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MREdictor: a two-step dynamic interaction model that accounts for mRNA accessibility and Pumilio binding accurately predicts microRNA targets.

Incarnato D, Neri F, Diamanti D, Oliviero S - Nucleic Acids Res. (2013)

Bottom Line: The prediction of pairing between microRNAs (miRNAs) and the miRNA recognition elements (MREs) on mRNAs is expected to be an important tool for understanding gene regulation.Here, we show that mRNAs that contain Pumilio recognition elements (PRE) in the proximity of predicted miRNA-binding sites are more likely to form stable secondary structures within their 3'-UTR, and we demonstrated using a PUM1 and PUM2 double knockdown that Pumilio proteins are general regulators of miRNA accessibility.On the basis of these findings, we developed a computational method for predicting miRNA targets that accounts for the presence of PRE in the proximity of seed-match sequences within poorly accessible structures.

View Article: PubMed Central - PubMed

Affiliation: Human Genetics Foundation (HuGeF), via Nizza 52, 10126 Torino, Italy, Dipartimento di Biotecnologie, Chimica e Farmacia, Università degli Studi di Siena, Via Fiorentina 1, 53100 Siena, Italy and Siena Biotech, Strada Petriccio Belriguardo 35, Siena, Italy.

ABSTRACT
The prediction of pairing between microRNAs (miRNAs) and the miRNA recognition elements (MREs) on mRNAs is expected to be an important tool for understanding gene regulation. Here, we show that mRNAs that contain Pumilio recognition elements (PRE) in the proximity of predicted miRNA-binding sites are more likely to form stable secondary structures within their 3'-UTR, and we demonstrated using a PUM1 and PUM2 double knockdown that Pumilio proteins are general regulators of miRNA accessibility. On the basis of these findings, we developed a computational method for predicting miRNA targets that accounts for the presence of PRE in the proximity of seed-match sequences within poorly accessible structures. Moreover, we implement the miRNA-MRE duplex pairing as a two-step model, which better fits the available structural data. This algorithm, called MREdictor, allows for the identification of miRNA targets in poorly accessible regions and is not restricted to a perfect seed-match; these features are not present in other computational prediction methods.

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Validation of MREdictor method. (A) Comparison of standard performance measures of state-of-the-art algorithms and MREdictor. (B) Schematic representation of two non-canonical MREs predicted by MREdictor but not by other tools, in the absence of a perfect seed-match. Hsa-miR-122* was predicted to target REST (ΔGduplex = −20.9 kcal/mol), whereas mmu-miR-667* was predicted to target Sirt1 (ΔGduplex = −34.7 kcal/mol). (C) Dual luciferase assay validation of the two predicted MREs. Data are averaged over four replicates, and error bars are given for S.Ds.
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gkt629-F4: Validation of MREdictor method. (A) Comparison of standard performance measures of state-of-the-art algorithms and MREdictor. (B) Schematic representation of two non-canonical MREs predicted by MREdictor but not by other tools, in the absence of a perfect seed-match. Hsa-miR-122* was predicted to target REST (ΔGduplex = −20.9 kcal/mol), whereas mmu-miR-667* was predicted to target Sirt1 (ΔGduplex = −34.7 kcal/mol). (C) Dual luciferase assay validation of the two predicted MREs. Data are averaged over four replicates, and error bars are given for S.Ds.

Mentions: To assess the accuracy of MREdictor, we first created a test data set that was composed of 106 functional and 106 non-functional experimentally validated MREs from individual studies (Supplementary Table S3). Compared with state-of-the-art prediction algorithms (10,13–15,40), MREdictor correctly predicts a larger fraction of the functional sites and has the highest accuracy (ACC = 0.9; Figure 4A). To further test its ability to predict novel putative targets, we performed a whole-genome scan of human and mouse 3′-UTR and randomly picked two non-canonical MREs, which were not predicted by other algorithms. Hsa-miR-122* and mmu-miR-667*, two non-conserved miRNAs, were predicted by MREdictor to target, respectively, REST and Sirt1 on two non-conserved MREs; the interactions lacked perfect seed-pairing, bearing, respectively, a mismatch plus a G:U wobble or two consecutive G:U wobbles at the seed level (Figure 4B).Figure 4.


MREdictor: a two-step dynamic interaction model that accounts for mRNA accessibility and Pumilio binding accurately predicts microRNA targets.

Incarnato D, Neri F, Diamanti D, Oliviero S - Nucleic Acids Res. (2013)

Validation of MREdictor method. (A) Comparison of standard performance measures of state-of-the-art algorithms and MREdictor. (B) Schematic representation of two non-canonical MREs predicted by MREdictor but not by other tools, in the absence of a perfect seed-match. Hsa-miR-122* was predicted to target REST (ΔGduplex = −20.9 kcal/mol), whereas mmu-miR-667* was predicted to target Sirt1 (ΔGduplex = −34.7 kcal/mol). (C) Dual luciferase assay validation of the two predicted MREs. Data are averaged over four replicates, and error bars are given for S.Ds.
© Copyright Policy - creative-commons
Related In: Results  -  Collection

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getmorefigures.php?uid=PMC3794589&req=5

gkt629-F4: Validation of MREdictor method. (A) Comparison of standard performance measures of state-of-the-art algorithms and MREdictor. (B) Schematic representation of two non-canonical MREs predicted by MREdictor but not by other tools, in the absence of a perfect seed-match. Hsa-miR-122* was predicted to target REST (ΔGduplex = −20.9 kcal/mol), whereas mmu-miR-667* was predicted to target Sirt1 (ΔGduplex = −34.7 kcal/mol). (C) Dual luciferase assay validation of the two predicted MREs. Data are averaged over four replicates, and error bars are given for S.Ds.
Mentions: To assess the accuracy of MREdictor, we first created a test data set that was composed of 106 functional and 106 non-functional experimentally validated MREs from individual studies (Supplementary Table S3). Compared with state-of-the-art prediction algorithms (10,13–15,40), MREdictor correctly predicts a larger fraction of the functional sites and has the highest accuracy (ACC = 0.9; Figure 4A). To further test its ability to predict novel putative targets, we performed a whole-genome scan of human and mouse 3′-UTR and randomly picked two non-canonical MREs, which were not predicted by other algorithms. Hsa-miR-122* and mmu-miR-667*, two non-conserved miRNAs, were predicted by MREdictor to target, respectively, REST and Sirt1 on two non-conserved MREs; the interactions lacked perfect seed-pairing, bearing, respectively, a mismatch plus a G:U wobble or two consecutive G:U wobbles at the seed level (Figure 4B).Figure 4.

Bottom Line: The prediction of pairing between microRNAs (miRNAs) and the miRNA recognition elements (MREs) on mRNAs is expected to be an important tool for understanding gene regulation.Here, we show that mRNAs that contain Pumilio recognition elements (PRE) in the proximity of predicted miRNA-binding sites are more likely to form stable secondary structures within their 3'-UTR, and we demonstrated using a PUM1 and PUM2 double knockdown that Pumilio proteins are general regulators of miRNA accessibility.On the basis of these findings, we developed a computational method for predicting miRNA targets that accounts for the presence of PRE in the proximity of seed-match sequences within poorly accessible structures.

View Article: PubMed Central - PubMed

Affiliation: Human Genetics Foundation (HuGeF), via Nizza 52, 10126 Torino, Italy, Dipartimento di Biotecnologie, Chimica e Farmacia, Università degli Studi di Siena, Via Fiorentina 1, 53100 Siena, Italy and Siena Biotech, Strada Petriccio Belriguardo 35, Siena, Italy.

ABSTRACT
The prediction of pairing between microRNAs (miRNAs) and the miRNA recognition elements (MREs) on mRNAs is expected to be an important tool for understanding gene regulation. Here, we show that mRNAs that contain Pumilio recognition elements (PRE) in the proximity of predicted miRNA-binding sites are more likely to form stable secondary structures within their 3'-UTR, and we demonstrated using a PUM1 and PUM2 double knockdown that Pumilio proteins are general regulators of miRNA accessibility. On the basis of these findings, we developed a computational method for predicting miRNA targets that accounts for the presence of PRE in the proximity of seed-match sequences within poorly accessible structures. Moreover, we implement the miRNA-MRE duplex pairing as a two-step model, which better fits the available structural data. This algorithm, called MREdictor, allows for the identification of miRNA targets in poorly accessible regions and is not restricted to a perfect seed-match; these features are not present in other computational prediction methods.

Show MeSH
Related in: MedlinePlus