Doron Betel

The microRNA.org resource: targets and expression

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.

Comprehensive modeling of microRNA targets predicts functional non-conserved and non-canonical sites.

AbstractmirSVR is a new machine learning method for ranking microRNA target sites by a down-regulation score. The algorithm trains a regression model on sequence and contextual features extracted from miRanda-predicted target sites. In a large-scale evaluation, miRanda-mirSVR is competitive with other target prediction methods in identifying target genes and predicting the extent of their downregulation at the mRNA or protein levels. Importantly, the method identifies a significant number of experimentally determined non-canonical and non-conserved sites.

The Biomolecular Interaction Network Database and related tools 2005 update

The Biomolecular Interaction Network Database (BIND) (http://bind.ca) archives biomolecular interaction, reaction, complex and pathway information. Our aim is to curate the details about molecular interactions that arise from published experimental research and to provide this information, as well as tools to enable data analysis, freely to researchers worldwide. BIND data are curated into a comprehensive machine-readable archive of computable information and provides users with methods to discover interactions and molecular mechanisms. BIND has worked to develop new methods for visualization that amplify the underlying annotation of genes and proteins to facilitate the study of molecular interaction networks. BIND has maintained an open database policy since its inception in 1999. Data growth has proceeded at a tremendous rate, approaching over 100 000 records. New services provided include a new BIND Query and Submission interface, a Standard Object Access Protocol service and the Small Molecule Interaction Database (http://smid.blueprint.org) that allows users to determine probable small molecule binding sites of new sequences and examine conserved binding residues.

Comprehensive evaluation of differential gene expression analysis methods for RNA-seq data

A large number of computational methods have been developed for analyzing differential gene expression in RNA-seq data. We describe a comprehensive evaluation of common methods using the SEQC benchmark dataset and ENCODE data. We consider a number of key features, including normalization, accuracy of differential expression detection and differential expression analysis when one condition has no detectable expression. We find significant differences among the methods, but note that array-based methods adapted to RNA-seq data perform comparably to methods designed for RNA-seq. Our results demonstrate that increasing the number of replicate samples significantly improves detection power over increased sequencing depth.

Genetic dissection of the miR-17∼92 cluster of microRNAs in Myc-induced B-cell lymphomas

The miR-17 approximately 92 cluster is frequently amplified or overexpressed in human cancers and has emerged as the prototypical oncogenic polycistron microRNA (miRNA). miR-17 approximately 92 is a direct transcriptional target of c-Myc, and experiments in a mouse model of B-cell lymphomas have shown cooperation between these two oncogenes. However, both the molecular mechanism underlying this cooperation and the individual miRNAs that are responsible for it are unknown. By using a conditional knockout allele of miR-17 approximately 92, we show here that sustained expression of endogenous miR-17 approximately 92 is required to suppress apoptosis in Myc-driven B-cell lymphomas. Furthermore, we show that among the six miRNAs that are encoded by miR-17 approximately 92, miR-19a and miR-19b are absolutely required and largely sufficient to recapitulate the oncogenic properties of the entire cluster. Finally, by combining computational target prediction, gene expression profiling, and an in vitro screening strategy, we identify a subset of miR-19 targets that mediate its prosurvival activity.

Transfection of small RNAs globally perturbs gene regulation by endogenous microRNAs

Transfection of small RNAs (such as small interfering RNAs (siRNAs) and microRNAs (miRNAs)) into cells typically lowers expression of many genes. Unexpectedly, increased expression of genes also occurs. We investigated whether this upregulation results from a saturation effect—that is, competition among the transfected small RNAs and the endogenous pool of miRNAs for the intracellular machinery that processes small RNAs. To test this hypothesis, we analyzed genome-wide transcript responses from 151 published transfection experiments in seven different human cell types. We show that targets of endogenous miRNAs are expressed at significantly higher levels after transfection, consistent with impaired effectiveness of endogenous miRNA repression. This effect exhibited concentration and temporal dependence. Notably, the profile of endogenous miRNAs can be largely inferred by correlating miRNA sites with gene expression changes after transfections. The competition and saturation effects have practical implications for miRNA target prediction, the design of siRNA and short hairpin RNA (shRNA) genomic screens and siRNA therapeutics.

Characterization of Small RNAs in Aplysia Reveals a Role for miR-124 in Constraining Synaptic Plasticity through CREB

Memory storage and memory-related synaptic plasticity rely on precise spatiotemporal regulation of gene expression. To explore the role of small regulatory RNAs in learning-related synaptic plasticity, we carried out massive parallel sequencing to profile the small RNAs of Aplysia californica. We identified 170 distinct miRNAs, 13 of which were novel and specific to Aplysia. Nine miRNAs were brain enriched, and several of these were rapidly downregulated by transient exposure to serotonin, a modulatory neurotransmitter released during learning. Further characterization of the brain-enriched miRNAs revealed that miR-124, the most abundant and well-conserved brain-specific miRNA, was exclusively present presynaptically in a sensory-motor synapse where it constrains serotonin-induced synaptic facilitation through regulation of the transcriptional factor CREB. We therefore present direct evidence that a modulatory neurotransmitter important for learning can regulate the levels of small RNAs and present a role for miR-124 in long-term plasticity of synapses in the mature nervous system.

Genome-wide identification of microRNA targets in human ES cells reveals a role for miR-302 in modulating BMP response

MicroRNAs are important regulators in many cellular processes, including stem cell self-renewal. Recent studies demonstrated their function as pluripotency factors with the capacity for somatic cell reprogramming. However, their role in human embryonic stem (ES) cells (hESCs) remains poorly understood, partially due to the lack of genome-wide strategies to identify their targets. Here, we performed comprehensive microRNA profiling in hESCs and in purified neural and mesenchymal derivatives. Using a combination of AGO cross-linking and microRNA perturbation experiments, together with computational prediction, we identified the targets of the miR-302/367 cluster, the most abundant microRNAs in hESCs. Functional studies identified novel roles of miR-302/367 in maintaining pluripotency and regulating hESC differentiation. We show that in addition to its role in TGF-β signaling, miR-302/367 promotes bone morphogenetic protein (BMP) signaling by targeting BMP inhibitors TOB2, DAZAP2, and SLAIN1. This study broadens our understanding of microRNA function in hESCs and is a valuable resource for future studies in this area.

Genome-wide identification of miRNA targets by PAR-CLIP

miRNAs are short (20-23 nt) RNAs that are loaded into proteins of the Argonaute (AGO) family and guide them to partially complementary target sites on mRNAs, resulting in mRNA destabilization and/or translational repression. It is estimated that about 60% of the mammalian genes are potentially regulated by miRNAs, and therefore methods for experimental miRNA target determination have become valuable tools for the characterization of posttranscriptional gene regulation. Here we present a step-by-step protocol and guidelines for the computational analysis for the large-scale identification of miRNA target sites in cultured cells by photoactivatable ribonucleoside enhanced crosslinking and immunoprecipitation (PAR-CLIP) of AGO proteins.

SeqHound: biological sequence and structure database as a platform for bioinformatics research

BackgroundSeqHound has been developed as an integrated biological sequence, taxonomy, annotation and 3-D structure database system. It provides a high-performance server platform for bioinformatics research in a locally-hosted environment.ResultsSeqHound is based on the National Center for Biotechnology Information data model and programming tools. It offers daily updated contents of all Entrez sequence databases in addition to 3-D structural data and information about sequence redundancies, sequence neighbours, taxonomy, complete genomes, functional annotation including Gene Ontology terms and literature links to PubMed. SeqHound is accessible via a web server through a Perl, C or C++ remote API or an optimized local API. It provides functionality necessary to retrieve specialized subsets of sequences, structures and structural domains. Sequences may be retrieved in FASTA, GenBank, ASN.1 and XML formats. Structures are available in ASN.1, XML and PDB formats. Emphasis has been placed on complete genomes, taxonomy, domain and functional annotation as well as 3-D structural functionality in the API, while fielded text indexing functionality remains under development. SeqHound also offers a streamlined WWW interface for simple web-user queries.ConclusionsThe system has proven useful in several published bioinformatics projects such as the BIND database and offers a cost-effective infrastructure for research. SeqHound will continue to develop and be provided as a service of the Blueprint Initiative at the Samuel Lunenfeld Research Institute. The source code and examples are available under the terms of the GNU public license at the Sourceforge site http://sourceforge.net/projects/slritools/ in the SLRI Toolkit.