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Novel Modeling of Combinatorial miRNA Targeting Identifies SNP with Potential Role in Bone Density

Coronnello, C and Hartmaier, R and Arora, A and Huleihel, L and Pandit, KV and Bais, AS and Butterworth, M and Kaminski, N and Stormo, GD and Oesterreich, S and Benos, PV (2012) Novel Modeling of Combinatorial miRNA Targeting Identifies SNP with Potential Role in Bone Density. PLoS Computational Biology, 8 (12). ISSN 1553-734X

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Abstract

MicroRNAs (miRNAs) are post-transcriptional regulators that bind to their target mRNAs through base complementarity. Predicting miRNA targets is a challenging task and various studies showed that existing algorithms suffer from high number of false predictions and low to moderate overlap in their predictions. Until recently, very few algorithms considered the dynamic nature of the interactions, including the effect of less specific interactions, the miRNA expression level, and the effect of combinatorial miRNA binding. Addressing these issues can result in a more accurate miRNA:mRNA modeling with many applications, including efficient miRNA-related SNP evaluation. We present a novel thermodynamic model based on the Fermi-Dirac equation that incorporates miRNA expression in the prediction of target occupancy and we show that it improves the performance of two popular single miRNA target finders. Modeling combinatorial miRNA targeting is a natural extension of this model. Two other algorithms show improved prediction efficiency when combinatorial binding models were considered. ComiR (Combinatorial miRNA targeting), a novel algorithm we developed, incorporates the improved predictions of the four target finders into a single probabilistic score using ensemble learning. Combining target scores of multiple miRNAs using ComiR improves predictions over the naïve method for target combination. ComiR scoring scheme can be used for identification of SNPs affecting miRNA binding. As proof of principle, ComiR identified rs17737058 as disruptive to the miR-488-5p:NCOA1 interaction, which we confirmed in vitro. We also found rs17737058 to be significantly associated with decreased bone mineral density (BMD) in two independent cohorts indicating that the miR-488-5p/NCOA1 regulatory axis is likely critical in maintaining BMD in women. With increasing availability of comprehensive high-throughput datasets from patients ComiR is expected to become an essential tool for miRNA-related studies. © 2012 Coronnello et al.

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Details

Item Type: Article
Status: Published
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Coronnello, Cclc196@pitt.eduCLC196
Hartmaier, Rrjh70@pitt.eduRJH70orcid.org/0000-0001-7416-6036#sthash.wHE891bE.dpuf
Arora, A
Huleihel, L
Pandit, KV
Bais, AS
Butterworth, Mmichael7@pitt.eduMICHAEL7
Kaminski, N
Stormo, GD
Oesterreich, Ssto16@pitt.eduSTO16
Benos, PVbenos@pitt.eduGSBCPLRC
Contributors:
ContributionContributors NameEmailPitt UsernameORCID
EditorChen, KevinUNSPECIFIEDUNSPECIFIEDUNSPECIFIED
Date: 1 December 2012
Date Type: Publication
Journal or Publication Title: PLoS Computational Biology
Volume: 8
Number: 12
DOI or Unique Handle: 10.1371/journal.pcbi.1002830
Schools and Programs: School of Medicine > Cell Biology and Molecular Physiology
School of Medicine > Computational and Systems Biology
School of Medicine > Medicine
School of Medicine > Pharmacology and Chemical Biology
Refereed: Yes
ISSN: 1553-734X
Date Deposited: 01 Jul 2014 17:39
Last Modified: 29 Oct 2022 11:55
URI: http://d-scholarship.pitt.edu/id/eprint/22179

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