Biomedical subjects

S Tavazoie

Publications and source records attributed to S Tavazoie.

4 recordsLinked to original sources

PubMed2001

Selection analyses of insertional mutants using subgenic-resolution arrays.

We describe a method of genome-wide analysis of quantitative growth phenotypes using insertional mutagenesis and DNA microarrays. We applied the method to assess the fitness contributions of Escherichia coli gene domains under specific growth conditions. A transposon library was subjected to competitive growth selection in Luria-Bertani (LB) and in glucose minimal media. Transposon-containing genomic DNA fragments from the selected libraries were compared with the initial unselected transposon insertion library on DNA microarrays to identify insertions that affect fitness. Genes involved in the biosynthesis of nutrients not provided in the growth medium were found to be significantly enriched in the set of genes containing negatively selected insertions. The data also identify fitness contributions of several uncharacterized genes, including putative transcriptional regulators and enzymes. The applicability of this high-resolution array selection in other species is discussed.

Culture Media↗

PubMed2000

Computational identification of cis-regulatory elements associated with groups of functionally related genes in Saccharomyces cerevisiae.

AlignACE is a Gibbs sampling algorithm for identifying motifs that are over-represented in a set of DNA sequences. When used to search upstream of apparently coregulated genes, AlignACE finds motifs that often correspond to the DNA binding preferences of transcription factors. We previously used AlignACE to analyze whole genome mRNA expression data. Here, we present a more detailed study of its effectiveness as applied to a variety of groups of genes in the Saccharomyces cerevisiae genome. Published functional catalogs of genes and sets of genes grouped by common name provided 248 groups, resulting in 3311 motifs. In conjunction with this analysis, we present measures for gauging the tendency of a motif to target a given set of genes relative to all other genes in the genome and for gauging the degree to which a motif is preferentially located in a certain distance range upstream of translational start sites. We demonstrate improved methods for comparing and clustering sequence motifs. Many previously identified cis-regulatory elements were found. We also describe previously unidentified motifs, one of which has been verified by experiments in our laboratory. An extensive set of AlignACE runs on randomly selected sets of genes and on sets of genes whose upstream regions contain known transcription factor binding sites serve as controls.

Algorithms↗

PubMed1999

Systematic determination of genetic network architecture.

Technologies to measure whole-genome mRNA abundances and methods to organize and display such data are emerging as valuable tools for systems-level exploration of transcriptional regulatory networks. For instance, it has been shown that mRNA data from 118 genes, measured at several time points in the developing hindbrain of mice, can be hierarchically clustered into various patterns (or 'waves') whose members tend to participate in common processes. We have previously shown that hierarchical clustering can group together genes whose cis-regulatory elements are bound by the same proteins in vivo. Hierarchical clustering has also been used to organize genes into hierarchical dendograms on the basis of their expression across multiple growth conditions. The application of Fourier analysis to synchronized yeast mRNA expression data has identified cell-cycle periodic genes, many of which have expected cis-regulatory elements. Here we apply a systematic set of statistical algorithms, based on whole-genome mRNA data, partitional clustering and motif discovery, to identify transcriptional regulatory sub-networks in yeast-without any a priori knowledge of their structure or any assumptions about their dynamics. This approach uncovered new regulons (sets of co-regulated genes) and their putative cis-regulatory elements. We used statistical characterization of known regulons and motifs to derive criteria by which we infer the biological significance of newly discovered regulons and motifs. Our approach holds promise for the rapid elucidation of genetic network architecture in sequenced organisms in which little biology is known.

Animals↗

PubMed1998

Quantitative whole-genome analysis of DNA-protein interactions by in vivo methylase protection in E. coli.

A global methylation-based technique was used to identify, display, and quantitate the in vivo occupancy of numerous protein-binding sites within the Escherichia coli genome. The protein occupancy profiles of these sites showed variation across different growth conditions and genetic backgrounds. Of the 25 sites identified in this study, 24 occurred within 5' noncoding regions. Protein occupancy at 13 of these sites was supported by independent biochemical and genetic evidence. Most of the remaining 12 sites fell upstream of genes with no previously known function. A multivariate statistical analysis was utilized to group such uncharacterized genes with well-characterized ones, providing insights into their function based on a common pattern of transcriptional regulation.

DNA Modification Methylases↗