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Computational prediction of intronic microRNA targets using host gene expression reveals novel regulatory mechanisms.

Radfar MH, Wong W, Morris Q - PLoS ONE (2011)

Bottom Line: Host genes that InMiR predicts are bad surrogates contain significantly more miRNA target sites in their 3' UTRs and are significantly more likely to have predicted Pol II and Pol III promoters in their introns.We provide a dataset of 1,935 predicted mRNA targets for 22 intronic miRNAs.These prediction are supported both by sequence features and expression.By combining our results with previous reports, we distinguish three classes of intronic miRNAs: Those that are tightly regulated with their host gene; those that are likely to be expressed from the same promoter but whose host gene is highly regulated by miRNAs; and those likely to have independent promoters.

View Article: PubMed Central - PubMed

Affiliation: Department of Electrical and Computer Engineering, University of Toronto, Toronto, Ontario, Canada. h.radfar@utoronto.ca

ABSTRACT
Approximately half of known human miRNAs are located in the introns of protein coding genes. Some of these intronic miRNAs are only expressed when their host gene is and, as such, their steady state expression levels are highly correlated with those of the host gene's mRNA. Recently host gene expression levels have been used to predict the targets of intronic miRNAs by identifying other mRNAs that they have consistent negative correlation with. This is a potentially powerful approach because it allows a large number of expression profiling studies to be used but needs refinement because mRNAs can be targeted by multiple miRNAs and not all intronic miRNAs are co-expressed with their host genes.Here we introduce InMiR, a new computational method that uses a linear-Gaussian model to predict the targets of intronic miRNAs based on the expression profiles of their host genes across a large number of datasets. Our method recovers nearly twice as many true positives at the same fixed false positive rate as a comparable method that only considers correlations. Through an analysis of 140 Affymetrix datasets from Gene Expression Omnibus, we build a network of 19,926 interactions among 57 intronic miRNAs and 3,864 targets. InMiR can also predict which host genes have expression profiles that are good surrogates for those of their intronic miRNAs. Host genes that InMiR predicts are bad surrogates contain significantly more miRNA target sites in their 3' UTRs and are significantly more likely to have predicted Pol II and Pol III promoters in their introns.We provide a dataset of 1,935 predicted mRNA targets for 22 intronic miRNAs. These prediction are supported both by sequence features and expression. By combining our results with previous reports, we distinguish three classes of intronic miRNAs: Those that are tightly regulated with their host gene; those that are likely to be expressed from the same promoter but whose host gene is highly regulated by miRNAs; and those likely to have independent promoters.

Show MeSH
Number of intergenic and intronic miRNAs that putatively target our set of host genes.Bars marked by red circles are associated with the genes predicted to be good surrogates.
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pone-0019312-g010: Number of intergenic and intronic miRNAs that putatively target our set of host genes.Bars marked by red circles are associated with the genes predicted to be good surrogates.

Mentions: Even if a host gene and intronic miRNA are expressed from the same promoter, they could have different expression levels due to different post-transcriptional regulation. To investigate this, we examined the predicted miRNA targets within the 3′ UTRs of host genes. We found host genes are targeted by miRNAs much more than non-host genes (, Wilcoxon ranksum test) though we were unable to detect a preference for targeting by intronic versus intergenic miRNAs (Fig S5). However, we found that negatively enriched host genes have significantly fewer (, Wilcoxon ranksum test) miRNA targets than non-negatively enriched hosts (Fig. 10). So, down-regulation of the host gene by other miRNAs could provide another possible explanation for why some host expression levels are bad surrogates for those of their intronic miRNAs. The pattern of interactions among host genes and their intronic miRNAs suggests that there may be some hierarchical structure in intronic miRNA-based regulation (Fig S6).


Computational prediction of intronic microRNA targets using host gene expression reveals novel regulatory mechanisms.

Radfar MH, Wong W, Morris Q - PLoS ONE (2011)

Number of intergenic and intronic miRNAs that putatively target our set of host genes.Bars marked by red circles are associated with the genes predicted to be good surrogates.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3111417&req=5

pone-0019312-g010: Number of intergenic and intronic miRNAs that putatively target our set of host genes.Bars marked by red circles are associated with the genes predicted to be good surrogates.
Mentions: Even if a host gene and intronic miRNA are expressed from the same promoter, they could have different expression levels due to different post-transcriptional regulation. To investigate this, we examined the predicted miRNA targets within the 3′ UTRs of host genes. We found host genes are targeted by miRNAs much more than non-host genes (, Wilcoxon ranksum test) though we were unable to detect a preference for targeting by intronic versus intergenic miRNAs (Fig S5). However, we found that negatively enriched host genes have significantly fewer (, Wilcoxon ranksum test) miRNA targets than non-negatively enriched hosts (Fig. 10). So, down-regulation of the host gene by other miRNAs could provide another possible explanation for why some host expression levels are bad surrogates for those of their intronic miRNAs. The pattern of interactions among host genes and their intronic miRNAs suggests that there may be some hierarchical structure in intronic miRNA-based regulation (Fig S6).

Bottom Line: Host genes that InMiR predicts are bad surrogates contain significantly more miRNA target sites in their 3' UTRs and are significantly more likely to have predicted Pol II and Pol III promoters in their introns.We provide a dataset of 1,935 predicted mRNA targets for 22 intronic miRNAs.These prediction are supported both by sequence features and expression.By combining our results with previous reports, we distinguish three classes of intronic miRNAs: Those that are tightly regulated with their host gene; those that are likely to be expressed from the same promoter but whose host gene is highly regulated by miRNAs; and those likely to have independent promoters.

View Article: PubMed Central - PubMed

Affiliation: Department of Electrical and Computer Engineering, University of Toronto, Toronto, Ontario, Canada. h.radfar@utoronto.ca

ABSTRACT
Approximately half of known human miRNAs are located in the introns of protein coding genes. Some of these intronic miRNAs are only expressed when their host gene is and, as such, their steady state expression levels are highly correlated with those of the host gene's mRNA. Recently host gene expression levels have been used to predict the targets of intronic miRNAs by identifying other mRNAs that they have consistent negative correlation with. This is a potentially powerful approach because it allows a large number of expression profiling studies to be used but needs refinement because mRNAs can be targeted by multiple miRNAs and not all intronic miRNAs are co-expressed with their host genes.Here we introduce InMiR, a new computational method that uses a linear-Gaussian model to predict the targets of intronic miRNAs based on the expression profiles of their host genes across a large number of datasets. Our method recovers nearly twice as many true positives at the same fixed false positive rate as a comparable method that only considers correlations. Through an analysis of 140 Affymetrix datasets from Gene Expression Omnibus, we build a network of 19,926 interactions among 57 intronic miRNAs and 3,864 targets. InMiR can also predict which host genes have expression profiles that are good surrogates for those of their intronic miRNAs. Host genes that InMiR predicts are bad surrogates contain significantly more miRNA target sites in their 3' UTRs and are significantly more likely to have predicted Pol II and Pol III promoters in their introns.We provide a dataset of 1,935 predicted mRNA targets for 22 intronic miRNAs. These prediction are supported both by sequence features and expression. By combining our results with previous reports, we distinguish three classes of intronic miRNAs: Those that are tightly regulated with their host gene; those that are likely to be expressed from the same promoter but whose host gene is highly regulated by miRNAs; and those likely to have independent promoters.

Show MeSH