolutionary duplications and occur particularly frequently within families of paralogous C[subscript 2]H[subscript 2] zinc-finger genes, suggesting the potential for their coordinated regulation. Examples of ORFs targeted by miR-181 include both the well-known tumor suppressor RB1 and RBAK, encoding a C[subscript 2]H[subscript 2] zinc-finger protein and transcriptional binding partner of RB1. Our results indicate a function for repeat-rich coding sequences in mediating post-transcriptional regulation and reveal circumstances in which miRNA-mediated repression through ORF sites can be reliably predicted.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology. Department of Biology
Massachusetts Institute of Technology. Department of Mathematics
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DOI of Published Version
https://doi.org/10.1101/gr.121210.111
