Biomedical subjects

Chaim Linhart

Publications and source records attributed to Chaim Linhart.

9 recordsLinked to original sources

PubMed2005

Deciphering transcriptional regulatory elements that encode specific cell cycle phasing by comparative genomics analysis.

Transcriptional regulation is a major tier in the periodic engine that mobilizes cell cycle progression. The availability of complete genome sequences of multiple organisms holds promise for significantly improving the specificity of computational identification of functional elements. Here, we applied a comparative genomics analysis to decipher transcriptional regulatory elements that control cell cycle phasing. We analyzed genome-wide promoter sequences from 12 organisms, including worm, fly, fish, rodents and human, and identified conserved transcriptional modules that determine the expression of genes in specific cell cycle phases. We demonstrate that a canonical E2F signal encodes for expression highly specific to the G1/S phase, and that a cis-regulatory module comprising CHR-NF-Y elements dictates expression that is restricted to the G2 and G2/M phases. B-Myb binding site signatures occur in many of the CHR-NF-Y target genes, suggesting a specific role for this triplet in the regulation of the cell cycle transcriptional program. Remarkably, E2F signals are conserved in promoters of G1/S genes in all organisms from worm to human. The CHR-NF-Y module is conserved in promoters of G2/M regulated genes in all analyzed vertebrates. Our results reveal novel modules that determine specific cell cycle phasing, and identify their respective putative target genes with remarkably high specificity.

Animals↗

PubMed2005

EXPANDER--an integrative program suite for microarray data analysis.

BACKGROUND: Gene expression microarrays are a prominent experimental tool in functional genomics which has opened the opportunity for gaining global, systems-level understanding of transcriptional networks. Experiments that apply this technology typically generate overwhelming volumes of data, unprecedented in biological research. Therefore the task of mining meaningful biological knowledge out of the raw data is a major challenge in bioinformatics. Of special need are integrative packages that provide biologist users with advanced but yet easy to use, set of algorithms, together covering the whole range of steps in microarray data analysis. RESULTS: Here we present the EXPANDER 2.0 (EXPression ANalyzer and DisplayER) software package. EXPANDER 2.0 is an integrative package for the analysis of gene expression data, designed as a 'one-stop shop' tool that implements various data analysis algorithms ranging from the initial steps of normalization and filtering, through clustering and biclustering, to high-level functional enrichment analysis that points to biological processes that are active in the examined conditions, and to promoter cis-regulatory elements analysis that elucidates transcription factors that control the observed transcriptional response. EXPANDER is available with pre-compiled functional Gene Ontology (GO) and promoter sequence-derived data files for yeast, worm, fly, rat, mouse and human, supporting high-level analysis applied to data obtained from these six organisms. CONCLUSION: EXPANDER integrated capabilities and its built-in support of multiple organisms make it a very powerful tool for analysis of microarray data. The package is freely available for academic users at http://www.cs.tau.ac.il/~rshamir/expander.

Algorithms↗

PubMed2005

Dissection of a DNA-damage-induced transcriptional network using a combination of microarrays, RNA interference and computational promoter analysis.

BACKGROUND: Gene-expression microarrays and RNA interferences (RNAi) are among the most prominent techniques in functional genomics. The combination of the two holds promise for systematic, large-scale dissection of transcriptional networks. Recent studies, however, raise the concern that nonspecific responses to small interfering RNAs (siRNAs) might obscure the consequences of silencing the gene of interest, throwing into question the ability of this experimental strategy to achieve precise network dissections. RESULTS: We used microarrays and RNAi to dissect a transcriptional network induced by DNA damage in a human cellular system. We recorded expression profiles with and without exposure of the cells to a radiomimetic drug that induces DNA double-strand breaks (DSBs). Profiles were measured in control cells and in cells knocked-down for the Rel-A subunit of NFkappaB and for p53, two pivotal stress-induced transcription factors, and for the protein kinase ATM, the major transducer of the cellular responses to DSBs. We observed that NFkappaB and p53 mediated most of the damage-induced gene activation; that they controlled the activation of largely disjoint sets of genes; and that ATM was required for the activation of both pathways. Applying computational promoter analysis, we demonstrated that the dissection of the network into ATM/NFkappaB and ATM/p53-mediated arms was highly accurate. CONCLUSIONS: Our results demonstrate that the combined experimental strategy of expression arrays and RNAi is indeed a powerful method for the dissection of complex transcriptional networks, and that computational promoter analysis can provide a strong complementary means for assessing the accuracy of this dissection.

Ataxia Telangiectasia Mutated Proteins↗

PubMed2005

The degenerate primer design problem: theory and applications.

A PCR primer sequence is called degenerate if some of its positions have several possible bases. The degeneracy of the primer is the number of unique sequence combinations it contains. We study the problem of designing a pair of primers with prescribed degeneracy that match a maximum number of given input sequences. Such problems occur when studying a family of genes that is known only in part, or is known in a related species. We prove that various simplified versions of the problem are hard, show the polynomiality of some restricted cases, and develop approximation algorithms for one variant. Based on these algorithms, we implemented a program called HYDEN for designing highly degenerate primers for a set of genomic sequences. We report on the success of the program in several applications, one of which is an experimental scheme for identifying all human olfactory receptor (OR) genes. In that project, HYDEN was used to design primers with degeneracies up to 10(10) that amplified with high specificity many novel genes of that family, tripling the number of OR genes known at the time.

Algorithms↗

PubMed2004

In silico identification of transcriptional regulators associated with c-Myc.

The development of powerful experimental strategies for functional genomics and accompanying computational tools has brought major advances in the delineation of transcriptional networks in organisms ranging from yeast to human. Regulation of transcription of eukaryotic genes is to a large extent combinatorial. Here, we used an in silico approach to identify transcription factors (TFs) that form recurring regulatory modules with c-Myc, a protein encoded by an oncogene that is frequently disregulated in human malignancies. A recent study identified, on a genomic scale, human genes whose promoters are bound by c-Myc and its heterodimer partner Max in Burkitt's lymphoma cells. Using computational methods, we identified nine TFs whose binding-site signatures are highly overrepresented in this promoter set of c-Myc targets, pointing to possible functional links between these TFs and c-Myc. Binding sites of most of these TFs are also enriched on the set of mouse homolog promoters, suggesting functional conservation. Among the enriched TFs, there are several regulators known to control cell cycle progression. Another TF in this set, EGR-1, is rapidly activated by numerous stress challenges and plays a central role in angiogenesis. Experimental investigation confirmed that c-Myc and EGR-1 bind together on several target promoters. The approach applied here is general and demonstrates how computational analysis of functional genomics experiments can identify novel modules in complex networks of transcriptional regulation.

Animals↗

PubMed2004

The canine olfactory subgenome.

We identified 971 olfactory receptor (OR) genes in the dog genome, estimated to constitute approximately 80% of the canine OR repertoire. This was achieved by directed genomic DNA cloning of olfactory sequence tags as well as by mining the Celera canine genome sequences. The dog OR subgenome is estimated to have 12% pseudogenes, suggesting a functional repertoire similar to that of mouse and considerably larger than for humans. No novel OR families were discovered, but as many as 34 gene subfamilies were unique to the dog. "Fish-like" Class I ancient ORs constituted 18% of the repertoire, significantly more than in human and mouse. A set of 122 dog-human-mouse ortholog triplets was identified, with a relatively high fraction of Class I ORs. The elucidation of a large portion of the canine olfactory receptor gene superfamily, with some dog-specific attributes, may help us understand the unique chemosensory capacities of this species.

Animals↗

PubMed2003

Genome-wide in silico identification of transcriptional regulators controlling the cell cycle in human cells.

Dissection of regulatory networks that control gene transcription is one of the greatest challenges of functional genomics. Using human genomic sequences, models for binding sites of known transcription factors, and gene expression data, we demonstrate that the reverse engineering approach, which infers regulatory mechanisms from gene expression patterns, can reveal transcriptional networks in human cells. To date, such methodologies were successfully demonstrated only in prokaryotes and low eukaryotes. We developed computational methods for identifying putative binding sites of transcription factors and for evaluating the statistical significance of their prevalence in a given set of promoters. Focusing on transcriptional mechanisms that control cell cycle progression, our computational analyses revealed eight transcription factors whose binding sites are significantly overrepresented in promoters of genes whose expression is cell-cycle-dependent. The enrichment of some of these factors is specific to certain phases of the cell cycle. In addition, several pairs of these transcription factors show a significant co-occurrence rate in cell-cycle-regulated promoters. Each such pair indicates functional cooperation between its members in regulating the transcriptional program associated with cell cycle progression. The methods presented here are general and can be applied to the analysis of transcriptional networks controlling any biological process.

Binding Sites↗

PubMed2002

DEFOG: a practical scheme for deciphering families of genes.

We developed a novel efficient scheme, DEFOG (for "deciphering families of genes"), for determining sequences of numerous genes from a family of interest. The scheme provides a powerful means to obtain a gene family composition in species for which high-throughput genomic sequencing data are not available. DEFOG uses two key procedures. The first is a novel algorithm for designing highly degenerate primers based on a set of known genes from the family of interest. These primers are used in PCR reactions to amplify the members of the gene family. The second combines oligofingerprinting of the cloned PCR products with clustering of the clones based on their fingerprints. By selecting members from each cluster, a low-redundancy clone subset is chosen for sequencing. We applied the scheme to the human olfactory receptor (OR) genes. OR genes constitute the largest gene superfamily in the human genome, as well as in the genomes of other vertebrate species. DEFOG almost tripled the size of the initial repertoire of human ORs in a single experiment, and only 7% of the PCR clones had to be sequenced. Extremely high degeneracies, reaching over a billion combinations of distinct PCR primer pairs, proved to be very effective and yielded only 0.4% nonspecific products.

Algorithms↗

PubMed2002

The degenerate primer design problem.

A PCR primer sequence is called degenerate if some of its positions have several possible bases. The degeneracy of the primer is the number of unique sequence combinations it contains. We study the problem of designing a pair of primers with prescribed degeneracy that match a maximum number of given input sequences. Such problems occur when studying a family of genes that is known only in part, or is known in a related species. We prove that various simplified versions of the problem are hard, show the polynomiality of some restricted cases, and develop approximation algorithms for one variant. Based on these algorithms, we implemented a program called HYDEN for designing highly-degenerate primers for a set of genomic sequences. We report on the success of the program in an experimental scheme for identifying all human olfactory receptor (OR) genes. In that project, HYDEN was used to design primers with degeneracies up to 10(10) that amplified with high specificity many novel genes of that family, tripling the number of OR genes known at the time.

Algorithms↗