Showing papers by "Nikolaus Rajewsky published in 2004"
TL;DR: It is shown that overexpression of miR-375 suppressed glucose-induced insulin secretion, and conversely, inhibition of endogenous mi R-375 function enhanced insulin secretion and may constitute a novel pharmacological target for the treatment of diabetes.
Abstract: MicroRNAs (miRNAs) constitute a growing class of non-coding RNAs that are thought to regulate gene expression by translational repression Several miRNAs in animals exhibit tissue-specific or developmental-stage-specific expression, indicating that they could play important roles in many biological processes To study the role of miRNAs in pancreatic endocrine cells we cloned and identified a novel, evolutionarily conserved and islet-specific miRNA (miR-375) Here we show that overexpression of miR-375 suppressed glucose-induced insulin secretion, and conversely, inhibition of endogenous miR-375 function enhanced insulin secretion The mechanism by which secretion is modified by miR-375 is independent of changes in glucose metabolism or intracellular Ca2+-signalling but correlated with a direct effect on insulin exocytosis Myotrophin (Mtpn) was predicted to be and validated as a target of miR-375 Inhibition of Mtpn by small interfering (si)RNA mimicked the effects of miR-375 on glucose-stimulated insulin secretion and exocytosis Thus, miR-375 is a regulator of insulin secretion and may thereby constitute a novel pharmacological target for the treatment of diabetes
2,064 citations
TL;DR: Kinetic data demonstrate that BCR-less mature B cells have a severely reduced lifespan, with a half-life of 3-6 days, and establish that B CR signaling is required to keep resting mature B Cells alive in vivo.
540 citations
TL;DR: It is shown that maternal factors consistently act as activators and that gap factors act as repressors, except for the bimodal factor Hunchback, which suggests a simple context-dependent rule for its switch from repressive to activating function.
Abstract: The segmentation gene network of Drosophila consists of maternal and zygotic factors that generate, by transcriptional (cross-) regulation, expression patterns of increasing complexity along the anterior-posterior axis of the embryo. Using known binding site information for maternal and zygotic gap transcription factors, the computer algorithm Ahab recovers known segmentation control elements (modules) with excellent success and predicts many novel modules within the network and genome-wide. We show that novel module predictions are highly enriched in the network and typically clustered proximal to the promoter, not only upstream, but also in intronic space and downstream. When placed upstream of a reporter gene, they consistently drive patterned blastoderm expression, in most cases faithfully producing one or more pattern elements of the endogenous gene. Moreover, we demonstrate for the entire set of known and newly validated modules that Ahab's prediction of binding sites correlates well with the expression patterns produced by the modules, revealing basic rules governing their composition. Specifically, we show that maternal factors consistently act as activators and that gap factors act as repressors, except for the bimodal factor Hunchback. Our data suggest a simple context-dependent rule for its switch from repressive to activating function. Overall, the composition of modules appears well fitted to the spatiotemporal distribution of their positive and negative input factors. Finally, by comparing Ahab predictions with different categories of transcription factor input, we confirm the global regulatory structure of the segmentation gene network, but find odd skipped behaving like a primary pair-rule gene. The study expands our knowledge of the segmentation gene network by increasing the number of experimentally tested modules by 50%. For the first time, the entire set of validated modules is analyzed for binding site composition under a uniform set of criteria, permitting the definition of basic composition rules. The study demonstrates that computational methods are a powerful complement to experimental approaches in the analysis of transcription networks.
258 citations
TL;DR: This work presents a new computational method that is designed to identify microRNA target sites with high specificity and finds that many key developmental body patterning genes such as hairy and fushi-tarazu are likely to be translationally regulated by microRNAs.
246 citations
TL;DR: A new computational method which is designed to identify microRNA target sites and finds that a number of key developmental body patterning genes such as hairy and fushi-tarazu are likely to be translationally regulated by microRNAs.
Abstract: Recent experiments have shown that the genomes of organisms such as worm, fly, human and mouse encode hundreds of microRNA genes. Many of these microRNAs are thought to regulate the translational expression of other genes by binding to partially complementary sites in messenger RNAs. Phenotypic and expression analysis suggest an important role of microRNAs during development. Therefore, it is of fundamental importance to identify microRNA targets. However, no experimental or computational high-throughput method for target site identification in animals has been published yet. Our main result is a new computational method which is designed to identify microRNA target sites. This method recovers with high specificity known microRNA target sites which previously have been defined experimentally. Based on these results, we present a simple model for the mechanism of microRNA target site recognition. Our model incorporates both kinetic and thermodynamic components of target recognition. When we applied our method to a set of 74 Drosophila melanogaster microRNAs, searching 3' UTR sequences of a predefined set of fly mRNAs for target sites which were evolutionary conserved between Drosophila melanogaster and Drosophila pseudoobscura, we found that a number of key developmental body patterning genes such as hairy and fushi-tarazu are likely to be translationally regulated by microRNAs.
228 citations
TL;DR: It is speculated that the Rag antisilencing element belongs to a class of cis elements that might be useful for genome diversification by activating genes encoded by otherwise silent transposable elements.
Abstract: We have identified a silencer and an antisilencing element that interact at a distance of 85 kilobases to regulate expression of the recombination activating genes Rag1 and Rag2 in thymocytes. Transgenic experiments showed that Rag promoter-proximal cis elements directed tissue-specific expression and that a Runx-dependent intergenic silencer suppressed expression in developing T cells. Deletion of the antisilencing element from the genomic Rag locus unmasked the intergenic silencer and abrogated Rag expression in developing CD4(+)CD8(+) T cells. We speculate that the Rag antisilencing element belongs to a class of cis elements that might be useful for genome diversification by activating genes encoded by otherwise silent transposable elements.
78 citations
01 Jan 2004
TL;DR: This work presents a new computational method that is designed to identify microRNA target sites with high specificity and finds that many key developmental body patterning genes such as hairy and fushi-tarazu are likely to be translationally regulated by microRNAs.
Abstract: Recent experiments have shown that the genomes of organisms such as worm, fly, human, and mouse encode hundreds of microRNA genes. Many of these microRNAs are thought to regulate the translational expression of other genes by binding to partially complementary sites in messenger RNAs. Phenotypic and expression analysis suggests an important role of microRNAs during development. Therefore, it is of fundamental importance to identify microRNA targets. However, no experimental or computational high-throughput method for target site identification in animals has been published yet. Our main result is a new computational method that is designed to identify microRNA target sites. This method recovers with high specificity known microRNA target sites that have previously been defined experimentally. Based on these results, we present a simple model for the mechanism of microRNA target site recognition. Our model incorporates both kinetic and thermodynamic components of target recognition. When we applied our method to a set of 74 Drosophila melanogaster microRNAs, searching 3V UTR sequences of a predefined set of fly mRNAs for target sites which were evolutionary conserved between D. melanogaster and Drosophila pseudoobscura, we found that many key developmental body patterning genes such as hairy and fushi-tarazu are likely to be translationally regulated by microRNAs. D 2003 Elsevier Inc. All rights reserved.