Tissue and Process Specific microRNA–mRNA Co-Expression in Mammalian Development and Malignancy

An association between enrichment and depletion of microRNA (miRNA) binding sites, 3′ UTR length, and mRNA expression has been demonstrated in various developing tissues and tissues from different mature organs; but functional, context-dependent miRNA regulations have yet to be elucidated. Towards that goal, we examined miRNA–mRNA interactions by measuring miRNA and mRNA in the same tissue during development and also in malignant conditions. We identified significant miRNA-mediated biological process categories in developing mouse cerebellum and lung using non-targeted mRNA expression as the negative control. Although miRNAs in general suppress target mRNA messages, many predicted miRNA targets demonstrate a significantly higher level of co-expression than non-target genes in developing cerebellum. This phenomenon is tissue specific since it is not observed in developing lungs. Comparison of mouse cerebellar development and medulloblastoma demonstrates a shared miRNA–mRNA co-expression program for brain-specific neurologic processes such as synaptic transmission and exocytosis, in which miRNA target expression increases with the accumulation of multiple miRNAs in developing cerebellum and decreases with the loss of these miRNAs in brain tumors. These findings demonstrate the context-dependence of miRNA–mRNA co-expression.     

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.     

Accurate transcriptome-wide prediction of microRNA targets and small interfering RNA off-targets with MIRZA-G

Small interfering RNA (siRNA)-mediated knock-down is a widely used experimental approach to characterizing gene function. Although siRNAs are designed to guide the cleavage of perfectly complementary mRNA targets, acting similarly to microRNAs (miRNAs), siRNAs down-regulate the expression of hundreds of genes to which they have only partial complementarity. Prediction of these siRNA ‘off-targets’ remains difficult, due to the incomplete understanding of siRNA/miRNA–target interactions. Combining a biophysical model of miRNA–target interaction with structure and sequence features of putative target sites we developed a suite of algorithms, MIRZA-G, for the prediction of miRNA targets and siRNA off-targets on a genome-wide scale. The MIRZA-G variant that uses evolutionary conservation performs better than currently available methods in predicting canonical miRNA target sites and in addition, it predicts non-canonical miRNA target sites with similarly high accuracy. Furthermore, MIRZA-G variants predict siRNA off-target sites with an accuracy unmatched by currently available programs. Thus, MIRZA-G may prove instrumental in the analysis of data resulting from large-scale siRNA screens.     

Deep Sequencing of Small RNA Repertoires in Mice Reveals Metabolic Disorders-Associated Hepatic miRNAs

Obesity and associated metabolic disorders contribute importantly to the metabolic syndrome. On the other hand, microRNAs (miRNAs) are a class of small non-coding RNAs that repress target gene expression by inducing mRNA degradation and/or translation repression. Dysregulation of specific miRNAs in obesity may influence energy metabolism and cause insulin resistance, which leads to dyslipidemia, steatosis hepatis and type 2 diabetes. In the present study, we comprehensively analyzed and validated dysregulated miRNAs in ob/ob mouse liver, as well as miRNA groups based on miRNA gene cluster and gene family by using deep sequencing miRNA datasets. We found that over 13.8% of the total analyzed miRNAs were dysregulated, of which 37 miRNA species showed significantly differential expression. Further RT-qPCR analysis in some selected miRNAs validated the similar expression patterns observed in deep sequencing. Interestingly, we found that miRNA gene cluster and family always showed consistent dysregulation patterns in ob/ob mouse liver, although they had various enrichment levels. Functional enrichment analysis revealed the versatile physiological roles (over six signal pathways and five human diseases) of these miRNAs. Biological studies indicated that overexpression of miR-126 or inhibition of miR-24 in AML-12 cells attenuated free fatty acids-induced fat accumulation. Taken together, our data strongly suggest that obesity and metabolic disturbance are tightly associated with functional miRNAs. We also identified hepatic miRNA candidates serving as potential biomarkers for the diagnose of the metabolic syndrome.     

Efficiency of the miRNA–mRNA Interaction Prediction Programs

miRNAs play a key role in regulation of gene expression. Nowadays it is known more than 2500 human miRNAs, while a majority of miRNA–mRNA interactions remains unidentified. The recent development of a high-throughput CLASH (crosslinking, ligation and sequencing of hybrids) technique for discerning miRNA–mRNA interactions allowed an experimental analysis of the human miRNA–mRNA interactome. Therefore, it allowed us, for the first time, make an experimental analysis of the human miRNA–mRNA interactome as a whole and an evaluation of the quality of most commonly used miRNA prediction tools (TargetScan, PicTar, PITA, RNA22 and miRanda). To estimate efficiency of the miRNA–mRNA prediction tools, we used next parameters: sensitivity, positive predicted value, predictions in different mRNA regions (3' UTR, CDS, 5' UTR), predictions for different types of interactions (5 classes), predictions of “canonical” and “nocanonical” interactions, similarity with the random generated data. The analysis revealed low efficiency of all prediction programs in comparison with the CLASH data in terms of the all examined parameters.     

MicroRNA expression profile in RAW264.7 cells in response to Brucella melitensis infection

MicroRNA (miRNA) is small non-coding RNA with approximate 22 nt in length. Recent studies indicate that miRNAs play significant roles in pathogen-host interactions. Brucella organisms are Gram-negative facultative intracellular bacteria that cause Brucellosis. Brucella strains infect macrophages and establish chronic infection by altering host life activities including apoptosis and autophagy. Here, we report a comprehensive analysis of miRNA expression profiles in mock- and Brucella-infected RAW264.7 cells using high-throughput sequencing approach. In total, 344 unique miRNAs were co-expressed in the two libraries, in which 57 miRNAs were differentially expressed. Eight differentially expressed miRNAs with high abundance were subjected to further analysis. The GO enrichment analysis suggests that the putative target genes of these differentially expressed miRNAs are involved in apoptosis, autophagy and immune response. In particular, a total of 25 target genes are involved in regulating apoptosis and autophagy, indicating that these miRNAs may play important regulatory roles in the Brucella-host interactions. Furthermore, the interactions of miR-1981 and its target genes, Bcl-2 and Bid, were validated by luciferase assay. The results show that miR-1981 mimic up-regulated the luciferase activity of psiCHECK-2 Bcl-2 3' UTR, but the luciferase activity of psiCHECK-2 Bid 3' UTR was not changed significantly. Taken together, these data provide valuable framework on Brucella induced miRNA expression in RAW264.7 cells, and suggest that Brucella may establish chronic infection by regulating miRNA expression profile.     

Coordinated miRNA/mRNA expression profiles for understanding breed-specific metabolic characters of liver between Erhualian and large white pigs

MicroRNAs (miRNAs) are involved in the regulation of various metabolic processes in the liver, yet little is known on the breed-specific expression profiles of miRNAs in coordination with those of mRNAs. Here we used two breeds of male newborn piglets with distinct metabolic characteristics, Large White (LW) and Erhualian (EHL), to delineate the hepatic expression profiles of mRNA with microarray and miRNAs with both deep sequencing and microarray, and to analyze the functional relevance of integrated miRNA and mRNA expression in relation to the physiological and biochemical parameters. EHL had significantly lower body weight and liver weight at birth, but showed elevated serum levels of total cholesterol (TCH), high-density lipoprotein cholesterol (HDLC) and low-density lipoprotein cholesterol (LDLC), as well as higher liver content of cholesterol. Higher serum cortisol and lower serum insulin and leptin were also observed in EHL piglets. Compared to LW, 30 up-regulated and 18 down-regulated miRNAs were identified in the liver of EHL, together with 298 up-regulated and 510 down-regulated mRNAs (FDR<10%). RT-PCR validation of some differentially expressed miRNAs (DEMs) further confirmed the high-throughput data analysis. Using a target prediction algorithm, we found significant correlation between the up-regulated miRNAs and down-regulated mRNAs. Moreover, differentially expressed genes (DEGs), which are involved in proteolysis, were predicted to be mediated by DEMs. These findings provide new information on the miRNA and mRNA profiles in porcine liver, which would shed light on the molecular mechanisms underlying the breed-specific traits in the pig, and may serve as a basis for further investigation into the biological functions of miRNAs in porcine liver.     

Integrated analysis of miRNA and mRNA expression profiles in response to gut microbiota depletion in the abdomens of female Bactrocera dorsalis

Insect gut microbiota has been reported to participate in regulating host multiple biological processes including metabolism and reproduction. However, the corresponding molecular mechanisms remain largely unknown. Recent studies suggest that microRNAs (miRNAs) are involved in complex interactions between the gut microbiota and the host. Here, we used next-generation sequencing technology to characterize miRNA and mRNA expression profiles and construct the miRNA–gene regulatory network in response to gut microbiota depletion in the abdomens of female Bactrocera dorsalis. A total of 3016 differentially expressed genes (DEGs) and 18 differentially expressed miRNAs (DEMs) were identified. Based on the integrated analysis of miRNA and mRNA sequencing data, 229 negatively correlated miRNA–gene pairs were identified from the miRNA–mRNA network. Gene ontology enrichment analysis indicated that DEMs could target several genes involved in the metabolic process, oxidation–reduction process, oogenesis, and insulin signaling pathway. Finally, real-time quantitative polymerase chain reaction further verified the accuracy of RNA sequencing results. In conclusion, our study provides the profiles of miRNA and mRNA expressions under antibiotics treatment and provides an insight into the roles of miRNAs and their target genes in the interaction between the gut microbiota and its host.