Databases and Datasets

FAQs

Deletion Strains Available

References

Protocols &Technical Information

Useful Sites & Links

Guri Giaever¹, 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 D. 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 Philippsen¹³, Ronald W. Davis^1,2 & Mark Johnston⁵

¹Stanford Genome Technology Center, Palo Alto, California 94303, USA
²Department of Biochemistry, Stanford University School of Medicine, Stanford, California  94305-5307, USA
⁵Department of Genetics, Washington University Medical School, St. Louis, MO 63110, USA
¹³Biozentrum, Department of Molecular Microbiology, Biozentrum, University of Basel, Switzerland

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.

Nature 418 : 387-391 (2002)

Supplemental Infomation
(these will open in new windows on your browser)

Experimental Data -- click here

Methods and Materials -- click here