Determining the effect of gene deletion is a fundamental approach to understanding gene function. Conventional genetic screens exhibit biases, and genes contributing to a phenotype are often missed. We systematically constructed a nearly complete collection of gene-deletion mutants (96% of annotated open reading frames, or ORFs) of the yeast Saccharomyces cerevisiae. DNA sequences dubbed 'molecular bar codes' uniquely identify each strain, enabling their growth to be analysed in parallel and the fitness contribution of each gene to be quantitatively assessed by hybridization to high-density oligonucleotide arrays. We show that previously known and new genes are necessary for optimal growth under six well-studied conditions: high salt, sorbitol, galactose, pH 8, minimal medium and nystatin treatment. Less than 7% of genes that exhibit a significant increase in messenger RNA expression are also required for optimal growth in four of the tested conditions. Our results validate the yeast gene-deletion collection as a valuable resource for functional genomics.

The functions of many open reading frames (ORFs) identified in genome-sequencing projects are unknown. New, whole-genome approaches are required to systematically determine their function. A total of 6925 Saccharomyces cerevisiae strains were constructed, by a high-throughput strategy, each with a precise deletion of one of 2026 ORFs (more than one-third of the ORFs in the genome). Of the deleted ORFs, 17 percent were essential for viability in rich medium. The phenotypes of more than 500 deletion strains were assayed in parallel. Of the deletion strains, 40 percent showed quantitative growth defects in either rich or minimal medium.

The variety of environmental stresses is probably the major challenge imposed on transcription activators and the transcriptional machinery. To precisely describe the very early genomic response developed by yeast to accommodate a chemical stress, we performed time course analyses of the modifications of the yeast gene expression program which immediately follows the addition of the antimitotic drug benomyl. Similar analyses were conducted with different isogenic yeast strains in which genes coding for relevant transcription factors were deleted and coupled with efficient bioinformatics tools. Yap1 and Pdr1, two well-known key mediators of stress tolerance, appeared to be responsible for the very rapid establishment of a transient transcriptional response encompassing 119 genes. Yap1, which plays a predominant role in this response, binds, in vivo, promoters of genes which are not automatically up-regulated. We proposed that Yap1 nuclear localization and DNA binding are necessary but not sufficient to elicit the specificity of the chemical stress response.Cellular organisms develop a myriad of strategies to maintain specific internal conditions constantly challenged by the varying drug environment. The complexity of the yeast cell system for detecting and responding to environmental variations is only beginning to come to light. It has been reported previously (13) that a large set of yeast genes (about 900) showed a similar drastic response to a large variety of environmental changes including temperature shocks, hydrogen peroxide, menadione, diamide, dithiothreitol, hyper-or hypoosmotic shock, amino acid starvation, nitrogen source depletion, and progression into stationary phase. Since these pioneering studies were reported, many observations of the global effects of a large variety of drugs on gene expression have been made. In most of these studies, a binary comparison (i.e., control versus stress-exposed cells) was carried out, whereas in some cases, time course experiments over rather long periods (several hours) were conducted. Although much valuable information has been collected in these studies, the heterogeneity in the protocols followed precludes a simple comparison between the different drug responses. In particular, it is extremely difficult to identify the different regulatory networks and to establish their chronological relationships. Time series experiments soon appeared and were much more informative than simple binary experiments. Such approaches were a particularly valuable source of information in the case of cell cycle analyses (24, 27); however, they were less suitable to describe the chronology of transcriptional events in the case of environ-

Flax (Linum usitatissimum) stems contain cells showing contrasting cell wall structure: lignified in inner stem xylem tissue and hypolignified in outer stem bast fibers. We hypothesized that stem hypolignification should be associated with extensive phenolic accumulation and used metabolomics and transcriptomics to characterize these two tissues.1 H nuclear magnetic resonance clearly distinguished inner and outer stem tissues and identified different primary and secondary metabolites, including coniferin and p-coumaryl alcohol glucoside. Ultrahigh-performance liquid chromatography-Fourier transform ion cyclotron resonance-mass spectrometry aromatic profiling (lignomics) identified 81 phenolic compounds, of which 65 were identified, to our knowledge, for the first time in flax and 11 for the first time in higher plants. Both aglycone forms and glycosides of monolignols, lignin oligomers, and (neo)lignans were identified in both inner and outer stem tissues, with a preponderance of glycosides in the hypolignified outer stem, indicating the existence of a complex monolignol metabolism. The presence of coniferin-containing secondary metabolites suggested that coniferyl alcohol, in addition to being used in lignin and (neo)lignan formation, was also utilized in a third, partially uncharacterized metabolic pathway. Hypolignification of bast fibers in outer stem tissues was correlated with the low transcript abundance of monolignol biosynthetic genes, laccase genes, and certain peroxidase genes, suggesting that flax hypolignification is transcriptionally regulated. Transcripts of the key lignan genes Pinoresinol-Lariciresinol Reductase and Phenylcoumaran Benzylic Ether Reductase were also highly abundant in flax inner stem tissues. Expression profiling allowed the identification of NAC (NAM, ATAF1/2, CUC2) and MYB transcription factors that are likely involved in regulating both monolignol production and polymerization as well as (neo)lignan production.

We demonstrate a genomewide approach to determine the physiological role of a putative transcription factor, Ylr266, identified through yeast genome sequencing program. We constructed activated forms of the zinc finger (Zn 2 Cys 6 ) protein Ylr266, and we analyzed the corresponding transcriptomes with DNA microarrays to characterize the up-regulated genes. The direct target genes of Ylr266 were further identified by in vivo chromatin immunoprecipitation procedure. The functions of the genes directly controlled by YLR266c are in agreement with the observed drug-resistance phenotype of the cell expressing an activated form of Ylr266. These target genes code for ATP-binding cassette or major facilitator superfamily transporters such as PDR15, YOR1, or AZR1 or for other proteins such as SNG1, YJL216c, or YLL056c which are already known to be involved in the yeast pleiotropic drug resistance (PDR) phenomenon. YLR266c could thus be named PDR8. Overlaps with the other PDR networks argue in favor of a new specific role for PDR8 in connection with the well known PDR regulators PDR1/PDR3 and YRR1. This strategy to identify the regulatory properties of an anonymous transcription factor is likely to be generalized to all the Zn 2 Cys 6 transcription factors from Saccharomyces cerevisiae and related yeasts.With the advent of postgenomic approaches that provide a nearly complete analysis of the cell transcriptome, it has been disconcerting to discover the complexity of the cell genetic response to apparently simple physiological changes (1). This apparent complexity is likely to reflect the action of underlying regulatory networks that control gene-expression patterns characteristic of many different genetic changes (2). These transcriptional regulatory networks are under the combinatorial action of transcription factors, and dissection of the specific role of each transcription factor offers a good opportunity to decipher the complexity of genome expression (3).One of the main challenge further the understanding of genome functions is to describe the set of genes that are directly regulated by the different specific transcription factors. DNA microarrays are very efficient tools to address such questions, but they have to be coupled with properly designed experiments if one wishes to distinguish direct and indirect effects of the activity of a transcription factor. Such data are already available for several transcription factors (4) that were previously characterized by classical biological approaches. However, it should be kept in mind that even in Saccharomyces cerevisisae, many direct target genes of identified or putative transcription factors are unknown. Any experimental approach to complete these data relies on the possibility to activate the relevant transcription factor. We have recently designed an approach for the artificial activation of yeast Zn 2 Cys 6 transcription factors. The Zn 2 Cys 6 family of transcription factors, exemplified by Gal4, represents more than 25% of the yeast transcription regulators. Our ...

Highly flexible gene expression programs are required to allow cell growth in the presence of a wide variety of chemicals. We used genome-wide expression analyses coupled with chromatin immunoprecipitation experiments to study the regulatory relationships between two very similar yeast transcription factors involved in the control of the multidrug resistance phenomenon. Yrm1 (Yor172w) is a new zinc finger transcription factor, the overproduction of which decreases the level of transcription of the target genes of Yrr1, a zinc finger transcription factor controlling the expression of several membrane transporter-encoding genes. Surprisingly, the absence of YRR1 releases the transcriptional activity of Yrm1, which then up-regulates 23 genes, 14 of which are also direct target genes of Yrr1. Chromatin immunoprecipitation experiments confirmed that Yrm1 binds to the promoters of the upregulated genes only in yeast strains from which YRR1 has been deleted. This sophisticated regulatory program can be associated with drug resistance phenotypes of the cell. The program-specific distribution of paired transcription factors throughout the genome may be a general mechanism by which similar transcription factors regulate overlapping gene expression programs in response to chemical stress.

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