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Nikolaus Rajewsky

Publications and source records attributed to Nikolaus Rajewsky.

At least 19 recordsLinked to original sources
PubMed2007

The evolution of gene regulation by transcription factors and microRNAs.

Changes in the patterns of gene expression are widely believed to underlie many of the phenotypic differences within and between species. Although much emphasis has been placed on changes in transcriptional regulation, gene expression is regulated at many levels, all of which must ultimately be studied together to obtain a complete picture of the evolution of gene expression. Here we compare the evolution of transcriptional regulation and post-transcriptional regulation that is mediated by microRNAs, a large class of small, non-coding RNAs in plants and animals, focusing on the evolution of the individual regulators and their binding sites. As an initial step towards integrating these mechanisms into a unified framework, we propose a simple model that describes the transcriptional regulation of new microRNA genes.

Computational Biology↗
PubMed2006

Natural selection on human microRNA binding sites inferred from SNP data.

A fundamental problem in biology is understanding how natural selection has shaped the evolution of gene regulation. Here we use SNP genotype data and techniques from population genetics to study an entire layer of short, cis-regulatory sites in the human genome. MicroRNAs (miRNAs) are a class of small noncoding RNAs that post-transcriptionally repress mRNA through cis-regulatory sites in 3' UTRs. We show that negative selection in humans is stronger on computationally predicted conserved miRNA binding sites than on other conserved sequence motifs in 3' UTRs, thus providing independent support for the target prediction model and explicitly demonstrating the contribution of miRNAs to darwinian fitness. Our techniques extend to nonconserved miRNA binding sites, and we estimate that 30%-50% of these are functional when the mRNA and miRNA are endogenously coexpressed. As we show that polymorphisms in predicted miRNA binding sites are likely to be deleterious, they are candidates for causal variants of human disease. We believe that our approach can be extended to studying other classes of cis-regulatory sites.

3' Untranslated Regions↗
PubMed2006

Cell-type-specific signatures of microRNAs on target mRNA expression.

Although it is known that the human genome contains hundreds of microRNA (miRNA) genes and that each miRNA can regulate a large number of mRNA targets, the overall effect of miRNAs on mRNA tissue profiles has not been systematically elucidated. Here, we show that predicted human mRNA targets of several highly tissue-specific miRNAs are typically expressed in the same tissue as the miRNA but at significantly lower levels than in tissues where the miRNA is not present. Conversely, highly expressed genes are often enriched in mRNAs that do not have the recognition motifs for the miRNAs expressed in these tissues. Together, our data support the hypothesis that miRNA expression broadly contributes to tissue specificity of mRNA expression in many human tissues. Based on these insights, we apply a computational tool to directly correlate 3' UTR motifs with changes in mRNA levels upon miRNA overexpression or knockdown. We show that this tool can identify functionally important 3' UTR motifs without cross-species comparison.

3' Untranslated Regions↗
PubMed2006

A genome-wide map of conserved microRNA targets in C. elegans.

BACKGROUND: Metazoan miRNAs regulate protein-coding genes by binding the 3' UTR of cognate mRNAs. Identifying targets for the 115 known C. elegans miRNAs is essential for understanding their function. RESULTS: By using a new version of PicTar and sequence alignments of three nematodes, we predict that miRNAs regulate at least 10% of C. elegans genes through conserved interactions. We have developed a new experimental pipeline to assay 3' UTR-mediated posttranscriptional gene regulation via an endogenous reporter expression system amenable to high-throughput cloning, demonstrating the utility of this system using one of the most intensely studied miRNAs, let-7. Our expression analyses uncover several new potential let-7 targets and suggest a new let-7 activity in head muscle and neurons. To explore genome-wide trends in miRNA function, we analyzed functional categories of predicted target genes, finding that one-third of C. elegans miRNAs target gene sets are enriched for specific functional annotations. We have also integrated miRNA target predictions with other functional genomic data from C. elegans. CONCLUSIONS: At least 10% of C. elegans genes are predicted miRNA targets, and a number of nematode miRNAs seem to regulate biological processes by targeting functionally related genes. We have also developed and successfully utilized an in vivo system for testing miRNA target predictions in likely endogenous expression domains. The thousands of genome-wide miRNA target predictions for nematodes, humans, and flies are available from the PicTar website and are linked to an accessible graphical network-browsing tool allowing exploration of miRNA target predictions in the context of various functional genomic data resources.

Animals↗
PubMed2006

microRNA target predictions in animals.

In recent years, microRNAs (miRNAs) have emerged as a major class of regulatory genes, present in most metazoans and important for a diverse range of biological functions. Because experimental identification of miRNA targets is difficult, there has been an explosion of computational target predictions. Although the initial round of predictions resulted in very diverse results, subsequent computational and experimental analyses suggested that at least a certain class of conserved miRNA targets can be confidently predicted and that this class of targets is large, covering, for example, at least 30% of all human genes when considering about 60 conserved vertebrate miRNA gene families. Most recent approaches have also shown that there are correlations between domains of miRNA expression and mRNA levels of their targets. Our understanding of miRNA function is still extremely limited, but it may be that by integrating mRNA and miRNA sequence and expression data with other comparative genomic data, we will be able to gain global and yet specific insights into the function and evolution of a broad layer of post-transcriptional control.

Algorithms↗
PubMed2005

Silencing of microRNAs in vivo with 'antagomirs'.

MicroRNAs (miRNAs) are an abundant class of non-coding RNAs that are believed to be important in many biological processes through regulation of gene expression. The precise molecular function of miRNAs in mammals is largely unknown and a better understanding will require loss-of-function studies in vivo. Here we show that a novel class of chemically engineered oligonucleotides, termed 'antagomirs', are efficient and specific silencers of endogenous miRNAs in mice. Intravenous administration of antagomirs against miR-16, miR-122, miR-192 and miR-194 resulted in a marked reduction of corresponding miRNA levels in liver, lung, kidney, heart, intestine, fat, skin, bone marrow, muscle, ovaries and adrenals. The silencing of endogenous miRNAs by this novel method is specific, efficient and long-lasting. The biological significance of silencing miRNAs with the use of antagomirs was studied for miR-122, an abundant liver-specific miRNA. Gene expression and bioinformatic analysis of messenger RNA from antagomir-treated animals revealed that the 3' untranslated regions of upregulated genes are strongly enriched in miR-122 recognition motifs, whereas downregulated genes are depleted in these motifs. Analysis of the functional annotation of downregulated genes specifically predicted that cholesterol biosynthesis genes would be affected by miR-122, and plasma cholesterol measurements showed reduced levels in antagomir-122-treated mice. Our findings show that antagomirs are powerful tools to silence specific miRNAs in vivo and may represent a therapeutic strategy for silencing miRNAs in disease.

3' Untranslated Regions↗
PubMed2005

MicroRNA profiling of the murine hematopoietic system.

BACKGROUND: MicroRNAs (miRNAs) are a class of recently discovered noncoding RNA genes that post-transcriptionally regulate gene expression. It is becoming clear that miRNAs play an important role in the regulation of gene expression during development. However, in mammals, expression data are principally based on whole tissue analysis and are still very incomplete. RESULTS: We used oligonucleotide arrays to analyze miRNA expression in the murine hematopoietic system. Complementary oligonucleotides capable of hybridizing to 181 miRNAs were immobilized on a membrane and probed with radiolabeled RNA derived from low molecular weight fractions of total RNA from several different hematopoietic and neuronal cells. This method allowed us to analyze cell type-specific patterns of miRNA expression and to identify miRNAs that might be important for cell lineage specification and/or cell effector functions. CONCLUSION: This is the first report of systematic miRNA gene profiling in cells of the hematopoietic system. As expected, miRNA expression patterns were very different between hematopoietic and non-hematopoietic cells, with further subtle differences observed within the hematopoietic group. Interestingly, the most pronounced similarities were observed among fully differentiated effector cells (Th1 and Th2 lymphocytes and mast cells) and precursors at comparable stages of differentiation (double negative thymocytes and pro-B cells), suggesting that in addition to regulating the process of commitment to particular cellular lineages, miRNAs might have an important general role in the mechanism of cell differentiation and maintenance of cell identity.

Animals↗
PubMed2005

microRNA target predictions across seven Drosophila species and comparison to mammalian targets.

microRNAs are small noncoding genes that regulate the protein production of genes by binding to partially complementary sites in the mRNAs of targeted genes. Here, using our algorithm PicTar, we exploit cross-species comparisons to predict, on average, 54 targeted genes per microRNA above noise in Drosophila melanogaster. Analysis of the functional annotation of target genes furthermore suggests specific biological functions for many microRNAs. We also predict combinatorial targets for clustered microRNAs and find that some clustered microRNAs are likely to coordinately regulate target genes. Furthermore, we compare microRNA regulation between insects and vertebrates. We find that the widespread extent of gene regulation by microRNAs is comparable between flies and mammals but that certain microRNAs may function in clade-specific modes of gene regulation. One of these microRNAs (miR-210) is predicted to contribute to the regulation of fly oogenesis. We also list specific regulatory relationships that appear to be conserved between flies and mammals. Our findings provide the most extensive microRNA target predictions in Drosophila to date, suggest specific functional roles for most microRNAs, indicate the existence of coordinate gene regulation executed by clustered microRNAs, and shed light on the evolution of microRNA function across large evolutionary distances. All predictions are freely accessible at our searchable Web site http://pictar.bio.nyu.edu.

Journal Article↗
PubMed2005

Combinatorial microRNA target predictions.

MicroRNAs are small noncoding RNAs that recognize and bind to partially complementary sites in the 3' untranslated regions of target genes in animals and, by unknown mechanisms, regulate protein production of the target transcript. Different combinations of microRNAs are expressed in different cell types and may coordinately regulate cell-specific target genes. Here, we present PicTar, a computational method for identifying common targets of microRNAs. Statistical tests using genome-wide alignments of eight vertebrate genomes, PicTar's ability to specifically recover published microRNA targets, and experimental validation of seven predicted targets suggest that PicTar has an excellent success rate in predicting targets for single microRNAs and for combinations of microRNAs. We find that vertebrate microRNAs target, on average, roughly 200 transcripts each. Furthermore, our results suggest widespread coordinate control executed by microRNAs. In particular, we experimentally validate common regulation of Mtpn by miR-375, miR-124 and let-7b and thus provide evidence for coordinate microRNA control in mammals.

Algorithms↗
PubMed2004

A pancreatic islet-specific microRNA regulates insulin secretion.

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.

Animals↗
PubMed2004

Transcriptional control in the segmentation gene network of Drosophila.

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.

Algorithms↗
PubMed2004

Survival of resting mature B lymphocytes depends on BCR signaling via the Igalpha/beta heterodimer.

We previously showed that type I interferon-induced, Cre-mediated ablation of surface BCR expression in mature B cells through Ig-heavy chain deletion results in apoptosis of these cells. This led to the hypothesis that survival signals from the BCR are vital for mature B cells. Here, we test two critical assumptions of this model. First, we demonstrate loss of mature B cells upon induced mutation of a signaling module of the BCR, not precluding BCR surface expression. Second, we show that the cells are also lost upon BCR inactivation in the absence of an exogenous inducer like interferon, excluding that cell death depends on previous cellular activation by the latter. Kinetic data demonstrate that BCR-less mature B cells have a severely reduced lifespan, with a half-life of 3-6 days. Together these results establish that BCR signaling is required to keep resting mature B cells alive in vivo.

Animals↗
PubMed2004

Computational identification of microRNA targets.

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 3'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.

Algorithms↗
PubMed2004

A cis element in the recombination activating gene locus regulates gene expression by counteracting a distant silencer.

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.

Animals↗
PubMed2003

Conservation of regulatory elements between two species of Drosophila.

BACKGROUND: One of the important goals in the post-genomic era is to determine the regulatory elements within the non-coding DNA of a given organism's genome. The identification of functional cis-regulatory modules has proven difficult since the component factor binding sites are small and the rules governing their arrangement are poorly understood. However, the genomes of suitably diverged species help to predict regulatory elements based on the generally accepted assumption that conserved blocks of genomic sequence are likely to be functional. To judge the efficacy of strategies that prefilter by sequence conservation it is important to know to what extent the converse assumption holds, namely that functional elements common to both species will fall within these conserved blocks. The recently completed sequence of a second Drosophila species provides an opportunity to test this assumption for one of the experimentally best studied regulatory networks in multicellular organisms, the body patterning of the fly embryo. RESULTS: We find that 50%-70% of known binding sites reside in conserved sequence blocks, but these percentages are not greatly enriched over what is expected by chance. Finally, a computational genome-wide search in both species for regulatory modules based on clusters of binding sites suggests that genes central to the regulatory network are consistently recovered. CONCLUSIONS: Our results indicate that binding sites remain clustered for these "core modules" while not necessarily residing in conserved blocks. This is an important clue as to how regulatory information is encoded in the genome and how modules evolve.

Algorithms↗
PubMed2003

Decay rates of human mRNAs: correlation with functional characteristics and sequence attributes.

Although mRNA decay rates are a key determinant of the steady-state concentration for any given mRNA species, relatively little is known, on a population level, about what factors influence turnover rates and how these rates are integrated into cellular decisions. We decided to measure mRNA decay rates in two human cell lines with high-density oligonucleotide arrays that enable the measurement of decay rates simultaneously for thousands of mRNA species. Using existing annotation and the Gene Ontology hierarchy of biological processes, we assign mRNAs to functional classes at various levels of resolution and compare the decay rate statistics between these classes. The results show statistically significant organizational principles in the variation of decay rates among functional classes. In particular, transcription factor mRNAs have increased average decay rates compared with other transcripts and are enriched in "fast-decaying" mRNAs with half-lives <2 h. In contrast, we find that mRNAs for biosynthetic proteins have decreased average decay rates and are deficient in fast-decaying mRNAs. Our analysis of data from a previously published study of Saccharomyces cerevisiae mRNA decay shows the same functional organization of decay rates, implying that it is a general organizational scheme for eukaryotes. Additionally, we investigated the dependence of decay rates on sequence composition, that is, the presence or absence of short mRNA motifs in various regions of the mRNA transcript. Our analysis recovers the positive correlation of mRNA decay with known AU-rich mRNA motifs, but we also uncover further short mRNA motifs that show statistically significant correlation with decay. However, we also note that none of these motifs are strong predictors of mRNA decay rate, indicating that the regulation of mRNA decay is more complex and may involve the cooperative binding of several RNA-binding proteins at different sites.

Base Composition↗
PubMed2003

SMASHing regulatory sites in DNA by human-mouse sequence comparisons.

Regulatory sequence elements provide important clues to understanding and predicting gene expression. Although the binding sites for hundreds of transcription factors are known, there has been no systematic attempt to incorporate this information in the annotation of the human genome. Cross species sequence comparisons are critical to a meaningful annotation of regulatory elements since they generally reside in conserved non-coding regions. To take advantage of the recently completed drafts of the mouse and human genomes for annotating transcription factor binding sites, we developed SMASH, a computational pipeline that identifies thousands of orthologous human/ mouse proteins, maps them to genomic sequences, extracts and compares upstream regions and annotates putative regulatory elements in conserved, non-coding, upstream regions. Our current dataset consists of approximately 2,500 human/mouse gene pairs. Transcription start sites were estimated by mapping quasi-full length cDNA sequences. SMASH uses a novel probabilistic method to identify putative conserved binding sites that takes into account the competition between transcription factors for binding DNA. SMASH presents the results via a genome browser web interface which displays the predicted regulatory information together with the current annotations for the human genome. Our results are validated by comparison to previously published experimental data. SMASH results compare favorably to other existing computational approaches.

Algorithms↗