Thousands of long intervening noncoding RNAs (lincRNAs) have been identified in mammals. To bette... more Thousands of long intervening noncoding RNAs (lincRNAs) have been identified in mammals. To better understand the evolution and functions of these enigmatic RNAs, we used chromatin marks, poly (A)-site mapping and RNA-Seq data to identify more than 550 distinct lincRNAs in zebrafish. Although these shared many characteristics with mammalian lincRNAs, only 29 had detectable sequence similarity with putative mammalian orthologs, typically restricted to a single short region of high conservation.
Gene knock-out studies have shown that only~ 18% of S. cerevisiae genes are essential for growth ... more Gene knock-out studies have shown that only~ 18% of S. cerevisiae genes are essential for growth on a rich medium. Consequently, buffering on the genetic level is believed to be abundant in eukaryotes. To understand the role of nonessential genes better, several large scale studies performed double knock-outs, and identified many events of synthetic lethality, where a mutant carrying deletions of two nonessential genes is lethal, and synthetic sickness, where the mutant shows a weaker phenotype.
Abstract The rapid accumulation of knowledge on biological signaling pathways and their regulator... more Abstract The rapid accumulation of knowledge on biological signaling pathways and their regulatory mechanisms has highlighted the need for specific repositories that can store, organize and allow retrieval of pathway information in a way that will be useful for the research community. SPIKE (Signaling Pathways Integrated Knowledge Engine; http://www. cs. tau. ac.
To use microRNAs to downregulate mRNA targets, cells must first process these∼ 22 nt RNAs from pr... more To use microRNAs to downregulate mRNA targets, cells must first process these∼ 22 nt RNAs from primary transcripts (pri-miRNAs). These transcripts form RNA hairpins important for processing, but additional determinants must distinguish pri-miRNAs from the many other hairpin-containing transcripts expressed in each cell. Illustrating the complexity of this recognition, we show that most Caenorhabditis elegans pri-miRNAs lack determinants required for processing in human cells.
We have employed a novel approach for the identification of functionally important microRNA (miRN... more We have employed a novel approach for the identification of functionally important microRNA (miRNA)-target interactions, integrating miRNA, transcriptome and proteome profiles and advanced in silico analysis using the FAME algorithm. Since miRNAs play a crucial role in the inner ear, demonstrated by the discovery of mutations in a miRNA leading to human and mouse deafness, we applied this approach to microdissected auditory and vestibular sensory epithelia.
Background Mutations in eukaryotic translation initiation factor 2B (eIF2B) cause Childhood Ataxi... more Background Mutations in eukaryotic translation initiation factor 2B (eIF2B) cause Childhood Ataxia with CNS Hypomyelination (CACH), also known as Vanishing White Matter disease (VWM), which is associated with a clinical pathology of brain myelin loss upon physiological stress. eIF2B is the guanine nucleotide exchange factor (GEF) of eIF2, which delivers the initiator tRNA Met to the ribosome.
Abstract The post-transcriptional fate of messenger RNAs (mRNAs) is largely dictated by their 3'u... more Abstract The post-transcriptional fate of messenger RNAs (mRNAs) is largely dictated by their 3'untranslated regions (3'UTRs), which are defined by cleavage and polyadenylation (CPA) of pre-mRNAs. We used poly (A)-position profiling by sequencing (3P-seq) to map poly (A) sites at eight developmental stages and tissues in the zebrafish.
Functional annotation of proteins is a fundamental problem in the post-genomic era. The recent av... more Functional annotation of proteins is a fundamental problem in the post-genomic era. The recent availability of protein interaction networks for many model species has spurred on the development of computational methods for interpreting such data in order to elucidate protein function. In this review, we describe the current computational approaches for the task, including direct methods, which propagate functional information through the network, and module-assisted methods, which infer functional modules within the network and use those for the annotation task. Although a broad variety of interesting approaches has been developed, further progress in the field will depend on systematic evaluation of the methods and their dissemination in the biological community.
The biological interpretation of genetic interactions is a major challenge. Recently, Kelley and ... more The biological interpretation of genetic interactions is a major challenge. Recently, Kelley and Ideker proposed a method to analyze together genetic and physical networks, which explains many of the known genetic interactions as linking different pathways in the physical network. Here, we extend this method and devise novel analytic tools for interpreting genetic interactions in a physical context. Applying these tools on a large-scale Saccharomyces cerevisiae data set, our analysis reveals 140 between-pathway models that explain 3765 genetic interactions, roughly doubling those that were previously explained. Model genes tend to have short mRNA half-lives and many phosphorylation sites, suggesting that their stringent regulation is linked to pathway redundancy. We also identify ‘pivot' proteins that have many physical interactions with both pathways in our models, and show that pivots tend to be essential and highly conserved. Our analysis of models and pivots sheds light on the organization of the cellular machinery as well as on the roles of individual proteins.
Recent technological breakthroughs allow the quantification of hundreds of thousands of genetic i... more Recent technological breakthroughs allow the quantification of hundreds of thousands of genetic interactions (GIs) in Saccharomyces cerevisiae. The interpretation of these data is often difficult, but it can be improved by the joint analysis of GIs along with complementary data types. Here, we describe a novel methodology that integrates genetic and physical interaction data. We use our method to identify a collection of functional modules related to chromosomal biology and to investigate the relations among them. We show how the resulting map of modules provides clues for the elucidation of function both at the level of individual genes and at the level of functional modules.
Microarray-based gene expression studies have great potential but are frequently difficult to int... more Microarray-based gene expression studies have great potential but are frequently difficult to interpret due to their overwhelming dimensions. Recent studies have shown that the analysis of expression data can be improved by its integration with protein interaction networks, but the performance of these analyses has been hampered by the uneven quality of the interaction data. We present Co-Expression Zone ANalysis using NEtworks (CEZANNE), a novel confidence-based method for extraction of functionally coherent co-expressed gene sets. CEZANNE uses probabilities for individual interactions, which can be computed by any available method. We propose a probabilistic model and a weighting scheme in which the likelihood of the connectivity of a subnetwork is related to the weight of its minimum cut. Applying CEZANNE to an expression dataset of DNA damage response in Saccharomyces cerevisiae, we recover both known and novel modules and predict novel protein functions. We show that CEZANNE outperforms previous methods for analysis of expression and interaction data. CEZANNE is available as part of the MATISSE software at http://acgt.cs.tau.ac.il/matisse. Supplementary data are available at Bioinformatics online.
A major goal of system biology is the characterization of transcription factors and microRNAs (mi... more A major goal of system biology is the characterization of transcription factors and microRNAs (miRNAs) and the transcriptional programs they regulate. We present Allegro, a method for de-novo discovery of cis-regulatory transcriptional programs through joint analysis of genome-wide expression data and promoter or 3′ UTR sequences. The algorithm uses a novel log-likelihood-based, non-parametric model to describe the expression pattern shared by a group of co-regulated genes. We show that Allegro is more accurate and sensitive than existing techniques, and can simultaneously analyze multiple expression datasets with more than 100 conditions. We apply Allegro on datasets from several species and report on the transcriptional modules it uncovers. Our analysis reveals a novel motif over-represented in the promoters of genes highly expressed in murine oocytes, and several new motifs related to fly development. Finally, using stem-cell expression profiles, we identify three miRNA families with pivotal roles in human embryogenesis.
Thousands of long intervening noncoding RNAs (lincRNAs) have been identified in mammals. To bette... more Thousands of long intervening noncoding RNAs (lincRNAs) have been identified in mammals. To better understand the evolution and functions of these enigmatic RNAs, we used chromatin marks, poly (A)-site mapping and RNA-Seq data to identify more than 550 distinct lincRNAs in zebrafish. Although these shared many characteristics with mammalian lincRNAs, only 29 had detectable sequence similarity with putative mammalian orthologs, typically restricted to a single short region of high conservation.
Gene knock-out studies have shown that only~ 18% of S. cerevisiae genes are essential for growth ... more Gene knock-out studies have shown that only~ 18% of S. cerevisiae genes are essential for growth on a rich medium. Consequently, buffering on the genetic level is believed to be abundant in eukaryotes. To understand the role of nonessential genes better, several large scale studies performed double knock-outs, and identified many events of synthetic lethality, where a mutant carrying deletions of two nonessential genes is lethal, and synthetic sickness, where the mutant shows a weaker phenotype.
Abstract The rapid accumulation of knowledge on biological signaling pathways and their regulator... more Abstract The rapid accumulation of knowledge on biological signaling pathways and their regulatory mechanisms has highlighted the need for specific repositories that can store, organize and allow retrieval of pathway information in a way that will be useful for the research community. SPIKE (Signaling Pathways Integrated Knowledge Engine; http://www. cs. tau. ac.
To use microRNAs to downregulate mRNA targets, cells must first process these∼ 22 nt RNAs from pr... more To use microRNAs to downregulate mRNA targets, cells must first process these∼ 22 nt RNAs from primary transcripts (pri-miRNAs). These transcripts form RNA hairpins important for processing, but additional determinants must distinguish pri-miRNAs from the many other hairpin-containing transcripts expressed in each cell. Illustrating the complexity of this recognition, we show that most Caenorhabditis elegans pri-miRNAs lack determinants required for processing in human cells.
We have employed a novel approach for the identification of functionally important microRNA (miRN... more We have employed a novel approach for the identification of functionally important microRNA (miRNA)-target interactions, integrating miRNA, transcriptome and proteome profiles and advanced in silico analysis using the FAME algorithm. Since miRNAs play a crucial role in the inner ear, demonstrated by the discovery of mutations in a miRNA leading to human and mouse deafness, we applied this approach to microdissected auditory and vestibular sensory epithelia.
Background Mutations in eukaryotic translation initiation factor 2B (eIF2B) cause Childhood Ataxi... more Background Mutations in eukaryotic translation initiation factor 2B (eIF2B) cause Childhood Ataxia with CNS Hypomyelination (CACH), also known as Vanishing White Matter disease (VWM), which is associated with a clinical pathology of brain myelin loss upon physiological stress. eIF2B is the guanine nucleotide exchange factor (GEF) of eIF2, which delivers the initiator tRNA Met to the ribosome.
Abstract The post-transcriptional fate of messenger RNAs (mRNAs) is largely dictated by their 3'u... more Abstract The post-transcriptional fate of messenger RNAs (mRNAs) is largely dictated by their 3'untranslated regions (3'UTRs), which are defined by cleavage and polyadenylation (CPA) of pre-mRNAs. We used poly (A)-position profiling by sequencing (3P-seq) to map poly (A) sites at eight developmental stages and tissues in the zebrafish.
Functional annotation of proteins is a fundamental problem in the post-genomic era. The recent av... more Functional annotation of proteins is a fundamental problem in the post-genomic era. The recent availability of protein interaction networks for many model species has spurred on the development of computational methods for interpreting such data in order to elucidate protein function. In this review, we describe the current computational approaches for the task, including direct methods, which propagate functional information through the network, and module-assisted methods, which infer functional modules within the network and use those for the annotation task. Although a broad variety of interesting approaches has been developed, further progress in the field will depend on systematic evaluation of the methods and their dissemination in the biological community.
The biological interpretation of genetic interactions is a major challenge. Recently, Kelley and ... more The biological interpretation of genetic interactions is a major challenge. Recently, Kelley and Ideker proposed a method to analyze together genetic and physical networks, which explains many of the known genetic interactions as linking different pathways in the physical network. Here, we extend this method and devise novel analytic tools for interpreting genetic interactions in a physical context. Applying these tools on a large-scale Saccharomyces cerevisiae data set, our analysis reveals 140 between-pathway models that explain 3765 genetic interactions, roughly doubling those that were previously explained. Model genes tend to have short mRNA half-lives and many phosphorylation sites, suggesting that their stringent regulation is linked to pathway redundancy. We also identify ‘pivot' proteins that have many physical interactions with both pathways in our models, and show that pivots tend to be essential and highly conserved. Our analysis of models and pivots sheds light on the organization of the cellular machinery as well as on the roles of individual proteins.
Recent technological breakthroughs allow the quantification of hundreds of thousands of genetic i... more Recent technological breakthroughs allow the quantification of hundreds of thousands of genetic interactions (GIs) in Saccharomyces cerevisiae. The interpretation of these data is often difficult, but it can be improved by the joint analysis of GIs along with complementary data types. Here, we describe a novel methodology that integrates genetic and physical interaction data. We use our method to identify a collection of functional modules related to chromosomal biology and to investigate the relations among them. We show how the resulting map of modules provides clues for the elucidation of function both at the level of individual genes and at the level of functional modules.
Microarray-based gene expression studies have great potential but are frequently difficult to int... more Microarray-based gene expression studies have great potential but are frequently difficult to interpret due to their overwhelming dimensions. Recent studies have shown that the analysis of expression data can be improved by its integration with protein interaction networks, but the performance of these analyses has been hampered by the uneven quality of the interaction data. We present Co-Expression Zone ANalysis using NEtworks (CEZANNE), a novel confidence-based method for extraction of functionally coherent co-expressed gene sets. CEZANNE uses probabilities for individual interactions, which can be computed by any available method. We propose a probabilistic model and a weighting scheme in which the likelihood of the connectivity of a subnetwork is related to the weight of its minimum cut. Applying CEZANNE to an expression dataset of DNA damage response in Saccharomyces cerevisiae, we recover both known and novel modules and predict novel protein functions. We show that CEZANNE outperforms previous methods for analysis of expression and interaction data. CEZANNE is available as part of the MATISSE software at http://acgt.cs.tau.ac.il/matisse. Supplementary data are available at Bioinformatics online.
A major goal of system biology is the characterization of transcription factors and microRNAs (mi... more A major goal of system biology is the characterization of transcription factors and microRNAs (miRNAs) and the transcriptional programs they regulate. We present Allegro, a method for de-novo discovery of cis-regulatory transcriptional programs through joint analysis of genome-wide expression data and promoter or 3′ UTR sequences. The algorithm uses a novel log-likelihood-based, non-parametric model to describe the expression pattern shared by a group of co-regulated genes. We show that Allegro is more accurate and sensitive than existing techniques, and can simultaneously analyze multiple expression datasets with more than 100 conditions. We apply Allegro on datasets from several species and report on the transcriptional modules it uncovers. Our analysis reveals a novel motif over-represented in the promoters of genes highly expressed in murine oocytes, and several new motifs related to fly development. Finally, using stem-cell expression profiles, we identify three miRNA families with pivotal roles in human embryogenesis.
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Papers by Igor Ulitsky