Recognition sites for microRNAs (miRNAs) have been reported to be located in the 3 untranslated regions of transcripts. In a computational screen for highly conserved motifs within coding regions, we found an excess of sequences conserved at the nucleotide level within coding regions in the human genome, the highest scoring of which are enriched for miRNA target sequences. To validate our results, we experimentally demonstrated that the let-7 miRNA directly targets the miRNA-processing enzyme Dicer within its coding sequence, thus establishing a mechanism for a miRNA/Dicer autoregulatory negative feedback loop. We also found computational evidence to suggest that miRNA target sites in coding regions and 3 UTRs may differ in mechanism. This work demonstrates that miRNAs can directly target transcripts within their coding region in animals, and it suggests that a complete search for the regulatory targets of miRNAs should be expanded to include genes with recognition sites within their coding regions. As more genomes are sequenced, the methodological approach that we used for identifying motifs with high sequence conservation will be increasingly valuable for detecting functional sequence motifs within coding regions.computational biology ͉ posttranscriptional regulation ͉ comparative genomics ͉ multiple-sequence alignment ͉ evolutionary conservation M icroRNAs (miRNAs) are endogenously encoded, singlestranded regulatory RNAs that bind to and inhibit the translation of transcripts with complementary sequence (1). Computational evidence suggests that miRNAs regulate at least 20% of human genes and have been implicated in the regulation of a wide range of biological systems (2). In plants, miRNA targets can be predicted with relatively high confidence because of the extensive base pairing between plant miRNAs and their target mRNAs (1). In animals, in contrast, miRNAs typically bind to their targets with significantly less complementarity, and the short target sequences are, therefore, difficult to identify on the basis of sequence alone. As a result, most computational approaches to predict miRNA-target interactions rely on conservation of target sites (3-6).Although early studies reported some evidence for the targeting of miRNAs to sites within protein coding regions (4, 6), subsequent research has reported that there is minimal functionality for sites in ORFs or 5Ј UTRs (7). A focus on miRNAs present within 3Ј UTRs is supported by evidence suggesting that the G-cap/poly(A) tail interface (which connects the two ends of eukaryotic mRNAs during translation) is important for miRNA function (8) and that miRNAs tend to be more effective when localized at the end of the 3Ј UTR rather than the middle (7, 9). Indeed, the protein translation machinery might be expected to displace an miRNA complex present within a gene's coding sequence. However, exogenously added siRNAs that target coding sequences, including siRNAs with imperfect base pairing, are effective at silencing (10). More recent reports have also shown that, c...

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The recent revelation that there are small, noncoding RNAs that regulate the expression of many other genes has led to an exciting, emerging body of literature defining the biological role for these molecules within signaling networks. In a flurry of recent papers, a microRNA polycistron induced by the oncogenic transcription factor c-myc has been found to be involved in an unusually structured network of interactions. This network includes the seemingly paradoxical transcriptional induction and translational inhibition of the same molecule, the E2F1 transcription factor. This microRNA cluster has been implicated in inhibiting proliferation, as well as inhibiting apoptosis, and promoting angiogenesis. Consistent with its seemingly paradoxical functions, the region of the genome in which it is encoded is deleted in some tumors and overexpressed in others. We consider the possibility that members of this polycistronic microRNA cluster help cells to integrate signals from the environment and decide whether a signal should be interpreted as proliferative or apoptotic.

microRNAs play a critically important role in a wide array of biological processes including those implicated in cancer, neurodegenerative and metabolic disorders, and viral infection. Although we have begun to understand microRNA biogenesis and function, experimental demonstration of their functional effects and the molecular mechanisms by which they function remains a challenge. Members of the let-7/miR-98 family play a critical role in cell cycle control with respect to differentiation and tumorigenesis. In this study, we show that exogenous addition of pre-let-7 in primary human fibroblasts results in a decrease in cell number and an increased fraction of cells in the G 2 /M cell cycle phase. Combining microarray techniques with DNA sequence analysis to identify potential let-7 targets, we discovered 838 genes with a let-7 binding site in their 3-untranslated region that were down-regulated upon overexpression of let-7b. Among these genes is cdc34, the ubiquitin-conjugating enzyme of the Skp1/cullin/F-box (SCF) complex. Cdc34 protein levels are strongly down-regulated by let-7 overexpression. Reporter assays demonstrated direct regulation of the cdc34 3-untranslated region by let-7. We hypothesized that low Cdc34 levels would result in decreased SCF activity, stabilization of the SCF target Wee1, and G 2 /M accumulation. Consistent with this hypothesis, small interfering RNA-mediated down-regulation of Wee1 reversed the G 2 /M phenotype induced by let-7 overexpression. We conclude that Cdc34 is a functional target of let-7 and that let-7 induces down-regulation of Cdc34, stabilization of the Wee1 kinase, and an increased fraction of cells in G 2 /M in primary fibroblasts. miRNAs 2 are non-coding, single-stranded, conserved RNAs of ϳ22 nucleotides that function as gene regulators (1). miRNAs have emerged as central post-transcriptional negative regulators and have been implicated in a wide array of biological processes including cell cycle control. In metazoans, individual miRNAs can down-regulate hundreds of mRNA targets by interacting with partially complementary sequences within their 3Ј-untranslated region (3Ј-UTR) (2, 3).The let-7 miRNA was originally discovered in Caenorhabditis elegans as a switch gene induced as cells exit the cell cycle when C. elegans reach their adult stage (4). In humans and mouse, like C. elegans, the expression of let-7 is barely detectable in embryonic developmental stages but increases after differentiation and in mature tissue (5). let-7 family members have been implicated as tumor suppressors. Some of the 12 members of the let-7 family map onto genomic regions altered or deleted in human tumors (6, 7). Further, members of the let-7 family of miRNAs are consistently down-regulated in lung and colon cancer (8 -10). In lung cancers, low levels of let-7 correlated with shorter survival after resection (9). Decreased let-7 levels in tumors are associated with elevated levels of Ras, which contains several let-7 binding sites within its 3Ј-UTR (8). let-7 expression is reduced in m...

Supplementary data are available at Bioinformatics online.

BackgroundAlthough quiescence (reversible cell cycle arrest) is a key part in the life history and fate of many mammalian cell types, the mechanisms of gene regulation in quiescent cells are poorly understood. We sought to clarify the role of microRNAs as regulators of the cellular functions of quiescent human fibroblasts.ResultsUsing microarrays, we discovered that the expression of the majority of profiled microRNAs differed between proliferating and quiescent fibroblasts. Fibroblasts induced into quiescence by contact inhibition or serum starvation had similar microRNA profiles, indicating common changes induced by distinct quiescence signals. By analyzing the gene expression patterns of microRNA target genes with quiescence, we discovered a strong regulatory function for miR-29, which is downregulated with quiescence. Using microarrays and immunoblotting, we confirmed that miR-29 targets genes encoding collagen and other extracellular matrix proteins and that those target genes are induced in quiescence. In addition, overexpression of miR-29 resulted in more rapid cell cycle re-entry from quiescence. We also found that let-7 and miR-125 were upregulated in quiescent cells. Overexpression of either one alone resulted in slower cell cycle re-entry from quiescence, while the combination of both together slowed cell cycle re-entry even further.ConclusionsmicroRNAs regulate key aspects of fibroblast quiescence including the proliferative state of the cells as well as their gene expression profiles, in particular, the induction of extracellular matrix proteins in quiescent fibroblasts.

Accurately and effectively detecting the locations where search queries are truly about has huge potential impact on increasing search relevance. In this paper, we define a search query's dominant location (QDL) and propose a solution to correctly detect it. QDL is geographical location(s) associated with a query in collective human knowledge, i.e., one or few prominent locations agreed by majority of people who know the answer to the query. QDL is a subjective and collective attribute of search queries and we are able to detect QDLs from both queries containing geographical location names and queries not containing them. The key challenges to QDL detection include false positive suppression (not all contained location names in queries mean geographical locations), and detecting implied locations by the context of the query. In our solution, a query is recursively broken into atomic tokens according to its most popular web usage for reducing false positives. If we do not find a dominant location in this step, we mine the top search results and/or query logs (with different approaches discussed in this paper) to discover implicit query locations. Our large-scale experiments on recent MSN Search queries show that our query location detection solution has consistent high accuracy for all query frequency ranges.

Background: Graph theory provides a computational framework for modeling a variety of datasets including those emerging from genomics, proteomics, and chemical genetics. Networks of genes, proteins, small molecules, or other objects of study can be represented as graphs of nodes (vertices) and interactions (edges) that can carry different weights. SpectralNET is a flexible application for analyzing and visualizing these biological and chemical networks.