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Michal Lapidot

Publications and source records attributed to Michal Lapidot.

6 recordsLinked to original sources

Genome-wide natural antisense transcription: coupling its regulation to its different regulatory mechanisms.

Many genomic loci contain transcription units on both strands, therefore two oppositely oriented transcripts can overlap. Often, one strand codes for a protein, whereas the transcript from the other strand is non-encoding. Such natural antisense transcripts (NATs) can negatively regulate the conjugated sense transcript. NATs are highly prevalent in a wide range of species--for example, around 15% of human protein-encoding genes have an associated NAT. The regulatory mechanisms by which NATs act are diverse, as are the means to control their expression. Here, we review the current understanding of NAT function and its mechanistic basis, which has been gathered from both individual gene cases and genome-wide studies. In parallel, we survey findings about the regulation of NAT transcription. Finally, we hypothesize that the regulation of antisense transcription might be tailored to its mode of action. According to this model, the observed relationship between the expression patterns of NATs and their targets might indicate the regulatory mechanism that is in action.

Animals↗

A catalog of stability-associated sequence elements in 3' UTRs of yeast mRNAs.

BACKGROUND: In recent years, intensive computational efforts have been directed towards the discovery of promoter motifs that correlate with mRNA expression profiles. Nevertheless, it is still not always possible to predict steady-state mRNA expression levels based on promoter signals alone, suggesting that other factors may be involved. Other genic regions, in particular 3' UTRs, which are known to exert regulatory effects especially through controlling RNA stability and localization, were less comprehensively investigated, and deciphering regulatory motifs within them is thus crucial. RESULTS: By analyzing 3' UTR sequences and mRNA decay profiles of Saccharomyces cerevisiae genes, we derived a catalog of 53 sequence motifs that may be implicated in stabilization or destabilization of mRNAs. Some of the motifs correspond to known RNA-binding protein sites, and one of them may act in destabilization of ribosome biogenesis genes during stress response. In addition, we present for the first time a catalog of 23 motifs associated with subcellular localization. A significant proportion of the 3' UTR motifs is highly conserved in orthologous yeast genes, and some of the motifs are strikingly similar to recently published mammalian 3' UTR motifs. We classified all genes into those regulated only at transcription initiation level, only at degradation level, and those regulated by a combination of both. Interestingly, different biological functionalities and expression patterns correspond to such classification. CONCLUSION: The present motif catalogs are a first step towards the understanding of the regulation of mRNA degradation and subcellular localization, two important processes which--together with transcription regulation--determine the cell transcriptome.

3' Untranslated Regions↗

Comprehensive quantitative analyses of the effects of promoter sequence elements on mRNA transcription.

We have generated a WWW interface for automated comprehensive analyses of promoter regulatory motifs and the effect they exert on mRNA expression profiles. The server provides a wide spectrum of analysis tools that allow de novo discovery of regulatory motifs, along with refinement and in-depth investigation of fully or partially characterized motifs. The presented discovery and analysis tools are fundamentally different from existing tools in their basic rational, statistical background and specificity and sensitivity towards true regulatory elements. We thus anticipate that the service will be of great importance to the experimental and computational biology communities alike. The motif discovery and diagnosis workbench is available at http://longitude.weizmann.ac.il/rMotif/.

Internet↗

Human Gene-Centric Databases at the Weizmann Institute of Science: GeneCards, UDB, CroW 21 and HORDE.

Recent enhancements and current research in the GeneCards (GC) (http://bioinfo.weizmann.ac.il/cards/) project are described, including the addition of gene expression profiles and integrated gene locations. Also highlighted are the contributions of specialized associated human gene-centric databases developed at the Weizmann Institute. These include the Unified Database (UDB) (http://bioinfo.weizmann.ac.il/udb) for human genome mapping, the human Chromosome 21 database at the Weizmann Insti-tute (CroW 21) (http://bioinfo.weizmann.ac.il/crow21), and the Human Olfactory Receptor Data Explora-torium (HORDE) (http://bioinfo.weizmann.ac.il/HORDE). The synergistic relationships amongst these efforts have positively impacted the quality, quantity and usefulness of the GeneCards gene compendium.

Algorithms↗

GeneLoc: exon-based integration of human genome maps.

MOTIVATION: Despite the numerous available whole-genome mapping resources, no comprehensive, integrated map of the human genome yet exists. RESULTS: GeneLoc, software adjunct to GeneCards and UDB, integrates gene lists by comparing genomic coordinates at the exon level and assigns unique and meaningful identifiers to each gene.

Chromosome Mapping↗

GeneCards 2002: towards a complete, object-oriented, human gene compendium.

MOTIVATION: In the post-genomic era, functional analysis of genes requires a sophisticated interdisciplinary arsenal. Comprehensive resources are challenged to provide consistently improving, state-of-the-art tools. RESULTS: GeneCards (Rebhan et al., 1998) has made innovative strides: (a). regular updates and enhancements incorporating new genes enriched with sequences, genomic locations, cDNA assemblies, orthologies, medical information, 3D protein structures, gene expression, and focused SNP summaries; (b). restructured software using object-oriented Perl, migration to schema-driven XML, and (c). pilot studies, introducing methods to produce cards for novel and predicted genes.

Algorithms↗