The evolution and functional diversification of animal microRNA genes

microRNAs （miRNAs） are an abundant class of-22 nucleotide （nt） regulatory RNAs that are pervasive in higher eukaryotic genomes. In order to fully understand their prominence in genomes, it is necessary to elucidate the molecular mechanisms that can diversify miRNA activities. In this review, we describe some of the many strategies that allow novel miRNA functions to emerge, with particular emphasis on how miRNA genes evolve in animals. These mechanisms include changes in their sequence, processing, or expression pattern; acquisition of miRNA^＊ functionality or antisense processing; and de novo gene birth. The facility and versatility of miRNAs to evolve and change likely underlies how they have become dominant constituents of higher genomes.     

siRNA, miRNA and HIV： promises and challenges

Small interfering RNA （siRNA） and microRNA （miRNA） are small RNAs of 18-25 nucleotides （nt） in length that play important roles in regulating gene expression. They are incorporated into an RNA-induced silencing complex （RISC） and serve as guides for silencing their corresponding target mRNAs based on complementary base-pairing. The promise of gene silencing has led many researchers to consider siRNA as an anti-viral tool. However, in long-term settings, many viruses appear to escape from this therapeutical strategy. An example of this may be seen in the case of human immunodeficiency virus type-1 （HIV-1） which is able to evade RNA silencing by either mutating the siRNA-targeted sequence or by encoding for a partial suppressor of RNAi （RNA interference）. On the other hand, because miRNA targeting does not require absolute complementarity of base-pairing, mutational escape by viruses from miRNA-specified silencing may be more difficult to achieve. In this review, we discuss stratagems used by various viruses to avoid the cells＇ antiviral si/mi-RNA defenses and notions of how viruses might control and regulate host cell genes by encoding viral miRNAs （vmiRNAs）.     

Mining the 30UTR of Autism-implicated Genes for SNPs Perturbing MicroRNA Regulation

Autism spectrum disorder（ASD） refers to a group of childhood neurodevelopmental disorders with polygenic etiology. The expression of many genes implicated in ASD is tightly regulated by various factors including microRNAs（miRNAs）, a class of noncoding RNAs 22 nucleotides in length that function to suppress translation by pairing with ‘miRNA recognition elements’（MREs） present in the 30untranslated region（30UTR） of target mRNAs. This emphasizes the role played by miRNAs in regulating neurogenesis, brain development and differentiation and hence any perturbations in this regulatory mechanism might affect these processes as well. Recently, single nucleotide polymorphisms（SNPs） present within 30UTRs of mRNAs have been shown to modulate existing MREs or even create new MREs. Therefore, we hypothesized that SNPs perturbing miRNA-mediated gene regulation might lead to aberrant expression of autism-implicated genes, thus resulting in disease predisposition or pathogenesis in at least a subpopulation of ASD individuals. We developed a systematic computational pipeline that integrates data from well-established databases. By following a stringent selection criterion, we identified 9 MRE-modulating SNPs and another 12 MRE-creating SNPs in the 30UTR of autism-implicated genes. These high-confidence candidate SNPs may play roles in ASD and hence would be valuable for further functional validation.     

Genomics of microRNA

Discovered just over a decade ago, microRNA (miRNA) is now recognized as one of the major regulatory gene families in eukaryotic cells. Hundreds of miRNAs have been found in animals, plants and viruses, and there are certainly more to come. Through specific base-pairing with mRNAs, these tiny approximately 22-nt RNAs induce mRNA degradation or translational repression, or both. Because a miRNA can target numerous mRNAs, often in combination with other miRNAs, miRNAs operate highly complex regulatory networks. In this article, we summarize the current status of miRNA gene mining and miRNA expression profiling. We also review up-to-date knowledge of miRNA gene structure and the biogenesis mechanism. Our focus is on animal miRNAs.     

microRNAs - powerful repression comes from small RNAs

microRNAs (miRNAs) encode a novel class of small, non-coding RNAs that regulate gene expression post-trancriptionally. miRNAs comprise one of the major non-coding RNA families, whose diverse biological functions and unusual capacity for gene regulation have attracted enormous interests in the RNA world. Over the past 16 years, genetic, biochemical and computational approaches have greatly shaped the growth of the field, leading to the identification of thousands of miRNA genes in nearly all metazoans. The key molecular machinery for miRNA biogenesis and silencing has been identified, yet the precise biochemical and regulatory mechanisms still remain elusive. However, recent findings have shed new light on how miRNAs are generated and how they function to repress gene expression. miRNAs provide a paradigm for endogenous small RNAs that mediate gene silencing at a genome-wide level. The gene silencing mediated by these small RNAs constitutes a major component of gene regulation during various developmental and physiological processes. The accumulating knowledge about their biogenesis and gene silencing mechanism will add a new dimension to our understanding about the complex gene regulatory networks.     

Identifying functional miRNA-mRNA regulatory modules with correspondence latent dirichlet allocation

MOTIVATION: MicroRNAs (miRNAs) are small non-coding RNAs that cause mRNA degradation and translational inhibition. They are important regulators of development and cellular homeostasis through their control of diverse processes. Recently, great efforts have been made to elucidate their regulatory mechanism, but the functions of most miRNAs and their precise regulatory mechanisms remain elusive. With more and more matched expression profiles of miRNAs and mRNAs having been made available, it is of great interest to utilize both expression profiles to discover the functional regulatory networks of miRNAs and their target mRNAs for potential biological processes that they may participate in. RESULTS: We present a probabilistic graphical model to discover functional miRNA regulatory modules at potential biological levels by integrating heterogeneous datasets, including expression profiles of miRNAs and mRNAs, with or without the prior target binding information. We applied this model to a mouse mammary dataset. It effectively captured several biological process specific modules involving miRNAs and their target mRNAs. Furthermore, without using prior target binding information, the identified miRNAs and mRNAs in each module show a large proportion of overlap with predicted miRNA target relationships, suggesting that expression profiles are crucial for both target identification and discovery of regulatory modules.