Limits...
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
The host genes that significantly negatively interact with the target genes.Each dark green bar shows the number of putative targets–-obtained from TargetScan–-of intronic miRNAs of the corresponding host gene labeled in the x-axis. Light green bars indicate the number of putative targets which satisfy the condition  (significantly regulated). Number of putative targets that meet the both conditions  and  (significantly negatively regulated), are shown by yellow bars.
© Copyright Policy
Related In: Results  -  Collection


getmorefigures.php?uid=PMC3111417&req=5

pone-0019312-g007: The host genes that significantly negatively interact with the target genes.Each dark green bar shows the number of putative targets–-obtained from TargetScan–-of intronic miRNAs of the corresponding host gene labeled in the x-axis. Light green bars indicate the number of putative targets which satisfy the condition (significantly regulated). Number of putative targets that meet the both conditions and (significantly negatively regulated), are shown by yellow bars.

Mentions: Fig. 7 shows the number of TargetScan-predicted targets for each of these host genes, along with the number of significant interactions for these predicted targets and the number of these significant interactions that are negative. As shown, for 21 out of 22 host genes, almost all interactions are negative (equal light green and yellow bars). We take this as evidence that the host gene expression level is a good surrogate for that of its intronic miRNAs. Indeed when we consider all of the host genes with any significant interactions, we find that they fall into two main classes: those whose interactions are almost exclusively negative and those that are non-negative (Fig. 8). Furthermore, those that are non-negative are highly enriched for those with possible promoters, as predicted by sequence analysis in [58], for their intronic miRNAs (Fig. 8 and Fig. 9). We also observe that significantly negatively enriched host genes have, on average, high mean p-values (blue circles). For instance, 7 out of 8 host genes, namely HNRNPK , COPZ1, HUWE1, PANK2, ACADVL, LARP7, and IARS2 appear at the top of the ranked mean p-value list. Thus, significantly negatively interactions and high mean p-values are two determinants which may provide strong evidence for detecting co-expressed host-intronic miRNA pairs.


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

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

The host genes that significantly negatively interact with the target genes.Each dark green bar shows the number of putative targets–-obtained from TargetScan–-of intronic miRNAs of the corresponding host gene labeled in the x-axis. Light green bars indicate the number of putative targets which satisfy the condition  (significantly regulated). Number of putative targets that meet the both conditions  and  (significantly negatively regulated), are shown by yellow bars.
© Copyright Policy
Related In: Results  -  Collection

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

pone-0019312-g007: The host genes that significantly negatively interact with the target genes.Each dark green bar shows the number of putative targets–-obtained from TargetScan–-of intronic miRNAs of the corresponding host gene labeled in the x-axis. Light green bars indicate the number of putative targets which satisfy the condition (significantly regulated). Number of putative targets that meet the both conditions and (significantly negatively regulated), are shown by yellow bars.
Mentions: Fig. 7 shows the number of TargetScan-predicted targets for each of these host genes, along with the number of significant interactions for these predicted targets and the number of these significant interactions that are negative. As shown, for 21 out of 22 host genes, almost all interactions are negative (equal light green and yellow bars). We take this as evidence that the host gene expression level is a good surrogate for that of its intronic miRNAs. Indeed when we consider all of the host genes with any significant interactions, we find that they fall into two main classes: those whose interactions are almost exclusively negative and those that are non-negative (Fig. 8). Furthermore, those that are non-negative are highly enriched for those with possible promoters, as predicted by sequence analysis in [58], for their intronic miRNAs (Fig. 8 and Fig. 9). We also observe that significantly negatively enriched host genes have, on average, high mean p-values (blue circles). For instance, 7 out of 8 host genes, namely HNRNPK , COPZ1, HUWE1, PANK2, ACADVL, LARP7, and IARS2 appear at the top of the ranked mean p-value list. Thus, significantly negatively interactions and high mean p-values are two determinants which may provide strong evidence for detecting co-expressed host-intronic miRNA pairs.

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