A microRNA component of the p53 tumour suppressor network.

A global decrease in microRNA (miRNA) levels is often observed in human cancers, indicating that small RNAs may have an intrinsic function in tumour suppression. To identify miRNA components of tumour suppressor pathways, we compared miRNA expression profiles of wild-type and p53-deficient cells. Here we describe a family of miRNAs, miR-34a-c, whose expression reflected p53 status. Genes encoding miRNAs in the miR-34 family are direct transcriptional targets of p53, whose induction by DNA damage and oncogenic stress depends on p53 both in vitro and in vivo. Ectopic expression of miR-34 induces cell cycle arrest in both primary and tumour-derived cell lines, which is consistent with the observed ability of miR-34 to downregulate a programme of genes promoting cell cycle progression. The p53 network suppresses tumour formation through the coordinated activation of multiple transcriptional targets, and miR-34 may act in concert with other effectors to inhibit inappropriate cell proliferation.

The microRNA body map: dissecting microRNA function through integrative genomics.

While a growing body of evidence implicates regulatory miRNA modules in various aspects of human disease and development, insights into specific miRNA function remain limited. Here, we present an innovative approach to elucidate tissue-specific miRNA functions that goes beyond miRNA target prediction and expression correlation. This approach is based on a multi-level integration of corresponding miRNA and mRNA gene expression levels, miRNA target prediction, transcription factor target prediction and mechanistic models of gene network regulation. Predicted miRNA functions were either validated experimentally or compared to published data. The predicted miRNA functions are accessible in the miRNA bodymap, an interactive online compendium and mining tool of high-dimensional newly generated and published miRNA expression profiles. The miRNA bodymap enables prioritization of candidate miRNAs based on their expression pattern or functional annotation across tissue or disease subgroup. The miRNA bodymap project provides users with a single one-stop data-mining solution and has great potential to become a community resource.

Characterization of microRNA expression levels and their biological correlates in human cancer cell lines.

MicroRNAs are small noncoding RNAs that function by regulating target gene expression posttranscriptionally. They play a critical role in developmental and physiologic processes and are implicated in the pathogenesis of several human diseases including cancer. We examined the expression profiles of 241 human microRNAs in normal tissues and the NCI-60 panel of human tumor-derived cell lines. To quantify microRNA expression, we employed a highly sensitive technique that uses stem-loop primers for reverse transcription followed by real-time PCR. Most microRNAs were expressed at lower levels in tumor-derived cell lines compared with the corresponding normal tissue. Agglomerative hierarchical clustering analysis of microRNA expression revealed four groups among the NCI-60 cell lines consisting of hematologic, colon, central nervous system, and melanoma tumor-derived cell lines clustered in a manner that reflected their tissue of origin. We identified specific subsets of microRNAs that provide candidate molecular signatures characteristic of the tumor-derived cell lines belonging to these four clusters. We also identified specific microRNA expression patterns that correlated with the proliferation indices of the NCI-60 cell lines, and we developed evidence for the identification of specific microRNAs as candidate oncogenes and tumor suppressor genes in different tumor types. Our results provide evidence that microRNA expression patterns may mark specific biological characteristics of tumors and/or mediate biological activities important for the pathobiology of malignant tumors. These findings call attention to the potential of microRNAs to provide etiologic insights as well as to serve as both diagnostic markers and therapeutic targets for many different tumor types.

Characterization of microRNA expression profiles in normal human tissues.

BACKGROUND: Measuring the quantity of miRNAs in tissues of different physiological and pathological conditions is an important first step to investigate the functions of miRNAs. Matched samples from normal state can provide essential baseline references to analyze the variation of miRNA abundance. RESULTS: We provided expression data of 345 miRNAs in 40 normal human tissues, which identified universally expressed miRNAs, and several groups of miRNAs expressed exclusively or preferentially in certain tissue types. Many miRNAs with co-regulated expression patterns are located within the same genomic clusters, and candidate transcriptional factors that control the pattern of their expression may be identified by a comparative genomic strategy. Hierarchical clustering of normal tissues by their miRNA expression profiles basically followed the structure, anatomical locations, and physiological functions of the organs, suggesting that functions of a miRNA could be appreciated by linking to the biologies of the tissues in which it is uniquely expressed. Many predicted target genes of miRNAs that had specific reduced expression in brain and peripheral blood mononuclear cells are required for embryonic development of the nervous and hematopoietic systems based on database search. CONCLUSION: We presented a global view of tissue distribution of miRNAs in relation to their chromosomal locations and genomic structures. We also described evidence from the cis-regulatory elements and the predicted target genes of miRNAs to support their tissue-specific functional roles to regulate the physiologies of the normal tissues in which they are expressed.

Real-time quantification of microRNAs by stem-loop RT-PCR.

A novel microRNA (miRNA) quantification method has been developed using stem-loop RT followed by TaqMan PCR analysis. Stem-loop RT primers are better than conventional ones in terms of RT efficiency and specificity. TaqMan miRNA assays are specific for mature miRNAs and discriminate among related miRNAs that differ by as little as one nucleotide. Furthermore, they are not affected by genomic DNA contamination. Precise quantification is achieved routinely with as little as 25 pg of total RNA for most miRNAs. In fact, the high sensitivity, specificity and precision of this method allows for direct analysis of a single cell without nucleic acid purification. Like standard TaqMan gene expression assays, TaqMan miRNA assays exhibit a dynamic range of seven orders of magnitude. Quantification of five miRNAs in seven mouse tissues showed variation from less than 10 to more than 30,000 copies per cell. This method enables fast, accurate and sensitive miRNA expression profiling and can identify and monitor potential biomarkers specific to tissues or diseases. Stem-loop RT-PCR can be used for the quantification of other small RNA molecules such as short interfering RNAs (siRNAs). Furthermore, the concept of stem-loop RT primer design could be applied in small RNA cloning and multiplex assays for better specificity and efficiency.

The SNPlex genotyping system: a flexible and scalable platform for SNP genotyping.

We developed the SNPlex Genotyping System to address the need for accurate genotyping data, high sample throughput, study design flexibility, and cost efficiency. The system uses oligonucleotide ligation/polymerase chain reaction and capillary electrophoresis to analyze bi-allelic single nucleotide polymorphism genotypes. It is well suited for single nucleotide polymorphism genotyping efforts in which throughput and cost efficiency are essential. The SNPlex Genotyping System offers a high degree of flexibility and scalability, allowing the selection of custom-defined sets of SNPs for medium- to high-throughput genotyping projects. It is therefore suitable for a broad range of study designs. In this article we describe the principle and applications of the SNPlex Genotyping System, as well as a set of single nucleotide polymorphism selection tools and validated assay resources that accelerate the assay design process. We developed the control pool, an oligonucleotide ligation probe set for training and quality-control purposes, which interrogates 48 SNPs simultaneously. We present performance data from this control pool obtained by testing genomic DNA samples from 44 individuals. in addition, we present data from a study that analyzed 521 SNPs in 92 individuals. Combined, both studies show the SNPlex Genotyping system to have a 99.32% overall call rate, 99.95% precision, and 99.84% concordance with genotypes analyzed by TaqMan probe-based assays. The SNPlex Genotyping System is an efficient and reliable tool for a broad range of genotyping applications, supported by applications for study design, data analysis, and data management.

Defining embryonic stem cell identity using differentiation-related microRNAs and their potential targets.

Defining the identity of embryonic stem (ES) cells in quantitative molecular terms is a prerequisite to understanding their functional characteristics. Little is known about the role of microRNAs (miRNAs) in the regulation of ES cell identity. Statistical analysis of miRNA expression revealed unique expression signatures that could definitively classify mouse ES (mES), embryoid bodies (mEB), and somatic tissues. Analysis of these data sets also provides further confirmation of the nonrestrictive expression of miRNAs during murine development. Using combined genome-wide expression analyses of both miRNAs and mRNAs, we observed both negative and positive correlations in gene expression between miRNAs and their predicted targets. ES-specific miRNAs were positively correlated with their predicted targets, suggesting that mES-specific miRNAs may have a different role or mechanism in regulating their targets in mES maintenance or differentiation. The concept of cellular identity has changed with technology; this study redefines cellular identity by a generic statistical method of known dimension.

Nonrestrictive developmental regulation of microRNA gene expression.

During different periods of mammalian development, global changes in gene expression occur. Developmental changes in global gene expression have been modeled as a restrictive process. To test the restriction model of global changes in gene expression, we have used embryonic stem (ES) cells as a model system for the early mammalian embryo. ES cells are pluripotent cells that can contribute to all cellular lineages of the developing mammalian fetus and are derived from early embryonic cells. Using this model system, we have studied a new class of RNAs called microRNAs that have been identified and shown to play a role in the direct regulation of messenger RNAs. Here we report the expression signature for 248 microRNAs in 13 independent murine ES cells, embryoid bodies, and somatic tissues. The expression profile for 248 mouse microRNAs was determined for embryonic stem cells, embryoid bodies, mouse embryos, mature heart, lung, liver, kidney, and brain. Characteristic microRNA expression signatures were observed for each evaluated sample. When the characteristic microRNA signatures for developmentally ordered samples were compared, immature samples exhibited a less complex microRNA transcript profile than did mature samples. Our data support a progressive model of microRNA gene expression. Based on the progressive increase in complexity of micro- RNA expression, we hypothesize that the mammalian developmental program requires a temporal coupling of expression between microRNAs and messenger RNAs to enable the developmental potential observed in mammalian ontogeny.