CiteULike: bootsy's library [304 articles]

Metagenomics reveals our incomplete knowledge of global diversity.

Miguel Pignatelli — 2008-07-18T07:57:13-00:00

Bioinformatics (Oxford, England) (13 July 2008)

Mouse let-7 miRNA populations exhibit RNA editing that is constrained in the 5'-seed/cleavage/anchor regions and stabilize predicted mmu-let-7a:mRNA duplexes

Jeffrey Reid — 2008-07-14T07:04:36-00:00

Genome Res. (9 July 2008), gr.078246.108.

Massively parallel sequencing of millions of <30 nt RNAs expressed in mouse ovary, embryonic pancreas (E14.5) and insulin-secreting beta-cells (TC-3) reveals that ~50% of the mature miRNAs representing mostly the mmu-let-7 family display internal insertion/deletions and substitutions when compared to precursor miRNA and the mouse genome reference sequences. Approximately, 12-20% of species associated with mmu-let-7 populations exhibits sequence discrepancies that are dramatically reduced in nucleotides 3-7 (5'-seed) and 10-15 (cleavage and anchor sites). This observation is inconsistent with sequencing error and leads us to propose that the changes arise predominantly from post-transcriptional RNA editing activity operating on miRNA:target mRNA complexes. Internal nucleotide modifications are most enriched at the 9th nucleotide position. A common 9th base edit of U-to-G results in a significant increase in stability of down regulated let-7a targets in inhibin knockout mutants (Inha-/-). An excess of U-insertions (14.8%) over U-deletions (1.5%) and the presence of cleaved intermediates suggests that a mammalian TUTase (terminal uridylyl transferase) mediated dUTP-dependent U-insertion/U-deletion cycle maybe a possible mechanism. We speculate that mRNA target site-directed editing of mmu-let-7a duplex-bulges stabilizes 'loose' miRNA:mRNA target associations and functions to expand the target repertoire and/or enhance mRNA decay over translational repression. Our results also demonstrate that the systematic study of sequence variation within specific RNA classes in a given cell type from millions of sequences generated by next generation sequencing (NGS) technologies ('intranomics') can be used broadly to infer functional constraints on specific parts of completely uncharacterized RNAs. 10.1101/gr.078246.108

Seeking a New Biology through Text Mining

Andrey Rzhetsky — 2008-07-11T13:26:03-00:00

Cell, Vol. 134, No. 1. (11 July 2008), pp. 9-13.

Tens of thousands of biomedical journals exist, and the deluge of new articles in the biomedical sciences is leading to information overload. Hence, there is much interest in text mining, the use of computational tools to enhance the human ability to parse and understand complex text.

Evolution of Evolvability in Gene Regulatory Networks

Anton Crombach — 2008-07-11T23:04:19-00:00

PLoS Comput Biol, Vol. 4, No. 7. (11 July 2008), e1000112.

Gene regulatory networks are perhaps the most important organizational level in the cell where signals from the cell state and the outside environment are integrated in terms of activation and inhibition of genes. For the last decade, the study of such networks has been fueled by large-scale experiments and renewed attention from the theoretical field. Different models have been proposed to, for instance, investigate expression dynamics, explain the network topology we observe in bacteria and yeast, and for the analysis of evolvability and robustness of such networks. Yet how these gene regulatory networks evolve and become evolvable remains an open question. An individual-oriented evolutionary model is used to shed light on this matter. Each individual has a genome from which its gene regulatory network is derived. Mutations, such as gene duplications and deletions, alter the genome, while the resulting network determines the gene expression pattern and hence fitness. With this protocol we let a population of individuals evolve under Darwinian selection in an environment that changes through time. Our work demonstrates that long-term evolution of complex gene regulatory networks in a changing environment can lead to a striking increase in the efficiency of generating beneficial mutations. We show that the population evolves towards genotype-phenotype mappings that allow for an orchestrated network-wide change in the gene expression pattern, requiring only a few specific gene indels. The genes involved are hubs of the networks, or directly influencing the hubs. Moreover, throughout the evolutionary trajectory the networks maintain their mutational robustness. In other words, evolution in an alternating environment leads to a network that is sensitive to a small class of beneficial mutations, while the majority of mutations remain neutral: an example of evolution of evolvability.

Synchronous vs. Asynchronous Modeling of Gene Regulatory Networks.

Abhishek Garg — 2008-07-14T07:04:17-00:00

Bioinformatics (Oxford, England) (9 July 2008)

MOTIVATION: In silico modeling of gene regulatory networks has gained some momentum recently due to increased interest in analyzing the dynamics of biological systems. This has been further facilitated by the increasing availability of experimental data on gene-gene, protein-protein and gene-protein interactions. The two dynamical properties that are often experimentally testable are perturbations and stable steady states. Although a lot of work has been done on the identification of steady states, not much work has been reported on in silico modeling of cellular differentiation processes. RESULTS: In this manuscript, we provide algorithms based on Reduced Ordered Binary Decision Diagrams (ROBDDs) for Boolean modeling of gene regulatory networks. Algorithms for Synchronous and Asynchronous transition models have been proposed and their corresponding computational properties have been analysed. These algorithms allow users to compute cyclic attractors of large networks that are currently not feasible using existing software. Hereby we provide a framework to analyze the effect of multiple gene perturbation protocols, and their effect on cell differentiation processes. These algorithms were validated on the T-helper model showing the correct steady state identification and Th1-Th2 cellular differentiation process. AVAILABILITY: The software binaries for Windows and Linux platforms can be downloaded from http://si2.epfl.ch/~garg/genysis.html. CONTACT: abhishek.garg@epfl.ch.

MicroRNA regulation and the variability of human cortical gene expression.

Rui Zhang — 2008-07-14T07:01:14-00:00

Nucleic acids research (10 July 2008)

Understanding the driving forces of gene expression variation within human populations will provide important insights into the molecular basis of human phenotypic variation. In the genome, the gene expression variability differs among genes, and at present, most research has focused on identifying the genetic variants responsible for the within population gene expression variation. However, little is known about whether microRNAs (miRNAs), which are small noncoding RNAs modulating expression of their target genes, could have impact on the variability of gene expression. Here we demonstrate that miRNAs likely lead to the difference of expression variability among genes. With the use of the genome-wide expression data in 193 human brain samples, we show that the increased variability of gene expression is concomitant with the increased number of the miRNA seeds interacting with the target genes, suggesting a direct influence of miRNA on gene expression variability. Compared with the non-miRNA-target genes, genes targeted by more than two miRNA seeds have increased expression variability, independent of the miRNA types. In addition, single-nucleotide polymorphisms (SNPs) located in the miRNA binding sites could further increase the gene expression variability of the target genes. We propose that miRNAs are one of the driving forces causing expression variability in the human genome.

Defining diversity, specialization, and gene specificity in transcriptomes through information theory.

Octavio Martínez — 2008-07-10T07:33:43-00:00

Proceedings of the National Academy of Sciences of the United States of America (7 July 2008)

The transcriptome is a set of genes transcribed in a given tissue under specific conditions and can be characterized by a list of genes with their corresponding frequencies of transcription. Transcriptome changes can be measured by counting gene tags from mRNA libraries or by measuring light signals in DNA microarrays. In any case, it is difficult to completely comprehend the global changes that occur in the transcriptome, given that thousands of gene expression measurements are involved. We propose an approach to define and estimate the diversity and specialization of transcriptomes and gene specificity. We define transcriptome diversity as the Shannon entropy of its frequency distribution. Gene specificity is defined as the mutual information between the tissues and the corresponding transcript, allowing detection of either housekeeping or highly specific genes and clarifying the meaning of these concepts in the literature. Tissue specialization is measured by average gene specificity. We introduce the formulae using a simple example and show their application in two datasets of gene expression in human tissues. Visualization of the positions of transcriptomes in a system of diversity and specialization coordinates makes it possible to understand at a glance their interrelations, summarizing in a powerful way which transcriptomes are richer in diversity of expressed genes, or which are relatively more specialized. The framework presented enlightens the relation among transcriptomes, allowing a better understanding of their changes through the development of the organism or in response to environmental stimuli.

Gene network dynamics controlling keratinocyte migration

Hauke Busch — 2008-07-06T06:47:46-00:00

Mol Syst Biol, Vol. 4 (1 July 2008)

Identifying functional modules in protein-protein interaction networks: an integrated exact approach.

MT Dittrich — 2008-07-02T02:39:29-00:00

Bioinformatics (Oxford, England), Vol. 24, No. 13. (1 July 2008)

MOTIVATION: With the exponential growth of expression and protein-protein interaction (PPI) data, the frontier of research in systems biology shifts more and more to the integrated analysis of these large datasets. Of particular interest is the identification of functional modules in PPI networks, sharing common cellular function beyond the scope of classical pathways, by means of detecting differentially expressed regions in PPI networks. This requires on the one hand an adequate scoring of the nodes in the network to be identified and on the other hand the availability of an effective algorithm to find the maximally scoring network regions. Various heuristic approaches have been proposed in the literature. RESULTS: Here we present the first exact solution for this problem, which is based on integer-linear programming and its connection to the well-known prize-collecting Steiner tree problem from Operations Research. Despite the NP-hardness of the underlying combinatorial problem, our method typically computes provably optimal subnetworks in large PPI networks in a few minutes. An essential ingredient of our approach is a scoring function defined on network nodes. We propose a new additive score with two desirable properties: (i) it is scalable by a statistically interpretable parameter and (ii) it allows a smooth integration of data from various sources. We apply our method to a well-established lymphoma microarray dataset in combination with associated survival data and the large interaction network of HPRD to identify functional modules by computing optimal-scoring subnetworks. In particular, we find a functional interaction module associated with proliferation over-expressed in the aggressive ABC subtype as well as modules derived from non-malignant by-stander cells. AVAILABILITY: Our software is available freely for non-commercial purposes at http://www.planet-lisa.net.

MicroRNA prediction with a novel ranking algorithm based on random walks.

Y Xu — 2008-07-06T06:35:37-00:00

Bioinformatics (Oxford, England), Vol. 24, No. 13. (1 July 2008)

MicroRNA (miRNAs) play essential roles in post-transcriptional gene regulation in animals and plants. Several existing computational approaches have been developed to complement experimental methods in discovery of miRNAs that express restrictively in specific environmental conditions or cell types. These computational methods require a sufficient number of characterized miRNAs as training samples, and rely on genome annotation to reduce the number of predicted putative miRNAs. However, most sequenced genomes have not been well annotated and many of them have a very few experimentally characterized miRNAs. As a result, the existing methods are not effective or even feasible for identifying miRNAs in these genomes. Aiming at identifying miRNAs from genomes with a few known miRNA and/or little annotation, we propose and develop a novel miRNA prediction method, miRank, based on our new random walks- based ranking algorithm. We first tested our method on Homo sapiens genome; using a very few known human miRNAs as samples, our method achieved a prediction accuracy greater than 95%. We then applied our method to predict 200 miRNAs in Anopheles gambiae, which is the most important vector of malaria in Africa. Our further study showed that 78 out of the 200 putative miRNA precursors encode mature miRNAs that are conserved in at least one other animal species. These conserved putative miRNAs are good candidates for further experimental study to understand malaria infection. AVAILABILITY: MiRank is programmed in Matlab on Windows platform. The source code is available upon request.

A max-margin model for efficient simultaneous alignment and folding of RNA sequences.

CB Do — 2008-07-06T06:33:22-00:00

Bioinformatics (Oxford, England), Vol. 24, No. 13. (1 July 2008)

MOTIVATION: The need for accurate and efficient tools for computational RNA structure analysis has become increasingly apparent over the last several years: RNA folding algorithms underlie numerous applications in bioinformatics, ranging from microarray probe selection to de novo non-coding RNA gene prediction. In this work, we present RAF (RNA Alignment and Folding), an efficient algorithm for simultaneous alignment and consensus folding of unaligned RNA sequences. Algorithmically, RAF exploits sparsity in the set of likely pairing and alignment candidates for each nucleotide (as identified by the CONTRAfold or CONTRAlign programs) to achieve an effectively quadratic running time for simultaneous pairwise alignment and folding. RAF's fast sparse dynamic programming, in turn, serves as the inference engine within a discriminative machine learning algorithm for parameter estimation. RESULTS: In cross-validated benchmark tests, RAF achieves accuracies equaling or surpassing the current best approaches for RNA multiple sequence secondary structure prediction. However, RAF requires nearly an order of magnitude less time than other simultaneous folding and alignment methods, thus making it especially appropriate for high-throughput studies. AVAILABILITY: Source code for RAF is available at:http://contra.stanford.edu/contrafold/.

Coherent Coupling of Feedback Loops: A Design Principle of Cell Signaling Networks.

Yung-Keun Kwon — 2008-07-06T06:28:52-00:00

Bioinformatics (Oxford, England) (2 July 2008)

MOTIVATION: It is widely accepted that cell signaling networks have been evolved to be robust against perturbations. To investigate the topological characteristics resulting in such robustness, we have examined large-scale signaling networks and found that a number of feedback loops are present mostly in coupled structures. In particular, the coupling was made in a coherent way implying that same types of feedback loops are interlinked together. RESULTS: We have investigated the role of such coherently coupled feedback loops through extensive Boolean network simulations and found that a high proportion of coherent couplings can enhance the robustness of a network against its state perturbations. Moreover, we found that the robustness achieved by coherently coupled feedback loops can be kept evolutionarily stable. All these results imply that the coherent coupling of feedback loops might be a design principle of cell signaling networks devised to achieve the robustness. CONTACT: ckh@kaist.ac.kr SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Tuning gene expression to changing environments: from rapid responses to evolutionary adaptation.

Luis López-Maury — 2008-07-03T12:20:07-00:00

Nature reviews. Genetics (1 July 2008)

Organisms are constantly exposed to a wide range of environmental changes, including both short-term changes during their lifetime and longer-term changes across generations. Stress-related gene expression programmes, characterized by distinct transcriptional mechanisms and high levels of noise in their expression patterns, need to be balanced with growth-related gene expression programmes. A range of recent studies give fascinating insight into cellular strategies for keeping gene expression in tune with physiological needs dictated by the environment, promoting adaptation to both short- and long-term environmental changes. Not only do organisms show great resilience to external challenges, but emerging data suggest that they also exploit these challenges to fuel phenotypic variation and evolutionary innovation.

Horizontal gene transfer in eukaryotic evolution.

Patrick J Keeling — 2008-07-03T12:19:06-00:00

Nature reviews. Genetics (1 July 2008)

Horizontal gene transfer (HGT; also known as lateral gene transfer) has had an important role in eukaryotic genome evolution, but its importance is often overshadowed by the greater prevalence and our more advanced understanding of gene transfer in prokaryotes. Recurrent endosymbioses and the generally poor sampling of most nuclear genes from diverse lineages have also complicated the search for transferred genes. Nevertheless, the number of well-supported cases of transfer from both prokaryotes and eukaryotes, many with significant functional implications, is now expanding rapidly. Major recent trends include the important role of HGT in adaptation to certain specialized niches and the highly variable impact of HGT in different lineages.

The mechanism of micro-RNA-mediated translation repression is determined by the promoter of the target gene

Yi Kong — 2008-06-28T12:39:37-00:00

Proceedings of the National Academy of Sciences (25 June 2008), 0800650105.

MicroRNAs (miRNAs) are noncoding RNAs that base pair imperfectly to homologous regions in target mRNAs and negatively influence the synthesis of the corresponding proteins. Repression is mediated by a number of mechanisms, one of which is the direct inhibition of protein synthesis. Surprisingly, previous studies have suggested that two mutually exclusive mechanisms exist, one acting at the initiation phase of protein synthesis and the other at a postinitiation event. Here, we resolve this apparent dichotomy by demonstrating that the promoter used to transcribe the mRNA influences the type of miRNA-mediated translational repression. Transcripts derived from the SV40 promoter that contain let-7 target sites in their 3' UTRs are repressed at the initiation stage of translation, whereas essentially identical mRNAs derived from the TK promoter are repressed at a postinitiation step. We also show that there is a miR-34 target site within the 3' UTR of c-myc mRNA and that promoter dependency is also true for this endogenous 3' UTR. Overall, these data establish a link between the nuclear history of an mRNA and the mechanism of miRNA-mediated translational regulation in the cytoplasm. 10.1073/pnas.0800650105

Comparative analyses of bidirectional promoters in vertebrates.

MQ Yang — 2008-06-30T10:23:01-00:00

BMC bioinformatics, Vol. 9 Suppl 6 (2008)

BACKGROUND: Orthologous genes with deep phylogenetic histories are likely to retain similar regulatory features. In this report we utilize orthology assignments for pairs of genes co-regulated by bidirectional promoters to map the ancestral history of the promoter regions. RESULTS: Our mapping of bidirectional promoters from humans to fish shows that many such promoters emerged after the divergence of chickens and fish. Furthermore, annotations of promoters in deep phylogenies enable detection of missing data or assembly problems present in higher vertebrates. The functional importance of bidirectional promoters is indicated by selective pressure to maintain the arrangement of genes regulated by the promoter over long evolutionary time spans. Characteristics unique to bidirectional promoters are further elucidated using a technique for unsupervised classification, known as ESPERR. CONCLUSION: Results of these analyses will aid in our understanding of the evolution of bidirectional promoters, including whether the regulation of two genes evolved as a consequence of their proximity or if function dictated their co-regulation.

Systems biology driven software design for the research enterprise

John Boyle — 2008-06-25T23:08:38-00:00

BMC Bioinformatics, Vol. 9 (25 June 2008), 295.

Highly sensitive and specific microRNA expression profiling using BeadArray technology.

Jing Chen — 2008-06-30T10:12:29-00:00

Nucleic acids research (25 June 2008)

We have developed a highly sensitive, specific and reproducible method for microRNA (miRNA) expression profiling, using the BeadArraytrade mark technology. This method incorporates an enzyme-assisted specificity step, a solid-phase primer extension to distinguish between members of miRNA families. In addition, a universal PCR is used to amplify all targets prior to array hybridization. Currently, assay probes are designed to simultaneously analyse 735 well-annotated human miRNAs. Using this method, highly reproducible miRNA expression profiles were generated with 100-200 ng total RNA input. Furthermore, very similar expression profiles were obtained with total RNA and enriched small RNA species (R(2) >/= 0.97). The method has a 3.5-4 log (10(5)-10(9) molecules) dynamic range and is able to detect 1.2- to 1.3-fold-differences between samples. Expression profiles generated by this method are highly comparable to those obtained with RT-PCR (R(2) = 0.85-0.90) and direct sequencing (R = 0.87-0.89). This method, in conjunction with the 96-sample array matrix should prove useful for high-throughput expression profiling of miRNAs in large numbers of tissue samples.

Dispatched Homolog 2 is targeted by miR-214 through a combination of three weak microRNA recognition sites.

Nan Li — 2008-06-30T10:04:13-00:00

Nucleic acids research (26 June 2008)

MicroRNAs (miRNAs) regulate gene expression by inhibiting translation of target mRNAs through pairing with miRNA recognition elements (MREs), usually in 3' UTRs. Because pairing is imperfect, identification of bona fide mRNA targets presents a challenge. Most target recognition algorithms strongly emphasize pairing between nucleotides 2-8 of the miRNA (the 'seed' sequence) and the mRNA but adjacent sequences and the local context of the 3' UTR also affect targeting. Here, we show that dispatched 2 is a target of miR-214. In zebrafish, dispatched 2 is expressed in the telencephalon and ventral hindbrain and is essential for normal zebrafish development. Regulation of dispatched 2 by miR-214 is via pairing with three, noncanonical, weak MREs. By comparing the repression capacity of GFP reporters containing different dispatched 2 sequences, we found that a combination of weak sites, which lack canonical seed pairing, can effectively target an mRNA for silencing. This finding underscores the challenge that prediction algorithms face and emphasizes the need to experimentally validate predicted MREs.

The Systems Biology Research Tool: evolvable open-source software

Jeremiah Wright — 2008-06-30T10:00:02-00:00

BMC Systems Biology, Vol. 2, No. 1. (2008)

BACKGROUND:Research in the field of systems biology requires software for a variety of purposes. Software must be used to store, retrieve, analyze, and sometimes even to collect the data obtained from system-level (often high-throughput) experiments. Software must also be used to implement mathematical models and algorithms required for simulation and theoretical predictions on the system-level.RESULTS:We introduce a free, easy-to-use, open-source, integrated software platform called the Systems Biology Research Tool (SBRT) to facilitate the computational aspects of systems biology. The SBRT currently performs 35 methods for analyzing stoichiometric networks and 16 methods from fields such as graph theory, geometry, algebra, and combinatorics. New computational techniques can be added to the SBRT via process plug-ins, providing a high degree of evolvability and a unifying framework for software development in systems biology.CONCLUSIONS:The Systems Biology Research Tool represents a technological advance for systems biology. This software can be used to make sophisticated computational techniques accessible to everyone (including those with no programming ability), to facilitate cooperation among researchers, and to expedite progress in the field of systems biology.

Lin-28 interaction with the Let-7 precursor loop mediates regulated microRNA processing.

Martin A Newman — 2008-06-25T07:40:57-00:00

RNA (New York, N.Y.) (19 June 2008)

A hallmark of mammalian embryonic development is the widespread induction of microRNA (miRNA) expression. Surprisingly, the transcription of many of these small, noncoding RNAs is unchanged through development; rather, a post-transcriptional regulatory event prevents accumulation of the mature miRNA species. Here, we present a biochemical framework for the regulated production of the Let-7 family of miRNAs. Embryonic cells contain a Drosha Inhibitor that prevents processing of the Let-7 primary transcript. This inhibitor specifically binds to conserved nucleotides in the loop region of the Let-7 precursor, and competitor RNAs that mimic the binding site restore Let-7 processing. We have identified the Drosha Inhibitor as the embryonic stem cell specific protein Lin-28. Lin-28 has been previously implicated in developmental regulatory pathways in Caenorhabditis elegans, and it promotes reprogramming of human somatic cells into pluripotent stem cells. Our findings outline a microRNA post-transcriptional regulatory network and establish a novel role for the miRNA precursor loop in the regulated production of mature Let-7.

Long noncoding RNAs in mouse embryonic stem cell pluripotency and differentiation.

Marcel E Dinger — 2008-06-25T07:34:53-00:00

Genome research (18 June 2008)

The transcriptional networks that regulate embryonic stem (ES) cell pluripotency and lineage specification are the subject of considerable attention. To date such studies have focused almost exclusively on protein-coding transcripts. However, recent transcriptome analyses show that the mammalian genome contains thousands of long noncoding RNAs (ncRNAs), many of which appear to be expressed in a developmentally regulated manner. The functions of these remain untested. To identify ncRNAs involved in ES cell biology, we used a custom-designed microarray to examine the expression profiles of mouse ES cells differentiating as embryoid bodies (EBs) over a 16-day time-course. We identified 945 ncRNAs expressed during EB differentiation, of which 174 were differentially expressed, many correlating with pluripotency or specific differentiation events. Candidate ncRNAs were identified for further characterization by an integrated examination of expression profiles, genomic context, chromatin state, and promoter analysis. Many ncRNAs showed coordinated expression with genomically associated developmental genes, such as Dlx1, Dlx4, GATA6 and Ecsit. We examined two novel developmentally-regulated ncRNAs, Evx1AS and HoxB5/6AS, which are derived from homeotic loci and share similar expression patterns and localization in mouse embryos with their associated protein-coding genes. Using chromatin immunoprecipitation, we show both ncRNAs are associated with trimethylated H3K4 histones and histone methyltransferase Mll1, suggesting a role in epigenetic regulation of homeotic loci during ES cell differentiation. Taken together, our data indicate that long ncRNAs are likely to be important in processes directing pluripotency and alternative differentiation programs, in some cases through engagement of the epigenetic machinery.

Inferring causal relationships among different histone modifications and gene expression

Hong Yu — 2008-06-19T04:53:55-00:00

Genome Res. (18 June 2008), gr.073080.107.

Histone modifications are major epigenetic factors regulating gene expression. They play important roles in maintaining stem cell pluripotency and in cancer pathogenesis. Different modifications may combine to form complex "histone codes." Recent high throughput technologies, such as "ChIP-chip" and "ChIP-seq," have generated high resolution maps for many histone modifications on the human genome. Here we use these maps to build a Bayesian network to infer causal and combinatorial relationships among histone modifications and gene expression. A pilot network derived by the same method among polycomb group (PcG) genes and H3K27 trimethylation is accurately supported by current literature. Our unbiased network model among histone modifications is also well supported by cross validation results. It not only confirmed already known relationships, such as those of H3K27me3 to gene silencing, H3K4me3 to gene activation, and the effect of bivalent modification of both H3K4me3 and H3K27me3, but also identified many other relationships that may predict new epigenetic interactions important in epigenetic gene regulation. Our automated inference method, which is potentially applicable to other ChIP-chip or ChIP-seq data analyses, provides a much-needed guide to deciphering the complex histone codes. 10.1101/gr.073080.107

Proliferating Cells Express mRNAs with Shortened 3' Untranslated Regions and Fewer MicroRNA Target Sites

Rickard Sandberg — 2008-06-20T15:33:43-00:00

Science, Vol. 320, No. 5883. (20 June 2008), pp. 1643-1647.

Messenger RNA (mRNA) stability, localization, and translation are largely determined by sequences in the 3' untranslated region (3'UTR). We found a conserved increase in expression of mRNAs terminating at upstream polyadenylation sites after activation of primary murine CD4+ T lymphocytes. This program, resulting in shorter 3'UTRs, is a characteristic of gene expression during immune cell activation and correlates with proliferation across diverse cell types and tissues. Forced expression of full-length 3'UTRs conferred reduced protein expression. In some cases the reduction in protein expression could be reversed by deletion of predicted microRNA target sites in the variably included region. Our data indicate that gene expression is coordinately regulated, such that states of increased proliferation are associated with widespread reductions in the 3'UTR-based regulatory capacity of mRNAs. 10.1126/science.1155390

Systematic reconstruction of TRANSPATH data into Cell System Markup Language

Masao Nagasaki — 2008-06-23T07:58:26-00:00

BMC Systems Biology, Vol. 2, No. 1. (2008)

BACKGROUND:Many biological repositories store static descriptions of the biological processes within a cell, such as protein-protein interactions, metabolic pathways, signal transduction pathways, regulations of transcription factors, and regulations of miRNA. Unfortunately, it is difficult to directly use such static descriptions when generating simulation-based models. Thus, modeling rules for encoding biological knowledge into system-dynamics-oriented standardized formats would be very useful for fully understanding cellular dynamics at the system level.RESULTS:In this work, we have created 16 modeling rules based on hybrid functional Petri net with extension (HFPNe). These rules are applied to the TRANSPATH database, a manually curated high-quality pathway database, which stores more than 115,000 cellular events in humans, mice, and rats, collected from over 31,500 publications. In the modeling rules, each Petri net element is incorporated with Cell System Ontology (CSO) to enable semantic interoperability of models. As a formal ontology for biological pathway modeling with dynamics, CSO internally maintains predefined terms and corresponding icons. With the CSO features, the modeling rules translate TRANSPATH to simulation-based and semantically valid models with embedded icons. The results are encoded into a biological pathway format, Cell System Markup Language (CSML), which eases the exchange and integration of biological data and models. CONCLUSIONS:By using the 16 modeling rules, 97 of the reactions in TRANSPATH are converted into simulation-based models in CSML. This reconstruction demonstrates that it is possible to use our rules to generate quantitative models from static pathway descriptions.

A computational analysis of the protein-protein interaction networks in neurodegenerative diseases

Joaquin Goni — 2008-06-20T13:44:26-00:00

BMC Systems Biology, Vol. 2, No. 1. (2008)

BACKGROUND:Recent developments have meant that network theory is making an important contribution to the topological study of biological networks, such as protein-protein interaction (PPI) networks. The identification of differentially expressed genes in DNA array experiments is a source of information regarding the molecular pathways involved in disease. Thus, considering PPI analysis and gene expression studies together may provide a better understanding of multifactorial neurodegenerative diseases such as Multiple Sclerosis (MS) and Alzheimer disease (AD). The aim of this study was to assess whether the parameters of degree and betweenness, two fundamental measures in network theory, are properties that differentiate between implicated (seed-proteins) and non-implicated nodes (neighbors) in MS and AD. We used experimentally validated PPI information to obtain the neighbors for each seed group and we studied these parameters in four networks: MS-blood network; MS-brain network; AD-blood network; and AD-brain network. RESULTS:Specific features of seed-proteins were revealed, whereby they displayed a lower average degree in both diseases and tissues, and a higher betweenness in AD-brain and MS-blood networks. Additionally, the heterogeneity of the processes involved indicate that these findings are not pathway specific but rather that they are spread over different pathways.CONCLUSION:Our findings show differential centrality properties of proteins whose gene expression is impaired in neurodegenerative diseases.

Splicing and dicing with a SERRATEd edge.

Taiowa A Montgomery — 2008-06-20T08:08:51-00:00

Proceedings of the National Academy of Sciences of the United States of America (16 June 2008)

Dual roles of the nuclear cap-binding complex and SERRATE in pre-mRNA splicing and microRNA processing in Arabidopsis thaliana.

Sascha Laubinger — 2008-06-17T06:54:43-00:00

Proceedings of the National Academy of Sciences of the United States of America (12 June 2008)

The processing of Arabidopsis thaliana microRNAs (miRNAs) from longer primary transcripts (pri-miRNAs) requires the activity of several proteins, including DICER-LIKE1 (DCL1), the double-stranded RNA-binding protein HYPONASTIC LEAVES1 (HYL1), and the zinc finger protein SERRATE (SE). It has been noted before that the morphological appearance of weak se mutants is reminiscent of plants with mutations in ABH1/CBP80 and CBP20, which encode the two subunits of the nuclear cap-binding complex. We report that, like SE, the cap-binding complex is necessary for proper processing of pri-miRNAs. Inactivation of either ABH1/CBP80 or CBP20 results in decreased levels of mature miRNAs accompanied by apparent stabilization of pri-miRNAs. Whole-genome tiling array analyses reveal that se, abh1/cbp80, and cbp20 mutants also share similar splicing defects, leading to the accumulation of many partially spliced transcripts. This is unlikely to be an indirect consequence of improper miRNA processing or other mRNA turnover pathways, because introns retained in se, abh1/cbp80, and cbp20 mutants are not affected by mutations in other genes required for miRNA processing or for nonsense-mediated mRNA decay. Taken together, our results uncover dual roles in splicing and miRNA processing that distinguish SE and the cap-binding complex from specialized miRNA processing factors such as DCL1 and HYL1.

The microRNA.org resource: targets and expression.

Doron Betel — 2007-12-27T07:04:46-00:00

Nucleic Acids Res (23 December 2007)

MicroRNA.org (http://www.microrna.org) is a comprehensive resource of microRNA target predictions and expression profiles. Target predictions are based on a development of the miRanda algorithm which incorporates current biological knowledge on target rules and on the use of an up-to-date compendium of mammalian microRNAs. MicroRNA expression profiles are derived from a comprehensive sequencing project of a large set of mammalian tissues and cell lines of normal and disease origin. Using an improved graphical interface, a user can explore (i) the set of genes that are potentially regulated by a particular microRNA, (ii) the implied cooperativity of multiple microRNAs on a particular mRNA and (iii) microRNA expression profiles in various tissues. To facilitate future updates and development, the microRNA.org database structure and software architecture is flexibly designed to incorporate new expression and target discoveries. The web resource provides users with functional information about the growing number of microRNAs and their interaction with target genes in many species and facilitates novel discoveries in microRNA gene regulation.

A novel microarray approach reveals new tissue-specific signatures of known and predicted mammalian microRNAs.

Iwan Beuvink — 2007-03-17T08:10:56-00:00

Nucleic Acids Res (13 March 2007)

Microarrays to examine the global expression levels of microRNAs (miRNAs) in a systematic in-parallel manner have become important tools to help unravel the functions of miRNAs and to understand their roles in RNA-based regulation and their implications in human diseases. We have established a novel miRNA-specific microarray platform that enables the simultaneous expression analysis of both known and predicted miRNAs obtained from human or mouse origin. Chemically modified 2'-O-(2-methoxyethyl)-(MOE) oligoribonucleotide probes were arrayed onto Evanescent Resonance (ER) microchips by robotic spotting. Supplementing the complementary probes against miRNAs with carefully designed mismatch controls allowed for accurate sequence-specific determination of miRNA expression profiles obtained from a panel of mouse tissues. This revealed new expression signatures of known miRNAs as well as of novel miRNAs previously predicted using bioinformatic methods. Systematic confirmation of the array data with northern blotting and, in particular, real-time PCR suggests that the described microarray platform is a powerful tool to analyze miRNA expression patterns with rapid throughput and high fidelity.

A custom microarray platform for analysis of microRNA gene expression.

JM Thomson — 2005-08-14T16:13:42-00:00

Nat Methods, Vol. 1, No. 1. (October 2004), pp. 47-53.

MicroRNAs are short, noncoding RNA transcripts that post-transcriptionally regulate gene expression. Several hundred microRNA genes have been identified in Caenorhabditis elegans, Drosophila, plants and mammals. MicroRNAs have been linked to developmental processes in C. elegans, plants and humans and to cell growth and apoptosis in Drosophila. A major impediment in the study of microRNA function is the lack of quantitative expression profiling methods. To close this technological gap, we have designed dual-channel microarrays that monitor expression levels of 124 mammalian microRNAs. Using these tools, we observed distinct patterns of expression among adult mouse tissues and embryonic stem cells. Expression profiles of staged embryos demonstrate temporal regulation of a large class of microRNAs, including members of the let-7 family. This microarray technology enables comprehensive investigation of microRNA expression, and furthers our understanding of this class of recently discovered noncoding RNAs.

Inferring microRNA activities by combining gene expression with microRNA target prediction.

C Cheng — 2008-06-12T11:10:24-00:00

PLoS ONE, Vol. 3, No. 4. (2008)

BACKGROUND: MicroRNAs (miRNAs) play crucial roles in a variety of biological processes via regulating expression of their target genes at the mRNA level. A number of computational approaches regarding miRNAs have been proposed, but most of them focus on miRNA gene finding or target predictions. Little computational work has been done to investigate the effective regulation of miRNAs. METHODOLOGY/PRINCIPAL FINDINGS: We propose a method to infer the effective regulatory activities of miRNAs by integrating microarray expression data with miRNA target predictions. The method is based on the idea that regulatory activity changes of miRNAs could be reflected by the expression changes of their target transcripts measured by microarray. To validate this method, we apply it to the microarray data sets that measure gene expression changes in cell lines after transfection or inhibition of several specific miRNAs. The results indicate that our method can detect activity enhancement of the transfected miRNAs as well as activity reduction of the inhibited miRNAs with high sensitivity and specificity. Furthermore, we show that our inference is robust with respect to false positives of target prediction. CONCLUSIONS/SIGNIFICANCE: A huge amount of gene expression data sets are available in the literature, but miRNA regulation underlying these data sets is largely unknown. The method is easy to be implemented and can be used to investigate the miRNA effective regulation underlying the expression change profiles obtained from microarray experiments.

Everything you wanted to know about small RNA but were afraid to ask

Scott Boyd — 2008-04-21T17:31:41-00:00

Laboratory Investigation, Vol. aop, No. current.

TiGER: a database for tissue-specific gene expression and regulation

Xiong Liu — 2008-06-10T19:46:24-00:00

BMC Bioinformatics, Vol. 9 (09 June 2008), 271.

Enriched Transcription Factor Binding Sites in Hypermethylated Gene Promoters in Drug Resistant Cancer Cells.

Meng Li — 2008-06-11T07:40:54-00:00

Bioinformatics (Oxford, England) (6 June 2008)

MOTIVATION: In the human genome, "CpG islands", CG-rich region located in or near gene promoters, are normally unmethylated. However, in cancer cells, CpG islands frequently gain methylation, resulting in silencing of growth-limiting tumor suppressor genes. To our knowledge, the potential relationship between CpG island hypermethylation, transcription factor (TF) binding in local promoter regions, and transcriptional control has not been previously explored in a genome-wide context. RESULTS: In this study, we utilized bioinformatics tools and TF binding site databases to globally analyze sequences methylated in a laboratory model for the development of drug-resistant cancer. Our results demonstrated that four transcription factor binding sites (TFBS) were enriched in hyper-methylated sequences. More interestingly, over-representation of these TFBS was observed in hyper-/hypo-methylated sequences where significant changes in methylation levels were observed in drug-resistant cancer cells. In summary, we believe that these findings offer a means to further explore the relationship between DNA methylation and gene expression in drug resistance and tumorigenesis. CONTACT: sunkim2@indiana.edu, knephew@indiana.edu.

Combinatorial microRNA target predictions

Azra Krek — 2005-04-27T18:51:58-00:00

Nature Genetics, Vol. 37, No. 5. (03 April 2005), pp. 495-500.

MicroRNA-target pairs in the rat kidney identified by microRNA microarray, proteomic, and bioinformatic analysis.

Zhongmin Tian — 2008-02-01T07:56:51-00:00

Genome Res (29 January 2008)

Mammalian genomes contain several hundred highly conserved genes encoding microRNAs. In silico analysis has predicted that a typical microRNA may regulate the expression of hundreds of target genes, suggesting miRNAs might have broad biological significance. A major challenge is to obtain experimental evidence for predicted microRNA-target pairs. We reasoned that reciprocal expression of a microRNA and a predicted target within a physiological context would support the presence and relevance of a microRNA-target pair. We used microRNA microarray and proteomic techniques to analyze the cortex and the medulla of rat kidneys. Of the 377 microRNAs analyzed, we identified 6 as enriched in the renal cortex and 11 in the renal medulla. From approximately 2100 detectable protein spots in two-dimensional gels, we identified 58 proteins as more abundant in the renal cortex and 72 in the renal medulla. The differential expression of several microRNAs and proteins was verified by real-time PCR and Western blot analyses, respectively. Several pairs of reciprocally expressed microRNAs and proteins were predicted to be microRNA-target pairs by TargetScan, PicTar, or miRanda. Seven pairs were predicted by two algorithms and two pairs by all three algorithms. The identification of reciprocal expression of microRNAs and their computationally predicted targets in the rat kidney provides a unique molecular basis for further exploring the biological role of microRNA. In addition, this study establishes a differential profile of microRNA expression between the renal cortex and the renal medulla and greatly expands the known differential proteome profiles between the two kidney regions.

NeAT: a toolbox for the analysis of biological networks, clusters, classes and pathways.

Sylvain Brohée — 2008-06-07T21:47:40-00:00

Nucleic acids research (4 June 2008)

The network analysis tools (NeAT) (http://rsat.ulb.ac.be/neat/) provide a user-friendly web access to a collection of modular tools for the analysis of networks (graphs) and clusters (e.g. microarray clusters, functional classes, etc.). A first set of tools supports basic operations on graphs (comparison between two graphs, neighborhood of a set of input nodes, path finding and graph randomization). Another set of programs makes the connection between networks and clusters (graph-based clustering, cliques discovery and mapping of clusters onto a network). The toolbox also includes programs for detecting significant intersections between clusters/classes (e.g. clusters of co-expression versus functional classes of genes). NeAT are designed to cope with large datasets and provide a flexible toolbox for analyzing biological networks stored in various databases (protein interactions, regulation and metabolism) or obtained from high-throughput experiments (two-hybrid, mass-spectrometry and microarrays). The web interface interconnects the programs in predefined analysis flows, enabling to address a series of questions about networks of interest. Each tool can also be used separately by entering custom data for a specific analysis. NeAT can also be used as web services (SOAP/WSDL interface), in order to design programmatic workflows and integrate them with other available resources.

A computational screen for mouse signaling pathways targeted by microRNA clusters.

Jianzhen Xu — 2008-06-02T14:20:34-00:00

RNA (New York, N.Y.) (29 May 2008)

MicroRNAs (miRNAs) are one class of short, endogenous RNAs which can regulate gene expression at the post-transcriptional level. Previous analysis revealed that mammalian miRNAs tend to cluster on chromosomes. However, the functional consequences of this clustering and conservation property are largely unknown. In this study we present a method to identify signaling pathways targeted by clustered miRNAs. We performed a computational screen for mouse signaling pathways targeted by miRNA clusters. Here, we report that the target genes of 3 miRNA clusters are overrepresented in 15 signaling pathways. We provided experimental evidence that one miRNA cluster, mmu-mir-183-96-182 targets Irs1, Rasa1, and Grb2, all of which are located in the insulin signaling pathway. Theses results suggest that by targeting components with different roles along a signaling pathway, different members of one miRNA cluster can act as a whole to coordinately control the signal transduction process.

Evolution and Creationism in America's Classrooms: A National Portrait.

Michael B Berkman — 2008-05-30T08:06:05-00:00

PLoS biology, Vol. 6, No. 5. (20 May 2008)

Coordinated regulation of transcription factors through Notch2 is an important mediator of mast cell fate.

Mamiko Sakata-Yanagimoto — 2008-05-25T08:25:05-00:00

Proceedings of the National Academy of Sciences of the United States of America (22 May 2008)

Mast cells are thought to participate in a wide variety of pathophysiological conditions. Mechanisms of regulation, however, of mast cell production and maturation are still to be elucidated. Mast cell developmental process is likely to be profoundly affected by cell-autonomous transcriptional regulators such as the GATA family and CCAAT/enhancer binding protein (C/EBP) family members. Extracellular regulators such as stem cell factor and IL-3 have essential roles in basal and inducible mast cell generation, respectively. The relationship, however, between the extracellular signaling and cellular transcriptional control is unclear, and the trigger of the mast cell development remains elusive. Notch signaling plays a fundamental role in the lymphopoietic compartment, but its role in myeloid differentiation is less clear. Here, we demonstrate that Notch signaling connects environmental cues and transcriptional control for mast cell fate decision. Delta1, an established Notch ligand, instructs bone marrow common myeloid progenitors and granulocyte-macrophage progenitors toward mast cell lineage at the expense of other granulocyte-macrophage lineages, depending on the function of the Notch2 gene. Notch2 signaling results in the up-regulation of Hes-1 and GATA3, whereas simultaneous overexpression of these transcription factors remarkably biases the progenitor fate toward the mast cell-containing colony-forming cells. C/EBPalpha mRNA was down-regulated in myeloid progenitors as a consequence of Hes-1 overexpression, in agreement with the recent proposal that the down-regulation of C/EBPalpha is necessary for mast cell fate determination. Taken together, signaling through Notch2 determines the fate of myeloid progenitors toward mast cell-producing progenitors, via coordinately up-regulating Hes-1 and GATA3.

RNALogo: a new approach to display structural RNA alignment.

Tzu-Hao Chang — 2008-05-24T09:15:37-00:00

Nucleic acids research (21 May 2008)

Regulatory RNAs play essential roles in many essential biological processes, ranging from gene regulation to protein synthesis. This work presents a web-based tool, RNALogo, to create a new graphical representation of the patterns in a multiple RNA sequence alignment with a consensus structure. The RNALogo graph can indicate significant features within an RNA sequence alignment and its consensus RNA secondary structure. RNALogo extends Sequence logos, and specifically incorporates RNA secondary structures and mutual information of base-paired regions into the graphical representation. Each RNALogo graph is composed of stacks of letters, with one stack for each position in the consensus RNA secondary structure. RNALogo provides a convenient and high configurable logo generator. An RNALogo graph is generated for each RNA family in Rfam, and these generated logos are accumulated into a gallery of RNALogo. Users can search or browse RNALogo graphs in this gallery to receive additional perspectives of known RNA families. RNALogo is now available at: http://rnalogo.mbc.nctu.edu.tw/.

Inducible expression of microRNA-194 is regulated by HNF-1alpha during intestinal epithelial cell differentiation.

Kimihiro Hino — 2008-05-23T08:03:22-00:00

RNA (New York, N.Y.) (20 May 2008)

Maintenance of the intestinal epithelium is based on well-balanced molecular mechanisms that confer the stable and continuous supply of specialized epithelial cell lineages from multipotent progenitors. Lineage commitment decisions in the intestinal epithelium system involve multiple regulatory systems that interplay with each other to establish the cellular identities. Here, we demonstrate that the microRNA system could be involved in intestinal epithelial cell differentiation, and that microRNA-194 (miR-194) is highly induced during this process. To investigate this inducible expression mechanism, we identified the genomic structure of the miR-194-2, -192 gene, one of the inducible class of miR-194 parental genes. Furthermore, we identified its transcriptional regulatory region that contains a consensus-binding motif for hepatocyte nuclear factor-1alpha (HNF-1alpha), which is well known as a transcription factor to regulate gene expression in intestinal epithelial cells. By chromatin immunoprecipitation assay and luciferase reporter analysis, we revealed that pri-miR-194-2 expression is controlled by HNF-1alpha, and its consensus binding region is required for the transcription of pri-miR-194-2 in vivo in an intestinal epithelial cell line, Caco-2. Our observations indicate that microRNA genes could be targets of lineage-specific transcription factors and that microRNAs are regulated by a tissue-specific manner in the intestinal epithelium. Therefore, our work suggests that induced expression of these microRNAs have important roles in intestinal epithelium maturation.

WAR: Webserver for aligning structural RNAs.

Elfar Torarinsson — 2008-05-23T07:59:39-00:00

Nucleic acids research (20 May 2008)

We present an easy-to-use webserver that makes it possible to simultaneously use a number of state of the art methods for performing multiple alignment and secondary structure prediction for noncoding RNA sequences. This makes it possible to use the programs without having to download the code and get the programs to run. The results of all the programs are presented on a webpage and can easily be downloaded for further analysis. Additional measures are calculated for each program to make it easier to judge the individual predictions, and a consensus prediction taking all the programs into account is also calculated. This website is free and open to all users and there is no login requirement. The webserver can be found at: http://genome.ku.dk/resources/war.

Inter- and intra-combinatorial regulation by transcription factors and microRNAs

Yiming Zhou — 2007-10-31T09:34:56-00:00

BMC Genomics, Vol. 8 (30 October 2007), 396.

Teaching resource. Quantitative models of mammalian cell signaling pathways.

R Iyengar — 2008-05-21T09:02:01-00:00

Science signaling, Vol. 1, No. 7. (2008)

This teaching resource provides lecture notes and slides for a class on mathematical modeling of mammalian signaling pathways. This lecture was part of the course .Cell Signaling Systems: A Course for Graduate Students. and focused on quantitative modeling. The lecture describes how different types of mathematical representations are applied to different signaling systems to provide insight into how a signaling system controls cell behavior. The development of an ordinary differential equation.based model for a bistable switch and the predictions that can be obtained from the model are described. The lecture concludes with a description of how models can be tested experimentally and modified when the details of the models and the resultant predictive behavior are not confirmed by experimentation.

Principles of microRNA regulation of a human cellular signaling network.

Q Cui — 2006-09-15T12:49:12-00:00

Mol Syst Biol, Vol. 2 (2006)

MicroRNAs (miRNAs) are endogenous approximately 22-nucleotide RNAs, which suppress gene expression by selectively binding to the 3'-noncoding region of specific messenger RNAs through base-pairing. Given the diversity and abundance of miRNA targets, miRNAs appear to functionally interact with various components of many cellular networks. By analyzing the interactions between miRNAs and a human cellular signaling network, we found that miRNAs predominantly target positive regulatory motifs, highly connected scaffolds and most downstream network components such as signaling transcription factors, but less frequently target negative regulatory motifs, common components of basic cellular machines and most upstream network components such as ligands. In addition, when an adaptor has potential to recruit more downstream components, these components are more frequently targeted by miRNAs. This work uncovers the principles of miRNA regulation of signal transduction networks and implies a potential function of miRNAs for facilitating robust transitions of cellular response to extracellular signals and maintaining cellular homeostasis.

Alternative splicing and protein structure evolution.

F Birzele — 2008-02-26T20:44:21-00:00

Nucleic Acids Res, Vol. 36, No. 2. (February 2008), pp. 550-558.

Alternative splicing is thought to be one of the major sources for functional diversity in higher eukaryotes. Interestingly, when mapping splicing events onto protein structures, about half of the events affect structured and even highly conserved regions i.e. are non-trivial on the structure level. This has led to the controversial hypothesis that such splice variants result in nonsense-mediated mRNA decay or non-functional, unstructured proteins, which do not contribute to the functional diversity of an organism. Here we show in a comprehensive study on alternative splicing that proteins appear to be much more tolerant to structural deletions, insertions and replacements than previously thought. We find literature evidence that such non-trivial splicing isoforms exhibit different functional properties compared to their native counterparts and allow for interesting regulatory patterns on the protein network level. We provide examples that splicing events may represent transitions between different folds in the protein sequence-structure space and explain these links by a common genetic mechanism. Taken together, those findings hint to a more prominent role of splicing in protein structure evolution and to a different view of phenotypic plasticity of protein structures.

Identification of tissue-specific cis-regulatory modules based on interactions between transcription factors

Xueping Yu — 2007-11-10T21:48:55-00:00

BMC Bioinformatics, Vol. 8 (09 November 2007), 437.

MicroRNAs and Other Tiny Endogenous RNAs in C. elegans

Victor Ambros — 2008-05-19T08:59:51-00:00

Current Biology, Vol. 13, No. 10. (13 May 2003), pp. 807-818.

Background: MicroRNAs (miRNAs) are small noncoding RNAs that are processed from hairpin precursor transcripts by Dicer. miRNAs probably inhibit translation of mRNAs via imprecise antisense base-pairing. Small interfering RNAs (siRNAs) are similar in size to miRNAs, but they recognize targets by precise complementarity and elicit RNA-mediated interference (RNAi). We employed cDNA sequencing and comparative genomics to identify additional C. elegans small RNAs with properties similar to miRNAs and siRNAs. Results: We found three broad classes of small RNAs in C. elegans: (1) 21 new miRNA genes (we estimate that C. elegans contains approximately 100 distinct miRNA genes, about 30% of which are conserved in vertebrates; (2), 33 distinct members of a class of tiny noncoding RNA (tncRNA) genes with transcripts that are similar in length to miRNAs (approximately 20-21 nt) and that are in some cases developmentally regulated but are apparently not processed from a miRNA-like hairpin precursor and are not phylogenetically conserved; (3) more than 700 distinct small antisense RNAs, about 20 nt long, that are precisely complementary to protein coding regions of more than 500 different genes and therefore seem to be endogenous siRNAs. Conclusions: The presence of diverse endogenous siRNAs in normal worms suggests ongoing, genome-wide gene silencing by RNAi. miRNAs and tncRNAs are not predicted to form complete Watson-Crick hybrids with any C. elegans RNA target, and so they are likely to regulate the activity of other genes by non-RNAi mechanisms. These results suggest that diverse modes of small RNA-mediated gene regulation are deployed in normal worms.