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.

The Isw2 chromatin remodeling complex represses early meiotic genes upon recruitment by Ume6p.

The ISWI class of chromatin remodeling factors exhibits potent chromatin remodeling activities in vitro. However, the in vivo functions of this class of factors are unknown at a molecular level. We have found that S. cerevisiae Isw2 complex represses transcription of early meiotic genes during mitotic growth in a parallel pathway to Rpd3-Sin3 histone deacetylase complex. This repressor function of lsw2 complex is largely dependent upon Ume6p, which recruits the complex to target genes. Nuclease digestion analyses revealed that lsw2 complex establishes nuclease-inaccessible chromatin structure near the Ume6p binding site in vivo. Based on these findings, we propose a model for the mechanism of transcriptional repression by two distinct chromatin remodeling complexes.

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.

Finding DNA regulatory motifs within unaligned noncoding sequences clustered by whole-genome mRNA quantitation.

Whole-genome mRNA quantitation can be used to identify the genes that are most responsive to environmental or genotypic change. By searching for mutually similar DNA elements among the upstream non-coding DNA sequences of these genes, we can identify candidate regulatory motifs and corresponding candidate sets of coregulated genes. We have tested this strategy by applying it to three extensively studied regulatory systems in the yeast Saccharomyces cerevisiae: galactose response, heat shock, and mating type. Galactose-response data yielded the known binding site of Gal4, and six of nine genes known to be induced by galactose. Heat shock data yielded the cell-cycle activation motif, which is known to mediate cell-cycle dependent activation, and a set of genes coding for all four nucleosomal proteins. Mating type alpha and a data yielded all of the four relevant DNA motifs and most of the known a- and alpha-specific genes.