Many disease states result from gene overexpression, often in a specific genetic context. To explore gene overexpression phenotypes systematically, we assembled an array of 5280 yeast strains, each containing an inducible copy of an S. cerevisiae gene, covering >80% of the genome. Approximately 15% of the overexpressed genes (769) reduced growth rate. This gene set was enriched for cell cycle-regulated genes, signaling molecules, and transcription factors. Overexpression of most toxic genes resulted in phenotypes different from known deletion mutant phenotypes, suggesting that overexpression phenotypes usually reflect a specific regulatory imbalance rather than disruption of protein complex stoichiometry. Global overexpression effects were also assayed in the context of a cyclin-dependent kinase mutant (pho85Delta). The resultant gene set was enriched for Pho85p targets and identified the yeast calcineurin-responsive transcription factor Crz1p as a substrate. Large-scale application of this approach should provide a strategy for identifying target molecules regulated by specific signaling pathways.
To verify the genome annotation and to create a resource to functionally characterize the proteome, we attempted to Gateway-clone all predicted protein-encoding open reading frames (ORFs), or the 'ORFeome,' of Caenorhabditis elegans. We successfully cloned approximately 12,000 ORFs (ORFeome 1.1), of which roughly 4,000 correspond to genes that are untouched by any cDNA or expressed-sequence tag (EST). More than 50% of predicted genes needed corrections in their intron-exon structures. Notably, approximately 11,000 C. elegans proteins can now be expressed under many conditions and characterized using various high-throughput strategies, including large-scale interactome mapping. We suggest that similar ORFeome projects will be valuable for other organisms, including humans.
• Abstract. To identify genes involved in the export of messenger RNA from the nucleus to the cytoplasm, we used an in situ hybridization assay to screen temperature-sensitive strains of Saccharomyces cerevisiae. This identified those which accumulated poly(A) ÷ RNA in their nuclei when shifted to the non-permissive temperature of 37°C. We describe here the properties of yeast strains carrying mutations in the RA T2 gene (RA Tribonucleic acid trafficking) and the cloning of the RA T2 gene. Only a low percentage of cells carrying the rat2-1 allele showed nuclear accumulation of poly(A) + RNA when cultured at 15 ° or 23°C, but within 4 h of a shift to the nonpermissive temperature of 37°C, poly(A) ÷ RNA accumulated within the nuclei of approximately 80% of cells. No defect was seen in the nuclear import of a reporter protein bearing a nuclear localization signal. Nuclear pore complexes (NPCs) are distributed relatively evenly around the nuclear envelope in wild-type cells. In cells carrying either the rat2-1 or rat2-2 allele, NPCs were clustered together into one or a few regions of the nuclear envelope. This clustering was a constitutive property of mutant cells. NPCs remained clustered in crude nuclei isolated from mutant cells, indicating that these clusters are not able to redistribute around the nuclear envelope when nuclei are separated from cytoplasmic components. Electron microscopy revealed that these clusters were frequently found in a protuberance of the nuclear envelope and were often located close to the spindle pole body. The RA T2 gene encodes a 120-kD protein without similarity to other known proteins. It was essential for growth only at 37°C, but the growth defect at high temperature could be suppressed by growth of mutant ceils in the presence of high osmolarity media containing 1.0 M sorbitol or 0.9 M NaC1. The phenotypes seen in cells carrying a disruption of the RA T2 gene were very similar to those seen with the rat2-1 and rat2-2 alleles. Epitope tagging was used to show that Rat2p is located at the nuclear periphery and co-localizes with yeast NPC proteins recognized by the RL1 monoclonal antibody. The rat2-1 allele was synthetically lethal with both the rat3-1/nup133-1 and rat7-1/nup159-1 alleles. These results indicate that the product of this gene is a nucleoporin which we refer to as Rat2pfNupl20p.
The rexA and rexB genes of bacteriophage A. encode a two-component system that aborts lytic growth of bacterial viruses. Rex exclusion is characterized by termination of macromolecular synthesis, loss of active transport, the hydrolysis of ATP, and cell death. By analogy to colicins El and K, these results can be explained by depolarization of the cytoplasmic membrane. We have fractionated cells to determine the intracellular location of the RexB protein and made RexB-alkaline phosphatase fusions to analyze its membrane topology. The RexB protein appears to be a polytopic transmembrane protein. We suggest that RexB proteins form ion channels that, in response to lytic growth of bacteriophages, depolarize the cytoplasmic membrane. The Rex system requires a mechanism to prevent X itself from being excluded during lytic growth. We have determined that overexpression of RexB in A. lysogens prevents the exclusion of both T4 rll mutants and X ren mutants. We suspect that overexpression of RexB is the basis for preventing self-exclusion following the induction of a \ lysogen and that RexB overexpression is accomplished through transcriptional regulation.
Policies supporting the rapid and open sharing of genomic data have directly fueled the accelerated pace of discovery in large-scale genomics research. The proteomics community is starting to implement analogous policies and infrastructure for making large-scale proteomics data widely available on a pre-competitive basis. On August 14, 2008, the National Cancer Institute (NCI) convened the “International Summit on Proteomics Data Release and Sharing Policy” in Amsterdam, the Netherlands, to identify and address potential roadblocks to rapid and open access to data. The six principles agreed upon by key stakeholders at the summit addressed issues surrounding 1) timing, 2) comprehensiveness, 3) format, 4) deposition to repositories, 5) quality metrics, and 6) responsibility for proteomics data release. This summit report explores various approaches to develop a framework of data release and sharing principles that will most effectively fulfill the needs of the funding agencies and the research community.
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