Joint Genome-Wide Profiling of miRNA and mRNA Expression in Alzheimer's Disease Cortex Reveals Altered miRNA Regulation

Although microRNAs are being extensively studied for their involvement in cancer and development, little is known about their roles in Alzheimer''s disease (AD). In this study, we used microarrays for the first joint profiling and analysis of miRNAs and mRNAs expression in brain cortex from AD and age-matched control subjects. These data provided the unique opportunity to study the relationship between miRNA and mRNA expression in normal and AD brains. Using a non-parametric analysis, we showed that the levels of many miRNAs can be either positively or negatively correlated with those of their target mRNAs. Comparative analysis with independent cancer datasets showed that such miRNA-mRNA expression correlations are not static, but rather context-dependent. Subsequently, we identified a large set of miRNA-mRNA associations that are changed in AD versus control, highlighting AD-specific changes in the miRNA regulatory system. Our results demonstrate a robust relationship between the levels of miRNAs and those of their targets in the brain. This has implications in the study of the molecular pathology of AD, as well as miRNA biology in general.     

Tethering of human Ago proteins to mRNA mimics the miRNA-mediated repression of protein synthesis

MicroRNAs (miRNAs) are approximately 21-nt-long RNAs involved in regulating development, differentiation, and other processes in eukaryotes. In metazoa, nearly all miRNAs control gene expression by imperfectly base-pairing with the 3'-untranslated region (3'-UTR) of target mRNAs and repressing protein synthesis by an unknown mechanism. It is also unknown whether miRNA-mRNA duplexes containing mismatches and bulges provide specific features that are recognized by factors mediating the repression. miRNAs form part of ribonucleoprotein complexes, miRNPs, that contain Argonaute (Ago) and other proteins. Here we demonstrate that effects of miRNAs on translation can be mimicked in human HeLa cells by the miRNA-independent tethering of Ago proteins to the 3'-UTR of a reporter mRNA. Inhibition of protein synthesis occurred without a change in the reporter mRNA level and was dependent on the number, but not the position, of the hairpins tethering hAgo2 to the 3'-UTR. These findings indicate that a primary function of miRNAs is to guide their associated proteins to the mRNA.     

Discovery of microRNA-mRNA modules via population-based probabilistic learning

MOTIVATION: MicroRNAs (miRNAs) and mRNAs constitute an important part of gene regulatory networks, influencing diverse biological phenomena. Elucidating closely related miRNAs and mRNAs can be an essential first step towards the discovery of their combinatorial effects on different cellular states. Here, we propose a probabilistic learning method to identify synergistic miRNAs involving regulation of their condition-specific target genes (mRNAs) from multiple information sources, i.e. computationally predicted target genes of miRNAs and their respective expression profiles. RESULTS: We used data sets consisting of miRNA-target gene binding information and expression profiles of miRNAs and mRNAs on human cancer samples. Our method allowed us to detect functionally correlated miRNA-mRNA modules involved in specific biological processes from multiple data sources by using a balanced fitness function and efficient searching over multiple populations. The proposed algorithm found two miRNA-mRNA modules, highly correlated with respect to their expression and biological function. Moreover, the mRNAs included in the same module showed much higher correlations when the related miRNAs were highly expressed, demonstrating our method's ability for finding coherent miRNA-mRNA modules. Most members of these modules have been reported to be closely related with cancer. Consequently, our method can provide a primary source of miRNA and target sets presumed to constitute closely related parts of gene regulatory pathways.     

Inference of miRNA targets using evolutionary conservation and pathway analysis

Background

MicroRNAs have emerged as important regulatory genes in a variety of cellular processes and, in recent years, hundreds of such genes have been discovered in animals. In contrast, functional annotations are available only for a very small fraction of these miRNAs, and even in these cases only partially.

Results

We developed a general Bayesian method for the inference of miRNA target sites, in which, for each miRNA, we explicitly model the evolution of orthologous target sites in a set of related species. Using this method we predict target sites for all known miRNAs in flies, worms, fish, and mammals. By comparing our predictions in fly with a reference set of experimentally tested miRNA-mRNA interactions we show that our general method performs at least as well as the most accurate methods available to date, including ones specifically tailored for target prediction in fly. An important novel feature of our model is that it explicitly infers the phylogenetic distribution of functional target sites, independently for each miRNA. This allows us to infer species-specific and clade-specific miRNA targeting. We also show that, in long human 3' UTRs, miRNA target sites occur preferentially near the start and near the end of the 3' UTR. To characterize miRNA function beyond the predicted lists of targets we further present a method to infer significant associations between the sets of targets predicted for individual miRNAs and specific biochemical pathways, in particular those of the KEGG pathway database. We show that this approach retrieves several known functional miRNA-mRNA associations, and predicts novel functions for known miRNAs in cell growth and in development.

Conclusion

We have presented a Bayesian target prediction algorithm without any tunable parameters, that can be applied to sequences from any clade of species. The algorithm automatically infers the phylogenetic distribution of functional sites for each miRNA, and assigns a posterior probability to each putative target site. The results presented here indicate that our general method achieves very good performance in predicting miRNA target sites, providing at the same time insights into the evolution of target sites for individual miRNAs. Moreover, by combining our predictions with pathway analysis, we propose functions of specific miRNAs in nervous system development, inter-cellular communication and cell growth. The complete target site predictions as well as the miRNA/pathway associations are accessible on the ElMMo web server.     

Sucrose induction of <Emphasis Type="Italic">Arabidopsis</Emphasis> miR398 represses two Cu/Zn superoxide dismutases

MicroRNAs (miRNAs) are approximately 21-nt RNAs that reduce target accumulation through mRNA cleavage or translational repression. Arabidopsis miR398 regulates mRNAs encoding two copper superoxide dismutase (CSD) enzymes and a cytochrome c oxidase subunit. miR398 itself is down-regulated in response to copper and stress. Here we show that miR398 is positively regulated by sucrose, resulting in decreased CSD1 and CSD2 mRNA and protein accumulation. This sucrose regulation is maintained both in the presence and absence of physiologically relevant levels of supplemental copper. Additionally, we show that plants expressing CSD1 and CSD2 mRNAs with altered miR398 complementarity sites display increased mRNA accumulation, whereas CSD1 and CSD2 protein accumulation remain sensitive to miR398 levels, suggesting that miR398 can act as a translational repressor when target site complementarity is reduced. These results reveal a novel miR398 regulatory mechanism and demonstrate that plant miRNA targets can resist miRNA regulation at the mRNA level while maintaining sensitivity at the level of protein accumulation. Our results suggest that even in plants, where miRNAs are thought to act primarily through target mRNA cleavage, monitoring target protein levels along with target mRNA levels is necessary to fully assess the consequences of disrupted miRNA-mRNA pairing. Moreover, the limited complementarity required to maintain robust miR398-directed repression of target protein accumulation suggests that similarly regulated endogenous plant miRNA targets may have eluded detection.     

Methods for predicting single-cell miRNA in breast cancer

It has been demonstrated that miRNAs are involved in many biological processes including cell proliferation and differentiation, apoptosis, and stress responses. Although single-cell RNA sequencing technology is prevailing nowadays, it still remains challenging in quantifying miRNA at the single-cell level. Herein, we present the computational methods to infer the single-cell miRNA expression level using its target gene abundances. Firstly, we developed an enrichment-based approach in estimating miRNA expression considering miRNA-mRNA regulation information and miRNA-mRNA correlation signal captured from existing TCGA datasets. Further efforts were made to infer the miRNA expression with machine learning models. The methods were applied to compare the accuracy and robustness with the simulated single-cell data. Finally, we applied the method in single-cell RNA-seq triple negative breast cancer (TNBC) patients to further discover miRNA marker at the single-cell level for the malignant cells. Our tool is available online at: https://github.com/ChengkuiZhao/Single-cell-miRNA-prediction.     

星形细胞瘤生存预后相关miRNA-mRNA调控关系对筛选

利用GEO数据库中的芯片数据,筛选与星形细胞瘤生存预后相关的miRNA-mRNA调控关系对,为后续研究提供理论支持.下载芯片数据利用R语言进行差异表达分析,得到星形细胞瘤较正常组织表达显著改变的miRNA与mRNA;通过miRNA靶基因预测,将靶基因与差异表达mRNA取交集,明确mRNA与miRNA之间的关系;利用GE...