|Title||Functional profiling of the Saccharomyces cerevisiae genome.|
|Authors||Guri Giaever, Angela M Chu, Li Ni, Carla Connelly, Linda Riles, Steeve Véronneau, Sally Dow, Ankuta Lucau-Danila, Keith Anderson, Bruno André, Adam P Arkin, Anna Astromoff, Mohamed El-Bakkoury, Rhonda Bangham, Rocio Benito, Sophie Brachat, Stefano Campanaro, Matt Curtiss, Karen Davis, Adam Deutschbauer, Karl-Dieter Entian, Patrick Flaherty, Francoise Foury, David J Garfinkel, Mark Gerstein, Deanna Gotte, Ulrich Güldener, Johannes H Hegemann, Svenja Hempel, Zelek Herman, Daniel F Jaramillo, Diane E Kelly, Steven L Kelly, Peter Kötter, Darlene LaBonte, David C Lamb, Ning Lan, Hong Liang, Hong Liao, Lucy Liu, Chuanyun Luo, Marc Lussier, Rong Mao, Patrice Menard, Siew Loon Ooi, Jose L Revuelta, Christopher J Roberts, Matthias Rose, Petra Ross-Macdonald, Bart Scherens, Greg Schimmack, Brenda Shafer, Daniel D Shoemaker, Sharon Sookhai-Mahadeo, Reginald K Storms, Jeffrey N Strathern, Giorgio Valle, Marleen Voet, Guido Volckaert, Ching-yun Wang, Teresa R Ward, Julie Wilhelmy, Elizabeth A Winzeler, Yonghong Yang, Grace Yen, Elaine Youngman, Kexin Yu, Howard Bussey, Jef D Boeke, Michael Snyder, Peter Philippsen, Ronald W Davis, Mark Johnston|
|Abstract||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.|
|Citation||Nature 2002; 418:387-91|
|Notes||"Data analysis for the sorbitol, pH 8, 1M salt, Nystatin, minimal media and galactose conditions was performed as follows: A sample size of 10-15 hybridizations were collected for the control condition (YPD at 30oC) for each generation time (5 and 15). The data was centered using the mean intensity across the chip after censoring poor readings as described in the preprocessing section. For each generation time, a Gaussian distribution was fit to the base 10 logarithm of the signal intensity for each tag across all hybridizations. In any particular experiment (defined as a condition measured at 5 or 15 generations), the likelihood of observing a tag's intensity under the control distribution was calculated. The fitness of a strain is then found by averaging the likelihood of the 4 tags associated with that ORF (see below). For computational and data presentation purposes, the negative natural log of this value is taken and dubbed the 'fitness defect score'. Therefore, the larger the fitness defect score the greater the probability a strain has a significant growth defect in the condition tested. In a statistical sense, this is a hypothesis test of observing the intensity in the condition experiment in normal YPD at 30oC conditions."|
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