An optimized isolation and labeling platform for accurate microRNA expression profiling

MicroRNAs (miRNAs) are small, noncoding RNAs that regulate gene expression in both plants and animals. miRNA genes have been implicated in a variety of important biological processes, including development, differentiation, apoptosis, fat metabolism, viral infection, and cancer. Similar to protein-coding messenger RNAs, miRNA expression varies between tissues and developmental states. To acquire a better understanding of global miRNA expression in tissues and cells, we have developed isolation, labeling, and array procedures to measure the relative abundance of all of the known human mature miRNAs. The method relies on rapid isolation of RNA species smaller than ~40 nucleotides (nt), direct and homogenous enzymatic labeling of the mature miRNAs with amine modified ribonucleotides, and hybridization to antisense DNA oligonucleotide probes. A thorough performance study showed that this miRNA microarray system can detect subfemtomole amounts of individual miRNAs from <1 mug of total RNA, with 98% correlation between independent replicates. The system has been applied to compare the global miRNA expression profiles in 26 different normal human tissues. This comprehensive analysis identified miRNAs that are preferentially expressed in one or a few related tissues and revealed that human adult tissues have unique miRNA profiles. This implicates miRNAs as important components of tissue development and differentiation. Taken together, these results emphasize the immense potential of microarrays for sensitive and high-throughput analysis of miRNA expression in normal and disease states.     

miRNAs的表达调控机制

microRNAs(miRNAs)是一类在转录后基因调控中发挥功能的非编码小RNAs,在发育、生长和分化等过程中发挥重要作用.至今已经在动物、植物和微生物等不同生物体中鉴定出来数千种miRNAs. miRNAs可以通过降解mRNA或抑制蛋白翻译的方式调节特异基因表达.生物体内约30%的基因都受miRNAs的调节.miRNAs的表达与功能受到转录因子、表观遗传学、多核苷酸多态性及其RNA编辑等多种因素的调节.此外,特异miRNA基因敲除的成功为研究miRNAs功能提供了有力的实验模型.     

Expression profile analysis of microRNA (miRNA) in mouse central nervous system using a new miRNA detection system that examines hybridization signals at every step of washing

MicroRNAs (miRNAs) are small noncoding RNAs, with a length of 19 to 23 nucleotides, which appear to be involved in the regulation of gene expression by inhibiting the translation of messenger RNA. Expression profile analysis of miRNAs is necessary to understand their complex role in the regulation of gene expression during the development and differentiation of cells and in various tissues. We describe here a detection system for miRNA expression profiles, using a new type of DNA chip and fluorescent labeled cellular RNAs, which allows real-time detection of hybridization signals at every step of washing and results in highly reproducible miRNA expression profiles. Using the system, we investigated the expression profiles of miRNA in the mouse central nervous system (CNS), namely the spinal cord, medulla oblongata, pons, cerebellum, midbrain, diencephalons, and cerebral hemispheres. The results indicated that although the CNS subregions expressed similar miRNA genes, the expression levels of the miRNAs varied among the subregions, suggesting that the CNS subregions specialized for different functions possess different expression profiles of miRNAs.     

Cloning and characterization of miRNAs from maize seedling roots under low phosphorus stress

MicroRNAs (miRNAs) are a class of small, non-coding regulatory RNAs that regulate gene expression by guiding target mRNA cleavage or translational inhibition in plants and animals. In this study, a small RNA library was constructed to identify conserved miRNAs as well as novel miRNAs in maize seedling roots under low level phosphorus stress. Twelve miRNAs were identified by high throughput sequencing of the library and subsequent analysis, two belong to conserved miRNA families (miRNA399b and miRNA156), and the remaining ten are novel and one of latter is conserved in gramineous species. Based on sequence homology, we predicted 125 potential target genes of these miRNAs and then expression patterns of 7 miRNAs were validated by semi-RT-PCR analysis. MiRNA399b, Zma-miR3, and their target genes (Zmpt1 and Zmpt2) were analyzed by real-time PCR. It is shown that both miRNA399b and Zma-miR3 are induced by low phosphorus stress and regulated by their target genes (Zmpt1 and Zmpt2). Moreover, Zma-miR3, regulated by two maize inorganic phosphate transporters as a newly identified miRNAs, would likely be directly involved in phosphate homeostasis, so was miRNA399b in Arabidopsis and rice. These results indicate that both conserved and maize-specific miRNAs play important roles in stress responses and other physiological processes correlated with phosphate starvation, regulated by their target genes. Identification of these differentially expressed miRNAs will facilitate us to uncover the molecular mechanisms underlying the progression of maize seedling roots development under low level phosphorus stress.     

Solexa sequencing analysis of chicken pre-adipocyte microRNAs

MicroRNAs (miRNAs) are small non-coding RNAs that play important roles in a variety of biological processes. Studies of miRNAs in mammals suggest that many are involved in lipid metabolism and adipocyte differentiation, but little is known about miRNA expression profiles during chicken adipogenesis. In this study, the Solexa sequencing approach was used to sequence a small RNA library prepared from Arbor Acres broiler pre-adipocytes, and more than 10? short sequence reads were obtained. From these, 159 known chicken miRNAs and 63 novel miRNAs were identified using a bioinformatics approach. Fifty-nine of these miRNA genes were further organized into 27 compact miRNA genomic clusters, and 34 new chicken mirtrons were also discovered, among which there were 27 mirtron candidates. These findings should serve as a foundation for future research on the functional roles of miRNAs in chicken adipocyte differentiation.     

Deep sequencing reveals novel microRNAs and regulation of microRNA expression during cell senescence

In cell senescence, cultured cells cease proliferating and acquire aberrant gene expression patterns. MicroRNAs (miRNAs) modulate gene expression through translational repression or mRNA degradation and have been implicated in senescence. We used deep sequencing to carry out a comprehensive survey of miRNA expression and involvement in cell senescence. Informatic analysis of small RNA sequence datasets from young and senescent IMR90 human fibroblasts identifies many miRNAs that are regulated (either up or down) with cell senescence. Comparison with mRNA expression profiles reveals potential mRNA targets of these senescence-regulated miRNAs. The target mRNAs are enriched for genes involved in biological processes associated with cell senescence. This result greatly extends existing information on the role of miRNAs in cell senescence and is consistent with miRNAs having a causal role in the process.     

Clustered miRNAs and their role in biological functions and diseases

MicroRNAs (miRNAs) are endogenous, small non‐coding RNAs known to regulate expression of protein‐coding genes. A large proportion of miRNAs are highly conserved, localized as clusters in the genome, transcribed together from physically adjacent miRNAs and show similar expression profiles. Since a single miRNA can target multiple genes and miRNA clusters contain multiple miRNAs, it is important to understand their regulation, effects and various biological functions. Like protein‐coding genes, miRNA clusters are also regulated by genetic and epigenetic events. These clusters can potentially regulate every aspect of cellular function including growth, proliferation, differentiation, development, metabolism, infection, immunity, cell death, organellar biogenesis, messenger signalling, DNA repair and self‐renewal, among others. Dysregulation of miRNA clusters leading to altered biological functions is key to the pathogenesis of many diseases including carcinogenesis. Here, we review recent advances in miRNA cluster research and discuss their regulation and biological functions in pathological conditions.     

Computational identification of novel family members of microRNA genes in Arabidopsis thaliana and Oryza sativa

MicroRNAs (miRNAs) are a class of endogenous small RNAs that play important regulatory roles in both animals and plants, miRNA genes have been intensively studied in animals, but not in plants. In this study, we adopted a homology search approach to identify homologs of previously validated plant miRNAs in Arabidopsis thaliana and Oryza sativa. We identified 20 potential miRNA genes in Arabidopsis and 40 in O. sativa, providing a relatively complete enumeration of family members for these miRNAs in plants. In addition, a greater number of Arabidopsis miRNAs (MIR168, MIR159 and MIR172) were found to be conserved in rice. With the novel homologs, most of the miRNAs have closely related fellow miRNAs and the number of paralogs varies in the different miRNA families. Moreover, a probable functional segment highly conserved on the elongated stem of pre-miRNA fold-backs of MIR319 and MIR159 family was identified. These results support a model of variegated miRNA regulation in plants, in which miRNAs with different functional elements on their pre-miRNA fold-backs can differ in their function or regulation, and closely related miRNAs can be diverse in their specificity or competence to downregulate target genes. It appears that the sophisticated regulation of miRNAs can achieve complex biological effects through qualitative and quantitative modulation of gene expression profiles in plants.     

Genome-wide analysis of aberrantly expressed circulating miRNAs in patients with coal workers’ pneumoconiosis

Emerging evidence indicates that microRNAs (miRNAs), a class of small non-coding regulatory RNAs, have important roles in multiple biological processes. To determine the potential contribution of miRNAs to coal workers’ pneumoconiosis (CWP), we comprehensively surveyed and identified differentially expressed miRNA profiles in patients with CWP by small RNA sequencing and analysis. Mixed serum samples from the different stages of CWP and the control samples were subjected to deep sequencing by applying next-generation sequencing technology. Samples at different disease stages exhibited inconsistent miRNA expression profiles and differentially expressed miRNA profiles. Generally, these miRNAs were dynamically expressed across the different disease stages and showed various relative expression levels. Some miRNAs (such as miR-18a*, 149, 222 and 671-3p) were consistently up-regulated or down-regulated in the different stages of CWP samples. Most of the aberrantly expressed miRNAs showed a down-regulation trend. Differentially expressed miRNAs were also subjected to pairwise comparison between the different stages. Some miRNAs showed significant inconsistent expression trends across the three stages, although they were not significantly dysregulated based on the control sample. Furthermore, a series of special miRNAs organized into miRNA gene clusters and gene families were also surveyed for aberrant expression (such as mir-200 gene family and mir-222 gene cluster). According to experimentally validated target mRNAs of the aberrantly and abundantly expressed miRNAs, functional enrichment analysis suggests that these miRNAs play important roles in various biological processes, including lung tumorigenesis. In summary, we demonstrated that aberrantly expressed circulating miRNAs showed dynamic expression patterns across diseased samples, which suggests that these miRNAs may have critical roles in the occurrence and development of CWP. In addition, some significantly dysregulated miRNAs may be potential non-invasive diagnosis biomarkers based on further study.     

Genome-wide screen for aberrantly expressed miRNAs reveals miRNA profile signature in breast cancer

Dysregulation in the expression of miRNAs contributes to the occurrence and development of many human cancers. We herein attempted to obtain the potential association between miRNA expression profile and breast cancer by applying high-throughput sequencing technology. Small RNAs from seven paired tumor and adjacent normal tissue samples were sequenced. To determine the miRNA expression profiles in tissues and sera, another five equally pooled serum samples from 20 patients and 30 normal women were sequenced. Despite a similar number in abundantly expressed miRNAs across samples, we detected varying miRNA expression profiles. Some miRNAs showed inconsistent or opposite dysregulation trends across different tumor tissues, including some abundantly expressed miRNA gene clusters and gene families. Wilcoxon sign-rank test for paired samples analysis revealed that abnormal miRNAs showed a higher level of variation across the seven tumor samples. We also completely surveyed abnormal miRNAs expressed in tumor and serum tissues in the mixed datasets based on the relative expression levels. Most of these miRNAs were significantly down-regulated in tumor samples, but nine abnormal miRNAs (miR-18a, 19a, 20a, 30a, 103b, 126, 126*, 192, 1287) were consistently expressed in tumor tissues and serum samples. Based on experimentally validated target mRNAs, functional enrichment analysis indicated that these abnormal miRNAs and miRNA groups (miRNA gene clusters and gene families) have important roles in multiple biological processes. Dynamic miRNA expression profiles, various abnormal miRNA profiles and complexity of the miRNA regulatory network reveal that the miRNA expression profile is a potential biomarker for classifying or detecting human disease.     

Missing value imputation for microRNA expression data by using a GO-based similarity measure

Missing values are commonly present in microarray data profiles. Instead of discarding genes or samples with incomplete expression level, missing values need to be properly imputed for accurate data analysis. The imputation methods can be roughly categorized as expression level-based and domain knowledge-based. The first type of methods only rely on expression data without the help of external data sources, while the second type incorporates available domain knowledge into expression data to improve imputation accuracy. In recent years, microRNA (miRNA) microarray has been largely developed and used for identifying miRNA biomarkers in complex human disease studies. Similar to mRNA profiles, miRNA expression profiles with missing values can be treated with the existing imputation methods. However, the domain knowledge-based methods are hard to be applied due to the lack of direct functional annotation for miRNAs. With the rapid accumulation of miRNA microarray data, it is increasingly needed to develop domain knowledge-based imputation algorithms specific to miRNA expression profiles to improve the quality of miRNA data analysis. We connect miRNAs with domain knowledge of Gene Ontology (GO) via their target genes, and define miRNA functional similarity based on the semantic similarity of GO terms in GO graphs. A new measure combining miRNA functional similarity and expression similarity is used in the imputation of missing values. The new measure is tested on two miRNA microarray datasets from breast cancer research and achieves improved performance compared with the expression-based method on both datasets. The experimental results demonstrate that the biological domain knowledge can benefit the estimation of missing values in miRNA profiles as well as mRNA profiles. Especially, functional similarity defined by GO terms annotated for the target genes of miRNAs can be useful complementary information for the expression-based method to improve the imputation accuracy of miRNA array data. Our method and data are available to the public upon request.