Assessing the utility of thermodynamic features for microRNA target prediction under relaxed seed and no conservation requirements

Background

Many computational microRNA target prediction tools are focused on several key features, including complementarity to 5′seed of miRNAs and evolutionary conservation. While these features allow for successful target identification, not all miRNA target sites are conserved and adhere to canonical seed complementarity. Several studies have propagated the use of energy features of mRNA:miRNA duplexes as an alternative feature. However, different independent evaluations reported conflicting results on the reliability of energy-based predictions. Here, we reassess the usefulness of energy features for mammalian target prediction, aiming to relax or eliminate the need for perfect seed matches and conservation requirement.

Methodology/Principal Findings

We detect significant differences of energy features at experimentally supported human miRNA target sites and at genome-wide sites of AGO protein interaction. This trend is confirmed on datasets that assay the effect of miRNAs on mRNA and protein expression changes, and a simple linear regression model leads to significant correlation of predicted versus observed expression change. Compared to 6-mer seed matches as baseline, application of our energy-based model leads to ∼3–5-fold enrichment on highly down-regulated targets, and allows for prediction of strictly imperfect targets with enrichment above baseline.

Conclusions/Significance

In conclusion, our results indicate significant promise for energy-based miRNA target prediction that includes a broader range of targets without having to use conservation or impose stringent seed match rules.     

MiR-107 and MiR-185 Can Induce Cell Cycle Arrest in Human Non Small Cell Lung Cancer Cell Lines

Background

MicroRNAs (miRNAs) are short single stranded noncoding RNAs that suppress gene expression through either translational repression or degradation of target mRNAs. The annealing between messenger RNAs and 5′ seed region of miRNAs is believed to be essential for the specific suppression of target gene expression. One miRNA can have several hundred different targets in a cell. Rapidly accumulating evidence suggests that many miRNAs are involved in cell cycle regulation and consequentially play critical roles in carcinogenesis.

Methodology/Principal Findings

Introduction of synthetic miR-107 or miR-185 suppressed growth of the human non-small cell lung cancer cell lines. Flow cytometry analysis revealed these miRNAs induce a G1 cell cycle arrest in H1299 cells and the suppression of cell cycle progression is stronger than that by Let-7 miRNA. By the gene expression analyses with oligonucleotide microarrays, we find hundreds of genes are affected by transfection of these miRNAs. Using miRNA-target prediction analyses and the array data, we listed up a set of likely targets of miR-107 and miR-185 for G1 cell cycle arrest and validate a subset of them using real-time RT-PCR and immunoblotting for CDK6.

Conclusions/Significance

We identified new cell cycle regulating miRNAs, miR-107 and miR-185, localized in frequently altered chromosomal regions in human lung cancers. Especially for miR-107, a large number of down-regulated genes are annotated with the gene ontology term ‘cell cycle’. Our results suggest that these miRNAs may contribute to regulate cell cycle in human malignant tumors.     

Tissue-Specific Expression and Regulatory Networks of Pig MicroRNAome

Background

Despite the economic and medical importance of the pig, knowledge about its genome organization, gene expression regulation, and molecular mechanisms involved in physiological processes is far from that achieved for mouse and rat, the two most used model organisms in biomedical research. MicroRNAs (miRNAs) are a wide class of molecules that exert a recognized role in gene expression modulation, but only 280 miRNAs in pig have been characterized to date.

Results

We applied a novel computational approach to predict species-specific and conserved miRNAs in the pig genome, which were then subjected to experimental validation. We experimentally identified candidate miRNAs sequences grouped in high-confidence (424) and medium-confidence (353) miRNAs according to RNA-seq results. A group of miRNAs was also validated by PCR experiments. We established the subtle variability in expression of isomiRs and miRNA-miRNA star couples supporting a biological function for these molecules. Finally, miRNA and mRNA expression profiles produced from the same sample of 20 different tissue of the animal were combined, using a correlation threshold to filter miRNA-target predictions, to identify tissue-specific regulatory networks.

Conclusions

Our data represent a significant progress in the current understanding of miRNAome in pig. The identification of miRNAs, their target mRNAs, and the construction of regulatory circuits will provide new insights into the complex biological networks in several tissues of this important animal model.     

Identification of Wolbachia-responsive microRNAs in the two-spotted spider mite,Tetranychus urticae

Background

The two-spotted spider mite, Tetranychus urticae, is infected with Wolbachia, which have the ability to manipulate host reproduction and fitness. MicroRNAs (miRNAs) are small non-coding RNAs that are involved in many biological processes such as development, reproduction and host-pathogen interactions. Although miRNA was observed to involve in Wolbachia-host interactions in the other insect systems, its roles have not been fully deciphered in the two-spotted spider mite.

Results

Small RNA libraries of infected and uninfected T. urticae for both sexes (in total four libraries) were constructed. By integrating the mRNA data originated from the same samples, the target genes of the differentially expressed miRNAs were predicted. Then, GO and pathway analyses were performed for the target genes. Comparison of libraries showed that Wolbachia infection significantly regulated 91 miRNAs in females and 20 miRNAs in males, with an overall suppression of miRNAs in Wolbachia-infected libraries. A comparison of the miRNA and mRNA data predicted that the differentially expressed miRNAs negatively regulated 90 mRNAs in females and 9 mRNAs in males. An analysis of target genes showed that Wolbachia-responsive miRNAs regulated genes with function in sphingolipid metabolism, lysosome function, apoptosis and lipid transporting in both sexes, as well as reproduction in females.

Conclusion

Comparisons of the miRNA and mRNA data can help to identify miRNAs and miRNA target genes involving in Wolbachia-host interactions. The molecular targets identified in this study should be useful in further functional studies.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-1122) contains supplementary material, which is available to authorized users.     

SNP Regulation of microRNA Expression and Subsequent Colon Cancer Risk

Introduction

MicroRNAs (miRNAs) regulate messenger RNAs (mRNAs) and as such have been implicated in a variety of diseases, including cancer. MiRNAs regulate mRNAs through binding of the miRNA 5’ seed sequence (~7–8 nucleotides) to the mRNA 3’ UTRs; polymorphisms in these regions have the potential to alter miRNA-mRNA target associations. SNPs in miRNA genes as well as miRNA-target genes have been proposed to influence cancer risk through altered miRNA expression levels.

Methods

MiRNA-SNPs and miRNA-target gene-SNPs were identified through the literature. We used SNPs from Genome-Wide Association Study (GWAS) data that were matched to individuals with miRNA expression data generated from an Agilent platform for colon tumor and non-tumor paired tissues. These samples were used to evaluate 327 miRNA-SNP pairs for associations between SNPs and miRNA expression levels as well as for SNP associations with colon cancer.

Results

Twenty-two miRNAs expressed in non-tumor tissue were significantly different by genotype and 21 SNPs were associated with altered tumor/non-tumor differential miRNA expression across genotypes. Two miRNAs were associated with SNP genotype for both non-tumor and tumor/non-tumor differential expression. Of the 41 miRNAs significantly associated with SNPs all but seven were significantly differentially expressed in colon tumor tissue. Two of the 41 SNPs significantly associated with miRNA expression levels were associated with colon cancer risk: rs8176318 (BRCA1), OR_AA 1.31 95% CI 1.01, 1.78, and rs8905 (PRKAR1A), OR_GG 2.31 95% CI 1.11, 4.77.

Conclusion

Of the 327 SNPs identified in the literature as being important because of their potential regulation of miRNA expression levels, 12.5% had statistically significantly associations with miRNA expression. However, only two of these SNPs were significantly associated with colon cancer.     

A comparison of performance of plant miRNA target prediction tools and the characterization of features for genome-wide target prediction

Background

Deep-sequencing has enabled the identification of large numbers of miRNAs and siRNAs, making the high-throughput target identification a main limiting factor in defining their function. In plants, several tools have been developed to predict targets, majority of them being trained on Arabidopsis datasets. An extensive and systematic evaluation has not been made for their suitability for predicting targets in species other than Arabidopsis. Nor, these have not been evaluated for their suitability for high-throughput target prediction at genome level.

Results

We evaluated the performance of 11 computational tools in identifying genome-wide targets in Arabidopsis and other plants with procedures that optimized score-cutoffs for estimating targets. Targetfinder was most efficient [89% ‘precision’ (accuracy of prediction), 97% ‘recall’ (sensitivity)] in predicting ‘true-positive’ targets in Arabidopsis miRNA-mRNA interactions. In contrast, only 46% of true positive interactions from non-Arabidopsis species were detected, indicating low ‘recall’ values. Score optimizations increased the ‘recall’ to only 70% (corresponding ‘precision’: 65%) for datasets of true miRNA-mRNA interactions in species other than Arabidopsis. Combining the results of Targetfinder and psRNATarget delivers high true positive coverage, whereas the intersection of psRNATarget and Tapirhybrid outputs deliver highly ‘precise’ predictions. The large number of ‘false negative’ predictions delivered from non-Arabidopsis datasets by all the available tools indicate the diversity in miRNAs-mRNA interaction features between Arabidopsis and other species. A subset of miRNA-mRNA interactions differed significantly for features in seed regions as well as the total number of matches/mismatches.

Conclusion

Although, many plant miRNA target prediction tools may be optimized to predict targets with high specificity in Arabidopsis, such optimized thresholds may not be suitable for many targets in non-Arabidopsis species. More importantly, non-conventional features of miRNA-mRNA interaction may exist in plants indicating alternate mode of miRNA target recognition. Incorporation of these divergent features would enable next-generation of algorithms to better identify target interactions.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-348) contains supplementary material, which is available to authorized users.     

Integrated miRNA-mRNA Analysis Revealing the Potential Roles of miRNAs in Chordomas

Introduction

Emerging evidence suggests that microRNAs (miRNAs) are crucially involved in tumorigenesis and that paired expression profiles of miRNAs and mRNAs can be used to identify functional miRNA-target relationships with high precision. However, no studies have applied integrated analysis to miRNA and mRNA profiles in chordomas. The purpose of this study was to provide insights into the pathogenesis of chordomas by using this integrated analysis method.

Methods

Differentially expressed miRNAs and mRNAs of chordomas (n = 3) and notochord tissues (n = 3) were analyzed by using microarrays with hierarchical clustering analysis. Subsequently, the target genes of the differentially expressed miRNAs were predicted and overlapped with the differentially expressed mRNAs. Then, GO and pathway analyses were performed for the intersecting genes.

Results

The microarray analysis indicated that 33 miRNAs and 2,791 mRNAs were significantly dysregulated between the two groups. Among the 2,791 mRNAs, 911 overlapped with putative miRNA target genes. A pathway analysis showed that the MAPK pathway was consistently enriched in the chordoma tissue and that miR-149-3p, miR-663a, miR-1908, miR-2861 and miR-3185 likely play important roles in the regulation of MAPK pathways. Furthermore, the Notch signaling pathway and the loss of the calcification or ossification capacity of the notochord may also be involved in chordoma pathogenesis.

Conclusion

This study provides an integrated dataset of the miRNA and mRNA profiles in chordomas, and the results demonstrate that not only the MAPK pathway and its related miRNAs but also the Notch pathway may be involved in chordoma development. The occurrence of chordoma may be associated with dysfunctional calcification or ossification of the notochord.     

Expression and localization of microRNAs in perinatal rat pancreas: role of miR-21 in regulation of cholesterol metabolism

Objective

To investigate the expression of pancreatic microRNAs (miRNAs) during the period of perinatal beta-cell expansion and maturation in rats, determine the localization of these miRNAs and perform a pathway analysis with predicted target mRNAs expressed in perinatal pancreas.

Research Design and Methods

RNA was extracted from whole pancreas at embryonic day 20 (E20), on the day of birth (P0) and two days after birth (P2) and hybridized to miRNA microarrays. Differentially expressed miRNAs were verified by northern blotting and their pancreatic localization determined by in situ hybridization. Pathway analysis was done using regulated sets of mRNAs predicted as targets of the miRNAs. Possible target genes were tested using reporter-gene analysis in INS-1E cells.

Results

Nine miRNAs were differentially expressed perinatally, seven were confirmed to be regulated at the level of the mature miRNA. The localization studies showed endocrine localization of six of these miRNAs (miR-21, -23a, -29a, -125b-5p, -376b-3p and -451), and all were expressed in exocrine cells at one time point at least. Pathways involving metabolic processes, terpenoid and sterol metabolism were selectively affected by concomitant regulation by miRNAs and mRNAs, and Srebf1 was validated as a target of miR-21.

Conclusions

The findings suggest that miRNAs are involved in the functional maturation of pancreatic exocrine and endocrine tissue following birth. Pathway analysis of target genes identify changes in sterol metabolism around birth as being selectively affected by differential miRNA expression during this period.