Refining microRNA target predictions: Sorting the wheat from the chaff

microRNAs are short RNAs that reduce gene expression by binding to their targets. The accurate prediction of microRNA targets is essential to understanding the function of microRNAs. Computational predictions indicate that all human genes may be regulated by microRNAs, with each microRNA possibly targeting thousands of genes. Here we discuss computational methods for identifying mammalian microRNA targets and refining them for further experimental validation. We describe microRNA target prediction resources and procedures and how they integrate with various types of experimental techniques that aim to validate them or further explore their function. We also provide a list of target prediction databases and explain how these are curated.     

Genome-wide prioritization of disease genes and identification of disease-disease associations from an integrated human functional linkage network

Background

Recent studies have shown that the regulatory effect of microRNAs can be investigated by examining expression changes of their target genes. Given this, it is useful to define an overall metric of regulatory effect for a specific microRNA and see how this changes across different conditions.

Results

Here, we define a regulatory effect score (RE-score) to measure the inhibitory effect of a microRNA in a sample, essentially the average difference in expression of its targets versus non-targets. Then we compare the RE-scores of various microRNAs between two breast cancer subtypes: estrogen receptor positive (ER⁺) and negative (ER^-). We applied this approach to five microarray breast cancer datasets and found that the expression of target genes of most microRNAs was more repressed in ER^- than ER⁺; that is, microRNAs appear to have higher RE-scores in ER^- breast cancer. These results are robust to the microRNA target prediction method. To interpret these findings, we analyzed the level of microRNA expression in previous studies and found that higher microRNA expression was not always accompanied by higher inhibitory effects. However, several key microRNA processing genes, especially Ago2 and Dicer, were differentially expressed between ER^- and ER⁺ breast cancer, which may explain the different regulatory effects of microRNAs in these two breast cancer subtypes.

Conclusions

The RE-score is a promising indicator to measure microRNAs' inhibitory effects. Most microRNAs exhibit higher RE-scores in ER^- than in ER⁺ samples, suggesting that they have stronger inhibitory effects in ER^- breast cancers.     

mRNA expression profiles show differential regulatory effects of microRNAs between estrogen receptor-positive and estrogen receptor-negative breast cancer

Background

Recent studies have shown that the regulatory effect of microRNAs can be investigated by examining expression changes of their target genes. Given this, it is useful to define an overall metric of regulatory effect for a specific microRNA and see how this changes across different conditions.

Results

Here, we define a regulatory effect score (RE-score) to measure the inhibitory effect of a microRNA in a sample, essentially the average difference in expression of its targets versus non-targets. Then we compare the RE-scores of various microRNAs between two breast cancer subtypes: estrogen receptor positive (ER⁺) and negative (ER^-). We applied this approach to five microarray breast cancer datasets and found that the expression of target genes of most microRNAs was more repressed in ER^- than ER⁺; that is, microRNAs appear to have higher RE-scores in ER^- breast cancer. These results are robust to the microRNA target prediction method. To interpret these findings, we analyzed the level of microRNA expression in previous studies and found that higher microRNA expression was not always accompanied by higher inhibitory effects. However, several key microRNA processing genes, especially Ago2 and Dicer, were differentially expressed between ER^- and ER⁺ breast cancer, which may explain the different regulatory effects of microRNAs in these two breast cancer subtypes.

Conclusions

The RE-score is a promising indicator to measure microRNAs'' inhibitory effects. Most microRNAs exhibit higher RE-scores in ER^- than in ER⁺ samples, suggesting that they have stronger inhibitory effects in ER^- breast cancers.     

miRSel: Automated extraction of associations between microRNAs and genes from the biomedical literature

Background  

MicroRNAs have been discovered as important regulators of gene expression. To identify the target genes of microRNAs, several databases and prediction algorithms have been developed. Only few experimentally confirmed microRNA targets are available in databases. Many of the microRNA targets stored in databases were derived from large-scale experiments that are considered not very reliable. We propose to use text mining of publication abstracts for extracting microRNA-gene associations including microRNA-target relations to complement current repositories.     

microRNA target predictions across seven Drosophila species and comparison to mammalian targets

microRNAs are small noncoding genes that regulate the protein production of genes by binding to partially complementary sites in the mRNAs of targeted genes. Here, using our algorithm PicTar, we exploit cross-species comparisons to predict, on average, 54 targeted genes per microRNA above noise in Drosophila melanogaster. Analysis of the functional annotation of target genes furthermore suggests specific biological functions for many microRNAs. We also predict combinatorial targets for clustered microRNAs and find that some clustered microRNAs are likely to coordinately regulate target genes. Furthermore, we compare microRNA regulation between insects and vertebrates. We find that the widespread extent of gene regulation by microRNAs is comparable between flies and mammals but that certain microRNAs may function in clade-specific modes of gene regulation. One of these microRNAs (miR-210) is predicted to contribute to the regulation of fly oogenesis. We also list specific regulatory relationships that appear to be conserved between flies and mammals. Our findings provide the most extensive microRNA target predictions in Drosophila to date, suggest specific functional roles for most microRNAs, indicate the existence of coordinate gene regulation executed by clustered microRNAs, and shed light on the evolution of microRNA function across large evolutionary distances. All predictions are freely accessible at our searchable Web site http://pictar.bio.nyu.edu.     

Age‐associated microRNA expression in human peripheral blood is associated with all‐cause mortality and age‐related traits

Recent studies provide evidence of correlations of DNA methylation and expression of protein‐coding genes with human aging. The relations of microRNA expression with age and age‐related clinical outcomes have not been characterized thoroughly. We explored associations of age with whole‐blood microRNA expression in 5221 adults and identified 127 microRNAs that were differentially expressed by age at P < 3.3 × 10^?4 (Bonferroni‐corrected). Most microRNAs were underexpressed in older individuals. Integrative analysis of microRNA and mRNA expression revealed changes in age‐associated mRNA expression possibly driven by age‐associated microRNAs in pathways that involve RNA processing, translation, and immune function. We fitted a linear model to predict ‘microRNA age’ that incorporated expression levels of 80 microRNAs. MicroRNA age correlated modestly with predicted age from DNA methylation (r = 0.3) and mRNA expression (r = 0.2), suggesting that microRNA age may complement mRNA and epigenetic age prediction models. We used the difference between microRNA age and chronological age as a biomarker of accelerated aging (Δage) and found that Δage was associated with all‐cause mortality (hazards ratio 1.1 per year difference, P = 4.2 × 10^?5 adjusted for sex and chronological age). Additionally, Δage was associated with coronary heart disease, hypertension, blood pressure, and glucose levels. In conclusion, we constructed a microRNA age prediction model based on whole‐blood microRNA expression profiling. Age‐associated microRNAs and their targets have potential utility to detect accelerated aging and to predict risks for age‐related diseases.     

利用种子序列检测山羊皮肤中microRNA靶基因分子方法的建立

文章旨在建立一种种子序列介导的可控遗传操作—microRNA靶基因指纹图谱(MicroRNA targets fingerprint,MTFP),用于在基因表达检测中筛选与特定microRNA相关的靶基因。在设定上游种子序列的互补序列和下游锚定序列的基础上添加特殊接头,通过反转录和特殊二步PCR将microRNA的靶基因扩增;扩增后的microRNA靶基因在聚丙烯酰胺凝胶电泳中检测其片段大小和表达丰度,用于筛选在不同生理状态或试验条件下特异表达的基因;特定的靶基因序列通过DNA回收和测序方法得到。以miR-203为例,在不同生理状态的山羊皮肤样品中获得了5条大小分别为718 bp(JN709494)、349 bp(JN709495)、243 bp(JN709496)、156 bp(JN709497)和97 bp(JN709498)的靶基因序列。MTFP经济适用、可操作性强,可用于探索microRNA调节的靶基因,或用来评估靶基因的表达谱特征。     

Identification and Validation of Human Papillomavirus Encoded microRNAs

We report here identification and validation of the first papillomavirus encoded microRNAs expressed in human cervical lesions and cell lines. We established small RNA libraries from ten human papillomavirus associated cervical lesions including cancer and two human papillomavirus harboring cell lines. These libraries were sequenced using SOLiD 4 technology. We used the sequencing data to predict putative viral microRNAs and discovered nine putative papillomavirus encoded microRNAs. Validation was performed for five candidates, four of which were successfully validated by qPCR from cervical tissue samples and cell lines: two were encoded by HPV 16, one by HPV 38 and one by HPV 68. The expression of HPV 16 microRNAs was further confirmed by in situ hybridization, and colocalization with p16INK4A was established. Prediction of cellular target genes of HPV 16 encoded microRNAs suggests that they may play a role in cell cycle, immune functions, cell adhesion and migration, development, and cancer. Two putative viral target sites for the two validated HPV 16 miRNAs were mapped to the E5 gene, one in the E1 gene, two in the L1 gene and one in the LCR region. This is the first report to show that papillomaviruses encode their own microRNA species. Importantly, microRNAs were found in libraries established from human cervical disease and carcinoma cell lines, and their expression was confirmed in additional tissue samples. To our knowledge, this is also the first paper to use in situ hybridization to show the expression of a viral microRNA in human tissue.     

The miR-30 MicroRNA Family Targets smoothened to Regulate Hedgehog Signalling in Zebrafish Early Muscle Development

The importance of microRNAs in development is now widely accepted. However, identifying the specific targets of individual microRNAs and understanding their biological significance remains a major challenge. We have used the zebrafish model system to evaluate the expression and function of microRNAs potentially involved in muscle development and study their interaction with predicted target genes. We altered expression of the miR-30 microRNA family and generated phenotypes that mimicked misregulation of the Hedgehog pathway. Inhibition of the miR-30 family increases activity of the pathway, resulting in elevated ptc1 expression and increased numbers of superficial slow-muscle fibres. We show that the transmembrane receptor smoothened is a target of this microRNA family. Our results indicate that fine coordination of smoothened activity by the miR-30 family allows the correct specification and differentiation of distinct muscle cell types during zebrafish embryonic development.     

microRNA的调控和被调控

microRNA是一大类长度约22 nt的非编码RNA,可与靶基因的3′-UTR区部分或完全配对结合,进而通过降低靶mRNA的稳定性或抑制翻译而下调目的基因的表达. microRNA不仅参与细胞的增殖、分化、死亡等正常生理过程,而且还与包括癌症在内的诸多病理过程密切相关.microRNA通常位于编码基因的内含子区,主要由RNA聚合酶Ⅱ催化而转录为初始microRNA,接着经过一系列的核内、胞浆内酶切步骤而组装成有功能的RNA诱导的沉默复合体.本文将在简要介绍microRNA生物合成和调控功能的基础上,重点综述microRNA被调控的研究进展,主要包括表观遗传学水平、转录水平、转录后水平和降解的调控.近年来的研究,逐步丰富甚至推翻了以往对microRNA的认识,体现了microRNA生物学的复杂性.可以预见,随着研究的深入,microRNA将在疾病的早期防治中发挥越来越重要的作用.     

MicroRNAs in vertebrate development

The vertebrate genome contains hundreds of small non-coding 'microRNAs' that have been implicated in controlling the expression of potentially thousands of target genes. Presently, only a handful of these targets have been characterized. Recent reports of microRNA 'sensors', microRNA microarrays and the creation of vertebrates that lack all microRNA activity will aid in determining the roles played by microRNAs, and the genes that they regulate, during vertebrate development.